From f2ac0050e02661e0158f6508727038310c6dfe7b Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 16 Mar 2023 14:56:03 -0400 Subject: [PATCH 001/330] Eye gaze classification model WIP --- bcipy/helpers/raw_data_gaze.py | 89 ++++++++++++++ bcipy/signal/model/fusion_model.py | 29 +++++ bcipy/signal/model/offline_gaze_analysis.py | 122 ++++++++++++++++++++ 3 files changed, 240 insertions(+) create mode 100644 bcipy/helpers/raw_data_gaze.py create mode 100644 bcipy/signal/model/fusion_model.py create mode 100644 bcipy/signal/model/offline_gaze_analysis.py diff --git a/bcipy/helpers/raw_data_gaze.py b/bcipy/helpers/raw_data_gaze.py new file mode 100644 index 000000000..625c1e725 --- /dev/null +++ b/bcipy/helpers/raw_data_gaze.py @@ -0,0 +1,89 @@ +import csv +from typing import List, Optional, TextIO, Tuple + +import numpy as np +import pandas as pd + +from bcipy.config import DEFAULT_ENCODING + +class RawGazeData: + """Represents the raw eye gaze data format used by BciPy. Used primarily for loading + a raw data file into memory.""" + + def __init__(self, + daq_type: Optional[str] = None, + sample_rate: Optional[int] = None, + columns: Optional[List[str]] = None, + column_types: Optional[List[str]] = None): + self.daq_type = daq_type + self.sample_rate = sample_rate + self.columns = columns or [] + # accept a custom column type definition or default to all eeg type + self.column_types = column_types + self._rows = [] + self._dataframe = None + + @classmethod + def load(cls, filename: str): + """Constructs a RawData object by deserializing the given file. + All data will be read into memory. + + Parameters + ---------- + - filename : path to the csv file to read + """ + return load(filename) + + @property + def rows(self) -> List[List]: + """Returns the data rows""" + return self._rows + + @rows.setter + def rows(self, value): + self._rows = value + self._dataframe = None + + + @property + def dataframe(self) -> pd.DataFrame: + """Returns a dataframe of the row data.""" + if self._dataframe is None: + self._dataframe = pd.DataFrame(data=self.rows, + columns=self.columns) + return self._dataframe + + +def load(filename: str) -> RawGazeData: + """Reads the file at the given path and initializes a RawData object. + All data will be read into memory. + + Parameters + ---------- + - filename : path to the csv file to read + """ + # Loading all data from a csv is faster using pandas than using the + # RawDataReader. + with open(filename, mode='r', encoding=DEFAULT_ENCODING) as file_obj: + daq_type, sample_rate = read_metadata(file_obj) + dataframe = pd.read_csv(file_obj) + data = RawGazeData(daq_type, sample_rate, list(dataframe.columns)) + data.rows = dataframe.values.tolist() + return data + +def read_metadata(file_obj: TextIO) -> Tuple[str, float]: + """Reads the metadata from an open raw data file and retuns the result as + a tuple. Increments the reader. + + Parameters + ---------- + - file_obj : open TextIO object + + Returns + ------- + tuple of daq_type, sample_rate + """ + daq_type = next(file_obj).strip().split(',')[1] + sample_rate = float(next(file_obj).strip().split(",")[1]) + return daq_type, sample_rate + diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py new file mode 100644 index 000000000..0552dd28a --- /dev/null +++ b/bcipy/signal/model/fusion_model.py @@ -0,0 +1,29 @@ +import logging +from pathlib import Path +from typing import Tuple + +import numpy as np +import pandas as pd +from matplotlib import pyplot as plt +from sklearn.mixture import GaussianMixture + +betts_data_path = '/Users/basak/Documents/BciPy/data/MatrixEyeTracking/BP_001/BP_001_Matrix_Calibration_Wed_08_Mar_2023_12hr39min04sec_-0800/raw_data.csv' +betts_triggers_path = '/Users/basak/Documents/BciPy/data/MatrixEyeTracking/BP_001/BP_001_Matrix_Calibration_Wed_08_Mar_2023_12hr39min04sec_-0800/triggers.txt' + +if __name__ == "__main__": + df = pd.read_csv(betts_data_path) + df = df.dropna() + # df = df.reset_index(drop=True) + X = df[['left_x', 'left_y']].to_numpy() + timestamp = df['lsl_timestamp'].to_numpy() + gm = GaussianMixture(n_components=28, random_state=0).fit(X) + plt.scatter(X[:, 0], X[:, 1]) + plt.show() + # plt.scatter(X[:, 2], X[:, 3]) + # plt.show() + print(gm.means_) + plt.scatter(gm.means_[:,0], gm.means_[:,1]) + plt.show() + # evaluate the components’ density for each sample + conditionals = gm.predict_proba(X) + breakpoint() \ No newline at end of file diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py new file mode 100644 index 000000000..b656c5495 --- /dev/null +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -0,0 +1,122 @@ +import logging +from pathlib import Path +from typing import Tuple + +import numpy as np +import pandas as pd +from matplotlib import pyplot as plt +from sklearn.mixture import GaussianMixture + +from bcipy.config import DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME +from bcipy.preferences import preferences +from bcipy.helpers.load import ( + load_experimental_data, + load_json_parameters, + load_raw_data, +) +from bcipy.helpers.triggers import TriggerType, trigger_decoder + +from sklearn.model_selection import train_test_split + +log = logging.getLogger(__name__) +logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") + +betts_data_path = '/Users/basak/Documents/BciPy/data/MatrixEyeTracking/BP_001/BP_001_Matrix_Calibration_Wed_08_Mar_2023_12hr39min04sec_-0800/raw_data.csv' + +def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): + """Performs a train/test split on the provided data and labels, accounting for + the current shape convention (channel dimension in front, instead of batch dimension in front). + + Args: + data (np.ndarray): Shape (channels, items, time) + labels (np.ndarray): Shape (items,) + test_size (float): fraction of data to be used for testing + random_state (int, optional): fixed random seed + + Returns: + train_data (np.ndarray): Shape (channels, train_items, time) + test_data (np.ndarray): Shape (channels, test_items, time) + train_labels (np.ndarray): Shape (train_items,) + test_labels (np.ndarray): Shape (test_items,) + """ + data = data.swapaxes(0, 1) + train_data, test_data, train_labels, test_labels = train_test_split( + data, labels, test_size=test_size, random_state=random_state + ) + train_data = train_data.swapaxes(0, 1) + test_data = test_data.swapaxes(0, 1) + return train_data, test_data, train_labels, test_labels + + +def offline_gaze_analysis( + data_folder: str = None, + parameters: dict = {}, +): + + if not data_folder: + data_folder = load_experimental_data() + + # extract relevant session information from parameters file + poststim_length = parameters.get("trial_length") + prestim_length = parameters.get("prestim_length") + trials_per_inquiry = parameters.get("stim_length") + static_offset = parameters.get("static_trigger_offset") + # The task buffer length defines the min time between two inquiries + # We use half of that time here to buffer during transforms + buffer = int(parameters.get("task_buffer_length") / 2) + raw_data_file = f"{RAW_DATA_FILENAME}.csv" + + log.info( + f"\nData processing settings: \n" + f"Poststimulus: {poststim_length}s, Prestimulus: {prestim_length}s, Buffer: {buffer}s, Trials per inquiry: {trials_per_inquiry} \n" + ) + + # Load raw data + raw_data = load_raw_data(Path(data_folder, raw_data_file)) + + # Process triggers.txt files + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + offset=static_offset, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + + breakpoint() + results = np.empty() + + return results + + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser() + parser.add_argument("-d", "--data_folder", default=None) + parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) + args = parser.parse_args() + + log.info(f"Loading params from {args.parameters_file}") + parameters = load_json_parameters(args.parameters_file, value_cast=True) + + offline_gaze_analysis( + args.data_folder, + parameters) + log.info("Offline Analysis complete.") + + + + # df = pd.read_csv(betts_data_path) + # df = df.dropna() + # # df = df.reset_index(drop=True) + # X = df[['left_x', 'left_y']].to_numpy() + # gm = GaussianMixture(n_components=28, random_state=0).fit(X) + # plt.scatter(X[:, 0], X[:, 1]) + # plt.show() + # # plt.scatter(X[:, 2], X[:, 3]) + # # plt.show() + # print(gm.means_) + # plt.scatter(gm.means_[:,0], gm.means_[:,1]) + # plt.show() + # # evaluate the components’ density for each sample + # conditionals = gm.predict_proba(X) + # breakpoint() \ No newline at end of file From a3c71547251db42e96ff363c95187eec4c071d3e Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 16 Mar 2023 15:00:41 -0400 Subject: [PATCH 002/330] Offline gaze analysis WIP --- bcipy/signal/model/fusion_model.py | 29 --------------------- bcipy/signal/model/offline_gaze_analysis.py | 25 +++--------------- 2 files changed, 3 insertions(+), 51 deletions(-) delete mode 100644 bcipy/signal/model/fusion_model.py diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py deleted file mode 100644 index 0552dd28a..000000000 --- a/bcipy/signal/model/fusion_model.py +++ /dev/null @@ -1,29 +0,0 @@ -import logging -from pathlib import Path -from typing import Tuple - -import numpy as np -import pandas as pd -from matplotlib import pyplot as plt -from sklearn.mixture import GaussianMixture - -betts_data_path = '/Users/basak/Documents/BciPy/data/MatrixEyeTracking/BP_001/BP_001_Matrix_Calibration_Wed_08_Mar_2023_12hr39min04sec_-0800/raw_data.csv' -betts_triggers_path = '/Users/basak/Documents/BciPy/data/MatrixEyeTracking/BP_001/BP_001_Matrix_Calibration_Wed_08_Mar_2023_12hr39min04sec_-0800/triggers.txt' - -if __name__ == "__main__": - df = pd.read_csv(betts_data_path) - df = df.dropna() - # df = df.reset_index(drop=True) - X = df[['left_x', 'left_y']].to_numpy() - timestamp = df['lsl_timestamp'].to_numpy() - gm = GaussianMixture(n_components=28, random_state=0).fit(X) - plt.scatter(X[:, 0], X[:, 1]) - plt.show() - # plt.scatter(X[:, 2], X[:, 3]) - # plt.show() - print(gm.means_) - plt.scatter(gm.means_[:,0], gm.means_[:,1]) - plt.show() - # evaluate the components’ density for each sample - conditionals = gm.predict_proba(X) - breakpoint() \ No newline at end of file diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py index b656c5495..772051fa1 100644 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -81,9 +81,8 @@ def offline_gaze_analysis( exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], ) - breakpoint() - results = np.empty() - + results = [] + return results @@ -101,22 +100,4 @@ def offline_gaze_analysis( offline_gaze_analysis( args.data_folder, parameters) - log.info("Offline Analysis complete.") - - - - # df = pd.read_csv(betts_data_path) - # df = df.dropna() - # # df = df.reset_index(drop=True) - # X = df[['left_x', 'left_y']].to_numpy() - # gm = GaussianMixture(n_components=28, random_state=0).fit(X) - # plt.scatter(X[:, 0], X[:, 1]) - # plt.show() - # # plt.scatter(X[:, 2], X[:, 3]) - # # plt.show() - # print(gm.means_) - # plt.scatter(gm.means_[:,0], gm.means_[:,1]) - # plt.show() - # # evaluate the components’ density for each sample - # conditionals = gm.predict_proba(X) - # breakpoint() \ No newline at end of file + log.info("Offline Analysis complete.") \ No newline at end of file From 1d89a7cab54afb65f81b2278cc450fa09bd7d0d4 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 16 Mar 2023 15:21:30 -0400 Subject: [PATCH 003/330] Gaze data class added --- bcipy/helpers/load.py | 14 +++++++++++++ bcipy/helpers/raw_data_gaze.py | 23 +++++++++++++++++++++ bcipy/signal/model/offline_gaze_analysis.py | 7 ++++--- 3 files changed, 41 insertions(+), 3 deletions(-) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 44306739e..bb953db17 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -20,6 +20,7 @@ InvalidExperimentException) from bcipy.helpers.parameters import Parameters from bcipy.helpers.raw_data import RawData +from bcipy.helpers.raw_data_gaze import RawGazeData from bcipy.signal.model import SignalModel log = logging.getLogger(__name__) @@ -230,6 +231,19 @@ def load_raw_data(filename: str) -> RawData: """ return RawData.load(filename) +def load_raw_gaze_data(filename: str) -> RawData: + """Reads the data (.csv) file written by data acquisition. + + Parameters + ---------- + - filename : path to the serialized data (csv file) + + Returns + ------- + RawData object with data held in memory + """ + return RawGazeData.load(filename) + def load_txt_data() -> str: filename = ask_filename('*.txt') # show dialog box and return the path diff --git a/bcipy/helpers/raw_data_gaze.py b/bcipy/helpers/raw_data_gaze.py index 625c1e725..b7b100c6f 100644 --- a/bcipy/helpers/raw_data_gaze.py +++ b/bcipy/helpers/raw_data_gaze.py @@ -44,6 +44,29 @@ def rows(self, value): self._rows = value self._dataframe = None + @property + def channels(self) -> List[str]: + """Compute the list of channels. Channels are the numeric columns + excluding the timestamp column.""" + + # Start data slice at 1 to remove the timestamp column. + return list(self.numeric_data.columns[1:]) + + @property + def numeric_data(self) -> pd.DataFrame: + """Data for columns with numeric data. This is usually comprised of the + timestamp column and device channels, excluding string triggers.""" + return self.dataframe.select_dtypes(exclude=['object']) + + @property + def channel_data(self): + """Data for columns with numeric data, excluding the timestamp column.""" + numeric_data = self.numeric_data + + numeric_vals = numeric_data.values + numeric_column_count = numeric_vals.shape[1] + # Start data slice at 1 to remove the timestamp column. + return numeric_vals[:, 1:numeric_column_count].transpose() @property def dataframe(self) -> pd.DataFrame: diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py index 772051fa1..8a7835210 100644 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -13,6 +13,7 @@ load_experimental_data, load_json_parameters, load_raw_data, + load_raw_gaze_data ) from bcipy.helpers.triggers import TriggerType, trigger_decoder @@ -21,8 +22,6 @@ log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") -betts_data_path = '/Users/basak/Documents/BciPy/data/MatrixEyeTracking/BP_001/BP_001_Matrix_Calibration_Wed_08_Mar_2023_12hr39min04sec_-0800/raw_data.csv' - def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): """Performs a train/test split on the provided data and labels, accounting for the current shape convention (channel dimension in front, instead of batch dimension in front). @@ -72,7 +71,8 @@ def offline_gaze_analysis( ) # Load raw data - raw_data = load_raw_data(Path(data_folder, raw_data_file)) + gaze_data = load_raw_gaze_data(Path(data_folder, raw_data_file)) + # TODO: Dataframe is excluding the first 2 rows. Why? # Process triggers.txt files trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( @@ -81,6 +81,7 @@ def offline_gaze_analysis( exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], ) + breakpoint() results = [] return results From 2d6708fb42fb835a4c8d7653920c92975684458d Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Fri, 17 Mar 2023 14:50:19 -0400 Subject: [PATCH 004/330] Trigger decoding WIP --- bcipy/signal/model/offline_gaze_analysis.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py index 8a7835210..0b3d70403 100644 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -72,11 +72,14 @@ def offline_gaze_analysis( # Load raw data gaze_data = load_raw_gaze_data(Path(data_folder, raw_data_file)) - # TODO: Dataframe is excluding the first 2 rows. Why? + channels = gaze_data.channels + type_amp = gaze_data.daq_type + sample_rate = gaze_data.sample_rate # Process triggers.txt files trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( offset=static_offset, + remove_pre_fixation = False, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], ) From b48f0826f989bfe14918ebdf8f395ee634c1692e Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Tue, 4 Apr 2023 16:25:24 -0400 Subject: [PATCH 005/330] Gaze Reshaper WIP --- bcipy/helpers/stimuli.py | 105 ++++++++++++++++++++ bcipy/parameters/devices.json | 3 +- bcipy/signal/model/offline_gaze_analysis.py | 25 ++++- 3 files changed, 130 insertions(+), 3 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index bd8d55d4f..c75285f90 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -176,6 +176,8 @@ def get_inquiry_len(inq_trigs): stop = first_trigger + num_samples_per_inq + buffer_samples reshaped_data.append(eeg_data[:, start:stop]) + breakpoint() + return np.stack(reshaped_data, 1), labels, reshaped_trigger_timing @staticmethod @@ -197,6 +199,109 @@ def extract_trials(inquiries, samples_per_trial, inquiry_timing, downsample_rate new_trials.append(inquiries[:, inquiry_idx, time:y]) return np.stack(new_trials, 1) # C x T x S +class GazeReshaper: + def __call__(self, + trial_targetness_label: List[str], + timing_info: List[float], + gaze_data: np.ndarray, + sample_rate: int, + trials_per_inquiry: int, + offset: float = 0, + channel_map: List[int] = None, + poststimulus_length: float = 0.5, + prestimulus_length: float = 0.0, + transformation_buffer: float = 0.0, + target_label: str = 'target') -> Tuple[np.ndarray, np.ndarray]: + """Extract inquiry data and labels. + + Args: + trial_targetness_label (List[str]): labels each trial as "target", "non-target", "first_pres_target", etc + timing_info (List[float]): Timestamp of each event in seconds + eeg_data (np.ndarray): shape (channels, samples) preprocessed EEG data + sample_rate (int): sample rate of data provided in eeg_data + trials_per_inquiry (int): number of trials in each inquiry + offset (float, optional): Any calculated or hypothesized offsets in timings. Defaults to 0. + channel_map (List[int], optional): Describes which channels to include or discard. + Defaults to None; all channels will be used. + poststimulus_length (float, optional): time in seconds needed after the last trial in an inquiry. + prestimulus_length (float, optional): time in seconds needed before the first trial in an inquiry. + transformation_buffer (float, optional): time in seconds to buffer the end of the inquiry. Defaults to 0.0. + target_label (str): label of target symbol. Defaults to "target" + + Returns: + reshaped_data (np.ndarray): inquiry data of shape (Channels, Inquiries, Samples) + labels (np.ndarray): integer label for each inquiry. With `trials_per_inquiry=K`, + a label of [0, K-1] indicates the position of `target_label`, or label of K indicates + `target_label` was not present. + reshaped_trigger_timing (List[List[int]]): For each inquiry, a list of the sample index where each trial + begins, accounting for the prestim buffer that may have been added to the front of each inquiry. + """ + if channel_map: + # Remove the channels that we are not interested in + channels_to_remove = [idx for idx, value in enumerate(channel_map) if value == 0] + eeg_data = np.delete(eeg_data, channels_to_remove, axis=0) + + n_inquiry = len(timing_info) // trials_per_inquiry + trial_duration_samples = int(poststimulus_length * sample_rate) + prestimulus_samples = int(prestimulus_length * sample_rate) + + # triggers in seconds are mapped to triggers in number of samples. + triggers = list(map(lambda x: int((x + offset) * sample_rate), timing_info)) + + # First, find the longest inquiry in this experiment + # We'll add or remove a few samples from all other inquiries, to match this length + def get_inquiry_len(inq_trigs): + return inq_trigs[-1] - inq_trigs[0] + + longest_inquiry = max(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) + num_samples_per_inq = get_inquiry_len(longest_inquiry) + trial_duration_samples + buffer_samples = int(transformation_buffer * sample_rate) + + # Label for every inquiry + labels = np.zeros( + (n_inquiry, trials_per_inquiry), dtype=np.compat.long + ) # maybe this can be configurable? return either class indexes or labels ('nontarget' etc) + reshaped_data, reshaped_trigger_timing = [], [] + for inquiry_idx, trials_within_inquiry in enumerate( + grouper(zip(trial_targetness_label, triggers), trials_per_inquiry, fillvalue='x') + ): + first_trigger = trials_within_inquiry[0][1] + + trial_triggers = [] + for trial_idx, (trial_label, trigger) in enumerate(trials_within_inquiry): + if trial_label == target_label: + labels[inquiry_idx, trial_idx] = 1 + + # If presimulus buffer is used, we add it here so that trigger timings will + # still line up with trial onset + trial_triggers.append((trigger - first_trigger) + prestimulus_samples) + reshaped_trigger_timing.append(trial_triggers) + start = first_trigger - prestimulus_samples + stop = first_trigger + num_samples_per_inq + buffer_samples + reshaped_data.append(eeg_data[:, start:stop]) + + breakpoint() + + return np.stack(reshaped_data, 1), labels, reshaped_trigger_timing + + @staticmethod + def extract_trials(inquiries, samples_per_trial, inquiry_timing, downsample_rate=1): + """Extract Trials. + + After using the InquiryReshaper, it may be necessary to futher trial the data for processing. + Using the number of samples and inquiry timing, the data is reshaped from Channels, Inquiry, Samples to + Channels, Trials, Samples. These should match with the trials extracted from the TrialReshaper given the same + slicing parameters. + """ + new_trials = [] + num_inquiries = inquiries.shape[1] + for inquiry_idx, timing in zip(range(num_inquiries), inquiry_timing): # C x I x S + + for time in timing: + time = time // downsample_rate + y = time + samples_per_trial + new_trials.append(inquiries[:, inquiry_idx, time:y]) + return np.stack(new_trials, 1) # C x T x S class TrialReshaper(Reshaper): def __call__(self, diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index f57d1477a..5498eb0b1 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -87,6 +87,7 @@ { "name": "right_pupil", "label": "right_pupil", "type": "pupilsize" } ], "sample_rate": 60.0, - "description": "Tobii Nano. For use with the Tobii Pro SDK." + "description": "Tobii Nano. For use with the Tobii Pro SDK.", + "excluded_from_analysis": ["device_ts", "system_ts", "left_pupil", "right_pupil"] } ] \ No newline at end of file diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py index 0b3d70403..c8c0e0e3a 100644 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -9,10 +9,10 @@ from bcipy.config import DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME from bcipy.preferences import preferences +from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import ( load_experimental_data, load_json_parameters, - load_raw_data, load_raw_gaze_data ) from bcipy.helpers.triggers import TriggerType, trigger_decoder @@ -76,17 +76,38 @@ def offline_gaze_analysis( type_amp = gaze_data.daq_type sample_rate = gaze_data.sample_rate + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + # Process triggers.txt files trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - offset=static_offset, remove_pre_fixation = False, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], ) + # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module + # The timestamp column [0] is already excluded. breakpoint() + channel_map = analysis_channels(channels, type_amp) + + print(channel_map) + # data, fs = raw_data.by_channel() + # TODO: Implementation + + channel_map = [0,0,0,1,1,0,1,1,0,1] # default to use all channels in inquiry reshaper + + breakpoint() + # reshaper! results = [] + #TODO: + # Implement reshaper. We might not need a separate reshaper function. + # Plotting for offset + # Plot the gaze data (check NSLR) fixation, saccade, blink + # Coordinates in Tobii for targets in each inquiry (Tobii to Psychopy units) + + return results From 180c01f837d0ce7652626537b34cc8eb8cf28dba Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Wed, 5 Apr 2023 16:36:31 -0400 Subject: [PATCH 006/330] Loading error solved --- bcipy/helpers/raw_data_gaze.py | 14 ++++++++++++++ bcipy/signal/model/offline_gaze_analysis.py | 8 ++------ 2 files changed, 16 insertions(+), 6 deletions(-) diff --git a/bcipy/helpers/raw_data_gaze.py b/bcipy/helpers/raw_data_gaze.py index b7b100c6f..bc5727e44 100644 --- a/bcipy/helpers/raw_data_gaze.py +++ b/bcipy/helpers/raw_data_gaze.py @@ -67,6 +67,20 @@ def channel_data(self): numeric_column_count = numeric_vals.shape[1] # Start data slice at 1 to remove the timestamp column. return numeric_vals[:, 1:numeric_column_count].transpose() + + def by_channel(self) -> np.ndarray: + """Data organized by channel. + + Returns + ---------- + data: C x N numpy array with samples where C is the number of channels and N + is number of time samples + fs: resulting sample rate if any transformations applied""" + + data = self.channel_data + fs = self.sample_rate + + return data, fs @property def dataframe(self) -> pd.DataFrame: diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py index c8c0e0e3a..26f7819ec 100644 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -88,14 +88,10 @@ def offline_gaze_analysis( # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module # The timestamp column [0] is already excluded. - breakpoint() channel_map = analysis_channels(channels, type_amp) + # channel_map = [0,0,1,1,0,1,1,0,0] - print(channel_map) - # data, fs = raw_data.by_channel() - # TODO: Implementation - - channel_map = [0,0,0,1,1,0,1,1,0,1] # default to use all channels in inquiry reshaper + data, fs = gaze_data.by_channel() # no transformations applied at this stage breakpoint() # reshaper! From 5607f571d817532a67a14a2e0b1b4688ff13eb1a Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 6 Apr 2023 16:43:52 -0400 Subject: [PATCH 007/330] Tobii device name updated in devices.json --- bcipy/parameters/devices.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index 5498eb0b1..90fce6e21 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -74,7 +74,7 @@ "description": "GTec g.USBamp" }, { - "name": "Tobii Nano", + "name": "Tobii-P0", "content_type": "Eyetracker", "channels": [ { "name": "device_ts", "label": "device_ts" }, From 666a78511304e31f22a2560418b09d466e92559f Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 28 Apr 2023 12:04:49 -0700 Subject: [PATCH 008/330] #184752380 ; Added range type to Parameters; Added new RangeInput and RangeWidget for editing the new type using the params_form GUI --- bcipy/gui/main.py | 189 +++++++++++++++++++++---- bcipy/gui/parameters/params_form.py | 21 +-- bcipy/helpers/parameters.py | 44 +++++- bcipy/helpers/tests/test_parameters.py | 27 +++- 4 files changed, 234 insertions(+), 47 deletions(-) diff --git a/bcipy/gui/main.py b/bcipy/gui/main.py index bc1bbae26..932dfb9f0 100644 --- a/bcipy/gui/main.py +++ b/bcipy/gui/main.py @@ -1,18 +1,20 @@ # pylint: disable=E0611 import logging import os -import sys import re +import sys from decimal import Decimal from enum import Enum -from typing import Any, Callable, List, NamedTuple, Optional +from typing import Any, Callable, List, NamedTuple, Optional, Tuple, Union -from PyQt5.QtCore import pyqtSlot, Qt, QEvent, QTimer +from PyQt5.QtCore import QEvent, Qt, QTimer, pyqtSlot from PyQt5.QtGui import QFont, QPixmap, QShowEvent -from PyQt5.QtWidgets import (QApplication, QCheckBox, QComboBox, QDoubleSpinBox, - QFileDialog, QHBoxLayout, QSpinBox, QLabel, QLineEdit, - QMessageBox, QPushButton, QScrollArea, - QVBoxLayout, QWidget) +from PyQt5.QtWidgets import (QApplication, QCheckBox, QComboBox, + QDoubleSpinBox, QFileDialog, QHBoxLayout, QLabel, + QLineEdit, QMessageBox, QPushButton, QScrollArea, + QSpinBox, QVBoxLayout, QWidget) + +from bcipy.helpers.parameters import parse_range def font(size: int = 14, font_family: str = 'Helvetica') -> QFont: @@ -36,7 +38,8 @@ def contains_whitespaces(string: str) -> bool: return re.match(r'^(?=.*[\s])', string) -def contains_special_characters(string: str, regex: str = '[^0-9a-zA-Z_]+') -> bool: +def contains_special_characters(string: str, + regex: str = '[^0-9a-zA-Z_]+') -> bool: """Contains Special Characters. Checks for the presence of special chracters in a string. By default it will allow underscores. @@ -433,6 +436,23 @@ def value(self) -> str: return 'true' if self.control.isChecked() else 'false' +class RangeInput(FormInput): + """FormInput to select a range of values (low, high). + + Serializes to 'low_value:high_value'. Appropriate boundaries are determined + from the starting value and list of recommended_values if provided. + """ + + def init_control(self, value) -> QWidget: + """Initialize the form control widget. + + Parameter: + --------- + value - initial value + """ + return RangeWidget(value, self.options) + + class SelectionInput(FormInput): """FormInput to select from a list of options. The options keyword parameter is required for this input. @@ -447,7 +467,8 @@ class SelectionInput(FormInput): help_color - color of the help text.""" def __init__(self, **kwargs): - assert isinstance(kwargs['options'], list), f"options are required for {kwargs['label']}" + assert isinstance(kwargs['options'], + list), f"options are required for {kwargs['label']}" super(SelectionInput, self).__init__(**kwargs) def init_control(self, value) -> QWidget: @@ -550,6 +571,92 @@ def prompt_path(self): return QFileDialog.getExistingDirectory(caption='Select a path') +class RangeWidget(QWidget): + """Input widget that allows the user to provide a high and low value + (min/max). + + Serializes to 'low_value:high_value'. Appropriate boundaries are determined + from the list of options, which should each be formatted as 'low:high' values. + """ + + def __init__(self, + value: Tuple[int, int], + options: List[str] = None, + label_low: str = "Low:", + label_high="High:"): + super(RangeWidget, self).__init__() + + self.low, self.high = parse_range(value) + self.input_min = None + self.input_max = None + if options: + ranges = [parse_range(rng) for rng in options] + mins = [rng[0] for rng in ranges] + [self.low] + maxes = [rng[1] for rng in ranges] + [self.high] + self.input_min = min(mins) + self.input_max = max(maxes) + + self.cast = int if isinstance(self.low, int) else float + + self.low_input = self.create_input(self.low) + self.high_input = self.create_input(self.high) + + hbox = QHBoxLayout() + hbox.addWidget(static_text_control(None, label=label_low)) + hbox.addWidget(self.low_input) + + hbox.addWidget(static_text_control(None, label=label_high)) + hbox.addWidget(self.high_input) + + self.setLayout(hbox) + + def create_input(self, value: Union[int, float]) -> QWidget: + """Construct an input widget for the given numeric value""" + if isinstance(value, int): + return self.int_input(value) + return self.float_input(value) + + def float_input(self, value: float) -> QWidget: + """Construct a float input""" + spin_box = QDoubleSpinBox() + + # Make a reasonable guess about precision and step size based on the initial value. + props = float_input_properties(value) + + spin_box.setMinimum( + props.min if self.input_min is None else self.input_min) + spin_box.setMaximum( + props.max if self.input_max is None else self.input_max) + spin_box.setDecimals(props.decimals) + spin_box.setSingleStep(props.step) + spin_box.setValue(value) + return spin_box + + def int_input(self, value: int) -> QWidget: + """Construct an int input.""" + spin_box = QSpinBox() + + spin_box.setMinimum( + -100000 if self.input_min is None else self.input_min) + spin_box.setMaximum( + 100000 if self.input_max is None else self.input_max) + if value: + spin_box.setValue(value) + return spin_box + + def text(self): + """Text value""" + low = self.low_input.text() or self.low + high = self.high_input.text() or self.high + # only update the values if valid + if self.cast(low) < self.cast(high): + self.low = self.cast(low) + self.high = self.cast(high) + self.low_input.setValue(self.low) + self.high_input.setValue(self.high) + return f"{self.low}:{self.high}" + + class SearchInput(QWidget): """Search input widget. Consists of a text input field and a Clear button. Text changes to the input are passed to the on_search action. @@ -596,11 +703,11 @@ class BCIGui(QWidget): Primary GUI for downstream abstraction. Convenient handling of widgets and asset creation. """ - def __init__(self, title: str, width: int, height: int, background_color: str): + def __init__(self, title: str, width: int, height: int, + background_color: str): super(BCIGui, self).__init__() - logging.basicConfig( - level=logging.DEBUG, - format='%(name)s - %(levelname)s - %(message)s') + logging.basicConfig(level=logging.DEBUG, + format='%(name)s - %(levelname)s - %(message)s') self.logger = logging self.buttons = [] @@ -637,7 +744,8 @@ def create_main_window(self) -> None: Construct the main window for display of assets. """ self.window_layout = QHBoxLayout() - self.window.setStyleSheet(f'background-color: {self.background_color};') + self.window.setStyleSheet( + f'background-color: {self.background_color};') self.window_layout.addWidget(self.window) self.vbox.addLayout(self.window_layout) @@ -726,7 +834,8 @@ def add_button(self, btn.move(position[0], position[1]) btn.resize(size[0], size[1]) - btn.setStyleSheet(f'background-color: {background_color}; color: {text_color};') + btn.setStyleSheet( + f'background-color: {background_color}; color: {text_color};') if action: btn.clicked.connect(action) @@ -736,9 +845,14 @@ def add_button(self, self.buttons.append(btn) return btn - def add_combobox(self, position: list, size: list, items: list, background_color='default', + def add_combobox(self, + position: list, + size: list, + items: list, + background_color='default', text_color='default', - action=None, editable=False) -> QComboBox: + action=None, + editable=False) -> QComboBox: """Add combobox.""" combobox = QComboBox(self.window) @@ -750,7 +864,8 @@ def add_combobox(self, position: list, size: list, items: list, background_color else: combobox.currentTextChanged.connect(self.default_on_dropdown) - combobox.setStyleSheet(f'background-color: {background_color}; color: {text_color};') + combobox.setStyleSheet( + f'background-color: {background_color}; color: {text_color};') if editable: combobox.setEditable(True) @@ -799,7 +914,8 @@ def add_static_textbox(self, static_text.setText(text) if wrap_text: static_text.setWordWrap(True) - static_text.setStyleSheet(f'background-color: {background_color}; color: {text_color};') + static_text.setStyleSheet( + f'background-color: {background_color}; color: {text_color};') static_text.move(position[0], position[1]) text_settings = QFont(font_family, font_size) @@ -819,12 +935,13 @@ def add_text_input(self, position: list, size: list) -> QLineEdit: self.input_text.append(textbox) return textbox - def throw_alert_message(self, - title: str, - message: str, - message_type: AlertMessageType = AlertMessageType.INFO, - message_response: AlertMessageResponse = AlertMessageResponse.OTE, - message_timeout: float = 0) -> MessageBox: + def throw_alert_message( + self, + title: str, + message: str, + message_type: AlertMessageType = AlertMessageType.INFO, + message_response: AlertMessageResponse = AlertMessageResponse.OTE, + message_timeout: float = 0) -> MessageBox: """Throw Alert Message.""" msg = alert_message(message, title=title, @@ -838,7 +955,8 @@ def get_filename_dialog(self, file_type: str = 'All Files (*)', location: str = "") -> str: """Get Filename Dialog.""" - file_name, _ = QFileDialog.getOpenFileName(self.window, message, location, file_type) + file_name, _ = QFileDialog.getOpenFileName(self.window, message, + location, file_type) return file_name @@ -848,7 +966,11 @@ class ScrollableFrame(QWidget): A QWidget that constructs a scrollable frame and accepts another widget to display within the scrollable area. """ - def __init__(self, height: int, width: int, background_color: str = 'black', widget: QWidget = None): + def __init__(self, + height: int, + width: int, + background_color: str = 'black', + widget: QWidget = None): super().__init__() self.height = height @@ -943,7 +1065,8 @@ def construct_line_items(self) -> None: color = item[item_label][key]['color'] action = item[item_label][key]['action'] button = PushButton(key) - button.setStyleSheet(f'background-color: {color}; color: {text_color};') + button.setStyleSheet( + f'background-color: {color}; color: {text_color};') button.clicked.connect(action) if item[item_label][key].get('id'): @@ -964,7 +1087,10 @@ def app(args) -> QApplication: def start_app() -> None: """Start BCIGui.""" bcipy_gui = app(sys.argv) - ex = BCIGui(title='BCI GUI', height=650, width=650, background_color='white') + ex = BCIGui(title='BCI GUI', + height=650, + width=650, + background_color='white') # ex.get_filename_dialog() # ex.add_button(message='Test Button', position=[200, 300], size=[100, 100], id=1) @@ -978,7 +1104,10 @@ def start_app() -> None: # ex.add_combobox(position=[100, 100], size=[100, 100], items=['first', 'second', 'third'], editable=True) # ex.add_text_input(position=[100, 100], size=[100, 100]) ex.show_gui() - ex.throw_alert_message(title='title', message='test', message_response=AlertMessageResponse.OCE, message_timeout=5) + ex.throw_alert_message(title='title', + message='test', + message_response=AlertMessageResponse.OCE, + message_timeout=5) sys.exit(bcipy_gui.exec_()) diff --git a/bcipy/gui/parameters/params_form.py b/bcipy/gui/parameters/params_form.py index 081559bc8..9c0bde281 100644 --- a/bcipy/gui/parameters/params_form.py +++ b/bcipy/gui/parameters/params_form.py @@ -8,22 +8,13 @@ from PyQt5.QtCore import Qt from PyQt5.QtWidgets import (QApplication, QFileDialog, QHBoxLayout, QPushButton, QScrollArea, QVBoxLayout, QWidget) + from bcipy.config import BCIPY_ROOT +from bcipy.gui.main import (BoolInput, DirectoryInput, FileInput, FloatInput, + FormInput, IntegerInput, RangeInput, SearchInput, + SelectionInput, TextInput, static_text_control) from bcipy.helpers.parameters import Parameters, changes_from_default -from bcipy.gui.main import ( - BoolInput, - DirectoryInput, - FileInput, - FloatInput, - FormInput, - IntegerInput, - SearchInput, - SelectionInput, - static_text_control, - TextInput, -) - class ParamsForm(QWidget): """The ParamsForm class is a QWidget that creates controls/inputs for each parameter in the @@ -86,7 +77,8 @@ def parameter_input(self, param: Dict[str, str]) -> FormInput: 'float': FloatInput, 'bool': BoolInput, 'filepath': FileInput, - 'directorypath': DirectoryInput + 'directorypath': DirectoryInput, + 'range': RangeInput } has_options = isinstance(param['recommended_values'], list) form_input = type_inputs.get( @@ -437,6 +429,7 @@ def main(json_file, title='BCI Parameters', size=(450, 550)): if __name__ == '__main__': import argparse + from bcipy.config import DEFAULT_PARAMETERS_PATH parser = argparse.ArgumentParser() diff --git a/bcipy/helpers/parameters.py b/bcipy/helpers/parameters.py index 286b8e44a..29f8eea59 100644 --- a/bcipy/helpers/parameters.py +++ b/bcipy/helpers/parameters.py @@ -3,6 +3,7 @@ from collections import abc from json import dump, load from pathlib import Path +from re import fullmatch from typing import Any, Dict, NamedTuple, Tuple from bcipy.config import DEFAULT_ENCODING, DEFAULT_PARAMETERS_PATH @@ -24,6 +25,44 @@ class ParameterChange(NamedTuple): original_value: Any +def parse_range(range_str: str) -> Tuple: + """Parse the range description into a tuple of (low, high). + + If either value can be parsed as a float the resulting tuple will have + float values, otherwise they will be ints. + + Parameters + ---------- + range_str - range description formatted 'low:high' + + >>> parse_range("1:10") + (1, 10) + """ + assert ':' in range_str, "Invalid range format; values must be separated by ':'" + low, high = range_str.split(':') + int_pattern = "-?\\d+" + if fullmatch(int_pattern, low) and fullmatch(int_pattern, high): + low = int(low) + high = int(high) + else: + low = float(low) + high = float(high) + + assert low < high, "Low value must be less that the high value" + return (low, high) + + +def serialize_value(value_type: str, value: any) -> str: + """Serialize the given value to a string. Serialized values should be able + to be cast using the conversions.""" + if value_type == 'bool': + return str(value).lower() + if value_type == 'range': + low, high = value + return f"{low}:{high}" + return str(value) + + class Parameters(dict): """Configuration parameters for BciPy. @@ -49,7 +88,8 @@ def __init__(self, source: str = None, cast_values: bool = False): 'bool': lambda val: val == 'true' or val is True, 'str': str, 'directorypath': str, - 'filepath': str + 'filepath': str, + 'range': parse_range } self.load_from_source() @@ -63,7 +103,7 @@ def from_cast_values(cls, **kwargs): params = Parameters(source=None, cast_values=True) for key, val in kwargs.items(): value_type = type(val).__name__ - value_str = str(val).lower() if value_type == 'bool' else str(val) + value_str = serialize_value(value_type, val) params.add_entry( key, { 'value': value_str, diff --git a/bcipy/helpers/tests/test_parameters.py b/bcipy/helpers/tests/test_parameters.py index 2b5c553c4..dcf340e19 100644 --- a/bcipy/helpers/tests/test_parameters.py +++ b/bcipy/helpers/tests/test_parameters.py @@ -6,7 +6,7 @@ from pathlib import Path from bcipy.config import DEFAULT_PARAMETERS_PATH -from bcipy.helpers.parameters import Parameters +from bcipy.helpers.parameters import Parameters, parse_range class TestParameters(unittest.TestCase): @@ -103,6 +103,22 @@ def test_load_data_with_unsupported_type(self): with self.assertRaises(Exception): parameters.load(data_with_unsupported_type) + def test_parse_range(self): + """Test function to parse a range into low, high values""" + self.assertEqual(parse_range("1:10"), (1, 10)) + self.assertEqual(parse_range("1 : 10"), (1, 10)) + self.assertEqual(parse_range("1.0:10"), (1.0, 10.0)) + self.assertEqual(parse_range("1.3:10.2"), (1.3, 10.2)) + self.assertEqual(parse_range("-1:1"), (-1, 1)) + self.assertEqual(parse_range("-75E-6:75E+6"), (-75E-6, 75E+6)) + self.assertEqual(parse_range("-5:10"), (-5, 10)) + + with self.assertRaises(Exception): + parse_range("1 - 10") + + with self.assertRaises(Exception): + parse_range("10:1") + def test_cast_values(self): """Test cast_values.""" @@ -139,6 +155,14 @@ def test_cast_values(self): "recommended_values": "", "type": "str" }, + "my_int_range": { + "value": "5:10", + "section": "", + "readableName": "", + "helpTip": "", + "recommended_values": "", + "type": "range" + } } parameters = Parameters(source=None, cast_values=True) parameters.load(sample_config) @@ -157,6 +181,7 @@ def test_cast_values(self): self.assertEqual(parameters['mystr'], 'hello') self.assertEqual(parameters.get('mystr'), 'hello') self.assertFalse(parameters.get('missing_param', False)) + self.assertEqual(parameters['my_int_range'], (5, 10)) parameters.cast_values = False self.assertEqual(parameters['myint']['value'], '1') From abf8e2103bbffaa4aa06af4d7a46bdc0eae310bd Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Fri, 28 Apr 2023 15:07:21 -0400 Subject: [PATCH 009/330] Offline analysis fusion WIP --- bcipy/helpers/stimuli.py | 21 ++- bcipy/signal/model/offline_analysis_fusion.py | 138 ++++++++++++++++++ bcipy/signal/model/offline_gaze_analysis.py | 27 +++- 3 files changed, 177 insertions(+), 9 deletions(-) create mode 100644 bcipy/signal/model/offline_analysis_fusion.py diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index c75285f90..3355341c6 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -150,6 +150,7 @@ def get_inquiry_len(inq_trigs): return inq_trigs[-1] - inq_trigs[0] longest_inquiry = max(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) + breakpoint() num_samples_per_inq = get_inquiry_len(longest_inquiry) + trial_duration_samples buffer_samples = int(transformation_buffer * sample_rate) @@ -217,12 +218,12 @@ def __call__(self, Args: trial_targetness_label (List[str]): labels each trial as "target", "non-target", "first_pres_target", etc timing_info (List[float]): Timestamp of each event in seconds - eeg_data (np.ndarray): shape (channels, samples) preprocessed EEG data + gaze_data (np.ndarray): shape (channels, samples) eye tracking data sample_rate (int): sample rate of data provided in eeg_data trials_per_inquiry (int): number of trials in each inquiry offset (float, optional): Any calculated or hypothesized offsets in timings. Defaults to 0. channel_map (List[int], optional): Describes which channels to include or discard. - Defaults to None; all channels will be used. + Defaults to None; all channels will be used. poststimulus_length (float, optional): time in seconds needed after the last trial in an inquiry. prestimulus_length (float, optional): time in seconds needed before the first trial in an inquiry. transformation_buffer (float, optional): time in seconds to buffer the end of the inquiry. Defaults to 0.0. @@ -239,7 +240,7 @@ def __call__(self, if channel_map: # Remove the channels that we are not interested in channels_to_remove = [idx for idx, value in enumerate(channel_map) if value == 0] - eeg_data = np.delete(eeg_data, channels_to_remove, axis=0) + gaze_data = np.delete(gaze_data, channels_to_remove, axis=0) n_inquiry = len(timing_info) // trials_per_inquiry trial_duration_samples = int(poststimulus_length * sample_rate) @@ -248,12 +249,22 @@ def __call__(self, # triggers in seconds are mapped to triggers in number of samples. triggers = list(map(lambda x: int((x + offset) * sample_rate), timing_info)) + # First, find the longest inquiry in this experiment # We'll add or remove a few samples from all other inquiries, to match this length def get_inquiry_len(inq_trigs): return inq_trigs[-1] - inq_trigs[0] - + + # Finds the longest inquiry in the experiment by subtracting the first trigger from the last trigger in each inquiry longest_inquiry = max(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) + + # What we need from gaze data is actually the shortest inquiry, not the longest + shortest_inquiry = min(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) + breakpoint() + + # We will trim off the extra bits in each inquiry to match the shortest inquiry + + num_samples_per_inq = get_inquiry_len(longest_inquiry) + trial_duration_samples buffer_samples = int(transformation_buffer * sample_rate) @@ -278,7 +289,7 @@ def get_inquiry_len(inq_trigs): reshaped_trigger_timing.append(trial_triggers) start = first_trigger - prestimulus_samples stop = first_trigger + num_samples_per_inq + buffer_samples - reshaped_data.append(eeg_data[:, start:stop]) + reshaped_data.append(gaze_data[:, start:stop]) breakpoint() diff --git a/bcipy/signal/model/offline_analysis_fusion.py b/bcipy/signal/model/offline_analysis_fusion.py new file mode 100644 index 000000000..e1775cf14 --- /dev/null +++ b/bcipy/signal/model/offline_analysis_fusion.py @@ -0,0 +1,138 @@ +import logging +from pathlib import Path +from typing import Tuple + +import numpy as np +import pandas as pd +from matplotlib import pyplot as plt +from sklearn.mixture import GaussianMixture + +from bcipy.config import DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME +from bcipy.preferences import preferences +from bcipy.helpers.acquisition import analysis_channels +from bcipy.helpers.load import ( + load_experimental_data, + load_json_parameters, + load_raw_gaze_data +) +from bcipy.helpers.triggers import TriggerType, trigger_decoder +from bcipy.signal.model.fusion_model import GazeModel + +from sklearn.model_selection import train_test_split + +log = logging.getLogger(__name__) +logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") + +def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): + """Performs a train/test split on the provided data and labels, accounting for + the current shape convention (channel dimension in front, instead of batch dimension in front). + + Args: + data (np.ndarray): Shape (channels, items, time) + labels (np.ndarray): Shape (items,) + test_size (float): fraction of data to be used for testing + random_state (int, optional): fixed random seed + + Returns: + train_data (np.ndarray): Shape (channels, train_items, time) + test_data (np.ndarray): Shape (channels, test_items, time) + train_labels (np.ndarray): Shape (train_items,) + test_labels (np.ndarray): Shape (test_items,) + """ + data = data.swapaxes(0, 1) + train_data, test_data, train_labels, test_labels = train_test_split( + data, labels, test_size=test_size, random_state=random_state + ) + train_data = train_data.swapaxes(0, 1) + test_data = test_data.swapaxes(0, 1) + return train_data, test_data, train_labels, test_labels + + +def offline_analysis_fusion( + data_folder: str = None, + parameters: dict = {}, +): + + if not data_folder: + data_folder = load_experimental_data() + + # extract relevant session information from parameters file + poststim_length = parameters.get("trial_length") + prestim_length = parameters.get("prestim_length") + trials_per_inquiry = parameters.get("stim_length") + static_offset = parameters.get("static_trigger_offset") + # The task buffer length defines the min time between two inquiries + # We use half of that time here to buffer during transforms + buffer = int(parameters.get("task_buffer_length") / 2) + raw_data_file = f"{RAW_DATA_FILENAME}.csv" + + log.info( + f"\nData processing settings: \n" + f"Poststimulus: {poststim_length}s, Prestimulus: {prestim_length}s, Buffer: {buffer}s, Trials per inquiry: {trials_per_inquiry} \n" + ) + + # Load raw data + gaze_data = load_raw_gaze_data(Path(data_folder, raw_data_file)) + channels = gaze_data.channels + type_amp = gaze_data.daq_type + sample_rate = gaze_data.sample_rate + + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + + # Process triggers.txt files + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + remove_pre_fixation = False, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.OFFSET], + ) + + # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module + # The timestamp column [0] is already excluded. + channel_map = analysis_channels(channels, type_amp) + # channel_map = [0,0,1,1,0,1,1,0,0] + + data, fs = gaze_data.by_channel() # no transformations applied at this stage + + model = GazeModel() + + # Note that we are calling a Gaze Reshaper instead of a Trial or Inquiry Reshaper. + # We might not need a separate reshaper function. + inquiries, inquiry_labels, inquiry_timing = model.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=trigger_timing, + gaze_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=poststim_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) + + + + + + results = [] + # A joint reshaper? + + + return results + + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser() + parser.add_argument("-d", "--data_folder", default=None) + parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) + args = parser.parse_args() + + log.info(f"Loading params from {args.parameters_file}") + parameters = load_json_parameters(args.parameters_file, value_cast=True) + + offline_analysis_fusion( + args.data_folder, + parameters) + log.info("Offline Analysis complete.") \ No newline at end of file diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py index 26f7819ec..6a586c22b 100644 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -16,6 +16,7 @@ load_raw_gaze_data ) from bcipy.helpers.triggers import TriggerType, trigger_decoder +from bcipy.signal.model.fusion_model import GazeModel from sklearn.model_selection import train_test_split @@ -83,7 +84,7 @@ def offline_gaze_analysis( trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( remove_pre_fixation = False, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.OFFSET], ) # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module @@ -93,15 +94,33 @@ def offline_gaze_analysis( data, fs = gaze_data.by_channel() # no transformations applied at this stage - breakpoint() - # reshaper! + model = GazeModel() + + # Note that we are calling a Gaze Reshaper instead of a Trial or Inquiry Reshaper. + # We might not need a separate reshaper function. + inquiries, inquiry_labels, inquiry_timing = model.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=trigger_timing, + gaze_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=poststim_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) + + + + + results = [] #TODO: # Implement reshaper. We might not need a separate reshaper function. # Plotting for offset # Plot the gaze data (check NSLR) fixation, saccade, blink - # Coordinates in Tobii for targets in each inquiry (Tobii to Psychopy units) + # Use Tobii to Psychopy units conversion return results From 13dff991bb97796a77d7eb5ba2e696067ddc8861 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Fri, 28 Apr 2023 12:22:00 -0700 Subject: [PATCH 010/330] WIP testing --- bcipy/config.py | 1 + bcipy/helpers/load.py | 2 +- bcipy/helpers/raw_data_gaze.py | 84 -------------------------- bcipy/signal/model/offline_analysis.py | 2 +- 4 files changed, 3 insertions(+), 86 deletions(-) diff --git a/bcipy/config.py b/bcipy/config.py index 18e3f2dee..8ae227814 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -30,6 +30,7 @@ # core data configuration RAW_DATA_FILENAME = 'raw_data' +EYE_TRACKER_FILENAME_PREFIX = 'eyetracker_data' TRIGGER_FILENAME = 'triggers.txt' SESSION_DATA_FILENAME = 'session.json' SESSION_SUMMARY_FILENAME = 'session.xlsx' diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index bb953db17..56464ac57 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -242,7 +242,7 @@ def load_raw_gaze_data(filename: str) -> RawData: ------- RawData object with data held in memory """ - return RawGazeData.load(filename) + return RawData.load(filename) def load_txt_data() -> str: diff --git a/bcipy/helpers/raw_data_gaze.py b/bcipy/helpers/raw_data_gaze.py index bc5727e44..39b61e882 100644 --- a/bcipy/helpers/raw_data_gaze.py +++ b/bcipy/helpers/raw_data_gaze.py @@ -6,90 +6,6 @@ from bcipy.config import DEFAULT_ENCODING -class RawGazeData: - """Represents the raw eye gaze data format used by BciPy. Used primarily for loading - a raw data file into memory.""" - - def __init__(self, - daq_type: Optional[str] = None, - sample_rate: Optional[int] = None, - columns: Optional[List[str]] = None, - column_types: Optional[List[str]] = None): - self.daq_type = daq_type - self.sample_rate = sample_rate - self.columns = columns or [] - # accept a custom column type definition or default to all eeg type - self.column_types = column_types - self._rows = [] - self._dataframe = None - - @classmethod - def load(cls, filename: str): - """Constructs a RawData object by deserializing the given file. - All data will be read into memory. - - Parameters - ---------- - - filename : path to the csv file to read - """ - return load(filename) - - @property - def rows(self) -> List[List]: - """Returns the data rows""" - return self._rows - - @rows.setter - def rows(self, value): - self._rows = value - self._dataframe = None - - @property - def channels(self) -> List[str]: - """Compute the list of channels. Channels are the numeric columns - excluding the timestamp column.""" - - # Start data slice at 1 to remove the timestamp column. - return list(self.numeric_data.columns[1:]) - - @property - def numeric_data(self) -> pd.DataFrame: - """Data for columns with numeric data. This is usually comprised of the - timestamp column and device channels, excluding string triggers.""" - return self.dataframe.select_dtypes(exclude=['object']) - - @property - def channel_data(self): - """Data for columns with numeric data, excluding the timestamp column.""" - numeric_data = self.numeric_data - - numeric_vals = numeric_data.values - numeric_column_count = numeric_vals.shape[1] - # Start data slice at 1 to remove the timestamp column. - return numeric_vals[:, 1:numeric_column_count].transpose() - - def by_channel(self) -> np.ndarray: - """Data organized by channel. - - Returns - ---------- - data: C x N numpy array with samples where C is the number of channels and N - is number of time samples - fs: resulting sample rate if any transformations applied""" - - data = self.channel_data - fs = self.sample_rate - - return data, fs - - @property - def dataframe(self) -> pd.DataFrame: - """Returns a dataframe of the row data.""" - if self._dataframe is None: - self._dataframe = pd.DataFrame(data=self.rows, - columns=self.columns) - return self._dataframe - def load(filename: str) -> RawGazeData: """Reads the file at the given path and initializes a RawData object. diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index ab7a7bd6b..53217a0ad 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -3,7 +3,7 @@ from typing import Tuple import numpy as np -from bcipy.config import DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME, STATIC_AUDIO_PATH +from bcipy.config import DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME, STATIC_AUDIO_PATH, EYE_TRACKER_FILENAME_PREFIX from bcipy.preferences import preferences from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import ( From 93e68fa79da902d6890147ea446ec20e8a373a10 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Fri, 28 Apr 2023 13:56:34 -0700 Subject: [PATCH 011/330] Working EEG classification! A little hacky, but all data should be loaded correctly TODO implement the GazeModel and transfer to offline analysis --- bcipy/helpers/load.py | 15 +- bcipy/helpers/raw_data.py | 8 +- bcipy/helpers/raw_data_gaze.py | 42 ----- bcipy/helpers/stimuli.py | 3 - bcipy/signal/model/offline_analysis.py | 213 ++++++++++++++----------- 5 files changed, 139 insertions(+), 142 deletions(-) delete mode 100644 bcipy/helpers/raw_data_gaze.py diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 56464ac57..e5bc05ff7 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -20,7 +20,6 @@ InvalidExperimentException) from bcipy.helpers.parameters import Parameters from bcipy.helpers.raw_data import RawData -from bcipy.helpers.raw_data_gaze import RawGazeData from bcipy.signal.model import SignalModel log = logging.getLogger(__name__) @@ -218,18 +217,26 @@ def choose_csv_file(filename: str = None) -> str: return filename -def load_raw_data(filename: str) -> RawData: +def load_raw_data(data_folder: str, data_paths: List[str]) -> List[RawData]: """Reads the data (.csv) file written by data acquisition. Parameters ---------- - - filename : path to the serialized data (csv file) + - data_folder : path to the serialized data location + - data_paths : list of paths to the serialized data (csv file) Returns ------- RawData object with data held in memory """ - return RawData.load(filename) + data = [] + for data_path in data_paths: + filename = Path(data_folder, data_path) + if os.path.exists(filename): + data.append(RawData.load(filename)) + else: + raise FileNotFoundError(f'Could not find {filename}') + return data def load_raw_gaze_data(filename: str) -> RawData: """Reads the data (.csv) file written by data acquisition. diff --git a/bcipy/helpers/raw_data.py b/bcipy/helpers/raw_data.py index 997add14e..e915c0362 100644 --- a/bcipy/helpers/raw_data.py +++ b/bcipy/helpers/raw_data.py @@ -181,6 +181,12 @@ def append(self, row: List): self._rows.append(row) self._dataframe = None + def __str__(self) -> str: + return f"RawData({self.daq_type})" + + def __repr__(self) -> str: + return f"RawData({self.daq_type})" + def maybe_float(val): """Attempt to convert the given value to float. If conversion fails return @@ -323,7 +329,7 @@ def load(filename: str) -> RawData: def read_metadata(file_obj: TextIO) -> Tuple[str, float]: - """Reads the metadata from an open raw data file and retuns the result as + """Reads the metadata from an open raw data file and returns the result as a tuple. Increments the reader. Parameters diff --git a/bcipy/helpers/raw_data_gaze.py b/bcipy/helpers/raw_data_gaze.py deleted file mode 100644 index 39b61e882..000000000 --- a/bcipy/helpers/raw_data_gaze.py +++ /dev/null @@ -1,42 +0,0 @@ -import csv -from typing import List, Optional, TextIO, Tuple - -import numpy as np -import pandas as pd - -from bcipy.config import DEFAULT_ENCODING - - -def load(filename: str) -> RawGazeData: - """Reads the file at the given path and initializes a RawData object. - All data will be read into memory. - - Parameters - ---------- - - filename : path to the csv file to read - """ - # Loading all data from a csv is faster using pandas than using the - # RawDataReader. - with open(filename, mode='r', encoding=DEFAULT_ENCODING) as file_obj: - daq_type, sample_rate = read_metadata(file_obj) - dataframe = pd.read_csv(file_obj) - data = RawGazeData(daq_type, sample_rate, list(dataframe.columns)) - data.rows = dataframe.values.tolist() - return data - -def read_metadata(file_obj: TextIO) -> Tuple[str, float]: - """Reads the metadata from an open raw data file and retuns the result as - a tuple. Increments the reader. - - Parameters - ---------- - - file_obj : open TextIO object - - Returns - ------- - tuple of daq_type, sample_rate - """ - daq_type = next(file_obj).strip().split(',')[1] - sample_rate = float(next(file_obj).strip().split(",")[1]) - return daq_type, sample_rate - diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 53423940e..5f51dc89c 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -150,7 +150,6 @@ def get_inquiry_len(inq_trigs): return inq_trigs[-1] - inq_trigs[0] longest_inquiry = max(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) - breakpoint() num_samples_per_inq = get_inquiry_len(longest_inquiry) + trial_duration_samples buffer_samples = int(transformation_buffer * sample_rate) @@ -177,8 +176,6 @@ def get_inquiry_len(inq_trigs): stop = first_trigger + num_samples_per_inq + buffer_samples reshaped_data.append(eeg_data[:, start:stop]) - breakpoint() - return np.stack(reshaped_data, 1), labels, reshaped_trigger_timing @staticmethod diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index f7d957622..0975decf9 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -4,7 +4,8 @@ from bcipy.config import (DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME, STATIC_AUDIO_PATH, - DEFAULT_DEVICE_SPEC_FILENAME) + DEFAULT_DEVICE_SPEC_FILENAME, + EYE_TRACKER_FILENAME_PREFIX) from bcipy.preferences import preferences from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import ( @@ -99,7 +100,27 @@ def offline_analysis( # The task buffer length defines the min time between two inquiries # We use half of that time here to buffer during transforms buffer = int(parameters.get("task_buffer_length") / 2) - raw_data_file = f"{RAW_DATA_FILENAME}.csv" + + acq_mode = parameters.get("acq_mode") + # handle multiple acquisition. Note: we only currently support Eyetracker + EEG + data_file_paths = [] + if '+' in acq_mode: + if 'eyetracker' in acq_mode.lower(): + # find the eyetracker data file with the prefix of EYE_TRACKER_FILENAME_PREFIX + eye_tracker_file = [ f.name for f in Path(data_folder).iterdir() if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] + assert len(eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {data_folder}. Expected 1." + data_file_paths.extend(eye_tracker_file) + else: + raise ValueError(f"Unsupported acquisition mode: {acq_mode}. Eyetracker must be included.") + if 'eeg' in acq_mode.lower(): + # find the eeg data file with the prefix of EEG_FILENAME_PREFIX + eeg_file = [ f.name for f in Path(data_folder).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] + assert len(eeg_file) == 1, f"Found {len(eeg_file)} EEG files in {data_folder}. Expected 1." + data_file_paths.extend(eeg_file) + else: + raise ValueError(f"Unsupported acquisition mode: {acq_mode}. EEG must be included.") + else: + data_file_paths = [f"{RAW_DATA_FILENAME}.csv"] # get signal filtering information downsample_rate = parameters.get("down_sampling_rate") @@ -117,97 +138,105 @@ def offline_analysis( f"Static offset: {static_offset}" ) - # Load raw data - raw_data = load_raw_data(Path(data_folder, raw_data_file)) - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - - devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=notch_filter, - bandpass_low=filter_low, - bandpass_high=filter_high, - bandpass_order=filter_order, - downsample_factor=downsample_rate, - ) - - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") - - k_folds = parameters.get("k_folds") - model = PcaRdaKdeModel(k_folds=k_folds) + # Load raw data: [RawData(Tobii-P0), RawData(DSI-24)] + raw_data = load_raw_data(data_folder, data_file_paths) + + for mode_data in raw_data: + devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(mode_data.daq_type) + # extract relevant information from raw data object eeg + if device_spec.content_type == "EEG": + channels = mode_data.channels + type_amp = mode_data.daq_type + sample_rate = mode_data.sample_rate + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=notch_filter, + bandpass_low=filter_low, + bandpass_high=filter_high, + bandpass_order=filter_order, + downsample_factor=downsample_rate, + ) + + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + + k_folds = parameters.get("k_folds") + model = PcaRdaKdeModel(k_folds=k_folds) + + # Process triggers.txt files + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + offset=static_offset, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + # Channel map can be checked from data.csv file or the devices.json located in the acquisition module + # The timestamp column [0] is already excluded. + channel_map = analysis_channels(channels, device_spec) + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + log.info(f'Channels used in analysis: {channels_used}') + + data, fs = mode_data.by_channel() + + inquiries, inquiry_labels, inquiry_timing = model.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=trigger_timing, + eeg_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=poststim_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) + + inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) + inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) + trial_duration_samples = int(poststim_length * fs) + trial_data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) + + # define the training classes using integers, where 0=nontargets/1=targets + labels = inquiry_labels.flatten() + + # train and save the model as a pkl file + log.info("Training EEG model. This will take some time...") + model = PcaRdaKdeModel(k_folds=k_folds) + model.fit(trial_data, labels) + log.info(f"Training EEG complete [AUC={model.auc:0.4f}]. Saving data...") + + model.save(data_folder + f"/model_{model.auc:0.4f}.pkl") + preferences.signal_model_directory = data_folder + + # Using an 80/20 split, report on balanced accuracy + if estimate_balanced_acc: + train_data, test_data, train_labels, test_labels = subset_data(trial_data, labels, test_size=0.2) + dummy_model = PcaRdaKdeModel(k_folds=k_folds) + dummy_model.fit(train_data, train_labels) + probs = dummy_model.predict_proba(test_data) + preds = probs.argmax(-1) + score = balanced_accuracy_score(test_labels, preds) + log.info(f"Balanced acc with 80/20 split: {score}") + del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds + + figure_handles = visualize_erp( + mode_data, + channel_map, + trigger_timing, + labels, + poststim_length, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + save_path=data_folder if save_figures else None, + show=show_figures + ) + if device_spec.content_type == "Eyetracker": + # TODO: Add eyetracker processing + log.info("Eyetracker data found. Processing not yet implemented.") + pass - # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - offset=static_offset, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - ) - # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module - # The timestamp column [0] is already excluded. - channel_map = analysis_channels(channels, device_spec) - channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] - log.info(f'Channels used in analysis: {channels_used}') - - data, fs = raw_data.by_channel() - - inquiries, inquiry_labels, inquiry_timing = model.reshaper( - trial_targetness_label=trigger_targetness, - timing_info=trigger_timing, - eeg_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=poststim_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer, - ) - - inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) - inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) - trial_duration_samples = int(poststim_length * fs) - data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) - - # define the training classes using integers, where 0=nontargets/1=targets - labels = inquiry_labels.flatten() - - # train and save the model as a pkl file - log.info("Training model. This will take some time...") - model = PcaRdaKdeModel(k_folds=k_folds) - model.fit(data, labels) - log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") - - model.save(data_folder + f"/model_{model.auc:0.4f}.pkl") - preferences.signal_model_directory = data_folder - - # Using an 80/20 split, report on balanced accuracy - if estimate_balanced_acc: - train_data, test_data, train_labels, test_labels = subset_data(data, labels, test_size=0.2) - dummy_model = PcaRdaKdeModel(k_folds=k_folds) - dummy_model.fit(train_data, train_labels) - probs = dummy_model.predict_proba(test_data) - preds = probs.argmax(-1) - score = balanced_accuracy_score(test_labels, preds) - log.info(f"Balanced acc with 80/20 split: {score}") - del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds - - figure_handles = visualize_erp( - raw_data, - channel_map, - trigger_timing, - labels, - poststim_length, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=data_folder if save_figures else None, - show=show_figures - ) if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") return model, figure_handles From 97113b1b886ad0c95192b1fee25388eb494082cf Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 4 May 2023 19:12:46 -0700 Subject: [PATCH 012/330] WIP plotting --- scripts/python/matrix_grid.png | Bin 0 -> 62273 bytes scripts/python/plot_eye_data.py | 89 ++++++++++++++++++++++++++++++++ 2 files changed, 89 insertions(+) create mode 100644 scripts/python/matrix_grid.png create mode 100644 scripts/python/plot_eye_data.py diff --git a/scripts/python/matrix_grid.png b/scripts/python/matrix_grid.png new file mode 100644 index 0000000000000000000000000000000000000000..d276b5caa3d080cfb82e32a2e57447d77ed6ce70 GIT binary patch literal 62273 zcmeFZc{J7Q`!~Lum7|iVC{A@Eb261ol_B%A-^LITHj+YRZcrg9GRKy2+uM+_A~c|k zJGN;X5*Z>x=9%ZZcc0Jq`(4lT{QFz$`K|S7t$D zyI^tyhuirH{oe4|g=B-nO|_~ioyFg>813Hng1v>l?K>Om-e*TPa%B3mc!icK=SpYh z&VMtreynu)aqefO%c90f?PjB;^Q3mY+{C|`HVP;|7o9lay`yCQo4K(^kt}sWn#b#k 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Z|0VNuP1HKsxAd(|jkg+QZrFS3zW|tS)0O}L literal 0 HcmV?d00001 diff --git a/scripts/python/plot_eye_data.py b/scripts/python/plot_eye_data.py new file mode 100644 index 000000000..0a1dd0ef1 --- /dev/null +++ b/scripts/python/plot_eye_data.py @@ -0,0 +1,89 @@ + +from bcipy.helpers.raw_data import load + +DIPSIZE = (1707, 1067) +IMG_PATH = 'C:\\Users\\tabme\\work\\bci\\BciPy\\scripts\\python\\matrix_grid.png' + +def load_eye_tracking_data(path): + data = load(f'{path}/eyetracker_data_tobii-p0.csv') + + left_eye_channel_map = [0,0,1,1,0,0,0,0,0] + left_eye_data, _, _ = data.by_channel_map(left_eye_channel_map) + left_eye_x = left_eye_data[0] + left_eye_y = left_eye_data[1] + + right_eye_channel_map = [0,0,0,0,0,1,1,0,0] + right_eye_data, _, _ = data.by_channel_map(right_eye_channel_map) + right_eye_x = right_eye_data[0] + right_eye_y = right_eye_data[1] + return left_eye_x, left_eye_y, right_eye_x, right_eye_y + + +if __name__ == "__main__": + import argparse + from pathlib import Path + from bcipy.helpers.load import load_experimental_data + import matplotlib.pyplot as plt + from matplotlib import image + import numpy as np + import seaborn as sns + import pandas as pd + + parser = argparse.ArgumentParser() + parser.add_argument( + '-p', + '--path', + help='Path to the directory with raw_data to be converted', + required=False) + args = parser.parse_args() + + # if no path is provided, prompt for one using a GUI + path = args.path + if not path: + path = load_experimental_data() + + data = load_eye_tracking_data(path) + lx, ly, rx, ry = data + + dpi = 100 + + # load the image + img = plt.imread(IMG_PATH) + # img = np.flipud(img) + + w, h = len(img[0]), len(img) + + # resize the image to fit the display + # img = np.resize(img, (DIPSIZE[1], DIPSIZE[0], 4)) + fig, ax = plt.subplots() + ax.imshow(img, extent=[0, 1, 0, 1]) + # ax.scatter(lx, ly, c='r', s=1) + # ax.scatter(rx, ry, c='b', s=1) + # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis + lx = np.clip(lx, 0, 1) + ly = np.clip(ly, 0, 1) + rx = np.clip(rx, 0, 1) + ry = np.clip(ry, 0, 1) + ly = 1 - ly + ry = 1 - ry + + # plot the eye data + # ax.plot(lx, ly, c='r', linewidth=1) + # ax.plot(rx, ry, c='b', linewidth=1) + + # remove nan values + # lx = lx[~np.isnan(lx)] + # ly = ly[~np.isnan(ly)] + # rx = rx[~np.isnan(rx)] + # ry = ry[~np.isnan(ry)] + + # determine kde of the eye data + # ax = sns.kdeplot(lx, ly, cmap="mako", fill=False, thresh=0.05, levels=10) + + + ax.scatter(lx, ly, c='r', s=1) + ax.scatter(rx, ry, c='b', s=1) + + # plt.show() + + breakpoint() \ No newline at end of file From 2801438ee7b84629dcadcc216cf003bca3273c40 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 9 May 2023 16:36:40 -0700 Subject: [PATCH 013/330] Added the ContentType enum for supported data acquisition device types --- bcipy/acquisition/exceptions.py | 4 +++ bcipy/acquisition/multimodal.py | 33 ++++++++++++++++-- bcipy/acquisition/tests/test_content_type.py | 35 ++++++++++++++++++++ 3 files changed, 70 insertions(+), 2 deletions(-) create mode 100644 bcipy/acquisition/tests/test_content_type.py diff --git a/bcipy/acquisition/exceptions.py b/bcipy/acquisition/exceptions.py index f0e8e2f48..449bd0050 100644 --- a/bcipy/acquisition/exceptions.py +++ b/bcipy/acquisition/exceptions.py @@ -1,3 +1,7 @@ class InvalidClockError(Exception): def __init__(self, msg): Exception.__init__(self, msg) + +class UnsupportedContentType(Exception): + """Error that occurs when attempting to collect data from a device with a + content type that is not yet supported by BciPy.""" \ No newline at end of file diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index a60ab0de5..90a2f8352 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -1,12 +1,41 @@ """Functionality for managing multiple devices.""" import logging -from typing import Dict, List, Optional -from bcipy.acquisition.protocols.lsl.lsl_client import LslAcquisitionClient +from enum import Enum +from typing import Any, Dict, List, Optional + from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.exceptions import UnsupportedContentType +from bcipy.acquisition.protocols.lsl.lsl_client import LslAcquisitionClient log = logging.getLogger(__name__) +class ContentType(Enum): + """Generalized list of supported content types. Allows for case-insensitive + matching, as well as synonyms for some types. + + >>> ContentType('Eeg') == ContentType.EEG + True + """ + + EEG = ('eeg', []) + EYETRACKER = ('eyetracker', ['gaze', 'eye_tracker']) + MARKERS = ('markers', ['switch']) + + def __init__(self, label, synonyms): + self.label = label + self.synonyms = synonyms + + @classmethod + def _missing_(cls, value: Any): + """Lookup function used when a value is not found.""" + value = str(value).lower() + for member in cls: + if member.label == value or value in member.synonyms: + return member + raise UnsupportedContentType("ContentType not supported") + + class ClientManager(): """Manages multiple acquisition clients. This class can also act as an acquisition client. If used in this way, it dispatches to the managed diff --git a/bcipy/acquisition/tests/test_content_type.py b/bcipy/acquisition/tests/test_content_type.py new file mode 100644 index 000000000..1d528b28a --- /dev/null +++ b/bcipy/acquisition/tests/test_content_type.py @@ -0,0 +1,35 @@ +"""Unit tests for ContentType""" +import unittest + +from bcipy.acquisition.exceptions import UnsupportedContentType +from bcipy.acquisition.multimodal import ContentType + + +class TestContentType(unittest.TestCase): + """Tests for multimodal ContentType enum.""" + + def test_label(self): + """Test that labels are strings""" + self.assertEqual('eeg', ContentType.EEG.label) + self.assertEqual('eyetracker', ContentType.EYETRACKER.label) + + def test_constructor(self): + """Test retrieving an enum by value""" + self.assertEqual(ContentType.EEG, ContentType('EEG')) + self.assertEqual(ContentType.EEG, ContentType('eeg')) + self.assertEqual(ContentType.EEG, ContentType('Eeg')) + + self.assertEqual(ContentType.EYETRACKER, ContentType('Eyetracker')) + + def test_synonyms(self): + """Test that synonyms can be used for some values""" + self.assertEqual(ContentType.EYETRACKER, ContentType('Gaze')) + self.assertEqual(ContentType.EYETRACKER, ContentType('Eye_tracker')) + + def test_unsupported_type(self): + """Test that an unsupported type raises an exception""" + with self.assertRaises(UnsupportedContentType): + ContentType('FooBar') + +if __name__ == '__main__': + unittest.main() From 8db8d9edcaee7c5470a163c723ac88d8025d008e Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 11 May 2023 14:57:45 -0700 Subject: [PATCH 014/330] Refactored multimodal ClientManager to use ContentType enum, rather than strings. Added method for querying data from multiple devices --- bcipy/acquisition/exceptions.py | 3 +- bcipy/acquisition/multimodal.py | 61 ++++++++++++++----- .../acquisition/tests/test_client_manager.py | 35 +++++++++-- bcipy/acquisition/tests/test_content_type.py | 9 +-- bcipy/helpers/system_utils.py | 19 +++++- bcipy/task/task_registry.py | 19 ++---- 6 files changed, 105 insertions(+), 41 deletions(-) diff --git a/bcipy/acquisition/exceptions.py b/bcipy/acquisition/exceptions.py index 449bd0050..6551ab2db 100644 --- a/bcipy/acquisition/exceptions.py +++ b/bcipy/acquisition/exceptions.py @@ -2,6 +2,7 @@ class InvalidClockError(Exception): def __init__(self, msg): Exception.__init__(self, msg) + class UnsupportedContentType(Exception): """Error that occurs when attempting to collect data from a device with a - content type that is not yet supported by BciPy.""" \ No newline at end of file + content type that is not yet supported by BciPy.""" diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 90a2f8352..5e56c85f1 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -1,39 +1,41 @@ """Functionality for managing multiple devices.""" import logging -from enum import Enum from typing import Any, Dict, List, Optional from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.exceptions import UnsupportedContentType from bcipy.acquisition.protocols.lsl.lsl_client import LslAcquisitionClient +from bcipy.acquisition.record import Record +from bcipy.helpers.system_utils import AutoNumberEnum log = logging.getLogger(__name__) -class ContentType(Enum): - """Generalized list of supported content types. Allows for case-insensitive - matching, as well as synonyms for some types. +class ContentType(AutoNumberEnum): + """Enum of supported acquisition device (LSL) content types. Allows for + case-insensitive matching, as well as synonyms for some types. + >>> ContentType(1) == ContentType.EEG + True >>> ContentType('Eeg') == ContentType.EEG True """ - EEG = ('eeg', []) - EYETRACKER = ('eyetracker', ['gaze', 'eye_tracker']) - MARKERS = ('markers', ['switch']) - - def __init__(self, label, synonyms): - self.label = label + def __init__(self, synonyms: List[str]): self.synonyms = synonyms + EEG = [] + EYETRACKER = ['gaze', 'eye_tracker'] + MARKERS = ['switch'] + @classmethod def _missing_(cls, value: Any): """Lookup function used when a value is not found.""" value = str(value).lower() for member in cls: - if member.label == value or value in member.synonyms: + if member.name.lower() == value or value in member.synonyms: return member - raise UnsupportedContentType("ContentType not supported") + raise UnsupportedContentType(f"ContentType not supported: {value}") class ClientManager(): @@ -55,8 +57,8 @@ class ClientManager(): default_content_type - used for dispatching calls to an LslClient. """ - def __init__(self, default_content_type: str = 'EEG'): - self._clients: Dict[str, LslAcquisitionClient] = {} + def __init__(self, default_content_type: ContentType = ContentType.EEG): + self._clients: Dict[ContentType, LslAcquisitionClient] = {} self.default_content_type = default_content_type @property @@ -76,9 +78,11 @@ def default_client(self) -> Optional[LslAcquisitionClient]: def add_client(self, client: LslAcquisitionClient): """Add the given client to the manager.""" - self._clients[client.device_spec.content_type] = client + content_type = ContentType(client.device_spec.content_type) + self._clients[content_type] = client - def get_client(self, content_type: str) -> Optional[LslAcquisitionClient]: + def get_client( + self, content_type: ContentType) -> Optional[LslAcquisitionClient]: """Get client by content type""" return self._clients.get(content_type, None) @@ -93,6 +97,31 @@ def stop_acquisition(self): for client in self.clients: client.stop_acquisition() + def get_data_by_device( + self, + start: float = None, + seconds: float = None, + content_types: List[ContentType] = None + ) -> Dict[ContentType, List[Record]]: + """Get data for one or more devices. The number of samples for each + device depends on the sample rate and may be different for item. + + Parameters + ---------- + start - start time (acquisition clock) of data window + seconds - duration of data to return for each device + content_types - specifies which devices to include + """ + output = {} + for content_type in content_types: + client = self.get_client(content_type) + count = round(seconds * client.device_spec.sample_rate) + log.debug( + f'Need {count} records for processing {content_type.name} data' + ) + output[content_type] = client.get_data(start=start, limit=count) + return output + def cleanup(self): """Perform any cleanup tasks""" for client in self.clients: diff --git a/bcipy/acquisition/tests/test_client_manager.py b/bcipy/acquisition/tests/test_client_manager.py index 3abf06ea3..7fbc3484a 100644 --- a/bcipy/acquisition/tests/test_client_manager.py +++ b/bcipy/acquisition/tests/test_client_manager.py @@ -1,6 +1,7 @@ import unittest from unittest.mock import Mock -from bcipy.acquisition.multimodal import ClientManager + +from bcipy.acquisition.multimodal import ClientManager, ContentType class TestClientManager(unittest.TestCase): @@ -11,6 +12,7 @@ def setUp(self): self.eeg_device_mock = Mock() self.eeg_device_mock.name = 'DSI-24' self.eeg_device_mock.content_type = 'EEG' + self.eeg_device_mock.sample_rate = 300 self.eeg_client_mock = Mock() self.eeg_client_mock.device_spec = self.eeg_device_mock @@ -18,15 +20,17 @@ def setUp(self): self.gaze_device_mock = Mock() self.gaze_device_mock.content_type = 'Eyetracker' + self.gaze_device_mock.sample_rate = 60 self.gaze_client_mock = Mock() self.gaze_client_mock.device_spec = self.gaze_device_mock def test_add_client(self): """Test adding a client""" manager = ClientManager() - self.assertEqual(manager.get_client('EEG'), None) + self.assertEqual(manager.get_client(ContentType.EEG), None) manager.add_client(self.eeg_client_mock) - self.assertEqual(manager.get_client('EEG'), self.eeg_client_mock) + self.assertEqual(manager.get_client(ContentType.EEG), + self.eeg_client_mock) def test_start_acquisition(self): """Test that manager can start acquisition in clients""" @@ -55,9 +59,10 @@ def test_default_client(self): manager.add_client(self.eeg_client_mock) manager.add_client(self.gaze_client_mock) + self.assertEqual(manager.default_content_type, ContentType.EEG) self.assertEqual(manager.default_client, self.eeg_client_mock) - manager.default_content_type = self.gaze_device_mock.content_type + manager.default_content_type = ContentType.EYETRACKER self.assertEqual(manager.default_client, self.gaze_client_mock) def test_device_specs(self): @@ -84,7 +89,27 @@ def test_dispatching_methods(self): daq.add_client(self.eeg_client_mock) daq.get_data(start=100, limit=1000) - self.eeg_client_mock.get_data.assert_called_once_with(start=100, limit=1000) + self.eeg_client_mock.get_data.assert_called_once_with(start=100, + limit=1000) + + def test_get_data_by_device(self): + """Test getting data for multiple devices""" + daq = ClientManager() + daq.add_client(self.eeg_client_mock) + daq.add_client(self.gaze_client_mock) + + results = daq.get_data_by_device( + start=100, + seconds=5, + content_types=[ContentType.EEG, ContentType.EYETRACKER]) + + self.eeg_client_mock.get_data.assert_called_once_with(start=100, + limit=1500) + self.gaze_client_mock.get_data.assert_called_once_with(start=100, + limit=300) + + self.assertTrue(ContentType.EEG in results) + self.assertTrue(ContentType.EYETRACKER in results) if __name__ == '__main__': diff --git a/bcipy/acquisition/tests/test_content_type.py b/bcipy/acquisition/tests/test_content_type.py index 1d528b28a..2803fd26d 100644 --- a/bcipy/acquisition/tests/test_content_type.py +++ b/bcipy/acquisition/tests/test_content_type.py @@ -8,10 +8,10 @@ class TestContentType(unittest.TestCase): """Tests for multimodal ContentType enum.""" - def test_label(self): - """Test that labels are strings""" - self.assertEqual('eeg', ContentType.EEG.label) - self.assertEqual('eyetracker', ContentType.EYETRACKER.label) + def test_value(self): + """Test that values are autoincremented""" + self.assertEqual(1, ContentType.EEG.value) + self.assertEqual(2, ContentType.EYETRACKER.value) def test_constructor(self): """Test retrieving an enum by value""" @@ -31,5 +31,6 @@ def test_unsupported_type(self): with self.assertRaises(UnsupportedContentType): ContentType('FooBar') + if __name__ == '__main__': unittest.main() diff --git a/bcipy/helpers/system_utils.py b/bcipy/helpers/system_utils.py index 5a47b75b0..c6882b0e6 100644 --- a/bcipy/helpers/system_utils.py +++ b/bcipy/helpers/system_utils.py @@ -8,13 +8,14 @@ import socket import sys import time -import torch +from enum import Enum from pathlib import Path -from typing import Callable, List, Optional, NamedTuple +from typing import Callable, List, NamedTuple, Optional import pkg_resources import psutil import pyglet +import torch from cpuinfo import get_cpu_info from bcipy.config import DEFAULT_ENCODING, LOG_FILENAME @@ -303,3 +304,17 @@ def wrap(*args, **kwargs): log.info('{:s} method took {:0.4f}s to execute'.format(func.__name__, (time2 - time1))) return response return wrap + + +class AutoNumberEnum(Enum): + """Enum that auto-numbers the value for each item. + + See: https://docs.python.org/3/howto/enum.html + """ + + def __new__(cls, *args): + """Autoincrements the value of each item added to the enum.""" + value = len(cls.__members__) + 1 + obj = object.__new__(cls) + obj._value_ = value + return obj diff --git a/bcipy/task/task_registry.py b/bcipy/task/task_registry.py index a587b427e..88661f531 100644 --- a/bcipy/task/task_registry.py +++ b/bcipy/task/task_registry.py @@ -1,7 +1,6 @@ """Task Registry ; used to provide task options to the GUI and command line tools. User defined tasks can be added to the Registry.""" - # NOTE: # In the future we may want to consider dynamically retrieving all subclasses # of Task and use these to populate a registry. We could also provide @@ -13,13 +12,13 @@ # the Task subclasses causes pygame (a psychopy dependency) to create a GUI, # which seems to prevent our other GUI code from working. -from enum import Enum from typing import List from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.helpers.system_utils import AutoNumberEnum -class TaskType(Enum): +class TaskType(AutoNumberEnum): """Enum of the registered experiment types (Tasks), along with the label used for display in the GUI and command line tools. Values are looked up by their (1-based) index. @@ -39,13 +38,6 @@ class TaskType(Enum): MATRIX_TIMING_VERIFICATION_CALIBRATION = 'Matrix Time Test Calibration' MATRIX_COPY_PHRASE = 'Matrix Copy Phrase' - def __new__(cls, *args, **kwds): - """Autoincrements the value of each item added to the enum.""" - value = len(cls.__members__) + 1 - obj = object.__new__(cls) - obj._value_ = value - return obj - def __init__(self, label): self.label = label @@ -60,9 +52,10 @@ def by_value(cls, item): @classmethod def calibration_tasks(cls) -> List['TaskType']: - return [task for task in cls - if task.name.endswith('CALIBRATION') and 'COPY_PHRASE' - not in task.name] + return [ + task for task in cls if task.name.endswith('CALIBRATION') and + 'COPY_PHRASE' not in task.name + ] @classmethod def list(cls) -> List[str]: From 35fc9551cd8df39878256e8794ced02e0fc76730 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 11 May 2023 15:37:34 -0700 Subject: [PATCH 015/330] Refactored bci_main to send the ClientManager directly to tasks --- bcipy/main.py | 10 +++++----- bcipy/task/start_task.py | 19 +++++++++--------- bcipy/tests/test_bci_main.py | 38 ++++++++++++++++-------------------- 3 files changed, 32 insertions(+), 35 deletions(-) diff --git a/bcipy/main.py b/bcipy/main.py index bdaf95ad0..9f8445875 100644 --- a/bcipy/main.py +++ b/bcipy/main.py @@ -1,14 +1,14 @@ import argparse import logging import multiprocessing - from typing import List from psychopy import visual -from bcipy.acquisition import LslDataServer, ClientManager +from bcipy.acquisition import ClientManager, LslDataServer +from bcipy.config import (DEFAULT_EXPERIMENT_ID, DEFAULT_PARAMETERS_PATH, + STATIC_AUDIO_PATH) from bcipy.display import init_display_window -from bcipy.config import DEFAULT_PARAMETERS_PATH, DEFAULT_EXPERIMENT_ID, STATIC_AUDIO_PATH from bcipy.helpers.acquisition import init_eeg_acquisition from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import (load_experiments, load_json_parameters, @@ -18,7 +18,7 @@ from bcipy.helpers.stimuli import play_sound from bcipy.helpers.system_utils import configure_logger, get_system_info from bcipy.helpers.task import print_message -from bcipy.helpers.validate import validate_experiment, validate_bcipy_session +from bcipy.helpers.validate import validate_bcipy_session, validate_experiment from bcipy.helpers.visualization import visualize_session_data from bcipy.signal.model import PcaRdaKdeModel from bcipy.task import TaskType @@ -159,7 +159,7 @@ def execute_task( # Start Task try: start_task(display, - daq.get_client('EEG'), + daq, task, parameters, save_folder, diff --git a/bcipy/task/start_task.py b/bcipy/task/start_task.py index f8acdb784..57949d8c8 100644 --- a/bcipy/task/start_task.py +++ b/bcipy/task/start_task.py @@ -1,14 +1,15 @@ """Code for constructing and executing registered tasks""" -from bcipy.task.paradigm.rsvp.calibration.calibration import RSVPCalibrationTask -from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask -from bcipy.task.paradigm.rsvp.calibration.timing_verification import RSVPTimingVerificationCalibration - -from bcipy.task.paradigm.matrix.calibration import MatrixCalibrationTask -from bcipy.task.paradigm.matrix.timing_verification import MatrixTimingVerificationCalibration -from bcipy.task.paradigm.matrix.copy_phrase import MatrixCopyPhraseTask - from bcipy.task import Task from bcipy.task.exceptions import TaskRegistryException +from bcipy.task.paradigm.matrix.calibration import MatrixCalibrationTask +from bcipy.task.paradigm.matrix.copy_phrase import MatrixCopyPhraseTask +from bcipy.task.paradigm.matrix.timing_verification import \ + MatrixTimingVerificationCalibration +from bcipy.task.paradigm.rsvp.calibration.calibration import \ + RSVPCalibrationTask +from bcipy.task.paradigm.rsvp.calibration.timing_verification import \ + RSVPTimingVerificationCalibration +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask from bcipy.task.task_registry import TaskType @@ -19,7 +20,7 @@ def make_task(display_window, daq, task, parameters, file_save, Parameters: ----------- display_window: psychopy Window - daq: DataAcquisitionClient + daq: ClientManager - manages one or more acquisition clients task: TaskType parameters: dict file_save: str - path to file in which to save data diff --git a/bcipy/tests/test_bci_main.py b/bcipy/tests/test_bci_main.py index 4ad19e905..bfc47cbf8 100644 --- a/bcipy/tests/test_bci_main.py +++ b/bcipy/tests/test_bci_main.py @@ -1,20 +1,16 @@ +import logging import unittest -from mockito import any, unstub, when, mock, verify, verifyStubbedInvocationsAreUsed, verifyNoUnwantedInteractions + +from mockito import (any, mock, unstub, verify, verifyNoUnwantedInteractions, + verifyStubbedInvocationsAreUsed, when) from bcipy import main -from bcipy.main import ( - bci_main, - _clean_up_session, - execute_task -) -from bcipy.config import DEFAULT_PARAMETERS_PATH, DEFAULT_EXPERIMENT_ID, STATIC_AUDIO_PATH - -from bcipy.helpers.exceptions import ( - UnregisteredExperimentException, -) +from bcipy.config import (DEFAULT_EXPERIMENT_ID, DEFAULT_PARAMETERS_PATH, + STATIC_AUDIO_PATH) +from bcipy.helpers.exceptions import UnregisteredExperimentException +from bcipy.main import _clean_up_session, bci_main, execute_task from bcipy.task import TaskType -import logging logging.disable(logging.CRITICAL) @@ -357,7 +353,7 @@ def test_execute_task_fake_data(self) -> None: verify(main, times=1).print_message(self.display_mock, any()) verify(main, times=1).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -379,7 +375,7 @@ def test_execute_task_real_data(self) -> None: when(main).print_message(self.display_mock, any()) when(main).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -399,7 +395,7 @@ def test_execute_task_real_data(self) -> None: verify(main, times=1).print_message(self.display_mock, any()) verify(main, times=1).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -431,7 +427,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: when(main).init_language_model(self.parameters).thenReturn(language_model) when(main).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -451,7 +447,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: verify(main, times=1).print_message(self.display_mock, any()) verify(main, times=1).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -488,7 +484,7 @@ def test_execute_language_model_enabled(self) -> None: }, filename='').thenReturn(load_model_response) when(main).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -508,7 +504,7 @@ def test_execute_language_model_enabled(self) -> None: verify(main, times=1).print_message(self.display_mock, any()) verify(main, times=1).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -534,7 +530,7 @@ def test_execute_with_alert_enabled(self): when(main).print_message(self.display_mock, any()) when(main).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, @@ -555,7 +551,7 @@ def test_execute_with_alert_enabled(self): verify(main, times=1).print_message(self.display_mock, any()) verify(main, times=1).start_task( self.display_mock, - self.eeg_client, + self.daq, self.task, self.parameters, self.save_folder, From a5f7085c654eebdb522552542c12612b25755276 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 11 May 2023 16:14:29 -0700 Subject: [PATCH 016/330] Modified multimodal get_data to correctly handle marker queries --- bcipy/acquisition/multimodal.py | 14 +++++++---- .../acquisition/tests/test_client_manager.py | 24 +++++++++++++++---- 2 files changed, 29 insertions(+), 9 deletions(-) diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 5e56c85f1..1040c4257 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -115,11 +115,15 @@ def get_data_by_device( output = {} for content_type in content_types: client = self.get_client(content_type) - count = round(seconds * client.device_spec.sample_rate) - log.debug( - f'Need {count} records for processing {content_type.name} data' - ) - output[content_type] = client.get_data(start=start, limit=count) + if client.device_spec.sample_rate > 0: + count = round(seconds * client.device_spec.sample_rate) + log.debug( + f'Need {count} records for processing {content_type.name} data' + ) + output[content_type] = client.get_data(start=start, limit=count) + else: + # Markers have an IRREGULAR_RATE. + output[content_type] = client.get_data(start=start, end=start+seconds) return output def cleanup(self): diff --git a/bcipy/acquisition/tests/test_client_manager.py b/bcipy/acquisition/tests/test_client_manager.py index 7fbc3484a..fa9d08819 100644 --- a/bcipy/acquisition/tests/test_client_manager.py +++ b/bcipy/acquisition/tests/test_client_manager.py @@ -94,22 +94,38 @@ def test_dispatching_methods(self): def test_get_data_by_device(self): """Test getting data for multiple devices""" + # Set up switch device mock + switch_device_mock = Mock() + switch_device_mock.name = 'Test-switch-2000' + switch_device_mock.content_type = 'Markers' + switch_device_mock.sample_rate = 0.0 + + switch_client_mock = Mock() + switch_client_mock.device_spec = switch_device_mock + switch_client_mock.get_data = Mock() + daq = ClientManager() daq.add_client(self.eeg_client_mock) daq.add_client(self.gaze_client_mock) + daq.add_client(switch_client_mock) - results = daq.get_data_by_device( - start=100, - seconds=5, - content_types=[ContentType.EEG, ContentType.EYETRACKER]) + results = daq.get_data_by_device(start=100, + seconds=5, + content_types=[ + ContentType.EEG, + ContentType.EYETRACKER, + ContentType.MARKERS + ]) self.eeg_client_mock.get_data.assert_called_once_with(start=100, limit=1500) self.gaze_client_mock.get_data.assert_called_once_with(start=100, limit=300) + switch_client_mock.get_data.assert_called_with(start=100, end=105) self.assertTrue(ContentType.EEG in results) self.assertTrue(ContentType.EYETRACKER in results) + self.assertTrue(ContentType.MARKERS in results) if __name__ == '__main__': From ca1302b5c15c4c33e1e251a44edfdd65f3f51dd5 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Fri, 12 May 2023 13:44:33 -0400 Subject: [PATCH 017/330] WIP Offline Analysis Fusion --- bcipy/helpers/acquisition.py | 2 +- bcipy/helpers/load.py | 13 ------------- bcipy/signal/model/offline_analysis.py | 4 ++-- bcipy/signal/model/offline_gaze_analysis.py | 14 ++++++++++---- scripts/python/plot_eye_data.py | 14 +++++++------- 5 files changed, 20 insertions(+), 27 deletions(-) diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index ff813ed9e..83c878dea 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -206,7 +206,7 @@ def analysis_channels(channels: List[str], device_spec: DeviceSpec) -> list: ---------- - channels(list(str)): list of channel names from the raw_data (excluding the timestamp) - - device_spec(str): device from which the data was collected + - device_spec: device from which the data was collected Returns -------- diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index e5bc05ff7..57b4597d4 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -238,19 +238,6 @@ def load_raw_data(data_folder: str, data_paths: List[str]) -> List[RawData]: raise FileNotFoundError(f'Could not find {filename}') return data -def load_raw_gaze_data(filename: str) -> RawData: - """Reads the data (.csv) file written by data acquisition. - - Parameters - ---------- - - filename : path to the serialized data (csv file) - - Returns - ------- - RawData object with data held in memory - """ - return RawData.load(filename) - def load_txt_data() -> str: filename = ask_filename('*.txt') # show dialog box and return the path diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 0975decf9..37312dbeb 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -233,8 +233,8 @@ def offline_analysis( show=show_figures ) if device_spec.content_type == "Eyetracker": - # TODO: Add eyetracker processing - log.info("Eyetracker data found. Processing not yet implemented.") + print(device_spec) + breakpoint() pass if alert_finished: diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py index 6a586c22b..de8a6796b 100644 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ b/bcipy/signal/model/offline_gaze_analysis.py @@ -7,16 +7,20 @@ from matplotlib import pyplot as plt from sklearn.mixture import GaussianMixture -from bcipy.config import DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME +from bcipy.config import (DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, + RAW_DATA_FILENAME, STATIC_AUDIO_PATH, + DEFAULT_DEVICE_SPEC_FILENAME, + EYE_TRACKER_FILENAME_PREFIX) from bcipy.preferences import preferences from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import ( load_experimental_data, load_json_parameters, - load_raw_gaze_data + load_raw_data ) from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.signal.model.fusion_model import GazeModel +import bcipy.acquisition.devices as devices from sklearn.model_selection import train_test_split @@ -64,15 +68,17 @@ def offline_gaze_analysis( # The task buffer length defines the min time between two inquiries # We use half of that time here to buffer during transforms buffer = int(parameters.get("task_buffer_length") / 2) - raw_data_file = f"{RAW_DATA_FILENAME}.csv" log.info( f"\nData processing settings: \n" f"Poststimulus: {poststim_length}s, Prestimulus: {prestim_length}s, Buffer: {buffer}s, Trials per inquiry: {trials_per_inquiry} \n" ) + data_file_path = [f"{RAW_DATA_FILENAME}.csv"] + # Load raw data - gaze_data = load_raw_gaze_data(Path(data_folder, raw_data_file)) + data_list = load_raw_data(data_folder, data_file_path) + gaze_data = data_list[0] channels = gaze_data.channels type_amp = gaze_data.daq_type sample_rate = gaze_data.sample_rate diff --git a/scripts/python/plot_eye_data.py b/scripts/python/plot_eye_data.py index 0a1dd0ef1..13c85ee1b 100644 --- a/scripts/python/plot_eye_data.py +++ b/scripts/python/plot_eye_data.py @@ -2,7 +2,7 @@ from bcipy.helpers.raw_data import load DIPSIZE = (1707, 1067) -IMG_PATH = 'C:\\Users\\tabme\\work\\bci\\BciPy\\scripts\\python\\matrix_grid.png' +IMG_PATH = '/Users/basak/Documents/BciPy/scripts/python/matrix_grid.png' def load_eye_tracking_data(path): data = load(f'{path}/eyetracker_data_tobii-p0.csv') @@ -72,18 +72,18 @@ def load_eye_tracking_data(path): # ax.plot(rx, ry, c='b', linewidth=1) # remove nan values - # lx = lx[~np.isnan(lx)] - # ly = ly[~np.isnan(ly)] - # rx = rx[~np.isnan(rx)] - # ry = ry[~np.isnan(ry)] + lx = lx[~np.isnan(lx)] + ly = ly[~np.isnan(ly)] + rx = rx[~np.isnan(rx)] + ry = ry[~np.isnan(ry)] # determine kde of the eye data - # ax = sns.kdeplot(lx, ly, cmap="mako", fill=False, thresh=0.05, levels=10) + ax = sns.kdeplot(lx, ly, cmap="mako", fill=False, thresh=0.05, levels=10, colorbar=True) ax.scatter(lx, ly, c='r', s=1) ax.scatter(rx, ry, c='b', s=1) - # plt.show() + plt.show() breakpoint() \ No newline at end of file From b39cb462371e89b60268ce3188a37fd119b27d87 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 12 May 2023 17:08:12 -0700 Subject: [PATCH 018/330] Added a module for evidence evaluators; created an evaluator for EEG evidence. Added some utility functions for using subsets of parameters --- bcipy/acquisition/multimodal.py | 5 + bcipy/helpers/parameters.py | 11 ++ bcipy/helpers/tests/test_parameters.py | 38 ++++++- bcipy/task/control/evidence.py | 117 ++++++++++++++++++++ bcipy/task/data.py | 1 + bcipy/task/exceptions.py | 4 + bcipy/task/tests/core/test_eeg_evaluator.py | 93 ++++++++++++++++ 7 files changed, 268 insertions(+), 1 deletion(-) create mode 100644 bcipy/task/control/evidence.py create mode 100644 bcipy/task/tests/core/test_eeg_evaluator.py diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 1040c4257..844cf2db0 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -66,6 +66,11 @@ def clients(self) -> List[LslAcquisitionClient]: """Returns a list of the managed clients.""" return self._clients.values() + @property + def clients_by_type(self) -> Dict[ContentType, LslAcquisitionClient]: + """Returns a dict of clients keyed by their content type""" + return self._clients + @property def device_specs(self) -> List[DeviceSpec]: """Returns a list of DeviceSpecs for all the clients.""" diff --git a/bcipy/helpers/parameters.py b/bcipy/helpers/parameters.py index 286b8e44a..6dc63a6c2 100644 --- a/bcipy/helpers/parameters.py +++ b/bcipy/helpers/parameters.py @@ -267,6 +267,17 @@ def diff(self, parameters) -> Dict[str, ParameterChange]: original_value=None) return diffs + def instantiate(self, named_tuple_class: type) -> NamedTuple: + """Instantiate a namedtuple whose fields represent a subset of the + parameters.""" + vals = [ + self.cast_value(self.get_entry(key)) + for key in named_tuple_class._fields + ] + return named_tuple_class(*vals) + + + def changes_from_default(source: str) -> Dict[str, ParameterChange]: """Determines which parameters have changed from the default params. diff --git a/bcipy/helpers/tests/test_parameters.py b/bcipy/helpers/tests/test_parameters.py index 2b5c553c4..fb85cea96 100644 --- a/bcipy/helpers/tests/test_parameters.py +++ b/bcipy/helpers/tests/test_parameters.py @@ -2,7 +2,7 @@ import shutil import tempfile import unittest -from collections import abc +from collections import abc, namedtuple from pathlib import Path from bcipy.config import DEFAULT_PARAMETERS_PATH @@ -552,6 +552,42 @@ def test_changed_parameters(self): self.assertEqual(changes["entry_3"].parameter['value'], entry3_modified['value']) + def test_instantiate_tuple(self): + """Test that a namedtuple can be instantiated.""" + sample_config = { + "a": { + "value": "1", + "section": "", + "readableName": "", + "helpTip": "", + "recommended_values": "", + "type": "int" + }, + "b": { + "value": "2", + "section": "", + "readableName": "", + "helpTip": "", + "recommended_values": [], + "type": "int" + }, + "c": { + "value": "3", + "section": "", + "readableName": "", + "helpTip": "", + "recommended_values": [], + "type": "str" + } + } + parameters = Parameters(source=None, cast_values=True) + parameters.load(sample_config) + + MyTuple = namedtuple("MyTuple", 'a c') + my_tuple = parameters.instantiate(MyTuple) + self.assertEqual(my_tuple.a, 1) + self.assertEqual(my_tuple.c, '3') + self.assertEqual((1, '3'), my_tuple) if __name__ == '__main__': unittest.main() diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py new file mode 100644 index 000000000..2a61a721f --- /dev/null +++ b/bcipy/task/control/evidence.py @@ -0,0 +1,117 @@ +"""Classes and functions for extracting evidence from raw device data.""" +from typing import List, NamedTuple + +import numpy as np + +from bcipy.acquisition.multimodal import ContentType +from bcipy.helpers.acquisition import DeviceSpec, analysis_channels +from bcipy.helpers.stimuli import TrialReshaper +from bcipy.signal.model import SignalModel +from bcipy.signal.process import get_default_transform +from bcipy.task.data import EvidenceType +from bcipy.task.exceptions import MissingEvidenceEvaluator + + +class EvidenceEvaluator: + """Base class""" + + @property + def consumes(self) -> ContentType: + """ContentType of the data that should be input""" + + @property + def produces(self) -> EvidenceType: + """Type of evidence that is output""" + + def evaluate(self, *args, **kwargs): + """Evaluate the evidence""" + + +# TODO: can this go in the signal module? +class FilterParams(NamedTuple): + """Parameters used to filter signal data""" + notch_filter_frequency: int = 60 + filter_low: int = 2 + filter_high: int = 45 + filter_order: int = 2 + downsample_rate: int = 2 + + +class EegEvaluator(EvidenceEvaluator): + """Extracts symbol likelihoods from raw EEG data""" + consumes = ContentType.EEG + produces = EvidenceType.ERP + + def __init__(self, symbol_set: List[str], signal_model: SignalModel, + device_spec: DeviceSpec, filter_params: FilterParams): + assert ContentType( + device_spec.content_type + ) == self.consumes, "evaluator is not compatible with the given device" + self.symbol_set = symbol_set + self.signal_model = signal_model + self.filter_params = filter_params + + self.sample_rate = device_spec.sample_rate + self.channel_map = analysis_channels(device_spec.channels, device_spec) + + # pylint: disable=arguments-differ + def evaluate(self, raw_data: np.array, symbols: List[str], + times: List[float], target_info: List[str], + window_length: float) -> np.array: + """Evaluate the evidence. + + Parameters + ---------- + raw_data - C x L eeg data where C is number of channels and L is the + signal length + symbols - symbols displayed in the inquiry + times - timestamps associated with each symbol + target_info - target information about the stimuli; + ex. ['nontarget', 'nontarget', ...] + window_length - The length of the time between stimuli presentation + """ + + transform = get_default_transform( + sample_rate_hz=self.sample_rate, + notch_freq_hz=self.filter_params.notch_filter_frequency, + bandpass_low=self.filter_params.filter_low, + bandpass_high=self.filter_params.filter_high, + bandpass_order=self.filter_params.filter_order, + downsample_factor=self.filter_params.downsample_rate, + ) + + transformed_data, transform_sample_rate = transform( + raw_data, self.sample_rate) + + # The data from DAQ is assumed to have offsets applied + reshape = TrialReshaper() + reshaped_data, _lbls = reshape(trial_targetness_label=target_info, + timing_info=times, + eeg_data=transformed_data, + sample_rate=transform_sample_rate, + channel_map=self.channel_map, + poststimulus_length=window_length) + + return self.signal_model.predict(reshaped_data, symbols, + self.symbol_set) + + +def get_evaluator(data_source: ContentType, + evidence_type: EvidenceType) -> EvidenceEvaluator: + """Returns the matching evaluator. + + Parameters + ---------- + data_source - type of data that the evaluator should consume + evidence_type - type of evidence that the evaluator should produce. + """ + matches = [ + cls for cls in EvidenceEvaluator.__subclasses__() + if cls.consumes == data_source and cls.produces == evidence_type + ] + if matches: + return matches[0] + else: + raise MissingEvidenceEvaluator( + f"Evidence Evaluator not found for {data_source.name} -> {evidence_type.name}" + ) diff --git a/bcipy/task/data.py b/bcipy/task/data.py index f77a927cc..9a4bdb97a 100644 --- a/bcipy/task/data.py +++ b/bcipy/task/data.py @@ -21,6 +21,7 @@ class EvidenceType(Enum): LM = 'LM' # Language Model ERP = 'ERP' # Event-Related Potential using EEG signals BTN = 'BTN' # Button + EYE = 'EYE' # Eyetracker @classmethod def list(cls) -> List[str]: diff --git a/bcipy/task/exceptions.py b/bcipy/task/exceptions.py index 73a7590c9..ecf52d73d 100644 --- a/bcipy/task/exceptions.py +++ b/bcipy/task/exceptions.py @@ -19,3 +19,7 @@ class TaskRegistryException(Exception): def __init__(self, message, errors=None): super().__init__(message) self.errors = errors + +class MissingEvidenceEvaluator(Exception): + """Thrown when an evidence evaluator can't be found that matches the + provided data content type input and evidence_type output""" \ No newline at end of file diff --git a/bcipy/task/tests/core/test_eeg_evaluator.py b/bcipy/task/tests/core/test_eeg_evaluator.py new file mode 100644 index 000000000..2a80bdc1e --- /dev/null +++ b/bcipy/task/tests/core/test_eeg_evaluator.py @@ -0,0 +1,93 @@ +"""Tests for EEG evidence evaluator""" + +import unittest +from unittest.mock import Mock, patch + +from bcipy.task.control.evidence import EegEvaluator, FilterParams + + +class TestEegEvaluator(unittest.TestCase): + """Tests for EEG evidence evaluator.""" + + def setUp(self): + """Setup common state""" + self.symbol_set = [] + + self.device_mock = Mock() + self.device_mock.content_type = 'EEG' + self.device_mock.channels = ['ch1', 'ch2', 'ch3'] + self.device_mock.sample_rate = 300 + + self.filter_params = FilterParams() + self.signal_model_mock = Mock() + + @patch('bcipy.task.control.evidence.analysis_channels') + def test_init(self, analysis_channels_mock): + """Test initialization""" + EegEvaluator(self.symbol_set, self.signal_model_mock, self.device_mock, + self.filter_params) + analysis_channels_mock.assert_called_with(self.device_mock.channels, + self.device_mock) + + @patch('bcipy.task.control.evidence.analysis_channels') + @patch('bcipy.task.control.evidence.get_default_transform') + @patch('bcipy.task.control.evidence.TrialReshaper') + def test_evaluate(self, reshaper_factory_mock, transform_factory_mock, + analysis_channels_mock): + """Test evaluation of evidence""" + + # Mocks + raw_data = Mock() + channel_map = Mock() + analysis_channels_mock.return_value = channel_map + + transformed_data = Mock() + transformer_mock = Mock() + transform_factory_mock.return_value = transformer_mock + transformer_mock.return_value = (transformed_data, 150) + + reshaper_mock = Mock() + reshaper_factory_mock.return_value = reshaper_mock + reshaped_data = Mock() + reshaper_mock.return_value = reshaped_data, Mock() + + # Parameters + symbols = ["+", "H", "D", "J", "B", "C", "A", "F", "G", "I", "E"] + times = [ + 0.0, 0.56, 0.81, 1.08, 1.33, 1.58, 1.83, 2.08, 2.33, 2.58, 2.83 + ] + target_info = ['nontarget'] * len(symbols) + window_length = 0.5 + + # Run the code + evaluator = EegEvaluator(self.symbol_set, self.signal_model_mock, + self.device_mock, self.filter_params) + evaluator.evaluate(raw_data, symbols, times, target_info, + window_length) + + # Assertions + transform_factory_mock.assert_called_once_with( + sample_rate_hz=self.device_mock.sample_rate, + notch_freq_hz=self.filter_params.notch_filter_frequency, + bandpass_low=self.filter_params.filter_low, + bandpass_high=self.filter_params.filter_high, + bandpass_order=self.filter_params.filter_order, + downsample_factor=self.filter_params.downsample_rate) + + transformer_mock.assert_called_once_with(raw_data, + self.device_mock.sample_rate) + + reshaper_mock.assert_called_once_with( + trial_targetness_label=target_info, + timing_info=times, + eeg_data=transformed_data, + sample_rate=150, + channel_map=channel_map, + poststimulus_length=window_length) + + self.signal_model_mock.assert_called_once_with(reshaped_data, symbols, + self.symbol_set) + + +if __name__ == '__main__': + unittest.main() From 6af1c9c40476911e61f4dda30eca63b92e35c0f5 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 12 May 2023 17:08:44 -0700 Subject: [PATCH 019/330] Added offset triggers for all devices in calibration and copy phrase trigger data --- .../paradigm/rsvp/calibration/calibration.py | 59 +++++++++--------- bcipy/task/paradigm/rsvp/copy_phrase.py | 60 ++++++++++--------- 2 files changed, 63 insertions(+), 56 deletions(-) diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index cd4538e59..014cbf5d1 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -1,20 +1,21 @@ -from psychopy import core from typing import List, Tuple +from psychopy import core + +from bcipy.acquisition.multimodal import ContentType from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE -from bcipy.display import ( - InformationProperties, - PreviewInquiryProperties, - StimuliProperties) -from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay +from bcipy.display import (InformationProperties, PreviewInquiryProperties, + StimuliProperties) from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay from bcipy.helpers.clock import Clock - -from bcipy.helpers.stimuli import (StimuliOrder, TargetPositions, calibration_inquiry_generator) +from bcipy.helpers.stimuli import (StimuliOrder, TargetPositions, + calibration_inquiry_generator) +from bcipy.helpers.symbols import alphabet from bcipy.helpers.task import (get_user_input, pause_calibration, trial_complete_message) -from bcipy.helpers.symbols import alphabet -from bcipy.helpers.triggers import FlushFrequency, TriggerHandler, Trigger, TriggerType, convert_timing_triggers +from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, + TriggerType, convert_timing_triggers) from bcipy.task import Task @@ -199,15 +200,16 @@ def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None See RSVPDisplay._trigger_pulse() for more information. """ # write offsets. currently, we only check for offsets at the beginning. - if self.daq.is_calibrated and first_run: - self.trigger_handler.add_triggers( - [Trigger( - 'starting_offset', - TriggerType.OFFSET, - # offset will factor in true offset and time relative from beginning - (self.daq.offset(self.rsvp.first_stim_time) - self.rsvp.first_stim_time) - )] - ) + # offset will factor in true offset and time relative from beginning + if first_run: + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + suffix = '' if content_type == ContentType.EEG else '_' + content_type.name + label = f"starting_offset{suffix}" + time = client.offset( + self.rsvp.first_stim_time) - self.rsvp.first_stim_time + triggers.append(Trigger(label, TriggerType.OFFSET, time)) + self.trigger_handler.add_triggers(triggers) # make sure triggers are written for the inquiry self.trigger_handler.add_triggers(convert_timing_triggers(timing, timing[0][0], self.trigger_type)) @@ -215,15 +217,16 @@ def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None def write_offset_trigger(self) -> None: """Append an offset value to the end of the trigger file. """ - if self.daq.is_calibrated: - self.trigger_handler.add_triggers( - [Trigger( - 'daq_sample_offset', - TriggerType.SYSTEM, - # to help support future refactoring or use of lsl timestamps only - # we write only the sample offset here - self.daq.offset(self.rsvp.first_stim_time) - )]) + # To help support future refactoring or use of lsl timestamps only + # we write only the sample offset here. + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + suffix = '' if content_type == ContentType.EEG else '_' + content_type.name + label = f"daq_sample_offset{suffix}" + time = client.offset(self.rsvp.first_stim_time) + triggers.append(Trigger(label, TriggerType.SYSTEM, time)) + + self.trigger_handler.add_triggers(triggers) self.trigger_handler.close() def name(self): diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index c275c4354..4f97569ad 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -3,13 +3,13 @@ from psychopy import core -from bcipy.config import ( - SESSION_DATA_FILENAME, TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE, SESSION_SUMMARY_FILENAME) -from bcipy.display import (InformationProperties, PreviewInquiryProperties, - StimuliProperties) -from bcipy.display import Display -from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay +from bcipy.acquisition.multimodal import ContentType +from bcipy.config import (SESSION_DATA_FILENAME, SESSION_SUMMARY_FILENAME, + TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE) +from bcipy.display import (Display, InformationProperties, + PreviewInquiryProperties, StimuliProperties) from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay from bcipy.feedback.visual.visual_feedback import VisualFeedback from bcipy.helpers.clock import Clock from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper @@ -18,11 +18,10 @@ from bcipy.helpers.save import _save_session_related_data from bcipy.helpers.session import session_excel from bcipy.helpers.stimuli import InquirySchedule, StimuliOrder -from bcipy.helpers.task import (construct_triggers, - fake_copy_phrase_decision, +from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet +from bcipy.helpers.task import (construct_triggers, fake_copy_phrase_decision, get_data_for_decision, get_user_input, target_info, trial_complete_message) -from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, convert_timing_triggers) from bcipy.signal.model.inquiry_preview import compute_probs_after_preview @@ -482,6 +481,8 @@ def add_evidence(self, stim_times: List[List], -------- - self.copy_phrase_task """ + # TODO: refactor compute_eeg_evidence to compute_device_evidence + # for each daq client evidences = [ self.compute_button_press_evidence(proceed), self.compute_eeg_evidence(stim_times, proceed) @@ -666,15 +667,16 @@ def write_session_data(self) -> None: def write_offset_trigger(self) -> None: """Append the offset to the end of the triggers file. """ - if self.daq.is_calibrated: - self.trigger_handler.add_triggers( - [Trigger( - 'daq_sample_offset', - TriggerType.SYSTEM, - # to help support future refactoring or use of lsl timestamps only - # we write only the sample offset here - self.daq.offset(self.rsvp.first_stim_time) - )]) + # To help support future refactoring or use of lsl timestamps only + # we write only the sample offset here. + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + suffix = '' if content_type == ContentType.EEG else '_' + content_type.name + label = f"daq_sample_offset{suffix}" + time = client.offset(self.rsvp.first_stim_time) + triggers.append(Trigger(label, TriggerType.SYSTEM, time)) + + self.trigger_handler.add_triggers(triggers) self.trigger_handler.close() def write_trigger_data(self, stim_times: List[Tuple[str, float]], target_stimuli: str) -> None: @@ -685,16 +687,18 @@ def write_trigger_data(self, stim_times: List[Tuple[str, float]], target_stimuli - stim_times : list of (stim, clock_time) tuples - target_stimuli : current target stimuli """ - if self.first_run and self.daq.is_calibrated: - # write offset first - self.trigger_handler.add_triggers( - [Trigger( - 'starting_offset', - TriggerType.OFFSET, - # offset will factor in true offset and time relative from beginning - (self.daq.offset(self.rsvp.first_stim_time) - self.rsvp.first_stim_time) - )] - ) + + if self.first_run: + # offset will factor in true offset and time relative from beginning + offset_triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + suffix = '' if content_type == ContentType.EEG else '_' + content_type.name + label = f"starting_offset{suffix}" + time = client.offset( + self.rsvp.first_stim_time) - self.rsvp.first_stim_time + offset_triggers.append(Trigger(label, TriggerType.OFFSET, + time)) + self.trigger_handler.add_triggers(offset_triggers) triggers = convert_timing_triggers(stim_times, target_stimuli, self.trigger_type) self.trigger_handler.add_triggers(triggers) From ff35f05f0f610d2f492c5c314a7dd0366efc8b17 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Mon, 15 May 2023 21:18:13 -0700 Subject: [PATCH 020/330] Cleanup and add rsvp image --- .../static/images/main}/matrix_grid.png | Bin bcipy/static/images/main/rsvp.png | Bin 0 -> 13768 bytes scripts/python/plot_eye_data.py | 7 +++++-- 3 files changed, 5 insertions(+), 2 deletions(-) rename {scripts/python => bcipy/static/images/main}/matrix_grid.png (100%) create mode 100644 bcipy/static/images/main/rsvp.png diff --git a/scripts/python/matrix_grid.png b/bcipy/static/images/main/matrix_grid.png similarity index 100% rename from scripts/python/matrix_grid.png rename to bcipy/static/images/main/matrix_grid.png diff --git a/bcipy/static/images/main/rsvp.png b/bcipy/static/images/main/rsvp.png new file mode 100644 index 0000000000000000000000000000000000000000..2dad51227087cb482dd7e8cef41e3ea7daa4074b GIT binary patch literal 13768 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b/scripts/python/plot_eye_data.py index c149e3a22..0fd04515f 100644 --- a/scripts/python/plot_eye_data.py +++ b/scripts/python/plot_eye_data.py @@ -3,7 +3,7 @@ from bcipy.config import STATIC_IMAGES_PATH DIPSIZE = (1707, 1067) -IMG_PATH = f'{STATIC_IMAGES_PATH}/matrix_grid.png' +IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' # IMG_PATH = f'{STATIC_IMAGES_PATH}/rsvp.png' TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' From 9d32bdb1da1628c9e821cb663fc53f7a930dcd33 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Tue, 23 May 2023 11:00:07 -0400 Subject: [PATCH 022/330] Merging gaze plotting and offline analysis WIP --- bcipy/helpers/load.py | 13 +++++ bcipy/helpers/stimuli.py | 1 + bcipy/parameters/parameters.json | 2 +- bcipy/signal/model/offline_analysis.py | 71 ++++++++++++++++++++++++-- scripts/python/plot_eye_data.py | 5 +- 5 files changed, 85 insertions(+), 7 deletions(-) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 57b4597d4..f93bff73d 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -162,6 +162,19 @@ def load_experimental_data() -> str: return filename +def load_eye_tracking_data(gaze_data: RawData): + left_eye_channel_map = [0,0,1,1,0,0,0,0,0] + left_eye_data, _, _ = gaze_data.by_channel_map(left_eye_channel_map) + left_eye_x = left_eye_data[0] + left_eye_y = left_eye_data[1] + + right_eye_channel_map = [0,0,0,0,0,1,1,0,0] + right_eye_data, _, _ = gaze_data.by_channel_map(right_eye_channel_map) + right_eye_x = right_eye_data[0] + right_eye_y = right_eye_data[1] + return left_eye_x, left_eye_y, right_eye_x, right_eye_y + + def load_signal_model(model_class: SignalModel, model_kwargs: Dict[str, Any], filename: str = None) -> Tuple[SignalModel, str]: """Construct the specified model and load pretrained parameters. diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 5f51dc89c..c95a6cc23 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -289,6 +289,7 @@ def get_inquiry_len(inq_trigs): breakpoint() # We will trim off the extra bits in each inquiry to match the shortest inquiry + # TODO num_samples_per_inq = get_inquiry_len(longest_inquiry) + trial_duration_samples diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 48c6b093b..a779570c2 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -8,7 +8,7 @@ "type": "bool" }, "acq_mode": { - "value": "EEG", + "value": "EEG+Eyetracker", "section": "acq_config", "readableName": "Acquisition Mode", "helpTip": "Specifies the hardware device(s) used for data collection.", diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 37312dbeb..2d8a9bacb 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -5,13 +5,14 @@ from bcipy.config import (DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME, STATIC_AUDIO_PATH, DEFAULT_DEVICE_SPEC_FILENAME, - EYE_TRACKER_FILENAME_PREFIX) + EYE_TRACKER_FILENAME_PREFIX, STATIC_IMAGES_PATH) from bcipy.preferences import preferences from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import ( load_experimental_data, load_json_parameters, load_raw_data, + load_eye_tracking_data ) from bcipy.helpers.stimuli import play_sound, update_inquiry_timing from bcipy.helpers.system_utils import report_execution_time @@ -19,10 +20,13 @@ from bcipy.helpers.visualization import visualize_erp from bcipy.signal.model.base_model import SignalModel from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel +from bcipy.signal.model.fusion_model import GazeModel from bcipy.signal.process import filter_inquiries, get_default_transform - import numpy as np from matplotlib.figure import Figure +import matplotlib.pyplot as plt +from matplotlib import image +import seaborn as sns from sklearn.metrics import balanced_accuracy_score from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices @@ -30,6 +34,9 @@ log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") +DIPSIZE = (1707, 1067) +IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' +# IMG_PATH = f'{STATIC_IMAGES_PATH}/main/rsvp.png' def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): """Performs a train/test split on the provided data and labels, accounting for @@ -233,9 +240,65 @@ def offline_analysis( show=show_figures ) if device_spec.content_type == "Eyetracker": - print(device_spec) + lx, ly, rx, ry = load_eye_tracking_data(mode_data) + dpi = 100 + img = plt.imread(IMG_PATH) + w, h = len(img[0]), len(img) + + fig, ax = plt.subplots() + ax.imshow(img, extent=[0, 1, 0, 1]) + # transform the eye data to fit the display. remove > 1 values < 0 values, remove nan values + for axes in [lx, ly, rx, ry]: + axes = axes[~np.isnan(axes)] + axes = np.clip(axes, 0, 1) + + # flip the y axis + ly = 1 - ly + ry = 1 - ry + + # # determine kde of the eye data + # ax = sns.kdeplot(lx, ly, cmap="mako", fill=False, thresh=0.05, levels=10, colorbar=True) + + ax.scatter(lx, ly, c='r', s=1) + ax.scatter(rx, ry, c='b', s=1) + plt.show() + channels = mode_data.channels + type_amp = mode_data.daq_type + sample_rate = mode_data.sample_rate + + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + + channel_map = analysis_channels(channels, device_spec) + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + log.info(f'Channels used in analysis: {channels_used}') + + data, fs = mode_data.by_channel() + + model = GazeModel() breakpoint() - pass + + # Process triggers.txt files (again!) + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + remove_pre_fixation = False, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.OFFSET], + ) + + inquiries, inquiry_labels, inquiry_timing = model.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=trigger_timing, + gaze_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=poststim_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) + + breakpoint() + if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") diff --git a/scripts/python/plot_eye_data.py b/scripts/python/plot_eye_data.py index 0fd04515f..8e58ccbad 100644 --- a/scripts/python/plot_eye_data.py +++ b/scripts/python/plot_eye_data.py @@ -1,11 +1,12 @@ - +import os from bcipy.helpers.raw_data import load from bcipy.config import STATIC_IMAGES_PATH DIPSIZE = (1707, 1067) IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' -# IMG_PATH = f'{STATIC_IMAGES_PATH}/rsvp.png' +# IMG_PATH = f'{STATIC_IMAGES_PATH}/main/rsvp.png' TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' +# IMG_PATH = os.path.abspath(os.path.dirname(__file__))+ '/matrix_grid.png' def load_eye_tracking_data(path): data = load(f'{path}/{TOBII_FILENAME}') From daa1173ff8fe3c4d11648f2dfd8300e620f78748 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 23 May 2023 15:46:48 -0700 Subject: [PATCH 023/330] Add a visualize gaze method, cleanup --- bcipy/helpers/visualization.py | 109 +++++++++++++++++- bcipy/signal/model/offline_analysis.py | 8 +- .../main/{matrix_grid.png => matrix.png} | Bin requirements.txt | 2 +- scripts/python/plot_eye_data.py | 62 +--------- 5 files changed, 119 insertions(+), 62 deletions(-) rename bcipy/static/images/main/{matrix_grid.png => matrix.png} (100%) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 0eceb5362..00ff441f1 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -6,7 +6,8 @@ import matplotlib.pyplot as plt from bcipy.config import (TRIGGER_FILENAME, RAW_DATA_FILENAME, - DEFAULT_DEVICE_SPEC_FILENAME) + DEFAULT_DEVICE_SPEC_FILENAME, + STATIC_IMAGES_PATH) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.convert import convert_to_mne @@ -19,6 +20,10 @@ import mne from mne import Epochs from mne.io import read_raw_edf +import numpy as np +import seaborn as sns +import matplotlib.pyplot as plt +import pandas as pd log = logging.getLogger(__name__) @@ -70,6 +75,102 @@ def visualize_erp( return figs +def visualize_gaze( + data, + left_keys=['left_x', 'left_y'], + right_keys=['right_x', 'right_y'], + save_path=None, + show=False, + img_path=None, + screen_size=(1920, 1080), + heatmap=False, + raw_plot=False): + """Visualize Eye Data. + + Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default + image used is for the matrix calibration task on a 1920x1080 screen. + + Parameters + ---------- + data: RawData + save_path: Optional[str] + show: Optional[bool] + img_path: Optional[str] + screen_size: Optional[Tuple[int, int]] TODO + """ + + title = f'{data.daq_type} ' + if heatmap: + title += 'Heatmap ' + if raw_plot: + title += 'Raw Gaze ' + + if img_path is None: + img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img = plt.imread(img_path) + channels = data.channels + left_eye_channel_map = [1 if channel in left_keys else 0 for channel in channels] + left_eye_data, _, _ = data.by_channel_map(left_eye_channel_map) + left_eye_x = left_eye_data[0] + left_eye_y = left_eye_data[1] + + right_eye_channel_map = [1 if channel in right_keys else 0 for channel in channels] + right_eye_data, _, _ = data.by_channel_map(right_eye_channel_map) + right_eye_x = right_eye_data[0] + right_eye_y = right_eye_data[1] + eye_data = (left_eye_x, left_eye_y, right_eye_x, right_eye_y) + + # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis + lx = np.clip(left_eye_x, 0, 1) + ly = np.clip(left_eye_y, 0, 1) + rx = np.clip(right_eye_x, 0, 1) + ry = np.clip(right_eye_y, 0, 1) + ly = 1 - ly + ry = 1 - ry + + # remove nan values + lx = lx[~np.isnan(lx)] + ly = ly[~np.isnan(ly)] + rx = rx[~np.isnan(rx)] + ry = ry[~np.isnan(ry)] + + # scale the eye data to the image + fig, ax = plt.subplots() + ax.imshow(img, extent=[0, 1, 0, 1]) + + if heatmap: + # create a dataframe making a column for each x, y pair for both eyes and a column for the eye (left or right) + df = pd.DataFrame({ + 'x': np.concatenate((lx, rx)), + 'y': np.concatenate((ly, ry)), + 'eye': ['left'] * len(lx) + ['right'] * len(rx) + }) + ax = sns.kdeplot( + data=df, + hue='eye', + x='x', + y='y', + fill=False, + thresh=0.05, + levels=10, + cmap="mako", + colorbar=True) + + if raw_plot: + ax.scatter(lx, ly, c='r', s=1) + ax.scatter(rx, ry, c='b', s=1) + + plt.title(f'{title}Plot') + + if save_path is not None: + plt.savefig(f"{save_path}/{title.lower().replace(' ', '_')}plot.png", dpi=fig.dpi) + + if show: + plt.show() + + return fig + + def plot_edf(edf_path: str, auto_scale: Optional[bool] = False): """Plot data from the raw edf file. Note: this works from an iPython session but seems to throw errors when provided in a script. @@ -197,6 +298,8 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi filter_order = parameters.get("filter_order") static_offset = parameters.get("static_trigger_offset") + # TODO check for existence of these files and throw error if not found + # TODO check for other data types (tobii) raw_data = load_raw_data(Path(session_path, f'{RAW_DATA_FILENAME}.csv')) channels = raw_data.channels sample_rate = raw_data.sample_rate @@ -226,7 +329,7 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] channel_map = analysis_channels(channels, device_spec) - return visualize_erp( + erp = visualize_erp( raw_data, channel_map, trigger_timing, @@ -238,3 +341,5 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi save_path=session_path, show=show, ) + + eye_data = visualize_eye_data diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 37312dbeb..a79bbccc5 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -16,7 +16,7 @@ from bcipy.helpers.stimuli import play_sound, update_inquiry_timing from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.helpers.visualization import visualize_erp +from bcipy.helpers.visualization import visualize_erp, visualize_gaze from bcipy.signal.model.base_model import SignalModel from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import filter_inquiries, get_default_transform @@ -234,6 +234,12 @@ def offline_analysis( ) if device_spec.content_type == "Eyetracker": print(device_spec) + figure_handles = visualize_gaze( + mode_data, + save_path=data_folder if save_figures else None, + show=show_figures, + raw_plot=True, + ) breakpoint() pass diff --git a/bcipy/static/images/main/matrix_grid.png b/bcipy/static/images/main/matrix.png similarity index 100% rename from bcipy/static/images/main/matrix_grid.png rename to bcipy/static/images/main/matrix.png diff --git a/requirements.txt b/requirements.txt index 6502c030b..14aeebfad 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,7 +13,7 @@ sounddevice==0.4.1 SoundFile==0.12.1 scipy==1.10.1 scikit-learn==1.2.2 -seaborn==0.9.0 +seaborn==0.12.2 matplotlib==3.4.2 pylsl==1.14.0 pandas==1.5.3 diff --git a/scripts/python/plot_eye_data.py b/scripts/python/plot_eye_data.py index 0fd04515f..5a1ef2c64 100644 --- a/scripts/python/plot_eye_data.py +++ b/scripts/python/plot_eye_data.py @@ -1,31 +1,18 @@ from bcipy.helpers.raw_data import load -from bcipy.config import STATIC_IMAGES_PATH DIPSIZE = (1707, 1067) -IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' -# IMG_PATH = f'{STATIC_IMAGES_PATH}/rsvp.png' TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' def load_eye_tracking_data(path): data = load(f'{path}/{TOBII_FILENAME}') - - left_eye_channel_map = [0,0,1,1,0,0,0,0,0] - left_eye_data, _, _ = data.by_channel_map(left_eye_channel_map) - left_eye_x = left_eye_data[0] - left_eye_y = left_eye_data[1] - - right_eye_channel_map = [0,0,0,0,0,1,1,0,0] - right_eye_data, _, _ = data.by_channel_map(right_eye_channel_map) - right_eye_x = right_eye_data[0] - right_eye_y = right_eye_data[1] - return left_eye_x, left_eye_y, right_eye_x, right_eye_y - + return data if __name__ == "__main__": import argparse from pathlib import Path from bcipy.helpers.load import load_experimental_data + from bcipy.helpers.visualization import visualize_gaze import matplotlib.pyplot as plt from matplotlib import image import numpy as np @@ -46,47 +33,6 @@ def load_eye_tracking_data(path): path = load_experimental_data() data = load_eye_tracking_data(path) - lx, ly, rx, ry = data - - dpi = 100 - - # load the image - img = plt.imread(IMG_PATH) - # img = np.flipud(img) - - w, h = len(img[0]), len(img) - - # resize the image to fit the display - # img = np.resize(img, (DIPSIZE[1], DIPSIZE[0], 4)) - fig, ax = plt.subplots() - ax.imshow(img, extent=[0, 1, 0, 1]) - # ax.scatter(lx, ly, c='r', s=1) - # ax.scatter(rx, ry, c='b', s=1) - # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis - lx = np.clip(lx, 0, 1) - ly = np.clip(ly, 0, 1) - rx = np.clip(rx, 0, 1) - ry = np.clip(ry, 0, 1) - ly = 1 - ly - ry = 1 - ry - - # plot the eye data - # ax.plot(lx, ly, c='r', linewidth=1) - # ax.plot(rx, ry, c='b', linewidth=1) - - # remove nan values - lx = lx[~np.isnan(lx)] - ly = ly[~np.isnan(ly)] - rx = rx[~np.isnan(rx)] - ry = ry[~np.isnan(ry)] - - # determine kde of the eye data - ax = sns.kdeplot(lx, ly, cmap="mako", fill=False, thresh=0.05, levels=10, colorbar=True) - - - ax.scatter(lx, ly, c='r', s=1) - ax.scatter(rx, ry, c='b', s=1) - - plt.show() - breakpoint() \ No newline at end of file + # Plot the eye data + visualize_gaze(data, show=True, save_path=path, heatmap=True, raw_plot=False) From 13dfdb9f0902e1f90a5aa5a2b91e7d0d84e1e7f6 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 23 May 2023 15:48:01 -0700 Subject: [PATCH 024/330] Add some documentation --- scripts/python/plot_eye_data.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/scripts/python/plot_eye_data.py b/scripts/python/plot_eye_data.py index 5a1ef2c64..a51f3cbe9 100644 --- a/scripts/python/plot_eye_data.py +++ b/scripts/python/plot_eye_data.py @@ -34,5 +34,5 @@ def load_eye_tracking_data(path): data = load_eye_tracking_data(path) - # Plot the eye data - visualize_gaze(data, show=True, save_path=path, heatmap=True, raw_plot=False) + # Plot the eye data, set save_path to None to not save the plot. You can have both plots at the same time. + visualize_gaze(data, show=True, save_path=path, heatmap=False, raw_plot=True) From 987a701e5aba8576b156ab30e145a0f7196aea7f Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 6 Jun 2023 14:37:40 -0700 Subject: [PATCH 025/330] Stubbed out changes to model loading --- bcipy/helpers/load.py | 17 ++++++++--------- bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 13 ++++++++----- bcipy/task/control/evidence.py | 4 +--- 3 files changed, 17 insertions(+), 17 deletions(-) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 44306739e..a59e7d383 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -6,20 +6,15 @@ from time import localtime, strftime from typing import Any, Dict, List, Tuple -from bcipy.config import ( - ROOT, - DEFAULT_ENCODING, - DEFAULT_EXPERIMENT_PATH, - DEFAULT_PARAMETERS_PATH, - DEFAULT_FIELD_PATH, - EXPERIMENT_FILENAME, - FIELD_FILENAME) +from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_PATH, + DEFAULT_FIELD_PATH, DEFAULT_PARAMETERS_PATH, + EXPERIMENT_FILENAME, FIELD_FILENAME, ROOT) from bcipy.gui.file_dialog import ask_directory, ask_filename -from bcipy.preferences import preferences from bcipy.helpers.exceptions import (BciPyCoreException, InvalidExperimentException) from bcipy.helpers.parameters import Parameters from bcipy.helpers.raw_data import RawData +from bcipy.preferences import preferences from bcipy.signal.model import SignalModel log = logging.getLogger(__name__) @@ -192,6 +187,10 @@ def load_signal_model(model_class: SignalModel, return signal_model, filename +def load_signal_models(directory: str = None) -> List[SignalModel]: + """Load all signal models in a given directory""" + # TODO: + def choose_csv_file(filename: str = None) -> str: """GUI prompt to select a csv file from the file system. diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index b92d6a3c7..5c7c4a10f 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -3,20 +3,23 @@ from typing import List import numpy as np + +from bcipy.helpers.exceptions import SignalException +from bcipy.helpers.stimuli import InquiryReshaper from bcipy.signal.model import ModelEvaluationReport, SignalModel from bcipy.signal.model.classifier import RegularizedDiscriminantAnalysis -from bcipy.signal.model.cross_validation import cost_cross_validation_auc, cross_validation +from bcipy.signal.model.cross_validation import (cost_cross_validation_auc, + cross_validation) from bcipy.signal.model.density_estimation import KernelDensityEstimate -from bcipy.signal.model.dimensionality_reduction import ChannelWisePrincipalComponentAnalysis +from bcipy.signal.model.dimensionality_reduction import \ + ChannelWisePrincipalComponentAnalysis from bcipy.signal.model.pipeline import Pipeline -from bcipy.helpers.exceptions import SignalException -from bcipy.helpers.stimuli import InquiryReshaper class PcaRdaKdeModel(SignalModel): reshaper = InquiryReshaper() - def __init__(self, k_folds: int, prior_type="uniform", pca_n_components=0.9): + def __init__(self, k_folds: int = 10, prior_type="uniform", pca_n_components=0.9): self.k_folds = k_folds self.prior_type = prior_type self.pca_n_components = pca_n_components diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py index 2a61a721f..52f3e4b88 100644 --- a/bcipy/task/control/evidence.py +++ b/bcipy/task/control/evidence.py @@ -23,11 +23,10 @@ def consumes(self) -> ContentType: def produces(self) -> EvidenceType: """Type of evidence that is output""" - def evaluate(self, *args, **kwargs): + def evaluate(self, **kwargs): """Evaluate the evidence""" -# TODO: can this go in the signal module? class FilterParams(NamedTuple): """Parameters used to filter signal data""" notch_filter_frequency: int = 60 @@ -95,7 +94,6 @@ def evaluate(self, raw_data: np.array, symbols: List[str], return self.signal_model.predict(reshaped_data, symbols, self.symbol_set) - def get_evaluator(data_source: ContentType, evidence_type: EvidenceType) -> EvidenceEvaluator: """Returns the matching evaluator. From 411f610b09c3341103ff21a3343339b6ebb51637 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 7 Jun 2023 11:52:20 -0700 Subject: [PATCH 026/330] Save and loading behavior for SignalModels to make it easier to load multiple models from a single directory --- bcipy/config.py | 1 + bcipy/helpers/load.py | 32 ++++++++++++++++--- bcipy/helpers/save.py | 20 +++++++++++- bcipy/signal/model/offline_analysis.py | 31 +++++++++--------- bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 15 +++++---- .../model/pca_rda_kde/test_pca_rda_kde.py | 15 +++++++-- 6 files changed, 84 insertions(+), 30 deletions(-) diff --git a/bcipy/config.py b/bcipy/config.py index bc9015b8a..f07ffff47 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -30,6 +30,7 @@ BCIPY_LOGO_PATH = f'{STATIC_IMAGES_PATH}/gui/cambi.png' PREFERENCES_PATH = f'{ROOT}/.bcipy/bcipy_cache' LM_PATH = f'{BCIPY_ROOT}/language/lms' +SIGNAL_MODEL_FILE_SUFFIX = '.pkl' # core data configuration RAW_DATA_FILENAME = 'raw_data' diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index a59e7d383..825208995 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -1,14 +1,16 @@ import json import logging import os +import pickle from pathlib import Path from shutil import copyfile from time import localtime, strftime -from typing import Any, Dict, List, Tuple +from typing import Any, Dict, List, Optional, Tuple from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_PATH, DEFAULT_FIELD_PATH, DEFAULT_PARAMETERS_PATH, - EXPERIMENT_FILENAME, FIELD_FILENAME, ROOT) + EXPERIMENT_FILENAME, FIELD_FILENAME, ROOT, + SIGNAL_MODEL_FILE_SUFFIX) from bcipy.gui.file_dialog import ask_directory, ask_filename from bcipy.helpers.exceptions import (BciPyCoreException, InvalidExperimentException) @@ -187,9 +189,29 @@ def load_signal_model(model_class: SignalModel, return signal_model, filename -def load_signal_models(directory: str = None) -> List[SignalModel]: - """Load all signal models in a given directory""" - # TODO: +def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: + """Load all signal models in a given directory. + + Models should be serialized as pickled files. Note that reading pickled + files is a potential security concern so only load from trusted + directories. + + Args: + dirname (str, optional): Location of pretrained models. If not + provided the user will be prompted for a location. + """ + if not directory or Path(directory).is_file(): + directory = ask_directory() + + # update preferences + path = Path(directory) + preferences.signal_model_directory = str(path) + + models = [] + for file_path in path.glob(f"*{SIGNAL_MODEL_FILE_SUFFIX}"): + with open(file_path, "rb") as file: + models.append(pickle.load(file)) + return models def choose_csv_file(filename: str = None) -> str: diff --git a/bcipy/helpers/save.py b/bcipy/helpers/save.py index a77bad09b..c6f3c0423 100644 --- a/bcipy/helpers/save.py +++ b/bcipy/helpers/save.py @@ -1,6 +1,7 @@ import errno import json import os +import pickle from pathlib import Path from shutil import copyfile from time import localtime, strftime @@ -10,8 +11,9 @@ from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_ID, DEFAULT_LM_PARAMETERS_FILENAME, DEFAULT_LM_PARAMETERS_PATH, - DEFAULT_PARAMETER_FILENAME) + DEFAULT_PARAMETER_FILENAME, SIGNAL_MODEL_FILE_SUFFIX) from bcipy.helpers.validate import validate_experiments +from bcipy.signal.model.base_model import SignalModel def save_json_data(data: Any, location: str, name: str) -> str: @@ -149,3 +151,19 @@ def _save_session_related_data(file, session_dictionary): # Use the file to dump data to json.dump(session_dictionary, file, indent=2) return file + +def save_model(model: SignalModel, path: Path): + """Save model weights (e.g. after training) to `path` + + Parameters + ---------- + model - SignalModel to serialize + path - path to the file which will be created. If the path does not + have the SIGNAL_MODEL_FILE_SUFFIX then that will be appended. + """ + path = path.with_suffix(SIGNAL_MODEL_FILE_SUFFIX) + with open(path, "wb") as file: + # Protocol 4 is the default in Python 3.8, but supported as low as 3.4. + # It supports very large objects and some data format optimizations + # making it appropriate for signal models. + pickle.dump(model, file, protocol=4) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index f7d957622..946d2cd00 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -2,30 +2,28 @@ from pathlib import Path from typing import Tuple -from bcipy.config import (DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, - RAW_DATA_FILENAME, STATIC_AUDIO_PATH, - DEFAULT_DEVICE_SPEC_FILENAME) -from bcipy.preferences import preferences +import numpy as np +from matplotlib.figure import Figure +from sklearn.metrics import balanced_accuracy_score +from sklearn.model_selection import train_test_split + +import bcipy.acquisition.devices as devices +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETERS_PATH, RAW_DATA_FILENAME, + STATIC_AUDIO_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels -from bcipy.helpers.load import ( - load_experimental_data, - load_json_parameters, - load_raw_data, -) +from bcipy.helpers.load import (load_experimental_data, load_json_parameters, + load_raw_data) +from bcipy.helpers.save import save_model from bcipy.helpers.stimuli import play_sound, update_inquiry_timing from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import visualize_erp +from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import filter_inquiries, get_default_transform -import numpy as np -from matplotlib.figure import Figure -from sklearn.metrics import balanced_accuracy_score -from sklearn.model_selection import train_test_split -import bcipy.acquisition.devices as devices - log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") @@ -182,7 +180,8 @@ def offline_analysis( model.fit(data, labels) log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") - model.save(data_folder + f"/model_{model.auc:0.4f}.pkl") + # model.save(data_folder + f"/model_{model.auc:0.4f}.pkl") + save_model(model, data_folder + f"/model_{model.auc:0.4f}.pkl") preferences.signal_model_directory = data_folder # Using an 80/20 split, report on balanced accuracy diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index 5c7c4a10f..75541ae6a 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -29,7 +29,11 @@ def __init__(self, k_folds: int = 10, prior_type="uniform", pca_n_components=0.9 self.max = 1e2 self.model = None self.auc = None - self._ready_to_predict = False + + @property + def ready_to_predict(self) -> bool: + """Returns True if a model has been trained""" + return bool(self.model) def fit(self, train_data: np.array, train_labels: np.array) -> SignalModel: """ @@ -81,7 +85,6 @@ def fit(self, train_data: np.array, train_labels: np.array) -> SignalModel: else: raise ValueError("prior_type must be 'empirical' or 'uniform'") - self._ready_to_predict = True return self def evaluate(self, test_data: np.array, test_labels: np.array) -> ModelEvaluationReport: @@ -97,7 +100,7 @@ def evaluate(self, test_data: np.array, test_labels: np.array) -> ModelEvaluatio Returns: ModelEvaluationReport: stores AUC """ - if not self._ready_to_predict: + if not self.ready_to_predict: raise SignalException("must use model.fit() before model.evaluate()") tmp_model = Pipeline([self.model.pipeline[0], self.model.pipeline[1]]) @@ -129,7 +132,7 @@ def predict(self, data: np.array, inquiry: List[str], symbol_set: List[str]) -> np.array: multiplicative update term (likelihood ratios) for each symbol in the `symbol_set`. """ - if not self._ready_to_predict: + if not self.ready_to_predict: raise SignalException("must use model.fit() before model.predict()") # Evaluate likelihood probabilities for p(e|l=1) and p(e|l=0) @@ -151,7 +154,7 @@ def predict_proba(self, data: np.array) -> np.array: posterior (np.ndarray): shape (num_items, 2) - for each item, the model's predicted probability for the two labels. """ - if not self._ready_to_predict: + if not self.ready_to_predict: raise SignalException("must use model.fit() before model.predict_proba()") # Model originally produces p(eeg | label). We want p(label | eeg): @@ -177,4 +180,4 @@ def load(self, path: Path): """Load pretrained model weights from `path`""" with open(path, "rb") as f: self.model = pickle.load(f) - self._ready_to_predict = True + diff --git a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py index 4ed65a0ff..a80503764 100644 --- a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py +++ b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py @@ -8,14 +8,15 @@ import pytest from scipy.stats import norm +from bcipy.helpers.exceptions import SignalException from bcipy.helpers.symbols import alphabet from bcipy.signal.model import ModelEvaluationReport, PcaRdaKdeModel from bcipy.signal.model.classifier import RegularizedDiscriminantAnalysis from bcipy.signal.model.cross_validation import cross_validation from bcipy.signal.model.density_estimation import KernelDensityEstimate -from bcipy.signal.model.dimensionality_reduction import ChannelWisePrincipalComponentAnalysis +from bcipy.signal.model.dimensionality_reduction import \ + ChannelWisePrincipalComponentAnalysis from bcipy.signal.model.pipeline import Pipeline -from bcipy.helpers.exceptions import SignalException expected_output_folder = Path(__file__).absolute().parent.parent / "unit_test_expected_output" @@ -235,6 +236,11 @@ def test_save_load(self): self.assertTrue(np.allclose(output_before, output_after)) + try: + other_model.predict_proba(self.x) + except Exception: + pytest.fail("Should be able to compute predict_proba after loading a model") + def test_predict_before_fit(self): model = PcaRdaKdeModel(k_folds=10) with self.assertRaises(SignalException): @@ -245,6 +251,11 @@ def test_evaluate_before_fit(self): with self.assertRaises(SignalException): model.evaluate(self.x, self.y) + def test_predict_proba_before_fit(self): + model = PcaRdaKdeModel(k_folds=10) + with self.assertRaises(SignalException): + model.predict_proba(self.x) + if __name__ == "__main__": unittest.main() From 97c31f70462cc6a77dccf568c70946d01d960ea7 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 7 Jun 2023 15:53:34 -0700 Subject: [PATCH 027/330] Updated bci_main to load multiple signal models from a directory; better documentation --- bcipy/helpers/load.py | 5 +++-- bcipy/helpers/save.py | 6 +++--- bcipy/main.py | 17 ++++++++-------- bcipy/signal/model/offline_analysis.py | 3 +-- .../model/pca_rda_kde/test_pca_rda_kde.py | 11 +++++++--- bcipy/tests/test_bci_main.py | 20 ++++++------------- 6 files changed, 29 insertions(+), 33 deletions(-) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 825208995..adda32f1b 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -192,8 +192,9 @@ def load_signal_model(model_class: SignalModel, def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: """Load all signal models in a given directory. - Models should be serialized as pickled files. Note that reading pickled - files is a potential security concern so only load from trusted + Models are assumed to have been written using bcipy.helpers.save.save_model + function and should be serialized as pickled files. Note that reading + pickled files is a potential security concern so only load from trusted directories. Args: diff --git a/bcipy/helpers/save.py b/bcipy/helpers/save.py index c6f3c0423..d5e075d9c 100644 --- a/bcipy/helpers/save.py +++ b/bcipy/helpers/save.py @@ -5,7 +5,7 @@ from pathlib import Path from shutil import copyfile from time import localtime, strftime -from typing import Any, List +from typing import Any, List, Union from bcipy.acquisition.devices import DeviceSpec from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_ID, @@ -152,7 +152,7 @@ def _save_session_related_data(file, session_dictionary): json.dump(session_dictionary, file, indent=2) return file -def save_model(model: SignalModel, path: Path): +def save_model(model: SignalModel, path: Union[Path, str]): """Save model weights (e.g. after training) to `path` Parameters @@ -161,7 +161,7 @@ def save_model(model: SignalModel, path: Path): path - path to the file which will be created. If the path does not have the SIGNAL_MODEL_FILE_SUFFIX then that will be appended. """ - path = path.with_suffix(SIGNAL_MODEL_FILE_SUFFIX) + path = Path(path).with_suffix(SIGNAL_MODEL_FILE_SUFFIX) with open(path, "wb") as file: # Protocol 4 is the default in Python 3.8, but supported as low as 3.4. # It supports very large objects and some data format optimizations diff --git a/bcipy/main.py b/bcipy/main.py index 9f8445875..2c2b4d1e9 100644 --- a/bcipy/main.py +++ b/bcipy/main.py @@ -12,7 +12,7 @@ from bcipy.helpers.acquisition import init_eeg_acquisition from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import (load_experiments, load_json_parameters, - load_signal_model) + load_signal_models) from bcipy.helpers.save import init_save_data_structure from bcipy.helpers.session import collect_experiment_field_data from bcipy.helpers.stimuli import play_sound @@ -20,7 +20,6 @@ from bcipy.helpers.task import print_message from bcipy.helpers.validate import validate_bcipy_session, validate_experiment from bcipy.helpers.visualization import visualize_session_data -from bcipy.signal.model import PcaRdaKdeModel from bcipy.task import TaskType from bcipy.task.start_task import start_task @@ -136,13 +135,13 @@ def execute_task( # Try loading in our signal_model and starting a langmodel(if enabled) if not fake: try: - signal_model, _filename = load_signal_model( - model_class=PcaRdaKdeModel, - model_kwargs={'k_folds': parameters['k_folds']}, - filename=parameters['signal_model_path']) - except Exception as e: - log.exception(f'Cannot load signal model. Exiting. {e}') - raise e + model_dir = parameters['signal_model_path'] + signal_models = load_signal_models(directory=model_dir) + assert signal_models, f"No signal models found in {model_dir}" + signal_model = signal_models[0] + except Exception as error: + log.exception(f'Cannot load signal model. Exiting. {error}') + raise error language_model = init_language_model(parameters) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 946d2cd00..124e0eb3d 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -180,8 +180,7 @@ def offline_analysis( model.fit(data, labels) log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") - # model.save(data_folder + f"/model_{model.auc:0.4f}.pkl") - save_model(model, data_folder + f"/model_{model.auc:0.4f}.pkl") + save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) preferences.signal_model_directory = data_folder # Using an 80/20 split, report on balanced accuracy diff --git a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py index a80503764..e4238d2b7 100644 --- a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py +++ b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py @@ -9,6 +9,8 @@ from scipy.stats import norm from bcipy.helpers.exceptions import SignalException +from bcipy.helpers.load import load_signal_models +from bcipy.helpers.save import save_model from bcipy.helpers.symbols import alphabet from bcipy.signal.model import ModelEvaluationReport, PcaRdaKdeModel from bcipy.signal.model.classifier import RegularizedDiscriminantAnalysis @@ -229,9 +231,12 @@ def test_save_load(self): output_before = self.model.predict(data=data, inquiry=inquiry, symbol_set=symbol_set) checkpoint_path = self.tmp_dir / "model.pkl" - self.model.save(checkpoint_path) - other_model = PcaRdaKdeModel(k_folds=self.model.k_folds) - other_model.load(checkpoint_path) + save_model(self.model, checkpoint_path) + + loaded_models = load_signal_models(self.tmp_dir) + self.assertEqual(1, len(loaded_models)) + other_model = loaded_models[0] + self.assertEqual(self.model.k_folds, other_model.k_folds) output_after = other_model.predict(data=data, inquiry=inquiry, symbol_set=symbol_set) self.assertTrue(np.allclose(output_before, output_after)) diff --git a/bcipy/tests/test_bci_main.py b/bcipy/tests/test_bci_main.py index bfc47cbf8..82a98bc56 100644 --- a/bcipy/tests/test_bci_main.py +++ b/bcipy/tests/test_bci_main.py @@ -413,7 +413,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: signal_model = mock() language_model = mock() file_name = 'test' - load_model_response = (signal_model, file_name) + load_model_response = [signal_model] eeg_response = (self.daq, self.server) when(main).init_eeg_acquisition( self.parameters, @@ -421,9 +421,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: server=self.fake).thenReturn(eeg_response) when(main).init_display_window(self.parameters).thenReturn(self.display_mock) when(main).print_message(self.display_mock, any()) - when(main).load_signal_model(model_class=any(), model_kwargs={ - 'k_folds': self.parameters['k_folds'] - }, filename=model_path).thenReturn(load_model_response) + when(main).load_signal_models(directory=model_path).thenReturn(load_model_response) when(main).init_language_model(self.parameters).thenReturn(language_model) when(main).start_task( self.display_mock, @@ -455,9 +453,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: signal_model=signal_model, fake=self.fake, ) - verify(main, times=1).load_signal_model(model_class=any(), model_kwargs={ - 'k_folds': self.parameters['k_folds'] - }, filename=model_path) + verify(main, times=1).load_signal_models(directory=model_path) verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) def test_execute_language_model_enabled(self) -> None: @@ -468,7 +464,7 @@ def test_execute_language_model_enabled(self) -> None: signal_model = mock() file_name = 'test' language_model = mock() - load_model_response = (signal_model, file_name) + load_model_response = [signal_model] # mock the behavior of execute task eeg_response = (self.daq, self.server) @@ -479,9 +475,7 @@ def test_execute_language_model_enabled(self) -> None: when(main).init_language_model(self.parameters).thenReturn(language_model) when(main).init_display_window(self.parameters).thenReturn(self.display_mock) when(main).print_message(self.display_mock, any()) - when(main).load_signal_model(model_class=any(), model_kwargs={ - 'k_folds': self.parameters['k_folds'] - }, filename='').thenReturn(load_model_response) + when(main).load_signal_models(directory='').thenReturn(load_model_response) when(main).start_task( self.display_mock, self.daq, @@ -512,9 +506,7 @@ def test_execute_language_model_enabled(self) -> None: signal_model=signal_model, fake=self.fake, ) - verify(main, times=1).load_signal_model(model_class=any(), model_kwargs={ - 'k_folds': self.parameters['k_folds'] - }, filename='') + verify(main, times=1).load_signal_models(directory='') verify(main, times=1).init_language_model(self.parameters) verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) From 0549b0fa82e76693e017b0c6140c6d30f49b179b Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 7 Jun 2023 16:05:53 -0700 Subject: [PATCH 028/330] Fixed unit test --- bcipy/task/tests/core/test_eeg_evaluator.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/task/tests/core/test_eeg_evaluator.py b/bcipy/task/tests/core/test_eeg_evaluator.py index 2a80bdc1e..311f8d730 100644 --- a/bcipy/task/tests/core/test_eeg_evaluator.py +++ b/bcipy/task/tests/core/test_eeg_evaluator.py @@ -85,8 +85,8 @@ def test_evaluate(self, reshaper_factory_mock, transform_factory_mock, channel_map=channel_map, poststimulus_length=window_length) - self.signal_model_mock.assert_called_once_with(reshaped_data, symbols, - self.symbol_set) + self.signal_model_mock.predict.assert_called_once_with( + reshaped_data, symbols, self.symbol_set) if __name__ == '__main__': From 2a41e2571fefe41d747b8ec19f1b4262262b0cf2 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 12 Jun 2023 13:34:12 -0700 Subject: [PATCH 029/330] Refactor to pass multiple models in to tasks --- bcipy/main.py | 5 ++--- bcipy/task/paradigm/matrix/copy_phrase.py | 7 +++---- bcipy/task/paradigm/rsvp/copy_phrase.py | 7 +++---- bcipy/task/start_task.py | 12 ++++++------ 4 files changed, 14 insertions(+), 17 deletions(-) diff --git a/bcipy/main.py b/bcipy/main.py index 2c2b4d1e9..37e6df437 100644 --- a/bcipy/main.py +++ b/bcipy/main.py @@ -126,7 +126,7 @@ def execute_task( Returns: (bool): True if the task was successfully executed, False otherwise """ - signal_model = None + signal_models = [] language_model = None # Init EEG Model, if needed. Calibration Tasks Don't require probabilistic @@ -138,7 +138,6 @@ def execute_task( model_dir = parameters['signal_model_path'] signal_models = load_signal_models(directory=model_dir) assert signal_models, f"No signal models found in {model_dir}" - signal_model = signal_models[0] except Exception as error: log.exception(f'Cannot load signal model. Exiting. {error}') raise error @@ -163,7 +162,7 @@ def execute_task( parameters, save_folder, language_model=language_model, - signal_model=signal_model, + signal_models=signal_models, fake=fake) # If exception, close all display and acquisition objects diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index 44a96a593..53e9e9ecc 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -1,9 +1,9 @@ """Defines the Copy Phrase Task which uses a Matrix display""" -from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask from bcipy.display import Display, InformationProperties, StimuliProperties -from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.paradigm.matrix.display import MatrixDisplay +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask class MatrixCopyPhraseTask(RSVPCopyPhraseTask): @@ -23,8 +23,7 @@ class MatrixCopyPhraseTask(RSVPCopyPhraseTask): configuration details regarding the experiment. See parameters.json file_save : str, path location of where to save data from the session - signal_model : loaded pickle file, - trained signal model. + signal_models : list of trained signal models. language_model: object, trained language model. fake : boolean, optional diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 4f97569ad..a435a6954 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -65,8 +65,7 @@ class RSVPCopyPhraseTask(Task): configuration details regarding the experiment. See parameters.json file_save : str, path location of where to save data from the session - signal_model : loaded pickle file, - trained signal model. + signal_models : list of trained signal models. language_model: object, trained language model. fake : boolean, optional @@ -96,7 +95,7 @@ class RSVPCopyPhraseTask(Task): 'info_pos_x', 'info_pos_y', 'info_color', 'info_height', 'info_text', 'info_color', 'info_height', 'info_text', ] - def __init__(self, win, daq, parameters, file_save, signal_model, + def __init__(self, win, daq, parameters, file_save, signal_models, language_model, fake): super(RSVPCopyPhraseTask, self).__init__() @@ -126,7 +125,7 @@ def __init__(self, win, daq, parameters, file_save, signal_model, self.fake = fake self.language_model = language_model - self.signal_model = signal_model + self.signal_model = signal_models[0] if signal_models else None self.evidence_precision = 5 self.feedback = VisualFeedback( diff --git a/bcipy/task/start_task.py b/bcipy/task/start_task.py index 57949d8c8..264ca2a20 100644 --- a/bcipy/task/start_task.py +++ b/bcipy/task/start_task.py @@ -14,7 +14,7 @@ def make_task(display_window, daq, task, parameters, file_save, - signal_model=None, language_model=None, fake=True) -> Task: + signal_models=None, language_model=None, fake=True) -> Task: """Creates a Task based on the provided parameters. Parameters: @@ -24,7 +24,7 @@ def make_task(display_window, daq, task, parameters, file_save, task: TaskType parameters: dict file_save: str - path to file in which to save data - signal_model + signal_models - list of trained models language_model - language model fake: boolean - true if eeg stream is randomly generated Returns: @@ -39,7 +39,7 @@ def make_task(display_window, daq, task, parameters, file_save, if task is TaskType.RSVP_COPY_PHRASE: return RSVPCopyPhraseTask( - display_window, daq, parameters, file_save, signal_model, + display_window, daq, parameters, file_save, signal_models, language_model, fake=fake) if task is TaskType.RSVP_TIMING_VERIFICATION_CALIBRATION: @@ -55,15 +55,15 @@ def make_task(display_window, daq, task, parameters, file_save, if task is TaskType.MATRIX_COPY_PHRASE: return MatrixCopyPhraseTask( - display_window, daq, parameters, file_save, signal_model, + display_window, daq, parameters, file_save, signal_models, language_model, fake=fake) raise TaskRegistryException( 'The provided experiment type is not registered.') def start_task(display_window, daq, task, parameters, file_save, - signal_model=None, language_model=None, fake=True): + signal_models=None, language_model=None, fake=True): """Creates a Task and starts execution.""" task = make_task(display_window, daq, task, parameters, file_save, - signal_model, language_model, fake) + signal_models, language_model, fake) task.execute() From b4a10ee66b1258604a010779fb37d20b81fadac5 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 12 Jun 2023 13:36:40 -0700 Subject: [PATCH 030/330] Factored parameters for the default_transform into a NamedTuple that can be extracted from the provided Parameters. Added metadata to SignalModels that can be used to match to an EvidenceEvaluator as well as encapsulate the filter parameters and device used to train the model. --- bcipy/signal/model/base_model.py | 27 +++- bcipy/signal/model/offline_analysis.py | 32 ++--- bcipy/signal/process/__init__.py | 7 +- bcipy/signal/process/transform.py | 21 ++- bcipy/task/control/evidence.py | 182 ++++++++++++++++++------- 5 files changed, 202 insertions(+), 67 deletions(-) diff --git a/bcipy/signal/model/base_model.py b/bcipy/signal/model/base_model.py index 26c9c9974..8a854f72b 100644 --- a/bcipy/signal/model/base_model.py +++ b/bcipy/signal/model/base_model.py @@ -1,11 +1,36 @@ from abc import ABC, abstractmethod from pathlib import Path -from typing import List +from typing import List, NamedTuple + import numpy as np + +from bcipy.acquisition.devices import DeviceSpec from bcipy.helpers.stimuli import Reshaper +from bcipy.signal.process import Composition + + +class SignalModelMetadata(NamedTuple): + """Metadata about the SignalModel, including how the model was trained + (device, filters, etc).""" + + device_spec: DeviceSpec # device used to train the model + transform: Composition # data preprocessing steps + evidence_type: str = None # optional; type of evidence produced class SignalModel(ABC): + + @property + def metadata(self) -> SignalModelMetadata: + """Information regarding the data and parameters used to train the + model.""" + return self._metadata + + @metadata.setter + def metadata(self, value): + """Set the metadata""" + self._metadata = value + @property @abstractmethod def reshaper(self) -> Reshaper: diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 124e0eb3d..19a8ca3e5 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -14,15 +14,17 @@ from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) +from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import save_model from bcipy.helpers.stimuli import play_sound, update_inquiry_timing from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import visualize_erp from bcipy.preferences import preferences -from bcipy.signal.model.base_model import SignalModel +from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel -from bcipy.signal.process import filter_inquiries, get_default_transform +from bcipy.signal.process import (TransformParams, filter_inquiries, + get_default_transform) log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") @@ -56,7 +58,7 @@ def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_s @report_execution_time def offline_analysis( data_folder: str = None, - parameters: dict = {}, + parameters: Parameters = None, alert_finished: bool = True, estimate_balanced_acc: bool = False, show_figures: bool = False, @@ -86,7 +88,7 @@ def offline_analysis( - generates and [optional] saves/shows the ERP figure - [optional] alert the user finished processing """ - + assert parameters, "Parameters are required" if not data_folder: data_folder = load_experimental_data() @@ -100,17 +102,13 @@ def offline_analysis( raw_data_file = f"{RAW_DATA_FILENAME}.csv" # get signal filtering information - downsample_rate = parameters.get("down_sampling_rate") - notch_filter = parameters.get("notch_filter_frequency") - filter_high = parameters.get("filter_high") - filter_low = parameters.get("filter_low") - filter_order = parameters.get("filter_order") + transform_params = parameters.instantiate(TransformParams) + downsample_rate = transform_params.down_sampling_rate static_offset = parameters.get("static_trigger_offset") log.info( f"\nData processing settings: \n" - f"Filter: [{filter_low}-{filter_high}], Order: {filter_order}," - f" Notch: {notch_filter}, Downsample: {downsample_rate} \n" + f"{str(transform_params)} \n" f"Poststimulus: {poststim_length}s, Prestimulus: {prestim_length}s, Buffer: {buffer}s \n" f"Static offset: {static_offset}" ) @@ -127,11 +125,11 @@ def offline_analysis( # setup filtering default_transform = get_default_transform( sample_rate_hz=sample_rate, - notch_freq_hz=notch_filter, - bandpass_low=filter_low, - bandpass_high=filter_high, - bandpass_order=filter_order, - downsample_factor=downsample_rate, + notch_freq_hz=transform_params.notch_filter, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, ) log.info(f"Channels read from csv: {channels}") @@ -178,6 +176,8 @@ def offline_analysis( log.info("Training model. This will take some time...") model = PcaRdaKdeModel(k_folds=k_folds) model.fit(data, labels) + model.metadata = SignalModelMetadata(device_spec=device_spec, + transform=default_transform) log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) diff --git a/bcipy/signal/process/__init__.py b/bcipy/signal/process/__init__.py index cc75033f5..689ae620f 100644 --- a/bcipy/signal/process/__init__.py +++ b/bcipy/signal/process/__init__.py @@ -1,9 +1,12 @@ -from bcipy.signal.process.transform import get_default_transform, Downsample, Composition from bcipy.signal.process.filter import filter_inquiries +from bcipy.signal.process.transform import (Composition, Downsample, + TransformParams, + get_default_transform) __all__ = [ "filter_inquiries", "get_default_transform", "Downsample", - "Composition" + "Composition", + "TransformParams" ] diff --git a/bcipy/signal/process/transform.py b/bcipy/signal/process/transform.py index 734eff358..853164a8f 100644 --- a/bcipy/signal/process/transform.py +++ b/bcipy/signal/process/transform.py @@ -1,7 +1,8 @@ -from typing import Optional, Tuple +from typing import NamedTuple, Optional, Tuple import numpy as np -from bcipy.signal.process.filter import Notch, Bandpass + +from bcipy.signal.process.filter import Bandpass, Notch class Composition: @@ -28,6 +29,22 @@ def __call__(self, data: np.ndarray, fs: Optional[int] = None) -> Tuple[np.ndarr else: return data[:, :: self.factor], None +class TransformParams(NamedTuple): + """Parameters used for the default transform.""" + notch_filter_frequency: int = 60 + filter_low: int = 2 + filter_high: int = 45 + filter_order: int = 2 + down_sampling_rate: int = 2 + + def __str__(self): + return ', '.join([ + f"Filter: [{self.filter_low}-{self.filter_high}]" + f"Order: {self.filter_order}", + f"Notch: {self.notch_filter_frequency}", + f"Downsample: {self.down_sampling_rate}" + ]) + def get_default_transform( sample_rate_hz: int, diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py index 52f3e4b88..ba098390d 100644 --- a/bcipy/task/control/evidence.py +++ b/bcipy/task/control/evidence.py @@ -1,5 +1,6 @@ """Classes and functions for extracting evidence from raw device data.""" -from typing import List, NamedTuple +import logging +from typing import List, Optional import numpy as np @@ -7,13 +8,32 @@ from bcipy.helpers.acquisition import DeviceSpec, analysis_channels from bcipy.helpers.stimuli import TrialReshaper from bcipy.signal.model import SignalModel -from bcipy.signal.process import get_default_transform +from bcipy.signal.process import TransformParams, get_default_transform from bcipy.task.data import EvidenceType from bcipy.task.exceptions import MissingEvidenceEvaluator +log = logging.getLogger(__name__) + class EvidenceEvaluator: - """Base class""" + """Base class + + Parameters + ---------- + symbol_set: set of possible symbols presented + signal_model: model trained using a calibration session of the same user. + device_spec: Specification for the device providing data. + """ + + def __init__(self, symbol_set: List[str], signal_model: SignalModel): + assert signal_model.metadata, "Metadata missing from signal model." + device_spec = signal_model.metadata.device_spec + assert ContentType( + signal_model.metadata.device_spec.content_type + ) == self.consumes, "evaluator is not compatible with the given model" + self.symbol_set = symbol_set + self.signal_model = signal_model + self.device_spec = device_spec @property def consumes(self) -> ContentType: @@ -27,31 +47,53 @@ def evaluate(self, **kwargs): """Evaluate the evidence""" -class FilterParams(NamedTuple): - """Parameters used to filter signal data""" - notch_filter_frequency: int = 60 - filter_low: int = 2 - filter_high: int = 45 - filter_order: int = 2 - downsample_rate: int = 2 - - class EegEvaluator(EvidenceEvaluator): - """Extracts symbol likelihoods from raw EEG data""" + """Extracts symbol likelihoods from raw EEG data + + Parameters + ---------- + symbol_set: set of possible symbols presented + signal_model: model trained using a calibration session of the same user. + device_spec: Specification for the device providing data. + filter_params: configuration for the data transfor; values here should + match the values used when training the model. + """ consumes = ContentType.EEG produces = EvidenceType.ERP - def __init__(self, symbol_set: List[str], signal_model: SignalModel, - device_spec: DeviceSpec, filter_params: FilterParams): - assert ContentType( - device_spec.content_type - ) == self.consumes, "evaluator is not compatible with the given device" - self.symbol_set = symbol_set - self.signal_model = signal_model - self.filter_params = filter_params + def __init__(self, symbol_set: List[str], signal_model: SignalModel): + super().__init__(symbol_set, signal_model) - self.sample_rate = device_spec.sample_rate - self.channel_map = analysis_channels(device_spec.channels, device_spec) + self.channel_map = analysis_channels(self.device_spec.channels, + self.device_spec) + self.transform = signal_model.metadata.transform + self.reshape = TrialReshaper() + + def preprocess(self, raw_data: np.array, times: List[float], + target_info: List[str], window_length: float) -> np.ndarray: + """Preprocess the inquiry data. + + Parameters + ---------- + raw_data - C x L eeg data where C is number of channels and L is the + signal length + symbols - symbols displayed in the inquiry + times - timestamps associated with each symbol + target_info - target information about the stimuli; + ex. ['nontarget', 'nontarget', ...] + window_length - The length of the time between stimuli presentation + """ + transformed_data, transform_sample_rate = self.transform( + raw_data, self.device_spec.sample_rate) + + # The data from DAQ is assumed to have offsets applied + reshaped_data, _lbls = self.reshape(trial_targetness_label=target_info, + timing_info=times, + eeg_data=transformed_data, + sample_rate=transform_sample_rate, + channel_map=self.channel_map, + poststimulus_length=window_length) + return reshaped_data # pylint: disable=arguments-differ def evaluate(self, raw_data: np.array, symbols: List[str], @@ -69,33 +111,63 @@ def evaluate(self, raw_data: np.array, symbols: List[str], ex. ['nontarget', 'nontarget', ...] window_length - The length of the time between stimuli presentation """ + data = self.preprocess(raw_data, times, target_info, window_length) + return self.signal_model.predict(data, symbols, self.symbol_set) + + +class EegPreprocessor: + """Preprocesses EEG data for model prediction""" + content_type = ContentType.EEG + + def __init__(self, device_spec: DeviceSpec, + filter_params: TransformParams): + assert ContentType( + device_spec.content_type + ) == self.content_type, "processor is not compatible with device" + + self.device_spec = device_spec + self.channel_map = analysis_channels(device_spec.channels, device_spec) - transform = get_default_transform( - sample_rate_hz=self.sample_rate, - notch_freq_hz=self.filter_params.notch_filter_frequency, - bandpass_low=self.filter_params.filter_low, - bandpass_high=self.filter_params.filter_high, - bandpass_order=self.filter_params.filter_order, - downsample_factor=self.filter_params.downsample_rate, + self.transform = get_default_transform( + sample_rate_hz=device_spec.sample_rate, + notch_freq_hz=filter_params.notch_filter_frequency, + bandpass_low=filter_params.filter_low, + bandpass_high=filter_params.filter_high, + bandpass_order=filter_params.filter_order, + downsample_factor=filter_params.down_sampling_rate, ) - transformed_data, transform_sample_rate = transform( - raw_data, self.sample_rate) + self.reshape = TrialReshaper() + + def preprocess(self, raw_data: np.array, times: List[float], + target_info: List[str], window_length: float) -> np.ndarray: + """Preprocess the inquiry data. + + Parameters + ---------- + raw_data - C x L eeg data where C is number of channels and L is the + signal length + times - timestamps associated with each symbol in the inquiry + target_info - target information about the stimuli; + ex. ['nontarget', 'nontarget', ...] + window_length - The length of the time between stimuli presentation + """ + transformed_data, transform_sample_rate = self.transform( + raw_data, self.device_spec.sample_rate) # The data from DAQ is assumed to have offsets applied - reshape = TrialReshaper() - reshaped_data, _lbls = reshape(trial_targetness_label=target_info, - timing_info=times, - eeg_data=transformed_data, - sample_rate=transform_sample_rate, - channel_map=self.channel_map, - poststimulus_length=window_length) - - return self.signal_model.predict(reshaped_data, symbols, - self.symbol_set) - -def get_evaluator(data_source: ContentType, - evidence_type: EvidenceType) -> EvidenceEvaluator: + reshaped_data, _lbls = self.reshape(trial_targetness_label=target_info, + timing_info=times, + eeg_data=transformed_data, + sample_rate=transform_sample_rate, + channel_map=self.channel_map, + poststimulus_length=window_length) + return reshaped_data + + +def get_evaluator( + data_source: ContentType, + evidence_type: Optional[EvidenceType] = None) -> EvidenceEvaluator: """Returns the matching evaluator. Parameters @@ -105,7 +177,8 @@ def get_evaluator(data_source: ContentType, """ matches = [ cls for cls in EvidenceEvaluator.__subclasses__() - if cls.consumes == data_source and cls.produces == evidence_type + if cls.consumes == data_source and ( + evidence_type is None or cls.produces == evidence_type) ] if matches: return matches[0] @@ -113,3 +186,20 @@ def get_evaluator(data_source: ContentType, raise MissingEvidenceEvaluator( f"Evidence Evaluator not found for {data_source.name} -> {evidence_type.name}" ) + + +def find_matching_evaluator(signal_model: SignalModel) -> EvidenceEvaluator: + """Find the first EvidenceEvaluator compatible with the given signal + model.""" + content_type = ContentType(signal_model.metadata.device_spec.content_type) + # Metadata may provide an EvidenceType with a model so the same data source can + # be used to produce multiple types of evidence (ex. alpha) + evidence_type = None + model_output = signal_model.metadata.evidence_type + if model_output: + try: + evidence_type = EvidenceType(model_output.upper()) + except ValueError: + log.error(f"Unsupported evidence type: {model_output}") + + return get_evaluator(content_type, evidence_type) From a8a4ff6041c45b38939d90654644678f225395e1 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 12 Jun 2023 13:37:04 -0700 Subject: [PATCH 031/330] Added tests for EvidenceType --- bcipy/task/tests/core/test_data.py | 20 +++++++++++++++++++- 1 file changed, 19 insertions(+), 1 deletion(-) diff --git a/bcipy/task/tests/core/test_data.py b/bcipy/task/tests/core/test_data.py index b3db246cb..2b85006e2 100644 --- a/bcipy/task/tests/core/test_data.py +++ b/bcipy/task/tests/core/test_data.py @@ -1,7 +1,8 @@ """Tests for session-related functionality.""" import unittest -from bcipy.task.data import Session, Inquiry, EvidenceType + +from bcipy.task.data import EvidenceType, Inquiry, Session def sample_stim_seq(include_evidence: bool = False): @@ -62,6 +63,23 @@ def sample_stim_seq(include_evidence: bool = False): return stim_seq +class TestEvidenceType(unittest.TestCase): + """Tests for EvidenceType enum""" + + def test_str(self): + """Test string representation""" + self.assertEqual('BTN', str(EvidenceType.BTN)) + + def test_serialization(self): + """Test serialization / deserialization""" + + self.assertEqual( + EvidenceType.ERP, + EvidenceType.deserialized(EvidenceType.ERP.serialized)) + self.assertEqual(EvidenceType.LM, + EvidenceType.deserialized(EvidenceType.LM.serialized)) + + class TestSessionData(unittest.TestCase): """Tests for session data.""" From 236332f3ef72aa5fa40a70eb4f74f01a7cd559b1 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 12 Jun 2023 14:13:41 -0700 Subject: [PATCH 032/330] Cleanup and tests for task evidence module --- bcipy/task/control/evidence.py | 69 +++------------------ bcipy/task/tests/core/test_eeg_evaluator.py | 36 +++++------ bcipy/task/tests/core/test_evidence.py | 67 ++++++++++++++++++++ 3 files changed, 89 insertions(+), 83 deletions(-) create mode 100644 bcipy/task/tests/core/test_evidence.py diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py index ba098390d..ef6b767d1 100644 --- a/bcipy/task/control/evidence.py +++ b/bcipy/task/control/evidence.py @@ -5,10 +5,9 @@ import numpy as np from bcipy.acquisition.multimodal import ContentType -from bcipy.helpers.acquisition import DeviceSpec, analysis_channels +from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.stimuli import TrialReshaper from bcipy.signal.model import SignalModel -from bcipy.signal.process import TransformParams, get_default_transform from bcipy.task.data import EvidenceType from bcipy.task.exceptions import MissingEvidenceEvaluator @@ -48,15 +47,12 @@ def evaluate(self, **kwargs): class EegEvaluator(EvidenceEvaluator): - """Extracts symbol likelihoods from raw EEG data + """Extracts symbol likelihoods from raw EEG data. Parameters ---------- symbol_set: set of possible symbols presented - signal_model: model trained using a calibration session of the same user. - device_spec: Specification for the device providing data. - filter_params: configuration for the data transfor; values here should - match the values used when training the model. + signal_model: trained signal model """ consumes = ContentType.EEG produces = EvidenceType.ERP @@ -115,60 +111,10 @@ def evaluate(self, raw_data: np.array, symbols: List[str], return self.signal_model.predict(data, symbols, self.symbol_set) -class EegPreprocessor: - """Preprocesses EEG data for model prediction""" - content_type = ContentType.EEG - - def __init__(self, device_spec: DeviceSpec, - filter_params: TransformParams): - assert ContentType( - device_spec.content_type - ) == self.content_type, "processor is not compatible with device" - - self.device_spec = device_spec - self.channel_map = analysis_channels(device_spec.channels, device_spec) - - self.transform = get_default_transform( - sample_rate_hz=device_spec.sample_rate, - notch_freq_hz=filter_params.notch_filter_frequency, - bandpass_low=filter_params.filter_low, - bandpass_high=filter_params.filter_high, - bandpass_order=filter_params.filter_order, - downsample_factor=filter_params.down_sampling_rate, - ) - - self.reshape = TrialReshaper() - - def preprocess(self, raw_data: np.array, times: List[float], - target_info: List[str], window_length: float) -> np.ndarray: - """Preprocess the inquiry data. - - Parameters - ---------- - raw_data - C x L eeg data where C is number of channels and L is the - signal length - times - timestamps associated with each symbol in the inquiry - target_info - target information about the stimuli; - ex. ['nontarget', 'nontarget', ...] - window_length - The length of the time between stimuli presentation - """ - transformed_data, transform_sample_rate = self.transform( - raw_data, self.device_spec.sample_rate) - - # The data from DAQ is assumed to have offsets applied - reshaped_data, _lbls = self.reshape(trial_targetness_label=target_info, - timing_info=times, - eeg_data=transformed_data, - sample_rate=transform_sample_rate, - channel_map=self.channel_map, - poststimulus_length=window_length) - return reshaped_data - - def get_evaluator( data_source: ContentType, evidence_type: Optional[EvidenceType] = None) -> EvidenceEvaluator: - """Returns the matching evaluator. + """Returns the matching evaluator class. Parameters ---------- @@ -183,9 +129,10 @@ def get_evaluator( if matches: return matches[0] else: - raise MissingEvidenceEvaluator( - f"Evidence Evaluator not found for {data_source.name} -> {evidence_type.name}" - ) + msg = f"Evidence Evaluator not found for {data_source.name}" + if evidence_type: + msg += f" -> {evidence_type.name}" + raise MissingEvidenceEvaluator(msg) def find_matching_evaluator(signal_model: SignalModel) -> EvidenceEvaluator: diff --git a/bcipy/task/tests/core/test_eeg_evaluator.py b/bcipy/task/tests/core/test_eeg_evaluator.py index 311f8d730..0d6e721d9 100644 --- a/bcipy/task/tests/core/test_eeg_evaluator.py +++ b/bcipy/task/tests/core/test_eeg_evaluator.py @@ -3,7 +3,7 @@ import unittest from unittest.mock import Mock, patch -from bcipy.task.control.evidence import EegEvaluator, FilterParams +from bcipy.task.control.evidence import EegEvaluator class TestEegEvaluator(unittest.TestCase): @@ -18,22 +18,23 @@ def setUp(self): self.device_mock.channels = ['ch1', 'ch2', 'ch3'] self.device_mock.sample_rate = 300 - self.filter_params = FilterParams() + self.transform_mock = Mock() self.signal_model_mock = Mock() + meta_mock = Mock() + meta_mock.device_spec = self.device_mock + meta_mock.transform = self.transform_mock + self.signal_model_mock.metadata = meta_mock @patch('bcipy.task.control.evidence.analysis_channels') def test_init(self, analysis_channels_mock): """Test initialization""" - EegEvaluator(self.symbol_set, self.signal_model_mock, self.device_mock, - self.filter_params) + EegEvaluator(self.symbol_set, self.signal_model_mock) analysis_channels_mock.assert_called_with(self.device_mock.channels, self.device_mock) @patch('bcipy.task.control.evidence.analysis_channels') - @patch('bcipy.task.control.evidence.get_default_transform') @patch('bcipy.task.control.evidence.TrialReshaper') - def test_evaluate(self, reshaper_factory_mock, transform_factory_mock, - analysis_channels_mock): + def test_evaluate(self, reshaper_factory_mock, analysis_channels_mock): """Test evaluation of evidence""" # Mocks @@ -42,9 +43,8 @@ def test_evaluate(self, reshaper_factory_mock, transform_factory_mock, analysis_channels_mock.return_value = channel_map transformed_data = Mock() - transformer_mock = Mock() - transform_factory_mock.return_value = transformer_mock - transformer_mock.return_value = (transformed_data, 150) + + self.transform_mock.return_value = (transformed_data, 150) reshaper_mock = Mock() reshaper_factory_mock.return_value = reshaper_mock @@ -60,22 +60,14 @@ def test_evaluate(self, reshaper_factory_mock, transform_factory_mock, window_length = 0.5 # Run the code - evaluator = EegEvaluator(self.symbol_set, self.signal_model_mock, - self.device_mock, self.filter_params) + evaluator = EegEvaluator(self.symbol_set, self.signal_model_mock) evaluator.evaluate(raw_data, symbols, times, target_info, window_length) # Assertions - transform_factory_mock.assert_called_once_with( - sample_rate_hz=self.device_mock.sample_rate, - notch_freq_hz=self.filter_params.notch_filter_frequency, - bandpass_low=self.filter_params.filter_low, - bandpass_high=self.filter_params.filter_high, - bandpass_order=self.filter_params.filter_order, - downsample_factor=self.filter_params.downsample_rate) - - transformer_mock.assert_called_once_with(raw_data, - self.device_mock.sample_rate) + + self.transform_mock.assert_called_once_with( + raw_data, self.device_mock.sample_rate) reshaper_mock.assert_called_once_with( trial_targetness_label=target_info, diff --git a/bcipy/task/tests/core/test_evidence.py b/bcipy/task/tests/core/test_evidence.py new file mode 100644 index 000000000..4b556edaf --- /dev/null +++ b/bcipy/task/tests/core/test_evidence.py @@ -0,0 +1,67 @@ +"""Tests for functions in the evidence module.""" + +import unittest +from unittest.mock import Mock + +from bcipy.acquisition.multimodal import ContentType +from bcipy.task.control.evidence import (EegEvaluator, find_matching_evaluator, + get_evaluator) +from bcipy.task.data import EvidenceType +from bcipy.task.exceptions import MissingEvidenceEvaluator + + +class TestEvidence(unittest.TestCase): + """Test evidence functions""" + + def test_get_evaluator(self): + """Test getting an evaluator""" + self.assertEqual(EegEvaluator, get_evaluator(ContentType.EEG)) + self.assertEqual(EegEvaluator, + get_evaluator(ContentType.EEG, EvidenceType.ERP)) + + def test_missing_evaluator(self): + """Test error condition when evaluator is missing""" + with self.assertRaises(MissingEvidenceEvaluator): + get_evaluator(ContentType.MARKERS) + + with self.assertRaises(MissingEvidenceEvaluator): + get_evaluator(ContentType.EEG, EvidenceType.EYE) + + def test_find_matching_evaluator(self): + """Test finding an evaluator for a given SignalModel""" + device_mock = Mock() + device_mock.content_type = 'EEG' + signal_model_mock = Mock() + meta_mock = Mock() + meta_mock.device_spec = device_mock + signal_model_mock.metadata = meta_mock + + self.assertEqual(EegEvaluator, + find_matching_evaluator(signal_model_mock)) + + def test_match_with_bad_evidence_type(self): + """Test matching an evaulator when EvidenceType is not found""" + device_mock = Mock() + device_mock.content_type = 'EEG' + signal_model_mock = Mock() + meta_mock = Mock() + meta_mock.device_spec = device_mock + meta_mock.evidence_type = 'NOT_AN_EVIDENCE_TYPE' + signal_model_mock.metadata = meta_mock + + self.assertEqual(EegEvaluator, + find_matching_evaluator(signal_model_mock), + "should ignore the evidence type") + + def test_match_should_use_evidence(self): + """Test matching an evaluator should use the evidence if provided.""" + device_mock = Mock() + device_mock.content_type = 'EEG' + signal_model_mock = Mock() + meta_mock = Mock() + meta_mock.device_spec = device_mock + meta_mock.evidence_type = 'EYE' + signal_model_mock.metadata = meta_mock + + with self.assertRaises(MissingEvidenceEvaluator): + find_matching_evaluator(signal_model_mock) From e04876a4b34ae1e23cabd448e5916565192fa74a Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Jun 2023 15:44:53 -0700 Subject: [PATCH 033/330] Updated session module to handle eyetracker evidence type. Initial work on multimodal Copy Phrase task using EvidenceEvaluators. Fix unit tests and general cleanup --- bcipy/acquisition/multimodal.py | 12 +- bcipy/helpers/load.py | 1 + bcipy/helpers/parameters.py | 2 - bcipy/helpers/save.py | 1 + bcipy/helpers/session.py | 20 +- .../tests/resources/mock_session/session.csv | 394 +++++++++--------- bcipy/helpers/tests/test_parameters.py | 1 + bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 1 - bcipy/signal/process/transform.py | 1 + bcipy/task/control/evidence.py | 23 +- bcipy/task/exceptions.py | 8 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 94 ++++- bcipy/task/tests/core/test_data.py | 13 +- .../tests/paradigm/rsvp/test_copy_phrase.py | 95 +++-- bcipy/tests/test_bci_main.py | 20 +- 15 files changed, 413 insertions(+), 273 deletions(-) diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 844cf2db0..2f19be645 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -76,6 +76,12 @@ def device_specs(self) -> List[DeviceSpec]: """Returns a list of DeviceSpecs for all the clients.""" return [client.device_spec for client in self.clients] + @property + def device_content_types(self) -> List[ContentType]: + """Returns a list of ContentTypes provided by the configured devices. + """ + return self._clients.keys() + @property def default_client(self) -> Optional[LslAcquisitionClient]: """Returns the default client.""" @@ -125,10 +131,12 @@ def get_data_by_device( log.debug( f'Need {count} records for processing {content_type.name} data' ) - output[content_type] = client.get_data(start=start, limit=count) + output[content_type] = client.get_data(start=start, + limit=count) else: # Markers have an IRREGULAR_RATE. - output[content_type] = client.get_data(start=start, end=start+seconds) + output[content_type] = client.get_data(start=start, + end=start + seconds) return output def cleanup(self): diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index adda32f1b..bb5536cf2 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -189,6 +189,7 @@ def load_signal_model(model_class: SignalModel, return signal_model, filename + def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: """Load all signal models in a given directory. diff --git a/bcipy/helpers/parameters.py b/bcipy/helpers/parameters.py index 3dbce6e2b..9a95ebacf 100644 --- a/bcipy/helpers/parameters.py +++ b/bcipy/helpers/parameters.py @@ -317,8 +317,6 @@ def instantiate(self, named_tuple_class: type) -> NamedTuple: return named_tuple_class(*vals) - - def changes_from_default(source: str) -> Dict[str, ParameterChange]: """Determines which parameters have changed from the default params. diff --git a/bcipy/helpers/save.py b/bcipy/helpers/save.py index d5e075d9c..e471466a9 100644 --- a/bcipy/helpers/save.py +++ b/bcipy/helpers/save.py @@ -152,6 +152,7 @@ def _save_session_related_data(file, session_dictionary): json.dump(session_dictionary, file, indent=2) return file + def save_model(model: SignalModel, path: Union[Path, str]): """Save model weights (e.g. after training) to `path` diff --git a/bcipy/helpers/session.py b/bcipy/helpers/session.py index 6354f090b..bc7932ba2 100644 --- a/bcipy/helpers/session.py +++ b/bcipy/helpers/session.py @@ -14,14 +14,9 @@ from openpyxl.styles.borders import BORDER_THIN, Border, Side from openpyxl.styles.colors import BLACK, WHITE, YELLOW -from bcipy.config import ( - BCIPY_ROOT, - DEFAULT_ENCODING, - DEFAULT_PARAMETER_FILENAME, - EXPERIMENT_DATA_FILENAME, - SESSION_DATA_FILENAME, - SESSION_SUMMARY_FILENAME, -) +from bcipy.config import (BCIPY_ROOT, DEFAULT_ENCODING, + DEFAULT_PARAMETER_FILENAME, EXPERIMENT_DATA_FILENAME, + SESSION_DATA_FILENAME, SESSION_SUMMARY_FILENAME) from bcipy.helpers.load import (load_experiment_fields, load_experiments, load_json_parameters) from bcipy.helpers.validate import validate_field_data_written @@ -71,6 +66,7 @@ class EvidenceRecord: stim: str lm: float eeg: float + eye: float btn: float cumulative: float inq_position: int @@ -121,6 +117,7 @@ def evidence_records(session: Session) -> List[EvidenceRecord]: stim=stim, lm=evidence['lm_evidence'].get(stim, ''), eeg=evidence['eeg_evidence'].get(stim, ''), + eye=evidence.get('eye_evidence', {}).get(stim, ''), btn=evidence.get('btn_evidence', {}).get(stim, ''), cumulative=evidence['likelihood'][stim], inq_position=stimuli.index(stim) if stim in stimuli else None, @@ -150,6 +147,8 @@ def session_db(session: Session, db_file: str = 'session.db'): first inquiry) - eeg real (likelihood for the given inquiry; a value of 1.0 indicates that the letter was not presented) + - btn real (button press evidence) + - eye real (eyetracker evidence) - cumulative real (cumulative likelihood for the trial thus far) - inq_position integer (inquiry position; null if not presented) - is_target integer (boolean; true(1) if this letter is the target) @@ -288,8 +287,9 @@ def session_excel(session: Session, chart.add_data(data, titles_from_data=False) chart.series[0].title = openpyxl.chart.series.SeriesLabel(v="lm") chart.series[1].title = openpyxl.chart.series.SeriesLabel(v="eeg") - chart.series[2].title = openpyxl.chart.series.SeriesLabel(v="btn") - chart.series[3].title = openpyxl.chart.series.SeriesLabel( + chart.series[2].title = openpyxl.chart.series.SeriesLabel(v="eye") + chart.series[3].title = openpyxl.chart.series.SeriesLabel(v="btn") + chart.series[4].title = openpyxl.chart.series.SeriesLabel( v="combined") chart.set_categories(categories) diff --git a/bcipy/helpers/tests/resources/mock_session/session.csv b/bcipy/helpers/tests/resources/mock_session/session.csv index cb3b07777..f023a39ac 100644 --- a/bcipy/helpers/tests/resources/mock_session/session.csv +++ b/bcipy/helpers/tests/resources/mock_session/session.csv @@ -1,197 +1,197 @@ -series,inquiry,stim,lm,eeg,btn,cumulative,inq_position,is_target,presented,above_threshold -1,0,A,0.03518518518518518,1.0771572587661082,,0.03806880657023323,5,0,1,0 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+2,2,Y,0.03518518518518518,1.0,,,0.03630255003185779,,0,0,0 +2,2,Z,0.03518518518518518,1.0,,,0.03630255003185779,,0,0,0 +2,2,<,0.05,1.0479584201231897,,,0.05017771776702011,7,0,1,0 +2,2,_,0.03518518518518518,1.0,,,0.03630255003185779,,0,0,0 diff --git a/bcipy/helpers/tests/test_parameters.py b/bcipy/helpers/tests/test_parameters.py index 8f430af88..c46b20088 100644 --- a/bcipy/helpers/tests/test_parameters.py +++ b/bcipy/helpers/tests/test_parameters.py @@ -614,5 +614,6 @@ def test_instantiate_tuple(self): self.assertEqual(my_tuple.c, '3') self.assertEqual((1, '3'), my_tuple) + if __name__ == '__main__': unittest.main() diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index 75541ae6a..4910107c1 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -180,4 +180,3 @@ def load(self, path: Path): """Load pretrained model weights from `path`""" with open(path, "rb") as f: self.model = pickle.load(f) - diff --git a/bcipy/signal/process/transform.py b/bcipy/signal/process/transform.py index 853164a8f..63886264e 100644 --- a/bcipy/signal/process/transform.py +++ b/bcipy/signal/process/transform.py @@ -29,6 +29,7 @@ def __call__(self, data: np.ndarray, fs: Optional[int] = None) -> Tuple[np.ndarr else: return data[:, :: self.factor], None + class TransformParams(NamedTuple): """Parameters used for the default transform.""" notch_filter_frequency: int = 60 diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py index ef6b767d1..d1b98b322 100644 --- a/bcipy/task/control/evidence.py +++ b/bcipy/task/control/evidence.py @@ -1,6 +1,6 @@ """Classes and functions for extracting evidence from raw device data.""" import logging -from typing import List, Optional +from typing import List, Optional, Type import numpy as np @@ -15,13 +15,14 @@ class EvidenceEvaluator: - """Base class + """Base class for a class that can evaluate raw device data using a + signal_model. EvidenceEvaluators are responsible for performing necessary + preprocessing steps such as filtering and reshaping. Parameters ---------- symbol_set: set of possible symbols presented signal_model: model trained using a calibration session of the same user. - device_spec: Specification for the device providing data. """ def __init__(self, symbol_set: List[str], signal_model: SignalModel): @@ -47,7 +48,7 @@ def evaluate(self, **kwargs): class EegEvaluator(EvidenceEvaluator): - """Extracts symbol likelihoods from raw EEG data. + """EvidenceEvaluator that extracts symbol likelihoods from raw EEG data. Parameters ---------- @@ -113,7 +114,8 @@ def evaluate(self, raw_data: np.array, symbols: List[str], def get_evaluator( data_source: ContentType, - evidence_type: Optional[EvidenceType] = None) -> EvidenceEvaluator: + evidence_type: Optional[EvidenceType] = None +) -> Type[EvidenceEvaluator]: """Returns the matching evaluator class. Parameters @@ -135,7 +137,8 @@ def get_evaluator( raise MissingEvidenceEvaluator(msg) -def find_matching_evaluator(signal_model: SignalModel) -> EvidenceEvaluator: +def find_matching_evaluator( + signal_model: SignalModel) -> Type[EvidenceEvaluator]: """Find the first EvidenceEvaluator compatible with the given signal model.""" content_type = ContentType(signal_model.metadata.device_spec.content_type) @@ -150,3 +153,11 @@ def find_matching_evaluator(signal_model: SignalModel) -> EvidenceEvaluator: log.error(f"Unsupported evidence type: {model_output}") return get_evaluator(content_type, evidence_type) + + +def init_evidence_evaluator(symbol_set: List[str], + signal_model: SignalModel) -> EvidenceEvaluator: + """Find an EvidenceEvaluator that matches the given signal_model and + initialize it.""" + evaluator_class = find_matching_evaluator(signal_model) + return evaluator_class(symbol_set, signal_model) diff --git a/bcipy/task/exceptions.py b/bcipy/task/exceptions.py index ecf52d73d..3a686c874 100644 --- a/bcipy/task/exceptions.py +++ b/bcipy/task/exceptions.py @@ -20,6 +20,12 @@ def __init__(self, message, errors=None): super().__init__(message) self.errors = errors + class MissingEvidenceEvaluator(Exception): """Thrown when an evidence evaluator can't be found that matches the - provided data content type input and evidence_type output""" \ No newline at end of file + provided data content type input and evidence_type output""" + + +class DuplicateModelEvidence(Exception): + """Thrown from a task when more than one of the provided models produces + the same type of evidence""" diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index a435a6954..2360c340b 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -26,7 +26,10 @@ TriggerType, convert_timing_triggers) from bcipy.signal.model.inquiry_preview import compute_probs_after_preview from bcipy.task import Task +from bcipy.task.control.evidence import (EvidenceEvaluator, + init_evidence_evaluator) from bcipy.task.data import EvidenceType, Inquiry, Session +from bcipy.task.exceptions import DuplicateModelEvidence class Decision(NamedTuple): @@ -98,7 +101,7 @@ class RSVPCopyPhraseTask(Task): def __init__(self, win, daq, parameters, file_save, signal_models, language_model, fake): super(RSVPCopyPhraseTask, self).__init__() - + self.logger = logging.getLogger(__name__) self.window = win self.daq = daq self.parameters = parameters @@ -113,7 +116,12 @@ def __init__(self, win, daq, parameters, file_save, signal_models, self.alp = alphabet(self.parameters) self.button_press_error_prob = 0.05 - self.evidence_types = [EvidenceType.LM, EvidenceType.ERP] + + self.evidence_evaluators = self.init_evidence_evaluators(signal_models) + + self.evidence_types = [EvidenceType.LM] + self.evidence_types.extend( + [evaluator.produces for evaluator in self.evidence_evaluators]) if self.parameters['show_preview_inquiry']: self.evidence_types.append(EvidenceType.BTN) @@ -125,6 +133,7 @@ def __init__(self, win, daq, parameters, file_save, signal_models, self.fake = fake self.language_model = language_model + # TODO: remove this self.signal_model = signal_models[0] if signal_models else None self.evidence_precision = 5 @@ -155,6 +164,32 @@ def __init__(self, win, daq, parameters, file_save, signal_models, self.rsvp = self.init_display() + def init_evidence_evaluators(self, + signal_models) -> List[EvidenceEvaluator]: + """Initializes the evidence evaluators from the provided signal models. + + Returns a list of evaluators for active devices. Raises an exception if + more than one evaluator provides the same type of evidence. + """ + evidence_types = [] + evaluators = [] + for model in signal_models: + evaluator = init_evidence_evaluator(self.alp, model) + content_type = evaluator.consumes + evidence_type = evaluator.produces + if content_type in self.daq.device_content_types: + evaluators.append(evaluator) + if evidence_type in evidence_types: + raise DuplicateModelEvidence( + f"More than one model produces {evidence_type} evidence" + ) + evidence_types.append(evidence_type) + else: + self.logger.info( + f"SignalModel not used: there is no active device of type: {content_type}" + ) + return evaluators + def setup(self) -> None: """Initialize/reset parameters used in the execute run loop.""" @@ -226,6 +261,7 @@ def init_copy_phrase_task(self) -> None: initialized CopyPhraseWrapper """ + # TODO: remove signal_model self.copy_phrase_task = CopyPhraseWrapper( self.parameters['min_inq_len'], self.parameters['max_inq_per_series'], @@ -480,12 +516,14 @@ def add_evidence(self, stim_times: List[List], -------- - self.copy_phrase_task """ - # TODO: refactor compute_eeg_evidence to compute_device_evidence - # for each daq client evidences = [ - self.compute_button_press_evidence(proceed), - self.compute_eeg_evidence(stim_times, proceed) + self.compute_button_press_evidence(proceed) ] + + for evidence_evaluator in self.evidence_evaluators: + evidences.append( + self.compute_device_evidence(evidence_evaluator, stim_times)) + evidence_types = [] for evidence in evidences: if evidence: @@ -520,6 +558,50 @@ def compute_button_press_evidence( proceed) return (EvidenceType.BTN, probs) + def compute_device_evidence( + self, + evidence_evaluator: EvidenceEvaluator, + stim_times: List[List], + proceed: bool = True + ) -> Optional[Tuple[EvidenceType, List[float]]]: + """Evaluate the evidence using the provided evaluator but + don't yet attempt a decision. + + Parameters + ---------- + - stim_times : list of stimuli returned from the display + - proceed : whether or not to evaluate the evidence, if `False` returns + empty values. + + Returns + ------- + tuple of (evidence type, evidence) + """ + if not proceed or self.fake: + return None + + # currently prestim_length is used as a buffer for filter application, use the same at the end of the inquiry + post_stim_buffer = self.parameters['prestim_length'] + + raw_data, triggers = get_data_for_decision( + inquiry_timing=self.stims_for_decision(stim_times), + daq=self.daq.get_client(evidence_evaluator.consumes), + offset=self.parameters['static_trigger_offset'], + prestim=self.parameters['prestim_length'], + poststim=post_stim_buffer + self.parameters['trial_length']) + + # we assume all are nontargets at this point + labels = ['nontarget'] * len(triggers) + letters, times, filtered_labels = self.copy_phrase_task.letter_info( + triggers, labels) + probs = evidence_evaluator.evaluate( + raw_data=raw_data, + symbols=letters, + times=times, + target_info=filtered_labels, + window_length=self.parameters['trial_length']) + return (evidence_evaluator.produces, probs) + def compute_eeg_evidence(self, stim_times: List[List], proceed: bool = True diff --git a/bcipy/task/tests/core/test_data.py b/bcipy/task/tests/core/test_data.py index 2b85006e2..5b44c7b5a 100644 --- a/bcipy/task/tests/core/test_data.py +++ b/bcipy/task/tests/core/test_data.py @@ -6,6 +6,7 @@ def sample_stim_seq(include_evidence: bool = False): + """Generates a sample Inquiry.""" stim_seq = Inquiry( stimuli=["+", "I", "D", "H", "G", "F", "<", "E", "B", "C", "A"], timing=[0.5, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3], @@ -99,7 +100,7 @@ def test_stim_sequence(self): for key in expected_keys: self.assertTrue(key in serialized) - self.assertEqual(serialized[key], stim_seq.__getattribute__(key)) + self.assertEqual(serialized[key], getattr(stim_seq, key)) for key in ['lm_evidence', 'erp_evidence', 'likelihood']: self.assertFalse(key in serialized) @@ -108,7 +109,7 @@ def test_stim_sequence_deserialization(self): """Test that a stim sequence can be deserialized from a dict.""" stim_seq = sample_stim_seq(include_evidence=True) serialized = stim_seq.as_dict() - self.assertTrue('lm_evidence' in serialized.keys()) + self.assertTrue('lm_evidence' in serialized) self.assertEqual(serialized['lm_evidence'], stim_seq.evidences[EvidenceType.LM]) @@ -209,8 +210,8 @@ def test_session(self): self.assertEqual(1, serialized['total_selections']) self.assertEqual(3, serialized['inquiries_per_selection']) - self.assertTrue('1' in serialized['series'].keys()) - self.assertTrue('2' in serialized['series'].keys()) + self.assertTrue('1' in serialized['series']) + self.assertTrue('2' in serialized['series']) self.assertEqual(2, len(serialized['series']['1'].keys())) self.assertEqual(1, len(serialized['series']['2'].keys())) @@ -272,11 +273,11 @@ def test_session_deserialization(self): def test_task_summary(self): """Test that arbitrary data can be added.""" session = Session(save_location=".") - self.assertFalse('task_summary' in session.as_dict().keys()) + self.assertFalse('task_summary' in session.as_dict()) session.task_summary = {"typing_accuracy": 22} serialized = session.as_dict() - self.assertTrue('task_summary' in serialized.keys()) + self.assertTrue('task_summary' in serialized) self.assertEqual(serialized['task_summary']['typing_accuracy'], 22) def test_has_evidence(self): diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 9c59ad0aa..34d43ad65 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -8,17 +8,18 @@ from mock import patch from mockito import any, mock, unstub, verify, when -from bcipy.config import DEFAULT_ENCODING import bcipy.display.paradigm.rsvp.mode.copy_phrase -from bcipy.helpers.triggers import TriggerHandler -from bcipy.helpers.exceptions import TaskConfigurationException from bcipy.acquisition import LslAcquisitionClient from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.multimodal import ContentType +from bcipy.config import DEFAULT_ENCODING from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper +from bcipy.helpers.exceptions import TaskConfigurationException from bcipy.helpers.parameters import Parameters -from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask -from bcipy.task.data import Session, EvidenceType from bcipy.helpers.stimuli import InquirySchedule +from bcipy.helpers.triggers import TriggerHandler +from bcipy.task.data import EvidenceType, Session +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask class TestCopyPhrase(unittest.TestCase): @@ -88,16 +89,31 @@ def setUp(self): device_spec = DeviceSpec(name='Testing', channels=['a', 'b', 'c'], sample_rate=300.0) - self.daq = mock( + self.eeg_client_mock = mock( { 'device_spec': device_spec, 'is_calibrated': True, - 'offset': lambda x: 0.0 + 'offset': lambda x: 0.0, }, spec=LslAcquisitionClient) - + self.daq = mock( + { + 'device_spec': device_spec, + 'is_calibrated': True, + 'offset': lambda x: 0.0, + 'device_content_types': [ContentType.EEG], + 'clients_by_type': { + ContentType.EEG: self.eeg_client_mock + } + }) + when(self.daq).get_client(ContentType.EEG).thenReturn(self.eeg_client_mock) self.temp_dir = tempfile.mkdtemp() - self.signal_model = mock() + self.model_metadata = mock({ + 'device_spec': device_spec, + 'transform': mock(), + 'evidence_type': 'ERP' + }) + self.signal_model = mock({'metadata': self.model_metadata}) self.language_model = mock() decision_maker = mock() @@ -132,7 +148,7 @@ def test_initialize(self): daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -142,7 +158,7 @@ def test_validate_parameters(self): daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -157,7 +173,7 @@ def test_validate_parameters_throws_task_exception_missing_parameter(self): daq=self.daq, parameters=parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -170,7 +186,7 @@ def test_validate_parameters_throws_task_exception_excess_prestim_length(self): daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -183,7 +199,7 @@ def test_validate_parameters_throws_task_exception_excess_trial_length(self): daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -197,7 +213,7 @@ def test_execute_without_inquiry(self, message_mock, daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -229,7 +245,7 @@ def test_execute_fake_data_single_inquiry(self, process_data_mock, message_mock, daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -268,7 +284,7 @@ def test_max_inq_len(self, process_data_mock, message_mock, daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -309,7 +325,7 @@ def test_spelling_complete(self, process_data_mock, daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -346,7 +362,7 @@ def test_spelled_letters(self): daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -358,7 +374,7 @@ def test_stims_for_eeg(self): daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) timings1 = [['calibration_trigger', 2.0539278959913645], @@ -408,7 +424,7 @@ def test_next_letter(self, process_data_mock, message_mock, daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) task.spelled_text = 'H' @@ -437,7 +453,7 @@ def test_execute_fake_data_with_preview(self, process_data_mock, message_mock, daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=True) @@ -461,12 +477,15 @@ def test_execute_fake_data_with_preview(self, process_data_mock, message_mock, verify(self.copy_phrase_wrapper, times=1).add_evidence(EvidenceType.BTN, ...) self.assertEqual(self.temp_dir, result) + @patch('bcipy.task.paradigm.rsvp.copy_phrase.init_evidence_evaluator') @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_data_for_decision') def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, - user_input_mock): + user_input_mock, init_evaluator_mock): """Test that fake data does not use the decision maker""" + evaluator_mock = mock() + init_evaluator_mock.return_value = evaluator_mock conjugator_mock = mock({ 'latest_evidence': { @@ -536,20 +555,32 @@ def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, 'white', 'white', 'white', 'white', 'white' ]]))) - when(self.display).do_inquiry().thenReturn( - [['calibration_trigger', 2.5866074122022837], - ['+', 4.274230484152213], ['<', 4.741131300106645], - ['G', 4.957655837060884], ['A', 5.1744828461669385], - ['E', 5.391295877052471], ['H', 5.608199302107096], - ['D', 5.8250101080629975], ['F', 6.04189362609759], - ['I', 6.258658453123644], ['B', 6.475744977127761], - ['C', 6.692347120027989]]) + triggers = [['calibration_trigger', 2.5866074122022837], + ['+', 4.274230484152213], ['<', 4.741131300106645], + ['G', 4.957655837060884], ['A', 5.1744828461669385], + ['E', 5.391295877052471], ['H', 5.608199302107096], + ['D', 5.8250101080629975], ['F', 6.04189362609759], + ['I', 6.258658453123644], ['B', 6.475744977127761], + ['C', 6.692347120027989]] + when(self.display).do_inquiry().thenReturn(triggers) + + when(copy_phrase_wrapper_mock).letter_info(any(), any()).thenReturn( + (['<', 'G', 'A', 'E', 'H', 'D', 'F', 'I', 'B', 'C'], [ + 4.741131300106645, 4.957655837060884, 5.1744828461669385, + 5.391295877052471, 5.608199302107096, 5.8250101080629975, + 6.04189362609759, 6.258658453123644, 6.475744977127761, + 6.692347120027989 + ], [ + 'nontarget', 'nontarget', 'nontarget', 'nontarget', + 'nontarget', 'nontarget', 'nontarget', 'nontarget', + 'nontarget', 'nontarget' + ])) task = RSVPCopyPhraseTask(win=self.win, daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_model=self.signal_model, + signal_models=[self.signal_model], language_model=self.language_model, fake=False) diff --git a/bcipy/tests/test_bci_main.py b/bcipy/tests/test_bci_main.py index 82a98bc56..4b51234f0 100644 --- a/bcipy/tests/test_bci_main.py +++ b/bcipy/tests/test_bci_main.py @@ -338,7 +338,7 @@ def test_execute_task_fake_data(self) -> None: self.parameters, self.save_folder, language_model=None, - signal_model=None, + signal_models=[], fake=self.fake, ) when(main)._clean_up_session(self.display_mock, self.daq, self.server) @@ -358,7 +358,7 @@ def test_execute_task_fake_data(self) -> None: self.parameters, self.save_folder, language_model=None, - signal_model=None, + signal_models=[], fake=self.fake, ) verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) @@ -380,7 +380,7 @@ def test_execute_task_real_data(self) -> None: self.parameters, self.save_folder, language_model=None, - signal_model=None, + signal_models=[], fake=self.fake, ) when(main)._clean_up_session(self.display_mock, self.daq, self.server) @@ -400,7 +400,7 @@ def test_execute_task_real_data(self) -> None: self.parameters, self.save_folder, language_model=None, - signal_model=None, + signal_models=[], fake=self.fake, ) verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) @@ -430,7 +430,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: self.parameters, self.save_folder, language_model=language_model, - signal_model=signal_model, + signal_models=[signal_model], fake=self.fake, ) when(main)._clean_up_session(self.display_mock, self.daq, self.server) @@ -450,7 +450,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: self.parameters, self.save_folder, language_model=language_model, - signal_model=signal_model, + signal_models=[signal_model], fake=self.fake, ) verify(main, times=1).load_signal_models(directory=model_path) @@ -483,7 +483,7 @@ def test_execute_language_model_enabled(self) -> None: self.parameters, self.save_folder, language_model=language_model, - signal_model=signal_model, + signal_models=[signal_model], fake=self.fake, ) when(main)._clean_up_session(self.display_mock, self.daq, self.server) @@ -503,7 +503,7 @@ def test_execute_language_model_enabled(self) -> None: self.parameters, self.save_folder, language_model=language_model, - signal_model=signal_model, + signal_models=[signal_model], fake=self.fake, ) verify(main, times=1).load_signal_models(directory='') @@ -527,7 +527,7 @@ def test_execute_with_alert_enabled(self): self.parameters, self.save_folder, language_model=None, - signal_model=None, + signal_models=[], fake=self.fake, ) when(main)._clean_up_session(self.display_mock, self.daq, self.server) @@ -548,7 +548,7 @@ def test_execute_with_alert_enabled(self): self.parameters, self.save_folder, language_model=None, - signal_model=None, + signal_models=[], fake=self.fake, ) verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) From 76959a6a2dac5229e4146623e47a7e7a8f3837ea Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Jun 2023 15:55:38 -0700 Subject: [PATCH 034/330] Bug fix --- bcipy/signal/model/offline_analysis.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 19a8ca3e5..f51f12cb5 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -125,7 +125,7 @@ def offline_analysis( # setup filtering default_transform = get_default_transform( sample_rate_hz=sample_rate, - notch_freq_hz=transform_params.notch_filter, + notch_freq_hz=transform_params.notch_filter_frequency, bandpass_low=transform_params.filter_low, bandpass_high=transform_params.filter_high, bandpass_order=transform_params.filter_order, From a3ee18739fbca3c69ab19c719378e2969cb547ff Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Jun 2023 17:20:48 -0700 Subject: [PATCH 035/330] Removed unused code and parameters from CopyPhraseWrapper --- bcipy/helpers/copy_phrase_wrapper.py | 125 ++---------------- .../helpers/tests/test_copy_phrase_wrapper.py | 115 +--------------- bcipy/task/paradigm/rsvp/copy_phrase.py | 44 ------ 3 files changed, 15 insertions(+), 269 deletions(-) diff --git a/bcipy/helpers/copy_phrase_wrapper.py b/bcipy/helpers/copy_phrase_wrapper.py index 6888fa25c..ec7126be7 100644 --- a/bcipy/helpers/copy_phrase_wrapper.py +++ b/bcipy/helpers/copy_phrase_wrapper.py @@ -1,29 +1,21 @@ """Defines the CopyPhraseWrapper.""" +import logging from typing import List, Tuple -import logging import numpy as np -from bcipy.helpers.acquisition import analysis_channels, DeviceSpec + from bcipy.helpers.exceptions import BciPyCoreException -from bcipy.helpers.language_model import ( - histogram, - with_min_prob, -) -from bcipy.helpers.stimuli import InquirySchedule, StimuliOrder, TrialReshaper +from bcipy.helpers.language_model import histogram, with_min_prob +from bcipy.helpers.stimuli import InquirySchedule, StimuliOrder from bcipy.helpers.symbols import BACKSPACE_CHAR -from bcipy.signal.model import SignalModel -from bcipy.signal.process import get_default_transform +from bcipy.language.main import LanguageModel +from bcipy.task.control.criteria import (CriteriaEvaluator, + MaxIterationsCriteria, + MinIterationsCriteria, + ProbThresholdCriteria) from bcipy.task.control.handler import DecisionMaker, EvidenceFusion from bcipy.task.control.query import NBestStimuliAgent -from bcipy.task.control.criteria import ( - CriteriaEvaluator, - MaxIterationsCriteria, - MinIterationsCriteria, - ProbThresholdCriteria, -) from bcipy.task.data import EvidenceType -from bcipy.language.main import LanguageModel - log = logging.getLogger(__name__) @@ -39,14 +31,11 @@ class CopyPhraseWrapper: - Determining when to stop an inquiry and make a decision (StoppageCriteria). - Generation of inquiries. - Coordination with the Language Model. - - Preparing EEG data for the SignalModel for classification. Parameters ---------- - min_num_inq: The minimum number of inquiries to be displayed - max_num_inq: The maximum number of inquiries to be displayed - - device_spec: Specification for the EEG device used for data collection. - - signal_model: model trained using a calibration session of the same user. - k: down sampling rate - alp: symbol set of the task - evidence_names: list of evidence types used for decision-making @@ -58,10 +47,6 @@ class CopyPhraseWrapper: backspace character. - backspace_always_shown: whether or not the backspace should always be presented. - - filter_high: filter setting used when evaluating EEG data - - filter_low: filter setting used when evaluating EEG data - - filter_order: filter setting used when evaluating EEG data - - notch_filter_frequency: filter setting used when evaluating EEG data - stim_length(int): the number of stimuli to present in each inquiry - stim_timing: seconds each stimuli is displayed; used for inquiry generation @@ -72,23 +57,16 @@ def __init__(self, min_num_inq: int, max_num_inq: int, lmodel: LanguageModel, - device_spec: DeviceSpec, - signal_model: SignalModel = None, - k: int = 2, alp: List[str] = None, evidence_names: List[EvidenceType] = [ EvidenceType.LM, EvidenceType.ERP ], - task_list: List[Tuple[str, str]] = [('I_LOVE_COOKIES', - 'I_LOVE_')], + task_list: List[Tuple[str, + str]] = [('I_LOVE_COOKIES', 'I_LOVE_')], is_txt_stim: bool = True, decision_threshold: float = 0.8, backspace_prob: float = 0.05, backspace_always_shown: bool = False, - filter_high: int = 45, - filter_low: int = 2, - filter_order: int = 2, - notch_filter_frequency: int = 60, stim_timing: List[float] = [1, .2], stim_length: int = 10, stim_jitter: float = 0, @@ -127,90 +105,9 @@ def __init__(self, # non-letter target labels include the fixation cross and calibration. self.nonletters = ['+', 'PLUS', 'calibration_trigger'] self.valid_targets = set(self.alp) - - self.signal_model = signal_model - self.sampling_rate = device_spec.sample_rate - self.downsample_rate = k - self.filter_high = filter_high - self.filter_low = filter_low - self.filter_order = filter_order - self.notch_filter_frequency = notch_filter_frequency - - self.mode = 'copy_phrase' self.task_list = task_list - self.channel_map = analysis_channels(device_spec.channels, device_spec) self.backspace_prob = backspace_prob - def evaluate_inquiry( - self, raw_data: np.array, triggers: List[Tuple[str, float]], - target_info: List[str], window_length: float - ) -> Tuple[bool, Tuple[List[str], List[float], List[str]]]: - """Once data is collected, infers meaning from the data and attempt to - make a decision. - - Parameters - ---------- - - raw_data: C x L eeg data where C is number of channels and L is the - signal length - - triggers: triggers e.g. `('A', 1)` as letter and flash time for the - letter - - target_info: target information about the stimuli - - window_length: The length of the time between stimuli presentation - - Returns - ------- - - (True, None) when commitment is made. - - (False, next set of stimuli) when not enough evidence has - been provided and stoppage criteria is not yet met. - """ - lik_r = self.evaluate_eeg_evidence(raw_data, triggers, target_info, - window_length) - self.add_evidence(EvidenceType.ERP, lik_r) - return self.decide() - - def evaluate_eeg_evidence(self, raw_data: np.array, - triggers: List[Tuple[str, float]], - target_info: List[str], - window_length: float) -> np.array: - """Once data is collected, infers meaning from the data and return the results. - - Parameters - ---------- - - raw_data: C x L eeg data where C is number of channels and L is the - signal length - - triggers: triggers e.g. `('A', 1)` as letter and flash time for the - letter - - target_info: target information about the stimuli - - window_length: The length of the time between stimuli presentation - - Returns - ------- - np.array of likelihood evidence - """ - letters, times, target_info = self.letter_info(triggers, target_info) - - default_transform = get_default_transform( - sample_rate_hz=self.sampling_rate, - notch_freq_hz=self.notch_filter_frequency, - bandpass_low=self.filter_low, - bandpass_high=self.filter_high, - bandpass_order=self.filter_order, - downsample_factor=self.downsample_rate, - ) - - data, transformed_sample_rate = default_transform(raw_data, self.sampling_rate) - - # The data from DAQ is assumed to have offsets applied - data, _ = TrialReshaper()( - trial_targetness_label=target_info, - timing_info=times, - eeg_data=data, - sample_rate=transformed_sample_rate, - channel_map=self.channel_map, - poststimulus_length=window_length) - - return self.signal_model.predict(data, letters, self.alp) - def add_evidence(self, evidence_type: EvidenceType, evidence: List[float]) -> np.array: """Add evidence to the conjugator. diff --git a/bcipy/helpers/tests/test_copy_phrase_wrapper.py b/bcipy/helpers/tests/test_copy_phrase_wrapper.py index 14bc909f1..f04066d5e 100644 --- a/bcipy/helpers/tests/test_copy_phrase_wrapper.py +++ b/bcipy/helpers/tests/test_copy_phrase_wrapper.py @@ -1,78 +1,20 @@ -import random -import shutil -import tempfile import unittest -from pathlib import Path - -import numpy as np - -from bcipy.config import DEFAULT_PARAMETERS_PATH -from bcipy.acquisition.devices import DeviceSpec, register from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper -from bcipy.helpers.load import load_json_parameters from bcipy.helpers.symbols import alphabet from bcipy.language.model.uniform import UniformLanguageModel -from bcipy.signal.model import PcaRdaKdeModel from bcipy.task.data import EvidenceType class TestCopyPhraseWrapper(unittest.TestCase): """Test CopyPhraseWrapper""" - @classmethod - def setUpClass(cls): - np.random.seed(0) - random.seed(0) - cls.tmp_dir = Path(tempfile.mkdtemp()) - - cls.device_spec = DeviceSpec(name="dummy_device", channels=["1", "2", "3"], sample_rate=10) - register(cls.device_spec) - - cls.params_used = DEFAULT_PARAMETERS_PATH - cls.params = load_json_parameters(cls.params_used, value_cast=True) - - # # Generate fake data and train a model - # Specify data dimensions - cls.num_trial = cls.params["stim_length"] - cls.dim_x = 5 - cls.num_channel = cls.device_spec.channel_count - cls.num_x_pos = 200 - cls.num_x_neg = 200 - - # Generate Gaussian random data - # TODO - deduplicate, add to test utils somewhere (data generation matching a device_spec) - cls.pos_mean, cls.pos_std = 0, 0.5 - cls.neg_mean, cls.neg_std = 1, 0.5 - x_pos = cls.pos_mean + cls.pos_std * np.random.randn(cls.num_channel, cls.num_x_pos, cls.dim_x) - x_neg = cls.neg_mean + cls.neg_std * np.random.randn(cls.num_channel, cls.num_x_neg, cls.dim_x) - y_pos = np.ones(cls.num_x_pos) - y_neg = np.zeros(cls.num_x_neg) - - # Stack and permute data - x = np.concatenate([x_pos, x_neg], 1) - y = np.concatenate([y_pos, y_neg], 0) - permutation = np.random.permutation(cls.num_x_pos + cls.num_x_neg) - x = x[:, permutation, :] - y = y[permutation] - - cls.model = PcaRdaKdeModel(k_folds=10) - cls.model.fit(x, y) - - @classmethod - def tearDownClass(cls): - shutil.rmtree(cls.tmp_dir) - def test_valid_letters(self): alp = alphabet() cp = CopyPhraseWrapper( min_num_inq=1, max_num_inq=50, lmodel=None, - device_spec=self.device_spec, - signal_model=None, - # fs=25, - k=2, alp=alp, task_list=[("HELLO_WORLD", "HE")], is_txt_stim=True, @@ -158,76 +100,27 @@ def test_valid_letters(self): # Test it throws an exception when letter is outside alphabet with self.assertRaises(Exception): - cp.letter_info([("A", 0.0), ("*", 1.0)], ["nontarget", "nontarget"]) + cp.letter_info([("A", 0.0), ("*", 1.0)], + ["nontarget", "nontarget"]) - def test_init_series_evaluate_inquiry(self): + def test_init_series(self): alp = alphabet() - # Create fake data to provide as the user's response - duration = int(self.num_trial * self.device_spec.sample_rate * self.params["trial_length"]) - response_eeg = self.pos_mean + self.pos_std * np.random.randn(self.num_channel, duration) - - # Note that frequencies for notch and bandpass filter below are chosen to be < 1/2 of sampling frequency - # due to limitations of nyquist-shannon sampling theorem copy_phrase_task = CopyPhraseWrapper( min_num_inq=1, max_num_inq=50, lmodel=UniformLanguageModel(symbol_set=alp), - device_spec=self.device_spec, - signal_model=self.model, - k=1, alp=alp, task_list=[("HELLO_WORLD", "HE")], is_txt_stim=True, evidence_names=[EvidenceType.LM, EvidenceType.ERP], stim_timing=[0.5, 0.25], - notch_filter_frequency=4.0, - filter_low=1.0, - filter_high=4.0, - stim_length=self.params["stim_length"], + stim_length=10, ) is_accepted, sti = copy_phrase_task.initialize_series() self.assertFalse(is_accepted) - triggers = [ - ("+", 0.0), - ("H", 0.5670222830376588), - ("D", 0.8171830819919705), - ("J", 1.0843321380089037), - ("B", 1.3329724550130777), - ("C", 1.5825864360085689), - ("A", 1.833380013005808), - ("F", 2.083211077027954), - ("G", 2.333359022042714), - ("I", 2.583265081048012), - ("E", 2.833274284028448), - ] - stimuli = [label for (label, _) in triggers] - target_info = [ - "nontarget", - "nontarget", - "nontarget", - "nontarget", - "nontarget", - "nontarget", - "nontarget", - "nontarget", - "nontarget", - "nontarget", - "nontarget", - ] - - new_series, inquiry = copy_phrase_task.evaluate_inquiry( - response_eeg, triggers, target_info, self.params["trial_length"] - ) - self.assertFalse(new_series) - self.assertEqual(sorted(inquiry.stimuli[0]), sorted(stimuli)) - self.assertEqual(inquiry.durations[0], [self.params["time_fixation"]] + - [self.params["time_flash"]] * self.params["stim_length"]) - self.assertEqual(inquiry.colors[0], [self.params["fixation_color"]] + - [self.params["stim_color"]] * self.params["stim_length"]) - if __name__ == '__main__': unittest.main() diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 2360c340b..8c33f77d1 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -261,14 +261,10 @@ def init_copy_phrase_task(self) -> None: initialized CopyPhraseWrapper """ - # TODO: remove signal_model self.copy_phrase_task = CopyPhraseWrapper( self.parameters['min_inq_len'], self.parameters['max_inq_per_series'], lmodel=self.language_model, - device_spec=self.daq.device_spec, - signal_model=self.signal_model, - k=self.parameters['down_sampling_rate'], alp=self.alp, evidence_names=self.evidence_types, task_list=[(str(self.copy_phrase), self.spelled_text)], @@ -279,10 +275,6 @@ def init_copy_phrase_task(self) -> None: decision_threshold=self.parameters['decision_threshold'], backspace_prob=self.parameters['lm_backspace_prob'], backspace_always_shown=self.parameters['backspace_always_shown'], - filter_high=self.parameters['filter_high'], - filter_low=self.parameters['filter_low'], - filter_order=self.parameters['filter_order'], - notch_filter_frequency=self.parameters['notch_filter_frequency'], stim_length=self.parameters['stim_length'], stim_jitter=self.parameters['stim_jitter'], stim_order=StimuliOrder(self.parameters['stim_order'])) @@ -602,42 +594,6 @@ def compute_device_evidence( window_length=self.parameters['trial_length']) return (evidence_evaluator.produces, probs) - def compute_eeg_evidence(self, - stim_times: List[List], - proceed: bool = True - ) -> Optional[Tuple[EvidenceType, List[float]]]: - """Evaluate the EEG evidence and add it to the copy_phrase_task, but - don't yet attempt a decision. - - Parameters - ---------- - - stim_times : list of stimuli returned from the display - - proceed : whether or not to evaluate the evidence, if `False` returns - empty values. - - Returns - ------- - tuple of (evidence type, evidence) - """ - if not proceed or self.fake: - return None - - # currently prestim_length is used as a buffer for filter application, use the same at the end of the inquiry - post_stim_buffer = self.parameters['prestim_length'] - raw_data, triggers = get_data_for_decision( - inquiry_timing=self.stims_for_decision(stim_times), - daq=self.daq, - offset=self.parameters['static_trigger_offset'], - prestim=self.parameters['prestim_length'], - poststim=post_stim_buffer + self.parameters['trial_length']) - - # we assume all are nontargets at this point - labels = ['nontarget'] * len(triggers) - - probs = self.copy_phrase_task.evaluate_eeg_evidence( - raw_data, triggers, labels, self.parameters['trial_length']) - return (EvidenceType.ERP, probs) - def stims_for_decision(self, stim_times: List[List]) -> List[List]: """The stim_timings from the display may include non-letter stimuli such as calibration and inquiry_preview timings. This method extracts From 72c6631e85b5de66bdbac20ae89041580f26e95c Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Tue, 20 Jun 2023 14:56:13 -0400 Subject: [PATCH 036/330] Inquiry plotting changes added --- bcipy/helpers/stimuli.py | 9 +- bcipy/helpers/visualization.py | 2 +- bcipy/signal/model/offline_analysis.py | 2 +- bcipy/signal/model/offline_analysis_fusion.py | 138 ---------------- bcipy/signal/model/offline_gaze_analysis.py | 149 ------------------ scripts/python/plot_eye_data.py | 2 - scripts/python/plot_inquiry_data.py | 105 ++++++++++++ 7 files changed, 112 insertions(+), 295 deletions(-) delete mode 100644 bcipy/signal/model/offline_analysis_fusion.py delete mode 100644 bcipy/signal/model/offline_gaze_analysis.py create mode 100644 scripts/python/plot_inquiry_data.py diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index c95a6cc23..2a501c72d 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -275,6 +275,8 @@ def __call__(self, # triggers in seconds are mapped to triggers in number of samples. triggers = list(map(lambda x: int((x + offset) * sample_rate), timing_info)) + inquiry_triggers = list(map(lambda x: int(x * sample_rate), timing_info)) + # First, find the longest inquiry in this experiment # We'll add or remove a few samples from all other inquiries, to match this length @@ -284,12 +286,11 @@ def get_inquiry_len(inq_trigs): # Finds the longest inquiry in the experiment by subtracting the first trigger from the last trigger in each inquiry longest_inquiry = max(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) - # What we need from gaze data is actually the shortest inquiry, not the longest - shortest_inquiry = min(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) - breakpoint() + # What we need is to find the shortest distance from 1st letter to last in each inquiry + shortest_inquiry = min(grouper(triggers, inquiry_triggers, trials_per_inquiry, fillvalue='x')) # We will trim off the extra bits in each inquiry to match the shortest inquiry - # TODO + num_samples_per_inq = get_inquiry_len(longest_inquiry) + trial_duration_samples diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 00ff441f1..29918c4c3 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -342,4 +342,4 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi show=show, ) - eye_data = visualize_eye_data + # eye_data = visualize_gaze diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 8d044fb44..372633da0 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -247,6 +247,7 @@ def offline_analysis( show=show_figures, raw_plot=True, ) + plt.show() channels = mode_data.channels type_amp = mode_data.daq_type sample_rate = mode_data.sample_rate @@ -261,7 +262,6 @@ def offline_analysis( data, fs = mode_data.by_channel() model = GazeModel() - breakpoint() # Process triggers.txt files (again!) trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( diff --git a/bcipy/signal/model/offline_analysis_fusion.py b/bcipy/signal/model/offline_analysis_fusion.py deleted file mode 100644 index e1775cf14..000000000 --- a/bcipy/signal/model/offline_analysis_fusion.py +++ /dev/null @@ -1,138 +0,0 @@ -import logging -from pathlib import Path -from typing import Tuple - -import numpy as np -import pandas as pd -from matplotlib import pyplot as plt -from sklearn.mixture import GaussianMixture - -from bcipy.config import DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, RAW_DATA_FILENAME -from bcipy.preferences import preferences -from bcipy.helpers.acquisition import analysis_channels -from bcipy.helpers.load import ( - load_experimental_data, - load_json_parameters, - load_raw_gaze_data -) -from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.signal.model.fusion_model import GazeModel - -from sklearn.model_selection import train_test_split - -log = logging.getLogger(__name__) -logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") - -def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): - """Performs a train/test split on the provided data and labels, accounting for - the current shape convention (channel dimension in front, instead of batch dimension in front). - - Args: - data (np.ndarray): Shape (channels, items, time) - labels (np.ndarray): Shape (items,) - test_size (float): fraction of data to be used for testing - random_state (int, optional): fixed random seed - - Returns: - train_data (np.ndarray): Shape (channels, train_items, time) - test_data (np.ndarray): Shape (channels, test_items, time) - train_labels (np.ndarray): Shape (train_items,) - test_labels (np.ndarray): Shape (test_items,) - """ - data = data.swapaxes(0, 1) - train_data, test_data, train_labels, test_labels = train_test_split( - data, labels, test_size=test_size, random_state=random_state - ) - train_data = train_data.swapaxes(0, 1) - test_data = test_data.swapaxes(0, 1) - return train_data, test_data, train_labels, test_labels - - -def offline_analysis_fusion( - data_folder: str = None, - parameters: dict = {}, -): - - if not data_folder: - data_folder = load_experimental_data() - - # extract relevant session information from parameters file - poststim_length = parameters.get("trial_length") - prestim_length = parameters.get("prestim_length") - trials_per_inquiry = parameters.get("stim_length") - static_offset = parameters.get("static_trigger_offset") - # The task buffer length defines the min time between two inquiries - # We use half of that time here to buffer during transforms - buffer = int(parameters.get("task_buffer_length") / 2) - raw_data_file = f"{RAW_DATA_FILENAME}.csv" - - log.info( - f"\nData processing settings: \n" - f"Poststimulus: {poststim_length}s, Prestimulus: {prestim_length}s, Buffer: {buffer}s, Trials per inquiry: {trials_per_inquiry} \n" - ) - - # Load raw data - gaze_data = load_raw_gaze_data(Path(data_folder, raw_data_file)) - channels = gaze_data.channels - type_amp = gaze_data.daq_type - sample_rate = gaze_data.sample_rate - - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") - - # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - remove_pre_fixation = False, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.OFFSET], - ) - - # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module - # The timestamp column [0] is already excluded. - channel_map = analysis_channels(channels, type_amp) - # channel_map = [0,0,1,1,0,1,1,0,0] - - data, fs = gaze_data.by_channel() # no transformations applied at this stage - - model = GazeModel() - - # Note that we are calling a Gaze Reshaper instead of a Trial or Inquiry Reshaper. - # We might not need a separate reshaper function. - inquiries, inquiry_labels, inquiry_timing = model.reshaper( - trial_targetness_label=trigger_targetness, - timing_info=trigger_timing, - gaze_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=poststim_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer, - ) - - - - - - results = [] - # A joint reshaper? - - - return results - - -if __name__ == "__main__": - import argparse - - parser = argparse.ArgumentParser() - parser.add_argument("-d", "--data_folder", default=None) - parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) - args = parser.parse_args() - - log.info(f"Loading params from {args.parameters_file}") - parameters = load_json_parameters(args.parameters_file, value_cast=True) - - offline_analysis_fusion( - args.data_folder, - parameters) - log.info("Offline Analysis complete.") \ No newline at end of file diff --git a/bcipy/signal/model/offline_gaze_analysis.py b/bcipy/signal/model/offline_gaze_analysis.py deleted file mode 100644 index de8a6796b..000000000 --- a/bcipy/signal/model/offline_gaze_analysis.py +++ /dev/null @@ -1,149 +0,0 @@ -import logging -from pathlib import Path -from typing import Tuple - -import numpy as np -import pandas as pd -from matplotlib import pyplot as plt -from sklearn.mixture import GaussianMixture - -from bcipy.config import (DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, - RAW_DATA_FILENAME, STATIC_AUDIO_PATH, - DEFAULT_DEVICE_SPEC_FILENAME, - EYE_TRACKER_FILENAME_PREFIX) -from bcipy.preferences import preferences -from bcipy.helpers.acquisition import analysis_channels -from bcipy.helpers.load import ( - load_experimental_data, - load_json_parameters, - load_raw_data -) -from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.signal.model.fusion_model import GazeModel -import bcipy.acquisition.devices as devices - -from sklearn.model_selection import train_test_split - -log = logging.getLogger(__name__) -logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") - -def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): - """Performs a train/test split on the provided data and labels, accounting for - the current shape convention (channel dimension in front, instead of batch dimension in front). - - Args: - data (np.ndarray): Shape (channels, items, time) - labels (np.ndarray): Shape (items,) - test_size (float): fraction of data to be used for testing - random_state (int, optional): fixed random seed - - Returns: - train_data (np.ndarray): Shape (channels, train_items, time) - test_data (np.ndarray): Shape (channels, test_items, time) - train_labels (np.ndarray): Shape (train_items,) - test_labels (np.ndarray): Shape (test_items,) - """ - data = data.swapaxes(0, 1) - train_data, test_data, train_labels, test_labels = train_test_split( - data, labels, test_size=test_size, random_state=random_state - ) - train_data = train_data.swapaxes(0, 1) - test_data = test_data.swapaxes(0, 1) - return train_data, test_data, train_labels, test_labels - - -def offline_gaze_analysis( - data_folder: str = None, - parameters: dict = {}, -): - - if not data_folder: - data_folder = load_experimental_data() - - # extract relevant session information from parameters file - poststim_length = parameters.get("trial_length") - prestim_length = parameters.get("prestim_length") - trials_per_inquiry = parameters.get("stim_length") - static_offset = parameters.get("static_trigger_offset") - # The task buffer length defines the min time between two inquiries - # We use half of that time here to buffer during transforms - buffer = int(parameters.get("task_buffer_length") / 2) - - log.info( - f"\nData processing settings: \n" - f"Poststimulus: {poststim_length}s, Prestimulus: {prestim_length}s, Buffer: {buffer}s, Trials per inquiry: {trials_per_inquiry} \n" - ) - - data_file_path = [f"{RAW_DATA_FILENAME}.csv"] - - # Load raw data - data_list = load_raw_data(data_folder, data_file_path) - gaze_data = data_list[0] - channels = gaze_data.channels - type_amp = gaze_data.daq_type - sample_rate = gaze_data.sample_rate - - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") - - # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - remove_pre_fixation = False, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.OFFSET], - ) - - # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module - # The timestamp column [0] is already excluded. - channel_map = analysis_channels(channels, type_amp) - # channel_map = [0,0,1,1,0,1,1,0,0] - - data, fs = gaze_data.by_channel() # no transformations applied at this stage - - model = GazeModel() - - # Note that we are calling a Gaze Reshaper instead of a Trial or Inquiry Reshaper. - # We might not need a separate reshaper function. - inquiries, inquiry_labels, inquiry_timing = model.reshaper( - trial_targetness_label=trigger_targetness, - timing_info=trigger_timing, - gaze_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=poststim_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer, - ) - - - - - - results = [] - - #TODO: - # Implement reshaper. We might not need a separate reshaper function. - # Plotting for offset - # Plot the gaze data (check NSLR) fixation, saccade, blink - # Use Tobii to Psychopy units conversion - - - return results - - -if __name__ == "__main__": - import argparse - - parser = argparse.ArgumentParser() - parser.add_argument("-d", "--data_folder", default=None) - parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) - args = parser.parse_args() - - log.info(f"Loading params from {args.parameters_file}") - parameters = load_json_parameters(args.parameters_file, value_cast=True) - - offline_gaze_analysis( - args.data_folder, - parameters) - log.info("Offline Analysis complete.") \ No newline at end of file diff --git a/scripts/python/plot_eye_data.py b/scripts/python/plot_eye_data.py index 2b2e2fe9e..cb9461d62 100644 --- a/scripts/python/plot_eye_data.py +++ b/scripts/python/plot_eye_data.py @@ -1,9 +1,7 @@ -import os from bcipy.helpers.raw_data import load DIPSIZE = (1707, 1067) TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' -# IMG_PATH = os.path.abspath(os.path.dirname(__file__))+ '/matrix_grid.png' def load_eye_tracking_data(path): data = load(f'{path}/{TOBII_FILENAME}') diff --git a/scripts/python/plot_inquiry_data.py b/scripts/python/plot_inquiry_data.py new file mode 100644 index 000000000..4243ad134 --- /dev/null +++ b/scripts/python/plot_inquiry_data.py @@ -0,0 +1,105 @@ +from bcipy.helpers.raw_data import load +from bcipy.config import STATIC_IMAGES_PATH + +DIPSIZE = (1707, 1067) +IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' +TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' + +def load_eye_tracking_data(path): + data = load(f'{path}/{TOBII_FILENAME}') + + left_eye_channel_map = [0,0,1,1,0,0,0,0,0] + left_eye_data, _, _ = data.by_channel_map(left_eye_channel_map) + left_eye_x = left_eye_data[0] + left_eye_y = left_eye_data[1] + + right_eye_channel_map = [0,0,0,0,0,1,1,0,0] + right_eye_data, _, _ = data.by_channel_map(right_eye_channel_map) + right_eye_x = right_eye_data[0] + right_eye_y = right_eye_data[1] + return left_eye_x, left_eye_y, right_eye_x, right_eye_y + + +if __name__ == "__main__": + import argparse + from pathlib import Path + from bcipy.helpers.load import load_experimental_data + import matplotlib.pyplot as plt + from matplotlib import image + import numpy as np + import seaborn as sns + import pandas as pd + + parser = argparse.ArgumentParser() + parser.add_argument( + '-p', + '--path', + help='Path to the directory with raw_data to be converted', + required=False) + args = parser.parse_args() + + # if no path is provided, prompt for one using a GUI + path = args.path + if not path: + path = load_experimental_data() + + data = load_eye_tracking_data(path) + lx, ly, rx, ry = data + + dpi = 100 + + # load the image + img = plt.imread(IMG_PATH) + # img = np.flipud(img) + + w, h = len(img[0]), len(img) + + # resize the image to fit the display + # img = np.resize(img, (DIPSIZE[1], DIPSIZE[0], 4)) + fig, ax = plt.subplots() + ax.imshow(img, extent=[0, 1, 0, 1]) + # ax.scatter(lx, ly, c='r', s=1) + # ax.scatter(rx, ry, c='b', s=1) + # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis + lx = np.clip(lx, 0, 1) + ly = np.clip(ly, 0, 1) + rx = np.clip(rx, 0, 1) + ry = np.clip(ry, 0, 1) + ly = 1 - ly + ry = 1 - ry + + # plot the eye data + # ax.plot(lx, ly, c='r', linewidth=1) + # ax.plot(rx, ry, c='b', linewidth=1) + + # # remove nan values + # lx = lx[~np.isnan(lx)] + # ly = ly[~np.isnan(ly)] + # rx = rx[~np.isnan(rx)] + # ry = ry[~np.isnan(ry)] + + # determine kde of the eye data + # ax = sns.kdeplot(rx, ry, cmap="mako", fill=False, thresh=0.05, levels=10) + + lx_inq = lx[48368:48535] + ly_inq = ly[48368:48535] + rx_inq = rx[48368:48535] + ry_inq = ry[48368:48535] + + # remove nan values + lx_inq = lx_inq[~np.isnan(lx_inq)] + ly_inq = ly_inq[~np.isnan(ly_inq)] + rx_inq = rx_inq[~np.isnan(rx_inq)] + ry_inq = ry_inq[~np.isnan(ry_inq)] + + + ax.scatter(lx_inq, ly_inq, c='r', s=1) + ax.scatter(rx_inq, ry_inq, c='b', s=1) + + + # ax.scatter(lx, ly, c='r', s=1) + # ax.scatter(rx, ry, c='b', s=1) + + plt.show() + + breakpoint() \ No newline at end of file From a2aafb1803a86a755418260da8f061143e25b27d Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 20 Jun 2023 14:32:16 -0700 Subject: [PATCH 037/330] Added error handling for multimodal data queries for insufficient data --- bcipy/acquisition/exceptions.py | 7 +++ bcipy/acquisition/multimodal.py | 22 ++++++--- .../acquisition/tests/test_client_manager.py | 45 +++++++++++++++++-- 3 files changed, 65 insertions(+), 9 deletions(-) diff --git a/bcipy/acquisition/exceptions.py b/bcipy/acquisition/exceptions.py index 6551ab2db..d5035c902 100644 --- a/bcipy/acquisition/exceptions.py +++ b/bcipy/acquisition/exceptions.py @@ -6,3 +6,10 @@ def __init__(self, msg): class UnsupportedContentType(Exception): """Error that occurs when attempting to collect data from a device with a content type that is not yet supported by BciPy.""" + + +class InsufficientDataException(Exception): + """Insufficient Data Exception. + + Thrown when data requirements to execute task are violated. + """ diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 2f19be645..b93136735 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -3,7 +3,8 @@ from typing import Any, Dict, List, Optional from bcipy.acquisition.devices import DeviceSpec -from bcipy.acquisition.exceptions import UnsupportedContentType +from bcipy.acquisition.exceptions import (InsufficientDataException, + UnsupportedContentType) from bcipy.acquisition.protocols.lsl.lsl_client import LslAcquisitionClient from bcipy.acquisition.record import Record from bcipy.helpers.system_utils import AutoNumberEnum @@ -112,7 +113,8 @@ def get_data_by_device( self, start: float = None, seconds: float = None, - content_types: List[ContentType] = None + content_types: List[ContentType] = None, + strict: bool = True ) -> Dict[ContentType, List[Record]]: """Get data for one or more devices. The number of samples for each device depends on the sample rate and may be different for item. @@ -121,18 +123,26 @@ def get_data_by_device( ---------- start - start time (acquisition clock) of data window seconds - duration of data to return for each device - content_types - specifies which devices to include + content_types - specifies which devices to include; if not + unspecified, data for all types is returned. + strict - if True, raises an exception if the returned rows is + less than the requested number of records. """ output = {} + if not content_types: + content_types = self.device_content_types for content_type in content_types: + name = content_type.name client = self.get_client(content_type) if client.device_spec.sample_rate > 0: count = round(seconds * client.device_spec.sample_rate) - log.debug( - f'Need {count} records for processing {content_type.name} data' - ) + log.debug(f'Need {count} records for processing {name} data') output[content_type] = client.get_data(start=start, limit=count) + data_count = len(output[content_type]) + if strict and data_count < count: + msg = f'Needed {count} {name} records but received {data_count}' + raise InsufficientDataException(msg) else: # Markers have an IRREGULAR_RATE. output[content_type] = client.get_data(start=start, diff --git a/bcipy/acquisition/tests/test_client_manager.py b/bcipy/acquisition/tests/test_client_manager.py index fa9d08819..dc5ed8194 100644 --- a/bcipy/acquisition/tests/test_client_manager.py +++ b/bcipy/acquisition/tests/test_client_manager.py @@ -1,6 +1,7 @@ import unittest -from unittest.mock import Mock +from unittest.mock import MagicMock, Mock +from bcipy.acquisition.exceptions import InsufficientDataException from bcipy.acquisition.multimodal import ClientManager, ContentType @@ -16,7 +17,9 @@ def setUp(self): self.eeg_client_mock = Mock() self.eeg_client_mock.device_spec = self.eeg_device_mock - self.eeg_client_mock.get_data = Mock() + self.eeg_data_mock = Mock() + self.eeg_client_mock.get_data = MagicMock( + return_value=self.eeg_data_mock) self.gaze_device_mock = Mock() self.gaze_device_mock.content_type = 'Eyetracker' @@ -102,7 +105,15 @@ def test_get_data_by_device(self): switch_client_mock = Mock() switch_client_mock.device_spec = switch_device_mock - switch_client_mock.get_data = Mock() + switch_data_mock = Mock() + switch_data_mock.__len__ = lambda self: 5 + switch_client_mock.get_data = MagicMock(return_value=switch_data_mock) + + gaze_data_mock = Mock() + gaze_data_mock.__len__ = lambda self: 300 + self.gaze_client_mock.get_data = MagicMock(return_value=gaze_data_mock) + + self.eeg_data_mock.__len__ = lambda self: 1500 daq = ClientManager() daq.add_client(self.eeg_client_mock) @@ -127,6 +138,34 @@ def test_get_data_by_device(self): self.assertTrue(ContentType.EYETRACKER in results) self.assertTrue(ContentType.MARKERS in results) + def test_insufficient_data(self): + """Test insufficient data exception in strict mode.""" + + gaze_data_mock = Mock() + gaze_data_mock.__len__ = lambda self: 299 + self.gaze_client_mock.get_data = MagicMock(return_value=gaze_data_mock) + + daq = ClientManager() + daq.add_client(self.gaze_client_mock) + + with self.assertRaises(InsufficientDataException): + daq.get_data_by_device(start=100, seconds=5) + + def test_non_strict_data_request(self): + """Test data request in non-strict mode.""" + + gaze_data_mock = Mock() + gaze_data_mock.__len__ = lambda self: 299 + self.gaze_client_mock.get_data = MagicMock(return_value=gaze_data_mock) + + daq = ClientManager() + daq.add_client(self.gaze_client_mock) + + results = daq.get_data_by_device(start=100, seconds=5, strict=False) + self.gaze_client_mock.get_data.assert_called_once_with(start=100, + limit=300) + self.assertTrue(ContentType.EYETRACKER in results) + if __name__ == '__main__': unittest.main() From 5748cf6122726cf1af4b9d11b712129fbd4300e7 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 20 Jun 2023 14:35:13 -0700 Subject: [PATCH 038/330] Refactored device querying in Copy Phrase task to ensure that each device is only queried once --- bcipy/helpers/task.py | 75 ++++++++++++++++++- bcipy/task/paradigm/rsvp/copy_phrase.py | 61 ++++++++------- .../tests/paradigm/rsvp/test_copy_phrase.py | 33 ++++---- 3 files changed, 127 insertions(+), 42 deletions(-) diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index a79a40af0..f66453c05 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -1,10 +1,11 @@ import logging import random -from typing import Any, List, Tuple, Union +from typing import Any, Dict, List, Tuple, Union import numpy as np from psychopy import core, event, visual +from bcipy.acquisition.multimodal import ClientManager, ContentType from bcipy.config import SESSION_COMPLETE_MESSAGE from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import get_fixation @@ -174,6 +175,78 @@ def get_data_for_decision(inquiry_timing, return raw_data, triggers +def get_device_data_for_decision( + inquiry_timing: List[Tuple], + daq: ClientManager, + offset: float = 0.0, + prestim: float = 0.0, + poststim: float = 0.0) -> Dict[ContentType, np.ndarray]: + """Queries the acquisition client manager for a slice of data from each + device and processes the resulting raw data into a form that can be passed + to signal processing and classifiers. + + Parameters + ---------- + - inquiry_timing(list): list of tuples containing stimuli timing and labels. + - daq (ClientManager): bcipy data acquisition client manager + - offset (float): offset present in the system which should be accounted for when creating data for classification. + This is determined experimentally. + - prestim (float): length of data needed before the first sample to reshape and apply transformations + - poststim (float): length of data needed after the last sample in order to reshape and apply transformations + + Returns + ------- + a dict mapping device content_type to the data; + data has shape C x L where C is number of channels and L is the + signal length. + """ + _, first_stim_time = inquiry_timing[0] + _, last_stim_time = inquiry_timing[-1] + + # adjust for offsets + time1 = first_stim_time + offset - prestim + time2 = last_stim_time + offset + + if time2 < time1: + raise InsufficientDataException( + f'Invalid data query [{time1}-{time2}] with parameters:' + f'[inquiry={inquiry_timing}, offset={offset}, prestim={prestim}, poststim={poststim}]' + ) + + data = daq.get_data_by_device(start=time1, + seconds=(time2 - time1 + poststim), + strict=True) + for content_type in data.keys(): + # Take only the sensor data from raw data and transpose it. + # TODO: Does this apply to all content types? If not this step could be + # moved to the evidence evaluators. + data[content_type] = np.array([ + np.array([_float_val(col) for col in record.data]) + for record in data[content_type] + ], + dtype=np.float64).transpose() + + return data + + +def relative_triggers(inquiry_timing: List[Tuple[str, float]], + prestim: float) -> List[Tuple[str, float]]: + """Adjust the provided inquiry_timing triggers for processing. The new + timing values are relative to the first stim time, rather than using + absolute clock times. + + Parameters + ---------- + inquiry_timing - list of (symbol, timestamp) pairs for each trigger in + an inquiry + prestim - seconds of data needed before the first sample to reshape and + apply transformations + """ + _, first_stim_time = inquiry_timing[0] + return [(symbol, (timestamp - first_stim_time) + prestim) + for symbol, timestamp in inquiry_timing] + + def _float_val(col: Any) -> float: """Convert marker data to float values so we can put them in a typed np.array. The marker column has type float if it has a 0.0 diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 8c33f77d1..e62b28c8e 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -20,8 +20,9 @@ from bcipy.helpers.stimuli import InquirySchedule, StimuliOrder from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet from bcipy.helpers.task import (construct_triggers, fake_copy_phrase_decision, - get_data_for_decision, get_user_input, - target_info, trial_complete_message) + get_device_data_for_decision, get_user_input, + relative_triggers, target_info, + trial_complete_message) from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, convert_timing_triggers) from bcipy.signal.model.inquiry_preview import compute_probs_after_preview @@ -495,6 +496,9 @@ def add_evidence(self, stim_times: List[List], proceed: bool = True) -> List[EvidenceType]: """Add all evidence used to make a decision. + Evaluates evidence from various sources (button press, devices, + language model) and adds it to the CopyPhraseWrapper for evaluation. + Parameters ---------- - stim_times : list of stimuli returned from the display @@ -511,10 +515,8 @@ def add_evidence(self, stim_times: List[List], evidences = [ self.compute_button_press_evidence(proceed) ] - - for evidence_evaluator in self.evidence_evaluators: - evidences.append( - self.compute_device_evidence(evidence_evaluator, stim_times)) + # evidence from one or more devices + evidences.extend(self.compute_device_evidence(stim_times, proceed)) evidence_types = [] for evidence in evidences: @@ -552,47 +554,56 @@ def compute_button_press_evidence( def compute_device_evidence( self, - evidence_evaluator: EvidenceEvaluator, stim_times: List[List], - proceed: bool = True - ) -> Optional[Tuple[EvidenceType, List[float]]]: - """Evaluate the evidence using the provided evaluator but + proceed: bool = True) -> List[Tuple[EvidenceType, List[float]]]: + """Get inquiry data from all devices and evaluate the evidence, but don't yet attempt a decision. Parameters ---------- - stim_times : list of stimuli returned from the display - proceed : whether or not to evaluate the evidence, if `False` returns - empty values. + an empty array. Returns ------- - tuple of (evidence type, evidence) + list of (evidence type, evidence) tuples """ if not proceed or self.fake: - return None + return [] - # currently prestim_length is used as a buffer for filter application, use the same at the end of the inquiry + # currently prestim_length is used as a buffer for filter application; + # use the same at the end of the inquiry post_stim_buffer = self.parameters['prestim_length'] + prestim = self.parameters['prestim_length'] + inquiry_timing = self.stims_for_decision(stim_times) - raw_data, triggers = get_data_for_decision( - inquiry_timing=self.stims_for_decision(stim_times), - daq=self.daq.get_client(evidence_evaluator.consumes), + # Get all data at once so we don't redundantly query devices which are + # used in more than one signal model. + device_data = get_device_data_for_decision( + inquiry_timing=inquiry_timing, + daq=self.daq, offset=self.parameters['static_trigger_offset'], - prestim=self.parameters['prestim_length'], + prestim=prestim, poststim=post_stim_buffer + self.parameters['trial_length']) + triggers = relative_triggers(inquiry_timing, prestim) # we assume all are nontargets at this point labels = ['nontarget'] * len(triggers) letters, times, filtered_labels = self.copy_phrase_task.letter_info( triggers, labels) - probs = evidence_evaluator.evaluate( - raw_data=raw_data, - symbols=letters, - times=times, - target_info=filtered_labels, - window_length=self.parameters['trial_length']) - return (evidence_evaluator.produces, probs) + + evidences = [] + for evidence_evaluator in self.evidence_evaluators: + probs = evidence_evaluator.evaluate( + raw_data=device_data[evidence_evaluator.consumes], + symbols=letters, + times=times, + target_info=filtered_labels, + window_length=self.parameters['trial_length']) + evidences.append((evidence_evaluator.produces, probs)) + + return evidences def stims_for_decision(self, stim_times: List[List]) -> List[List]: """The stim_timings from the display may include non-letter stimuli diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 34d43ad65..f6dac8745 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -236,7 +236,7 @@ def test_execute_without_inquiry(self, message_mock, @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') - @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_data_for_decision') + @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_device_data_for_decision') def test_execute_fake_data_single_inquiry(self, process_data_mock, message_mock, user_input_mock): """Test that fake data does not use the decision maker""" @@ -275,7 +275,7 @@ def test_execute_fake_data_single_inquiry(self, process_data_mock, message_mock, @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') - @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_data_for_decision') + @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_device_data_for_decision') def test_max_inq_len(self, process_data_mock, message_mock, user_input_mock): """Test stoppage criteria for the max inquiry length""" @@ -314,7 +314,7 @@ def test_max_inq_len(self, process_data_mock, message_mock, @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') - @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_data_for_decision') + @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_device_data_for_decision') def test_spelling_complete(self, process_data_mock, message_mock, user_input_mock): """Test that the task stops when the copy_phrase has been correctly spelled.""" @@ -369,7 +369,7 @@ def test_spelled_letters(self): self.assertEqual(task.starting_spelled_letters(), 0) def test_stims_for_eeg(self): - """The correct stims should be sent to get_data_for_decision""" + """The correct stims should be sent to get_device_data_for_decision""" task = RSVPCopyPhraseTask(win=self.win, daq=self.daq, parameters=self.parameters, @@ -415,7 +415,7 @@ def test_stims_for_eeg(self): @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') - @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_data_for_decision') + @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_device_data_for_decision') def test_next_letter(self, process_data_mock, message_mock, user_input_mock): """Test that the task stops when the copy_phrase has been correctly spelled.""" @@ -444,7 +444,7 @@ def test_next_letter(self, process_data_mock, message_mock, @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') - @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_data_for_decision') + @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_device_data_for_decision') def test_execute_fake_data_with_preview(self, process_data_mock, message_mock, user_input_mock): """Test that preview is displayed""" @@ -480,7 +480,7 @@ def test_execute_fake_data_with_preview(self, process_data_mock, message_mock, @patch('bcipy.task.paradigm.rsvp.copy_phrase.init_evidence_evaluator') @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') - @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_data_for_decision') + @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_device_data_for_decision') def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, user_input_mock, init_evaluator_mock): """Test that fake data does not use the decision maker""" @@ -660,16 +660,17 @@ def mock_inquiry_timings(): def mock_process_data(): - """Generator that yields data mocking the get_data_for_decision helper""" - raw_data = None - triggers = [('+', 0.0), ('H', 0.4680980280973017), - ('C', 0.6852016930934042), ('D', 0.9016020260751247), - ('<', 1.1184057840146124), ('I', 1.335060202050954), - ('E', 1.552058998029679), ('B', 1.7685756811406463), - ('F', 1.9853776029776782), ('A', 2.202271921094507), - ('G', 2.4189279531128705)] - return (raw_data, triggers) + """Generator that yields data mocking the get_device_data_for_decision helper""" + return {ContentType.EEG: None} +def mock_triggers(): + """Mocks data from the task relative_triggers helper""" + return [('+', 0.0), ('H', 0.4680980280973017), ('C', 0.6852016930934042), + ('D', 0.9016020260751247), ('<', 1.1184057840146124), + ('I', 1.335060202050954), ('E', 1.552058998029679), + ('B', 1.7685756811406463), ('F', 1.9853776029776782), + ('A', 2.202271921094507), ('G', 2.4189279531128705)] + if __name__ == '__main__': unittest.main() From ac8077ac32840c90a4c05b4b869536c4f3f214f9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 21 Jun 2023 15:47:22 -0700 Subject: [PATCH 039/330] Cleanup and bug fixes --- bcipy/acquisition/protocols/lsl/lsl_client.py | 18 +++++++++++------- .../acquisition/protocols/lsl/lsl_recorder.py | 5 ++++- bcipy/helpers/load.py | 4 +++- bcipy/helpers/session.py | 6 +----- .../tests/paradigm/rsvp/test_copy_phrase.py | 1 + 5 files changed, 20 insertions(+), 14 deletions(-) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 1ea5c68b8..4a5937320 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -2,16 +2,18 @@ import logging from typing import List -from pylsl import StreamInfo, StreamInlet, local_clock, resolve_stream, resolve_byprop +from pylsl import (StreamInfo, StreamInlet, local_clock, resolve_byprop, + resolve_stream) -from bcipy.acquisition.devices import DEFAULT_DEVICE_TYPE, DeviceSpec, IRREGULAR_RATE +from bcipy.acquisition.devices import (DEFAULT_DEVICE_TYPE, IRREGULAR_RATE, + DeviceSpec) from bcipy.acquisition.exceptions import InvalidClockError from bcipy.acquisition.protocols.lsl.lsl_connector import (channel_names, check_device) from bcipy.acquisition.protocols.lsl.lsl_recorder import LslRecordingThread from bcipy.acquisition.record import Record -from bcipy.helpers.clock import Clock from bcipy.gui.viewer.ring_buffer import RingBuffer +from bcipy.helpers.clock import Clock log = logging.getLogger(__name__) @@ -101,13 +103,15 @@ def first_sample_time(self) -> float: def stop_acquisition(self) -> None: """Disconnect from the data source.""" - log.debug("Stopping Acquisition...") - if self.inlet: - self.inlet.close_stream() - self.inlet = None + log.debug(f"Stopping Acquisition from {self.device_spec.name} ...") if self.recorder: + log.debug(f"Closing {self.device_spec.name} data recorder") self.recorder.stop() self.recorder.join() + if self.inlet: + log.debug("Closing LSL connection") + self.inlet.close_stream() + self.inlet = None self.buffer = None diff --git a/bcipy/acquisition/protocols/lsl/lsl_recorder.py b/bcipy/acquisition/protocols/lsl/lsl_recorder.py index 4f9f5d3fc..9a8228adb 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_recorder.py +++ b/bcipy/acquisition/protocols/lsl/lsl_recorder.py @@ -7,7 +7,8 @@ from pylsl import StreamInfo, StreamInlet, resolve_streams from bcipy.acquisition.devices import DeviceSpec -from bcipy.acquisition.protocols.lsl.lsl_connector import channel_names, check_device +from bcipy.acquisition.protocols.lsl.lsl_connector import (channel_names, + check_device) from bcipy.acquisition.util import StoppableThread from bcipy.helpers.raw_data import RawDataWriter @@ -220,6 +221,7 @@ def run(self): log.info(f"Total recorded seconds: {self.recorded_seconds}") log.info(f"Total recorded samples: {self.sample_count}") inlet.close_stream() + inlet = None self._cleanup() @@ -243,6 +245,7 @@ def main(path: str, seconds: int = 5, debug: bool = False): if __name__ == '__main__': import argparse + # pylint: disable=invalid-name parser = argparse.ArgumentParser() parser.add_argument('--path', default='.') diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index bb5536cf2..c00e4c815 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -212,7 +212,9 @@ def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: models = [] for file_path in path.glob(f"*{SIGNAL_MODEL_FILE_SUFFIX}"): with open(file_path, "rb") as file: - models.append(pickle.load(file)) + model = pickle.load(file) + log.info(f"Loading model {model}") + models.append(model) return models diff --git a/bcipy/helpers/session.py b/bcipy/helpers/session.py index bc7932ba2..071f8cd12 100644 --- a/bcipy/helpers/session.py +++ b/bcipy/helpers/session.py @@ -231,7 +231,7 @@ def session_excel(session: Session, # Write rows inq_background = next(backgrounds_iter) - alp_len = None + alp_len = len(session.symbol_set) for i, record in enumerate(evidence_records(session)): rownum = i + 2 # Excel is 1-indexed; also account for column row. border = default_border @@ -244,10 +244,6 @@ def session_excel(session: Session, if record.inquiry != inquiry: inquiry = record.inquiry - - # Set the alphabet length used for chart data ranges. - if not alp_len and i > 0: - alp_len = i chart_data[f"Series {series} inquiry {inquiry}"] = rownum # Toggle the background for each inquiry for easier viewing. diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index f6dac8745..d84b2f9c9 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -672,5 +672,6 @@ def mock_triggers(): ('B', 1.7685756811406463), ('F', 1.9853776029776782), ('A', 2.202271921094507), ('G', 2.4189279531128705)] + if __name__ == '__main__': unittest.main() From 369c851c4ee22520229c86745288f5ca04858c92 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 10 Jul 2023 17:36:06 -0700 Subject: [PATCH 040/330] Refactored function and parameter names for clarity --- bcipy/helpers/demo/demo_stimuli_generation.py | 18 +- bcipy/helpers/stimuli.py | 103 +++--- bcipy/helpers/tests/test_stimuli.py | 301 ++++++++++-------- bcipy/task/paradigm/matrix/calibration.py | 20 +- .../paradigm/rsvp/calibration/calibration.py | 40 +-- 5 files changed, 264 insertions(+), 218 deletions(-) diff --git a/bcipy/helpers/demo/demo_stimuli_generation.py b/bcipy/helpers/demo/demo_stimuli_generation.py index e947f99ac..0518fb206 100644 --- a/bcipy/helpers/demo/demo_stimuli_generation.py +++ b/bcipy/helpers/demo/demo_stimuli_generation.py @@ -1,4 +1,4 @@ -from bcipy.helpers.stimuli import StimuliOrder, calibration_inquiry_generator, best_case_rsvp_inq_gen +from bcipy.helpers.stimuli import StimuliOrder, generate_calibration_inquiries, best_case_rsvp_inq_gen import numpy as np @@ -13,10 +13,10 @@ def _demo_random_rsvp_inquiry_generator(): len_samples)) print('Alphabet:{}'.format(alp)) - schedule = calibration_inquiry_generator(alp=alp, - stim_number=num_samples, - stim_length=len_samples, - stim_order=StimuliOrder.RANDOM) + schedule = generate_calibration_inquiries(alp=alp, + inquiry_count=num_samples, + stim_per_inquiry=len_samples, + stim_order=StimuliOrder.RANDOM) inquiries = schedule[0] timing = schedule[1] color = schedule[2] @@ -40,10 +40,10 @@ def _demo_alphabetical_rsvp_inquiry_generator(): len_samples)) print('Alphabet:{}'.format(alp)) - schedule = calibration_inquiry_generator(alp=alp, - stim_number=num_samples, - stim_length=len_samples, - stim_order=StimuliOrder.ALPHABETICAL) + schedule = generate_calibration_inquiries(alp=alp, + inquiry_count=num_samples, + stim_per_inquiry=len_samples, + stim_order=StimuliOrder.ALPHABETICAL) inquiries = schedule[0] timing = schedule[1] color = schedule[2] diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index a03b99313..1a2ebbe53 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -3,27 +3,26 @@ import logging import random import re - from abc import ABC, abstractmethod from enum import Enum from os import path, sep -from typing import Iterator, List, Tuple, NamedTuple, Optional +from typing import Iterator, List, NamedTuple, Optional, Tuple + +from PIL import Image from bcipy.helpers.exceptions import BciPyCoreException from bcipy.helpers.list import grouper -from PIL import Image # Prevents pillow from filling the console with debug info logging.getLogger('PIL').setLevel(logging.WARNING) -from psychopy import core +import mne import numpy as np import sounddevice as sd import soundfile as sf from mne import Annotations, Epochs from mne.io import RawArray -import mne - +from psychopy import core log = logging.getLogger(__name__) DEFAULT_FIXATION_PATH = 'bcipy/static/images/main/PLUS.png' @@ -426,8 +425,8 @@ def best_case_rsvp_inq_gen(alp: list, color(list[str]): Task specific color for generator First element is the target, second element is the fixation Observe that [-1] element represents the trial information - stim_number(int): number of random stimuli to be created - stim_length(int): number of trials in a inquiry + inquiry_count(int): number of random stimuli to be created + stim_per_inquiry(int): number of trials in a inquiry stim_order(StimuliOrder): ordering of stimuli in the inquiry inq_constants(list[str]): list of letters that should always be included in every inquiry. If provided, must be alp items. @@ -480,19 +479,18 @@ def best_case_rsvp_inq_gen(alp: list, return InquirySchedule(samples, times, colors) -def calibration_inquiry_generator( +def generate_calibration_inquiries( alp: List[str], - timing: List[float] = [0.5, 1, 0.2], + timing: List[float] = None, jitter: Optional[int] = None, - color: List[str] = ['green', 'red', 'white'], - stim_number: int = 10, - stim_length: int = 10, + color: List[str] = None, + inquiry_count: int = 10, + stim_per_inquiry: int = 10, stim_order: StimuliOrder = StimuliOrder.RANDOM, target_positions: TargetPositions = TargetPositions.RANDOM, - nontarget_inquiries: int = 10, + percentage_without_target: int = 10, is_txt: bool = True) -> InquirySchedule: - """Calibration Inquiry Generator. - + """ Generates inquiries with target letters in all possible positions. Parameters @@ -503,12 +501,12 @@ def calibration_inquiry_generator( jitter(int): jitter for stimuli timing. If None, no jitter is applied. color(list[str]): Task specific color for generator [target, fixation, stimuli] - stim_number(int): number of trials in a inquiry - stim_length(int): number of random stimuli to be created + inquiry_count(int): number of inquiries in a calibration + stim_per_inquiry(int): number of stimuli in each inquiry stim_order(StimuliOrder): ordering of stimuli in the inquiry target_positions(TargetPositions): positioning of targets to select for the inquiries - nontarget_inquiries(int): percentage of inquiries for which target letter flashed is not in inquiry - is_txt(bool): whether or not the stimuli type is text. False would be an image stimuli. + percentage_without_target(int): percentage of inquiries for which target letter flashed is not in inquiry + is_txt(bool): whether the stimuli type is text. False would be an image stimuli. Return ------ @@ -517,24 +515,28 @@ def calibration_inquiry_generator( timing(list[list[float]]): list of timings color(list(list[str])): list of colors)): scheduled inquiries """ + if timing is None: + timing = [0.5, 1, 0.2] + if color is None: + color = ['green', 'red', 'white'] assert len(timing) == 3, "timing must include values for [target, fixation, stimuli]" target_indexes = [] no_target = None - if (target_positions == target_positions.DISTRIBUTED): - target_indexes = distributed_target_positions(stim_number, stim_length, nontarget_inquiries) + if target_positions == TargetPositions.DISTRIBUTED: + target_indexes = distributed_target_positions(inquiry_count, stim_per_inquiry, percentage_without_target) else: # make list of random targets with correct number of non-target inquiries - num_nontarget_inquiry = int((nontarget_inquiries / 100) * stim_number) - num_target_inquiry = stim_number - num_nontarget_inquiry + num_nontarget_inquiry = int((percentage_without_target / 100) * inquiry_count) + num_target_inquiry = inquiry_count - num_nontarget_inquiry target_indexes = [no_target] * num_nontarget_inquiry - target_indexes.extend(random.choices(range(stim_length), k=num_target_inquiry)) + target_indexes.extend(random.choices(range(stim_per_inquiry), k=num_target_inquiry)) random.shuffle(target_indexes) samples, times, colors = [], [], [] - for i in range(stim_number): - inquiry = random.sample(alp, k=stim_length) + for i in range(inquiry_count): + inquiry = random.sample(alp, k=stim_per_inquiry) if stim_order == StimuliOrder.ALPHABETICAL: inquiry = alphabetize(inquiry) @@ -554,13 +556,13 @@ def calibration_inquiry_generator( # pull out timing for the inquiry stimuli stim_time = timing[-1] if jitter: - _inq_timing = jittered_timing(stim_time, jitter, stim_length) + _inq_timing = jittered_timing(stim_time, jitter, stim_per_inquiry) inq_timing = init_timing + _inq_timing else: - inq_timing = init_timing + [stim_time] * stim_length + inq_timing = init_timing + [stim_time] * stim_per_inquiry times.append(inq_timing) colors.append([color[i] for i in range(len(color) - 1)] + - [color[-1]] * stim_length) + [color[-1]] * stim_per_inquiry) return InquirySchedule(samples, times, colors) @@ -575,14 +577,14 @@ def jittered_timing(time: float, jitter: float, stim_count: int) -> List[float]: return np.random.uniform(low=time - jitter, high=time + jitter, size=(stim_count,)).tolist() -def distributed_target_positions(stim_number: int, stim_length: int, nontarget_inquiries: int) -> list: +def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, percentage_without_target: int) -> list: """Distributed Target Positions. Generates evenly distributed target positions, including target letter not flashed at all, and shuffles them. Args: - stim_number(int): Number of trials in calibration - stim_length(int): Number of stimuli in each inquiry - nontarget_inquiries(int): percentage of inquiries for which target letter flashed is not in inquiry + inquiry_count(int): Number of inquiries in calibration + stim_per_inquiry(int): Number of stimuli in each inquiry + percentage_without_target(int): percentage of inquiries for which target letter flashed is not in inquiry Return distributed_target_positions(list): targets: array of target indexes to be chosen """ @@ -591,21 +593,21 @@ def distributed_target_positions(stim_number: int, stim_length: int, nontarget_i no_target = None # find number of target and nontarget inquiries - num_nontarget_inquiry = int(stim_number * (nontarget_inquiries / 100)) - num_target_inquiry = stim_number - num_nontarget_inquiry + num_nontarget_inquiry = int(inquiry_count * (percentage_without_target / 100)) + num_target_inquiry = inquiry_count - num_nontarget_inquiry # find number each target position is repeated, and remaining number - num_pos = (int)(num_target_inquiry / stim_length) - num_rem_pos = (num_target_inquiry % stim_length) + num_pos = (int)(num_target_inquiry / stim_per_inquiry) + num_rem_pos = (num_target_inquiry % stim_per_inquiry) # add correct number of None's for nontarget inquiries targets = [no_target] * num_nontarget_inquiry # add distributed list of target positions - targets.extend(list(range(stim_length)) * num_pos) + targets.extend(list(range(stim_per_inquiry)) * num_pos) # pick leftover positions randomly - rem_pos = list(range(stim_length)) + rem_pos = list(range(stim_per_inquiry)) random.shuffle(rem_pos) rem_pos = rem_pos[0:num_rem_pos] targets.extend(rem_pos) @@ -615,6 +617,27 @@ def distributed_target_positions(stim_number: int, stim_length: int, nontarget_i return targets +def target_index(inquiry: List[str]) -> int: + """Given an inquiry, return the index of the target within the choices and + None if the target is not included as a choice. + + Parameters + ---------- + inquiry - list of [target, fixation, *choices] + + >>> inquiry = ['T', '+', 'G', 'J', 'K', 'L', 'M', 'Q', 'T', 'V', 'X', '<'] + >>> target_index(inquiry) + 6 + >>> inquiry = ['A', '+', 'G', 'J', 'K', 'L', 'M', 'Q', 'T', 'V', 'X', '<'] + >>> target_index(inquiry) + None + """ + assert len(inquiry) > 3, "Not enough choices" + target, _fixation, *choices = inquiry + try: + return choices.index(target) + except ValueError: + return None def get_task_info(experiment_length: int, task_color: str) -> Tuple[List[str], List[str]]: """Get Task Info. diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 829cb5801..bded90fc1 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -1,39 +1,43 @@ +import collections as cnt import glob import unittest - from os import path -from mockito import any, mock, unstub, verify, when -from psychopy import core import numpy as np import sounddevice as sd import soundfile as sf +from mockito import any, mock, unstub, verify, when +from psychopy import core -import collections as cnt from bcipy.helpers.exceptions import BciPyCoreException - -from bcipy.helpers.stimuli import ( - alphabetize, - best_case_rsvp_inq_gen, - best_selection, - calibration_inquiry_generator, - DEFAULT_FIXATION_PATH, - get_fixation, - TrialReshaper, - InquiryReshaper, - jittered_timing, - play_sound, - distributed_target_positions, - soundfiles, - StimuliOrder, - ssvep_to_code, - TargetPositions, - update_inquiry_timing, -) +from bcipy.helpers.stimuli import (DEFAULT_FIXATION_PATH, InquiryReshaper, + StimuliOrder, TargetPositions, + TrialReshaper, alphabetize, + best_case_rsvp_inq_gen, best_selection, + generate_calibration_inquiries, + distributed_target_positions, get_fixation, + jittered_timing, play_sound, soundfiles, + ssvep_to_code, target_index, + update_inquiry_timing) MOCK_FS = 44100 +def is_uniform_distribution(inquiry_count: int, stim_per_inquiry: int, + pct_without_target: int, + counter: cnt.Counter) -> bool: + """Determine if the counts in the provided counter are distributed + uniformly.""" + + count_without_target = (int)(inquiry_count * (pct_without_target / 100)) + target_inquiries = inquiry_count - count_without_target + num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) + + return all( + num_target_inquiries <= counter[i] <= num_target_inquiries + 1 + for i in counter if counter[i] is not None + ) + class TestStimuliGeneration(unittest.TestCase): """This is Test Case for Stimuli Generated via BciPy.""" @@ -47,34 +51,34 @@ def tearDown(self): unstub() def test_calibration_inquiry_generator_with_jitter(self): - stim_number = 10 - stim_length = 10 + inquiry_count = 10 + stim_per_inquiry = 10 stim_timing = [0.5, 1, 2] stim_jitter = 1 max_jitter = stim_timing[-1] + stim_jitter min_jitter = stim_timing[-1] - stim_jitter - inquiries, inq_timings, inq_colors = calibration_inquiry_generator( + inquiries, inq_timings, inq_colors = generate_calibration_inquiries( self.alp, timing=stim_timing, - stim_number=stim_number, - stim_length=stim_length, + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, jitter=stim_jitter) self.assertEqual( - len(inquiries), stim_number, + len(inquiries), inquiry_count, 'Should have produced the correct number of inquiries') - self.assertEqual(len(inq_timings), stim_number) - self.assertEqual(len(inq_colors), stim_number) + self.assertEqual(len(inq_timings), inquiry_count) + self.assertEqual(len(inq_colors), inquiry_count) inq_strings = [] for inq in inquiries: self.assertEqual( - len(inq), stim_length + 2, + len(inq), stim_per_inquiry + 2, ('inquiry should include the correct number of choices as ', 'well as the target and cross.')) choices = inq[2:] - self.assertEqual(stim_length, len(set(choices)), + self.assertEqual(stim_per_inquiry, len(set(choices)), 'All choices should be unique') # create a string of the options @@ -96,28 +100,28 @@ def test_calibration_inquiry_generator_with_jitter(self): def test_calibration_inquiry_generator_random_order(self): """Test generation of random inquiries""" - stim_number = 10 - stim_length = 10 - inquiries, inq_timings, inq_colors = calibration_inquiry_generator( + inquiry_count = 10 + stim_per_inquiry = 10 + inquiries, inq_timings, inq_colors = generate_calibration_inquiries( self.alp, - stim_number=stim_number, - stim_length=stim_length, + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, stim_order=StimuliOrder.RANDOM) self.assertEqual( - len(inquiries), stim_number, + len(inquiries), inquiry_count, 'Should have produced the correct number of inquiries') - self.assertEqual(len(inq_timings), stim_number) - self.assertEqual(len(inq_colors), stim_number) + self.assertEqual(len(inq_timings), inquiry_count) + self.assertEqual(len(inq_colors), inquiry_count) inq_strings = [] for inq in inquiries: self.assertEqual( - len(inq), stim_length + 2, + len(inq), stim_per_inquiry + 2, ('inquiry should include the correct number of choices as ', 'well as the target and cross.')) choices = inq[2:] - self.assertEqual(stim_length, len(set(choices)), + self.assertEqual(stim_per_inquiry, len(set(choices)), 'All choices should be unique') # create a string of the options @@ -129,28 +133,28 @@ def test_calibration_inquiry_generator_random_order(self): def test_calibration_inquiry_generator_alphabetical_order(self): """Test generation of random inquiries""" - stim_number = 10 - stim_length = 10 - inquiries, inq_timings, inq_colors = calibration_inquiry_generator( + inquiry_count = 10 + stim_per_inquiry = 10 + inquiries, inq_timings, inq_colors = generate_calibration_inquiries( self.alp, - stim_number=stim_number, - stim_length=stim_length, + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, stim_order=StimuliOrder.ALPHABETICAL) self.assertEqual( - len(inquiries), stim_number, + len(inquiries), inquiry_count, 'Should have produced the correct number of inquiries') - self.assertEqual(len(inq_timings), stim_number) - self.assertEqual(len(inq_colors), stim_number) + self.assertEqual(len(inq_timings), inquiry_count) + self.assertEqual(len(inq_colors), inquiry_count) inq_strings = [] for inq in inquiries: self.assertEqual( - len(inq), stim_length + 2, + len(inq), stim_per_inquiry + 2, ('inquiry should include the correct number of choices as ', 'well as the target and cross.')) choices = inq[2:] - self.assertEqual(stim_length, len(set(choices)), + self.assertEqual(stim_per_inquiry, len(set(choices)), 'All choices should be unique') self.assertEqual(alphabetize(choices), choices) @@ -161,33 +165,42 @@ def test_calibration_inquiry_generator_alphabetical_order(self): len(inquiries), len(set(inq_strings)), 'All inquiries should be different') + def test_target_index(self): + """Test target_index function""" + inquiry = ['T', '+', 'G', 'J', 'K', 'L', 'M', 'Q', 'T', 'V', 'X', '<'] + self.assertEqual(target_index(inquiry), 6) + + inquiry = ['A', '+', 'G', 'J', 'K', 'L', 'M', 'Q', 'T', 'V', 'X', '<'] + self.assertEqual(target_index(inquiry), None) + + def test_calibration_inquiry_generator_distributed_targets(self): """Test generation of inquiries with distributed target positions""" - stim_number = 10 - stim_length = 10 - nontarget_inquiries = 10 - inquiries, inq_timings, inq_colors = calibration_inquiry_generator( + inquiry_count = 10 + stim_per_inquiry = 10 + percentage_without_target = 10 + inquiries, inq_timings, inq_colors = generate_calibration_inquiries( self.alp, - stim_number=stim_number, - stim_length=stim_length, + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, stim_order=StimuliOrder.RANDOM, target_positions=TargetPositions.DISTRIBUTED, - nontarget_inquiries=nontarget_inquiries) + percentage_without_target=percentage_without_target) self.assertEqual( - len(inquiries), stim_number, + len(inquiries), inquiry_count, 'Should have produced the correct number of inquiries') - self.assertEqual(len(inq_timings), stim_number) - self.assertEqual(len(inq_colors), stim_number) + self.assertEqual(len(inq_timings), inquiry_count) + self.assertEqual(len(inq_colors), inquiry_count) inq_strings = [] for inq in inquiries: self.assertEqual( - len(inq), stim_length + 2, + len(inq), stim_per_inquiry + 2, ('inquiry should include the correct number of choices as ', 'well as the target and cross.')) choices = inq[2:] - self.assertEqual(stim_length, len(set(choices)), + self.assertEqual(stim_per_inquiry, len(set(choices)), 'All choices should be unique') # create a string of the options @@ -197,33 +210,45 @@ def test_calibration_inquiry_generator_distributed_targets(self): len(inquiries), len(set(inq_strings)), 'All inquiries should be different') + # Test distribution + nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) + target_inquiries = inquiry_count - nontarget_inquiry + num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) + + indices = [target_index(inq) for inq in inquiries] + counter = cnt.Counter(indices) + for i in counter: + self.assertTrue( + num_target_inquiries <= counter[i] <= num_target_inquiries + 1) + + def test_calibration_inquiry_generator_distributed_targets_alphabetical(self): """Test generation of inquiries with distributed target positions""" - stim_number = 10 - stim_length = 10 - nontarget_inquiries = 20 - inquiries, inq_timings, inq_colors = calibration_inquiry_generator( + inquiry_count = 10 + stim_per_inquiry = 10 + percentage_without_target = 20 + inquiries, inq_timings, inq_colors = generate_calibration_inquiries( self.alp, - stim_number=stim_number, - stim_length=stim_length, + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, stim_order=StimuliOrder.ALPHABETICAL, target_positions=TargetPositions.DISTRIBUTED, - nontarget_inquiries=nontarget_inquiries) + percentage_without_target=percentage_without_target) self.assertEqual( - len(inquiries), stim_number, + len(inquiries), inquiry_count, 'Should have produced the correct number of inquiries') - self.assertEqual(len(inq_timings), stim_number) - self.assertEqual(len(inq_colors), stim_number) + self.assertEqual(len(inq_timings), inquiry_count) + self.assertEqual(len(inq_colors), inquiry_count) inq_strings = [] for inq in inquiries: self.assertEqual( - len(inq), stim_length + 2, + len(inq), stim_per_inquiry + 2, ('inquiry should include the correct number of choices as ', 'well as the target and cross.')) choices = inq[2:] - self.assertEqual(stim_length, len(set(choices)), + self.assertEqual(stim_per_inquiry, len(set(choices)), 'All choices should be unique') # create a string of the options @@ -235,31 +260,31 @@ def test_calibration_inquiry_generator_distributed_targets_alphabetical(self): def test_calibration_inquiry_generator_distributed_targets_no_nontargets(self): """Test generation of inquiries with distributed target positions and no nontarget inquiries.""" - stim_number = 10 - stim_length = 10 - nontarget_inquiries = 0 - inquiries, inq_timings, inq_colors = calibration_inquiry_generator( + inquiry_count = 10 + stim_per_inquiry = 10 + percentage_without_target = 0 + inquiries, inq_timings, inq_colors = generate_calibration_inquiries( self.alp, - stim_number=stim_number, - stim_length=stim_length, + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, stim_order=StimuliOrder.RANDOM, target_positions=TargetPositions.DISTRIBUTED, - nontarget_inquiries=nontarget_inquiries) + percentage_without_target=percentage_without_target) self.assertEqual( - len(inquiries), stim_number, + len(inquiries), inquiry_count, 'Should have produced the correct number of inquiries') - self.assertEqual(len(inq_timings), stim_number) - self.assertEqual(len(inq_colors), stim_number) + self.assertEqual(len(inq_timings), inquiry_count) + self.assertEqual(len(inq_colors), inquiry_count) inq_strings = [] for inq in inquiries: self.assertEqual( - len(inq), stim_length + 2, + len(inq), stim_per_inquiry + 2, ('inquiry should include the correct number of choices as ', 'well as the target and cross.')) choices = inq[2:] - self.assertEqual(stim_length, len(set(choices)), + self.assertEqual(stim_per_inquiry, len(set(choices)), 'All choices should be unique') # create a string of the options @@ -269,29 +294,31 @@ def test_calibration_inquiry_generator_distributed_targets_no_nontargets(self): len(inquiries), len(set(inq_strings)), 'All inquiries should be different') + # Ensure all inquiries include the target + for inq in inquiries: + self.assertIsNotNone(target_index(inq)) + def test_calibration_inquiry_generator_distributed_targets_positions(self): """Test generation of distributed target positions with nontarget inquiries.""" - stim_number = 11 - stim_length = 10 - nontarget_inquiries = 10 + inquiry_count = 11 + stim_per_inquiry = 10 + percentage_without_target = 10 - nontarget_inquiry = (int)(stim_number * (nontarget_inquiries / 100)) - target_inquiries = stim_number - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_length) + nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) + target_inquiries = inquiry_count - nontarget_inquiry + num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) - targets = distributed_target_positions(stim_number=stim_number, - stim_length=stim_length, - nontarget_inquiries=nontarget_inquiries) + targets = distributed_target_positions(inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), stim_number, + len(targets), inquiry_count, 'Should have produced the correct number of targets for inquiries.') # count how many times each target position is used - count = cnt.Counter() - for pos in targets: - count[pos] += 1 + count = cnt.Counter(targets) # make sure position counts are equally distributed, including non-target for i in count: @@ -300,26 +327,24 @@ def test_calibration_inquiry_generator_distributed_targets_positions(self): def test_calibration_inquiry_generator_distributed_targets_positions_half_nontarget(self): """Test generation of distributed target positions with half being nontarget inquiries.""" - stim_number = 120 - stim_length = 9 - nontarget_inquiries = 50 + inquiry_count = 120 + stim_per_inquiry = 9 + percentage_without_target = 50 - nontarget_inquiry = (int)(stim_number * (nontarget_inquiries / 100)) - target_inquiries = stim_number - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_length) + nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) + target_inquiries = inquiry_count - nontarget_inquiry + num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) - targets = distributed_target_positions(stim_number=stim_number, - stim_length=stim_length, - nontarget_inquiries=nontarget_inquiries) + targets = distributed_target_positions(inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), stim_number, + len(targets), inquiry_count, 'Should have produced the correct number of targets for inquiries.') # count how many times each target position is used - count = cnt.Counter() - for pos in targets: - count[pos] += 1 + count = cnt.Counter(targets) # make sure target position counts are equally distributed for i in count: @@ -333,26 +358,24 @@ def test_calibration_inquiry_generator_distributed_targets_positions_half_nontar def test_calibration_inquiry_generator_distributed_targets_positions_no_nontargets(self): """Test generation of distributed target positions with no nontarget inquiries.""" - stim_number = 50 - stim_length = 11 - nontarget_inquiries = 0 + inquiry_count = 50 + stim_per_inquiry = 11 + percentage_without_target = 0 - nontarget_inquiry = (int)(stim_number * (nontarget_inquiries / 100)) - target_inquiries = stim_number - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_length) + nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) + target_inquiries = inquiry_count - nontarget_inquiry + num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) - targets = distributed_target_positions(stim_number=stim_number, - stim_length=stim_length, - nontarget_inquiries=nontarget_inquiries) + targets = distributed_target_positions(inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), stim_number, + len(targets), inquiry_count, 'Should have produced the correct number of targets for inquiries.') # count how many times each target position is used - count = cnt.Counter() - for pos in targets: - count[pos] += 1 + count = cnt.Counter(targets) # make sure target position counts are equally distributed for i in count: @@ -366,21 +389,21 @@ def test_calibration_inquiry_generator_distributed_targets_positions_no_nontarge def test_calibration_inquiry_generator_distributed_targets_all_nontargets(self): """Test generation of distributed target positions with all inquiries being non-target.""" - stim_number = 100 - stim_length = 6 - nontarget_inquiries = 100 + inquiry_count = 100 + stim_per_inquiry = 6 + percentage_without_target = 100 - nontarget_inquiry = (int)(stim_number * (nontarget_inquiries / 100)) - target_inquiries = stim_number - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_length) + nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) + target_inquiries = inquiry_count - nontarget_inquiry + num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) targets = distributed_target_positions( - stim_number=stim_number, - stim_length=stim_length, - nontarget_inquiries=nontarget_inquiries) + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), stim_number, + len(targets), inquiry_count, 'Should have produced the correct number of targets for inquiries.') # count how many times each target position is used @@ -394,7 +417,7 @@ def test_calibration_inquiry_generator_distributed_targets_all_nontargets(self): self.assertTrue(num_target_inquiries <= count[i] <= num_target_inquiries + 1) # make sure all inquries are non-target inquiries - self.assertEqual(count[None], stim_number, + self.assertEqual(count[None], inquiry_count, 'Should have produced all non-target positions.') def test_best_selection(self): diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index c4236ef24..ecc21d986 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -7,15 +7,15 @@ from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.helpers.clock import Clock -from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, StimuliOrder, - TargetPositions, - calibration_inquiry_generator, - InquirySchedule) +from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, InquirySchedule, + StimuliOrder, TargetPositions, + generate_calibration_inquiries) +from bcipy.helpers.symbols import alphabet from bcipy.helpers.task import (get_user_input, pause_calibration, trial_complete_message) -from bcipy.helpers.triggers import TriggerHandler, TriggerType, Trigger, FlushFrequency, convert_timing_triggers +from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, + TriggerType, convert_timing_triggers) from bcipy.task import Task -from bcipy.helpers.symbols import alphabet class MatrixCalibrationTask(Task): @@ -96,14 +96,14 @@ def generate_stimuli(self) -> InquirySchedule: timing(list[list[float]]): list of timings color(list(list[str])): list of colors) """ - return calibration_inquiry_generator( + return generate_calibration_inquiries( self.symbol_set, - stim_number=self.stim_number, - stim_length=self.stim_length, + inquiry_count=self.stim_number, + stim_per_inquiry=self.stim_length, stim_order=self.stim_order, jitter=self.jitter, target_positions=self.target_positions, - nontarget_inquiries=self.nontarget_inquiries, + percentage_without_target=self.nontarget_inquiries, timing=self.timing, color=self.color) diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index cd4538e59..6152bf873 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -1,20 +1,20 @@ -from psychopy import core from typing import List, Tuple +from psychopy import core + from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE -from bcipy.display import ( - InformationProperties, - PreviewInquiryProperties, - StimuliProperties) -from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay +from bcipy.display import (InformationProperties, PreviewInquiryProperties, + StimuliProperties) from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay from bcipy.helpers.clock import Clock - -from bcipy.helpers.stimuli import (StimuliOrder, TargetPositions, calibration_inquiry_generator) +from bcipy.helpers.stimuli import (StimuliOrder, TargetPositions, + generate_calibration_inquiries) +from bcipy.helpers.symbols import alphabet from bcipy.helpers.task import (get_user_input, pause_calibration, trial_complete_message) -from bcipy.helpers.symbols import alphabet -from bcipy.helpers.triggers import FlushFrequency, TriggerHandler, Trigger, TriggerType, convert_timing_triggers +from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, + TriggerType, convert_timing_triggers) from bcipy.task import Task @@ -91,16 +91,16 @@ def generate_stimuli(self): timing(list[list[float]]): list of timings color(list(list[str])): list of colors) """ - return calibration_inquiry_generator(self.alp, - stim_number=self.stim_number, - stim_length=self.stim_length, - stim_order=self.stim_order, - target_positions=self.target_positions, - nontarget_inquiries=self.nontarget_inquiries, - timing=self.timing, - jitter=self.jitter, - is_txt=self.rsvp.is_txt_stim, - color=self.color) + return generate_calibration_inquiries(self.alp, + inquiry_count=self.stim_number, + stim_per_inquiry=self.stim_length, + stim_order=self.stim_order, + target_positions=self.target_positions, + percentage_without_target=self.nontarget_inquiries, + timing=self.timing, + jitter=self.jitter, + is_txt=self.rsvp.is_txt_stim, + color=self.color) def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: """Trigger Type. From 023f8884400f39d3584414e4a8a7cb45fd8782bf Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 11 Jul 2023 17:43:25 -0700 Subject: [PATCH 041/330] Factored out test_stimuli to use a function for testing for uniform distribution. Factored out calculation of random_target_positions into its own function which could be thoroughly tested. Added unit tests for new function --- bcipy/helpers/stimuli.py | 46 ++- bcipy/helpers/tests/test_stimuli.py | 450 +++++++++++++++++----------- 2 files changed, 306 insertions(+), 190 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 1a2ebbe53..855707703 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -478,6 +478,7 @@ def best_case_rsvp_inq_gen(alp: list, [color[-1]] * stim_length) return InquirySchedule(samples, times, colors) +NO_TARGET_INDEX = None def generate_calibration_inquiries( alp: List[str], @@ -520,18 +521,15 @@ def generate_calibration_inquiries( if color is None: color = ['green', 'red', 'white'] assert len(timing) == 3, "timing must include values for [target, fixation, stimuli]" - target_indexes = [] - no_target = None + target_indexes = [] if target_positions == TargetPositions.DISTRIBUTED: - target_indexes = distributed_target_positions(inquiry_count, stim_per_inquiry, percentage_without_target) + target_indexes = distributed_target_positions( + inquiry_count, stim_per_inquiry, percentage_without_target) else: - # make list of random targets with correct number of non-target inquiries - num_nontarget_inquiry = int((percentage_without_target / 100) * inquiry_count) - num_target_inquiry = inquiry_count - num_nontarget_inquiry - target_indexes = [no_target] * num_nontarget_inquiry - target_indexes.extend(random.choices(range(stim_per_inquiry), k=num_target_inquiry)) - random.shuffle(target_indexes) + target_indexes = random_target_positions(inquiry_count, + stim_per_inquiry, + percentage_without_target) samples, times, colors = [], [], [] @@ -542,13 +540,12 @@ def generate_calibration_inquiries( inquiry = alphabetize(inquiry) target_index = target_indexes[i] - if target_index is no_target: + if target_index is NO_TARGET_INDEX: target = random.choice(list(set(alp) - set(inquiry))) else: target = inquiry[target_index] sample = [target, get_fixation(is_txt=is_txt), *inquiry] - samples.append(sample) # timing for fixation and prompt @@ -590,7 +587,6 @@ def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, perc """ targets = [] - no_target = None # find number of target and nontarget inquiries num_nontarget_inquiry = int(inquiry_count * (percentage_without_target / 100)) @@ -601,7 +597,7 @@ def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, perc num_rem_pos = (num_target_inquiry % stim_per_inquiry) # add correct number of None's for nontarget inquiries - targets = [no_target] * num_nontarget_inquiry + targets = [NO_TARGET_INDEX] * num_nontarget_inquiry # add distributed list of target positions targets.extend(list(range(stim_per_inquiry)) * num_pos) @@ -617,6 +613,30 @@ def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, perc return targets + +def random_target_positions(inquiry_count: int, stim_per_inquiry: int, + percentage_without_target: int) -> list: + """Generates randomly distributed target positions, including target letter + not flashed at all, and shuffles them. + + Args: + inquiry_count(int): Number of inquiries in calibration + stim_per_inquiry(int): Number of stimuli in each inquiry + percentage_without_target(int): percentage of inquiries for which + target letter flashed is not in inquiry + + Return list of target indexes to be chosen + """ + target_indexes = [] + num_nontarget_inquiry = int( + (percentage_without_target / 100) * inquiry_count) + num_target_inquiry = inquiry_count - num_nontarget_inquiry + target_indexes = [NO_TARGET_INDEX] * num_nontarget_inquiry + target_indexes.extend( + random.choices(range(stim_per_inquiry), k=num_target_inquiry)) + random.shuffle(target_indexes) + return target_indexes + def target_index(inquiry: List[str]) -> int: """Given an inquiry, return the index of the target within the choices and None if the target is not included as a choice. diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index bded90fc1..c37e658c5 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -1,6 +1,6 @@ -import collections as cnt import glob import unittest +from collections import Counter from os import path import numpy as np @@ -14,9 +14,10 @@ StimuliOrder, TargetPositions, TrialReshaper, alphabetize, best_case_rsvp_inq_gen, best_selection, + distributed_target_positions, generate_calibration_inquiries, - distributed_target_positions, get_fixation, - jittered_timing, play_sound, soundfiles, + get_fixation, jittered_timing, play_sound, + random_target_positions, soundfiles, ssvep_to_code, target_index, update_inquiry_timing) @@ -24,27 +25,27 @@ def is_uniform_distribution(inquiry_count: int, stim_per_inquiry: int, - pct_without_target: int, - counter: cnt.Counter) -> bool: + percentage_without_target: int, + counter: Counter) -> bool: """Determine if the counts in the provided counter are distributed uniformly.""" - count_without_target = (int)(inquiry_count * (pct_without_target / 100)) - target_inquiries = inquiry_count - count_without_target - num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) + nontarget_inquiries = (int)(inquiry_count * + (percentage_without_target / 100)) + target_inquiries = inquiry_count - nontarget_inquiries + expected_targets_per_position = (int)(target_inquiries / stim_per_inquiry) + + return all(expected_targets_per_position <= counter[pos] <= + expected_targets_per_position + 1 for pos in counter + if pos is not None) - return all( - num_target_inquiries <= counter[i] <= num_target_inquiries + 1 - for i in counter if counter[i] is not None - ) class TestStimuliGeneration(unittest.TestCase): """This is Test Case for Stimuli Generated via BciPy.""" alp = [ - 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', - 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', - '<', '_' + 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', + 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', '<', '_' ] def tearDown(self): @@ -88,15 +89,15 @@ def test_calibration_inquiry_generator_with_jitter(self): for j in inq_timings: inq_timing = j[2:] # remove the target presentaion and cross for inq_time in inq_timing: - self.assertTrue(min_jitter <= inq_time <= max_jitter, - 'Timing should be jittered and within the correct range') + self.assertTrue( + min_jitter <= inq_time <= max_jitter, + 'Timing should be jittered and within the correct range') self.assertTrue( len(set(inq_timing)) > 1, 'All choices should be unique') - self.assertEqual( - len(inquiries), len(set(inq_strings)), - 'All inquiries should be different') + self.assertEqual(len(inquiries), len(set(inq_strings)), + 'All inquiries should be different') def test_calibration_inquiry_generator_random_order(self): """Test generation of random inquiries""" @@ -127,9 +128,8 @@ def test_calibration_inquiry_generator_random_order(self): # create a string of the options inq_strings.append(''.join(choices)) - self.assertEqual( - len(inquiries), len(set(inq_strings)), - 'All inquiries should be different') + self.assertEqual(len(inquiries), len(set(inq_strings)), + 'All inquiries should be different') def test_calibration_inquiry_generator_alphabetical_order(self): """Test generation of random inquiries""" @@ -161,9 +161,8 @@ def test_calibration_inquiry_generator_alphabetical_order(self): # create a string of the options inq_strings.append(''.join(choices)) - self.assertEqual( - len(inquiries), len(set(inq_strings)), - 'All inquiries should be different') + self.assertEqual(len(inquiries), len(set(inq_strings)), + 'All inquiries should be different') def test_target_index(self): """Test target_index function""" @@ -173,10 +172,9 @@ def test_target_index(self): inquiry = ['A', '+', 'G', 'J', 'K', 'L', 'M', 'Q', 'T', 'V', 'X', '<'] self.assertEqual(target_index(inquiry), None) - def test_calibration_inquiry_generator_distributed_targets(self): """Test generation of inquiries with distributed target positions""" - inquiry_count = 10 + inquiry_count = 100 stim_per_inquiry = 10 percentage_without_target = 10 inquiries, inq_timings, inq_colors = generate_calibration_inquiries( @@ -206,25 +204,19 @@ def test_calibration_inquiry_generator_distributed_targets(self): # create a string of the options inq_strings.append(''.join(choices)) - self.assertEqual( - len(inquiries), len(set(inq_strings)), - 'All inquiries should be different') + self.assertEqual(len(inquiries), len(set(inq_strings)), + 'All inquiries should be different') # Test distribution - nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) - target_inquiries = inquiry_count - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) - - indices = [target_index(inq) for inq in inquiries] - counter = cnt.Counter(indices) - for i in counter: - self.assertTrue( - num_target_inquiries <= counter[i] <= num_target_inquiries + 1) + counter = Counter(target_index(inq) for inq in inquiries) + self.assertTrue( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, counter)) - - def test_calibration_inquiry_generator_distributed_targets_alphabetical(self): + def test_calibration_inquiry_generator_distributed_targets_alphabetical( + self): """Test generation of inquiries with distributed target positions""" - inquiry_count = 10 + inquiry_count = 100 stim_per_inquiry = 10 percentage_without_target = 20 inquiries, inq_timings, inq_colors = generate_calibration_inquiries( @@ -254,13 +246,13 @@ def test_calibration_inquiry_generator_distributed_targets_alphabetical(self): # create a string of the options inq_strings.append(''.join(choices)) - self.assertEqual( - len(inquiries), len(set(inq_strings)), - 'All inquiries should be different') + self.assertEqual(len(inquiries), len(set(inq_strings)), + 'All inquiries should be different') - def test_calibration_inquiry_generator_distributed_targets_no_nontargets(self): + def test_calibration_inquiry_generator_distributed_targets_no_nontargets( + self): """Test generation of inquiries with distributed target positions and no nontarget inquiries.""" - inquiry_count = 10 + inquiry_count = 100 stim_per_inquiry = 10 percentage_without_target = 0 inquiries, inq_timings, inq_colors = generate_calibration_inquiries( @@ -290,9 +282,8 @@ def test_calibration_inquiry_generator_distributed_targets_no_nontargets(self): # create a string of the options inq_strings.append(''.join(choices)) - self.assertEqual( - len(inquiries), len(set(inq_strings)), - 'All inquiries should be different') + self.assertEqual(len(inquiries), len(set(inq_strings)), + 'All inquiries should be different') # Ensure all inquiries include the target for inq in inquiries: @@ -305,119 +296,204 @@ def test_calibration_inquiry_generator_distributed_targets_positions(self): stim_per_inquiry = 10 percentage_without_target = 10 - nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) - target_inquiries = inquiry_count - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) - - targets = distributed_target_positions(inquiry_count=inquiry_count, - stim_per_inquiry=stim_per_inquiry, - percentage_without_target=percentage_without_target) + target_positions = distributed_target_positions( + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), inquiry_count, - 'Should have produced the correct number of targets for inquiries.') - - # count how many times each target position is used - count = cnt.Counter(targets) + len(target_positions), inquiry_count, + 'Should have produced the correct number of target_positions for inquiries.' + ) - # make sure position counts are equally distributed, including non-target - for i in count: - self.assertTrue(num_target_inquiries <= count[i] <= num_target_inquiries + 1) + self.assertTrue( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, + Counter(target_positions))) - def test_calibration_inquiry_generator_distributed_targets_positions_half_nontarget(self): + def test_calibration_inquiry_generator_distributed_targets_positions_half_nontarget( + self): """Test generation of distributed target positions with half being nontarget inquiries.""" inquiry_count = 120 stim_per_inquiry = 9 percentage_without_target = 50 - nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) - target_inquiries = inquiry_count - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) + nontarget_inquiries = (int)(inquiry_count * + (percentage_without_target / 100)) - targets = distributed_target_positions(inquiry_count=inquiry_count, - stim_per_inquiry=stim_per_inquiry, - percentage_without_target=percentage_without_target) + target_positions = distributed_target_positions( + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), inquiry_count, - 'Should have produced the correct number of targets for inquiries.') - + len(target_positions), inquiry_count, + 'Should have produced the correct number of target_positions for inquiries.' + ) # count how many times each target position is used - count = cnt.Counter(targets) - - # make sure target position counts are equally distributed - for i in count: - if i is not None: - self.assertTrue(num_target_inquiries <= count[i] <= num_target_inquiries + 1) + counter = Counter(target_positions) # make sure correct number of non-target inquiries - self.assertEqual(count[None], nontarget_inquiry, - 'Should have produced 50 percent of 120 non-target positions.') + self.assertEqual( + counter[None], nontarget_inquiries, + 'Should have produced 50 percent of 120 non-target positions.') - def test_calibration_inquiry_generator_distributed_targets_positions_no_nontargets(self): + self.assertTrue( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, counter)) + + def test_calibration_inquiry_generator_distributed_targets_positions_no_nontargets( + self): """Test generation of distributed target positions with no nontarget inquiries.""" inquiry_count = 50 stim_per_inquiry = 11 percentage_without_target = 0 - nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) - target_inquiries = inquiry_count - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) - - targets = distributed_target_positions(inquiry_count=inquiry_count, - stim_per_inquiry=stim_per_inquiry, - percentage_without_target=percentage_without_target) + target_positions = distributed_target_positions( + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), inquiry_count, - 'Should have produced the correct number of targets for inquiries.') + len(target_positions), inquiry_count, + 'Should have produced the correct number of target_positions for inquiries.' + ) # count how many times each target position is used - count = cnt.Counter(targets) + counter = Counter(target_positions) - # make sure target position counts are equally distributed - for i in count: - if i is not None: - self.assertTrue(num_target_inquiries <= count[i] <= num_target_inquiries + 1) + self.assertTrue( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, counter)) # make sure there are no non-target inquiries - self.assertEqual(count[None], 0, + self.assertEqual(counter[None], 0, 'Should have produced no non-target positions.') - def test_calibration_inquiry_generator_distributed_targets_all_nontargets(self): + def test_calibration_inquiry_generator_distributed_targets_all_nontargets( + self): """Test generation of distributed target positions with all inquiries being non-target.""" inquiry_count = 100 stim_per_inquiry = 6 percentage_without_target = 100 - nontarget_inquiry = (int)(inquiry_count * (percentage_without_target / 100)) - target_inquiries = inquiry_count - nontarget_inquiry - num_target_inquiries = (int)(target_inquiries / stim_per_inquiry) + target_positions = distributed_target_positions( + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) + + self.assertEqual( + len(target_positions), inquiry_count, + 'Should have produced the correct number of target_positions for inquiries.' + ) + + # count how many times each target position is used + counter = Counter(target_positions) + + self.assertTrue( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, counter)) + + # make sure all inquries are non-target inquiries + self.assertEqual(counter[None], inquiry_count, + 'Should have produced all non-target positions.') - targets = distributed_target_positions( + def test_random_target_positions(self): + """Test generation of random target positions with nontarget inquiries.""" + + inquiry_count = 100 + stim_per_inquiry = 10 + percentage_without_target = 10 + + target_positions = random_target_positions( + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) + + self.assertEqual( + len(target_positions), inquiry_count, + 'Should have produced the correct number of target_positions for inquiries.' + ) + counter = Counter(target_positions) + print(counter) + self.assertFalse( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, + counter)) + + def test_random_target_positions_half_nontarget(self): + """Test generation of random target positions with half being nontarget inquiries.""" + + inquiry_count = 120 + stim_per_inquiry = 9 + percentage_without_target = 50 + + target_positions = random_target_positions( + inquiry_count=inquiry_count, + stim_per_inquiry=stim_per_inquiry, + percentage_without_target=percentage_without_target) + + self.assertEqual( + len(target_positions), inquiry_count, + 'Should have produced the correct number of target_positions for inquiries.' + ) + # count how many times each target position is used + counter = Counter(target_positions) + + # make sure correct number of non-target inquiries + self.assertEqual( + counter[None], 60, + 'Should have produced 50 percent of 120 non-target positions.') + + self.assertFalse( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, counter)) + + def test_random_target_positions_no_nontargets(self): + """Test generation of random target positions with no nontarget inquiries.""" + + inquiry_count = 50 + stim_per_inquiry = 11 + percentage_without_target = 0 + + target_positions = random_target_positions( inquiry_count=inquiry_count, stim_per_inquiry=stim_per_inquiry, percentage_without_target=percentage_without_target) self.assertEqual( - len(targets), inquiry_count, - 'Should have produced the correct number of targets for inquiries.') + len(target_positions), inquiry_count, + 'Should have produced the correct number of target_positions for inquiries.' + ) # count how many times each target position is used - count = cnt.Counter() - for pos in targets: - count[pos] += 1 + counter = Counter(target_positions) + + self.assertFalse( + is_uniform_distribution(inquiry_count, stim_per_inquiry, + percentage_without_target, counter)) - # make sure target position counts are equally distributed - for i in count: - if i is not None: - self.assertTrue(num_target_inquiries <= count[i] <= num_target_inquiries + 1) + # make sure there are no non-target inquiries + self.assertEqual(counter[None], 0, + 'Should have produced no non-target positions.') + + def test_random_target_positions_all_nontargets(self): + """Test generation of random target positions with all inquiries being non-target.""" + inquiry_count = 100 + + target_positions = random_target_positions( + inquiry_count=inquiry_count, + stim_per_inquiry=6, + percentage_without_target=100) + + # count how many times each target position is used + counter = Counter(target_positions) # make sure all inquries are non-target inquiries - self.assertEqual(count[None], inquiry_count, + self.assertEqual(counter[None], inquiry_count, 'Should have produced all non-target positions.') def test_best_selection(self): @@ -439,20 +515,18 @@ def test_best_selection(self): # Test always included self.assertEqual( ['a', 'c', 'd'], - best_selection( - selection_elements=['a', 'b', 'c', 'd', 'e'], - val=[0.3, 0.1, 0.3, 0.1, 0.2], - len_query=3, - always_included=['d']), + best_selection(selection_elements=['a', 'b', 'c', 'd', 'e'], + val=[0.3, 0.1, 0.3, 0.1, 0.2], + len_query=3, + always_included=['d']), 'Included item should bump out the best item with the lowest val.') self.assertEqual( ['a', 'b', 'c'], - best_selection( - selection_elements=['a', 'b', 'c', 'd', 'e'], - val=[0.5, 0.4, 0.1, 0.0, 0.0], - len_query=3, - always_included=['b']), + best_selection(selection_elements=['a', 'b', 'c', 'd', 'e'], + val=[0.5, 0.4, 0.1, 0.0, 0.0], + len_query=3, + always_included=['b']), 'Included item should retain its position if already present') self.assertEqual(['a', 'b', 'e'], @@ -473,11 +547,11 @@ def test_best_selection(self): self.assertEqual(['a', 'b', 'c'], best_selection( - selection_elements=['a', 'b', 'c', 'd', 'e'], - val=[0.5, 0.4, 0.1, 0.0, 0.0], - len_query=3, - always_included=['<']), - 'should ignore items not in the set.') + selection_elements=['a', 'b', 'c', 'd', 'e'], + val=[0.5, 0.4, 0.1, 0.0, 0.0], + len_query=3, + always_included=['<']), + 'should ignore items not in the set.') def test_best_case_inquiry_gen(self): """Test best_case_rsvp_inq_gen""" @@ -513,8 +587,8 @@ def test_best_case_inquiry_gen_with_inq_constants(self): alp = ['a', 'b', 'c', 'd', 'e', 'f', 'g'] n = 5 - with self.assertRaises( - Exception, msg='Constants should be in the alphabet'): + with self.assertRaises(Exception, + msg='Constants should be in the alphabet'): best_case_rsvp_inq_gen( alp=alp, session_stimuli=[0.1, 0.1, 0.1, 0.2, 0.2, 0.1, 0.2], @@ -570,13 +644,15 @@ def test_jittered_timing_with_jitter_within_defined_limits(self): for r in resp: self.assertTrue(min_jitter <= r <= max_jitter) - def test_jittered_timing_throw_exception_when_jitter_greater_than_time(self): + def test_jittered_timing_throw_exception_when_jitter_greater_than_time( + self): # to prevent 0 values we prevent the jitter from being greater than the time time = 1 jitter = 1.5 stim_number = 100 - with self.assertRaises(Exception, msg='Jitter should be less than stimuli time'): + with self.assertRaises(Exception, + msg='Jitter should be less than stimuli time'): jittered_timing(time, jitter, stim_number) @@ -618,6 +694,7 @@ def test_alphabetize_special_characters_at_end(self): class TestTrialReshaper(unittest.TestCase): + def setUp(self): self.target_info = ['target', 'nontarget', 'nontarget'] self.timing_info = [1.001, 1.2001, 1.4001] @@ -640,7 +717,8 @@ def test_trial_reshaper(self): channel_map=self.channel_map, poststimulus_length=trial_length_s) trial_length_samples = int(sample_rate * trial_length_s) - expected_shape = (self.channel_number, len(self.target_info), trial_length_samples) + expected_shape = (self.channel_number, len(self.target_info), + trial_length_samples) self.assertTrue(np.all(labels == [1, 0, 0])) self.assertTrue(reshaped_trials.shape == expected_shape) @@ -654,27 +732,40 @@ def setUp(self): self.n_inquiry = 4 self.sample_rate = 10 self.target_info = [ - "target", "nontarget", "nontarget", - "nontarget", "nontarget", "nontarget", - "nontarget", "target", "nontarget", - "nontarget", "nontarget", "target", + "target", + "nontarget", + "nontarget", + "nontarget", + "nontarget", + "nontarget", + "nontarget", + "target", + "nontarget", + "nontarget", + "nontarget", + "target", ] - self.true_labels = np.array([ - [1, 0, 0], - [0, 0, 0], - [0, 1, 0], - [0, 0, 1] - ]) + self.true_labels = np.array([[1, 0, 0], [0, 0, 0], [0, 1, 0], + [0, 0, 1]]) self.timing_info = [ - 1.4, 2.4, 3.4, - 28.1, 30.1, 38.1, - 50.1, 51.1, 52.1, - 80.1, 81.1, 82.1, + 1.4, + 2.4, + 3.4, + 28.1, + 30.1, + 38.1, + 50.1, + 51.1, + 52.1, + 80.1, + 81.1, + 82.1, ] # Note this value must be greater than the difference between first and last timing info per inquiry # In this case there are 3 trials per inquiry and the difference between the first and last timing info is 10s self.inquiry_duration_s = 10 + self.trial_length - self.samples_per_inquiry = int(self.sample_rate * self.inquiry_duration_s) + self.samples_per_inquiry = int(self.sample_rate * + self.inquiry_duration_s) self.samples_per_trial = int(self.sample_rate * self.trial_length) # We create a wealth of samples, but only use the first 4 inquiries worth self.eeg = np.random.randn(self.n_channel, 10000) @@ -690,27 +781,32 @@ def test_inquiry_reshaper(self): channel_map=self.channel_map, poststimulus_length=self.trial_length, ) - expected_shape = (self.n_channel, self.n_inquiry, self.samples_per_inquiry) + expected_shape = (self.n_channel, self.n_inquiry, + self.samples_per_inquiry) self.assertTrue(reshaped_data.shape == expected_shape) self.assertTrue(np.all(labels == self.true_labels)) def test_inquiry_reshaper_trial_extraction(self): timing = [[1, 3, 4], [1, 4, 5], [1, 2, 3], [4, 5, 6]] # make a fake eeg data array (n_channels, n_inquiry, n_samples) - inquiries = np.random.randn(self.n_channel, self.n_inquiry, self.samples_per_inquiry) + inquiries = np.random.randn(self.n_channel, self.n_inquiry, + self.samples_per_inquiry) response = InquiryReshaper().extract_trials( inquiries=inquiries, samples_per_trial=self.samples_per_trial, inquiry_timing=timing, ) - expected_shape = (self.n_channel, (self.trials_per_inquiry * self.n_inquiry), self.samples_per_trial) + expected_shape = (self.n_channel, + (self.trials_per_inquiry * self.n_inquiry), + self.samples_per_trial) self.assertTrue(response.shape == expected_shape) def test_inquiry_reshaper_trial_extraction_with_prestimulus(self): timing = [[2, 7, 10], [2, 7, 15], [2, 12, 15], [4, 5, 6]] # make a fake eeg data array (n_channels, n_inquiry, n_samples) - inquiries = np.random.randn(self.n_channel, self.n_inquiry, self.samples_per_inquiry) + inquiries = np.random.randn(self.n_channel, self.n_inquiry, + self.samples_per_inquiry) prestimulus_samples = 1 response = InquiryReshaper().extract_trials( inquiries=inquiries, @@ -718,10 +814,9 @@ def test_inquiry_reshaper_trial_extraction_with_prestimulus(self): inquiry_timing=timing, prestimulus_samples=prestimulus_samples, ) - expected_shape = ( - self.n_channel, - (self.trials_per_inquiry * self.n_inquiry), - (self.samples_per_trial + prestimulus_samples)) + expected_shape = (self.n_channel, + (self.trials_per_inquiry * self.n_inquiry), + (self.samples_per_trial + prestimulus_samples)) self.assertTrue(response.shape == expected_shape) @@ -758,19 +853,22 @@ def test_default_flicker_and_refresh_rate_return_codes(self): def test_ssvep_to_codes_returns_the_length_of_refresh_rate(self): refresh_rate = 40 flicker_rate = 2 - response = ssvep_to_code(flicker_rate=flicker_rate, refresh_rate=refresh_rate) + response = ssvep_to_code(flicker_rate=flicker_rate, + refresh_rate=refresh_rate) self.assertTrue(len(response) == refresh_rate) self.assertEqual(response[0], 0) self.assertEqual(response[-1], 1) - def test_ssvep_to_code_raises_exception_when_refresh_rate_less_than_flicker_rate(self): + def test_ssvep_to_code_raises_exception_when_refresh_rate_less_than_flicker_rate( + self): flicker_rate = 300 refresh_rate = 1 with self.assertRaises(BciPyCoreException): ssvep_to_code(refresh_rate, flicker_rate) - def test_when_division_of_refresh_rate_by_flicker_rate_raise_exception_if_noninteger(self): + def test_when_division_of_refresh_rate_by_flicker_rate_raise_exception_if_noninteger( + self): flicker_rate = 11 refresh_rate = 60 @@ -780,11 +878,13 @@ def test_when_division_of_refresh_rate_by_flicker_rate_raise_exception_if_nonint def test_ssvep_to_code_returns_expected_codes(self): flicker_rate = 2 refresh_rate = 4 - response = ssvep_to_code(flicker_rate=flicker_rate, refresh_rate=refresh_rate) + response = ssvep_to_code(flicker_rate=flicker_rate, + refresh_rate=refresh_rate) expected_output = [0, 0, 1, 1] self.assertEqual(response, expected_output) - def test_ssvep_to_code_raises_exception_when_flicker_rate_one_or_less(self): + def test_ssvep_to_code_raises_exception_when_flicker_rate_one_or_less( + self): flicker_rate = 1 refresh_rate = 2 with self.assertRaises(BciPyCoreException): @@ -806,8 +906,8 @@ def test_play_sound_returns_timing(self): sound_file_path = 'test_sound_file_path' # mock the other library interactions - when(sf).read( - sound_file_path, dtype='float32').thenReturn(('data', MOCK_FS)) + when(sf).read(sound_file_path, dtype='float32').thenReturn( + ('data', MOCK_FS)) when(sd).play(any(), any()).thenReturn(None) when(core).wait(any()).thenReturn(None) @@ -827,8 +927,8 @@ def test_play_sound_raises_exception_if_soundfile_cannot_read_file(self): sound_file_path = 'test_sound_file_path' # mock the other library interactions - when(sf).read( - sound_file_path, dtype='float32').thenRaise(Exception('')) + when(sf).read(sound_file_path, + dtype='float32').thenRaise(Exception('')) # assert it raises the exception with self.assertRaises(Exception): @@ -850,8 +950,8 @@ def mock_callback_function(clock, stimuli): self.assertEqual(stimuli, self.test_timing[0]) # mock the other library interactions - when(sf).read( - sound_file_path, dtype='float32').thenReturn(('data', MOCK_FS)) + when(sf).read(sound_file_path, dtype='float32').thenReturn( + ('data', MOCK_FS)) when(sd).play(any(), any()).thenReturn(None) when(core).wait(any()).thenReturn(None) when(experiment_clock).getTime().thenReturn(test_trigger_time) @@ -878,10 +978,8 @@ def test_soundfiles_generator(self): path.join(directory, '1.wav'), path.join(directory, '2.wav') ] - when(glob).glob( - path.join( - directory, - '*.wav')).thenReturn(soundfile_paths) + when(glob).glob(path.join(directory, + '*.wav')).thenReturn(soundfile_paths) when(path).isdir(directory).thenReturn(True) gen = soundfiles(directory) @@ -901,10 +999,8 @@ def test_soundfiles_generator_path_arg(self): path.join(directory, '1.wav'), path.join(directory, '2.wav') ] - when(glob).glob( - path.join( - directory, - '*.wav')).thenReturn(soundfile_paths) + when(glob).glob(path.join(directory, + '*.wav')).thenReturn(soundfile_paths) when(path).isdir(directory).thenReturn(True) gen = soundfiles(directory) self.assertEqual(next(gen), soundfile_paths[0]) From c2b840f7c05e0e3a1f0ab5e55863ae287dc81787 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 13 Jul 2023 11:44:50 -0700 Subject: [PATCH 042/330] Refactoring and more tests --- bcipy/helpers/stimuli.py | 136 ++++++++++++++++++++-------- bcipy/helpers/tests/test_stimuli.py | 36 +++++++- 2 files changed, 130 insertions(+), 42 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 855707703..8bbba6317 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -521,75 +521,133 @@ def generate_calibration_inquiries( if color is None: color = ['green', 'red', 'white'] assert len(timing) == 3, "timing must include values for [target, fixation, stimuli]" + time_target, time_fixation, time_stim = timing + fixation = get_fixation(is_txt) - target_indexes = [] - if target_positions == TargetPositions.DISTRIBUTED: - target_indexes = distributed_target_positions( - inquiry_count, stim_per_inquiry, percentage_without_target) - else: - target_indexes = random_target_positions(inquiry_count, - stim_per_inquiry, - percentage_without_target) - - samples, times, colors = [], [], [] + target_indexes = generate_target_positions(inquiry_count, stim_per_inquiry, + percentage_without_target, + target_positions) + samples, times = [], [] for i in range(inquiry_count): - inquiry = random.sample(alp, k=stim_per_inquiry) + inquiry = generate_inquiry(symbols=alp, + length=stim_per_inquiry, + stim_order=stim_order) + target = inquiry_target(inquiry, target_position=target_indexes[i], symbols=alp) + samples.append([target, fixation, *inquiry]) - if stim_order == StimuliOrder.ALPHABETICAL: - inquiry = alphabetize(inquiry) + stim_timing = generate_inquiry_stim_timing(time_stim, stim_per_inquiry, jitter) + times.append([time_target, time_fixation, *stim_timing]) - target_index = target_indexes[i] - if target_index is NO_TARGET_INDEX: - target = random.choice(list(set(alp) - set(inquiry))) - else: - target = inquiry[target_index] + inquiry_colors = color[0:2] + [color[-1]] * stim_per_inquiry + colors = [inquiry_colors for _ in range(inquiry_count)] - sample = [target, get_fixation(is_txt=is_txt), *inquiry] - samples.append(sample) + return InquirySchedule(samples, times, colors) - # timing for fixation and prompt - init_timing = [timing[i] for i in range(len(timing) - 1)] - # pull out timing for the inquiry stimuli - stim_time = timing[-1] - if jitter: - _inq_timing = jittered_timing(stim_time, jitter, stim_per_inquiry) - inq_timing = init_timing + _inq_timing - else: - inq_timing = init_timing + [stim_time] * stim_per_inquiry - times.append(inq_timing) - colors.append([color[i] for i in range(len(color) - 1)] + - [color[-1]] * stim_per_inquiry) - return InquirySchedule(samples, times, colors) +def generate_inquiry(symbols: List[str], length: int, + stim_order: StimuliOrder) -> List[str]: + """Generate an inquiry from the list of symbols. No symbols are repeated + in the output list. + + Args: + symbols - values from which to select + length - number of items in the return list + stim_order - ordering of results + """ + inquiry = random.sample(symbols, k=length) + if stim_order == StimuliOrder.ALPHABETICAL: + inquiry = alphabetize(inquiry) + return inquiry + +def inquiry_target(inquiry: List[str], target_position: Optional[int], + symbols: List[str]) -> str: + """Returns the target for the given inquiry. If the optional + target position is not provided a target will randomly be selected from + the list of symbols and will not be in the inquiry. + + Args: + inquiry - list of symbols to be presented + target_position - optional position within the list of the target sym + symbols - used if position is not provided to select a random symbol + as the target. + + Returns target symbol + """ + if target_position is None: + return random.choice(list(set(symbols) - set(inquiry))) + return inquiry[target_position] +def generate_inquiry_stim_timing(time_stim: float, length: int, + jitter: bool) -> List[float]: + """Generate stimuli timing values for a given inquiry. + + Args: + time_stim: seconds to display each stimuli + length: Number of timings to generate + jitter: whether the timing should be jittered. + + Returns list of times (in seconds) + """ + if jitter: + return jittered_timing(time_stim, jitter, length) + + return [time_stim] * length def jittered_timing(time: float, jitter: float, stim_count: int) -> List[float]: """Jittered timing. - Using a base time and a jitter, generate a list (with length stim_count) of timing that is uniformly distributed. + Using a base time and a jitter, generate a list (with length stim_count) of + timing that is uniformly distributed. """ assert time > jitter, ( f'Jitter timing [{jitter}] must be less than stimuli timing =[{time}] in the inquiry.') return np.random.uniform(low=time - jitter, high=time + jitter, size=(stim_count,)).tolist() -def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, percentage_without_target: int) -> list: +def generate_target_positions(inquiry_count: int, stim_per_inquiry: int, + percentage_without_target: int, + distribution: TargetPositions) -> List[int]: + """ + Generates target positions distributed according to the provided parameter. + + Args: + inquiry_count: Number of inquiries in calibration + stim_per_inquiry: Number of stimuli in each inquiry + percentage_without_target: percentage of inquiries for which + target letter flashed is not in inquiry + distribution: specifies how targets should be distributed + + Returns list of indexes + """ + if distribution is TargetPositions.DISTRIBUTED: + return distributed_target_positions(inquiry_count, stim_per_inquiry, + percentage_without_target) + return random_target_positions(inquiry_count, stim_per_inquiry, + percentage_without_target) + +def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, + percentage_without_target: int) -> list: """Distributed Target Positions. - Generates evenly distributed target positions, including target letter not flashed at all, and shuffles them. + Generates evenly distributed target positions, including target letter + not flashed at all, and shuffles them. + Args: inquiry_count(int): Number of inquiries in calibration stim_per_inquiry(int): Number of stimuli in each inquiry - percentage_without_target(int): percentage of inquiries for which target letter flashed is not in inquiry + percentage_without_target(int): percentage of inquiries for which + target letter flashed is not in inquiry - Return distributed_target_positions(list): targets: array of target indexes to be chosen + Return distributed_target_positions(list): targets: array of target + indexes to be chosen """ targets = [] # find number of target and nontarget inquiries - num_nontarget_inquiry = int(inquiry_count * (percentage_without_target / 100)) + num_nontarget_inquiry = int(inquiry_count * + (percentage_without_target / 100)) num_target_inquiry = inquiry_count - num_nontarget_inquiry # find number each target position is repeated, and remaining number diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index c37e658c5..36e7458b1 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -16,7 +16,8 @@ best_case_rsvp_inq_gen, best_selection, distributed_target_positions, generate_calibration_inquiries, - get_fixation, jittered_timing, play_sound, + generate_inquiry, get_fixation, + inquiry_target, jittered_timing, play_sound, random_target_positions, soundfiles, ssvep_to_code, target_index, update_inquiry_timing) @@ -496,6 +497,35 @@ def test_random_target_positions_all_nontargets(self): self.assertEqual(counter[None], inquiry_count, 'Should have produced all non-target positions.') + def test_inquiry_target(self): + """Test inquiry target""" + + symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] + inquiry = ['C', 'A', 'F', 'E'] + self.assertEqual(inquiry_target(inquiry, 0, symbols), 'C') + self.assertEqual(inquiry_target(inquiry, 3, symbols), 'E') + + target = inquiry_target(inquiry, None, symbols) + self.assertTrue(target not in inquiry) + self.assertTrue(target in symbols) + + def test_generate_inquiry(self): + """Test generation of a single inquiry""" + symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] + inquiry = generate_inquiry(symbols=symbols, + length=3, + stim_order=StimuliOrder.RANDOM) + + # NOTE: it's possible an inquiry in Random order will be in alphabetical order + self.assertEqual(3, len(inquiry)) + for sym in inquiry: + self.assertTrue(sym in symbols) + + inquiry = generate_inquiry(symbols=symbols, + length=3, + stim_order=StimuliOrder.ALPHABETICAL) + self.assertEqual(inquiry, sorted(inquiry)) + def test_best_selection(self): """Test best_selection""" @@ -687,9 +717,9 @@ def test_alphabetize_image_name(self): def test_alphabetize_special_characters_at_end(self): character = '<' + stimuli = ['Z', character, 'Q', 'A', 'G'] expected = ['A', 'G', 'Q', 'Z', character] - self.list_to_alphabetize.insert(1, character) - response = alphabetize(self.list_to_alphabetize) + response = alphabetize(stimuli) self.assertEqual(expected, response) From 4f7d531a19e157cc96602e667c37a62304a496c2 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 19 Jul 2023 14:42:14 -0700 Subject: [PATCH 043/330] Added functions for testing statistical properties of generated inquiries. Refactored to ensure that symbols were presented as targets with equal frequency --- bcipy/helpers/stimuli.py | 182 ++++++++++++++++++++++++++-- bcipy/helpers/tests/test_stimuli.py | 118 ++++++++++++++++-- 2 files changed, 281 insertions(+), 19 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 8bbba6317..d9e0becd0 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -4,10 +4,12 @@ import random import re from abc import ABC, abstractmethod +from collections import Counter from enum import Enum from os import path, sep -from typing import Iterator, List, NamedTuple, Optional, Tuple +from typing import Dict, Iterator, List, NamedTuple, Optional, Tuple +from pandas import Series from PIL import Image from bcipy.helpers.exceptions import BciPyCoreException @@ -485,7 +487,7 @@ def generate_calibration_inquiries( timing: List[float] = None, jitter: Optional[int] = None, color: List[str] = None, - inquiry_count: int = 10, + inquiry_count: int = 100, stim_per_inquiry: int = 10, stim_order: StimuliOrder = StimuliOrder.RANDOM, target_positions: TargetPositions = TargetPositions.RANDOM, @@ -494,6 +496,13 @@ def generate_calibration_inquiries( """ Generates inquiries with target letters in all possible positions. + This function attempts to display all symbols as targets an equal number of + times when stim_order is RANDOM. When the stim_order is ALPHABETICAL there + is much more variation in the counts (target distribution takes priority) + and some symbols may not appear as targets depending on the inquiry_count. + The frequency that each symbol is displayed as a nontarget should follow a + uniform distribution. + Parameters ---------- alp(list[str]): stimuli @@ -527,17 +536,28 @@ def generate_calibration_inquiries( target_indexes = generate_target_positions(inquiry_count, stim_per_inquiry, percentage_without_target, target_positions) - - samples, times = [], [] + if stim_order == StimuliOrder.ALPHABETICAL: + targets = None + else: + targets = generate_targets(alp, inquiry_count, percentage_without_target) + inquiries = generate_inquiries(alp, inquiry_count, stim_per_inquiry, + stim_order) + samples = [] + target = None for i in range(inquiry_count): - inquiry = generate_inquiry(symbols=alp, - length=stim_per_inquiry, - stim_order=stim_order) - target = inquiry_target(inquiry, target_position=target_indexes[i], symbols=alp) + inquiry = inquiries[i] + target_pos = target_indexes[i] + target = inquiry_target(inquiry, + target_pos, + symbols=alp, + next_targets=targets, + last_target=target) samples.append([target, fixation, *inquiry]) - stim_timing = generate_inquiry_stim_timing(time_stim, stim_per_inquiry, jitter) - times.append([time_target, time_fixation, *stim_timing]) + times = [[ + time_target, time_fixation, + *generate_inquiry_stim_timing(time_stim, stim_per_inquiry, jitter) + ] for _ in range(inquiry_count)] inquiry_colors = color[0:2] + [color[-1]] * stim_per_inquiry colors = [inquiry_colors for _ in range(inquiry_count)] @@ -545,10 +565,74 @@ def generate_calibration_inquiries( return InquirySchedule(samples, times, colors) +def inquiry_target_counts(inquiries: List[List[str]], symbols: List[str]) -> dict: + """Count the number of times each symbol was presented as a target. + + Args: + inquiries - list of inquiries where each inquiry is structured as + [target, fixation, *stim] + symbols - list of all possible symbols + """ + target_presentations = [inq[0] for inq in inquiries if inq[0] in inq[2:]] + counter = dict.fromkeys(symbols, 0) + for target in target_presentations: + counter[target] += 1 + return counter + + +def inquiry_nontarget_counts(inquiries: List[List[str]], symbols: List[str]) -> dict: + """Count the number of times each symbol was presented as a nontarget.""" + counter = dict.fromkeys(symbols, 0) + for inq in inquiries: + target, _fixation, *stimuli = inq + for stim in stimuli: + if stim != target: + counter[stim] += 1 + return counter + + +def inquiry_stats(inquiries: List[List[str]], + symbols: List[str]) -> Dict[str, Dict[str, float]]: + """Descriptive stats for the number of times each target and nontarget + symbol is shown in the inquiries""" + + target_stats = dict( + Series(Counter(inquiry_target_counts(inquiries, symbols))).describe()) + + nontarget_stats = dict( + Series(Counter(inquiry_nontarget_counts(inquiries, + symbols))).describe()) + + return { + 'target_symbols': target_stats, + 'nontarget_symbols': nontarget_stats + } + + + +def generate_inquiries(symbols: List[str], inquiry_count: int, + stim_per_inquiry: int, stim_order: StimuliOrder) -> List[List[str]]: + """Generate a list of inquiries. For each inquiry no symbols are repeated. + Inquiries do not include the target or fixation. Symbols should be + distributed uniformly across inquiries. + + Args: + + symbols - values from which to select + inquiry_count - total number of inquiries to generate + stim_per_inquiry - length of each inquiry + stim_order - ordering of results + """ + return [ + generate_inquiry(symbols=symbols, + length=stim_per_inquiry, + stim_order=stim_order) for _ in range(inquiry_count) + ] + def generate_inquiry(symbols: List[str], length: int, stim_order: StimuliOrder) -> List[str]: """Generate an inquiry from the list of symbols. No symbols are repeated - in the output list. + in the output list. Output does not include the target or fixation. Args: symbols - values from which to select @@ -560,8 +644,9 @@ def generate_inquiry(symbols: List[str], length: int, inquiry = alphabetize(inquiry) return inquiry + def inquiry_target(inquiry: List[str], target_position: Optional[int], - symbols: List[str]) -> str: + symbols: List[str], next_targets: List[str] = None, last_target: str = None) -> str: """Returns the target for the given inquiry. If the optional target position is not provided a target will randomly be selected from the list of symbols and will not be in the inquiry. @@ -571,11 +656,44 @@ def inquiry_target(inquiry: List[str], target_position: Optional[int], target_position - optional position within the list of the target sym symbols - used if position is not provided to select a random symbol as the target. + next_targets - list of targets from which to select + last_target - target from the previous inquiry; used to avoid selecting + the same target consecutively. Returns target symbol """ if target_position is None: return random.choice(list(set(symbols) - set(inquiry))) + + if next_targets: + # select the next target from the symbols in the current inquiry. + # if none of the symbols in the current inquiry are in the choices, the + # target is determined strictly from the target_position. + choice_index = None + symbol_inquiry_position = None + target = None + for position, symbol in enumerate(inquiry): + # avoid repeating targets + if symbol == last_target: + continue + try: + symbol_index = next_targets.index(symbol) + if choice_index is None or symbol_index < choice_index: + choice_index = symbol_index + symbol_inquiry_position = position + target = symbol + except ValueError: + continue + + if target is not None: + # update next_targets list + next_targets.remove(target) # removes first occurrence of value + + # update inquiry to set the target at the expected position. + symbol_at_target_position = inquiry[target_position] + inquiry[symbol_inquiry_position] = symbol_at_target_position + inquiry[target_position] = target + return inquiry[target_position] def generate_inquiry_stim_timing(time_stim: float, length: int, @@ -605,6 +723,22 @@ def jittered_timing(time: float, jitter: float, stim_count: int) -> List[float]: return np.random.uniform(low=time - jitter, high=time + jitter, size=(stim_count,)).tolist() +def num_inquiries_with_targets( + inquiry_count: int, percentage_without_target: int) -> Tuple[int, int]: + """Determine the number of inquiries that should display targets. + + Args: + inquiry_count: Number of inquiries in calibration + percentage_without_target: percentage of inquiries for which + target letter flashed is not in inquiry + + Returns tuple of num_nontarget_inquiry, num_target_inquiry + """ + num_nontarget_inquiry = int(inquiry_count * + (percentage_without_target / 100)) + num_target_inquiry = inquiry_count - num_nontarget_inquiry + return num_target_inquiry, num_nontarget_inquiry + def generate_target_positions(inquiry_count: int, stim_per_inquiry: int, percentage_without_target: int, distribution: TargetPositions) -> List[int]: @@ -671,6 +805,30 @@ def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, return targets +def generate_targets(symbols: List[str], inquiry_count: int, + percentage_without_target: int) -> List[str]: + """Generates list of target symbols. Generates an equal number of each + target. The resulting list may be less than the inquiry_count. Used for + sampling without replacement to get approximately equal numbers of each + target. + + Args: + symbols: + inquiry_count: number of inquiries in calibration + percentage_without_target: percentage of inquiries for which + target letter flashed is not in inquiry + """ + nontarget_count = int(inquiry_count * + (percentage_without_target / 100)) + target_count = inquiry_count - nontarget_count + + # each symbol should appear at least once + symbol_count = int(target_count / len(symbols)) or 1 + targets = symbols * symbol_count + random.shuffle(targets) + return targets + + def random_target_positions(inquiry_count: int, stim_per_inquiry: int, percentage_without_target: int) -> list: diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 36e7458b1..49a116337 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -16,8 +16,10 @@ best_case_rsvp_inq_gen, best_selection, distributed_target_positions, generate_calibration_inquiries, - generate_inquiry, get_fixation, - inquiry_target, jittered_timing, play_sound, + generate_inquiry, generate_targets, + get_fixation, inquiry_nontarget_counts, + inquiry_target, inquiry_target_counts, + jittered_timing, play_sound, random_target_positions, soundfiles, ssvep_to_code, target_index, update_inquiry_timing) @@ -497,17 +499,91 @@ def test_random_target_positions_all_nontargets(self): self.assertEqual(counter[None], inquiry_count, 'Should have produced all non-target positions.') - def test_inquiry_target(self): - """Test inquiry target""" + def test_generate_targets(self): + """Test target generation""" + symbols = ['A', 'B', 'C', 'D'] + targets = generate_targets(symbols, inquiry_count = 9, percentage_without_target=0) + self.assertEqual(len(targets), 8) + self.assertTrue(all(val == 2 for val in Counter(targets).values())) + + targets = generate_targets(symbols, inquiry_count = 9, percentage_without_target=50) + self.assertEqual(len(targets), 4) + self.assertTrue(all(val == 1 for val in Counter(targets).values())) + def test_inquiry_target(self): + """Test inquiry target behavior.""" symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] inquiry = ['C', 'A', 'F', 'E'] - self.assertEqual(inquiry_target(inquiry, 0, symbols), 'C') - self.assertEqual(inquiry_target(inquiry, 3, symbols), 'E') + next_targets = ['Q', 'F', 'A'] + target = inquiry_target(inquiry, + target_position=0, + symbols=symbols, + next_targets=next_targets) - target = inquiry_target(inquiry, None, symbols) + self.assertEqual( + target, 'F', + 'the inquiry symbol next in order in the target choices should have been selected' + ) + self.assertSequenceEqual(inquiry, ['F', 'A', 'C', 'E'], + 'inquiry should have been re-ordered') + self.assertSequenceEqual( + next_targets, ['Q', 'A'], + 'list of next targets should have been modified') + + def test_inquiry_target_with_none_position(self): + """Test inquiry target with position of None.""" + symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] + inquiry = ['C', 'A', 'F', 'E'] + next_targets = ['Q', 'F', 'A'] + target = inquiry_target(inquiry, None, symbols, next_targets) self.assertTrue(target not in inquiry) self.assertTrue(target in symbols) + self.assertSequenceEqual(inquiry, ['C', 'A', 'F', 'E'], 'inquiry should not have changed') + + def test_inquiry_target_missing(self): + """Test inquiry target where none of the next_targets are present in + the current inquiry.""" + symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] + inquiry = ['C', 'A', 'F', 'E'] + next_targets = ['Q', 'D'] + target = inquiry_target(inquiry, + target_position=0, + symbols=symbols, + next_targets=next_targets) + self.assertTrue(target in inquiry) + self.assertTrue(target not in next_targets) + self.assertSequenceEqual(inquiry, ['C', 'A', 'F', 'E'], 'inquiry should not have changed') + self.assertSequenceEqual(next_targets, ['Q', 'D'], 'next_targets should not have changed') + + def test_inquiry_target_no_targets(self): + """Test inquiry_target when no next_targets are provided""" + symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] + inquiry = ['C', 'A', 'F', 'E'] + next_targets = ['Q', 'D'] + target = inquiry_target(inquiry, + target_position=0, + symbols=symbols, + next_targets=next_targets) + self.assertEqual(target, 'C', 'should have used the target_position to get the target') + self.assertSequenceEqual(inquiry, ['C', 'A', 'F', 'E'], 'inquiry should not have changed') + + def test_inquiry_target_last_target(self): + """Test inquiry target behavior.""" + symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G'] + inquiry = ['C', 'A', 'F', 'E'] + next_targets = ['Q', 'F', 'A'] + target = inquiry_target(inquiry, + target_position=0, + symbols=symbols, + next_targets=next_targets, + last_target='F') + + self.assertEqual(target, 'A', 'last_target should have been skipped') + self.assertSequenceEqual(inquiry, ['A', 'C', 'F', 'E'], + 'inquiry should have been re-ordered') + self.assertSequenceEqual( + next_targets, ['Q', 'F'], + 'list of next targets should have been modified') def test_generate_inquiry(self): """Test generation of a single inquiry""" @@ -526,6 +602,34 @@ def test_generate_inquiry(self): stim_order=StimuliOrder.ALPHABETICAL) self.assertEqual(inquiry, sorted(inquiry)) + def test_inquiry_target_counts(self): + """Test inquiry_target_counts""" + inquiries = [['D', '+', 'Z', 'Q', 'T', 'C', 'D'], + ['Q', '+', 'L', 'Q', 'B', 'J', 'N'], + ['W', '+', 'Q', 'F', 'M', 'W', 'N'], + ['Q', '+', 'X', 'G', 'Z', 'J', 'V']] + + targeted = ['D', 'Q', 'W'] + not_targeted = list(set(self.alp) - set(targeted)) + target_counts = inquiry_target_counts(inquiries, symbols=self.alp) + self.assertTrue(all(target_counts[sym] == 1 for sym in targeted)) + self.assertTrue(all(target_counts[sym] == 0 for sym in not_targeted)) + + def test_inquiry_nontarget_counts(self): + """Test inquiry_nontarget_counts""" + symbols = ['A', 'B', 'C', 'D', 'E', 'F'] + inquiries = [['C', '+', 'B', 'E', 'C'], + ['E', '+', 'B', 'F', 'E'], + ['E', '+', 'A', 'C', 'E'], + ['B', '+', 'D', 'E', 'B'], + ['C', '+', 'F', 'B', 'C']] + + + expected = {'A': 1, 'B': 3, 'C': 1, 'D': 1, 'E': 2, 'F': 2} + counts = inquiry_nontarget_counts(inquiries, symbols=symbols) + self.assertDictEqual(counts, expected) + + def test_best_selection(self): """Test best_selection""" From b51c1f484773403740dfbf5dd1fb7147cd0e45dd Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 19 Jul 2023 17:13:08 -0700 Subject: [PATCH 044/330] Formatting changes --- bcipy/helpers/stimuli.py | 87 ++++++++++++++++++++++++---------------- 1 file changed, 52 insertions(+), 35 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index d9e0becd0..8bea29764 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -482,6 +482,7 @@ def best_case_rsvp_inq_gen(alp: list, NO_TARGET_INDEX = None + def generate_calibration_inquiries( alp: List[str], timing: List[float] = None, @@ -529,7 +530,9 @@ def generate_calibration_inquiries( timing = [0.5, 1, 0.2] if color is None: color = ['green', 'red', 'white'] - assert len(timing) == 3, "timing must include values for [target, fixation, stimuli]" + assert len( + timing + ) == 3, "timing must include values for [target, fixation, stimuli]" time_target, time_fixation, time_stim = timing fixation = get_fixation(is_txt) @@ -539,7 +542,8 @@ def generate_calibration_inquiries( if stim_order == StimuliOrder.ALPHABETICAL: targets = None else: - targets = generate_targets(alp, inquiry_count, percentage_without_target) + targets = generate_targets(alp, inquiry_count, + percentage_without_target) inquiries = generate_inquiries(alp, inquiry_count, stim_per_inquiry, stim_order) samples = [] @@ -565,7 +569,8 @@ def generate_calibration_inquiries( return InquirySchedule(samples, times, colors) -def inquiry_target_counts(inquiries: List[List[str]], symbols: List[str]) -> dict: +def inquiry_target_counts(inquiries: List[List[str]], + symbols: List[str]) -> dict: """Count the number of times each symbol was presented as a target. Args: @@ -580,7 +585,8 @@ def inquiry_target_counts(inquiries: List[List[str]], symbols: List[str]) -> dic return counter -def inquiry_nontarget_counts(inquiries: List[List[str]], symbols: List[str]) -> dict: +def inquiry_nontarget_counts(inquiries: List[List[str]], + symbols: List[str]) -> dict: """Count the number of times each symbol was presented as a nontarget.""" counter = dict.fromkeys(symbols, 0) for inq in inquiries: @@ -609,9 +615,9 @@ def inquiry_stats(inquiries: List[List[str]], } - def generate_inquiries(symbols: List[str], inquiry_count: int, - stim_per_inquiry: int, stim_order: StimuliOrder) -> List[List[str]]: + stim_per_inquiry: int, + stim_order: StimuliOrder) -> List[List[str]]: """Generate a list of inquiries. For each inquiry no symbols are repeated. Inquiries do not include the target or fixation. Symbols should be distributed uniformly across inquiries. @@ -629,6 +635,7 @@ def generate_inquiries(symbols: List[str], inquiry_count: int, stim_order=stim_order) for _ in range(inquiry_count) ] + def generate_inquiry(symbols: List[str], length: int, stim_order: StimuliOrder) -> List[str]: """Generate an inquiry from the list of symbols. No symbols are repeated @@ -645,8 +652,11 @@ def generate_inquiry(symbols: List[str], length: int, return inquiry -def inquiry_target(inquiry: List[str], target_position: Optional[int], - symbols: List[str], next_targets: List[str] = None, last_target: str = None) -> str: +def inquiry_target(inquiry: List[str], + target_position: Optional[int], + symbols: List[str], + next_targets: List[str] = None, + last_target: str = None) -> str: """Returns the target for the given inquiry. If the optional target position is not provided a target will randomly be selected from the list of symbols and will not be in the inquiry. @@ -696,6 +706,7 @@ def inquiry_target(inquiry: List[str], target_position: Optional[int], return inquiry[target_position] + def generate_inquiry_stim_timing(time_stim: float, length: int, jitter: bool) -> List[float]: """Generate stimuli timing values for a given inquiry. @@ -712,15 +723,20 @@ def generate_inquiry_stim_timing(time_stim: float, length: int, return [time_stim] * length -def jittered_timing(time: float, jitter: float, stim_count: int) -> List[float]: + +def jittered_timing(time: float, jitter: float, + stim_count: int) -> List[float]: """Jittered timing. Using a base time and a jitter, generate a list (with length stim_count) of timing that is uniformly distributed. """ assert time > jitter, ( - f'Jitter timing [{jitter}] must be less than stimuli timing =[{time}] in the inquiry.') - return np.random.uniform(low=time - jitter, high=time + jitter, size=(stim_count,)).tolist() + f'Jitter timing [{jitter}] must be less than stimuli timing =[{time}] in the inquiry.' + ) + return np.random.uniform(low=time - jitter, + high=time + jitter, + size=(stim_count, )).tolist() def num_inquiries_with_targets( @@ -739,6 +755,7 @@ def num_inquiries_with_targets( num_target_inquiry = inquiry_count - num_nontarget_inquiry return num_target_inquiry, num_nontarget_inquiry + def generate_target_positions(inquiry_count: int, stim_per_inquiry: int, percentage_without_target: int, distribution: TargetPositions) -> List[int]: @@ -760,6 +777,7 @@ def generate_target_positions(inquiry_count: int, stim_per_inquiry: int, return random_target_positions(inquiry_count, stim_per_inquiry, percentage_without_target) + def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, percentage_without_target: int) -> list: """Distributed Target Positions. @@ -805,30 +823,6 @@ def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, return targets -def generate_targets(symbols: List[str], inquiry_count: int, - percentage_without_target: int) -> List[str]: - """Generates list of target symbols. Generates an equal number of each - target. The resulting list may be less than the inquiry_count. Used for - sampling without replacement to get approximately equal numbers of each - target. - - Args: - symbols: - inquiry_count: number of inquiries in calibration - percentage_without_target: percentage of inquiries for which - target letter flashed is not in inquiry - """ - nontarget_count = int(inquiry_count * - (percentage_without_target / 100)) - target_count = inquiry_count - nontarget_count - - # each symbol should appear at least once - symbol_count = int(target_count / len(symbols)) or 1 - targets = symbols * symbol_count - random.shuffle(targets) - return targets - - def random_target_positions(inquiry_count: int, stim_per_inquiry: int, percentage_without_target: int) -> list: @@ -853,6 +847,29 @@ def random_target_positions(inquiry_count: int, stim_per_inquiry: int, random.shuffle(target_indexes) return target_indexes + +def generate_targets(symbols: List[str], inquiry_count: int, + percentage_without_target: int) -> List[str]: + """Generates list of target symbols. Generates an equal number of each + target. The resulting list may be less than the inquiry_count. Used for + sampling without replacement to get approximately equal numbers of each + target. + + Args: + symbols: + inquiry_count: number of inquiries in calibration + percentage_without_target: percentage of inquiries for which + target letter flashed is not in inquiry + """ + nontarget_count = int(inquiry_count * (percentage_without_target / 100)) + target_count = inquiry_count - nontarget_count + + # each symbol should appear at least once + symbol_count = int(target_count / len(symbols)) or 1 + targets = symbols * symbol_count + random.shuffle(targets) + return targets + def target_index(inquiry: List[str]) -> int: """Given an inquiry, return the index of the target within the choices and None if the target is not included as a choice. From eb6210136feecf1153fc1ed564b8693a8325f4dd Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 19 Jul 2023 17:31:31 -0700 Subject: [PATCH 045/330] Refactor redundant code; clearer naming; formatting --- bcipy/helpers/stimuli.py | 47 +++++++++++++++-------------- bcipy/helpers/tests/test_stimuli.py | 12 +++----- 2 files changed, 29 insertions(+), 30 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 8bea29764..1992c3710 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -480,6 +480,7 @@ def best_case_rsvp_inq_gen(alp: list, [color[-1]] * stim_length) return InquirySchedule(samples, times, colors) + NO_TARGET_INDEX = None @@ -739,21 +740,21 @@ def jittered_timing(time: float, jitter: float, size=(stim_count, )).tolist() -def num_inquiries_with_targets( - inquiry_count: int, percentage_without_target: int) -> Tuple[int, int]: - """Determine the number of inquiries that should display targets. +def compute_counts(inquiry_count: int, + percentage_without_target: int) -> Tuple[int, int]: + """Determine the number of inquiries that should display targets and the + number that should not. Args: inquiry_count: Number of inquiries in calibration percentage_without_target: percentage of inquiries for which target letter flashed is not in inquiry - Returns tuple of num_nontarget_inquiry, num_target_inquiry + Returns tuple of (target_count, no_target_count) """ - num_nontarget_inquiry = int(inquiry_count * - (percentage_without_target / 100)) - num_target_inquiry = inquiry_count - num_nontarget_inquiry - return num_target_inquiry, num_nontarget_inquiry + no_target_count = int(inquiry_count * (percentage_without_target / 100)) + target_count = inquiry_count - no_target_count + return target_count, no_target_count def generate_target_positions(inquiry_count: int, stim_per_inquiry: int, @@ -797,17 +798,16 @@ def distributed_target_positions(inquiry_count: int, stim_per_inquiry: int, targets = [] - # find number of target and nontarget inquiries - num_nontarget_inquiry = int(inquiry_count * - (percentage_without_target / 100)) - num_target_inquiry = inquiry_count - num_nontarget_inquiry + # find number of target and no_target inquiries + target_count, no_target_count = compute_counts(inquiry_count, + percentage_without_target) # find number each target position is repeated, and remaining number - num_pos = (int)(num_target_inquiry / stim_per_inquiry) - num_rem_pos = (num_target_inquiry % stim_per_inquiry) + num_pos = (int)(target_count / stim_per_inquiry) + num_rem_pos = (target_count % stim_per_inquiry) # add correct number of None's for nontarget inquiries - targets = [NO_TARGET_INDEX] * num_nontarget_inquiry + targets = [NO_TARGET_INDEX] * no_target_count # add distributed list of target positions targets.extend(list(range(stim_per_inquiry)) * num_pos) @@ -837,13 +837,12 @@ def random_target_positions(inquiry_count: int, stim_per_inquiry: int, Return list of target indexes to be chosen """ - target_indexes = [] - num_nontarget_inquiry = int( - (percentage_without_target / 100) * inquiry_count) - num_target_inquiry = inquiry_count - num_nontarget_inquiry - target_indexes = [NO_TARGET_INDEX] * num_nontarget_inquiry + target_count, no_target_count = compute_counts(inquiry_count, + percentage_without_target) + + target_indexes = [NO_TARGET_INDEX] * no_target_count target_indexes.extend( - random.choices(range(stim_per_inquiry), k=num_target_inquiry)) + random.choices(range(stim_per_inquiry), k=target_count)) random.shuffle(target_indexes) return target_indexes @@ -861,8 +860,8 @@ def generate_targets(symbols: List[str], inquiry_count: int, percentage_without_target: percentage of inquiries for which target letter flashed is not in inquiry """ - nontarget_count = int(inquiry_count * (percentage_without_target / 100)) - target_count = inquiry_count - nontarget_count + target_count, no_target_count = compute_counts(inquiry_count, + percentage_without_target) # each symbol should appear at least once symbol_count = int(target_count / len(symbols)) or 1 @@ -870,6 +869,7 @@ def generate_targets(symbols: List[str], inquiry_count: int, random.shuffle(targets) return targets + def target_index(inquiry: List[str]) -> int: """Given an inquiry, return the index of the target within the choices and None if the target is not included as a choice. @@ -892,6 +892,7 @@ def target_index(inquiry: List[str]) -> int: except ValueError: return None + def get_task_info(experiment_length: int, task_color: str) -> Tuple[List[str], List[str]]: """Get Task Info. diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 49a116337..4a21b423b 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -33,9 +33,9 @@ def is_uniform_distribution(inquiry_count: int, stim_per_inquiry: int, """Determine if the counts in the provided counter are distributed uniformly.""" - nontarget_inquiries = (int)(inquiry_count * + no_target_inquiries = (int)(inquiry_count * (percentage_without_target / 100)) - target_inquiries = inquiry_count - nontarget_inquiries + target_inquiries = inquiry_count - no_target_inquiries expected_targets_per_position = (int)(target_inquiries / stim_per_inquiry) return all(expected_targets_per_position <= counter[pos] <= @@ -502,11 +502,11 @@ def test_random_target_positions_all_nontargets(self): def test_generate_targets(self): """Test target generation""" symbols = ['A', 'B', 'C', 'D'] - targets = generate_targets(symbols, inquiry_count = 9, percentage_without_target=0) + targets = generate_targets(symbols, inquiry_count=9, percentage_without_target=0) self.assertEqual(len(targets), 8) self.assertTrue(all(val == 2 for val in Counter(targets).values())) - targets = generate_targets(symbols, inquiry_count = 9, percentage_without_target=50) + targets = generate_targets(symbols, inquiry_count=9, percentage_without_target=50) self.assertEqual(len(targets), 4) self.assertTrue(all(val == 1 for val in Counter(targets).values())) @@ -610,7 +610,7 @@ def test_inquiry_target_counts(self): ['Q', '+', 'X', 'G', 'Z', 'J', 'V']] targeted = ['D', 'Q', 'W'] - not_targeted = list(set(self.alp) - set(targeted)) + not_targeted = list(set(self.alp) - set(targeted)) target_counts = inquiry_target_counts(inquiries, symbols=self.alp) self.assertTrue(all(target_counts[sym] == 1 for sym in targeted)) self.assertTrue(all(target_counts[sym] == 0 for sym in not_targeted)) @@ -624,12 +624,10 @@ def test_inquiry_nontarget_counts(self): ['B', '+', 'D', 'E', 'B'], ['C', '+', 'F', 'B', 'C']] - expected = {'A': 1, 'B': 3, 'C': 1, 'D': 1, 'E': 2, 'F': 2} counts = inquiry_nontarget_counts(inquiries, symbols=symbols) self.assertDictEqual(counts, expected) - def test_best_selection(self): """Test best_selection""" From 8ac3dd8b987dae4ed54fff33e90610bb8673f270 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 27 Jul 2023 14:23:49 -0700 Subject: [PATCH 046/330] Refinements based on feedback --- bcipy/parameters/parameters.json | 1 + bcipy/signal/model/offline_analysis.py | 4 ++-- bcipy/signal/process/__init__.py | 4 ++-- bcipy/signal/process/transform.py | 2 +- bcipy/task/control/evidence.py | 2 +- bcipy/task/tests/core/test_eeg_evaluator.py | 6 +++--- bcipy/task/tests/core/test_evidence.py | 10 +++++----- 7 files changed, 15 insertions(+), 14 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index baf528c57..516ee3c51 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -13,6 +13,7 @@ "readableName": "Acquisition Mode", "helpTip": "Specifies the hardware device(s) used for data collection.", "recommended_values": [ + "EEG", "EEG/DSI-24", "Eyetracker", "EEG+Eyetracker" diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index f51f12cb5..1b489c07b 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -23,7 +23,7 @@ from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel -from bcipy.signal.process import (TransformParams, filter_inquiries, +from bcipy.signal.process import (ERPTransformParams, filter_inquiries, get_default_transform) log = logging.getLogger(__name__) @@ -102,7 +102,7 @@ def offline_analysis( raw_data_file = f"{RAW_DATA_FILENAME}.csv" # get signal filtering information - transform_params = parameters.instantiate(TransformParams) + transform_params = parameters.instantiate(ERPTransformParams) downsample_rate = transform_params.down_sampling_rate static_offset = parameters.get("static_trigger_offset") diff --git a/bcipy/signal/process/__init__.py b/bcipy/signal/process/__init__.py index 689ae620f..ce21a5ae5 100644 --- a/bcipy/signal/process/__init__.py +++ b/bcipy/signal/process/__init__.py @@ -1,6 +1,6 @@ from bcipy.signal.process.filter import filter_inquiries from bcipy.signal.process.transform import (Composition, Downsample, - TransformParams, + ERPTransformParams, get_default_transform) __all__ = [ @@ -8,5 +8,5 @@ "get_default_transform", "Downsample", "Composition", - "TransformParams" + "ERPTransformParams" ] diff --git a/bcipy/signal/process/transform.py b/bcipy/signal/process/transform.py index 63886264e..14cda23f2 100644 --- a/bcipy/signal/process/transform.py +++ b/bcipy/signal/process/transform.py @@ -30,7 +30,7 @@ def __call__(self, data: np.ndarray, fs: Optional[int] = None) -> Tuple[np.ndarr return data[:, :: self.factor], None -class TransformParams(NamedTuple): +class ERPTransformParams(NamedTuple): """Parameters used for the default transform.""" notch_filter_frequency: int = 60 filter_low: int = 2 diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py index d1b98b322..0db138011 100644 --- a/bcipy/task/control/evidence.py +++ b/bcipy/task/control/evidence.py @@ -47,7 +47,7 @@ def evaluate(self, **kwargs): """Evaluate the evidence""" -class EegEvaluator(EvidenceEvaluator): +class EEGEvaluator(EvidenceEvaluator): """EvidenceEvaluator that extracts symbol likelihoods from raw EEG data. Parameters diff --git a/bcipy/task/tests/core/test_eeg_evaluator.py b/bcipy/task/tests/core/test_eeg_evaluator.py index 0d6e721d9..21a594a1a 100644 --- a/bcipy/task/tests/core/test_eeg_evaluator.py +++ b/bcipy/task/tests/core/test_eeg_evaluator.py @@ -3,7 +3,7 @@ import unittest from unittest.mock import Mock, patch -from bcipy.task.control.evidence import EegEvaluator +from bcipy.task.control.evidence import EEGEvaluator class TestEegEvaluator(unittest.TestCase): @@ -28,7 +28,7 @@ def setUp(self): @patch('bcipy.task.control.evidence.analysis_channels') def test_init(self, analysis_channels_mock): """Test initialization""" - EegEvaluator(self.symbol_set, self.signal_model_mock) + EEGEvaluator(self.symbol_set, self.signal_model_mock) analysis_channels_mock.assert_called_with(self.device_mock.channels, self.device_mock) @@ -60,7 +60,7 @@ def test_evaluate(self, reshaper_factory_mock, analysis_channels_mock): window_length = 0.5 # Run the code - evaluator = EegEvaluator(self.symbol_set, self.signal_model_mock) + evaluator = EEGEvaluator(self.symbol_set, self.signal_model_mock) evaluator.evaluate(raw_data, symbols, times, target_info, window_length) diff --git a/bcipy/task/tests/core/test_evidence.py b/bcipy/task/tests/core/test_evidence.py index 4b556edaf..4f0a994e0 100644 --- a/bcipy/task/tests/core/test_evidence.py +++ b/bcipy/task/tests/core/test_evidence.py @@ -4,7 +4,7 @@ from unittest.mock import Mock from bcipy.acquisition.multimodal import ContentType -from bcipy.task.control.evidence import (EegEvaluator, find_matching_evaluator, +from bcipy.task.control.evidence import (EEGEvaluator, find_matching_evaluator, get_evaluator) from bcipy.task.data import EvidenceType from bcipy.task.exceptions import MissingEvidenceEvaluator @@ -15,8 +15,8 @@ class TestEvidence(unittest.TestCase): def test_get_evaluator(self): """Test getting an evaluator""" - self.assertEqual(EegEvaluator, get_evaluator(ContentType.EEG)) - self.assertEqual(EegEvaluator, + self.assertEqual(EEGEvaluator, get_evaluator(ContentType.EEG)) + self.assertEqual(EEGEvaluator, get_evaluator(ContentType.EEG, EvidenceType.ERP)) def test_missing_evaluator(self): @@ -36,7 +36,7 @@ def test_find_matching_evaluator(self): meta_mock.device_spec = device_mock signal_model_mock.metadata = meta_mock - self.assertEqual(EegEvaluator, + self.assertEqual(EEGEvaluator, find_matching_evaluator(signal_model_mock)) def test_match_with_bad_evidence_type(self): @@ -49,7 +49,7 @@ def test_match_with_bad_evidence_type(self): meta_mock.evidence_type = 'NOT_AN_EVIDENCE_TYPE' signal_model_mock.metadata = meta_mock - self.assertEqual(EegEvaluator, + self.assertEqual(EEGEvaluator, find_matching_evaluator(signal_model_mock), "should ignore the evidence type") From 860a773579adc92a54bf027fe18436648a4897f5 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 1 Aug 2023 10:30:29 -0700 Subject: [PATCH 047/330] Change default value for percentage_without_target --- bcipy/helpers/stimuli.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 1992c3710..92e34d82a 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -493,7 +493,7 @@ def generate_calibration_inquiries( stim_per_inquiry: int = 10, stim_order: StimuliOrder = StimuliOrder.RANDOM, target_positions: TargetPositions = TargetPositions.RANDOM, - percentage_without_target: int = 10, + percentage_without_target: int = 0, is_txt: bool = True) -> InquirySchedule: """ Generates inquiries with target letters in all possible positions. From 5500012851afedfa32d3f9f3cc6afe3266e909b3 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Wed, 2 Aug 2023 09:54:46 -0700 Subject: [PATCH 048/330] Update log level to prevent pollution from matplotlib, update the useful logs to info --- bcipy/acquisition/datastream/lsl_server.py | 13 ++++++------- .../datastream/mock/eye_tracker_server.py | 4 ++-- bcipy/acquisition/datastream/producer.py | 2 +- bcipy/acquisition/demo/demo_lsl_server.py | 4 ++-- bcipy/acquisition/marker_writer.py | 2 +- bcipy/acquisition/multimodal.py | 2 +- bcipy/acquisition/protocols/lsl/lsl_client.py | 16 ++++++++-------- bcipy/acquisition/protocols/lsl/lsl_recorder.py | 10 +++++----- bcipy/gui/main.py | 2 +- bcipy/gui/viewer/data_source/file_streamer.py | 6 +++--- bcipy/helpers/copy_phrase_wrapper.py | 2 +- bcipy/helpers/load.py | 2 +- bcipy/helpers/system_utils.py | 2 +- bcipy/helpers/task.py | 2 +- bcipy/helpers/visualization.py | 2 +- bcipy/signal/model/cross_validation.py | 2 +- bcipy/task/control/criteria.py | 8 ++++---- .../paradigm/rsvp/calibration/calibration.py | 2 +- .../rsvp/calibration/timing_verification.py | 2 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 14 +++++++------- setup.py | 2 +- 21 files changed, 50 insertions(+), 51 deletions(-) diff --git a/bcipy/acquisition/datastream/lsl_server.py b/bcipy/acquisition/datastream/lsl_server.py index a94d731cd..80f8181fa 100644 --- a/bcipy/acquisition/datastream/lsl_server.py +++ b/bcipy/acquisition/datastream/lsl_server.py @@ -54,7 +54,7 @@ def __init__(self, device_spec: DeviceSpec, generator: Generator = None, include self.device_spec = device_spec self.generator = generator or random_data_generator(channel_count=device_spec.channel_count) - log.debug("Starting LSL server for device: %s", device_spec.name) + log.info("Starting LSL server for device: %s", device_spec.name) print(f"Serving: {device_spec}") info = StreamInfo(device_spec.name, device_spec.content_type, device_spec.channel_count, @@ -82,8 +82,7 @@ def __init__(self, device_spec: DeviceSpec, generator: Generator = None, include # "gUSBamp_" + boost::lexical_cast(deviceNumber) + # "_" + boost::lexical_cast(serialNumber) + # "_markers"); - log.debug("Creating marker stream") - print(f"Marker channel name: {marker_stream_name}") + log.info(f"Creating marker stream {marker_stream_name}") markers_info = StreamInfo(marker_stream_name, "Markers", 1, 0, 'string', "uid12345_markers") @@ -93,7 +92,7 @@ def __init__(self, device_spec: DeviceSpec, generator: Generator = None, include def stop(self): """Stop the thread and cleanup resources.""" - log.debug("[*] Stopping data server") + log.info("[*] Stopping data server") super(LslDataServer, self).stop() # Allows pylsl to cleanup; The outlet will no longer be discoverable @@ -129,7 +128,7 @@ def run(self): # deleted in another thread. break - log.debug("[*] No longer pushing data") + log.info("[*] No longer pushing data") def _settings(filename): @@ -194,9 +193,9 @@ def main(): try: server = LslDataServer(device_spec=device_spec, generator=generator, add_markers=markers) - log.debug("New server created") + log.info("New server created") server.start() - log.debug("Server started") + log.info("Server started") while True: time.sleep(1) except KeyboardInterrupt: diff --git a/bcipy/acquisition/datastream/mock/eye_tracker_server.py b/bcipy/acquisition/datastream/mock/eye_tracker_server.py index 82b7567f4..a0022a065 100644 --- a/bcipy/acquisition/datastream/mock/eye_tracker_server.py +++ b/bcipy/acquisition/datastream/mock/eye_tracker_server.py @@ -59,9 +59,9 @@ def main(): """Create an run an lsl_server""" try: server = eye_tracker_server() - log.debug("New server created") + log.info("New server created") server.start() - log.debug("Server started") + log.info("Server started") while True: time.sleep(1) except KeyboardInterrupt: diff --git a/bcipy/acquisition/datastream/producer.py b/bcipy/acquisition/datastream/producer.py index e40a3d484..1552f8780 100644 --- a/bcipy/acquisition/datastream/producer.py +++ b/bcipy/acquisition/datastream/producer.py @@ -105,7 +105,7 @@ def run(self): while True: if not self._q.empty(): item = self._q.get() - log.debug('Getting %s: %s items in queue', + log.info('Getting %s: %s items in queue', str(item), str(self._q.qsize())) time.sleep(random.random()) diff --git a/bcipy/acquisition/demo/demo_lsl_server.py b/bcipy/acquisition/demo/demo_lsl_server.py index 979c6885f..d654ebf21 100644 --- a/bcipy/acquisition/demo/demo_lsl_server.py +++ b/bcipy/acquisition/demo/demo_lsl_server.py @@ -23,9 +23,9 @@ def main(): try: server = LslDataServer(device_spec=device_spec) - log.debug("New server created") + log.info("New server created") server.start() - log.debug("Server started") + log.info("Server started") while True: time.sleep(1) except KeyboardInterrupt: diff --git a/bcipy/acquisition/marker_writer.py b/bcipy/acquisition/marker_writer.py index f4c13f462..b7c36d1ab 100644 --- a/bcipy/acquisition/marker_writer.py +++ b/bcipy/acquisition/marker_writer.py @@ -50,7 +50,7 @@ def push_marker(self, marker: Any): - marker : any object that can be converted to a str """ stamp = pylsl.local_clock() - log.debug(f'Pushing marker {str(marker)} at {stamp}') + log.info(f'Pushing marker {str(marker)} at {stamp}') self.markers_outlet.push_sample([str(marker)], stamp) if not self.first_marker_stamp: self.first_marker_stamp = stamp diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index b93136735..4426ab431 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -136,7 +136,7 @@ def get_data_by_device( client = self.get_client(content_type) if client.device_spec.sample_rate > 0: count = round(seconds * client.device_spec.sample_rate) - log.debug(f'Need {count} records for processing {name} data') + log.info(f'Need {count} records for processing {name} data') output[content_type] = client.get_data(start=start, limit=count) data_count = len(output[content_type]) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 4a5937320..1bf8c372d 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -103,13 +103,13 @@ def first_sample_time(self) -> float: def stop_acquisition(self) -> None: """Disconnect from the data source.""" - log.debug(f"Stopping Acquisition from {self.device_spec.name} ...") + log.info(f"Stopping Acquisition from {self.device_spec.name} ...") if self.recorder: - log.debug(f"Closing {self.device_spec.name} data recorder") + log.info(f"Closing {self.device_spec.name} data recorder") self.recorder.stop() self.recorder.join() if self.inlet: - log.debug("Closing LSL connection") + log.info("Closing LSL connection") self.inlet.close_stream() self.inlet = None @@ -140,7 +140,7 @@ def get_data(self, ------- List of Records """ - log.debug(f"Getting data from: {start} to: {end} limit: {limit}") + log.info(f"Getting data from: {start} to: {end} limit: {limit}") # Only data in the current buffer is available to query; # requests for data outside of this will fail. Buffer size is @@ -148,10 +148,10 @@ def get_data(self, data = self.get_latest_data() if not data: - log.debug('No records available') + log.info('No records available') return [] - log.debug((f'{len(data)} records available ' + log.info((f'{len(data)} records available ' f'(From: {data[0].timestamp} To: {data[-1].timestamp})')) start = start or data[0].timestamp end = end or data[-1].timestamp @@ -163,7 +163,7 @@ def get_data(self, data_slice = [ record for record in data if start <= record.timestamp <= end ][0:limit] - log.debug(f'{len(data_slice)} records returned') + log.info(f'{len(data_slice)} records returned') return data_slice @property @@ -293,7 +293,7 @@ def offset(self, first_stim_time: float) -> float: return 0.0 assert self.first_sample_time, "Acquisition was not started." offset_from_stim = first_stim_time - self.first_sample_time - log.debug(f"Acquisition offset: {offset_from_stim}") + log.info(f"Acquisition offset: {offset_from_stim}") return offset_from_stim def cleanup(self): diff --git a/bcipy/acquisition/protocols/lsl/lsl_recorder.py b/bcipy/acquisition/protocols/lsl/lsl_recorder.py index 9a8228adb..e6b504ef1 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_recorder.py +++ b/bcipy/acquisition/protocols/lsl/lsl_recorder.py @@ -35,7 +35,7 @@ def start(self): """Start recording all streams currently on the network.""" if not self.streams: - log.debug("Recording data") + log.info("Recording data") # create a thread for each. self.streams = [ LslRecordingThread(stream, self.path, @@ -127,7 +127,7 @@ def _init_data_writer(self, stream_info: StreamInfo) -> None: channels = self.device_spec.channels path = Path(self.directory, self.filename) - log.debug(f"Writing data to {path}") + log.info(f"Writing data to {path}") self.writer = RawDataWriter( path, daq_type=self.stream_info.name(), @@ -196,8 +196,8 @@ def run(self): inlet = StreamInlet(self.stream_info) full_metadata = inlet.info() - log.debug("Acquiring data from data stream:") - log.debug(full_metadata.as_xml()) + log.info("Acquiring data from data stream:") + log.info(full_metadata.as_xml()) self._reset() self._init_data_writer(full_metadata) @@ -212,7 +212,7 @@ def run(self): time.sleep(self.sleep_seconds) # Pull any remaining samples up to the current time. - log.debug("Pulling remaining samples") + log.info("Pulling remaining samples") record_count = self._pull_chunk(inlet) while record_count == self.max_chunk_size: record_count = self._pull_chunk(inlet) diff --git a/bcipy/gui/main.py b/bcipy/gui/main.py index 932dfb9f0..b4c729974 100644 --- a/bcipy/gui/main.py +++ b/bcipy/gui/main.py @@ -706,7 +706,7 @@ class BCIGui(QWidget): def __init__(self, title: str, width: int, height: int, background_color: str): super(BCIGui, self).__init__() - logging.basicConfig(level=logging.DEBUG, + logging.basicConfig(level=logging.INFO, format='%(name)s - %(levelname)s - %(message)s') self.logger = logging diff --git a/bcipy/gui/viewer/data_source/file_streamer.py b/bcipy/gui/viewer/data_source/file_streamer.py index 328c84481..dd725b98a 100644 --- a/bcipy/gui/viewer/data_source/file_streamer.py +++ b/bcipy/gui/viewer/data_source/file_streamer.py @@ -24,11 +24,11 @@ def __init__(self, data_file, data_queue): self.data_queue = data_queue def run(self): - log.debug("Starting raw_data file streamer") + log.info("Starting raw_data file streamer") with RawDataReader(self.data_file, convert_data=True) as reader: fs = reader.sample_rate - log.debug(f"Publishing data at sample rate {fs} hz") + log.info(f"Publishing data at sample rate {fs} hz") # publish data for data in reader: @@ -36,4 +36,4 @@ def run(self): break self.data_queue.put(data) time.sleep(1 / fs) - log.debug("Stopping raw_data file streamer") + log.info("Stopping raw_data file streamer") diff --git a/bcipy/helpers/copy_phrase_wrapper.py b/bcipy/helpers/copy_phrase_wrapper.py index ec7126be7..6dbb4c200 100644 --- a/bcipy/helpers/copy_phrase_wrapper.py +++ b/bcipy/helpers/copy_phrase_wrapper.py @@ -204,7 +204,7 @@ def initialize_series(self) -> Tuple[bool, InquirySchedule]: ] # display histogram of LM probabilities - log.debug(histogram(lm_letter_prior)) + log.info(histogram(lm_letter_prior)) # Try fusing the lmodel evidence try: diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index c00e4c815..8f36024d5 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -155,7 +155,7 @@ def load_json_parameters(path: str, value_cast: bool = False) -> Parameters: def load_experimental_data() -> str: filename = ask_directory() # show dialog box and return the path - log.debug("Loaded Experimental Data From: %s" % filename) + log.info("Loaded Experimental Data From: %s" % filename) return filename diff --git a/bcipy/helpers/system_utils.py b/bcipy/helpers/system_utils.py index c6882b0e6..9b3c6b2cf 100644 --- a/bcipy/helpers/system_utils.py +++ b/bcipy/helpers/system_utils.py @@ -194,7 +194,7 @@ def get_system_info() -> dict: def configure_logger( save_folder: str, log_name=LOG_FILENAME, - log_level=logging.DEBUG, + log_level=logging.INFO, version=None) -> None: """Configure Logger. diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index f66453c05..e135f3b8e 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -154,7 +154,7 @@ def get_data_for_decision(inquiry_timing, # Define the amount of data required for any processing to occur. data_limit = round((time2 - time1 + poststim) * daq.device_spec.sample_rate) - log.debug(f'Need {data_limit} records for processing') + log.info(f'Need {data_limit} records for processing') # Query for raw data raw_data = daq.get_data(start=time1, limit=data_limit) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 0eceb5362..8a2a00890 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -117,7 +117,7 @@ def visualize_csv_eeg_triggers(trigger_col: Optional[int] = None): plt.ylabel('Trigger Value') plt.xlabel('Samples') - log.debug('Press Ctrl + C to exit!') + log.info('Press Ctrl + C to exit!') # Show us the figure! Depending on your OS / IDE this may not close when # The window is closed, see the message above plt.show() diff --git a/bcipy/signal/model/cross_validation.py b/bcipy/signal/model/cross_validation.py index b79c67f21..f2ecff702 100644 --- a/bcipy/signal/model/cross_validation.py +++ b/bcipy/signal/model/cross_validation.py @@ -142,7 +142,7 @@ def cross_validation(x, y, model, opt_el=1, k_folds=10, split='uniform'): gamma and AUC values for each fold respectively. """ - log.debug('Starting Cross Validation !') + log.info('Starting Cross Validation !') arg_opt = nonlinear_opt(model, opt_el, x, y, op_type='cost_auc', arg_op_type=[k_folds, split]) return arg_opt diff --git a/bcipy/task/control/criteria.py b/bcipy/task/control/criteria.py index 9e1ef128e..29249dbd4 100644 --- a/bcipy/task/control/criteria.py +++ b/bcipy/task/control/criteria.py @@ -50,7 +50,7 @@ def decide(self, series: Dict): # than this, since the language model distribution is added before # the first inquiry is displayed. current_inq = len(series['list_sti']) - log.debug( + log.info( f"Checking min iterations; current iteration is {current_inq}") return current_inq < self.min_num_inq @@ -82,7 +82,7 @@ def decide(self, series: Dict): # see MinIterationsCriteria comment current_inq = len(series['list_sti']) if current_inq >= self.max_num_inq: - log.debug( + log.info( "Committing to decision: max iterations have been reached.") return True return False @@ -103,7 +103,7 @@ def __init__(self, threshold: float): def decide(self, series: Dict): current_distribution = series['list_distribution'][-1] if np.max(current_distribution) > self.tau: - log.debug("Committing to decision: posterior exceeded threshold.") + log.info("Committing to decision: posterior exceeded threshold.") return True return False @@ -132,7 +132,7 @@ def decide(self, series: Dict): stopping_rule = np.abs(candidates[0] - candidates[1]) d = stopping_rule > self.margin if d: - log.debug("Committing to decision: margin is high enough.") + log.info("Committing to decision: margin is high enough.") return d diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 67afd017d..6aef7d1dd 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -121,7 +121,7 @@ def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: def execute(self): - self.logger.debug(f'Starting {self.name()}!') + self.logger.info(f'Starting {self.name()}!') run = True # Check user input to make sure we should be going diff --git a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py index 259cd3583..70262a2be 100644 --- a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py +++ b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py @@ -62,7 +62,7 @@ def generate_stimuli(self): return (samples, times, colors) def execute(self): - self.logger.debug(f'Starting {self.name()}!') + self.logger.info(f'Starting {self.name()}!') self._task.execute() @classmethod diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index e62b28c8e..704cbefcb 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -243,7 +243,7 @@ def starting_spelled_letters(self) -> int: """Number of letters already spelled at the start of the task.""" spelled_letters_count = self.parameters['spelled_letters_count'] if spelled_letters_count > len(self.copy_phrase): - self.logger.debug('Already spelled letters exceeds phrase length.') + self.logger.info('Already spelled letters exceeds phrase length.') spelled_letters_count = 0 return spelled_letters_count @@ -294,7 +294,7 @@ def user_wants_to_continue(self) -> bool: self.parameters['stim_color'], first_run=self.first_run) if not should_continue: - self.logger.debug('User wants to exit.') + self.logger.info('User wants to exit.') return should_continue def wait(self, seconds: float = None): @@ -368,23 +368,23 @@ def check_stop_criteria(self) -> bool: should continue. """ if self.copy_phrase == self.spelled_text: - self.logger.debug('Spelling complete') + self.logger.info('Spelling complete') return False if (self.inq_counter + 1) >= self.parameters['max_inq_len']: - self.logger.debug('Max tries exceeded: to allow for more tries' + self.logger.info('Max tries exceeded: to allow for more tries' ' adjust the Maximum inquiry Length ' '(max_inq_len) parameter.') return False if self.session.total_time_spent >= (self.parameters['max_minutes'] * 60): - self.logger.debug('Max time exceeded. To allow for more time ' + self.logger.info('Max time exceeded. To allow for more time ' 'adjust the max_minutes parameter.') return False if self.session.total_number_decisions >= self.parameters['max_selections']: - self.logger.debug('Max number of selections reached ' + self.logger.info('Max number of selections reached ' '(configured with the max_selections parameter)') return False @@ -405,7 +405,7 @@ def execute(self) -> str: ------- data save location (triggers.txt, session.json) """ - self.logger.debug('Starting Copy Phrase Task!') + self.logger.info('Starting Copy Phrase Task!') run = True self.wait() # buffer for data processing diff --git a/setup.py b/setup.py index 72c4c503c..b08607348 100644 --- a/setup.py +++ b/setup.py @@ -13,7 +13,7 @@ AUTHOR = 'CAMBI' REQUIRES_PYTHON = '>3.7,<3.10' -VERSION = '2.0.0rc3' +VERSION = '2.0.0rc4' REQUIRED = [] From 9742baa46f88c3290d1946fb510e51dd037f0eec Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Wed, 2 Aug 2023 10:01:21 -0700 Subject: [PATCH 049/330] fix lint errors --- bcipy/acquisition/datastream/producer.py | 2 +- bcipy/acquisition/protocols/lsl/lsl_client.py | 2 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 8 ++++---- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/bcipy/acquisition/datastream/producer.py b/bcipy/acquisition/datastream/producer.py index 1552f8780..e5ad0c079 100644 --- a/bcipy/acquisition/datastream/producer.py +++ b/bcipy/acquisition/datastream/producer.py @@ -106,7 +106,7 @@ def run(self): if not self._q.empty(): item = self._q.get() log.info('Getting %s: %s items in queue', - str(item), str(self._q.qsize())) + str(item), str(self._q.qsize())) time.sleep(random.random()) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 1bf8c372d..1a5afa53f 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -152,7 +152,7 @@ def get_data(self, return [] log.info((f'{len(data)} records available ' - f'(From: {data[0].timestamp} To: {data[-1].timestamp})')) + f'(From: {data[0].timestamp} To: {data[-1].timestamp})')) start = start or data[0].timestamp end = end or data[-1].timestamp limit = limit or -1 diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 704cbefcb..e31a733f0 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -373,19 +373,19 @@ def check_stop_criteria(self) -> bool: if (self.inq_counter + 1) >= self.parameters['max_inq_len']: self.logger.info('Max tries exceeded: to allow for more tries' - ' adjust the Maximum inquiry Length ' - '(max_inq_len) parameter.') + ' adjust the Maximum inquiry Length ' + '(max_inq_len) parameter.') return False if self.session.total_time_spent >= (self.parameters['max_minutes'] * 60): self.logger.info('Max time exceeded. To allow for more time ' - 'adjust the max_minutes parameter.') + 'adjust the max_minutes parameter.') return False if self.session.total_number_decisions >= self.parameters['max_selections']: self.logger.info('Max number of selections reached ' - '(configured with the max_selections parameter)') + '(configured with the max_selections parameter)') return False return True From c204a459eb1b28cf59e86fc6fb54364ed80adedd Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Wed, 2 Aug 2023 10:04:05 -0700 Subject: [PATCH 050/330] Update changelog --- CHANGELOG.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 4b8772129..c9e2e8b44 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,19 @@ +# 2.0.0-rc.4 + +Our last release candidate before the official 2.0 release! + +## Contributions + +- Multimodal Acquisition and Querying + - Support for multiple devices in online querying #286 +- Stimuli + - Updates to ensure stimuli are presented at the same frequency #287 +- Parameters + - Add a Range type parameter #285 +- Cleanup + - Change default log level to INFO to prevent too many messages in the experiment logs #288 + + # 2.0.0-rc.3 ## Contributions From f31cde820656b033248a4cf0e76f7ab909a7bb74 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 8 Aug 2023 18:03:52 -0700 Subject: [PATCH 051/330] update to use a trial_window parameter --- bcipy/helpers/demo/demo_visualization.py | 4 ++-- bcipy/helpers/stimuli.py | 14 +++++++------ bcipy/helpers/visualization.py | 26 +++++++++++++++++++++--- bcipy/parameters/parameters.json | 10 ++++----- bcipy/signal/model/offline_analysis.py | 20 ++++++++++++------ bcipy/signal/process/transform.py | 10 ++++----- bcipy/task/paradigm/rsvp/copy_phrase.py | 20 ++++++++++-------- 7 files changed, 69 insertions(+), 35 deletions(-) diff --git a/bcipy/helpers/demo/demo_visualization.py b/bcipy/helpers/demo/demo_visualization.py index dffc0401d..a6194d0d3 100644 --- a/bcipy/helpers/demo/demo_visualization.py +++ b/bcipy/helpers/demo/demo_visualization.py @@ -50,7 +50,7 @@ parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) # extract all relevant parameters - poststim_length = parameters.get("trial_length") + trial_window = parameters.get("trial_window") prestim_length = parameters.get("prestim_length") trials_per_inquiry = parameters.get("stim_length") # The task buffer length defines the min time between two inquiries @@ -96,7 +96,7 @@ channel_map, trigger_timing, labels, - poststim_length, + trial_window, transform=default_transform, plot_average=True, plot_topomaps=True, diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 92e34d82a..fed0fe595 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -295,19 +295,21 @@ def update_inquiry_timing(timing: List[List[float]], downsample: int) -> List[Li return timing -def mne_epochs(mne_data: RawArray, trigger_timing: List[float], - trial_length: float, trigger_labels: List[int]) -> Epochs: +def mne_epochs(mne_data: RawArray, + trigger_timing: List[float], + trial_length: float, + trigger_labels: List[int], + baseline: Tuple[float, float] = (None, 0.0), + buffer=0.1) -> Epochs: """MNE Epochs. Using an MNE RawArray, reshape the data given trigger information. If two labels present [0, 1], each may be accessed by numbered order. Ex. first_class = epochs['1'], second_class = epochs['2'] """ - annotations = Annotations(trigger_timing, [trial_length] * len(trigger_timing), trigger_labels) + annotations = Annotations(trigger_timing, [trial_length + buffer] * len(trigger_timing), trigger_labels) mne_data.set_annotations(annotations) - events_from_annot, _ = mne.events_from_annotations(mne_data) - return Epochs(mne_data, events_from_annot) - + return Epochs(mne_data, events_from_annot, tmax=trial_length, baseline=baseline) def alphabetize(stimuli: List[str]) -> List[str]: """Alphabetize. diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 8a2a00890..c9d88a6b6 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -28,7 +28,7 @@ def visualize_erp( channel_map: List[int], trigger_timing: List[float], trigger_labels: List[int], - trial_length: float, + trial_window: Tuple[float, float], transform: Optional[Composition] = None, plot_average: Optional[bool] = True, plot_topomaps: Optional[bool] = True, @@ -55,8 +55,17 @@ def visualize_erp( show: Optional[boolean]: whether or not to show the figures generated. Default: False save_path: optional path to a save location of the figure generated """ + # check for trial length in seconds + trial_length = trial_window[1] - 0.0 + + # check for baseline interval + if trial_window[0] < 0: + baseline = (trial_window[0], 0) + else: + baseline = (None, 0) + mne_data = convert_to_mne(raw_data, channel_map=channel_map, transform=transform) - epochs = mne_epochs(mne_data, trigger_timing, trial_length, trigger_labels) + epochs = mne_epochs(mne_data, trigger_timing, trial_length, trigger_labels, baseline=baseline) # *Note* We assume, as described above, two trigger classes are defined for use in trigger_labels # (Nontarget=0 and Target=1). This will map into two corresponding MNE epochs whose indexing starts at 1. # Therefore, epochs['1'] == Nontarget and epochs['2'] == Target. @@ -65,7 +74,18 @@ def visualize_erp( if plot_average: figs.extend(visualize_evokeds(epochs, save_path=save_path, show=show)) if plot_topomaps: - figs.extend(visualize_joint_average(epochs, ['Non-Target', 'Target'], save_path=save_path, show=show)) + # make a list of equally spaced times to plot topomaps using the time window + # defined in the task parameters + times = [round(trial_window[0] + i * (trial_window[1] - trial_window[0]) / 5, 1) for i in range(6)] + + # clip any times that are out of bounds of the time window or zero + times = [time for time in times if trial_window[0] <= time <= trial_window[1] and time != 0] + + figs.extend(visualize_joint_average( + epochs, ['Non-Target', 'Target'], + save_path=save_path, + show=show, + plot_joint_times=times)) return figs diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 516ee3c51..64f89220a 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -47,13 +47,13 @@ "recommended_values": "[10]", "type": "int" }, - "trial_length": { - "value": "0.5", + "trial_window": { + "value": "0.2:0.8", "section": "bci_config", - "readableName": "Data Collection Window Length", - "helpTip": "Specifies the length (in seconds) of the EEG data collection window after each stimulus presentation. Default: 0.5", + "readableName": "Trial Classification Window Length", + "helpTip": "Specifies the window (in seconds) of the EEG data collection window after each stimulus presentation. Default: 0.0:0.5", "recommended_values": "", - "type": "float" + "type": "range" }, "prestim_length": { "value": "1", diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 1b489c07b..789a83dd0 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -93,7 +93,9 @@ def offline_analysis( data_folder = load_experimental_data() # extract relevant session information from parameters file - poststim_length = parameters.get("trial_length") + trial_window = parameters.get("trial_window") + window_length = trial_window[1] - trial_window[0] + prestim_length = parameters.get("prestim_length") trials_per_inquiry = parameters.get("stim_length") # The task buffer length defines the min time between two inquiries @@ -109,7 +111,8 @@ def offline_analysis( log.info( f"\nData processing settings: \n" f"{str(transform_params)} \n" - f"Poststimulus: {poststim_length}s, Prestimulus: {prestim_length}s, Buffer: {buffer}s \n" + f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " + f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer}s \n" f"Static offset: {static_offset}" ) @@ -144,6 +147,10 @@ def offline_analysis( trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], ) + + # update the trigger timing list to account for the initial trial window + corrected_trigger_timing = [timing + trial_window[0] for timing in trigger_timing] + # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module # The timestamp column [0] is already excluded. channel_map = analysis_channels(channels, device_spec) @@ -154,19 +161,19 @@ def offline_analysis( inquiries, inquiry_labels, inquiry_timing = model.reshaper( trial_targetness_label=trigger_targetness, - timing_info=trigger_timing, + timing_info=corrected_trigger_timing, eeg_data=data, sample_rate=sample_rate, trials_per_inquiry=trials_per_inquiry, channel_map=channel_map, - poststimulus_length=poststim_length, + poststimulus_length=window_length, prestimulus_length=prestim_length, transformation_buffer=buffer, ) inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) - trial_duration_samples = int(poststim_length * fs) + trial_duration_samples = int(window_length * fs) data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) # define the training classes using integers, where 0=nontargets/1=targets @@ -194,12 +201,13 @@ def offline_analysis( log.info(f"Balanced acc with 80/20 split: {score}") del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds + # this should have uncorrected trigger timing for display purposes figure_handles = visualize_erp( raw_data, channel_map, trigger_timing, labels, - poststim_length, + trial_window, transform=default_transform, plot_average=True, plot_topomaps=True, diff --git a/bcipy/signal/process/transform.py b/bcipy/signal/process/transform.py index 14cda23f2..679832fdb 100644 --- a/bcipy/signal/process/transform.py +++ b/bcipy/signal/process/transform.py @@ -39,11 +39,11 @@ class ERPTransformParams(NamedTuple): down_sampling_rate: int = 2 def __str__(self): - return ', '.join([ - f"Filter: [{self.filter_low}-{self.filter_high}]" - f"Order: {self.filter_order}", - f"Notch: {self.notch_filter_frequency}", - f"Downsample: {self.down_sampling_rate}" + return ' '.join([ + f"Filter: [{self.filter_low}-{self.filter_high}] Hz \n" + f"Order: {self.filter_order} \n", + f"Notch: {self.notch_filter_frequency} Hz \n", + f"Downsample: {self.down_sampling_rate} \n" ]) diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index e31a733f0..bc2f45c5e 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -572,22 +572,26 @@ def compute_device_evidence( if not proceed or self.fake: return [] - # currently prestim_length is used as a buffer for filter application; - # use the same at the end of the inquiry - post_stim_buffer = self.parameters['prestim_length'] - prestim = self.parameters['prestim_length'] + # currently prestim_length is used as a buffer for filter application + post_stim_buffer = int(self.parameters.get("task_buffer_length") / 2) + prestim_buffer = self.parameters['prestim_length'] + trial_window = self.parameters['trial_window'] + window_length = trial_window[1] - trial_window[0] inquiry_timing = self.stims_for_decision(stim_times) + # update the inquiry timing list (stim, time) based on the trial window first time value + inquiry_timing = [(stim, time + trial_window[0]) for stim, time in inquiry_timing] + # Get all data at once so we don't redundantly query devices which are # used in more than one signal model. device_data = get_device_data_for_decision( inquiry_timing=inquiry_timing, daq=self.daq, offset=self.parameters['static_trigger_offset'], - prestim=prestim, - poststim=post_stim_buffer + self.parameters['trial_length']) + prestim=prestim_buffer, + poststim=post_stim_buffer + window_length) - triggers = relative_triggers(inquiry_timing, prestim) + triggers = relative_triggers(inquiry_timing, prestim_buffer) # we assume all are nontargets at this point labels = ['nontarget'] * len(triggers) letters, times, filtered_labels = self.copy_phrase_task.letter_info( @@ -600,7 +604,7 @@ def compute_device_evidence( symbols=letters, times=times, target_info=filtered_labels, - window_length=self.parameters['trial_length']) + window_length=window_length) evidences.append((evidence_evaluator.produces, probs)) return evidences From 23337c6abbcaadccb7166ce3a2772e1309a22c3a Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 8 Aug 2023 18:23:27 -0700 Subject: [PATCH 052/330] update to include an epoch buffer and rename --- bcipy/helpers/stimuli.py | 7 ++++--- bcipy/helpers/visualization.py | 2 +- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index fed0fe595..6976408f3 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -300,16 +300,17 @@ def mne_epochs(mne_data: RawArray, trial_length: float, trigger_labels: List[int], baseline: Tuple[float, float] = (None, 0.0), - buffer=0.1) -> Epochs: + epoch_buffer=0.1) -> Epochs: """MNE Epochs. Using an MNE RawArray, reshape the data given trigger information. If two labels present [0, 1], each may be accessed by numbered order. Ex. first_class = epochs['1'], second_class = epochs['2'] """ - annotations = Annotations(trigger_timing, [trial_length + buffer] * len(trigger_timing), trigger_labels) + plot_length = trial_length + epoch_buffer + annotations = Annotations(trigger_timing, [plot_length] * len(trigger_timing), trigger_labels) mne_data.set_annotations(annotations) events_from_annot, _ = mne.events_from_annotations(mne_data) - return Epochs(mne_data, events_from_annot, tmax=trial_length, baseline=baseline) + return Epochs(mne_data, events_from_annot, tmax=plot_length, baseline=baseline) def alphabetize(stimuli: List[str]) -> List[str]: """Alphabetize. diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index c9d88a6b6..f7032a2e4 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -76,7 +76,7 @@ def visualize_erp( if plot_topomaps: # make a list of equally spaced times to plot topomaps using the time window # defined in the task parameters - times = [round(trial_window[0] + i * (trial_window[1] - trial_window[0]) / 5, 1) for i in range(6)] + times = [round(trial_window[0] + i * (trial_window[1] - trial_window[0]) / 5, 1) for i in range(7)] # clip any times that are out of bounds of the time window or zero times = [time for time in times if trial_window[0] <= time <= trial_window[1] and time != 0] From 5f7287289d5af175e4163de26a7d1045bc087061 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Wed, 9 Aug 2023 21:52:39 -0700 Subject: [PATCH 053/330] working replay session with windows and older parameter files Note: the older signal models cannot be used on a newer codebase... remove unusable load methods after refactor --- bcipy/helpers/load.py | 35 +- bcipy/helpers/stimuli.py | 4 +- bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 10 +- scripts/python/replay_session.py | 366 ++++++++---------- 4 files changed, 173 insertions(+), 242 deletions(-) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 8f36024d5..f7b14aa87 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -159,37 +159,6 @@ def load_experimental_data() -> str: return filename -def load_signal_model(model_class: SignalModel, - model_kwargs: Dict[str, Any], filename: str = None) -> Tuple[SignalModel, str]: - """Construct the specified model and load pretrained parameters. - - Args: - model_class (SignalModel, optional): Model class to construct. - model_kwargs (dict, optional): Keyword arguments for constructing model. - filename (str, optional): Location of pretrained model parameters. - - Returns: - SignalModel: Model after loading pretrained parameters. - """ - # use python's internal gui to call file explorers and get the filename - if not filename or Path(filename).is_dir(): - directory = filename or preferences.signal_model_directory - filename = ask_filename('*.pkl', directory) - - # update preferences - path = Path(filename) - if path.is_file(): - preferences.signal_model_directory = str(path.parent) - - # load the signal_model with pickle - signal_model = model_class(**model_kwargs) - signal_model.load(filename) - - log.info(f'Loaded signal model from {filename}') - - return signal_model, filename - - def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: """Load all signal models in a given directory. @@ -211,8 +180,8 @@ def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: models = [] for file_path in path.glob(f"*{SIGNAL_MODEL_FILE_SUFFIX}"): - with open(file_path, "rb") as file: - model = pickle.load(file) + with open(file_path, "rb") as signal_file: + model = pickle.load(signal_file) log.info(f"Loading model {model}") models.append(model) return models diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 6976408f3..27e19c45e 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -29,6 +29,7 @@ log = logging.getLogger(__name__) DEFAULT_FIXATION_PATH = 'bcipy/static/images/main/PLUS.png' DEFAULT_TEXT_FIXATION = '+' +NO_TARGET_INDEX = None class StimuliOrder(Enum): @@ -484,9 +485,6 @@ def best_case_rsvp_inq_gen(alp: list, return InquirySchedule(samples, times, colors) -NO_TARGET_INDEX = None - - def generate_calibration_inquiries( alp: List[str], timing: List[float] = None, diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index 4910107c1..faab1de69 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -171,12 +171,14 @@ def predict_proba(self, data: np.array) -> np.array: posterior = np.exp(np.stack([log_post_0, log_post_1], axis=-1)) return posterior - def save(self, path: Path): + def save(self, path: Path) -> None: """Save model weights (e.g. after training) to `path`""" with open(path, "wb") as f: pickle.dump(self.model, f) - def load(self, path: Path): - """Load pretrained model weights from `path`""" + def load(self, path: Path) -> SignalModel: + """Load pretrained model from `path`""" with open(path, "rb") as f: - self.model = pickle.load(f) + model = pickle.load(f) + + return model diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 6d02b1f49..7ef0f30d2 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -1,7 +1,9 @@ """Script that will replay sessions and allow us to simulate new model predictions on that data.""" import json import logging as logger +from typing import Tuple from pathlib import Path +import pickle import matplotlib.pyplot as plt import numpy as np @@ -17,215 +19,152 @@ import bcipy.acquisition.devices as devices from bcipy.helpers.list import grouper from bcipy.helpers.load import load_json_parameters, load_raw_data -from bcipy.helpers.stimuli import InquiryReshaper, TrialReshaper, update_inquiry_timing +from bcipy.helpers.stimuli import InquiryReshaper, update_inquiry_timing from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.symbols import alphabet from bcipy.signal.model import PcaRdaKdeModel -from bcipy.signal.process import get_default_transform +from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams -logger.getLogger() +logger.getLogger().setLevel(logger.INFO) -SYMBOLS = alphabet() - - -def load_model(model_path: Path, k_folds: int): - """Load the PcaRdaKdeModel model at the given path""" - model = PcaRdaKdeModel(k_folds=k_folds) - model.load(model_path) +def load_model(model_path: Path, k_folds: int, model_class=PcaRdaKdeModel): + """Load the model at the given path""" + with open(model_path, "rb") as f: + model = pickle.load(f) + breakpoint() return model -def comparison1(data_folder, parameters, model_path: Path): - """Check that we get trials from correct positions""" - - # extract relevant session information from parameters file - trial_length = parameters.get("trial_length") +def generate_replay_outputs( + data_folder, + parameters, + model_path: Path, + model_class=PcaRdaKdeModel, + symbol_set=alphabet(), + write_output=False) -> Tuple[dict, list, list]: + """Replay a session and generate outputs for the provided model. + + Parameters + ---------- + data_folder: Path + Path to the data folder containing the session data (session.json, raw_data.csv, triggers.txt) + parameters: dict + Parameters to use for the replay session. + model_path: Path + Path to the model to use for the replay session. + model_class: class + Class of the model to use for the replay session. By default, this is PcaRdaKdeModel. + symbol_set: list + List of symbols to use for the replay session. By default, this is the alphabet. + write_output: bool + Whether or not to write the output to a file. By default, this is False. + + Returns + ------- + tuple - new_model_outputs, old_model_target_output, old_model_nontarget_output + """ + k_folds = parameters.get("k_folds") + model = load_model(model_path, k_folds, model_class) + logger.info(f"Loaded model from {model_path}") + + # get trial information; to make backwards compatible, we will try to get the trial length + # from the parameters file (old), but if it's not there, we use the trial window and adjust timing (>2.0). + adjust_trials_by_window = False + trial_length = parameters.get("trial_length", None) + if trial_length is None: + trial_window = parameters.get("trial_window") + trial_length = trial_window[1] - trial_window[0] + adjust_trials_by_window = True + logger.info(f"Trial Window: {trial_window[0]}-{trial_window[1]}s") + trials_per_inquiry = parameters.get("stim_length") prestim_length = parameters.get("prestim_length", trial_length) - # time_flash = parameters.get("time_flash") + buffer_length = int(parameters.get("task_buffer_length") / 2) # get signal filtering information - downsample_rate = parameters.get("down_sampling_rate") - notch_filter = parameters.get("notch_filter_frequency") - hp_filter = parameters.get("filter_high") - lp_filter = parameters.get("filter_low") - filter_order = parameters.get("filter_order") static_offset = parameters.get("static_trigger_offset") k_folds = parameters.get("k_folds") + transform_params = parameters.instantiate(ERPTransformParams) + downsample_rate = transform_params.down_sampling_rate + + logger.info( + f"\nData processing settings: \n" + f"{str(transform_params)} \n" + f"Trial Length: {trial_length}s, Trials per Inquiry: {trials_per_inquiry} \n" + f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer_length}s \n" + f"Static offset: {static_offset}" + ) - # Load raw data raw_data = load_raw_data(Path(data_folder, f"{RAW_DATA_FILENAME}.csv")) channels = raw_data.channels type_amp = raw_data.daq_type sample_rate = raw_data.sample_rate - devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) device_spec = devices.preconfigured_device(raw_data.daq_type) - - logger.info(f"Channels read from csv: {channels}") - logger.info(f"Device type: {type_amp}") - - # data = raw_data.by_channel() - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=notch_filter, - bandpass_low=lp_filter, - bandpass_high=hp_filter, - bandpass_order=filter_order, - downsample_factor=downsample_rate, - ) - data, transformed_sample_rate = default_transform(raw_data.by_channel(), sample_rate) - - # Process triggers.txt - trigger_targetness, trigger_timing, trigger_labels = trigger_decoder( - offset=static_offset, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT], - ) - # Channel map can be checked from raw_data.csv file. - # The timestamp column is already excluded. channel_map = analysis_channels(channels, device_spec) - model = load_model(model_path, k_folds) + # extract the raw data for the channels we care about. The channel map will further reduce this if necessary. + # by default, only the sample number and internal trigger channels are excluded. + raw_data, _ = raw_data.by_channel() - # data , [0: 1, 0, 1], [0, ... , n] - inquiries, _, inquiry_timing = InquiryReshaper()( - trial_targetness_label=trigger_targetness, - timing_info=trigger_timing, - eeg_data=data, - sample_rate=transformed_sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=trial_length, - prestimulus_length=prestim_length, - transformation_buffer=trial_length, # use this to add time to the end of the Inquiry for processing! - ) - - # NOTE - - # If doing: Raw -> filter -> inquiries -> InquiryReshaper.extract_trials - # Then do: use downsample_rate=1 during InquiryReshaper.extract_trials - # If doing: Raw -> inquiries -> filter -> InquiryReshaper.extract_trials - # Then do: use downsample_rate=2 during InquiryReshaper.extract_trials - - # Uncomment to filter by inquiries - # inquiries = filter_inquiries(inquiries, default_transform, sample_rate) - trial_duration_samples = int(trial_length * transformed_sample_rate) - inquiry_timing = update_inquiry_timing(inquiry_timing, transformed_sample_rate) - trials = InquiryReshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) - - # "Can we get the trials from exact same time windows" - # 1a: raw data -> filtered data -> TrialReshaper - # 1b: raw data -> filtered -> InquiryReshaper -> TrialReshaper - # Note that we're not doing the same kind of preprocessing - # as we do "online". - # uncomment to validate against the trial reshaper. Note: check reshape parameters are set correctly! - validate_response = validate_inquiry_based_trials_against_trial_reshaper( - raw_data, - raw_data.sample_rate, - model, - default_transform, - trigger_targetness, - trigger_timing, - trials_per_inquiry, - channel_map, - trial_length, - trials, - ) - logger.info(f"Inquiry trials == trial reshaper? {validate_response}") - assert validate_response - - -def generate_replay_outputs(data_folder, parameters, model_path: Path, write_output=False): - """Try running a previous model as follows. Shouldn't get errors. - - # 2a (real, online model): raw -> inquiries -> filter -> trials -> model preds - # 2b (trying to replay): raw data -> InquiryReshaper -> filtered -> TrialReshaper - - raw data -> inquiries -> filter -> trials -> run model - """ - - # extract relevant session information from parameters file - trial_length = parameters.get("trial_length") - trials_per_inquiry = parameters.get("stim_length") - prestim_length = parameters.get("prestim_length", trial_length) - # time_flash = parameters.get("time_flash") - - # get signal filtering information - downsample_rate = parameters.get("down_sampling_rate") - notch_filter = parameters.get("notch_filter_frequency") - hp_filter = parameters.get("filter_high") - lp_filter = parameters.get("filter_low") - filter_order = parameters.get("filter_order") - static_offset = parameters.get("static_trigger_offset") - k_folds = parameters.get("k_folds") - - # Load raw data - raw_data = load_raw_data(Path(data_folder, f"{RAW_DATA_FILENAME}.csv")) - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - - devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) - - logger.info(f"Channels read from csv: {channels}") logger.info(f"Device type: {type_amp}") + logger.info(f"Channels read from csv: {channels}") + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + logger.info(f'Channels used in analysis: {channels_used}') - # Process triggers.txt trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( offset=static_offset, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT], ) - # Channel map can be checked from raw_data.csv file. - # The timestamp column is already excluded. - channel_map = analysis_channels(channels, device_spec) - model = load_model(model_path, k_folds) + # Adjust trigger timing by trial window if necessary + if adjust_trials_by_window: + trigger_timing = [timing + trial_window[0] for timing in trigger_timing] - # data , [0: 1, 0, 1], [0, ... , n] inquiries, inquiry_labels, inquiry_timing = InquiryReshaper()( trial_targetness_label=trigger_targetness, timing_info=trigger_timing, - eeg_data=raw_data.by_channel(), - fs=sample_rate, + eeg_data=raw_data, + sample_rate=sample_rate, trials_per_inquiry=trials_per_inquiry, channel_map=channel_map, poststimulus_length=trial_length, prestimulus_length=prestim_length, - transformation_buffer=trial_length, # use this to add time to the end of the Inquiry for processing! + transformation_buffer=buffer_length, ) default_transform = get_default_transform( sample_rate_hz=sample_rate, - notch_freq_hz=notch_filter, - bandpass_low=lp_filter, - bandpass_high=hp_filter, - bandpass_order=filter_order, - downsample_factor=downsample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, ) + inquiries, transformed_sample_rate = filter_inquiries(inquiries, default_transform, sample_rate) trial_duration_samples = int(trial_length * transformed_sample_rate) - inquiry_timing = update_inquiry_timing(inquiry_timing, transformed_sample_rate) + inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) trials = InquiryReshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) - alpha = alphabet() + # get the model outputs using the reshaped data outputs = {} inquiry_worth_of_trials = np.split(trials, inquiries.shape[1], 1) inquiry_worth_of_letters = grouper(trigger_symbols, trials_per_inquiry, incomplete="ignore") for i, (inquiry_trials, this_inquiry_letters, this_inquiry_labels) in enumerate( zip(inquiry_worth_of_trials, inquiry_worth_of_letters, inquiry_labels) ): - response = model.predict(inquiry_trials, this_inquiry_letters, symbol_set=alpha) + response = model.predict(inquiry_trials, this_inquiry_letters, symbol_set=symbol_set) if np.any(this_inquiry_labels == 1): index_of_target_trial = np.argwhere(this_inquiry_labels == 1)[0][0] target_letter = this_inquiry_letters[index_of_target_trial] - target_index_in_alphabet = alpha.index(target_letter) + target_index_in_alphabet = symbol_set.index(target_letter) - nontarget_idx_in_alphabet = [alpha.index(q) for q in this_inquiry_letters if q != target_letter] + nontarget_idx_in_alphabet = [symbol_set.index(q) for q in this_inquiry_letters if q != target_letter] else: target_index_in_alphabet = None - nontarget_idx_in_alphabet = [alpha.index(q) for q in this_inquiry_letters] + nontarget_idx_in_alphabet = [symbol_set.index(q) for q in this_inquiry_letters] outputs[i] = { "eeg_evidence": list(response), @@ -237,14 +176,31 @@ def generate_replay_outputs(data_folder, parameters, model_path: Path, write_out with open(data_folder / "replay_outputs.json", "w") as f: json.dump(outputs, f, indent=2) - # Get values computed during actual experiment from session.json + # TODO separate this from the method + # Get values computed during actual experiment from session.json for comparison session_json = data_folder / SESSION_DATA_FILENAME - all_target_eeg, all_nontarget_eeg = load_from_session_json(session_json) + all_target_eeg, all_nontarget_eeg = load_eeg_evidence_from_session_json(session_json, symbol_set) return outputs, all_target_eeg, all_nontarget_eeg -def load_from_session_json(session_json) -> list: +def load_eeg_evidence_from_session_json(session_json, symbol_set) -> Tuple[list, list]: + """Load EEG evidence from session.json file for comparison with replay outputs. + + Parameters + ---------- + session_json : str + Path to session.json file + symbol_set : list + List of symbols used in experiment + + Returns + ------- + all_target_eeg : list + List of EEG evidence for target stimuli + all_nontarget_eeg : list + List of EEG evidence for nontarget stimuli + """ with open(session_json, "r") as f: contents = json.load(f) series = contents["series"] @@ -258,10 +214,10 @@ def load_from_session_json(session_json) -> list: continue else: stim_label = inquiry["stimuli"][0] # name of symbols presented - stim_label.pop(0) - stim_indices = [SYMBOLS.index(sym) for sym in stim_label] + stim_label.pop(0) # remove fixation cross + stim_indices = [symbol_set.index(sym) for sym in stim_label] targetness = inquiry["target_info"] # targetness of stimuli - # target_letter = inquiry['target_letter'] + targetness.pop(0) # remove fixation cross target = [index for index, label in zip(stim_indices, targetness) if label == "target"] nontarget = [index for index, label in zip(stim_indices, targetness) if label == "nontarget"] all_target_eeg.extend([inquiry["eeg_evidence"][pos] for pos in target]) @@ -270,49 +226,27 @@ def load_from_session_json(session_json) -> list: return all_target_eeg, all_nontarget_eeg -def validate_inquiry_based_trials_against_trial_reshaper( - raw_data, - sample_rate, - model, - transform, - trigger_targetness, - trigger_timing, - trials_per_inquiry, - channel_map, - trial_length, - inquiry_trials, -): - """Add np.allclose(new_trials, trials)""" - data, sample_rate = transform(raw_data.by_channel(), sample_rate) - # because the reshapers can change timing with offsets, we should still return the timing that updated - trials, _targetness_labels = TrialReshaper()( - trial_targetness_label=trigger_targetness, - timing_info=trigger_timing, - eeg_data=data, - sample_rate=sample_rate, - channel_map=channel_map, - poststimulus_length=trial_length, - ) - - logger.info(f"is finite (trials): {np.all(np.isfinite(trials))}") - logger.info(f"is finite (inquiry_trials): {np.all(np.isfinite(inquiry_trials))}") - is_allclose = np.allclose(trials, inquiry_trials) - logger.info(f"Is allclose: {is_allclose}") - return is_allclose - - -def filter_inquiries(inquiries, transform, sample_rate): - old_shape = inquiries.shape # (C, I, 699) - inq_flatten = inquiries.reshape(-1, old_shape[-1]) # (C*I, 699) - inq_flatten_filtered, transformed_sample_rate = transform(inq_flatten, sample_rate) - inquiries = inq_flatten_filtered.reshape(*old_shape[:2], inq_flatten_filtered.shape[-1]) # (C, I, ...) - return inquiries, transformed_sample_rate - - -def plot_collected_outputs(outputs_with_new_model, targets_with_old_model, nontargets_with_old_model, outdir): +def plot_collected_outputs( + outputs_with_new_model: dict, + targets_with_old_model: list, + nontargets_with_old_model: list, + outdir: str) -> None: + """Plot collected outputs from replay experiment. + + Parameters + ---------- + outputs_with_new_model : dict + List of outputs from replay experiment using new model + targets_with_old_model : list + List of outputs from the session data using old model for target stimuli + nontargets_with_old_model : list + List of outputs from the session using old model for nontarget stimuli + outdir : str + Path to directory to save plots + """ records = [] for output in outputs_with_new_model: # each session - for inquiry_idx, inquiry_contents in output.items(): # each inquiry + for _, inquiry_contents in output.items(): # each inquiry target_idx = inquiry_contents["target_idx"] if target_idx is not None: records.append( @@ -373,30 +307,58 @@ def plot_collected_outputs(outputs_with_new_model, targets_with_old_model, nonta import argparse parser = argparse.ArgumentParser() - parser.add_argument("-d", "--data_folders", action="append", type=Path, default=None) + parser.add_argument( + "-d", + "--data_folders", + action="append", + type=Path, + required=True, + help="Session data folders to be processed. This argument can be repeated to accumulate sessions data.") parser.add_argument("-m", "--model_file", required=True) - outdir = Path(__file__).resolve().parent - logger.info(f"Outdir: {outdir}") + parser.add_argument("-o", "--outdir", type=Path, default=None) + parser.add_argument( + "-p", + "--parameter_file", + type=Path, + default=None, + help="Parameter file to be used for replay. If none, the session parameter file will be used.") + args = parser.parse_args() assert len(set(args.data_folders)) == len(args.data_folders), "Duplicated data folders" + if args.outdir is None: + args.outdir = Path(__file__).resolve().parent + + logger.info(f"Outdir: {args.outdir}") + outputs_with_new_model = [] targets_with_old_model = [] nontargets_with_old_model = [] for data_folder in args.data_folders: logger.info(f"Processing {data_folder}") - params_file = Path(data_folder, DEFAULT_PARAMETER_FILENAME) + + if args.parameter_file is not None: + params_file = args.parameter_file + else: + params_file = Path(data_folder, DEFAULT_PARAMETER_FILENAME) logger.info(f"Loading params from {params_file}") params = load_json_parameters(params_file, value_cast=True) - comparison1(data_folder, params, args.model_file) + + # Generate replay outputs using the model provided against the session data in data_folder outputs, all_target_eeg, all_nontarget_eeg = generate_replay_outputs( - data_folder, params, args.model_file, write_output=True + data_folder, params, args.model_file, write_output=False ) outputs_with_new_model.append(outputs) targets_with_old_model.extend(all_target_eeg) nontargets_with_old_model.extend(all_nontarget_eeg) - plot_collected_outputs(outputs_with_new_model, targets_with_old_model, nontargets_with_old_model, outdir) + plot_collected_outputs( + outputs_with_new_model, + targets_with_old_model, + nontargets_with_old_model, + args.outdir) + + breakpoint() logger.info("Replay complete.") From 4d79b5a300362459d63c032514586f9d024ff616 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 18 Aug 2023 11:23:01 -0700 Subject: [PATCH 054/330] Functionality for computing grid positions using psychopy 'norm' units --- bcipy/display/components/layout.py | 83 +++++++++++++++---- bcipy/display/paradigm/matrix/layout.py | 57 +++++++++++++ .../paradigm/matrix/test_matrix_layout.py | 83 +++++++++++++++++++ 3 files changed, 206 insertions(+), 17 deletions(-) create mode 100644 bcipy/display/paradigm/matrix/layout.py create mode 100644 bcipy/display/tests/paradigm/matrix/test_matrix_layout.py diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index 1091c52d3..c9bd3d083 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -1,9 +1,10 @@ """Defines common functionality for GUI layouts.""" -from typing import Tuple +from typing import Protocol, Tuple + from psychopy import visual -class Container: +class Container(Protocol): """Protocol for an enclosing container with units and size.""" win: visual.Window size: Tuple[float, float] @@ -28,21 +29,6 @@ def units(self): return self.win.units -def at_top(parent: Container, height: float): - """Constructs a layout of a given height that spans the full width of the - window and is positioned at the top. - - Parameters - ---------- - height - value in 'norm' units - """ - return Layout(parent=parent, - left=-1.0, - top=1.0, - right=1.0, - bottom=1.0 - height) - - class Layout(Container): """Base class for a component with methods for positioning elements. """ @@ -127,3 +113,66 @@ def left_middle(self) -> Tuple[float, float]: def right_middle(self) -> Tuple[float, float]: """Point centered on the right-most edge.""" return (self.right, self.vertical_middle) + + def above(self, y_coordinate: float, amount: float) -> float: + """Returns a new y_coordinate value that is above the provided value + by the given amount.""" + # assert self.bottom <= y_coordinate <= self.top, "y_coordinate out of range" + assert amount >= 0, 'Amount must be positive' + return y_coordinate + amount + + def below(self, y_coordinate: float, amount: float) -> float: + """Returns a new y_coordinate value that is below the provided value + by the given amount.""" + # assert self.bottom <= y_coordinate <= self.top, "y_coordinate out of range" + assert amount >= 0, 'Amount must be positive' + return y_coordinate - amount + + def right_of(self, x_coordinate: float, amount: float) -> float: + """Returns a new x_coordinate value that is to the right of the + provided value by the given amount.""" + # assert self.left <= x_coordinate <= self.right, "y_coordinate out of range" + assert amount >= 0, 'Amount must be positive' + return x_coordinate + amount + + def left_of(self, x_coordinate: float, amount: float) -> float: + """Returns a new x_coordinate value that is to the left of the + provided value by the given amount.""" + # assert self.left <= x_coordinate <= self.right, "y_coordinate out of range" + assert amount >= 0, 'Amount must be positive' + return x_coordinate - amount + + +def at_top(parent: Container, height: float): + """Constructs a layout of a given height that spans the full width of the + window and is positioned at the top. + + Parameters + ---------- + height - value in 'norm' units + """ + return Layout(parent=parent, + left=-1.0, + top=1.0, + right=1.0, + bottom=1.0 - height) + + +def centered(parent: Container, width: float = None, height: float = None): + """Constructs a centered layout""" + + +def below(layout: Layout, width: float = None, height: float = None): + """Constructs a layout below another layout. + + Parameters + ---------- + layout - another layout relative to the one constructed. Other + properties will be copied from this one. + """ + # TODO: account for height + return Layout(parent=layout.parent, + left=-1.0, + top=layout.bottom, + right=1.0, + bottom=-1.0) \ No newline at end of file diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py new file mode 100644 index 000000000..682a2a66a --- /dev/null +++ b/bcipy/display/paradigm/matrix/layout.py @@ -0,0 +1,57 @@ +"""Functions for calculating matrix layouts""" +from typing import List, Tuple + +from bcipy.display.components.layout import Layout + + +def symbol_positions(layout: Layout, rows: int, + columns: int) -> List[Tuple[float, float]]: + """Compute the positions for arranging a number of symbols in a grid + layout. + + Parameters + ---------- + layout - layout in which the grid should be placed + rows - number of rows in the grid + columns - number of columns in the grid + + Returns + ------- + list of (x,y) tuples with (rows * columns) positions in row,col order + """ + assert rows >= 1 and columns >= 1, "There must be at least one row and one column" + + # compute the spacing (in layout units) from the layout width and height + horizontal_spacing = layout.width / (rows + 1) + vertical_spacing = layout.height / (columns + 1) + spacing = min(horizontal_spacing, vertical_spacing) + half_space = spacing / 2 + + # Work back from center to compute the starting position + center_x, center_y = layout.center + spaces_left_of_center = int(columns / 2) + start_pos_left = layout.left_of(center_x, spaces_left_of_center * spacing) + if columns % 2 == 0 and columns > 1: + # even number of columns; adjust start_pos so that center_x is between + # the middle two items. + start_pos_left = layout.right_of(start_pos_left, half_space) + + spaces_above_center = int(rows / 2) + start_pos_top = layout.above(center_y, spaces_above_center * spacing) + if rows % 2 == 0 and rows > 1: + start_pos_top = layout.below(start_pos_top, half_space) + + # adjust the beginning x,y values so adding a space results in the first + # position. + x_coord = layout.left_of(start_pos_left, spacing) + y_coord = layout.above(start_pos_top, spacing) + + positions = [] + for _row in range(rows): + y_coord = layout.below(y_coord, spacing) + x_coord = layout.left_of(start_pos_left, spacing) + for _col in range(columns): + x_coord = layout.right_of(x_coord, spacing) + positions.append((x_coord, y_coord)) + + return positions \ No newline at end of file diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py new file mode 100644 index 000000000..d6d115b4e --- /dev/null +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py @@ -0,0 +1,83 @@ +"""Tests for Matrix layout functions""" +import unittest + +from mockito import mock + +from bcipy.display.components.layout import Layout, WindowContainer +from bcipy.display.paradigm.matrix.layout import symbol_positions + + +class TestMatrixLayout(unittest.TestCase): + """Tests for calculating the grid layout""" + + def setUp(self): + """Set up needed items for test.""" + self.window = mock({"size": (500, 500), "units": "norm"}) + self.container = WindowContainer(win=self.window) + self.layout = Layout(parent=self.container, + left=-1.0, + top=1.0, + right=1.0, + bottom=-1.0) + + def test_regular_grid(self): + """Test basic properties of a regular grid""" + row_count = 4 + col_count = 5 + positions = symbol_positions(self.layout, + rows=row_count, + columns=col_count) + self.assertEqual(len(positions), 20) + + x_coords = [pos[0] for pos in positions] + y_coords = [pos[1] for pos in positions] + self.assertEqual(len(set(y_coords)), row_count) + self.assertEqual(len(set(x_coords)), col_count) + + def test_single_row(self): + """Test position calculations for a single row""" + + positions = symbol_positions(self.layout, rows=1, columns=10) + self.assertEqual(len(positions), 10) + + y_coord = positions[0][1] + self.assertEqual(y_coord, self.layout.center[1], + "y-values should be centered") + self.assertTrue(all(pos[1] == y_coord for pos in positions), + "all coordinates have the same y-value") + self.assertEqual(len(set(pos[0] for pos in positions)), len(positions), + "all x-values should be different") + self.assertTrue( + all(self.layout.left <= pos[0] <= self.layout.right + for pos in positions), + "all x-values should be within the bounds of the display") + + self.assertAlmostEqual(abs(self.layout.left - positions[0][0]), + abs(self.layout.right - positions[-1][0]), + msg="should have the same left and right gap") + # should all be equally spaced + + def test_single_column(self): + """Test position calculations for a single column""" + positions = symbol_positions(self.layout, rows=10, columns=1) + self.assertEqual(len(positions), 10) + + x_coord = positions[0][0] + self.assertEqual(x_coord, self.layout.center[0], + "x-values should be centered") + self.assertTrue(all(pos[0] == x_coord for pos in positions), + "all coordinates have the same x-value") + self.assertEqual(len(set(pos[1] for pos in positions)), len(positions), + "all y-values should be different") + self.assertTrue( + all(self.layout.bottom <= pos[1] <= self.layout.top + for pos in positions), + "all y-values should be within the bounds of the display") + + self.assertAlmostEqual(abs(self.layout.top - positions[0][1]), + abs(self.layout.bottom - positions[-1][1]), + msg="should have the same top and bottom gap") + + +if __name__ == '__main__': + unittest.main() \ No newline at end of file From bf20fd4d025588d3a2aaecf66b68e5f0af7104f3 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Fri, 18 Aug 2023 15:37:24 -0400 Subject: [PATCH 055/330] GazeReshaper updates --- bcipy/helpers/stimuli.py | 49 ++++++++------------------ bcipy/signal/model/offline_analysis.py | 19 +++++++--- scripts/python/plot_inquiry_data.py | 40 ++++++++------------- 3 files changed, 44 insertions(+), 64 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 2a501c72d..d4d509bf5 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -176,6 +176,8 @@ def get_inquiry_len(inq_trigs): stop = first_trigger + num_samples_per_inq + buffer_samples reshaped_data.append(eeg_data[:, start:stop]) + breakpoint() + return np.stack(reshaped_data, 1), labels, reshaped_trigger_timing @staticmethod @@ -229,7 +231,8 @@ def extract_trials( class GazeReshaper: def __call__(self, trial_targetness_label: List[str], - timing_info: List[float], + inq_start_times: List[float], + target_symbols: List[str], gaze_data: np.ndarray, sample_rate: int, trials_per_inquiry: int, @@ -238,7 +241,8 @@ def __call__(self, poststimulus_length: float = 0.5, prestimulus_length: float = 0.0, transformation_buffer: float = 0.0, - target_label: str = 'target') -> Tuple[np.ndarray, np.ndarray]: + target_label: str = 'target' + ) -> Tuple[np.ndarray, np.ndarray]: """Extract inquiry data and labels. Args: @@ -268,38 +272,17 @@ def __call__(self, channels_to_remove = [idx for idx, value in enumerate(channel_map) if value == 0] gaze_data = np.delete(gaze_data, channels_to_remove, axis=0) - n_inquiry = len(timing_info) // trials_per_inquiry - trial_duration_samples = int(poststimulus_length * sample_rate) + n_inquiry = len(inq_start_times) prestimulus_samples = int(prestimulus_length * sample_rate) - # triggers in seconds are mapped to triggers in number of samples. - triggers = list(map(lambda x: int((x + offset) * sample_rate), timing_info)) - - inquiry_triggers = list(map(lambda x: int(x * sample_rate), timing_info)) - - - # First, find the longest inquiry in this experiment - # We'll add or remove a few samples from all other inquiries, to match this length - def get_inquiry_len(inq_trigs): - return inq_trigs[-1] - inq_trigs[0] - - # Finds the longest inquiry in the experiment by subtracting the first trigger from the last trigger in each inquiry - longest_inquiry = max(grouper(triggers, trials_per_inquiry, fillvalue='x'), key=lambda xy: get_inquiry_len(xy)) - # What we need is to find the shortest distance from 1st letter to last in each inquiry - shortest_inquiry = min(grouper(triggers, inquiry_triggers, trials_per_inquiry, fillvalue='x')) - - # We will trim off the extra bits in each inquiry to match the shortest inquiry - - - - num_samples_per_inq = get_inquiry_len(longest_inquiry) + trial_duration_samples - buffer_samples = int(transformation_buffer * sample_rate) + # triggers in seconds are mapped to triggers in number of samples. + triggers = list(map(lambda x: int(x * sample_rate), inq_start_times)) + # TODO: This ends up adding ~300ms shift to the triggers. Why? # Label for every inquiry - labels = np.zeros( - (n_inquiry, trials_per_inquiry), dtype=np.compat.long - ) # maybe this can be configurable? return either class indexes or labels ('nontarget' etc) + labels = target_symbols + reshaped_data, reshaped_trigger_timing = [], [] for inquiry_idx, trials_within_inquiry in enumerate( grouper(zip(trial_targetness_label, triggers), trials_per_inquiry, fillvalue='x') @@ -308,15 +291,13 @@ def get_inquiry_len(inq_trigs): trial_triggers = [] for trial_idx, (trial_label, trigger) in enumerate(trials_within_inquiry): - if trial_label == target_label: - labels[inquiry_idx, trial_idx] = 1 - # If presimulus buffer is used, we add it here so that trigger timings will # still line up with trial onset + breakpoint() trial_triggers.append((trigger - first_trigger) + prestimulus_samples) reshaped_trigger_timing.append(trial_triggers) - start = first_trigger - prestimulus_samples - stop = first_trigger + num_samples_per_inq + buffer_samples + start = first_trigger + stop = first_trigger + (sample_rate * 3) # (60 samples * 3 seconds) reshaped_data.append(gaze_data[:, start:stop]) breakpoint() diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 372633da0..01500d260 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -267,22 +267,33 @@ def offline_analysis( trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( remove_pre_fixation = False, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.OFFSET], + #exclusion=[TriggerType.PREVIEW, TriggerType.EVENT] + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.SYSTEM, TriggerType.OFFSET] ) + ''' Trigger_timing includes PROMPT and excludes FIXATION ''' + # Use trigger_timing to generate time windows for each letter flashing + # Take every 10th trigger as the start point of timing. x = list(range(1000)), x[0::10] does that! + # trigger_targetness keeps the PROMPT info, use it to find the target symbol! + target_symbols = trigger_symbols[0::11] # target symbols + inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) + breakpoint() + + # Need to calculate the starting index, using inq_start. inquiries, inquiry_labels, inquiry_timing = model.reshaper( trial_targetness_label=trigger_targetness, - timing_info=trigger_timing, + inq_start_times=inq_start, + target_symbols = target_symbols, gaze_data=data, sample_rate=sample_rate, trials_per_inquiry=trials_per_inquiry, channel_map=channel_map, poststimulus_length=poststim_length, prestimulus_length=prestim_length, - transformation_buffer=buffer, + transformation_buffer=buffer ) - breakpoint() + # Merge subset of time windows if they have the same target symbol: if alert_finished: diff --git a/scripts/python/plot_inquiry_data.py b/scripts/python/plot_inquiry_data.py index 4243ad134..21e4a2130 100644 --- a/scripts/python/plot_inquiry_data.py +++ b/scripts/python/plot_inquiry_data.py @@ -2,22 +2,24 @@ from bcipy.config import STATIC_IMAGES_PATH DIPSIZE = (1707, 1067) -IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' +IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix.png' TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' def load_eye_tracking_data(path): data = load(f'{path}/{TOBII_FILENAME}') - left_eye_channel_map = [0,0,1,1,0,0,0,0,0] + left_eye_channel_map = [0,0,1,1,1,0,0,0,0] left_eye_data, _, _ = data.by_channel_map(left_eye_channel_map) left_eye_x = left_eye_data[0] left_eye_y = left_eye_data[1] + left_pupil = left_eye_data[2] - right_eye_channel_map = [0,0,0,0,0,1,1,0,0] + right_eye_channel_map = [0,0,0,0,0,1,1,1,0] right_eye_data, _, _ = data.by_channel_map(right_eye_channel_map) right_eye_x = right_eye_data[0] right_eye_y = right_eye_data[1] - return left_eye_x, left_eye_y, right_eye_x, right_eye_y + right_pupil = right_eye_data[2] + return left_eye_x, left_eye_y, left_pupil, right_eye_x, right_eye_y, right_pupil if __name__ == "__main__": @@ -44,7 +46,8 @@ def load_eye_tracking_data(path): path = load_experimental_data() data = load_eye_tracking_data(path) - lx, ly, rx, ry = data + lx, ly, lp, rx, ry, rp = data + dpi = 100 @@ -73,32 +76,17 @@ def load_eye_tracking_data(path): # ax.plot(rx, ry, c='b', linewidth=1) # # remove nan values - # lx = lx[~np.isnan(lx)] - # ly = ly[~np.isnan(ly)] - # rx = rx[~np.isnan(rx)] - # ry = ry[~np.isnan(ry)] + lx = lx[~np.isnan(lx)] + ly = ly[~np.isnan(ly)] + rx = rx[~np.isnan(rx)] + ry = ry[~np.isnan(ry)] # determine kde of the eye data # ax = sns.kdeplot(rx, ry, cmap="mako", fill=False, thresh=0.05, levels=10) - lx_inq = lx[48368:48535] - ly_inq = ly[48368:48535] - rx_inq = rx[48368:48535] - ry_inq = ry[48368:48535] - # remove nan values - lx_inq = lx_inq[~np.isnan(lx_inq)] - ly_inq = ly_inq[~np.isnan(ly_inq)] - rx_inq = rx_inq[~np.isnan(rx_inq)] - ry_inq = ry_inq[~np.isnan(ry_inq)] - - - ax.scatter(lx_inq, ly_inq, c='r', s=1) - ax.scatter(rx_inq, ry_inq, c='b', s=1) - - - # ax.scatter(lx, ly, c='r', s=1) - # ax.scatter(rx, ry, c='b', s=1) + ax.scatter(lx, ly, c='r', s=1) + ax.scatter(rx, ry, c='b', s=1) plt.show() From 8350d7cb17c14e22ccd7e28e6aabf14fcd354d67 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 18 Aug 2023 13:35:25 -0700 Subject: [PATCH 056/330] Refactor matrix display to use StimuliProperties for stim height --- .../demo/matrix/demo_calibration_matrix.py | 10 +++---- .../demo/matrix/demo_copyphrase_matrix.py | 8 ++--- bcipy/display/paradigm/matrix/display.py | 29 ++++++++++++------- 3 files changed, 28 insertions(+), 19 deletions(-) diff --git a/bcipy/display/demo/matrix/demo_calibration_matrix.py b/bcipy/display/demo/matrix/demo_calibration_matrix.py index 6dd8038ac..0ffa90234 100644 --- a/bcipy/display/demo/matrix/demo_calibration_matrix.py +++ b/bcipy/display/demo/matrix/demo_calibration_matrix.py @@ -1,11 +1,11 @@ """Demo Matrix Display functionality related to Calibration task logic.""" # pylint: disable=invalid-name from psychopy import core -from bcipy.display import InformationProperties, StimuliProperties -from bcipy.display.paradigm.matrix.display import MatrixDisplay -from bcipy.display.components.task_bar import CalibrationTaskBar -from bcipy.display import init_display_window +from bcipy.display import (InformationProperties, StimuliProperties, + init_display_window) +from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.matrix.display import MatrixDisplay info = InformationProperties( info_color=['white'], @@ -17,7 +17,7 @@ stim_properties = StimuliProperties(stim_font='Arial', stim_pos=(-0.6, 0.4), - stim_height=0.1, + stim_height=0.17, is_txt_stim=True) # Initialize Stimulus diff --git a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py index 10fcf340d..dca9c7e2c 100644 --- a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py +++ b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py @@ -5,10 +5,10 @@ from psychopy import core -from bcipy.display import (init_display_window, InformationProperties, - StimuliProperties) -from bcipy.display.paradigm.matrix.display import MatrixDisplay +from bcipy.display import (InformationProperties, StimuliProperties, + init_display_window) from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.paradigm.matrix.display import MatrixDisplay info = InformationProperties( info_color=['White'], @@ -23,7 +23,7 @@ stim_properties = StimuliProperties(stim_font='Arial', stim_pos=(-0.6, 0.4), - stim_height=0.1, + stim_height=0.17, is_txt_stim=True) # Initialize Stimulus diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 2b4d00ab8..c12a351ae 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -1,14 +1,15 @@ """Display for presenting stimuli in a grid.""" -from typing import Dict, List, Optional, Tuple, NamedTuple import logging +from typing import Dict, List, NamedTuple, Optional, Tuple -from psychopy import visual, core +from psychopy import core, visual -from bcipy.display import Display, StimuliProperties, InformationProperties, BCIPY_LOGO_PATH +from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, + StimuliProperties) +from bcipy.display.components.task_bar import TaskBar from bcipy.helpers.stimuli import resize_image -from bcipy.helpers.triggers import _calibration_trigger from bcipy.helpers.symbols import alphabet -from bcipy.display.components.task_bar import TaskBar +from bcipy.helpers.triggers import _calibration_trigger class SymbolDuration(NamedTuple): @@ -79,7 +80,7 @@ def __init__( # Set position and parameters for grid of alphabet self.position = stimuli.stim_pos - self.grid_stimuli_height = .17 + self.grid_stimuli_height = stimuli.stim_height self.position_increment = self.grid_stimuli_height + .05 self.max_grid_width = 0.7 @@ -163,17 +164,25 @@ def build_grid(self) -> Dict[str, visual.TextStim]: Builds a 7x4 matrix of stimuli. """ grid = {} - pos = self.position - for sym in self.symbol_set: + positions = self.symbol_positions() + for i, sym in enumerate(self.symbol_set): grid[sym] = visual.TextStim(win=self.window, text=sym, color=self.grid_color, opacity=self.start_opacity, - pos=pos, + pos=positions[i], height=self.grid_stimuli_height) - pos = self.increment_position(pos) return grid + def symbol_positions(self) -> List[Tuple[float, float]]: + """Compute the symbol positions""" + positions = [] + pos = self.position + for _sym in self.symbol_set: + positions.append(pos) + pos = self.increment_position(pos) + return positions + def increment_position(self, pos: Tuple[float, float]) -> Tuple[float, float]: """Computes the position of the next symbol in the matrix.""" x_coordinate, y_coordinate = pos From 72100848fd7b5a60fb8bd50e4a8ca1ea99cf8db5 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 18 Aug 2023 17:11:33 -0700 Subject: [PATCH 057/330] Refactored matrix display to use the new module for computing positions; added parameters for rows and columns. --- bcipy/display/components/layout.py | 93 +++++++++++++++---- bcipy/display/main.py | 3 +- bcipy/display/paradigm/matrix/display.py | 32 ++----- bcipy/display/paradigm/matrix/layout.py | 31 ++++--- .../paradigm/matrix/test_matrix_display.py | 17 +--- 5 files changed, 102 insertions(+), 74 deletions(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index c9bd3d083..ee33de35a 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -1,4 +1,5 @@ """Defines common functionality for GUI layouts.""" +from enum import Enum from typing import Protocol, Tuple from psychopy import visual @@ -29,12 +30,22 @@ def units(self): return self.win.units +DEFAULT_LEFT = -1.0 +DEFAULT_TOP = 1.0 +DEFAULT_RIGHT = 1.0 +DEFAULT_BOTTOM = -1.0 + + class Layout(Container): - """Base class for a component with methods for positioning elements. + """Class with methods for positioning elements within a parent container. """ - def __init__(self, parent: Container, left: float, top: float, - right: float, bottom: float): + def __init__(self, + parent: Container, + left: float = DEFAULT_LEFT, + top: float = DEFAULT_TOP, + right: float = DEFAULT_RIGHT, + bottom: float = DEFAULT_BOTTOM): self.parent = parent self.top = top @@ -143,7 +154,13 @@ def left_of(self, x_coordinate: float, amount: float) -> float: return x_coordinate - amount -def at_top(parent: Container, height: float): +class Alignment(Enum): + CENTERED = 1 + LEFT = 2 + RIGHT = 3 + + +def at_top(parent: Container, height: float) -> Layout: """Constructs a layout of a given height that spans the full width of the window and is positioned at the top. @@ -151,28 +168,64 @@ def at_top(parent: Container, height: float): ---------- height - value in 'norm' units """ + top = DEFAULT_TOP return Layout(parent=parent, - left=-1.0, - top=1.0, - right=1.0, - bottom=1.0 - height) - - -def centered(parent: Container, width: float = None, height: float = None): - """Constructs a centered layout""" + left=DEFAULT_LEFT, + top=top, + right=DEFAULT_RIGHT, + bottom=top - height) - -def below(layout: Layout, width: float = None, height: float = None): - """Constructs a layout below another layout. +def at_bottom(parent: Container, height: float) -> Layout: + """Constructs a layout of a given height that spans the full width of the + window and is positioned at the bottom""" + bottom = DEFAULT_BOTTOM + return Layout(parent=parent, + left=DEFAULT_LEFT, + top=DEFAULT_BOTTOM + height, + right=DEFAULT_RIGHT, + bottom=bottom) + + +def horizontally_aligned(parent: Layout, + alignment: Alignment, + width: float = None) -> Tuple[float, float]: + """Returns a tuple of (left, right), indicating the values to be used""" + + left = parent.left + right = parent.right + if width: + margin = parent.width - width + if alignment == Alignment.CENTERED: + half_margin = margin / 2 + left = left + half_margin + right = right - half_margin + elif alignment == Alignment.LEFT: + right = right - margin + elif alignment == Alignment.RIGHT: + left = left + margin + return left, right + + +def below(layout: Layout, + width_pct: float = 1.0, + alignment: Alignment = Alignment.CENTERED): + """Constructs a layout immediately below another layout. Parameters ---------- layout - another layout relative to the one constructed. Other properties will be copied from this one. + width_pct - percentage of the available width. """ - # TODO: account for height + width = layout.width * width_pct + + left, right = horizontally_aligned(layout, alignment, width) + top = layout.bottom + # bottom = top - height if height else DEFAULT_BOTTOM + bottom = DEFAULT_BOTTOM + return Layout(parent=layout.parent, - left=-1.0, - top=layout.bottom, - right=1.0, - bottom=-1.0) \ No newline at end of file + left=left, + top=top, + right=right, + bottom=bottom) \ No newline at end of file diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 444bd2d89..8512fb98d 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -131,7 +131,7 @@ class StimuliProperties: def __init__( self, stim_font: str, - stim_pos: Tuple[float, float], + stim_pos: Union[Tuple[float, float], List[Tuple[float, float]]], stim_height: float, stim_inquiry: List[str] = None, stim_colors: List[str] = None, @@ -142,6 +142,7 @@ def __init__( stim_font(List[str]): Ordered list of colors to apply to information stimuli stim_pos(Tuple[float, float]): Position on window where the stimuli will be presented + or a list of positions (ex. for matrix displays) stim_height(float): Height of all stimuli stim_inquiry(List[str]): Ordered list of text to build stimuli with stim_colors(List[str]): Ordered list of colors to apply to stimuli diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index c12a351ae..8e52fcf3b 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -4,9 +4,11 @@ from psychopy import core, visual +import bcipy.display.components.layout as layout from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, StimuliProperties) from bcipy.display.components.task_bar import TaskBar +from bcipy.display.paradigm.matrix.layout import symbol_positions from bcipy.helpers.stimuli import resize_image from bcipy.helpers.symbols import alphabet from bcipy.helpers.triggers import _calibration_trigger @@ -39,6 +41,7 @@ def __init__( stimuli: StimuliProperties, task_bar: TaskBar, info: InformationProperties, + rows:int=5, columns:int=6, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, should_prompt_target: bool = True): @@ -73,16 +76,19 @@ def __init__( self.stimuli_timing = [] self.stimuli_colors = [] self.stimuli_font = stimuli.stim_font + # self.symbol_positions = stimuli.stim_pos assert stimuli.is_txt_stim, "Matrix display is a text only display" self.symbol_set = symbol_set or alphabet() # Set position and parameters for grid of alphabet - self.position = stimuli.stim_pos self.grid_stimuli_height = stimuli.stim_height - self.position_increment = self.grid_stimuli_height + .05 - self.max_grid_width = 0.7 + + display_container = layout.below(task_bar.layout, + width_pct=0.7, + alignment=layout.Alignment.CENTERED) + self.positions = symbol_positions(display_container, rows, columns) self.grid_color = 'white' self.start_opacity = 0.15 @@ -164,33 +170,15 @@ def build_grid(self) -> Dict[str, visual.TextStim]: Builds a 7x4 matrix of stimuli. """ grid = {} - positions = self.symbol_positions() for i, sym in enumerate(self.symbol_set): grid[sym] = visual.TextStim(win=self.window, text=sym, color=self.grid_color, opacity=self.start_opacity, - pos=positions[i], + pos=self.positions[i], height=self.grid_stimuli_height) return grid - def symbol_positions(self) -> List[Tuple[float, float]]: - """Compute the symbol positions""" - positions = [] - pos = self.position - for _sym in self.symbol_set: - positions.append(pos) - pos = self.increment_position(pos) - return positions - - def increment_position(self, pos: Tuple[float, float]) -> Tuple[float, float]: - """Computes the position of the next symbol in the matrix.""" - x_coordinate, y_coordinate = pos - x_coordinate += self.position_increment - if x_coordinate >= self.max_grid_width: - y_coordinate -= self.position_increment - x_coordinate = self.position[0] - return (x_coordinate, y_coordinate) def draw_grid(self, opacity: float = 1, diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index 682a2a66a..5a1ec40dd 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -4,14 +4,14 @@ from bcipy.display.components.layout import Layout -def symbol_positions(layout: Layout, rows: int, +def symbol_positions(container: Layout, rows: int, columns: int) -> List[Tuple[float, float]]: """Compute the positions for arranging a number of symbols in a grid layout. Parameters ---------- - layout - layout in which the grid should be placed + container - container in which the grid should be placed rows - number of rows in the grid columns - number of columns in the grid @@ -21,37 +21,38 @@ def symbol_positions(layout: Layout, rows: int, """ assert rows >= 1 and columns >= 1, "There must be at least one row and one column" - # compute the spacing (in layout units) from the layout width and height - horizontal_spacing = layout.width / (rows + 1) - vertical_spacing = layout.height / (columns + 1) + # compute the spacing (in container units) from the container width and height + horizontal_spacing = container.width / (rows + 1) + vertical_spacing = container.height / (columns + 1) spacing = min(horizontal_spacing, vertical_spacing) half_space = spacing / 2 # Work back from center to compute the starting position - center_x, center_y = layout.center + center_x, center_y = container.center spaces_left_of_center = int(columns / 2) - start_pos_left = layout.left_of(center_x, spaces_left_of_center * spacing) + start_pos_left = container.left_of(center_x, + spaces_left_of_center * spacing) if columns % 2 == 0 and columns > 1: # even number of columns; adjust start_pos so that center_x is between # the middle two items. - start_pos_left = layout.right_of(start_pos_left, half_space) + start_pos_left = container.right_of(start_pos_left, half_space) spaces_above_center = int(rows / 2) - start_pos_top = layout.above(center_y, spaces_above_center * spacing) + start_pos_top = container.above(center_y, spaces_above_center * spacing) if rows % 2 == 0 and rows > 1: - start_pos_top = layout.below(start_pos_top, half_space) + start_pos_top = container.below(start_pos_top, half_space) # adjust the beginning x,y values so adding a space results in the first # position. - x_coord = layout.left_of(start_pos_left, spacing) - y_coord = layout.above(start_pos_top, spacing) + x_coord = container.left_of(start_pos_left, spacing) + y_coord = container.above(start_pos_top, spacing) positions = [] for _row in range(rows): - y_coord = layout.below(y_coord, spacing) - x_coord = layout.left_of(start_pos_left, spacing) + y_coord = container.below(y_coord, spacing) + x_coord = container.left_of(start_pos_left, spacing) for _col in range(columns): - x_coord = layout.right_of(x_coord, spacing) + x_coord = container.right_of(x_coord, spacing) positions.append((x_coord, y_coord)) return positions \ No newline at end of file diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py index abec06009..c4f634b98 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py @@ -5,7 +5,7 @@ from mockito import (any, mock, unstub, verify, verifyNoUnwantedInteractions, when) -from bcipy.display import (InformationProperties, StimuliProperties) +from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import TaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay, SymbolDuration @@ -152,21 +152,6 @@ def test_draw_grid(self): self.matrix.draw_grid() verify(self.text_stim_mock, times=len(self.matrix.symbol_set)).draw() - def test_increment_position_increments_x_when_max_grid_width_not_met(self): - self.matrix.position_increment = 0.2 - self.matrix.max_grid_width = 0.7 - self.matrix.position = (0, 0) - # response should be 0,0 incremented by 0.2 in the x direction because 0.7 was not reached - response = self.matrix.increment_position(self.matrix.position) - self.assertEqual(response, (self.matrix.position_increment, 0)) - - def test_increment_position_increments_y_when_max_grid_width_is_reached(self): - self.matrix.position_increment = 0.2 - self.matrix.max_grid_width = 0.2 - self.matrix.position = (0, 0) - # response should be 0,0 incremented by -0.2 in the y direction because 0.2 was reached - response = self.matrix.increment_position(self.matrix.position) - self.assertEqual(response, (0, -self.matrix.position_increment)) def test_animate_scp(self): # mock the text stims and window From 95080ce81368d59486b5e92968831434b82536c3 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 21 Aug 2023 18:07:39 -0700 Subject: [PATCH 058/330] Added functionality to the layout module to simplify the downstream API. Refactored code to align with these changes --- bcipy/display/components/layout.py | 182 ++++++++++-------- bcipy/display/components/task_bar.py | 10 +- bcipy/display/paradigm/matrix/display.py | 14 +- bcipy/display/paradigm/matrix/layout.py | 2 +- bcipy/display/tests/components/test_layout.py | 79 +++++++- .../paradigm/matrix/test_matrix_display.py | 4 - .../paradigm/matrix/test_matrix_layout.py | 6 +- 7 files changed, 192 insertions(+), 105 deletions(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index ee33de35a..37750ee19 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -2,51 +2,49 @@ from enum import Enum from typing import Protocol, Tuple -from psychopy import visual - class Container(Protocol): """Protocol for an enclosing container with units and size.""" - win: visual.Window size: Tuple[float, float] units: str -class WindowContainer(Container): - """Wrapper for a Window. This is not needed in Python 3.8+ if Container is - a subclass of typing.Protocol.""" - - def __init__(self, win: visual.Window): - self.win = win - - @property - def size(self): - """Window size""" - return self.win.size - - @property - def units(self): - """Window units""" - return self.win.units - - DEFAULT_LEFT = -1.0 DEFAULT_TOP = 1.0 DEFAULT_RIGHT = 1.0 DEFAULT_BOTTOM = -1.0 +class Alignment(Enum): + """Specifies how elements should be aligned spatially""" + CENTERED = 1 + LEFT = 2 + RIGHT = 3 + TOP = 4 + BOTTOM = 5 + + @classmethod + def horizontal(cls): + """Subset used for horizontal alignment""" + return [Alignment.CENTERED, Alignment.LEFT, Alignment.RIGHT] + + @classmethod + def vertical(cls): + """Subset used for vertical alignment""" + return [Alignment.CENTERED, Alignment.TOP, Alignment.BOTTOM] + + class Layout(Container): """Class with methods for positioning elements within a parent container. """ def __init__(self, - parent: Container, + parent: Container = None, left: float = DEFAULT_LEFT, top: float = DEFAULT_TOP, right: float = DEFAULT_RIGHT, bottom: float = DEFAULT_BOTTOM): - + self.units = "norm" self.parent = parent self.top = top self.left = left @@ -58,7 +56,7 @@ def check_invariants(self): """Check that all invariants hold true.""" # TODO: units could be configurable; min and max depends on units. # https://psychopy.org/general/units.html#units - assert self.parent.units == "norm", "Position calculations assume norm units." + assert self.units == "norm", "Position calculations assume norm units." assert (0.0 <= self.height <= 2.0), "Height must be in norm units." assert (0.0 <= self.width <= 2.0), "Width must be in norm units." @@ -70,20 +68,11 @@ def check_invariants(self): assert (-1.0 <= self.right <= 1.0), "Right must be an x-value in norm units" - assert 0 < self.width <= self.parent.size[ - 0], "Width must be greater than 0 and fit within the parent width." - assert 0 < self.height <= self.parent.size[ - 1], "Height must be greater than 0 and fit within the parent height." - - @property - def win(self) -> visual.Window: - """Returns the Window on which the layout will be drawn.""" - return self.parent.win - - @property - def units(self) -> str: - """Units for drawing; affects calculations related to position, size and radius.""" - return self.parent.units + if self.parent: + assert 0 < self.width <= self.parent.size[ + 0], "Width must be greater than 0 and fit within the parent width." + assert 0 < self.height <= self.parent.size[ + 1], "Height must be greater than 0 and fit within the parent height." @property def size(self) -> Tuple[float, float]: @@ -153,11 +142,68 @@ def left_of(self, x_coordinate: float, amount: float) -> float: assert amount >= 0, 'Amount must be positive' return x_coordinate - amount + def resize_width(self, + width_pct: float, + alignment: Alignment = Alignment.CENTERED) -> float: + """Adjust the width of the current layout. -class Alignment(Enum): - CENTERED = 1 - LEFT = 2 - RIGHT = 3 + Parameters + ---------- + width_pct - percentage of the current width + alignment - specifies how the remaining width should be aligned. + """ + assert 0 < width_pct, 'width_pct must be greater than 0' + assert alignment in Alignment.horizontal() + new_width = self.width * width_pct + + left = self.left + right = self.right + + margin = self.width - new_width + if alignment == Alignment.CENTERED: + half_margin = margin / 2 + left = left + half_margin + right = right - half_margin + elif alignment == Alignment.LEFT: + right = right - margin + elif alignment == Alignment.RIGHT: + left = left + margin + + self.left = left + self.right = right + self.check_invariants() + + def resize_height(self, + height_pct: float, + alignment: Alignment = Alignment.CENTERED) -> float: + """Adjust the height of the current layout. + + Parameters + ---------- + height_pct - percentage of the current width + alignment - specifies how the remaining width should be aligned. + """ + assert 0 < height_pct, 'height_pct must be greater than 0' + assert alignment in Alignment.vertical() + + new_height = self.height * height_pct + + top = self.top + bottom = self.bottom + + margin = self.height - new_height + if alignment == Alignment.CENTERED: + half_margin = margin / 2 + top = top - half_margin + bottom = bottom + half_margin + elif alignment == Alignment.TOP: + bottom = bottom + margin + elif alignment == Alignment.BOTTOM: + top = top - margin + + self.top = top + self.bottom = bottom + self.check_invariants() def at_top(parent: Container, height: float) -> Layout: @@ -175,6 +221,7 @@ def at_top(parent: Container, height: float) -> Layout: right=DEFAULT_RIGHT, bottom=top - height) + def at_bottom(parent: Container, height: float) -> Layout: """Constructs a layout of a given height that spans the full width of the window and is positioned at the bottom""" @@ -186,46 +233,19 @@ def at_bottom(parent: Container, height: float) -> Layout: bottom=bottom) -def horizontally_aligned(parent: Layout, - alignment: Alignment, - width: float = None) -> Tuple[float, float]: - """Returns a tuple of (left, right), indicating the values to be used""" - - left = parent.left - right = parent.right - if width: - margin = parent.width - width - if alignment == Alignment.CENTERED: - half_margin = margin / 2 - left = left + half_margin - right = right - half_margin - elif alignment == Alignment.LEFT: - right = right - margin - elif alignment == Alignment.RIGHT: - left = left + margin - return left, right - - -def below(layout: Layout, - width_pct: float = 1.0, - alignment: Alignment = Alignment.CENTERED): - """Constructs a layout immediately below another layout. +def centered(width_pct: float = 1.0, height_pct: float = 1.0) -> Layout: + """Constructs a layout that is centered on the screen. Default size is + fullscreen but optional parameters can be used to adjust the width and + height. Parameters ---------- - layout - another layout relative to the one constructed. Other - properties will be copied from this one. - width_pct - percentage of the available width. + width_pct - optional; sets the width to a given percentage of + fullscreen. + height_pct - optional; sets the height to a given percentage of + fullscreen. """ - width = layout.width * width_pct - - left, right = horizontally_aligned(layout, alignment, width) - top = layout.bottom - # bottom = top - height if height else DEFAULT_BOTTOM - bottom = DEFAULT_BOTTOM - - return Layout(parent=layout.parent, - left=left, - top=top, - right=right, - bottom=bottom) \ No newline at end of file + container = Layout() + container.resize_width(width_pct, alignment=Alignment.CENTERED) + container.resize_height(height_pct, alignment=Alignment.CENTERED) + return container diff --git a/bcipy/display/components/task_bar.py b/bcipy/display/components/task_bar.py index 826d229c2..fb2f5f0fd 100644 --- a/bcipy/display/components/task_bar.py +++ b/bcipy/display/components/task_bar.py @@ -1,9 +1,11 @@ """Task bar component""" from typing import Dict, List + from psychopy import visual from psychopy.visual.basevisual import BaseVisualStim from psychopy.visual.line import Line + import bcipy.display.components.layout as layout @@ -26,12 +28,12 @@ def __init__(self, font: str = 'Courier New', height: float = 0.1, text: str = ''): + self.win = win self.colors = colors or ['white'] self.font = font self.height = height self.text = text - self.layout = layout.at_top(layout.WindowContainer(win), - self.compute_height()) + self.layout = layout.at_top(win, self.compute_height()) self.stim = self.init_stim() def compute_height(self): @@ -55,7 +57,7 @@ def update(self, text: str = ''): def border_stim(self) -> Line: """Create the task bar outline""" - return visual.line.Line(win=self.layout.win, + return visual.line.Line(win=self.win, units=self.layout.units, start=(self.layout.left, self.layout.bottom), end=(self.layout.right, self.layout.bottom), @@ -72,7 +74,7 @@ def text_stim(self, **kwargs) -> visual.TextStim: def default_text_props(self) -> dict: """Default properties for constructing a TextStim.""" return { - 'win': self.layout.win, + 'win': self.win, 'text': self.text, 'pos': self.layout.center, 'units': self.layout.units, diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 8e52fcf3b..4fe4adb5c 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -1,6 +1,6 @@ """Display for presenting stimuli in a grid.""" import logging -from typing import Dict, List, NamedTuple, Optional, Tuple +from typing import Dict, List, NamedTuple, Optional from psychopy import core, visual @@ -41,7 +41,7 @@ def __init__( stimuli: StimuliProperties, task_bar: TaskBar, info: InformationProperties, - rows:int=5, columns:int=6, + rows: int = 5, columns: int = 6, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, should_prompt_target: bool = True): @@ -85,9 +85,7 @@ def __init__( # Set position and parameters for grid of alphabet self.grid_stimuli_height = stimuli.stim_height - display_container = layout.below(task_bar.layout, - width_pct=0.7, - alignment=layout.Alignment.CENTERED) + display_container = layout.centered(width_pct=0.7) self.positions = symbol_positions(display_container, rows, columns) self.grid_color = 'white' @@ -165,10 +163,7 @@ def do_inquiry(self) -> List[float]: return self._timing def build_grid(self) -> Dict[str, visual.TextStim]: - """Build grid. - - Builds a 7x4 matrix of stimuli. - """ + """Build the text stimuli to populate the grid.""" grid = {} for i, sym in enumerate(self.symbol_set): grid[sym] = visual.TextStim(win=self.window, @@ -179,7 +174,6 @@ def build_grid(self) -> Dict[str, visual.TextStim]: height=self.grid_stimuli_height) return grid - def draw_grid(self, opacity: float = 1, color: Optional[str] = 'white', diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index 5a1ec40dd..bccc7b208 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -55,4 +55,4 @@ def symbol_positions(container: Layout, rows: int, x_coord = container.right_of(x_coord, spacing) positions.append((x_coord, y_coord)) - return positions \ No newline at end of file + return positions diff --git a/bcipy/display/tests/components/test_layout.py b/bcipy/display/tests/components/test_layout.py index 84f786ab5..ba99860e4 100644 --- a/bcipy/display/tests/components/test_layout.py +++ b/bcipy/display/tests/components/test_layout.py @@ -3,7 +3,8 @@ from mockito import mock -from bcipy.display.components.layout import Layout, WindowContainer, at_top +from bcipy.display.components.layout import (Alignment, Layout, at_bottom, + at_top, centered) class TestLayout(unittest.TestCase): @@ -12,7 +13,7 @@ class TestLayout(unittest.TestCase): def setUp(self): """Set up needed items for test.""" self.window = mock({"size": (500, 500), "units": "norm"}) - self.container = WindowContainer(win=self.window) + self.container = self.window def test_container(self): """Test container protocol""" @@ -50,6 +51,15 @@ def test_full_size(self): bottom=-1.0) self.assertEqual((0.0, 0.0), layout.center) + def test_default_layout(self): + """Test that default layout is fullscreen""" + layout = Layout() + self.assertEqual(1.0, layout.top) + self.assertEqual(1.0, layout.right) + self.assertEqual(-1.0, layout.bottom) + self.assertEqual(-1.0, layout.left) + self.assertEqual((0.0, 0.0), layout.center) + def test_invariants(self): """Test invariant checks""" with self.assertRaises(AssertionError, msg="Left prop out of range"): @@ -80,6 +90,71 @@ def test_invariants(self): right=1.0, bottom=-1.1) + def test_position_at_bottom(self): + """Test at_bottom constructor""" + layout = at_bottom(self.container, height=0.1) + self.assertEqual(-1.0, layout.left) + self.assertEqual(1.0, layout.right) + self.assertEqual(-0.9, layout.top) + self.assertEqual(-1.0, layout.bottom) + + def test_centered(self): + """Test constructor for centered layout""" + layout = centered(width_pct=0.7, height_pct=0.8) + self.assertEqual(-0.7, layout.left) + self.assertEqual(0.7, layout.right) + self.assertEqual(0.8, layout.top) + self.assertEqual(-0.8, layout.bottom) + + def test_resize_width_center_aligned(self): + """Test width resize with center alignment""" + layout = Layout() + layout.resize_width(0.5, alignment=Alignment.CENTERED) + self.assertEqual(-0.5, layout.left) + self.assertEqual(0.5, layout.right) + + def test_resize_width_left_aligned(self): + """Test width resize with left alignment""" + layout = Layout() + layout.resize_width(0.5, alignment=Alignment.LEFT) + self.assertEqual(-1.0, layout.left) + self.assertEqual(0.0, layout.right) + + def test_resize_width_right_aligned(self): + """Test width resize with right alignment""" + layout = Layout() + layout.resize_width(0.5, alignment=Alignment.RIGHT) + self.assertEqual(0.0, layout.left) + self.assertEqual(1.0, layout.right) + + def test_resize_width_larger(self): + """Test increase in width""" + layout = Layout(left=-0.5, right=0.5) + layout.resize_width(2.0, alignment=Alignment.CENTERED) + self.assertEqual(-1.0, layout.left) + self.assertEqual(1.0, layout.right) + + def test_resize_height_center_aligned(self): + """Test height resize with center alignment""" + layout = Layout() + layout.resize_height(0.5, alignment=Alignment.CENTERED) + self.assertEqual(-0.5, layout.bottom) + self.assertEqual(0.5, layout.top) + + def test_resize_height_top_aligned(self): + """Test height resize with top alignment""" + layout = Layout() + layout.resize_height(0.5, alignment=Alignment.TOP) + self.assertEqual(1.0, layout.top) + self.assertEqual(0.0, layout.bottom) + + def test_resize_height_bottom_aligned(self): + """Test height resize with bottom alignment""" + layout = Layout() + layout.resize_height(0.5, alignment=Alignment.BOTTOM) + self.assertEqual(0.0, layout.top) + self.assertEqual(-1.0, layout.bottom) + if __name__ == '__main__': unittest.main() diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py index c4f634b98..5f6afebad 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py @@ -138,21 +138,17 @@ def test_build_grid(self): pos=any(), opacity=any() ).thenReturn(self.text_stim_mock) - when(self.matrix).increment_position(any()).thenReturn() sym_length = len(self.matrix.symbol_set) grid = self.matrix.build_grid() self.assertEqual(len(grid), sym_length) - # verify that the position was incremented each time - verify(self.matrix, times=sym_length).increment_position(any()) def test_draw_grid(self): """Test that all items in the grid draw.""" self.matrix.draw_grid() verify(self.text_stim_mock, times=len(self.matrix.symbol_set)).draw() - def test_animate_scp(self): # mock the text stims and window when(psychopy.visual).TextStim( diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py index d6d115b4e..eba82345d 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py @@ -3,7 +3,7 @@ from mockito import mock -from bcipy.display.components.layout import Layout, WindowContainer +from bcipy.display.components.layout import Layout from bcipy.display.paradigm.matrix.layout import symbol_positions @@ -13,7 +13,7 @@ class TestMatrixLayout(unittest.TestCase): def setUp(self): """Set up needed items for test.""" self.window = mock({"size": (500, 500), "units": "norm"}) - self.container = WindowContainer(win=self.window) + self.container = self.window self.layout = Layout(parent=self.container, left=-1.0, top=1.0, @@ -80,4 +80,4 @@ def test_single_column(self): if __name__ == '__main__': - unittest.main() \ No newline at end of file + unittest.main() From 393bff47125f2c0d156ec08af15794a6e042b56e Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Wed, 23 Aug 2023 14:01:06 -0400 Subject: [PATCH 059/330] Gaze Reshaper Complete --- bcipy/helpers/stimuli.py | 72 +++++++++++---------- bcipy/helpers/visualization.py | 90 ++++++++++++++++++++++++++ bcipy/signal/model/offline_analysis.py | 29 +++++++-- 3 files changed, 150 insertions(+), 41 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index d4d509bf5..e90b48d04 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -11,6 +11,7 @@ from bcipy.helpers.exceptions import BciPyCoreException from bcipy.helpers.list import grouper +from bcipy.helpers.symbols import alphabet from PIL import Image # Prevents pillow from filling the console with debug info @@ -127,7 +128,7 @@ def __call__(self, Returns: reshaped_data (np.ndarray): inquiry data of shape (Channels, Inquiries, Samples) labels (np.ndarray): integer label for each inquiry. With `trials_per_inquiry=K`, - a label of [0, K-1] indicates the position of `target_label`, or label of K indicates + a label of [0, K-1] indicates the position of `target_label`, or label of [0 ... 0] indicates `target_label` was not present. reshaped_trigger_timing (List[List[int]]): For each inquiry, a list of the sample index where each trial begins, accounting for the prestim buffer that may have been added to the front of each inquiry. @@ -176,7 +177,6 @@ def get_inquiry_len(inq_trigs): stop = first_trigger + num_samples_per_inq + buffer_samples reshaped_data.append(eeg_data[:, start:stop]) - breakpoint() return np.stack(reshaped_data, 1), labels, reshaped_trigger_timing @@ -241,8 +241,7 @@ def __call__(self, poststimulus_length: float = 0.5, prestimulus_length: float = 0.0, transformation_buffer: float = 0.0, - target_label: str = 'target' - ) -> Tuple[np.ndarray, np.ndarray]: + ) -> dict: """Extract inquiry data and labels. Args: @@ -257,52 +256,55 @@ def __call__(self, poststimulus_length (float, optional): time in seconds needed after the last trial in an inquiry. prestimulus_length (float, optional): time in seconds needed before the first trial in an inquiry. transformation_buffer (float, optional): time in seconds to buffer the end of the inquiry. Defaults to 0.0. - target_label (str): label of target symbol. Defaults to "target" Returns: - reshaped_data (np.ndarray): inquiry data of shape (Channels, Inquiries, Samples) - labels (np.ndarray): integer label for each inquiry. With `trials_per_inquiry=K`, - a label of [0, K-1] indicates the position of `target_label`, or label of K indicates - `target_label` was not present. - reshaped_trigger_timing (List[List[int]]): For each inquiry, a list of the sample index where each trial - begins, accounting for the prestim buffer that may have been added to the front of each inquiry. + reshaped_data (np.ndarray): inquiry data of shape (Inquiries, Channels, Samples) + labels (List[str]): Target letter in each inquiry. + + data_by_targets (dict): Dictionary where keys are the symbol set and values are the appended inquiries + for each symbol. dict[Key] = list of shape (Channels, Samples) """ if channel_map: # Remove the channels that we are not interested in channels_to_remove = [idx for idx, value in enumerate(channel_map) if value == 0] gaze_data = np.delete(gaze_data, channels_to_remove, axis=0) - - n_inquiry = len(inq_start_times) - prestimulus_samples = int(prestimulus_length * sample_rate) - - - # triggers in seconds are mapped to triggers in number of samples. - triggers = list(map(lambda x: int(x * sample_rate), inq_start_times)) - # TODO: This ends up adding ~300ms shift to the triggers. Why? + + # Find the value closest to (& greater than) inq_start_times + gaze_data_timing = gaze_data[-1,:].tolist() + + start_times = [] + for times in inq_start_times: + start_times.append(list(filter(lambda x: x > times, gaze_data_timing))[0]) + + triggers = [] + for val in start_times: + triggers.append(gaze_data_timing.index(val)) # Label for every inquiry labels = target_symbols - reshaped_data, reshaped_trigger_timing = [], [] - for inquiry_idx, trials_within_inquiry in enumerate( - grouper(zip(trial_targetness_label, triggers), trials_per_inquiry, fillvalue='x') - ): - first_trigger = trials_within_inquiry[0][1] + symbol_set = alphabet() - trial_triggers = [] - for trial_idx, (trial_label, trigger) in enumerate(trials_within_inquiry): - # If presimulus buffer is used, we add it here so that trigger timings will - # still line up with trial onset - breakpoint() - trial_triggers.append((trigger - first_trigger) + prestimulus_samples) - reshaped_trigger_timing.append(trial_triggers) - start = first_trigger - stop = first_trigger + (sample_rate * 3) # (60 samples * 3 seconds) + # Create a dictionary with symbols as keys and data as values + # 'A': [], 'B': [] ... + data_by_targets = {} + for symbol in symbol_set: + data_by_targets[symbol] = [] + + reshaped_data = [] + # Merge the inquiries if they have the same target letter: + for i, inquiry_index in enumerate(triggers): + start = inquiry_index + stop = int(inquiry_index + (sample_rate * 3)) # (60 samples * 3 seconds) reshaped_data.append(gaze_data[:, start:stop]) - breakpoint() + # Create a dictionary: + for symbol in symbol_set: + if symbol == labels[i]: + data_by_targets[symbol].append(gaze_data[:, start:stop]) - return np.stack(reshaped_data, 1), labels, reshaped_trigger_timing + # return np.stack(reshaped_data, 0), labels + return data_by_targets @staticmethod def extract_trials(inquiries, samples_per_trial, inquiry_timing, downsample_rate=1): diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 29918c4c3..6927ab0d6 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -170,6 +170,96 @@ def visualize_gaze( return fig +def visualize_gaze_inquiries( + data, + save_path=None, + show=False, + img_path=None, + screen_size=(1920, 1080), + heatmap=False, + raw_plot=False): + """Visualize Eye Data. + + Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default + image used is for the matrix calibration task on a 1920x1080 screen. + + Parameters + ---------- + data: RawData + save_path: Optional[str] + show: Optional[bool] + img_path: Optional[str] + screen_size: Optional[Tuple[int, int]] TODO + """ + + title = 'Raw Gaze Inquiries ' + + if img_path is None: + img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img = plt.imread(img_path) + + data = np.transpose(np.array(data), (1,0,2)) + + inq_data = np.reshape(data, (9,-1)) + + left_eye_x = inq_data[2,:] + left_eye_y = inq_data[3,:] + left_pupil = inq_data[4,:] + + right_eye_x = inq_data[5,:] + right_eye_y = inq_data[6,:] + right_pupil = inq_data[7,:] + + # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis + lx = np.clip(left_eye_x, 0, 1) + ly = np.clip(left_eye_y, 0, 1) + rx = np.clip(right_eye_x, 0, 1) + ry = np.clip(right_eye_y, 0, 1) + ly = 1 - ly + ry = 1 - ry + + # remove nan values + lx = lx[~np.isnan(lx)] + ly = ly[~np.isnan(ly)] + rx = rx[~np.isnan(rx)] + ry = ry[~np.isnan(ry)] + + # scale the eye data to the image + fig, ax = plt.subplots() + ax.imshow(img, extent=[0, 1, 0, 1]) + + if heatmap: + # create a dataframe making a column for each x, y pair for both eyes and a column for the eye (left or right) + df = pd.DataFrame({ + 'x': np.concatenate((lx, rx)), + 'y': np.concatenate((ly, ry)), + 'eye': ['left'] * len(lx) + ['right'] * len(rx) + }) + ax = sns.kdeplot( + data=df, + hue='eye', + x='x', + y='y', + fill=False, + thresh=0.05, + levels=10, + cmap="mako", + colorbar=True) + + if raw_plot: + ax.scatter(lx, ly, c='r', s=1) + ax.scatter(rx, ry, c='b', s=1) + + plt.title(f'{title}Plot') + + if save_path is not None: + plt.savefig(f"{save_path}/{title.lower().replace(' ', '_')}plot.png", dpi=fig.dpi) + + if show: + plt.show() + + return fig + def plot_edf(edf_path: str, auto_scale: Optional[bool] = False): """Plot data from the raw edf file. Note: this works from an iPython diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 01500d260..9be389948 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -16,8 +16,9 @@ ) from bcipy.helpers.stimuli import play_sound, update_inquiry_timing from bcipy.helpers.system_utils import report_execution_time +from bcipy.helpers.symbols import alphabet from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.helpers.visualization import visualize_erp, visualize_gaze +from bcipy.helpers.visualization import visualize_erp, visualize_gaze, visualize_gaze_inquiries from bcipy.signal.model.base_model import SignalModel from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.model.fusion_model import GazeModel @@ -263,9 +264,14 @@ def offline_analysis( model = GazeModel() + # Add back the system offset: + system_offset = 926453.0228878 + # TODO: This is handled in TriggerHandler. Remove automatic addition off system offset! + # Process triggers.txt files (again!) trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( remove_pre_fixation = False, + offset = system_offset, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", #exclusion=[TriggerType.PREVIEW, TriggerType.EVENT] exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.SYSTEM, TriggerType.OFFSET] @@ -277,24 +283,35 @@ def offline_analysis( # trigger_targetness keeps the PROMPT info, use it to find the target symbol! target_symbols = trigger_symbols[0::11] # target symbols inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) - breakpoint() - # Need to calculate the starting index, using inq_start. - inquiries, inquiry_labels, inquiry_timing = model.reshaper( + # Find the inquiries starting by the inq_start_times, (9, 100, 180): + inquiries = model.reshaper( trial_targetness_label=trigger_targetness, inq_start_times=inq_start, target_symbols = target_symbols, gaze_data=data, sample_rate=sample_rate, trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, poststimulus_length=poststim_length, prestimulus_length=prestim_length, transformation_buffer=buffer ) - # Merge subset of time windows if they have the same target symbol: + # Plot samples for each target symbol: + symbol_set = alphabet() + for i in symbol_set: + figure_handles = visualize_gaze_inquiries( + inquiries[i], + save_path=None, + show=show_figures, + raw_plot=True, + ) + # plt.show() + + + breakpoint() + if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") From 620a544d003423ec672f4856d1c73a92b67df2cc Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 23 Aug 2023 17:32:57 -0700 Subject: [PATCH 060/330] Added parameters for specifying matrix rows, columns, and width. Integrated new parameters in tasks --- bcipy/display/paradigm/matrix/display.py | 28 +++++++++---------- bcipy/display/paradigm/matrix/layout.py | 17 +++++++---- .../paradigm/matrix/test_matrix_layout.py | 25 +++++++++++++++++ bcipy/parameters/parameters.json | 26 ++++++++++++++++- bcipy/task/paradigm/matrix/calibration.py | 3 ++ bcipy/task/paradigm/matrix/copy_phrase.py | 3 ++ 6 files changed, 81 insertions(+), 21 deletions(-) diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 4fe4adb5c..8ca2825a6 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -34,17 +34,18 @@ class MatrixDisplay(Display): stim_height: 0.1 """ - def __init__( - self, - window: visual.Window, - experiment_clock: core.Clock, - stimuli: StimuliProperties, - task_bar: TaskBar, - info: InformationProperties, - rows: int = 5, columns: int = 6, - trigger_type: str = 'text', - symbol_set: Optional[List[str]] = None, - should_prompt_target: bool = True): + def __init__(self, + window: visual.Window, + experiment_clock: core.Clock, + stimuli: StimuliProperties, + task_bar: TaskBar, + info: InformationProperties, + rows: int = 5, + columns: int = 6, + width_pct: float = 0.7, + trigger_type: str = 'text', + symbol_set: Optional[List[str]] = None, + should_prompt_target: bool = True): """Initialize Matrix display parameters and objects. PARAMETERS: @@ -76,16 +77,15 @@ def __init__( self.stimuli_timing = [] self.stimuli_colors = [] self.stimuli_font = stimuli.stim_font - # self.symbol_positions = stimuli.stim_pos assert stimuli.is_txt_stim, "Matrix display is a text only display" self.symbol_set = symbol_set or alphabet() # Set position and parameters for grid of alphabet - self.grid_stimuli_height = stimuli.stim_height + self.grid_stimuli_height = 0.17 # stimuli.stim_height - display_container = layout.centered(width_pct=0.7) + display_container = layout.centered(width_pct=width_pct) self.positions = symbol_positions(display_container, rows, columns) self.grid_color = 'white' diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index bccc7b208..8a0c00b2c 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -4,8 +4,10 @@ from bcipy.display.components.layout import Layout -def symbol_positions(container: Layout, rows: int, - columns: int) -> List[Tuple[float, float]]: +def symbol_positions(container: Layout, + rows: int, + columns: int, + spacing: float = None) -> List[Tuple[float, float]]: """Compute the positions for arranging a number of symbols in a grid layout. @@ -14,6 +16,8 @@ def symbol_positions(container: Layout, rows: int, container - container in which the grid should be placed rows - number of rows in the grid columns - number of columns in the grid + spacing - optional value to specify the space between positions + (in the same units of the container) Returns ------- @@ -21,10 +25,11 @@ def symbol_positions(container: Layout, rows: int, """ assert rows >= 1 and columns >= 1, "There must be at least one row and one column" - # compute the spacing (in container units) from the container width and height - horizontal_spacing = container.width / (rows + 1) - vertical_spacing = container.height / (columns + 1) - spacing = min(horizontal_spacing, vertical_spacing) + if not spacing: + # compute the spacing (in container units) from the container width and height + horizontal_spacing = container.width / (rows + 1) + vertical_spacing = container.height / (columns + 1) + spacing = min(horizontal_spacing, vertical_spacing) half_space = spacing / 2 # Work back from center to compute the starting position diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py index eba82345d..fbb76f42a 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py @@ -78,6 +78,31 @@ def test_single_column(self): abs(self.layout.bottom - positions[-1][1]), msg="should have the same top and bottom gap") + def test_spacing(self): + """Test grid spacing""" + positions = symbol_positions(self.layout, rows=2, columns=2) + self.assertEqual(len(positions), 4) + + top_left = positions[0] + top_right = positions[1] + bottom_left = positions[2] + bottom_right = positions[3] + self.assertEqual(top_left[0], bottom_left[0], + "values in left column should have the same x-coord") + self.assertEqual( + top_right[0], bottom_right[0], + "values in right column should have the same x-coord") + self.assertEqual(top_left[1], top_right[1], + "Top row values should have the same y-coord") + self.assertEqual(bottom_left[1], bottom_right[1], + "Bottom row values should have the same y-coord") + + row_spacing = abs(top_left[1] - bottom_left[1]) + column_spacing = abs(top_right[0] - top_left[0]) + + self.assertEqual(row_spacing, column_spacing, + "Rows and columns should have the same spacing") + if __name__ == '__main__': unittest.main() diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 516ee3c51..6afe44894 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -224,6 +224,30 @@ "recommended_values": "", "type": "int" }, + "matrix_rows": { + "value": "6", + "section": "bci_config", + "readableName": "Matrix Rows", + "helpTip": "Specifies the number of rows to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", + "recommended_values": "", + "type": "int" + }, + "matrix_columns": { + "value": "5", + "section": "bci_config", + "readableName": "Matrix Columns", + "helpTip": "Specifies the number of columns to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", + "recommended_values": "", + "type": "int" + }, + "matrix_width_pct": { + "value": "0.7", + "section": "bci_config", + "readableName": "Matrix Width (%)", + "helpTip": "Specifies the max percentage of the display that the matrix grid should utilize. Must be between 0 and 1", + "recommended_values": "", + "type": "float" + }, "acq_show_viewer": { "value": "false", "section": "acq_config", @@ -618,7 +642,7 @@ "type": "int" }, "lang_model_type": { - "value": "MIXTURE", + "value": "UNIFORM", "section": "lang_model_config", "readableName": "Language Model Type", "helpTip": "Specifies which language model to use. Default: MIXTURE", diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index ecc21d986..a556cfa73 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -271,5 +271,8 @@ def init_calibration_display_task( stimuli, task_bar, info, + rows=parameters['matrix_rows'], + columns=parameters['matrix_columns'], + width_pct=parameters['matrix_width_pct'], trigger_type=parameters['trigger_type'], symbol_set=symbol_set) diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index 53e9e9ecc..d397328f8 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -80,5 +80,8 @@ def init_display(parameters, win, experiment_clock, starting_spelled_text): stimuli, task_bar, info, + rows=parameters['matrix_rows'], + columns=parameters['matrix_columns'], + width_pct=parameters['matrix_width_pct'], trigger_type=parameters['trigger_type'], should_prompt_target=False) From cc1009b55380b7300c7602892e89a77b625323a4 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 24 Aug 2023 08:52:58 -0700 Subject: [PATCH 061/330] Added logging for matrix symbol positions --- bcipy/display/paradigm/matrix/display.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 8ca2825a6..85d4d74ee 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -87,6 +87,9 @@ def __init__(self, display_container = layout.centered(width_pct=width_pct) self.positions = symbol_positions(display_container, rows, columns) + self.logger.info( + f"Symbol positions ({display_container.units} units): {self.positions}" + ) self.grid_color = 'white' self.start_opacity = 0.15 From c2e42c573a09e9de772212fdce4105e8abb6c0ad Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 24 Aug 2023 09:00:04 -0700 Subject: [PATCH 062/330] Fixed parameters for rows and columns --- bcipy/parameters/parameters.json | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 6afe44894..d6ccba53f 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -225,7 +225,7 @@ "type": "int" }, "matrix_rows": { - "value": "6", + "value": "5", "section": "bci_config", "readableName": "Matrix Rows", "helpTip": "Specifies the number of rows to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", @@ -233,7 +233,7 @@ "type": "int" }, "matrix_columns": { - "value": "5", + "value": "6", "section": "bci_config", "readableName": "Matrix Columns", "helpTip": "Specifies the number of columns to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", From bb6224fa0ff9745193198dbafa1d72d9f3c0a6da Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 24 Aug 2023 13:10:33 -0400 Subject: [PATCH 063/330] Gaze Model v1 complete --- bcipy/helpers/stimuli.py | 49 ++++++++++++++-------- bcipy/helpers/visualization.py | 28 +++++-------- bcipy/signal/model/fusion_model.py | 57 ++++++++++++++++++++++++++ bcipy/signal/model/offline_analysis.py | 49 +++++++++++++++------- 4 files changed, 135 insertions(+), 48 deletions(-) create mode 100644 bcipy/signal/model/fusion_model.py diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index e90b48d04..34052ad0c 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -274,7 +274,9 @@ def __call__(self, start_times = [] for times in inq_start_times: - start_times.append(list(filter(lambda x: x > times, gaze_data_timing))[0]) + temp = list(filter(lambda x: x > times, gaze_data_timing)) + if len(temp) > 0: + start_times.append(temp[0]) triggers = [] for val in start_times: @@ -307,23 +309,38 @@ def __call__(self, return data_by_targets @staticmethod - def extract_trials(inquiries, samples_per_trial, inquiry_timing, downsample_rate=1): - """Extract Trials. - - After using the InquiryReshaper, it may be necessary to futher trial the data for processing. - Using the number of samples and inquiry timing, the data is reshaped from Channels, Inquiry, Samples to - Channels, Trials, Samples. These should match with the trials extracted from the TrialReshaper given the same - slicing parameters. + def extract_eye_info(data): + """ Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples + Extract Left and Right Eye info from data. + + Args: + data (List(float)): Data in shape of num_targetness x num_channels x num_samples + + Returns: + left_eye (np.ndarray), left_pupil (List(float)) + right_eye (np.ndarray), right_pupil (List(float)) """ - new_trials = [] - num_inquiries = inquiries.shape[1] - for inquiry_idx, timing in zip(range(num_inquiries), inquiry_timing): # C x I x S - for time in timing: - time = time // downsample_rate - y = time + samples_per_trial - new_trials.append(inquiries[:, inquiry_idx, time:y]) - return np.stack(new_trials, 1) # C x T x S + temp_data = np.transpose(np.array(data), (1,0,2)) + inq_data = np.reshape(temp_data, (len(temp_data), -1)) # num_channels x num_samples + + # Extract samples from channels + lx = inq_data[2,:] + ly = inq_data[3,:] + left_pupil = inq_data[4,:] + + rx = inq_data[5,:] + ry = inq_data[6,:] + right_pupil = inq_data[7,:] + + left_eye = np.vstack((np.array(lx), np.array(ly))).T + right_eye = np.vstack((np.array(rx), np.array(ry))).T + + # Remove blinks (i.e. Nan values) + left_eye = left_eye[~np.isnan(left_eye).any(axis=1)] + right_eye = right_eye[~np.isnan(right_eye).any(axis=1)] + + return left_eye, left_pupil, right_eye, right_pupil class TrialReshaper(Reshaper): def __call__(self, diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 6927ab0d6..37f60acc5 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -171,7 +171,8 @@ def visualize_gaze( return fig def visualize_gaze_inquiries( - data, + left_eye, + right_eye, save_path=None, show=False, img_path=None, @@ -185,7 +186,7 @@ def visualize_gaze_inquiries( Parameters ---------- - data: RawData + left eye, right eye: Raw gaze data (np.ndarray) save_path: Optional[str] show: Optional[bool] img_path: Optional[str] @@ -198,17 +199,10 @@ def visualize_gaze_inquiries( img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' img = plt.imread(img_path) - data = np.transpose(np.array(data), (1,0,2)) - - inq_data = np.reshape(data, (9,-1)) - - left_eye_x = inq_data[2,:] - left_eye_y = inq_data[3,:] - left_pupil = inq_data[4,:] - - right_eye_x = inq_data[5,:] - right_eye_y = inq_data[6,:] - right_pupil = inq_data[7,:] + left_eye_x = left_eye[:,0] + left_eye_y = left_eye[:,1] + right_eye_x = right_eye[:,0] + right_eye_y = right_eye[:,1] # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis lx = np.clip(left_eye_x, 0, 1) @@ -219,10 +213,10 @@ def visualize_gaze_inquiries( ry = 1 - ry # remove nan values - lx = lx[~np.isnan(lx)] - ly = ly[~np.isnan(ly)] - rx = rx[~np.isnan(rx)] - ry = ry[~np.isnan(ry)] + # lx = lx[~np.isnan(lx)] + # ly = ly[~np.isnan(ly)] + # rx = rx[~np.isnan(rx)] + # ry = ry[~np.isnan(ry)] # scale the eye data to the image fig, ax = plt.subplots() diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py new file mode 100644 index 000000000..b2a7eda4e --- /dev/null +++ b/bcipy/signal/model/fusion_model.py @@ -0,0 +1,57 @@ +import logging +from pathlib import Path +from typing import Tuple + +import numpy as np +import pandas as pd +from matplotlib import pyplot as plt +from sklearn.mixture import GaussianMixture +from bcipy.helpers.stimuli import GazeReshaper + +class GazeModel(): + reshaper = GazeReshaper() + + def __init__(self, num_components=3): + self.num_components = num_components # number of gaussians to fit + + def fit(self, train_data: np.array): + model = GaussianMixture(n_components=2, random_state=0, init_params='kmeans') + model.fit(train_data) + self.model = model + + return self + + def predict(self, test_data: np.array): + predictions = self.model.predict_proba(test_data) + means = self.model.means_ + + return predictions, means + + + +# if __name__ == "__main__": +# # Dummy model test +# letterdata = np.load('/Users/basak/Documents/BciPy/S001_A.npz') +# left_eye = np.vstack((letterdata['lx'], letterdata['ly'])).T +# right_eye = np.vstack((letterdata['rx'], letterdata['ry'])).T + +# # Train test split the data +# test_size_right = int(len(right_eye) * 0.2) +# train_size_right = len(right_eye) - test_size_right +# train_right_eye = right_eye[:train_size_right] +# test_right_eye = right_eye[train_size_right:] + +# test_size_left = int(len(left_eye) * 0.2) +# train_size_left = len(left_eye) - test_size_left +# train_left_eye = left_eye[:train_size_left] +# test_left_eye = left_eye[train_size_left:] + +# gm = GaussianMixture(n_components=2, random_state=0, init_params='kmeans').fit(train_right_eye) +# predictions = gm.predict_proba(test_right_eye) +# print(predictions) +# plt.scatter(left_eye[:, 0], left_eye[:, 1], c='r', s=1) +# plt.scatter(right_eye[:, 0], right_eye[:, 1], c='b', s=1) +# means = gm.means_ +# plt.scatter(means[:,0], means[:,1], c='black', s=20, marker='^') +# plt.show() +# breakpoint() diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 9be389948..880b88eb2 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -12,12 +12,11 @@ load_experimental_data, load_json_parameters, load_raw_data, - load_eye_tracking_data ) from bcipy.helpers.stimuli import play_sound, update_inquiry_timing from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.symbols import alphabet -from bcipy.helpers.triggers import TriggerType, trigger_decoder +from bcipy.helpers.triggers import TriggerType, trigger_decoder, TriggerHandler from bcipy.helpers.visualization import visualize_erp, visualize_gaze, visualize_gaze_inquiries from bcipy.signal.model.base_model import SignalModel from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel @@ -264,23 +263,24 @@ def offline_analysis( model = GazeModel() - # Add back the system offset: - system_offset = 926453.0228878 - # TODO: This is handled in TriggerHandler. Remove automatic addition off system offset! + # Add back the starting offset: + # This is handled in TriggerHandler. Remove automatic addition off system offset: + trigx, starting_offset = TriggerHandler.read_text_file(f"{data_folder}/{TRIGGER_FILENAME}") + # TODO: I access TriggerHandler directly to not cause an issue during EEG analysis. + # There's probably a smarter way to discard starting_offset # Process triggers.txt files (again!) trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( remove_pre_fixation = False, - offset = system_offset, + offset = starting_offset*-1, # cancel out the starting_offset trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - #exclusion=[TriggerType.PREVIEW, TriggerType.EVENT] exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.SYSTEM, TriggerType.OFFSET] ) ''' Trigger_timing includes PROMPT and excludes FIXATION ''' # Use trigger_timing to generate time windows for each letter flashing - # Take every 10th trigger as the start point of timing. x = list(range(1000)), x[0::10] does that! - # trigger_targetness keeps the PROMPT info, use it to find the target symbol! + # Take every 10th trigger as the start point of timing. + # trigger_targetness keeps the PROMPT info, use it to find the target symbol. target_symbols = trigger_symbols[0::11] # target symbols inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) @@ -297,19 +297,38 @@ def offline_analysis( transformation_buffer=buffer ) - # Plot samples for each target symbol: symbol_set = alphabet() + # Train the model for each target label and each eye separately. for i in symbol_set: + # Do more preprocesssing to extract eye info: + left_eye, left_pupil, right_eye, right_pupil = model.reshaper.extract_eye_info(inquiries[i]) + + # Train test split: + test_size = int(len(right_eye) * 0.2) + train_size = len(right_eye) - test_size + train_right_eye = right_eye[:train_size] + test_right_eye = right_eye[train_size:] + + train_left_eye = left_eye[:train_size] + test_left_eye = left_eye[train_size:] + + # Fit the model: + model.fit(train_right_eye) + + predictions, means = model.predict(test_right_eye) + # print(predictions) + + # Visualize the results: figure_handles = visualize_gaze_inquiries( - inquiries[i], + left_eye, + right_eye, save_path=None, show=show_figures, raw_plot=True, - ) - # plt.show() - + ) + plt.show() - breakpoint() + breakpoint() From 7606a86167b0043ac57058a11682569da9e3bd8f Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 24 Aug 2023 11:56:19 -0700 Subject: [PATCH 064/330] update tests and cleanup / documentation --- bcipy/helpers/parameters.py | 3 + bcipy/helpers/stimuli.py | 8 +-- .../resources/mock_session/parameters.json | 16 ++++-- bcipy/helpers/visualization.py | 54 +++++++++++------- bcipy/parameters/parameters.json | 10 +++- bcipy/signal/model/offline_analysis.py | 33 +++++++---- .../test_nontarget_topomap.png | Bin 121544 -> 120183 bytes .../test_target_topomap.png | Bin 119310 -> 115767 bytes bcipy/task/paradigm/matrix/copy_phrase.py | 7 --- bcipy/task/paradigm/rsvp/copy_phrase.py | 4 +- .../tests/paradigm/rsvp/test_copy_phrase.py | 6 +- 11 files changed, 82 insertions(+), 59 deletions(-) diff --git a/bcipy/helpers/parameters.py b/bcipy/helpers/parameters.py index 9a95ebacf..d89eacbba 100644 --- a/bcipy/helpers/parameters.py +++ b/bcipy/helpers/parameters.py @@ -103,6 +103,9 @@ def from_cast_values(cls, **kwargs): params = Parameters(source=None, cast_values=True) for key, val in kwargs.items(): value_type = type(val).__name__ + # Convert tuple to range + if value_type == 'tuple': + value_type = 'range' value_str = serialize_value(value_type, val) params.add_entry( key, { diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 27e19c45e..8552f7a3d 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -300,18 +300,16 @@ def mne_epochs(mne_data: RawArray, trigger_timing: List[float], trial_length: float, trigger_labels: List[int], - baseline: Tuple[float, float] = (None, 0.0), - epoch_buffer=0.1) -> Epochs: + baseline: Tuple[float, float] = (None, 0)) -> Epochs: """MNE Epochs. Using an MNE RawArray, reshape the data given trigger information. If two labels present [0, 1], each may be accessed by numbered order. Ex. first_class = epochs['1'], second_class = epochs['2'] """ - plot_length = trial_length + epoch_buffer - annotations = Annotations(trigger_timing, [plot_length] * len(trigger_timing), trigger_labels) + annotations = Annotations(trigger_timing, [trial_length] * len(trigger_timing), trigger_labels) mne_data.set_annotations(annotations) events_from_annot, _ = mne.events_from_annotations(mne_data) - return Epochs(mne_data, events_from_annot, tmax=plot_length, baseline=baseline) + return Epochs(mne_data, events_from_annot, tmax=trial_length, baseline=baseline) def alphabetize(stimuli: List[str]) -> List[str]: """Alphabetize. diff --git a/bcipy/helpers/tests/resources/mock_session/parameters.json b/bcipy/helpers/tests/resources/mock_session/parameters.json index e29e64391..ab56fd55b 100644 --- a/bcipy/helpers/tests/resources/mock_session/parameters.json +++ b/bcipy/helpers/tests/resources/mock_session/parameters.json @@ -74,13 +74,17 @@ "recommended_values": "[10]", "type": "int" }, - "trial_length": { - "value": "0.5", + "trial_window": { + "value": "0.0:0.5", "section": "bci_config", - "readableName": "Data Collection Window Length", - "helpTip": "Specifies the length (in seconds) of the EEG data collection window after each stimulus presentation. Default: 0.5", - "recommended_values": "", - "type": "float" + "readableName": "Trial Classification Window Length", + "helpTip": "Specifies the window (in seconds) of the EEG data collection window after each stimulus presentation. Default: 0.0:0.5", + "recommended_values": [ + "0.0:0.5", + "0.0:0.8", + "0.2:0.8" + ], + "type": "range" }, "prestim_length": { "value": "1", diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index f7032a2e4..b511eed39 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -13,7 +13,7 @@ from bcipy.helpers.load import choose_csv_file, load_raw_data from bcipy.helpers.stimuli import mne_epochs from bcipy.helpers.raw_data import RawData -from bcipy.signal.process import Composition, get_default_transform +from bcipy.signal.process import Composition, get_default_transform, ERPTransformParams import bcipy.acquisition.devices as devices import mne @@ -48,17 +48,17 @@ def visualize_erp( channel_map(List[int]): Map of channels to remove (0) or keep (1) trigger_timing: list of trigger timing trigger_labels: list of trigger labels - trial_length: length of trials described in trigger_timing / labels in seconds + trial_window: Tuple[float, float]: time window to plot transform(Composition): Optional BciPy composition to apply to data before visualization plot_average: Optional[boolean]: whether or not to average over all channels. Default: True plot_topomap: Optional[boolean]: whether or not to plot all channels across target/nontarget. Default: True show: Optional[boolean]: whether or not to show the figures generated. Default: False save_path: optional path to a save location of the figure generated """ - # check for trial length in seconds + # check for trial length in seconds from stimuli start (0.0) trial_length = trial_window[1] - 0.0 - # check for baseline interval + # check for a baseline interval or set to None if trial_window[0] < 0: baseline = (trial_window[0], 0) else: @@ -155,7 +155,17 @@ def visualize_joint_average( See: https://mne.tools/dev/generated/mne.Evoked.html#mne.Evoked.plot_joint + Parameters: + epochs(Tuple[Epochs]): MNE Epochs + labels(List[str]): List of labels for each Epoch + plot_joint_times(List[float]): List of times to plot topomaps + save_path(Optional[str]): Path to save the figures + show(Optional[bool]): Whether to show the figures + Note: assumes the number of Epochs (passed as a tuple) is equal to the number of labels provided + + Returns: + List of figures generated """ assert len(epochs) == len(labels), "The number of epochs must match labels in Visualize Joint Average" @@ -171,16 +181,22 @@ def visualize_joint_average( return figs -def visualize_evokeds(epochs: Tuple[Epochs, Epochs], save_path: Optional[str] - = None, show: Optional[bool] = False) -> List[Figure]: +def visualize_evokeds(epochs: Tuple[Epochs, Epochs], + save_path: Optional[str] = None, + show: Optional[bool] = False) -> List[Figure]: """Visualize Evokeds. Using MNE Epochs, generate a compare evokeds plot using the mean and showing parametric confidence interval in shaded region. See: https://mne.tools/stable/generated/mne.viz.plot_compare_evokeds.html - - Note: Assumes first epoch is nontarget and second is target.""" + + Parameters: + + epochs(Tuple[Epochs]): MNE Epochs Note: Assumes first epoch is nontarget and second is target. + save_path(Optional[str]): Path to save the figures + show(Optional[bool]): Whether to show the figures + """ evokeds = dict(nontarget=list(epochs[0].iter_evoked()), target=list(epochs[1].iter_evoked())) fig = mne.viz.plot_compare_evokeds(evokeds, combine='mean', show=show) @@ -208,30 +224,26 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi Figure of Session Data """ # extract all relevant parameters - poststim_length = parameters.get("trial_length") - # get signal filtering information - downsample_rate = parameters.get("down_sampling_rate") - notch_filter = parameters.get("notch_filter_frequency") - filter_high = parameters.get("filter_high") - filter_low = parameters.get("filter_low") - filter_order = parameters.get("filter_order") + trial_window = parameters.get("trial_window") static_offset = parameters.get("static_trigger_offset") raw_data = load_raw_data(Path(session_path, f'{RAW_DATA_FILENAME}.csv')) channels = raw_data.channels sample_rate = raw_data.sample_rate + transform_params = parameters.instantiate(ERPTransformParams) + devices.load(Path(session_path, DEFAULT_DEVICE_SPEC_FILENAME)) device_spec = devices.preconfigured_device(raw_data.daq_type) # setup filtering default_transform = get_default_transform( sample_rate_hz=sample_rate, - notch_freq_hz=notch_filter, - bandpass_low=filter_low, - bandpass_high=filter_high, - bandpass_order=filter_order, - downsample_factor=downsample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, ) # Process triggers.txt files trigger_targetness, trigger_timing, _ = trigger_decoder( @@ -251,7 +263,7 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi channel_map, trigger_timing, labels, - poststim_length, + trial_window, transform=default_transform, plot_average=True, plot_topomaps=True, diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 64f89220a..2dc7822ac 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -48,11 +48,15 @@ "type": "int" }, "trial_window": { - "value": "0.2:0.8", + "value": "0.0:0.5", "section": "bci_config", "readableName": "Trial Classification Window Length", "helpTip": "Specifies the window (in seconds) of the EEG data collection window after each stimulus presentation. Default: 0.0:0.5", - "recommended_values": "", + "recommended_values": [ + "0.0:0.5", + "0.0:0.8", + "0.2:0.8" + ], "type": "range" }, "prestim_length": { @@ -618,7 +622,7 @@ "type": "int" }, "lang_model_type": { - "value": "MIXTURE", + "value": "UNIFORM", "section": "lang_model_config", "readableName": "Language Model Type", "helpTip": "Specifies which language model to use. Default: MIXTURE", diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 789a83dd0..8c58017fe 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -34,13 +34,15 @@ def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_s """Performs a train/test split on the provided data and labels, accounting for the current shape convention (channel dimension in front, instead of batch dimension in front). - Args: + Parameters: + ----------- data (np.ndarray): Shape (channels, items, time) labels (np.ndarray): Shape (items,) test_size (float): fraction of data to be used for testing random_state (int, optional): fixed random seed Returns: + -------- train_data (np.ndarray): Shape (channels, train_items, time) test_data (np.ndarray): Shape (channels, test_items, time) train_labels (np.ndarray): Shape (train_items,) @@ -66,15 +68,6 @@ def offline_analysis( ) -> Tuple[SignalModel, Figure]: """Gets calibration data and trains the model in an offline fashion. pickle dumps the model into a .pkl folder - Args: - data_folder(str): folder of the data - save all information and load all from this folder - parameter(dict): parameters for running offline analysis - alert_finished(bool): whether or not to alert the user offline analysis complete - estimate_balanced_acc(bool): if true, uses another model copy on an 80/20 split to - estimate balanced accuracy - show_figures(bool): if true, shows ERP figures after training - save_figures(bool): if true, saves ERP figures after training to the data folder How it Works: - reads data and information from a .csv calibration file @@ -87,8 +80,24 @@ def offline_analysis( - pickle dumps model into .pkl file - generates and [optional] saves/shows the ERP figure - [optional] alert the user finished processing + + Parameters: + ---------- + data_folder(str): folder of the data + save all information and load all from this folder + parameter(dict): parameters for running offline analysis + alert_finished(bool): whether or not to alert the user offline analysis complete + estimate_balanced_acc(bool): if true, uses another model copy on an 80/20 split to + estimate balanced accuracy + show_figures(bool): if true, shows ERP figures after training + save_figures(bool): if true, saves ERP figures after training to the data folder + + Returns: + -------- + model (SignalModel): trained model + figure_handles (Figure): handles to the ERP figures """ - assert parameters, "Parameters are required" + assert parameters, "Parameters are required for offline analysis." if not data_folder: data_folder = load_experimental_data() @@ -142,7 +151,7 @@ def offline_analysis( model = PcaRdaKdeModel(k_folds=k_folds) # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + trigger_targetness, trigger_timing, _ = trigger_decoder( offset=static_offset, 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Display: def init_display(parameters, win, experiment_clock, starting_spelled_text): """Constructs a new Matrix display""" - # preview_inquiry = PreviewInquiryProperties( - # preview_only=parameters['preview_only'], - # preview_inquiry_length=parameters['preview_inquiry_length'], - # preview_inquiry_key_input=parameters['preview_inquiry_key_input'], - # preview_inquiry_progress_method=parameters[ - # 'preview_inquiry_progress_method'], - # preview_inquiry_isi=parameters['preview_inquiry_isi']) info = InformationProperties( info_color=[parameters['info_color']], diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index bc2f45c5e..04c6121d7 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -84,7 +84,7 @@ class RSVPCopyPhraseTask(Task): MODE = 'RSVP' PARAMETERS_USED = [ - 'time_fixation', 'time_flash', 'time_prompt', 'trial_length', + 'time_fixation', 'time_flash', 'time_prompt', 'trial_window', 'font', 'fixation_color', 'trigger_type', 'filter_high', 'filter_low', 'filter_order', 'notch_filter_frequency', 'down_sampling_rate', 'prestim_length', 'is_txt_stim', 'lm_backspace_prob', 'backspace_always_shown', @@ -230,7 +230,7 @@ def validate_parameters(self) -> None: # ensure data / query parameters are set correctly buffer_len = self.parameters['task_buffer_length'] prestim = self.parameters['prestim_length'] - poststim = self.parameters['trial_length'] + poststim = self.parameters['trial_window'][1] - self.parameters['trial_window'][0] if buffer_len < prestim: raise TaskConfigurationException( f'task_buffer_length=[{buffer_len}] must be greater than prestim_length=[{prestim}]') diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index d84b2f9c9..68fb1e794 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -79,7 +79,7 @@ def setUp(self): 'time_fixation': 0.5, 'time_flash': 0.25, 'time_prompt': 1.0, - 'trial_length': 0.5, + 'trial_window': (0.0, 0.5), 'trigger_type': 'image', } self.parameters = Parameters.from_cast_values(**parameters) @@ -190,8 +190,8 @@ def test_validate_parameters_throws_task_exception_excess_prestim_length(self): language_model=self.language_model, fake=True) - def test_validate_parameters_throws_task_exception_excess_trial_length(self): - self.parameters['trial_length'] = 1000 + def test_validate_parameters_throws_task_exception_excess_trial_window(self): + self.parameters['trial_window'] = "0.0:1000.0" with self.assertRaises(TaskConfigurationException): RSVPCopyPhraseTask( From ecf2df2109051cbc580345528528fa137c778894 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 24 Aug 2023 12:41:55 -0700 Subject: [PATCH 065/330] linting --- bcipy/helpers/load.py | 2 +- bcipy/helpers/stimuli.py | 1 + bcipy/helpers/visualization.py | 6 +++--- bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 2 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 4 ++-- 5 files changed, 8 insertions(+), 7 deletions(-) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index f7b14aa87..a12980ef3 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -5,7 +5,7 @@ from pathlib import Path from shutil import copyfile from time import localtime, strftime -from typing import Any, Dict, List, Optional, Tuple +from typing import List, Optional from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_PATH, DEFAULT_FIELD_PATH, DEFAULT_PARAMETERS_PATH, diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 8552f7a3d..d4e55dd0a 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -311,6 +311,7 @@ def mne_epochs(mne_data: RawArray, events_from_annot, _ = mne.events_from_annotations(mne_data) return Epochs(mne_data, events_from_annot, tmax=trial_length, baseline=baseline) + def alphabetize(stimuli: List[str]) -> List[str]: """Alphabetize. diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index b511eed39..c4e4b6cfc 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -57,7 +57,7 @@ def visualize_erp( """ # check for trial length in seconds from stimuli start (0.0) trial_length = trial_window[1] - 0.0 - + # check for a baseline interval or set to None if trial_window[0] < 0: baseline = (trial_window[0], 0) @@ -190,9 +190,9 @@ def visualize_evokeds(epochs: Tuple[Epochs, Epochs], interval in shaded region. See: https://mne.tools/stable/generated/mne.viz.plot_compare_evokeds.html - + Parameters: - + epochs(Tuple[Epochs]): MNE Epochs Note: Assumes first epoch is nontarget and second is target. save_path(Optional[str]): Path to save the figures show(Optional[bool]): Whether to show the figures diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index faab1de69..6d30f2386 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -180,5 +180,5 @@ def load(self, path: Path) -> SignalModel: """Load pretrained model from `path`""" with open(path, "rb") as f: model = pickle.load(f) - + return model diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 04c6121d7..8affe1fa4 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -230,7 +230,7 @@ def validate_parameters(self) -> None: # ensure data / query parameters are set correctly buffer_len = self.parameters['task_buffer_length'] prestim = self.parameters['prestim_length'] - poststim = self.parameters['trial_window'][1] - self.parameters['trial_window'][0] + poststim = self.parameters['trial_window'][1] - self.parameters['trial_window'][0] if buffer_len < prestim: raise TaskConfigurationException( f'task_buffer_length=[{buffer_len}] must be greater than prestim_length=[{prestim}]') @@ -580,7 +580,7 @@ def compute_device_evidence( inquiry_timing = self.stims_for_decision(stim_times) # update the inquiry timing list (stim, time) based on the trial window first time value - inquiry_timing = [(stim, time + trial_window[0]) for stim, time in inquiry_timing] + inquiry_timing = [(stim, time + trial_window[0]) for stim, time in inquiry_timing] # Get all data at once so we don't redundantly query devices which are # used in more than one signal model. From 4922d203ceb5621dd1dabf9e0bb011a78cffeb8c Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 24 Aug 2023 14:14:49 -0700 Subject: [PATCH 066/330] Renamed matrix_width parameter; added changelog --- CHANGELOG.md | 1 + bcipy/parameters/parameters.json | 2 +- bcipy/task/paradigm/matrix/calibration.py | 2 +- bcipy/task/paradigm/matrix/copy_phrase.py | 2 +- 4 files changed, 4 insertions(+), 3 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 4b8772129..2c5c6e59c 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -13,6 +13,7 @@ - Matrix - Matrix calibration refinements #262 - Matrix Copy Phrase Task #261 + - Matrix displays can be parameterized with a given number of rows and columns. #289 - RSVP - RSVP Calibration pulls out inquiry preview parameters and calls the display with them if enabled - RSVP Display `do_inquiry` accepts a preview_calibration argument that will present the full inquiry to come if True after the prompt and before the fixation diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index d6ccba53f..9abbf79c2 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -240,7 +240,7 @@ "recommended_values": "", "type": "int" }, - "matrix_width_pct": { + "matrix_width": { "value": "0.7", "section": "bci_config", "readableName": "Matrix Width (%)", diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index a556cfa73..5c9147b8b 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -273,6 +273,6 @@ def init_calibration_display_task( info, rows=parameters['matrix_rows'], columns=parameters['matrix_columns'], - width_pct=parameters['matrix_width_pct'], + width_pct=parameters['matrix_width'], trigger_type=parameters['trigger_type'], symbol_set=symbol_set) diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index d397328f8..f4eba92ab 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -82,6 +82,6 @@ def init_display(parameters, win, experiment_clock, starting_spelled_text): info, rows=parameters['matrix_rows'], columns=parameters['matrix_columns'], - width_pct=parameters['matrix_width_pct'], + width_pct=parameters['matrix_width'], trigger_type=parameters['trigger_type'], should_prompt_target=False) From 979610eeb6b2f97b87b3d25ec9b1b5df0b1c29d8 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 24 Aug 2023 19:57:59 -0700 Subject: [PATCH 067/330] Add to changelog and lint scripts --- CHANGELOG.md | 2 ++ scripts/python/lm_eval.py | 36 +++++++++++++++++------------ scripts/python/mixture_tuning.py | 38 +++++++++++++++---------------- scripts/python/offset_analysis.py | 34 ++++++++++++++------------- scripts/python/replay_session.py | 18 +++++++-------- 5 files changed, 69 insertions(+), 59 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index c9e2e8b44..7899428c7 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,6 +8,8 @@ Our last release candidate before the official 2.0 release! - Support for multiple devices in online querying #286 - Stimuli - Updates to ensure stimuli are presented at the same frequency #287 +- Dynamic Selection Window + - Updated trial_length to trial_window to allow for greater control of window used after stimulus presentations #291 - Parameters - Add a Range type parameter #285 - Cleanup diff --git a/scripts/python/lm_eval.py b/scripts/python/lm_eval.py index 8db5f53d1..bc377f7b6 100644 --- a/scripts/python/lm_eval.py +++ b/scripts/python/lm_eval.py @@ -5,7 +5,7 @@ from bcipy.language.main import ResponseType from math import log10 from timeit import default_timer as timer -from bcipy.helpers.symbols import BACKSPACE_CHAR, SPACE_CHAR, alphabet +from bcipy.helpers.symbols import SPACE_CHAR, alphabet import argparse import numpy as np import sys @@ -14,13 +14,15 @@ parser = argparse.ArgumentParser() parser.add_argument('--verbose', dest='verbose', type=int, required=True, - help='0: Only output model averages\n1: Output results from each phrase\n2: Output results from each character') + help=('0: Only output model averages\n1: Output results from each phrase\n2: ' + 'Output results from each character')) parser.add_argument('--model', dest='model', type=int, required=True, - help='1: Unigram\n2: Mixture (80/20 Causal GPT-2/Unigram)\n3: KenLM n-gram\n4: Causal Hugging Face') + help=('1: Unigram\n2: Mixture (80/20 Causal GPT-2/Unigram)\n3: ' + 'KenLM n-gram\n4: Causal Hugging Face')) parser.add_argument('--phrases', dest='phrases', type=str, required=True, - help='Phrase set filename') + help='Phrase set filename') parser.add_argument('--model-name', dest='model_name') parser.add_argument('--model-dir', @@ -41,11 +43,11 @@ phrases = args.phrases if model == 3 and not args.model_dir: - print(f"ERROR: For KenLM n-gram model you must specify filename of model using --model-dir") + print("ERROR: For KenLM n-gram model you must specify filename of model using --model-dir") sys.exit(1) if model == 4 and not args.model_name: - print(f"ERROR: For causal model you must specify name of model using --model-name") + print("ERROR: For causal model you must specify name of model using --model-name") sys.exit(1) # Allow passing in of space characters in the context using word @@ -65,7 +67,7 @@ lm = None start = timer() - + symbol_set = alphabet() response_type = ResponseType.SYMBOL if model == 1: @@ -122,7 +124,7 @@ correct_char = "" # BciPy treats space as underscore - if(token == ""): + if (token == ""): token = SPACE_CHAR correct_char = SPACE_CHAR else: @@ -132,7 +134,8 @@ predict_time = timer() - start_predict predict_time_arr = np.append(predict_time_arr, predict_time) - predict_details_arr = np.append(predict_details_arr, f"sentence = {sentence}, index = {i}, p( {token} | {prev_token} )") + predict_details_arr = np.append(predict_details_arr, + f"sentence = {sentence}, index = {i}, p( {token} | {prev_token} )") # Find the probability for the correct character p = next_char_pred[[c[0] for c in next_char_pred].index(correct_char)][1] @@ -167,14 +170,17 @@ if accum == 1: if verbose >= 1: print("Zero-prob event encountered, terminating phrase") - print(f"per-symbol prediction time = {per_symbol_time:.6f} +/- {phrase_std:.6f} [{phrase_min:.6f}, {phrase_max:.6f}]\n") + print(f"per-symbol prediction time = {per_symbol_time:.6f} +/- {phrase_std:.6f} [{phrase_min:.6f}, " + f"{phrase_max:.6f}]\n") else: per_symbol_logprob = accum / symbols # Phrase-level output if verbose >= 1: - print(f"sum logprob = {accum:.4f}, per-symbol logprob = {per_symbol_logprob:.4f}, ppl = {pow(10,-1 * per_symbol_logprob):.4f}") - print(f"per-symbol prediction time = {per_symbol_time:.6f} +/- {phrase_std:.6f} [{phrase_min:.6f}, {phrase_max:.6f}]\n") + print(f"sum logprob = {accum:.4f}, per-symbol logprob = {per_symbol_logprob:.4f}, " + f"ppl = {pow(10,-1 * per_symbol_logprob):.4f}") + print(f"per-symbol prediction time = {per_symbol_time:.6f} +/- {phrase_std:.6f} " + f"[{phrase_min:.6f}, {phrase_max:.6f}]\n") sum_per_symbol_logprob += per_symbol_logprob phrase_count += 1 @@ -189,14 +195,14 @@ ci_floor = overall_per_symbol_time - (3 * overall_std_time) ci_ceiling = overall_per_symbol_time + (3 * overall_std_time) - # Model-level output print(f"OVERALL \ \nphrases = {phrase_count}, \ \naverage per symbol logprob = {average_per_symbol_logprob:.4f}, \ \nppl = {pow(10,-1 * average_per_symbol_logprob):.4f}, \ \nzero-prob events = {zero_prob} \ - \nper-symbol prediction time = {overall_per_symbol_time:.6f} +/- {overall_std_time:.6f} [{overall_min_time:.6f}, {overall_max_time:.6f}] \ + \nper-symbol prediction time = {overall_per_symbol_time:.6f} +/- {overall_std_time:.6f} \ + [{overall_min_time:.6f}, {overall_max_time:.6f}] \ \n95% CI = [{ci_floor}, {ci_ceiling}]\n") print(f"Inference time = {timer() - start:.6f}") @@ -205,4 +211,4 @@ if time < ci_floor: print(f"LOW OUTLIER: {overall_predict_details_arr[i]}, predict time = {time:.6f}\n") if time > ci_ceiling: - print(f"HIGH OUTLIER: {overall_predict_details_arr[i]}, predict time = {time:.6f}\n") \ No newline at end of file + print(f"HIGH OUTLIER: {overall_predict_details_arr[i]}, predict time = {time:.6f}\n") diff --git a/scripts/python/mixture_tuning.py b/scripts/python/mixture_tuning.py index 576d94681..e8e5e172f 100644 --- a/scripts/python/mixture_tuning.py +++ b/scripts/python/mixture_tuning.py @@ -6,10 +6,10 @@ if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument('--step', dest='step', type=int, required=True, - help='The number of weight steps to be used in the sweep search') + help='The number of weight steps to be used in the sweep search') parser.add_argument('--in', dest='files', type=str, required=True, nargs='+', - help="Two or more paths pointing to output files from the lm_eval script with --verbose 2") + help="Two or more paths pointing to output files from the lm_eval script with --verbose 2") args = parser.parse_args() @@ -32,39 +32,39 @@ sentence_pslp_arr = [] for line in zip(*lines): if line[0].startswith("sentence = "): - for l in line: - if not l.startswith("sentence = "): + for elm in line: + if not elm.startswith("sentence = "): print("Line mismatch. Please ensure all files were run on the same phrase set.") exit() probs = [] elif line[0].startswith("p( "): - for l in line: - if not l.startswith("p( "): + for elm in line: + if not elm.startswith("p( "): print("Line mismatch. Please ensure all files were run on the same phrase set.") exit() - if l[-5:] == " = 0\n": + if elm[-5:] == " = 0\n": print("Error: Component model zero prob.") exit() component_probs = [] mixed_probs = [] - for l in line: - component_probs.append(float(l[l.index("=") + 2:l.index("[") - 1])) - for w in weights: - mixed_probs.append(np.dot(w, component_probs)) + for elm in line: + component_probs.append(float(elm[elm.index("=") + 2:elm.index("[") - 1])) + for weight in weights: + mixed_probs.append(np.dot(weight, component_probs)) probs.append(mixed_probs) elif line[0].startswith("sum logprob = "): - for l in line: - if not l.startswith("sum logprob = "): + for elm in line: + if not elm.startswith("sum logprob = "): print("Line mismatch. Please ensure all files were run on the same phrase set.") exit() logprobs = [] - for p in probs: - l = [log10(i) for i in p] - logprobs.append(l) + for prob in probs: + log_list = [log10(i) for i in prob] + logprobs.append(log_list) sentence_pslp_arr.append([np.average(w) for w in zip(*logprobs)]) elif line[0].startswith("OVERALL"): - for l in line: - if not l.startswith("OVERALL"): + for elm in line: + if not elm.startswith("OVERALL"): print("Line mismatch. Please ensure all files were run on the same phrase set.") exit() @@ -74,4 +74,4 @@ print(f"{weight}\t\t{ppl:.3f}") print(f"\nBEST: {weights[np.argmin(overall_ppl_arr)]} {np.min(overall_ppl_arr):.3f}") - break \ No newline at end of file + break diff --git a/scripts/python/offset_analysis.py b/scripts/python/offset_analysis.py index a70b306ad..0001926b5 100644 --- a/scripts/python/offset_analysis.py +++ b/scripts/python/offset_analysis.py @@ -2,27 +2,29 @@ Assumptions: - The raw_data.csv file is available. - - The raw_data.csv file contains a TRG column, which is a continuous line of 0s and values greater than 0 (indicating a photodiode trigger event). + - The raw_data.csv file contains a TRG column, which is a continuous line of 0s and values greater than 0 + (indicating a photodiode trigger event). - The triggers.txt file is available. - All data are in the same directory and in the BciPy session data format. Usage: - Run the script from the command line. - Select the directory containing the raw_data.csv and triggers.txt files. - - The script will plot the TRG column from the raw_data.csv file, as well as the triggers.txt file. - - The script will also print out the results of the analysis, including the number of violations (set using the --tolerance flag) and the recommended static offset (-r). + - The script will plot the TRG column from the raw_data.csv file, as well as the triggers.txt file. + - The script will also print out the results of the analysis, including the number of violations + (set using the --tolerance flag) and the recommended static offset (-r). + + Example usage to recommend a static offset: + python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' -r - Example usage to recommned a static offset: - python offset_analysis.py -p C:/Users/bcipy/Documents/BCI-Project/bcipy/bcipy/tests/test_data/test_offset_analysis/ -r - Example usage to recommend a static offset using the RSVP Time Test Calibrations: - python offset_analysis.py -p C:/Users/bcipy/Documents/BCI-Project/bcipy/bcipy/tests/test_data/test_offset_analysis/ --rsvp -r + python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' --rsvp -r Example usage to plot the data next to photodiode results with a static offset applied: - python offset_analysis.py -p C:/Users/bcipy/Documents/BCI-Project/bcipy/bcipy/tests/test_data/test_offset_analysis/ --offset 0.01 + python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' --offset 0.01 Example usage to plot the data next to photodiode results with a static offset applied and a tolerance of 10 ms: - python offset_analysis.py -p C:/Users/bcipy/Documents/BCI-Project/bcipy/bcipy/tests/test_data/test_offset_analysis/ --offset 0.01 --tolerance 0.01 + python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' --offset 0.01 --tolerance 0.01 """ from pathlib import Path from textwrap import wrap @@ -204,7 +206,8 @@ def read_triggers(triggers_file: str, static_offset: float): return corrected -def main(data_dir: str, recommend: bool = False, static_offset: float = 0.105, tolerance: float = 0.01, rsvp: bool = False): +def main(data_dir: str, recommend: bool = False, static_offset: float = 0.105, + tolerance: float = 0.01, rsvp: bool = False): """Run the viewer gui Parameters: @@ -231,8 +234,7 @@ def main(data_dir: str, recommend: bool = False, static_offset: float = 0.105, t import argparse parser = argparse.ArgumentParser( - description= - "Graphs trigger data from a bcipy session to visualize system latency") + description="Graphs trigger data from a bcipy session to visualize system latency") parser.add_argument('-p', '--path', help='path to the data directory', @@ -244,18 +246,18 @@ def main(data_dir: str, recommend: bool = False, static_offset: float = 0.105, t parser.add_argument('--offset', help='static offset applied to triggers for plotting and analysis', default=0.114) - parser.add_argument('-t','--tolerance', + parser.add_argument('-t', '--tolerance', help='Allowable tolerance between triggers and photodiode. Deafult 10 ms', default=0.01) parser.add_argument('--rsvp', - help='RSVP Calibration Task. Default False. Corrects for issue with fixation causing a false positive.', + help=('RSVP Calibration Task. Default False. ' + 'Corrects for issue with fixation causing a false positive.'), type=bool, default=True) - args = parser.parse_args() path = args.path if not path: path = ask_directory() - main(path, bool(args.recommend), float(args.offset), float(args.tolerance), bool(args.rsvp)) \ No newline at end of file + main(path, bool(args.recommend), float(args.offset), float(args.tolerance), bool(args.rsvp)) diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 7ef0f30d2..35b8475a8 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -27,6 +27,7 @@ logger.getLogger().setLevel(logger.INFO) + def load_model(model_path: Path, k_folds: int, model_class=PcaRdaKdeModel): """Load the model at the given path""" with open(model_path, "rb") as f: @@ -43,7 +44,7 @@ def generate_replay_outputs( symbol_set=alphabet(), write_output=False) -> Tuple[dict, list, list]: """Replay a session and generate outputs for the provided model. - + Parameters ---------- data_folder: Path @@ -58,7 +59,7 @@ def generate_replay_outputs( List of symbols to use for the replay session. By default, this is the alphabet. write_output: bool Whether or not to write the output to a file. By default, this is False. - + Returns ------- tuple - new_model_outputs, old_model_target_output, old_model_nontarget_output @@ -76,7 +77,7 @@ def generate_replay_outputs( trial_length = trial_window[1] - trial_window[0] adjust_trials_by_window = True logger.info(f"Trial Window: {trial_window[0]}-{trial_window[1]}s") - + trials_per_inquiry = parameters.get("stim_length") prestim_length = parameters.get("prestim_length", trial_length) buffer_length = int(parameters.get("task_buffer_length") / 2) @@ -176,7 +177,6 @@ def generate_replay_outputs( with open(data_folder / "replay_outputs.json", "w") as f: json.dump(outputs, f, indent=2) - # TODO separate this from the method # Get values computed during actual experiment from session.json for comparison session_json = data_folder / SESSION_DATA_FILENAME all_target_eeg, all_nontarget_eeg = load_eeg_evidence_from_session_json(session_json, symbol_set) @@ -186,7 +186,7 @@ def generate_replay_outputs( def load_eeg_evidence_from_session_json(session_json, symbol_set) -> Tuple[list, list]: """Load EEG evidence from session.json file for comparison with replay outputs. - + Parameters ---------- session_json : str @@ -214,10 +214,10 @@ def load_eeg_evidence_from_session_json(session_json, symbol_set) -> Tuple[list, continue else: stim_label = inquiry["stimuli"][0] # name of symbols presented - stim_label.pop(0) # remove fixation cross + stim_label.pop(0) # remove fixation cross stim_indices = [symbol_set.index(sym) for sym in stim_label] targetness = inquiry["target_info"] # targetness of stimuli - targetness.pop(0) # remove fixation cross + targetness.pop(0) # remove fixation cross target = [index for index, label in zip(stim_indices, targetness) if label == "target"] nontarget = [index for index, label in zip(stim_indices, targetness) if label == "nontarget"] all_target_eeg.extend([inquiry["eeg_evidence"][pos] for pos in target]) @@ -358,7 +358,7 @@ def plot_collected_outputs( targets_with_old_model, nontargets_with_old_model, args.outdir) - - breakpoint() + + # breakpoint() logger.info("Replay complete.") From 713f8702991901d55a3a7cea605f7e03f521639e Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 24 Aug 2023 20:21:29 -0700 Subject: [PATCH 068/330] remove breakpoint from model loading --- scripts/python/replay_session.py | 1 - 1 file changed, 1 deletion(-) diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 35b8475a8..91d24026a 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -32,7 +32,6 @@ def load_model(model_path: Path, k_folds: int, model_class=PcaRdaKdeModel): """Load the model at the given path""" with open(model_path, "rb") as f: model = pickle.load(f) - breakpoint() return model From c5e40e313dd2432bb89ffbb56b095d789d6ee9f0 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 24 Aug 2023 23:30:28 -0400 Subject: [PATCH 069/330] Visualization for results added --- bcipy/helpers/stimuli.py | 45 ++++++++++++++++---------- bcipy/helpers/visualization.py | 33 +++++++++++++++++-- bcipy/signal/model/fusion_model.py | 3 +- bcipy/signal/model/offline_analysis.py | 6 ++-- 4 files changed, 63 insertions(+), 24 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 34052ad0c..c429e5d46 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -258,11 +258,11 @@ def __call__(self, transformation_buffer (float, optional): time in seconds to buffer the end of the inquiry. Defaults to 0.0. Returns: - reshaped_data (np.ndarray): inquiry data of shape (Inquiries, Channels, Samples) + reshaped_data (List[float]): inquiry data of shape (Inquiries, Channels, Samples) labels (List[str]): Target letter in each inquiry. data_by_targets (dict): Dictionary where keys are the symbol set and values are the appended inquiries - for each symbol. dict[Key] = list of shape (Channels, Samples) + for each symbol. dict[Key] = (np.ndarray) of shape (Channels, Samples) """ if channel_map: # Remove the channels that we are not interested in @@ -298,12 +298,26 @@ def __call__(self, for i, inquiry_index in enumerate(triggers): start = inquiry_index stop = int(inquiry_index + (sample_rate * 3)) # (60 samples * 3 seconds) - reshaped_data.append(gaze_data[:, start:stop]) + # Check if the data exists for the inquiry: + if stop > len(gaze_data[0,:]): + continue + + reshaped_data.append(gaze_data[:, start:stop]) + # (Optional) extracted data (Inquiries x Channels x Samples) + + # Populate the dict by appending the inquiry to the correct key: + data_by_targets[labels[i]].append(gaze_data[:, start:stop]) + + # After populating, flatten the arrays in the dictionary to (Channels x Samples): + for symbol in symbol_set: + if len(data_by_targets[symbol]) > 0: + data_by_targets[symbol] = np.transpose(np.array(data_by_targets[symbol]), (1,0,2)) + data_by_targets[symbol] = np.reshape(data_by_targets[symbol], (len(data_by_targets[symbol]), -1)) - # Create a dictionary: - for symbol in symbol_set: - if symbol == labels[i]: - data_by_targets[symbol].append(gaze_data[:, start:stop]) + # TODO: Note that this is a workaround to the issue of having different number of targetness in + # each symbol. If a target symbol is prompted more than once, the data is appended to the dict as a list. + # Which is why we need to convert it to a (np.ndarray) and flatten the dimensions. + # This is not ideal, but it works for now. # return np.stack(reshaped_data, 0), labels return data_by_targets @@ -314,24 +328,21 @@ def extract_eye_info(data): Extract Left and Right Eye info from data. Args: - data (List(float)): Data in shape of num_targetness x num_channels x num_samples + data (np.ndarray): Data in shape of num_channels x num_samples Returns: left_eye (np.ndarray), left_pupil (List(float)) right_eye (np.ndarray), right_pupil (List(float)) """ - temp_data = np.transpose(np.array(data), (1,0,2)) - inq_data = np.reshape(temp_data, (len(temp_data), -1)) # num_channels x num_samples - # Extract samples from channels - lx = inq_data[2,:] - ly = inq_data[3,:] - left_pupil = inq_data[4,:] + lx = data[2,:] + ly = data[3,:] + left_pupil = data[4,:] - rx = inq_data[5,:] - ry = inq_data[6,:] - right_pupil = inq_data[7,:] + rx = data[5,:] + ry = data[6,:] + right_pupil = data[7,:] left_eye = np.vstack((np.array(lx), np.array(ly))).T right_eye = np.vstack((np.array(rx), np.array(ry))).T diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 37f60acc5..8754c2842 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -3,6 +3,7 @@ from typing import List, Optional, Tuple from pathlib import Path from matplotlib.figure import Figure +from matplotlib.patches import Ellipse import matplotlib.pyplot as plt from bcipy.config import (TRIGGER_FILENAME, RAW_DATA_FILENAME, @@ -22,6 +23,7 @@ from mne.io import read_raw_edf import numpy as np import seaborn as sns +from scipy import linalg import matplotlib.pyplot as plt import pandas as pd @@ -173,6 +175,8 @@ def visualize_gaze( def visualize_gaze_inquiries( left_eye, right_eye, + means=None, + covs=None, save_path=None, show=False, img_path=None, @@ -186,7 +190,8 @@ def visualize_gaze_inquiries( Parameters ---------- - left eye, right eye: Raw gaze data (np.ndarray) + left eye, right eye: (np.ndarray): Raw gaze data, plotting both eyes is optional + means, covs: Optional(np.ndarray): Means and covariances of the Gaussian Mixture Model save_path: Optional[str] show: Optional[bool] img_path: Optional[str] @@ -212,6 +217,11 @@ def visualize_gaze_inquiries( ly = 1 - ly ry = 1 - ry + if means is not None: + means[:,0] = np.clip(means[:,0], 0, 1) + means[:,1] = np.clip(means[:,1], 0, 1) + means[:,1] = 1 - means[:,1] + # remove nan values # lx = lx[~np.isnan(lx)] # ly = ly[~np.isnan(ly)] @@ -241,8 +251,25 @@ def visualize_gaze_inquiries( colorbar=True) if raw_plot: - ax.scatter(lx, ly, c='r', s=1) - ax.scatter(rx, ry, c='b', s=1) + # ax.scatter(lx, ly, c='lightcoral', s=1) + ax.scatter(rx, ry, c='bisque', s=1) + + if means is not None: + for i, (mean, cov) in enumerate(zip(means, covs)): + v, w = linalg.eigh(cov) + v = 2.0 * np.sqrt(2.0) * np.sqrt(v) + u = w[0] / linalg.norm(w[0]) + + # Plot an ellipse to show the Gaussian component + angle = np.arctan(u[1] / u[0]) + angle = 180.0 * angle / np.pi # convert to degrees + ell = Ellipse(mean, v[0], v[1], angle=180.0 + angle, color='navy') + ell.set_clip_box(ax) + ell.set_alpha(0.5) + ax.add_artist(ell) + + # ax.scatter(means[:,0], means[:,1], c='yellow', s=20, marker='^') + plt.title(f'{title}Plot') diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py index b2a7eda4e..55e9bd201 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/fusion_model.py @@ -24,8 +24,9 @@ def fit(self, train_data: np.array): def predict(self, test_data: np.array): predictions = self.model.predict_proba(test_data) means = self.model.means_ + covs = self.model.covariances_ - return predictions, means + return predictions, means, covs diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 880b88eb2..e5ad5757b 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -315,13 +315,13 @@ def offline_analysis( # Fit the model: model.fit(train_right_eye) - predictions, means = model.predict(test_right_eye) + predictions, means, covs = model.predict(test_right_eye) # print(predictions) # Visualize the results: figure_handles = visualize_gaze_inquiries( - left_eye, - right_eye, + left_eye, right_eye, + means, covs, save_path=None, show=show_figures, raw_plot=True, From ee49f82a2022724bdbd1ff2f8e1d44ee51180784 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 25 Aug 2023 15:52:44 -0700 Subject: [PATCH 070/330] Added the ability to layout a matrix in qwerty order --- .../display/demo/matrix/demo_matrix_layout.py | 54 +++++++++++++++++++ bcipy/display/paradigm/matrix/display.py | 14 +++-- bcipy/helpers/symbols.py | 26 +++++++++ 3 files changed, 89 insertions(+), 5 deletions(-) create mode 100644 bcipy/display/demo/matrix/demo_matrix_layout.py diff --git a/bcipy/display/demo/matrix/demo_matrix_layout.py b/bcipy/display/demo/matrix/demo_matrix_layout.py new file mode 100644 index 000000000..7379af0f2 --- /dev/null +++ b/bcipy/display/demo/matrix/demo_matrix_layout.py @@ -0,0 +1,54 @@ +"""Demo Matrix Display functionality related to Calibration task logic.""" +# pylint: disable=invalid-name +from psychopy import core + +import bcipy.display.components.layout as layout +from bcipy.display import (InformationProperties, StimuliProperties, + init_display_window) +from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.matrix.display import MatrixDisplay +from bcipy.helpers.symbols import qwerty_order + +# Initialize Stimulus +window_parameters = { + 'full_screen': False, + 'window_height': 500, + 'window_width': 700, + 'stim_screen': 0, + 'background_color': 'black' +} + +experiment_clock = core.Clock() +win = init_display_window(window_parameters) +win.recordFrameIntervals = False + +task_bar = CalibrationTaskBar(win, + inquiry_count=5, + current_index=0, + font='Arial') + +stim_properties = StimuliProperties(stim_font='Arial', + stim_pos=[], + stim_height=0.17, + is_txt_stim=True) + +info = InformationProperties( + info_color=['white'], + info_pos=[layout.at_bottom(win, height=0.21).center], + info_height=[0.1], + info_font=['Arial'], + info_text=['Matrix Calibration Demo'], +) + +matrix_display = MatrixDisplay(win, + experiment_clock, + stim_properties, + task_bar=task_bar, + info=info, + rows=3, + columns=10, + sort_order=qwerty_order(is_txt_stim=True)) + +matrix_display.draw(grid_opacity=matrix_display.full_grid_opacity, + grid_color=matrix_display.grid_color, + duration=10) diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 85d4d74ee..74dfc8880 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -1,6 +1,6 @@ """Display for presenting stimuli in a grid.""" import logging -from typing import Dict, List, NamedTuple, Optional +from typing import Callable, Dict, List, NamedTuple, Optional from psychopy import core, visual @@ -45,7 +45,8 @@ def __init__(self, width_pct: float = 0.7, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, - should_prompt_target: bool = True): + should_prompt_target: bool = True, + sort_order: Callable = None): """Initialize Matrix display parameters and objects. PARAMETERS: @@ -68,6 +69,8 @@ def __init__(self, symbol_set default = none : subset of stimuli to be highlighted during an inquiry should_prompt_target(bool): when True prompts for the target symbol. Assumes that this is the first symbol of each inquiry. For example: [target, fixation, *stim]. + sort_order - optional function to define the position index for each + symbol. Using a custom function it is possible to skip a position. """ self.window = window @@ -81,7 +84,7 @@ def __init__(self, assert stimuli.is_txt_stim, "Matrix display is a text only display" self.symbol_set = symbol_set or alphabet() - + self.sort_order = sort_order or self.symbol_set.index # Set position and parameters for grid of alphabet self.grid_stimuli_height = 0.17 # stimuli.stim_height @@ -168,12 +171,13 @@ def do_inquiry(self) -> List[float]: def build_grid(self) -> Dict[str, visual.TextStim]: """Build the text stimuli to populate the grid.""" grid = {} - for i, sym in enumerate(self.symbol_set): + for sym in self.symbol_set: + pos_index = self.sort_order(sym) grid[sym] = visual.TextStim(win=self.window, text=sym, color=self.grid_color, opacity=self.start_opacity, - pos=self.positions[i], + pos=self.positions[pos_index], height=self.grid_stimuli_height) return grid diff --git a/bcipy/helpers/symbols.py b/bcipy/helpers/symbols.py index 0029df0c2..d39113e33 100644 --- a/bcipy/helpers/symbols.py +++ b/bcipy/helpers/symbols.py @@ -1,6 +1,7 @@ """Defines helper methods and variables related to input symbols""" import os from string import ascii_uppercase +from typing import Callable SPACE_CHAR = '_' BACKSPACE_CHAR = '<' @@ -33,4 +34,29 @@ def alphabet(parameters=None, include_path=True): return list(ascii_uppercase) + [BACKSPACE_CHAR, SPACE_CHAR] +def qwerty_order(is_txt_stim: bool = True) -> Callable: + """Returns a function that can be used to sort the alphabet symbols + in QWERTY order. Note that sorting only works for text stim. + """ + if not is_txt_stim: + raise NotImplementedError('QWERTY ordering not implemented for images') + + # Optionally, consider using the following: + # f"QWERTYUIOPASDFGHJKL ZXCVBNM{BACKSPACE_CHAR}{SPACE_CHAR}".index + row1 = "QWERTYUIOP" + row2 = "ASDFGHJKL<" + row3 = " ZXCV_BNM " + return f"{row1}{row2}{row3}".index + + +def frequency_order(is_txt_stim: bool = True) -> Callable: + """Returns a function that can be used to sort the alphabet symbols + in most frequently used order in the English language. + """ + if not is_txt_stim: + raise NotImplementedError( + 'Frequency ordering not implemented for images') + return f"ETAOINSHRDLCUMWFGYPBVKJXQZ{BACKSPACE_CHAR}{SPACE_CHAR}".index + + DEFAULT_SYMBOL_SET = alphabet() From b57c33a2dd1f872720f2f8888997d3d176aad412 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 28 Aug 2023 16:13:19 -0400 Subject: [PATCH 071/330] Visualization update --- bcipy/helpers/visualization.py | 23 ++++++----------------- bcipy/signal/model/offline_analysis.py | 14 ++++++++------ 2 files changed, 14 insertions(+), 23 deletions(-) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 8754c2842..333935294 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -180,7 +180,6 @@ def visualize_gaze_inquiries( save_path=None, show=False, img_path=None, - screen_size=(1920, 1080), heatmap=False, raw_plot=False): """Visualize Eye Data. @@ -195,7 +194,6 @@ def visualize_gaze_inquiries( save_path: Optional[str] show: Optional[bool] img_path: Optional[str] - screen_size: Optional[Tuple[int, int]] TODO """ title = 'Raw Gaze Inquiries ' @@ -204,16 +202,11 @@ def visualize_gaze_inquiries( img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' img = plt.imread(img_path) - left_eye_x = left_eye[:,0] - left_eye_y = left_eye[:,1] - right_eye_x = right_eye[:,0] - right_eye_y = right_eye[:,1] - # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis - lx = np.clip(left_eye_x, 0, 1) - ly = np.clip(left_eye_y, 0, 1) - rx = np.clip(right_eye_x, 0, 1) - ry = np.clip(right_eye_y, 0, 1) + lx = np.clip(left_eye[:,0], 0, 1) + ly = np.clip(left_eye[:,1], 0, 1) + rx = np.clip(right_eye[:,0], 0, 1) + ry = np.clip(right_eye[:,1], 0, 1) ly = 1 - ly ry = 1 - ry @@ -222,12 +215,6 @@ def visualize_gaze_inquiries( means[:,1] = np.clip(means[:,1], 0, 1) means[:,1] = 1 - means[:,1] - # remove nan values - # lx = lx[~np.isnan(lx)] - # ly = ly[~np.isnan(ly)] - # rx = rx[~np.isnan(rx)] - # ry = ry[~np.isnan(ry)] - # scale the eye data to the image fig, ax = plt.subplots() ax.imshow(img, extent=[0, 1, 0, 1]) @@ -278,6 +265,8 @@ def visualize_gaze_inquiries( if show: plt.show() + else: + plt.close() return fig diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index e5ad5757b..78a2aa7b3 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -244,10 +244,10 @@ def offline_analysis( figure_handles = visualize_gaze( mode_data, save_path=data_folder if save_figures else None, - show=show_figures, + show=True, raw_plot=True, ) - plt.show() + channels = mode_data.channels type_amp = mode_data.daq_type sample_rate = mode_data.sample_rate @@ -300,6 +300,9 @@ def offline_analysis( symbol_set = alphabet() # Train the model for each target label and each eye separately. for i in symbol_set: + # Skip if there's no evidence for this symbol: + if len(inquiries[i]) == 0: + continue # Do more preprocesssing to extract eye info: left_eye, left_pupil, right_eye, right_pupil = model.reshaper.extract_eye_info(inquiries[i]) @@ -323,12 +326,11 @@ def offline_analysis( left_eye, right_eye, means, covs, save_path=None, - show=show_figures, + show=False, raw_plot=True, - ) - plt.show() + ) - breakpoint() + breakpoint() From 2c482f2b9dd6a050e4872c3c65f8bd82f128ac6a Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 29 Aug 2023 17:12:01 -0700 Subject: [PATCH 072/330] Finalize QWERTY ordering --- bcipy/helpers/symbols.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/bcipy/helpers/symbols.py b/bcipy/helpers/symbols.py index d39113e33..467f5f59f 100644 --- a/bcipy/helpers/symbols.py +++ b/bcipy/helpers/symbols.py @@ -34,18 +34,18 @@ def alphabet(parameters=None, include_path=True): return list(ascii_uppercase) + [BACKSPACE_CHAR, SPACE_CHAR] -def qwerty_order(is_txt_stim: bool = True) -> Callable: +def qwerty_order(is_txt_stim: bool = True, + space: str = SPACE_CHAR, + backspace: str = BACKSPACE_CHAR) -> Callable: """Returns a function that can be used to sort the alphabet symbols in QWERTY order. Note that sorting only works for text stim. """ if not is_txt_stim: raise NotImplementedError('QWERTY ordering not implemented for images') - # Optionally, consider using the following: - # f"QWERTYUIOPASDFGHJKL ZXCVBNM{BACKSPACE_CHAR}{SPACE_CHAR}".index row1 = "QWERTYUIOP" - row2 = "ASDFGHJKL<" - row3 = " ZXCV_BNM " + row2 = f"ASDFGHJKL{backspace}" + row3 = f" ZXCV{space}BNM " return f"{row1}{row2}{row3}".index From 17a23417efb7d5829357941fcaa235f7bfc72afb Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 31 Aug 2023 16:42:54 -0700 Subject: [PATCH 073/330] #185934928 ; specify acquisition chunksize to override default values set by the device driver; modified lsl_server to simulate different chunk sizes --- bcipy/acquisition/datastream/lsl_server.py | 39 ++++++++++++------- bcipy/acquisition/protocols/lsl/lsl_client.py | 5 ++- .../acquisition/protocols/lsl/lsl_recorder.py | 2 +- 3 files changed, 30 insertions(+), 16 deletions(-) diff --git a/bcipy/acquisition/datastream/lsl_server.py b/bcipy/acquisition/datastream/lsl_server.py index 80f8181fa..75221a084 100644 --- a/bcipy/acquisition/datastream/lsl_server.py +++ b/bcipy/acquisition/datastream/lsl_server.py @@ -1,18 +1,18 @@ """Data server that streams EEG data over a LabStreamingLayer StreamOutlet using pylsl.""" import logging -from queue import Empty, Queue -from typing import Generator import time import uuid +from queue import Empty, Queue +from typing import Generator from pylsl import StreamInfo, StreamOutlet -from bcipy.config import DEFAULT_ENCODING from bcipy.acquisition.datastream.generator import random_data_generator from bcipy.acquisition.datastream.producer import Producer from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.util import StoppableThread +from bcipy.config import DEFAULT_ENCODING log = logging.getLogger(__name__) @@ -45,17 +45,24 @@ class LslDataServer(StoppableThread): channel at a fixed frequency. marker_stream_name: str, optional name of the sample marker stream + chunk_size: int, optional chunk size. """ - def __init__(self, device_spec: DeviceSpec, generator: Generator = None, include_meta: bool = True, - add_markers: bool = False, marker_stream_name: str = MARKER_STREAM_NAME): + def __init__(self, + device_spec: DeviceSpec, + generator: Generator = None, + include_meta: bool = True, + add_markers: bool = False, + marker_stream_name: str = MARKER_STREAM_NAME, + chunk_size: int = 0): super(LslDataServer, self).__init__() self.device_spec = device_spec self.generator = generator or random_data_generator(channel_count=device_spec.channel_count) - log.info("Starting LSL server for device: %s", device_spec.name) + log.debug("Starting LSL server for device: %s", device_spec.name) print(f"Serving: {device_spec}") + print(f"Chunk size: {chunk_size}") info = StreamInfo(device_spec.name, device_spec.content_type, device_spec.channel_count, device_spec.sample_rate, @@ -72,7 +79,7 @@ def __init__(self, device_spec: DeviceSpec, generator: Generator = None, include if channel.type: channel_node.append_child_value('type', channel.type) - self.outlet = StreamOutlet(info) + self.outlet = StreamOutlet(info, chunk_size=chunk_size) self.add_markers = add_markers if add_markers: @@ -82,7 +89,8 @@ def __init__(self, device_spec: DeviceSpec, generator: Generator = None, include # "gUSBamp_" + boost::lexical_cast(deviceNumber) + # "_" + boost::lexical_cast(serialNumber) + # "_markers"); - log.info(f"Creating marker stream {marker_stream_name}") + log.debug("Creating marker stream") + print(f"Marker channel name: {marker_stream_name}") markers_info = StreamInfo(marker_stream_name, "Markers", 1, 0, 'string', "uid12345_markers") @@ -92,7 +100,7 @@ def __init__(self, device_spec: DeviceSpec, generator: Generator = None, include def stop(self): """Stop the thread and cleanup resources.""" - log.info("[*] Stopping data server") + log.debug("[*] Stopping data server") super(LslDataServer, self).stop() # Allows pylsl to cleanup; The outlet will no longer be discoverable @@ -128,7 +136,7 @@ def run(self): # deleted in another thread. break - log.info("[*] No longer pushing data") + log.debug("[*] No longer pushing data") def _settings(filename): @@ -165,7 +173,6 @@ def await_start(dataserver: LslDataServer, max_wait: float = 2): def main(): """Initialize and start the server.""" - import time import argparse from bcipy.acquisition.datastream.generator import file_data_generator @@ -177,6 +184,7 @@ def main(): "if missing, random data will be served.") parser.add_argument('-m', '--markers', action="store_true", default=False) parser.add_argument('-n', '--name', default='DSI-24', help='Name of the device spec to mock.') + parser.add_argument('-c', '--chunk_size', default=0, type=int, help='Chunk size') args = parser.parse_args() if args.filename: @@ -191,11 +199,14 @@ def main(): markers = True if args.markers else False try: - server = LslDataServer(device_spec=device_spec, generator=generator, add_markers=markers) + server = LslDataServer(device_spec=device_spec, + generator=generator, + add_markers=markers, + chunk_size=args.chunk_size) - log.info("New server created") + log.debug("New server created") server.start() - log.info("Server started") + log.debug("Server started") while True: time.sleep(1) except KeyboardInterrupt: diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 1a5afa53f..3309e184a 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -74,7 +74,9 @@ def start_acquisition(self) -> bool: f'LSL Stream not found for content type {content_type}') stream_info = streams[0] - self.inlet = StreamInlet(stream_info, max_buflen=self.max_buffer_len) + self.inlet = StreamInlet(stream_info, + max_buflen=self.max_buffer_len, + max_chunklen=1) if self.device_spec: check_device(self.device_spec, self.inlet.info()) @@ -98,6 +100,7 @@ def first_sample_time(self) -> float: """Timestamp returned by the first sample. If the data is being recorded this value reflects the timestamp of the first recorded sample""" if self.recorder: + # TODO: wait until there is a value return self.recorder.first_sample_time return self._first_sample_time diff --git a/bcipy/acquisition/protocols/lsl/lsl_recorder.py b/bcipy/acquisition/protocols/lsl/lsl_recorder.py index e6b504ef1..13d7be9c2 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_recorder.py +++ b/bcipy/acquisition/protocols/lsl/lsl_recorder.py @@ -193,7 +193,7 @@ def run(self): until the `stop()` method is called. """ # Note that self.stream_info does not have the channel names. - inlet = StreamInlet(self.stream_info) + inlet = StreamInlet(self.stream_info, max_chunklen=1) full_metadata = inlet.info() log.info("Acquiring data from data stream:") From ade6a6128a1ce5bd9949d26291080b57893da7a4 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 31 Aug 2023 16:56:50 -0700 Subject: [PATCH 074/330] Updated changelog --- CHANGELOG.md | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 5fcf485bf..e1eaf4807 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -28,6 +28,7 @@ Our last release candidate before the official 2.0 release! - Set channel spec information in devices.json. Removed aliases. #266 Updated default analysis channels for Wearable Sensing devices #279 - Refactor to allow multiple devices to be configured for multimodal acquisition. #277 - Refinements to LSL server to use the device ChannelSpec information for generating metadata. #282 + - Updated data consumers to explicitly set a chunk size. Refinements to LSL server to simulate different chunk sizes. #292 - Matrix - Matrix calibration refinements #262 - Matrix Copy Phrase Task #261 From 0e66a483c4cdc99729fe687ce1bd210207f3a8a9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 1 Sep 2023 09:24:21 -0700 Subject: [PATCH 075/330] Removed TODO --- bcipy/acquisition/protocols/lsl/lsl_client.py | 1 - 1 file changed, 1 deletion(-) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 3309e184a..3fb8f3f8c 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -100,7 +100,6 @@ def first_sample_time(self) -> float: """Timestamp returned by the first sample. If the data is being recorded this value reflects the timestamp of the first recorded sample""" if self.recorder: - # TODO: wait until there is a value return self.recorder.first_sample_time return self._first_sample_time From ae84f1f5e4c068f57b6c89976d954c1f4c27d888 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 4 Sep 2023 17:14:54 -0400 Subject: [PATCH 076/330] Trigger offset update. New models WIP --- bcipy/helpers/triggers.py | 12 +++++++++--- bcipy/signal/model/fusion_model.py | 20 +++++++++++++++++--- bcipy/signal/model/offline_analysis.py | 14 ++++---------- 3 files changed, 30 insertions(+), 16 deletions(-) diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 42dc65595..f668aa2ec 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -286,6 +286,7 @@ def read_text_file(path: str) -> Tuple[List[Trigger], float]: @staticmethod def load(path: str, offset: Optional[float] = 0.0, + apply_system_offset: bool = True, exclusion: Optional[List[TriggerType]] = None) -> List[Trigger]: """ Loads a list of triggers from a .txt of triggers. @@ -316,7 +317,12 @@ def load(path: str, # Checking for file with given path, with or without .txt triggers, system_offset = TriggerHandler.read_text_file(path) excluded_types = exclusion or [] - total_offset = offset + system_offset + + if apply_system_offset: + total_offset = offset + system_offset + else: + total_offset = offset + return [ trg.with_offset(total_offset) for trg in triggers if trg.type not in excluded_types @@ -354,7 +360,7 @@ def convert_timing_triggers(timing: List[tuple], target_stimuli: str, trigger_ty def trigger_decoder(trigger_path: str, remove_pre_fixation: bool = True, offset: float = 0.0, - exclusion: List[TriggerType] = []) -> Tuple[list, list, list]: + exclusion: List[TriggerType] = [], apply_system_offset: bool = True) -> Tuple[list, list, list]: """Trigger Decoder. Given a path to trigger data, this method loads valid Triggers and returns their type, timing and label. @@ -372,7 +378,7 @@ def trigger_decoder(trigger_path: str, remove_pre_fixation: bool = True, offset: exclusion += [TriggerType.FIXATION, TriggerType.PROMPT, TriggerType.SYSTEM, TriggerType.OFFSET] else: exclusion += [TriggerType.SYSTEM] - triggers = TriggerHandler.load(trigger_path, offset=offset, exclusion=exclusion) + triggers = TriggerHandler.load(trigger_path, offset=offset, exclusion=exclusion, apply_system_offset=apply_system_offset) # from the stimuli array, pull out the symbol information trigger_type = [trigger.type.value for trigger in triggers] diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py index 55e9bd201..d74610d8f 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/fusion_model.py @@ -21,12 +21,26 @@ def fit(self, train_data: np.array): return self - def predict(self, test_data: np.array): - predictions = self.model.predict_proba(test_data) + def get_scores(self, test_data: np.array): + ''' + Compute the log-likelihood of each sample. + Compute the mean and covariance of each mixture component. + ''' + + scores = self.model.score_samples(test_data) means = self.model.means_ covs = self.model.covariances_ - return predictions, means, covs + return scores, means, covs + + def predict(self, scores: np.array): + ''' + Predict the labels for the test data. + ''' + # Compute over log-likelihood scores + # Get the argmax of the scores + + #return predictions diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 78a2aa7b3..4580239b9 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -263,16 +263,10 @@ def offline_analysis( model = GazeModel() - # Add back the starting offset: - # This is handled in TriggerHandler. Remove automatic addition off system offset: - trigx, starting_offset = TriggerHandler.read_text_file(f"{data_folder}/{TRIGGER_FILENAME}") - # TODO: I access TriggerHandler directly to not cause an issue during EEG analysis. - # There's probably a smarter way to discard starting_offset - # Process triggers.txt files (again!) trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( remove_pre_fixation = False, - offset = starting_offset*-1, # cancel out the starting_offset + apply_system_offset=False, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.SYSTEM, TriggerType.OFFSET] ) @@ -318,15 +312,15 @@ def offline_analysis( # Fit the model: model.fit(train_right_eye) - predictions, means, covs = model.predict(test_right_eye) - # print(predictions) + scores, means, covs = model.get_scores(test_right_eye) + # print(scores) # Visualize the results: figure_handles = visualize_gaze_inquiries( left_eye, right_eye, means, covs, save_path=None, - show=False, + show=True, raw_plot=True, ) From 1e3c3e6416d6e542afc270e00bcbf193e5d8fa7e Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Thu, 7 Sep 2023 13:06:33 -0400 Subject: [PATCH 077/330] replay session refactored.1 + LM evidence --- bcipy/parameters/parameters.json | 4 +- requirements.txt | 6 +- scripts/python/replay_session.py | 195 +++++++++++++++++-------------- 3 files changed, 113 insertions(+), 92 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 2dc7822ac..2a746638e 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -1,6 +1,6 @@ { "fake_data": { - "value": "false", + "value": "true", "section": "bci_config", "readableName": "Fake EEG Data On/Off", "helpTip": "If ‘true’, fake EEG data will be used instead of real EEG data. Useful for testing by software development team.", @@ -622,7 +622,7 @@ "type": "int" }, "lang_model_type": { - "value": "UNIFORM", + "value": "KENLM", "section": "lang_model_config", "readableName": "Language Model Type", "helpTip": "Specifies which language model to use. Default: MIXTURE", diff --git a/requirements.txt b/requirements.txt index 6502c030b..f1d50ffd8 100644 --- a/requirements.txt +++ b/requirements.txt @@ -15,12 +15,12 @@ scipy==1.10.1 scikit-learn==1.2.2 seaborn==0.9.0 matplotlib==3.4.2 -pylsl==1.14.0 +pylsl==1.15.0 pandas==1.5.3 psutil==5.7.2 Pillow==9.0.1 py-cpuinfo==7.0.0 -pyedflib==0.1.30 -PyQt5==5.15.1 +pyedflib +pyqt5 pywavelets==1.4.1 tqdm==4.62.2 \ No newline at end of file diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 91d24026a..7bc188191 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -17,31 +17,27 @@ ) from bcipy.helpers.acquisition import analysis_channels import bcipy.acquisition.devices as devices +from bcipy.helpers.language_model import init_language_model from bcipy.helpers.list import grouper from bcipy.helpers.load import load_json_parameters, load_raw_data +from bcipy.helpers.session import session_data, read_session, evidence_records from bcipy.helpers.stimuli import InquiryReshaper, update_inquiry_timing from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.symbols import alphabet +from bcipy.language.model import kenlm from bcipy.signal.model import PcaRdaKdeModel from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams logger.getLogger().setLevel(logger.INFO) -def load_model(model_path: Path, k_folds: int, model_class=PcaRdaKdeModel): - """Load the model at the given path""" - with open(model_path, "rb") as f: - model = pickle.load(f) - return model - - def generate_replay_outputs( data_folder, parameters, model_path: Path, model_class=PcaRdaKdeModel, symbol_set=alphabet(), - write_output=False) -> Tuple[dict, list, list]: + write_output=False) -> Tuple[dict, list, list, list]: """Replay a session and generate outputs for the provided model. Parameters @@ -63,8 +59,12 @@ def generate_replay_outputs( ------- tuple - new_model_outputs, old_model_target_output, old_model_nontarget_output """ - k_folds = parameters.get("k_folds") - model = load_model(model_path, k_folds, model_class) + # k_folds = + # model = load_model(model_path, k_folds, model_class) + + base_model = PcaRdaKdeModel(parameters.get("k_folds")) + model = base_model.load(model_path) + logger.info(f"Loaded model from {model_path}") # get trial information; to make backwards compatible, we will try to get the trial length @@ -83,7 +83,6 @@ def generate_replay_outputs( # get signal filtering information static_offset = parameters.get("static_trigger_offset") - k_folds = parameters.get("k_folds") transform_params = parameters.instantiate(ERPTransformParams) downsample_rate = transform_params.down_sampling_rate @@ -153,7 +152,7 @@ def generate_replay_outputs( inquiry_worth_of_trials = np.split(trials, inquiries.shape[1], 1) inquiry_worth_of_letters = grouper(trigger_symbols, trials_per_inquiry, incomplete="ignore") for i, (inquiry_trials, this_inquiry_letters, this_inquiry_labels) in enumerate( - zip(inquiry_worth_of_trials, inquiry_worth_of_letters, inquiry_labels) + zip(inquiry_worth_of_trials, inquiry_worth_of_letters, inquiry_labels) ): response = model.predict(inquiry_trials, this_inquiry_letters, symbol_set=symbol_set) if np.any(this_inquiry_labels == 1): @@ -176,53 +175,82 @@ def generate_replay_outputs( with open(data_folder / "replay_outputs.json", "w") as f: json.dump(outputs, f, indent=2) - # Get values computed during actual experiment from session.json for comparison - session_json = data_folder / SESSION_DATA_FILENAME - all_target_eeg, all_nontarget_eeg = load_eeg_evidence_from_session_json(session_json, symbol_set) - - return outputs, all_target_eeg, all_nontarget_eeg - + # Get target and nontarget eeg values from actual experiment in session.json for comparison + session_records = evidence_records(read_session(data_folder / SESSION_DATA_FILENAME)) + all_target_eeg = [record.eeg for record in session_records if record.is_target == 1] + all_nontarget_eeg = [record.eeg for record in session_records if record.is_target == 0] -def load_eeg_evidence_from_session_json(session_json, symbol_set) -> Tuple[list, list]: - """Load EEG evidence from session.json file for comparison with replay outputs. + # loading lm values from experiment and comparing with diff lm models + # lm_evidences = load_lm_evidence_from_session_json(session_json, parameters) + # print(f"f len of lm_evidences {len(lm_evidences)}, should be equal to number of series") - Parameters - ---------- - session_json : str - Path to session.json file - symbol_set : list - List of symbols used in experiment + return outputs, all_target_eeg, all_nontarget_eeg, None - Returns - ------- - all_target_eeg : list - List of EEG evidence for target stimuli - all_nontarget_eeg : list - List of EEG evidence for nontarget stimuli - """ +def load_lm_evidence_from_session_json(session_json, parameters, symbol_set=alphabet()): with open(session_json, "r") as f: contents = json.load(f) series = contents["series"] - all_target_eeg = [] - all_nontarget_eeg = [] + lm_evidences = [] + lm_model = init_language_model(parameters) + + for i, inquiries in enumerate(series.values()): + init_inquiry = inquiries["0"] - for inquiries in series.values(): - for inquiry in inquiries.values(): - if len(inquiry["eeg_evidence"]) < 1: - continue - else: - stim_label = inquiry["stimuli"][0] # name of symbols presented - stim_label.pop(0) # remove fixation cross - stim_indices = [symbol_set.index(sym) for sym in stim_label] - targetness = inquiry["target_info"] # targetness of stimuli - targetness.pop(0) # remove fixation cross - target = [index for index, label in zip(stim_indices, targetness) if label == "target"] - nontarget = [index for index, label in zip(stim_indices, targetness) if label == "nontarget"] - all_target_eeg.extend([inquiry["eeg_evidence"][pos] for pos in target]) - all_nontarget_eeg.extend([inquiry["eeg_evidence"][pos] for pos in nontarget]) + # calculating new prediction for current_text + old_lm_evidence = init_inquiry.get('lm_evidence') + curr_pred = lm_model.predict(list(init_inquiry['current_text'])) - return all_target_eeg, all_nontarget_eeg + # unsorting the predictions to fit session json format + temp_dic = dict(curr_pred) + curr_pred_formatted = [temp_dic[char] for char in symbol_set] + + lm_evidence = {"old_lm_evidence": old_lm_evidence, "new_lm_evidence": curr_pred_formatted, + "target_letter": init_inquiry['target_letter'], "current_text": init_inquiry['current_text']} + + lm_evidences.append(lm_evidence) + print(f"top prediction for series {i} - {init_inquiry['current_text']} - ", curr_pred[0]) + + return lm_evidences + + +def plot_comparison_records(records, outdir, title="response_values", y_scale="log"): + df = pd.DataFrame.from_records(records) + logger.info(f"{df.describe()}") + ax = sns.stripplot( + x="which_model", + y="response_value", + data=df, + order=["old_target", "new_target", "old_nontarget", "new_nontarget"], + ) + sns.boxplot( + showmeans=True, + meanline=True, + meanprops={"color": "k", "ls": "-", "lw": 2}, + medianprops={"visible": False}, + whiskerprops={"visible": False}, + zorder=10, + x="which_model", + y="response_value", + data=df, + showfliers=False, + showbox=False, + showcaps=False, + ax=ax, + order=["old_target", "new_target", "old_nontarget", "new_nontarget"], + ) + + ax.set(yscale=y_scale) + plt.savefig(outdir / f"{title}.stripplot.png", dpi=150, bbox_inches="tight") + plt.close() + ax = sns.boxplot( + x="which_model", + y="response_value", + data=df, + order=["old_target", "new_target", "old_nontarget", "new_nontarget"], + ) + ax.set(yscale=y_scale) + plt.savefig(outdir / f"{title}.boxplot.png", dpi=150, bbox_inches="tight") def plot_collected_outputs( @@ -264,42 +292,33 @@ def plot_collected_outputs( for nontarget_response in nontargets_with_old_model: records.append({"which_model": "old_nontarget", "response_value": nontarget_response}) - df = pd.DataFrame.from_records(records) - logger.info(f"{df.describe()}") - ax = sns.stripplot( - x="which_model", - y="response_value", - data=df, - order=["old_target", "new_target", "old_nontarget", "new_nontarget"], - ) - sns.boxplot( - showmeans=True, - meanline=True, - meanprops={"color": "k", "ls": "-", "lw": 2}, - medianprops={"visible": False}, - whiskerprops={"visible": False}, - zorder=10, - x="which_model", - y="response_value", - data=df, - showfliers=False, - showbox=False, - showcaps=False, - ax=ax, - order=["old_target", "new_target", "old_nontarget", "new_nontarget"], - ) + plot_comparison_records(records, outdir, y_scale="log") - ax.set(yscale="log") - plt.savefig(outdir / "response_values.stripplot.png", dpi=150, bbox_inches="tight") - plt.close() - ax = sns.boxplot( - x="which_model", - y="response_value", - data=df, - order=["old_target", "new_target", "old_nontarget", "new_nontarget"], - ) - ax.set(yscale="log") - plt.savefig(outdir / "response_values.boxplot.png", dpi=150, bbox_inches="tight") +def plot_lm_outputs(lm_evidences, outdir, symbol_set=alphabet()): + def format_records(values, which_model): + return [{"which_model": which_model, "response_value": val} for val in values] + + records = [] + for lm_series_content in lm_evidences: # each session + target_evidence_idx = symbol_set.index(lm_series_content['target_letter']) + old_vals, new_vals = lm_series_content['old_lm_evidence'], lm_series_content['new_lm_evidence'] + + old_target_val = old_vals[target_evidence_idx] + new_target_val = new_vals[target_evidence_idx] + + old_non_target_vals = np.delete(old_vals, target_evidence_idx) + new_non_target_vals = np.delete(new_vals, target_evidence_idx) + + records.extend(format_records([old_target_val], "old_target")) + records.extend(format_records([new_target_val], "new_target")) + records.extend(format_records(old_non_target_vals, "old_nontarget")) + records.extend(format_records(new_non_target_vals, "new_nontarget")) + + df = pd.DataFrame(records) + + df.to_csv('records.csv', index=False) + + plot_comparison_records(records, outdir, title="LM_responses", y_scale="linear") if __name__ == "__main__": @@ -344,8 +363,10 @@ def plot_collected_outputs( logger.info(f"Loading params from {params_file}") params = load_json_parameters(params_file, value_cast=True) + # breakpoint() + # Generate replay outputs using the model provided against the session data in data_folder - outputs, all_target_eeg, all_nontarget_eeg = generate_replay_outputs( + outputs, all_target_eeg, all_nontarget_eeg, lm_evidences = generate_replay_outputs( data_folder, params, args.model_file, write_output=False ) outputs_with_new_model.append(outputs) @@ -358,6 +379,6 @@ def plot_collected_outputs( nontargets_with_old_model, args.outdir) - # breakpoint() + # plot_lm_outputs(lm_evidences, args.outdir) logger.info("Replay complete.") From f6f5bb059b6406e0736f2e56c8cd13bfb3963937 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Thu, 7 Sep 2023 13:09:53 -0400 Subject: [PATCH 078/330] replay session refactored.1 minus LM evidence support --- scripts/python/replay_session.py | 68 ++------------------------------ 1 file changed, 3 insertions(+), 65 deletions(-) diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 7bc188191..ab43a6c98 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -37,7 +37,7 @@ def generate_replay_outputs( model_path: Path, model_class=PcaRdaKdeModel, symbol_set=alphabet(), - write_output=False) -> Tuple[dict, list, list, list]: + write_output=False) -> Tuple[dict, list, list]: """Replay a session and generate outputs for the provided model. Parameters @@ -180,40 +180,7 @@ def generate_replay_outputs( all_target_eeg = [record.eeg for record in session_records if record.is_target == 1] all_nontarget_eeg = [record.eeg for record in session_records if record.is_target == 0] - # loading lm values from experiment and comparing with diff lm models - # lm_evidences = load_lm_evidence_from_session_json(session_json, parameters) - # print(f"f len of lm_evidences {len(lm_evidences)}, should be equal to number of series") - - return outputs, all_target_eeg, all_nontarget_eeg, None - -def load_lm_evidence_from_session_json(session_json, parameters, symbol_set=alphabet()): - with open(session_json, "r") as f: - contents = json.load(f) - series = contents["series"] - - lm_evidences = [] - lm_model = init_language_model(parameters) - - for i, inquiries in enumerate(series.values()): - init_inquiry = inquiries["0"] - - # calculating new prediction for current_text - old_lm_evidence = init_inquiry.get('lm_evidence') - curr_pred = lm_model.predict(list(init_inquiry['current_text'])) - - # unsorting the predictions to fit session json format - temp_dic = dict(curr_pred) - curr_pred_formatted = [temp_dic[char] for char in symbol_set] - - lm_evidence = {"old_lm_evidence": old_lm_evidence, "new_lm_evidence": curr_pred_formatted, - "target_letter": init_inquiry['target_letter'], "current_text": init_inquiry['current_text']} - - lm_evidences.append(lm_evidence) - print(f"top prediction for series {i} - {init_inquiry['current_text']} - ", curr_pred[0]) - - return lm_evidences - - + return outputs, all_target_eeg, all_nontarget_eeg def plot_comparison_records(records, outdir, title="response_values", y_scale="log"): df = pd.DataFrame.from_records(records) logger.info(f"{df.describe()}") @@ -294,33 +261,6 @@ def plot_collected_outputs( plot_comparison_records(records, outdir, y_scale="log") -def plot_lm_outputs(lm_evidences, outdir, symbol_set=alphabet()): - def format_records(values, which_model): - return [{"which_model": which_model, "response_value": val} for val in values] - - records = [] - for lm_series_content in lm_evidences: # each session - target_evidence_idx = symbol_set.index(lm_series_content['target_letter']) - old_vals, new_vals = lm_series_content['old_lm_evidence'], lm_series_content['new_lm_evidence'] - - old_target_val = old_vals[target_evidence_idx] - new_target_val = new_vals[target_evidence_idx] - - old_non_target_vals = np.delete(old_vals, target_evidence_idx) - new_non_target_vals = np.delete(new_vals, target_evidence_idx) - - records.extend(format_records([old_target_val], "old_target")) - records.extend(format_records([new_target_val], "new_target")) - records.extend(format_records(old_non_target_vals, "old_nontarget")) - records.extend(format_records(new_non_target_vals, "new_nontarget")) - - df = pd.DataFrame(records) - - df.to_csv('records.csv', index=False) - - plot_comparison_records(records, outdir, title="LM_responses", y_scale="linear") - - if __name__ == "__main__": import argparse @@ -366,7 +306,7 @@ def format_records(values, which_model): # breakpoint() # Generate replay outputs using the model provided against the session data in data_folder - outputs, all_target_eeg, all_nontarget_eeg, lm_evidences = generate_replay_outputs( + outputs, all_target_eeg, all_nontarget_eeg = generate_replay_outputs( data_folder, params, args.model_file, write_output=False ) outputs_with_new_model.append(outputs) @@ -379,6 +319,4 @@ def format_records(values, which_model): nontargets_with_old_model, args.outdir) - # plot_lm_outputs(lm_evidences, args.outdir) - logger.info("Replay complete.") From 6b73b1c49490e35bff6b7317cebbb1e4e55b8813 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 8 Sep 2023 17:49:49 -0700 Subject: [PATCH 079/330] #185905314 ; trigger decoder changes to allow getting corrected triggers relative to a given device --- bcipy/helpers/tests/test_convert.py | 36 ++--- bcipy/helpers/tests/test_triggers.py | 220 +++++++++++++++++++++++++-- bcipy/helpers/triggers.py | 175 +++++++++++++++++---- 3 files changed, 373 insertions(+), 58 deletions(-) diff --git a/bcipy/helpers/tests/test_convert.py b/bcipy/helpers/tests/test_convert.py index fdd14763c..fc31a184e 100644 --- a/bcipy/helpers/tests/test_convert.py +++ b/bcipy/helpers/tests/test_convert.py @@ -2,34 +2,26 @@ import os import shutil import tempfile -from typing import Tuple, Union import unittest import warnings - from pathlib import Path +from typing import Tuple, Union -from mockito import mock, when, unstub, verify, verifyNoMoreInteractions, any as any_value +from mne.io import read_raw_bdf, read_raw_edf +from mockito import any as any_value +from mockito import mock, unstub, verify, verifyNoMoreInteractions, when -from bcipy.config import DEFAULT_ENCODING, RAW_DATA_FILENAME, TRIGGER_FILENAME, DEFAULT_PARAMETER_FILENAME +from bcipy.config import (DEFAULT_ENCODING, DEFAULT_PARAMETER_FILENAME, + RAW_DATA_FILENAME, TRIGGER_FILENAME) from bcipy.helpers import convert -from bcipy.helpers.convert import ( - archive_list, - compress, - convert_to_bdf, - convert_to_edf, - convert_to_mne, - decompress, - pyedf_convert, - tobii_to_norm, - norm_to_tobii, -) +from bcipy.helpers.convert import (archive_list, compress, convert_to_bdf, + convert_to_edf, convert_to_mne, decompress, + norm_to_tobii, pyedf_convert, tobii_to_norm) from bcipy.helpers.parameters import Parameters -from bcipy.helpers.raw_data import sample_data, write, RawData +from bcipy.helpers.raw_data import RawData, sample_data, write from bcipy.helpers.triggers import MOCK_TRIGGER_DATA from bcipy.signal.generator.generator import gen_random_data -from mne.io import read_raw_edf, read_raw_bdf - def create_bcipy_session_artifacts( write_dir: str, @@ -137,8 +129,8 @@ def test_convert_to_edf_with_write_targetness(self): warnings.simplefilter('ignore') edf = read_raw_edf(path, preload=True) - self.assertIn('target', edf.annotations.description) - self.assertIn('nontarget', edf.annotations.description) + self.assertTrue('target' in edf.annotations.description) + self.assertTrue('nontarget' in edf.annotations.description) def test_convert_to_edf_without_write_targetness(self): """Test creating the EDF with labels as event annotations""" @@ -400,7 +392,7 @@ def test_pyedf_convert_with_pre_filter(self): def test_pyedf_convert_with_write_targetness(self): """Test the pyedf_convert function with targetness for event annotations""" data, channels, fs, events, annotation_channels, _ = pyedf_convert( - self.temp_dir, write_targetness=True) + self.temp_dir, write_targetness=True, remove_pre_fixation=True) self.assertTrue(len(data) > 0) self.assertTrue(len(channels) > 0) @@ -410,7 +402,7 @@ def test_pyedf_convert_with_write_targetness(self): self.assertEqual(annotation_channels, 1) for event in events: _, _, label = event - # in this casae label and targetness should not be the same + # in this case label and targetness should not be the same self.assertTrue(label in ['target', 'nontarget']) def test_pyedf_convert_without_write_targetness(self): diff --git a/bcipy/helpers/tests/test_triggers.py b/bcipy/helpers/tests/test_triggers.py index ff878780d..2f52e8239 100644 --- a/bcipy/helpers/tests/test_triggers.py +++ b/bcipy/helpers/tests/test_triggers.py @@ -1,18 +1,16 @@ import os import unittest -from unittest.mock import patch, mock_open +from unittest.mock import mock_open, patch -from mockito import any, mock, when, verify, unstub import psychopy +from mockito import any, mock, unstub, verify, when from bcipy.helpers.exceptions import BciPyCoreException -from bcipy.helpers.triggers import ( - _calibration_trigger, - FlushFrequency, - TriggerType, - Trigger, - TriggerHandler -) +from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, + TriggerType, _calibration_trigger, + apply_offsets, exclude_types, + find_starting_offset, read, read_data, + trigger_decoder) class TestCalibrationTrigger(unittest.TestCase): @@ -320,5 +318,209 @@ def test_read_data_unicode(self, path_exists_mock): self.assertEqual(offset, 3.47) +class TestTriggerFunctions(unittest.TestCase): + """Test module functions""" + + def test_read_data(self): + """Test reading data from a given source""" + trg_data = '''starting_offset offset 3.47 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30''' + triggers = read_data(trg_data.split('\n')) + self.assertEqual(len(triggers), 9) + self.assertEqual(triggers[1].label, 'J') + self.assertEqual(triggers[1].type, TriggerType.PROMPT) + self.assertEqual(triggers[1].time, 6.15) + + def test_read_data_exception(self): + """Invalid triggers should throw an exception""" + trg_data = '''starting_offset offset 3.47 + J prompt 6.15 + + fixation 8.11 + foobarbaz''' + with self.assertRaises(BciPyCoreException): + read_data(trg_data.split('\n')) + + @patch('bcipy.helpers.triggers.os.path.exists') + def test_read_from_file(self, path_exists_mock): + """Test reading triggers from a file""" + trg_data = '''starting_offset offset 3.47 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30''' + path_exists_mock.returnValue = True + with patch('builtins.open', mock_open(read_data=trg_data), create=True): + triggers = read('triggers.txt') + self.assertEqual(len(triggers), 9) + self.assertEqual(triggers[1].label, 'J') + self.assertEqual(triggers[1].type, TriggerType.PROMPT) + self.assertEqual(triggers[1].time, 6.15) + + def test_find_starting_offset_default(self): + """Test default behavior for find_starting_offset""" + triggers = read_data('''J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30'''.split('\n')) + offset = find_starting_offset(triggers) + self.assertEqual(offset.time, 0.0) + + def test_find_starting_offset_default_device(self): + """Test behavior for find_starting_offset when not given a device""" + triggers = read_data('''starting_offset offset 3.47 + starting_offset_EYETRACKER offset 4.47 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30'''.split('\n')) + offset = find_starting_offset(triggers) + self.assertEqual(offset.label, 'starting_offset') + self.assertEqual(offset.time, 3.47) + + def test_find_starting_offset_for_device(self): + """Test behavior for find_starting_offset given a device""" + triggers = read_data('''starting_offset offset 3.47 + starting_offset_EYETRACKER offset 4.47 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30'''.split('\n')) + offset = find_starting_offset(triggers, device_type='EYETRACKER') + self.assertEqual(offset.label, 'starting_offset_EYETRACKER') + self.assertEqual(offset.time, 4.47) + + def test_apply_offsets_without_static(self): + """Test application of offsets without a static offset""" + triggers = read_data('''starting_offset offset -3.47 + starting_offset_EYETRACKER offset -4.45 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18'''.split('\n')) + offset = Trigger('starting_offset_EYETRACKER', TriggerType.OFFSET, + -4.45) + corrected = apply_offsets(triggers, offset) + self.assertEqual(len(corrected), 5, + "offset triggers should be excluded from the result") + self.assertEqual(corrected[0].label, 'J') + self.assertAlmostEqual(corrected[0].time, 1.7) + self.assertEqual(corrected[-1].label, 'J') + self.assertAlmostEqual(corrected[-1].time, 4.73) + + def test_apply_offsets_with_static(self): + """Test application of offsets with a static offset""" + triggers = read_data('''starting_offset offset -3.47 + starting_offset_EYETRACKER offset -4.45 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18'''.split('\n')) + offset = Trigger('starting_offset_EYETRACKER', TriggerType.OFFSET, + -4.45) + corrected = apply_offsets(triggers, offset, static_offset=0.1) + self.assertEqual(len(corrected), 5, + "offset triggers should be excluded from the result") + self.assertEqual(corrected[0].label, 'J') + self.assertAlmostEqual(corrected[0].time, 1.8) + self.assertEqual(corrected[-1].label, 'J') + self.assertAlmostEqual(corrected[-1].time, 4.83) + + def test_exclude_types(self): + """Test exclude types""" + triggers = read_data('''starting_offset offset -3.47 + starting_offset_EYETRACKER offset -4.45 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18'''.split('\n')) + self.assertListEqual(triggers, exclude_types(triggers, [])) + + filtered = exclude_types( + triggers, + [TriggerType.OFFSET, TriggerType.PROMPT, TriggerType.FIXATION]) + self.assertTrue( + all(trg.type in [TriggerType.NONTARGET, TriggerType.TARGET] + for trg in filtered)) + + @patch('bcipy.helpers.triggers.os.path.exists') + def test_trigger_decoder_defaults(self, path_exists_mock): + """Test trigger decoder""" + trg_data = '''starting_offset offset -3.47 + starting_offset_EYETRACKER offset -4.45 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30''' + path_exists_mock.returnValue = True + with patch('builtins.open', mock_open(read_data=trg_data), + create=True): + types, times, labels = trigger_decoder('triggers.txt') + + self.assertListEqual(types, [ + 'nontarget', 'nontarget', 'target', 'nontarget', 'nontarget', + 'nontarget' + ]) + self.assertListEqual(labels, ['F', 'D', 'J', 'T', 'K', '_']) + self.assertAlmostEqual(times[0], 5.11) + self.assertAlmostEqual(times[-1], 7.83) + + @patch('bcipy.helpers.triggers.os.path.exists') + def test_trigger_decoder_with_device(self, path_exists_mock): + """Test trigger decoder""" + trg_data = '''starting_offset offset -3.47 + starting_offset_EYETRACKER offset -4.45 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30''' + path_exists_mock.returnValue = True + with patch('builtins.open', mock_open(read_data=trg_data), + create=True): + types, times, labels = trigger_decoder('triggers.txt', + device_type='EYETRACKER') + + self.assertListEqual(types, [ + 'nontarget', 'nontarget', 'target', 'nontarget', 'nontarget', + 'nontarget' + ]) + self.assertListEqual(labels, ['F', 'D', 'J', 'T', 'K', '_']) + self.assertAlmostEqual(times[0], 4.13) + self.assertAlmostEqual(times[-1], 6.85) + + if __name__ == '__main__': unittest.main() diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 42dc65595..698e92812 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -1,8 +1,7 @@ import logging import os -from dataclasses import dataclass from enum import Enum -from typing import Callable, Dict, List, Optional, Tuple +from typing import Callable, Dict, Iterable, List, NamedTuple, Optional, Tuple from psychopy import core, visual @@ -165,12 +164,20 @@ def list(cls) -> List[str]: """Returns all enum values as a list""" return list(map(lambda c: c.value, cls)) + @classmethod + def pre_fixation(cls) -> List: + """Returns the subset of TriggerTypes that occur before and including + the FIXATION trigger.""" + return [ + TriggerType.FIXATION, TriggerType.PROMPT, TriggerType.SYSTEM, + TriggerType.OFFSET + ] + def __str__(self) -> str: return f'{self.value}' -@dataclass(frozen=True) -class Trigger: +class Trigger(NamedTuple): """ Object that encompasses data for a single trigger instance. """ @@ -343,40 +350,154 @@ def add_triggers(self, triggers: List[Trigger]) -> List[Trigger]: return self.triggers -def convert_timing_triggers(timing: List[tuple], target_stimuli: str, trigger_type: Callable) -> List[Trigger]: +def read_data(lines: Iterable[str]) -> List[Trigger]: + """Read raw trigger data from the given source. + + Parameters + ---------- + data - iterable object where each item is a str with data for a single + trigger. + + Returns + ------- + list of all Triggers in the data. + """ + triggers = [] + for i, line in enumerate(lines): + try: + trg = Trigger.from_list(line.split()) + triggers.append(trg) + except (AssertionError, ValueError) as trg_error: + raise BciPyCoreException( + f'Error reading trigger from line {i+1}: {trg_error}' + ) from trg_error + return triggers + + +def find_starting_offset(triggers: List[Trigger], device_type: str = None) -> Trigger: + """Given a list of raw trigger data, determine the starting offset for the + given device. The returned trigger has the timestamp of the first sample + recorded for the device. + + If no device is provided the EEG offset will be used. If there are + no offset triggers in the given data a Trigger with offset of 0.0 will be + returned. + + Parameters + ---------- + triggers - list of trigger data; should include Triggers of + TriggerType.OFFSET + device_type - each device will generally have a different offset. This + parameter is used to determine which trigger to use. If not given + the EEG offset will be used by default. Ex. 'EYETRACKER' + Returns + ------- + The Trigger for the first matching offset for the given device, or a + Trigger with offset of 0.0 if a matching offset was not found. + """ + label = 'starting_offset' + if device_type and device_type != 'EEG': + label += f"_{device_type}" + for trg in triggers: + if trg.type == TriggerType.OFFSET and trg.label == label: + return trg + log.info(f"Offset not found (device_type: {device_type}); using 0.0") + return Trigger('starting_offset', TriggerType.OFFSET, 0.0) + + +def read(path: str) -> List[Trigger]: + """Read all Triggers from the given text file. + + Parameters + ---------- + path - trigger (.txt) file to read + Returns + ------- + triggers + """ + if not path.endswith('.txt') or not os.path.exists(path): + raise FileNotFoundError( + f'Valid triggers .txt file not found at [{path}].') + with open(path, encoding=DEFAULT_ENCODING) as raw_txt: + triggers = read_data(raw_txt) + return triggers + + +def apply_offsets(triggers: List[Trigger], + starting_offset: Trigger, + static_offset: float = 0.0) -> List[Trigger]: + """Returns a list of triggers with timestamps adjusted relative to the + device start time. Offset triggers are filtered out if present. + + Parameters + ---------- + triggers - list of triggers + starting_offset - offset from the device start time. + static_offset - the measured static system offset + + Returns + ------- + a list of triggers with timestamps relative to the starting_offset + """ + total_offset = starting_offset.time + static_offset + return [ + trg.with_offset(total_offset) for trg in triggers + if trg.type != TriggerType.OFFSET + ] + + +def exclude_types(triggers: List[Trigger], + types: List[TriggerType] = None) -> List[Trigger]: + """Filter the list of triggers to exclude the provided types""" + if not types: + return triggers + return [trg for trg in triggers if trg.type not in types] + + +def convert_timing_triggers(timing: List[tuple], target_stimuli: str, + trigger_type: Callable) -> List[Trigger]: """Convert Stimuli Times to Triggers. Using the stimuli presentation times provided by the display, convert them into BciPy Triggers. """ return [ - Trigger(symbol, trigger_type(symbol, target_stimuli, i), time) for i, (symbol, time) in enumerate(timing) + Trigger(symbol, trigger_type(symbol, target_stimuli, i), time) + for i, (symbol, time) in enumerate(timing) ] -def trigger_decoder(trigger_path: str, remove_pre_fixation: bool = True, offset: float = 0.0, - exclusion: List[TriggerType] = []) -> Tuple[list, list, list]: +def trigger_decoder(trigger_path: str, + remove_pre_fixation: bool = True, + offset: float = 0.0, + exclusion: List[TriggerType] = None, + device_type: str = None) -> Tuple[list, list, list]: """Trigger Decoder. Given a path to trigger data, this method loads valid Triggers and returns their type, timing and label. - PARAMETERS + Parameters ---------- - :param: trigger_path: path to triggers file - :param: remove_pre_fixation: boolean to determine whether any stimuli before a fixation + system should be removed - :param: offset: additional offset value to apply to triggers. If a valid 'starting_offset' present in the trigger - file this will be applied be default. - :param: exclusion [Optional]: any TriggerTypes to be filtered from data returned - :return: tuple: trigger_type, trigger_timing, trigger_label + trigger_path: path to triggers file + remove_pre_fixation: boolean to determine whether any stimuli before a fixation + system should be removed + offset: static offset value to apply to triggers. + exclusion: any TriggerTypes to be filtered from data returned + device_type: used to determine which starting_offset value to use; if + a 'starting_offset' trigger is found it will be applied. + + Returns + ------- + tuple: trigger_type, trigger_timing, trigger_label """ - if remove_pre_fixation: - exclusion += [TriggerType.FIXATION, TriggerType.PROMPT, TriggerType.SYSTEM, TriggerType.OFFSET] - else: - exclusion += [TriggerType.SYSTEM] - triggers = TriggerHandler.load(trigger_path, offset=offset, exclusion=exclusion) - - # from the stimuli array, pull out the symbol information - trigger_type = [trigger.type.value for trigger in triggers] - trigger_label = [trigger.label for trigger in triggers] - trigger_timing = [trigger.time for trigger in triggers] - - return trigger_type, trigger_timing, trigger_label + excluded_types = exclusion or [] + excluded_types += TriggerType.pre_fixation() if remove_pre_fixation else [ + TriggerType.SYSTEM + ] + + triggers = read(trigger_path) + starting_offset = find_starting_offset(triggers, device_type) + + filtered = exclude_types(triggers, excluded_types) + corrected = apply_offsets(filtered, starting_offset, static_offset=offset) + + labels, types, times = zip(*corrected) + return list(map(str, types)), list(times), list(labels) From 538ba58fb58d638fef1b2bbb311c59366ad4a509 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 11 Sep 2023 11:40:50 -0700 Subject: [PATCH 080/330] Refactored TriggerHandler static methods to use new helper functions --- bcipy/helpers/tests/test_triggers.py | 50 ++++-- bcipy/helpers/triggers.py | 248 +++++++++++++-------------- 2 files changed, 147 insertions(+), 151 deletions(-) diff --git a/bcipy/helpers/tests/test_triggers.py b/bcipy/helpers/tests/test_triggers.py index 2f52e8239..ecd02c298 100644 --- a/bcipy/helpers/tests/test_triggers.py +++ b/bcipy/helpers/tests/test_triggers.py @@ -203,29 +203,41 @@ def test_add_triggers_calls_write_when_flush_every(self): verify(self.handler, times=1).write() - def test_load_returns_list_of_triggers(self): - trg = Trigger('A', TriggerType.NONTARGET, 1) - when(TriggerHandler).read_text_file(any()).thenReturn(([trg], 0.0)) - - response = self.handler.load('test_path_not_real') - self.assertEqual(response[0], trg) + @patch('bcipy.helpers.triggers.os.path.exists') + def test_load_returns_list_of_triggers(self, path_exists_mock): + """Test static load method""" + path_exists_mock.returnValue = True + trg_data = '''A nontarget 1.0''' - def test_load_applies_offset(self): - trg = Trigger('A', TriggerType.NONTARGET, 1) + trg = Trigger('A', TriggerType.NONTARGET, 1.0) + with patch('builtins.open', mock_open(read_data=trg_data), + create=True): + response = self.handler.load('test_path_not_real.txt') + self.assertEqual(response[0], trg) - when(TriggerHandler).read_text_file(any()).thenReturn(([trg], 0.0)) - response = self.handler.load('test_path_not_real', offset=1) - self.assertEqual(response[0].time, 2) + @patch('bcipy.helpers.triggers.os.path.exists') + def test_load_applies_offset(self, path_exists_mock): + """Test that static load method applies offsets""" + path_exists_mock.returnValue = True + trg_data = '''starting_offset offset 0.5 + A nontarget 1.0''' + with patch('builtins.open', mock_open(read_data=trg_data), + create=True): + response = self.handler.load('test_path_not_real.txt', offset=1) + self.assertEqual(response[0].time, 2.5) - def test_load_exclusion(self): + @patch('bcipy.helpers.triggers.os.path.exists') + def test_load_exclusion(self, path_exists_mock): + """Test that static load can exclude trigger types""" + path_exists_mock.returnValue = True + trg_data = '''A nontarget 1 + + fixation 2''' fixation_trg = Trigger('+', TriggerType.FIXATION, 2) - trg_list = [Trigger('A', TriggerType.NONTARGET, 1), fixation_trg] - - when(TriggerHandler).read_text_file(any()).thenReturn((trg_list, 0.0)) - - response = self.handler.load('test_path_not_real', - exclusion=[TriggerType.NONTARGET]) - self.assertEqual(response[0], fixation_trg) + with patch('builtins.open', mock_open(read_data=trg_data), + create=True): + response = self.handler.load('test_path_not_real.txt', + exclusion=[TriggerType.NONTARGET]) + self.assertEqual(response[0], fixation_trg) @patch('bcipy.helpers.triggers.os.path.exists') def test_read_data(self, path_exists_mock): diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 698e92812..97f7bf1a8 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -214,6 +214,110 @@ class FlushFrequency(Enum): END = "flush at end of session" +def read_data(lines: Iterable[str]) -> List[Trigger]: + """Read raw trigger data from the given source. + + Parameters + ---------- + data - iterable object where each item is a str with data for a single + trigger. + + Returns + ------- + list of all Triggers in the data. + """ + triggers = [] + for i, line in enumerate(lines): + try: + trg = Trigger.from_list(line.split()) + triggers.append(trg) + except (AssertionError, ValueError) as trg_error: + raise BciPyCoreException( + f'Error reading trigger from line {i+1}: {trg_error}' + ) from trg_error + return triggers + + +def find_starting_offset(triggers: List[Trigger], device_type: str = None) -> Trigger: + """Given a list of raw trigger data, determine the starting offset for the + given device. The returned trigger has the timestamp of the first sample + recorded for the device. + + If no device is provided the EEG offset will be used. If there are + no offset triggers in the given data a Trigger with offset of 0.0 will be + returned. + + Parameters + ---------- + triggers - list of trigger data; should include Triggers of + TriggerType.OFFSET + device_type - each device will generally have a different offset. This + parameter is used to determine which trigger to use. If not given + the EEG offset will be used by default. Ex. 'EYETRACKER' + Returns + ------- + The Trigger for the first matching offset for the given device, or a + Trigger with offset of 0.0 if a matching offset was not found. + """ + label = 'starting_offset' + if device_type and device_type != 'EEG': + label += f"_{device_type}" + for trg in triggers: + if trg.type == TriggerType.OFFSET and trg.label == label: + return trg + log.info(f"Offset not found (device_type: {device_type}); using 0.0") + return Trigger('starting_offset', TriggerType.OFFSET, 0.0) + + +def read(path: str) -> List[Trigger]: + """Read all Triggers from the given text file. + + Parameters + ---------- + path - trigger (.txt) file to read + Returns + ------- + triggers + """ + if not path.endswith('.txt') or not os.path.exists(path): + raise FileNotFoundError( + f'Valid triggers .txt file not found at [{path}].') + with open(path, encoding=DEFAULT_ENCODING) as raw_txt: + triggers = read_data(raw_txt) + return triggers + + +def apply_offsets(triggers: List[Trigger], + starting_offset: Trigger, + static_offset: float = 0.0) -> List[Trigger]: + """Returns a list of triggers with timestamps adjusted relative to the + device start time. Offset triggers are filtered out if present. + + Parameters + ---------- + triggers - list of triggers + starting_offset - offset from the device start time. + static_offset - the measured static system offset + + Returns + ------- + a list of triggers with timestamps relative to the starting_offset + """ + total_offset = starting_offset.time + static_offset + return [ + trg.with_offset(total_offset) for trg in triggers + if trg.type != TriggerType.OFFSET + ] + + +def exclude_types(triggers: List[Trigger], + types: List[TriggerType] = None) -> List[Trigger]: + """Filter the list of triggers to exclude the provided types""" + if not types: + return triggers + return [trg for trg in triggers if trg.type not in types] + + class TriggerHandler: """ Class that contains methods to work with Triggers, including adding and @@ -269,31 +373,16 @@ def read_text_file(path: str) -> Tuple[List[Trigger], float]: ------- triggers, offset """ - if not path.endswith('.txt') or not os.path.exists(path): - raise FileNotFoundError(f'Valid triggers .txt file not found at [{path}].') - - with open(path, encoding=TriggerHandler.encoding) as raw_txt: - triggers = [] - for i, line in enumerate(raw_txt): - try: - trg = Trigger.from_list(line.split()) - triggers.append(trg) - except (AssertionError, ValueError) as trg_error: - raise BciPyCoreException( - f'Error reading trigger on line {i+1} of {path}: {trg_error}') from trg_error - - # find next offset values in list and return or create a trigger with offset of 0.0 - offset = next( - filter(lambda trg: trg.type == TriggerType.OFFSET, triggers), - Trigger('starting_offset', TriggerType.OFFSET, 0.0)) - triggers = [trg for trg in triggers if trg.type != TriggerType.SYSTEM] - + triggers = read(path) + offset = find_starting_offset(triggers) + triggers = exclude_types(triggers, [TriggerType.SYSTEM]) return triggers, offset.time @staticmethod def load(path: str, offset: Optional[float] = 0.0, - exclusion: Optional[List[TriggerType]] = None) -> List[Trigger]: + exclusion: Optional[List[TriggerType]] = None, + device_type: str = None) -> List[Trigger]: """ Loads a list of triggers from a .txt of triggers. @@ -314,20 +403,19 @@ def load(path: str, positive number for adding time, negative number for subtracting time. exclusion (Optional List[TriggerType]): if desired, list of TriggerType's to be removed from the loaded trigger list. + device_type : optional; if specified looks for the starting_offset for + a given device; default is to use the EEG offset. Returns ------- List of Triggers from loaded .txt file with desired modifications """ - - # Checking for file with given path, with or without .txt - triggers, system_offset = TriggerHandler.read_text_file(path) excluded_types = exclusion or [] - total_offset = offset + system_offset - return [ - trg.with_offset(total_offset) for trg in triggers - if trg.type not in excluded_types - ] + triggers = read(path) + starting_offset = find_starting_offset(triggers, device_type) + return apply_offsets(exclude_types(triggers, excluded_types), + starting_offset, + static_offset=offset) def add_triggers(self, triggers: List[Trigger]) -> List[Trigger]: """ @@ -350,110 +438,6 @@ def add_triggers(self, triggers: List[Trigger]) -> List[Trigger]: return self.triggers -def read_data(lines: Iterable[str]) -> List[Trigger]: - """Read raw trigger data from the given source. - - Parameters - ---------- - data - iterable object where each item is a str with data for a single - trigger. - - Returns - ------- - list of all Triggers in the data. - """ - triggers = [] - for i, line in enumerate(lines): - try: - trg = Trigger.from_list(line.split()) - triggers.append(trg) - except (AssertionError, ValueError) as trg_error: - raise BciPyCoreException( - f'Error reading trigger from line {i+1}: {trg_error}' - ) from trg_error - return triggers - - -def find_starting_offset(triggers: List[Trigger], device_type: str = None) -> Trigger: - """Given a list of raw trigger data, determine the starting offset for the - given device. The returned trigger has the timestamp of the first sample - recorded for the device. - - If no device is provided the EEG offset will be used. If there are - no offset triggers in the given data a Trigger with offset of 0.0 will be - returned. - - Parameters - ---------- - triggers - list of trigger data; should include Triggers of - TriggerType.OFFSET - device_type - each device will generally have a different offset. This - parameter is used to determine which trigger to use. If not given - the EEG offset will be used by default. Ex. 'EYETRACKER' - Returns - ------- - The Trigger for the first matching offset for the given device, or a - Trigger with offset of 0.0 if a matching offset was not found. - """ - label = 'starting_offset' - if device_type and device_type != 'EEG': - label += f"_{device_type}" - for trg in triggers: - if trg.type == TriggerType.OFFSET and trg.label == label: - return trg - log.info(f"Offset not found (device_type: {device_type}); using 0.0") - return Trigger('starting_offset', TriggerType.OFFSET, 0.0) - - -def read(path: str) -> List[Trigger]: - """Read all Triggers from the given text file. - - Parameters - ---------- - path - trigger (.txt) file to read - Returns - ------- - triggers - """ - if not path.endswith('.txt') or not os.path.exists(path): - raise FileNotFoundError( - f'Valid triggers .txt file not found at [{path}].') - with open(path, encoding=DEFAULT_ENCODING) as raw_txt: - triggers = read_data(raw_txt) - return triggers - - -def apply_offsets(triggers: List[Trigger], - starting_offset: Trigger, - static_offset: float = 0.0) -> List[Trigger]: - """Returns a list of triggers with timestamps adjusted relative to the - device start time. Offset triggers are filtered out if present. - - Parameters - ---------- - triggers - list of triggers - starting_offset - offset from the device start time. - static_offset - the measured static system offset - - Returns - ------- - a list of triggers with timestamps relative to the starting_offset - """ - total_offset = starting_offset.time + static_offset - return [ - trg.with_offset(total_offset) for trg in triggers - if trg.type != TriggerType.OFFSET - ] - - -def exclude_types(triggers: List[Trigger], - types: List[TriggerType] = None) -> List[Trigger]: - """Filter the list of triggers to exclude the provided types""" - if not types: - return triggers - return [trg for trg in triggers if trg.type not in types] - - def convert_timing_triggers(timing: List[tuple], target_stimuli: str, trigger_type: Callable) -> List[Trigger]: """Convert Stimuli Times to Triggers. From 22d73218ce486b0c4e36a10592264e2e99df833d Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 11 Sep 2023 11:46:43 -0700 Subject: [PATCH 081/330] Added changelog --- CHANGELOG.md | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index e1eaf4807..381298c39 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -6,6 +6,7 @@ Our last release candidate before the official 2.0 release! - Multimodal Acquisition and Querying - Support for multiple devices in online querying #286 + - Support for trigger handling relative to a given device #293 - Stimuli - Updates to ensure stimuli are presented at the same frequency #287 - Dynamic Selection Window From 23787c685cbebed963783c4eee7ab92312c1ca3a Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 12 Sep 2023 16:12:00 -0700 Subject: [PATCH 082/330] Trigger Cleanup ; added functions for offset labels in the triggers module that can be used consistently in tasks, as well as be used to find offsets by type in the resulting triggers.txt file --- bcipy/helpers/tests/test_triggers.py | 62 ++++++++++++++++- bcipy/helpers/triggers.py | 69 +++++++++++++++---- bcipy/signal/model/offline_analysis.py | 1 + .../paradigm/rsvp/calibration/calibration.py | 10 ++- bcipy/task/paradigm/rsvp/copy_phrase.py | 10 ++- 5 files changed, 126 insertions(+), 26 deletions(-) diff --git a/bcipy/helpers/tests/test_triggers.py b/bcipy/helpers/tests/test_triggers.py index ecd02c298..7138d32bf 100644 --- a/bcipy/helpers/tests/test_triggers.py +++ b/bcipy/helpers/tests/test_triggers.py @@ -9,7 +9,9 @@ from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, _calibration_trigger, apply_offsets, exclude_types, - find_starting_offset, read, read_data, + find_starting_offset, offset_device, + offset_label, read, read_data, + starting_offsets_by_device, trigger_decoder) @@ -333,6 +335,36 @@ def test_read_data_unicode(self, path_exists_mock): class TestTriggerFunctions(unittest.TestCase): """Test module functions""" + def test_starting_offset_label(self): + """Test functions for generating offset labels""" + self.assertEqual(offset_label(), 'starting_offset') + self.assertEqual(offset_label('EEG'), 'starting_offset') + self.assertEqual(offset_label('EYETRACKER'), + 'starting_offset_EYETRACKER') + + self.assertEqual(offset_label(prefix='daq_offset'), 'daq_offset') + self.assertEqual(offset_label(device_type='EEG', prefix='daq_offset'), + 'daq_offset') + self.assertEqual( + offset_label(device_type='EYETRACKER', prefix='daq_offset'), + 'daq_offset_EYETRACKER') + + def test_offset_device_type(self): + """Test functions for generating offset labels""" + self.assertEqual(offset_device('starting_offset'), 'EEG') + self.assertEqual(offset_device('starting_offset_EEG'), 'EEG') + self.assertEqual(offset_device('starting_offset_EYETRACKER'), + 'EYETRACKER') + self.assertEqual(offset_device('starting_offset_EYE_TRACKER'), + 'EYE_TRACKER') + + self.assertEqual( + offset_device('daq_offset_EYE_TRACKER', prefix='daq_offset'), + 'EYE_TRACKER') + + with self.assertRaises(AssertionError): + offset_device('offset', prefix='starting_offset') + def test_read_data(self): """Test reading data from a given source""" trg_data = '''starting_offset offset 3.47 @@ -424,6 +456,34 @@ def test_find_starting_offset_for_device(self): self.assertEqual(offset.label, 'starting_offset_EYETRACKER') self.assertEqual(offset.time, 4.47) + def test_starting_offsets_by_device(self): + """Test default behavior for starting_offsets_by_device""" + triggers = read_data('''starting_offset offset 3.47 + starting_offset_EYETRACKER offset 4.47 + J prompt 6.15 + + fixation 8.11'''.split('\n')) + offsets = starting_offsets_by_device(triggers) + self.assertEqual(len(offsets), 2) + self.assertEqual(offsets['EEG'].time, 3.47) + self.assertEqual(offsets['EYETRACKER'].time, 4.47) + + def test_starting_offsets_by_device_no_offset(self): + """Test default behavior for starting_offsets_by_device with no offsets + """ + triggers = read_data('''J prompt 6.15 + + fixation 8.11'''.split('\n')) + offsets = starting_offsets_by_device(triggers) + self.assertFalse(offsets) + + def test_starting_offsets_by_device_defaults(self): + """Test default values""" + triggers = read_data('''J prompt 6.15 + + fixation 8.11'''.split('\n')) + offsets = starting_offsets_by_device(triggers, device_types=['EEG', 'EYETRACKER']) + self.assertEqual(len(offsets), 2) + self.assertEqual(offsets['EEG'].time, 0.0) + self.assertEqual(offsets['EYETRACKER'].time, 0.0) + def test_apply_offsets_without_static(self): """Test application of offsets without a static offset""" triggers = read_data('''starting_offset offset -3.47 diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 97f7bf1a8..8613a8de8 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -165,7 +165,7 @@ def list(cls) -> List[str]: return list(map(lambda c: c.value, cls)) @classmethod - def pre_fixation(cls) -> List: + def pre_fixation(cls) -> List['TriggerType']: """Returns the subset of TriggerTypes that occur before and including the FIXATION trigger.""" return [ @@ -238,7 +238,51 @@ def read_data(lines: Iterable[str]) -> List[Trigger]: return triggers -def find_starting_offset(triggers: List[Trigger], device_type: str = None) -> Trigger: +def offset_label(device_type: Optional[str] = None, prefix: str = 'starting_offset') -> str: + """Compute the offset label for the given device. + """ + if not device_type or device_type == 'EEG': + return prefix + return f"{prefix}_{device_type}" + + +def offset_device(label: str, prefix: str = 'starting_offset') -> str: + """Given an label, determine the device type""" + assert label.startswith( + prefix), "Label must start with the given prefix" + try: + idx = label.index('_', len(prefix)) + return label[idx + 1:] + except ValueError: + return 'EEG' + + +def starting_offsets_by_device( + triggers: List[Trigger], + device_types: Optional[List[str]] = None) -> Dict[str, Trigger]: + """Returns a dict of starting_offset triggers keyed by device type. + + If device_types are provided, an entry is created for each one, using a + default offset of 0.0 if a match is not found. + """ + offset_triggers = {} + for trg in triggers: + if trg.type == TriggerType.OFFSET: + device_type = offset_device(trg.label) + offset_triggers[device_type] = trg + + if device_types: + data = {} + for device_type in device_types: + data[device_type] = offset_triggers.get( + device_type, + Trigger(offset_label(device_type), TriggerType.OFFSET, 0.0)) + return data + return offset_triggers + + +def find_starting_offset(triggers: List[Trigger], + device_type: Optional[str] = None) -> Trigger: """Given a list of raw trigger data, determine the starting offset for the given device. The returned trigger has the timestamp of the first sample recorded for the device. @@ -259,14 +303,12 @@ def find_starting_offset(triggers: List[Trigger], device_type: str = None) -> Tr The Trigger for the first matching offset for the given device, or a Trigger with offset of 0.0 if a matching offset was not found. """ - label = 'starting_offset' - if device_type and device_type != 'EEG': - label += f"_{device_type}" + label = offset_label(device_type) for trg in triggers: if trg.type == TriggerType.OFFSET and trg.label == label: return trg log.info(f"Offset not found (device_type: {device_type}); using 0.0") - return Trigger('starting_offset', TriggerType.OFFSET, 0.0) + return Trigger(label, TriggerType.OFFSET, 0.0) def read(path: str) -> List[Trigger]: @@ -311,7 +353,7 @@ def apply_offsets(triggers: List[Trigger], def exclude_types(triggers: List[Trigger], - types: List[TriggerType] = None) -> List[Trigger]: + types: Optional[List[TriggerType]] = None) -> List[Trigger]: """Filter the list of triggers to exclude the provided types""" if not types: return triggers @@ -382,7 +424,7 @@ def read_text_file(path: str) -> Tuple[List[Trigger], float]: def load(path: str, offset: Optional[float] = 0.0, exclusion: Optional[List[TriggerType]] = None, - device_type: str = None) -> List[Trigger]: + device_type: Optional[str] = None) -> List[Trigger]: """ Loads a list of triggers from a .txt of triggers. @@ -450,11 +492,12 @@ def convert_timing_triggers(timing: List[tuple], target_stimuli: str, ] -def trigger_decoder(trigger_path: str, - remove_pre_fixation: bool = True, - offset: float = 0.0, - exclusion: List[TriggerType] = None, - device_type: str = None) -> Tuple[list, list, list]: +def trigger_decoder( + trigger_path: str, + remove_pre_fixation: bool = True, + offset: float = 0.0, + exclusion: Optional[List[TriggerType]] = None, + device_type: Optional[str] = None) -> Tuple[list, list, list]: """Trigger Decoder. Given a path to trigger data, this method loads valid Triggers and returns their type, timing and label. diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 8c58017fe..262854189 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -155,6 +155,7 @@ def offline_analysis( offset=static_offset, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + device_type='EEG' ) # update the trigger timing list to account for the initial trial window diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 6aef7d1dd..23aa220b1 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -2,7 +2,6 @@ from psychopy import core -from bcipy.acquisition.multimodal import ContentType from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE from bcipy.display import (InformationProperties, PreviewInquiryProperties, StimuliProperties) @@ -15,7 +14,8 @@ from bcipy.helpers.task import (get_user_input, pause_calibration, trial_complete_message) from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, - TriggerType, convert_timing_triggers) + TriggerType, convert_timing_triggers, + offset_label) from bcipy.task import Task @@ -204,8 +204,7 @@ def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None if first_run: triggers = [] for content_type, client in self.daq.clients_by_type.items(): - suffix = '' if content_type == ContentType.EEG else '_' + content_type.name - label = f"starting_offset{suffix}" + label = offset_label(content_type.name) time = client.offset( self.rsvp.first_stim_time) - self.rsvp.first_stim_time triggers.append(Trigger(label, TriggerType.OFFSET, time)) @@ -221,8 +220,7 @@ def write_offset_trigger(self) -> None: # we write only the sample offset here. triggers = [] for content_type, client in self.daq.clients_by_type.items(): - suffix = '' if content_type == ContentType.EEG else '_' + content_type.name - label = f"daq_sample_offset{suffix}" + label = offset_label(content_type.name, prefix='daq_sample_offset') time = client.offset(self.rsvp.first_stim_time) triggers.append(Trigger(label, TriggerType.SYSTEM, time)) diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 8affe1fa4..4bb120d2a 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -3,7 +3,6 @@ from psychopy import core -from bcipy.acquisition.multimodal import ContentType from bcipy.config import (SESSION_DATA_FILENAME, SESSION_SUMMARY_FILENAME, TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE) from bcipy.display import (Display, InformationProperties, @@ -24,7 +23,8 @@ relative_triggers, target_info, trial_complete_message) from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, - TriggerType, convert_timing_triggers) + TriggerType, convert_timing_triggers, + offset_label) from bcipy.signal.model.inquiry_preview import compute_probs_after_preview from bcipy.task import Task from bcipy.task.control.evidence import (EvidenceEvaluator, @@ -723,8 +723,7 @@ def write_offset_trigger(self) -> None: # we write only the sample offset here. triggers = [] for content_type, client in self.daq.clients_by_type.items(): - suffix = '' if content_type == ContentType.EEG else '_' + content_type.name - label = f"daq_sample_offset{suffix}" + label = offset_label(content_type.name, prefix='daq_sample_offset') time = client.offset(self.rsvp.first_stim_time) triggers.append(Trigger(label, TriggerType.SYSTEM, time)) @@ -744,8 +743,7 @@ def write_trigger_data(self, stim_times: List[Tuple[str, float]], target_stimuli # offset will factor in true offset and time relative from beginning offset_triggers = [] for content_type, client in self.daq.clients_by_type.items(): - suffix = '' if content_type == ContentType.EEG else '_' + content_type.name - label = f"starting_offset{suffix}" + label = offset_label(content_type.name) time = client.offset( self.rsvp.first_stim_time) - self.rsvp.first_stim_time offset_triggers.append(Trigger(label, TriggerType.OFFSET, From f3292cc805e4d6ca40b3091cdb5f97f251d974db Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 12 Sep 2023 17:02:10 -0700 Subject: [PATCH 083/330] Updated README --- bcipy/helpers/README.md | 51 +++++++++++++++++++++++++++++++++++------ 1 file changed, 44 insertions(+), 7 deletions(-) diff --git a/bcipy/helpers/README.md b/bcipy/helpers/README.md index 89a6d5a24..1ab392cfd 100644 --- a/bcipy/helpers/README.md +++ b/bcipy/helpers/README.md @@ -20,7 +20,7 @@ Modules necessary for BciPy system operation. These range from system utilities - `system_utils`: utilities for extracting git version, system information and handling of logging - `task`: common task methods and utilities, including Trial and InquiryReshaper. - `triggers`: methods and data classes defining BciPy internal triggering -- `validate`: methods for validating experiments and fields +- `validate`: methods for validating experiments and fields - `visualization`: method for visualizing EEG data collected in BciPy. Used in offline_analysis.py. @@ -53,11 +53,11 @@ PREVIEW = "preview" ### TriggerHandler -You can use the BciPy TriggerHandler to read and write any Triggers! +You can use the BciPy TriggerHandler to read and write any Triggers! ### Writing -You will need three pieces of information to create a new handler for writing: +You will need three pieces of information to create a new handler for writing: 1. path where trigger data should be written 2. name of the trigger file without extension @@ -85,7 +85,7 @@ handler.close() # this will call write one final time on any triggers added sinc ### Loading -To load a BciPy triggers.txt file, the TriggerHandler load method can be used. Because it is a staticmethod, the class does not need to be initialized before the load method is used. +To load a BciPy triggers.txt file, the TriggerHandler load method can be used. Because it is a staticmethod, the class does not need to be initialized before the load method is used. ```python from bcipy.helpers.triggers import TriggerHandler @@ -93,7 +93,7 @@ from bcipy.helpers.triggers import TriggerHandler path_to_trigger_save_location = './triggers.txt' triggers = TriggerHandler.load(path_to_trigger_save_location) -# it will load in data like this: +# it will load in data like this: # [Trigger: label=[starting_offset] type=[offset] time=[-13149613.488788936], Trigger: label=[x] type=[prompt] time=[4.96745322458446]] ``` @@ -107,7 +107,7 @@ path_to_trigger_save_location = './triggers.txt' # exclude system triggers triggers = TriggerHandler.load(path_to_trigger_save_location, exclusion=[TriggerType.SYSTEM]) -# apply a 2 second offset to all timestamps loaded +# apply a 2 second offset to all timestamps loaded triggers = TriggerHandler.load(path_to_trigger_save_location, offset=2.0) ``` @@ -137,4 +137,41 @@ N target 3493.7257014 X prompt 3495.4642608 + fixation 3496.4697921 Z nontarget 3496.9749562 -``` \ No newline at end of file +``` + +### Multiple Devices + +When multiple devices are in use, each device should provide its own starting_offset trigger. The trigger time should be the timestamp associated with the first sample in the data for that device. + +```python +from bcipy.helpers.triggers import Trigger, TriggerType, offset_label + +# label can be any utf-8 compliant string +eeg_offset = Trigger(offset_label(device_type='EEG'), TriggerType.OFFSET, -3400.0) +eyetracker_offset = Trigger(offset_label(device_type='EYETRACKER'), TriggerType.OFFSET, -3450.0) +``` + +After adding other triggers, the resulting file will look something like: + +``` +starting_offset offset -3400.0 +starting_offset_EYETRACKER offset -3450.0 +N prompt 3490.3607581 ++ fixation 3491.3668763 +Y nontarget 3491.8722132 +... +``` + +Triggers can then be loaded with timestamps relative to a device's start. + +```python +from bcipy.helpers.triggers import trigger_decoder, TriggerType + +types, times, labels = trigger_decoder('triggers.txt', device_type='EEG') +# types == ['prompt', 'fixation', 'prompt'] +# times == [90.36075810000011, 91.36687630000006, 91.8722131999998] +# labels == ['N', '+', 'Y'] + +_, times, _ = trigger_decoder('triggers.txt', device_type='EYETRACKER') +# times == [40.36075810000011, 41.36687630000006, 41.872213199999806] +``` From c81b4e3109ce909a5defb35d4dca2093ff5924f8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 13 Sep 2023 14:44:34 -0700 Subject: [PATCH 084/330] Updated VEP display and calibration demo to work with the latest codebase --- .../display/demo/vep/demo_calibration_vep.py | 41 ++++++---- bcipy/display/paradigm/vep/display.py | 79 +++++++++++-------- 2 files changed, 68 insertions(+), 52 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index d2666ab38..6ed33cd64 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -1,8 +1,9 @@ from psychopy import core, visual +from bcipy.display import InformationProperties, VEPStimuliProperties +from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.helpers.clock import Clock -from bcipy.display import InformationProperties, TaskDisplayProperties, VEPStimuliProperties info = InformationProperties( info_color=['White'], @@ -11,19 +12,21 @@ info_font=['Consolas'], info_text=['VEP Display Demo'], ) -task_display = TaskDisplayProperties(colors=['White'], - font='Consolas', - height=.1, - text='1/4') task_text = ['1/4', '2/4', '3/4', '4/4'] task_color = [['white'], ['white'], ['white'], ['white']] num_boxes = 4 start_positions_for_boxes = [(-.3, -.3), (.3, -.3), (.3, .3), (-.3, .3)] -win = visual.Window(size=[700, 700], fullscr=False, screen=1, allowGUI=False, - allowStencil=False, monitor='testMonitor', color='black', - colorSpace='rgb', blendMode='avg', +win = visual.Window(size=[700, 700], + fullscr=False, + screen=1, + allowGUI=False, + allowStencil=False, + monitor='testMonitor', + color='black', + colorSpace='rgb', + blendMode='avg', waitBlanking=False, winType='pyglet') win.recordFrameIntervals = True @@ -31,31 +34,35 @@ print(f'Monitor refresh rate: {frameRate} Hz') -clock = core.Clock() experiment_clock = Clock() len_stimuli = 10 stimuli = VEPStimuliProperties( stim_color=[['white'] * num_boxes], stim_pos=start_positions_for_boxes, stim_height=0.1, - stim_font='Consolas', + stim_font='Arial', timing=(1, 0.5, 4), # prompt, fixation, stimuli stim_length=1, # how many times to stimuli ) -vep = VEPDisplay(win, experiment_clock, stimuli, task_display, info) +task_bar = CalibrationTaskBar(win, + inquiry_count=4, + current_index=0, + font='Arial') +vep = VEPDisplay(win, experiment_clock, stimuli, task_bar, info) timing = [] -t = 2 +wait_seconds = 2 # loop over the text and colors, present the stimuli and record the timing for (txt, color) in zip(task_text, task_color): - vep.update_task(txt, color[0]) - vep.schedule_to([['A', 'B'], ['Z'], ['P'], ['R', 'W']], [1, 0.5, 5], [['blue'], ['purple'], ['red'], ['white']]) + vep.update_task_bar(txt) + vep.schedule_to([['A', 'B'], ['Z'], ['P'], ['R', 'W']], [1, 0.5, 5], + [['blue'], ['purple'], ['red'], ['white']]) timing += vep.do_inquiry() # show the wait screen, this will only happen once - while t > 0: - t -= 1 - vep.wait_screen(f"Waiting for {t}s", color='white') + while wait_seconds > 0: + wait_seconds -= 1 + vep.wait_screen(f"Waiting for {wait_seconds}s", color='white') core.wait(1) print(timing) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 655489e42..4f8ab6340 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -1,18 +1,17 @@ import logging -from typing import List, Tuple, Optional -from bcipy.display import ( - BCIPY_LOGO_PATH, - Display, - InformationProperties, - VEPStimuliProperties, - TaskDisplayProperties, -) +from typing import List, Tuple + import numpy as np -from psychopy import visual, core +from psychopy import core, visual +from psychopy.visual.grating import GratingStim + +from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, + VEPStimuliProperties) +from bcipy.display.components.task_bar import TaskBar from bcipy.helpers.clock import Clock +from bcipy.helpers.stimuli import get_fixation, resize_image from bcipy.helpers.symbols import SPACE_CHAR from bcipy.helpers.triggers import TriggerCallback, _calibration_trigger -from bcipy.helpers.stimuli import resize_image, get_fixation def create_vep_codes(length=32, count=4) -> List[List[int]]: @@ -31,11 +30,11 @@ class VEPBox: """A class to represent a VEP box. Attributes: - flicker: A list of two visual.GratingStim objects, one for on and one for off. + flicker: A list of two GratingStim objects, one for on and one for off. code: A list of integers representing the VEP code for this box. """ - def __init__(self, flicker: List[Tuple[visual.GratingStim, visual.GratingStim]], code: List[int]) -> None: + def __init__(self, flicker: List[Tuple[GratingStim, GratingStim]], code: List[int]) -> None: self.flicker = flicker self.code = code @@ -49,13 +48,13 @@ def frame_off(self) -> None: class VEPDisplay(Display): - + """Display for VEP paradigm""" def __init__( self, window: visual.Window, experiment_clock: Clock, stimuli: VEPStimuliProperties, - task_display: TaskDisplayProperties, + task_bar: TaskBar, info: InformationProperties, trigger_type: str = 'text', space_char: str = SPACE_CHAR, @@ -104,8 +103,8 @@ def __init__( # Task parameters self.space_char = space_char - self.task_display = task_display - self.task = task_display.build_task(self.window) + + self.task_bar = task_bar # Information parameters self.info = info @@ -126,6 +125,7 @@ def __init__( self.animation_duration = 2 + def do_fixation(self) -> None: # draw fixation cross self.fixation.draw() @@ -234,17 +234,26 @@ def stimulate(self) -> List[float]: return self.trigger_callback.timing def draw_static(self) -> None: - """Draw static elements for the display.""" - self.task.draw() + """Draw static elements in a stimulus.""" + if self.task_bar: + self.task_bar.draw() + for info in self.info_text: info.draw() - def update_task(self, text: str, color: str, pos: Optional[Tuple] = None) -> None: - """Update the task display which is displayed using the draw_static function.""" - self.task.text = text - self.task.color = color - if pos: - self.task.pos = pos + def update_task_bar(self, text: str = ''): + """Update Task. + + Update any task related display items not related to the inquiry. Ex. stimuli count 1/200. + + PARAMETERS: + + text: text for task + color_list: list of the colors for each stimuli + pos: position of task + """ + if self.task_bar: + self.task_bar.update(text) def _build_inquiry_stimuli(self) -> None: """Build the inquiry stimuli.""" @@ -268,7 +277,7 @@ def _build_vep_corner_stimuli( pos: Tuple[float, float], codes: List[int], colors: List[Tuple[str]], - box_size: float) -> List[visual.GratingStim]: + box_size: float) -> List[GratingStim]: """Build the corner stimuli for the VEP. Args: @@ -285,7 +294,7 @@ def _build_1x1_vep_grid( position: Tuple[float], size: float, color: str, - code: List[int]) -> List[visual.GratingStim]: + code: List[int]) -> List[GratingStim]: """Build a 1x1 VEP grid. Args: @@ -295,16 +304,16 @@ def _build_1x1_vep_grid( code: code to be used with the flicking box Returns: - list of visual.GratingStim objects + list of GratingStim objects """ assert len(code) >= self.refresh_rate, 'Code must be longer than refresh rate' - pattern1 = visual.GratingStim(win=self.window, name=f'1x1-1-{position}', units='height', + pattern1 = GratingStim(win=self.window, name=f'1x1-1-{position}', units='height', tex=None, mask=None, ori=0, pos=position, size=size, sf=1, phase=0.0, color=color[0], colorSpace='rgb', opacity=1, texRes=256, interpolate=True, depth=-1.0) - pattern2 = visual.GratingStim(win=self.window, name=f'1x1-2-{position}', units='height', + pattern2 = GratingStim(win=self.window, name=f'1x1-2-{position}', units='height', tex=None, mask=None, ori=0, pos=position, size=size, sf=1, phase=0, color=color[1], colorSpace='rgb', opacity=1, @@ -317,7 +326,7 @@ def _build_2x2_vep_grid(self, position: Tuple[float], size: float, color: str, - code: List[int]) -> List[visual.GratingStim]: + code: List[int]) -> List[GratingStim]: """Build a 2x2 VEP grid. Args: @@ -327,7 +336,7 @@ def _build_2x2_vep_grid(self, code: code to be used with the flicking box Returns: - list of visual.GratingStim objects + list of GratingStim objects """ assert len(code) >= self.refresh_rate, 'Code must be longer than refresh rate' @@ -340,12 +349,12 @@ def _build_2x2_vep_grid(self, ] box = [] for pos in positions: - pattern1 = visual.GratingStim(win=self.window, name=f'2x2-1-{pos}', units='height', + pattern1 = GratingStim(win=self.window, name=f'2x2-1-{pos}', units='height', tex=None, mask=None, ori=0, pos=pos, size=size, sf=1, phase=0.0, color=color[0], colorSpace='rgb', opacity=1, texRes=256, interpolate=True, depth=-1.0) - pattern2 = visual.GratingStim(win=self.window, name=f'2x2-2-{pos}', units='height', + pattern2 = GratingStim(win=self.window, name=f'2x2-2-{pos}', units='height', tex=None, mask=None, ori=0, pos=pos, size=size, sf=1, phase=0, color=color[1], colorSpace='rgb', opacity=1, @@ -390,10 +399,10 @@ def _build_text_boxes(self) -> List[visual.TextBox2]: # generate the inquiry stimuli assert len( self.stimuli_colors) == self.vep_type, ( - f"stmuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") + f"stimuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") assert len( self.stimuli_pos) == self.vep_type, ( - f"stmuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}") + f"stimuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}") self.text_boxes = [] inc_q = int(self.vep_type / 2) From 18daec4a2fa9292dcfb58072f582081451964d3b Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 14 Sep 2023 13:21:39 -0700 Subject: [PATCH 085/330] VEP Display cleanup --- .../display/demo/vep/demo_calibration_vep.py | 6 +- bcipy/display/paradigm/vep/display.py | 105 ++++++++---------- 2 files changed, 51 insertions(+), 60 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 6ed33cd64..de47ea459 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -9,7 +9,7 @@ info_color=['White'], info_pos=[(-.5, -.75)], info_height=[0.1], - info_font=['Consolas'], + info_font=['Arial'], info_text=['VEP Display Demo'], ) @@ -37,7 +37,7 @@ experiment_clock = Clock() len_stimuli = 10 stimuli = VEPStimuliProperties( - stim_color=[['white'] * num_boxes], + stim_color=[['blue'], ['purple'], ['red'], ['green']], stim_pos=start_positions_for_boxes, stim_height=0.1, stim_font='Arial', @@ -56,7 +56,7 @@ for (txt, color) in zip(task_text, task_color): vep.update_task_bar(txt) vep.schedule_to([['A', 'B'], ['Z'], ['P'], ['R', 'W']], [1, 0.5, 5], - [['blue'], ['purple'], ['red'], ['white']]) + [['blue'], ['purple'], ['red'], ['green']]) timing += vep.do_inquiry() # show the wait screen, this will only happen once diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 4f8ab6340..5b7cb1c5b 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -57,8 +57,6 @@ def __init__( task_bar: TaskBar, info: InformationProperties, trigger_type: str = 'text', - space_char: str = SPACE_CHAR, - full_screen: bool = False, codes: List[int] = None): self.window = window self.window_size = self.window.size # [w, h] @@ -66,27 +64,25 @@ def __init__( self.logger = logging.getLogger(__name__) + # number of VEP text areas; TODO: make this configurable + self.vep_type = 4 + # Stimuli parameters, these are set on display in order to allow - # easy updating after defintion + # easy updating after definition self.stimuli_inquiry = stimuli.stim_inquiry self.stimuli_colors = stimuli.stim_colors self.stimuli_timing = stimuli.stim_timing self.stimuli_font = stimuli.stim_font self.stimuli_height = stimuli.stim_height self.stimuli_pos = stimuli.stim_pos - self.logger.info(self.stimuli_pos) self.is_txt_stim = stimuli.is_txt_stim self.stim_length = stimuli.stim_length - self.sti = [] - self.fixation = visual.TextStim( - self.window, - text=get_fixation(True), - color='red', - height=self.stimuli_height, - units='height', - pos=[0, 0]) - self.full_screen = full_screen + self.logger.info(self.stimuli_pos) + self.check_configuration() + + self.sti = [] + self.fixation = self._build_fixation() self.static_clock = core.Clock() @@ -101,33 +97,30 @@ def __init__( self.first_stim_callback = lambda _sti: None self.size_list_sti = [] - # Task parameters - self.space_char = space_char - self.task_bar = task_bar - - # Information parameters - self.info = info self.info_text = info.build_info_text(window) - self.colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] - if not codes: - self.codes = create_vep_codes(length=self.refresh_rate, count=4) - else: - self.codes = codes - # build the VEP stimuli - self.vep = [] - self.text_boxes = [] - self.vep_type = 4 - assert self.vep_type == 4, 'Only 4 stimuli are supported in VEP display at this time!' - self.vep_box_size = .1 + if not codes: + codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) + vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] + vep_box_size = .1 + self.vep = self._build_vep_corner_stimuli(self.stimuli_pos, codes, vep_colors, vep_box_size) + self.text_boxes = self._build_text_boxes(vep_box_size) self.animation_duration = 2 + def check_configuration(self): + """Check that configured properties are consistent""" + assert len( + self.stimuli_colors) == self.vep_type, ( + f"stimuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") + assert len( + self.stimuli_pos) == self.vep_type, ( + f"stimuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}") def do_fixation(self) -> None: - # draw fixation cross + """Draw fixation cross""" self.fixation.draw() self.draw_static() self.window.flip() @@ -138,11 +131,9 @@ def do_inquiry(self) -> List[float]: timing = [] - # if this is the first run, calibrate using the trigger pulse and setup the VEP and text boxes + # if this is the first run, calibrate using the trigger pulse if self.first_run: self._trigger_pulse() - self._build_vep_corner_stimuli(self.stimuli_pos, self.codes, self.colors, self.vep_box_size) - self._build_text_boxes() # fixation --> animation / prompting --> VEP stimulate self.do_fixation() @@ -255,6 +246,15 @@ def update_task_bar(self, text: str = ''): if self.task_bar: self.task_bar.update(text) + def _build_fixation(self) -> visual.TextStim: + """Build the fixation stim""" + return visual.TextStim(self.window, + text=get_fixation(self.is_txt_stim), + color='red', + height=self.stimuli_height, + units='height', + pos=[0, 0]) + def _build_inquiry_stimuli(self) -> None: """Build the inquiry stimuli.""" all_letters = [] @@ -277,7 +277,7 @@ def _build_vep_corner_stimuli( pos: Tuple[float, float], codes: List[int], colors: List[Tuple[str]], - box_size: float) -> List[GratingStim]: + box_size: float) -> List[VEPBox]: """Build the corner stimuli for the VEP. Args: @@ -294,7 +294,7 @@ def _build_1x1_vep_grid( position: Tuple[float], size: float, color: str, - code: List[int]) -> List[GratingStim]: + code: List[int]) -> List[VEPBox]: """Build a 1x1 VEP grid. Args: @@ -319,14 +319,13 @@ def _build_1x1_vep_grid( color=color[1], colorSpace='rgb', opacity=1, texRes=256, interpolate=True, depth=-2.0) box = [VEPBox(flicker=[pattern1, pattern2], code=code)] - self.vep += box return box def _build_2x2_vep_grid(self, position: Tuple[float], size: float, color: str, - code: List[int]) -> List[GratingStim]: + code: List[int]) -> List[VEPBox]: """Build a 2x2 VEP grid. Args: @@ -362,7 +361,6 @@ def _build_2x2_vep_grid(self, color = (color[1], color[0]) box += [VEPBox(flicker=[pattern1, pattern2], code=code)] - self.vep += box return box def _trigger_pulse(self) -> None: @@ -389,26 +387,18 @@ def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]], color """ self.stimuli_inquiry = stimuli self.stimuli_timing = timing - self.stimuli_colors = colors + assert colors is None or colors == self.stimuli_colors, "Colors must match the pre-configured values" - def _build_text_boxes(self) -> List[visual.TextBox2]: + def _build_text_boxes(self, vep_box_size: float) -> List[visual.TextBox2]: """Build the text boxes for the experiment. This assumes that vep_type is 4 using a 2x2 grid. Additional configurations can be added in the future. """ - # generate the inquiry stimuli - assert len( - self.stimuli_colors) == self.vep_type, ( - f"stimuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") - assert len( - self.stimuli_pos) == self.vep_type, ( - f"stimuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}") - - self.text_boxes = [] + text_boxes = [] inc_q = int(self.vep_type / 2) - size = self.vep_box_size * inc_q + size = vep_box_size * inc_q inc = 0 # get the last box in the grating stim per vep - for color in self.stimuli_colors: + for i, color in enumerate(self.stimuli_colors): text = ' ' first = self.vep[inc].flicker[0].pos best_neighbor = self.vep[inc + inc_q].flicker[0].pos @@ -416,7 +406,8 @@ def _build_text_boxes(self) -> List[visual.TextBox2]: # the textbox requires the pos to be centered on the middle of the box, so # we need to calculate the center of the vep stimulus boxes pos = (first[0] + best_neighbor[0]) / 2, (first[1] + best_neighbor[1]) / 2 - self.text_boxes += [visual.TextBox2( + print(f"Position of {color} text area (#{i}): {pos}") + text_boxes += [visual.TextBox2( win=self.window, text=text, font=self.stimuli_font, @@ -428,10 +419,10 @@ def _build_text_boxes(self) -> List[visual.TextBox2]: alignment='center', anchor='center', borderWidth=2, - borderColor='white', + borderColor=color, letterHeight=self.stimuli_height / 2)] inc += self.vep_type - return self.text_boxes + return text_boxes def _reset_text_boxes(self) -> None: """Reset text boxes. @@ -449,10 +440,10 @@ def _set_inquiry(self) -> List[visual.TextBox2]: # generate the inquiry stimuli assert len( self.stimuli_inquiry) == self.vep_type, ( - f"stmuli inquiry {len(self.stimuli_inquiry)} must be the same length as vep type {self.vep_type}") + f"stimuli inquiry {len(self.stimuli_inquiry)} must be the same length as vep type {self.vep_type}") assert len( self.stimuli_colors) == self.vep_type, ( - f"stmuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") + f"stimuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") for box_content, color, box in zip(self.stimuli_inquiry, self.stimuli_colors, self.text_boxes): text = ' '.join(box_content) box.text = text From 7361045dd21b1656982ba82092cae8be48368c94 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Sat, 16 Sep 2023 13:38:57 -0400 Subject: [PATCH 086/330] First gaze model ready for PR --- bcipy/helpers/stimuli.py | 26 ++++++++++++++++------- bcipy/signal/model/fusion_model.py | 29 -------------------------- bcipy/signal/model/offline_analysis.py | 15 ++++++------- 3 files changed, 27 insertions(+), 43 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index c429e5d46..f05fb5081 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -9,7 +9,7 @@ from os import path, sep from typing import Iterator, List, Tuple, NamedTuple, Optional -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.helpers.exceptions import BciPyCoreException, SignalException from bcipy.helpers.list import grouper from bcipy.helpers.symbols import alphabet @@ -325,7 +325,7 @@ def __call__(self, @staticmethod def extract_eye_info(data): """ Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples - Extract Left and Right Eye info from data. + Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. Args: data (np.ndarray): Data in shape of num_channels x num_samples @@ -338,7 +338,7 @@ def extract_eye_info(data): # Extract samples from channels lx = data[2,:] ly = data[3,:] - left_pupil = data[4,:] + left_pupil = data[4,:] # Use if needed rx = data[5,:] ry = data[6,:] @@ -347,11 +347,23 @@ def extract_eye_info(data): left_eye = np.vstack((np.array(lx), np.array(ly))).T right_eye = np.vstack((np.array(rx), np.array(ry))).T - # Remove blinks (i.e. Nan values) - left_eye = left_eye[~np.isnan(left_eye).any(axis=1)] - right_eye = right_eye[~np.isnan(right_eye).any(axis=1)] + # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. + # Make sure that the number of samples are the same for both eyes + left_eye_nan_idx = np.isnan(left_eye).any(axis=1) + left_eye = left_eye[~left_eye_nan_idx] + right_eye = right_eye[~left_eye_nan_idx] - return left_eye, left_pupil, right_eye, right_pupil + right_eye_nan_idx = np.isnan(right_eye).any(axis=1) + left_eye = left_eye[~right_eye_nan_idx] + right_eye = right_eye[~right_eye_nan_idx] + + try: + len(left_eye) != len(right_eye) + except AssertionError: + raise SignalException( + f'Number of samples for left and right eye are not the same.') + + return left_eye, right_eye class TrialReshaper(Reshaper): def __call__(self, diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py index d74610d8f..5da04ad68 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/fusion_model.py @@ -41,32 +41,3 @@ def predict(self, scores: np.array): # Get the argmax of the scores #return predictions - - - -# if __name__ == "__main__": -# # Dummy model test -# letterdata = np.load('/Users/basak/Documents/BciPy/S001_A.npz') -# left_eye = np.vstack((letterdata['lx'], letterdata['ly'])).T -# right_eye = np.vstack((letterdata['rx'], letterdata['ry'])).T - -# # Train test split the data -# test_size_right = int(len(right_eye) * 0.2) -# train_size_right = len(right_eye) - test_size_right -# train_right_eye = right_eye[:train_size_right] -# test_right_eye = right_eye[train_size_right:] - -# test_size_left = int(len(left_eye) * 0.2) -# train_size_left = len(left_eye) - test_size_left -# train_left_eye = left_eye[:train_size_left] -# test_left_eye = left_eye[train_size_left:] - -# gm = GaussianMixture(n_components=2, random_state=0, init_params='kmeans').fit(train_right_eye) -# predictions = gm.predict_proba(test_right_eye) -# print(predictions) -# plt.scatter(left_eye[:, 0], left_eye[:, 1], c='r', s=1) -# plt.scatter(right_eye[:, 0], right_eye[:, 1], c='b', s=1) -# means = gm.means_ -# plt.scatter(means[:,0], means[:,1], c='black', s=20, marker='^') -# plt.show() -# breakpoint() diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 4580239b9..93496e7cb 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -292,14 +292,18 @@ def offline_analysis( ) symbol_set = alphabet() - # Train the model for each target label and each eye separately. + + # Extract the data for each target label and each eye separately. + # Apply preprocessing: + preprocessed_data = {i: [] for i in symbol_set} for i in symbol_set: # Skip if there's no evidence for this symbol: if len(inquiries[i]) == 0: continue - # Do more preprocesssing to extract eye info: - left_eye, left_pupil, right_eye, right_pupil = model.reshaper.extract_eye_info(inquiries[i]) - + + left_eye, right_eye = model.reshaper.extract_eye_info(inquiries[i]) + preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) + # Train test split: test_size = int(len(right_eye) * 0.2) train_size = len(right_eye) - test_size @@ -323,9 +327,6 @@ def offline_analysis( show=True, raw_plot=True, ) - - breakpoint() - if alert_finished: From 9d754af4733176c17b14073617d0e066866f4319 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Sat, 16 Sep 2023 14:08:51 -0400 Subject: [PATCH 087/330] Linting and Changelog updates --- CHANGELOG.md | 7 ++++ bcipy/helpers/load.py | 4 +- bcipy/helpers/raw_data.py | 2 +- bcipy/helpers/stimuli.py | 51 +++++++++++------------ bcipy/helpers/triggers.py | 6 ++- bcipy/helpers/visualization.py | 29 +++++++------ bcipy/signal/model/fusion_model.py | 21 ++++------ bcipy/signal/model/offline_analysis.py | 56 ++++++++++++++------------ 8 files changed, 93 insertions(+), 83 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index d59823b2f..a45c95495 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,3 +1,10 @@ +# 2.0.1-rc.4 + +## Contributions + +- Signal Model + - Offline analysis of multimodal fusion. First version of gaze model is completed #294 Gaze reshaper is updated #294 Visualization for the gaze classification is added #294 + # 2.0.1-rc.3 ## Contributions diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index f93bff73d..3f0834626 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -163,12 +163,12 @@ def load_experimental_data() -> str: def load_eye_tracking_data(gaze_data: RawData): - left_eye_channel_map = [0,0,1,1,0,0,0,0,0] + left_eye_channel_map = [0, 0, 1, 1, 0, 0, 0, 0, 0] left_eye_data, _, _ = gaze_data.by_channel_map(left_eye_channel_map) left_eye_x = left_eye_data[0] left_eye_y = left_eye_data[1] - right_eye_channel_map = [0,0,0,0,0,1,1,0,0] + right_eye_channel_map = [0, 0, 0, 0, 0, 1, 1, 0, 0] right_eye_data, _, _ = gaze_data.by_channel_map(right_eye_channel_map) right_eye_x = right_eye_data[0] right_eye_y = right_eye_data[1] diff --git a/bcipy/helpers/raw_data.py b/bcipy/helpers/raw_data.py index e915c0362..d4e946b5d 100644 --- a/bcipy/helpers/raw_data.py +++ b/bcipy/helpers/raw_data.py @@ -183,7 +183,7 @@ def append(self, row: List): def __str__(self) -> str: return f"RawData({self.daq_type})" - + def __repr__(self) -> str: return f"RawData({self.daq_type})" diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index f05fb5081..b369809e3 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -177,7 +177,6 @@ def get_inquiry_len(inq_trigs): stop = first_trigger + num_samples_per_inq + buffer_samples reshaped_data.append(eeg_data[:, start:stop]) - return np.stack(reshaped_data, 1), labels, reshaped_trigger_timing @staticmethod @@ -228,6 +227,7 @@ def extract_trials( f'prestimulus_samples: {prestimulus_samples}, samples_per_trial: {samples_per_trial} \n') return np.stack(new_trials, 1) # C x T x S + class GazeReshaper: def __call__(self, trial_targetness_label: List[str], @@ -268,14 +268,14 @@ def __call__(self, # Remove the channels that we are not interested in channels_to_remove = [idx for idx, value in enumerate(channel_map) if value == 0] gaze_data = np.delete(gaze_data, channels_to_remove, axis=0) - + # Find the value closest to (& greater than) inq_start_times - gaze_data_timing = gaze_data[-1,:].tolist() - + gaze_data_timing = gaze_data[-1, :].tolist() + start_times = [] for times in inq_start_times: temp = list(filter(lambda x: x > times, gaze_data_timing)) - if len(temp) > 0: + if len(temp) > 0: start_times.append(temp[0]) triggers = [] @@ -297,58 +297,58 @@ def __call__(self, # Merge the inquiries if they have the same target letter: for i, inquiry_index in enumerate(triggers): start = inquiry_index - stop = int(inquiry_index + (sample_rate * 3)) # (60 samples * 3 seconds) + stop = int(inquiry_index + (sample_rate * 3)) # (60 samples * 3 seconds) # Check if the data exists for the inquiry: - if stop > len(gaze_data[0,:]): + if stop > len(gaze_data[0, :]): continue - - reshaped_data.append(gaze_data[:, start:stop]) + + reshaped_data.append(gaze_data[:, start:stop]) # (Optional) extracted data (Inquiries x Channels x Samples) # Populate the dict by appending the inquiry to the correct key: data_by_targets[labels[i]].append(gaze_data[:, start:stop]) - + # After populating, flatten the arrays in the dictionary to (Channels x Samples): for symbol in symbol_set: if len(data_by_targets[symbol]) > 0: - data_by_targets[symbol] = np.transpose(np.array(data_by_targets[symbol]), (1,0,2)) + data_by_targets[symbol] = np.transpose(np.array(data_by_targets[symbol]), (1, 0, 2)) data_by_targets[symbol] = np.reshape(data_by_targets[symbol], (len(data_by_targets[symbol]), -1)) # TODO: Note that this is a workaround to the issue of having different number of targetness in # each symbol. If a target symbol is prompted more than once, the data is appended to the dict as a list. # Which is why we need to convert it to a (np.ndarray) and flatten the dimensions. - # This is not ideal, but it works for now. + # This is not ideal, but it works for now. # return np.stack(reshaped_data, 0), labels return data_by_targets - + @staticmethod def extract_eye_info(data): """ Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. - + Args: data (np.ndarray): Data in shape of num_channels x num_samples - + Returns: left_eye (np.ndarray), left_pupil (List(float)) right_eye (np.ndarray), right_pupil (List(float)) """ # Extract samples from channels - lx = data[2,:] - ly = data[3,:] - left_pupil = data[4,:] # Use if needed + lx = data[2, :] + ly = data[3, :] + left_pupil = data[4, :] # Use if needed - rx = data[5,:] - ry = data[6,:] - right_pupil = data[7,:] + rx = data[5, :] + ry = data[6, :] + right_pupil = data[7, :] - left_eye = np.vstack((np.array(lx), np.array(ly))).T + left_eye = np.vstack((np.array(lx), np.array(ly))).T right_eye = np.vstack((np.array(rx), np.array(ry))).T - # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. - # Make sure that the number of samples are the same for both eyes + # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. + # Make sure that the number of samples are the same for both eyes left_eye_nan_idx = np.isnan(left_eye).any(axis=1) left_eye = left_eye[~left_eye_nan_idx] right_eye = right_eye[~left_eye_nan_idx] @@ -361,10 +361,11 @@ def extract_eye_info(data): len(left_eye) != len(right_eye) except AssertionError: raise SignalException( - f'Number of samples for left and right eye are not the same.') + 'Number of samples for left and right eye are not the same.') return left_eye, right_eye + class TrialReshaper(Reshaper): def __call__(self, trial_targetness_label: list, diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index f668aa2ec..7a6b965e6 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -378,7 +378,11 @@ def trigger_decoder(trigger_path: str, remove_pre_fixation: bool = True, offset: exclusion += [TriggerType.FIXATION, TriggerType.PROMPT, TriggerType.SYSTEM, TriggerType.OFFSET] else: exclusion += [TriggerType.SYSTEM] - triggers = TriggerHandler.load(trigger_path, offset=offset, exclusion=exclusion, apply_system_offset=apply_system_offset) + triggers = TriggerHandler.load( + trigger_path, + offset=offset, + exclusion=exclusion, + apply_system_offset=apply_system_offset) # from the stimuli array, pull out the symbol information trigger_type = [trigger.type.value for trigger in triggers] diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 333935294..d9f10d82d 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -4,7 +4,6 @@ from pathlib import Path from matplotlib.figure import Figure from matplotlib.patches import Ellipse -import matplotlib.pyplot as plt from bcipy.config import (TRIGGER_FILENAME, RAW_DATA_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME, @@ -157,13 +156,13 @@ def visualize_gaze( levels=10, cmap="mako", colorbar=True) - + if raw_plot: ax.scatter(lx, ly, c='r', s=1) ax.scatter(rx, ry, c='b', s=1) plt.title(f'{title}Plot') - + if save_path is not None: plt.savefig(f"{save_path}/{title.lower().replace(' ', '_')}plot.png", dpi=fig.dpi) @@ -172,8 +171,9 @@ def visualize_gaze( return fig + def visualize_gaze_inquiries( - left_eye, + left_eye, right_eye, means=None, covs=None, @@ -203,17 +203,17 @@ def visualize_gaze_inquiries( img = plt.imread(img_path) # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis - lx = np.clip(left_eye[:,0], 0, 1) - ly = np.clip(left_eye[:,1], 0, 1) - rx = np.clip(right_eye[:,0], 0, 1) - ry = np.clip(right_eye[:,1], 0, 1) + lx = np.clip(left_eye[:, 0], 0, 1) + ly = np.clip(left_eye[:, 1], 0, 1) + rx = np.clip(right_eye[:, 0], 0, 1) + ry = np.clip(right_eye[:, 1], 0, 1) ly = 1 - ly ry = 1 - ry if means is not None: - means[:,0] = np.clip(means[:,0], 0, 1) - means[:,1] = np.clip(means[:,1], 0, 1) - means[:,1] = 1 - means[:,1] + means[:, 0] = np.clip(means[:, 0], 0, 1) + means[:, 1] = np.clip(means[:, 1], 0, 1) + means[:, 1] = 1 - means[:, 1] # scale the eye data to the image fig, ax = plt.subplots() @@ -236,7 +236,7 @@ def visualize_gaze_inquiries( levels=10, cmap="mako", colorbar=True) - + if raw_plot: # ax.scatter(lx, ly, c='lightcoral', s=1) ax.scatter(rx, ry, c='bisque', s=1) @@ -254,12 +254,11 @@ def visualize_gaze_inquiries( ell.set_clip_box(ax) ell.set_alpha(0.5) ax.add_artist(ell) - - # ax.scatter(means[:,0], means[:,1], c='yellow', s=20, marker='^') + # ax.scatter(means[:,0], means[:,1], c='yellow', s=20, marker='^') plt.title(f'{title}Plot') - + if save_path is not None: plt.savefig(f"{save_path}/{title.lower().replace(' ', '_')}plot.png", dpi=fig.dpi) diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py index 5da04ad68..62f88fab4 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/fusion_model.py @@ -1,43 +1,38 @@ -import logging -from pathlib import Path -from typing import Tuple - import numpy as np -import pandas as pd -from matplotlib import pyplot as plt from sklearn.mixture import GaussianMixture from bcipy.helpers.stimuli import GazeReshaper + class GazeModel(): reshaper = GazeReshaper() def __init__(self, num_components=3): self.num_components = num_components # number of gaussians to fit - + def fit(self, train_data: np.array): model = GaussianMixture(n_components=2, random_state=0, init_params='kmeans') model.fit(train_data) self.model = model return self - + def get_scores(self, test_data: np.array): ''' Compute the log-likelihood of each sample. Compute the mean and covariance of each mixture component. ''' - + scores = self.model.score_samples(test_data) means = self.model.means_ covs = self.model.covariances_ - + return scores, means, covs - + def predict(self, scores: np.array): ''' Predict the labels for the test data. ''' # Compute over log-likelihood scores # Get the argmax of the scores - - #return predictions + + # return predictions diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 93496e7cb..49a1d1986 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -16,7 +16,7 @@ from bcipy.helpers.stimuli import play_sound, update_inquiry_timing from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.symbols import alphabet -from bcipy.helpers.triggers import TriggerType, trigger_decoder, TriggerHandler +from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import visualize_erp, visualize_gaze, visualize_gaze_inquiries from bcipy.signal.model.base_model import SignalModel from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel @@ -24,9 +24,6 @@ from bcipy.signal.process import filter_inquiries, get_default_transform import numpy as np from matplotlib.figure import Figure -import matplotlib.pyplot as plt -from matplotlib import image -import seaborn as sns from sklearn.metrics import balanced_accuracy_score from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices @@ -38,6 +35,7 @@ IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' # IMG_PATH = f'{STATIC_IMAGES_PATH}/main/rsvp.png' + def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): """Performs a train/test split on the provided data and labels, accounting for the current shape convention (channel dimension in front, instead of batch dimension in front). @@ -114,14 +112,16 @@ def offline_analysis( if '+' in acq_mode: if 'eyetracker' in acq_mode.lower(): # find the eyetracker data file with the prefix of EYE_TRACKER_FILENAME_PREFIX - eye_tracker_file = [ f.name for f in Path(data_folder).iterdir() if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] - assert len(eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {data_folder}. Expected 1." + eye_tracker_file = [f.name for f in Path(data_folder).iterdir() + if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] + assert len( + eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {data_folder}. Expected 1." data_file_paths.extend(eye_tracker_file) else: raise ValueError(f"Unsupported acquisition mode: {acq_mode}. Eyetracker must be included.") if 'eeg' in acq_mode.lower(): # find the eeg data file with the prefix of EEG_FILENAME_PREFIX - eeg_file = [ f.name for f in Path(data_folder).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] + eeg_file = [f.name for f in Path(data_folder).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] assert len(eeg_file) == 1, f"Found {len(eeg_file)} EEG files in {data_folder}. Expected 1." data_file_paths.extend(eeg_file) else: @@ -247,13 +247,13 @@ def offline_analysis( show=True, raw_plot=True, ) - + channels = mode_data.channels type_amp = mode_data.daq_type sample_rate = mode_data.sample_rate log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") channel_map = analysis_channels(channels, device_spec) channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] @@ -265,42 +265,47 @@ def offline_analysis( # Process triggers.txt files (again!) trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - remove_pre_fixation = False, + remove_pre_fixation=False, apply_system_offset=False, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.SYSTEM, TriggerType.OFFSET] + exclusion=[ + TriggerType.PREVIEW, + TriggerType.EVENT, + TriggerType.FIXATION, + TriggerType.SYSTEM, + TriggerType.OFFSET] ) ''' Trigger_timing includes PROMPT and excludes FIXATION ''' - + # Use trigger_timing to generate time windows for each letter flashing # Take every 10th trigger as the start point of timing. # trigger_targetness keeps the PROMPT info, use it to find the target symbol. target_symbols = trigger_symbols[0::11] # target symbols inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) - # Find the inquiries starting by the inq_start_times, (9, 100, 180): + # Find the inquiries starting by the inq_start_times, (9, 100, 180): inquiries = model.reshaper( - trial_targetness_label=trigger_targetness, - inq_start_times=inq_start, - target_symbols = target_symbols, - gaze_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - poststimulus_length=poststim_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer + trial_targetness_label=trigger_targetness, + inq_start_times=inq_start, + target_symbols=target_symbols, + gaze_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + poststimulus_length=poststim_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer ) symbol_set = alphabet() - # Extract the data for each target label and each eye separately. + # Extract the data for each target label and each eye separately. # Apply preprocessing: preprocessed_data = {i: [] for i in symbol_set} for i in symbol_set: # Skip if there's no evidence for this symbol: if len(inquiries[i]) == 0: continue - + left_eye, right_eye = model.reshaper.extract_eye_info(inquiries[i]) preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) @@ -326,8 +331,7 @@ def offline_analysis( save_path=None, show=True, raw_plot=True, - ) - + ) if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") From eaf4bf7b1929321bc017e586d2f618fe208f4f01 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 17 Sep 2023 17:06:45 -0400 Subject: [PATCH 088/330] Refactored replay_session into Simulator object basic functionality --- bcipy/simulator/__init__.py | 0 bcipy/simulator/helpers/signal_helpers.py | 135 ++++++++++++++++++++ bcipy/simulator/helpers/sim_viz.py | 68 ++++++++++ bcipy/simulator/main.py | 52 ++++++++ bcipy/simulator/sim_copy_phrase.py | 148 ++++++++++++++++++++++ bcipy/simulator/sim_factory.py | 29 +++++ bcipy/simulator/sim_parameters.json | 24 ++++ bcipy/simulator/simulator_base.py | 36 ++++++ 8 files changed, 492 insertions(+) create mode 100644 bcipy/simulator/__init__.py create mode 100644 bcipy/simulator/helpers/signal_helpers.py create mode 100644 bcipy/simulator/helpers/sim_viz.py create mode 100644 bcipy/simulator/main.py create mode 100644 bcipy/simulator/sim_copy_phrase.py create mode 100644 bcipy/simulator/sim_factory.py create mode 100644 bcipy/simulator/sim_parameters.json create mode 100644 bcipy/simulator/simulator_base.py diff --git a/bcipy/simulator/__init__.py b/bcipy/simulator/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py new file mode 100644 index 000000000..698cd94ca --- /dev/null +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -0,0 +1,135 @@ +import json +import logging as logger +from dataclasses import dataclass +from typing import Tuple +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import seaborn as sns +from bcipy.config import ( + RAW_DATA_FILENAME, + TRIGGER_FILENAME, + DEFAULT_PARAMETER_FILENAME, SESSION_DATA_FILENAME, + DEFAULT_DEVICE_SPEC_FILENAME, +) +from bcipy.helpers.acquisition import analysis_channels +import bcipy.acquisition.devices as devices +from bcipy.helpers.list import grouper +from bcipy.helpers.load import load_json_parameters, load_raw_data, load_experimental_data +from bcipy.helpers.session import read_session, evidence_records +from bcipy.helpers.stimuli import update_inquiry_timing +from bcipy.helpers.triggers import TriggerType, trigger_decoder +from bcipy.helpers.symbols import alphabet +from bcipy.signal.model import PcaRdaKdeModel +from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams + +logger.getLogger().setLevel(logger.INFO) +log = logger.getLogger(__name__) + + +@dataclass() +class ExtractedExperimentData: # TODO clean up design + inquiries: np.ndarray + trials: np.ndarray + labels: list + inquiry_timing: list + + decoded_triggers: tuple + + +def process_raw_data_for_model(data_folder, parameters, model_class=PcaRdaKdeModel) -> ExtractedExperimentData: + + assert parameters, "Parameters are required for offline analysis." + if not data_folder: + data_folder = load_experimental_data() + + # extract relevant session information from parameters file + trial_window = parameters.get("trial_window") + window_length = trial_window[1] - trial_window[0] + + prestim_length = parameters.get("prestim_length") + trials_per_inquiry = parameters.get("stim_length") + # The task buffer length defines the min time between two inquiries + # We use half of that time here to buffer during transforms + buffer = int(parameters.get("task_buffer_length") / 2) + raw_data_file = f"{RAW_DATA_FILENAME}.csv" + + # get signal filtering information + transform_params = parameters.instantiate(ERPTransformParams) + downsample_rate = transform_params.down_sampling_rate + static_offset = parameters.get("static_trigger_offset") + + log.info( + f"\nData processing settings: \n" + f"{str(transform_params)} \n" + f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " + f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer}s \n" + f"Static offset: {static_offset}" + ) + + # Load raw data + raw_data = load_raw_data(Path(data_folder, raw_data_file)) + channels = raw_data.channels + type_amp = raw_data.daq_type + sample_rate = raw_data.sample_rate + + devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(raw_data.daq_type) + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) + + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + + k_folds = parameters.get("k_folds") + model = model_class(k_folds=k_folds) + + # Process triggers.txt files + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + offset=static_offset, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + + # update the trigger timing list to account for the initial trial window + corrected_trigger_timing = [timing + trial_window[0] for timing in trigger_timing] + + # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module + # The timestamp column [0] is already excluded. + channel_map = analysis_channels(channels, device_spec) + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + log.info(f'Channels used in analysis: {channels_used}') + + data, fs = raw_data.by_channel() + + inquiries, inquiry_labels, inquiry_timing = model.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=corrected_trigger_timing, + eeg_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=window_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) + + inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) + inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) + trial_duration_samples = int(window_length * fs) + trials = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) + + # define the training classes using integers, where 0=nontargets/1=targets + # labels = inquiry_labels.flatten() + + return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, (trigger_targetness, trigger_timing, trigger_symbols)) diff --git a/bcipy/simulator/helpers/sim_viz.py b/bcipy/simulator/helpers/sim_viz.py new file mode 100644 index 000000000..4c94805a4 --- /dev/null +++ b/bcipy/simulator/helpers/sim_viz.py @@ -0,0 +1,68 @@ +import logging as logger + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import seaborn as sns + +from bcipy.helpers.parameters import Parameters + +logger.getLogger().setLevel(logger.INFO) + + +def plot_comparison_records(records, outdir, title="response_values", y_scale="log"): + df = pd.DataFrame.from_records(records) + ax = sns.stripplot( + x="which_model", + y="response_value", + data=df, + order=["old_target", "new_target", "old_non_target", "new_non_target"], + ) + sns.boxplot( + showmeans=True, + meanline=True, + meanprops={"color": "k", "ls": "-", "lw": 2}, + medianprops={"visible": False}, + whiskerprops={"visible": False}, + zorder=10, + x="which_model", + y="response_value", + data=df, + showfliers=False, + showbox=False, + showcaps=False, + ax=ax, + order=["old_target", "new_target", "old_non_target", "new_non_target"], + ) + + ax.set(yscale=y_scale) + plt.savefig(outdir / f"{title}.stripplot.png", dpi=150, bbox_inches="tight") + plt.close() + ax = sns.boxplot( + x="which_model", + y="response_value", + data=df, + order=["old_target", "new_target", "old_non_target", "new_non_target"], + ) + ax.set(yscale=y_scale) + plt.savefig(outdir / f"{title}.boxplot.png", dpi=150, bbox_inches="tight") + + +def plot_replay_comparison(new_target_eeg_evidence: np.ndarray, + new_non_target_eeg_evidence: np.ndarray, + old_target_eeg_evidence: np.ndarray, + old_non_target_eeg_evidence: np.ndarray, + outdir: str, + parameters: Parameters, + ) -> None: + def convert_to_records(arr, key_value, key_name="which_model", value_name="response_value") -> [dict]: + return [{key_name: key_value, value_name: val} for val in arr] + + records = [] + + records.extend(convert_to_records(new_target_eeg_evidence, "new_target")) + records.extend(convert_to_records(new_non_target_eeg_evidence, "new_non_target")) + records.extend(convert_to_records(old_target_eeg_evidence, "old_target")) + records.extend(convert_to_records(old_non_target_eeg_evidence, "old_non_target")) + + plot_comparison_records(records, outdir, y_scale="log") diff --git a/bcipy/simulator/main.py b/bcipy/simulator/main.py new file mode 100644 index 000000000..360ad8299 --- /dev/null +++ b/bcipy/simulator/main.py @@ -0,0 +1,52 @@ +import argparse +from pathlib import Path + +from bcipy.helpers.load import load_json_parameters +from bcipy.simulator.sim_factory import SimulationFactory + +if __name__ == "__main__": + + parser = argparse.ArgumentParser() + parser.add_argument( + "-d", + "--data_folders", + action="append", + type=Path, + required=True, + help="Session data folders to be processed. This argument can be repeated to accumulate sessions data.") + parser.add_argument( + "-sm", + "--smodel_files", + action="append", + type=Path, + required=True, + help="Signal models to be used") + parser.add_argument( + "-lm", + "--lmodel_file", + action="append", + type=Path, + required=False, + help="Language models to be used") + parser.add_argument("-o", "--out_dir", type=Path, default=None) + parser.add_argument( + "-p", + "--parameter_path", + type=Path, + default=None, + help="Parameter file to be used for replay. If none, the session parameter file will be used.") + + args = vars(parser.parse_args()) + + # assert len(set(args['data_folders'])) == len(args.data_folders), "Duplicated data folders" + + if args['out_dir'] is None: + args['out_dir'] = Path(__file__).resolve().parent + + # Load parameters + sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) + sim_task = sim_parameters.get("sim_task") + args['sim_task'] = sim_task + + simulator = SimulationFactory.create(**args) + simulator.run() diff --git a/bcipy/simulator/sim_copy_phrase.py b/bcipy/simulator/sim_copy_phrase.py new file mode 100644 index 000000000..95300dc87 --- /dev/null +++ b/bcipy/simulator/sim_copy_phrase.py @@ -0,0 +1,148 @@ +from typing import Optional + +import numpy as np + +from bcipy.config import SESSION_DATA_FILENAME +from bcipy.helpers import load +from bcipy.helpers.list import grouper +from bcipy.helpers.session import evidence_records, read_session +from bcipy.helpers.symbols import alphabet +from bcipy.signal.model import PcaRdaKdeModel +from bcipy.simulator.helpers.signal_helpers import process_raw_data_for_model, ExtractedExperimentData +from bcipy.simulator.helpers.sim_viz import plot_replay_comparison +from bcipy.simulator.simulator_base import Simulator, SimulatorData + + +class SimulatorCopyPhraseReplay(Simulator): + """Simulator. + + Base class for BciPy Simulations. + + Requirements: + - run closed loop simulation of {TaskType} with {data} with {simulation_params} + """ + + def __init__(self, parameter_path, save_dir, signal_models: [tuple], language_models, replay_data_path=None, + verbose=False): + super(SimulatorCopyPhraseReplay, self).__init__() + + self.parameters = self.load_parameters(parameter_path) + self.save_dir = save_dir + self.signal_models = signal_models + self.language_models = language_models + self.replay_data_path = replay_data_path + + self.symbol_set = alphabet() + self.write_output = False + self.data_loader = None + + self.signal_models_classes = [PcaRdaKdeModel for m in self.signal_models] # Hardcoded rn + + def run(self): + self.init_data_loader() + + self.logger.info(f"Initialized data loader") + + # TODO need to support multimodal and language models + model_file, model_class = self.signal_models[0], self.signal_models_classes[0] # hardcoded rn + model = model_class(self.parameters.get("k_folds")) + model = model.load(model_file) + + self.logger.info(f"Loaded model from {model_file}, with model_class {model_class}") + + target_eeg_evidences, non_target_eeg_evidences = [], [] + while not self.data_loader.is_end(): + inquiry_trials, this_inquiry_letters, this_inquiry_labels = self.data_loader.next() + target_eeg_evidence, non_target_eeg_evidence = [], [] + response = model.predict(inquiry_trials, this_inquiry_letters, symbol_set=self.symbol_set) + + symbol_letter_idx_map = [self.symbol_set.index(letter) for letter in this_inquiry_letters] + for i, label in enumerate(this_inquiry_labels): + if label: + target_eeg_evidence.append(response[symbol_letter_idx_map[i]]) + else: + non_target_eeg_evidence.append(response[symbol_letter_idx_map[i]]) + + target_eeg_evidences.append(target_eeg_evidence) + non_target_eeg_evidences.append(non_target_eeg_evidence) + + target_eeg_evidences, non_target_eeg_evidences = np.concatenate(target_eeg_evidences), np.concatenate( + non_target_eeg_evidences) + + # Get target and non_target eeg values from actual experiment in session.json for comparison + session_records = evidence_records(read_session(self.replay_data_path / SESSION_DATA_FILENAME)) + session_target_eeg = np.array([record.eeg for record in session_records if record.is_target]) + session_non_target_eeg = np.array([record.eeg for record in session_records if not record.is_target]) + + # note this flattens any grouping of inquiries which might be problem for future visualizations + + # visualizing comparison of results + plot_replay_comparison(target_eeg_evidences, non_target_eeg_evidences, session_target_eeg, + session_non_target_eeg, self.save_dir, self.parameters) + + self.logger.info(f"Plotted comparison charts " + f"\n New: {len(target_eeg_evidences)} target_eeg_evidences | {len(non_target_eeg_evidences)} non_target_eeg_evidences " + f"\n Old: {len(session_target_eeg)} target_eeg_evidences | {len(session_non_target_eeg)} non_target_eeg_evidences ") + + def get_param(self, name): + return self.parameters.get(name, None) + + def init_data_loader(self): + + if self.replay_data_path: + self.data_loader = ReplayDataLoader(self.replay_data_path, self.parameters) + else: + pass # TODO sampling data logic + pass + + def load_parameters(self, path): + # TODO validate parameters + parameters = load.load_json_parameters(path, value_cast=True) + sim_parameters = load.load_json_parameters( + "bcipy/simulator/sim_parameters.json", value_cast=True) + + parameters.add_missing_items(sim_parameters) + return parameters + + +class ReplayDataLoader(SimulatorData): + + def __init__(self, source_path, parameters): + self.source_path = source_path + self.parameters = parameters + self.verbose = False + + self.inquiry_worth_of_letters = None + self.inquiry_worth_of_trials = None + self.data: Optional[ExtractedExperimentData] = None + + self.load() + + self.i = 0 + + def load(self): + experiment_data = process_raw_data_for_model(self.source_path, self.parameters) + + # formatting data into inquiries + trigger_targetness, trigger_timing, trigger_symbols = experiment_data.decoded_triggers + self.inquiry_worth_of_trials = np.split(experiment_data.trials, experiment_data.inquiries.shape[1], 1) + self.inquiry_worth_of_letters = [list(group) for group in + grouper(trigger_symbols, self.parameters.get('stim_length'), + incomplete="ignore")] + + self.data = experiment_data + + def next(self): + if self.i < len(self.inquiry_worth_of_letters): + cur_trials = self.inquiry_worth_of_trials[self.i] + cur_letters = self.inquiry_worth_of_letters[self.i] + cur_labels = self.data.labels[self.i] + + self.i += 1 + + return cur_trials, cur_letters, cur_labels # TODO turn into dataclass + + return None, None, None + + def is_end(self): + return self.i >= len(self.inquiry_worth_of_letters) diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py new file mode 100644 index 000000000..68c83a2aa --- /dev/null +++ b/bcipy/simulator/sim_factory.py @@ -0,0 +1,29 @@ +from pathlib import Path + +from bcipy.config import DEFAULT_PARAMETER_FILENAME +from bcipy.simulator.sim_copy_phrase import SimulatorCopyPhraseReplay +from bcipy.simulator.simulator_base import Simulator + + +class SimulationFactory: + + @staticmethod + def create( + sim_task="", + parameter_path="", + smodel_files=None, + lmodel_files=None, + data_folders=None, + out_dir="", + **kwargs) -> Simulator: + if sim_task == 'RSVP_COPY_PHRASE': + # TODO validate arguments + + if not parameter_path: + data_folder = data_folders[0] + parameter_path = Path(data_folder, DEFAULT_PARAMETER_FILENAME) + + return SimulatorCopyPhraseReplay(parameter_path, out_dir, smodel_files, lmodel_files, data_folders[0], + verbose=kwargs.get('verbose', False)) + + # parameter_path, save_dir, signal_models: [tuple], language_models, replay_data_path=None, diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json new file mode 100644 index 000000000..301ab6203 --- /dev/null +++ b/bcipy/simulator/sim_parameters.json @@ -0,0 +1,24 @@ +{ + "sim_task": { + "value": "RSVP_COPY_PHRASE", + "section": "sim_config", + "readableName": "Simulation Task", + "helpTip": "Specifies Task to simulate", + "recommended_values": [ + "RSVP_COPY_PHRASE", + "RSVP_CALIBRATION" + ], + "type": "str" + }, + "sim_sample_mode": { + "value": "0", + "section": "sim_config", + "readableName": "Simulation Sample Mode", + "helpTip": "Specifies method for sampling based on sampling registry", + "recommended_values": [ + "0", + "1" + ], + "type": "str" + } +} \ No newline at end of file diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py new file mode 100644 index 000000000..283000da3 --- /dev/null +++ b/bcipy/simulator/simulator_base.py @@ -0,0 +1,36 @@ +import logging + +from abc import ABC, abstractmethod + + +class Simulator(ABC): + """Simulator. + + Base class for BciPy Simulations. + + Requirements: + - run closed loop simulation of {TaskType} with {data} with {simulation_params} + """ + + def __init__(self): + super(Simulator, self).__init__() + self.logger = logging.getLogger(__name__) + + @abstractmethod + def run(self): + ... + + @abstractmethod + def get_param(self, name): + ... + + +class SimulatorData(ABC): + + @abstractmethod + def next(self): + ... + + @abstractmethod + def is_end(self) -> bool: + ... From b3e1914833e376c3a43ce3a775010b2730a3aa85 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 19 Sep 2023 14:38:29 -0700 Subject: [PATCH 089/330] Added functions to support height layout calculations --- bcipy/display/components/layout.py | 76 +++++++++++++++++++++++------- 1 file changed, 60 insertions(+), 16 deletions(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index 37750ee19..b83675afa 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -1,6 +1,6 @@ """Defines common functionality for GUI layouts.""" from enum import Enum -from typing import Protocol, Tuple +from typing import Optional, Protocol, Tuple class Container(Protocol): @@ -8,7 +8,7 @@ class Container(Protocol): size: Tuple[float, float] units: str - +# for norm units DEFAULT_LEFT = -1.0 DEFAULT_TOP = 1.0 DEFAULT_RIGHT = 1.0 @@ -43,8 +43,9 @@ def __init__(self, left: float = DEFAULT_LEFT, top: float = DEFAULT_TOP, right: float = DEFAULT_RIGHT, - bottom: float = DEFAULT_BOTTOM): - self.units = "norm" + bottom: float = DEFAULT_BOTTOM, + units: float = "norm"): + self.units = units self.parent = parent self.top = top self.left = left @@ -54,19 +55,22 @@ def __init__(self, def check_invariants(self): """Check that all invariants hold true.""" - # TODO: units could be configurable; min and max depends on units. # https://psychopy.org/general/units.html#units - assert self.units == "norm", "Position calculations assume norm units." - - assert (0.0 <= self.height <= 2.0), "Height must be in norm units." - assert (0.0 <= self.width <= 2.0), "Width must be in norm units." - assert (-1.0 <= self.top <= 1.0), "Top must be a y-value in norm units" - assert (-1.0 <= self.left <= - 1.0), "Left must be an x-value in norm units" - assert (-1.0 <= self.bottom <= - 1.0), "Bottom must be a y-value in norm units" - assert (-1.0 <= self.right <= - 1.0), "Right must be an x-value in norm units" + assert self.units in ['height', 'norm'], "Units must be 'height' or 'norm'" + if self.units == "norm": + assert (0.0 <= self.height <= 2.0), "Height must be in norm units." + assert (0.0 <= self.width <= 2.0), "Width must be in norm units." + assert (-1.0 <= self.top <= 1.0), "Top must be a y-value in norm units" + assert (-1.0 <= self.left <= + 1.0), "Left must be an x-value in norm units" + assert (-1.0 <= self.bottom <= + 1.0), "Bottom must be a y-value in norm units" + assert (-1.0 <= self.right <= + 1.0), "Right must be an x-value in norm units" + if self.units == "height": + assert (0.0 <= self.height <= 1.0), "Height must be in height units." + assert (-0.5 <= self.top <= 0.5), "Top must be a y-value in height units" + assert (-0.5 <= self.bottom <= 0.5), "Bottom must be a y-value in height units" if self.parent: assert 0 < self.width <= self.parent.size[ @@ -74,6 +78,23 @@ def check_invariants(self): assert 0 < self.height <= self.parent.size[ 1], "Height must be greater than 0 and fit within the parent height." + def scaled_size(self, height: float, window_size: Optional[Tuple[float, float]] = None) -> Tuple[float, float]: + """Returns the value scaled to reflect the aspect ratio of a + visual.Window. Used for creating squared stimulus""" + if self.units == 'height': + width = height + return (width, height) + + # norm units + if window_size is not None: + win_width, win_height = window_size + elif self.parent: + win_width, win_height = self.parent.size + else: + raise ValueError("window_size or parent is required") + width = (win_height / win_width) * height + return (width, height) + @property def size(self) -> Tuple[float, float]: """Layout size.""" @@ -89,6 +110,16 @@ def height(self) -> float: """Height in norm units of this component.""" return self.top - self.bottom + @property + def left_top(self) -> float: + """Top left position""" + return (self.left, self.top) + + @property + def right_bottom(self) -> float: + """Bottom right position""" + return (self.right, self.bottom) + @property def horizontal_middle(self) -> float: """x-axis value in norm units for the midpoint of this component""" @@ -249,3 +280,16 @@ def centered(width_pct: float = 1.0, height_pct: float = 1.0) -> Layout: container.resize_width(width_pct, alignment=Alignment.CENTERED) container.resize_height(height_pct, alignment=Alignment.CENTERED) return container + +def height_units(window_size: Tuple[float, float]): + """Constructs a layout with height units using the given Window + dimensions + + for an aspect ratio of 4:3 + 4 widths / 3 height = 1.333 + 1.333 / 2 = 0.667 + so, left is -0.667 and right is 0.667 + """ + win_width, win_height = window_size + right = (win_width / win_height) / 2 + return Layout(left=-right, top=0.5, right=right, bottom=-0.5, units='height') From 9bb1680bd8641bf805cf8aa8d191acde24702ea0 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 19 Sep 2023 14:39:55 -0700 Subject: [PATCH 090/330] Added module for VEP layout calculations. Added a module for visualizing layout elements. --- bcipy/display/demo/components/demo_layouts.py | 290 ++++++++++++++++++ bcipy/display/paradigm/vep/layout.py | 165 ++++++++++ 2 files changed, 455 insertions(+) create mode 100644 bcipy/display/demo/components/demo_layouts.py create mode 100644 bcipy/display/paradigm/vep/layout.py diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py new file mode 100644 index 000000000..e115950f7 --- /dev/null +++ b/bcipy/display/demo/components/demo_layouts.py @@ -0,0 +1,290 @@ +"""Useful for viewing computed positions in a window""" +import time +from itertools import cycle +from typing import Callable, List, Tuple, Union + +from psychopy import visual +from psychopy.visual.circle import Circle +from psychopy.visual.grating import GratingStim +from psychopy.visual.line import Line +from psychopy.visual.rect import Rect + +from bcipy.display.components.layout import (Layout, at_top, centered, + height_units) +from bcipy.display.paradigm.vep.layout import BoxConfiguration, checkerboard + + +def make_window(): + """Make a sample window on which to draw.""" + return visual.Window(size=[700, 500], + fullscr=False, + screen=0, + waitBlanking=False, + color='black', + winType='pyglet') + + +def draw_boundary(win, + layout: Layout, + color: str = 'blue', + line_px: int = 5, + name: str = None): + """Display the layout's outline.""" + if name: + print(f"Drawing boundary for {name}") + top = Line(win=win, + units=layout.units, + start=(layout.left, layout.top), + end=(layout.right, layout.top), + lineColor=color, + lineWidth=line_px) + + bottom = Line(win=win, + units=layout.units, + start=(layout.left, layout.bottom), + end=(layout.right, layout.bottom), + lineColor=color, + lineWidth=line_px) + + left = Line(win=win, + units=layout.units, + start=(layout.left, layout.top), + end=(layout.left, layout.bottom), + lineColor=color, + lineWidth=line_px) + right = Line(win=win, + units=layout.units, + start=(layout.right, layout.top), + end=(layout.right, layout.bottom), + lineColor=color, + lineWidth=line_px) + border = [top, right, bottom, left] + for line in border: + print(f"Drawing line from {line.start} to {line.end}") + line.draw() + + +def draw_position(win: visual.Window, + pos: Tuple[float, float], + color: str = 'blue', + size: Union[float, Tuple[float, float]] = 0.025, + name: str = None): + """Draw the provided positions""" + if name: + print(f"Drawing position {name} at {pos}") + circle = Circle(win, pos=pos, color=color, size=size) + circle.draw() + + +def draw_positions(win: visual.Window, + positions: List[Tuple[float, float]], + color: str = 'blue', + size: Union[float, Tuple[float, float]] = 0.025): + """Draw the provided positions""" + for pos in positions: + draw_position(win, pos, color, size) + + +def show_layouts(window: visual.Window): + """Show boundaries for various layouts""" + draw_boundary(window, Layout(), 'red', 5, name='full_screen') + draw_boundary(window, + at_top(window, 0.1), + color='blue', + line_px=5, + name='task_bar') + draw_boundary(window, + centered(width_pct=0.9, height_pct=0.9), + color='green', + line_px=5, + name='main_display') + + window.flip() + + +def show_layout_coords(win: visual.Window): + """Show the points that make up a layout's envelope""" + layout = centered(width_pct=0.9, height_pct=0.9) + layout.parent = win + draw_boundary(win, layout, color='green') + draw_position(win, (layout.left, layout.top), + size=layout.scaled_size(0.025), + name='top_left') + draw_position(win, (layout.right, layout.bottom), name='bottom_right') + + Rect(win, + pos=(layout.left, layout.top), + size=layout.scaled_size(0.05), + lineColor='blue').draw() + Rect(win, + pos=(layout.right, layout.bottom), + size=layout.scaled_size(0.05), + lineColor='blue').draw() + win.flip() + + +def vep_box_quadrant(win: visual.Window, pos: Tuple[float, float], anchor: str, + color: Tuple[str, str], size: Tuple[float, float]): + + pattern1 = GratingStim(win=win, + name=f'2x2-1-{pos}-{anchor}', + tex=None, + pos=pos, + size=size, + sf=1, + phase=0.0, + color=color[0], + colorSpace='rgb', + opacity=1, + texRes=256, + interpolate=True, + depth=-1.0, + anchor=anchor) + pattern2 = GratingStim(win=win, + name=f'2x2-2-{pos}-{anchor}', + tex=None, + pos=pos, + size=size, + sf=1, + phase=0.0, + color=color[1], + colorSpace='rgb', + opacity=1, + texRes=256, + interpolate=True, + depth=-1.0, + anchor=anchor) + border = Rect(win, pos=pos, size=size, lineColor='white', anchor=anchor) + return [pattern1, pattern2, border] + + +def demo_vep(win: visual.Window): + """Demo layout elements for VEP display""" + layout = centered(width_pct=0.9, height_pct=0.9) + layout.parent = win + + box_config = BoxConfiguration(layout, num_boxes=4, height_pct=0.28) + size = box_config.box_size() + positions = box_config.positions + + draw_boundary(win, layout, color='gray', line_px=2) + draw_positions(win, + positions, + color='blue', + size=layout.scaled_size(0.025)) + + vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), + ('orange', 'green'), ('white', 'black'), ('red', 'green')] + colors = ['#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232'] + # draw boxes + anchor_points = ['right_bottom', 'left_bottom', 'left_top', 'right_top'] + + for i, pos in enumerate(positions): + gradient_colors: Tuple[str, str] = vep_colors[i] + + for anchor, color in zip( + anchor_points, + cycle([gradient_colors, + tuple(reversed(gradient_colors))])): + for stim in vep_box_quadrant(win, pos, anchor, color, + layout.scaled_size(0.1)): + stim.draw() + + rect = visual.TextBox2(win, + text=' ', + borderColor=colors[i], + pos=pos, + size=size) + rect.draw() + win.flip() + + +def demo_checkerboard(win: visual.Window): + """Demo checkerboard""" + layout = centered(width_pct=0.9, height_pct=0.9) + layout.parent = win + board = checkerboard(layout, + squares=16, + colors=('red', 'green'), + center=(0, 0), + board_size=layout.scaled_size(0.4)) + for square in board: + Rect(win, + pos=square.pos, + size=square.size, + lineColor='white', + fillColor=square.color).draw() + win.flip() + + +def demo_height_units(win: visual.Window): + """Demo behavior when using height units""" + norm_layout = centered(width_pct=0.85, height_pct=0.85) + draw_boundary(win, norm_layout, line_px=5, color='red') + layout = height_units(win.size) + layout.resize_width(0.85) + layout.resize_height(0.85) + draw_boundary(win, layout, line_px=3, color='green') + + circle = Circle(win, + pos=layout.center, + color='blue', + size=0.025, + units='height') + circle.draw() + rects = [ + Rect(win, + pos=layout.center, + size=layout.scaled_size(0.05), + lineColor='green', + units='height'), + # don't need to scale with height units + Rect(win, + pos=layout.left_top, + size=(0.05, 0.05), + lineColor='green', + units='height'), + # scaling the size should still work + Rect(win, + pos=layout.right_bottom, + size=layout.scaled_size(0.05), + lineColor='green', + units=layout.units) + ] + for rect in rects: + rect.draw() + win.flip() + + +def run(demo: Callable[[visual.Window], None], seconds=30): + """Run the given function for the provided duration. + + Parameters + ---------- + demo - function to run; a Window object is passed to this function. + seconds - Window is closed after this duration. + """ + try: + win = make_window() + print( + f'Displaying window for {seconds}s... (Interrupt [Ctl-C] to stop)\n' + ) + + demo(win) + while True: + time.sleep(seconds) + break + except KeyboardInterrupt: + print('Keyboard Interrupt: Demo stopped') + except Exception as other_exception: + print(f'{other_exception}') + raise other_exception + finally: + win.close() + print('Demo complete.') + + +# run(demo_vep) +# run(demo_height_units) +# run(show_layout_coords) +run(demo_checkerboard) diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py new file mode 100644 index 000000000..e716a706f --- /dev/null +++ b/bcipy/display/paradigm/vep/layout.py @@ -0,0 +1,165 @@ +"""Functionality for computing positions for elements within a VEP display""" + +from itertools import cycle +from math import sqrt +from typing import List, NamedTuple, Optional, Tuple + +from bcipy.display.components.layout import Layout + + +class CheckerboardSquare(NamedTuple): + """Represents a single square within a checkerboard""" + pos: Tuple[float, float] + color: str + size: Tuple[float, float] + + def inverse(self, colors: Tuple[str, str]) -> 'CheckerboardSquare': + """Returns a new CheckerboardSquare whose color is the inverse + of the current one. + + Parameters + ---------- + colors - 2-tuple of color choices; the current square's color + must be included. + """ + assert len(colors) == 2, "Colors must be a 2-tuple" + first, second = colors + color = {first: second, second: first}[self.color] + return CheckerboardSquare(self.pos, color, self.size) + + +def checkerboard(layout: Layout, squares: int, colors: Tuple[str, str], + center: Tuple[float, float], + board_size: Tuple[float, float]) -> List[CheckerboardSquare]: + """Computes positions and colors for squares used to represent a + checkerboard pattern. Returned positions are the center point of + each square + + Parameters + ---------- + layout - layout in which the checkerboard will be rendered. Used for + positioning and scale. + squares - total number of squares in the board; must be a perfect + square (ex. 4, 9, 16, 25) + colors - tuple of color names between which to alternate + center - position of the center point of the board + board_size - size in layout units of the entire checkerboard; square + size will be computed from this. + """ + boxes_per_row = int(sqrt(squares)) + assert boxes_per_row**2 == squares, "Must be a perfect square" + + square_width = board_size[0] / boxes_per_row + square_height = board_size[1] / boxes_per_row + square_size = (square_width, square_height) + center_x, center_y = center + + # find the center position of the left_top square + move_count = int(boxes_per_row / 2) + if squares % 2 == 0: + # with an even number the center is on a vertex; adjust by half a box + move_count -= 0.5 + left = layout.left_of(center_x, square_width * move_count) + top = layout.above(center_y, square_height * move_count) + + # iterate starting at the top left and proceeding in a zig zag + # pattern to correspond with alternating checkerboard colors. + positions = [] + for row in range(boxes_per_row): + if row > 0: + top = layout.below(top, square_height) + for col in range(boxes_per_row): + positions.append((left, top)) + if col < boxes_per_row - 1: + if row % 2 == 0: + left = layout.right_of(left, square_width) + else: + left = layout.left_of(left, square_width) + return [ + CheckerboardSquare(*args) + for args in zip(positions, cycle(colors), cycle([square_size])) + ] + + +class BoxConfiguration(): + """Computes box size and positions for a VEP display. + + In this configuration, there is one row on top and one on the bottom. + + Parameters + ---------- + num_boxes - number of boxes; currently supports 4 or 6. + layout - defines the boundaries within a Window in which the text areas + will be placed + spacing_pct - used to specify spacing between boxes within a row. + row_pct - what percentage of the height each row should use. + """ + + def __init__(self, + layout: Layout, + num_boxes: int, + spacing_pct: Optional[float] = None, + height_pct: float = 0.25): + assert num_boxes == 4 or num_boxes == 6, 'Number of boxes must be 4 or 6' + assert height_pct <= 0.5, "Rows can't take more than 50% of the height" + self.num_boxes = num_boxes + self.layout = layout + + default_spacing = {4: 0.1, 6: 0.05} + if not spacing_pct: + spacing_pct = default_spacing[num_boxes] + self.spacing_pct = spacing_pct + self.height_pct = height_pct + self._row_count = 2 + + def validate(self): + """Validate invariants""" + assert self.num_boxes == 4 or self.num_boxes == 6, 'Number of boxes must be 4 or 6' + assert self.height_pct <= 0.5, "Rows can't take more than 50% of the height" + + def box_size(self, validate: bool = True) -> Tuple[float, float]: + """Computes the size of each box""" + if validate: + self.validate() + number_per_row = self.num_boxes / self._row_count + + # left and right boxes go to the edges, with a space between each box + spaces_per_row = number_per_row - 1 + + total_box_width_pct = 1 - (self.spacing_pct * spaces_per_row) + width_pct = (total_box_width_pct / number_per_row) + + width = self.layout.width * width_pct + height = self.layout.height * self.height_pct + + return (width, height) + + @property + def units(self) -> str: + """Position units""" + return self.layout.units + + @property + def positions(self) -> List[Tuple]: + """Computes positions for text areas which contain symbols. Boxes are + positioned in the corners for 4 elements. With 6 there are also areas + in the middle. + """ + self.validate() + + # size = box_size(num, layout, spacing_pct) + width, height = self.box_size(validate=False) + + layout = self.layout + top = layout.below(layout.top, (height / 2)) + bottom = layout.above(layout.bottom, (height / 2)) + + left = layout.right_of(layout.left, width / 2) + right = layout.left_of(layout.right, width / 2) + + positions = [(left, top), (right, top), (left, bottom), + (right, bottom)] + if self.num_boxes == 6: + positions += [(layout.horizontal_middle, top), + (layout.horizontal_middle, bottom)] + return positions \ No newline at end of file From da9ad0f4aa45a573970426342caea682317e52a1 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 19 Sep 2023 14:41:00 -0700 Subject: [PATCH 091/330] Updated VEP layout to use the new calculated position information --- .../display/demo/vep/demo_calibration_vep.py | 30 ++- bcipy/display/paradigm/vep/display.py | 189 +++++++++++++----- 2 files changed, 163 insertions(+), 56 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index de47ea459..e26bb1838 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -1,8 +1,10 @@ from psychopy import core, visual from bcipy.display import InformationProperties, VEPStimuliProperties +from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.vep.display import VEPDisplay +from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock info = InformationProperties( @@ -13,10 +15,8 @@ info_text=['VEP Display Demo'], ) -task_text = ['1/4', '2/4', '3/4', '4/4'] -task_color = [['white'], ['white'], ['white'], ['white']] -num_boxes = 4 -start_positions_for_boxes = [(-.3, -.3), (.3, -.3), (.3, .3), (-.3, .3)] +task_text = ['1/4'] #, '2/4', '3/4', '4/4'] +num_boxes = 6 win = visual.Window(size=[700, 700], fullscr=False, @@ -34,11 +34,18 @@ print(f'Monitor refresh rate: {frameRate} Hz') +start_positions_for_boxes = [(-.3, -.3), (.3, -.3), (.3, .3), (-.3, .3)] + +box_colors = ['#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232'] +stim_color = [[color] for i, color in enumerate(box_colors) if i < num_boxes] + +box_config = BoxConfiguration(layout=centered(width_pct=0.95, height_pct=0.80), num_boxes=num_boxes) + experiment_clock = Clock() len_stimuli = 10 stimuli = VEPStimuliProperties( - stim_color=[['blue'], ['purple'], ['red'], ['green']], - stim_pos=start_positions_for_boxes, + stim_color = stim_color, + stim_pos=box_config.positions, stim_height=0.1, stim_font='Arial', timing=(1, 0.5, 4), # prompt, fixation, stimuli @@ -48,15 +55,18 @@ inquiry_count=4, current_index=0, font='Arial') -vep = VEPDisplay(win, experiment_clock, stimuli, task_bar, info) +vep = VEPDisplay(win, experiment_clock, stimuli, task_bar, info, box_config=box_config) timing = [] wait_seconds = 2 # loop over the text and colors, present the stimuli and record the timing -for (txt, color) in zip(task_text, task_color): +for txt in task_text: vep.update_task_bar(txt) - vep.schedule_to([['A', 'B'], ['Z'], ['P'], ['R', 'W']], [1, 0.5, 5], - [['blue'], ['purple'], ['red'], ['green']]) + if num_boxes == 4: + stim = [['A', 'B'], ['Z'], ['P'], ['R', 'W']] + if num_boxes == 6: + stim = [['A'], ['B'], ['Z'], ['P'], ['R'], ['W']] + vep.schedule_to(stim, [1, 0.5, 5], stim_color) timing += vep.do_inquiry() # show the wait screen, this will only happen once diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 5b7cb1c5b..125ae8a67 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -1,4 +1,5 @@ import logging +from itertools import cycle from typing import List, Tuple import numpy as np @@ -8,9 +9,11 @@ from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, VEPStimuliProperties) from bcipy.display.components.task_bar import TaskBar +from bcipy.display.paradigm.vep.layout import (BoxConfiguration, + CheckerboardSquare, + checkerboard) from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import get_fixation, resize_image -from bcipy.helpers.symbols import SPACE_CHAR from bcipy.helpers.triggers import TriggerCallback, _calibration_trigger @@ -26,6 +29,8 @@ def create_vep_codes(length=32, count=4) -> List[List[int]]: return [np.random.randint(2, size=length) for _ in range(count)] + + class VEPBox: """A class to represent a VEP box. @@ -57,15 +62,16 @@ def __init__( task_bar: TaskBar, info: InformationProperties, trigger_type: str = 'text', - codes: List[int] = None): + codes: List[int] = None, + box_config: BoxConfiguration = None): self.window = window self.window_size = self.window.size # [w, h] self.refresh_rate = round(window.getActualFrameRate()) self.logger = logging.getLogger(__name__) - # number of VEP text areas; TODO: make this configurable - self.vep_type = 4 + # number of VEP text areas + self.vep_type = box_config.num_boxes # Stimuli parameters, these are set on display in order to allow # easy updating after definition @@ -104,9 +110,18 @@ def __init__( if not codes: codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] - vep_box_size = .1 - self.vep = self._build_vep_corner_stimuli(self.stimuli_pos, codes, vep_colors, vep_box_size) - self.text_boxes = self._build_text_boxes(vep_box_size) + + # vep_box_size = box_config.layout.scaled_size(0.1, self.window_size) + # self.vep = self._build_vep_corner_stimuli(box_config.positions, codes, vep_colors, vep_box_size) + + vep_stim_size = box_config.layout.scaled_size(0.2, self.window_size) + self.vep = self.build_vep_stimuli(box_config=box_config, + codes=codes, + colors=cycle(vep_colors), + stim_size=vep_stim_size, + num_squares=25) + + self.text_boxes = self._build_text_boxes(box_config) self.animation_duration = 2 @@ -272,22 +287,114 @@ def _build_inquiry_stimuli(self) -> None: return self.sti + def grating_stim(self, square: CheckerboardSquare) -> GratingStim: + """Construct a grating stim from a checkerboard square""" + return GratingStim(win=self.window, + name=f"{square.color} square at {square.pos}", + tex=None, + pos=square.pos, + size=square.size, + sf=1, + phase=0.0, + color=square.color, + colorSpace='rgb', + opacity=1, + texRes=256, + interpolate=True, + depth=-1.0) + + def build_vep_stimuli(self, + box_config: BoxConfiguration, + codes: List[int], + colors: List[Tuple[str]], + stim_size: Tuple[float, float], + num_squares: int = 25) -> List[VEPBox]: + """Build the VEP flashing checkerboard squares""" + stim = [] + for pos, code, color in zip(box_config.positions, codes, colors): + board = checkerboard(box_config.layout, + squares=num_squares, + colors=color, + center=pos, + board_size=stim_size) + for square in board: + pattern1 = self.grating_stim(square) + pattern2 = self.grating_stim(square.inverse(color)) + stim.append(VEPBox(flicker=[pattern1, pattern2], code=code)) + return stim + def _build_vep_corner_stimuli( self, - pos: Tuple[float, float], + positions: List[Tuple[float, float]], codes: List[int], colors: List[Tuple[str]], - box_size: float) -> List[VEPBox]: + box_size: Tuple[float, float]) -> List[VEPBox]: """Build the corner stimuli for the VEP. Args: window: psychopy window object """ - corner_stim = [] - for pos, code, color in zip(pos, codes, colors): - corner_stim += self._build_2x2_vep_grid(pos, box_size, color, code) + stim = [] + + for pos, code, color in zip(positions, codes, colors): + # border = Rect(self.window, pos=pos, size=box_size, lineColor='white', anchor=anchor) + stim.extend(self.build_vep_grid(pos, color, + box_size, code)) + return stim + # corner_stim = [] + # for pos, code, color in zip(pos, codes, colors): + # corner_stim += self._build_2x2_vep_grid(pos, box_size, color, code) + + # return corner_stim - return corner_stim + def build_vep_grid(self, pos: Tuple[float, float], + color: Tuple[str, str], size: Tuple[float, float], code: List[int]) -> List[VEPBox]: + """Build a 2x2 VEP grid. + + Args: + position: center position of the flickering box + size: size of the box + color: colors that the box will alternate between + code: specifies the flicker pattern + + Returns: + list of VEPBox objects, each of which represents a box in a grid.""" + anchor_points = ['right_bottom', 'left_bottom', 'left_top', 'right_top'] + quadrants = [] + for anchor, color in zip( + anchor_points, + cycle([color, + tuple(reversed(color))])): + pattern1 = GratingStim(win=self.window, + name=f'2x2-1-{pos}-{anchor}', + tex=None, + pos=pos, + size=size, + sf=1, + phase=0.0, + color=color[0], + colorSpace='rgb', + opacity=1, + texRes=256, + interpolate=True, + depth=-1.0, + anchor=anchor) + pattern2 = GratingStim(win=self.window, + name=f'2x2-2-{pos}-{anchor}', + tex=None, + pos=pos, + size=size, + sf=1, + phase=0.0, + color=color[1], + colorSpace='rgb', + opacity=1, + texRes=256, + interpolate=True, + depth=-1.0, + anchor=anchor) + quadrants.append(VEPBox(flicker=[pattern1, pattern2], code=code)) + return quadrants def _build_1x1_vep_grid( self, @@ -389,40 +496,30 @@ def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]], color self.stimuli_timing = timing assert colors is None or colors == self.stimuli_colors, "Colors must match the pre-configured values" - def _build_text_boxes(self, vep_box_size: float) -> List[visual.TextBox2]: - """Build the text boxes for the experiment. - - This assumes that vep_type is 4 using a 2x2 grid. Additional configurations can be added in the future. + def _build_text_boxes(self, box_config: BoxConfiguration) -> List[visual.TextBox2]: + """Build the text boxes for the experiment. These are the areas into + which the symbols are partitioned. Each text_box will have an + associated VEP Box. """ - text_boxes = [] - inc_q = int(self.vep_type / 2) - size = vep_box_size * inc_q - inc = 0 # get the last box in the grating stim per vep - for i, color in enumerate(self.stimuli_colors): - text = ' ' - first = self.vep[inc].flicker[0].pos - best_neighbor = self.vep[inc + inc_q].flicker[0].pos - - # the textbox requires the pos to be centered on the middle of the box, so - # we need to calculate the center of the vep stimulus boxes - pos = (first[0] + best_neighbor[0]) / 2, (first[1] + best_neighbor[1]) / 2 - print(f"Position of {color} text area (#{i}): {pos}") - text_boxes += [visual.TextBox2( - win=self.window, - text=text, - font=self.stimuli_font, - units='height', - pos=pos, - color=color[0], - colorSpace='rgb', - size=[size, size], - alignment='center', - anchor='center', - borderWidth=2, - borderColor=color, - letterHeight=self.stimuli_height / 2)] - inc += self.vep_type - return text_boxes + positions = box_config.positions + size = box_config.box_size() + return [ + visual.TextBox2(win=self.window, + text=" ", + font=self.stimuli_font, + pos=pos, + units=box_config.units, + color=color, + colorSpace='rgb', + size=size, + alignment='center', + anchor='center', + borderWidth=2, + borderColor=color, + letterHeight=self.stimuli_height) + for pos, color in zip(positions, cycle(self.stimuli_colors)) + ] + def _reset_text_boxes(self) -> None: """Reset text boxes. From 9be5b0640a110dc746d0759c08869c366cdccc17 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 20 Sep 2023 11:18:28 -0700 Subject: [PATCH 092/330] Code cleanup; clarified the use of timing parameters --- bcipy/display/demo/components/demo_layouts.py | 10 +- .../display/demo/vep/demo_calibration_vep.py | 6 +- bcipy/display/paradigm/vep/display.py | 211 +++--------------- 3 files changed, 39 insertions(+), 188 deletions(-) diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index e115950f7..077a138ea 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -163,7 +163,7 @@ def demo_vep(win: visual.Window): layout = centered(width_pct=0.9, height_pct=0.9) layout.parent = win - box_config = BoxConfiguration(layout, num_boxes=4, height_pct=0.28) + box_config = BoxConfiguration(layout, num_boxes=6, height_pct=0.28) size = box_config.box_size() positions = box_config.positions @@ -204,10 +204,10 @@ def demo_checkerboard(win: visual.Window): layout = centered(width_pct=0.9, height_pct=0.9) layout.parent = win board = checkerboard(layout, - squares=16, + squares=25, colors=('red', 'green'), center=(0, 0), - board_size=layout.scaled_size(0.4)) + board_size=layout.scaled_size(0.6)) for square in board: Rect(win, pos=square.pos, @@ -284,7 +284,7 @@ def run(demo: Callable[[visual.Window], None], seconds=30): print('Demo complete.') -# run(demo_vep) +run(demo_vep) # run(demo_height_units) # run(show_layout_coords) -run(demo_checkerboard) +# run(demo_checkerboard) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index e26bb1838..769fa211c 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -16,7 +16,7 @@ ) task_text = ['1/4'] #, '2/4', '3/4', '4/4'] -num_boxes = 6 +num_boxes = 4 win = visual.Window(size=[700, 700], fullscr=False, @@ -48,7 +48,7 @@ stim_pos=box_config.positions, stim_height=0.1, stim_font='Arial', - timing=(1, 0.5, 4), # prompt, fixation, stimuli + timing=(1, 0.5, 2, 4), # prompt, fixation, stimuli stim_length=1, # how many times to stimuli ) task_bar = CalibrationTaskBar(win, @@ -66,7 +66,7 @@ stim = [['A', 'B'], ['Z'], ['P'], ['R', 'W']] if num_boxes == 6: stim = [['A'], ['B'], ['Z'], ['P'], ['R'], ['W']] - vep.schedule_to(stim, [1, 0.5, 5], stim_color) + vep.schedule_to(stimuli=stim) timing += vep.do_inquiry() # show the wait screen, this will only happen once diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 125ae8a67..e4d1d8e85 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -5,6 +5,7 @@ import numpy as np from psychopy import core, visual from psychopy.visual.grating import GratingStim +from psychopy.visual.rect import Rect from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, VEPStimuliProperties) @@ -29,8 +30,6 @@ def create_vep_codes(length=32, count=4) -> List[List[int]]: return [np.random.randint(2, size=length) for _ in range(count)] - - class VEPBox: """A class to represent a VEP box. @@ -67,7 +66,7 @@ def __init__( self.window = window self.window_size = self.window.size # [w, h] self.refresh_rate = round(window.getActualFrameRate()) - + print(f"Refresh rate: {self.refresh_rate}") self.logger = logging.getLogger(__name__) # number of VEP text areas @@ -77,7 +76,7 @@ def __init__( # easy updating after definition self.stimuli_inquiry = stimuli.stim_inquiry self.stimuli_colors = stimuli.stim_colors - self.stimuli_timing = stimuli.stim_timing + self.timing_prompt, self.timing_fixation, self.timing_animation, self.timing_stimuli = stimuli.stim_timing self.stimuli_font = stimuli.stim_font self.stimuli_height = stimuli.stim_height self.stimuli_pos = stimuli.stim_pos @@ -110,20 +109,15 @@ def __init__( if not codes: codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] - - # vep_box_size = box_config.layout.scaled_size(0.1, self.window_size) - # self.vep = self._build_vep_corner_stimuli(box_config.positions, codes, vep_colors, vep_box_size) - vep_stim_size = box_config.layout.scaled_size(0.2, self.window_size) self.vep = self.build_vep_stimuli(box_config=box_config, codes=codes, colors=cycle(vep_colors), stim_size=vep_stim_size, - num_squares=25) + num_squares=4) self.text_boxes = self._build_text_boxes(box_config) - self.animation_duration = 2 def check_configuration(self): """Check that configured properties are consistent""" @@ -139,7 +133,7 @@ def do_fixation(self) -> None: self.fixation.draw() self.draw_static() self.window.flip() - core.wait(self.stimuli_timing[1]) + core.wait(self.timing_fixation) def do_inquiry(self) -> List[float]: """Do the inquiry.""" @@ -178,7 +172,7 @@ def animate_inquiry(self) -> List[float]: self._build_inquiry_stimuli() self.static_clock.reset() - while self.static_clock.getTime() < self.animation_duration: + while self.static_clock.getTime() < self.timing_animation: self.draw_boxes() self.draw_animation() self.draw_static() @@ -193,7 +187,7 @@ def animate_inquiry(self) -> List[float]: 'VEP_INQUIRY') # display the inquiry self.static_clock.reset() - while self.static_clock.getTime() < self.stimuli_timing[0]: + while self.static_clock.getTime() < self.timing_prompt: self.draw_boxes() self.draw_static() self.window.flip() @@ -213,19 +207,21 @@ def draw_boxes(self) -> None: box.draw() def stimulate(self) -> List[float]: - """Stimulate. - - This is the main display function of the VEP paradigm. It is responsible for drawing the flickering stimuli. + """ + This is the main display function of the VEP paradigm. It is + responsible for drawing the flickering stimuli. - It assumes that the VEP stimuli are already constructed using the _build_vep_corner_stimuli function. - These boxes are drawn in the order they are in the list as defined in self.vep.""" + It assumes that the VEP stimuli are already constructed. These boxes + are drawn in the order they are in the list as defined in self.vep. + """ self.trigger_callback.reset() self.window.callOnFlip( self.trigger_callback.callback, self.experiment_clock, 'VEP_STIMULATE') self.static_clock.reset() - while self.static_clock.getTime() < self.stimuli_timing[-1]: + while self.static_clock.getTime() < self.timing_stimuli: + # TODO: check exit condition within the for loop for frame in range(self.refresh_rate): for box in self.vep: if box.code[frame] == 1: @@ -234,8 +230,12 @@ def stimulate(self) -> List[float]: box.frame_off() # flicker! + self.draw_boxes() self.draw_static() self.window.flip() + self.logger.debug( + f"Stimulate expected run time: {self.timing_stimuli}; actual run time: {self.static_clock.getTime()}" + ) return self.trigger_callback.timing @@ -248,15 +248,12 @@ def draw_static(self) -> None: info.draw() def update_task_bar(self, text: str = ''): - """Update Task. - - Update any task related display items not related to the inquiry. Ex. stimuli count 1/200. + """Update any task related display items not related to the inquiry. + Ex. stimuli count 1/200. - PARAMETERS: - - text: text for task - color_list: list of the colors for each stimuli - pos: position of task + Parameters + ---------- + text - text for task """ if self.task_bar: self.task_bar.update(text) @@ -287,8 +284,8 @@ def _build_inquiry_stimuli(self) -> None: return self.sti - def grating_stim(self, square: CheckerboardSquare) -> GratingStim: - """Construct a grating stim from a checkerboard square""" + def vep_square_stim(self, square: CheckerboardSquare) -> GratingStim: + """Construct a stim from a checkerboard square""" return GratingStim(win=self.window, name=f"{square.color} square at {square.pos}", tex=None, @@ -308,7 +305,7 @@ def build_vep_stimuli(self, codes: List[int], colors: List[Tuple[str]], stim_size: Tuple[float, float], - num_squares: int = 25) -> List[VEPBox]: + num_squares: int) -> List[VEPBox]: """Build the VEP flashing checkerboard squares""" stim = [] for pos, code, color in zip(box_config.positions, codes, colors): @@ -318,157 +315,11 @@ def build_vep_stimuli(self, center=pos, board_size=stim_size) for square in board: - pattern1 = self.grating_stim(square) - pattern2 = self.grating_stim(square.inverse(color)) + pattern1 = self.vep_square_stim(square) + pattern2 = self.vep_square_stim(square.inverse(color)) stim.append(VEPBox(flicker=[pattern1, pattern2], code=code)) return stim - def _build_vep_corner_stimuli( - self, - positions: List[Tuple[float, float]], - codes: List[int], - colors: List[Tuple[str]], - box_size: Tuple[float, float]) -> List[VEPBox]: - """Build the corner stimuli for the VEP. - - Args: - window: psychopy window object - """ - stim = [] - - for pos, code, color in zip(positions, codes, colors): - # border = Rect(self.window, pos=pos, size=box_size, lineColor='white', anchor=anchor) - stim.extend(self.build_vep_grid(pos, color, - box_size, code)) - return stim - # corner_stim = [] - # for pos, code, color in zip(pos, codes, colors): - # corner_stim += self._build_2x2_vep_grid(pos, box_size, color, code) - - # return corner_stim - - def build_vep_grid(self, pos: Tuple[float, float], - color: Tuple[str, str], size: Tuple[float, float], code: List[int]) -> List[VEPBox]: - """Build a 2x2 VEP grid. - - Args: - position: center position of the flickering box - size: size of the box - color: colors that the box will alternate between - code: specifies the flicker pattern - - Returns: - list of VEPBox objects, each of which represents a box in a grid.""" - anchor_points = ['right_bottom', 'left_bottom', 'left_top', 'right_top'] - quadrants = [] - for anchor, color in zip( - anchor_points, - cycle([color, - tuple(reversed(color))])): - pattern1 = GratingStim(win=self.window, - name=f'2x2-1-{pos}-{anchor}', - tex=None, - pos=pos, - size=size, - sf=1, - phase=0.0, - color=color[0], - colorSpace='rgb', - opacity=1, - texRes=256, - interpolate=True, - depth=-1.0, - anchor=anchor) - pattern2 = GratingStim(win=self.window, - name=f'2x2-2-{pos}-{anchor}', - tex=None, - pos=pos, - size=size, - sf=1, - phase=0.0, - color=color[1], - colorSpace='rgb', - opacity=1, - texRes=256, - interpolate=True, - depth=-1.0, - anchor=anchor) - quadrants.append(VEPBox(flicker=[pattern1, pattern2], code=code)) - return quadrants - - def _build_1x1_vep_grid( - self, - position: Tuple[float], - size: float, - color: str, - code: List[int]) -> List[VEPBox]: - """Build a 1x1 VEP grid. - - Args: - position: position of the flicking box - size: size of the flicking box - color: color of the flicking box - code: code to be used with the flicking box - - Returns: - list of GratingStim objects - - """ - assert len(code) >= self.refresh_rate, 'Code must be longer than refresh rate' - pattern1 = GratingStim(win=self.window, name=f'1x1-1-{position}', units='height', - tex=None, mask=None, - ori=0, pos=position, size=size, sf=1, phase=0.0, - color=color[0], colorSpace='rgb', opacity=1, - texRes=256, interpolate=True, depth=-1.0) - pattern2 = GratingStim(win=self.window, name=f'1x1-2-{position}', units='height', - tex=None, mask=None, - ori=0, pos=position, size=size, sf=1, phase=0, - color=color[1], colorSpace='rgb', opacity=1, - texRes=256, interpolate=True, depth=-2.0) - box = [VEPBox(flicker=[pattern1, pattern2], code=code)] - return box - - def _build_2x2_vep_grid(self, - position: Tuple[float], - size: float, - color: str, - code: List[int]) -> List[VEPBox]: - """Build a 2x2 VEP grid. - - Args: - position: position of the flicking box - size: size of the flicking box - color: color of the flicking box - code: code to be used with the flicking box - - Returns: - list of GratingStim objects - """ - - assert len(code) >= self.refresh_rate, 'Code must be longer than refresh rate' - starting_position = position - positions = [ - starting_position, # bottom left - [starting_position[0] + size, starting_position[1]], # bottom right - [starting_position[0] + size, starting_position[1] + size], # top right - [starting_position[0], starting_position[1] + size], # top left - ] - box = [] - for pos in positions: - pattern1 = GratingStim(win=self.window, name=f'2x2-1-{pos}', units='height', - tex=None, mask=None, - ori=0, pos=pos, size=size, sf=1, phase=0.0, - color=color[0], colorSpace='rgb', opacity=1, - texRes=256, interpolate=True, depth=-1.0) - pattern2 = GratingStim(win=self.window, name=f'2x2-2-{pos}', units='height', - tex=None, mask=None, - ori=0, pos=pos, size=size, sf=1, phase=0, - color=color[1], colorSpace='rgb', opacity=1, - texRes=256, interpolate=True, depth=-2.0) - color = (color[1], color[0]) - box += [VEPBox(flicker=[pattern1, pattern2], code=code)] - - return box def _trigger_pulse(self) -> None: """Trigger Pulse. @@ -489,11 +340,11 @@ def _trigger_pulse(self) -> None: self.first_stim_time = calibration_time[-1] self.first_run = False - def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]], colors: List[List[str]]) -> None: + def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]]=None, colors: List[List[str]]=None) -> None: """Schedule stimuli elements (works as a buffer). """ self.stimuli_inquiry = stimuli - self.stimuli_timing = timing + assert timing is None or timing == self.stimuli_timing, "Timing values must match pre-configured values" assert colors is None or colors == self.stimuli_colors, "Colors must match the pre-configured values" def _build_text_boxes(self, box_config: BoxConfiguration) -> List[visual.TextBox2]: From b7efdacb5df718c6bd2afce51528c143b6975206 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Sep 2023 11:14:05 -0700 Subject: [PATCH 093/330] Refactored VEP display to put the details of which visual stim is used as the responsibility of a VEPStim object. Added some debugging to report on stim timing --- bcipy/display/paradigm/vep/display.py | 83 +++++++++++++++++++-------- 1 file changed, 59 insertions(+), 24 deletions(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index e4d1d8e85..dccdd087b 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -30,25 +30,64 @@ def create_vep_codes(length=32, count=4) -> List[List[int]]: return [np.random.randint(2, size=length) for _ in range(count)] -class VEPBox: - """A class to represent a VEP box. - - Attributes: - flicker: A list of two GratingStim objects, one for on and one for off. - code: A list of integers representing the VEP code for this box. +class VEPStim: + """Represents a checkerboard of squares that can be flashed at a rate. + Flashing is accomplished by inverting the colors of each square. + + Parameters + ---------- + window - used to build the stimulus + code - A list of integers representing the VEP code for each box + squares - list of CheckerboardSquares with a defined position + and size """ - def __init__(self, flicker: List[Tuple[GratingStim, GratingStim]], code: List[int]) -> None: - self.flicker = flicker + def __init__(self, window: visual.Window, code: List[int], + squares: List[CheckerboardSquare]): + self.window = window self.code = code + self.colors = squares[0].color, squares[1].color + self.squares = squares + self.stim = self.build_stim(squares[0]) + + self.on_stim = [self.build_stim(square) for square in self.squares] + self.off_stim = [ + self.build_stim(square.inverse(self.colors)) + for square in self.squares + ] + + def build_stim(self, square: CheckerboardSquare) -> GratingStim: + """Constructs a single re-usable stim""" + return GratingStim(win=self.window, + tex=None, + pos=square.pos, + size=square.size, + sf=1, + phase=0.0, + color=square.color, + colorSpace='rgb', + opacity=1, + texRes=256, + interpolate=True, + depth=-1.0) + + def render_frame(self, frame: int) -> None: + """Render a given frame number, where frame refers to a code index""" + if self.code[frame] == 1: + self.frame_on() + else: + self.frame_off() def frame_on(self) -> None: - """Frame On. Draw the frame for the first grating stim on the screen.""" - self.flicker[0].draw() + """Each square is set to a starting color and draw.""" + for stim in self.on_stim: + stim.draw() def frame_off(self) -> None: - """Frame Off. Draw the frame for the second grating stim on the screen.""" - self.flicker[1].draw() + """Invert each square from its starting color and draw.""" + for stim in self.off_stim: + stim.draw() + class VEPDisplay(Display): @@ -220,19 +259,18 @@ def stimulate(self) -> List[float]: self.experiment_clock, 'VEP_STIMULATE') self.static_clock.reset() + first_frame = True while self.static_clock.getTime() < self.timing_stimuli: - # TODO: check exit condition within the for loop for frame in range(self.refresh_rate): - for box in self.vep: - if box.code[frame] == 1: - box.frame_on() - else: - box.frame_off() + for stim in self.vep: + stim.render_frame(frame) - # flicker! self.draw_boxes() self.draw_static() self.window.flip() + if first_frame: + first_frame = False + print(f"Frame duration: {self.static_clock.getTime()}") self.logger.debug( f"Stimulate expected run time: {self.timing_stimuli}; actual run time: {self.static_clock.getTime()}" ) @@ -305,7 +343,7 @@ def build_vep_stimuli(self, codes: List[int], colors: List[Tuple[str]], stim_size: Tuple[float, float], - num_squares: int) -> List[VEPBox]: + num_squares: int) -> List[VEPStim]: """Build the VEP flashing checkerboard squares""" stim = [] for pos, code, color in zip(box_config.positions, codes, colors): @@ -314,10 +352,7 @@ def build_vep_stimuli(self, colors=color, center=pos, board_size=stim_size) - for square in board: - pattern1 = self.vep_square_stim(square) - pattern2 = self.vep_square_stim(square.inverse(color)) - stim.append(VEPBox(flicker=[pattern1, pattern2], code=code)) + stim.append(VEPStim(self.window, code, board)) return stim From ae68d968effe994c11fc529446e963e0343f7539 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Sep 2023 11:17:04 -0700 Subject: [PATCH 094/330] Added layout code for computing the envelope of a shape; proof of concept demo for constructing a complex polygon with holes that may be used to generate a checkerboard using fewer visual stim. --- bcipy/display/components/layout.py | 46 ++++++-- bcipy/display/demo/components/demo_layouts.py | 109 +++++++++--------- bcipy/display/paradigm/vep/layout.py | 6 + 3 files changed, 100 insertions(+), 61 deletions(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index b83675afa..40815df66 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -1,6 +1,6 @@ """Defines common functionality for GUI layouts.""" from enum import Enum -from typing import Optional, Protocol, Tuple +from typing import List, Optional, Protocol, Tuple class Container(Protocol): @@ -8,6 +8,7 @@ class Container(Protocol): size: Tuple[float, float] units: str + # for norm units DEFAULT_LEFT = -1.0 DEFAULT_TOP = 1.0 @@ -56,11 +57,13 @@ def __init__(self, def check_invariants(self): """Check that all invariants hold true.""" # https://psychopy.org/general/units.html#units - assert self.units in ['height', 'norm'], "Units must be 'height' or 'norm'" + assert self.units in ['height', + 'norm'], "Units must be 'height' or 'norm'" if self.units == "norm": assert (0.0 <= self.height <= 2.0), "Height must be in norm units." assert (0.0 <= self.width <= 2.0), "Width must be in norm units." - assert (-1.0 <= self.top <= 1.0), "Top must be a y-value in norm units" + assert (-1.0 <= self.top <= + 1.0), "Top must be a y-value in norm units" assert (-1.0 <= self.left <= 1.0), "Left must be an x-value in norm units" assert (-1.0 <= self.bottom <= @@ -68,9 +71,12 @@ def check_invariants(self): assert (-1.0 <= self.right <= 1.0), "Right must be an x-value in norm units" if self.units == "height": - assert (0.0 <= self.height <= 1.0), "Height must be in height units." - assert (-0.5 <= self.top <= 0.5), "Top must be a y-value in height units" - assert (-0.5 <= self.bottom <= 0.5), "Bottom must be a y-value in height units" + assert (0.0 <= self.height <= + 1.0), "Height must be in height units." + assert (-0.5 <= self.top <= + 0.5), "Top must be a y-value in height units" + assert (-0.5 <= self.bottom <= + 0.5), "Bottom must be a y-value in height units" if self.parent: assert 0 < self.width <= self.parent.size[ @@ -78,8 +84,12 @@ def check_invariants(self): assert 0 < self.height <= self.parent.size[ 1], "Height must be greater than 0 and fit within the parent height." - def scaled_size(self, height: float, window_size: Optional[Tuple[float, float]] = None) -> Tuple[float, float]: - """Returns the value scaled to reflect the aspect ratio of a + def scaled_size( + self, + height: float, + window_size: Optional[Tuple[float, + float]] = None) -> Tuple[float, float]: + """Returns the (w,h ) value scaled to reflect the aspect ratio of a visual.Window. Used for creating squared stimulus""" if self.units == 'height': width = height @@ -281,6 +291,20 @@ def centered(width_pct: float = 1.0, height_pct: float = 1.0) -> Layout: container.resize_height(height_pct, alignment=Alignment.CENTERED) return container + +def envelope(layout: Layout, pos: Tuple[float, float], + size: Tuple[float, float]) -> List[Tuple[float, float]]: + """Compute the vertices for the envelope of a shape centered at pos with + the given size.""" + width, height = size + half_w = width / 2 + half_h = height / 2 + return [(layout.left_of(pos[0], half_w), layout.above(pos[1], half_h)), + (layout.right_of(pos[0], half_w), layout.above(pos[1], half_h)), + (layout.right_of(pos[0], half_w), layout.below(pos[1], half_h)), + (layout.left_of(pos[0], half_w), layout.below(pos[1], half_h))] + + def height_units(window_size: Tuple[float, float]): """Constructs a layout with height units using the given Window dimensions @@ -292,4 +316,8 @@ def height_units(window_size: Tuple[float, float]): """ win_width, win_height = window_size right = (win_width / win_height) / 2 - return Layout(left=-right, top=0.5, right=right, bottom=-0.5, units='height') + return Layout(left=-right, + top=0.5, + right=right, + bottom=-0.5, + units='height') diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index 077a138ea..de0476bc0 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -1,16 +1,15 @@ """Useful for viewing computed positions in a window""" import time -from itertools import cycle from typing import Callable, List, Tuple, Union from psychopy import visual from psychopy.visual.circle import Circle -from psychopy.visual.grating import GratingStim from psychopy.visual.line import Line from psychopy.visual.rect import Rect +from psychopy.visual.shape import ShapeStim from bcipy.display.components.layout import (Layout, at_top, centered, - height_units) + envelope, height_units) from bcipy.display.paradigm.vep.layout import BoxConfiguration, checkerboard @@ -123,47 +122,12 @@ def show_layout_coords(win: visual.Window): win.flip() -def vep_box_quadrant(win: visual.Window, pos: Tuple[float, float], anchor: str, - color: Tuple[str, str], size: Tuple[float, float]): - - pattern1 = GratingStim(win=win, - name=f'2x2-1-{pos}-{anchor}', - tex=None, - pos=pos, - size=size, - sf=1, - phase=0.0, - color=color[0], - colorSpace='rgb', - opacity=1, - texRes=256, - interpolate=True, - depth=-1.0, - anchor=anchor) - pattern2 = GratingStim(win=win, - name=f'2x2-2-{pos}-{anchor}', - tex=None, - pos=pos, - size=size, - sf=1, - phase=0.0, - color=color[1], - colorSpace='rgb', - opacity=1, - texRes=256, - interpolate=True, - depth=-1.0, - anchor=anchor) - border = Rect(win, pos=pos, size=size, lineColor='white', anchor=anchor) - return [pattern1, pattern2, border] - - def demo_vep(win: visual.Window): """Demo layout elements for VEP display""" layout = centered(width_pct=0.9, height_pct=0.9) layout.parent = win - box_config = BoxConfiguration(layout, num_boxes=6, height_pct=0.28) + box_config = BoxConfiguration(layout, num_boxes=4, height_pct=0.28) size = box_config.box_size() positions = box_config.positions @@ -176,19 +140,20 @@ def demo_vep(win: visual.Window): vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green'), ('white', 'black'), ('red', 'green')] colors = ['#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232'] - # draw boxes - anchor_points = ['right_bottom', 'left_bottom', 'left_top', 'right_top'] for i, pos in enumerate(positions): - gradient_colors: Tuple[str, str] = vep_colors[i] - - for anchor, color in zip( - anchor_points, - cycle([gradient_colors, - tuple(reversed(gradient_colors))])): - for stim in vep_box_quadrant(win, pos, anchor, color, - layout.scaled_size(0.1)): - stim.draw() + color_tup: Tuple[str, str] = vep_colors[i] + board = checkerboard(layout, + squares=16, + colors=color_tup, + center=pos, + board_size=layout.scaled_size(0.2)) + for square in board: + Rect(win, + pos=square.pos, + size=square.size, + lineColor='white', + fillColor=square.color).draw() rect = visual.TextBox2(win, text=' ', @@ -204,7 +169,7 @@ def demo_checkerboard(win: visual.Window): layout = centered(width_pct=0.9, height_pct=0.9) layout.parent = win board = checkerboard(layout, - squares=25, + squares=16, colors=('red', 'green'), center=(0, 0), board_size=layout.scaled_size(0.6)) @@ -256,6 +221,45 @@ def demo_height_units(win: visual.Window): win.flip() +def demo_checkerboard2(win: visual.Window): + """Demo checkerboard rendered using a complex shapestim""" + layout = centered(width_pct=0.9, height_pct=0.9) + layout.parent = win + + board_pos = (0, 0) + board_size = layout.scaled_size(0.6) + + colors = ('red', 'green') + board = checkerboard(layout, + squares=25, + colors=colors, + center=board_pos, + board_size=board_size) + board_boundaries = envelope(layout, pos=board_pos, size=board_size) + + evens = [] + odds = [] + for square in board: + square_boundary = envelope(layout, pos=square.pos, size=square.size) + if square.color == colors[0]: + evens.append(square_boundary) + else: + odds.append(square_boundary) + + rect = ShapeStim(win, + lineColor='green', + fillColor='green', + vertices=board_boundaries) + rect.draw() + stim = ShapeStim(win, + lineWidth=0, + fillColor=colors[0], + closeShape=True, + vertices=[board_boundaries, *evens]) + stim.draw() + win.flip() + + def run(demo: Callable[[visual.Window], None], seconds=30): """Run the given function for the provided duration. @@ -284,7 +288,8 @@ def run(demo: Callable[[visual.Window], None], seconds=30): print('Demo complete.') -run(demo_vep) +# run(demo_vep) # run(demo_height_units) # run(show_layout_coords) # run(demo_checkerboard) +run(demo_checkerboard2) \ No newline at end of file diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index e716a706f..e475904b2 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -13,6 +13,12 @@ class CheckerboardSquare(NamedTuple): color: str size: Tuple[float, float] + def inverse_color(self, colors: Tuple[str, str]) -> str: + """Get the inverse color of this square""" + if self.color == colors[0]: + return colors[1] + return colors[0] + def inverse(self, colors: Tuple[str, str]) -> 'CheckerboardSquare': """Returns a new CheckerboardSquare whose color is the inverse of the current one. From 074e9975daf0d9752fcb33e36b1f9c23a245360d Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Sep 2023 11:45:18 -0700 Subject: [PATCH 095/330] Refactored API of VEPStim --- bcipy/display/paradigm/vep/display.py | 61 +++++++++++++-------------- 1 file changed, 29 insertions(+), 32 deletions(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index dccdd087b..3cd492ae0 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -9,6 +9,7 @@ from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, VEPStimuliProperties) +from bcipy.display.components.layout import Layout from bcipy.display.components.task_bar import TaskBar from bcipy.display.paradigm.vep.layout import (BoxConfiguration, CheckerboardSquare, @@ -38,22 +39,32 @@ class VEPStim: ---------- window - used to build the stimulus code - A list of integers representing the VEP code for each box - squares - list of CheckerboardSquares with a defined position - and size + colors - tuple of colors for the checkerboard pattern + center - center position of the checkerboard + size - size of the checkerboard, in layout units + num_squares - number of squares in the checkerboard """ - def __init__(self, window: visual.Window, code: List[int], - squares: List[CheckerboardSquare]): - self.window = window + def __init__(self, + layout: Layout, + code: List[int], + colors: Tuple[str, str], + center: Tuple[float, float], + size: Tuple[float, float], + num_squares: int = 4): + assert isinstance(layout.parent, + visual.Window), 'Layout must have a Window parent' + self.window = layout.parent self.code = code - self.colors = squares[0].color, squares[1].color - self.squares = squares - self.stim = self.build_stim(squares[0]) + squares = checkerboard(layout, + squares=num_squares, + colors=colors, + center=center, + board_size=size) - self.on_stim = [self.build_stim(square) for square in self.squares] + self.on_stim = [self.build_stim(square) for square in squares] self.off_stim = [ - self.build_stim(square.inverse(self.colors)) - for square in self.squares + self.build_stim(square.inverse(colors)) for square in squares ] def build_stim(self, square: CheckerboardSquare) -> GratingStim: @@ -322,21 +333,6 @@ def _build_inquiry_stimuli(self) -> None: return self.sti - def vep_square_stim(self, square: CheckerboardSquare) -> GratingStim: - """Construct a stim from a checkerboard square""" - return GratingStim(win=self.window, - name=f"{square.color} square at {square.pos}", - tex=None, - pos=square.pos, - size=square.size, - sf=1, - phase=0.0, - color=square.color, - colorSpace='rgb', - opacity=1, - texRes=256, - interpolate=True, - depth=-1.0) def build_vep_stimuli(self, box_config: BoxConfiguration, @@ -347,12 +343,13 @@ def build_vep_stimuli(self, """Build the VEP flashing checkerboard squares""" stim = [] for pos, code, color in zip(box_config.positions, codes, colors): - board = checkerboard(box_config.layout, - squares=num_squares, - colors=color, - center=pos, - board_size=stim_size) - stim.append(VEPStim(self.window, code, board)) + stim.append( + VEPStim(box_config.layout, + code, + color, + center=pos, + size=stim_size, + num_squares=num_squares)) return stim From 149560ca50d7fd3ee9d3e2215a3c949781193351 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Sep 2023 13:50:57 -0700 Subject: [PATCH 096/330] Refactored VEP stim to use a polygon with holes to represent a checkerboard, making rendering more efficient --- bcipy/display/paradigm/vep/display.py | 59 +++++++++++++++++++++------ 1 file changed, 47 insertions(+), 12 deletions(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 3cd492ae0..d9e91a912 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -6,10 +6,11 @@ from psychopy import core, visual from psychopy.visual.grating import GratingStim from psychopy.visual.rect import Rect +from psychopy.visual.shape import ShapeStim from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, VEPStimuliProperties) -from bcipy.display.components.layout import Layout +from bcipy.display.components.layout import Layout, envelope from bcipy.display.components.task_bar import TaskBar from bcipy.display.paradigm.vep.layout import (BoxConfiguration, CheckerboardSquare, @@ -56,15 +57,51 @@ def __init__(self, visual.Window), 'Layout must have a Window parent' self.window = layout.parent self.code = code + squares = checkerboard(layout, squares=num_squares, colors=colors, center=center, board_size=size) - - self.on_stim = [self.build_stim(square) for square in squares] + board_boundary = envelope(layout, pos=center, size=size) + + frame1_holes = [] + frame2_holes = [] + for square in squares: + square_boundary = envelope(layout, pos=square.pos, size=square.size) + # squares define the holes in the polygon + if square.color == colors[0]: + frame2_holes.append(square_boundary) + elif square.color == colors[1]: + frame1_holes.append(square_boundary) + + # checkerboard is represented as a polygon with holes, backed by a + # simple square with the alternating color. + self.on_stim = [ + # background + ShapeStim(self.window, + lineColor=colors[1], + fillColor=colors[1], + vertices=board_boundary), + # polygon with holes + ShapeStim(self.window, + lineWidth=0, + fillColor=colors[0], + closeShape=True, + vertices=[board_boundary, *frame1_holes]) + ] self.off_stim = [ - self.build_stim(square.inverse(colors)) for square in squares + # background + ShapeStim(self.window, + lineColor=colors[1], + fillColor=colors[1], + vertices=board_boundary), + # polygon with holes + ShapeStim(self.window, + lineWidth=0, + fillColor=colors[0], + closeShape=True, + vertices=[board_boundary, *frame2_holes]) ] def build_stim(self, square: CheckerboardSquare) -> GratingStim: @@ -164,7 +201,7 @@ def __init__( codes=codes, colors=cycle(vep_colors), stim_size=vep_stim_size, - num_squares=4) + num_squares=25) self.text_boxes = self._build_text_boxes(box_config) @@ -270,21 +307,19 @@ def stimulate(self) -> List[float]: self.experiment_clock, 'VEP_STIMULATE') self.static_clock.reset() - first_frame = True while self.static_clock.getTime() < self.timing_stimuli: for frame in range(self.refresh_rate): for stim in self.vep: stim.render_frame(frame) self.draw_boxes() - self.draw_static() + # self.draw_static() self.window.flip() - if first_frame: - first_frame = False - print(f"Frame duration: {self.static_clock.getTime()}") + ended_at = self.static_clock.getTime() self.logger.debug( - f"Stimulate expected run time: {self.timing_stimuli}; actual run time: {self.static_clock.getTime()}" + f"Expected stim time: {self.timing_stimuli}; actual run time: {ended_at}" ) + self.logger.debug(f"Average frame duration: {ended_at/self.timing_stimuli}") return self.trigger_callback.timing @@ -340,7 +375,7 @@ def build_vep_stimuli(self, colors: List[Tuple[str]], stim_size: Tuple[float, float], num_squares: int) -> List[VEPStim]: - """Build the VEP flashing checkerboard squares""" + """Build the VEP flashing checkerboards""" stim = [] for pos, code, color in zip(box_config.positions, codes, colors): stim.append( From 56493a43331cb8460818763038c79e974da2a684 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Sep 2023 15:15:30 -0700 Subject: [PATCH 097/330] Cleaned up API for computing coordinates relative to another value --- bcipy/display/components/layout.py | 120 +++++++++--------- bcipy/display/demo/components/demo_layouts.py | 25 ++-- .../display/demo/vep/demo_calibration_vep.py | 15 ++- bcipy/display/paradigm/matrix/layout.py | 22 ++-- bcipy/display/paradigm/vep/display.py | 69 ++++------ bcipy/display/paradigm/vep/layout.py | 28 ++-- 6 files changed, 130 insertions(+), 149 deletions(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index 40815df66..ae2beac46 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -35,6 +35,62 @@ def vertical(cls): return [Alignment.CENTERED, Alignment.TOP, Alignment.BOTTOM] +# Positioning functions +def above(y_coordinate: float, amount: float) -> float: + """Returns a new y_coordinate value that is above the provided value + by the given amount.""" + assert amount >= 0, 'Amount must be positive' + return y_coordinate + amount + + +def below(y_coordinate: float, amount: float) -> float: + """Returns a new y_coordinate value that is below the provided value + by the given amount.""" + assert amount >= 0, 'Amount must be positive' + return y_coordinate - amount + + +def right_of(x_coordinate: float, amount: float) -> float: + """Returns a new x_coordinate value that is to the right of the + provided value by the given amount.""" + assert amount >= 0, 'Amount must be positive' + return x_coordinate + amount + + +def left_of(x_coordinate: float, amount: float) -> float: + """Returns a new x_coordinate value that is to the left of the + provided value by the given amount.""" + assert amount >= 0, 'Amount must be positive' + return x_coordinate - amount + + +def envelope(pos: Tuple[float, float], + size: Tuple[float, float]) -> List[Tuple[float, float]]: + """Compute the vertices for the envelope of a shape centered at pos with + the given size.""" + width, height = size + half_w = width / 2 + half_h = height / 2 + return [(left_of(pos[0], half_w), above(pos[1], half_h)), + (right_of(pos[0], half_w), above(pos[1], half_h)), + (right_of(pos[0], half_w), below(pos[1], half_h)), + (left_of(pos[0], half_w), below(pos[1], half_h))] + + +def scaled_size(height: float, + window_size: [Tuple[float, float]], + units: str = 'norm') -> Tuple[float, float]: + """Scales the provided height value to reflect the aspect ratio of a + visual.Window. Used for creating squared stimulus. Returns (w,h) tuple""" + if units == 'height': + width = height + return (width, height) + + win_width, win_height = window_size + width = (win_height / win_width) * height + return (width, height) + + class Layout(Container): """Class with methods for positioning elements within a parent container. """ @@ -84,26 +140,14 @@ def check_invariants(self): assert 0 < self.height <= self.parent.size[ 1], "Height must be greater than 0 and fit within the parent height." - def scaled_size( - self, - height: float, - window_size: Optional[Tuple[float, - float]] = None) -> Tuple[float, float]: - """Returns the (w,h ) value scaled to reflect the aspect ratio of a + def scaled_size(self, height: float) -> Tuple[float, float]: + """Returns the (w,h) value scaled to reflect the aspect ratio of a visual.Window. Used for creating squared stimulus""" if self.units == 'height': width = height return (width, height) - - # norm units - if window_size is not None: - win_width, win_height = window_size - elif self.parent: - win_width, win_height = self.parent.size - else: - raise ValueError("window_size or parent is required") - width = (win_height / win_width) * height - return (width, height) + assert self.parent is not None, 'Parent must be configured' + return scaled_size(height, self.parent.size, self.units) @property def size(self) -> Tuple[float, float]: @@ -155,34 +199,6 @@ def right_middle(self) -> Tuple[float, float]: """Point centered on the right-most edge.""" return (self.right, self.vertical_middle) - def above(self, y_coordinate: float, amount: float) -> float: - """Returns a new y_coordinate value that is above the provided value - by the given amount.""" - # assert self.bottom <= y_coordinate <= self.top, "y_coordinate out of range" - assert amount >= 0, 'Amount must be positive' - return y_coordinate + amount - - def below(self, y_coordinate: float, amount: float) -> float: - """Returns a new y_coordinate value that is below the provided value - by the given amount.""" - # assert self.bottom <= y_coordinate <= self.top, "y_coordinate out of range" - assert amount >= 0, 'Amount must be positive' - return y_coordinate - amount - - def right_of(self, x_coordinate: float, amount: float) -> float: - """Returns a new x_coordinate value that is to the right of the - provided value by the given amount.""" - # assert self.left <= x_coordinate <= self.right, "y_coordinate out of range" - assert amount >= 0, 'Amount must be positive' - return x_coordinate + amount - - def left_of(self, x_coordinate: float, amount: float) -> float: - """Returns a new x_coordinate value that is to the left of the - provided value by the given amount.""" - # assert self.left <= x_coordinate <= self.right, "y_coordinate out of range" - assert amount >= 0, 'Amount must be positive' - return x_coordinate - amount - def resize_width(self, width_pct: float, alignment: Alignment = Alignment.CENTERED) -> float: @@ -247,6 +263,7 @@ def resize_height(self, self.check_invariants() +# Factory functions def at_top(parent: Container, height: float) -> Layout: """Constructs a layout of a given height that spans the full width of the window and is positioned at the top. @@ -292,20 +309,7 @@ def centered(width_pct: float = 1.0, height_pct: float = 1.0) -> Layout: return container -def envelope(layout: Layout, pos: Tuple[float, float], - size: Tuple[float, float]) -> List[Tuple[float, float]]: - """Compute the vertices for the envelope of a shape centered at pos with - the given size.""" - width, height = size - half_w = width / 2 - half_h = height / 2 - return [(layout.left_of(pos[0], half_w), layout.above(pos[1], half_h)), - (layout.right_of(pos[0], half_w), layout.above(pos[1], half_h)), - (layout.right_of(pos[0], half_w), layout.below(pos[1], half_h)), - (layout.left_of(pos[0], half_w), layout.below(pos[1], half_h))] - - -def height_units(window_size: Tuple[float, float]): +def height_units(window_size: Tuple[float, float]) -> Layout: """Constructs a layout with height units using the given Window dimensions diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index de0476bc0..43cce9755 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -9,7 +9,8 @@ from psychopy.visual.shape import ShapeStim from bcipy.display.components.layout import (Layout, at_top, centered, - envelope, height_units) + envelope, height_units, + scaled_size) from bcipy.display.paradigm.vep.layout import BoxConfiguration, checkerboard @@ -143,8 +144,7 @@ def demo_vep(win: visual.Window): for i, pos in enumerate(positions): color_tup: Tuple[str, str] = vep_colors[i] - board = checkerboard(layout, - squares=16, + board = checkerboard(squares=16, colors=color_tup, center=pos, board_size=layout.scaled_size(0.2)) @@ -166,13 +166,10 @@ def demo_vep(win: visual.Window): def demo_checkerboard(win: visual.Window): """Demo checkerboard""" - layout = centered(width_pct=0.9, height_pct=0.9) - layout.parent = win - board = checkerboard(layout, - squares=16, + board = checkerboard(squares=16, colors=('red', 'green'), center=(0, 0), - board_size=layout.scaled_size(0.6)) + board_size=scaled_size(0.6, win.size)) for square in board: Rect(win, pos=square.pos, @@ -223,24 +220,20 @@ def demo_height_units(win: visual.Window): def demo_checkerboard2(win: visual.Window): """Demo checkerboard rendered using a complex shapestim""" - layout = centered(width_pct=0.9, height_pct=0.9) - layout.parent = win - board_pos = (0, 0) - board_size = layout.scaled_size(0.6) + board_size = scaled_size(0.6, win.size) colors = ('red', 'green') - board = checkerboard(layout, - squares=25, + board = checkerboard(squares=25, colors=colors, center=board_pos, board_size=board_size) - board_boundaries = envelope(layout, pos=board_pos, size=board_size) + board_boundaries = envelope(pos=board_pos, size=board_size) evens = [] odds = [] for square in board: - square_boundary = envelope(layout, pos=square.pos, size=square.size) + square_boundary = envelope(pos=square.pos, size=square.size) if square.color == colors[0]: evens.append(square_boundary) else: diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 769fa211c..57e9867f3 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -1,3 +1,6 @@ +import logging +import sys + from psychopy import core, visual from bcipy.display import InformationProperties, VEPStimuliProperties @@ -7,6 +10,12 @@ from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock +root = logging.getLogger() +root.setLevel(logging.DEBUG) +handler = logging.StreamHandler(sys.stdout) +handler.setLevel(logging.DEBUG) +root.addHandler(handler) + info = InformationProperties( info_color=['White'], info_pos=[(-.5, -.75)], @@ -16,7 +25,7 @@ ) task_text = ['1/4'] #, '2/4', '3/4', '4/4'] -num_boxes = 4 +num_boxes = 6 win = visual.Window(size=[700, 700], fullscr=False, @@ -39,7 +48,9 @@ box_colors = ['#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232'] stim_color = [[color] for i, color in enumerate(box_colors) if i < num_boxes] -box_config = BoxConfiguration(layout=centered(width_pct=0.95, height_pct=0.80), num_boxes=num_boxes) +layout=centered(width_pct=0.95, height_pct=0.80) +layout.parent = win +box_config = BoxConfiguration(layout, num_boxes=num_boxes) experiment_clock = Clock() len_stimuli = 10 diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index 8a0c00b2c..a5063572b 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -1,7 +1,8 @@ """Functions for calculating matrix layouts""" from typing import List, Tuple -from bcipy.display.components.layout import Layout +from bcipy.display.components.layout import (Layout, above, below, left_of, + right_of) def symbol_positions(container: Layout, @@ -35,29 +36,28 @@ def symbol_positions(container: Layout, # Work back from center to compute the starting position center_x, center_y = container.center spaces_left_of_center = int(columns / 2) - start_pos_left = container.left_of(center_x, - spaces_left_of_center * spacing) + start_pos_left = left_of(center_x, spaces_left_of_center * spacing) if columns % 2 == 0 and columns > 1: # even number of columns; adjust start_pos so that center_x is between # the middle two items. - start_pos_left = container.right_of(start_pos_left, half_space) + start_pos_left = right_of(start_pos_left, half_space) spaces_above_center = int(rows / 2) - start_pos_top = container.above(center_y, spaces_above_center * spacing) + start_pos_top = above(center_y, spaces_above_center * spacing) if rows % 2 == 0 and rows > 1: - start_pos_top = container.below(start_pos_top, half_space) + start_pos_top = below(start_pos_top, half_space) # adjust the beginning x,y values so adding a space results in the first # position. - x_coord = container.left_of(start_pos_left, spacing) - y_coord = container.above(start_pos_top, spacing) + x_coord = left_of(start_pos_left, spacing) + y_coord = above(start_pos_top, spacing) positions = [] for _row in range(rows): - y_coord = container.below(y_coord, spacing) - x_coord = container.left_of(start_pos_left, spacing) + y_coord = below(y_coord, spacing) + x_coord = left_of(start_pos_left, spacing) for _col in range(columns): - x_coord = container.right_of(x_coord, spacing) + x_coord = right_of(x_coord, spacing) positions.append((x_coord, y_coord)) return positions diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index d9e91a912..90f405893 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -4,17 +4,13 @@ import numpy as np from psychopy import core, visual -from psychopy.visual.grating import GratingStim -from psychopy.visual.rect import Rect from psychopy.visual.shape import ShapeStim from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, VEPStimuliProperties) -from bcipy.display.components.layout import Layout, envelope +from bcipy.display.components.layout import envelope, scaled_size from bcipy.display.components.task_bar import TaskBar -from bcipy.display.paradigm.vep.layout import (BoxConfiguration, - CheckerboardSquare, - checkerboard) +from bcipy.display.paradigm.vep.layout import BoxConfiguration, checkerboard from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import get_fixation, resize_image from bcipy.helpers.triggers import TriggerCallback, _calibration_trigger @@ -33,12 +29,12 @@ def create_vep_codes(length=32, count=4) -> List[List[int]]: class VEPStim: - """Represents a checkerboard of squares that can be flashed at a rate. - Flashing is accomplished by inverting the colors of each square. + """Represents a checkerboard of squares that can be flashed at a given + rate. Flashing is accomplished by inverting the colors of each square. Parameters ---------- - window - used to build the stimulus + layout - used to build the stimulus code - A list of integers representing the VEP code for each box colors - tuple of colors for the checkerboard pattern center - center position of the checkerboard @@ -47,28 +43,25 @@ class VEPStim: """ def __init__(self, - layout: Layout, + win: visual.Window, code: List[int], colors: Tuple[str, str], center: Tuple[float, float], size: Tuple[float, float], num_squares: int = 4): - assert isinstance(layout.parent, - visual.Window), 'Layout must have a Window parent' - self.window = layout.parent + self.window = win self.code = code - squares = checkerboard(layout, - squares=num_squares, + squares = checkerboard(squares=num_squares, colors=colors, center=center, board_size=size) - board_boundary = envelope(layout, pos=center, size=size) + board_boundary = envelope(pos=center, size=size) frame1_holes = [] frame2_holes = [] for square in squares: - square_boundary = envelope(layout, pos=square.pos, size=square.size) + square_boundary = envelope(pos=square.pos, size=square.size) # squares define the holes in the polygon if square.color == colors[0]: frame2_holes.append(square_boundary) @@ -77,12 +70,12 @@ def __init__(self, # checkerboard is represented as a polygon with holes, backed by a # simple square with the alternating color. + background = ShapeStim(self.window, + lineColor=colors[1], + fillColor=colors[1], + vertices=board_boundary) self.on_stim = [ - # background - ShapeStim(self.window, - lineColor=colors[1], - fillColor=colors[1], - vertices=board_boundary), + background, # polygon with holes ShapeStim(self.window, lineWidth=0, @@ -91,11 +84,7 @@ def __init__(self, vertices=[board_boundary, *frame1_holes]) ] self.off_stim = [ - # background - ShapeStim(self.window, - lineColor=colors[1], - fillColor=colors[1], - vertices=board_boundary), + background, # polygon with holes ShapeStim(self.window, lineWidth=0, @@ -104,21 +93,6 @@ def __init__(self, vertices=[board_boundary, *frame2_holes]) ] - def build_stim(self, square: CheckerboardSquare) -> GratingStim: - """Constructs a single re-usable stim""" - return GratingStim(win=self.window, - tex=None, - pos=square.pos, - size=square.size, - sf=1, - phase=0.0, - color=square.color, - colorSpace='rgb', - opacity=1, - texRes=256, - interpolate=True, - depth=-1.0) - def render_frame(self, frame: int) -> None: """Render a given frame number, where frame refers to a code index""" if self.code[frame] == 1: @@ -196,8 +170,8 @@ def __init__( if not codes: codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] - vep_stim_size = box_config.layout.scaled_size(0.2, self.window_size) - self.vep = self.build_vep_stimuli(box_config=box_config, + vep_stim_size = scaled_size(0.2, self.window_size) + self.vep = self.build_vep_stimuli(positions=box_config.positions, codes=codes, colors=cycle(vep_colors), stim_size=vep_stim_size, @@ -316,6 +290,7 @@ def stimulate(self) -> List[float]: # self.draw_static() self.window.flip() ended_at = self.static_clock.getTime() + # TODO: should we have a trigger for VEP_STIM_END? self.logger.debug( f"Expected stim time: {self.timing_stimuli}; actual run time: {ended_at}" ) @@ -370,16 +345,16 @@ def _build_inquiry_stimuli(self) -> None: def build_vep_stimuli(self, - box_config: BoxConfiguration, + positions: List[Tuple[float, float]], codes: List[int], colors: List[Tuple[str]], stim_size: Tuple[float, float], num_squares: int) -> List[VEPStim]: """Build the VEP flashing checkerboards""" stim = [] - for pos, code, color in zip(box_config.positions, codes, colors): + for pos, code, color in zip(positions, codes, colors): stim.append( - VEPStim(box_config.layout, + VEPStim(self.window, code, color, center=pos, diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index e475904b2..4d26cc139 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -4,7 +4,8 @@ from math import sqrt from typing import List, NamedTuple, Optional, Tuple -from bcipy.display.components.layout import Layout +from bcipy.display.components.layout import (Layout, above, below, left_of, + right_of) class CheckerboardSquare(NamedTuple): @@ -34,8 +35,8 @@ def inverse(self, colors: Tuple[str, str]) -> 'CheckerboardSquare': return CheckerboardSquare(self.pos, color, self.size) -def checkerboard(layout: Layout, squares: int, colors: Tuple[str, str], - center: Tuple[float, float], +def checkerboard(squares: int, colors: Tuple[str, str], center: Tuple[float, + float], board_size: Tuple[float, float]) -> List[CheckerboardSquare]: """Computes positions and colors for squares used to represent a checkerboard pattern. Returned positions are the center point of @@ -43,8 +44,6 @@ def checkerboard(layout: Layout, squares: int, colors: Tuple[str, str], Parameters ---------- - layout - layout in which the checkerboard will be rendered. Used for - positioning and scale. squares - total number of squares in the board; must be a perfect square (ex. 4, 9, 16, 25) colors - tuple of color names between which to alternate @@ -65,22 +64,22 @@ def checkerboard(layout: Layout, squares: int, colors: Tuple[str, str], if squares % 2 == 0: # with an even number the center is on a vertex; adjust by half a box move_count -= 0.5 - left = layout.left_of(center_x, square_width * move_count) - top = layout.above(center_y, square_height * move_count) + left = left_of(center_x, square_width * move_count) + top = above(center_y, square_height * move_count) # iterate starting at the top left and proceeding in a zig zag # pattern to correspond with alternating checkerboard colors. positions = [] for row in range(boxes_per_row): if row > 0: - top = layout.below(top, square_height) + top = below(top, square_height) for col in range(boxes_per_row): positions.append((left, top)) if col < boxes_per_row - 1: if row % 2 == 0: - left = layout.right_of(left, square_width) + left = right_of(left, square_width) else: - left = layout.left_of(left, square_width) + left = left_of(left, square_width) return [ CheckerboardSquare(*args) for args in zip(positions, cycle(colors), cycle([square_size])) @@ -153,15 +152,14 @@ def positions(self) -> List[Tuple]: """ self.validate() - # size = box_size(num, layout, spacing_pct) width, height = self.box_size(validate=False) layout = self.layout - top = layout.below(layout.top, (height / 2)) - bottom = layout.above(layout.bottom, (height / 2)) + top = below(layout.top, (height / 2)) + bottom = above(layout.bottom, (height / 2)) - left = layout.right_of(layout.left, width / 2) - right = layout.left_of(layout.right, width / 2) + left = right_of(layout.left, width / 2) + right = left_of(layout.right, width / 2) positions = [(left, top), (right, top), (left, bottom), (right, bottom)] From 1dd56570da5389a0049f066b86105ab9335a1cc6 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Sep 2023 15:37:56 -0700 Subject: [PATCH 098/330] Type fix --- bcipy/display/components/layout.py | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index ae2beac46..a746ad51b 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -78,7 +78,7 @@ def envelope(pos: Tuple[float, float], def scaled_size(height: float, - window_size: [Tuple[float, float]], + window_size: Tuple[float, float], units: str = 'norm') -> Tuple[float, float]: """Scales the provided height value to reflect the aspect ratio of a visual.Window. Used for creating squared stimulus. Returns (w,h) tuple""" @@ -91,6 +91,17 @@ def scaled_size(height: float, return (width, height) +def scaled_height(width: float, + window_size: Tuple[float, float], + units: str = 'norm') -> float: + """Given a width, find the equivalent height scaled to the aspect ratio of + a window with the given size""" + if units == 'height': + return width + win_width, win_height = window_size + return width / (win_height / win_width) + + class Layout(Container): """Class with methods for positioning elements within a parent container. """ From 195a058da2a1a3091807c8b13b76cded2e7a701d Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 25 Sep 2023 17:49:47 -0700 Subject: [PATCH 099/330] Cleanup and unit tests --- bcipy/display/components/layout.py | 12 +- bcipy/display/demo/components/demo_layouts.py | 6 +- .../display/demo/vep/demo_calibration_vep.py | 8 +- bcipy/display/paradigm/vep/display.py | 11 +- bcipy/display/paradigm/vep/layout.py | 11 +- bcipy/display/tests/components/test_layout.py | 43 +++++- bcipy/display/tests/vep/test_vep_layout.py | 130 ++++++++++++++++++ 7 files changed, 202 insertions(+), 19 deletions(-) create mode 100644 bcipy/display/tests/vep/test_vep_layout.py diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index a746ad51b..a61e20f19 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -107,7 +107,7 @@ class Layout(Container): """ def __init__(self, - parent: Container = None, + parent: Optional[Container] = None, left: float = DEFAULT_LEFT, top: float = DEFAULT_TOP, right: float = DEFAULT_RIGHT, @@ -320,6 +320,16 @@ def centered(width_pct: float = 1.0, height_pct: float = 1.0) -> Layout: return container +def from_envelope(verts: List[Tuple[float, float]]) -> Layout: + """Constructs a layout from a list of vertices which comprise a shape's + envelope.""" + x_coords, y_coords = zip(*verts) + return Layout(left=min(x_coords), + top=max(y_coords), + right=max(x_coords), + bottom=min(y_coords)) + + def height_units(window_size: Tuple[float, float]) -> Layout: """Constructs a layout with height units using the given Window dimensions diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index 43cce9755..e4809cd36 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -129,7 +129,7 @@ def demo_vep(win: visual.Window): layout.parent = win box_config = BoxConfiguration(layout, num_boxes=4, height_pct=0.28) - size = box_config.box_size() + size = box_config.box_size positions = box_config.positions draw_boundary(win, layout, color='gray', line_px=2) @@ -281,8 +281,8 @@ def run(demo: Callable[[visual.Window], None], seconds=30): print('Demo complete.') -# run(demo_vep) +run(demo_vep) # run(demo_height_units) # run(show_layout_coords) # run(demo_checkerboard) -run(demo_checkerboard2) \ No newline at end of file +# run(demo_checkerboard2) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 57e9867f3..29f264b13 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -24,7 +24,7 @@ info_text=['VEP Display Demo'], ) -task_text = ['1/4'] #, '2/4', '3/4', '4/4'] +task_text = ['1/4'] # , '2/4', '3/4', '4/4'] num_boxes = 6 win = visual.Window(size=[700, 700], @@ -43,19 +43,19 @@ print(f'Monitor refresh rate: {frameRate} Hz') -start_positions_for_boxes = [(-.3, -.3), (.3, -.3), (.3, .3), (-.3, .3)] +start_positions_for_boxes = [(-.3, -.3), (.3, -.3), (.3, .3), (-.3, .3)] box_colors = ['#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232'] stim_color = [[color] for i, color in enumerate(box_colors) if i < num_boxes] -layout=centered(width_pct=0.95, height_pct=0.80) +layout = centered(width_pct=0.95, height_pct=0.80) layout.parent = win box_config = BoxConfiguration(layout, num_boxes=num_boxes) experiment_clock = Clock() len_stimuli = 10 stimuli = VEPStimuliProperties( - stim_color = stim_color, + stim_color=stim_color, stim_pos=box_config.positions, stim_height=0.1, stim_font='Arial', diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 90f405893..1e2c07a21 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -111,9 +111,9 @@ def frame_off(self) -> None: stim.draw() - class VEPDisplay(Display): """Display for VEP paradigm""" + def __init__( self, window: visual.Window, @@ -179,7 +179,6 @@ def __init__( self.text_boxes = self._build_text_boxes(box_config) - def check_configuration(self): """Check that configured properties are consistent""" assert len( @@ -343,7 +342,6 @@ def _build_inquiry_stimuli(self) -> None: return self.sti - def build_vep_stimuli(self, positions: List[Tuple[float, float]], codes: List[int], @@ -362,7 +360,6 @@ def build_vep_stimuli(self, num_squares=num_squares)) return stim - def _trigger_pulse(self) -> None: """Trigger Pulse. @@ -382,7 +379,8 @@ def _trigger_pulse(self) -> None: self.first_stim_time = calibration_time[-1] self.first_run = False - def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]]=None, colors: List[List[str]]=None) -> None: + def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]] + = None, colors: List[List[str]] = None) -> None: """Schedule stimuli elements (works as a buffer). """ self.stimuli_inquiry = stimuli @@ -395,7 +393,7 @@ def _build_text_boxes(self, box_config: BoxConfiguration) -> List[visual.TextBox associated VEP Box. """ positions = box_config.positions - size = box_config.box_size() + size = box_config.box_size return [ visual.TextBox2(win=self.window, text=" ", @@ -413,7 +411,6 @@ def _build_text_boxes(self, box_config: BoxConfiguration) -> List[visual.TextBox for pos, color in zip(positions, cycle(self.stimuli_colors)) ] - def _reset_text_boxes(self) -> None: """Reset text boxes. diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index 4d26cc139..eeaf6ef28 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -122,7 +122,7 @@ def validate(self): assert self.num_boxes == 4 or self.num_boxes == 6, 'Number of boxes must be 4 or 6' assert self.height_pct <= 0.5, "Rows can't take more than 50% of the height" - def box_size(self, validate: bool = True) -> Tuple[float, float]: + def _box_size(self, validate: bool = True) -> Tuple[float, float]: """Computes the size of each box""" if validate: self.validate() @@ -139,6 +139,11 @@ def box_size(self, validate: bool = True) -> Tuple[float, float]: return (width, height) + @property + def box_size(self) -> Tuple[float, float]: + """Size of each box""" + return self._box_size() + @property def units(self) -> str: """Position units""" @@ -152,7 +157,7 @@ def positions(self) -> List[Tuple]: """ self.validate() - width, height = self.box_size(validate=False) + width, height = self._box_size(validate=False) layout = self.layout top = below(layout.top, (height / 2)) @@ -166,4 +171,4 @@ def positions(self) -> List[Tuple]: if self.num_boxes == 6: positions += [(layout.horizontal_middle, top), (layout.horizontal_middle, bottom)] - return positions \ No newline at end of file + return positions diff --git a/bcipy/display/tests/components/test_layout.py b/bcipy/display/tests/components/test_layout.py index ba99860e4..cbe25803e 100644 --- a/bcipy/display/tests/components/test_layout.py +++ b/bcipy/display/tests/components/test_layout.py @@ -4,7 +4,9 @@ from mockito import mock from bcipy.display.components.layout import (Alignment, Layout, at_bottom, - at_top, centered) + at_top, centered, envelope, + from_envelope, scaled_height, + scaled_size) class TestLayout(unittest.TestCase): @@ -155,6 +157,45 @@ def test_resize_height_bottom_aligned(self): self.assertEqual(0.0, layout.top) self.assertEqual(-1.0, layout.bottom) + def test_envelope(self): + """Test calculation of a shape's envelope""" + pos = (0, 0) + width = 0.2 + height = 0.1 + verts = envelope(pos=pos, size=(width, height)) + self.assertEqual(len(verts), 4) + self.assertTrue((-0.1, 0.05) in verts) + self.assertTrue((-0.1, -0.05) in verts) + self.assertTrue((0.1, -0.05) in verts) + self.assertTrue((0.1, 0.05) in verts) + + def test_from_envelope(self): + """Test constructing a layout from an envelope""" + verts = envelope(pos=(0, 0), size=(0.2, 0.1)) + layout = from_envelope(verts) + self.assertEqual(layout.top, 0.05) + self.assertEqual(layout.bottom, -0.05) + self.assertEqual(layout.left, -0.1) + self.assertEqual(layout.right, 0.1) + self.assertEqual(layout.center, (0, 0)) + + def test_scaled_size(self): + """Test scaling the size to make shapes that display as squares""" + self.assertEqual( + scaled_size(height=0.2, window_size=(500, 500)), (0.2, 0.2), + msg="Height and width should be the same in a square window") + self.assertEqual( + scaled_size(height=0.2, window_size=(800, 500)), (0.125, 0.2), + msg="Width should be proportional to the window aspect") + + self.assertEqual( + scaled_size(height=0.2, window_size=(800, 500), units='height'), (0.2, 0.2), + msg="Width should be the same in 'height' units") + + def test_scaled_height(self): + """Test calculation of scaled height based on width""" + self.assertEqual(scaled_height(0.125, window_size=(800, 500)), 0.2) + if __name__ == '__main__': unittest.main() diff --git a/bcipy/display/tests/vep/test_vep_layout.py b/bcipy/display/tests/vep/test_vep_layout.py new file mode 100644 index 000000000..b73bf62fa --- /dev/null +++ b/bcipy/display/tests/vep/test_vep_layout.py @@ -0,0 +1,130 @@ +"""Tests for VEP layout functions""" +import unittest + +from mockito import mock + +from bcipy.display.components.layout import Layout +from bcipy.display.paradigm.vep.layout import (BoxConfiguration, + CheckerboardSquare, + checkerboard) + + +class TestVEPLayout(unittest.TestCase): + """Test VEP Layout functionality.""" + + def setUp(self): + """Set up needed items for test.""" + self.window = mock({"size": (500, 500), "units": "norm"}) + self.container = self.window + + def test_2x2_checkerboard(self): + """Test creation of a 2x2 board""" + squares = checkerboard(squares=4, + colors=('red', 'green'), + center=(0, 0), + board_size=(0.2, 0.2)) + self.assertEqual(len(squares), 4) + self.assertTrue(all(sq.size == (0.1, 0.1) for sq in squares)) + self.assertEqual( + [sq.pos for sq in squares], [(-0.05, 0.05), (0.05, 0.05), + (0.05, -0.05), (-0.05, -0.05)], + msg="Squares should be ordered in a zig-zag arrangement") + self.assertEqual([sq.color for sq in squares], + ['red', 'green', 'red', 'green'], + msg="colors should alternate") + + def test_3x3_checkerboard(self): + """Test creation of a 3x3 board""" + colors = ('blue', 'yellow') + squares = checkerboard(squares=9, + colors=colors, + center=(0, 0), + board_size=(0.48, 0.48)) + self.assertEqual(len(squares), 9) + self.assertTrue(all(sq.size == (0.16, 0.16) for sq in squares)) + self.assertEqual(squares[0].pos, (-0.16, 0.16)) + self.assertEqual( + squares[3].pos, (0.16, 0.0), + msg="First item on second row should be at the far right") + + for i, square in enumerate(squares): + self.assertEqual(colors[i % 2], square.color, + "Colors should alternate") + + def test_checkerboard_inverse(self): + """Test that a Checkerboard square can invert colors""" + colors = ('red', 'green') + square = CheckerboardSquare(pos=(0, 0), color='red', size=(0.1, 0.1)) + self.assertEqual( + square.inverse(colors), + CheckerboardSquare(pos=(0, 0), color='green', size=(0.1, 0.1))) + + self.assertEqual(square.inverse_color(colors), 'green') + + def test_4_box_config_defaults(self): + """Test box configuration""" + full_window = Layout() + config = BoxConfiguration(layout=full_window, + num_boxes=4, + height_pct=0.25, + spacing_pct=0.1) + width, height = config.box_size + window_width, window_height = full_window.size + + self.assertEqual(window_width, 2.0) + self.assertEqual(window_height, 2.0) + self.assertEqual( + width, + 0.9, + msg="Box width should be half of the remaining width after accounting for the spacing." + ) + self.assertEqual( + height, + 0.5, + msg="Box height should be height_pct of the window height") + + positions = config.positions + self.assertEqual(len(positions), 4) + self.assertTrue((-0.55, 0.75) in positions, + msg="A box should be positioned at the top left") + self.assertTrue((0.55, 0.75) in positions, + msg="A box should be positioned at the top right") + self.assertTrue((-0.55, -0.75) in positions, + msg="A box should be positioned at the bottom left") + self.assertTrue((0.55, -0.75) in positions, + msg="A box should be positioned at the bottom right") + + def test_6_box_config_defaults(self): + """Test box configuration""" + full_window = Layout() + config = BoxConfiguration(layout=full_window, + num_boxes=6, + height_pct=0.25, + spacing_pct=0.05) + self.assertEqual( + config.box_size, (0.6, 0.5), + msg="width should account for 3 boxes in a row and 2 spaces") + + positions = config.positions + self.assertEqual(len(positions), 6) + self.assertEqual(len([box for box in positions if box[0] == 0.0]), + 2, + msg="Two boxes should be positioned in the middle") + + def test_other_box_config(self): + """Test supported number of boxes""" + full_window = Layout() + with self.assertRaises(AssertionError): + BoxConfiguration(layout=full_window, + num_boxes=2, + height_pct=0.25, + spacing_pct=0.05) + + def test_height_pct_validation(self): + """Test validations""" + full_window = Layout() + with self.assertRaises(AssertionError): + BoxConfiguration(layout=full_window, + num_boxes=4, + height_pct=0.6, + spacing_pct=0.1) From 5cbc5bd820f62501c6f221d5527a39bbc246e811 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 27 Sep 2023 17:30:27 -0700 Subject: [PATCH 100/330] Demo cleanup --- bcipy/display/demo/vep/demo_calibration_vep.py | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 29f264b13..0bffab679 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -24,7 +24,7 @@ info_text=['VEP Display Demo'], ) -task_text = ['1/4'] # , '2/4', '3/4', '4/4'] +task_text = ['1/4', '2/4', '3/4', '4/4'] num_boxes = 6 win = visual.Window(size=[700, 700], @@ -43,13 +43,10 @@ print(f'Monitor refresh rate: {frameRate} Hz') -start_positions_for_boxes = [(-.3, -.3), (.3, -.3), (.3, .3), (-.3, .3)] - box_colors = ['#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232'] stim_color = [[color] for i, color in enumerate(box_colors) if i < num_boxes] layout = centered(width_pct=0.95, height_pct=0.80) -layout.parent = win box_config = BoxConfiguration(layout, num_boxes=num_boxes) experiment_clock = Clock() @@ -59,7 +56,7 @@ stim_pos=box_config.positions, stim_height=0.1, stim_font='Arial', - timing=(1, 0.5, 2, 4), # prompt, fixation, stimuli + timing=(1, 0.5, 2, 4), # prompt, fixation, animation, stimuli stim_length=1, # how many times to stimuli ) task_bar = CalibrationTaskBar(win, @@ -76,7 +73,7 @@ if num_boxes == 4: stim = [['A', 'B'], ['Z'], ['P'], ['R', 'W']] if num_boxes == 6: - stim = [['A'], ['B'], ['Z'], ['P'], ['R'], ['W']] + stim = [['A'], ['B'], ['Z', 'X'], ['P', 'I'], ['R'], ['W', 'C']] vep.schedule_to(stimuli=stim) timing += vep.do_inquiry() From 924c97f7f8c639657182dc791d54f77d75b53237 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 27 Sep 2023 17:38:54 -0700 Subject: [PATCH 101/330] Code cleanup and documentation --- bcipy/display/paradigm/vep/display.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 1e2c07a21..95a8f7f61 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -68,8 +68,10 @@ def __init__(self, elif square.color == colors[1]: frame1_holes.append(square_boundary) - # checkerboard is represented as a polygon with holes, backed by a + # Checkerboard is represented as a polygon with holes, backed by a # simple square with the alternating color. + # This technique renders more efficiently and scales better than using + # separate shapes (Rect or Gradient) for each square. background = ShapeStim(self.window, lineColor=colors[1], fillColor=colors[1], @@ -127,7 +129,6 @@ def __init__( self.window = window self.window_size = self.window.size # [w, h] self.refresh_rate = round(window.getActualFrameRate()) - print(f"Refresh rate: {self.refresh_rate}") self.logger = logging.getLogger(__name__) # number of VEP text areas From 7bf6f71e6a9c7bfdc9f0bc25bd46bfcc6bb6293f Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 28 Sep 2023 19:31:34 -0400 Subject: [PATCH 102/330] Sanity check after merge from 2.0.0rc4 branch, Offline_analysis and Triggers bug fixes. --- bcipy/helpers/stimuli.py | 21 +- bcipy/helpers/triggers.py | 28 +- bcipy/parameters/parameters.json | 2 +- bcipy/signal/model/offline_analysis.py | 351 ++++++++++++------------- 4 files changed, 196 insertions(+), 206 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index f5afec7ea..f574565ed 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -232,32 +232,21 @@ def extract_trials( class GazeReshaper: def __call__(self, - trial_targetness_label: List[str], inq_start_times: List[float], target_symbols: List[str], gaze_data: np.ndarray, sample_rate: int, - trials_per_inquiry: int, - offset: float = 0, channel_map: List[int] = None, - poststimulus_length: float = 0.5, - prestimulus_length: float = 0.0, - transformation_buffer: float = 0.0, ) -> dict: """Extract inquiry data and labels. Args: - trial_targetness_label (List[str]): labels each trial as "target", "non-target", "first_pres_target", etc - timing_info (List[float]): Timestamp of each event in seconds + inq_start_times (List[float]): Timestamp of each event in seconds + target_symbols (List[str]): Prompted symbol in each inquiry gaze_data (np.ndarray): shape (channels, samples) eye tracking data sample_rate (int): sample rate of data provided in eeg_data - trials_per_inquiry (int): number of trials in each inquiry - offset (float, optional): Any calculated or hypothesized offsets in timings. Defaults to 0. channel_map (List[int], optional): Describes which channels to include or discard. Defaults to None; all channels will be used. - poststimulus_length (float, optional): time in seconds needed after the last trial in an inquiry. - prestimulus_length (float, optional): time in seconds needed before the first trial in an inquiry. - transformation_buffer (float, optional): time in seconds to buffer the end of the inquiry. Defaults to 0.0. Returns: reshaped_data (List[float]): inquiry data of shape (Inquiries, Channels, Samples) @@ -295,11 +284,13 @@ def __call__(self, for symbol in symbol_set: data_by_targets[symbol] = [] + window_length = 3 # seconds, total length of flickering after prompt for each inquiry + reshaped_data = [] # Merge the inquiries if they have the same target letter: for i, inquiry_index in enumerate(triggers): start = inquiry_index - stop = int(inquiry_index + (sample_rate * 3)) # (60 samples * 3 seconds) + stop = int(inquiry_index + (sample_rate * window_length)) # (60 samples * 3 seconds) # Check if the data exists for the inquiry: if stop > len(gaze_data[0, :]): continue @@ -316,7 +307,7 @@ def __call__(self, data_by_targets[symbol] = np.transpose(np.array(data_by_targets[symbol]), (1, 0, 2)) data_by_targets[symbol] = np.reshape(data_by_targets[symbol], (len(data_by_targets[symbol]), -1)) - # TODO: Note that this is a workaround to the issue of having different number of targetness in + # Note that this is a workaround to the issue of having different number of targetness in # each symbol. If a target symbol is prompted more than once, the data is appended to the dict as a list. # Which is why we need to convert it to a (np.ndarray) and flatten the dimensions. # This is not ideal, but it works for now. diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 4b5a0718d..ce38f9397 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -282,7 +282,8 @@ def starting_offsets_by_device( def find_starting_offset(triggers: List[Trigger], - device_type: Optional[str] = None) -> Trigger: + device_type: Optional[str] = None, + apply_system_offset: Optional[bool] = True) -> Trigger: """Given a list of raw trigger data, determine the starting offset for the given device. The returned trigger has the timestamp of the first sample recorded for the device. @@ -298,16 +299,20 @@ def find_starting_offset(triggers: List[Trigger], device_type - each device will generally have a different offset. This parameter is used to determine which trigger to use. If not given the EEG offset will be used by default. Ex. 'EYETRACKER' + apply_system_offset (Optional bool) - if True, applies the system offset loaded from the triggers file. + If False, returns a Trigger with offset of 0.0. Returns ------- The Trigger for the first matching offset for the given device, or a Trigger with offset of 0.0 if a matching offset was not found. """ label = offset_label(device_type) - for trg in triggers: - if trg.type == TriggerType.OFFSET and trg.label == label: - return trg - log.info(f"Offset not found (device_type: {device_type}); using 0.0") + + if apply_system_offset: + for trg in triggers: + if trg.type == TriggerType.OFFSET and trg.label == label: + return trg + log.info(f"Offset not found, or not used (device_type: {device_type}); using 0.0") return Trigger(label, TriggerType.OFFSET, 0.0) @@ -456,10 +461,8 @@ def load(path: str, """ excluded_types = exclusion or [] - starting_offset = 0.0 - if apply_system_offset: - triggers = read(path) - starting_offset = find_starting_offset(triggers, device_type) + triggers = read(path) + starting_offset = find_starting_offset(triggers, device_type, apply_system_offset) return apply_offsets(exclude_types(triggers, excluded_types), starting_offset.time, @@ -516,6 +519,8 @@ def trigger_decoder( exclusion: any TriggerTypes to be filtered from data returned device_type: used to determine which starting_offset value to use; if a 'starting_offset' trigger is found it will be applied. + apply_system_offset: if True, keeps the 'starting_offset' value from the triggers file. + If False, sets it to 0.0. Returns ------- @@ -527,10 +532,7 @@ def trigger_decoder( ] triggers = read(trigger_path) - - starting_offset = 0.0 - if apply_system_offset: - starting_offset = find_starting_offset(triggers, device_type) + starting_offset = find_starting_offset(triggers, device_type, apply_system_offset) filtered = exclude_types(triggers, excluded_types) corrected = apply_offsets(filtered, starting_offset, static_offset=offset) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 9b13246b2..4cf2a615c 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -8,7 +8,7 @@ "type": "bool" }, "acq_mode": { - "value": "EEG+Eyetracker", + "value": "EEG", "section": "acq_config", "readableName": "Acquisition Mode", "helpTip": "Specifies the hardware device(s) used for data collection.", diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index e2df326f4..311909970 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -6,7 +6,6 @@ RAW_DATA_FILENAME, STATIC_AUDIO_PATH, DEFAULT_DEVICE_SPEC_FILENAME, STATIC_IMAGES_PATH, EYE_TRACKER_FILENAME_PREFIX) -from bcipy.preferences import preferences from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) @@ -23,7 +22,6 @@ from bcipy.signal.process import (ERPTransformParams, filter_inquiries, get_default_transform) from bcipy.signal.model.fusion_model import GazeModel -from bcipy.signal.process import filter_inquiries, get_default_transform import numpy as np from matplotlib.figure import Figure from sklearn.metrics import balanced_accuracy_score @@ -167,191 +165,190 @@ def offline_analysis( type_amp = mode_data.daq_type sample_rate = mode_data.sample_rate - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=transform_params.notch_filter_frequency, - bandpass_low=transform_params.filter_low, - bandpass_high=transform_params.filter_high, - bandpass_order=transform_params.filter_order, - downsample_factor=transform_params.down_sampling_rate, - ) + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") - k_folds = parameters.get("k_folds") - model = PcaRdaKdeModel(k_folds=k_folds) + k_folds = parameters.get("k_folds") + model = PcaRdaKdeModel(k_folds=k_folds) - # Process triggers.txt files - trigger_targetness, trigger_timing, _ = trigger_decoder( - offset=static_offset, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - device_type='EEG' - ) + # Process triggers.txt files + trigger_targetness, trigger_timing, _ = trigger_decoder( + offset=static_offset, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + device_type='EEG', + apply_system_offset=True + ) - # update the trigger timing list to account for the initial trial window - corrected_trigger_timing = [timing + trial_window[0] for timing in trigger_timing] - - # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module - # The timestamp column [0] is already excluded. - channel_map = analysis_channels(channels, device_spec) - channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] - log.info(f'Channels used in analysis: {channels_used}') - - data, fs = mode_data.by_channel() - - inquiries, inquiry_labels, inquiry_timing = model.reshaper( - trial_targetness_label=trigger_targetness, - timing_info=corrected_trigger_timing, - eeg_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=window_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer, - ) + # update the trigger timing list to account for the initial trial window + corrected_trigger_timing = [timing + trial_window[0] for timing in trigger_timing] + + # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module + # The timestamp column [0] is already excluded. + channel_map = analysis_channels(channels, device_spec) + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + log.info(f'Channels used in analysis: {channels_used}') + + data, fs = mode_data.by_channel() + + inquiries, inquiry_labels, inquiry_timing = model.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=corrected_trigger_timing, + eeg_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=window_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) - inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) - inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) - trial_duration_samples = int(window_length * fs) - data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) - - # define the training classes using integers, where 0=nontargets/1=targets - labels = inquiry_labels.flatten() - - # train and save the model as a pkl file - log.info("Training model. This will take some time...") - model = PcaRdaKdeModel(k_folds=k_folds) - model.fit(data, labels) - model.metadata = SignalModelMetadata(device_spec=device_spec, - transform=default_transform) - log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") - - save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) - preferences.signal_model_directory = data_folder - - # Using an 80/20 split, report on balanced accuracy - if estimate_balanced_acc: - train_data, test_data, train_labels, test_labels = subset_data(data, labels, test_size=0.2) - dummy_model = PcaRdaKdeModel(k_folds=k_folds) - dummy_model.fit(train_data, train_labels) - probs = dummy_model.predict_proba(test_data) - preds = probs.argmax(-1) - score = balanced_accuracy_score(test_labels, preds) - log.info(f"Balanced acc with 80/20 split: {score}") - del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds - - # this should have uncorrected trigger timing for display purposes - figure_handles = visualize_erp( - mode_data, - channel_map, - trigger_timing, - labels, - trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=data_folder if save_figures else None, - show=show_figures - ) + inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) + inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) + trial_duration_samples = int(window_length * fs) + data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) + + # define the training classes using integers, where 0=nontargets/1=targets + labels = inquiry_labels.flatten() + + # train and save the model as a pkl file + log.info("Training model. This will take some time...") + model = PcaRdaKdeModel(k_folds=k_folds) + model.fit(data, labels) + model.metadata = SignalModelMetadata(device_spec=device_spec, + transform=default_transform) + log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") + + save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) + preferences.signal_model_directory = data_folder + + # Using an 80/20 split, report on balanced accuracy + if estimate_balanced_acc: + train_data, test_data, train_labels, test_labels = subset_data(data, labels, test_size=0.2) + dummy_model = PcaRdaKdeModel(k_folds=k_folds) + dummy_model.fit(train_data, train_labels) + probs = dummy_model.predict_proba(test_data) + preds = probs.argmax(-1) + score = balanced_accuracy_score(test_labels, preds) + log.info(f"Balanced acc with 80/20 split: {score}") + del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds + + # this should have uncorrected trigger timing for display purposes + figure_handles = visualize_erp( + mode_data, + channel_map, + trigger_timing, + labels, + trial_window, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + save_path=data_folder if save_figures else None, + show=show_figures + ) - if device_spec.content_type == "Eyetracker": - print(device_spec) - figure_handles = visualize_gaze( - mode_data, - save_path=data_folder if save_figures else None, - show=True, - raw_plot=True, - ) - - channels = mode_data.channels - type_amp = mode_data.daq_type - sample_rate = mode_data.sample_rate - - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") - channel_map = analysis_channels(channels, device_spec) - - channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] - log.info(f'Channels used in analysis: {channels_used}') - - data, fs = mode_data.by_channel() - - model = GazeModel() - - # Process triggers.txt files (again!) - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - remove_pre_fixation=False, - apply_system_offset=False, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[ - TriggerType.PREVIEW, - TriggerType.EVENT, - TriggerType.FIXATION, - TriggerType.SYSTEM, - TriggerType.OFFSET] - ) - ''' Trigger_timing includes PROMPT and excludes FIXATION ''' - - # Use trigger_timing to generate time windows for each letter flashing - # Take every 10th trigger as the start point of timing. - # trigger_targetness keeps the PROMPT info, use it to find the target symbol. - target_symbols = trigger_symbols[0::11] # target symbols - inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) - - # Find the inquiries starting by the inq_start_times, (9, 100, 180): - inquiries = model.reshaper( - trial_targetness_label=trigger_targetness, - inq_start_times=inq_start, - target_symbols=target_symbols, - gaze_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - poststimulus_length=window_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer - ) - - symbol_set = alphabet() - - # Extract the data for each target label and each eye separately. - # Apply preprocessing: - preprocessed_data = {i: [] for i in symbol_set} - for i in symbol_set: - # Skip if there's no evidence for this symbol: - if len(inquiries[i]) == 0: - continue - - left_eye, right_eye = model.reshaper.extract_eye_info(inquiries[i]) - preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) - - # Train test split: - test_size = int(len(right_eye) * 0.2) - train_size = len(right_eye) - test_size - train_right_eye = right_eye[:train_size] - test_right_eye = right_eye[train_size:] - - train_left_eye = left_eye[:train_size] - test_left_eye = left_eye[train_size:] - - # Fit the model: - model.fit(train_right_eye) - - scores, means, covs = model.get_scores(test_right_eye) - # print(scores) - - # Visualize the results: - figure_handles = visualize_gaze_inquiries( - left_eye, right_eye, - means, covs, - save_path=None, + if device_spec.content_type == "Eyetracker": + print(device_spec) + figure_handles = visualize_gaze( + mode_data, + save_path=data_folder if save_figures else None, show=True, raw_plot=True, ) + channels = mode_data.channels + type_amp = mode_data.daq_type + sample_rate = mode_data.sample_rate + + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + channel_map = analysis_channels(channels, device_spec) + + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + log.info(f'Channels used in analysis: {channels_used}') + + data, fs = mode_data.by_channel() + + model = GazeModel() + + # Extract all Triggers info + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + remove_pre_fixation=False, + apply_system_offset=False, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[ + TriggerType.PREVIEW, + TriggerType.EVENT, + TriggerType.FIXATION, + TriggerType.SYSTEM, + TriggerType.OFFSET], + device_type='EYETRACKER' + ) + ''' Trigger_timing includes PROMPT and excludes FIXATION ''' + + # Use trigger_timing to generate time windows for each letter flashing + # Take every 10th trigger as the start point of timing. + # trigger_symbols keeps the PROMPT info, use it to find the target symbol. + target_symbols = trigger_symbols[0::11] # target symbols + inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) + + # Extract the inquiries dictionary with keys as target symbols and values as inquiry windows: + inquiries = model.reshaper( + inq_start_times=inq_start, + target_symbols=target_symbols, + gaze_data=data, + sample_rate=sample_rate + ) + + symbol_set = alphabet() + + # Extract the data for each target label and each eye separately. + # Apply preprocessing: + preprocessed_data = {i: [] for i in symbol_set} + for i in symbol_set: + # Skip if there's no evidence for this symbol: + if len(inquiries[i]) == 0: + continue + + left_eye, right_eye = model.reshaper.extract_eye_info(inquiries[i]) + preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) + + # Train test split: + test_size = int(len(right_eye) * 0.2) + train_size = len(right_eye) - test_size + train_right_eye = right_eye[:train_size] + test_right_eye = right_eye[train_size:] + + train_left_eye = left_eye[:train_size] + test_left_eye = left_eye[train_size:] + + # Fit the model: + model.fit(train_right_eye) + + scores, means, covs = model.get_scores(test_right_eye) + # print(scores) + + # Visualize the results: + figure_handles = visualize_gaze_inquiries( + left_eye, right_eye, + means, covs, + save_path=None, + show=True, + raw_plot=True, + ) + + breakpoint() + if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") return model, figure_handles From d666df55fd5004ab9b5f43982a9ebce1d7d28edd Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 1 Oct 2023 20:00:25 -0400 Subject: [PATCH 103/330] simulator with sampling design --- bcipy/simulator/interfaces.py | 58 ++++++++ bcipy/simulator/sim_sampler.py | 189 ++++++++++++++++++++++++++ bcipy/simulator/tests/sampler_test.py | 45 ++++++ 3 files changed, 292 insertions(+) create mode 100644 bcipy/simulator/interfaces.py create mode 100644 bcipy/simulator/sim_sampler.py create mode 100644 bcipy/simulator/tests/sampler_test.py diff --git a/bcipy/simulator/interfaces.py b/bcipy/simulator/interfaces.py new file mode 100644 index 000000000..4a5e8a230 --- /dev/null +++ b/bcipy/simulator/interfaces.py @@ -0,0 +1,58 @@ +from abc import ABC +from dataclasses import dataclass + + +@dataclass +class SessionState: + target_symbol: str + inquiry_n: int + series_n: int + target_sentence: str + current_sentence: str + display_alphabet: list[str] + + +class StateManager(ABC): + + def update(self, evidence): + ... + + def is_done(self) -> bool: + ... + + def get_state(self) -> SessionState: + ... + + def add_state(self, state_field, state_value): + pass + + +class ModelHandler(ABC): + + def generate_evidence(self, state: SessionState, features): + ... + + def get_model(self, key=None): + ... + + +class Sampler(ABC): + + def sample(self, state: SessionState): + ... + + +class MetricReferee: + ... + + +class DataEngine(ABC): + + def load(self): + ... + + def transform(self): + ... + + def get_data(self): + ... diff --git a/bcipy/simulator/sim_sampler.py b/bcipy/simulator/sim_sampler.py new file mode 100644 index 000000000..80d428152 --- /dev/null +++ b/bcipy/simulator/sim_sampler.py @@ -0,0 +1,189 @@ +import random +from abc import ABC +from dataclasses import dataclass +from pathlib import Path + +import pandas as pd + +from bcipy.helpers.parameters import Parameters +from bcipy.simulator.interfaces import DataEngine, ModelHandler, Sampler, MetricReferee, StateManager, SessionState +from bcipy.simulator.simulator_base import Simulator +from typing import Optional, Callable, Dict, Any + +import numpy as np + +from bcipy.config import SESSION_DATA_FILENAME, DEFAULT_PARAMETER_FILENAME +from bcipy.helpers import load +from bcipy.helpers.list import grouper +from bcipy.helpers.session import evidence_records, read_session +from bcipy.helpers.symbols import alphabet +from bcipy.signal.model import PcaRdaKdeModel +from bcipy.simulator.helpers.signal_helpers import process_raw_data_for_model, ExtractedExperimentData +from bcipy.simulator.helpers.sim_viz import plot_replay_comparison +from bcipy.simulator.simulator_base import Simulator, SimulatorData + + +class SimulatorCopyPhraseSampler(Simulator): + """Simulator. + + Base class for BciPy Simulations. + + Requirements: + - run closed loop simulation of {TaskType} with {data} with {simulation_params} + """ + + def __init__(self, parameter_path, save_dir, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, + state_manager: StateManager, referee: MetricReferee, source_data_path=None, + verbose=False): + super(SimulatorCopyPhraseSampler, self).__init__() + + self.parameters = self.load_parameters(parameter_path) + self.save_dir = save_dir + self.model_handler: ModelHandler = model_handler + self.sampler: Sampler = sampler + self.referee: MetricReferee = referee + self.state_manager: StateManager = state_manager + + self.data_engine: DataEngine = data_engine + self.source_data_path = source_data_path + + self.symbol_set = alphabet() + self.write_output = False + self.data_loader = None + + # self.signal_models_classes = [PcaRdaKdeModel for m in self.signal_models] # Hardcoded rn + + def run(self): + while not self.state_manager.is_done(): + self.state_manager.add_state('display_alphabet', self.__get_inquiry_alp_subset(self.state_manager.get_state())) + sampled_data = self.sampler.sample(self.state_manager.get_state()) + evidence = self.model_handler.generate_evidence(self.state_manager.get_state(), sampled_data) + + self.state_manager.update(evidence) + + def __get_inquiry_alp_subset(self, state: SessionState): + # TODO put this in own file or object + subset_length = 10 + return random.sample(self.symbol_set, subset_length) + + def load_parameters(self, path): + # TODO validate parameters + parameters = load.load_json_parameters(path, value_cast=True) + sim_parameters = load.load_json_parameters( + "bcipy/simulator/sim_parameters.json", value_cast=True) + + parameters.add_missing_items(sim_parameters) + return parameters + + +class RawDataEngine(DataEngine): + + def __init__(self, source_dirs: list[str], parameters: list[Parameters]): + self.source_dirs: list[str] = source_dirs + self.parameters: list[Parameters] = parameters + self.data: Optional[list[ExtractedExperimentData]] = None + self.trials_by_inquiry: list[np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). + self.symbols_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) + self.labels_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) + self.schema: Optional[pd.DataFrame] = None + self.load() + + def load(self) -> DataEngine: + # formatting data into inquiries + + assert len(self.source_dirs) == len(self.parameters) + + self.data = [process_raw_data_for_model(source_dir, parameter) for source_dir, parameter in + zip(self.source_dirs, self.parameters)] + + for data_source, parameter in zip(self.data, self.parameters): + trigger_targetness, trigger_timing, trigger_symbols = data_source.decoded_triggers + self.trials_by_inquiry.append(np.split(data_source.trials, data_source.inquiries.shape[1], 1)) + self.symbols_by_inquiry.append([list(group) for group in + grouper(trigger_symbols, parameter.get('stim_length'), + incomplete="ignore")]) + + self.labels_by_inquiry.append(data_source.labels) + + return self + + def transform(self) -> DataEngine: + # setting the schema + + cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] + types = [int, int, int, str, int, np.ndarray] + + rows = [] + for d_i in range(len(self.data)): + for i in range(len(self.trials_by_inquiry[d_i])): + symbols = self.symbols_by_inquiry[d_i][i] + inquiry_labels = self.labels_by_inquiry[d_i][i] + inquiry_eeg = self.trials_by_inquiry[d_i][i] + + symbol_rows = [] + for t_i in range(len(symbols)): + channel_eeg_samples_for_t = [channel[t_i] for channel in inquiry_eeg] # (channel_n, sample_n) + row = {'inquiry_n': i, 'trial_n': t_i, 'symbol': symbols[t_i], 'target': inquiry_labels[t_i], + 'eeg': np.array(channel_eeg_samples_for_t)} + + symbol_rows.append(row) + + rows.extend(symbol_rows) + + self.schema = pd.DataFrame(rows) + + return self + + def get_data(self): + return self.schema.copy() if self.schema is not None else self.data + + +class SimpleLetterSampler(Sampler): + + def __init__(self, data_engine: RawDataEngine, params=None, model_reshaper: Callable = None): + self.data_engine: RawDataEngine = data_engine + self.params: Parameters = params if params else self.data_engine.parameters + self.model_input_reshaper: Callable = model_reshaper if model_reshaper else self.__default_reshaper + + self.alphabet: list[str] = params.get('symbol_set') if params else alphabet() + self.data: pd.DataFrame = self.data_engine.transform().get_data() + + def sample(self, state: SessionState) -> np.ndarray: + """ + - randomly generate subset of letters for inquiry, shud eventually be based on language model (stored in state) + - query eeg response by letter + - reshape for model input + + Return: + (n_channel, n_trial, n_sample) + """ + # TODO make map of inquiry_n -> target_symbol, maybe + + inquiry_letter_subset = state.display_alphabet + target_letter = state.target_symbol + eeg_responses = [] + for symbol in inquiry_letter_subset: + is_target = int(symbol == target_letter) + filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') + row = filtered_data.sample( + 1) if len(filtered_data) else None # TODO figure out what to do when no sample is found. e.g no eeg data for nontarget symbol of 'x' + + if row is None: + print("row is None") + breakpoint() + + eeg_responses.append(row['eeg']) + + print(inquiry_letter_subset) + return self.model_input_reshaper(eeg_responses) + + def __default_reshaper(self, eeg_response) -> np.ndarray: + + channels_eeg = [[] for i in range(len(eeg_response[0]))] + for t_i, trial_channels_eeg in enumerate(eeg_response): + for c_i, channel_eeg in enumerate(trial_channels_eeg): + channels_eeg[c_i].append(channel_eeg) + + return np.array(channels_eeg[0]) + +# TODO add typing hints diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py new file mode 100644 index 000000000..e9b4fcbeb --- /dev/null +++ b/bcipy/simulator/tests/sampler_test.py @@ -0,0 +1,45 @@ +import argparse +import random +from pathlib import Path +import numpy as np + +from bcipy.config import DEFAULT_PARAMETER_FILENAME +from bcipy.helpers import load +from bcipy.helpers.load import load_json_parameters +from bcipy.helpers.symbols import alphabet +from bcipy.signal.model import PcaRdaKdeModel +from bcipy.simulator.interfaces import SessionState, Sampler +from bcipy.simulator.sim_factory import SimulationFactory +from bcipy.simulator.sim_sampler import RawDataEngine, SimpleLetterSampler + +if __name__ == "__main__": + args = dict() + args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_18hr58min16sec_-0700"] + args['parameter_path'] = [load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for data_folder in + args['data_folders']] + args['out_dir'] = Path(__file__).resolve().parent + model_file = Path( + "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Calibration_Thu_24_Aug_2023_18hr41min37sec_-0700/model_0.9524_200_800.pkl") + sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) + + data_engine = RawDataEngine(args['data_folders'], args['parameter_path']) + target_phrase = "HELLO_WORLD" + target_symbol = "H" + + display_alp = random.sample(alphabet(), 10) + state: SessionState = SessionState(target_symbol=target_symbol, inquiry_n=0, series_n=0, target_sentence=target_phrase, + current_sentence="", display_alphabet=display_alp) + + sampler: Sampler = SimpleLetterSampler(data_engine) + sample: np.ndarray = sampler.sample(state) + + model = PcaRdaKdeModel() + model = model.load(model_file) + + breakpoint() + eeg_evidence = model.predict(sample, state.display_alphabet, alphabet()) + + print(eeg_evidence.shape) + print(eeg_evidence) + + breakpoint() From e377505e7cddae6b8ea842b002669c778ed94b6d Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 2 Oct 2023 00:14:59 -0400 Subject: [PATCH 104/330] documentation and seperated files --- bcipy/simulator/helpers/data_engine.py | 103 +++++++++++++ bcipy/simulator/helpers/sampler.py | 73 +++++++++ bcipy/simulator/helpers/signal_helpers.py | 3 +- bcipy/simulator/helpers/sim_state.py | 28 ++++ bcipy/simulator/interfaces.py | 47 +----- bcipy/simulator/sim_copy_phrase.py | 8 +- bcipy/simulator/sim_factory.py | 2 +- bcipy/simulator/sim_sampler.py | 172 +++++----------------- bcipy/simulator/simulator_base.py | 13 +- bcipy/simulator/tests/sampler_test.py | 10 +- 10 files changed, 251 insertions(+), 208 deletions(-) create mode 100644 bcipy/simulator/helpers/data_engine.py create mode 100644 bcipy/simulator/helpers/sampler.py create mode 100644 bcipy/simulator/helpers/sim_state.py diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py new file mode 100644 index 000000000..34ae92e5d --- /dev/null +++ b/bcipy/simulator/helpers/data_engine.py @@ -0,0 +1,103 @@ +from abc import ABC +from typing import Optional + +import numpy as np +import pandas as pd + +from bcipy.helpers.list import grouper +from bcipy.helpers.parameters import Parameters +from bcipy.simulator.helpers.signal_helpers import ExtractedExperimentData, process_raw_data_for_model + + +class DataEngine(ABC): + + def load(self): + ... + + def transform(self): + ... + + def get_data(self): + ... + + +class RawDataEngine(DataEngine): + """ + Object that loads in list of previous session data folders and transforms data into implemented schema + """ + + def __init__(self, source_dirs: list[str], parameters: list[Parameters]): + self.source_dirs: list[str] = source_dirs + self.parameters: list[Parameters] = parameters + self.data: Optional[list[ExtractedExperimentData]] = None + self.trials_by_inquiry: list[np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). + self.symbols_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) + self.labels_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) + self.schema: Optional[pd.DataFrame] = None + self.load() + + def load(self) -> DataEngine: + """ + Processes raw data from data folders using provided parameter files. + - Extracts and stores trial data, stimuli, and stimuli_labels by inquiries + + Returns: + self for chaining + """ + assert len(self.source_dirs) == len(self.parameters) + + self.data = [process_raw_data_for_model(source_dir, parameter) for source_dir, parameter in + zip(self.source_dirs, self.parameters)] + + for data_source, parameter in zip(self.data, self.parameters): + trigger_targetness, trigger_timing, trigger_symbols = data_source.decoded_triggers + self.trials_by_inquiry.append(np.split(data_source.trials, data_source.inquiries.shape[1], 1)) + self.symbols_by_inquiry.append([list(group) for group in + grouper(trigger_symbols, parameter.get('stim_length'), + incomplete="ignore")]) + + self.labels_by_inquiry.append(data_source.labels) + + return self + + def transform(self) -> DataEngine: + """ + Organizes all data into the following schema + - Dataframe {"series_n":int, "inquiry_n":int, "trial_n":int, "symbol":str, "target":int, "eeg":ndarray} + + The "eeg" data for trial looks like this + - ndarray.shape = (channel_n, sample_n) + - a trial is an eeg response for a symbol being displayed + + Returns: + self for chaining + """ + + cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] + types = [int, int, int, str, int, np.ndarray] + + rows = [] + for d_i in range(len(self.data)): + for i in range(len(self.trials_by_inquiry[d_i])): + symbols = self.symbols_by_inquiry[d_i][i] + inquiry_labels = self.labels_by_inquiry[d_i][i] + inquiry_eeg = self.trials_by_inquiry[d_i][i] + + symbol_rows = [] + for t_i in range(len(symbols)): + channel_eeg_samples_for_t = [channel[t_i] for channel in inquiry_eeg] # (channel_n, sample_n) + row = {'inquiry_n': i, 'trial_n': t_i, 'symbol': symbols[t_i], 'target': inquiry_labels[t_i], + 'eeg': np.array(channel_eeg_samples_for_t)} + + symbol_rows.append(row) + + rows.extend(symbol_rows) + + self.schema = pd.DataFrame(rows) + + return self + + def get_data(self): + return self.schema.copy() if self.schema is not None else self.data + +# TODO ReplaySessionDataEngine \ No newline at end of file diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py new file mode 100644 index 000000000..28d5c8227 --- /dev/null +++ b/bcipy/simulator/helpers/sampler.py @@ -0,0 +1,73 @@ +from abc import ABC +from typing import Callable + +import numpy as np +import pandas as pd + +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.symbols import alphabet +from bcipy.simulator.helpers.data_engine import RawDataEngine +from bcipy.simulator.interfaces import SimSessionState + + +class Sampler(ABC): + """ Interface to generate sample of data usable by a model """ + + def sample(self, state: SimSessionState): + ... + + def set_reshaper(self, reshaper: Callable): + ... + + +class SimpleLetterSampler(Sampler): + + def __init__(self, data_engine: RawDataEngine, params=None): + self.data_engine: RawDataEngine = data_engine + self.params: Parameters = params if params else self.data_engine.parameters + self.model_input_reshaper: Callable = self.__default_reshaper + + self.alphabet: list[str] = params.get('symbol_set') if params else alphabet() + self.data: pd.DataFrame = self.data_engine.transform().get_data() + + def sample(self, state: SimSessionState) -> np.ndarray: + """ + - query eeg response by letter + - reshape for signal model input + + Return: + nd array (n_channel, n_trial, n_sample) + """ + + inquiry_letter_subset = state.display_alphabet + target_letter = state.target_symbol + eeg_responses = [] + for symbol in inquiry_letter_subset: + is_target = int(symbol == target_letter) + filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') + row = filtered_data.sample( + 1) if len(filtered_data) else None # TODO figure out what to do when no sample is found. e.g no eeg data for nontarget symbol of 'x' + + if row is None: + print("row is None") + breakpoint() + + eeg_responses.append(row['eeg']) + + print(inquiry_letter_subset) + return self.model_input_reshaper(eeg_responses) + + def set_reshaper(self, reshaper: Callable): + self.model_input_reshaper = reshaper + + def __default_reshaper(self, eeg_response) -> np.ndarray: + + channels_eeg = [[] for i in range(len(eeg_response[0]))] + for t_i, trial_channels_eeg in enumerate(eeg_response): + for c_i, channel_eeg in enumerate(trial_channels_eeg): + channels_eeg[c_i].append(channel_eeg) + + return np.array(channels_eeg[0]) + + +# TODO ReplaySampler \ No newline at end of file diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 698cd94ca..7dfae2051 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -30,7 +30,7 @@ @dataclass() -class ExtractedExperimentData: # TODO clean up design +class ExtractedExperimentData: # TODO clean up design inquiries: np.ndarray trials: np.ndarray labels: list @@ -40,7 +40,6 @@ class ExtractedExperimentData: # TODO clean up design def process_raw_data_for_model(data_folder, parameters, model_class=PcaRdaKdeModel) -> ExtractedExperimentData: - assert parameters, "Parameters are required for offline analysis." if not data_folder: data_folder = load_experimental_data() diff --git a/bcipy/simulator/helpers/sim_state.py b/bcipy/simulator/helpers/sim_state.py new file mode 100644 index 000000000..19ddfc1a1 --- /dev/null +++ b/bcipy/simulator/helpers/sim_state.py @@ -0,0 +1,28 @@ +from abc import ABC +from dataclasses import dataclass + + +@dataclass +class SimSessionState: + """ Represents the state of a current session during simulation """ + target_symbol: str + current_sentence: str + target_sentence: str + display_alphabet: list[str] + inquiry_n: int + series_n: int + + +class StateManager(ABC): + + def update(self, evidence): + ... + + def is_done(self) -> bool: + ... + + def get_state(self) -> SimSessionState: + ... + + def add_state(self, state_field, state_value): + pass diff --git a/bcipy/simulator/interfaces.py b/bcipy/simulator/interfaces.py index 4a5e8a230..55a9e6e0c 100644 --- a/bcipy/simulator/interfaces.py +++ b/bcipy/simulator/interfaces.py @@ -1,58 +1,15 @@ from abc import ABC -from dataclasses import dataclass - - -@dataclass -class SessionState: - target_symbol: str - inquiry_n: int - series_n: int - target_sentence: str - current_sentence: str - display_alphabet: list[str] - - -class StateManager(ABC): - - def update(self, evidence): - ... - - def is_done(self) -> bool: - ... - - def get_state(self) -> SessionState: - ... - - def add_state(self, state_field, state_value): - pass +from bcipy.simulator.helpers.sim_state import SimSessionState class ModelHandler(ABC): - def generate_evidence(self, state: SessionState, features): + def generate_evidence(self, state: SimSessionState, features): ... def get_model(self, key=None): ... -class Sampler(ABC): - - def sample(self, state: SessionState): - ... - - class MetricReferee: ... - - -class DataEngine(ABC): - - def load(self): - ... - - def transform(self): - ... - - def get_data(self): - ... diff --git a/bcipy/simulator/sim_copy_phrase.py b/bcipy/simulator/sim_copy_phrase.py index 95300dc87..525aab094 100644 --- a/bcipy/simulator/sim_copy_phrase.py +++ b/bcipy/simulator/sim_copy_phrase.py @@ -10,7 +10,7 @@ from bcipy.signal.model import PcaRdaKdeModel from bcipy.simulator.helpers.signal_helpers import process_raw_data_for_model, ExtractedExperimentData from bcipy.simulator.helpers.sim_viz import plot_replay_comparison -from bcipy.simulator.simulator_base import Simulator, SimulatorData +from bcipy.simulator.simulator_base import Simulator class SimulatorCopyPhraseReplay(Simulator): @@ -36,7 +36,7 @@ def __init__(self, parameter_path, save_dir, signal_models: [tuple], language_mo self.write_output = False self.data_loader = None - self.signal_models_classes = [PcaRdaKdeModel for m in self.signal_models] # Hardcoded rn + self.signal_models_classes = [PcaRdaKdeModel for m in self.signal_models] # Hardcoded rn def run(self): self.init_data_loader() @@ -44,7 +44,7 @@ def run(self): self.logger.info(f"Initialized data loader") # TODO need to support multimodal and language models - model_file, model_class = self.signal_models[0], self.signal_models_classes[0] # hardcoded rn + model_file, model_class = self.signal_models[0], self.signal_models_classes[0] # hardcoded rn model = model_class(self.parameters.get("k_folds")) model = model.load(model_file) @@ -105,7 +105,7 @@ def load_parameters(self, path): return parameters -class ReplayDataLoader(SimulatorData): +class ReplayDataLoader: def __init__(self, source_path, parameters): self.source_path = source_path diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 68c83a2aa..38fbb5f73 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -26,4 +26,4 @@ def create( return SimulatorCopyPhraseReplay(parameter_path, out_dir, smodel_files, lmodel_files, data_folders[0], verbose=kwargs.get('verbose', False)) - # parameter_path, save_dir, signal_models: [tuple], language_models, replay_data_path=None, + # TODO refactor for sampling simulator diff --git a/bcipy/simulator/sim_sampler.py b/bcipy/simulator/sim_sampler.py index 80d428152..9b26c3cf0 100644 --- a/bcipy/simulator/sim_sampler.py +++ b/bcipy/simulator/sim_sampler.py @@ -1,56 +1,56 @@ import random -from abc import ABC -from dataclasses import dataclass -from pathlib import Path -import pandas as pd - -from bcipy.helpers.parameters import Parameters -from bcipy.simulator.interfaces import DataEngine, ModelHandler, Sampler, MetricReferee, StateManager, SessionState +from bcipy.helpers import load +from bcipy.helpers.symbols import alphabet +from bcipy.simulator.helpers.data_engine import DataEngine +from bcipy.simulator.helpers.sampler import Sampler +from bcipy.simulator.helpers.sim_state import StateManager, SimSessionState +from bcipy.simulator.interfaces import MetricReferee, ModelHandler from bcipy.simulator.simulator_base import Simulator -from typing import Optional, Callable, Dict, Any -import numpy as np -from bcipy.config import SESSION_DATA_FILENAME, DEFAULT_PARAMETER_FILENAME -from bcipy.helpers import load -from bcipy.helpers.list import grouper -from bcipy.helpers.session import evidence_records, read_session -from bcipy.helpers.symbols import alphabet -from bcipy.signal.model import PcaRdaKdeModel -from bcipy.simulator.helpers.signal_helpers import process_raw_data_for_model, ExtractedExperimentData -from bcipy.simulator.helpers.sim_viz import plot_replay_comparison -from bcipy.simulator.simulator_base import Simulator, SimulatorData +class SimulatorCopyPhrase(Simulator): + """ + Copy Phrase simulator. -class SimulatorCopyPhraseSampler(Simulator): - """Simulator. + Run loop: + - The loop runs until StateManager determines simulation is over + - The generated stimuli are passed into sampler, which returns some eeg response + - The Model handler will generate predictions and feed back into StateManager + - StateManager will resolve the state while the MetricReferee observes and records any metrics - Base class for BciPy Simulations. + Main components: + - DataEngine: loading and storing data + - Sampler: logic for sampling from data, composed of DataEngine + - StateManager: manages run loop details and fuses model evidence with current state + - MetricReferee: tracks and scores the simulation on different metrics for later evaluation + - ModelHandler: wrapper for models that deals with loading in models and generating evidence Requirements: - run closed loop simulation of {TaskType} with {data} with {simulation_params} """ - def __init__(self, parameter_path, save_dir, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, source_data_path=None, - verbose=False): - super(SimulatorCopyPhraseSampler, self).__init__() + def __init__(self, parameter_path: str, save_dir: str, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, + state_manager: StateManager, referee: MetricReferee, verbose=False, visualize=False): + super(SimulatorCopyPhrase, self).__init__() self.parameters = self.load_parameters(parameter_path) - self.save_dir = save_dir + self.save_dir: str = save_dir self.model_handler: ModelHandler = model_handler self.sampler: Sampler = sampler self.referee: MetricReferee = referee self.state_manager: StateManager = state_manager self.data_engine: DataEngine = data_engine - self.source_data_path = source_data_path self.symbol_set = alphabet() self.write_output = False self.data_loader = None + self.verbose = verbose + self.visualize = visualize + # self.signal_models_classes = [PcaRdaKdeModel for m in self.signal_models] # Hardcoded rn def run(self): @@ -61,7 +61,9 @@ def run(self): self.state_manager.update(evidence) - def __get_inquiry_alp_subset(self, state: SessionState): + # TODO visualize results + + def __get_inquiry_alp_subset(self, state: SimSessionState): # TODO put this in own file or object subset_length = 10 return random.sample(self.symbol_set, subset_length) @@ -75,115 +77,7 @@ def load_parameters(self, path): parameters.add_missing_items(sim_parameters) return parameters + def get_param(self, name): + pass -class RawDataEngine(DataEngine): - - def __init__(self, source_dirs: list[str], parameters: list[Parameters]): - self.source_dirs: list[str] = source_dirs - self.parameters: list[Parameters] = parameters - self.data: Optional[list[ExtractedExperimentData]] = None - self.trials_by_inquiry: list[np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). - self.symbols_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) - self.labels_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) - self.schema: Optional[pd.DataFrame] = None - self.load() - - def load(self) -> DataEngine: - # formatting data into inquiries - - assert len(self.source_dirs) == len(self.parameters) - - self.data = [process_raw_data_for_model(source_dir, parameter) for source_dir, parameter in - zip(self.source_dirs, self.parameters)] - - for data_source, parameter in zip(self.data, self.parameters): - trigger_targetness, trigger_timing, trigger_symbols = data_source.decoded_triggers - self.trials_by_inquiry.append(np.split(data_source.trials, data_source.inquiries.shape[1], 1)) - self.symbols_by_inquiry.append([list(group) for group in - grouper(trigger_symbols, parameter.get('stim_length'), - incomplete="ignore")]) - - self.labels_by_inquiry.append(data_source.labels) - - return self - - def transform(self) -> DataEngine: - # setting the schema - - cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] - types = [int, int, int, str, int, np.ndarray] - - rows = [] - for d_i in range(len(self.data)): - for i in range(len(self.trials_by_inquiry[d_i])): - symbols = self.symbols_by_inquiry[d_i][i] - inquiry_labels = self.labels_by_inquiry[d_i][i] - inquiry_eeg = self.trials_by_inquiry[d_i][i] - - symbol_rows = [] - for t_i in range(len(symbols)): - channel_eeg_samples_for_t = [channel[t_i] for channel in inquiry_eeg] # (channel_n, sample_n) - row = {'inquiry_n': i, 'trial_n': t_i, 'symbol': symbols[t_i], 'target': inquiry_labels[t_i], - 'eeg': np.array(channel_eeg_samples_for_t)} - - symbol_rows.append(row) - - rows.extend(symbol_rows) - - self.schema = pd.DataFrame(rows) - - return self - - def get_data(self): - return self.schema.copy() if self.schema is not None else self.data - - -class SimpleLetterSampler(Sampler): - - def __init__(self, data_engine: RawDataEngine, params=None, model_reshaper: Callable = None): - self.data_engine: RawDataEngine = data_engine - self.params: Parameters = params if params else self.data_engine.parameters - self.model_input_reshaper: Callable = model_reshaper if model_reshaper else self.__default_reshaper - - self.alphabet: list[str] = params.get('symbol_set') if params else alphabet() - self.data: pd.DataFrame = self.data_engine.transform().get_data() - - def sample(self, state: SessionState) -> np.ndarray: - """ - - randomly generate subset of letters for inquiry, shud eventually be based on language model (stored in state) - - query eeg response by letter - - reshape for model input - - Return: - (n_channel, n_trial, n_sample) - """ - # TODO make map of inquiry_n -> target_symbol, maybe - - inquiry_letter_subset = state.display_alphabet - target_letter = state.target_symbol - eeg_responses = [] - for symbol in inquiry_letter_subset: - is_target = int(symbol == target_letter) - filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') - row = filtered_data.sample( - 1) if len(filtered_data) else None # TODO figure out what to do when no sample is found. e.g no eeg data for nontarget symbol of 'x' - - if row is None: - print("row is None") - breakpoint() - - eeg_responses.append(row['eeg']) - - print(inquiry_letter_subset) - return self.model_input_reshaper(eeg_responses) - - def __default_reshaper(self, eeg_response) -> np.ndarray: - - channels_eeg = [[] for i in range(len(eeg_response[0]))] - for t_i, trial_channels_eeg in enumerate(eeg_response): - for c_i, channel_eeg in enumerate(trial_channels_eeg): - channels_eeg[c_i].append(channel_eeg) - - return np.array(channels_eeg[0]) - -# TODO add typing hints +# TODO add stronger typing hints diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py index 283000da3..96f0cbac0 100644 --- a/bcipy/simulator/simulator_base.py +++ b/bcipy/simulator/simulator_base.py @@ -22,15 +22,4 @@ def run(self): @abstractmethod def get_param(self, name): - ... - - -class SimulatorData(ABC): - - @abstractmethod - def next(self): - ... - - @abstractmethod - def is_end(self) -> bool: - ... + ... \ No newline at end of file diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index e9b4fcbeb..de68850b5 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -8,9 +8,9 @@ from bcipy.helpers.load import load_json_parameters from bcipy.helpers.symbols import alphabet from bcipy.signal.model import PcaRdaKdeModel -from bcipy.simulator.interfaces import SessionState, Sampler -from bcipy.simulator.sim_factory import SimulationFactory -from bcipy.simulator.sim_sampler import RawDataEngine, SimpleLetterSampler +from bcipy.simulator.helpers.sampler import Sampler, SimpleLetterSampler +from bcipy.simulator.interfaces import SimSessionState +from bcipy.simulator.sim_sampler import RawDataEngine if __name__ == "__main__": args = dict() @@ -27,8 +27,8 @@ target_symbol = "H" display_alp = random.sample(alphabet(), 10) - state: SessionState = SessionState(target_symbol=target_symbol, inquiry_n=0, series_n=0, target_sentence=target_phrase, - current_sentence="", display_alphabet=display_alp) + state: SimSessionState = SimSessionState(target_symbol=target_symbol, inquiry_n=0, series_n=0, target_sentence=target_phrase, + current_sentence="", display_alphabet=display_alp) sampler: Sampler = SimpleLetterSampler(data_engine) sample: np.ndarray = sampler.sample(state) From 845dbfcf37259584bd8c0b16925cb2334541cbca Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Wed, 4 Oct 2023 18:00:41 -0400 Subject: [PATCH 105/330] PR comments addressed --- bcipy/helpers/load.py | 13 ---- bcipy/helpers/stimuli.py | 82 ++++++++++++++------------ bcipy/helpers/triggers.py | 2 +- bcipy/helpers/visualization.py | 40 ++++++++----- bcipy/parameters/devices.json | 2 +- bcipy/parameters/parameters.json | 2 +- bcipy/signal/model/offline_analysis.py | 8 +-- bcipy/signal/process/__init__.py | 4 +- bcipy/signal/process/extract_gaze.py | 47 +++++++++++++++ 9 files changed, 126 insertions(+), 74 deletions(-) create mode 100644 bcipy/signal/process/extract_gaze.py diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index d7474ccfd..5d45b7070 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -159,19 +159,6 @@ def load_experimental_data() -> str: return filename -def load_eye_tracking_data(gaze_data: RawData): - left_eye_channel_map = [0, 0, 1, 1, 0, 0, 0, 0, 0] - left_eye_data, _, _ = gaze_data.by_channel_map(left_eye_channel_map) - left_eye_x = left_eye_data[0] - left_eye_y = left_eye_data[1] - - right_eye_channel_map = [0, 0, 0, 0, 0, 1, 1, 0, 0] - right_eye_data, _, _ = gaze_data.by_channel_map(right_eye_channel_map) - right_eye_x = right_eye_data[0] - right_eye_y = right_eye_data[1] - return left_eye_x, left_eye_y, right_eye_x, right_eye_y - - def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: """Load all signal models in a given directory. diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index f574565ed..3cf190f73 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -12,7 +12,7 @@ from pandas import Series from PIL import Image -from bcipy.helpers.exceptions import BciPyCoreException, SignalException +from bcipy.helpers.exceptions import BciPyCoreException from bcipy.helpers.list import grouper from bcipy.helpers.symbols import alphabet @@ -238,7 +238,13 @@ def __call__(self, sample_rate: int, channel_map: List[int] = None, ) -> dict: - """Extract inquiry data and labels. + """Extract inquiry data and labels. Different from the EEG inquiry, the gaze inquiry window starts with + the first flicker and ends with the last flicker in the inquiry. Each inquiry has a length of ~3 seconds. + The labels are provided in the target_symbols list. It returns a Dict, where keys are the target symbols and + the values are inquiries (appended in order of appearance) where the corresponding target symbol is prompted. + Optional outputs: + reshape_data is the list of data reshaped into (Inquiries, Channels, Samples), where inquirires are appended + in chronological order. labels returns the list of target symbols in each inquiry. Args: inq_start_times (List[float]): Timestamp of each event in seconds @@ -249,11 +255,11 @@ def __call__(self, Defaults to None; all channels will be used. Returns: - reshaped_data (List[float]): inquiry data of shape (Inquiries, Channels, Samples) - labels (List[str]): Target letter in each inquiry. - data_by_targets (dict): Dictionary where keys are the symbol set and values are the appended inquiries for each symbol. dict[Key] = (np.ndarray) of shape (Channels, Samples) + + reshaped_data (List[float]) [optional]: inquiry data of shape (Inquiries, Channels, Samples) + labels (List[str]) [optional] : Target symbol in each inquiry. """ if channel_map: # Remove the channels that we are not interested in @@ -315,48 +321,48 @@ def __call__(self, # return np.stack(reshaped_data, 0), labels return data_by_targets - @staticmethod - def extract_eye_info(data): - """ Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples - Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. + # @staticmethod + # def extract_eye_info(data): + # """ Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples + # Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. - Args: - data (np.ndarray): Data in shape of num_channels x num_samples + # Args: + # data (np.ndarray): Data in shape of num_channels x num_samples - Returns: - left_eye (np.ndarray), left_pupil (List(float)) - right_eye (np.ndarray), right_pupil (List(float)) - """ + # Returns: + # left_eye (np.ndarray), left_pupil (List(float)) + # right_eye (np.ndarray), right_pupil (List(float)) + # """ - # Extract samples from channels - lx = data[2, :] - ly = data[3, :] - left_pupil = data[4, :] # Use if needed + # # Extract samples from channels + # lx = data[2, :] + # ly = data[3, :] + # left_pupil = data[4, :] # Use if needed - rx = data[5, :] - ry = data[6, :] - right_pupil = data[7, :] + # rx = data[5, :] + # ry = data[6, :] + # right_pupil = data[7, :] - left_eye = np.vstack((np.array(lx), np.array(ly))).T - right_eye = np.vstack((np.array(rx), np.array(ry))).T + # left_eye = np.vstack((np.array(lx), np.array(ly))).T + # right_eye = np.vstack((np.array(rx), np.array(ry))).T - # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. - # Make sure that the number of samples are the same for both eyes - left_eye_nan_idx = np.isnan(left_eye).any(axis=1) - left_eye = left_eye[~left_eye_nan_idx] - right_eye = right_eye[~left_eye_nan_idx] + # # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. + # # Make sure that the number of samples are the same for both eyes + # left_eye_nan_idx = np.isnan(left_eye).any(axis=1) + # left_eye = left_eye[~left_eye_nan_idx] + # right_eye = right_eye[~left_eye_nan_idx] - right_eye_nan_idx = np.isnan(right_eye).any(axis=1) - left_eye = left_eye[~right_eye_nan_idx] - right_eye = right_eye[~right_eye_nan_idx] + # right_eye_nan_idx = np.isnan(right_eye).any(axis=1) + # left_eye = left_eye[~right_eye_nan_idx] + # right_eye = right_eye[~right_eye_nan_idx] - try: - len(left_eye) != len(right_eye) - except AssertionError: - raise SignalException( - 'Number of samples for left and right eye are not the same.') + # try: + # len(left_eye) != len(right_eye) + # except AssertionError: + # raise SignalException( + # 'Number of samples for left and right eye are not the same.') - return left_eye, right_eye + # return left_eye, right_eye class TrialReshaper(Reshaper): diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index ce38f9397..505784256 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -519,7 +519,7 @@ def trigger_decoder( exclusion: any TriggerTypes to be filtered from data returned device_type: used to determine which starting_offset value to use; if a 'starting_offset' trigger is found it will be applied. - apply_system_offset: if True, keeps the 'starting_offset' value from the triggers file. + apply_system_offset: if True, keeps the 'starting_offset' value from the triggers file. If False, sets it to 0.0. Returns diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index dd7b17019..c7295d770 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -28,6 +28,22 @@ log = logging.getLogger(__name__) +def clip_to_display(data, screen_limits): + """Clip to Display. This function is used to clip the eye data to the display size. Removes + > 1 values and < 0 values. Removes nan values. + + Input: + data (np.ndarray): Eye data + screen_limits (tuple): Screen limits + + Output: + clipped_data (np.ndarray): Clipped eye data + """ + clipped_data = np.clip(data, screen_limits[0], screen_limits[1]) + clipped_data = clipped_data[~np.isnan(clipped_data)] + + return clipped_data + def visualize_erp( raw_data: RawData, @@ -140,21 +156,19 @@ def visualize_gaze( right_eye_x = right_eye_data[0] right_eye_y = right_eye_data[1] eye_data = (left_eye_x, left_eye_y, right_eye_x, right_eye_y) - - # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis - lx = np.clip(left_eye_x, 0, 1) - ly = np.clip(left_eye_y, 0, 1) - rx = np.clip(right_eye_x, 0, 1) - ry = np.clip(right_eye_y, 0, 1) + + # Transform the eye data to fit the display. Remove values < 1 & > 0, remove nan values + screen_limits = (0, 1) + clipped_data = [] + for i in eye_data: + clipped_data.append(clip_to_display(i, screen_limits)) + + lx, ly, rx, ry = clipped_data + + # Flip y axis ly = 1 - ly ry = 1 - ry - # remove nan values - lx = lx[~np.isnan(lx)] - ly = ly[~np.isnan(ly)] - rx = rx[~np.isnan(rx)] - ry = ry[~np.isnan(ry)] - # scale the eye data to the image fig, ax = plt.subplots() ax.imshow(img, extent=[0, 1, 0, 1]) @@ -427,8 +441,6 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi trial_window = parameters.get("trial_window") static_offset = parameters.get("static_trigger_offset") - # TODO check for existence of these files and throw error if not found - # TODO check for other data types (tobii) raw_data = load_raw_data(Path(session_path, f'{RAW_DATA_FILENAME}.csv')) channels = raw_data.channels sample_rate = raw_data.sample_rate diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index 381284398..48af0e2bc 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -84,7 +84,7 @@ "description": "GTec g.USBamp" }, { - "name": "Tobii-P0", + "name": "Tobii Nano", "content_type": "Eyetracker", "channels": [ { "name": "device_ts", "label": "device_ts" }, diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 4cf2a615c..9b13246b2 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -8,7 +8,7 @@ "type": "bool" }, "acq_mode": { - "value": "EEG", + "value": "EEG+Eyetracker", "section": "acq_config", "readableName": "Acquisition Mode", "helpTip": "Specifies the hardware device(s) used for data collection.", diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 311909970..972673a1c 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -20,7 +20,7 @@ from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import (ERPTransformParams, filter_inquiries, - get_default_transform) + get_default_transform, extract_eye_info) from bcipy.signal.model.fusion_model import GazeModel import numpy as np from matplotlib.figure import Figure @@ -153,7 +153,7 @@ def offline_analysis( f"Static offset: {static_offset}" ) - # Load raw data: [RawData(Tobii-P0), RawData(DSI-24)] + # raw_data: [RawData(EyeTracker, RawData(EEG)] raw_data = load_raw_data(data_folder, data_file_paths) for mode_data in raw_data: @@ -258,7 +258,6 @@ def offline_analysis( ) if device_spec.content_type == "Eyetracker": - print(device_spec) figure_handles = visualize_gaze( mode_data, save_path=data_folder if save_figures else None, @@ -320,7 +319,7 @@ def offline_analysis( if len(inquiries[i]) == 0: continue - left_eye, right_eye = model.reshaper.extract_eye_info(inquiries[i]) + left_eye, right_eye = extract_eye_info(inquiries[i]) preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) # Train test split: @@ -336,7 +335,6 @@ def offline_analysis( model.fit(train_right_eye) scores, means, covs = model.get_scores(test_right_eye) - # print(scores) # Visualize the results: figure_handles = visualize_gaze_inquiries( diff --git a/bcipy/signal/process/__init__.py b/bcipy/signal/process/__init__.py index ce21a5ae5..e2239aab0 100644 --- a/bcipy/signal/process/__init__.py +++ b/bcipy/signal/process/__init__.py @@ -2,11 +2,13 @@ from bcipy.signal.process.transform import (Composition, Downsample, ERPTransformParams, get_default_transform) +from bcipy.signal.process.extract_gaze import extract_eye_info __all__ = [ "filter_inquiries", "get_default_transform", "Downsample", "Composition", - "ERPTransformParams" + "ERPTransformParams", + "extract_eye_info" ] diff --git a/bcipy/signal/process/extract_gaze.py b/bcipy/signal/process/extract_gaze.py new file mode 100644 index 000000000..c208438d2 --- /dev/null +++ b/bcipy/signal/process/extract_gaze.py @@ -0,0 +1,47 @@ +import numpy as np + +from bcipy.helpers.exceptions import SignalException + +def extract_eye_info(data): + """"Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples + Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. + The data is extracted according to the channel map: + ['device_ts, 'system_ts', 'left_x', 'left_y', 'left_pupil', 'right_x', 'right_y', 'right_pupil'] + + Args: + data (np.ndarray): Data in shape of num_channels x num_samples + + Returns: + left_eye (np.ndarray), left_pupil (List(float)) + right_eye (np.ndarray), right_pupil (List(float)) + """ + + # Extract samples from channels + lx = data[2, :] + ly = data[3, :] + left_pupil = data[4, :] # Use if needed + + rx = data[5, :] + ry = data[6, :] + right_pupil = data[7, :] # Use if needed + + left_eye = np.vstack((np.array(lx), np.array(ly))).T + right_eye = np.vstack((np.array(rx), np.array(ry))).T + + # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. + # Make sure that the number of samples are the same for both eyes + left_eye_nan_idx = np.isnan(left_eye).any(axis=1) + left_eye = left_eye[~left_eye_nan_idx] + right_eye = right_eye[~left_eye_nan_idx] + + right_eye_nan_idx = np.isnan(right_eye).any(axis=1) + left_eye = left_eye[~right_eye_nan_idx] + right_eye = right_eye[~right_eye_nan_idx] + + try: + len(left_eye) != len(right_eye) + except AssertionError: + raise SignalException( + 'Number of samples for left and right eye are not the same.') + + return left_eye, right_eye \ No newline at end of file From bc202ada53c58ccf866501aeaf6a98d19ebcf6be Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 8 Oct 2023 17:41:44 -0400 Subject: [PATCH 106/330] resolve PR comments --- bcipy/simulator/helpers/data_engine.py | 31 ++++++++++++++--------- bcipy/simulator/helpers/sampler.py | 23 +++++++---------- bcipy/simulator/helpers/signal_helpers.py | 31 ++++++++--------------- bcipy/simulator/sim_sampler.py | 4 +-- bcipy/simulator/tests/sampler_test.py | 10 +++----- 5 files changed, 42 insertions(+), 57 deletions(-) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 34ae92e5d..dd668c18f 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,9 +1,12 @@ from abc import ABC -from typing import Optional +from pathlib import Path +from typing import Optional, List import numpy as np import pandas as pd +from bcipy.config import DEFAULT_PARAMETER_FILENAME +from bcipy.helpers import load from bcipy.helpers.list import grouper from bcipy.helpers.parameters import Parameters from bcipy.simulator.helpers.signal_helpers import ExtractedExperimentData, process_raw_data_for_model @@ -26,13 +29,15 @@ class RawDataEngine(DataEngine): Object that loads in list of previous session data folders and transforms data into implemented schema """ - def __init__(self, source_dirs: list[str], parameters: list[Parameters]): - self.source_dirs: list[str] = source_dirs - self.parameters: list[Parameters] = parameters - self.data: Optional[list[ExtractedExperimentData]] = None - self.trials_by_inquiry: list[np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). - self.symbols_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) - self.labels_by_inquiry: list[list] = [] # shape (i_inquiry, s_alphabet_subset) + def __init__(self, source_dirs: List[str]): + # TODO read parameters from source dirx + # TODO maybe rely upon single source of data, write some scripts that clean data and group them + self.source_dirs: List[str] = source_dirs + self.parameter_files: List[Parameters] = [] + self.data: Optional[List[ExtractedExperimentData]] = None + self.trials_by_inquiry: List[np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). + self.symbols_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) + self.labels_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) self.schema: Optional[pd.DataFrame] = None self.load() @@ -44,12 +49,14 @@ def load(self) -> DataEngine: Returns: self for chaining """ - assert len(self.source_dirs) == len(self.parameters) + self.parameter_files = [load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for data_folder in self.source_dirs] + + assert len(self.source_dirs) == len(self.parameter_files) # TODO more general parameter validation function self.data = [process_raw_data_for_model(source_dir, parameter) for source_dir, parameter in - zip(self.source_dirs, self.parameters)] + zip(self.source_dirs, self.parameter_files)] - for data_source, parameter in zip(self.data, self.parameters): + for data_source, parameter in zip(self.data, self.parameter_files): trigger_targetness, trigger_timing, trigger_symbols = data_source.decoded_triggers self.trials_by_inquiry.append(np.split(data_source.trials, data_source.inquiries.shape[1], 1)) self.symbols_by_inquiry.append([list(group) for group in @@ -100,4 +107,4 @@ def transform(self) -> DataEngine: def get_data(self): return self.schema.copy() if self.schema is not None else self.data -# TODO ReplaySessionDataEngine \ No newline at end of file +# TODO ReplaySessionDataEngine diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 28d5c8227..62dfdad4f 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -1,9 +1,10 @@ from abc import ABC -from typing import Callable +from typing import Callable, List import numpy as np import pandas as pd +from bcipy.helpers.exceptions import TaskConfigurationException from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import RawDataEngine @@ -22,12 +23,11 @@ def set_reshaper(self, reshaper: Callable): class SimpleLetterSampler(Sampler): - def __init__(self, data_engine: RawDataEngine, params=None): + def __init__(self, data_engine: RawDataEngine, params: List[Parameters] = None): self.data_engine: RawDataEngine = data_engine - self.params: Parameters = params if params else self.data_engine.parameters + self.parameter_files: List[Parameters] = params if params else self.data_engine.parameter_files self.model_input_reshaper: Callable = self.__default_reshaper - - self.alphabet: list[str] = params.get('symbol_set') if params else alphabet() + self.alphabet: List[str] = params[0].get('symbol_set') if params else alphabet() self.data: pd.DataFrame = self.data_engine.transform().get_data() def sample(self, state: SimSessionState) -> np.ndarray: @@ -45,16 +45,12 @@ def sample(self, state: SimSessionState) -> np.ndarray: for symbol in inquiry_letter_subset: is_target = int(symbol == target_letter) filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') - row = filtered_data.sample( - 1) if len(filtered_data) else None # TODO figure out what to do when no sample is found. e.g no eeg data for nontarget symbol of 'x' - - if row is None: - print("row is None") - breakpoint() + if not len(filtered_data): + raise TaskConfigurationException(message="No eeg sample found with provided data and query") + row = filtered_data.sample(1) eeg_responses.append(row['eeg']) - print(inquiry_letter_subset) return self.model_input_reshaper(eeg_responses) def set_reshaper(self, reshaper: Callable): @@ -69,5 +65,4 @@ def __default_reshaper(self, eeg_response) -> np.ndarray: return np.array(channels_eeg[0]) - -# TODO ReplaySampler \ No newline at end of file +# TODO ReplaySampler diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 7dfae2051..738643d3c 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -1,28 +1,20 @@ -import json import logging as logger from dataclasses import dataclass -from typing import Tuple from pathlib import Path +from typing import List -import matplotlib.pyplot as plt import numpy as np -import pandas as pd -import seaborn as sns + +import bcipy.acquisition.devices as devices from bcipy.config import ( RAW_DATA_FILENAME, TRIGGER_FILENAME, - DEFAULT_PARAMETER_FILENAME, SESSION_DATA_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME, ) from bcipy.helpers.acquisition import analysis_channels -import bcipy.acquisition.devices as devices -from bcipy.helpers.list import grouper -from bcipy.helpers.load import load_json_parameters, load_raw_data, load_experimental_data -from bcipy.helpers.session import read_session, evidence_records -from bcipy.helpers.stimuli import update_inquiry_timing +from bcipy.helpers.load import load_raw_data, load_experimental_data +from bcipy.helpers.stimuli import update_inquiry_timing, InquiryReshaper from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.helpers.symbols import alphabet -from bcipy.signal.model import PcaRdaKdeModel from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams logger.getLogger().setLevel(logger.INFO) @@ -33,13 +25,13 @@ class ExtractedExperimentData: # TODO clean up design inquiries: np.ndarray trials: np.ndarray - labels: list - inquiry_timing: list + labels: List + inquiry_timing: List decoded_triggers: tuple -def process_raw_data_for_model(data_folder, parameters, model_class=PcaRdaKdeModel) -> ExtractedExperimentData: +def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshaper = InquiryReshaper()) -> ExtractedExperimentData: assert parameters, "Parameters are required for offline analysis." if not data_folder: data_folder = load_experimental_data() @@ -90,9 +82,6 @@ def process_raw_data_for_model(data_folder, parameters, model_class=PcaRdaKdeMod log.info(f"Channels read from csv: {channels}") log.info(f"Device type: {type_amp}, fs={sample_rate}") - k_folds = parameters.get("k_folds") - model = model_class(k_folds=k_folds) - # Process triggers.txt files trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( offset=static_offset, @@ -111,7 +100,7 @@ def process_raw_data_for_model(data_folder, parameters, model_class=PcaRdaKdeMod data, fs = raw_data.by_channel() - inquiries, inquiry_labels, inquiry_timing = model.reshaper( + inquiries, inquiry_labels, inquiry_timing = reshaper( trial_targetness_label=trigger_targetness, timing_info=corrected_trigger_timing, eeg_data=data, @@ -126,7 +115,7 @@ def process_raw_data_for_model(data_folder, parameters, model_class=PcaRdaKdeMod inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) trial_duration_samples = int(window_length * fs) - trials = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) + trials = reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) # define the training classes using integers, where 0=nontargets/1=targets # labels = inquiry_labels.flatten() diff --git a/bcipy/simulator/sim_sampler.py b/bcipy/simulator/sim_sampler.py index 9b26c3cf0..a406ccc73 100644 --- a/bcipy/simulator/sim_sampler.py +++ b/bcipy/simulator/sim_sampler.py @@ -51,8 +51,6 @@ def __init__(self, parameter_path: str, save_dir: str, data_engine: DataEngine, self.verbose = verbose self.visualize = visualize - # self.signal_models_classes = [PcaRdaKdeModel for m in self.signal_models] # Hardcoded rn - def run(self): while not self.state_manager.is_done(): self.state_manager.add_state('display_alphabet', self.__get_inquiry_alp_subset(self.state_manager.get_state())) @@ -61,7 +59,7 @@ def run(self): self.state_manager.update(evidence) - # TODO visualize results + # TODO visualize result metrics def __get_inquiry_alp_subset(self, state: SimSessionState): # TODO put this in own file or object diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index de68850b5..de15de330 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -1,28 +1,24 @@ -import argparse import random from pathlib import Path + import numpy as np -from bcipy.config import DEFAULT_PARAMETER_FILENAME -from bcipy.helpers import load from bcipy.helpers.load import load_json_parameters from bcipy.helpers.symbols import alphabet from bcipy.signal.model import PcaRdaKdeModel +from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.sampler import Sampler, SimpleLetterSampler from bcipy.simulator.interfaces import SimSessionState -from bcipy.simulator.sim_sampler import RawDataEngine if __name__ == "__main__": args = dict() args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_18hr58min16sec_-0700"] - args['parameter_path'] = [load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for data_folder in - args['data_folders']] args['out_dir'] = Path(__file__).resolve().parent model_file = Path( "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Calibration_Thu_24_Aug_2023_18hr41min37sec_-0700/model_0.9524_200_800.pkl") sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) - data_engine = RawDataEngine(args['data_folders'], args['parameter_path']) + data_engine = RawDataEngine(args['data_folders']) target_phrase = "HELLO_WORLD" target_symbol = "H" From dfef5403b12cffa73e98c2853d18f3cd6a79514d Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 9 Oct 2023 13:55:44 -0700 Subject: [PATCH 107/330] Address PR feedback --- .../display/demo/vep/demo_calibration_vep.py | 29 +++++++++---------- bcipy/display/paradigm/vep/display.py | 1 - bcipy/display/paradigm/vep/layout.py | 7 ++--- 3 files changed, 17 insertions(+), 20 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 0bffab679..974674fc4 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -3,7 +3,8 @@ from psychopy import core, visual -from bcipy.display import InformationProperties, VEPStimuliProperties +from bcipy.display import (InformationProperties, VEPStimuliProperties, + init_display_window) from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.vep.display import VEPDisplay @@ -16,28 +17,26 @@ handler.setLevel(logging.DEBUG) root.addHandler(handler) +font = 'Courier New' info = InformationProperties( info_color=['White'], info_pos=[(-.5, -.75)], info_height=[0.1], - info_font=['Arial'], + info_font=[font], info_text=['VEP Display Demo'], ) task_text = ['1/4', '2/4', '3/4', '4/4'] num_boxes = 6 -win = visual.Window(size=[700, 700], - fullscr=False, - screen=1, - allowGUI=False, - allowStencil=False, - monitor='testMonitor', - color='black', - colorSpace='rgb', - blendMode='avg', - waitBlanking=False, - winType='pyglet') +window_parameters = { + 'full_screen': False, + 'window_height': 700, + 'window_width': 700, + 'stim_screen': 1, + 'background_color': 'black' +} +win = init_display_window(window_parameters) win.recordFrameIntervals = True frameRate = win.getActualFrameRate() @@ -55,14 +54,14 @@ stim_color=stim_color, stim_pos=box_config.positions, stim_height=0.1, - stim_font='Arial', + stim_font=font, timing=(1, 0.5, 2, 4), # prompt, fixation, animation, stimuli stim_length=1, # how many times to stimuli ) task_bar = CalibrationTaskBar(win, inquiry_count=4, current_index=0, - font='Arial') + font=font) vep = VEPDisplay(win, experiment_clock, stimuli, task_bar, info, box_config=box_config) timing = [] wait_seconds = 2 diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 95a8f7f61..e0d889699 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -290,7 +290,6 @@ def stimulate(self) -> List[float]: # self.draw_static() self.window.flip() ended_at = self.static_clock.getTime() - # TODO: should we have a trigger for VEP_STIM_END? self.logger.debug( f"Expected stim time: {self.timing_stimuli}; actual run time: {ended_at}" ) diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index eeaf6ef28..c89af8308 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -105,16 +105,15 @@ def __init__(self, num_boxes: int, spacing_pct: Optional[float] = None, height_pct: float = 0.25): - assert num_boxes == 4 or num_boxes == 6, 'Number of boxes must be 4 or 6' - assert height_pct <= 0.5, "Rows can't take more than 50% of the height" - self.num_boxes = num_boxes self.layout = layout + self.num_boxes = num_boxes + self.height_pct = height_pct + self.validate() default_spacing = {4: 0.1, 6: 0.05} if not spacing_pct: spacing_pct = default_spacing[num_boxes] self.spacing_pct = spacing_pct - self.height_pct = height_pct self._row_count = 2 def validate(self): From 251cf43b1cc587fdbd66d166855155604144ffaa Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 9 Oct 2023 17:27:29 -0400 Subject: [PATCH 108/330] run loop logic and decision making. draft --- bcipy/simulator/helpers/data_engine.py | 9 +- bcipy/simulator/helpers/decision.py | 237 +++++++++++++++++++++++++ bcipy/simulator/helpers/sampler.py | 6 +- bcipy/simulator/helpers/sim_state.py | 115 +++++++++++- bcipy/simulator/helpers/types.py | 11 ++ bcipy/simulator/interfaces.py | 9 +- bcipy/simulator/sim_sampler.py | 33 ++-- bcipy/simulator/tests/sampler_test.py | 56 ++++-- 8 files changed, 439 insertions(+), 37 deletions(-) create mode 100644 bcipy/simulator/helpers/decision.py create mode 100644 bcipy/simulator/helpers/types.py diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index dd668c18f..e2b3a1af4 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -23,6 +23,9 @@ def transform(self): def get_data(self): ... + def get_parameters(self) -> List[Parameters]: + ... + class RawDataEngine(DataEngine): """ @@ -49,7 +52,8 @@ def load(self) -> DataEngine: Returns: self for chaining """ - self.parameter_files = [load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for data_folder in self.source_dirs] + self.parameter_files = [load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for data_folder in + self.source_dirs] assert len(self.source_dirs) == len(self.parameter_files) # TODO more general parameter validation function @@ -107,4 +111,7 @@ def transform(self) -> DataEngine: def get_data(self): return self.schema.copy() if self.schema is not None else self.data + def get_parameters(self): + return self.parameter_files + # TODO ReplaySessionDataEngine diff --git a/bcipy/simulator/helpers/decision.py b/bcipy/simulator/helpers/decision.py new file mode 100644 index 000000000..dd8998e26 --- /dev/null +++ b/bcipy/simulator/helpers/decision.py @@ -0,0 +1,237 @@ +from abc import ABC + +import numpy as np +import logging +from typing import Dict, List +from copy import copy + +from bcipy.simulator.helpers.types import InquiryResult + +log = logging.getLogger(__name__) + + +# TODO copied over criteria.py. Still debating whether to tie our simulator to that class or not. For now, just hotfixing logic to fit with my implementation + +class SimDecisionCriteria(ABC): + """Abstract class for Criteria which can be applied to evaluate a inquiry + """ + + def reset(self): + pass + + def decide(self, series: List[InquiryResult]): + # TODO update documentation + """ + Apply the given criteria. + Parameters: + ----------- + series - series data + - target(str): target of the series + - time_spent(ndarray[float]): |num_trials|x1 + time spent on the inquiry + - list_sti(list[list[str]]): presented symbols in each + inquiry + - list_distribution(list[ndarray[float]]): list of |alp|x1 + arrays with prob. dist. over alp + + """ + raise NotImplementedError() + + +class MinIterations(SimDecisionCriteria): + """ Returns true if the minimum number of iterations have not yet + been reached. """ + + def __init__(self, min_num_inq: int): + """ Args: + min_num_inq(int): minimum number of inquiry number before any + termination objective is allowed to be triggered """ + self.min_num_inq = min_num_inq + + def decide(self, series: List[InquiryResult]): + # Note: we use 'list_sti' parameter since this is the number of + # inquiries displayed. The length of 'list_distribution' is 1 greater + # than this, since the language model distribution is added before + # the first inquiry is displayed. + current_inq = len(series) if series else 0 + log.info( + f"Checking min iterations; current iteration is {current_inq}") + return current_inq < self.min_num_inq + + +# +# class DecreasedProbabilityCriteria(DecisionCriteria): +# """Returns true if the letter with the max probability decreased from the +# last inquiry.""" +# +# def decide(self, series: Dict): +# if len(series['list_distribution']) < 2: +# return False +# prev_dist = series['list_distribution'][-2] +# cur_dist = series['list_distribution'][-1] +# return np.argmax(cur_dist) == np.argmax( +# prev_dist) and np.max(cur_dist) < np.max(prev_dist) +# +# +class MaxIterationsSim(SimDecisionCriteria): + """Returns true if the max iterations have been reached.""" + + def __init__(self, max_num_inq: int): + """ Args: + max_num_inq(int): maximum number of inquiries allowed before + mandatory termination """ + self.max_num_inq = max_num_inq + + def decide(self, series: List[InquiryResult]): + # Note: len(series['list_sti']) != len(series['list_distribution']) + # see MinIterationsCriteria comment + current_inq = len(series) if series else 0 + if current_inq >= self.max_num_inq: + log.info( + "Committing to decision: max iterations have been reached.") + return True + return False + + +class ProbThresholdSim(SimDecisionCriteria): + """Returns true if the commit threshold has been met.""" + + def __init__(self, threshold: float): + """ Args: + threshold(float in [0,1]): A threshold on most likely + candidate posterior. If a candidate exceeds a posterior + the system terminates. + """ + assert 1 >= threshold >= 0, "stopping threshold should be in [0,1]" + self.tau = threshold + + def decide(self, series: List[InquiryResult]): + current_distribution = series[-1].evidence_likelihoods + if np.max(current_distribution) > self.tau: + log.info("Committing to decision: posterior exceeded threshold.") + return True + return False + +# +# class MarginCriteria(DecisionCriteria): +# """ Stopping criteria based on the difference of two most likely candidates. +# This condition enforces the likelihood difference between two top +# candidates to be at least a value. E.g. in 4 category case with +# a margin 0.2, the edge cases [0.6,0.4,0.,0.] and [0.4,0.2,0.2,0.2] +# satisfy the condition. +# """ +# +# def __init__(self, margin: float): +# """ Args: +# margin(float in [0,1]): Minimum distance required between +# two most likely competing candidates to trigger termination. +# """ +# assert 1 >= margin >= 0, "difference margin should be in [0,1]" +# self.margin = margin +# +# def decide(self, series: Dict): +# # Get the current posterior probability values +# p = copy(series['list_distribution'][-1]) +# # This criteria compares most likely candidates (best competitors) +# candidates = [p[idx] for idx in list(np.argsort(p)[-2:])] +# stopping_rule = np.abs(candidates[0] - candidates[1]) +# d = stopping_rule > self.margin +# if d: +# log.info("Committing to decision: margin is high enough.") +# +# return d +# +# +# class MomentumCommitCriteria(DecisionCriteria): +# """ Stopping criteria based on Shannon entropy on the simplex +# Attr: +# lam(float): linear combination parameter between entropy and the +# speed term +# tau(float): decision threshold +# """ +# +# def __init__(self, tau: float, lam: float): +# self.lam = lam +# self.tau = tau +# +# def reset(self): +# pass +# +# def decide(self, series): +# eps = np.power(.1, 6) +# +# prob_history = copy(series['list_distribution']) +# p = prob_history[-1] +# +# tmp_p = np.ones(len(p)) * (1 - self.tau) / (len(p) - 1) +# tmp_p[0] = self.tau +# +# tmp = -np.sum(p * np.log2(p + eps)) +# tau_ = -np.sum(tmp_p * np.log2(tmp_p + eps)) +# +# tmp_ = np.array(prob_history) +# mom_ = tmp_[1:] * (np.log(tmp_[1:] + eps) - np.log(tmp_[:-1] + eps)) +# momentum = np.linalg.norm(mom_) / len(prob_history) +# +# if len(prob_history) > 1: +# stopping_rule = tmp - self.lam * momentum +# else: +# stopping_rule = tmp +# +# d = stopping_rule < tau_ +# +# return d +# +# +# class CriteriaEvaluator(): +# """Evaluates whether an series should commit to a decision based on the +# provided criteria. +# +# Parameters: +# ----------- +# continue_criteria: list of criteria; if any of these evaluate to true the +# decision maker continues. +# commit_criteria: list of criteria; if any of these return true and +# continue_criteria are all false, decision maker commits to a decision. +# """ +# +# def __init__(self, continue_criteria: List[DecisionCriteria], +# commit_criteria: List[DecisionCriteria]): +# self.continue_criteria = continue_criteria or [] +# self.commit_criteria = commit_criteria or [] +# +# @classmethod +# def default(cls, min_num_inq: int, max_num_inq: int, threshold: float): +# return cls(continue_criteria=[MinIterationsCriteria(min_num_inq)], +# commit_criteria=[ +# MaxIterationsCriteria(max_num_inq), +# ProbThresholdCriteria(threshold) +# ]) +# +# def do_series(self): +# for el_ in self.continue_criteria: +# el_.reset() +# for el in self.commit_criteria: +# el.reset() +# +# def should_commit(self, series: Dict): +# """Evaluates the given series; returns true if stoppage criteria has +# been met, otherwise false. +# +# Parameters: +# ----------- +# series - series data +# - target(str): target of the series +# - time_spent(ndarray[float]): |num_trials|x1 +# time spent on the inquiry +# - list_sti(list[list[str]]): presented symbols in each +# inquiry +# - list_distribution(list[ndarray[float]]): list of |alp|x1 +# arrays with prob. dist. over alp +# """ +# if any( +# criteria.decide(series) +# for criteria in self.continue_criteria): +# return False +# return any( +# criteria.decide(series) for criteria in self.commit_criteria) diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 62dfdad4f..657e2ad85 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -8,13 +8,13 @@ from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.interfaces import SimSessionState +from bcipy.simulator.interfaces import SimState class Sampler(ABC): """ Interface to generate sample of data usable by a model """ - def sample(self, state: SimSessionState): + def sample(self, state: SimState): ... def set_reshaper(self, reshaper: Callable): @@ -30,7 +30,7 @@ def __init__(self, data_engine: RawDataEngine, params: List[Parameters] = None): self.alphabet: List[str] = params[0].get('symbol_set') if params else alphabet() self.data: pd.DataFrame = self.data_engine.transform().get_data() - def sample(self, state: SimSessionState) -> np.ndarray: + def sample(self, state: SimState) -> np.ndarray: """ - query eeg response by letter - reshape for signal model input diff --git a/bcipy/simulator/helpers/sim_state.py b/bcipy/simulator/helpers/sim_state.py index 19ddfc1a1..379b1bc49 100644 --- a/bcipy/simulator/helpers/sim_state.py +++ b/bcipy/simulator/helpers/sim_state.py @@ -1,28 +1,129 @@ +import copy from abc import ABC from dataclasses import dataclass +from typing import List, Optional + +import numpy as np + +from bcipy.helpers.exceptions import FieldException +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.symbols import alphabet +from bcipy.simulator.helpers.decision import SimDecisionCriteria, MaxIterationsSim, ProbThresholdSim +from bcipy.simulator.helpers.types import InquiryResult +from bcipy.task.control.criteria import DecisionCriteria, MaxIterationsCriteria, ProbThresholdCriteria @dataclass -class SimSessionState: +class SimState: """ Represents the state of a current session during simulation """ target_symbol: str current_sentence: str target_sentence: str - display_alphabet: list[str] + display_alphabet: List[str] inquiry_n: int series_n: int + series_results: List[List[InquiryResult]] + + decision_criterion: List[SimDecisionCriteria] + + def total_inquiry_count(self): + count = 0 + for series in self.series_results: + count += len(series) + + return count class StateManager(ABC): - def update(self, evidence): - ... + def update(self, evidence: np.ndarray): + raise NotImplementedError() def is_done(self) -> bool: - ... + raise NotImplementedError() - def get_state(self) -> SimSessionState: + def get_state(self) -> SimState: ... - def add_state(self, state_field, state_value): + def mutate_state(self, state_field, state_value): pass + + +class StateManagerImpl(StateManager): + + def __init__(self, parameters: Parameters): + self.state: SimState = self.initial_state() + self.parameters = parameters + + self.stop_inq = 50 # TODO pull from parameters + + def is_done(self) -> bool: + + return self.state.total_inquiry_count() > self.stop_inq or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 + + def update(self, evidence: np.ndarray) -> InquiryResult: + + temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, + evidence_likelihoods=list(evidence), decision=None) + + # finding out whether max iterations is hit or prob threshold is hit + temp_series = copy.deepcopy(self.get_state().series_results) + temp_series[-1].append(temp_inquiry_result) + is_decidable = any([decider.decide(temp_series[-1]) for decider in self.state.decision_criterion]) + decision = None + # TODO what to do when max inquiry count is reached? + + new_state = self.get_state().__dict__ + if is_decidable: + decision = alphabet()[np.argmax(evidence)] # deciding the maximum probability symbol TODO abstract + + if decision == self.state.target_symbol: # correct decision + new_state['series_n'] += 1 # TODO abstract out into reset function + new_state['series_results'].append([]) + new_state['inquiry_n'] = 0 + + new_state['current_sentence'] += decision + + next_target_symbol_idx = len(new_state['current_sentence']) + if next_target_symbol_idx >= len(self.state.target_sentence): + pass + else: + new_state['target_symbol'] = self.state.target_sentence[next_target_symbol_idx] + + else: # wrong decision + new_state['series_n'] += 1 + new_state['series_results'].append([]) + new_state['inquiry_n'] = 0 + + else: + new_state['inquiry_n'] += 1 + + new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, + evidence_likelihoods=list(evidence), decision=decision) + + new_state['series_results'][self.state.series_n].append(new_inquiry_result) + + self.state = SimState(**new_state) + + return new_inquiry_result + + def get_state(self) -> SimState: + return copy.copy(self.state) + + def mutate_state(self, state_field, state_value) -> SimState: + state_dict = self.get_state().__dict__ + if state_field in state_dict: + state_dict[state_field] = state_value + self.state = SimState(**state_dict) + return self.get_state() + else: + raise FieldException(f"Cannot find state field {state_field}") + + @staticmethod + def initial_state(parameters: Parameters = None) -> SimState: + sentence = "HELLO_WORLD" # TODO abstract out with sim_parameters.json + target_symbol = sentence[0] + default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] + + return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, display_alphabet=[], inquiry_n=0, series_n=0, + series_results=[[]], decision_criterion=default_criterion) diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py new file mode 100644 index 000000000..c965867a9 --- /dev/null +++ b/bcipy/simulator/helpers/types.py @@ -0,0 +1,11 @@ +from dataclasses import dataclass +from typing import Optional, List + + +@dataclass +class InquiryResult: + target: Optional[str] + time_spent: int # TODO what does time_spent mean? + stimuli: List + evidence_likelihoods: List + decision: Optional[str] diff --git a/bcipy/simulator/interfaces.py b/bcipy/simulator/interfaces.py index 55a9e6e0c..02659d050 100644 --- a/bcipy/simulator/interfaces.py +++ b/bcipy/simulator/interfaces.py @@ -1,10 +1,13 @@ from abc import ABC -from bcipy.simulator.helpers.sim_state import SimSessionState + +from bcipy.helpers.symbols import alphabet +from bcipy.signal.model import PcaRdaKdeModel +from bcipy.simulator.helpers.sim_state import SimState class ModelHandler(ABC): - def generate_evidence(self, state: SimSessionState, features): + def generate_evidence(self, state: SimState, features): ... def get_model(self, key=None): @@ -13,3 +16,5 @@ def get_model(self, key=None): class MetricReferee: ... + + diff --git a/bcipy/simulator/sim_sampler.py b/bcipy/simulator/sim_sampler.py index a406ccc73..57d4c6b68 100644 --- a/bcipy/simulator/sim_sampler.py +++ b/bcipy/simulator/sim_sampler.py @@ -1,10 +1,12 @@ import random +from time import sleep from bcipy.helpers import load from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine from bcipy.simulator.helpers.sampler import Sampler -from bcipy.simulator.helpers.sim_state import StateManager, SimSessionState +from bcipy.simulator.helpers.sim_state import StateManager, SimState +from bcipy.simulator.helpers.types import InquiryResult from bcipy.simulator.interfaces import MetricReferee, ModelHandler from bcipy.simulator.simulator_base import Simulator @@ -31,11 +33,10 @@ class SimulatorCopyPhrase(Simulator): - run closed loop simulation of {TaskType} with {data} with {simulation_params} """ - def __init__(self, parameter_path: str, save_dir: str, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, verbose=False, visualize=False): + def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, + state_manager: StateManager, referee: MetricReferee, parameter_path: str = None, save_dir: str = None, verbose=False, visualize=False): super(SimulatorCopyPhrase, self).__init__() - self.parameters = self.load_parameters(parameter_path) self.save_dir: str = save_dir self.model_handler: ModelHandler = model_handler self.sampler: Sampler = sampler @@ -44,34 +45,46 @@ def __init__(self, parameter_path: str, save_dir: str, data_engine: DataEngine, self.data_engine: DataEngine = data_engine + self.parameters = self.load_parameters(parameter_path) + self.symbol_set = alphabet() self.write_output = False - self.data_loader = None self.verbose = verbose self.visualize = visualize def run(self): while not self.state_manager.is_done(): - self.state_manager.add_state('display_alphabet', self.__get_inquiry_alp_subset(self.state_manager.get_state())) + print(f"Series {self.state_manager.get_state().series_n} | Inquiry {self.state_manager.get_state().inquiry_n}") + self.state_manager.mutate_state('display_alphabet', self.__get_inquiry_alp_subset(self.state_manager.get_state())) sampled_data = self.sampler.sample(self.state_manager.get_state()) evidence = self.model_handler.generate_evidence(self.state_manager.get_state(), sampled_data) - self.state_manager.update(evidence) + print(f"Evidence for stimuli {self.state_manager.get_state().display_alphabet} \n {evidence}") + + inq_record: InquiryResult = self.state_manager.update(evidence) + if inq_record.decision: + print(f"Decided {inq_record.decision} for target {inq_record.target} for sentence {self.state_manager.get_state().target_sentence}") + + print("\n") + sleep(.1) # TODO visualize result metrics - def __get_inquiry_alp_subset(self, state: SimSessionState): + def __get_inquiry_alp_subset(self, state: SimState): # TODO put this in own file or object subset_length = 10 return random.sample(self.symbol_set, subset_length) def load_parameters(self, path): # TODO validate parameters - parameters = load.load_json_parameters(path, value_cast=True) + if not path: + parameters = self.data_engine.get_parameters()[0] # TODO fix this parameter logic. for now assuming one parameter file speaks for all + else: + parameters = load.load_json_parameters(path, value_cast=True) + sim_parameters = load.load_json_parameters( "bcipy/simulator/sim_parameters.json", value_cast=True) - parameters.add_missing_items(sim_parameters) return parameters diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index de15de330..00a25772c 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -8,7 +8,33 @@ from bcipy.signal.model import PcaRdaKdeModel from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.sampler import Sampler, SimpleLetterSampler -from bcipy.simulator.interfaces import SimSessionState +from bcipy.simulator.helpers.sim_state import StateManagerImpl, StateManager, SimState +from bcipy.simulator.interfaces import ModelHandler, MetricReferee +from bcipy.simulator.sim_sampler import SimulatorCopyPhrase + + +class DummyModelHandler(ModelHandler): + + def __init__(self, model_file): + self.model_file = model_file + + def generate_evidence(self, state: SimState, features): + model = PcaRdaKdeModel() + model = model.load(self.model_file) + + stimuli = state.display_alphabet + alp = alphabet() + eeg_evidence = model.predict(features, stimuli, alp) + + return eeg_evidence + + def get_model(self, key=None): + pass + + +class DummyRef(MetricReferee): + pass + if __name__ == "__main__": args = dict() @@ -19,23 +45,25 @@ sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) data_engine = RawDataEngine(args['data_folders']) - target_phrase = "HELLO_WORLD" - target_symbol = "H" display_alp = random.sample(alphabet(), 10) - state: SimSessionState = SimSessionState(target_symbol=target_symbol, inquiry_n=0, series_n=0, target_sentence=target_phrase, - current_sentence="", display_alphabet=display_alp) - sampler: Sampler = SimpleLetterSampler(data_engine) - sample: np.ndarray = sampler.sample(state) + stateManager: StateManager = StateManagerImpl(sim_parameters) + stateManager.mutate_state("display_alphabet", display_alp) + print(stateManager.get_state()) - model = PcaRdaKdeModel() - model = model.load(model_file) - - breakpoint() - eeg_evidence = model.predict(sample, state.display_alphabet, alphabet()) + sampler: Sampler = SimpleLetterSampler(data_engine) + sample: np.ndarray = sampler.sample(stateManager.get_state()) - print(eeg_evidence.shape) - print(eeg_evidence) + # model = PcaRdaKdeModel() + # model = model.load(model_file) + # + # eeg_evidence = model.predict(sample, stateManager.get_state().display_alphabet, alphabet()) + # + # print(eeg_evidence.shape) + # print(eeg_evidence) + model_handler = DummyModelHandler(model_file) + sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, DummyRef()) + sim.run() breakpoint() From ed8160064db020f3e4be2e3f7be6b78626b8bda9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 9 Oct 2023 14:55:57 -0700 Subject: [PATCH 109/330] Fix lint error --- bcipy/display/demo/vep/demo_calibration_vep.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 974674fc4..ca6f493d8 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -1,7 +1,7 @@ import logging import sys -from psychopy import core, visual +from psychopy import core from bcipy.display import (InformationProperties, VEPStimuliProperties, init_display_window) From 6b40782fb4a71c2381483f3b194142c7a1806b88 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 10 Oct 2023 17:44:15 -0700 Subject: [PATCH 110/330] #185935799 ; matrix row spacing: computed positions now display equally spaced regardless of the Window's aspect ratio --- bcipy/display/components/layout.py | 16 ++++- bcipy/display/demo/components/demo_layouts.py | 33 +++++++++- .../display/demo/matrix/demo_matrix_layout.py | 1 + bcipy/display/paradigm/matrix/display.py | 7 ++- bcipy/display/paradigm/matrix/layout.py | 60 +++++++++++-------- bcipy/display/tests/components/test_layout.py | 8 ++- .../paradigm/matrix/test_matrix_layout.py | 17 ++++++ 7 files changed, 112 insertions(+), 30 deletions(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index a61e20f19..1ad8692a3 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -102,6 +102,15 @@ def scaled_height(width: float, return width / (win_height / win_width) +def scaled_width(height: float, + window_size: Tuple[float, float], + units: str = 'norm'): + """Given a height, find the equivalent width scaled to the aspect ratio of + a window with the given size""" + width, _height = scaled_size(height, window_size, units) + return width + + class Layout(Container): """Class with methods for positioning elements within a parent container. """ @@ -302,19 +311,22 @@ def at_bottom(parent: Container, height: float) -> Layout: bottom=bottom) -def centered(width_pct: float = 1.0, height_pct: float = 1.0) -> Layout: +def centered(parent: Optional[Container] = None, + width_pct: float = 1.0, + height_pct: float = 1.0) -> Layout: """Constructs a layout that is centered on the screen. Default size is fullscreen but optional parameters can be used to adjust the width and height. Parameters ---------- + parent - optional parent width_pct - optional; sets the width to a given percentage of fullscreen. height_pct - optional; sets the height to a given percentage of fullscreen. """ - container = Layout() + container = Layout(parent=parent) container.resize_width(width_pct, alignment=Alignment.CENTERED) container.resize_height(height_pct, alignment=Alignment.CENTERED) return container diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index e4809cd36..6fe4afc9c 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -1,4 +1,6 @@ """Useful for viewing computed positions in a window""" +import logging +import sys import time from typing import Callable, List, Tuple, Union @@ -11,7 +13,9 @@ from bcipy.display.components.layout import (Layout, at_top, centered, envelope, height_units, scaled_size) +from bcipy.display.paradigm.matrix.layout import symbol_positions from bcipy.display.paradigm.vep.layout import BoxConfiguration, checkerboard +from bcipy.helpers.symbols import alphabet def make_window(): @@ -253,6 +257,26 @@ def demo_checkerboard2(win: visual.Window): win.flip() +def demo_matrix_positions(win: visual.Window): + """Demo matrix positions. Useful for visualizing how adjustments to layout + dimensions as well as the number of rows and columns affects positioning. + """ + # norm_layout = centered(parent=win, width_pct=1., height_pct=0.5) + norm_layout = centered(parent=win, width_pct=0.75, height_pct=1) + positions = symbol_positions(norm_layout, rows=5, columns=6) + + for sym, pos in zip(alphabet(), positions): + stim = visual.TextStim(win, + text=sym, + pos=pos, + color='white', + height=0.17) + stim.draw() + draw_boundary(win, norm_layout, line_px=5, color='gray') + draw_positions(win, positions, size=scaled_size(0.025, win.size)) + win.flip() + + def run(demo: Callable[[visual.Window], None], seconds=30): """Run the given function for the provided duration. @@ -261,6 +285,12 @@ def run(demo: Callable[[visual.Window], None], seconds=30): demo - function to run; a Window object is passed to this function. seconds - Window is closed after this duration. """ + root = logging.getLogger() + root.setLevel(logging.DEBUG) + handler = logging.StreamHandler(sys.stdout) + handler.setLevel(logging.DEBUG) + root.addHandler(handler) + try: win = make_window() print( @@ -281,8 +311,9 @@ def run(demo: Callable[[visual.Window], None], seconds=30): print('Demo complete.') -run(demo_vep) +# run(demo_vep) # run(demo_height_units) # run(show_layout_coords) # run(demo_checkerboard) # run(demo_checkerboard2) +run(demo_matrix_positions) diff --git a/bcipy/display/demo/matrix/demo_matrix_layout.py b/bcipy/display/demo/matrix/demo_matrix_layout.py index 7379af0f2..061b24803 100644 --- a/bcipy/display/demo/matrix/demo_matrix_layout.py +++ b/bcipy/display/demo/matrix/demo_matrix_layout.py @@ -47,6 +47,7 @@ info=info, rows=3, columns=10, + width_pct=0.9, sort_order=qwerty_order(is_txt_stim=True)) matrix_display.draw(grid_opacity=matrix_display.full_grid_opacity, diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 74dfc8880..64d2fc5ab 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -42,7 +42,8 @@ def __init__(self, info: InformationProperties, rows: int = 5, columns: int = 6, - width_pct: float = 0.7, + width_pct: float = 0.75, + height_pct: float = 0.8, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, should_prompt_target: bool = True, @@ -88,7 +89,9 @@ def __init__(self, # Set position and parameters for grid of alphabet self.grid_stimuli_height = 0.17 # stimuli.stim_height - display_container = layout.centered(width_pct=width_pct) + display_container = layout.centered(parent=window, + width_pct=width_pct, + height_pct=height_pct) self.positions = symbol_positions(display_container, rows, columns) self.logger.info( f"Symbol positions ({display_container.units} units): {self.positions}" diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index a5063572b..82ad1b26f 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -1,63 +1,75 @@ """Functions for calculating matrix layouts""" +import logging from typing import List, Tuple from bcipy.display.components.layout import (Layout, above, below, left_of, - right_of) + right_of, scaled_height, + scaled_width) +logger = logging.getLogger(__name__) -def symbol_positions(container: Layout, - rows: int, - columns: int, - spacing: float = None) -> List[Tuple[float, float]]: + +def symbol_positions(container: Layout, rows: int, + columns: int, max_spacing: float = None) -> List[Tuple[float, float]]: """Compute the positions for arranging a number of symbols in a grid layout. Parameters ---------- - container - container in which the grid should be placed + container - container in which the grid should be placed; must have a + visual.Window parent, which is used to determine the aspect ratio. rows - number of rows in the grid columns - number of columns in the grid - spacing - optional value to specify the space between positions - (in the same units of the container) - + max_spacing - optional max spacing (in layout units) in the height + direction; width will be normalized to this value if provided Returns ------- list of (x,y) tuples with (rows * columns) positions in row,col order """ + assert container.parent, "Container must have a parent" assert rows >= 1 and columns >= 1, "There must be at least one row and one column" - if not spacing: - # compute the spacing (in container units) from the container width and height - horizontal_spacing = container.width / (rows + 1) - vertical_spacing = container.height / (columns + 1) - spacing = min(horizontal_spacing, vertical_spacing) - half_space = spacing / 2 + # compute the spacing (in container units) from the container width and height + horizontal_spacing = container.width / (columns + 1) + vertical_spacing = container.height / (rows + 1) + + if max_spacing and vertical_spacing > max_spacing: + vertical_spacing = max_spacing + + # Use the minimum spacing + if horizontal_spacing < vertical_spacing: + vertical_spacing = scaled_height(horizontal_spacing, + container.parent.size) + else: + horizontal_spacing = scaled_width(vertical_spacing, + container.parent.size) # Work back from center to compute the starting position center_x, center_y = container.center spaces_left_of_center = int(columns / 2) - start_pos_left = left_of(center_x, spaces_left_of_center * spacing) + start_pos_left = left_of(center_x, + spaces_left_of_center * horizontal_spacing) if columns % 2 == 0 and columns > 1: # even number of columns; adjust start_pos so that center_x is between # the middle two items. - start_pos_left = right_of(start_pos_left, half_space) + start_pos_left = right_of(start_pos_left, horizontal_spacing / 2) spaces_above_center = int(rows / 2) - start_pos_top = above(center_y, spaces_above_center * spacing) + start_pos_top = above(center_y, spaces_above_center * vertical_spacing) if rows % 2 == 0 and rows > 1: - start_pos_top = below(start_pos_top, half_space) + start_pos_top = below(start_pos_top, vertical_spacing / 2) # adjust the beginning x,y values so adding a space results in the first # position. - x_coord = left_of(start_pos_left, spacing) - y_coord = above(start_pos_top, spacing) + x_coord = left_of(start_pos_left, horizontal_spacing) + y_coord = above(start_pos_top, vertical_spacing) positions = [] for _row in range(rows): - y_coord = below(y_coord, spacing) - x_coord = left_of(start_pos_left, spacing) + y_coord = below(y_coord, vertical_spacing) + x_coord = left_of(start_pos_left, horizontal_spacing) for _col in range(columns): - x_coord = right_of(x_coord, spacing) + x_coord = right_of(x_coord, horizontal_spacing) positions.append((x_coord, y_coord)) return positions diff --git a/bcipy/display/tests/components/test_layout.py b/bcipy/display/tests/components/test_layout.py index cbe25803e..846c589c1 100644 --- a/bcipy/display/tests/components/test_layout.py +++ b/bcipy/display/tests/components/test_layout.py @@ -6,7 +6,7 @@ from bcipy.display.components.layout import (Alignment, Layout, at_bottom, at_top, centered, envelope, from_envelope, scaled_height, - scaled_size) + scaled_size, scaled_width) class TestLayout(unittest.TestCase): @@ -196,6 +196,12 @@ def test_scaled_height(self): """Test calculation of scaled height based on width""" self.assertEqual(scaled_height(0.125, window_size=(800, 500)), 0.2) + def test_scaled_width(self): + """Test calculation of a scaled width based on height""" + self.assertEqual(scaled_width(height=0.2, window_size=(500, 500)), 0.2) + self.assertEqual(scaled_width(height=0.2, window_size=(800, 500)), + 0.125) + if __name__ == '__main__': unittest.main() diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py index fbb76f42a..a6c7c8b4f 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py @@ -103,6 +103,23 @@ def test_spacing(self): self.assertEqual(row_spacing, column_spacing, "Rows and columns should have the same spacing") + def test_max_spacing(self): + """Test max_spacing parameter""" + max_spacing = 0.1 + positions = symbol_positions(self.layout, + rows=2, + columns=2, + max_spacing=max_spacing) + + top_left = positions[0] + top_right = positions[1] + bottom_left = positions[2] + + row_spacing = abs(top_left[1] - bottom_left[1]) + column_spacing = abs(top_right[0] - top_left[0]) + self.assertEqual(row_spacing, max_spacing) + self.assertEqual(column_spacing, max_spacing) + if __name__ == '__main__': unittest.main() From 86a8091bafc6768581a69479117b11d24ab1a816 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 10 Oct 2023 18:07:53 -0700 Subject: [PATCH 111/330] Added logging for matrix symbol positions --- bcipy/display/paradigm/matrix/display.py | 19 +++++++++++++++---- 1 file changed, 15 insertions(+), 4 deletions(-) diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 64d2fc5ab..a9ad5f30c 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -1,6 +1,6 @@ """Display for presenting stimuli in a grid.""" import logging -from typing import Callable, Dict, List, NamedTuple, Optional +from typing import Callable, Dict, List, NamedTuple, Optional, Tuple from psychopy import core, visual @@ -93,9 +93,6 @@ def __init__(self, width_pct=width_pct, height_pct=height_pct) self.positions = symbol_positions(display_container, rows, columns) - self.logger.info( - f"Symbol positions ({display_container.units} units): {self.positions}" - ) self.grid_color = 'white' self.start_opacity = 0.15 @@ -116,6 +113,20 @@ def __init__(self, self.stim_registry = self.build_grid() self.should_prompt_target = should_prompt_target + self.logger.info( + f"Symbol positions ({display_container.units} units):\n{self._stim_positions}" + ) + self.logger.info(f"Matrix center position: {display_container.center}") + + @property + def _stim_positions(self) -> Dict[str, Tuple[float, float]]: + """Returns a dict with the position for each stim""" + assert self.stim_registry, "stim_registry not yet initialized" + return { + sym: tuple(stim.pos) + for sym, stim in self.stim_registry.items() + } + def schedule_to(self, stimuli: list, timing: list, colors: list) -> None: """Schedule stimuli elements (works as a buffer). From 78be80ec3321904bd699d62c9091751c1bc417f6 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 11 Oct 2023 11:25:22 -0700 Subject: [PATCH 112/330] Fixed broken test --- bcipy/display/tests/paradigm/matrix/test_matrix_display.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py index 5f6afebad..a8285517a 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py @@ -39,10 +39,11 @@ def setUp(self): self.window = mock({"units": "norm", "size": (2.0, 2.0)}) self.experiment_clock = mock() self.static_clock = mock() - self.text_stim_mock = mock(psychopy.visual.TextStim) + self.text_stim_mock = mock({'pos': (0, 0)}, spec=psychopy.visual.TextStim) when(self.text_stim_mock).setOpacity(...).thenReturn() when(self.text_stim_mock).setColor(...).thenReturn() when(self.text_stim_mock).draw(...).thenReturn() + # grid item when(psychopy.visual).TextStim( win=self.window, From 2b515441ffb399442fc2c722d8ea5279c69363d2 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Wed, 11 Oct 2023 18:17:48 -0400 Subject: [PATCH 113/330] load_data script is updated to include multimodal data loading --- bcipy/helpers/convert.py | 4 +- bcipy/helpers/demo/demo_load_raw_data.py | 57 +++++++-- bcipy/helpers/demo/demo_visualization.py | 156 ++++++++++++++--------- bcipy/helpers/stimuli.py | 2 +- bcipy/helpers/visualization.py | 143 +++++++++++---------- bcipy/signal/model/offline_analysis.py | 5 + bcipy/signal/process/extract_gaze.py | 85 ++++++------ scripts/python/replay_session.py | 4 +- 8 files changed, 266 insertions(+), 190 deletions(-) diff --git a/bcipy/helpers/convert.py b/bcipy/helpers/convert.py index ab07a7fb5..93d3bade4 100644 --- a/bcipy/helpers/convert.py +++ b/bcipy/helpers/convert.py @@ -170,7 +170,9 @@ def pyedf_convert(data_dir: str, params = load_json_parameters(Path(data_dir, DEFAULT_PARAMETER_FILENAME), value_cast=True) - data = load_raw_data(Path(data_dir, f'{RAW_DATA_FILENAME}.csv')) + data_list = load_raw_data(data_dir, [f'{RAW_DATA_FILENAME}.csv']) + # NOTE: With the current inputs this function only loads the EEG data. Update needed for eyetracker data. + data = data_list[0] fs = data.sample_rate if pre_filter: default_transform = get_default_transform( diff --git a/bcipy/helpers/demo/demo_load_raw_data.py b/bcipy/helpers/demo/demo_load_raw_data.py index 1b8bcd6ea..d039cc3ba 100644 --- a/bcipy/helpers/demo/demo_load_raw_data.py +++ b/bcipy/helpers/demo/demo_load_raw_data.py @@ -1,22 +1,26 @@ from bcipy.helpers.load import ( - load_raw_data, + load_raw_data, load_json_parameters ) from pathlib import Path +from bcipy.config import (DEFAULT_PARAMETERS_PATH, EYE_TRACKER_FILENAME_PREFIX) -def main(data_folder, file_name): +def main(data_folder, data_file_paths): """Load BciPy raw data, print info to console, and return data to caller.""" - raw_data = load_raw_data(Path(data_folder, file_name)) - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - # access data using raw_data.channel_data or raw_data.numerical_data - print(f'Successfully loaded raw data from {file_name}') - print(f'Channels: {channels}') - print(f'Type: {type_amp}') - print(f'Sample rate: {sample_rate}') - print(f'Data shape: {raw_data.channel_data.shape}') - return raw_data + # Load all data saved in the directory + + raw_data_list = load_raw_data(data_folder, data_file_paths) + for mode_data in raw_data_list: + channels = mode_data.channels + type_amp = mode_data.daq_type + sample_rate = mode_data.sample_rate + # access data using raw_data.channel_data or raw_data.numerical_data + print(f'Successfully loaded raw data from {type_amp}') + print(f'Channels: {channels}') + print(f'Type: {type_amp}') + print(f'Sample rate: {sample_rate}') + print(f'Data shape: {mode_data.channel_data.shape}') + return raw_data_list if __name__ == "__main__": @@ -25,6 +29,31 @@ def main(data_folder, file_name): parser = argparse.ArgumentParser() parser.add_argument('-d', '--data_folder', required=True, help='Path to data folder') + parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) args = parser.parse_args() - raw_data = main(args.data_folder, file_name=f'{RAW_DATA_FILENAME}.csv') + parameters = load_json_parameters(args.parameters_file, value_cast=True) + acq_mode = parameters.get("acq_mode") + + data_file_paths = [] + if '+' in acq_mode: + if 'eyetracker' in acq_mode.lower(): + # find the eyetracker data file with the prefix of EYE_TRACKER_FILENAME_PREFIX + eye_tracker_file = [f.name for f in Path(args.data_folder).iterdir() + if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] + assert len( + eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {args.data_folder}." + data_file_paths.extend(eye_tracker_file) + else: + raise ValueError(f"Unsupported acquisition mode: {acq_mode}. Eyetracker must be included.") + if 'eeg' in acq_mode.lower(): + # find the eeg data file with the prefix of EEG_FILENAME_PREFIX + eeg_file = [f.name for f in Path(args.data_folder).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] + assert len(eeg_file) == 1, f"Found {len(eeg_file)} EEG files in {args.data_folder}. Expected 1." + data_file_paths.extend(eeg_file) + else: + raise ValueError(f"Unsupported acquisition mode: {acq_mode}. EEG must be included.") + else: + data_file_paths = [f"{RAW_DATA_FILENAME}.csv"] + + raw_data_list = main(args.data_folder, data_file_paths) diff --git a/bcipy/helpers/demo/demo_visualization.py b/bcipy/helpers/demo/demo_visualization.py index a6194d0d3..078266eb0 100644 --- a/bcipy/helpers/demo/demo_visualization.py +++ b/bcipy/helpers/demo/demo_visualization.py @@ -13,8 +13,9 @@ - - `python bcipy/helpers/demo/demo_visualization.py --save"` this will save the visualizations generated to the provided or selected path """ -from bcipy.config import (TRIGGER_FILENAME, DEFAULT_PARAMETER_FILENAME, - RAW_DATA_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME) +from bcipy.config import (TRIGGER_FILENAME, RAW_DATA_FILENAME, EYE_TRACKER_FILENAME_PREFIX, + DEFAULT_DEVICE_SPEC_FILENAME, DEFAULT_PARAMETERS_PATH, + DEFAULT_PARAMETER_FILENAME) from bcipy.helpers.acquisition import analysis_channels from bcipy.signal.process import get_default_transform from bcipy.helpers.load import ( @@ -33,73 +34,106 @@ parser = argparse.ArgumentParser() parser.add_argument( - '-p', - '--path', + '-d', + '--data_folder', help='Path to the directory with raw_data to be converted', required=False) + parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) parser.add_argument("--show", dest="show", action="store_true") parser.add_argument("--save", dest="save", action="store_true") parser.set_defaults(show=False) parser.set_defaults(save=False) args = parser.parse_args() - path = args.path + path = args.data_folder if not path: path = load_experimental_data() + parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) + else: + parameters = load_json_parameters(args.parameters_file, value_cast=True) - parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) - - # extract all relevant parameters - trial_window = parameters.get("trial_window") - prestim_length = parameters.get("prestim_length") - trials_per_inquiry = parameters.get("stim_length") - # The task buffer length defines the min time between two inquiries - # We use half of that time here to buffer during transforms - buffer = int(parameters.get("task_buffer_length") / 2) - # get signal filtering information - downsample_rate = parameters.get("down_sampling_rate") - notch_filter = parameters.get("notch_filter_frequency") - filter_high = parameters.get("filter_high") - filter_low = parameters.get("filter_low") - filter_order = parameters.get("filter_order") - static_offset = parameters.get("static_trigger_offset") - raw_data = load_raw_data(Path(path, f'{RAW_DATA_FILENAME}.csv')) - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=notch_filter, - bandpass_low=filter_low, - bandpass_high=filter_high, - bandpass_order=filter_order, - downsample_factor=downsample_rate, - ) - # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - offset=static_offset, - trigger_path=f"{path}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - ) - labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] - - devices.load(Path(path, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) - channel_map = analysis_channels(channels, device_spec) - - save_path = None if not args.save else path - - figure_handles = visualize_erp( - raw_data, - channel_map, - trigger_timing, - labels, - trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=save_path, - show=args.show - ) + acq_mode = parameters.get("acq_mode") + + # Make sure you are loading the correct raw data: + data_file_paths = [] + if '+' in acq_mode: + if 'eyetracker' in acq_mode.lower(): + # find the eyetracker data file with the prefix of EYE_TRACKER_FILENAME_PREFIX + eye_tracker_file = [f.name for f in Path(path).iterdir() + if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] + assert len( + eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {path}. Expected 1." + data_file_paths.extend(eye_tracker_file) + else: + raise ValueError(f"Unsupported acquisition mode: {acq_mode}. Eyetracker must be included.") + if 'eeg' in acq_mode.lower(): + # find the eeg data file with the prefix of EEG_FILENAME_PREFIX + eeg_file = [f.name for f in Path(path).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] + assert len(eeg_file) == 1, f"Found {len(eeg_file)} EEG files in {path}. Expected 1." + data_file_paths.extend(eeg_file) + else: + raise ValueError(f"Unsupported acquisition mode: {acq_mode}. EEG must be included.") + else: + data_file_paths = [f"{RAW_DATA_FILENAME}.csv"] + + raw_data_list = load_raw_data(path, data_file_paths) + + for mode_data in raw_data_list: + devices.load(Path(path, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(mode_data.daq_type) + # extract all relevant parameters from raw data object eeg + if device_spec.content_type == "Eyetracker": + continue + elif device_spec.content_type == "EEG": + trial_window = parameters.get("trial_window") + if trial_window is None: + trial_window = [0.0, 0.5] + prestim_length = parameters.get("prestim_length") + trials_per_inquiry = parameters.get("stim_length") + # The task buffer length defines the min time between two inquiries + # We use half of that time here to buffer during transforms + buffer = int(parameters.get("task_buffer_length") / 2) + # get signal filtering information + downsample_rate = parameters.get("down_sampling_rate") + notch_filter = parameters.get("notch_filter_frequency") + filter_high = parameters.get("filter_high") + filter_low = parameters.get("filter_low") + filter_order = parameters.get("filter_order") + static_offset = parameters.get("static_trigger_offset") + channels = mode_data.channels + type_amp = mode_data.daq_type + sample_rate = mode_data.sample_rate + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=notch_filter, + bandpass_low=filter_low, + bandpass_high=filter_high, + bandpass_order=filter_order, + downsample_factor=downsample_rate, + ) + # Process triggers.txt files + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + offset=static_offset, + trigger_path=f"{path}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] + + channel_map = analysis_channels(channels, device_spec) + + save_path = None if not args.save else path + + figure_handles = visualize_erp( + mode_data, + channel_map, + trigger_timing, + labels, + trial_window, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + save_path=save_path, + show=args.show + ) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 3cf190f73..118d2806c 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -240,7 +240,7 @@ def __call__(self, ) -> dict: """Extract inquiry data and labels. Different from the EEG inquiry, the gaze inquiry window starts with the first flicker and ends with the last flicker in the inquiry. Each inquiry has a length of ~3 seconds. - The labels are provided in the target_symbols list. It returns a Dict, where keys are the target symbols and + The labels are provided in the target_symbols list. It returns a Dict, where keys are the target symbols and the values are inquiries (appended in order of appearance) where the corresponding target symbol is prompted. Optional outputs: reshape_data is the list of data reshaped into (Inquiries, Channels, Samples), where inquirires are appended diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index c7295d770..2679b8afc 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -28,6 +28,7 @@ log = logging.getLogger(__name__) + def clip_to_display(data, screen_limits): """Clip to Display. This function is used to clip the eye data to the display size. Removes > 1 values and < 0 values. Removes nan values. @@ -37,11 +38,11 @@ def clip_to_display(data, screen_limits): screen_limits (tuple): Screen limits Output: - clipped_data (np.ndarray): Clipped eye data + clipped_data (np.ndarray): Clipped eye data """ clipped_data = np.clip(data, screen_limits[0], screen_limits[1]) clipped_data = clipped_data[~np.isnan(clipped_data)] - + return clipped_data @@ -156,13 +157,13 @@ def visualize_gaze( right_eye_x = right_eye_data[0] right_eye_y = right_eye_data[1] eye_data = (left_eye_x, left_eye_y, right_eye_x, right_eye_y) - + # Transform the eye data to fit the display. Remove values < 1 & > 0, remove nan values screen_limits = (0, 1) clipped_data = [] for i in eye_data: clipped_data.append(clip_to_display(i, screen_limits)) - + lx, ly, rx, ry = clipped_data # Flip y axis @@ -334,27 +335,29 @@ def visualize_csv_eeg_triggers(trigger_col: Optional[int] = None): Figure of Triggers """ # Load in CSV - data = load_raw_data(choose_csv_file()) - raw_data = data.by_channel() - - # Pull out the triggers - if not trigger_col: - triggers = raw_data[-1] - else: - triggers = raw_data[trigger_col] - - # Plot the triggers - plt.plot(triggers) - - # Add some titles and labels to the figure - plt.title('Trigger Signal') - plt.ylabel('Trigger Value') - plt.xlabel('Samples') - - log.info('Press Ctrl + C to exit!') - # Show us the figure! Depending on your OS / IDE this may not close when - # The window is closed, see the message above - plt.show() + filename = choose_csv_file() + raw_data_list = load_raw_data(filename, [filename]) + for mode_data in raw_data_list: + raw_data = mode_data.by_channel() + + # Pull out the triggers + if not trigger_col: + triggers = raw_data[-1] + else: + triggers = raw_data[trigger_col] + + # Plot the triggers + plt.plot(triggers) + + # Add some titles and labels to the figure + plt.title('Trigger Signal') + plt.ylabel('Trigger Value') + plt.xlabel('Samples') + + log.info('Press Ctrl + C to exit!') + # Show us the figure! Depending on your OS / IDE this may not close when + # The window is closed, see the message above + plt.show() def visualize_joint_average( @@ -441,48 +444,48 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi trial_window = parameters.get("trial_window") static_offset = parameters.get("static_trigger_offset") - raw_data = load_raw_data(Path(session_path, f'{RAW_DATA_FILENAME}.csv')) - channels = raw_data.channels - sample_rate = raw_data.sample_rate - - transform_params = parameters.instantiate(ERPTransformParams) - - devices.load(Path(session_path, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=transform_params.notch_filter_frequency, - bandpass_low=transform_params.filter_low, - bandpass_high=transform_params.filter_high, - bandpass_order=transform_params.filter_order, - downsample_factor=transform_params.down_sampling_rate, - ) - # Process triggers.txt files - trigger_targetness, trigger_timing, _ = trigger_decoder( - offset=static_offset, - trigger_path=f"{session_path}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - ) - assert "nontarget" in trigger_targetness, "No nontarget triggers found." - assert "target" in trigger_targetness, "No target triggers found." - assert len(trigger_targetness) == len(trigger_timing), "Trigger targetness and timing must be the same length." - - labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] - channel_map = analysis_channels(channels, device_spec) - - erp = visualize_erp( - raw_data, - channel_map, - trigger_timing, - labels, - trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=session_path, - show=show, - ) - - # eye_data = visualize_gaze + raw_data_list = load_raw_data(session_path, [f'{RAW_DATA_FILENAME}.csv']) + + for mode_data in raw_data_list: + channels = mode_data.channels + sample_rate = mode_data.sample_rate + + transform_params = parameters.instantiate(ERPTransformParams) + + devices.load(Path(session_path, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(mode_data.daq_type) + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) + # Process triggers.txt files + trigger_targetness, trigger_timing, _ = trigger_decoder( + offset=static_offset, + trigger_path=f"{session_path}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + assert "nontarget" in trigger_targetness, "No nontarget triggers found." + assert "target" in trigger_targetness, "No target triggers found." + assert len(trigger_targetness) == len(trigger_timing), "Trigger targetness and timing must be the same length." + + labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] + channel_map = analysis_channels(channels, device_spec) + + erp = visualize_erp( + mode_data, + channel_map, + trigger_timing, + labels, + trial_window, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + save_path=session_path, + show=show, + ) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 972673a1c..1dd239e5f 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -34,6 +34,7 @@ DIPSIZE = (1707, 1067) IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' # IMG_PATH = f'{STATIC_IMAGES_PATH}/main/rsvp.png' +# TODO: Update images to contain the path to directory of the respective calibration session. def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): @@ -144,6 +145,10 @@ def offline_analysis( transform_params = parameters.instantiate(ERPTransformParams) downsample_rate = transform_params.down_sampling_rate static_offset = parameters.get("static_trigger_offset") + if trial_window is None: + trial_window = [0.0, 0.5] + # NOTE: Had to add it manually for offline analysis of multimodal datasets, + # since the trial_window information was not available in the parameters file. log.info( f"\nData processing settings: \n" diff --git a/bcipy/signal/process/extract_gaze.py b/bcipy/signal/process/extract_gaze.py index c208438d2..6c707dad0 100644 --- a/bcipy/signal/process/extract_gaze.py +++ b/bcipy/signal/process/extract_gaze.py @@ -2,46 +2,47 @@ from bcipy.helpers.exceptions import SignalException + def extract_eye_info(data): - """"Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples - Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. - The data is extracted according to the channel map: - ['device_ts, 'system_ts', 'left_x', 'left_y', 'left_pupil', 'right_x', 'right_y', 'right_pupil'] - - Args: - data (np.ndarray): Data in shape of num_channels x num_samples - - Returns: - left_eye (np.ndarray), left_pupil (List(float)) - right_eye (np.ndarray), right_pupil (List(float)) - """ - - # Extract samples from channels - lx = data[2, :] - ly = data[3, :] - left_pupil = data[4, :] # Use if needed - - rx = data[5, :] - ry = data[6, :] - right_pupil = data[7, :] # Use if needed - - left_eye = np.vstack((np.array(lx), np.array(ly))).T - right_eye = np.vstack((np.array(rx), np.array(ry))).T - - # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. - # Make sure that the number of samples are the same for both eyes - left_eye_nan_idx = np.isnan(left_eye).any(axis=1) - left_eye = left_eye[~left_eye_nan_idx] - right_eye = right_eye[~left_eye_nan_idx] - - right_eye_nan_idx = np.isnan(right_eye).any(axis=1) - left_eye = left_eye[~right_eye_nan_idx] - right_eye = right_eye[~right_eye_nan_idx] - - try: - len(left_eye) != len(right_eye) - except AssertionError: - raise SignalException( - 'Number of samples for left and right eye are not the same.') - - return left_eye, right_eye \ No newline at end of file + """"Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples + Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. + The data is extracted according to the channel map: + ['device_ts, 'system_ts', 'left_x', 'left_y', 'left_pupil', 'right_x', 'right_y', 'right_pupil'] + + Args: + data (np.ndarray): Data in shape of num_channels x num_samples + + Returns: + left_eye (np.ndarray), left_pupil (List(float)) + right_eye (np.ndarray), right_pupil (List(float)) + """ + + # Extract samples from channels + lx = data[2, :] + ly = data[3, :] + left_pupil = data[4, :] # Use if needed + + rx = data[5, :] + ry = data[6, :] + right_pupil = data[7, :] # Use if needed + + left_eye = np.vstack((np.array(lx), np.array(ly))).T + right_eye = np.vstack((np.array(rx), np.array(ry))).T + + # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. + # Make sure that the number of samples are the same for both eyes + left_eye_nan_idx = np.isnan(left_eye).any(axis=1) + left_eye = left_eye[~left_eye_nan_idx] + right_eye = right_eye[~left_eye_nan_idx] + + right_eye_nan_idx = np.isnan(right_eye).any(axis=1) + left_eye = left_eye[~right_eye_nan_idx] + right_eye = right_eye[~right_eye_nan_idx] + + try: + len(left_eye) != len(right_eye) + except AssertionError: + raise SignalException( + 'Number of samples for left and right eye are not the same.') + + return left_eye, right_eye diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 91d24026a..d37c3a973 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -95,7 +95,9 @@ def generate_replay_outputs( f"Static offset: {static_offset}" ) - raw_data = load_raw_data(Path(data_folder, f"{RAW_DATA_FILENAME}.csv")) + data_list = load_raw_data(data_folder, [f"{RAW_DATA_FILENAME}.csv"]) + # NOTE: With the current inputs this function only loads the EEG data. Update needed for eyetracker data. + raw_data = data_list[0] channels = raw_data.channels type_amp = raw_data.daq_type sample_rate = raw_data.sample_rate From 31ae2fd912faba3b51e010f889f57a24e74a7e78 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 20 Oct 2023 09:59:50 -0700 Subject: [PATCH 114/330] Initial work on generating calibration inquiries for VEP --- bcipy/helpers/list.py | 22 ++++- bcipy/helpers/stimuli.py | 180 ++++++++++++++++++++++++++++++++++++++- 2 files changed, 200 insertions(+), 2 deletions(-) diff --git a/bcipy/helpers/list.py b/bcipy/helpers/list.py index a8cfeb7c8..7a64fa48d 100644 --- a/bcipy/helpers/list.py +++ b/bcipy/helpers/list.py @@ -1,6 +1,6 @@ """Utility functions for list processing.""" -from typing import Callable, List from itertools import zip_longest +from typing import Any, Callable, List, Optional, Union def destutter(items: List, key: Callable = lambda x: x) -> List: @@ -34,3 +34,23 @@ def grouper(iterable, chunk_size, incomplete="fill", fillvalue=None): return zip(*chunks) raise ValueError("Expected fill or ignore") + + +def find_index(iterable: List, + match_item: Union[Any, Callable], + key: Callable = lambda x: x) -> Optional[int]: + """Find the index of the first item in the iterable which matches.""" + for i, value in enumerate(iterable): + if callable(match_item): + result = match_item(value) + else: + result = key(value) == match_item + if result: + return i + return None + +def swapped(lst: List, index1: int, index2: int) -> None: + """Creates a copy of the provided list with elements at the given indices + swapped.""" + replacements = { index1: lst[index2], index2: lst[index1] } + return [replacements.get(i, val) for i, val in enumerate(lst)] diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index d4e55dd0a..32288cc69 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -13,7 +13,7 @@ from PIL import Image from bcipy.helpers.exceptions import BciPyCoreException -from bcipy.helpers.list import grouper +from bcipy.helpers.list import find_index, grouper, swapped # Prevents pillow from filling the console with debug info logging.getLogger('PIL').setLevel(logging.WARNING) @@ -1069,3 +1069,181 @@ def ssvep_to_code(refresh_rate: int = 60, flicker_rate: int = 10) -> List[int]: t = 1 - t return codes + +# def generate_vep_calibration_inquiries( +# alp: List[str], +# timing: List[float] = None, +# color: List[str] = None, +# inquiry_count: int = 100, +# num_boxes: int = 4, +# is_txt: bool = True) -> InquirySchedule: +# """ +# Generates VEP inquiries with target letters in all possible positions. + +# In the VEP paradigm, all stimuli in the alphabet are displayed in each +# inquiry. The symbols with the highest likelihoods are displayed alone +# while those with lower likelihoods occur together. + +# Parameters +# ---------- +# alp(list[str]): stimuli +# timing(list[float]): Task specific timing for generator. +# [target, fixation, stimuli] +# color(list[str]): Task specific color for generator +# [target, fixation, stimuli] +# inquiry_count(int): number of inquiries in a calibration +# num_boxes(int): number of display boxes +# is_txt(bool): whether the stimuli type is text. False would be an image stimuli. + +# Return +# ------ +# schedule_inq(tuple( +# samples[list[list[str]]]: list of inquiries +# timing(list[list[float]]): list of timings +# color(list(list[str])): list of colors)): scheduled inquiries +# """ +# if timing is None: +# timing = [0.5, 1, 2] +# # if color is None: +# # color = ['green', 'red', 'white'] +# assert len( +# timing +# ) == 3, "timing must include values for [target, fixation, stimuli]" +# time_target, time_fixation, time_stim = timing +# fixation = get_fixation(is_txt) + +# inquiries = generate_vep_inquiries(alp, inquiry_count, num_boxes) + + +# return InquirySchedule(samples, times, colors) + +def generate_vep_inquiries(alphabet: List[str], num_boxes: int=6, inquiry_count: int=100): + """Generates inquiries""" + + +def stim_per_box(num_symbols: int, + num_boxes: int = 6, + max_empty_boxes: int = 1, + max_single_sym_boxes: int = 4) -> List[int]: + """Determine the number of stimuli per vep box. + + Parameters + ---------- + num_symbols - number of symbols + num_boxes - number of boxes + max_empty_boxes - the maximum number of boxes which won't have any + symbols within them. + max_single_sym_boxes - maximum number of boxes with a single symbol + + Returns + ------- + A list of length num_boxes, where each number in the list represents + the number of symbols that should be in the box at that position. + + Post conditions: + The sum of the list should equal num_symbols. Further, there should + be at most max_empty_boxes with value of 0 and max_single_sym_boxes + with a value of 1. + """ + # Logic based off of example sessions from: + # https://www.youtube.com/watch?v=JNFYSeIIOrw + # [[2, 3, 5, 5, 6, 7], + # [2, 1, 10, 1, 1, 13], + # [3, 4, 17, 1, 1, 2], + # [1, 1, 1, 0, 1, 24], + # [1, 2, 1, 22, 1, 1], + # [2, 1, 1, 21, 2, 1], + # [1, 1, 25, 0, 1, 0]] + # and + # [[7, 3, 4, 9, 2, 3], + # 1, 1, 6, 9, 7, 2], + # 1, 2, 18, 2, 3, 2], + # 1, 1, 4, 4, 17, 1], + # 1, 3, 1, 1, 20, 2], + # 1, 1, 1, 20, 3, 2], + # 1, 1, 1, 4, 21, 0]] + + # no more than 1 empty box + empty_boxes = [0] * random.choice(range(max_empty_boxes + 1)) + + # no more than 4 boxes with a single symbol + single_boxes = [1] * random.choice( + range((max_single_sym_boxes + 1) - len(empty_boxes))) + + boxes = empty_boxes + single_boxes + + remaining_symbols = num_symbols - sum(boxes) + remaining_boxes = num_boxes - len(boxes) + + # iterate through the remaining boxes except for the last one + for _box in range(remaining_boxes - 1): + # each remaining box must have 2 or more symbols + box_max = remaining_symbols - (2 * remaining_boxes - 1) + + n = random.choice(range(2, box_max + 1)) + boxes.append(n) + remaining_boxes -= 1 + remaining_symbols = remaining_symbols - n + + # last box + boxes.append(remaining_symbols) + # random.shuffle(boxes) + return sorted(boxes) + + +def generate_vep_inquiry(alphabet: List[str], + num_boxes: int = 6, + target: str = None, + target_pos: int = None) -> List[List[str]]: + """Generates a single random inquiry. + + Parameters + ---------- + alphabet - list of symbols from which to select. + num_boxes - number of display areas; symbols will be partitioned into + these areas. + target - target symbol for the generated inquiry + target_pos - box index that should contain the target + + Returns + ------- + An inquiry represented by a list of lists, where each sublist + represents a display box and contains symbols that should appear in that box. + + Post-conditions: + Symbols will not be repeated and all symbols will be partitioned into + one of the boxes. + """ + + box_counts = stim_per_box(num_symbols=len(alphabet), num_boxes=num_boxes) + + syms = [sym for sym in alphabet] + random.shuffle(syms) + + if target: + # Move the target to the front so it gets put in the lowest count box + # greater than 0. + syms = swapped(syms, + index1=0, + index2=syms.index(target)) + # Put syms in boxes + boxes = [] + sym_index = 0 + for count in box_counts: + box = [] + for _i in range(count): + box.append(syms[sym_index]) + sym_index += 1 + box.sort() # sort stim within box + boxes.append(box) + + random.shuffle(boxes) + + if target and target_pos is not None: + # Find the box with the target and swap with the box currently at the + # target_pos. + boxes = swapped(boxes, + index1=find_index(boxes, lambda box: target in box), + index2=target_pos) + + return boxes From d1a08785f5fdc04c5d0cc1c4f56bc55c4fcbdddf Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 20 Oct 2023 10:01:15 -0700 Subject: [PATCH 115/330] Stubs for VEP calibration task --- bcipy/task/paradigm/vep/__init__.py | 0 bcipy/task/paradigm/vep/calibration.py | 5 +++++ 2 files changed, 5 insertions(+) create mode 100644 bcipy/task/paradigm/vep/__init__.py create mode 100644 bcipy/task/paradigm/vep/calibration.py diff --git a/bcipy/task/paradigm/vep/__init__.py b/bcipy/task/paradigm/vep/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py new file mode 100644 index 000000000..d92240fc9 --- /dev/null +++ b/bcipy/task/paradigm/vep/calibration.py @@ -0,0 +1,5 @@ +from bcipy.task import Task + + +class VEPCalibrationTask(Task): + """VEP Calibration Task""" \ No newline at end of file From b19e41aaa676612c400717cdc6c49a47d90330c8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 20 Oct 2023 14:00:59 -0700 Subject: [PATCH 116/330] Reverted triggers.py; added parameter to trigger_decoder for the option to not apply the starting offset; updated offline_analysis with the new changes and fixed the imports --- bcipy/helpers/tests/test_triggers.py | 27 ++++++++++++++++++ bcipy/helpers/triggers.py | 37 ++++++++++-------------- bcipy/signal/model/offline_analysis.py | 39 +++++++++++++------------- 3 files changed, 62 insertions(+), 41 deletions(-) diff --git a/bcipy/helpers/tests/test_triggers.py b/bcipy/helpers/tests/test_triggers.py index 7138d32bf..51268a783 100644 --- a/bcipy/helpers/tests/test_triggers.py +++ b/bcipy/helpers/tests/test_triggers.py @@ -593,6 +593,33 @@ def test_trigger_decoder_with_device(self, path_exists_mock): self.assertAlmostEqual(times[0], 4.13) self.assertAlmostEqual(times[-1], 6.85) + @patch('bcipy.helpers.triggers.os.path.exists') + def test_trigger_decoder_without_starting_offset(self, path_exists_mock): + """Test trigger decoder""" + trg_data = '''starting_offset offset -3.47 + starting_offset_EYETRACKER offset -4.45 + J prompt 6.15 + + fixation 8.11 + F nontarget 8.58 + D nontarget 8.88 + J target 9.18 + T nontarget 9.49 + K nontarget 9.79 + _ nontarget 11.30''' + path_exists_mock.returnValue = True + with patch('builtins.open', mock_open(read_data=trg_data), + create=True): + types, times, labels = trigger_decoder('triggers.txt', + device_type='EYETRACKER', + apply_starting_offset=False) + + self.assertListEqual(types, [ + 'nontarget', 'nontarget', 'target', 'nontarget', 'nontarget', + 'nontarget' + ]) + self.assertListEqual(labels, ['F', 'D', 'J', 'T', 'K', '_']) + self.assertAlmostEqual(times[0], 8.58) + self.assertAlmostEqual(times[-1], 11.30) if __name__ == '__main__': unittest.main() diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 505784256..cbee64413 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -282,8 +282,7 @@ def starting_offsets_by_device( def find_starting_offset(triggers: List[Trigger], - device_type: Optional[str] = None, - apply_system_offset: Optional[bool] = True) -> Trigger: + device_type: Optional[str] = None) -> Trigger: """Given a list of raw trigger data, determine the starting offset for the given device. The returned trigger has the timestamp of the first sample recorded for the device. @@ -299,20 +298,16 @@ def find_starting_offset(triggers: List[Trigger], device_type - each device will generally have a different offset. This parameter is used to determine which trigger to use. If not given the EEG offset will be used by default. Ex. 'EYETRACKER' - apply_system_offset (Optional bool) - if True, applies the system offset loaded from the triggers file. - If False, returns a Trigger with offset of 0.0. Returns ------- The Trigger for the first matching offset for the given device, or a Trigger with offset of 0.0 if a matching offset was not found. """ label = offset_label(device_type) - - if apply_system_offset: - for trg in triggers: - if trg.type == TriggerType.OFFSET and trg.label == label: - return trg - log.info(f"Offset not found, or not used (device_type: {device_type}); using 0.0") + for trg in triggers: + if trg.type == TriggerType.OFFSET and trg.label == label: + return trg + log.info(f"Offset not found (device_type: {device_type}); using 0.0") return Trigger(label, TriggerType.OFFSET, 0.0) @@ -428,7 +423,6 @@ def read_text_file(path: str) -> Tuple[List[Trigger], float]: @staticmethod def load(path: str, offset: Optional[float] = 0.0, - apply_system_offset: bool = True, exclusion: Optional[List[TriggerType]] = None, device_type: Optional[str] = None) -> List[Trigger]: """ @@ -449,7 +443,6 @@ def load(path: str, Input string must include file extension (.txt). offset (Optional float): if desired, time offset for all loaded triggers, positive number for adding time, negative number for subtracting time. - apply_system_offset (Optional bool): if desired, applies the system offset loaded from the triggers file. exclusion (Optional List[TriggerType]): if desired, list of TriggerType's to be removed from the loaded trigger list. device_type : optional; if specified looks for the starting_offset for @@ -460,12 +453,10 @@ def load(path: str, List of Triggers from loaded .txt file with desired modifications """ excluded_types = exclusion or [] - triggers = read(path) - starting_offset = find_starting_offset(triggers, device_type, apply_system_offset) - + starting_offset = find_starting_offset(triggers, device_type) return apply_offsets(exclude_types(triggers, excluded_types), - starting_offset.time, + starting_offset, static_offset=offset) def add_triggers(self, triggers: List[Trigger]) -> List[Trigger]: @@ -506,7 +497,8 @@ def trigger_decoder( remove_pre_fixation: bool = True, offset: float = 0.0, exclusion: Optional[List[TriggerType]] = None, - device_type: Optional[str] = None, apply_system_offset: bool = True) -> Tuple[list, list, list]: + device_type: Optional[str] = None, + apply_starting_offset: bool = True) -> Tuple[list, list, list]: """Trigger Decoder. Given a path to trigger data, this method loads valid Triggers and returns their type, timing and label. @@ -519,9 +511,8 @@ def trigger_decoder( exclusion: any TriggerTypes to be filtered from data returned device_type: used to determine which starting_offset value to use; if a 'starting_offset' trigger is found it will be applied. - apply_system_offset: if True, keeps the 'starting_offset' value from the triggers file. - If False, sets it to 0.0. - + apply_starting_offset: if False, does not apply the starting offset for + the given device_type. Returns ------- tuple: trigger_type, trigger_timing, trigger_label @@ -532,10 +523,12 @@ def trigger_decoder( ] triggers = read(trigger_path) - starting_offset = find_starting_offset(triggers, device_type, apply_system_offset) + starting_offset = Trigger('', TriggerType.OFFSET, 0.0) + if apply_starting_offset: + starting_offset = find_starting_offset(triggers, device_type) filtered = exclude_types(triggers, excluded_types) corrected = apply_offsets(filtered, starting_offset, static_offset=offset) labels, types, times = zip(*corrected) - return list(map(str, types)), list(times), list(labels) + return list(map(str, types)), list(times), list(labels) \ No newline at end of file diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 1dd239e5f..5b98e3cd6 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -2,31 +2,33 @@ from pathlib import Path from typing import Tuple -from bcipy.config import (DEFAULT_PARAMETERS_PATH, TRIGGER_FILENAME, +import numpy as np +from matplotlib.figure import Figure +from sklearn.metrics import balanced_accuracy_score +from sklearn.model_selection import train_test_split + +import bcipy.acquisition.devices as devices +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETERS_PATH, EYE_TRACKER_FILENAME_PREFIX, RAW_DATA_FILENAME, STATIC_AUDIO_PATH, - DEFAULT_DEVICE_SPEC_FILENAME, - STATIC_IMAGES_PATH, EYE_TRACKER_FILENAME_PREFIX) + STATIC_IMAGES_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import save_model from bcipy.helpers.stimuli import play_sound, update_inquiry_timing -from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.symbols import alphabet +from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.helpers.visualization import visualize_erp, visualize_gaze, visualize_gaze_inquiries +from bcipy.helpers.visualization import (visualize_erp, visualize_gaze, + visualize_gaze_inquiries) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata -from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel -from bcipy.signal.process import (ERPTransformParams, filter_inquiries, - get_default_transform, extract_eye_info) from bcipy.signal.model.fusion_model import GazeModel -import numpy as np -from matplotlib.figure import Figure -from sklearn.metrics import balanced_accuracy_score -from sklearn.model_selection import train_test_split -import bcipy.acquisition.devices as devices +from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel +from bcipy.signal.process import (ERPTransformParams, extract_eye_info, + filter_inquiries, get_default_transform) log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") @@ -188,11 +190,10 @@ def offline_analysis( # Process triggers.txt files trigger_targetness, trigger_timing, _ = trigger_decoder( - offset=static_offset, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - device_type='EEG', - apply_system_offset=True + offset=static_offset, + device_type='EEG' ) # update the trigger timing list to account for the initial trial window @@ -287,16 +288,16 @@ def offline_analysis( # Extract all Triggers info trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - remove_pre_fixation=False, - apply_system_offset=False, trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + remove_pre_fixation=False, exclusion=[ TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION, TriggerType.SYSTEM, TriggerType.OFFSET], - device_type='EYETRACKER' + device_type='EYETRACKER', + apply_starting_offset=False ) ''' Trigger_timing includes PROMPT and excludes FIXATION ''' From ab204dda1ff4f726366ca74c49b005493041a13b Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 20 Oct 2023 16:39:09 -0700 Subject: [PATCH 117/330] Added function in acquisition helper for computing the raw_data filename based on the device spec. Refactored offline_analysis to use the new function for finding the appropriate raw data file. --- bcipy/helpers/acquisition.py | 24 +++++++++++---- bcipy/helpers/load.py | 2 +- bcipy/helpers/tests/test_acquisition.py | 25 ++++++++++++++-- bcipy/helpers/tests/test_triggers.py | 1 + bcipy/helpers/triggers.py | 2 +- bcipy/signal/model/offline_analysis.py | 40 +++++++------------------ 6 files changed, 55 insertions(+), 39 deletions(-) diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index 83c878dea..fc0098cb0 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -2,17 +2,19 @@ import logging import subprocess import time -from typing import Dict, List, Tuple, Optional +from typing import Dict, List, Optional, Tuple import numpy as np +from bcipy.acquisition import (ClientManager, LslAcquisitionClient, + LslDataServer, await_start, + discover_device_spec) from bcipy.acquisition.devices import (DeviceSpec, preconfigured_device, with_content_type) -from bcipy.acquisition import (LslAcquisitionClient, await_start, - LslDataServer, discover_device_spec, - ClientManager) +from bcipy.config import BCIPY_ROOT +from bcipy.config import DEFAULT_DEVICE_SPEC_FILENAME as spec_name +from bcipy.config import RAW_DATA_FILENAME from bcipy.helpers.save import save_device_specs -from bcipy.config import BCIPY_ROOT, RAW_DATA_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME as spec_name log = logging.getLogger(__name__) @@ -62,7 +64,7 @@ def init_eeg_acquisition( await_start(dataserver) device_spec = init_device(content_type, device_name) - raw_data_name = f'{RAW_DATA_FILENAME}.csv' if content_type == 'EEG' else None + raw_data_name = raw_data_filename(device_spec) client = init_lsl_client(parameters, device_spec, save_folder, raw_data_name) @@ -80,6 +82,16 @@ def init_eeg_acquisition( return (manager, servers) +def raw_data_filename(device_spec: DeviceSpec) -> str: + """Returns the name of the raw data file for the given device.""" + if device_spec.content_type == 'EEG': + return f'{RAW_DATA_FILENAME}.csv' + + content_type = '_'.join(device_spec.content_type.split()).lower() + name = '_'.join(device_spec.name.split()).lower() + return f"{content_type}_data_{name}.csv" + + def init_device(content_type: str, device_name: Optional[str] = None) -> DeviceSpec: """Initialize a DeviceSpec for the given content type. diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 5d45b7070..863885629 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -226,7 +226,7 @@ def load_raw_data(data_folder: str, data_paths: List[str]) -> List[RawData]: data = [] for data_path in data_paths: filename = Path(data_folder, data_path) - if os.path.exists(filename): + if filename.exists(): data.append(RawData.load(filename)) else: raise FileNotFoundError(f'Could not find {filename}') diff --git a/bcipy/helpers/tests/test_acquisition.py b/bcipy/helpers/tests/test_acquisition.py index 057c90fc1..1cc741ca7 100644 --- a/bcipy/helpers/tests/test_acquisition.py +++ b/bcipy/helpers/tests/test_acquisition.py @@ -4,10 +4,13 @@ from pathlib import Path from unittest.mock import Mock, patch +from bcipy.acquisition.devices import DeviceSpec from bcipy.config import DEFAULT_PARAMETERS_PATH -from bcipy.helpers.acquisition import (init_device, init_eeg_acquisition, +from bcipy.helpers.acquisition import (RAW_DATA_FILENAME, init_device, + init_eeg_acquisition, max_inquiry_duration, parse_stream_type, - server_spec, stream_types) + raw_data_filename, server_spec, + stream_types) from bcipy.helpers.load import load_json_parameters from bcipy.helpers.save import init_save_data_structure @@ -166,6 +169,24 @@ def test_server_spec_without_named_device(self, with_content_type_mock): with_content_type_mock.assert_called_with('EEG') self.assertEqual(device_spec, device1) + def test_raw_data_filename_eeg(self): + """Test generation of filename for EEG devices""" + device = DeviceSpec(name='DSI-24', + channels=[], + sample_rate=300.0, + content_type='EEG') + self.assertEqual(raw_data_filename(device), f'{RAW_DATA_FILENAME}.csv') + + def test_raw_data_filename(self): + """Test generation of filename""" + + device = DeviceSpec(name='Tobii-P0', + channels=[], + sample_rate=60, + content_type='EYETRACKER') + self.assertEqual(raw_data_filename(device), + 'eyetracker_data_tobii-p0.csv') + if __name__ == '__main__': unittest.main() diff --git a/bcipy/helpers/tests/test_triggers.py b/bcipy/helpers/tests/test_triggers.py index 51268a783..9b9d2a59a 100644 --- a/bcipy/helpers/tests/test_triggers.py +++ b/bcipy/helpers/tests/test_triggers.py @@ -621,5 +621,6 @@ def test_trigger_decoder_without_starting_offset(self, path_exists_mock): self.assertAlmostEqual(times[0], 8.58) self.assertAlmostEqual(times[-1], 11.30) + if __name__ == '__main__': unittest.main() diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index cbee64413..65f0c1710 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -531,4 +531,4 @@ def trigger_decoder( corrected = apply_offsets(filtered, starting_offset, static_offset=offset) labels, types, times = zip(*corrected) - return list(map(str, types)), list(times), list(labels) \ No newline at end of file + return list(map(str, types)), list(times), list(labels) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 5b98e3cd6..08aca7b27 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -9,10 +9,9 @@ import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, - DEFAULT_PARAMETERS_PATH, EYE_TRACKER_FILENAME_PREFIX, - RAW_DATA_FILENAME, STATIC_AUDIO_PATH, + DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH, STATIC_IMAGES_PATH, TRIGGER_FILENAME) -from bcipy.helpers.acquisition import analysis_channels +from bcipy.helpers.acquisition import analysis_channels, raw_data_filename from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) from bcipy.helpers.parameters import Parameters @@ -120,29 +119,6 @@ def offline_analysis( # We use half of that time here to buffer during transforms buffer = int(parameters.get("task_buffer_length") / 2) - acq_mode = parameters.get("acq_mode") - # handle multiple acquisition. Note: we only currently support Eyetracker + EEG - data_file_paths = [] - if '+' in acq_mode: - if 'eyetracker' in acq_mode.lower(): - # find the eyetracker data file with the prefix of EYE_TRACKER_FILENAME_PREFIX - eye_tracker_file = [f.name for f in Path(data_folder).iterdir() - if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] - assert len( - eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {data_folder}. Expected 1." - data_file_paths.extend(eye_tracker_file) - else: - raise ValueError(f"Unsupported acquisition mode: {acq_mode}. Eyetracker must be included.") - if 'eeg' in acq_mode.lower(): - # find the eeg data file with the prefix of EEG_FILENAME_PREFIX - eeg_file = [f.name for f in Path(data_folder).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] - assert len(eeg_file) == 1, f"Found {len(eeg_file)} EEG files in {data_folder}. Expected 1." - data_file_paths.extend(eeg_file) - else: - raise ValueError(f"Unsupported acquisition mode: {acq_mode}. EEG must be included.") - else: - data_file_paths = [f"{RAW_DATA_FILENAME}.csv"] - # get signal filtering information transform_params = parameters.instantiate(ERPTransformParams) downsample_rate = transform_params.down_sampling_rate @@ -160,12 +136,19 @@ def offline_analysis( f"Static offset: {static_offset}" ) + devices_by_name = devices.load( + Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME), replace=True) + data_file_paths = [ + path for path in (Path(data_folder, raw_data_filename(device_spec)) + for device_spec in devices_by_name.values()) + if path.exists() + ] + # raw_data: [RawData(EyeTracker, RawData(EEG)] raw_data = load_raw_data(data_folder, data_file_paths) for mode_data in raw_data: - devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(mode_data.daq_type) + device_spec = devices_by_name.get(mode_data.daq_type) # extract relevant information from raw data object eeg if device_spec.content_type == "EEG": channels = mode_data.channels @@ -351,7 +334,6 @@ def offline_analysis( raw_plot=True, ) - breakpoint() if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") From 7b5963f39cb3edd5c9c486cea185e6640465d42f Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 20 Oct 2023 17:42:00 -0700 Subject: [PATCH 118/330] Reverted load_raw_data back to taking a single parameter. --- bcipy/helpers/convert.py | 20 ++- bcipy/helpers/demo/demo_load_raw_data.py | 59 -------- bcipy/helpers/demo/demo_visualization.py | 171 +++++++++-------------- bcipy/helpers/load.py | 14 +- bcipy/helpers/visualization.py | 171 +++++++++++------------ bcipy/signal/model/offline_analysis.py | 29 ++-- 6 files changed, 174 insertions(+), 290 deletions(-) delete mode 100644 bcipy/helpers/demo/demo_load_raw_data.py diff --git a/bcipy/helpers/convert.py b/bcipy/helpers/convert.py index 93d3bade4..5a5f5ee7e 100644 --- a/bcipy/helpers/convert.py +++ b/bcipy/helpers/convert.py @@ -3,22 +3,20 @@ import os import tarfile from pathlib import Path -from typing import Dict, List, Tuple, Optional +from typing import Dict, List, Optional, Tuple +import mne import numpy as np - -from pyedflib import FILETYPE_EDFPLUS, EdfWriter, FILETYPE_BDFPLUS +from mne.io import RawArray +from pyedflib import FILETYPE_BDFPLUS, FILETYPE_EDFPLUS, EdfWriter from tqdm import tqdm -from bcipy.config import RAW_DATA_FILENAME, TRIGGER_FILENAME, DEFAULT_PARAMETER_FILENAME +from bcipy.config import (DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, + TRIGGER_FILENAME) from bcipy.helpers.load import load_json_parameters, load_raw_data from bcipy.helpers.raw_data import RawData -from bcipy.signal.process import Composition, get_default_transform from bcipy.helpers.triggers import trigger_decoder, trigger_durations - -import mne -from mne.io import RawArray - +from bcipy.signal.process import Composition, get_default_transform logger = logging.getLogger(__name__) @@ -170,9 +168,7 @@ def pyedf_convert(data_dir: str, params = load_json_parameters(Path(data_dir, DEFAULT_PARAMETER_FILENAME), value_cast=True) - data_list = load_raw_data(data_dir, [f'{RAW_DATA_FILENAME}.csv']) - # NOTE: With the current inputs this function only loads the EEG data. Update needed for eyetracker data. - data = data_list[0] + data = load_raw_data(Path(data_dir, f'{RAW_DATA_FILENAME}.csv')) fs = data.sample_rate if pre_filter: default_transform = get_default_transform( diff --git a/bcipy/helpers/demo/demo_load_raw_data.py b/bcipy/helpers/demo/demo_load_raw_data.py deleted file mode 100644 index d039cc3ba..000000000 --- a/bcipy/helpers/demo/demo_load_raw_data.py +++ /dev/null @@ -1,59 +0,0 @@ -from bcipy.helpers.load import ( - load_raw_data, load_json_parameters -) -from pathlib import Path -from bcipy.config import (DEFAULT_PARAMETERS_PATH, EYE_TRACKER_FILENAME_PREFIX) - - -def main(data_folder, data_file_paths): - """Load BciPy raw data, print info to console, and return data to caller.""" - # Load all data saved in the directory - - raw_data_list = load_raw_data(data_folder, data_file_paths) - for mode_data in raw_data_list: - channels = mode_data.channels - type_amp = mode_data.daq_type - sample_rate = mode_data.sample_rate - # access data using raw_data.channel_data or raw_data.numerical_data - print(f'Successfully loaded raw data from {type_amp}') - print(f'Channels: {channels}') - print(f'Type: {type_amp}') - print(f'Sample rate: {sample_rate}') - print(f'Data shape: {mode_data.channel_data.shape}') - return raw_data_list - - -if __name__ == "__main__": - import argparse - from bcipy.config import RAW_DATA_FILENAME - - parser = argparse.ArgumentParser() - parser.add_argument('-d', '--data_folder', required=True, help='Path to data folder') - parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) - args = parser.parse_args() - - parameters = load_json_parameters(args.parameters_file, value_cast=True) - acq_mode = parameters.get("acq_mode") - - data_file_paths = [] - if '+' in acq_mode: - if 'eyetracker' in acq_mode.lower(): - # find the eyetracker data file with the prefix of EYE_TRACKER_FILENAME_PREFIX - eye_tracker_file = [f.name for f in Path(args.data_folder).iterdir() - if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] - assert len( - eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {args.data_folder}." - data_file_paths.extend(eye_tracker_file) - else: - raise ValueError(f"Unsupported acquisition mode: {acq_mode}. Eyetracker must be included.") - if 'eeg' in acq_mode.lower(): - # find the eeg data file with the prefix of EEG_FILENAME_PREFIX - eeg_file = [f.name for f in Path(args.data_folder).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] - assert len(eeg_file) == 1, f"Found {len(eeg_file)} EEG files in {args.data_folder}. Expected 1." - data_file_paths.extend(eeg_file) - else: - raise ValueError(f"Unsupported acquisition mode: {acq_mode}. EEG must be included.") - else: - data_file_paths = [f"{RAW_DATA_FILENAME}.csv"] - - raw_data_list = main(args.data_folder, data_file_paths) diff --git a/bcipy/helpers/demo/demo_visualization.py b/bcipy/helpers/demo/demo_visualization.py index 078266eb0..5d0fd83bd 100644 --- a/bcipy/helpers/demo/demo_visualization.py +++ b/bcipy/helpers/demo/demo_visualization.py @@ -13,20 +13,16 @@ - - `python bcipy/helpers/demo/demo_visualization.py --save"` this will save the visualizations generated to the provided or selected path """ -from bcipy.config import (TRIGGER_FILENAME, RAW_DATA_FILENAME, EYE_TRACKER_FILENAME_PREFIX, - DEFAULT_DEVICE_SPEC_FILENAME, DEFAULT_PARAMETERS_PATH, - DEFAULT_PARAMETER_FILENAME) +import bcipy.acquisition.devices as devices +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, + TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels -from bcipy.signal.process import get_default_transform -from bcipy.helpers.load import ( - load_experimental_data, - load_json_parameters, - load_raw_data, -) -from bcipy.helpers.visualization import visualize_erp +from bcipy.helpers.load import (load_experimental_data, load_json_parameters, + load_raw_data) from bcipy.helpers.triggers import TriggerType, trigger_decoder -import bcipy.acquisition.devices as devices - +from bcipy.helpers.visualization import visualize_erp +from bcipy.signal.process import get_default_transform if __name__ == '__main__': import argparse @@ -34,106 +30,73 @@ parser = argparse.ArgumentParser() parser.add_argument( - '-d', - '--data_folder', + '-p', + '--path', help='Path to the directory with raw_data to be converted', required=False) - parser.add_argument("-p", "--parameters_file", default=DEFAULT_PARAMETERS_PATH) parser.add_argument("--show", dest="show", action="store_true") parser.add_argument("--save", dest="save", action="store_true") parser.set_defaults(show=False) parser.set_defaults(save=False) args = parser.parse_args() - path = args.data_folder + path = args.path if not path: path = load_experimental_data() - parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) - else: - parameters = load_json_parameters(args.parameters_file, value_cast=True) - - acq_mode = parameters.get("acq_mode") - - # Make sure you are loading the correct raw data: - data_file_paths = [] - if '+' in acq_mode: - if 'eyetracker' in acq_mode.lower(): - # find the eyetracker data file with the prefix of EYE_TRACKER_FILENAME_PREFIX - eye_tracker_file = [f.name for f in Path(path).iterdir() - if f.name.startswith(EYE_TRACKER_FILENAME_PREFIX)] - assert len( - eye_tracker_file) == 1, f"Found {len(eye_tracker_file)} eyetracker files in {path}. Expected 1." - data_file_paths.extend(eye_tracker_file) - else: - raise ValueError(f"Unsupported acquisition mode: {acq_mode}. Eyetracker must be included.") - if 'eeg' in acq_mode.lower(): - # find the eeg data file with the prefix of EEG_FILENAME_PREFIX - eeg_file = [f.name for f in Path(path).iterdir() if f.name.startswith(RAW_DATA_FILENAME)] - assert len(eeg_file) == 1, f"Found {len(eeg_file)} EEG files in {path}. Expected 1." - data_file_paths.extend(eeg_file) - else: - raise ValueError(f"Unsupported acquisition mode: {acq_mode}. EEG must be included.") - else: - data_file_paths = [f"{RAW_DATA_FILENAME}.csv"] - - raw_data_list = load_raw_data(path, data_file_paths) - - for mode_data in raw_data_list: - devices.load(Path(path, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(mode_data.daq_type) - # extract all relevant parameters from raw data object eeg - if device_spec.content_type == "Eyetracker": - continue - elif device_spec.content_type == "EEG": - trial_window = parameters.get("trial_window") - if trial_window is None: - trial_window = [0.0, 0.5] - prestim_length = parameters.get("prestim_length") - trials_per_inquiry = parameters.get("stim_length") - # The task buffer length defines the min time between two inquiries - # We use half of that time here to buffer during transforms - buffer = int(parameters.get("task_buffer_length") / 2) - # get signal filtering information - downsample_rate = parameters.get("down_sampling_rate") - notch_filter = parameters.get("notch_filter_frequency") - filter_high = parameters.get("filter_high") - filter_low = parameters.get("filter_low") - filter_order = parameters.get("filter_order") - static_offset = parameters.get("static_trigger_offset") - channels = mode_data.channels - type_amp = mode_data.daq_type - sample_rate = mode_data.sample_rate - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=notch_filter, - bandpass_low=filter_low, - bandpass_high=filter_high, - bandpass_order=filter_order, - downsample_factor=downsample_rate, - ) - # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - offset=static_offset, - trigger_path=f"{path}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - ) - labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] - - channel_map = analysis_channels(channels, device_spec) - - save_path = None if not args.save else path - figure_handles = visualize_erp( - mode_data, - channel_map, - trigger_timing, - labels, - trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=save_path, - show=args.show - ) + parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) + + # extract all relevant parameters + trial_window = parameters.get("trial_window") + prestim_length = parameters.get("prestim_length") + trials_per_inquiry = parameters.get("stim_length") + # The task buffer length defines the min time between two inquiries + # We use half of that time here to buffer during transforms + buffer = int(parameters.get("task_buffer_length") / 2) + # get signal filtering information + downsample_rate = parameters.get("down_sampling_rate") + notch_filter = parameters.get("notch_filter_frequency") + filter_high = parameters.get("filter_high") + filter_low = parameters.get("filter_low") + filter_order = parameters.get("filter_order") + static_offset = parameters.get("static_trigger_offset") + raw_data = load_raw_data(Path(path, f'{RAW_DATA_FILENAME}.csv')) + channels = raw_data.channels + type_amp = raw_data.daq_type + sample_rate = raw_data.sample_rate + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=notch_filter, + bandpass_low=filter_low, + bandpass_high=filter_high, + bandpass_order=filter_order, + downsample_factor=downsample_rate, + ) + # Process triggers.txt files + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + offset=static_offset, + trigger_path=f"{path}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] + + devices.load(Path(path, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(raw_data.daq_type) + channel_map = analysis_channels(channels, device_spec) + + save_path = None if not args.save else path + + figure_handles = visualize_erp( + raw_data, + channel_map, + trigger_timing, + labels, + trial_window, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + save_path=save_path, + show=args.show + ) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 863885629..a12980ef3 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -211,26 +211,18 @@ def choose_csv_file(filename: str = None) -> str: return filename -def load_raw_data(data_folder: str, data_paths: List[str]) -> List[RawData]: +def load_raw_data(filename: str) -> RawData: """Reads the data (.csv) file written by data acquisition. Parameters ---------- - - data_folder : path to the serialized data location - - data_paths : list of paths to the serialized data (csv file) + - filename : path to the serialized data (csv file) Returns ------- RawData object with data held in memory """ - data = [] - for data_path in data_paths: - filename = Path(data_folder, data_path) - if filename.exists(): - data.append(RawData.load(filename)) - else: - raise FileNotFoundError(f'Could not find {filename}') - return data + return RawData.load(filename) def load_txt_data() -> str: diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 2679b8afc..04d4ef4b8 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -1,30 +1,29 @@ import logging - -from typing import List, Optional, Tuple from pathlib import Path +from typing import List, Optional, Tuple + +import matplotlib.pyplot as plt +import mne +import numpy as np +import pandas as pd +import seaborn as sns from matplotlib.figure import Figure from matplotlib.patches import Ellipse +from mne import Epochs +from mne.io import read_raw_edf +from scipy import linalg -from bcipy.config import (TRIGGER_FILENAME, RAW_DATA_FILENAME, - DEFAULT_DEVICE_SPEC_FILENAME, - STATIC_IMAGES_PATH) +import bcipy.acquisition.devices as devices +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, RAW_DATA_FILENAME, + STATIC_IMAGES_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels -from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.convert import convert_to_mne from bcipy.helpers.load import choose_csv_file, load_raw_data -from bcipy.helpers.stimuli import mne_epochs from bcipy.helpers.raw_data import RawData -from bcipy.signal.process import Composition, get_default_transform, ERPTransformParams - -import bcipy.acquisition.devices as devices -import mne -from mne import Epochs -from mne.io import read_raw_edf -import numpy as np -import seaborn as sns -from scipy import linalg -import matplotlib.pyplot as plt -import pandas as pd +from bcipy.helpers.stimuli import mne_epochs +from bcipy.helpers.triggers import TriggerType, trigger_decoder +from bcipy.signal.process import (Composition, ERPTransformParams, + get_default_transform) log = logging.getLogger(__name__) @@ -122,7 +121,7 @@ def visualize_gaze( img_path=None, screen_size=(1920, 1080), heatmap=False, - raw_plot=False): + raw_plot=False) -> Figure: """Visualize Eye Data. Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default @@ -216,7 +215,7 @@ def visualize_gaze_inquiries( show=False, img_path=None, heatmap=False, - raw_plot=False): + raw_plot=False) -> Figure: """Visualize Eye Data. Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default @@ -335,29 +334,27 @@ def visualize_csv_eeg_triggers(trigger_col: Optional[int] = None): Figure of Triggers """ # Load in CSV - filename = choose_csv_file() - raw_data_list = load_raw_data(filename, [filename]) - for mode_data in raw_data_list: - raw_data = mode_data.by_channel() - - # Pull out the triggers - if not trigger_col: - triggers = raw_data[-1] - else: - triggers = raw_data[trigger_col] - - # Plot the triggers - plt.plot(triggers) - - # Add some titles and labels to the figure - plt.title('Trigger Signal') - plt.ylabel('Trigger Value') - plt.xlabel('Samples') - - log.info('Press Ctrl + C to exit!') - # Show us the figure! Depending on your OS / IDE this may not close when - # The window is closed, see the message above - plt.show() + data = load_raw_data(choose_csv_file()) + raw_data = data.by_channel() + + # Pull out the triggers + if not trigger_col: + triggers = raw_data[-1] + else: + triggers = raw_data[trigger_col] + + # Plot the triggers + plt.plot(triggers) + + # Add some titles and labels to the figure + plt.title('Trigger Signal') + plt.ylabel('Trigger Value') + plt.xlabel('Samples') + + log.info('Press Ctrl + C to exit!') + # Show us the figure! Depending on your OS / IDE this may not close when + # The window is closed, see the message above + plt.show() def visualize_joint_average( @@ -444,48 +441,46 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi trial_window = parameters.get("trial_window") static_offset = parameters.get("static_trigger_offset") - raw_data_list = load_raw_data(session_path, [f'{RAW_DATA_FILENAME}.csv']) - - for mode_data in raw_data_list: - channels = mode_data.channels - sample_rate = mode_data.sample_rate - - transform_params = parameters.instantiate(ERPTransformParams) - - devices.load(Path(session_path, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(mode_data.daq_type) - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=transform_params.notch_filter_frequency, - bandpass_low=transform_params.filter_low, - bandpass_high=transform_params.filter_high, - bandpass_order=transform_params.filter_order, - downsample_factor=transform_params.down_sampling_rate, - ) - # Process triggers.txt files - trigger_targetness, trigger_timing, _ = trigger_decoder( - offset=static_offset, - trigger_path=f"{session_path}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - ) - assert "nontarget" in trigger_targetness, "No nontarget triggers found." - assert "target" in trigger_targetness, "No target triggers found." - assert len(trigger_targetness) == len(trigger_timing), "Trigger targetness and timing must be the same length." - - labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] - channel_map = analysis_channels(channels, device_spec) - - erp = visualize_erp( - mode_data, - channel_map, - trigger_timing, - labels, - trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=session_path, - show=show, - ) + raw_data = load_raw_data(Path(session_path, f'{RAW_DATA_FILENAME}.csv')) + channels = raw_data.channels + sample_rate = raw_data.sample_rate + + transform_params = parameters.instantiate(ERPTransformParams) + + devices.load(Path(session_path, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(raw_data.daq_type) + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) + # Process triggers.txt files + trigger_targetness, trigger_timing, _ = trigger_decoder( + offset=static_offset, + trigger_path=f"{session_path}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + assert "nontarget" in trigger_targetness, "No nontarget triggers found." + assert "target" in trigger_targetness, "No target triggers found." + assert len(trigger_targetness) == len(trigger_timing), "Trigger targetness and timing must be the same length." + + labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] + channel_map = analysis_channels(channels, device_spec) + + return visualize_erp( + raw_data, + channel_map, + trigger_timing, + labels, + trial_window, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + save_path=session_path, + show=show, + ) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 08aca7b27..167c073b7 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -144,16 +144,14 @@ def offline_analysis( if path.exists() ] - # raw_data: [RawData(EyeTracker, RawData(EEG)] - raw_data = load_raw_data(data_folder, data_file_paths) - - for mode_data in raw_data: - device_spec = devices_by_name.get(mode_data.daq_type) + for raw_data_path in data_file_paths: + raw_data = load_raw_data(raw_data_path) + device_spec = devices_by_name.get(raw_data.daq_type) # extract relevant information from raw data object eeg if device_spec.content_type == "EEG": - channels = mode_data.channels - type_amp = mode_data.daq_type - sample_rate = mode_data.sample_rate + channels = raw_data.channels + type_amp = raw_data.daq_type + sample_rate = raw_data.sample_rate # setup filtering default_transform = get_default_transform( @@ -188,7 +186,7 @@ def offline_analysis( channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] log.info(f'Channels used in analysis: {channels_used}') - data, fs = mode_data.by_channel() + data, fs = raw_data.by_channel() inquiries, inquiry_labels, inquiry_timing = model.reshaper( trial_targetness_label=trigger_targetness, @@ -234,7 +232,7 @@ def offline_analysis( # this should have uncorrected trigger timing for display purposes figure_handles = visualize_erp( - mode_data, + raw_data, channel_map, trigger_timing, labels, @@ -248,15 +246,15 @@ def offline_analysis( if device_spec.content_type == "Eyetracker": figure_handles = visualize_gaze( - mode_data, + raw_data, save_path=data_folder if save_figures else None, show=True, raw_plot=True, ) - channels = mode_data.channels - type_amp = mode_data.daq_type - sample_rate = mode_data.sample_rate + channels = raw_data.channels + type_amp = raw_data.daq_type + sample_rate = raw_data.sample_rate log.info(f"Channels read from csv: {channels}") log.info(f"Device type: {type_amp}, fs={sample_rate}") @@ -265,7 +263,7 @@ def offline_analysis( channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] log.info(f'Channels used in analysis: {channels_used}') - data, fs = mode_data.by_channel() + data, fs = raw_data.by_channel() model = GazeModel() @@ -334,7 +332,6 @@ def offline_analysis( raw_plot=True, ) - if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") return model, figure_handles From 5c3b38ab86882ce90efeab4de02201642887db5d Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 20 Oct 2023 17:53:30 -0700 Subject: [PATCH 119/330] Added code to save the eyetracker model --- bcipy/signal/model/offline_analysis.py | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 167c073b7..114617e12 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -248,7 +248,7 @@ def offline_analysis( figure_handles = visualize_gaze( raw_data, save_path=data_folder if save_figures else None, - show=True, + show=show_figures, raw_plot=True, ) @@ -328,10 +328,17 @@ def offline_analysis( left_eye, right_eye, means, covs, save_path=None, - show=True, + show=show_figures, raw_plot=True, ) + model.metadata = SignalModelMetadata(device_spec=device_spec, + transform=None) + log.info("Training complete for Eyetracker model. Saving data...") + save_model( + model, + Path(data_folder, f"model_{device_spec.content_type}.pkl")) + if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") return model, figure_handles From bcd3a2c153e6e72fa3c3627424049cd1867f2a17 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 22 Oct 2023 21:35:42 -0400 Subject: [PATCH 120/330] integrated evidence fuser to calculate likelihoods --- bcipy/simulator/helpers/decision.py | 2 +- bcipy/simulator/helpers/evidence_fuser.py | 45 +++++++++++++++++++++++ bcipy/simulator/helpers/sim_state.py | 41 ++++++++++++++------- bcipy/simulator/helpers/types.py | 5 ++- bcipy/simulator/sim_sampler.py | 7 +++- 5 files changed, 82 insertions(+), 18 deletions(-) create mode 100644 bcipy/simulator/helpers/evidence_fuser.py diff --git a/bcipy/simulator/helpers/decision.py b/bcipy/simulator/helpers/decision.py index dd8998e26..7b52b5340 100644 --- a/bcipy/simulator/helpers/decision.py +++ b/bcipy/simulator/helpers/decision.py @@ -106,7 +106,7 @@ def __init__(self, threshold: float): self.tau = threshold def decide(self, series: List[InquiryResult]): - current_distribution = series[-1].evidence_likelihoods + current_distribution = series[-1].fused_likelihood if np.max(current_distribution) > self.tau: log.info("Committing to decision: posterior exceeded threshold.") return True diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py new file mode 100644 index 000000000..d6c85862a --- /dev/null +++ b/bcipy/simulator/helpers/evidence_fuser.py @@ -0,0 +1,45 @@ +from abc import abstractmethod, ABC +from typing import Optional, Dict + +import numpy as np + + +class EvidenceFuser(ABC): + + @abstractmethod + def fuse(self, prior_likelihood: Optional[np.ndarray], evidence: Dict) -> np.ndarray: + ... + + +class MultipyFuser(EvidenceFuser): + + def __init__(self): + pass + + def fuse(self, prior_likelihood, evidence) -> np.ndarray: + + len_dist = len(list(evidence.values())[0]) + prior_likelihood = prior_likelihood if prior_likelihood is not None else self.__make_prior(len_dist) + ret_likelihood = prior_likelihood.copy() + + for value in evidence.values(): + ret_likelihood *= value[:] + ret_likelihood = self.__clean_likelihood(ret_likelihood) + + return ret_likelihood + + def __make_prior(self, len_dist): + return np.ones(len_dist) / len_dist + + def __clean_likelihood(self, likelihood): + + cleaned_likelihood = likelihood.copy() + if np.isinf(np.sum(likelihood)): + tmp = np.zeros(len(likelihood)) + tmp[np.where(likelihood == np.inf)[0][0]] = 1 + cleaned_likelihood = tmp + + if not np.isnan(np.sum(likelihood)): + cleaned_likelihood = likelihood / np.sum(likelihood) + + return cleaned_likelihood diff --git a/bcipy/simulator/helpers/sim_state.py b/bcipy/simulator/helpers/sim_state.py index 379b1bc49..2a252a216 100644 --- a/bcipy/simulator/helpers/sim_state.py +++ b/bcipy/simulator/helpers/sim_state.py @@ -1,7 +1,7 @@ import copy -from abc import ABC +from abc import ABC, abstractmethod from dataclasses import dataclass -from typing import List, Optional +from typing import List, Optional, Dict import numpy as np @@ -9,8 +9,10 @@ from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.decision import SimDecisionCriteria, MaxIterationsSim, ProbThresholdSim +from bcipy.simulator.helpers.evidence_fuser import MultipyFuser, EvidenceFuser from bcipy.simulator.helpers.types import InquiryResult from bcipy.task.control.criteria import DecisionCriteria, MaxIterationsCriteria, ProbThresholdCriteria +from bcipy.task.control.handler import EvidenceFusion @dataclass @@ -23,7 +25,7 @@ class SimState: inquiry_n: int series_n: int series_results: List[List[InquiryResult]] - + # TODO store the fused results decision_criterion: List[SimDecisionCriteria] def total_inquiry_count(self): @@ -36,7 +38,7 @@ def total_inquiry_count(self): class StateManager(ABC): - def update(self, evidence: np.ndarray): + def update(self, evidence: np.ndarray): # TODO change evidence type to dictionary or some dataclass raise NotImplementedError() def is_done(self) -> bool: @@ -51,32 +53,40 @@ def mutate_state(self, state_field, state_value): class StateManagerImpl(StateManager): - def __init__(self, parameters: Parameters): + def __init__(self, parameters: Parameters, fuser_class=MultipyFuser): self.state: SimState = self.initial_state() self.parameters = parameters + self.fuser_class: EvidenceFuser.__class__ = fuser_class - self.stop_inq = 50 # TODO pull from parameters + self.max_inq_len = self.parameters.get('max_inq_len', 50) + # TODO add stoppage criterion, Stoppage criterion is seperate from decision. Decision should we go on to next letter or not def is_done(self) -> bool: - return self.state.total_inquiry_count() > self.stop_inq or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 + return self.state.total_inquiry_count() > self.max_inq_len or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 - def update(self, evidence: np.ndarray) -> InquiryResult: + def update(self, evidence) -> InquiryResult: + + fuser = self.fuser_class() + current_series: List[InquiryResult] = self.state.series_results[self.state.series_n] + prior_likelihood: Optional[np.ndarray] = current_series.pop().fused_likelihood if current_series else None # most recent likelihood + evidence_dict = {"SM": evidence} # TODO create wrapper object for Evidences + fused_likelihood = fuser.fuse(prior_likelihood, evidence_dict) - temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - evidence_likelihoods=list(evidence), decision=None) # finding out whether max iterations is hit or prob threshold is hit + temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, + evidence_likelihoods=list(evidence), fused_likelihood=fused_likelihood, # TODO change to use evidence_dict + decision=None) + temp_series = copy.deepcopy(self.get_state().series_results) temp_series[-1].append(temp_inquiry_result) is_decidable = any([decider.decide(temp_series[-1]) for decider in self.state.decision_criterion]) decision = None - # TODO what to do when max inquiry count is reached? new_state = self.get_state().__dict__ if is_decidable: decision = alphabet()[np.argmax(evidence)] # deciding the maximum probability symbol TODO abstract - if decision == self.state.target_symbol: # correct decision new_state['series_n'] += 1 # TODO abstract out into reset function new_state['series_results'].append([]) @@ -99,7 +109,7 @@ def update(self, evidence: np.ndarray) -> InquiryResult: new_state['inquiry_n'] += 1 new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - evidence_likelihoods=list(evidence), decision=decision) + evidence_likelihoods=list(evidence), decision=decision, fused_likelihood=fused_likelihood) new_state['series_results'][self.state.series_n].append(new_inquiry_result) @@ -122,8 +132,11 @@ def mutate_state(self, state_field, state_value) -> SimState: @staticmethod def initial_state(parameters: Parameters = None) -> SimState: sentence = "HELLO_WORLD" # TODO abstract out with sim_parameters.json - target_symbol = sentence[0] + target_symbol = sentence[0] # TODO use parameters.get('spelled_letters_count') default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] + evidence_types = parameters.get( + 'evidence_types') if parameters else None # TODO make new parameter and create default series_likelihoods object based off that + return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, display_alphabet=[], inquiry_n=0, series_n=0, series_results=[[]], decision_criterion=default_criterion) diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py index c965867a9..6769d71bb 100644 --- a/bcipy/simulator/helpers/types.py +++ b/bcipy/simulator/helpers/types.py @@ -1,11 +1,14 @@ from dataclasses import dataclass from typing import Optional, List +import numpy as np + @dataclass class InquiryResult: target: Optional[str] time_spent: int # TODO what does time_spent mean? stimuli: List - evidence_likelihoods: List + evidence_likelihoods: List # TODO make this into a dictionary to support multimodal. e.g {SignalModel: evidence_list, LanguageModel:evidence_list} + fused_likelihood: np.ndarray decision: Optional[str] diff --git a/bcipy/simulator/sim_sampler.py b/bcipy/simulator/sim_sampler.py index 57d4c6b68..0ac5d0235 100644 --- a/bcipy/simulator/sim_sampler.py +++ b/bcipy/simulator/sim_sampler.py @@ -55,15 +55,18 @@ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler def run(self): while not self.state_manager.is_done(): - print(f"Series {self.state_manager.get_state().series_n} | Inquiry {self.state_manager.get_state().inquiry_n}") + print(f"Series {self.state_manager.get_state().series_n} | Inquiry {self.state_manager.get_state().inquiry_n} | Target {self.state_manager.get_state().target_symbol}") self.state_manager.mutate_state('display_alphabet', self.__get_inquiry_alp_subset(self.state_manager.get_state())) sampled_data = self.sampler.sample(self.state_manager.get_state()) - evidence = self.model_handler.generate_evidence(self.state_manager.get_state(), sampled_data) + evidence = self.model_handler.generate_evidence(self.state_manager.get_state(), + sampled_data) # TODO make this evidence be a dict (mapping of evidence type to evidence) print(f"Evidence for stimuli {self.state_manager.get_state().display_alphabet} \n {evidence}") inq_record: InquiryResult = self.state_manager.update(evidence) + print(f"Fused Likelihoods {[str(round(p, 3)) for p in inq_record.fused_likelihood]}") + if inq_record.decision: print(f"Decided {inq_record.decision} for target {inq_record.target} for sentence {self.state_manager.get_state().target_sentence}") From bec1bb56d4db920f057f792ef0160934335e0aa2 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 23 Oct 2023 05:56:44 -0400 Subject: [PATCH 121/330] Offline analysis PR comments addressed. Visualization doc updated --- bcipy/helpers/visualization.py | 84 +++-- bcipy/signal/model/offline_analysis.py | 458 +++++++++++++------------ 2 files changed, 295 insertions(+), 247 deletions(-) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 04d4ef4b8..1d07f7d85 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -113,27 +113,36 @@ def visualize_erp( def visualize_gaze( - data, - left_keys=['left_x', 'left_y'], - right_keys=['right_x', 'right_y'], - save_path=None, - show=False, - img_path=None, - screen_size=(1920, 1080), - heatmap=False, - raw_plot=False) -> Figure: + data: RawData, + left_keys: List[str] = ['left_x', 'left_y'], + right_keys: List[str] = ['right_x', 'right_y'], + save_path: Optional[str] = None, + show: Optional[bool] = False, + img_path: Optional[str] = None, + screen_size: Tuple[int, int] = (1920, 1080), + heatmap: Optional[bool] = False, + raw_plot: Optional[bool] = False) -> Figure: """Visualize Eye Data. Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default - image used is for the matrix calibration task on a 1920x1080 screen. + image used is for the matrix calibration task on a 1920x1080 screen. + + Generates a comparative matrix figure following the execution of tasks. Given a set of + trailed data, the gaze distribution are plotted and may be saved or shown in a window. + + Returns a list of the figure handles created. Parameters ---------- - data: RawData - save_path: Optional[str] - show: Optional[bool] - img_path: Optional[str] - screen_size: Optional[Tuple[int, int]] TODO + data: RawData: Gaze RawData + left_keys: Optional[List[str]]: List of channels for the left eye data. Default: ['left_x', 'left_y'] + right_keys: Optional[List[str]]: List of channels for the right eye data. Default: ['right_x', 'right_y'] + save_path: Optional[str]: optional path to a save location of the figure generated + show: Optional[bool]: whether or not to show the figures generated. Default: False + img_path: Optional[str]: Image to be used as the background. Default: matrix.png + screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy Phrase tasks. Default: (1920, 1080) + heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False + raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False """ title = f'{data.daq_type} ' @@ -207,27 +216,40 @@ def visualize_gaze( def visualize_gaze_inquiries( - left_eye, - right_eye, - means=None, - covs=None, - save_path=None, - show=False, - img_path=None, - heatmap=False, - raw_plot=False) -> Figure: - """Visualize Eye Data. + left_eye: np.ndarray, + right_eye: np.ndarray, + means: Optional[np.ndarray] = None, + covs: Optional[np.ndarray] = None, + save_path: Optional[str] = None, + show: Optional[bool] = False, + img_path: Optional[str] = None, + screen_size: Tuple[int, int] = (1920, 1080), + heatmap: Optional[bool] = False, + raw_plot: Optional[bool] = False) -> Figure: + """Visualize Gaze Inquiries. Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default - image used is for the matrix calibration task on a 1920x1080 screen. + image used is for the matrix calibration task on a 1920x1080 screen. + + Generates a comparative matrix figure following the execution of offline analysis. Given a set of + trailed data (left & right eye), the gaze distribution for each prompted symbol are plotted, along + with the contour plots of mean and covariances calculated by the Gaussian Mixture Model. + The figures may be saved or shown in a window. + + Returns a list of the figure handles created. Parameters ---------- - left eye, right eye: (np.ndarray): Raw gaze data, plotting both eyes is optional - means, covs: Optional(np.ndarray): Means and covariances of the Gaussian Mixture Model - save_path: Optional[str] - show: Optional[bool] - img_path: Optional[str] + left_eye: (np.ndarray): Data array for the left eye data. + right_eye: (np.ndarray): Data array for the right eye data. + means: Optional[np.ndarray]: Means of the Gaussian Mixture Model + covs: Optional[np.ndarray]: Covariances of the Gaussian Mixture Model + save_path: Optional[str]: optional path to a save location of the figure generated + show: Optional[bool]: whether or not to show the figures generated. Default: False + img_path: Optional[str]: Image to be used as the background. Default: matrix.png + screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy Phrase tasks. Default: (1920, 1080) + heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False + raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False """ title = 'Raw Gaze Inquiries ' diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 114617e12..b2a4206e6 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -65,6 +65,242 @@ def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_s return train_data, test_data, train_labels, test_labels +def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balanced_acc, + save_figures=True, show_figures=False): + """Analyze ERP data and return/save the ERP model. + Extract relevant information from raw data object. + Extract timing information from trigger file. + Apply filtering and preprocessing on the raw data. + Reshape and label the data for the training procedure. + Fit the model to the data. Use cross validation to select parameters. + Pickle dump model into .pkl file + Generate and [optional] save/show ERP figures. + """ + # Extract relevant session information from parameters file + trial_window = parameters.get("trial_window") + # This parameter does not exist in parameters files for Multimodal datasets. Adding manually. + # TODO: Update parameters files for multimodal datasets. + if trial_window is None: + trial_window = [0.0, 0.5] + window_length = trial_window[1] - trial_window[0] + + prestim_length = parameters.get("prestim_length") + trials_per_inquiry = parameters.get("stim_length") + # The task buffer length defines the min time between two inquiries + # We use half of that time here to buffer during transforms + buffer = int(parameters.get("task_buffer_length") / 2) + + # Get signal filtering information + transform_params = parameters.instantiate(ERPTransformParams) + downsample_rate = transform_params.down_sampling_rate + static_offset = parameters.get("static_trigger_offset") + + log.info( + f"\nData processing settings: \n" + f"{str(transform_params)} \n" + f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " + f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer}s \n" + f"Static offset: {static_offset}" + ) + channels = erp_data.channels + type_amp = erp_data.daq_type + sample_rate = erp_data.sample_rate + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) + + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + + k_folds = parameters.get("k_folds") + model = PcaRdaKdeModel(k_folds=k_folds) + + # Process triggers.txt files + trigger_targetness, trigger_timing, _ = trigger_decoder( + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + offset=static_offset, + device_type='EEG' + ) + + # update the trigger timing list to account for the initial trial window + corrected_trigger_timing = [timing + trial_window[0] for timing in trigger_timing] + + # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module + # The timestamp column [0] is already excluded. + channel_map = analysis_channels(channels, device_spec) + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + log.info(f'Channels used in analysis: {channels_used}') + + data, fs = erp_data.by_channel() + + inquiries, inquiry_labels, inquiry_timing = model.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=corrected_trigger_timing, + eeg_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=window_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) + + inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) + inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) + trial_duration_samples = int(window_length * fs) + data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) + + # define the training classes using integers, where 0=nontargets/1=targets + labels = inquiry_labels.flatten() + + # train and save the model as a pkl file + log.info("Training model. This will take some time...") + model = PcaRdaKdeModel(k_folds=k_folds) + model.fit(data, labels) + model.metadata = SignalModelMetadata(device_spec=device_spec, + transform=default_transform) + log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") + + save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) + preferences.signal_model_directory = data_folder + + # Using an 80/20 split, report on balanced accuracy + if estimate_balanced_acc: + train_data, test_data, train_labels, test_labels = subset_data(data, labels, test_size=0.2) + dummy_model = PcaRdaKdeModel(k_folds=k_folds) + dummy_model.fit(train_data, train_labels) + probs = dummy_model.predict_proba(test_data) + preds = probs.argmax(-1) + score = balanced_accuracy_score(test_labels, preds) + log.info(f"Balanced acc with 80/20 split: {score}") + del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds + + # this should have uncorrected trigger timing for display purposes + figure_handles = visualize_erp( + erp_data, + channel_map, + trigger_timing, + labels, + trial_window, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + save_path=data_folder if save_figures else None, + show=show_figures + ) + + +def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_figures=False): + """Analyze gaze data and return/save the gaze model. + Extract relevant information from gaze data object. + Extract timing information from trigger file. + Apply preprocessing on the raw data. Extract the data for each target label and each eye separately. + Extract inquiries dictionary with keys as target symbols and values as inquiry windows. + Fit the model to the data. + Pickle dump model into .pkl file + Generate and [optional] save/show gaze figures. + """ + figure_handles = visualize_gaze( + gaze_data, + save_path=data_folder if save_figures else None, + show=show_figures, + raw_plot=True, + ) + + channels = gaze_data.channels + type_amp = gaze_data.daq_type + sample_rate = gaze_data.sample_rate + + log.info(f"Channels read from csv: {channels}") + log.info(f"Device type: {type_amp}, fs={sample_rate}") + channel_map = analysis_channels(channels, device_spec) + + channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] + log.info(f'Channels used in analysis: {channels_used}') + + data, fs = gaze_data.by_channel() + + model = GazeModel() + + # Extract all Triggers info + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + remove_pre_fixation=False, + exclusion=[ + TriggerType.PREVIEW, + TriggerType.EVENT, + TriggerType.FIXATION, + TriggerType.SYSTEM, + TriggerType.OFFSET], + device_type='EYETRACKER', + apply_starting_offset=False + ) + ''' Trigger_timing includes PROMPT and excludes FIXATION ''' + + target_symbols = trigger_symbols[0::11] # target symbols are the PROMPT triggers + # Use trigger_timing to generate time windows for each letter flashing + # Take every 10th trigger as the start point of timing. + inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) + + # Extract the inquiries dictionary with keys as target symbols and values as inquiry windows: + inquiries = model.reshaper( + inq_start_times=inq_start, + target_symbols=target_symbols, + gaze_data=data, + sample_rate=sample_rate + ) + + symbol_set = alphabet() + + # Extract the data for each target label and each eye separately. + # Apply preprocessing: + preprocessed_data = {i: [] for i in symbol_set} + for i in symbol_set: + # Skip if there's no evidence for this symbol: + if len(inquiries[i]) == 0: + continue + + left_eye, right_eye = extract_eye_info(inquiries[i]) + preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) + + # Train test split: + test_size = int(len(right_eye) * 0.2) + train_size = len(right_eye) - test_size + train_right_eye = right_eye[:train_size] + test_right_eye = right_eye[train_size:] + + train_left_eye = left_eye[:train_size] + test_left_eye = left_eye[train_size:] + + # Fit the model: + model.fit(train_right_eye) + + scores, means, covs = model.get_scores(test_right_eye) + + # Visualize the results: + figure_handles = visualize_gaze_inquiries( + left_eye, right_eye, + means, covs, + save_path=None, + show=show_figures, + raw_plot=True, + ) + model.metadata = SignalModelMetadata(device_spec=device_spec, + transform=None) + log.info("Training complete for Eyetracker model. Saving data...") + save_model( + model, + Path(data_folder, f"model_{device_spec.content_type}.pkl")) + + @report_execution_time def offline_analysis( data_folder: str = None, @@ -109,33 +345,6 @@ def offline_analysis( if not data_folder: data_folder = load_experimental_data() - # extract relevant session information from parameters file - trial_window = parameters.get("trial_window") - window_length = trial_window[1] - trial_window[0] - - prestim_length = parameters.get("prestim_length") - trials_per_inquiry = parameters.get("stim_length") - # The task buffer length defines the min time between two inquiries - # We use half of that time here to buffer during transforms - buffer = int(parameters.get("task_buffer_length") / 2) - - # get signal filtering information - transform_params = parameters.instantiate(ERPTransformParams) - downsample_rate = transform_params.down_sampling_rate - static_offset = parameters.get("static_trigger_offset") - if trial_window is None: - trial_window = [0.0, 0.5] - # NOTE: Had to add it manually for offline analysis of multimodal datasets, - # since the trial_window information was not available in the parameters file. - - log.info( - f"\nData processing settings: \n" - f"{str(transform_params)} \n" - f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " - f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer}s \n" - f"Static offset: {static_offset}" - ) - devices_by_name = devices.load( Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME), replace=True) data_file_paths = [ @@ -149,199 +358,16 @@ def offline_analysis( device_spec = devices_by_name.get(raw_data.daq_type) # extract relevant information from raw data object eeg if device_spec.content_type == "EEG": - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=transform_params.notch_filter_frequency, - bandpass_low=transform_params.filter_low, - bandpass_high=transform_params.filter_high, - bandpass_order=transform_params.filter_order, - downsample_factor=transform_params.down_sampling_rate, - ) - - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") - - k_folds = parameters.get("k_folds") - model = PcaRdaKdeModel(k_folds=k_folds) - - # Process triggers.txt files - trigger_targetness, trigger_timing, _ = trigger_decoder( - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - offset=static_offset, - device_type='EEG' - ) - - # update the trigger timing list to account for the initial trial window - corrected_trigger_timing = [timing + trial_window[0] for timing in trigger_timing] - - # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module - # The timestamp column [0] is already excluded. - channel_map = analysis_channels(channels, device_spec) - channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] - log.info(f'Channels used in analysis: {channels_used}') - - data, fs = raw_data.by_channel() - - inquiries, inquiry_labels, inquiry_timing = model.reshaper( - trial_targetness_label=trigger_targetness, - timing_info=corrected_trigger_timing, - eeg_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=window_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer, - ) - - inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) - inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) - trial_duration_samples = int(window_length * fs) - data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) - - # define the training classes using integers, where 0=nontargets/1=targets - labels = inquiry_labels.flatten() - - # train and save the model as a pkl file - log.info("Training model. This will take some time...") - model = PcaRdaKdeModel(k_folds=k_folds) - model.fit(data, labels) - model.metadata = SignalModelMetadata(device_spec=device_spec, - transform=default_transform) - log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") - - save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) - preferences.signal_model_directory = data_folder - - # Using an 80/20 split, report on balanced accuracy - if estimate_balanced_acc: - train_data, test_data, train_labels, test_labels = subset_data(data, labels, test_size=0.2) - dummy_model = PcaRdaKdeModel(k_folds=k_folds) - dummy_model.fit(train_data, train_labels) - probs = dummy_model.predict_proba(test_data) - preds = probs.argmax(-1) - score = balanced_accuracy_score(test_labels, preds) - log.info(f"Balanced acc with 80/20 split: {score}") - del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds - - # this should have uncorrected trigger timing for display purposes - figure_handles = visualize_erp( - raw_data, - channel_map, - trigger_timing, - labels, - trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=data_folder if save_figures else None, - show=show_figures - ) + analyze_erp(raw_data, parameters, device_spec, data_folder, estimate_balanced_acc, + save_figures, show_figures) if device_spec.content_type == "Eyetracker": - figure_handles = visualize_gaze( - raw_data, - save_path=data_folder if save_figures else None, - show=show_figures, - raw_plot=True, - ) - - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") - channel_map = analysis_channels(channels, device_spec) - - channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] - log.info(f'Channels used in analysis: {channels_used}') - - data, fs = raw_data.by_channel() - - model = GazeModel() - - # Extract all Triggers info - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - remove_pre_fixation=False, - exclusion=[ - TriggerType.PREVIEW, - TriggerType.EVENT, - TriggerType.FIXATION, - TriggerType.SYSTEM, - TriggerType.OFFSET], - device_type='EYETRACKER', - apply_starting_offset=False - ) - ''' Trigger_timing includes PROMPT and excludes FIXATION ''' - - # Use trigger_timing to generate time windows for each letter flashing - # Take every 10th trigger as the start point of timing. - # trigger_symbols keeps the PROMPT info, use it to find the target symbol. - target_symbols = trigger_symbols[0::11] # target symbols - inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) - - # Extract the inquiries dictionary with keys as target symbols and values as inquiry windows: - inquiries = model.reshaper( - inq_start_times=inq_start, - target_symbols=target_symbols, - gaze_data=data, - sample_rate=sample_rate - ) - - symbol_set = alphabet() - - # Extract the data for each target label and each eye separately. - # Apply preprocessing: - preprocessed_data = {i: [] for i in symbol_set} - for i in symbol_set: - # Skip if there's no evidence for this symbol: - if len(inquiries[i]) == 0: - continue - - left_eye, right_eye = extract_eye_info(inquiries[i]) - preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) - - # Train test split: - test_size = int(len(right_eye) * 0.2) - train_size = len(right_eye) - test_size - train_right_eye = right_eye[:train_size] - test_right_eye = right_eye[train_size:] - - train_left_eye = left_eye[:train_size] - test_left_eye = left_eye[train_size:] - - # Fit the model: - model.fit(train_right_eye) - - scores, means, covs = model.get_scores(test_right_eye) - - # Visualize the results: - figure_handles = visualize_gaze_inquiries( - left_eye, right_eye, - means, covs, - save_path=None, - show=show_figures, - raw_plot=True, - ) - - model.metadata = SignalModelMetadata(device_spec=device_spec, - transform=None) - log.info("Training complete for Eyetracker model. Saving data...") - save_model( - model, - Path(data_folder, f"model_{device_spec.content_type}.pkl")) + analyze_gaze(raw_data, device_spec, data_folder, save_figures, show_figures) if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") - return model, figure_handles + # return model, figure_handles + return if __name__ == "__main__": @@ -357,7 +383,7 @@ def offline_analysis( parser.set_defaults(alert=False) parser.set_defaults(balanced=False) parser.set_defaults(save_figures=False) - parser.set_defaults(show_figures=False) + parser.set_defaults(show_figures=True) args = parser.parse_args() log.info(f"Loading params from {args.parameters_file}") From 6de317002d0e769e5c2ca07201d6210fc22ec73d Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Oct 2023 10:56:56 -0700 Subject: [PATCH 122/330] Fix linting errors --- bcipy/helpers/visualization.py | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 1d07f7d85..90ea94229 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -127,7 +127,7 @@ def visualize_gaze( Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default image used is for the matrix calibration task on a 1920x1080 screen. - Generates a comparative matrix figure following the execution of tasks. Given a set of + Generates a comparative matrix figure following the execution of tasks. Given a set of trailed data, the gaze distribution are plotted and may be saved or shown in a window. Returns a list of the figure handles created. @@ -140,7 +140,8 @@ def visualize_gaze( save_path: Optional[str]: optional path to a save location of the figure generated show: Optional[bool]: whether or not to show the figures generated. Default: False img_path: Optional[str]: Image to be used as the background. Default: matrix.png - screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy Phrase tasks. Default: (1920, 1080) + screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy + Phrase tasks. Default: (1920, 1080) heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False """ @@ -231,9 +232,9 @@ def visualize_gaze_inquiries( Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default image used is for the matrix calibration task on a 1920x1080 screen. - Generates a comparative matrix figure following the execution of offline analysis. Given a set of - trailed data (left & right eye), the gaze distribution for each prompted symbol are plotted, along - with the contour plots of mean and covariances calculated by the Gaussian Mixture Model. + Generates a comparative matrix figure following the execution of offline analysis. Given a set of + trailed data (left & right eye), the gaze distribution for each prompted symbol are plotted, along + with the contour plots of mean and covariances calculated by the Gaussian Mixture Model. The figures may be saved or shown in a window. Returns a list of the figure handles created. @@ -247,7 +248,8 @@ def visualize_gaze_inquiries( save_path: Optional[str]: optional path to a save location of the figure generated show: Optional[bool]: whether or not to show the figures generated. Default: False img_path: Optional[str]: Image to be used as the background. Default: matrix.png - screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy Phrase tasks. Default: (1920, 1080) + screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy + Phrase tasks. Default: (1920, 1080) heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False """ From b4af622669ba12b202832bc6b2c937e8fc3de055 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 23 Oct 2023 15:43:27 -0400 Subject: [PATCH 123/330] Second gaze model added, multimodal_v2 changes are merged into multimodal --- bcipy/helpers/stimuli.py | 57 +++------ bcipy/helpers/visualization.py | 90 +++++++++++++- bcipy/signal/model/fusion_model.py | 80 ++++++++++++- bcipy/signal/model/offline_analysis.py | 157 +++++++++++++++++++------ symbol_positions.json | 114 ++++++++++++++++++ 5 files changed, 417 insertions(+), 81 deletions(-) create mode 100644 symbol_positions.json diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 118d2806c..51675bb11 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -321,48 +321,21 @@ def __call__(self, # return np.stack(reshaped_data, 0), labels return data_by_targets - # @staticmethod - # def extract_eye_info(data): - # """ Rearrange the dimensions of gaze inquiry data and reshape it to num_channels x num_samples - # Extract Left and Right Eye info from data. Remove all blinks, do necessary preprocessing. - - # Args: - # data (np.ndarray): Data in shape of num_channels x num_samples - - # Returns: - # left_eye (np.ndarray), left_pupil (List(float)) - # right_eye (np.ndarray), right_pupil (List(float)) - # """ - - # # Extract samples from channels - # lx = data[2, :] - # ly = data[3, :] - # left_pupil = data[4, :] # Use if needed - - # rx = data[5, :] - # ry = data[6, :] - # right_pupil = data[7, :] - - # left_eye = np.vstack((np.array(lx), np.array(ly))).T - # right_eye = np.vstack((np.array(rx), np.array(ry))).T - - # # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. - # # Make sure that the number of samples are the same for both eyes - # left_eye_nan_idx = np.isnan(left_eye).any(axis=1) - # left_eye = left_eye[~left_eye_nan_idx] - # right_eye = right_eye[~left_eye_nan_idx] - - # right_eye_nan_idx = np.isnan(right_eye).any(axis=1) - # left_eye = left_eye[~right_eye_nan_idx] - # right_eye = right_eye[~right_eye_nan_idx] - - # try: - # len(left_eye) != len(right_eye) - # except AssertionError: - # raise SignalException( - # 'Number of samples for left and right eye are not the same.') - - # return left_eye, right_eye + @staticmethod + def centralize_all_data(data, symbol_pos): + """ Using the symbol locations in matrix, centralize all data (in Tobii units). + This data will only be used in certain model types. + Args: + data (np.ndarray): Data in shape of num_channels x num_samples + symbol_pos (np.ndarray(float)): Array of the current symbol posiiton in Tobii units + Returns: + data (np.ndarray): Centralized data in shape of num_channels x num_samples + """ + for i in range(len(data)): + data[i] = data[i] - symbol_pos + # TODO: List comprehension + + return data class TrialReshaper(Reshaper): diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 90ea94229..cf6bceb12 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -141,7 +141,8 @@ def visualize_gaze( show: Optional[bool]: whether or not to show the figures generated. Default: False img_path: Optional[str]: Image to be used as the background. Default: matrix.png screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy - Phrase tasks. Default: (1920, 1080) + Phrase tasks. + Default: (1920, 1080) heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False """ @@ -249,7 +250,8 @@ def visualize_gaze_inquiries( show: Optional[bool]: whether or not to show the figures generated. Default: False img_path: Optional[str]: Image to be used as the background. Default: matrix.png screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy - Phrase tasks. Default: (1920, 1080) + Phrase tasks. + Default: (1920, 1080) heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False """ @@ -328,6 +330,90 @@ def visualize_gaze_inquiries( return fig +def visualize_centralized_data( + left_eye: np.ndarray, + right_eye: np.ndarray, + save_path: Optional[str] = None, + show: Optional[bool] = False, + img_path: Optional[str] = None, + screen_size: Tuple[int, int] = (1920, 1080), + heatmap: Optional[bool] = False, + raw_plot: Optional[bool] = False) -> Figure: + """Visualize centralized data for each symbol. + + Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default + image used is for the matrix calibration task on a 1920x1080 screen. + + Generates a comparative matrix figure following the execution of offline analysis. Given a set of + trailed data (left & right eye), the gaze distribution for ALL prompted symbols are plotted after + the data has been centralized (i.e., mid coordinates of each symbol is subtracted from corresponding + symbol data to populate all data around (0,0) on the screen). + The figures may be saved or shown in a window. + + Returns a list of the figure handles created. + + Parameters + ---------- + left_eye: (np.ndarray): Data array for the centralized left eye data. + right_eye: (np.ndarray): Data array for the centralized right eye data. + save_path: Optional[str]: optional path to a save location of the figure generated + show: Optional[bool]: whether or not to show the figures generated. Default: False + img_path: Optional[str]: Image to be used as the background. Default: matrix.png + screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy Phrase tasks. + Default: (1920, 1080) + heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False + raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False + """ + title = 'Centralized Data for All Symbols ' + + if img_path is None: + img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img = plt.imread(img_path) + + # scale the eye data to the image + fig, ax = plt.subplots() + + # Transform the eye data to fit the display. Clip values > 1 and < -1 + # The idea here is to have the center at (0,0) + lx = np.clip(left_eye[:, 0], -1, 1) + ly = np.clip(left_eye[:, 1], -1, 1) + rx = np.clip(right_eye[:, 0], -1, 1) + ry = np.clip(right_eye[:, 1], -1, 1) + ax.imshow(img, extent=[-1, 1, -1, 1]) + + if heatmap: + # create a dataframe making a column for each x, y pair for both eyes and a column for the eye (left or right) + df = pd.DataFrame({ + 'x': np.concatenate((lx, rx)), + 'y': np.concatenate((ly, ry)), + 'eye': ['left'] * len(lx) + ['right'] * len(rx) + }) + ax = sns.kdeplot( + data=df, + hue='eye', + x='x', + y='y', + fill=False, + thresh=0.05, + levels=10, + cmap="mako", + colorbar=True) + + if raw_plot: + ax.scatter(lx, ly, c='r', s=1) + ax.scatter(rx, ry, c='b', s=1) + + plt.title(f'{title}Plot') + + if save_path is not None: + plt.savefig(f"{save_path}/{title.lower().replace(' ', '_')}plot.png", dpi=fig.dpi) + + if show: + plt.show() + + return fig + + def plot_edf(edf_path: str, auto_scale: Optional[bool] = False): """Plot data from the raw edf file. Note: this works from an iPython session but seems to throw errors when provided in a script. diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py index 62f88fab4..cd4c03ce6 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/fusion_model.py @@ -1,12 +1,17 @@ +from pathlib import Path + import numpy as np +from bcipy.signal.model import SignalModel from sklearn.mixture import GaussianMixture from bcipy.helpers.stimuli import GazeReshaper +from sklearn.model_selection import cross_val_score # noqa +from sklearn.utils.estimator_checks import check_estimator # noqa -class GazeModel(): +class GazeModel(SignalModel): reshaper = GazeReshaper() - def __init__(self, num_components=3): + def __init__(self, num_components=2): self.num_components = num_components # number of gaussians to fit def fit(self, train_data: np.array): @@ -36,3 +41,74 @@ def predict(self, scores: np.array): # Get the argmax of the scores # return predictions + + def evaluate(self, test_data: np.ndarray, test_labels: np.ndarray): + ''' + Compute model performance characteristics on the provided test data and labels. + ''' + # Compute the AUC + + # return ModelEvaluationReport(auc) + + def save(self, path: Path): + """Save model state to the provided checkpoint""" + ... + + def load(self, path: Path): + """Load model state from the provided checkpoint""" + ... + + +class GazeModel_AllSymbols(SignalModel): + '''Gaze model that uses all symbols to fit a single Gaussian ''' + reshaper = GazeReshaper() + + def __init__(self, num_components=1): + self.num_components = num_components # number of gaussians to fit + + def fit(self, train_data: np.array): + model = GaussianMixture(n_components=1, random_state=0, init_params='kmeans') + model.fit(train_data) + self.model = model + + return self + + def get_scores(self, test_data: np.array, sym_pos: np.array): + ''' + Compute the log-likelihood of each sample. + Return the mean and covariance of each mixture component. + + test_data: gaze data for each symbol + sym_pos: mid positions for each symbol in Tobii coordinates + ''' + + scores = self.model.score_samples(test_data) + means = self.model.means_ + sym_pos + covs = self.model.covariances_ + + return scores, means, covs + + def predict(self, scores: np.array): + ''' + Predict the labels for the test data. + ''' + # Compute over log-likelihood scores + # Get the argmax of the scores + + # return predictions + + def evaluate(self, test_data: np.ndarray, test_labels: np.ndarray): + ''' + Compute model performance characteristics on the provided test data and labels. + ''' + # Compute the AUC + + # return ModelEvaluationReport(auc) + + def save(self, path: Path): + """Save model state to the provided checkpoint""" + ... + + def load(self, path: Path): + """Load model state from the provided checkpoint""" + ... diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index b2a4206e6..a27a54481 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -1,6 +1,7 @@ import logging from pathlib import Path from typing import Tuple +import json import numpy as np from matplotlib.figure import Figure @@ -8,7 +9,7 @@ from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices -from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, ROOT, DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH, STATIC_IMAGES_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename @@ -21,10 +22,10 @@ from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import (visualize_erp, visualize_gaze, - visualize_gaze_inquiries) + visualize_gaze_inquiries, visualize_centralized_data) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata -from bcipy.signal.model.fusion_model import GazeModel +from bcipy.signal.model.fusion_model import GazeModel, GazeModel_AllSymbols from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import (ERPTransformParams, extract_eye_info, filter_inquiries, get_default_transform) @@ -38,7 +39,7 @@ # TODO: Update images to contain the path to directory of the respective calibration session. -def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state=0): +def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state: int = 0, swap_axes: bool = True): """Performs a train/test split on the provided data and labels, accounting for the current shape convention (channel dimension in front, instead of batch dimension in front). @@ -48,6 +49,7 @@ def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_s labels (np.ndarray): Shape (items,) test_size (float): fraction of data to be used for testing random_state (int, optional): fixed random seed + swap_axes (bool, optional): if true, swaps the axes of the data before splitting Returns: -------- @@ -56,16 +58,22 @@ def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_s train_labels (np.ndarray): Shape (train_items,) test_labels (np.ndarray): Shape (test_items,) """ - data = data.swapaxes(0, 1) - train_data, test_data, train_labels, test_labels = train_test_split( - data, labels, test_size=test_size, random_state=random_state - ) - train_data = train_data.swapaxes(0, 1) - test_data = test_data.swapaxes(0, 1) + if swap_axes: + data = data.swapaxes(0, 1) + train_data, test_data, train_labels, test_labels = train_test_split( + data, labels, test_size=test_size, random_state=random_state + ) + train_data = train_data.swapaxes(0, 1) + test_data = test_data.swapaxes(0, 1) + + else: + train_data, test_data, train_labels, test_labels = train_test_split( + data, labels, test_size=test_size, random_state=random_state + ) return train_data, test_data, train_labels, test_labels -def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balanced_acc, +def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balanced_acc, save_figures=True, show_figures=False): """Analyze ERP data and return/save the ERP model. Extract relevant information from raw data object. @@ -75,6 +83,17 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance Fit the model to the data. Use cross validation to select parameters. Pickle dump model into .pkl file Generate and [optional] save/show ERP figures. + + Parameters: + ----------- + erp_data (RawData): RawData object containing the data to be analyzed. + parameters (Parameters): Parameters object retireved from parameters.json. + device_spec (DeviceSpec): DeviceSpec object containing information about the device used. + data_folder (str): Path to the folder containing the data to be analyzed. + estimate_balanced_acc (bool): If true, uses another model copy on an 80/20 split to + estimate balanced accuracy. + save_figures (bool): If true, saves ERP figures after training to the data folder. + show_figures (bool): If true, shows ERP figures after training. """ # Extract relevant session information from parameters file trial_window = parameters.get("trial_window") @@ -166,7 +185,7 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance model = PcaRdaKdeModel(k_folds=k_folds) model.fit(data, labels) model.metadata = SignalModelMetadata(device_spec=device_spec, - transform=default_transform) + transform=default_transform) log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) @@ -198,15 +217,26 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance ) -def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_figures=False): +def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_figures=False, model_type="Individual"): """Analyze gaze data and return/save the gaze model. - Extract relevant information from gaze data object. + Extract relevant information from gaze data object. Extract timing information from trigger file. Apply preprocessing on the raw data. Extract the data for each target label and each eye separately. Extract inquiries dictionary with keys as target symbols and values as inquiry windows. - Fit the model to the data. + Based on the model type, fit the model to the data. Pickle dump model into .pkl file Generate and [optional] save/show gaze figures. + + Parameters: + ----------- + gaze_data (RawData): RawData object containing the data to be analyzed. + device_spec (DeviceSpec): DeviceSpec object containing information about the device used. + data_folder (str): Path to the folder containing the data to be analyzed. + save_figures (bool): If true, saves ERP figures after training to the data folder. + show_figures (bool): If true, shows ERP figures after training. + model_type (str): Type of gaze model to be used. Options are: + "Individual": Fits a separate Gaussian for each symbol. Default model + "Centralized": Uses data from all symbols to fit a single centralized Gaussian """ figure_handles = visualize_gaze( gaze_data, @@ -228,7 +258,10 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f data, fs = gaze_data.by_channel() - model = GazeModel() + if model_type == "Individual": + model = GazeModel() + elif model_type == "Centralized": + model = GazeModel_AllSymbols() # Extract all Triggers info trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( @@ -271,34 +304,87 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f left_eye, right_eye = extract_eye_info(inquiries[i]) preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) - # Train test split: - test_size = int(len(right_eye) * 0.2) - train_size = len(right_eye) - test_size - train_right_eye = right_eye[:train_size] - test_right_eye = right_eye[train_size:] - - train_left_eye = left_eye[:train_size] - test_left_eye = left_eye[train_size:] - - # Fit the model: - model.fit(train_right_eye) + centralized_data_left = [] + centralized_data_right = [] + test_dict = {} + for sym in symbol_set: + le = preprocessed_data[sym][0] + re = preprocessed_data[sym][1] - scores, means, covs = model.get_scores(test_right_eye) + # Train test split: + labels = np.array([sym] * len(le)) # Labels are the same for both eyes + train_le, test_le, train_labels_le, test_labels_le = subset_data(le, labels, test_size=0.2, swap_axes=False) + train_re, test_re, train_labels_re, test_labels_re = subset_data(re, labels, test_size=0.2, swap_axes=False) + test_dict[sym] = [test_le, test_re] + + if model_type == "Centralized": + # Centralize the data using symbol positions: + # Load json file. + # TODO: move this to a helper function, or get the symbol positions from the build_grid method + with open(f"{ROOT}/symbol_positions.json", 'r') as params_file: + symbol_positions = json.load(params_file) + # Subtract the symbol positions from the data: + centralized_data_left.append(model.reshaper.centralize_all_data(train_le, symbol_positions[sym])) + centralized_data_right.append(model.reshaper.centralize_all_data(train_re, symbol_positions[sym])) + + # Fit the model based on model type. + # Model 1: Fit Gaussian mixture (comp=2) on each symbol and each eye separately + if model_type == "Individual": + model.fit(train_re) + + scores, means, covs = model.get_scores(test_re) + print(means) + + # Visualize the results: + figure_handles = visualize_gaze_inquiries( + le, re, + means, covs, + save_path=None, + show=show_figures, + raw_plot=True, + ) + breakpoint() + + if model_type == "Centralized": + # Model 2: Fit Gaussian mixture (comp=1) on a centralized data + cent_left = np.concatenate(np.array(centralized_data_left, dtype=object)) + cent_right = np.concatenate(np.array(centralized_data_right, dtype=object)) # Visualize the results: - figure_handles = visualize_gaze_inquiries( - left_eye, right_eye, - means, covs, + figure_handles = visualize_centralized_data( + cent_left, cent_right, save_path=None, show=show_figures, raw_plot=True, ) + + # Fit the model: + model.fit(cent_left) + + # Add the means back to the symbol positions. + # Calculate scores for the test set. + for sym in symbol_set: + scores, means, covs = model.get_scores(test_dict[sym][0], symbol_positions[sym]) + + le = preprocessed_data[sym][0] + re = preprocessed_data[sym][1] + # Visualize the results: + figure_handles = visualize_gaze_inquiries( + le, re, + means, covs, + save_path=None, + show=show_figures, + raw_plot=True, + ) + + breakpoint() + model.metadata = SignalModelMetadata(device_spec=device_spec, - transform=None) + transform=None) log.info("Training complete for Eyetracker model. Saving data...") save_model( model, - Path(data_folder, f"model_{device_spec.content_type}.pkl")) + Path(data_folder, f"model_{device_spec.content_type}_{model_type}.pkl")) @report_execution_time @@ -358,11 +444,12 @@ def offline_analysis( device_spec = devices_by_name.get(raw_data.daq_type) # extract relevant information from raw data object eeg if device_spec.content_type == "EEG": - analyze_erp(raw_data, parameters, device_spec, data_folder, estimate_balanced_acc, + analyze_erp(raw_data, parameters, device_spec, data_folder, estimate_balanced_acc, save_figures, show_figures) if device_spec.content_type == "Eyetracker": - analyze_gaze(raw_data, device_spec, data_folder, save_figures, show_figures) + analyze_gaze(raw_data, device_spec, data_folder, save_figures, show_figures, + model_type="Centralized") if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") diff --git a/symbol_positions.json b/symbol_positions.json new file mode 100644 index 000000000..0c9ad42af --- /dev/null +++ b/symbol_positions.json @@ -0,0 +1,114 @@ +{ + "A": [ + 0.20, + 0.30 + ], + "B": [ + 0.31, + 0.30 + ], + "C": [ + 0.42, + 0.30 + ], + "D": [ + 0.53, + 0.30 + ], + "E": [ + 0.64, + 0.30 + ], + "F": [ + 0.75, + 0.30 + ], + "G": [ + 0.20, + 0.41 + ], + "H": [ + 0.31, + 0.41 + ], + "I": [ + 0.42, + 0.41 + ], + "J": [ + 0.53, + 0.41 + ], + "K": [ + 0.64, + 0.41 + ], + "L": [ + 0.75, + 0.41 + ], + "M": [ + 0.20, + 0.52 + ], + "N": [ + 0.31, + 0.52 + ], + "O": [ + 0.42, + 0.52 + ], + "P": [ + 0.53, + 0.49 + ], + "Q": [ + 0.64, + 0.52 + ], + "R": [ + 0.75, + 0.52 + ], + "S": [ + 0.20, + 0.63 + ], + "T": [ + 0.31, + 0.63 + ], + "U": [ + 0.42, + 0.63 + ], + "V": [ + 0.53, + 0.63 + ], + "W": [ + 0.64, + 0.63 + ], + "X": [ + 0.75, + 0.63 + ], + "Y": [ + 0.20, + 0.74 + ], + "Z": [ + 0.31, + 0.74 + ], + "<": [ + 0.42, + 0.74 + ], + "_": [ + 0.53, + 0.79 + ] +} \ No newline at end of file From c4d6bcac9d203eb8748c0933e543efe3222b8fd1 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 23 Oct 2023 15:56:44 -0400 Subject: [PATCH 124/330] removing breakpoints --- bcipy/signal/model/offline_analysis.py | 3 --- scripts/python/plot_inquiry_data.py | 4 +--- 2 files changed, 1 insertion(+), 6 deletions(-) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index a27a54481..6f8c7c2c1 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -343,7 +343,6 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f show=show_figures, raw_plot=True, ) - breakpoint() if model_type == "Centralized": # Model 2: Fit Gaussian mixture (comp=1) on a centralized data @@ -377,8 +376,6 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f raw_plot=True, ) - breakpoint() - model.metadata = SignalModelMetadata(device_spec=device_spec, transform=None) log.info("Training complete for Eyetracker model. Saving data...") diff --git a/scripts/python/plot_inquiry_data.py b/scripts/python/plot_inquiry_data.py index 21e4a2130..40f628dad 100644 --- a/scripts/python/plot_inquiry_data.py +++ b/scripts/python/plot_inquiry_data.py @@ -88,6 +88,4 @@ def load_eye_tracking_data(path): ax.scatter(lx, ly, c='r', s=1) ax.scatter(rx, ry, c='b', s=1) - plt.show() - - breakpoint() \ No newline at end of file + plt.show() \ No newline at end of file From ae2c15ac8f1a7b447ee03ace87813ddaec131934 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 23 Oct 2023 16:10:46 -0400 Subject: [PATCH 125/330] remove print statements, plotting updates --- bcipy/helpers/visualization.py | 15 +++++++++++++++ bcipy/signal/model/offline_analysis.py | 1 - 2 files changed, 15 insertions(+), 1 deletion(-) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index cf6bceb12..36a64bbc5 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -206,6 +206,11 @@ def visualize_gaze( ax.scatter(lx, ly, c='r', s=1) ax.scatter(rx, ry, c='b', s=1) + ax.set_xticks([]) + ax.set_yticks([]) + ax.set_xticklabels([]) + ax.set_yticklabels([]) + plt.title(f'{title}Plot') if save_path is not None: @@ -317,6 +322,11 @@ def visualize_gaze_inquiries( # ax.scatter(means[:,0], means[:,1], c='yellow', s=20, marker='^') + ax.set_xticks([]) + ax.set_yticks([]) + ax.set_xticklabels([]) + ax.set_yticklabels([]) + plt.title(f'{title}Plot') if save_path is not None: @@ -403,6 +413,11 @@ def visualize_centralized_data( ax.scatter(lx, ly, c='r', s=1) ax.scatter(rx, ry, c='b', s=1) + ax.set_xticks([]) + ax.set_yticks([]) + ax.set_xticklabels([]) + ax.set_yticklabels([]) + plt.title(f'{title}Plot') if save_path is not None: diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 6f8c7c2c1..8bc967c2d 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -333,7 +333,6 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f model.fit(train_re) scores, means, covs = model.get_scores(test_re) - print(means) # Visualize the results: figure_handles = visualize_gaze_inquiries( From 0d368230b11ef5dbfda009eace538c1cc59f8cb6 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 29 Oct 2023 14:02:25 -0400 Subject: [PATCH 126/330] fuser name fix --- bcipy/simulator/helpers/evidence_fuser.py | 2 +- bcipy/simulator/helpers/sim_state.py | 7 +++---- bcipy/simulator/sim_sampler.py | 2 +- 3 files changed, 5 insertions(+), 6 deletions(-) diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py index d6c85862a..16a02fe55 100644 --- a/bcipy/simulator/helpers/evidence_fuser.py +++ b/bcipy/simulator/helpers/evidence_fuser.py @@ -11,7 +11,7 @@ def fuse(self, prior_likelihood: Optional[np.ndarray], evidence: Dict) -> np.nda ... -class MultipyFuser(EvidenceFuser): +class MultiplyFuser(EvidenceFuser): def __init__(self): pass diff --git a/bcipy/simulator/helpers/sim_state.py b/bcipy/simulator/helpers/sim_state.py index 2a252a216..75abf3ebe 100644 --- a/bcipy/simulator/helpers/sim_state.py +++ b/bcipy/simulator/helpers/sim_state.py @@ -9,7 +9,7 @@ from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.decision import SimDecisionCriteria, MaxIterationsSim, ProbThresholdSim -from bcipy.simulator.helpers.evidence_fuser import MultipyFuser, EvidenceFuser +from bcipy.simulator.helpers.evidence_fuser import MultiplyFuser, EvidenceFuser from bcipy.simulator.helpers.types import InquiryResult from bcipy.task.control.criteria import DecisionCriteria, MaxIterationsCriteria, ProbThresholdCriteria from bcipy.task.control.handler import EvidenceFusion @@ -53,16 +53,15 @@ def mutate_state(self, state_field, state_value): class StateManagerImpl(StateManager): - def __init__(self, parameters: Parameters, fuser_class=MultipyFuser): + def __init__(self, parameters: Parameters, fuser_class=MultiplyFuser): self.state: SimState = self.initial_state() self.parameters = parameters self.fuser_class: EvidenceFuser.__class__ = fuser_class self.max_inq_len = self.parameters.get('max_inq_len', 50) - # TODO add stoppage criterion, Stoppage criterion is seperate from decision. Decision should we go on to next letter or not def is_done(self) -> bool: - + # TODO add stoppage criterion, Stoppage criterion is seperate from decision. Decision should we go on to next letter or not return self.state.total_inquiry_count() > self.max_inq_len or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 def update(self, evidence) -> InquiryResult: diff --git a/bcipy/simulator/sim_sampler.py b/bcipy/simulator/sim_sampler.py index 0ac5d0235..9f0d03df3 100644 --- a/bcipy/simulator/sim_sampler.py +++ b/bcipy/simulator/sim_sampler.py @@ -71,7 +71,7 @@ def run(self): print(f"Decided {inq_record.decision} for target {inq_record.target} for sentence {self.state_manager.get_state().target_sentence}") print("\n") - sleep(.1) + sleep(.5) # TODO visualize result metrics def __get_inquiry_alp_subset(self, state: SimState): From e391010ac95148a876eb0f3654794f7ca2c7b26a Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 29 Oct 2023 14:53:54 -0400 Subject: [PATCH 127/330] using best selection for inqiuiry stimuli --- bcipy/simulator/helpers/evidence_fuser.py | 8 +++--- .../{sim_state.py => state_manager.py} | 9 +++++-- bcipy/simulator/helpers/types.py | 2 +- bcipy/simulator/interfaces.py | 2 +- bcipy/simulator/{sim_sampler.py => sim.py} | 27 ++++++++++++------- bcipy/simulator/tests/sampler_test.py | 4 +-- 6 files changed, 34 insertions(+), 18 deletions(-) rename bcipy/simulator/helpers/{sim_state.py => state_manager.py} (96%) rename bcipy/simulator/{sim_sampler.py => sim.py} (80%) diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py index 16a02fe55..43b594208 100644 --- a/bcipy/simulator/helpers/evidence_fuser.py +++ b/bcipy/simulator/helpers/evidence_fuser.py @@ -10,6 +10,10 @@ class EvidenceFuser(ABC): def fuse(self, prior_likelihood: Optional[np.ndarray], evidence: Dict) -> np.ndarray: ... + @staticmethod + def make_prior(len_dist): + return np.ones(len_dist) / len_dist + class MultiplyFuser(EvidenceFuser): @@ -19,7 +23,7 @@ def __init__(self): def fuse(self, prior_likelihood, evidence) -> np.ndarray: len_dist = len(list(evidence.values())[0]) - prior_likelihood = prior_likelihood if prior_likelihood is not None else self.__make_prior(len_dist) + prior_likelihood = prior_likelihood if prior_likelihood is not None else EvidenceFuser.make_prior(len_dist) ret_likelihood = prior_likelihood.copy() for value in evidence.values(): @@ -28,8 +32,6 @@ def fuse(self, prior_likelihood, evidence) -> np.ndarray: return ret_likelihood - def __make_prior(self, len_dist): - return np.ones(len_dist) / len_dist def __clean_likelihood(self, likelihood): diff --git a/bcipy/simulator/helpers/sim_state.py b/bcipy/simulator/helpers/state_manager.py similarity index 96% rename from bcipy/simulator/helpers/sim_state.py rename to bcipy/simulator/helpers/state_manager.py index 75abf3ebe..8aaccfa79 100644 --- a/bcipy/simulator/helpers/sim_state.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -25,7 +25,6 @@ class SimState: inquiry_n: int series_n: int series_results: List[List[InquiryResult]] - # TODO store the fused results decision_criterion: List[SimDecisionCriteria] def total_inquiry_count(self): @@ -35,6 +34,13 @@ def total_inquiry_count(self): return count + def get_current_likelihood(self) -> Optional[np.ndarray]: + cur_likelihood = None + if self.inquiry_n: + cur_likelihood = self.series_results[-1][-1].fused_likelihood + + return cur_likelihood + class StateManager(ABC): @@ -72,7 +78,6 @@ def update(self, evidence) -> InquiryResult: evidence_dict = {"SM": evidence} # TODO create wrapper object for Evidences fused_likelihood = fuser.fuse(prior_likelihood, evidence_dict) - # finding out whether max iterations is hit or prob threshold is hit temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, evidence_likelihoods=list(evidence), fused_likelihood=fused_likelihood, # TODO change to use evidence_dict diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py index 6769d71bb..2de09f88f 100644 --- a/bcipy/simulator/helpers/types.py +++ b/bcipy/simulator/helpers/types.py @@ -7,7 +7,7 @@ @dataclass class InquiryResult: target: Optional[str] - time_spent: int # TODO what does time_spent mean? + time_spent: int stimuli: List evidence_likelihoods: List # TODO make this into a dictionary to support multimodal. e.g {SignalModel: evidence_list, LanguageModel:evidence_list} fused_likelihood: np.ndarray diff --git a/bcipy/simulator/interfaces.py b/bcipy/simulator/interfaces.py index 02659d050..cac2c8120 100644 --- a/bcipy/simulator/interfaces.py +++ b/bcipy/simulator/interfaces.py @@ -2,7 +2,7 @@ from bcipy.helpers.symbols import alphabet from bcipy.signal.model import PcaRdaKdeModel -from bcipy.simulator.helpers.sim_state import SimState +from bcipy.simulator.helpers.state_manager import SimState class ModelHandler(ABC): diff --git a/bcipy/simulator/sim_sampler.py b/bcipy/simulator/sim.py similarity index 80% rename from bcipy/simulator/sim_sampler.py rename to bcipy/simulator/sim.py index 9f0d03df3..290e5e747 100644 --- a/bcipy/simulator/sim_sampler.py +++ b/bcipy/simulator/sim.py @@ -1,11 +1,15 @@ import random from time import sleep +from typing import Optional -from bcipy.helpers import load +import numpy as np + +from bcipy.helpers import load, stimuli, symbols from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine +from bcipy.simulator.helpers.evidence_fuser import EvidenceFuser from bcipy.simulator.helpers.sampler import Sampler -from bcipy.simulator.helpers.sim_state import StateManager, SimState +from bcipy.simulator.helpers.state_manager import StateManager, SimState from bcipy.simulator.helpers.types import InquiryResult from bcipy.simulator.interfaces import MetricReferee, ModelHandler from bcipy.simulator.simulator_base import Simulator @@ -55,8 +59,9 @@ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler def run(self): while not self.state_manager.is_done(): - print(f"Series {self.state_manager.get_state().series_n} | Inquiry {self.state_manager.get_state().inquiry_n} | Target {self.state_manager.get_state().target_symbol}") - self.state_manager.mutate_state('display_alphabet', self.__get_inquiry_alp_subset(self.state_manager.get_state())) + print( + f"Series {self.state_manager.get_state().series_n} | Inquiry {self.state_manager.get_state().inquiry_n} | Target {self.state_manager.get_state().target_symbol}") + self.state_manager.mutate_state('display_alphabet', self.__make_stimuli(self.state_manager.get_state())) sampled_data = self.sampler.sample(self.state_manager.get_state()) evidence = self.model_handler.generate_evidence(self.state_manager.get_state(), sampled_data) # TODO make this evidence be a dict (mapping of evidence type to evidence) @@ -74,10 +79,16 @@ def run(self): sleep(.5) # TODO visualize result metrics - def __get_inquiry_alp_subset(self, state: SimState): - # TODO put this in own file or object + def __make_stimuli(self, state: SimState): + # TODO abstract out subset_length = 10 - return random.sample(self.symbol_set, subset_length) + val_func: Optional[np.ndarray] = state.get_current_likelihood() + always_in_stimuli = [symbols.SPACE_CHAR, symbols.BACKSPACE_CHAR] + + if val_func is not None: + return stimuli.best_selection(self.symbol_set, list(val_func), subset_length, always_included=always_in_stimuli) + else: + return random.sample(self.symbol_set, subset_length) def load_parameters(self, path): # TODO validate parameters @@ -93,5 +104,3 @@ def load_parameters(self, path): def get_param(self, name): pass - -# TODO add stronger typing hints diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index 00a25772c..7c2adea5c 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -8,9 +8,9 @@ from bcipy.signal.model import PcaRdaKdeModel from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.sampler import Sampler, SimpleLetterSampler -from bcipy.simulator.helpers.sim_state import StateManagerImpl, StateManager, SimState +from bcipy.simulator.helpers.state_manager import StateManagerImpl, StateManager, SimState from bcipy.simulator.interfaces import ModelHandler, MetricReferee -from bcipy.simulator.sim_sampler import SimulatorCopyPhrase +from bcipy.simulator.sim import SimulatorCopyPhrase class DummyModelHandler(ModelHandler): From af057cb9738ca3bac364f50c8261df80ca3a270f Mon Sep 17 00:00:00 2001 From: Tab Date: Wed, 30 Aug 2023 18:56:03 -0700 Subject: [PATCH 128/330] Upgrade requirements, upgrade from pyqt5 to pyqt6 --- .bcipy/experiment/experiments.json | 17 +++++++++++ .bcipy/field/fields.json | 4 +++ bcipy/acquisition/datastream/mock/switch.py | 2 +- bcipy/gui/BCInterface.py | 2 +- bcipy/gui/alert.py | 2 +- bcipy/gui/experiments/ExperimentField.py | 12 ++++---- bcipy/gui/experiments/ExperimentRegistry.py | 2 +- bcipy/gui/experiments/FieldRegistry.py | 2 +- bcipy/gui/file_dialog.py | 7 +++-- bcipy/gui/main.py | 34 ++++++++++----------- bcipy/gui/parameters/params_form.py | 14 ++++----- bcipy/gui/viewer/data_viewer.py | 27 +++++++++------- bcipy/parameters/parameters.json | 4 +-- requirements.txt | 12 ++++---- 14 files changed, 84 insertions(+), 57 deletions(-) diff --git a/.bcipy/experiment/experiments.json b/.bcipy/experiment/experiments.json index d8a4c9eed..aa3909efd 100644 --- a/.bcipy/experiment/experiments.json +++ b/.bcipy/experiment/experiments.json @@ -2,5 +2,22 @@ "default": { "fields": [], "summary": "Default experiment to test various BciPy features without registering a full experiment." + }, + "test": { + "fields": [ + { + "age": { + "required": "true", + "anonymize": "true" + } + }, + { + "tst": { + "required": "false", + "anonymize": "true" + } + } + ], + "summary": "asdfasdf" } } \ No newline at end of file diff --git a/.bcipy/field/fields.json b/.bcipy/field/fields.json index c47e04f2e..129e00326 100644 --- a/.bcipy/field/fields.json +++ b/.bcipy/field/fields.json @@ -2,5 +2,9 @@ "age": { "help_text": "Age (in years) of user.", "type": "int" + }, + "tst": { + "help_text": "d", + "type": "int" } } \ No newline at end of file diff --git a/bcipy/acquisition/datastream/mock/switch.py b/bcipy/acquisition/datastream/mock/switch.py index afdc7e074..38145f5b2 100644 --- a/bcipy/acquisition/datastream/mock/switch.py +++ b/bcipy/acquisition/datastream/mock/switch.py @@ -81,7 +81,7 @@ def main(switch: Switch): background_color='black') ex.show_gui() - result = gui.exec_() + result = gui.exec() switch.quit() sys.exit(result) diff --git a/bcipy/gui/BCInterface.py b/bcipy/gui/BCInterface.py index 0e5f10c4e..912b97986 100644 --- a/bcipy/gui/BCInterface.py +++ b/bcipy/gui/BCInterface.py @@ -461,7 +461,7 @@ def start_app() -> None: ex.show_gui() - sys.exit(bcipy_gui.exec_()) + sys.exit(bcipy_gui.exec()) if __name__ == '__main__': diff --git a/bcipy/gui/alert.py b/bcipy/gui/alert.py index 042d5d552..d974349d9 100644 --- a/bcipy/gui/alert.py +++ b/bcipy/gui/alert.py @@ -1,7 +1,7 @@ """GUI alert messages""" # pylint: disable=no-name-in-module import sys -from PyQt5.QtWidgets import QApplication +from PyQt6.QtWidgets import QApplication from bcipy.gui.main import alert_message, AlertMessageType, AlertResponse, AlertMessageResponse diff --git a/bcipy/gui/experiments/ExperimentField.py b/bcipy/gui/experiments/ExperimentField.py index cbe5ae5a7..bf8bd7e20 100644 --- a/bcipy/gui/experiments/ExperimentField.py +++ b/bcipy/gui/experiments/ExperimentField.py @@ -5,8 +5,8 @@ from typing import List -from PyQt5.QtCore import Qt -from PyQt5.QtWidgets import ( +from PyQt6.QtCore import Qt +from PyQt6.QtWidgets import ( QHBoxLayout, QPushButton, QScrollArea, @@ -210,7 +210,7 @@ def throw_alert_message(self, elif message_response is AlertMessageResponse.OCE: msg.setStandardButtons(AlertResponse.OK.value | AlertResponse.CANCEL.value) - return msg.exec_() + return msg.exec() class MainPanel(QWidget): @@ -240,8 +240,8 @@ def initUI(self): vbox = QVBoxLayout() self.form_panel = QScrollArea() - self.form_panel.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOn) - self.form_panel.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff) + self.form_panel.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOn) + self.form_panel.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff) self.form_panel.setWidgetResizable(True) self.form_panel.setFixedWidth(self.width) self.form_panel.setWidget(self.form) @@ -307,7 +307,7 @@ def start_app() -> None: save_path=save_path, file_name=file_name ) - bcipy_gui.exec_() + bcipy_gui.exec() if validate: if validate_field_data_written(save_path, file_name): diff --git a/bcipy/gui/experiments/ExperimentRegistry.py b/bcipy/gui/experiments/ExperimentRegistry.py index 9d10d6db8..365675ad5 100644 --- a/bcipy/gui/experiments/ExperimentRegistry.py +++ b/bcipy/gui/experiments/ExperimentRegistry.py @@ -461,7 +461,7 @@ def start_app() -> None: width=600, background_color='black') - sys.exit(bcipy_gui.exec_()) + sys.exit(bcipy_gui.exec()) if __name__ == '__main__': diff --git a/bcipy/gui/experiments/FieldRegistry.py b/bcipy/gui/experiments/FieldRegistry.py index eeb65e576..54cb4741f 100644 --- a/bcipy/gui/experiments/FieldRegistry.py +++ b/bcipy/gui/experiments/FieldRegistry.py @@ -279,7 +279,7 @@ def start_app() -> None: ex.show_gui() - sys.exit(bcipy_gui.exec_()) + sys.exit(bcipy_gui.exec()) if __name__ == '__main__': diff --git a/bcipy/gui/file_dialog.py b/bcipy/gui/file_dialog.py index f88deb766..f54ee2881 100644 --- a/bcipy/gui/file_dialog.py +++ b/bcipy/gui/file_dialog.py @@ -1,7 +1,8 @@ # pylint: disable=no-name-in-module,missing-docstring,too-few-public-methods import sys from pathlib import Path -from PyQt5.QtWidgets import QApplication, QWidget, QFileDialog, QDesktopWidget +from PyQt6.QtWidgets import QApplication, QWidget, QFileDialog +from PyQt6 import QtGui from bcipy.preferences import preferences DEFAULT_FILE_TYPES = "All Files (*)" @@ -12,14 +13,14 @@ class FileDialog(QWidget): def __init__(self): super().__init__() - self.title = 'PyQt5 file dialogs - pythonspot.com' + self.title = 'PyQt6 file dialogs - pythonspot.com' self.width = 640 self.height = 480 # Center on screen self.resize(self.width, self.height) frame_geom = self.frameGeometry() - frame_geom.moveCenter(QDesktopWidget().availableGeometry().center()) + frame_geom.moveCenter(QtGui.QGuiApplication.primaryScreen().availableGeometry().center()) self.move(frame_geom.topLeft()) # The native dialog may prevent the selection from closing after a diff --git a/bcipy/gui/main.py b/bcipy/gui/main.py index b4c729974..9f77c7193 100644 --- a/bcipy/gui/main.py +++ b/bcipy/gui/main.py @@ -7,9 +7,9 @@ from enum import Enum from typing import Any, Callable, List, NamedTuple, Optional, Tuple, Union -from PyQt5.QtCore import QEvent, Qt, QTimer, pyqtSlot -from PyQt5.QtGui import QFont, QPixmap, QShowEvent -from PyQt5.QtWidgets import (QApplication, QCheckBox, QComboBox, +from PyQt6.QtCore import QEvent, Qt, QTimer, pyqtSlot +from PyQt6.QtGui import QFont, QPixmap, QShowEvent, QWheelEvent +from PyQt6.QtWidgets import (QApplication, QCheckBox, QComboBox, QDoubleSpinBox, QFileDialog, QHBoxLayout, QLabel, QLineEdit, QMessageBox, QPushButton, QScrollArea, QSpinBox, QVBoxLayout, QWidget) @@ -19,7 +19,7 @@ def font(size: int = 14, font_family: str = 'Helvetica') -> QFont: """Create a Font object with the given parameters.""" - return QFont(font_family, size, QFont.Normal) + return QFont(font_family, size, weight=0) def invalid_length(min=1, max=25) -> bool: @@ -68,10 +68,10 @@ class AlertMessageType(Enum): Custom enum used to abstract PyQT message types from downstream users. """ - WARN = QMessageBox.Warning - QUESTION = QMessageBox.Question - INFO = QMessageBox.Information - CRIT = QMessageBox.Critical + WARN = QMessageBox.Icon.Warning + QUESTION = QMessageBox.Icon.Question + INFO = QMessageBox.Icon.Information + CRIT = QMessageBox.Icon.Critical class AlertResponse(Enum): @@ -79,10 +79,10 @@ class AlertResponse(Enum): Custom enum used to abstract PyQT alert responses from downstream users. """ - OK = QMessageBox.Ok - CANCEL = QMessageBox.Cancel - YES = QMessageBox.Yes - NO = QMessageBox.No + OK = QMessageBox.StandardButton.Ok + CANCEL = QMessageBox.StandardButton.Cancel + YES = QMessageBox.StandardButton.Yes + NO = QMessageBox.StandardButton.No class PushButton(QPushButton): @@ -245,7 +245,7 @@ def __init__(self, def eventFilter(self, source, event): """Event filter that suppresses the scroll wheel event.""" - if (event.type() == QEvent.Wheel and source is self.control): + if (event.type() == QWheelEvent and source is self.control): return True return False @@ -948,7 +948,7 @@ def throw_alert_message( message_type=message_type, message_response=message_response, message_timeout=message_timeout) - return msg.exec_() + return msg.exec() def get_filename_dialog(self, message: str = 'Open File', @@ -983,8 +983,8 @@ def __init__(self, # create the scrollable are self.frame = QScrollArea() - self.frame.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOn) - self.frame.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff) + self.frame.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOn) + self.frame.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff) self.frame.setWidgetResizable(True) self.frame.setFixedWidth(self.width) self.setFixedHeight(self.height) @@ -1109,7 +1109,7 @@ def start_app() -> None: message_response=AlertMessageResponse.OCE, message_timeout=5) - sys.exit(bcipy_gui.exec_()) + sys.exit(bcipy_gui.exec()) if __name__ == '__main__': diff --git a/bcipy/gui/parameters/params_form.py b/bcipy/gui/parameters/params_form.py index 9c0bde281..39280aa13 100644 --- a/bcipy/gui/parameters/params_form.py +++ b/bcipy/gui/parameters/params_form.py @@ -5,8 +5,8 @@ from pathlib import Path from typing import Dict, Tuple -from PyQt5.QtCore import Qt -from PyQt5.QtWidgets import (QApplication, QFileDialog, QHBoxLayout, +from PyQt6.QtCore import Qt +from PyQt6.QtWidgets import (QApplication, QFileDialog, QHBoxLayout, QPushButton, QScrollArea, QVBoxLayout, QWidget) from bcipy.config import BCIPY_ROOT @@ -244,8 +244,8 @@ def __init__(self, json_file: str): self.layout = QVBoxLayout() self.changes_area = QScrollArea() - self.changes_area.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOn) - self.changes_area.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff) + self.changes_area.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOn) + self.changes_area.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff) self.changes_area.setWidgetResizable(True) self.changes_area.setWidget(self.change_items) self.changes_area.setVisible(not self.collapsed) @@ -328,8 +328,8 @@ def initUI(self): vbox.addLayout(self.changes_panel) self.form_panel = QScrollArea() - self.form_panel.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOn) - self.form_panel.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff) + self.form_panel.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOn) + self.form_panel.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff) self.form_panel.setWidgetResizable(True) self.form_panel.setFixedWidth(self.size[0]) self.form_panel.setWidget(self.form) @@ -423,7 +423,7 @@ def main(json_file, title='BCI Parameters', size=(450, 550)): """Set up the GUI components and start the main loop.""" app = QApplication(sys.argv) _panel = MainPanel(json_file, title, size) - sys.exit(app.exec_()) + sys.exit(app.exec()) if __name__ == '__main__': diff --git a/bcipy/gui/viewer/data_viewer.py b/bcipy/gui/viewer/data_viewer.py index cf654fa7d..85e6b59e0 100644 --- a/bcipy/gui/viewer/data_viewer.py +++ b/bcipy/gui/viewer/data_viewer.py @@ -4,16 +4,21 @@ from queue import Queue from typing import Callable, Dict, List, Optional, Tuple -import matplotlib.ticker as ticker -import numpy as np -from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg -from matplotlib.figure import Figure -from PyQt5.QtCore import Qt, QTimer # pylint: disable=no-name-in-module +from PyQt6.QtCore import Qt, QTimer # pylint: disable=no-name-in-module # pylint: disable=no-name-in-module -from PyQt5.QtWidgets import (QApplication, QCheckBox, QComboBox, QHBoxLayout, +from PyQt6.QtWidgets import (QApplication, QCheckBox, QComboBox, QHBoxLayout, QLabel, QPushButton, QSpinBox, QVBoxLayout, QWidget) +import matplotlib +import matplotlib.ticker as ticker +import numpy as np +matplotlib.use('Qt5Agg') +import matplotlib.pyplot as plt +from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg as FigureCanvas +from matplotlib.figure import Figure + + from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.util import StoppableProcess from bcipy.gui.main import static_text_control @@ -138,7 +143,7 @@ def __init__(self, lbl = QLabel(label) lbl.setStyleSheet(stylesheet) - lbl.setAlignment(Qt.AlignRight) + lbl.setAlignment(Qt.AlignmentFlag.AlignRight) lbl.setContentsMargins(0, 2, 0, 0) layout.addWidget(lbl) @@ -146,9 +151,9 @@ def __init__(self, self.fixed_scale_input.setMaximum(max_value) self.fixed_scale_input.setValue(initial_value) self.fixed_scale_input.setStyleSheet(stylesheet) - self.fixed_scale_input.setAlignment(Qt.AlignLeft) + self.fixed_scale_input.setAlignment(Qt.AlignmentFlag.AlignLeft) self.fixed_scale_input.valueChanged.connect(on_change_fn) - self.fixed_scale_input.setFocusPolicy(Qt.ClickFocus) + self.fixed_scale_input.setFocusPolicy(Qt.FocusPolicy.ClickFocus) layout.addWidget(self.fixed_scale_input) self.setLayout(layout) @@ -236,7 +241,7 @@ def init_canvas(self): self.axes = self.init_axes() self.axes_bounds = self.init_axes_bounds() - self.canvas = FigureCanvasQTAgg(self.figure) + self.canvas = FigureCanvas(self.figure) # pylint: disable=invalid-name,attribute-defined-outside-init def initUI(self): @@ -686,7 +691,7 @@ def main(data_file: str, panel.start() - app_exit = app.exec_() + app_exit = app.exec() if proc: proc.stop() sys.exit(app_exit) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index d390e9ba9..50f5c907d 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -153,7 +153,7 @@ "type": "bool" }, "high_voltage_value": { - "value": "75E+6", + "value": "75000000.0", "section": "artifact_rejection", "readableName": "High Voltage Threshold Value", "helpTip": "Specifies the high voltage threshold (in microvolts) for artifact rejection (High Voltage Threshold must be set to ‘true’). Default: 75E+6. This is not implemented in the current version of the system.", @@ -169,7 +169,7 @@ "type": "bool" }, "low_voltage_value": { - "value": "-75E-6", + "value": "-0.000075", "section": "artifact_rejection", "readableName": "LowVoltage Threshold Value", "helpTip": "Specifies the low voltage threshold (in microvolts) for artifact rejection (Low Voltage Threshold must be set to ‘true’). Default: -75E-6 This is not implemented in the current version of the system.", diff --git a/requirements.txt b/requirements.txt index 6502c030b..578e06a8b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -6,7 +6,7 @@ mne==1.0.2 pyo==1.0.4 pygame==2.1.2 pyglet<=1.5.27,>=1.4 -PsychoPy==2023.1.0 +PsychoPy==2023.2.1 openpyxl==2.6.3 numpy==1.20.3 sounddevice==0.4.1 @@ -14,13 +14,13 @@ SoundFile==0.12.1 scipy==1.10.1 scikit-learn==1.2.2 seaborn==0.9.0 -matplotlib==3.4.2 -pylsl==1.14.0 +matplotlib==3.7.2 +pylsl==1.16 pandas==1.5.3 psutil==5.7.2 -Pillow==9.0.1 +Pillow==9.4.0 py-cpuinfo==7.0.0 -pyedflib==0.1.30 -PyQt5==5.15.1 +pyedflib==0.1.34 +PyQt6==6.5.2 pywavelets==1.4.1 tqdm==4.62.2 \ No newline at end of file From 3ebd117e0a86e2cc5be1c8a4b2d7d20c056914a9 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Mon, 30 Oct 2023 12:27:10 -0700 Subject: [PATCH 129/330] remove test fields and experiment --- .bcipy/experiment/experiments.json | 17 ----------------- .bcipy/field/fields.json | 4 ---- 2 files changed, 21 deletions(-) diff --git a/.bcipy/experiment/experiments.json b/.bcipy/experiment/experiments.json index aa3909efd..d8a4c9eed 100644 --- a/.bcipy/experiment/experiments.json +++ b/.bcipy/experiment/experiments.json @@ -2,22 +2,5 @@ "default": { "fields": [], "summary": "Default experiment to test various BciPy features without registering a full experiment." - }, - "test": { - "fields": [ - { - "age": { - "required": "true", - "anonymize": "true" - } - }, - { - "tst": { - "required": "false", - "anonymize": "true" - } - } - ], - "summary": "asdfasdf" } } \ No newline at end of file diff --git a/.bcipy/field/fields.json b/.bcipy/field/fields.json index 129e00326..c47e04f2e 100644 --- a/.bcipy/field/fields.json +++ b/.bcipy/field/fields.json @@ -2,9 +2,5 @@ "age": { "help_text": "Age (in years) of user.", "type": "int" - }, - "tst": { - "help_text": "d", - "type": "int" } } \ No newline at end of file From bb439deedace6b99bb37ec6d7c6c45c22d4c7dec Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Mon, 30 Oct 2023 13:27:46 -0700 Subject: [PATCH 130/330] cleanup and linting --- bcipy/gui/BCInterface.py | 53 ++++++++++++++++++++------------- bcipy/gui/main.py | 5 ++-- bcipy/gui/viewer/data_viewer.py | 2 -- requirements.txt | 4 +-- 4 files changed, 38 insertions(+), 26 deletions(-) diff --git a/bcipy/gui/BCInterface.py b/bcipy/gui/BCInterface.py index 912b97986..c3e8eb63e 100644 --- a/bcipy/gui/BCInterface.py +++ b/bcipy/gui/BCInterface.py @@ -28,11 +28,13 @@ class BCInterface(BCIGui): tasks = TaskType.list() default_text = '...' - padding = 30 + padding = 20 btn_height = 40 + btn_width = 100 max_length = 25 min_length = 1 timeout = 3 + font = 'Consolas' def __init__(self, *args, **kwargs): super(BCInterface, self).__init__(*args, **kwargs) @@ -63,7 +65,7 @@ def __init__(self, *args, **kwargs): self.autoclose = False self.alert = True - self.static_font_size = 24 + self.static_font_size = 16 self.user_id_validations = [ (invalid_length(min=self.min_length, max=self.max_length), @@ -77,36 +79,43 @@ def build_buttons(self) -> None: Build all buttons necessary for the UI. Define their action on click using the named argument action. """ + self.add_button( - message='Load Parameters', position=[self.padding, 450], - size=[110, self.btn_height], background_color='white', + message='Load', position=[self.padding, 450], + size=[self.btn_width, self.btn_height], background_color='Plum', + text_color='black', + font_family=self.font, action=self.select_parameters) self.add_button( - message='Edit Parameters', position=[self.padding + 115, 450], - size=[105, self.btn_height], background_color='white', + message='Edit', position=[self.padding + self.btn_width + 10, 450], + size=[self.btn_width, self.btn_height], background_color='LightCoral', + text_color='black', + font_family=self.font, action=self.edit_parameters) - btn_auc_width = 100 - btn_auc_x = self.padding + 225 + btn_auc_x = self.padding + (self.btn_width * 2) + 20 self.add_button( - message='Calculate AUC', position=(btn_auc_x, 450), - size=(btn_auc_width, self.btn_height), background_color='white', + message='Train', position=(btn_auc_x, 450), + size=(self.btn_width, self.btn_height), background_color='LightSeaGreen', + text_color='black', + font_family=self.font, action=self.offline_analysis) - btn_start_width = 200 + btn_start_width = self.btn_width * 2 + 10 btn_start_x = self.width - (self.padding + btn_start_width) self.add_button( - message='Start Experiment Session', position=[btn_start_x, 450], - size=[btn_start_width, self.btn_height], + message='Start Session', position=[btn_start_x, 440], + size=[btn_start_width, self.btn_height + 10], background_color='green', action=self.start_experiment, - text_color='white') + text_color='white', + font_family=self.font) self.add_button( message='+', position=[self.width - self.padding - 200, 260], - size=[40, self.btn_height - 10], + size=[35, self.btn_height - 10], background_color='green', action=self.create_experiment, text_color='white' @@ -202,10 +211,11 @@ def build_text(self) -> None: """ self.add_static_textbox( text='BCInterface', - position=[275, 0], - size=[200, 50], + position=[210, 0], + size=[250, 50], background_color='black', text_color='white', + font_family=self.font, font_size=30) text_x = 145 @@ -215,12 +225,14 @@ def build_text(self) -> None: size=[200, 50], background_color='black', text_color='white', + font_family=self.font, font_size=self.static_font_size) self.add_static_textbox( text='Experiment', position=[text_x, 205], size=[300, 50], background_color='black', + font_family=self.font, text_color='white', font_size=self.static_font_size) self.add_static_textbox( @@ -229,6 +241,7 @@ def build_text(self) -> None: size=[300, 50], background_color='black', text_color='white', + font_family=self.font, font_size=self.static_font_size) def build_images(self) -> None: @@ -430,8 +443,8 @@ def action_disabled(self) -> bool: return True else: self.disable = True - # set the update time to every 1000ms - self.timer.start(1000) + # set the update time to every 500ms + self.timer.start(500) return False def _disable_action(self) -> bool: @@ -456,7 +469,7 @@ def start_app() -> None: ex = BCInterface( title='Brain Computer Interface', height=550, - width=750, + width=700, background_color='black') ex.show_gui() diff --git a/bcipy/gui/main.py b/bcipy/gui/main.py index 9f77c7193..4532bfb03 100644 --- a/bcipy/gui/main.py +++ b/bcipy/gui/main.py @@ -7,7 +7,7 @@ from enum import Enum from typing import Any, Callable, List, NamedTuple, Optional, Tuple, Union -from PyQt6.QtCore import QEvent, Qt, QTimer, pyqtSlot +from PyQt6.QtCore import Qt, QTimer, pyqtSlot from PyQt6.QtGui import QFont, QPixmap, QShowEvent, QWheelEvent from PyQt6.QtWidgets import (QApplication, QCheckBox, QComboBox, QDoubleSpinBox, QFileDialog, QHBoxLayout, QLabel, @@ -827,6 +827,7 @@ def add_button(self, id: int = -1, background_color: str = 'white', text_color: str = 'default', + font_family: str = 'Times', action: Optional[Callable] = None) -> PushButton: """Add Button.""" btn = PushButton(message, self.window) @@ -835,7 +836,7 @@ def add_button(self, btn.resize(size[0], size[1]) btn.setStyleSheet( - f'background-color: {background_color}; color: {text_color};') + f'background-color: {background_color}; color: {text_color}; font-family: {font_family};') if action: btn.clicked.connect(action) diff --git a/bcipy/gui/viewer/data_viewer.py b/bcipy/gui/viewer/data_viewer.py index 85e6b59e0..820c93866 100644 --- a/bcipy/gui/viewer/data_viewer.py +++ b/bcipy/gui/viewer/data_viewer.py @@ -5,7 +5,6 @@ from typing import Callable, Dict, List, Optional, Tuple from PyQt6.QtCore import Qt, QTimer # pylint: disable=no-name-in-module -# pylint: disable=no-name-in-module from PyQt6.QtWidgets import (QApplication, QCheckBox, QComboBox, QHBoxLayout, QLabel, QPushButton, QSpinBox, QVBoxLayout, QWidget) @@ -14,7 +13,6 @@ import matplotlib.ticker as ticker import numpy as np matplotlib.use('Qt5Agg') -import matplotlib.pyplot as plt from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure diff --git a/requirements.txt b/requirements.txt index 578e06a8b..a7c1d24ca 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,6 +1,6 @@ attrdict3==2.0.2 transformers==4.26.0 -torch==1.10.1 +torch==2.0.0 construct==2.8.14 mne==1.0.2 pyo==1.0.4 @@ -9,7 +9,7 @@ pyglet<=1.5.27,>=1.4 PsychoPy==2023.2.1 openpyxl==2.6.3 numpy==1.20.3 -sounddevice==0.4.1 +sounddevice==0.4.4 SoundFile==0.12.1 scipy==1.10.1 scikit-learn==1.2.2 From e7fbe4cbe308a5c34761825133892bf5fa7b6b1a Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Mon, 30 Oct 2023 15:49:29 -0700 Subject: [PATCH 131/330] Use latest pyqt6 --- requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index a7c1d24ca..c857299d4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -21,6 +21,6 @@ psutil==5.7.2 Pillow==9.4.0 py-cpuinfo==7.0.0 pyedflib==0.1.34 -PyQt6==6.5.2 +PyQt6==6.6.0 pywavelets==1.4.1 tqdm==4.62.2 \ No newline at end of file From 071b83e99709470e2e5f386f54b59de2d8ba7320 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 31 Oct 2023 09:40:07 -0700 Subject: [PATCH 132/330] Updated stimuli generation for VEP; updated VEP display with better handling for symbols prior to putting them in boxes; updated VEP calib demo --- .../display/demo/vep/demo_calibration_vep.py | 54 +++- bcipy/display/paradigm/vep/display.py | 245 +++++++++++------- bcipy/helpers/list.py | 26 +- bcipy/helpers/stimuli.py | 124 +++++---- 4 files changed, 292 insertions(+), 157 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index ca6f493d8..cec8e652d 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -42,38 +42,68 @@ print(f'Monitor refresh rate: {frameRate} Hz') -box_colors = ['#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232'] -stim_color = [[color] for i, color in enumerate(box_colors) if i < num_boxes] +stim_color = [ + 'green', 'red', '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', + '#FF8232' +] layout = centered(width_pct=0.95, height_pct=0.80) box_config = BoxConfiguration(layout, num_boxes=num_boxes) experiment_clock = Clock() len_stimuli = 10 -stimuli = VEPStimuliProperties( +stim_props = VEPStimuliProperties( stim_color=stim_color, stim_pos=box_config.positions, stim_height=0.1, stim_font=font, - timing=(1, 0.5, 2, 4), # prompt, fixation, animation, stimuli + timing=[1, 0.5, 4], # prompt, fixation, stimuli stim_length=1, # how many times to stimuli ) task_bar = CalibrationTaskBar(win, inquiry_count=4, current_index=0, font=font) -vep = VEPDisplay(win, experiment_clock, stimuli, task_bar, info, box_config=box_config) -timing = [] +vep = VEPDisplay(win, + experiment_clock, + stim_props, + task_bar, + info, + box_config=box_config, + should_prompt_target=True) wait_seconds = 2 +inquiries = [['U', + '+', + ['C', 'M', 'S'], + ['D', 'P', 'X', '_'], + ['L', 'U', 'Y'], + ['E', 'K', 'O'], + ['<', 'A', 'F', 'H', 'I', 'J', 'N', 'Q', 'R', 'V', 'Z'], + ['B', 'G', 'T', 'W']], + ['D', + '+', + ['O', 'X'], + ['D'], + ['P', 'U'], + ['<', 'B', 'E', 'G', 'H', 'J', 'K', 'L', 'R', 'T'], + ['A', 'C', 'F', 'I', 'M', 'N', 'Q', 'V', 'Y', '_'], + ['S', 'W', 'Z']], + ['S', + '+', + ['A', 'J', 'K', 'T', 'V', 'W'], + ['S'], + ['_'], + ['E', 'G', 'M', 'R'], + ['<', 'B', 'C', 'D', 'H', 'I', 'L', 'N', 'O', 'P', 'Q', 'U', 'X', 'Z'], + ['F', 'Y']]] + +timing = [] # loop over the text and colors, present the stimuli and record the timing -for txt in task_text: +for i, txt in enumerate(task_text): vep.update_task_bar(txt) - if num_boxes == 4: - stim = [['A', 'B'], ['Z'], ['P'], ['R', 'W']] - if num_boxes == 6: - stim = [['A'], ['B'], ['Z', 'X'], ['P', 'I'], ['R'], ['W', 'C']] - vep.schedule_to(stimuli=stim) + + vep.schedule_to(stimuli=inquiries[i]) timing += vep.do_inquiry() # show the wait screen, this will only happen once diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index e0d889699..9eeeb2ae9 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -1,19 +1,23 @@ import logging from itertools import cycle -from typing import List, Tuple +from typing import List, NamedTuple, Optional, Tuple, Union import numpy as np from psychopy import core, visual from psychopy.visual.shape import ShapeStim +import bcipy.display.components.layout as layout from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, VEPStimuliProperties) from bcipy.display.components.layout import envelope, scaled_size from bcipy.display.components.task_bar import TaskBar +from bcipy.display.paradigm.matrix.layout import symbol_positions from bcipy.display.paradigm.vep.layout import BoxConfiguration, checkerboard from bcipy.helpers.clock import Clock -from bcipy.helpers.stimuli import get_fixation, resize_image -from bcipy.helpers.triggers import TriggerCallback, _calibration_trigger +from bcipy.helpers.list import expanded +from bcipy.helpers.stimuli import resize_image +from bcipy.helpers.symbols import alphabet +from bcipy.helpers.triggers import _calibration_trigger def create_vep_codes(length=32, count=4) -> List[List[int]]: @@ -27,6 +31,11 @@ def create_vep_codes(length=32, count=4) -> List[List[int]]: np.random.seed(1) return [np.random.randint(2, size=length) for _ in range(count)] +class StimProps(NamedTuple): + """Represents properties of a single symbol (or stim box)""" + symbol: Union[str, List[str]] + duration: float + color: str class VEPStim: """Represents a checkerboard of squares that can be flashed at a given @@ -124,8 +133,10 @@ def __init__( task_bar: TaskBar, info: InformationProperties, trigger_type: str = 'text', + symbol_set: Optional[List[str]] = None, codes: List[int] = None, - box_config: BoxConfiguration = None): + box_config: BoxConfiguration = None, + should_prompt_target: bool = True): self.window = window self.window_size = self.window.size # [w, h] self.refresh_rate = round(window.getActualFrameRate()) @@ -138,26 +149,40 @@ def __init__( # easy updating after definition self.stimuli_inquiry = stimuli.stim_inquiry self.stimuli_colors = stimuli.stim_colors - self.timing_prompt, self.timing_fixation, self.timing_animation, self.timing_stimuli = stimuli.stim_timing + self.stimuli_timing = stimuli.stim_timing + self.timing_prompt, self.timing_fixation, self.timing_stimuli = stimuli.stim_timing + self.timing_animation = 2 self.stimuli_font = stimuli.stim_font self.stimuli_height = stimuli.stim_height self.stimuli_pos = stimuli.stim_pos - self.is_txt_stim = stimuli.is_txt_stim - self.stim_length = stimuli.stim_length + self.stim_length = stimuli.stim_length self.logger.info(self.stimuli_pos) self.check_configuration() - self.sti = [] + self.symbol_set = symbol_set or alphabet() + self.sort_order = self.symbol_set.index + + # Build starting list of symbols + display_container = layout.centered(width_pct=0.7) + self.starting_positions = symbol_positions(display_container, + rows=3, + columns=10) + self.logger.info( + f"Symbol starting positions ({display_container.units} units): {self.starting_positions}" + ) + self.fixation = self._build_fixation() + self.starting_color = 'white' + self.sti = self._build_inquiry_stimuli() self.static_clock = core.Clock() # Trigger handling self.first_stim_time = None self.trigger_type = trigger_type - self.trigger_callback = TriggerCallback() self.experiment_clock = experiment_clock + self._timing = [] # Callback used on presentation of first stimulus. self.first_run = True @@ -179,95 +204,135 @@ def __init__( num_squares=25) self.text_boxes = self._build_text_boxes(box_config) + self.should_prompt_target = should_prompt_target def check_configuration(self): """Check that configured properties are consistent""" - assert len( - self.stimuli_colors) == self.vep_type, ( - f"stimuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") assert len( self.stimuli_pos) == self.vep_type, ( f"stimuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}") - def do_fixation(self) -> None: + def do_fixation(self, fixation: StimProps) -> None: """Draw fixation cross""" + duration = fixation.duration or self.timing_fixation + self.fixation.text = fixation.symbol + self.fixation.color = fixation.color self.fixation.draw() self.draw_static() self.window.flip() - core.wait(self.timing_fixation) + core.wait(duration) + + def stim_properties(self) -> List[StimProps]: + """Returns a tuple of (symbol, duration, and color) for each stimuli, + including the target and fixation stim. Stimuli that represent VEP + boxes will have a list of symbols.""" + stim_num = len(self.stimuli_inquiry) + assert len(self.stimuli_colors) == stim_num, "Each box should have its own color" + + return [ + StimProps(*props) + for props in zip(self.stimuli_inquiry, + expanded(list(self.stimuli_timing), length=stim_num), + self.stimuli_colors) + ] def do_inquiry(self) -> List[float]: """Do the inquiry.""" - - timing = [] + self.reset_timing() # if this is the first run, calibrate using the trigger pulse if self.first_run: self._trigger_pulse() + if self.should_prompt_target: + [target, fixation, *stim] = self.stim_properties() + self.prompt_target(target) + else: + [fixation, *stim] = self.stim_properties() + # fixation --> animation / prompting --> VEP stimulate - self.do_fixation() - timing += self.animate_inquiry() - timing += self.stimulate() + self.do_fixation(fixation) + self.animate_inquiry(stim) + self.stimulate() - # clear everyting expect static stimuli + # clear everything expect static stimuli self.draw_static() self.window.flip() - return timing + return self._timing - def animate_inquiry(self) -> List[float]: + + def prompt_target(self, target: StimProps) -> float: + """Present the target for the configured length of time. Records the + stimuli timing information. + + Parameters + ---------- + target - (symbol, duration, color) tuple + """ + # register any timing and marker callbacks + self.window.callOnFlip(self.add_timing, target.symbol) + stim = visual.TextStim(self.window, + text=target.symbol, + color=target.color, + height=self.stimuli_height, + pos=[0, 0]) + stim.draw() + self.draw_static() + self.window.flip() + core.wait(target.duration) + + def animate_inquiry(self, stimuli: List[StimProps]) -> None: """Display the inquiry. Inquiry is a list of lists of strings. Each list contains what stimuli to display for each box defined in self.vep. """ - timing = [] - self.trigger_callback.reset() - self.window.callOnFlip( - self.trigger_callback.callback, - self.experiment_clock, - 'VEP_INQ_ANIMATION') + self.window.callOnFlip(self.add_timing, 'VEP_INQ_ANIMATION') self._reset_text_boxes() - self._build_inquiry_stimuli() - - self.static_clock.reset() - while self.static_clock.getTime() < self.timing_animation: - self.draw_boxes() - self.draw_animation() - self.draw_static() - self.window.flip() - timing += self.trigger_callback.timing + self.reset_symbol_positions() + self.set_stimuli_colors(stimuli) + self.draw_animation() + self._set_inquiry(stimuli) - self._set_inquiry() - self.trigger_callback.reset() - self.window.callOnFlip( - self.trigger_callback.callback, - self.experiment_clock, - 'VEP_INQUIRY') + self.window.callOnFlip(self.add_timing, 'VEP_INQUIRY') # display the inquiry + self.draw_boxes() + self.draw_static() + self.window.flip() + core.wait(self.timing_prompt) + + def set_stimuli_colors(self, stim_groups: List[StimProps]) -> None: + """Update the colors of the stimuli associated with each symbol to + reflect which box it will be placed in.""" + for group in stim_groups: + for sym in group.symbol: + self.sti[sym].color = group.color + + def draw_animation(self) -> None: + """Draw the stimuli animation. + + TODO: animate the symbols moving to their end positions + - determine the number of frames in self.timing_animation seconds + - calculate end positions for each symbol (using symbol_positions with each box as the layout) + - compute the intermediate positions (line trajectory of each symbol) + - update position on each tick + """ self.static_clock.reset() - while self.static_clock.getTime() < self.timing_prompt: + while self.static_clock.getTime() < self.timing_animation: self.draw_boxes() + for sti in self.sti.values(): + sti.draw() self.draw_static() self.window.flip() - timing += self.trigger_callback.timing - - return timing - - def draw_animation(self) -> None: - """Draw the stimuli animation.""" - for sti in self.sti: - sti.draw() - def draw_boxes(self) -> None: """Draw the text boxes under VEP stimuli.""" for box in self.text_boxes: box.draw() - def stimulate(self) -> List[float]: + def stimulate(self) -> None: """ This is the main display function of the VEP paradigm. It is responsible for drawing the flickering stimuli. @@ -275,11 +340,7 @@ def stimulate(self) -> List[float]: It assumes that the VEP stimuli are already constructed. These boxes are drawn in the order they are in the list as defined in self.vep. """ - self.trigger_callback.reset() - self.window.callOnFlip( - self.trigger_callback.callback, - self.experiment_clock, - 'VEP_STIMULATE') + self.window.callOnFlip(self.add_timing, 'VEP_STIMULATE') self.static_clock.reset() while self.static_clock.getTime() < self.timing_stimuli: for frame in range(self.refresh_rate): @@ -295,7 +356,6 @@ def stimulate(self) -> List[float]: ) self.logger.debug(f"Average frame duration: {ended_at/self.timing_stimuli}") - return self.trigger_callback.timing def draw_static(self) -> None: """Draw static elements in a stimulus.""" @@ -316,31 +376,42 @@ def update_task_bar(self, text: str = ''): if self.task_bar: self.task_bar.update(text) + def add_timing(self, stimuli: str): + """Add a new timing entry using the stimuli as a label. + + Useful as a callback function to register a marker at the time it is + first displayed.""" + self._timing.append([stimuli, self.experiment_clock.getTime()]) + + def reset_timing(self): + """Reset the trigger timing.""" + self._timing = [] + def _build_fixation(self) -> visual.TextStim: """Build the fixation stim""" return visual.TextStim(self.window, - text=get_fixation(self.is_txt_stim), + text='+', color='red', height=self.stimuli_height, - units='height', pos=[0, 0]) - def _build_inquiry_stimuli(self) -> None: + def _build_inquiry_stimuli(self) -> List[visual.TextStim]: """Build the inquiry stimuli.""" - all_letters = [] - all_colors = [] - self.sti = [] - for letters, colors in zip(self.stimuli_inquiry, self.stimuli_colors): - for letter in letters: - all_letters.append(letter) - all_colors.append(colors[0]) - pos = (0, 0) - for letter, color in zip(all_letters, all_colors): - pos = (pos[0] + self.stimuli_height, pos[1]) - self.sti.append( - visual.TextStim(self.window, text=letter, color=color, pos=pos, height=self.stimuli_height)) - - return self.sti + grid = {} + for sym in self.symbol_set: + pos_index = self.sort_order(sym) + grid[sym] = visual.TextStim(win=self.window, + text=sym, + color=self.starting_color, + pos=self.starting_positions[pos_index], + height=self.stimuli_height) + return grid + + def reset_symbol_positions(self) -> None: + """Reset the position of each symbol to its starting position""" + for sym in self.symbol_set: + pos_index = self.sort_order(sym) + self.sti[sym].pos = self.starting_positions[pos_index] def build_vep_stimuli(self, positions: List[Tuple[float, float]], @@ -419,22 +490,14 @@ def _reset_text_boxes(self) -> None: for text_box in self.text_boxes: text_box.setText(' ') - def _set_inquiry(self) -> List[visual.TextBox2]: - """Generate Inquiry. - - This method sets the correct inquiry text for each text boxes. + def _set_inquiry(self, stimuli: List[StimProps]) -> List[visual.TextBox2]: + """Set the correct inquiry text for each text boxes. """ - # generate the inquiry stimuli - assert len( - self.stimuli_inquiry) == self.vep_type, ( - f"stimuli inquiry {len(self.stimuli_inquiry)} must be the same length as vep type {self.vep_type}") - assert len( - self.stimuli_colors) == self.vep_type, ( - f"stimuli colors {len(self.stimuli_colors)} must be the same length as vep type {self.vep_type}") - for box_content, color, box in zip(self.stimuli_inquiry, self.stimuli_colors, self.text_boxes): - text = ' '.join(box_content) + for i, sti in enumerate(stimuli): + box = self.text_boxes[i] + text = ' '.join(sti.symbol) box.text = text - box.color = color[0] + box.color = sti.color return self.text_boxes def wait_screen(self, message: str, color: str) -> None: diff --git a/bcipy/helpers/list.py b/bcipy/helpers/list.py index 7a64fa48d..d1fca1004 100644 --- a/bcipy/helpers/list.py +++ b/bcipy/helpers/list.py @@ -49,8 +49,32 @@ def find_index(iterable: List, return i return None + def swapped(lst: List, index1: int, index2: int) -> None: """Creates a copy of the provided list with elements at the given indices swapped.""" - replacements = { index1: lst[index2], index2: lst[index1] } + replacements = {index1: lst[index2], index2: lst[index1]} return [replacements.get(i, val) for i, val in enumerate(lst)] + + +def expanded(lst: List, + length: int, + fill: Union[Any, Callable] = lambda x: x[-1]) -> List: + """Creates a copy of the provided list expanded to the given length. By + default the last item is used as the fill item. + + Parameters + ---------- + lst - list of items to copy + length - expands list to this length + fill - optional; used to determine which element to use for + the fill, given the list. Defaults to the last element. + + >>> expand([1,2,3], length=5) + [1,2,3,3,3] + """ + times = length - len(lst) + if lst and times > 0: + item = fill(lst) if callable(fill) else fill + return lst + ([item] * times) + return lst diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 32288cc69..5af1e5484 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -1070,60 +1070,80 @@ def ssvep_to_code(refresh_rate: int = 60, flicker_rate: int = 10) -> List[int]: return codes -# def generate_vep_calibration_inquiries( -# alp: List[str], -# timing: List[float] = None, -# color: List[str] = None, -# inquiry_count: int = 100, -# num_boxes: int = 4, -# is_txt: bool = True) -> InquirySchedule: -# """ -# Generates VEP inquiries with target letters in all possible positions. - -# In the VEP paradigm, all stimuli in the alphabet are displayed in each -# inquiry. The symbols with the highest likelihoods are displayed alone -# while those with lower likelihoods occur together. - -# Parameters -# ---------- -# alp(list[str]): stimuli -# timing(list[float]): Task specific timing for generator. -# [target, fixation, stimuli] -# color(list[str]): Task specific color for generator -# [target, fixation, stimuli] -# inquiry_count(int): number of inquiries in a calibration -# num_boxes(int): number of display boxes -# is_txt(bool): whether the stimuli type is text. False would be an image stimuli. - -# Return -# ------ -# schedule_inq(tuple( -# samples[list[list[str]]]: list of inquiries -# timing(list[list[float]]): list of timings -# color(list(list[str])): list of colors)): scheduled inquiries -# """ -# if timing is None: -# timing = [0.5, 1, 2] -# # if color is None: -# # color = ['green', 'red', 'white'] -# assert len( -# timing -# ) == 3, "timing must include values for [target, fixation, stimuli]" -# time_target, time_fixation, time_stim = timing -# fixation = get_fixation(is_txt) - -# inquiries = generate_vep_inquiries(alp, inquiry_count, num_boxes) - - -# return InquirySchedule(samples, times, colors) - -def generate_vep_inquiries(alphabet: List[str], num_boxes: int=6, inquiry_count: int=100): + +def generate_vep_calibration_inquiries(alp: List[str], + timing: List[float] = None, + color: List[str] = None, + inquiry_count: int = 100, + num_boxes: int = 4, + is_txt: bool = True) -> InquirySchedule: + """ + Generates VEP inquiries with target letters in all possible positions. + + In the VEP paradigm, all stimuli in the alphabet are displayed in each + inquiry. The symbols with the highest likelihoods are displayed alone + while those with lower likelihoods occur together. + + Parameters + ---------- + alp(list[str]): stimuli + timing(list[float]): Task specific timing for generator. + [target, fixation, stimuli] + color(list[str]): Task specific color for generator + [target, fixation, stimuli] + inquiry_count(int): number of inquiries in a calibration + num_boxes(int): number of display boxes + is_txt(bool): whether the stimuli type is text. False would be an image stimuli. + + Return + ------ + schedule_inq(tuple( + samples[list[list[str]]]: list of inquiries + timing(list[list[float]]): list of timings + color(list(list[str])): list of colors)): scheduled inquiries + """ + if timing is None: + timing = [0.5, 1, 2] + default_colors = [ + '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' + ] + if color is None: + box_colors = list( + itertools.islice(itertools.cycle(default_colors), num_boxes)) + color = ['green', 'red'] + box_colors + assert len( + timing + ) == 3, "timing must include values for [target, fixation, stimuli]" + + inquiries = generate_vep_inquiries(alp, num_boxes, inquiry_count, is_txt) + times = [timing for _ in range(inquiry_count)] + colors = [color for _ in range(inquiry_count)] + + return InquirySchedule(inquiries, times, colors) + + +def generate_vep_inquiries(symbols: List[str], + num_boxes: int = 6, + inquiry_count: int = 20, + is_txt: bool = True): """Generates inquiries""" + fixation = get_fixation(is_txt) + target_indices = random_target_positions(inquiry_count, + stim_per_inquiry=num_boxes, + percentage_without_target=0) + targets = generate_targets(symbols, + inquiry_count, + percentage_without_target=0.0) + return [[target, fixation] + generate_vep_inquiry(alphabet=symbols, + num_boxes=num_boxes, + target=target, + target_pos=target_pos) + for target, target_pos in zip(targets, target_indices)] def stim_per_box(num_symbols: int, num_boxes: int = 6, - max_empty_boxes: int = 1, + max_empty_boxes: int = 0, max_single_sym_boxes: int = 4) -> List[int]: """Determine the number of stimuli per vep box. @@ -1223,9 +1243,7 @@ def generate_vep_inquiry(alphabet: List[str], if target: # Move the target to the front so it gets put in the lowest count box # greater than 0. - syms = swapped(syms, - index1=0, - index2=syms.index(target)) + syms = swapped(syms, index1=0, index2=syms.index(target)) # Put syms in boxes boxes = [] sym_index = 0 @@ -1234,7 +1252,7 @@ def generate_vep_inquiry(alphabet: List[str], for _i in range(count): box.append(syms[sym_index]) sym_index += 1 - box.sort() # sort stim within box + box.sort() # sort stim within box boxes.append(box) random.shuffle(boxes) From f854e76bbcf1da30b5ec8a28f02786dd8f1a8e2e Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 31 Oct 2023 09:53:35 -0700 Subject: [PATCH 133/330] Fixed error resulting from upstream merge --- bcipy/display/paradigm/vep/display.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 9eeeb2ae9..157ce838f 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -164,7 +164,7 @@ def __init__( self.sort_order = self.symbol_set.index # Build starting list of symbols - display_container = layout.centered(width_pct=0.7) + display_container = layout.centered(parent=self.window, width_pct=0.7) self.starting_positions = symbol_positions(display_container, rows=3, columns=10) From 4b9ffb05f2f666b9c7e0b6a17207224346b41e54 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 31 Oct 2023 18:06:31 -0700 Subject: [PATCH 134/330] upgrades to permit use on m2 chips --- .github/workflows/codeql-analysis.yml | 70 --------------------------- bcipy/helpers/session.py | 6 ++- bcipy/helpers/system_utils.py | 2 +- requirements.txt | 8 +-- scripts/shell/m2chip_install.sh | 32 ++++++++++++ 5 files changed, 41 insertions(+), 77 deletions(-) delete mode 100644 .github/workflows/codeql-analysis.yml create mode 100644 scripts/shell/m2chip_install.sh diff --git a/.github/workflows/codeql-analysis.yml b/.github/workflows/codeql-analysis.yml deleted file mode 100644 index 1e137f55c..000000000 --- a/.github/workflows/codeql-analysis.yml +++ /dev/null @@ -1,70 +0,0 @@ -# For most projects, this workflow file will not need changing; you simply need -# to commit it to your repository. -# -# You may wish to alter this file to override the set of languages analyzed, -# or to provide custom queries or build logic. -# -# ******** NOTE ******** -# We have attempted to detect the languages in your repository. Please check -# the `language` matrix defined below to confirm you have the correct set of -# supported CodeQL languages. -# -name: "CodeQL" - -on: - push: - branches: [ main ] - pull_request: - # The branches below must be a subset of the branches above - branches: [ main ] - schedule: - - cron: '19 16 * * 4' - -jobs: - analyze: - name: Analyze - runs-on: ubuntu-latest - permissions: - actions: read - contents: read - security-events: write - - strategy: - fail-fast: false - matrix: - language: [ 'python' ] - # CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python', 'ruby' ] - # Learn more about CodeQL language support at https://git.io/codeql-language-support - - steps: - - name: Checkout repository - uses: actions/checkout@v3 - - # Initializes the CodeQL tools for scanning. - - name: Initialize CodeQL - uses: github/codeql-action/init@v2 - with: - languages: ${{ matrix.language }} - # If you wish to specify custom queries, you can do so here or in a config file. - # By default, queries listed here will override any specified in a config file. - # Prefix the list here with "+" to use these queries and those in the config file. - # queries: ./path/to/local/query, your-org/your-repo/queries@main - - # Autobuild attempts to build any compiled languages (C/C++, C#, or Java). - # If this step fails, then you should remove it and run the build manually (see below) - - name: Autobuild - uses: github/codeql-action/autobuild@v2 - - # ℹ️ Command-line programs to run using the OS shell. - # 📚 https://git.io/JvXDl - - # ✏️ If the Autobuild fails above, remove it and uncomment the following three lines - # and modify them (or add more) to build your code if your project - # uses a compiled language - - #- run: | - # make bootstrap - # make release - - - name: Perform CodeQL Analysis - uses: github/codeql-action/analyze@v2 diff --git a/bcipy/helpers/session.py b/bcipy/helpers/session.py index 071f8cd12..a690f438e 100644 --- a/bcipy/helpers/session.py +++ b/bcipy/helpers/session.py @@ -12,8 +12,10 @@ from openpyxl.chart import BarChart, Reference from openpyxl.styles import PatternFill from openpyxl.styles.borders import BORDER_THIN, Border, Side -from openpyxl.styles.colors import BLACK, WHITE, YELLOW - +from openpyxl.styles.colors import COLOR_INDEX +BLACK = COLOR_INDEX[0] +WHITE = COLOR_INDEX[1] +YELLOW = COLOR_INDEX[5] from bcipy.config import (BCIPY_ROOT, DEFAULT_ENCODING, DEFAULT_PARAMETER_FILENAME, EXPERIMENT_DATA_FILENAME, SESSION_DATA_FILENAME, SESSION_SUMMARY_FILENAME) diff --git a/bcipy/helpers/system_utils.py b/bcipy/helpers/system_utils.py index 9b3c6b2cf..268bfc008 100644 --- a/bcipy/helpers/system_utils.py +++ b/bcipy/helpers/system_utils.py @@ -169,6 +169,7 @@ def get_system_info() -> dict: screen_info = get_screen_info() info = get_cpu_info() gpu_info = get_gpu_info() + return { 'os': sys.platform, 'py_version': sys.version, @@ -182,7 +183,6 @@ def get_system_info() -> dict: 'processor': platform.processor(), 'cpu_count': os.cpu_count(), 'cpu_brand': info['brand_raw'], - 'cpu_hz': info['hz_actual_friendly'], 'gpu_available': torch.cuda.is_available(), 'gpu_count': len(gpu_info), 'gpu_details': gpu_info, diff --git a/requirements.txt b/requirements.txt index c857299d4..9b423b689 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,12 +3,12 @@ transformers==4.26.0 torch==2.0.0 construct==2.8.14 mne==1.0.2 -pyo==1.0.4 +pyo==1.0.5 pygame==2.1.2 pyglet<=1.5.27,>=1.4 PsychoPy==2023.2.1 -openpyxl==2.6.3 -numpy==1.20.3 +openpyxl==3.1.2 +numpy==1.25.2 sounddevice==0.4.4 SoundFile==0.12.1 scipy==1.10.1 @@ -19,7 +19,7 @@ pylsl==1.16 pandas==1.5.3 psutil==5.7.2 Pillow==9.4.0 -py-cpuinfo==7.0.0 +py-cpuinfo==9.0.0 pyedflib==0.1.34 PyQt6==6.6.0 pywavelets==1.4.1 diff --git a/scripts/shell/m2chip_install.sh b/scripts/shell/m2chip_install.sh new file mode 100644 index 000000000..c706ea2c6 --- /dev/null +++ b/scripts/shell/m2chip_install.sh @@ -0,0 +1,32 @@ +"""Mac M2 install script. + +This script is intended to be run from the root of the BciPy repository. It may work for M1 chips, but +this has not been tested and may require use of Rosetta 2. + +This script will install the necessary dependencies for the M2 chip on a Mac. It will also install +the psychopy version that is compatible with the M2 chip (no deps). This script assumes that you have homebrew +installed. If you do not, please install it before running this script. + +This script will install the following dependencies manually or via homebrew: + - hdf5 + - portaudio + - pyaudio + - pyo + - psychopy + +This script will also install the kenlm package with the max_order=12 option. This is necessary for +the language model and tests to run. +""" + +xcode-select --install +brew install hdf5 +brew install portaudio +# also make sure the path is correct/exported in .zprofile or .bash_profile +export HDF5_DIR=/opt/homebrew/opt/hdf5 +# portaudio installation for soundfile and pyo +python -m pip install pyaudio +# your path may be different to the portaudio version +pip install --global-option='build_ext' --global-option='-I/usr/local/Cellar/portaudio/19.7.0/include' --global-option='-L/usr/local/Cellar/portaudio/19.7.0/lib' pyo +pip install Psychopy==2023.2.1 --no-deps # install psychopy without dependencies +pip install -e . +pip install kenlm==0.1 --global-option="--max_order=12" # install kenlm with max_order=12 for language model. Not required for BciPy to run in most places. \ No newline at end of file From 93ad08bb7870228a45e03fd9125ed9249666f8b2 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 31 Oct 2023 18:15:44 -0700 Subject: [PATCH 135/330] updating the CHANGELOG, downgrade the numpy version for 3.8 --- CHANGELOG.md | 2 +- requirements.txt | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 381298c39..a5f297b57 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -14,7 +14,7 @@ Our last release candidate before the official 2.0 release! - Parameters - Add a Range type parameter #285 - Cleanup - - Change default log level to INFO to prevent too many messages in the experiment logs #288 + - Change default log level to INFO to prevent too many messages in the experiment logs #288 Upgrade requirements for m1/2 chips #299/#300 # 2.0.0-rc.3 diff --git a/requirements.txt b/requirements.txt index 9b423b689..fd04a9186 100644 --- a/requirements.txt +++ b/requirements.txt @@ -8,7 +8,7 @@ pygame==2.1.2 pyglet<=1.5.27,>=1.4 PsychoPy==2023.2.1 openpyxl==3.1.2 -numpy==1.25.2 +numpy==1.24.4 sounddevice==0.4.4 SoundFile==0.12.1 scipy==1.10.1 From fba45ed618a83a9f3e46283909be8c31a0f9c434 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 31 Oct 2023 18:24:21 -0700 Subject: [PATCH 136/330] fix option assignment --- bcipy/gui/file_dialog.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/bcipy/gui/file_dialog.py b/bcipy/gui/file_dialog.py index f54ee2881..8c5247b12 100644 --- a/bcipy/gui/file_dialog.py +++ b/bcipy/gui/file_dialog.py @@ -25,8 +25,7 @@ def __init__(self): # The native dialog may prevent the selection from closing after a # directory is selected. - self.options = QFileDialog.Options() - self.options |= QFileDialog.DontUseNativeDialog + self.options = QFileDialog.Option(3) def ask_file(self, file_types: str = DEFAULT_FILE_TYPES, directory: str = "") -> str: """Opens a file dialog window. From 2fa0e248fef386375cfb7dcf539c10a3baaac9d4 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Wed, 1 Nov 2023 16:30:34 -0400 Subject: [PATCH 137/330] New visualization method added --- bcipy/helpers/visualization.py | 119 +++++++++++++++++- .../parameters/symbol_positions.json | 0 bcipy/signal/model/offline_analysis.py | 34 +++-- 3 files changed, 144 insertions(+), 9 deletions(-) rename symbol_positions.json => bcipy/parameters/symbol_positions.json (100%) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 36a64bbc5..63ab10ce5 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -320,8 +320,6 @@ def visualize_gaze_inquiries( ell.set_alpha(0.5) ax.add_artist(ell) - # ax.scatter(means[:,0], means[:,1], c='yellow', s=20, marker='^') - ax.set_xticks([]) ax.set_yticks([]) ax.set_xticklabels([]) @@ -429,6 +427,123 @@ def visualize_centralized_data( return fig +def visualize_results_all_symbols( + left_eye_all: List[np.ndarray], + right_eye_all: List[np.ndarray], + means_all: List[np.ndarray], + covs_all: List[np.ndarray], + save_path: Optional[str] = None, + show: Optional[bool] = False, + img_path: Optional[str] = None, + screen_size: Tuple[int, int] = (1920, 1080), + heatmap: Optional[bool] = False, + raw_plot: Optional[bool] = False) -> Figure: + """Visualize results for all symbols. + + Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default + image used is for the matrix calibration task on a 1920x1080 screen. + + Generates a comparative matrix figure following the execution of offline analysis. Given a set of + trailed data (left & right eye), the gaze distribution for all prompted symbols are shown in a + single image, along with mean-cov contours of gaze distribution with respect to each symbol. + The figures may be saved or shown in a window. + + Returns a list of the figure handles created. + + Parameters + ---------- + left_eye: (np.ndarray): Data array for the left eye data. + right_eye: (np.ndarray): Data array for the right eye data. + means: Optional[np.ndarray]: Means of the Gaussian Mixture Model + covs: Optional[np.ndarray]: Covariances of the Gaussian Mixture Model + save_path: Optional[str]: optional path to a save location of the figure generated + show: Optional[bool]: whether or not to show the figures generated. Default: False + img_path: Optional[str]: Image to be used as the background. Default: matrix.png + screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy + Phrase tasks. + Default: (1920, 1080) + heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False + raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False + """ + + title = 'Map of Gaze Data and Contours ' + + if img_path is None: + img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img = plt.imread(img_path) + + # scale the eye data to the image + fig, ax = plt.subplots() + ax.imshow(img, extent=[0, 1, 0, 1]) + + for _, (left_eye, right_eye, means, covs) in enumerate(zip(left_eye_all, right_eye_all, means_all, covs_all)): + # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis + lx = np.clip(left_eye[:, 0], 0, 1) + ly = np.clip(left_eye[:, 1], 0, 1) + rx = np.clip(right_eye[:, 0], 0, 1) + ry = np.clip(right_eye[:, 1], 0, 1) + ly = 1 - ly + ry = 1 - ry + + if means is not None: + means[:, 0] = np.clip(means[:, 0], 0, 1) + means[:, 1] = np.clip(means[:, 1], 0, 1) + + if heatmap: + # create a dataframe making a column for each x, y pair for both eyes and + # a column for the eye (left or right) + df = pd.DataFrame({ + 'x': np.concatenate((lx, rx)), + 'y': np.concatenate((ly, ry)), + 'eye': ['left'] * len(lx) + ['right'] * len(rx) + }) + ax = sns.kdeplot( + data=df, + hue='eye', + x='x', + y='y', + fill=False, + thresh=0.05, + levels=10, + cmap="mako", + colorbar=True) + + if raw_plot: + # ax.scatter(lx, ly, c='lightcoral', s=1) + ax.scatter(rx, ry, c='bisque', s=1) + + if means is not None: + for i, (mean, cov) in enumerate(zip(means, covs)): + v, w = linalg.eigh(cov) + v = 2.0 * np.sqrt(2.0) * np.sqrt(v) + u = w[0] / linalg.norm(w[0]) + + # Plot an ellipse to show the Gaussian component + angle = np.arctan(u[1] / u[0]) + angle = 180.0 * angle / np.pi # convert to degrees + ell = Ellipse(mean, v[0], v[1], angle=180.0 + angle, color='navy') + ell.set_clip_box(ax) + ell.set_alpha(0.5) + ax.add_artist(ell) + + ax.set_xticks([]) + ax.set_yticks([]) + ax.set_xticklabels([]) + ax.set_yticklabels([]) + + plt.title(f'{title}Plot') + + if save_path is not None: + plt.savefig(f"{save_path}/{title.lower().replace(' ', '_')}plot.png", dpi=fig.dpi) + + if show: + plt.show() + else: + plt.close() + + return fig + + def plot_edf(edf_path: str, auto_scale: Optional[bool] = False): """Plot data from the raw edf file. Note: this works from an iPython session but seems to throw errors when provided in a script. diff --git a/symbol_positions.json b/bcipy/parameters/symbol_positions.json similarity index 100% rename from symbol_positions.json rename to bcipy/parameters/symbol_positions.json diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 8bc967c2d..9e5746c49 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -9,7 +9,7 @@ from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices -from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, ROOT, +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH, STATIC_IMAGES_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename @@ -22,7 +22,8 @@ from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import (visualize_erp, visualize_gaze, - visualize_gaze_inquiries, visualize_centralized_data) + visualize_gaze_inquiries, visualize_centralized_data, + visualize_results_all_symbols) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata from bcipy.signal.model.fusion_model import GazeModel, GazeModel_AllSymbols @@ -97,8 +98,6 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance """ # Extract relevant session information from parameters file trial_window = parameters.get("trial_window") - # This parameter does not exist in parameters files for Multimodal datasets. Adding manually. - # TODO: Update parameters files for multimodal datasets. if trial_window is None: trial_window = [0.0, 0.5] window_length = trial_window[1] - trial_window[0] @@ -307,6 +306,11 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f centralized_data_left = [] centralized_data_right = [] test_dict = {} + + left_eye_all = [] + right_eye_all = [] + means_all = [] + covs_all = [] for sym in symbol_set: le = preprocessed_data[sym][0] re = preprocessed_data[sym][1] @@ -321,7 +325,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f # Centralize the data using symbol positions: # Load json file. # TODO: move this to a helper function, or get the symbol positions from the build_grid method - with open(f"{ROOT}/symbol_positions.json", 'r') as params_file: + with open(f"{DEFAULT_PARAMETERS_PATH}/symbol_positions.json", 'r') as params_file: symbol_positions = json.load(params_file) # Subtract the symbol positions from the data: centralized_data_left.append(model.reshaper.centralize_all_data(train_le, symbol_positions[sym])) @@ -342,6 +346,10 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f show=show_figures, raw_plot=True, ) + left_eye_all.append(le) + right_eye_all.append(re) + means_all.append(means) + covs_all.append(covs) if model_type == "Centralized": # Model 2: Fit Gaussian mixture (comp=1) on a centralized data @@ -374,6 +382,18 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f show=show_figures, raw_plot=True, ) + left_eye_all.append(le) + right_eye_all.append(re) + means_all.append(means) + covs_all.append(covs) + + fig_handles = visualize_results_all_symbols( + left_eye_all, right_eye_all, + means_all, covs_all, + save_path=None, + show=True, + raw_plot=True, + ) model.metadata = SignalModelMetadata(device_spec=device_spec, transform=None) @@ -445,7 +465,7 @@ def offline_analysis( if device_spec.content_type == "Eyetracker": analyze_gaze(raw_data, device_spec, data_folder, save_figures, show_figures, - model_type="Centralized") + model_type="Individual") if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") @@ -466,7 +486,7 @@ def offline_analysis( parser.set_defaults(alert=False) parser.set_defaults(balanced=False) parser.set_defaults(save_figures=False) - parser.set_defaults(show_figures=True) + parser.set_defaults(show_figures=False) args = parser.parse_args() log.info(f"Loading params from {args.parameters_file}") From 6df9ee8ae83402f693e856a3972536dd1992dff1 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 6 Nov 2023 12:12:23 -0500 Subject: [PATCH 138/330] Offline analysis bug fix --- bcipy/helpers/visualization.py | 1 + bcipy/signal/model/offline_analysis.py | 36 +++++++++++++------------- 2 files changed, 19 insertions(+), 18 deletions(-) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 63ab10ce5..e1ff25ea2 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -488,6 +488,7 @@ def visualize_results_all_symbols( if means is not None: means[:, 0] = np.clip(means[:, 0], 0, 1) means[:, 1] = np.clip(means[:, 1], 0, 1) + means[:, 1] = 1 - means[:, 1] if heatmap: # create a dataframe making a column for each x, y pair for both eyes and diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 9e5746c49..0aa5746cd 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -9,7 +9,7 @@ from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices -from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, BCIPY_ROOT, DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH, STATIC_IMAGES_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename @@ -325,7 +325,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f # Centralize the data using symbol positions: # Load json file. # TODO: move this to a helper function, or get the symbol positions from the build_grid method - with open(f"{DEFAULT_PARAMETERS_PATH}/symbol_positions.json", 'r') as params_file: + with open(f"{BCIPY_ROOT}/parameters/symbol_positions.json", 'r') as params_file: symbol_positions = json.load(params_file) # Subtract the symbol positions from the data: centralized_data_left.append(model.reshaper.centralize_all_data(train_le, symbol_positions[sym])) @@ -339,13 +339,13 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f scores, means, covs = model.get_scores(test_re) # Visualize the results: - figure_handles = visualize_gaze_inquiries( - le, re, - means, covs, - save_path=None, - show=show_figures, - raw_plot=True, - ) + # figure_handles = visualize_gaze_inquiries( + # le, re, + # means, covs, + # save_path=None, + # show=show_figures, + # raw_plot=True, + # ) left_eye_all.append(le) right_eye_all.append(re) means_all.append(means) @@ -375,13 +375,13 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f le = preprocessed_data[sym][0] re = preprocessed_data[sym][1] # Visualize the results: - figure_handles = visualize_gaze_inquiries( - le, re, - means, covs, - save_path=None, - show=show_figures, - raw_plot=True, - ) + # figure_handles = visualize_gaze_inquiries( + # le, re, + # means, covs, + # save_path=None, + # show=show_figures, + # raw_plot=True, + # ) left_eye_all.append(le) right_eye_all.append(re) means_all.append(means) @@ -465,7 +465,7 @@ def offline_analysis( if device_spec.content_type == "Eyetracker": analyze_gaze(raw_data, device_spec, data_folder, save_figures, show_figures, - model_type="Individual") + model_type="Centralized") if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") @@ -486,7 +486,7 @@ def offline_analysis( parser.set_defaults(alert=False) parser.set_defaults(balanced=False) parser.set_defaults(save_figures=False) - parser.set_defaults(show_figures=False) + parser.set_defaults(show_figures=True) args = parser.parse_args() log.info(f"Loading params from {args.parameters_file}") From c2f23aec85882092a66c1727184872382cf5b195 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Mon, 6 Nov 2023 12:15:24 -0500 Subject: [PATCH 139/330] Linting --- bcipy/signal/model/offline_analysis.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 0aa5746cd..100c34c64 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -22,7 +22,7 @@ from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import (visualize_erp, visualize_gaze, - visualize_gaze_inquiries, visualize_centralized_data, + visualize_centralized_data, visualize_results_all_symbols) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata From 3b94689779bc73b89f793436c98a0f42054fa52b Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 6 Nov 2023 11:44:35 -0800 Subject: [PATCH 140/330] VEP display changes for presenting a target and animating symbols into boxes --- .../display/demo/vep/demo_calibration_vep.py | 11 +- bcipy/display/main.py | 4 +- bcipy/display/paradigm/vep/display.py | 128 ++++++++++++------ bcipy/display/paradigm/vep/layout.py | 29 +++- 4 files changed, 120 insertions(+), 52 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index cec8e652d..da951a650 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -57,8 +57,9 @@ stim_pos=box_config.positions, stim_height=0.1, stim_font=font, - timing=[1, 0.5, 4], # prompt, fixation, stimuli + timing=[4, 0.5, 4], # target, fixation, stimuli stim_length=1, # how many times to stimuli + animation_seconds=1.0 ) task_bar = CalibrationTaskBar(win, inquiry_count=4, @@ -107,10 +108,10 @@ timing += vep.do_inquiry() # show the wait screen, this will only happen once - while wait_seconds > 0: - wait_seconds -= 1 - vep.wait_screen(f"Waiting for {wait_seconds}s", color='white') - core.wait(1) + # while wait_seconds > 0: + # wait_seconds -= 1 + # vep.wait_screen(f"Waiting for {wait_seconds}s", color='white') + # core.wait(1) print(timing) win.close() diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 8512fb98d..ce2cf7b95 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -272,7 +272,8 @@ def __init__( timing: Tuple[float, float, float] = None, stim_color: List[List[str]] = None, inquiry: List[List[str]] = None, - stim_length: int = 1): + stim_length: int = 1, + animation_seconds: float = 1.0): """Initialize VEP Stimuli Parameters. stim_color(List[str]): Ordered list of colors to apply to VEP stimuli stim_font(str): Font to apply to all VEP stimuli @@ -292,6 +293,7 @@ def __init__( # dynamic properties, must be a a list of lists where each list is a different box self.stim_colors = stim_color self.stim_inquiry = inquiry + self.animation_seconds = animation_seconds def build_init_stimuli(self, window: visual.Window) -> None: """"Build Initial Stimuli.""" diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 157ce838f..65d5bb35c 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -12,7 +12,8 @@ from bcipy.display.components.layout import envelope, scaled_size from bcipy.display.components.task_bar import TaskBar from bcipy.display.paradigm.matrix.layout import symbol_positions -from bcipy.display.paradigm.vep.layout import BoxConfiguration, checkerboard +from bcipy.display.paradigm.vep.layout import (BoxConfiguration, + animation_path, checkerboard) from bcipy.helpers.clock import Clock from bcipy.helpers.list import expanded from bcipy.helpers.stimuli import resize_image @@ -151,17 +152,18 @@ def __init__( self.stimuli_colors = stimuli.stim_colors self.stimuli_timing = stimuli.stim_timing self.timing_prompt, self.timing_fixation, self.timing_stimuli = stimuli.stim_timing - self.timing_animation = 2 + self.timing_animation = stimuli.animation_seconds self.stimuli_font = stimuli.stim_font self.stimuli_height = stimuli.stim_height self.stimuli_pos = stimuli.stim_pos + self.logger.info(self.stimuli_pos) self.stim_length = stimuli.stim_length - self.logger.info(self.stimuli_pos) - self.check_configuration() + self.should_prompt_target = should_prompt_target self.symbol_set = symbol_set or alphabet() self.sort_order = self.symbol_set.index + self.check_configuration() # Build starting list of symbols display_container = layout.centered(parent=self.window, width_pct=0.7) @@ -195,6 +197,7 @@ def __init__( # build the VEP stimuli if not codes: codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) + self.logger.info(f"VEP Codes: {codes}") vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] vep_stim_size = scaled_size(0.2, self.window_size) self.vep = self.build_vep_stimuli(positions=box_config.positions, @@ -204,7 +207,15 @@ def __init__( num_squares=25) self.text_boxes = self._build_text_boxes(box_config) - self.should_prompt_target = should_prompt_target + + @property + def box_colors(self) -> List[str]: + """Get the colors used for boxes""" + if self.should_prompt_target: + [_target_color, _fixation_color, *colors] = self.stimuli_colors + else: + [_fixation_color, *colors] = self.stimuli_colors + return colors def check_configuration(self): """Check that configured properties are consistent""" @@ -212,16 +223,6 @@ def check_configuration(self): self.stimuli_pos) == self.vep_type, ( f"stimuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}") - def do_fixation(self, fixation: StimProps) -> None: - """Draw fixation cross""" - duration = fixation.duration or self.timing_fixation - self.fixation.text = fixation.symbol - self.fixation.color = fixation.color - self.fixation.draw() - self.draw_static() - self.window.flip() - core.wait(duration) - def stim_properties(self) -> List[StimProps]: """Returns a tuple of (symbol, duration, and color) for each stimuli, including the target and fixation stim. Stimuli that represent VEP @@ -244,11 +245,16 @@ def do_inquiry(self) -> List[float]: if self.first_run: self._trigger_pulse() + self._reset_text_boxes() + self.reset_symbol_positions() + if self.should_prompt_target: [target, fixation, *stim] = self.stim_properties() + self.set_stimuli_colors(stim) self.prompt_target(target) else: [fixation, *stim] = self.stim_properties() + self.set_stimuli_colors(stim) # fixation --> animation / prompting --> VEP stimulate self.do_fixation(fixation) @@ -261,6 +267,10 @@ def do_inquiry(self) -> List[float]: return self._timing + def starting_position(self, sym: str) -> Tuple[float, float]: + """Get the starting position for the given symbol""" + pos_index = self.sort_order(sym) + return self.starting_positions[pos_index] def prompt_target(self, target: StimProps) -> float: """Present the target for the configured length of time. Records the @@ -270,17 +280,48 @@ def prompt_target(self, target: StimProps) -> float: ---------- target - (symbol, duration, color) tuple """ - # register any timing and marker callbacks + + # Show all symbols in the matrix at reduced opacity + for sym in self.symbol_set: + pos_index = self.sort_order(sym) + sti = self.sti[sym] + sti.pos = self.starting_positions[pos_index] + sti.setOpacity(0.25) + sti.draw() + self.draw_static() + self.draw_boxes() + + # pause for a time + self.window.flip() + core.wait(target.duration / 2) + + # highlight target self.window.callOnFlip(self.add_timing, target.symbol) - stim = visual.TextStim(self.window, - text=target.symbol, - color=target.color, - height=self.stimuli_height, - pos=[0, 0]) - stim.draw() + target_stim = self.sti[target.symbol] + target_stim.setOpacity(1) + + for sti in self.sti.values(): + sti.draw() + self.draw_static() + self.draw_boxes() + self.window.flip() - core.wait(target.duration) + core.wait(target.duration / 2) + + def do_fixation(self, fixation: StimProps) -> None: + """Show all boxes at full opacity before animating.""" + duration = fixation.duration or self.timing_fixation + + for sym in self.symbol_set: + sti = self.sti[sym] + sti.setOpacity(1.0) + sti.draw() + + self.draw_static() + self.draw_boxes() + self.window.flip() + core.wait(duration) def animate_inquiry(self, stimuli: List[StimProps]) -> None: """Display the inquiry. @@ -290,10 +331,8 @@ def animate_inquiry(self, stimuli: List[StimProps]) -> None: """ self.window.callOnFlip(self.add_timing, 'VEP_INQ_ANIMATION') - self._reset_text_boxes() - self.reset_symbol_positions() self.set_stimuli_colors(stimuli) - self.draw_animation() + self.draw_animation(stimuli) self._set_inquiry(stimuli) self.window.callOnFlip(self.add_timing, 'VEP_INQUIRY') @@ -310,22 +349,31 @@ def set_stimuli_colors(self, stim_groups: List[StimProps]) -> None: for sym in group.symbol: self.sti[sym].color = group.color - def draw_animation(self) -> None: + def draw_animation(self, stimuli: List[StimProps]) -> None: """Draw the stimuli animation. - TODO: animate the symbols moving to their end positions - - determine the number of frames in self.timing_animation seconds - - calculate end positions for each symbol (using symbol_positions with each box as the layout) - - compute the intermediate positions (line trajectory of each symbol) - - update position on each tick + Parameters + ---------- + stimuli - information about each symbol's destination. """ + frames = int(self.refresh_rate * self.timing_animation) + # Compute intermediate positions + animation_paths = {} + for i, stim_props in enumerate(stimuli): + end_pos = self.text_boxes[i].pos + for sym in stim_props.symbol: + start_pos = self.starting_position(sym) + animation_paths[sym] = animation_path(start_pos, end_pos, frames) + self.static_clock.reset() while self.static_clock.getTime() < self.timing_animation: - self.draw_boxes() - for sti in self.sti.values(): - sti.draw() - self.draw_static() - self.window.flip() + for frame in range(frames): + self.draw_boxes() + for sym, sti in self.sti.items(): + sti.pos = animation_paths[sym][frame] + sti.draw() + self.draw_static() + self.window.flip() def draw_boxes(self) -> None: """Draw the text boxes under VEP stimuli.""" @@ -344,10 +392,10 @@ def stimulate(self) -> None: self.static_clock.reset() while self.static_clock.getTime() < self.timing_stimuli: for frame in range(self.refresh_rate): + self.draw_boxes() for stim in self.vep: stim.render_frame(frame) - self.draw_boxes() # self.draw_static() self.window.flip() ended_at = self.static_clock.getTime() @@ -476,10 +524,10 @@ def _build_text_boxes(self, box_config: BoxConfiguration) -> List[visual.TextBox size=size, alignment='center', anchor='center', - borderWidth=2, + borderWidth=4, borderColor=color, letterHeight=self.stimuli_height) - for pos, color in zip(positions, cycle(self.stimuli_colors)) + for pos, color in zip(positions, cycle(self.box_colors)) ] def _reset_text_boxes(self) -> None: diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index c89af8308..142fd444b 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -165,9 +165,26 @@ def positions(self) -> List[Tuple]: left = right_of(layout.left, width / 2) right = left_of(layout.right, width / 2) - positions = [(left, top), (right, top), (left, bottom), - (right, bottom)] - if self.num_boxes == 6: - positions += [(layout.horizontal_middle, top), - (layout.horizontal_middle, bottom)] - return positions + + if self.num_boxes == 4: + return [(left, top), (right, top), (left, bottom), (right, bottom)] + + middle = layout.horizontal_middle + return [(left, top), (middle, top), (right, top), + (left, bottom), (middle, bottom), (right, bottom)] + + +def animation_path(start_pos: Tuple[float, float], end_pos: Tuple[float, + float], + frames: int) -> List[Tuple[float, float]]: + """Computes the animation path from start_pos to end_pos""" + x1, y1 = start_pos + x2, y2 = end_pos + xdiff = x2 - x1 + ydiff = y2 - y1 + positions = [] + for i in range(frames): + from_start = (i + 1) / frames + pos = (x1 + (from_start * xdiff), y1 + (from_start * ydiff)) + positions.append(pos) + return positions \ No newline at end of file From 0956e74c29aef1e0627261cb21e5b8dfd8754f0e Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 6 Nov 2023 15:42:41 -0800 Subject: [PATCH 141/330] Added code to highlight the box with the target symbol and de-emphasize the rest --- .../display/demo/vep/demo_calibration_vep.py | 2 +- bcipy/display/paradigm/vep/display.py | 56 +++++++++++++++---- 2 files changed, 46 insertions(+), 12 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index da951a650..7a6da066b 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -48,7 +48,7 @@ ] layout = centered(width_pct=0.95, height_pct=0.80) -box_config = BoxConfiguration(layout, num_boxes=num_boxes) +box_config = BoxConfiguration(layout, num_boxes=num_boxes, height_pct=0.30) experiment_clock = Clock() len_stimuli = 10 diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 65d5bb35c..a7fd098a8 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -199,13 +199,13 @@ def __init__( codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) self.logger.info(f"VEP Codes: {codes}") vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] - vep_stim_size = scaled_size(0.2, self.window_size) + vep_stim_size = scaled_size(0.24, self.window_size) self.vep = self.build_vep_stimuli(positions=box_config.positions, codes=codes, colors=cycle(vep_colors), stim_size=vep_stim_size, num_squares=25) - + self.box_border_width = 4 self.text_boxes = self._build_text_boxes(box_config) @property @@ -237,6 +237,13 @@ def stim_properties(self) -> List[StimProps]: self.stimuli_colors) ] + def box_index(self, stim_groups: List[StimProps], sym: str) -> int: + """Box index for the given symbol""" + for i, group in enumerate(stim_groups): + if sym in group.symbol: + return i + raise Exception(f"Symbol not found: {sym}") + def do_inquiry(self) -> List[float]: """Do the inquiry.""" self.reset_timing() @@ -251,14 +258,14 @@ def do_inquiry(self) -> List[float]: if self.should_prompt_target: [target, fixation, *stim] = self.stim_properties() self.set_stimuli_colors(stim) - self.prompt_target(target) + self.prompt_target(target, target_box_index=self.box_index(stim, target.symbol)) else: [fixation, *stim] = self.stim_properties() self.set_stimuli_colors(stim) - # fixation --> animation / prompting --> VEP stimulate - self.do_fixation(fixation) + # self.do_fixation(fixation) self.animate_inquiry(stim) + core.wait(self.timing_fixation) self.stimulate() # clear everything expect static stimuli @@ -272,7 +279,7 @@ def starting_position(self, sym: str) -> Tuple[float, float]: pos_index = self.sort_order(sym) return self.starting_positions[pos_index] - def prompt_target(self, target: StimProps) -> float: + def prompt_target(self, target: StimProps, target_box_index: int = None) -> float: """Present the target for the configured length of time. Records the stimuli timing information. @@ -286,7 +293,7 @@ def prompt_target(self, target: StimProps) -> float: pos_index = self.sort_order(sym) sti = self.sti[sym] sti.pos = self.starting_positions[pos_index] - sti.setOpacity(0.25) + sti.setOpacity(0.5) sti.draw() self.draw_static() self.draw_boxes() @@ -303,25 +310,50 @@ def prompt_target(self, target: StimProps) -> float: for sti in self.sti.values(): sti.draw() + if target_box_index: + self.highlight_target_box(target_box_index) + self.draw_static() self.draw_boxes() self.window.flip() core.wait(target.duration / 2) + def highlight_target_box(self, target_box_index: int) -> None: + """Emphasize the box at the given index""" + for i, box in enumerate(self.text_boxes): + if i == target_box_index: + box.borderWidth = self.box_border_width + 4 + box.setOpacity(1.0) + else: + box.borderWidth = self.box_border_width - 2 + box.setOpacity(0.8) + def do_fixation(self, fixation: StimProps) -> None: - """Show all boxes at full opacity before animating.""" + """Show all symbols before animating.""" duration = fixation.duration or self.timing_fixation + starting_opacity = {} for sym in self.symbol_set: sti = self.sti[sym] + starting_opacity[sym] = sti.opacity sti.setOpacity(1.0) sti.draw() + self.draw_static() + self.draw_boxes() + self.window.flip() + core.wait(duration / 2) + # reset to starting opacity + for sym in self.symbol_set: + sti = self.sti[sym] + sti.setOpacity(starting_opacity[sym]) + sti.draw() self.draw_static() self.draw_boxes() self.window.flip() - core.wait(duration) + core.wait(duration / 2) + def animate_inquiry(self, stimuli: List[StimProps]) -> None: """Display the inquiry. @@ -340,7 +372,7 @@ def animate_inquiry(self, stimuli: List[StimProps]) -> None: self.draw_boxes() self.draw_static() self.window.flip() - core.wait(self.timing_prompt) + def set_stimuli_colors(self, stim_groups: List[StimProps]) -> None: """Update the colors of the stimuli associated with each symbol to @@ -524,7 +556,7 @@ def _build_text_boxes(self, box_config: BoxConfiguration) -> List[visual.TextBox size=size, alignment='center', anchor='center', - borderWidth=4, + borderWidth=self.box_border_width, borderColor=color, letterHeight=self.stimuli_height) for pos, color in zip(positions, cycle(self.box_colors)) @@ -537,6 +569,8 @@ def _reset_text_boxes(self) -> None: """ for text_box in self.text_boxes: text_box.setText(' ') + text_box.setOpacity(1.0) + text_box.borderWidth = self.box_border_width def _set_inquiry(self, stimuli: List[StimProps]) -> List[visual.TextBox2]: """Set the correct inquiry text for each text boxes. From 53724451436fadff2853fd2d4b64f820f3b80c10 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 13 Nov 2023 16:53:01 -0800 Subject: [PATCH 142/330] Fix typing issues --- bcipy/display/components/layout.py | 2 +- .../display/demo/vep/demo_calibration_vep.py | 104 ++++++++------ bcipy/display/main.py | 23 ++- bcipy/display/paradigm/vep/display.py | 136 ++++++++++-------- bcipy/display/paradigm/vep/layout.py | 5 +- 5 files changed, 149 insertions(+), 121 deletions(-) diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index 1ad8692a3..759d9eebd 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -121,7 +121,7 @@ def __init__(self, top: float = DEFAULT_TOP, right: float = DEFAULT_RIGHT, bottom: float = DEFAULT_BOTTOM, - units: float = "norm"): + units: str = "norm"): self.units = units self.parent = parent self.top = top diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 7a6da066b..f1289285c 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -1,7 +1,7 @@ +"""Demo VEP display""" import logging import sys - -from psychopy import core +from typing import Any, List from bcipy.display import (InformationProperties, VEPStimuliProperties, init_display_window) @@ -26,7 +26,7 @@ info_text=['VEP Display Demo'], ) -task_text = ['1/4', '2/4', '3/4', '4/4'] +task_text = ['1/3', '2/3', '3/3'] num_boxes = 6 window_parameters = { @@ -46,72 +46,88 @@ 'green', 'red', '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' ] - +codes = [[ + 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, + 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, + 0, 1, 0, 0, 1, 1, 1, 0, 1, 0 +], + [ + 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, + 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, + 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0 +], + [ + 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, + 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, + 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0 +], + [ + 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, + 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, + 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1 +], + [ + 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, + 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, + 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1 +], + [ + 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, + 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, + 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0 +]] layout = centered(width_pct=0.95, height_pct=0.80) box_config = BoxConfiguration(layout, num_boxes=num_boxes, height_pct=0.30) experiment_clock = Clock() len_stimuli = 10 stim_props = VEPStimuliProperties( - stim_color=stim_color, + stim_font=font, stim_pos=box_config.positions, stim_height=0.1, - stim_font=font, timing=[4, 0.5, 4], # target, fixation, stimuli + stim_color=stim_color, + inquiry=[], stim_length=1, # how many times to stimuli - animation_seconds=1.0 -) -task_bar = CalibrationTaskBar(win, - inquiry_count=4, - current_index=0, - font=font) + animation_seconds=1.0) +task_bar = CalibrationTaskBar(win, inquiry_count=3, current_index=0, font=font) vep = VEPDisplay(win, experiment_clock, stim_props, task_bar, info, box_config=box_config, + codes=codes, should_prompt_target=True) wait_seconds = 2 -inquiries = [['U', - '+', - ['C', 'M', 'S'], - ['D', 'P', 'X', '_'], - ['L', 'U', 'Y'], - ['E', 'K', 'O'], - ['<', 'A', 'F', 'H', 'I', 'J', 'N', 'Q', 'R', 'V', 'Z'], - ['B', 'G', 'T', 'W']], - ['D', - '+', - ['O', 'X'], - ['D'], - ['P', 'U'], - ['<', 'B', 'E', 'G', 'H', 'J', 'K', 'L', 'R', 'T'], - ['A', 'C', 'F', 'I', 'M', 'N', 'Q', 'V', 'Y', '_'], - ['S', 'W', 'Z']], - ['S', - '+', - ['A', 'J', 'K', 'T', 'V', 'W'], - ['S'], - ['_'], - ['E', 'G', 'M', 'R'], - ['<', 'B', 'C', 'D', 'H', 'I', 'L', 'N', 'O', 'P', 'Q', 'U', 'X', 'Z'], - ['F', 'Y']]] +inquiries: List[List[Any]] = [[ + 'U', '+', ['C', 'M', 'S'], ['D', 'P', 'X', '_'], ['L', 'U', 'Y'], + ['E', 'K', 'O'], ['<', 'A', 'F', 'H', 'I', 'J', 'N', 'Q', 'R', 'V', 'Z'], + ['B', 'G', 'T', 'W'] +], + [ + 'D', '+', ['O', 'X'], ['D'], ['P', 'U'], + ['<', 'B', 'E', 'G', 'H', 'J', 'K', 'L', 'R', 'T'], + ['A', 'C', 'F', 'I', 'M', 'N', 'Q', 'V', 'Y', '_'], + ['S', 'W', 'Z'] +], + [ + 'S', '+', ['A', 'J', 'K', 'T', 'V', 'W'], ['S'], ['_'], + ['E', 'G', 'M', 'R'], + [ + '<', 'B', 'C', 'D', 'H', 'I', 'L', 'N', 'O', 'P', 'Q', + 'U', 'X', 'Z' + ], ['F', 'Y'] +]] timing = [] # loop over the text and colors, present the stimuli and record the timing for i, txt in enumerate(task_text): vep.update_task_bar(txt) - - vep.schedule_to(stimuli=inquiries[i]) + inq = inquiries[i] + vep.schedule_to(stimuli=inq) timing += vep.do_inquiry() - # show the wait screen, this will only happen once - # while wait_seconds > 0: - # wait_seconds -= 1 - # vep.wait_screen(f"Waiting for {wait_seconds}s", color='white') - # core.wait(1) - print(timing) win.close() diff --git a/bcipy/display/main.py b/bcipy/display/main.py index ce2cf7b95..df00651ca 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -1,6 +1,6 @@ from abc import ABC, abstractmethod from logging import Logger -from typing import List, Tuple, Union +from typing import Any, List, Tuple, Union from psychopy import visual @@ -32,7 +32,7 @@ def do_inquiry(self) -> List[float]: ... @abstractmethod - def wait_screen(self) -> None: + def wait_screen(self, *args, **kwargs) -> None: """Wait Screen. Define what happens on the screen when a user pauses a session. @@ -264,16 +264,15 @@ def __init__( class VEPStimuliProperties(StimuliProperties): - def __init__( - self, - stim_font: str, - stim_pos: List[Tuple[float, float]], - stim_height: float, - timing: Tuple[float, float, float] = None, - stim_color: List[List[str]] = None, - inquiry: List[List[str]] = None, - stim_length: int = 1, - animation_seconds: float = 1.0): + def __init__(self, + stim_font: str, + stim_pos: List[Tuple[float, float]], + stim_height: float, + timing: List[float], + stim_color: List[str], + inquiry: List[List[Any]], + stim_length: int = 1, + animation_seconds: float = 1.0): """Initialize VEP Stimuli Parameters. stim_color(List[str]): Ordered list of colors to apply to VEP stimuli stim_font(str): Font to apply to all VEP stimuli diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index a7fd098a8..ecabce8c2 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -1,6 +1,7 @@ import logging from itertools import cycle -from typing import List, NamedTuple, Optional, Tuple, Union +from typing import (Any, Dict, Iterable, List, NamedTuple, Optional, Tuple, + Union) import numpy as np from psychopy import core, visual @@ -20,6 +21,9 @@ from bcipy.helpers.symbols import alphabet from bcipy.helpers.triggers import _calibration_trigger +# Should only be two elements, but a list rather than a Tuple +StimTime = List[Union[str, float]] + def create_vep_codes(length=32, count=4) -> List[List[int]]: """Create a list of random VEP codes. @@ -32,12 +36,14 @@ def create_vep_codes(length=32, count=4) -> List[List[int]]: np.random.seed(1) return [np.random.randint(2, size=length) for _ in range(count)] + class StimProps(NamedTuple): """Represents properties of a single symbol (or stim box)""" symbol: Union[str, List[str]] duration: float color: str + class VEPStim: """Represents a checkerboard of squares that can be flashed at a given rate. Flashing is accomplished by inverting the colors of each square. @@ -126,25 +132,26 @@ def frame_off(self) -> None: class VEPDisplay(Display): """Display for VEP paradigm""" - def __init__( - self, - window: visual.Window, - experiment_clock: Clock, - stimuli: VEPStimuliProperties, - task_bar: TaskBar, - info: InformationProperties, - trigger_type: str = 'text', - symbol_set: Optional[List[str]] = None, - codes: List[int] = None, - box_config: BoxConfiguration = None, - should_prompt_target: bool = True): + def __init__(self, + window: visual.Window, + experiment_clock: Clock, + stimuli: VEPStimuliProperties, + task_bar: TaskBar, + info: InformationProperties, + box_config: BoxConfiguration, + trigger_type: str = 'text', + symbol_set: Optional[List[str]] = None, + codes: Optional[List[List[int]]] = None, + should_prompt_target: bool = True): self.window = window + frame_rate = self.window.getActualFrameRate() + assert frame_rate, 'An accurate window frame rate could not be established' self.window_size = self.window.size # [w, h] - self.refresh_rate = round(window.getActualFrameRate()) + self.refresh_rate = round(frame_rate) self.logger = logging.getLogger(__name__) # number of VEP text areas - self.vep_type = box_config.num_boxes + self.vep_type: int = box_config.num_boxes # Stimuli parameters, these are set on display in order to allow # easy updating after definition @@ -171,7 +178,7 @@ def __init__( rows=3, columns=10) self.logger.info( - f"Symbol starting positions ({display_container.units} units): {self.starting_positions}" + f"Symbol starting positions ({str(display_container.units)} units): {self.starting_positions}" ) self.fixation = self._build_fixation() @@ -181,24 +188,27 @@ def __init__( self.static_clock = core.Clock() # Trigger handling - self.first_stim_time = None + self.first_stim_time: Optional[float] = None self.trigger_type = trigger_type self.experiment_clock = experiment_clock - self._timing = [] + self._timing: List[StimTime] = [] # Callback used on presentation of first stimulus. self.first_run = True self.first_stim_callback = lambda _sti: None - self.size_list_sti = [] + # TODO: needed? + # self.size_list_sti = [] self.task_bar = task_bar self.info_text = info.build_info_text(window) # build the VEP stimuli if not codes: - codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) + codes = create_vep_codes(length=self.refresh_rate, + count=self.vep_type) self.logger.info(f"VEP Codes: {codes}") - vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] + vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), + ('orange', 'green')] vep_stim_size = scaled_size(0.24, self.window_size) self.vep = self.build_vep_stimuli(positions=box_config.positions, codes=codes, @@ -219,22 +229,23 @@ def box_colors(self) -> List[str]: def check_configuration(self): """Check that configured properties are consistent""" - assert len( - self.stimuli_pos) == self.vep_type, ( - f"stimuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}") + assert len(self.stimuli_pos) == self.vep_type, ( + f"stimuli position {len(self.stimuli_pos)} must be the same length as vep type {self.vep_type}" + ) def stim_properties(self) -> List[StimProps]: """Returns a tuple of (symbol, duration, and color) for each stimuli, including the target and fixation stim. Stimuli that represent VEP boxes will have a list of symbols.""" stim_num = len(self.stimuli_inquiry) - assert len(self.stimuli_colors) == stim_num, "Each box should have its own color" + assert len(self.stimuli_colors + ) == stim_num, "Each box should have its own color" return [ - StimProps(*props) - for props in zip(self.stimuli_inquiry, - expanded(list(self.stimuli_timing), length=stim_num), - self.stimuli_colors) + StimProps(*props) for props in zip( + self.stimuli_inquiry, + expanded(list(self.stimuli_timing), length=stim_num), + self.stimuli_colors) ] def box_index(self, stim_groups: List[StimProps], sym: str) -> int: @@ -244,7 +255,7 @@ def box_index(self, stim_groups: List[StimProps], sym: str) -> int: return i raise Exception(f"Symbol not found: {sym}") - def do_inquiry(self) -> List[float]: + def do_inquiry(self) -> List[StimTime]: # type: ignore """Do the inquiry.""" self.reset_timing() @@ -257,8 +268,11 @@ def do_inquiry(self) -> List[float]: if self.should_prompt_target: [target, fixation, *stim] = self.stim_properties() - self.set_stimuli_colors(stim) - self.prompt_target(target, target_box_index=self.box_index(stim, target.symbol)) + if isinstance(target.symbol, str): + self.set_stimuli_colors(stim) + self.prompt_target(target, + target_box_index=self.box_index( + stim, target.symbol)) else: [fixation, *stim] = self.stim_properties() self.set_stimuli_colors(stim) @@ -279,7 +293,9 @@ def starting_position(self, sym: str) -> Tuple[float, float]: pos_index = self.sort_order(sym) return self.starting_positions[pos_index] - def prompt_target(self, target: StimProps, target_box_index: int = None) -> float: + def prompt_target(self, + target: StimProps, + target_box_index: Optional[int] = None) -> None: """Present the target for the configured length of time. Records the stimuli timing information. @@ -287,7 +303,7 @@ def prompt_target(self, target: StimProps, target_box_index: int = None) -> floa ---------- target - (symbol, duration, color) tuple """ - + assert isinstance(target.symbol, str), "Target must be a str" # Show all symbols in the matrix at reduced opacity for sym in self.symbol_set: pos_index = self.sort_order(sym) @@ -354,7 +370,6 @@ def do_fixation(self, fixation: StimProps) -> None: self.window.flip() core.wait(duration / 2) - def animate_inquiry(self, stimuli: List[StimProps]) -> None: """Display the inquiry. @@ -373,7 +388,6 @@ def animate_inquiry(self, stimuli: List[StimProps]) -> None: self.draw_static() self.window.flip() - def set_stimuli_colors(self, stim_groups: List[StimProps]) -> None: """Update the colors of the stimuli associated with each symbol to reflect which box it will be placed in.""" @@ -395,7 +409,8 @@ def draw_animation(self, stimuli: List[StimProps]) -> None: end_pos = self.text_boxes[i].pos for sym in stim_props.symbol: start_pos = self.starting_position(sym) - animation_paths[sym] = animation_path(start_pos, end_pos, frames) + animation_paths[sym] = animation_path(start_pos, end_pos, + frames) self.static_clock.reset() while self.static_clock.getTime() < self.timing_animation: @@ -434,8 +449,8 @@ def stimulate(self) -> None: self.logger.debug( f"Expected stim time: {self.timing_stimuli}; actual run time: {ended_at}" ) - self.logger.debug(f"Average frame duration: {ended_at/self.timing_stimuli}") - + self.logger.debug( + f"Average frame duration: {ended_at/self.timing_stimuli}") def draw_static(self) -> None: """Draw static elements in a stimulus.""" @@ -475,7 +490,7 @@ def _build_fixation(self) -> visual.TextStim: height=self.stimuli_height, pos=[0, 0]) - def _build_inquiry_stimuli(self) -> List[visual.TextStim]: + def _build_inquiry_stimuli(self) -> Dict[str, visual.TextStim]: """Build the inquiry stimuli.""" grid = {} for sym in self.symbol_set: @@ -493,10 +508,9 @@ def reset_symbol_positions(self) -> None: pos_index = self.sort_order(sym) self.sti[sym].pos = self.starting_positions[pos_index] - def build_vep_stimuli(self, - positions: List[Tuple[float, float]], - codes: List[int], - colors: List[Tuple[str]], + def build_vep_stimuli(self, positions: List[Tuple[float, float]], + codes: List[List[int]], colors: Iterable[Tuple[str, + str]], stim_size: Tuple[float, float], num_squares: int) -> List[VEPStim]: """Build the VEP flashing checkerboards""" @@ -520,25 +534,28 @@ def _trigger_pulse(self) -> None: beginning of an experiment. If drift is detected in your experiment, more frequent pulses and offset correction may be required. """ - calibration_time = _calibration_trigger( + calibration_time: StimTime = _calibration_trigger( # type: ignore self.experiment_clock, trigger_type=self.trigger_type, display=self.window) # set the first stim time if not present and first_run to False if not self.first_stim_time: - self.first_stim_time = calibration_time[-1] + self.first_stim_time = calibration_time[-1] # type: ignore self.first_run = False - def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]] - = None, colors: List[List[str]] = None) -> None: + def schedule_to(self, + stimuli: List[List[Any]], + timing: Optional[List[List[float]]] = None, + colors: Optional[List[List[Any]]] = None) -> None: """Schedule stimuli elements (works as a buffer). """ - self.stimuli_inquiry = stimuli + self.stimuli_inquiry = stimuli # type: ignore assert timing is None or timing == self.stimuli_timing, "Timing values must match pre-configured values" assert colors is None or colors == self.stimuli_colors, "Colors must match the pre-configured values" - def _build_text_boxes(self, box_config: BoxConfiguration) -> List[visual.TextBox2]: + def _build_text_boxes( + self, box_config: BoxConfiguration) -> List[visual.TextBox2]: """Build the text boxes for the experiment. These are the areas into which the symbols are partitioned. Each text_box will have an associated VEP Box. @@ -604,20 +621,17 @@ def wait_screen(self, message: str, color: str) -> None: # try adding the BciPy logo to the wait screen try: - wait_logo = visual.ImageStim( - self.window, - image=BCIPY_LOGO_PATH, - pos=(0, .25), - mask=None, - ori=0.0) - wait_logo.size = resize_image( - BCIPY_LOGO_PATH, - self.window.size, - 1) + wait_logo = visual.ImageStim(self.window, + image=BCIPY_LOGO_PATH, + pos=(0, .25), + mask=None, + ori=0.0) + wait_logo.size = resize_image(BCIPY_LOGO_PATH, self.window.size, 1) wait_logo.draw() except Exception as e: - self.logger.exception(f'Cannot load logo image from path=[{BCIPY_LOGO_PATH}]') + self.logger.exception( + f'Cannot load logo image from path=[{BCIPY_LOGO_PATH}]') raise e # Draw and flip the screen. diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index 142fd444b..5859831b2 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -60,7 +60,7 @@ def checkerboard(squares: int, colors: Tuple[str, str], center: Tuple[float, center_x, center_y = center # find the center position of the left_top square - move_count = int(boxes_per_row / 2) + move_count = float(int(boxes_per_row / 2)) if squares % 2 == 0: # with an even number the center is on a vertex; adjust by half a box move_count -= 0.5 @@ -165,7 +165,6 @@ def positions(self) -> List[Tuple]: left = right_of(layout.left, width / 2) right = left_of(layout.right, width / 2) - if self.num_boxes == 4: return [(left, top), (right, top), (left, bottom), (right, bottom)] @@ -187,4 +186,4 @@ def animation_path(start_pos: Tuple[float, float], end_pos: Tuple[float, from_start = (i + 1) / frames pos = (x1 + (from_start * xdiff), y1 + (from_start * ydiff)) positions.append(pos) - return positions \ No newline at end of file + return positions From dca547ca33e04cab34ede03eafcea27b7799a14d Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 13 Nov 2023 16:53:36 -0800 Subject: [PATCH 143/330] Fix issue with VEP stimuli generation --- bcipy/helpers/stimuli.py | 26 ++++-- bcipy/helpers/tests/test_stimuli_vep.py | 106 ++++++++++++++++++++++++ 2 files changed, 123 insertions(+), 9 deletions(-) create mode 100644 bcipy/helpers/tests/test_stimuli_vep.py diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 5af1e5484..8a38ec318 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -1,13 +1,14 @@ import glob import itertools import logging +import math import random import re from abc import ABC, abstractmethod from collections import Counter from enum import Enum from os import path, sep -from typing import Dict, Iterator, List, NamedTuple, Optional, Tuple +from typing import Any, Dict, Iterator, List, NamedTuple, Optional, Tuple from pandas import Series from PIL import Image @@ -1125,15 +1126,18 @@ def generate_vep_calibration_inquiries(alp: List[str], def generate_vep_inquiries(symbols: List[str], num_boxes: int = 6, inquiry_count: int = 20, - is_txt: bool = True): + is_txt: bool = True) -> List[List[Any]]: """Generates inquiries""" fixation = get_fixation(is_txt) target_indices = random_target_positions(inquiry_count, stim_per_inquiry=num_boxes, percentage_without_target=0) - targets = generate_targets(symbols, - inquiry_count, - percentage_without_target=0.0) + + # repeat the symbols as necessary to ensure an adequate size for sampling + # without replacement. + population = symbols * math.ceil(inquiry_count / len(symbols)) + targets = random.sample(population, inquiry_count) + return [[target, fixation] + generate_vep_inquiry(alphabet=symbols, num_boxes=num_boxes, target=target, @@ -1183,6 +1187,10 @@ def stim_per_box(num_symbols: int, # 1, 1, 1, 20, 3, 2], # 1, 1, 1, 4, 21, 0]] + if max_empty_boxes + max_single_sym_boxes >= num_boxes: + max_empty_boxes = 0 + max_single_sym_boxes = num_boxes - 1 + # no more than 1 empty box empty_boxes = [0] * random.choice(range(max_empty_boxes + 1)) @@ -1207,14 +1215,14 @@ def stim_per_box(num_symbols: int, # last box boxes.append(remaining_symbols) - # random.shuffle(boxes) + return sorted(boxes) def generate_vep_inquiry(alphabet: List[str], num_boxes: int = 6, - target: str = None, - target_pos: int = None) -> List[List[str]]: + target: Optional[str] = None, + target_pos: Optional[int] = None) -> List[List[str]]: """Generates a single random inquiry. Parameters @@ -1236,7 +1244,7 @@ def generate_vep_inquiry(alphabet: List[str], """ box_counts = stim_per_box(num_symbols=len(alphabet), num_boxes=num_boxes) - + assert len(box_counts) == num_boxes syms = [sym for sym in alphabet] random.shuffle(syms) diff --git a/bcipy/helpers/tests/test_stimuli_vep.py b/bcipy/helpers/tests/test_stimuli_vep.py new file mode 100644 index 000000000..b3771029f --- /dev/null +++ b/bcipy/helpers/tests/test_stimuli_vep.py @@ -0,0 +1,106 @@ +import unittest + +from bcipy.helpers.stimuli import (generate_vep_calibration_inquiries, + generate_vep_inquiry, stim_per_box) +from bcipy.helpers.symbols import alphabet + + +class SSVEPStimuli(unittest.TestCase): + """Tests for VEP inquiry generation""" + + def test_stim_per_box(self): + """Test number of stimuli per box""" + symbol_count = 27 + for _i in range(10): + counts = stim_per_box(num_symbols=symbol_count, + num_boxes=6, + max_empty_boxes=1, + max_single_sym_boxes=4) + self.assertEqual(symbol_count, sum(counts)) + self.assertTrue( + sum([cnt for cnt in counts if cnt == 1]) <= 4, + "There should be no more than 4 single-symbol boxes") + self.assertTrue( + sum([cnt for cnt in counts if cnt == 0]) <= 1, + "There should be no more than 1 empty box") + + def test_stim_per_box_few_boxes(self): + """Test number of stimuli per box when max values sum to more than the + number of boxes.""" + symbol_count = 27 + for _i in range(10): + counts = stim_per_box(num_symbols=symbol_count, + num_boxes=4, + max_empty_boxes=1, + max_single_sym_boxes=4) + self.assertEqual(symbol_count, sum(counts)) + self.assertTrue( + sum([cnt for cnt in counts if cnt == 1]) <= 3, + "There should be no more than 3 single-symbol boxes") + self.assertTrue( + sum([cnt for cnt in counts if cnt == 0]) == 0, + "There should be no empty boxes") + + def test_stim_per_box_few_boxes_adjusted_params(self): + """Test number of stimuli per box where max values have been + adjusted.""" + symbol_count = 27 + for _i in range(10): + counts = stim_per_box(num_symbols=symbol_count, + num_boxes=4, + max_empty_boxes=1, + max_single_sym_boxes=2) + self.assertEqual(symbol_count, sum(counts)) + self.assertTrue( + sum([cnt for cnt in counts if cnt == 1]) <= 2, + "There should be no more than 2 single-symbol boxes") + self.assertTrue( + sum([cnt for cnt in counts if cnt == 0]) <= 1, + "There should be at most one empty box") + + def test_generate_single_vep_calib_inquiry(self): + """Test generation of a single VEP calibration inquiry""" + symbols = alphabet() + box_count = 6 + inq = generate_vep_inquiry(symbols, + num_boxes=box_count, + target='M', + target_pos=2) + + self.assertEqual(box_count, len(inq)) + self.assertTrue('M' in inq[2]) + self.assertEqual(len(symbols), + sum([len(box_items) for box_items in inq])) + + def test_generate_vep_calibration_inquiries(self): + """Test generate calibration inquiries""" + alp = alphabet() + stim_colors = ['green', 'red', 'blue', 'yellow', 'orange', 'purple'] + stim_timing = [4, 0.5, 4] + schedule = generate_vep_calibration_inquiries( + alp=alp, + timing=stim_timing, + color=stim_colors, + inquiry_count=20, + num_boxes=4) + + self.assertEqual(20, len(schedule.stimuli)) + self.assertEqual(6, len(schedule.stimuli[0])) + for inq in schedule.stimuli: + self.assertEqual(6, len(inq)) + self.assertTrue(isinstance(inq[0], str), + "First item should be the target") + self.assertTrue(isinstance(inq[1], str), + "Second item should be the fixation") + for pos in range(2, 6): + self.assertTrue(isinstance(inq[pos], list), + "Item should be a list of symbols") + + for color in schedule.colors: + self.assertEqual(stim_colors, color) + for timing in schedule.durations: + self.assertEqual(stim_timing, timing) + + +if __name__ == '__main__': + unittest.main() From ac382b73370a873a23973d4a1b25586ed5f05cb2 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 13 Nov 2023 16:54:16 -0800 Subject: [PATCH 144/330] Add VEP calibration task --- bcipy/task/paradigm/vep/calibration.py | 264 ++++++++++++++++++++++++- bcipy/task/start_task.py | 5 + bcipy/task/task_registry.py | 1 + 3 files changed, 269 insertions(+), 1 deletion(-) diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index d92240fc9..1feebed74 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -1,5 +1,267 @@ +"""VEP Calibration task-related code""" +from typing import List, Tuple + +from psychopy import core, visual + +from bcipy.acquisition.multimodal import ClientManager +from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE +from bcipy.display import InformationProperties, VEPStimuliProperties +from bcipy.display.components.layout import centered +from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.vep.display import VEPDisplay +from bcipy.display.paradigm.vep.layout import BoxConfiguration +from bcipy.helpers.clock import Clock +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, InquirySchedule, + generate_vep_calibration_inquiries) +from bcipy.helpers.symbols import alphabet +from bcipy.helpers.task import get_user_input, trial_complete_message +from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, + TriggerType, convert_timing_triggers, + offset_label) from bcipy.task import Task +def trigger_type(symbol: str, target: str, index: int) -> TriggerType: + """Trigger Type. + + This method is passed to convert_timing_triggers to properly assign TriggerTypes + to the timing of stimuli presented. + """ + if index == 0: + return TriggerType.PROMPT + if symbol == DEFAULT_TEXT_FIXATION: + return TriggerType.FIXATION + if target == symbol: + return TriggerType.TARGET + return TriggerType.NONTARGET + + class VEPCalibrationTask(Task): - """VEP Calibration Task""" \ No newline at end of file + """VEP Calibration Task. + + A task begins setting up variables --> initializing eeg --> + awaiting user input to start --> + setting up stimuli --> highlighting inquiries --> + saving data + + PARAMETERS: + ---------- + win (PsychoPy Display Object) + daq (Data Acquisition Object) + parameters (Dictionary) + file_save (String) + """ + + def __init__(self, win: visual.Window, daq: ClientManager, + parameters: Parameters, file_save: str): + super(VEPCalibrationTask, self).__init__() + self.num_boxes = 6 + self.window = win + self.frame_rate = self.window.getActualFrameRate() + self.parameters = parameters + self.daq = daq + self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) + self.experiment_clock = Clock() + self.buffer_val = parameters['task_buffer_length'] + self.symbol_set = alphabet(parameters) + + self.file_save = file_save + self.trigger_handler = TriggerHandler(self.file_save, TRIGGER_FILENAME, + FlushFrequency.EVERY) + + self.wait_screen_message = WAIT_SCREEN_MESSAGE + self.wait_screen_message_color = parameters['stim_color'] + + self.stim_number = parameters['stim_number'] + + self.timing = [ + parameters['time_prompt'], parameters['time_fixation'], + parameters['time_flash'] + ] + + self.color = [ + parameters['target_color'], parameters['fixation_color'], + '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' + ] + + self.is_txt_stim = parameters['is_txt_stim'] + self.display = self.init_display() + + def init_display(self) -> VEPDisplay: + """Initialize the display""" + return init_calibration_display(self.parameters, self.window, + self.experiment_clock, self.symbol_set, + self.timing, self.color) + + def generate_stimuli(self) -> InquirySchedule: + """Generates the inquiries to be presented. + Returns: + -------- + tuple( + samples[list[list[str]]]: list of inquiries + timing(list[list[float]]): list of timings + color(list(list[str])): list of colors) + """ + return generate_vep_calibration_inquiries( + alp=self.symbol_set, + timing=self.timing, + color=self.color, + inquiry_count=self.stim_number, + num_boxes=self.num_boxes, + is_txt=self.is_txt_stim) + + def execute(self): + + self.logger.info(f'Starting {self.name()}!') + run = True + + # Check user input to make sure we should be going + if not get_user_input(self.display, + self.wait_screen_message, + self.wait_screen_message_color, + first_run=True): + run = False + + # Wait for a time + core.wait(self.buffer_val) + + # Begin the Experiment + while run: + + # Get inquiry information given stimuli parameters + (stimuli_labels, _timing, _colors) = self.generate_stimuli() + + for inquiry in range(self.stim_number): + + # check user input to make sure we should be going + if not get_user_input(self.display, self.wait_screen_message, + self.wait_screen_message_color): + break + + # update task state + self.display.update_task_bar(str(inquiry + 1)) + + # Draw and flip screen + self.display.draw_static() + self.window.flip() + + self.display.schedule_to(stimuli_labels[inquiry]) + # Schedule a inquiry + + # Wait for a time + core.wait(self.buffer_val) + + # Do the inquiry + timing = self.display.do_inquiry() + + # Write triggers for the inquiry + self.write_trigger_data(timing, (inquiry == 0)) + + # Wait for a time + core.wait(self.buffer_val) + + # Set run to False to stop looping + run = False + + # Say Goodbye! + self.display.info_text = trial_complete_message( + self.window, self.parameters) + self.display.draw_static() + self.window.flip() + + # Allow for some training data to be collected + core.wait(self.buffer_val) + + self.write_offset_trigger() + + return self.file_save + + def write_trigger_data(self, timing: List[Tuple[str, float]], + first_run: bool) -> None: + """Write Trigger Data. + + Using the timing provided from the display and calibration information + from the data acquisition client, write trigger data in the correct + format. + + *Note on offsets*: we write the full offset value which can be used to + transform all stimuli to the time since session start (t = 0) for all + values (as opposed to most system clocks which start much higher). + We do not write the calibration trigger used to generate this offset + from the display. See display _trigger_pulse() for more information. + """ + if first_run: + assert self.display.first_stim_time, "First stim time not set" + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + label = offset_label(content_type.name) + time = client.offset(self.display.first_stim_time + ) - self.display.first_stim_time + triggers.append(Trigger(label, TriggerType.OFFSET, time)) + self.trigger_handler.add_triggers(triggers) + + # make sure triggers are written for the inquiry + self.trigger_handler.add_triggers( + convert_timing_triggers(timing, timing[0][0], trigger_type)) + + def write_offset_trigger(self) -> None: + """Append an offset value to the end of the trigger file. + """ + assert self.display.first_stim_time, "First stim time not set" + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + label = offset_label(content_type.name, prefix='daq_sample_offset') + time = client.offset(self.display.first_stim_time) + triggers.append(Trigger(label, TriggerType.SYSTEM, time)) + + self.trigger_handler.add_triggers(triggers) + self.trigger_handler.close() + + def name(self): + return 'VEP Calibration Task' + + +def init_calibration_display(parameters: Parameters, + window, + experiment_clock, + symbol_set, + timing, + colors, + num_boxes=6): + """Initialize the display""" + info = InformationProperties( + info_color=[parameters['info_color']], + info_pos=[(parameters['info_pos_x'], parameters['info_pos_y'])], + info_height=[parameters['info_height']], + info_font=[parameters['font']], + info_text=[parameters['info_text']], + ) + + layout = centered(width_pct=0.95, height_pct=0.80) + box_config = BoxConfiguration(layout, num_boxes=num_boxes, height_pct=0.30) + + stim_props = VEPStimuliProperties(stim_font=parameters['font'], + stim_pos=box_config.positions, + stim_height=0.1, + timing=timing, + stim_color=colors, + inquiry=[], + stim_length=1, + animation_seconds=1.0) + + task_bar = CalibrationTaskBar(window, + inquiry_count=parameters['stim_number'], + current_index=0, + colors=[parameters['task_color']], + font=parameters['font'], + height=parameters['task_height']) + + return VEPDisplay(window, + experiment_clock, + stim_props, + task_bar, + info, + symbol_set=symbol_set, + box_config=box_config, + should_prompt_target=True) diff --git a/bcipy/task/start_task.py b/bcipy/task/start_task.py index 264ca2a20..f6f40872f 100644 --- a/bcipy/task/start_task.py +++ b/bcipy/task/start_task.py @@ -10,6 +10,7 @@ from bcipy.task.paradigm.rsvp.calibration.timing_verification import \ RSVPTimingVerificationCalibration from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask +from bcipy.task.paradigm.vep.calibration import VEPCalibrationTask from bcipy.task.task_registry import TaskType @@ -57,6 +58,10 @@ def make_task(display_window, daq, task, parameters, file_save, return MatrixCopyPhraseTask( display_window, daq, parameters, file_save, signal_models, language_model, fake=fake) + + if task is TaskType.VEP_CALIBRATION: + return VEPCalibrationTask(display_window, daq, parameters, file_save) + raise TaskRegistryException( 'The provided experiment type is not registered.') diff --git a/bcipy/task/task_registry.py b/bcipy/task/task_registry.py index 88661f531..661b1d339 100644 --- a/bcipy/task/task_registry.py +++ b/bcipy/task/task_registry.py @@ -37,6 +37,7 @@ class TaskType(AutoNumberEnum): MATRIX_CALIBRATION = 'Matrix Calibration' MATRIX_TIMING_VERIFICATION_CALIBRATION = 'Matrix Time Test Calibration' MATRIX_COPY_PHRASE = 'Matrix Copy Phrase' + VEP_CALIBRATION = 'VEP Calibration' def __init__(self, label): self.label = label From f902e8e7762917aeb4ec0b28e8820dadf92b0d36 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Tue, 7 Nov 2023 13:06:00 -0800 Subject: [PATCH 145/330] Adds test for InquiryReshaper Ensures that InquiryReshaper works when passed None for it's channel_map --- bcipy/helpers/tests/test_stimuli.py | 14 ++++++++++++++ 1 file changed, 14 insertions(+) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 4a21b423b..14a187da7 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -918,6 +918,20 @@ def test_inquiry_reshaper(self): self.assertTrue(reshaped_data.shape == expected_shape) self.assertTrue(np.all(labels == self.true_labels)) + def test_inquiry_reshaper_with_no_channel_map(self): + reshaped_data, labels, _ = InquiryReshaper()( + trial_targetness_label=self.target_info, + timing_info=self.timing_info, + eeg_data=self.eeg, + sample_rate=self.sample_rate, + trials_per_inquiry=self.trials_per_inquiry, + channel_map=None, + poststimulus_length=self.trial_length + ) + expected_shape = (self.n_channel, self.n_inquiry, self.samples_per_inquiry) + self.assertTrue(reshaped_data.shape == expected_shape) + self.assertTrue(np.all(labels == self.true_labels)) + def test_inquiry_reshaper_trial_extraction(self): timing = [[1, 3, 4], [1, 4, 5], [1, 2, 3], [4, 5, 6]] # make a fake eeg data array (n_channels, n_inquiry, n_samples) From 0545cdeaea20250e55964c511b45250280502812 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Wed, 8 Nov 2023 00:26:01 -0800 Subject: [PATCH 146/330] Adds test for trial reshaper with no channel map --- bcipy/helpers/tests/test_stimuli.py | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 14a187da7..8ac019380 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -854,6 +854,21 @@ def test_trial_reshaper(self): self.assertTrue(np.all(labels == [1, 0, 0])) self.assertTrue(reshaped_trials.shape == expected_shape) + def test_trial_reshaper_with_no_channel_map(self): + sample_rate = 256 + trial_length_s = 0.5 + reshaped_trials, labels = TrialReshaper()( + trial_targetness_label=self.target_info, + timing_info=self.timing_info, + eeg_data=self.eeg, + sample_rate=sample_rate, + channel_map=None, + poststimulus_length=trial_length_s + ) + trial_length_samples = int(sample_rate * trial_length_s) + expected_shape = (self.channel_number, len(self.target_info), trial_length_samples) + self.assertTrue(np.all(labels== [1, 0, 0])) + self.assertTrue(reshaped_trials.shape == expected_shape) class TestInquiryReshaper(unittest.TestCase): From f91c24a3f3fb47d2974cb111614749ba1ad019d7 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Wed, 8 Nov 2023 14:18:03 -0800 Subject: [PATCH 147/330] Adds test case for invalid alp shape in best_case_rsvp_inq_gen function --- bcipy/helpers/tests/test_stimuli.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 8ac019380..103c24088 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -713,6 +713,22 @@ def test_best_case_inquiry_gen(self): self.assertEqual([1] + ([0.2] * n), times[0]) self.assertEqual(['red'] + (['white'] * n), colors[0]) + def test_best_case_inquiry_gen_invalid_alp(self): + """Test best_case_rsvp_inq_gen throws error when passed invalid alp shape""" + alp = ['a', 'b', 'c', 'd'] + session_stimuli = [0.1, 0.1, 0.1, 0.2, 0.2, 0.1, 0.2] + n = 5 + with self.assertRaises(BciPyCoreException, msg='Missing information about the alphabet.'): + best_case_rsvp_inq_gen( + alp=alp, + session_stimuli=session_stimuli, + timing=[1, 0.2], + color=['red', 'white'], + stim_number=1, + stim_length=n, + is_txt=True + ) + def test_best_case_inquiry_gen_with_inq_constants(self): """Test best_case_rsvp_inq_gen with inquiry constants""" From fa13dd66d2566948ae8020732b7bad4e5f909f03 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Mon, 13 Nov 2023 01:10:50 -0800 Subject: [PATCH 148/330] Fixes formatting in test_stimuli.py --- bcipy/helpers/tests/test_stimuli.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 103c24088..38c63fcf2 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -883,9 +883,10 @@ def test_trial_reshaper_with_no_channel_map(self): ) trial_length_samples = int(sample_rate * trial_length_s) expected_shape = (self.channel_number, len(self.target_info), trial_length_samples) - self.assertTrue(np.all(labels== [1, 0, 0])) + self.assertTrue(np.all(labels == [1, 0, 0])) self.assertTrue(reshaped_trials.shape == expected_shape) + class TestInquiryReshaper(unittest.TestCase): def setUp(self): From 803e904815a8b97f7c504ea22d317ed67a3a4471 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Tue, 14 Nov 2023 10:28:39 -0800 Subject: [PATCH 149/330] Adds no cover to untouched branch --- bcipy/helpers/stimuli.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index d4e55dd0a..8ac9393bd 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -221,7 +221,7 @@ def extract_trials( try: new_trials.append(inquiries[:, inquiry_idx, start:end]) - except IndexError: + except IndexError: # pragma: no cover raise BciPyCoreException( f'InquiryReshaper.extract_trials: index out of bounds. \n' f'Inquiry: [{inquiry_idx}] from {start}:{end}. init_time: {time}, ' From 28044b95b216254a4b610291a3fd3944eb48f392 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 14 Nov 2023 10:34:48 -0800 Subject: [PATCH 150/330] appease the linter --- bcipy/helpers/stimuli.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 8ac9393bd..e89aa440a 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -221,7 +221,7 @@ def extract_trials( try: new_trials.append(inquiries[:, inquiry_idx, start:end]) - except IndexError: # pragma: no cover + except IndexError: # pragma: no cover raise BciPyCoreException( f'InquiryReshaper.extract_trials: index out of bounds. \n' f'Inquiry: [{inquiry_idx}] from {start}:{end}. init_time: {time}, ' From b89c4fee7188cbe8e81664638c6e549470b54155 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Tue, 14 Nov 2023 10:51:08 -0800 Subject: [PATCH 151/330] improve variable name --- bcipy/helpers/tests/test_stimuli.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 38c63fcf2..155fd5b37 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -717,7 +717,7 @@ def test_best_case_inquiry_gen_invalid_alp(self): """Test best_case_rsvp_inq_gen throws error when passed invalid alp shape""" alp = ['a', 'b', 'c', 'd'] session_stimuli = [0.1, 0.1, 0.1, 0.2, 0.2, 0.1, 0.2] - n = 5 + stim_length = 5 with self.assertRaises(BciPyCoreException, msg='Missing information about the alphabet.'): best_case_rsvp_inq_gen( alp=alp, @@ -725,7 +725,7 @@ def test_best_case_inquiry_gen_invalid_alp(self): timing=[1, 0.2], color=['red', 'white'], stim_number=1, - stim_length=n, + stim_length=stim_length, is_txt=True ) From 2352c4615fbbff0fa43a946f213c157d8e5861b0 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 14 Nov 2023 16:21:02 -0800 Subject: [PATCH 152/330] Refactor for clarity; fix typing issues --- bcipy/display/paradigm/vep/codes.py | 16 +++ bcipy/display/paradigm/vep/display.py | 142 +++---------------------- bcipy/display/paradigm/vep/vep_stim.py | 92 ++++++++++++++++ bcipy/helpers/triggers.py | 2 +- bcipy/task/paradigm/vep/calibration.py | 39 +++---- 5 files changed, 138 insertions(+), 153 deletions(-) create mode 100644 bcipy/display/paradigm/vep/codes.py create mode 100644 bcipy/display/paradigm/vep/vep_stim.py diff --git a/bcipy/display/paradigm/vep/codes.py b/bcipy/display/paradigm/vep/codes.py new file mode 100644 index 000000000..1ec003ffd --- /dev/null +++ b/bcipy/display/paradigm/vep/codes.py @@ -0,0 +1,16 @@ +"""Functions related to VEP flash rates""" +from typing import List + +import numpy as np + + +def create_vep_codes(length=32, count=4) -> List[List[int]]: + """Create a list of random VEP codes. + + length - how many bits in each code. This should be greater than or equal to the refresh rate + if using these to flicker. For example, if the refresh rate is 60Hz, then the length should + be at least 60. + count - how many codes to generate, each will be unique. + """ + np.random.seed(1) + return [np.random.randint(2, size=length) for _ in range(count)] diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index ecabce8c2..d587e35ea 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -3,38 +3,28 @@ from typing import (Any, Dict, Iterable, List, NamedTuple, Optional, Tuple, Union) -import numpy as np -from psychopy import core, visual -from psychopy.visual.shape import ShapeStim +from psychopy import core, visual # type: ignore import bcipy.display.components.layout as layout from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, VEPStimuliProperties) -from bcipy.display.components.layout import envelope, scaled_size +from bcipy.display.components.layout import scaled_size from bcipy.display.components.task_bar import TaskBar from bcipy.display.paradigm.matrix.layout import symbol_positions -from bcipy.display.paradigm.vep.layout import (BoxConfiguration, - animation_path, checkerboard) +from bcipy.display.paradigm.vep.codes import create_vep_codes +from bcipy.display.paradigm.vep.layout import BoxConfiguration, animation_path +from bcipy.display.paradigm.vep.vep_stim import VEPStim from bcipy.helpers.clock import Clock from bcipy.helpers.list import expanded from bcipy.helpers.stimuli import resize_image from bcipy.helpers.symbols import alphabet from bcipy.helpers.triggers import _calibration_trigger -# Should only be two elements, but a list rather than a Tuple -StimTime = List[Union[str, float]] - -def create_vep_codes(length=32, count=4) -> List[List[int]]: - """Create a list of random VEP codes. - - length - how many bits in each code. This should be greater than or equal to the refresh rate - if using these to flicker. For example, if the refresh rate is 60Hz, then the length should - be at least 60. - count - how many codes to generate, each will be unique. - """ - np.random.seed(1) - return [np.random.randint(2, size=length) for _ in range(count)] +class StimTime(NamedTuple): + """Represents the time that the given symbol was displayed""" + symbol: str + time: float class StimProps(NamedTuple): @@ -44,91 +34,6 @@ class StimProps(NamedTuple): color: str -class VEPStim: - """Represents a checkerboard of squares that can be flashed at a given - rate. Flashing is accomplished by inverting the colors of each square. - - Parameters - ---------- - layout - used to build the stimulus - code - A list of integers representing the VEP code for each box - colors - tuple of colors for the checkerboard pattern - center - center position of the checkerboard - size - size of the checkerboard, in layout units - num_squares - number of squares in the checkerboard - """ - - def __init__(self, - win: visual.Window, - code: List[int], - colors: Tuple[str, str], - center: Tuple[float, float], - size: Tuple[float, float], - num_squares: int = 4): - self.window = win - self.code = code - - squares = checkerboard(squares=num_squares, - colors=colors, - center=center, - board_size=size) - board_boundary = envelope(pos=center, size=size) - - frame1_holes = [] - frame2_holes = [] - for square in squares: - square_boundary = envelope(pos=square.pos, size=square.size) - # squares define the holes in the polygon - if square.color == colors[0]: - frame2_holes.append(square_boundary) - elif square.color == colors[1]: - frame1_holes.append(square_boundary) - - # Checkerboard is represented as a polygon with holes, backed by a - # simple square with the alternating color. - # This technique renders more efficiently and scales better than using - # separate shapes (Rect or Gradient) for each square. - background = ShapeStim(self.window, - lineColor=colors[1], - fillColor=colors[1], - vertices=board_boundary) - self.on_stim = [ - background, - # polygon with holes - ShapeStim(self.window, - lineWidth=0, - fillColor=colors[0], - closeShape=True, - vertices=[board_boundary, *frame1_holes]) - ] - self.off_stim = [ - background, - # polygon with holes - ShapeStim(self.window, - lineWidth=0, - fillColor=colors[0], - closeShape=True, - vertices=[board_boundary, *frame2_holes]) - ] - - def render_frame(self, frame: int) -> None: - """Render a given frame number, where frame refers to a code index""" - if self.code[frame] == 1: - self.frame_on() - else: - self.frame_off() - - def frame_on(self) -> None: - """Each square is set to a starting color and draw.""" - for stim in self.on_stim: - stim.draw() - - def frame_off(self) -> None: - """Invert each square from its starting color and draw.""" - for stim in self.off_stim: - stim.draw() - - class VEPDisplay(Display): """Display for VEP paradigm""" @@ -181,7 +86,6 @@ def __init__(self, f"Symbol starting positions ({str(display_container.units)} units): {self.starting_positions}" ) - self.fixation = self._build_fixation() self.starting_color = 'white' self.sti = self._build_inquiry_stimuli() @@ -196,8 +100,6 @@ def __init__(self, # Callback used on presentation of first stimulus. self.first_run = True self.first_stim_callback = lambda _sti: None - # TODO: needed? - # self.size_list_sti = [] self.task_bar = task_bar self.info_text = info.build_info_text(window) @@ -267,14 +169,14 @@ def do_inquiry(self) -> List[StimTime]: # type: ignore self.reset_symbol_positions() if self.should_prompt_target: - [target, fixation, *stim] = self.stim_properties() + [target, _fixation, *stim] = self.stim_properties() if isinstance(target.symbol, str): self.set_stimuli_colors(stim) self.prompt_target(target, target_box_index=self.box_index( stim, target.symbol)) else: - [fixation, *stim] = self.stim_properties() + [_fixation, *stim] = self.stim_properties() self.set_stimuli_colors(stim) # self.do_fixation(fixation) @@ -476,20 +378,12 @@ def add_timing(self, stimuli: str): Useful as a callback function to register a marker at the time it is first displayed.""" - self._timing.append([stimuli, self.experiment_clock.getTime()]) + self._timing.append(StimTime(stimuli, self.experiment_clock.getTime())) def reset_timing(self): """Reset the trigger timing.""" self._timing = [] - def _build_fixation(self) -> visual.TextStim: - """Build the fixation stim""" - return visual.TextStim(self.window, - text='+', - color='red', - height=self.stimuli_height, - pos=[0, 0]) - def _build_inquiry_stimuli(self) -> Dict[str, visual.TextStim]: """Build the inquiry stimuli.""" grid = {} @@ -534,14 +428,12 @@ def _trigger_pulse(self) -> None: beginning of an experiment. If drift is detected in your experiment, more frequent pulses and offset correction may be required. """ - calibration_time: StimTime = _calibration_trigger( # type: ignore - self.experiment_clock, - trigger_type=self.trigger_type, - display=self.window) - - # set the first stim time if not present and first_run to False + trg = _calibration_trigger(self.experiment_clock, + trigger_type=self.trigger_type, + display=self.window) + calibration_time = StimTime(*trg) if not self.first_stim_time: - self.first_stim_time = calibration_time[-1] # type: ignore + self.first_stim_time = calibration_time.time self.first_run = False def schedule_to(self, diff --git a/bcipy/display/paradigm/vep/vep_stim.py b/bcipy/display/paradigm/vep/vep_stim.py new file mode 100644 index 000000000..366f6e836 --- /dev/null +++ b/bcipy/display/paradigm/vep/vep_stim.py @@ -0,0 +1,92 @@ +from typing import List, Tuple + +from psychopy import visual # type: ignore +from psychopy.visual.shape import ShapeStim # type: ignore + +from bcipy.display.components.layout import envelope +from bcipy.display.paradigm.vep.layout import checkerboard + + +class VEPStim: + """Represents a checkerboard of squares that can be flashed at a given + rate. Flashing is accomplished by inverting the colors of each square. + + Parameters + ---------- + layout - used to build the stimulus + code - A list of integers representing the VEP code for each box + colors - tuple of colors for the checkerboard pattern + center - center position of the checkerboard + size - size of the checkerboard, in layout units + num_squares - number of squares in the checkerboard + """ + + def __init__(self, + win: visual.Window, + code: List[int], + colors: Tuple[str, str], + center: Tuple[float, float], + size: Tuple[float, float], + num_squares: int = 4): + self.window = win + self.code = code + + squares = checkerboard(squares=num_squares, + colors=colors, + center=center, + board_size=size) + board_boundary = envelope(pos=center, size=size) + + frame1_holes = [] + frame2_holes = [] + for square in squares: + square_boundary = envelope(pos=square.pos, size=square.size) + # squares define the holes in the polygon + if square.color == colors[0]: + frame2_holes.append(square_boundary) + elif square.color == colors[1]: + frame1_holes.append(square_boundary) + + # Checkerboard is represented as a polygon with holes, backed by a + # simple square with the alternating color. + # This technique renders more efficiently and scales better than using + # separate shapes (Rect or Gradient) for each square. + background = ShapeStim(self.window, + lineColor=colors[1], + fillColor=colors[1], + vertices=board_boundary) + self.on_stim = [ + background, + # polygon with holes + ShapeStim(self.window, + lineWidth=0, + fillColor=colors[0], + closeShape=True, + vertices=[board_boundary, *frame1_holes]) + ] + self.off_stim = [ + background, + # polygon with holes + ShapeStim(self.window, + lineWidth=0, + fillColor=colors[0], + closeShape=True, + vertices=[board_boundary, *frame2_holes]) + ] + + def render_frame(self, frame: int) -> None: + """Render a given frame number, where frame refers to a code index""" + if self.code[frame] == 1: + self.frame_on() + else: + self.frame_off() + + def frame_on(self) -> None: + """Each square is set to a starting color and draw.""" + for stim in self.on_stim: + stim.draw() + + def frame_off(self) -> None: + """Invert each square from its starting color and draw.""" + for stim in self.off_stim: + stim.draw() diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 8613a8de8..cf4cf2a40 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -66,7 +66,7 @@ def _calibration_trigger(experiment_clock: Clock, trigger_name: str = 'calibration', trigger_time: float = 1, display=None, - on_trigger=None) -> List[tuple]: + on_trigger=None) -> List: """Calibration Trigger. Outputs triggers for the purpose of calibrating data and stimuli. diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 1feebed74..a18110530 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -12,7 +12,7 @@ from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters -from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, InquirySchedule, +from bcipy.helpers.stimuli import (InquirySchedule, generate_vep_calibration_inquiries) from bcipy.helpers.symbols import alphabet from bcipy.helpers.task import get_user_input, trial_complete_message @@ -22,19 +22,15 @@ from bcipy.task import Task -def trigger_type(symbol: str, target: str, index: int) -> TriggerType: +def trigger_type(symbol: str, target: str, _index: int) -> TriggerType: """Trigger Type. This method is passed to convert_timing_triggers to properly assign TriggerTypes to the timing of stimuli presented. """ - if index == 0: - return TriggerType.PROMPT - if symbol == DEFAULT_TEXT_FIXATION: - return TriggerType.FIXATION if target == symbol: return TriggerType.TARGET - return TriggerType.NONTARGET + return TriggerType.EVENT class VEPCalibrationTask(Task): @@ -112,7 +108,7 @@ def generate_stimuli(self) -> InquirySchedule: is_txt=self.is_txt_stim) def execute(self): - + """Main task loop""" self.logger.info(f'Starting {self.name()}!') run = True @@ -133,7 +129,6 @@ def execute(self): (stimuli_labels, _timing, _colors) = self.generate_stimuli() for inquiry in range(self.stim_number): - # check user input to make sure we should be going if not get_user_input(self.display, self.wait_screen_message, self.wait_screen_message_color): @@ -147,7 +142,7 @@ def execute(self): self.window.flip() self.display.schedule_to(stimuli_labels[inquiry]) - # Schedule a inquiry + # Schedule an inquiry # Wait for a time core.wait(self.buffer_val) @@ -156,7 +151,7 @@ def execute(self): timing = self.display.do_inquiry() # Write triggers for the inquiry - self.write_trigger_data(timing, (inquiry == 0)) + self.write_trigger_data(timing, first_run=(inquiry == 0)) # Wait for a time core.wait(self.buffer_val) @@ -172,7 +167,6 @@ def execute(self): # Allow for some training data to be collected core.wait(self.buffer_val) - self.write_offset_trigger() return self.file_save @@ -184,30 +178,21 @@ def write_trigger_data(self, timing: List[Tuple[str, float]], Using the timing provided from the display and calibration information from the data acquisition client, write trigger data in the correct format. - - *Note on offsets*: we write the full offset value which can be used to - transform all stimuli to the time since session start (t = 0) for all - values (as opposed to most system clocks which start much higher). - We do not write the calibration trigger used to generate this offset - from the display. See display _trigger_pulse() for more information. """ + triggers = [] if first_run: assert self.display.first_stim_time, "First stim time not set" - triggers = [] for content_type, client in self.daq.clients_by_type.items(): label = offset_label(content_type.name) - time = client.offset(self.display.first_stim_time - ) - self.display.first_stim_time + time = client.offset(self.display.first_stim_time) - self.display.first_stim_time triggers.append(Trigger(label, TriggerType.OFFSET, time)) - self.trigger_handler.add_triggers(triggers) - # make sure triggers are written for the inquiry - self.trigger_handler.add_triggers( - convert_timing_triggers(timing, timing[0][0], trigger_type)) + target = timing[0][0] + triggers.extend(convert_timing_triggers(timing, target, trigger_type)) + self.trigger_handler.add_triggers(triggers) def write_offset_trigger(self) -> None: - """Append an offset value to the end of the trigger file. - """ + """Append an offset value to the end of the trigger file.""" assert self.display.first_stim_time, "First stim time not set" triggers = [] for content_type, client in self.daq.clients_by_type.items(): From 8731cf5a3d0b30275a1a9b1095f81dcc34c252f1 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Wed, 15 Nov 2023 22:08:03 -0500 Subject: [PATCH 153/330] Logging output to file. Sampler reshaper fixes. Single data source typing workssss --- bcipy/simulator/__init__.py | 31 +++++ bcipy/simulator/helpers/data_engine.py | 10 +- bcipy/simulator/helpers/decision.py | 132 +--------------------- bcipy/simulator/helpers/evidence_fuser.py | 4 +- bcipy/simulator/helpers/sampler.py | 27 +++-- bcipy/simulator/helpers/signal_helpers.py | 12 +- bcipy/simulator/helpers/types.py | 13 ++- bcipy/simulator/sim.py | 33 ++++-- bcipy/simulator/simulator_base.py | 1 - bcipy/simulator/tests/sampler_test.py | 6 +- 10 files changed, 107 insertions(+), 162 deletions(-) diff --git a/bcipy/simulator/__init__.py b/bcipy/simulator/__init__.py index e69de29bb..2a543a621 100644 --- a/bcipy/simulator/__init__.py +++ b/bcipy/simulator/__init__.py @@ -0,0 +1,31 @@ +import datetime +import logging +import sys + +log = logging.getLogger(__name__) +log.setLevel(logging.DEBUG) +# Create handlers for logging to the standard output and a file +stdoutHandler = logging.StreamHandler(stream=sys.stdout) +fileHandler = logging.FileHandler(f"bcipy/simulator/sim_output_{datetime.datetime.now()}.log") + +# Set the log levels on the handlers +stdoutHandler.setLevel(logging.INFO) +fileHandler.setLevel(logging.DEBUG) + +# Create a log format using Log Record attributes +fmt_file = logging.Formatter( + "%(asctime)s | %(levelname)s | %(filename)s:%(lineno)s >> %(message)s" +) + +fmt = logging.Formatter( + "%(levelname)s >> %(message)s" +) + + +# Set the log format on each handler +stdoutHandler.setFormatter(fmt) +fileHandler.setFormatter(fmt_file) + +# Add each handler to the Logger object +log.addHandler(stdoutHandler) +log.addHandler(fileHandler) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index e2b3a1af4..234df0aa2 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,3 +1,4 @@ +import logging from abc import ABC from pathlib import Path from typing import Optional, List @@ -11,6 +12,8 @@ from bcipy.helpers.parameters import Parameters from bcipy.simulator.helpers.signal_helpers import ExtractedExperimentData, process_raw_data_for_model +log = logging.getLogger(__name__) + class DataEngine(ABC): @@ -42,6 +45,7 @@ def __init__(self, source_dirs: List[str]): self.symbols_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) self.labels_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) self.schema: Optional[pd.DataFrame] = None + self.load() def load(self) -> DataEngine: @@ -52,6 +56,8 @@ def load(self) -> DataEngine: Returns: self for chaining """ + log.debug(f"Loading data from {len(self.source_dirs)} source directories") + self.parameter_files = [load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for data_folder in self.source_dirs] @@ -69,6 +75,7 @@ def load(self) -> DataEngine: self.labels_by_inquiry.append(data_source.labels) + log.info("Finished loading all data") return self def transform(self) -> DataEngine: @@ -84,7 +91,7 @@ def transform(self) -> DataEngine: self for chaining """ - cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] + cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] # TODO store how good evidence was in session types = [int, int, int, str, int, np.ndarray] rows = [] @@ -105,6 +112,7 @@ def transform(self) -> DataEngine: rows.extend(symbol_rows) self.schema = pd.DataFrame(rows) + # breakpoint() return self diff --git a/bcipy/simulator/helpers/decision.py b/bcipy/simulator/helpers/decision.py index 7b52b5340..72a0544c0 100644 --- a/bcipy/simulator/helpers/decision.py +++ b/bcipy/simulator/helpers/decision.py @@ -54,7 +54,7 @@ def decide(self, series: List[InquiryResult]): # than this, since the language model distribution is added before # the first inquiry is displayed. current_inq = len(series) if series else 0 - log.info( + log.debug( f"Checking min iterations; current iteration is {current_inq}") return current_inq < self.min_num_inq @@ -87,7 +87,7 @@ def decide(self, series: List[InquiryResult]): # see MinIterationsCriteria comment current_inq = len(series) if series else 0 if current_inq >= self.max_num_inq: - log.info( + log.debug( "Committing to decision: max iterations have been reached.") return True return False @@ -108,130 +108,6 @@ def __init__(self, threshold: float): def decide(self, series: List[InquiryResult]): current_distribution = series[-1].fused_likelihood if np.max(current_distribution) > self.tau: - log.info("Committing to decision: posterior exceeded threshold.") + log.debug("Committing to decision: posterior exceeded threshold.") return True - return False - -# -# class MarginCriteria(DecisionCriteria): -# """ Stopping criteria based on the difference of two most likely candidates. -# This condition enforces the likelihood difference between two top -# candidates to be at least a value. E.g. in 4 category case with -# a margin 0.2, the edge cases [0.6,0.4,0.,0.] and [0.4,0.2,0.2,0.2] -# satisfy the condition. -# """ -# -# def __init__(self, margin: float): -# """ Args: -# margin(float in [0,1]): Minimum distance required between -# two most likely competing candidates to trigger termination. -# """ -# assert 1 >= margin >= 0, "difference margin should be in [0,1]" -# self.margin = margin -# -# def decide(self, series: Dict): -# # Get the current posterior probability values -# p = copy(series['list_distribution'][-1]) -# # This criteria compares most likely candidates (best competitors) -# candidates = [p[idx] for idx in list(np.argsort(p)[-2:])] -# stopping_rule = np.abs(candidates[0] - candidates[1]) -# d = stopping_rule > self.margin -# if d: -# log.info("Committing to decision: margin is high enough.") -# -# return d -# -# -# class MomentumCommitCriteria(DecisionCriteria): -# """ Stopping criteria based on Shannon entropy on the simplex -# Attr: -# lam(float): linear combination parameter between entropy and the -# speed term -# tau(float): decision threshold -# """ -# -# def __init__(self, tau: float, lam: float): -# self.lam = lam -# self.tau = tau -# -# def reset(self): -# pass -# -# def decide(self, series): -# eps = np.power(.1, 6) -# -# prob_history = copy(series['list_distribution']) -# p = prob_history[-1] -# -# tmp_p = np.ones(len(p)) * (1 - self.tau) / (len(p) - 1) -# tmp_p[0] = self.tau -# -# tmp = -np.sum(p * np.log2(p + eps)) -# tau_ = -np.sum(tmp_p * np.log2(tmp_p + eps)) -# -# tmp_ = np.array(prob_history) -# mom_ = tmp_[1:] * (np.log(tmp_[1:] + eps) - np.log(tmp_[:-1] + eps)) -# momentum = np.linalg.norm(mom_) / len(prob_history) -# -# if len(prob_history) > 1: -# stopping_rule = tmp - self.lam * momentum -# else: -# stopping_rule = tmp -# -# d = stopping_rule < tau_ -# -# return d -# -# -# class CriteriaEvaluator(): -# """Evaluates whether an series should commit to a decision based on the -# provided criteria. -# -# Parameters: -# ----------- -# continue_criteria: list of criteria; if any of these evaluate to true the -# decision maker continues. -# commit_criteria: list of criteria; if any of these return true and -# continue_criteria are all false, decision maker commits to a decision. -# """ -# -# def __init__(self, continue_criteria: List[DecisionCriteria], -# commit_criteria: List[DecisionCriteria]): -# self.continue_criteria = continue_criteria or [] -# self.commit_criteria = commit_criteria or [] -# -# @classmethod -# def default(cls, min_num_inq: int, max_num_inq: int, threshold: float): -# return cls(continue_criteria=[MinIterationsCriteria(min_num_inq)], -# commit_criteria=[ -# MaxIterationsCriteria(max_num_inq), -# ProbThresholdCriteria(threshold) -# ]) -# -# def do_series(self): -# for el_ in self.continue_criteria: -# el_.reset() -# for el in self.commit_criteria: -# el.reset() -# -# def should_commit(self, series: Dict): -# """Evaluates the given series; returns true if stoppage criteria has -# been met, otherwise false. -# -# Parameters: -# ----------- -# series - series data -# - target(str): target of the series -# - time_spent(ndarray[float]): |num_trials|x1 -# time spent on the inquiry -# - list_sti(list[list[str]]): presented symbols in each -# inquiry -# - list_distribution(list[ndarray[float]]): list of |alp|x1 -# arrays with prob. dist. over alp -# """ -# if any( -# criteria.decide(series) -# for criteria in self.continue_criteria): -# return False -# return any( -# criteria.decide(series) for criteria in self.commit_criteria) + return False \ No newline at end of file diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py index 43b594208..6f04b6c34 100644 --- a/bcipy/simulator/helpers/evidence_fuser.py +++ b/bcipy/simulator/helpers/evidence_fuser.py @@ -28,12 +28,12 @@ def fuse(self, prior_likelihood, evidence) -> np.ndarray: for value in evidence.values(): ret_likelihood *= value[:] - ret_likelihood = self.__clean_likelihood(ret_likelihood) + ret_likelihood = self.__normalize_likelihood(ret_likelihood) return ret_likelihood - def __clean_likelihood(self, likelihood): + def __normalize_likelihood(self, likelihood): cleaned_likelihood = likelihood.copy() if np.isinf(np.sum(likelihood)): diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 657e2ad85..4b3f6fb06 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -1,3 +1,4 @@ +import logging from abc import ABC from typing import Callable, List @@ -10,6 +11,8 @@ from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.interfaces import SimState +log = logging.getLogger(__name__) + class Sampler(ABC): """ Interface to generate sample of data usable by a model """ @@ -41,28 +44,36 @@ def sample(self, state: SimState) -> np.ndarray: inquiry_letter_subset = state.display_alphabet target_letter = state.target_symbol - eeg_responses = [] + sample_rows = [] for symbol in inquiry_letter_subset: is_target = int(symbol == target_letter) - filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') + # filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') + filtered_data = self.data.query(f'target == {is_target}') if not len(filtered_data): raise TaskConfigurationException(message="No eeg sample found with provided data and query") row = filtered_data.sample(1) - eeg_responses.append(row['eeg']) + sample_rows.append(row) + + log.debug(f"EEG Samples: \n {', '.join([r.to_string() for r in sample_rows])}") + eeg_responses = [r['eeg'].to_numpy()[0] for r in sample_rows] + sample = self.model_input_reshaper(eeg_responses) - return self.model_input_reshaper(eeg_responses) + return sample def set_reshaper(self, reshaper: Callable): self.model_input_reshaper = reshaper - def __default_reshaper(self, eeg_response) -> np.ndarray: + def __default_reshaper(self, eeg_responses: List[np.ndarray]) -> np.ndarray: + # returns (channel_n, trial_n, sample_n) + + channels_eeg = [[] for i in range(len(eeg_responses[0]))] - channels_eeg = [[] for i in range(len(eeg_response[0]))] - for t_i, trial_channels_eeg in enumerate(eeg_response): + for t_i, trial_channels_eeg in enumerate(eeg_responses): for c_i, channel_eeg in enumerate(trial_channels_eeg): channels_eeg[c_i].append(channel_eeg) - return np.array(channels_eeg[0]) + # TODO make sure this returns (7, 10, 90) + return np.array(channels_eeg) # TODO ReplaySampler diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 738643d3c..df3d7c738 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -17,7 +17,6 @@ from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams -logger.getLogger().setLevel(logger.INFO) log = logger.getLogger(__name__) @@ -33,9 +32,8 @@ class ExtractedExperimentData: # TODO clean up design def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshaper = InquiryReshaper()) -> ExtractedExperimentData: assert parameters, "Parameters are required for offline analysis." - if not data_folder: - data_folder = load_experimental_data() + log.debug(f"Processing raw data for {data_folder}") # extract relevant session information from parameters file trial_window = parameters.get("trial_window") window_length = trial_window[1] - trial_window[0] @@ -52,7 +50,7 @@ def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshape downsample_rate = transform_params.down_sampling_rate static_offset = parameters.get("static_trigger_offset") - log.info( + log.debug( f"\nData processing settings: \n" f"{str(transform_params)} \n" f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " @@ -79,8 +77,8 @@ def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshape downsample_factor=transform_params.down_sampling_rate, ) - log.info(f"Channels read from csv: {channels}") - log.info(f"Device type: {type_amp}, fs={sample_rate}") + log.debug(f"Channels read from csv: {channels}") + log.debug(f"Device type: {type_amp}, fs={sample_rate}") # Process triggers.txt files trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( @@ -96,7 +94,7 @@ def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshape # The timestamp column [0] is already excluded. channel_map = analysis_channels(channels, device_spec) channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] - log.info(f'Channels used in analysis: {channels_used}') + log.debug(f'Channels used in analysis: {channels_used}') data, fs = raw_data.by_channel() diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py index 2de09f88f..20b71bee3 100644 --- a/bcipy/simulator/helpers/types.py +++ b/bcipy/simulator/helpers/types.py @@ -1,14 +1,23 @@ from dataclasses import dataclass -from typing import Optional, List +from typing import Optional, List, Dict import numpy as np +from bcipy.task.data import EvidenceType + @dataclass class InquiryResult: target: Optional[str] time_spent: int stimuli: List - evidence_likelihoods: List # TODO make this into a dictionary to support multimodal. e.g {SignalModel: evidence_list, LanguageModel:evidence_list} + evidence_likelihoods: List # TODO make this into a dictionary to support multimodal. e.g {SignalModel: evidence_list, LanguageModel:evidence_list} fused_likelihood: np.ndarray decision: Optional[str] + + +@dataclass +class SimEvidence: + evidence_type: EvidenceType + evidence: np.ndarray + symbol_set: List[str] diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 290e5e747..a7a0f36e6 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -1,3 +1,5 @@ +import datetime +import logging import random from time import sleep from typing import Optional @@ -7,13 +9,14 @@ from bcipy.helpers import load, stimuli, symbols from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine -from bcipy.simulator.helpers.evidence_fuser import EvidenceFuser from bcipy.simulator.helpers.sampler import Sampler from bcipy.simulator.helpers.state_manager import StateManager, SimState from bcipy.simulator.helpers.types import InquiryResult from bcipy.simulator.interfaces import MetricReferee, ModelHandler from bcipy.simulator.simulator_base import Simulator +log = logging.getLogger(__name__) + class SimulatorCopyPhrase(Simulator): """ @@ -58,25 +61,33 @@ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler self.visualize = visualize def run(self): + log.info(f"SIM START with target word {self.state_manager.get_state().target_sentence}") + while not self.state_manager.is_done(): - print( - f"Series {self.state_manager.get_state().series_n} | Inquiry {self.state_manager.get_state().inquiry_n} | Target {self.state_manager.get_state().target_symbol}") - self.state_manager.mutate_state('display_alphabet', self.__make_stimuli(self.state_manager.get_state())) - sampled_data = self.sampler.sample(self.state_manager.get_state()) - evidence = self.model_handler.generate_evidence(self.state_manager.get_state(), + curr_state = self.state_manager.get_state() + log.info(f"Series {curr_state.series_n} | Inquiry {curr_state.inquiry_n} | Target {curr_state.target_symbol}") + + self.state_manager.mutate_state('display_alphabet', self.__make_stimuli(curr_state)) + sampled_data = self.sampler.sample(curr_state) + evidence = self.model_handler.generate_evidence(curr_state, sampled_data) # TODO make this evidence be a dict (mapping of evidence type to evidence) - print(f"Evidence for stimuli {self.state_manager.get_state().display_alphabet} \n {evidence}") + log.debug(f"Evidence for stimuli {curr_state.display_alphabet} \n {evidence}") inq_record: InquiryResult = self.state_manager.update(evidence) - - print(f"Fused Likelihoods {[str(round(p, 3)) for p in inq_record.fused_likelihood]}") + updated_state = self.state_manager.get_state() + log.debug(f"Fused Likelihoods {[str(round(p, 3)) for p in inq_record.fused_likelihood]}") if inq_record.decision: - print(f"Decided {inq_record.decision} for target {inq_record.target} for sentence {self.state_manager.get_state().target_sentence}") + log.info(f"Decided {inq_record.decision} for target {inq_record.target}") - print("\n") + log.info(f"Current typed: {updated_state.current_sentence}") sleep(.5) + + final_state = self.state_manager.get_state() + log.info(f"SIM END") + log.debug(f"Final State: {final_state}") + # TODO visualize result metrics def __make_stimuli(self, state: SimState): diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py index 96f0cbac0..68ae72b6e 100644 --- a/bcipy/simulator/simulator_base.py +++ b/bcipy/simulator/simulator_base.py @@ -14,7 +14,6 @@ class Simulator(ABC): def __init__(self): super(Simulator, self).__init__() - self.logger = logging.getLogger(__name__) @abstractmethod def run(self): diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index 7c2adea5c..1e8233fca 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -38,7 +38,10 @@ class DummyRef(MetricReferee): if __name__ == "__main__": args = dict() - args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_18hr58min16sec_-0700"] + args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_18hr58min16sec_-0700", + # "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_19hr07min50sec_-0700", + # "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_19hr15min29sec_-0700" + ] args['out_dir'] = Path(__file__).resolve().parent model_file = Path( "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Calibration_Thu_24_Aug_2023_18hr41min37sec_-0700/model_0.9524_200_800.pkl") @@ -66,4 +69,3 @@ class DummyRef(MetricReferee): model_handler = DummyModelHandler(model_file) sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, DummyRef()) sim.run() - breakpoint() From ea5be74346b693297cc281d252c1bd1ea8b8f9e2 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Thu, 16 Nov 2023 14:20:37 -0500 Subject: [PATCH 154/330] Model and visualization updates --- bcipy/helpers/visualization.py | 23 ++++++++- bcipy/signal/model/fusion_model.py | 64 +++++++++++++++--------- bcipy/signal/model/offline_analysis.py | 67 +++++++++++++++++++------- 3 files changed, 114 insertions(+), 40 deletions(-) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index e1ff25ea2..02767b536 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -1,6 +1,6 @@ import logging from pathlib import Path -from typing import List, Optional, Tuple +from typing import List, Dict, Optional, Tuple import matplotlib.pyplot as plt import mne @@ -725,3 +725,24 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi save_path=session_path, show=show, ) + + +def visualize_gaze_accuracies(accuracy_dict: Dict[str, np.ndarray], + accuracy: float, + save_path: Optional[str] = None, + show: Optional[bool] = False) -> Figure: + """ + Visualize Gaze Accuracies. + + Plot the accuracies of each symbol using a bar plot. + + Returns a list of the figure handles created. + """ + + fig, ax = plt.subplots() + ax.bar(accuracy_dict.keys(), accuracy_dict.values()) + ax.set_xlabel('Symbol') + ax.set_ylabel('Accuracy') + ax.set_title('Overall Accuracy: ' + str(round(accuracy, 2))) + + return fig \ No newline at end of file diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py index cd4c03ce6..e47178697 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/fusion_model.py @@ -6,6 +6,10 @@ from bcipy.helpers.stimuli import GazeReshaper from sklearn.model_selection import cross_val_score # noqa from sklearn.utils.estimator_checks import check_estimator # noqa +import cvxpy as cp +import scipy.stats as stats + +from typing import Optional class GazeModel(SignalModel): @@ -15,40 +19,55 @@ def __init__(self, num_components=2): self.num_components = num_components # number of gaussians to fit def fit(self, train_data: np.array): - model = GaussianMixture(n_components=2, random_state=0, init_params='kmeans') + model = GaussianMixture(n_components=1, random_state=0, init_params='kmeans') model.fit(train_data) self.model = model return self - def get_scores(self, test_data: np.array): + def evaluate(self, test_data: np.array): ''' - Compute the log-likelihood of each sample. - Compute the mean and covariance of each mixture component. + Compute mean and covariance of each mixture component. ''' - scores = self.model.score_samples(test_data) means = self.model.means_ covs = self.model.covariances_ - return scores, means, covs + return means, covs - def predict(self, scores: np.array): + def predict(self, test_data: np.array, means: np.array, covs: np.array): ''' + Compute log-likelihood of each sample. Predict the labels for the test data. ''' - # Compute over log-likelihood scores - # Get the argmax of the scores - # return predictions + num_components = len(means) + + N, D = test_data.shape + K = num_components + + likelihoods = np.zeros((N, K), dtype=object) + predictions = np.zeros(N, dtype=object) - def evaluate(self, test_data: np.ndarray, test_labels: np.ndarray): + # Find the likelihoods by insterting the test data into the pdf of each component + for i in range(N): + for k in range(K): + mu = means[k] + sigma = covs[k] + + likelihoods[i,k] = stats.multivariate_normal.pdf(test_data[i], mu, sigma) + + # Find the argmax of the likelihoods to get the predictions + predictions[i] = np.argmax(likelihoods[i]) + + return likelihoods, predictions + + def calculate_acc(self, test_data: np.ndarray, test_labels: Optional[np.ndarray]): ''' Compute model performance characteristics on the provided test data and labels. ''' - # Compute the AUC - # return ModelEvaluationReport(auc) + # return accuracy def save(self, path: Path): """Save model state to the provided checkpoint""" @@ -73,37 +92,38 @@ def fit(self, train_data: np.array): return self - def get_scores(self, test_data: np.array, sym_pos: np.array): + def evaluate(self, test_data: np.array, sym_pos: np.array): ''' - Compute the log-likelihood of each sample. - Return the mean and covariance of each mixture component. + Return mean and covariance of each mixture component. test_data: gaze data for each symbol sym_pos: mid positions for each symbol in Tobii coordinates ''' - scores = self.model.score_samples(test_data) means = self.model.means_ + sym_pos covs = self.model.covariances_ - return scores, means, covs + return means, covs - def predict(self, scores: np.array): + def predict(self, test_data: np.array): ''' + Compute log-likelihood of each sample. Predict the labels for the test data. ''' # Compute over log-likelihood scores # Get the argmax of the scores + scores = self.model.score_samples(test_data) + # return predictions - def evaluate(self, test_data: np.ndarray, test_labels: np.ndarray): + def calculate_acc(self, test_data: np.ndarray, sym_pos: np.array): ''' Compute model performance characteristics on the provided test data and labels. ''' - # Compute the AUC - # return ModelEvaluationReport(auc) + + # return accuracy def save(self, path: Path): """Save model state to the provided checkpoint""" diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 100c34c64..4e76554d8 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -23,7 +23,8 @@ from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import (visualize_erp, visualize_gaze, visualize_centralized_data, - visualize_results_all_symbols) + visualize_results_all_symbols, + visualize_gaze_accuracies) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata from bcipy.signal.model.fusion_model import GazeModel, GazeModel_AllSymbols @@ -312,6 +313,10 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f means_all = [] covs_all = [] for sym in symbol_set: + # Skip if there's no evidence for this symbol: + if len(inquiries[sym]) == 0: + test_dict[sym] = [] + continue le = preprocessed_data[sym][0] re = preprocessed_data[sym][1] @@ -319,24 +324,14 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f labels = np.array([sym] * len(le)) # Labels are the same for both eyes train_le, test_le, train_labels_le, test_labels_le = subset_data(le, labels, test_size=0.2, swap_axes=False) train_re, test_re, train_labels_re, test_labels_re = subset_data(re, labels, test_size=0.2, swap_axes=False) - test_dict[sym] = [test_le, test_re] - - if model_type == "Centralized": - # Centralize the data using symbol positions: - # Load json file. - # TODO: move this to a helper function, or get the symbol positions from the build_grid method - with open(f"{BCIPY_ROOT}/parameters/symbol_positions.json", 'r') as params_file: - symbol_positions = json.load(params_file) - # Subtract the symbol positions from the data: - centralized_data_left.append(model.reshaper.centralize_all_data(train_le, symbol_positions[sym])) - centralized_data_right.append(model.reshaper.centralize_all_data(train_re, symbol_positions[sym])) + test_dict[sym] = np.concatenate((test_le, test_re), axis=0) # Fit the model based on model type. # Model 1: Fit Gaussian mixture (comp=2) on each symbol and each eye separately if model_type == "Individual": model.fit(train_re) - scores, means, covs = model.get_scores(test_re) + means, covs = model.evaluate(test_re) # Visualize the results: # figure_handles = visualize_gaze_inquiries( @@ -351,8 +346,45 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f means_all.append(means) covs_all.append(covs) - if model_type == "Centralized": + # scores, predictions = model.predict(test_re) + # Model 2: Fit Gaussian mixture (comp=1) on a centralized data + if model_type == "Centralized": + # Centralize the data using symbol positions: + # Load json file. + # TODO: move this to a helper function, or get the symbol positions from the build_grid method + with open(f"{BCIPY_ROOT}/parameters/symbol_positions.json", 'r') as params_file: + symbol_positions = json.load(params_file) + # Subtract the symbol positions from the data: + centralized_data_left.append(model.reshaper.centralize_all_data(train_le, symbol_positions[sym])) + centralized_data_right.append(model.reshaper.centralize_all_data(train_re, symbol_positions[sym])) + + if model_type == "Individual": + # Takes in all means and covs from individual symbols, and + # calculates the likelihoods and predictions for each test point. + # Convert test_dict to a list of arrays: + accuracy = 0 + acc_all_symbols = {} + counter = 0 + for sym in symbol_set: + # Skip if test_dict is empty for certain symbols: + if len(test_dict[sym]) == 0: + acc_all_symbols[sym] = 0 + continue + likelihoods, predictions = model.predict(test_dict[sym], np.squeeze(np.array(means_all)), np.squeeze(np.array(covs_all))) + acc_all_symbols[sym] = np.sum(predictions == counter) / len(predictions) * 100 + accuracy += np.sum(predictions == counter) / len(predictions) * 100 + print(f"""Correct predictions for {sym}: {np.sum(predictions == counter)} / {len(predictions)}, + Accuracy {sym}: {np.sum(predictions == counter) / len(predictions) * 100:.2f}""") + counter += 1 + accuracy /= counter + print(f"Overall accuracy: {accuracy:.2f}") + + # Plot all accuracies as bar plot: + figure_handles = visualize_gaze_accuracies(acc_all_symbols, accuracy, save_path=None, show=True) + + + if model_type == "Centralized": cent_left = np.concatenate(np.array(centralized_data_left, dtype=object)) cent_right = np.concatenate(np.array(centralized_data_right, dtype=object)) @@ -370,7 +402,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f # Add the means back to the symbol positions. # Calculate scores for the test set. for sym in symbol_set: - scores, means, covs = model.get_scores(test_dict[sym][0], symbol_positions[sym]) + means, covs = model.evaluate(test_dict[sym][0], symbol_positions[sym]) le = preprocessed_data[sym][0] re = preprocessed_data[sym][1] @@ -387,6 +419,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f means_all.append(means) covs_all.append(covs) + fig_handles = visualize_results_all_symbols( left_eye_all, right_eye_all, means_all, covs_all, @@ -465,7 +498,7 @@ def offline_analysis( if device_spec.content_type == "Eyetracker": analyze_gaze(raw_data, device_spec, data_folder, save_figures, show_figures, - model_type="Centralized") + model_type="Individual") if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") @@ -484,7 +517,7 @@ def offline_analysis( parser.add_argument("--alert", dest="alert", action="store_true") parser.add_argument("--balanced-acc", dest="balanced", action="store_true") parser.set_defaults(alert=False) - parser.set_defaults(balanced=False) + parser.set_defaults(balanced=True) parser.set_defaults(save_figures=False) parser.set_defaults(show_figures=True) args = parser.parse_args() From 08a4b9365a025ddc8508ad5b2cbd84262d517c4c Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 16 Nov 2023 11:22:50 -0800 Subject: [PATCH 155/330] remove unused import --- bcipy/signal/model/fusion_model.py | 1 - 1 file changed, 1 deletion(-) diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/fusion_model.py index e47178697..c6f56de41 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/fusion_model.py @@ -6,7 +6,6 @@ from bcipy.helpers.stimuli import GazeReshaper from sklearn.model_selection import cross_val_score # noqa from sklearn.utils.estimator_checks import check_estimator # noqa -import cvxpy as cp import scipy.stats as stats from typing import Optional From b98cd364ac03d2151c0fc640fcd6c7c7bf2247cd Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 16 Nov 2023 12:12:25 -0800 Subject: [PATCH 156/330] add return type to model training, lint, update the integration tests --- bcipy/helpers/visualization.py | 6 +- bcipy/parameters/parameters.json | 4 +- bcipy/signal/model/__init__.py | 3 + .../signal/model/gaussian_mixture/__init__.py | 6 + .../gaussian_mixture.py} | 21 ++-- bcipy/signal/model/offline_analysis.py | 91 ++++++++++------ .../model/integration_test_input/devices.json | 103 ++++++++++++++++++ .../tests/model/test_offline_analysis.py | 6 +- 8 files changed, 186 insertions(+), 54 deletions(-) create mode 100644 bcipy/signal/model/gaussian_mixture/__init__.py rename bcipy/signal/model/{fusion_model.py => gaussian_mixture/gaussian_mixture.py} (84%) create mode 100644 bcipy/signal/tests/model/integration_test_input/devices.json diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 02767b536..d65340407 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -733,16 +733,16 @@ def visualize_gaze_accuracies(accuracy_dict: Dict[str, np.ndarray], show: Optional[bool] = False) -> Figure: """ Visualize Gaze Accuracies. - + Plot the accuracies of each symbol using a bar plot. Returns a list of the figure handles created. """ - + fig, ax = plt.subplots() ax.bar(accuracy_dict.keys(), accuracy_dict.values()) ax.set_xlabel('Symbol') ax.set_ylabel('Accuracy') ax.set_title('Overall Accuracy: ' + str(round(accuracy, 2))) - return fig \ No newline at end of file + return fig diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index ca61b165c..c1fe3cb0b 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -8,10 +8,10 @@ "type": "bool" }, "acq_mode": { - "value": "EEG+Eyetracker", + "value": "EEG", "section": "acq_config", "readableName": "Acquisition Mode", - "helpTip": "Specifies the hardware device(s) used for data collection.", + "helpTip": "Specifies the hardware device(s) used for data collection. Default: EEG", "recommended_values": [ "EEG", "EEG/DSI-24", diff --git a/bcipy/signal/model/__init__.py b/bcipy/signal/model/__init__.py index d95f3d026..6e9e0a4fe 100644 --- a/bcipy/signal/model/__init__.py +++ b/bcipy/signal/model/__init__.py @@ -1,10 +1,13 @@ from bcipy.signal.model.base_model import SignalModel, ModelEvaluationReport from bcipy.signal.model.pca_rda_kde.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.model.rda_kde.rda_kde import RdaKdeModel +from bcipy.signal.model.gaussian_mixture.gaussian_mixture import GazeModelIndividual, GazeModelCombined __all__ = [ "SignalModel", "PcaRdaKdeModel", "RdaKdeModel", + "GazeModelIndividual", + "GazeModelCombined", "ModelEvaluationReport", ] diff --git a/bcipy/signal/model/gaussian_mixture/__init__.py b/bcipy/signal/model/gaussian_mixture/__init__.py new file mode 100644 index 000000000..1a5dc0dfe --- /dev/null +++ b/bcipy/signal/model/gaussian_mixture/__init__.py @@ -0,0 +1,6 @@ +from .gaussian_mixture import GazeModelCombined, GazeModelIndividual + +__all__ = [ + "GazeModelCombined", + "GazeModelIndividual", +] diff --git a/bcipy/signal/model/fusion_model.py b/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py similarity index 84% rename from bcipy/signal/model/fusion_model.py rename to bcipy/signal/model/gaussian_mixture/gaussian_mixture.py index c6f56de41..29307b84f 100644 --- a/bcipy/signal/model/fusion_model.py +++ b/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py @@ -11,20 +11,20 @@ from typing import Optional -class GazeModel(SignalModel): +class GazeModelIndividual(SignalModel): reshaper = GazeReshaper() def __init__(self, num_components=2): self.num_components = num_components # number of gaussians to fit - def fit(self, train_data: np.array): + def fit(self, train_data: np.ndarray) -> 'GazeModelIndividual': model = GaussianMixture(n_components=1, random_state=0, init_params='kmeans') model.fit(train_data) self.model = model return self - def evaluate(self, test_data: np.array): + def evaluate(self, test_data: np.ndarray): ''' Compute mean and covariance of each mixture component. ''' @@ -34,7 +34,7 @@ def evaluate(self, test_data: np.array): return means, covs - def predict(self, test_data: np.array, means: np.array, covs: np.array): + def predict(self, test_data: np.ndarray, means: np.ndarray, covs: np.ndarray): ''' Compute log-likelihood of each sample. Predict the labels for the test data. @@ -54,7 +54,7 @@ def predict(self, test_data: np.array, means: np.array, covs: np.array): mu = means[k] sigma = covs[k] - likelihoods[i,k] = stats.multivariate_normal.pdf(test_data[i], mu, sigma) + likelihoods[i, k] = stats.multivariate_normal.pdf(test_data[i], mu, sigma) # Find the argmax of the likelihoods to get the predictions predictions[i] = np.argmax(likelihoods[i]) @@ -77,21 +77,21 @@ def load(self, path: Path): ... -class GazeModel_AllSymbols(SignalModel): +class GazeModelCombined(SignalModel): '''Gaze model that uses all symbols to fit a single Gaussian ''' reshaper = GazeReshaper() def __init__(self, num_components=1): self.num_components = num_components # number of gaussians to fit - def fit(self, train_data: np.array): + def fit(self, train_data: np.ndarray): model = GaussianMixture(n_components=1, random_state=0, init_params='kmeans') model.fit(train_data) self.model = model return self - def evaluate(self, test_data: np.array, sym_pos: np.array): + def evaluate(self, test_data: np.ndarray, sym_pos: np.ndarray): ''' Return mean and covariance of each mixture component. @@ -104,7 +104,7 @@ def evaluate(self, test_data: np.array, sym_pos: np.array): return means, covs - def predict(self, test_data: np.array): + def predict(self, test_data: np.ndarray): ''' Compute log-likelihood of each sample. Predict the labels for the test data. @@ -116,12 +116,11 @@ def predict(self, test_data: np.array): # return predictions - def calculate_acc(self, test_data: np.ndarray, sym_pos: np.array): + def calculate_acc(self, test_data: np.ndarray, sym_pos: np.ndarray): ''' Compute model performance characteristics on the provided test data and labels. ''' - # return accuracy def save(self, path: Path): diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 4e76554d8..9a967515e 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -11,7 +11,7 @@ import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, BCIPY_ROOT, DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH, - STATIC_IMAGES_PATH, TRIGGER_FILENAME) + TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) @@ -22,12 +22,13 @@ from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import (visualize_erp, visualize_gaze, + visualize_gaze_inquiries, visualize_centralized_data, visualize_results_all_symbols, visualize_gaze_accuracies) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata -from bcipy.signal.model.fusion_model import GazeModel, GazeModel_AllSymbols +from bcipy.signal.model.gaussian_mixture import GazeModelIndividual, GazeModelCombined from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import (ERPTransformParams, extract_eye_info, filter_inquiries, get_default_transform) @@ -35,11 +36,6 @@ log = logging.getLogger(__name__) logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") -DIPSIZE = (1707, 1067) -IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix_grid.png' -# IMG_PATH = f'{STATIC_IMAGES_PATH}/main/rsvp.png' -# TODO: Update images to contain the path to directory of the respective calibration session. - def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_state: int = 0, swap_axes: bool = True): """Performs a train/test split on the provided data and labels, accounting for @@ -215,9 +211,17 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance save_path=data_folder if save_figures else None, show=show_figures ) + return model, figure_handles -def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_figures=False, model_type="Individual"): +def analyze_gaze( + gaze_data, + parameters, + device_spec, + data_folder, + save_figures=False, + show_figures=False, + model_type="Individual"): """Analyze gaze data and return/save the gaze model. Extract relevant information from gaze data object. Extract timing information from trigger file. @@ -230,6 +234,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f Parameters: ----------- gaze_data (RawData): RawData object containing the data to be analyzed. + parameters (Parameters): Parameters object retireved from parameters.json. device_spec (DeviceSpec): DeviceSpec object containing information about the device used. data_folder (str): Path to the folder containing the data to be analyzed. save_figures (bool): If true, saves ERP figures after training to the data folder. @@ -238,12 +243,14 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f "Individual": Fits a separate Gaussian for each symbol. Default model "Centralized": Uses data from all symbols to fit a single centralized Gaussian """ + figures = [] figure_handles = visualize_gaze( gaze_data, save_path=data_folder if save_figures else None, show=show_figures, raw_plot=True, ) + figures.extend(figure_handles) channels = gaze_data.channels type_amp = gaze_data.daq_type @@ -256,12 +263,12 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] log.info(f'Channels used in analysis: {channels_used}') - data, fs = gaze_data.by_channel() + data, _fs = gaze_data.by_channel() if model_type == "Individual": - model = GazeModel() + model = GazeModelIndividual() elif model_type == "Centralized": - model = GazeModel_AllSymbols() + model = GazeModelCombined() # Extract all Triggers info trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( @@ -334,25 +341,26 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f means, covs = model.evaluate(test_re) # Visualize the results: - # figure_handles = visualize_gaze_inquiries( - # le, re, - # means, covs, - # save_path=None, - # show=show_figures, - # raw_plot=True, - # ) + figure_handles = visualize_gaze_inquiries( + le, re, + means, covs, + save_path=None, + show=show_figures, + raw_plot=True, + ) + figures.extend(figure_handles) left_eye_all.append(le) right_eye_all.append(re) means_all.append(means) covs_all.append(covs) + # TODO: Calculate scores for the test set. # scores, predictions = model.predict(test_re) # Model 2: Fit Gaussian mixture (comp=1) on a centralized data if model_type == "Centralized": # Centralize the data using symbol positions: # Load json file. - # TODO: move this to a helper function, or get the symbol positions from the build_grid method with open(f"{BCIPY_ROOT}/parameters/symbol_positions.json", 'r') as params_file: symbol_positions = json.load(params_file) # Subtract the symbol positions from the data: @@ -371,10 +379,13 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f if len(test_dict[sym]) == 0: acc_all_symbols[sym] = 0 continue - likelihoods, predictions = model.predict(test_dict[sym], np.squeeze(np.array(means_all)), np.squeeze(np.array(covs_all))) + likelihoods, predictions = model.predict( + test_dict[sym], np.squeeze( + np.array(means_all)), np.squeeze( + np.array(covs_all))) acc_all_symbols[sym] = np.sum(predictions == counter) / len(predictions) * 100 accuracy += np.sum(predictions == counter) / len(predictions) * 100 - print(f"""Correct predictions for {sym}: {np.sum(predictions == counter)} / {len(predictions)}, + print(f"""Correct predictions for {sym}: {np.sum(predictions == counter)} / {len(predictions)}, Accuracy {sym}: {np.sum(predictions == counter) / len(predictions) * 100:.2f}""") counter += 1 accuracy /= counter @@ -382,7 +393,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f # Plot all accuracies as bar plot: figure_handles = visualize_gaze_accuracies(acc_all_symbols, accuracy, save_path=None, show=True) - + figures.extend(figure_handles) if model_type == "Centralized": cent_left = np.concatenate(np.array(centralized_data_left, dtype=object)) @@ -395,6 +406,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f show=show_figures, raw_plot=True, ) + figures.extend(figure_handles) # Fit the model: model.fit(cent_left) @@ -407,19 +419,19 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f le = preprocessed_data[sym][0] re = preprocessed_data[sym][1] # Visualize the results: - # figure_handles = visualize_gaze_inquiries( - # le, re, - # means, covs, - # save_path=None, - # show=show_figures, - # raw_plot=True, - # ) + figure_handles = visualize_gaze_inquiries( + le, re, + means, covs, + save_path=None, + show=show_figures, + raw_plot=True, + ) + figures.extend(figure_handles) left_eye_all.append(le) right_eye_all.append(re) means_all.append(means) covs_all.append(covs) - fig_handles = visualize_results_all_symbols( left_eye_all, right_eye_all, means_all, covs_all, @@ -427,6 +439,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f show=True, raw_plot=True, ) + figures.extend(fig_handles) model.metadata = SignalModelMetadata(device_spec=device_spec, transform=None) @@ -434,6 +447,7 @@ def analyze_gaze(gaze_data, device_spec, data_folder, save_figures=False, show_f save_model( model, Path(data_folder, f"model_{device_spec.content_type}_{model_type}.pkl")) + return model, figures @report_execution_time @@ -488,22 +502,27 @@ def offline_analysis( if path.exists() ] + models = [] + figure_handles = [] for raw_data_path in data_file_paths: raw_data = load_raw_data(raw_data_path) device_spec = devices_by_name.get(raw_data.daq_type) # extract relevant information from raw data object eeg if device_spec.content_type == "EEG": - analyze_erp(raw_data, parameters, device_spec, data_folder, estimate_balanced_acc, - save_figures, show_figures) + erp_model, erp_figure_handles = analyze_erp( + raw_data, parameters, device_spec, data_folder, estimate_balanced_acc, save_figures, show_figures) + models.append(erp_model) + figure_handles.extend(erp_figure_handles) if device_spec.content_type == "Eyetracker": - analyze_gaze(raw_data, device_spec, data_folder, save_figures, show_figures, - model_type="Individual") + et_model, et_figure_handles = analyze_gaze( + raw_data, parameters, device_spec, data_folder, save_figures, show_figures, model_type="Individual") + models.append(et_model) + figure_handles.extend(et_figure_handles) if alert_finished: play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") - # return model, figure_handles - return + return models, figure_handles if __name__ == "__main__": diff --git a/bcipy/signal/tests/model/integration_test_input/devices.json b/bcipy/signal/tests/model/integration_test_input/devices.json new file mode 100644 index 000000000..48af0e2bc --- /dev/null +++ b/bcipy/signal/tests/model/integration_test_input/devices.json @@ -0,0 +1,103 @@ +[ + { + "name": "DSI-24", + "content_type": "EEG", + "channels": [ + { "name": "P3", "label": "P3", "units": "microvolts", "type": "EEG" }, + { "name": "C3", "label": "C3", "units": "microvolts", "type": "EEG" }, + { "name": "F3", "label": "F3", "units": "microvolts", "type": "EEG" }, + { "name": "Fz", "label": "Fz", "units": "microvolts", "type": "EEG" }, + { "name": "F4", "label": "F4", "units": "microvolts", "type": "EEG" }, + { "name": "C4", "label": "C4", "units": "microvolts", "type": "EEG" }, + { "name": "P4", "label": "P4", "units": "microvolts", "type": "EEG" }, + { "name": "Cz", "label": "Cz", "units": "microvolts", "type": "EEG" }, + { "name": "Pz", "label": "Pz", "units": "microvolts", "type": "EEG" }, + { "name": "Fp1", "label": "Fp1", "units": "microvolts", "type": "EEG" }, + { "name": "Fp2", "label": "Fp2", "units": "microvolts", "type": "EEG" }, + { "name": "T3", "label": "T3", "units": "microvolts", "type": "EEG" }, + { "name": "T5", "label": "T5", "units": "microvolts", "type": "EEG" }, + { "name": "O1", "label": "O1", "units": "microvolts", "type": "EEG" }, + { "name": "O2", "label": "O2", "units": "microvolts", "type": "EEG" }, + { "name": "X3", "label": "X3", "units": "microvolts", "type": "EEG" }, + { "name": "X2", "label": "X2", "units": "microvolts", "type": "EEG" }, + { "name": "F7", "label": "F7", "units": "microvolts", "type": "EEG" }, + { "name": "F8", "label": "F8", "units": "microvolts", "type": "EEG" }, + { "name": "X1", "label": "X1", "units": "microvolts", "type": "EEG" }, + { "name": "A2", "label": "A2", "units": "microvolts", "type": "EEG" }, + { "name": "T6", "label": "T6", "units": "microvolts", "type": "EEG" }, + { "name": "T4", "label": "T4", "units": "microvolts", "type": "EEG" }, + { "name": "TRG", "label": "TRG", "units": "microvolts", "type": "EEG "} + ], + "sample_rate": 300.0, + "description": "Wearable Sensing DSI-24", + "excluded_from_analysis": [ + "TRG", + "X1", "X2", "X3", + "A2", + "T3", "T4", + "Fp1", "Fp2", + "F7", "F8", + "P3", "P4", + "F3", "F4", + "C3", "C4" + ] + }, + { + "name": "DSI-VR300", + "content_type": "EEG", + "channels": [ + { "name": "P4", "label": "P4", "units": "microvolts", "type": "EEG" }, + { "name": "Fz", "label": "Fz", "units": "microvolts", "type": "EEG" }, + { "name": "Pz", "label": "Pz", "units": "microvolts", "type": "EEG" }, + { "name": "F7", "label": "F7", "units": "microvolts", "type": "EEG" }, + { "name": "PO8", "label": "PO8", "units": "microvolts", "type": "EEG" }, + { "name": "PO7", "label": "PO7", "units": "microvolts", "type": "EEG" }, + { "name": "Oz", "label": "Oz", "units": "microvolts", "type": "EEG" }, + { "name": "TRG", "label": "TRG", "units": "microvolts", "type": "EEG" } + ], + "sample_rate": 300.0, + "description": "Wearable Sensing DSI-VR300", + "excluded_from_analysis": ["TRG", "F7"] + }, + { + "name": "g.USBamp-1", + "content_type": "EEG", + "channels": [ + { "name": "Ch1", "label": "Ch1", "units": "microvolts", "type": "EEG" }, + { "name": "Ch2", "label": "Ch2", "units": "microvolts", "type": "EEG" }, + { "name": "Ch3", "label": "Ch3", "units": "microvolts", "type": "EEG" }, + { "name": "Ch4", "label": "Ch4", "units": "microvolts", "type": "EEG" }, + { "name": "Ch5", "label": "Ch5", "units": "microvolts", "type": "EEG" }, + { "name": "Ch6", "label": "Ch6", "units": "microvolts", "type": "EEG" }, + { "name": "Ch7", "label": "Ch7", "units": "microvolts", "type": "EEG" }, + { "name": "Ch8", "label": "Ch8", "units": "microvolts", "type": "EEG" }, + { "name": "Ch9", "label": "Ch9", "units": "microvolts", "type": "EEG" }, + { "name": "Ch10", "label": "Ch10", "units": "microvolts", "type": "EEG" }, + { "name": "Ch11", "label": "Ch11", "units": "microvolts", "type": "EEG" }, + { "name": "Ch12", "label": "Ch12", "units": "microvolts", "type": "EEG" }, + { "name": "Ch13", "label": "Ch13", "units": "microvolts", "type": "EEG" }, + { "name": "Ch14", "label": "Ch14", "units": "microvolts", "type": "EEG" }, + { "name": "Ch15", "label": "Ch15", "units": "microvolts", "type": "EEG" }, + { "name": "Ch16", "label": "Ch16", "units": "microvolts", "type": "EEG" } + ], + "sample_rate": 256.0, + "description": "GTec g.USBamp" + }, + { + "name": "Tobii Nano", + "content_type": "Eyetracker", + "channels": [ + { "name": "device_ts", "label": "device_ts" }, + { "name": "system_ts", "label": "system_ts" }, + { "name": "left_x", "label": "left_x", "units": "screencoords", "type": "ScreenX" }, + { "name": "left_y", "label": "left_y", "units": "screencoords", "type": "ScreenY" }, + { "name": "left_pupil", "label": "left_pupil", "type": "pupilsize" }, + { "name": "right_x", "label": "right_x", "units": "screencoords", "type": "ScreenX" }, + { "name": "right_y", "label": "right_y", "units": "screencoords", "type": "ScreenY" }, + { "name": "right_pupil", "label": "right_pupil", "type": "pupilsize" } + ], + "sample_rate": 60.0, + "description": "Tobii Nano. For use with the Tobii Pro SDK.", + "excluded_from_analysis": ["device_ts", "system_ts", "left_pupil", "right_pupil"] + } +] \ No newline at end of file diff --git a/bcipy/signal/tests/model/test_offline_analysis.py b/bcipy/signal/tests/model/test_offline_analysis.py index 5ad4ca148..3f8535e2e 100644 --- a/bcipy/signal/tests/model/test_offline_analysis.py +++ b/bcipy/signal/tests/model/test_offline_analysis.py @@ -9,7 +9,7 @@ import random import gzip -from bcipy.config import RAW_DATA_FILENAME, DEFAULT_PARAMETER_FILENAME, TRIGGER_FILENAME +from bcipy.config import RAW_DATA_FILENAME, DEFAULT_PARAMETER_FILENAME, TRIGGER_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME from bcipy.helpers.load import load_json_parameters from bcipy.signal.model.offline_analysis import offline_analysis @@ -46,11 +46,13 @@ def setUpClass(cls): # copy the other required inputs into tmp_dir shutil.copyfile(input_folder / TRIGGER_FILENAME, cls.tmp_dir / TRIGGER_FILENAME) + shutil.copyfile(input_folder / DEFAULT_DEVICE_SPEC_FILENAME, cls.tmp_dir / DEFAULT_DEVICE_SPEC_FILENAME) params_path = pwd.parent.parent.parent / "parameters" / DEFAULT_PARAMETER_FILENAME cls.parameters = load_json_parameters(params_path, value_cast=True) - cls.model, fig_handles = offline_analysis( + models, fig_handles = offline_analysis( str(cls.tmp_dir), cls.parameters, save_figures=True, show_figures=False, alert_finished=False) + cls.model = models[0] cls.mean_erp_fig_handle = fig_handles[0] cls.mean_nontarget_topomap_handle = fig_handles[1] cls.mean_target_topomap_handle = fig_handles[2] From fd865d02e7c53526b101b59d85dd54da84e0a9b8 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 16 Nov 2023 12:19:16 -0800 Subject: [PATCH 157/330] add symbol set as an arg to gaze reshaper, remove todo --- bcipy/helpers/stimuli.py | 5 +---- bcipy/signal/model/offline_analysis.py | 5 +++-- 2 files changed, 4 insertions(+), 6 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 097f86b2e..8475a2d4e 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -236,6 +236,7 @@ def __call__(self, target_symbols: List[str], gaze_data: np.ndarray, sample_rate: int, + symbol_set: List[str], channel_map: List[int] = None, ) -> dict: """Extract inquiry data and labels. Different from the EEG inquiry, the gaze inquiry window starts with @@ -282,8 +283,6 @@ def __call__(self, # Label for every inquiry labels = target_symbols - symbol_set = alphabet() - # Create a dictionary with symbols as keys and data as values # 'A': [], 'B': [] ... data_by_targets = {} @@ -333,8 +332,6 @@ def centralize_all_data(data, symbol_pos): """ for i in range(len(data)): data[i] = data[i] - symbol_pos - # TODO: List comprehension - return data diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 9a967515e..e0a73a95f 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -291,14 +291,15 @@ def analyze_gaze( inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) # Extract the inquiries dictionary with keys as target symbols and values as inquiry windows: + symbol_set = alphabet() inquiries = model.reshaper( inq_start_times=inq_start, target_symbols=target_symbols, gaze_data=data, - sample_rate=sample_rate + sample_rate=sample_rate, + symbol_set=symbol_set ) - symbol_set = alphabet() # Extract the data for each target label and each eye separately. # Apply preprocessing: From d7a6739064ba43fd0a9b5e40eb59f614e77ebc0f Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 16 Nov 2023 12:21:50 -0800 Subject: [PATCH 158/330] update filename --- bcipy/helpers/tests/test_acquisition.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/helpers/tests/test_acquisition.py b/bcipy/helpers/tests/test_acquisition.py index 1cc741ca7..3ec07e6ed 100644 --- a/bcipy/helpers/tests/test_acquisition.py +++ b/bcipy/helpers/tests/test_acquisition.py @@ -177,8 +177,8 @@ def test_raw_data_filename_eeg(self): content_type='EEG') self.assertEqual(raw_data_filename(device), f'{RAW_DATA_FILENAME}.csv') - def test_raw_data_filename(self): - """Test generation of filename""" + def test_raw_data_filename_eye_tracker(self): + """Test generation of filename for EyeTracker devices""" device = DeviceSpec(name='Tobii-P0', channels=[], From 17051a2ad6891182551aa5676b981f6a83cc81c7 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Thu, 16 Nov 2023 12:26:47 -0800 Subject: [PATCH 159/330] add documentation and linting --- README.md | 2 +- bcipy/helpers/stimuli.py | 1 - bcipy/signal/model/README.md | 4 ++++ bcipy/signal/model/offline_analysis.py | 1 - 4 files changed, 5 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index f43991916..ee5f86959 100644 --- a/README.md +++ b/README.md @@ -102,7 +102,7 @@ This a list of the major modules and their functionality. Each module will conta - `acquisition`: acquires data, gives back desired time series, saves to file at end of session. - `display`: handles display of stimuli on screen and passes back stimuli timing. -- `signal`: eeg signal models, filters, processing, evaluators and viewers. +- `signal`: eeg signal models, gaze signal models, filters, processing, evaluators and viewers. - `gui`: end-user interface into registered bci tasks and parameter editing. See BCInterface.py. - `helpers`: helpful functions needed for interactions between modules, basic I/O, and data visualization. - `language`: gives probabilities of next symbols during typing. diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 8475a2d4e..7d5e2d0a4 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -14,7 +14,6 @@ from bcipy.helpers.exceptions import BciPyCoreException from bcipy.helpers.list import grouper -from bcipy.helpers.symbols import alphabet # Prevents pillow from filling the console with debug info logging.getLogger('PIL').setLevel(logging.WARNING) diff --git a/bcipy/signal/model/README.md b/bcipy/signal/model/README.md index 6a270ed8f..ad49a0aba 100644 --- a/bcipy/signal/model/README.md +++ b/bcipy/signal/model/README.md @@ -16,6 +16,10 @@ This model involves the following stages: 6. In order to make a Bayesian update, we need to compute the ratio of the generative likelihood terms for the presented letter (`p(eeg | +)` and `p(eeg | -)`). This ratio is obtained from the final kernel density estimation step and is used in the final decision rule. See `pca_rda_kde/pca_rda_kde.py`. +## Gaze Model! + +We have one! Documentation to come... + ## RDA/KDE Model This model involves the following stages: diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index e0a73a95f..39e864453 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -300,7 +300,6 @@ def analyze_gaze( symbol_set=symbol_set ) - # Extract the data for each target label and each eye separately. # Apply preprocessing: preprocessed_data = {i: [] for i in symbol_set} From 630481beb12277a5f4fbde64b6d708b83084640e Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 17 Nov 2023 11:00:09 -0800 Subject: [PATCH 160/330] Refactoring --- bcipy/display/paradigm/vep/codes.py | 46 ++++ bcipy/display/paradigm/vep/layout.py | 14 +- bcipy/display/paradigm/vep/vep_stim.py | 1 + bcipy/display/tests/vep/test_codes.py | 66 +++++ bcipy/helpers/list.py | 6 +- bcipy/helpers/stimuli.py | 248 +----------------- bcipy/helpers/tests/test_stimuli.py | 57 +--- bcipy/task/paradigm/vep/calibration.py | 6 +- bcipy/task/paradigm/vep/stim_generation.py | 214 +++++++++++++++ .../tests/paradigm/vep}/test_stimuli_vep.py | 4 +- 10 files changed, 350 insertions(+), 312 deletions(-) create mode 100644 bcipy/display/tests/vep/test_codes.py create mode 100644 bcipy/task/paradigm/vep/stim_generation.py rename bcipy/{helpers/tests => task/tests/paradigm/vep}/test_stimuli_vep.py (96%) diff --git a/bcipy/display/paradigm/vep/codes.py b/bcipy/display/paradigm/vep/codes.py index 1ec003ffd..ae54af88f 100644 --- a/bcipy/display/paradigm/vep/codes.py +++ b/bcipy/display/paradigm/vep/codes.py @@ -1,8 +1,13 @@ """Functions related to VEP flash rates""" +import logging from typing import List import numpy as np +from bcipy.helpers.exceptions import BciPyCoreException + +log = logging.getLogger(__name__) + def create_vep_codes(length=32, count=4) -> List[List[int]]: """Create a list of random VEP codes. @@ -14,3 +19,44 @@ def create_vep_codes(length=32, count=4) -> List[List[int]]: """ np.random.seed(1) return [np.random.randint(2, size=length) for _ in range(count)] + + +def ssvep_to_code(refresh_rate: int = 60, flicker_rate: int = 10) -> List[int]: + """Convert SSVEP to Code. + + Converts a SSVEP (steady state visual evoked potential; ex. 10 Hz) to a code (0,1) + given the refresh rate of the monitor (Hz) provided and a desired flicker rate (Hz). + + Parameters: + ----------- + refresh_rate: int, refresh rate of the monitor (Hz) + flicker_rate: int, desired flicker rate (Hz) + Returns: + -------- + list of 0s and 1s that represent the code for the SSVEP on the monitor. + """ + if flicker_rate > refresh_rate: + raise BciPyCoreException( + 'flicker rate cannot be greater than refresh rate') + if flicker_rate <= 1: + raise BciPyCoreException('flicker rate must be greater than 1') + + # get the number of frames per flicker + length_flicker = refresh_rate / flicker_rate + + if length_flicker.is_integer(): + length_flicker = int(length_flicker) + else: + err_message = f'flicker rate={flicker_rate} is not an integer multiple of refresh rate={refresh_rate}' + log.exception(err_message) + raise BciPyCoreException(err_message) + + # start the first frames as off (0) for length of flicker; + # it will then toggle on (1)/ off (0) for length of flicker until all frames are filled for refresh rate. + t = 0 + codes = [] + for _ in range(flicker_rate): + codes += [t] * length_flicker + t = 1 - t + + return codes diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index 5859831b2..2a873c044 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -169,8 +169,18 @@ def positions(self) -> List[Tuple]: return [(left, top), (right, top), (left, bottom), (right, bottom)] middle = layout.horizontal_middle - return [(left, top), (middle, top), (right, top), - (left, bottom), (middle, bottom), (right, bottom)] + return [(left, top), (middle, top), (right, top), (left, bottom), + (middle, bottom), (right, bottom)] + + @property + def names(self) -> List[str]: + """Box names for each position.""" + if self.num_boxes == 4: + return ['LEFT_TOP', 'RIGHT_TOP', 'LEFT_BOTTOM', 'RIGHT_BOTTOM'] + return [ + 'LEFT_TOP', 'MIDDLE_TOP', 'RIGHT_TOP', 'LEFT_BOTTOM', + 'MIDDLE_BOTTOM', 'RIGHT_BOTTOM' + ] def animation_path(start_pos: Tuple[float, float], end_pos: Tuple[float, diff --git a/bcipy/display/paradigm/vep/vep_stim.py b/bcipy/display/paradigm/vep/vep_stim.py index 366f6e836..c7e04d11d 100644 --- a/bcipy/display/paradigm/vep/vep_stim.py +++ b/bcipy/display/paradigm/vep/vep_stim.py @@ -1,3 +1,4 @@ +"""Display components for VEP""" from typing import List, Tuple from psychopy import visual # type: ignore diff --git a/bcipy/display/tests/vep/test_codes.py b/bcipy/display/tests/vep/test_codes.py new file mode 100644 index 000000000..56f399796 --- /dev/null +++ b/bcipy/display/tests/vep/test_codes.py @@ -0,0 +1,66 @@ +import unittest + +from bcipy.display.paradigm.vep.codes import ssvep_to_code +from bcipy.helpers.exceptions import BciPyCoreException + + +class SSVEPStimuli(unittest.TestCase): + """Tests for ssvep_to_code""" + + def test_default_flicker_and_refresh_rate_return_codes(self): + """Test defaults""" + response = ssvep_to_code() + self.assertIsInstance(response, list) + self.assertEqual(response[0], 0) + + def test_ssvep_to_codes_returns_the_length_of_refresh_rate(self): + """Test with custom refresh rate""" + refresh_rate = 40 + flicker_rate = 2 + response = ssvep_to_code(flicker_rate=flicker_rate, + refresh_rate=refresh_rate) + self.assertTrue(len(response) == refresh_rate) + self.assertEqual(response[0], 0) + self.assertEqual(response[-1], 1) + + def test_exception_when_refresh_rate_less_than_flicker_rate(self): + """Test refresh rate less than flicker rate""" + flicker_rate = 300 + refresh_rate = 1 + + with self.assertRaises(BciPyCoreException): + ssvep_to_code(refresh_rate, flicker_rate) + + def test_refresh_rate_not_evenly_divisible(self): + """Test when refresh to flicker rates is not evenly divisible.""" + flicker_rate = 11 + refresh_rate = 60 + + with self.assertRaises(BciPyCoreException): + ssvep_to_code(refresh_rate, flicker_rate) + + def test_expected_codes(self): + """Test that the expected codes are returned""" + flicker_rate = 2 + refresh_rate = 4 + response = ssvep_to_code(flicker_rate=flicker_rate, + refresh_rate=refresh_rate) + expected_output = [0, 0, 1, 1] + self.assertEqual(response, expected_output) + + def test_insufficient_flicker_rate(self): + """Test that an exception is thrown when the flicker rate is 1 or less + """ + flicker_rate = 1 + refresh_rate = 2 + with self.assertRaises(BciPyCoreException): + ssvep_to_code(refresh_rate, flicker_rate) + + flicker_rate = 0 + refresh_rate = 2 + with self.assertRaises(BciPyCoreException): + ssvep_to_code(refresh_rate, flicker_rate) + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/helpers/list.py b/bcipy/helpers/list.py index d1fca1004..d1e86ead1 100644 --- a/bcipy/helpers/list.py +++ b/bcipy/helpers/list.py @@ -50,16 +50,16 @@ def find_index(iterable: List, return None -def swapped(lst: List, index1: int, index2: int) -> None: +def swapped(lst: List[Any], index1: int, index2: int) -> List[Any]: """Creates a copy of the provided list with elements at the given indices swapped.""" replacements = {index1: lst[index2], index2: lst[index1]} return [replacements.get(i, val) for i, val in enumerate(lst)] -def expanded(lst: List, +def expanded(lst: List[Any], length: int, - fill: Union[Any, Callable] = lambda x: x[-1]) -> List: + fill: Union[Any, Callable] = lambda x: x[-1]) -> List[Any]: """Creates a copy of the provided list expanded to the given length. By default the last item is used as the fill item. diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 8a38ec318..95f20f152 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -1,20 +1,19 @@ import glob import itertools import logging -import math import random import re from abc import ABC, abstractmethod from collections import Counter from enum import Enum from os import path, sep -from typing import Any, Dict, Iterator, List, NamedTuple, Optional, Tuple +from typing import Dict, Iterator, List, NamedTuple, Optional, Tuple from pandas import Series from PIL import Image from bcipy.helpers.exceptions import BciPyCoreException -from bcipy.helpers.list import find_index, grouper, swapped +from bcipy.helpers.list import grouper # Prevents pillow from filling the console with debug info logging.getLogger('PIL').setLevel(logging.WARNING) @@ -1030,246 +1029,3 @@ def get_fixation(is_txt: bool) -> str: return DEFAULT_TEXT_FIXATION else: return DEFAULT_FIXATION_PATH - - -def ssvep_to_code(refresh_rate: int = 60, flicker_rate: int = 10) -> List[int]: - """Convert SSVEP to Code. - - Converts a SSVEP (steady state visual evoked potential; ex. 10 Hz) to a code (0,1) - given the refresh rate of the monitor (Hz) provided and a desired flicker rate (Hz). - - Parameters: - ----------- - refresh_rate: int, refresh rate of the monitor (Hz) - flicker_rate: int, desired flicker rate (Hz) - Returns: - -------- - list of 0s and 1s that represent the code for the SSVEP on the monitor. - """ - if flicker_rate > refresh_rate: - raise BciPyCoreException('flicker rate cannot be greater than refresh rate') - if flicker_rate <= 1: - raise BciPyCoreException('flicker rate must be greater than 1') - - # get the number of frames per flicker - length_flicker = refresh_rate / flicker_rate - - if length_flicker.is_integer(): - length_flicker = int(length_flicker) - else: - err_message = f'flicker rate={flicker_rate} is not an integer multiple of refresh rate={refresh_rate}' - log.exception(err_message) - raise BciPyCoreException(err_message) - - # start the first frames as off (0) for length of flicker; - # it will then toggle on (1)/ off (0) for length of flicker until all frames are filled for refresh rate. - t = 0 - codes = [] - for _ in range(flicker_rate): - codes += [t] * length_flicker - t = 1 - t - - return codes - - -def generate_vep_calibration_inquiries(alp: List[str], - timing: List[float] = None, - color: List[str] = None, - inquiry_count: int = 100, - num_boxes: int = 4, - is_txt: bool = True) -> InquirySchedule: - """ - Generates VEP inquiries with target letters in all possible positions. - - In the VEP paradigm, all stimuli in the alphabet are displayed in each - inquiry. The symbols with the highest likelihoods are displayed alone - while those with lower likelihoods occur together. - - Parameters - ---------- - alp(list[str]): stimuli - timing(list[float]): Task specific timing for generator. - [target, fixation, stimuli] - color(list[str]): Task specific color for generator - [target, fixation, stimuli] - inquiry_count(int): number of inquiries in a calibration - num_boxes(int): number of display boxes - is_txt(bool): whether the stimuli type is text. False would be an image stimuli. - - Return - ------ - schedule_inq(tuple( - samples[list[list[str]]]: list of inquiries - timing(list[list[float]]): list of timings - color(list(list[str])): list of colors)): scheduled inquiries - """ - if timing is None: - timing = [0.5, 1, 2] - default_colors = [ - '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' - ] - if color is None: - box_colors = list( - itertools.islice(itertools.cycle(default_colors), num_boxes)) - color = ['green', 'red'] + box_colors - assert len( - timing - ) == 3, "timing must include values for [target, fixation, stimuli]" - - inquiries = generate_vep_inquiries(alp, num_boxes, inquiry_count, is_txt) - times = [timing for _ in range(inquiry_count)] - colors = [color for _ in range(inquiry_count)] - - return InquirySchedule(inquiries, times, colors) - - -def generate_vep_inquiries(symbols: List[str], - num_boxes: int = 6, - inquiry_count: int = 20, - is_txt: bool = True) -> List[List[Any]]: - """Generates inquiries""" - fixation = get_fixation(is_txt) - target_indices = random_target_positions(inquiry_count, - stim_per_inquiry=num_boxes, - percentage_without_target=0) - - # repeat the symbols as necessary to ensure an adequate size for sampling - # without replacement. - population = symbols * math.ceil(inquiry_count / len(symbols)) - targets = random.sample(population, inquiry_count) - - return [[target, fixation] + generate_vep_inquiry(alphabet=symbols, - num_boxes=num_boxes, - target=target, - target_pos=target_pos) - for target, target_pos in zip(targets, target_indices)] - - -def stim_per_box(num_symbols: int, - num_boxes: int = 6, - max_empty_boxes: int = 0, - max_single_sym_boxes: int = 4) -> List[int]: - """Determine the number of stimuli per vep box. - - Parameters - ---------- - num_symbols - number of symbols - num_boxes - number of boxes - max_empty_boxes - the maximum number of boxes which won't have any - symbols within them. - max_single_sym_boxes - maximum number of boxes with a single symbol - - Returns - ------- - A list of length num_boxes, where each number in the list represents - the number of symbols that should be in the box at that position. - - Post conditions: - The sum of the list should equal num_symbols. Further, there should - be at most max_empty_boxes with value of 0 and max_single_sym_boxes - with a value of 1. - """ - # Logic based off of example sessions from: - # https://www.youtube.com/watch?v=JNFYSeIIOrw - # [[2, 3, 5, 5, 6, 7], - # [2, 1, 10, 1, 1, 13], - # [3, 4, 17, 1, 1, 2], - # [1, 1, 1, 0, 1, 24], - # [1, 2, 1, 22, 1, 1], - # [2, 1, 1, 21, 2, 1], - # [1, 1, 25, 0, 1, 0]] - # and - # [[7, 3, 4, 9, 2, 3], - # 1, 1, 6, 9, 7, 2], - # 1, 2, 18, 2, 3, 2], - # 1, 1, 4, 4, 17, 1], - # 1, 3, 1, 1, 20, 2], - # 1, 1, 1, 20, 3, 2], - # 1, 1, 1, 4, 21, 0]] - - if max_empty_boxes + max_single_sym_boxes >= num_boxes: - max_empty_boxes = 0 - max_single_sym_boxes = num_boxes - 1 - - # no more than 1 empty box - empty_boxes = [0] * random.choice(range(max_empty_boxes + 1)) - - # no more than 4 boxes with a single symbol - single_boxes = [1] * random.choice( - range((max_single_sym_boxes + 1) - len(empty_boxes))) - - boxes = empty_boxes + single_boxes - - remaining_symbols = num_symbols - sum(boxes) - remaining_boxes = num_boxes - len(boxes) - - # iterate through the remaining boxes except for the last one - for _box in range(remaining_boxes - 1): - # each remaining box must have 2 or more symbols - box_max = remaining_symbols - (2 * remaining_boxes - 1) - - n = random.choice(range(2, box_max + 1)) - boxes.append(n) - remaining_boxes -= 1 - remaining_symbols = remaining_symbols - n - - # last box - boxes.append(remaining_symbols) - - return sorted(boxes) - - -def generate_vep_inquiry(alphabet: List[str], - num_boxes: int = 6, - target: Optional[str] = None, - target_pos: Optional[int] = None) -> List[List[str]]: - """Generates a single random inquiry. - - Parameters - ---------- - alphabet - list of symbols from which to select. - num_boxes - number of display areas; symbols will be partitioned into - these areas. - target - target symbol for the generated inquiry - target_pos - box index that should contain the target - - Returns - ------- - An inquiry represented by a list of lists, where each sublist - represents a display box and contains symbols that should appear in that box. - - Post-conditions: - Symbols will not be repeated and all symbols will be partitioned into - one of the boxes. - """ - - box_counts = stim_per_box(num_symbols=len(alphabet), num_boxes=num_boxes) - assert len(box_counts) == num_boxes - syms = [sym for sym in alphabet] - random.shuffle(syms) - - if target: - # Move the target to the front so it gets put in the lowest count box - # greater than 0. - syms = swapped(syms, index1=0, index2=syms.index(target)) - # Put syms in boxes - boxes = [] - sym_index = 0 - for count in box_counts: - box = [] - for _i in range(count): - box.append(syms[sym_index]) - sym_index += 1 - box.sort() # sort stim within box - boxes.append(box) - - random.shuffle(boxes) - - if target and target_pos is not None: - # Find the box with the target and swap with the box currently at the - # target_pos. - boxes = swapped(boxes, - index1=find_index(boxes, lambda box: target in box), - index2=target_pos) - - return boxes diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 4a21b423b..310b1bd54 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -9,7 +9,6 @@ from mockito import any, mock, unstub, verify, when from psychopy import core -from bcipy.helpers.exceptions import BciPyCoreException from bcipy.helpers.stimuli import (DEFAULT_FIXATION_PATH, InquiryReshaper, StimuliOrder, TargetPositions, TrialReshaper, alphabetize, @@ -21,8 +20,7 @@ inquiry_target, inquiry_target_counts, jittered_timing, play_sound, random_target_positions, soundfiles, - ssvep_to_code, target_index, - update_inquiry_timing) + target_index, update_inquiry_timing) MOCK_FS = 44100 @@ -975,59 +973,6 @@ def test_update_inquiry_timing_with_non_int_timing_after_correction(self): self.assertTrue(new_timing == expected_timing) -class SSVEPStimuli(unittest.TestCase): - - def test_default_flicker_and_refresh_rate_return_codes(self): - response = ssvep_to_code() - self.assertIsInstance(response, list) - self.assertEqual(response[0], 0) - - def test_ssvep_to_codes_returns_the_length_of_refresh_rate(self): - refresh_rate = 40 - flicker_rate = 2 - response = ssvep_to_code(flicker_rate=flicker_rate, - refresh_rate=refresh_rate) - self.assertTrue(len(response) == refresh_rate) - self.assertEqual(response[0], 0) - self.assertEqual(response[-1], 1) - - def test_ssvep_to_code_raises_exception_when_refresh_rate_less_than_flicker_rate( - self): - flicker_rate = 300 - refresh_rate = 1 - - with self.assertRaises(BciPyCoreException): - ssvep_to_code(refresh_rate, flicker_rate) - - def test_when_division_of_refresh_rate_by_flicker_rate_raise_exception_if_noninteger( - self): - flicker_rate = 11 - refresh_rate = 60 - - with self.assertRaises(BciPyCoreException): - ssvep_to_code(refresh_rate, flicker_rate) - - def test_ssvep_to_code_returns_expected_codes(self): - flicker_rate = 2 - refresh_rate = 4 - response = ssvep_to_code(flicker_rate=flicker_rate, - refresh_rate=refresh_rate) - expected_output = [0, 0, 1, 1] - self.assertEqual(response, expected_output) - - def test_ssvep_to_code_raises_exception_when_flicker_rate_one_or_less( - self): - flicker_rate = 1 - refresh_rate = 2 - with self.assertRaises(BciPyCoreException): - ssvep_to_code(refresh_rate, flicker_rate) - - flicker_rate = 0 - refresh_rate = 2 - with self.assertRaises(BciPyCoreException): - ssvep_to_code(refresh_rate, flicker_rate) - - class TestSoundStimuli(unittest.TestCase): def tearDown(self): diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index a18110530..86c82a307 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -1,7 +1,7 @@ """VEP Calibration task-related code""" from typing import List, Tuple -from psychopy import core, visual +from psychopy import core, visual # type: ignore from bcipy.acquisition.multimodal import ClientManager from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE @@ -12,14 +12,14 @@ from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters -from bcipy.helpers.stimuli import (InquirySchedule, - generate_vep_calibration_inquiries) from bcipy.helpers.symbols import alphabet from bcipy.helpers.task import get_user_input, trial_complete_message from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, convert_timing_triggers, offset_label) from bcipy.task import Task +from bcipy.task.paradigm.vep.stim_generation import ( + InquirySchedule, generate_vep_calibration_inquiries) def trigger_type(symbol: str, target: str, _index: int) -> TriggerType: diff --git a/bcipy/task/paradigm/vep/stim_generation.py b/bcipy/task/paradigm/vep/stim_generation.py new file mode 100644 index 000000000..e5111f8e6 --- /dev/null +++ b/bcipy/task/paradigm/vep/stim_generation.py @@ -0,0 +1,214 @@ +"""Functions related to stimuli generation for VEP tasks""" +import itertools +import math +import random +from typing import Any, List, Optional + +from bcipy.helpers.list import find_index, swapped +from bcipy.helpers.stimuli import (InquirySchedule, get_fixation, + random_target_positions) + + +def generate_vep_calibration_inquiries(alp: List[str], + timing: Optional[List[float]] = None, + color: Optional[List[str]] = None, + inquiry_count: int = 100, + num_boxes: int = 4, + is_txt: bool = True) -> InquirySchedule: + """ + Generates VEP inquiries with target letters in all possible positions. + + In the VEP paradigm, all stimuli in the alphabet are displayed in each + inquiry. The symbols with the highest likelihoods are displayed alone + while those with lower likelihoods occur together. + + Parameters + ---------- + alp(list[str]): stimuli + timing(list[float]): Task specific timing for generator. + [target, fixation, stimuli] + color(list[str]): Task specific color for generator + [target, fixation, stimuli] + inquiry_count(int): number of inquiries in a calibration + num_boxes(int): number of display boxes + is_txt(bool): whether the stimuli type is text. False would be an image stimuli. + + Return + ------ + schedule_inq(tuple( + samples[list[list[str]]]: list of inquiries + timing(list[list[float]]): list of timings + color(list(list[str])): list of colors)): scheduled inquiries + """ + if timing is None: + timing = [0.5, 1, 2] + default_colors = [ + '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' + ] + if color is None: + box_colors = list( + itertools.islice(itertools.cycle(default_colors), num_boxes)) + color = ['green', 'red'] + box_colors + assert len( + timing + ) == 3, "timing must include values for [target, fixation, stimuli]" + + inquiries = generate_vep_inquiries(alp, num_boxes, inquiry_count, is_txt) + times = [timing for _ in range(inquiry_count)] + colors = [color for _ in range(inquiry_count)] + + return InquirySchedule(inquiries, times, colors) + + +def generate_vep_inquiries(symbols: List[str], + num_boxes: int = 6, + inquiry_count: int = 20, + is_txt: bool = True) -> List[List[Any]]: + """Generates inquiries""" + fixation = get_fixation(is_txt) + target_indices = random_target_positions(inquiry_count, + stim_per_inquiry=num_boxes, + percentage_without_target=0) + + # repeat the symbols as necessary to ensure an adequate size for sampling + # without replacement. + population = symbols * math.ceil(inquiry_count / len(symbols)) + targets = random.sample(population, inquiry_count) + + return [[target, fixation] + generate_vep_inquiry(alphabet=symbols, + num_boxes=num_boxes, + target=target, + target_pos=target_pos) + for target, target_pos in zip(targets, target_indices)] + + +def stim_per_box(num_symbols: int, + num_boxes: int = 6, + max_empty_boxes: int = 0, + max_single_sym_boxes: int = 4) -> List[int]: + """Determine the number of stimuli per vep box. + + Parameters + ---------- + num_symbols - number of symbols + num_boxes - number of boxes + max_empty_boxes - the maximum number of boxes which won't have any + symbols within them. + max_single_sym_boxes - maximum number of boxes with a single symbol + + Returns + ------- + A list of length num_boxes, where each number in the list represents + the number of symbols that should be in the box at that position. + + Post conditions: + The sum of the list should equal num_symbols. Further, there should + be at most max_empty_boxes with value of 0 and max_single_sym_boxes + with a value of 1. + """ + # Logic based off of example sessions from: + # https://www.youtube.com/watch?v=JNFYSeIIOrw + # [[2, 3, 5, 5, 6, 7], + # [2, 1, 10, 1, 1, 13], + # [3, 4, 17, 1, 1, 2], + # [1, 1, 1, 0, 1, 24], + # [1, 2, 1, 22, 1, 1], + # [2, 1, 1, 21, 2, 1], + # [1, 1, 25, 0, 1, 0]] + # and + # [[7, 3, 4, 9, 2, 3], + # 1, 1, 6, 9, 7, 2], + # 1, 2, 18, 2, 3, 2], + # 1, 1, 4, 4, 17, 1], + # 1, 3, 1, 1, 20, 2], + # 1, 1, 1, 20, 3, 2], + # 1, 1, 1, 4, 21, 0]] + + if max_empty_boxes + max_single_sym_boxes >= num_boxes: + max_empty_boxes = 0 + max_single_sym_boxes = num_boxes - 1 + + # no more than 1 empty box + empty_boxes = [0] * random.choice(range(max_empty_boxes + 1)) + + # no more than 4 boxes with a single symbol + single_boxes = [1] * random.choice( + range((max_single_sym_boxes + 1) - len(empty_boxes))) + + boxes = empty_boxes + single_boxes + + remaining_symbols = num_symbols - sum(boxes) + remaining_boxes = num_boxes - len(boxes) + + # iterate through the remaining boxes except for the last one + for _box in range(remaining_boxes - 1): + # each remaining box must have 2 or more symbols + box_max = remaining_symbols - (2 * remaining_boxes - 1) + + n = random.choice(range(2, box_max + 1)) + boxes.append(n) + remaining_boxes -= 1 + remaining_symbols = remaining_symbols - n + + # last box + boxes.append(remaining_symbols) + + return sorted(boxes) + + +def generate_vep_inquiry(alphabet: List[str], + num_boxes: int = 6, + target: Optional[str] = None, + target_pos: Optional[int] = None) -> List[List[str]]: + """Generates a single random inquiry. + + Parameters + ---------- + alphabet - list of symbols from which to select. + num_boxes - number of display areas; symbols will be partitioned into + these areas. + target - target symbol for the generated inquiry + target_pos - box index that should contain the target + + Returns + ------- + An inquiry represented by a list of lists, where each sublist + represents a display box and contains symbols that should appear in that box. + + Post-conditions: + Symbols will not be repeated and all symbols will be partitioned into + one of the boxes. + """ + + box_counts = stim_per_box(num_symbols=len(alphabet), num_boxes=num_boxes) + assert len(box_counts) == num_boxes + syms = [sym for sym in alphabet] + random.shuffle(syms) + + if target: + # Move the target to the front so it gets put in the lowest count box + # greater than 0. + syms = swapped(syms, index1=0, index2=syms.index(target)) + # Put syms in boxes + boxes = [] + sym_index = 0 + for count in box_counts: + box = [] + for _i in range(count): + box.append(syms[sym_index]) + sym_index += 1 + box.sort() # sort stim within box + boxes.append(box) + + random.shuffle(boxes) + + if target and target_pos is not None: + # Find the box with the target and swap with the box currently at the + # target_pos. + current_target_pos = find_index(boxes, lambda box: target in box) + if current_target_pos is not None: + boxes = swapped(boxes, + index1=current_target_pos, + index2=target_pos) + + return boxes diff --git a/bcipy/helpers/tests/test_stimuli_vep.py b/bcipy/task/tests/paradigm/vep/test_stimuli_vep.py similarity index 96% rename from bcipy/helpers/tests/test_stimuli_vep.py rename to bcipy/task/tests/paradigm/vep/test_stimuli_vep.py index b3771029f..b7f4d5170 100644 --- a/bcipy/helpers/tests/test_stimuli_vep.py +++ b/bcipy/task/tests/paradigm/vep/test_stimuli_vep.py @@ -1,8 +1,8 @@ import unittest -from bcipy.helpers.stimuli import (generate_vep_calibration_inquiries, - generate_vep_inquiry, stim_per_box) from bcipy.helpers.symbols import alphabet +from bcipy.task.paradigm.vep.stim_generation import ( + generate_vep_calibration_inquiries, generate_vep_inquiry, stim_per_box) class SSVEPStimuli(unittest.TestCase): From 27d1ad030f5ba0d6ca389d5aa5edcd9c5385baad Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 17 Nov 2023 11:03:35 -0800 Subject: [PATCH 161/330] New parameter for vep animation time --- bcipy/parameters/parameters.json | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index d390e9ba9..8753864f3 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -367,6 +367,14 @@ "recommended_values": "", "type": "float" }, + "time_vep_animation": { + "value": "1.0", + "section": "bci_config", + "readableName": "Time VEP Animation (sec)", + "helpTip": "The amount of time in seconds for the animation moving symbols to boxes.", + "recommended_values": "", + "type": "float" + }, "stim_jitter": { "value": "0.0", "section": "bci_config", From 2423c42b1263fa71a71fe396f5047fb3482501e9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 17 Nov 2023 11:02:20 -0800 Subject: [PATCH 162/330] New parameter for vep animation time --- bcipy/parameters/parameters.json | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index c1fe3cb0b..90eb22511 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -367,6 +367,14 @@ "recommended_values": "", "type": "float" }, + "time_vep_animation": { + "value": "1.0", + "section": "bci_config", + "readableName": "Time VEP Animation (sec)", + "helpTip": "The amount of time in seconds for the animation moving symbols to boxes.", + "recommended_values": "", + "type": "float" + }, "stim_jitter": { "value": "0.0", "section": "bci_config", From 7ae1f4ebd94b7c6b596130b25ecf8739f0e826d3 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 17 Nov 2023 11:05:00 -0800 Subject: [PATCH 163/330] Revert "New parameter for vep animation time" This reverts commit 437572ace09eb107aa09966e5a8360673131ea4d. --- bcipy/parameters/parameters.json | 8 -------- 1 file changed, 8 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 90eb22511..c1fe3cb0b 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -367,14 +367,6 @@ "recommended_values": "", "type": "float" }, - "time_vep_animation": { - "value": "1.0", - "section": "bci_config", - "readableName": "Time VEP Animation (sec)", - "helpTip": "The amount of time in seconds for the animation moving symbols to boxes.", - "recommended_values": "", - "type": "float" - }, "stim_jitter": { "value": "0.0", "section": "bci_config", From 348f6717ac8df5f213340437d419836850b4e86e Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 17 Nov 2023 11:48:11 -0800 Subject: [PATCH 164/330] Added missing import --- bcipy/helpers/tests/test_stimuli.py | 1 + 1 file changed, 1 insertion(+) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index e1cbbf45f..397ca2eac 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -9,6 +9,7 @@ from mockito import any, mock, unstub, verify, when from psychopy import core +from bcipy.helpers.exceptions import BciPyCoreException from bcipy.helpers.stimuli import (DEFAULT_FIXATION_PATH, InquiryReshaper, StimuliOrder, TargetPositions, TrialReshaper, alphabetize, From b03dcd2ceb4b8d259273374966f316732b5418ab Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Fri, 17 Nov 2023 16:27:52 -0800 Subject: [PATCH 165/330] Add mypy and various clean up (#301) --- .coveragerc | 7 +- .github/workflows/main.yml | 65 ++++++++------ .gitignore | 15 ++-- CHANGELOG.md | 8 +- Makefile | 23 ++++- README.md | 41 +++++++-- bcipy/acquisition/datastream/generator.py | 4 +- bcipy/acquisition/datastream/lsl_server.py | 15 ++-- .../datastream/mock/eye_tracker_server.py | 2 +- bcipy/acquisition/datastream/producer.py | 6 +- bcipy/acquisition/devices.py | 14 +-- bcipy/acquisition/exceptions.py | 1 + bcipy/acquisition/multimodal.py | 23 ++--- bcipy/acquisition/protocols/lsl/lsl_client.py | 48 +++++------ .../protocols/lsl/lsl_connector.py | 4 +- .../acquisition/protocols/lsl/lsl_recorder.py | 24 +++--- .../tests/protocols/lsl/test_lsl_recorder.py | 4 + bcipy/acquisition/util.py | 18 ---- bcipy/config.py | 5 ++ bcipy/display/components/layout.py | 13 +-- bcipy/display/components/task_bar.py | 18 ++-- bcipy/display/demo/components/demo_layouts.py | 6 +- bcipy/display/main.py | 17 ++-- bcipy/display/paradigm/matrix/display.py | 2 +- bcipy/display/paradigm/matrix/layout.py | 4 +- bcipy/display/paradigm/rsvp/display.py | 12 +-- bcipy/display/paradigm/vep/display.py | 10 +-- .../display/tests/components/test_task_bar.py | 12 +-- bcipy/feedback/feedback.py | 2 +- bcipy/feedback/visual/visual_feedback.py | 28 ++++-- bcipy/gui/experiments/ExperimentField.py | 14 +-- bcipy/gui/main.py | 12 +-- bcipy/gui/parameters/params_form.py | 3 +- bcipy/helpers/acquisition.py | 6 +- bcipy/helpers/convert.py | 44 ++++++---- bcipy/helpers/copy_phrase_wrapper.py | 5 +- bcipy/helpers/list.py | 6 +- bcipy/helpers/load.py | 9 +- bcipy/helpers/parameters.py | 42 ++++----- bcipy/helpers/raw_data.py | 51 ++++++----- bcipy/helpers/save.py | 9 +- bcipy/helpers/session.py | 12 +-- bcipy/helpers/stimuli.py | 81 +++++++++--------- bcipy/helpers/system_utils.py | 7 +- bcipy/helpers/task.py | 25 +++--- bcipy/helpers/tests/test_raw_data.py | 2 +- bcipy/helpers/tests/test_visualization.py | 33 +++++-- bcipy/helpers/triggers.py | 18 ++-- bcipy/helpers/visualization.py | 21 +++-- bcipy/language/README.md | 2 +- bcipy/language/model/causal.py | 6 +- bcipy/language/model/kenlm.py | 4 +- bcipy/language/model/mixture.py | 8 +- bcipy/language/model/uniform.py | 2 +- bcipy/language/model/unigram.py | 4 +- bcipy/language/tests/test_kenlm.py | 4 + bcipy/main.py | 12 +-- bcipy/parameters/devices.json | 6 +- bcipy/preferences.py | 12 +-- bcipy/signal/evaluate/evaluator.py | 11 ++- bcipy/signal/evaluate/rules.py | 10 +-- bcipy/signal/model/README.md | 9 +- .../signal/model/dimensionality_reduction.py | 11 +-- bcipy/signal/model/offline_analysis.py | 8 +- bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 4 +- bcipy/signal/process/filter.py | 8 +- bcipy/signal/process/transform.py | 13 ++- .../test_mean_erp.png | Bin 84452 -> 84452 bytes .../test_nontarget_topomap.png | Bin 120183 -> 113716 bytes .../test_target_topomap.png | Bin 115767 -> 107509 bytes bcipy/task/control/evidence.py | 7 +- bcipy/task/control/handler.py | 5 +- bcipy/task/data.py | 44 +++++----- bcipy/task/exceptions.py | 6 +- bcipy/task/main.py | 10 +-- bcipy/task/paradigm/matrix/calibration.py | 12 ++- bcipy/task/paradigm/matrix/copy_phrase.py | 6 +- .../paradigm/matrix/timing_verification.py | 4 +- .../rsvp/calibration/timing_verification.py | 1 + bcipy/task/paradigm/rsvp/copy_phrase.py | 66 ++++++++------ bcipy/task/start_task.py | 43 ++++++++-- bcipy/task/tests/core/test_data.py | 28 +++--- .../tests/paradigm/rsvp/test_copy_phrase.py | 2 + .../rsvp/test_copy_phrase_task_summary.py | 10 ++- dev_requirements.txt | 2 + mypy.ini | 11 +++ pytest.ini | 2 +- requirements.txt | 3 +- 88 files changed, 720 insertions(+), 527 deletions(-) create mode 100644 mypy.ini diff --git a/.coveragerc b/.coveragerc index 3d00e8ade..a32c1d6e6 100644 --- a/.coveragerc +++ b/.coveragerc @@ -6,11 +6,14 @@ omit = *tests* *test* *demo* - *gui/* + */gui/* [report] exclude_lines = pragma: no cover def __repr__ + def __str__ raise NotImplementedError - if __name__ == .__main__.: \ No newline at end of file + @abstract + if __name__ == .__main__.: + log = logging.getLogger(__name__) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 3df0da8b2..ca1c4b974 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -26,7 +26,7 @@ jobs: uses: actions/setup-python@v2 with: python-version: ${{ matrix.python-version }} - - name: Install dependencies + - name: Update OS, pip & install custom dependencies run: | sudo apt-get update sudo apt-get install libgtk-3-dev @@ -36,14 +36,13 @@ jobs: sudo apt-get install libsndfile* sudo apt-get install xvfb python -m pip install --upgrade pip + pip install kenlm==0.1 --global-option="--max_order=12" + pip install psychopy==2023.2.1 --no-deps pip install attrdict3 + - name: Install dependencies + run: | pip install -r dev_requirements.txt pip install -e . - pip install kenlm==0.1 --global-option="--max_order=12" - - name: Lint with flake8 - run: | - # stop the build if there are Python syntax errors or undefined names - flake8 bcipy - name: Unit test if: always() run: | @@ -59,6 +58,12 @@ jobs: else echo "Ubuntu test failure" fi + - name: type-check + run: | + mypy bcipy + - name: lint + run: | + flake8 bcipy build-windows: @@ -74,25 +79,29 @@ jobs: uses: actions/setup-python@v2 with: python-version: ${{ matrix.python-version }} - - name: Install dependencies for python3.9 - if: matrix.python-version == 3.9 + - name: update pip & install custom dependencies run: | python -m pip install --upgrade pip - pip install ./.bcipy/downloads/pyWinhook-1.6.2-cp39-cp39-win_amd64.whl - - name: Install dependencies + pip install kenlm==0.1 --global-option="--max_order=12" + pip install psychopy==2023.2.1 --no-deps + - name: install manually downloaded pyWinhook wheel for Python 3.9 + if: matrix.python-version == 3.9 + run: | + pip install ./.bcipy/downloads/pyWinhook-1.6.2-cp39-cp39-win_amd64.whl + - name: install dependencies run: | - python -m pip install --upgrade pip pip install -r dev_requirements.txt pip install -e . - pip install kenlm==0.1 --global-option="--max_order=12" - - name: Lint with flake8 - run: | - # stop the build if there are Python syntax errors or undefined names - flake8 bcipy - - name: Unit test + - name: unittest if: always() run: | coverage run --branch --source=bcipy -m pytest --mpl -k "not slow" + - name: type-check + run: | + mypy bcipy + - name: lint + run: | + flake8 bcipy build-macos: @@ -108,17 +117,25 @@ jobs: uses: actions/setup-python@v2 with: python-version: ${{ matrix.python-version }} - - name: Install dependencies + - name: update pip & install custom dependencies run: | python -m pip install --upgrade pip - pip install -r dev_requirements.txt - pip install -e . pip install kenlm==0.1 --global-option="--max_order=12" - - name: Lint with flake8 + pip install psychopy==2023.2.1 --no-deps + - name: install dependencies run: | - # stop the build if there are Python syntax errors or undefined names - flake8 bcipy - - name: Unit test + pip install -r dev_requirements.txt + pip install -e . + - name: unittest if: always() run: | coverage run --branch --source=bcipy -m pytest --mpl -k "not slow" + coverage report + - name: type-check + run: | + mypy bcipy + - name: lint + run: | + flake8 bcipy + + diff --git a/.gitignore b/.gitignore index 5a944e305..1b4f6af78 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ +# OS and Package Files *.pyc *~ .DS_Store @@ -5,7 +6,12 @@ .vscode/ .tm_properties .mypy_cache/ -data/ +mypy-html.css +.coverage +index.html +htmlcov/ +html/ + # Virtualenv venv/ venv*/ @@ -19,15 +25,12 @@ buffer.db lmwrap.log env.txt .idea -.coverage -htmlcov/ bcipy.egg-info/ +data/ build/ dist/ - bcipy/parameters/parameters_* bcipy_cache - bcipy/language/lms/lm_dec19_char_large_12gram.* bcipy/language/lms/out_* -bcipy/language/out/ +bcipy/language/out/ \ No newline at end of file diff --git a/CHANGELOG.md b/CHANGELOG.md index 97218f8fb..cf7e847d6 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,15 +8,17 @@ Our last release candidate before the official 2.0 release! - Support for multiple devices in online querying #286 - Support for trigger handling relative to a given device #293 - Model - - Offline analysis of multimodal fusion. First version of gaze model is completed #294 Gaze reshaper is updated #294 Visualization for the gaze classification is added #294 + - Offline analysis to support multimodal fusion. Initial release of GazeModel, GazeReshaper, and Gaze Visualization #294 - Stimuli - Updates to ensure stimuli are presented at the same frequency #287 - Dynamic Selection Window - Updated trial_length to trial_window to allow for greater control of window used after stimulus presentations #291 - Parameters - Add a Range type parameter #285 -- Cleanup - - Change default log level to INFO to prevent too many messages in the experiment logs #288 Upgrade requirements for m1/2 chips #299/#300 +- Housekeeping + - Add mypy typing to the codebase #301 + - Change default log level to INFO to prevent too many messages in the experiment logs #288 + - Upgrade requirements for m1/2 chips #299/#300 # 2.0.0-rc.3 diff --git a/Makefile b/Makefile index c42c0f43d..2a3e0a8ae 100644 --- a/Makefile +++ b/Makefile @@ -3,12 +3,14 @@ install: dev-install: pip install -r dev_requirements.txt - pip install -e . + pip install psychopy==2023.2.1 --no-deps + pip install kenlm==0.1 --global-option="--max_order=12" + make install test-all: - coverage run --branch --source=bcipy -m pytest --mpl -k "not slow" - coverage report - flake8 bcipy + make coverage-report + make type + make lint unit-test: pytest --mpl -k "not slow" @@ -16,14 +18,27 @@ unit-test: integration-test: pytest --mpl -k "slow" +coverage-report: + coverage run --branch --source=bcipy -m pytest --mpl -k "not slow" + coverage report + coverage-html: coverage run --branch --source=bcipy -m pytest --mpl -k "not slow" coverage html lint: + flake8 bcipy + +lint-fix: autopep8 --in-place --aggressive -r bcipy flake8 bcipy +type: + mypy bcipy + +type-html: + mypy bcipy --html-report type-report + clean: find . -name "*.py[co]" -o -name __pycache__ -exec rm -rf {} + find . -path "*/*.pyo" -delete diff --git a/README.md b/README.md index ee5f86959..7e1d2cca5 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ [![Follow on Twitter](https://img.shields.io/twitter/follow/cambi_tech?label=Follow&style=social)](https://twitter.com/cambi_tech) -BciPy is a library for conducting Brain-Computer Interface experiments in Python. It functions as a standalone application for experimental data collection or you can take the tools you need and start coding your own system. See our official BciPy documentation including affiliations and more context information [here](https://bcipy.github.io/) (in progress). +BciPy is a library for conducting Brain-Computer Interface experiments in Python. It functions as a standalone application for experimental data collection or you can take the tools you need and start coding your own system. See our official BciPy documentation including affiliations and more context information [here](https://bcipy.github.io/). It will run on the latest windows (7, 10, 11), linux (ubuntu 22.04) and macos (Big Sur). Other versions may work as well, but are not guaranteed. To see supported versions and operating systems as of this release see here: [BciPy Builds](https://github.com/CAMBI-tech/BciPy/actions/workflows/main.yml). @@ -18,7 +18,7 @@ Memmott, T., Koçanaoğulları, A., Lawhead, M., Klee, D., Dudy, S., Fried-Oken, ## Dependencies --------------- -This project requires Python 3.8 or 3.9. Please see notes below for additional OS specific dependencies before installation can be completed. +This project requires Python 3.8 or 3.9. Please see notes below for additional OS specific dependencies before installation can be completed and reference our documentation/FAQs for more information: https://bcipy.github.io/hardware-os-config/ ### Linux @@ -33,7 +33,9 @@ You will need to install pyWinhook manually. See [here](https://www.lfd.uci.edu/ ### Mac -If you are using a Mac, you will need to install XCode and enable command line tools. `xcode-select --install`. +If you are using a Mac, you will need to install XCode and enable command line tools. `xcode-select --install`. If using an m1/2 chip, you will need to use the install script in `scripts/shell/m2chip_install.sh` to install the prerequisites. You may also need to use the Rosetta terminal to run the install script, but this has not been necessary in our testing using m2 chips. + +If using zsh, instead of bash, you may encounter a segementation fault when running BciPy. This is due to an issue in a dependeancy of psychopy with no known fix as of yet. Please use bash instead of zsh for now. ## Installation --------------- @@ -42,14 +44,15 @@ If you are using a Mac, you will need to install XCode and enable command line t In order to run BciPy on your computer, after following the dependencies above, you will need to install the BciPy package. -To install for use locally, +To install for use locally and use of the GUI: 1. Git clone https://github.com/BciPy/BciPy.git -2. Change directory in your terminal to the repo -3. Run `pip install -e .` -4. To use the KenLMLanguageModel class, you must manually install the kenlm package. `pip install kenlm==0.1 --global-option="--max_order=12"`. +2. Change directory in your terminal to the repo directory. +3. Install the kenlm language model package. `pip install kenlm==0.1 --global-option="--max_order=12"`. +4. Install PsychoPy with no dependencies. `pip install psychopy==2023.2.1 --no-deps`. +5. Install BciPy in development mode. `pip install -e .` -If wanting the latest version from PyPi: +If wanting the latest version from PyPi and to build using modules: 1. `pip install bcipy` Alternately, if [Make](http://www.mingw.org/) is installed, you may run the follow command to install: @@ -216,6 +219,28 @@ Alternately, if Make is installed, you may run the follow command to run autopep make lint ``` +## Type Checking +---------------- + +This project enforces `mypy` type checking. The typing project configuration is found in the mypy.ini file. To run type checking, run the following command: + +```sh +mypy bcipy +``` + +To generate a report, run the following command: + +```sh +mypy --html-report bcipy +``` + +Alternately, if Make is installed, you may run the follow command to run mypy: + +```sh +make type +``` + + ### Contributions Welcome! If you want to be added to the development team slack or have additional questions, please reach out to us at support@cambi.tech! diff --git a/bcipy/acquisition/datastream/generator.py b/bcipy/acquisition/datastream/generator.py index 70046ed29..f96cf85eb 100644 --- a/bcipy/acquisition/datastream/generator.py +++ b/bcipy/acquisition/datastream/generator.py @@ -1,7 +1,7 @@ """Functions for generating mock data to be used for testing/development.""" import logging -from typing import Generator, Callable +from typing import Optional, Generator, Callable from past.builtins import range from bcipy.config import DEFAULT_ENCODING @@ -63,7 +63,7 @@ def random_data_generator(encoder=_DefaultEncoder(), yield encoder.encode(sensor_data) -def file_data_generator(filename, header_row=3, encoder=_DefaultEncoder(), channel_count: int = None): +def file_data_generator(filename, header_row=3, encoder=_DefaultEncoder(), channel_count: Optional[int] = None): """Generates data from a source file and encodes it according to the provided encoder. diff --git a/bcipy/acquisition/datastream/lsl_server.py b/bcipy/acquisition/datastream/lsl_server.py index 75221a084..dc064a708 100644 --- a/bcipy/acquisition/datastream/lsl_server.py +++ b/bcipy/acquisition/datastream/lsl_server.py @@ -1,10 +1,11 @@ +# mypy: disable-error-code="misc" """Data server that streams EEG data over a LabStreamingLayer StreamOutlet using pylsl.""" import logging import time import uuid from queue import Empty, Queue -from typing import Generator +from typing import Optional, Generator from pylsl import StreamInfo, StreamOutlet @@ -12,14 +13,12 @@ from bcipy.acquisition.datastream.producer import Producer from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.util import StoppableThread -from bcipy.config import DEFAULT_ENCODING +from bcipy.config import DEFAULT_ENCODING, MARKER_STREAM_NAME log = logging.getLogger(__name__) # pylint: disable=too-many-arguments -MARKER_STREAM_NAME = 'TRG_device_stream' - class LslDataServer(StoppableThread): """Data server that streams EEG data over a LabStreamingLayer StreamOutlet @@ -50,7 +49,7 @@ class LslDataServer(StoppableThread): def __init__(self, device_spec: DeviceSpec, - generator: Generator = None, + generator: Optional[Generator] = None, include_meta: bool = True, add_markers: bool = False, marker_stream_name: str = MARKER_STREAM_NAME, @@ -120,7 +119,7 @@ def run(self): sample_counter = 0 self.started = True - data_queue = Queue() + data_queue: Queue = Queue() with Producer(data_queue, generator=self.generator, freq=1 / self.device_spec.sample_rate): while self.running(): @@ -149,7 +148,7 @@ def _settings(filename): return (daq_type, sample_hz, channels) -def await_start(dataserver: LslDataServer, max_wait: float = 2): +def await_start(dataserver: LslDataServer, max_wait: float = 2.0): """Blocks until server is started. Raises if max_wait is exceeded before server is started. @@ -161,7 +160,7 @@ def await_start(dataserver: LslDataServer, max_wait: float = 2): """ dataserver.start() - wait = 0 + wait = 0.0 wait_interval = 0.01 while not dataserver.started: time.sleep(wait_interval) diff --git a/bcipy/acquisition/datastream/mock/eye_tracker_server.py b/bcipy/acquisition/datastream/mock/eye_tracker_server.py index a0022a065..e0a5e4d1d 100644 --- a/bcipy/acquisition/datastream/mock/eye_tracker_server.py +++ b/bcipy/acquisition/datastream/mock/eye_tracker_server.py @@ -20,7 +20,7 @@ def eye_tracker_device() -> DeviceSpec: 'leftPupilArea', 'rightPupilArea', 'pixelsPerDegreeX', 'pixelsPerDegreeY' ], - sample_rate=500.0, + sample_rate=500, content_type='Gaze') diff --git a/bcipy/acquisition/datastream/producer.py b/bcipy/acquisition/datastream/producer.py index e5ad0c079..58633395c 100644 --- a/bcipy/acquisition/datastream/producer.py +++ b/bcipy/acquisition/datastream/producer.py @@ -112,9 +112,9 @@ def run(self): def main(): """Main method""" - data_queue = Queue() - producer = Producer(data_queue) - consumer = _ConsumerThread(data_queue) + data_queue: Queue = Queue() + producer: Producer = Producer(data_queue) + consumer: _ConsumerThread = _ConsumerThread(data_queue) producer.start() consumer.start() diff --git a/bcipy/acquisition/devices.py b/bcipy/acquisition/devices.py index 0aae6b188..12a2c1f56 100644 --- a/bcipy/acquisition/devices.py +++ b/bcipy/acquisition/devices.py @@ -3,13 +3,13 @@ import json import logging from pathlib import Path -from typing import Dict, List, NamedTuple, Union +from typing import Optional, Dict, List, NamedTuple, Union from bcipy.config import DEFAULT_ENCODING, DEVICE_SPEC_PATH -IRREGULAR_RATE = 0.0 +IRREGULAR_RATE: int = 0 DEFAULT_CONFIG = DEVICE_SPEC_PATH -_SUPPORTED_DEVICES = {} +_SUPPORTED_DEVICES: Dict[str, 'DeviceSpec'] = {} # see https://labstreaminglayer.readthedocs.io/projects/liblsl/ref/enums.html SUPPORTED_DATA_TYPES = [ 'float32', 'double64', 'string', 'int32', 'int16', 'int8' @@ -72,10 +72,10 @@ class DeviceSpec: def __init__(self, name: str, channels: Union[List[str], List[ChannelSpec], List[dict]], - sample_rate: float, + sample_rate: int, content_type: str = DEFAULT_DEVICE_TYPE, - description: str = None, - excluded_from_analysis: List[str] = None, + description: Optional[str] = None, + excluded_from_analysis: Optional[List[str]] = None, data_type='float32'): assert sample_rate >= 0, "Sample rate can't be negative." @@ -83,7 +83,7 @@ def __init__(self, self.name = name self.channel_specs = [channel_spec(ch) for ch in channels] - self.sample_rate = sample_rate + self.sample_rate = int(sample_rate) self.content_type = content_type self.description = description or name self.data_type = data_type diff --git a/bcipy/acquisition/exceptions.py b/bcipy/acquisition/exceptions.py index d5035c902..7caaf1f54 100644 --- a/bcipy/acquisition/exceptions.py +++ b/bcipy/acquisition/exceptions.py @@ -1,3 +1,4 @@ + class InvalidClockError(Exception): def __init__(self, msg): Exception.__init__(self, msg) diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 4426ab431..43b3ca560 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="arg-type" """Functionality for managing multiple devices.""" import logging from typing import Any, Dict, List, Optional @@ -25,12 +26,12 @@ class ContentType(AutoNumberEnum): def __init__(self, synonyms: List[str]): self.synonyms = synonyms - EEG = [] - EYETRACKER = ['gaze', 'eye_tracker'] - MARKERS = ['switch'] + EEG: List[str] = [] + EYETRACKER: List[str] = ['gaze', 'eye_tracker'] + MARKERS: List[str] = ['switch'] @classmethod - def _missing_(cls, value: Any): + def _missing_(cls, value: Any) -> 'ContentType': """Lookup function used when a value is not found.""" value = str(value).lower() for member in cls: @@ -58,14 +59,14 @@ class ClientManager(): default_content_type - used for dispatching calls to an LslClient. """ - def __init__(self, default_content_type: ContentType = ContentType.EEG): + def __init__(self, default_content_type: ContentType = ContentType.EEG) -> None: self._clients: Dict[ContentType, LslAcquisitionClient] = {} self.default_content_type = default_content_type @property def clients(self) -> List[LslAcquisitionClient]: """Returns a list of the managed clients.""" - return self._clients.values() + return list(self._clients.values()) @property def clients_by_type(self) -> Dict[ContentType, LslAcquisitionClient]: @@ -81,7 +82,7 @@ def device_specs(self) -> List[DeviceSpec]: def device_content_types(self) -> List[ContentType]: """Returns a list of ContentTypes provided by the configured devices. """ - return self._clients.keys() + return list(self._clients.keys()) @property def default_client(self) -> Optional[LslAcquisitionClient]: @@ -111,9 +112,9 @@ def stop_acquisition(self): def get_data_by_device( self, - start: float = None, - seconds: float = None, - content_types: List[ContentType] = None, + start: Optional[float] = None, + seconds: Optional[float] = None, + content_types: Optional[List[ContentType]] = None, strict: bool = True ) -> Dict[ContentType, List[Record]]: """Get data for one or more devices. The number of samples for each @@ -154,7 +155,7 @@ def cleanup(self): for client in self.clients: client.cleanup() - def __getattr__(self, name): + def __getattr__(self, name: str) -> Any: """Dispatch unknown properties and methods to the client with the default content type.""" client = self.default_client diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 3fb8f3f8c..d8571f18b 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -1,6 +1,6 @@ """DataAcquisitionClient for LabStreamingLayer data sources.""" import logging -from typing import List +from typing import Optional, List from pylsl import (StreamInfo, StreamInlet, local_clock, resolve_byprop, resolve_stream) @@ -37,26 +37,24 @@ class LslAcquisitionClient: raw_data_file_name: if present, uses this name for the data file. """ + inlet: StreamInlet = None + recorder: LslRecordingThread = None + buffer: RingBuffer = None + _first_sample_time: float = None + experiment_clock: Clock = None + def __init__(self, max_buffer_len: float = 1, - device_spec: DeviceSpec = None, - save_directory: str = None, - raw_data_file_name: str = None): + device_spec: Optional[DeviceSpec] = None, + save_directory: Optional[str] = None, + raw_data_file_name: Optional[str] = None): super().__init__() + self.device_spec = device_spec self.max_buffer_len = max_buffer_len - - self.experiment_clock = None - - self.inlet = None - self._first_sample_time = None - self.save_directory = save_directory self.raw_data_file_name = raw_data_file_name - self.recorder = None - self.buffer = None - def start_acquisition(self) -> bool: """Connect to the datasource and start acquiring data. @@ -74,9 +72,10 @@ def start_acquisition(self) -> bool: f'LSL Stream not found for content type {content_type}') stream_info = streams[0] - self.inlet = StreamInlet(stream_info, - max_buflen=self.max_buffer_len, - max_chunklen=1) + self.inlet = StreamInlet( + stream_info, + max_buflen=self.max_buffer_len, + max_chunklen=1) if self.device_spec: check_device(self.device_spec, self.inlet.info()) @@ -84,10 +83,11 @@ def start_acquisition(self) -> bool: self.device_spec = device_from_metadata(self.inlet.info()) if self.save_directory: - self.recorder = LslRecordingThread(stream_info, - self.save_directory, - self.raw_data_file_name, - self.device_spec) + self.recorder = LslRecordingThread( + stream_info, + self.save_directory, + self.raw_data_file_name, + self.device_spec) self.recorder.start() if self.max_buffer_len and self.max_buffer_len > 0: @@ -127,9 +127,9 @@ def __exit__(self, _exc_type, _exc_value, _traceback): self.stop_acquisition() def get_data(self, - start: float = None, - end: float = None, - limit: int = None) -> List[Record]: + start: Optional[float] = None, + end: Optional[float] = None, + limit: Optional[int] = None) -> List[Record]: """Get data in time range. Parameters @@ -237,7 +237,7 @@ def is_calibrated(self, bool_val): if True, uses a 0 offset; if False forces the calculation. """ - def clock_offset(self, experiment_clock: Clock = None) -> float: + def clock_offset(self, experiment_clock: Optional[Clock] = None) -> float: """ Offset in seconds from the experiment clock to the acquisition local clock. diff --git a/bcipy/acquisition/protocols/lsl/lsl_connector.py b/bcipy/acquisition/protocols/lsl/lsl_connector.py index 0423c8b11..629e90f6f 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_connector.py +++ b/bcipy/acquisition/protocols/lsl/lsl_connector.py @@ -51,7 +51,7 @@ def inlet_name(inlet) -> str: def channel_names(stream_info: pylsl.StreamInfo) -> List[str]: """Extracts the channel names from the LSL Stream metadata.""" - channels = [] + channels: List[str] = [] if stream_info.type() == 'Markers': return ['Marker'] if stream_info.desc().child("channels").empty(): @@ -59,7 +59,7 @@ def channel_names(stream_info: pylsl.StreamInfo) -> List[str]: channel = stream_info.desc().child("channels").child("channel") for _ in range(stream_info.channel_count()): - channel_name = channel.child_value("label") + channel_name: str = channel.child_value("label") channels.append(channel_name) channel = channel.next_sibling() diff --git a/bcipy/acquisition/protocols/lsl/lsl_recorder.py b/bcipy/acquisition/protocols/lsl/lsl_recorder.py index 13d7be9c2..f877a15f5 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_recorder.py +++ b/bcipy/acquisition/protocols/lsl/lsl_recorder.py @@ -2,7 +2,7 @@ import logging import time from pathlib import Path -from typing import List, Tuple +from typing import Optional, List from pylsl import StreamInfo, StreamInlet, resolve_streams @@ -25,13 +25,14 @@ class LslRecorder: Devices without an entry will use a naming convention. """ - def __init__(self, path: str, filenames: dict = None): + streams: List['LslRecordingThread'] = None + + def __init__(self, path: str, filenames: Optional[dict] = None) -> None: super().__init__() self.path = path - self.streams = None self.filenames = filenames or {} - def start(self): + def start(self) -> None: """Start recording all streams currently on the network.""" if not self.streams: @@ -50,7 +51,7 @@ def start(self): for stream in self.streams: stream.start() - def stop(self, wait: bool = False): + def stop(self, wait: bool = False) -> None: """Stop recording. Parameters @@ -76,11 +77,13 @@ class LslRecordingThread(StoppableThread): from here. """ + writer: RawDataWriter = None + def __init__(self, stream_info: StreamInfo, directory: str, - filename: str = None, - device_spec: DeviceSpec = None): + filename: Optional[str] = None, + device_spec: Optional[DeviceSpec] = None) -> None: super().__init__() self.stream_info = stream_info self.directory = directory @@ -92,7 +95,6 @@ def __init__(self, # seconds to sleep between data pulls from LSL self.sleep_seconds = 0.2 - self.writer = None self.filename = filename if filename else self.default_filename() self.first_sample_time = None @@ -126,7 +128,7 @@ def _init_data_writer(self, stream_info: StreamInfo) -> None: check_device(self.device_spec, stream_info) channels = self.device_spec.channels - path = Path(self.directory, self.filename) + path = str(Path(self.directory, self.filename)) log.info(f"Writing data to {path}") self.writer = RawDataWriter( path, @@ -157,7 +159,7 @@ def _write_chunk(self, data: List, timestamps: List) -> None: chunk.append([self.sample_count] + sample + [timestamps[i]]) self.writer.writerows(chunk) - def _pull_chunk(self, inlet: StreamInlet) -> Tuple[int, float]: + def _pull_chunk(self, inlet: StreamInlet) -> int: """Pull a chunk of data and persist. Updates first_sample_time, last_sample_time, and sample_count. @@ -173,7 +175,7 @@ def _pull_chunk(self, inlet: StreamInlet) -> Tuple[int, float]: # available. data, timestamps = inlet.pull_chunk(timeout=0.0, max_samples=self.max_chunk_size) - if timestamps: + if timestamps and data: if not self.first_sample_time: self.first_sample_time = timestamps[0] self.last_sample_time = timestamps[-1] diff --git a/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py b/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py index 812a7d397..527b906f9 100644 --- a/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py +++ b/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py @@ -93,3 +93,7 @@ def test_duplicate_streams(self): recorder.start() dup_server.stop() + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/acquisition/util.py b/bcipy/acquisition/util.py index 04a5150dd..15472c23d 100644 --- a/bcipy/acquisition/util.py +++ b/bcipy/acquisition/util.py @@ -21,24 +21,6 @@ def mock_data(n_records: int, n_cols: int, low: int = -1000, high: int = 1000): """ return (mock_record(n_cols, low, high) for _i in range(n_records)) -# def mock_data_stream(n_records: int, length: int, low: int= -1000, -# high: int = 1000): -# """Generator for mock data that streams continuously. - -# Parameters: -# ----------- -# n_records: number of records to generate -# length: length of each record -# low: optional; min value for each item; default is -1000 -# high: optional; max value for each item; default is 1000 - -# Returns: -# -------- -# A generator that yields arrays of random data -# """ -# while True: -# yield mock_record(length, low, high) - def mock_record(n_cols: int = 25, low: int = -1000, high: int = 1000): """Create an list of random data. diff --git a/bcipy/config.py b/bcipy/config.py index a7504548a..02a079d76 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -6,6 +6,8 @@ from pathlib import Path DEFAULT_ENCODING = 'utf-8' +DEFAULT_EVIDENCE_PRECISION = 5 # number of decimal places to round evidence to by default +MARKER_STREAM_NAME = 'TRG_device_stream' # experiment configuration DEFAULT_EXPERIMENT_ID = 'default' @@ -32,6 +34,9 @@ LM_PATH = f'{BCIPY_ROOT}/language/lms' SIGNAL_MODEL_FILE_SUFFIX = '.pkl' +DEFAULT_FIXATION_PATH = f'{STATIC_IMAGES_PATH}/main/PLUS.png' +DEFAULT_TEXT_FIXATION = '+' + # core data configuration RAW_DATA_FILENAME = 'raw_data' EYE_TRACKER_FILENAME_PREFIX = 'eyetracker_data' diff --git a/bcipy/display/components/layout.py b/bcipy/display/components/layout.py index 1ad8692a3..e0887a79f 100644 --- a/bcipy/display/components/layout.py +++ b/bcipy/display/components/layout.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="override" """Defines common functionality for GUI layouts.""" from enum import Enum from typing import List, Optional, Protocol, Tuple @@ -121,8 +122,8 @@ def __init__(self, top: float = DEFAULT_TOP, right: float = DEFAULT_RIGHT, bottom: float = DEFAULT_BOTTOM, - units: float = "norm"): - self.units = units + units: str = "norm"): + self.units: str = units self.parent = parent self.top = top self.left = left @@ -185,12 +186,12 @@ def height(self) -> float: return self.top - self.bottom @property - def left_top(self) -> float: + def left_top(self) -> Tuple[float, float]: """Top left position""" return (self.left, self.top) @property - def right_bottom(self) -> float: + def right_bottom(self) -> Tuple[float, float]: """Bottom right position""" return (self.right, self.bottom) @@ -221,7 +222,7 @@ def right_middle(self) -> Tuple[float, float]: def resize_width(self, width_pct: float, - alignment: Alignment = Alignment.CENTERED) -> float: + alignment: Alignment = Alignment.CENTERED) -> None: """Adjust the width of the current layout. Parameters @@ -252,7 +253,7 @@ def resize_width(self, def resize_height(self, height_pct: float, - alignment: Alignment = Alignment.CENTERED) -> float: + alignment: Alignment = Alignment.CENTERED) -> None: """Adjust the height of the current layout. Parameters diff --git a/bcipy/display/components/task_bar.py b/bcipy/display/components/task_bar.py index fb2f5f0fd..3d490faf6 100644 --- a/bcipy/display/components/task_bar.py +++ b/bcipy/display/components/task_bar.py @@ -1,10 +1,9 @@ """Task bar component""" -from typing import Dict, List +from typing import Optional, Dict, List from psychopy import visual from psychopy.visual.basevisual import BaseVisualStim -from psychopy.visual.line import Line import bcipy.display.components.layout as layout @@ -24,7 +23,7 @@ class TaskBar: def __init__(self, win: visual.Window, - colors: List[str] = None, + colors: Optional[List[str]] = None, font: str = 'Courier New', height: float = 0.1, text: str = ''): @@ -55,13 +54,14 @@ def update(self, text: str = ''): """Update the task bar to display the given text.""" self.stim['task_text'].text = text - def border_stim(self) -> Line: + def border_stim(self) -> visual.Line: """Create the task bar outline""" - return visual.line.Line(win=self.win, - units=self.layout.units, - start=(self.layout.left, self.layout.bottom), - end=(self.layout.right, self.layout.bottom), - lineColor=self.colors[0]) + return visual.Line( + win=self.win, + units=self.layout.units, + start=(self.layout.left, self.layout.bottom), + end=(self.layout.right, self.layout.bottom), + lineColor=self.colors[0]) def text_stim(self, **kwargs) -> visual.TextStim: """Constructs a TextStim. Uses the config to set default properties diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index 6fe4afc9c..234107fb4 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -2,7 +2,7 @@ import logging import sys import time -from typing import Callable, List, Tuple, Union +from typing import Optional, Callable, List, Tuple, Union from psychopy import visual from psychopy.visual.circle import Circle @@ -32,7 +32,7 @@ def draw_boundary(win, layout: Layout, color: str = 'blue', line_px: int = 5, - name: str = None): + name: Optional[str] = None): """Display the layout's outline.""" if name: print(f"Drawing boundary for {name}") @@ -72,7 +72,7 @@ def draw_position(win: visual.Window, pos: Tuple[float, float], color: str = 'blue', size: Union[float, Tuple[float, float]] = 0.025, - name: str = None): + name: Optional[str] = None): """Draw the provided positions""" if name: print(f"Drawing position {name} at {pos}") diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 8512fb98d..d8238fb3e 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -1,6 +1,7 @@ +# mypy: disable-error-code="assignment,empty-body" from abc import ABC, abstractmethod from logging import Logger -from typing import List, Tuple, Union +from typing import Optional, List, Tuple, Union from psychopy import visual @@ -133,11 +134,11 @@ def __init__( stim_font: str, stim_pos: Union[Tuple[float, float], List[Tuple[float, float]]], stim_height: float, - stim_inquiry: List[str] = None, - stim_colors: List[str] = None, - stim_timing: List[float] = None, + stim_inquiry: Optional[List[str]] = None, + stim_colors: Optional[List[str]] = None, + stim_timing: Optional[List[float]] = None, is_txt_stim: bool = True, - prompt_time: float = None): + prompt_time: Optional[float] = None): """Initialize Stimuli Parameters. stim_font(List[str]): Ordered list of colors to apply to information stimuli @@ -269,9 +270,9 @@ def __init__( stim_font: str, stim_pos: List[Tuple[float, float]], stim_height: float, - timing: Tuple[float, float, float] = None, - stim_color: List[List[str]] = None, - inquiry: List[List[str]] = None, + timing: Optional[Tuple[float, float, float]] = None, + stim_color: Optional[List[List[str]]] = None, + inquiry: Optional[List[List[str]]] = None, stim_length: int = 1): """Initialize VEP Stimuli Parameters. stim_color(List[str]): Ordered list of colors to apply to VEP stimuli diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index a9ad5f30c..ccb8bd1ef 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -47,7 +47,7 @@ def __init__(self, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, should_prompt_target: bool = True, - sort_order: Callable = None): + sort_order: Optional[Callable] = None): """Initialize Matrix display parameters and objects. PARAMETERS: diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index 82ad1b26f..0261b677c 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -1,6 +1,6 @@ """Functions for calculating matrix layouts""" import logging -from typing import List, Tuple +from typing import Optional, List, Tuple from bcipy.display.components.layout import (Layout, above, below, left_of, right_of, scaled_height, @@ -10,7 +10,7 @@ def symbol_positions(container: Layout, rows: int, - columns: int, max_spacing: float = None) -> List[Tuple[float, float]]: + columns: int, max_spacing: Optional[float] = None) -> List[Tuple[float, float]]: """Compute the positions for arranging a number of symbols in a grid layout. diff --git a/bcipy/display/paradigm/rsvp/display.py b/bcipy/display/paradigm/rsvp/display.py index 85cd8f28f..9813d5ade 100644 --- a/bcipy/display/paradigm/rsvp/display.py +++ b/bcipy/display/paradigm/rsvp/display.py @@ -1,6 +1,6 @@ import logging import os.path as path -from typing import List, Tuple +from typing import Optional, List, Tuple from psychopy import core, visual, event @@ -34,7 +34,7 @@ def __init__( stimuli: StimuliProperties, task_bar: TaskBar, info: InformationProperties, - preview_inquiry: PreviewInquiryProperties = None, + preview_inquiry: Optional[PreviewInquiryProperties] = None, trigger_type: str = 'image', space_char: str = SPACE_CHAR, full_screen: bool = False): @@ -117,9 +117,9 @@ def draw_static(self): info.draw() def schedule_to(self, - stimuli: List[str] = None, - timing: List[float] = None, - colors: List[str] = None): + stimuli: Optional[List[str]] = None, + timing: Optional[List[float]] = None, + colors: Optional[List[str]] = None): """Schedule stimuli elements (works as a buffer). Args: @@ -357,7 +357,7 @@ def _generate_inquiry(self) -> list: stim_info.append(current_stim) return stim_info - def update_task_bar(self, text: str = None) -> None: + def update_task_bar(self, text: Optional[str] = None) -> None: """Update task state. Removes letters or appends to the right. diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index e0d889699..ecf1cc120 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -1,6 +1,6 @@ import logging from itertools import cycle -from typing import List, Tuple +from typing import Optional, List, Tuple import numpy as np from psychopy import core, visual @@ -124,8 +124,8 @@ def __init__( task_bar: TaskBar, info: InformationProperties, trigger_type: str = 'text', - codes: List[int] = None, - box_config: BoxConfiguration = None): + codes: Optional[List[int]] = None, + box_config: Optional[BoxConfiguration] = None): self.window = window self.window_size = self.window.size # [w, h] self.refresh_rate = round(window.getActualFrameRate()) @@ -379,8 +379,8 @@ def _trigger_pulse(self) -> None: self.first_stim_time = calibration_time[-1] self.first_run = False - def schedule_to(self, stimuli: List[List[str]], timing: List[List[float]] - = None, colors: List[List[str]] = None) -> None: + def schedule_to(self, stimuli: List[List[str]], timing: Optional[List[List[float]]] + = None, colors: Optional[List[List[str]]] = None) -> None: """Schedule stimuli elements (works as a buffer). """ self.stimuli_inquiry = stimuli diff --git a/bcipy/display/tests/components/test_task_bar.py b/bcipy/display/tests/components/test_task_bar.py index 98add9c05..94f5183d7 100644 --- a/bcipy/display/tests/components/test_task_bar.py +++ b/bcipy/display/tests/components/test_task_bar.py @@ -13,13 +13,13 @@ def test_task_bar(self, visual_mock): border_mock = Mock() visual_mock.TextStim.return_value = text_stim_mock - visual_mock.line.Line.return_value = border_mock + visual_mock.Line.return_value = border_mock win = Mock(size=(500, 500), units="norm") task_bar = TaskBar(win, text='Testing') self.assertEqual(len(task_bar.stim.items()), 2) visual_mock.TextStim.assert_called_once() - visual_mock.line.Line.assert_called_once() + visual_mock.Line.assert_called_once() phrase = 'Hello, world' task_bar.update(phrase) @@ -36,7 +36,7 @@ def test_calibration_task_bar(self, visual_mock): border_mock = Mock() visual_mock.TextStim.return_value = text_stim_mock - visual_mock.line.Line.return_value = border_mock + visual_mock.Line.return_value = border_mock win = Mock(size=(500, 500), units="norm") task_bar = CalibrationTaskBar(win, @@ -54,7 +54,7 @@ def test_calibration_task_bar(self, visual_mock): text=' 1/100', units='norm', win=win) - visual_mock.line.Line.assert_called_once() + visual_mock.Line.assert_called_once() self.assertEqual(len(task_bar.stim.items()), 2) self.assertEqual(task_bar.stim['task_text'], text_stim_mock) @@ -72,7 +72,7 @@ def test_copy_phrase_task_bar(self, visual_mock): text_stim_mock = Mock() spelled_stim_mock = Mock() visual_mock.TextStim.side_effect = [text_stim_mock, spelled_stim_mock] - visual_mock.line.Line.return_value = Mock() + visual_mock.Line.return_value = Mock() win = Mock(size=(500, 500), units="norm") task_bar = CopyPhraseTaskBar(win, @@ -80,7 +80,7 @@ def test_copy_phrase_task_bar(self, visual_mock): spelled_text='HELLO_') self.assertEqual(2, visual_mock.TextStim.call_count) - visual_mock.line.Line.assert_called_once() + visual_mock.Line.assert_called_once() self.assertEqual(len(task_bar.stim.items()), 3) self.assertEqual(task_bar.displayed_text(), 'HELLO_ ') diff --git a/bcipy/feedback/feedback.py b/bcipy/feedback/feedback.py index e4e96d8b1..9bb264f39 100644 --- a/bcipy/feedback/feedback.py +++ b/bcipy/feedback/feedback.py @@ -14,7 +14,7 @@ def __init__(self, feedback_type): def configure(self): raise NotImplementedError() - def administer(self): + def administer(self, *args, **kwargs): raise NotImplementedError() def _type(self): diff --git a/bcipy/feedback/visual/visual_feedback.py b/bcipy/feedback/visual/visual_feedback.py index 7c9f1165c..95e70f44e 100644 --- a/bcipy/feedback/visual/visual_feedback.py +++ b/bcipy/feedback/visual/visual_feedback.py @@ -1,6 +1,8 @@ +# mypy: disable-error-code="return-value" from enum import Enum from psychopy import core, visual +from typing import Tuple, List, Union from bcipy.feedback.feedback import Feedback from bcipy.helpers.clock import Clock @@ -15,7 +17,7 @@ class FeedbackType(Enum): class VisualFeedback(Feedback): """Visual Feedback.""" - def __init__(self, display, parameters: dict, clock: Clock): + def __init__(self, display: visual.Window, parameters: dict, clock: Clock) -> None: # Register Feedback Type self.feedback_type = 'Visual Feedback' @@ -27,8 +29,8 @@ def __init__(self, display, parameters: dict, clock: Clock): # Parameters self.parameters = parameters - self.font_stim = self.parameters['feedback_font'] - self.height_stim = self.parameters['feedback_stim_height'] + self.font_stim: str = self.parameters['feedback_font'] + self.height_stim: int = self.parameters['feedback_stim_height'] pos_x = self.parameters['feedback_pos_x'] pos_y = self.parameters['feedback_pos_y'] @@ -38,15 +40,14 @@ def __init__(self, display, parameters: dict, clock: Clock): self.feedback_length = self.parameters['feedback_duration'] self.color = self.parameters['feedback_color'] - # Clock self.clock = clock self.feedback_timestamp_label = 'visual_feedback' def administer( self, - stimulus, - stimuli_type=FeedbackType.TEXT): + stimulus: str, + stimuli_type=FeedbackType.TEXT) -> List[Tuple[str, float]]: """Administer. Administer visual feedback. Timing information from parameters, @@ -65,17 +66,26 @@ def administer( return [time] - def _show_stimuli(self, stimulus) -> None: + def _show_stimuli(self, stimulus: Union[visual.TargetStim, visual.ImageStim]) -> Tuple[str, float]: stimulus.draw() time = [self.feedback_timestamp_label, self.clock.getTime()] # TODO: use callback for better precision self.display.flip() return time - def _resize_image(self, stimulus, display_size, stimuli_height): + def _resize_image( + self, + stimulus: str, + display_size: Tuple[float, float], + stimuli_height: int) -> Tuple[float, float]: return resize_image( stimulus, display_size, stimuli_height) - def _construct_stimulus(self, stimulus, pos, fill_color, stimuli_type): + def _construct_stimulus( + self, + stimulus: str, + pos: Tuple[float, float], + fill_color: str, + stimuli_type: FeedbackType) -> Union[visual.TargetStim, visual.ImageStim]: if stimuli_type == FeedbackType.IMAGE: image_stim = visual.ImageStim( win=self.display, diff --git a/bcipy/gui/experiments/ExperimentField.py b/bcipy/gui/experiments/ExperimentField.py index bf8bd7e20..290e6c692 100644 --- a/bcipy/gui/experiments/ExperimentField.py +++ b/bcipy/gui/experiments/ExperimentField.py @@ -41,11 +41,11 @@ class ExperimentFieldCollection(QWidget): field_data: List[tuple] = [] field_inputs: List[FormInput] = [] type_inputs = { - 'int': IntegerInput, - 'float': FloatInput, - 'bool': BoolInput, - 'filepath': FileInput, - 'directorypath': DirectoryInput + 'int': (IntegerInput, 0), + 'float': (FloatInput, 0.0), + 'bool': (BoolInput, False), + 'filepath': (FileInput, ''), + 'directorypath': (DirectoryInput, ''), } require_mark = '*' alert_timeout = 10 @@ -96,13 +96,13 @@ def field_input(self, field_name: str, field_type: str, help_tip: str, required: attributes. """ - form_input = self.type_inputs.get(field_type, TextInput) + form_input, init_value = self.type_inputs.get(field_type, TextInput) if required: field_name += self.require_mark return form_input( label=field_name, - value='', + value=init_value, help_tip=help_tip, help_size=self.help_size, help_color=self.help_color) diff --git a/bcipy/gui/main.py b/bcipy/gui/main.py index 4532bfb03..2c0d00923 100644 --- a/bcipy/gui/main.py +++ b/bcipy/gui/main.py @@ -173,7 +173,7 @@ class AlertMessageResponse(Enum): def alert_message( message: str, - title: str = None, + title: Optional[str] = None, message_type: AlertMessageType = AlertMessageType.INFO, message_response: AlertMessageResponse = AlertMessageResponse.OTE, message_timeout: float = 0) -> MessageBox: @@ -222,8 +222,8 @@ class FormInput(QWidget): def __init__(self, label: str, value: str, - help_tip: str = None, - options: List[str] = None, + help_tip: Optional[str] = None, + options: Optional[List[str]] = None, help_size: int = 12, help_color: str = 'darkgray', should_display: bool = True): @@ -581,7 +581,7 @@ class RangeWidget(QWidget): def __init__(self, value: Tuple[int, int], - options: List[str] = None, + options: Optional[List[str]] = None, label_low: str = "Low:", label_high="High:"): super(RangeWidget, self).__init__() @@ -905,7 +905,7 @@ def add_static_textbox(self, position: list, background_color: str = 'white', text_color: str = 'default', - size: list = None, + size: Optional[list] = None, font_family='Times', font_size=12, wrap_text=False) -> QLabel: @@ -971,7 +971,7 @@ def __init__(self, height: int, width: int, background_color: str = 'black', - widget: QWidget = None): + widget: Optional[QWidget] = None): super().__init__() self.height = height diff --git a/bcipy/gui/parameters/params_form.py b/bcipy/gui/parameters/params_form.py index 39280aa13..fc82c7780 100644 --- a/bcipy/gui/parameters/params_form.py +++ b/bcipy/gui/parameters/params_form.py @@ -397,8 +397,7 @@ def on_save(self): def on_save_as(self): """Event handler for saving form data to another parameters file.""" - options = QFileDialog.Options() - options |= QFileDialog.DontUseNativeDialog + options = QFileDialog.Option.DontUseNativeDialog filename, _ = QFileDialog.getSaveFileName( self, diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index fc0098cb0..46c76bac6 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -117,7 +117,7 @@ def init_device(content_type: str, def server_spec(content_type: str, - device_name: Optional[str] = None) -> LslDataServer: + device_name: Optional[str] = None) -> DeviceSpec: """Get the device_spec definition to use for a mock data server. If the device_name is provided, the matching preconfigured_device will be used. Otherwise, the first matching preconfigured device with the given @@ -139,7 +139,7 @@ def server_spec(content_type: str, def parse_stream_type(stream_type: str, - delimiter: str = "/") -> Tuple[str, str]: + delimiter: str = "/") -> Tuple[str, Optional[str]]: """Parses the stream type into a tuple of (content_type, device_name). Parameters @@ -161,7 +161,7 @@ def parse_stream_type(stream_type: str, def init_lsl_client(parameters: dict, device_spec: DeviceSpec, save_folder: str, - raw_data_file_name: str = None): + raw_data_file_name: Optional[str] = None): """Initialize a client that acquires data from LabStreamingLayer.""" data_buffer_seconds = round(max_inquiry_duration(parameters)) diff --git a/bcipy/helpers/convert.py b/bcipy/helpers/convert.py index 5a5f5ee7e..409a40f3d 100644 --- a/bcipy/helpers/convert.py +++ b/bcipy/helpers/convert.py @@ -1,9 +1,10 @@ +# mypy: disable-error-code="no-redef" """Functionality for converting the bcipy raw data output to other formats""" import logging import os import tarfile from pathlib import Path -from typing import Dict, List, Optional, Tuple +from typing import Dict, List, Tuple, Optional, Union import mne import numpy as np @@ -24,12 +25,12 @@ def convert_to_edf(data_dir: str, - edf_path: str = None, + edf_path: Optional[str] = None, overwrite: bool = False, write_targetness: bool = False, use_event_durations: bool = False, remove_pre_fixation: bool = False, - pre_filter: bool = False) -> Path: + pre_filter: bool = False) -> str: """ Converts BciPy data to the EDF+ filetype using pyEDFlib. See https://www.edfplus.info/ for more detailed information about the edf specification. @@ -60,7 +61,7 @@ def convert_to_edf(data_dir: str, if not edf_path.endswith('.edf'): raise ValueError(f'edf_path=[{edf_path}] must end in .edf') - data, channels, fs, events, annotation_channels, pre_filter = pyedf_convert( + data, channels, fs, events, annotation_channels, filt = pyedf_convert( data_dir, write_targetness=write_targetness, use_event_durations=use_event_durations, @@ -76,16 +77,16 @@ def convert_to_edf(data_dir: str, FILETYPE_EDFPLUS, overwrite, annotation_channels, - pre_filter) + filt) def convert_to_bdf(data_dir: str, - bdf_path: str = None, + bdf_path: Optional[str] = None, overwrite: bool = False, write_targetness: bool = False, use_event_durations: bool = False, remove_pre_fixation: bool = False, - pre_filter: bool = False) -> Path: + pre_filter: bool = False) -> Union[Path, str]: """ Converts BciPy data to the BDF+ filetype using pyEDFlib. See https://www.biosemi.com/faq/file_format.htm for more detailed information about the BDF specification. @@ -116,7 +117,7 @@ def convert_to_bdf(data_dir: str, if not bdf_path.endswith('.bdf'): raise ValueError(f'bdf_path=[{bdf_path}] must end in .bdf') - data, channels, fs, events, annotation_channels, pre_filter = pyedf_convert( + data, channels, fs, events, annotation_channels, filt = pyedf_convert( data_dir, write_targetness=write_targetness, use_event_durations=use_event_durations, @@ -132,14 +133,20 @@ def convert_to_bdf(data_dir: str, FILETYPE_BDFPLUS, overwrite, annotation_channels, - pre_filter) + filt) def pyedf_convert(data_dir: str, write_targetness: bool = False, use_event_durations: bool = False, remove_pre_fixation: bool = False, - pre_filter: bool = False) -> Tuple[RawData, List[str], int, List[Tuple[str, int, int]], int]: + pre_filter: bool = False) -> Tuple[ + np.ndarray, + List[str], + int, + List[Tuple[float, float, str]], + int, + Union[bool, str]]: """ Converts BciPy data to formats that can be used by pyEDFlib. Parameters @@ -166,9 +173,9 @@ def pyedf_convert(data_dir: str, otherwise a string of the filter parameters used to filter the data """ - params = load_json_parameters(Path(data_dir, DEFAULT_PARAMETER_FILENAME), + params = load_json_parameters(str(Path(data_dir, DEFAULT_PARAMETER_FILENAME)), value_cast=True) - data = load_raw_data(Path(data_dir, f'{RAW_DATA_FILENAME}.csv')) + data = load_raw_data(str(Path(data_dir, f'{RAW_DATA_FILENAME}.csv'))) fs = data.sample_rate if pre_filter: default_transform = get_default_transform( @@ -180,9 +187,10 @@ def pyedf_convert(data_dir: str, downsample_factor=params.get("down_sampling_rate"), ) raw_data, fs = data.by_channel(transform=default_transform) - pre_filter = (f"HP:{params.get('filter_low')} LP:{params.get('filter_high')}" - f"N:{params.get('notch_filter_frequency')} D:{params.get('down_sampling_rate')} " - f"O:{params.get('filter_order')}") + pre_filter: str = ( + f"HP:{params.get('filter_low')} LP:{params.get('filter_high')}" + f"N:{params.get('notch_filter_frequency')} D:{params.get('down_sampling_rate')} " + f"O:{params.get('filter_order')}") else: raw_data, _ = data.by_channel() durations = trigger_durations(params) if use_event_durations else {} @@ -246,14 +254,14 @@ def compile_triggers(labels: List[str], targetness: List[str], timing: List[floa def write_pyedf(output_path: str, - raw_data: np.array, + raw_data: np.ndarray, ch_names: List[str], sample_rate: float, events: List[Tuple[float, float, str]], file_type: str = FILETYPE_EDFPLUS, overwrite: bool = False, annotation_channels: int = 1, - pre_filter: Optional[str] = None) -> Path: + pre_filter: Union[bool, str] = False) -> str: """ Converts BciPy raw_data to the EDF+ or BDF+ filetype using pyEDFlib. @@ -484,7 +492,7 @@ def tar_name_checker(tar_file_name: str) -> str: def convert_to_mne( raw_data: RawData, - channel_map: List[int] = None, + channel_map: Optional[List[int]] = None, channel_types: Optional[List[str]] = None, transform: Optional[Composition] = None, montage: str = 'standard_1020', diff --git a/bcipy/helpers/copy_phrase_wrapper.py b/bcipy/helpers/copy_phrase_wrapper.py index 6dbb4c200..d779fc463 100644 --- a/bcipy/helpers/copy_phrase_wrapper.py +++ b/bcipy/helpers/copy_phrase_wrapper.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="arg-type, assignment" """Defines the CopyPhraseWrapper.""" import logging from typing import List, Tuple @@ -57,7 +58,7 @@ def __init__(self, min_num_inq: int, max_num_inq: int, lmodel: LanguageModel, - alp: List[str] = None, + alp: List[str], evidence_names: List[EvidenceType] = [ EvidenceType.LM, EvidenceType.ERP ], @@ -109,7 +110,7 @@ def __init__(self, self.backspace_prob = backspace_prob def add_evidence(self, evidence_type: EvidenceType, - evidence: List[float]) -> np.array: + evidence: List[float]) -> np.ndarray: """Add evidence to the conjugator. Parameters diff --git a/bcipy/helpers/list.py b/bcipy/helpers/list.py index a8cfeb7c8..d1ca9d20e 100644 --- a/bcipy/helpers/list.py +++ b/bcipy/helpers/list.py @@ -1,9 +1,9 @@ """Utility functions for list processing.""" -from typing import Callable, List +from typing import Any, Callable, List from itertools import zip_longest -def destutter(items: List, key: Callable = lambda x: x) -> List: +def destutter(items: List[Any], key: Callable = lambda x: x) -> List: """Removes sequential duplicates from a list. Retains the last item in the sequence. Equality is determined using the provided key function. @@ -12,7 +12,7 @@ def destutter(items: List, key: Callable = lambda x: x) -> List: items - list of items with sequential duplicates key - equality function """ - deduped = [] + deduped: List[Any] = [] for item in items: if len(deduped) == 0 or key(item) != key(deduped[-1]): deduped.append(item) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index a12980ef3..7b36c2a43 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="arg-type, union-attr" import json import logging import os @@ -23,7 +24,7 @@ def copy_parameters(path: str = DEFAULT_PARAMETERS_PATH, - destination: str = None) -> str: + destination: Optional[str] = None) -> str: """Creates a copy of the given configuration (parameters.json) to the given directory and returns the path. @@ -187,7 +188,7 @@ def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: return models -def choose_csv_file(filename: str = None) -> str: +def choose_csv_file(filename: Optional[str] = None) -> Optional[str]: """GUI prompt to select a csv file from the file system. Parameters @@ -236,7 +237,7 @@ def load_txt_data() -> str: return filename -def load_users(data_save_loc) -> List[str]: +def load_users(data_save_loc: str) -> List[str]: """Load Users. Loads user directory names below experiments from the data path defined and returns them as a list. @@ -244,7 +245,7 @@ def load_users(data_save_loc) -> List[str]: have been run yet. """ # build a saved users list, pull out the data save location from parameters - saved_users = [] + saved_users: List[str] = [] # check the directory is valid, if it is, set path as data save location if os.path.isdir(data_save_loc): diff --git a/bcipy/helpers/parameters.py b/bcipy/helpers/parameters.py index d89eacbba..970d9a023 100644 --- a/bcipy/helpers/parameters.py +++ b/bcipy/helpers/parameters.py @@ -4,7 +4,7 @@ from json import dump, load from pathlib import Path from re import fullmatch -from typing import Any, Dict, NamedTuple, Tuple +from typing import Optional, Any, Dict, NamedTuple, Tuple from bcipy.config import DEFAULT_ENCODING, DEFAULT_PARAMETERS_PATH @@ -52,7 +52,7 @@ def parse_range(range_str: str) -> Tuple: return (low, high) -def serialize_value(value_type: str, value: any) -> str: +def serialize_value(value_type: str, value: Any) -> str: """Serialize the given value to a string. Serialized values should be able to be cast using the conversions.""" if value_type == 'bool': @@ -73,7 +73,7 @@ class Parameters(dict): cast_values: bool - if True cast values to specified type; default is False. """ - def __init__(self, source: str = None, cast_values: bool = False): + def __init__(self, source: Optional[str] = None, cast_values: bool = False): super().__init__() self.source = source self.cast_values = cast_values @@ -119,28 +119,28 @@ def from_cast_values(cls, **kwargs): return params @property - def supported_types(self): + def supported_types(self) -> set: """Supported types for casting values""" return self.conversions.keys() - def cast_value(self, entry: dict): + def cast_value(self, entry: dict) -> Any: """Takes an entry with a desired type and attempts to cast it to that type.""" cast = self.conversions[entry['type']] return cast(entry['value']) - def serialized_value(self, value, entry_type): + def serialized_value(self, value, entry_type) -> str: """Convert a value back into its serialized form""" serialized = str(value) return serialized.lower() if entry_type == 'bool' else serialized - def __getitem__(self, key): + def __getitem__(self, key) -> Any: """Override to handle cast values""" entry = self.get_entry(key) if self.cast_values: return self.cast_value(entry) return entry - def __setitem__(self, key, value): + def __setitem__(self, key, value) -> None: """Override to handle cast values""" if self.cast_values: # Can only set values for existing entries when cast. @@ -149,53 +149,53 @@ def __setitem__(self, key, value): else: self.add_entry(key, value) - def add_entry(self, key, value): + def add_entry(self, key, value) -> None: """Adds a configuration parameter.""" self.check_valid_entry(key, value) super().__setitem__(key, value) - def get_entry(self, key): + def get_entry(self, key) -> dict: """Get the non-cast entry associated with the given key.""" return super().__getitem__(key) - def get(self, key, d=None): + def get(self, key, d=None) -> Any: """Override to handle cast values""" entry = super().get(key, d) if self.cast_values and entry != d: return self.cast_value(entry) return entry - def entries(self): + def entries(self) -> list: """Uncast items""" return super().items() - def items(self): + def items(self) -> list: """Override to handle cast values""" if self.cast_values: return [(key, self.cast_value(entry)) for key, entry in self.entries()] return self.entries() - def values(self): + def values(self) -> list: """Override to handle cast values""" vals = super().values() if self.cast_values: return [self.cast_value(entry) for entry in vals] return vals - def update(self, *args, **kwargs): + def update(self, *args, **kwargs) -> None: """Override to ensure update uses __setitem___""" for key, value in dict(*args, **kwargs).items(): self[key] = value - def copy(self): + def copy(self) -> 'Parameters': """Override """ params = Parameters(source=None, cast_values=self.cast_values) params.load(super().copy()) return params - def load(self, data: dict): + def load(self, data: dict) -> None: """Load values from a dict, validating entries (see check_valid_entry) and raising an exception for invalid values. @@ -204,7 +204,7 @@ def load(self, data: dict): for name, entry in data.items(): self.add_entry(name, entry) - def load_from_source(self): + def load_from_source(self) -> None: """Load data from the configured JSON file.""" if self.source: with codecsopen(self.source, 'r', @@ -212,7 +212,7 @@ def load_from_source(self): data = load(json_file) self.load(data) - def check_valid_entry(self, entry_name: str, entry: dict): + def check_valid_entry(self, entry_name: str, entry: dict) -> None: """Checks if the given entry is valid. Raises an exception unless the entry is formatted: "fake_data": { @@ -252,7 +252,7 @@ def source_location(self) -> Tuple[Path, str]: return (path.parent, path.name) return (None, None) - def save(self, directory: str = None, name: str = None): + def save(self, directory: Optional[str] = None, name: Optional[str] = None) -> str: """Save parameters to the given location directory: str - optional location to save; default is the source_directory. @@ -310,7 +310,7 @@ def diff(self, parameters) -> Dict[str, ParameterChange]: original_value=None) return diffs - def instantiate(self, named_tuple_class: type) -> NamedTuple: + def instantiate(self, named_tuple_class: NamedTuple) -> NamedTuple: """Instantiate a namedtuple whose fields represent a subset of the parameters.""" vals = [ diff --git a/bcipy/helpers/raw_data.py b/bcipy/helpers/raw_data.py index d4e946b5d..51f1c5627 100644 --- a/bcipy/helpers/raw_data.py +++ b/bcipy/helpers/raw_data.py @@ -1,6 +1,7 @@ """Functionality for reading and writing raw signal data.""" import csv -from typing import List, Optional, TextIO, Tuple +from io import TextIOWrapper +from typing import List, Optional, TextIO, Tuple, Union, Any import numpy as np import pandas as pd @@ -17,18 +18,13 @@ class RawData: """Represents the raw data format used by BciPy. Used primarily for loading a raw data file into memory.""" - def __init__(self, - daq_type: Optional[str] = None, - sample_rate: Optional[int] = None, - columns: Optional[List[str]] = None, - column_types: Optional[List[str]] = None): + def __init__(self, daq_type: str, sample_rate: int, columns: List[str]) -> None: self.daq_type = daq_type self.sample_rate = sample_rate - self.columns = columns or [] - # accept a custom column type definition or default to all eeg type - self.column_types = column_types - self._rows = [] - self._dataframe = None + self.columns = columns + + self._dataframe: Optional[pd.DataFrame] = None + self._rows: List[Any] = [] @classmethod def load(cls, filename: str): @@ -48,7 +44,7 @@ def rows(self) -> List[List]: return self._rows @rows.setter - def rows(self, value): + def rows(self, value: Any) -> None: self._rows = value self._dataframe = None @@ -67,7 +63,7 @@ def numeric_data(self) -> pd.DataFrame: return self.dataframe.select_dtypes(exclude=['object']) @property - def channel_data(self): + def channel_data(self) -> np.ndarray: """Data for columns with numeric data, excluding the timestamp column.""" numeric_data = self.numeric_data @@ -76,7 +72,7 @@ def channel_data(self): # Start data slice at 1 to remove the timestamp column. return numeric_vals[:, 1:numeric_column_count].transpose() - def by_channel(self, transform: Optional[Composition] = None) -> np.ndarray: + def by_channel(self, transform: Optional[Composition] = None) -> Tuple[np.ndarray, int]: """Data organized by channel. Optionally, it can apply a BciPy Composition to the data before returning using the transform arg. @@ -100,7 +96,7 @@ def by_channel(self, transform: Optional[Composition] = None) -> np.ndarray: def by_channel_map( self, channel_map: List[int], - transform: Optional[Composition] = None) -> Tuple[np.ndarray, List[str], List[str]]: + transform: Optional[Composition] = None) -> Tuple[np.ndarray, List[str], int]: """By Channel Map. Returns channels with columns removed if index in list (channel_map) is zero. The channel map must align @@ -115,11 +111,11 @@ def by_channel_map( data, fs = self.by_channel(transform) channels_to_remove = [idx for idx, value in enumerate(channel_map) if value == 0] data = np.delete(data, channels_to_remove, axis=0) - channels = np.delete(self.channels, channels_to_remove, axis=0).tolist() + channels: List[str] = np.delete(self.channels, channels_to_remove, axis=0).tolist() return data, channels, fs - def apply_transform(self, data: np.ndarray, transform: Composition) -> Tuple[np.ndarray, float]: + def apply_transform(self, data: np.ndarray, transform: Composition) -> Tuple[np.ndarray, int]: """Apply Transform. Using data provided as an np.ndarray, call the Composition with self.sample_rate to apply @@ -170,7 +166,7 @@ def query(self, mask = (dataframe[column] >= start) & (dataframe[column] <= stop) return dataframe[mask] - def append(self, row: List): + def append(self, row: list) -> None: """Append the given row of data. Parameters @@ -188,7 +184,7 @@ def __repr__(self) -> str: return f"RawData({self.daq_type})" -def maybe_float(val): +def maybe_float(val: Any) -> Union[float, Any]: """Attempt to convert the given value to float. If conversion fails return as is.""" try: @@ -217,10 +213,10 @@ class RawDataReader: - convert_data : if True attempts to convert data values to floats; default is False """ + _file_obj: TextIOWrapper def __init__(self, file_path: str, convert_data: bool = False): self.file_path = file_path - self._file_obj = None self.convert_data = convert_data def __enter__(self): @@ -232,7 +228,8 @@ def __enter__(self): def __exit__(self, *args, **kwargs): """Exit the context manager. Close resources""" - self._file_obj.close() + if self._file_obj: + self._file_obj.close() def __iter__(self): return self @@ -265,14 +262,14 @@ class RawDataWriter: - sample_rate : sample frequency in Hz - columns : list of column names """ + _file_obj: TextIOWrapper def __init__(self, file_path: str, daq_type: str, sample_rate: float, - columns: List[str]): + columns: List[str]) -> None: self.file_path = file_path self.daq_type = daq_type self.sample_rate = sample_rate self.columns = columns - self._file_obj = None def __enter__(self): """Enter the context manager. Initializes the underlying data file.""" @@ -328,8 +325,8 @@ def load(filename: str) -> RawData: raise BciPyCoreException(f"\nError loading BciPy RawData. Valid data not found at: {filename}") -def read_metadata(file_obj: TextIO) -> Tuple[str, float]: - """Reads the metadata from an open raw data file and returns the result as +def read_metadata(file_obj: TextIO) -> Tuple[str, int]: + """Reads the metadata from an open raw data file and retuns the result as a tuple. Increments the reader. Parameters @@ -341,7 +338,7 @@ def read_metadata(file_obj: TextIO) -> Tuple[str, float]: tuple of daq_type, sample_rate """ daq_type = next(file_obj).strip().split(',')[1] - sample_rate = float(next(file_obj).strip().split(",")[1]) + sample_rate = int(float(next(file_obj).strip().split(",")[1])) return daq_type, sample_rate @@ -378,7 +375,7 @@ def settings(filename: str) -> Tuple[str, float, List[str]]: def sample_data(rows: int = 1000, ch_names: List[str] = ['ch1', 'ch2', 'ch3'], daq_type: str = 'SampleDevice', - sample_rate: float = 256.0, + sample_rate: int = 256, triggers: List[Tuple[float, str]] = []) -> RawData: """Creates sample data to be written as a raw_data.csv file. The resulting data has a column for the timestamp, one for each channel, and a TRG column. diff --git a/bcipy/helpers/save.py b/bcipy/helpers/save.py index e471466a9..812a66ee6 100644 --- a/bcipy/helpers/save.py +++ b/bcipy/helpers/save.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="arg-type, misc" import errno import json import os @@ -107,12 +108,12 @@ def save_device_specs(device_specs: List[DeviceSpec], location: str, name) -def _save_session_related_data(file, session_dictionary): +def _save_session_related_data(save_path: str, session_dictionary: dict) -> Any: """ Save Session Related Data. Parameters ---------- - file[str]: string of path to save our data in + save_path[str]: string of path to save our data in session_dictionary[dict]: dictionary of session data. It will appear as follows: {{ "series": { @@ -144,9 +145,9 @@ def _save_session_related_data(file, session_dictionary): """ # Try opening as json, if not able to use open() to create first try: - file = json.load(file, 'wt') + file = json.load(save_path, 'wt') except BaseException: - file = open(file, 'wt', encoding=DEFAULT_ENCODING) + file = open(save_path, 'wt', encoding=DEFAULT_ENCODING) # Use the file to dump data to json.dump(session_dictionary, file, indent=2) diff --git a/bcipy/helpers/session.py b/bcipy/helpers/session.py index a690f438e..1e747f0ad 100644 --- a/bcipy/helpers/session.py +++ b/bcipy/helpers/session.py @@ -6,7 +6,7 @@ import sqlite3 import subprocess from dataclasses import dataclass, fields -from typing import Any, Dict, List +from typing import Any, Dict, List, Optional import openpyxl from openpyxl.chart import BarChart, Reference @@ -25,7 +25,7 @@ from bcipy.task.data import Session -def read_session(file_name=SESSION_DATA_FILENAME) -> Session: +def read_session(file_name: str = SESSION_DATA_FILENAME) -> Session: """Read the session data from the given file.""" with open(file_name, 'r', encoding=DEFAULT_ENCODING) as json_file: return Session.from_dict(json.load(json_file)) @@ -45,9 +45,9 @@ def session_data(data_dir: str) -> Dict: return data -def collect_experiment_field_data(experiment_name, - save_path, - file_name=EXPERIMENT_DATA_FILENAME) -> None: +def collect_experiment_field_data(experiment_name: str, + save_path: str, + file_name: str = EXPERIMENT_DATA_FILENAME) -> None: experiment = load_experiments()[experiment_name] experiment_fields = load_experiment_fields(experiment) @@ -71,7 +71,7 @@ class EvidenceRecord: eye: float btn: float cumulative: float - inq_position: int + inq_position: Optional[int] is_target: int presented: int above_threshold: int diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 7d5e2d0a4..a2433a3c7 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="arg-type" import glob import itertools import logging @@ -7,28 +8,27 @@ from collections import Counter from enum import Enum from os import path, sep -from typing import Dict, Iterator, List, NamedTuple, Optional, Tuple - -from pandas import Series -from PIL import Image - -from bcipy.helpers.exceptions import BciPyCoreException -from bcipy.helpers.list import grouper - -# Prevents pillow from filling the console with debug info -logging.getLogger('PIL').setLevel(logging.WARNING) +from typing import Any, Dict, Iterator, List, NamedTuple, Optional, Tuple, Union import mne import numpy as np import sounddevice as sd import soundfile as sf + from mne import Annotations, Epochs from mne.io import RawArray +from pandas import Series +from PIL import Image from psychopy import core +from bcipy.config import DEFAULT_TEXT_FIXATION, DEFAULT_FIXATION_PATH +from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.helpers.list import grouper + +# Prevents pillow from filling the console with debug info +logging.getLogger('PIL').setLevel(logging.WARNING) log = logging.getLogger(__name__) -DEFAULT_FIXATION_PATH = 'bcipy/static/images/main/PLUS.png' -DEFAULT_TEXT_FIXATION = '+' + NO_TARGET_INDEX = None @@ -85,15 +85,15 @@ class InquirySchedule(NamedTuple): - durations: `List[List[float]]` - colors: `List[List[str]]` """ - stimuli: List[List[str]] - durations: List[List[float]] - colors: List[List[str]] + stimuli: Union[List[List[str]], List[str]] + durations: Union[List[List[float]], List[float]] + colors: Union[List[List[str]], List[str]] class Reshaper(ABC): @abstractmethod - def __call__(self): + def __call__(self, *args, **kwargs) -> Any: ... @@ -105,11 +105,11 @@ def __call__(self, sample_rate: int, trials_per_inquiry: int, offset: float = 0, - channel_map: List[int] = None, + channel_map: Optional[List[int]] = None, poststimulus_length: float = 0.5, prestimulus_length: float = 0.0, transformation_buffer: float = 0.0, - target_label: str = 'target') -> Tuple[np.ndarray, np.ndarray]: + target_label: str = 'target') -> Tuple[np.ndarray, np.ndarray, List[List[float]]]: """Extract inquiry data and labels. Args: @@ -157,7 +157,7 @@ def get_inquiry_len(inq_trigs): # Label for every inquiry labels = np.zeros( - (n_inquiry, trials_per_inquiry), dtype=np.compat.long + (n_inquiry, trials_per_inquiry), dtype=np.longlong ) # maybe this can be configurable? return either class indexes or labels ('nontarget' etc) reshaped_data, reshaped_trigger_timing = [], [] for inquiry_idx, trials_within_inquiry in enumerate( @@ -184,7 +184,7 @@ def get_inquiry_len(inq_trigs): def extract_trials( inquiries: np.ndarray, samples_per_trial: int, - inquiry_timing: List[List[float]], + inquiry_timing: List[List[int]], prestimulus_samples: int = 0) -> np.ndarray: """Extract Trials. @@ -199,7 +199,7 @@ def extract_trials( shape (Channels, Inquiries, Samples) samples_per_trial : int number of samples per trial - inquiry_timing : List[List[float]] + inquiry_timing : List[List[int]] For each inquiry, a list of the sample index where each trial begins prestimulus_samples : int, optional Number of samples to move the start of each trial in each inquiry, by default 0. @@ -236,7 +236,7 @@ def __call__(self, gaze_data: np.ndarray, sample_rate: int, symbol_set: List[str], - channel_map: List[int] = None, + channel_map: Optional[List[int]] = None, ) -> dict: """Extract inquiry data and labels. Different from the EEG inquiry, the gaze inquiry window starts with the first flicker and ends with the last flicker in the inquiry. Each inquiry has a length of ~3 seconds. @@ -284,7 +284,7 @@ def __call__(self, # Create a dictionary with symbols as keys and data as values # 'A': [], 'B': [] ... - data_by_targets = {} + data_by_targets: Dict[str, list] = {} for symbol in symbol_set: data_by_targets[symbol] = [] @@ -341,7 +341,7 @@ def __call__(self, eeg_data: np.ndarray, sample_rate: int, offset: float = 0, - channel_map: List[int] = None, + channel_map: Optional[List[int]] = None, poststimulus_length: float = 0.5, prestimulus_length: float = 0.0, target_label: str = "target") -> Tuple[np.ndarray, np.ndarray]: @@ -379,7 +379,7 @@ def __call__(self, triggers = list(map(lambda x: int((x + offset) * sample_rate), timing_info)) # Label for every trial in 0 or 1 - targetness_labels = np.zeros(len(triggers), dtype=np.compat.long) + targetness_labels = np.zeros(len(triggers), dtype=np.longlong) reshaped_trials = [] for trial_idx, (trial_label, trigger) in enumerate(zip(trial_targetness_label, triggers)): if trial_label == target_label: @@ -405,7 +405,7 @@ def mne_epochs(mne_data: RawArray, trigger_timing: List[float], trial_length: float, trigger_labels: List[int], - baseline: Tuple[float, float] = (None, 0)) -> Epochs: + baseline: Optional[Tuple[Any, float]] = None) -> Epochs: """MNE Epochs. Using an MNE RawArray, reshape the data given trigger information. If two labels present [0, 1], @@ -414,6 +414,8 @@ def mne_epochs(mne_data: RawArray, annotations = Annotations(trigger_timing, [trial_length] * len(trigger_timing), trigger_labels) mne_data.set_annotations(annotations) events_from_annot, _ = mne.events_from_annotations(mne_data) + if not baseline: + baseline = (None, 0.0) return Epochs(mne_data, events_from_annot, tmax=trial_length, baseline=baseline) @@ -480,7 +482,7 @@ def inq_generator(query: List[str], def best_selection(selection_elements: list, val: list, len_query: int, - always_included: List[str] = None) -> list: + always_included: Optional[List[str]] = None) -> list: """Best Selection. Given set of elements and a value function over the set, picks the len_query @@ -521,7 +523,7 @@ def best_case_rsvp_inq_gen(alp: list, stim_length: int = 10, stim_order: StimuliOrder = StimuliOrder.RANDOM, is_txt: bool = True, - inq_constants: List[str] = None) -> InquirySchedule: + inq_constants: Optional[List[str]] = None) -> InquirySchedule: """Best Case RSVP Inquiry Generation. Generates RSVPKeyboard inquiry by picking n-most likely letters. @@ -591,9 +593,9 @@ def best_case_rsvp_inq_gen(alp: list, def generate_calibration_inquiries( alp: List[str], - timing: List[float] = None, + timing: Optional[List[float]] = None, jitter: Optional[int] = None, - color: List[str] = None, + color: Optional[List[str]] = None, inquiry_count: int = 100, stim_per_inquiry: int = 10, stim_order: StimuliOrder = StimuliOrder.RANDOM, @@ -761,8 +763,8 @@ def generate_inquiry(symbols: List[str], length: int, def inquiry_target(inquiry: List[str], target_position: Optional[int], symbols: List[str], - next_targets: List[str] = None, - last_target: str = None) -> str: + next_targets: Optional[List[str]] = None, + last_target: Optional[str] = None) -> str: """Returns the target for the given inquiry. If the optional target position is not provided a target will randomly be selected from the list of symbols and will not be in the inquiry. @@ -786,7 +788,6 @@ def inquiry_target(inquiry: List[str], # if none of the symbols in the current inquiry are in the choices, the # target is determined strictly from the target_position. choice_index = None - symbol_inquiry_position = None target = None for position, symbol in enumerate(inquiry): # avoid repeating targets @@ -975,7 +976,7 @@ def generate_targets(symbols: List[str], inquiry_count: int, return targets -def target_index(inquiry: List[str]) -> int: +def target_index(inquiry: List[str]) -> Optional[int]: """Given an inquiry, return the index of the target within the choices and None if the target is not included as a choice. @@ -1013,14 +1014,14 @@ def get_task_info(experiment_length: int, task_color: str) -> Tuple[List[str], L """ # Do list comprehensions to get the arrays for the task we need. - task_text = ['%s/%s' % (stim + 1, experiment_length) - for stim in range(experiment_length)] - task_color = [[str(task_color)] for stim in range(experiment_length)] + task_text_list = ['%s/%s' % (stim + 1, experiment_length) + for stim in range(experiment_length)] + task_color_list = [str(task_color) for _ in range(experiment_length)] - return (task_text, task_color) + return (task_text_list, task_color_list) -def resize_image(image_path: str, screen_size: tuple, sti_height: int) -> Tuple[float, float]: +def resize_image(image_path: str, screen_size: tuple, sti_height: float) -> Tuple[float, float]: """Resize Image. Returns the width and height that a given image should be displayed at @@ -1056,7 +1057,7 @@ def play_sound(sound_file_path: str, sound_callback=None, sound_load_buffer_time: float = 0.5, experiment_clock=None, - trigger_name: str = None, + trigger_name: Optional[str] = None, timing: list = []) -> list: """Play Sound. diff --git a/bcipy/helpers/system_utils.py b/bcipy/helpers/system_utils.py index cb178ca40..f0bd30d5c 100644 --- a/bcipy/helpers/system_utils.py +++ b/bcipy/helpers/system_utils.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="import-untyped" """Utilities for system information and general functionality that may be shared across modules.""" import importlib @@ -74,7 +75,7 @@ def is_screen_refresh_rate_low(refresh: Optional[float] = None) -> bool: return refresh < 120 -def git_dir() -> str: +def git_dir() -> Optional[str]: """Git Directory. Returns the root directory with the .git folder. If this source code @@ -127,7 +128,7 @@ def bcipy_version() -> str: Gets the current bcipy version. If the current instance of bcipy is a git repository, appends the current abbreviated sha hash. """ - version = pkg_resources.get_distribution('bcipy').version + version: str = pkg_resources.get_distribution('bcipy').version sha_hash = git_hash() return f'{version} - {sha_hash}' if sha_hash else version @@ -151,7 +152,7 @@ def get_gpu_info() -> List[dict]: """Information about GPUs available for processing.""" properties = [] for idx in range(torch.cuda.device_count()): - prop = torch.get_device_properties(idx) + prop = torch.cuda.get_device_properties(idx) properties.append(dict(name=prop.name, total_memory=prop.total_memory)) return properties diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index e135f3b8e..07a1b401e 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -1,11 +1,12 @@ import logging import random -from typing import Any, Dict, List, Tuple, Union +from typing import Optional, Any, Dict, List, Tuple, Union import numpy as np from psychopy import core, event, visual from bcipy.acquisition.multimodal import ClientManager, ContentType +from bcipy.acquisition.record import Record from bcipy.config import SESSION_COMPLETE_MESSAGE from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import get_fixation @@ -14,7 +15,7 @@ log = logging.getLogger(__name__) -def fake_copy_phrase_decision(copy_phrase, target_letter, text_task): +def fake_copy_phrase_decision(copy_phrase: str, target_letter: str, text_task: str) -> Tuple[str, str, bool]: """Fake Copy Phrase Decision. Parameters @@ -51,7 +52,7 @@ def fake_copy_phrase_decision(copy_phrase, target_letter, text_task): # else, end the run else: run = False - next_target_letter = None + next_target_letter = '' text_task = copy_phrase return next_target_letter, text_task, run @@ -75,7 +76,7 @@ def calculate_stimulation_freq(flash_time: float) -> float: return 1 / flash_time -def construct_triggers(inquiry_timing: List[List]) -> List[Tuple[str, float]]: +def construct_triggers(inquiry_timing: List[Tuple[str, float]]) -> List[Tuple[str, float]]: """Construct triggers from inquiry_timing data. Parameters @@ -95,7 +96,7 @@ def construct_triggers(inquiry_timing: List[List]) -> List[Tuple[str, float]]: def target_info(triggers: List[Tuple[str, float]], - target_letter: str = None, + target_letter: Optional[str] = None, is_txt: bool = True) -> List[str]: """Targetness for each item in triggers. @@ -114,11 +115,11 @@ def target_info(triggers: List[Tuple[str, float]], return [labels.get(trg[0], 'nontarget') for trg in triggers] -def get_data_for_decision(inquiry_timing, - daq, - offset=0.0, - prestim=0.0, - poststim=0.0): +def get_data_for_decision(inquiry_timing: List[Tuple[str, float]], + daq: ClientManager, + offset: float = 0.0, + prestim: float = 0.0, + poststim: float = 0.0) -> Tuple[np.ndarray, List[Tuple[str, float]]]: """Queries the acquisition client for a slice of data and processes the resulting raw data into a form that can be passed to signal processing and classifiers. @@ -176,11 +177,11 @@ def get_data_for_decision(inquiry_timing, def get_device_data_for_decision( - inquiry_timing: List[Tuple], + inquiry_timing: List[Tuple[str, float]], daq: ClientManager, offset: float = 0.0, prestim: float = 0.0, - poststim: float = 0.0) -> Dict[ContentType, np.ndarray]: + poststim: float = 0.0) -> Dict[ContentType, List[Record]]: """Queries the acquisition client manager for a slice of data from each device and processes the resulting raw data into a form that can be passed to signal processing and classifiers. diff --git a/bcipy/helpers/tests/test_raw_data.py b/bcipy/helpers/tests/test_raw_data.py index 6e6812e97..803697915 100644 --- a/bcipy/helpers/tests/test_raw_data.py +++ b/bcipy/helpers/tests/test_raw_data.py @@ -24,7 +24,7 @@ def setUp(self): self.temp_dir = tempfile.mkdtemp() self.path = Path(self.temp_dir, 'test_raw_data.csv') self.daq_type = 'Test-Device' - self.sample_rate = 300.0 + self.sample_rate = 300 self.columns = ['timestamp', 'ch1', 'ch2', 'ch3'] self.row1 = [1, 1.0, 2.0, 3.0] self.row2 = [2, 4.0, 5.0, 6.0] diff --git a/bcipy/helpers/tests/test_visualization.py b/bcipy/helpers/tests/test_visualization.py index bd94706df..e285a929d 100644 --- a/bcipy/helpers/tests/test_visualization.py +++ b/bcipy/helpers/tests/test_visualization.py @@ -16,7 +16,7 @@ class TestVisualizeSessionData(unittest.TestCase): """Test Session Data Visualization.""" def setUp(self): - self.tmp_dir = Path(tempfile.mkdtemp()) + self.tmp_dir = str(Path(tempfile.mkdtemp())) self.parameters = load_json_parameters(DEFAULT_PARAMETERS_PATH, value_cast=True) self.raw_data_mock = mock() self.raw_data_mock.daq_type = 'DSI-24' @@ -35,7 +35,10 @@ def test_visualize_session_data(self): when(RawData).load(any()).thenReturn(self.raw_data_mock) when(visualization).analysis_channels(any(), any()).thenReturn(self.channel_map_mock) when(visualization).trigger_decoder( - offset=any(), trigger_path=any(), exclusion=any()).thenReturn( + offset=any(), + trigger_path=any(), + exclusion=any(), + device_type=any()).thenReturn( (trigger_label_mock, trigger_timing_mock, [])) when(visualization).visualize_erp( self.raw_data_mock, @@ -55,7 +58,11 @@ def test_visualize_session_data(self): self.assertTrue(resp) verify(RawData, times=1).load(any()) verify(visualization, times=1).analysis_channels(any(), any()) - verify(visualization, times=1).trigger_decoder(offset=any(), trigger_path=any(), exclusion=any()) + verify(visualization, times=1).trigger_decoder( + offset=any(), + trigger_path=any(), + exclusion=any(), + device_type=any()) verify(visualization, times=1).visualize_erp( self.raw_data_mock, self.channel_map_mock, @@ -77,7 +84,10 @@ def test_visualize_session_data_with_no_valid_targets(self): when(RawData).load(any()).thenReturn(self.raw_data_mock) when(visualization).analysis_channels(any(), any()).thenReturn(self.channel_map_mock) when(visualization).trigger_decoder( - offset=any(), trigger_path=any(), exclusion=any()).thenReturn( + offset=any(), + trigger_path=any(), + exclusion=any(), + device_type=any()).thenReturn( (trigger_label_mock, trigger_timing_mock, [])) with self.assertRaises(AssertionError): @@ -92,7 +102,10 @@ def test_visualize_session_data_with_no_valid_nontargets(self): when(RawData).load(any()).thenReturn(self.raw_data_mock) when(visualization).analysis_channels(any(), any()).thenReturn(self.channel_map_mock) when(visualization).trigger_decoder( - offset=any(), trigger_path=any(), exclusion=any()).thenReturn( + offset=any(), + trigger_path=any(), + exclusion=any(), + device_type=any()).thenReturn( (trigger_label_mock, trigger_timing_mock, [])) with self.assertRaises(AssertionError): @@ -107,7 +120,10 @@ def test_visualize_session_data_with_invalid_timing(self): when(RawData).load(any()).thenReturn(self.raw_data_mock) when(visualization).analysis_channels(any(), any()).thenReturn(self.channel_map_mock) when(visualization).trigger_decoder( - offset=any(), trigger_path=any(), exclusion=any()).thenReturn( + offset=any(), + trigger_path=any(), + exclusion=any(), + device_type=any()).thenReturn( (trigger_label_mock, trigger_timing_mock, [])) with self.assertRaises(AssertionError): @@ -116,7 +132,10 @@ def test_visualize_session_data_with_invalid_timing(self): # in this case, add a third trigger time trigger_timing_mock = [1, 2, 3] when(visualization).trigger_decoder( - offset=any(), trigger_path=any(), exclusion=any()).thenReturn( + offset=any(), + trigger_path=any(), + exclusion=any(), + device_type=any()).thenReturn( (trigger_label_mock, trigger_timing_mock, [])) with self.assertRaises(AssertionError): diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 65f0c1710..7d3064e20 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -48,12 +48,12 @@ def list(cls): class TriggerCallback: - timing = None - first_time = True + timing: Optional[Tuple[str, float]] = None + first_time: bool = True def callback(self, clock: Clock, stimuli: str) -> None: if self.first_time: - self.timing = [stimuli, clock.getTime()] + self.timing = (stimuli, clock.getTime()) self.first_time = False def reset(self): @@ -66,7 +66,7 @@ def _calibration_trigger(experiment_clock: Clock, trigger_name: str = 'calibration', trigger_time: float = 1, display=None, - on_trigger=None) -> List[tuple]: + on_trigger=None) -> Tuple[str, float]: """Calibration Trigger. Outputs triggers for the purpose of calibrating data and stimuli. @@ -130,6 +130,9 @@ def _calibration_trigger(experiment_clock: Clock, display.flip() core.wait(trigger_time) + if trigger_callback.timing is None: + log.warning(f'No trigger found for [{trigger_name}]') + return trigger_name, 0.0 return trigger_callback.timing @@ -375,10 +378,9 @@ def __init__(self, self.path = path self.file_name = f'{file_name}.txt' if not file_name.endswith('.txt') else file_name self.flush = flush - self.triggers = [] + self.triggers: List[Trigger] = [] self.file_path = f'{self.path}/{self.file_name}' self.flush = flush - self.triggers = [] if os.path.exists(self.file_name): raise Exception(f"[{self.file_name}] already exists, any writing " @@ -422,7 +424,7 @@ def read_text_file(path: str) -> Tuple[List[Trigger], float]: @staticmethod def load(path: str, - offset: Optional[float] = 0.0, + offset: float = 0.0, exclusion: Optional[List[TriggerType]] = None, device_type: Optional[str] = None) -> List[Trigger]: """ @@ -480,7 +482,7 @@ def add_triggers(self, triggers: List[Trigger]) -> List[Trigger]: return self.triggers -def convert_timing_triggers(timing: List[tuple], target_stimuli: str, +def convert_timing_triggers(timing: List[Tuple[str, float]], target_stimuli: str, trigger_type: Callable) -> List[Trigger]: """Convert Stimuli Times to Triggers. diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index d65340407..44586e714 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -1,6 +1,8 @@ +# mypy: disable-error-code="attr-defined,union-attr,arg-type" +# needed for the ERPTransformParams import logging +from typing import List, Dict, Optional, Tuple, Union from pathlib import Path -from typing import List, Dict, Optional, Tuple import matplotlib.pyplot as plt import mne @@ -17,6 +19,7 @@ from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, RAW_DATA_FILENAME, STATIC_IMAGES_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels +from bcipy.helpers.parameters import Parameters from bcipy.helpers.convert import convert_to_mne from bcipy.helpers.load import choose_csv_file, load_raw_data from bcipy.helpers.raw_data import RawData @@ -82,9 +85,9 @@ def visualize_erp( # check for a baseline interval or set to None if trial_window[0] < 0: - baseline = (trial_window[0], 0) + baseline = (trial_window[0], 0.0) else: - baseline = (None, 0) + baseline = None mne_data = convert_to_mne(raw_data, channel_map=channel_map, transform=transform) epochs = mne_epochs(mne_data, trigger_timing, trial_length, trigger_labels, baseline=baseline) @@ -576,7 +579,7 @@ def visualize_csv_eeg_triggers(trigger_col: Optional[int] = None): """ # Load in CSV data = load_raw_data(choose_csv_file()) - raw_data = data.by_channel() + raw_data, _ = data.by_channel() # Pull out the triggers if not trigger_col: @@ -661,7 +664,7 @@ def visualize_evokeds(epochs: Tuple[Epochs, Epochs], return fig -def visualize_session_data(session_path: str, parameters: dict, show=True) -> Figure: +def visualize_session_data(session_path: str, parameters: Union[dict, Parameters], show=True) -> Figure: """Visualize Session Data. This method is used to load and visualize EEG data after a session. @@ -682,14 +685,15 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi trial_window = parameters.get("trial_window") static_offset = parameters.get("static_trigger_offset") - raw_data = load_raw_data(Path(session_path, f'{RAW_DATA_FILENAME}.csv')) + raw_data = load_raw_data(str(Path(session_path, f'{RAW_DATA_FILENAME}.csv'))) channels = raw_data.channels sample_rate = raw_data.sample_rate + daq_type = raw_data.daq_type - transform_params = parameters.instantiate(ERPTransformParams) + transform_params: ERPTransformParams = parameters.instantiate(ERPTransformParams) devices.load(Path(session_path, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) + device_spec = devices.preconfigured_device(daq_type) # setup filtering default_transform = get_default_transform( @@ -705,6 +709,7 @@ def visualize_session_data(session_path: str, parameters: dict, show=True) -> Fi offset=static_offset, trigger_path=f"{session_path}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + device_type='EEG', ) assert "nontarget" in trigger_targetness, "No nontarget triggers found." assert "target" in trigger_targetness, "No target triggers found." diff --git a/bcipy/language/README.md b/bcipy/language/README.md index e4150f18f..1438a7455 100644 --- a/bcipy/language/README.md +++ b/bcipy/language/README.md @@ -31,7 +31,7 @@ The language module has the following structure: The UniformLanguageModel provides equal probabilities for all symbols in the symbol set. This model is useful for evaluating other aspects of the system, such as EEG signal quality, without any influence from a language model. ## KenLM Model -The KenLMLanguageModel utilizes a pretrained n-gram language model to generate probabilities for all symbols in the symbol set. N-gram models use frequencies of different character sequences to generate their predictions. Models trained on AAC-like data can be found [here](https://imagineville.org/software/lm/dec19_char/). For faster load times, it is recommended to use the binary models located at the bottom of the page. The default parameters file utilizes `lm_dec19_char_large_12gram.kenlm`. +The KenLMLanguageModel utilizes a pretrained n-gram language model to generate probabilities for all symbols in the symbol set. N-gram models use frequencies of different character sequences to generate their predictions. Models trained on AAC-like data can be found [here](https://imagineville.org/software/lm/dec19_char/). For faster load times, it is recommended to use the binary models located at the bottom of the page. The default parameters file utilizes `lm_dec19_char_large_12gram.kenlm`. If you have issues accessing, please reach out to us on GitHub or via email at `cambi_support@googlegroups.com`. For models that import the kenlm module, this must be manually installed using `pip install kenlm==0.1 --global-option="max_order=12"`. diff --git a/bcipy/language/model/causal.py b/bcipy/language/model/causal.py index 9461034d8..6e7aa2b51 100644 --- a/bcipy/language/model/causal.py +++ b/bcipy/language/model/causal.py @@ -1,6 +1,6 @@ from collections import Counter import torch -from typing import List, Tuple +from typing import Optional, List, Tuple from transformers import AutoModelForCausalLM, AutoTokenizer import itertools import heapq @@ -22,8 +22,8 @@ class CausalLanguageModel(LanguageModel): def __init__(self, response_type: ResponseType, symbol_set: List[str], - lang_model_name: str = None, - lm_path: str = None, + lang_model_name: Optional[str] = None, + lm_path: Optional[str] = None, lm_device: str = "cpu", lm_left_context: str = "", ): diff --git a/bcipy/language/model/kenlm.py b/bcipy/language/model/kenlm.py index 815e0d693..8da4ea8c8 100644 --- a/bcipy/language/model/kenlm.py +++ b/bcipy/language/model/kenlm.py @@ -1,5 +1,5 @@ from collections import Counter -from typing import List, Tuple +from typing import Optional, List, Tuple from bcipy.helpers.symbols import BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.main import LanguageModel, ResponseType from bcipy.helpers.exceptions import InvalidLanguageModelException, KenLMInstallationException @@ -15,7 +15,7 @@ class KenLMLanguageModel(LanguageModel): """Character n-gram language model using the KenLM library for querying""" - def __init__(self, response_type: ResponseType, symbol_set: List[str], lm_path: str = None): + def __init__(self, response_type: ResponseType, symbol_set: List[str], lm_path: Optional[str] = None): super().__init__(response_type=response_type, symbol_set=symbol_set) self.model = None diff --git a/bcipy/language/model/mixture.py b/bcipy/language/model/mixture.py index 19b9a936f..8a7bd2548 100644 --- a/bcipy/language/model/mixture.py +++ b/bcipy/language/model/mixture.py @@ -1,5 +1,5 @@ from collections import Counter -from typing import Dict, List, Tuple +from typing import Optional, Dict, List, Tuple from math import isclose from bcipy.language.main import LanguageModel, ResponseType @@ -49,9 +49,9 @@ def validate_parameters(types: List[str], weights: List[float], params: List[Dic def __init__(self, response_type: ResponseType, symbol_set: List[str], - lm_types: List[str] = None, - lm_weights: List[float] = None, - lm_params: List[Dict[str, str]] = None): + lm_types: Optional[List[str]] = None, + lm_weights: Optional[List[float]] = None, + lm_params: Optional[List[Dict[str, str]]] = None): """ Initialize instance variables and load the language model with given path Args: diff --git a/bcipy/language/model/uniform.py b/bcipy/language/model/uniform.py index 35420cb8d..013735ba6 100644 --- a/bcipy/language/model/uniform.py +++ b/bcipy/language/model/uniform.py @@ -48,7 +48,7 @@ def load(self) -> None: def equally_probable(alphabet: List[str], - specified: Dict[str, float] = None) -> List[float]: + specified: Optional[Dict[str, float]] = None) -> List[float]: """Returns a list of probabilities which correspond to the provided alphabet. Unless overridden by the specified values, all items will have the same probability. All probabilities sum to 1.0. diff --git a/bcipy/language/model/unigram.py b/bcipy/language/model/unigram.py index 40bdda067..4222898c2 100644 --- a/bcipy/language/model/unigram.py +++ b/bcipy/language/model/unigram.py @@ -1,4 +1,4 @@ -from typing import List, Tuple +from typing import Optional, List, Tuple from bcipy.helpers.symbols import BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.main import LanguageModel, ResponseType from bcipy.helpers.exceptions import InvalidLanguageModelException @@ -9,7 +9,7 @@ class UnigramLanguageModel(LanguageModel): """Character language model based on trained unigram weights""" - def __init__(self, response_type: ResponseType, symbol_set: List[str], lm_path: str = None): + def __init__(self, response_type: ResponseType, symbol_set: List[str], lm_path: Optional[str] = None): super().__init__(response_type=response_type, symbol_set=symbol_set) self.model = None diff --git a/bcipy/language/tests/test_kenlm.py b/bcipy/language/tests/test_kenlm.py index 3c2ec3429..1e0a81e36 100644 --- a/bcipy/language/tests/test_kenlm.py +++ b/bcipy/language/tests/test_kenlm.py @@ -129,3 +129,7 @@ def test_nonzero_prob(self): prob_values = [item[1] for item in symbol_probs if item[0] != BACKSPACE_CHAR] for value in prob_values: self.assertTrue(value > 0) + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/main.py b/bcipy/main.py index d185091de..2a9d1bfc4 100644 --- a/bcipy/main.py +++ b/bcipy/main.py @@ -1,7 +1,7 @@ import argparse import logging import multiprocessing -from typing import List +from typing import List, Optional from psychopy import visual @@ -122,7 +122,7 @@ def execute_task( which will initialize experiment. Input: - (str): registered bcipy TaskType + task(TaskType): Task that should be registered in TaskType parameters (dict): parameter dictionary save_folder (str): path to save folder alert (bool): whether to alert the user when the task is complete @@ -183,7 +183,7 @@ def execute_task( def _clean_up_session( display: visual.Window, daq: ClientManager, - servers: List[LslDataServer] = None) -> bool: + servers: Optional[List[LslDataServer]] = None) -> bool: """Clean up session. Closes the display window and data acquisition objects. Returns True if the session was closed successfully. @@ -198,8 +198,10 @@ def _clean_up_session( daq.stop_acquisition() daq.cleanup() - for server in servers: - server.stop() + # Stop Servers + if servers: + for server in servers: + server.stop() # Close the display window # NOTE: There is currently a bug in psychopy when attempting to shutdown diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index 48af0e2bc..5400ba106 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -28,7 +28,7 @@ { "name": "T4", "label": "T4", "units": "microvolts", "type": "EEG" }, { "name": "TRG", "label": "TRG", "units": "microvolts", "type": "EEG "} ], - "sample_rate": 300.0, + "sample_rate": 300, "description": "Wearable Sensing DSI-24", "excluded_from_analysis": [ "TRG", @@ -55,7 +55,7 @@ { "name": "Oz", "label": "Oz", "units": "microvolts", "type": "EEG" }, { "name": "TRG", "label": "TRG", "units": "microvolts", "type": "EEG" } ], - "sample_rate": 300.0, + "sample_rate": 300, "description": "Wearable Sensing DSI-VR300", "excluded_from_analysis": ["TRG", "F7"] }, @@ -80,7 +80,7 @@ { "name": "Ch15", "label": "Ch15", "units": "microvolts", "type": "EEG" }, { "name": "Ch16", "label": "Ch16", "units": "microvolts", "type": "EEG" } ], - "sample_rate": 256.0, + "sample_rate": 256, "description": "GTec g.USBamp" }, { diff --git a/bcipy/preferences.py b/bcipy/preferences.py index a36fea5de..15963e3fb 100644 --- a/bcipy/preferences.py +++ b/bcipy/preferences.py @@ -1,7 +1,7 @@ """Module for recording and loading application state and user preferences.""" import json from pathlib import Path -from typing import Any +from typing import Optional, Any, Dict from bcipy.config import DEFAULT_ENCODING, PREFERENCES_PATH, BCIPY_ROOT @@ -17,7 +17,7 @@ class Pref: default - default value assigned to the attribute. """ - def __init__(self, default: Any = None): + def __init__(self, default: Optional[Any] = None): self.default = default self.name = None @@ -44,12 +44,12 @@ class Preferences: ---------- filename - optional file used for persisting entries. """ - signal_model_directory: str = Pref() - last_directory: str = Pref(default=str(BCIPY_ROOT)) + signal_model_directory = Pref() + last_directory = Pref(default=str(BCIPY_ROOT)) - def __init__(self, filename: str = PREFERENCES_PATH): + def __init__(self, filename: str = PREFERENCES_PATH) -> None: self.filename = filename - self.entries = {} + self.entries: Dict[Any, Any] = {} self.load() def load(self): diff --git a/bcipy/signal/evaluate/evaluator.py b/bcipy/signal/evaluate/evaluator.py index 7883d6320..052743170 100644 --- a/bcipy/signal/evaluate/evaluator.py +++ b/bcipy/signal/evaluate/evaluator.py @@ -1,4 +1,7 @@ -from bcipy.signal.evaluate.rules import HighVoltage, LowVoltage +from bcipy.signal.evaluate.rules import HighVoltage, LowVoltage, Rule +from typing import List + +import numpy as np class Evaluator: @@ -15,8 +18,8 @@ class Evaluator: rules (list of rule objects, defined in rules.py) """ - def __init__(self, parameters, high_voltage, low_voltage): - self.rules = [] + def __init__(self, parameters, high_voltage, low_voltage) -> None: + self.rules: List[Rule] = [] # if high_voltage threshold is enabled, add to rules if high_voltage: @@ -26,7 +29,7 @@ def __init__(self, parameters, high_voltage, low_voltage): if low_voltage: self.rules.append(LowVoltage(parameters['low_voltage_value'])) - def evaluate(self, data): + def evaluate(self, data: np.ndarray) -> bool: """Evaluate. Evaluates inquiry data using selected rules from parameters file. diff --git a/bcipy/signal/evaluate/rules.py b/bcipy/signal/evaluate/rules.py index 2d8c46cde..b85ffa921 100644 --- a/bcipy/signal/evaluate/rules.py +++ b/bcipy/signal/evaluate/rules.py @@ -16,7 +16,7 @@ def __init__(self, threshold): # a method required for all subclasses @abstractmethod - def is_broken(self, data): + def is_broken(self, data: np.ndarray) -> bool: ... @@ -30,7 +30,7 @@ class HighVoltage(Rule): parameters.json """ - def is_broken(self, data): + def is_broken(self, data: np.ndarray) -> bool: """Is Broken. Test data against threshold value. Return broken @@ -49,7 +49,7 @@ def is_broken(self, data): return False - def __str__(self): + def __str__(self) -> str: return f'High Voltage with threshold {self.threshold}' @@ -59,7 +59,7 @@ class LowVoltage(Rule): Set low threshold for permitted voltage. """ - def is_broken(self, data): + def is_broken(self, data: np.ndarray) -> bool: """Is Broken. Test data against threshold value. Return false @@ -78,5 +78,5 @@ def is_broken(self, data): return False - def __str__(self): + def __str__(self) -> str: return f'Low Voltage with threshold {self.threshold}' diff --git a/bcipy/signal/model/README.md b/bcipy/signal/model/README.md index ad49a0aba..2ab4e0786 100644 --- a/bcipy/signal/model/README.md +++ b/bcipy/signal/model/README.md @@ -37,18 +37,21 @@ This model involves the following stages: # Testing -Run tests for this module with: +Run tests for this module as follows (from the root directory): + ```bash pytest --mpl bcipy/signal/tests/model -k "not slow" # unit tests only pytest --mpl bcipy/signal/tests/model -k "slow" # integration tests only pytest --mpl bcipy/signal/tests/model # all tests ``` -## pytest-mpl +### notes on pytest-mpl Some tests in `bcipy/signal/tests/model` use a pytest plugin to compare an output plot against the expected output plot. -When the code is in a known working state, generate the "expected" results by running: +If debugging integration tests using pytest-mpl (e.g. `Failed: Error: Image files did not match.`), you can use the `--mpl-generate-summary=html` flag to generate a summary of the figures generated by the tests to compare to the expected output. This will generate a file `pytest-mpl-summary.html` in the current directory. + +When the code is in a known working state, you can generate the "expected" results by running: ```bash pytest -k --mpl-generate-path= diff --git a/bcipy/signal/model/dimensionality_reduction.py b/bcipy/signal/model/dimensionality_reduction.py index f5c3c9e0b..2a4d4bfc8 100644 --- a/bcipy/signal/model/dimensionality_reduction.py +++ b/bcipy/signal/model/dimensionality_reduction.py @@ -30,7 +30,7 @@ def __init__(self, n_components: Optional[float] = None, random_state: Optional[ self.logger = logging.getLogger(__name__) self.logger.info(f"PCA. n_components={n_components}, random_state={random_state}, num_ch={num_ch}") - def fit(self, x: np.ndarray, y: np.ndarray = None) -> None: + def fit(self, x: np.ndarray, y: Optional[np.ndarray] = None) -> None: """Fit PCA to each channel of data. Args: @@ -42,7 +42,7 @@ def fit(self, x: np.ndarray, y: np.ndarray = None) -> None: for i in range(self.num_ch): self.list_pca[i].fit(x[i, :, :], y) - def transform(self, x: np.ndarray, y: np.ndarray = None) -> np.ndarray: + def transform(self, x: np.ndarray, y: Optional[np.ndarray] = None) -> np.ndarray: """Apply fitted PCA to each channel. Args: @@ -57,7 +57,7 @@ def transform(self, x: np.ndarray, y: np.ndarray = None) -> np.ndarray: f_vector.append(self.list_pca[i].transform(x[i, :, :])) return np.concatenate(f_vector, axis=1) - def fit_transform(self, x: np.ndarray, y: np.ndarray = None) -> np.ndarray: + def fit_transform(self, x: np.ndarray, y: Optional[np.ndarray] = None) -> np.ndarray: self.fit(x) return self.transform(x) @@ -71,7 +71,7 @@ def __init__(self, *args, **kw): def fit(self, *args, **kw): pass - def transform(self, x: np.ndarray, y: np.ndarray = None, var_tol: Optional[float] = None) -> np.ndarray: + def transform(self, x: np.ndarray, y: Optional[np.ndarray] = None, var_tol: Optional[float] = None) -> np.ndarray: """Mock transform method for testing purposes. Args: @@ -86,6 +86,7 @@ def transform(self, x: np.ndarray, y: np.ndarray = None, var_tol: Optional[float x = x.reshape([x.shape[0], -1]) return x - def fit_transform(self, x: np.ndarray, y: np.ndarray = None, var_tol: Optional[float] = None) -> np.ndarray: + def fit_transform(self, x: np.ndarray, y: Optional[np.ndarray] + = None, var_tol: Optional[float] = None) -> np.ndarray: self.fit(x) return self.transform(x, y, var_tol) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 39e864453..ff7e1122b 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -1,3 +1,5 @@ +# mypy: disable-error-code="attr-defined" +# needed for the ERPTransformParams import logging from pathlib import Path from typing import Tuple @@ -72,7 +74,7 @@ def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_s def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balanced_acc, - save_figures=True, show_figures=False): + save_figures=False, show_figures=False): """Analyze ERP data and return/save the ERP model. Extract relevant information from raw data object. Extract timing information from trigger file. @@ -96,7 +98,7 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance # Extract relevant session information from parameters file trial_window = parameters.get("trial_window") if trial_window is None: - trial_window = [0.0, 0.5] + trial_window = (0.0, 0.5) window_length = trial_window[1] - trial_window[0] prestim_length = parameters.get("prestim_length") @@ -174,7 +176,7 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance data = model.reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) # define the training classes using integers, where 0=nontargets/1=targets - labels = inquiry_labels.flatten() + labels = inquiry_labels.flatten().tolist() # train and save the model as a pkl file log.info("Training model. This will take some time...") diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index 6d30f2386..7187e5c2c 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -17,7 +17,7 @@ class PcaRdaKdeModel(SignalModel): - reshaper = InquiryReshaper() + reshaper: InquiryReshaper = InquiryReshaper() def __init__(self, k_folds: int = 10, prior_type="uniform", pca_n_components=0.9): self.k_folds = k_folds @@ -147,7 +147,7 @@ def predict(self, data: np.array, inquiry: List[str], symbol_set: List[str]) -> likelihood_ratios[symbol_set.index(inquiry[idx])] *= subset_likelihood_ratios[idx] return likelihood_ratios - def predict_proba(self, data: np.array) -> np.array: + def predict_proba(self, data: np.ndarray) -> np.ndarray: """Converts log likelihoods from model into class probabilities. Returns: diff --git a/bcipy/signal/process/filter.py b/bcipy/signal/process/filter.py index 49643bf05..daea1c95d 100644 --- a/bcipy/signal/process/filter.py +++ b/bcipy/signal/process/filter.py @@ -1,4 +1,4 @@ -from typing import Optional, Tuple +from typing import Tuple import numpy as np from scipy.signal import butter, filtfilt, iirnotch, sosfiltfilt @@ -11,7 +11,7 @@ def __init__(self, sample_rate_hz, remove_freq_hz=60.0, quality_factor=30): remove_freq_hz = remove_freq_hz / (sample_rate_hz / 2) self.b, self.a = iirnotch(remove_freq_hz, quality_factor) - def __call__(self, data: np.ndarray, fs: Optional[int] = None) -> Tuple[np.ndarray, int]: + def __call__(self, data: np.ndarray, fs: int) -> Tuple[np.ndarray, int]: return filtfilt(self.b, self.a, data), fs @@ -23,11 +23,11 @@ def __init__(self, lo, hi, sample_rate_hz, order=5): lo, hi = lo / nyq, hi / nyq self.sos = butter(order, [lo, hi], analog=False, btype="band", output="sos") - def __call__(self, data: np.ndarray, fs: Optional[int] = None) -> Tuple[np.ndarray, int]: + def __call__(self, data: np.ndarray, fs: int) -> Tuple[np.ndarray, int]: return sosfiltfilt(self.sos, data), fs -def filter_inquiries(inquiries, transform, sample_rate) -> Tuple[np.ndarray, float]: +def filter_inquiries(inquiries: np.ndarray, transform, sample_rate: int) -> Tuple[np.ndarray, int]: """Filter Inquiries. The shape of data after reshaping into inquiries requires a bit of pre-processing to apply the diff --git a/bcipy/signal/process/transform.py b/bcipy/signal/process/transform.py index 679832fdb..486861ecc 100644 --- a/bcipy/signal/process/transform.py +++ b/bcipy/signal/process/transform.py @@ -1,4 +1,4 @@ -from typing import NamedTuple, Optional, Tuple +from typing import NamedTuple, Tuple import numpy as np @@ -11,7 +11,7 @@ class Composition: def __init__(self, *transforms): self.transforms = transforms - def __call__(self, data: np.ndarray, fs: Optional[int] = None) -> Tuple[np.ndarray, int]: + def __call__(self, data: np.ndarray, fs: int) -> Tuple[np.ndarray, int]: for transform in self.transforms: data, fs = transform(data, fs) return data, fs @@ -20,14 +20,11 @@ def __call__(self, data: np.ndarray, fs: Optional[int] = None) -> Tuple[np.ndarr class Downsample: """Downsampling by an integer factor""" - def __init__(self, factor: int = 2): + def __init__(self, factor: int = 2, 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create a flowable for each figure + flowables = [self.convert_figure_to_image(fig) for fig in self.figures] + return flowables + + def convert_figure_to_image(self, fig: Figure) -> Image: + """Convert Figure to Image. + + Converts a matplotlib figure to a reportlab Image. + retrieved from: https://nicd.org.uk/knowledge-hub/creating-pdf-reports-with-reportlab-and-pandas + """ + buf = io.BytesIO() + fig.savefig(buf, format='png', dpi=300) + buf.seek(0) + x, y = fig.get_size_inches() + return Image(buf, x * inch, y * inch) + + def _create_header(self) -> Paragraph: + """Create Header. + + Creates a header for the Signal Report section. + """ + header = Paragraph('Signal Report', self.style['Heading3']) + return header + + +class SessionReportSection(ReportSection): + """Session Report Section. + + A class to handle the creation of a Session Report section in a BciPy Report using a summary dictionary. + """ + + def __init__(self, summary: Optional[dict] = None) -> None: + self.summary = summary + self.style = getSampleStyleSheet() + self.summary_table = None + + def compile(self) -> Flowable: + """Compile. + + Compiles the Session Report sections into a flowable that can be used to generate a Report. + """ + summary_table = self._create_summary_flowable() + self.summary_table = summary_table + return summary_table + + def _create_summary_flowable(self) -> Flowable: + """Create Summary Flowable. + + Creates a flowable table with the summary dictionary. + """ + if self.summary: + # split the summary keys and values into a list + values = list(self.summary.values()) + keys = sorted(self.summary.keys()) + # sort the keys by alphabetical order and get the values in the same order + values = [self.summary[key] for key in keys] + keys = [str(key).replace('_', ' ').capitalize() for key in keys] + # create a seperate table with the keys and values + summary_list = self._create_summary_text(keys, values) + return KeepTogether(summary_list) + + def _create_summary_text(self, keys: list, values: list) -> List[Paragraph]: + """Create Summary Text. + + Creates a list of paragraphs with the keys and values from the provided summary. + """ + # create a table with the keys and values, adding a header + table = [self._create_header()] + for key, value in zip(keys, values): + text = Paragraph(f'{key}: {value}', self.style['BodyText']) + table.append(text) + return table + + def _create_header(self) -> Paragraph: + """Create Header. + + Creates a header for the Session Report section. + """ + header = Paragraph('Session Summary', self.style['Heading3']) + return header + + +class Report: + """Report. + + A class to handle compiling and saving a BciPy Report after at least one session. + """ + + DEFAULT_NAME: str = 'BciPyReport.pdf' + + def __init__(self, + save_path: str, + name: Optional[str] = None, + sections: Optional[List[ReportSection]] = None, + autocompile: bool = False): + if sections: + assert isinstance(sections, list), "Sections should be a list." + assert all(isinstance(section, ReportSection) + for section in sections), "All sections should be of type ReportSection." + self.sections = sections or [] + self.elements: List[Flowable] = [] + if not name: + name = self.DEFAULT_NAME + assert name.endswith('.pdf'), "The report name should end with .pdf" + + self.name = name + self.path = f'{save_path}/{name}' + self.document = SimpleDocTemplate(self.path, pagesize=letter) + + self.styles = getSampleStyleSheet() + self.header: Optional[Flowable] = None + + if sections is not None and autocompile: + self.compile() + + def add(self, section: ReportSection) -> None: + """Add. + + Adds a ReportSection to the Report. + """ + self.sections.append(section) + + def compile(self) -> None: + """Compile. + + Compiles the Report by adding the header and all sections to the elements list. + """ + if self.header is None: + self._construct_report_header() + header_group = KeepTogether(self.header) + self.elements.append(header_group) + for section in self.sections: + self.elements.append(section.compile()) + + def save(self) -> None: + """Save. + + Exports the Report to a PDF file. + """ + self.document.build(self.elements) + + def _construct_report_header(self) -> None: + """Construct Report Header. + + Constructs the header for the Report. This should be called before adding any other elements. + The header should consist of the CAMBI logo and a report title. + """ + assert len(self.elements) < 1, "The report header should be constructed before other elements" + report_title = Paragraph('BciPy Report', self.styles['Title']) + logo = Image(BCIPY_FULL_LOGO_PATH, hAlign='LEFT', width=170, height=50) + report_title.hAlign = 'CENTER' + report_title.height = 100 + header = [logo, report_title] + self.header = header + + +if __name__ == '__main__': + # use the demo_visualization.py to generate figure handles + # sr = SignalReportSection(figure_handles) + report = Report('.') + session = {'session': 1, 'date': '2021-10-01'} + session_text = SessionReportSection(session) + report.add(session_text) + # report.add(sr) + report.compile() + report.save() diff --git a/bcipy/helpers/tests/test_report.py b/bcipy/helpers/tests/test_report.py new file mode 100644 index 000000000..7df690816 --- /dev/null +++ b/bcipy/helpers/tests/test_report.py @@ -0,0 +1,175 @@ +import os +import unittest +from unittest.mock import patch +import tempfile +import shutil + +import matplotlib.pyplot as plt +import numpy as np +from reportlab.platypus import Paragraph, Image +from reportlab.platypus import Flowable, KeepTogether + +from bcipy.helpers.report import Report, SessionReportSection, ReportSection, SignalReportSection + + +class TestReport(unittest.TestCase): + + def setUp(self): + self.temp_dir = tempfile.mkdtemp() + + def tearDown(self): + shutil.rmtree(self.temp_dir) + + def test_init_name(self): + name = 'report_name.pdf' + report = Report(self.temp_dir, name=name) + self.assertEqual(report.name, name) + + def test_init_no_name_default(self): + report = Report(self.temp_dir) + self.assertEqual(report.name, Report.DEFAULT_NAME) + + def test_init_sections(self): + report_section = SessionReportSection() + section = [report_section] + report = Report(self.temp_dir, sections=section) + self.assertEqual(report.sections, section) + + def test_init_no_sections(self): + report = Report(self.temp_dir) + self.assertEqual(report.sections, []) + + def test_init_sections_not_list(self): + with self.assertRaises(AssertionError): + Report(self.temp_dir, sections='section') + + def test_init_sections_not_report_section(self): + with self.assertRaises(AssertionError): + Report(self.temp_dir, sections=['section']) + + def test_add_section(self): + report = Report(self.temp_dir) + summary = { + 'session': 'session_name', + 'date': '11/11/1111', + 'duration': 2, + 'participant': 'T01', + } + report_section = SessionReportSection(summary=summary) + report.add(report_section) + self.assertEqual(report.sections, [report_section]) + another_report_section = SessionReportSection(summary=summary) + report.add(another_report_section) + self.assertEqual(report.sections, [report_section, another_report_section]) + + def test_save(self): + report = Report(self.temp_dir) + report_section = SessionReportSection() + report.add(report_section) + report.save() + self.assertTrue(os.path.exists(os.path.join(self.temp_dir, report.name))) + + def test_save_no_sections(self): + report = Report(self.temp_dir) + report.save() + self.assertTrue(os.path.exists(os.path.join(self.temp_dir, report.name))) + + def test_complile_adds_section_and_header(self): + report = Report(self.temp_dir) + summary = { + 'session': 'session_name', + 'date': '11/11/1111', + 'duration': 2, + 'participant': 'T01', + } + report_section = SessionReportSection(summary=summary) + report.add(report_section) + report.compile() + self.assertEqual(len(report.elements), 2) + + def test_create_header_is_called_once_compile(self): + with patch('bcipy.helpers.report.Report._construct_report_header') as mock_construct_header: + report = Report(self.temp_dir) + summary = { + 'session': 'session_name', + 'date': '11/11/1111', + 'duration': 2, + 'participant': 'T01', + } + report_section = SessionReportSection(summary=summary) + report.add(report_section) + report.compile() + mock_construct_header.assert_called_once() + + +class TestSessionReportSection(unittest.TestCase): + + def setUp(self) -> None: + self.session_data = { + 'session': 'session_name', + 'date': '11/11/1111', + 'duration': 2, + 'participant': 'T01', + } + + def test_init(self): + report_section = SessionReportSection() + self.assertIsInstance(report_section, ReportSection) + self.assertIsNotNone(report_section.style) + + def test_create_summary_text(self): + report_section = SessionReportSection(summary=self.session_data) + + table = report_section._create_summary_flowable() + self.assertIsInstance(table, Flowable) + + def test_create_header(self): + report_section = SessionReportSection() + header = report_section._create_header() + self.assertIsInstance(header, Paragraph) + + def test_compile(self): + report_section = SessionReportSection(self.session_data) + compiled = report_section.compile() + self.assertIsInstance(compiled, KeepTogether) + + +class TestSignalReportSectionSection(unittest.TestCase): + + def setUp(self) -> None: + # create matplotlib figure + self.fig = plt.figure() + self.ax = self.fig.add_subplot(111) + self.ax.plot(np.random.rand(10)) + self.figures = [self.fig] + + def test_init(self): + report_section = SignalReportSection(self.figures) + self.assertIsInstance(report_section, ReportSection) + self.assertIsNotNone(report_section.style) + self.assertEqual(report_section.figures, self.figures) + + def test_create_header(self): + report_section = SignalReportSection(self.figures) + header = report_section._create_header() + self.assertIsInstance(header, Paragraph) + + def test_create_epochs_section(self): + report_section = SignalReportSection(self.figures) + epochs = report_section._create_epochs_section() + self.assertIsInstance(epochs, list) + self.assertIsInstance(epochs[0], Image) + + def test_convert_figure_to_image(self): + report_section = 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zP+PBIB682c%sjUJoQkapK3RPo0dKg(;Hcz{ZAtYXS&i04q9`v}|5u`|+w<l6L}c><%*};qqnE!G6no1q2vD zLY5+|0dEK0pfPjG3AZS Date: Tue, 4 Jun 2024 11:23:04 -0700 Subject: [PATCH 249/330] Added a base calibration class for generically representing a calibration run loop --- bcipy/helpers/stimuli.py | 13 ++ bcipy/task/base_calibration.py | 298 +++++++++++++++++++++++++++++++++ 2 files changed, 311 insertions(+) create mode 100644 bcipy/task/base_calibration.py diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 2106247b1..b33b928fb 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -89,6 +89,19 @@ class InquirySchedule(NamedTuple): durations: Union[List[List[float]], List[float]] colors: Union[List[List[str]], List[str]] + @property + def count(self) -> int: + """Number of stimuli""" + return len(self.stimuli) + + def __iter__(self): + count = self.count + index = 0 + while index < count: + yield (self.stimuli[index], self.durations[index], + self.colors[index]) + index += 1 + class Reshaper(ABC): diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py new file mode 100644 index 000000000..9c21c212f --- /dev/null +++ b/bcipy/task/base_calibration.py @@ -0,0 +1,298 @@ +"""Base calibration task.""" + +from typing import Iterator, List, NamedTuple, Optional, Tuple + +from psychopy import core, visual + +from bcipy.acquisition import ClientManager +from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE +from bcipy.display import InformationProperties, StimuliProperties +from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.matrix.display import MatrixDisplay +from bcipy.helpers.clock import Clock +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, StimuliOrder, + TargetPositions, + generate_calibration_inquiries) +from bcipy.helpers.symbols import alphabet +from bcipy.helpers.task import (get_user_input, pause_calibration, + trial_complete_message) +from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, + TriggerType, convert_timing_triggers, + offset_label) +from bcipy.task import Task + + +class Inquiry(NamedTuple): + """Represents a single Inquiry""" + # TODO: types should also work for VEP + stimuli: List[str] + durations: List[float] + colors: List[str] + + +class BaseCalibrationTask(Task): + """Base Calibration Task. + + Calibration task performs a stimulus inquiry to elicit a response. Subclasses + can define a Display for specializing the nature of the stimulus + (RSVP, Matrix, etc). + + PARAMETERS: + ---------- + win (PsychoPy Display) + daq (Data Acquisition Client) + parameters (dict) + file_save (str) + """ + + def __init__(self, win: visual.Window, daq: ClientManager, + parameters: Parameters, file_save: str) -> None: + super().__init__() + self.window = win + + self.frame_rate = self.window.getActualFrameRate() + self.parameters = parameters + self.daq = daq + self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) + self.experiment_clock = Clock() + self.symbol_set = alphabet(parameters) + + self.file_save = file_save + self.trigger_handler = TriggerHandler(self.file_save, TRIGGER_FILENAME, + FlushFrequency.EVERY) + + self.wait_screen_message = WAIT_SCREEN_MESSAGE + self.wait_screen_message_color = parameters['stim_color'] + + self.inquiry_generator = self.init_inquiry_generator() + self.display = self.init_display() + + @property + def enable_breaks(self) -> bool: + """Whether to allow breaks""" + return self.parameters['enable_breaks'] + + def wait(self, seconds: Optional[float] = None) -> None: + """Pause for a time. + + Parameters + ---------- + - seconds : duration of time to wait; if missing, defaults to the + value of the parameter `'task_buffer_length'` + """ + seconds = seconds or self.parameters['task_buffer_length'] + core.wait(seconds) + + def init_display(self) -> MatrixDisplay: + """Initialize the display""" + return init_calibration_display_task(self.parameters, self.window, + self.experiment_clock, + self.symbol_set) + + def init_inquiry_generator(self) -> Iterator[Inquiry]: + """Initializes a generator that returns inquiries to be presented.""" + parameters = self.parameters + schedule = generate_calibration_inquiries( + self.symbol_set, + inquiry_count=parameters['stim_number'], + stim_per_inquiry=parameters['stim_length'], + stim_order=StimuliOrder(parameters['stim_order']), + jitter=parameters['stim_jitter'], + target_positions=TargetPositions(parameters['target_positions']), + percentage_without_target=parameters['nontarget_inquiries'], + timing=[ + parameters['time_prompt'], parameters['time_fixation'], + parameters['time_flash'] + ], + color=[ + parameters['target_color'], parameters['fixation_color'], + parameters['stim_color'] + ]) + return (Inquiry(*inq) for inq in schedule) + + def trigger_type(self, symbol: str, target: str, + index: int) -> TriggerType: + """Trigger Type. + + This method is passed to convert_timing_triggers to properly assign TriggerTypes + to the timing of stimuli presented. + """ + if index == 0: + return TriggerType.PROMPT + if symbol == DEFAULT_TEXT_FIXATION: + return TriggerType.FIXATION + if target == symbol: + return TriggerType.TARGET + return TriggerType.NONTARGET + + def present_inquiry(self, index: int, + inquiry: Inquiry) -> List[Tuple[str, float]]: + """Present the given inquiry and return the trigger timing info. + + Parameters + ---------- + - index : current index + - inquiry : next sequence of stimuli to present. + + Returns + ------- + List of stim_times (tuples representing the stimulus and time that + it was presented relative to the experiment clock) + """ + self.display.update_task_bar(str(index + 1)) + self.display.draw_static() + self.window.flip() + + self.display.schedule_to(inquiry.stimuli, inquiry.durations, + inquiry.colors) + self.wait() + timing = self.display.do_inquiry() + return timing + + def user_wants_to_continue(self, first_inquiry: bool = False) -> bool: + """Check if user wants to continue or terminate. + + Returns + ------- + - `True` to continue + - `False` to finish the task. + """ + should_continue = get_user_input(self.display, + self.wait_screen_message, + self.wait_screen_message_color, + first_run=first_inquiry) + if not should_continue: + self.logger.info('User wants to exit.') + return should_continue + + def execute(self) -> str: + """Task run loop.""" + self.logger.info(f'Starting {self.name()}!') + self.wait() + + inq_index = 0 + while self.user_wants_to_continue(inq_index == 0): + try: + inquiry = next(self.inquiry_generator) + except StopIteration: + break + if self.enable_breaks: + # Take a break at the defined interval + pause_calibration(self.window, self.display, inq_index, + self.parameters) + + timing = self.present_inquiry(inq_index, inquiry) + + # Write triggers for the inquiry + self.write_trigger_data(timing, first_run=inq_index == 0) + + # Wait for a time + self.wait() + inq_index += 1 + + self.exit_display() + self.cleanup() + + self.write_offset_trigger() + # TODO: write session data? + # self.write_stimuli_positions() + + return self.file_save + + def exit_display(self) -> None: + """Close the UI and cleanup.""" + # Say Goodbye! + self.display.info_text = trial_complete_message( + self.window, self.parameters) + self.display.draw_static() + self.window.flip() + + # Allow for some additional data to be collected for later processing + self.wait() + + def cleanup(self) -> None: + """Any cleanup code to run after the last inquiry is complete.""" + + def write_trigger_data(self, timing: List[Tuple[str, float]], + first_run) -> None: + """Write Trigger Data. + + Using the timing provided from the display and calibration information from the data acquisition + client, write trigger data in the correct format. + + *Note on offsets*: we write the full offset value which can be used to transform all stimuli to the time since + session start (t = 0) for all values (as opposed to most system clocks which start much higher). + We do not write the calibration trigger used to generate this offset from the display. + See MatrixDisplay._trigger_pulse() for more information. + """ + if first_run: + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + label = offset_label(content_type.name) + time = client.offset(self.display.first_stim_time + ) - self.display.first_stim_time + triggers.append(Trigger(label, TriggerType.OFFSET, time)) + self.trigger_handler.add_triggers(triggers) + + # make sure triggers are written for the inquiry + self.trigger_handler.add_triggers( + convert_timing_triggers(timing, timing[0][0], self.trigger_type)) + + def write_offset_trigger(self) -> None: + """Append an offset value to the end of the trigger file. + """ + # To help support future refactoring or use of lsl timestamps only + # we write only the sample offset here. + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + label = offset_label(content_type.name, prefix='daq_sample_offset') + time = client.offset(self.display.first_stim_time) + triggers.append(Trigger(label, TriggerType.SYSTEM, time)) + + self.trigger_handler.add_triggers(triggers) + self.trigger_handler.close() + + def name(self) -> str: + return 'Matrix Calibration Task' + + +def init_calibration_display_task( + parameters: Parameters, window: visual.Window, experiment_clock: Clock, + symbol_set: core.StaticPeriod) -> MatrixDisplay: + info = InformationProperties( + info_color=[parameters['info_color']], + info_pos=[(parameters['info_pos_x'], parameters['info_pos_y'])], + info_height=[parameters['info_height']], + info_font=[parameters['font']], + info_text=[parameters['info_text']], + ) + stimuli = StimuliProperties(stim_font=parameters['font'], + stim_pos=(-0.6, 0.4), + stim_height=0.1, + stim_inquiry=[''] * parameters['stim_length'], + stim_colors=[parameters['stim_color']] * + parameters['stim_length'], + stim_timing=[10] * parameters['stim_length'], + is_txt_stim=parameters['is_txt_stim'], + prompt_time=parameters["time_prompt"]) + + task_bar = CalibrationTaskBar(window, + inquiry_count=parameters['stim_number'], + current_index=0, + colors=[parameters['task_color']], + font=parameters['font'], + height=parameters['task_height'], + padding=parameters['task_padding']) + + return MatrixDisplay(window, + experiment_clock, + stimuli, + task_bar, + info, + rows=parameters['matrix_rows'], + columns=parameters['matrix_columns'], + width_pct=parameters['matrix_width'], + height_pct=1 - (2 * task_bar.height_pct), + trigger_type=parameters['trigger_type'], + symbol_set=symbol_set) From 6b0edb7ade4af5089ed29edd2d4f92257f1ca020 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 4 Jun 2024 14:20:57 -0700 Subject: [PATCH 250/330] Added session data to base calibration task --- bcipy/task/base_calibration.py | 120 ++++++++++++++++++--------------- 1 file changed, 66 insertions(+), 54 deletions(-) diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index 9c21c212f..281b7181b 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -4,13 +4,14 @@ from psychopy import core, visual +import bcipy.task.data as session_data from bcipy.acquisition import ClientManager -from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE -from bcipy.display import InformationProperties, StimuliProperties -from bcipy.display.components.task_bar import CalibrationTaskBar -from bcipy.display.paradigm.matrix.display import MatrixDisplay +from bcipy.config import (SESSION_DATA_FILENAME, TRIGGER_FILENAME, + WAIT_SCREEN_MESSAGE) +from bcipy.display import Display from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters +from bcipy.helpers.save import _save_session_related_data from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, StimuliOrder, TargetPositions, generate_calibration_inquiries) @@ -30,6 +31,17 @@ class Inquiry(NamedTuple): durations: List[float] colors: List[str] + @property + def labels(self) -> List[str]: + """labels for each stimuli""" + [target, _fixation, *symbols] = self.stimuli + return ['target' if sym == target else 'nontarget' for sym in symbols] + + @property + def target(self) -> str: + """target symbol""" + return self.stimuli[0] + class BaseCalibrationTask(Task): """Base Calibration Task. @@ -46,6 +58,8 @@ class BaseCalibrationTask(Task): file_save (str) """ + MODE = 'Undefined' + def __init__(self, win: visual.Window, daq: ClientManager, parameters: Parameters, file_save: str) -> None: super().__init__() @@ -56,6 +70,7 @@ def __init__(self, win: visual.Window, daq: ClientManager, self.daq = daq self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) self.experiment_clock = Clock() + self.start_time = self.experiment_clock.getTime() self.symbol_set = alphabet(parameters) self.file_save = file_save @@ -68,11 +83,18 @@ def __init__(self, win: visual.Window, daq: ClientManager, self.inquiry_generator = self.init_inquiry_generator() self.display = self.init_display() + self.session = self.init_session() + self.write_session_data() + @property def enable_breaks(self) -> bool: """Whether to allow breaks""" return self.parameters['enable_breaks'] + def name(self) -> str: + """Task name""" + return 'Calibration Task' + def wait(self, seconds: Optional[float] = None) -> None: """Pause for a time. @@ -84,11 +106,9 @@ def wait(self, seconds: Optional[float] = None) -> None: seconds = seconds or self.parameters['task_buffer_length'] core.wait(seconds) - def init_display(self) -> MatrixDisplay: + def init_display(self) -> Display: """Initialize the display""" - return init_calibration_display_task(self.parameters, self.window, - self.experiment_clock, - self.symbol_set) + raise NotImplementedError def init_inquiry_generator(self) -> Iterator[Inquiry]: """Initializes a generator that returns inquiries to be presented.""" @@ -111,6 +131,18 @@ def init_inquiry_generator(self) -> Iterator[Inquiry]: ]) return (Inquiry(*inq) for inq in schedule) + def init_session(self) -> session_data.Session: + """Initialize the session data.""" + return session_data.Session(save_location=self.file_save, + task='Calibration', + mode=self.MODE, + symbol_set=self.symbol_set, + task_data=self.session_task_data()) + + def session_task_data(self): + """"Task-specific session data""" + return None + def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: """Trigger Type. @@ -186,6 +218,7 @@ def execute(self) -> str: # Write triggers for the inquiry self.write_trigger_data(timing, first_run=inq_index == 0) + self.add_session_data(inquiry) # Wait for a time self.wait() @@ -193,10 +226,7 @@ def execute(self) -> str: self.exit_display() self.cleanup() - self.write_offset_trigger() - # TODO: write session data? - # self.write_stimuli_positions() return self.file_save @@ -253,46 +283,28 @@ def write_offset_trigger(self) -> None: self.trigger_handler.add_triggers(triggers) self.trigger_handler.close() - def name(self) -> str: - return 'Matrix Calibration Task' - - -def init_calibration_display_task( - parameters: Parameters, window: visual.Window, experiment_clock: Clock, - symbol_set: core.StaticPeriod) -> MatrixDisplay: - info = InformationProperties( - info_color=[parameters['info_color']], - info_pos=[(parameters['info_pos_x'], parameters['info_pos_y'])], - info_height=[parameters['info_height']], - info_font=[parameters['font']], - info_text=[parameters['info_text']], - ) - stimuli = StimuliProperties(stim_font=parameters['font'], - stim_pos=(-0.6, 0.4), - stim_height=0.1, - stim_inquiry=[''] * parameters['stim_length'], - stim_colors=[parameters['stim_color']] * - parameters['stim_length'], - stim_timing=[10] * parameters['stim_length'], - is_txt_stim=parameters['is_txt_stim'], - prompt_time=parameters["time_prompt"]) - - task_bar = CalibrationTaskBar(window, - inquiry_count=parameters['stim_number'], - current_index=0, - colors=[parameters['task_color']], - font=parameters['font'], - height=parameters['task_height'], - padding=parameters['task_padding']) - - return MatrixDisplay(window, - experiment_clock, - stimuli, - task_bar, - info, - rows=parameters['matrix_rows'], - columns=parameters['matrix_columns'], - width_pct=parameters['matrix_width'], - height_pct=1 - (2 * task_bar.height_pct), - trigger_type=parameters['trigger_type'], - symbol_set=symbol_set) + def write_session_data(self) -> None: + """Save session data to disk.""" + if self.session: + session_file = _save_session_related_data( + f"{self.file_save}/{SESSION_DATA_FILENAME}", + self.session.as_dict()) + session_file.close() + + def add_session_data(self, inquiry: Inquiry) -> None: + """Adds the latest inquiry to the session data.""" + data = session_data.Inquiry( + stimuli=inquiry, + timing=inquiry.durations, + triggers=[], + target_info=inquiry.labels, + target_letter=inquiry.target, + task_data=self.session_inquiry_data(inquiry)) + self.session.add_sequence(data) + self.session.total_time_spent = self.experiment_clock.getTime( + ) - self.start_time + self.write_session_data() + + def session_inquiry_data(self, inquiry: Inquiry) -> Optional[dict]: + """Defines task-specific session data for each inquiry.""" + return None From 7dd459f1df9d7dcae680457a14d70a806eb40549 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Tue, 4 Jun 2024 16:28:54 -0700 Subject: [PATCH 251/330] adds test to see if stimuli are randomized --- bcipy/helpers/tests/test_stimuli.py | 19 ++++++++++++++++++- 1 file changed, 18 insertions(+), 1 deletion(-) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 4c017e828..829c24499 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -762,7 +762,24 @@ def test_best_case_inquiry_gen_with_inq_constants(self): self.assertEqual([1] + ([0.2] * n), times[0]) self.assertEqual(['red'] + (['white'] * n), colors[0]) - + + def test_best_case_inq_gen_is_random(self): + """Test that best_case_inq_gen produces random results. While this test can technically fail, + the odds are incredibly low, around 1 in 1 million""" + samps = [] + for i in range(25): + alp = ['a', 'b', 'c', 'd', 'e', 'f', 'g', '<'] + samples, _, _ = best_case_rsvp_inq_gen( + alp=alp, + session_stimuli=[0.1, 0.1, 0.1, 0.2, 0.2, 0.1, 0.2, 0.0], + stim_number=1, + stim_length=8, + is_txt=True, + inq_constants=['<']) + samps.append(tuple(samples[0])) + set(samps) + self.assertTrue(len(set(samps)) > 1, 'Should produce random results') + class TestJitteredTiming(unittest.TestCase): From db3a8fa2a4d6a501ef59006272919b9d7ea4ac03 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Tue, 4 Jun 2024 16:33:15 -0700 Subject: [PATCH 252/330] Update changelog --- CHANGELOG.md | 1 + 1 file changed, 1 insertion(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 41c9f1e50..2ddfade1c 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -20,6 +20,7 @@ Our last release candidate before the official 2.0 release! - Change default log level to INFO to prevent too many messages in the experiment logs #288 - Upgrade requirements for m1/2 chips #299/#300 - Fix GitHub actions build issues with macOS + - Fix occasionally failing test in `test_stimuli` # 2.0.0-rc.3 From 2952f6c280b309ab0cb1a098a8375f4182ee2ed8 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Tue, 4 Jun 2024 16:34:37 -0700 Subject: [PATCH 253/330] Lints `test_stimuli` --- bcipy/helpers/tests/test_stimuli.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 829c24499..c48eabfa9 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -762,9 +762,9 @@ def test_best_case_inquiry_gen_with_inq_constants(self): self.assertEqual([1] + ([0.2] * n), times[0]) self.assertEqual(['red'] + (['white'] * n), colors[0]) - + def test_best_case_inq_gen_is_random(self): - """Test that best_case_inq_gen produces random results. While this test can technically fail, + """Test that best_case_inq_gen produces random results. While this test can technically fail, the odds are incredibly low, around 1 in 1 million""" samps = [] for i in range(25): @@ -779,7 +779,7 @@ def test_best_case_inq_gen_is_random(self): samps.append(tuple(samples[0])) set(samps) self.assertTrue(len(set(samps)) > 1, 'Should produce random results') - + class TestJitteredTiming(unittest.TestCase): From cc6d830b6f038c8a2bca849c59314fd8e5492c86 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Wed, 5 Jun 2024 10:36:06 -0700 Subject: [PATCH 254/330] simplifies sample set insertion --- bcipy/helpers/tests/test_stimuli.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index c48eabfa9..201951410 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -766,7 +766,7 @@ def test_best_case_inquiry_gen_with_inq_constants(self): def test_best_case_inq_gen_is_random(self): """Test that best_case_inq_gen produces random results. While this test can technically fail, the odds are incredibly low, around 1 in 1 million""" - samps = [] + samps = set() for i in range(25): alp = ['a', 'b', 'c', 'd', 'e', 'f', 'g', '<'] samples, _, _ = best_case_rsvp_inq_gen( @@ -776,9 +776,8 @@ def test_best_case_inq_gen_is_random(self): stim_length=8, is_txt=True, inq_constants=['<']) - samps.append(tuple(samples[0])) - set(samps) - self.assertTrue(len(set(samps)) > 1, 'Should produce random results') + samps.add(tuple(samples[0])) + self.assertTrue(len(samps) > 1, '`best_case_rsvp_inq_gen` Should produce random results') class TestJitteredTiming(unittest.TestCase): From 4a809944a64e124bad2fbf16e669589704a9d605 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Wed, 5 Jun 2024 10:37:00 -0700 Subject: [PATCH 255/330] Adds PR reference to changelog --- CHANGELOG.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 2ddfade1c..171a673de 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -20,7 +20,7 @@ Our last release candidate before the official 2.0 release! - Change default log level to INFO to prevent too many messages in the experiment logs #288 - Upgrade requirements for m1/2 chips #299/#300 - Fix GitHub actions build issues with macOS - - Fix occasionally failing test in `test_stimuli` + - Fix occasionally failing test in `test_stimuli` #326 # 2.0.0-rc.3 From 69dfe484970d58551647f76df5eb31f97604f3c9 Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Sun, 9 Jun 2024 12:08:03 -0700 Subject: [PATCH 256/330] Offset analysis updates (#327) --- CHANGELOG.md | 2 + Makefile | 6 + README.md | 32 ++ bcipy/config.py | 2 + bcipy/helpers/offset.py | 360 ++++++++++++++++++ .../time_test_data/raw_data.csv.zip | Bin 0 -> 10824794 bytes .../time_test_data/triggers.txt.zip | Bin 0 -> 9085 bytes bcipy/helpers/tests/test_offset.py | 166 ++++++++ scripts/python/offset_analysis.py | 263 ------------- scripts/python/plot_eye_data.py | 37 -- scripts/python/plot_inquiry_data.py | 91 ----- 11 files changed, 568 insertions(+), 391 deletions(-) create mode 100644 bcipy/helpers/offset.py create mode 100644 bcipy/helpers/tests/resources/mock_offset/time_test_data/raw_data.csv.zip create mode 100644 bcipy/helpers/tests/resources/mock_offset/time_test_data/triggers.txt.zip create mode 100644 bcipy/helpers/tests/test_offset.py delete mode 100644 scripts/python/offset_analysis.py delete mode 100644 scripts/python/plot_eye_data.py delete mode 100644 scripts/python/plot_inquiry_data.py diff --git a/CHANGELOG.md b/CHANGELOG.md index 1b2a8ba6c..56e81e89b 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -15,6 +15,8 @@ Our last release candidate before the official 2.0 release! - Updated trial_length to trial_window to allow for greater control of window used after stimulus presentations #291 - Report - Functionality to generate a report in the form of a PDF #325 +- Offset Support + - Add support for determining offsets between timing verification Tasks (Ex. RSVPTimingVerificationCalibration) and RawData with a photodiode trigger column. This is useful for setting up new systems and preventing errors before an experiment begins. #TODO - Parameters - Add a Range type parameter #285 - Housekeeping diff --git a/Makefile b/Makefile index 2a3e0a8ae..dcdc1e0a9 100644 --- a/Makefile +++ b/Makefile @@ -49,3 +49,9 @@ bci-gui: viewer: python bcipy/gui/viewer/data_viewer.py --file $(filepath) + +offset: + python bcipy/helpers/offset.py -p + +offset-recommend: + python bcipy/helpers/offset.py -r -p diff --git a/README.md b/README.md index 7e1d2cca5..9c19fd7d4 100644 --- a/README.md +++ b/README.md @@ -158,6 +158,38 @@ For example, you may run the main BciPy demo by: This demo will load in parameters and execute a demo task defined in the file. There are demo files for all modules listed above except helpers and utils. Run them as a python script! +## Offset Determination and Correction +-------------------------------------- + +Static offset determination and correction are critical steps before starting an experiment. BciPy uses LSL to acquire EEG data and Psychopy to present stimuli. + +[LSL synchronization documentation](https://labstreaminglayer.readthedocs.io/info/time_synchronization.html) +[PsychoPy timing documentation](https://www.psychopy.org/general/timing/index.html) + +A static offset is the regular time difference between our signals and stimuli. This offset is determined through testing via a photodiode or other triggering mechanism. The offset correction is done by shifting the EEG signal by the determined offset using the `static_offset` parameter. + +After running a timing verification task (such as, RSVPTimingVerification) with a photodiode attached to the display and connected to a device, the offset can be determined by analyzing the data. Use the `offset` module to recommend an offset correction value and display the results. + +To run the offset determination and print the results, use the following command: + +```bash +python bcipy/helpers/offset.py -r +``` + +After running the above command, the recommended offset correction value will be displayed in the terminal and can be passed to determine system stability and display the results. + +```bash +# Let's say the recommneded offset value is 0.1 +python bcipy/helpers/offset.py --offset "0.1" -p + +``` + +Alternately, if Make is installed, you may run the follow command to run offset determination and display the results: + +```sh +make offset-recommend +``` + ## Testing ---------- diff --git a/bcipy/config.py b/bcipy/config.py index 08cfd66bb..f49c77cc9 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -8,6 +8,8 @@ DEFAULT_ENCODING = 'utf-8' DEFAULT_EVIDENCE_PRECISION = 5 # number of decimal places to round evidence to by default MARKER_STREAM_NAME = 'TRG_device_stream' +DEFAULT_TRIGGER_CHANNEL_NAME = 'TRG' +DIODE_TRIGGER = '\u25A0' # experiment configuration DEFAULT_EXPERIMENT_ID = 'default' diff --git a/bcipy/helpers/offset.py b/bcipy/helpers/offset.py new file mode 100644 index 000000000..c84d34720 --- /dev/null +++ b/bcipy/helpers/offset.py @@ -0,0 +1,360 @@ +from typing import Any, List, Tuple +from textwrap import wrap +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np + +from scipy.stats import normaltest + +from bcipy.helpers.load import load_raw_data, ask_directory, load_json_parameters +from bcipy.helpers.raw_data import RawData +from bcipy.helpers.triggers import trigger_decoder, TriggerType + +from bcipy.config import ( + TRIGGER_FILENAME, + DIODE_TRIGGER, + RAW_DATA_FILENAME, + DEFAULT_TRIGGER_CHANNEL_NAME, + DEFAULT_PARAMETER_FILENAME +) + + +def sample_to_seconds(sample_rate: float, sample: int) -> float: + """Convert the given raw_data sample number to seconds.""" + assert sample > 0, f"Sample # must be greater than 0. Got {sample}" + assert sample_rate > 0, f"Sample rate must be greater than 0. Got {sample_rate}" + return sample / sample_rate + + +def calculate_latency(raw_data: RawData, + diode_channel: str, + triggers: List[Tuple[Any, Any, Any]], + stim_length: int, + plot_title: str = "", + recommend_static: bool = False, + plot: bool = False, + tolerance: float = 0.01, + correct_diode_false_positive: int = 0) -> Tuple[List[float], List[str]]: + """Calculate the latency between the photodiode and the trigger timestamps. + + This method uses collected photodiode information and trigger timestamps from + BciPy Time Test Tasks to determine system offsets that need to be accounted for before usage. + + This can be determined using the recommend_static parameter, which will provide a recommended + static offset based on the median and mean of the differences between the photodiode and trigger timestamps. + + Using a tolerance value, the method reports any differences between the photodiode and trigger + that would be considered excessive for data collection. + + Note: Often photodiode information is collected from a trigger box, and + provided as a channel in the raw_data. This has been tested using + Wearable Sensing's and Brain Vision's trigger boxes with the photodiode + connected. The photodiode channel is expected to be a continuous signal with + values >0 indicating light. + + Plots: + ------ + - Plot triggers and photodiode data to visualize the differences between the + two. The photodiode data is plotted as a continuous line with values >0 + indicating light. The triggers are plotted as vertical lines at the + timestamps provided in the triggers.txt file. + + - LSL timestamp differences are plotted as a scatter plot to visualize any delays from + the acquisition of data. All values should be within the sample rate of the data. + + - Offset differences are plotted as a scatter plot to visualize the differences between the + photodiode and trigger timestamps over the course of the session. This can be used to determine + if there are any patterns of delay or offset that need to be accounted for. + + Parameters: + ----------- + raw_data - complete list of samples read in from the raw_data.csv file. + diode_channel - the channel name for the photodiode in the raw_data. + triggers - list of (trg, trg_type, stamp) values from the triggers.txt + file. Stamps have been converted to the acquisition clock using + the offset recorded in the triggers.txt. + plot_title - title for the plot. + recommend_static - if True, recommend a static offset using the median and mean. + plot - if True, display the plot. + tolerance - the allowable difference between the photodiode and trigger timestamps for reporting. + + Returns: + -------- + diffs - list of differences between the photodiode and trigger timestamps. + errors - list of differences that exceed the tolerance. + """ + # Photodiode column; this is a continuous line with >0 indicating light. + trg_box_channel = raw_data.dataframe[diode_channel] + + # Initialize variables for photodiode data extraction + trg_box_x = [] + trg_box_y = [] + trg_ymax = 1.5 + diode_enc = False + starts = [] + + # Get the photodiode trigger data in the form of a list of timestamps + for i, val in enumerate(trg_box_channel): + timestamp = sample_to_seconds(raw_data.sample_rate, i + 1) + value = int(float(val)) + trg_box_x.append(timestamp) + trg_box_y.append(value) + + if value > 0 and not diode_enc: + diode_enc = True + starts.append(timestamp) + + if value > 0 and diode_enc: + pass + + if value < 1 and diode_enc: + diode_enc = False + + # Plot triggers.txt data if present; vertical line for each value. + if triggers: + trigger_diodes_timestamps = [ + stamp for (_name, _trgtype, stamp) in triggers if _name == DIODE_TRIGGER + ] + + # If the photodiode is falsing detected at the beginning of the session, we remove the first timestamp + if correct_diode_false_positive > 0: + starts = starts[correct_diode_false_positive:] + + # In the case of ending the session before the triggers are finished or the photo diode is detected at the end, + # we balance the timestamps + if (len(starts) != len(trigger_diodes_timestamps)): + if len(starts) > len(trigger_diodes_timestamps): + starts = starts[:len(trigger_diodes_timestamps)] + else: + trigger_diodes_timestamps = trigger_diodes_timestamps[:len(starts)] + + # Check for differences between the photodiode and trigger timestamps. + # Store any differences that exceed the tolerance. + errors = [] + diffs = [] + x = 0 + + for trigger_stamp, diode_stamp in zip(trigger_diodes_timestamps, starts): + diff = trigger_stamp - diode_stamp + + # TODO: RSVP and Matrix Calibration Task: Correct for prompt/fixation causing a false positive + if x > 0: + if abs(diff) > tolerance and not recommend_static: + errors.append( + f'trigger={trigger_stamp} diode={diode_stamp} diff={diff}' + ) + diffs.append(diff) + + # Reset x to 0 if we are at the end of the inquiry. + if x == (stim_length / 2) - 1: + x = 0 + + else: + x += 1 + + if recommend_static: + # test for normality + _, p_value = normaltest(diffs) + + # if it's not normal, take the median + if p_value < 0.05: + print(f'Non-normal distribution of diffs. p-value=[{p_value}] Consider using median for static offset.') + recommended_static = abs(np.median(diffs)) + print( + f'System recommended static offset median=[{recommended_static}]') + recommended_static = abs(np.mean(diffs)) + print(f'System recommended static offset mean=[{recommended_static}]') + + else: + if errors: + num_errors = len(errors) + print( + f'RESULTS: Allowable tolerance between triggers and photodiode exceeded. {errors}' + f'Number of violations: {num_errors}') + else: + print( + f'RESULTS: Triggers and photodiode timestamps within limit of [{tolerance}s]!' + ) + + # display the plot + if plot: + fig = plt.figure() + ax = fig.add_subplot(1, 1, 1) + plt.title("\n".join(wrap(plot_title, 50))) + plt.xlabel('acquisition clock (secs)') + plt.ylabel(f'{diode_channel} (photodiode)') + + if triggers: + plt.vlines(trigger_diodes_timestamps, + ymin=-1.0, + ymax=trg_ymax, + label=f'{TRIGGER_FILENAME} (adjusted)', + linewidth=0.5, + color='cyan') + + ax.plot(trg_box_x, trg_box_y, label=f'{diode_channel} (photodiode triggers)') + + # Add labels for TRGs + first_trg = trigger_diodes_timestamps[0] + + # Set initial zoom to +-5 seconds around the calibration_trigger + if first_trg: + ax.set_xlim(left=first_trg - 5, right=first_trg + 5) + + ax.grid(axis='x', linestyle='--', color="0.5", linewidth=0.4) + plt.legend(loc='lower left', fontsize='small') + plt.show() + + lsl_timestamp_diffs(raw_data, plot=plot) + sample_rate_diffs(raw_data) + + # plot a scatter of the differences + plt.scatter(range(len(diffs)), diffs) + plt.show() + + return diffs, errors + + +def lsl_timestamp_diffs(raw_data: RawData, plot: bool = False) -> List[float]: + """Calculate the differences between the LSL timestamps and plot the differences. + + Parameters: + ----------- + raw_data - BciPy RawData object. + plot - if True, display a plot of the differences between LSL timestamps. + + Returns: + -------- + diffs - list of differences between the LSL timestamps. + """ + # using the lsl timestamps, calculate the difference between each timestamp + lsl_time_stamps = raw_data.dataframe['lsl_timestamp'] + diffs = np.diff(lsl_time_stamps) + + # display the plot if requested. This will show the differences between each timestamp, + # which should be consistent. + if plot: + plt.plot(diffs) + plt.show() + + return diffs.tolist() + + +def sample_rate_diffs(raw_data: RawData) -> Tuple[int, float]: + """Calculate the expected time recorded from the raw_data and LSL timestamps. + + Differences in this time may indicate a problem with sample loss. + + Parameters: + ----------- + raw_data - BciPy RawData object. + + Returns: + -------- + lsl_sample_diff - the difference between the first and last LSL timestamps (seconds). + sample_time - all samples recorded from raw_data (seconds). + """ + # using the lsl timestamps and samples, calculate the expected time recorded. + + # extract the first and last lsl timestamps to get the total time recorded + lsl_time_stamps = raw_data.dataframe['lsl_timestamp'].values + first_sample = lsl_time_stamps[0] + last_sample = lsl_time_stamps[-1] + lsl_sample_diff = last_sample - first_sample + + # get the count of all the samples and calculate the time recorded from the raw_data + sample_time = raw_data.dataframe.shape[0] / raw_data.sample_rate + print(f'LSL Timestamp Sample Count: {lsl_sample_diff} EEG Sample Count: {sample_time}') + return lsl_sample_diff, sample_time + + +def extract_data_latency_calculation( + data_dir: str, + recommend: bool, + static_offset: float) -> Tuple[RawData, List[Tuple[Any, Any, Any]], float]: + """Extract the raw data and triggers from the data directory. + + If recommend is True, a static offset is recommended. Any static offset provided as + an arg will be set to zero to calculate the recommended offset. + + Parameters: + ----------- + data_dir - path to the data directory, containing raw_data.csv and triggers.txt + recommend - whether to recommend a static offset. If True, plots are not displayed. + static_offset - fixed offset applied to triggers for plotting and analysis. + """ + # We set the static offset to zero if we are recommending a new offet value + if recommend: + static_offset = 0.0 + + raw_data = load_raw_data(str(Path(data_dir, f'{RAW_DATA_FILENAME}.csv'))) + trigger_targetness, trigger_timing, trigger_label = trigger_decoder( + trigger_path=str(Path(data_dir, f'{TRIGGER_FILENAME}')), + exclusion=[TriggerType.FIXATION], + remove_pre_fixation=False, + offset=static_offset, + device_type='EEG' + ) + triggers = list(zip(trigger_label, trigger_targetness, trigger_timing)) + return raw_data, triggers, static_offset + + +if __name__ == '__main__': + import argparse + + parser = argparse.ArgumentParser( + description='Graphs trigger data from a bcipy session to visualize system latency.' + 'Recommends a static offset if requested.') + parser.add_argument('-d', + '--data_path', + help='Path to the data directory', + default=None) + parser.add_argument('-p', + '--plot', + help='Flag used for plotting the data. If set, plots are displayed', + default=False, + action='store_true') + parser.add_argument('-r', + '--recommend', + help='Flag used for recommending a static offset. If set, plots are not displayed', + default=False, + action='store_true') + parser.add_argument('-trg', + help='Argument to change the photodiode trigger name. ' + f'Default is {DEFAULT_TRIGGER_CHANNEL_NAME}', + default=DEFAULT_TRIGGER_CHANNEL_NAME, + type=str, + dest='trigger_name') + parser.add_argument('--offset', + help='The static offset applied to triggers for plotting and analysis', + default=0.09) + parser.add_argument('-t', '--tolerance', + help='Allowable tolerance between triggers and photodiode. Deafult 10 ms', + default=0.015) + parser.add_argument('-f', '--false_positive', + help='Allows to correct the false positive of the photodiode at the beginning of the session.', + default=0, + type=int) + + args = parser.parse_args() + data_path = args.data_path + if not data_path: + data_path = ask_directory() + + # grab the stim length from the data directory parameters + stim_length = load_json_parameters(f'{data_path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True)['stim_length'] + + raw_data, triggers, static_offset = extract_data_latency_calculation( + data_path, + bool(args.recommend), + float(args.offset)) + response = calculate_latency( + raw_data, + args.trigger_name, + triggers, + stim_length, + recommend_static=args.recommend, + plot=args.plot, + tolerance=float(args.tolerance), + correct_diode_false_positive=args.false_positive) diff --git a/bcipy/helpers/tests/resources/mock_offset/time_test_data/raw_data.csv.zip 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zZ%cRHXtun?91)FJn;P{p)zB}Ujdl^tz9_@eouxdFDlym+lltLx#BxwZTfW5`OMWt* z@>c3CsAhm`Sr`-=y0wZ9E6NWAvG8tHtuZPTpN96hhVCRs)a5t@b0sf$ilb7DCPXLk zu{=+EB@&81(@BI1F~@%0AWp*$2u(3=qvf-X!o-GT#RJK72v7P@vsPv2)~3GlTpSKp zD7aI9QLzkoqI1kW{K+FZmXKv)WoDhW;VKPptC0d#m(WrbJ@aPrvBgCGg1`{>@-wh) zZO`{U!IV}Z&@XJ1U8%*T-QDn?Ld>DYo5!s*E@R6eZ; zU4f;3ltcN0^zmIb#2Ggr(#)qgxRJRLILSAD318EM~jr@VCXe$S<&zEt52S$e)bsY+F*9 zEC-2lI2z?QFe-G6cH4xj=ngUdGnsR$&OHY0x&wEvD8T2YorlB&6|z$YXKG-n67DwD z%wt6p&O$*{+(OrQu0Uk}tk2TXFCBPPx`^M8%}F?jK7Xv=<8j2k8B6R}%SN zVuNYBmaP7D(&Z)F_i9pQGGT8Wrm&pd=T@!A=M#5vdDHK%#EH4tjtQZv>8w!vRy`6% z4_*{g!jxgzGt6q{J|@LSl4 z+u|6M$?x5*6}vmu2-%j_BCU=h2WkRvCc=Y1N1QIJ&EYkjpxuU80Rs*s42Dg+h{Rs2M%>(- z9Y_ATvWvJmTeR!n|8sKD|2YD?eI=ffazUci&$F1mdK(EeASQA9wY_7_g@f}in*sbE zsSUti6oc_EwP9yxsIF;j@={#P?tcY1-u}M;hvO>-N7q*luYMUmGy6qtmI#c(%VfeA zpkc*5;o&4YW!7dpPmQm1+Fa`XYGk($W>0mId+SKp1NXXXta36AN_e>HqI9X<93 z*MXFX2o!5=4{-oF*y_313gc^TrVf;=%7pvNt9mARZ1iUi9t?GnvjO&5nO-tk78Mj! z6;$!FSSq>#ws)#5CI8Kkn8a4nggfmoS@LgQKm%Mn0RDfHD*siDe@T`9u-52*NB?Wu r{{y%3-y{FmRsU7 None: + self.tmp_dir = Path(tempfile.mkdtemp()) + self.raw_data_path = self.tmp_dir / f'{RAW_DATA_FILENAME}.csv' + self.triggers_path = str(self.tmp_dir / f'{TRIGGER_FILENAME}') + with zipfile.ZipFile(input_folder / 'raw_data.csv.zip', 'r') as zip_ref: + zip_ref.extractall(self.tmp_dir) + with zipfile.ZipFile(input_folder / 'triggers.txt.zip', 'r') as zip_ref: + zip_ref.extractall(self.tmp_dir) + self.raw_data = load_raw_data(self.raw_data_path) + trigger_targetness, trigger_time, trigger_label = trigger_decoder( + self.triggers_path, + remove_pre_fixation=False, + exclusion=[TriggerType.FIXATION], + device_type='EEG') + self.triggers = list(zip(trigger_label, trigger_targetness, trigger_time)) + self.diode_channel = 'TRG' + self.stim_number = 10 + + def tearDown(self) -> None: + shutil.rmtree(self.tmp_dir) + unstub() + return super().tearDown() + + def test_sample_to_seconds(self): + self.assertEqual(sample_to_seconds(100, 1), 0.01) + self.assertEqual(sample_to_seconds(100, 100), 1) + self.assertEqual(sample_to_seconds(200, 100), 0.5) + + def test_sample_to_seconds_throws_error_on_zero_args(self): + with self.assertRaises(AssertionError): + sample_to_seconds(100, 0) + + with self.assertRaises(AssertionError): + sample_to_seconds(0, 100) + + def test_extract_data_latency_calculation(self): + static_offset = 0.0 + recommend = False + resp = extract_data_latency_calculation(self.tmp_dir, recommend, static_offset) + self.assertIsInstance(resp[0], RawData) + self.assertEqual(resp[1], self.triggers) + self.assertEqual(resp[2], static_offset) + + def test_extract_data_latency_calculation_resets_static_offset_on_recommend(self): + static_offset = 1.0 + recommend = True + resp = extract_data_latency_calculation(self.tmp_dir, recommend, static_offset) + self.assertIsInstance(resp[0], RawData) + self.assertEqual(resp[1], self.triggers) + self.assertNotEqual(resp[2], static_offset) + self.assertEqual(resp[2], 0.0) + + def test_sample_rate_diffs(self): + response = sample_rate_diffs(self.raw_data) + self.assertIsInstance(response, tuple) + self.assertEqual(int(response[0]), int(response[1])) + + def test_lsl_timestamp_diffs(self): + response = lsl_timestamp_diffs(self.raw_data) + self.assertIsInstance(response, list) + + def test_calculate_latency_defaults(self): + response = calculate_latency( + self.raw_data, + self.diode_channel, + self.triggers, + self.stim_number) + self.assertIsInstance(response, tuple) + self.assertIsInstance(response[0], list) + self.assertIsInstance(response[1], list) + # check that error response is not empty + self.assertTrue(len(response[1]) > 1) + + def test_calculate_latency_with_high_tolerance(self): + response = calculate_latency( + self.raw_data, + self.diode_channel, + self.triggers, + self.stim_number, + tolerance=0.5) + self.assertIsInstance(response, tuple) + self.assertIsInstance(response[0], list) + self.assertIsInstance(response[1], list) + # check that given the high tolerance, the error response is empty for this data + self.assertEqual(len(response[1]), 0.0) + + def test_calculate_latency_with_recommend(self): + recommend = True + response = calculate_latency( + self.raw_data, + self.diode_channel, + self.triggers, + self.stim_number, + recommend_static=recommend) + self.assertIsInstance(response, tuple) + self.assertIsInstance(response[0], list) + self.assertIsInstance(response[1], list) + self.assertEqual(len(response[1]), 0.0) + + def test_calculate_latency_ploting(self): + # stub the plot show function before calling + when(plt).show().thenReturn(None) + + calculate_latency( + self.raw_data, + self.diode_channel, + self.triggers, + self.stim_number, + plot=True) + + # verify that the plot show function was called 3 times as expected + verify(plt, times=3).show() + + def test_calculate_latency_ploting_with_false_positive_correction(self): + """Test calculate_latency with false positive correction.""" + corrections = 2 + + response1 = calculate_latency( + self.raw_data, + self.diode_channel, + self.triggers, + self.stim_number) + + response2 = calculate_latency( + self.raw_data, + self.diode_channel, + self.triggers, + self.stim_number, + correct_diode_false_positive=corrections) + + # verify two responses are different in the expected way + self.assertNotEqual(response1[0], response2[0]) + self.assertEqual(len(response2[0]), len(response1[0]) - corrections) + self.assertNotEqual(response1[1][0], response2[1][0]) + + +if __name__ == "__main__": + unittest.main() diff --git a/scripts/python/offset_analysis.py b/scripts/python/offset_analysis.py deleted file mode 100644 index 0001926b5..000000000 --- a/scripts/python/offset_analysis.py +++ /dev/null @@ -1,263 +0,0 @@ -"""GUI tool to visualize offset analysis when analyzing system latency. - -Assumptions: - - The raw_data.csv file is available. - - The raw_data.csv file contains a TRG column, which is a continuous line of 0s and values greater than 0 - (indicating a photodiode trigger event). - - The triggers.txt file is available. - - All data are in the same directory and in the BciPy session data format. - -Usage: - - Run the script from the command line. - - Select the directory containing the raw_data.csv and triggers.txt files. - - The script will plot the TRG column from the raw_data.csv file, as well as the triggers.txt file. - - The script will also print out the results of the analysis, including the number of violations - (set using the --tolerance flag) and the recommended static offset (-r). - - Example usage to recommend a static offset: - python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' -r - - Example usage to recommend a static offset using the RSVP Time Test Calibrations: - python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' --rsvp -r - - Example usage to plot the data next to photodiode results with a static offset applied: - python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' --offset 0.01 - - Example usage to plot the data next to photodiode results with a static offset applied and a tolerance of 10 ms: - python offset_analysis.py -p 'C:/Users/test_data/test_offset_analysis_session/' --offset 0.01 --tolerance 0.01 -""" -from pathlib import Path -from textwrap import wrap -from typing import List - -import matplotlib.pyplot as plt -import numpy as np -from scipy.stats import describe, normaltest - -from bcipy.gui.file_dialog import ask_directory -from bcipy.helpers.raw_data import RawData, load -from bcipy.config import RAW_DATA_FILENAME, TRIGGER_FILENAME - - -def clock_seconds(sample_rate: float, sample: int) -> float: - """Convert the given raw_data sample number to acquisition clock - seconds.""" - assert sample > 0 - return sample / sample_rate - - -def calculate_latency(raw_data: RawData, - triggers: List[tuple], - title: str = "", - recommend_static: bool = False, - plot: bool = False, - tolerance: float = 0.01, - rsvp: bool = False): - """Plot raw_data triggers, including the TRG_device_stream data - (channel streamed from the device; usually populated from a trigger box), - as well as TRG data populated from the LSL Marker Stream. Also plots data - from the triggers.txt file if available. - - Parameters: - ----------- - raw_data - complete list of samples read in from the raw_data.csv file. - triggers - list of (trg, trg_type, stamp) values from the triggers.txt - file. Stamps have been converted to the acquisition clock using - the offset recorded in the triggers.txt. - """ - - fig = plt.figure() - ax = fig.add_subplot(1, 1, 1) - plt.xlabel('acquisition clock (secs)') - plt.ylabel('TRG value') - if title: - plt.title("\n".join(wrap(title, 50))) - - # Plot TRG column; this is a continuous line with >0 indicating light. - trg_box_channel = raw_data.dataframe['TRG'] - trg_box_y = [] - trg_ymax = 1.5 - trg_box_x = [] - - # setup some analysis variable - diode_enc = False - starts = [] - lengths = [] - length = 0 - - for i, val in enumerate(trg_box_channel): - timestamp = clock_seconds(raw_data.sample_rate, i + 1) - value = int(float(val)) - trg_box_x.append(timestamp) - trg_box_y.append(value) - - if value > 0 and not diode_enc: - diode_enc = True - starts.append(timestamp) - - if value > 0 and diode_enc: - length += 0 - - if value < 1 and diode_enc: - diode_enc = False - lengths.append(length) - length = 0 - - ax.plot(trg_box_x, trg_box_y, label='TRG (trigger box)') - - # Plot triggers.txt data if present; vertical line for each value. - if triggers: - trigger_diodes_timestamps = [ - stamp for (_name, _trgtype, stamp) in triggers if _name == '\u25A0' - ] - plt.vlines(trigger_diodes_timestamps, - ymin=-1.0, - ymax=trg_ymax, - label=f'{TRIGGER_FILENAME} (adjusted)', - linewidth=0.5, - color='cyan') - - errors = [] - diffs = [] - x = 0 - if (len(starts) > len(trigger_diodes_timestamps)): - len_diff = len(starts) - len(trigger_diodes_timestamps) - starts = starts[len_diff:] - - for trigger_stamp, diode_stamp in zip(trigger_diodes_timestamps, starts): - diff = trigger_stamp - diode_stamp - - # rsvp bug with fixation - if rsvp: - if x > 0: - if abs(diff) > tolerance: - errors.append( - f'trigger={trigger_stamp} diode={diode_stamp} diff={diff}' - ) - diffs.append(diff) - if x == 4: - x = 0 - else: - x += 1 - else: - if abs(diff) > tolerance: - errors.append( - f'trigger={trigger_stamp} diode={diode_stamp} diff={diff}') - diffs.append(diff) - - if recommend_static: - # test for normality - _, p_value = normaltest(diffs) - print(f'{describe(diffs)}') - - # if it's not normal, take the median - if p_value < 0.05: - print('Non-normal distribution') - recommended_static = abs(np.median(diffs)) - print( - f'System recommended static offset median=[{recommended_static}]') - recommended_static = abs(np.mean(diffs)) - print(f'System recommended static offset mean=[{recommended_static}]') - - else: - if errors: - num_errors = len(errors) - print( - f'RESULTS: Allowable tolerance between triggers and photodiode exceeded. {errors}' - f'Number of violations: {num_errors}') - else: - print( - f'RESULTS: Triggers and photodiode timestamps within limit of [{tolerance}s]!' - ) - - # Add labels for TRGs - first_trg = trigger_diodes_timestamps[0] - - # Set initial zoom to +-5 seconds around the calibration_trigger - if first_trg: - ax.set_xlim(left=first_trg - 5, right=first_trg + 5) - - ax.grid(axis='x', linestyle='--', color="0.5", linewidth=0.4) - plt.legend(loc='lower left', fontsize='small') - # display the plot - if plot: - plt.show() - - -def read_triggers(triggers_file: str, static_offset: float): - """Read in the triggers.txt file. Convert the timestamps to be in - acquisition clock units using the offset listed in the file (last entry). - Returns: - -------- - list of (symbol, targetness, stamp) tuples.""" - - with open(triggers_file, encoding='utf-8') as trgfile: - records = [line.split(' ') for line in trgfile.readlines()] - (_cname, _ctype, cstamp) = records[0] - records.pop(0) - # (_acq_name, _acq_type, acq_stamp) = records[-1] - offset = float(cstamp) + static_offset - - corrected = [] - for i, (name, trg_type, stamp) in enumerate(records): - if i < len(records) - 1: - # omit offset record for plotting - corrected.append((name, trg_type, float(stamp) + offset)) - return corrected - - -def main(data_dir: str, recommend: bool = False, static_offset: float = 0.105, - tolerance: float = 0.01, rsvp: bool = False): - """Run the viewer gui - - Parameters: - ----------- - data_dir - path to the data directory, containing raw_data.csv and triggers.txt - recommend - whether to recommend a static offset. If True, plots are not displayed. - static_offset - fixed offset applied to triggers for plotting and analysis. - """ - if recommend: - static_offset = 0.0 - raw_data = load(Path(data_dir, f'{RAW_DATA_FILENAME}.csv')) - triggers = read_triggers(Path(data_dir, f'{TRIGGER_FILENAME}'), static_offset) - - calculate_latency(raw_data, - triggers, - title=Path(data_dir).name, - recommend_static=recommend, - plot=not recommend, - tolerance=tolerance, - rsvp=rsvp) - - -if __name__ == "__main__": - import argparse - - parser = argparse.ArgumentParser( - description="Graphs trigger data from a bcipy session to visualize system latency") - parser.add_argument('-p', - '--path', - help='path to the data directory', - default=None) - parser.add_argument('-r', - '--recommend', - help='flag used for recommending a static offset. If set, plots are not displayed', - action='store_true') - parser.add_argument('--offset', - help='static offset applied to triggers for plotting and analysis', - default=0.114) - parser.add_argument('-t', '--tolerance', - help='Allowable tolerance between triggers and photodiode. Deafult 10 ms', - default=0.01) - parser.add_argument('--rsvp', - help=('RSVP Calibration Task. Default False. ' - 'Corrects for issue with fixation causing a false positive.'), - type=bool, - default=True) - - args = parser.parse_args() - path = args.path - if not path: - path = ask_directory() - - main(path, bool(args.recommend), float(args.offset), float(args.tolerance), bool(args.rsvp)) diff --git a/scripts/python/plot_eye_data.py b/scripts/python/plot_eye_data.py deleted file mode 100644 index cb9461d62..000000000 --- a/scripts/python/plot_eye_data.py +++ /dev/null @@ -1,37 +0,0 @@ -from bcipy.helpers.raw_data import load - -DIPSIZE = (1707, 1067) -TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' - -def load_eye_tracking_data(path): - data = load(f'{path}/{TOBII_FILENAME}') - return data - -if __name__ == "__main__": - import argparse - from pathlib import Path - from bcipy.helpers.load import load_experimental_data - from bcipy.helpers.visualization import visualize_gaze - import matplotlib.pyplot as plt - from matplotlib import image - import numpy as np - import seaborn as sns - import pandas as pd - - parser = argparse.ArgumentParser() - parser.add_argument( - '-p', - '--path', - help='Path to the directory with raw_data to be converted', - required=False) - args = parser.parse_args() - - # if no path is provided, prompt for one using a GUI - path = args.path - if not path: - path = load_experimental_data() - - data = load_eye_tracking_data(path) - - # Plot the eye data, set save_path to None to not save the plot. You can have both plots at the same time. - visualize_gaze(data, show=True, save_path=path, heatmap=False, raw_plot=True) diff --git a/scripts/python/plot_inquiry_data.py b/scripts/python/plot_inquiry_data.py deleted file mode 100644 index 40f628dad..000000000 --- a/scripts/python/plot_inquiry_data.py +++ /dev/null @@ -1,91 +0,0 @@ -from bcipy.helpers.raw_data import load -from bcipy.config import STATIC_IMAGES_PATH - -DIPSIZE = (1707, 1067) -IMG_PATH = f'{STATIC_IMAGES_PATH}/main/matrix.png' -TOBII_FILENAME = 'eyetracker_data_tobii-p0.csv' - -def load_eye_tracking_data(path): - data = load(f'{path}/{TOBII_FILENAME}') - - left_eye_channel_map = [0,0,1,1,1,0,0,0,0] - left_eye_data, _, _ = data.by_channel_map(left_eye_channel_map) - left_eye_x = left_eye_data[0] - left_eye_y = left_eye_data[1] - left_pupil = left_eye_data[2] - - right_eye_channel_map = [0,0,0,0,0,1,1,1,0] - right_eye_data, _, _ = data.by_channel_map(right_eye_channel_map) - right_eye_x = right_eye_data[0] - right_eye_y = right_eye_data[1] - right_pupil = right_eye_data[2] - return left_eye_x, left_eye_y, left_pupil, right_eye_x, right_eye_y, right_pupil - - -if __name__ == "__main__": - import argparse - from pathlib import Path - from bcipy.helpers.load import load_experimental_data - import matplotlib.pyplot as plt - from matplotlib import image - import numpy as np - import seaborn as sns - import pandas as pd - - parser = argparse.ArgumentParser() - parser.add_argument( - '-p', - '--path', - help='Path to the directory with raw_data to be converted', - required=False) - args = parser.parse_args() - - # if no path is provided, prompt for one using a GUI - path = args.path - if not path: - path = load_experimental_data() - - data = load_eye_tracking_data(path) - lx, ly, lp, rx, ry, rp = data - - - dpi = 100 - - # load the image - img = plt.imread(IMG_PATH) - # img = np.flipud(img) - - w, h = len(img[0]), len(img) - - # resize the image to fit the display - # img = np.resize(img, (DIPSIZE[1], DIPSIZE[0], 4)) - fig, ax = plt.subplots() - ax.imshow(img, extent=[0, 1, 0, 1]) - # ax.scatter(lx, ly, c='r', s=1) - # ax.scatter(rx, ry, c='b', s=1) - # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis - lx = np.clip(lx, 0, 1) - ly = np.clip(ly, 0, 1) - rx = np.clip(rx, 0, 1) - ry = np.clip(ry, 0, 1) - ly = 1 - ly - ry = 1 - ry - - # plot the eye data - # ax.plot(lx, ly, c='r', linewidth=1) - # ax.plot(rx, ry, c='b', linewidth=1) - - # # remove nan values - lx = lx[~np.isnan(lx)] - ly = ly[~np.isnan(ly)] - rx = rx[~np.isnan(rx)] - ry = ry[~np.isnan(ry)] - - # determine kde of the eye data - # ax = sns.kdeplot(rx, ry, cmap="mako", fill=False, thresh=0.05, levels=10) - - - ax.scatter(lx, ly, c='r', s=1) - ax.scatter(rx, ry, c='b', s=1) - - plt.show() \ No newline at end of file From d5c79e36e60a2a60bfe1337baa871e07cd96772a Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 11 Jun 2024 10:10:40 -0700 Subject: [PATCH 257/330] Refactored base calibration to make it easier to subclass --- bcipy/task/base_calibration.py | 37 ++++++++++++++++++++++++---------- 1 file changed, 26 insertions(+), 11 deletions(-) diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index 281b7181b..5a4c3093d 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -31,12 +31,6 @@ class Inquiry(NamedTuple): durations: List[float] colors: List[str] - @property - def labels(self) -> List[str]: - """labels for each stimuli""" - [target, _fixation, *symbols] = self.stimuli - return ['target' if sym == target else 'nontarget' for sym in symbols] - @property def target(self) -> str: """target symbol""" @@ -56,6 +50,15 @@ class BaseCalibrationTask(Task): daq (Data Acquisition Client) parameters (dict) file_save (str) + + Subclasses should override the provided MODE and can specialize behavior by overriding + the following methods: + - init_display ; initializes the stimulus display + - init_inquiry_generator ; creates a generator that returns inquiries to be presented + - trigger_type ; used for assigning trigger types to the timing data + - session_task_data ; provide task-specific session data + - session_inquiry_data ; provide task-specific inquiry data to the session + - cleanup ; perform any necessary cleanup (closing connections, etc.) """ MODE = 'Undefined' @@ -71,7 +74,7 @@ def __init__(self, win: visual.Window, daq: ClientManager, self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) self.experiment_clock = Clock() self.start_time = self.experiment_clock.getTime() - self.symbol_set = alphabet(parameters) + self._symbol_set = alphabet(parameters) self.file_save = file_save self.trigger_handler = TriggerHandler(self.file_save, TRIGGER_FILENAME, @@ -91,9 +94,14 @@ def enable_breaks(self) -> bool: """Whether to allow breaks""" return self.parameters['enable_breaks'] + @property + def symbol_set(self) -> List[str]: + """Symbols used in the calibration""" + return self._symbol_set + def name(self) -> str: """Task name""" - return 'Calibration Task' + return f"{self.MODE} Calibration Task" def wait(self, seconds: Optional[float] = None) -> None: """Pause for a time. @@ -225,8 +233,8 @@ def execute(self) -> str: inq_index += 1 self.exit_display() - self.cleanup() self.write_offset_trigger() + self.cleanup() return self.file_save @@ -291,13 +299,20 @@ def write_session_data(self) -> None: self.session.as_dict()) session_file.close() + def stim_labels(self, inquiry: Inquiry) -> List[str]: + """labels for each stimuli""" + return [ + str(self.trigger_type(symbol, inquiry.target, index)) + for index, symbol in enumerate(inquiry.stimuli) + ] + def add_session_data(self, inquiry: Inquiry) -> None: """Adds the latest inquiry to the session data.""" data = session_data.Inquiry( - stimuli=inquiry, + stimuli=inquiry.stimuli, timing=inquiry.durations, triggers=[], - target_info=inquiry.labels, + target_info=self.stim_labels(inquiry), target_letter=inquiry.target, task_data=self.session_inquiry_data(inquiry)) self.session.add_sequence(data) From a5952681bca27f37b41b65f8380317fee3b69314 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 11 Jun 2024 10:11:13 -0700 Subject: [PATCH 258/330] Refactored RsvpCalibrationTask to subclass BaseCalibration --- .../paradigm/rsvp/calibration/calibration.py | 259 +++--------------- 1 file changed, 35 insertions(+), 224 deletions(-) diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 98d9d2419..816b04e59 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -1,28 +1,16 @@ -from typing import List, Tuple - from psychopy import core, visual -from bcipy.acquisition import ClientManager -from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE -from bcipy.display import (InformationProperties, PreviewInquiryProperties, - StimuliProperties) +from bcipy.display import (Display, InformationProperties, + PreviewInquiryProperties, StimuliProperties) from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters -from bcipy.helpers.stimuli import (InquirySchedule, StimuliOrder, TargetPositions, - generate_calibration_inquiries) -from bcipy.helpers.symbols import alphabet -from bcipy.helpers.task import (get_user_input, pause_calibration, - trial_complete_message) -from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, - TriggerType, convert_timing_triggers, - offset_label) - -from bcipy.task import Task +from bcipy.helpers.triggers import TriggerType +from bcipy.task.base_calibration import BaseCalibrationTask -class RSVPCalibrationTask(Task): +class RSVPCalibrationTask(BaseCalibrationTask): """RSVP Calibration Task. Calibration task performs an RSVP stimulus inquiry @@ -42,81 +30,10 @@ class RSVPCalibrationTask(Task): parameters (dict) file_save (str) """ + MODE = 'RSVP' - def __init__( - self, - win: visual.Window, - daq: ClientManager, - parameters: Parameters, - file_save: str) -> None: - super(RSVPCalibrationTask, self).__init__() - - self.window = win - self.frame_rate = self.window.getActualFrameRate() - self.parameters = parameters - self.daq = daq - self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) - self.experiment_clock = Clock() - self.buffer_val = parameters['task_buffer_length'] - self.alp = alphabet(parameters) - self.rsvp = init_calibration_display_task( - self.parameters, self.window, - self.static_clock, self.experiment_clock) - self.file_save = file_save - self.trigger_handler = TriggerHandler( - self.file_save, - TRIGGER_FILENAME, - FlushFrequency.EVERY) - - self.stim_number = parameters['stim_number'] - self.stim_length = parameters['stim_length'] - self.stim_order = StimuliOrder(parameters['stim_order']) - self.target_positions = TargetPositions(parameters['target_positions']) - self.nontarget_inquiries = parameters['nontarget_inquiries'] - - self.show_preview_inquiry = parameters['show_preview_inquiry'] - - self.timing = [parameters['time_prompt'], - parameters['time_fixation'], - parameters['time_flash']] - self.jitter = parameters['stim_jitter'] - - self.color = [parameters['target_color'], - parameters['fixation_color'], - parameters['stim_color']] - self.wait_screen_message_color = self.color[-1] - self.task_info_color = parameters['task_color'] - - self.stimuli_height = parameters['stim_height'] - self.is_txt_stim = parameters['is_txt_stim'] - self.enable_breaks = parameters['enable_breaks'] - - def generate_stimuli(self) -> InquirySchedule: - """Generates the inquiries to be presented. - Returns: - -------- - tuple( - samples[list[list[str]]]: list of inquiries - timing(list[list[float]]): list of timings - color(list(list[str])): list of colors) - """ - return generate_calibration_inquiries(self.alp, - inquiry_count=self.stim_number, - stim_per_inquiry=self.stim_length, - stim_order=self.stim_order, - target_positions=self.target_positions, - percentage_without_target=self.nontarget_inquiries, - timing=self.timing, - jitter=self.jitter, - is_txt=self.rsvp.is_txt_stim, - color=self.color) - - def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: - """Trigger Type. - - This method is passed to convert_timing_triggers to properly assign TriggerTypes - to the timing of stimuli presented. - """ + def trigger_type(self, symbol: str, target: str, + index: int) -> TriggerType: if index == 0: return TriggerType.PROMPT if symbol == 'inquiry_preview': @@ -127,139 +44,33 @@ def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: return TriggerType.TARGET return TriggerType.NONTARGET - def execute(self) -> str: - - self.logger.info(f'Starting {self.name()}!') - run = True - - # Check user input to make sure we should be going - if not get_user_input(self.rsvp, WAIT_SCREEN_MESSAGE, - self.wait_screen_message_color, - first_run=True): - run = False - - # Begin the Experiment - while run: - - # Get inquiry information given stimuli parameters - (stimuli, stimuli_timing, stimuli_color) = self.generate_stimuli() - - # Execute the RSVP inquiries - for inquiry in range(self.stim_number): - - # check user input to make sure we should be going - if not get_user_input(self.rsvp, WAIT_SCREEN_MESSAGE, - self.wait_screen_message_color): - break - - # Take a break every number of trials defined - if self.enable_breaks: - pause_calibration(self.window, self.rsvp, inquiry, - self.parameters) - - # update task state - self.rsvp.update_task_bar() - - # Draw and flip screen - self.rsvp.draw_static() - self.window.flip() - - # Schedule a inquiry - self.rsvp.stimuli_inquiry = stimuli[inquiry] - - # check if text stimuli or not for color information - if self.is_txt_stim: - self.rsvp.stimuli_colors = stimuli_color[inquiry] - - self.rsvp.stimuli_timing = stimuli_timing[inquiry] - - core.wait(self.buffer_val) - - # do inquiry and get timing information back from the display - timing = self.rsvp.do_inquiry(preview_calibration=self.show_preview_inquiry) - - self.write_trigger_data(timing, (inquiry == 0)) - core.wait(self.buffer_val) - - # Set run to False to stop looping - run = False - - # Say Goodbye! - self.rsvp.info_text = trial_complete_message(self.window, self.parameters) - self.rsvp.draw_static() - self.window.flip() - - self.write_offset_trigger() - - # Wait some time before exiting so there is trailing eeg data saved - core.wait(self.buffer_val) - - return self.file_save - - def write_trigger_data(self, timing: List[Tuple[str, float]], first_run: bool) -> None: - """Write Trigger Data. - - Using the timing provided from the display and calibration information from the data acquisition - client, write trigger data in the correct format. - - *Note on offsets*: we write the full offset value which can be used to transform all stimuli to the time since - session start (t = 0) for all values (as opposed to most system clocks which start much higher). - We do not write the calibration trigger used to generate this offset from the display. - See RSVPDisplay._trigger_pulse() for more information. - """ - # write offsets. currently, we only check for offsets at the beginning. - # offset will factor in true offset and time relative from beginning - if first_run: - triggers = [] - for content_type, client in self.daq.clients_by_type.items(): - label = offset_label(content_type.name) - time = client.offset( - self.rsvp.first_stim_time) - self.rsvp.first_stim_time - triggers.append(Trigger(label, TriggerType.OFFSET, time)) - self.trigger_handler.add_triggers(triggers) - - # make sure triggers are written for the inquiry - self.trigger_handler.add_triggers(convert_timing_triggers(timing, timing[0][0], self.trigger_type)) - - def write_offset_trigger(self) -> None: - """Append an offset value to the end of the trigger file. - """ - # To help support future refactoring or use of lsl timestamps only - # we write only the sample offset here. - triggers = [] - for content_type, client in self.daq.clients_by_type.items(): - label = offset_label(content_type.name, prefix='daq_sample_offset') - time = client.offset(self.rsvp.first_stim_time) - triggers.append(Trigger(label, TriggerType.SYSTEM, time)) - - self.trigger_handler.add_triggers(triggers) - self.trigger_handler.close() - def name(self) -> str: - return 'RSVP Calibration Task' + def init_display(self) -> Display: + return init_calibration_display_task(self.parameters, self.window, + self.static_clock, + self.experiment_clock) def init_calibration_display_task( - parameters: Parameters, - window: visual.Window, + parameters: Parameters, window: visual.Window, static_clock: core.StaticPeriod, experiment_clock: Clock) -> CalibrationDisplay: + """Initialize the display""" info = InformationProperties( info_color=[parameters['info_color']], - info_pos=[(parameters['info_pos_x'], - parameters['info_pos_y'])], + info_pos=[(parameters['info_pos_x'], parameters['info_pos_y'])], info_height=[parameters['info_height']], info_font=[parameters['font']], info_text=[parameters['info_text']], ) - stimuli = StimuliProperties(stim_font=parameters['font'], - stim_pos=(parameters['stim_pos_x'], - parameters['stim_pos_y']), - stim_height=parameters['stim_height'], - stim_inquiry=[''] * parameters['stim_length'], - stim_colors=[parameters['stim_color']] * parameters['stim_length'], - stim_timing=[10] * parameters['stim_length'], - is_txt_stim=parameters['is_txt_stim']) + stimuli = StimuliProperties( + stim_font=parameters['font'], + stim_pos=(parameters['stim_pos_x'], parameters['stim_pos_y']), + stim_height=parameters['stim_height'], + stim_inquiry=[''] * parameters['stim_length'], + stim_colors=[parameters['stim_color']] * parameters['stim_length'], + stim_timing=[10] * parameters['stim_length'], + is_txt_stim=parameters['is_txt_stim']) task_bar = CalibrationTaskBar(window, inquiry_count=parameters['stim_number'], @@ -272,18 +83,18 @@ def init_calibration_display_task( preview_inquiry = PreviewInquiryProperties( preview_only=True, preview_inquiry_length=parameters['preview_inquiry_length'], - preview_inquiry_progress_method=parameters['preview_inquiry_progress_method'], + preview_inquiry_progress_method=parameters[ + 'preview_inquiry_progress_method'], preview_inquiry_key_input=parameters['preview_inquiry_key_input'], preview_inquiry_isi=parameters['preview_inquiry_isi']) - return CalibrationDisplay( - window, - static_clock, - experiment_clock, - stimuli, - task_bar, - info, - preview_inquiry=preview_inquiry, - trigger_type=parameters['trigger_type'], - space_char=parameters['stim_space_char'], - full_screen=parameters['full_screen']) + return CalibrationDisplay(window, + static_clock, + experiment_clock, + stimuli, + task_bar, + info, + preview_inquiry=preview_inquiry, + trigger_type=parameters['trigger_type'], + space_char=parameters['stim_space_char'], + full_screen=parameters['full_screen']) From 1902fe39aaac4d0ab58919930b24a5df1de465c1 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 11 Jun 2024 10:11:48 -0700 Subject: [PATCH 259/330] Refactored RSVP timing verification to subclass RsvpCalibration --- .../rsvp/calibration/timing_verification.py | 80 ++++++++----------- 1 file changed, 33 insertions(+), 47 deletions(-) diff --git a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py index 55af4b995..be94ca30c 100644 --- a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py +++ b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py @@ -1,18 +1,19 @@ # mypy: disable-error-code="assignment" -from itertools import cycle - -from typing import Tuple +from itertools import cycle, islice, repeat +from typing import Iterator, List from psychopy import visual from bcipy.acquisition import ClientManager -from bcipy.task import Task -from bcipy.task.paradigm.rsvp.calibration.calibration import RSVPCalibrationTask from bcipy.helpers.parameters import Parameters -from bcipy.helpers.stimuli import PhotoDiodeStimuli, get_fixation, jittered_timing +from bcipy.helpers.stimuli import (PhotoDiodeStimuli, get_fixation, + jittered_timing) +from bcipy.task.base_calibration import Inquiry +from bcipy.task.paradigm.rsvp.calibration.calibration import \ + RSVPCalibrationTask -class RSVPTimingVerificationCalibration(Task): +class RSVPTimingVerificationCalibration(RSVPCalibrationTask): """RSVP Calibration Task. This task is used for verifying display timing by alternating solid and empty boxes. These @@ -29,54 +30,39 @@ class RSVPTimingVerificationCalibration(Task): """ TASK_NAME = 'RSVP Timing Verification Task' - def __init__( - self, - win: visual.Window, - daq: ClientManager, - parameters: Parameters, - file_save: str) -> None: - super(RSVPTimingVerificationCalibration, self).__init__() + def __init__(self, win: visual.Window, daq: ClientManager, + parameters: Parameters, file_save: str) -> None: parameters['stim_height'] = 0.8 parameters['stim_pos_y'] = 0.0 - self.stimuli = PhotoDiodeStimuli.list() - self._task = RSVPCalibrationTask(win, daq, parameters, file_save) - self._task.generate_stimuli = self.generate_stimuli + super(RSVPTimingVerificationCalibration, + self).__init__(win, daq, parameters, file_save) - def generate_stimuli(self) -> Tuple[list, list, list]: - """Generates the inquiries to be presented. - Returns: - -------- - tuple( - samples[list[list[str]]]: list of inquiries - timing(list[list[float]]): list of timings - color(list(list[str])): list of colors) - """ - samples, times, colors = [], [], [] + @property + def symbol_set(self) -> List[str]: + """Symbols used in the calibration""" + return PhotoDiodeStimuli.list() - # alternate between solid and empty boxes - letters = cycle(self.stimuli) - time_prompt, time_fixation, time_stim = self._task.timing - color_target, color_fixation, color_stim = self._task.color - inq_len = self._task.stim_length + def init_inquiry_generator(self) -> Iterator[Inquiry]: + params = self.parameters - stim_timing = jittered_timing(time_stim, self._task.jitter, inq_len) + # alternate between solid and empty boxes + letters = cycle(self.symbol_set) target = next(letters) fixation = get_fixation(is_txt=True) - inq_stim = [target, fixation, *[next(letters) for _ in range(inq_len)]] - inq_times = [time_prompt, time_fixation] + stim_timing - inq_colors = [color_target, color_fixation, *[color_stim for _ in range(inq_len)]] - - for _ in range(self._task.stim_number): - samples.append(inq_stim) - times.append(inq_times) - colors.append(inq_colors) - - return (samples, times, colors) - - def execute(self) -> str: - self.logger.info(f'Starting {self.name()}!') - return self._task.execute() + inq_len = params['stim_length'] + stimuli = [target, fixation, *islice(letters, inq_len)] + durations = [ + params['time_prompt'], params['time_fixation'], *jittered_timing( + params['time_flash'], params['stim_jitter'], inq_len) + ] + colors = [ + params['target_color'], params['fixation_color'], + *repeat(params['stim_color'], inq_len) + ] + + return repeat(Inquiry(stimuli, durations, colors), + params['stim_number']) @classmethod def label(cls) -> str: From 28c95cf722c298b9a7ae5cd04f15c81ee6fe1b03 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 11 Jun 2024 13:37:14 -0700 Subject: [PATCH 260/330] Refactored Matrix calibration to subclass BaseCalibration; refactored associated timing test --- bcipy/display/paradigm/matrix/display.py | 4 +- bcipy/task/base_calibration.py | 6 +- bcipy/task/paradigm/matrix/calibration.py | 292 +++--------------- .../paradigm/matrix/timing_verification.py | 65 ++-- 4 files changed, 81 insertions(+), 286 deletions(-) diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 8fb0cd2a8..b36ba75d3 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -115,12 +115,12 @@ def __init__(self, self.should_prompt_target = should_prompt_target self.logger.info( - f"Symbol positions ({display_container.units} units):\n{self._stim_positions}" + f"Symbol positions ({display_container.units} units):\n{self.stim_positions}" ) self.logger.info(f"Matrix center position: {display_container.center}") @property - def _stim_positions(self) -> Dict[str, Tuple[float, float]]: + def stim_positions(self) -> Dict[str, Tuple[float, float]]: """Returns a dict with the position for each stim""" assert self.stim_registry, "stim_registry not yet initialized" return { diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index 5a4c3093d..9d042bd01 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -1,6 +1,6 @@ """Base calibration task.""" -from typing import Iterator, List, NamedTuple, Optional, Tuple +from typing import Any, Dict, Iterator, List, NamedTuple, Optional, Tuple from psychopy import core, visual @@ -147,7 +147,7 @@ def init_session(self) -> session_data.Session: symbol_set=self.symbol_set, task_data=self.session_task_data()) - def session_task_data(self): + def session_task_data(self) -> Optional[Dict[str, Any]]: """"Task-specific session data""" return None @@ -320,6 +320,6 @@ def add_session_data(self, inquiry: Inquiry) -> None: ) - self.start_time self.write_session_data() - def session_inquiry_data(self, inquiry: Inquiry) -> Optional[dict]: + def session_inquiry_data(self, inquiry: Inquiry) -> Optional[Dict[str, Any]]: """Defines task-specific session data for each inquiry.""" return None diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index 170889675..58f939213 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -1,29 +1,18 @@ -from typing import List, Tuple +from typing import Any, Dict, Optional from psychopy import core, visual -from bcipy.acquisition import ClientManager -from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE -from bcipy.display import InformationProperties, StimuliProperties +from bcipy.display import Display, InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import save_stimuli_position_info -from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, InquirySchedule, - StimuliOrder, TargetPositions, - generate_calibration_inquiries) -from bcipy.helpers.symbols import alphabet from bcipy.helpers.system_utils import get_screen_info -from bcipy.helpers.task import (get_user_input, pause_calibration, - trial_complete_message) -from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, - TriggerType, convert_timing_triggers, - offset_label) -from bcipy.task import Task +from bcipy.task.base_calibration import BaseCalibrationTask -class MatrixCalibrationTask(Task): +class MatrixCalibrationTask(BaseCalibrationTask): """Matrix Calibration Task. Calibration task performs an Matrix stimulus inquiry @@ -43,242 +32,43 @@ class MatrixCalibrationTask(Task): parameters (Parameters Object) file_save (String) """ + MODE = 'Matrix' - def __init__( - self, - win: visual.Window, - daq: ClientManager, - parameters: Parameters, - file_save: str) -> None: - super(MatrixCalibrationTask, self).__init__() - self.window = win - self.frame_rate = self.window.getActualFrameRate() - - _screen_info = get_screen_info() - - self.screen_info = { + @property + def screen_info(self) -> Dict[str, Any]: + """Screen properties""" + return { 'screen_size_pixels': self.window.size.tolist(), - 'screen_hz': _screen_info.rate, + 'screen_hz': get_screen_info().rate, 'screen_units': 'norm', } - self.parameters = parameters - self.daq = daq - self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) - self.experiment_clock = Clock() - self.buffer_val = parameters['task_buffer_length'] - self.symbol_set = alphabet(parameters) - - self.file_save = file_save - self.trigger_handler = TriggerHandler( - self.file_save, - TRIGGER_FILENAME, - FlushFrequency.EVERY) - - self.wait_screen_message = WAIT_SCREEN_MESSAGE - self.wait_screen_message_color = parameters['stim_color'] - - self.stim_number = parameters['stim_number'] - self.stim_length = parameters['stim_length'] - self.jitter = parameters['stim_jitter'] - self.stim_order = StimuliOrder(parameters['stim_order']) - self.target_positions = TargetPositions(parameters['target_positions']) - self.nontarget_inquiries = parameters['nontarget_inquiries'] - - self.timing = [ - parameters['time_prompt'], parameters['time_fixation'], - parameters['time_flash'] - ] - self.color = [ - parameters['target_color'], parameters['fixation_color'], - parameters['stim_color'] - ] - self.task_info_color = parameters['task_color'] - self.stimuli_height = parameters['stim_height'] - self.is_txt_stim = parameters['is_txt_stim'] - self.enable_breaks = parameters['enable_breaks'] - - self.matrix = self.init_display() - - def init_display(self) -> MatrixDisplay: + def init_display(self) -> Display: """Initialize the display""" - return init_calibration_display_task(self.parameters, self.window, - self.experiment_clock, - self.symbol_set) - - def generate_stimuli(self) -> InquirySchedule: - """Generates the inquiries to be presented. - Returns: - -------- - tuple( - samples[list[list[str]]]: list of inquiries - timing(list[list[float]]): list of timings - color(list(list[str])): list of colors) - """ - return generate_calibration_inquiries( - self.symbol_set, - inquiry_count=self.stim_number, - stim_per_inquiry=self.stim_length, - stim_order=self.stim_order, - jitter=self.jitter, - target_positions=self.target_positions, - percentage_without_target=self.nontarget_inquiries, - timing=self.timing, - color=self.color) - - def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: - """Trigger Type. - - This method is passed to convert_timing_triggers to properly assign TriggerTypes - to the timing of stimuli presented. - """ - if index == 0: - return TriggerType.PROMPT - if symbol == DEFAULT_TEXT_FIXATION: - return TriggerType.FIXATION - if target == symbol: - return TriggerType.TARGET - return TriggerType.NONTARGET - - def execute(self) -> str: - - self.logger.info(f'Starting {self.name()}!') - run = True - - # Check user input to make sure we should be going - if not get_user_input(self.matrix, self.wait_screen_message, - self.wait_screen_message_color, - first_run=True): - run = False - - # Wait for a time - core.wait(self.buffer_val) - - # Begin the Experiment - while run: - - # Get inquiry information given stimuli parameters - (stimuli_labels, stimuli_timing, stimuli_colors) = self.generate_stimuli() - - assert len(stimuli_labels) == len(stimuli_timing) - - for inquiry in range(self.stim_number): - - # check user input to make sure we should be going - if not get_user_input(self.matrix, self.wait_screen_message, - self.wait_screen_message_color): - break - - # Take a break every number of trials defined - if self.enable_breaks: - pause_calibration(self.window, self.matrix, inquiry, - self.parameters) - - # update task state - self.matrix.update_task_bar(str(inquiry + 1)) - - # Draw and flip screen - self.matrix.draw_static() - self.window.flip() - - self.matrix.schedule_to( - stimuli_labels[inquiry], - stimuli_timing[inquiry], - stimuli_colors[inquiry]) - # Schedule a inquiry - - # Wait for a time - core.wait(self.buffer_val) - - # Do the inquiry - timing = self.matrix.do_inquiry() - - # Write triggers for the inquiry - self.write_trigger_data(timing, (inquiry == 0)) - - # Wait for a time - core.wait(self.buffer_val) - - # Set run to False to stop looping - run = False - - # Save the grid screenshot - self.matrix.capture_grid_screenshot(self.file_save) - - # Say Goodbye! - self.matrix.info_text = trial_complete_message( - self.window, self.parameters) - self.matrix.draw_static() - self.window.flip() - - # Allow for some additional data to be collected for later processing - core.wait(self.buffer_val) - - self.write_offset_trigger() - self.write_stimuli_positions() - - return self.file_save - - def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None: - """Write Trigger Data. - - Using the timing provided from the display and calibration information from the data acquisition - client, write trigger data in the correct format. - - *Note on offsets*: we write the full offset value which can be used to transform all stimuli to the time since - session start (t = 0) for all values (as opposed to most system clocks which start much higher). - We do not write the calibration trigger used to generate this offset from the display. - See MatrixDisplay._trigger_pulse() for more information. - """ - if first_run: - triggers = [] - for content_type, client in self.daq.clients_by_type.items(): - label = offset_label(content_type.name) - time = client.offset( - self.matrix.first_stim_time) - self.matrix.first_stim_time - triggers.append(Trigger(label, TriggerType.OFFSET, time)) - self.trigger_handler.add_triggers(triggers) - - # make sure triggers are written for the inquiry - self.trigger_handler.add_triggers(convert_timing_triggers(timing, timing[0][0], self.trigger_type)) - - def write_offset_trigger(self) -> None: - """Append an offset value to the end of the trigger file. - """ - # To help support future refactoring or use of lsl timestamps only - # we write only the sample offset here. - triggers = [] - for content_type, client in self.daq.clients_by_type.items(): - label = offset_label(content_type.name, prefix='daq_sample_offset') - time = client.offset(self.matrix.first_stim_time) - triggers.append(Trigger(label, TriggerType.SYSTEM, time)) - - self.trigger_handler.add_triggers(triggers) - self.trigger_handler.close() + return init_matrix_display(self.parameters, self.window, + self.experiment_clock, self.symbol_set) - def write_stimuli_positions(self) -> None: - """Write Stimuli Positions. + def exit_display(self) -> None: + self.display.capture_grid_screenshot(self.file_save) + return super().exit_display() - Write the positions of the stimuli to a json file. - """ - save_stimuli_position_info( - self.matrix._stim_positions, - self.file_save, - self.screen_info) + def cleanup(self) -> None: + # TODO: refactor offline_analysis to use session data and and remove this. + save_stimuli_position_info(self.display.stim_positions, self.file_save, + self.screen_info) + return super().cleanup() - def name(self) -> str: - return 'Matrix Calibration Task' + def session_task_data(self) -> Optional[Dict[str, Any]]: + return {**self.display.stim_positions, **self.screen_info} -def init_calibration_display_task( - parameters: Parameters, - window: visual.Window, - experiment_clock: Clock, - symbol_set: core.StaticPeriod) -> MatrixDisplay: +def init_matrix_display(parameters: Parameters, window: visual.Window, + experiment_clock: Clock, + symbol_set: core.StaticPeriod) -> MatrixDisplay: + """Initialize the matrix display""" info = InformationProperties( info_color=[parameters['info_color']], - info_pos=[(parameters['info_pos_x'], - parameters['info_pos_y'])], + info_pos=[(parameters['info_pos_x'], parameters['info_pos_y'])], info_height=[parameters['info_height']], info_font=[parameters['font']], info_text=[parameters['info_text']], @@ -287,7 +77,8 @@ def init_calibration_display_task( stim_pos=(-0.6, 0.4), stim_height=0.1, stim_inquiry=[''] * parameters['stim_length'], - stim_colors=[parameters['stim_color']] * parameters['stim_length'], + stim_colors=[parameters['stim_color']] * + parameters['stim_length'], stim_timing=[10] * parameters['stim_length'], is_txt_stim=parameters['is_txt_stim'], prompt_time=parameters["time_prompt"]) @@ -300,15 +91,14 @@ def init_calibration_display_task( height=parameters['task_height'], padding=parameters['task_padding']) - return MatrixDisplay( - window, - experiment_clock, - stimuli, - task_bar, - info, - rows=parameters['matrix_rows'], - columns=parameters['matrix_columns'], - width_pct=parameters['matrix_width'], - height_pct=1 - (2 * task_bar.height_pct), - trigger_type=parameters['trigger_type'], - symbol_set=symbol_set) + return MatrixDisplay(window, + experiment_clock, + stimuli, + task_bar, + info, + rows=parameters['matrix_rows'], + columns=parameters['matrix_columns'], + width_pct=parameters['matrix_width'], + height_pct=1 - (2 * task_bar.height_pct), + trigger_type=parameters['trigger_type'], + symbol_set=symbol_set) diff --git a/bcipy/task/paradigm/matrix/timing_verification.py b/bcipy/task/paradigm/matrix/timing_verification.py index ea5f9fa1d..2638f52a8 100644 --- a/bcipy/task/paradigm/matrix/timing_verification.py +++ b/bcipy/task/paradigm/matrix/timing_verification.py @@ -1,9 +1,11 @@ -from itertools import cycle -from typing import List -from bcipy.task.paradigm.matrix.calibration import ( - MatrixCalibrationTask, InquirySchedule, DEFAULT_TEXT_FIXATION, MatrixDisplay, - init_calibration_display_task) -from bcipy.helpers.stimuli import PhotoDiodeStimuli, jittered_timing +from itertools import cycle, islice, repeat +from typing import Iterator, List + +from bcipy.helpers.stimuli import (PhotoDiodeStimuli, get_fixation, + jittered_timing) +from bcipy.task.base_calibration import Inquiry +from bcipy.task.paradigm.matrix.calibration import (MatrixCalibrationTask, + MatrixDisplay) class MatrixTimingVerificationCalibration(MatrixCalibrationTask): @@ -25,36 +27,39 @@ class MatrixTimingVerificationCalibration(MatrixCalibrationTask): def init_display(self) -> MatrixDisplay: """Initialize the display""" - display = init_calibration_display_task( - self.parameters, self.window, self.experiment_clock, - symbols_with_photodiode_stim(self.symbol_set)) + display = super().init_display() display.start_opacity = 0.0 return display - def generate_stimuli(self) -> InquirySchedule: - """Generates the inquiries to be presented. - """ - samples, times, colors = [], [], [] - [time_target, time_fixation, time_stim] = self.timing - stimuli = cycle(PhotoDiodeStimuli.list()) - stim_timing = jittered_timing(time_stim, self.jitter, self.stim_length) + @property + def symbol_set(self) -> List[str]: + """Symbols used in the calibration""" + return symbols_with_photodiode_stim(super().symbol_set) - # advance iterator to start on the solid stim. - next(stimuli) + def init_inquiry_generator(self) -> Iterator[Inquiry]: + params = self.parameters # alternate between solid and empty boxes - inq_stim = [PhotoDiodeStimuli.SOLID.value, DEFAULT_TEXT_FIXATION - ] + [next(stimuli) for _ in range(self.stim_length)] - inq_times = [time_target, time_fixation - ] + stim_timing - inq_colors = [self.color[0]] * (self.stim_length + 2) - - for _ in range(self.stim_number): - samples.append(inq_stim) - times.append(inq_times) - colors.append(inq_colors) - - return InquirySchedule(samples, times, colors) + letters = cycle(PhotoDiodeStimuli.list()) + # advance to solid + next(letters) + fixation = get_fixation(is_txt=True) + + inq_len = params['stim_length'] + stimuli = [ + PhotoDiodeStimuli.SOLID.value, fixation, *islice(letters, inq_len) + ] + durations = [ + params['time_prompt'], params['time_fixation'], *jittered_timing( + params['time_flash'], params['stim_jitter'], inq_len) + ] + colors = [ + params['target_color'], params['fixation_color'], + *repeat(params['stim_color'], inq_len) + ] + + return repeat(Inquiry(stimuli, durations, colors), + params['stim_number']) def symbols_with_photodiode_stim(symbols: List[str]) -> List[str]: From e957f941ebdb607db0ad110b55802489bb786af7 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 11 Jun 2024 17:03:48 -0700 Subject: [PATCH 261/330] Refactor VEP calibration to subclass BaseCalibration task --- bcipy/task/paradigm/vep/calibration.py | 294 ++++++------------------- 1 file changed, 65 insertions(+), 229 deletions(-) diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index f090276c7..1119f7422 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -1,11 +1,9 @@ """VEP Calibration task-related code""" -from typing import Any, Dict, List, Tuple, Union +from typing import Any, Dict, Iterator, List, Optional -from psychopy import core, visual # type: ignore +from psychopy import visual # type: ignore from bcipy.acquisition.multimodal import ClientManager -from bcipy.config import (SESSION_DATA_FILENAME, TRIGGER_FILENAME, - WAIT_SCREEN_MESSAGE) from bcipy.display import InformationProperties, VEPStimuliProperties from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar @@ -14,30 +12,13 @@ from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters -from bcipy.helpers.save import _save_session_related_data -from bcipy.helpers.symbols import alphabet -from bcipy.helpers.task import get_user_input, trial_complete_message -from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, - TriggerType, convert_timing_triggers, - offset_label) -from bcipy.task import Task -from bcipy.task.data import Inquiry, Session -from bcipy.task.paradigm.vep.stim_generation import ( - InquirySchedule, generate_vep_calibration_inquiries) +from bcipy.helpers.triggers import TriggerType +from bcipy.task.base_calibration import BaseCalibrationTask, Inquiry +from bcipy.task.paradigm.vep.stim_generation import \ + generate_vep_calibration_inquiries -def trigger_type(symbol: str, target: str, _index: int) -> TriggerType: - """Trigger Type. - - This method is passed to convert_timing_triggers to properly assign TriggerTypes - to the timing of stimuli presented. - """ - if target == symbol: - return TriggerType.TARGET - return TriggerType.EVENT - - -class VEPCalibrationTask(Task): +class VEPCalibrationTask(BaseCalibrationTask): """VEP Calibration Task. A task begins setting up variables --> initializing eeg --> @@ -56,46 +37,40 @@ class VEPCalibrationTask(Task): def __init__(self, win: visual.Window, daq: ClientManager, parameters: Parameters, file_save: str): - super(VEPCalibrationTask, self).__init__() - self.num_boxes = 6 - self.window = win - self.frame_rate = self.window.getActualFrameRate() - self.parameters = parameters - self.daq = daq - self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) - self.experiment_clock = Clock() - self.start_time = self.experiment_clock.getTime() - self.buffer_val = parameters['task_buffer_length'] - self.symbol_set = alphabet(parameters) - - self.file_save = file_save - self.trigger_handler = TriggerHandler(self.file_save, TRIGGER_FILENAME, - FlushFrequency.EVERY) - - self.wait_screen_message = WAIT_SCREEN_MESSAGE - self.wait_screen_message_color = parameters['stim_color'] - - self.stim_number = parameters['stim_number'] - - self.timing = [ - parameters['time_prompt'], parameters['time_fixation'], - parameters['time_flash'] - ] - - self.color = [ - parameters['target_color'], parameters['fixation_color'], + self.box_colors = [ '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' ] + self.num_boxes = 6 + super().__init__(win, daq, parameters, file_save) - self.is_txt_stim = parameters['is_txt_stim'] - self.display = self.init_display() - - self.session = Session(save_location=self.file_save, - task='Calibration', - mode=self.MODE, - symbol_set=self.symbol_set, - task_data=self.session_task_data()) - self.write_session_data() + def init_display(self) -> VEPDisplay: + """Initialize the display""" + return init_vep_display(self.parameters, self.window, + self.experiment_clock, self.symbol_set, + self.box_colors) + + def init_inquiry_generator(self) -> Iterator[Inquiry]: + """Initializes a generator that returns inquiries to be presented.""" + parameters = self.parameters + schedule = generate_vep_calibration_inquiries( + alp=self.symbol_set, + timing=[ + parameters['time_prompt'], parameters['time_fixation'], + parameters['time_flash'] + ], + color=[ + parameters['target_color'], parameters['fixation_color'], + *self.box_colors + ], + inquiry_count=parameters['stim_number'], + num_boxes=self.num_boxes) + return (Inquiry(*inq) for inq in schedule) + + def trigger_type(self, symbol: str, target: str, + index: int) -> TriggerType: + if target == symbol: + return TriggerType.TARGET + return TriggerType.EVENT def session_task_data(self) -> Dict[str, Any]: """Task-specific session data""" @@ -109,185 +84,39 @@ def session_task_data(self) -> Dict[str, Any]: "symbol_starting_positions": self.display.starting_positions } - def init_display(self) -> VEPDisplay: - """Initialize the display""" - return init_calibration_display(self.parameters, self.window, - self.experiment_clock, self.symbol_set, - self.timing, self.color) - - def generate_stimuli(self) -> InquirySchedule: - """Generates the inquiries to be presented. - Returns: - -------- - tuple( - samples[list[list[str]]]: list of inquiries - timing(list[list[float]]): list of timings - color(list(list[str])): list of colors) - """ - return generate_vep_calibration_inquiries( - alp=self.symbol_set, - timing=self.timing, - color=self.color, - inquiry_count=self.stim_number, - num_boxes=self.num_boxes, - is_txt=self.is_txt_stim) - - def execute(self): - """Main task loop""" - self.logger.info(f'Starting {self.name()}!') - run = True - - # Check user input to make sure we should be going - if not get_user_input(self.display, - self.wait_screen_message, - self.wait_screen_message_color, - first_run=True): - run = False - - # Wait for a time - core.wait(self.buffer_val) - - # Begin the Experiment - while run: - - # Get inquiry information given stimuli parameters - (stimuli_labels, _timing, _colors) = self.generate_stimuli() - - for inquiry in range(self.stim_number): - # check user input to make sure we should be going - if not get_user_input(self.display, self.wait_screen_message, - self.wait_screen_message_color): - break - - # update task state - self.display.update_task_bar(str(inquiry + 1)) - - # Draw and flip screen - self.display.draw_static() - self.window.flip() - - self.display.schedule_to(stimuli_labels[inquiry]) - # Schedule an inquiry - - # Wait for a time - core.wait(self.buffer_val) - - # Do the inquiry - timing = self.display.do_inquiry() - - # Write triggers for the inquiry - self.write_trigger_data(timing, first_run=(inquiry == 0)) - - self.update_session_data(stimuli_labels[inquiry]) - - # Wait for a time - core.wait(self.buffer_val) - - # Set run to False to stop looping - run = False - - # Say Goodbye! - self.display.info_text = trial_complete_message( - self.window, self.parameters) - self.display.draw_static() - self.window.flip() - - # Allow for some training data to be collected - core.wait(self.buffer_val) - self.write_offset_trigger() - - return self.file_save - - def write_trigger_data(self, timing: List[Tuple[str, float]], - first_run: bool) -> None: - """Write Trigger Data. - - Using the timing provided from the display and calibration information - from the data acquisition client, write trigger data in the correct - format. - """ - triggers = [] - if first_run: - assert self.display.first_stim_time, "First stim time not set" - for content_type, client in self.daq.clients_by_type.items(): - label = offset_label(content_type.name) - time = client.offset(self.display.first_stim_time - ) - self.display.first_stim_time - triggers.append(Trigger(label, TriggerType.OFFSET, time)) - - target = timing[0][0] - triggers.extend(convert_timing_triggers(timing, target, trigger_type)) - self.trigger_handler.add_triggers(triggers) - - def write_offset_trigger(self) -> None: - """Append an offset value to the end of the trigger file.""" - assert self.display.first_stim_time, "First stim time not set" - triggers = [] - for content_type, client in self.daq.clients_by_type.items(): - label = offset_label(content_type.name, prefix='daq_sample_offset') - time = client.offset(self.display.first_stim_time) - triggers.append(Trigger(label, TriggerType.SYSTEM, time)) - - self.trigger_handler.add_triggers(triggers) - self.trigger_handler.close() - - def write_session_data(self) -> None: - """Save session data to disk.""" - if self.session: - session_file = _save_session_related_data( - f"{self.file_save}/{SESSION_DATA_FILENAME}", - self.session.as_dict()) - session_file.close() - - def update_session_data(self, inquiry: List[Union[List[str], - str]]) -> None: - """Adds the inquiry to the session data and writes to disk. - - Parameters - ---------- - inquiry - list of target, fixation, and sublists representing each - vep box and its content symbols. - """ - target_letter, _fixation, *boxes = inquiry - assert isinstance(target_letter, str), "unexpected inquiry format" - - target_box = None - for i, box in enumerate(boxes): - if target_letter in box: - target_box = i - + def session_inquiry_data(self, + inquiry: Inquiry) -> Optional[Dict[str, Any]]: + """Defines task-specific session data for each inquiry.""" + target_box = target_box_index(inquiry) target_freq = self.display.flicker_rates[ target_box] if target_box is not None else None - - task_data = { + return { 'target_box_index': target_box, 'target_frequency': target_freq } + def stim_labels(self, inquiry: Inquiry) -> List[str]: + """labels for each stimuli in the session data.""" + target_box = target_box_index(inquiry) targetness = [TriggerType.NONTARGET for _ in range(self.num_boxes)] if target_box is not None: targetness[target_box] = TriggerType.TARGET - trg_types = [TriggerType.PROMPT, TriggerType.FIXATION, *targetness] + labels = [TriggerType.PROMPT, TriggerType.FIXATION, *targetness] + return list(map(str, labels)) - data = Inquiry(stimuli=inquiry, - timing=[], - triggers=[], - target_info=list(map(str, trg_types)), - target_letter=target_letter, - task_data=task_data) - self.session.add_sequence(data) - self.session.total_time_spent = self.experiment_clock.getTime( - ) - self.start_time - self.write_session_data() - def name(self): - return 'VEP Calibration Task' +def target_box_index(inquiry: Inquiry) -> Optional[int]: + """Index of the target box.""" + target_letter, _fixation, *boxes = inquiry.stimuli + for i, box in enumerate(boxes): + if target_letter in box: + return i + return None -def init_calibration_display(parameters: Parameters, window: visual.Window, - experiment_clock: Clock, symbol_set: List[str], - timing: List[float], - colors: List[str]) -> VEPDisplay: +def init_vep_display(parameters: Parameters, window: visual.Window, + experiment_clock: Clock, symbol_set: List[str], + box_colors: List[str]) -> VEPDisplay: """Initialize the display""" info = InformationProperties( info_color=[parameters['info_color']], @@ -300,6 +129,13 @@ def init_calibration_display(parameters: Parameters, window: visual.Window, layout = centered(width_pct=0.95, height_pct=0.80) box_config = BoxConfiguration(layout, height_pct=0.30) + timing = [ + parameters['time_prompt'], parameters['time_fixation'], + parameters['time_flash'] + ] + colors = [ + parameters['target_color'], parameters['fixation_color'], *box_colors + ] stim_props = VEPStimuliProperties( stim_font=parameters['font'], stim_pos=box_config.positions, From 10f91c4409089a4d8a25b9523a945d9094793598 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 11 Jun 2024 17:12:31 -0700 Subject: [PATCH 262/330] Linting --- bcipy/task/base_calibration.py | 2 +- bcipy/task/paradigm/rsvp/calibration/calibration.py | 1 - 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index 9d042bd01..e62dd5904 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -174,7 +174,7 @@ def present_inquiry(self, index: int, ---------- - index : current index - inquiry : next sequence of stimuli to present. - + Returns ------- List of stim_times (tuples representing the stimulus and time that diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 816b04e59..9155b611a 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -44,7 +44,6 @@ def trigger_type(self, symbol: str, target: str, return TriggerType.TARGET return TriggerType.NONTARGET - def init_display(self) -> Display: return init_calibration_display_task(self.parameters, self.window, self.static_clock, From c8fa778fafc1e2a561d330329e643560b85c786f Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 26 Jun 2024 10:19:05 -0700 Subject: [PATCH 263/330] Refactor InquirySchedule iterator to retain expected properties of a NamedTuple --- bcipy/helpers/stimuli.py | 4 +++- bcipy/task/base_calibration.py | 4 ++-- bcipy/task/paradigm/vep/calibration.py | 2 +- 3 files changed, 6 insertions(+), 4 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index b33b928fb..7bd6b4a68 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -94,7 +94,9 @@ def count(self) -> int: """Number of stimuli""" return len(self.stimuli) - def __iter__(self): + def inquiries(self) -> Iterator[Tuple]: + """Generator that iterates through each Inquiry. Yields tuples of + (stim, duration, color).""" count = self.count index = 0 while index < count: diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index e62dd5904..eaf8b7f71 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -137,7 +137,7 @@ def init_inquiry_generator(self) -> Iterator[Inquiry]: parameters['target_color'], parameters['fixation_color'], parameters['stim_color'] ]) - return (Inquiry(*inq) for inq in schedule) + return (Inquiry(*inq) for inq in schedule.inquiries()) def init_session(self) -> session_data.Session: """Initialize the session data.""" @@ -225,7 +225,7 @@ def execute(self) -> str: timing = self.present_inquiry(inq_index, inquiry) # Write triggers for the inquiry - self.write_trigger_data(timing, first_run=inq_index == 0) + self.write_trigger_data(timing, inq_index == 0) self.add_session_data(inquiry) # Wait for a time diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 1119f7422..b3f15d325 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -64,7 +64,7 @@ def init_inquiry_generator(self) -> Iterator[Inquiry]: ], inquiry_count=parameters['stim_number'], num_boxes=self.num_boxes) - return (Inquiry(*inq) for inq in schedule) + return (Inquiry(*inq) for inq in schedule.inquiries()) def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: From 18ebe1e3b09b6701f84f3c29fb6cbc94bbe062a8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 26 Jun 2024 10:19:37 -0700 Subject: [PATCH 264/330] Refactor unit tests for matrix calibration --- .../matrix/test_matrix_calibration.py | 302 ++++++++++-------- 1 file changed, 176 insertions(+), 126 deletions(-) diff --git a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py index f9bd4b24f..0ab9c8081 100644 --- a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py +++ b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py @@ -1,10 +1,11 @@ import unittest +from unittest.mock import Mock, patch import numpy as np import psychopy -from mock import mock_open, patch from mockito import any, mock, unstub, verify, when +import bcipy.task.base_calibration import bcipy.task.paradigm.matrix.calibration from bcipy.acquisition import LslAcquisitionClient from bcipy.acquisition.devices import DeviceSpec @@ -83,16 +84,15 @@ def setUp(self): 'offset': lambda x: 0.0, }, spec=LslAcquisitionClient) - self.daq = mock( - { - 'device_spec': device_spec, - 'is_calibrated': True, - 'offset': lambda x: 0.0, - 'device_content_types': [ContentType.EEG], - 'clients_by_type': { - ContentType.EEG: self.eeg_client_mock - } - }) + self.daq = mock({ + 'device_spec': device_spec, + 'is_calibrated': True, + 'offset': lambda x: 0.0, + 'device_content_types': [ContentType.EEG], + 'clients_by_type': { + ContentType.EEG: self.eeg_client_mock + } + }) self.temp_dir = '' self.model_metadata = mock({ 'device_spec': device_spec, @@ -102,216 +102,266 @@ def setUp(self): self.display = mock() self.display.first_stim_time = 0.0 - self.mock_do_inquiry_response = [('a', 0.0), ('+', 0.1), ('b', 0.2), ('c', 0.3), ('a', 0.4)] - when(self.display).do_inquiry().thenReturn(self.mock_do_inquiry_response) + self.display.stim_positions = {'a': (0, 0), 'b': (0, 1)} + self.mock_do_inquiry_response = [('a', 0.0), ('+', 0.1), ('b', 0.2), + ('c', 0.3), ('a', 0.4)] + when(self.display).do_inquiry().thenReturn( + self.mock_do_inquiry_response) when(self.display).wait_screen().thenReturn(None) - when(bcipy.task.paradigm.matrix.calibration).init_calibration_display_task( + when(bcipy.task.paradigm.matrix.calibration).init_matrix_display( self.parameters, self.win, any(), any()).thenReturn(self.display) - when(bcipy.task.paradigm.matrix.calibration).trial_complete_message(any(), any()).thenReturn([]) - + # when(bcipy.task.paradigm.matrix.calibration).trial_complete_message(any(), any()).thenReturn([]) + when( + bcipy.task.paradigm.matrix.calibration).save_stimuli_position_info( + any(), any(), any()).thenReturn(None) when(TriggerHandler).add_triggers(any()).thenReturn() when(psychopy.event).getKeys(keyList=['space', 'escape'], modifiers=False, timeStamped=False).thenReturn(['space']) - when(psychopy.event).getKeys(keyList=['space', 'escape']).thenReturn(['space']) + when(psychopy.event).getKeys(keyList=['space', 'escape']).thenReturn( + ['space']) when(psychopy.core).wait(any()).thenReturn(None) def tearDown(self): """Override""" unstub() - def test_initialize(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_initialize(self, save_session_mock, trigger_handler_mock): """Test initialization""" + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) - verify(bcipy.task.paradigm.matrix.calibration, times=1).init_calibration_display_task( - self.parameters, self.win, any(), any()) + verify(bcipy.task.paradigm.matrix.calibration, + times=1).init_matrix_display(self.parameters, self.win, any(), + any()) - def test_execute(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_execute(self, save_session_mock, trigger_handler_mock): """Test task execute""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) - - when(task).write_stimuli_positions().thenReturn(None) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + when(task).write_offset_trigger().thenReturn(None) when(task).write_trigger_data(any(), any()).thenReturn(None) + when(task).write_session_data().thenReturn(None) + when(task).exit_display().thenReturn(None) task.execute() verify(self.display, times=self.parameters['stim_number']).do_inquiry() - verify(task, times=self.parameters['stim_number']).write_trigger_data(any(), any()) + verify(task, times=self.parameters['stim_number']).write_trigger_data( + any(), any()) verify(task, times=1).write_offset_trigger() - def test_validate_parameters_throws_task_exception_empty_parameter(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_validate_parameters_throws_task_exception_empty_parameter( + self, save_session_mock, trigger_handler_mock): """Test validate parameters throws task exception when parameters is empty.""" + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() parameters = {} with self.assertRaises(Exception): - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=parameters, - file_save=self.temp_dir) - - def test_execute_save_stimuli_positions(self): + MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=parameters, + file_save=self.temp_dir) + + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_execute_save_stimuli_positions(self, save_session_mock, + trigger_handler_mock): """Test execute save stimuli positions method is called as expected.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) - - when(bcipy.task.paradigm.matrix.calibration).save_stimuli_position_info( - any(), any(), task.screen_info).thenReturn(None) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + when(task).write_offset_trigger().thenReturn(None) when(task).write_trigger_data(any(), any()).thenReturn(None) + when(task).write_session_data().thenReturn(None) + when(task).exit_display().thenReturn(None) task.execute() + verify(bcipy.task.paradigm.matrix.calibration, + times=1).save_stimuli_position_info(any(), any(), + task.screen_info) - verify(bcipy.task.paradigm.matrix.calibration, times=1).save_stimuli_position_info( - any(), any(), task.screen_info) verify(self.display, times=self.parameters['stim_number']).do_inquiry() - verify(task, times=self.parameters['stim_number']).write_trigger_data(any(), any()) + verify(task, times=self.parameters['stim_number']).write_trigger_data( + any(), any()) verify(task, times=1).write_offset_trigger() - def test_trigger_type_targetness(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_trigger_type_targetness(self, save_session_mock, + trigger_handler_mock): """Test trigger type targetness.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) # non-target symbol = 'N' target = 'X' index = 1 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.NONTARGET) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.NONTARGET) # target symbol = 'X' target = 'X' index = 1 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.TARGET) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.TARGET) - def test_trigger_type_fixation(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_trigger_type_fixation(self, save_session_mock, + trigger_handler_mock): """Test trigger type fixation.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) # fixation symbol = '+' target = 'X' index = 1 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.FIXATION) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.FIXATION) - def test_trigger_type_prompt(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_trigger_type_prompt(self, save_session_mock, + trigger_handler_mock): """Test trigger type prompt.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) # prompt, index = 0, otherwise it would be a target symbol = 'P' target = 'P' index = 0 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PROMPT) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.PROMPT) - def test_write_trigger_data_first_run(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_write_trigger_data_first_run(self, save_session_mock, + trigger_handler_mock): """Test write trigger data when it is the first run of the task.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + handler_mock = Mock() + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = handler_mock + + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} timing_mock = mock() timing = [('a', 0.0)] first_run = True - when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.paradigm.matrix.calibration).offset_label('EEG').thenReturn('starting_offset') - when(bcipy.task.paradigm.matrix.calibration).convert_timing_triggers( + when(self.daq).client_by_type( + ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.base_calibration).offset_label('EEG').thenReturn( + 'starting_offset') + when(bcipy.task.base_calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) + self.assertEqual(2, handler_mock.add_triggers.call_count) - verify(TriggerHandler, times=2).add_triggers(any()) verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.paradigm.matrix.calibration, times=1).offset_label( - 'EEG') - verify(bcipy.task.paradigm.matrix.calibration, times=1).convert_timing_triggers( - timing, timing[0][0], any()) - - def test_write_trigger_data_not_first_run(self): + verify(bcipy.task.base_calibration, times=1).offset_label('EEG') + verify(bcipy.task.base_calibration, + times=1).convert_timing_triggers(timing, timing[0][0], any()) + + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_write_trigger_data_not_first_run(self, save_session_mock, + trigger_handler_mock): """Test write trigger data when it is not the first run of the task.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + handler_mock = Mock() + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = handler_mock + + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) timing_mock = mock() timing = [('a', 0.0)] first_run = False - when(bcipy.task.paradigm.matrix.calibration).convert_timing_triggers( + when(bcipy.task.base_calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) + handler_mock.add_triggers.assert_called_once() - verify(TriggerHandler, times=1).add_triggers(any()) - - def test_write_offset_trigger(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_write_offset_trigger(self, save_session_mock, + trigger_handler_mock): """Test write offset trigger""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = MatrixCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + handler_mock = Mock() + trigger_handler_mock.return_value = handler_mock + + task = MatrixCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} - when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.paradigm.matrix.calibration).offset_label( - 'EEG', - prefix='daq_sample_offset').thenReturn('daq_sample_offset') - - when(TriggerHandler).close().thenReturn() + when(self.daq).client_by_type( + ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.base_calibration).offset_label( + 'EEG', prefix='daq_sample_offset').thenReturn('daq_sample_offset') task.write_offset_trigger() - - verify(TriggerHandler, times=1).close() - verify(TriggerHandler, times=1).add_triggers(any()) + handler_mock.close.assert_called_once() + handler_mock.add_triggers.assert_called_once() verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.paradigm.matrix.calibration, times=1).offset_label( - 'EEG', prefix='daq_sample_offset') + verify(bcipy.task.base_calibration, + times=1).offset_label('EEG', prefix='daq_sample_offset') if __name__ == '__main__': From cca8366f04730d594a32899154c5c94105bc346e Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 26 Jun 2024 11:33:13 -0700 Subject: [PATCH 265/330] Refactor RSVP calibration unit tests --- .../rsvp/calibration/test_rsvp_calibration.py | 297 ++++++++++-------- 1 file changed, 169 insertions(+), 128 deletions(-) diff --git a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py index 8f6f10f52..f2dda084d 100644 --- a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py +++ b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py @@ -1,7 +1,7 @@ import unittest +from unittest.mock import Mock, patch import psychopy -from mock import mock_open, patch from mockito import any, mock, unstub, verify, when import bcipy.task.paradigm.rsvp.calibration.calibration @@ -82,16 +82,15 @@ def setUp(self): 'offset': lambda x: 0.0, }, spec=LslAcquisitionClient) - self.daq = mock( - { - 'device_spec': device_spec, - 'is_calibrated': True, - 'offset': lambda x: 0.0, - 'device_content_types': [ContentType.EEG], - 'clients_by_type': { - ContentType.EEG: self.eeg_client_mock - } - }) + self.daq = mock({ + 'device_spec': device_spec, + 'is_calibrated': True, + 'offset': lambda x: 0.0, + 'device_content_types': [ContentType.EEG], + 'clients_by_type': { + ContentType.EEG: self.eeg_client_mock + } + }) self.temp_dir = '' self.model_metadata = mock({ 'device_spec': device_spec, @@ -101,212 +100,254 @@ def setUp(self): self.display = mock() self.display.first_stim_time = 0.0 - self.mock_do_inquiry_response = [('a', 0.0), ('+', 0.1), ('b', 0.2), ('c', 0.3), ('a', 0.4)] - when(self.display).do_inquiry(preview_calibration=False).thenReturn(self.mock_do_inquiry_response) + self.mock_do_inquiry_response = [('a', 0.0), ('+', 0.1), ('b', 0.2), + ('c', 0.3), ('a', 0.4)] + when(self.display).do_inquiry(preview_calibration=False).thenReturn( + self.mock_do_inquiry_response) when(self.display).wait_screen().thenReturn(None) - when(bcipy.task.paradigm.rsvp.calibration.calibration).init_calibration_display_task( - self.parameters, self.win, any(), any()).thenReturn(self.display) - when(bcipy.task.paradigm.rsvp.calibration.calibration).trial_complete_message(any(), any()).thenReturn([]) - when(TriggerHandler).write().thenReturn() - when(TriggerHandler).add_triggers(any()).thenReturn() + when(bcipy.task.paradigm.rsvp.calibration.calibration + ).init_calibration_display_task(self.parameters, self.win, any(), + any()).thenReturn(self.display) + when(bcipy.task.base_calibration).trial_complete_message( + any(), any()).thenReturn([]) + when(bcipy.task.base_calibration.TriggerHandler).write().thenReturn() + when(bcipy.task.base_calibration.TriggerHandler).add_triggers( + any()).thenReturn() when(psychopy.event).getKeys(keyList=['space', 'escape'], modifiers=False, timeStamped=False).thenReturn(['space']) - when(psychopy.event).getKeys(keyList=['space', 'escape']).thenReturn(['space']) + when(psychopy.event).getKeys(keyList=['space', 'escape']).thenReturn( + ['space']) when(psychopy.core).wait(any()).thenReturn(None) def tearDown(self): """Override""" unstub() - def test_initialize(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_initialize(self, save_session_mock, trigger_handler_mock): """Test initialization""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) - - verify( - bcipy.task.paradigm.rsvp.calibration.calibration, - times=1).init_calibration_display_task( - self.parameters, - self.win, - any(), - any()) - - def test_execute(self): + + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + + RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + verify(bcipy.task.paradigm.rsvp.calibration.calibration, + times=1).init_calibration_display_task(self.parameters, + self.win, any(), any()) + + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_execute(self, save_session_mock, trigger_handler_mock): """Test task execute""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + when(task).write_offset_trigger().thenReturn(None) when(task).write_trigger_data(any(), any()).thenReturn(None) + when(task).write_session_data().thenReturn(None) + when(task).exit_display().thenReturn(None) task.execute() - verify(self.display, times=self.parameters['stim_number']).do_inquiry(preview_calibration=False) - verify(task, times=self.parameters['stim_number']).write_trigger_data(any(), any()) + verify(self.display, times=self.parameters['stim_number']).do_inquiry() + verify(task, times=self.parameters['stim_number']).write_trigger_data( + any(), any()) verify(task, times=1).write_offset_trigger() - def test_validate_parameters_throws_task_exception_empty_parameter(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_validate_parameters_throws_task_exception_empty_parameter( + self, save_session_mock, trigger_handler_mock): """Test validate parameters throws task exception when parameters is empty.""" parameters = {} - + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() with self.assertRaises(Exception): - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=parameters, - file_save=self.temp_dir) - - def test_trigger_type_targetness(self): + RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=parameters, + file_save=self.temp_dir) + + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_trigger_type_targetness(self, save_session_mock, + trigger_handler_mock): """Test trigger type targetness.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) # non-target symbol = 'N' target = 'X' index = 2 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.NONTARGET) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.NONTARGET) # target symbol = 'X' target = 'X' index = 1 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.TARGET) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.TARGET) - def test_trigger_type_fixation(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_trigger_type_fixation(self, save_session_mock, + trigger_handler_mock): """Test trigger type fixation.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) # fixation symbol = '+' target = 'X' index = 1 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.FIXATION) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.FIXATION) - def test_trigger_type_prompt(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_trigger_type_prompt(self, save_session_mock, + trigger_handler_mock): """Test trigger type prompt.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) # prompt, index = 0, otherwise it would be a target symbol = 'P' target = 'P' index = 0 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PROMPT) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.PROMPT) - def test_trigger_type_preview(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_trigger_type_preview(self, save_session_mock, + trigger_handler_mock): """Test trigger type preview.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = mock() + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) # preview, index > 0, otherwise it would be a prompt symbol = 'inquiry_preview' target = 'P' index = 1 - self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PREVIEW) + self.assertEqual(task.trigger_type(symbol, target, index), + TriggerType.PREVIEW) - def test_write_trigger_data_first_run(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_write_trigger_data_first_run(self, save_session_mock, + trigger_handler_mock): """Test write trigger data when it is the first run of the task.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + handler_mock = Mock() + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = handler_mock + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} timing_mock = mock() timing = [('a', 0.0)] first_run = True - when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.paradigm.rsvp.calibration.calibration).offset_label('EEG').thenReturn('starting_offset') - when(bcipy.task.paradigm.rsvp.calibration.calibration).convert_timing_triggers( + when(self.daq).client_by_type( + ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.base_calibration).offset_label('EEG').thenReturn( + 'starting_offset') + when(bcipy.task.base_calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) - verify(TriggerHandler, times=2).add_triggers(any()) + self.assertEqual(2, handler_mock.add_triggers.call_count) verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.paradigm.rsvp.calibration.calibration, times=1).offset_label( - 'EEG') - verify(bcipy.task.paradigm.rsvp.calibration.calibration, times=1).convert_timing_triggers( - timing, timing[0][0], any()) - - def test_write_trigger_data_not_first_run(self): + verify(bcipy.task.base_calibration, times=1).offset_label('EEG') + verify(bcipy.task.base_calibration, + times=1).convert_timing_triggers(timing, timing[0][0], any()) + + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_write_trigger_data_not_first_run(self, save_session_mock, + trigger_handler_mock): """Test write trigger data when it is not the first run of the task.""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + handler_mock = Mock() + save_session_mock.return_value = mock() + trigger_handler_mock.return_value = handler_mock + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) timing_mock = mock() timing = [('a', 0.0)] first_run = False - when(bcipy.task.paradigm.rsvp.calibration.calibration).convert_timing_triggers( + when(bcipy.task.base_calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) + handler_mock.add_triggers.assert_called_once() - verify(TriggerHandler, times=1).add_triggers(any()) - - def test_write_offset_trigger(self): + @patch('bcipy.task.base_calibration.TriggerHandler') + @patch('bcipy.task.base_calibration._save_session_related_data') + def test_write_offset_trigger(self, save_session_mock, + trigger_handler_mock): """Test write offset trigger""" - with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): - task = RSVPCalibrationTask( - win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + save_session_mock.return_value = mock() + handler_mock = Mock() + trigger_handler_mock.return_value = handler_mock + task = RSVPCalibrationTask(win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} - when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.paradigm.rsvp.calibration.calibration).offset_label( - 'EEG', - prefix='daq_sample_offset').thenReturn('daq_sample_offset') + when(self.daq).client_by_type( + ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.base_calibration).offset_label( + 'EEG', prefix='daq_sample_offset').thenReturn('daq_sample_offset') when(TriggerHandler).close().thenReturn() task.write_offset_trigger() - - verify(TriggerHandler, times=1).close() - verify(TriggerHandler, times=1).add_triggers(any()) + handler_mock.close.assert_called_once() + handler_mock.add_triggers.assert_called_once() verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.paradigm.rsvp.calibration.calibration, times=1).offset_label( - 'EEG', prefix='daq_sample_offset') + verify(bcipy.task.base_calibration, + times=1).offset_label('EEG', prefix='daq_sample_offset') if __name__ == '__main__': From 8e32c5e858956f2a0b4bce2d6c213589bc9cb80c Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 27 Jun 2024 14:24:42 -0700 Subject: [PATCH 266/330] Fixed typing issues and linting --- bcipy/display/main.py | 4 +++- bcipy/display/paradigm/rsvp/display.py | 21 +++++++------------ bcipy/helpers/stimuli.py | 7 +------ bcipy/task/paradigm/matrix/calibration.py | 7 +++++-- bcipy/task/paradigm/vep/calibration.py | 2 ++ .../matrix/test_matrix_calibration.py | 9 ++++++-- .../rsvp/calibration/test_rsvp_calibration.py | 2 +- 7 files changed, 27 insertions(+), 25 deletions(-) diff --git a/bcipy/display/main.py b/bcipy/display/main.py index c87cb12e0..793f21774 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -23,9 +23,11 @@ class Display(ABC): stimuli_colors: List[str] = None stimuli_timing: List[float] = None task = None + info_text: List[Any] = None + first_stim_time: float = None @abstractmethod - def do_inquiry(self) -> List[float]: + def do_inquiry(self) -> List[Tuple[str, float]]: """Do inquiry. Animates an inquiry of stimuli and returns a list of stimuli trigger timing. diff --git a/bcipy/display/paradigm/rsvp/display.py b/bcipy/display/paradigm/rsvp/display.py index 9813d5ade..25bc577f8 100644 --- a/bcipy/display/paradigm/rsvp/display.py +++ b/bcipy/display/paradigm/rsvp/display.py @@ -1,22 +1,17 @@ import logging import os.path as path -from typing import Optional, List, Tuple +from typing import List, Optional, Tuple -from psychopy import core, visual, event +from psychopy import core, event, visual -from bcipy.helpers.clock import Clock -from bcipy.helpers.task import get_key_press -from bcipy.helpers.symbols import SPACE_CHAR -from bcipy.display import ( - BCIPY_LOGO_PATH, - Display, - InformationProperties, - PreviewInquiryProperties, - StimuliProperties -) +from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, + PreviewInquiryProperties, StimuliProperties) from bcipy.display.components.task_bar import TaskBar +from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import resize_image +from bcipy.helpers.symbols import SPACE_CHAR from bcipy.helpers.system_utils import get_screen_info +from bcipy.helpers.task import get_key_press from bcipy.helpers.triggers import TriggerCallback, _calibration_trigger @@ -131,7 +126,7 @@ def schedule_to(self, self.stimuli_timing = timing or [] self.stimuli_colors = colors or [] - def do_inquiry(self, preview_calibration: bool = False) -> List[float]: + def do_inquiry(self, preview_calibration: bool = False) -> List[Tuple[str, float]]: """Do inquiry. Animates an inquiry of flashing letters to achieve RSVP. diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 7bd6b4a68..567e2d8ef 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -89,15 +89,10 @@ class InquirySchedule(NamedTuple): durations: Union[List[List[float]], List[float]] colors: Union[List[List[str]], List[str]] - @property - def count(self) -> int: - """Number of stimuli""" - return len(self.stimuli) - def inquiries(self) -> Iterator[Tuple]: """Generator that iterates through each Inquiry. Yields tuples of (stim, duration, color).""" - count = self.count + count = len(self.stimuli) index = 0 while index < count: yield (self.stimuli[index], self.durations[index], diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index 58f939213..6014fbafe 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -2,7 +2,7 @@ from psychopy import core, visual -from bcipy.display import Display, InformationProperties, StimuliProperties +from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.helpers.clock import Clock @@ -43,22 +43,25 @@ def screen_info(self) -> Dict[str, Any]: 'screen_units': 'norm', } - def init_display(self) -> Display: + def init_display(self) -> MatrixDisplay: """Initialize the display""" return init_matrix_display(self.parameters, self.window, self.experiment_clock, self.symbol_set) def exit_display(self) -> None: + assert isinstance(self.display, MatrixDisplay) self.display.capture_grid_screenshot(self.file_save) return super().exit_display() def cleanup(self) -> None: + assert isinstance(self.display, MatrixDisplay) # TODO: refactor offline_analysis to use session data and and remove this. save_stimuli_position_info(self.display.stim_positions, self.file_save, self.screen_info) return super().cleanup() def session_task_data(self) -> Optional[Dict[str, Any]]: + assert isinstance(self.display, MatrixDisplay) return {**self.display.stim_positions, **self.screen_info} diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index b3f15d325..e291a6121 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -74,6 +74,7 @@ def trigger_type(self, symbol: str, target: str, def session_task_data(self) -> Dict[str, Any]: """Task-specific session data""" + assert isinstance(self.display, VEPDisplay) boxes = [{ "colors": box.colors, "flicker_rate": self.display.flicker_rates[i], @@ -87,6 +88,7 @@ def session_task_data(self) -> Dict[str, Any]: def session_inquiry_data(self, inquiry: Inquiry) -> Optional[Dict[str, Any]]: """Defines task-specific session data for each inquiry.""" + assert isinstance(self.display, VEPDisplay) target_box = target_box_index(inquiry) target_freq = self.display.flicker_rates[ target_box] if target_box is not None else None diff --git a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py index 0ab9c8081..a72faa29a 100644 --- a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py +++ b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py @@ -10,6 +10,7 @@ from bcipy.acquisition import LslAcquisitionClient from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.multimodal import ContentType +from bcipy.display.paradigm.matrix import MatrixDisplay from bcipy.helpers.parameters import Parameters from bcipy.helpers.triggers import TriggerHandler, TriggerType from bcipy.task.paradigm.matrix.calibration import MatrixCalibrationTask @@ -100,14 +101,18 @@ def setUp(self): 'evidence_type': 'ERP' }) - self.display = mock() + self.display = mock(spec=MatrixDisplay) self.display.first_stim_time = 0.0 self.display.stim_positions = {'a': (0, 0), 'b': (0, 1)} self.mock_do_inquiry_response = [('a', 0.0), ('+', 0.1), ('b', 0.2), ('c', 0.3), ('a', 0.4)] when(self.display).do_inquiry().thenReturn( self.mock_do_inquiry_response) - when(self.display).wait_screen().thenReturn(None) + # Shouldn't have to mock all these, but otherwise throws an AttributeError. + when(self.display).wait_screen(any, any).thenReturn(None) + when(self.display).update_task_bar(any).thenReturn(None) + when(self.display).draw_static().thenReturn(None) + when(self.display).schedule_to(any, any, any).thenReturn(None) when(bcipy.task.paradigm.matrix.calibration).init_matrix_display( self.parameters, self.win, any(), any()).thenReturn(self.display) diff --git a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py index f2dda084d..24031d05f 100644 --- a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py +++ b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py @@ -104,7 +104,7 @@ def setUp(self): ('c', 0.3), ('a', 0.4)] when(self.display).do_inquiry(preview_calibration=False).thenReturn( self.mock_do_inquiry_response) - when(self.display).wait_screen().thenReturn(None) + when(self.display).wait_screen(any, any).thenReturn(None) when(bcipy.task.paradigm.rsvp.calibration.calibration ).init_calibration_display_task(self.parameters, self.win, any(), From 7c2418878ecdfdcd371c93593ff3eaed91b98251 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 27 Jun 2024 14:47:48 -0700 Subject: [PATCH 267/330] Updated comments --- bcipy/task/base_calibration.py | 1 - 1 file changed, 1 deletion(-) diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index eaf8b7f71..4cb018479 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -26,7 +26,6 @@ class Inquiry(NamedTuple): """Represents a single Inquiry""" - # TODO: types should also work for VEP stimuli: List[str] durations: List[float] colors: List[str] From 4ebbb7c3d4f494a65f5ea4fb89a79f982c83a4d0 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 3 Jul 2024 13:31:03 -0700 Subject: [PATCH 268/330] Added documentation --- bcipy/task/base_calibration.py | 12 ++++++++++-- 1 file changed, 10 insertions(+), 2 deletions(-) diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index 4cb018479..93db1d3e0 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -25,7 +25,12 @@ class Inquiry(NamedTuple): - """Represents a single Inquiry""" + """Represents a single Inquiry. + + stimuli - list of [target, fixation, *inquiry_symbols] + durations - duration in seconds to display each symbol + colors - color for each symbol + """ stimuli: List[str] durations: List[float] colors: List[str] @@ -100,6 +105,8 @@ def symbol_set(self) -> List[str]: def name(self) -> str: """Task name""" + if self.MODE == 'Undefined': + raise NotImplementedError return f"{self.MODE} Calibration Task" def wait(self, seconds: Optional[float] = None) -> None: @@ -155,7 +162,8 @@ def trigger_type(self, symbol: str, target: str, """Trigger Type. This method is passed to convert_timing_triggers to properly assign TriggerTypes - to the timing of stimuli presented. + to the timing of stimuli presented. The default implementation assumes an + inquiry with the shape [prompt, fixation, *symbols]. """ if index == 0: return TriggerType.PROMPT From 1df200c2073d91ef2e127d3d8717d6bd33c12838 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 10 Jul 2024 17:17:59 -0700 Subject: [PATCH 269/330] #187737714 ; refactor to configure static_offset per device --- bcipy/acquisition/devices.py | 17 +++++-- bcipy/acquisition/multimodal.py | 12 +++-- .../acquisition/tests/test_client_manager.py | 7 ++- bcipy/acquisition/tests/test_devices.py | 49 +++++++++++++++++-- bcipy/helpers/convert.py | 6 ++- bcipy/helpers/demo/demo_visualization.py | 11 +++-- bcipy/helpers/task.py | 7 ++- .../resources/mock_session/parameters.json | 8 --- bcipy/helpers/tests/test_convert.py | 17 ++++--- bcipy/helpers/visualization.py | 12 ++--- bcipy/parameters/devices.json | 15 ++++-- bcipy/parameters/parameters.json | 8 --- bcipy/signal/model/offline_analysis.py | 2 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 3 +- .../matrix/test_matrix_calibration.py | 1 - .../rsvp/calibration/test_rsvp_calibration.py | 1 - .../tests/paradigm/rsvp/test_copy_phrase.py | 1 - 17 files changed, 113 insertions(+), 64 deletions(-) diff --git a/bcipy/acquisition/devices.py b/bcipy/acquisition/devices.py index 4eb194df9..115b9c00c 100644 --- a/bcipy/acquisition/devices.py +++ b/bcipy/acquisition/devices.py @@ -16,6 +16,7 @@ 'float32', 'double64', 'string', 'int32', 'int16', 'int8' ] DEFAULT_DEVICE_TYPE = 'EEG' +DEFAULT_STATIC_OFFSET = 0.1 log = logging.getLogger(__name__) @@ -85,6 +86,12 @@ class DeviceSpec: see https://labstreaminglayer.readthedocs.io/projects/liblsl/ref/enums.html excluded_from_analysis - list of channels (label) to exclude from analysis. status - recording status + static_offset - Specifies the static trigger offset (in seconds) used to align + triggers properly with EEG data from LSL. The system includes built-in + offset correction, but there is still a hardware-limited offset between EEG + and trigger timing values for which the system does not account. The correct + value may be different for each computer, and must be determined on a + case-by-case basis. Default: 0.1", """ def __init__(self, @@ -95,7 +102,8 @@ def __init__(self, description: Optional[str] = None, excluded_from_analysis: Optional[List[str]] = None, data_type: str = 'float32', - status: DeviceStatus = DeviceStatus.ACTIVE): + status: DeviceStatus = DeviceStatus.ACTIVE, + static_offset: float = DEFAULT_STATIC_OFFSET): assert sample_rate >= 0, "Sample rate can't be negative." assert data_type in SUPPORTED_DATA_TYPES @@ -109,6 +117,7 @@ def __init__(self, self.excluded_from_analysis = excluded_from_analysis or [] self._validate_excluded_channels() self.status = status + self.static_offset = static_offset @property def channel_count(self) -> int: @@ -152,7 +161,8 @@ def to_dict(self) -> dict: 'sample_rate': self.sample_rate, 'description': self.description, 'excluded_from_analysis': self.excluded_from_analysis, - 'status': str(self.status) + 'status': str(self.status), + 'static_offset': self.static_offset } def __str__(self): @@ -188,7 +198,8 @@ def make_device_spec(config: dict) -> DeviceSpec: description=config['description'], excluded_from_analysis=config.get( 'excluded_from_analysis', []), - status=DeviceStatus.from_str(config.get('status', default_status))) + status=DeviceStatus.from_str(config.get('status', default_status)), + static_offset=config.get('static_offset', DEFAULT_STATIC_OFFSET)) def load(config_path: Path = Path(DEFAULT_CONFIG), replace: bool = False) -> Dict[str, DeviceSpec]: diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 7a29405bb..cf13a5613 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -131,7 +131,9 @@ def get_data_by_device( Parameters ---------- - start - start time (acquisition clock) of data window + start - start time (acquisition clock) of data window; NOTE: the + actual start time will be adjusted to by the static_offset + configured for each device. seconds - duration of data to return for each device content_types - specifies which devices to include; if not unspecified, data for all types is returned. @@ -144,10 +146,12 @@ def get_data_by_device( for content_type in content_types: name = content_type.name client = self.get_client(content_type) + + adjusted_start = start + client.device_spec.static_offset if client.device_spec.sample_rate > 0: count = round(seconds * client.device_spec.sample_rate) log.info(f'Need {count} records for processing {name} data') - output[content_type] = client.get_data(start=start, + output[content_type] = client.get_data(start=adjusted_start, limit=count) data_count = len(output[content_type]) if strict and data_count < count: @@ -155,8 +159,8 @@ def get_data_by_device( raise InsufficientDataException(msg) else: # Markers have an IRREGULAR_RATE. - output[content_type] = client.get_data(start=start, - end=start + seconds) + output[content_type] = client.get_data(start=adjusted_start, + end=adjusted_start + seconds) return output def cleanup(self): diff --git a/bcipy/acquisition/tests/test_client_manager.py b/bcipy/acquisition/tests/test_client_manager.py index 425008698..0d7065d75 100644 --- a/bcipy/acquisition/tests/test_client_manager.py +++ b/bcipy/acquisition/tests/test_client_manager.py @@ -15,6 +15,7 @@ def setUp(self): self.eeg_device_mock.content_type = 'EEG' self.eeg_device_mock.sample_rate = 300 self.eeg_device_mock.is_active = True + self.eeg_device_mock.static_offset = 0.1 self.eeg_client_mock = Mock() self.eeg_client_mock.device_spec = self.eeg_device_mock @@ -26,6 +27,7 @@ def setUp(self): self.gaze_device_mock.content_type = 'Eyetracker' self.gaze_device_mock.sample_rate = 60 self.gaze_device_mock.is_active = False + self.gaze_device_mock.static_offset = 0.0 self.gaze_client_mock = Mock() self.gaze_client_mock.device_spec = self.gaze_device_mock @@ -115,6 +117,7 @@ def test_get_data_by_device(self): switch_device_mock.name = 'Test-switch-2000' switch_device_mock.content_type = 'Markers' switch_device_mock.sample_rate = 0.0 + switch_device_mock.static_offset = 0.2 switch_client_mock = Mock() switch_client_mock.device_spec = switch_device_mock @@ -141,11 +144,11 @@ def test_get_data_by_device(self): ContentType.MARKERS ]) - self.eeg_client_mock.get_data.assert_called_once_with(start=100, + self.eeg_client_mock.get_data.assert_called_once_with(start=100.1, limit=1500) self.gaze_client_mock.get_data.assert_called_once_with(start=100, limit=300) - switch_client_mock.get_data.assert_called_with(start=100, end=105) + switch_client_mock.get_data.assert_called_with(start=100.2, end=105.2) self.assertTrue(ContentType.EEG in results) self.assertTrue(ContentType.EYETRACKER in results) diff --git a/bcipy/acquisition/tests/test_devices.py b/bcipy/acquisition/tests/test_devices.py index aedaea775..dc86980cd 100644 --- a/bcipy/acquisition/tests/test_devices.py +++ b/bcipy/acquisition/tests/test_devices.py @@ -57,6 +57,7 @@ def test_load_from_config(self): self.assertEqual(channels, spec.channels) self.assertEqual(devices.DeviceStatus.ACTIVE, spec.status) self.assertTrue(spec.is_active) + self.assertEqual(spec.static_offset, devices.DEFAULT_STATIC_OFFSET) self.assertEqual(spec, devices.preconfigured_device('DSI-VR300')) shutil.rmtree(temp_dir) @@ -222,9 +223,22 @@ def test_device_spec_to_dict(self): """DeviceSpec should be able to be converted to a dictionary.""" device_name = 'TestDevice' channels = ['C1', 'C2', 'C3'] - expected_channel_output = [{'label': 'C1', 'name': 'C1', 'type': None, 'units': None}, - {'label': 'C2', 'name': 'C2', 'type': None, 'units': None}, - {'label': 'C3', 'name': 'C3', 'type': None, 'units': None}] + expected_channel_output = [{ + 'label': 'C1', + 'name': 'C1', + 'type': None, + 'units': None + }, { + 'label': 'C2', + 'name': 'C2', + 'type': None, + 'units': None + }, { + 'label': 'C3', + 'name': 'C3', + 'type': None, + 'units': None + }] sample_rate = 256.0 content_type = 'EEG' spec = devices.DeviceSpec(name=device_name, @@ -238,6 +252,8 @@ def test_device_spec_to_dict(self): self.assertEqual(expected_channel_output, spec_dict['channels']) self.assertEqual(sample_rate, spec_dict['sample_rate']) self.assertEqual('passive', spec_dict['status']) + self.assertEqual(spec_dict['static_offset'], + devices.DEFAULT_STATIC_OFFSET) def test_load_status(self): """Should be able to load a list of supported devices from a @@ -259,7 +275,32 @@ def test_load_status(self): devices.load(config_path, replace=True) supported = devices.preconfigured_devices() - self.assertEqual(devices.DeviceStatus.PASSIVE, supported['MyDevice'].status) + self.assertEqual(devices.DeviceStatus.PASSIVE, + supported['MyDevice'].status) + shutil.rmtree(temp_dir) + + def test_load_static_offset(self): + """Loaded device should support using a custom static offset.""" + + # create a config file in a temp location. + temp_dir = tempfile.mkdtemp() + offset = 0.2 + my_devices = [ + dict(name="MyDevice", + content_type="EEG", + description="My Device", + channels=["a", "b", "c"], + sample_rate=100.0, + status=str(devices.DeviceStatus.PASSIVE), + static_offset=offset) + ] + config_path = Path(temp_dir, 'my_devices.json') + with open(config_path, 'w', encoding=DEFAULT_ENCODING) as config_file: + json.dump(my_devices, config_file) + + devices.load(config_path, replace=True) + supported = devices.preconfigured_devices() + self.assertEqual(supported['MyDevice'].static_offset, offset) shutil.rmtree(temp_dir) def test_device_status(self): diff --git a/bcipy/helpers/convert.py b/bcipy/helpers/convert.py index 409a40f3d..1b365f9ea 100644 --- a/bcipy/helpers/convert.py +++ b/bcipy/helpers/convert.py @@ -4,7 +4,7 @@ import os import tarfile from pathlib import Path -from typing import Dict, List, Tuple, Optional, Union +from typing import Dict, List, Optional, Tuple, Union import mne import numpy as np @@ -12,6 +12,7 @@ from pyedflib import FILETYPE_BDFPLUS, FILETYPE_EDFPLUS, EdfWriter from tqdm import tqdm +from bcipy.acquisition.devices import preconfigured_device from bcipy.config import (DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME) from bcipy.helpers.load import load_json_parameters, load_raw_data @@ -177,6 +178,7 @@ def pyedf_convert(data_dir: str, value_cast=True) data = load_raw_data(str(Path(data_dir, f'{RAW_DATA_FILENAME}.csv'))) fs = data.sample_rate + device_spec = preconfigured_device(data.daq_type) if pre_filter: default_transform = get_default_transform( sample_rate_hz=data.sample_rate, @@ -194,7 +196,7 @@ def pyedf_convert(data_dir: str, else: raw_data, _ = data.by_channel() durations = trigger_durations(params) if use_event_durations else {} - static_offset = params['static_trigger_offset'] + static_offset = device_spec.static_offset logger.info(f'Static offset: {static_offset}') trigger_type, trigger_timing, trigger_label = trigger_decoder( diff --git a/bcipy/helpers/demo/demo_visualization.py b/bcipy/helpers/demo/demo_visualization.py index 05e7cfe61..8c08701b9 100644 --- a/bcipy/helpers/demo/demo_visualization.py +++ b/bcipy/helpers/demo/demo_visualization.py @@ -44,7 +44,8 @@ if not path: path = load_experimental_data() - parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) + parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', + value_cast=True) # extract all relevant parameters trial_window = parameters.get("trial_window", (0, 0.5)) @@ -59,12 +60,16 @@ filter_high = parameters.get("filter_high") filter_low = parameters.get("filter_low") filter_order = parameters.get("filter_order") - static_offset = parameters.get("static_trigger_offset") + raw_data = load_raw_data(Path(path, f'{RAW_DATA_FILENAME}.csv')) channels = raw_data.channels type_amp = raw_data.daq_type sample_rate = raw_data.sample_rate + devices.load(Path(path, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(raw_data.daq_type) + static_offset = device_spec.static_offset + # setup filtering default_transform = get_default_transform( sample_rate_hz=sample_rate, @@ -82,8 +87,6 @@ ) labels = [0 if label == 'nontarget' else 1 for label in trigger_targetness] - devices.load(Path(path, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) channel_map = analysis_channels(channels, device_spec) save_path = None if not args.save else path diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index 01a2fa018..1984bd1a4 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -180,7 +180,6 @@ def get_data_for_decision(inquiry_timing: List[Tuple[str, float]], def get_device_data_for_decision( inquiry_timing: List[Tuple[str, float]], daq: ClientManager, - offset: float = 0.0, prestim: float = 0.0, poststim: float = 0.0) -> Dict[ContentType, List[Record]]: """Queries the acquisition client manager for a slice of data from each @@ -206,13 +205,13 @@ def get_device_data_for_decision( _, last_stim_time = inquiry_timing[-1] # adjust for offsets - time1 = first_stim_time + offset - prestim - time2 = last_stim_time + offset + time1 = first_stim_time - prestim + time2 = last_stim_time if time2 < time1: raise InsufficientDataException( f'Invalid data query [{time1}-{time2}] with parameters:' - f'[inquiry={inquiry_timing}, offset={offset}, prestim={prestim}, poststim={poststim}]' + f'[inquiry={inquiry_timing}, prestim={prestim}, poststim={poststim}]' ) data = daq.get_data_by_device(start=time1, diff --git a/bcipy/helpers/tests/resources/mock_session/parameters.json b/bcipy/helpers/tests/resources/mock_session/parameters.json index ab56fd55b..f9fcf37d6 100644 --- a/bcipy/helpers/tests/resources/mock_session/parameters.json +++ b/bcipy/helpers/tests/resources/mock_session/parameters.json @@ -58,14 +58,6 @@ ], "type": "str" }, - "static_trigger_offset": { - "value": ".1", - "section": "bci_config", - "readableName": "Static Trigger Offset", - "helpTip": "Specifies the static trigger offset (in seconds) used to align triggers properly with EEG data from LSL. The system includes built-in offset correction, but there is still a hardware-limited offset between EEG and trigger timing values for which the system does not account. The default value of 0.1 has been verified for OHSU hardware. The correct value may be different for other computers, and must be determined on a case-by-case basis. Default: .1", - "recommended_values": "", - "type": "float" - }, "k_folds": { "value": "10", "section": "signal_config", diff --git a/bcipy/helpers/tests/test_convert.py b/bcipy/helpers/tests/test_convert.py index fc31a184e..83399279a 100644 --- a/bcipy/helpers/tests/test_convert.py +++ b/bcipy/helpers/tests/test_convert.py @@ -11,6 +11,7 @@ from mockito import any as any_value from mockito import mock, unstub, verify, verifyNoMoreInteractions, when +import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_ENCODING, DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME) from bcipy.helpers import convert @@ -33,8 +34,7 @@ def create_bcipy_session_artifacts( 'filter_high': 30, 'filter_order': 5, 'notch_filter_frequency': 60, - 'down_sampling_rate': 3, - 'static_trigger_offset': 0.0 + 'down_sampling_rate': 3 }, ) -> Tuple[str, RawData, Parameters]: """Write BciPy session artifacts to a temporary directory. @@ -44,7 +44,9 @@ def create_bcipy_session_artifacts( trg_data = MOCK_TRIGGER_DATA if isinstance(channels, int): channels = [f'ch{i}' for i in range(channels)] - data = sample_data(ch_names=channels, sample_rate=sample_rate, rows=samples) + data = sample_data(ch_names=channels, daq_type='SampleDevice', sample_rate=sample_rate, rows=samples) + devices.register(devices.DeviceSpec('SampleDevice', channels=channels, sample_rate=sample_rate)) + with open(Path(write_dir, TRIGGER_FILENAME), 'w', encoding=DEFAULT_ENCODING) as trg_file: trg_file.write(trg_data) @@ -57,7 +59,6 @@ def create_bcipy_session_artifacts( time_prompt=0.5, time_flash=0.5, # define filter settings - static_trigger_offset=filter_settings['static_trigger_offset'], down_sampling_rate=filter_settings['down_sampling_rate'], notch_filter_frequency=filter_settings['notch_filter_frequency'], filter_high=filter_settings['filter_high'], @@ -348,8 +349,7 @@ def setUp(self) -> None: 'filter_high': 30, 'filter_order': 5, 'notch_filter_frequency': 60, - 'down_sampling_rate': 3, - 'static_trigger_offset': 0.0 + 'down_sampling_rate': 3 } create_bcipy_session_artifacts( self.temp_dir, @@ -476,11 +476,12 @@ def setUp(self): 'filter_high': 30, 'filter_order': 5, 'notch_filter_frequency': 60, - 'down_sampling_rate': 3, - 'static_trigger_offset': 0.0 + 'down_sampling_rate': 3 } self.channels = ['timestamp', 'O1', 'O2', 'Pz'] self.raw_data = RawData('SampleDevice', self.sample_rate, self.channels) + devices.register(devices.DeviceSpec('SampleDevice', channels=self.channels, sample_rate=self.sample_rate)) + # generate 100 random samples of data for _ in range(0, 100): channel_data = gen_random_data(low=-1000, diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index c8e9dfc45..46f394990 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -1,8 +1,8 @@ # mypy: disable-error-code="attr-defined,union-attr,arg-type" # needed for the ERPTransformParams import logging -from typing import List, Dict, Optional, Tuple, Union from pathlib import Path +from typing import Dict, List, Optional, Tuple, Union import matplotlib.pyplot as plt import mne @@ -16,12 +16,13 @@ from scipy import linalg import bcipy.acquisition.devices as devices -from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, RAW_DATA_FILENAME, - DEFAULT_GAZE_IMAGE_PATH, TRIGGER_FILENAME) +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_GAZE_IMAGE_PATH, RAW_DATA_FILENAME, + TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels -from bcipy.helpers.parameters import Parameters from bcipy.helpers.convert import convert_to_mne from bcipy.helpers.load import choose_csv_file, load_raw_data +from bcipy.helpers.parameters import Parameters from bcipy.helpers.raw_data import RawData from bcipy.helpers.stimuli import mne_epochs from bcipy.helpers.triggers import TriggerType, trigger_decoder @@ -684,7 +685,6 @@ def visualize_session_data(session_path: str, parameters: Union[dict, Parameters """ # extract all relevant parameters trial_window = parameters.get("trial_window") - static_offset = parameters.get("static_trigger_offset") raw_data = load_raw_data(str(Path(session_path, f'{RAW_DATA_FILENAME}.csv'))) channels = raw_data.channels @@ -707,7 +707,7 @@ def visualize_session_data(session_path: str, parameters: Union[dict, Parameters ) # Process triggers.txt files trigger_targetness, trigger_timing, _ = trigger_decoder( - offset=static_offset, + offset=device_spec.static_offset, trigger_path=f"{session_path}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], device_type='EEG', diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index c9254b966..b65624cf9 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -41,7 +41,8 @@ "F3", "F4", "C3", "C4" ], - "status": "active" + "status": "active", + "static_offset": 0.1 }, { "name": "DSI-VR300", @@ -59,7 +60,8 @@ "sample_rate": 300, "description": "Wearable Sensing DSI-VR300", "excluded_from_analysis": ["TRG", "F7"], - "status": "active" + "status": "active", + "static_offset": 0.1 }, { "name": "DSI-Flex", @@ -77,7 +79,8 @@ "sample_rate": 300.0, "description": "Wearable Sensing DSI-Flex", "excluded_from_analysis": ["TRG"], - "status": "active" + "status": "active", + "static_offset": 0.1 }, { "name": "g.USBamp-1", @@ -102,7 +105,8 @@ ], "sample_rate": 256, "description": "GTec g.USBamp", - "status": "active" + "status": "active", + "static_offset": 0.1 }, { "name": "Tobii Nano", @@ -120,6 +124,7 @@ "sample_rate": 60.0, "description": "Tobii Nano. For use with the Tobii Pro SDK.", "excluded_from_analysis": ["device_ts", "system_ts", "left_pupil", "right_pupil"], - "status": "active" + "status": "active", + "static_offset": 0.0 } ] \ No newline at end of file diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 46018a72a..36c088342 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -32,14 +32,6 @@ ], "type": "str" }, - "static_trigger_offset": { - "value": "0.1", - "section": "bci_config", - "readableName": "Static Trigger Offset", - "helpTip": "Specifies the static trigger offset (in seconds) used to align triggers properly with EEG data from LSL. The system includes built-in offset correction, but there is still a hardware-limited offset between EEG and trigger timing values for which the system does not account. The default value of 0.1 has been verified for OHSU hardware. The correct value may be different for other computers, and must be determined on a case-by-case basis. Default: 0.1", - "recommended_values": "", - "type": "float" - }, "k_folds": { "value": "10", "section": "signal_config", diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 9144dc7c0..1c26f335a 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -111,7 +111,7 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance # Get signal filtering information transform_params = parameters.instantiate(ERPTransformParams) downsample_rate = transform_params.down_sampling_rate - static_offset = parameters.get("static_trigger_offset") + static_offset = device_spec.static_offset log.info( f"\nData processing settings: \n" diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index cb3b44810..82640dd20 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -98,7 +98,7 @@ class RSVPCopyPhraseTask(Task): 'show_feedback', 'feedback_duration', 'show_preview_inquiry', 'preview_inquiry_isi', 'preview_inquiry_key_input', 'preview_inquiry_length', 'preview_inquiry_progress_method', - 'spelled_letters_count', 'static_trigger_offset', + 'spelled_letters_count', 'stim_color', 'stim_height', 'stim_jitter', 'stim_length', 'stim_number', 'stim_order', 'stim_pos_x', 'stim_pos_y', 'stim_space_char', 'target_color', 'task_buffer_length', 'task_color', 'task_height', 'task_text', @@ -599,7 +599,6 @@ def compute_device_evidence( device_data = get_device_data_for_decision( inquiry_timing=inquiry_timing, daq=self.daq, - offset=self.parameters['static_trigger_offset'], prestim=prestim_buffer, poststim=post_stim_buffer + window_length) diff --git a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py index a72faa29a..da0651efe 100644 --- a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py +++ b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py @@ -47,7 +47,6 @@ def setUp(self): 'preview_inquiry_length': 5.0, 'show_feedback': False, 'show_preview_inquiry': False, - 'static_trigger_offset': 0.1, 'stim_color': 'white', 'stim_height': 0.6, 'stim_jitter': 0.0, diff --git a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py index 24031d05f..8011205ce 100644 --- a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py +++ b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py @@ -45,7 +45,6 @@ def setUp(self): 'preview_inquiry_length': 5.0, 'show_feedback': False, 'show_preview_inquiry': False, - 'static_trigger_offset': 0.1, 'stim_color': 'white', 'stim_height': 0.6, 'stim_jitter': 0.0, diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 7c4b97b3b..fff068107 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -58,7 +58,6 @@ def setUp(self): 'show_feedback': False, 'show_preview_inquiry': False, 'spelled_letters_count': 0, - 'static_trigger_offset': 0.1, 'stim_color': 'white', 'stim_height': 0.6, 'stim_length': 10, From fc29194c028e8c23415cb44c3601b65f5f2ee279 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 16 Jul 2024 10:18:44 -0700 Subject: [PATCH 270/330] Updated Tobii eyetracker device with a static offset of 0.1 --- bcipy/parameters/devices.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index b65624cf9..f54b9c3d5 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -125,6 +125,6 @@ "description": "Tobii Nano. For use with the Tobii Pro SDK.", "excluded_from_analysis": ["device_ts", "system_ts", "left_pupil", "right_pupil"], "status": "active", - "static_offset": 0.0 + "static_offset": 0.1 } ] \ No newline at end of file From c5204da49715925e11f4da92b13cf66cfca91d8d Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 16 Jul 2024 10:24:34 -0700 Subject: [PATCH 271/330] Reset Tobii static_offset back to 0.0 --- bcipy/parameters/devices.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index f54b9c3d5..b65624cf9 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -125,6 +125,6 @@ "description": "Tobii Nano. For use with the Tobii Pro SDK.", "excluded_from_analysis": ["device_ts", "system_ts", "left_pupil", "right_pupil"], "status": "active", - "static_offset": 0.1 + "static_offset": 0.0 } ] \ No newline at end of file From 34757cfe980d3bc69ee57598ed376240da30f940 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 29 Jul 2024 15:47:02 -0700 Subject: [PATCH 272/330] Fixed linting errors --- bcipy/simulator/__main__.py | 2 +- bcipy/simulator/helpers/artifact.py | 1 - bcipy/simulator/helpers/data_engine.py | 16 +++++++++------- bcipy/simulator/helpers/model_handler.py | 6 +++--- bcipy/simulator/helpers/sampler.py | 6 +++--- bcipy/simulator/helpers/sim_runner.py | 2 +- bcipy/simulator/helpers/sim_viz.py | 7 +++++-- bcipy/simulator/helpers/state_manager.py | 10 ++++++++-- bcipy/simulator/sim_factory.py | 5 ++--- bcipy/simulator/tests/test_data_engine.py | 5 +++-- 10 files changed, 35 insertions(+), 25 deletions(-) diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 34a889d07..2453d724e 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -32,7 +32,7 @@ type=Path, required=True, help="Parameter File to be used") - + parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) args = parser.parse_args() sim_args = vars(args) diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 06b7586bb..6bde9cb17 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -46,4 +46,3 @@ def init_save_dir(output_path, save_dir_name): os.makedirs(f"{save_dir}/logs") return save_dir - diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index ff7211c45..6e75c6660 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -6,7 +6,6 @@ import numpy as np import pandas as pd -from bcipy.helpers.list import grouper from bcipy.helpers.parameters import Parameters from bcipy.simulator.helpers.signal_helpers import (ExtractedExperimentData, process_raw_data_for_model) @@ -28,6 +27,7 @@ def get_data(self): def get_parameters(self) -> List[Parameters]: ... + class Trial(NamedTuple): """Data for a given trial (a symbol within an Inquiry). @@ -50,6 +50,7 @@ class Trial(NamedTuple): target: int eeg: np.ndarray + class RawDataEngine(DataEngine): """ Object that loads in list of session data folders and transforms data into sample-able pd.df @@ -111,12 +112,13 @@ def transform(self) -> DataEngine: # iterate through each symbol in the inquiry eeg_samples = [channel[sym_i] for channel in inquiry_eeg ] # (channel_n, sample_n) - rows.append(Trial(source=data_source.source_dir, - inquiry_n=i, - inquiry_pos=sym_i + 1, - symbol=symbol, - target=inquiry_labels[sym_i], - eeg=np.array(eeg_samples))) + rows.append( + Trial(source=data_source.source_dir, + inquiry_n=i, + inquiry_pos=sym_i + 1, + symbol=symbol, + target=inquiry_labels[sym_i], + eeg=np.array(eeg_samples))) self.schema = pd.DataFrame(rows) diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index 21de3e1c2..68987e004 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -1,3 +1,4 @@ +import inspect import logging import pickle from abc import ABC, abstractmethod @@ -5,15 +6,14 @@ import numpy as np -from bcipy.helpers.language_model import (histogram, init_language_model, - with_min_prob, language_models_by_name) +from bcipy.helpers.language_model import (histogram, language_models_by_name, + with_min_prob) from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet from bcipy.language import LanguageModel, ResponseType from bcipy.signal.model import SignalModel from bcipy.simulator.helpers.state_manager import SimState from bcipy.simulator.helpers.types import SimEvidence from bcipy.task.data import EvidenceType -import inspect log = logging.getLogger(__name__) diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 439eecfa3..d84b2e62a 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -145,7 +145,7 @@ def prepare_data( def sample(self, state: SimState) -> np.ndarray: """Samples a random inquiry for a random data source. - + Ensures that if a target is shown in the current inquiry the sampled data will be from an inquiry where the target was presented. @@ -187,12 +187,12 @@ def sample(self, state: SimState) -> np.ndarray: # target already in the correct location, no need to adjust new_target_position = inquiry_target_position elif inquiry_target_position < target_position: - # target in the inquiry needs to be pushed later in the inquiry; + # target in the inquiry needs to be pushed later in the inquiry; # There is another symbol currently at that position, so we need # to ensure that the target is past that symbol (by adding 0.5). new_target_position = target_position + 0.5 elif inquiry_target_position > target_position: - # the target in the inquiry needs to be moved earlier in the inquiry; + # the target in the inquiry needs to be moved earlier in the inquiry; # there is another non-target symbol currently at that position so # the target needs to be moved before that symbol. new_target_position = target_position - 0.5 diff --git a/bcipy/simulator/helpers/sim_runner.py b/bcipy/simulator/helpers/sim_runner.py index bd10cd169..49dc22606 100644 --- a/bcipy/simulator/helpers/sim_runner.py +++ b/bcipy/simulator/helpers/sim_runner.py @@ -34,7 +34,7 @@ def run(self): # creating save dir for sim_i, then mutating sim_i save_directory sim_i_save_dir = artifact.init_save_dir(self.wrapper_save_dir, f"run{i}") self.simulator.save_dir = sim_i_save_dir - artifact.configure_logger(f"{sim_i_save_dir}/logs", f"logs") + artifact.configure_logger(f"{sim_i_save_dir}/logs", "logs") # running simulator self.simulator.run() diff --git a/bcipy/simulator/helpers/sim_viz.py b/bcipy/simulator/helpers/sim_viz.py index 14644335d..b3fdbf618 100644 --- a/bcipy/simulator/helpers/sim_viz.py +++ b/bcipy/simulator/helpers/sim_viz.py @@ -55,8 +55,11 @@ def plot_replay_comparison(new_target_eeg_evidence: np.ndarray, outdir: str, parameters: Parameters, ) -> None: - def convert_to_records(arr, key_value, key_name="which_model", value_name="response_value") -> [ - dict]: + + def convert_to_records(arr, + key_value, + key_name="which_model", + value_name="response_value") -> [dict]: return [{key_name: key_value, value_name: val} for val in arr] records = [] diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 74eefbd79..8b7126171 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -125,9 +125,15 @@ def update(self, evidence) -> InquiryResult: evidences=evidence, decision=decision, fused_likelihood=fused_likelihood) + debug_info = [ + 'Fused Likelihoods', + f'current typed - {self.state.current_sentence}', + f'stimuli {self.state.display_alphabet}' + ] log.debug( - f"Fused Likelihoods | current typed - {self.state.current_sentence} | stimuli {self.state.display_alphabet} \n " - f"{histogram(fmt_likelihoods_for_hist(new_inquiry_result.fused_likelihood, alphabet()))}") + f"{' | '.join(debug_info)} \n " + f"{histogram(fmt_likelihoods_for_hist(new_inquiry_result.fused_likelihood, alphabet()))}" + ) new_state['series_results'][self.state.series_n].append(new_inquiry_result) if is_decidable: diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 4b5208b05..d28725bba 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -1,14 +1,13 @@ """ Factory for Simulator objects """ -import logging from pathlib import Path from typing import List from bcipy.helpers.load import load_json_parameters -from bcipy.simulator.helpers.data_engine import (RawDataEngine) +from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.metrics import (MetricReferee, RefereeImpl, SimMetrics1Handler) from bcipy.simulator.helpers.model_handler import (ModelHandler, - SigLmModelHandler1, ) + SigLmModelHandler1) from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler from bcipy.simulator.helpers.state_manager import (StateManager, StateManagerImpl) diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py index e9e01af8d..ba2b2ce39 100644 --- a/bcipy/simulator/tests/test_data_engine.py +++ b/bcipy/simulator/tests/test_data_engine.py @@ -7,7 +7,8 @@ import pandas as pd from bcipy.helpers import load -from bcipy.simulator.helpers.data_engine import DataEngine, RawDataEngine, RawDataEngineWrapper +from bcipy.simulator.helpers.data_engine import (RawDataEngine, + RawDataEngineWrapper) # Import the module or class you want to test @@ -87,7 +88,7 @@ def test_RawDataEngineWrapper(self): def test_matrix_single(self): source_dir = "/Users/srikarananthoju/cambi/data/matrixTestWrapper" - param_path = "/Users/srikarananthoju/cambi/data/matrixTestWrapper/S007_Matrix_Calibration_Thu_20_Jul_2023_09hr48min56sec_-0400/parameters.json" + param_path = f"{source_dir}/S007_Matrix_Calibration_Thu_20_Jul_2023_09hr48min56sec_-0400/parameters.json" params = load.load_json_parameters(str(Path(param_path)), value_cast=True) data_engine = RawDataEngineWrapper(source_dir, params) From 8db897581b61f9f9a0759fab106519aa7a26691f Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 30 Jul 2024 16:48:41 -0700 Subject: [PATCH 273/330] Refactored RawDataEngine to take a data_processor parameter; refactored function for processing data into a separate class; fixed unit tests --- bcipy/simulator/helpers/data_engine.py | 38 ++-- bcipy/simulator/helpers/signal_helpers.py | 238 ++++++++++++---------- bcipy/simulator/tests/sampler_test.py | 7 +- bcipy/simulator/tests/test_data_engine.py | 161 +++++++-------- 4 files changed, 226 insertions(+), 218 deletions(-) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 6e75c6660..ec699a092 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -7,8 +7,9 @@ import pandas as pd from bcipy.helpers.parameters import Parameters -from bcipy.simulator.helpers.signal_helpers import (ExtractedExperimentData, - process_raw_data_for_model) +from bcipy.simulator.helpers.signal_helpers import (EegRawDataProcessor, + ExtractedExperimentData, + RawDataProcessor) log = logging.getLogger(__name__) @@ -53,12 +54,14 @@ class Trial(NamedTuple): class RawDataEngine(DataEngine): """ - Object that loads in list of session data folders and transforms data into sample-able pd.df + Object that loads in list of session data folders and transforms data into sample-able DataFrame """ - def __init__(self, source_dirs: List[str], parameters: Parameters): + def __init__(self, source_dirs: List[str], parameters: Parameters, data_processor: RawDataProcessor = None): self.source_dirs: List[str] = source_dirs self.parameters: Parameters = parameters + + self.data_processor = data_processor or EegRawDataProcessor() self.data: Optional[List[ExtractedExperimentData]] = None self.schema: Optional[pd.DataFrame] = None @@ -76,11 +79,11 @@ def load(self) -> DataEngine: log.debug(f"Loading data from {len(self.source_dirs)} source directories") self.data = [ - process_raw_data_for_model(source_dir, self.parameters) + self.data_processor.process(source_dir, self.parameters) for source_dir in self.source_dirs ] - log.info("Finished loading all data") + log.debug("Finished loading all data") return self def transform(self) -> DataEngine: @@ -121,7 +124,6 @@ def transform(self) -> DataEngine: eeg=np.array(eeg_samples))) self.schema = pd.DataFrame(rows) - return self def get_data(self): @@ -138,19 +140,9 @@ class RawDataEngineWrapper(RawDataEngine): - each data dir contains its raw_data and triggers """ - def __init__(self, source_dir: str, parameters: Parameters): - data_paths = self.get_data_dirs(source_dir) - super().__init__(data_paths, parameters) - - @staticmethod - def get_data_dirs(source_dir: str) -> [str]: - """ - Returns all the data dirs within the source dir - - e.g [dataDir1Path, dataDir2Path ... ] - """ - - assert source_dir - - directories: List[str] = [str(d) for d in Path(source_dir).iterdir() if d.is_dir()] - - return directories + def __init__(self, + source_dir: str, + parameters: Parameters, + data_processor: RawDataProcessor = None): + data_paths = [str(d) for d in Path(source_dir).iterdir() if d.is_dir()] + super().__init__(data_paths, parameters, data_processor) diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 2bf56be77..5f577d621 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -12,6 +12,7 @@ from bcipy.helpers.exceptions import TaskConfigurationException from bcipy.helpers.list import grouper from bcipy.helpers.load import load_raw_data +from bcipy.helpers.parameters import Parameters from bcipy.helpers.stimuli import InquiryReshaper, update_inquiry_timing from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.signal.process import (ERPTransformParams, filter_inquiries, @@ -53,108 +54,135 @@ def labels_by_inquiry(self) -> List[List[int]]: return self.labels -def process_raw_data_for_model(data_folder, parameters, - reshaper: InquiryReshaper = InquiryReshaper()) -> ExtractedExperimentData: - assert parameters, "Parameters are required for offline analysis." - - log.debug(f"Processing raw data for {data_folder}") - # extract relevant session information from parameters file - trial_window = parameters.get("trial_window") - if trial_window is None: - # using trial_length instead and converting to trial window - trial_length = parameters.get('trial_length') - if not trial_length: - raise TaskConfigurationException( - "Could not find trial_window or trial_length in parameters") - - trial_window = tuple([0, trial_length]) # trial_length=0.5 -> trial_window=(0,0.5) - - window_length = trial_window[1] - trial_window[0] - prestim_length = parameters.get("prestim_length") - trials_per_inquiry = parameters.get("stim_length") - # The task buffer length defines the min time between two inquiries - # We use half of that time here to buffer during transforms - buffer = int(parameters.get("task_buffer_length") / 2) - raw_data_file = f"{RAW_DATA_FILENAME}.csv" - - # get signal filtering information - transform_params = parameters.instantiate(ERPTransformParams) - downsample_rate = transform_params.down_sampling_rate - static_offset = parameters.get("static_trigger_offset") - - log.debug( - f"\nData processing settings: \n" - f"{str(transform_params)} \n" - f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " - f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer}s \n" - f"Static offset: {static_offset}" - ) - - # Load raw data - raw_data = load_raw_data(Path(data_folder, raw_data_file)) - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - - devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=transform_params.notch_filter_frequency, - bandpass_low=transform_params.filter_low, - bandpass_high=transform_params.filter_high, - bandpass_order=transform_params.filter_order, - downsample_factor=transform_params.down_sampling_rate, - ) - - log.debug(f"Channels read from csv: {channels}") - log.debug(f"Device type: {type_amp}, fs={sample_rate}") - - # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - offset=static_offset, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], - ) - - # update the trigger timing list to account for the initial trial window - corrected_trigger_timing = [timing + trial_window[0] for timing in trigger_timing] - - # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module - # The timestamp column [0] is already excluded. - channel_map = analysis_channels(channels, device_spec) - channels_used = [channels[i] for i, keep in enumerate(channel_map) if keep == 1] - log.debug(f'Channels used in analysis: {channels_used}') - - data, fs = raw_data.by_channel() - - inquiries, inquiry_labels, inquiry_timing = reshaper( - trial_targetness_label=trigger_targetness, - timing_info=corrected_trigger_timing, - eeg_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=window_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer, - ) - - inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) - inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) - trial_duration_samples = int(window_length * fs) - trials = reshaper.extract_trials(inquiries, trial_duration_samples, inquiry_timing) - - # define the training classes using integers, where 0=nontargets/1=targets - # labels = inquiry_labels.flatten() - - return ExtractedExperimentData( - data_folder, - inquiries, - trials, - inquiry_labels, - inquiry_timing, - decoded_triggers=(trigger_targetness, trigger_timing, trigger_symbols), - trials_per_inquiry=trials_per_inquiry) +class RawDataProcessor(): + """Processes raw data for a given device and converts it to + ExtractedExperimentData for use in the simulator.""" + + def process(self, data_folder: str, + parameters: Parameters) -> ExtractedExperimentData: + """Load and process the data""" + + +class EegRawDataProcessor(RawDataProcessor): + """RawDataProcessor that processes EEG data.""" + + def __init__(self): + + self.reshaper = InquiryReshaper() + + def process(self, data_folder: str, + parameters: Parameters) -> ExtractedExperimentData: + # TODO: refactor + + log.debug(f"Processing raw data for {data_folder}") + # extract relevant session information from parameters file + trial_window = parameters.get("trial_window") + if trial_window is None: + # using trial_length instead and converting to trial window + trial_length = parameters.get('trial_length') + if not trial_length: + raise TaskConfigurationException( + "Could not find trial_window or trial_length in parameters" + ) + + trial_window = tuple( + [0, trial_length]) # trial_length=0.5 -> trial_window=(0,0.5) + + window_length = trial_window[1] - trial_window[0] + prestim_length = parameters.get("prestim_length") + trials_per_inquiry = parameters.get("stim_length") + # The task buffer length defines the min time between two inquiries + # We use half of that time here to buffer during transforms + buffer = int(parameters.get("task_buffer_length") / 2) + raw_data_file = f"{RAW_DATA_FILENAME}.csv" + + # get signal filtering information + transform_params = parameters.instantiate(ERPTransformParams) + downsample_rate = transform_params.down_sampling_rate + static_offset = parameters.get("static_trigger_offset") + + log.debug( + f"\nData processing settings: \n" + f"{str(transform_params)} \n" + f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " + f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer}s \n" + f"Static offset: {static_offset}") + + # Load raw data + raw_data = load_raw_data(Path(data_folder, raw_data_file)) + channels = raw_data.channels + type_amp = raw_data.daq_type + sample_rate = raw_data.sample_rate + + devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(raw_data.daq_type) + + # setup filtering + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) + + log.debug(f"Channels read from csv: {channels}") + log.debug(f"Device type: {type_amp}, fs={sample_rate}") + + # Process triggers.txt files + trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( + offset=static_offset, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=[ + TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION + ], + ) + + # update the trigger timing list to account for the initial trial window + corrected_trigger_timing = [ + timing + trial_window[0] for timing in trigger_timing + ] + + # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module + # The timestamp column [0] is already excluded. + channel_map = analysis_channels(channels, device_spec) + channels_used = [ + channels[i] for i, keep in enumerate(channel_map) if keep == 1 + ] + log.debug(f'Channels used in analysis: {channels_used}') + + data, fs = raw_data.by_channel() + + inquiries, inquiry_labels, inquiry_timing = self.reshaper( + trial_targetness_label=trigger_targetness, + timing_info=corrected_trigger_timing, + eeg_data=data, + sample_rate=sample_rate, + trials_per_inquiry=trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=window_length, + prestimulus_length=prestim_length, + transformation_buffer=buffer, + ) + + inquiries, fs = filter_inquiries(inquiries, default_transform, + sample_rate) + inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) + trial_duration_samples = int(window_length * fs) + trials = self.reshaper.extract_trials(inquiries, + trial_duration_samples, + inquiry_timing) + + # define the training classes using integers, where 0=nontargets/1=targets + # labels = inquiry_labels.flatten() + + return ExtractedExperimentData(data_folder, + inquiries, + trials, + inquiry_labels, + inquiry_timing, + decoded_triggers=(trigger_targetness, + trigger_timing, + trigger_symbols), + trials_per_inquiry=trials_per_inquiry) diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index f9e5399a3..fe7fb3658 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -7,9 +7,10 @@ from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.metrics import RefereeImpl, SimMetrics1Handler -from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler -from bcipy.simulator.helpers.state_manager import StateManagerImpl, StateManager from bcipy.simulator.helpers.model_handler import SignalModelHandler1 +from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler +from bcipy.simulator.helpers.state_manager import (StateManager, + StateManagerImpl) from bcipy.simulator.sim import SimulatorCopyPhrase if __name__ == "__main__": @@ -25,7 +26,7 @@ ) sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) - data_engine = RawDataEngine(args['data_folders']) + data_engine = RawDataEngine(args['data_folders'], sim_parameters) display_alp = random.sample(alphabet(), 10) diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py index ba2b2ce39..932e7b9cb 100644 --- a/bcipy/simulator/tests/test_data_engine.py +++ b/bcipy/simulator/tests/test_data_engine.py @@ -1,102 +1,89 @@ -import shutil import unittest -import zipfile from pathlib import Path +from unittest.mock import Mock import numpy as np -import pandas as pd -from bcipy.helpers import load -from bcipy.simulator.helpers.data_engine import (RawDataEngine, - RawDataEngineWrapper) - -# Import the module or class you want to test - -FILE_PATH_PREFIX = "bcipy/simulator/tests" +from bcipy.simulator.helpers.data_engine import (ExtractedExperimentData, + RawDataEngine) class TestRawDataEngine(unittest.TestCase): + """Tests for RawDataEngine""" - @classmethod - def setUp(cls) -> None: - with zipfile.ZipFile(f'{FILE_PATH_PREFIX}/resource/rsvpTest1.zip', 'r') as zip_ref: - zip_ref.extractall(f'{FILE_PATH_PREFIX}/resource/rsvpTest1') - - @classmethod - def tearDown(cls) -> None: - shutil.rmtree(f'{FILE_PATH_PREFIX}/resource/rsvpTest1') - - @classmethod - def check_eeg_shape(cls, schema: pd.DataFrame): - # checking all eeg response data has same shape - - eeg_responses = schema['eeg'] - ret = True - ret = ret and not (None in eeg_responses or np.NaN in eeg_responses) - shape_set = set(eeg_responses.apply(lambda x: x.shape)) - ret = ret and (len(shape_set) == 1) - - return ret - - def test_one_source(self): - # Test the function with a specific input and assert the expected output - - data_paths = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700"] - param_path = "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/parameters.json" - params = load.load_json_parameters(str(Path(param_path)), value_cast=True) - - data_engine = RawDataEngine(data_paths, params) - self.assertFalse(data_engine.get_data()) - - data_engine.transform() - self.assertTrue(len(data_engine.schema)) - - self.assertTrue(self.check_eeg_shape(data_engine.get_data())) + def setUp(self) -> None: + """Setup common state""" - def test_two_sources(self): - # Test the function with a specific input and assert the expected output + self.data_processor = Mock() + self.data_processor.process = Mock() + self.parameters = Mock() - data_paths = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700", - "/Users/srikarananthoju/cambi/tab_test_dynamic/50sec_-0700"] - param_path = "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/parameters.json" - params = load.load_json_parameters(str(Path(param_path)), value_cast=True) - - data_engine = RawDataEngine(data_paths, params) + def test_init(self): + """"Test initialization""" + data_engine = RawDataEngine(source_dirs=[], + parameters=self.parameters, + data_processor=self.data_processor) self.assertFalse(data_engine.get_data()) - - data_engine.transform() - self.assertTrue(len(data_engine.get_data())) - - # asserting all eeg response data has same shape - self.assertTrue(self.check_eeg_shape(data_engine.get_data())) - - def test_RawDataEngineWrapper(self): - # Testing loading and transformaing data from a singular wrapper folder - - # source_dir = "/Users/srikarananthoju/cambi/tab_test_dynamic/wrapper" - source_dir = FILE_PATH_PREFIX + "/resource/rsvpTest1/wrapper" - param_path = "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/parameters.json" - params = load.load_json_parameters(str(Path(param_path)), value_cast=True) - - data_engine = RawDataEngineWrapper(source_dir, params) - self.assertEqual(len(data_engine.source_dirs), 2) - - data_engine.transform() - self.assertTrue(len(data_engine.get_data())) - - self.assertTrue(self.check_eeg_shape(data_engine.get_data())) - - def test_matrix_single(self): - source_dir = "/Users/srikarananthoju/cambi/data/matrixTestWrapper" - param_path = f"{source_dir}/S007_Matrix_Calibration_Thu_20_Jul_2023_09hr48min56sec_-0400/parameters.json" - params = load.load_json_parameters(str(Path(param_path)), value_cast=True) - - data_engine = RawDataEngineWrapper(source_dir, params) - data_engine.transform() - - self.assertTrue(len(data_engine.get_data())) - - self.assertTrue(self.check_eeg_shape(data_engine.get_data())) + self.assertEqual(self.parameters, data_engine.get_parameters()) + + def test_single_data_source(self): + """Test loading data from a single directory.""" + RawDataEngine(source_dirs=['data-dir1'], + parameters=self.parameters, + data_processor=self.data_processor) + self.data_processor.process.assert_called_once_with( + 'data-dir1', self.parameters) + + def test_multiple_sources(self): + """Test loading data from multiple directories.""" + RawDataEngine(source_dirs=['data-dir1', 'data-dir2', 'data-dir3'], + parameters=self.parameters, + data_processor=self.data_processor) + self.assertEqual(self.data_processor.process.call_count, 3) + # last call + self.data_processor.process.assert_called_with('data-dir3', + self.parameters) + + def test_transform(self): + """Test the data transformation method""" + # Setup context + # mock the experiment data; single inquiry + mock_data = ExtractedExperimentData( + source_dir=Path('data-dir1'), + inquiries=np.zeros((7, 1, 692)), + trials=np.zeros((7, 10, 74)), + labels=np.array([[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]]), + inquiry_timing=[[150, 185, 220, 255, 291, 326, 361, 397, 432, + 467]], + decoded_triggers=([ + 'nontarget', 'nontarget', 'nontarget', 'nontarget', + 'nontarget', 'target', 'nontarget', 'nontarget', 'nontarget', + 'nontarget' + ], [ + 9.730993399999988, 9.966709099999662, 10.201713299999938, + 10.436247999999978, 10.672083899999961, 10.90684519999968, + 11.141479799999615, 11.377909999999702, 11.614850199999637, + 11.849502299999585 + ], ['G', 'C', 'D', 'B', 'I', 'A', 'H', '<', 'E', 'F']), + trials_per_inquiry=10) + self.data_processor.process = Mock(return_value=mock_data) + engine = RawDataEngine(source_dirs=['data-dir1'], + parameters=self.parameters, + data_processor=self.data_processor) + engine.transform() + data = engine.get_data() + + self.assertEqual(10, len(data)) + + self.assertEqual(data.iloc[0].symbol, 'G') + self.assertEqual(data.iloc[0].inquiry_n, 0) + self.assertEqual(data.iloc[0].inquiry_pos, 1) + self.assertEqual(data.iloc[0].target, 0) + + self.assertEqual(data.iloc[len(data) - 1].symbol, 'F') + self.assertEqual(data.iloc[len(data) - 1].inquiry_n, 0) + self.assertEqual(data.iloc[len(data) - 1].inquiry_pos, 10) + self.assertEqual(data.iloc[len(data) - 1].target, 0) if __name__ == '__main__': From 18063e88464b95749e34db8f296abdb6abf2bd63 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 30 Jul 2024 17:27:21 -0700 Subject: [PATCH 274/330] Remove duplicate code with hard-coded paths --- bcipy/simulator/tests/sampler_test.py | 43 --------------------------- 1 file changed, 43 deletions(-) delete mode 100644 bcipy/simulator/tests/sampler_test.py diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py deleted file mode 100644 index fe7fb3658..000000000 --- a/bcipy/simulator/tests/sampler_test.py +++ /dev/null @@ -1,43 +0,0 @@ -import random -from pathlib import Path - -import numpy as np - -from bcipy.helpers.load import load_json_parameters -from bcipy.helpers.symbols import alphabet -from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.metrics import RefereeImpl, SimMetrics1Handler -from bcipy.simulator.helpers.model_handler import SignalModelHandler1 -from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler -from bcipy.simulator.helpers.state_manager import (StateManager, - StateManagerImpl) -from bcipy.simulator.sim import SimulatorCopyPhrase - -if __name__ == "__main__": - args = dict() - args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700", - "/Users/srikarananthoju/cambi/tab_test_dynamic/50sec_-0700", - # "/Users/srikarananthoju/cambi/tab_test_dynamic/29sec_-0700" - ] - args['out_dir'] = Path(__file__).resolve().parent - model_file = Path( - "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/model_0.9524_200_800.pkl" - # "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/model_0.9595.pkl" - ) - sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) - - data_engine = RawDataEngine(args['data_folders'], sim_parameters) - - display_alp = random.sample(alphabet(), 10) - - stateManager: StateManager = StateManagerImpl(sim_parameters) - stateManager.mutate_state("display_alphabet", display_alp) - print(stateManager.get_state()) - - sampler: Sampler = EEGByLetterSampler(data_engine) - sample: np.ndarray = sampler.sample(stateManager.get_state()) - - model_handler = SignalModelHandler1(model_file) - sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, - RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()})) - sim.run() From c34c67a9dc896d0837fedbc8c4eea3b00bb3ded2 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 30 Jul 2024 17:32:37 -0700 Subject: [PATCH 275/330] Renamed SimulationFactory and reformatted --- bcipy/simulator/__main__.py | 4 ++-- bcipy/simulator/sim_factory.py | 32 ++++++++++++++++++++++---------- 2 files changed, 24 insertions(+), 12 deletions(-) diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 2453d724e..9ac8f3f04 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -5,7 +5,7 @@ from pathlib import Path from bcipy.simulator.helpers.sim_runner import MultiSimRunner, SingleSimRunner -from bcipy.simulator.sim_factory import SimulationFactoryV2 +from bcipy.simulator.sim_factory import SimulationFactory from bcipy.simulator.simulator_base import Simulator if __name__ == "__main__": @@ -42,7 +42,7 @@ if Path(d).is_dir() ] - simulator: Simulator = SimulationFactoryV2.create(**sim_args) + simulator = SimulationFactory.create(**sim_args) sim_run_count = simulator.get_parameters().get('sim_run_count', 1) diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index d28725bba..c83f81c8a 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -11,30 +11,42 @@ from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler from bcipy.simulator.helpers.state_manager import (StateManager, StateManagerImpl) -from bcipy.simulator.sim import SimulatorCopyPhrase +from bcipy.simulator.sim import Simulator, SimulatorCopyPhrase -class SimulationFactoryV2: +class SimulationFactory: """ Factory class to create Simulator instances """ @staticmethod - def create(source_dirs: List[Path], smodel_files: List[str], - sim_param_path="bcipy/simulator/sim_parameters.json", save_dir=None, **kwargs): + def create(source_dirs: List[Path], + smodel_files: List[str], + sim_param_path="bcipy/simulator/sim_parameters.json", + save_dir=None, + **kwargs) -> Simulator: + """Create a Simulation, performing all of the necessary setup.""" # out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) # combining parameters model_file = Path(smodel_files.pop()) sim_parameters = load_json_parameters(sim_param_path, value_cast=True) - base_parameters = load_json_parameters(kwargs.get('parameters'), value_cast=True) + base_parameters = load_json_parameters(kwargs.get('parameters'), + value_cast=True) base_parameters.add_missing_items(sim_parameters) data_engine = RawDataEngine(source_dirs, base_parameters) state_manager: StateManager = StateManagerImpl(base_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) - model_handler: ModelHandler = SigLmModelHandler1(model_file, base_parameters) - referee: MetricReferee = RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()}) - - sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, state_manager, referee, - parameters=base_parameters, save_dir=save_dir) + model_handler: ModelHandler = SigLmModelHandler1( + model_file, base_parameters) + referee: MetricReferee = RefereeImpl( + metric_handlers={'basic': SimMetrics1Handler()}) + + sim = SimulatorCopyPhrase(data_engine, + model_handler, + sampler, + state_manager, + referee, + parameters=base_parameters, + save_dir=save_dir) return sim From 440e3a10c113e54580a345538c60dc01109ab262 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 31 Jul 2024 16:31:36 -0700 Subject: [PATCH 276/330] Fix typing issues --- bcipy/helpers/stimuli.py | 5 ++-- bcipy/simulator/__main__.py | 11 +++----- bcipy/simulator/helpers/artifact.py | 2 +- bcipy/simulator/helpers/data_engine.py | 15 +++++++---- bcipy/simulator/helpers/model_handler.py | 4 --- bcipy/simulator/helpers/sampler.py | 27 +++++++------------ bcipy/simulator/helpers/signal_helpers.py | 15 +++++++---- bcipy/simulator/helpers/sim_runner.py | 32 ++++++++++++++++++----- bcipy/simulator/helpers/sim_viz.py | 3 ++- bcipy/simulator/helpers/state_manager.py | 8 +++--- bcipy/simulator/sim.py | 31 ++++++++++++---------- bcipy/simulator/sim_factory.py | 7 ++--- bcipy/simulator/simulator_base.py | 2 ++ 13 files changed, 90 insertions(+), 72 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 567e2d8ef..cd849c67a 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -401,12 +401,11 @@ def __call__(self, return np.stack(reshaped_trials, 1), targetness_labels -def update_inquiry_timing(timing: List[List[float]], downsample: int) -> List[List[float]]: +def update_inquiry_timing(timing: List[List[int]], downsample: int) -> List[List[int]]: """Update inquiry timing to reflect downsampling.""" - for i, inquiry in enumerate(timing): for j, time in enumerate(inquiry): - timing[i][j] = time // downsample + timing[i][j] = int(time // downsample) return timing diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 9ac8f3f04..78ff3ad59 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -6,7 +6,6 @@ from bcipy.simulator.helpers.sim_runner import MultiSimRunner, SingleSimRunner from bcipy.simulator.sim_factory import SimulationFactory -from bcipy.simulator.simulator_base import Simulator if __name__ == "__main__": glob_help = ('glob pattern to select a subset of data folders' @@ -46,9 +45,7 @@ sim_run_count = simulator.get_parameters().get('sim_run_count', 1) - if sim_run_count > 1: # running multiple times - runner = MultiSimRunner(simulator, sim_run_count) - runner.run() - else: - runner = SingleSimRunner(simulator) - runner.run() + runner = MultiSimRunner( + simulator, + sim_run_count) if sim_run_count > 1 else SingleSimRunner(simulator) + runner.run() diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 6bde9cb17..8b1e9b9d5 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -28,7 +28,7 @@ def configure_logger(log_path, file_name): fileHandler.setFormatter(fmt_file) # Add each handler to the Logger object - if stdoutHandler.stream.name not in [handler.stream.name for handler in log.handlers]: + if stdoutHandler not in log.handlers: log.addHandler(stdoutHandler) log.addHandler(fileHandler) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index ec699a092..8804ee3a1 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,5 +1,5 @@ import logging -from abc import ABC +from abc import ABC, abstractmethod from pathlib import Path from typing import List, NamedTuple, Optional @@ -25,6 +25,7 @@ def transform(self): def get_data(self): ... + @abstractmethod def get_parameters(self) -> List[Parameters]: ... @@ -57,12 +58,15 @@ class RawDataEngine(DataEngine): Object that loads in list of session data folders and transforms data into sample-able DataFrame """ - def __init__(self, source_dirs: List[str], parameters: Parameters, data_processor: RawDataProcessor = None): + def __init__(self, + source_dirs: List[str], + parameters: Parameters, + data_processor: Optional[RawDataProcessor] = None): self.source_dirs: List[str] = source_dirs self.parameters: Parameters = parameters self.data_processor = data_processor or EegRawDataProcessor() - self.data: Optional[List[ExtractedExperimentData]] = None + self.data: List[ExtractedExperimentData] = [] self.schema: Optional[pd.DataFrame] = None # TODO validate parameters @@ -76,7 +80,8 @@ def load(self) -> DataEngine: Returns: self for chaining """ - log.debug(f"Loading data from {len(self.source_dirs)} source directories") + log.debug( + f"Loading data from {len(self.source_dirs)} source directories") self.data = [ self.data_processor.process(source_dir, self.parameters) @@ -143,6 +148,6 @@ class RawDataEngineWrapper(RawDataEngine): def __init__(self, source_dir: str, parameters: Parameters, - data_processor: RawDataProcessor = None): + data_processor: Optional[RawDataProcessor] = None): data_paths = [str(d) for d in Path(source_dir).iterdir() if d.is_dir()] super().__init__(data_paths, parameters, data_processor) diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index 68987e004..8da949b25 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -2,7 +2,6 @@ import logging import pickle from abc import ABC, abstractmethod -from typing import Optional import numpy as np @@ -10,7 +9,6 @@ with_min_prob) from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet from bcipy.language import LanguageModel, ResponseType -from bcipy.signal.model import SignalModel from bcipy.simulator.helpers.state_manager import SimState from bcipy.simulator.helpers.types import SimEvidence from bcipy.task.data import EvidenceType @@ -33,7 +31,6 @@ class SignalModelHandler1(ModelHandler): def __init__(self, model_file): self.model_file = model_file - self.signal_model: Optional[SignalModel] = None with open(self.model_file, "rb") as signal_file: self.signal_model = pickle.load(signal_file) @@ -85,7 +82,6 @@ def __init__(self, sm_model_file, parameters): parameters: only needs to contain which type of language model """ self.sm_model_file = sm_model_file - self.signal_model: Optional[SignalModel] = None self.lm_model: LanguageModel = sim_init_lm(parameters) log.info(f"Language Model Type: {self.lm_model.name()}") self.alp = alphabet() diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index d84b2e62a..96a2d48c0 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -36,7 +36,7 @@ def __init__(self, parameters: Parameters = None): self.data_engine: RawDataEngine = data_engine self.parameters: Parameters = self.data_engine.parameters if not parameters else parameters - self.model_input_reshaper: Callable = self.__default_reshaper + self.model_input_reshaper: Callable = default_reshaper self.alphabet: List[str] = self.parameters.get( 'symbol_set') if self.parameters else alphabet() self.data: pd.DataFrame = self.data_engine.transform().get_data() @@ -75,19 +75,6 @@ def sample(self, state: SimState) -> np.ndarray: def set_reshaper(self, reshaper: Callable): self.model_input_reshaper = reshaper - def __default_reshaper(self, - eeg_responses: List[np.ndarray]) -> np.ndarray: - # returns (channel_n, trial_n, sample_n) - - channels_eeg = [[] for i in range(len(eeg_responses[0]))] - - for t_i, trial_channels_eeg in enumerate(eeg_responses): - for c_i, channel_eeg in enumerate(trial_channels_eeg): - channels_eeg[c_i].append(channel_eeg) - - # make sure this returns (7, 10, 90) for tab_test_dynamic - return np.array(channels_eeg) - def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: """Default data reshaper. @@ -97,7 +84,9 @@ def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: ndarray with shape (channel_n, trial_n, sample_n) """ - channels_eeg = [[] for i in range(len(eeg_responses[0]))] + channels_eeg: List[List[np.ndarray]] = [ + [] for i in range(len(eeg_responses[0])) + ] for _i, trial_channels_eeg in enumerate(eeg_responses): for c_i, channel_eeg in enumerate(trial_channels_eeg): @@ -180,12 +169,14 @@ def sample(self, state: SimState) -> np.ndarray: # new_target_position for the target. inquiry_target_position = target_position if target_letter in inquiry_letter_subset: - inquiry_target_index = inquiry_df[inquiry_df['target'] == 1].index[0] - inquiry_target_position = inquiry_df.index.tolist().index(inquiry_target_index) + inquiry_target_index = inquiry_df[inquiry_df['target'] == + 1].index[0] + inquiry_target_position = inquiry_df.index.tolist().index( + inquiry_target_index) if inquiry_target_position == target_position: # target already in the correct location, no need to adjust - new_target_position = inquiry_target_position + new_target_position = inquiry_target_position + 0.0 elif inquiry_target_position < target_position: # target in the inquiry needs to be pushed later in the inquiry; # There is another symbol currently at that position, so we need diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 5f577d621..2080b9f5a 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -61,6 +61,7 @@ class RawDataProcessor(): def process(self, data_folder: str, parameters: Parameters) -> ExtractedExperimentData: """Load and process the data""" + raise NotImplementedError class EegRawDataProcessor(RawDataProcessor): @@ -109,7 +110,7 @@ def process(self, data_folder: str, f"Static offset: {static_offset}") # Load raw data - raw_data = load_raw_data(Path(data_folder, raw_data_file)) + raw_data = load_raw_data(str(Path(data_folder, raw_data_file))) channels = raw_data.channels type_amp = raw_data.daq_type sample_rate = raw_data.sample_rate @@ -153,7 +154,6 @@ def process(self, data_folder: str, log.debug(f'Channels used in analysis: {channels_used}') data, fs = raw_data.by_channel() - inquiries, inquiry_labels, inquiry_timing = self.reshaper( trial_targetness_label=trigger_targetness, timing_info=corrected_trigger_timing, @@ -168,11 +168,16 @@ def process(self, data_folder: str, inquiries, fs = filter_inquiries(inquiries, default_transform, sample_rate) - inquiry_timing = update_inquiry_timing(inquiry_timing, downsample_rate) + # Convince mypy that the values received from the reshaper are actually ints. + inquiry_timing_ints: List[List[int]] = [ + list(map(int, inq)) for inq in inquiry_timing + ] + updated_inquiry_timing = update_inquiry_timing(inquiry_timing_ints, + downsample_rate) trial_duration_samples = int(window_length * fs) trials = self.reshaper.extract_trials(inquiries, trial_duration_samples, - inquiry_timing) + updated_inquiry_timing) # define the training classes using integers, where 0=nontargets/1=targets # labels = inquiry_labels.flatten() @@ -180,7 +185,7 @@ def process(self, data_folder: str, return ExtractedExperimentData(data_folder, inquiries, trials, - inquiry_labels, + [list(arr) for arr in inquiry_labels], inquiry_timing, decoded_triggers=(trigger_targetness, trigger_timing, diff --git a/bcipy/simulator/helpers/sim_runner.py b/bcipy/simulator/helpers/sim_runner.py index 49dc22606..a96b611a6 100644 --- a/bcipy/simulator/helpers/sim_runner.py +++ b/bcipy/simulator/helpers/sim_runner.py @@ -11,15 +11,29 @@ from bcipy.simulator.simulator_base import Simulator -class MultiSimRunner: +class SimRunner: + """An object that orchestrates one or more simulation runs.""" - def __init__(self, simulator: Simulator, n: int, save_dir=None, iteration_sleep=0): + def run(self): + """Run the simulation""" + ... + + +class MultiSimRunner(SimRunner): + """Runs multiple iterations of the simulation.""" + + def __init__(self, + simulator: Simulator, + n: int, + save_dir=None, + iteration_sleep=0): self.simulator: Simulator = simulator self.parameters: Parameters = self.simulator.get_parameters() self.n: int = n self.iteration_sleep: int = iteration_sleep - self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path() + self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path( + ) def run(self): # making wrapper dir for all simulations @@ -32,7 +46,8 @@ def run(self): for i in range(self.n): # creating save dir for sim_i, then mutating sim_i save_directory - sim_i_save_dir = artifact.init_save_dir(self.wrapper_save_dir, f"run{i}") + sim_i_save_dir = artifact.init_save_dir(self.wrapper_save_dir, + f"run{i}") self.simulator.save_dir = sim_i_save_dir artifact.configure_logger(f"{sim_i_save_dir}/logs", "logs") @@ -62,17 +77,20 @@ def __make_default_save_path(self): def __save_average_metrics(self, avg_metric_dict: Dict): """ Writing average dictionary of metrics to a json file in root of MultiRun save dir """ - with open(f"{self.wrapper_save_dir}/avg_metrics.json", 'w') as output_file: + with open(f"{self.wrapper_save_dir}/avg_metrics.json", + 'w') as output_file: json.dump(avg_metric_dict, output_file, indent=1) -class SingleSimRunner: +class SingleSimRunner(SimRunner): + """Runs the simulation once.""" def __init__(self, simulator: Simulator, save_dir=None): self.simulator: Simulator = simulator self.parameters: Parameters = self.simulator.get_parameters() - self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path() + self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path( + ) def run(self): # logging and save details diff --git a/bcipy/simulator/helpers/sim_viz.py b/bcipy/simulator/helpers/sim_viz.py index b3fdbf618..de3dab254 100644 --- a/bcipy/simulator/helpers/sim_viz.py +++ b/bcipy/simulator/helpers/sim_viz.py @@ -1,4 +1,5 @@ import logging as logger +from typing import List import matplotlib.pyplot as plt import numpy as np @@ -59,7 +60,7 @@ def plot_replay_comparison(new_target_eeg_evidence: np.ndarray, def convert_to_records(arr, key_value, key_name="which_model", - value_name="response_value") -> [dict]: + value_name="response_value") -> List[dict]: return [{key_name: key_value, value_name: val} for val in arr] records = [] diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 8b7126171..20862fc04 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -4,7 +4,7 @@ import random from abc import ABC from dataclasses import dataclass -from typing import Dict, List, Optional +from typing import Callable, Dict, List, Optional import numpy as np @@ -68,7 +68,7 @@ def is_done(self) -> bool: raise NotImplementedError() def get_state(self) -> SimState: - ... + raise NotImplementedError() def mutate_state(self, state_field, state_value): pass @@ -82,7 +82,7 @@ class StateManagerImpl(StateManager): def __init__(self, parameters: Parameters, fuser_class=MultiplyFuser): self.state: SimState = self.initial_state(parameters) self.parameters = parameters - self.fuser_class: EvidenceFuser.__class__ = fuser_class + self.fuser_class: Callable[[], EvidenceFuser] = fuser_class self.max_inq_len = self.parameters.get('max_inq_len', 100) @@ -204,7 +204,7 @@ def format_sim_state_dump(state: SimState): ret.pop('series_results') series_dict = {} for i, series in enumerate(state.series_results): - curr_series_dict = {} + curr_series_dict: Dict = {} series_dict[str(i + 1)] = curr_series_dict for inq_idx, inq in enumerate(series): inq_dict = inq.to_json() diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index bee346ae4..8b8cbf946 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -3,7 +3,7 @@ import logging import random from time import sleep -from typing import Optional, Dict +from typing import Dict, Optional import numpy as np @@ -11,13 +11,15 @@ from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine +from bcipy.simulator.helpers.log_utils import (fmt_reshaped_evidence, + fmt_stim_likelihoods) from bcipy.simulator.helpers.metrics import MetricReferee +from bcipy.simulator.helpers.model_handler import ModelHandler from bcipy.simulator.helpers.rsvp_utils import format_lm_output from bcipy.simulator.helpers.sampler import Sampler -from bcipy.simulator.helpers.state_manager import StateManager, SimState, format_sim_state_dump +from bcipy.simulator.helpers.state_manager import (SimState, StateManager, + format_sim_state_dump) from bcipy.simulator.helpers.types import InquiryResult, SimEvidence -from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods, fmt_reshaped_evidence -from bcipy.simulator.helpers.model_handler import ModelHandler from bcipy.simulator.simulator_base import Simulator from bcipy.task.data import EvidenceType @@ -47,23 +49,24 @@ class SimulatorCopyPhrase(Simulator): """ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, parameters: Parameters = None, - save_dir: str = None): + state_manager: StateManager, referee: MetricReferee, parameters: Optional[Parameters] = None, + save_dir: Optional[str] = None): super().__init__() - self.save_dir: str = save_dir - self.model_handler: ModelHandler = model_handler - self.sampler: Sampler = sampler - self.referee: MetricReferee = referee - self.state_manager: StateManager = state_manager - self.data_engine: DataEngine = data_engine + self.save_dir = save_dir + self.model_handler = model_handler + self.sampler = sampler + self.referee = referee + self.state_manager = state_manager + self.data_engine = data_engine - self.parameters: Parameters = self.load_parameters(parameters) + self.parameters = self.load_parameters(parameters) self.symbol_set = alphabet() self.write_output = False def run(self): + assert self.save_dir, "Save directory not set" log.info(f"SIM START with target word {self.state_manager.get_state().target_sentence}") while not self.state_manager.is_done(): @@ -152,7 +155,7 @@ def load_parameters(self, params: Optional[Parameters]): def save_run(self): """ Outputs the results of a run to json file """ - + assert self.save_dir, "Save directory not set" # creating result.json object with final state and metrics final_state = self.state_manager.get_state() final_state_json: Dict = format_sim_state_dump(final_state) diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index c83f81c8a..293a15b5a 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -29,11 +29,12 @@ def create(source_dirs: List[Path], # combining parameters model_file = Path(smodel_files.pop()) sim_parameters = load_json_parameters(sim_param_path, value_cast=True) - base_parameters = load_json_parameters(kwargs.get('parameters'), - value_cast=True) + params_path: str = kwargs.get('parameters', None) + base_parameters = load_json_parameters(params_path, value_cast=True) base_parameters.add_missing_items(sim_parameters) - data_engine = RawDataEngine(source_dirs, base_parameters) + data_engine = RawDataEngine(list(map(str, source_dirs)), + base_parameters) state_manager: StateManager = StateManagerImpl(base_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) model_handler: ModelHandler = SigLmModelHandler1( diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py index 68013701f..30aa13fc1 100644 --- a/bcipy/simulator/simulator_base.py +++ b/bcipy/simulator/simulator_base.py @@ -1,6 +1,7 @@ """ base simulator interface """ from abc import ABC, abstractmethod +from typing import Optional from bcipy.helpers.parameters import Parameters from bcipy.simulator.helpers import metrics @@ -25,6 +26,7 @@ class Simulator(ABC): data_engine: DataEngine referee: metrics.MetricReferee parameters: Parameters + save_dir: Optional[str] @abstractmethod def run(self): From 65bdbbb0d3b07c4622311676b0ca24ec675b8fc0 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Aug 2024 10:58:39 -0700 Subject: [PATCH 277/330] Refactored SimRunner to simplify to a single case (multiple runs). Refactored the folder structure for simulation data. Added a logfile for the simulation. General cleanup. --- bcipy/simulator/__main__.py | 15 +- bcipy/simulator/helpers/artifact.py | 49 ++++--- bcipy/simulator/helpers/data_engine.py | 15 +- bcipy/simulator/helpers/metrics.py | 20 +-- bcipy/simulator/helpers/sim_runner.py | 182 +++++++++++++------------ bcipy/simulator/sim.py | 2 - bcipy/simulator/sim_factory.py | 4 +- 7 files changed, 155 insertions(+), 132 deletions(-) diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 78ff3ad59..9271af8d0 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -4,7 +4,7 @@ from glob import glob from pathlib import Path -from bcipy.simulator.helpers.sim_runner import MultiSimRunner, SingleSimRunner +from bcipy.simulator.helpers.sim_runner import SimRunner from bcipy.simulator.sim_factory import SimulationFactory if __name__ == "__main__": @@ -32,6 +32,12 @@ required=True, help="Parameter File to be used") + parser.add_argument( + "-n", + type=int, + required=False, + default=1, + help="Number of times to run the simulation") parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) args = parser.parse_args() sim_args = vars(args) @@ -42,10 +48,5 @@ ] simulator = SimulationFactory.create(**sim_args) - - sim_run_count = simulator.get_parameters().get('sim_run_count', 1) - - runner = MultiSimRunner( - simulator, - sim_run_count) if sim_run_count > 1 else SingleSimRunner(simulator) + runner = SimRunner(simulator, args.n) runner.run() diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 8b1e9b9d5..2b0262b3d 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -3,35 +3,46 @@ import os import random import sys - - -def configure_logger(log_path, file_name): - """ configures logger for standard out nad file output """ - - log = logging.getLogger(None) # configuring root logger +from typing import Optional + + +def configure_logger(log_path: str, + file_name: str, + logger_name: Optional[str] = None, + use_stdout: bool = True): + """Configures logger for standard out and file output. + + Parameters + ---------- + log_path - directory in which log file will reside + file_name - name of the log file + logger_name - None configures the root logger; otherwise configures a named logger. + use_stdout - if True, INFO messages will be output to stdout. + """ + + log = logging.getLogger(logger_name) # configuring root logger log.setLevel(logging.DEBUG) # Create handlers for logging to the standard output and a file - stdoutHandler = logging.StreamHandler(stream=sys.stdout) - fileHandler = logging.FileHandler(f"{log_path}/{file_name}.log") + stdout_handler = logging.StreamHandler(stream=sys.stdout) + file_handler = logging.FileHandler(f"{log_path}/{file_name}") # Set the log levels on the handlers - stdoutHandler.setLevel(logging.INFO) - fileHandler.setLevel(logging.DEBUG) - - # Create a log format using Log Record attributes - fmt_file = logging.Formatter("%(levelname)s | %(filename)s >> %(message)s") + stdout_handler.setLevel(logging.INFO) + file_handler.setLevel(logging.DEBUG) - fmt = logging.Formatter("%(message)s") + fmt = '[%(asctime)s][%(name)s][%(levelname)s]: %(message)s' + fmt_file = logging.Formatter(fmt) + fmt_stdout = logging.Formatter("%(message)s") # Set the log format on each handler - stdoutHandler.setFormatter(fmt) - fileHandler.setFormatter(fmt_file) + stdout_handler.setFormatter(fmt_stdout) + file_handler.setFormatter(fmt_file) # Add each handler to the Logger object - if stdoutHandler not in log.handlers: - log.addHandler(stdoutHandler) + if use_stdout and stdout_handler not in log.handlers: + log.addHandler(stdout_handler) - log.addHandler(fileHandler) + log.addHandler(file_handler) def init_save_dir(output_path, save_dir_name): diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 8804ee3a1..c96b9dcfc 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -80,15 +80,16 @@ def load(self) -> DataEngine: Returns: self for chaining """ - log.debug( - f"Loading data from {len(self.source_dirs)} source directories") + if not self.data: + log.debug( + f"Loading data from {len(self.source_dirs)} source directories") - self.data = [ - self.data_processor.process(source_dir, self.parameters) - for source_dir in self.source_dirs - ] + self.data = [ + self.data_processor.process(source_dir, self.parameters) + for source_dir in self.source_dirs + ] - log.debug("Finished loading all data") + log.debug("Finished loading all data") return self def transform(self) -> DataEngine: diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py index c016c2a12..40ce1619d 100644 --- a/bcipy/simulator/helpers/metrics.py +++ b/bcipy/simulator/helpers/metrics.py @@ -1,7 +1,7 @@ import dataclasses from abc import ABC, abstractmethod from functools import reduce -from typing import Dict, Any, List +from typing import Any, Dict, List import numpy as np @@ -11,7 +11,7 @@ @dataclasses.dataclass -class SimMetrics1: +class SimMetrics: total_series: int = 0 total_inquiries: int = 0 total_decisions: int = 0 @@ -21,10 +21,10 @@ class SimMetrics1: inquiries_per_selection: float = 0.0 -def average_sim_metrics(run_scores: List[SimMetrics1]) -> Dict: - """ Averages the values in multiple SimMetrics1 objects """ +def average_sim_metrics(run_scores: List[SimMetrics]) -> Dict: + """ Averages the values in multiple SimMetrics objects """ - metric_acc_dict = dataclasses.asdict(SimMetrics1()) + metric_acc_dict = dataclasses.asdict(SimMetrics()) N = len(run_scores) if N < 1: @@ -46,7 +46,7 @@ def handle(self, sim) -> Dict[str, Any]: ... -class SimMetrics1Handler(RefereeHandler): +class SimMetricsHandler(RefereeHandler): def handle(self, sim) -> Dict[str, Any]: state: SimState = getattr(sim, "state_manager").get_state() @@ -75,7 +75,7 @@ def handle(self, sim) -> Dict[str, Any]: max_inq_time = max_inquiry_duration(parameters) total_time_spent = total_inquiries * max_inq_time - ret = SimMetrics1(total_series=total_series, total_inquiries=total_inquiries, + ret = SimMetrics(total_series=total_series, total_inquiries=total_inquiries, total_decisions=total_decisions, total_time_spent=total_time_spent, inquiries_per_selection=inquiries_per_selection, total_incorrect_decisions=total_incorrect_decisions) @@ -112,8 +112,8 @@ def __init__(self, metric_handlers=None, viz_handlers=None): self.inquiry_time: float = 1 # 1 inq -> 1 second # TODO maybe some configurable parameters for visualizations - def score(self, sim) -> SimMetrics1: - metrics = SimMetrics1() + def score(self, sim) -> SimMetrics: + metrics = SimMetrics() metrics_dict = dataclasses.asdict(metrics) for handler_name, handler in self.metric_handlers.items(): handler_metrics = handler.handle(sim) @@ -122,7 +122,7 @@ def score(self, sim) -> SimMetrics1: if key in metrics_dict: metrics_dict[key] = val - return SimMetrics1(**metrics_dict) + return SimMetrics(**metrics_dict) def visualize(self, sim): for handler_name, viz_handler in self.viz_handlers.items(): diff --git a/bcipy/simulator/helpers/sim_runner.py b/bcipy/simulator/helpers/sim_runner.py index a96b611a6..f52b326b3 100644 --- a/bcipy/simulator/helpers/sim_runner.py +++ b/bcipy/simulator/helpers/sim_runner.py @@ -1,112 +1,124 @@ """ Wrappers that run a simulation """ +import dataclasses import datetime import json +import logging import os import time -from typing import Dict +from typing import Dict, List, NamedTuple -from bcipy.helpers.parameters import Parameters +from bcipy.config import BCIPY_ROOT from bcipy.simulator.helpers import artifact -from bcipy.simulator.helpers.metrics import average_sim_metrics +from bcipy.simulator.helpers.metrics import SimMetrics, average_sim_metrics from bcipy.simulator.simulator_base import Simulator +log = logging.getLogger('sim_logger') -class SimRunner: - """An object that orchestrates one or more simulation runs.""" - def run(self): - """Run the simulation""" - ... +class RunSummary(NamedTuple): + """Summary for a simulation run.""" + run: int + target_text: str + typed_text: str + metrics: SimMetrics + + def to_dict(self) -> Dict: + """Convert to a dictionary""" + d = self._asdict() # pylint: disable=no-member + d['metrics'] = dataclasses.asdict(self.metrics) + return d -class MultiSimRunner(SimRunner): - """Runs multiple iterations of the simulation.""" +class SimRunner(): + """Runs one or more iterations of the simulation.""" def __init__(self, simulator: Simulator, - n: int, - save_dir=None, - iteration_sleep=0): - self.simulator: Simulator = simulator - self.parameters: Parameters = self.simulator.get_parameters() - self.n: int = n - self.iteration_sleep: int = iteration_sleep - - self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path( - ) + runs: int = 1, + iteration_sleep: int = 0): + self.simulator = simulator + self.runs = runs + self.iteration_sleep = iteration_sleep + self.save_dir = f"{self.default_save_location()}/{self.directory_name()}" + self.sim_log = 'sim.log' def run(self): - # making wrapper dir for all simulations - os.makedirs(self.wrapper_save_dir) - - # list of metrics from sim runs - all_run_metrics = [] - + """Run one or more simulations""" + os.makedirs(self.save_dir) + artifact.configure_logger(self.save_dir, + self.sim_log, + logger_name='sim_logger', + use_stdout=True) + log.info("Starting simulation...\n") + + run_summaries = [] # running simulator n times. resetting after each run - for i in range(self.n): + for i in range(self.runs): + summary = self.do_run(i) + log.info(summary.to_dict()) + run_summaries.append(summary) + time.sleep(self.iteration_sleep) - # creating save dir for sim_i, then mutating sim_i save_directory - sim_i_save_dir = artifact.init_save_dir(self.wrapper_save_dir, - f"run{i}") - self.simulator.save_dir = sim_i_save_dir - artifact.configure_logger(f"{sim_i_save_dir}/logs", "logs") + self.summarize_metrics(run_summaries) + log.info(f"\nResults logged to {self.save_dir}/{self.sim_log}") - # running simulator - self.simulator.run() + def do_run(self, run: int) -> RunSummary: + """Do a simulator run and return the computed summary.""" - if self.iteration_sleep > 0: - time.sleep(self.iteration_sleep) - - # aggregating metrics from each run - run_metrics = self.simulator.referee.score(self.simulator) - all_run_metrics.append(run_metrics) - - self.simulator.reset() - - # save averaged results to a file in root of wrapper dir - average_metrics = average_sim_metrics(all_run_metrics) - self.__save_average_metrics(average_metrics) - - def __make_default_save_path(self): - output_path = "bcipy/simulator/generated" - now_time = datetime.datetime.now().strftime("%m-%d-%H:%M") - dir_name = f"SIM_MULTI_{self.n}_{now_time}" + path = self.configure_run_directory(run) + self.simulator.save_dir = path + self.simulator.run() - return f"{output_path}/{dir_name}" + state = self.simulator.state_manager.get_state() + run_metrics = self.simulator.referee.score(self.simulator) + + summary = RunSummary(run + 1, + target_text=state.target_sentence, + typed_text=state.current_sentence, + metrics=run_metrics) + self.simulator.reset() + return summary + + def configure_run_directory(self, run: int) -> str: + """Create the necessary directories and configure the logger. + Returns the run directory. + """ + run_name = f"run_{run + 1}" + path = f"{self.save_dir}/{run_name}" + os.mkdir(path) + artifact.configure_logger(log_path=path, + file_name=f"{run_name}.log", + use_stdout=False) + return path + + def summarize_metrics(self, run_summaries: List[RunSummary]) -> None: + """Summarize metrics from all runs.""" + all_run_metrics = [run.metrics for run in run_summaries] + self.__save_average_metrics(average_sim_metrics(all_run_metrics)) + + summary_dict = { + summary.run: summary.to_dict() + for summary in run_summaries + } + self.save_run_summaries(summary_dict) + + def default_save_location(self) -> str: + """Directory in which simulations are saved.""" + return f"{BCIPY_ROOT}/simulator/generated" + + def directory_name(self) -> str: + """Name of the directory for a new simulation run.""" + return datetime.datetime.now().strftime("SIM_%m-%d-%Y_%H_%M_%S") def __save_average_metrics(self, avg_metric_dict: Dict): - """ Writing average dictionary of metrics to a json file in root of MultiRun save dir """ + """ Write average dictionary of metrics to a json file in root of save dir.""" - with open(f"{self.wrapper_save_dir}/avg_metrics.json", - 'w') as output_file: - json.dump(avg_metric_dict, output_file, indent=1) - - -class SingleSimRunner(SimRunner): - """Runs the simulation once.""" - - def __init__(self, simulator: Simulator, save_dir=None): - self.simulator: Simulator = simulator - self.parameters: Parameters = self.simulator.get_parameters() - - self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path( - ) - - def run(self): - # logging and save details - now_time = datetime.datetime.now().strftime("%m-%d-%H:%M") - save_dir_path = artifact.init_save_dir(self.wrapper_save_dir, now_time) - - # configuring logger to save to {output_wrapper_path}/logs - log_path = f"{save_dir_path}/logs" - artifact.configure_logger(log_path, now_time) - - # mutating simulator to save to specific save_dir - self.simulator.save_dir = save_dir_path - - # running sim - self.simulator.run() + with open(f"{self.save_dir}/avg_metrics.json", 'w', + encoding='utf8') as output_file: + json.dump(avg_metric_dict, output_file, indent=2) - def __make_default_save_path(self): - output_path = "bcipy/simulator/generated" - return f"{output_path}" + def save_run_summaries(self, summary_dict: Dict): + """Write the summary for each run in the save directory.""" + with open(f"{self.save_dir}/run_summaries.json", 'w', + encoding='utf8') as output: + json.dump(summary_dict, output, indent=2) diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 8b8cbf946..ae680f70a 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -104,8 +104,6 @@ def run(self): log.info(f"FINAL TYPED: {final_state.current_sentence}") log.info(self.referee.score(self).__dict__) - log.debug(f"Final State: {final_state}") - self.save_run() def __make_stimuli(self, state: SimState): diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 293a15b5a..dc161987e 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -5,7 +5,7 @@ from bcipy.helpers.load import load_json_parameters from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.metrics import (MetricReferee, RefereeImpl, - SimMetrics1Handler) + SimMetricsHandler) from bcipy.simulator.helpers.model_handler import (ModelHandler, SigLmModelHandler1) from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler @@ -40,7 +40,7 @@ def create(source_dirs: List[Path], model_handler: ModelHandler = SigLmModelHandler1( model_file, base_parameters) referee: MetricReferee = RefereeImpl( - metric_handlers={'basic': SimMetrics1Handler()}) + metric_handlers={'basic': SimMetricsHandler()}) sim = SimulatorCopyPhrase(data_engine, model_handler, From 3ef8a683173c1e84f48d22bc0bcf4262f0befb25 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Aug 2024 15:30:46 -0700 Subject: [PATCH 278/330] Refactor to capture logging from data engine --- bcipy/simulator/__main__.py | 4 +++- bcipy/simulator/helpers/artifact.py | 21 +++++---------------- bcipy/simulator/helpers/data_engine.py | 13 ++++++------- bcipy/simulator/helpers/sim_runner.py | 24 ++++++++++++++++++------ bcipy/simulator/sim_factory.py | 1 - 5 files changed, 32 insertions(+), 31 deletions(-) diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 9271af8d0..628d604b4 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -47,6 +47,8 @@ if Path(d).is_dir() ] + runner = SimRunner(simulator=None, runs = args.n) + runner.setup() simulator = SimulationFactory.create(**sim_args) - runner = SimRunner(simulator, args.n) + runner.simulator = simulator runner.run() diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 2b0262b3d..78119417f 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -1,10 +1,13 @@ """ Handles artifacts related logic ie. logs, save dir creation, result.json, ...""" import logging -import os -import random import sys from typing import Optional +# For a simulation, two loggers are configured: a top level logger summarizing +# setup and progress, and a logger for each simulation run. The root logger is +# re-configured for each simulation run. +TOP_LEVEL_LOGGER_NAME = 'sim_logger' + def configure_logger(log_path: str, file_name: str, @@ -43,17 +46,3 @@ def configure_logger(log_path: str, log.addHandler(stdout_handler) log.addHandler(file_handler) - - -def init_save_dir(output_path, save_dir_name): - """ creating wrapper dir to save sim results to. - - Saves to {output_path} - - Adds a unique 4-digit id to end - """ - - unique_id = random.sample(range(1000, 10000), 1)[0] - save_dir = f"{output_path}/SIM_{save_dir_name}_{unique_id}" - os.makedirs(save_dir) - os.makedirs(f"{save_dir}/logs") - - return save_dir diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index c96b9dcfc..d1db7d88a 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -7,11 +7,12 @@ import pandas as pd from bcipy.helpers.parameters import Parameters +from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME from bcipy.simulator.helpers.signal_helpers import (EegRawDataProcessor, ExtractedExperimentData, RawDataProcessor) -log = logging.getLogger(__name__) +log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) class DataEngine(ABC): @@ -82,12 +83,10 @@ def load(self) -> DataEngine: """ if not self.data: log.debug( - f"Loading data from {len(self.source_dirs)} source directories") - - self.data = [ - self.data_processor.process(source_dir, self.parameters) - for source_dir in self.source_dirs - ] + f"Loading data from {len(self.source_dirs)} source directories:") + for source_dir in self.source_dirs: + log.debug(source_dir) + self.data.append(self.data_processor.process(source_dir, self.parameters)) log.debug("Finished loading all data") return self diff --git a/bcipy/simulator/helpers/sim_runner.py b/bcipy/simulator/helpers/sim_runner.py index f52b326b3..bee12c526 100644 --- a/bcipy/simulator/helpers/sim_runner.py +++ b/bcipy/simulator/helpers/sim_runner.py @@ -5,6 +5,7 @@ import logging import os import time +from pathlib import Path from typing import Dict, List, NamedTuple from bcipy.config import BCIPY_ROOT @@ -12,7 +13,7 @@ from bcipy.simulator.helpers.metrics import SimMetrics, average_sim_metrics from bcipy.simulator.simulator_base import Simulator -log = logging.getLogger('sim_logger') +log = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) class RunSummary(NamedTuple): @@ -40,15 +41,26 @@ def __init__(self, self.runs = runs self.iteration_sleep = iteration_sleep self.save_dir = f"{self.default_save_location()}/{self.directory_name()}" + + self.logger_name = artifact.TOP_LEVEL_LOGGER_NAME self.sim_log = 'sim.log' + def setup(self) -> None: + """Setup the folder structure and logging for the simulation.""" + if not self.setup_complete(): + os.makedirs(self.save_dir) + artifact.configure_logger(self.save_dir, + self.sim_log, + logger_name=self.logger_name, + use_stdout=True) + + def setup_complete(self) -> bool: + """Check if setup has already been run.""" + return Path(self.save_dir).is_dir() + def run(self): """Run one or more simulations""" - os.makedirs(self.save_dir) - artifact.configure_logger(self.save_dir, - self.sim_log, - logger_name='sim_logger', - use_stdout=True) + self.setup() log.info("Starting simulation...\n") run_summaries = [] diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index dc161987e..eeb274a9b 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -24,7 +24,6 @@ def create(source_dirs: List[Path], save_dir=None, **kwargs) -> Simulator: """Create a Simulation, performing all of the necessary setup.""" - # out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) # combining parameters model_file = Path(smodel_files.pop()) From 29607be0e696e86e9742ba4388c207c01d164822 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Aug 2024 16:16:47 -0700 Subject: [PATCH 279/330] Refactor sim directory creation code out of sim_runner. Refactor to only save parameters.json once per simulation. --- bcipy/simulator/__main__.py | 7 ++++-- bcipy/simulator/helpers/artifact.py | 31 ++++++++++++++++++++++++++ bcipy/simulator/helpers/sim_runner.py | 32 ++++++--------------------- bcipy/simulator/sim.py | 6 ++--- 4 files changed, 45 insertions(+), 31 deletions(-) diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 628d604b4..a79a50caf 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -4,6 +4,7 @@ from glob import glob from pathlib import Path +from bcipy.simulator.helpers import artifact from bcipy.simulator.helpers.sim_runner import SimRunner from bcipy.simulator.sim_factory import SimulationFactory @@ -47,8 +48,10 @@ if Path(d).is_dir() ] - runner = SimRunner(simulator=None, runs = args.n) - runner.setup() + sim_dir = artifact.init_simulation_dir() simulator = SimulationFactory.create(**sim_args) + runner = SimRunner(save_dir=sim_dir, + simulator=simulator, + runs=args.n) runner.simulator = simulator runner.run() diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 78119417f..459698182 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -1,12 +1,18 @@ """ Handles artifacts related logic ie. logs, save dir creation, result.json, ...""" +import datetime import logging +import os import sys from typing import Optional +from bcipy.config import BCIPY_ROOT + # For a simulation, two loggers are configured: a top level logger summarizing # setup and progress, and a logger for each simulation run. The root logger is # re-configured for each simulation run. TOP_LEVEL_LOGGER_NAME = 'sim_logger' +DEFAULT_LOGFILE_NAME = 'sim.log' +DEFAULT_SAVE_LOCATION = f"{BCIPY_ROOT}/simulator/generated" def configure_logger(log_path: str, @@ -46,3 +52,28 @@ def configure_logger(log_path: str, log.addHandler(stdout_handler) log.addHandler(file_handler) + + +def init_simulation_dir(save_location: str = DEFAULT_SAVE_LOCATION, + logfile_name: str = DEFAULT_LOGFILE_NAME) -> str: + """Setup the folder structure and logging for a simulation. + + Parameters + ---------- + save_location - optional path in which new simulation directory will be created. + logfile_name - optional name of the top level logfile within that directory. + + Returns the path of the simulation directory. + """ + save_dir = f"{save_location}/{directory_name()}" + os.makedirs(save_dir) + configure_logger(save_dir, + logfile_name, + logger_name=TOP_LEVEL_LOGGER_NAME, + use_stdout=True) + return save_dir + + +def directory_name() -> str: + """Name of the directory for a new simulation run.""" + return datetime.datetime.now().strftime("SIM_%m-%d-%Y_%H_%M_%S") diff --git a/bcipy/simulator/helpers/sim_runner.py b/bcipy/simulator/helpers/sim_runner.py index bee12c526..8e5d7ca3c 100644 --- a/bcipy/simulator/helpers/sim_runner.py +++ b/bcipy/simulator/helpers/sim_runner.py @@ -1,6 +1,5 @@ """ Wrappers that run a simulation """ import dataclasses -import datetime import json import logging import os @@ -8,7 +7,6 @@ from pathlib import Path from typing import Dict, List, NamedTuple -from bcipy.config import BCIPY_ROOT from bcipy.simulator.helpers import artifact from bcipy.simulator.helpers.metrics import SimMetrics, average_sim_metrics from bcipy.simulator.simulator_base import Simulator @@ -34,33 +32,25 @@ class SimRunner(): """Runs one or more iterations of the simulation.""" def __init__(self, + save_dir: str, simulator: Simulator, runs: int = 1, + sim_log: str = artifact.DEFAULT_LOGFILE_NAME, iteration_sleep: int = 0): self.simulator = simulator self.runs = runs self.iteration_sleep = iteration_sleep - self.save_dir = f"{self.default_save_location()}/{self.directory_name()}" - - self.logger_name = artifact.TOP_LEVEL_LOGGER_NAME - self.sim_log = 'sim.log' - - def setup(self) -> None: - """Setup the folder structure and logging for the simulation.""" - if not self.setup_complete(): - os.makedirs(self.save_dir) - artifact.configure_logger(self.save_dir, - self.sim_log, - logger_name=self.logger_name, - use_stdout=True) + self.save_dir = save_dir + self.sim_log = sim_log def setup_complete(self) -> bool: """Check if setup has already been run.""" - return Path(self.save_dir).is_dir() + return Path(self.save_dir).is_dir() and self.simulator is not None def run(self): """Run one or more simulations""" - self.setup() + assert self.setup_complete(), "Setup is not complete." + self.simulator.parameters.save(self.save_dir) log.info("Starting simulation...\n") run_summaries = [] @@ -114,14 +104,6 @@ def summarize_metrics(self, run_summaries: List[RunSummary]) -> None: } self.save_run_summaries(summary_dict) - def default_save_location(self) -> str: - """Directory in which simulations are saved.""" - return f"{BCIPY_ROOT}/simulator/generated" - - def directory_name(self) -> str: - """Name of the directory for a new simulation run.""" - return datetime.datetime.now().strftime("SIM_%m-%d-%Y_%H_%M_%S") - def __save_average_metrics(self, avg_metric_dict: Dict): """ Write average dictionary of metrics to a json file in root of save dir.""" diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index ae680f70a..9efda6a9c 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -161,12 +161,10 @@ def save_run(self): metric_dict.update(final_state_json) # adding state data to metrics # writing result.json - with open(f"{self.save_dir}/result.json", 'w') as output_file: + with open(f"{self.save_dir}/session.json", 'w', + encoding='utf8') as output_file: json.dump(metric_dict, output_file, indent=1) - # writing params - self.parameters.save(directory=self.save_dir) - def reset(self): self.state_manager.reset_state() From e58b662f2c6bd74c5639d57ab7a7822d6cc38981 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Aug 2024 17:08:13 -0700 Subject: [PATCH 280/330] Logged simulation config --- bcipy/simulator/helpers/data_engine.py | 4 +-- bcipy/simulator/helpers/model_handler.py | 9 ++++++ bcipy/simulator/helpers/sampler.py | 2 ++ bcipy/simulator/sim.py | 3 ++ bcipy/simulator/sim_factory.py | 36 +++++++++++++++--------- 5 files changed, 39 insertions(+), 15 deletions(-) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index d1db7d88a..6df802f54 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -84,8 +84,8 @@ def load(self) -> DataEngine: if not self.data: log.debug( f"Loading data from {len(self.source_dirs)} source directories:") - for source_dir in self.source_dirs: - log.debug(source_dir) + for i, source_dir in enumerate(self.source_dirs): + log.debug(f"{i+1}. {Path(source_dir).name}") self.data.append(self.data_processor.process(source_dir, self.parameters)) log.debug("Finished loading all data") diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index 8da949b25..7294aa1dc 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -2,6 +2,7 @@ import logging import pickle from abc import ABC, abstractmethod +from pathlib import Path import numpy as np @@ -118,3 +119,11 @@ def get_model(self, key=None): return self.lm_model else: raise RuntimeError(f"Can't find model {key}") + + def __str__(self): + props = { + 'signal_model': self.signal_model.__class__.__name__, + 'language_model': self.lm_model.__class__.__name__, + 'sm_file': f".../{Path(self.sm_model_file).parent.name}/{Path(self.sm_model_file).name}" + } + return f"<{self.__class__.__name__} {props}>" diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 96a2d48c0..66639f861 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -75,6 +75,8 @@ def sample(self, state: SimState) -> np.ndarray: def set_reshaper(self, reshaper: Callable): self.model_input_reshaper = reshaper + def __str__(self): + return f"<{self.__class__.__name__}>" def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: """Default data reshaper. diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 9efda6a9c..4a7e1c57f 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -170,3 +170,6 @@ def reset(self): def get_parameters(self): return self.parameters.copy() + + def __str__(self): + return f"<{self.__class__.__name__}>" diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index eeb274a9b..a3111f194 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -1,18 +1,19 @@ """ Factory for Simulator objects """ +import logging from pathlib import Path from typing import List from bcipy.helpers.load import load_json_parameters +from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.metrics import (MetricReferee, RefereeImpl, - SimMetricsHandler) -from bcipy.simulator.helpers.model_handler import (ModelHandler, - SigLmModelHandler1) -from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler -from bcipy.simulator.helpers.state_manager import (StateManager, - StateManagerImpl) +from bcipy.simulator.helpers.metrics import RefereeImpl, SimMetricsHandler +from bcipy.simulator.helpers.model_handler import SigLmModelHandler1 +from bcipy.simulator.helpers.sampler import EEGByLetterSampler +from bcipy.simulator.helpers.state_manager import StateManagerImpl from bcipy.simulator.sim import Simulator, SimulatorCopyPhrase +log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) + class SimulationFactory: """ Factory class to create Simulator instances """ @@ -27,6 +28,7 @@ def create(source_dirs: List[Path], # combining parameters model_file = Path(smodel_files.pop()) + sim_parameters = load_json_parameters(sim_param_path, value_cast=True) params_path: str = kwargs.get('parameters', None) base_parameters = load_json_parameters(params_path, value_cast=True) @@ -34,12 +36,12 @@ def create(source_dirs: List[Path], data_engine = RawDataEngine(list(map(str, source_dirs)), base_parameters) - state_manager: StateManager = StateManagerImpl(base_parameters) - sampler: Sampler = EEGByLetterSampler(data_engine) - model_handler: ModelHandler = SigLmModelHandler1( - model_file, base_parameters) - referee: MetricReferee = RefereeImpl( - metric_handlers={'basic': SimMetricsHandler()}) + state_manager = StateManagerImpl(base_parameters) + sampler = EEGByLetterSampler(data_engine) + model_handler = SigLmModelHandler1(model_file, base_parameters) + + + referee = RefereeImpl(metric_handlers={'basic': SimMetricsHandler()}) sim = SimulatorCopyPhrase(data_engine, model_handler, @@ -48,5 +50,13 @@ def create(source_dirs: List[Path], referee, parameters=base_parameters, save_dir=save_dir) + config = { + 'parameters_directory': Path(params_path).parent.name, + 'sampler': str(sampler), + 'model': str(model_handler), + 'task': str(sim) + } + for key, value in config.items(): + log.debug(f"{key}: {value}") return sim From 18b3c958845a441befa5e89e7352bb110aafa5a9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 13 Aug 2024 17:10:31 -0700 Subject: [PATCH 281/330] Linting --- bcipy/simulator/helpers/artifact.py | 6 +++--- bcipy/simulator/helpers/metrics.py | 10 ++++++---- bcipy/simulator/helpers/sampler.py | 1 + bcipy/simulator/sim_factory.py | 3 +-- 4 files changed, 11 insertions(+), 9 deletions(-) diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 459698182..8338fa89e 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -20,7 +20,7 @@ def configure_logger(log_path: str, logger_name: Optional[str] = None, use_stdout: bool = True): """Configures logger for standard out and file output. - + Parameters ---------- log_path - directory in which log file will reside @@ -55,9 +55,9 @@ def configure_logger(log_path: str, def init_simulation_dir(save_location: str = DEFAULT_SAVE_LOCATION, - logfile_name: str = DEFAULT_LOGFILE_NAME) -> str: + logfile_name: str = DEFAULT_LOGFILE_NAME) -> str: """Setup the folder structure and logging for a simulation. - + Parameters ---------- save_location - optional path in which new simulation directory will be created. diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py index 40ce1619d..766f767de 100644 --- a/bcipy/simulator/helpers/metrics.py +++ b/bcipy/simulator/helpers/metrics.py @@ -75,10 +75,12 @@ def handle(self, sim) -> Dict[str, Any]: max_inq_time = max_inquiry_duration(parameters) total_time_spent = total_inquiries * max_inq_time - ret = SimMetrics(total_series=total_series, total_inquiries=total_inquiries, - total_decisions=total_decisions, total_time_spent=total_time_spent, - inquiries_per_selection=inquiries_per_selection, - total_incorrect_decisions=total_incorrect_decisions) + ret = SimMetrics(total_series=total_series, + total_inquiries=total_inquiries, + total_decisions=total_decisions, + total_time_spent=total_time_spent, + inquiries_per_selection=inquiries_per_selection, + total_incorrect_decisions=total_incorrect_decisions) return dataclasses.asdict(ret) diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 66639f861..34557cd4b 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -78,6 +78,7 @@ def set_reshaper(self, reshaper: Callable): def __str__(self): return f"<{self.__class__.__name__}>" + def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: """Default data reshaper. diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index a3111f194..aad05f868 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -28,7 +28,7 @@ def create(source_dirs: List[Path], # combining parameters model_file = Path(smodel_files.pop()) - + sim_parameters = load_json_parameters(sim_param_path, value_cast=True) params_path: str = kwargs.get('parameters', None) base_parameters = load_json_parameters(params_path, value_cast=True) @@ -40,7 +40,6 @@ def create(source_dirs: List[Path], sampler = EEGByLetterSampler(data_engine) model_handler = SigLmModelHandler1(model_file, base_parameters) - referee = RefereeImpl(metric_handlers={'basic': SimMetricsHandler()}) sim = SimulatorCopyPhrase(data_engine, From 0b969c0e37830c59d0871874a26f36a312a0c08f Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 14 Aug 2024 15:10:45 -0700 Subject: [PATCH 282/330] Remove breakpoint in code --- bcipy/helpers/language_model.py | 1 - 1 file changed, 1 deletion(-) diff --git a/bcipy/helpers/language_model.py b/bcipy/helpers/language_model.py index 1c8c1f363..5b1d083bc 100644 --- a/bcipy/helpers/language_model.py +++ b/bcipy/helpers/language_model.py @@ -49,7 +49,6 @@ def init_language_model(parameters: dict) -> LanguageModel: # select the relevant parameters into a dict. params = {key: parameters[key] for key in args & parameters.keys()} - breakpoint() return model(response_type=ResponseType.SYMBOL, symbol_set=alphabet(parameters), From 9440eda737f00f6bcab58ac0f5acb8d8093404a3 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 14 Aug 2024 15:11:04 -0700 Subject: [PATCH 283/330] Revert parameters --- bcipy/parameters/parameters.json | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index acbbafa4b..859d2bb63 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -1,6 +1,6 @@ { "fake_data": { - "value": "true", + "value": "false", "section": "bci_config", "readableName": "Fake EEG Data On/Off", "helpTip": "If ‘true’, fake EEG data will be used instead of real EEG data. Useful for testing by software development team.", @@ -337,7 +337,7 @@ "type": "int" }, "time_flash": { - "value": "0.25", + "value": "0.2", "section": "bci_config", "readableName": "Stimulus Presentation Duration", "helpTip": "Specifies the duration of time (in seconds) that each stimulus is displayed in an inquiry.", @@ -657,7 +657,7 @@ "type": "int" }, "lang_model_type": { - "value": "KENLM", + "value": "UNIFORM", "section": "lang_model_config", "readableName": "Language Model Type", "helpTip": "Specifies which language model to use. Default: UNIFORM", From c66bcfca1912218b860567e61b4ca50dde754ac2 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 14 Aug 2024 15:12:22 -0700 Subject: [PATCH 284/330] Output simulation run as session.json data that can be analyzed and visualized with existing BciPy tools --- bcipy/simulator/sim.py | 65 ++++++++++++++++++++++++++++++++++++++---- 1 file changed, 60 insertions(+), 5 deletions(-) diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 4a7e1c57f..0fb140334 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -9,6 +9,7 @@ from bcipy.helpers import stimuli, symbols from bcipy.helpers.parameters import Parameters +from bcipy.helpers.session import session_excel from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine from bcipy.simulator.helpers.log_utils import (fmt_reshaped_evidence, @@ -21,7 +22,7 @@ format_sim_state_dump) from bcipy.simulator.helpers.types import InquiryResult, SimEvidence from bcipy.simulator.simulator_base import Simulator -from bcipy.task.data import EvidenceType +from bcipy.task.data import EvidenceType, Inquiry, Session log = logging.getLogger(__name__) @@ -69,6 +70,13 @@ def run(self): assert self.save_dir, "Save directory not set" log.info(f"SIM START with target word {self.state_manager.get_state().target_sentence}") + session = Session( + save_location=self.save_dir, + task='Copy Phrase Simulation', + mode='RSVP', + symbol_set=self.symbol_set, + decision_threshold=self.parameters['decision_threshold']) + while not self.state_manager.is_done(): self.state_manager.mutate_state('display_alphabet', self.__make_stimuli(self.state_manager.get_state())) @@ -93,8 +101,12 @@ def run(self): inq_record: InquiryResult = self.state_manager.update(reshaped_evidence) updated_state = self.state_manager.get_state() + data = self.new_data_record(curr_state, inq_record) + session.add_sequence(data) + if inq_record.decision: log.info(f"Decided {inq_record.decision} for target {inq_record.target}") + session.add_series() log.info(f"Current typed: {updated_state.current_sentence}") sleep(self.parameters.get("sim_sleep_time", 0.5)) @@ -104,7 +116,7 @@ def run(self): log.info(f"FINAL TYPED: {final_state.current_sentence}") log.info(self.referee.score(self).__dict__) - self.save_run() + self.save_run(session) def __make_stimuli(self, state: SimState): """ @@ -151,7 +163,42 @@ def load_parameters(self, params: Optional[Parameters]): else: return self.data_engine.get_parameters() - def save_run(self): + def new_data_record(self, inquiry_state: SimState, inquiry_result: InquiryResult) -> Inquiry: + """Construct a new inquiry data record. + + Parameters + ---------- + - inquiry_state : state prior to presenting the inquiry + - inquiry_result : result of presenting the inquiry + - post_inquiry_state : updated state + + Returns + ------- + Inquiry data for the current schedule + """ + target_info = [ + 'target' if inquiry_result == sym else 'nontarget' + for sym in inquiry_result.stimuli + ] + + data = Inquiry(stimuli=inquiry_result.stimuli, + timing=[], + triggers=[], + target_info=target_info, + target_letter=inquiry_result.target, + current_text=inquiry_state.current_sentence, + target_text=inquiry_state.target_sentence) + data.precision = 4 + data.evidences = { + val.evidence_type: val.evidence + for val in inquiry_result.evidences.values() + } + if EvidenceType.LM not in data.evidences: + data.evidences[EvidenceType.LM] = [] + data.likelihood = list(inquiry_result.fused_likelihood) + return data + + def save_run(self, session: Session): """ Outputs the results of a run to json file """ assert self.save_dir, "Save directory not set" # creating result.json object with final state and metrics @@ -161,9 +208,17 @@ def save_run(self): metric_dict.update(final_state_json) # adding state data to metrics # writing result.json - with open(f"{self.save_dir}/session.json", 'w', + with open(f"{self.save_dir}/result.json", 'w', encoding='utf8') as output_file: - json.dump(metric_dict, output_file, indent=1) + json.dump(metric_dict, output_file, indent=2) + + with open(f"{self.save_dir}/session.json", 'wt', + encoding='utf8') as session_file: + json.dump(session.as_dict(), session_file, indent=2) + + if session.has_evidence(): + session_excel(session=session, + excel_file=f"{self.save_dir}/session.xlsx") def reset(self): self.state_manager.reset_state() From 586e4d10a065404fd0d4977080ceae4a2385e3f8 Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Mon, 19 Aug 2024 12:24:30 -0400 Subject: [PATCH 285/330] Artifact Detection and BCI-Fit Artifact Report (#336) --- bcipy/helpers/demo/demo_report.py | 131 ++++ bcipy/helpers/report.py | 70 ++- bcipy/helpers/stimuli.py | 34 +- bcipy/helpers/triggers.py | 1 + bcipy/helpers/visualization.py | 2 +- bcipy/parameters/devices.json | 10 +- bcipy/signal/evaluate/README.md | 105 +++- bcipy/signal/evaluate/__init__.py | 5 - bcipy/signal/evaluate/artifact.py | 595 ++++++++++++++++++ bcipy/signal/evaluate/evaluator.py | 48 -- bcipy/signal/evaluate/rules.py | 82 --- bcipy/signal/tests/evaluate/test_artifact.py | 128 ++++ bcipy/signal/tests/evaluate/test_evaluator.py | 56 -- bcipy/signal/tests/evaluate/test_rules.py | 62 -- 14 files changed, 1023 insertions(+), 306 deletions(-) create mode 100644 bcipy/helpers/demo/demo_report.py create mode 100644 bcipy/signal/evaluate/artifact.py delete mode 100644 bcipy/signal/evaluate/evaluator.py delete mode 100644 bcipy/signal/evaluate/rules.py create mode 100644 bcipy/signal/tests/evaluate/test_artifact.py delete mode 100644 bcipy/signal/tests/evaluate/test_evaluator.py delete mode 100644 bcipy/signal/tests/evaluate/test_rules.py diff --git a/bcipy/helpers/demo/demo_report.py b/bcipy/helpers/demo/demo_report.py new file mode 100644 index 000000000..0936d214d --- /dev/null +++ b/bcipy/helpers/demo/demo_report.py @@ -0,0 +1,131 @@ +from pathlib import Path +from bcipy.helpers.load import load_json_parameters, load_raw_data, load_experimental_data +from bcipy.helpers.triggers import trigger_decoder, TriggerType +from bcipy.config import ( + BCIPY_ROOT, + DEFAULT_PARAMETER_FILENAME, + RAW_DATA_FILENAME, + TRIGGER_FILENAME, + DEFAULT_DEVICE_SPEC_FILENAME) + +from bcipy.acquisition import devices +from bcipy.helpers.acquisition import analysis_channels +from bcipy.helpers.visualization import visualize_erp +from bcipy.signal.process import get_default_transform +from bcipy.signal.evaluate.artifact import ArtifactDetection +from bcipy.helpers.report import Report, SignalReportSection, SessionReportSection + + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser() + parser.add_argument( + '-p', + '--path', + help='Path to the directory with >= 1 sessions to be analyzed for artifacts', + required=False) + + args = parser.parse_args() + colabel = True + # if no path is provided, prompt for one using a GUI + path = args.path + if not path: + path = load_experimental_data() + + trial_window = (0, 1.0) + + positions = None + for session in Path(path).iterdir(): + # loop through the sessions, pausing after each one to allow for manual stopping + if session.is_dir(): + print(f'Processing {session}') + prompt = input('Hit enter to continue or type "skip" to skip processing: ') + if prompt != 'skip': + # load the parameters from the data directory + parameters = load_json_parameters( + f'{session}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) + + # load the raw data from the data directory + raw_data = load_raw_data(Path(session, f'{RAW_DATA_FILENAME}.csv')) + type_amp = raw_data.daq_type + channels = raw_data.channels + sample_rate = raw_data.sample_rate + downsample_rate = parameters.get("down_sampling_rate") + notch_filter = parameters.get("notch_filter_frequency") + filter_high = parameters.get("filter_high") + filter_low = parameters.get("filter_low") + filter_order = parameters.get("filter_order") + static_offset = parameters.get("static_trigger_offset") + + default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=notch_filter, + bandpass_low=filter_low, + bandpass_high=filter_high, + bandpass_order=filter_order, + downsample_factor=downsample_rate, + ) + + # load the triggers + if colabel: + trigger_type, trigger_timing, trigger_label = trigger_decoder( + offset=parameters.get('static_trigger_offset'), + trigger_path=f"{session}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + triggers = (trigger_type, trigger_timing, trigger_label) + else: + triggers = None + + devices.load(Path(BCIPY_ROOT, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(raw_data.daq_type) + channel_map = analysis_channels(channels, device_spec) + + # check the device spec for any frontal channels to use for EOG detection + eye_channels = [] + for channel in device_spec.channels: + if 'F' in channel: + eye_channels.append(channel) + if len(eye_channels) == 0: + eye_channels = None + + artifact_detector = ArtifactDetection( + raw_data, + parameters, + device_spec, + eye_channels=eye_channels, + session_triggers=triggers) + + detected = artifact_detector.detect_artifacts() + figure_handles = visualize_erp( + raw_data, + channel_map, + trigger_timing, + trigger_label, + trial_window, + transform=default_transform, + plot_average=True, + plot_topomaps=True, + ) + + # Try to find a pkl file in the session folder + pkl_file = None + for file in session.iterdir(): + if file.suffix == '.pkl': + pkl_file = file + break + + if pkl_file: + auc = pkl_file.stem.split('_')[-1] + else: + auc = 'No Signal Model found in session folder' + + sr = SignalReportSection(figure_handles, artifact_detector) + report = Report(session) + session = {'Label': 'Demo Session Report', 'AUC': auc} + session_text = SessionReportSection(session) + report.add(session_text) + report.add(sr) + report.compile() + report.save() diff --git a/bcipy/helpers/report.py b/bcipy/helpers/report.py index 6029ba5b0..4836a7a0c 100644 --- a/bcipy/helpers/report.py +++ b/bcipy/helpers/report.py @@ -1,6 +1,9 @@ +# mypy: disable-error-code="union-attr" import io from abc import ABC -from typing import List, Optional +from typing import List, Optional, Tuple + +from matplotlib import pyplot as plt from matplotlib.figure import Figure from reportlab.platypus import SimpleDocTemplate, Paragraph, Image @@ -10,6 +13,7 @@ from reportlab.lib.units import inch from bcipy.config import BCIPY_FULL_LOGO_PATH +from bcipy.signal.evaluate.artifact import ArtifactDetection class ReportSection(ABC): @@ -40,9 +44,15 @@ class SignalReportSection(ReportSection): def __init__( self, - figures: List[Figure]) -> None: + figures: List[Figure], + artifact: Optional[ArtifactDetection] = None) -> None: self.figures = figures self.report_flowables: List[Flowable] = [] + self.artifact = artifact + + if self.artifact: + assert self.artifact.analysis_done is not False, ( + "If providing artifact for this report, an analysis must be complete to run this report.") self.style = getSampleStyleSheet() def compile(self) -> Flowable: @@ -51,9 +61,65 @@ def compile(self) -> Flowable: Compiles the Signal Report sections into a flowable that can be used to generate a Report. """ self.report_flowables.append(self._create_header()) + if self.artifact: + self.report_flowables.append(self._create_artifact_section()) self.report_flowables.extend(self._create_epochs_section()) + return KeepTogether(self.report_flowables) + def _create_artifact_section(self) -> Flowable: + """Create Artifact Section. + + Creates a paragraph with the artifact information. This is only included if an artifact detection is provided. + """ + artifact_report = [] + artifacts_detected = self.artifact.dropped + artifact_text = 'Artifact:' + artifact_section = Paragraph(artifact_text, self.style['BodyText']) + artifact_overview = f'Artifacts Detected: {artifacts_detected}' + artifact_section = Paragraph(artifact_overview, self.style['BodyText']) + artifact_report.append(artifact_section) + + if self.artifact.eog_annotations: + eog_artifacts = f'EOG Artifacts: {len(self.artifact.eog_annotations)}' + eog_section = Paragraph(eog_artifacts, self.style['BodyText']) + artifact_report.append(eog_section) + heatmap = self._create_heatmap( + self.artifact.eog_annotations.onset, + (0, self.artifact.total_time), + 'EOG') + artifact_report.append(heatmap) + + if self.artifact.voltage_annotations: + voltage_artifacts = f'Voltage Artifacts: {len(self.artifact.voltage_annotations)}' + voltage_section = Paragraph(voltage_artifacts, self.style['BodyText']) + artifact_report.append(voltage_section) + + # create a heatmap with the onset values of the voltage artifacts + onsets = self.artifact.voltage_annotations.onset + heatmap = self._create_heatmap( + onsets, + (0, self.artifact.total_time), + 'Voltage') + artifact_report.append(heatmap) + return KeepTogether(artifact_report) + + def _create_heatmap(self, onsets: List[float], range: Tuple[float, float], type: str) -> Image: + """Create Heatmap. + + Creates a heatmap image with the onset values of the voltage artifacts. + """ + # create a heatmap with the onset values + fig, ax = plt.subplots() + fig.set_size_inches(6, 3) + ax.hist(onsets, bins=100, range=range, color='red', alpha=0.7) + ax.set_title(f'{type} Artifact Onsets') + ax.set_xlabel('Time (s)') + # make the label text smaller + ax.set_ylabel('Frequency') + heatmap = self.convert_figure_to_image(fig) + return heatmap + def _create_epochs_section(self) -> List[Image]: """Create Epochs Section. diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 567e2d8ef..6eeaf99d1 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -412,21 +412,37 @@ def update_inquiry_timing(timing: List[List[float]], downsample: int) -> List[Li def mne_epochs(mne_data: RawArray, - trigger_timing: List[float], trial_length: float, - trigger_labels: List[int], - baseline: Optional[Tuple[Any, float]] = None) -> Epochs: + trigger_timing: Optional[List[float]] = None, + trigger_labels: Optional[List[int]] = None, + baseline: Optional[Tuple[Any, float]] = None, + reject_by_annotation: bool = False, + preload: bool = False) -> Epochs: """MNE Epochs. Using an MNE RawArray, reshape the data given trigger information. If two labels present [0, 1], each may be accessed by numbered order. Ex. first_class = epochs['1'], second_class = epochs['2'] """ - annotations = Annotations(trigger_timing, [trial_length] * len(trigger_timing), trigger_labels) - mne_data.set_annotations(annotations) - events_from_annot, _ = mne.events_from_annotations(mne_data) - if not baseline: - baseline = (None, 0.0) - return Epochs(mne_data, events_from_annot, tmax=trial_length, baseline=baseline) + old_annotations = mne_data.annotations + if trigger_timing and trigger_labels: + new_annotations = Annotations(trigger_timing, [trial_length] * len(trigger_timing), trigger_labels) + all_annotations = new_annotations + old_annotations + else: + all_annotations = old_annotations + + tmp_data = mne_data.copy() + tmp_data.set_annotations(all_annotations) + + events_from_annot, _ = mne.events_from_annotations(tmp_data) + return Epochs( + mne_data, + events_from_annot, + baseline=baseline, + tmax=trial_length, + tmin=-0.05, + proj=False, # apply SSP projection to data. Defaults to True in Epochs. + reject_by_annotation=reject_by_annotation, + preload=preload) def alphabetize(stimuli: List[str]) -> List[str]: diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 7d3064e20..259b46d69 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -161,6 +161,7 @@ class TriggerType(Enum): OFFSET = "offset" EVENT = "event" PREVIEW = "preview" + ARTIFACT = "artifact" @classmethod def list(cls) -> List[str]: diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 46f394990..38815a95d 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -91,7 +91,7 @@ def visualize_erp( baseline = None mne_data = convert_to_mne(raw_data, channel_map=channel_map, transform=transform) - epochs = mne_epochs(mne_data, trigger_timing, trial_length, trigger_labels, baseline=baseline) + epochs = mne_epochs(mne_data, trial_length, trigger_timing, trigger_labels, baseline=baseline) # *Note* We assume, as described above, two trigger classes are defined for use in trigger_labels # (Nontarget=0 and Target=1). This will map into two corresponding MNE epochs whose indexing starts at 1. # Therefore, epochs['1'] == Nontarget and epochs['2'] == Target. diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index b65624cf9..63aca8295 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -33,13 +33,7 @@ "excluded_from_analysis": [ "TRG", "X1", "X2", "X3", - "A2", - "T3", "T4", - "Fp1", "Fp2", - "F7", "F8", - "P3", "P4", - "F3", "F4", - "C3", "C4" + "A2" ], "status": "active", "static_offset": 0.1 @@ -67,7 +61,7 @@ "name": "DSI-Flex", "content_type": "EEG", "channels": [ - { "name": "F3", "label": "Fz", "units": "microvolts", "type": "EEG" }, + { "name": "P4", "label": "Cz", "units": "microvolts", "type": "EEG" }, { "name": "S2", "label": "Oz", "units": "microvolts", "type": "EEG" }, { "name": "S3", "label": "P4", "units": "microvolts", "type": "EEG" }, { "name": "S4", "label": "P3", "units": "microvolts", "type": "EEG" }, diff --git a/bcipy/signal/evaluate/README.md b/bcipy/signal/evaluate/README.md index a74767f08..a1019ce9d 100644 --- a/bcipy/signal/evaluate/README.md +++ b/bcipy/signal/evaluate/README.md @@ -1,62 +1,101 @@ # Evaluate Module Class definitions for handling signal evaluation and rules by which the signal is to be -evaluated. +evaluated. The module contains classes for detecting and correcting artifacts in the data. -## Evaluator +## Artifact Detection -Handles signal evaluation by maintaining a set of enabled rules and testing inquiries against -each rule. Is boolean in nature, informing whether a rule was broken. +Artifact detection is the process of identifying and labeling unwanted signals from the data. This is +done by comparing the signal to a set of voltage and EOG thresholds. The thresholds are set by the user +and can be adjusted to fit the needs of the user. By default, the thresholds are set to 100uV for the +voltage threshold and 50uV for the EOG threshold. The artifact detection process is done in the following +steps: -### Example usage +1. The signal is passed through a bandpass filter to remove unwanted frequencies. +2. The signal is then passed through a notch filter to remove the 60Hz noise. +3. The signal is then compared to the voltage and EOG thresholds. +4. If the signal exceeds the thresholds, it is labeled as an artifact. All artifacts are annotated in the + data file with the prefix `BAD_`. -Evaluator is initialized with parameters file and whether a rule is enabled. In this case, high and low voltage rules are configured. +### Usage + +The `ArtifactDetection` class is used to detect artifacts in the data. The class takes in a `RawData` object, a `DeviceSpec` object, and a `Parameters` object. The `RawData` object contains the data to be analyzed, the `DeviceSpec` object contains the specifications of the device used to collect the data, and the `Parameters` object contains the parameters used to detect the artifacts. The `ArtifactDetection` class has a method called `detect_artifacts` that returns a list of the detected artifacts. ```python -# configuration -parameter_location = 'bcipy/parameters/parameters.json' -high_voltage_rule = True -low_voltage_rule = False +from bcipy.signal.evaluate.artifact import ArtifactDetection -# init evaluator -evaluator = Evaluator(parameter_location, high_voltage_rule, low_voltage_rule) +# Assuming BciPy raw data object, device spec and parameters object are already defined. -# Evaluate if inquiry is good (returns True / False) -evaluator.evaluate(inquiry) +artifact_detector = ArtifactDetection(raw_data, parameters device_spec) +detected_artifacts = artifact_detector.detect_artifacts() ``` -### Importing +Optionally, the user can provide session_triggers on initialization of the `ArtifactDetection` object. This is useful when the user wants to determine artifacts overlapping with triggers of interest. The `session_triggers` parameter is a tuple of lists, where the tuple contains (trigger_type, trigger_timing, trigger_label). + +```python +from bcipy.signal.evaluate.artifact import ArtifactDetection -The `__init__.py` file already contains instructions for importing Evaluator: +# Assuming BciPy raw data object, device spec and parameters object are already defined. Additionally, session_triggers is defined. + +artifact_detector = ArtifactDetection(raw_data, parameters, device_spec, session_triggers=session_triggers) +detected_artifacts = artifact_detector.detect_artifacts() +``` + +This can be used in conjunction with the `ArtifactDetection` semiautomatic mode to determine artifacts that overlap with triggers of interest and correct any labels before removal. To use the semiautomatic mode, the user must provide a list of triggers of interest. The `ArtifactDetection` class can be inititalized with `semi_automatic`. ```python -from bcipy.signal.evaluate.evaluator import Evaluator -__all__ = [ - 'Evaluator' -] +from bcipy.signal.evaluate.artifact import ArtifactDetection + +# Assuming BciPy raw data object, device spec and parameters object are already defined. Additionally, session_triggers is defined. + +artifact_detector = ArtifactDetection(raw_data, parameters, device_spec, session_triggers=session_triggers semi_automatic=True) +detected_artifacts = artifact_detector.detect_artifacts() ``` -With this, any future script that imports Evaluator can do the following: - -`from bcipy.signal.evaluate import Evaluator` +To output the detected artifacts to a new file, the `ArtifactDetection` class can be initialized with the `save_path` parameter. The `save_path` parameter is the path to the MNE file with the detected artifacts will be written. -## Rules +```python +from bcipy.signal.evaluate.artifact import ArtifactDetection -A Python abstract base class (ABC) that utilizes the abstract method, is_broken, which tests an -array of data based on some criteria unique to the rule (threshold, etc.). +# Assuming BciPy raw data object, device spec and parameters object are already defined. Additionally, session_triggers is defined. -### Example usage +artifact_detector = ArtifactDetection(raw_data, parameters, device_spec, session_triggers=session_triggers, save_path='path/to/save/file') +detected_artifacts = artifact_detector.detect_artifacts() +``` + +Finally, if wanting to export only the triggers with timestamps for use in another software, the detected artifcats can be exported to a txt file using the `write_mne_annotations` method. + +```python +from bcipy.signal.evaluate.artifact import ArtifactDetection, write_mne_annotations -Voltage rules, for example, are initialized with threshold values +# Assuming BciPy raw data object, device spec and parameters object are already defined. -`high_rule = HighVoltage(75E-6)` +artifact_detector = ArtifactDetection(raw_data, parameters, device_spec) +detected_artifacts = artifact_detector.detect_artifacts() +write_mne_annotations( + detected_artifacts, + 'path/to/save/file', + 'artifact_annotations.txt') +``` + +## Artifact Correction +Artifact correction is the process of removing unwanted signals from the data. After detection is complete, the user may use the MNE epoching tool to remove the unwanted epochs and channels. -Determine if rule is broken (returns True / False) +```python +from bcipy.signal.evaluate.artifact import ArtifactDetection, mne_epochs -`high_rule.is_broken(data)` +# Assuming BciPy raw data object, device spec and parameters object are already defined. Additionally, session_triggers is defined. +artifact_detector = ArtifactDetection(raw_data, parameters, device_spec, session_triggers=session_triggers) +# After calling this an mne_data object is created in the artifact_detector object with the annotations +detected_artifacts = artifact_detector.detect_artifacts() -### Importing +# Use MNE epoching tool to remove unwanted epochs and channels +mne_data = artifact_detector.mne_data +trial_length = 0.5 # seconds +# This will return the epochs object with the bad epochs removed. If no artifact detection was done, trigger_timing and trigger_labels must be provided. +epochs = mne_epochs(mne_data, trial_length, preload=True, reject_by_annotation=True) -`from bcipy.signal.evaluate.rules import HighVoltage, LowVoltage` \ No newline at end of file +# This will return the epochs object with the bad epochs removed. A drop log can be accessed to see which and how many epochs were removed. +``` diff --git a/bcipy/signal/evaluate/__init__.py b/bcipy/signal/evaluate/__init__.py index 7e0d3fd3a..e69de29bb 100644 --- a/bcipy/signal/evaluate/__init__.py +++ b/bcipy/signal/evaluate/__init__.py @@ -1,5 +0,0 @@ -from bcipy.signal.evaluate.evaluator import Evaluator - -__all__ = [ - 'Evaluator' -] diff --git a/bcipy/signal/evaluate/artifact.py b/bcipy/signal/evaluate/artifact.py new file mode 100644 index 000000000..ed7f5be78 --- /dev/null +++ b/bcipy/signal/evaluate/artifact.py @@ -0,0 +1,595 @@ +# mypy: disable-error-code="assignment,arg-type" +import os +from enum import Enum +from pathlib import Path +from typing import Union, List, Tuple, Optional +from logging import getLogger + +log = getLogger(__name__) + +from bcipy.config import ( + DEFAULT_PARAMETER_FILENAME, + RAW_DATA_FILENAME, + TRIGGER_FILENAME, + DEFAULT_DEVICE_SPEC_FILENAME, + BCIPY_ROOT +) +from bcipy.helpers.acquisition import analysis_channels +from bcipy.helpers.load import ( + load_experimental_data, + load_json_parameters, + load_raw_data, +) +from bcipy.helpers.stimuli import mne_epochs +from bcipy.helpers.convert import convert_to_mne +from bcipy.helpers.raw_data import RawData +from bcipy.signal.process import get_default_transform +from bcipy.helpers.triggers import TriggerType, trigger_decoder +import bcipy.acquisition.devices as devices +from bcipy.acquisition.devices import DeviceSpec + +import mne +mne.set_log_level('WARNING') +from mne import Annotations + + +class DefaultArtifactParameters(Enum): + """Default Artifact Parameters. + + These values are used as defaults for artifact analysis purposes. + """ + + # Voltage + PEAK_THRESHOLD = 100e-7 + PEAK_MIN_DURATION = 0.005 + FLAT_THRESHOLD = 0.5e-6 + FLAT_MIN_DURATION = 0.1 + VOlTAGE_LABEL_DURATION = 0.25 + + # Eye + EOG_LABEL_DURATION = 0.2 + EOG_THRESHOLD = 75e-6 + EOG_MIN_DURATION = 0.5 + + # I/O + ARTIFACT_LABELLED_FILENAME = 'artifacts.fif' + + def __str__(self) -> str: + """Return the value of the artifact type.""" + return self.value + + def __repr__(self) -> str: + """Return the class name and the artifact type name.""" + return f'{self.__class__.__name__}.{self.name}' + + +class ArtifactType(Enum): + """Artifact Type Enum. + + The artifact type enum is used to define the types of artifacts that can be detected in the data. + """ + + VOLTAGE = 'voltage' + EOG = 'eog' + BLINK = 'blink' + ECG = 'ecg' + EMG = 'emg' + FLAT = 'flat' + EVENT = 'event' + + def __str__(self) -> str: + """Return the value of the artifact type.""" + return self.value + + def __repr__(self) -> str: + """Return the class name and the artifact type name.""" + return f'{self.__class__.__name__}.{self.name}' + + def label(self) -> str: + """Label the artifact type. + + Returns + ------- + label - string - The label for the artifact type with the prefix BAD. + This is used for epoch handling by MNE. + """ + return f'BAD_{self.value}' + + +class ArtifactDetection: + """Artifact Detection Class. + + The artifact detection class is used to detect and label artifacts in the raw data. This class is designed to be + used in a pipeline for artifact detection and labelling. + + + Parameters + ---------- + raw_data : RawData + The raw data to process for artifacts. + + parameters : dict + The parameters used in the collection of the raw data. + + device_spec : dict + The device specification for the raw data. + + save_path : optional str + The path to save the artifact labelled data. If none provided, data is not saved. + + session_triggers : optional list + Optional list of session triggers to use for co-labelling the data. This is useful for determining the impact + of artifacts on the relevant epochs. + + percent_bad : float + The percentage of bad epochs to allow before channel exclusion. Defaults to 50%. + + detect_eog : bool + Whether to detect EOG artifacts. Defaults to True. Eye channels must be provided if this is set to True. + + eye_channels : list + The list of eye channels to use for detecting EOG artifacts. Defaults to None. If provided, the channels should + look like ['Fp1', 'Fp2', 'F7', 'F8']. + + detect_voltage : bool + Whether to detect voltage artifacts. Defaults to True. + """ + + supported_units: List[str] = ['volts', 'microvolts'] + support_device_types: List[str] = ['EEG'] + analysis_done: bool = False + dropped: Optional[str] = None + eog_annotations: Optional[Annotations] = None + voltage_annotations: Optional[Annotations] = None + + def __init__( + self, + raw_data: RawData, + parameters: dict, + device_spec: DeviceSpec, + save_path: Optional[str] = None, + semi_automatic: bool = False, + session_triggers: Optional[Tuple[list, list, list]] = None, + percent_bad: float = 50.0, + detect_eog: bool = True, + eye_channels: Optional[List[str]] = None, + detect_voltage: bool = True) -> None: + self.raw_data = raw_data + self.total_time = raw_data.total_seconds + self.device_spec = device_spec + assert self.device_spec.content_type in self.support_device_types, \ + f'BciPy Artifact Analysis only supports {self.support_device_types} data at this time.' + self.eye_channels = eye_channels + self.percent_bad = percent_bad + self.parameters = parameters + + # get the trial window from the parameters, in older versions it was not included default to 0.5 + start_trial, end_trial = self.parameters.get('trial_window', (0, 0.5)) + self.trial_duration = end_trial - start_trial + + self.session_triggers = None + if session_triggers: + self.triggers = session_triggers + self.trigger_description = session_triggers[0] + self.trigger_time = session_triggers[1] + self.trigger_label = session_triggers[2] + + self.session_triggers = mne.Annotations( + self.trigger_time, [self.trial_duration] * len(self.trigger_time), self.trigger_description) + + assert len(device_spec.channel_specs) > 0, 'DeviceSpec used must have channels. None found.' + self.units = device_spec.channel_specs[0].units + assert self.units in self.supported_units, \ + f'Data loaded in units that cannot be processed. Support units={self.supported_units}' + # MNE assumes that data is recorded in Volts. However, many devices use microvolts. + # If this value is False, a conversion to volts will be required. + self.volts = True if self.units == 'volts' else False + self.mne_data = self.raw_data_to_mne(raw_data, volts=self.volts) + self.detect_voltage = detect_voltage + self.detect_eog = detect_eog + self.semi_automatic = semi_automatic + + self.save_path = save_path + + def detect_artifacts(self) -> Tuple[str, float]: + """Detect artifacts in the raw data.""" + + labels = self.label_artifacts(extra_labels=self.session_triggers) + percent_dropped = 0 + + # calculate the impact of artifacts on the session triggers by creating epochs around the triggers + # and dropping artifacts using MNE + if self.session_triggers: + log.info('Calculating the impact of artifacts on session triggers.') + epochs = mne_epochs( + self.mne_data, + self.trial_duration, + reject_by_annotation=True, + preload=True) + + # calculate the percentage of dropped epochs + kept_epochs = len(epochs) + total_epochs = len(self.trigger_label) + percent_dropped = (1 - (kept_epochs / total_epochs)) * 100 + self.dropped = ( + f'{kept_epochs}/{total_epochs} retained. {percent_dropped}% epochs dropped due to artifacts.' + ) + + self.analysis_done = True + if self.save_path: + self.save_artifacts(overwrite=True) + log.info(f'Artifact labelled data saved to {self.save_path}') + + labels = f'{len(labels)} artifacts found in the data.' + + return labels, percent_dropped + + def label_artifacts( + self, + detect_voltage: bool = True, + detect_eog: bool = True, + extra_labels: Optional[Annotations] = None) -> Annotations: + """Label the artifacts in the raw data.""" + # Create an empty annotations object to store all the annotations + annotations = mne.Annotations(0, 0, 'start') + + if detect_voltage: + voltage = self.label_voltage_events() + if voltage: + voltage_annotations, bad_channels = voltage + log.info(f'Voltage violation events found: {len(voltage_annotations)}') + if bad_channels: + # add bad channel labels to the raw data + self.mne_data.info['bads'] = bad_channels + log.info(f'Bad channels detected: {bad_channels}') + + if voltage_annotations: + annotations += voltage_annotations + self.voltage_annotations = voltage_annotations + + if detect_eog: + eog = self.label_eog_events() + if eog: + eog_annotations, eog_events = eog + log.info(f'EOG events found: {len(eog_events)}') + if eog_annotations: + annotations += eog_annotations + self.eog_annotations = eog_annotations + + # Combine the annotations if multiple returned because set_annotations overwrites + # existing labels. + if extra_labels: + annotations += extra_labels + + if len(annotations) > 0: + self.mne_data.set_annotations(annotations) + else: + log.info('No artifacts or labels provided for the data.') + + # Plot the data with all annotations. This allows a user to reject additional bad epochs + # or modify existing annotations. + if self.semi_automatic: + self.mne_data.plot(block=True) + + return annotations + + def save_artifacts(self, overwrite: bool = False) -> None: + """Save the artifact file to disk.""" + if self.analysis_done: + self.mne_data.save( + f'{self.save_path}/{DefaultArtifactParameters.ARTIFACT_LABELLED_FILENAME.value}', + overwrite=overwrite) + else: + log.info('Artifact cannot be saved, artifact analysis has been done yet.') + + def raw_data_to_mne(self, raw_data: RawData, volts: bool = False) -> mne.io.RawArray: + """Convert the raw data to an MNE RawArray.""" + + downsample_rate = self.parameters.get("down_sampling_rate") + notch_filter = self.parameters.get("notch_filter_frequency") + filter_high = self.parameters.get("filter_high") + filter_low = self.parameters.get("filter_low") + filter_order = self.parameters.get("filter_order") + + default_transform = get_default_transform( + sample_rate_hz=raw_data.sample_rate, + notch_freq_hz=notch_filter, + bandpass_low=filter_low, + bandpass_high=filter_high, + bandpass_order=filter_order, + downsample_factor=downsample_rate, + ) + + return convert_to_mne( + raw_data, + channel_map=analysis_channels(raw_data.channels, self.device_spec), + transform=default_transform, + volts=volts) + + def label_eog_events( + self, + preblink: float = DefaultArtifactParameters.EOG_LABEL_DURATION.value, + postblink: float = DefaultArtifactParameters.EOG_LABEL_DURATION.value, + label: str = ArtifactType.BLINK.label(), + threshold: float = DefaultArtifactParameters.EOG_THRESHOLD.value) -> Optional[Tuple[mne.Annotations, list]]: + """Label EOG artifacts. + + Parameters + ---------- + raw : mne.RawArray + preblink : float | int + The time before the blink to label as an artifact. Defaults to DefaultArtifactParameters.EOG_DURATION. + postblink : float | int + The time after the blink to label as an artifact. Defaults to DefaultArtifactParameters.EOG_DURATION. + label : str + The label to use for the eog epochs. Note: The prefix + BAD or BAD_ must be present for epoch rejection. Defaults to ArtifactType.BLINK.label(). + threshold : float + The voltage threshold to use for detecting blinks. Defaults to DefaultArtifactParameters.EOG_THRESHOLD. + + Returns + ------- + ( mne.Annotations, list) | None + """ + if not self.eye_channels: + log.info('No eye channels provided. Cannot detect EOG artifacts.') + return None + + log.info(f'Using blink threshold of {threshold} for channels {self.eye_channels}.') + eog_events = mne.preprocessing.find_eog_events(self.mne_data, ch_name=self.eye_channels, thresh=threshold) + # eog_events = mne.preprocessing.ica_find_eog_events(raw) TODO compare to ICA + + if len(eog_events) > 0: + # Create annotations around blinks + onsets = eog_events[:, 0] / self.mne_data.info['sfreq'] - preblink + durations = [postblink + preblink] * len(eog_events) + descriptions = [label] * len(eog_events) + blink_annotations = mne.Annotations(onsets, durations, descriptions) + + return blink_annotations, eog_events + return None + + def label_voltage_events( + self, + pre_event: float = DefaultArtifactParameters.VOlTAGE_LABEL_DURATION.value, + post_event: float = DefaultArtifactParameters.VOlTAGE_LABEL_DURATION.value, + peak: Optional[Tuple[float, float, str]] = None, + flat: Optional[Tuple[float, float, str]] = None) -> Optional[Tuple[mne.Annotations, List[str]]]: + """Annotate Voltage Events in the data. + + Parameters + ---------- + raw : mne.RawArray + pre_event : float | int + The time before the voltage to label. + post_event : float | int + The time after the voltage to label. + peak : tuple + The voltage threshold to use for peak detection. The tuple should be (threshold, min_duration, label). + Defaults to ( + DefaultArtifactParameters.PEAK_THRESHOLD.value, + DefaultArtifactParameters.PEAK_MIN_DURATION.value, + ArtifactType.VOLTAGE.label() + ) + flat : tuple + The voltage threshold to use for flat detection. The tuple should be (threshold, min_duration, label). + Defaults to ( + DefaultArtifactParameters.FLAT_THRESHOLD.value, + DefaultArtifactParameters.FLAT_MIN_DURATION.value, + ArtifactType.FLAT.label()) + + Returns + ------- + (mne.Annotations, list) | None + + """ + if not flat: + flat = ( + DefaultArtifactParameters.FLAT_THRESHOLD.value, + DefaultArtifactParameters.FLAT_MIN_DURATION.value, + ArtifactType.FLAT.label()) + + if not peak: + peak = ( + DefaultArtifactParameters.PEAK_THRESHOLD.value, + DefaultArtifactParameters.PEAK_MIN_DURATION.value, + ArtifactType.VOLTAGE.label()) + + onsets: List[float] = [] + duration: List[float] = [] + descriptions: List[str] = [] + + # get the voltage events for threshold + peak_voltage_annotations, bad_channels1 = mne.preprocessing.annotate_amplitude( + self.mne_data, + min_duration=peak[1], + bad_percent=self.percent_bad, + peak=peak[0]) + if len(peak_voltage_annotations) > 0: + onsets, durations, descriptions = self.concat_annotations( + peak_voltage_annotations, + pre_event, + post_event, + peak[2], + onsets, + duration, + descriptions) + + # get the voltage events for flat + flat_voltage_annotations, bad_channels2 = mne.preprocessing.annotate_amplitude( + self.mne_data, min_duration=flat[1], bad_percent=self.percent_bad, flat=flat[0]) + if len(flat_voltage_annotations) > 0: + onsets, durations, descriptions = self.concat_annotations( + flat_voltage_annotations, + pre_event, + post_event, + flat[2], + onsets, + duration, + descriptions) + + # combine the bad channels + bad_channels = bad_channels1 + bad_channels2 + + if len(onsets) > 0 or len(bad_channels) > 0: + return mne.Annotations(onsets, durations, descriptions), bad_channels + + return None + + def concat_annotations( + self, + annotations: mne.Annotations, + pre: Union[float, int], + post: Union[float, int], + label: str, + onsets: List[float], + duration: List[str], + descriptions: List[str]) -> Tuple[list, list, list]: + """Concatenate annotations. + + Iters through the annotations and adds the pre and post time to the onsets and duration. + + Parameters + ---------- + annotations : mne.Annotations + pre : float | int + The time before the voltage to label. + post : float | int + The time after the voltage to label. + label : str + The label to use for the voltage epochs. Note: The prefix + BAD or BAD_ must be present for epoch rejection. + onsets : list + The list of onsets to append to. + duration : list + The list of durations to append to. + descriptions : list + The list of descriptions to append to. + + Returns + ------- + Tuple[list, list, list] - The onsets, durations, and descriptions. + + """ + + for annotation in annotations: + # hack for the start of the recording, if greater than prevoltage, then set to 0.0 + if (annotation['onset']) > pre: + onset = annotation['onset'] - pre + else: + onset = 0.0 + onsets.append(onset) + duration.append(annotation['duration'] + pre + post) + descriptions.append(label) + + return onsets, duration, descriptions + + +def write_mne_annotations( + annotations: mne.Annotations, + path: str, + filename: str) -> None: + """Write MNE annotations to a text file. + + This is useful for sharing annotations for use outside of MNE. + + Parameters + ---------- + annotations : mne.Annotations + The annotations to write. + path : str + The path to write the annotations to. + filename : str + The filename for the new annotations file. + + Returns + ------- + None + """ + # write the annotations to a text file where each line is [description, bcipy_label, onset, duration] + with open(os.path.join(path, filename), 'w') as tmp_file: + for annotation in annotations: + tmp_file.write( + f"{annotation['description'].split('BAD_')[-1]} " + f"{TriggerType.ARTIFACT} {annotation['onset']} {annotation['duration']}\n") + + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser() + parser.add_argument( + '-p', + '--path', + help='Path to the directory with >= 1 sessions to be analyzed for artifacts', + required=False) + # Semi-supervised artifact detection. + # If flag used, the user will be prompted with a GUI to correct or add labels for artifacts. + parser.add_argument("--semi", dest="semi", action="store_true") + # Save the data after artifact detection as .fif file (MNE). + parser.add_argument("--save", dest="save", action="store_true") + # If flag used with semi, the user will be prompted to correct or add labels for + # artifacts alongside the other session triggers. + parser.add_argument("--colabel", dest="colabel", action="store_true") + parser.set_defaults(semi=False) + parser.set_defaults(save=False) + parser.set_defaults(colabel=False) + args = parser.parse_args() + + # if no path is provided, prompt for one using a GUI + path = args.path + if not path: + path = load_experimental_data() + + positions = None + for session in Path(path).iterdir(): + # loop through the sessions, pausing after each one to allow for manual stopping + if session.is_dir(): + log.info(f'Processing {session}') + prompt = input('Hit enter to continue or type "skip" to skip processing: ') + if prompt != 'skip': + # load the parameters from the data directory + parameters = load_json_parameters( + f'{session}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) + + # load the raw data from the data directory + raw_data = load_raw_data(str(Path(session, f'{RAW_DATA_FILENAME}.csv'))) + type_amp = raw_data.daq_type + + # load the triggers + if args.colabel: + trigger_type, trigger_timing, trigger_label = trigger_decoder( + offset=parameters.get('static_trigger_offset'), + trigger_path=f"{session}/{TRIGGER_FILENAME}", + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + ) + triggers = (trigger_type, trigger_timing, trigger_label) + else: + triggers = None + + devices.load(Path(BCIPY_ROOT, DEFAULT_DEVICE_SPEC_FILENAME)) + device_spec = devices.preconfigured_device(raw_data.daq_type) + + # check the device spec for any frontal channels to use for EOG detection + eye_channels = [] + for channel in device_spec.channels: + if 'F' in channel: + eye_channels.append(channel) + if len(eye_channels) == 0: + eye_channels = None + + artifact_detector = ArtifactDetection( + raw_data, + parameters, + device_spec, + eye_channels=eye_channels, + session_triggers=triggers, + save_path=None if not args.save else session, + semi_automatic=args.semi) + + detected = artifact_detector.detect_artifacts() + # write_mne_annotations(detected, session, 'artifacts.txt') + else: + log.info(f'Skipping {session}') + # Uncomment below to pause between sessions. + # breakpoint() diff --git a/bcipy/signal/evaluate/evaluator.py b/bcipy/signal/evaluate/evaluator.py deleted file mode 100644 index 052743170..000000000 --- a/bcipy/signal/evaluate/evaluator.py +++ /dev/null @@ -1,48 +0,0 @@ -from bcipy.signal.evaluate.rules import HighVoltage, LowVoltage, Rule -from typing import List - -import numpy as np - - -class Evaluator: - """Evaluator. - - Takes in raw data and tests them against given - rules, which elicit the rejection of a inquiry when broken. - Feeds warnings to artifact rejector as suggestions. - - Add rules given in parameters to evaluator's ruleset and set - keys for broken_rules. One heading per rule. - - parameters (dict): dictionary of parameters from json file, given by caller - rules (list of rule objects, defined in rules.py) - """ - - def __init__(self, parameters, high_voltage, low_voltage) -> None: - self.rules: List[Rule] = [] - - # if high_voltage threshold is enabled, add to rules - if high_voltage: - self.rules.append(HighVoltage(parameters['high_voltage_value'])) - - # if low_voltage threshold is enabled, add to rules - if low_voltage: - self.rules.append(LowVoltage(parameters['low_voltage_value'])) - - def evaluate(self, data: np.ndarray) -> bool: - """Evaluate. - - Evaluates inquiry data using selected rules from parameters file. - """ - - for rule in self.rules: - - if rule.is_broken(data): - - return False - - return True - - def __str__(self): - rules = [str(rule) for rule in self.rules] - return f'Evaluator with {rules}' diff --git a/bcipy/signal/evaluate/rules.py b/bcipy/signal/evaluate/rules.py deleted file mode 100644 index b85ffa921..000000000 --- a/bcipy/signal/evaluate/rules.py +++ /dev/null @@ -1,82 +0,0 @@ -import numpy as np -from abc import ABC, abstractmethod - - -class Rule(ABC): - """Rule. - - Python Abstract Base Class for a Rule. - (https://docs.python.org/3/library/abc.html) - Each rule has a 'is_broken' method which acts as instructions for - the evaluator to use when evaluating data. Returns True upon - rule breakage, otherwise defaults to False.""" - - def __init__(self, threshold): - self.threshold = threshold - - # a method required for all subclasses - @abstractmethod - def is_broken(self, data: np.ndarray) -> bool: - ... - - -class HighVoltage(Rule): - """High Voltage Rule. - - Set high threshold for permitted voltage. - - Allows different types of rules to be fed to artifact rejector so that experimenter can differentiate between - high and low warnings easily. Makes it so that rules are singularly defined. Names must be equal to value in - parameters.json - """ - - def is_broken(self, data: np.ndarray) -> bool: - """Is Broken. - - Test data against threshold value. Return broken - if threshold exceeded. - - data(ndarray[float]): C x N length array where - C is the number of channels and N is the number of samples - - np.amax takes the maximum value in an - array even of length 1: - (https://docs.scipy.org/doc/numpy/ - reference/generated/numpy.amax.html) - """ - if np.amax(data) >= self.threshold: - return True - - return False - - def __str__(self) -> str: - return f'High Voltage with threshold {self.threshold}' - - -class LowVoltage(Rule): - """Low Voltage Rule. - - Set low threshold for permitted voltage. - """ - - def is_broken(self, data: np.ndarray) -> bool: - """Is Broken. - - Test data against threshold value. Return false - if threshold exceeded. - - - data(ndarray[float]): C x N length array where - C is the number of channels and N is the number of samples - - - np.amin takes the minimum value in an array even of length 1: - (https://docs.scipy.org/doc/numpy/reference/generated/numpy.amin.html) - """ - if np.amin(data) <= self.threshold: - return True - - return False - - def __str__(self) -> str: - return f'Low Voltage with threshold {self.threshold}' diff --git a/bcipy/signal/tests/evaluate/test_artifact.py b/bcipy/signal/tests/evaluate/test_artifact.py new file mode 100644 index 000000000..c2fa2bc99 --- /dev/null +++ b/bcipy/signal/tests/evaluate/test_artifact.py @@ -0,0 +1,128 @@ +import unittest +from mockito import when, mock, unstub +from bcipy.signal.evaluate.artifact import ArtifactDetection, DefaultArtifactParameters, ArtifactType +from bcipy.signal.evaluate import artifact + + +class TestArtifactDetection(unittest.TestCase): + + def setUp(self): + self.raw_data = mock() + self.raw_data.total_seconds = 10 + self.raw_data.sample_rate = 1000 + self.raw_data.channels = ['Fp1', 'Fp2'] + self.mne_data = mock() + self.parameters = { + 'down_sampling_rate': 2, + 'notch_filter_frequency': 60, + 'filter_high': 50, + 'filter_low': 0.5, + 'filter_order': 4, + } + self.device_spec = mock() + self.device_spec.content_type = 'EEG' + self.device_spec.units = 'volts' + self.channel_spec = mock() + self.channel_spec.name = 'Fp1' + self.channel_spec.units = 'volts' + self.device_spec.channel_specs = [self.channel_spec] + self.device_spec.analysis_channels = ['Fp1'] + self.channel_map = [1, 0] + when(artifact).convert_to_mne( + self.raw_data, + channel_map=self.channel_map, + transform=any, + volts=True).thenReturn( + self.mne_data) + + def tearDown(self) -> None: + unstub() + + def test_artifact_detection_init(self): + """Test the ArtifactDetection class.""" + ar = ArtifactDetection(raw_data=self.raw_data, parameters=self.parameters, device_spec=self.device_spec) + self.assertIsInstance(ar, ArtifactDetection) + self.assertFalse(ar.analysis_done) + self.assertIsNone(ar.dropped) + self.assertIsNone(ar.eog_annotations) + self.assertIsNone(ar.voltage_annotations) + self.assertIsNone(ar.session_triggers) + + def test_artifact_detection_init_throws_exception_unsupported_device(self): + """Test the ArtifactDetection class throws exception when using a device that is not supported.""" + self.device_spec.content_type = 'MEG' + with self.assertRaises(AssertionError): + ArtifactDetection( + raw_data=self.raw_data, + parameters=self.parameters, + device_spec=self.device_spec) + + def test_artifact_detection_init_throws_exception_unsupported_units(self): + """Test the ArtifactDetection class throws exception with unsupported units.""" + self.device_spec.units = 'unsupported' + self.channel_spec.units = 'unsupported' + + with self.assertRaises(AssertionError): + ArtifactDetection( + raw_data=self.raw_data, + parameters=self.parameters, + device_spec=self.device_spec) + + def test_artifact_detection_init_throws_exception_no_channels(self): + """Test the ArtifactDetection class throws an exception if no channels are provided.""" + self.device_spec.channel_specs = [] + + with self.assertRaises(AssertionError): + ArtifactDetection( + raw_data=self.raw_data, + parameters=self.parameters, + device_spec=self.device_spec) + + def test_artifact_detection_with_session_labels(self): + description = ['test', 'target', 'test'] + timing = [1, 2, 3] + labels = [0, 1, 0] + session_triggers = (description, timing, labels) + ar = ArtifactDetection( + raw_data=self.raw_data, + parameters=self.parameters, + device_spec=self.device_spec, + session_triggers=session_triggers) + self.assertIsNotNone(ar.session_triggers) + + def test_artifact_detection_detect_artifacts(self): + """Test the ArtifactDetection class label artifacts method.""" + ar = ArtifactDetection( + raw_data=self.raw_data, + parameters=self.parameters, + device_spec=self.device_spec) + labels = [mock()] + expected_label_response = f'{len(labels)} artifacts found in the data.' + when(ar).label_artifacts(extra_labels=ar.session_triggers).thenReturn(labels) + response_labels, response_dropped = ar.detect_artifacts() + self.assertEqual(response_labels, expected_label_response) + self.assertEqual(response_dropped, 0) + + def test_artifact_detection_label_artifacts(self): + """Test the ArtifactDetection class label artifacts method with no labels.""" + ar = ArtifactDetection( + raw_data=self.raw_data, + parameters=self.parameters, + device_spec=self.device_spec) + response = ar.label_artifacts(False, False) + self.assertTrue(len(response) == 1) + + def test_artifact_type(self): + """Test the ArtifactType class.""" + self.assertEqual(ArtifactType.BLINK.value, 'blink') + self.assertEqual(ArtifactType.EOG.value, 'eog') + + def test_default_artifact_parameters(self): + """Test the DefaultArtifactParameters class.""" + self.assertEqual(DefaultArtifactParameters.EOG_THRESHOLD.value, 75e-6) + self.assertEqual(DefaultArtifactParameters.VOlTAGE_LABEL_DURATION.value, 0.25) + self.assertEqual(DefaultArtifactParameters.ARTIFACT_LABELLED_FILENAME.value, 'artifacts.fif') + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/signal/tests/evaluate/test_evaluator.py b/bcipy/signal/tests/evaluate/test_evaluator.py deleted file mode 100644 index d8894a83d..000000000 --- a/bcipy/signal/tests/evaluate/test_evaluator.py +++ /dev/null @@ -1,56 +0,0 @@ -import unittest -from bcipy.signal.evaluate.evaluator import Evaluator -from bcipy.signal.evaluate.rules import HighVoltage, LowVoltage -from mockito import any, unstub, when -from bcipy.signal.generator.generator import gen_random_data - - -class TestEvaluator(unittest.TestCase): - """Test Evaluator init and class methods """ - - def setUp(self): - self.expected_high_voltage = True - self.expected_low_voltage = True - self.parameters = { - 'high_voltage_value': 1, - 'low_voltage_value': -1 - } - - self.evaluator = Evaluator(self.parameters, - self.expected_high_voltage, - self.expected_low_voltage) - - self.channels = 32 - - def tearDown(self): - unstub() - - def test_init_high_voltage_rule(self): - """Test that high voltage rule initialized correctly into ruleset""" - if self.expected_high_voltage: - self.assertIsInstance(self.evaluator.rules[0], HighVoltage) - - def test_init_low_voltage_rule(self): - """Test that high voltage rule initialized correctly into ruleset""" - if self.expected_low_voltage: - self.assertIsInstance(self.evaluator.rules[1], LowVoltage) - - def test_evaluate_with_broken_rules(self): - """Test evaluate with is_broken returning True, - thus resulting in evaluate returning False""" - when(self.evaluator.rules[0]).is_broken(any()).thenReturn(True) - when(self.evaluator.rules[1]).is_broken(any()).thenReturn(True) - data = gen_random_data(-1, 2, self.channels) - self.assertFalse(self.evaluator.evaluate(data)) - - def test_evaluate_with_no_broken_rules(self): - """Test evaluate with is_broken returning False, - thus resulting in evaluate returning True""" - when(self.evaluator.rules[0]).is_broken(any()).thenReturn(False) - when(self.evaluator.rules[1]).is_broken(any()).thenReturn(False) - data = gen_random_data(-1, 2, self.channels) - self.assertTrue(self.evaluator.evaluate(data)) - - -if __name__ == "__main__": - unittest.main() diff --git a/bcipy/signal/tests/evaluate/test_rules.py b/bcipy/signal/tests/evaluate/test_rules.py deleted file mode 100644 index 94f4284a5..000000000 --- a/bcipy/signal/tests/evaluate/test_rules.py +++ /dev/null @@ -1,62 +0,0 @@ -import unittest -import numpy as np -from bcipy.signal.evaluate.rules import Rule, HighVoltage, LowVoltage -from bcipy.signal.generator.generator import gen_random_data - - -class TestRules(unittest.TestCase): - """Test Rules init and class methods """ - - def setUp(self): - """Create rule objects to test """ - - # Set thresholds for testing - self.highvoltage_value = 1 - self.lowvoltage_value = -1 - - self.highvoltage_rule = HighVoltage(self.highvoltage_value) - self.lowvoltage_rule = LowVoltage(self.lowvoltage_value) - - self.channels = 32 - - def test_high_voltage_rule_init(self): - """Test that high voltage inits correctly""" - self.assertEqual(self.highvoltage_rule.threshold, - self.highvoltage_value) - - self.assertIsInstance(self.highvoltage_rule, Rule) - - def test_low_voltage_rule_init(self): - """Test that low voltage inits correctly""" - self.assertEqual(self.lowvoltage_rule.threshold, - self.lowvoltage_value) - - self.assertIsInstance(self.lowvoltage_rule, Rule) - - def test_low_voltage_failing_signal(self): - """Test generated sub threshold signal against low voltage""" - data = gen_random_data(1, 5, self.channels) - # ascertain that at least one random datapoint is below threshold to test np.amin edgecase - data[np.random.randint(self.channels)] = -1.5 - self.assertTrue(self.lowvoltage_rule.is_broken(data)) - - def test_low_voltage_passing_signal(self): - """Test generated signal that is consistently above threshold""" - data = gen_random_data(-0.5, 0.5, self.channels) - self.assertFalse(self.lowvoltage_rule.is_broken(data)) - - def test_high_voltage_failing_signal(self): - """Test generated signal with one data point above threshold """ - data = gen_random_data(-5, 0, self.channels) - # ascertain that at least one random datapoint is above threshold to test np.amax edgecase - data[np.random.randint(self.channels)] = 1.5 - self.assertTrue(self.highvoltage_rule.is_broken(data)) - - def test_high_voltage_passing_signal(self): - """Test generated signal that is consistently below threshold""" - data = gen_random_data(-0.5, 0.5, self.channels) - self.assertFalse(self.highvoltage_rule.is_broken(data)) - - -if __name__ == "__main__": - unittest.main() From 18c5434ef3f177c7950515a0f7304840921459f9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 22 Aug 2024 11:14:50 -0700 Subject: [PATCH 286/330] Fixed linting and typing issues --- bcipy/simulator/sim.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 0fb140334..45ce565f9 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -190,7 +190,7 @@ def new_data_record(self, inquiry_state: SimState, inquiry_result: InquiryResult target_text=inquiry_state.target_sentence) data.precision = 4 data.evidences = { - val.evidence_type: val.evidence + val.evidence_type: list(val.evidence) for val in inquiry_result.evidences.values() } if EvidenceType.LM not in data.evidences: @@ -218,7 +218,7 @@ def save_run(self, session: Session): if session.has_evidence(): session_excel(session=session, - excel_file=f"{self.save_dir}/session.xlsx") + excel_file=f"{self.save_dir}/session.xlsx") def reset(self): self.state_manager.reset_state() From c254376b92c3e1de5786aecf2638f4112fd792b6 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 23 Aug 2024 10:38:13 -0700 Subject: [PATCH 287/330] Fixes inquiry initialization bug for simulator --- bcipy/simulator/helpers/model_handler.py | 6 ++++++ bcipy/simulator/sim.py | 22 ++++++++++++++-------- 2 files changed, 20 insertions(+), 8 deletions(-) diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index 7294aa1dc..88bf28f3f 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -27,6 +27,9 @@ def generate_evidence(self, state: SimState, features): def get_model(self, key=None): """ get the model """ + def includes_language_model(self) -> bool: + return False + class SignalModelHandler1(ModelHandler): @@ -120,6 +123,9 @@ def get_model(self, key=None): else: raise RuntimeError(f"Can't find model {key}") + def includes_language_model(self) -> bool: + return True + def __str__(self): props = { 'signal_model': self.signal_model.__class__.__name__, diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 45ce565f9..f2e1ce853 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -118,6 +118,10 @@ def run(self): self.save_run(session) + def has_language_model(self) -> bool: + """Indicates whether this task has been configured with a language model""" + return self.model_handler.includes_language_model() + def __make_stimuli(self, state: SimState): """ Creates next set of stimuli: @@ -125,22 +129,24 @@ def __make_stimuli(self, state: SimState): - uses language model for beginning of series - random letters in case of no LM and beginning of series """ - subset_length = 10 - val_func: Optional[np.ndarray] = state.get_current_likelihood() - always_in_stimuli = [symbols.SPACE_CHAR, symbols.BACKSPACE_CHAR] + subset_length = self.parameters['stim_length'] + priors: Optional[np.ndarray] = state.get_current_likelihood() + always_in_stimuli = [] + if self.parameters.get('backspace_always_shown', False): + always_in_stimuli.append(symbols.BACKSPACE_CHAR) # during series - if val_func is not None: + if priors is not None: return stimuli.best_selection(self.symbol_set, list( - val_func), subset_length, always_included=always_in_stimuli) + priors), subset_length, always_included=always_in_stimuli) # beginning of series - elif self.parameters.get('sim_lm_active', 0) == 1: + elif self.has_language_model(): # use lang model for priors to make stim lm_model = self.model_handler.get_model('lm') lm_model_evidence = lm_model.predict(list(state.current_sentence)) - val_func = format_lm_output(lm_model_evidence, self.symbol_set) + priors = format_lm_output(lm_model_evidence, self.symbol_set) return stimuli.best_selection(self.symbol_set, list( - val_func), subset_length, always_included=always_in_stimuli) + priors), subset_length, always_included=always_in_stimuli) return random.sample(self.symbol_set, subset_length) From 324dc1a3dc254bb12afc93e76c1e80c9619fd691 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 26 Aug 2024 18:20:52 -0700 Subject: [PATCH 288/330] Created a new Copy Phrase Task for simulation to more closely utilize the existing BciPy code whenever possible. Refactored Sampler code to utilize common patterns and clarify the API for future multi-modal support --- bcipy/simulator/helpers/data_engine.py | 13 +- bcipy/simulator/helpers/log_utils.py | 5 + bcipy/simulator/helpers/sampler.py | 153 ++++++++++++---------- bcipy/simulator/sim.py | 2 +- bcipy/simulator/task/copy_phrase.py | 128 ++++++++++++++++++ bcipy/simulator/task/null_display.py | 17 +++ bcipy/simulator/task/task_runner.py | 167 ++++++++++++++++++++++++ bcipy/task/paradigm/rsvp/copy_phrase.py | 53 +++++--- 8 files changed, 449 insertions(+), 89 deletions(-) create mode 100644 bcipy/simulator/task/copy_phrase.py create mode 100644 bcipy/simulator/task/null_display.py create mode 100644 bcipy/simulator/task/task_runner.py diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 6df802f54..ba0086fe5 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -51,7 +51,18 @@ class Trial(NamedTuple): inquiry_pos: int symbol: str target: int - eeg: np.ndarray + eeg: np.ndarray # Channels by Samples + + def __str__(self): + fields = [ + f"source='{self.source}'", f"inquiry_n={self.inquiry_n}", + f"inquiry_pos={self.inquiry_pos}", f"symbol='{self.symbol}'", + f"target={self.target}", f"eeg={self.eeg.shape}" + ] + return f"Trial({', '.join(fields)})" + + def __repr__(self): + return str(self) class RawDataEngine(DataEngine): diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 78964f53f..61c111bd0 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -2,6 +2,7 @@ import pandas as pd +from bcipy.simulator.helpers.data_engine import Trial from bcipy.simulator.helpers.types import SimEvidence @@ -17,6 +18,10 @@ def fmt_likelihoods_for_hist(likelihoods, alp): return formatted +def format_samples(sample_rows: List[Trial]) -> str: + """Returns a tabular representation of the sample rows.""" + return '\n'.join([str(row) for row in sample_rows]) + def format_sample_rows(sample_rows: List[pd.Series]) -> str: """Returns a tabular representation of the sample rows.""" return pd.DataFrame(sample_rows).drop(columns=['eeg']).to_string( diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 34557cd4b..23419138c 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -9,101 +9,119 @@ import pandas as pd from bcipy.helpers.exceptions import TaskConfigurationException -from bcipy.helpers.parameters import Parameters -from bcipy.helpers.symbols import alphabet -from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.log_utils import (format_sample_df, - format_sample_rows) +from bcipy.simulator.helpers.data_engine import RawDataEngine, Trial +from bcipy.simulator.helpers.log_utils import format_samples from bcipy.simulator.helpers.state_manager import SimState log = logging.getLogger(__name__) -class Sampler(ABC): - """ Interface to generate sample of data usable by a model """ +def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: + """Default data reshaper. - def sample(self, state: SimState): - ... + Returns + ------- + ndarray with shape (channel_n, trial_n, sample_n) + """ - def set_reshaper(self, reshaper: Callable): - ... + channels_eeg: List[List[np.ndarray]] = [ + [] for i in range(len(eeg_responses[0])) + ] + for _i, trial_channels_eeg in enumerate(eeg_responses): + for c_i, channel_eeg in enumerate(trial_channels_eeg): + channels_eeg[c_i].append(channel_eeg) -class EEGByLetterSampler(Sampler): + return np.array(channels_eeg) + + +class Sampler(ABC): + """Represents a strategy for sampling signal model data from a DataEngine + comprised of signal data from one or more data collection sessions.""" - def __init__(self, - data_engine: RawDataEngine, - parameters: Parameters = None): + def __init__(self, data_engine: RawDataEngine): self.data_engine: RawDataEngine = data_engine - self.parameters: Parameters = self.data_engine.parameters if not parameters else parameters self.model_input_reshaper: Callable = default_reshaper - self.alphabet: List[str] = self.parameters.get( - 'symbol_set') if self.parameters else alphabet() self.data: pd.DataFrame = self.data_engine.transform().get_data() - def sample(self, state: SimState) -> np.ndarray: + def sample(self, state: SimState) -> List[Trial]: """ - - query eeg response by letter - - reshape for signal model input + Query the data engine for a list of trials corresponding to each + currently displayed symbol. - Return: - nd array (n_channel, n_trial, n_sample) - """ + Parameters + ---------- + state - specifies the target symbol and current inquiry (displayed symbols). - inquiry_letter_subset = state.display_alphabet - target_letter = state.target_symbol - sample_rows = [] - for symbol in inquiry_letter_subset: - is_target = int(symbol == target_letter) - # filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') - filtered_data: pd.DataFrame = self.data.query( - f'target == {is_target}') - if filtered_data is None or len(filtered_data) == 0: - raise TaskConfigurationException( - message="No eeg sample found with provided data and query") + Returns + ------- + a list of Trials with an item for each symbol in the current inquiry. + """ + raise NotImplementedError - row = filtered_data.sample(1).iloc[0] - sample_rows.append(row) + def sample_data(self, state: SimState) -> np.ndarray: + """ + Query for trials and reshape for signal model input according to the + provided reshaper. - log.debug(f"EEG Samples: \n {format_sample_rows(sample_rows)}") + Return: + ndarray of shape (n_channel, n_trial, n_sample) + """ + trials = self.sample(state) + return self.reshaped(trials) - eeg_responses = [r['eeg'] for r in sample_rows] - sample = self.model_input_reshaper(eeg_responses) + def sample_with_context(self, + state: SimState) -> Tuple[np.ndarray, List[Trial]]: + """ + Returns + ------- + A tuple of the reshaped data (ndarray of shape (n_channel, n_trial, n_sample)) as + well as a list of Trial data (metadata and data not reshaped) for context. + """ + trials = self.sample(state) + data = self.reshaped(trials) + return data, trials - return sample + def reshaped(self, sample_rows: List[Trial]) -> np.ndarray: + """Returns the queried trials reshaped into a format that a model can predict.""" + return self.model_input_reshaper([trial.eeg for trial in sample_rows]) def set_reshaper(self, reshaper: Callable): + """Set the reshaper""" self.model_input_reshaper = reshaper def __str__(self): return f"<{self.__class__.__name__}>" -def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: - """Default data reshaper. - - Returns - ------- - ndarray with shape (channel_n, trial_n, sample_n) - """ +class EEGByLetterSampler(Sampler): + """Sampler that that queries based on target/non-target label.""" - channels_eeg: List[List[np.ndarray]] = [ - [] for i in range(len(eeg_responses[0])) - ] + def sample(self, state: SimState) -> List[Trial]: + current_stimuli = state.display_alphabet + target_letter = state.target_symbol + sample_rows = [] + for symbol in current_stimuli: + is_target = int(symbol == target_letter) + # filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') + filtered_data: pd.DataFrame = self.data.query( + f'target == {is_target}') + if filtered_data is None or len(filtered_data) == 0: + raise TaskConfigurationException( + message="No eeg sample found with provided data and query") - for _i, trial_channels_eeg in enumerate(eeg_responses): - for c_i, channel_eeg in enumerate(trial_channels_eeg): - channels_eeg[c_i].append(channel_eeg) + row = filtered_data.sample(1).iloc[0] + sample_rows.append(Trial(**row)) - return np.array(channels_eeg) + log.debug(f"EEG Samples:\n{format_samples(sample_rows)}") + return sample_rows class InquirySampler(Sampler): """Samples an inquiry of data at a time.""" def __init__(self, data_engine: RawDataEngine): - self.model_input_reshaper = default_reshaper - self.data: pd.DataFrame = data_engine.transform().get_data() + super().__init__(data_engine) # map source to inquiry numbers self.target_inquiries, self.no_target_inquiries = self.prepare_data( @@ -135,15 +153,20 @@ def prepare_data( return target_inquiries, no_target_inquiries - def sample(self, state: SimState) -> np.ndarray: + def sample(self, state: SimState) -> List[Trial]: """Samples a random inquiry for a random data source. Ensures that if a target is shown in the current inquiry the sampled data will be from an inquiry where the target was presented. + Parameters + ---------- + state - specifies the target symbol and current inquiry (displayed symbols). + Returns ------- - nd array (n_channel, n_trial, n_sample) + a list of Trials with an item for each symbol in the current + inquiry. """ target_letter = state.target_symbol @@ -197,13 +220,9 @@ def sample(self, state: SimState) -> np.ndarray: # select the inquiry items in sorted position sorted_inquiry_df = inquiry_df.loc[sort_pos.sort_values().index] - log.debug(f"EEG Samples: \n {format_sample_df(sorted_inquiry_df)}") - rows = [ - sorted_inquiry_df.iloc[i] for i in range(len(sorted_inquiry_df)) + Trial(**sorted_inquiry_df.iloc[i]) + for i in range(len(sorted_inquiry_df)) ] - eeg_responses = [r['eeg'] for r in rows] - return self.model_input_reshaper(eeg_responses) - - def set_reshaper(self, reshaper: Callable): - self.model_input_reshaper = reshaper + log.debug(f"EEG Samples:\n{format_samples(rows)}") + return rows diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index f2e1ce853..821b94121 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -87,7 +87,7 @@ def run(self): f"Target '{curr_state.target_symbol}' | " + f"Stimuli {curr_state.display_alphabet}") - sampled_data = self.sampler.sample(self.state_manager.get_state()) + sampled_data = self.sampler.sample_data(self.state_manager.get_state()) evidence: Dict[str, SimEvidence] = self.model_handler.generate_evidence(curr_state, sampled_data) diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py new file mode 100644 index 000000000..fc6ad5783 --- /dev/null +++ b/bcipy/simulator/task/copy_phrase.py @@ -0,0 +1,128 @@ +"""Simulates the Copy Phrase task""" +from typing import List, Optional, Tuple + +from bcipy.display.main import Display +from bcipy.feedback.visual.visual_feedback import VisualFeedback +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.stimuli import InquirySchedule +from bcipy.language.main import LanguageModel +from bcipy.signal.model.base_model import SignalModel +from bcipy.simulator.helpers.sampler import Sampler +from bcipy.simulator.helpers.state_manager import SimState +from bcipy.simulator.task.null_display import NullDisplay +from bcipy.task.control.evidence import EvidenceEvaluator +from bcipy.task.data import EvidenceType +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask + + +class SimulatorCopyPhraseTask(RSVPCopyPhraseTask): + """CopyPhraseTask that simulates user interactions by sampling data + from a DataSampler.""" + + def __init__(self, parameters: Parameters, file_save: str, + signal_models: List[SignalModel], + language_model: LanguageModel, sampler: Sampler): + super().__init__(win=None, + daq=None, + parameters=parameters, + file_save=file_save, + signal_models=signal_models, + language_model=language_model, + fake=False) + self.save_session_every_inquiry = False + # TODO: support multi-modal by including a sampler for every model + # TODO: easily swap out samplers (parameter -> list of samplers, one for each mode/evidence type) + # maybe accept a List[Tuple[SignalModel, Sampler]] + self.sampler = sampler + + def init_evidence_evaluators( + self, signal_models: List[SignalModel]) -> List[EvidenceEvaluator]: + # Evidence will be sampled so we don't need to evaluate raw data. + return [] + + def init_evidence_types( + self, evidence_evaluators: List[EvidenceEvaluator] + ) -> List[EvidenceType]: + # TODO: revisit this based on the provided models + return [EvidenceType.LM, EvidenceType.ERP] + + def init_display(self) -> Display: + return NullDisplay() + + def init_feedback(self) -> Optional[VisualFeedback]: + return None + + def user_wants_to_continue(self) -> bool: + return True + + def wait(self, seconds: Optional[float] = None) -> None: + """Override to do nothing""" + + def present_inquiry( + self, inquiry_schedule: InquirySchedule + ) -> Tuple[List[Tuple[str, float]], bool]: + """Override ; returns empty timing info; always proceed for inquiry + preview""" + return [], True + + def show_feedback(self, selection: str, correct: bool = True) -> None: + """Override to do nothing""" + # TODO: consider tracking metrics + + def compute_button_press_evidence( + self, proceed: bool) -> Optional[Tuple[EvidenceType, List[float]]]: + # TODO: consider adding a sampler for this + return None + + def compute_device_evidence( + self, + stim_times: List[List], + proceed: bool = True) -> List[Tuple[EvidenceType, List[float]]]: + # TODO: sample for each evidence type + self.logger.info("Computing evidence with sim_state:") + self.logger.info(self.get_sim_state()) + + # sampled_trial = self.sampler.sample_trial(self.get_sim_state()) + sampled_data = self.sampler.sample_data(self.get_sim_state()) + + + # trial_info = (datasource, inquiry_n) + # eye_gaze_data = self.sampler['EYE'].sample(self.get_sim_state(), trial_info) + evidence = self.signal_model.predict(sampled_data, + self.current_symbols(), self.alp) + return [(EvidenceType.ERP, evidence)] + + def exit_display(self) -> None: + """Close the UI and cleanup.""" + + def elapsed_seconds(self) -> float: + # TODO: estimate this + return 0.0 + + def write_offset_trigger(self) -> None: + """Do nothing""" + + def write_trigger_data(self, stim_times: List[Tuple[str, float]], + target_stimuli: str) -> None: + """Do nothing""" + + def get_sim_state(self) -> SimState: + """Get the current state in the format expected by the simulation tools.""" + + return SimState( + target_symbol=self.next_target(), + current_sentence=self.spelled_text, + target_sentence=self.copy_phrase, + display_alphabet=self.current_symbols(), + # TODO: + inquiry_n=0, + series_n=0, + series_results=[], + decision_criterion=[]) + + def current_symbols(self) -> List[str]: + """Get the list of symbols from the current inquiry.""" + schedule = self.current_inquiry + stimuli = schedule.stimuli[0] + _fixation, *symbols = stimuli + return symbols diff --git a/bcipy/simulator/task/null_display.py b/bcipy/simulator/task/null_display.py new file mode 100644 index 000000000..fb5767e6c --- /dev/null +++ b/bcipy/simulator/task/null_display.py @@ -0,0 +1,17 @@ +"""Display that doesn't do anything""" +from typing import List, Tuple + +from bcipy.display import Display + + +class NullDisplay(Display): + """Display that doesn't show anything to the user.""" + + def do_inquiry(self) -> List[Tuple[str, float]]: + return [] + + def wait_screen(self, *args, **kwargs) -> None: + """Do nothing""" + + def update_task_bar(self, *args, **kwargs) -> None: + """Do nothing""" diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py new file mode 100644 index 000000000..609453c04 --- /dev/null +++ b/bcipy/simulator/task/task_runner.py @@ -0,0 +1,167 @@ +"""Setup and run the task""" + +import argparse +import logging +import os +from glob import glob +from pathlib import Path +from typing import List + +from bcipy.helpers.language_model import init_language_model +from bcipy.helpers.load import load_json_parameters, load_signal_models +from bcipy.helpers.parameters import Parameters +from bcipy.simulator.helpers import artifact +from bcipy.simulator.helpers.data_engine import RawDataEngine +from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler +from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask +from bcipy.task.main import Task + +logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) + + +def configure_run_directory(sim_dir: str, run: int) -> str: + """Create the necessary directories and configure the logger. + Returns the run directory. + """ + run_name = f"run_{run}" + path = f"{sim_dir}/{run_name}" + os.mkdir(path) + artifact.configure_logger(log_path=path, + file_name=f"{run_name}.log", + use_stdout=False) + return path + + +class TaskRunner(): + """Responsible for executing a task a given number of times.""" + + def __init__(self, + model_path: str, + params_path: str, + source_dirs: List[str], + save_dir: str, + runs: int = 1): + self.model_path = model_path + self.params_path = params_path + self.source_dirs = source_dirs + self.sim_dir = save_dir + self.runs = runs + + self.parameters = None + self.signal_models = [] + self.language_model = None + self.sampler = None + + def setup(self) -> None: + """Setup the task objects""" + logger.info("Loading parameters") + self.parameters = load_json_parameters(self.params_path, + value_cast=True) + + logger.info("Loading signal models") + self.signal_models = load_signal_models(directory=self.model_path) + logger.debug(self.signal_models) + + logger.info("Initializing language model") + self.language_model = init_language_model(self.parameters) + logger.debug(self.language_model) + + logger.info("Creating data engine") + data_engine = self.init_data_engine(self.source_dirs, self.parameters) + self.sampler = self.init_sampler(data_engine) + logger.debug("Using sampler:") + logger.debug(self.sampler) + + def setup_complete(self) -> bool: + """Determines if the runner has been setup correctly.""" + return all([ + self.parameters is not None, + len(self.signal_models) > 0, self.language_model is not None, + self.sampler is not None + ]) + + def init_data_engine(self, source_dirs: List[str], + parameters: Parameters) -> RawDataEngine: + """Initialize the data engine""" + return RawDataEngine(list(map(str, source_dirs)), parameters) + + def init_sampler(self, data_engine: RawDataEngine) -> Sampler: + """Initialize the Sampler""" + return EEGByLetterSampler(data_engine) + + def make_task(self, run_dir) -> Task: + """Create the task. This is done for every run.""" + return SimulatorCopyPhraseTask(self.parameters, + file_save=run_dir, + signal_models=self.signal_models, + language_model=self.language_model, + sampler=self.sampler) + + def run(self): + """Run one or more simulations""" + if not self.setup_complete(): + self.setup() + self.parameters.save(self.sim_dir) + for i in range(self.runs): + logger.info(f"Executing task {i+1}") + self.do_run(i + 1) + logger.info("Task complete") + + def do_run(self, run: int): + """Execute a simulation run.""" + run_dir = configure_run_directory(self.sim_dir, run) + logger.info(run_dir) + task = self.make_task(run_dir) + task.execute() + + +def main(): + """Run the task""" + glob_help = ('glob pattern to select a subset of data folders' + ' Ex. "*RSVP_Copy_Phrase*"') + parser = argparse.ArgumentParser() + parser.add_argument( + "-d", + "--data_folder", + type=Path, + required=True, + help= + "Raw data folders to be processed. Singular wrapper dir with data folders" + ) + parser.add_argument('-g', '--glob_pattern', help=glob_help, default="*") + parser.add_argument("-m", + "--model_path", + type=Path, + required=True, + help="Signal model to be used") + parser.add_argument("-p", + "--parameters", + type=Path, + required=True, + help="Parameter File to be used") + parser.add_argument("-n", + type=int, + required=False, + default=1, + help="Number of times to run the simulation") + args = parser.parse_args() + sim_args = vars(args) + + sim_args['source_dirs'] = [ + Path(d) for d in glob(str(Path(args.data_folder, args.glob_pattern))) + if Path(d).is_dir() + ] + + sim_dir = artifact.init_simulation_dir() + logger.info(sim_dir) + runner = TaskRunner(model_path=sim_args['model_path'], + params_path=sim_args['parameters'], + source_dirs=sim_args['source_dirs'], + save_dir=sim_dir, + runs=sim_args['n']) + runner.run() + + + +if __name__ == '__main__': + main() diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 82640dd20..5eb9d959f 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -122,8 +122,9 @@ def __init__( self.validate_parameters() - self.static_clock = core.StaticPeriod( - screenHz=self.window.getActualFrameRate()) + self.static_clock = None + # self.static_clock = core.StaticPeriod( + # screenHz=self.window.getActualFrameRate()) self.experiment_clock = Clock() self.start_time = self.experiment_clock.getTime() @@ -132,14 +133,10 @@ def __init__( self.button_press_error_prob = 0.05 self.evidence_evaluators = self.init_evidence_evaluators(signal_models) - - self.evidence_types = [EvidenceType.LM] - self.evidence_types.extend( - [evaluator.produces for evaluator in self.evidence_evaluators]) - if self.parameters['show_preview_inquiry']: - self.evidence_types.append(EvidenceType.BTN) + self.evidence_types = self.init_evidence_types(self.evidence_evaluators) self.file_save = file_save + self.save_session_every_inquiry = True self.trigger_handler = TriggerHandler(self.file_save, TRIGGER_FILENAME, FlushFrequency.EVERY) self.session_save_location = f"{self.file_save}/{SESSION_DATA_FILENAME}" @@ -150,15 +147,7 @@ def __init__( self.signal_model = signal_models[0] if signal_models else None self.evidence_precision = DEFAULT_EVIDENCE_PRECISION - self.feedback = VisualFeedback( - self.window, - {'feedback_font': self.parameters['font'], - 'feedback_color': self.parameters['info_color'], - 'feedback_pos_x': self.parameters['info_pos_x'], - 'feedback_pos_y': self.parameters['info_pos_y'], - 'feedback_stim_height': self.parameters['info_height'], - 'feedback_duration': self.parameters['feedback_duration']}, - self.experiment_clock) + self.feedback = self.init_feedback() self.setup() @@ -203,6 +192,14 @@ def init_evidence_evaluators(self, ) return evaluators + def init_evidence_types(self, evidence_evaluators: List[EvidenceEvaluator]) -> List[EvidenceType]: + evidence_types = [EvidenceType.LM] + evidence_types.extend( + [evaluator.produces for evaluator in evidence_evaluators]) + if self.parameters['show_preview_inquiry']: + evidence_types.append(EvidenceType.BTN) + return evidence_types + def setup(self) -> None: """Initialize/reset parameters used in the execute run loop.""" @@ -228,6 +225,18 @@ def init_display(self) -> CopyPhraseDisplay: self.experiment_clock, self.spelled_text) + def init_feedback(self) -> Optional[VisualFeedback]: + """Initialize visual feedback""" + return VisualFeedback( + self.window, { + 'feedback_font': self.parameters['font'], + 'feedback_color': self.parameters['info_color'], + 'feedback_pos_x': self.parameters['info_pos_x'], + 'feedback_pos_y': self.parameters['info_pos_y'], + 'feedback_stim_height': self.parameters['info_height'], + 'feedback_duration': self.parameters['feedback_duration'] + }, self.experiment_clock) + def validate_parameters(self) -> None: """Validate. @@ -372,7 +381,7 @@ def show_feedback(self, selection: str, correct: bool = True) -> None: - selection : selected stimulus to display - correct : whether or not the correct stim was chosen """ - if self.parameters['show_feedback']: + if self.parameters['show_feedback'] and self.feedback: self.feedback.administer(f'Selected: {selection}') def check_stop_criteria(self) -> bool: @@ -438,7 +447,7 @@ def execute(self) -> str: decision=decision, evidence_types=evidence_types) self.update_session_data(data, - save=True, + save=self.save_session_every_inquiry, decision_made=decision.decision_made) if decision.decision_made: @@ -713,12 +722,16 @@ def update_session_data(self, - self.session """ self.session.add_sequence(data) - self.session.total_time_spent = self.experiment_clock.getTime() - self.start_time + self.session.total_time_spent = self.elapsed_seconds() if save: self.write_session_data() if decision_made: self.session.add_series() + def elapsed_seconds(self) -> float: + """Compute the number of seconds elapsed since the experiment start.""" + return self.experiment_clock.getTime() - self.start_time + def write_session_data(self) -> None: """Save session data to disk.""" if self.session: From d20d314e7f373b11878404ff5f58651a29672b15 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 30 Aug 2024 15:29:13 -0700 Subject: [PATCH 289/330] Added a data_process module to the simulator. Re-structured the data processing code to support other models. Refactored data engine. --- bcipy/simulator/exceptions.py | 15 + bcipy/simulator/helpers/data_engine.py | 56 ++-- bcipy/simulator/helpers/data_process.py | 400 ++++++++++++++++++++++++ bcipy/simulator/task/copy_phrase.py | 16 +- bcipy/simulator/task/task_runner.py | 34 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 12 +- 6 files changed, 480 insertions(+), 53 deletions(-) create mode 100644 bcipy/simulator/exceptions.py create mode 100644 bcipy/simulator/helpers/data_process.py diff --git a/bcipy/simulator/exceptions.py b/bcipy/simulator/exceptions.py new file mode 100644 index 000000000..479fc1220 --- /dev/null +++ b/bcipy/simulator/exceptions.py @@ -0,0 +1,15 @@ +class DeviceSpecNotFoundError(Exception): + """Thrown when a suitable DeviceSpec was not found in the devices.json file + """ + +class IncompatibleData(Exception): + """Thrown when data is not suitable for the current simulation.""" + +class IncompatibleDeviceSpec(IncompatibleData): + """Thrown when a DeviceSpec in a data directory did not match the data or + when the model's spec was incompatible. + """ + +class IncompatibleParameters(IncompatibleData): + """Thrown when the timing parameters used for data collection are + incompatible with the timing parameters of the simulation.""" \ No newline at end of file diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index ba0086fe5..1935b9c73 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -51,7 +51,7 @@ class Trial(NamedTuple): inquiry_pos: int symbol: str target: int - eeg: np.ndarray # Channels by Samples + eeg: np.ndarray # Channels by Samples def __str__(self): fields = [ @@ -81,7 +81,6 @@ def __init__(self, self.data: List[ExtractedExperimentData] = [] self.schema: Optional[pd.DataFrame] = None - # TODO validate parameters self.load() def load(self) -> DataEngine: @@ -94,10 +93,12 @@ def load(self) -> DataEngine: """ if not self.data: log.debug( - f"Loading data from {len(self.source_dirs)} source directories:") + f"Loading data from {len(self.source_dirs)} source directories:" + ) for i, source_dir in enumerate(self.source_dirs): log.debug(f"{i+1}. {Path(source_dir).name}") - self.data.append(self.data_processor.process(source_dir, self.parameters)) + self.data.append( + self.data_processor.process(source_dir, self.parameters)) log.debug("Finished loading all data") return self @@ -114,34 +115,37 @@ def transform(self) -> DataEngine: Returns: self for chaining """ - - # TODO store how good evidence was in session - rows = [] for data_source in self.data: - symbols_by_inquiry = data_source.symbols_by_inquiry - labels_by_inquiry = data_source.labels_by_inquiry - - for i, inquiry_eeg in enumerate(data_source.trials_by_inquiry): - # iterate through each inquiry - inquiry_symbols = symbols_by_inquiry[i] - inquiry_labels = labels_by_inquiry[i] - - for sym_i, symbol in enumerate(inquiry_symbols): - # iterate through each symbol in the inquiry - eeg_samples = [channel[sym_i] for channel in inquiry_eeg - ] # (channel_n, sample_n) - rows.append( - Trial(source=data_source.source_dir, - inquiry_n=i, - inquiry_pos=sym_i + 1, - symbol=symbol, - target=inquiry_labels[sym_i], - eeg=np.array(eeg_samples))) + rows.extend(self.trials(data_source)) self.schema = pd.DataFrame(rows) return self + def trials(self, data_source: ExtractedExperimentData) -> List[Trial]: + """Convert extracted data from a single data source to a list of Trials.""" + trials = [] + symbols_by_inquiry = data_source.symbols_by_inquiry + labels_by_inquiry = data_source.labels_by_inquiry + + for i, inquiry_eeg in enumerate(data_source.trials_by_inquiry): + # iterate through each inquiry + inquiry_symbols = symbols_by_inquiry[i] + inquiry_labels = labels_by_inquiry[i] + + for sym_i, symbol in enumerate(inquiry_symbols): + # iterate through each symbol in the inquiry + eeg_samples = [channel[sym_i] for channel in inquiry_eeg + ] # (channel_n, sample_n) + trials.append( + Trial(source=data_source.source_dir, + inquiry_n=i, + inquiry_pos=sym_i + 1, + symbol=symbol, + target=inquiry_labels[sym_i], + eeg=np.array(eeg_samples))) + return trials + def get_data(self): return self.schema.copy() if self.schema is not None else None diff --git a/bcipy/simulator/helpers/data_process.py b/bcipy/simulator/helpers/data_process.py new file mode 100644 index 000000000..5a050250e --- /dev/null +++ b/bcipy/simulator/helpers/data_process.py @@ -0,0 +1,400 @@ +"""This defines functionality related to pre-processing simulation data. +Processed data can be subsequently sampled and provided to a SignalModel +for classification.""" + +import logging as logger +from dataclasses import dataclass +from pathlib import Path +from typing import Any, List, NamedTuple, Optional, Tuple + +import numpy as np + +from bcipy.acquisition import devices +from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.multimodal import ContentType +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETER_FILENAME, TRIGGER_FILENAME) +from bcipy.helpers.acquisition import analysis_channels, raw_data_filename +from bcipy.helpers.list import grouper +from bcipy.helpers.load import load_json_parameters, load_raw_data +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.raw_data import RawData +from bcipy.helpers.stimuli import update_inquiry_timing +from bcipy.helpers.triggers import TriggerType, trigger_decoder +from bcipy.signal.model.base_model import SignalModel +from bcipy.signal.process import (ERPTransformParams, filter_inquiries, + get_default_transform) +from bcipy.signal.process.transform import Composition +from bcipy.simulator.exceptions import (DeviceSpecNotFoundError, + IncompatibleDeviceSpec, + IncompatibleParameters) +from bcipy.task.data import EvidenceType + +log = logger.getLogger(__name__) + + +def load_device_data(data_folder: str, + content_type: str) -> Tuple[RawData, DeviceSpec]: + """Loads the data into the RawData format for the given content type. + + Parameters + ---------- + data_folder - session data folder with the raw data, device_spec, etc. + content_type - content type of the data to load. + + Returns + ------- + tuple of the raw data and the associated DeviceSpec for the device used + to record that data. + """ + devices_by_name = devices.load(Path(data_folder, + DEFAULT_DEVICE_SPEC_FILENAME), + replace=True) + specs = [ + spec for spec in devices_by_name.values() + if spec.is_active and spec.content_type == content_type + ] + if not specs: + raise DeviceSpecNotFoundError( + f"Suitable entry not found in {data_folder}/devices.json") + device_spec = specs[0] + raw_data_path = Path(data_folder, raw_data_filename(device_spec)) + if not raw_data_path.exists(): + raise FileNotFoundError(f"Raw data file not found: {raw_data_path}") + raw_data = load_raw_data(raw_data_path) + + if device_spec != devices.preconfigured_device(raw_data.daq_type): + raise IncompatibleDeviceSpec( + "DeviceSpec in devices.json does not match the raw data.") + + return raw_data, device_spec + + +class DecodedTriggers(NamedTuple): + """Extracted properties after decoding the triggers.txt file and applying + the necessary offsets and corrections.""" + targetness: List[str] # TriggerType + times: List[float] + symbols: List[str] # symbol + corrected_times: List[float] + + +@dataclass() +class ExtractedExperimentData: + source_dir: str + inquiries: np.ndarray + trials: np.ndarray + labels: List + inquiry_timing: List + + decoded_triggers: DecodedTriggers + trials_per_inquiry: int + + @property + def trials_by_inquiry(self) -> List[np.ndarray]: + """EEG data by inquiry. + shape (i_inquiry, n_channel, m_trial, x_sample) + """ + return np.split(self.trials, self.inquiries.shape[1], 1) + + @property + def symbols_by_inquiry(self) -> List[List[str]]: + """Get symbols by inquiry. shape (i_inquiry, s_alphabet_subset)""" + trigger_symbols = self.decoded_triggers.symbols + return [ + list(group) for group in grouper( + trigger_symbols, self.trials_per_inquiry, incomplete="ignore") + ] + + @property + def labels_by_inquiry(self) -> List[List[int]]: + """Shape (i_inquiry, s_alphabet_subset)""" + return self.labels + + +class TimingParams(NamedTuple): + """Timing-related parameters used in parsing the raw data into inquiries and trials.""" + # window (in seconds) of data collection after each stimulus presentation. + trial_window: Tuple[float, float] + # seconds before the start of the inquiry to use. + prestim_length: float + + # delay time (in seconds) between the final stimulus in one inquiry and the + # beginning (target stimulus or fixation cross) of the next inquiry. + task_buffer_length: float + stim_length: int + time_flash: float + + @property + def trials_per_inquiry(self) -> int: + """Alias for stim_length""" + return self.stim_length + + @property + def buffer(self) -> float: + """The task buffer length defines the min time between two inquiries + We use half of that time here to buffer during transforms""" + return self.task_buffer_length / 2 + + @property + def window_length(self) -> float: + """window (in seconds) of data collection after each stimulus presentation""" + start, end = self.trial_window + return end - start + + def __str__(self): + return ( + f"Timing settings: \n" + f"Trial Window: {self.trial_window[0]} to {self.trial_window[1]}s, " + f"Prestimulus Buffer: {self.prestim_length}s, Poststimulus Buffer: {self.buffer}s \n" + ) + + +def decode_triggers( + data_folder: str, + timing_params: TimingParams, + device_offset: float = 0.0, + excluded_triggers: Optional[List[TriggerType]] = None +) -> DecodedTriggers: + """Decode the triggers.txt file in the given directory.""" + if not excluded_triggers: + excluded_triggers = [ + TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION + ] + targetness, times, symbols = trigger_decoder( + offset=device_offset, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=excluded_triggers, + ) + corrected = [time + timing_params.trial_window[0] for time in times] + return DecodedTriggers(targetness=targetness, + times=times, + symbols=symbols, + corrected_times=corrected) + + +class ReshapedData(): + """Represents data components after reshaping""" + + def __init__(self): + self.inquiries: np.ndarray = np.array([]) + self.inquiry_labels: np.ndarray = np.array([]) + self.inquiry_timing: List[List[int]] = [] + + +class RawDataProcessor(): + """Processes raw data for a given device and converts it to + ExtractedExperimentData for use in the simulator. + + 1. Loads the data file as a RawData object + 2. Extract timing information from trigger file based on the device of interest. + 3. Reshape and label the data. + 4. Apply filtering. + 5. Extract trials. + + Parameters + ---------- + model - signal model which will be used to classify the resulting data + """ + + def __init__(self, model: SignalModel): + self.check_model_compatibility(model) + self.model = model + + @property + def consumes(self) -> ContentType: + """ContentType of the data that should be input""" + + @property + def produces(self) -> EvidenceType: + """Type of evidence that is output""" + + @property + def content_type(self): + """Get the content_type of the data.""" + return self.consumes + + @property + def model_device(self) -> DeviceSpec: + """Device used to collect data for training the model.""" + return self.model.metadata.device_spec + + @property + def reshaper(self): + """data reshaper""" + return self.model.reshaper + + def check_model_compatibility(self, model: SignalModel) -> None: + """Check that the given model is compatible with this processor. + Checked on initialization.""" + assert model.metadata, "Metadata missing from signal model." + assert ContentType( + model.metadata.device_spec.content_type + ) == self.consumes, "DataProcessor is not compatible with the given model" + + def check_data_compatibility(self, data_device: DeviceSpec, + sim_timing_params: TimingParams, + data_timing_params: TimingParams) -> None: + """Check the compatibility of a dataset with the model.""" + if not self.devices_compatible(self.model_device, data_device): + raise IncompatibleDeviceSpec("Devices are not compatible") + if not self.parameters_compatible(sim_timing_params, + data_timing_params): + raise IncompatibleParameters( + "Timing parameters are not compatible") + + if data_device.static_offset == devices.DEFAULT_STATIC_OFFSET: + log.warning(' '.join([ + f"Using the default static offset to decode triggers for {data_device.name}.", + "Please make sure the correct offset is included in the devices.json file." + ])) + + def process(self, data_folder: str, + parameters: Parameters) -> ExtractedExperimentData: + """Load and process the data + + Parameters + ---------- + data_folder - session directory for a given dataset + (contains raw_data, devices.json, and parameters.json). + parameters - parameters.json file for the calibration session used + to train the model / run the simulation. + """ + raw_data, device_spec = load_device_data(data_folder, + self.content_type.name) + data_parameters = load_json_parameters( + f"{data_folder}/{DEFAULT_PARAMETER_FILENAME}", value_cast=True) + + timing_params = parameters.instantiate(TimingParams) + transform_params = self.transform_parameters(parameters) + + self.check_data_compatibility( + data_device=device_spec, + sim_timing_params=timing_params, + data_timing_params=data_parameters.instantiate(TimingParams)) + + decoded_triggers = decode_triggers(data_folder, timing_params, + device_spec.static_offset, + self.excluded_triggers()) + + reshaped_data = self.reshape_data(raw_data, decoded_triggers, + timing_params) + + filtered_reshaped_data, new_sample_rate = self.apply_filters( + reshaped_data, transform_params, raw_data.sample_rate) + + trials = self.extract_trials(filtered_reshaped_data, timing_params, + new_sample_rate) + return ExtractedExperimentData( + data_folder, + filtered_reshaped_data.inquiries, + trials, + [list(arr) for arr in filtered_reshaped_data.inquiry_labels], + filtered_reshaped_data.inquiry_timing, + decoded_triggers=decoded_triggers, + trials_per_inquiry=timing_params.trials_per_inquiry) + + def reshape_data(self, raw_data: RawData, + decoded_triggers: DecodedTriggers, + timing_params: TimingParams) -> ReshapedData: + """Use the configured reshaper to reshape the data.""" + + data, _fs = raw_data.by_channel() + channel_map = analysis_channels(raw_data.channels, self.model_device) + inquiries, inquiry_labels, inquiry_timing = self.reshaper( + trial_targetness_label=decoded_triggers.targetness, + timing_info=decoded_triggers.corrected_times, + eeg_data=data, + sample_rate=raw_data.sample_rate, + trials_per_inquiry=timing_params.trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=timing_params.window_length, + prestimulus_length=timing_params.prestim_length, + transformation_buffer=timing_params.buffer, + ) + reshaped = ReshapedData() + reshaped.inquiries = inquiries + reshaped.inquiry_labels = inquiry_labels + reshaped.inquiry_timing = inquiry_timing + return reshaped + + def reshaped_data_inquiries(self, reshaped_data: Any) -> np.ndarray: + """Get the inquiries from the result of calling self.reshape_data(...)""" + return reshaped_data[0] + + def apply_filters(self, reshaped_data: ReshapedData, + transform_params: NamedTuple, + data_sample_rate: float) -> Tuple[ReshapedData, int]: + """Apply any filters to the reshaped data. + + Returns + ------- + inquiry data after filtering, updated sample_rate + """ + transform = self.get_transform(transform_params, data_sample_rate) + inquiries, fs = filter_inquiries(reshaped_data.inquiries, transform, + data_sample_rate) + inquiry_timing_ints: List[List[int]] = [ + list(map(int, inq)) for inq in reshaped_data.inquiry_timing + ] + filtered_reshaped_data = ReshapedData() + filtered_reshaped_data.inquiries = inquiries + filtered_reshaped_data.inquiry_timing = update_inquiry_timing( + inquiry_timing_ints, transform_params.down_sampling_rate) + filtered_reshaped_data.inquiry_labels = reshaped_data.inquiry_labels + return filtered_reshaped_data, fs + + def extract_trials(self, filtered_reshaped_data: ReshapedData, + timing_params: TimingParams, + updated_sample_rate: float) -> np.ndarray: + """Extract trial data from the filtered, reshaped data. + + Returns + ------- + np.ndarray of shape (Channels, Trials, Samples) + """ + trial_duration_samples = int(timing_params.window_length * + updated_sample_rate) + return self.reshaper.extract_trials( + filtered_reshaped_data.inquiries, trial_duration_samples, + filtered_reshaped_data.inquiry_timing) + + def get_transform(self, transform_params: NamedTuple, + data_sample_rate: float) -> Composition: + """"Get the transform used for filtering the data.""" + return get_default_transform( + sample_rate_hz=data_sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) + + def excluded_triggers(self): + """Trigger types to exclude when decoding""" + return [TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION] + + def transform_parameters(self, parameters: Parameters) -> NamedTuple: + """Extract the parameters used for filtering.""" + return parameters.instantiate(ERPTransformParams) + + def devices_compatible(self, model_device: DeviceSpec, + data_device: DeviceSpec) -> bool: + """Check compatibility between the device on which the model was trained + and the device used for data collection.""" + + # TODO: check analysis channels? + return model_device.sample_rate == data_device.sample_rate + + def parameters_compatible(self, sim_timing_params: TimingParams, + data_timing_params: TimingParams) -> bool: + """Check compatibility between the parameters used for simulation and + those used for data collection.""" + return sim_timing_params.time_flash == data_timing_params.time_flash + + +class EegRawDataProcessor(RawDataProcessor): + """RawDataProcessor that processes EEG data.""" + consumes = ContentType.EEG + produces = EvidenceType.ERP diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index fc6ad5783..7539fdcff 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -14,6 +14,13 @@ from bcipy.task.data import EvidenceType from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask +DEFAULT_EVIDENCE_TYPE = EvidenceType.ERP + + +def get_evidence_type(model: SignalModel) -> EvidenceType: + """Get the evidence type provided by the given model""" + return model.metadata.evidence_type or DEFAULT_EVIDENCE_TYPE + class SimulatorCopyPhraseTask(RSVPCopyPhraseTask): """CopyPhraseTask that simulates user interactions by sampling data @@ -41,10 +48,12 @@ def init_evidence_evaluators( return [] def init_evidence_types( - self, evidence_evaluators: List[EvidenceEvaluator] + self, signal_models: List[SignalModel], + evidence_evaluators: List[EvidenceEvaluator] ) -> List[EvidenceType]: - # TODO: revisit this based on the provided models - return [EvidenceType.LM, EvidenceType.ERP] + evidence_types = set( + [get_evidence_type(model) for model in self.signal_models]) + return [EvidenceType.LM, *evidence_types] def init_display(self) -> Display: return NullDisplay() @@ -85,7 +94,6 @@ def compute_device_evidence( # sampled_trial = self.sampler.sample_trial(self.get_sim_state()) sampled_data = self.sampler.sample_data(self.get_sim_state()) - # trial_info = (datasource, inquiry_n) # eye_gaze_data = self.sampler['EYE'].sample(self.get_sim_state(), trial_info) evidence = self.signal_model.predict(sampled_data, diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index 609453c04..225ad2497 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -9,10 +9,10 @@ from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import load_json_parameters, load_signal_models -from bcipy.helpers.parameters import Parameters from bcipy.simulator.helpers import artifact from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler +from bcipy.simulator.helpers.data_process import EegRawDataProcessor +from bcipy.simulator.helpers.sampler import EEGByLetterSampler from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask from bcipy.task.main import Task @@ -47,6 +47,9 @@ def __init__(self, self.sim_dir = save_dir self.runs = runs + self.sampling_strategy = EEGByLetterSampler + self.simulation_task = SimulatorCopyPhraseTask + self.parameters = None self.signal_models = [] self.language_model = None @@ -67,8 +70,11 @@ def setup(self) -> None: logger.debug(self.language_model) logger.info("Creating data engine") - data_engine = self.init_data_engine(self.source_dirs, self.parameters) - self.sampler = self.init_sampler(data_engine) + # TODO: initialize a data engine and sampler for each model + data_processor = EegRawDataProcessor(self.signal_models[0]) + data_engine = RawDataEngine(list(map(str, self.source_dirs)), + self.parameters, data_processor) + self.sampler = self.sampling_strategy(data_engine) logger.debug("Using sampler:") logger.debug(self.sampler) @@ -80,22 +86,13 @@ def setup_complete(self) -> bool: self.sampler is not None ]) - def init_data_engine(self, source_dirs: List[str], - parameters: Parameters) -> RawDataEngine: - """Initialize the data engine""" - return RawDataEngine(list(map(str, source_dirs)), parameters) - - def init_sampler(self, data_engine: RawDataEngine) -> Sampler: - """Initialize the Sampler""" - return EEGByLetterSampler(data_engine) - def make_task(self, run_dir) -> Task: """Create the task. This is done for every run.""" - return SimulatorCopyPhraseTask(self.parameters, - file_save=run_dir, - signal_models=self.signal_models, - language_model=self.language_model, - sampler=self.sampler) + return self.simulation_task(self.parameters, + file_save=run_dir, + signal_models=self.signal_models, + language_model=self.language_model, + sampler=self.sampler) def run(self): """Run one or more simulations""" @@ -162,6 +159,5 @@ def main(): runner.run() - if __name__ == '__main__': main() diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 5eb9d959f..16c99dc68 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -119,6 +119,9 @@ def __init__( self.window = win self.daq = daq self.parameters = parameters + self.signal_models = signal_models + self.language_model = language_model + self.fake = fake self.validate_parameters() @@ -133,7 +136,7 @@ def __init__( self.button_press_error_prob = 0.05 self.evidence_evaluators = self.init_evidence_evaluators(signal_models) - self.evidence_types = self.init_evidence_types(self.evidence_evaluators) + self.evidence_types = self.init_evidence_types(self.signal_models, self.evidence_evaluators) self.file_save = file_save self.save_session_every_inquiry = True @@ -142,8 +145,6 @@ def __init__( self.session_save_location = f"{self.file_save}/{SESSION_DATA_FILENAME}" self.copy_phrase = parameters['task_text'] - self.fake = fake - self.language_model = language_model self.signal_model = signal_models[0] if signal_models else None self.evidence_precision = DEFAULT_EVIDENCE_PRECISION @@ -192,7 +193,10 @@ def init_evidence_evaluators(self, ) return evaluators - def init_evidence_types(self, evidence_evaluators: List[EvidenceEvaluator]) -> List[EvidenceType]: + def init_evidence_types( + self, signal_models: List[SignalModel], + evidence_evaluators: List[EvidenceEvaluator] + ) -> List[EvidenceType]: evidence_types = [EvidenceType.LM] evidence_types.extend( [evaluator.produces for evaluator in evidence_evaluators]) From c2533d884cdeefef47d0adc36f3b9b05adc7ad75 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 30 Aug 2024 16:09:53 -0700 Subject: [PATCH 290/330] Code cleanup --- bcipy/simulator/exceptions.py | 7 +- bcipy/simulator/helpers/data_process.py | 103 +++++++++++++++--------- bcipy/simulator/helpers/log_utils.py | 1 + bcipy/simulator/helpers/sampler.py | 4 +- bcipy/simulator/task/task_runner.py | 13 ++- 5 files changed, 80 insertions(+), 48 deletions(-) diff --git a/bcipy/simulator/exceptions.py b/bcipy/simulator/exceptions.py index 479fc1220..a7f3bad15 100644 --- a/bcipy/simulator/exceptions.py +++ b/bcipy/simulator/exceptions.py @@ -2,14 +2,17 @@ class DeviceSpecNotFoundError(Exception): """Thrown when a suitable DeviceSpec was not found in the devices.json file """ + class IncompatibleData(Exception): - """Thrown when data is not suitable for the current simulation.""" + """Thrown when data is not suitable for the current simulation.""" + class IncompatibleDeviceSpec(IncompatibleData): """Thrown when a DeviceSpec in a data directory did not match the data or when the model's spec was incompatible. """ + class IncompatibleParameters(IncompatibleData): """Thrown when the timing parameters used for data collection are - incompatible with the timing parameters of the simulation.""" \ No newline at end of file + incompatible with the timing parameters of the simulation.""" diff --git a/bcipy/simulator/helpers/data_process.py b/bcipy/simulator/helpers/data_process.py index 5a050250e..5bb4ed8d7 100644 --- a/bcipy/simulator/helpers/data_process.py +++ b/bcipy/simulator/helpers/data_process.py @@ -5,7 +5,7 @@ import logging as logger from dataclasses import dataclass from pathlib import Path -from typing import Any, List, NamedTuple, Optional, Tuple +from typing import List, NamedTuple, Optional, Tuple import numpy as np @@ -36,7 +36,7 @@ def load_device_data(data_folder: str, content_type: str) -> Tuple[RawData, DeviceSpec]: """Loads the data into the RawData format for the given content type. - + Parameters ---------- data_folder - session data folder with the raw data, device_spec, etc. @@ -185,7 +185,7 @@ def __init__(self): class RawDataProcessor(): """Processes raw data for a given device and converts it to ExtractedExperimentData for use in the simulator. - + 1. Loads the data file as a RawData object 2. Extract timing information from trigger file based on the device of interest. 3. Reshape and label the data. @@ -252,10 +252,10 @@ def check_data_compatibility(self, data_device: DeviceSpec, def process(self, data_folder: str, parameters: Parameters) -> ExtractedExperimentData: """Load and process the data - + Parameters ---------- - data_folder - session directory for a given dataset + data_folder - session directory for a given dataset (contains raw_data, devices.json, and parameters.json). parameters - parameters.json file for the calibration session used to train the model / run the simulation. @@ -294,6 +294,63 @@ def process(self, data_folder: str, decoded_triggers=decoded_triggers, trials_per_inquiry=timing_params.trials_per_inquiry) + def reshape_data(self, raw_data: RawData, + decoded_triggers: DecodedTriggers, + timing_params: TimingParams) -> ReshapedData: + """Use the configured reshaper to reshape the data.""" + raise NotImplementedError + + def apply_filters(self, reshaped_data: ReshapedData, + transform_params: Optional[NamedTuple], + data_sample_rate: float) -> Tuple[ReshapedData, int]: + """Apply any filters to the reshaped data. + + Returns + ------- + inquiry data after filtering, updated sample_rate + """ + raise NotImplementedError + + def extract_trials(self, filtered_reshaped_data: ReshapedData, + timing_params: TimingParams, + updated_sample_rate: float) -> np.ndarray: + """Extract trial data from the filtered, reshaped data. + + Returns + ------- + np.ndarray of shape (Channels, Trials, Samples) + """ + raise NotImplementedError + + def excluded_triggers(self): + """Trigger types to exclude when decoding""" + return [TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION] + + def transform_parameters(self, + parameters: Parameters) -> Optional[NamedTuple]: + """Extract the parameters used for filtering.""" + raise NotImplementedError + + def devices_compatible(self, model_device: DeviceSpec, + data_device: DeviceSpec) -> bool: + """Check compatibility between the device on which the model was trained + and the device used for data collection.""" + + # TODO: check analysis channels? + return model_device.sample_rate == data_device.sample_rate + + def parameters_compatible(self, sim_timing_params: TimingParams, + data_timing_params: TimingParams) -> bool: + """Check compatibility between the parameters used for simulation and + those used for data collection.""" + return sim_timing_params.time_flash == data_timing_params.time_flash + + +class EegRawDataProcessor(RawDataProcessor): + """RawDataProcessor that processes EEG data.""" + consumes = ContentType.EEG + produces = EvidenceType.ERP + def reshape_data(self, raw_data: RawData, decoded_triggers: DecodedTriggers, timing_params: TimingParams) -> ReshapedData: @@ -318,12 +375,8 @@ def reshape_data(self, raw_data: RawData, reshaped.inquiry_timing = inquiry_timing return reshaped - def reshaped_data_inquiries(self, reshaped_data: Any) -> np.ndarray: - """Get the inquiries from the result of calling self.reshape_data(...)""" - return reshaped_data[0] - def apply_filters(self, reshaped_data: ReshapedData, - transform_params: NamedTuple, + transform_params: Optional[NamedTuple], data_sample_rate: float) -> Tuple[ReshapedData, int]: """Apply any filters to the reshaped data. @@ -331,6 +384,7 @@ def apply_filters(self, reshaped_data: ReshapedData, ------- inquiry data after filtering, updated sample_rate """ + assert transform_params, "Transform params not initialized." transform = self.get_transform(transform_params, data_sample_rate) inquiries, fs = filter_inquiries(reshaped_data.inquiries, transform, data_sample_rate) @@ -348,7 +402,7 @@ def extract_trials(self, filtered_reshaped_data: ReshapedData, timing_params: TimingParams, updated_sample_rate: float) -> np.ndarray: """Extract trial data from the filtered, reshaped data. - + Returns ------- np.ndarray of shape (Channels, Trials, Samples) @@ -371,30 +425,7 @@ def get_transform(self, transform_params: NamedTuple, downsample_factor=transform_params.down_sampling_rate, ) - def excluded_triggers(self): - """Trigger types to exclude when decoding""" - return [TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION] - - def transform_parameters(self, parameters: Parameters) -> NamedTuple: + def transform_parameters(self, + parameters: Parameters) -> ERPTransformParams: """Extract the parameters used for filtering.""" return parameters.instantiate(ERPTransformParams) - - def devices_compatible(self, model_device: DeviceSpec, - data_device: DeviceSpec) -> bool: - """Check compatibility between the device on which the model was trained - and the device used for data collection.""" - - # TODO: check analysis channels? - return model_device.sample_rate == data_device.sample_rate - - def parameters_compatible(self, sim_timing_params: TimingParams, - data_timing_params: TimingParams) -> bool: - """Check compatibility between the parameters used for simulation and - those used for data collection.""" - return sim_timing_params.time_flash == data_timing_params.time_flash - - -class EegRawDataProcessor(RawDataProcessor): - """RawDataProcessor that processes EEG data.""" - consumes = ContentType.EEG - produces = EvidenceType.ERP diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 61c111bd0..42e6a0a22 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -22,6 +22,7 @@ def format_samples(sample_rows: List[Trial]) -> str: """Returns a tabular representation of the sample rows.""" return '\n'.join([str(row) for row in sample_rows]) + def format_sample_rows(sample_rows: List[pd.Series]) -> str: """Returns a tabular representation of the sample rows.""" return pd.DataFrame(sample_rows).drop(columns=['eeg']).to_string( diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 23419138c..cd2b0441a 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -72,11 +72,11 @@ def sample_data(self, state: SimState) -> np.ndarray: def sample_with_context(self, state: SimState) -> Tuple[np.ndarray, List[Trial]]: - """ + """ Returns ------- A tuple of the reshaped data (ndarray of shape (n_channel, n_trial, n_sample)) as - well as a list of Trial data (metadata and data not reshaped) for context. + well as a list of Trial data (metadata and data not reshaped) for context. """ trials = self.sample(state) data = self.reshaped(trials) diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index 225ad2497..be984710f 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -117,14 +117,11 @@ def main(): glob_help = ('glob pattern to select a subset of data folders' ' Ex. "*RSVP_Copy_Phrase*"') parser = argparse.ArgumentParser() - parser.add_argument( - "-d", - "--data_folder", - type=Path, - required=True, - help= - "Raw data folders to be processed. Singular wrapper dir with data folders" - ) + parser.add_argument("-d", + "--data_folder", + type=Path, + required=True, + help="Raw data folders to be processed.") parser.add_argument('-g', '--glob_pattern', help=glob_help, default="*") parser.add_argument("-m", "--model_path", From f91c758c27c9b773540bb1bbd13944eec1d16cc1 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 30 Aug 2024 16:27:43 -0700 Subject: [PATCH 291/330] Typing fixes --- bcipy/simulator/helpers/data_process.py | 30 +++++++++---------------- bcipy/simulator/task/task_runner.py | 11 +++++---- 2 files changed, 17 insertions(+), 24 deletions(-) diff --git a/bcipy/simulator/helpers/data_process.py b/bcipy/simulator/helpers/data_process.py index 5bb4ed8d7..213f83961 100644 --- a/bcipy/simulator/helpers/data_process.py +++ b/bcipy/simulator/helpers/data_process.py @@ -61,7 +61,7 @@ def load_device_data(data_folder: str, raw_data_path = Path(data_folder, raw_data_filename(device_spec)) if not raw_data_path.exists(): raise FileNotFoundError(f"Raw data file not found: {raw_data_path}") - raw_data = load_raw_data(raw_data_path) + raw_data = load_raw_data(str(raw_data_path)) if device_spec != devices.preconfigured_device(raw_data.daq_type): raise IncompatibleDeviceSpec( @@ -208,6 +208,7 @@ def consumes(self) -> ContentType: @property def produces(self) -> EvidenceType: """Type of evidence that is output""" + raise NotImplementedError @property def content_type(self): @@ -266,7 +267,6 @@ def process(self, data_folder: str, f"{data_folder}/{DEFAULT_PARAMETER_FILENAME}", value_cast=True) timing_params = parameters.instantiate(TimingParams) - transform_params = self.transform_parameters(parameters) self.check_data_compatibility( data_device=device_spec, @@ -281,7 +281,7 @@ def process(self, data_folder: str, timing_params) filtered_reshaped_data, new_sample_rate = self.apply_filters( - reshaped_data, transform_params, raw_data.sample_rate) + reshaped_data, parameters, raw_data.sample_rate) trials = self.extract_trials(filtered_reshaped_data, timing_params, new_sample_rate) @@ -301,8 +301,8 @@ def reshape_data(self, raw_data: RawData, raise NotImplementedError def apply_filters(self, reshaped_data: ReshapedData, - transform_params: Optional[NamedTuple], - data_sample_rate: float) -> Tuple[ReshapedData, int]: + parameters: Parameters, + data_sample_rate: int) -> Tuple[ReshapedData, int]: """Apply any filters to the reshaped data. Returns @@ -326,11 +326,6 @@ def excluded_triggers(self): """Trigger types to exclude when decoding""" return [TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION] - def transform_parameters(self, - parameters: Parameters) -> Optional[NamedTuple]: - """Extract the parameters used for filtering.""" - raise NotImplementedError - def devices_compatible(self, model_device: DeviceSpec, data_device: DeviceSpec) -> bool: """Check compatibility between the device on which the model was trained @@ -376,15 +371,15 @@ def reshape_data(self, raw_data: RawData, return reshaped def apply_filters(self, reshaped_data: ReshapedData, - transform_params: Optional[NamedTuple], - data_sample_rate: float) -> Tuple[ReshapedData, int]: + parameters: Parameters, + data_sample_rate: int) -> Tuple[ReshapedData, int]: """Apply any filters to the reshaped data. Returns ------- inquiry data after filtering, updated sample_rate """ - assert transform_params, "Transform params not initialized." + transform_params = parameters.instantiate(ERPTransformParams) transform = self.get_transform(transform_params, data_sample_rate) inquiries, fs = filter_inquiries(reshaped_data.inquiries, transform, data_sample_rate) @@ -413,8 +408,8 @@ def extract_trials(self, filtered_reshaped_data: ReshapedData, filtered_reshaped_data.inquiries, trial_duration_samples, filtered_reshaped_data.inquiry_timing) - def get_transform(self, transform_params: NamedTuple, - data_sample_rate: float) -> Composition: + def get_transform(self, transform_params: ERPTransformParams, + data_sample_rate: int) -> Composition: """"Get the transform used for filtering the data.""" return get_default_transform( sample_rate_hz=data_sample_rate, @@ -424,8 +419,3 @@ def get_transform(self, transform_params: NamedTuple, bandpass_order=transform_params.filter_order, downsample_factor=transform_params.down_sampling_rate, ) - - def transform_parameters(self, - parameters: Parameters) -> ERPTransformParams: - """Extract the parameters used for filtering.""" - return parameters.instantiate(ERPTransformParams) diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index be984710f..18ec00728 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -5,14 +5,15 @@ import os from glob import glob from pathlib import Path -from typing import List +from typing import List, Optional from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import load_json_parameters, load_signal_models +from bcipy.signal.model.base_model import SignalModel from bcipy.simulator.helpers import artifact from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.data_process import EegRawDataProcessor -from bcipy.simulator.helpers.sampler import EEGByLetterSampler +from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask from bcipy.task.main import Task @@ -51,9 +52,9 @@ def __init__(self, self.simulation_task = SimulatorCopyPhraseTask self.parameters = None - self.signal_models = [] + self.signal_models: List[SignalModel] = [] self.language_model = None - self.sampler = None + self.sampler: Optional[Sampler] = None def setup(self) -> None: """Setup the task objects""" @@ -88,6 +89,7 @@ def setup_complete(self) -> bool: def make_task(self, run_dir) -> Task: """Create the task. This is done for every run.""" + assert self.sampler, "Sampler must be initialized" return self.simulation_task(self.parameters, file_save=run_dir, signal_models=self.signal_models, @@ -98,6 +100,7 @@ def run(self): """Run one or more simulations""" if not self.setup_complete(): self.setup() + assert self.parameters, "Parameters is not initialized" self.parameters.save(self.sim_dir) for i in range(self.runs): logger.info(f"Executing task {i+1}") From 8640e8df094522478d981744169d3bdd4c30fa5b Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 30 Aug 2024 17:31:59 -0700 Subject: [PATCH 292/330] Created TaskFactory for constructing new simulation tasks. Separated out behavior from TaskRunner. Functions to match a model with an appropriate DataProcessor --- bcipy/simulator/helpers/data_process.py | 50 ++++++++++- bcipy/simulator/task/copy_phrase.py | 20 +++-- bcipy/simulator/task/task_runner.py | 109 +++++++++++++----------- 3 files changed, 117 insertions(+), 62 deletions(-) diff --git a/bcipy/simulator/helpers/data_process.py b/bcipy/simulator/helpers/data_process.py index 213f83961..ec4611375 100644 --- a/bcipy/simulator/helpers/data_process.py +++ b/bcipy/simulator/helpers/data_process.py @@ -5,7 +5,7 @@ import logging as logger from dataclasses import dataclass from pathlib import Path -from typing import List, NamedTuple, Optional, Tuple +from typing import List, NamedTuple, Optional, Tuple, Type import numpy as np @@ -419,3 +419,51 @@ def get_transform(self, transform_params: ERPTransformParams, bandpass_order=transform_params.filter_order, downsample_factor=transform_params.down_sampling_rate, ) + + +def get_processor( + data_source: ContentType, + evidence_type: Optional[EvidenceType] = None +) -> Type[RawDataProcessor]: + """Returns the matching processor class. + + Parameters + ---------- + data_source - type of data that the processor should consume + evidence_type - type of evidence that the processor should produce. + """ + matches = [ + cls for cls in RawDataProcessor.__subclasses__() + if cls.consumes == data_source and ( + evidence_type is None or cls.produces == evidence_type) + ] + if matches: + return matches[0] + else: + msg = f"Data processor not found for {data_source.name}" + if evidence_type: + msg += f" -> {evidence_type.name}" + raise Exception(msg) + + +def find_data_processor(model: SignalModel) -> Type[RawDataProcessor]: + """Get the DataProcessor appropriate for the given model.""" + content_type = ContentType(model.metadata.device_spec.content_type) + # Metadata may provide an EvidenceType with a model so the same data source can + # be used to produce multiple types of evidence (ex. alpha) + evidence_type = None + model_output = model.metadata.evidence_type + if model_output: + try: + evidence_type = EvidenceType(model_output.upper()) + except ValueError: + logger.error(f"Unsupported evidence type: {model_output}") + + return get_processor(content_type, evidence_type) + + +def init_data_processor(signal_model: SignalModel) -> RawDataProcessor: + """Find an DataProcessor that matches the given signal_model and + initialize it.""" + processor_class = find_data_processor(signal_model) + return processor_class(signal_model) diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 7539fdcff..71675e835 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -22,13 +22,13 @@ def get_evidence_type(model: SignalModel) -> EvidenceType: return model.metadata.evidence_type or DEFAULT_EVIDENCE_TYPE -class SimulatorCopyPhraseTask(RSVPCopyPhraseTask): - """CopyPhraseTask that simulates user interactions by sampling data - from a DataSampler.""" +class SimTask(RSVPCopyPhraseTask): + """"Task used for simulation. API differs from a regular task in its use of + data samplers.""" def __init__(self, parameters: Parameters, file_save: str, signal_models: List[SignalModel], - language_model: LanguageModel, sampler: Sampler): + language_model: LanguageModel, samplers: List[Sampler]): super().__init__(win=None, daq=None, parameters=parameters, @@ -37,10 +37,12 @@ def __init__(self, parameters: Parameters, file_save: str, language_model=language_model, fake=False) self.save_session_every_inquiry = False - # TODO: support multi-modal by including a sampler for every model - # TODO: easily swap out samplers (parameter -> list of samplers, one for each mode/evidence type) - # maybe accept a List[Tuple[SignalModel, Sampler]] - self.sampler = sampler + self.samplers = samplers + + +class SimulatorCopyPhraseTask(SimTask): + """CopyPhraseTask that simulates user interactions by sampling data + from a DataSampler.""" def init_evidence_evaluators( self, signal_models: List[SignalModel]) -> List[EvidenceEvaluator]: @@ -92,7 +94,7 @@ def compute_device_evidence( self.logger.info(self.get_sim_state()) # sampled_trial = self.sampler.sample_trial(self.get_sim_state()) - sampled_data = self.sampler.sample_data(self.get_sim_state()) + sampled_data = self.samplers[0].sample_data(self.get_sim_state()) # trial_info = (datasource, inquiry_n) # eye_gaze_data = self.sampler['EYE'].sample(self.get_sim_state(), trial_info) diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index 18ec00728..97c02ae78 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -5,17 +5,16 @@ import os from glob import glob from pathlib import Path -from typing import List, Optional +from typing import List, Type from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import load_json_parameters, load_signal_models from bcipy.signal.model.base_model import SignalModel from bcipy.simulator.helpers import artifact from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.data_process import EegRawDataProcessor +from bcipy.simulator.helpers.data_process import init_data_processor from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler -from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask -from bcipy.task.main import Task +from bcipy.simulator.task.copy_phrase import SimTask, SimulatorCopyPhraseTask logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) @@ -33,31 +32,21 @@ def configure_run_directory(sim_dir: str, run: int) -> str: return path -class TaskRunner(): - """Responsible for executing a task a given number of times.""" +class TaskFactory(): + """Constructs the hierarchy of objects necessary for initializing a task.""" def __init__(self, - model_path: str, params_path: str, + model_path: str, source_dirs: List[str], - save_dir: str, - runs: int = 1): - self.model_path = model_path + sampling_strategy: Type[Sampler] = EEGByLetterSampler, + task: Type[SimTask] = SimulatorCopyPhraseTask): self.params_path = params_path + self.model_path = model_path self.source_dirs = source_dirs - self.sim_dir = save_dir - self.runs = runs - - self.sampling_strategy = EEGByLetterSampler - self.simulation_task = SimulatorCopyPhraseTask - - self.parameters = None - self.signal_models: List[SignalModel] = [] - self.language_model = None - self.sampler: Optional[Sampler] = None + self.sampling_strategy = sampling_strategy + self.simulation_task = task - def setup(self) -> None: - """Setup the task objects""" logger.info("Loading parameters") self.parameters = load_json_parameters(self.params_path, value_cast=True) @@ -70,38 +59,51 @@ def setup(self) -> None: self.language_model = init_language_model(self.parameters) logger.debug(self.language_model) - logger.info("Creating data engine") - # TODO: initialize a data engine and sampler for each model - data_processor = EegRawDataProcessor(self.signal_models[0]) - data_engine = RawDataEngine(list(map(str, self.source_dirs)), - self.parameters, data_processor) - self.sampler = self.sampling_strategy(data_engine) - logger.debug("Using sampler:") - logger.debug(self.sampler) - - def setup_complete(self) -> bool: - """Determines if the runner has been setup correctly.""" - return all([ - self.parameters is not None, - len(self.signal_models) > 0, self.language_model is not None, - self.sampler is not None - ]) - - def make_task(self, run_dir) -> Task: - """Create the task. This is done for every run.""" - assert self.sampler, "Sampler must be initialized" + self.samplers = self.init_samplers(self.signal_models) + logger.debug(self.samplers) + + def init_samplers(self, signal_models: List[SignalModel]) -> List[Sampler]: + """Initializes the evidence evaluators from the provided signal models. + + Returns a list of evaluators for active devices. Raises an exception if + more than one evaluator provides the same type of evidence. + """ + + samplers = [] + for model in signal_models: + processor = init_data_processor(model) + logger.info(f"Creating data engine for {model}") + engine = RawDataEngine(list(map(str, self.source_dirs)), + self.parameters, + data_processor=processor) + sampler = self.sampling_strategy(engine) + samplers.append(sampler) + return samplers + + def make_task(self, run_dir: str) -> SimTask: + """Construct a new task""" return self.simulation_task(self.parameters, file_save=run_dir, signal_models=self.signal_models, language_model=self.language_model, - sampler=self.sampler) + samplers=self.samplers) + + +class TaskRunner(): + """Responsible for executing a task a given number of times.""" + + def __init__(self, + save_dir: str, + task_factory: TaskFactory, + runs: int = 1): + + self.task_factory = task_factory + self.sim_dir = save_dir + self.runs = runs def run(self): """Run one or more simulations""" - if not self.setup_complete(): - self.setup() - assert self.parameters, "Parameters is not initialized" - self.parameters.save(self.sim_dir) + self.task_factory.parameters.save(self.sim_dir) for i in range(self.runs): logger.info(f"Executing task {i+1}") self.do_run(i + 1) @@ -111,7 +113,7 @@ def do_run(self, run: int): """Execute a simulation run.""" run_dir = configure_run_directory(self.sim_dir, run) logger.info(run_dir) - task = self.make_task(run_dir) + task = self.task_factory.make_task(run_dir) task.execute() @@ -151,10 +153,13 @@ def main(): sim_dir = artifact.init_simulation_dir() logger.info(sim_dir) - runner = TaskRunner(model_path=sim_args['model_path'], - params_path=sim_args['parameters'], - source_dirs=sim_args['source_dirs'], - save_dir=sim_dir, + task_factory = TaskFactory(params_path=sim_args['parameters'], + model_path=sim_args['model_path'], + source_dirs=sim_args['source_dirs'], + sampling_strategy=EEGByLetterSampler, + task=SimulatorCopyPhraseTask) + runner = TaskRunner(save_dir=sim_dir, + task_factory=task_factory, runs=sim_args['n']) runner.run() From 0887d8ceef2c8556a3325dd73db7e23e9cc2f4c8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 3 Sep 2024 17:04:10 -0700 Subject: [PATCH 293/330] Refactored TaskFactory into its own module. Cleaned up types and documentation. --- bcipy/simulator/helpers/data_engine.py | 21 +++++--- bcipy/simulator/helpers/data_process.py | 1 + bcipy/simulator/task/copy_phrase.py | 1 + bcipy/simulator/task/task_factory.py | 70 +++++++++++++++++++++++++ bcipy/simulator/task/task_runner.py | 68 ++---------------------- 5 files changed, 89 insertions(+), 72 deletions(-) create mode 100644 bcipy/simulator/task/task_factory.py diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 1935b9c73..a09978959 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,12 +1,13 @@ import logging from abc import ABC, abstractmethod from pathlib import Path -from typing import List, NamedTuple, Optional +from typing import List, NamedTuple, Optional, Union import numpy as np import pandas as pd from bcipy.helpers.parameters import Parameters +from bcipy.simulator.helpers import data_process from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME from bcipy.simulator.helpers.signal_helpers import (EegRawDataProcessor, ExtractedExperimentData, @@ -70,15 +71,18 @@ class RawDataEngine(DataEngine): Object that loads in list of session data folders and transforms data into sample-able DataFrame """ - def __init__(self, - source_dirs: List[str], - parameters: Parameters, - data_processor: Optional[RawDataProcessor] = None): + def __init__( + self, + source_dirs: List[str], + parameters: Parameters, + data_processor: Optional[Union[RawDataProcessor, + data_process.RawDataProcessor]] = None): self.source_dirs: List[str] = source_dirs self.parameters: Parameters = parameters self.data_processor = data_processor or EegRawDataProcessor() - self.data: List[ExtractedExperimentData] = [] + self.data: List[Union[ExtractedExperimentData, + data_process.ExtractedExperimentData]] = [] self.schema: Optional[pd.DataFrame] = None self.load() @@ -122,7 +126,10 @@ def transform(self) -> DataEngine: self.schema = pd.DataFrame(rows) return self - def trials(self, data_source: ExtractedExperimentData) -> List[Trial]: + def trials( + self, data_source: Union[ExtractedExperimentData, + data_process.ExtractedExperimentData] + ) -> List[Trial]: """Convert extracted data from a single data source to a list of Trials.""" trials = [] symbols_by_inquiry = data_source.symbols_by_inquiry diff --git a/bcipy/simulator/helpers/data_process.py b/bcipy/simulator/helpers/data_process.py index ec4611375..a45c8f29c 100644 --- a/bcipy/simulator/helpers/data_process.py +++ b/bcipy/simulator/helpers/data_process.py @@ -81,6 +81,7 @@ class DecodedTriggers(NamedTuple): @dataclass() class ExtractedExperimentData: + """Data from an acquisition device after reshaping and filtering.""" source_dir: str inquiries: np.ndarray trials: np.ndarray diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 71675e835..8b3321e5a 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -132,6 +132,7 @@ def get_sim_state(self) -> SimState: def current_symbols(self) -> List[str]: """Get the list of symbols from the current inquiry.""" + assert self.current_inquiry, "current inquiry not initialized." schedule = self.current_inquiry stimuli = schedule.stimuli[0] _fixation, *symbols = stimuli diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py new file mode 100644 index 000000000..ddf95fcf3 --- /dev/null +++ b/bcipy/simulator/task/task_factory.py @@ -0,0 +1,70 @@ +import logging +from typing import List, Type + +from bcipy.helpers.language_model import init_language_model +from bcipy.helpers.load import load_json_parameters, load_signal_models +from bcipy.signal.model.base_model import SignalModel +from bcipy.simulator.helpers import artifact +from bcipy.simulator.helpers.data_engine import RawDataEngine +from bcipy.simulator.helpers.data_process import init_data_processor +from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler +from bcipy.simulator.task.copy_phrase import SimTask, SimulatorCopyPhraseTask + +logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) + + +class TaskFactory(): + """Constructs the hierarchy of objects necessary for initializing a task.""" + + def __init__(self, + params_path: str, + model_path: str, + source_dirs: List[str], + sampling_strategy: Type[Sampler] = EEGByLetterSampler, + task: Type[SimTask] = SimulatorCopyPhraseTask): + self.params_path = params_path + self.model_path = model_path + self.source_dirs = source_dirs + self.sampling_strategy = sampling_strategy + self.simulation_task = task + + logger.info("Loading parameters") + self.parameters = load_json_parameters(self.params_path, + value_cast=True) + + logger.info("Loading signal models") + self.signal_models = load_signal_models(directory=self.model_path) + logger.debug(self.signal_models) + + logger.info("Initializing language model") + self.language_model = init_language_model(self.parameters) + logger.debug(self.language_model) + + self.samplers = self.init_samplers(self.signal_models) + logger.debug(self.samplers) + + def init_samplers(self, signal_models: List[SignalModel]) -> List[Sampler]: + """Initializes the evidence evaluators from the provided signal models. + + Returns a list of evaluators for active devices. Raises an exception if + more than one evaluator provides the same type of evidence. + """ + + samplers = [] + for model in signal_models: + processor = init_data_processor(model) + logger.info(f"Creating data engine for {model}") + engine = RawDataEngine(list(map(str, self.source_dirs)), + self.parameters, + data_processor=processor) + sampler = self.sampling_strategy(engine) + samplers.append(sampler) + return samplers + + def make_task(self, run_dir: str) -> SimTask: + """Construct a new task""" + return self.simulation_task(self.parameters, + file_save=run_dir, + signal_models=self.signal_models, + language_model=self.language_model, + samplers=self.samplers) diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index 97c02ae78..b50c87ba0 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -5,16 +5,11 @@ import os from glob import glob from pathlib import Path -from typing import List, Type -from bcipy.helpers.language_model import init_language_model -from bcipy.helpers.load import load_json_parameters, load_signal_models -from bcipy.signal.model.base_model import SignalModel from bcipy.simulator.helpers import artifact -from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.data_process import init_data_processor -from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler -from bcipy.simulator.task.copy_phrase import SimTask, SimulatorCopyPhraseTask +from bcipy.simulator.helpers.sampler import EEGByLetterSampler +from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask +from bcipy.simulator.task.task_factory import TaskFactory logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) @@ -32,63 +27,6 @@ def configure_run_directory(sim_dir: str, run: int) -> str: return path -class TaskFactory(): - """Constructs the hierarchy of objects necessary for initializing a task.""" - - def __init__(self, - params_path: str, - model_path: str, - source_dirs: List[str], - sampling_strategy: Type[Sampler] = EEGByLetterSampler, - task: Type[SimTask] = SimulatorCopyPhraseTask): - self.params_path = params_path - self.model_path = model_path - self.source_dirs = source_dirs - self.sampling_strategy = sampling_strategy - self.simulation_task = task - - logger.info("Loading parameters") - self.parameters = load_json_parameters(self.params_path, - value_cast=True) - - logger.info("Loading signal models") - self.signal_models = load_signal_models(directory=self.model_path) - logger.debug(self.signal_models) - - logger.info("Initializing language model") - self.language_model = init_language_model(self.parameters) - logger.debug(self.language_model) - - self.samplers = self.init_samplers(self.signal_models) - logger.debug(self.samplers) - - def init_samplers(self, signal_models: List[SignalModel]) -> List[Sampler]: - """Initializes the evidence evaluators from the provided signal models. - - Returns a list of evaluators for active devices. Raises an exception if - more than one evaluator provides the same type of evidence. - """ - - samplers = [] - for model in signal_models: - processor = init_data_processor(model) - logger.info(f"Creating data engine for {model}") - engine = RawDataEngine(list(map(str, self.source_dirs)), - self.parameters, - data_processor=processor) - sampler = self.sampling_strategy(engine) - samplers.append(sampler) - return samplers - - def make_task(self, run_dir: str) -> SimTask: - """Construct a new task""" - return self.simulation_task(self.parameters, - file_save=run_dir, - signal_models=self.signal_models, - language_model=self.language_model, - samplers=self.samplers) - - class TaskRunner(): """Responsible for executing a task a given number of times.""" From 9ee8237dda2589c967d8b1f4fd8a7681f103c5fb Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 10 Sep 2024 17:40:44 -0700 Subject: [PATCH 294/330] Refactored DataEngine process for loading and transforming data. Provided DataEngine with a query interface to allow the engine to abstract out the details about how the data is stored. Added a mechanism to the Copy Phrase simulation Task to match SignalModels to Samplers and used this in the compute_device_evidence method to support gathering evidence from multiple sources. --- bcipy/simulator/helpers/data_engine.py | 194 ++++++++++++++-------- bcipy/simulator/helpers/sampler.py | 35 ++-- bcipy/simulator/sim.py | 11 +- bcipy/simulator/sim_factory.py | 4 +- bcipy/simulator/task/copy_phrase.py | 32 ++-- bcipy/simulator/task/task_factory.py | 13 +- bcipy/simulator/task/task_runner.py | 4 +- bcipy/simulator/tests/test_data_engine.py | 7 +- 8 files changed, 173 insertions(+), 127 deletions(-) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index a09978959..95c0e807c 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,11 +1,12 @@ import logging from abc import ABC, abstractmethod from pathlib import Path -from typing import List, NamedTuple, Optional, Union +from typing import Any, List, NamedTuple, Optional, Union import numpy as np import pandas as pd +from bcipy.helpers.exceptions import TaskConfigurationException from bcipy.helpers.parameters import Parameters from bcipy.simulator.helpers import data_process from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME @@ -16,22 +17,6 @@ log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) -class DataEngine(ABC): - - def load(self): - ... - - def transform(self): - ... - - def get_data(self): - ... - - @abstractmethod - def get_parameters(self) -> List[Parameters]: - ... - - class Trial(NamedTuple): """Data for a given trial (a symbol within an Inquiry). @@ -52,7 +37,7 @@ class Trial(NamedTuple): inquiry_pos: int symbol: str target: int - eeg: np.ndarray # Channels by Samples + eeg: np.ndarray # Channels by Samples ; ndarray.shape = (channel_n, sample_n) def __str__(self): fields = [ @@ -66,9 +51,75 @@ def __repr__(self): return str(self) +class QueryFilter(NamedTuple): + """Used to query for data.""" + field: str + operator: str + value: Any + + def is_valid(self) -> bool: + """Check if the filter is valid.""" + # pylint: disable=no-member + return self.field in Trial._fields and self.operator in self.valid_operators and isinstance( + self.value, Trial.__annotations__[self.field]) + + @property + def valid_operators(self) -> List[str]: + """List of supported query operators""" + return ["<", "<=", ">", ">=", "==", "!="] + + +class DataEngine(ABC): + """Abstract class for an object that loads data from one or more sources, + processes the data using a provided processor, and provides an interface + for querying the processed data.""" + + def load(self): + """Load data from sources.""" + + @property + def trials_df(self) -> pd.DataFrame: + """Returns a dataframe of Trial data.""" + + @abstractmethod + def query(self, + filters: List[QueryFilter], + samples: int = 1) -> List[Trial]: + """Query the data.""" + + +def convert_trials( + data_source: Union[ExtractedExperimentData, + data_process.ExtractedExperimentData] +) -> List[Trial]: + """Convert extracted data from a single data source to a list of Trials.""" + trials = [] + symbols_by_inquiry = data_source.symbols_by_inquiry + labels_by_inquiry = data_source.labels_by_inquiry + + for i, inquiry_eeg in enumerate(data_source.trials_by_inquiry): + # iterate through each inquiry + inquiry_symbols = symbols_by_inquiry[i] + inquiry_labels = labels_by_inquiry[i] + + for sym_i, symbol in enumerate(inquiry_symbols): + # iterate through each symbol in the inquiry + eeg_samples = [channel[sym_i] + for channel in inquiry_eeg] # (channel_n, sample_n) + trials.append( + Trial(source=data_source.source_dir, + inquiry_n=i, + inquiry_pos=sym_i + 1, + symbol=symbol, + target=inquiry_labels[sym_i], + eeg=np.array(eeg_samples))) + return trials + + class RawDataEngine(DataEngine): """ - Object that loads in list of session data folders and transforms data into sample-able DataFrame + Object that loads in list of session data folders and transforms data into + a queryable data structure. """ def __init__( @@ -83,7 +134,7 @@ def __init__( self.data_processor = data_processor or EegRawDataProcessor() self.data: List[Union[ExtractedExperimentData, data_process.ExtractedExperimentData]] = [] - self.schema: Optional[pd.DataFrame] = None + self._trials_df = pd.DataFrame() self.load() @@ -99,65 +150,64 @@ def load(self) -> DataEngine: log.debug( f"Loading data from {len(self.source_dirs)} source directories:" ) + rows = [] for i, source_dir in enumerate(self.source_dirs): log.debug(f"{i+1}. {Path(source_dir).name}") - self.data.append( - self.data_processor.process(source_dir, self.parameters)) + extracted_data = self.data_processor.process( + source_dir, self.parameters) + self.data.append(extracted_data) + rows.extend(convert_trials(extracted_data)) + self._trials_df = pd.DataFrame(rows) log.debug("Finished loading all data") return self - def transform(self) -> DataEngine: - """ - Organizes all data into the following schema - - Dataframe {"inquiry_n":int, "trial_n":int, "symbol":str, "target":int, "eeg":ndarray} - - The "eeg" data for trial looks like this - - ndarray.shape = (channel_n, sample_n) - - a trial is an eeg response for a symbol being displayed - - Returns: - self for chaining + @property + def trials_df(self) -> pd.DataFrame: + """Dataframe of Trial data.""" + if not self.data_loaded: + self.load() + return self._trials_df.copy() + + @property + def data_loaded(self) -> bool: + """Check if the data has been loaded""" + return bool(self.data) + + def query(self, + filters: List[QueryFilter], + samples: int = 1) -> List[Trial]: + """Query the engine for data using one or more filters. + + Parameters + ---------- + filters - list of query filters + samples - number of results to return. + check_insufficient_results - if True, raises an exception when + there are an insufficient number of samples. + + Returns a list of Trials. """ - rows = [] - for data_source in self.data: - rows.extend(self.trials(data_source)) - - self.schema = pd.DataFrame(rows) - return self - - def trials( - self, data_source: Union[ExtractedExperimentData, - data_process.ExtractedExperimentData] - ) -> List[Trial]: - """Convert extracted data from a single data source to a list of Trials.""" - trials = [] - symbols_by_inquiry = data_source.symbols_by_inquiry - labels_by_inquiry = data_source.labels_by_inquiry - - for i, inquiry_eeg in enumerate(data_source.trials_by_inquiry): - # iterate through each inquiry - inquiry_symbols = symbols_by_inquiry[i] - inquiry_labels = labels_by_inquiry[i] - - for sym_i, symbol in enumerate(inquiry_symbols): - # iterate through each symbol in the inquiry - eeg_samples = [channel[sym_i] for channel in inquiry_eeg - ] # (channel_n, sample_n) - trials.append( - Trial(source=data_source.source_dir, - inquiry_n=i, - inquiry_pos=sym_i + 1, - symbol=symbol, - target=inquiry_labels[sym_i], - eeg=np.array(eeg_samples))) - return trials - - def get_data(self): - return self.schema.copy() if self.schema is not None else None - - def get_parameters(self): - return self.parameters + assert self.data_loaded, "Data must be loaded before querying." + assert all(filt.is_valid() + for filt in filters), "Filters must all be valid" + assert samples >= 1, "Insufficient number of samples requested" + + expr = 'and '.join([self.query_condition(filt) for filt in filters]) + filtered_data = self._trials_df.query(expr) + if filtered_data is None or len(filtered_data) < samples: + raise TaskConfigurationException( + message="Not enough samples found") + + rows = filtered_data.sample(samples) + return [Trial(*row) for row in rows.itertuples(index=False, name=None)] + + def query_condition(self, query_filter: QueryFilter) -> str: + """Returns the string representation of of the given query condition.""" + value = query_filter.value + if (isinstance(value, str)): + value = f"'{value}'" + return f"{query_filter.field} {query_filter.operator} {value}" class RawDataEngineWrapper(RawDataEngine): diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index cd2b0441a..3ec40d606 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -8,8 +8,8 @@ import numpy as np import pandas as pd -from bcipy.helpers.exceptions import TaskConfigurationException -from bcipy.simulator.helpers.data_engine import RawDataEngine, Trial +from bcipy.simulator.helpers.data_engine import (QueryFilter, RawDataEngine, + Trial) from bcipy.simulator.helpers.log_utils import format_samples from bcipy.simulator.helpers.state_manager import SimState @@ -42,7 +42,6 @@ class Sampler(ABC): def __init__(self, data_engine: RawDataEngine): self.data_engine: RawDataEngine = data_engine self.model_input_reshaper: Callable = default_reshaper - self.data: pd.DataFrame = self.data_engine.transform().get_data() def sample(self, state: SimState) -> List[Trial]: """ @@ -94,28 +93,25 @@ def __str__(self): return f"<{self.__class__.__name__}>" -class EEGByLetterSampler(Sampler): +class TargetNontargetSampler(Sampler): """Sampler that that queries based on target/non-target label.""" def sample(self, state: SimState) -> List[Trial]: - current_stimuli = state.display_alphabet - target_letter = state.target_symbol sample_rows = [] - for symbol in current_stimuli: - is_target = int(symbol == target_letter) - # filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') - filtered_data: pd.DataFrame = self.data.query( - f'target == {is_target}') - if filtered_data is None or len(filtered_data) == 0: - raise TaskConfigurationException( - message="No eeg sample found with provided data and query") - - row = filtered_data.sample(1).iloc[0] - sample_rows.append(Trial(**row)) - - log.debug(f"EEG Samples:\n{format_samples(sample_rows)}") + for symbol in state.display_alphabet: + filters = self.query_filters( + symbol, is_target=(symbol == state.target_symbol)) + filtered_data = self.data_engine.query(filters, samples=1) + sample_rows.append(filtered_data[0]) + + log.debug(f"Samples:\n{format_samples(sample_rows)}") return sample_rows + def query_filters(self, symbol: str, is_target: bool) -> List[QueryFilter]: + """Expression used to query for a single sample.""" + # QueryFilter('symbol', '==', symbol) + return [QueryFilter('target', '==', int(is_target))] + class InquirySampler(Sampler): """Samples an inquiry of data at a time.""" @@ -124,6 +120,7 @@ def __init__(self, data_engine: RawDataEngine): super().__init__(data_engine) # map source to inquiry numbers + self.data = self.data_engine.trials_df self.target_inquiries, self.no_target_inquiries = self.prepare_data( self.data) diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 821b94121..8656301b4 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -50,7 +50,7 @@ class SimulatorCopyPhrase(Simulator): """ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, parameters: Optional[Parameters] = None, + state_manager: StateManager, referee: MetricReferee, parameters: Parameters, save_dir: Optional[str] = None): super().__init__() @@ -61,7 +61,7 @@ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler self.state_manager = state_manager self.data_engine = data_engine - self.parameters = self.load_parameters(parameters) + self.parameters = parameters self.symbol_set = alphabet() self.write_output = False @@ -162,13 +162,6 @@ def __reshape_evidences(self, evidences: Dict[str, SimEvidence]) -> Dict[str, Si return reshaped_evidence - def load_parameters(self, params: Optional[Parameters]): - # TODO validate parameters - if params: - return params - else: - return self.data_engine.get_parameters() - def new_data_record(self, inquiry_state: SimState, inquiry_result: InquiryResult) -> Inquiry: """Construct a new inquiry data record. diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index aad05f868..25f04a218 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -8,7 +8,7 @@ from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.metrics import RefereeImpl, SimMetricsHandler from bcipy.simulator.helpers.model_handler import SigLmModelHandler1 -from bcipy.simulator.helpers.sampler import EEGByLetterSampler +from bcipy.simulator.helpers.sampler import TargetNontargetSampler from bcipy.simulator.helpers.state_manager import StateManagerImpl from bcipy.simulator.sim import Simulator, SimulatorCopyPhrase @@ -37,7 +37,7 @@ def create(source_dirs: List[Path], data_engine = RawDataEngine(list(map(str, source_dirs)), base_parameters) state_manager = StateManagerImpl(base_parameters) - sampler = EEGByLetterSampler(data_engine) + sampler = TargetNontargetSampler(data_engine) model_handler = SigLmModelHandler1(model_file, base_parameters) referee = RefereeImpl(metric_handlers={'basic': SimMetricsHandler()}) diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 8b3321e5a..47e593e83 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -1,5 +1,5 @@ """Simulates the Copy Phrase task""" -from typing import List, Optional, Tuple +from typing import Dict, List, Optional, Tuple from bcipy.display.main import Display from bcipy.feedback.visual.visual_feedback import VisualFeedback @@ -28,7 +28,8 @@ class SimTask(RSVPCopyPhraseTask): def __init__(self, parameters: Parameters, file_save: str, signal_models: List[SignalModel], - language_model: LanguageModel, samplers: List[Sampler]): + language_model: LanguageModel, samplers: Dict[SignalModel, + Sampler]): super().__init__(win=None, daq=None, parameters=parameters, @@ -89,18 +90,23 @@ def compute_device_evidence( self, stim_times: List[List], proceed: bool = True) -> List[Tuple[EvidenceType, List[float]]]: - # TODO: sample for each evidence type - self.logger.info("Computing evidence with sim_state:") - self.logger.info(self.get_sim_state()) - - # sampled_trial = self.sampler.sample_trial(self.get_sim_state()) - sampled_data = self.samplers[0].sample_data(self.get_sim_state()) - # trial_info = (datasource, inquiry_n) - # eye_gaze_data = self.sampler['EYE'].sample(self.get_sim_state(), trial_info) - evidence = self.signal_model.predict(sampled_data, - self.current_symbols(), self.alp) - return [(EvidenceType.ERP, evidence)] + current_state = self.get_sim_state() + self.logger.info("Computing evidence with sim_state:") + self.logger.info(current_state) + + evidences = [] + + for model in self.signal_models: + sampler = self.samplers[model] + # is sampling independent or do we need to provide the trial context of the last sample? + # TODO: if so, we need another sampler API method for sample_trials(current_state, trial_info) + sampled_data = sampler.sample_data(current_state) + evidence = model.predict(sampled_data, self.current_symbols(), + self.alp) + evidence_type = model.metadata.evidence_type or EvidenceType.ERP + evidences.append((evidence_type, evidence)) + return evidences def exit_display(self) -> None: """Close the UI and cleanup.""" diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py index ddf95fcf3..92c898d5e 100644 --- a/bcipy/simulator/task/task_factory.py +++ b/bcipy/simulator/task/task_factory.py @@ -1,5 +1,5 @@ import logging -from typing import List, Type +from typing import Dict, List, Type from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import load_json_parameters, load_signal_models @@ -7,7 +7,7 @@ from bcipy.simulator.helpers import artifact from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.data_process import init_data_processor -from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler +from bcipy.simulator.helpers.sampler import Sampler, TargetNontargetSampler from bcipy.simulator.task.copy_phrase import SimTask, SimulatorCopyPhraseTask logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) @@ -16,11 +16,12 @@ class TaskFactory(): """Constructs the hierarchy of objects necessary for initializing a task.""" + # TODO: sampling strategy per model type def __init__(self, params_path: str, model_path: str, source_dirs: List[str], - sampling_strategy: Type[Sampler] = EEGByLetterSampler, + sampling_strategy: Type[Sampler] = TargetNontargetSampler, task: Type[SimTask] = SimulatorCopyPhraseTask): self.params_path = params_path self.model_path = model_path @@ -43,14 +44,14 @@ def __init__(self, self.samplers = self.init_samplers(self.signal_models) logger.debug(self.samplers) - def init_samplers(self, signal_models: List[SignalModel]) -> List[Sampler]: + def init_samplers(self, signal_models: List[SignalModel]) -> Dict[SignalModel, Sampler]: """Initializes the evidence evaluators from the provided signal models. Returns a list of evaluators for active devices. Raises an exception if more than one evaluator provides the same type of evidence. """ - samplers = [] + samplers = {} for model in signal_models: processor = init_data_processor(model) logger.info(f"Creating data engine for {model}") @@ -58,7 +59,7 @@ def init_samplers(self, signal_models: List[SignalModel]) -> List[Sampler]: self.parameters, data_processor=processor) sampler = self.sampling_strategy(engine) - samplers.append(sampler) + samplers[model] = sampler return samplers def make_task(self, run_dir: str) -> SimTask: diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index b50c87ba0..d8e9d7144 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -7,7 +7,7 @@ from pathlib import Path from bcipy.simulator.helpers import artifact -from bcipy.simulator.helpers.sampler import EEGByLetterSampler +from bcipy.simulator.helpers.sampler import TargetNontargetSampler from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask from bcipy.simulator.task.task_factory import TaskFactory @@ -94,7 +94,7 @@ def main(): task_factory = TaskFactory(params_path=sim_args['parameters'], model_path=sim_args['model_path'], source_dirs=sim_args['source_dirs'], - sampling_strategy=EEGByLetterSampler, + sampling_strategy=TargetNontargetSampler, task=SimulatorCopyPhraseTask) runner = TaskRunner(save_dir=sim_dir, task_factory=task_factory, diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py index 932e7b9cb..8abab6642 100644 --- a/bcipy/simulator/tests/test_data_engine.py +++ b/bcipy/simulator/tests/test_data_engine.py @@ -23,8 +23,8 @@ def test_init(self): data_engine = RawDataEngine(source_dirs=[], parameters=self.parameters, data_processor=self.data_processor) - self.assertFalse(data_engine.get_data()) - self.assertEqual(self.parameters, data_engine.get_parameters()) + + self.assertEqual(self.parameters, data_engine.parameters) def test_single_data_source(self): """Test loading data from a single directory.""" @@ -70,8 +70,7 @@ def test_transform(self): engine = RawDataEngine(source_dirs=['data-dir1'], parameters=self.parameters, data_processor=self.data_processor) - engine.transform() - data = engine.get_data() + data = engine.trials_df self.assertEqual(10, len(data)) From 7066c359166e3a67221fe0759b93e12908a52005 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 11 Sep 2024 16:00:35 -0700 Subject: [PATCH 295/330] Sim task cleanup --- bcipy/simulator/task/copy_phrase.py | 28 ++++++++++++++++++---------- 1 file changed, 18 insertions(+), 10 deletions(-) diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 47e593e83..a35288b56 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -22,9 +22,22 @@ def get_evidence_type(model: SignalModel) -> EvidenceType: return model.metadata.evidence_type or DEFAULT_EVIDENCE_TYPE -class SimTask(RSVPCopyPhraseTask): - """"Task used for simulation. API differs from a regular task in its use of - data samplers.""" +class SimTask(): + """Abstract class that marks a task as a simulation.""" + def __init__(self, parameters: Parameters, file_save: str, + signal_models: List[SignalModel], + language_model: LanguageModel, samplers: Dict[SignalModel, + Sampler]): + """Signature for a simulation task""" + + def execute(self) -> str: + """Executes the task""" + raise NotImplementedError + + +class SimulatorCopyPhraseTask(RSVPCopyPhraseTask, SimTask): + """CopyPhraseTask that simulates user interactions by sampling data + from a DataSampler.""" def __init__(self, parameters: Parameters, file_save: str, signal_models: List[SignalModel], @@ -40,11 +53,6 @@ def __init__(self, parameters: Parameters, file_save: str, self.save_session_every_inquiry = False self.samplers = samplers - -class SimulatorCopyPhraseTask(SimTask): - """CopyPhraseTask that simulates user interactions by sampling data - from a DataSampler.""" - def init_evidence_evaluators( self, signal_models: List[SignalModel]) -> List[EvidenceEvaluator]: # Evidence will be sampled so we don't need to evaluate raw data. @@ -99,8 +107,8 @@ def compute_device_evidence( for model in self.signal_models: sampler = self.samplers[model] - # is sampling independent or do we need to provide the trial context of the last sample? - # TODO: if so, we need another sampler API method for sample_trials(current_state, trial_info) + # This assumes that sampling is independent. Changes to the sampler API are needed if + # we need to provide the trial context of the last sample. sampled_data = sampler.sample_data(current_state) evidence = model.predict(sampled_data, self.current_symbols(), self.alp) From bd45e48e7a884b413a38bbbdf766f54027a69313 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 11 Sep 2024 16:54:47 -0700 Subject: [PATCH 296/330] Fixed unit tests and linting errors --- bcipy/simulator/task/copy_phrase.py | 2 +- bcipy/simulator/tests/test_data_engine.py | 47 +++++++++++++---------- 2 files changed, 27 insertions(+), 22 deletions(-) diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index a35288b56..634262a8c 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -107,7 +107,7 @@ def compute_device_evidence( for model in self.signal_models: sampler = self.samplers[model] - # This assumes that sampling is independent. Changes to the sampler API are needed if + # This assumes that sampling is independent. Changes to the sampler API are needed if # we need to provide the trial context of the last sample. sampled_data = sampler.sample_data(current_state) evidence = model.predict(sampled_data, self.current_symbols(), diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py index 8abab6642..ada6bb0ee 100644 --- a/bcipy/simulator/tests/test_data_engine.py +++ b/bcipy/simulator/tests/test_data_engine.py @@ -4,8 +4,29 @@ import numpy as np -from bcipy.simulator.helpers.data_engine import (ExtractedExperimentData, - RawDataEngine) +from bcipy.simulator.helpers.data_engine import RawDataEngine +from bcipy.simulator.helpers.data_process import (DecodedTriggers, + ExtractedExperimentData) + + +def mock_data() -> ExtractedExperimentData: + times = [ + 9.730993399999988, 9.966709099999662, 10.201713299999938, + 10.436247999999978, 10.672083899999961, 10.90684519999968, + 11.141479799999615, 11.377909999999702, 11.614850199999637, + 11.849502299999585 + ] + return ExtractedExperimentData( + source_dir=Path('data-dir1'), + inquiries=np.zeros((7, 1, 692)), + trials=np.zeros((7, 10, 74)), + labels=np.array([[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]]), + inquiry_timing=[[150, 185, 220, 255, 291, 326, 361, 397, 432, 467]], + decoded_triggers=DecodedTriggers([ + 'nontarget', 'nontarget', 'nontarget', 'nontarget', 'nontarget', + 'target', 'nontarget', 'nontarget', 'nontarget', 'nontarget' + ], times, ['G', 'C', 'D', 'B', 'I', 'A', 'H', '<', 'E', 'F'], times), + trials_per_inquiry=10) class TestRawDataEngine(unittest.TestCase): @@ -28,6 +49,7 @@ def test_init(self): def test_single_data_source(self): """Test loading data from a single directory.""" + self.data_processor.process = Mock(return_value=mock_data()) RawDataEngine(source_dirs=['data-dir1'], parameters=self.parameters, data_processor=self.data_processor) @@ -36,6 +58,7 @@ def test_single_data_source(self): def test_multiple_sources(self): """Test loading data from multiple directories.""" + self.data_processor.process = Mock(return_value=mock_data()) RawDataEngine(source_dirs=['data-dir1', 'data-dir2', 'data-dir3'], parameters=self.parameters, data_processor=self.data_processor) @@ -48,25 +71,7 @@ def test_transform(self): """Test the data transformation method""" # Setup context # mock the experiment data; single inquiry - mock_data = ExtractedExperimentData( - source_dir=Path('data-dir1'), - inquiries=np.zeros((7, 1, 692)), - trials=np.zeros((7, 10, 74)), - labels=np.array([[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]]), - inquiry_timing=[[150, 185, 220, 255, 291, 326, 361, 397, 432, - 467]], - decoded_triggers=([ - 'nontarget', 'nontarget', 'nontarget', 'nontarget', - 'nontarget', 'target', 'nontarget', 'nontarget', 'nontarget', - 'nontarget' - ], [ - 9.730993399999988, 9.966709099999662, 10.201713299999938, - 10.436247999999978, 10.672083899999961, 10.90684519999968, - 11.141479799999615, 11.377909999999702, 11.614850199999637, - 11.849502299999585 - ], ['G', 'C', 'D', 'B', 'I', 'A', 'H', '<', 'E', 'F']), - trials_per_inquiry=10) - self.data_processor.process = Mock(return_value=mock_data) + self.data_processor.process = Mock(return_value=mock_data()) engine = RawDataEngine(source_dirs=['data-dir1'], parameters=self.parameters, data_processor=self.data_processor) From 2d2ba564e1d8f28854920e54b92f1c02e1fa6a0b Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Mon, 16 Sep 2024 13:52:10 -0400 Subject: [PATCH 297/330] Surface btn error probability (#347) surface btn error probability --- bcipy/parameters/parameters.json | 8 ++++++++ bcipy/task/paradigm/rsvp/copy_phrase.py | 4 ++-- bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py | 1 + 3 files changed, 11 insertions(+), 2 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 36c088342..e8f7d7b81 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -686,6 +686,14 @@ "recommended_values": "", "type": "bool" }, + "preview_inquiry_error_prob": { + "value": "0.05", + "section": "bci_config", + "readableName": "Preview Inquiry Button Error Probability", + "helpTip": "Specifies the probability of a button error during inquiry preview. Default: 0.05", + "recommended_values": "", + "type": "float" + }, "preview_inquiry_progress_method": { "value": "0", "section": "bci_config", diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 82640dd20..383a9e331 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -96,7 +96,7 @@ class RSVPCopyPhraseTask(Task): 'is_txt_stim', 'lm_backspace_prob', 'backspace_always_shown', 'decision_threshold', 'max_inq_len', 'max_inq_per_series', 'max_minutes', 'max_selections', 'min_inq_len', 'show_feedback', 'feedback_duration', - 'show_preview_inquiry', 'preview_inquiry_isi', + 'show_preview_inquiry', 'preview_inquiry_isi', 'preview_inquiry_error_prob', 'preview_inquiry_key_input', 'preview_inquiry_length', 'preview_inquiry_progress_method', 'spelled_letters_count', 'stim_color', 'stim_height', 'stim_jitter', 'stim_length', 'stim_number', @@ -129,7 +129,7 @@ def __init__( self.alp = alphabet(self.parameters) - self.button_press_error_prob = 0.05 + self.button_press_error_prob = parameters['preview_inquiry_error_prob'] self.evidence_evaluators = self.init_evidence_evaluators(signal_models) diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index fff068107..657afe28c 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -73,6 +73,7 @@ def setUp(self): 'task_color': 'white', 'task_height': 0.1, 'task_text': 'HELLO_WORLD', + "preview_inquiry_error_prob": 0.05, 'info_pos_x': 0.0, 'info_pos_y': -0.75, 'time_fixation': 0.5, From d9950b1798274491b20699199b4c59a3e8450a27 Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Mon, 16 Sep 2024 19:29:32 -0400 Subject: [PATCH 298/330] Inquiry preview bugfix (#348) --- bcipy/display/main.py | 4 ++++ bcipy/display/paradigm/rsvp/display.py | 13 ++++--------- .../tests/paradigm/rsvp/test_rsvp_display.py | 1 + bcipy/task/paradigm/rsvp/calibration/calibration.py | 1 + bcipy/task/paradigm/rsvp/copy_phrase.py | 1 + 5 files changed, 11 insertions(+), 9 deletions(-) diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 793f21774..6e7ddba30 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -245,12 +245,15 @@ class PreviewInquiryProperties: def __init__( self, + preview_on: bool, preview_only: bool, preview_inquiry_length: float, preview_inquiry_progress_method: int, preview_inquiry_key_input: str, preview_inquiry_isi: float): """Initialize Inquiry Preview Parameters. + + preview_on(bool): If True, display an inquiry preview before the main inquiry. preview_only(bool): If True, only preview the inquiry and do not probe for response preview_inquiry_length(float): Length of time in seconds to present the inquiry preview preview_inquiry_progress_method(int): Method of progression for inquiry preview. @@ -258,6 +261,7 @@ def __init__( preview_inquiry_key_input(str): Defines which key should be listened to for progressing preview_inquiry_isi(float): Length of time after displaying the inquiry preview to display a blank screen """ + self.preview_on = preview_on self.preview_inquiry_length = preview_inquiry_length self.preview_inquiry_key_input = preview_inquiry_key_input self.press_to_accept = True if preview_inquiry_progress_method == 1 else False diff --git a/bcipy/display/paradigm/rsvp/display.py b/bcipy/display/paradigm/rsvp/display.py index 25bc577f8..b56ac4bc5 100644 --- a/bcipy/display/paradigm/rsvp/display.py +++ b/bcipy/display/paradigm/rsvp/display.py @@ -80,6 +80,8 @@ def __init__( self.full_screen = full_screen self._preview_inquiry = preview_inquiry + if self._preview_inquiry: + self.preview_calibration = self._preview_inquiry.preview_on self.staticPeriod = static_clock @@ -126,19 +128,12 @@ def schedule_to(self, self.stimuli_timing = timing or [] self.stimuli_colors = colors or [] - def do_inquiry(self, preview_calibration: bool = False) -> List[Tuple[str, float]]: + def do_inquiry(self) -> List[Tuple[str, float]]: """Do inquiry. Animates an inquiry of flashing letters to achieve RSVP. - PARAMETERS: - ----------- - preview_calibration(bool) default False: Whether or not to preview the upcoming inquiry stimuli. This feature - is used to help the participant prepare for the upcoming inquiry after a prompt. It will present after - the first stimulus of the inquiry (assumed to be a prompt). Not recommended for use outside of a - calibration task. - RETURNS: -------- timing(list[float]): list of timings of stimuli presented in the inquiry @@ -161,7 +156,7 @@ def do_inquiry(self, preview_calibration: bool = False) -> List[Tuple[str, float self.first_stim_callback(inquiry[idx]['sti']) # If previewing the inquiry, do so after the first stimulus - if preview_calibration and idx == 1: + if self.preview_calibration and idx == 1: time, _ = self.preview_inquiry() timing.extend(time) diff --git a/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py b/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py index a05fe433b..61bb2a483 100644 --- a/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py +++ b/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py @@ -88,6 +88,7 @@ def setUp(self, task_bar_mock): self.preview_inquiry_progress_method = 1 # preview only = 0; press to accept == 1; press to skip == 2 self.preview_inquiry_key_input = 'space' self.preview_inquiry = PreviewInquiryProperties( + preview_on=False, preview_only=False, preview_inquiry_length=self.preview_inquiry_length, preview_inquiry_isi=self.preview_inquiry_isi, diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 9155b611a..964a2fbad 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -80,6 +80,7 @@ def init_calibration_display_task( padding=parameters['task_padding']) preview_inquiry = PreviewInquiryProperties( + preview_on=parameters['show_preview_inquiry'], preview_only=True, preview_inquiry_length=parameters['preview_inquiry_length'], preview_inquiry_progress_method=parameters[ diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 383a9e331..17bc7a0cb 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -905,6 +905,7 @@ def _init_copy_phrase_display( experiment_clock: Clock, starting_spelled_text) -> CopyPhraseDisplay: preview_inquiry = PreviewInquiryProperties( + preview_on=parameters['show_preview_inquiry'], preview_only=parameters['preview_only'], preview_inquiry_length=parameters['preview_inquiry_length'], preview_inquiry_key_input=parameters['preview_inquiry_key_input'], From 96a838245c1e52ebbf5d5edcf5ace001ea647c76 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 20 Sep 2024 17:23:45 -0700 Subject: [PATCH 299/330] Delete unused or redundant code --- bcipy/simulator/README.md | 54 ++--- bcipy/simulator/__main__.py | 57 +----- bcipy/simulator/helpers/data_engine.py | 37 +--- bcipy/simulator/helpers/decision.py | 117 ----------- bcipy/simulator/helpers/evidence_fuser.py | 53 ----- bcipy/simulator/helpers/log_utils.py | 41 +--- bcipy/simulator/helpers/metrics.py | 137 ------------- bcipy/simulator/helpers/model_handler.py | 135 ------------- bcipy/simulator/helpers/rsvp_utils.py | 24 --- bcipy/simulator/helpers/sampler.py | 2 +- bcipy/simulator/helpers/signal_helpers.py | 193 ------------------ bcipy/simulator/helpers/sim_runner.py | 118 ----------- bcipy/simulator/helpers/sim_viz.py | 73 ------- bcipy/simulator/helpers/state.py | 13 ++ bcipy/simulator/helpers/state_manager.py | 214 -------------------- bcipy/simulator/helpers/types.py | 40 ---- bcipy/simulator/sim.py | 229 ---------------------- bcipy/simulator/sim_factory.py | 61 ------ bcipy/simulator/sim_parameters.json | 71 ------- bcipy/simulator/simulator_base.py | 40 ---- bcipy/simulator/task/copy_phrase.py | 21 +- bcipy/simulator/task/task_factory.py | 6 +- bcipy/simulator/task/task_runner.py | 2 +- 23 files changed, 59 insertions(+), 1679 deletions(-) delete mode 100644 bcipy/simulator/helpers/decision.py delete mode 100644 bcipy/simulator/helpers/evidence_fuser.py delete mode 100644 bcipy/simulator/helpers/metrics.py delete mode 100644 bcipy/simulator/helpers/model_handler.py delete mode 100644 bcipy/simulator/helpers/rsvp_utils.py delete mode 100644 bcipy/simulator/helpers/signal_helpers.py delete mode 100644 bcipy/simulator/helpers/sim_runner.py delete mode 100644 bcipy/simulator/helpers/sim_viz.py create mode 100644 bcipy/simulator/helpers/state.py delete mode 100644 bcipy/simulator/helpers/state_manager.py delete mode 100644 bcipy/simulator/helpers/types.py delete mode 100644 bcipy/simulator/sim.py delete mode 100644 bcipy/simulator/sim_factory.py delete mode 100644 bcipy/simulator/sim_parameters.json delete mode 100644 bcipy/simulator/simulator_base.py diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index 3bde0493b..bba55404e 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -2,20 +2,28 @@ ### Overview -This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and -running given models -in RSVP task loop, thus simulating a -live session. +This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and running given models in RSVP task loop, thus simulating a live session. ### Run steps -`main.py` is the entry point for program. After following, `BciPy` readme steps for setup, run the -module from shell as -such: - -``python3 bcipy/simulator -d "pathToDataFolderWrapper" -p "pathToParametersFile" -sm "pathToSignalModel.pkl"`` - -Then view the appropriate output folder for LOG file(s) and metrics. +`main.py` is the entry point for program. After following `BciPy` readme steps for setup, run the module from terminal: + +``` +(venv) $ python bcipy/simulator -h +usage: simulator [-h] -d DATA_FOLDER [-g GLOB_PATTERN] -m MODEL_PATH -p PARAMETERS [-n N] + +optional arguments: + -h, --help show this help message and exit + -d DATA_FOLDER, --data_folder DATA_FOLDER + Raw data folders to be processed. + -g GLOB_PATTERN, --glob_pattern GLOB_PATTERN + glob pattern to select a subset of data folders Ex. "*RSVP_Copy_Phrase*" + -m MODEL_PATH, --model_path MODEL_PATH + Signal models to be used + -p PARAMETERS, --parameters PARAMETERS + Parameter File to be used + -n N Number of times to run the simulation +``` #### Program Args @@ -26,25 +34,17 @@ Then view the appropriate output folder for LOG file(s) and metrics. - Glob patterns can also include nested directories (ex. `"*/*Matrix_Copy*"`). - `p` : path to the parameters.json file used to run the simulation. These parameters will be applied to all raw_data files when loading. -- `sm`: the signal model argument is necessary to generate evidence +- `m`: all pickle (.pkl) files in this directory will be loaded as signal models. #### Sim Output Details -Output folders are generally located at [simulator/generated](). - -- `result.json` captures metrics from the simulation and all the state from the simulation (like _session.json_) -- `parameters.json` captures params used, a combination of parameters inputted by you and the `sim_parameters.json` -- Single run Folder name: _SIM_month-day-hour:min_hash_ -- Multi Run Folder name: _SIM_MULTI_runCount_month-day-hour:min_ - - -#### Configuring Parameters - -There are various parameters that you can tweak in `sim_parameters.json` to run simulator multiple times with the same args, specify lang_model type ... - - -### Architecture +Output folders are generally located in the `simulator/generated` directory. Each simulation will create a new directory. The directory name will be prefixed with `SIM` and will include the current date and time. -![simDiagram.png](res/simDiagram.png) +- `parameters.json` captures params used for the simulation +- `sim.log` is a log file for the simulation +A directory is created for each simulation run. The directory contents are similar to the session output in a normal bcipy task. Each run directory contains: +- `run_n.log` log file specific to the run +- `session.json` session data output for the task, including evidence generated for each inquiry and overall metrics. +- `session.xlsx` session data summarized in an excel spreadsheet with charts for easier visualization. diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index a79a50caf..804ab1131 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -1,57 +1,6 @@ """ Entry point to run Simulator """ -import argparse -from glob import glob -from pathlib import Path +from bcipy.simulator.task import task_runner -from bcipy.simulator.helpers import artifact -from bcipy.simulator.helpers.sim_runner import SimRunner -from bcipy.simulator.sim_factory import SimulationFactory - -if __name__ == "__main__": - glob_help = ('glob pattern to select a subset of data folders' - ' Ex. "*RSVP_Copy_Phrase*"') - parser = argparse.ArgumentParser() - parser.add_argument( - "-d", - "--data_folder", - type=Path, - required=True, - help="Raw data folders to be processed. Singular wrapper dir with data folders") - parser.add_argument('-g', '--glob_pattern', help=glob_help, default="*") - parser.add_argument( - "-sm", - "--smodel_files", - action="append", - type=Path, - required=True, - help="Signal models to be used") - parser.add_argument( - "-p", - "--parameters", - type=Path, - required=True, - help="Parameter File to be used") - - parser.add_argument( - "-n", - type=int, - required=False, - default=1, - help="Number of times to run the simulation") - parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) - args = parser.parse_args() - sim_args = vars(args) - - sim_args['source_dirs'] = [ - Path(d) for d in glob(str(Path(args.data_folder, args.glob_pattern))) - if Path(d).is_dir() - ] - - sim_dir = artifact.init_simulation_dir() - simulator = SimulationFactory.create(**sim_args) - runner = SimRunner(save_dir=sim_dir, - simulator=simulator, - runs=args.n) - runner.simulator = simulator - runner.run() +if __name__ == '__main__': + task_runner.main() diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 95c0e807c..52ef246ed 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,7 +1,7 @@ import logging from abc import ABC, abstractmethod from pathlib import Path -from typing import Any, List, NamedTuple, Optional, Union +from typing import Any, List, NamedTuple, Union import numpy as np import pandas as pd @@ -10,9 +10,8 @@ from bcipy.helpers.parameters import Parameters from bcipy.simulator.helpers import data_process from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME -from bcipy.simulator.helpers.signal_helpers import (EegRawDataProcessor, - ExtractedExperimentData, - RawDataProcessor) +from bcipy.simulator.helpers.data_process import (ExtractedExperimentData, + RawDataProcessor) log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) @@ -88,10 +87,7 @@ def query(self, """Query the data.""" -def convert_trials( - data_source: Union[ExtractedExperimentData, - data_process.ExtractedExperimentData] -) -> List[Trial]: +def convert_trials(data_source: ExtractedExperimentData) -> List[Trial]: """Convert extracted data from a single data source to a list of Trials.""" trials = [] symbols_by_inquiry = data_source.symbols_by_inquiry @@ -122,16 +118,12 @@ class RawDataEngine(DataEngine): a queryable data structure. """ - def __init__( - self, - source_dirs: List[str], - parameters: Parameters, - data_processor: Optional[Union[RawDataProcessor, - data_process.RawDataProcessor]] = None): + def __init__(self, source_dirs: List[str], parameters: Parameters, + data_processor: RawDataProcessor): self.source_dirs: List[str] = source_dirs self.parameters: Parameters = parameters - self.data_processor = data_processor or EegRawDataProcessor() + self.data_processor = data_processor self.data: List[Union[ExtractedExperimentData, data_process.ExtractedExperimentData]] = [] self._trials_df = pd.DataFrame() @@ -208,18 +200,3 @@ def query_condition(self, query_filter: QueryFilter) -> str: if (isinstance(value, str)): value = f"'{value}'" return f"{query_filter.field} {query_filter.operator} {value}" - - -class RawDataEngineWrapper(RawDataEngine): - """ - Data engine that assumes all data is stored within single data folder - - single data folder contains dataDir1, dataDir2, ... - - each data dir contains its raw_data and triggers - """ - - def __init__(self, - source_dir: str, - parameters: Parameters, - data_processor: Optional[RawDataProcessor] = None): - data_paths = [str(d) for d in Path(source_dir).iterdir() if d.is_dir()] - super().__init__(data_paths, parameters, data_processor) diff --git a/bcipy/simulator/helpers/decision.py b/bcipy/simulator/helpers/decision.py deleted file mode 100644 index cc27bc31e..000000000 --- a/bcipy/simulator/helpers/decision.py +++ /dev/null @@ -1,117 +0,0 @@ -from abc import ABC - -import numpy as np -import logging -from typing import List - -from bcipy.simulator.helpers.types import InquiryResult - -log = logging.getLogger(__name__) - - -# TODO copied over criteria.py. Still debating whether to tie our -# simulator to that class or not. For now, just hotfixing logic to fit -# with my implementation - -class SimDecisionCriteria(ABC): - """Abstract class for Criteria which can be applied to evaluate a inquiry - """ - - def reset(self): - pass - - def decide(self, series: List[InquiryResult]): - # TODO update documentation - """ - Apply the given criteria. - Parameters: - ----------- - series - series data - - target(str): target of the series - - time_spent(ndarray[float]): |num_trials|x1 - time spent on the inquiry - - list_sti(list[list[str]]): presented symbols in each - inquiry - - list_distribution(list[ndarray[float]]): list of |alp|x1 - arrays with prob. dist. over alp - - """ - raise NotImplementedError() - - def __str__(self): - return type(self).__name__ - - -class MinIterations(SimDecisionCriteria): - """ Returns true if the minimum number of iterations have not yet - been reached. """ - - def __init__(self, min_num_inq: int): - """ Args: - min_num_inq(int): minimum number of inquiry number before any - termination objective is allowed to be triggered """ - self.min_num_inq = min_num_inq - - def decide(self, series: List[InquiryResult]): - # Note: we use 'list_sti' parameter since this is the number of - # inquiries displayed. The length of 'list_distribution' is 1 greater - # than this, since the language model distribution is added before - # the first inquiry is displayed. - current_inq = len(series) if series else 0 - log.debug( - f"Checking min iterations; current iteration is {current_inq}") - return current_inq < self.min_num_inq - - -# -# class DecreasedProbabilityCriteria(DecisionCriteria): -# """Returns true if the letter with the max probability decreased from the -# last inquiry.""" -# -# def decide(self, series: Dict): -# if len(series['list_distribution']) < 2: -# return False -# prev_dist = series['list_distribution'][-2] -# cur_dist = series['list_distribution'][-1] -# return np.argmax(cur_dist) == np.argmax( -# prev_dist) and np.max(cur_dist) < np.max(prev_dist) -# -# -class MaxIterationsSim(SimDecisionCriteria): - """Returns true if the max iterations have been reached.""" - - def __init__(self, max_num_inq: int): - """ Args: - max_num_inq(int): maximum number of inquiries allowed before - mandatory termination """ - self.max_num_inq = max_num_inq - - def decide(self, series: List[InquiryResult]): - # Note: len(series['list_sti']) != len(series['list_distribution']) - # see MinIterationsCriteria comment - current_inq = len(series) if series else 0 - if current_inq >= self.max_num_inq: - log.debug( - "Committing to decision: max iterations have been reached.") - return True - return False - - -class ProbThresholdSim(SimDecisionCriteria): - """Returns true if the commit threshold has been met.""" - - def __init__(self, threshold: float): - """ Args: - threshold(float in [0,1]): A threshold on most likely - candidate posterior. If a candidate exceeds a posterior - the system terminates. - """ - assert 1 >= threshold >= 0, "stopping threshold should be in [0,1]" - self.tau = threshold - - def decide(self, series: List[InquiryResult]): - current_distribution = series[-1].fused_likelihood - if np.max(current_distribution) > self.tau: - log.debug("Committing to decision: posterior exceeded threshold.") - return True - return False diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py deleted file mode 100644 index 8aa1e559d..000000000 --- a/bcipy/simulator/helpers/evidence_fuser.py +++ /dev/null @@ -1,53 +0,0 @@ -from abc import abstractmethod, ABC -from typing import Optional, Dict - -import numpy as np - -from bcipy.simulator.helpers.types import SimEvidence - - -class EvidenceFuser(ABC): - - @abstractmethod - def fuse(self, prior_likelihood: Optional[np.ndarray], - evidence: Dict[str, SimEvidence]) -> np.ndarray: - ... - - @staticmethod - def make_prior(len_dist): - return np.ones(len_dist) / len_dist - - -class MultiplyFuser(EvidenceFuser): - - def __init__(self): - pass - - def fuse(self, prior_likelihood, evidence) -> np.ndarray: - - distribution_shape = len(list(evidence.values())[0].evidence) - prior_likelihood = prior_likelihood if prior_likelihood is not None \ - else EvidenceFuser.make_prior(distribution_shape) - - ret_likelihood = prior_likelihood.copy() - - for sim_evidence in evidence.values(): - likelihoods = sim_evidence.evidence - assert ret_likelihood.shape == likelihoods.shape - ret_likelihood *= likelihoods[:] - ret_likelihood = self.__normalize_likelihood(ret_likelihood) - - return ret_likelihood - - def __normalize_likelihood(self, likelihood): - - cleaned_likelihood = likelihood.copy() - if np.isinf(np.sum(likelihood)): - tmp = np.zeros(len(likelihood)) - tmp[np.where(likelihood == np.inf)[0][0]] = 1 - cleaned_likelihood = tmp - - if not np.isnan(np.sum(likelihood)): - cleaned_likelihood = likelihood / np.sum(likelihood) - - return cleaned_likelihood diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 42e6a0a22..50ee084cd 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -1,47 +1,8 @@ -from typing import Dict, List - -import pandas as pd +from typing import List from bcipy.simulator.helpers.data_engine import Trial -from bcipy.simulator.helpers.types import SimEvidence - - -def fmt_stim_likelihoods(likelihoods, alp): - rounded = [round(lik, 3) for lik in likelihoods] - formatted = [f"{a} : {l}" for a, l in zip(alp, rounded)] - return formatted - - -def fmt_likelihoods_for_hist(likelihoods, alp): - rounded = [round(lik, 3) for lik in likelihoods] - formatted = [(a, l) for a, l in zip(alp, rounded)] - return formatted def format_samples(sample_rows: List[Trial]) -> str: """Returns a tabular representation of the sample rows.""" return '\n'.join([str(row) for row in sample_rows]) - - -def format_sample_rows(sample_rows: List[pd.Series]) -> str: - """Returns a tabular representation of the sample rows.""" - return pd.DataFrame(sample_rows).drop(columns=['eeg']).to_string( - index=False, header=True) - - -def format_sample_df(sample_rows: pd.DataFrame) -> str: - """Returns a tabular representation of the sample rows.""" - return sample_rows.drop(columns=['eeg']).to_string(index=False, - header=True) - - -def fmt_reshaped_evidence(evidences: Dict[str, SimEvidence]): - """ Formats evidences to log shapes pf ndarrays """ - - evidence_shape_strs = [] - - for evidence_name, evidence in evidences.items(): - evidence_shape = evidence.evidence.shape if evidence is not None else None - evidence_shape_strs.append(f"{evidence.evidence_type} => {evidence_shape}") - - return ", ".join(evidence_shape_strs) diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py deleted file mode 100644 index 766f767de..000000000 --- a/bcipy/simulator/helpers/metrics.py +++ /dev/null @@ -1,137 +0,0 @@ -import dataclasses -from abc import ABC, abstractmethod -from functools import reduce -from typing import Any, Dict, List - -import numpy as np - -from bcipy.helpers.acquisition import max_inquiry_duration -from bcipy.simulator.helpers.state_manager import SimState -from bcipy.simulator.helpers.types import InquiryResult - - -@dataclasses.dataclass -class SimMetrics: - total_series: int = 0 - total_inquiries: int = 0 - total_decisions: int = 0 - total_incorrect_decisions: int = -1 # negative one if uncalculated - - total_time_spent: float = 0.0 - inquiries_per_selection: float = 0.0 - - -def average_sim_metrics(run_scores: List[SimMetrics]) -> Dict: - """ Averages the values in multiple SimMetrics objects """ - - metric_acc_dict = dataclasses.asdict(SimMetrics()) - N = len(run_scores) - - if N < 1: - return metric_acc_dict - - for run_metrics in run_scores: - for field, val in dataclasses.asdict(run_metrics).items(): - metric_acc_dict[field] += val - - for key, val in metric_acc_dict.items(): - metric_acc_dict[key] = round(val / N, 3) - - return metric_acc_dict - - -class RefereeHandler(ABC): - @abstractmethod - def handle(self, sim) -> Dict[str, Any]: - ... - - -class SimMetricsHandler(RefereeHandler): - - def handle(self, sim) -> Dict[str, Any]: - state: SimState = getattr(sim, "state_manager").get_state() - - # calculating total decisions made and total incorrect decisions - flattened_inquiries: List[InquiryResult] = reduce(lambda l1, l2: l1 + l2, - state.series_results, []) - inqs_with_decisions = list(filter(lambda inq: bool(inq.decision), flattened_inquiries)) - total_decisions = len(inqs_with_decisions) - total_incorrect_decisions = len([inq for inq in inqs_with_decisions if - inq.decision != inq.target]) - - # average number of inqs before a decision - inq_counts = [] - for series in state.series_results: - if [inq for inq in series if inq.decision]: - inq_counts.append(len(series)) - inquiries_per_selection = round(np.array(inq_counts).mean(), 3) - - # inq and series counts - total_inquiries = state.total_inquiry_count() - total_series = state.series_n - - # total time spent estimate seconds = (max_inq_time_estimate * total_inquiries) - parameters = sim.get_parameters() - max_inq_time = max_inquiry_duration(parameters) - total_time_spent = total_inquiries * max_inq_time - - ret = SimMetrics(total_series=total_series, - total_inquiries=total_inquiries, - total_decisions=total_decisions, - total_time_spent=total_time_spent, - inquiries_per_selection=inquiries_per_selection, - total_incorrect_decisions=total_incorrect_decisions) - return dataclasses.asdict(ret) - - -class MetricReferee(ABC): - - # May change to SimState that is passed around not whole Simulator - # Depends on how much data encapsulated by SimState - @abstractmethod - def score(self, sim): - """ Generate registered metrics for simulation """ - - @abstractmethod - def visualize(self, sim): - """ Generate registered visualizations for sim """ - - @abstractmethod - def add_metric_handler(self, name: str, handler: RefereeHandler): - """ Add a metric calculation that will be executed upon self.score() """ - - @abstractmethod - def add_viz_handler(self, name: str, handler: RefereeHandler): - """ Register a visualization that will be executed upon self.visualize() """ - - -class RefereeImpl(MetricReferee): - - def __init__(self, metric_handlers=None, viz_handlers=None): - self.metric_handlers: Dict[str, RefereeHandler] = metric_handlers if metric_handlers else {} - self.viz_handlers: Dict[str, RefereeHandler] = viz_handlers if viz_handlers else {} - - self.inquiry_time: float = 1 # 1 inq -> 1 second - # TODO maybe some configurable parameters for visualizations - - def score(self, sim) -> SimMetrics: - metrics = SimMetrics() - metrics_dict = dataclasses.asdict(metrics) - for handler_name, handler in self.metric_handlers.items(): - handler_metrics = handler.handle(sim) - - for key, val in handler_metrics.items(): - if key in metrics_dict: - metrics_dict[key] = val - - return SimMetrics(**metrics_dict) - - def visualize(self, sim): - for handler_name, viz_handler in self.viz_handlers.items(): - viz_handler.handle(sim) - - def add_metric_handler(self, name: str, handler: RefereeHandler): - self.metric_handlers[name] = handler - - def add_viz_handler(self, name: str, handler: RefereeHandler): - self.viz_handlers[name] = handler diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py deleted file mode 100644 index 88bf28f3f..000000000 --- a/bcipy/simulator/helpers/model_handler.py +++ /dev/null @@ -1,135 +0,0 @@ -import inspect -import logging -import pickle -from abc import ABC, abstractmethod -from pathlib import Path - -import numpy as np - -from bcipy.helpers.language_model import (histogram, language_models_by_name, - with_min_prob) -from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet -from bcipy.language import LanguageModel, ResponseType -from bcipy.simulator.helpers.state_manager import SimState -from bcipy.simulator.helpers.types import SimEvidence -from bcipy.task.data import EvidenceType - -log = logging.getLogger(__name__) - - -class ModelHandler(ABC): - - @abstractmethod - def generate_evidence(self, state: SimState, features): - """ Run model on features to generate evidence """ - - @abstractmethod - def get_model(self, key=None): - """ get the model """ - - def includes_language_model(self) -> bool: - return False - - -class SignalModelHandler1(ModelHandler): - - def __init__(self, model_file): - self.model_file = model_file - with open(self.model_file, "rb") as signal_file: - self.signal_model = pickle.load(signal_file) - - def generate_evidence(self, state: SimState, features): - stimuli = state.display_alphabet - alp = alphabet() - eeg_evidence = self.signal_model.predict(features, stimuli, alp) - - return dict(sm=SimEvidence(EvidenceType.ERP, eeg_evidence, stimuli)) - - def get_model(self, key=None): - return self.signal_model - - -def sim_init_lm(parameters) -> LanguageModel: - """ - Init Language Model configured in the sim parameters. - Mostly copied from language_model.init_lang_model - - Parameters - ---------- - parameters : dict - configuration details and path locations - - Returns - ------- - instance of a LanguageModel - """ - - lm_classes = language_models_by_name() - model_class: LanguageModel.__class__ = lm_classes[parameters.get("sim_lm_type", "UNIFORM")] - # introspect the model arguments to determine what parameters to pass. - args = inspect.signature(model_class).parameters.keys() - - # select the relevant parameters into a dict. - params = {key: parameters[key] for key in args & parameters.keys()} - return model_class(response_type=ResponseType.SYMBOL, - symbol_set=alphabet(parameters), - **params) - - -class SigLmModelHandler1(ModelHandler): - - def __init__(self, sm_model_file, parameters): - """ - - Args: - sm_model_file: path to signal model pickle - parameters: only needs to contain which type of language model - """ - self.sm_model_file = sm_model_file - self.lm_model: LanguageModel = sim_init_lm(parameters) - log.info(f"Language Model Type: {self.lm_model.name()}") - self.alp = alphabet() - self.backspace_prob: float = parameters.get('lm_backspace_prob', 0.05) - - with open(self.sm_model_file, "rb") as signal_file: - self.signal_model = pickle.load(signal_file) - - def generate_evidence(self, state: SimState, eeg_responses): - stimuli = state.display_alphabet - eeg_evidence = self.signal_model.predict(eeg_responses, stimuli, self.alp) - lm_evidence = self.lm_model.predict( - list(state.current_sentence)) if state.inquiry_n == 0 else None - - ret_evidence = {} - if lm_evidence is not None: - - # adjusting evidence to include backspace prob - if BACKSPACE_CHAR in stimuli: - lm_evidence = with_min_prob(lm_evidence, (BACKSPACE_CHAR, self.backspace_prob)) - - ret_evidence['lm'] = SimEvidence(EvidenceType.LM, np.array(lm_evidence), self.alp) - log.debug(f"LM evidence for '{state.current_sentence}' -> \n {histogram(lm_evidence)}") - - if eeg_evidence is not None: - ret_evidence['sm'] = SimEvidence(EvidenceType.ERP, eeg_evidence, stimuli) - - return ret_evidence - - def get_model(self, key=None): - if key == 'sm': - return self.signal_model - elif key == 'lm': - return self.lm_model - else: - raise RuntimeError(f"Can't find model {key}") - - def includes_language_model(self) -> bool: - return True - - def __str__(self): - props = { - 'signal_model': self.signal_model.__class__.__name__, - 'language_model': self.lm_model.__class__.__name__, - 'sm_file': f".../{Path(self.sm_model_file).parent.name}/{Path(self.sm_model_file).name}" - } - return f"<{self.__class__.__name__} {props}>" diff --git a/bcipy/simulator/helpers/rsvp_utils.py b/bcipy/simulator/helpers/rsvp_utils.py deleted file mode 100644 index 78d3aebe3..000000000 --- a/bcipy/simulator/helpers/rsvp_utils.py +++ /dev/null @@ -1,24 +0,0 @@ -from typing import List, Tuple - -from bcipy.helpers.symbols import BACKSPACE_CHAR - - -def next_target_letter(current_sentence, target_sentence): - """Computes the next target letter based on the currently spelled_text. - """ - if target_sentence[0:len(current_sentence)] == current_sentence: - # if correctly spelled so far, get the next letter. - return target_sentence[len(current_sentence)] if len( - current_sentence) < len(target_sentence) else target_sentence[-1] - return BACKSPACE_CHAR - - -def format_lm_output(lm_evidence_tuples: List[Tuple], symbol_set): - """ Formats language model output into list of likelihoods in alphabet order """ - pos_map = {letter: i for i, letter in enumerate(symbol_set)} - reshaped_lm_lik = list(symbol_set) - # sorting the likelhoods by order of symbol set - for letter, lik in lm_evidence_tuples: - reshaped_lm_lik[pos_map[letter]] = float(lik) - - return reshaped_lm_lik diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 3ec40d606..d889f4bc3 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -11,7 +11,7 @@ from bcipy.simulator.helpers.data_engine import (QueryFilter, RawDataEngine, Trial) from bcipy.simulator.helpers.log_utils import format_samples -from bcipy.simulator.helpers.state_manager import SimState +from bcipy.simulator.helpers.state import SimState log = logging.getLogger(__name__) diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py deleted file mode 100644 index 2080b9f5a..000000000 --- a/bcipy/simulator/helpers/signal_helpers.py +++ /dev/null @@ -1,193 +0,0 @@ -import logging as logger -from dataclasses import dataclass -from pathlib import Path -from typing import List - -import numpy as np - -from bcipy.acquisition import devices -from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, RAW_DATA_FILENAME, - TRIGGER_FILENAME) -from bcipy.helpers.acquisition import analysis_channels -from bcipy.helpers.exceptions import TaskConfigurationException -from bcipy.helpers.list import grouper -from bcipy.helpers.load import load_raw_data -from bcipy.helpers.parameters import Parameters -from bcipy.helpers.stimuli import InquiryReshaper, update_inquiry_timing -from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.signal.process import (ERPTransformParams, filter_inquiries, - get_default_transform) - -log = logger.getLogger(__name__) - - -@dataclass() -class ExtractedExperimentData: - source_dir: str - inquiries: np.ndarray - trials: np.ndarray - labels: List - inquiry_timing: List - - decoded_triggers: tuple - trials_per_inquiry: int - - @property - def trials_by_inquiry(self) -> List[np.ndarray]: - """EEG data by inquiry. - shape (i_inquiry, n_channel, m_trial, x_sample) - """ - return np.split(self.trials, self.inquiries.shape[1], 1) - - @property - def symbols_by_inquiry(self) -> List[List[str]]: - """Get symbols by inquiry. shape (i_inquiry, s_alphabet_subset)""" - _targets, _times, trigger_symbols = self.decoded_triggers - return [ - list(group) for group in grouper( - trigger_symbols, self.trials_per_inquiry, incomplete="ignore") - ] - - @property - def labels_by_inquiry(self) -> List[List[int]]: - """Shape (i_inquiry, s_alphabet_subset)""" - return self.labels - - -class RawDataProcessor(): - """Processes raw data for a given device and converts it to - ExtractedExperimentData for use in the simulator.""" - - def process(self, data_folder: str, - parameters: Parameters) -> ExtractedExperimentData: - """Load and process the data""" - raise NotImplementedError - - -class EegRawDataProcessor(RawDataProcessor): - """RawDataProcessor that processes EEG data.""" - - def __init__(self): - - self.reshaper = InquiryReshaper() - - def process(self, data_folder: str, - parameters: Parameters) -> ExtractedExperimentData: - # TODO: refactor - - log.debug(f"Processing raw data for {data_folder}") - # extract relevant session information from parameters file - trial_window = parameters.get("trial_window") - if trial_window is None: - # using trial_length instead and converting to trial window - trial_length = parameters.get('trial_length') - if not trial_length: - raise TaskConfigurationException( - "Could not find trial_window or trial_length in parameters" - ) - - trial_window = tuple( - [0, trial_length]) # trial_length=0.5 -> trial_window=(0,0.5) - - window_length = trial_window[1] - trial_window[0] - prestim_length = parameters.get("prestim_length") - trials_per_inquiry = parameters.get("stim_length") - # The task buffer length defines the min time between two inquiries - # We use half of that time here to buffer during transforms - buffer = int(parameters.get("task_buffer_length") / 2) - raw_data_file = f"{RAW_DATA_FILENAME}.csv" - - # get signal filtering information - transform_params = parameters.instantiate(ERPTransformParams) - downsample_rate = transform_params.down_sampling_rate - static_offset = parameters.get("static_trigger_offset") - - log.debug( - f"\nData processing settings: \n" - f"{str(transform_params)} \n" - f"Trial Window: {trial_window[0]}-{trial_window[1]}s, " - f"Prestimulus Buffer: {prestim_length}s, Poststimulus Buffer: {buffer}s \n" - f"Static offset: {static_offset}") - - # Load raw data - raw_data = load_raw_data(str(Path(data_folder, raw_data_file))) - channels = raw_data.channels - type_amp = raw_data.daq_type - sample_rate = raw_data.sample_rate - - devices.load(Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME)) - device_spec = devices.preconfigured_device(raw_data.daq_type) - - # setup filtering - default_transform = get_default_transform( - sample_rate_hz=sample_rate, - notch_freq_hz=transform_params.notch_filter_frequency, - bandpass_low=transform_params.filter_low, - bandpass_high=transform_params.filter_high, - bandpass_order=transform_params.filter_order, - downsample_factor=transform_params.down_sampling_rate, - ) - - log.debug(f"Channels read from csv: {channels}") - log.debug(f"Device type: {type_amp}, fs={sample_rate}") - - # Process triggers.txt files - trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( - offset=static_offset, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[ - TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION - ], - ) - - # update the trigger timing list to account for the initial trial window - corrected_trigger_timing = [ - timing + trial_window[0] for timing in trigger_timing - ] - - # Channel map can be checked from raw_data.csv file or the devices.json located in the acquisition module - # The timestamp column [0] is already excluded. - channel_map = analysis_channels(channels, device_spec) - channels_used = [ - channels[i] for i, keep in enumerate(channel_map) if keep == 1 - ] - log.debug(f'Channels used in analysis: {channels_used}') - - data, fs = raw_data.by_channel() - inquiries, inquiry_labels, inquiry_timing = self.reshaper( - trial_targetness_label=trigger_targetness, - timing_info=corrected_trigger_timing, - eeg_data=data, - sample_rate=sample_rate, - trials_per_inquiry=trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=window_length, - prestimulus_length=prestim_length, - transformation_buffer=buffer, - ) - - inquiries, fs = filter_inquiries(inquiries, default_transform, - sample_rate) - # Convince mypy that the values received from the reshaper are actually ints. - inquiry_timing_ints: List[List[int]] = [ - list(map(int, inq)) for inq in inquiry_timing - ] - updated_inquiry_timing = update_inquiry_timing(inquiry_timing_ints, - downsample_rate) - trial_duration_samples = int(window_length * fs) - trials = self.reshaper.extract_trials(inquiries, - trial_duration_samples, - updated_inquiry_timing) - - # define the training classes using integers, where 0=nontargets/1=targets - # labels = inquiry_labels.flatten() - - return ExtractedExperimentData(data_folder, - inquiries, - trials, - [list(arr) for arr in inquiry_labels], - inquiry_timing, - decoded_triggers=(trigger_targetness, - trigger_timing, - trigger_symbols), - trials_per_inquiry=trials_per_inquiry) diff --git a/bcipy/simulator/helpers/sim_runner.py b/bcipy/simulator/helpers/sim_runner.py deleted file mode 100644 index 8e5d7ca3c..000000000 --- a/bcipy/simulator/helpers/sim_runner.py +++ /dev/null @@ -1,118 +0,0 @@ -""" Wrappers that run a simulation """ -import dataclasses -import json -import logging -import os -import time -from pathlib import Path -from typing import Dict, List, NamedTuple - -from bcipy.simulator.helpers import artifact -from bcipy.simulator.helpers.metrics import SimMetrics, average_sim_metrics -from bcipy.simulator.simulator_base import Simulator - -log = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) - - -class RunSummary(NamedTuple): - """Summary for a simulation run.""" - run: int - target_text: str - typed_text: str - metrics: SimMetrics - - def to_dict(self) -> Dict: - """Convert to a dictionary""" - d = self._asdict() # pylint: disable=no-member - d['metrics'] = dataclasses.asdict(self.metrics) - return d - - -class SimRunner(): - """Runs one or more iterations of the simulation.""" - - def __init__(self, - save_dir: str, - simulator: Simulator, - runs: int = 1, - sim_log: str = artifact.DEFAULT_LOGFILE_NAME, - iteration_sleep: int = 0): - self.simulator = simulator - self.runs = runs - self.iteration_sleep = iteration_sleep - self.save_dir = save_dir - self.sim_log = sim_log - - def setup_complete(self) -> bool: - """Check if setup has already been run.""" - return Path(self.save_dir).is_dir() and self.simulator is not None - - def run(self): - """Run one or more simulations""" - assert self.setup_complete(), "Setup is not complete." - self.simulator.parameters.save(self.save_dir) - log.info("Starting simulation...\n") - - run_summaries = [] - # running simulator n times. resetting after each run - for i in range(self.runs): - summary = self.do_run(i) - log.info(summary.to_dict()) - run_summaries.append(summary) - time.sleep(self.iteration_sleep) - - self.summarize_metrics(run_summaries) - log.info(f"\nResults logged to {self.save_dir}/{self.sim_log}") - - def do_run(self, run: int) -> RunSummary: - """Do a simulator run and return the computed summary.""" - - path = self.configure_run_directory(run) - self.simulator.save_dir = path - self.simulator.run() - - state = self.simulator.state_manager.get_state() - run_metrics = self.simulator.referee.score(self.simulator) - - summary = RunSummary(run + 1, - target_text=state.target_sentence, - typed_text=state.current_sentence, - metrics=run_metrics) - self.simulator.reset() - return summary - - def configure_run_directory(self, run: int) -> str: - """Create the necessary directories and configure the logger. - Returns the run directory. - """ - run_name = f"run_{run + 1}" - path = f"{self.save_dir}/{run_name}" - os.mkdir(path) - artifact.configure_logger(log_path=path, - file_name=f"{run_name}.log", - use_stdout=False) - return path - - def summarize_metrics(self, run_summaries: List[RunSummary]) -> None: - """Summarize metrics from all runs.""" - all_run_metrics = [run.metrics for run in run_summaries] - self.__save_average_metrics(average_sim_metrics(all_run_metrics)) - - summary_dict = { - summary.run: summary.to_dict() - for summary in run_summaries - } - self.save_run_summaries(summary_dict) - - def __save_average_metrics(self, avg_metric_dict: Dict): - """ Write average dictionary of metrics to a json file in root of save dir.""" - - with open(f"{self.save_dir}/avg_metrics.json", 'w', - encoding='utf8') as output_file: - json.dump(avg_metric_dict, output_file, indent=2) - - def save_run_summaries(self, summary_dict: Dict): - """Write the summary for each run in the save directory.""" - with open(f"{self.save_dir}/run_summaries.json", 'w', - encoding='utf8') as output: - json.dump(summary_dict, output, indent=2) diff --git a/bcipy/simulator/helpers/sim_viz.py b/bcipy/simulator/helpers/sim_viz.py deleted file mode 100644 index de3dab254..000000000 --- a/bcipy/simulator/helpers/sim_viz.py +++ /dev/null @@ -1,73 +0,0 @@ -import logging as logger -from typing import List - -import matplotlib.pyplot as plt -import numpy as np -import pandas as pd -import seaborn as sns - -from bcipy.helpers.parameters import Parameters - -logger.getLogger().setLevel(logger.INFO) - - -def plot_comparison_records(records, outdir, title="response_values", y_scale="log"): - df = pd.DataFrame.from_records(records) - ax = sns.stripplot( - x="which_model", - y="response_value", - data=df, - order=["old_target", "new_target", "old_non_target", "new_non_target"], - ) - sns.boxplot( - showmeans=True, - meanline=True, - meanprops={"color": "k", "ls": "-", "lw": 2}, - medianprops={"visible": False}, - whiskerprops={"visible": False}, - zorder=10, - x="which_model", - y="response_value", - data=df, - showfliers=False, - showbox=False, - showcaps=False, - ax=ax, - order=["old_target", "new_target", "old_non_target", "new_non_target"], - ) - - ax.set(yscale=y_scale) - plt.savefig(outdir / f"{title}.stripplot.png", dpi=150, bbox_inches="tight") - plt.close() - ax = sns.boxplot( - x="which_model", - y="response_value", - data=df, - order=["old_target", "new_target", "old_non_target", "new_non_target"], - ) - ax.set(yscale=y_scale) - plt.savefig(outdir / f"{title}.boxplot.png", dpi=150, bbox_inches="tight") - - -def plot_replay_comparison(new_target_eeg_evidence: np.ndarray, - new_non_target_eeg_evidence: np.ndarray, - old_target_eeg_evidence: np.ndarray, - old_non_target_eeg_evidence: np.ndarray, - outdir: str, - parameters: Parameters, - ) -> None: - - def convert_to_records(arr, - key_value, - key_name="which_model", - value_name="response_value") -> List[dict]: - return [{key_name: key_value, value_name: val} for val in arr] - - records = [] - - records.extend(convert_to_records(new_target_eeg_evidence, "new_target")) - records.extend(convert_to_records(new_non_target_eeg_evidence, "new_non_target")) - records.extend(convert_to_records(old_target_eeg_evidence, "old_target")) - records.extend(convert_to_records(old_non_target_eeg_evidence, "old_non_target")) - - plot_comparison_records(records, outdir, y_scale="log") diff --git a/bcipy/simulator/helpers/state.py b/bcipy/simulator/helpers/state.py new file mode 100644 index 000000000..0a07e2853 --- /dev/null +++ b/bcipy/simulator/helpers/state.py @@ -0,0 +1,13 @@ +from dataclasses import dataclass +from typing import List + + +@dataclass +class SimState: + """ Represents the state of a current session during simulation """ + target_symbol: str + current_sentence: str + target_sentence: str + display_alphabet: List[str] + inquiry_n: int + series_n: int diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py deleted file mode 100644 index 20862fc04..000000000 --- a/bcipy/simulator/helpers/state_manager.py +++ /dev/null @@ -1,214 +0,0 @@ -import copy -import dataclasses -import logging -import random -from abc import ABC -from dataclasses import dataclass -from typing import Callable, Dict, List, Optional - -import numpy as np - -from bcipy.helpers.exceptions import FieldException -from bcipy.helpers.language_model import histogram -from bcipy.helpers.parameters import Parameters -from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet -from bcipy.simulator.helpers.decision import (MaxIterationsSim, - ProbThresholdSim, - SimDecisionCriteria) -from bcipy.simulator.helpers.evidence_fuser import EvidenceFuser, MultiplyFuser -from bcipy.simulator.helpers.log_utils import fmt_likelihoods_for_hist -from bcipy.simulator.helpers.rsvp_utils import next_target_letter -from bcipy.simulator.helpers.types import InquiryResult, SimEvidence - -log = logging.getLogger(__name__) - - -@dataclass -class SimState: - """ Represents the state of a current session during simulation """ - target_symbol: str - current_sentence: str - target_sentence: str - display_alphabet: List[str] - inquiry_n: int - series_n: int - series_results: List[List[InquiryResult]] - decision_criterion: List[SimDecisionCriteria] - - def total_inquiry_count(self): - count = 0 - for series in self.series_results: - count += len(series) - - return count - - def get_current_likelihood(self) -> Optional[np.ndarray]: - cur_likelihood = None - if self.inquiry_n: - cur_likelihood = self.series_results[-1][-1].fused_likelihood - - return cur_likelihood - - def to_json(self): - d = dataclasses.asdict(self) - d['series_results'] = [list(map(lambda ir: ir.to_json(), lis)) for lis in - self.series_results] - - d['decision_criterion'] = [str(dec) for dec in self.decision_criterion] - - return d - - -class StateManager(ABC): - - def update(self, evidence: Dict[str, SimEvidence]): - raise NotImplementedError() - - def is_done(self) -> bool: - raise NotImplementedError() - - def get_state(self) -> SimState: - raise NotImplementedError() - - def mutate_state(self, state_field, state_value): - pass - - def reset_state(self): - ... - - -class StateManagerImpl(StateManager): - - def __init__(self, parameters: Parameters, fuser_class=MultiplyFuser): - self.state: SimState = self.initial_state(parameters) - self.parameters = parameters - self.fuser_class: Callable[[], EvidenceFuser] = fuser_class - - self.max_inq_len = self.parameters.get('max_inq_len', 100) - - def is_done(self) -> bool: - # Determines if simulator should end (max inq or max series reached, typed target sentence) - return self.state.total_inquiry_count( - ) > self.max_inq_len or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 - - def update(self, evidence) -> InquiryResult: - """ Updating the current state based on provided evidence - - fuses prior evidence with current evidence and makes potential decision - - stores inquiry, including typing decision or lack of decision - - resets series on decision and updates target letter - """ - - fuser = self.fuser_class() - current_series: List[InquiryResult] = self.state.series_results[self.state.series_n] - prior_likelihood: Optional[np.ndarray] = current_series.pop( - ).fused_likelihood if current_series else None # most recent likelihood - - fused_likelihood = fuser.fuse(prior_likelihood, evidence) - - # finding out whether max iterations is hit or prob threshold is hit - temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, - stimuli=self.state.display_alphabet, - evidences=evidence, - fused_likelihood=fused_likelihood, - decision=None) - - # can we make decision - temp_series = copy.deepcopy(self.get_state().series_results) - temp_series[-1].append(temp_inquiry_result) - is_decidable = any( - [decider.decide(temp_series[-1]) for decider in self.state.decision_criterion]) - decision = None - - new_state = self.get_state().__dict__ - new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, - stimuli=self.state.display_alphabet, - evidences=evidence, decision=decision, - fused_likelihood=fused_likelihood) - - debug_info = [ - 'Fused Likelihoods', - f'current typed - {self.state.current_sentence}', - f'stimuli {self.state.display_alphabet}' - ] - log.debug( - f"{' | '.join(debug_info)} \n " - f"{histogram(fmt_likelihoods_for_hist(new_inquiry_result.fused_likelihood, alphabet()))}" - ) - - new_state['series_results'][self.state.series_n].append(new_inquiry_result) - if is_decidable: - # Deciding max likelihood char - decision = alphabet()[np.argmax(fused_likelihood)] # TODO abstract decision criterion - - # resetting series - new_state['series_n'] += 1 - new_state['series_results'].append([]) - new_state['inquiry_n'] = 0 - - # updating current sentence and finding next target - new_state['current_sentence'] = new_state['current_sentence'] + decision \ - if decision != BACKSPACE_CHAR else new_state['current_sentence'][:-1] - new_state['target_symbol'] = next_target_letter(new_state['current_sentence'], - self.state.target_sentence) - - else: - new_state['inquiry_n'] += 1 - - new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, - stimuli=self.state.display_alphabet, - evidences=evidence, decision=decision, - fused_likelihood=fused_likelihood) - - new_state['series_results'][self.state.series_n].append(new_inquiry_result) - - self.state = SimState(**new_state) - - return new_inquiry_result - - def get_state(self) -> SimState: - return copy.copy(self.state) - - def mutate_state(self, state_field, state_value) -> SimState: - state_dict = self.get_state().__dict__ - if state_field in state_dict: - state_dict[state_field] = state_value - self.state = SimState(**state_dict) - return self.get_state() - - raise FieldException(f"Cannot find state field {state_field}") - - def reset_state(self): - self.state = self.initial_state(self.parameters) - return self - - @staticmethod - def initial_state(parameters: Parameters = None) -> SimState: - sentence = parameters.get('task_text', "HELLO_WORLD") - target_symbol = sentence[parameters.get('spelled_letters_count', 0)] - default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] - init_stimuli = random.sample(alphabet(), 10) - - return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, - display_alphabet=init_stimuli, inquiry_n=0, series_n=0, - series_results=[[]], decision_criterion=default_criterion) - - -def format_sim_state_dump(state: SimState): - """ Formats a SimState dump to look similar to session.json """ - - # TODO finish function - - ret = state.to_json() - - # removing the 'series_results' field and replacing with formatted 'series' dict - ret.pop('series_results') - series_dict = {} - for i, series in enumerate(state.series_results): - curr_series_dict: Dict = {} - series_dict[str(i + 1)] = curr_series_dict - for inq_idx, inq in enumerate(series): - inq_dict = inq.to_json() - curr_series_dict[str(inq_idx)] = inq_dict - ret['series'] = series_dict - - return ret diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py deleted file mode 100644 index 3103f951d..000000000 --- a/bcipy/simulator/helpers/types.py +++ /dev/null @@ -1,40 +0,0 @@ -import dataclasses -from dataclasses import dataclass -from typing import Optional, List, Dict - -import numpy as np - -from bcipy.task.data import EvidenceType - - -@dataclass -class SimEvidence: - evidence_type: EvidenceType - evidence: np.ndarray - symbol_set: List[str] - - def to_json(self) -> Dict: - d = dataclasses.asdict(self) - evidence_list = self.evidence.tolist() - d['evidence'] = evidence_list - d['evidence_type'] = self.evidence_type.name - - return d - - -@dataclass -class InquiryResult: - target: Optional[str] - time_spent: int - stimuli: List - evidences: Dict[str, SimEvidence] - fused_likelihood: np.ndarray - decision: Optional[str] - - def to_json(self): - d = dataclasses.asdict(self) - - d['fused_likelihood'] = self.fused_likelihood.tolist() - d['evidences'] = {k: v.to_json() for k, v in self.evidences.items()} - - return d diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py deleted file mode 100644 index 8656301b4..000000000 --- a/bcipy/simulator/sim.py +++ /dev/null @@ -1,229 +0,0 @@ -import dataclasses -import json -import logging -import random -from time import sleep -from typing import Dict, Optional - -import numpy as np - -from bcipy.helpers import stimuli, symbols -from bcipy.helpers.parameters import Parameters -from bcipy.helpers.session import session_excel -from bcipy.helpers.symbols import alphabet -from bcipy.simulator.helpers.data_engine import DataEngine -from bcipy.simulator.helpers.log_utils import (fmt_reshaped_evidence, - fmt_stim_likelihoods) -from bcipy.simulator.helpers.metrics import MetricReferee -from bcipy.simulator.helpers.model_handler import ModelHandler -from bcipy.simulator.helpers.rsvp_utils import format_lm_output -from bcipy.simulator.helpers.sampler import Sampler -from bcipy.simulator.helpers.state_manager import (SimState, StateManager, - format_sim_state_dump) -from bcipy.simulator.helpers.types import InquiryResult, SimEvidence -from bcipy.simulator.simulator_base import Simulator -from bcipy.task.data import EvidenceType, Inquiry, Session - -log = logging.getLogger(__name__) - - -class SimulatorCopyPhrase(Simulator): - """ - - Copy Phrase simulator. - - Run loop: - - The loop runs until StateManager determines simulation is over - - The generated stimuli are passed into sampler, which returns some eeg response - - The Model handler will generate predictions and feed back into StateManager - - StateManager will resolve the state while the MetricReferee observes and records any metrics - - Main components: - - DataEngine: loading and storing data - - Sampler: logic for sampling from data, composed of DataEngine - - StateManager: manages run loop details and fuses model evidence with current state - - MetricReferee: tracks and scores the simulation on different metrics for later evaluation - - ModelHandler: wrapper for models that deals with loading in models and generating evidence - - Requirements: - - run closed loop simulation of {TaskType} with {data} with {simulation_params} - """ - - def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, parameters: Parameters, - save_dir: Optional[str] = None): - super().__init__() - - self.save_dir = save_dir - self.model_handler = model_handler - self.sampler = sampler - self.referee = referee - self.state_manager = state_manager - self.data_engine = data_engine - - self.parameters = parameters - - self.symbol_set = alphabet() - self.write_output = False - - def run(self): - assert self.save_dir, "Save directory not set" - log.info(f"SIM START with target word {self.state_manager.get_state().target_sentence}") - - session = Session( - save_location=self.save_dir, - task='Copy Phrase Simulation', - mode='RSVP', - symbol_set=self.symbol_set, - decision_threshold=self.parameters['decision_threshold']) - - while not self.state_manager.is_done(): - self.state_manager.mutate_state('display_alphabet', - self.__make_stimuli(self.state_manager.get_state())) - curr_state = self.state_manager.get_state() - - log.info( - f"Series {curr_state.series_n} | Inquiry {curr_state.inquiry_n} | " + - f"Target '{curr_state.target_symbol}' | " + - f"Stimuli {curr_state.display_alphabet}") - - sampled_data = self.sampler.sample_data(self.state_manager.get_state()) - evidence: Dict[str, SimEvidence] = self.model_handler.generate_evidence(curr_state, - sampled_data) - - log.debug( - f"EEG Evidence for stimuli {curr_state.display_alphabet} " + - f"\n {fmt_stim_likelihoods(evidence['sm'].evidence, self.symbol_set)}") - - reshaped_evidence: Dict[str, SimEvidence] = self.__reshape_evidences(evidence) - log.debug(f"Evidence Shapes {fmt_reshaped_evidence(reshaped_evidence)}") - - inq_record: InquiryResult = self.state_manager.update(reshaped_evidence) - updated_state = self.state_manager.get_state() - - data = self.new_data_record(curr_state, inq_record) - session.add_sequence(data) - - if inq_record.decision: - log.info(f"Decided {inq_record.decision} for target {inq_record.target}") - session.add_series() - - log.info(f"Current typed: {updated_state.current_sentence}") - sleep(self.parameters.get("sim_sleep_time", 0.5)) - - final_state = self.state_manager.get_state() - log.info("SIM END") - log.info(f"FINAL TYPED: {final_state.current_sentence}") - log.info(self.referee.score(self).__dict__) - - self.save_run(session) - - def has_language_model(self) -> bool: - """Indicates whether this task has been configured with a language model""" - return self.model_handler.includes_language_model() - - def __make_stimuli(self, state: SimState): - """ - Creates next set of stimuli: - - uses current likelihoods while during a series - - uses language model for beginning of series - - random letters in case of no LM and beginning of series - """ - subset_length = self.parameters['stim_length'] - priors: Optional[np.ndarray] = state.get_current_likelihood() - always_in_stimuli = [] - if self.parameters.get('backspace_always_shown', False): - always_in_stimuli.append(symbols.BACKSPACE_CHAR) - - # during series - if priors is not None: - return stimuli.best_selection(self.symbol_set, list( - priors), subset_length, always_included=always_in_stimuli) - # beginning of series - elif self.has_language_model(): - # use lang model for priors to make stim - lm_model = self.model_handler.get_model('lm') - lm_model_evidence = lm_model.predict(list(state.current_sentence)) - priors = format_lm_output(lm_model_evidence, self.symbol_set) - return stimuli.best_selection(self.symbol_set, list( - priors), subset_length, always_included=always_in_stimuli) - - return random.sample(self.symbol_set, subset_length) - - def __reshape_evidences(self, evidences: Dict[str, SimEvidence]) -> Dict[str, SimEvidence]: - - # reshaping lm_evidence to look like signal model evidence - reshaped_evidence = evidences.copy() - if "lm" in evidences: - unshaped_lm_evidence = evidences["lm"].evidence # [('B', 0.5), ('C', 0.2), ('_', 0.02)] - reshaped_lm_lik = format_lm_output(list(unshaped_lm_evidence), self.symbol_set) - reshaped_evidence['lm'] = SimEvidence(EvidenceType.LM, np.array(reshaped_lm_lik), - evidences["lm"].symbol_set) - - return reshaped_evidence - - def new_data_record(self, inquiry_state: SimState, inquiry_result: InquiryResult) -> Inquiry: - """Construct a new inquiry data record. - - Parameters - ---------- - - inquiry_state : state prior to presenting the inquiry - - inquiry_result : result of presenting the inquiry - - post_inquiry_state : updated state - - Returns - ------- - Inquiry data for the current schedule - """ - target_info = [ - 'target' if inquiry_result == sym else 'nontarget' - for sym in inquiry_result.stimuli - ] - - data = Inquiry(stimuli=inquiry_result.stimuli, - timing=[], - triggers=[], - target_info=target_info, - target_letter=inquiry_result.target, - current_text=inquiry_state.current_sentence, - target_text=inquiry_state.target_sentence) - data.precision = 4 - data.evidences = { - val.evidence_type: list(val.evidence) - for val in inquiry_result.evidences.values() - } - if EvidenceType.LM not in data.evidences: - data.evidences[EvidenceType.LM] = [] - data.likelihood = list(inquiry_result.fused_likelihood) - return data - - def save_run(self, session: Session): - """ Outputs the results of a run to json file """ - assert self.save_dir, "Save directory not set" - # creating result.json object with final state and metrics - final_state = self.state_manager.get_state() - final_state_json: Dict = format_sim_state_dump(final_state) - metric_dict = dataclasses.asdict(self.referee.score(self)) - metric_dict.update(final_state_json) # adding state data to metrics - - # writing result.json - with open(f"{self.save_dir}/result.json", 'w', - encoding='utf8') as output_file: - json.dump(metric_dict, output_file, indent=2) - - with open(f"{self.save_dir}/session.json", 'wt', - encoding='utf8') as session_file: - json.dump(session.as_dict(), session_file, indent=2) - - if session.has_evidence(): - session_excel(session=session, - excel_file=f"{self.save_dir}/session.xlsx") - - def reset(self): - self.state_manager.reset_state() - - def get_parameters(self): - return self.parameters.copy() - - def __str__(self): - return f"<{self.__class__.__name__}>" diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py deleted file mode 100644 index 25f04a218..000000000 --- a/bcipy/simulator/sim_factory.py +++ /dev/null @@ -1,61 +0,0 @@ -""" Factory for Simulator objects """ -import logging -from pathlib import Path -from typing import List - -from bcipy.helpers.load import load_json_parameters -from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME -from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.metrics import RefereeImpl, SimMetricsHandler -from bcipy.simulator.helpers.model_handler import SigLmModelHandler1 -from bcipy.simulator.helpers.sampler import TargetNontargetSampler -from bcipy.simulator.helpers.state_manager import StateManagerImpl -from bcipy.simulator.sim import Simulator, SimulatorCopyPhrase - -log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) - - -class SimulationFactory: - """ Factory class to create Simulator instances """ - - @staticmethod - def create(source_dirs: List[Path], - smodel_files: List[str], - sim_param_path="bcipy/simulator/sim_parameters.json", - save_dir=None, - **kwargs) -> Simulator: - """Create a Simulation, performing all of the necessary setup.""" - - # combining parameters - model_file = Path(smodel_files.pop()) - - sim_parameters = load_json_parameters(sim_param_path, value_cast=True) - params_path: str = kwargs.get('parameters', None) - base_parameters = load_json_parameters(params_path, value_cast=True) - base_parameters.add_missing_items(sim_parameters) - - data_engine = RawDataEngine(list(map(str, source_dirs)), - base_parameters) - state_manager = StateManagerImpl(base_parameters) - sampler = TargetNontargetSampler(data_engine) - model_handler = SigLmModelHandler1(model_file, base_parameters) - - referee = RefereeImpl(metric_handlers={'basic': SimMetricsHandler()}) - - sim = SimulatorCopyPhrase(data_engine, - model_handler, - sampler, - state_manager, - referee, - parameters=base_parameters, - save_dir=save_dir) - config = { - 'parameters_directory': Path(params_path).parent.name, - 'sampler': str(sampler), - 'model': str(model_handler), - 'task': str(sim) - } - for key, value in config.items(): - log.debug(f"{key}: {value}") - - return sim diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json deleted file mode 100644 index 7a5964642..000000000 --- a/bcipy/simulator/sim_parameters.json +++ /dev/null @@ -1,71 +0,0 @@ -{ - "sim_task": { - "value": "RSVP_COPY_PHRASE", - "section": "sim_config", - "readableName": "Simulation Task", - "helpTip": "Specifies Task to simulate", - "recommended_values": [ - "RSVP_COPY_PHRASE", - "RSVP_CALIBRATION" - ], - "type": "str" - }, - "sim_sample_mode": { - "value": "0", - "section": "sim_config", - "readableName": "Simulation Sample Mode", - "helpTip": "Specifies method for sampling based on sampling registry", - "recommended_values": [ - "0", - "1" - ], - "type": "str" - }, - "sim_sleep_time": { - "value": "0", - "section": "sim_config", - "readableName": "Simulation Time Step ", - "helpTip": "How long to sleep in between simulation time steps", - "recommended_values": [ - "0", - "0.5", - "1" - ], - "type": "float" - }, - "sim_lm_parameters": { - "value": "", - "section": "sim_config", - "readableName": "Path to language model parameter file ", - "helpTip": "", - "recommended_values": [ - "/lm_parameters.json" - ], - "type": "str" - }, - "sim_lm_type": { - "value": "UNIFORM", - "section": "sim_config", - "readableName": "Language Model Type", - "helpTip": "Specifies which language model to use. Default: UNIFORM", - "recommended_values": [ - "UNIFORM", - "CAUSAL", - "KENLM", - "MIXTURE", - "ORACLE" - ], - "type": "str" - }, - "sim_run_count": { - "value": "1", - "section": "sim_config", - "readableName": "How many times to run simulator", - "helpTip": "", - "recommended_values": [ - "1", - "5" - ], - "type": "int" - } -} \ No newline at end of file diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py deleted file mode 100644 index 30aa13fc1..000000000 --- a/bcipy/simulator/simulator_base.py +++ /dev/null @@ -1,40 +0,0 @@ -""" base simulator interface """ - -from abc import ABC, abstractmethod -from typing import Optional - -from bcipy.helpers.parameters import Parameters -from bcipy.simulator.helpers import metrics -from bcipy.simulator.helpers.data_engine import DataEngine -from bcipy.simulator.helpers.model_handler import ModelHandler -from bcipy.simulator.helpers.sampler import Sampler -from bcipy.simulator.helpers.state_manager import StateManager - - -class Simulator(ABC): - """Simulator. - - Base class for BciPy Simulations. - - Requirements: - - run closed loop simulation of {TaskType} with {data} with {simulation_params} - """ - - model_handler: ModelHandler - sampler: Sampler - state_manager: StateManager - data_engine: DataEngine - referee: metrics.MetricReferee - parameters: Parameters - save_dir: Optional[str] - - @abstractmethod - def run(self): - """ Run loop for simulation""" - - @abstractmethod - def get_parameters(self) -> Parameters: - """ retrieving parameters copy""" - - def reset(self): - ... diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 634262a8c..5e5236516 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -8,7 +8,7 @@ from bcipy.language.main import LanguageModel from bcipy.signal.model.base_model import SignalModel from bcipy.simulator.helpers.sampler import Sampler -from bcipy.simulator.helpers.state_manager import SimState +from bcipy.simulator.helpers.state import SimState from bcipy.simulator.task.null_display import NullDisplay from bcipy.task.control.evidence import EvidenceEvaluator from bcipy.task.data import EvidenceType @@ -22,20 +22,7 @@ def get_evidence_type(model: SignalModel) -> EvidenceType: return model.metadata.evidence_type or DEFAULT_EVIDENCE_TYPE -class SimTask(): - """Abstract class that marks a task as a simulation.""" - def __init__(self, parameters: Parameters, file_save: str, - signal_models: List[SignalModel], - language_model: LanguageModel, samplers: Dict[SignalModel, - Sampler]): - """Signature for a simulation task""" - - def execute(self) -> str: - """Executes the task""" - raise NotImplementedError - - -class SimulatorCopyPhraseTask(RSVPCopyPhraseTask, SimTask): +class SimulatorCopyPhraseTask(RSVPCopyPhraseTask): """CopyPhraseTask that simulates user interactions by sampling data from a DataSampler.""" @@ -140,9 +127,7 @@ def get_sim_state(self) -> SimState: display_alphabet=self.current_symbols(), # TODO: inquiry_n=0, - series_n=0, - series_results=[], - decision_criterion=[]) + series_n=0) def current_symbols(self) -> List[str]: """Get the list of symbols from the current inquiry.""" diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py index 92c898d5e..5558eafe4 100644 --- a/bcipy/simulator/task/task_factory.py +++ b/bcipy/simulator/task/task_factory.py @@ -8,7 +8,7 @@ from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.data_process import init_data_processor from bcipy.simulator.helpers.sampler import Sampler, TargetNontargetSampler -from bcipy.simulator.task.copy_phrase import SimTask, SimulatorCopyPhraseTask +from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) @@ -22,7 +22,7 @@ def __init__(self, model_path: str, source_dirs: List[str], sampling_strategy: Type[Sampler] = TargetNontargetSampler, - task: Type[SimTask] = SimulatorCopyPhraseTask): + task: Type[SimulatorCopyPhraseTask] = SimulatorCopyPhraseTask): self.params_path = params_path self.model_path = model_path self.source_dirs = source_dirs @@ -62,7 +62,7 @@ def init_samplers(self, signal_models: List[SignalModel]) -> Dict[SignalModel, S samplers[model] = sampler return samplers - def make_task(self, run_dir: str) -> SimTask: + def make_task(self, run_dir: str) -> SimulatorCopyPhraseTask: """Construct a new task""" return self.simulation_task(self.parameters, file_save=run_dir, diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index d8e9d7144..9e7f6c6f0 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -70,7 +70,7 @@ def main(): "--model_path", type=Path, required=True, - help="Signal model to be used") + help="Signal models to be used") parser.add_argument("-p", "--parameters", type=Path, From c0fb47ee7ccdd2a3a2228fe2faec1bc9943625d7 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Sep 2024 11:24:40 -0700 Subject: [PATCH 300/330] Improved documentation --- bcipy/simulator/README.md | 32 ++++++++++++++++++++----- bcipy/simulator/helpers/data_engine.py | 5 ++-- bcipy/simulator/helpers/data_process.py | 9 +++++-- bcipy/simulator/task/null_display.py | 3 ++- bcipy/simulator/task/task_factory.py | 1 + 5 files changed, 38 insertions(+), 12 deletions(-) diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index bba55404e..e99fc2f4e 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -2,7 +2,7 @@ ### Overview -This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and running given models in RSVP task loop, thus simulating a live session. +This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and running given models in a task loop, thus simulating a live session. ### Run steps @@ -28,23 +28,43 @@ optional arguments: #### Program Args - `d` : the data wrapper folder argument is necessary. This folder is expected to contain 1 or more session folders. Each session folder should contain - _raw_data.csv_, _triggers.txt_, _parameters.json_. These files will be used to construct data pool from which simulator will sample EEG responses. -- `g` : optional glob filter that can be used to select a subset of data. + _raw_data.csv_, _triggers.txt_, _parameters.json_. These files will be used to construct a data pool from which simulator will sample EEG and other device responses. The parameters file in each data folder will be used to check compatibility with the simulation/model parameters. +- `g` : optional glob filter that can be used to select a subset of data within the wrapper directory. - Ex. `"*Matrix_Copy*Jan_2024*"` will select all data for all Matrix Copy Phrase sessions recorded in January of 2024 (assuming the BciPy folder naming convention). - Glob patterns can also include nested directories (ex. `"*/*Matrix_Copy*"`). - `p` : path to the parameters.json file used to run the simulation. These parameters will be applied to - all raw_data files when loading. + all raw_data files when loading. This file can specify various aspects of the simulation, including the language model to be used, the text to be spelled, etc. Timing-related parameters should generally match the parameters file used for training the signal model(s). - `m`: all pickle (.pkl) files in this directory will be loaded as signal models. #### Sim Output Details Output folders are generally located in the `simulator/generated` directory. Each simulation will create a new directory. The directory name will be prefixed with `SIM` and will include the current date and time. -- `parameters.json` captures params used for the simulation +- `parameters.json` captures params used for the simulation. - `sim.log` is a log file for the simulation A directory is created for each simulation run. The directory contents are similar to the session output in a normal bcipy task. Each run directory contains: -- `run_n.log` log file specific to the run +- `run_{n}.log` log file specific to the run, where n is the run number. - `session.json` session data output for the task, including evidence generated for each inquiry and overall metrics. - `session.xlsx` session data summarized in an excel spreadsheet with charts for easier visualization. + +## Main Components + +* Task - a simulation task to be run (ex. RSVP Copy Phrase) +* TaskRunner - runs one or more iterations of a simulation +* TaskFactory - constructs the hierarchy of objects needed for the simulation. +* DataEngine - loads data to be used in a simulation and provides an API to query for data. +* DataProcessor - used by the DataEngine to pre-process data. Pre-processed data can be classified by a signal model. +* Sampler - strategy for sampling data from the data pool stored in the DataEngine. + +## Device Support + +The simulator is structured to support evidence from multiple devices (multimodal). However, it currently only includes processing for EEG device data. To provide support for models trained on data from other devices (ex. Gaze), a `RawDataProcessor` must be added for that device. The Processor pre-processes data collected from that device and prepares it for sampling. A `RawDataProcessor` is matched up to a given signal model using that model's metadata (metadata.device_spec.content_type). See the `data_process` module for more details. + +## Current Limitations + +* Only provides EEG support +* Only one sampler maybe provided for all devices. Ideally we should support a different sampling strategy for each device. +* Only the RSVP Copy Phrase may be simulated +* Metrics are collected per run, but not summarized across all runs. \ No newline at end of file diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 52ef246ed..61b48fb7d 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,3 +1,4 @@ +"""Classes and functions related to loading and querying data to be used in a simulation.""" import logging from abc import ABC, abstractmethod from pathlib import Path @@ -19,8 +20,6 @@ class Trial(NamedTuple): """Data for a given trial (a symbol within an Inquiry). - TODO: add series to facilitate easier lookup in session data. - Attrs ----- source - directory of the data source @@ -51,7 +50,7 @@ def __repr__(self): class QueryFilter(NamedTuple): - """Used to query for data.""" + """Provides an API used to query a data engine for data.""" field: str operator: str value: Any diff --git a/bcipy/simulator/helpers/data_process.py b/bcipy/simulator/helpers/data_process.py index a45c8f29c..86485fa8a 100644 --- a/bcipy/simulator/helpers/data_process.py +++ b/bcipy/simulator/helpers/data_process.py @@ -1,4 +1,4 @@ -"""This defines functionality related to pre-processing simulation data. +"""This module defines functionality related to pre-processing simulation data. Processed data can be subsequently sampled and provided to a SignalModel for classification.""" @@ -187,6 +187,10 @@ class RawDataProcessor(): """Processes raw data for a given device and converts it to ExtractedExperimentData for use in the simulator. + The main API method, `process`, provides a template method that can be + specialized by subclasses. This method performs the following for a given + data directory. + 1. Loads the data file as a RawData object 2. Extract timing information from trigger file based on the device of interest. 3. Reshape and label the data. @@ -253,7 +257,7 @@ def check_data_compatibility(self, data_device: DeviceSpec, def process(self, data_folder: str, parameters: Parameters) -> ExtractedExperimentData: - """Load and process the data + """Load and process the data. Parameters ---------- @@ -422,6 +426,7 @@ def get_transform(self, transform_params: ERPTransformParams, ) +## Module functions for matching a model to the correct processor. def get_processor( data_source: ContentType, evidence_type: Optional[EvidenceType] = None diff --git a/bcipy/simulator/task/null_display.py b/bcipy/simulator/task/null_display.py index fb5767e6c..e59c07f02 100644 --- a/bcipy/simulator/task/null_display.py +++ b/bcipy/simulator/task/null_display.py @@ -5,7 +5,8 @@ class NullDisplay(Display): - """Display that doesn't show anything to the user.""" + """Display that doesn't show anything to the user. Useful in simulated tasks + that do not have a display component.""" def do_inquiry(self) -> List[Tuple[str, float]]: return [] diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py index 5558eafe4..8d08ac750 100644 --- a/bcipy/simulator/task/task_factory.py +++ b/bcipy/simulator/task/task_factory.py @@ -1,3 +1,4 @@ +"""Classes and functions for building a simulation.""" import logging from typing import Dict, List, Type From 36ebc40b4a0efed6e713d710fb22eb940b069aaa Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Sep 2024 11:41:59 -0700 Subject: [PATCH 301/330] Set simulator output to data folder. Re-organized modules --- .gitignore | 1 - bcipy/simulator/generated/.gitkeep | 0 bcipy/simulator/helpers/artifact.py | 4 +- bcipy/simulator/helpers/data_engine.py | 201 --------- bcipy/simulator/helpers/data_process.py | 475 ---------------------- bcipy/simulator/helpers/log_utils.py | 8 - bcipy/simulator/helpers/sampler.py | 225 ---------- bcipy/simulator/task/copy_phrase.py | 2 +- bcipy/simulator/task/task_factory.py | 6 +- bcipy/simulator/task/task_runner.py | 2 +- bcipy/simulator/tests/test_data_engine.py | 6 +- 11 files changed, 10 insertions(+), 920 deletions(-) delete mode 100644 bcipy/simulator/generated/.gitkeep delete mode 100644 bcipy/simulator/helpers/data_engine.py delete mode 100644 bcipy/simulator/helpers/data_process.py delete mode 100644 bcipy/simulator/helpers/log_utils.py delete mode 100644 bcipy/simulator/helpers/sampler.py diff --git a/.gitignore b/.gitignore index f1e72aded..54fabb0bf 100644 --- a/.gitignore +++ b/.gitignore @@ -37,4 +37,3 @@ bcipy/language/out/ bcipy/simulator/tests/resource/ -bcipy/simulator/generated/SIM_* diff --git a/bcipy/simulator/generated/.gitkeep b/bcipy/simulator/generated/.gitkeep deleted file mode 100644 index e69de29bb..000000000 diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 8338fa89e..b828adc42 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -5,14 +5,14 @@ import sys from typing import Optional -from bcipy.config import BCIPY_ROOT +from bcipy.config import ROOT # For a simulation, two loggers are configured: a top level logger summarizing # setup and progress, and a logger for each simulation run. The root logger is # re-configured for each simulation run. TOP_LEVEL_LOGGER_NAME = 'sim_logger' DEFAULT_LOGFILE_NAME = 'sim.log' -DEFAULT_SAVE_LOCATION = f"{BCIPY_ROOT}/simulator/generated" +DEFAULT_SAVE_LOCATION = f"{ROOT}/data/simulator" def configure_logger(log_path: str, diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py deleted file mode 100644 index 61b48fb7d..000000000 --- a/bcipy/simulator/helpers/data_engine.py +++ /dev/null @@ -1,201 +0,0 @@ -"""Classes and functions related to loading and querying data to be used in a simulation.""" -import logging -from abc import ABC, abstractmethod -from pathlib import Path -from typing import Any, List, NamedTuple, Union - -import numpy as np -import pandas as pd - -from bcipy.helpers.exceptions import TaskConfigurationException -from bcipy.helpers.parameters import Parameters -from bcipy.simulator.helpers import data_process -from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME -from bcipy.simulator.helpers.data_process import (ExtractedExperimentData, - RawDataProcessor) - -log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) - - -class Trial(NamedTuple): - """Data for a given trial (a symbol within an Inquiry). - - Attrs - ----- - source - directory of the data source - inquiry_n - starts at 0; does not reset at each series - inquiry_pos - starts at 1; position in which the symbol was presented - symbol - alphabet symbol that was presented - target - 1 or 0 indicating a boolean of whether this was a target symbol - eeg - EEG data associated with this trial - """ - source: str - # series_n: int - inquiry_n: int - inquiry_pos: int - symbol: str - target: int - eeg: np.ndarray # Channels by Samples ; ndarray.shape = (channel_n, sample_n) - - def __str__(self): - fields = [ - f"source='{self.source}'", f"inquiry_n={self.inquiry_n}", - f"inquiry_pos={self.inquiry_pos}", f"symbol='{self.symbol}'", - f"target={self.target}", f"eeg={self.eeg.shape}" - ] - return f"Trial({', '.join(fields)})" - - def __repr__(self): - return str(self) - - -class QueryFilter(NamedTuple): - """Provides an API used to query a data engine for data.""" - field: str - operator: str - value: Any - - def is_valid(self) -> bool: - """Check if the filter is valid.""" - # pylint: disable=no-member - return self.field in Trial._fields and self.operator in self.valid_operators and isinstance( - self.value, Trial.__annotations__[self.field]) - - @property - def valid_operators(self) -> List[str]: - """List of supported query operators""" - return ["<", "<=", ">", ">=", "==", "!="] - - -class DataEngine(ABC): - """Abstract class for an object that loads data from one or more sources, - processes the data using a provided processor, and provides an interface - for querying the processed data.""" - - def load(self): - """Load data from sources.""" - - @property - def trials_df(self) -> pd.DataFrame: - """Returns a dataframe of Trial data.""" - - @abstractmethod - def query(self, - filters: List[QueryFilter], - samples: int = 1) -> List[Trial]: - """Query the data.""" - - -def convert_trials(data_source: ExtractedExperimentData) -> List[Trial]: - """Convert extracted data from a single data source to a list of Trials.""" - trials = [] - symbols_by_inquiry = data_source.symbols_by_inquiry - labels_by_inquiry = data_source.labels_by_inquiry - - for i, inquiry_eeg in enumerate(data_source.trials_by_inquiry): - # iterate through each inquiry - inquiry_symbols = symbols_by_inquiry[i] - inquiry_labels = labels_by_inquiry[i] - - for sym_i, symbol in enumerate(inquiry_symbols): - # iterate through each symbol in the inquiry - eeg_samples = [channel[sym_i] - for channel in inquiry_eeg] # (channel_n, sample_n) - trials.append( - Trial(source=data_source.source_dir, - inquiry_n=i, - inquiry_pos=sym_i + 1, - symbol=symbol, - target=inquiry_labels[sym_i], - eeg=np.array(eeg_samples))) - return trials - - -class RawDataEngine(DataEngine): - """ - Object that loads in list of session data folders and transforms data into - a queryable data structure. - """ - - def __init__(self, source_dirs: List[str], parameters: Parameters, - data_processor: RawDataProcessor): - self.source_dirs: List[str] = source_dirs - self.parameters: Parameters = parameters - - self.data_processor = data_processor - self.data: List[Union[ExtractedExperimentData, - data_process.ExtractedExperimentData]] = [] - self._trials_df = pd.DataFrame() - - self.load() - - def load(self) -> DataEngine: - """ - Processes raw data from data folders using provided parameter files. - - Extracts and stores trial data, stimuli, and stimuli_labels by inquiries - - Returns: - self for chaining - """ - if not self.data: - log.debug( - f"Loading data from {len(self.source_dirs)} source directories:" - ) - rows = [] - for i, source_dir in enumerate(self.source_dirs): - log.debug(f"{i+1}. {Path(source_dir).name}") - extracted_data = self.data_processor.process( - source_dir, self.parameters) - self.data.append(extracted_data) - rows.extend(convert_trials(extracted_data)) - - self._trials_df = pd.DataFrame(rows) - log.debug("Finished loading all data") - return self - - @property - def trials_df(self) -> pd.DataFrame: - """Dataframe of Trial data.""" - if not self.data_loaded: - self.load() - return self._trials_df.copy() - - @property - def data_loaded(self) -> bool: - """Check if the data has been loaded""" - return bool(self.data) - - def query(self, - filters: List[QueryFilter], - samples: int = 1) -> List[Trial]: - """Query the engine for data using one or more filters. - - Parameters - ---------- - filters - list of query filters - samples - number of results to return. - check_insufficient_results - if True, raises an exception when - there are an insufficient number of samples. - - Returns a list of Trials. - """ - assert self.data_loaded, "Data must be loaded before querying." - assert all(filt.is_valid() - for filt in filters), "Filters must all be valid" - assert samples >= 1, "Insufficient number of samples requested" - - expr = 'and '.join([self.query_condition(filt) for filt in filters]) - filtered_data = self._trials_df.query(expr) - if filtered_data is None or len(filtered_data) < samples: - raise TaskConfigurationException( - message="Not enough samples found") - - rows = filtered_data.sample(samples) - return [Trial(*row) for row in rows.itertuples(index=False, name=None)] - - def query_condition(self, query_filter: QueryFilter) -> str: - """Returns the string representation of of the given query condition.""" - value = query_filter.value - if (isinstance(value, str)): - value = f"'{value}'" - return f"{query_filter.field} {query_filter.operator} {value}" diff --git a/bcipy/simulator/helpers/data_process.py b/bcipy/simulator/helpers/data_process.py deleted file mode 100644 index 86485fa8a..000000000 --- a/bcipy/simulator/helpers/data_process.py +++ /dev/null @@ -1,475 +0,0 @@ -"""This module defines functionality related to pre-processing simulation data. -Processed data can be subsequently sampled and provided to a SignalModel -for classification.""" - -import logging as logger -from dataclasses import dataclass -from pathlib import Path -from typing import List, NamedTuple, Optional, Tuple, Type - -import numpy as np - -from bcipy.acquisition import devices -from bcipy.acquisition.devices import DeviceSpec -from bcipy.acquisition.multimodal import ContentType -from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, - DEFAULT_PARAMETER_FILENAME, TRIGGER_FILENAME) -from bcipy.helpers.acquisition import analysis_channels, raw_data_filename -from bcipy.helpers.list import grouper -from bcipy.helpers.load import load_json_parameters, load_raw_data -from bcipy.helpers.parameters import Parameters -from bcipy.helpers.raw_data import RawData -from bcipy.helpers.stimuli import update_inquiry_timing -from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.signal.model.base_model import SignalModel -from bcipy.signal.process import (ERPTransformParams, filter_inquiries, - get_default_transform) -from bcipy.signal.process.transform import Composition -from bcipy.simulator.exceptions import (DeviceSpecNotFoundError, - IncompatibleDeviceSpec, - IncompatibleParameters) -from bcipy.task.data import EvidenceType - -log = logger.getLogger(__name__) - - -def load_device_data(data_folder: str, - content_type: str) -> Tuple[RawData, DeviceSpec]: - """Loads the data into the RawData format for the given content type. - - Parameters - ---------- - data_folder - session data folder with the raw data, device_spec, etc. - content_type - content type of the data to load. - - Returns - ------- - tuple of the raw data and the associated DeviceSpec for the device used - to record that data. - """ - devices_by_name = devices.load(Path(data_folder, - DEFAULT_DEVICE_SPEC_FILENAME), - replace=True) - specs = [ - spec for spec in devices_by_name.values() - if spec.is_active and spec.content_type == content_type - ] - if not specs: - raise DeviceSpecNotFoundError( - f"Suitable entry not found in {data_folder}/devices.json") - device_spec = specs[0] - raw_data_path = Path(data_folder, raw_data_filename(device_spec)) - if not raw_data_path.exists(): - raise FileNotFoundError(f"Raw data file not found: {raw_data_path}") - raw_data = load_raw_data(str(raw_data_path)) - - if device_spec != devices.preconfigured_device(raw_data.daq_type): - raise IncompatibleDeviceSpec( - "DeviceSpec in devices.json does not match the raw data.") - - return raw_data, device_spec - - -class DecodedTriggers(NamedTuple): - """Extracted properties after decoding the triggers.txt file and applying - the necessary offsets and corrections.""" - targetness: List[str] # TriggerType - times: List[float] - symbols: List[str] # symbol - corrected_times: List[float] - - -@dataclass() -class ExtractedExperimentData: - """Data from an acquisition device after reshaping and filtering.""" - source_dir: str - inquiries: np.ndarray - trials: np.ndarray - labels: List - inquiry_timing: List - - decoded_triggers: DecodedTriggers - trials_per_inquiry: int - - @property - def trials_by_inquiry(self) -> List[np.ndarray]: - """EEG data by inquiry. - shape (i_inquiry, n_channel, m_trial, x_sample) - """ - return np.split(self.trials, self.inquiries.shape[1], 1) - - @property - def symbols_by_inquiry(self) -> List[List[str]]: - """Get symbols by inquiry. shape (i_inquiry, s_alphabet_subset)""" - trigger_symbols = self.decoded_triggers.symbols - return [ - list(group) for group in grouper( - trigger_symbols, self.trials_per_inquiry, incomplete="ignore") - ] - - @property - def labels_by_inquiry(self) -> List[List[int]]: - """Shape (i_inquiry, s_alphabet_subset)""" - return self.labels - - -class TimingParams(NamedTuple): - """Timing-related parameters used in parsing the raw data into inquiries and trials.""" - # window (in seconds) of data collection after each stimulus presentation. - trial_window: Tuple[float, float] - # seconds before the start of the inquiry to use. - prestim_length: float - - # delay time (in seconds) between the final stimulus in one inquiry and the - # beginning (target stimulus or fixation cross) of the next inquiry. - task_buffer_length: float - stim_length: int - time_flash: float - - @property - def trials_per_inquiry(self) -> int: - """Alias for stim_length""" - return self.stim_length - - @property - def buffer(self) -> float: - """The task buffer length defines the min time between two inquiries - We use half of that time here to buffer during transforms""" - return self.task_buffer_length / 2 - - @property - def window_length(self) -> float: - """window (in seconds) of data collection after each stimulus presentation""" - start, end = self.trial_window - return end - start - - def __str__(self): - return ( - f"Timing settings: \n" - f"Trial Window: {self.trial_window[0]} to {self.trial_window[1]}s, " - f"Prestimulus Buffer: {self.prestim_length}s, Poststimulus Buffer: {self.buffer}s \n" - ) - - -def decode_triggers( - data_folder: str, - timing_params: TimingParams, - device_offset: float = 0.0, - excluded_triggers: Optional[List[TriggerType]] = None -) -> DecodedTriggers: - """Decode the triggers.txt file in the given directory.""" - if not excluded_triggers: - excluded_triggers = [ - TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION - ] - targetness, times, symbols = trigger_decoder( - offset=device_offset, - trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=excluded_triggers, - ) - corrected = [time + timing_params.trial_window[0] for time in times] - return DecodedTriggers(targetness=targetness, - times=times, - symbols=symbols, - corrected_times=corrected) - - -class ReshapedData(): - """Represents data components after reshaping""" - - def __init__(self): - self.inquiries: np.ndarray = np.array([]) - self.inquiry_labels: np.ndarray = np.array([]) - self.inquiry_timing: List[List[int]] = [] - - -class RawDataProcessor(): - """Processes raw data for a given device and converts it to - ExtractedExperimentData for use in the simulator. - - The main API method, `process`, provides a template method that can be - specialized by subclasses. This method performs the following for a given - data directory. - - 1. Loads the data file as a RawData object - 2. Extract timing information from trigger file based on the device of interest. - 3. Reshape and label the data. - 4. Apply filtering. - 5. Extract trials. - - Parameters - ---------- - model - signal model which will be used to classify the resulting data - """ - - def __init__(self, model: SignalModel): - self.check_model_compatibility(model) - self.model = model - - @property - def consumes(self) -> ContentType: - """ContentType of the data that should be input""" - - @property - def produces(self) -> EvidenceType: - """Type of evidence that is output""" - raise NotImplementedError - - @property - def content_type(self): - """Get the content_type of the data.""" - return self.consumes - - @property - def model_device(self) -> DeviceSpec: - """Device used to collect data for training the model.""" - return self.model.metadata.device_spec - - @property - def reshaper(self): - """data reshaper""" - return self.model.reshaper - - def check_model_compatibility(self, model: SignalModel) -> None: - """Check that the given model is compatible with this processor. - Checked on initialization.""" - assert model.metadata, "Metadata missing from signal model." - assert ContentType( - model.metadata.device_spec.content_type - ) == self.consumes, "DataProcessor is not compatible with the given model" - - def check_data_compatibility(self, data_device: DeviceSpec, - sim_timing_params: TimingParams, - data_timing_params: TimingParams) -> None: - """Check the compatibility of a dataset with the model.""" - if not self.devices_compatible(self.model_device, data_device): - raise IncompatibleDeviceSpec("Devices are not compatible") - if not self.parameters_compatible(sim_timing_params, - data_timing_params): - raise IncompatibleParameters( - "Timing parameters are not compatible") - - if data_device.static_offset == devices.DEFAULT_STATIC_OFFSET: - log.warning(' '.join([ - f"Using the default static offset to decode triggers for {data_device.name}.", - "Please make sure the correct offset is included in the devices.json file." - ])) - - def process(self, data_folder: str, - parameters: Parameters) -> ExtractedExperimentData: - """Load and process the data. - - Parameters - ---------- - data_folder - session directory for a given dataset - (contains raw_data, devices.json, and parameters.json). - parameters - parameters.json file for the calibration session used - to train the model / run the simulation. - """ - raw_data, device_spec = load_device_data(data_folder, - self.content_type.name) - data_parameters = load_json_parameters( - f"{data_folder}/{DEFAULT_PARAMETER_FILENAME}", value_cast=True) - - timing_params = parameters.instantiate(TimingParams) - - self.check_data_compatibility( - data_device=device_spec, - sim_timing_params=timing_params, - data_timing_params=data_parameters.instantiate(TimingParams)) - - decoded_triggers = decode_triggers(data_folder, timing_params, - device_spec.static_offset, - self.excluded_triggers()) - - reshaped_data = self.reshape_data(raw_data, decoded_triggers, - timing_params) - - filtered_reshaped_data, new_sample_rate = self.apply_filters( - reshaped_data, parameters, raw_data.sample_rate) - - trials = self.extract_trials(filtered_reshaped_data, timing_params, - new_sample_rate) - return ExtractedExperimentData( - data_folder, - filtered_reshaped_data.inquiries, - trials, - [list(arr) for arr in filtered_reshaped_data.inquiry_labels], - filtered_reshaped_data.inquiry_timing, - decoded_triggers=decoded_triggers, - trials_per_inquiry=timing_params.trials_per_inquiry) - - def reshape_data(self, raw_data: RawData, - decoded_triggers: DecodedTriggers, - timing_params: TimingParams) -> ReshapedData: - """Use the configured reshaper to reshape the data.""" - raise NotImplementedError - - def apply_filters(self, reshaped_data: ReshapedData, - parameters: Parameters, - data_sample_rate: int) -> Tuple[ReshapedData, int]: - """Apply any filters to the reshaped data. - - Returns - ------- - inquiry data after filtering, updated sample_rate - """ - raise NotImplementedError - - def extract_trials(self, filtered_reshaped_data: ReshapedData, - timing_params: TimingParams, - updated_sample_rate: float) -> np.ndarray: - """Extract trial data from the filtered, reshaped data. - - Returns - ------- - np.ndarray of shape (Channels, Trials, Samples) - """ - raise NotImplementedError - - def excluded_triggers(self): - """Trigger types to exclude when decoding""" - return [TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION] - - def devices_compatible(self, model_device: DeviceSpec, - data_device: DeviceSpec) -> bool: - """Check compatibility between the device on which the model was trained - and the device used for data collection.""" - - # TODO: check analysis channels? - return model_device.sample_rate == data_device.sample_rate - - def parameters_compatible(self, sim_timing_params: TimingParams, - data_timing_params: TimingParams) -> bool: - """Check compatibility between the parameters used for simulation and - those used for data collection.""" - return sim_timing_params.time_flash == data_timing_params.time_flash - - -class EegRawDataProcessor(RawDataProcessor): - """RawDataProcessor that processes EEG data.""" - consumes = ContentType.EEG - produces = EvidenceType.ERP - - def reshape_data(self, raw_data: RawData, - decoded_triggers: DecodedTriggers, - timing_params: TimingParams) -> ReshapedData: - """Use the configured reshaper to reshape the data.""" - - data, _fs = raw_data.by_channel() - channel_map = analysis_channels(raw_data.channels, self.model_device) - inquiries, inquiry_labels, inquiry_timing = self.reshaper( - trial_targetness_label=decoded_triggers.targetness, - timing_info=decoded_triggers.corrected_times, - eeg_data=data, - sample_rate=raw_data.sample_rate, - trials_per_inquiry=timing_params.trials_per_inquiry, - channel_map=channel_map, - poststimulus_length=timing_params.window_length, - prestimulus_length=timing_params.prestim_length, - transformation_buffer=timing_params.buffer, - ) - reshaped = ReshapedData() - reshaped.inquiries = inquiries - reshaped.inquiry_labels = inquiry_labels - reshaped.inquiry_timing = inquiry_timing - return reshaped - - def apply_filters(self, reshaped_data: ReshapedData, - parameters: Parameters, - data_sample_rate: int) -> Tuple[ReshapedData, int]: - """Apply any filters to the reshaped data. - - Returns - ------- - inquiry data after filtering, updated sample_rate - """ - transform_params = parameters.instantiate(ERPTransformParams) - transform = self.get_transform(transform_params, data_sample_rate) - inquiries, fs = filter_inquiries(reshaped_data.inquiries, transform, - data_sample_rate) - inquiry_timing_ints: List[List[int]] = [ - list(map(int, inq)) for inq in reshaped_data.inquiry_timing - ] - filtered_reshaped_data = ReshapedData() - filtered_reshaped_data.inquiries = inquiries - filtered_reshaped_data.inquiry_timing = update_inquiry_timing( - inquiry_timing_ints, transform_params.down_sampling_rate) - filtered_reshaped_data.inquiry_labels = reshaped_data.inquiry_labels - return filtered_reshaped_data, fs - - def extract_trials(self, filtered_reshaped_data: ReshapedData, - timing_params: TimingParams, - updated_sample_rate: float) -> np.ndarray: - """Extract trial data from the filtered, reshaped data. - - Returns - ------- - np.ndarray of shape (Channels, Trials, Samples) - """ - trial_duration_samples = int(timing_params.window_length * - updated_sample_rate) - return self.reshaper.extract_trials( - filtered_reshaped_data.inquiries, trial_duration_samples, - filtered_reshaped_data.inquiry_timing) - - def get_transform(self, transform_params: ERPTransformParams, - data_sample_rate: int) -> Composition: - """"Get the transform used for filtering the data.""" - return get_default_transform( - sample_rate_hz=data_sample_rate, - notch_freq_hz=transform_params.notch_filter_frequency, - bandpass_low=transform_params.filter_low, - bandpass_high=transform_params.filter_high, - bandpass_order=transform_params.filter_order, - downsample_factor=transform_params.down_sampling_rate, - ) - - -## Module functions for matching a model to the correct processor. -def get_processor( - data_source: ContentType, - evidence_type: Optional[EvidenceType] = None -) -> Type[RawDataProcessor]: - """Returns the matching processor class. - - Parameters - ---------- - data_source - type of data that the processor should consume - evidence_type - type of evidence that the processor should produce. - """ - matches = [ - cls for cls in RawDataProcessor.__subclasses__() - if cls.consumes == data_source and ( - evidence_type is None or cls.produces == evidence_type) - ] - if matches: - return matches[0] - else: - msg = f"Data processor not found for {data_source.name}" - if evidence_type: - msg += f" -> {evidence_type.name}" - raise Exception(msg) - - -def find_data_processor(model: SignalModel) -> Type[RawDataProcessor]: - """Get the DataProcessor appropriate for the given model.""" - content_type = ContentType(model.metadata.device_spec.content_type) - # Metadata may provide an EvidenceType with a model so the same data source can - # be used to produce multiple types of evidence (ex. alpha) - evidence_type = None - model_output = model.metadata.evidence_type - if model_output: - try: - evidence_type = EvidenceType(model_output.upper()) - except ValueError: - logger.error(f"Unsupported evidence type: {model_output}") - - return get_processor(content_type, evidence_type) - - -def init_data_processor(signal_model: SignalModel) -> RawDataProcessor: - """Find an DataProcessor that matches the given signal_model and - initialize it.""" - processor_class = find_data_processor(signal_model) - return processor_class(signal_model) diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py deleted file mode 100644 index 50ee084cd..000000000 --- a/bcipy/simulator/helpers/log_utils.py +++ /dev/null @@ -1,8 +0,0 @@ -from typing import List - -from bcipy.simulator.helpers.data_engine import Trial - - -def format_samples(sample_rows: List[Trial]) -> str: - """Returns a tabular representation of the sample rows.""" - return '\n'.join([str(row) for row in sample_rows]) diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py deleted file mode 100644 index d889f4bc3..000000000 --- a/bcipy/simulator/helpers/sampler.py +++ /dev/null @@ -1,225 +0,0 @@ -import logging -import random -from abc import ABC -from collections import defaultdict -from pathlib import Path -from typing import Callable, Dict, List, Tuple - -import numpy as np -import pandas as pd - -from bcipy.simulator.helpers.data_engine import (QueryFilter, RawDataEngine, - Trial) -from bcipy.simulator.helpers.log_utils import format_samples -from bcipy.simulator.helpers.state import SimState - -log = logging.getLogger(__name__) - - -def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: - """Default data reshaper. - - Returns - ------- - ndarray with shape (channel_n, trial_n, sample_n) - """ - - channels_eeg: List[List[np.ndarray]] = [ - [] for i in range(len(eeg_responses[0])) - ] - - for _i, trial_channels_eeg in enumerate(eeg_responses): - for c_i, channel_eeg in enumerate(trial_channels_eeg): - channels_eeg[c_i].append(channel_eeg) - - return np.array(channels_eeg) - - -class Sampler(ABC): - """Represents a strategy for sampling signal model data from a DataEngine - comprised of signal data from one or more data collection sessions.""" - - def __init__(self, data_engine: RawDataEngine): - self.data_engine: RawDataEngine = data_engine - self.model_input_reshaper: Callable = default_reshaper - - def sample(self, state: SimState) -> List[Trial]: - """ - Query the data engine for a list of trials corresponding to each - currently displayed symbol. - - Parameters - ---------- - state - specifies the target symbol and current inquiry (displayed symbols). - - Returns - ------- - a list of Trials with an item for each symbol in the current inquiry. - """ - raise NotImplementedError - - def sample_data(self, state: SimState) -> np.ndarray: - """ - Query for trials and reshape for signal model input according to the - provided reshaper. - - Return: - ndarray of shape (n_channel, n_trial, n_sample) - """ - trials = self.sample(state) - return self.reshaped(trials) - - def sample_with_context(self, - state: SimState) -> Tuple[np.ndarray, List[Trial]]: - """ - Returns - ------- - A tuple of the reshaped data (ndarray of shape (n_channel, n_trial, n_sample)) as - well as a list of Trial data (metadata and data not reshaped) for context. - """ - trials = self.sample(state) - data = self.reshaped(trials) - return data, trials - - def reshaped(self, sample_rows: List[Trial]) -> np.ndarray: - """Returns the queried trials reshaped into a format that a model can predict.""" - return self.model_input_reshaper([trial.eeg for trial in sample_rows]) - - def set_reshaper(self, reshaper: Callable): - """Set the reshaper""" - self.model_input_reshaper = reshaper - - def __str__(self): - return f"<{self.__class__.__name__}>" - - -class TargetNontargetSampler(Sampler): - """Sampler that that queries based on target/non-target label.""" - - def sample(self, state: SimState) -> List[Trial]: - sample_rows = [] - for symbol in state.display_alphabet: - filters = self.query_filters( - symbol, is_target=(symbol == state.target_symbol)) - filtered_data = self.data_engine.query(filters, samples=1) - sample_rows.append(filtered_data[0]) - - log.debug(f"Samples:\n{format_samples(sample_rows)}") - return sample_rows - - def query_filters(self, symbol: str, is_target: bool) -> List[QueryFilter]: - """Expression used to query for a single sample.""" - # QueryFilter('symbol', '==', symbol) - return [QueryFilter('target', '==', int(is_target))] - - -class InquirySampler(Sampler): - """Samples an inquiry of data at a time.""" - - def __init__(self, data_engine: RawDataEngine): - super().__init__(data_engine) - - # map source to inquiry numbers - self.data = self.data_engine.trials_df - self.target_inquiries, self.no_target_inquiries = self.prepare_data( - self.data) - - def prepare_data( - self, data: pd.DataFrame - ) -> Tuple[Dict[Path, List[int]], Dict[Path, List[int]]]: - """Partition the data into those inquiries that displayed the target - and those that did not. The resulting data structures map the data - source with a list of inquiry_n numbers.""" - - target_inquiries = defaultdict(list) - no_target_inquiries = defaultdict(list) - - # TODO: there is probably a more optimal way to use pandas to compute. - # Look into groupby. - for source in data['source'].unique(): - source_df = data[data['source'] == source] - for n in source_df['inquiry_n'].unique(): - inquiry_df = source_df[source_df['inquiry_n'] == n] - has_target = inquiry_df[inquiry_df['target'] == - 1]['target'].any() - - if has_target: - target_inquiries[source].append(n) - else: - no_target_inquiries[source].append(n) - - return target_inquiries, no_target_inquiries - - def sample(self, state: SimState) -> List[Trial]: - """Samples a random inquiry for a random data source. - - Ensures that if a target is shown in the current inquiry the sampled - data will be from an inquiry where the target was presented. - - Parameters - ---------- - state - specifies the target symbol and current inquiry (displayed symbols). - - Returns - ------- - a list of Trials with an item for each symbol in the current - inquiry. - """ - - target_letter = state.target_symbol - inquiry_letter_subset = state.display_alphabet - - if target_letter in inquiry_letter_subset: - source_inquiries = self.target_inquiries - target_position = inquiry_letter_subset.index(target_letter) + 1 - else: - source_inquiries = self.no_target_inquiries - target_position = 0 # unused - - # randomly select a valid data source and inquiry - data_source = random.choice(list(source_inquiries.keys())) - inquiry_n = random.choice(source_inquiries[data_source]) - - # select all trials for the data_source and inquiry - inquiry_df = self.data.loc[(self.data['source'] == data_source) - & (self.data['inquiry_n'] == inquiry_n)] - assert len(inquiry_df) == len( - inquiry_letter_subset), f"Invalid data source {data_source}" - - # The inquiry may need to be re-ordered to ensure that the target is in - # the correct position. We do this by sorting the dataframe on a custom - # column that is the inquiry_pos for all non-targets, and the - # new_target_position for the target. - inquiry_target_position = target_position - if target_letter in inquiry_letter_subset: - inquiry_target_index = inquiry_df[inquiry_df['target'] == - 1].index[0] - inquiry_target_position = inquiry_df.index.tolist().index( - inquiry_target_index) - - if inquiry_target_position == target_position: - # target already in the correct location, no need to adjust - new_target_position = inquiry_target_position + 0.0 - elif inquiry_target_position < target_position: - # target in the inquiry needs to be pushed later in the inquiry; - # There is another symbol currently at that position, so we need - # to ensure that the target is past that symbol (by adding 0.5). - new_target_position = target_position + 0.5 - elif inquiry_target_position > target_position: - # the target in the inquiry needs to be moved earlier in the inquiry; - # there is another non-target symbol currently at that position so - # the target needs to be moved before that symbol. - new_target_position = target_position - 0.5 - - # define a sort column to move the target in the inquiry to the desired index - sort_pos = inquiry_df['inquiry_pos'].where(inquiry_df['target'] == 0, - new_target_position) - - # select the inquiry items in sorted position - sorted_inquiry_df = inquiry_df.loc[sort_pos.sort_values().index] - rows = [ - Trial(**sorted_inquiry_df.iloc[i]) - for i in range(len(sorted_inquiry_df)) - ] - log.debug(f"EEG Samples:\n{format_samples(rows)}") - return rows diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 5e5236516..e833a12d6 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -7,7 +7,7 @@ from bcipy.helpers.stimuli import InquirySchedule from bcipy.language.main import LanguageModel from bcipy.signal.model.base_model import SignalModel -from bcipy.simulator.helpers.sampler import Sampler +from bcipy.simulator.data.sampler import Sampler from bcipy.simulator.helpers.state import SimState from bcipy.simulator.task.null_display import NullDisplay from bcipy.task.control.evidence import EvidenceEvaluator diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py index 8d08ac750..210ce54ae 100644 --- a/bcipy/simulator/task/task_factory.py +++ b/bcipy/simulator/task/task_factory.py @@ -5,10 +5,10 @@ from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import load_json_parameters, load_signal_models from bcipy.signal.model.base_model import SignalModel +from bcipy.simulator.data.data_engine import RawDataEngine +from bcipy.simulator.data.data_process import init_data_processor +from bcipy.simulator.data.sampler import Sampler, TargetNontargetSampler from bcipy.simulator.helpers import artifact -from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.data_process import init_data_processor -from bcipy.simulator.helpers.sampler import Sampler, TargetNontargetSampler from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index 9e7f6c6f0..f0f81f2d9 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -6,8 +6,8 @@ from glob import glob from pathlib import Path +from bcipy.simulator.data.sampler import TargetNontargetSampler from bcipy.simulator.helpers import artifact -from bcipy.simulator.helpers.sampler import TargetNontargetSampler from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask from bcipy.simulator.task.task_factory import TaskFactory diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py index ada6bb0ee..0ff430d15 100644 --- a/bcipy/simulator/tests/test_data_engine.py +++ b/bcipy/simulator/tests/test_data_engine.py @@ -4,9 +4,9 @@ import numpy as np -from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.data_process import (DecodedTriggers, - ExtractedExperimentData) +from bcipy.simulator.data.data_engine import RawDataEngine +from bcipy.simulator.data.data_process import (DecodedTriggers, + ExtractedExperimentData) def mock_data() -> ExtractedExperimentData: From 980b93ac4506eb2b75d2b0865245eddfce32a9ac Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Sep 2024 11:48:49 -0700 Subject: [PATCH 302/330] Fix issue with gitignore --- .gitignore | 1 + bcipy/simulator/data/data_engine.py | 201 ++++++++++++ bcipy/simulator/data/data_process.py | 475 +++++++++++++++++++++++++++ bcipy/simulator/data/sampler.py | 228 +++++++++++++ 4 files changed, 905 insertions(+) create mode 100644 bcipy/simulator/data/data_engine.py create mode 100644 bcipy/simulator/data/data_process.py create mode 100644 bcipy/simulator/data/sampler.py diff --git a/.gitignore b/.gitignore index 54fabb0bf..0367e5eae 100644 --- a/.gitignore +++ b/.gitignore @@ -37,3 +37,4 @@ bcipy/language/out/ bcipy/simulator/tests/resource/ +!bcipy/simulator/data diff --git a/bcipy/simulator/data/data_engine.py b/bcipy/simulator/data/data_engine.py new file mode 100644 index 000000000..3878e3877 --- /dev/null +++ b/bcipy/simulator/data/data_engine.py @@ -0,0 +1,201 @@ +"""Classes and functions related to loading and querying data to be used in a simulation.""" +import logging +from abc import ABC, abstractmethod +from pathlib import Path +from typing import Any, List, NamedTuple, Union + +import numpy as np +import pandas as pd + +from bcipy.helpers.exceptions import TaskConfigurationException +from bcipy.helpers.parameters import Parameters +from bcipy.simulator.data import data_process +from bcipy.simulator.data.data_process import (ExtractedExperimentData, + RawDataProcessor) +from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME + +log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) + + +class Trial(NamedTuple): + """Data for a given trial (a symbol within an Inquiry). + + Attrs + ----- + source - directory of the data source + inquiry_n - starts at 0; does not reset at each series + inquiry_pos - starts at 1; position in which the symbol was presented + symbol - alphabet symbol that was presented + target - 1 or 0 indicating a boolean of whether this was a target symbol + eeg - EEG data associated with this trial + """ + source: str + # series_n: int + inquiry_n: int + inquiry_pos: int + symbol: str + target: int + eeg: np.ndarray # Channels by Samples ; ndarray.shape = (channel_n, sample_n) + + def __str__(self): + fields = [ + f"source='{self.source}'", f"inquiry_n={self.inquiry_n}", + f"inquiry_pos={self.inquiry_pos}", f"symbol='{self.symbol}'", + f"target={self.target}", f"eeg={self.eeg.shape}" + ] + return f"Trial({', '.join(fields)})" + + def __repr__(self): + return str(self) + + +class QueryFilter(NamedTuple): + """Provides an API used to query a data engine for data.""" + field: str + operator: str + value: Any + + def is_valid(self) -> bool: + """Check if the filter is valid.""" + # pylint: disable=no-member + return self.field in Trial._fields and self.operator in self.valid_operators and isinstance( + self.value, Trial.__annotations__[self.field]) + + @property + def valid_operators(self) -> List[str]: + """List of supported query operators""" + return ["<", "<=", ">", ">=", "==", "!="] + + +class DataEngine(ABC): + """Abstract class for an object that loads data from one or more sources, + processes the data using a provided processor, and provides an interface + for querying the processed data.""" + + def load(self): + """Load data from sources.""" + + @property + def trials_df(self) -> pd.DataFrame: + """Returns a dataframe of Trial data.""" + + @abstractmethod + def query(self, + filters: List[QueryFilter], + samples: int = 1) -> List[Trial]: + """Query the data.""" + + +def convert_trials(data_source: ExtractedExperimentData) -> List[Trial]: + """Convert extracted data from a single data source to a list of Trials.""" + trials = [] + symbols_by_inquiry = data_source.symbols_by_inquiry + labels_by_inquiry = data_source.labels_by_inquiry + + for i, inquiry_eeg in enumerate(data_source.trials_by_inquiry): + # iterate through each inquiry + inquiry_symbols = symbols_by_inquiry[i] + inquiry_labels = labels_by_inquiry[i] + + for sym_i, symbol in enumerate(inquiry_symbols): + # iterate through each symbol in the inquiry + eeg_samples = [channel[sym_i] + for channel in inquiry_eeg] # (channel_n, sample_n) + trials.append( + Trial(source=data_source.source_dir, + inquiry_n=i, + inquiry_pos=sym_i + 1, + symbol=symbol, + target=inquiry_labels[sym_i], + eeg=np.array(eeg_samples))) + return trials + + +class RawDataEngine(DataEngine): + """ + Object that loads in list of session data folders and transforms data into + a queryable data structure. + """ + + def __init__(self, source_dirs: List[str], parameters: Parameters, + data_processor: RawDataProcessor): + self.source_dirs: List[str] = source_dirs + self.parameters: Parameters = parameters + + self.data_processor = data_processor + self.data: List[Union[ExtractedExperimentData, + data_process.ExtractedExperimentData]] = [] + self._trials_df = pd.DataFrame() + + self.load() + + def load(self) -> DataEngine: + """ + Processes raw data from data folders using provided parameter files. + - Extracts and stores trial data, stimuli, and stimuli_labels by inquiries + + Returns: + self for chaining + """ + if not self.data: + log.debug( + f"Loading data from {len(self.source_dirs)} source directories:" + ) + rows = [] + for i, source_dir in enumerate(self.source_dirs): + log.debug(f"{i+1}. {Path(source_dir).name}") + extracted_data = self.data_processor.process( + source_dir, self.parameters) + self.data.append(extracted_data) + rows.extend(convert_trials(extracted_data)) + + self._trials_df = pd.DataFrame(rows) + log.debug("Finished loading all data") + return self + + @property + def trials_df(self) -> pd.DataFrame: + """Dataframe of Trial data.""" + if not self.data_loaded: + self.load() + return self._trials_df.copy() + + @property + def data_loaded(self) -> bool: + """Check if the data has been loaded""" + return bool(self.data) + + def query(self, + filters: List[QueryFilter], + samples: int = 1) -> List[Trial]: + """Query the engine for data using one or more filters. + + Parameters + ---------- + filters - list of query filters + samples - number of results to return. + check_insufficient_results - if True, raises an exception when + there are an insufficient number of samples. + + Returns a list of Trials. + """ + assert self.data_loaded, "Data must be loaded before querying." + assert all(filt.is_valid() + for filt in filters), "Filters must all be valid" + assert samples >= 1, "Insufficient number of samples requested" + + expr = 'and '.join([self.query_condition(filt) for filt in filters]) + filtered_data = self._trials_df.query(expr) + if filtered_data is None or len(filtered_data) < samples: + raise TaskConfigurationException( + message="Not enough samples found") + + rows = filtered_data.sample(samples) + return [Trial(*row) for row in rows.itertuples(index=False, name=None)] + + def query_condition(self, query_filter: QueryFilter) -> str: + """Returns the string representation of of the given query condition.""" + value = query_filter.value + if (isinstance(value, str)): + value = f"'{value}'" + return f"{query_filter.field} {query_filter.operator} {value}" diff --git a/bcipy/simulator/data/data_process.py b/bcipy/simulator/data/data_process.py new file mode 100644 index 000000000..134cc7a15 --- /dev/null +++ b/bcipy/simulator/data/data_process.py @@ -0,0 +1,475 @@ +"""This module defines functionality related to pre-processing simulation data. +Processed data can be subsequently sampled and provided to a SignalModel +for classification.""" + +import logging as logger +from dataclasses import dataclass +from pathlib import Path +from typing import List, NamedTuple, Optional, Tuple, Type + +import numpy as np + +from bcipy.acquisition import devices +from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.multimodal import ContentType +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETER_FILENAME, TRIGGER_FILENAME) +from bcipy.helpers.acquisition import analysis_channels, raw_data_filename +from bcipy.helpers.list import grouper +from bcipy.helpers.load import load_json_parameters, load_raw_data +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.raw_data import RawData +from bcipy.helpers.stimuli import update_inquiry_timing +from bcipy.helpers.triggers import TriggerType, trigger_decoder +from bcipy.signal.model.base_model import SignalModel +from bcipy.signal.process import (ERPTransformParams, filter_inquiries, + get_default_transform) +from bcipy.signal.process.transform import Composition +from bcipy.simulator.exceptions import (DeviceSpecNotFoundError, + IncompatibleDeviceSpec, + IncompatibleParameters) +from bcipy.task.data import EvidenceType + +log = logger.getLogger(__name__) + + +def load_device_data(data_folder: str, + content_type: str) -> Tuple[RawData, DeviceSpec]: + """Loads the data into the RawData format for the given content type. + + Parameters + ---------- + data_folder - session data folder with the raw data, device_spec, etc. + content_type - content type of the data to load. + + Returns + ------- + tuple of the raw data and the associated DeviceSpec for the device used + to record that data. + """ + devices_by_name = devices.load(Path(data_folder, + DEFAULT_DEVICE_SPEC_FILENAME), + replace=True) + specs = [ + spec for spec in devices_by_name.values() + if spec.is_active and spec.content_type == content_type + ] + if not specs: + raise DeviceSpecNotFoundError( + f"Suitable entry not found in {data_folder}/devices.json") + device_spec = specs[0] + raw_data_path = Path(data_folder, raw_data_filename(device_spec)) + if not raw_data_path.exists(): + raise FileNotFoundError(f"Raw data file not found: {raw_data_path}") + raw_data = load_raw_data(str(raw_data_path)) + + if device_spec != devices.preconfigured_device(raw_data.daq_type): + raise IncompatibleDeviceSpec( + "DeviceSpec in devices.json does not match the raw data.") + + return raw_data, device_spec + + +class DecodedTriggers(NamedTuple): + """Extracted properties after decoding the triggers.txt file and applying + the necessary offsets and corrections.""" + targetness: List[str] # TriggerType + times: List[float] + symbols: List[str] # symbol + corrected_times: List[float] + + +@dataclass() +class ExtractedExperimentData: + """Data from an acquisition device after reshaping and filtering.""" + source_dir: str + inquiries: np.ndarray + trials: np.ndarray + labels: List + inquiry_timing: List + + decoded_triggers: DecodedTriggers + trials_per_inquiry: int + + @property + def trials_by_inquiry(self) -> List[np.ndarray]: + """EEG data by inquiry. + shape (i_inquiry, n_channel, m_trial, x_sample) + """ + return np.split(self.trials, self.inquiries.shape[1], 1) + + @property + def symbols_by_inquiry(self) -> List[List[str]]: + """Get symbols by inquiry. shape (i_inquiry, s_alphabet_subset)""" + trigger_symbols = self.decoded_triggers.symbols + return [ + list(group) for group in grouper( + trigger_symbols, self.trials_per_inquiry, incomplete="ignore") + ] + + @property + def labels_by_inquiry(self) -> List[List[int]]: + """Shape (i_inquiry, s_alphabet_subset)""" + return self.labels + + +class TimingParams(NamedTuple): + """Timing-related parameters used in parsing the raw data into inquiries and trials.""" + # window (in seconds) of data collection after each stimulus presentation. + trial_window: Tuple[float, float] + # seconds before the start of the inquiry to use. + prestim_length: float + + # delay time (in seconds) between the final stimulus in one inquiry and the + # beginning (target stimulus or fixation cross) of the next inquiry. + task_buffer_length: float + stim_length: int + time_flash: float + + @property + def trials_per_inquiry(self) -> int: + """Alias for stim_length""" + return self.stim_length + + @property + def buffer(self) -> float: + """The task buffer length defines the min time between two inquiries + We use half of that time here to buffer during transforms""" + return self.task_buffer_length / 2 + + @property + def window_length(self) -> float: + """window (in seconds) of data collection after each stimulus presentation""" + start, end = self.trial_window + return end - start + + def __str__(self): + return ( + f"Timing settings: \n" + f"Trial Window: {self.trial_window[0]} to {self.trial_window[1]}s, " + f"Prestimulus Buffer: {self.prestim_length}s, Poststimulus Buffer: {self.buffer}s \n" + ) + + +def decode_triggers( + data_folder: str, + timing_params: TimingParams, + device_offset: float = 0.0, + excluded_triggers: Optional[List[TriggerType]] = None +) -> DecodedTriggers: + """Decode the triggers.txt file in the given directory.""" + if not excluded_triggers: + excluded_triggers = [ + TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION + ] + targetness, times, symbols = trigger_decoder( + offset=device_offset, + trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", + exclusion=excluded_triggers, + ) + corrected = [time + timing_params.trial_window[0] for time in times] + return DecodedTriggers(targetness=targetness, + times=times, + symbols=symbols, + corrected_times=corrected) + + +class ReshapedData(): + """Represents data components after reshaping""" + + def __init__(self): + self.inquiries: np.ndarray = np.array([]) + self.inquiry_labels: np.ndarray = np.array([]) + self.inquiry_timing: List[List[int]] = [] + + +class RawDataProcessor(): + """Processes raw data for a given device and converts it to + ExtractedExperimentData for use in the simulator. + + The main API method, `process`, provides a template method that can be + specialized by subclasses. This method performs the following for a given + data directory. + + 1. Loads the data file as a RawData object + 2. Extract timing information from trigger file based on the device of interest. + 3. Reshape and label the data. + 4. Apply filtering. + 5. Extract trials. + + Parameters + ---------- + model - signal model which will be used to classify the resulting data + """ + + def __init__(self, model: SignalModel): + self.check_model_compatibility(model) + self.model = model + + @property + def consumes(self) -> ContentType: + """ContentType of the data that should be input""" + + @property + def produces(self) -> EvidenceType: + """Type of evidence that is output""" + raise NotImplementedError + + @property + def content_type(self): + """Get the content_type of the data.""" + return self.consumes + + @property + def model_device(self) -> DeviceSpec: + """Device used to collect data for training the model.""" + return self.model.metadata.device_spec + + @property + def reshaper(self): + """data reshaper""" + return self.model.reshaper + + def check_model_compatibility(self, model: SignalModel) -> None: + """Check that the given model is compatible with this processor. + Checked on initialization.""" + assert model.metadata, "Metadata missing from signal model." + assert ContentType( + model.metadata.device_spec.content_type + ) == self.consumes, "DataProcessor is not compatible with the given model" + + def check_data_compatibility(self, data_device: DeviceSpec, + sim_timing_params: TimingParams, + data_timing_params: TimingParams) -> None: + """Check the compatibility of a dataset with the model.""" + if not self.devices_compatible(self.model_device, data_device): + raise IncompatibleDeviceSpec("Devices are not compatible") + if not self.parameters_compatible(sim_timing_params, + data_timing_params): + raise IncompatibleParameters( + "Timing parameters are not compatible") + + if data_device.static_offset == devices.DEFAULT_STATIC_OFFSET: + log.warning(' '.join([ + f"Using the default static offset to decode triggers for {data_device.name}.", + "Please make sure the correct offset is included in the devices.json file." + ])) + + def process(self, data_folder: str, + parameters: Parameters) -> ExtractedExperimentData: + """Load and process the data. + + Parameters + ---------- + data_folder - session directory for a given dataset + (contains raw_data, devices.json, and parameters.json). + parameters - parameters.json file for the calibration session used + to train the model / run the simulation. + """ + raw_data, device_spec = load_device_data(data_folder, + self.content_type.name) + data_parameters = load_json_parameters( + f"{data_folder}/{DEFAULT_PARAMETER_FILENAME}", value_cast=True) + + timing_params = parameters.instantiate(TimingParams) + + self.check_data_compatibility( + data_device=device_spec, + sim_timing_params=timing_params, + data_timing_params=data_parameters.instantiate(TimingParams)) + + decoded_triggers = decode_triggers(data_folder, timing_params, + device_spec.static_offset, + self.excluded_triggers()) + + reshaped_data = self.reshape_data(raw_data, decoded_triggers, + timing_params) + + filtered_reshaped_data, new_sample_rate = self.apply_filters( + reshaped_data, parameters, raw_data.sample_rate) + + trials = self.extract_trials(filtered_reshaped_data, timing_params, + new_sample_rate) + return ExtractedExperimentData( + data_folder, + filtered_reshaped_data.inquiries, + trials, + [list(arr) for arr in filtered_reshaped_data.inquiry_labels], + filtered_reshaped_data.inquiry_timing, + decoded_triggers=decoded_triggers, + trials_per_inquiry=timing_params.trials_per_inquiry) + + def reshape_data(self, raw_data: RawData, + decoded_triggers: DecodedTriggers, + timing_params: TimingParams) -> ReshapedData: + """Use the configured reshaper to reshape the data.""" + raise NotImplementedError + + def apply_filters(self, reshaped_data: ReshapedData, + parameters: Parameters, + data_sample_rate: int) -> Tuple[ReshapedData, int]: + """Apply any filters to the reshaped data. + + Returns + ------- + inquiry data after filtering, updated sample_rate + """ + raise NotImplementedError + + def extract_trials(self, filtered_reshaped_data: ReshapedData, + timing_params: TimingParams, + updated_sample_rate: float) -> np.ndarray: + """Extract trial data from the filtered, reshaped data. + + Returns + ------- + np.ndarray of shape (Channels, Trials, Samples) + """ + raise NotImplementedError + + def excluded_triggers(self): + """Trigger types to exclude when decoding""" + return [TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION] + + def devices_compatible(self, model_device: DeviceSpec, + data_device: DeviceSpec) -> bool: + """Check compatibility between the device on which the model was trained + and the device used for data collection.""" + + # TODO: check analysis channels? + return model_device.sample_rate == data_device.sample_rate + + def parameters_compatible(self, sim_timing_params: TimingParams, + data_timing_params: TimingParams) -> bool: + """Check compatibility between the parameters used for simulation and + those used for data collection.""" + return sim_timing_params.time_flash == data_timing_params.time_flash + + +class EegRawDataProcessor(RawDataProcessor): + """RawDataProcessor that processes EEG data.""" + consumes = ContentType.EEG + produces = EvidenceType.ERP + + def reshape_data(self, raw_data: RawData, + decoded_triggers: DecodedTriggers, + timing_params: TimingParams) -> ReshapedData: + """Use the configured reshaper to reshape the data.""" + + data, _fs = raw_data.by_channel() + channel_map = analysis_channels(raw_data.channels, self.model_device) + inquiries, inquiry_labels, inquiry_timing = self.reshaper( + trial_targetness_label=decoded_triggers.targetness, + timing_info=decoded_triggers.corrected_times, + eeg_data=data, + sample_rate=raw_data.sample_rate, + trials_per_inquiry=timing_params.trials_per_inquiry, + channel_map=channel_map, + poststimulus_length=timing_params.window_length, + prestimulus_length=timing_params.prestim_length, + transformation_buffer=timing_params.buffer, + ) + reshaped = ReshapedData() + reshaped.inquiries = inquiries + reshaped.inquiry_labels = inquiry_labels + reshaped.inquiry_timing = inquiry_timing + return reshaped + + def apply_filters(self, reshaped_data: ReshapedData, + parameters: Parameters, + data_sample_rate: int) -> Tuple[ReshapedData, int]: + """Apply any filters to the reshaped data. + + Returns + ------- + inquiry data after filtering, updated sample_rate + """ + transform_params = parameters.instantiate(ERPTransformParams) + transform = self.get_transform(transform_params, data_sample_rate) + inquiries, fs = filter_inquiries(reshaped_data.inquiries, transform, + data_sample_rate) + inquiry_timing_ints: List[List[int]] = [ + list(map(int, inq)) for inq in reshaped_data.inquiry_timing + ] + filtered_reshaped_data = ReshapedData() + filtered_reshaped_data.inquiries = inquiries + filtered_reshaped_data.inquiry_timing = update_inquiry_timing( + inquiry_timing_ints, transform_params.down_sampling_rate) + filtered_reshaped_data.inquiry_labels = reshaped_data.inquiry_labels + return filtered_reshaped_data, fs + + def extract_trials(self, filtered_reshaped_data: ReshapedData, + timing_params: TimingParams, + updated_sample_rate: float) -> np.ndarray: + """Extract trial data from the filtered, reshaped data. + + Returns + ------- + np.ndarray of shape (Channels, Trials, Samples) + """ + trial_duration_samples = int(timing_params.window_length * + updated_sample_rate) + return self.reshaper.extract_trials( + filtered_reshaped_data.inquiries, trial_duration_samples, + filtered_reshaped_data.inquiry_timing) + + def get_transform(self, transform_params: ERPTransformParams, + data_sample_rate: int) -> Composition: + """"Get the transform used for filtering the data.""" + return get_default_transform( + sample_rate_hz=data_sample_rate, + notch_freq_hz=transform_params.notch_filter_frequency, + bandpass_low=transform_params.filter_low, + bandpass_high=transform_params.filter_high, + bandpass_order=transform_params.filter_order, + downsample_factor=transform_params.down_sampling_rate, + ) + + +# Module functions for matching a model to the correct processor. +def get_processor( + data_source: ContentType, + evidence_type: Optional[EvidenceType] = None +) -> Type[RawDataProcessor]: + """Returns the matching processor class. + + Parameters + ---------- + data_source - type of data that the processor should consume + evidence_type - type of evidence that the processor should produce. + """ + matches = [ + cls for cls in RawDataProcessor.__subclasses__() + if cls.consumes == data_source and ( + evidence_type is None or cls.produces == evidence_type) + ] + if matches: + return matches[0] + else: + msg = f"Data processor not found for {data_source.name}" + if evidence_type: + msg += f" -> {evidence_type.name}" + raise Exception(msg) + + +def find_data_processor(model: SignalModel) -> Type[RawDataProcessor]: + """Get the DataProcessor appropriate for the given model.""" + content_type = ContentType(model.metadata.device_spec.content_type) + # Metadata may provide an EvidenceType with a model so the same data source can + # be used to produce multiple types of evidence (ex. alpha) + evidence_type = None + model_output = model.metadata.evidence_type + if model_output: + try: + evidence_type = EvidenceType(model_output.upper()) + except ValueError: + logger.error(f"Unsupported evidence type: {model_output}") + + return get_processor(content_type, evidence_type) + + +def init_data_processor(signal_model: SignalModel) -> RawDataProcessor: + """Find an DataProcessor that matches the given signal_model and + initialize it.""" + processor_class = find_data_processor(signal_model) + return processor_class(signal_model) diff --git a/bcipy/simulator/data/sampler.py b/bcipy/simulator/data/sampler.py new file mode 100644 index 000000000..17133a70e --- /dev/null +++ b/bcipy/simulator/data/sampler.py @@ -0,0 +1,228 @@ +import logging +import random +from abc import ABC +from collections import defaultdict +from pathlib import Path +from typing import Callable, Dict, List, Tuple + +import numpy as np +import pandas as pd + +from bcipy.simulator.data.data_engine import QueryFilter, RawDataEngine, Trial +from bcipy.simulator.helpers.state import SimState + +log = logging.getLogger(__name__) + + +def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: + """Default data reshaper. + + Returns + ------- + ndarray with shape (channel_n, trial_n, sample_n) + """ + + channels_eeg: List[List[np.ndarray]] = [ + [] for i in range(len(eeg_responses[0])) + ] + + for _i, trial_channels_eeg in enumerate(eeg_responses): + for c_i, channel_eeg in enumerate(trial_channels_eeg): + channels_eeg[c_i].append(channel_eeg) + + return np.array(channels_eeg) + + +class Sampler(ABC): + """Represents a strategy for sampling signal model data from a DataEngine + comprised of signal data from one or more data collection sessions.""" + + def __init__(self, data_engine: RawDataEngine): + self.data_engine: RawDataEngine = data_engine + self.model_input_reshaper: Callable = default_reshaper + + def sample(self, state: SimState) -> List[Trial]: + """ + Query the data engine for a list of trials corresponding to each + currently displayed symbol. + + Parameters + ---------- + state - specifies the target symbol and current inquiry (displayed symbols). + + Returns + ------- + a list of Trials with an item for each symbol in the current inquiry. + """ + raise NotImplementedError + + def sample_data(self, state: SimState) -> np.ndarray: + """ + Query for trials and reshape for signal model input according to the + provided reshaper. + + Return: + ndarray of shape (n_channel, n_trial, n_sample) + """ + trials = self.sample(state) + return self.reshaped(trials) + + def sample_with_context(self, + state: SimState) -> Tuple[np.ndarray, List[Trial]]: + """ + Returns + ------- + A tuple of the reshaped data (ndarray of shape (n_channel, n_trial, n_sample)) as + well as a list of Trial data (metadata and data not reshaped) for context. + """ + trials = self.sample(state) + data = self.reshaped(trials) + return data, trials + + def reshaped(self, sample_rows: List[Trial]) -> np.ndarray: + """Returns the queried trials reshaped into a format that a model can predict.""" + return self.model_input_reshaper([trial.eeg for trial in sample_rows]) + + def set_reshaper(self, reshaper: Callable): + """Set the reshaper""" + self.model_input_reshaper = reshaper + + def __str__(self): + return f"<{self.__class__.__name__}>" + + +class TargetNontargetSampler(Sampler): + """Sampler that that queries based on target/non-target label.""" + + def sample(self, state: SimState) -> List[Trial]: + sample_rows = [] + for symbol in state.display_alphabet: + filters = self.query_filters( + symbol, is_target=(symbol == state.target_symbol)) + filtered_data = self.data_engine.query(filters, samples=1) + sample_rows.append(filtered_data[0]) + + log.debug(f"Samples:\n{format_samples(sample_rows)}") + return sample_rows + + def query_filters(self, symbol: str, is_target: bool) -> List[QueryFilter]: + """Expression used to query for a single sample.""" + # QueryFilter('symbol', '==', symbol) + return [QueryFilter('target', '==', int(is_target))] + + +class InquirySampler(Sampler): + """Samples an inquiry of data at a time.""" + + def __init__(self, data_engine: RawDataEngine): + super().__init__(data_engine) + + # map source to inquiry numbers + self.data = self.data_engine.trials_df + self.target_inquiries, self.no_target_inquiries = self.prepare_data( + self.data) + + def prepare_data( + self, data: pd.DataFrame + ) -> Tuple[Dict[Path, List[int]], Dict[Path, List[int]]]: + """Partition the data into those inquiries that displayed the target + and those that did not. The resulting data structures map the data + source with a list of inquiry_n numbers.""" + + target_inquiries = defaultdict(list) + no_target_inquiries = defaultdict(list) + + # TODO: there is probably a more optimal way to use pandas to compute. + # Look into groupby. + for source in data['source'].unique(): + source_df = data[data['source'] == source] + for n in source_df['inquiry_n'].unique(): + inquiry_df = source_df[source_df['inquiry_n'] == n] + has_target = inquiry_df[inquiry_df['target'] == + 1]['target'].any() + + if has_target: + target_inquiries[source].append(n) + else: + no_target_inquiries[source].append(n) + + return target_inquiries, no_target_inquiries + + def sample(self, state: SimState) -> List[Trial]: + """Samples a random inquiry for a random data source. + + Ensures that if a target is shown in the current inquiry the sampled + data will be from an inquiry where the target was presented. + + Parameters + ---------- + state - specifies the target symbol and current inquiry (displayed symbols). + + Returns + ------- + a list of Trials with an item for each symbol in the current + inquiry. + """ + + target_letter = state.target_symbol + inquiry_letter_subset = state.display_alphabet + + if target_letter in inquiry_letter_subset: + source_inquiries = self.target_inquiries + target_position = inquiry_letter_subset.index(target_letter) + 1 + else: + source_inquiries = self.no_target_inquiries + target_position = 0 # unused + + # randomly select a valid data source and inquiry + data_source = random.choice(list(source_inquiries.keys())) + inquiry_n = random.choice(source_inquiries[data_source]) + + # select all trials for the data_source and inquiry + inquiry_df = self.data.loc[(self.data['source'] == data_source) + & (self.data['inquiry_n'] == inquiry_n)] + assert len(inquiry_df) == len( + inquiry_letter_subset), f"Invalid data source {data_source}" + + # The inquiry may need to be re-ordered to ensure that the target is in + # the correct position. We do this by sorting the dataframe on a custom + # column that is the inquiry_pos for all non-targets, and the + # new_target_position for the target. + inquiry_target_position = target_position + if target_letter in inquiry_letter_subset: + inquiry_target_index = inquiry_df[inquiry_df['target'] == + 1].index[0] + inquiry_target_position = inquiry_df.index.tolist().index( + inquiry_target_index) + + if inquiry_target_position == target_position: + # target already in the correct location, no need to adjust + new_target_position = inquiry_target_position + 0.0 + elif inquiry_target_position < target_position: + # target in the inquiry needs to be pushed later in the inquiry; + # There is another symbol currently at that position, so we need + # to ensure that the target is past that symbol (by adding 0.5). + new_target_position = target_position + 0.5 + elif inquiry_target_position > target_position: + # the target in the inquiry needs to be moved earlier in the inquiry; + # there is another non-target symbol currently at that position so + # the target needs to be moved before that symbol. + new_target_position = target_position - 0.5 + + # define a sort column to move the target in the inquiry to the desired index + sort_pos = inquiry_df['inquiry_pos'].where(inquiry_df['target'] == 0, + new_target_position) + + # select the inquiry items in sorted position + sorted_inquiry_df = inquiry_df.loc[sort_pos.sort_values().index] + rows = [ + Trial(**sorted_inquiry_df.iloc[i]) + for i in range(len(sorted_inquiry_df)) + ] + log.debug(f"EEG Samples:\n{format_samples(rows)}") + return rows + + +def format_samples(sample_rows: List[Trial]) -> str: + """Returns a tabular representation of the sample rows.""" + return '\n'.join([str(row) for row in sample_rows]) From bd29127dbd0aa91d8b213bf0b48742c316fb9d8f Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Sep 2024 13:31:12 -0700 Subject: [PATCH 303/330] Added functionality for debugging simulator output --- bcipy/simulator/helpers/state.py | 43 +++++++++++++++++++++++++++++++- 1 file changed, 42 insertions(+), 1 deletion(-) diff --git a/bcipy/simulator/helpers/state.py b/bcipy/simulator/helpers/state.py index 0a07e2853..ed4671c7a 100644 --- a/bcipy/simulator/helpers/state.py +++ b/bcipy/simulator/helpers/state.py @@ -1,5 +1,11 @@ +import argparse +import json from dataclasses import dataclass -from typing import List +from pathlib import Path +from typing import Any, Dict, List + +from bcipy.config import SESSION_DATA_FILENAME +from bcipy.helpers.session import read_session @dataclass @@ -11,3 +17,38 @@ class SimState: display_alphabet: List[str] inquiry_n: int series_n: int + + +def get_inquiry(session_dir: str, n: int) -> Dict[str, Any]: + """Extracts an inquiry from a session.json file. Useful for debugging + simulator output.""" + session = read_session(f"{session_dir}/{SESSION_DATA_FILENAME}") + inq = session.all_inquiries[n] + return inq.stim_evidence(session.symbol_set) + + +def main(): + """Command line program to get data from a single inquiry within a session.""" + parser = argparse.ArgumentParser() + parser.add_argument( + "-d", + "--data_folder", + type=Path, + required=True, + help= + "Session data folder to be processed. Singular wrapper dir with data folders" + ) + parser.add_argument("-n", + type=int, + required=False, + default=1, + help="inquiry number") + + args = parser.parse_args() + inq = get_inquiry(args.data_folder, args.n) + print(json.dumps(inq, indent=2)) + + +if __name__ == '__main__': + # python bcipy/simulator/helpers/state.py -h + main() From d38dd66129938159a9199d46f23b60ad2799c4e8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Sep 2024 13:59:26 -0700 Subject: [PATCH 304/330] Fixed linting issue --- bcipy/simulator/helpers/state.py | 13 +++++-------- 1 file changed, 5 insertions(+), 8 deletions(-) diff --git a/bcipy/simulator/helpers/state.py b/bcipy/simulator/helpers/state.py index ed4671c7a..a048dd8a7 100644 --- a/bcipy/simulator/helpers/state.py +++ b/bcipy/simulator/helpers/state.py @@ -30,14 +30,11 @@ def get_inquiry(session_dir: str, n: int) -> Dict[str, Any]: def main(): """Command line program to get data from a single inquiry within a session.""" parser = argparse.ArgumentParser() - parser.add_argument( - "-d", - "--data_folder", - type=Path, - required=True, - help= - "Session data folder to be processed. Singular wrapper dir with data folders" - ) + parser.add_argument("-d", + "--data_folder", + type=Path, + required=True, + help="Folder with the session.json file") parser.add_argument("-n", type=int, required=False, From 226c4ccd22dafa473a44529ee413c9afd3e0dcb5 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Sep 2024 16:01:09 -0700 Subject: [PATCH 305/330] Add missing parameters to the simulation params file --- bcipy/simulator/task/task_factory.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py index 210ce54ae..e25a6e239 100644 --- a/bcipy/simulator/task/task_factory.py +++ b/bcipy/simulator/task/task_factory.py @@ -4,6 +4,7 @@ from bcipy.helpers.language_model import init_language_model from bcipy.helpers.load import load_json_parameters, load_signal_models +from bcipy.helpers.parameters import DEFAULT_PARAMETERS_PATH from bcipy.signal.model.base_model import SignalModel from bcipy.simulator.data.data_engine import RawDataEngine from bcipy.simulator.data.data_process import init_data_processor @@ -33,6 +34,9 @@ def __init__(self, logger.info("Loading parameters") self.parameters = load_json_parameters(self.params_path, value_cast=True) + default_params = load_json_parameters(DEFAULT_PARAMETERS_PATH, value_cast=True) + # TODO: log which parameters were added + self.parameters.add_missing_items(default_params) logger.info("Loading signal models") self.signal_models = load_signal_models(directory=self.model_path) From 4af8825b689c095a51220d31714bd111064595c0 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 23 Sep 2024 16:11:00 -0700 Subject: [PATCH 306/330] Revert changes on non-simulator modules --- bcipy/helpers/language_model.py | 1 - bcipy/parameters/parameters.json | 2 +- scripts/python/replay_session.py | 170 +++++++++++++++++++------------ 3 files changed, 106 insertions(+), 67 deletions(-) diff --git a/bcipy/helpers/language_model.py b/bcipy/helpers/language_model.py index 5b1d083bc..0c9d87d7c 100644 --- a/bcipy/helpers/language_model.py +++ b/bcipy/helpers/language_model.py @@ -49,7 +49,6 @@ def init_language_model(parameters: dict) -> LanguageModel: # select the relevant parameters into a dict. params = {key: parameters[key] for key in args & parameters.keys()} - return model(response_type=ResponseType.SYMBOL, symbol_set=alphabet(parameters), **params) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 1904fd979..e8f7d7b81 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -337,7 +337,7 @@ "type": "int" }, "time_flash": { - "value": "0.2", + "value": "0.25", "section": "bci_config", "readableName": "Stimulus Presentation Duration", "helpTip": "Specifies the duration of time (in seconds) that each stimulus is displayed in an inquiry.", diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index c869e65e7..239bc8a00 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -1,36 +1,39 @@ """Script that will replay sessions and allow us to simulate new model predictions on that data.""" import json import logging as logger -from typing import Tuple -from pathlib import Path import pickle +from pathlib import Path +from typing import Tuple import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sns -from bcipy.config import ( - RAW_DATA_FILENAME, - TRIGGER_FILENAME, - DEFAULT_PARAMETER_FILENAME, SESSION_DATA_FILENAME, - DEFAULT_DEVICE_SPEC_FILENAME, -) -from bcipy.helpers.acquisition import analysis_channels + import bcipy.acquisition.devices as devices -from bcipy.helpers.language_model import init_language_model +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, + SESSION_DATA_FILENAME, TRIGGER_FILENAME) +from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.list import grouper from bcipy.helpers.load import load_json_parameters, load_raw_data -from bcipy.helpers.session import session_data, read_session, evidence_records from bcipy.helpers.stimuli import InquiryReshaper, update_inquiry_timing -from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.symbols import alphabet -from bcipy.language.model import kenlm +from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.signal.model import PcaRdaKdeModel -from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams +from bcipy.signal.process import (ERPTransformParams, filter_inquiries, + get_default_transform) logger.getLogger().setLevel(logger.INFO) +def load_model(model_path: Path, k_folds: int, model_class=PcaRdaKdeModel): + """Load the model at the given path""" + with open(model_path, "rb") as f: + model = pickle.load(f) + return model + + def generate_replay_outputs( data_folder, parameters, @@ -59,12 +62,8 @@ def generate_replay_outputs( ------- tuple - new_model_outputs, old_model_target_output, old_model_nontarget_output """ - # k_folds = - # model = load_model(model_path, k_folds, model_class) - - base_model = PcaRdaKdeModel(parameters.get("k_folds")) - model = base_model.load(model_path) - + k_folds = parameters.get("k_folds") + model = load_model(model_path, k_folds, model_class) logger.info(f"Loaded model from {model_path}") # get trial information; to make backwards compatible, we will try to get the trial length @@ -83,6 +82,7 @@ def generate_replay_outputs( # get signal filtering information static_offset = parameters.get("static_trigger_offset") + k_folds = parameters.get("k_folds") transform_params = parameters.instantiate(ERPTransformParams) downsample_rate = transform_params.down_sampling_rate @@ -154,7 +154,7 @@ def generate_replay_outputs( inquiry_worth_of_trials = np.split(trials, inquiries.shape[1], 1) inquiry_worth_of_letters = grouper(trigger_symbols, trials_per_inquiry, incomplete="ignore") for i, (inquiry_trials, this_inquiry_letters, this_inquiry_labels) in enumerate( - zip(inquiry_worth_of_trials, inquiry_worth_of_letters, inquiry_labels) + zip(inquiry_worth_of_trials, inquiry_worth_of_letters, inquiry_labels) ): response = model.predict(inquiry_trials, this_inquiry_letters, symbol_set=symbol_set) if np.any(this_inquiry_labels == 1): @@ -177,49 +177,53 @@ def generate_replay_outputs( with open(data_folder / "replay_outputs.json", "w") as f: json.dump(outputs, f, indent=2) - # Get target and nontarget eeg values from actual experiment in session.json for comparison - session_records = evidence_records(read_session(data_folder / SESSION_DATA_FILENAME)) - all_target_eeg = [record.eeg for record in session_records if record.is_target == 1] - all_nontarget_eeg = [record.eeg for record in session_records if record.is_target == 0] + # Get values computed during actual experiment from session.json for comparison + session_json = data_folder / SESSION_DATA_FILENAME + all_target_eeg, all_nontarget_eeg = load_eeg_evidence_from_session_json(session_json, symbol_set) return outputs, all_target_eeg, all_nontarget_eeg -def plot_comparison_records(records, outdir, title="response_values", y_scale="log"): - df = pd.DataFrame.from_records(records) - logger.info(f"{df.describe()}") - ax = sns.stripplot( - x="which_model", - y="response_value", - data=df, - order=["old_target", "new_target", "old_nontarget", "new_nontarget"], - ) - sns.boxplot( - showmeans=True, - meanline=True, - meanprops={"color": "k", "ls": "-", "lw": 2}, - medianprops={"visible": False}, - whiskerprops={"visible": False}, - zorder=10, - x="which_model", - y="response_value", - data=df, - showfliers=False, - showbox=False, - showcaps=False, - ax=ax, - order=["old_target", "new_target", "old_nontarget", "new_nontarget"], - ) - ax.set(yscale=y_scale) - plt.savefig(outdir / f"{title}.stripplot.png", dpi=150, bbox_inches="tight") - plt.close() - ax = sns.boxplot( - x="which_model", - y="response_value", - data=df, - order=["old_target", "new_target", "old_nontarget", "new_nontarget"], - ) - ax.set(yscale=y_scale) - plt.savefig(outdir / f"{title}.boxplot.png", dpi=150, bbox_inches="tight") + +def load_eeg_evidence_from_session_json(session_json, symbol_set) -> Tuple[list, list]: + """Load EEG evidence from session.json file for comparison with replay outputs. + + Parameters + ---------- + session_json : str + Path to session.json file + symbol_set : list + List of symbols used in experiment + + Returns + ------- + all_target_eeg : list + List of EEG evidence for target stimuli + all_nontarget_eeg : list + List of EEG evidence for nontarget stimuli + """ + with open(session_json, "r") as f: + contents = json.load(f) + series = contents["series"] + + all_target_eeg = [] + all_nontarget_eeg = [] + + for inquiries in series.values(): + for inquiry in inquiries.values(): + if len(inquiry["eeg_evidence"]) < 1: + continue + else: + stim_label = inquiry["stimuli"][0] # name of symbols presented + stim_label.pop(0) # remove fixation cross + stim_indices = [symbol_set.index(sym) for sym in stim_label] + targetness = inquiry["target_info"] # targetness of stimuli + targetness.pop(0) # remove fixation cross + target = [index for index, label in zip(stim_indices, targetness) if label == "target"] + nontarget = [index for index, label in zip(stim_indices, targetness) if label == "nontarget"] + all_target_eeg.extend([inquiry["eeg_evidence"][pos] for pos in target]) + all_nontarget_eeg.extend([inquiry["eeg_evidence"][pos] for pos in nontarget]) + + return all_target_eeg, all_nontarget_eeg def plot_collected_outputs( @@ -261,7 +265,43 @@ def plot_collected_outputs( for nontarget_response in nontargets_with_old_model: records.append({"which_model": "old_nontarget", "response_value": nontarget_response}) - plot_comparison_records(records, outdir, y_scale="log") + df = pd.DataFrame.from_records(records) + logger.info(f"{df.describe()}") + ax = sns.stripplot( + x="which_model", + y="response_value", + data=df, + order=["old_target", "new_target", "old_nontarget", "new_nontarget"], + ) + sns.boxplot( + showmeans=True, + meanline=True, + meanprops={"color": "k", "ls": "-", "lw": 2}, + medianprops={"visible": False}, + whiskerprops={"visible": False}, + zorder=10, + x="which_model", + y="response_value", + data=df, + showfliers=False, + showbox=False, + showcaps=False, + ax=ax, + order=["old_target", "new_target", "old_nontarget", "new_nontarget"], + ) + + ax.set(yscale="log") + plt.savefig(outdir / "response_values.stripplot.png", dpi=150, bbox_inches="tight") + plt.close() + ax = sns.boxplot( + x="which_model", + y="response_value", + data=df, + order=["old_target", "new_target", "old_nontarget", "new_nontarget"], + ) + ax.set(yscale="log") + plt.savefig(outdir / "response_values.boxplot.png", dpi=150, bbox_inches="tight") + if __name__ == "__main__": import argparse @@ -305,8 +345,6 @@ def plot_collected_outputs( logger.info(f"Loading params from {params_file}") params = load_json_parameters(params_file, value_cast=True) - # breakpoint() - # Generate replay outputs using the model provided against the session data in data_folder outputs, all_target_eeg, all_nontarget_eeg = generate_replay_outputs( data_folder, params, args.model_file, write_output=False @@ -321,4 +359,6 @@ def plot_collected_outputs( nontargets_with_old_model, args.outdir) - logger.info("Replay complete.") + # breakpoint() + + logger.info("Replay complete.") \ No newline at end of file From c211198da9e636736ab5f69e9359da5ddb910a51 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 25 Sep 2024 15:53:09 -0700 Subject: [PATCH 307/330] Cleanup based on PR feedback --- bcipy/simulator/README.md | 2 +- bcipy/simulator/data/data_engine.py | 3 +-- bcipy/simulator/data/data_process.py | 2 ++ bcipy/simulator/data/sampler.py | 11 +++++---- bcipy/simulator/task/copy_phrase.py | 19 ++++++--------- bcipy/simulator/task/task_factory.py | 4 ++-- bcipy/simulator/task/task_runner.py | 24 +++++-------------- bcipy/simulator/{helpers => util}/artifact.py | 13 ++++++++++ bcipy/simulator/{helpers => util}/state.py | 0 bcipy/task/paradigm/rsvp/copy_phrase.py | 9 ++++--- 10 files changed, 44 insertions(+), 43 deletions(-) rename bcipy/simulator/{helpers => util}/artifact.py (87%) rename bcipy/simulator/{helpers => util}/state.py (100%) diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index e99fc2f4e..0a239431b 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -66,5 +66,5 @@ The simulator is structured to support evidence from multiple devices (multimoda * Only provides EEG support * Only one sampler maybe provided for all devices. Ideally we should support a different sampling strategy for each device. -* Only the RSVP Copy Phrase may be simulated +* Only Copy Phrase is currently supported. * Metrics are collected per run, but not summarized across all runs. \ No newline at end of file diff --git a/bcipy/simulator/data/data_engine.py b/bcipy/simulator/data/data_engine.py index 3878e3877..0e10813ca 100644 --- a/bcipy/simulator/data/data_engine.py +++ b/bcipy/simulator/data/data_engine.py @@ -12,7 +12,7 @@ from bcipy.simulator.data import data_process from bcipy.simulator.data.data_process import (ExtractedExperimentData, RawDataProcessor) -from bcipy.simulator.helpers.artifact import TOP_LEVEL_LOGGER_NAME +from bcipy.simulator.util.artifact import TOP_LEVEL_LOGGER_NAME log = logging.getLogger(TOP_LEVEL_LOGGER_NAME) @@ -30,7 +30,6 @@ class Trial(NamedTuple): eeg - EEG data associated with this trial """ source: str - # series_n: int inquiry_n: int inquiry_pos: int symbol: str diff --git a/bcipy/simulator/data/data_process.py b/bcipy/simulator/data/data_process.py index 134cc7a15..c56153a60 100644 --- a/bcipy/simulator/data/data_process.py +++ b/bcipy/simulator/data/data_process.py @@ -3,6 +3,7 @@ for classification.""" import logging as logger +from abc import abstractmethod from dataclasses import dataclass from pathlib import Path from typing import List, NamedTuple, Optional, Tuple, Type @@ -299,6 +300,7 @@ def process(self, data_folder: str, decoded_triggers=decoded_triggers, trials_per_inquiry=timing_params.trials_per_inquiry) + @abstractmethod def reshape_data(self, raw_data: RawData, decoded_triggers: DecodedTriggers, timing_params: TimingParams) -> ReshapedData: diff --git a/bcipy/simulator/data/sampler.py b/bcipy/simulator/data/sampler.py index 17133a70e..fa1e3f8c4 100644 --- a/bcipy/simulator/data/sampler.py +++ b/bcipy/simulator/data/sampler.py @@ -1,6 +1,6 @@ import logging import random -from abc import ABC +from abc import ABC, abstractmethod from collections import defaultdict from pathlib import Path from typing import Callable, Dict, List, Tuple @@ -9,7 +9,7 @@ import pandas as pd from bcipy.simulator.data.data_engine import QueryFilter, RawDataEngine, Trial -from bcipy.simulator.helpers.state import SimState +from bcipy.simulator.util.state import SimState log = logging.getLogger(__name__) @@ -41,6 +41,7 @@ def __init__(self, data_engine: RawDataEngine): self.data_engine: RawDataEngine = data_engine self.model_input_reshaper: Callable = default_reshaper + @abstractmethod def sample(self, state: SimState) -> List[Trial]: """ Query the data engine for a list of trials corresponding to each @@ -132,8 +133,6 @@ def prepare_data( target_inquiries = defaultdict(list) no_target_inquiries = defaultdict(list) - # TODO: there is probably a more optimal way to use pandas to compute. - # Look into groupby. for source in data['source'].unique(): source_df = data[data['source'] == source] for n in source_df['inquiry_n'].unique(): @@ -152,7 +151,9 @@ def sample(self, state: SimState) -> List[Trial]: """Samples a random inquiry for a random data source. Ensures that if a target is shown in the current inquiry the sampled - data will be from an inquiry where the target was presented. + data will be from an inquiry where the target was presented. Note that + the inquiry may need to be re-ordered to ensure that the target is in + the correct position. Parameters ---------- diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index e833a12d6..1d78c44ec 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -8,8 +8,8 @@ from bcipy.language.main import LanguageModel from bcipy.signal.model.base_model import SignalModel from bcipy.simulator.data.sampler import Sampler -from bcipy.simulator.helpers.state import SimState from bcipy.simulator.task.null_display import NullDisplay +from bcipy.simulator.util.state import SimState from bcipy.task.control.evidence import EvidenceEvaluator from bcipy.task.data import EvidenceType from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask @@ -74,11 +74,9 @@ def present_inquiry( def show_feedback(self, selection: str, correct: bool = True) -> None: """Override to do nothing""" - # TODO: consider tracking metrics def compute_button_press_evidence( self, proceed: bool) -> Optional[Tuple[EvidenceType, List[float]]]: - # TODO: consider adding a sampler for this return None def compute_device_evidence( @@ -107,7 +105,6 @@ def exit_display(self) -> None: """Close the UI and cleanup.""" def elapsed_seconds(self) -> float: - # TODO: estimate this return 0.0 def write_offset_trigger(self) -> None: @@ -120,14 +117,12 @@ def write_trigger_data(self, stim_times: List[Tuple[str, float]], def get_sim_state(self) -> SimState: """Get the current state in the format expected by the simulation tools.""" - return SimState( - target_symbol=self.next_target(), - current_sentence=self.spelled_text, - target_sentence=self.copy_phrase, - display_alphabet=self.current_symbols(), - # TODO: - inquiry_n=0, - series_n=0) + return SimState(target_symbol=self.next_target(), + current_sentence=self.spelled_text, + target_sentence=self.copy_phrase, + display_alphabet=self.current_symbols(), + inquiry_n=len(self.session.series[-1]), + series_n=len(self.session.series)) def current_symbols(self) -> List[str]: """Get the list of symbols from the current inquiry.""" diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py index e25a6e239..0f4f9b927 100644 --- a/bcipy/simulator/task/task_factory.py +++ b/bcipy/simulator/task/task_factory.py @@ -9,10 +9,10 @@ from bcipy.simulator.data.data_engine import RawDataEngine from bcipy.simulator.data.data_process import init_data_processor from bcipy.simulator.data.sampler import Sampler, TargetNontargetSampler -from bcipy.simulator.helpers import artifact from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask +from bcipy.simulator.util.artifact import TOP_LEVEL_LOGGER_NAME -logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) +logger = logging.getLogger(TOP_LEVEL_LOGGER_NAME) class TaskFactory(): diff --git a/bcipy/simulator/task/task_runner.py b/bcipy/simulator/task/task_runner.py index f0f81f2d9..17cacce27 100644 --- a/bcipy/simulator/task/task_runner.py +++ b/bcipy/simulator/task/task_runner.py @@ -2,29 +2,17 @@ import argparse import logging -import os from glob import glob from pathlib import Path from bcipy.simulator.data.sampler import TargetNontargetSampler -from bcipy.simulator.helpers import artifact from bcipy.simulator.task.copy_phrase import SimulatorCopyPhraseTask from bcipy.simulator.task.task_factory import TaskFactory +from bcipy.simulator.util.artifact import (TOP_LEVEL_LOGGER_NAME, + configure_run_directory, + init_simulation_dir) -logger = logging.getLogger(artifact.TOP_LEVEL_LOGGER_NAME) - - -def configure_run_directory(sim_dir: str, run: int) -> str: - """Create the necessary directories and configure the logger. - Returns the run directory. - """ - run_name = f"run_{run}" - path = f"{sim_dir}/{run_name}" - os.mkdir(path) - artifact.configure_logger(log_path=path, - file_name=f"{run_name}.log", - use_stdout=False) - return path +logger = logging.getLogger(TOP_LEVEL_LOGGER_NAME) class TaskRunner(): @@ -39,7 +27,7 @@ def __init__(self, self.sim_dir = save_dir self.runs = runs - def run(self): + def run(self) -> None: """Run one or more simulations""" self.task_factory.parameters.save(self.sim_dir) for i in range(self.runs): @@ -89,7 +77,7 @@ def main(): if Path(d).is_dir() ] - sim_dir = artifact.init_simulation_dir() + sim_dir = init_simulation_dir() logger.info(sim_dir) task_factory = TaskFactory(params_path=sim_args['parameters'], model_path=sim_args['model_path'], diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/util/artifact.py similarity index 87% rename from bcipy/simulator/helpers/artifact.py rename to bcipy/simulator/util/artifact.py index b828adc42..dcc39f434 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/util/artifact.py @@ -74,6 +74,19 @@ def init_simulation_dir(save_location: str = DEFAULT_SAVE_LOCATION, return save_dir +def configure_run_directory(sim_dir: str, run: int) -> str: + """Create the necessary directories and configure the logger. + Returns the run directory. + """ + run_name = f"run_{run}" + path = f"{sim_dir}/{run_name}" + os.mkdir(path) + configure_logger(log_path=path, + file_name=f"{run_name}.log", + use_stdout=False) + return path + + def directory_name() -> str: """Name of the directory for a new simulation run.""" return datetime.datetime.now().strftime("SIM_%m-%d-%Y_%H_%M_%S") diff --git a/bcipy/simulator/helpers/state.py b/bcipy/simulator/util/state.py similarity index 100% rename from bcipy/simulator/helpers/state.py rename to bcipy/simulator/util/state.py diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 7586eb9e1..645490a95 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -126,8 +126,6 @@ def __init__( self.validate_parameters() self.static_clock = None - # self.static_clock = core.StaticPeriod( - # screenHz=self.window.getActualFrameRate()) self.experiment_clock = Clock() self.start_time = self.experiment_clock.getTime() @@ -141,7 +139,7 @@ def __init__( self.file_save = file_save self.save_session_every_inquiry = True - self.trigger_handler = TriggerHandler(self.file_save, TRIGGER_FILENAME, FlushFrequency.EVERY) + self.trigger_handler = self.default_trigger_handler() self.session_save_location = f"{self.file_save}/{SESSION_DATA_FILENAME}" self.copy_phrase = parameters['task_text'] @@ -204,6 +202,11 @@ def init_evidence_types( evidence_types.append(EvidenceType.BTN) return evidence_types + def default_trigger_handler(self) -> TriggerHandler: + """Default trigger handler""" + return TriggerHandler(self.file_save, TRIGGER_FILENAME, + FlushFrequency.EVERY) + def setup(self) -> None: """Initialize/reset parameters used in the execute run loop.""" From 2aeb419c5662b75e6a69b8db4fba5d026b578485 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 25 Sep 2024 16:37:56 -0700 Subject: [PATCH 308/330] Added logging for missing parameters --- bcipy/simulator/task/task_factory.py | 30 ++++++++++++++++++---------- 1 file changed, 20 insertions(+), 10 deletions(-) diff --git a/bcipy/simulator/task/task_factory.py b/bcipy/simulator/task/task_factory.py index 0f4f9b927..4de38fe0b 100644 --- a/bcipy/simulator/task/task_factory.py +++ b/bcipy/simulator/task/task_factory.py @@ -18,13 +18,13 @@ class TaskFactory(): """Constructs the hierarchy of objects necessary for initializing a task.""" - # TODO: sampling strategy per model type - def __init__(self, - params_path: str, - model_path: str, - source_dirs: List[str], - sampling_strategy: Type[Sampler] = TargetNontargetSampler, - task: Type[SimulatorCopyPhraseTask] = SimulatorCopyPhraseTask): + def __init__( + self, + params_path: str, + model_path: str, + source_dirs: List[str], + sampling_strategy: Type[Sampler] = TargetNontargetSampler, + task: Type[SimulatorCopyPhraseTask] = SimulatorCopyPhraseTask): self.params_path = params_path self.model_path = model_path self.source_dirs = source_dirs @@ -34,8 +34,16 @@ def __init__(self, logger.info("Loading parameters") self.parameters = load_json_parameters(self.params_path, value_cast=True) - default_params = load_json_parameters(DEFAULT_PARAMETERS_PATH, value_cast=True) - # TODO: log which parameters were added + default_params = load_json_parameters(DEFAULT_PARAMETERS_PATH, + value_cast=True) + + added_params = [ + key + for key, change in default_params.diff(self.parameters).items() + if change.original_value is None + ] + logger.info( + f"Added missing parameters using default values: {added_params}") self.parameters.add_missing_items(default_params) logger.info("Loading signal models") @@ -49,7 +57,9 @@ def __init__(self, self.samplers = self.init_samplers(self.signal_models) logger.debug(self.samplers) - def init_samplers(self, signal_models: List[SignalModel]) -> Dict[SignalModel, Sampler]: + def init_samplers( + self, + signal_models: List[SignalModel]) -> Dict[SignalModel, Sampler]: """Initializes the evidence evaluators from the provided signal models. Returns a list of evaluators for active devices. Raises an exception if From 45524bb16ffde2e09d5160fe7a807130cc249488 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 25 Sep 2024 16:53:10 -0700 Subject: [PATCH 309/330] Updated documentation --- README.md | 11 +++++++++++ bcipy/simulator/README.md | 3 +++ setup.py | 13 +++++++++---- 3 files changed, 23 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 9c19fd7d4..d17f471cc 100644 --- a/README.md +++ b/README.md @@ -78,6 +78,16 @@ from bcipy.helpers import system_utils system_utils.get_system_info() ``` +#### Simulator Usage + +The simulator can be run using the command line utility `bcipy-sim`. + +Ex. +`bcipy-sim -d my_data_folder/ -p my_parameters.json -m my_models/ -n 5` + +Run `bcipy-sim --help` for documentation or see the README in the simulator module. + + ## Glossary ----------- @@ -115,6 +125,7 @@ This a list of the major modules and their functionality. Each module will conta - `feedback`: feedback mechanisms for sound and visual stimuli. - `main`: executor of experiments. Main entry point into the application - `config`: configuration parameters for the application, including paths and data filenames. +- `simulator`: provides support for running simulations based off of previously collected data. ## Paradigms diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index 0a239431b..e3854a46c 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -25,6 +25,9 @@ optional arguments: -n N Number of times to run the simulation ``` +For example, +`$ python bcipy/simulator -d my_data_folder/ -p my_parameters.json -m my_models/ -n 5` + #### Program Args - `d` : the data wrapper folder argument is necessary. This folder is expected to contain 1 or more session folders. Each session folder should contain diff --git a/setup.py b/setup.py index f120b6148..7d0c34f83 100644 --- a/setup.py +++ b/setup.py @@ -17,11 +17,11 @@ """ import os -import sys import platform +import sys from shutil import rmtree -from setuptools import find_packages, setup, Command +from setuptools import Command, find_packages, setup # Package meta-data. NAME = 'bcipy' @@ -100,9 +100,14 @@ def run(self): author_email=EMAIL, python_requires=REQUIRES_PYTHON, url=URL, - packages=find_packages(exclude=('tests', 'demo', 'data', )), + packages=find_packages(exclude=( + 'tests', + 'demo', + 'data', + )), entry_points={ - 'console_scripts': ['bcipy = bcipy.main:bcipy_main'], + 'console_scripts': + ['bcipy = bcipy.main:bcipy_main', 'bcipy-sim = bcipy.simulator'], }, install_requires=REQUIRED, include_package_data=True, From 5ffff7d411c34c9e07c1b0ac848273e5a2cf8d91 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 26 Sep 2024 16:03:48 -0700 Subject: [PATCH 310/330] Added stoppage criteria for max incorrect --- bcipy/helpers/task.py | 19 ++++++++++++++ bcipy/helpers/tests/test_task.py | 26 ++++++++++++++----- bcipy/parameters/parameters.json | 10 ++++++- bcipy/task/paradigm/rsvp/copy_phrase.py | 15 +++++++++-- .../tests/paradigm/rsvp/test_copy_phrase.py | 1 + 5 files changed, 61 insertions(+), 10 deletions(-) diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index 1984bd1a4..a4e36c525 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -444,3 +444,22 @@ def generate_targets(alp, stim_number): targets = [target for sublist in lists for target in sublist] return targets + + +def consecutive_incorrect(target_text: str, spelled_text: str) -> int: + """Function that computes the number of consecutive symbols that + are incorrectly spelled. + + >>> consecutive_incorrect('WORLD', 'H') + 1 + >>> consecutive_incorrect('WORLD', 'W') + 0 + >>> consecutive_incorrect('WORLD', 'WOHL') + 2 + """ + if not target_text: + return len(spelled_text) + for i, character in enumerate(spelled_text): + if character != target_text[i]: + return len(spelled_text[i:]) + return 0 diff --git a/bcipy/helpers/tests/test_task.py b/bcipy/helpers/tests/test_task.py index cf45d327a..96817e319 100644 --- a/bcipy/helpers/tests/test_task.py +++ b/bcipy/helpers/tests/test_task.py @@ -1,20 +1,18 @@ import unittest - -from typing import List from collections import Counter -from mockito import unstub, mock, when, verify, verifyStubbedInvocationsAreUsed +from typing import List import numpy as np import psychopy +from mockito import mock, unstub, verify, verifyStubbedInvocationsAreUsed, when from bcipy.acquisition import LslAcquisitionClient from bcipy.acquisition.record import Record -from bcipy.task.exceptions import InsufficientDataException - -from bcipy.helpers.task import (_float_val, - calculate_stimulation_freq, construct_triggers, +from bcipy.helpers.task import (_float_val, calculate_stimulation_freq, + consecutive_incorrect, construct_triggers, generate_targets, get_data_for_decision, get_key_press, target_info) +from bcipy.task.exceptions import InsufficientDataException class TestCalculateStimulationFreq(unittest.TestCase): @@ -319,5 +317,19 @@ def test_get_data_for_decision_throws_insufficient_data_error_if_data_query_out_ get_data_for_decision(inquiry_timing, self.daq) +class TestUtils(unittest.TestCase): + """Tests for utility functions""" + + def test_consecutive_incorrect(self): + """Test calculation of consecutive incorrect""" + self.assertEqual( + 0, consecutive_incorrect(target_text='', spelled_text='')) + self.assertEqual(0, consecutive_incorrect('WORLD', '')) + self.assertEqual(0, consecutive_incorrect('WORLD', 'W')) + self.assertEqual(0, consecutive_incorrect('WORLD', 'WORLD')) + self.assertEqual(1, consecutive_incorrect('WORLD', 'H')) + self.assertEqual(2, consecutive_incorrect('WORLD', 'WOHL')) + + if __name__ == '__main__': unittest.main() diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index e8f7d7b81..7bd8a0860 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -535,7 +535,7 @@ "type": "float" }, "stim_number": { - "value": "100", + "value": "55", "section": "bci_config", "readableName": "Number of Calibration inquiries", "helpTip": "Specifies the number of inquiries to present in a calibration session. Default: 100", @@ -611,6 +611,14 @@ "recommended_values": "", "type": "int" }, + "max_incorrect": { + "value": "3", + "section": "bci_config", + "readableName": "Maximum Number of Incorrect Selections", + "helpTip": "The maximum number of consecutive incorrect selections for copy/spelling tasks. The task will end if this number is reached.", + "recommended_values": "", + "type": "int" + }, "decision_threshold": { "value": "0.8", "section": "bci_config", diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 645490a95..8bfa138dc 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -22,7 +22,8 @@ from bcipy.helpers.session import session_excel from bcipy.helpers.stimuli import InquirySchedule, StimuliOrder from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet -from bcipy.helpers.task import (construct_triggers, fake_copy_phrase_decision, +from bcipy.helpers.task import (consecutive_incorrect, construct_triggers, + fake_copy_phrase_decision, get_device_data_for_decision, get_user_input, relative_triggers, target_info, trial_complete_message) @@ -94,7 +95,8 @@ class RSVPCopyPhraseTask(Task): 'font', 'fixation_color', 'trigger_type', 'filter_high', 'filter_low', 'filter_order', 'notch_filter_frequency', 'down_sampling_rate', 'prestim_length', 'is_txt_stim', 'lm_backspace_prob', 'backspace_always_shown', - 'decision_threshold', 'max_inq_len', 'max_inq_per_series', 'max_minutes', 'max_selections', 'min_inq_len', + 'decision_threshold', 'max_inq_len', 'max_inq_per_series', 'max_minutes', 'max_selections', 'max_incorrect', + 'min_inq_len', 'show_feedback', 'feedback_duration', 'show_preview_inquiry', 'preview_inquiry_isi', 'preview_inquiry_error_prob', 'preview_inquiry_key_input', 'preview_inquiry_length', 'preview_inquiry_progress_method', @@ -416,6 +418,15 @@ def check_stop_criteria(self) -> bool: '(configured with the max_selections parameter)') return False + if consecutive_incorrect( + target_text=self.copy_phrase, + spelled_text=self.spelled_text) >= self.parameters.get( + 'max_incorrect', 3): + self.logger.info( + 'Max number of consecutive incorrect selections reached ' + '(configured with the max_incorrect parameter)') + return False + return True def next_target(self) -> str: diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 657afe28c..48d104aff 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -50,6 +50,7 @@ def setUp(self): 'max_minutes': 20, 'min_inq_len': 1, 'max_selections': 50, + 'max_incorrect': 10, 'notch_filter_frequency': 60.0, 'preview_inquiry_isi': 1.0, 'preview_inquiry_key_input': 'space', From a4b4d0168915d76b2141160d9d863e074bf11822 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 26 Sep 2024 16:49:45 -0700 Subject: [PATCH 311/330] Reverted parameter --- bcipy/parameters/parameters.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 7bd8a0860..3c35e73a2 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -535,7 +535,7 @@ "type": "float" }, "stim_number": { - "value": "55", + "value": "100", "section": "bci_config", "readableName": "Number of Calibration inquiries", "helpTip": "Specifies the number of inquiries to present in a calibration session. Default: 100", From 2d0929f77160e683155932f9f9bb1c5ac45e5a70 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 26 Sep 2024 17:28:53 -0700 Subject: [PATCH 312/330] Set default max_incorrect value to 5 --- bcipy/parameters/parameters.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 3c35e73a2..19756cefd 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -612,7 +612,7 @@ "type": "int" }, "max_incorrect": { - "value": "3", + "value": "5", "section": "bci_config", "readableName": "Maximum Number of Incorrect Selections", "helpTip": "The maximum number of consecutive incorrect selections for copy/spelling tasks. The task will end if this number is reached.", From c365be6e7fd100c7de9c20e148ef1fc8e3171afe Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 2 Oct 2024 13:03:41 -0700 Subject: [PATCH 313/330] Added inquiry preview to matrix display and tasks. --- .../components/button_press_handler.py | 119 ++++++++++ .../demo/matrix/demo_calibration_matrix.py | 9 +- .../demo/matrix/demo_copyphrase_matrix.py | 10 +- bcipy/display/main.py | 22 +- bcipy/display/paradigm/matrix/display.py | 88 ++++++-- .../components/test_button_press_handler.py | 205 ++++++++++++++++++ bcipy/task/paradigm/matrix/calibration.py | 4 +- bcipy/task/paradigm/matrix/copy_phrase.py | 4 +- 8 files changed, 441 insertions(+), 20 deletions(-) create mode 100644 bcipy/display/components/button_press_handler.py create mode 100644 bcipy/display/tests/components/test_button_press_handler.py diff --git a/bcipy/display/components/button_press_handler.py b/bcipy/display/components/button_press_handler.py new file mode 100644 index 000000000..3b3652409 --- /dev/null +++ b/bcipy/display/components/button_press_handler.py @@ -0,0 +1,119 @@ +"""Handles button press interactions""" +from abc import ABC, abstractmethod +from typing import List, Optional, Type + +from psychopy import core, event + +from bcipy.display.main import ButtonPressMode +from bcipy.helpers.clock import Clock +from bcipy.helpers.task import get_key_press + + +class ButtonPressHandler(ABC): + """Handles button press events.""" + + def __init__(self, + max_wait: float, + key_input: str, + clock: Optional[Clock] = None, + timer: Type[Clock] = core.CountdownTimer): + """ + Parameters + ---------- + wait_length - maximum number of seconds to wait for a key press + key_input - key that we are listening for. + clock - clock used to associate the key event with a timestamp + """ + self.max_wait = max_wait + self.key_input = key_input + self.clock = clock or Clock() + self.response: Optional[List] = None + + self._timer = None + self.make_timer = timer + + @property + def response_label(self) -> Optional[str]: + """Label for the latest button press""" + return self.response[0] if self.response else None + + @property + def response_timestamp(self) -> Optional[float]: + """Timestamp for the latest button response""" + return self.response[1] if self.response else None + + def _reset(self) -> None: + """Reset any existing events and timers.""" + self._timer = self.make_timer(self.max_wait) + self.response = None + event.clearEvents(eventType='keyboard') + self._timer.reset() + + def await_response(self): + """Wait for a button response for a maximum number of seconds. Wait + period could end early if the class determines that some other + criteria have been met (such as an acceptable response).""" + + self._reset() + while self._should_keep_waiting() and self._within_wait_period(): + self._check_key_press() + + def has_response(self) -> bool: + """Whether a response has been provided""" + return self.response is not None + + def _check_key_press(self) -> None: + """Check for any key press events and set the latest as the response.""" + self.response = get_key_press( + key_list=[self.key_input], + clock=self.clock, + ) + + def _within_wait_period(self) -> bool: + """Check that we are within the allotted time for a response.""" + return self._timer and self._timer.getTime() > 0 + + def _should_keep_waiting(self) -> bool: + """Check that we should keep waiting for responses.""" + return not self.has_response() + + @abstractmethod + def accept_result(self) -> bool: + """Should the result of a button press be affirmative""" + + +class AcceptButtonPressHandler(ButtonPressHandler): + """ButtonPressHandler where a matching button press indicates an affirmative result.""" + + def accept_result(self) -> bool: + """Should the result of a button press be affirmative""" + return self.has_response() + + +class RejectButtonPressHandler(ButtonPressHandler): + """ButtonPressHandler where a matching button press indicates a rejection.""" + + def accept_result(self) -> bool: + """Should the result of a button press be affirmative""" + return not self.has_response() + + +class PreviewOnlyButtonPressHandler(ButtonPressHandler): + """ButtonPressHandler that waits for the entire span of the configured max_wait.""" + + def _should_keep_waiting(self) -> bool: + return True + + def accept_result(self) -> bool: + """Should the result of a button press be affirmative""" + return True + + +def get_button_handler_class( + mode: ButtonPressMode) -> Type[ButtonPressHandler]: + """Get the appropriate handler constructor for the given button press mode.""" + return { + ButtonPressMode.NOTHING: PreviewOnlyButtonPressHandler, + ButtonPressMode.ACCEPT: AcceptButtonPressHandler, + ButtonPressMode.REJECT: RejectButtonPressHandler + }.get(mode) diff --git a/bcipy/display/demo/matrix/demo_calibration_matrix.py b/bcipy/display/demo/matrix/demo_calibration_matrix.py index 2e1cbf3ce..bb1a1cb02 100644 --- a/bcipy/display/demo/matrix/demo_calibration_matrix.py +++ b/bcipy/display/demo/matrix/demo_calibration_matrix.py @@ -5,6 +5,7 @@ from bcipy.display import (InformationProperties, StimuliProperties, init_display_window) from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.matrix.display import MatrixDisplay info = InformationProperties( @@ -34,11 +35,17 @@ win.recordFrameIntervals = False task_bar = CalibrationTaskBar(win, inquiry_count=4, current_index=0, font='Arial') +preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=2, + preview_inquiry_key_input='return', + preview_inquiry_progress_method=2, + preview_inquiry_isi=1) matrix_display = MatrixDisplay(win, experiment_clock, stim_properties, task_bar=task_bar, - info=info) + info=info, + preview_config=preview_config) time_target = 1 time_fixation = 0.5 diff --git a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py index 70fd4b92c..33b27ce2c 100644 --- a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py +++ b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py @@ -8,6 +8,7 @@ from bcipy.display import (InformationProperties, StimuliProperties, init_display_window) from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.matrix.display import MatrixDisplay font = "Overpass Mono" @@ -72,13 +73,18 @@ spelled_text='COPY_PHA', colors=['white', 'green'], font=font) - +preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=2, + preview_inquiry_key_input='return', + preview_inquiry_progress_method=0, + preview_inquiry_isi=1) display = MatrixDisplay(win, experiment_clock, stim_properties, task_bar, info, - should_prompt_target=False) + should_prompt_target=False, + preview_config=preview_config) counter = 0 diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 6e7ddba30..86e037539 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -1,7 +1,8 @@ # mypy: disable-error-code="assignment,empty-body" from abc import ABC, abstractmethod +from enum import Enum from logging import Logger -from typing import Any, List, Optional, Tuple, Union +from typing import Any, List, NamedTuple, Optional, Tuple, Union from psychopy import visual @@ -237,7 +238,12 @@ def build_info_text(self, window: visual.Window) -> List[visual.TextStim]: opacity=1, depth=-6.0)) return self.text_stim - +class ButtonPressMode(Enum): + """Represents the possible meanings for a button press (when using an Inquiry Preview.)""" + NOTHING = 0 + ACCEPT = 1 + REJECT = 2 + class PreviewInquiryProperties: """"Preview Inquiry Properties. An encapsulation of properties relevant to preview_inquiry() operation. @@ -268,6 +274,18 @@ def __init__( self.preview_only = preview_only self.preview_inquiry_isi = preview_inquiry_isi +class PreviewParams(NamedTuple): + """Parameters relevant for the Inquiry Preview functionality""" + show_preview_inquiry: bool + preview_inquiry_length:float + preview_inquiry_key_input: str + preview_inquiry_progress_method: int + preview_inquiry_isi: float + + @property + def button_press_mode(self): + return ButtonPressMode(self.preview_inquiry_progress_method) + class VEPStimuliProperties(StimuliProperties): diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index b36ba75d3..af52ceace 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -8,7 +8,10 @@ from bcipy.config import MATRIX_IMAGE_FILENAME from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, StimuliProperties) +from bcipy.display.components.button_press_handler import ( + ButtonPressHandler, get_button_handler_class) from bcipy.display.components.task_bar import TaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.matrix.layout import symbol_positions from bcipy.helpers.stimuli import resize_image from bcipy.helpers.symbols import alphabet @@ -48,7 +51,8 @@ def __init__(self, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, should_prompt_target: bool = True, - sort_order: Optional[Callable] = None): + sort_order: Optional[Callable] = None, + preview_config: Optional[PreviewParams] = None): """Initialize Matrix display parameters and objects. PARAMETERS: @@ -73,6 +77,7 @@ def __init__(self, the first symbol of each inquiry. For example: [target, fixation, *stim]. sort_order - optional function to define the position index for each symbol. Using a custom function it is possible to skip a position. + preview_config - optional configuration for previewing inquiries """ self.window = window @@ -114,6 +119,9 @@ def __init__(self, self.stim_registry = self.build_grid() self.should_prompt_target = should_prompt_target + self.preview_params = preview_config + self._preview_button_handler = self.init_preview_button_handler() + self.logger.info( f"Symbol positions ({display_container.units} units):\n{self.stim_positions}" ) @@ -128,6 +136,11 @@ def stim_positions(self) -> Dict[str, Tuple[float, float]]: for sym, stim in self.stim_registry.items() } + @property + def preview_enabled(self) -> bool: + """Should the inquiry preview be enabled.""" + return self.preview_params and self.preview_params.show_preview_inquiry + def capture_grid_screenshot(self, file_path: str) -> None: """Capture Grid Screenshot. @@ -171,12 +184,13 @@ def symbol_durations(self) -> List[SymbolDuration]: for sti in zip(self.stimuli_inquiry, self.stimuli_timing, self.stimuli_colors) ] - def add_timing(self, stimuli: str): + def add_timing(self, stimuli: str, stamp: Optional[float] = None): """Add a new timing entry using the stimuli as a label. Useful as a callback function to register a marker at the time it is first displayed.""" - self._timing.append((stimuli, self.experiment_clock.getTime())) + stamp = stamp or self.experiment_clock.getTime() + self._timing.append((stimuli, stamp)) def reset_timing(self): """Reset the trigger timing.""" @@ -196,7 +210,12 @@ def do_inquiry(self) -> List[Tuple[str, float]]: else: [fixation, *stim] = symbol_durations - self.animate_scp(fixation, stim) + should_proceed = True + if self.preview_enabled: + should_proceed = self.preview_inquiry(stim) + + if should_proceed: + self.animate_scp(fixation, stim) return self._timing @@ -217,7 +236,7 @@ def build_grid(self) -> Dict[str, visual.TextStim]: def draw_grid(self, opacity: float = 1, color: Optional[str] = 'white', - highlight: Optional[str] = None, + highlight: Optional[List[str]] = None, highlight_color: Optional[str] = None): """Draw the grid. @@ -225,16 +244,16 @@ def draw_grid(self, ---------- opacity - opacity for each item in the matrix color - optional color for each item in the matrix - highlight - optional stim label for the item to be highlighted + highlight - optional list of stim labels to be highlighted (rendered using the highlight_opacity). highlight_color - optional color to use for rendering the highlighted stim. """ for symbol, stim in self.stim_registry.items(): - stim.setOpacity(self.highlight_opacity if highlight == - symbol else opacity) + should_highlight = highlight and (symbol in highlight) + stim.setOpacity(self.highlight_opacity if should_highlight else opacity) stim.setColor(highlight_color if highlight_color and - highlight == symbol else color) + should_highlight else color) stim.draw() def prompt_target(self, target: SymbolDuration) -> float: @@ -249,14 +268,57 @@ def prompt_target(self, target: SymbolDuration) -> float: self.window.callOnFlip(self.add_timing, target.symbol) self.draw(grid_opacity=self.start_opacity, duration=target.duration, - highlight=target.symbol, + highlight=[target.symbol], highlight_color=target.color) + def init_preview_button_handler(self) -> Optional[ButtonPressHandler]: + """"Returns a button press handler for inquiry preview.""" + if not self.preview_enabled: + return None + + params = self.preview_params + make_handler = get_button_handler_class(params.button_press_mode) + return make_handler(max_wait=params.preview_inquiry_length, + key_input=params.preview_inquiry_key_input, + clock=self.experiment_clock) + + def preview_inquiry(self, stimuli: List[SymbolDuration]) -> bool: + """"Preview the inquiry and handle any button presses. + Parameters + ---------- + stimuli - list of stimuli to highlight (will be flashed in next inquiry) + + Returns + ------- + boolean indicating whether the participant would like to proceed + with the inquiry (True) or reject the inquiry (False) and + go on to the next one. + """ + assert self.preview_enabled, "Preview feature not enabled." + + handler = self._preview_button_handler + self.window.callOnFlip(self.add_timing, 'inquiry_preview') + + self.draw_preview(stimuli) + handler.await_response() + + if handler.has_response(): + self.add_timing(handler.response_label, handler.response_timestamp) + + self.draw(grid_opacity=self.start_opacity, duration=self.preview_params.preview_inquiry_isi) + return handler.accept_result() + + def draw_preview(self, stimuli: List[SymbolDuration]) -> None: + """Draw the inquiry preview by highlighting all of the symbols in the + list.""" + self.draw(grid_opacity=self.start_opacity, + highlight=[stim.symbol for stim in stimuli]) + def draw(self, grid_opacity: float, grid_color: Optional[str] = None, duration: Optional[float] = None, - highlight: Optional[str] = None, + highlight: Optional[List[str]] = None, highlight_color: Optional[str] = None): """Draw all screen elements and flip the window. @@ -265,7 +327,7 @@ def draw(self, grid_opacity - opacity value to use on all grid symbols grid_color - optional color to use for all grid symbols duration - optional seconds to wait after flipping the window. - highlight - optional symbol to highlight in the grid. + highlight - optional list of symbols to highlight in the grid. highlight_color - optional color to use for rendering the highlighted stim. """ @@ -299,7 +361,7 @@ def animate_scp(self, fixation: SymbolDuration, self.window.callOnFlip(self.add_timing, stim.symbol) self.draw(grid_opacity=self.start_opacity, duration=stim.duration, - highlight=stim.symbol, + highlight=[stim.symbol], highlight_color=stim.color) self.draw(self.start_opacity) diff --git a/bcipy/display/tests/components/test_button_press_handler.py b/bcipy/display/tests/components/test_button_press_handler.py new file mode 100644 index 000000000..9cfcc5dbf --- /dev/null +++ b/bcipy/display/tests/components/test_button_press_handler.py @@ -0,0 +1,205 @@ +"""Tests for button press handlers.""" + +import unittest +from unittest.mock import Mock, patch + +from bcipy.display.components.button_press_handler import ( + AcceptButtonPressHandler, PreviewOnlyButtonPressHandler, + RejectButtonPressHandler, get_button_handler_class) +from bcipy.display.main import ButtonPressMode + + +class TestButtonPressModule(unittest.TestCase): + """Test the module functions""" + + def test_get_handler_class(self): + """Test get handler class""" + self.assertEqual(PreviewOnlyButtonPressHandler, + get_button_handler_class(ButtonPressMode.NOTHING)) + self.assertEqual(AcceptButtonPressHandler, + get_button_handler_class(ButtonPressMode.ACCEPT)) + self.assertEqual(RejectButtonPressHandler, + get_button_handler_class(ButtonPressMode.REJECT)) + + +class TestPreviewOnlyButtonPressHandler(unittest.TestCase): + """Test the PreviewOnlyButtonPressHandler""" + + @patch('bcipy.display.components.button_press_handler.get_key_press') + def test_preview_only(self, get_key_press_mock): + """Test preview only""" + mock_timer_class = Mock() + mock_timer = Mock() + mock_timer_class.return_value = mock_timer + + # Timer counts down + mock_timer.reset.return_value = None + mock_timer.getTime.side_effect = [2.0, 1.0, 0.0] + get_key_press_mock.return_value = None + + handler = PreviewOnlyButtonPressHandler(max_wait=2, + key_input='space', + timer=mock_timer_class) + handler.await_response() + + mock_timer_class.assert_called_once() + mock_timer.reset.assert_called_once() + self.assertEqual(3, mock_timer.getTime.call_count) + self.assertEqual(2, get_key_press_mock.call_count) + + self.assertTrue(handler.accept_result()) + self.assertFalse(handler.has_response()) + + @patch('bcipy.display.components.button_press_handler.get_key_press') + def test_preview_only_with_keypress(self, get_key_press_mock): + """Test preview only with a keypress""" + mock_timer_class = Mock() + mock_timer = Mock() + mock_timer_class.return_value = mock_timer + + # Timer counts down + mock_timer.reset.return_value = None + mock_timer.getTime.side_effect = [2.0, 1.0, 0.0] + get_key_press_mock.side_effect = [None, ['bcipy_key_press_space', 1.5]] + + handler = PreviewOnlyButtonPressHandler(max_wait=2, + key_input='space', + timer=mock_timer_class) + handler.await_response() + + mock_timer_class.assert_called_once() + mock_timer.reset.assert_called_once() + self.assertEqual(3, mock_timer.getTime.call_count) + self.assertEqual(2, get_key_press_mock.call_count) + + self.assertTrue(handler.accept_result()) + self.assertTrue(handler.has_response()) + + @patch('bcipy.display.components.button_press_handler.get_key_press') + def test_preview_only_with_keypress_in_middle(self, get_key_press_mock): + """Test preview only with a keypress in the middle of the wait period""" + mock_timer_class = Mock() + mock_timer = Mock() + mock_timer_class.return_value = mock_timer + + # Timer counts down + mock_timer.reset.return_value = None + mock_timer.getTime.side_effect = [3.0, 2.0, 1.0, 0.0] + get_key_press_mock.side_effect = [ + None, ['bcipy_key_press_space', 1.5], None + ] + + handler = PreviewOnlyButtonPressHandler(max_wait=3, + key_input='space', + timer=mock_timer_class) + handler.await_response() + + self.assertEqual(4, mock_timer.getTime.call_count) + self.assertEqual(3, get_key_press_mock.call_count) + + self.assertTrue(handler.accept_result()) + self.assertFalse(handler.has_response()) + + +class TestAcceptButtonPressHandler(unittest.TestCase): + """Test for Press To Accept behavior""" + + @patch('bcipy.display.components.button_press_handler.get_key_press') + def test_press_to_accept_with_no_presses(self, get_key_press_mock): + """Test press to accept with no button presses.""" + mock_timer_class = Mock() + mock_timer = Mock() + mock_timer_class.return_value = mock_timer + + # Timer counts down + mock_timer.reset.return_value = None + mock_timer.getTime.side_effect = [2.0, 1.0, 0.0] + get_key_press_mock.return_value = None + + handler = AcceptButtonPressHandler(max_wait=2, + key_input='space', + timer=mock_timer_class) + handler.await_response() + + self.assertEqual(3, mock_timer.getTime.call_count) + self.assertEqual(2, get_key_press_mock.call_count) + + self.assertFalse(handler.accept_result()) + self.assertFalse(handler.has_response()) + + @patch('bcipy.display.components.button_press_handler.get_key_press') + def test_press_to_accept_with_keypress(self, get_key_press_mock): + """Test press to accept with a keypress""" + mock_timer_class = Mock() + mock_timer = Mock() + mock_timer_class.return_value = mock_timer + + # Timer counts down + mock_timer.reset.return_value = None + mock_timer.getTime.side_effect = [3.0, 2.0, 1.0, 0.0] + get_key_press_mock.side_effect = [None, ['bcipy_key_press_space', 1.5]] + + handler = AcceptButtonPressHandler(max_wait=2, + key_input='space', + timer=mock_timer_class) + handler.await_response() + + self.assertEqual(2, mock_timer.getTime.call_count) + self.assertEqual(2, get_key_press_mock.call_count) + + self.assertTrue(handler.accept_result()) + self.assertTrue(handler.has_response()) + self.assertEqual('bcipy_key_press_space', handler.response_label) + self.assertEqual(1.5, handler.response_timestamp) + + +class TestRejectButtonPressHandler(unittest.TestCase): + """Test for Press To Reject behavior""" + + @patch('bcipy.display.components.button_press_handler.get_key_press') + def test_press_to_reject_with_no_presses(self, get_key_press_mock): + """Test press to reject with no button presses.""" + mock_timer_class = Mock() + mock_timer = Mock() + mock_timer_class.return_value = mock_timer + + # Timer counts down + mock_timer.reset.return_value = None + mock_timer.getTime.side_effect = [2.0, 1.0, 0.0] + get_key_press_mock.return_value = None + + handler = RejectButtonPressHandler(max_wait=2, + key_input='space', + timer=mock_timer_class) + handler.await_response() + + self.assertEqual(3, mock_timer.getTime.call_count) + self.assertEqual(2, get_key_press_mock.call_count) + + self.assertTrue(handler.accept_result()) + self.assertFalse(handler.has_response()) + + @patch('bcipy.display.components.button_press_handler.get_key_press') + def test_press_to_reject_with_keypress(self, get_key_press_mock): + """Test press to accept with a keypress""" + mock_timer_class = Mock() + mock_timer = Mock() + mock_timer_class.return_value = mock_timer + + # Timer counts down + mock_timer.reset.return_value = None + mock_timer.getTime.side_effect = [3.0, 2.0, 1.0, 0.0] + get_key_press_mock.side_effect = [None, ['bcipy_key_press_space', 1.5]] + + handler = RejectButtonPressHandler(max_wait=2, + key_input='space', + timer=mock_timer_class) + handler.await_response() + + self.assertEqual(2, mock_timer.getTime.call_count) + self.assertEqual(2, get_key_press_mock.call_count) + + self.assertFalse(handler.accept_result()) + self.assertTrue(handler.has_response()) + self.assertEqual('bcipy_key_press_space', handler.response_label) + self.assertEqual(1.5, handler.response_timestamp) diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index 6014fbafe..a4ab773aa 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -4,6 +4,7 @@ from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters @@ -104,4 +105,5 @@ def init_matrix_display(parameters: Parameters, window: visual.Window, width_pct=parameters['matrix_width'], height_pct=1 - (2 * task_bar.height_pct), trigger_type=parameters['trigger_type'], - symbol_set=symbol_set) + symbol_set=symbol_set, + preview_config=parameters.instantiate(PreviewParams)) diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index 56caf03fb..a605688b8 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -2,6 +2,7 @@ from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask @@ -80,4 +81,5 @@ def init_display( width_pct=parameters['matrix_width'], height_pct=1 - (2 * task_bar.height_pct), trigger_type=parameters['trigger_type'], - should_prompt_target=False) + should_prompt_target=False, + preview_config=parameters.instantiate(PreviewParams)) From 2bab7853be372dad12164a9b08022fb22b7c87e1 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 2 Oct 2024 13:10:17 -0700 Subject: [PATCH 314/330] Linting --- bcipy/display/main.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 86e037539..2e1764700 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -238,12 +238,14 @@ def build_info_text(self, window: visual.Window) -> List[visual.TextStim]: opacity=1, depth=-6.0)) return self.text_stim + class ButtonPressMode(Enum): """Represents the possible meanings for a button press (when using an Inquiry Preview.)""" NOTHING = 0 ACCEPT = 1 REJECT = 2 - + + class PreviewInquiryProperties: """"Preview Inquiry Properties. An encapsulation of properties relevant to preview_inquiry() operation. @@ -274,10 +276,11 @@ def __init__( self.preview_only = preview_only self.preview_inquiry_isi = preview_inquiry_isi + class PreviewParams(NamedTuple): """Parameters relevant for the Inquiry Preview functionality""" show_preview_inquiry: bool - preview_inquiry_length:float + preview_inquiry_length: float preview_inquiry_key_input: str preview_inquiry_progress_method: int preview_inquiry_isi: float @@ -285,7 +288,7 @@ class PreviewParams(NamedTuple): @property def button_press_mode(self): return ButtonPressMode(self.preview_inquiry_progress_method) - + class VEPStimuliProperties(StimuliProperties): From de697bad97fce41ba49415f190e93856b6cdf010 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 2 Oct 2024 16:00:50 -0700 Subject: [PATCH 315/330] Added unit tests for matrix display --- .../paradigm/matrix/test_matrix_display.py | 133 ++++++++++++++---- 1 file changed, 106 insertions(+), 27 deletions(-) diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py index ca2579452..36bccca82 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py @@ -7,18 +7,18 @@ from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import TaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.matrix.display import MatrixDisplay, SymbolDuration # Define some reusable elements to test Matrix Display with LEN_STIM = 10 -TEST_STIM = StimuliProperties( - stim_font='Arial', - stim_pos=(-0.6, 0.4), - stim_height=0.1, - stim_inquiry=['A'], - stim_colors=[], - stim_timing=[0.1], - is_txt_stim=True) +TEST_STIM = StimuliProperties(stim_font='Arial', + stim_pos=(-0.6, 0.4), + stim_height=0.1, + stim_inquiry=['A'], + stim_colors=[], + stim_timing=[0.1], + is_txt_stim=True) TEST_INFO = InformationProperties( info_color=['White'], @@ -39,7 +39,8 @@ def setUp(self): self.window = mock({"units": "norm", "size": (2.0, 2.0)}) self.experiment_clock = mock() self.static_clock = mock() - self.text_stim_mock = mock({'pos': (0, 0)}, spec=psychopy.visual.TextStim) + self.text_stim_mock = mock({'pos': (0, 0)}, + spec=psychopy.visual.TextStim) when(self.text_stim_mock).setOpacity(...).thenReturn() when(self.text_stim_mock).setColor(...).thenReturn() when(self.text_stim_mock).draw(...).thenReturn() @@ -99,13 +100,17 @@ def tearDown(self): unstub() def test_information_properties_set_correctly(self): - self.assertEqual(self.matrix.info_text, self.info.build_info_text(self.window)) + self.assertEqual(self.matrix.info_text, + self.info.build_info_text(self.window)) def test_schedule_to(self): # Test schedule_to method correctly sets stim inquiry, timing, and colors to given parameters. - self.matrix.schedule_to(self.stimuli.stim_inquiry, self.stimuli.stim_timing, self.stimuli.stim_colors) + self.matrix.schedule_to(self.stimuli.stim_inquiry, + self.stimuli.stim_timing, + self.stimuli.stim_colors) - self.assertEqual(self.matrix.stimuli_inquiry, self.stimuli.stim_inquiry) + self.assertEqual(self.matrix.stimuli_inquiry, + self.stimuli.stim_inquiry) self.assertEqual(self.matrix.stimuli_timing, self.stimuli.stim_timing) def test_do_inquiry(self): @@ -129,16 +134,91 @@ def test_do_inquiry(self): verify(self.matrix, times=1).prompt_target(target) verify(self.matrix, times=1).animate_scp(fixation, stim_durations) + def test_do_inquiry_with_preview_accepted(self): + """Verify that the symbols are animated following an inquiry preview + in which the user accepts the input.""" + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=2, + preview_inquiry_key_input='return', + preview_inquiry_progress_method=2, + preview_inquiry_isi=1) + matrix = MatrixDisplay(window=self.window, + experiment_clock=self.experiment_clock, + stimuli=self.stimuli, + task_bar=self.task_bar_mock, + info=self.info, + preview_config=preview_config) + when(matrix)._trigger_pulse().thenReturn() + + stimuli = ['X', '+', 'A', 'B', 'C'] + timing = [0.5, 1.0, 0.2, 0.2, 0.2] + + target = SymbolDuration('X', 0.5) + fixation = SymbolDuration('+', 1.0) + stim_durations = [ + SymbolDuration(*sti) + for sti in [('A', 0.2), ('B', 0.2), ('C', 0.2)] + ] + + when(matrix).prompt_target(any()).thenReturn(0.0) + when(matrix).animate_scp(any(), any()).thenReturn([]) + when(matrix).preview_inquiry(any()).thenReturn(True) + + matrix.schedule_to(stimuli, timing, []) + matrix.do_inquiry() + + verify(matrix, times=1)._trigger_pulse() + verify(matrix, times=1).prompt_target(target) + verify(matrix, times=1).preview_inquiry(stim_durations) + verify(matrix, times=1).animate_scp(fixation, stim_durations) + + def test_do_inquiry_with_preview_rejected(self): + """Test that if an inquiry preview is rejected the inquiry does not + animate.""" + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=2, + preview_inquiry_key_input='return', + preview_inquiry_progress_method=2, + preview_inquiry_isi=1) + matrix = MatrixDisplay(window=self.window, + experiment_clock=self.experiment_clock, + stimuli=self.stimuli, + task_bar=self.task_bar_mock, + info=self.info, + preview_config=preview_config) + when(matrix)._trigger_pulse().thenReturn() + + stimuli = ['X', '+', 'A', 'B', 'C'] + timing = [0.5, 1.0, 0.2, 0.2, 0.2] + + target = SymbolDuration('X', 0.5) + fixation = SymbolDuration('+', 1.0) + stim_durations = [ + SymbolDuration(*sti) + for sti in [('A', 0.2), ('B', 0.2), ('C', 0.2)] + ] + + when(matrix).prompt_target(any()).thenReturn(0.0) + when(matrix).preview_inquiry(any()).thenReturn(False) + when(matrix).animate_scp(any(), any()).thenReturn([]) + + matrix.schedule_to(stimuli, timing, []) + matrix.do_inquiry() + + verify(matrix, times=1)._trigger_pulse() + verify(matrix, times=1).prompt_target(target) + verify(matrix, times=1).preview_inquiry(stim_durations) + verify(matrix, times=0).animate_scp(fixation, stim_durations) + def test_build_grid(self): # mock the text stims and increment_position - when(psychopy.visual).TextStim( - win=self.window, - height=any(), - text=any(), - color=any(), - pos=any(), - opacity=any() - ).thenReturn(self.text_stim_mock) + when(psychopy.visual).TextStim(win=self.window, + height=any(), + text=any(), + color=any(), + pos=any(), + opacity=any()).thenReturn( + self.text_stim_mock) sym_length = len(self.matrix.symbol_set) grid = self.matrix.build_grid() @@ -152,13 +232,12 @@ def test_draw_grid(self): def test_animate_scp(self): # mock the text stims and window - when(psychopy.visual).TextStim( - win=self.window, - height=any(), - text=any(), - pos=any(), - opacity=any() - ).thenReturn(self.text_stim_mock) + when(psychopy.visual).TextStim(win=self.window, + height=any(), + text=any(), + pos=any(), + opacity=any()).thenReturn( + self.text_stim_mock) when(self.matrix.window).callOnFlip(any(), any(), any()).thenReturn() when(self.matrix.window).callOnFlip(any(), any()).thenReturn() # mock the drawing of text stims From 7629ba812238699e85111b609e6fe1a6a6cad7e5 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 2 Oct 2024 17:50:41 -0700 Subject: [PATCH 316/330] Created a helper method for creating button press handlers. Refactor to move some code to main module --- .../components/button_press_handler.py | 11 ---- bcipy/display/main.py | 33 +++++++++- bcipy/display/paradigm/matrix/display.py | 64 ++++++++----------- .../components/test_button_press_handler.py | 16 +---- bcipy/display/tests/test_main.py | 20 +++++- 5 files changed, 76 insertions(+), 68 deletions(-) diff --git a/bcipy/display/components/button_press_handler.py b/bcipy/display/components/button_press_handler.py index 3b3652409..2d98b26ac 100644 --- a/bcipy/display/components/button_press_handler.py +++ b/bcipy/display/components/button_press_handler.py @@ -4,7 +4,6 @@ from psychopy import core, event -from bcipy.display.main import ButtonPressMode from bcipy.helpers.clock import Clock from bcipy.helpers.task import get_key_press @@ -107,13 +106,3 @@ def _should_keep_waiting(self) -> bool: def accept_result(self) -> bool: """Should the result of a button press be affirmative""" return True - - -def get_button_handler_class( - mode: ButtonPressMode) -> Type[ButtonPressHandler]: - """Get the appropriate handler constructor for the given button press mode.""" - return { - ButtonPressMode.NOTHING: PreviewOnlyButtonPressHandler, - ButtonPressMode.ACCEPT: AcceptButtonPressHandler, - ButtonPressMode.REJECT: RejectButtonPressHandler - }.get(mode) diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 2e1764700..ab9e673af 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -2,10 +2,13 @@ from abc import ABC, abstractmethod from enum import Enum from logging import Logger -from typing import Any, List, NamedTuple, Optional, Tuple, Union +from typing import Any, List, NamedTuple, Optional, Tuple, Type, Union from psychopy import visual +from bcipy.display.components.button_press_handler import ( + AcceptButtonPressHandler, ButtonPressHandler, + PreviewOnlyButtonPressHandler, RejectButtonPressHandler) from bcipy.helpers.clock import Clock from bcipy.helpers.system_utils import get_screen_info @@ -65,7 +68,7 @@ def draw_static(self) -> None: """ ... - def preview_inquiry(self) -> List[float]: + def preview_inquiry(self, *args, **kwargs) -> List[float]: """Preview Inquiry. Display an inquiry or instruction beforehand to the user. This should be called before do_inquiry. @@ -278,7 +281,11 @@ def __init__( class PreviewParams(NamedTuple): - """Parameters relevant for the Inquiry Preview functionality""" + """Parameters relevant for the Inquiry Preview functionality. + + Create from an existing Parameters instance using: + >>> parameters.instantiate(PreviewParams) + """ show_preview_inquiry: bool preview_inquiry_length: float preview_inquiry_key_input: str @@ -287,9 +294,29 @@ class PreviewParams(NamedTuple): @property def button_press_mode(self): + """Mode indicated by the inquiry progress method.""" return ButtonPressMode(self.preview_inquiry_progress_method) +def get_button_handler_class( + mode: ButtonPressMode) -> Type[ButtonPressHandler]: + """Get the appropriate handler constructor for the given button press mode.""" + return { + ButtonPressMode.NOTHING: PreviewOnlyButtonPressHandler, + ButtonPressMode.ACCEPT: AcceptButtonPressHandler, + ButtonPressMode.REJECT: RejectButtonPressHandler + }.get(mode) + + +def init_preview_button_handler(params: PreviewParams, + experiment_clock: Clock) -> ButtonPressHandler: + """"Returns a button press handler for inquiry preview.""" + make_handler = get_button_handler_class(params.button_press_mode) + return make_handler(max_wait=params.preview_inquiry_length, + key_input=params.preview_inquiry_key_input, + clock=experiment_clock) + + class VEPStimuliProperties(StimuliProperties): def __init__(self, diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index af52ceace..81faedec0 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -8,10 +8,8 @@ from bcipy.config import MATRIX_IMAGE_FILENAME from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, StimuliProperties) -from bcipy.display.components.button_press_handler import ( - ButtonPressHandler, get_button_handler_class) from bcipy.display.components.task_bar import TaskBar -from bcipy.display.main import PreviewParams +from bcipy.display.main import PreviewParams, init_preview_button_handler from bcipy.display.paradigm.matrix.layout import symbol_positions from bcipy.helpers.stimuli import resize_image from bcipy.helpers.symbols import alphabet @@ -120,7 +118,8 @@ def __init__(self, self.should_prompt_target = should_prompt_target self.preview_params = preview_config - self._preview_button_handler = self.init_preview_button_handler() + self.preview_button_handler = init_preview_button_handler( + preview_config, experiment_clock) if self.preview_enabled else None self.logger.info( f"Symbol positions ({display_container.units} units):\n{self.stim_positions}" @@ -171,7 +170,8 @@ def schedule_to(self, stimuli: list, timing: list, colors: list) -> None: self.stimuli_inquiry = stimuli self.stimuli_timing = timing if colors: - assert len(stimuli) == len(colors), "each stimuli must have a color" + assert len(stimuli) == len( + colors), "each stimuli must have a color" self.stimuli_colors = colors else: self.stimuli_colors = [self.grid_color] * len(stimuli) @@ -180,8 +180,8 @@ def symbol_durations(self) -> List[SymbolDuration]: """Symbols associated with their duration for the currently configured stimuli_inquiry.""" return [ - SymbolDuration(*sti) - for sti in zip(self.stimuli_inquiry, self.stimuli_timing, self.stimuli_colors) + SymbolDuration(*sti) for sti in zip( + self.stimuli_inquiry, self.stimuli_timing, self.stimuli_colors) ] def add_timing(self, stimuli: str, stamp: Optional[float] = None): @@ -251,9 +251,10 @@ def draw_grid(self, """ for symbol, stim in self.stim_registry.items(): should_highlight = highlight and (symbol in highlight) - stim.setOpacity(self.highlight_opacity if should_highlight else opacity) - stim.setColor(highlight_color if highlight_color and - should_highlight else color) + stim.setOpacity( + self.highlight_opacity if should_highlight else opacity) + stim.setColor(highlight_color + if highlight_color and should_highlight else color) stim.draw() def prompt_target(self, target: SymbolDuration) -> float: @@ -271,17 +272,6 @@ def prompt_target(self, target: SymbolDuration) -> float: highlight=[target.symbol], highlight_color=target.color) - def init_preview_button_handler(self) -> Optional[ButtonPressHandler]: - """"Returns a button press handler for inquiry preview.""" - if not self.preview_enabled: - return None - - params = self.preview_params - make_handler = get_button_handler_class(params.button_press_mode) - return make_handler(max_wait=params.preview_inquiry_length, - key_input=params.preview_inquiry_key_input, - clock=self.experiment_clock) - def preview_inquiry(self, stimuli: List[SymbolDuration]) -> bool: """"Preview the inquiry and handle any button presses. Parameters @@ -295,8 +285,9 @@ def preview_inquiry(self, stimuli: List[SymbolDuration]) -> bool: go on to the next one. """ assert self.preview_enabled, "Preview feature not enabled." + assert self.preview_button_handler, "Button handler must be initialized" - handler = self._preview_button_handler + handler = self.preview_button_handler self.window.callOnFlip(self.add_timing, 'inquiry_preview') self.draw_preview(stimuli) @@ -305,7 +296,8 @@ def preview_inquiry(self, stimuli: List[SymbolDuration]) -> bool: if handler.has_response(): self.add_timing(handler.response_label, handler.response_timestamp) - self.draw(grid_opacity=self.start_opacity, duration=self.preview_params.preview_inquiry_isi) + self.draw(grid_opacity=self.start_opacity, + duration=self.preview_params.preview_inquiry_isi) return handler.accept_result() def draw_preview(self, stimuli: List[SymbolDuration]) -> None: @@ -382,20 +374,17 @@ def wait_screen(self, message: str, message_color: str) -> None: # try adding the BciPy logo to the wait screen try: - wait_logo = visual.ImageStim( - self.window, - image=BCIPY_LOGO_PATH, - pos=(0, .25), - mask=None, - ori=0.0) - wait_logo.size = resize_image( - BCIPY_LOGO_PATH, - self.window.size, - 1) + wait_logo = visual.ImageStim(self.window, + image=BCIPY_LOGO_PATH, + pos=(0, .25), + mask=None, + ori=0.0) + wait_logo.size = resize_image(BCIPY_LOGO_PATH, self.window.size, 1) wait_logo.draw() except Exception as e: - self.logger.exception(f'Cannot load logo image from path=[{BCIPY_LOGO_PATH}]') + self.logger.exception( + f'Cannot load logo image from path=[{BCIPY_LOGO_PATH}]') raise e # Draw and flip the screen. @@ -436,10 +425,9 @@ def _trigger_pulse(self) -> None: beginning of an experiment. If drift is detected in your experiment, more frequent pulses and offset correction may be required. """ - calibration_time = _calibration_trigger( - self.experiment_clock, - trigger_type=self.trigger_type, - display=self.window) + calibration_time = _calibration_trigger(self.experiment_clock, + trigger_type=self.trigger_type, + display=self.window) # set the first stim time if not present and first_run to False if not self.first_stim_time: diff --git a/bcipy/display/tests/components/test_button_press_handler.py b/bcipy/display/tests/components/test_button_press_handler.py index 9cfcc5dbf..4de0bb832 100644 --- a/bcipy/display/tests/components/test_button_press_handler.py +++ b/bcipy/display/tests/components/test_button_press_handler.py @@ -5,21 +5,7 @@ from bcipy.display.components.button_press_handler import ( AcceptButtonPressHandler, PreviewOnlyButtonPressHandler, - RejectButtonPressHandler, get_button_handler_class) -from bcipy.display.main import ButtonPressMode - - -class TestButtonPressModule(unittest.TestCase): - """Test the module functions""" - - def test_get_handler_class(self): - """Test get handler class""" - self.assertEqual(PreviewOnlyButtonPressHandler, - get_button_handler_class(ButtonPressMode.NOTHING)) - self.assertEqual(AcceptButtonPressHandler, - get_button_handler_class(ButtonPressMode.ACCEPT)) - self.assertEqual(RejectButtonPressHandler, - get_button_handler_class(ButtonPressMode.REJECT)) + RejectButtonPressHandler) class TestPreviewOnlyButtonPressHandler(unittest.TestCase): diff --git a/bcipy/display/tests/test_main.py b/bcipy/display/tests/test_main.py index 9f3e50f9e..28d1d841c 100644 --- a/bcipy/display/tests/test_main.py +++ b/bcipy/display/tests/test_main.py @@ -1,8 +1,13 @@ import unittest -from mockito import any, mock, when, unstub import psychopy +from mockito import any, mock, unstub, when + from bcipy.display import init_display_window +from bcipy.display.components.button_press_handler import ( + AcceptButtonPressHandler, PreviewOnlyButtonPressHandler, + RejectButtonPressHandler) +from bcipy.display.main import ButtonPressMode, get_button_handler_class class TestInitializeDisplayWindow(unittest.TestCase): @@ -44,5 +49,18 @@ def test_init_display_window_returns_psychopy_window(self): self.assertEqual(self.display_window, self.window) +class TestButtonPressFunctions(unittest.TestCase): + """Test the module functions""" + + def test_get_handler_class(self): + """Test get handler class""" + self.assertEqual(PreviewOnlyButtonPressHandler, + get_button_handler_class(ButtonPressMode.NOTHING)) + self.assertEqual(AcceptButtonPressHandler, + get_button_handler_class(ButtonPressMode.ACCEPT)) + self.assertEqual(RejectButtonPressHandler, + get_button_handler_class(ButtonPressMode.REJECT)) + + if __name__ == '__main__': unittest.main() From f78e927effd960b74fa23b5eabf8db3413c898fc Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 4 Oct 2024 11:56:43 -0700 Subject: [PATCH 317/330] Fix typing issues --- bcipy/display/components/button_press_handler.py | 11 ++++++----- bcipy/display/main.py | 5 +++-- 2 files changed, 9 insertions(+), 7 deletions(-) diff --git a/bcipy/display/components/button_press_handler.py b/bcipy/display/components/button_press_handler.py index 2d98b26ac..3a087f74d 100644 --- a/bcipy/display/components/button_press_handler.py +++ b/bcipy/display/components/button_press_handler.py @@ -2,7 +2,8 @@ from abc import ABC, abstractmethod from typing import List, Optional, Type -from psychopy import core, event +from psychopy import event +from psychopy.core import CountdownTimer from bcipy.helpers.clock import Clock from bcipy.helpers.task import get_key_press @@ -15,7 +16,7 @@ def __init__(self, max_wait: float, key_input: str, clock: Optional[Clock] = None, - timer: Type[Clock] = core.CountdownTimer): + timer: Type[CountdownTimer] = CountdownTimer): """ Parameters ---------- @@ -28,7 +29,7 @@ def __init__(self, self.clock = clock or Clock() self.response: Optional[List] = None - self._timer = None + self._timer: Optional[CountdownTimer] = None self.make_timer = timer @property @@ -48,7 +49,7 @@ def _reset(self) -> None: event.clearEvents(eventType='keyboard') self._timer.reset() - def await_response(self): + def await_response(self) -> None: """Wait for a button response for a maximum number of seconds. Wait period could end early if the class determines that some other criteria have been met (such as an acceptable response).""" @@ -70,7 +71,7 @@ def _check_key_press(self) -> None: def _within_wait_period(self) -> bool: """Check that we are within the allotted time for a response.""" - return self._timer and self._timer.getTime() > 0 + return (self._timer is not None) and (self._timer.getTime() > 0) def _should_keep_waiting(self) -> bool: """Check that we should keep waiting for responses.""" diff --git a/bcipy/display/main.py b/bcipy/display/main.py index ab9e673af..52b227a29 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -301,11 +301,12 @@ def button_press_mode(self): def get_button_handler_class( mode: ButtonPressMode) -> Type[ButtonPressHandler]: """Get the appropriate handler constructor for the given button press mode.""" - return { + mapping = { ButtonPressMode.NOTHING: PreviewOnlyButtonPressHandler, ButtonPressMode.ACCEPT: AcceptButtonPressHandler, ButtonPressMode.REJECT: RejectButtonPressHandler - }.get(mode) + } + return mapping[mode] def init_preview_button_handler(params: PreviewParams, From 0eff172328e36c7205ea52519f29ab19a05c8b2e Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 4 Oct 2024 12:00:17 -0700 Subject: [PATCH 318/330] Refactored RSVP display to use button press handler. Fixed regression in Copy Phrase task which caused preview to be displayed twice. Updated demos and fixed unit tests --- .../demo/rsvp/demo_calibration_rsvp.py | 17 +- .../display/demo/rsvp/demo_copyphrase_rsvp.py | 44 +- bcipy/display/paradigm/matrix/display.py | 7 +- bcipy/display/paradigm/rsvp/display.py | 135 +++--- .../display/paradigm/rsvp/mode/calibration.py | 12 +- .../display/paradigm/rsvp/mode/copy_phrase.py | 18 +- .../tests/paradigm/rsvp/test_rsvp_display.py | 437 +++++++++--------- bcipy/task/paradigm/rsvp/copy_phrase.py | 13 +- .../tests/paradigm/rsvp/test_copy_phrase.py | 2 - 9 files changed, 347 insertions(+), 338 deletions(-) diff --git a/bcipy/display/demo/rsvp/demo_calibration_rsvp.py b/bcipy/display/demo/rsvp/demo_calibration_rsvp.py index 4ba601e96..58aeba78a 100644 --- a/bcipy/display/demo/rsvp/demo_calibration_rsvp.py +++ b/bcipy/display/demo/rsvp/demo_calibration_rsvp.py @@ -1,9 +1,11 @@ from psychopy import core +from bcipy.display import (InformationProperties, StimuliProperties, + init_display_window) +from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay from bcipy.helpers.clock import Clock -from bcipy.display import InformationProperties, StimuliProperties, init_display_window -from bcipy.display.components.task_bar import CalibrationTaskBar info = InformationProperties( info_color=['White'], @@ -44,7 +46,7 @@ 'full_screen': False, 'window_height': 500, 'window_width': 500, - 'stim_screen': 1, + 'stim_screen': 0, 'background_color': 'black' } win = init_display_window(window_parameters) @@ -70,13 +72,20 @@ inquiry_count=100, current_index=0, font='Arial') + +preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=2, + preview_inquiry_key_input='return', + preview_inquiry_progress_method=0, + preview_inquiry_isi=1) rsvp = CalibrationDisplay( win, clock, experiment_clock, stimuli, task_bar, - info) + info, + preview_config=preview_config) for idx_o in range(len(task_text)): diff --git a/bcipy/display/demo/rsvp/demo_copyphrase_rsvp.py b/bcipy/display/demo/rsvp/demo_copyphrase_rsvp.py index 558764f48..005b40d5c 100644 --- a/bcipy/display/demo/rsvp/demo_copyphrase_rsvp.py +++ b/bcipy/display/demo/rsvp/demo_copyphrase_rsvp.py @@ -4,24 +4,23 @@ from psychopy import core -from bcipy.display import ( - init_display_window, - InformationProperties, - PreviewInquiryProperties, - StimuliProperties) +from bcipy.display import (InformationProperties, StimuliProperties, + init_display_window) from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay from bcipy.helpers.clock import Clock # Initialize Stimulus is_txt_stim = True -show_preview_inquiry = True + # Inquiry preview -preview_inquiry_length = 5 -preview_inquiry_key_input = 'space' -preview_inquiry_progress_method = 1 # press to accept ==1 wait to accept ==2 -preview_inquiry_isi = 3 +preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=5, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=1, + preview_inquiry_isi=3) info = InformationProperties( info_color=['White'], @@ -50,7 +49,7 @@ 'full_screen': False, 'window_height': 500, 'window_width': 500, - 'stim_screen': 1, + 'stim_screen': 0, 'background_color': 'black' } @@ -86,12 +85,7 @@ clock = core.StaticPeriod(screenHz=frameRate) experiment_clock = Clock() task_bar = CopyPhraseTaskBar(win, task_text='COPY_PHRASE', font='Menlo') -preview_inquiry = PreviewInquiryProperties( - preview_only=True, - preview_inquiry_length=preview_inquiry_length, - preview_inquiry_key_input=preview_inquiry_key_input, - preview_inquiry_progress_method=preview_inquiry_progress_method, - preview_inquiry_isi=preview_inquiry_isi) + rsvp = CopyPhraseDisplay( win, clock, @@ -99,11 +93,11 @@ stimuli, task_bar, info, - preview_inquiry=preview_inquiry) + preview_config=preview_config) counter = 0 -for idx_o in range(len(spelled_text)): +for idx_o, _symbol in enumerate(spelled_text): rsvp.update_task_bar(text=spelled_text[idx_o]) rsvp.draw_static() @@ -119,16 +113,8 @@ core.wait(inter_stim_buffer) - if show_preview_inquiry: - inquiry_timing, proceed = rsvp.preview_inquiry() - print(inquiry_timing) - if proceed: - inquiry_timing.extend(rsvp.do_inquiry()) - else: - print('Rejected inquiry! Handle here') - inquiry_timing = rsvp.do_inquiry() - else: - inquiry_timing = rsvp.do_inquiry() + inquiry_timing = rsvp.do_inquiry() + print(inquiry_timing) core.wait(inter_stim_buffer) counter += 1 diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 81faedec0..6cbfa0198 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -120,6 +120,7 @@ def __init__(self, self.preview_params = preview_config self.preview_button_handler = init_preview_button_handler( preview_config, experiment_clock) if self.preview_enabled else None + self.preview_accepted = True self.logger.info( f"Symbol positions ({display_container.units} units):\n{self.stim_positions}" @@ -198,6 +199,7 @@ def reset_timing(self): def do_inquiry(self) -> List[Tuple[str, float]]: """Animates an inquiry of stimuli and returns a list of stimuli trigger timing.""" + self.preview_accepted = True self.reset_timing() symbol_durations = self.symbol_durations() @@ -210,11 +212,10 @@ def do_inquiry(self) -> List[Tuple[str, float]]: else: [fixation, *stim] = symbol_durations - should_proceed = True if self.preview_enabled: - should_proceed = self.preview_inquiry(stim) + self.preview_accepted = self.preview_inquiry(stim) - if should_proceed: + if self.preview_accepted: self.animate_scp(fixation, stim) return self._timing diff --git a/bcipy/display/paradigm/rsvp/display.py b/bcipy/display/paradigm/rsvp/display.py index b56ac4bc5..7e2d14163 100644 --- a/bcipy/display/paradigm/rsvp/display.py +++ b/bcipy/display/paradigm/rsvp/display.py @@ -2,16 +2,16 @@ import os.path as path from typing import List, Optional, Tuple -from psychopy import core, event, visual +from psychopy import core, visual from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, - PreviewInquiryProperties, StimuliProperties) + StimuliProperties) from bcipy.display.components.task_bar import TaskBar +from bcipy.display.main import PreviewParams, init_preview_button_handler from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import resize_image from bcipy.helpers.symbols import SPACE_CHAR from bcipy.helpers.system_utils import get_screen_info -from bcipy.helpers.task import get_key_press from bcipy.helpers.triggers import TriggerCallback, _calibration_trigger @@ -29,7 +29,7 @@ def __init__( stimuli: StimuliProperties, task_bar: TaskBar, info: InformationProperties, - preview_inquiry: Optional[PreviewInquiryProperties] = None, + preview_config: Optional[PreviewParams] = None, trigger_type: str = 'image', space_char: str = SPACE_CHAR, full_screen: bool = False): @@ -52,8 +52,8 @@ def __init__( info(InformationProperties): attributes to display informational stimuli alongside task and inquiry stimuli. # Preview Inquiry - preview_inquiry(PreviewInquiryProperties) Optional: attributes to display a preview of upcoming stimuli defined - via self.stimuli(StimuliProperties). + preview_config(PreviewParams) Optional: parameters used to specify the behavior for displaying a preview + of upcoming stimuli defined via self.stimuli(StimuliProperties). If None a preview is not displayed. trigger_type(str) default 'image': defines the calibration trigger type for the display at the beginning of any task. This will be used to reconcile timing differences between acquisition and the display. @@ -79,9 +79,11 @@ def __init__( self.stim_length = stimuli.stim_length self.full_screen = full_screen - self._preview_inquiry = preview_inquiry - if self._preview_inquiry: - self.preview_calibration = self._preview_inquiry.preview_on + + self.preview_params = preview_config + self.preview_button_handler = init_preview_button_handler( + preview_config, experiment_clock) if self.preview_enabled else None + self.preview_accepted = True self.staticPeriod = static_clock @@ -106,6 +108,11 @@ def __init__( # Create initial stimuli object for updating self.sti = stimuli.build_init_stimuli(window) + @property + def preview_enabled(self) -> bool: + """Should the inquiry preview be enabled.""" + return self.preview_params and self.preview_params.show_preview_inquiry + def draw_static(self): """Draw static elements in a stimulus.""" if self.task_bar: @@ -128,6 +135,15 @@ def schedule_to(self, self.stimuli_timing = timing or [] self.stimuli_colors = colors or [] + @property + def preview_index(self) -> int: + """Index within an inquiry at which the inquiry preview should be displayed. + + For calibration, we should display it after the target prompt (index = 1). + For copy phrase there is no target prompt so it should display before the + rest of the inquiry.""" + return 1 + def do_inquiry(self) -> List[Tuple[str, float]]: """Do inquiry. @@ -140,7 +156,8 @@ def do_inquiry(self) -> List[Tuple[str, float]]: """ # init an array for timing information - timing = [] + timing: List[Tuple[str, float]] = [] + self.preview_accepted = True if self.first_run: self._trigger_pulse() @@ -149,28 +166,29 @@ def do_inquiry(self) -> List[Tuple[str, float]]: inquiry = self._generate_inquiry() # do the inquiry - for idx in range(len(inquiry)): + for idx, stim_props in enumerate(inquiry): # If this is the start of an inquiry and a callback registered for first_stim_callback evoke it if idx == 0 and callable(self.first_stim_callback): - self.first_stim_callback(inquiry[idx]['sti']) + self.first_stim_callback(stim_props['sti']) - # If previewing the inquiry, do so after the first stimulus - if self.preview_calibration and idx == 1: - time, _ = self.preview_inquiry() - timing.extend(time) + # If previewing the inquiry during calibration, do so after the first stimulus + if self.preview_enabled and idx == self.preview_index: + self.preview_accepted = self.preview_inquiry(timing) + if not self.preview_accepted: + break # Reset the timing clock to start presenting self.window.callOnFlip( self.trigger_callback.callback, self.experiment_clock, - inquiry[idx]['sti_label']) + stim_props['sti_label']) # Draw stimulus for n frames - inquiry[idx]['sti'].draw() + stim_props['sti'].draw() self.draw_static() self.window.flip() - core.wait(inquiry[idx]['time_to_present']) + core.wait(stim_props['time_to_present']) # append timing information timing.append(self.trigger_callback.timing) @@ -202,74 +220,47 @@ def _trigger_pulse(self) -> None: self.first_stim_time = calibration_time[-1] self.first_run = False - def preview_inquiry(self) -> Tuple[List[float], bool]: + def preview_inquiry(self, timing: List[Tuple[str, float]]) -> bool: """Preview Inquiry. Given an inquiry defined to be presented via do_inquiry(), present the full inquiry to the user and allow input on whether the intended letter is present or not before going through the rapid serial visual presention. + Parameters: + timing - list to which all timing information should be appended. Returns: - - A tuple containing the timing information and a boolean describing whether to present - the inquiry (True) or generate another (False). + - A boolean describing whether to present the inquiry (True) or + generate another (False). """ - # self._preview_inquiry defaults to None on __init__, assert it is defined correctly - assert isinstance(self._preview_inquiry, PreviewInquiryProperties), ( - 'PreviewInquiryProperties are not set on this RSVPDisplay. ' - 'Add them as a preview_inquiry kwarg to use preview_inquiry().') - # construct the timing to return and generate the content for preview - timing = [] - if self.first_run: - self._trigger_pulse() - - content = self._generate_inquiry_preview() + assert self.preview_enabled, "Preview feature not enabled." + assert self.preview_button_handler, "Button handler must be initialized" - # define the trigger callbacks. Here we use the trigger_callback to return immediately + handler = self.preview_button_handler self.window.callOnFlip( self.trigger_callback.callback, self.experiment_clock, 'inquiry_preview') + self.draw_preview() - # Draw and flip the screen. - content.draw() - self.draw_static() - self.window.flip() + handler.await_response() timing.append(self.trigger_callback.timing) + if handler.has_response(): + timing.append((handler.response_label, handler.response_timestamp)) - timer = core.CountdownTimer(self._preview_inquiry.preview_inquiry_length) - response = False - - event.clearEvents(eventType='keyboard') - while timer.getTime() > 0: - # wait for a key press event - response = get_key_press( - key_list=[self._preview_inquiry.preview_inquiry_key_input], - clock=self.experiment_clock, - ) + self.trigger_callback.reset() + self.draw_static() + self.window.flip() + core.wait(self.preview_params.preview_inquiry_isi) - # break if a response given unless this is preview only and wait the timer - if response and not self._preview_inquiry.preview_only: - break + return handler.accept_result() + def draw_preview(self): + """Generate and draw the inquiry preview""" + content = self._generate_inquiry_preview() + content.draw() self.draw_static() self.window.flip() - self.trigger_callback.reset() - core.wait(self._preview_inquiry.preview_inquiry_isi) - - if self._preview_inquiry.preview_only: - return timing, True - - # depending on whether or not press to accept, define what to return to the task - if response and self._preview_inquiry.press_to_accept: - timing.append(response) - return timing, True - elif response and not self._preview_inquiry.press_to_accept: - timing.append(response) - return timing, False - elif not response and self._preview_inquiry.press_to_accept: - return timing, False - else: - return timing, True def _generate_inquiry_preview(self) -> visual.TextBox2: """Generate Inquiry Preview. @@ -294,7 +285,7 @@ def _generate_inquiry(self) -> list: Generate stimuli for next RSVP inquiry. [A + A, C, Q, D] """ stim_info = [] - for idx in range(len(self.stimuli_inquiry)): + for idx, stim in enumerate(self.stimuli_inquiry): current_stim = {} current_stim['time_to_present'] = self.stimuli_timing[idx] @@ -306,20 +297,20 @@ def _generate_inquiry(self) -> list: this_stimuli_size = self.stimuli_height # Set the Stimuli attrs - if self.stimuli_inquiry[idx].endswith('.png'): + if stim.endswith('.png'): current_stim['sti'] = self._create_stimulus( mode='image', height=this_stimuli_size, - stimulus=self.stimuli_inquiry[idx] + stimulus=stim ) current_stim['sti'].size = resize_image( current_stim['sti'].image, current_stim['sti'].win.size, this_stimuli_size) current_stim['sti_label'] = path.splitext( - path.basename(self.stimuli_inquiry[idx]))[0] + path.basename(stim))[0] else: # text stimulus current_stim['sti'] = self._create_stimulus(mode='text', height=this_stimuli_size) - txt = self.stimuli_inquiry[idx] + txt = stim # customize presentation of space char. current_stim['sti'].text = txt if txt != SPACE_CHAR else self.space_char current_stim['sti'].color = self.stimuli_colors[idx] diff --git a/bcipy/display/paradigm/rsvp/mode/calibration.py b/bcipy/display/paradigm/rsvp/mode/calibration.py index 3452d8a3c..df261ddef 100644 --- a/bcipy/display/paradigm/rsvp/mode/calibration.py +++ b/bcipy/display/paradigm/rsvp/mode/calibration.py @@ -13,7 +13,7 @@ def __init__(self, task_bar, info, trigger_type='image', - preview_inquiry=None, + preview_config=None, space_char=SPACE_CHAR, full_screen=False): @@ -24,6 +24,14 @@ def __init__(self, task_bar, info, trigger_type=trigger_type, - preview_inquiry=preview_inquiry, + preview_config=preview_config, space_char=space_char, full_screen=full_screen) + + @property + def preview_index(self) -> int: + """Index within an inquiry at which the inquiry preview should be displayed. + + For calibration, we should display it after the target prompt (index = 1). + """ + return 1 diff --git a/bcipy/display/paradigm/rsvp/mode/copy_phrase.py b/bcipy/display/paradigm/rsvp/mode/copy_phrase.py index 9a09cace0..051a14557 100644 --- a/bcipy/display/paradigm/rsvp/mode/copy_phrase.py +++ b/bcipy/display/paradigm/rsvp/mode/copy_phrase.py @@ -1,7 +1,8 @@ from psychopy import visual -from bcipy.display.paradigm.rsvp.display import RSVPDisplay, BCIPY_LOGO_PATH -from bcipy.helpers.symbols import SPACE_CHAR + +from bcipy.display.paradigm.rsvp.display import BCIPY_LOGO_PATH, RSVPDisplay from bcipy.helpers.stimuli import resize_image +from bcipy.helpers.symbols import SPACE_CHAR """Note: @@ -33,7 +34,7 @@ def __init__( starting_spelled_text='', trigger_type='image', space_char=SPACE_CHAR, - preview_inquiry=None, + preview_config=None, full_screen=False): """ Initializes Copy Phrase Task Objects """ self.starting_spelled_text = starting_spelled_text @@ -46,9 +47,18 @@ def __init__( info, trigger_type=trigger_type, space_char=space_char, - preview_inquiry=preview_inquiry, + preview_config=preview_config, full_screen=full_screen) + @property + def preview_index(self) -> int: + """Index within an inquiry at which the inquiry preview should be displayed. + + For copy phrase there is no target prompt so it should display before + the fixation. + """ + return 0 + def wait_screen(self, message: str, message_color: str) -> None: """Wait Screen. diff --git a/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py b/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py index 61bb2a483..bb3cdd7ec 100644 --- a/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py +++ b/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py @@ -1,25 +1,25 @@ import unittest -from unittest.mock import patch +from unittest.mock import Mock, patch import psychopy -from mockito import (any, mock, unstub, verifyNoUnwantedInteractions, +from mockito import (mock, unstub, verify, verifyNoUnwantedInteractions, verifyStubbedInvocationsAreUsed, when) -from bcipy.display import (InformationProperties, PreviewInquiryProperties, - StimuliProperties) +from bcipy.display import InformationProperties, StimuliProperties +from bcipy.display.components.button_press_handler import ButtonPressHandler from bcipy.display.components.task_bar import TaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.rsvp import RSVPDisplay # Define some reusable elements to test RSVPDisplay with LEN_STIM = 10 -TEST_STIM = StimuliProperties( - stim_font='Arial', - stim_pos=(0, 0), - stim_height=0.6, - stim_inquiry=['A', '+'] * LEN_STIM, - stim_colors=['white'] * LEN_STIM, - stim_timing=[3] * LEN_STIM, - is_txt_stim=True) +TEST_STIM = StimuliProperties(stim_font='Arial', + stim_pos=(0, 0), + stim_height=0.6, + stim_inquiry=['A', '+'] * LEN_STIM, + stim_colors=['white'] * LEN_STIM, + stim_timing=[3] * LEN_STIM, + is_txt_stim=True) TEST_INFO = InformationProperties( info_color=['White'], info_pos=[(-.5, -.75)], @@ -45,13 +45,9 @@ def setUp(self, task_bar_mock): self.task_bar_mock = mock(TaskBar) task_bar_mock.returnValue(self.task_bar_mock) when(psychopy.visual).TextStim(...).thenReturn(self.text_stim_mock) - self.rsvp = RSVPDisplay( - self.window, - self.static_clock, - self.experiment_clock, - self.stimuli, - self.task_bar_mock, - self.info) + self.rsvp = RSVPDisplay(self.window, self.static_clock, + self.experiment_clock, self.stimuli, + self.task_bar_mock, self.info) def tearDown(self): verifyNoUnwantedInteractions() @@ -63,7 +59,8 @@ def test_task_bar_config_properties_set_correctly(self): def test_information_properties_set_correctly(self): self.assertEqual(self.rsvp.info, self.info) - self.assertEqual(self.rsvp.info_text, self.info.build_info_text(self.window)) + self.assertEqual(self.rsvp.info_text, + self.info.build_info_text(self.window)) def test_stimuli_properties_set_correctly(self): """Stimuli properties are set on the instance to allow easy resetting of this properties during a task.""" @@ -78,218 +75,232 @@ def test_stimuli_properties_set_correctly(self): class TestRSVPDisplayInquiryPreview(unittest.TestCase): + + @patch('bcipy.display.paradigm.rsvp.display.init_preview_button_handler') @patch('bcipy.display.paradigm.rsvp.display.TaskBar') - def setUp(self, task_bar_mock): + def setUp(self, task_bar_mock, init_preview_button_handler_mock): """Set up needed items for test.""" self.info = TEST_INFO self.stimuli = TEST_STIM - self.preview_inquiry_length = 0.1 - self.preview_inquiry_isi = 0.1 - self.preview_inquiry_progress_method = 1 # preview only = 0; press to accept == 1; press to skip == 2 - self.preview_inquiry_key_input = 'space' - self.preview_inquiry = PreviewInquiryProperties( - preview_on=False, - preview_only=False, - preview_inquiry_length=self.preview_inquiry_length, - preview_inquiry_isi=self.preview_inquiry_isi, - preview_inquiry_progress_method=self.preview_inquiry_progress_method, - preview_inquiry_key_input=self.preview_inquiry_key_input - ) + self.window = mock({"units": "norm", "size": (2.0, 2.0)}) self.experiment_clock = mock() self.static_clock = mock() self.text_stim_mock = mock() self.rect_stim_mock = mock() self.task_bar_mock = mock(TaskBar) - task_bar_mock.returnValue(self.task_bar_mock) + task_bar_mock.return_value(self.task_bar_mock) when(psychopy.visual).TextStim(...).thenReturn(self.text_stim_mock) - self.rsvp = RSVPDisplay( - self.window, - self.static_clock, - self.experiment_clock, - self.stimuli, - self.task_bar_mock, - self.info, - preview_inquiry=self.preview_inquiry) + + self.rsvp = None def tearDown(self): verifyNoUnwantedInteractions() verifyStubbedInvocationsAreUsed() unstub() - def test_preview_inquiry_properties_set_correctly(self): - self.assertEqual(self.rsvp._preview_inquiry, self.preview_inquiry) - # In our test case, preview_inquiry_progress_method is 1 and should map to press_to_accept - self.assertEqual(self.rsvp._preview_inquiry.press_to_accept, True) - self.assertEqual( - self.rsvp._preview_inquiry.preview_inquiry_length, - self.preview_inquiry.preview_inquiry_length) - self.assertEqual( - self.rsvp._preview_inquiry.preview_inquiry_key_input, - self.preview_inquiry.preview_inquiry_key_input) - self.assertEqual( - self.rsvp._preview_inquiry.preview_inquiry_isi, - self.preview_inquiry.preview_inquiry_isi) - - def test_preview_inquiry_generate_inquiry_preview_fixation(self): - text = ' '.join(self.rsvp.stimuli_inquiry).split('+ ')[1] - stim_mock = mock() - when(self.rsvp)._create_stimulus( - any(), - stimulus=text, - units='height', - stimuli_position=self.rsvp.stimuli_pos, - mode='textbox', - align_text='left', - wrap_width=any() - ).thenReturn(stim_mock) - - response = self.rsvp._generate_inquiry_preview() - self.assertEqual(response, stim_mock) - - @patch('bcipy.display.paradigm.rsvp.display.get_key_press') - def test_preview_inquiry_evoked_press_to_accept_pressed(self, get_key_press_mock): - stim_mock = mock() - # mock the stimulus generation - when(self.rsvp)._generate_inquiry_preview().thenReturn(stim_mock) - when(stim_mock).draw().thenReturn() - when(self.rsvp).draw_static().thenReturn() - when(self.rsvp.window).flip().thenReturn() - when(self.rsvp)._trigger_pulse().thenReturn() - - # skip the core wait for testing - when(psychopy.core).wait(self.preview_inquiry.preview_inquiry_isi).thenReturn() - key_timestamp = 1000 - get_key_press_mock.return_value = [ - f'bcipy_key_press_{self.preview_inquiry_key_input}', key_timestamp - ] - response = self.rsvp.preview_inquiry() - # we expect the trigger callback to return none, the key press to return the time and key press message, - # The second item should be True as it is press to accept and a response was returned - expected = ([None, [f'bcipy_key_press_{self.preview_inquiry_key_input}', key_timestamp]], True) - self.assertEqual(response, expected) - - @patch('bcipy.display.paradigm.rsvp.display.get_key_press') - def test_preview_inquiry_evoked_press_to_skip_pressed(self, get_key_press_mock): - # set the progress method to press to skip - self.rsvp._preview_inquiry.press_to_accept = False - stim_mock = mock() - # mock the stimulus generation - when(self.rsvp)._generate_inquiry_preview().thenReturn(stim_mock) - when(stim_mock).draw().thenReturn() - when(self.rsvp).draw_static().thenReturn() - when(self.rsvp.window).flip().thenReturn() - when(self.rsvp)._trigger_pulse().thenReturn() - - # skip the core wait for testing - when(psychopy.core).wait(self.preview_inquiry.preview_inquiry_isi).thenReturn() - key_timestamp = 1000 - get_key_press_mock.return_value = [ - f'bcipy_key_press_{self.preview_inquiry_key_input}', key_timestamp - ] - response = self.rsvp.preview_inquiry() - # we expect the trigger callback to return none, the key press to return the time and key press message, - # The second item should be False as it is press to skip and a response was returned - expected = ([None, [f'bcipy_key_press_{self.preview_inquiry_key_input}', key_timestamp]], False) - self.assertEqual(response, expected) - - @patch('bcipy.display.paradigm.rsvp.display.get_key_press') - def test_preview_inquiry_evoked_press_to_accept_not_pressed(self, get_key_press_mock): - stim_mock = mock() - # mock the stimulus generation - when(self.rsvp)._generate_inquiry_preview().thenReturn(stim_mock) - when(stim_mock).draw().thenReturn() + def init_display(self, preview_config) -> None: + """Initializes a new display with the given config; """ + self.rsvp = RSVPDisplay(self.window, + self.static_clock, + self.experiment_clock, + self.stimuli, + self.task_bar_mock, + self.info, + preview_config=preview_config) + + # skip the gui components when(self.rsvp).draw_static().thenReturn() + when(self.rsvp).draw_preview().thenReturn() when(self.rsvp.window).flip().thenReturn() - when(self.rsvp)._trigger_pulse().thenReturn() - - # skip the core wait for testing - when(psychopy.core).wait(self.preview_inquiry.preview_inquiry_isi).thenReturn() - get_key_press_mock.return_value = None - response = self.rsvp.preview_inquiry() - # we expect the trigger callback to return none, the key press to return the time and key press message, - # The second item should be False as it is press to accept and a response was returned - expected = ([None], False) - self.assertEqual(response, expected) - - @patch('bcipy.display.paradigm.rsvp.display.get_key_press') - def test_preview_inquiry_evoked_press_to_skip_not_pressed(self, get_key_press_mock): - # set the progress method to press to skip - self.rsvp._preview_inquiry.press_to_accept = False - stim_mock = mock() - # mock the stimulus generation - when(self.rsvp)._generate_inquiry_preview().thenReturn(stim_mock) - when(stim_mock).draw().thenReturn() - when(self.rsvp).draw_static().thenReturn() - when(self.rsvp.window).flip().thenReturn() - when(self.rsvp)._trigger_pulse().thenReturn() - - # skip the core wait for testing - when(psychopy.core).wait(self.preview_inquiry.preview_inquiry_isi).thenReturn() - get_key_press_mock.return_value = None - response = self.rsvp.preview_inquiry() - # we expect the trigger callback to return none, the key press to return the time and key press message, - # The second item should be True as it is press to skip and a response was not returned - expected = ([None], True) - self.assertEqual(response, expected) - - @patch('bcipy.display.paradigm.rsvp.display.get_key_press') - def test_preview_inquiry_preview_only_response_registered(self, get_key_press_mock): - # set the progress method to press to skip - self.rsvp._preview_inquiry.press_to_accept = False - self.rsvp._preview_inquiry.preview_only = True - stim_mock = mock() - # mock the stimulus generation - when(self.rsvp)._generate_inquiry_preview().thenReturn(stim_mock) - when(stim_mock).draw().thenReturn() - when(self.rsvp).draw_static().thenReturn() - when(self.rsvp.window).flip().thenReturn() - when(self.rsvp)._trigger_pulse().thenReturn() - - # skip the core wait for testing - when(psychopy.core).wait(self.preview_inquiry.preview_inquiry_isi).thenReturn() - # we return a key press value here to demonstrate, even if a response is returned by this method, it will not - # be used in the preview_inquiry response from our display. - key_timestamp = 1000 - get_key_press_mock.return_value = [ - f'bcipy_key_press_{self.preview_inquiry_key_input}', key_timestamp - ] - response = self.rsvp.preview_inquiry() - # we expect the trigger callback to return none, no key press response even if returned, - # The second item should be True as it is preview only - expected = ([None], True) - self.assertEqual(response, expected) - - @patch('bcipy.display.paradigm.rsvp.display.get_key_press') - def test_preview_inquiry_preview_only_no_response(self, get_key_press_mock): - # set the progress method to press to skip - self.rsvp._preview_inquiry.press_to_accept = False - self.rsvp._preview_inquiry.preview_only = True - stim_mock = mock() - # mock the stimulus generation - when(self.rsvp)._generate_inquiry_preview().thenReturn(stim_mock) - when(stim_mock).draw().thenReturn() - when(self.rsvp).draw_static().thenReturn() - when(self.rsvp.window).flip().thenReturn() - when(self.rsvp)._trigger_pulse().thenReturn() - - # skip the core wait for testing - when(psychopy.core).wait(self.preview_inquiry.preview_inquiry_isi).thenReturn() - - get_key_press_mock.return_value = None - response = self.rsvp.preview_inquiry() - # we expect the trigger callback to return none, no key press response, - # The second item should be True as it is preview only - expected = ([None], True) - self.assertEqual(response, expected) - - def test_error_thrown_when_calling_preview_inquiry_without_properties_set(self): - # If not defined using the kwarg preview_inquiry, this value is set to None - self.rsvp._preview_inquiry = None - - # Assert when set to None, calling the method will result in an exception - with self.assertRaises(Exception): - self.rsvp.preview_inquiry() + when(psychopy.core).wait( + preview_config.preview_inquiry_isi).thenReturn() + + def test_preview_enabled_default(self): + """Test preview_enabled when preview_config is None.""" + rsvp = RSVPDisplay(self.window, + self.static_clock, + self.experiment_clock, + self.stimuli, + self.task_bar_mock, + self.info, + preview_config=None) + self.assertFalse(rsvp.preview_enabled) + + def test_preview_enabled_is_false(self): + """Test inquiry preview disabled when params specify not to + show_preview_inquiry.""" + preview_config = PreviewParams(show_preview_inquiry=False, + preview_inquiry_length=2, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=1, + preview_inquiry_isi=1) + rsvp = RSVPDisplay(self.window, + self.static_clock, + self.experiment_clock, + self.stimuli, + self.task_bar_mock, + self.info, + preview_config=preview_config) + self.assertFalse(rsvp.preview_enabled) + + def test_preview_enabled_is_true(self): + """Test inquiry preview disabled when params specify to + show_preview_inquiry.""" + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=2, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=1, + preview_inquiry_isi=1) + rsvp = RSVPDisplay(self.window, + self.static_clock, + self.experiment_clock, + self.stimuli, + self.task_bar_mock, + self.info, + preview_config=preview_config) + self.assertTrue(rsvp.preview_enabled) + + @patch('bcipy.display.paradigm.rsvp.display.init_preview_button_handler') + def test_preview_inquiry_evoked_press_to_accept_pressed( + self, init_preview_button_handler_mock): + """Test preview with a press to accept configuration.""" + + button_press_handler_mock = Mock(ButtonPressHandler) + init_preview_button_handler_mock.return_value = button_press_handler_mock + + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=0.01, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=1, + preview_inquiry_isi=0.01) + self.init_display(preview_config) + + button_press_handler_mock.has_response.return_value = True + button_press_handler_mock.accept_result.return_value = True + button_press_handler_mock.response_label = 'bcipy_key_press_space' + button_press_handler_mock.response_timestamp = 1.0 + + timing = [] + proceed = self.rsvp.preview_inquiry(timing) + + init_preview_button_handler_mock.assert_called_once_with( + preview_config, self.experiment_clock) + button_press_handler_mock.await_response.assert_called_once() + + verify(self.rsvp, times=1).draw_preview() + self.assertTrue(proceed) + self.assertEqual( + 2, len(timing), + "time stamps for the preview and the button press should be present" + ) + label, stamp = timing[-1] + self.assertEqual('bcipy_key_press_space', label) + self.assertEqual(1.0, stamp) + + @patch('bcipy.display.paradigm.rsvp.display.init_preview_button_handler') + def test_preview_inquiry_evoked_press_to_skip_pressed( + self, init_preview_button_handler_mock): + """Test preview with a press to reject/skip configuration.""" + button_press_handler_mock = Mock(ButtonPressHandler) + init_preview_button_handler_mock.return_value = button_press_handler_mock + + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=0.01, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=2, + preview_inquiry_isi=0.01) + self.init_display(preview_config) + + button_press_handler_mock.has_response.return_value = True + button_press_handler_mock.accept_result.return_value = False + button_press_handler_mock.response_label = 'bcipy_key_press_space' + button_press_handler_mock.response_timestamp = 1.0 + + timing = [] + proceed = self.rsvp.preview_inquiry(timing) + + verify(self.rsvp, times=1).draw_preview() + self.assertFalse(proceed) + self.assertEqual(2, len(timing)) + label, stamp = timing[-1] + self.assertEqual('bcipy_key_press_space', label) + self.assertEqual(1.0, stamp) + + @patch('bcipy.display.paradigm.rsvp.display.init_preview_button_handler') + def test_preview_inquiry_evoked_press_to_accept_not_pressed( + self, init_preview_button_handler_mock): + """Test preview with a press to accept with no button press.""" + button_press_handler_mock = Mock(ButtonPressHandler) + init_preview_button_handler_mock.return_value = button_press_handler_mock + + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=0.01, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=1, + preview_inquiry_isi=0.01) + self.init_display(preview_config) + + button_press_handler_mock.has_response.return_value = False + button_press_handler_mock.accept_result.return_value = False + + timing = [] + proceed = self.rsvp.preview_inquiry(timing) + verify(self.rsvp, times=1).draw_preview() + + self.assertFalse(proceed) + self.assertEqual(1, len(timing), + "Only the timing for the preview should be present.") + + @patch('bcipy.display.paradigm.rsvp.display.init_preview_button_handler') + def test_preview_inquiry_evoked_press_to_skip_not_pressed( + self, init_preview_button_handler_mock): + """Test preview with a press to reject/skip configuration when the + button was not pressed.""" + button_press_handler_mock = Mock(ButtonPressHandler) + init_preview_button_handler_mock.return_value = button_press_handler_mock + + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=0.01, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=2, + preview_inquiry_isi=0.01) + self.init_display(preview_config) + + button_press_handler_mock.has_response.return_value = False + button_press_handler_mock.accept_result.return_value = True + + timing = [] + proceed = self.rsvp.preview_inquiry(timing) + + verify(self.rsvp, times=1).draw_preview() + + self.assertTrue(proceed) + self.assertEqual(1, len(timing), + "Only the timing for the preview should be present.") + + @patch('bcipy.display.paradigm.rsvp.display.init_preview_button_handler') + def test_preview_inquiry_preview_only_response_registered( + self, init_preview_button_handler_mock): + """Test preview with preview only.""" + button_press_handler_mock = Mock(ButtonPressHandler) + init_preview_button_handler_mock.return_value = button_press_handler_mock + + preview_config = PreviewParams(show_preview_inquiry=True, + preview_inquiry_length=0.01, + preview_inquiry_key_input='space', + preview_inquiry_progress_method=0, + preview_inquiry_isi=0.01) + self.init_display(preview_config) + + button_press_handler_mock.has_response.return_value = False + button_press_handler_mock.accept_result.return_value = True + + timing = [] + proceed = self.rsvp.preview_inquiry(timing) + + verify(self.rsvp, times=1).draw_preview() + self.assertTrue(proceed) if __name__ == '__main__': diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 8bfa138dc..772d9c103 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -11,6 +11,7 @@ from bcipy.display import (InformationProperties, PreviewInquiryProperties, StimuliProperties) from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay from bcipy.feedback.visual.visual_feedback import VisualFeedback from bcipy.helpers.clock import Clock @@ -371,14 +372,8 @@ def present_inquiry(self, inquiry_schedule: InquirySchedule colors=inquiry_schedule.colors[0] if self.parameters['is_txt_stim'] else None) - if self.parameters['show_preview_inquiry']: - stim_times, proceed = self.rsvp.preview_inquiry() - if proceed: - stim_times.extend(self.rsvp.do_inquiry()) - else: - stim_times = self.rsvp.do_inquiry() - proceed = True - + stim_times = self.rsvp.do_inquiry() + proceed = not self.rsvp.preview_enabled or self.rsvp.preview_accepted return stim_times, proceed def show_feedback(self, selection: str, correct: bool = True) -> None: @@ -977,4 +972,4 @@ def _init_copy_phrase_display( starting_spelled_text, trigger_type=parameters['trigger_type'], space_char=parameters['stim_space_char'], - preview_inquiry=preview_inquiry) + preview_config=parameters.instantiate(PreviewParams)) diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 48d104aff..1ac1980ee 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -264,7 +264,6 @@ def test_execute_fake_data_single_inquiry(self, process_data_mock, message_mock, # Assertions verify(self.copy_phrase_wrapper, times=2).initialize_series() - verify(self.display, times=0).preview_inquiry() verify(self.display, times=1).do_inquiry() self.assertEqual(self.temp_dir, result) @@ -474,7 +473,6 @@ def test_execute_fake_data_with_preview(self, process_data_mock, message_mock, # Assertions verify(self.copy_phrase_wrapper, times=2).initialize_series() - verify(self.display, times=1).preview_inquiry() verify(self.display, times=1).do_inquiry() verify(self.copy_phrase_wrapper, times=1).add_evidence(EvidenceType.BTN, ...) self.assertEqual(self.temp_dir, result) From c14fccb05087abe349740552a9ea7db9df5891a9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 4 Oct 2024 13:25:51 -0700 Subject: [PATCH 319/330] Modified RSVP calibration task to correctly initialize the display --- .../task/paradigm/rsvp/calibration/calibration.py | 15 +++------------ 1 file changed, 3 insertions(+), 12 deletions(-) diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 964a2fbad..44b6a4cce 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -1,8 +1,8 @@ from psychopy import core, visual -from bcipy.display import (Display, InformationProperties, - PreviewInquiryProperties, StimuliProperties) +from bcipy.display import Display, InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.main import PreviewParams from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters @@ -79,22 +79,13 @@ def init_calibration_display_task( height=parameters['task_height'], padding=parameters['task_padding']) - preview_inquiry = PreviewInquiryProperties( - preview_on=parameters['show_preview_inquiry'], - preview_only=True, - preview_inquiry_length=parameters['preview_inquiry_length'], - preview_inquiry_progress_method=parameters[ - 'preview_inquiry_progress_method'], - preview_inquiry_key_input=parameters['preview_inquiry_key_input'], - preview_inquiry_isi=parameters['preview_inquiry_isi']) - return CalibrationDisplay(window, static_clock, experiment_clock, stimuli, task_bar, info, - preview_inquiry=preview_inquiry, + preview_config=parameters.instantiate(PreviewParams), trigger_type=parameters['trigger_type'], space_char=parameters['stim_space_char'], full_screen=parameters['full_screen']) From 963b6e614d88e3b59189b07aac4d9f1a66504d41 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 4 Oct 2024 15:37:48 -0700 Subject: [PATCH 320/330] Updated the base calibration to fix a trigger issue in matrix when using inquiry preview --- bcipy/task/base_calibration.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/bcipy/task/base_calibration.py b/bcipy/task/base_calibration.py index 93db1d3e0..392de4fc4 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/base_calibration.py @@ -167,6 +167,8 @@ def trigger_type(self, symbol: str, target: str, """ if index == 0: return TriggerType.PROMPT + if symbol == 'inquiry_preview': + return TriggerType.PREVIEW if symbol == DEFAULT_TEXT_FIXATION: return TriggerType.FIXATION if target == symbol: From 259f8effc34921f582ec600eb9560960d43eab64 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 18 Oct 2024 17:56:11 -0700 Subject: [PATCH 321/330] #188038501 ; Changed model loading behavior to prompt using a separate file dialog for each model --- bcipy/gui/file_dialog.py | 21 ++-- bcipy/helpers/acquisition.py | 33 ++++++ bcipy/helpers/load.py | 48 ++++++++ bcipy/helpers/tests/test_acquisition.py | 143 +++++++++++++++++++++++- bcipy/helpers/tests/test_load.py | 119 ++++++++++++++++---- bcipy/main.py | 13 ++- bcipy/tests/test_bci_main.py | 10 +- 7 files changed, 343 insertions(+), 44 deletions(-) diff --git a/bcipy/gui/file_dialog.py b/bcipy/gui/file_dialog.py index 8c5247b12..27a546b72 100644 --- a/bcipy/gui/file_dialog.py +++ b/bcipy/gui/file_dialog.py @@ -1,8 +1,10 @@ # pylint: disable=no-name-in-module,missing-docstring,too-few-public-methods import sys from pathlib import Path -from PyQt6.QtWidgets import QApplication, QWidget, QFileDialog + from PyQt6 import QtGui +from PyQt6.QtWidgets import QApplication, QFileDialog, QWidget + from bcipy.preferences import preferences DEFAULT_FILE_TYPES = "All Files (*)" @@ -25,18 +27,21 @@ def __init__(self): # The native dialog may prevent the selection from closing after a # directory is selected. - self.options = QFileDialog.Option(3) + self.options = QFileDialog.Option.DontUseNativeDialog - def ask_file(self, file_types: str = DEFAULT_FILE_TYPES, directory: str = "") -> str: + def ask_file(self, + file_types: str = DEFAULT_FILE_TYPES, + directory: str = "", + prompt: str = "Select File") -> str: """Opens a file dialog window. Returns ------- path or None """ filename, _ = QFileDialog.getOpenFileName(self, - "Select File", - directory, - file_types, + caption=prompt, + directory=directory, + filter=file_types, options=self.options) return filename @@ -53,7 +58,7 @@ def ask_directory(self, directory: str = "") -> str: options=self.options) -def ask_filename(file_types: str = DEFAULT_FILE_TYPES, directory: str = "") -> str: +def ask_filename(file_types: str = DEFAULT_FILE_TYPES, directory: str = "", prompt="Select File") -> str: """Prompt for a file. Parameters @@ -69,7 +74,7 @@ def ask_filename(file_types: str = DEFAULT_FILE_TYPES, directory: str = "") -> s app = QApplication(sys.argv) dialog = FileDialog() directory = directory or preferences.last_directory - filename = dialog.ask_file(file_types, directory) + filename = dialog.ask_file(file_types, directory, prompt=prompt) # update last directory preference path = Path(filename) diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index 0a92c9b7a..c1350444b 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -308,3 +308,36 @@ def stream_types(acq_mode: str, delimiter: str = "+") -> List[str]: """ return list( dict.fromkeys([mode.strip() for mode in acq_mode.split(delimiter)])) + + +def active_content_types(acq_mode: str) -> List[str]: + """Given the configured acquisition mode, determine which content types are + currently active and should be used in decision-making. + + Parameters + ---------- + acq_mode - delimited list of stream types (ex. 'EEG+Eyetracker') + """ + return [ + stream_type.content_type + for stream_type in map(parse_stream_type, stream_types(acq_mode)) + if is_stream_type_active(stream_type) + ] + + +def is_stream_type_active(stream_type: StreamType) -> bool: + """Check if the provided stream type is active. + + A stream type's status, if provided, will be used to make the determinition. + If missing, the status of a matching pre-configured device will be used.""" + content_type, device_name, status = stream_type + if status: + return status == DeviceStatus.ACTIVE + + if device_name: + device = preconfigured_device(device_name, strict=False) + if device: + return device.is_active + + specs_with_type = with_content_type(content_type) + return any(spec.is_active for spec in specs_with_type) diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 7b36c2a43..7bea71f3f 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -188,6 +188,54 @@ def load_signal_models(directory: Optional[str] = None) -> List[SignalModel]: return models +def choose_signal_models(device_types: List[str]) -> List[SignalModel]: + """Prompt the user to load a signal model for each provided device. + + Parameters + ---------- + device_types - list of device content types (ex. 'EEG') + """ + return [ + model for model in map(choose_signal_model, set(device_types)) if model + ] + + +def load_signal_model(file_path: str) -> SignalModel: + """Load signal model from persisted file. + + Models are assumed to have been written using bcipy.helpers.save.save_model + function and should be serialized as pickled files. Note that reading + pickled files is a potential security concern so only load from trusted + directories.""" + + with open(file_path, "rb") as signal_file: + model = pickle.load(signal_file) + log.info(f"Loading model {model}") + return model + + +def choose_signal_model(device_type: str) -> Optional[SignalModel]: + """Present a file dialog prompting the user to select a signal model for + the given device. + + Parameters + ---------- + device_type - ex. 'EEG' or 'Eyetracker'; this should correspond with + the content_type of the DeviceSpec of the model. + """ + + file_path = ask_filename(file_types=f"*{SIGNAL_MODEL_FILE_SUFFIX}", + directory=preferences.signal_model_directory, + prompt=f"Select the {device_type} signal model") + + if file_path: + # update preferences + path = Path(file_path) + preferences.signal_model_directory = str(path) + return load_signal_model(str(path)) + return None + + def choose_csv_file(filename: Optional[str] = None) -> Optional[str]: """GUI prompt to select a csv file from the file system. diff --git a/bcipy/helpers/tests/test_acquisition.py b/bcipy/helpers/tests/test_acquisition.py index 22a725c9b..0bb970857 100644 --- a/bcipy/helpers/tests/test_acquisition.py +++ b/bcipy/helpers/tests/test_acquisition.py @@ -6,8 +6,10 @@ from bcipy.acquisition.devices import DeviceSpec, DeviceStatus from bcipy.config import DEFAULT_PARAMETERS_PATH -from bcipy.helpers.acquisition import (RAW_DATA_FILENAME, init_device, +from bcipy.helpers.acquisition import (RAW_DATA_FILENAME, StreamType, + active_content_types, init_device, init_eeg_acquisition, + is_stream_type_active, max_inquiry_duration, parse_stream_type, raw_data_filename, server_spec, stream_types) @@ -148,7 +150,8 @@ def test_init_device_with_named_device(self, preconfigured_device_mock, def test_parse_stream_type(self): """Test function to split the stream type into content_type, name, and status""" - self.assertEqual(('EEG', 'DSI-24', None), parse_stream_type('EEG/DSI-24')) + self.assertEqual(('EEG', 'DSI-24', None), + parse_stream_type('EEG/DSI-24')) self.assertEqual(('Gaze', None, None), parse_stream_type('Gaze')) self.assertEqual(('Gaze', None, DeviceStatus.PASSIVE), parse_stream_type('Gaze:passive')) @@ -194,5 +197,141 @@ def test_raw_data_filename_eye_tracker(self): 'eyetracker_data_tobii-p0.csv') +class TestAcquisitionHelpers(unittest.TestCase): + """Unit tests for acquisition helper functions""" + + def test_stream_type_active_given_status(self): + """Test function to test if a StreamType is active given the provided + status.""" + + self.assertTrue( + is_stream_type_active( + StreamType(content_type='EEG', status=DeviceStatus.ACTIVE))) + + self.assertFalse( + is_stream_type_active( + StreamType(content_type='EEG', status=DeviceStatus.PASSIVE))) + + @patch('bcipy.helpers.acquisition.preconfigured_device') + def test_stream_type_active_using_preconfigured(self, + preconfigured_device_mock): + """Test function to test if a StreamType is active using a + preconfigured device.""" + + stream_type = StreamType(content_type='EEG', device_name='MyDevice') + device1 = Mock() + device1.is_active = True + preconfigured_device_mock.return_value = device1 + + self.assertTrue(is_stream_type_active(stream_type)) + preconfigured_device_mock.assert_called_with('MyDevice', strict=False) + + device1.is_active = False + self.assertFalse(is_stream_type_active(stream_type)) + + @patch('bcipy.helpers.acquisition.preconfigured_device') + @patch('bcipy.helpers.acquisition.with_content_type') + def test_stream_type_active_using_content_type(self, + with_content_type_mock, + preconfigured_device_mock): + """Test function to test if a StreamType is active using a + preconfigured device with type.""" + + stream_type = StreamType(content_type='EEG', device_name='MyDevice') + + preconfigured_device_mock.return_value = None + device1 = Mock() + device1.is_active = False + device2 = Mock() + device2.is_active = False + with_content_type_mock.return_value = [device1, device2] + + self.assertFalse(is_stream_type_active(stream_type)) + with_content_type_mock.assert_called_with('EEG') + + device1.is_active = True + self.assertTrue(is_stream_type_active(stream_type)) + + def test_active_content_types_with_declared_spec(self): + """Test active content types when the spec declares the status.""" + self.assertListEqual([], active_content_types('EEG:passive')) + self.assertListEqual( + [], active_content_types('EEG:passive+Eyetracker:passive')) + self.assertListEqual( + ['EEG'], active_content_types('EEG:active+Eyetracker:passive')) + self.assertListEqual( + ['EEG', 'Eyetracker'], + active_content_types('EEG:active+Eyetracker:active')) + self.assertListEqual( + ['Eyetracker'], + active_content_types('EEG:passive+Eyetracker:active')) + + @patch('bcipy.helpers.acquisition.preconfigured_device') + def test_active_content_types_using_preconfigured( + self, preconfigured_device_mock): + """Test active content types using a preconfigured device.""" + + device1 = Mock() + device1.is_active = True + preconfigured_device_mock.return_value = device1 + + self.assertListEqual(['EEG'], active_content_types('EEG/MyDevice')) + preconfigured_device_mock.assert_called_with('MyDevice', strict=False) + + @patch('bcipy.helpers.acquisition.preconfigured_device') + def test_active_content_types_using_preconfigured_false( + self, preconfigured_device_mock): + """Test active content types using a preconfigured device.""" + + device1 = Mock() + device1.is_active = False + preconfigured_device_mock.return_value = device1 + + self.assertListEqual([], active_content_types('EEG/MyDevice')) + preconfigured_device_mock.assert_called_with('MyDevice', strict=False) + + @patch('bcipy.helpers.acquisition.preconfigured_device') + def test_active_content_types_using_preconfigured_multiple_devices( + self, preconfigured_device_mock): + """Test active content types using a preconfigured device.""" + + device1 = Mock() + device1.is_active = False + device2 = Mock() + device2.is_active = True + preconfigured_device_mock.side_effect = [device1, device2] + + self.assertListEqual( + ['Eyetracker'], + active_content_types('EEG/MyDevice+Eyetracker/MyEyeDevice')) + + @patch('bcipy.helpers.acquisition.with_content_type') + def test_active_content_types_using_content_type_false( + self, with_content_type_mock): + """Test active content types using content type.""" + + device1 = Mock() + device1.is_active = False + device2 = Mock() + device2.is_active = False + with_content_type_mock.return_value = [device1, device2] + + self.assertListEqual([], active_content_types('EEG')) + with_content_type_mock.assert_called_with('EEG') + + @patch('bcipy.helpers.acquisition.with_content_type') + def test_active_content_types_using_content_type(self, + with_content_type_mock): + """Test active content types using content type.""" + device1 = Mock() + device1.is_active = False + device2 = Mock() + device2.is_active = True + with_content_type_mock.return_value = [device1, device2] + + self.assertListEqual(['EEG'], active_content_types('EEG')) + with_content_type_mock.assert_called_with('EEG') + + if __name__ == '__main__': unittest.main() diff --git a/bcipy/helpers/tests/test_load.py b/bcipy/helpers/tests/test_load.py index c42b9ec3a..8d0f9cb21 100644 --- a/bcipy/helpers/tests/test_load.py +++ b/bcipy/helpers/tests/test_load.py @@ -1,33 +1,24 @@ -import unittest +import json import os -from unittest.mock import patch, mock_open - -from collections import abc -import tempfile import shutil -import json +import tempfile +import unittest +from collections import abc +from unittest.mock import Mock, mock_open, patch from mockito import any, expect, unstub, when -from bcipy.config import ( - DEFAULT_ENCODING, - DEFAULT_EXPERIMENT_PATH, - DEFAULT_PARAMETERS_PATH, - DEFAULT_FIELD_PATH, - FIELD_FILENAME, - EXPERIMENT_FILENAME -) -from bcipy.helpers.load import ( - extract_mode, - load_json_parameters, - load_experiments, - load_experiment_fields, - load_fields, - load_users, - copy_parameters) +from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_PATH, + DEFAULT_FIELD_PATH, DEFAULT_PARAMETERS_PATH, + EXPERIMENT_FILENAME, FIELD_FILENAME) +from bcipy.helpers.exceptions import (BciPyCoreException, + InvalidExperimentException) +from bcipy.helpers.load import (choose_signal_model, choose_signal_models, + copy_parameters, extract_mode, + load_experiment_fields, load_experiments, + load_fields, load_json_parameters, + load_signal_model, load_users) from bcipy.helpers.parameters import Parameters -from bcipy.helpers.exceptions import BciPyCoreException, InvalidExperimentException - MOCK_EXPERIMENT = { "test": { @@ -217,5 +208,85 @@ def test_extract_mode_without_mode_defined(self): extract_mode(invalid_data_save_dir) +class TestModelLoad(unittest.TestCase): + """Test loading one or more signal models""" + + @patch("bcipy.helpers.load.pickle.load") + @patch("bcipy.helpers.load.open") + def test_load_model(self, open_mock, pickle_mock): + """Test loading a signal model""" + + load_signal_model("test-directory") + open_mock.assert_called_with("test-directory", 'rb') + pickle_mock.assert_called_once() + + @patch("bcipy.helpers.load.load_signal_model") + @patch("bcipy.helpers.load.ask_filename") + @patch("bcipy.helpers.load.preferences") + def test_choose_model(self, preferences_mock, ask_file_mock, + load_signal_model_mock): + """Test choosing a model""" + + preferences_mock.signal_model_directory = "." + ask_file_mock.return_value = "model-path" + model_mock = Mock() + load_signal_model_mock.return_value = model_mock + + model = choose_signal_model('EEG') + + load_signal_model_mock.assert_called_with("model-path") + ask_file_mock.assert_called_with(file_types="*.pkl", + directory=".", + prompt="Select the EEG signal model") + self.assertEqual(model, model_mock) + self.assertEqual("model-path", + preferences_mock.signal_model_directory, + msg="Should have updated the preferences") + + @patch("bcipy.helpers.load.load_signal_model") + @patch("bcipy.helpers.load.ask_filename") + @patch("bcipy.helpers.load.preferences") + def test_choose_model_with_cancel(self, preferences_mock, ask_file_mock, + load_signal_model_mock): + """Test choosing a model""" + + preferences_mock.signal_model_directory = "." + ask_file_mock.return_value = None + model_mock = Mock() + load_signal_model_mock.return_value = model_mock + + model = choose_signal_model('EEG') + + load_signal_model_mock.assert_not_called() + ask_file_mock.assert_called_with(file_types="*.pkl", + directory=".", + prompt="Select the EEG signal model") + self.assertEqual(None, model) + self.assertEqual(".", + preferences_mock.signal_model_directory, + msg="Should not have updated the preferences") + + @patch("bcipy.helpers.load.choose_signal_model") + def test_choose_signal_models(self, choose_signal_model_mock): + """Test choosing signal models""" + eeg_mock = Mock() + eyetracker_mock = Mock() + choose_signal_model_mock.side_effect = [eeg_mock, eyetracker_mock] + + models = choose_signal_models(['EEG', 'Eyetracker']) + self.assertListEqual([eeg_mock, eyetracker_mock], models) + + @patch("bcipy.helpers.load.choose_signal_model") + def test_choose_signal_models_missing_model(self, + choose_signal_model_mock): + """Test choosing signal models""" + + eyetracker_mock = Mock() + choose_signal_model_mock.side_effect = [None, eyetracker_mock] + + models = choose_signal_models(['EEG', 'Eyetracker']) + self.assertListEqual([eyetracker_mock], models) + + if __name__ == '__main__': unittest.main() diff --git a/bcipy/main.py b/bcipy/main.py index 2a9d1bfc4..ea4ca3d7d 100644 --- a/bcipy/main.py +++ b/bcipy/main.py @@ -9,10 +9,11 @@ from bcipy.config import (DEFAULT_EXPERIMENT_ID, DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH) from bcipy.display import init_display_window -from bcipy.helpers.acquisition import init_eeg_acquisition +from bcipy.helpers.acquisition import (active_content_types, + init_eeg_acquisition) from bcipy.helpers.language_model import init_language_model -from bcipy.helpers.load import (load_experiments, load_json_parameters, - load_signal_models) +from bcipy.helpers.load import (choose_signal_models, load_experiments, + load_json_parameters) from bcipy.helpers.save import init_save_data_structure from bcipy.helpers.session import collect_experiment_field_data from bcipy.helpers.stimuli import play_sound @@ -140,9 +141,9 @@ def execute_task( # Try loading in our signal_model and starting a langmodel(if enabled) if not fake: try: - model_dir = parameters['signal_model_path'] - signal_models = load_signal_models(directory=model_dir) - assert signal_models, f"No signal models found in {model_dir}" + signal_models = choose_signal_models( + active_content_types(parameters['acq_mode'])) + assert signal_models, "No signal models selected" except Exception as error: log.exception(f'Cannot load signal model. Exiting. {error}') raise error diff --git a/bcipy/tests/test_bci_main.py b/bcipy/tests/test_bci_main.py index 4b51234f0..edc7b1a2f 100644 --- a/bcipy/tests/test_bci_main.py +++ b/bcipy/tests/test_bci_main.py @@ -20,6 +20,7 @@ class TestBciMain(unittest.TestCase): data_save_location = '/' save_location = '/' parameters = { + 'acq_mode': 'EEG', 'data_save_loc': data_save_location, 'log_name': 'test_log', 'fake_data': False, @@ -304,6 +305,7 @@ class TestExecuteTask(unittest.TestCase): def setUp(self) -> None: self.parameters = { + 'acq_mode': 'EEG', 'k_folds': 10, 'is_txt_stim': True, 'signal_model_path': '', @@ -421,7 +423,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: server=self.fake).thenReturn(eeg_response) when(main).init_display_window(self.parameters).thenReturn(self.display_mock) when(main).print_message(self.display_mock, any()) - when(main).load_signal_models(directory=model_path).thenReturn(load_model_response) + when(main).choose_signal_models(['EEG']).thenReturn(load_model_response) when(main).init_language_model(self.parameters).thenReturn(language_model) when(main).start_task( self.display_mock, @@ -453,7 +455,7 @@ def test_execute_task_non_calibration_real_data(self) -> None: signal_models=[signal_model], fake=self.fake, ) - verify(main, times=1).load_signal_models(directory=model_path) + verify(main, times=1).choose_signal_models(['EEG']) verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) def test_execute_language_model_enabled(self) -> None: @@ -475,7 +477,7 @@ def test_execute_language_model_enabled(self) -> None: when(main).init_language_model(self.parameters).thenReturn(language_model) when(main).init_display_window(self.parameters).thenReturn(self.display_mock) when(main).print_message(self.display_mock, any()) - when(main).load_signal_models(directory='').thenReturn(load_model_response) + when(main).choose_signal_models(['EEG']).thenReturn(load_model_response) when(main).start_task( self.display_mock, self.daq, @@ -506,7 +508,7 @@ def test_execute_language_model_enabled(self) -> None: signal_models=[signal_model], fake=self.fake, ) - verify(main, times=1).load_signal_models(directory='') + verify(main, times=1).choose_signal_models(['EEG']) verify(main, times=1).init_language_model(self.parameters) verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) From a635baaffb7859de1090654bee3660a2702f9bb1 Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Wed, 23 Oct 2024 11:41:30 -0700 Subject: [PATCH 322/330] Session orchestrator (#339) * gets `main.py` functionality working in the orchestrator * Fixes task initialization process Save folder and parameters are now saved and loaded per task as they are executed rather than once per session. * Moves parameter loading to task execution * Adds functions for parsing visit actions * Adds some test to action parsing * Adds tests for action serialization * Adds parameter validation function with tests * Updates changelog.md * lints actions.py and test_actions.py * Adds constant for action separator * removes old file that has been moved * renames action parsing module and updates test imports * simplifies `serialize_actions` function * Fixes typing and formatting issues * removes `parse_actions.py` * renames `parse_actions` to `parse_sequence` * replaces magic '->' string with constant * removes unnecessary error check * Adds basic structure for orchestrator actions * refactors config function naming and adds support for actions in parsing functions * renames `test_actions` to `test_config` * Adds additional tests for action parsing * Adds action serialization tests * Add more actions * Refactors type unions to be `Optional`s * Adds parameter loading to the orchestrator * Adds initialize and cleanup methods to `Task` * makes `name` a property in `OfflineAnalysisAction` * Implements `setup` method in base `Task` class * Adds missing parent `execute` call * changes `initialize` call to `setup` in orchestrator * Refactors `name` to be a property in base `Task` class * Refactors `config.py` to only work with tasks * adds demo file for orchestrator execution * Fixes data_save initialization in orchestrator * Creates default_user_id constant * Fixes incorrect user initialization * Refactors orchestrator save structure * Implements `save` method * Adds `task_registry_dict` to simplify fetching classes for initialization This is currently redundant with the `TaskType` approach and ideally would be refactored to have only one source of string reference * Adds comment about `task_registry_dict` * Moves `task_registry_dict` to `orchestrator.config` * refactors `name` property of tasks * Adds task registry class * Refactor `super` calls in orchestrator actions * adds type hint for task parameter * calls `construct_command` in constructor * adds function to run experiment data collection without running from the command line * adds `ExperimentFieldCollectionAction` * refactors orchestrator demo file to use `ExperimentFieldCollectionAction` * lints `task_registry.py` * imports `Task` for correct typing in config * Updates `task_registry.py` to import all tasks * moves `TASK_SEPERATOR` to `config.py` * Adds docstring to orchestrator * Renames `TestConfig` * removes property decorator in task class * removes implementation of abstract class * updates changelog * removes super calls to abstract method `execute` * Filters out abstract subclasses from registry generation * removes registry dict empty initialization * Fixes typing issues * Removes task import from the registry * Refactors config to support TaskRegistry * Refactors task names * Refactors `TaskRegistry` to recursively collect subclasses This makes it compatible with the new `BaseCalibrationTask` as it will be able to collect grandchild classes of `Task` (which is all calibration tasks now) * Makes `BaseCalibrationTask` abstract * removes name and label from `timing_verification.py` * imports tasks in their module's `__init__.py` This makes all tasks available to the task registry when it is initialized. * Enforces `name` attribute in base task class * adds calibration task check to the registry. TaskType now no longer exists * fixes incorrect method name in TaskRegistry * updates bci_main_tests to call main methods properly * updates method calls in protocol parsing tests * refactors `start_app` to use `start_experiment_field_collection_gui` * changes orchestrator directory name to work on windows * Adds basic selection box for orchestrator protocol * Adds the ability to add and remove tasks to the protocol * renames `sequence` to `protocol` in orchestrator config * Allows protocol to be saved to `experiments.json` * adds move up and down controls to tasks in protocol * Refactors scrollable frames to have a title label. Some buttons are still misaligned in the ExperimentRegistry * Moves create experiment button to the bottom of the gui * changes task and action names to be more consistent * adds basic `TaskData` return object * fixes failing test in `test_copy_phrase` * fixes missing return statement for `construct_command` * adds `task_dict` to `TaskData` * updates changelog * adds seperate BCIUI file with stylsheet This will hopefully replace BCIGui later, but I am keeping it seperate for now as to not break existing uis on this branch * update demo experiment layout * adjust stylesheet to remove label backgrounds * improves gui code to allow for editing fields * add basic removeable element * add dynamic list class for easy ui reactivity * Add small button component * removes explicit color from small button * adds basic toggle class * changes toggle componenet to be simple connecting function * makes on off callbacks optional in `make_toggle` * add toggle to optional button * swaps confusing parameter names * loads experiment fields into combobox * adds field buttons * refactors gui to be inherited class This improves state handling, as variables and widgets can be stored on the class itself * add simple `show_alert` method * add show_alert method * adds validation to added fields * adds experiment creation to application * rename `gui_rewrite` to `bciui` * adds app start method * adds vertical center option to bciui * add the beginning of intertask action ui * add progress text * allows for additional args in app running * add functional progress bar * Add next task display and functioning buttons * adds seperate BCIUI file with stylesheet This will hopefully replace BCIGui later, but I am keeping it seperate for now as to not break existing uis on this branch * update demo experiment layout * adjust stylesheet to remove label backgrounds * improves gui code to allow for editing fields * add basic removeable element * add dynamic list class for easy ui reactivity * Add small button component * removes explicit color from small button * adds basic toggle class * changes toggle componenet to be simple connecting function * makes on off callbacks optional in `make_toggle` * add toggle to optional button * swaps confusing parameter names * loads experiment fields into combobox * adds field buttons * refactors gui to be inherited class This improves state handling, as variables and widgets can be stored on the class itself * add simple `show_alert` method * add show_alert method * adds validation to added fields * remove debug prints * adds experiment creation to application * remove unused code * rename `gui_rewrite` to `bciui` * adds app start method * adds vertical center option to bciui * add beginning of intertask action ui * add progress text * allows for additional args in app running * add functional progress bar * Add next task display and functioning buttons * add protocol layout and fix bug in DynamicList * Parameter guardrails and cleanup (#340) * supports adding tasks to the interface * add reordering to tasks in the protocol * allows adding new fields through the ui * adds saving protocol in experiment from gui * Task initialization and cleanup (#343) * Adds documentation to ui methods * rename `intertask_action` to `intertask_gui` * add action that displays intertask GUI * Add proper types and docs to bciui * Deprecates old ExperimentRegistry in favor of new ui code * Fixes incorrect background color when using dark mode * improve stylsheet loading to use existing bcipy constants * update legacy BCInterface to base session-orchestrator * Session Orchestrator Updates [Post-Testing] (#344) * Add logger to each task run * Bcipy client refactor (#346) * Task specific params and Matrix Layout (#349) * Orchestrator - Load a JSON of copy phrases to use during execution (#352) * fix logger assignment * BciPy report action, offline analysis updates, Intertask GUI. (#354) * updates to include IP changes * Update to get static offset from the device --------- Co-authored-by: Carson Reader Co-authored-by: lawhead --- .coveragerc | 2 +- BciPyReport.pdf | Bin 9155 -> 0 bytes CHANGELOG.md | 19 +- README.md | 41 +- bcipy/acquisition/datastream/generator.py | 3 - bcipy/acquisition/datastream/lsl_server.py | 5 +- .../datastream/mock/eye_tracker_server.py | 3 +- bcipy/acquisition/datastream/mock/switch.py | 7 +- bcipy/acquisition/datastream/producer.py | 3 +- bcipy/acquisition/demo/demo_lsl_acq_client.py | 1 - bcipy/acquisition/demo/demo_lsl_server.py | 2 +- bcipy/acquisition/devices.py | 8 +- bcipy/acquisition/marker_writer.py | 3 +- bcipy/acquisition/multimodal.py | 11 +- bcipy/acquisition/protocols/lsl/lsl_client.py | 38 +- .../protocols/lsl/lsl_connector.py | 3 +- .../acquisition/protocols/lsl/lsl_recorder.py | 9 +- .../tests/protocols/lsl/test_lsl_recorder.py | 5 +- bcipy/config.py | 10 +- bcipy/demo/bci_main_demo.py | 58 +- bcipy/display/demo/components/demo_layouts.py | 5 +- .../demo/matrix/demo_calibration_matrix.py | 3 +- .../demo/matrix/demo_copyphrase_matrix.py | 3 +- .../display/demo/matrix/demo_matrix_layout.py | 4 +- bcipy/display/main.py | 10 +- bcipy/display/paradigm/matrix/README.md | 15 - bcipy/display/paradigm/matrix/display.py | 47 +- bcipy/display/paradigm/matrix/layout.py | 13 +- bcipy/display/paradigm/vep/codes.py | 2 +- bcipy/display/paradigm/vep/display.py | 11 +- .../paradigm/matrix/test_matrix_display.py | 18 +- .../paradigm/matrix/test_matrix_layout.py | 30 +- bcipy/display/tests/vep/test_codes.py | 2 +- bcipy/{helpers => }/exceptions.py | 0 bcipy/feedback/feedback.py | 3 +- bcipy/gui/BCInterface.py | 44 +- bcipy/gui/alert.py | 5 +- bcipy/gui/bcipy_stylesheet.css | 87 +++ bcipy/gui/bciui.py | 238 ++++++ bcipy/gui/experiments/ExperimentField.py | 195 +++-- bcipy/gui/experiments/ExperimentRegistry.py | 713 +++++++----------- bcipy/gui/intertask_gui.py | 86 +++ bcipy/gui/main.py | 101 ++- bcipy/gui/parameters/params_form.py | 15 +- bcipy/gui/viewer/data_source/file_streamer.py | 4 +- bcipy/helpers/README.md | 2 + bcipy/helpers/acquisition.py | 16 +- bcipy/helpers/convert.py | 4 +- bcipy/helpers/copy_phrase_wrapper.py | 5 +- bcipy/helpers/language_model.py | 2 +- bcipy/helpers/load.py | 30 +- bcipy/helpers/parameters.py | 19 +- bcipy/helpers/raw_data.py | 2 +- bcipy/helpers/report.py | 10 +- bcipy/helpers/save.py | 2 - bcipy/helpers/stimuli.py | 6 +- bcipy/helpers/symbols.py | 11 +- bcipy/helpers/system_utils.py | 24 +- bcipy/helpers/task.py | 4 +- .../resources/mock_session/parameters.json | 531 +++++++------ bcipy/helpers/tests/test_acquisition.py | 9 +- bcipy/helpers/tests/test_load.py | 21 +- bcipy/helpers/tests/test_parameters.py | 170 +++-- bcipy/helpers/tests/test_raw_data.py | 2 +- bcipy/helpers/tests/test_report.py | 12 +- bcipy/helpers/tests/test_stimuli.py | 2 +- bcipy/helpers/tests/test_triggers.py | 2 +- bcipy/helpers/tests/test_validate.py | 42 +- bcipy/helpers/triggers.py | 6 +- bcipy/helpers/validate.py | 16 +- bcipy/helpers/visualization.py | 50 +- bcipy/language/demo/demo_kenlm.py | 2 +- bcipy/language/main.py | 2 +- bcipy/language/model/causal.py | 2 +- bcipy/language/model/kenlm.py | 2 +- bcipy/language/model/mixture.py | 2 +- bcipy/language/model/oracle.py | 3 +- bcipy/language/model/unigram.py | 2 +- bcipy/language/tests/test_causal.py | 2 +- bcipy/language/tests/test_kenlm.py | 2 +- bcipy/language/tests/test_mixture.py | 2 +- bcipy/language/tests/test_unigram.py | 2 +- bcipy/main.py | 248 ++---- bcipy/parameters/experiment/experiments.json | 8 +- bcipy/parameters/experiment/phrases.json | 13 + bcipy/parameters/parameters.json | 683 ++++++++++------- bcipy/signal/evaluate/artifact.py | 23 +- bcipy/signal/model/__init__.py | 3 - bcipy/signal/model/base_model.py | 4 + bcipy/signal/model/cross_validation.py | 5 +- bcipy/signal/model/density_estimation.py | 4 +- .../signal/model/dimensionality_reduction.py | 4 +- .../signal/model/gaussian_mixture/__init__.py | 6 - .../gaussian_mixture/gaussian_mixture.py | 3 +- bcipy/signal/model/offline_analysis.py | 154 ++-- bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 3 +- bcipy/signal/model/rda_kde/rda_kde.py | 3 +- bcipy/signal/process/decomposition/psd.py | 2 +- bcipy/signal/process/extract_gaze.py | 2 +- .../model/pca_rda_kde/test_pca_rda_kde.py | 2 +- .../tests/model/rda_kde/test_rda_kde.py | 2 +- .../tests/model/test_offline_analysis.py | 28 +- .../decomposition/test_decomposition.py | 2 +- bcipy/simulator/data/data_engine.py | 2 +- bcipy/simulator/data/sampler.py | 4 +- bcipy/simulator/task/copy_phrase.py | 3 + bcipy/task/README.md | 162 +++- bcipy/task/__init__.py | 10 +- bcipy/task/actions.py | 380 ++++++++++ .../{base_calibration.py => calibration.py} | 108 ++- bcipy/task/control/criteria.py | 3 +- bcipy/task/control/evidence.py | 3 +- bcipy/task/control/handler.py | 3 +- bcipy/task/demo/demo_orchestrator.py | 54 ++ bcipy/task/main.py | 53 +- bcipy/task/orchestrator/__init__.py | 3 + bcipy/task/orchestrator/orchestrator.py | 295 ++++++++ bcipy/task/orchestrator/protocol.py | 76 ++ bcipy/task/paradigm/matrix/__init__.py | 4 + bcipy/task/paradigm/matrix/calibration.py | 31 +- bcipy/task/paradigm/matrix/copy_phrase.py | 101 ++- .../paradigm/matrix/timing_verification.py | 11 +- bcipy/task/paradigm/rsvp/__init__.py | 4 + .../paradigm/rsvp/calibration/calibration.py | 16 +- .../rsvp/calibration/timing_verification.py | 36 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 628 ++++++++------- bcipy/task/paradigm/vep/__init__.py | 2 + bcipy/task/paradigm/vep/calibration.py | 46 +- bcipy/task/registry.py | 49 ++ bcipy/task/start_task.py | 104 --- bcipy/task/task_registry.py | 63 -- bcipy/task/tests/core/test_actions.py | 73 ++ bcipy/task/tests/core/test_task_main.py | 57 ++ .../tests/orchestrator/test_orchestrator.py | 157 ++++ .../task/tests/orchestrator/test_protocol.py | 72 ++ .../matrix/test_matrix_calibration.py | 163 ++-- .../rsvp/calibration/test_rsvp_calibration.py | 228 ++++-- .../tests/paradigm/rsvp/test_copy_phrase.py | 235 +++--- bcipy/tests/test_bci_main.py | 655 +++------------- requirements.txt | 10 +- scripts/shell/run_gui.sh | 7 - setup.py | 6 +- 142 files changed, 4921 insertions(+), 3106 deletions(-) delete mode 100644 BciPyReport.pdf rename bcipy/{helpers => }/exceptions.py (100%) create mode 100644 bcipy/gui/bcipy_stylesheet.css create mode 100644 bcipy/gui/bciui.py create mode 100644 bcipy/gui/intertask_gui.py create mode 100644 bcipy/parameters/experiment/phrases.json create mode 100644 bcipy/task/actions.py rename bcipy/task/{base_calibration.py => calibration.py} (81%) create mode 100644 bcipy/task/demo/demo_orchestrator.py create mode 100644 bcipy/task/orchestrator/__init__.py create mode 100644 bcipy/task/orchestrator/orchestrator.py create mode 100644 bcipy/task/orchestrator/protocol.py create mode 100644 bcipy/task/registry.py delete mode 100644 bcipy/task/start_task.py delete mode 100644 bcipy/task/task_registry.py create mode 100644 bcipy/task/tests/core/test_actions.py create mode 100644 bcipy/task/tests/core/test_task_main.py create mode 100644 bcipy/task/tests/orchestrator/test_orchestrator.py create mode 100644 bcipy/task/tests/orchestrator/test_protocol.py delete mode 100644 scripts/shell/run_gui.sh diff --git a/.coveragerc b/.coveragerc index c7ad07bca..443874bee 100644 --- a/.coveragerc +++ b/.coveragerc @@ -17,4 +17,4 @@ exclude_lines = raise NotImplementedError @abstract if __name__ == .__main__.: - 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There are demo files for all modules listed above except helpers and utils. Run them as a python script! +This demo will load in parameters and execute a demo task defined in the file. There are demo files contained in most modules, excepting gui, signal and parameters. Run them as a python script! ## Offset Determination and Correction @@ -293,14 +314,14 @@ If you want to be added to the development team slack or have additional questio We follow and will enforce the contributor's covenant to foster a safe and inclusive environment for this open source software, please reference this link for more information: https://www.contributor-covenant.org/ Other guidelines: -- All features require tests and a demo. +- All modules require tests and a demo. - All tests must pass to merge, even if they are seemingly unrelated to your work. - Use Spaces, not Tabs. - Use informative names for functions and classes. - Document the input and output of your functions / classes in the code. eg in-line commenting and typing. - Do not push IDE or other local configuration files. - All new modules or major functionality should be documented outside of the code with a README.md. - See README.md in repo or go to this site for inspiration: https://github.com/matiassingers/awesome-readme. Always use a Markdown interpreter before pushing. There are many free online or your IDE may come with one. + See README.md in repo or go to this site for inspiration: https://github.com/matiassingers/awesome-readme. Always use a Markdown interpreter before pushing. See this resource for examples: http://docs.python-guide.org/en/latest/writing/style/ diff --git a/bcipy/acquisition/datastream/generator.py b/bcipy/acquisition/datastream/generator.py index f96cf85eb..8c6798bb5 100644 --- a/bcipy/acquisition/datastream/generator.py +++ b/bcipy/acquisition/datastream/generator.py @@ -1,14 +1,11 @@ """Functions for generating mock data to be used for testing/development.""" -import logging from typing import Optional, Generator, Callable from past.builtins import range from bcipy.config import DEFAULT_ENCODING from bcipy.signal.generator.generator import gen_random_data -log = logging.getLogger(__name__) - def advance_to_row(filehandle, rownum): """Utility function to advance a file cursor to the given row.""" diff --git a/bcipy/acquisition/datastream/lsl_server.py b/bcipy/acquisition/datastream/lsl_server.py index dc064a708..0f8f82aa3 100644 --- a/bcipy/acquisition/datastream/lsl_server.py +++ b/bcipy/acquisition/datastream/lsl_server.py @@ -13,10 +13,9 @@ from bcipy.acquisition.datastream.producer import Producer from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.util import StoppableThread -from bcipy.config import DEFAULT_ENCODING, MARKER_STREAM_NAME - -log = logging.getLogger(__name__) +from bcipy.config import DEFAULT_ENCODING, MARKER_STREAM_NAME, SESSION_LOG_FILENAME +log = logging.getLogger(SESSION_LOG_FILENAME) # pylint: disable=too-many-arguments diff --git a/bcipy/acquisition/datastream/mock/eye_tracker_server.py b/bcipy/acquisition/datastream/mock/eye_tracker_server.py index e0a5e4d1d..9cc3c3e73 100644 --- a/bcipy/acquisition/datastream/mock/eye_tracker_server.py +++ b/bcipy/acquisition/datastream/mock/eye_tracker_server.py @@ -8,8 +8,9 @@ from bcipy.acquisition.datastream.lsl_server import LslDataServer from bcipy.acquisition.devices import DeviceSpec +from bcipy.config import SESSION_LOG_FILENAME -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) def eye_tracker_device() -> DeviceSpec: diff --git a/bcipy/acquisition/datastream/mock/switch.py b/bcipy/acquisition/datastream/mock/switch.py index 38145f5b2..824195171 100644 --- a/bcipy/acquisition/datastream/mock/switch.py +++ b/bcipy/acquisition/datastream/mock/switch.py @@ -6,8 +6,9 @@ from bcipy.acquisition.devices import DeviceSpec, IRREGULAR_RATE from bcipy.gui.main import BCIGui, app +from bcipy.config import SESSION_LOG_FILENAME -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) def switch_device() -> DeviceSpec: @@ -41,7 +42,7 @@ def quit(self): self.outlet = None -class SwitchGui(BCIGui): +class SwitchGui(BCIGui): # pragma: no cover """GUI to emulate a switch.""" def __init__(self, switch: Switch, *args, **kwargs): @@ -70,7 +71,7 @@ def build_text(self) -> None: font_size=16) -def main(switch: Switch): +def main(switch: Switch): # pragma: no cover """Creates a PyQt5 GUI with a single button in the middle. Performs the switch action when clicked.""" gui = app(sys.argv) diff --git a/bcipy/acquisition/datastream/producer.py b/bcipy/acquisition/datastream/producer.py index 58633395c..d62ba60d3 100644 --- a/bcipy/acquisition/datastream/producer.py +++ b/bcipy/acquisition/datastream/producer.py @@ -8,8 +8,9 @@ import time from bcipy.acquisition.datastream.generator import random_data_generator +from bcipy.config import SESSION_LOG_FILENAME -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) class Producer(threading.Thread): diff --git a/bcipy/acquisition/demo/demo_lsl_acq_client.py b/bcipy/acquisition/demo/demo_lsl_acq_client.py index b1c0eacbf..3679e94c4 100644 --- a/bcipy/acquisition/demo/demo_lsl_acq_client.py +++ b/bcipy/acquisition/demo/demo_lsl_acq_client.py @@ -1,7 +1,6 @@ """Demo for the LslAcquisitionClient""" import time - from bcipy.acquisition import LslAcquisitionClient diff --git a/bcipy/acquisition/demo/demo_lsl_server.py b/bcipy/acquisition/demo/demo_lsl_server.py index d654ebf21..7ef7bf9c4 100644 --- a/bcipy/acquisition/demo/demo_lsl_server.py +++ b/bcipy/acquisition/demo/demo_lsl_server.py @@ -29,7 +29,7 @@ def main(): while True: time.sleep(1) except KeyboardInterrupt: - print("Keyboard Interrupt") + log.info("Keyboard Interrupt") server.stop() diff --git a/bcipy/acquisition/devices.py b/bcipy/acquisition/devices.py index 115b9c00c..74b152e58 100644 --- a/bcipy/acquisition/devices.py +++ b/bcipy/acquisition/devices.py @@ -6,7 +6,8 @@ from pathlib import Path from typing import Dict, List, NamedTuple, Optional, Union -from bcipy.config import DEFAULT_ENCODING, DEVICE_SPEC_PATH +from bcipy.config import DEFAULT_ENCODING, DEVICE_SPEC_PATH, SESSION_LOG_FILENAME + IRREGULAR_RATE: int = 0 DEFAULT_CONFIG = DEVICE_SPEC_PATH @@ -18,7 +19,7 @@ DEFAULT_DEVICE_TYPE = 'EEG' DEFAULT_STATIC_OFFSET = 0.1 -log = logging.getLogger(__name__) +logger = logging.getLogger(SESSION_LOG_FILENAME) class ChannelSpec(NamedTuple): @@ -182,7 +183,7 @@ def _validate_excluded_channels(self): """Warn if excluded channels are not in the list of channels""" for channel in self.excluded_from_analysis: if channel not in self.channels: - log.warning( + logger.warning( f"Excluded channel {channel} not found in spec for {self.name}" ) @@ -247,6 +248,7 @@ def preconfigured_device(name: str, strict: bool = True) -> DeviceSpec: "\n" "You may register new devices using the device module `register` function or in bulk" " using `load`.") + logger.error(msg) raise ValueError(msg) return device diff --git a/bcipy/acquisition/marker_writer.py b/bcipy/acquisition/marker_writer.py index b7c36d1ab..6d4172654 100644 --- a/bcipy/acquisition/marker_writer.py +++ b/bcipy/acquisition/marker_writer.py @@ -3,8 +3,9 @@ from typing import Any import pylsl +from bcipy.config import SESSION_LOG_FILENAME -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) class MarkerWriter(): diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index cf13a5613..f39d0c266 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -9,8 +9,9 @@ from bcipy.acquisition.protocols.lsl.lsl_client import LslAcquisitionClient from bcipy.acquisition.record import Record from bcipy.helpers.system_utils import AutoNumberEnum +from bcipy.config import SESSION_LOG_FILENAME -log = logging.getLogger(__name__) +logger = logging.getLogger(SESSION_LOG_FILENAME) class ContentType(AutoNumberEnum): @@ -111,11 +112,12 @@ def get_client( def start_acquisition(self): """Start acquiring data for all clients""" for client in self.clients: - log.info(f"Connecting to {client.device_spec.name}...") + logger.info(f"Connecting to {client.device_spec.name}...") client.start_acquisition() def stop_acquisition(self): """Stop acquiring data for all clients""" + logger.info("Stopping acquisition...") for client in self.clients: client.stop_acquisition() @@ -150,12 +152,13 @@ def get_data_by_device( adjusted_start = start + client.device_spec.static_offset if client.device_spec.sample_rate > 0: count = round(seconds * client.device_spec.sample_rate) - log.info(f'Need {count} records for processing {name} data') + logger.info(f'Need {count} records for processing {name} data') output[content_type] = client.get_data(start=adjusted_start, limit=count) data_count = len(output[content_type]) if strict and data_count < count: msg = f'Needed {count} {name} records but received {data_count}' + logger.error(msg) raise InsufficientDataException(msg) else: # Markers have an IRREGULAR_RATE. @@ -174,4 +177,6 @@ def __getattr__(self, name: str) -> Any: client = self.default_client if client: return client.__getattribute__(name) + + logger.error(f"Missing attribute: {name}") raise AttributeError(f"Missing attribute: {name}") diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 86d0dbe1a..754a4d119 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -13,14 +13,14 @@ from bcipy.acquisition.protocols.lsl.lsl_connector import check_device from bcipy.acquisition.protocols.lsl.lsl_recorder import LslRecordingThread from bcipy.acquisition.record import Record -from bcipy.config import MAX_PAUSE_SECONDS +from bcipy.config import MAX_PAUSE_SECONDS, SESSION_LOG_FILENAME from bcipy.gui.viewer.ring_buffer import RingBuffer from bcipy.helpers.clock import Clock -log = logging.getLogger(__name__) - LSL_TIMEOUT = 5.0 # seconds +logger = logging.getLogger(SESSION_LOG_FILENAME) + def time_range(stamps: List[float], precision: int = 3, @@ -112,8 +112,8 @@ def start_acquisition(self) -> bool: stream_info, max_buflen=MAX_PAUSE_SECONDS, max_chunklen=1) - log.info("Acquiring data from data stream:") - log.info(self.inlet.info().as_xml()) + logger.info("Acquiring data from data stream:") + logger.info(self.inlet.info().as_xml()) if self.device_spec: check_device(self.device_spec, self.inlet.info()) @@ -128,10 +128,10 @@ def start_acquisition(self) -> bool: device_spec=self.device_spec, queue=msg_queue) self.recorder.start() - log.info("Waiting for first sample from lsl_recorder") + logger.info("Waiting for first sample from lsl_recorder") self._first_sample_time = msg_queue.get(block=True, timeout=LSL_TIMEOUT) - log.info(f"First sample time: {self.first_sample_time}") + logger.info(f"First sample time: {self.first_sample_time}") self.inlet.open_stream(timeout=LSL_TIMEOUT) if self.max_buffer_len and self.max_buffer_len > 0: @@ -142,16 +142,16 @@ def start_acquisition(self) -> bool: def stop_acquisition(self) -> None: """Disconnect from the data source.""" - log.info(f"Stopping Acquisition from {self.device_spec.name} ...") + logger.info(f"Stopping Acquisition from {self.device_spec.name} ...") if self.recorder: - log.info(f"Closing {self.device_spec.name} data recorder") + logger.info(f"Closing {self.device_spec.name} data recorder") self.recorder.stop() self.recorder.join() if self.inlet: - log.info("Closing LSL connection") + logger.info("Closing LSL connection") self.inlet.close_stream() self.inlet = None - log.info("Inlet closed") + logger.info("Inlet closed") self.buffer = None @@ -202,16 +202,16 @@ def get_data(self, ------- List of Records """ - log.info(request_desc(start, end, limit)) + logger.info(request_desc(start, end, limit)) data = self.get_latest_data() if not data: - log.info('No records available') + logger.info('No records available') return [] data_start = data[0].timestamp data_end = data[-1].timestamp - log.info(f'Available data: {self._data_stats(data)}') + logger.info(f'Available data: {self._data_stats(data)}') if start is None: start = data_start @@ -224,7 +224,7 @@ def get_data(self, data_slice = [ record for record in data if start <= record.timestamp <= end ][0:limit] - log.info(f"Filtered records: {self._data_stats(data_slice)}") + logger.info(f"Filtered records: {self._data_stats(data_slice)}") return data_slice @@ -247,12 +247,12 @@ def _pull_chunk(self) -> int: """Pull a chunk of samples from LSL and record in the buffer. Returns the count of samples pulled. """ - log.debug(f"\tPulling chunk (max_samples: {self.max_samples})") + logger.debug(f"\tPulling chunk (max_samples: {self.max_samples})") # A timeout of 0.0 gets currently available samples without blocking. samples, timestamps = self.inlet.pull_chunk( timeout=0.0, max_samples=self.max_samples) count = len(samples) - log.debug(f"\t-> received {count} samples: {time_range(timestamps)}") + logger.debug(f"\t-> received {count} samples: {time_range(timestamps)}") for sample, stamp in zip(samples, timestamps): self.buffer.append(Record(sample, stamp)) return count @@ -361,7 +361,7 @@ def offset(self, first_stim_time: float) -> float: return 0.0 assert self.first_sample_time, "Acquisition was not started." offset_from_stim = first_stim_time - self.first_sample_time - log.info(f"Acquisition offset: {offset_from_stim}") + logger.info(f"Acquisition offset: {offset_from_stim}") return offset_from_stim def cleanup(self): @@ -371,7 +371,7 @@ def cleanup(self): def discover_device_spec(content_type: str) -> DeviceSpec: """Finds the first LSL stream with the given content type and creates a device spec from the stream's metadata.""" - log.info(f"Waiting for {content_type} data to be streamed over LSL.") + logger.info(f"Waiting for {content_type} data to be streamed over LSL.") streams = resolve_byprop('type', content_type, timeout=LSL_TIMEOUT) if not streams: raise Exception( diff --git a/bcipy/acquisition/protocols/lsl/lsl_connector.py b/bcipy/acquisition/protocols/lsl/lsl_connector.py index 629e90f6f..31363db38 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_connector.py +++ b/bcipy/acquisition/protocols/lsl/lsl_connector.py @@ -7,8 +7,9 @@ import pylsl from bcipy.acquisition.devices import DeviceSpec +from bcipy.config import SESSION_LOG_FILENAME -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) LSL_TIMESTAMP = 'LSL_timestamp' LSL_TIMEOUT_SECONDS = 5.0 diff --git a/bcipy/acquisition/protocols/lsl/lsl_recorder.py b/bcipy/acquisition/protocols/lsl/lsl_recorder.py index 2846d0ee1..75ddee170 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_recorder.py +++ b/bcipy/acquisition/protocols/lsl/lsl_recorder.py @@ -13,9 +13,10 @@ from bcipy.acquisition.protocols.lsl.lsl_connector import (channel_names, check_device) from bcipy.acquisition.util import StoppableProcess +from bcipy.config import SESSION_LOG_FILENAME from bcipy.helpers.raw_data import RawDataWriter -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) class LslRecorder: @@ -144,9 +145,9 @@ def _init_data_writer(self, stream_info: StreamInfo) -> None: def _cleanup(self) -> None: """Performs cleanup tasks.""" - assert self.writer, "Writer not initialized" - self.writer.__exit__() - self.writer = None + if self.writer: + self.writer.__exit__() + self.writer = None def _write_chunk(self, data: List, timestamps: List) -> None: """Persists the data resulting from pulling a chunk from the inlet. diff --git a/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py b/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py index 2db91b78a..e0649e3d2 100644 --- a/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py +++ b/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py @@ -5,6 +5,7 @@ from pathlib import Path import pytest +import logging from bcipy.acquisition.datastream.lsl_server import LslDataServer from bcipy.acquisition.datastream.mock.eye_tracker_server import \ @@ -13,8 +14,10 @@ from bcipy.acquisition.protocols.lsl.lsl_recorder import LslRecorder from bcipy.helpers.raw_data import TIMESTAMP_COLUMN, load +log = logging.getLogger(__name__) + DEVICE_NAME = 'DSI-24' -DEVICE = preconfigured_device(DEVICE_NAME) +DEVICE = preconfigured_device(DEVICE_NAME, log) @pytest.mark.slow diff --git a/bcipy/config.py b/bcipy/config.py index f49c77cc9..0bbc4b562 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -13,15 +13,22 @@ # experiment configuration DEFAULT_EXPERIMENT_ID = 'default' +DEFAULT_FRAME_RATE = 60 +CUSTOM_TASK_EXPERIMENT_ID = "CustomTaskExecution" EXPERIMENT_FILENAME = 'experiments.json' FIELD_FILENAME = 'fields.json' EXPERIMENT_DATA_FILENAME = 'experiment_data.json' +MULTIPHRASE_FILENAME = 'phrases.json' +PROTOCOL_FILENAME = 'protocol.json' BCIPY_ROOT = Path(__file__).resolve().parent ROOT = BCIPY_ROOT.parent DEFAULT_EXPERIMENT_PATH = f'{BCIPY_ROOT}/parameters/experiment' DEFAULT_FIELD_PATH = f'{BCIPY_ROOT}/parameters/field' +DEFAULT_USER_ID = 'test_user' +TASK_SEPERATOR = '->' DEFAULT_PARAMETER_FILENAME = 'parameters.json' +DEFAULT_DEVICES_PATH = f"{BCIPY_ROOT}/parameters" DEFAULT_PARAMETERS_PATH = f'{BCIPY_ROOT}/parameters/{DEFAULT_PARAMETER_FILENAME}' DEFAULT_DEVICE_SPEC_FILENAME = 'devices.json' DEVICE_SPEC_PATH = f'{BCIPY_ROOT}/parameters/{DEFAULT_DEVICE_SPEC_FILENAME}' @@ -49,7 +56,8 @@ TRIGGER_FILENAME = 'triggers.txt' SESSION_DATA_FILENAME = 'session.json' SESSION_SUMMARY_FILENAME = 'session.xlsx' -LOG_FILENAME = 'bcipy_system_log.txt' +SESSION_LOG_FILENAME = 'session_log.txt' +PROTOCOL_LOG_FILENAME = 'protocol_log.txt' STIMULI_POSITIONS_FILENAME = 'stimuli_positions.json' # misc configuration diff --git a/bcipy/demo/bci_main_demo.py b/bcipy/demo/bci_main_demo.py index b2ac274f3..4e3c0adb3 100644 --- a/bcipy/demo/bci_main_demo.py +++ b/bcipy/demo/bci_main_demo.py @@ -1,26 +1,32 @@ -# This is a demo of the main bci system. It will run the task defined here -# using the parameters file passed to it. - - -def main(): - from bcipy.main import bcipy_main - from bcipy.task import TaskType - from bcipy.helpers.parameters import DEFAULT_PARAMETERS_PATH - - # Load a parameters file - parameters = DEFAULT_PARAMETERS_PATH - - # Task. Ex. `RSVP Calibration` - task = TaskType.by_value('RSVP Calibration') - - # Experiment. Use the default registered experiment! - experiment = 'default' - - # Define a user - user = 'bci_main_demo_user' - - bcipy_main(parameters, user, task, experiment) - - -if __name__ == "__main__": - main() +from bcipy.main import bci_main +from bcipy.config import DEFAULT_PARAMETERS_PATH + +parameter_location = DEFAULT_PARAMETERS_PATH # Path to a valid BciPy parameters file +user = 'test_demo_user' # User ID +experiment_id = 'default' # This will run two tasks: RSVP Calibration and Matrix Calibration +alert = False # Set to True to alert user when tasks are complete +visualize = False # Set to True to visualize data at the end of a task +fake_data = True # Set to True to use fake acquisition data during the session +# A single task or experiment ID must be provided to run. If a task is provided, the experiment ID will be ignored. +task = None + + +def bcipy_main(): + """BCI Main Demo. + + This function demonstrates how to use the BciPy main function outside of the client interface to execute tasks + or experiments. + """ + bci_main( + parameter_location=parameter_location, + user=user, + experiment_id=experiment_id, + alert=alert, + visualize=visualize, + fake=fake_data, + task=task + ) + + +if __name__ == '__main__': + bcipy_main() diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index adb2fd071..08521c73f 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -264,11 +264,12 @@ def demo_matrix_positions(win: visual.Window): # norm_layout = centered(parent=win, width_pct=1., height_pct=0.5) task_bar = at_top(parent=win, height=0.25) win_layout = Layout(win) + symbols = alphabet() norm_layout = centered(parent=win, width_pct=0.7, height_pct=0.75) - positions = symbol_positions(norm_layout, rows=5, columns=6) + positions = symbol_positions(norm_layout, symbol_set=symbols, rows=5, columns=6) - for sym, pos in zip(alphabet(), positions): + for sym, pos in zip(symbols, positions): stim = visual.TextStim(win, text=sym, pos=pos, diff --git a/bcipy/display/demo/matrix/demo_calibration_matrix.py b/bcipy/display/demo/matrix/demo_calibration_matrix.py index bb1a1cb02..3e737644d 100644 --- a/bcipy/display/demo/matrix/demo_calibration_matrix.py +++ b/bcipy/display/demo/matrix/demo_calibration_matrix.py @@ -19,7 +19,8 @@ stim_properties = StimuliProperties(stim_font='Arial', stim_pos=(-0.6, 0.4), stim_height=0.17, - is_txt_stim=True) + is_txt_stim=True, + layout='ALP') # Initialize Stimulus window_parameters = { diff --git a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py index 33b27ce2c..f2b7e73c0 100644 --- a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py +++ b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py @@ -26,7 +26,8 @@ stim_properties = StimuliProperties(stim_font=font, stim_pos=(-0.6, 0.4), stim_height=0.17, - is_txt_stim=True) + is_txt_stim=True, + layout='ALP') # Initialize Stimulus window_parameters = { diff --git a/bcipy/display/demo/matrix/demo_matrix_layout.py b/bcipy/display/demo/matrix/demo_matrix_layout.py index 72249743b..62ba0a0af 100644 --- a/bcipy/display/demo/matrix/demo_matrix_layout.py +++ b/bcipy/display/demo/matrix/demo_matrix_layout.py @@ -35,7 +35,8 @@ stim_properties = StimuliProperties(stim_font=font, stim_pos=[], stim_height=0.5, - is_txt_stim=True) + is_txt_stim=True, + layout='QWERTY') info = InformationProperties( info_color=['white'], @@ -54,7 +55,6 @@ columns=7, width_pct=0.7, height_pct=matrix_height_pct) -# sort_order=qwerty_order(is_txt_stim=True)) matrix_display.draw(grid_opacity=matrix_display.full_grid_opacity, grid_color=matrix_display.grid_color, diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 52b227a29..8aa9f9b94 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -1,7 +1,6 @@ # mypy: disable-error-code="assignment,empty-body" from abc import ABC, abstractmethod from enum import Enum -from logging import Logger from typing import Any, List, NamedTuple, Optional, Tuple, Type, Union from psychopy import visual @@ -22,7 +21,6 @@ class Display(ABC): window: visual.Window = None timing_clock: Clock = None experiment_clock: Clock = None - logger: Logger = None stimuli_inquiry: List[str] = None stimuli_colors: List[str] = None stimuli_timing: List[float] = None @@ -132,7 +130,7 @@ def init_display_window(parameters): class StimuliProperties: """"Stimuli Properties. - An encapsulation of properties relevant to core stimuli presentation in an RSVP or Matrix paradigm. + An encapsulation of properties relevant to core stimuli presentation in a paradigm. """ def __init__( @@ -144,7 +142,8 @@ def __init__( stim_colors: Optional[List[str]] = None, stim_timing: Optional[List[float]] = None, is_txt_stim: bool = True, - prompt_time: Optional[float] = None): + prompt_time: Optional[float] = None, + layout: Optional[str] = None): """Initialize Stimuli Parameters. stim_font(List[str]): Ordered list of colors to apply to information stimuli @@ -156,6 +155,8 @@ def __init__( stim_timing(List[float]): Ordered list of timing to apply to an inquiry using the stimuli is_txt_stim(bool): Whether or not this is a text based stimuli (False implies image based) prompt_time(float): Time to display target prompt for at the beginning of inquiry + layout(str): Layout of stimuli on the screen (ex. 'ALPHABET' or 'QWERTY'). + This is only used for matrix displays. """ self.stim_font = stim_font self.stim_pos = stim_pos @@ -167,6 +168,7 @@ def __init__( self.stim_length = len(self.stim_inquiry) self.sti = None self.prompt_time = prompt_time + self.layout = layout def build_init_stimuli(self, window: visual.Window) -> Union[visual.TextStim, visual.ImageStim]: """"Build Initial Stimuli. diff --git a/bcipy/display/paradigm/matrix/README.md b/bcipy/display/paradigm/matrix/README.md index 22d731125..0fbdf4a89 100644 --- a/bcipy/display/paradigm/matrix/README.md +++ b/bcipy/display/paradigm/matrix/README.md @@ -55,21 +55,6 @@ matrix_display = MatrixDisplay(win, columns=7) ``` -## Sorting stimuli - -A sort order function for the symbols can specified. The sort function includes the ability to provide blank spaces within the grid. - -``` -from bcipy.helpers.symbols import qwerty_order -matrix_display = MatrixDisplay(win, - experiment_clock, - stim_properties, - task_bar=task_bar, - info=info, - rows=3, - columns=10, - sort_order=qwerty_order(is_txt_stim=True)) -``` ## Layout diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 6cbfa0198..b22f081b4 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -1,20 +1,22 @@ """Display for presenting stimuli in a grid.""" import logging -from typing import Callable, Dict, List, NamedTuple, Optional, Tuple +from typing import Dict, List, NamedTuple, Optional, Tuple from psychopy import core, visual import bcipy.display.components.layout as layout -from bcipy.config import MATRIX_IMAGE_FILENAME +from bcipy.config import MATRIX_IMAGE_FILENAME, SESSION_LOG_FILENAME from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, StimuliProperties) from bcipy.display.components.task_bar import TaskBar from bcipy.display.main import PreviewParams, init_preview_button_handler from bcipy.display.paradigm.matrix.layout import symbol_positions from bcipy.helpers.stimuli import resize_image -from bcipy.helpers.symbols import alphabet +from bcipy.helpers.symbols import alphabet, qwerty_order, frequency_order from bcipy.helpers.triggers import _calibration_trigger +logger = logging.getLogger(SESSION_LOG_FILENAME) + class SymbolDuration(NamedTuple): """Represents a symbol and its associated duration to display""" @@ -33,7 +35,7 @@ class MatrixDisplay(Display): time_fixation: 2 stim_pos_x: -0.6 stim_pos_y: 0.4 - stim_height: 0.1 + stim_height: 0.17 """ def __init__(self, @@ -47,9 +49,8 @@ def __init__(self, width_pct: float = 0.75, height_pct: float = 0.8, trigger_type: str = 'text', - symbol_set: Optional[List[str]] = None, + symbol_set: Optional[List[str]] = alphabet(), should_prompt_target: bool = True, - sort_order: Optional[Callable] = None, preview_config: Optional[PreviewParams] = None): """Initialize Matrix display parameters and objects. @@ -79,8 +80,6 @@ def __init__(self, """ self.window = window - self.logger = logging.getLogger(__name__) - self.stimuli_inquiry = [] self.stimuli_timing = [] self.stimuli_colors = [] @@ -88,15 +87,16 @@ def __init__(self, assert stimuli.is_txt_stim, "Matrix display is a text only display" - self.symbol_set = symbol_set or alphabet() - self.sort_order = sort_order or self.symbol_set.index + self.symbol_set = symbol_set + self.sort_order = self.build_sort_order(stimuli) # Set position and parameters for grid of alphabet - self.grid_stimuli_height = 0.17 # stimuli.stim_height + self.grid_stimuli_height = stimuli.stim_height display_container = layout.centered(parent=window, width_pct=width_pct, height_pct=height_pct) - self.positions = symbol_positions(display_container, rows, columns) + self.positions = symbol_positions( + display_container, rows, columns, symbol_set) self.grid_color = 'white' self.start_opacity = 0.15 @@ -122,10 +122,23 @@ def __init__(self, preview_config, experiment_clock) if self.preview_enabled else None self.preview_accepted = True - self.logger.info( + logger.info( f"Symbol positions ({display_container.units} units):\n{self.stim_positions}" ) - self.logger.info(f"Matrix center position: {display_container.center}") + logger.info(f"Matrix center position: {display_container.center}") + + def build_sort_order(self, stimuli: StimuliProperties) -> List[str]: + """Build the symbol set for the display.""" + if stimuli.layout == 'ALP': + return self.symbol_set.index + elif stimuli.layout == 'QWERTY': + logger.info('Using QWERTY layout') + return qwerty_order() + elif stimuli.layout == 'FREQ': + logger.info('Using frequency layout') + return frequency_order() + else: + raise ValueError(f'Unknown layout: {stimuli.layout}') @property def stim_positions(self) -> Dict[str, Tuple[float, float]]: @@ -222,11 +235,13 @@ def do_inquiry(self) -> List[Tuple[str, float]]: def build_grid(self) -> Dict[str, visual.TextStim]: """Build the text stimuli to populate the grid.""" + grid = {} for sym in self.symbol_set: pos_index = self.sort_order(sym) pos = self.positions[pos_index] grid[sym] = visual.TextStim(win=self.window, + font=self.stimuli_font, text=sym, color=self.grid_color, opacity=self.start_opacity, @@ -334,7 +349,7 @@ def draw(self, core.wait(duration) def animate_scp(self, fixation: SymbolDuration, - stimuli: List[SymbolDuration]): + stimuli: List[SymbolDuration]) -> None: """Animate the given stimuli using single character presentation. Flashes each stimuli in stimuli_inquiry for their respective flash @@ -405,7 +420,7 @@ def draw_components(self) -> None: for info in self.info_text: info.draw() - def update_task_bar(self, text: str = ''): + def update_task_bar(self, text: str = '') -> None: """Update Task. Update any task related display items not related to the inquiry. Ex. stimuli count 1/200. diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index 7ecccd814..994642bf4 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -1,16 +1,16 @@ """Functions for calculating matrix layouts""" -import logging from typing import List, Optional, Tuple from bcipy.display.components.layout import (Layout, above, below, left_of, right_of, scaled_height, scaled_width) -logger = logging.getLogger(__name__) - -def symbol_positions(container: Layout, rows: int, - columns: int, max_spacing: Optional[float] = None) -> List[Tuple[float, float]]: +def symbol_positions(container: Layout, + rows: int, + columns: int, + symbol_set: List[str], + max_spacing: Optional[float] = None) -> List[Tuple[float, float]]: """Compute the positions for arranging a number of symbols in a grid layout. @@ -20,6 +20,7 @@ def symbol_positions(container: Layout, rows: int, visual.Window parent, which is used to determine the aspect ratio. rows - number of rows in the grid columns - number of columns in the grid + symbol_set - list of symbols to place in the grid max_spacing - optional max spacing (in layout units) in the height direction; width will be normalized to this value if provided Returns @@ -28,6 +29,8 @@ def symbol_positions(container: Layout, rows: int, """ assert container.parent, "Container must have a parent" assert rows >= 1 and columns >= 1, "There must be at least one row and one column" + assert rows * columns >= len(symbol_set), \ + f"Not enough positions for symbols {len(symbol_set)}. Increase rows or columns." # compute the spacing (in container units) from the container width and height win_size = container.parent.size diff --git a/bcipy/display/paradigm/vep/codes.py b/bcipy/display/paradigm/vep/codes.py index 86e367460..833288ae4 100644 --- a/bcipy/display/paradigm/vep/codes.py +++ b/bcipy/display/paradigm/vep/codes.py @@ -4,7 +4,7 @@ import numpy as np -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.exceptions import BciPyCoreException log = logging.getLogger(__name__) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 0df6032ac..f3fb0afeb 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -89,7 +89,8 @@ def __init__(self, display_container = layout.centered(parent=self.window, width_pct=0.7) self.starting_positions = symbol_positions(display_container, rows=3, - columns=10) + columns=10, + symbol_set=self.symbol_set) self.logger.info( f"Symbol starting positions ({str(display_container.units)} units): {self.starting_positions}" ) @@ -112,6 +113,8 @@ def __init__(self, self.task_bar = task_bar self.info_text = info.build_info_text(window) + self.box_stim_height = 0.24 + # build the VEP stimuli self.flicker_rates = flicker_rates self.logger.info(f"VEP flicker rates (hz): {flicker_rates}") @@ -122,7 +125,7 @@ def __init__(self, ] vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] - vep_stim_size = scaled_size(0.24, self.window_size) + vep_stim_size = scaled_size(self.box_stim_height, self.window_size) self.vep = self.build_vep_stimuli(positions=box_config.positions, codes=codes, colors=cycle(vep_colors), @@ -381,9 +384,6 @@ def draw_static(self) -> None: if self.task_bar: self.task_bar.draw() - for info in self.info_text: - info.draw() - def update_task_bar(self, text: str = ''): """Update any task related display items not related to the inquiry. Ex. stimuli count 1/200. @@ -412,6 +412,7 @@ def _build_inquiry_stimuli(self) -> Dict[str, visual.TextStim]: for sym in self.symbol_set: pos_index = self.sort_order(sym) grid[sym] = visual.TextStim(win=self.window, + font=self.stimuli_font, text=sym, color=self.starting_color, pos=self.starting_positions[pos_index], diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py index 36bccca82..dd71cc251 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py @@ -12,13 +12,15 @@ # Define some reusable elements to test Matrix Display with LEN_STIM = 10 -TEST_STIM = StimuliProperties(stim_font='Arial', - stim_pos=(-0.6, 0.4), - stim_height=0.1, - stim_inquiry=['A'], - stim_colors=[], - stim_timing=[0.1], - is_txt_stim=True) +TEST_STIM = StimuliProperties( + stim_font='Arial', + stim_pos=(-0.6, 0.4), + stim_height=0.1, + stim_inquiry=['A'], + stim_colors=[], + stim_timing=[0.1], + is_txt_stim=True, + layout='QWERTY') TEST_INFO = InformationProperties( info_color=['White'], @@ -43,7 +45,7 @@ def setUp(self): spec=psychopy.visual.TextStim) when(self.text_stim_mock).setOpacity(...).thenReturn() when(self.text_stim_mock).setColor(...).thenReturn() - when(self.text_stim_mock).draw(...).thenReturn() + when(self.text_stim_mock).draw().thenReturn() # grid item when(psychopy.visual).TextStim( diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py index a6c7c8b4f..bd562dbd2 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_layout.py @@ -19,12 +19,14 @@ def setUp(self): top=1.0, right=1.0, bottom=-1.0) + self.symbols = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J'] def test_regular_grid(self): """Test basic properties of a regular grid""" row_count = 4 col_count = 5 positions = symbol_positions(self.layout, + symbol_set=self.symbols, rows=row_count, columns=col_count) self.assertEqual(len(positions), 20) @@ -37,7 +39,11 @@ def test_regular_grid(self): def test_single_row(self): """Test position calculations for a single row""" - positions = symbol_positions(self.layout, rows=1, columns=10) + positions = symbol_positions( + self.layout, + symbol_set=self.symbols, + rows=1, + columns=10) self.assertEqual(len(positions), 10) y_coord = positions[0][1] @@ -59,7 +65,11 @@ def test_single_row(self): def test_single_column(self): """Test position calculations for a single column""" - positions = symbol_positions(self.layout, rows=10, columns=1) + positions = symbol_positions( + self.layout, + symbol_set=self.symbols, + rows=10, + columns=1) self.assertEqual(len(positions), 10) x_coord = positions[0][0] @@ -80,7 +90,11 @@ def test_single_column(self): def test_spacing(self): """Test grid spacing""" - positions = symbol_positions(self.layout, rows=2, columns=2) + positions = symbol_positions( + self.layout, + symbol_set=['A', 'B', 'C', 'D'], + rows=2, + columns=2) self.assertEqual(len(positions), 4) top_left = positions[0] @@ -107,6 +121,7 @@ def test_max_spacing(self): """Test max_spacing parameter""" max_spacing = 0.1 positions = symbol_positions(self.layout, + symbol_set=['A', 'B', 'C', 'D'], rows=2, columns=2, max_spacing=max_spacing) @@ -120,6 +135,15 @@ def test_max_spacing(self): self.assertEqual(row_spacing, max_spacing) self.assertEqual(column_spacing, max_spacing) + def test_symbol_position_throws_error_with_too_many_symbols(self): + """Test that an error is thrown if there are too many symbols for the grid""" + with self.assertRaises(AssertionError): + symbol_positions(self.layout, + symbol_set=self.symbols, + rows=2, + columns=2, + max_spacing=0.1) + if __name__ == '__main__': unittest.main() diff --git a/bcipy/display/tests/vep/test_codes.py b/bcipy/display/tests/vep/test_codes.py index cd0584dbb..5b1d82b4b 100644 --- a/bcipy/display/tests/vep/test_codes.py +++ b/bcipy/display/tests/vep/test_codes.py @@ -1,7 +1,7 @@ import unittest from bcipy.display.paradigm.vep.codes import round_refresh_rate, ssvep_to_code -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.exceptions import BciPyCoreException class SSVEPStimuli(unittest.TestCase): diff --git a/bcipy/helpers/exceptions.py b/bcipy/exceptions.py similarity index 100% rename from bcipy/helpers/exceptions.py rename to bcipy/exceptions.py diff --git a/bcipy/feedback/feedback.py b/bcipy/feedback/feedback.py index 9bb264f39..8496371b8 100644 --- a/bcipy/feedback/feedback.py +++ b/bcipy/feedback/feedback.py @@ -1,4 +1,5 @@ import logging +from bcipy.config import SESSION_LOG_FILENAME REGISTERED_FEEDBACK_TYPES = ['sound', 'visual'] @@ -9,7 +10,7 @@ class Feedback: def __init__(self, feedback_type): super(Feedback, self).__init__() self.feedback_type = feedback_type - self.logger = logging.getLogger(__name__) + self.logger = logging.getLogger(SESSION_LOG_FILENAME) def configure(self): raise NotImplementedError() diff --git a/bcipy/gui/BCInterface.py b/bcipy/gui/BCInterface.py index 326e2a1f6..3a4c79134 100644 --- a/bcipy/gui/BCInterface.py +++ b/bcipy/gui/BCInterface.py @@ -1,16 +1,19 @@ import subprocess import sys +import logging from typing import List from bcipy.config import (BCIPY_ROOT, DEFAULT_PARAMETERS_PATH, - STATIC_IMAGES_PATH) + STATIC_IMAGES_PATH, PROTOCOL_LOG_FILENAME) from bcipy.gui.main import (AlertMessageResponse, AlertMessageType, AlertResponse, BCIGui, app, contains_special_characters, contains_whitespaces, invalid_length) from bcipy.helpers.load import (copy_parameters, load_experiments, load_json_parameters, load_users) -from bcipy.task import TaskType +from bcipy.task import TaskRegistry + +logger = logging.getLogger(PROTOCOL_LOG_FILENAME) class BCInterface(BCIGui): @@ -20,7 +23,7 @@ class BCInterface(BCIGui): editing and loading, and offline analysis execution. """ - tasks = TaskType.list() + tasks = TaskRegistry().list() default_text = '...' padding = 20 @@ -29,7 +32,7 @@ class BCInterface(BCIGui): max_length = 25 min_length = 1 timeout = 3 - font = 'Consolas' + font = 'Courier New' def __init__(self, *args, **kwargs): super(BCInterface, self).__init__(*args, **kwargs) @@ -333,17 +336,18 @@ def check_input(self) -> bool: try: if not self.check_user_id(): return False - if self.experiment == BCInterface.default_text: + + if self.experiment == BCInterface.default_text and self.task == BCInterface.default_text: self.throw_alert_message( title='BciPy Alert', - message='Please select or create an Experiment', + message='Please select an Experiment or Task for execution', message_type=AlertMessageType.INFO, message_response=AlertMessageResponse.OTE) return False - if self.task == BCInterface.default_text: + if self.experiment != BCInterface.default_text and self.task != BCInterface.default_text: self.throw_alert_message( title='BciPy Alert', - message='Please select a Task', + message='Please select only an Experiment or Task', message_type=AlertMessageType.INFO, message_response=AlertMessageResponse.OTE) return False @@ -407,13 +411,25 @@ def start_experiment(self) -> None: message_type=AlertMessageType.INFO, message_response=AlertMessageResponse.OTE, message_timeout=self.task_start_timeout) - cmd = ( - f'bcipy -e "{self.experiment}" ' - f'-u "{self.user}" -t "{self.task}" -p "{self.parameter_location}"' - ) + if self.task != BCInterface.default_text: + cmd = ( + f'bcipy ' + f'-u "{self.user}" -t "{self.task}" -p "{self.parameter_location}"' + ) + else: + cmd = ( + f'bcipy ' + f'-u "{self.user}" -e "{self.experiment}" -p "{self.parameter_location}"' + ) if self.alert: cmd += ' -a' - subprocess.Popen(cmd, shell=True) + output = subprocess.run(cmd, shell=True) + if output.returncode != 0: + self.throw_alert_message( + title='BciPy Alert', + message=f'Error: {output.stderr.decode()}', + message_type=AlertMessageType.CRIT, + message_response=AlertMessageResponse.OTE) if self.autoclose: self.close() @@ -424,7 +440,7 @@ def offline_analysis(self) -> None: Run offline analysis as a script in a new process. """ if not self.action_disabled(): - cmd = f'python {BCIPY_ROOT}/signal/model/offline_analysis.py --alert --p "{self.parameter_location}"' + cmd = f'bcipy-train --alert --p "{self.parameter_location}" -v -s' subprocess.Popen(cmd, shell=True) def action_disabled(self) -> bool: diff --git a/bcipy/gui/alert.py b/bcipy/gui/alert.py index d974349d9..91fec4c9e 100644 --- a/bcipy/gui/alert.py +++ b/bcipy/gui/alert.py @@ -15,12 +15,13 @@ def confirm(message: str) -> bool: ------- users selection : True for selecting Ok, False for Cancel. """ - app = QApplication(sys.argv) + app = QApplication(sys.argv).instance() + if not app: + app = QApplication(sys.argv) dialog = alert_message(message, message_type=AlertMessageType.INFO, message_response=AlertMessageResponse.OCE) button = dialog.exec() - result = bool(button == AlertResponse.OK.value) app.quit() return result diff --git a/bcipy/gui/bcipy_stylesheet.css b/bcipy/gui/bcipy_stylesheet.css new file mode 100644 index 000000000..58b53a88b --- /dev/null +++ b/bcipy/gui/bcipy_stylesheet.css @@ -0,0 +1,87 @@ +/* This stylesheet uses the QSS syntax, but is named as a CSS file to take advantage of IDE CSS tooling */ + +QWidget[class="experiment-registry"] { + background-color: black; +} + +QWidget[class="inter-task"] { + background-color: black; +} + +QLabel { + background-color: black; + color: white; +} + +QLabel[class="task-label"] { + background-color: transparent; + color: black; +} + +QPushButton { + background-color: rgb(16, 173, 39); + color: white; + padding: 10px; + border-radius: 10px; +} + +QPushButton[class="remove-button"] { + background-color: rgb(243, 58, 58); +} + +QPushButton[class="remove-button"]:hover { + background-color: rgb(255, 0, 0); +} + +QPushButton[class="small-button"] { + background-color: darkslategray; + color: white; + padding: 5px; + border-radius: 5px; +} + +QPushButton[class="small-button"]:hover { + background-color: darkgreen; +} + + +QPushButton:pressed { + background-color: darkslategrey; +} + +QComboBox { + background-color: white; + color: black; + padding: 4px; + border-radius: 1px; +} + +QComboBox:hover { + background-color: #e6f5ea; + color: black; +} + +QComboBox:on { + background-color: #e6f5ea; + color: black; +} + +QListView { + background-color: white; + color: black; + padding: 5px; +} + +QLineEdit { + background-color: white; + color: black; + padding: 5px; + border: none; + border-radius: 1px; +} + +QScrollArea { + background-color: white; + color: black; + border-radius: 1px; +} \ No newline at end of file diff --git a/bcipy/gui/bciui.py b/bcipy/gui/bciui.py new file mode 100644 index 000000000..b3c301832 --- /dev/null +++ b/bcipy/gui/bciui.py @@ -0,0 +1,238 @@ +from typing import Callable, Type +from PyQt6.QtCore import pyqtSignal +from PyQt6.QtWidgets import ( + QWidget, + QVBoxLayout, + QHBoxLayout, + QPushButton, + QScrollArea, + QLayout, + QSizePolicy, + QMessageBox, + QApplication, +) +from typing import Optional, List +from bcipy.config import BCIPY_ROOT +import sys + + +class BCIUI(QWidget): + contents: QVBoxLayout + center_content_vertically: bool = False + + def __init__(self, title: str = "BCIUI", default_width: int = 500, default_height: int = 600) -> None: + super().__init__() + self.resize(default_width, default_height) + self.setWindowTitle(title) + self.contents = QVBoxLayout() + self.setLayout(self.contents) + + def app(self): + ... + + def apply_stylesheet(self) -> None: + stylesheet_path = f'{BCIPY_ROOT}/gui/bcipy_stylesheet.css' # TODO: move to config + with open(stylesheet_path, "r") as f: + stylesheet = f.read() + self.setStyleSheet(stylesheet) + + def display(self) -> None: + # Push contents to the top of the window + """ + Display the UI window and apply the stylesheet. + """ + self.app() + if not self.center_content_vertically: + self.contents.addStretch() + self.apply_stylesheet() + self.show() + + def show_alert(self, alert_text: str) -> int: + """ + Shows an alert dialog with the specified text. + + PARAMETERS + ---------- + :param: alert_text: string text to display in the alert dialog. + """ + msg = QMessageBox() + msg.setText(alert_text) + msg.setWindowTitle("Alert") + return msg.exec() + + @staticmethod + def centered(widget: QWidget) -> QHBoxLayout: + layout = QHBoxLayout() + layout.addStretch() + layout.addWidget(widget) + layout.addStretch() + return layout + + @staticmethod + def make_list_scroll_area(widget: QWidget) -> QScrollArea: + scroll_area = QScrollArea() + scroll_area.setWidget(widget) + scroll_area.setWidgetResizable(True) + return scroll_area + + @staticmethod + def make_toggle( + on_button: QPushButton, + off_button: QPushButton, + on_action: Optional[Callable] = lambda: None, + off_action: Optional[Callable] = lambda: None, + ) -> None: + """ + Connects two buttons to toggle between eachother and call passed methods + + PARAMETERS + ---------- + :param: on_button: QPushButton to toggle on + :param: off_button: QPushButton to toggle off + :param: on_action: function to call when on_button is clicked + :param: off_action: function to call when off_button is clicked + + """ + off_button.hide() + + def toggle_off(): + on_button.hide() + off_button.show() + off_action() + + def toggle_on(): + on_button.show() + off_button.hide() + on_action() + + on_button.clicked.connect(toggle_off) + off_button.clicked.connect(toggle_on) + + def hide(self) -> None: + """Close the UI window""" + self.hide() + + +class SmallButton(QPushButton): + """A small button with a fixed size""" + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.setProperty("class", "small-button") + self.setSizePolicy(QSizePolicy.Policy.Fixed, QSizePolicy.Policy.Fixed) + + +class DynamicItem(QWidget): + """A widget that can be dynamically added and removed from the ui""" + + on_remove: pyqtSignal = pyqtSignal() + data: dict = {} + + def remove(self) -> None: + """Remove the widget from it's parent DynamicList, removing it from the UI and deleting it""" + self.on_remove.emit() + + +class DynamicList(QWidget): + """A list of QWidgets that can be dynamically updated""" + + widgets: List[QWidget] + + def __init__(self, layout: Optional[QLayout] = None): + super().__init__() + if layout is None: + layout = QVBoxLayout() + self.setLayout(layout) + self.widgets = [] + + def __len__(self): + return len(self.widgets) + + def add_item(self, item: DynamicItem) -> None: + """ + Add a DynamicItem to the list. + + PARAMETERS + ---------- + :param: item: DynamicItem to add to the list. + """ + self.widgets.append(item) + item.on_remove.connect(lambda: self.remove_item(item)) + self.layout().addWidget(item) + + def move_item(self, item: DynamicItem, new_index: int) -> None: + """ + Move a DynamicItem to a new index in the list. + + PARAMETERS + ---------- + :param: item: A reference to the DynamicItem in the list to be moved. + :param: new_index: int new index to move the item to. + """ + if new_index < 0 or new_index >= len(self): + raise IndexError(f"Index out of range for length {len(self)}") + + self.widgets.pop(self.widgets.index(item)) + self.widgets.insert(new_index, item) + self.layout().removeWidget(item) + self.layout().insertWidget(new_index, item) + + def index(self, item: DynamicItem) -> int: + """ + Get the index of a DynamicItem in the list. + + PARAMETERS + ---------- + :param: item: A reference to the DynamicItem in the list to get the index of. + + Returns + ------- + The index of the item in the list. + """ + return self.widgets.index(item) + + def remove_item(self, item: DynamicItem) -> None: + """ + Remove a DynamicItem from the list. + + PARAMETERS + ---------- + :param: item: A reference to the DynamicItem to remove from the list + """ + self.widgets.remove(item) + self.layout().removeWidget(item) + item.deleteLater() + + def clear(self) -> None: + """Remove all items from the list""" + for widget in self.widgets: + self.layout().removeWidget(widget) + widget.deleteLater() + self.widgets = [] + + def list(self): + return [widget.data for widget in self.widgets] + + def list_property(self, prop: str): + """ + Get a list of values for a given property of each DynamicItem's data dictionary. + + PARAMETERS + ---------- + :param: prop: string property name to get the values of. + + Returns + ------- + A list of values for the given property. + """ + return [widget.data[prop] for widget in self.widgets] + + +def run_bciui(ui: Type[BCIUI], *args, **kwargs): + # add app to kwargs + app = QApplication(sys.argv).instance() + if not app: + app = QApplication(sys.argv) + ui_instance = ui(*args, **kwargs) + ui_instance.display() + return app.exec() diff --git a/bcipy/gui/experiments/ExperimentField.py b/bcipy/gui/experiments/ExperimentField.py index 290e6c692..4ec1e51a0 100644 --- a/bcipy/gui/experiments/ExperimentField.py +++ b/bcipy/gui/experiments/ExperimentField.py @@ -1,4 +1,5 @@ """GUI form for collecting experimental field data.""" + # pylint: disable=E0611 import sys @@ -26,8 +27,10 @@ FloatInput, FormInput, IntegerInput, - TextInput + TextInput, ) +from bcipy.config import EXPERIMENT_DATA_FILENAME +from bcipy.helpers.validate import validate_experiment, validate_field_data_written from bcipy.helpers.load import load_experiments, load_fields from bcipy.helpers.save import save_experiment_field_data @@ -38,20 +41,29 @@ class ExperimentFieldCollection(QWidget): Given an experiment with fields to be collected, this UI can be used to collect data in the correct format and require fields which are noted as such in the experiment. """ + field_data: List[tuple] = [] field_inputs: List[FormInput] = [] type_inputs = { - 'int': (IntegerInput, 0), - 'float': (FloatInput, 0.0), - 'bool': (BoolInput, False), - 'filepath': (FileInput, ''), - 'directorypath': (DirectoryInput, ''), + "int": (IntegerInput, 0), + "float": (FloatInput, 0.0), + "bool": (BoolInput, False), + "filepath": (FileInput, ""), + "directorypath": (DirectoryInput, ""), } - require_mark = '*' + require_mark = "*" alert_timeout = 10 save_data = {} - def __init__(self, title: str, width: int, height: int, experiment_name: str, save_path: str, file_name: str): + def __init__( + self, + title: str, + width: int, + height: int, + experiment_name: str, + save_path: str, + file_name: str, + ): super().__init__() self.experiment_name = experiment_name @@ -59,7 +71,7 @@ def __init__(self, title: str, width: int, height: int, experiment_name: str, sa self.save_path = save_path self.file_name = file_name self.help_size = 12 - self.help_color = 'darkgray' + self.help_color = "darkgray" self.width = width self.height = height self.title = title @@ -87,9 +99,13 @@ def build_form(self) -> None: Loop over the field data and create UI field inputs for data collection. """ for field_name, field_type, required, help_text in self.field_data: - self.field_inputs.append(self.field_input(field_name, field_type, help_text, required)) + self.field_inputs.append( + self.field_input(field_name, field_type, help_text, required) + ) - def field_input(self, field_name: str, field_type: str, help_tip: str, required: bool) -> FormInput: + def field_input( + self, field_name: str, field_type: str, help_tip: str, required: bool + ) -> FormInput: """Field Input. Construct a FormInput for the given field based on its python type and other @@ -105,7 +121,8 @@ def field_input(self, field_name: str, field_type: str, help_tip: str, required: value=init_value, help_tip=help_tip, help_size=self.help_size, - help_color=self.help_color) + help_color=self.help_color, + ) def build_assets(self) -> None: """Build Assets. @@ -124,11 +141,12 @@ def check_input(self) -> bool: name = field.label if self.require_mark in field.label and not _input: self.throw_alert_message( - title='BciPy Alert', - message=f'Required field {name.strip(self.require_mark)} must be filled out!', + title="BciPy Alert", + message=f"Required field {name.strip(self.require_mark)} must be filled out!", message_type=AlertMessageType.CRIT, message_response=AlertMessageResponse.OCE, - message_timeout=self.alert_timeout) + message_timeout=self.alert_timeout, + ) return False return True @@ -138,13 +156,18 @@ def build_field_data(self) -> None: Using the fields defined in the experiment, fetch the other attributes of the field. It will be stored in self.field_data as a list of tuples (name, field type, required, help text). """ - for field in self.experiment['fields']: + for field in self.experiment["fields"]: # the field name and requirement for name, required in field.items(): # help text and type field_data = self.fields[name] self.field_data.append( - (name.title(), field_data['type'], self.map_to_bool(required['required']), field_data['help_text']) + ( + name.title(), + field_data["type"], + self.map_to_bool(required["required"]), + field_data["help_text"], + ) ) def map_to_bool(self, string_boolean: str) -> bool: @@ -152,11 +175,11 @@ def map_to_bool(self, string_boolean: str) -> bool: All data is loaded from json ("true"/"false"). This method will return a python boolean (True/False). """ - if string_boolean == 'true': + if string_boolean == "true": return True - elif string_boolean == 'false': + elif string_boolean == "false": return False - raise Exception(f'Unsupported boolean value {string_boolean}') + raise Exception(f"Unsupported boolean value {string_boolean}") def save(self) -> None: if self.check_input(): @@ -172,31 +195,34 @@ def build_save_data(self) -> None: self.save_data[name] = _input except ValueError as e: self.throw_alert_message( - title='Error', - message=f'Error saving data. Invalid value provided. \n {e}', + title="Error", + message=f"Error saving data. Invalid value provided. \n {e}", message_type=AlertMessageType.WARN, message_response=AlertMessageResponse.OCE, - message_timeout=self.alert_timeout + message_timeout=self.alert_timeout, ) def write_save_data(self) -> None: save_experiment_field_data(self.save_data, self.save_path, self.file_name) self.throw_alert_message( - title='Success', + title="Success", message=( - f'Data successfully written to: \n\n{self.save_path}/{self.file_name} \n\n\n' - 'Please wait or close this window to start the task!'), + f"Data successfully written to: \n\n{self.save_path}/{self.file_name} \n\n\n" + "Please wait or close this window to start the task!" + ), message_type=AlertMessageType.INFO, message_response=AlertMessageResponse.OCE, message_timeout=self.alert_timeout, ) - def throw_alert_message(self, - title: str, - message: str, - message_type: AlertMessageType = AlertMessageType.INFO, - message_response: AlertMessageResponse = AlertMessageResponse.OTE, - message_timeout: float = 0) -> MessageBox: + def throw_alert_message( + self, + title: str, + message: str, + message_type: AlertMessageType = AlertMessageType.INFO, + message_response: AlertMessageResponse = AlertMessageResponse.OTE, + message_timeout: float = 0, + ) -> MessageBox: """Throw Alert Message.""" msg = MessageBox() @@ -226,13 +252,23 @@ class MainPanel(QWidget): file_name: name of the file to write with collected field_data """ - def __init__(self, title: str, width: int, height: int, experiment_name: str, save_path: str, file_name: str): + def __init__( + self, + title: str, + width: int, + height: int, + experiment_name: str, + save_path: str, + file_name: str, + ): super().__init__() self.title = title self.width = width self.height = height - self.form = ExperimentFieldCollection(title, width, height, experiment_name, save_path, file_name) + self.form = ExperimentFieldCollection( + title, width, height, experiment_name, save_path, file_name + ) self.initUI() def initUI(self): @@ -241,7 +277,9 @@ def initUI(self): self.form_panel = QScrollArea() self.form_panel.setVerticalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOn) - self.form_panel.setHorizontalScrollBarPolicy(Qt.ScrollBarPolicy.ScrollBarAlwaysOff) + self.form_panel.setHorizontalScrollBarPolicy( + Qt.ScrollBarPolicy.ScrollBarAlwaysOff + ) self.form_panel.setWidgetResizable(True) self.form_panel.setFixedWidth(self.width) self.form_panel.setWidget(self.form) @@ -255,7 +293,7 @@ def initUI(self): control_box = QHBoxLayout() control_box.addStretch() - save_button = QPushButton('Save') + save_button = QPushButton("Save") save_button.setFixedWidth(80) save_button.clicked.connect(self.save) control_box.addWidget(save_button) @@ -267,56 +305,67 @@ def save(self): self.close() -def start_app() -> None: - """Start Experiment Field Collection.""" - import argparse - from bcipy.config import DEFAULT_EXPERIMENT_ID, EXPERIMENT_DATA_FILENAME - from bcipy.helpers.validate import validate_experiment, validate_field_data_written - - parser = argparse.ArgumentParser() - - # experiment_name - parser.add_argument('-p', '--path', default='.', - help='Path to save collected field data to in json format') - parser.add_argument('-e', '--experiment', default=DEFAULT_EXPERIMENT_ID, - help='Select a valid experiment to run the task for this user') - parser.add_argument('-f', '--filename', default=EXPERIMENT_DATA_FILENAME, - help='Provide a json filename to write the field data to. Ex, experiment_data.json') - parser.add_argument('-v', '--validate', default=False, - help='Whether or not to validate the experiment before proceeding to data collection.') - - args = parser.parse_args() - - experiment_name = args.experiment - validate = args.validate - +def start_experiment_field_collection_gui( + experiment_name: str, + save_path: str, + file_name: str = EXPERIMENT_DATA_FILENAME, + validate: bool = True, +) -> None: if validate: validate_experiment(experiment_name) - print('Experiment valid!') - - save_path = args.path - file_name = args.filename bcipy_gui = app(sys.argv) - - ex = MainPanel( - title='Experiment Field Collection', + _ = MainPanel( + title="Experiment Field Collection", height=250, width=600, experiment_name=experiment_name, save_path=save_path, - file_name=file_name + file_name=file_name, ) + bcipy_gui.exec() + if validate and not validate_field_data_written(save_path, file_name): + raise Exception(f"Field data not written to {save_path}/{file_name}") - if validate: - if validate_field_data_written(save_path, file_name): - print('Field data successfully written!') - else: - raise Exception(f'Field data not written to {save_path}/{file_name}') +def start_app() -> None: + """Start Experiment Field Collection.""" + import argparse + from bcipy.config import DEFAULT_EXPERIMENT_ID, EXPERIMENT_DATA_FILENAME + + parser = argparse.ArgumentParser() + + # experiment_name + parser.add_argument( + "-p", + "--path", + default=".", + help="Path to save collected field data to in json format", + ) + parser.add_argument( + "-e", + "--experiment", + default=DEFAULT_EXPERIMENT_ID, + help="Select a valid experiment to run the task for this user", + ) + parser.add_argument( + "-f", + "--filename", + default=EXPERIMENT_DATA_FILENAME, + help="Provide a json filename to write the field data to. Ex, experiment_data.json", + ) + parser.add_argument( + "-v", + "--validate", + default=False, + help="Whether or not to validate the experiment before proceeding to data collection.", + ) + + args = parser.parse_args() + start_experiment_field_collection_gui(args.experiment, args.path, args.filename, args.validate) sys.exit() -if __name__ == '__main__': +if __name__ == "__main__": start_app() diff --git a/bcipy/gui/experiments/ExperimentRegistry.py b/bcipy/gui/experiments/ExperimentRegistry.py index 365675ad5..b1bd74de5 100644 --- a/bcipy/gui/experiments/ExperimentRegistry.py +++ b/bcipy/gui/experiments/ExperimentRegistry.py @@ -1,468 +1,331 @@ -import sys -import subprocess - -from bcipy.gui.main import BCIGui, app, AlertMessageType, AlertMessageResponse, ScrollableFrame, LineItems - -from bcipy.config import BCIPY_ROOT, DEFAULT_EXPERIMENT_PATH, EXPERIMENT_FILENAME -from bcipy.helpers.load import load_experiments, load_fields +from typing import List, Optional +from PyQt6.QtWidgets import ( + QComboBox, + QVBoxLayout, + QHBoxLayout, + QLabel, + QLineEdit, + QPushButton, + QScrollArea, +) +from bcipy.gui.bciui import BCIUI, DynamicItem, DynamicList, SmallButton, run_bciui +from bcipy.helpers.load import load_fields, load_experiments from bcipy.helpers.save import save_experiment_data +from bcipy.config import ( + DEFAULT_ENCODING, + DEFAULT_EXPERIMENT_PATH, + DEFAULT_FIELD_PATH, + EXPERIMENT_FILENAME, + FIELD_FILENAME, + BCIPY_ROOT, +) +from bcipy.task.registry import TaskRegistry +import subprocess +from bcipy.task.orchestrator.protocol import serialize_protocol +import json -class ExperimentRegistry(BCIGui): - """Experiment Registry. - - User interface for creating new experiments for use in BCInterface.py. - """ - - padding = 100 - btn_height = 50 - default_text = '...' - alert_title = 'Experiment Registry Alert' - alert_timeout = 10 - experiment_fields = [] - - def __init__(self, *args, **kwargs): - super(ExperimentRegistry, self).__init__(*args, **kwargs) - - # Structure of an experiment: - # { name: { fields : {name: '', required: bool, anonymize: bool}, summary: '' } } - self.update_experiment_data() - - # These are set in the build_inputs and represent text inputs from the user - self.name_input = None - self.summary_input = None - self.field_input = None - self.panel = None - self.line_items = None - - # fields is for display of registered fields - self.fields = [] - self.registered_fields = load_fields() - self.name = None - self.summary = None - - # for registered fields - self.build_scroll_area() - - self.show_gui() - self.update_field_list() - - def build_scroll_area(self) -> None: - """Build Scroll Area. +class ExperimentRegistry(BCIUI): - Appends a scrollable area at the bottom of the UI for management of registered fields via LineItems. - """ - line_widget = LineItems([], self.width) - self.panel = ScrollableFrame(200, self.width, background_color='white', widget=line_widget) - self.add_widget(self.panel) + task_registry: TaskRegistry - def refresh_field_panel(self) -> None: - """Refresh Field Panel. + def __init__(self): + super().__init__("Experiment Registry", 600, 700) + self.task_registry = TaskRegistry() + self.setProperty("class", "experiment-registry") - Reconstruct the line items from the registered fields and refresh the scrollable panel of registered fields. + def format_experiment_combobox( + self, + label_text: str, + combobox: QComboBox, + buttons: Optional[List[QPushButton]], + class_name: str = 'default', + ) -> QVBoxLayout: """ - self.build_line_items_from_fields() - self.panel.refresh(self.line_items) + Create a formatted widget for a the experiment comboboxes with optional buttons. - def toggle_required_field(self) -> None: - """Toggle Required Field. + PARAMETERS + ---------- + :param: label_text: string text to display above the combobox. + :param: combobox: the combobox. + :param: buttons: list of buttons to add to right side of the combobox. - *Button Action* - - Using the field_name retrieved from the button (get_id), find the field in self.experiment_fields and toggle - the required field ('true' or 'false'). - """ - field_name = self.window.sender().get_id() - for field in self.experiment_fields: - if field_name in field: - required = field[field_name]['required'] - if required == 'false': - field[field_name]['required'] = 'true' - else: - field[field_name]['required'] = 'false' - self.refresh_field_panel() - - def toggle_anonymize_field(self) -> None: - """Toggle Anonymize Field. - - *Button Action* - - Using the field_name retrieved from the button (get_id), find the field in self.experiment_fields and toggle - the anonymize field ('true' or 'false'). + Returns + ------- + A QVBoxLayout with the label, combobox, and buttons. """ - field_name = self.window.sender().get_id() - for field in self.experiment_fields: - if field_name in field: - anonymize = field[field_name]['anonymize'] - if anonymize == 'false': - field[field_name]['anonymize'] = 'true' - else: - field[field_name]['anonymize'] = 'false' - self.refresh_field_panel() - - def remove_field(self) -> None: - """Remove Field. - - *Button Action* - - Using the field_name retrieved from the button (get_id), find the field in self.experiment_fields and remove it - from the list. + label = QLabel(label_text) + area = QVBoxLayout() + input_area = QHBoxLayout() + input_area.setContentsMargins(15, 0, 0, 15) + area.addWidget(label) + combobox.setProperty("class", class_name) + input_area.addWidget(combobox, 1) + if buttons: + for button in buttons: + input_area.addWidget(button) + area.addLayout(input_area) + return area + + def make_task_entry(self, name: str) -> DynamicItem: """ - field_name = self.window.sender().get_id() - - idx = 0 - remove = None - for field in self.experiment_fields: - if field_name in field: - remove = idx - break - idx += 1 - - self.experiment_fields.pop(remove) - self.refresh_field_panel() + Create a formatted widget for a task entry. - def build_line_items_from_fields(self) -> None: - """Build Line Items From Fields. + PARAMETERS + ---------- + :param: name: string name of the task that will be displayed. - Loop over the registered experiment fields and create LineItems, which can by used to toggle the required - field, anonymization, or remove as a registered experiment field. + Returns + ------- + A DynamicItem widget with the 'task_name' property set as it's data. """ - items = [] - for field in self.experiment_fields: - # experiment fields is a list of dicts, here we loop over the dict to get - # the field_name, anonymization, and requirement - for field_name, required in field.items(): - - # Set the button text and colors, based on the requirement and anonymization - if required['required'] == 'false': - required_button_label = 'Optional' - required_button_color = 'black' - required_button_text_color = 'white' - else: - required_button_label = 'Required' - required_button_color = 'green' - required_button_text_color = 'white' - - if required['anonymize'] == 'false': - anon_button_label = 'Onymous' - anon_button_color = 'black' - anon_button_text_color = 'white' - else: - anon_button_label = 'Anonymous' - anon_button_color = 'green' - anon_button_text_color = 'white' - - # Construct the item to turn into a LineItem, we set the id as field_name to use later via the action - item = { - field_name: { - required_button_label: { - 'action': self.toggle_required_field, - 'color': required_button_color, - 'textColor': required_button_text_color, - 'id': field_name - }, - anon_button_label: { - 'action': self.toggle_anonymize_field, - 'color': anon_button_color, - 'textColor': anon_button_text_color, - 'id': field_name - }, - 'Remove': { - 'action': self.remove_field, - 'color': 'red', - 'textColor': 'white', - 'id': field_name - } - } - } - items.append(item) - - # finally, set the new line items for rendering - self.line_items = LineItems(items, self.width) - - def build_text(self) -> None: - """Build Text. - - Build all static text needed for the UI. - Positions are relative to the height / width of the UI defined in start_app. - """ - text_x = 25 - text_y = 70 - font_size = 18 - self.add_static_textbox( - text='Create BciPy Experiment', - position=[self.width / 2 - self.padding - 50, 0], - size=[300, 100], - background_color='black', - text_color='white', - font_size=22 - ) - self.add_static_textbox( - text='Name', - position=[text_x, text_y], - size=[200, 50], - background_color='black', - text_color='white', - font_size=font_size) - text_y += self.padding - self.add_static_textbox( - text='Summary', - position=[text_x, text_y], - size=[300, 50], - background_color='black', - text_color='white', - font_size=font_size) - text_y += self.padding - self.add_static_textbox( - text='Fields', - position=[text_x, text_y], - size=[300, 50], - background_color='black', - text_color='white', - font_size=font_size) - text_y += self.padding + 45 - self.add_static_textbox( - text='Registered fields *click to toggle required field*', - position=[text_x, text_y], - size=[300, 50], - background_color='black', - text_color='white', - font_size=14) - - def build_inputs(self) -> None: - """Build Inputs. - - Build all text entry inputs for the UI. - """ - input_x = 50 - input_y = 120 - input_size = [280, 25] - self.name_input = self.add_combobox( - position=[input_x, input_y], - size=input_size, - items=[self.default_text], - editable=True, - background_color='white', - text_color='black') - - input_y += self.padding - self.summary_input = self.add_combobox( - position=[input_x, input_y], - size=input_size, - items=[self.default_text], - editable=True, - background_color='white', - text_color='black') - - input_y += self.padding - self.field_input = self.add_combobox( - position=[input_x, input_y], - size=input_size, - items=self.fields, - editable=False, - background_color='white', - text_color='black') - - def build_buttons(self): - """Build Buttons. - - Build all buttons necessary for the UI. Define their action on click using the named argument action. - """ - btn_create_x = self.width - self.padding - 10 - btn_create_y = self.height - self.padding - 200 - size = 150 - self.add_button( - message='Create Experiment', position=[btn_create_x - (size / 2), btn_create_y], - size=[size, self.btn_height], - background_color='green', - action=self.create_experiment, - text_color='white') - - btn_field_x = (self.width / 2) + 150 - btn_field_y = 310 - # create field - self.add_button( - message='+', - position=[btn_field_x, btn_field_y], - size=[40, self.btn_height - 10], - background_color='green', - action=self.create_field, - text_color='white' + layout = QHBoxLayout() + label = QLabel(name) + label.setProperty("class", "task-label") + layout.addWidget(label) + widget = DynamicItem() + + # The indices will have to be updated to reflect the actual index we want to move to + move_up_button = SmallButton(" ▲ ") + move_up_button.clicked.connect( + lambda: self.protocol_contents.move_item( + widget, max(self.protocol_contents.index(widget) - 1, 0) + ) ) - - # add field - self.add_button( - message='Register', - position=[btn_field_x - 75, btn_field_y], - size=[60, self.btn_height - 10], - background_color='grey', - action=self.add_field, - text_color='white' + move_down_button = SmallButton(" ▼ ") + move_down_button.clicked.connect( + lambda: self.protocol_contents.move_item( + widget, + min( + self.protocol_contents.index(widget) + 1, + len(self.protocol_contents) - 1, + ), + ) ) - - def create_experiment(self) -> None: - """Create Experiment. - - After inputing all required fields, verified by check_input, add it to the experiment list and save it. + layout.addWidget(move_up_button) + layout.addWidget(move_down_button) + + remove_button = SmallButton("Remove") + remove_button.setProperty("class", "remove-button") + remove_button.clicked.connect( + lambda: layout.deleteLater() + ) # This may not be needed + remove_button.clicked.connect(lambda: widget.remove()) + layout.addWidget(remove_button) + + widget.data = {"task_name": name} + widget.setLayout(layout) + return widget + + def make_field_entry(self, name: str) -> DynamicItem: """ - if self.check_input(): - self.add_experiment() - self.save_experiments() - self.throw_alert_message( - title=self.alert_title, - message='Experiment saved successfully! Please exit window or create another experiment!', - message_type=AlertMessageType.INFO, - message_response=AlertMessageResponse.OTE, - message_timeout=self.alert_timeout - ) - self.update_experiment_data() + Create a formatted widget for a field entry. - def update_experiment_data(self): - """Update Experiment Data. + PARAMETERS + ---------- + :param: name: string name of the field that will be displayed. - Fetches the experiments and extracts the registered names. + Returns + ------- + A DynamicItem widget with the 'field_name', 'anonymous', and 'optional' properties set as it's data. """ - self.experiments = load_experiments() - self.experiment_names = self.experiments.keys() - - def add_experiment(self) -> None: - """Add Experiment: + layout = QHBoxLayout() + label = QLabel(name) + label.setProperty("class", "task-label") + layout.addWidget(label) + widget = DynamicItem() + + remove_button = SmallButton("Remove") + remove_button.setStyleSheet("background-color: red;") + remove_button.clicked.connect(lambda: layout.deleteLater()) + + anonymous_button = SmallButton("Anonymous") + onymous_button = SmallButton("Onymous") + BCIUI.make_toggle( + anonymous_button, + onymous_button, + on_action=lambda: widget.data.update({"anonymous": True}), + off_action=lambda: widget.data.update({"anonymous": False}), + ) + layout.addWidget(anonymous_button) + layout.addWidget(onymous_button) + anonymous_button.setStyleSheet("background-color: black;") + + optional_button = SmallButton("Optional") + required_button = SmallButton("Required") + BCIUI.make_toggle( + optional_button, + required_button, + on_action=lambda: widget.data.update({"optional": True}), + off_action=lambda: widget.data.update({"optional": False}), + ) + layout.addWidget(optional_button) + layout.addWidget(required_button) + + layout.addWidget(remove_button) + widget.data = {"field_name": name, "anonymous": True, "optional": True} + remove_button.clicked.connect(lambda: widget.remove()) + widget.setLayout(layout) + return widget + + def load_fields(path: str = f"{DEFAULT_FIELD_PATH}/{FIELD_FILENAME}") -> dict: + """Load Fields. + + PARAMETERS + ---------- + :param: path: string path to the fields file. + + Returns + ------- + A dictionary of fields, with the following format: + { + "field_name": { + "help_text": "", + "type": "" + } - Add a new experiment to the dict of experiments. It follows the format: - { name: { fields : {name: '', required: bool, anonymize: bool}, summary: '' } } """ - self.experiments[self.name] = { - 'fields': self.experiment_fields, - 'summary': self.summary + with open(path, "r", encoding=DEFAULT_ENCODING) as json_file: + return json.load(json_file) + + def create_experiment(self): + existing_experiments = load_experiments() + experiment_name = self.experiment_name_input.text() + if not experiment_name: + self.show_alert("Please specify an experiment name") + return + experiment_summary = self.experiment_summary_input.text() + if not experiment_summary: + self.show_alert("Please specify an experiment summary") + return + fields = self.fields_content.list() + + field_list = [ + { + field["field_name"]: { + "anonymize": field["anonymous"], + "required": not field["optional"], + } + } + for field in fields + ] + task_names = self.protocol_contents.list_property("task_name") + task_objects = [self.task_registry.get(task_name) for task_name in task_names] + protocol = serialize_protocol(task_objects) + + existing_experiments[experiment_name] = { + "fields": field_list, + "summary": experiment_summary, + "protocol": protocol, } + save_experiment_data( + existing_experiments, + load_fields(), + DEFAULT_EXPERIMENT_PATH, + EXPERIMENT_FILENAME, + ) + self.show_alert("created experiment") - def save_experiments(self) -> None: - """Save Experiment. - - Save the experiments registered to the correct path as pulled from system_utils. - """ - # add fields to the experiment - save_experiment_data(self.experiments, self.registered_fields, DEFAULT_EXPERIMENT_PATH, EXPERIMENT_FILENAME) - - def create_field(self) -> None: + def create_experiment_field(self) -> None: """Create Field. Launch to FieldRegistry to create a new field for experiments. """ subprocess.call( - f'python {BCIPY_ROOT}/gui/experiments/FieldRegistry.py', - shell=True) + f"python {BCIPY_ROOT}/gui/experiments/FieldRegistry.py", shell=True + ) self.update_field_list() - def add_field(self) -> None: - """Add Field. + def update_field_list(self): + self.field_input.clear() + self.field_input.addItems(load_fields()) + + def app(self): + # Add form fields + self.center_content_vertically = True + header = QLabel("Experiment Registry") + header.setStyleSheet("font-size: 24px") + self.contents.addLayout(BCIUI.centered(header)) + form_area = QVBoxLayout() + form_area.setContentsMargins(30, 0, 30, 0) + self.experiment_name_input = QLineEdit() + experiment_name_box = self.format_experiment_combobox( + "Name", self.experiment_name_input, None + ) + form_area.addLayout(experiment_name_box) - Functionality to add fields to the newly created experiment. It will ensure no duplicates are addded. - """ - # get the current field value and compute a list of field names already added - field = self.field_input.currentText() - registered_fields = [name for field in self.experiment_fields for name in field.keys()] - - # if the field selected is already registered throw an alert to the user - if field in registered_fields: - return self.throw_alert_message( - title=self.alert_title, - message=f'{field} already registered with this experiment!', - message_type=AlertMessageType.INFO, - message_response=AlertMessageResponse.OTE, - message_timeout=self.alert_timeout, + self.experiment_summary_input = QLineEdit() + experiment_summary_box = self.format_experiment_combobox( + "Summary", self.experiment_summary_input, None + ) + form_area.addLayout(experiment_summary_box) + + def add_field(): + if self.field_input.currentText() in self.fields_content.list_property( + "field_name" + ): + self.show_alert("Field already added") + return + self.fields_content.add_item( + self.make_field_entry(self.field_input.currentText()) ) - # else add the field! - self.experiment_fields.append( - { - field: - { - 'required': 'false', - 'anonymize': 'true' - } - } + def add_task(): + self.protocol_contents.add_item( + self.make_task_entry(self.experiment_protocol_input.currentText()) + ) + + self.experiment_protocol_input = QComboBox() + self.experiment_protocol_input.addItems(self.task_registry.list()) + add_task_button = QPushButton("Add") + add_task_button.clicked.connect(add_task) + experiment_protocol_box = self.format_experiment_combobox( + "Protocol", + self.experiment_protocol_input, + [add_task_button], + "protocol", + ) + form_area.addLayout(experiment_protocol_box) + + self.field_input = QComboBox() + self.field_input.addItems(load_fields()) + add_field_button = QPushButton("Add") + new_field_button = QPushButton("New") + new_field_button.clicked.connect(self.create_experiment_field) + form_area.addLayout( + self.format_experiment_combobox( + "Fields", + self.field_input, + [add_field_button, new_field_button], + "fields", + ) ) - self.refresh_field_panel() + self.contents.addLayout(form_area) - def update_field_list(self) -> None: - """Updates the field_input combo box with a list of fields. """ + scroll_area_layout = QHBoxLayout() - self.field_input.clear() - self.field_input.addItem(ExperimentRegistry.default_text) - self.registered_fields = load_fields() - self.fields = [item for item in self.registered_fields] - self.field_input.addItems(self.fields) + self.fields_content = DynamicList() + fields_scroll_area = BCIUI.make_list_scroll_area(self.fields_content) + label = QLabel("Fields") + label.setStyleSheet("color: black;") + scroll_area_layout.addWidget(fields_scroll_area) - def build_assets(self) -> None: - """Build Assets. + protocol_scroll_area = QScrollArea() + self.protocol_contents = DynamicList() + protocol_scroll_area = BCIUI.make_list_scroll_area(self.protocol_contents) + label = QLabel("Protocol") + label.setStyleSheet("color: black;") + scroll_area_layout.addWidget(protocol_scroll_area) - Define the assets to build in the UI. - """ - self.build_inputs() - self.build_text() - self.build_buttons() + self.contents.addLayout(scroll_area_layout) - def check_input(self) -> bool: - """Check Input. + add_field_button.clicked.connect(add_field) + create_experiment_button = QPushButton("Create experiment") + create_experiment_button.clicked.connect(self.create_experiment) + self.contents.addWidget(create_experiment_button) - Checks to make sure user has input all required fields. Currently, only name and summary are required. - """ - self.name = self.name_input.currentText() - self.summary = self.summary_input.currentText() - try: - if self.name == ExperimentRegistry.default_text: - self.throw_alert_message( - title=self.alert_title, - message='Please add an Experiment Name!', - message_type=AlertMessageType.WARN, - message_response=AlertMessageResponse.OTE, - message_timeout=self.alert_timeout) - return False - if self.name in self.experiment_names: - self.throw_alert_message( - title=self.alert_title, - message=( - 'Experiment name already registered. \n' - 'Please use a unique Experiment name! \n' - f'Registed names: {self.experiment_names}' - ), - message_type=AlertMessageType.WARN, - message_response=AlertMessageResponse.OTE, - message_timeout=self.alert_timeout) - return False - if self.summary == ExperimentRegistry.default_text: - self.throw_alert_message( - title=self.alert_title, - message='Please add an Experiment Summary!', - message_type=AlertMessageType.WARN, - message_response=AlertMessageResponse.OTE, - message_timeout=self.alert_timeout) - return False - except Exception as e: - self.throw_alert_message( - title=self.alert_title, - message=f'Error, {e}', - message_type=AlertMessageType.CRIT, - message_response=AlertMessageResponse.OTE, - message_timeout=self.alert_timeout) - return False - return True - - -def start_app() -> None: - """Start Experiment Registry.""" - bcipy_gui = app(sys.argv) - ex = ExperimentRegistry( - title='Experiment Registry', - height=700, - width=600, - background_color='black') - - sys.exit(bcipy_gui.exec()) - - -if __name__ == '__main__': - start_app() + +if __name__ == "__main__": + run_bciui(ExperimentRegistry) diff --git a/bcipy/gui/intertask_gui.py b/bcipy/gui/intertask_gui.py new file mode 100644 index 000000000..87e1a8e47 --- /dev/null +++ b/bcipy/gui/intertask_gui.py @@ -0,0 +1,86 @@ +from typing import Callable, List + +from PyQt6.QtWidgets import ( + QLabel, + QHBoxLayout, + QPushButton, + QProgressBar, + QApplication +) +from bcipy.gui.bciui import BCIUI, run_bciui +from bcipy.config import SESSION_LOG_FILENAME +import logging + +logger = logging.getLogger(SESSION_LOG_FILENAME) + + +class IntertaskGUI(BCIUI): + + action_name = "IntertaskAction" + + def __init__( + self, + next_task_index: int, + tasks: List[str], + exit_callback: Callable, + ): + self.tasks = tasks + self.current_task_index = next_task_index + self.next_task_name = tasks[self.current_task_index] + self.total_tasks = len(tasks) + self.task_progress = next_task_index + self.callback = exit_callback + super().__init__("Progress", 800, 150) + self.setProperty("class", "inter-task") + + def app(self): + self.contents.addLayout(BCIUI.centered(QLabel("Experiment Progress"))) + + progress_container = QHBoxLayout() + progress_container.addWidget( + QLabel(f"({self.task_progress}/{self.total_tasks})") + ) + self.progress = QProgressBar() + self.progress.setValue(int(self.task_progress / self.total_tasks * 100)) + self.progress.setTextVisible(False) + progress_container.addWidget(self.progress) + self.contents.addLayout(progress_container) + + next_info = QHBoxLayout() + next_info.addWidget(QLabel("Next Task: ")) + next_task = QLabel(self.next_task_name) + next_task.setStyleSheet("font-weight: bold; color: green;") + next_info.addWidget(next_task) + self.contents.addLayout(next_info) + + self.contents.addStretch(1) + self.next_button = QPushButton("Next") + self.stop_button = QPushButton("Stop") + self.stop_button.setStyleSheet("background-color: red") + buttons_layout = QHBoxLayout() + buttons_layout.addWidget(self.stop_button) + buttons_layout.addWidget(self.next_button) + self.contents.addLayout(buttons_layout) + + self.next_button.clicked.connect(self.next) + self.stop_button.clicked.connect(self.stop_tasks) + + def stop_tasks(self): + # This should exit Task executions + logger.info(f"Stopping Tasks... user requested. Using callback: {self.callback}") + self.callback() + self.quit() + logger.info("Tasks Stopped") + + def next(self): + logger.info(f"Next Task=[{self.next_task_name}] requested") + self.quit() + + def quit(self): + QApplication.instance().quit() + + +if __name__ == "__main__": + tasks = ["RSVP Calibration", "IntertaskAction", "Matrix Calibration", "IntertaskAction"] + + run_bciui(IntertaskGUI, tasks=tasks, next_task_index=1, exit_callback=lambda: print("Stopping orchestrator")) diff --git a/bcipy/gui/main.py b/bcipy/gui/main.py index 2c0d00923..9d032dfa6 100644 --- a/bcipy/gui/main.py +++ b/bcipy/gui/main.py @@ -17,7 +17,7 @@ from bcipy.helpers.parameters import parse_range -def font(size: int = 14, font_family: str = 'Helvetica') -> QFont: +def font(size: int = 16, font_family: str = 'Helvetica') -> QFont: """Create a Font object with the given parameters.""" return QFont(font_family, size, weight=0) @@ -51,7 +51,7 @@ def contains_special_characters(string: str, def static_text_control(parent, label: str, color: str = 'black', - size: int = 14, + size: int = 16, font_family: str = 'Helvetica') -> QLabel: """Creates a static text control with the given font parameters. Useful for creating labels and help components.""" @@ -224,6 +224,7 @@ def __init__(self, value: str, help_tip: Optional[str] = None, options: Optional[List[str]] = None, + editable: bool = True, help_size: int = 12, help_color: str = 'darkgray', should_display: bool = True): @@ -236,6 +237,7 @@ def __init__(self, self.label_widget = self.init_label() self.help_tip_widget = self.init_help(help_size, help_color) + self.editable_widget = self.init_editable(editable) self.control = self.init_control(value) self.control.installEventFilter(self) self.init_layout() @@ -251,7 +253,7 @@ def eventFilter(self, source, event): def init_label(self) -> QWidget: """Initialize the label widget.""" - return static_text_control(None, label=self.label) + return static_text_control(None, label=self.label, size=16) def init_help(self, font_size: int, color: str) -> QWidget: """Initialize the help text widget.""" @@ -271,6 +273,13 @@ def init_control(self, value) -> QWidget: # Default is a text input return QLineEdit(value) + def init_editable(self, value: bool) -> QWidget: + "Override. Another checkbox is needed for editable" + editable_checkbox = QCheckBox("Editable") + editable_checkbox.setChecked(value) + editable_checkbox.setFont(font(size=12)) + return editable_checkbox + def init_layout(self): """Initialize the layout by adding the label, help, and control widgets.""" self.vbox = QVBoxLayout() @@ -278,15 +287,35 @@ def init_layout(self): self.vbox.addWidget(self.label_widget) if self.help_tip_widget: self.vbox.addWidget(self.help_tip_widget) + if self.editable_widget: + self.vbox.addWidget(self.editable_widget) self.vbox.addWidget(self.control) + + self.vbox.addWidget(self.separator()) self.setLayout(self.vbox) + def separator(self): + """Creates a separator line.""" + line = QLabel() + line.setFixedHeight(1) + line.setStyleSheet("background-color: grey;") + return line + def value(self) -> str: """Returns the value associated with the form input.""" if self.control: return self.control.text() return None + def is_editable(self) -> bool: + """Returns whether the input is editable.""" + return self.editable_widget.isChecked() + + @property + def editable(self) -> bool: + """Returns whether the input is editable.""" + return True if self.editable_widget.isChecked() else False + def cast_value(self) -> Any: """Returns the value associated with the form input, cast to the correct type. @@ -417,19 +446,11 @@ class BoolInput(FormInput): def __init__(self, **kwargs): super(BoolInput, self).__init__(**kwargs) - def init_label(self) -> QWidget: - """Override. Checkboxes do not have a separate label.""" - return None - - def init_help(self, font_size: int, color: str) -> QWidget: - """Override. Checkboxes do not display help.""" - return None - def init_control(self, value): """Override to create a checkbox.""" - ctl = QCheckBox(self.label) + ctl = QCheckBox(f'Enable {self.label}') ctl.setChecked(value == 'true') - ctl.setFont(font()) + ctl.setFont(font(size=14)) return ctl def value(self) -> str: @@ -440,7 +461,7 @@ class RangeInput(FormInput): """FormInput to select a range of values (low, high). Serializes to 'low_value:high_value'. Appropriate boundaries are determined - from the starting value and list of recommended_values if provided. + from the starting value and list of recommended if provided. """ def init_control(self, value) -> QWidget: @@ -450,7 +471,7 @@ def init_control(self, value) -> QWidget: --------- value - initial value """ - return RangeWidget(value, self.options) + return RangeWidget(value, self.options, size=14) class SelectionInput(FormInput): @@ -542,10 +563,14 @@ def init_layout(self) -> None: self.vbox.addWidget(self.label_widget) if self.help_tip_widget: self.vbox.addWidget(self.help_tip_widget) + if self.editable_widget: + self.vbox.addWidget(self.editable_widget) + hbox = QHBoxLayout() hbox.addWidget(self.control) hbox.addWidget(self.button) self.vbox.addLayout(hbox) + self.vbox.addWidget(self.separator()) self.setLayout(self.vbox) def widgets(self) -> List[QWidget]: @@ -583,7 +608,8 @@ def __init__(self, value: Tuple[int, int], options: Optional[List[str]] = None, label_low: str = "Low:", - label_high="High:"): + label_high="High:", + size=14): super(RangeWidget, self).__init__() self.low, self.high = parse_range(value) @@ -602,10 +628,10 @@ def __init__(self, self.high_input = self.create_input(self.high) hbox = QHBoxLayout() - hbox.addWidget(static_text_control(None, label=label_low)) + hbox.addWidget(static_text_control(None, label=label_low, size=size)) hbox.addWidget(self.low_input) - hbox.addWidget(static_text_control(None, label=label_high)) + hbox.addWidget(static_text_control(None, label=label_high, size=size)) hbox.addWidget(self.high_input) self.setLayout(hbox) @@ -668,7 +694,7 @@ class SearchInput(QWidget): contents of the text box. """ - def __init__(self, on_search, font_size: int = 10): + def __init__(self, on_search, font_size: int = 12): super(SearchInput, self).__init__() self.on_search = on_search @@ -907,7 +933,7 @@ def add_static_textbox(self, text_color: str = 'default', size: Optional[list] = None, font_family='Times', - font_size=12, + font_size=14, wrap_text=False) -> QLabel: """Add Static Text.""" @@ -971,7 +997,8 @@ def __init__(self, height: int, width: int, background_color: str = 'black', - widget: Optional[QWidget] = None): + widget: Optional[QWidget] = None, + title: Optional[str] = None): super().__init__() self.height = height @@ -995,6 +1022,15 @@ def __init__(self, self.widget = widget self.frame.setWidget(widget) + # If there is a title, add it to the top of the frame + if title: + title_label = QLabel(title) + title_label.setStyleSheet( + 'background-color: black; color: white;') + title_label.setAlignment(Qt.AlignmentFlag.AlignCenter) + title_label.setFont(font(16)) + self.vbox.addWidget(title_label) + # add the frame and set the layout self.vbox.addWidget(self.frame) self.setLayout(self.vbox) @@ -1082,7 +1118,11 @@ def app(args) -> QApplication: Passes args from main and initializes the app """ - return QApplication(args) + + bci_app = QApplication(args).instance() + if not bci_app: + return QApplication(args) + return bci_app def start_app() -> None: @@ -1092,24 +1132,7 @@ def start_app() -> None: height=650, width=650, background_color='white') - - # ex.get_filename_dialog() - # ex.add_button(message='Test Button', position=[200, 300], size=[100, 100], id=1) - # ex.add_image(path='../static/images/gui/bci_cas_logo.png', position=[50, 50], size=200) - # ex.add_static_textbox( - # text='Test static text', - # background_color='black', - # text_color='white', - # position=[100, 20], - # wrap_text=True) - # ex.add_combobox(position=[100, 100], size=[100, 100], items=['first', 'second', 'third'], editable=True) - # ex.add_text_input(position=[100, 100], size=[100, 100]) ex.show_gui() - ex.throw_alert_message(title='title', - message='test', - message_response=AlertMessageResponse.OCE, - message_timeout=5) - sys.exit(bcipy_gui.exec()) diff --git a/bcipy/gui/parameters/params_form.py b/bcipy/gui/parameters/params_form.py index 0e6a4510a..602d6a816 100644 --- a/bcipy/gui/parameters/params_form.py +++ b/bcipy/gui/parameters/params_form.py @@ -80,13 +80,14 @@ def parameter_input(self, param: Dict[str, str]) -> FormInput: 'directorypath': DirectoryInput, 'range': RangeInput } - has_options = isinstance(param['recommended_values'], list) + has_options = isinstance(param['recommended'], list) form_input = type_inputs.get( param['type'], SelectionInput if has_options else TextInput) - return form_input(label=param['readableName'], + return form_input(label=param['name'], value=param['value'], help_tip=param['helpTip'], - options=param['recommended_values'], + options=param['recommended'], + editable=bool(param['editable']), help_size=self.help_size, help_color=self.help_color, should_display=bool(param['section'])) @@ -129,8 +130,12 @@ def update_parameters(self): for param_name, form_input in self.controls.items(): param = self.params[param_name] value = form_input.value() + editable = form_input.editable if value != param['value']: self.params[param_name]['value'] = value + if editable != param['editable']: + editable = True if editable == "true" or editable is True else False + self.params[param_name]['editable'] = editable def clear_layout(layout): @@ -192,7 +197,7 @@ def _init_changes(self): lbl = static_text_control( None, - label=f"* {param['readableName']}: {param['value']}", + label=f"* {param['name']}: {param['value']}", size=13, color="darkgreen") @@ -418,7 +423,7 @@ def on_save_as(self): self.repaint() -def main(json_file, title='BCI Parameters', size=(450, 550)) -> str: +def main(json_file, title='BCI Parameters', size=(750, 800)) -> str: """Set up the GUI components and start the main loop.""" app = QApplication(sys.argv) panel = MainPanel(json_file, title, size) diff --git a/bcipy/gui/viewer/data_source/file_streamer.py b/bcipy/gui/viewer/data_source/file_streamer.py index dd725b98a..ff6d33c7d 100644 --- a/bcipy/gui/viewer/data_source/file_streamer.py +++ b/bcipy/gui/viewer/data_source/file_streamer.py @@ -2,8 +2,10 @@ import logging import time from bcipy.acquisition.util import StoppableThread +from bcipy.config import SESSION_LOG_FILENAME from bcipy.helpers.raw_data import RawDataReader -log = logging.getLogger(__name__) + +log = logging.getLogger(SESSION_LOG_FILENAME) class FileStreamer(StoppableThread): diff --git a/bcipy/helpers/README.md b/bcipy/helpers/README.md index 1ab392cfd..bca1658a5 100644 --- a/bcipy/helpers/README.md +++ b/bcipy/helpers/README.md @@ -14,9 +14,11 @@ Modules necessary for BciPy system operation. These range from system utilities - `load`: methods for loading most BciPy data. For loading of triggers, see triggers.py - `parameters`: module for functionality related to system configuration via the parameters.json file - `raw_data`: functionality for reading and writing raw signal data +- `report`: methods for generating BciPy PDF reports - `save`: methods for saving BciPy data in supported formats. For saving of triggers, see triggers.py - `session`: methods for managing and parsing session.json data - `stimuli`: methods for generating stimuli and inquiries for presentation +- `symbols`: methods for working with symbols and symbol lists. Ex. Alphabet, QWERTY, etc. - `system_utils`: utilities for extracting git version, system information and handling of logging - `task`: common task methods and utilities, including Trial and InquiryReshaper. - `triggers`: methods and data classes defining BciPy internal triggering diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index 0a92c9b7a..05c1d1565 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -11,21 +11,20 @@ discover_device_spec) from bcipy.acquisition.devices import (DeviceSpec, DeviceStatus, preconfigured_device, with_content_type) -from bcipy.config import BCIPY_ROOT +from bcipy.config import BCIPY_ROOT, RAW_DATA_FILENAME, SESSION_LOG_FILENAME from bcipy.config import DEFAULT_DEVICE_SPEC_FILENAME as spec_name -from bcipy.config import RAW_DATA_FILENAME from bcipy.helpers.save import save_device_specs -log = logging.getLogger(__name__) +logger = logging.getLogger(SESSION_LOG_FILENAME) -def init_eeg_acquisition( +def init_acquisition( parameters: dict, save_folder: str, server: bool = False) -> Tuple[ClientManager, List[LslDataServer]]: """Initialize EEG Acquisition. - Initializes a client that connects with the EEG data source and begins + Initializes a client that connects with ta data source and begins data collection. Parameters @@ -56,7 +55,7 @@ def init_eeg_acquisition( if server: server_device_spec = server_spec(content_type, device_name) - log.info( + logger.info( f"Generating mock device data for {server_device_spec.name}") dataserver = LslDataServer(server_device_spec) servers.append(dataserver) @@ -68,8 +67,7 @@ def init_eeg_acquisition( device_spec.status = status raw_data_name = raw_data_filename(device_spec) - client = init_lsl_client(parameters, device_spec, save_folder, - raw_data_name) + client = init_lsl_client(parameters, device_spec, save_folder, raw_data_name) manager.add_client(client) manager.start_acquisition() @@ -187,7 +185,7 @@ def init_lsl_client(parameters: dict, """Initialize a client that acquires data from LabStreamingLayer.""" data_buffer_seconds = round(max_inquiry_duration(parameters)) - log.info( + logger.info( f"Setting an acquisition buffer for {device_spec.name} of {data_buffer_seconds} seconds" ) return LslAcquisitionClient(max_buffer_len=data_buffer_seconds, diff --git a/bcipy/helpers/convert.py b/bcipy/helpers/convert.py index 1b365f9ea..07c6ec34f 100644 --- a/bcipy/helpers/convert.py +++ b/bcipy/helpers/convert.py @@ -14,13 +14,13 @@ from bcipy.acquisition.devices import preconfigured_device from bcipy.config import (DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, - TRIGGER_FILENAME) + TRIGGER_FILENAME, SESSION_LOG_FILENAME) from bcipy.helpers.load import load_json_parameters, load_raw_data from bcipy.helpers.raw_data import RawData from bcipy.helpers.triggers import trigger_decoder, trigger_durations from bcipy.signal.process import Composition, get_default_transform -logger = logging.getLogger(__name__) +logger = logging.getLogger(SESSION_LOG_FILENAME) FILE_LENGTH_LIMIT = 150 diff --git a/bcipy/helpers/copy_phrase_wrapper.py b/bcipy/helpers/copy_phrase_wrapper.py index d779fc463..aa546948e 100644 --- a/bcipy/helpers/copy_phrase_wrapper.py +++ b/bcipy/helpers/copy_phrase_wrapper.py @@ -5,7 +5,8 @@ import numpy as np -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.config import SESSION_LOG_FILENAME +from bcipy.exceptions import BciPyCoreException from bcipy.helpers.language_model import histogram, with_min_prob from bcipy.helpers.stimuli import InquirySchedule, StimuliOrder from bcipy.helpers.symbols import BACKSPACE_CHAR @@ -18,7 +19,7 @@ from bcipy.task.control.query import NBestStimuliAgent from bcipy.task.data import EvidenceType -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) class CopyPhraseWrapper: diff --git a/bcipy/helpers/language_model.py b/bcipy/helpers/language_model.py index 0c9d87d7c..b1b77a05d 100644 --- a/bcipy/helpers/language_model.py +++ b/bcipy/helpers/language_model.py @@ -13,7 +13,7 @@ """Only imported models will be included in language_models_by_name""" # flake8: noqa -from bcipy.helpers.exceptions import InvalidLanguageModelException +from bcipy.exceptions import InvalidLanguageModelException from bcipy.language.model.causal import CausalLanguageModel from bcipy.language.model.kenlm import KenLMLanguageModel from bcipy.language.model.mixture import MixtureLanguageModel diff --git a/bcipy/helpers/load.py b/bcipy/helpers/load.py index 7b36c2a43..229c4b67e 100644 --- a/bcipy/helpers/load.py +++ b/bcipy/helpers/load.py @@ -6,21 +6,21 @@ from pathlib import Path from shutil import copyfile from time import localtime, strftime -from typing import List, Optional +from typing import List, Optional, Union from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_PATH, DEFAULT_FIELD_PATH, DEFAULT_PARAMETERS_PATH, EXPERIMENT_FILENAME, FIELD_FILENAME, ROOT, - SIGNAL_MODEL_FILE_SUFFIX) + SIGNAL_MODEL_FILE_SUFFIX, SESSION_LOG_FILENAME) from bcipy.gui.file_dialog import ask_directory, ask_filename -from bcipy.helpers.exceptions import (BciPyCoreException, - InvalidExperimentException) +from bcipy.exceptions import (BciPyCoreException, + InvalidExperimentException) from bcipy.helpers.parameters import Parameters from bcipy.helpers.raw_data import RawData from bcipy.preferences import preferences from bcipy.signal.model import SignalModel -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) def copy_parameters(path: str = DEFAULT_PARAMETERS_PATH, @@ -136,9 +136,10 @@ def load_json_parameters(path: str, value_cast: bool = False) -> Parameters: "fake_data": { "value": "true", "section": "bci_config", - "readableName": "Fake Data Sessions", + "name": "Fake Data Sessions", "helpTip": "If true, fake data server used", - "recommended_values": "", + "recommended": "", + "editable": "true", "type": "bool" } @@ -212,7 +213,7 @@ def choose_csv_file(filename: Optional[str] = None) -> Optional[str]: return filename -def load_raw_data(filename: str) -> RawData: +def load_raw_data(filename: Union[Path, str]) -> RawData: """Reads the data (.csv) file written by data acquisition. Parameters @@ -260,14 +261,11 @@ def load_users(data_save_loc: str) -> List[str]: return saved_users # grab all experiments in the directory and iterate over them to get the users - experiments = fast_scandir(path, return_path=True) - - for experiment in experiments: - users = fast_scandir(experiment, return_path=False) - # If it is a new user, append it to the saved_user list - for user in users: - if user not in saved_users: - saved_users.append(user) + users = fast_scandir(path, return_path=True) + + for user in users: + if user not in saved_users: + saved_users.append(user.split('/')[-1]) return saved_users diff --git a/bcipy/helpers/parameters.py b/bcipy/helpers/parameters.py index 970d9a023..3be5f3d48 100644 --- a/bcipy/helpers/parameters.py +++ b/bcipy/helpers/parameters.py @@ -13,9 +13,10 @@ class Parameter(NamedTuple): """Represents a single parameter""" value: Any section: str - readableName: str + name: str helpTip: str - recommended_values: list + recommended: list + editable: bool type: str @@ -79,8 +80,8 @@ def __init__(self, source: Optional[str] = None, cast_values: bool = False): self.cast_values = cast_values self.required_keys = set([ - 'value', 'section', 'readableName', 'helpTip', - 'recommended_values', 'type' + 'value', 'section', 'name', 'helpTip', + 'recommended', 'editable', 'type' ]) self.conversions = { 'int': int, @@ -111,9 +112,10 @@ def from_cast_values(cls, **kwargs): key, { 'value': value_str, 'section': '', - 'readableName': '', + 'name': '', 'helpTip': '', - 'recommended_values': '', + 'recommended': '', + 'editable': '', 'type': value_type }) return params @@ -218,9 +220,10 @@ def check_valid_entry(self, entry_name: str, entry: dict) -> None: "fake_data": { "value": "true", "section": "bci_config", - "readableName": "Fake Data Sessions", + "name": "Fake Data Sessions", "helpTip": "If true, fake data server used", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "bool" } diff --git a/bcipy/helpers/raw_data.py b/bcipy/helpers/raw_data.py index 51f1c5627..d94ac2174 100644 --- a/bcipy/helpers/raw_data.py +++ b/bcipy/helpers/raw_data.py @@ -7,7 +7,7 @@ import pandas as pd from bcipy.config import DEFAULT_ENCODING -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.exceptions import BciPyCoreException from bcipy.signal.generator.generator import gen_random_data from bcipy.signal.process import Composition diff --git a/bcipy/helpers/report.py b/bcipy/helpers/report.py index 4836a7a0c..774e7ea8e 100644 --- a/bcipy/helpers/report.py +++ b/bcipy/helpers/report.py @@ -111,7 +111,7 @@ def _create_heatmap(self, onsets: List[float], range: Tuple[float, float], type: """ # create a heatmap with the onset values fig, ax = plt.subplots() - fig.set_size_inches(6, 3) + fig.set_size_inches(4, 2) ax.hist(onsets, bins=100, range=range, color='red', alpha=0.7) ax.set_title(f'{type} Artifact Onsets') ax.set_xlabel('Time (s)') @@ -156,8 +156,12 @@ class SessionReportSection(ReportSection): A class to handle the creation of a Session Report section in a BciPy Report using a summary dictionary. """ - def __init__(self, summary: Optional[dict] = None) -> None: + def __init__(self, summary: dict) -> None: self.summary = summary + if 'task' in self.summary: + self.session_name = self.summary['task'] + else: + self.session_name = 'Session Summary' self.style = getSampleStyleSheet() self.summary_table = None @@ -203,7 +207,7 @@ def _create_header(self) -> Paragraph: Creates a header for the Session Report section. """ - header = Paragraph('Session Summary', self.style['Heading3']) + header = Paragraph(f'{self.session_name}', self.style['Heading3']) return header diff --git a/bcipy/helpers/save.py b/bcipy/helpers/save.py index 84d275d69..8d0f197e9 100644 --- a/bcipy/helpers/save.py +++ b/bcipy/helpers/save.py @@ -16,7 +16,6 @@ DEFAULT_PARAMETER_FILENAME, SIGNAL_MODEL_FILE_SUFFIX, STIMULI_POSITIONS_FILENAME) -from bcipy.helpers.validate import validate_experiments from bcipy.signal.model.base_model import SignalModel @@ -41,7 +40,6 @@ def save_experiment_data( fields: dict, location: str, name: str) -> str: - validate_experiments(experiments, fields) return save_json_data(experiments, location, name) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 01bd4aae3..8a1af1a11 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -21,13 +21,13 @@ from PIL import Image from psychopy import core -from bcipy.config import DEFAULT_FIXATION_PATH, DEFAULT_TEXT_FIXATION -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.config import DEFAULT_FIXATION_PATH, DEFAULT_TEXT_FIXATION, SESSION_LOG_FILENAME +from bcipy.exceptions import BciPyCoreException from bcipy.helpers.list import grouper # Prevents pillow from filling the console with debug info logging.getLogger('PIL').setLevel(logging.WARNING) -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) NO_TARGET_INDEX = None diff --git a/bcipy/helpers/symbols.py b/bcipy/helpers/symbols.py index 467f5f59f..dca9feb4c 100644 --- a/bcipy/helpers/symbols.py +++ b/bcipy/helpers/symbols.py @@ -7,7 +7,7 @@ BACKSPACE_CHAR = '<' -def alphabet(parameters=None, include_path=True): +def alphabet(parameters=None, include_path=True, backspace=BACKSPACE_CHAR, space=SPACE_CHAR): """Alphabet. Function used to standardize the symbols we use as alphabet. @@ -31,7 +31,7 @@ def alphabet(parameters=None, include_path=True): stimulus_array.append(img) return stimulus_array - return list(ascii_uppercase) + [BACKSPACE_CHAR, SPACE_CHAR] + return list(ascii_uppercase) + [backspace, space] def qwerty_order(is_txt_stim: bool = True, @@ -49,14 +49,17 @@ def qwerty_order(is_txt_stim: bool = True, return f"{row1}{row2}{row3}".index -def frequency_order(is_txt_stim: bool = True) -> Callable: +def frequency_order( + is_txt_stim: bool = True, + space: str = SPACE_CHAR, + backspace: str = BACKSPACE_CHAR) -> Callable: """Returns a function that can be used to sort the alphabet symbols in most frequently used order in the English language. """ if not is_txt_stim: raise NotImplementedError( 'Frequency ordering not implemented for images') - return f"ETAOINSHRDLCUMWFGYPBVKJXQZ{BACKSPACE_CHAR}{SPACE_CHAR}".index + return f"ETAOINSHRDLCUMWFGYPBVKJXQZ{backspace}{space}".index DEFAULT_SYMBOL_SET = alphabet() diff --git a/bcipy/helpers/system_utils.py b/bcipy/helpers/system_utils.py index 6b9450404..c423dde4a 100644 --- a/bcipy/helpers/system_utils.py +++ b/bcipy/helpers/system_utils.py @@ -19,7 +19,7 @@ import torch from cpuinfo import get_cpu_info -from bcipy.config import DEFAULT_ENCODING, LOG_FILENAME +from bcipy.config import DEFAULT_ENCODING, SESSION_LOG_FILENAME class ScreenInfo(NamedTuple): @@ -197,30 +197,32 @@ def get_system_info() -> dict: def configure_logger( save_folder: str, - log_name=LOG_FILENAME, - log_level=logging.INFO, - version=None) -> None: + log_name=SESSION_LOG_FILENAME, + log_level=logging.INFO) -> logging.Logger: """Configure Logger. - Does what it says. + Configures a logger to print to a file in the save_folder directory. """ # create the log file logfile = os.path.join(save_folder, 'logs', log_name) # configure it - root_logger = logging.getLogger() - root_logger.setLevel(log_level) + logger = logging.getLogger(name=log_name) + logger.setLevel(log_level) + for hdlr in logger.handlers[:]: # remove all old handlers + logger.removeHandler(hdlr) handler = logging.FileHandler(logfile, 'w', encoding='utf-8') handler.setFormatter(logging.Formatter( '[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s')) - root_logger.addHandler(handler) + logger.addHandler(handler) # print to console the absolute path of the log file to aid in debugging path_to_logs = os.path.abspath(logfile) - print(f'Printing all BciPy logs to: {path_to_logs}') + msg = f'Writing logs to: {path_to_logs}' + logger.info(msg) + print(msg) - if version: - logging.info(f'Start of Session for BciPy Version: ({version})') + return logger def import_submodules(package, recursive=True): diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index a4e36c525..983dec8ec 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -8,12 +8,12 @@ from bcipy.acquisition.multimodal import ClientManager, ContentType from bcipy.acquisition.record import Record -from bcipy.config import MAX_PAUSE_SECONDS, SESSION_COMPLETE_MESSAGE +from bcipy.config import MAX_PAUSE_SECONDS, SESSION_COMPLETE_MESSAGE, SESSION_LOG_FILENAME from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import get_fixation from bcipy.task.exceptions import InsufficientDataException -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) def fake_copy_phrase_decision(copy_phrase: str, target_letter: str, text_task: str) -> Tuple[str, str, bool]: diff --git a/bcipy/helpers/tests/resources/mock_session/parameters.json b/bcipy/helpers/tests/resources/mock_session/parameters.json index f9fcf37d6..9331fe714 100644 --- a/bcipy/helpers/tests/resources/mock_session/parameters.json +++ b/bcipy/helpers/tests/resources/mock_session/parameters.json @@ -2,738 +2,781 @@ "fake_data": { "value": "false", "section": "bci_config", - "readableName": "Fake EEG Data On/Off", + "name": "Fake EEG Data", "helpTip": "If ‘true’, fake EEG data will be used instead of real EEG data. Useful for testing by software development team.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "bool" }, - "acq_device": { - "value": "DSI-24", + "acq_mode": { + "value": "EEG", "section": "acq_config", - "readableName": "Acquisition Device", - "helpTip": "Specifies the hardware used for EEG data collection.", - "recommended_values": [ - "DSI-24", - "DSI-VR300", - "g.USBamp-1", - "Tobii Nano" + "name": "Acquisition Mode", + "helpTip": "Specifies the hardware device(s) used for data collection. Default: EEG.", + "recommended": [ + "EEG", + "EEG/DSI-24", + "Eyetracker", + "EEG+Eyetracker", + "EEG+Eyetracker:passive" ], + "editable": true, "type": "str" }, - "acq_connection_method": { - "value": "LSL", - "section": "acq_connection_method", - "readableName": "Acquisition Connection Method", - "helpTip": "Specifies the method used to connect to the data acquisition device (LSL or TCP). Default: LSL", - "recommended_values": [ - "LSL", - "TCP" - ], - "type": "str" - }, - "acq_host": { - "value": "127.0.0.1", - "section": "acq_config", - "readableName": "TCP Connection Host", - "helpTip": "Specifies the host for a TCP connection (used when Acquisition Connection Method is set to 'TCP'). Default: 127.0.0.1", - "recommended_values": "", - "type": "str" - }, - "acq_port": { - "value": "9000", - "section": "acq_config", - "readableName": "TCP Connection Port", - "helpTip": "Specifies the port for a TCP connection (used when Acquisition Connection Method is set to ‘TCP’). Default: 9000", - "recommended_values": "", - "type": "int" - }, "trigger_type": { "value": "text", "section": "bci_config", - "readableName": "Trigger Stimulus Type", - "helpTip": "Specifies whether to use a picture or auditory stimulus to calibrate trigger latency. Default: text", - "recommended_values": [ + "name": "Trigger Stimulus Type", + "helpTip": "Specifies whether to use text, image or auditory stimulus to calibrate trigger latency. Default: text", + "recommended": [ "image", "text" ], + "editable": true, "type": "str" }, "k_folds": { "value": "10", "section": "signal_config", - "readableName": "Number of Cross-Validation Folds", + "name": "Number of Cross-Validation Folds", "helpTip": "Specifies the number of folds used for cross-validation when calculating AUC. Default: 10", - "recommended_values": "[10]", + "recommended": "[10]", + "editable": true, "type": "int" }, "trial_window": { "value": "0.0:0.5", "section": "bci_config", - "readableName": "Trial Classification Window Length", + "name": "Trial Classification Window Length", "helpTip": "Specifies the window (in seconds) of the EEG data collection window after each stimulus presentation. Default: 0.0:0.5", - "recommended_values": [ + "recommended": [ "0.0:0.5", "0.0:0.8", "0.2:0.8" ], + "editable": true, "type": "range" }, "prestim_length": { "value": "1", "section": "bci_config", - "readableName": "Prestimulus Window Length", + "name": "Prestimulus Window Length", "helpTip": "Specifies the length (in seconds) of the EEG data window to return before inquiry presentation. Default: 1", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "alert_sound_file": { - "value": "bcipy/static/sounds/beep.wav", + "value": "beep.wav", "section": "bci_config", - "readableName": "Alert Tone", - "helpTip": "Specifies the path to an audio file to be played as an alert tone when experiments or offline analysis is complete. Default: bcipy/static/sounds/beep.wav", - "recommended_values": "", + "name": "Alert Tone", + "helpTip": "Specifies the path to an audio file to be played as an alert tone when experiments or offline analysis is complete. Default: beep.wav", + "recommended": "", + "editable": true, "type": "filepath" }, "signal_model_path": { "value": "", "section": "bci_config", - "readableName": "Signal Model Path", + "name": "Signal Model Path", "helpTip": "Directory of the pre-trained signal model. This is often the the calibration session directory.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "directorypath" }, "filter_high": { "value": "20", "section": "signal_config", - "readableName": "High Frequency Filter Cutoff", + "name": "High Frequency Filter Cutoff", "helpTip": "Specifies the frequency bound (in Hz) of the low-pass filter (high cutoff). Default: 20", - "recommended_values": [ + "recommended": [ "20", "45", "50" ], + "editable": true, "type": "float" }, "filter_low": { "value": "1", "section": "signal_config", - "readableName": "Low Frequency Filter Cutoff", + "name": "Low Frequency Filter Cutoff", "helpTip": "Specifies the frequency bound (in Hz) of the high-pass filter (low cutoff). Default: 1", - "recommended_values": [ + "recommended": [ "1", "2" ], + "editable": true, "type": "float" }, "filter_order": { "value": "2", "section": "signal_config", - "readableName": "Filter Order", + "name": "Filter Order", "helpTip": "Specifies the slope of the low-pass and high-pass filters. Default: 2", - "recommended_values": [ + "recommended": [ "2", "3" ], + "editable": true, "type": "float" }, "notch_filter_frequency": { "value": "60", "section": "signal_config", - "readableName": "Notch Filter Frequency", + "name": "Notch Filter Frequency", "helpTip": "Specifies the frequency (in Hz) of the notch filter used to remove electrical artifact from the surrounding environment. Default: 60", - "recommended_values": [ + "recommended": [ "59", "60" ], + "editable": true, "type": "float" }, "down_sampling_rate": { "value": "2", "section": "signal_config", - "readableName": "Downsampling Rate", + "name": "Downsampling Rate", "helpTip": "Specifies the decimation factor (integer only) for downsampling of EEG data. Default: 2", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, - "artifact_rejection": { - "value": "false", - "section": "artifact_rejection", - "readableName": "Artifact Rejection On/Off", - "helpTip": "If ‘true’, the system will detect and reject inquiries containing unwanted artifacts (e.g. blinks). This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "bool" - }, - "high_voltage_threshold": { - "value": "false", - "section": "artifact_rejection", - "readableName": "High Voltage Threshold On/Off", - "helpTip": "If ‘true’, an upper voltage threshold will be set for artifact rejection. Detection of values above the specified threshold will trigger rejection of a inquiry. This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "bool" - }, - "high_voltage_value": { - "value": "75E+6", - "section": "artifact_rejection", - "readableName": "High Voltage Threshold Value", - "helpTip": "Specifies the high voltage threshold (in microvolts) for artifact rejection (High Voltage Threshold must be set to ‘true’). Default: 75E+6. This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "float" - }, - "low_voltage_threshold": { - "value": "false", - "section": "artifact_rejection", - "readableName": "Low Voltage Threshold On/Off", - "helpTip": "If ‘true’, a lower voltage threshold will be set for artifact rejection. Detection of values below the specified threshold will trigger rejection of a inquiry. This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "bool" - }, - "low_voltage_value": { - "value": "-75E-6", - "section": "artifact_rejection", - "readableName": "LowVoltage Threshold Value", - "helpTip": "Specifies the low voltage threshold (in microvolts) for artifact rejection (Low Voltage Threshold must be set to ‘true’). Default: -75E-6 This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "float" - }, "summarize_session": { "value": "true", "section": "bci_config", - "readableName": "Summarize Session Data", + "name": "Summarize Session Data", "helpTip": "If 'true', writes an Excel file which summarizes the session data by charting evidence per inquiry.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "bool" }, "parameter_location": { "value": "bcipy/parameters/parameters.json", "section": "bci_config", - "readableName": "Parameter File", + "name": "Parameter File", "helpTip": "Specifies the file containing the current system parameters. Default: bcipy/parameters/parameters.json", - "recommended_values": [ + "recommended": [ "parameters/parameters.json" ], + "editable": true, "type": "filepath" }, "data_save_loc": { "value": "data/", "section": "bci_config", - "readableName": "Data Save Location", + "name": "Data Save Location", "helpTip": "Specifies the location in which to save data files after each recording. This must be a directory ending with /. Default: data/", - "recommended_values": [ + "recommended": [ "data/" ], + "editable": true, "type": "directorypath" }, "full_screen": { "value": "false", "section": "bci_config", - "readableName": "Full Screen Mode On/Off", + "name": "Full Screen Mode", "helpTip": "If ‘true’, the task will be displayed in full screen mode. If ‘false’, the task will be displayed in a window.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "bool" }, "window_height": { "value": "500", "section": "bci_config", - "readableName": "Task Window Height", + "name": "Task Window Height", "helpTip": "Specifies the height (in norm units) of the task window when not in full screen mode (Full Screen Mode On/Off must be set to ‘false’). See https://www.psychopy.org/general/units.html. Default: 500", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "window_width": { "value": "500", "section": "bci_config", - "readableName": "Task Window Width", + "name": "Task Window Width", "helpTip": "Specifies the width (in norm units) of the task window when not in full screen mode (Full Screen Mode On/Off must be set to ‘false’). See https://www.psychopy.org/general/units.html. Default: 500", - "recommended_values": "", + "recommended": "", + "editable": true, + "type": "int" + }, + "matrix_rows": { + "value": "5", + "section": "bci_config", + "name": "Matrix Rows", + "helpTip": "Specifies the number of rows to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", + "recommended": "", + "editable": true, + "type": "int" + }, + "matrix_columns": { + "value": "6", + "section": "bci_config", + "name": "Matrix Columns", + "helpTip": "Specifies the number of columns to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", + "recommended": "", + "editable": true, "type": "int" }, + "matrix_width": { + "value": "0.7", + "section": "bci_config", + "name": "Matrix Width (%)", + "helpTip": "Specifies the max percentage of the display that the matrix grid should utilize. Must be between 0 and 1", + "recommended": "", + "editable": true, + "type": "float" + }, "acq_show_viewer": { "value": "false", "section": "acq_config", - "readableName": " EEG Viewer On/Off", - "helpTip": "If ‘true’, the EEG signal viewer will be displayed.", - "recommended_values": "", + "name": " EEG Viewer", + "helpTip": "If ‘true’, the EEG signal viewer will be displayed along with the Task.", + "recommended": "", + "editable": true, "type": "bool" }, "stim_screen": { "value": "0", "section": "bci_config", - "readableName": "Task Display Monitor", + "name": "Task Display Monitor", "helpTip": "Specifies which monitor to use for task display when two monitors are in use. If ‘0’, the task will be displayed on the primary monitor (with the EEG signal viewer on the second monitor, if EEG Viewer On/Off is set to ‘true’). If ‘1’, the opposite monitor assignment will be used.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "task_buffer_length": { "value": "2", "section": "bci_config", - "readableName": "Inter-inquiry Interval", + "name": "Inter-inquiry Interval", "helpTip": "Specifies the delay time (in seconds) between the final stimulus in one inquiry and the beginning (target stimulus or fixation cross) of the next inquiry in a task. Default: 2", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "is_txt_stim": { "value": "true", "section": "bci_config", - "readableName": "Text Stimuli On/Off", - "helpTip": "If ‘true’, text stimuli will be used. If ‘false’, image stimuli will be loaded from the folder specified in Image Stimulus Folder.", - "recommended_values": "", + "name": "Text Stimuli", + "helpTip": "If ‘true’, text stimuli will be used. If ‘false’, image stimuli will be loaded from the folder specified in Image Stimulus Folder. Default: true", + "recommended": "", + "editable": true, "type": "bool" }, "path_to_presentation_images": { "value": "bcipy/static/images/rsvp/", "section": "bci_config", - "readableName": "Image Stimulus Folder", + "name": "Image Stimulus Folder", "helpTip": "Specifies the location of image files to be used as stimuli (Text Stimuli On/Off must be set to ‘false’). This must be a directory ending with /.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "directorypath" }, "stim_space_char": { "value": "–", "section": "bci_config", - "readableName": "Space Character", + "name": "Space Character", "helpTip": "Specifies the text or Unicode character which represents a space during text-stimuli tasks. Default: –", - "recommended_values": [ + "recommended": [ "_", "–", "‒", "□" ], + "editable": true, "type": "str" }, "stim_order": { "value": "random", "section": "bci_config", - "readableName": "Stimuli Order", + "name": "Stimuli Order", "helpTip": "Specifies the ordering of stimuli in an inquiry. Default is random.", - "recommended_values": [ + "recommended": [ "alphabetical", "random" ], + "editable": true, "type": "str" }, "target_positions": { "value": "distributed", "section": "bci_config", - "readableName": "Target Positions", + "name": "Target Positions", "helpTip": "Specifies the positions of target stimuli in calibration task. Default is random.", - "recommended_values": [ + "recommended": [ "distributed", "random" ], + "editable": true, "type": "str" }, "nontarget_inquiries": { "value": "10", "section": "bci_config", - "readableName": "Percentage of Nontarget Inquiries", + "name": "Percentage of Nontarget Inquiries", "helpTip": "Specifies the percentage (0-100) of inquiries which target stimuli flashed is not in inquiry. Default is 10 percent.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "stim_length": { "value": "10", "section": "bci_config", - "readableName": "Stimuli Per inquiry", + "name": "Stimuli Per inquiry", "helpTip": "Specifies the number of stimuli to present in each inquiry. Default: 10", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "time_flash": { "value": "0.25", "section": "bci_config", - "readableName": "Stimulus Presentation Duration", + "name": "Stimulus Presentation Duration", "helpTip": "Specifies the duration of time (in seconds) that each stimulus is displayed in an inquiry.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "time_prompt": { "value": "1", "section": "bci_config", - "readableName": "Time Prompt Stimuli (sec)", + "name": "Time Prompt Stimuli (sec)", "helpTip": "The amount of time in seconds to present the target stimuli prompt in an inquiry.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "time_fixation": { "value": "0.5", "section": "bci_config", - "readableName": "Time Fixation Stimuli (sec)", + "name": "Time Fixation Stimuli (sec)", "helpTip": "The amount of time in seconds to present the fixation stimuli in an inquiry.", - "recommended_values": "", + "recommended": "", + "editable": true, + "type": "float" + }, + "time_vep_animation": { + "value": "1.0", + "section": "bci_config", + "name": "Time VEP Animation (sec)", + "helpTip": "The amount of time in seconds for the animation moving symbols to boxes.", + "recommended": "", + "editable": true, "type": "float" }, "stim_jitter": { "value": "0.0", "section": "bci_config", - "readableName": "Stimulus Presentation Jitter (sec)", + "name": "Stimulus Presentation Jitter (sec)", "helpTip": "Specifies the time (sec) to jitter presentation rates. Default: 0.0", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "stim_pos_x": { "value": "0", "section": "bci_config", - "readableName": "Stimulus Position Horizontal", + "name": "Stimulus Position Horizontal", "helpTip": "Specifies the center point of the stimulus position along the X axis. Possible values range from -1 to 1, with 0 representing the center. Default: 0", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "stim_pos_y": { "value": "0", "section": "bci_config", - "readableName": "Stimulus Position Vertical", + "name": "Stimulus Position Vertical", "helpTip": "Specifies the center point of the stimulus position along the Y axis. Possible values range from -1 to 1, with 0 representing the center. Default: 0", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "font": { - "value": "Consolas", + "value": "Courier New", "section": "bci_config", - "readableName": "Font", - "helpTip": "Specifies the font used for all text stimuli. Default: Consolas", - "recommended_values": [ + "name": "Font", + "helpTip": "Specifies the font used for all text stimuli. Default: Courier New", + "recommended": [ "Courier New", - "Lucida Sans", - "Consolas" + "Lucida Sans" ], + "editable": true, "type": "str" }, "stim_height": { "value": "0.5", "section": "bci_config", - "readableName": "Stimulus Size", + "name": "Stimulus Size", "helpTip": "Specifies the height of text stimuli. See https://www.psychopy.org/general/units.html. Default: 0.5", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "stim_color": { "value": "white", "section": "bci_config", - "readableName": "Stimulus Color", + "name": "Stimulus Color", "helpTip": "Specifies the color of text stimuli within the RSVP stream. Default: white", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "str" }, "target_color": { "value": "white", "section": "bci_config", - "readableName": "Target Color", + "name": "Target Color", "helpTip": "Specifies the color of target characters during calibration. Default: white", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "str" }, "fixation_color": { "value": "red", "section": "bci_config", - "readableName": "Fixation Cross Color", + "name": "Fixation Cross Color", "helpTip": "Specifies the color of the fixation cross that appears before each inquiry. Default: red", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "str" }, "background_color": { "value": "black", "section": "bci_config", - "readableName": "Task Background Color", + "name": "Task Background Color", "helpTip": "Specifies the color of the task background. Default: black", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "str" }, "info_pos_x": { "value": "0", "section": "bci_config", - "readableName": "Position Text (X)", + "name": "Position Text (X)", "helpTip": "Position Text (X)", - "recommended_values": [ + "recommended": [ "0" ], + "editable": true, "type": "float" }, "info_pos_y": { "value": "-0.75", "section": "bci_config", - "readableName": "Position Text (Y)", + "name": "Position Text (Y)", "helpTip": "Position Text (Y)", - "recommended_values": [ + "recommended": [ "-0.75" ], + "editable": true, "type": "float" }, "info_text": { "value": "", "section": "bci_config", - "readableName": "Text below main presentation", + "name": "Text below main presentation", "helpTip": "Text below main presentation", - "recommended_values": [ + "recommended": [ "", "Demo Text", "DEMO" ], + "editable": true, "type": "str" }, "info_height": { "value": "0.1", "section": "bci_config", - "readableName": "Text below main presentation height", + "name": "Text below main presentation height", "helpTip": "Specifies the height of info text stimuli. See https://www.psychopy.org/general/units.html. Default: 0.1", - "recommended_values": [ + "recommended": [ "0.1" ], + "editable": true, "type": "float" }, "info_color": { "value": "white", "section": "bci_config", - "readableName": "Color Text", + "name": "Color Text", "helpTip": "Color Text", - "recommended_values": [ + "recommended": [ "white", "black", "blue" ], + "editable": true, "type": "str" }, "task_text": { "value": "HELLO_WORLD", "section": "bci_config", - "readableName": "Target Phrase", + "name": "Target Phrase", "helpTip": "Specifies the target phrase displayed at the top of the screen during text-stimuli copy/spelling tasks.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "str" }, "task_height": { "value": "0.1", "section": "bci_config", - "readableName": "Task Text Size", + "name": "Task Text Size", "helpTip": "Specifies the height of task-specific text, e.g. #/100 in calibration and target phrase in copy/spelling. See https://www.psychopy.org/general/units.html. Default: 0.1", - "recommended_values": [ + "recommended": [ "0.1" ], + "editable": true, "type": "float" }, "task_color": { "value": "white", "section": "bci_config", - "readableName": "Task Text Color", + "name": "Task Text Color", "helpTip": "Specifies the color of task-specific text, e.g. #/100 in calibration and target phrase in copy/spelling. Default: white", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "str" }, + "task_padding": { + "value": "0.05", + "section": "bci_config", + "name": "Task Bar Padding", + "helpTip": "Specifies the padding around the task bar text. Default: 0.05", + "recommended": [ + "0.05" + ], + "editable": true, + "type": "float" + }, "stim_number": { "value": "100", "section": "bci_config", - "readableName": "Number of Calibration inquiries", + "name": "Number of Calibration inquiries", "helpTip": "Specifies the number of inquiries to present in a calibration session. Default: 100", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "enable_breaks": { "value": "false", "section": "bci_config", - "readableName": "Automatic Calibration Breaks On/Off", + "name": "Automatic Calibration Breaks", "helpTip": "If ‘true’, automatic breaks will be added to the calibration session. If ‘false’, automatic breaks will not occur, but the session can still be paused by pressing Space.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "bool" }, "break_len": { "value": "30", "section": "bci_config", - "readableName": "Automatic Calibration Break Length", + "name": "Automatic Calibration Break Length", "helpTip": "Specifies the length (in seconds) of automatic calibration breaks (Automatic Calibration Breaks On/Off must be set to ‘true’).", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "trials_before_break": { "value": "20", "section": "bci_config", - "readableName": "Automatic Calibration Break Timing", + "name": "Automatic Calibration Break Timing", "helpTip": "Specifies the number of inquiries between automatic calibration breaks (Automatic Calibration Breaks On/Off must be set to ‘true’).", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "break_message": { "value": "Take a break!", "section": "bci_config", - "readableName": "Automatic Calibration Break Message", + "name": "Automatic Calibration Break Message", "helpTip": "Specifies the message displayed during automatic calibration breaks (Automatic Calibration Breaks On/Off must be set to ‘true’).", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "str" }, - "min_inq_len": { - "value": "1", - "section": "bci_config", - "readableName": "Minimum Inquiry Length", - "helpTip": "The minimum number of inquiries to present in spelling tasks", - "recommended_values": [ - "1" - ], - "type": "int" - }, "max_inq_len": { "value": "50", "section": "bci_config", - "readableName": "Maximum Inquiry Length", + "name": "Maximum Inquiry Length", "helpTip": "Specifies the maximum number of inquiries to present in copy/spelling tasks. The task will end if this number is reached.", - "recommended_values": [ + "recommended": [ "20", "25" ], + "editable": true, "type": "int" }, "max_minutes": { "value": "20", "section": "bci_config", - "readableName": "Maximum Task Length (Time)", + "name": "Maximum Task Length (Time)", "helpTip": "Specifies the time limit (in minutes) for copy/spelling tasks. The task will end if this time limit is reached.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "max_selections": { "value": "25", "section": "bci_config", - "readableName": "Maximum Number of Selections", + "name": "Maximum Number of Selections", "helpTip": "The maximum number of selections for copy/spelling tasks. The task will end if this number is reached.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "decision_threshold": { "value": "0.8", "section": "bci_config", - "readableName": "Decision Threshold", + "name": "Decision Threshold", "helpTip": "Specifies the decision threshold for stimulus selection in copy/spelling class. If the posterior probability (combining EEG and language model evidence) for a stimulus reaches this threshold, it will be selected. Possible value range: 0.0-1.0. Default: 0.8", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "min_inq_per_series": { "value": "1", "section": "bci_config", - "readableName": "Minimum Inquiries Per Series", + "name": "Minimum Inquiries Per Series", "helpTip": "Specifies the minimum number of inquiries to present before making a decision in copy/spelling tasks. Default: 1", - "recommended_values": [ + "recommended": [ "1" ], + "editable": true, "type": "int" }, "max_inq_per_series": { "value": "11", "section": "bci_config", - "readableName": "Maximum Inquiries Per Series", + "name": "Maximum Inquiries Per Series", "helpTip": "Specifies the maximum number of inquiries to present before making a decision in copy/spelling tasks.", - "recommended_values": [ + "recommended": [ "10", "15" ], + "editable": true, "type": "int" }, "backspace_always_shown": { "value": "true", "section": "bci_config", - "readableName": "Always Show Backspace On/Off", + "name": "Always Show Backspace", "helpTip": "If ‘true’, the backspace character will be included in every inquiry in text-stimuli copy/spelling tasks. If ‘false’, the backspace character will be treated the same as other characters, appearing in inquiries only when warranted by EEG/language model evidence.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "bool" }, "spelled_letters_count": { "value": "0", "section": "bci_config", - "readableName": "Pre-Selected Letters Count", + "name": "Pre-Selected Letters Count", "helpTip": "Specifies the number of letters in the target phrase that are already typed when the task begins, e.g. if the target phrase is “THE_DOG”, setting this parameter to ‘4’ would display “THE_” as the typed string, and the user would begin typing with D. If ‘0’, the typed string will be blank.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "int" }, "lang_model_type": { - "value": "MIXTURE", + "value": "UNIFORM", "section": "lang_model_config", - "readableName": "Language Model Type", - "helpTip": "Specifies which language model to use. Default: MIXTURE", - "recommended_values": [ + "name": "Language Model Type", + "helpTip": "Specifies which language model to use. Default: UNIFORM", + "recommended": [ "UNIFORM", "CAUSAL", "KENLM", - "MIXTURE" + "MIXTURE", + "ORACLE" ], + "editable": true, "type": "str" }, "lm_backspace_prob": { - "value": "0.05", + "value": "0.0", "section": "bci_config", - "readableName": "Backspace Probability", - "helpTip": "Specifies the initial probability assigned to the backspace character in the language model. Possible value range: 0.0-1.0. Default: 0.05", - "recommended_values": "", + "name": "Backspace Probability", + "helpTip": "Specifies the minimum probability assigned to the backspace character in the language model. Possible value range: 0.0-1.0. Default: 0.0", + "recommended": "0.05", + "editable": true, "type": "float" }, "show_preview_inquiry": { "value": "false", "section": "bci_config", - "readableName": "Preview Inquiry On/Off", - "helpTip": "If ‘true’, the inquiry will be previewed as applicable for the task. *Note* Not all tasks will have this enabled!", - "recommended_values": "", + "name": "Preview Inquiry Display", + "helpTip": "If ‘true’, the inquiry will be previewed as applicable for the Task. *Note* Not all tasks will have this enabled!", + "recommended": "", + "editable": true, "type": "bool" }, "preview_inquiry_progress_method": { "value": "0", "section": "bci_config", - "readableName": "Preview Inquiry Progression Method", + "name": "Preview Inquiry Progression Method", "helpTip": "If show_preview_inquiry true, this will determine how to proceed after a key hit. 0 = preview only; 1 = press to confirm; 2 = press to skip to another inquiry", - "recommended_values": [ + "recommended": [ "0", "1", "2" ], + "editable": true, "type": "int" }, "preview_inquiry_length": { "value": "5", "section": "bci_config", - "readableName": "Preview Inquiry Display Length", + "name": "Preview Inquiry Display Length", "helpTip": "Length of time in seconds to present an inquiry preview to the user.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "preview_inquiry_key_input": { "value": "return", "section": "bci_config", - "readableName": "Preview Inquiry Display Key Input Method", + "name": "Preview Inquiry Display Key Input Method", "helpTip": "Defines the key used to engage with inquiry preview.", - "recommended_values": [ + "recommended": [ "space", "escape", "return" ], + "editable": true, "type": "str" }, "preview_inquiry_isi": { "value": "1", "section": "bci_config", - "readableName": "Preview Inquiry Inter-Stimulus Interval", + "name": "Preview Inquiry Inter-Stimulus Interval", "helpTip": "The time between previewing an inquiry and the start of an inquiry.", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "show_feedback": { "value": "true", "section": "bci_config", - "readableName": "Feedback On/Off", - "helpTip": "If ‘true’, feedback will be shown after each inquiry.", - "recommended_values": "", + "name": "Feedback Display", + "helpTip": "If ‘true’, feedback will be shown after each inquiry. If ‘false’, feedback will not be shown. *Note* Not all tasks will have this enabled!", + "recommended": "", + "editable": true, "type": "bool" }, "feedback_duration": { "value": "2", "section": "bci_config", - "readableName": "Feedback Time (seconds)", + "name": "Feedback Time (seconds)", "helpTip": "Specifies the length in time (seconds) feedback will be displayed after each inquiry in registered tasks (ex. RSVP Copy Phrase). Default: 2", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "psd_method": { "value": "Welch", "section": "bci_config", - "readableName": "Power Spectral Density Method", + "name": "Power Spectral Density Method", "helpTip": "Specifies the method used to approximate power spectral density bands (Welch or MultiTaper). Default: Welch", - "recommended_values": [ + "recommended": [ "Welch", "MutliTaper" ], + "editable": true, "type": "str" } } \ No newline at end of file diff --git a/bcipy/helpers/tests/test_acquisition.py b/bcipy/helpers/tests/test_acquisition.py index 22a725c9b..2a468320f 100644 --- a/bcipy/helpers/tests/test_acquisition.py +++ b/bcipy/helpers/tests/test_acquisition.py @@ -2,12 +2,13 @@ import shutil import unittest from pathlib import Path +import logging from unittest.mock import Mock, patch from bcipy.acquisition.devices import DeviceSpec, DeviceStatus from bcipy.config import DEFAULT_PARAMETERS_PATH from bcipy.helpers.acquisition import (RAW_DATA_FILENAME, init_device, - init_eeg_acquisition, + init_acquisition, max_inquiry_duration, parse_stream_type, raw_data_filename, server_spec, stream_types) @@ -36,12 +37,14 @@ def tearDown(self): shutil.rmtree(self.save) def test_init_acquisition(self): - """Test init_eeg_acquisition with LSL client.""" + """Test init_acquisition with LSL client.""" params = self.parameters + logger = Mock(spec=logging.Logger) + logger.info = lambda x: x params['acq_mode'] = 'EEG:passive/DSI-24' - client, servers = init_eeg_acquisition(params, self.save, server=True) + client, servers = init_acquisition(params, self.save, server=True) client.stop_acquisition() client.cleanup() diff --git a/bcipy/helpers/tests/test_load.py b/bcipy/helpers/tests/test_load.py index c42b9ec3a..77a6845bf 100644 --- a/bcipy/helpers/tests/test_load.py +++ b/bcipy/helpers/tests/test_load.py @@ -26,7 +26,7 @@ load_users, copy_parameters) from bcipy.helpers.parameters import Parameters -from bcipy.helpers.exceptions import BciPyCoreException, InvalidExperimentException +from bcipy.exceptions import BciPyCoreException, InvalidExperimentException MOCK_EXPERIMENT = { @@ -164,6 +164,12 @@ def setUp(self): self.directory_name = 'test_data_load_user' self.data_save_loc = f'{self.directory_name}/' + def tearDown(self): + try: + shutil.rmtree(self.data_save_loc) + except FileNotFoundError: + pass + def test_user_load_with_no_directory_written(self): """Use defined data save location without writing anything""" response = load_users(self.data_save_loc) @@ -172,7 +178,7 @@ def test_user_load_with_no_directory_written(self): def test_user_load_with_valid_directory(self): user = 'user_001' - file_path = f'{self.directory_name}/experiment/{user}' + file_path = f'{self.directory_name}/{user}/experiment' os.makedirs(file_path) response = load_users(self.data_save_loc) @@ -183,36 +189,33 @@ def test_user_load_with_valid_directory(self): # assert user returned is user defined above self.assertEqual(response[0], user) - shutil.rmtree(self.data_save_loc) def test_user_load_with_invalid_directory(self): # create an invalid save structure and assert expected behavior. - user = 'user_001' - file_path = f'{self.directory_name}/experiment{user}' + file_path = f'{self.directory_name}/' os.makedirs(file_path) response = load_users(self.data_save_loc) length_of_users = len(response) self.assertTrue(length_of_users == 0) - shutil.rmtree(self.data_save_loc) class TestExtractMode(unittest.TestCase): def test_extract_mode_calibration(self): - data_save_path = 'data/default/user/user_RSVP_Calibration_Mon_01_Mar_2021_11hr19min49sec_-0800' + data_save_path = 'data/user/default/user_RSVP_Calibration_Mon_01_Mar_2021_11hr19min49sec_-0800' expected_mode = 'calibration' response = extract_mode(data_save_path) self.assertEqual(expected_mode, response) def test_extract_mode_copy_phrase(self): - data_save_path = 'data/default/user/user_RSVP_Copy_Phrase_Mon_01_Mar_2021_11hr19min49sec_-0800' + data_save_path = 'data/user/default/user_RSVP_Copy_Phrase_Mon_01_Mar_2021_11hr19min49sec_-0800' expected_mode = 'copy_phrase' response = extract_mode(data_save_path) self.assertEqual(expected_mode, response) def test_extract_mode_without_mode_defined(self): - invalid_data_save_dir = 'data/default/user/user_bad_dir' + invalid_data_save_dir = 'data/user/default/user_bad_dir' with self.assertRaises(BciPyCoreException): extract_mode(invalid_data_save_dir) diff --git a/bcipy/helpers/tests/test_parameters.py b/bcipy/helpers/tests/test_parameters.py index c46b20088..58b0acbd9 100644 --- a/bcipy/helpers/tests/test_parameters.py +++ b/bcipy/helpers/tests/test_parameters.py @@ -52,19 +52,21 @@ def test_load_data(self): "fake_data": { "value": "true", "section": "bci_config", - "readableName": "Fake EEG Data On/Off", + "name": "Fake EEG Data On/Off", "helpTip": "If ‘true’, fake EEG data will be used instead of real EEG data.", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "bool" }, "acq_device": { "value": "LSL", "section": "acq_config", - "readableName": "Acquisition Device Connection Method", + "name": "Acquisition Device Connection Method", "helpTip": "Specifies the method used to connect to the data acquisition device (LSL or DSI).", - "recommended_values": ["DSI", "LSL"], + "recommended": ["DSI", "LSL"], + "editable": True, "type": "str" } } @@ -78,8 +80,9 @@ def test_load_data_with_missing_field(self): "fake_data": { "value": "true", "section": "bci_config", - "readableName": "Fake EEG Data On/Off", - "recommended_values": "", + "name": "Fake EEG Data On/Off", + "recommended": "", + "editable": True, "type": "bool" } } @@ -93,9 +96,10 @@ def test_load_data_with_unsupported_type(self): "fake_data": { "value": "true", "section": "bci_config", - "readableName": "Fake EEG Data On/Off", + "name": "Fake EEG Data On/Off", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "custom_type" } } @@ -126,41 +130,46 @@ def test_cast_values(self): "myint": { "value": "1", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "int" }, "mybool": { "value": "true", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "bool" }, "mypath": { "value": "bcipy/parameters/parameters.json", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "directorypath" }, "mystr": { "value": "hello", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "str" }, "my_int_range": { "value": "5:10", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "range" } } @@ -194,9 +203,10 @@ def test_setting_valid_values(self): parameters['mystr'] = { "value": "hello", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "str" } self.assertEqual(len(parameters), 1) @@ -206,16 +216,18 @@ def test_setting_invalid_values(self): missing_help_tip = { "value": "true", "section": "", - "readableName": "", - "recommended_values": "", + "name": "", + "recommended": "", + "editable": True, "type": "bool" } unsupported_type = { "value": "true", "section": "bci_config", - "readableName": "Fake EEG Data On/Off", + "name": "Fake EEG Data On/Off", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "custom_type" } @@ -234,9 +246,10 @@ def test_updating_uncast_values(self): parameters['mystr'] = { "value": "hello", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "str" } parameters['mystr']['value'] = 'hello world' @@ -248,25 +261,28 @@ def test_setting_existing_cast_values(self): "acq_port": { "value": "8000", "section": "acquisition", - "readableName": "Acquisition Port", + "name": "Acquisition Port", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "int" }, "acq_device": { "value": "LSL", "section": "acquisition", - "readableName": "Acquisition Device", + "name": "Acquisition Device", "helpTip": "", - "recommended_values": ["LSL", "DSI"], + "recommended": ["LSL", "DSI"], + "editable": True, "type": "str" }, "is_txt_stim": { "value": "false", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "bool" } } @@ -293,17 +309,19 @@ def test_update(self): "acq_port": { "value": "8000", "section": "acquisition", - "readableName": "Acquisition Port", + "name": "Acquisition Port", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "int" }, "acq_device": { "value": "LSL", "section": "acquisition", - "readableName": "Acquisition Device", + "name": "Acquisition Device", "helpTip": "", - "recommended_values": ["LSL", "DSI"], + "recommended": ["LSL", "DSI"], + "editable": True, "type": "str" } } @@ -326,17 +344,19 @@ def test_values(self): "acq_port": { "value": "8000", "section": "acquisition", - "readableName": "Acquisition Port", + "name": "Acquisition Port", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "int" }, "acq_device": { "value": "LSL", "section": "acquisition", - "readableName": "Acquisition Device", + "name": "Acquisition Device", "helpTip": "", - "recommended_values": ["LSL", "DSI"], + "recommended": ["LSL", "DSI"], + "editable": True, "type": "str" } } @@ -391,9 +411,10 @@ def test_save_new(self): parameters['mystr'] = { "value": "hello", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "str" } with self.assertRaises(Exception): @@ -413,9 +434,10 @@ def test_items(self): parameters['mystr'] = { "value": "hello", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "str" } self.assertEqual(len(parameters.items()), 1) @@ -445,9 +467,10 @@ def test_check_entry(self): "fake_data", { "value": "true", "section": "bci_config", - "readableName": "Fake Data Sessions", + "name": "Fake Data Sessions", "helpTip": "If true, fake data server used", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "bool" }) with self.assertRaises(Exception): @@ -461,9 +484,10 @@ def test_check_entry_bool_type(self): "fake_data", { "value": True, "section": "bci_config", - "readableName": "Fake Data Sessions", + "name": "Fake Data Sessions", "helpTip": "If true, fake data server used", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "bool" }) @@ -487,17 +511,19 @@ def test_add_missing(self): entry1 = { "value": "8000", "section": "acquisition", - "readableName": "Acquisition Port", + "name": "Acquisition Port", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "int" } entry2 = { "value": "LSL", "section": "acquisition", - "readableName": "Acquisition Device", + "name": "Acquisition Device", "helpTip": "", - "recommended_values": ["LSL", "DSI"], + "recommended": ["LSL", "DSI"], + "editable": True, "type": "str" } @@ -519,41 +545,46 @@ def test_changed_parameters(self): entry1 = { "value": "8000", "section": "acquisition", - "readableName": "Acquisition Port", + "name": "Acquisition Port", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "int" } entry2 = { "value": "75E+6", "section": "artifact_rejection", - "readableName": "High Voltage Threshold Value", + "name": "High Voltage Threshold Value", "helpTip": "Specifies the high voltage threshold (in microvolts)", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "float" } entry2_same = { "value": "75000000.0", "section": "artifact_rejection", - "readableName": "High Voltage Threshold Value", + "name": "High Voltage Threshold Value", "helpTip": "Specifies the high voltage threshold (in microvolts)", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "float" } entry3 = { "value": "DSI-24", "section": "acquisition", - "readableName": "Acquisition Device", + "name": "Acquisition Device", "helpTip": "", - "recommended_values": ["DSI-24", "DSI-VR300"], + "recommended": ["DSI-24", "DSI-VR300"], + "editable": True, "type": "str" } entry3_modified = { "value": "DSI-VR300", "section": "acquisition", - "readableName": "Acquisition Device", + "name": "Acquisition Device", "helpTip": "", - "recommended_values": ["DSI-24", "DSI-VR300"], + "recommended": ["DSI-24", "DSI-VR300"], + "editable": True, "type": "str" } parameters = Parameters(source=None) @@ -583,25 +614,28 @@ def test_instantiate_tuple(self): "a": { "value": "1", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": "", + "recommended": "", + "editable": True, "type": "int" }, "b": { "value": "2", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": [], + "recommended": [], + "editable": True, "type": "int" }, "c": { "value": "3", "section": "", - "readableName": "", + "name": "", "helpTip": "", - "recommended_values": [], + "recommended": [], + "editable": True, "type": "str" } } diff --git a/bcipy/helpers/tests/test_raw_data.py b/bcipy/helpers/tests/test_raw_data.py index 803697915..12fc67bb5 100644 --- a/bcipy/helpers/tests/test_raw_data.py +++ b/bcipy/helpers/tests/test_raw_data.py @@ -10,7 +10,7 @@ from mockito import any, mock, when, verify, unstub -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.exceptions import BciPyCoreException from bcipy.helpers.raw_data import (RawData, RawDataReader, RawDataWriter, load, sample_data, settings, write) diff --git a/bcipy/helpers/tests/test_report.py b/bcipy/helpers/tests/test_report.py index 7df690816..3d28833d4 100644 --- a/bcipy/helpers/tests/test_report.py +++ b/bcipy/helpers/tests/test_report.py @@ -30,7 +30,8 @@ def test_init_no_name_default(self): self.assertEqual(report.name, Report.DEFAULT_NAME) def test_init_sections(self): - report_section = SessionReportSection() + summary = {} + report_section = SessionReportSection(summary) section = [report_section] report = Report(self.temp_dir, sections=section) self.assertEqual(report.sections, section) @@ -64,7 +65,8 @@ def test_add_section(self): def test_save(self): report = Report(self.temp_dir) - report_section = SessionReportSection() + summary = {} + report_section = SessionReportSection(summary) report.add(report_section) report.save() self.assertTrue(os.path.exists(os.path.join(self.temp_dir, report.name))) @@ -113,7 +115,8 @@ def setUp(self) -> None: } def test_init(self): - report_section = SessionReportSection() + summary = {} + report_section = SessionReportSection(summary) self.assertIsInstance(report_section, ReportSection) self.assertIsNotNone(report_section.style) @@ -124,7 +127,8 @@ def test_create_summary_text(self): self.assertIsInstance(table, Flowable) def test_create_header(self): - report_section = SessionReportSection() + summary = {} + report_section = SessionReportSection(summary) header = report_section._create_header() self.assertIsInstance(header, Paragraph) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 201951410..2c1dc5b2f 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -9,7 +9,7 @@ from mockito import any, mock, unstub, verify, when from psychopy import core -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.exceptions import BciPyCoreException from bcipy.helpers.stimuli import (DEFAULT_FIXATION_PATH, InquiryReshaper, StimuliOrder, TargetPositions, TrialReshaper, alphabetize, diff --git a/bcipy/helpers/tests/test_triggers.py b/bcipy/helpers/tests/test_triggers.py index 9b9d2a59a..478015733 100644 --- a/bcipy/helpers/tests/test_triggers.py +++ b/bcipy/helpers/tests/test_triggers.py @@ -5,7 +5,7 @@ import psychopy from mockito import any, mock, unstub, verify, when -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.exceptions import BciPyCoreException from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, _calibration_trigger, apply_offsets, exclude_types, diff --git a/bcipy/helpers/tests/test_validate.py b/bcipy/helpers/tests/test_validate.py index dc398178d..0c7c6a8f6 100644 --- a/bcipy/helpers/tests/test_validate.py +++ b/bcipy/helpers/tests/test_validate.py @@ -2,8 +2,7 @@ from bcipy.config import DEFAULT_EXPERIMENT_ID from bcipy.helpers.validate import validate_experiment, validate_experiments -from bcipy.helpers.save import save_experiment_data -from bcipy.helpers.exceptions import ( +from bcipy.exceptions import ( InvalidExperimentException, InvalidFieldException, UnregisteredExperimentException, @@ -26,24 +25,6 @@ def test_validate_experiment_throws_unregistered_expection_on_unregistered_exper with self.assertRaises(UnregisteredExperimentException): validate_experiment(experiment_name) - def test_save_experiment_data_throws_unregistered_exception_on_unregistered_fields(self): - # create a fake experiment to load - experiment_name = 'test' - fields = { - 'registered_field': { - 'help_text': 'test', - 'type': 'int' - } - } - experiment = { - experiment_name: { - 'fields': [{'does_not_exist': {'required': 'false', 'anonymize': 'true'}}], 'summary': ''} - } - - # assert it raises the expected exception - with self.assertRaises(UnregisteredFieldException): - save_experiment_data(experiment, fields, '.', 'test_experiment.json') - def test_validate_experiment_throws_file_not_found_with_incorrect_experiment_path(self): # define an invalid path path = 'does/not/exist' @@ -71,7 +52,9 @@ class TestValidateExperiments(unittest.TestCase): } experiments = { experiment_name: { - 'fields': [{'registered_field': {'required': 'false', 'anonymize': 'true'}}], 'summary': ''} + 'fields': [{'registered_field': {'required': 'false', 'anonymize': 'true'}}], + 'summary': '', + 'protocol': ''} } def test_validate_experiments_returns_true_on_valid_experiment(self): @@ -82,7 +65,8 @@ def test_validate_experiments_returns_true_on_valid_experiment(self): def test_validate_experiments_throws_invalid_experiment_exception_on_invalid_experiment_no_field(self): experiments = { 'invalid': { - 'summary': ''} + 'summary': '', + 'protocol': ''} } with self.assertRaises(InvalidExperimentException): validate_experiments(experiments, self.fields) @@ -91,7 +75,7 @@ def test_validate_experiments_throws_invalid_experiment_exception_on_invalid_exp experiments = { 'invalid': { 'summary': '', - 'fields': 'should_be_list!'} + 'fields': 'should_be_list!', 'protocol': ''} } with self.assertRaises(InvalidExperimentException): validate_experiments(experiments, self.fields) @@ -100,7 +84,7 @@ def test_validate_experiments_throws_invalid_experiment_exception_on_invalid_exp experiments = { 'invalid': { 'summary': [], - 'fields': []} + 'fields': [], 'protocol': ''} } with self.assertRaises(InvalidExperimentException): validate_experiments(experiments, self.fields) @@ -108,7 +92,7 @@ def test_validate_experiments_throws_invalid_experiment_exception_on_invalid_exp def test_validate_experiments_throws_invalid_experiment_exception_on_invalid_experiment_no_summary(self): experiments = { 'invalid': { - 'fields': []} + 'fields': [], 'protocol': ''} } with self.assertRaises(InvalidExperimentException): validate_experiments(experiments, self.fields) @@ -116,7 +100,7 @@ def test_validate_experiments_throws_invalid_experiment_exception_on_invalid_exp def test_validate_experiments_throws_invalid_field_exception_on_invalid_field_no_required(self): experiments = { self.experiment_name: { - 'fields': [{'registered_field': {'anonymize': 'true'}}], 'summary': ''} + 'fields': [{'registered_field': {'anonymize': 'true'}}], 'summary': '', 'protocol': ''} } with self.assertRaises(InvalidFieldException): validate_experiments(experiments, self.fields) @@ -124,7 +108,7 @@ def test_validate_experiments_throws_invalid_field_exception_on_invalid_field_no def test_validate_experiments_throws_invalid_field_exception_on_invalid_field_no_anonymize(self): experiments = { self.experiment_name: { - 'fields': [{'registered_field': {'required': 'true'}}], 'summary': ''} + 'fields': [{'registered_field': {'required': 'true'}}], 'summary': '', 'protocol': ''} } with self.assertRaises(InvalidFieldException): validate_experiments(experiments, self.fields) @@ -132,7 +116,9 @@ def test_validate_experiments_throws_invalid_field_exception_on_invalid_field_no def test_validate_experiments_throws_unregistered_exception_on_unregistered_fields(self): experiment = { self.experiment_name: { - 'fields': [{'does_not_exist': {'required': 'false', 'anonymize': 'true'}}], 'summary': ''} + 'fields': [{'does_not_exist': {'required': 'false', 'anonymize': 'true'}}], + 'summary': '', + 'protocol': ''} } # assert it raises the expected exception diff --git a/bcipy/helpers/triggers.py b/bcipy/helpers/triggers.py index 259b46d69..47624ffc3 100644 --- a/bcipy/helpers/triggers.py +++ b/bcipy/helpers/triggers.py @@ -5,13 +5,13 @@ from psychopy import core, visual -from bcipy.config import DEFAULT_ENCODING +from bcipy.config import DEFAULT_ENCODING, SESSION_LOG_FILENAME from bcipy.helpers.clock import Clock -from bcipy.helpers.exceptions import BciPyCoreException +from bcipy.exceptions import BciPyCoreException from bcipy.helpers.parameters import Parameters from bcipy.helpers.stimuli import resize_image -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) NONE_VALUES = ['0', '0.0'] diff --git a/bcipy/helpers/validate.py b/bcipy/helpers/validate.py index d9d47a4d9..7e6e75520 100644 --- a/bcipy/helpers/validate.py +++ b/bcipy/helpers/validate.py @@ -7,11 +7,12 @@ FIELD_FILENAME) from bcipy.helpers.load import load_experiments, load_fields from bcipy.helpers.system_utils import is_battery_powered, is_connected, is_screen_refresh_rate_low -from bcipy.helpers.exceptions import (InvalidFieldException, - InvalidExperimentException, - UnregisteredExperimentException, - UnregisteredFieldException) +from bcipy.exceptions import (InvalidFieldException, + InvalidExperimentException, + UnregisteredExperimentException, + UnregisteredFieldException) from bcipy.gui.alert import confirm +from bcipy.task.orchestrator.protocol import validate_protocol_string def validate_bcipy_session(parameters: dict, fake_data: bool) -> bool: @@ -46,7 +47,7 @@ def validate_experiment( experiment_name: str, experiment_path: str = f'{DEFAULT_EXPERIMENT_PATH}/{EXPERIMENT_FILENAME}', field_path: str = f'{DEFAULT_FIELD_PATH}/{FIELD_FILENAME}' -) -> bool: +) -> dict: """Validate Experiment. Validate the experiment is in the correct format and the fields are properly registered. @@ -65,7 +66,7 @@ def validate_experiment( _validate_experiment_format(experiment, experiment_name) _validate_experiment_fields(experiment['fields'], fields) - return True + return experiment def _validate_experiment_fields(experiment_fields, fields): @@ -118,6 +119,9 @@ def _validate_experiment_format(experiment, name): assert isinstance(exp_summary, str) experiment_fields = experiment['fields'] assert isinstance(experiment_fields, list) + protocol = experiment['protocol'] + if protocol: + validate_protocol_string(protocol) except KeyError: raise InvalidExperimentException( f'Experiment [{name}] is formatted incorrectly. It should contain the keys: summary and fields.') diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 38815a95d..2c4402736 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -9,6 +9,7 @@ import numpy as np import pandas as pd import seaborn as sns + from matplotlib.figure import Figure from matplotlib.patches import Ellipse from mne import Epochs @@ -18,10 +19,11 @@ import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, DEFAULT_GAZE_IMAGE_PATH, RAW_DATA_FILENAME, - TRIGGER_FILENAME) + TRIGGER_FILENAME, SESSION_LOG_FILENAME, + DEFAULT_PARAMETERS_PATH) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.convert import convert_to_mne -from bcipy.helpers.load import choose_csv_file, load_raw_data +from bcipy.helpers.load import choose_csv_file, load_raw_data, load_json_parameters from bcipy.helpers.parameters import Parameters from bcipy.helpers.raw_data import RawData from bcipy.helpers.stimuli import mne_epochs @@ -29,7 +31,7 @@ from bcipy.signal.process import (Composition, ERPTransformParams, get_default_transform) -log = logging.getLogger(__name__) +logger = logging.getLogger(SESSION_LOG_FILENAME) def clip_to_display(data, screen_limits): @@ -597,7 +599,7 @@ def visualize_csv_eeg_triggers(trigger_col: Optional[int] = None): plt.ylabel('Trigger Value') plt.xlabel('Samples') - log.info('Press Ctrl + C to exit!') + logger.info('Press Ctrl + C to exit!') # Show us the figure! Depending on your OS / IDE this may not close when # The window is closed, see the message above plt.show() @@ -666,7 +668,11 @@ def visualize_evokeds(epochs: Tuple[Epochs, Epochs], return fig -def visualize_session_data(session_path: str, parameters: Union[dict, Parameters], show=True) -> Figure: +def visualize_session_data( + session_path: str, + parameters: Union[dict, Parameters], + show=True, + save=True) -> Figure: """Visualize Session Data. This method is used to load and visualize EEG data after a session. @@ -683,6 +689,7 @@ def visualize_session_data(session_path: str, parameters: Union[dict, Parameters Output: Figure of Session Data """ + logger.info(f"Visualizing session data at {session_path}") # extract all relevant parameters trial_window = parameters.get("trial_window") @@ -728,7 +735,7 @@ def visualize_session_data(session_path: str, parameters: Union[dict, Parameters transform=default_transform, plot_average=True, plot_topomaps=True, - save_path=session_path, + save_path=session_path if save else None, show=show, ) @@ -752,3 +759,34 @@ def visualize_gaze_accuracies(accuracy_dict: Dict[str, np.ndarray], ax.set_title('Overall Accuracy: ' + str(round(accuracy, 2))) return fig + + +def erp(): + import argparse + + parser = argparse.ArgumentParser(description='Visualize ERP data') + + parser.add_argument( + '-s', '--session_path', + type=str, + help='Path to the session directory', + required=True) + parser.add_argument( + '-p', '--parameters', + type=str, + help='Path to the parameters file', + default=DEFAULT_PARAMETERS_PATH) + parser.add_argument( + '--show', + action='store_true', + help='Whether to show the figure', + default=False) + parser.add_argument( + '--save', + action='store_true', + help='Whether to save the figure', default=True) + + args = parser.parse_args() + + parameters = load_json_parameters(args.parameters, value_cast=True) + visualize_session_data(args.session_path, parameters, args.show, args.save) diff --git a/bcipy/language/demo/demo_kenlm.py b/bcipy/language/demo/demo_kenlm.py index d613c8aa1..d90421e42 100644 --- a/bcipy/language/demo/demo_kenlm.py +++ b/bcipy/language/demo/demo_kenlm.py @@ -4,7 +4,7 @@ from bcipy.helpers.symbols import alphabet from bcipy.language.main import ResponseType from bcipy.config import LM_PATH -from bcipy.helpers.exceptions import KenLMInstallationException +from bcipy.exceptions import KenLMInstallationException try: import kenlm diff --git a/bcipy/language/main.py b/bcipy/language/main.py index 84230c417..8a1922338 100644 --- a/bcipy/language/main.py +++ b/bcipy/language/main.py @@ -4,7 +4,7 @@ from typing import List, Optional, Tuple import json -from bcipy.helpers.exceptions import UnsupportedResponseType +from bcipy.exceptions import UnsupportedResponseType from bcipy.helpers.symbols import DEFAULT_SYMBOL_SET from bcipy.config import DEFAULT_LM_PARAMETERS_PATH diff --git a/bcipy/language/model/causal.py b/bcipy/language/model/causal.py index 6e7aa2b51..677215369 100644 --- a/bcipy/language/model/causal.py +++ b/bcipy/language/model/causal.py @@ -8,7 +8,7 @@ from bcipy.helpers.symbols import BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.main import LanguageModel, ResponseType -from bcipy.helpers.exceptions import InvalidLanguageModelException +from bcipy.exceptions import InvalidLanguageModelException from scipy.special import logsumexp from scipy.special import softmax diff --git a/bcipy/language/model/kenlm.py b/bcipy/language/model/kenlm.py index 8da4ea8c8..1c95241e7 100644 --- a/bcipy/language/model/kenlm.py +++ b/bcipy/language/model/kenlm.py @@ -2,7 +2,7 @@ from typing import Optional, List, Tuple from bcipy.helpers.symbols import BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.main import LanguageModel, ResponseType -from bcipy.helpers.exceptions import InvalidLanguageModelException, KenLMInstallationException +from bcipy.exceptions import InvalidLanguageModelException, KenLMInstallationException from bcipy.config import LM_PATH try: import kenlm diff --git a/bcipy/language/model/mixture.py b/bcipy/language/model/mixture.py index 8a7bd2548..2220c029a 100644 --- a/bcipy/language/model/mixture.py +++ b/bcipy/language/model/mixture.py @@ -4,7 +4,7 @@ from bcipy.language.main import LanguageModel, ResponseType -from bcipy.helpers.exceptions import InvalidLanguageModelException +from bcipy.exceptions import InvalidLanguageModelException # pylint: disable=unused-import # flake8: noqa diff --git a/bcipy/language/model/oracle.py b/bcipy/language/model/oracle.py index 42b5cc560..a23e4789e 100644 --- a/bcipy/language/model/oracle.py +++ b/bcipy/language/model/oracle.py @@ -4,11 +4,12 @@ import numpy as np +from bcipy.config import SESSION_LOG_FILENAME from bcipy.helpers.symbols import BACKSPACE_CHAR from bcipy.language.main import LanguageModel, ResponseType from bcipy.language.model.uniform import equally_probable -logger = logging.getLogger() +logger = logging.getLogger(SESSION_LOG_FILENAME) TARGET_BUMP_MIN = 0.0 TARGET_BUMP_MAX = 0.95 diff --git a/bcipy/language/model/unigram.py b/bcipy/language/model/unigram.py index 4222898c2..9e61e213c 100644 --- a/bcipy/language/model/unigram.py +++ b/bcipy/language/model/unigram.py @@ -1,7 +1,7 @@ from typing import Optional, List, Tuple from bcipy.helpers.symbols import BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.main import LanguageModel, ResponseType -from bcipy.helpers.exceptions import InvalidLanguageModelException +from bcipy.exceptions import InvalidLanguageModelException import json from bcipy.config import LM_PATH diff --git a/bcipy/language/tests/test_causal.py b/bcipy/language/tests/test_causal.py index 561b3a03a..b1d7ed191 100644 --- a/bcipy/language/tests/test_causal.py +++ b/bcipy/language/tests/test_causal.py @@ -4,7 +4,7 @@ import unittest from operator import itemgetter -from bcipy.helpers.exceptions import UnsupportedResponseType, InvalidLanguageModelException +from bcipy.exceptions import UnsupportedResponseType, InvalidLanguageModelException from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.model.causal import CausalLanguageModel from bcipy.language.main import ResponseType diff --git a/bcipy/language/tests/test_kenlm.py b/bcipy/language/tests/test_kenlm.py index 1e0a81e36..a0cc4805b 100644 --- a/bcipy/language/tests/test_kenlm.py +++ b/bcipy/language/tests/test_kenlm.py @@ -5,7 +5,7 @@ import os from operator import itemgetter -from bcipy.helpers.exceptions import UnsupportedResponseType, InvalidLanguageModelException +from bcipy.exceptions import UnsupportedResponseType, InvalidLanguageModelException from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.model.kenlm import KenLMLanguageModel from bcipy.language.main import ResponseType diff --git a/bcipy/language/tests/test_mixture.py b/bcipy/language/tests/test_mixture.py index 6f383c8f7..53c160212 100644 --- a/bcipy/language/tests/test_mixture.py +++ b/bcipy/language/tests/test_mixture.py @@ -5,7 +5,7 @@ import os from operator import itemgetter -from bcipy.helpers.exceptions import UnsupportedResponseType, InvalidLanguageModelException +from bcipy.exceptions import UnsupportedResponseType, InvalidLanguageModelException from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR, SPACE_CHAR from bcipy.language.model.mixture import MixtureLanguageModel from bcipy.language.main import ResponseType diff --git a/bcipy/language/tests/test_unigram.py b/bcipy/language/tests/test_unigram.py index 858849aa8..7a07b002e 100644 --- a/bcipy/language/tests/test_unigram.py +++ b/bcipy/language/tests/test_unigram.py @@ -4,7 +4,7 @@ import unittest import os -from bcipy.helpers.exceptions import UnsupportedResponseType, InvalidLanguageModelException +from bcipy.exceptions import UnsupportedResponseType, InvalidLanguageModelException from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR from bcipy.language.model.unigram import UnigramLanguageModel from bcipy.language.main import ResponseType diff --git a/bcipy/main.py b/bcipy/main.py index 2a9d1bfc4..211c4e370 100644 --- a/bcipy/main.py +++ b/bcipy/main.py @@ -1,220 +1,110 @@ import argparse import logging import multiprocessing -from typing import List, Optional +from typing import Type, Optional -from psychopy import visual - -from bcipy.acquisition import ClientManager, LslDataServer -from bcipy.config import (DEFAULT_EXPERIMENT_ID, DEFAULT_PARAMETERS_PATH, - STATIC_AUDIO_PATH) -from bcipy.display import init_display_window -from bcipy.helpers.acquisition import init_eeg_acquisition -from bcipy.helpers.language_model import init_language_model -from bcipy.helpers.load import (load_experiments, load_json_parameters, - load_signal_models) -from bcipy.helpers.save import init_save_data_structure -from bcipy.helpers.session import collect_experiment_field_data -from bcipy.helpers.stimuli import play_sound -from bcipy.helpers.system_utils import configure_logger, get_system_info -from bcipy.helpers.task import print_message +from bcipy.config import (DEFAULT_PARAMETERS_PATH, CUSTOM_TASK_EXPERIMENT_ID) +from bcipy.exceptions import BciPyCoreException +from bcipy.helpers.load import (load_experiments, load_json_parameters) from bcipy.helpers.validate import validate_bcipy_session, validate_experiment -from bcipy.helpers.visualization import visualize_session_data -from bcipy.task import TaskType -from bcipy.task.start_task import start_task +from bcipy.task import TaskRegistry, Task +from bcipy.task.orchestrator import SessionOrchestrator +from bcipy.task.orchestrator.protocol import parse_protocol -log = logging.getLogger(__name__) +logger = logging.getLogger(__name__) def bci_main( parameter_location: str, user: str, - task: TaskType, - experiment: str = DEFAULT_EXPERIMENT_ID, + experiment_id: Optional[str] = None, alert: bool = False, visualize: bool = True, - fake: bool = False) -> bool: + fake: bool = False, + task: Optional[Type[Task]] = None) -> bool: """BCI Main. The BCI main function will initialize a save folder, construct needed information and execute the task. This is the main connection between any UI and running the app. + A Task or Experiment ID must be provided to run the task. If a task is provided, the experiment + ID will be ignored. + It may also be invoked via tha command line. Ex. `bcipy` this will default parameters, mode, user, and type. You can pass it those attributes with flags, if desired. - Ex. `bcipy --user "bci_user" --task "RSVP Calibration" --experiment "default" + Ex. `bcipy --user "bci_user" --task "RSVP Calibration" + Input: parameter_location (str): location of parameters file to use user (str): name of the user - task (TaskType): registered bcipy TaskType - experiment_id (str): Name of the experiment. Default name is DEFAULT_EXPERIMENT_ID. + experiment_id (str): Name of the experiment. If task is provided, this will be ignored. alert (bool): whether to alert the user when the task is complete visualize (bool): whether to visualize data at the end of a task fake (bool): whether to use fake acquisition data during the session. If None, the fake data will be determined by the parameters file. + task (Task): registered bcipy Task to execute. If None, the task will be determined by the + experiment protocol. """ - validate_experiment(experiment) + logger.info('Starting BciPy...') + logger.info( + f'User: {user} | Experiment: {experiment_id} | Task: {task} | ' + f'Parameters: {parameter_location} | ' + f'Alert: {alert} | Visualize: {visualize} | Fake: {fake}') + # If no task is provided, extract the tasks from the experiment protocol. Otherwise, we will assume + # the task is a custom task execution with no experiment attached. + if not task and experiment_id: + experiment = validate_experiment(experiment_id) + # extract protocol from experiment + tasks = parse_protocol(experiment['protocol']) + elif task: + tasks = [task] + experiment_id = CUSTOM_TASK_EXPERIMENT_ID + else: + msg = 'No experiment or task provided to BciPy.' + logger.exception(msg) + raise BciPyCoreException(msg) + # Load parameters parameters = load_json_parameters(parameter_location, value_cast=True) # cli overrides parameters file for fake data if provided fake = fake if fake is True else parameters['fake_data'] + parameters['fake_data'] = fake if not validate_bcipy_session(parameters, fake): return False - # Update property to reflect the parameter source + # Update property to reflect the parameter source: parameters['parameter_location'] = parameter_location if parameter_location != DEFAULT_PARAMETERS_PATH: parameters.save() - default_params = load_json_parameters(DEFAULT_PARAMETERS_PATH, value_cast=True) - if parameters.add_missing_items(default_params): - msg = 'Parameters file out of date.' - log.exception(msg) - raise Exception(msg) - - # update our parameters file with system related information - sys_info = get_system_info() - - # Initialize Save Folder - save_folder = init_save_data_structure( - parameters['data_save_loc'], - user, - parameter_location, - task=task.label, - experiment_id=experiment) - - # configure bcipy session logging - configure_logger(save_folder, - version=sys_info['bcipy_version']) - - log.info(sys_info) - - # Collect experiment field data - collect_experiment_field_data(experiment, save_folder) - - if execute_task(task, parameters, save_folder, alert, fake): - if visualize: - - # Visualize session data and fail silently if it errors - try: - visualize_session_data(save_folder, parameters) - except Exception as e: - log.info(f'Error visualizing session data: {e}') - return True - - return False - - -def execute_task( - task: TaskType, - parameters: dict, - save_folder: str, - alert: bool, - fake: bool) -> bool: - """Execute Task. - - Executes the desired task by setting up the display window and - data acquisition, then passing on to the start_task function - which will initialize experiment. - - Input: - task(TaskType): Task that should be registered in TaskType - parameters (dict): parameter dictionary - save_folder (str): path to save folder - alert (bool): whether to alert the user when the task is complete - fake (bool): whether to use fake acquisition data during the session - - Returns: - (bool): True if the task was successfully executed, False otherwise - """ - signal_models = [] - language_model = None - # Init EEG Model, if needed. Calibration Tasks Don't require probabilistic - # modules to be loaded. - if task not in TaskType.calibration_tasks(): - # Try loading in our signal_model and starting a langmodel(if enabled) - if not fake: - try: - model_dir = parameters['signal_model_path'] - signal_models = load_signal_models(directory=model_dir) - assert signal_models, f"No signal models found in {model_dir}" - except Exception as error: - log.exception(f'Cannot load signal model. Exiting. {error}') - raise error + # Initialize an orchestrator + orchestrator = SessionOrchestrator( + experiment_id=experiment_id, + user=user, + parameters_path=parameter_location, + parameters=parameters, + fake=fake, + alert=alert, + visualize=visualize, + ) + orchestrator.add_tasks(tasks) - language_model = init_language_model(parameters) - - # Initialize DAQ and export the device configuration - daq, servers = init_eeg_acquisition( - parameters, save_folder, server=fake) - - # Initialize Display Window - # We have to wait until after the prompt to load the signal model before - # displaying the window, otherwise in fullscreen mode this throws an error - display = init_display_window(parameters) - print_message(display, f'Initializing {task}...') - - # Start Task try: - start_task(display, - daq, - task, - parameters, - save_folder, - language_model=language_model, - signal_models=signal_models, - fake=fake) - - # If exception, close all display and acquisition objects + orchestrator.execute() except Exception as e: - log.exception(str(e)) - - if alert: - play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") - - return _clean_up_session(display, daq, servers) - - -def _clean_up_session( - display: visual.Window, - daq: ClientManager, - servers: Optional[List[LslDataServer]] = None) -> bool: - """Clean up session. - - Closes the display window and data acquisition objects. Returns True if the session was closed successfully. - - Input: - display (visual.Window): display window - daq (LslAcquisitionClient): data acquisition client - server (LslDataServer): data server - """ - try: - # Stop Acquisition - daq.stop_acquisition() - daq.cleanup() - - # Stop Servers - if servers: - for server in servers: - server.stop() - - # Close the display window - # NOTE: There is currently a bug in psychopy when attempting to shutdown - # windows when using a USB-C monitor. Putting the display close last in - # the inquiry allows acquisition to properly shutdown. - display.close() - return True - except Exception as e: - log.exception(str(e)) + logger.exception(f'Error executing task: {e}') return False + return True + -def bcipy_main() -> None: +def bcipy_main() -> None: # pragma: no cover """BciPy Main. Command line interface used for running a registered experiment task in BciPy. To see what @@ -222,21 +112,22 @@ def bcipy_main() -> None: """ # Needed for windows machines multiprocessing.freeze_support() - + tr = TaskRegistry() experiment_options = list(load_experiments().keys()) - task_options = TaskType.list() + task_options = tr.list() parser = argparse.ArgumentParser() # Command line utility for adding arguments/ paths via command line parser.add_argument('-p', '--parameters', default=DEFAULT_PARAMETERS_PATH, help='Parameter location. Pass as *.json') parser.add_argument('-u', '--user', default='test_user') - parser.add_argument('-t', '--task', default='RSVP Calibration', - help=f'Task type to execute. Registered options: {task_options}') + parser.add_argument('-t', '--task', required=False, + help=f'Task type to execute. Registered options: {task_options}', + choices=task_options) parser.add_argument( '-e', '--experiment', - default=DEFAULT_EXPERIMENT_ID, + required=False, help=f'Select a valid experiment to run the task for this user. Available options: {experiment_options}') parser.add_argument( '-a', @@ -258,9 +149,20 @@ def bcipy_main() -> None: help='Use fake acquisition data for testing.') args = parser.parse_args() + if args.task: + task = tr.get(args.task) + else: + task = None + # Start BCI Main - bci_main(args.parameters, str(args.user), TaskType.by_value(str(args.task)), - str(args.experiment), args.alert, args.noviz, args.fake) + bci_main( + args.parameters, + str(args.user), + str(args.experiment), + args.alert, + args.noviz, + args.fake, + task) if __name__ == '__main__': diff --git a/bcipy/parameters/experiment/experiments.json b/bcipy/parameters/experiment/experiments.json index 8b3e2cf6c..add8e1184 100644 --- a/bcipy/parameters/experiment/experiments.json +++ b/bcipy/parameters/experiment/experiments.json @@ -1,6 +1,12 @@ { "default": { "fields": [], - "summary": "Default experiment to test various BciPy features without registering a full experiment." + "summary": "Default experiment to test various BciPy features without registering a full experiment.", + "protocol": "RSVP Calibration -> Matrix Calibration" + }, + "BCIOne": { + "fields": [], + "summary": "BCIOne experiment", + "protocol": "RSVP Calibration -> IntertaskAction -> OfflineAnalysisAction -> IntertaskAction -> Matrix Calibration -> IntertaskAction -> OfflineAnalysisAction -> IntertaskAction -> BciPy Report Action" } } \ No newline at end of file diff --git a/bcipy/parameters/experiment/phrases.json b/bcipy/parameters/experiment/phrases.json new file mode 100644 index 000000000..4ec1ea70e --- /dev/null +++ b/bcipy/parameters/experiment/phrases.json @@ -0,0 +1,13 @@ +{ + "Phrases" : [ + ["HELLO_WORLD", 0], + ["GOOD_MORNING", 1], + ["GOOD_AFTERNOON", 5], + ["GOOD_EVENING", 0], + ["GOOD_NIGHT", 5], + ["HOW_ARE_YOU", 4], + ["I_AM_FINE", 5], + ["THANK_YOU", 6], + ["WELCOME_HOME", 8] + ] +} \ No newline at end of file diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 19756cefd..296d91858 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -1,772 +1,893 @@ { "fake_data": { "value": "false", - "section": "bci_config", - "readableName": "Fake EEG Data On/Off", + "section": "acq_config", + "name": "Fake EEG Data", "helpTip": "If ‘true’, fake EEG data will be used instead of real EEG data. Useful for testing by software development team.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "bool" }, "acq_mode": { "value": "EEG", "section": "acq_config", - "readableName": "Acquisition Mode", + "name": "Acquisition Mode", "helpTip": "Specifies the hardware device(s) used for data collection. Default: EEG.", - "recommended_values": [ + "recommended": [ "EEG", "EEG/DSI-24", "Eyetracker", "EEG+Eyetracker", "EEG+Eyetracker:passive" ], + "editable": false, "type": "str" }, "trigger_type": { "value": "text", "section": "bci_config", - "readableName": "Trigger Stimulus Type", - "helpTip": "Specifies whether to use a picture or auditory stimulus to calibrate trigger latency. Default: text", - "recommended_values": [ + "name": "Trigger Stimulus Type", + "helpTip": "Specifies whether to use text, image or auditory stimulus to calibrate trigger latency. Default: text", + "recommended": [ "image", "text" ], + "editable": false, "type": "str" }, "k_folds": { "value": "10", - "section": "signal_config", - "readableName": "Number of Cross-Validation Folds", + "section": "model_config", + "name": "Number of Cross-Validation Folds", "helpTip": "Specifies the number of folds used for cross-validation when calculating AUC. Default: 10", - "recommended_values": "[10]", + "recommended": "[10]", + "editable": false, "type": "int" }, "trial_window": { "value": "0.0:0.5", - "section": "bci_config", - "readableName": "Trial Classification Window Length", + "section": "signal_config", + "name": "Trial Classification Window Length", "helpTip": "Specifies the window (in seconds) of the EEG data collection window after each stimulus presentation. Default: 0.0:0.5", - "recommended_values": [ + "recommended": [ "0.0:0.5", "0.0:0.8", "0.2:0.8" ], + "editable": false, "type": "range" }, "prestim_length": { "value": "1", - "section": "bci_config", - "readableName": "Prestimulus Window Length", + "section": "signal_config", + "name": "Prestimulus Window Length", "helpTip": "Specifies the length (in seconds) of the EEG data window to return before inquiry presentation. Default: 1", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "alert_sound_file": { "value": "beep.wav", - "section": "bci_config", - "readableName": "Alert Tone", + "section": "task_config", + "name": "Alert Tone", "helpTip": "Specifies the path to an audio file to be played as an alert tone when experiments or offline analysis is complete. Default: beep.wav", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "filepath" }, "signal_model_path": { "value": "", - "section": "bci_config", - "readableName": "Signal Model Path", + "section": "model_config", + "name": "Signal Model Path", "helpTip": "Directory of the pre-trained signal model. This is often the the calibration session directory.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "directorypath" }, "filter_high": { "value": "20", "section": "signal_config", - "readableName": "High Frequency Filter Cutoff", + "name": "High Frequency Filter Cutoff", "helpTip": "Specifies the frequency bound (in Hz) of the low-pass filter (high cutoff). Default: 20", - "recommended_values": [ + "recommended": [ "20", "45", "50" ], + "editable": false, "type": "float" }, "filter_low": { "value": "1", "section": "signal_config", - "readableName": "Low Frequency Filter Cutoff", + "name": "Low Frequency Filter Cutoff", "helpTip": "Specifies the frequency bound (in Hz) of the high-pass filter (low cutoff). Default: 1", - "recommended_values": [ + "recommended": [ "1", "2" ], + "editable": false, "type": "float" }, "filter_order": { "value": "2", "section": "signal_config", - "readableName": "Filter Order", + "name": "Filter Order", "helpTip": "Specifies the slope of the low-pass and high-pass filters. Default: 2", - "recommended_values": [ + "recommended": [ "2", "3" ], + "editable": false, "type": "float" }, "notch_filter_frequency": { "value": "60", "section": "signal_config", - "readableName": "Notch Filter Frequency", + "name": "Notch Filter Frequency", "helpTip": "Specifies the frequency (in Hz) of the notch filter used to remove electrical artifact from the surrounding environment. Default: 60", - "recommended_values": [ + "recommended": [ "59", "60" ], + "editable": false, "type": "float" }, "down_sampling_rate": { "value": "2", "section": "signal_config", - "readableName": "Downsampling Rate", + "name": "Downsampling Rate", "helpTip": "Specifies the decimation factor (integer only) for downsampling of EEG data. Default: 2", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, - "artifact_rejection": { - "value": "false", - "section": "artifact_rejection", - "readableName": "Artifact Rejection On/Off", - "helpTip": "If ‘true’, the system will detect and reject inquiries containing unwanted artifacts (e.g. blinks). This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "bool" - }, - "high_voltage_threshold": { - "value": "false", - "section": "artifact_rejection", - "readableName": "High Voltage Threshold On/Off", - "helpTip": "If ‘true’, an upper voltage threshold will be set for artifact rejection. Detection of values above the specified threshold will trigger rejection of a inquiry. This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "bool" - }, - "high_voltage_value": { - "value": "75000000.0", - "section": "artifact_rejection", - "readableName": "High Voltage Threshold Value", - "helpTip": "Specifies the high voltage threshold (in microvolts) for artifact rejection (High Voltage Threshold must be set to ‘true’). Default: 75E+6. This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "float" - }, - "low_voltage_threshold": { - "value": "false", - "section": "artifact_rejection", - "readableName": "Low Voltage Threshold On/Off", - "helpTip": "If ‘true’, a lower voltage threshold will be set for artifact rejection. Detection of values below the specified threshold will trigger rejection of a inquiry. This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "bool" - }, - "low_voltage_value": { - "value": "-0.000075", - "section": "artifact_rejection", - "readableName": "LowVoltage Threshold Value", - "helpTip": "Specifies the low voltage threshold (in microvolts) for artifact rejection (Low Voltage Threshold must be set to ‘true’). Default: -75E-6 This is not implemented in the current version of the system.", - "recommended_values": "", - "type": "float" - }, "summarize_session": { "value": "true", - "section": "bci_config", - "readableName": "Summarize Session Data", + "section": "task_config", + "name": "Summarize Session Data", "helpTip": "If 'true', writes an Excel file which summarizes the session data by charting evidence per inquiry.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "bool" }, "parameter_location": { "value": "bcipy/parameters/parameters.json", - "section": "bci_config", - "readableName": "Parameter File", + "section": "task_config", + "name": "Parameter File", "helpTip": "Specifies the file containing the current system parameters. Default: bcipy/parameters/parameters.json", - "recommended_values": [ + "recommended": [ "parameters/parameters.json" ], + "editable": false, "type": "filepath" }, "data_save_loc": { "value": "data/", "section": "bci_config", - "readableName": "Data Save Location", + "name": "Data Save Location", "helpTip": "Specifies the location in which to save data files after each recording. This must be a directory ending with /. Default: data/", - "recommended_values": [ + "recommended": [ "data/" ], + "editable": false, "type": "directorypath" }, "full_screen": { "value": "false", - "section": "bci_config", - "readableName": "Full Screen Mode On/Off", + "section": "task_config", + "name": "Full Screen Mode", "helpTip": "If ‘true’, the task will be displayed in full screen mode. If ‘false’, the task will be displayed in a window.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "bool" }, "window_height": { "value": "500", - "section": "bci_config", - "readableName": "Task Window Height", + "section": "task_config", + "name": "Task Window Height", "helpTip": "Specifies the height (in norm units) of the task window when not in full screen mode (Full Screen Mode On/Off must be set to ‘false’). See https://www.psychopy.org/general/units.html. Default: 500", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "window_width": { "value": "500", - "section": "bci_config", - "readableName": "Task Window Width", + "section": "task_config", + "name": "Task Window Width", "helpTip": "Specifies the width (in norm units) of the task window when not in full screen mode (Full Screen Mode On/Off must be set to ‘false’). See https://www.psychopy.org/general/units.html. Default: 500", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "matrix_rows": { "value": "5", - "section": "bci_config", - "readableName": "Matrix Rows", + "section": "matrix_task_config", + "name": "Matrix Rows", "helpTip": "Specifies the number of rows to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "matrix_columns": { "value": "6", - "section": "bci_config", - "readableName": "Matrix Columns", + "section": "matrix_task_config", + "name": "Matrix Columns", "helpTip": "Specifies the number of columns to use in the Matrix task. Rows * columns should be greater than or equal to the number of symbols.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "matrix_width": { "value": "0.7", - "section": "bci_config", - "readableName": "Matrix Width (%)", + "section": "matrix_task_config", + "name": "Matrix Width (%)", "helpTip": "Specifies the max percentage of the display that the matrix grid should utilize. Must be between 0 and 1", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "acq_show_viewer": { "value": "false", "section": "acq_config", - "readableName": " EEG Viewer On/Off", - "helpTip": "If ‘true’, the EEG signal viewer will be displayed.", - "recommended_values": "", + "name": " EEG Viewer", + "helpTip": "If ‘true’, the EEG signal viewer will be displayed along with the Task. Note: This has not been throughly tested and could cause timing issues. Use with caution.", + "recommended": "", + "editable": false, "type": "bool" }, "stim_screen": { "value": "0", "section": "bci_config", - "readableName": "Task Display Monitor", + "name": "Task Display Monitor", "helpTip": "Specifies which monitor to use for task display when two monitors are in use. If ‘0’, the task will be displayed on the primary monitor (with the EEG signal viewer on the second monitor, if EEG Viewer On/Off is set to ‘true’). If ‘1’, the opposite monitor assignment will be used.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "task_buffer_length": { "value": "2", - "section": "bci_config", - "readableName": "Inter-inquiry Interval", + "section": "task_config", + "name": "Inter-inquiry Interval", "helpTip": "Specifies the delay time (in seconds) between the final stimulus in one inquiry and the beginning (target stimulus or fixation cross) of the next inquiry in a task. Default: 2", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "is_txt_stim": { "value": "true", "section": "bci_config", - "readableName": "Text Stimuli On/Off", - "helpTip": "If ‘true’, text stimuli will be used. If ‘false’, image stimuli will be loaded from the folder specified in Image Stimulus Folder.", - "recommended_values": "", + "name": "Text Stimuli", + "helpTip": "If ‘true’, text stimuli will be used. If ‘false’, image stimuli will be loaded from the folder specified in Image Stimulus Folder. Default: true", + "recommended": "", + "editable": false, "type": "bool" }, "path_to_presentation_images": { "value": "bcipy/static/images/rsvp/", "section": "bci_config", - "readableName": "Image Stimulus Folder", + "name": "Image Stimulus Folder", "helpTip": "Specifies the location of image files to be used as stimuli (Text Stimuli On/Off must be set to ‘false’). This must be a directory ending with /.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "directorypath" }, "stim_space_char": { "value": "–", - "section": "bci_config", - "readableName": "Space Character", - "helpTip": "Specifies the text or Unicode character which represents a space during text-stimuli tasks. Default: –", - "recommended_values": [ + "section": "task_config", + "name": "Space Character", + "helpTip": "Specifies the text or Unicode character which represents a space during text-stimuli tasks. *Note* This only applies to RSVP Tasks. Default: –", + "recommended": [ "_", "–", "‒", "□" ], + "editable": false, "type": "str" }, "stim_order": { "value": "random", "section": "bci_config", - "readableName": "Stimuli Order", + "name": "Stimuli Order", "helpTip": "Specifies the ordering of stimuli in an inquiry. Default is random.", - "recommended_values": [ + "recommended": [ "alphabetical", "random" ], + "editable": false, "type": "str" }, "target_positions": { "value": "distributed", "section": "bci_config", - "readableName": "Target Positions", + "name": "Target Positions", "helpTip": "Specifies the positions of target stimuli in calibration task. Default is random.", - "recommended_values": [ + "recommended": [ "distributed", "random" ], + "editable": false, "type": "str" }, "nontarget_inquiries": { - "value": "10", + "value": "0", "section": "bci_config", - "readableName": "Percentage of Nontarget Inquiries", - "helpTip": "Specifies the percentage (0-100) of inquiries which target stimuli flashed is not in inquiry. Default is 10 percent.", - "recommended_values": "", + "name": "Percentage of Nontarget Inquiries", + "helpTip": "Specifies the percentage (0-100) of inquiries which target stimuli flashed is not in inquiry. Default is 0 percent.", + "recommended": "", + "editable": false, "type": "int" }, "stim_length": { "value": "10", - "section": "bci_config", - "readableName": "Stimuli Per inquiry", + "section": "task_config", + "name": "Stimuli Per inquiry", "helpTip": "Specifies the number of stimuli to present in each inquiry. Default: 10", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "time_flash": { - "value": "0.25", - "section": "bci_config", - "readableName": "Stimulus Presentation Duration", - "helpTip": "Specifies the duration of time (in seconds) that each stimulus is displayed in an inquiry.", - "recommended_values": "", + "value": "0.2", + "section": "task_config", + "name": "Stimulus Presentation Duration", + "helpTip": "Specifies the duration of time (in seconds) that each stimulus is displayed in an inquiry. Default: 0.2", + "recommended": "", + "editable": false, "type": "float" }, "time_prompt": { "value": "1", - "section": "bci_config", - "readableName": "Time Prompt Stimuli (sec)", + "section": "task_config", + "name": "Time Prompt Stimuli (sec)", "helpTip": "The amount of time in seconds to present the target stimuli prompt in an inquiry.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "time_fixation": { "value": "0.5", - "section": "bci_config", - "readableName": "Time Fixation Stimuli (sec)", + "section": "task_config", + "name": "Time Fixation Stimuli (sec)", "helpTip": "The amount of time in seconds to present the fixation stimuli in an inquiry.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "time_vep_animation": { "value": "1.0", - "section": "bci_config", - "readableName": "Time VEP Animation (sec)", + "section": "vep_task_config", + "name": "Time VEP Animation (sec)", "helpTip": "The amount of time in seconds for the animation moving symbols to boxes.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "stim_jitter": { "value": "0.0", "section": "bci_config", - "readableName": "Stimulus Presentation Jitter (sec)", + "name": "Stimulus Presentation Jitter (sec)", "helpTip": "Specifies the time (sec) to jitter presentation rates. Default: 0.0", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, - "stim_pos_x": { + "rsvp_stim_pos_x": { "value": "0", - "section": "bci_config", - "readableName": "Stimulus Position Horizontal", + "section": "rsvp_task_config", + "name": "RSVP Stimulus Position Horizontal", "helpTip": "Specifies the center point of the stimulus position along the X axis. Possible values range from -1 to 1, with 0 representing the center. Default: 0", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, - "stim_pos_y": { + "rsvp_stim_pos_y": { "value": "0", - "section": "bci_config", - "readableName": "Stimulus Position Vertical", + "section": "rsvp_task_config", + "name": "RSVP Stimulus Position Vertical", "helpTip": "Specifies the center point of the stimulus position along the Y axis. Possible values range from -1 to 1, with 0 representing the center. Default: 0", - "recommended_values": "", + "recommended": "", + "editable": false, + "type": "float" + }, + "matrix_stim_pos_x": { + "value": "-0.6", + "section": "matrix_task_config", + "name": "Matrix Stimulus Starting Position Horizontal", + "helpTip": "Specifies the center point of the stimulus position along the X axis. Possible values range from -1 to 1, with 0 representing the center. Default: -0.6", + "recommended": "", + "editable": false, + "type": "float" + }, + "matrix_stim_pos_y": { + "value": "0.4", + "section": "matrix_task_config", + "name": "Matrix Stimulus Starting Position Vertical", + "helpTip": "Specifies the center point of the stimulus position along the Y axis. Possible values range from -1 to 1, with 0 representing the center. Default: 0.4", + "recommended": "", + "editable": false, "type": "float" }, "font": { - "value": "Overpass Mono Medium", - "section": "bci_config", - "readableName": "Font", - "helpTip": "Specifies the font used for all text stimuli. Default: Consolas", - "recommended_values": [ + "value": "Courier New", + "section": "task_config", + "name": "Font", + "helpTip": "Specifies the font used for all text stimuli. Default: Courier New", + "recommended": [ "Courier New", "Lucida Sans", + "Arial", "Consolas" ], + "editable": false, "type": "str" }, - "stim_height": { - "value": "0.5", - "section": "bci_config", - "readableName": "Stimulus Size", - "helpTip": "Specifies the height of text stimuli. See https://www.psychopy.org/general/units.html. Default: 0.5", - "recommended_values": "", + "rsvp_stim_height": { + "value": "0.4", + "section": "rsvp_task_config", + "name": "RSVP Stimulus Size", + "helpTip": "Specifies the height of text stimuli. See https://www.psychopy.org/general/units.html. Default: 0.4", + "recommended": "", + "editable": false, + "type": "float" + }, + "vep_stim_height": { + "value": "0.1", + "section": "vep_task_config", + "name": "VEP Stimulus Size", + "helpTip": "Specifies the height of text stimuli. See https://www.psychopy.org/general/units.html. Default: 0.1", + "recommended": "", + "editable": false, + "type": "float" + }, + "matrix_stim_height": { + "value": "0.17", + "section": "matrix_task_config", + "name": "Matrix Stimulus Size", + "helpTip": "Specifies the height of text stimuli. See https://www.psychopy.org/general/units.html. Default: 0.17", + "recommended": "", + "editable": false, "type": "float" }, + "matrix_keyboard_layout": { + "value": "ALP", + "section": "matrix_task_config", + "name": "Matrix Keyboard Layout", + "helpTip": "Specifies the keyboard layout to use for the Matrix task. Default: ALP (Alphabetical)", + "recommended": [ + "ALP", + "QWERTY", + "FREQ" + ], + "editable": false, + "type": "str" + }, "stim_color": { "value": "white", "section": "bci_config", - "readableName": "Stimulus Color", + "name": "Stimulus Color", "helpTip": "Specifies the color of text stimuli within the RSVP stream. Default: white", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "str" }, "target_color": { "value": "white", "section": "bci_config", - "readableName": "Target Color", + "name": "Target Color", "helpTip": "Specifies the color of target characters during calibration. Default: white", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "str" }, "fixation_color": { "value": "red", "section": "bci_config", - "readableName": "Fixation Cross Color", + "name": "Fixation Cross Color", "helpTip": "Specifies the color of the fixation cross that appears before each inquiry. Default: red", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "str" }, "background_color": { "value": "black", - "section": "bci_config", - "readableName": "Task Background Color", + "section": "task_config", + "name": "Task Background Color", "helpTip": "Specifies the color of the task background. Default: black", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "str" }, "info_pos_x": { "value": "0", - "section": "bci_config", - "readableName": "Position Text (X)", + "section": "task_config", + "name": "Position Text (X)", "helpTip": "Position Text (X)", - "recommended_values": [ + "recommended": [ "0" ], + "editable": false, "type": "float" }, "info_pos_y": { "value": "-0.75", - "section": "bci_config", - "readableName": "Position Text (Y)", + "section": "task_config", + "name": "Position Text (Y)", "helpTip": "Position Text (Y)", - "recommended_values": [ + "recommended": [ "-0.75" ], + "editable": false, "type": "float" }, "info_text": { "value": "", - "section": "bci_config", - "readableName": "Text below main presentation", + "section": "task_config", + "name": "Text below main presentation", "helpTip": "Text below main presentation", - "recommended_values": [ + "recommended": [ "", "Demo Text", "DEMO" ], + "editable": false, "type": "str" }, "info_height": { "value": "0.1", - "section": "bci_config", - "readableName": "Text below main presentation height", + "section": "task_config", + "name": "Text below main presentation height", "helpTip": "Specifies the height of info text stimuli. See https://www.psychopy.org/general/units.html. Default: 0.1", - "recommended_values": [ + "recommended": [ "0.1" ], + "editable": false, "type": "float" }, "info_color": { "value": "white", - "section": "bci_config", - "readableName": "Color Text", + "section": "task_config", + "name": "Color Text", "helpTip": "Color Text", - "recommended_values": [ + "recommended": [ "white", "black", "blue" ], + "editable": false, "type": "str" }, "task_text": { "value": "HELLO_WORLD", - "section": "bci_config", - "readableName": "Target Phrase", - "helpTip": "Specifies the target phrase displayed at the top of the screen during text-stimuli copy/spelling tasks.", - "recommended_values": "", + "section": "online_config", + "name": "Target Phrase", + "helpTip": "Specifies the target phrase displayed at the top of the screen during text-stimuli copy/spelling tasks. If copy_phrases_location is provided, this parameter will be ignored and overwritten in parameter saving.", + "recommended": "", + "editable": true, "type": "str" }, - "task_height": { + "copy_phrases_location": { + "value": "bcipy/parameters/experiment/phrases.json", + "section": "online_config", + "name": "Copy Phrases Location", + "helpTip": "Specifies a list of copy phrases to execute during Task Orchestration. If provided, any copy phrases in the protocol will be executed in order pulling task text and starting locations from the file.", + "recommended": "", + "editable": true, + "type": "filepath" + }, + "rsvp_task_height": { "value": "0.1", - "section": "bci_config", - "readableName": "Task Text Size", + "section": "rsvp_task_config", + "name": "RSVP Task Text Size", + "helpTip": "Specifies the height of task-specific text, e.g. #/100 in calibration and target phrase in copy/spelling. See https://www.psychopy.org/general/units.html. Default: 0.1", + "recommended": [ + "0.1" + ], + "editable": false, + "type": "float" + }, + "vep_task_height": { + "value": "0.1", + "section": "vep_task_config", + "name": "VEP Task Text Size", "helpTip": "Specifies the height of task-specific text, e.g. #/100 in calibration and target phrase in copy/spelling. See https://www.psychopy.org/general/units.html. Default: 0.1", - "recommended_values": [ + "recommended": [ "0.1" ], + "editable": false, + "type": "float" + }, + "matrix_task_height": { + "value": "0.1", + "section": "matrix_task_config", + "name": "Matrix Task Text Size", + "helpTip": "Specifies the height of task-specific text, e.g. #/100 in calibration and target phrase in copy/spelling. See https://www.psychopy.org/general/units.html. Default: 0.1", + "recommended": [ + "0.1" + ], + "editable": false, "type": "float" }, "task_color": { "value": "white", "section": "bci_config", - "readableName": "Task Text Color", + "name": "Task Text Color", "helpTip": "Specifies the color of task-specific text, e.g. #/100 in calibration and target phrase in copy/spelling. Default: white", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "str" }, - "task_padding": { + "rsvp_task_padding": { + "value": "0.05", + "section": "bci_config", + "name": "RSVP Task Bar Padding", + "helpTip": "Specifies the padding around the task bar text for RSVP tasks. Default: 0.05", + "recommended": [ + "0.05" + ], + "editable": false, + "type": "float" + }, + "matrix_task_padding": { "value": "0.05", "section": "bci_config", - "readableName": "Task Bar Padding", - "helpTip": "Specifies the padding around the task bar text. Default: 0.05", - "recommended_values": [ + "name": "Matrix Task Bar Padding", + "helpTip": "Specifies the padding around the task bar text for Matrix Tasks. Default: 0.05", + "recommended": [ "0.05" ], + "editable": false, "type": "float" }, "stim_number": { - "value": "100", + "value": "5", "section": "bci_config", - "readableName": "Number of Calibration inquiries", + "name": "Number of Calibration inquiries", "helpTip": "Specifies the number of inquiries to present in a calibration session. Default: 100", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "enable_breaks": { "value": "false", "section": "bci_config", - "readableName": "Automatic Calibration Breaks On/Off", + "name": "Automatic Calibration Breaks", "helpTip": "If ‘true’, automatic breaks will be added to the calibration session. If ‘false’, automatic breaks will not occur, but the session can still be paused by pressing Space.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "bool" }, "break_len": { "value": "30", "section": "bci_config", - "readableName": "Automatic Calibration Break Length", + "name": "Automatic Calibration Break Length", "helpTip": "Specifies the length (in seconds) of automatic calibration breaks (Automatic Calibration Breaks On/Off must be set to ‘true’).", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "trials_before_break": { "value": "20", "section": "bci_config", - "readableName": "Automatic Calibration Break Timing", + "name": "Automatic Calibration Break Timing", "helpTip": "Specifies the number of inquiries between automatic calibration breaks (Automatic Calibration Breaks On/Off must be set to ‘true’).", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "break_message": { "value": "Take a break!", "section": "bci_config", - "readableName": "Automatic Calibration Break Message", + "name": "Automatic Calibration Break Message", "helpTip": "Specifies the message displayed during automatic calibration breaks (Automatic Calibration Breaks On/Off must be set to ‘true’).", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "str" }, - "min_inq_len": { - "value": "1", - "section": "bci_config", - "readableName": "Minimum Inquiry Length", - "helpTip": "The minimum number of inquiries to present in spelling tasks", - "recommended_values": [ - "1" - ], - "type": "int" - }, "max_inq_len": { "value": "50", - "section": "bci_config", - "readableName": "Maximum Inquiry Length", + "section": "online_config", + "name": "Maximum Inquiry Length", "helpTip": "Specifies the maximum number of inquiries to present in copy/spelling tasks. The task will end if this number is reached.", - "recommended_values": [ + "recommended": [ "20", "25" ], + "editable": false, "type": "int" }, "max_minutes": { "value": "20", - "section": "bci_config", - "readableName": "Maximum Task Length (Time)", + "section": "online_config", + "name": "Maximum Task Length (Time)", "helpTip": "Specifies the time limit (in minutes) for copy/spelling tasks. The task will end if this time limit is reached.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "max_selections": { "value": "25", - "section": "bci_config", - "readableName": "Maximum Number of Selections", + "section": "online_config", + "name": "Maximum Number of Selections", "helpTip": "The maximum number of selections for copy/spelling tasks. The task will end if this number is reached.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "max_incorrect": { "value": "5", "section": "bci_config", - "readableName": "Maximum Number of Incorrect Selections", + "name": "Maximum Number of Incorrect Selections", "helpTip": "The maximum number of consecutive incorrect selections for copy/spelling tasks. The task will end if this number is reached.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "decision_threshold": { "value": "0.8", - "section": "bci_config", - "readableName": "Decision Threshold", + "section": "online_config", + "name": "Decision Threshold", "helpTip": "Specifies the decision threshold for stimulus selection in copy/spelling class. If the posterior probability (combining EEG and language model evidence) for a stimulus reaches this threshold, it will be selected. Possible value range: 0.0-1.0. Default: 0.8", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, - "min_inq_per_series": { + "min_inq_len": { "value": "1", - "section": "bci_config", - "readableName": "Minimum Inquiries Per Series", + "section": "online_config", + "name": "Minimum Inquiries Per Series", "helpTip": "Specifies the minimum number of inquiries to present before making a decision in copy/spelling tasks. Default: 1", - "recommended_values": [ + "recommended": [ "1" ], + "editable": false, "type": "int" }, "max_inq_per_series": { "value": "11", - "section": "bci_config", - "readableName": "Maximum Inquiries Per Series", + "section": "online_config", + "name": "Maximum Inquiries Per Series", "helpTip": "Specifies the maximum number of inquiries to present before making a decision in copy/spelling tasks.", - "recommended_values": [ + "recommended": [ "10", "15" ], + "editable": false, "type": "int" }, "backspace_always_shown": { "value": "true", - "section": "bci_config", - "readableName": "Always Show Backspace On/Off", + "section": "lang_model_config", + "name": "Always Show Backspace", "helpTip": "If ‘true’, the backspace character will be included in every inquiry in text-stimuli copy/spelling tasks. If ‘false’, the backspace character will be treated the same as other characters, appearing in inquiries only when warranted by EEG/language model evidence.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "bool" }, "spelled_letters_count": { "value": "0", - "section": "bci_config", - "readableName": "Pre-Selected Letters Count", + "section": "lang_model_config", + "name": "Pre-Selected Letters Count", "helpTip": "Specifies the number of letters in the target phrase that are already typed when the task begins, e.g. if the target phrase is “THE_DOG”, setting this parameter to ‘4’ would display “THE_” as the typed string, and the user would begin typing with D. If ‘0’, the typed string will be blank.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "int" }, "lang_model_type": { "value": "UNIFORM", "section": "lang_model_config", - "readableName": "Language Model Type", + "name": "Language Model Type", "helpTip": "Specifies which language model to use. Default: UNIFORM", - "recommended_values": [ + "recommended": [ "UNIFORM", "CAUSAL", "KENLM", "MIXTURE", "ORACLE" ], + "editable": false, "type": "str" }, "lm_backspace_prob": { "value": "0.0", - "section": "bci_config", - "readableName": "Backspace Probability", + "section": "lang_model_config", + "name": "Backspace Probability", "helpTip": "Specifies the minimum probability assigned to the backspace character in the language model. Possible value range: 0.0-1.0. Default: 0.0", - "recommended_values": "0.05", + "recommended": "0.05", + "editable": false, "type": "float" }, "show_preview_inquiry": { "value": "false", - "section": "bci_config", - "readableName": "Preview Inquiry On/Off", - "helpTip": "If ‘true’, the inquiry will be previewed as applicable for the task. *Note* Not all tasks will have this enabled!", - "recommended_values": "", + "section": "task_config", + "name": "Preview Inquiry Display", + "helpTip": "If ‘true’, the inquiry will be previewed as applicable for the Task. *Note* Not all tasks will have this enabled!", + "recommended": "", + "editable": false, "type": "bool" }, "preview_inquiry_error_prob": { "value": "0.05", "section": "bci_config", - "readableName": "Preview Inquiry Button Error Probability", + "name": "Preview Inquiry Button Error Probability", "helpTip": "Specifies the probability of a button error during inquiry preview. Default: 0.05", - "recommended_values": "", + "recommended": "", + "editable": true, "type": "float" }, "preview_inquiry_progress_method": { "value": "0", - "section": "bci_config", - "readableName": "Preview Inquiry Progression Method", + "section": "task_config", + "name": "Preview Inquiry Progression Method", "helpTip": "If show_preview_inquiry true, this will determine how to proceed after a key hit. 0 = preview only; 1 = press to confirm; 2 = press to skip to another inquiry", - "recommended_values": [ + "recommended": [ "0", "1", "2" ], + "editable": false, "type": "int" }, "preview_inquiry_length": { "value": "5", - "section": "bci_config", - "readableName": "Preview Inquiry Display Length", + "section": "task_config", + "name": "Preview Inquiry Display Length", "helpTip": "Length of time in seconds to present an inquiry preview to the user.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "preview_inquiry_key_input": { "value": "return", - "section": "bci_config", - "readableName": "Preview Inquiry Display Key Input Method", + "section": "task_config", + "name": "Preview Inquiry Display Key Input Method", "helpTip": "Defines the key used to engage with inquiry preview.", - "recommended_values": [ + "recommended": [ "space", "escape", "return" ], + "editable": false, "type": "str" }, "preview_inquiry_isi": { "value": "1", - "section": "bci_config", - "readableName": "Preview Inquiry Inter-Stimulus Interval", + "section": "task_config", + "name": "Preview Inquiry Inter-Stimulus Interval", "helpTip": "The time between previewing an inquiry and the start of an inquiry.", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "show_feedback": { "value": "true", - "section": "bci_config", - "readableName": "Feedback On/Off", - "helpTip": "If ‘true’, feedback will be shown after each inquiry.", - "recommended_values": "", + "section": "task_config", + "name": "Feedback Display", + "helpTip": "If ‘true’, feedback will be shown after each inquiry. If ‘false’, feedback will not be shown. *Note* Not all tasks will have this enabled!", + "recommended": "", + "editable": false, "type": "bool" }, "feedback_duration": { "value": "2", - "section": "bci_config", - "readableName": "Feedback Time (seconds)", + "section": "task_config", + "name": "Feedback Time (seconds)", "helpTip": "Specifies the length in time (seconds) feedback will be displayed after each inquiry in registered tasks (ex. RSVP Copy Phrase). Default: 2", - "recommended_values": "", + "recommended": "", + "editable": false, "type": "float" }, "psd_method": { "value": "Welch", - "section": "bci_config", - "readableName": "Power Spectral Density Method", + "section": "signal_config", + "name": "Power Spectral Density Method", "helpTip": "Specifies the method used to approximate power spectral density bands (Welch or MultiTaper). Default: Welch", - "recommended_values": [ + "recommended": [ "Welch", "MutliTaper" ], + "editable": false, "type": "str" } } \ No newline at end of file diff --git a/bcipy/signal/evaluate/artifact.py b/bcipy/signal/evaluate/artifact.py index ed7f5be78..19ec6180f 100644 --- a/bcipy/signal/evaluate/artifact.py +++ b/bcipy/signal/evaluate/artifact.py @@ -5,14 +5,13 @@ from typing import Union, List, Tuple, Optional from logging import getLogger -log = getLogger(__name__) - from bcipy.config import ( DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME, - BCIPY_ROOT + BCIPY_ROOT, + SESSION_LOG_FILENAME ) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import ( @@ -29,6 +28,7 @@ from bcipy.acquisition.devices import DeviceSpec import mne +log = getLogger(SESSION_LOG_FILENAME) mne.set_log_level('WARNING') from mne import Annotations @@ -40,7 +40,7 @@ class DefaultArtifactParameters(Enum): """ # Voltage - PEAK_THRESHOLD = 100e-7 + PEAK_THRESHOLD = 75e-7 PEAK_MIN_DURATION = 0.005 FLAT_THRESHOLD = 0.5e-6 FLAT_MIN_DURATION = 0.1 @@ -133,6 +133,12 @@ class ArtifactDetection: detect_voltage : bool Whether to detect voltage artifacts. Defaults to True. + + semi_automatic : bool + Whether to use a semi-automatic approach to artifact detection. Defaults to False. + + session_triggers : tuple + A tuple of lists containing the trigger type, trigger timing, and trigger label for the session. """ supported_units: List[str] = ['volts', 'microvolts'] @@ -237,13 +243,13 @@ def label_artifacts( voltage = self.label_voltage_events() if voltage: voltage_annotations, bad_channels = voltage - log.info(f'Voltage violation events found: {len(voltage_annotations)}') if bad_channels: # add bad channel labels to the raw data self.mne_data.info['bads'] = bad_channels log.info(f'Bad channels detected: {bad_channels}') if voltage_annotations: + log.info(f'Voltage violation events found: {len(voltage_annotations)}') annotations += voltage_annotations self.voltage_annotations = voltage_annotations @@ -251,8 +257,9 @@ def label_artifacts( eog = self.label_eog_events() if eog: eog_annotations, eog_events = eog - log.info(f'EOG events found: {len(eog_events)}') + if eog_annotations: + log.info(f'EOG events found: {len(eog_events)}') annotations += eog_annotations self.eog_annotations = eog_annotations @@ -431,8 +438,10 @@ def label_voltage_events( # combine the bad channels bad_channels = bad_channels1 + bad_channels2 - if len(onsets) > 0 or len(bad_channels) > 0: + if len(onsets) > 0 and len(bad_channels) > 0: return mne.Annotations(onsets, durations, descriptions), bad_channels + elif len(bad_channels) > 0: + return None, bad_channels return None diff --git a/bcipy/signal/model/__init__.py b/bcipy/signal/model/__init__.py index 6e9e0a4fe..d95f3d026 100644 --- a/bcipy/signal/model/__init__.py +++ b/bcipy/signal/model/__init__.py @@ -1,13 +1,10 @@ from bcipy.signal.model.base_model import SignalModel, ModelEvaluationReport from bcipy.signal.model.pca_rda_kde.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.model.rda_kde.rda_kde import RdaKdeModel -from bcipy.signal.model.gaussian_mixture.gaussian_mixture import GazeModelIndividual, GazeModelCombined __all__ = [ "SignalModel", "PcaRdaKdeModel", "RdaKdeModel", - "GazeModelIndividual", - "GazeModelCombined", "ModelEvaluationReport", ] diff --git a/bcipy/signal/model/base_model.py b/bcipy/signal/model/base_model.py index 8a854f72b..828e3bb1e 100644 --- a/bcipy/signal/model/base_model.py +++ b/bcipy/signal/model/base_model.py @@ -16,10 +16,14 @@ class SignalModelMetadata(NamedTuple): device_spec: DeviceSpec # device used to train the model transform: Composition # data preprocessing steps evidence_type: str = None # optional; type of evidence produced + auc: float = None # optional; area under the curve + balanced_accuracy: float = None # optional; balanced accuracy class SignalModel(ABC): + name = "undefined" + @property def metadata(self) -> SignalModelMetadata: """Information regarding the data and parameters used to train the diff --git a/bcipy/signal/model/cross_validation.py b/bcipy/signal/model/cross_validation.py index f2ecff702..238229b0a 100644 --- a/bcipy/signal/model/cross_validation.py +++ b/bcipy/signal/model/cross_validation.py @@ -2,10 +2,11 @@ import scipy.optimize from sklearn import metrics +from bcipy.config import SESSION_LOG_FILENAME import logging -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) def cost_cross_validation_auc(model, opt_el, x, y, param, k_folds=10, @@ -14,7 +15,7 @@ def cost_cross_validation_auc(model, opt_el, x, y, param, k_folds=10, Cost function: given a particular architecture (model). Fits the parameters to the folds with leave one fold out procedure. Calculates scores for the validation fold. Concatenates all calculated scores - together and returns a -AUC vale. + together and returns a -AUC value. Args: model(pipeline): model to be iterated on opt_el(int): number of the element in pipeline to be optimized diff --git a/bcipy/signal/model/density_estimation.py b/bcipy/signal/model/density_estimation.py index 5422abcd4..7e88442b9 100644 --- a/bcipy/signal/model/density_estimation.py +++ b/bcipy/signal/model/density_estimation.py @@ -5,6 +5,8 @@ from scipy.stats import iqr from sklearn.neighbors import KernelDensity +from bcipy.config import SESSION_LOG_FILENAME + class KernelDensityEstimate: """Kernel density estimate using scikit learn. @@ -16,7 +18,7 @@ class KernelDensityEstimate: def __init__(self, scores: Optional[np.array] = None, kernel="gaussian", num_cls=2): bandwidth = 1.0 if scores is None else self._compute_bandwidth(scores, scores.shape[0]) - self.logger = logging.getLogger(__name__) + self.logger = logging.getLogger(SESSION_LOG_FILENAME) self.logger.info(f"KDE. bandwidth={bandwidth}, kernel={kernel}") self.num_cls = num_cls self.list_den_est = [KernelDensity(bandwidth=bandwidth, kernel=kernel) for _ in range(self.num_cls)] diff --git a/bcipy/signal/model/dimensionality_reduction.py b/bcipy/signal/model/dimensionality_reduction.py index 2a4d4bfc8..288cc3da3 100644 --- a/bcipy/signal/model/dimensionality_reduction.py +++ b/bcipy/signal/model/dimensionality_reduction.py @@ -4,6 +4,8 @@ import numpy as np from sklearn.decomposition import PCA +from bcipy.config import SESSION_LOG_FILENAME + class ChannelWisePrincipalComponentAnalysis: """Creates a PCA object for each channel. @@ -27,7 +29,7 @@ class ChannelWisePrincipalComponentAnalysis: def __init__(self, n_components: Optional[float] = None, random_state: Optional[int] = None, num_ch: int = 1): self.num_ch = num_ch self.list_pca = [PCA(n_components=n_components, random_state=random_state) for _ in range(self.num_ch)] - self.logger = logging.getLogger(__name__) + self.logger = logging.getLogger(SESSION_LOG_FILENAME) self.logger.info(f"PCA. n_components={n_components}, random_state={random_state}, num_ch={num_ch}") def fit(self, x: np.ndarray, y: Optional[np.ndarray] = None) -> None: diff --git a/bcipy/signal/model/gaussian_mixture/__init__.py b/bcipy/signal/model/gaussian_mixture/__init__.py index 1a5dc0dfe..e69de29bb 100644 --- a/bcipy/signal/model/gaussian_mixture/__init__.py +++ b/bcipy/signal/model/gaussian_mixture/__init__.py @@ -1,6 +0,0 @@ -from .gaussian_mixture import GazeModelCombined, GazeModelIndividual - -__all__ = [ - "GazeModelCombined", - "GazeModelIndividual", -] diff --git a/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py b/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py index 29307b84f..0f71f6c94 100644 --- a/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py +++ b/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py @@ -5,7 +5,6 @@ from sklearn.mixture import GaussianMixture from bcipy.helpers.stimuli import GazeReshaper from sklearn.model_selection import cross_val_score # noqa -from sklearn.utils.estimator_checks import check_estimator # noqa import scipy.stats as stats from typing import Optional @@ -13,6 +12,7 @@ class GazeModelIndividual(SignalModel): reshaper = GazeReshaper() + name = "gaze_model_individual" def __init__(self, num_components=2): self.num_components = num_components # number of gaussians to fit @@ -80,6 +80,7 @@ def load(self, path: Path): class GazeModelCombined(SignalModel): '''Gaze model that uses all symbols to fit a single Gaussian ''' reshaper = GazeReshaper() + name = "gaze_model_combined" def __init__(self, num_components=1): self.num_components = num_components # number of gaussians to fit diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 1c26f335a..bbbda64e4 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -1,42 +1,43 @@ # mypy: disable-error-code="attr-defined" -# needed for the ERPTransformParams import json import logging +import subprocess from pathlib import Path -from typing import Tuple +from typing import List import numpy as np -from matplotlib.figure import Figure + from sklearn.metrics import balanced_accuracy_score from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices from bcipy.config import (BCIPY_ROOT, DEFAULT_DEVICE_SPEC_FILENAME, - DEFAULT_PARAMETERS_PATH, MATRIX_IMAGE_FILENAME, - STATIC_AUDIO_PATH, TRIGGER_FILENAME) + DEFAULT_PARAMETERS_PATH, MATRIX_IMAGE_FILENAME, DEFAULT_DEVICES_PATH, + TRIGGER_FILENAME, SESSION_LOG_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) +from bcipy.gui.alert import confirm from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import save_model -from bcipy.helpers.stimuli import play_sound, update_inquiry_timing +from bcipy.helpers.stimuli import update_inquiry_timing from bcipy.helpers.symbols import alphabet from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.helpers.visualization import (visualize_centralized_data, - visualize_erp, visualize_gaze, + visualize_gaze, visualize_gaze_accuracies, visualize_gaze_inquiries, visualize_results_all_symbols) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata -from bcipy.signal.model.gaussian_mixture import (GazeModelCombined, - GazeModelIndividual) +from bcipy.signal.model.gaussian_mixture.gaussian_mixture import (GazeModelCombined, + GazeModelIndividual) from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import (ERPTransformParams, extract_eye_info, filter_inquiries, get_default_transform) -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) logging.basicConfig(level=logging.INFO, format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") @@ -74,7 +75,7 @@ def subset_data(data: np.ndarray, labels: np.ndarray, test_size: float, random_s return train_data, test_data, train_labels, test_labels -def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balanced_acc, +def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balanced_acc: bool, save_figures=False, show_figures=False): """Analyze ERP data and return/save the ERP model. Extract relevant information from raw data object. @@ -182,39 +183,46 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance # train and save the model as a pkl file log.info("Training model. This will take some time...") model = PcaRdaKdeModel(k_folds=k_folds) - model.fit(data, labels) - model.metadata = SignalModelMetadata(device_spec=device_spec, - transform=default_transform) - log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") + try: + model.fit(data, labels) + model.metadata = SignalModelMetadata(device_spec=device_spec, + transform=default_transform, + evidence_type="ERP", + auc=model.auc) + log.info(f"Training complete [AUC={model.auc:0.4f}]. Saving data...") + except Exception as e: + log.error(f"Error training model: {e}") + + try: + # Using an 80/20 split, report on balanced accuracy + if estimate_balanced_acc: + train_data, test_data, train_labels, test_labels = subset_data(data, labels, test_size=0.2) + dummy_model = PcaRdaKdeModel(k_folds=k_folds) + dummy_model.fit(train_data, train_labels) + probs = dummy_model.predict_proba(test_data) + preds = probs.argmax(-1) + score = balanced_accuracy_score(test_labels, preds) + log.info(f"Balanced acc with 80/20 split: {score}") + model.metadata.balanced_accuracy = score + del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds + + except Exception as e: + log.error(f"Error calculating balanced accuracy: {e}") save_model(model, Path(data_folder, f"model_{model.auc:0.4f}.pkl")) preferences.signal_model_directory = data_folder - # Using an 80/20 split, report on balanced accuracy - if estimate_balanced_acc: - train_data, test_data, train_labels, test_labels = subset_data(data, labels, test_size=0.2) - dummy_model = PcaRdaKdeModel(k_folds=k_folds) - dummy_model.fit(train_data, train_labels) - probs = dummy_model.predict_proba(test_data) - preds = probs.argmax(-1) - score = balanced_accuracy_score(test_labels, preds) - log.info(f"Balanced acc with 80/20 split: {score}") - del dummy_model, train_data, test_data, train_labels, test_labels, probs, preds - - # this should have uncorrected trigger timing for display purposes - figure_handles = visualize_erp( - erp_data, - channel_map, - trigger_timing, - labels, - trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, - save_path=data_folder if save_figures else None, - show=show_figures - ) - return model, figure_handles + if save_figures or show_figures: + cmd = f'bcipy-erp-viz --session_path "{data_folder}" --parameters "{parameters["parameter_location"]}"' + if save_figures: + cmd += ' --save' + if show_figures: + cmd += ' --show' + subprocess.run( + cmd, + shell=True + ) + return model def analyze_gaze( @@ -248,15 +256,13 @@ def analyze_gaze( "Individual": Fits a separate Gaussian for each symbol. Default model "Centralized": Uses data from all symbols to fit a single centralized Gaussian """ - figures = [] - figure_handles = visualize_gaze( + visualize_gaze( gaze_data, save_path=save_figures, img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', show=show_figures, raw_plot=plot_points, ) - figures.extend(figure_handles) channels = gaze_data.channels type_amp = gaze_data.daq_type @@ -347,7 +353,7 @@ def analyze_gaze( means, covs = model.evaluate(test_re) # Visualize the results: - figure_handles = visualize_gaze_inquiries( + visualize_gaze_inquiries( le, re, means, covs, save_path=save_figures, @@ -355,7 +361,6 @@ def analyze_gaze( show=show_figures, raw_plot=plot_points, ) - figures.extend(figure_handles) left_eye_all.append(le) right_eye_all.append(re) means_all.append(means) @@ -399,22 +404,20 @@ def analyze_gaze( print(f"Overall accuracy: {accuracy:.2f}") # Plot all accuracies as bar plot: - figure_handles = visualize_gaze_accuracies(acc_all_symbols, accuracy, save_path=None, show=True) - figures.extend(figure_handles) + visualize_gaze_accuracies(acc_all_symbols, accuracy, save_path=None, show=True) if model_type == "Centralized": cent_left = np.concatenate(np.array(centralized_data_left, dtype=object)) cent_right = np.concatenate(np.array(centralized_data_right, dtype=object)) # Visualize the results: - figure_handles = visualize_centralized_data( + visualize_centralized_data( cent_left, cent_right, save_path=save_figures, img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', show=show_figures, raw_plot=plot_points, ) - figures.extend(figure_handles) # Fit the model: model.fit(cent_left) @@ -427,7 +430,7 @@ def analyze_gaze( le = preprocessed_data[sym][0] re = preprocessed_data[sym][1] # Visualize the results: - figure_handles = visualize_gaze_inquiries( + visualize_gaze_inquiries( le, re, means, covs, save_path=save_figures, @@ -435,13 +438,13 @@ def analyze_gaze( show=show_figures, raw_plot=plot_points, ) - figures.extend(figure_handles) left_eye_all.append(le) right_eye_all.append(re) means_all.append(means) covs_all.append(covs) - fig_handles = visualize_results_all_symbols( + # TODO: add visualizations to subprocess + visualize_results_all_symbols( left_eye_all, right_eye_all, means_all, covs_all, img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', @@ -449,7 +452,6 @@ def analyze_gaze( show=show_figures, raw_plot=plot_points, ) - figures.extend(fig_handles) model.metadata = SignalModelMetadata(device_spec=device_spec, transform=None) @@ -457,7 +459,7 @@ def analyze_gaze( save_model( model, Path(data_folder, f"model_{device_spec.content_type}_{model_type}.pkl")) - return model, figures + return model @report_execution_time @@ -468,7 +470,7 @@ def offline_analysis( estimate_balanced_acc: bool = False, show_figures: bool = False, save_figures: bool = False, -) -> Tuple[SignalModel, Figure]: +) -> List[SignalModel]: """Gets calibration data and trains the model in an offline fashion. pickle dumps the model into a .pkl folder @@ -499,45 +501,52 @@ def offline_analysis( Returns: -------- model (SignalModel): trained model - figure_handles (Figure): handles to the ERP figures """ assert parameters, "Parameters are required for offline analysis." if not data_folder: data_folder = load_experimental_data() + # Load default devices which are used for training the model with different channels, etc. devices_by_name = devices.load( - Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME), replace=True) + Path(DEFAULT_DEVICES_PATH, DEFAULT_DEVICE_SPEC_FILENAME), replace=True) - active_devices = (spec for spec in devices_by_name.values() + # Load the active devices used during a session; this will be used to exclude inactive devices + active_devices_by_name = devices.load( + Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME), replace=True) + active_devices = (spec for spec in active_devices_by_name.values() if spec.is_active) active_raw_data_paths = (Path(data_folder, raw_data_filename(device_spec)) for device_spec in active_devices) data_file_paths = [path for path in active_raw_data_paths if path.exists()] + assert len(data_file_paths) < 3, "BciPy only supports up to 2 devices for offline analysis." + assert len(data_file_paths) > 0, "No data files found for offline analysis." + models = [] - figure_handles = [] + log.info(f"Starting offline analysis for {data_file_paths}") for raw_data_path in data_file_paths: raw_data = load_raw_data(raw_data_path) device_spec = devices_by_name.get(raw_data.daq_type) # extract relevant information from raw data object eeg if device_spec.content_type == "EEG": - erp_model, erp_figure_handles = analyze_erp( + erp_model = analyze_erp( raw_data, parameters, device_spec, data_folder, estimate_balanced_acc, save_figures, show_figures) models.append(erp_model) - figure_handles.extend(erp_figure_handles) if device_spec.content_type == "Eyetracker": - et_model, et_figure_handles = analyze_gaze( + et_model = analyze_gaze( raw_data, parameters, device_spec, data_folder, save_figures, show_figures, model_type="Individual") models.append(et_model) - figure_handles.extend(et_figure_handles) if alert_finished: - play_sound(f"{STATIC_AUDIO_PATH}/{parameters['alert_sound_file']}") - return models, figure_handles + log.info("Alerting Offline Analysis Complete") + results = [f"{model.name}: {model.auc}" for model in models] + confirm(f"Offline analysis complete! \n Results={results}") + log.info("Offline analysis complete") + return models -if __name__ == "__main__": +def main(): import argparse parser = argparse.ArgumentParser() @@ -548,13 +557,17 @@ def offline_analysis( parser.add_argument("--alert", dest="alert", action="store_true") parser.add_argument("--balanced-acc", dest="balanced", action="store_true") parser.set_defaults(alert=False) - parser.set_defaults(balanced=True) + parser.set_defaults(balanced=False) parser.set_defaults(save_figures=False) - parser.set_defaults(show_figures=True) + parser.set_defaults(show_figures=False) args = parser.parse_args() log.info(f"Loading params from {args.parameters_file}") parameters = load_json_parameters(args.parameters_file, value_cast=True) + log.info( + f"Starting offline analysis client with the following: Data={args.data_folder} || " + f"Save Figures={args.save_figures} || Show Figures={args.show_figures} || " + f"Alert={args.alert} || Calculate Balanced Accuracy={args.balanced}") offline_analysis( args.data_folder, @@ -563,4 +576,7 @@ def offline_analysis( estimate_balanced_acc=args.balanced, save_figures=args.save_figures, show_figures=args.show_figures) - log.info("Offline Analysis complete.") + + +if __name__ == "__main__": + main() diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index 7187e5c2c..28280c1d3 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -4,7 +4,7 @@ import numpy as np -from bcipy.helpers.exceptions import SignalException +from bcipy.exceptions import SignalException from bcipy.helpers.stimuli import InquiryReshaper from bcipy.signal.model import ModelEvaluationReport, SignalModel from bcipy.signal.model.classifier import RegularizedDiscriminantAnalysis @@ -18,6 +18,7 @@ class PcaRdaKdeModel(SignalModel): reshaper: InquiryReshaper = InquiryReshaper() + name = "pca_rda_kde" def __init__(self, k_folds: int = 10, prior_type="uniform", pca_n_components=0.9): self.k_folds = k_folds diff --git a/bcipy/signal/model/rda_kde/rda_kde.py b/bcipy/signal/model/rda_kde/rda_kde.py index 405250374..6c716d569 100644 --- a/bcipy/signal/model/rda_kde/rda_kde.py +++ b/bcipy/signal/model/rda_kde/rda_kde.py @@ -9,12 +9,13 @@ from bcipy.signal.model.density_estimation import KernelDensityEstimate from bcipy.signal.model.dimensionality_reduction import MockPCA from bcipy.signal.model.pipeline import Pipeline -from bcipy.helpers.exceptions import SignalException +from bcipy.exceptions import SignalException from bcipy.helpers.stimuli import InquiryReshaper class RdaKdeModel(SignalModel): reshaper = InquiryReshaper() + name = "rda_kde" def __init__(self, k_folds: int, prior_type: str = "uniform"): self.k_folds = k_folds diff --git a/bcipy/signal/process/decomposition/psd.py b/bcipy/signal/process/decomposition/psd.py index 69869f2d4..ddeda93da 100644 --- a/bcipy/signal/process/decomposition/psd.py +++ b/bcipy/signal/process/decomposition/psd.py @@ -8,7 +8,7 @@ from typing import Tuple -from bcipy.helpers.exceptions import SignalException +from bcipy.exceptions import SignalException class PSD_TYPE(Enum): diff --git a/bcipy/signal/process/extract_gaze.py b/bcipy/signal/process/extract_gaze.py index 6c707dad0..6aa95d6fb 100644 --- a/bcipy/signal/process/extract_gaze.py +++ b/bcipy/signal/process/extract_gaze.py @@ -1,6 +1,6 @@ import numpy as np -from bcipy.helpers.exceptions import SignalException +from bcipy.exceptions import SignalException def extract_eye_info(data): diff --git a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py index e4238d2b7..4d5439ecc 100644 --- a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py +++ b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py @@ -8,7 +8,7 @@ import pytest from scipy.stats import norm -from bcipy.helpers.exceptions import SignalException +from bcipy.exceptions import SignalException from bcipy.helpers.load import load_signal_models from bcipy.helpers.save import save_model from bcipy.helpers.symbols import alphabet diff --git a/bcipy/signal/tests/model/rda_kde/test_rda_kde.py b/bcipy/signal/tests/model/rda_kde/test_rda_kde.py index 9ea8312ca..c09e53e0c 100644 --- a/bcipy/signal/tests/model/rda_kde/test_rda_kde.py +++ b/bcipy/signal/tests/model/rda_kde/test_rda_kde.py @@ -15,7 +15,7 @@ from bcipy.signal.model.density_estimation import KernelDensityEstimate from bcipy.signal.model.dimensionality_reduction import MockPCA from bcipy.signal.model.pipeline import Pipeline -from bcipy.helpers.exceptions import SignalException +from bcipy.exceptions import SignalException expected_output_folder = Path(__file__).absolute().parent.parent / "unit_test_expected_output" diff --git a/bcipy/signal/tests/model/test_offline_analysis.py b/bcipy/signal/tests/model/test_offline_analysis.py index 3f8535e2e..54f84d8e3 100644 --- a/bcipy/signal/tests/model/test_offline_analysis.py +++ b/bcipy/signal/tests/model/test_offline_analysis.py @@ -19,7 +19,7 @@ @pytest.mark.slow -class TestOfflineAnalysis(unittest.TestCase): +class TestOfflineAnalysisEEG(unittest.TestCase): """Integration test of offline_analysis.py (slow) This test is slow because it runs the full offline analysis pipeline and compares its' output @@ -50,12 +50,14 @@ def setUpClass(cls): params_path = pwd.parent.parent.parent / "parameters" / DEFAULT_PARAMETER_FILENAME cls.parameters = load_json_parameters(params_path, value_cast=True) - models, fig_handles = offline_analysis( - str(cls.tmp_dir), cls.parameters, save_figures=True, show_figures=False, alert_finished=False) + models = offline_analysis( + str(cls.tmp_dir), + cls.parameters, + save_figures=False, + show_figures=False, + alert_finished=False) + # only one model is generated using the default parameters cls.model = models[0] - cls.mean_erp_fig_handle = fig_handles[0] - cls.mean_nontarget_topomap_handle = fig_handles[1] - cls.mean_target_topomap_handle = fig_handles[2] @classmethod def tearDownClass(cls): @@ -73,20 +75,6 @@ def test_model_AUC(self): found_auc = self.get_auc(list(self.tmp_dir.glob("model_*.pkl"))[0].name) self.assertAlmostEqual(expected_auc, found_auc, delta=0.005) - @pytest.mark.mpl_image_compare(baseline_dir=expected_output_folder, filename="test_mean_erp.png", remove_text=True) - def test_mean_erp(self): - return self.mean_erp_fig_handle - - @pytest.mark.mpl_image_compare(baseline_dir=expected_output_folder, - filename="test_target_topomap.png", remove_text=False) - def test_target_topomap(self): - return self.mean_target_topomap_handle - - @pytest.mark.mpl_image_compare(baseline_dir=expected_output_folder, - filename="test_nontarget_topomap.png", remove_text=False) - def test_nontarget_topomap(self): - return self.mean_nontarget_topomap_handle - if __name__ == "__main__": unittest.main() diff --git a/bcipy/signal/tests/process/decomposition/test_decomposition.py b/bcipy/signal/tests/process/decomposition/test_decomposition.py index 540685e5d..6f6adf887 100644 --- a/bcipy/signal/tests/process/decomposition/test_decomposition.py +++ b/bcipy/signal/tests/process/decomposition/test_decomposition.py @@ -1,7 +1,7 @@ import unittest from bcipy.config import BCIPY_ROOT -from bcipy.helpers.exceptions import SignalException +from bcipy.exceptions import SignalException from bcipy.signal.process.decomposition import continuous_wavelet_transform from bcipy.signal.process.decomposition.psd import power_spectral_density, PSD_TYPE import numpy as np diff --git a/bcipy/simulator/data/data_engine.py b/bcipy/simulator/data/data_engine.py index 0e10813ca..fe591db85 100644 --- a/bcipy/simulator/data/data_engine.py +++ b/bcipy/simulator/data/data_engine.py @@ -7,7 +7,7 @@ import numpy as np import pandas as pd -from bcipy.helpers.exceptions import TaskConfigurationException +from bcipy.exceptions import TaskConfigurationException from bcipy.helpers.parameters import Parameters from bcipy.simulator.data import data_process from bcipy.simulator.data.data_process import (ExtractedExperimentData, diff --git a/bcipy/simulator/data/sampler.py b/bcipy/simulator/data/sampler.py index fa1e3f8c4..5424c95e2 100644 --- a/bcipy/simulator/data/sampler.py +++ b/bcipy/simulator/data/sampler.py @@ -180,8 +180,8 @@ def sample(self, state: SimState) -> List[Trial]: inquiry_n = random.choice(source_inquiries[data_source]) # select all trials for the data_source and inquiry - inquiry_df = self.data.loc[(self.data['source'] == data_source) - & (self.data['inquiry_n'] == inquiry_n)] + inquiry_df = self.data.loc[(self.data['source'] == data_source) & + (self.data['inquiry_n'] == inquiry_n)] assert len(inquiry_df) == len( inquiry_letter_subset), f"Invalid data source {data_source}" diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 1d78c44ec..1dee73b09 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -1,5 +1,7 @@ +# mypy: disable-error-code="union-attr" """Simulates the Copy Phrase task""" from typing import Dict, List, Optional, Tuple +import logging from bcipy.display.main import Display from bcipy.feedback.visual.visual_feedback import VisualFeedback @@ -39,6 +41,7 @@ def __init__(self, parameters: Parameters, file_save: str, fake=False) self.save_session_every_inquiry = False self.samplers = samplers + self.logger = logging.getLogger(__name__) def init_evidence_evaluators( self, signal_models: List[SignalModel]) -> List[EvidenceEvaluator]: diff --git a/bcipy/task/README.md b/bcipy/task/README.md index 3943d744c..7defbe7e4 100644 --- a/bcipy/task/README.md +++ b/bcipy/task/README.md @@ -5,8 +5,7 @@ These are the tasks that can be run to collect experimental data. ## Paradigms ------------ -Within `task/` there are folders for each of the supported paradigms, and within them, the supported modes. To add new paradigms, create a folder for it and place the tasks in files within it. Be sure to add it to the `start_task` file at the root to be able execute it! An entry must also be added to the task_registry TaskType -enum. This updates the GUI (BCInterface.py) and makes the task available to `start_task`. +Within `task/` there are folders for each of the supported paradigms, and within them, the supported modes. To add new paradigms, create a folder for it and place the tasks in files within it. An entry must also be added to the task_registry TaskType and/or TaskMode enum. This updates the GUI (BCInterface.py) and makes the task available to the BciPy Client. Currently, these are the supported paradigms and modes: @@ -33,25 +32,160 @@ Currently, these are the supported paradigms and modes: > Copy Phrase: Used to copy a phrase using the Matrix paradigm (e.g. P300 Speller) on data from a P300 calibration +### *Paradigm: VEP* -## Start Task -------------- +##### Mode: Calibration + +> Calibration: Used to calibrate the VEP paradigm for a user. Note this has not been extensively tested, use with caution. + + +## Running Tasks using the SessionOrchestrator + +The `SessionOrchestrator` is a class that can be used to run a Protocol (sequence of Tasks/Actions). The core BciPy client and GUI use this class and resulting data strucutures. It will run the tasks in the order defined, handle the transition between tasks, and persist data. There are several optional arguments that can be provided to the orchestrator: + +experiment_id: str + This is used to load any defined protocols or field collections. If no experiment_id is provided, a default will be used, and the orchestrator will run any tasks in the order they were added. +user: str + The user ID to associate with the session data. By default, this is DEFAULT_USER. +parameters_path: str + The path to the BciPy parameters file. By default, this is DEFAULT_PARAMETERS_PATH, located at bcipy/parameters/parameters.json. +parameters: Parameters + A Parameters object to use for the Tasks. If provided, this will override the parameters_path. +fake: bool + If True, the Tasks will run in fake mode. This is useful for testing or debugging paradigms with streaming data or models. By default, this is False. +alert: bool + If True, after a Task execution the orchestrator will alert experimenters when a task is complete. By default, this is False. +visualize: bool + If True, after a Task execution the orchestrator will visualize data. By default, this is False. This only works for EEG data with target/non-target labels. + + +The data will be saved in the following format in the specified data_save_loc (default is bcipy/data/): + +``` + +data_save_loc/ + user_id/ + experiment_id/ + run_id / + task_id/ + logs/ + task_log_data + task_data (e.g. acquisition data, parameters, visualizations) + task_id/ + logs/ + task_log_data + task_data (e.g. acquisition data, parameters, visualizations) + logs/ + protocol_log_data + protocol_data (system data, protocol/tasks executed) +``` + +### Usage manually + +```python +from bcipy.task import Task +from bcipy.task import SessionOrchestrator +from bcipy.task.action import OfflineAnalysisAction +from bcipy.task.task_registry import TaskType +from bcipy.task.paradigm.rsvp.calibration import RSVPCalibration +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhrase + +# Create a list of tasks to run, These should not be initialized. +tasks = [ + RSVPCalibration, + OfflineAnalysisAction, + RSVPCopyPhrase +] + +# Create a SessionOrchestrator +orchestrator = SessionOrchestrator() + +# add the tasks to the orchestrator +orchestrator.add_tasks(tasks) + +# run the tasks +orchestrator.execute() +``` + +### Usage with a Protocol -Start Task takes in Display [object], parameters [dict], file save [str-path] and task type [dict]. Using the -task type, start_task() will route to the correct paradigm (RSVP, SSVEP, MATRIX) and mode (Calibration, Copy Phrase, etc.) +```python +from bcipy.task import Task +from bcipy.task import SessionOrchestrator +from bcipy.task.action import OfflineAnalysisAction +from bcipy.task.task_registry import TaskType +from bcipy.task.paradigm.rsvp.calibration import RSVPCalibration +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhrase +from bcipy.task.protocol import parse_protocol -It is called in the following way: +# Create a protocol. This would be extracted from a registered experiment. +example_protocol = 'RSVPCalibration -> OfflineAnalysisAction -> RSVPCopyPhrase' +# Parse the protocol into a list of tasks. This will raise an error if the TaskType is not registered. +tasks = parse_protocol(example_protocol) +# Create a SessionOrchestrator +orchestrator = SessionOrchestrator() +# add the tasks to the orchestrator +orchestrator.add_tasks(tasks) + +# run the tasks +orchestrator.execute() ``` - from bcipy.task.start_task import start_task - start_task( - display_window, - data_acquisition_client, - parameters, - file_save) +### Usage from experiment loading + +Note: A new experiment must be registered in the `bcipy/parameters/experiments.json` file. The BCInterface may also be used to create a new named experiment. + +```python +from bcipy.task import Task +from bcipy.task import SessionOrchestrator +from bcipy.task.action import OfflineAnalysisAction +from bcipy.task.task_registry import TaskType +from bcipy.task.paradigm.rsvp.calibration import RSVPCalibration +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhrase +from bcipy.task.protocol import parse_protocol +from bcipy.helpers.load import load_experiment + +# Load an experiment from the registered experiments +experiment_name = 'default' +experiment = load_experiment(experiment_name) +# grab the protocol from the experiment and parse it +protocol = experiment['protocol'] +tasks = parse_protocol(protocol) + +# Create a SessionOrchestrator +orchestrator = SessionOrchestrator() +# add the tasks to the orchestrator +orchestrator.add_tasks(tasks) + +# run the tasks +orchestrator.execute() ``` -It will throw an error if the task isn't implemented. +### Using orchestration to type using multiple copy phrases with different text and spelled letters + +There are experiments in which multiple copy phrases would be used to test the performance of a user and the system over a variety of phrases. This is especially useful for testing the language model performance over different contexts and starting data. Additionally, this can be used to test the performance of the system over different spelling lengths and complexity. + +If the `copy_phrase_location` parameter is set in the parameters.json file, the orchestrator will use the provided file to load the phrases to be copied in Tasks with the mode TaskMode.COPYPHRASE. The file should be a JSON file with the following format: + +```json +{ + "Phrases": [ + ["This is the first phrase", 1], + ["This is the second phrase", 2], + ["This is the third phrase", 3] + ] +} +``` + +Each phrase should be a list with the phrase as the first element (string) and the spelled letter count as the second element (integer). The orchestrator will iterate through the phrases in order, copying each one the specified number of times. If any phrases are remaining, the orchestrator will save the phrase list to the run directory for future use. + + + + + + + + diff --git a/bcipy/task/__init__.py b/bcipy/task/__init__.py index 79f953973..2a60353aa 100644 --- a/bcipy/task/__init__.py +++ b/bcipy/task/__init__.py @@ -1,10 +1,14 @@ """ This import statement allows users to import submodules from Task """ -from .main import Task -from .task_registry import TaskType +from .main import Task, TaskData, TaskMode + +# Makes the following classes available to the task registry +from .registry import TaskRegistry __all__ = [ 'Task', - 'TaskType', + 'TaskRegistry', + 'TaskData', + 'TaskMode' ] diff --git a/bcipy/task/actions.py b/bcipy/task/actions.py new file mode 100644 index 000000000..12b520624 --- /dev/null +++ b/bcipy/task/actions.py @@ -0,0 +1,380 @@ +# mypy: disable-error-code="assignment,arg-type" +import subprocess +from typing import Any, Optional, List, Callable, Tuple +import logging +from pathlib import Path +import glob + +from bcipy.gui.bciui import run_bciui +from matplotlib.figure import Figure + +from bcipy.gui.intertask_gui import IntertaskGUI +from bcipy.gui.experiments.ExperimentField import start_experiment_field_collection_gui +from bcipy.task import Task, TaskMode, TaskData +from bcipy.helpers.triggers import trigger_decoder, TriggerType + +from bcipy.acquisition import devices +from bcipy.helpers.acquisition import analysis_channels +from bcipy.helpers.parameters import Parameters +from bcipy.acquisition.devices import DeviceSpec +from bcipy.helpers.load import load_raw_data +from bcipy.helpers.raw_data import RawData +from bcipy.signal.process import get_default_transform +from bcipy.helpers.report import SignalReportSection, SessionReportSection, Report, ReportSection +from bcipy.config import SESSION_LOG_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME +from bcipy.helpers.visualization import visualize_erp +from bcipy.signal.evaluate.artifact import ArtifactDetection + + +logger = logging.getLogger(SESSION_LOG_FILENAME) + + +class CodeHookAction(Task): + """ + Action for running generic code hooks. + """ + + name = "CodeHookAction" + mode = TaskMode.ACTION + + def __init__( + self, + parameters: Parameters, + data_directory: str, + code_hook: Optional[str] = None, + subprocess: bool = True, + **kwargs) -> None: + super().__init__() + self.code_hook = code_hook + self.subprocess = subprocess + + def execute(self) -> TaskData: + if self.code_hook: + if self.subprocess: + subprocess.Popen(self.code_hook, shell=True) + + else: + subprocess.run(self.code_hook, shell=True) + return TaskData() + + +class OfflineAnalysisAction(Task): + """ + Action for running offline analysis. + """ + + name = "OfflineAnalysisAction" + mode = TaskMode.ACTION + + def __init__( + self, + parameters: Parameters, + data_directory: str, + parameters_path: str, + last_task_dir: Optional[str] = None, + alert_finished: bool = False, + **kwargs: Any) -> None: + super().__init__() + self.parameters = parameters + self.parameters_path = parameters_path + self.alert_finished = alert_finished + + # TODO: add a feature to orchestrator to permit the user to select the last task directory or have it loaded. + if last_task_dir: + self.data_directory = last_task_dir + else: + self.data_directory = data_directory + + def execute(self) -> TaskData: + """Execute the offline analysis. + + Note: This function is called by the orchestrator to execute the offline analysis task. Some of the + exceptions that can be raised by this function are not recoverable and will cause the orchestrator + to stop execution. For example, if Exception is thrown in cross_validation due to the # of folds being + inconsistent. + + """ + logger.info("Running offline analysis action") + try: + cmd = f'bcipy-train -p "{self.parameters_path}"' + if self.alert_finished: + cmd += " --alert" + response = subprocess.run( + cmd, + shell=True, + check=True, + ) + except Exception as e: + logger.exception(f"Error running offline analysis: {e}") + raise e + return TaskData( + save_path=self.data_directory, + task_dict={"parameters": self.parameters_path, + "response": response}, + ) + + +class IntertaskAction(Task): + name = "IntertaskAction" + mode = TaskMode.ACTION + tasks: List[Task] + current_task_index: int + + def __init__( + self, + parameters: Parameters, + save_path: str, + progress: Optional[int] = None, + tasks: Optional[List[Task]] = None, + exit_callback: Optional[Callable] = None, + **kwargs: Any) -> None: + super().__init__() + self.save_folder = save_path + self.parameters = parameters + assert progress is not None and tasks is not None, "Either progress or tasks must be provided" + self.next_task_index = progress # progress is 1-indexed, tasks is 0-indexed so we can use the same index + assert self.next_task_index >= 0, "Progress must be greater than 1 " + self.tasks = tasks + self.task_name = self.tasks[self.next_task_index].name + self.task_names = [task.name for task in self.tasks] + self.exit_callback = exit_callback + + def execute(self) -> TaskData: + + run_bciui( + IntertaskGUI, + tasks=self.task_names, + next_task_index=self.next_task_index, + exit_callback=self.exit_callback), + + return TaskData( + save_path=self.save_folder, + task_dict={ + "next_task_index": self.next_task_index, + "tasks": self.task_names, + "task_name": self.task_name, + }, + ) + + def alert(self): + pass + + +class ExperimentFieldCollectionAction(Task): + """ + Action for collecting experiment field data. + """ + + name = "ExperimentFieldCollectionAction" + mode = TaskMode.ACTION + + def __init__( + self, + parameters: Parameters, + data_directory: str, + experiment_id: str = 'default', + **kwargs: Any) -> None: + super().__init__() + self.experiment_id = experiment_id + self.save_folder = data_directory + self.parameters = parameters + + def execute(self) -> TaskData: + logger.info( + f"Collecting experiment field data for experiment {self.experiment_id} in save folder {self.save_folder}" + ) + start_experiment_field_collection_gui(self.experiment_id, self.save_folder) + return TaskData( + save_path=self.save_folder, + task_dict={ + "experiment_id": self.experiment_id, + }, + ) + + +class BciPyCalibrationReportAction(Task): + """ + Action for generating a report after calibration Tasks. + """ + + name = "BciPyReportAction" + mode = TaskMode.ACTION + + def __init__( + self, + parameters: Parameters, + save_path: str, + protocol_path: Optional[str] = None, + last_task_dir: Optional[str] = None, + trial_window: Optional[Tuple[float, float]] = None, + **kwargs: Any) -> None: + super().__init__() + self.save_folder = save_path + # Currently we assume all Tasks have the same parameters, this may change in the future. + self.parameters = parameters + self.protocol_path = protocol_path or '' + self.last_task_dir = last_task_dir + self.default_transform = None + self.trial_window = (-0.2, 1.0) + self.static_offset = None + self.report = Report(self.protocol_path) + self.report_sections: List[ReportSection] = [] + self.all_raw_data: List[RawData] = [] + self.type_amp = None + + def execute(self) -> TaskData: + """Excute the report generation action. + + This assumes all data were collected using the same protocol, device, and parameters. + """ + logger.info(f"Generating report in save folder {self.save_folder}") + # loop through all the files in the last_task_dir + + data_directories = [] + # If a protocol is given, loop over and look for any calibration directories + try: + if self.protocol_path: + # Use glob to find all directories with Calibration in the name + calibration_directories = glob.glob( + f"{self.protocol_path}/**/*Calibration*", + recursive=True) + for data_dir in calibration_directories: + path_data_dir = Path(data_dir) + # pull out the last directory name + task_name = path_data_dir.parts[-1].split('_')[0] + data_directories.append(path_data_dir) + # For each calibration directory, attempt to load the raw data + signal_report_section = self.create_signal_report(path_data_dir) + session_report = self.create_session_report(path_data_dir, task_name) + self.report_sections.append(session_report) + self.report.add(session_report) + self.report_sections.append(signal_report_section) + self.report.add(signal_report_section) + if data_directories: + logger.info(f"Saving report generated from: {self.protocol_path}") + else: + logger.info(f"No data found in {self.protocol_path}") + + except Exception as e: + logger.exception(f"Error generating report: {e}") + + self.report.compile() + self.report.save() + return TaskData( + save_path=self.save_folder, + task_dict={}, + ) + + def create_signal_report(self, data_dir: Path) -> SignalReportSection: + raw_data = load_raw_data(Path(data_dir, f'{RAW_DATA_FILENAME}.csv')) + if not self.type_amp: + self.type_amp = raw_data.daq_type + channels = raw_data.channels + sample_rate = raw_data.sample_rate + device_spec = devices.preconfigured_device(raw_data.daq_type) + self.static_offset = device_spec.static_offset + channel_map = analysis_channels(channels, device_spec) + self.all_raw_data.append(raw_data) + + # Set the default transform if not already set + if not self.default_transform: + self.set_default_transform(sample_rate) + + triggers = self.get_triggers(data_dir) + # get figure handles + figure_handles = self.get_figure_handles(raw_data, channel_map, triggers) + artifact_detector = self.get_artifact_detector(raw_data, device_spec, triggers) + return SignalReportSection(figure_handles, artifact_detector) + + def create_session_report(self, data_dir, task_name) -> SessionReportSection: + # get task name + summary_dict = { + "task": task_name, + "data_location": data_dir, + "amplifier": self.type_amp + } + signal_model_metrics = self.get_signal_model_metrics(data_dir) + summary_dict.update(signal_model_metrics) + + return SessionReportSection(summary_dict) + + def get_signal_model_metrics(self, data_directory: Path) -> dict: + """Get the signal model metrics from the session folder. + + In the future, the model will save a ModelMetrics with the pkl file. + For now, we just look for the pkl file and extract the AUC from the filename. + """ + pkl_file = None + for file in data_directory.iterdir(): + if file.suffix == '.pkl': + pkl_file = file + break + + if pkl_file: + auc = pkl_file.stem.split('_')[-1] + else: + auc = 'No Signal Model found in session folder' + + return {'AUC': auc} + + def set_default_transform(self, sample_rate: int) -> None: + downsample_rate = self.parameters.get("down_sampling_rate") + notch_filter = self.parameters.get("notch_filter_frequency") + filter_high = self.parameters.get("filter_high") + filter_low = self.parameters.get("filter_low") + filter_order = self.parameters.get("filter_order") + self.default_transform = get_default_transform( + sample_rate_hz=sample_rate, + notch_freq_hz=notch_filter, + bandpass_low=filter_low, + bandpass_high=filter_high, + bandpass_order=filter_order, + downsample_factor=downsample_rate, + ) + + def find_eye_channels(self, device_spec: DeviceSpec) -> Optional[list]: + eye_channels = [] + for channel in device_spec.channels: + if 'F' in channel: + eye_channels.append(channel) + if len(eye_channels) == 0: + eye_channels = None + return eye_channels + + def get_triggers(self, session) -> tuple: + trigger_type, trigger_timing, trigger_label = trigger_decoder( + offset=self.static_offset, + trigger_path=f"{session}/{TRIGGER_FILENAME}", + exclusion=[ + TriggerType.PREVIEW, + TriggerType.EVENT, + TriggerType.FIXATION], + device_type='EEG' + ) + return trigger_type, trigger_timing, trigger_label + + def get_figure_handles(self, raw_data, channel_map, triggers) -> List[Figure]: + _, trigger_timing, trigger_label = triggers + figure_handles = visualize_erp( + raw_data, + channel_map, + trigger_timing, + trigger_label, + self.trial_window, + transform=self.default_transform, + plot_average=True, + plot_topomaps=True, + show=False, + ) + return figure_handles + + def get_artifact_detector(self, raw_data, device_spec, triggers) -> ArtifactDetection: + eye_channels = self.find_eye_channels(device_spec) + artifact_detector = ArtifactDetection( + raw_data, + self.parameters, + device_spec, + eye_channels=eye_channels, + session_triggers=triggers) + artifact_detector.detect_artifacts() + return artifact_detector diff --git a/bcipy/task/base_calibration.py b/bcipy/task/calibration.py similarity index 81% rename from bcipy/task/base_calibration.py rename to bcipy/task/calibration.py index 392de4fc4..839c85eda 100644 --- a/bcipy/task/base_calibration.py +++ b/bcipy/task/calibration.py @@ -1,14 +1,16 @@ """Base calibration task.""" - +from abc import abstractmethod from typing import Any, Dict, Iterator, List, NamedTuple, Optional, Tuple -from psychopy import core, visual +from psychopy import core +from psychopy.visual import Window import bcipy.task.data as session_data from bcipy.acquisition import ClientManager from bcipy.config import (SESSION_DATA_FILENAME, TRIGGER_FILENAME, - WAIT_SCREEN_MESSAGE) -from bcipy.display import Display + WAIT_SCREEN_MESSAGE, SESSION_LOG_FILENAME) +from bcipy.helpers.acquisition import init_acquisition, LslDataServer +from bcipy.display import init_display_window, Display from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import _save_session_related_data @@ -21,7 +23,10 @@ from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, convert_timing_triggers, offset_label) -from bcipy.task import Task +from bcipy.task import Task, TaskData, TaskMode + +import logging +logger = logging.getLogger(SESSION_LOG_FILENAME) class Inquiry(NamedTuple): @@ -50,10 +55,9 @@ class BaseCalibrationTask(Task): PARAMETERS: ---------- - win (PsychoPy Display) - daq (Data Acquisition Client) parameters (dict) file_save (str) + fake (bool) Subclasses should override the provided MODE and can specialize behavior by overriding the following methods: @@ -62,19 +66,33 @@ class BaseCalibrationTask(Task): - trigger_type ; used for assigning trigger types to the timing data - session_task_data ; provide task-specific session data - session_inquiry_data ; provide task-specific inquiry data to the session - - cleanup ; perform any necessary cleanup (closing connections, etc.) + - cleanup ; perform any necessary cleanup (closing connections, etc.). + + Returns: + ------- + TaskData """ - MODE = 'Undefined' + mode = TaskMode.CALIBRATION + paradigm = 'Undefined' + initalized = False - def __init__(self, win: visual.Window, daq: ClientManager, - parameters: Parameters, file_save: str) -> None: + def __init__(self, + parameters: Parameters, + file_save: str, + fake: bool = False, + **kwargs: Any) -> None: super().__init__() + + self.fake = fake + self.validate() + daq, servers, win = self.setup(parameters, file_save, fake) self.window = win self.frame_rate = self.window.getActualFrameRate() self.parameters = parameters self.daq = daq + self.servers = servers self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) self.experiment_clock = Clock() self.start_time = self.experiment_clock.getTime() @@ -103,11 +121,47 @@ def symbol_set(self) -> List[str]: """Symbols used in the calibration""" return self._symbol_set - def name(self) -> str: - """Task name""" - if self.MODE == 'Undefined': - raise NotImplementedError - return f"{self.MODE} Calibration Task" + def setup(self, parameters, data_save_location, fake=False) -> Tuple[ClientManager, List[LslDataServer], Window]: + # Initialize Acquisition + daq, servers = init_acquisition( + parameters, data_save_location, server=fake) + + # Initialize Display + display = init_display_window(parameters) + self.initalized = True + + return daq, servers, display + + def validate(self) -> None: + """Validate the task.""" + assert self.paradigm != 'Undefined', 'Paradigm must be defined in subclass.' + + def cleanup(self) -> None: + """Any cleanup code to run after the last inquiry is complete.""" + logger.info('Cleaning up task acquisition and display.') + self.exit_display() + self.write_offset_trigger() + self.wait() + if self.initalized: + try: + # Stop Acquisition + self.daq.stop_acquisition() + self.daq.cleanup() + + # Stop Servers + if self.servers: + for server in self.servers: + server.stop() + + # Close the display window + # NOTE: There is currently a bug in psychopy when attempting to shutdown + # windows when using a USB-C monitor. Putting the display close last in + # the inquiry allows acquisition to properly shutdown. + self.window.close() + self.initalized = False + + except Exception as e: + logger.exception(str(e)) def wait(self, seconds: Optional[float] = None) -> None: """Pause for a time. @@ -120,9 +174,10 @@ def wait(self, seconds: Optional[float] = None) -> None: seconds = seconds or self.parameters['task_buffer_length'] core.wait(seconds) + @abstractmethod def init_display(self) -> Display: """Initialize the display""" - raise NotImplementedError + ... def init_inquiry_generator(self) -> Iterator[Inquiry]: """Initializes a generator that returns inquiries to be presented.""" @@ -148,8 +203,8 @@ def init_inquiry_generator(self) -> Iterator[Inquiry]: def init_session(self) -> session_data.Session: """Initialize the session data.""" return session_data.Session(save_location=self.file_save, - task='Calibration', - mode=self.MODE, + task=self.name, + mode=str(self.mode), symbol_set=self.symbol_set, task_data=self.session_task_data()) @@ -212,12 +267,12 @@ def user_wants_to_continue(self, first_inquiry: bool = False) -> bool: self.wait_screen_message_color, first_run=first_inquiry) if not should_continue: - self.logger.info('User wants to exit.') + logger.info('User wants to exit.') return should_continue - def execute(self) -> str: + def execute(self) -> TaskData: """Task run loop.""" - self.logger.info(f'Starting {self.name()}!') + logger.info(f'Starting {self.name}!') self.wait() inq_index = 0 @@ -241,11 +296,9 @@ def execute(self) -> str: self.wait() inq_index += 1 - self.exit_display() - self.write_offset_trigger() self.cleanup() - return self.file_save + return TaskData(save_path=self.file_save, task_dict=self.session.as_dict()) def exit_display(self) -> None: """Close the UI and cleanup.""" @@ -258,9 +311,6 @@ def exit_display(self) -> None: # Allow for some additional data to be collected for later processing self.wait() - def cleanup(self) -> None: - """Any cleanup code to run after the last inquiry is complete.""" - def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None: """Write Trigger Data. @@ -331,4 +381,4 @@ def add_session_data(self, inquiry: Inquiry) -> None: def session_inquiry_data(self, inquiry: Inquiry) -> Optional[Dict[str, Any]]: """Defines task-specific session data for each inquiry.""" - return None + ... diff --git a/bcipy/task/control/criteria.py b/bcipy/task/control/criteria.py index 29249dbd4..701fb544d 100644 --- a/bcipy/task/control/criteria.py +++ b/bcipy/task/control/criteria.py @@ -3,7 +3,8 @@ from typing import Dict, List from copy import copy -log = logging.getLogger(__name__) +from bcipy.config import SESSION_LOG_FILENAME +log = logging.getLogger(SESSION_LOG_FILENAME) class DecisionCriteria: diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py index 929f38eaf..3cb7c1480 100644 --- a/bcipy/task/control/evidence.py +++ b/bcipy/task/control/evidence.py @@ -6,13 +6,14 @@ import numpy as np from bcipy.acquisition.multimodal import ContentType +from bcipy.config import SESSION_LOG_FILENAME from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.stimuli import TrialReshaper from bcipy.signal.model import SignalModel from bcipy.task.data import EvidenceType from bcipy.task.exceptions import MissingEvidenceEvaluator -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) class EvidenceEvaluator: diff --git a/bcipy/task/control/handler.py b/bcipy/task/control/handler.py index 56ec283dd..9ca1a6262 100644 --- a/bcipy/task/control/handler.py +++ b/bcipy/task/control/handler.py @@ -4,13 +4,14 @@ import numpy as np +from bcipy.config import SESSION_LOG_FILENAME from bcipy.helpers.stimuli import InquirySchedule, inq_generator, StimuliOrder from bcipy.helpers.symbols import SPACE_CHAR, BACKSPACE_CHAR from bcipy.task.control.query import RandomStimuliAgent, StimuliAgent from bcipy.task.control.criteria import CriteriaEvaluator from bcipy.task.data import EvidenceType -log = logging.getLogger(__name__) +log = logging.getLogger(SESSION_LOG_FILENAME) class EvidenceFusion(): diff --git a/bcipy/task/demo/demo_orchestrator.py b/bcipy/task/demo/demo_orchestrator.py new file mode 100644 index 000000000..d57bd0013 --- /dev/null +++ b/bcipy/task/demo/demo_orchestrator.py @@ -0,0 +1,54 @@ +from bcipy.config import DEFAULT_PARAMETERS_PATH +from bcipy.task.orchestrator import SessionOrchestrator +from bcipy.task.actions import (OfflineAnalysisAction, IntertaskAction, BciPyCalibrationReportAction) +from bcipy.task.paradigm.rsvp import RSVPCalibrationTask +# from bcipy.task.paradigm.rsvp import RSVPCopyPhraseTask, RSVPTimingVerificationCalibration +from bcipy.task.paradigm.matrix import MatrixCalibrationTask +# from bcipy.task.paradigm.matrix.timing_verification import MatrixTimingVerificationCalibration + + +def demo_orchestrator(parameters_path: str) -> None: + """Demo the SessionOrchestrator. + + This function demonstrates how to use the SessionOrchestrator to execute actions. + + The action in this case is an OfflineAnalysisAction, which will analyze the data in a given directory. + """ + fake_data = True + alert_finished = True + tasks = [ + RSVPCalibrationTask, + IntertaskAction, + # OfflineAnalysisAction, + # IntertaskAction, + MatrixCalibrationTask, + IntertaskAction, + OfflineAnalysisAction, + IntertaskAction, + BciPyCalibrationReportAction + ] + orchestrator = SessionOrchestrator( + user='offline_testing', + parameters_path=parameters_path, + alert=alert_finished, + visualize=True, + fake=fake_data) + orchestrator.add_tasks(tasks) + orchestrator.execute() + + +if __name__ == '__main__': + + import argparse + + parser = argparse.ArgumentParser(description="Demo the SessionOrchestrator") + parser.add_argument( + '-p', + '--parameters_path', + help='Path to the parameters file to use for training. If none provided, data path will be used.', + default=DEFAULT_PARAMETERS_PATH) + args = parser.parse_args() + + parameters_path = f'{args.parameters_path}' + + demo_orchestrator(parameters_path) diff --git a/bcipy/task/main.py b/bcipy/task/main.py index 9e6b92f06..65083f8d1 100644 --- a/bcipy/task/main.py +++ b/bcipy/task/main.py @@ -1,6 +1,35 @@ -import logging - +from dataclasses import dataclass +from typing import Optional +from bcipy.helpers.parameters import Parameters from abc import ABC, abstractmethod +from enum import Enum + +from bcipy.helpers.stimuli import play_sound +from bcipy.config import STATIC_AUDIO_PATH + + +@dataclass +class TaskData(): + """TaskData. + + Data structure for storing task return data. + """ + save_path: Optional[str] = None + task_dict: Optional[dict] = None + + +class TaskMode(Enum): + CALIBRATION = "calibration" + COPYPHRASE = "copy phrase" + TIMING_VERIFICATION = "timing verification" + ACTION = "action" + TRAINING = "training" + + def __str__(self) -> str: + return self.value + + def __repr__(self) -> str: + return self.value class Task(ABC): @@ -8,15 +37,25 @@ class Task(ABC): Base class for BciPy tasks. """ + name: str + mode: TaskMode + parameters: Parameters + data_save_location: str - def __init__(self) -> None: + def __init__(self, *args, **kwargs) -> None: super(Task, self).__init__() - self.logger = logging.getLogger(__name__) + assert getattr(self, 'name', None) is not None, "Task must have a `name` attribute defined" + assert getattr(self, 'mode', None) is not None, "Task must have a `mode` attribute defined" @abstractmethod - def execute(self) -> str: + def execute(self) -> TaskData: ... - @abstractmethod - def name(self) -> str: + def setup(self, *args, **kwargs): ... + + def cleanup(self, *args, **kwargs): + ... + + def alert(self): + play_sound(f"{STATIC_AUDIO_PATH}/{self.parameters['alert_sound_file']}") diff --git a/bcipy/task/orchestrator/__init__.py b/bcipy/task/orchestrator/__init__.py new file mode 100644 index 000000000..df0973e4c --- /dev/null +++ b/bcipy/task/orchestrator/__init__.py @@ -0,0 +1,3 @@ +from bcipy.task.orchestrator.orchestrator import SessionOrchestrator + +__all__ = ['SessionOrchestrator'] diff --git a/bcipy/task/orchestrator/orchestrator.py b/bcipy/task/orchestrator/orchestrator.py new file mode 100644 index 000000000..b3b493242 --- /dev/null +++ b/bcipy/task/orchestrator/orchestrator.py @@ -0,0 +1,295 @@ +# mypy: disable-error-code="arg-type, assignment" +import errno +import os +import json +import subprocess +from datetime import datetime +import random +import logging +import time +from logging import Logger +from typing import List, Type, Optional + +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.system_utils import get_system_info, configure_logger +from bcipy.task import Task, TaskData, TaskMode +from bcipy.config import ( + DEFAULT_EXPERIMENT_ID, + DEFAULT_PARAMETERS_PATH, + DEFAULT_USER_ID, + MULTIPHRASE_FILENAME, + PROTOCOL_FILENAME, + PROTOCOL_LOG_FILENAME, + SESSION_LOG_FILENAME, +) +from bcipy.helpers.load import load_json_parameters + + +class SessionOrchestrator: + """ + Session Orchestrator + -------------------- + + The Session Orchestrator is responsible for managing the execution of a protocol of tasks. It is initialized with an + experiment ID, user ID, and parameters file. Tasks are added to the orchestrator, which are then executed in order. + """ + tasks: List[Type[Task]] + task_names: List[str] + parameters: Parameters + sys_info: dict + log: Logger + save_folder: str + session_data: List[TaskData] + ready_to_execute: bool = False + last_task_dir: Optional[str] = None + + def __init__( + self, + experiment_id: str = DEFAULT_EXPERIMENT_ID, + user: str = DEFAULT_USER_ID, + parameters_path: str = DEFAULT_PARAMETERS_PATH, + parameters: Parameters = None, + fake: bool = False, + alert: bool = False, + visualize: bool = False + ) -> None: + self.parameters_path = parameters_path + if not parameters: + self.parameters = load_json_parameters(parameters_path, value_cast=True) + else: + # This allows for the parameters to be passed in directly and modified before executions + self.parameters = parameters + + self.copyphrases = None + self.next_phrase = None + self.starting_index = 0 + + self.initialize_copy_phrases() + + self.user = user + self.fake = fake + self.experiment_id = experiment_id + self.sys_info = self.get_system_info() + self.tasks = [] + self.task_names = [] + self.session_data = [] + self.save_folder = self._init_orchestrator_save_folder(self.parameters["data_save_loc"]) + self.logger = self._init_orchestrator_logger(self.save_folder) + + self.alert = alert + self.logger.info("Alerts are on") if self.alert else self.logger.info("Alerts are off") + self.visualize = visualize + self.progress = 0 + + self.ready_to_execute = False + self.user_exit = False + self.logger.info("Session Orchestrator initialized successfully") + + def add_task(self, task: Type[Task]) -> None: + """Add a task to the orchestrator""" + self.tasks.append(task) + self.task_names.append(task.name) + self.ready_to_execute = True + + def add_tasks(self, tasks: List[Type[Task]]) -> None: + """Add a list of tasks to the orchestrator""" + for task in tasks: + self.add_task(task) + self.ready_to_execute = True + + def set_next_phrase(self) -> None: + """Set the next phrase to be copied from the list of copy phrases loaded or the parameters directly. + + If there are no more phrases to copy, the task text and spelled letters from parameters will be used. + """ + if self.copyphrases: + if len(self.copyphrases) > 0: + text, index = self.copyphrases.pop(0) + self.next_phrase = text + self.starting_index = index + else: + self.next_phrase = self.parameters['task_text'] + self.parameters['task_text'] = self.next_phrase + self.parameters['spelled_letters_count'] = self.starting_index + + def initialize_copy_phrases(self) -> None: + """Load copy phrases from a json file or take the task text if no file is provided. + + Expects a json file structured as follows: + { + "Phrases": [ + [string, int], + [string, int], + ... + ] + } + """ + # load copy phrases from json file or take the task text if no file is provided + if self.parameters.get('copy_phrases_location'): + with open(self.parameters['copy_phrases_location'], 'r') as f: + copy_phrases = json.load(f) + self.copyphrases = copy_phrases['Phrases'] + # randomize the order of the phrases + random.shuffle(self.copyphrases) + else: + self.copyphrases = None + self.next_phrase = self.parameters['task_text'] + self.starting_index = self.parameters['spelled_letters_count'] + + def execute(self) -> None: + """Executes queued tasks in order""" + + if not self.ready_to_execute: + msg = "Orchestrator not ready to execute. No tasks have been added." + self.log.error(msg) + raise Exception(msg) + + self.logger.info(f"Session Orchestrator executing tasks in order: {self.task_names}") + for task in self.tasks: + self.progress += 1 + if task.mode == TaskMode.COPYPHRASE: + self.set_next_phrase() + try: + # initialize the task save folder and logger + self.logger.info(f"Initializing task {self.progress}/{len(self.tasks)} {task.name}") + data_save_location = self._init_task_save_folder(task) + self._init_task_logger(data_save_location) + + # initialize the task and execute it + initialized_task: Task = task( + self.parameters, + data_save_location, + fake=self.fake, + alert_finished=self.alert, + experiment_id=self.experiment_id, + parameters_path=self.parameters_path, + protocol_path=self.save_folder, + last_task_dir=self.last_task_dir, + progress=self.progress, + tasks=self.tasks, + exit_callback=self.close_experiment_callback) + task_data = initialized_task.execute() + self.session_data.append(task_data) + self.logger.info(f"Task {task.name} completed successfully") + # some tasks may need access to the previous task's data + self.last_task_dir = data_save_location + + if self.user_exit: + break + + if initialized_task.mode != TaskMode.ACTION: + if self.alert: + initialized_task.alert() + + if self.visualize: + # Visualize session data and fail silently if it errors + try: + self.logger.info(f"Visualizing session data. Saving to {data_save_location}") + subprocess.run( + f'bcipy-erp-viz -s "{data_save_location}" ' + f'--parameters "{self.parameters_path}" --show --save', + shell=True) + except Exception as e: + self.logger.info(f'Error visualizing session data: {e}') + + initialized_task = None + + except Exception as e: + self.logger.error(f"Task {task.name} failed to execute") + self.logger.exception(e) + try: + initialized_task.cleanup() + except BaseException: + pass + + # give the orchestrator time to save data before exiting + time.sleep(1) + + # Save the protocol data and reset the orchestrator + self._save_data() + self.ready_to_execute = False + self.tasks = [] + self.task_names = [] + self.progress = 0 + + def _init_orchestrator_logger(self, save_folder: str) -> Logger: + return configure_logger( + save_folder, + PROTOCOL_LOG_FILENAME, + logging.DEBUG) + + def _init_orchestrator_save_folder(self, save_path: str) -> str: + timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") + # * No '/' after `save_folder` since it is included in + # * `data_save_location` in parameters + path = f'{save_path}{self.user}/{self.experiment_id}/{timestamp}/' + os.makedirs(path) + os.makedirs(os.path.join(path, 'logs'), exist_ok=True) + return path + + def _init_task_save_folder(self, task: Type[Task]) -> str: + timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") + save_directory = self.save_folder + f'{task.name.replace(" ", "_")}_{timestamp}/' + try: + # make a directory to save task data to + os.makedirs(save_directory) + os.makedirs(os.path.join(save_directory, 'logs'), exist_ok=True) + # save parameters to save directory with task name + self.parameters.add_entry( + "task", + { + "value": task.name, + "section": "task_congig", + "name": "BciPy Task", + "helpTip": "A string representing the task that was executed", + "recommended": "", + "editable": "false", + "type": "str", + } + ) + self.parameters.save(save_directory) + + except OSError as error: + # If the error is anything other than file existing, raise an error + if error.errno != errno.EEXIST: + raise error + return save_directory + + def _init_task_logger(self, save_folder: str) -> None: + configure_logger( + save_folder, + SESSION_LOG_FILENAME, + logging.DEBUG) + + def _save_data(self) -> None: + + self._save_procotol_data() + # Save the remaining phrase data to a json file to be used in the next session + if self.copyphrases and len(self.copyphrases) > 0: + self._save_copy_phrases() + + def _save_procotol_data(self) -> None: + # Save the protocol data to a json file + with open(f'{self.save_folder}/{PROTOCOL_FILENAME}', 'w') as f: + f.write(json.dumps({ + 'tasks': self.task_names, + 'parameters': self.parameters_path, + 'system_info': self.sys_info, + })) + self.logger.info("Protocol data successfully saved") + + def _save_copy_phrases(self) -> None: + # Save the copy phrases data to a json file + with open(f'{self.save_folder}/{MULTIPHRASE_FILENAME}', 'w') as f: + f.write(json.dumps({ + 'Phrases': self.copyphrases + })) + self.logger.info("Copy phrases data successfully saved") + + def get_system_info(self) -> dict: + return get_system_info() + + def close_experiment_callback(self): + """Callback to close the experiment.""" + self.logger.info("User has exited the experiment.") + self.user_exit = True diff --git a/bcipy/task/orchestrator/protocol.py b/bcipy/task/orchestrator/protocol.py new file mode 100644 index 000000000..af950162c --- /dev/null +++ b/bcipy/task/orchestrator/protocol.py @@ -0,0 +1,76 @@ +"""This file can define actions that can happen in a session orchestrator visit. +To start these will be 1:1 with tasks, but later this can be extended to represent training sequences, GUI popups etc""" + +from typing import List, Type +from bcipy.task import Task +from bcipy.config import TASK_SEPERATOR +from bcipy.task.registry import TaskRegistry + + +def parse_protocol(protocol: str) -> List[Type[Task]]: + """ + Parses a string of actions into a list of Task objects. + + Converts a string of actions into a list of Task objects. The string is expected + to be in the format of 'Action1 -> Action2 -> ... -> ActionN'. + Parameters + ---------- + protocol : str + A string of actions in the format of 'Action1 -> Action2 -> ... -> ActionN'. + + Returns + ------- + List[TaskType] + A list of TaskType objects that represent the actions in the input string. + """ + task_registry = TaskRegistry() + return [task_registry.get(item.strip()) for item in protocol.split(TASK_SEPERATOR)] + + +def validate_protocol_string(protocol: str) -> None: + """ + Validates a string of actions. + + Validates a string of actions. The string is expected to be in the format of 'Action1 -> Action2 -> ... -> ActionN'. + + Parameters + ---------- + protocol : str + A string of actions in the format of 'Action1 -> Action2 -> ... -> ActionN'. + + Raises + ------ + ValueError + If the string of actions is invalid. + """ + for protocol_item in protocol.split(TASK_SEPERATOR): + if protocol_item.strip() not in TaskRegistry().list(): + raise ValueError(f"Invalid task '{protocol_item}' name in protocol string.") + + +def serialize_protocol(protocol: List[Type[Task]]) -> str: + """ + Converts a list of TaskType objects into a string of actions. + + Converts a list of TaskType objects into a string of actions. The string is in the format of + 'Action1 -> Action2 -> ... -> ActionN'. + + Parameters + ---------- + protocol : str + A string of actions in the format of 'Action1 -> Action2 -> ... -> ActionN'. + + Returns + ------- + List[TaskType] + A list of TaskType objects that represent the actions in the input string. + """ + + return f" {TASK_SEPERATOR} ".join([item.name for item in protocol]) + + +if __name__ == '__main__': + actions = parse_protocol("Matrix Calibration -> Matrix Copy Phrase") + string = serialize_protocol(actions) + print(actions) + print(string) diff --git a/bcipy/task/paradigm/matrix/__init__.py b/bcipy/task/paradigm/matrix/__init__.py index e69de29bb..f7dd6bc2c 100644 --- a/bcipy/task/paradigm/matrix/__init__.py +++ b/bcipy/task/paradigm/matrix/__init__.py @@ -0,0 +1,4 @@ +# Import all matrix tasks to make them available to the task registry +from .calibration import MatrixCalibrationTask # noqa +from .copy_phrase import MatrixCopyPhraseTask # noqa +from .timing_verification import MatrixTimingVerificationCalibration # noqa diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index a4ab773aa..a16cc6305 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -1,6 +1,6 @@ -from typing import Any, Dict, Optional +from typing import Any, Dict, Optional, List -from psychopy import core, visual +from psychopy import visual from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CalibrationTaskBar @@ -10,7 +10,7 @@ from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import save_stimuli_position_info from bcipy.helpers.system_utils import get_screen_info -from bcipy.task.base_calibration import BaseCalibrationTask +from bcipy.task.calibration import BaseCalibrationTask class MatrixCalibrationTask(BaseCalibrationTask): @@ -28,12 +28,13 @@ class MatrixCalibrationTask(BaseCalibrationTask): PARAMETERS: ---------- - win (PsychoPy Display Object) - daq (Data Acquisition Object [ClientManager]]) - parameters (Parameters Object) - file_save (String) + parameters (dict) + file_save (str) + fake (bool) + """ - MODE = 'Matrix' + name = 'Matrix Calibration' + paradigm = 'Matrix' @property def screen_info(self) -> Dict[str, Any]: @@ -56,7 +57,6 @@ def exit_display(self) -> None: def cleanup(self) -> None: assert isinstance(self.display, MatrixDisplay) - # TODO: refactor offline_analysis to use session data and and remove this. save_stimuli_position_info(self.display.stim_positions, self.file_save, self.screen_info) return super().cleanup() @@ -68,7 +68,7 @@ def session_task_data(self) -> Optional[Dict[str, Any]]: def init_matrix_display(parameters: Parameters, window: visual.Window, experiment_clock: Clock, - symbol_set: core.StaticPeriod) -> MatrixDisplay: + symbol_set: List[str]) -> MatrixDisplay: """Initialize the matrix display""" info = InformationProperties( info_color=[parameters['info_color']], @@ -78,22 +78,23 @@ def init_matrix_display(parameters: Parameters, window: visual.Window, info_text=[parameters['info_text']], ) stimuli = StimuliProperties(stim_font=parameters['font'], - stim_pos=(-0.6, 0.4), - stim_height=0.1, + stim_pos=(parameters['matrix_stim_pos_x'], parameters['matrix_stim_pos_y']), + stim_height=parameters['matrix_stim_height'], stim_inquiry=[''] * parameters['stim_length'], stim_colors=[parameters['stim_color']] * parameters['stim_length'], stim_timing=[10] * parameters['stim_length'], is_txt_stim=parameters['is_txt_stim'], - prompt_time=parameters["time_prompt"]) + prompt_time=parameters['time_prompt'], + layout=parameters['matrix_keyboard_layout']) task_bar = CalibrationTaskBar(window, inquiry_count=parameters['stim_number'], current_index=0, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height'], - padding=parameters['task_padding']) + height=parameters['matrix_task_height'], + padding=parameters['matrix_task_padding']) return MatrixDisplay(window, experiment_clock, diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index a605688b8..79748e7b7 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -1,10 +1,14 @@ """Defines the Copy Phrase Task which uses a Matrix display""" +from psychopy import visual from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.main import PreviewParams from bcipy.display.paradigm.matrix.display import MatrixDisplay +from bcipy.task import TaskMode from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.clock import Clock class MatrixCopyPhraseTask(RSVPCopyPhraseTask): @@ -16,26 +20,83 @@ class MatrixCopyPhraseTask(RSVPCopyPhraseTask): Parameters ---------- - win : object, - display window to present visual stimuli. - daq : object, - data acquisition object initialized for the desired protocol parameters : dict, configuration details regarding the experiment. See parameters.json file_save : str, path location of where to save data from the session - signal_models : list of trained signal models. - language_model: object, - trained language model. fake : boolean, optional boolean to indicate whether this is a fake session or not. Returns ------- - file_save : str, - path location of where to save data from the session + TaskData """ - TASK_NAME = 'Matrix Copy Phrase Task' - MODE = 'Matrix' + name = 'Matrix Copy Phrase' + paradigm = 'Matrix' + mode = TaskMode.COPYPHRASE + + PARAMETERS_USED = [ + "time_fixation", + "time_flash", + "time_prompt", + "trial_window", + "font", + "fixation_color", + "trigger_type", + "filter_high", + "filter_low", + "filter_order", + "notch_filter_frequency", + "down_sampling_rate", + "prestim_length", + "is_txt_stim", + "lm_backspace_prob", + "backspace_always_shown", + "decision_threshold", + "max_inq_len", + "max_inq_per_series", + "max_minutes", + "max_selections", + "max_incorrect", + "min_inq_len", + "show_feedback", + "feedback_duration", + "show_preview_inquiry", + "preview_inquiry_isi", + "preview_inquiry_key_input", + "preview_inquiry_error_prob", + "preview_inquiry_length", + "preview_inquiry_progress_method", + "spelled_letters_count", + "stim_color", + "matrix_stim_height", + "stim_jitter", + "stim_length", + "stim_number", + "stim_order", + "stim_pos_x", + "stim_pos_y", + "stim_space_char", + "target_color", + "task_buffer_length", + "task_color", + "matrix_task_height", + "matrix_task_padding", + "matrix_keyboard_layout", + "matrix_rows", + "matrix_columns", + "matrix_width", + "matrix_stim_pos_x", + "matrix_stim_pos_y", + "task_text", + "info_pos_x", + "info_pos_y", + "info_color", + "info_height", + "info_text", + "info_color", + "info_height", + "info_text", + ] def init_display(self) -> MatrixDisplay: """Initialize the Matrix display""" @@ -44,7 +105,10 @@ def init_display(self) -> MatrixDisplay: def init_display( - parameters, win, experiment_clock, starting_spelled_text) -> MatrixDisplay: + parameters: Parameters, + win: visual.Window, + experiment_clock: Clock, + starting_spelled_text: str) -> MatrixDisplay: """Constructs a new Matrix display""" info = InformationProperties( @@ -56,19 +120,20 @@ def init_display( ) stimuli = StimuliProperties(stim_font=parameters['font'], - stim_pos=(parameters['stim_pos_x'], - parameters['stim_pos_y']), - stim_height=parameters['stim_height'], + stim_pos=(parameters['matrix_stim_pos_x'], + parameters['matrix_stim_pos_y']), + stim_height=parameters['matrix_stim_height'], is_txt_stim=parameters['is_txt_stim'], - prompt_time=parameters['time_prompt']) + prompt_time=parameters['time_prompt'], + layout=parameters['matrix_keyboard_layout']) task_bar = CopyPhraseTaskBar(win, task_text=parameters['task_text'], spelled_text=starting_spelled_text, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height'], - padding=parameters['task_padding']) + height=parameters['matrix_task_height'], + padding=parameters['matrix_task_padding']) return MatrixDisplay( win, diff --git a/bcipy/task/paradigm/matrix/timing_verification.py b/bcipy/task/paradigm/matrix/timing_verification.py index 2638f52a8..a26c20876 100644 --- a/bcipy/task/paradigm/matrix/timing_verification.py +++ b/bcipy/task/paradigm/matrix/timing_verification.py @@ -3,7 +3,8 @@ from bcipy.helpers.stimuli import (PhotoDiodeStimuli, get_fixation, jittered_timing) -from bcipy.task.base_calibration import Inquiry +from bcipy.task.calibration import Inquiry +from bcipy.task import TaskMode from bcipy.task.paradigm.matrix.calibration import (MatrixCalibrationTask, MatrixDisplay) @@ -15,15 +16,15 @@ class MatrixTimingVerificationCalibration(MatrixCalibrationTask): stimuli can be used with a photodiode to ensure accurate presentations. Input: - win (PsychoPy Display Object) - daq (Data Acquisition Object) parameters (Dictionary) file_save (String) + fake (Boolean) Output: - file_save (String) + TaskData """ - TASK_NAME = 'Matrix Timing Verification Task' + name = 'Matrix Timing Verification' + mode = TaskMode.TIMING_VERIFICATION def init_display(self) -> MatrixDisplay: """Initialize the display""" diff --git a/bcipy/task/paradigm/rsvp/__init__.py b/bcipy/task/paradigm/rsvp/__init__.py index e69de29bb..111883a46 100644 --- a/bcipy/task/paradigm/rsvp/__init__.py +++ b/bcipy/task/paradigm/rsvp/__init__.py @@ -0,0 +1,4 @@ +# Import all RSVP tasks to make them available to the task registry +from .calibration.calibration import RSVPCalibrationTask # noqa +from .calibration.timing_verification import RSVPTimingVerificationCalibration # noqa +from .copy_phrase import RSVPCopyPhraseTask # noqa diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 44b6a4cce..b381349f6 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -7,7 +7,7 @@ from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters from bcipy.helpers.triggers import TriggerType -from bcipy.task.base_calibration import BaseCalibrationTask +from bcipy.task.calibration import BaseCalibrationTask class RSVPCalibrationTask(BaseCalibrationTask): @@ -25,12 +25,12 @@ class RSVPCalibrationTask(BaseCalibrationTask): PARAMETERS: ---------- - win (PsychoPy Display) - daq (Data Acquisition Client) parameters (dict) file_save (str) + fake (bool) """ - MODE = 'RSVP' + name = 'RSVP Calibration' + paradigm = 'RSVP' def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: @@ -64,8 +64,8 @@ def init_calibration_display_task( ) stimuli = StimuliProperties( stim_font=parameters['font'], - stim_pos=(parameters['stim_pos_x'], parameters['stim_pos_y']), - stim_height=parameters['stim_height'], + stim_pos=(parameters['rsvp_stim_pos_x'], parameters['rsvp_stim_pos_y']), + stim_height=parameters['rsvp_stim_height'], stim_inquiry=[''] * parameters['stim_length'], stim_colors=[parameters['stim_color']] * parameters['stim_length'], stim_timing=[10] * parameters['stim_length'], @@ -76,8 +76,8 @@ def init_calibration_display_task( current_index=0, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height'], - padding=parameters['task_padding']) + height=parameters['rsvp_task_height'], + padding=parameters['rsvp_task_padding']) return CalibrationDisplay(window, static_clock, diff --git a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py index be94ca30c..07bcbba74 100644 --- a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py +++ b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py @@ -1,14 +1,12 @@ # mypy: disable-error-code="assignment" from itertools import cycle, islice, repeat -from typing import Iterator, List +from typing import Any, Iterator, List -from psychopy import visual - -from bcipy.acquisition import ClientManager from bcipy.helpers.parameters import Parameters from bcipy.helpers.stimuli import (PhotoDiodeStimuli, get_fixation, jittered_timing) -from bcipy.task.base_calibration import Inquiry +from bcipy.task.calibration import Inquiry +from bcipy.task import TaskMode from bcipy.task.paradigm.rsvp.calibration.calibration import \ RSVPCalibrationTask @@ -20,22 +18,25 @@ class RSVPTimingVerificationCalibration(RSVPCalibrationTask): stimuli can be used with a photodiode to ensure accurate presentations. Input: - win (PsychoPy Window) - daq (ClientManager) parameters (Parameters) file_save (str) + fake (bool) Output: - file_save (str) + TaskData """ - TASK_NAME = 'RSVP Timing Verification Task' + name = 'RSVP Timing Verification' + mode = TaskMode.TIMING_VERIFICATION - def __init__(self, win: visual.Window, daq: ClientManager, - parameters: Parameters, file_save: str) -> None: - parameters['stim_height'] = 0.8 - parameters['stim_pos_y'] = 0.0 + def __init__(self, + parameters: Parameters, + file_save: str, + fake: bool = False, + **kwargs: Any) -> None: + parameters['rsvp_stim_height'] = 0.8 + parameters['rsvp_stim_pos_y'] = 0.0 super(RSVPTimingVerificationCalibration, - self).__init__(win, daq, parameters, file_save) + self).__init__(parameters, file_save, fake=fake) @property def symbol_set(self) -> List[str]: @@ -63,10 +64,3 @@ def init_inquiry_generator(self) -> Iterator[Inquiry]: return repeat(Inquiry(stimuli, durations, colors), params['stim_number']) - - @classmethod - def label(cls) -> str: - return RSVPTimingVerificationCalibration.TASK_NAME - - def name(self) -> str: - return RSVPTimingVerificationCalibration.TASK_NAME diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 772d9c103..6380f029d 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -1,22 +1,34 @@ # mypy: disable-error-code="arg-type" import logging -from typing import List, NamedTuple, Optional, Tuple +from typing import Any, List, NamedTuple, Optional, Tuple from psychopy import core, visual +from psychopy.visual import Window from bcipy.acquisition import ClientManager -from bcipy.config import (DEFAULT_EVIDENCE_PRECISION, SESSION_DATA_FILENAME, - SESSION_SUMMARY_FILENAME, TRIGGER_FILENAME, - WAIT_SCREEN_MESSAGE) -from bcipy.display import (InformationProperties, PreviewInquiryProperties, - StimuliProperties) +from bcipy.config import ( + DEFAULT_EVIDENCE_PRECISION, + SESSION_DATA_FILENAME, + SESSION_SUMMARY_FILENAME, + TRIGGER_FILENAME, + WAIT_SCREEN_MESSAGE, + SESSION_LOG_FILENAME +) +from bcipy.display import ( + InformationProperties, + StimuliProperties, +) from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.main import PreviewParams from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay from bcipy.feedback.visual.visual_feedback import VisualFeedback +from bcipy.helpers.acquisition import init_acquisition, LslDataServer from bcipy.helpers.clock import Clock from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper -from bcipy.helpers.exceptions import TaskConfigurationException +from bcipy.display import init_display_window +from bcipy.exceptions import TaskConfigurationException +from bcipy.helpers.language_model import init_language_model +from bcipy.helpers.load import load_signal_models from bcipy.helpers.list import destutter from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import _save_session_related_data @@ -34,12 +46,13 @@ from bcipy.language.main import LanguageModel from bcipy.signal.model import SignalModel from bcipy.signal.model.inquiry_preview import compute_probs_after_preview -from bcipy.task import Task -from bcipy.task.control.evidence import (EvidenceEvaluator, - init_evidence_evaluator) +from bcipy.task import Task, TaskData, TaskMode +from bcipy.task.control.evidence import EvidenceEvaluator, init_evidence_evaluator from bcipy.task.data import EvidenceType, Inquiry, Session from bcipy.task.exceptions import DuplicateModelEvidence +logger = logging.getLogger(SESSION_LOG_FILENAME) + class Decision(NamedTuple): """Represents the result of evaluating evidence. @@ -53,6 +66,7 @@ class Decision(NamedTuple): - new_inq_schedule : the next inquiry to present if there was not a decision. """ + decision_made: bool selection: str spelled_text: str @@ -69,27 +83,21 @@ class RSVPCopyPhraseTask(Task): Parameters ---------- - win : object, - display window to present visual stimuli. - daq : object, - data acquisition object initialized for the desired protocol parameters : dict, configuration details regarding the experiment. See parameters.json file_save : str, path location of where to save data from the session - signal_models : list of trained signal models. - language_model: object, - trained language model. fake : boolean, optional boolean to indicate whether this is a fake session or not. Returns ------- - file_save : str, - path location of where to save data from the session + TaskData """ - TASK_NAME = 'RSVP Copy Phrase Task' - MODE = 'RSVP' + name = "RSVP Copy Phrase" + paradigm = "RSVP" + mode = TaskMode.COPYPHRASE + initalized = False PARAMETERS_USED = [ 'time_fixation', 'time_flash', 'time_prompt', 'trial_window', @@ -102,29 +110,28 @@ class RSVPCopyPhraseTask(Task): 'show_preview_inquiry', 'preview_inquiry_isi', 'preview_inquiry_error_prob', 'preview_inquiry_key_input', 'preview_inquiry_length', 'preview_inquiry_progress_method', 'spelled_letters_count', - 'stim_color', 'stim_height', 'stim_jitter', 'stim_length', 'stim_number', - 'stim_order', 'stim_pos_x', 'stim_pos_y', 'stim_space_char', 'target_color', - 'task_buffer_length', 'task_color', 'task_height', 'task_text', + 'stim_color', 'rsvp_stim_height', 'stim_jitter', 'stim_length', 'stim_number', + 'stim_order', 'rsvp_stim_pos_x', 'rsvp_stim_pos_y', 'stim_space_char', 'target_color', + 'task_buffer_length', 'task_color', 'rsvp_task_height', 'task_text', 'rsvp_task_padding', 'info_pos_x', 'info_pos_y', 'info_color', 'info_height', 'info_text', 'info_color', 'info_height', 'info_text', ] def __init__( - self, - win: visual.Window, - daq: ClientManager, - parameters: Parameters, - file_save: str, - signal_models: List[SignalModel], - language_model: LanguageModel, - fake: bool) -> None: + self, + parameters: Parameters, + file_save: str, + fake: bool = False, + **kwargs: Any + ) -> None: super(RSVPCopyPhraseTask, self).__init__() - self.logger = logging.getLogger(__name__) + self.fake = fake + self.parameters = parameters + self.language_model = self.get_language_model() + self.signal_models = self.get_signal_models() + daq, servers, win = self.setup(parameters, file_save, fake) + self.servers = servers self.window = win self.daq = daq - self.parameters = parameters - self.signal_models = signal_models - self.language_model = language_model - self.fake = fake self.validate_parameters() @@ -136,7 +143,8 @@ def __init__( self.button_press_error_prob = parameters['preview_inquiry_error_prob'] - self.evidence_evaluators = self.init_evidence_evaluators(signal_models) + self.signal_model = self.signal_models[0] if self.signal_models else None + self.evidence_evaluators = self.init_evidence_evaluators(self.signal_models) self.evidence_types = self.init_evidence_types(self.signal_models, self.evidence_evaluators) self.file_save = file_save @@ -144,32 +152,108 @@ def __init__( self.trigger_handler = self.default_trigger_handler() self.session_save_location = f"{self.file_save}/{SESSION_DATA_FILENAME}" - self.copy_phrase = parameters['task_text'] + self.copy_phrase = parameters["task_text"] - self.signal_model = signal_models[0] if signal_models else None self.evidence_precision = DEFAULT_EVIDENCE_PRECISION self.feedback = self.init_feedback() - self.setup() + self.set() # set a preview_only parameter self.parameters.add_entry( - 'preview_only', + "preview_only", { - 'value': 'true' if self.parameters['preview_inquiry_progress_method'] == 0 else 'false', - 'section': '', - 'readableName': '', - 'helpTip': '', - 'recommended_values': '', - 'type': 'bool' - } + "value": ( + "true" + if self.parameters["preview_inquiry_progress_method"] == 0 + else "false" + ), + "section": "", + "name": "", + "helpTip": "", + "recommended": "", + "editable": "false", + "type": "bool", + }, ) self.rsvp = self.init_display() - def init_evidence_evaluators(self, - signal_models: List[SignalModel]) -> List[EvidenceEvaluator]: + def setup(self, parameters, data_save_location, fake=False) -> Tuple[ClientManager, List[LslDataServer], Window]: + # Initialize Acquisition + daq, servers = init_acquisition( + parameters, data_save_location, server=fake) + + # Initialize Display + display = init_display_window(parameters) + self.initalized = True + + return daq, servers, display + + def get_language_model(self) -> LanguageModel: + return init_language_model(self.parameters) + + def get_signal_models(self) -> Optional[List[SignalModel]]: + if not self.fake: + try: + model_dir = self.parameters.get('signal_model_path', None) + signal_models = load_signal_models(directory=model_dir) + assert signal_models, f"No signal models found in {model_dir}" + except Exception as error: + logger.exception(f'Cannot load signal model. Exiting. {error}') + raise error + return signal_models + return [] + + def cleanup(self): + self.exit_display() + self.write_offset_trigger() + self.save_session_data() + # Wait some time before exiting so there is trailing eeg data saved + self.wait() + + if self.initalized: + + try: + # Stop Acquisition + self.daq.stop_acquisition() + self.daq.cleanup() + + # Stop Servers + if self.servers: + for server in self.servers: + server.stop() + + # Close the display window + # NOTE: There is currently a bug in psychopy when attempting to shutdown + # windows when using a USB-C monitor. Putting the display close last in + # the inquiry allows acquisition to properly shutdown. + self.window.close() + self.initalized = False + + except Exception as e: + logger.exception(str(e)) + + def save_session_data(self) -> None: + self.session.task_summary = TaskSummary( + self.session, + self.parameters["show_preview_inquiry"], + self.parameters["preview_inquiry_progress_method"], + self.trigger_handler.file_path, + ).as_dict() + self.write_session_data() + + # Evidence is not recorded in the session when using fake decisions. + if self.parameters["summarize_session"] and self.session.has_evidence(): + session_excel( + session=self.session, + excel_file=f"{self.file_save}/{SESSION_SUMMARY_FILENAME}", + ) + + def init_evidence_evaluators( + self, signal_models: List[SignalModel] + ) -> List[EvidenceEvaluator]: """Initializes the evidence evaluators from the provided signal models. Returns a list of evaluators for active devices. Raises an exception if @@ -189,7 +273,7 @@ def init_evidence_evaluators(self, ) evidence_types.append(evidence_type) else: - self.logger.info( + logger.info( f"SignalModel not used: there is no active device of type: {content_type}" ) return evaluators @@ -210,19 +294,19 @@ def default_trigger_handler(self) -> TriggerHandler: return TriggerHandler(self.file_save, TRIGGER_FILENAME, FlushFrequency.EVERY) - def setup(self) -> None: + def set(self) -> None: """Initialize/reset parameters used in the execute run loop.""" - self.spelled_text = str( - self.copy_phrase[0:self.starting_spelled_letters()]) - self.last_selection = '' + self.spelled_text = str(self.copy_phrase[0: self.starting_spelled_letters()]) + self.last_selection = "" self.inq_counter = 0 self.session = Session( save_location=self.file_save, - task='Copy Phrase', - mode=self.MODE, + task="Copy Phrase", + mode=str(self.mode), symbol_set=self.alp, - decision_threshold=self.parameters['decision_threshold']) + decision_threshold=self.parameters["decision_threshold"], + ) self.write_session_data() self.init_copy_phrase_task() @@ -230,10 +314,13 @@ def setup(self) -> None: def init_display(self) -> CopyPhraseDisplay: """Initialize the display""" - return _init_copy_phrase_display(self.parameters, self.window, - self.static_clock, - self.experiment_clock, - self.spelled_text) + return _init_copy_phrase_display( + self.parameters, + self.window, + self.static_clock, + self.experiment_clock, + self.spelled_text, + ) def init_feedback(self) -> Optional[VisualFeedback]: """Initialize visual feedback""" @@ -259,22 +346,26 @@ def validate_parameters(self) -> None: raise TaskConfigurationException(f"parameter '{param}' is required") # ensure data / query parameters are set correctly - buffer_len = self.parameters['task_buffer_length'] - prestim = self.parameters['prestim_length'] - poststim = self.parameters['trial_window'][1] - self.parameters['trial_window'][0] + buffer_len = self.parameters["task_buffer_length"] + prestim = self.parameters["prestim_length"] + poststim = ( + self.parameters["trial_window"][1] - self.parameters["trial_window"][0] + ) if buffer_len < prestim: raise TaskConfigurationException( - f'task_buffer_length=[{buffer_len}] must be greater than prestim_length=[{prestim}]') + f"task_buffer_length=[{buffer_len}] must be greater than prestim_length=[{prestim}]" + ) if buffer_len < poststim: raise TaskConfigurationException( - f'task_buffer_length=[{buffer_len}] must be greater than trial_length=[{poststim}]') + f"task_buffer_length=[{buffer_len}] must be greater than trial_length=[{poststim}]" + ) def starting_spelled_letters(self) -> int: """Number of letters already spelled at the start of the task.""" - spelled_letters_count = self.parameters['spelled_letters_count'] + spelled_letters_count = self.parameters["spelled_letters_count"] if spelled_letters_count > len(self.copy_phrase): - self.logger.info('Already spelled letters exceeds phrase length.') + logger.info("Already spelled letters exceeds phrase length.") spelled_letters_count = 0 return spelled_letters_count @@ -294,22 +385,24 @@ def init_copy_phrase_task(self) -> None: """ self.copy_phrase_task = CopyPhraseWrapper( - self.parameters['min_inq_len'], - self.parameters['max_inq_per_series'], + self.parameters["min_inq_len"], + self.parameters["max_inq_per_series"], lmodel=self.language_model, alp=self.alp, evidence_names=self.evidence_types, task_list=[(str(self.copy_phrase), self.spelled_text)], - is_txt_stim=self.parameters['is_txt_stim'], + is_txt_stim=self.parameters["is_txt_stim"], stim_timing=[ - self.parameters['time_fixation'], self.parameters['time_flash'] + self.parameters["time_fixation"], + self.parameters["time_flash"], ], - decision_threshold=self.parameters['decision_threshold'], - backspace_prob=self.parameters['lm_backspace_prob'], - backspace_always_shown=self.parameters['backspace_always_shown'], - stim_length=self.parameters['stim_length'], - stim_jitter=self.parameters['stim_jitter'], - stim_order=StimuliOrder(self.parameters['stim_order'])) + decision_threshold=self.parameters["decision_threshold"], + backspace_prob=self.parameters["lm_backspace_prob"], + backspace_always_shown=self.parameters["backspace_always_shown"], + stim_length=self.parameters["stim_length"], + stim_jitter=self.parameters["stim_jitter"], + stim_order=StimuliOrder(self.parameters["stim_order"]), + ) def user_wants_to_continue(self) -> bool: """Check if user wants to continue or terminate. @@ -322,10 +415,11 @@ def user_wants_to_continue(self) -> bool: should_continue = get_user_input( self.rsvp, WAIT_SCREEN_MESSAGE, - self.parameters['stim_color'], - first_run=self.first_run) + self.parameters["stim_color"], + first_run=self.first_run, + ) if not should_continue: - self.logger.info('User wants to exit.') + logger.info("User wants to exit.") return should_continue def wait(self, seconds: Optional[float] = None) -> None: @@ -336,11 +430,12 @@ def wait(self, seconds: Optional[float] = None) -> None: - seconds : duration of time to wait; if missing, defaults to the value of the parameter `'task_buffer_length'` """ - seconds = seconds or self.parameters['task_buffer_length'] + seconds = seconds or self.parameters["task_buffer_length"] core.wait(seconds) - def present_inquiry(self, inquiry_schedule: InquirySchedule - ) -> Tuple[List[Tuple[str, float]], bool]: + def present_inquiry( + self, inquiry_schedule: InquirySchedule + ) -> Tuple[List[Tuple[str, float]], bool]: """Present the given inquiry and return the trigger timing info. Parameters @@ -367,10 +462,13 @@ def present_inquiry(self, inquiry_schedule: InquirySchedule self.wait() # Setup the new stimuli - self.rsvp.schedule_to(stimuli=inquiry_schedule.stimuli[0], - timing=inquiry_schedule.durations[0], - colors=inquiry_schedule.colors[0] - if self.parameters['is_txt_stim'] else None) + self.rsvp.schedule_to( + stimuli=inquiry_schedule.stimuli[0], + timing=inquiry_schedule.durations[0], + colors=( + inquiry_schedule.colors[0] if self.parameters["is_txt_stim"] else None + ), + ) stim_times = self.rsvp.do_inquiry() proceed = not self.rsvp.preview_enabled or self.rsvp.preview_accepted @@ -393,31 +491,36 @@ def check_stop_criteria(self) -> bool: should continue. """ if self.copy_phrase == self.spelled_text: - self.logger.info('Spelling complete') + logger.info("Spelling complete") return False - if (self.inq_counter + 1) >= self.parameters['max_inq_len']: - self.logger.info('Max tries exceeded: to allow for more tries' - ' adjust the Maximum inquiry Length ' - '(max_inq_len) parameter.') + if (self.inq_counter + 1) >= self.parameters["max_inq_len"]: + logger.info( + "Max tries exceeded: to allow for more tries" + " adjust the Maximum inquiry Length " + "(max_inq_len) parameter." + ) return False - if self.session.total_time_spent >= (self.parameters['max_minutes'] * - 60): - self.logger.info('Max time exceeded. To allow for more time ' - 'adjust the max_minutes parameter.') + if self.session.total_time_spent >= (self.parameters["max_minutes"] * 60): + logger.info( + "Max time exceeded. To allow for more time " + "adjust the max_minutes parameter." + ) return False - if self.session.total_number_decisions >= self.parameters['max_selections']: - self.logger.info('Max number of selections reached ' - '(configured with the max_selections parameter)') + if self.session.total_number_decisions >= self.parameters["max_selections"]: + logger.info( + "Max number of selections reached " + "(configured with the max_selections parameter)" + ) return False if consecutive_incorrect( target_text=self.copy_phrase, spelled_text=self.spelled_text) >= self.parameters.get( - 'max_incorrect', 3): - self.logger.info( + 'max_incorrect'): + logger.info( 'Max number of consecutive incorrect selections reached ' '(configured with the max_incorrect parameter)') return False @@ -425,28 +528,26 @@ def check_stop_criteria(self) -> bool: return True def next_target(self) -> str: - """Computes the next target letter based on the currently spelled_text. - """ - if self.copy_phrase[0:len(self.spelled_text)] == self.spelled_text: + """Computes the next target letter based on the currently spelled_text.""" + if self.copy_phrase[0: len(self.spelled_text)] == self.spelled_text: # if correctly spelled so far, get the next letter. return self.copy_phrase[len(self.spelled_text)] return BACKSPACE_CHAR - def execute(self) -> str: + def execute(self) -> TaskData: """Executes the task. Returns ------- data save location (triggers.txt, session.json) """ - self.logger.info('Starting Copy Phrase Task!') + logger.info("Starting Copy Phrase Task!") run = True self.wait() # buffer for data processing while run and self.user_wants_to_continue() and self.current_inquiry: target_stimuli = self.next_target() - stim_times, proceed = self.present_inquiry( - self.current_inquiry) + stim_times, proceed = self.present_inquiry(self.current_inquiry) self.write_trigger_data(stim_times, target_stimuli) self.wait() @@ -464,8 +565,9 @@ def execute(self) -> str: decision_made=decision.decision_made) if decision.decision_made: - self.show_feedback(decision.selection, - (decision.selection == target_stimuli)) + self.show_feedback( + decision.selection, (decision.selection == target_stimuli) + ) self.spelled_text = decision.spelled_text self.current_inquiry = self.next_inquiry() @@ -475,24 +577,9 @@ def execute(self) -> str: run = self.check_stop_criteria() self.inq_counter += 1 - self.exit_display() - self.write_offset_trigger() - - self.session.task_summary = TaskSummary( - self.session, self.parameters['show_preview_inquiry'], - self.parameters['preview_inquiry_progress_method'], - self.trigger_handler.file_path).as_dict() - self.write_session_data() - - # Evidence is not recorded in the session when using fake decisions. - if self.parameters['summarize_session'] and self.session.has_evidence(): - session_excel(session=self.session, - excel_file=f"{self.file_save}/{SESSION_SUMMARY_FILENAME}") - - # Wait some time before exiting so there is trailing eeg data saved - self.wait() + self.cleanup() - return self.file_save + return TaskData(save_path=self.file_save, task_dict=self.session.as_dict()) def evaluate_evidence(self) -> Decision: """Uses the `copy_phrase_task` parameter to evaluate the provided @@ -503,9 +590,9 @@ def evaluate_evidence(self) -> Decision: - self.copy_phrase_task """ if self.fake: - _, spelled, _ = fake_copy_phrase_decision(self.copy_phrase, - self.next_target(), - self.spelled_text) + _, spelled, _ = fake_copy_phrase_decision( + self.copy_phrase, self.next_target(), self.spelled_text + ) # Reset the stoppage criteria by forcing the commit to a decision. self.copy_phrase_task.decision_maker.do_series() # In fake mode, only the LM is providing evidence, so the decision @@ -513,21 +600,24 @@ def evaluate_evidence(self) -> Decision: self.copy_phrase_task.decision_maker.update(spelled) # In fake mode, all inquiries result in a selection. - return Decision(decision_made=True, - selection=spelled[-1], - spelled_text=spelled, - new_inq_schedule=None) + return Decision( + decision_made=True, + selection=spelled[-1], + spelled_text=spelled, + new_inq_schedule=None, + ) decision_made, new_sti = self.copy_phrase_task.decide() spelled_text = self.copy_phrase_task.decision_maker.displayed_state - selection = '' + selection = "" if decision_made: selection = self.copy_phrase_task.decision_maker.last_selection return Decision(decision_made, selection, spelled_text, new_sti) - def add_evidence(self, stim_times: List[List], - proceed: bool = True) -> List[EvidenceType]: + def add_evidence( + self, stim_times: List[List], proceed: bool = True + ) -> List[EvidenceType]: """Add all evidence used to make a decision. Evaluates evidence from various sources (button press, devices, @@ -546,9 +636,7 @@ def add_evidence(self, stim_times: List[List], -------- - self.copy_phrase_task """ - evidences = [ - self.compute_button_press_evidence(proceed) - ] + evidences = [self.compute_button_press_evidence(proceed)] # evidence from one or more devices evidences.extend(self.compute_device_evidence(stim_times, proceed)) @@ -563,7 +651,8 @@ def add_evidence(self, stim_times: List[List], return evidence_types def compute_button_press_evidence( - self, proceed: bool) -> Optional[Tuple[EvidenceType, List[float]]]: + self, proceed: bool + ) -> Optional[Tuple[EvidenceType, List[float]]]: """If 'show_preview_inquiry' feature is enabled, compute the button press evidence and add it to the copy phrase task. @@ -576,20 +665,23 @@ def compute_button_press_evidence( tuple of (evidence type, evidence) or None if inquiry preview is not enabled. """ - if not self.parameters['show_preview_inquiry'] \ - or not self.current_inquiry \ - or self.parameters['preview_only']: + if ( + not self.parameters["show_preview_inquiry"] or + not self.current_inquiry or + self.parameters["preview_only"] + ): return None - probs = compute_probs_after_preview(self.current_inquiry.stimuli[0], - self.alp, - self.button_press_error_prob, - proceed) + probs = compute_probs_after_preview( + self.current_inquiry.stimuli[0], + self.alp, + self.button_press_error_prob, + proceed, + ) return (EvidenceType.BTN, probs) def compute_device_evidence( - self, - stim_times: List[List], - proceed: bool = True) -> List[Tuple[EvidenceType, List[float]]]: + self, stim_times: List[List], proceed: bool = True + ) -> List[Tuple[EvidenceType, List[float]]]: """Get inquiry data from all devices and evaluate the evidence, but don't yet attempt a decision. @@ -608,13 +700,15 @@ def compute_device_evidence( # currently prestim_length is used as a buffer for filter application post_stim_buffer = int(self.parameters.get("task_buffer_length") / 2) - prestim_buffer: float = self.parameters['prestim_length'] - trial_window: Tuple[float, float] = self.parameters['trial_window'] + prestim_buffer: float = self.parameters["prestim_length"] + trial_window: Tuple[float, float] = self.parameters["trial_window"] window_length = trial_window[1] - trial_window[0] inquiry_timing = self.stims_for_decision(stim_times) # update the inquiry timing list (stim, time) based on the trial window first time value - inquiry_timing = [(stim, time + trial_window[0]) for stim, time in inquiry_timing] + inquiry_timing = [ + (stim, time + trial_window[0]) for stim, time in inquiry_timing + ] # Get all data at once so we don't redundantly query devices which are # used in more than one signal model. @@ -622,13 +716,15 @@ def compute_device_evidence( inquiry_timing=inquiry_timing, daq=self.daq, prestim=prestim_buffer, - poststim=post_stim_buffer + window_length) + poststim=post_stim_buffer + window_length, + ) triggers = relative_triggers(inquiry_timing, prestim_buffer) # we assume all are nontargets at this point - labels = ['nontarget'] * len(triggers) + labels = ["nontarget"] * len(triggers) letters, times, filtered_labels = self.copy_phrase_task.letter_info( - triggers, labels) + triggers, labels + ) evidences = [] for evidence_evaluator in self.evidence_evaluators: @@ -637,12 +733,15 @@ def compute_device_evidence( symbols=letters, times=times, target_info=filtered_labels, - window_length=window_length) + window_length=window_length, + ) evidences.append((evidence_evaluator.produces, probs)) return evidences - def stims_for_decision(self, stim_times: List[Tuple[str, float]]) -> List[Tuple[str, float]]: + def stims_for_decision( + self, stim_times: List[Tuple[str, float]] + ) -> List[Tuple[str, float]]: """The stim_timings from the display may include non-letter stimuli such as calibration and inquiry_preview timings. This method extracts only the letter data used to process the data for a decision. @@ -656,16 +755,16 @@ def stims_for_decision(self, stim_times: List[Tuple[str, float]]) -> List[Tuple[ stim times where the stim is in the current alphabet; filters out 'calibration', 'inquiry_preview', etc. """ - return [ - timing for timing in stim_times if timing[0] in (self.alp + ['+']) - ] - - def new_data_record(self, - stim_times: List[Tuple[str, float]], - target_stimuli: str, - current_text: str, - decision: Decision, - evidence_types: Optional[List[EvidenceType]] = None) -> Inquiry: + return [timing for timing in stim_times if timing[0] in (self.alp + ["+"])] + + def new_data_record( + self, + stim_times: List[Tuple[str, float]], + target_stimuli: str, + current_text: str, + decision: Decision, + evidence_types: Optional[List[EvidenceType]] = None, + ) -> Inquiry: """Construct a new inquiry data record. Parameters @@ -685,16 +784,19 @@ def new_data_record(self, assert self.current_inquiry, "Current inquiry is required" evidence_types = evidence_types or [] triggers = construct_triggers(self.stims_for_decision(stim_times)) - data = Inquiry(stimuli=self.current_inquiry.stimuli, - timing=self.current_inquiry.durations, - triggers=triggers, - target_info=target_info(triggers, target_stimuli, - self.parameters['is_txt_stim']), - target_letter=target_stimuli, - current_text=current_text, - target_text=self.copy_phrase, - selection=decision.selection, - next_display_state=decision.spelled_text) + data = Inquiry( + stimuli=self.current_inquiry.stimuli, + timing=self.current_inquiry.durations, + triggers=triggers, + target_info=target_info( + triggers, target_stimuli, self.parameters["is_txt_stim"] + ), + target_letter=target_stimuli, + current_text=current_text, + target_text=self.copy_phrase, + selection=decision.selection, + next_display_state=decision.spelled_text, + ) data.precision = self.evidence_precision if not self.fake: @@ -719,10 +821,9 @@ def exit_display(self) -> None: # Give the system time to process self.wait() - def update_session_data(self, - data: Inquiry, - save: bool = True, - decision_made: bool = False) -> None: + def update_session_data( + self, data: Inquiry, save: bool = True, decision_made: bool = False + ) -> None: """Update the current session with the latest inquiry data Parameters @@ -749,25 +850,26 @@ def write_session_data(self) -> None: """Save session data to disk.""" if self.session: session_file = _save_session_related_data( - self.session_save_location, - self.session.as_dict()) + self.session_save_location, self.session.as_dict() + ) session_file.close() def write_offset_trigger(self) -> None: - """Append the offset to the end of the triggers file. - """ + """Append the offset to the end of the triggers file.""" # To help support future refactoring or use of lsl timestamps only # we write only the sample offset here. triggers = [] for content_type, client in self.daq.clients_by_type.items(): - label = offset_label(content_type.name, prefix='daq_sample_offset') + label = offset_label(content_type.name, prefix="daq_sample_offset") time = client.offset(self.rsvp.first_stim_time) triggers.append(Trigger(label, TriggerType.SYSTEM, time)) self.trigger_handler.add_triggers(triggers) self.trigger_handler.close() - def write_trigger_data(self, stim_times: List[Tuple[str, float]], target_stimuli: str) -> None: + def write_trigger_data( + self, stim_times: List[Tuple[str, float]], target_stimuli: str + ) -> None: """Save trigger data to disk. Parameters @@ -781,13 +883,15 @@ def write_trigger_data(self, stim_times: List[Tuple[str, float]], target_stimuli offset_triggers = [] for content_type, client in self.daq.clients_by_type.items(): label = offset_label(content_type.name) - time = client.offset( - self.rsvp.first_stim_time) - self.rsvp.first_stim_time - offset_triggers.append(Trigger(label, TriggerType.OFFSET, - time)) + time = ( + client.offset(self.rsvp.first_stim_time) - self.rsvp.first_stim_time + ) + offset_triggers.append(Trigger(label, TriggerType.OFFSET, time)) self.trigger_handler.add_triggers(offset_triggers) - triggers = convert_timing_triggers(stim_times, target_stimuli, self.trigger_type) + triggers = convert_timing_triggers( + stim_times, target_stimuli, self.trigger_type + ) self.trigger_handler.add_triggers(triggers) def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: @@ -795,19 +899,16 @@ def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: Cast a given symbol to a TriggerType. """ - if symbol == 'inquiry_preview': + if symbol == "inquiry_preview": return TriggerType.PREVIEW - if 'bcipy_key_press' in symbol: + if "bcipy_key_press" in symbol: return TriggerType.EVENT - if symbol == '+': + if symbol == "+": return TriggerType.FIXATION if target == symbol: return TriggerType.TARGET return TriggerType.NONTARGET - def name(self) -> str: - return self.TASK_NAME - @property def first_run(self) -> bool: """First run. @@ -830,50 +931,47 @@ class TaskSummary: 2 = press to skip to another inquiry """ - def __init__(self, - session: Session, - show_preview: bool = False, - preview_mode: int = 0, - trigger_path: Optional[str] = None) -> None: - assert preview_mode in range(3), 'Preview mode out of range' + def __init__( + self, + session: Session, + show_preview: bool = False, + preview_mode: int = 0, + trigger_path: Optional[str] = None, + ) -> None: + assert preview_mode in range(3), "Preview mode out of range" self.session = session self.show_preview = show_preview self.preview_mode = preview_mode self.trigger_path = trigger_path - self.logger = logging.getLogger(__name__) + logger = logging.getLogger(__name__) def as_dict(self) -> dict: """Computes the task summary data to append to the session.""" - selections = [ - inq for inq in self.session.all_inquiries if inq.selection - ] + selections = [inq for inq in self.session.all_inquiries if inq.selection] correct = [inq for inq in selections if inq.is_correct_decision] incorrect = [inq for inq in selections if not inq.is_correct_decision] # Note that SPACE is considered a symbol - correct_symbols = [ - inq for inq in correct if inq.selection != BACKSPACE_CHAR - ] + correct_symbols = [inq for inq in correct if inq.selection != BACKSPACE_CHAR] btn_presses = self.btn_press_count() sel_count = len(selections) - switch_per_selection = (btn_presses / - sel_count) if sel_count > 0 else 0 + switch_per_selection = (btn_presses / sel_count) if sel_count > 0 else 0 accuracy = (len(correct) / sel_count) if sel_count > 0 else 0 # Note that minutes includes startup time and any breaks. minutes = self.session.total_time_spent / 60 return { - 'selections_correct': len(correct), - 'selections_incorrect': len(incorrect), - 'selections_correct_symbols': len(correct_symbols), - 'switch_total': btn_presses, - 'switch_per_selection': switch_per_selection, - 'switch_response_time': self.switch_response_time(), - 'typing_accuracy': accuracy, - 'correct_rate': len(correct) / minutes if minutes else 0, - 'copy_rate': len(correct_symbols) / minutes if minutes else 0 + "selections_correct": len(correct), + "selections_incorrect": len(incorrect), + "selections_correct_symbols": len(correct_symbols), + "switch_total": btn_presses, + "switch_per_selection": switch_per_selection, + "switch_response_time": self.switch_response_time(), + "typing_accuracy": accuracy, + "correct_rate": len(correct) / minutes if minutes else 0, + "copy_rate": len(correct_symbols) / minutes if minutes else 0, } def btn_press_count(self) -> int: @@ -903,13 +1001,12 @@ def switch_response_time(self) -> Optional[float]: # Confirm that the data is structured as expected. for preview, keypress in pairs: if (preview.type != TriggerType.PREVIEW) or ( - keypress.type != TriggerType.EVENT): - self.logger.info('Could not compute switch_response_time') + keypress.type != TriggerType.EVENT + ): + logger.info("Could not compute switch_response_time") return None - response_times = [ - keypress.time - preview.time for preview, keypress in pairs - ] + response_times = [keypress.time - preview.time for preview, keypress in pairs] count = len(response_times) return sum(response_times) / count if count > 0 else None @@ -919,48 +1016,45 @@ def switch_triggers(self) -> List[Trigger]: return [] triggers, _offset = TriggerHandler.read_text_file(self.trigger_path) return [ - trg for trg in triggers + trg + for trg in triggers if trg.type in [TriggerType.PREVIEW, TriggerType.EVENT] ] def _init_copy_phrase_display( - parameters: Parameters, - win: visual.Window, - static_clock: core.StaticPeriod, - experiment_clock: Clock, - starting_spelled_text) -> CopyPhraseDisplay: - preview_inquiry = PreviewInquiryProperties( - preview_on=parameters['show_preview_inquiry'], - preview_only=parameters['preview_only'], - preview_inquiry_length=parameters['preview_inquiry_length'], - preview_inquiry_key_input=parameters['preview_inquiry_key_input'], - preview_inquiry_progress_method=parameters[ - 'preview_inquiry_progress_method'], - preview_inquiry_isi=parameters['preview_inquiry_isi']) + parameters: Parameters, + win: visual.Window, + static_clock: core.StaticPeriod, + experiment_clock: Clock, + starting_spelled_text, +) -> CopyPhraseDisplay: info = InformationProperties( - info_color=[parameters['info_color']], - info_pos=[(parameters['info_pos_x'], parameters['info_pos_y'])], - info_height=[parameters['info_height']], - info_font=[parameters['font']], - info_text=[parameters['info_text']], + info_color=[parameters["info_color"]], + info_pos=[(parameters["info_pos_x"], parameters["info_pos_y"])], + info_height=[parameters["info_height"]], + info_font=[parameters["font"]], + info_text=[parameters["info_text"]], + ) + stimuli = StimuliProperties( + stim_font=parameters["font"], + stim_pos=(parameters["rsvp_stim_pos_x"], parameters["rsvp_stim_pos_y"]), + stim_height=parameters["rsvp_stim_height"], + stim_inquiry=["A"] * parameters["stim_length"], + stim_colors=[parameters["stim_color"]] * parameters["stim_length"], + stim_timing=[10] * parameters["stim_length"], + is_txt_stim=parameters["is_txt_stim"], + ) + + task_bar = CopyPhraseTaskBar( + win, + task_text=parameters["task_text"], + spelled_text=starting_spelled_text, + colors=[parameters["task_color"]], + font=parameters["font"], + height=parameters["rsvp_task_height"], + padding=parameters["rsvp_task_padding"], ) - stimuli = StimuliProperties(stim_font=parameters['font'], - stim_pos=(parameters['stim_pos_x'], - parameters['stim_pos_y']), - stim_height=parameters['stim_height'], - stim_inquiry=['A'] * parameters['stim_length'], - stim_colors=[parameters['stim_color']] * parameters['stim_length'], - stim_timing=[10] * parameters['stim_length'], - is_txt_stim=parameters['is_txt_stim']) - - task_bar = CopyPhraseTaskBar(win, - task_text=parameters['task_text'], - spelled_text=starting_spelled_text, - colors=[parameters['task_color']], - font=parameters['font'], - height=parameters['task_height'], - padding=parameters['task_padding']) return CopyPhraseDisplay( win, diff --git a/bcipy/task/paradigm/vep/__init__.py b/bcipy/task/paradigm/vep/__init__.py index e69de29bb..bbcb8bd6c 100644 --- a/bcipy/task/paradigm/vep/__init__.py +++ b/bcipy/task/paradigm/vep/__init__.py @@ -0,0 +1,2 @@ +# Import all VEP tasks to make them available to the task registry +from .calibration import VEPCalibrationTask # noqa diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index e291a6121..34cf9909e 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -1,9 +1,10 @@ """VEP Calibration task-related code""" +import logging from typing import Any, Dict, Iterator, List, Optional from psychopy import visual # type: ignore -from bcipy.acquisition.multimodal import ClientManager +from bcipy.config import DEFAULT_FRAME_RATE, SESSION_LOG_FILENAME from bcipy.display import InformationProperties, VEPStimuliProperties from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar @@ -13,10 +14,12 @@ from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters from bcipy.helpers.triggers import TriggerType -from bcipy.task.base_calibration import BaseCalibrationTask, Inquiry +from bcipy.task.calibration import BaseCalibrationTask, Inquiry from bcipy.task.paradigm.vep.stim_generation import \ generate_vep_calibration_inquiries +logger = logging.getLogger(SESSION_LOG_FILENAME) + class VEPCalibrationTask(BaseCalibrationTask): """VEP Calibration Task. @@ -28,26 +31,30 @@ class VEPCalibrationTask(BaseCalibrationTask): PARAMETERS: ---------- - win (PsychoPy Display Object) - daq (Data Acquisition Object) - parameters (Dictionary) - file_save (String) + parameters (dict) + file_save (str) + fake (bool) """ - MODE = 'VEP' - - def __init__(self, win: visual.Window, daq: ClientManager, - parameters: Parameters, file_save: str): + name = 'VEP Calibration' + paradigm = 'VEP' + + def __init__(self, + parameters: Parameters, + file_save: str, + fake: bool = False, + **kwargs: Any) -> None: self.box_colors = [ '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' ] self.num_boxes = 6 - super().__init__(win, daq, parameters, file_save) + super().__init__(parameters, file_save, fake=fake, **kwargs) def init_display(self) -> VEPDisplay: """Initialize the display""" return init_vep_display(self.parameters, self.window, self.experiment_clock, self.symbol_set, - self.box_colors) + self.box_colors, + fake=self.fake) def init_inquiry_generator(self) -> Iterator[Inquiry]: """Initializes a generator that returns inquiries to be presented.""" @@ -118,7 +125,7 @@ def target_box_index(inquiry: Inquiry) -> Optional[int]: def init_vep_display(parameters: Parameters, window: visual.Window, experiment_clock: Clock, symbol_set: List[str], - box_colors: List[str]) -> VEPDisplay: + box_colors: List[str], fake: bool = False) -> VEPDisplay: """Initialize the display""" info = InformationProperties( info_color=[parameters['info_color']], @@ -141,7 +148,7 @@ def init_vep_display(parameters: Parameters, window: visual.Window, stim_props = VEPStimuliProperties( stim_font=parameters['font'], stim_pos=box_config.positions, - stim_height=0.1, + stim_height=parameters['vep_stim_height'], timing=timing, stim_color=colors, inquiry=[], @@ -153,9 +160,15 @@ def init_vep_display(parameters: Parameters, window: visual.Window, current_index=0, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height']) + height=parameters['vep_task_height']) # issue #186641183 ; determine a better configuration strategy for flicker + if fake: + frame_rate = window.getActualFrameRate() + if frame_rate is None: + frame_rate = DEFAULT_FRAME_RATE + + logger.info(f"Frame rate set to: {frame_rate}") return VEPDisplay(window, experiment_clock, @@ -165,4 +178,5 @@ def init_vep_display(parameters: Parameters, window: visual.Window, symbol_set=symbol_set, box_config=box_config, flicker_rates=DEFAULT_FLICKER_RATES, - should_prompt_target=True) + should_prompt_target=True, + frame_rate=frame_rate if fake else None) diff --git a/bcipy/task/registry.py b/bcipy/task/registry.py new file mode 100644 index 000000000..36b1bacf2 --- /dev/null +++ b/bcipy/task/registry.py @@ -0,0 +1,49 @@ +"""Task Registry ; used to provide task options to the GUI and command line +tools. User defined tasks can be added to the Registry.""" +from typing import Dict, List, Type +from bcipy.task import Task + + +class TaskRegistry: + registry_dict: Dict[str, Type[Task]] + + def __init__(self): + # Collects all non-abstract subclasses of Task. type ignore is used to work around a mypy bug + # https://github.com/python/mypy/issues/3115 + from bcipy.task.paradigm import vep, rsvp, matrix # noqa + from bcipy.task import actions # noqa + + self.registry_dict = {} + self.collect_subclasses(Task) # type: ignore[type-abstract] + + def collect_subclasses(self, cls: Type[Task]): + """Recursively collects all non-abstract subclasses of the given class and adds them to the registry.""" + for sub_class in cls.__subclasses__(): + if not getattr(sub_class, '__abstractmethods__', False): + self.registry_dict[sub_class.name] = sub_class + self.collect_subclasses(sub_class) + + def get(self, task_name: str) -> Type[Task]: + """Returns a task type based on its name property.""" + if task_name in self.registry_dict: + return self.registry_dict[task_name] + raise ValueError(f'{task_name} not a registered task') + + def get_all_types(self) -> List[Type[Task]]: + """Returns a list of all registered tasks.""" + return list(self.registry_dict.values()) + + def list(self) -> List[str]: + """Returns a list of all registered task names.""" + return list(self.registry_dict.keys()) + + def calibration_tasks(self) -> List[Type[Task]]: + """Returns a list of all registered calibration tasks.""" + from bcipy.task.calibration import BaseCalibrationTask + return [task for task in self.get_all_types() if issubclass(task, BaseCalibrationTask)] + + def register_task(self, task: Type[Task]) -> None: + """Registers a task with the TaskRegistry.""" + # Note that all imported tasks are automatically registered when the TaskRegistry is initialized. This + # method allows for the registration of additional tasks after initialization. + self.registry_dict[task.name] = task diff --git a/bcipy/task/start_task.py b/bcipy/task/start_task.py deleted file mode 100644 index a42a04d67..000000000 --- a/bcipy/task/start_task.py +++ /dev/null @@ -1,104 +0,0 @@ -"""Code for constructing and executing registered tasks""" -# mypy: disable-error-code="arg-type, misc" -from typing import List, Optional -from psychopy import visual - -from bcipy.task import Task -from bcipy.task.exceptions import TaskRegistryException -from bcipy.task.paradigm.matrix.calibration import MatrixCalibrationTask -from bcipy.task.paradigm.matrix.copy_phrase import MatrixCopyPhraseTask -from bcipy.task.paradigm.matrix.timing_verification import \ - MatrixTimingVerificationCalibration -from bcipy.task.paradigm.rsvp.calibration.calibration import \ - RSVPCalibrationTask -from bcipy.task.paradigm.rsvp.calibration.timing_verification import \ - RSVPTimingVerificationCalibration -from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask -from bcipy.task.paradigm.vep.calibration import VEPCalibrationTask -from bcipy.task.task_registry import TaskType - -from bcipy.acquisition import ClientManager -from bcipy.helpers.parameters import Parameters -from bcipy.signal.model import SignalModel -from bcipy.language import LanguageModel - - -def make_task( - display_window: visual.Window, - daq: ClientManager, - task: TaskType, - parameters: Parameters, - file_save: str, - signal_models: Optional[List[SignalModel]] = None, - language_model: Optional[LanguageModel] = None, - fake: bool = True) -> Task: - """Creates a Task based on the provided parameters. - - Parameters: - ----------- - display_window: psychopy Window - daq: ClientManager - manages one or more acquisition clients - task: TaskType - parameters: dict - file_save: str - path to file in which to save data - signal_models - list of trained models - language_model - language model - fake: boolean - true if eeg stream is randomly generated - Returns: - -------- - Task instance - """ - - # NORMAL RSVP MODES - if task is TaskType.RSVP_CALIBRATION: - return RSVPCalibrationTask( - display_window, daq, parameters, file_save) - - if task is TaskType.RSVP_COPY_PHRASE: - return RSVPCopyPhraseTask( - display_window, daq, parameters, file_save, signal_models, - language_model, fake=fake) - - if task is TaskType.RSVP_TIMING_VERIFICATION_CALIBRATION: - return RSVPTimingVerificationCalibration(display_window, daq, parameters, file_save) - - if task is TaskType.MATRIX_CALIBRATION: - return MatrixCalibrationTask( - display_window, daq, parameters, file_save - ) - - if task is TaskType.MATRIX_TIMING_VERIFICATION_CALIBRATION: - return MatrixTimingVerificationCalibration(display_window, daq, parameters, file_save) - - if task is TaskType.MATRIX_COPY_PHRASE: - return MatrixCopyPhraseTask( - display_window, daq, parameters, file_save, signal_models, - language_model, fake=fake) - - if task is TaskType.VEP_CALIBRATION: - return VEPCalibrationTask(display_window, daq, parameters, file_save) - - raise TaskRegistryException( - 'The provided experiment type is not registered.') - - -def start_task( - display_window: visual.Window, - daq: ClientManager, - task: TaskType, - parameters: Parameters, - file_save: str, - signal_models: Optional[List[SignalModel]] = None, - language_model: Optional[LanguageModel] = None, - fake: bool = True) -> str: - """Creates a Task and starts execution.""" - bcipy_task = make_task( - display_window, - daq, - task, - parameters, - file_save, - signal_models, - language_model, - fake) - return bcipy_task.execute() diff --git a/bcipy/task/task_registry.py b/bcipy/task/task_registry.py deleted file mode 100644 index 661b1d339..000000000 --- a/bcipy/task/task_registry.py +++ /dev/null @@ -1,63 +0,0 @@ -"""Task Registry ; used to provide task options to the GUI and command line -tools. User defined tasks can be added to the Registry.""" - -# NOTE: -# In the future we may want to consider dynamically retrieving all subclasses -# of Task and use these to populate a registry. We could also provide -# functionality for bcipy users to define their own tasks and register them so -# they would appear as options in the GUI. -# -# However, this approach is currently problematic for the GUI interface. Due -# to the tight coupling of the display code with the Tasks, importing any of -# the Task subclasses causes pygame (a psychopy dependency) to create a GUI, -# which seems to prevent our other GUI code from working. - -from typing import List - -from bcipy.helpers.exceptions import BciPyCoreException -from bcipy.helpers.system_utils import AutoNumberEnum - - -class TaskType(AutoNumberEnum): - """Enum of the registered experiment types (Tasks), along with the label - used for display in the GUI and command line tools. Values are looked up - by their (1-based) index. - - Examples: - >>> TaskType(1) - - - >>> TaskType(1).label - 'RSVP Calibration' - """ - - RSVP_CALIBRATION = 'RSVP Calibration' - RSVP_COPY_PHRASE = 'RSVP Copy Phrase' - RSVP_TIMING_VERIFICATION_CALIBRATION = 'RSVP Time Test Calibration' - MATRIX_CALIBRATION = 'Matrix Calibration' - MATRIX_TIMING_VERIFICATION_CALIBRATION = 'Matrix Time Test Calibration' - MATRIX_COPY_PHRASE = 'Matrix Copy Phrase' - VEP_CALIBRATION = 'VEP Calibration' - - def __init__(self, label): - self.label = label - - @classmethod - def by_value(cls, item): - tasks = cls.list() - # The cls.list method returns a sorted list of enum tasks - # check if item present and return the index + 1 (which is the ENUM value for the task) - if item in tasks: - return cls(tasks.index(item) + 1) - raise BciPyCoreException(f'{item} not a registered TaskType={tasks}') - - @classmethod - def calibration_tasks(cls) -> List['TaskType']: - return [ - task for task in cls if task.name.endswith('CALIBRATION') and - 'COPY_PHRASE' not in task.name - ] - - @classmethod - def list(cls) -> List[str]: - return list(map(lambda c: c.label, cls)) diff --git a/bcipy/task/tests/core/test_actions.py b/bcipy/task/tests/core/test_actions.py new file mode 100644 index 000000000..185ba8cf3 --- /dev/null +++ b/bcipy/task/tests/core/test_actions.py @@ -0,0 +1,73 @@ +import unittest +import subprocess + +from mockito import mock, when, verify, unstub +from bcipy.task import actions, TaskData +from bcipy.task.actions import CodeHookAction, OfflineAnalysisAction, ExperimentFieldCollectionAction + + +class TestActions(unittest.TestCase): + + def setUp(self) -> None: + self.parameters = mock() + self.parameters_path = 'parameters_path' + self.data_directory = 'data/' + + def tearDown(self) -> None: + unstub() + + def test_code_hook_action_subprocess(self) -> None: + code_hook = 'code_hook' + when(subprocess).Popen(code_hook, shell=True).thenReturn(None) + action = CodeHookAction( + parameters=self.parameters, + data_directory=self.data_directory, + code_hook=code_hook, + subprocess=True + ) + response = action.execute() + self.assertIsInstance(response, TaskData) + verify(subprocess, times=1).Popen(code_hook, shell=True) + + def test_code_hook_action_no_subprocess(self) -> None: + code_hook = 'code_hook' + when(subprocess).run(code_hook, shell=True).thenReturn(None) + action = CodeHookAction( + parameters=self.parameters, + data_directory=self.data_directory, + code_hook=code_hook, + subprocess=False + ) + response = action.execute() + self.assertIsInstance(response, TaskData) + verify(subprocess, times=1).run(code_hook, shell=True) + + def test_offline_analysis_action(self) -> None: + cmd_expected = f'bcipy-train -p "{self.parameters_path}"' + + when(subprocess).run(cmd_expected, shell=True, check=True).thenReturn(None) + action = OfflineAnalysisAction( + parameters=self.parameters, + data_directory=self.data_directory, + parameters_path=self.parameters_path, + ) + response = action.execute() + self.assertIsInstance(response, TaskData) + verify(subprocess, times=1).run(cmd_expected, shell=True, check=True) + + def test_experiment_field_collection_action(self) -> None: + experiment_id = 'experiment_id' + when(actions).start_experiment_field_collection_gui(experiment_id, self.data_directory).thenReturn(None) + action = ExperimentFieldCollectionAction( + parameters=self.parameters, + data_directory=self.data_directory, + experiment_id=experiment_id + ) + task_data = action.execute() + self.assertIsNotNone(task_data) + self.assertIsInstance(task_data, TaskData) + verify(actions, times=1).start_experiment_field_collection_gui(experiment_id, self.data_directory) + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/task/tests/core/test_task_main.py b/bcipy/task/tests/core/test_task_main.py new file mode 100644 index 000000000..dd3ce22f1 --- /dev/null +++ b/bcipy/task/tests/core/test_task_main.py @@ -0,0 +1,57 @@ +import unittest +from bcipy.task import Task, TaskData, TaskMode + + +class TestTask(unittest.TestCase): + + def test_task_fails_without_name(self): + mode = TaskMode.CALIBRATION + + class TestTask(Task): + + def execute(self) -> TaskData: + ... + + with self.assertRaises(AssertionError): + TestTask(mode=mode) + + def test_task_fails_without_mode(self): + name = "test task" + + class TestTask(Task): + + def execute(self) -> TaskData: + ... + + with self.assertRaises(AssertionError): + TestTask(name=name) + + def test_task_fails_without_execute(self): + name = "test task" + mode = TaskMode.CALIBRATION + + class TestTask(Task): + pass + + with self.assertRaises(TypeError): + TestTask(name=name, mode=mode) + + def test_task_initializes(self): + name = "test task" + mode = TaskMode.CALIBRATION + + class TestTask(Task): + + def __init__(self, name: str, mode: TaskMode): + self.name = name + self.mode = mode + + def execute(self) -> TaskData: + ... + task = TestTask(name=name, mode=mode) + self.assertEqual(task.name, name) + self.assertEqual(task.mode, mode) + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/task/tests/orchestrator/test_orchestrator.py b/bcipy/task/tests/orchestrator/test_orchestrator.py new file mode 100644 index 000000000..f2805a849 --- /dev/null +++ b/bcipy/task/tests/orchestrator/test_orchestrator.py @@ -0,0 +1,157 @@ +import unittest +import logging +import json +from mock import mock_open +from mockito import any, mock, when, unstub, verify +from bcipy.task.orchestrator import SessionOrchestrator +from bcipy.task import Task, TaskData +from bcipy.config import DEFAULT_PARAMETERS_PATH +from bcipy.helpers.load import load_json_parameters + + +class TestSessionOrchestrator(unittest.TestCase): + parameter_location = DEFAULT_PARAMETERS_PATH + + def setUp(self) -> None: + self.logger = mock(spec=logging.Logger) + self.logger.info = lambda x: x + self.logger.error = lambda x: x + self.logger.exception = lambda x: x + + def tearDown(self) -> None: + unstub() + + def test_orchestrator_add_task(self) -> None: + task = mock(spec=Task) + task.name = "test task" + task.mode = "test mode" + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + orchestrator = SessionOrchestrator() + self.assertTrue(orchestrator.tasks == []) + orchestrator.add_task(task) + self.assertTrue(len(orchestrator.tasks) == 1) + + verify(SessionOrchestrator, times=1)._init_orchestrator_save_folder(any()) + verify(SessionOrchestrator, times=1)._init_orchestrator_logger(any()) + + def test_orchestrator_add_tasks(self) -> None: + task1 = mock(spec=Task) + task1.name = "test task" + task1.mode = "test mode" + task2 = mock(spec=Task) + task2.name = "test task" + task2.mode = "test mode" + tasks = [task1, task2] + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + orchestrator = SessionOrchestrator() + self.assertTrue(orchestrator.tasks == []) + orchestrator.add_tasks(tasks) + self.assertTrue(len(orchestrator.tasks) == 2) + + self.assertEqual(orchestrator.tasks[0], task1) + self.assertEqual(orchestrator.tasks[1], task2) + + verify(SessionOrchestrator, times=1)._init_orchestrator_save_folder(any()) + verify(SessionOrchestrator, times=1)._init_orchestrator_logger(any()) + + def test_orchestrator_execute(self) -> None: + task = mock(spec=Task) + task.name = "test task" + task.mode = "test mode" + task.execute = lambda: TaskData() + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + when(SessionOrchestrator)._init_task_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_task_logger(any()).thenReturn() + when(SessionOrchestrator)._save_data().thenReturn() + when(task).__call__( + any(), + any(), + fake=False, + experiment_id=any(), + alert_finished=any(), + parameters_path=any(), + last_task_dir=None, + protocol_path=any(), + progress=any(), + tasks=any(), + exit_callback=any(), + ).thenReturn(task) + orchestrator = SessionOrchestrator() + orchestrator.add_task(task) + orchestrator.execute() + + verify(task, times=1).__call__( + any(), + any(), + fake=False, + experiment_id=any(), + alert_finished=any(), + parameters_path=any(), + last_task_dir=None, + protocol_path=any(), + progress=any(), + tasks=any(), + exit_callback=any()) + verify(SessionOrchestrator, times=1)._init_orchestrator_save_folder(any()) + verify(SessionOrchestrator, times=1)._init_orchestrator_logger(any()) + verify(SessionOrchestrator, times=1)._init_task_save_folder(any()) + verify(SessionOrchestrator, times=1)._init_task_logger(any()) + verify(SessionOrchestrator, times=1)._save_data() + + @mock_open(read_data='{"Phrases": []}') + def test_orchestrator_multiple_copyphrases_loads_from_parameters_when_set(self, mock_file): + parameters = load_json_parameters(self.parameter_location, value_cast=True) + copy_phrase_location = "bcipy/parameters/experiments/phrases.json" + parameters['copy_phrases_location'] = copy_phrase_location + mock_copy_phrases = {"Phrases": [["test", 0], ["test2", 1]]} + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + when(SessionOrchestrator)._init_task_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_task_logger(any()).thenReturn() + when(SessionOrchestrator)._save_data().thenReturn() + when(json).load(mock_file).thenReturn(mock_copy_phrases) + + orchestrator = SessionOrchestrator(parameters=parameters) + + self.assertEqual(orchestrator.copyphrases, mock_copy_phrases['Phrases']) + verify(json, times=1).load(mock_file) + + def test_orchestrator_save_data_multiple_copyphrases_saves_remaining_phrases(self): + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + when(SessionOrchestrator)._init_task_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_task_logger(any()).thenReturn() + when(SessionOrchestrator)._save_procotol_data().thenReturn() + when(SessionOrchestrator)._save_copy_phrases().thenReturn() + + orchestrator = SessionOrchestrator() + orchestrator.copyphrases = [["test", 0], ["test2", 1]] + + orchestrator._save_data() + verify(SessionOrchestrator, times=1)._save_procotol_data() + verify(SessionOrchestrator, times=1)._save_copy_phrases() + + def test_orchestrator_next_phrase(self): + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + when(SessionOrchestrator)._init_task_save_folder(any()).thenReturn() + when(SessionOrchestrator)._init_task_logger(any()).thenReturn() + when(SessionOrchestrator)._save_procotol_data().thenReturn() + when(SessionOrchestrator).initialize_copy_phrases().thenReturn() + + orchestrator = SessionOrchestrator() + orchestrator.copyphrases = [["test", 5], ["test2", 1]] + + self.assertEqual(orchestrator.next_phrase, None) + self.assertEqual(orchestrator.starting_index, 0) + orchestrator.set_next_phrase() + self.assertEqual(orchestrator.next_phrase, "test") + self.assertEqual(orchestrator.starting_index, 5) + self.assertTrue(len(orchestrator.copyphrases) == 1) + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/task/tests/orchestrator/test_protocol.py b/bcipy/task/tests/orchestrator/test_protocol.py new file mode 100644 index 000000000..1ea8750fe --- /dev/null +++ b/bcipy/task/tests/orchestrator/test_protocol.py @@ -0,0 +1,72 @@ +import unittest +from bcipy.task.orchestrator.protocol import parse_protocol, serialize_protocol, validate_protocol_string +from bcipy.task.actions import OfflineAnalysisAction +from bcipy.task.paradigm.rsvp.calibration.calibration import RSVPCalibrationTask +from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask + + +class TestTaskProtocolProcessing(unittest.TestCase): + + def test_parses_one_task(self) -> None: + sequence = 'RSVP Calibration' + parsed = parse_protocol(sequence) + assert len(parsed) == 1 + assert parsed[0] is RSVPCalibrationTask + + def test_parses_with_task_name(self) -> None: + actions = OfflineAnalysisAction.name + parsed = parse_protocol(actions) + assert len(parsed) == 1 + assert parsed[0] is OfflineAnalysisAction + + def test_parses_multiple_tasks(self) -> None: + actions = 'RSVP Calibration -> RSVP Copy Phrase' + parsed = parse_protocol(actions) + assert len(parsed) == 2 + assert parsed[0] is RSVPCalibrationTask + assert parsed[1] is RSVPCopyPhraseTask + + def test_parses_actions_and_tasks(self) -> None: + sequence = 'RSVP Calibration -> OfflineAnalysisAction -> RSVP Copy Phrase' + parsed = parse_protocol(sequence) + assert len(parsed) == 3 + assert parsed[0] is RSVPCalibrationTask + assert parsed[1] is OfflineAnalysisAction + assert parsed[2] is RSVPCopyPhraseTask + + def test_parses_sequence_with_extra_spaces(self) -> None: + actions = ' RSVP Calibration -> OfflineAnalysisAction -> RSVP Copy Phrase ' + parsed = parse_protocol(actions) + assert len(parsed) == 3 + assert parsed[0] is RSVPCalibrationTask + assert parsed[1] is OfflineAnalysisAction + assert parsed[2] is RSVPCopyPhraseTask + + def test_throws_exception_on_invalid_task(self) -> None: + actions = 'RSVP Calibration -> does not exist' + with self.assertRaises(ValueError): + parse_protocol(actions) + + def test_throws_exception_on_invalid_string(self) -> None: + actions = 'thisstringisbad' + with self.assertRaises(ValueError): + parse_protocol(actions) + + def test_validates_valid_action_string(self) -> None: + actions = 'RSVP Calibration -> RSVP Copy Phrase' + validate_protocol_string(actions) + + def test_throws_exception_on_invalid_action_string(self) -> None: + actions = 'RSVP Calibration -> RSVP Copy Phrase -> does not exist' + with self.assertRaises(ValueError): + validate_protocol_string(actions) + + def test_serializes_one_task(self) -> None: + actions = [RSVPCalibrationTask] + serialized = serialize_protocol(actions) + assert serialized == RSVPCalibrationTask.name + + def test_serializes_multiple_tasks(self) -> None: + sequence = [RSVPCalibrationTask, OfflineAnalysisAction, RSVPCopyPhraseTask] + serialized = serialize_protocol(sequence) + assert serialized == 'RSVP Calibration -> OfflineAnalysisAction -> RSVP Copy Phrase' diff --git a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py index da0651efe..d6ae98e4b 100644 --- a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py +++ b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py @@ -5,7 +5,6 @@ import psychopy from mockito import any, mock, unstub, verify, when -import bcipy.task.base_calibration import bcipy.task.paradigm.matrix.calibration from bcipy.acquisition import LslAcquisitionClient from bcipy.acquisition.devices import DeviceSpec @@ -48,31 +47,37 @@ def setUp(self): 'show_feedback': False, 'show_preview_inquiry': False, 'stim_color': 'white', - 'stim_height': 0.6, + 'matrix_stim_height': 0.6, 'stim_jitter': 0.0, 'stim_length': 3, 'stim_number': 10, 'stim_order': 'random', - 'stim_pos_x': 0.0, - 'stim_pos_y': 0.0, + 'matrix_stim_pos_x': 0.0, + 'matrix_stim_pos_y': 0.0, 'stim_space_char': '_', 'target_color': 'white', 'target_positions': 'distributed', 'task_buffer_length': 2, 'task_color': 'white', - 'task_height': 0.1, + 'matrix_task_height': 0.1, + 'matrix_task_padding': 0.1, 'task_text': 'HELLO_WORLD', 'time_fixation': 0.1, 'time_flash': 0.1, 'time_prompt': 0.1, 'trial_window': (0.0, 0.5), 'trials_before_break': 100, + "preview_inquiry_error_prob": 0.05, 'break_message': 'Take a break!', 'trigger_type': 'image', + 'matrix_keyboard_layout': 'QWERTY', + 'matrix_rows': 3, + 'matrix_columns': 3, + 'matrix_width': 0.6, } self.parameters = Parameters.from_cast_values(**parameters) - self.win = mock({'size': np.array([500, 500]), 'units': 'height'}) + self.servers = [mock()] device_spec = DeviceSpec(name='Testing', channels=['a', 'b', 'c'], @@ -99,6 +104,7 @@ def setUp(self): 'transform': mock(), 'evidence_type': 'ERP' }) + self.fake = False self.display = mock(spec=MatrixDisplay) self.display.first_stim_time = 0.0 @@ -132,33 +138,34 @@ def tearDown(self): """Override""" unstub() - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_initialize(self, save_session_mock, trigger_handler_mock): """Test initialization""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) - MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) verify(bcipy.task.paradigm.matrix.calibration, times=1).init_matrix_display(self.parameters, self.win, any(), any()) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_execute(self, save_session_mock, trigger_handler_mock): """Test task execute""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) when(task).write_offset_trigger().thenReturn(None) when(task).write_trigger_data(any(), any()).thenReturn(None) @@ -172,33 +179,35 @@ def test_execute(self, save_session_mock, trigger_handler_mock): any(), any()) verify(task, times=1).write_offset_trigger() - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_validate_parameters_throws_task_exception_empty_parameter( self, save_session_mock, trigger_handler_mock): """Test validate parameters throws task exception when parameters is empty.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() parameters = {} + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) with self.assertRaises(Exception): - MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=parameters, - file_save=self.temp_dir) + MatrixCalibrationTask(parameters=parameters, + file_save=self.temp_dir, + fake=self.fake) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_execute_save_stimuli_positions(self, save_session_mock, trigger_handler_mock): """Test execute save stimuli positions method is called as expected.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) when(task).write_offset_trigger().thenReturn(None) when(task).write_trigger_data(any(), any()).thenReturn(None) @@ -215,18 +224,19 @@ def test_execute_save_stimuli_positions(self, save_session_mock, any(), any()) verify(task, times=1).write_offset_trigger() - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_trigger_type_targetness(self, save_session_mock, trigger_handler_mock): """Test trigger type targetness.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) # non-target symbol = 'N' @@ -244,17 +254,18 @@ def test_trigger_type_targetness(self, save_session_mock, self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.TARGET) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_trigger_type_fixation(self, save_session_mock, trigger_handler_mock): """Test trigger type fixation.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) # fixation symbol = '+' @@ -264,18 +275,19 @@ def test_trigger_type_fixation(self, save_session_mock, self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.FIXATION) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_trigger_type_prompt(self, save_session_mock, trigger_handler_mock): """Test trigger type prompt.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) # prompt, index = 0, otherwise it would be a target symbol = 'P' @@ -285,19 +297,20 @@ def test_trigger_type_prompt(self, save_session_mock, self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PROMPT) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_write_trigger_data_first_run(self, save_session_mock, trigger_handler_mock): """Test write trigger data when it is the first run of the task.""" handler_mock = Mock() save_session_mock.return_value = mock() trigger_handler_mock.return_value = handler_mock + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} timing_mock = mock() @@ -305,66 +318,68 @@ def test_write_trigger_data_first_run(self, save_session_mock, first_run = True when(self.daq).client_by_type( ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.base_calibration).offset_label('EEG').thenReturn( + when(bcipy.task.calibration).offset_label('EEG').thenReturn( 'starting_offset') - when(bcipy.task.base_calibration).convert_timing_triggers( + when(bcipy.task.calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) self.assertEqual(2, handler_mock.add_triggers.call_count) verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.base_calibration, times=1).offset_label('EEG') - verify(bcipy.task.base_calibration, + verify(bcipy.task.calibration, times=1).offset_label('EEG') + verify(bcipy.task.calibration, times=1).convert_timing_triggers(timing, timing[0][0], any()) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_write_trigger_data_not_first_run(self, save_session_mock, trigger_handler_mock): """Test write trigger data when it is not the first run of the task.""" handler_mock = Mock() save_session_mock.return_value = mock() trigger_handler_mock.return_value = handler_mock + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) timing_mock = mock() timing = [('a', 0.0)] first_run = False - when(bcipy.task.base_calibration).convert_timing_triggers( + when(bcipy.task.calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) handler_mock.add_triggers.assert_called_once() - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_write_offset_trigger(self, save_session_mock, trigger_handler_mock): """Test write offset trigger""" save_session_mock.return_value = mock() handler_mock = Mock() trigger_handler_mock.return_value = handler_mock + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) - task = MatrixCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + task = MatrixCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} when(self.daq).client_by_type( ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.base_calibration).offset_label( + when(bcipy.task.calibration).offset_label( 'EEG', prefix='daq_sample_offset').thenReturn('daq_sample_offset') task.write_offset_trigger() handler_mock.close.assert_called_once() handler_mock.add_triggers.assert_called_once() verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.base_calibration, + verify(bcipy.task.calibration, times=1).offset_label('EEG', prefix='daq_sample_offset') diff --git a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py index 8011205ce..2ab8fc9dd 100644 --- a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py +++ b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py @@ -4,6 +4,7 @@ import psychopy from mockito import any, mock, unstub, verify, when +import bcipy.task.calibration import bcipy.task.paradigm.rsvp.calibration.calibration from bcipy.acquisition import LslAcquisitionClient from bcipy.acquisition.devices import DeviceSpec @@ -46,19 +47,20 @@ def setUp(self): 'show_feedback': False, 'show_preview_inquiry': False, 'stim_color': 'white', - 'stim_height': 0.6, + 'rsvp_stim_height': 0.6, 'stim_jitter': 0.0, 'stim_length': 3, 'stim_number': 10, 'stim_order': 'random', - 'stim_pos_x': 0.0, - 'stim_pos_y': 0.0, + 'rsvp_stim_pos_x': 0.0, + 'rsvp_stim_pos_y': 0.0, 'stim_space_char': '_', 'target_color': 'white', 'target_positions': 'distributed', 'task_buffer_length': 2, 'task_color': 'white', - 'task_height': 0.1, + 'rsvp_task_height': 0.1, + 'rsvp_task_padding': 0.1, 'task_text': 'HELLO_WORLD', 'time_fixation': 0.1, 'time_flash': 0.1, @@ -91,6 +93,8 @@ def setUp(self): } }) self.temp_dir = '' + self.fake = False + self.servers = [mock()] self.model_metadata = mock({ 'device_spec': device_spec, 'transform': mock(), @@ -108,10 +112,10 @@ def setUp(self): when(bcipy.task.paradigm.rsvp.calibration.calibration ).init_calibration_display_task(self.parameters, self.win, any(), any()).thenReturn(self.display) - when(bcipy.task.base_calibration).trial_complete_message( + when(bcipy.task.calibration).trial_complete_message( any(), any()).thenReturn([]) - when(bcipy.task.base_calibration.TriggerHandler).write().thenReturn() - when(bcipy.task.base_calibration.TriggerHandler).add_triggers( + when(bcipy.task.calibration.TriggerHandler).write().thenReturn() + when(bcipy.task.calibration.TriggerHandler).add_triggers( any()).thenReturn() when(psychopy.event).getKeys(keyList=['space', 'escape'], @@ -125,33 +129,37 @@ def tearDown(self): """Override""" unstub() - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') - def test_initialize(self, save_session_mock, trigger_handler_mock): + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') + @patch('bcipy.task.calibration.BaseCalibrationTask.cleanup') + def test_initialize(self, save_session_mock, trigger_handler_mock, cleanup_mock): """Test initialization""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + cleanup_mock.return_value = None - RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) verify(bcipy.task.paradigm.rsvp.calibration.calibration, times=1).init_calibration_display_task(self.parameters, self.win, any(), any()) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_execute(self, save_session_mock, trigger_handler_mock): """Test task execute""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) when(task).write_offset_trigger().thenReturn(None) when(task).write_trigger_data(any(), any()).thenReturn(None) @@ -165,31 +173,33 @@ def test_execute(self, save_session_mock, trigger_handler_mock): any(), any()) verify(task, times=1).write_offset_trigger() - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_validate_parameters_throws_task_exception_empty_parameter( self, save_session_mock, trigger_handler_mock): """Test validate parameters throws task exception when parameters is empty.""" parameters = {} save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) with self.assertRaises(Exception): - RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=parameters, - file_save=self.temp_dir) + RSVPCalibrationTask(parameters=parameters, + file_save=self.temp_dir, + fake=self.fake) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_trigger_type_targetness(self, save_session_mock, trigger_handler_mock): """Test trigger type targetness.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) # non-target symbol = 'N' @@ -207,17 +217,18 @@ def test_trigger_type_targetness(self, save_session_mock, self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.TARGET) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_trigger_type_fixation(self, save_session_mock, trigger_handler_mock): """Test trigger type fixation.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) # fixation symbol = '+' @@ -227,17 +238,18 @@ def test_trigger_type_fixation(self, save_session_mock, self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.FIXATION) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_trigger_type_prompt(self, save_session_mock, trigger_handler_mock): """Test trigger type prompt.""" + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) # prompt, index = 0, otherwise it would be a target symbol = 'P' @@ -247,17 +259,18 @@ def test_trigger_type_prompt(self, save_session_mock, self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PROMPT) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_trigger_type_preview(self, save_session_mock, trigger_handler_mock): """Test trigger type preview.""" save_session_mock.return_value = mock() trigger_handler_mock.return_value = mock() - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) # preview, index > 0, otherwise it would be a prompt symbol = 'inquiry_preview' @@ -267,18 +280,19 @@ def test_trigger_type_preview(self, save_session_mock, self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PREVIEW) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_write_trigger_data_first_run(self, save_session_mock, trigger_handler_mock): """Test write trigger data when it is the first run of the task.""" handler_mock = Mock() save_session_mock.return_value = mock() + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) trigger_handler_mock.return_value = handler_mock - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} timing_mock = mock() @@ -286,57 +300,59 @@ def test_write_trigger_data_first_run(self, save_session_mock, first_run = True when(self.daq).client_by_type( ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.base_calibration).offset_label('EEG').thenReturn( + when(bcipy.task.calibration).offset_label('EEG').thenReturn( 'starting_offset') - when(bcipy.task.base_calibration).convert_timing_triggers( + when(bcipy.task.calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) self.assertEqual(2, handler_mock.add_triggers.call_count) verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.base_calibration, times=1).offset_label('EEG') - verify(bcipy.task.base_calibration, + verify(bcipy.task.calibration, times=1).offset_label('EEG') + verify(bcipy.task.calibration, times=1).convert_timing_triggers(timing, timing[0][0], any()) - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_write_trigger_data_not_first_run(self, save_session_mock, trigger_handler_mock): """Test write trigger data when it is not the first run of the task.""" handler_mock = Mock() save_session_mock.return_value = mock() trigger_handler_mock.return_value = handler_mock - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) timing_mock = mock() timing = [('a', 0.0)] first_run = False - when(bcipy.task.base_calibration).convert_timing_triggers( + when(bcipy.task.calibration).convert_timing_triggers( timing, timing[0][0], any()).thenReturn(timing_mock) task.write_trigger_data(timing, first_run) handler_mock.add_triggers.assert_called_once() - @patch('bcipy.task.base_calibration.TriggerHandler') - @patch('bcipy.task.base_calibration._save_session_related_data') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') def test_write_offset_trigger(self, save_session_mock, trigger_handler_mock): """Test write offset trigger""" save_session_mock.return_value = mock() handler_mock = Mock() trigger_handler_mock.return_value = handler_mock - task = RSVPCalibrationTask(win=self.win, - daq=self.daq, - parameters=self.parameters, - file_save=self.temp_dir) + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} when(self.daq).client_by_type( ContentType.EEG).thenReturn(client_by_type_resp) - when(bcipy.task.base_calibration).offset_label( + when(bcipy.task.calibration).offset_label( 'EEG', prefix='daq_sample_offset').thenReturn('daq_sample_offset') when(TriggerHandler).close().thenReturn() @@ -345,9 +361,71 @@ def test_write_offset_trigger(self, save_session_mock, handler_mock.close.assert_called_once() handler_mock.add_triggers.assert_called_once() verify(self.eeg_client_mock, times=1).offset(0.0) - verify(bcipy.task.base_calibration, + verify(bcipy.task.calibration, times=1).offset_label('EEG', prefix='daq_sample_offset') + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') + def test_setup(self, save_session_mock, trigger_handler_mock): + """Test setup""" + save_session_mock.return_value = mock() + handler_mock = Mock() + trigger_handler_mock.return_value = handler_mock + when(bcipy.task.calibration).init_acquisition(any(), any(), server=self.fake).thenReturn( + (self.daq, self.servers)) + when(bcipy.task.calibration).init_display_window(self.parameters).thenReturn( + self.win) + + self.assertFalse(RSVPCalibrationTask.initalized) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) + + self.assertTrue(task.initalized) + verify(bcipy.task.calibration, times=1).init_acquisition( + self.parameters, self.temp_dir, server=self.fake) + verify(bcipy.task.calibration, times=1).init_display_window( + self.parameters) + self.assertEqual((self.daq, self.servers, self.win), + task.setup(self.parameters, self.temp_dir, self.fake)) + + @patch('bcipy.task.calibration.TriggerHandler') + @patch('bcipy.task.calibration._save_session_related_data') + def test_cleanup(self, save_session_mock, trigger_handler_mock): + """Test cleanup""" + save_session_mock.return_value = mock() + handler_mock = Mock() + trigger_handler_mock.return_value = handler_mock + when(bcipy.task.calibration.BaseCalibrationTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + + # Mock the default cleanup + when(bcipy.task.calibration.BaseCalibrationTask).write_offset_trigger().thenReturn(None) + when(bcipy.task.calibration.BaseCalibrationTask).exit_display().thenReturn(None) + when(bcipy.task.calibration.BaseCalibrationTask).wait().thenReturn(None) + + # Mock the initialized cleanup + when(self.daq).stop_acquisition().thenReturn(None) + when(self.daq).cleanup().thenReturn(None) + when(self.servers[0]).stop().thenReturn(None) + when(self.win).close().thenReturn(None) + task = RSVPCalibrationTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=self.fake) + # because the task is not initialized via setup, we need to set it to True here + task.initalized = True + + task.cleanup() + + verify(self.daq, times=1).stop_acquisition() + verify(self.daq, times=1).cleanup() + verify(self.servers[0], times=1).stop() + verify(self.win, times=1).close() + verify(bcipy.task.calibration.BaseCalibrationTask, times=1).setup(any(), any(), any()) + verify(bcipy.task.calibration.BaseCalibrationTask, times=1).write_offset_trigger() + verify(bcipy.task.calibration.BaseCalibrationTask, times=1).exit_display() + verify(bcipy.task.calibration.BaseCalibrationTask, times=1).wait() + if __name__ == '__main__': unittest.main() diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 1ac1980ee..59706bfc1 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -14,7 +14,7 @@ from bcipy.acquisition.multimodal import ContentType from bcipy.config import DEFAULT_ENCODING from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper -from bcipy.helpers.exceptions import TaskConfigurationException +from bcipy.exceptions import TaskConfigurationException from bcipy.helpers.parameters import Parameters from bcipy.helpers.stimuli import InquirySchedule from bcipy.helpers.triggers import TriggerHandler @@ -48,7 +48,7 @@ def setUp(self): 'max_inq_len': 50, 'max_inq_per_series': 10, 'max_minutes': 20, - 'min_inq_len': 1, + 'min_inq_len': 5, 'max_selections': 50, 'max_incorrect': 10, 'notch_filter_frequency': 60.0, @@ -60,19 +60,20 @@ def setUp(self): 'show_preview_inquiry': False, 'spelled_letters_count': 0, 'stim_color': 'white', - 'stim_height': 0.6, + 'rsvp_stim_height': 0.6, 'stim_length': 10, 'stim_number': 100, 'stim_jitter': 0.0, 'stim_order': 'random', - 'stim_pos_x': 0.0, - 'stim_pos_y': 0.0, + 'rsvp_stim_pos_x': 0.0, + 'rsvp_stim_pos_y': 0.0, 'stim_space_char': '–', 'summarize_session': False, 'target_color': 'white', 'task_buffer_length': 2, 'task_color': 'white', - 'task_height': 0.1, + 'rsvp_task_height': 0.1, + 'rsvp_task_padding': 0.1, 'task_text': 'HELLO_WORLD', "preview_inquiry_error_prob": 0.05, 'info_pos_x': 0.0, @@ -84,7 +85,7 @@ def setUp(self): 'trigger_type': 'image', } self.parameters = Parameters.from_cast_values(**parameters) - + self.fake = True self.win = mock({'size': [500, 500], 'units': 'height'}) device_spec = DeviceSpec(name='Testing', @@ -108,6 +109,7 @@ def setUp(self): ContentType.EEG: self.eeg_client_mock } }) + self.servers = [mock()] when(self.daq).get_client(ContentType.EEG).thenReturn(self.eeg_client_mock) self.temp_dir = tempfile.mkdtemp() self.model_metadata = mock({ @@ -115,7 +117,7 @@ def setUp(self): 'transform': mock(), 'evidence_type': 'ERP' }) - self.signal_model = mock({'metadata': self.model_metadata}) + self.signal_models = [mock({'metadata': self.model_metadata})] self.language_model = mock() decision_maker = mock() @@ -131,12 +133,17 @@ def setUp(self): when(bcipy.task.paradigm.rsvp.copy_phrase).CopyPhraseWrapper( ...).thenReturn(self.copy_phrase_wrapper) + # mock data for initial series series_gen = mock_inquiry_data() when(self.copy_phrase_wrapper).initialize_series().thenReturn( next(series_gen)) when(TriggerHandler).write().thenReturn() when(TriggerHandler).add_triggers(any()).thenReturn() + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).get_language_model().thenReturn( + self.language_model) + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).get_signal_models().thenReturn( + self.signal_models) def tearDown(self): """Override""" @@ -145,79 +152,70 @@ def tearDown(self): def test_initialize(self): """Test initialization""" + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) RSVPCopyPhraseTask( - win=self.win, - daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + fake=self.fake) def test_validate_parameters(self): + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) task = RSVPCopyPhraseTask( - win=self.win, - daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + fake=self.fake) task.validate_parameters() def test_validate_parameters_throws_task_exception_missing_parameter(self): parameters = {} + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) with self.assertRaises(TaskConfigurationException): RSVPCopyPhraseTask( - win=self.win, - daq=self.daq, parameters=parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) def test_validate_parameters_throws_task_exception_excess_prestim_length(self): self.parameters['prestim_length'] = 1000 + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) with self.assertRaises(TaskConfigurationException): RSVPCopyPhraseTask( - win=self.win, - daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) def test_validate_parameters_throws_task_exception_excess_trial_window(self): self.parameters['trial_window'] = "0.0:1000.0" + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) with self.assertRaises(TaskConfigurationException): RSVPCopyPhraseTask( - win=self.win, - daq=self.daq, parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @patch('bcipy.task.paradigm.rsvp.copy_phrase.trial_complete_message') def test_execute_without_inquiry(self, message_mock, user_input_mock): """User should be able to exit the task without viewing any inquiries""" - - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) user_input_mock.return_value = False @@ -227,7 +225,7 @@ def test_execute_without_inquiry(self, message_mock, verify(self.copy_phrase_wrapper, times=1).initialize_series() verify(self.display, times=0).preview_inquiry() verify(self.display, times=0).do_inquiry() - self.assertEqual(self.temp_dir, result) + self.assertEqual(self.temp_dir, result.save_path) self.assertTrue( Path(task.session_save_location).is_file(), @@ -242,14 +240,12 @@ def test_execute_without_inquiry(self, message_mock, def test_execute_fake_data_single_inquiry(self, process_data_mock, message_mock, user_input_mock): """Test that fake data does not use the decision maker""" - - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) # Execute a single inquiry then `escape` to stop user_input_mock.side_effect = [True, False] @@ -265,7 +261,7 @@ def test_execute_fake_data_single_inquiry(self, process_data_mock, message_mock, # Assertions verify(self.copy_phrase_wrapper, times=2).initialize_series() verify(self.display, times=1).do_inquiry() - self.assertEqual(self.temp_dir, result) + self.assertEqual(self.temp_dir, result.save_path) self.assertTrue( Path(task.session_save_location).is_file(), @@ -281,13 +277,12 @@ def test_max_inq_len(self, process_data_mock, message_mock, user_input_mock): """Test stoppage criteria for the max inquiry length""" self.parameters['max_inq_len'] = 2 - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) # Don't provide any `escape` input from the user user_input_mock.return_value = True @@ -302,7 +297,7 @@ def test_max_inq_len(self, process_data_mock, message_mock, # Assertions verify(self.display, times=2).do_inquiry() - self.assertEqual(self.temp_dir, result) + self.assertEqual(self.temp_dir, result.save_path) self.assertTrue( Path(task.session_save_location).is_file(), @@ -321,14 +316,12 @@ def test_spelling_complete(self, process_data_mock, """Test that the task stops when the copy_phrase has been correctly spelled.""" self.parameters['task_text'] = 'Hello' self.parameters['spelled_letters_count'] = 4 - - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) # Don't provide any `escape` input from the user user_input_mock.return_value = True @@ -343,7 +336,7 @@ def test_spelling_complete(self, process_data_mock, # Assertions verify(self.display, times=1).do_inquiry() - self.assertEqual(self.temp_dir, result) + self.assertEqual(self.temp_dir, result.save_path) self.assertTrue( Path(task.session_save_location).is_file(), @@ -359,25 +352,23 @@ def test_spelled_letters(self): """Spelled letters should reset if count is larger than copy phrase.""" self.parameters['task_text'] = 'Hi' self.parameters['spelled_letters_count'] = 3 - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) self.assertEqual(task.starting_spelled_letters(), 0) def test_stims_for_eeg(self): """The correct stims should be sent to get_device_data_for_decision""" - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) timings1 = [['calibration_trigger', 2.0539278959913645], ['+', 3.7769652379938634], ['Y', 4.247819707990857], ['S', 4.46274590199755], ['W', 4.679621118993964], @@ -419,15 +410,14 @@ def test_stims_for_eeg(self): @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_device_data_for_decision') def test_next_letter(self, process_data_mock, message_mock, user_input_mock): + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) """Test that the task stops when the copy_phrase has been correctly spelled.""" self.parameters['task_text'] = 'Hello' - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) task.spelled_text = 'H' self.assertEqual(task.next_target(), 'e') @@ -450,13 +440,12 @@ def test_execute_fake_data_with_preview(self, process_data_mock, message_mock, user_input_mock): """Test that preview is displayed""" self.parameters['show_preview_inquiry'] = True - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, - fake=True) + + fake=self.fake) # Execute a single inquiry then `escape` to stop user_input_mock.side_effect = [True, False] @@ -475,7 +464,7 @@ def test_execute_fake_data_with_preview(self, process_data_mock, message_mock, verify(self.copy_phrase_wrapper, times=2).initialize_series() verify(self.display, times=1).do_inquiry() verify(self.copy_phrase_wrapper, times=1).add_evidence(EvidenceType.BTN, ...) - self.assertEqual(self.temp_dir, result) + self.assertEqual(self.temp_dir, result.save_path) @patch('bcipy.task.paradigm.rsvp.copy_phrase.init_evidence_evaluator') @patch('bcipy.task.paradigm.rsvp.copy_phrase.get_user_input') @@ -531,7 +520,8 @@ def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, when(bcipy.task.paradigm.rsvp.copy_phrase).CopyPhraseWrapper( ...).thenReturn(copy_phrase_wrapper_mock) - + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) # mock data for initial series when(copy_phrase_wrapper_mock).initialize_series().thenReturn( (False, @@ -576,12 +566,9 @@ def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, 'nontarget', 'nontarget' ])) - task = RSVPCopyPhraseTask(win=self.win, - daq=self.daq, - parameters=self.parameters, + task = RSVPCopyPhraseTask(parameters=self.parameters, file_save=self.temp_dir, - signal_models=[self.signal_model], - language_model=self.language_model, + fake=False) # Execute a single inquiry then `escape` to stop @@ -597,7 +584,7 @@ def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, verify(copy_phrase_wrapper_mock, times=1).decide(...) verify(self.display, times=0).preview_inquiry() verify(self.display, times=1).do_inquiry() - self.assertEqual(self.temp_dir, result) + self.assertEqual(self.temp_dir, result.save_path) self.assertTrue( Path(task.session_save_location).is_file(), @@ -606,6 +593,62 @@ def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, session = Session.from_dict(json.load(json_file)) self.assertEqual(1, session.total_number_series) + def test_setup(self): + """Test setup""" + + when(bcipy.task.paradigm.rsvp.copy_phrase).init_acquisition(any(), any(), server=self.fake).thenReturn( + (self.daq, self.servers)) + when(bcipy.task.paradigm.rsvp.copy_phrase).init_display_window(self.parameters).thenReturn( + self.win) + + self.assertFalse(RSVPCopyPhraseTask.initalized) + task = RSVPCopyPhraseTask(parameters=self.parameters, + file_save=self.temp_dir, + + fake=self.fake) + + self.assertTrue(task.initalized) + verify(bcipy.task.paradigm.rsvp.copy_phrase, times=1).init_acquisition( + self.parameters, self.temp_dir, server=self.fake) + verify(bcipy.task.paradigm.rsvp.copy_phrase, times=1).init_display_window( + self.parameters) + self.assertEqual((self.daq, self.servers, self.win), + task.setup(self.parameters, self.temp_dir, self.fake)) + + def test_cleanup(self): + """Test cleanup""" + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + + # Mock the default cleanup + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).write_offset_trigger().thenReturn(None) + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).exit_display().thenReturn(None) + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).save_session_data().thenReturn(None) + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).wait().thenReturn(None) + + # Mock the initialized cleanup + when(self.daq).stop_acquisition().thenReturn(None) + when(self.daq).cleanup().thenReturn(None) + when(self.servers[0]).stop().thenReturn(None) + when(self.win).close().thenReturn(None) + task = RSVPCopyPhraseTask(parameters=self.parameters, + file_save=self.temp_dir, + + fake=self.fake) + # because the task is not initialized via setup, we need to set it to True here + task.initalized = True + + task.cleanup() + + verify(self.daq, times=1).stop_acquisition() + verify(self.daq, times=1).cleanup() + verify(self.servers[0], times=1).stop() + verify(self.win, times=1).close() + verify(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask, times=1).setup(any(), any(), any()) + verify(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask, times=1).write_offset_trigger() + verify(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask, times=1).exit_display() + verify(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask, times=1).wait() + def mock_inquiry_data(): """Generator that yields data mocking the copy_phrase_wrapper initialize_series method""" diff --git a/bcipy/tests/test_bci_main.py b/bcipy/tests/test_bci_main.py index 4b51234f0..e87dd8c9a 100644 --- a/bcipy/tests/test_bci_main.py +++ b/bcipy/tests/test_bci_main.py @@ -1,558 +1,131 @@ -import logging import unittest -from mockito import (any, mock, unstub, verify, verifyNoUnwantedInteractions, - verifyStubbedInvocationsAreUsed, when) - +from mockito import when, mock, verify, unstub, any +from bcipy.config import DEFAULT_PARAMETERS_PATH +from bcipy.exceptions import BciPyCoreException, UnregisteredExperimentException +from bcipy.task.orchestrator import SessionOrchestrator +from bcipy.main import bci_main from bcipy import main -from bcipy.config import (DEFAULT_EXPERIMENT_ID, DEFAULT_PARAMETERS_PATH, - STATIC_AUDIO_PATH) -from bcipy.helpers.exceptions import UnregisteredExperimentException -from bcipy.main import _clean_up_session, bci_main, execute_task -from bcipy.task import TaskType - -logging.disable(logging.CRITICAL) - - -class TestBciMain(unittest.TestCase): - - parameter_location = DEFAULT_PARAMETERS_PATH - data_save_location = '/' - save_location = '/' - parameters = { - 'data_save_loc': data_save_location, - 'log_name': 'test_log', - 'fake_data': False, - 'signal_model_path': '', - 'lm_path': '', - 'alert_sound_file': 'test.wav', - } - system_info = { - 'bcipy_version': 'test_version' - } - user = 'test_user' - task = mock() - task.label = 'RSVP Calibration' - experiment = DEFAULT_EXPERIMENT_ID - alert = False - fake = parameters['fake_data'] - - def tearDown(self) -> None: - verifyStubbedInvocationsAreUsed() - verifyNoUnwantedInteractions() - unstub() - - def test_bci_main_default_experiment(self) -> None: - when(main).validate_experiment(self.experiment).thenReturn(True) - when(main).validate_bcipy_session(self.parameters, self.fake).thenReturn(True) - when(main).load_json_parameters(self.parameter_location, value_cast=True).thenReturn( - self.parameters - ) - when(main).visualize_session_data(self.save_location, self.parameters).thenReturn(None) - when(main).get_system_info().thenReturn(self.system_info) - when(main).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment, - ).thenReturn(self.save_location) - when(main).configure_logger( - self.save_location, - version=self.system_info['bcipy_version'] - ) - when(main).collect_experiment_field_data(self.experiment, self.save_location) - when(main).execute_task( - self.task, - self.parameters, - self.save_location, - self.alert, - self.fake).thenReturn(True) - - response = bci_main(self.parameter_location, self.user, self.task) - self.assertEqual(response, True) - - # validate all the calls happen as expected and the correct # of times - verify(main, times=1).validate_experiment(self.experiment) - verify(main, times=1).validate_bcipy_session(self.parameters, self.fake) - verify(main, times=1).load_json_parameters(self.parameter_location, value_cast=True) - verify(main, times=1).get_system_info() - verify(main, times=1).visualize_session_data(self.save_location, self.parameters) - verify(main, times=1).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment) - verify(main, times=1).configure_logger( - self.save_location, - version=self.system_info['bcipy_version']) - verify(main, times=1).collect_experiment_field_data(self.experiment, self.save_location) - verify(main, times=1).execute_task(self.task, self.parameters, self.save_location, self.alert, self.fake) - - def test_bci_main_invalid_experiment(self) -> None: - experiment = 'does_not_exist' - with self.assertRaises(UnregisteredExperimentException): - bci_main(self.parameter_location, self.user, self.task, experiment) - - def test_invalid_parameter_location(self) -> None: - invalid_parameter_location = 'does/not/exist.json' - when(main).validate_experiment(self.experiment).thenReturn(True) - - with self.assertRaises(FileNotFoundError): - bci_main(invalid_parameter_location, self.user, self.task) - - verify(main, times=1).validate_experiment(self.experiment) - - def test_bci_main_visualize(self) -> None: - """Test bci_main with visualization enabled.""" - when(main).validate_experiment(self.experiment).thenReturn(True) - when(main).validate_bcipy_session(self.parameters, self.fake).thenReturn(True) - when(main).load_json_parameters(self.parameter_location, value_cast=True).thenReturn( - self.parameters - ) - when(main).visualize_session_data(self.save_location, self.parameters).thenReturn(None) - when(main).get_system_info().thenReturn(self.system_info) - when(main).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment, - ).thenReturn(self.save_location) - when(main).configure_logger( - self.save_location, - version=self.system_info['bcipy_version'] - ) - when(main).collect_experiment_field_data(self.experiment, self.save_location) - when(main).execute_task( - self.task, - self.parameters, - self.save_location, - self.alert, - self.fake).thenReturn(True) - - response = bci_main(self.parameter_location, self.user, self.task, visualize=True) - self.assertEqual(response, True) - - # validate all the calls happen as expected and the correct # of times - verify(main, times=1).validate_experiment(self.experiment) - verify(main, times=1).validate_bcipy_session(self.parameters, self.fake) - verify(main, times=1).load_json_parameters(self.parameter_location, value_cast=True) - verify(main, times=1).get_system_info() - verify(main, times=1).visualize_session_data(self.save_location, self.parameters) - verify(main, times=1).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment) - verify(main, times=1).configure_logger( - self.save_location, - version=self.system_info['bcipy_version']) - verify(main, times=1).collect_experiment_field_data(self.experiment, self.save_location) - verify(main, times=1).execute_task(self.task, self.parameters, self.save_location, self.alert, self.fake) - - def test_bci_main_visualize_disabled(self) -> None: - """Test bci_main with visualization disabled.""" - when(main).validate_experiment(self.experiment).thenReturn(True) - when(main).validate_bcipy_session(self.parameters, self.fake).thenReturn(True) - when(main).load_json_parameters(self.parameter_location, value_cast=True).thenReturn( - self.parameters - ) - when(main).get_system_info().thenReturn(self.system_info) - when(main).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment, - ).thenReturn(self.save_location) - when(main).configure_logger( - self.save_location, - version=self.system_info['bcipy_version'] - ) - when(main).collect_experiment_field_data(self.experiment, self.save_location) - when(main).execute_task( - self.task, - self.parameters, - self.save_location, - self.alert, - self.fake).thenReturn(True) - - response = bci_main(self.parameter_location, self.user, self.task, visualize=False) - self.assertEqual(response, True) - - # validate all the calls happen as expected and the correct # of times - verify(main, times=1).validate_experiment(self.experiment) - verify(main, times=1).validate_bcipy_session(self.parameters, self.fake) - verify(main, times=1).load_json_parameters(self.parameter_location, value_cast=True) - verify(main, times=1).get_system_info() - verify(main, times=1).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment) - verify(main, times=1).configure_logger( - self.save_location, - version=self.system_info['bcipy_version']) - verify(main, times=1).collect_experiment_field_data(self.experiment, self.save_location) - verify(main, times=1).execute_task(self.task, self.parameters, self.save_location, self.alert, self.fake) - - def test_bci_main_fake(self) -> None: - """Test bci_main with fake data override.""" - fake = True - when(main).validate_experiment(self.experiment).thenReturn(True) - when(main).validate_bcipy_session(self.parameters, fake).thenReturn(True) - when(main).load_json_parameters(self.parameter_location, value_cast=True).thenReturn( - self.parameters - ) - when(main).visualize_session_data(self.save_location, self.parameters).thenReturn(None) - when(main).get_system_info().thenReturn(self.system_info) - when(main).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment, - ).thenReturn(self.save_location) - when(main).configure_logger( - self.save_location, - version=self.system_info['bcipy_version'] - ) - when(main).collect_experiment_field_data(self.experiment, self.save_location) - when(main).execute_task( - self.task, - self.parameters, - self.save_location, - self.alert, - fake).thenReturn(True) - - response = bci_main(self.parameter_location, self.user, self.task, fake=fake) - self.assertEqual(response, True) - - # validate all the calls happen as expected and the correct # of times - verify(main, times=1).validate_experiment(self.experiment) - verify(main, times=1).validate_bcipy_session(self.parameters, fake) - verify(main, times=1).load_json_parameters(self.parameter_location, value_cast=True) - verify(main, times=1).get_system_info() - verify(main, times=1).visualize_session_data(self.save_location, self.parameters) - verify(main, times=1).init_save_data_structure( - self.data_save_location, - self.user, - self.parameter_location, - task=self.task.label, - experiment_id=self.experiment) - verify(main, times=1).configure_logger( - self.save_location, - version=self.system_info['bcipy_version']) - verify(main, times=1).collect_experiment_field_data(self.experiment, self.save_location) - verify(main, times=1).execute_task(self.task, self.parameters, self.save_location, self.alert, fake) - - -class TestCleanUpSession(unittest.TestCase): - - def tearDown(self) -> None: - unstub() - - def test_clean_up_no_server(self) -> None: - daq = mock() - display = mock() - servers = [] - # mock the required daq calls - when(daq).stop_acquisition() - when(daq).cleanup() - # mock the required display call - when(display).close() - - response = _clean_up_session(display, daq, servers) - self.assertTrue(response) - - verify(daq, times=1).stop_acquisition() - verify(daq, times=1).cleanup() - verify(display, times=1).close() - - def test_clean_up_with_server(self) -> None: - daq = mock() - display = mock() - server = mock() - servers = [server] - - # mock the required daq calls - when(daq).stop_acquisition() - when(daq).cleanup() - - # mock the required display call - when(display).close() - - # mock the required server call - when(server).stop() - - response = _clean_up_session(display, daq, servers) - self.assertTrue(response) - - verify(daq, times=1).stop_acquisition() - verify(daq, times=1).cleanup() - verify(display, times=1).close() - verify(server, times=1).stop() - - -class TestExecuteTask(unittest.TestCase): +class TestBCIMain(unittest.TestCase): def setUp(self) -> None: + self.parameters_path = DEFAULT_PARAMETERS_PATH self.parameters = { - 'k_folds': 10, - 'is_txt_stim': True, - 'signal_model_path': '', - 'alert_sound_file': 'test.wav', + 'fake_data': False, + 'parameter_location': False, + 'visualize': False, + 'data_save_loc': 'data/', } - self.save_folder = '/' + self.user = 'test user' + self.experiment = 'default' self.alert = False - self.task = TaskType(1) - self.fake = True - self.display_mock = mock() - self.daq = mock() - self.eeg_client = mock() - when(self.daq).get_client('EEG').thenReturn(self.eeg_client) - self.server = [mock()] + self.visualize = False + self.fake = False + self.logger = mock() + self.logger.info = lambda x: x def tearDown(self) -> None: unstub() - def test_execute_task_fake_data(self) -> None: - response = (self.daq, self.server) - when(main).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake - ).thenReturn(response) - when(main).init_display_window(self.parameters).thenReturn(self.display_mock) - when(main).print_message(self.display_mock, any()) - when(main).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=None, - signal_models=[], - fake=self.fake, - ) - when(main)._clean_up_session(self.display_mock, self.daq, self.server) - - execute_task(self.task, self.parameters, self.save_folder, self.alert, self.fake) - - verify(main, times=1).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake) - verify(main, times=1).init_display_window(self.parameters) - verify(main, times=1).print_message(self.display_mock, any()) - verify(main, times=1).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=None, - signal_models=[], - fake=self.fake, - ) - verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) - - def test_execute_task_real_data(self) -> None: - self.fake = False - response = (self.daq, self.server) - when(main).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake - ).thenReturn(response) - when(main).init_display_window(self.parameters).thenReturn(self.display_mock) - when(main).print_message(self.display_mock, any()) - when(main).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=None, - signal_models=[], - fake=self.fake, - ) - when(main)._clean_up_session(self.display_mock, self.daq, self.server) - - execute_task(self.task, self.parameters, self.save_folder, self.alert, self.fake) - - verify(main, times=1).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake) - verify(main, times=1).init_display_window(self.parameters) - verify(main, times=1).print_message(self.display_mock, any()) - verify(main, times=1).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=None, - signal_models=[], - fake=self.fake, - ) - verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) - - def test_execute_task_non_calibration_real_data(self) -> None: - self.fake = False - model_path = "data/mycalib/" - self.parameters['signal_model_path'] = model_path - self.task = TaskType(2) - signal_model = mock() - language_model = mock() - file_name = 'test' - load_model_response = [signal_model] - eeg_response = (self.daq, self.server) - when(main).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake).thenReturn(eeg_response) - when(main).init_display_window(self.parameters).thenReturn(self.display_mock) - when(main).print_message(self.display_mock, any()) - when(main).load_signal_models(directory=model_path).thenReturn(load_model_response) - when(main).init_language_model(self.parameters).thenReturn(language_model) - when(main).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=language_model, - signal_models=[signal_model], - fake=self.fake, - ) - when(main)._clean_up_session(self.display_mock, self.daq, self.server) - - execute_task(self.task, self.parameters, self.save_folder, self.alert, self.fake) - - verify(main, times=1).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake) - verify(main, times=1).init_display_window(self.parameters) - verify(main, times=1).print_message(self.display_mock, any()) - verify(main, times=1).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=language_model, - signal_models=[signal_model], - fake=self.fake, - ) - verify(main, times=1).load_signal_models(directory=model_path) - verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) - - def test_execute_language_model_enabled(self) -> None: - self.fake = False - self.task = TaskType(2) # set to a noncalibration task - - # mock the signal and language models - signal_model = mock() - file_name = 'test' - language_model = mock() - load_model_response = [signal_model] - - # mock the behavior of execute task - eeg_response = (self.daq, self.server) - when(main).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake).thenReturn(eeg_response) - when(main).init_language_model(self.parameters).thenReturn(language_model) - when(main).init_display_window(self.parameters).thenReturn(self.display_mock) - when(main).print_message(self.display_mock, any()) - when(main).load_signal_models(directory='').thenReturn(load_model_response) - when(main).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=language_model, - signal_models=[signal_model], - fake=self.fake, - ) - when(main)._clean_up_session(self.display_mock, self.daq, self.server) - - execute_task(self.task, self.parameters, self.save_folder, self.alert, self.fake) - - verify(main, times=1).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake) - verify(main, times=1).init_display_window(self.parameters) - verify(main, times=1).print_message(self.display_mock, any()) - verify(main, times=1).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=language_model, - signal_models=[signal_model], - fake=self.fake, - ) - verify(main, times=1).load_signal_models(directory='') - verify(main, times=1).init_language_model(self.parameters) - verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) - - def test_execute_with_alert_enabled(self): - expected_alert_path = f"{STATIC_AUDIO_PATH}/{self.parameters['alert_sound_file']}" - response = (self.daq, self.server) - when(main).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake, - ).thenReturn(response) - when(main).init_display_window(self.parameters).thenReturn(self.display_mock) - when(main).print_message(self.display_mock, any()) - when(main).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=None, - signal_models=[], - fake=self.fake, - ) - when(main)._clean_up_session(self.display_mock, self.daq, self.server) - when(main).play_sound(expected_alert_path) - - execute_task(self.task, self.parameters, self.save_folder, True, self.fake) - - verify(main, times=1).init_eeg_acquisition( - self.parameters, - self.save_folder, - server=self.fake) - verify(main, times=1).init_display_window(self.parameters) - verify(main, times=1).print_message(self.display_mock, any()) - verify(main, times=1).start_task( - self.display_mock, - self.daq, - self.task, - self.parameters, - self.save_folder, - language_model=None, - signal_models=[], - fake=self.fake, - ) - verify(main, times=1)._clean_up_session(self.display_mock, self.daq, self.server) - verify(main, times=1).play_sound(expected_alert_path) + def test_bci_main_fails_without_experiment_or_task(self) -> None: + with self.assertRaises(BciPyCoreException): + bci_main( + parameter_location=self.parameters_path, + user=self.user, + alert=self.alert, + visualize=self.visualize, + fake=self.fake + ) + + def test_bcipy_main_fails_with_invalid_experiment(self) -> None: + when(main).validate_bcipy_session(any(), any()).thenRaise(UnregisteredExperimentException) + with self.assertRaises(UnregisteredExperimentException): + bci_main( + parameter_location=self.parameters_path, + user=self.user, + experiment_id='invalid_experiment', + alert=self.alert, + visualize=self.visualize, + fake=self.fake + ) + + def test_bci_main_runs_with_valid_experiment(self) -> None: + when(main).validate_bcipy_session(any(), any()).thenReturn(True) # Mock the validate_bcipy_session function + when(main).load_json_parameters( + any(), value_cast=any()).thenReturn( + self.parameters) # Mock the load_json_parameters function + when(SessionOrchestrator).get_system_info().thenReturn(None) + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn(None) + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + when(SessionOrchestrator).initialize_copy_phrases().thenReturn(None) + when(SessionOrchestrator).add_tasks(any()).thenReturn(None) + when(SessionOrchestrator).execute().thenReturn(None) + + bci_main( + parameter_location=self.parameters_path, + user=self.user, + experiment_id=self.experiment, + alert=self.alert, + visualize=self.visualize, + fake=self.fake + ) + verify(SessionOrchestrator, times=1).add_tasks(any()) + verify(SessionOrchestrator, times=1).execute() + verify(SessionOrchestrator, times=1).initialize_copy_phrases() + verify(SessionOrchestrator, times=1)._init_orchestrator_logger(any()) + verify(SessionOrchestrator, times=1)._init_orchestrator_save_folder(any()) + verify(main, times=1).load_json_parameters(any(), value_cast=any()) + verify(SessionOrchestrator, times=1).get_system_info() + + def test_bci_main_runs_with_valid_task(self) -> None: + when(main).validate_bcipy_session(any(), any()).thenReturn(True) + when(main).load_json_parameters(any(), value_cast=any()).thenReturn(self.parameters) + when(SessionOrchestrator).get_system_info().thenReturn(None) + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn(None) + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + when(SessionOrchestrator).initialize_copy_phrases().thenReturn(None) + when(SessionOrchestrator).add_tasks(any()).thenReturn(None) + when(SessionOrchestrator).execute().thenReturn(None) + + bci_main( + parameter_location=self.parameters_path, + user=self.user, + task='RSVP Calibration', + alert=self.alert, + visualize=self.visualize, + fake=self.fake + ) + + verify(SessionOrchestrator, times=1).add_tasks(any()) + verify(SessionOrchestrator, times=1).execute() + verify(SessionOrchestrator, times=1).initialize_copy_phrases() + verify(SessionOrchestrator, times=1)._init_orchestrator_logger(any()) + verify(SessionOrchestrator, times=1)._init_orchestrator_save_folder(any()) + verify(main, times=1).load_json_parameters(any(), value_cast=any()) + verify(SessionOrchestrator, times=1).get_system_info() + + def test_bci_main_returns_false_with_orchestrator_execute_exception(self): + when(main).validate_bcipy_session(any(), any()).thenReturn(True) + when(main).load_json_parameters(any(), value_cast=any()).thenReturn(self.parameters) + when(SessionOrchestrator).get_system_info().thenReturn(None) + when(SessionOrchestrator)._init_orchestrator_save_folder(any()).thenReturn(None) + when(SessionOrchestrator)._init_orchestrator_logger(any()).thenReturn(self.logger) + when(SessionOrchestrator).initialize_copy_phrases().thenReturn(None) + when(SessionOrchestrator).add_tasks(any()).thenReturn(None) + when(SessionOrchestrator).execute().thenRaise(Exception) + + response = bci_main( + parameter_location=self.parameters_path, + user=self.user, + task='RSVP Calibration', + alert=self.alert, + visualize=self.visualize, + fake=self.fake + ) + + self.assertFalse(response) if __name__ == '__main__': diff --git a/requirements.txt b/requirements.txt index f3f9df88e..f4a764fdd 100644 --- a/requirements.txt +++ b/requirements.txt @@ -5,7 +5,7 @@ construct==2.8.14 mne==1.5.0 pyo==1.0.5 pyglet<=1.5.27,>=1.4 -PsychoPy==2023.2.1 +PsychoPy==2024.2.1 openpyxl==3.1.2 numpy==1.24.4 sounddevice==0.4.4 @@ -13,15 +13,15 @@ SoundFile==0.12.1 scipy==1.10.1 scikit-learn==1.2.2 seaborn==0.9.0 -matplotlib==3.7.2 +matplotlib==3.7.5 pylsl==1.16.2 -pandas==1.5.3 +pandas==2.0.3 psutil==5.7.2 Pillow==9.4.0 py-cpuinfo==9.0.0 pyedflib==0.1.34 -PyQt6==6.6.0 -PyQt6-Qt6==6.6.0 +pyopengl==3.1.7 +PyQt6==6.7.1 pywavelets==1.4.1 tqdm==4.62.2 reportlab==4.2.0 diff --git a/scripts/shell/run_gui.sh b/scripts/shell/run_gui.sh deleted file mode 100644 index 26065ada7..000000000 --- a/scripts/shell/run_gui.sh +++ /dev/null @@ -1,7 +0,0 @@ -#!/bin/bash -###### RUN BCI. ####### -# cd to path of bcipy code -# cd bcipy - -# Execute the gui code -python bcipy/gui/BCInterface.py diff --git a/setup.py b/setup.py index 7d0c34f83..76a95b252 100644 --- a/setup.py +++ b/setup.py @@ -107,7 +107,11 @@ def run(self): )), entry_points={ 'console_scripts': - ['bcipy = bcipy.main:bcipy_main', 'bcipy-sim = bcipy.simulator'], + [ + 'bcipy = bcipy.main:bcipy_main', + 'bcipy-erp-viz = bcipy.helpers.visualization:erp', + 'bcipy-sim = bcipy.simulator', + "bcipy-train = bcipy.signal.model.offline_analysis:main"], }, install_requires=REQUIRED, include_package_data=True, From 40f0770930025d7814112cecd442d13f7263330f Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 24 Oct 2024 09:57:00 -0700 Subject: [PATCH 323/330] Added model loading changes to Copy Phrase task --- bcipy/task/paradigm/rsvp/copy_phrase.py | 35 +++++++++++-------------- 1 file changed, 15 insertions(+), 20 deletions(-) diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 6380f029d..1a7be6384 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -6,30 +6,23 @@ from psychopy.visual import Window from bcipy.acquisition import ClientManager -from bcipy.config import ( - DEFAULT_EVIDENCE_PRECISION, - SESSION_DATA_FILENAME, - SESSION_SUMMARY_FILENAME, - TRIGGER_FILENAME, - WAIT_SCREEN_MESSAGE, - SESSION_LOG_FILENAME -) -from bcipy.display import ( - InformationProperties, - StimuliProperties, -) +from bcipy.config import (DEFAULT_EVIDENCE_PRECISION, SESSION_DATA_FILENAME, + SESSION_LOG_FILENAME, SESSION_SUMMARY_FILENAME, + TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE) +from bcipy.display import (InformationProperties, StimuliProperties, + init_display_window) from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.main import PreviewParams from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay +from bcipy.exceptions import TaskConfigurationException from bcipy.feedback.visual.visual_feedback import VisualFeedback -from bcipy.helpers.acquisition import init_acquisition, LslDataServer +from bcipy.helpers.acquisition import (LslDataServer, active_content_types, + init_acquisition) from bcipy.helpers.clock import Clock from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper -from bcipy.display import init_display_window -from bcipy.exceptions import TaskConfigurationException from bcipy.helpers.language_model import init_language_model -from bcipy.helpers.load import load_signal_models from bcipy.helpers.list import destutter +from bcipy.helpers.load import choose_signal_models from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import _save_session_related_data from bcipy.helpers.session import session_excel @@ -47,7 +40,8 @@ from bcipy.signal.model import SignalModel from bcipy.signal.model.inquiry_preview import compute_probs_after_preview from bcipy.task import Task, TaskData, TaskMode -from bcipy.task.control.evidence import EvidenceEvaluator, init_evidence_evaluator +from bcipy.task.control.evidence import (EvidenceEvaluator, + init_evidence_evaluator) from bcipy.task.data import EvidenceType, Inquiry, Session from bcipy.task.exceptions import DuplicateModelEvidence @@ -197,9 +191,9 @@ def get_language_model(self) -> LanguageModel: def get_signal_models(self) -> Optional[List[SignalModel]]: if not self.fake: try: - model_dir = self.parameters.get('signal_model_path', None) - signal_models = load_signal_models(directory=model_dir) - assert signal_models, f"No signal models found in {model_dir}" + signal_models = choose_signal_models( + active_content_types(self.parameters['acq_mode'])) + assert signal_models, "No signal models selected" except Exception as error: logger.exception(f'Cannot load signal model. Exiting. {error}') raise error @@ -982,6 +976,7 @@ def btn_press_count(self) -> int: return 0 inquiries = self.session.all_inquiries + activations = [] if self.preview_mode == 1: # press to confirm activations = [inq for inq in inquiries if inq.eeg_evidence] From d8065eab3b43fbb8cebe0a308ce0e8d47d25f7ca Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 24 Oct 2024 10:37:53 -0700 Subject: [PATCH 324/330] Preview Copy Phrase on the Matrix wait screen --- bcipy/display/paradigm/matrix/display.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index b22f081b4..f05f2b3e2 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -12,7 +12,7 @@ from bcipy.display.main import PreviewParams, init_preview_button_handler from bcipy.display.paradigm.matrix.layout import symbol_positions from bcipy.helpers.stimuli import resize_image -from bcipy.helpers.symbols import alphabet, qwerty_order, frequency_order +from bcipy.helpers.symbols import alphabet, frequency_order, qwerty_order from bcipy.helpers.triggers import _calibration_trigger logger = logging.getLogger(SESSION_LOG_FILENAME) @@ -378,6 +378,7 @@ def wait_screen(self, message: str, message_color: str) -> None: Define what happens on the screen when a user pauses a session. """ + self.draw_components() # Construct the wait message wait_message = visual.TextStim(win=self.window, @@ -399,7 +400,7 @@ def wait_screen(self, message: str, message_color: str) -> None: wait_logo.draw() except Exception as e: - self.logger.exception( + logger.exception( f'Cannot load logo image from path=[{BCIPY_LOGO_PATH}]') raise e From 437e720dbea96aa9c1b46ee0b71bb250d849b0a5 Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Tue, 29 Oct 2024 10:56:02 -0700 Subject: [PATCH 325/330] Report artifact enhancements, README, Python 3.10.6 support (#357) --- .coveragerc | 5 +- .github/workflows/main.yml | 6 +- Makefile | 2 +- README.md | 105 +++++++++++++----- bcipy/display/main.py | 1 + bcipy/display/paradigm/rsvp/display.py | 13 ++- .../paradigm/matrix/test_matrix_display.py | 6 +- .../tests/paradigm/rsvp/test_rsvp_display.py | 21 ++-- bcipy/gui/file_dialog.py | 16 ++- bcipy/helpers/convert.py | 2 +- bcipy/helpers/stimuli.py | 9 +- bcipy/helpers/tests/test_convert.py | 2 +- bcipy/helpers/visualization.py | 2 +- bcipy/parameters/experiment/experiments.json | 2 +- bcipy/parameters/parameters.json | 9 ++ bcipy/signal/evaluate/artifact.py | 42 +++++-- bcipy/signal/model/offline_analysis.py | 3 +- bcipy/signal/tests/evaluate/test_artifact.py | 2 +- bcipy/simulator/__init__.py | 5 + bcipy/simulator/__main__.py | 6 - bcipy/simulator/data/__init__.py | 0 bcipy/simulator/task/__init__.py | 0 bcipy/simulator/task/copy_phrase.py | 5 + bcipy/simulator/util/__init__.py | 0 bcipy/task/README.md | 32 ++++++ bcipy/task/actions.py | 32 ++++-- bcipy/task/calibration.py | 2 + .../demo/actions/demo_calibration_report.py | 35 ++++++ .../{ => orchestrator}/demo_orchestrator.py | 0 bcipy/task/paradigm/matrix/copy_phrase.py | 1 + .../paradigm/rsvp/calibration/calibration.py | 13 --- bcipy/task/paradigm/rsvp/copy_phrase.py | 7 +- .../matrix/test_matrix_calibration.py | 1 + .../tests/paradigm/rsvp/test_copy_phrase.py | 1 + requirements.txt | 2 +- scripts/shell/m2chip_install.sh | 2 +- setup.py | 4 +- 37 files changed, 290 insertions(+), 106 deletions(-) delete mode 100644 bcipy/simulator/__main__.py create mode 100644 bcipy/simulator/data/__init__.py create mode 100644 bcipy/simulator/task/__init__.py create mode 100644 bcipy/simulator/util/__init__.py create mode 100644 bcipy/task/demo/actions/demo_calibration_report.py rename bcipy/task/demo/{ => orchestrator}/demo_orchestrator.py (100%) diff --git a/.coveragerc b/.coveragerc index 443874bee..437e6b790 100644 --- a/.coveragerc +++ b/.coveragerc @@ -2,12 +2,15 @@ [run] omit = *__init__* + *__main__* */usr/local/lib* *tests* *test* *demo* *exceptions.py - */gui/* + */gui/experiments/* + */gui/viewer/* + */gui/BCInterface.py [report] exclude_lines = diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 5ced794ff..770802069 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -18,7 +18,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [3.8, 3.9] + python-version: [3.8, 3.9, 3.10.6] steps: - uses: actions/checkout@v2 @@ -68,7 +68,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [3.8, 3.9] + python-version: [3.8, 3.9, 3.10.6] steps: - uses: actions/checkout@v2 @@ -103,7 +103,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [3.8, 3.9] + python-version: [3.8, 3.9, 3.10.6] steps: - uses: actions/checkout@v4 diff --git a/Makefile b/Makefile index dcdc1e0a9..25f836f37 100644 --- a/Makefile +++ b/Makefile @@ -3,7 +3,7 @@ install: dev-install: pip install -r dev_requirements.txt - pip install psychopy==2023.2.1 --no-deps + pip install psychopy==2024.2.1 --no-deps pip install kenlm==0.1 --global-option="--max_order=12" make install diff --git a/README.md b/README.md index da8abf015..624bcdba3 100644 --- a/README.md +++ b/README.md @@ -40,7 +40,8 @@ If using zsh, instead of bash, you may encounter a segementation fault when runn ## Installation --------------- -#### BciPy Setup +### BciPy Setup +---------------- In order to run BciPy on your computer, after following the dependencies above, you will need to install the BciPy package. @@ -62,26 +63,86 @@ Alternately, if [Make](http://www.mingw.org/) is installed, you may run the foll make dev-install ``` -#### Client Usage - Invoke an experiment protocol or task directly using command line utility `bcipy`. - - You can pass it attributes with flags, if desired. - Running with a User ID and Task: `bcipy --user "bci_user" --task "RSVP Calibration"` - Running with a User ID and Tasks with a registered Protocol: `bcipy --user "bci_user" --experiment "default"` - Running with fake data: `bcipy --fake` - Running without visualizations: `bcipy --noviz` - Running with alerts after each Task execution: `bcipy --alert` - Running with custom parameters: `bcipy --parameters "path/to/valid/parameters.json"` +### Client Usage +---------------- + +##### Run an experiment protocol or task + +Invoke an experiment protocol or task directly using command line utility `bcipy`. + +- Use the help flag to see other available input options: `bcipy --help` + - You can pass it attributes with flags, if desired. + - Running with a User ID and Task: + - `bcipy --user "bci_user" --task "RSVP Calibration"` + - Running with a User ID and Tasks with a registered Protocol: + - `bcipy --user "bci_user" --experiment "default"` + - Running with fake data: + - `bcipy --fake` + - Running without visualizations: + - `bcipy --noviz` + - Running with alerts after each Task execution: + - `bcipy --alert` + - Running with custom parameters: + - `bcipy --parameters "path/to/valid/parameters.json"` + +##### Train a signal model with registered BciPy models + +To train a signal model (currently `PCARDAKDE`), run the following command after installing BciPy: + +`bcipy-train` + +- Use the help flag to see other available input options: `bcipy-train --help` + - You can pass it attributes with flags, if desired. + - Running without a window prompting for data session folder: + - `bcipy-train -d path/to/data` + - Running with data visualizations (ERPs, etc.): + - `bcipy-train -v` + - Running with data visualizations that do not show, but save to file: + - `bcipy-train -s` + - Running with balanced accuracy: + - `bcipy-train --balanced-acc` + - Running with alerts after each Task execution: + - `bcipy-train --alert` + - Running with custom parameters: + - `bcipy-train -p "path/to/valid/parameters.json"` + +##### Visualize ERP data from a session with Target / Non-Target labels + +To generate plots that can be shown or saved after collection of data, run the following command after installing BciPy: + +`bcipy-erp-viz` + +- Use the help flag to see other available input options: `bcipy-erp-viz --help` + - You can pass it attributes with flags, if desired. + - Running without a window prompting for data session folder: + - `bcipy-erp-viz -s path/to/data` + - Running with data visualizations (ERPs, etc.): + - `bcipy-erp-viz --show` + - Running with data visualizations that do not show, but save to file: + - `bcipy-erp-viz --save` + - Running with custom parameters (default is in bcipy/parameters/parameters.json): + - `bcipy-erp-viz -p "path/to/valid/parameters.json"` + +##### BciPy Simulator Usage + +The simulator can be run using the command line utility `bcipy-sim`. + +Ex. +`bcipy-sim -d my_data_folder/ -p my_parameters.json -m my_models/ -n 5` + +Run `bcipy-sim --help` for documentation or see the README in the simulator module. - - Use the help flag to see other available input options: `bcipy --help` -##### Example Usage as a Package +### Package Usage +------------------- ```python from bcipy.helpers import system_utils system_utils.get_system_info() ``` -#### Example Usage through the GUI +### GUI Usage +------------- Run the following command in your terminal to start the BciPy GUI: ```sh @@ -95,16 +156,6 @@ make bci-gui ``` -#### Simulator Usage - -The simulator can be run using the command line utility `bcipy-sim`. - -Ex. -`bcipy-sim -d my_data_folder/ -p my_parameters.json -m my_models/ -n 5` - -Run `bcipy-sim --help` for documentation or see the README in the simulator module. - - ## Glossary ----------- @@ -150,7 +201,7 @@ This a list of the major modules and their functionality. Each module will conta ## Paradigms ------------ -See `bcipy/task/README.md` for more information on all supported paradigms and modes. The following are the supported and validated paradigms: +See `bcipy/task/README.md` for more information on all supported paradigms, tasks, actions and modes. The following are the supported and validated paradigms: > RSVPKeyboard @@ -213,7 +264,6 @@ After running the above command, the recommended offset correction value will be ```bash # Let's say the recommneded offset value is 0.1 python bcipy/helpers/offset.py --offset "0.1" -p - ``` Alternately, if Make is installed, you may run the follow command to run offset determination and display the results: @@ -306,10 +356,11 @@ make type ### Contributions Welcome! +-------------------------- If you want to be added to the development team slack or have additional questions, please reach out to us at support@cambi.tech! -### Contribution Guidelines +#### Contribution Guidelines We follow and will enforce the contributor's covenant to foster a safe and inclusive environment for this open source software, please reference this link for more information: https://www.contributor-covenant.org/ @@ -325,7 +376,7 @@ Other guidelines: See this resource for examples: http://docs.python-guide.org/en/latest/writing/style/ -## Contributors +### Contributors --------------- All contributions are greatly appreciated! diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 8aa9f9b94..019abae64 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -293,6 +293,7 @@ class PreviewParams(NamedTuple): preview_inquiry_key_input: str preview_inquiry_progress_method: int preview_inquiry_isi: float + preview_box_text_size: float @property def button_press_mode(self): diff --git a/bcipy/display/paradigm/rsvp/display.py b/bcipy/display/paradigm/rsvp/display.py index 7e2d14163..2a696b12d 100644 --- a/bcipy/display/paradigm/rsvp/display.py +++ b/bcipy/display/paradigm/rsvp/display.py @@ -73,6 +73,8 @@ def __init__( self.stimuli_colors = stimuli.stim_colors self.stimuli_timing = stimuli.stim_timing self.stimuli_font = stimuli.stim_font + # Note: there is a bug in TextBox2 that prevents certain custom fonts from being used. This is to avoid that. + self.textbox_font = 'Consolas' self.stimuli_height = stimuli.stim_height self.stimuli_pos = stimuli.stim_pos self.is_txt_stim = stimuli.is_txt_stim @@ -271,13 +273,12 @@ def _generate_inquiry_preview(self) -> visual.TextBox2: text = ' '.join(self.stimuli_inquiry).split('+ ')[1] return self._create_stimulus( - 0.12, + self.preview_params.preview_box_text_size, stimulus=text, units='height', stimuli_position=self.stimuli_pos, mode='textbox', - align_text='left', - wrap_width=0.025) + align_text='left') def _generate_inquiry(self) -> list: """Generate inquiry. @@ -439,9 +440,11 @@ def _create_stimulus( borderWidth=2, borderColor='white', units=units, - font=self.stimuli_font, + padding=0.05, + font=self.textbox_font, letterHeight=height, - size=[.5, .5], + size=[.55, .55], pos=stimuli_position, alignment=align_text, + editable=False, ) diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py index dd71cc251..fceca5154 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py @@ -143,7 +143,8 @@ def test_do_inquiry_with_preview_accepted(self): preview_inquiry_length=2, preview_inquiry_key_input='return', preview_inquiry_progress_method=2, - preview_inquiry_isi=1) + preview_inquiry_isi=1, + preview_box_text_size=0.1) matrix = MatrixDisplay(window=self.window, experiment_clock=self.experiment_clock, stimuli=self.stimuli, @@ -181,7 +182,8 @@ def test_do_inquiry_with_preview_rejected(self): preview_inquiry_length=2, preview_inquiry_key_input='return', preview_inquiry_progress_method=2, - preview_inquiry_isi=1) + preview_inquiry_isi=1, + preview_box_text_size=0.1) matrix = MatrixDisplay(window=self.window, experiment_clock=self.experiment_clock, stimuli=self.stimuli, diff --git a/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py b/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py index bb3cdd7ec..95816a9cf 100644 --- a/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py +++ b/bcipy/display/tests/paradigm/rsvp/test_rsvp_display.py @@ -134,7 +134,8 @@ def test_preview_enabled_is_false(self): preview_inquiry_length=2, preview_inquiry_key_input='space', preview_inquiry_progress_method=1, - preview_inquiry_isi=1) + preview_inquiry_isi=1, + preview_box_text_size=0.1) rsvp = RSVPDisplay(self.window, self.static_clock, self.experiment_clock, @@ -151,7 +152,8 @@ def test_preview_enabled_is_true(self): preview_inquiry_length=2, preview_inquiry_key_input='space', preview_inquiry_progress_method=1, - preview_inquiry_isi=1) + preview_inquiry_isi=1, + preview_box_text_size=0.1) rsvp = RSVPDisplay(self.window, self.static_clock, self.experiment_clock, @@ -173,7 +175,8 @@ def test_preview_inquiry_evoked_press_to_accept_pressed( preview_inquiry_length=0.01, preview_inquiry_key_input='space', preview_inquiry_progress_method=1, - preview_inquiry_isi=0.01) + preview_inquiry_isi=0.01, + preview_box_text_size=0.1) self.init_display(preview_config) button_press_handler_mock.has_response.return_value = True @@ -209,7 +212,8 @@ def test_preview_inquiry_evoked_press_to_skip_pressed( preview_inquiry_length=0.01, preview_inquiry_key_input='space', preview_inquiry_progress_method=2, - preview_inquiry_isi=0.01) + preview_inquiry_isi=0.01, + preview_box_text_size=0.1) self.init_display(preview_config) button_press_handler_mock.has_response.return_value = True @@ -238,7 +242,8 @@ def test_preview_inquiry_evoked_press_to_accept_not_pressed( preview_inquiry_length=0.01, preview_inquiry_key_input='space', preview_inquiry_progress_method=1, - preview_inquiry_isi=0.01) + preview_inquiry_isi=0.01, + preview_box_text_size=0.1) self.init_display(preview_config) button_press_handler_mock.has_response.return_value = False @@ -264,7 +269,8 @@ def test_preview_inquiry_evoked_press_to_skip_not_pressed( preview_inquiry_length=0.01, preview_inquiry_key_input='space', preview_inquiry_progress_method=2, - preview_inquiry_isi=0.01) + preview_inquiry_isi=0.01, + preview_box_text_size=0.1) self.init_display(preview_config) button_press_handler_mock.has_response.return_value = False @@ -290,7 +296,8 @@ def test_preview_inquiry_preview_only_response_registered( preview_inquiry_length=0.01, preview_inquiry_key_input='space', preview_inquiry_progress_method=0, - preview_inquiry_isi=0.01) + preview_inquiry_isi=0.01, + preview_box_text_size=0.1) self.init_display(preview_config) button_press_handler_mock.has_response.return_value = False diff --git a/bcipy/gui/file_dialog.py b/bcipy/gui/file_dialog.py index 27a546b72..715b223b9 100644 --- a/bcipy/gui/file_dialog.py +++ b/bcipy/gui/file_dialog.py @@ -15,7 +15,7 @@ class FileDialog(QWidget): def __init__(self): super().__init__() - self.title = 'PyQt6 file dialogs - pythonspot.com' + self.title = 'File Dialog' self.width = 640 self.height = 480 @@ -45,7 +45,7 @@ def ask_file(self, options=self.options) return filename - def ask_directory(self, directory: str = "") -> str: + def ask_directory(self, directory: str = "", prompt: str = "Select Directory") -> str: """Opens a dialog window to select a directory. Returns @@ -53,12 +53,15 @@ def ask_directory(self, directory: str = "") -> str: path or None """ return QFileDialog.getExistingDirectory(self, - "Select Directory", + prompt, directory=directory, options=self.options) -def ask_filename(file_types: str = DEFAULT_FILE_TYPES, directory: str = "", prompt="Select File") -> str: +def ask_filename( + file_types: str = DEFAULT_FILE_TYPES, + directory: str = "", + prompt: str = "Select File") -> str: """Prompt for a file. Parameters @@ -87,7 +90,7 @@ def ask_filename(file_types: str = DEFAULT_FILE_TYPES, directory: str = "", prom return filename -def ask_directory() -> str: +def ask_directory(prompt: str = "Select Directory") -> str: """Prompt for a directory. Returns @@ -100,9 +103,10 @@ def ask_directory() -> str: directory = '' if preferences.last_directory: directory = str(Path(preferences.last_directory).parent) - name = dialog.ask_directory(directory) + name = dialog.ask_directory(directory, prompt=prompt) if name and Path(name).is_dir(): preferences.last_directory = name + # Alternatively, we could use `app.closeAllWindows()` app.quit() diff --git a/bcipy/helpers/convert.py b/bcipy/helpers/convert.py index 07c6ec34f..3550c7ff8 100644 --- a/bcipy/helpers/convert.py +++ b/bcipy/helpers/convert.py @@ -498,7 +498,7 @@ def convert_to_mne( channel_types: Optional[List[str]] = None, transform: Optional[Composition] = None, montage: str = 'standard_1020', - volts: bool = True) -> RawArray: + volts: bool = False) -> RawArray: """Convert to MNE. Returns BciPy RawData as an MNE RawArray. This assumes all channel names diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 8a1af1a11..795218db3 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -433,12 +433,19 @@ def mne_epochs(mne_data: RawArray, tmp_data.set_annotations(all_annotations) events_from_annot, _ = mne.events_from_annotations(tmp_data) + + if baseline is None: + baseline = (0, 0) + tmin = -0.1 + else: + tmin = baseline[0] + return Epochs( mne_data, events_from_annot, baseline=baseline, tmax=trial_length, - tmin=-0.05, + tmin=tmin, proj=False, # apply SSP projection to data. Defaults to True in Epochs. reject_by_annotation=reject_by_annotation, preload=preload) diff --git a/bcipy/helpers/tests/test_convert.py b/bcipy/helpers/tests/test_convert.py index 83399279a..2b402c88d 100644 --- a/bcipy/helpers/tests/test_convert.py +++ b/bcipy/helpers/tests/test_convert.py @@ -528,7 +528,7 @@ def test_convert_to_mne_with_transform(self): def transform(x, fs): return x * multiplier, fs - data = convert_to_mne(self.raw_data, transform=transform) + data = convert_to_mne(self.raw_data, transform=transform, volts=True) self.assertTrue(len(data) > 0) self.assertEqual(data.ch_names, self.channels[1:]) diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 2c4402736..7f0d37dc3 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -87,7 +87,7 @@ def visualize_erp( trial_length = trial_window[1] - 0.0 # check for a baseline interval or set to None - if trial_window[0] < 0: + if trial_window[0] <= 0: baseline = (trial_window[0], 0.0) else: baseline = None diff --git a/bcipy/parameters/experiment/experiments.json b/bcipy/parameters/experiment/experiments.json index add8e1184..1c27911f4 100644 --- a/bcipy/parameters/experiment/experiments.json +++ b/bcipy/parameters/experiment/experiments.json @@ -7,6 +7,6 @@ "BCIOne": { "fields": [], "summary": "BCIOne experiment", - "protocol": "RSVP Calibration -> IntertaskAction -> OfflineAnalysisAction -> IntertaskAction -> Matrix Calibration -> IntertaskAction -> OfflineAnalysisAction -> IntertaskAction -> BciPy Report Action" + "protocol": "RSVP Calibration -> IntertaskAction -> OfflineAnalysisAction -> IntertaskAction -> Matrix Calibration -> IntertaskAction -> OfflineAnalysisAction -> IntertaskAction -> BciPyReportAction" } } \ No newline at end of file diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 296d91858..74a8b5697 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -807,6 +807,15 @@ "editable": false, "type": "bool" }, + "preview_box_text_size": { + "value": "0.1", + "section": "task_config", + "name": "Preview Inquiry Box Text Size", + "helpTip": "Specifies the height of text stimuli in the preview inquiry box. See https://www.psychopy.org/general/units.html. Default: 0.1", + "recommended": "", + "editable": false, + "type": "float" + }, "preview_inquiry_error_prob": { "value": "0.05", "section": "bci_config", diff --git a/bcipy/signal/evaluate/artifact.py b/bcipy/signal/evaluate/artifact.py index 19ec6180f..f40bcf134 100644 --- a/bcipy/signal/evaluate/artifact.py +++ b/bcipy/signal/evaluate/artifact.py @@ -4,6 +4,7 @@ from pathlib import Path from typing import Union, List, Tuple, Optional from logging import getLogger +import logging from bcipy.config import ( DEFAULT_PARAMETER_FILENAME, @@ -28,29 +29,34 @@ from bcipy.acquisition.devices import DeviceSpec import mne -log = getLogger(SESSION_LOG_FILENAME) mne.set_log_level('WARNING') +log = getLogger(SESSION_LOG_FILENAME) + from mne import Annotations class DefaultArtifactParameters(Enum): """Default Artifact Parameters. - These values are used as defaults for artifact analysis purposes. + These values are used as defaults for artifact analysis purposes. These values were determined through + experimentation and are used as a starting point for artifact detection. These values should be adjusted + based on the data being analyzed. """ # Voltage - PEAK_THRESHOLD = 75e-7 - PEAK_MIN_DURATION = 0.005 + PEAK_THRESHOLD = 15e-6 + PEAK_MIN_DURATION = 0.001 FLAT_THRESHOLD = 0.5e-6 FLAT_MIN_DURATION = 0.1 + VOlTAGE_LABEL_DURATION = 0.25 # Eye - EOG_LABEL_DURATION = 0.2 - EOG_THRESHOLD = 75e-6 + EOG_THRESHOLD = 55e-6 EOG_MIN_DURATION = 0.5 + EOG_LABEL_DURATION = 0.25 + # I/O ARTIFACT_LABELLED_FILENAME = 'artifacts.fif' @@ -185,6 +191,7 @@ def __init__( assert len(device_spec.channel_specs) > 0, 'DeviceSpec used must have channels. None found.' self.units = device_spec.channel_specs[0].units + log.info(f'Artifact detection using {self.units} units.') assert self.units in self.supported_units, \ f'Data loaded in units that cannot be processed. Support units={self.supported_units}' # MNE assumes that data is recorded in Volts. However, many devices use microvolts. @@ -195,6 +202,8 @@ def __init__( self.detect_eog = detect_eog self.semi_automatic = semi_automatic + log.info(f'Artifact detection with {self.detect_voltage=}, {self.detect_eog=}, {self.semi_automatic=}') + self.save_path = save_path def detect_artifacts(self) -> Tuple[str, float]: @@ -220,6 +229,7 @@ def detect_artifacts(self) -> Tuple[str, float]: self.dropped = ( f'{kept_epochs}/{total_epochs} retained. {percent_dropped}% epochs dropped due to artifacts.' ) + log.info(f'{self.dropped=}') self.analysis_done = True if self.save_path: @@ -413,6 +423,7 @@ def label_voltage_events( bad_percent=self.percent_bad, peak=peak[0]) if len(peak_voltage_annotations) > 0: + log.info(f'Peak voltage events found: {len(peak_voltage_annotations)}') onsets, durations, descriptions = self.concat_annotations( peak_voltage_annotations, pre_event, @@ -426,6 +437,7 @@ def label_voltage_events( flat_voltage_annotations, bad_channels2 = mne.preprocessing.annotate_amplitude( self.mne_data, min_duration=flat[1], bad_percent=self.percent_bad, flat=flat[0]) if len(flat_voltage_annotations) > 0: + log.info(f'Flat voltage events found: {len(flat_voltage_annotations)}') onsets, durations, descriptions = self.concat_annotations( flat_voltage_annotations, pre_event, @@ -438,13 +450,15 @@ def label_voltage_events( # combine the bad channels bad_channels = bad_channels1 + bad_channels2 - if len(onsets) > 0 and len(bad_channels) > 0: + if len(bad_channels) == 0: + bad_channels = None + + if len(onsets) > 0: return mne.Annotations(onsets, durations, descriptions), bad_channels - elif len(bad_channels) > 0: + else: + log.info('No voltage events found.') return None, bad_channels - return None - def concat_annotations( self, annotations: mne.Annotations, @@ -524,6 +538,10 @@ def write_mne_annotations( if __name__ == "__main__": + logging.basicConfig( + level=logging.INFO, + format="[%(threadName)-9s][%(asctime)s][%(name)s][%(levelname)s]: %(message)s") + import argparse parser = argparse.ArgumentParser() @@ -554,7 +572,7 @@ def write_mne_annotations( for session in Path(path).iterdir(): # loop through the sessions, pausing after each one to allow for manual stopping if session.is_dir(): - log.info(f'Processing {session}') + print(f'Processing {session}') prompt = input('Hit enter to continue or type "skip" to skip processing: ') if prompt != 'skip': # load the parameters from the data directory @@ -568,7 +586,7 @@ def write_mne_annotations( # load the triggers if args.colabel: trigger_type, trigger_timing, trigger_label = trigger_decoder( - offset=parameters.get('static_trigger_offset'), + offset=0.1, trigger_path=f"{session}/{TRIGGER_FILENAME}", exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], ) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index bbbda64e4..ae0ff6845 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -144,8 +144,9 @@ def analyze_erp(erp_data, parameters, device_spec, data_folder, estimate_balance # Process triggers.txt files trigger_targetness, trigger_timing, _ = trigger_decoder( trigger_path=f"{data_folder}/{TRIGGER_FILENAME}", - exclusion=[TriggerType.PREVIEW, TriggerType.EVENT, TriggerType.FIXATION], + exclusion=[TriggerType.PREVIEW, TriggerType.EVENT], offset=static_offset, + remove_pre_fixation=True, device_type='EEG' ) diff --git a/bcipy/signal/tests/evaluate/test_artifact.py b/bcipy/signal/tests/evaluate/test_artifact.py index c2fa2bc99..758dc535f 100644 --- a/bcipy/signal/tests/evaluate/test_artifact.py +++ b/bcipy/signal/tests/evaluate/test_artifact.py @@ -119,7 +119,7 @@ def test_artifact_type(self): def test_default_artifact_parameters(self): """Test the DefaultArtifactParameters class.""" - self.assertEqual(DefaultArtifactParameters.EOG_THRESHOLD.value, 75e-6) + self.assertEqual(DefaultArtifactParameters.EOG_THRESHOLD.value, 5.5e-05) self.assertEqual(DefaultArtifactParameters.VOlTAGE_LABEL_DURATION.value, 0.25) self.assertEqual(DefaultArtifactParameters.ARTIFACT_LABELLED_FILENAME.value, 'artifacts.fif') diff --git a/bcipy/simulator/__init__.py b/bcipy/simulator/__init__.py index b3cc41c2d..7bb813e41 100644 --- a/bcipy/simulator/__init__.py +++ b/bcipy/simulator/__init__.py @@ -1 +1,6 @@ """ Simulator package. View README """ +from bcipy.simulator.task import task_runner + + +def main(): + task_runner.main() diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py deleted file mode 100644 index 804ab1131..000000000 --- a/bcipy/simulator/__main__.py +++ /dev/null @@ -1,6 +0,0 @@ -""" Entry point to run Simulator """ - -from bcipy.simulator.task import task_runner - -if __name__ == '__main__': - task_runner.main() diff --git a/bcipy/simulator/data/__init__.py b/bcipy/simulator/data/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/bcipy/simulator/task/__init__.py b/bcipy/simulator/task/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 1dee73b09..119f129a5 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -14,6 +14,7 @@ from bcipy.simulator.util.state import SimState from bcipy.task.control.evidence import EvidenceEvaluator from bcipy.task.data import EvidenceType +from bcipy.task import TaskMode from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask DEFAULT_EVIDENCE_TYPE = EvidenceType.ERP @@ -28,6 +29,10 @@ class SimulatorCopyPhraseTask(RSVPCopyPhraseTask): """CopyPhraseTask that simulates user interactions by sampling data from a DataSampler.""" + name = "Simulator Copy Phrase" + paradigm = "RSVP" + mode = TaskMode.COPYPHRASE + def __init__(self, parameters: Parameters, file_save: str, signal_models: List[SignalModel], language_model: LanguageModel, samplers: Dict[SignalModel, diff --git a/bcipy/simulator/util/__init__.py b/bcipy/simulator/util/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/bcipy/task/README.md b/bcipy/task/README.md index 7defbe7e4..2efd0fa5b 100644 --- a/bcipy/task/README.md +++ b/bcipy/task/README.md @@ -39,6 +39,38 @@ Currently, these are the supported paradigms and modes: > Calibration: Used to calibrate the VEP paradigm for a user. Note this has not been extensively tested, use with caution. +## Actions +----------- + +### BciPy Calibration Report Action + +This action is used to generate a calibration report for a user. It will generate a report with the following information: + +- Session Summary + - Task / Paradigm (RSVP, Matrix, or VEP) + - AUC (if available) + - Amplifier + - Data Location +- Signal Report + - Signal Artifact Report + - Determine the percentage of data that is artifact based on the artifact thresholds + - See `bcipy.signal.evaluate.artifact.py` for more information, to visualize the artifacts or to adjust the thresholds. + - Signal Plots (target / non-target) + - ERP + - Topographic Maps + +The report will be saved in the protocol directory. A demo of the action can be used offline by running the following command: + +```bash +python bcipy/task/demo/demo_calibration_report.py +``` + +This will prompt the user to select a protocol directory to generate a calibration report for. The report will be saved in the protocol directory. + +### Offline Analysis Action + +This action is used to run an offline analysis on the data collected during a session. It will run the command line version of the BciPy client on the data collected during the session. The results will be saved in the session directory. + ## Running Tasks using the SessionOrchestrator The `SessionOrchestrator` is a class that can be used to run a Protocol (sequence of Tasks/Actions). The core BciPy client and GUI use this class and resulting data strucutures. It will run the tasks in the order defined, handle the transition between tasks, and persist data. There are several optional arguments that can be provided to the orchestrator: diff --git a/bcipy/task/actions.py b/bcipy/task/actions.py index 12b520624..907e7456a 100644 --- a/bcipy/task/actions.py +++ b/bcipy/task/actions.py @@ -8,6 +8,7 @@ from bcipy.gui.bciui import run_bciui from matplotlib.figure import Figure +from bcipy.gui.file_dialog import ask_directory from bcipy.gui.intertask_gui import IntertaskGUI from bcipy.gui.experiments.ExperimentField import start_experiment_field_collection_gui from bcipy.task import Task, TaskMode, TaskData @@ -79,7 +80,6 @@ def __init__( self.parameters_path = parameters_path self.alert_finished = alert_finished - # TODO: add a feature to orchestrator to permit the user to select the last task directory or have it loaded. if last_task_dir: self.data_directory = last_task_dir else: @@ -96,6 +96,8 @@ def execute(self) -> TaskData: """ logger.info("Running offline analysis action") try: + # Note: The subprocess.run function will cause a segmentation fault if visualization and alerting are + # enabled. This is because the MNE library. cmd = f'bcipy-train -p "{self.parameters_path}"' if self.alert_finished: cmd += " --alert" @@ -212,15 +214,21 @@ def __init__( self.save_folder = save_path # Currently we assume all Tasks have the same parameters, this may change in the future. self.parameters = parameters - self.protocol_path = protocol_path or '' + + if not protocol_path: + protocol_path = ask_directory( + prompt="Select BciPy protocol directory with calibration data...") + self.protocol_path = protocol_path self.last_task_dir = last_task_dir - self.default_transform = None self.trial_window = (-0.2, 1.0) - self.static_offset = None self.report = Report(self.protocol_path) self.report_sections: List[ReportSection] = [] self.all_raw_data: List[RawData] = [] + + # These are pulled off the device spec / set from parameters + self.default_transform = None self.type_amp = None + self.static_offset = None def execute(self) -> TaskData: """Excute the report generation action. @@ -262,7 +270,9 @@ def execute(self) -> TaskData: self.report.save() return TaskData( save_path=self.save_folder, - task_dict={}, + task_dict={ + 'reports': len(calibration_directories), + }, ) def create_signal_report(self, data_dir: Path) -> SignalReportSection: @@ -274,7 +284,11 @@ def create_signal_report(self, data_dir: Path) -> SignalReportSection: device_spec = devices.preconfigured_device(raw_data.daq_type) self.static_offset = device_spec.static_offset channel_map = analysis_channels(channels, device_spec) - self.all_raw_data.append(raw_data) + + logger.info( + f"Creating signal section for {data_dir}. \n" + f"Channels: {channels}, Sample Rate: {sample_rate}, " + f"Device: {self.type_amp}, Static Offset: {self.static_offset}") # Set the default transform if not already set if not self.default_transform: @@ -341,7 +355,7 @@ def find_eye_channels(self, device_spec: DeviceSpec) -> Optional[list]: eye_channels = None return eye_channels - def get_triggers(self, session) -> tuple: + def get_triggers(self, session: str) -> tuple: trigger_type, trigger_timing, trigger_label = trigger_decoder( offset=self.static_offset, trigger_path=f"{session}/{TRIGGER_FILENAME}", @@ -354,12 +368,12 @@ def get_triggers(self, session) -> tuple: return trigger_type, trigger_timing, trigger_label def get_figure_handles(self, raw_data, channel_map, triggers) -> List[Figure]: - _, trigger_timing, trigger_label = triggers + trigger_type, trigger_timing, _ = triggers figure_handles = visualize_erp( raw_data, channel_map, trigger_timing, - trigger_label, + trigger_type, self.trial_window, transform=self.default_transform, plot_average=True, diff --git a/bcipy/task/calibration.py b/bcipy/task/calibration.py index 839c85eda..3f39ff2e9 100644 --- a/bcipy/task/calibration.py +++ b/bcipy/task/calibration.py @@ -228,6 +228,8 @@ def trigger_type(self, symbol: str, target: str, return TriggerType.FIXATION if target == symbol: return TriggerType.TARGET + if 'key_press' in symbol: + return TriggerType.EVENT return TriggerType.NONTARGET def present_inquiry(self, index: int, diff --git a/bcipy/task/demo/actions/demo_calibration_report.py b/bcipy/task/demo/actions/demo_calibration_report.py new file mode 100644 index 000000000..bce16274c --- /dev/null +++ b/bcipy/task/demo/actions/demo_calibration_report.py @@ -0,0 +1,35 @@ +import logging +from bcipy.task.actions import BciPyCalibrationReportAction +from bcipy.config import DEFAULT_PARAMETERS_PATH +from bcipy.helpers.load import load_json_parameters + +logging.basicConfig(level=logging.INFO) + + +if __name__ == '__main__': + import argparse + parser = argparse.ArgumentParser(description='Generate a calibration report from a session data file.') + # Add the arguments: parameters and protocol + parser.add_argument( + '--parameters', + help=f'Path to a BciPy parameters file. Defaults to {DEFAULT_PARAMETERS_PATH}', + default=DEFAULT_PARAMETERS_PATH) + parser.add_argument( + '--protocol', + help=('Path to BciPy Protocol. Must contain one or more calibration session directories. ' + 'If none provided, a window will prompt for one.'), + default=None) + args = parser.parse_args() + parameters = load_json_parameters(args.parameters, value_cast=True) + """ + **Note:** + Save path is not used in this action, the protocol path is most important and where + the report will be saved. In other tasks, the save path is used to save the output of the tasks + (raw data, model, etc.). Whereas in this case, the report is saved in the protocol path because it reads + several of the underlying files in the protocol. In other words, it is a top level report. + + The protocol path is the path to the directory containing the calibration sessions. + """ + action = BciPyCalibrationReportAction(parameters=parameters, save_path='.', protocol_path=args.protocol) + print('Generating Report.') + task_data = action.execute() diff --git a/bcipy/task/demo/demo_orchestrator.py b/bcipy/task/demo/orchestrator/demo_orchestrator.py similarity index 100% rename from bcipy/task/demo/demo_orchestrator.py rename to bcipy/task/demo/orchestrator/demo_orchestrator.py diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index 79748e7b7..03c3f8368 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -66,6 +66,7 @@ class MatrixCopyPhraseTask(RSVPCopyPhraseTask): "preview_inquiry_error_prob", "preview_inquiry_length", "preview_inquiry_progress_method", + "preview_box_text_size", "spelled_letters_count", "stim_color", "matrix_stim_height", diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index b381349f6..cd8fa0b25 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -6,7 +6,6 @@ from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters -from bcipy.helpers.triggers import TriggerType from bcipy.task.calibration import BaseCalibrationTask @@ -32,18 +31,6 @@ class RSVPCalibrationTask(BaseCalibrationTask): name = 'RSVP Calibration' paradigm = 'RSVP' - def trigger_type(self, symbol: str, target: str, - index: int) -> TriggerType: - if index == 0: - return TriggerType.PROMPT - if symbol == 'inquiry_preview': - return TriggerType.PREVIEW - if symbol == '+': - return TriggerType.FIXATION - if target == symbol: - return TriggerType.TARGET - return TriggerType.NONTARGET - def init_display(self) -> Display: return init_calibration_display_task(self.parameters, self.window, self.static_clock, diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 1a7be6384..b473f2f09 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -101,8 +101,9 @@ class RSVPCopyPhraseTask(Task): 'decision_threshold', 'max_inq_len', 'max_inq_per_series', 'max_minutes', 'max_selections', 'max_incorrect', 'min_inq_len', 'show_feedback', 'feedback_duration', - 'show_preview_inquiry', 'preview_inquiry_isi', 'preview_inquiry_error_prob', - 'preview_inquiry_key_input', 'preview_inquiry_length', 'preview_inquiry_progress_method', + 'show_preview_inquiry', 'preview_inquiry_isi', + 'preview_inquiry_error_prob', 'preview_inquiry_key_input', 'preview_inquiry_length', + 'preview_inquiry_progress_method', 'preview_box_text_size', 'spelled_letters_count', 'stim_color', 'rsvp_stim_height', 'stim_jitter', 'stim_length', 'stim_number', 'stim_order', 'rsvp_stim_pos_x', 'rsvp_stim_pos_y', 'stim_space_char', 'target_color', @@ -895,7 +896,7 @@ def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: """ if symbol == "inquiry_preview": return TriggerType.PREVIEW - if "bcipy_key_press" in symbol: + if "key_press" in symbol: return TriggerType.EVENT if symbol == "+": return TriggerType.FIXATION diff --git a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py index d6ae98e4b..1e4c9b073 100644 --- a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py +++ b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py @@ -44,6 +44,7 @@ def setUp(self): 'prestim_length': 1, 'preview_inquiry_isi': 1.0, 'preview_inquiry_length': 5.0, + 'preview_box_text_size': 0.1, 'show_feedback': False, 'show_preview_inquiry': False, 'stim_color': 'white', diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 59706bfc1..2bad0ef4b 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -56,6 +56,7 @@ def setUp(self): 'preview_inquiry_key_input': 'space', 'preview_inquiry_length': 5.0, 'preview_inquiry_progress_method': 1, + 'preview_box_text_size': 0.1, 'show_feedback': False, 'show_preview_inquiry': False, 'spelled_letters_count': 0, diff --git a/requirements.txt b/requirements.txt index f4a764fdd..b6c87fecc 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,7 +2,7 @@ attrdict3==2.0.2 transformers==4.26.0 torch==2.0.0 construct==2.8.14 -mne==1.5.0 +mne==1.6.1 pyo==1.0.5 pyglet<=1.5.27,>=1.4 PsychoPy==2024.2.1 diff --git a/scripts/shell/m2chip_install.sh b/scripts/shell/m2chip_install.sh index 3fe41ee8c..6b8977099 100644 --- a/scripts/shell/m2chip_install.sh +++ b/scripts/shell/m2chip_install.sh @@ -27,6 +27,6 @@ export HDF5_DIR=/opt/homebrew/opt/hdf5 python -m pip install pyaudio # your path may be different to the portaudio version pip install --global-option='build_ext' --global-option='-I/usr/local/Cellar/portaudio/19.7.0/include' --global-option='-L/usr/local/Cellar/portaudio/19.7.0/lib' pyo -pip install Psychopy==2023.2.1 --no-deps # install psychopy without dependencies +pip install Psychopy==2024.2.1 --no-deps # install psychopy without dependencies pip install -e . pip install kenlm==0.1 --global-option="--max_order=12" # install kenlm with max_order=12 for language model. Not required for BciPy to run in most places. \ No newline at end of file diff --git a/setup.py b/setup.py index 76a95b252..4d4571e52 100644 --- a/setup.py +++ b/setup.py @@ -29,7 +29,7 @@ URL = 'https://github.com/CAMBI-tech/BciPy' EMAIL = 'cambi_support@googlegroups.com' AUTHOR = 'CAMBI' -REQUIRES_PYTHON = '>3.7,<3.10' +REQUIRES_PYTHON = '>3.7,<3.11' VERSION = '2.0.0rc4' @@ -110,7 +110,7 @@ def run(self): [ 'bcipy = bcipy.main:bcipy_main', 'bcipy-erp-viz = bcipy.helpers.visualization:erp', - 'bcipy-sim = bcipy.simulator', + 'bcipy-sim = bcipy.simulator:main', "bcipy-train = bcipy.signal.model.offline_analysis:main"], }, install_requires=REQUIRED, From be07e59957de181ee50f4908e825c827999efc66 Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Wed, 30 Oct 2024 13:23:30 -0700 Subject: [PATCH 326/330] Simulator fix and orchestrator saving updates (#358) --- CHANGELOG.md | 51 ++++++++-- bcipy/config.py | 4 +- bcipy/display/__init__.py | 2 - bcipy/display/main.py | 31 ------- .../components/test_button_press_handler.py | 4 + bcipy/helpers/convert.py | 4 +- bcipy/helpers/demo/demo_report.py | 4 +- bcipy/helpers/demo/demo_visualization.py | 4 +- bcipy/helpers/offset.py | 4 +- bcipy/helpers/save.py | 4 +- bcipy/helpers/session.py | 4 +- bcipy/helpers/tests/test_convert.py | 4 +- bcipy/helpers/tests/test_save.py | 4 +- bcipy/signal/evaluate/artifact.py | 4 +- .../tests/model/test_offline_analysis.py | 4 +- bcipy/simulator/data/data_process.py | 4 +- bcipy/simulator/task/copy_phrase.py | 52 ++++++++--- bcipy/task/README.md | 27 +++--- bcipy/task/calibration.py | 13 ++- bcipy/task/orchestrator/orchestrator.py | 9 +- bcipy/task/paradigm/matrix/copy_phrase.py | 70 +++++++------- bcipy/task/paradigm/rsvp/copy_phrase.py | 92 ++++++++++++------- scripts/python/replay_session.py | 4 +- 23 files changed, 235 insertions(+), 168 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 49e2db25f..b192ebe43 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -7,36 +7,68 @@ Our final release candidate before the official 2.0 release! - Multimodal Acquisition and Querying - Support for multiple devices in online querying #286 - Support for trigger handling relative to a given device #293 -- Session Orchestrator - - New task protocol for orchestrating tasks in a session. This refactors several Task and Cli functionality #339 + - Support multiple device static offests #331 + - Support for Device Status (passive or active) #310 +- Session Orchestrator #339 + - New task protocol for orchestrating tasks in a session. This refactors several Task and Cli functionality #339, #343 + - Parameter guardrails #340 + - Allow multiple phrases in a single protocol to be defined in a phrase.json and randomized #352 +- BciPy Client Additions #346 + - Other commands added for offline analysis, visualization and simulation. +- Artifact Module #336 +- Simulator #350 +- Task + - Calibration Task Refactor: pulls out common elements from RSVP and Matrix calibration tasks #330 + - Registry Refactor #332 + - Inquiry Preview + - Surface button error probability #347 + - Add to Matrix #353 + - Bugfixes/Refactor #348 + - Add more stoppage criteria #351 (max_incorrect) + - Matrix + - Layout Support #349 + - Grid always on #313 + - Output stimuli position, screen capture and monitor information after Matrix tasks #303 + - Row/Column spacing support #298 + - VEP Calibration #304/#296 + - session data to VEP calibration #322 - Model - Offline analysis to support multimodal fusion. Initial release of GazeModel, GazeReshaper, and Gaze Visualization #294 +- Language Model + - Add Oracle model #316 + - Random Uniform model #311 - Stimuli - - Updates to ensure stimuli are presented at the same frequency #287 Output stimuli position, screen capture and monitor information after Matrix tasks #303 + - Updates to ensure stimuli are presented at the same frequency #287 - Dynamic Selection Window - Updated trial_length to trial_window to allow for greater control of window used after stimulus presentations #291 - Report - Functionality to generate a report in the form of a PDF #325 + - Add a BciPy Calbiraiton Report Action #357 - Offset Support - - Add support for determining offsets between timing verification Tasks (Ex. RSVPTimingVerificationCalibration) and RawData with a photodiode trigger column. This is useful for setting up new systems and preventing errors before an experiment begins. #TODO + - Add support for determining offsets between timing verification Tasks (Ex. RSVPTimingVerificationCalibration) and RawData with a photodiode trigger column. This is useful for setting up new systems and preventing errors before an experiment begins. #327 - Parameters - Add a Range type parameter #285 Add editable fields #340 Update parameters.json to seperate relevant parameters by task - Housekeeping - Add mypy typing to the codebase #301 - Change default log level to INFO to prevent too many messages in the experiment logs #288 - Upgrade requirements for m1/2 chips #299/#300 - - Fix GitHub actions build issues with macOS - - Fix occasionally failing test in `test_stimuli` #326 -- GUI Refactor + - Fix GitHub actions build issues with macOS #324 + - Tests Improvements + - Fix occasionally failing test in `test_stimuli` #326 + - Reshaper tests #302 + - Fix parameter save as #323 + - Pause error #321 + - Fix data buffer issue #308 +- GUI Refactor #337 - Create new `BCIUI` class for simpler more straightforward UI creation. - Create dedicated external stylesheet for global styling - Rewrite Experiment Registry to use new GUI code - Create intertask action UI -- Task Return Object +- Task Return Object #334 - Create `TaskData` dataclass to be returned from tasks - updates task `execute` methods to return an instance of `TaskData` - Allows for optional storage of a save path and task dictionary in `TaskData` --Experiment Refactor +-Experiment Refactor #333 #329 - Refactors the Experiment Field Collection GUI to be an action - Allows task protocol to be defined in the orchestrator @@ -77,7 +109,6 @@ Our final release candidate before the official 2.0 release! - added KenLM model `kenlm.py` #268 - added mixture model `mixture.py` and script to tune weights `mixture_tuning.py` #268 - added script to evaluate language model performance `lm_eval.py` #268 - - added Oracle model #316 - Signal Model - added `RdaKdeModel` and restructured to pull out common elements from the PcaRdaKdeModel #279 - Bug Fixes diff --git a/bcipy/config.py b/bcipy/config.py index 0bbc4b562..9325e2447 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -27,9 +27,9 @@ DEFAULT_USER_ID = 'test_user' TASK_SEPERATOR = '->' -DEFAULT_PARAMETER_FILENAME = 'parameters.json' +DEFAULT_PARAMETERS_FILENAME = 'parameters.json' DEFAULT_DEVICES_PATH = f"{BCIPY_ROOT}/parameters" -DEFAULT_PARAMETERS_PATH = f'{BCIPY_ROOT}/parameters/{DEFAULT_PARAMETER_FILENAME}' +DEFAULT_PARAMETERS_PATH = f'{BCIPY_ROOT}/parameters/{DEFAULT_PARAMETERS_FILENAME}' DEFAULT_DEVICE_SPEC_FILENAME = 'devices.json' DEVICE_SPEC_PATH = f'{BCIPY_ROOT}/parameters/{DEFAULT_DEVICE_SPEC_FILENAME}' DEFAULT_LM_PARAMETERS_FILENAME = 'lm_params.json' diff --git a/bcipy/display/__init__.py b/bcipy/display/__init__.py index 960a818bc..58bbf82eb 100644 --- a/bcipy/display/__init__.py +++ b/bcipy/display/__init__.py @@ -8,7 +8,6 @@ Display, InformationProperties, init_display_window, - PreviewInquiryProperties, StimuliProperties, VEPStimuliProperties ) @@ -20,5 +19,4 @@ 'StimuliProperties', 'VEPStimuliProperties', 'InformationProperties', - 'PreviewInquiryProperties' ] diff --git a/bcipy/display/main.py b/bcipy/display/main.py index 019abae64..bb8edd33f 100644 --- a/bcipy/display/main.py +++ b/bcipy/display/main.py @@ -251,37 +251,6 @@ class ButtonPressMode(Enum): REJECT = 2 -class PreviewInquiryProperties: - """"Preview Inquiry Properties. - An encapsulation of properties relevant to preview_inquiry() operation. - """ - - def __init__( - self, - preview_on: bool, - preview_only: bool, - preview_inquiry_length: float, - preview_inquiry_progress_method: int, - preview_inquiry_key_input: str, - preview_inquiry_isi: float): - """Initialize Inquiry Preview Parameters. - - preview_on(bool): If True, display an inquiry preview before the main inquiry. - preview_only(bool): If True, only preview the inquiry and do not probe for response - preview_inquiry_length(float): Length of time in seconds to present the inquiry preview - preview_inquiry_progress_method(int): Method of progression for inquiry preview. - 0 == preview only; 1 == press to accept inquiry; 2 == press to skip inquiry. - preview_inquiry_key_input(str): Defines which key should be listened to for progressing - preview_inquiry_isi(float): Length of time after displaying the inquiry preview to display a blank screen - """ - self.preview_on = preview_on - self.preview_inquiry_length = preview_inquiry_length - self.preview_inquiry_key_input = preview_inquiry_key_input - self.press_to_accept = True if preview_inquiry_progress_method == 1 else False - self.preview_only = preview_only - self.preview_inquiry_isi = preview_inquiry_isi - - class PreviewParams(NamedTuple): """Parameters relevant for the Inquiry Preview functionality. diff --git a/bcipy/display/tests/components/test_button_press_handler.py b/bcipy/display/tests/components/test_button_press_handler.py index 4de0bb832..bf131e52a 100644 --- a/bcipy/display/tests/components/test_button_press_handler.py +++ b/bcipy/display/tests/components/test_button_press_handler.py @@ -189,3 +189,7 @@ def test_press_to_reject_with_keypress(self, get_key_press_mock): self.assertTrue(handler.has_response()) self.assertEqual('bcipy_key_press_space', handler.response_label) self.assertEqual(1.5, handler.response_timestamp) + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/helpers/convert.py b/bcipy/helpers/convert.py index 3550c7ff8..4367dc8cd 100644 --- a/bcipy/helpers/convert.py +++ b/bcipy/helpers/convert.py @@ -13,7 +13,7 @@ from tqdm import tqdm from bcipy.acquisition.devices import preconfigured_device -from bcipy.config import (DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, +from bcipy.config import (DEFAULT_PARAMETERS_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME, SESSION_LOG_FILENAME) from bcipy.helpers.load import load_json_parameters, load_raw_data from bcipy.helpers.raw_data import RawData @@ -174,7 +174,7 @@ def pyedf_convert(data_dir: str, otherwise a string of the filter parameters used to filter the data """ - params = load_json_parameters(str(Path(data_dir, DEFAULT_PARAMETER_FILENAME)), + params = load_json_parameters(str(Path(data_dir, DEFAULT_PARAMETERS_FILENAME)), value_cast=True) data = load_raw_data(str(Path(data_dir, f'{RAW_DATA_FILENAME}.csv'))) fs = data.sample_rate diff --git a/bcipy/helpers/demo/demo_report.py b/bcipy/helpers/demo/demo_report.py index 0936d214d..1ee4ff363 100644 --- a/bcipy/helpers/demo/demo_report.py +++ b/bcipy/helpers/demo/demo_report.py @@ -3,7 +3,7 @@ from bcipy.helpers.triggers import trigger_decoder, TriggerType from bcipy.config import ( BCIPY_ROOT, - DEFAULT_PARAMETER_FILENAME, + DEFAULT_PARAMETERS_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME) @@ -44,7 +44,7 @@ if prompt != 'skip': # load the parameters from the data directory parameters = load_json_parameters( - f'{session}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) + f'{session}/{DEFAULT_PARAMETERS_FILENAME}', value_cast=True) # load the raw data from the data directory raw_data = load_raw_data(Path(session, f'{RAW_DATA_FILENAME}.csv')) diff --git a/bcipy/helpers/demo/demo_visualization.py b/bcipy/helpers/demo/demo_visualization.py index 8c08701b9..3ccd8fdf4 100644 --- a/bcipy/helpers/demo/demo_visualization.py +++ b/bcipy/helpers/demo/demo_visualization.py @@ -15,7 +15,7 @@ """ import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, - DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, + DEFAULT_PARAMETERS_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.load import (load_experimental_data, load_json_parameters, @@ -44,7 +44,7 @@ if not path: path = load_experimental_data() - parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETER_FILENAME}', + parameters = load_json_parameters(f'{path}/{DEFAULT_PARAMETERS_FILENAME}', value_cast=True) # extract all relevant parameters diff --git a/bcipy/helpers/offset.py b/bcipy/helpers/offset.py index c84d34720..0858aadc3 100644 --- a/bcipy/helpers/offset.py +++ b/bcipy/helpers/offset.py @@ -16,7 +16,7 @@ DIODE_TRIGGER, RAW_DATA_FILENAME, DEFAULT_TRIGGER_CHANNEL_NAME, - DEFAULT_PARAMETER_FILENAME + DEFAULT_PARAMETERS_FILENAME ) @@ -343,7 +343,7 @@ def extract_data_latency_calculation( data_path = ask_directory() # grab the stim length from the data directory parameters - stim_length = load_json_parameters(f'{data_path}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True)['stim_length'] + stim_length = load_json_parameters(f'{data_path}/{DEFAULT_PARAMETERS_FILENAME}', value_cast=True)['stim_length'] raw_data, triggers, static_offset = extract_data_latency_calculation( data_path, diff --git a/bcipy/helpers/save.py b/bcipy/helpers/save.py index 8d0f197e9..98a232645 100644 --- a/bcipy/helpers/save.py +++ b/bcipy/helpers/save.py @@ -13,7 +13,7 @@ DEFAULT_EXPERIMENT_ID, DEFAULT_LM_PARAMETERS_FILENAME, DEFAULT_LM_PARAMETERS_PATH, - DEFAULT_PARAMETER_FILENAME, + DEFAULT_PARAMETERS_FILENAME, SIGNAL_MODEL_FILE_SUFFIX, STIMULI_POSITIONS_FILENAME) from bcipy.signal.model.base_model import SignalModel @@ -95,7 +95,7 @@ def init_save_data_structure(data_save_path: str, os.makedirs(save_directory) os.makedirs(os.path.join(save_directory, 'logs'), exist_ok=True) - copyfile(parameters, Path(save_directory, DEFAULT_PARAMETER_FILENAME)) + copyfile(parameters, Path(save_directory, DEFAULT_PARAMETERS_FILENAME)) copyfile(DEFAULT_LM_PARAMETERS_PATH, Path(save_directory, DEFAULT_LM_PARAMETERS_FILENAME)) diff --git a/bcipy/helpers/session.py b/bcipy/helpers/session.py index 1e747f0ad..d447d17f6 100644 --- a/bcipy/helpers/session.py +++ b/bcipy/helpers/session.py @@ -17,7 +17,7 @@ WHITE = COLOR_INDEX[1] YELLOW = COLOR_INDEX[5] from bcipy.config import (BCIPY_ROOT, DEFAULT_ENCODING, - DEFAULT_PARAMETER_FILENAME, EXPERIMENT_DATA_FILENAME, + DEFAULT_PARAMETERS_FILENAME, EXPERIMENT_DATA_FILENAME, SESSION_DATA_FILENAME, SESSION_SUMMARY_FILENAME) from bcipy.helpers.load import (load_experiment_fields, load_experiments, load_json_parameters) @@ -37,7 +37,7 @@ def session_data(data_dir: str) -> Dict: not useful for debugging.""" parameters = load_json_parameters(os.path.join(data_dir, - DEFAULT_PARAMETER_FILENAME), + DEFAULT_PARAMETERS_FILENAME), value_cast=True) session = read_session(os.path.join(data_dir, SESSION_DATA_FILENAME)) data = session.as_dict(evidence_only=True) diff --git a/bcipy/helpers/tests/test_convert.py b/bcipy/helpers/tests/test_convert.py index 2b402c88d..28aade773 100644 --- a/bcipy/helpers/tests/test_convert.py +++ b/bcipy/helpers/tests/test_convert.py @@ -12,7 +12,7 @@ from mockito import mock, unstub, verify, verifyNoMoreInteractions, when import bcipy.acquisition.devices as devices -from bcipy.config import (DEFAULT_ENCODING, DEFAULT_PARAMETER_FILENAME, +from bcipy.config import (DEFAULT_ENCODING, DEFAULT_PARAMETERS_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME) from bcipy.helpers import convert from bcipy.helpers.convert import (archive_list, compress, convert_to_bdf, @@ -64,7 +64,7 @@ def create_bcipy_session_artifacts( filter_high=filter_settings['filter_high'], filter_low=filter_settings['filter_low'], filter_order=filter_settings['filter_order']) - params.save(write_dir, DEFAULT_PARAMETER_FILENAME) + params.save(write_dir, DEFAULT_PARAMETERS_FILENAME) return trg_data, data, params diff --git a/bcipy/helpers/tests/test_save.py b/bcipy/helpers/tests/test_save.py index a54aedd76..ba46b4a25 100644 --- a/bcipy/helpers/tests/test_save.py +++ b/bcipy/helpers/tests/test_save.py @@ -6,7 +6,7 @@ from bcipy.config import ( DEFAULT_PARAMETERS_PATH, - DEFAULT_PARAMETER_FILENAME, + DEFAULT_PARAMETERS_FILENAME, DEFAULT_EXPERIMENT_ID, STIMULI_POSITIONS_FILENAME) from bcipy.helpers import save @@ -50,7 +50,7 @@ def test_init_save_data_structure_creates_correct_save_folder(self): def test_parameter_file_copies(self): # construct the path of the parameters - param_path = self.save_folder_name + f'/{DEFAULT_PARAMETER_FILENAME}' + param_path = self.save_folder_name + f'/{DEFAULT_PARAMETERS_FILENAME}' # assert that the params file was created in the correct location self.assertTrue(os.path.isfile(param_path)) diff --git a/bcipy/signal/evaluate/artifact.py b/bcipy/signal/evaluate/artifact.py index f40bcf134..f4bc7bde0 100644 --- a/bcipy/signal/evaluate/artifact.py +++ b/bcipy/signal/evaluate/artifact.py @@ -7,7 +7,7 @@ import logging from bcipy.config import ( - DEFAULT_PARAMETER_FILENAME, + DEFAULT_PARAMETERS_FILENAME, RAW_DATA_FILENAME, TRIGGER_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME, @@ -577,7 +577,7 @@ def write_mne_annotations( if prompt != 'skip': # load the parameters from the data directory parameters = load_json_parameters( - f'{session}/{DEFAULT_PARAMETER_FILENAME}', value_cast=True) + f'{session}/{DEFAULT_PARAMETERS_FILENAME}', value_cast=True) # load the raw data from the data directory raw_data = load_raw_data(str(Path(session, f'{RAW_DATA_FILENAME}.csv'))) diff --git a/bcipy/signal/tests/model/test_offline_analysis.py b/bcipy/signal/tests/model/test_offline_analysis.py index 54f84d8e3..53563898e 100644 --- a/bcipy/signal/tests/model/test_offline_analysis.py +++ b/bcipy/signal/tests/model/test_offline_analysis.py @@ -9,7 +9,7 @@ import random import gzip -from bcipy.config import RAW_DATA_FILENAME, DEFAULT_PARAMETER_FILENAME, TRIGGER_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME +from bcipy.config import RAW_DATA_FILENAME, DEFAULT_PARAMETERS_FILENAME, TRIGGER_FILENAME, DEFAULT_DEVICE_SPEC_FILENAME from bcipy.helpers.load import load_json_parameters from bcipy.signal.model.offline_analysis import offline_analysis @@ -48,7 +48,7 @@ def setUpClass(cls): shutil.copyfile(input_folder / TRIGGER_FILENAME, cls.tmp_dir / TRIGGER_FILENAME) shutil.copyfile(input_folder / DEFAULT_DEVICE_SPEC_FILENAME, cls.tmp_dir / DEFAULT_DEVICE_SPEC_FILENAME) - params_path = pwd.parent.parent.parent / "parameters" / DEFAULT_PARAMETER_FILENAME + params_path = pwd.parent.parent.parent / "parameters" / DEFAULT_PARAMETERS_FILENAME cls.parameters = load_json_parameters(params_path, value_cast=True) models = offline_analysis( str(cls.tmp_dir), diff --git a/bcipy/simulator/data/data_process.py b/bcipy/simulator/data/data_process.py index c56153a60..d56445cc8 100644 --- a/bcipy/simulator/data/data_process.py +++ b/bcipy/simulator/data/data_process.py @@ -14,7 +14,7 @@ from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.multimodal import ContentType from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, - DEFAULT_PARAMETER_FILENAME, TRIGGER_FILENAME) + DEFAULT_PARAMETERS_FILENAME, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename from bcipy.helpers.list import grouper from bcipy.helpers.load import load_json_parameters, load_raw_data @@ -270,7 +270,7 @@ def process(self, data_folder: str, raw_data, device_spec = load_device_data(data_folder, self.content_type.name) data_parameters = load_json_parameters( - f"{data_folder}/{DEFAULT_PARAMETER_FILENAME}", value_cast=True) + f"{data_folder}/{DEFAULT_PARAMETERS_FILENAME}", value_cast=True) timing_params = parameters.instantiate(TimingParams) diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index 119f129a5..b672c7077 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -1,6 +1,6 @@ # mypy: disable-error-code="union-attr" """Simulates the Copy Phrase task""" -from typing import Dict, List, Optional, Tuple +from typing import Any, Dict, List, Optional, Tuple import logging from bcipy.display.main import Display @@ -21,8 +21,20 @@ def get_evidence_type(model: SignalModel) -> EvidenceType: - """Get the evidence type provided by the given model""" - return model.metadata.evidence_type or DEFAULT_EVIDENCE_TYPE + """Get the evidence type provided by the given model and return it as an enum (EvidenceType). + + If the model does not provide an evidence type, the default evidence type is returned (ERP). + """ + evidence_type = model.metadata.evidence_type + + # Note: once more than one evidence type is supported, this should be updated to throw an error + if not evidence_type: + return DEFAULT_EVIDENCE_TYPE + + try: + return EvidenceType(evidence_type) + except ValueError: + raise ValueError(f"Unsupported evidence type: {evidence_type}. Supported types: {EvidenceType.list()}") class SimulatorCopyPhraseTask(RSVPCopyPhraseTask): @@ -37,16 +49,34 @@ def __init__(self, parameters: Parameters, file_save: str, signal_models: List[SignalModel], language_model: LanguageModel, samplers: Dict[SignalModel, Sampler]): - super().__init__(win=None, - daq=None, - parameters=parameters, - file_save=file_save, - signal_models=signal_models, - language_model=language_model, - fake=False) + self.args_sm = signal_models + self.args_lm = language_model self.save_session_every_inquiry = False self.samplers = samplers self.logger = logging.getLogger(__name__) + super().__init__(parameters=parameters, + file_save=file_save, + fake=False) + + def setup( + self, + parameters: Parameters, + data_save_location: str, + fake: bool = False) -> Tuple[Any, Any, Display]: + """Override the setup method to avoid initializing the data acquisition.""" + daq = None + server = None + display = self.init_display() + self.initalized = True + return daq, server, display + + def get_signal_models(self): + """Override the get the signal models""" + return self.args_sm + + def get_language_model(self): + """Override the get the language model""" + return self.args_lm def init_evidence_evaluators( self, signal_models: List[SignalModel]) -> List[EvidenceEvaluator]: @@ -105,7 +135,7 @@ def compute_device_evidence( sampled_data = sampler.sample_data(current_state) evidence = model.predict(sampled_data, self.current_symbols(), self.alp) - evidence_type = model.metadata.evidence_type or EvidenceType.ERP + evidence_type = get_evidence_type(model) evidences.append((evidence_type, evidence)) return evidences diff --git a/bcipy/task/README.md b/bcipy/task/README.md index 2efd0fa5b..e0394c26e 100644 --- a/bcipy/task/README.md +++ b/bcipy/task/README.md @@ -97,19 +97,20 @@ The data will be saved in the following format in the specified data_save_loc (d data_save_loc/ user_id/ - experiment_id/ - run_id / - task_id/ - logs/ - task_log_data - task_data (e.g. acquisition data, parameters, visualizations) - task_id/ - logs/ - task_log_data - task_data (e.g. acquisition data, parameters, visualizations) - logs/ - protocol_log_data - protocol_data (system data, protocol/tasks executed) + date/ + experiment_id/ + run_id / + task_id/ + logs/ + task_log_data + task_data (e.g. acquisition data, parameters, visualizations) + task_id/ + logs/ + task_log_data + task_data (e.g. acquisition data, parameters, visualizations) + logs/ + protocol_log_data + protocol_data (system data, protocol/tasks executed) ``` ### Usage manually diff --git a/bcipy/task/calibration.py b/bcipy/task/calibration.py index 3f39ff2e9..c80496480 100644 --- a/bcipy/task/calibration.py +++ b/bcipy/task/calibration.py @@ -121,7 +121,11 @@ def symbol_set(self) -> List[str]: """Symbols used in the calibration""" return self._symbol_set - def setup(self, parameters, data_save_location, fake=False) -> Tuple[ClientManager, List[LslDataServer], Window]: + def setup( + self, + parameters: Parameters, + data_save_location: str, + fake: bool = False) -> Tuple[ClientManager, List[LslDataServer], Window]: # Initialize Acquisition daq, servers = init_acquisition( parameters, data_save_location, server=fake) @@ -212,7 +216,9 @@ def session_task_data(self) -> Optional[Dict[str, Any]]: """"Task-specific session data""" return None - def trigger_type(self, symbol: str, target: str, + def trigger_type(self, + symbol: str, + target: str, index: int) -> TriggerType: """Trigger Type. @@ -232,7 +238,8 @@ def trigger_type(self, symbol: str, target: str, return TriggerType.EVENT return TriggerType.NONTARGET - def present_inquiry(self, index: int, + def present_inquiry(self, + index: int, inquiry: Inquiry) -> List[Tuple[str, float]]: """Present the given inquiry and return the trigger timing info. diff --git a/bcipy/task/orchestrator/orchestrator.py b/bcipy/task/orchestrator/orchestrator.py index b3b493242..1f07fb82a 100644 --- a/bcipy/task/orchestrator/orchestrator.py +++ b/bcipy/task/orchestrator/orchestrator.py @@ -15,6 +15,7 @@ from bcipy.task import Task, TaskData, TaskMode from bcipy.config import ( DEFAULT_EXPERIMENT_ID, + DEFAULT_PARAMETERS_FILENAME, DEFAULT_PARAMETERS_PATH, DEFAULT_USER_ID, MULTIPHRASE_FILENAME, @@ -219,10 +220,12 @@ def _init_orchestrator_logger(self, save_folder: str) -> Logger: logging.DEBUG) def _init_orchestrator_save_folder(self, save_path: str) -> str: - timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") + date_time = datetime.now() + date = date_time.strftime("%Y-%m-%d") + timestamp = date_time.strftime("%Y-%m-%d_%H-%M-%S") # * No '/' after `save_folder` since it is included in # * `data_save_location` in parameters - path = f'{save_path}{self.user}/{self.experiment_id}/{timestamp}/' + path = f'{save_path}{self.user}/{date}/{self.experiment_id}/{timestamp}/' os.makedirs(path) os.makedirs(os.path.join(path, 'logs'), exist_ok=True) return path @@ -247,7 +250,7 @@ def _init_task_save_folder(self, task: Type[Task]) -> str: "type": "str", } ) - self.parameters.save(save_directory) + self.parameters.save(save_directory, name=DEFAULT_PARAMETERS_FILENAME) except OSError as error: # If the error is anything other than file existing, raise an error diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index 03c3f8368..56f89d8bc 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -35,41 +35,52 @@ class MatrixCopyPhraseTask(RSVPCopyPhraseTask): mode = TaskMode.COPYPHRASE PARAMETERS_USED = [ - "time_fixation", - "time_flash", - "time_prompt", - "trial_window", - "font", - "fixation_color", - "trigger_type", + "backspace_always_shown", + "decision_threshold", + "down_sampling_rate", + "feedback_duration", "filter_high", "filter_low", "filter_order", - "notch_filter_frequency", - "down_sampling_rate", - "prestim_length", + "fixation_color", + "font", + "info_color", + "info_color", + "info_height", + "info_height", + "info_pos_x", + "info_pos_y", + "info_text", + "info_text", "is_txt_stim", "lm_backspace_prob", - "backspace_always_shown", - "decision_threshold", + "matrix_columns", + "matrix_keyboard_layout", + "matrix_rows", + "matrix_stim_height", + "matrix_stim_pos_x", + "matrix_stim_pos_y", + "matrix_task_height", + "matrix_task_padding", + "matrix_width", + "max_incorrect", "max_inq_len", "max_inq_per_series", "max_minutes", "max_selections", - "max_incorrect", "min_inq_len", - "show_feedback", - "feedback_duration", - "show_preview_inquiry", + "notch_filter_frequency", + "prestim_length", + "preview_box_text_size", + "preview_inquiry_error_prob", "preview_inquiry_isi", "preview_inquiry_key_input", - "preview_inquiry_error_prob", "preview_inquiry_length", "preview_inquiry_progress_method", - "preview_box_text_size", + "show_feedback", + "show_preview_inquiry", "spelled_letters_count", "stim_color", - "matrix_stim_height", "stim_jitter", "stim_length", "stim_number", @@ -80,23 +91,12 @@ class MatrixCopyPhraseTask(RSVPCopyPhraseTask): "target_color", "task_buffer_length", "task_color", - "matrix_task_height", - "matrix_task_padding", - "matrix_keyboard_layout", - "matrix_rows", - "matrix_columns", - "matrix_width", - "matrix_stim_pos_x", - "matrix_stim_pos_y", "task_text", - "info_pos_x", - "info_pos_y", - "info_color", - "info_height", - "info_text", - "info_color", - "info_height", - "info_text", + "time_fixation", + "time_flash", + "time_prompt", + "trial_window", + "trigger_type", ] def init_display(self) -> MatrixDisplay: diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index b473f2f09..1800c207d 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -94,21 +94,60 @@ class RSVPCopyPhraseTask(Task): initalized = False PARAMETERS_USED = [ - 'time_fixation', 'time_flash', 'time_prompt', 'trial_window', - 'font', 'fixation_color', 'trigger_type', - 'filter_high', 'filter_low', 'filter_order', 'notch_filter_frequency', 'down_sampling_rate', 'prestim_length', - 'is_txt_stim', 'lm_backspace_prob', 'backspace_always_shown', - 'decision_threshold', 'max_inq_len', 'max_inq_per_series', 'max_minutes', 'max_selections', 'max_incorrect', + 'backspace_always_shown', + 'decision_threshold', + 'down_sampling_rate', + 'feedback_duration', + 'filter_high', + 'filter_low', + 'filter_order', + 'fixation_color', + 'font', + 'info_color', + 'info_color', + 'info_height', + 'info_height', + 'info_pos_x', 'info_pos_y', + 'info_text', + 'info_text', + 'is_txt_stim', + 'lm_backspace_prob', + 'max_incorrect', + 'max_inq_len', + 'max_inq_per_series', + 'max_minutes', + 'max_selections', 'min_inq_len', - 'show_feedback', 'feedback_duration', - 'show_preview_inquiry', 'preview_inquiry_isi', - 'preview_inquiry_error_prob', 'preview_inquiry_key_input', 'preview_inquiry_length', - 'preview_inquiry_progress_method', 'preview_box_text_size', + 'notch_filter_frequency', + 'prestim_length', + 'preview_box_text_size', + 'preview_inquiry_error_prob', + 'preview_inquiry_isi', + 'preview_inquiry_key_input', + 'preview_inquiry_length', + 'preview_inquiry_progress_method', + 'rsvp_stim_height', + 'rsvp_stim_pos_x', 'rsvp_stim_pos_y', + 'rsvp_task_height', + 'rsvp_task_padding', + 'show_feedback', + 'show_preview_inquiry', 'spelled_letters_count', - 'stim_color', 'rsvp_stim_height', 'stim_jitter', 'stim_length', 'stim_number', - 'stim_order', 'rsvp_stim_pos_x', 'rsvp_stim_pos_y', 'stim_space_char', 'target_color', - 'task_buffer_length', 'task_color', 'rsvp_task_height', 'task_text', 'rsvp_task_padding', - 'info_pos_x', 'info_pos_y', 'info_color', 'info_height', 'info_text', 'info_color', 'info_height', 'info_text', + 'stim_color', + 'stim_jitter', + 'stim_length', + 'stim_number', + 'stim_order', + 'stim_space_char', + 'target_color', + 'task_buffer_length', + 'task_color', + 'task_text', + 'time_fixation', + 'time_flash', + 'time_prompt', + 'trial_window', + 'trigger_type', ] def __init__( @@ -155,27 +194,13 @@ def __init__( self.set() - # set a preview_only parameter - self.parameters.add_entry( - "preview_only", - { - "value": ( - "true" - if self.parameters["preview_inquiry_progress_method"] == 0 - else "false" - ), - "section": "", - "name": "", - "helpTip": "", - "recommended": "", - "editable": "false", - "type": "bool", - }, - ) - self.rsvp = self.init_display() - def setup(self, parameters, data_save_location, fake=False) -> Tuple[ClientManager, List[LslDataServer], Window]: + def setup( + self, + parameters: Parameters, + data_save_location: str, + fake: bool = False) -> Tuple[ClientManager, List[LslDataServer], Window]: # Initialize Acquisition daq, servers = init_acquisition( parameters, data_save_location, server=fake) @@ -662,8 +687,7 @@ def compute_button_press_evidence( """ if ( not self.parameters["show_preview_inquiry"] or - not self.current_inquiry or - self.parameters["preview_only"] + not self.current_inquiry ): return None probs = compute_probs_after_preview( diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 239bc8a00..421d96a37 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -12,7 +12,7 @@ import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, - DEFAULT_PARAMETER_FILENAME, RAW_DATA_FILENAME, + DEFAULT_PARAMETERS_FILENAME, RAW_DATA_FILENAME, SESSION_DATA_FILENAME, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.list import grouper @@ -341,7 +341,7 @@ def plot_collected_outputs( if args.parameter_file is not None: params_file = args.parameter_file else: - params_file = Path(data_folder, DEFAULT_PARAMETER_FILENAME) + params_file = Path(data_folder, DEFAULT_PARAMETERS_FILENAME) logger.info(f"Loading params from {params_file}") params = load_json_parameters(params_file, value_cast=True) From 3882e19da8b3080fec954bc9ac1aa494b84de83d Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 1 Nov 2024 16:43:03 -0700 Subject: [PATCH 327/330] #188514964 ensure that button evidence is only produced when button presses are meaningful --- bcipy/task/paradigm/rsvp/copy_phrase.py | 18 +++-- .../tests/paradigm/rsvp/test_copy_phrase.py | 73 ++++++++++++++++++- 2 files changed, 82 insertions(+), 9 deletions(-) diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 1800c207d..1c385f0f1 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -671,8 +671,7 @@ def add_evidence( return evidence_types def compute_button_press_evidence( - self, proceed: bool - ) -> Optional[Tuple[EvidenceType, List[float]]]: + self, proceed: bool) -> Optional[Tuple[EvidenceType, List[float]]]: """If 'show_preview_inquiry' feature is enabled, compute the button press evidence and add it to the copy phrase task. @@ -685,10 +684,7 @@ def compute_button_press_evidence( tuple of (evidence type, evidence) or None if inquiry preview is not enabled. """ - if ( - not self.parameters["show_preview_inquiry"] or - not self.current_inquiry - ): + if (not self.should_compute_button_press_evidence()): return None probs = compute_probs_after_preview( self.current_inquiry.stimuli[0], @@ -698,9 +694,15 @@ def compute_button_press_evidence( ) return (EvidenceType.BTN, probs) + def should_compute_button_press_evidence(self) -> bool: + """Determine if button press evidence should be computed""" + return self.parameters["show_preview_inquiry"] and self.parameters[ + 'preview_inquiry_progress_method'] > 0 and self.current_inquiry + def compute_device_evidence( - self, stim_times: List[List], proceed: bool = True - ) -> List[Tuple[EvidenceType, List[float]]]: + self, + stim_times: List[List], + proceed: bool = True) -> List[Tuple[EvidenceType, List[float]]]: """Get inquiry data from all devices and evaluate the evidence, but don't yet attempt a decision. diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 2bad0ef4b..d5465fe29 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -13,8 +13,8 @@ from bcipy.acquisition.devices import DeviceSpec from bcipy.acquisition.multimodal import ContentType from bcipy.config import DEFAULT_ENCODING -from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper from bcipy.exceptions import TaskConfigurationException +from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper from bcipy.helpers.parameters import Parameters from bcipy.helpers.stimuli import InquirySchedule from bcipy.helpers.triggers import TriggerHandler @@ -594,6 +594,77 @@ def test_execute_real_data_single_inquiry(self, process_data_mock, message_mock, session = Session.from_dict(json.load(json_file)) self.assertEqual(1, session.total_number_series) + def test_btn_evidence_without_inquiry_preview_enabled(self): + """Test button evidence without the inquiry preview functionality""" + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + self.parameters['show_preview_inquiry'] = False + task = RSVPCopyPhraseTask( + parameters=self.parameters, + file_save=self.temp_dir, + fake=False) + self.assertIsNone(task.compute_button_press_evidence(True)) + self.assertIsNone(task.compute_button_press_evidence(False)) + + def test_btn_evidence_without_current_inquiry(self): + """Test button evidence without a current inquiry""" + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + self.parameters['show_preview_inquiry'] = True + task = RSVPCopyPhraseTask( + parameters=self.parameters, + file_save=self.temp_dir, + fake=False) + task.current_inquiry = None + self.assertIsNone(task.compute_button_press_evidence(True)) + self.assertIsNone(task.compute_button_press_evidence(False)) + + @patch('bcipy.task.paradigm.rsvp.copy_phrase.compute_probs_after_preview') + def test_btn_evidence_with_inquiry_preview_enabled(self, + compute_probs_mock): + """Test button evidence with the inquiry preview functionality""" + probs = [ + 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.05, 0.05, + 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, 0.05, + 0.05, 0.05, 0.05, 0.05, 0.95, 0.05 + ] + compute_probs_mock.return_value = probs + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup( + any(), any(), any()).thenReturn((self.daq, self.servers, self.win)) + self.parameters['show_preview_inquiry'] = True + self.parameters['preview_inquiry_progress_method'] = 1 + task = RSVPCopyPhraseTask(parameters=self.parameters, + file_save=self.temp_dir, + fake=False) + + self.assertEqual(task.compute_button_press_evidence(True), + (EvidenceType.BTN, probs)) + compute_probs_mock.assert_called_with(task.current_inquiry.stimuli[0], + task.alp, + task.button_press_error_prob, + True) + self.assertEqual(task.compute_button_press_evidence(False), + (EvidenceType.BTN, probs)) + compute_probs_mock.assert_called_with(task.current_inquiry.stimuli[0], + task.alp, + task.button_press_error_prob, + False) + + def test_btn_evidence_with_preview_only(self): + """Test button evidence with inquiry preview mode set to preview only.""" + when(bcipy.task.paradigm.rsvp.copy_phrase.RSVPCopyPhraseTask).setup(any(), any(), any()).thenReturn( + (self.daq, self.servers, self.win)) + self.parameters['show_preview_inquiry'] = True + self.parameters['preview_inquiry_progress_method'] = 0 # ButtonPressMode.NOTHING.value + + task = RSVPCopyPhraseTask( + parameters=self.parameters, + file_save=self.temp_dir, + fake=False) + + self.assertIsNone(task.compute_button_press_evidence(True)) + self.assertIsNone(task.compute_button_press_evidence(False)) + def test_setup(self): """Test setup""" From 95a12b20b05457d4e53ed616b5077179a9315120 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 1 Nov 2024 17:26:00 -0700 Subject: [PATCH 328/330] Fixed type errors --- bcipy/task/paradigm/rsvp/copy_phrase.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 1c385f0f1..a7f335dbd 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -686,6 +686,7 @@ def compute_button_press_evidence( """ if (not self.should_compute_button_press_evidence()): return None + assert self.current_inquiry, "Current inquiry is required" probs = compute_probs_after_preview( self.current_inquiry.stimuli[0], self.alp, @@ -696,8 +697,8 @@ def compute_button_press_evidence( def should_compute_button_press_evidence(self) -> bool: """Determine if button press evidence should be computed""" - return self.parameters["show_preview_inquiry"] and self.parameters[ - 'preview_inquiry_progress_method'] > 0 and self.current_inquiry + return bool(self.parameters["show_preview_inquiry"] and self.parameters[ + 'preview_inquiry_progress_method'] > 0 and self.current_inquiry) def compute_device_evidence( self, From a56e1d8aec8999bc6910899305204caf2bdcfbe5 Mon Sep 17 00:00:00 2001 From: Basak Celik Date: Tue, 5 Nov 2024 13:39:00 -0500 Subject: [PATCH 329/330] Offline analysis updates for multimodal fusion. (#360) --- .gitignore | 2 +- CHANGELOG.md | 3 + bcipy/helpers/demo/demo_visualization.py | 3 - bcipy/helpers/stimuli.py | 94 +++--- bcipy/helpers/visualization.py | 169 +++++++--- bcipy/parameters/symbol_positions.json | 114 ------- bcipy/signal/model/__init__.py | 7 + bcipy/signal/model/base_model.py | 27 ++ .../signal/model/gaussian_mixture/__init__.py | 8 + .../gaussian_mixture/gaussian_mixture.py | 287 ++++++++++++++--- bcipy/signal/model/offline_analysis.py | 300 ++++++++++-------- bcipy/signal/model/pca_rda_kde/pca_rda_kde.py | 51 ++- bcipy/signal/process/extract_gaze.py | 22 +- .../model/pca_rda_kde/test_pca_rda_kde.py | 6 +- bcipy/simulator/task/copy_phrase.py | 6 +- bcipy/task/control/evidence.py | 69 +++- bcipy/task/control/handler.py | 4 +- bcipy/task/tests/core/test_eeg_evaluator.py | 3 +- scripts/python/replay_session.py | 6 +- setup.py | 2 +- 20 files changed, 762 insertions(+), 421 deletions(-) delete mode 100644 bcipy/parameters/symbol_positions.json diff --git a/.gitignore b/.gitignore index 0367e5eae..1fdadd6e1 100644 --- a/.gitignore +++ b/.gitignore @@ -37,4 +37,4 @@ bcipy/language/out/ bcipy/simulator/tests/resource/ -!bcipy/simulator/data +!bcipy/simulator/data \ No newline at end of file diff --git a/CHANGELOG.md b/CHANGELOG.md index b192ebe43..a5f814ef9 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -34,11 +34,14 @@ Our final release candidate before the official 2.0 release! - session data to VEP calibration #322 - Model - Offline analysis to support multimodal fusion. Initial release of GazeModel, GazeReshaper, and Gaze Visualization #294 + - Updates to ensure seamless offline analysis for both EEG and Gaze data #305 + - Offline analysis support for EEG and (multiple) gaze models. Updates to support Eye Tracker Evidence class #360 - Language Model - Add Oracle model #316 - Random Uniform model #311 - Stimuli - Updates to ensure stimuli are presented at the same frequency #287 + - Output stimuli position, screen capture and monitor information after Matrix tasks #303 - Dynamic Selection Window - Updated trial_length to trial_window to allow for greater control of window used after stimulus presentations #291 - Report diff --git a/bcipy/helpers/demo/demo_visualization.py b/bcipy/helpers/demo/demo_visualization.py index 3ccd8fdf4..078db292a 100644 --- a/bcipy/helpers/demo/demo_visualization.py +++ b/bcipy/helpers/demo/demo_visualization.py @@ -97,9 +97,6 @@ trigger_timing, labels, trial_window, - transform=default_transform, - plot_average=True, - plot_topomaps=True, save_path=save_path, show=args.show ) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 795218db3..558a513e2 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -24,6 +24,7 @@ from bcipy.config import DEFAULT_FIXATION_PATH, DEFAULT_TEXT_FIXATION, SESSION_LOG_FILENAME from bcipy.exceptions import BciPyCoreException from bcipy.helpers.list import grouper +from bcipy.helpers.symbols import alphabet # Prevents pillow from filling the console with debug info logging.getLogger('PIL').setLevel(logging.WARNING) @@ -198,7 +199,7 @@ def extract_trials( prestimulus_samples: int = 0) -> np.ndarray: """Extract Trials. - After using the InquiryReshaper, it may be necessary to further trial the data for processing. + After using the InquiryReshaper, it may be necessary to further extract the trials for processing. Using the number of samples and inquiry timing, the data is reshaped from Channels, Inquiry, Samples to Channels, Trials, Samples. These should match with the trials extracted from the TrialReshaper given the same slicing parameters. @@ -245,38 +246,46 @@ def __call__(self, target_symbols: List[str], gaze_data: np.ndarray, sample_rate: int, - symbol_set: List[str], + stimulus_duration: float, + num_stimuli_per_inquiry: int, + symbol_set: List[str] = alphabet(), channel_map: Optional[List[int]] = None, - ) -> dict: - """Extract inquiry data and labels. Different from the EEG inquiry, the gaze inquiry window starts with - the first flicker and ends with the last flicker in the inquiry. Each inquiry has a length of ~3 seconds. - The labels are provided in the target_symbols list. It returns a Dict, where keys are the target symbols and - the values are inquiries (appended in order of appearance) where the corresponding target symbol is prompted. + ) -> Tuple[dict, list, List[str]]: + """Extract gaze trajectory data and labels. + + Different from the EEG, gaze inquiry windows start with the first highlighted symbol and end with the + last highlighted symbol in the inquiry. Each inquiry has a length of (trial duration x num of trials) + seconds. Labels are provided in 'target_symbols'. It returns a Dict, where keys are the target symbols + and the values are inquiries (appended in order of appearance) where the corresponding target symbol is + prompted. + Optional outputs: - reshape_data is the list of data reshaped into (Inquiries, Channels, Samples), where inquirires are appended - in chronological order. labels returns the list of target symbols in each inquiry. + reshape_data is the list of data reshaped into (Inquiries, Channels, Samples), where inquirires are + appended in chronological order. + labels returns the list of target symbols in each inquiry. - Args: + Parameters + ---------- inq_start_times (List[float]): Timestamp of each event in seconds target_symbols (List[str]): Prompted symbol in each inquiry gaze_data (np.ndarray): shape (channels, samples) eye tracking data - sample_rate (int): sample rate of data provided in eeg_data + sample_rate (int): sample rate of eye tracker data + stimulus_duration (float): duration of flash time (in seconds) for each trial + num_stimuli_per_inquiry (int): number of stimuli in each inquiry (default: 10) + symbol_set (List[str]): list of all symbols for the task channel_map (List[int], optional): Describes which channels to include or discard. Defaults to None; all channels will be used. - Returns: - data_by_targets (dict): Dictionary where keys are the symbol set and values are the appended inquiries - for each symbol. dict[Key] = (np.ndarray) of shape (Channels, Samples) + Returns + ------- + data_by_targets (dict): Dictionary where keys consist of the symbol set, and values + the appended inquiries for each symbol. dict[Key] = (np.ndarray) of shape (Channels, Samples) reshaped_data (List[float]) [optional]: inquiry data of shape (Inquiries, Channels, Samples) labels (List[str]) [optional] : Target symbol in each inquiry. """ - if channel_map: - # Remove the channels that we are not interested in - channels_to_remove = [idx for idx, value in enumerate(channel_map) if value == 0] - gaze_data = np.delete(gaze_data, channels_to_remove, axis=0) - - # Find the value closest to (& greater than) inq_start_times + # Find the timestamp value closest to (& greater than) inq_start_times. + # Lsl timestamps are the last row in the gaze_data gaze_data_timing = gaze_data[-1, :].tolist() start_times = [] @@ -294,54 +303,45 @@ def __call__(self, # Create a dictionary with symbols as keys and data as values # 'A': [], 'B': [] ... - data_by_targets: Dict[str, list] = {} + data_by_targets_dict: Dict[str, list] = {} for symbol in symbol_set: - data_by_targets[symbol] = [] + data_by_targets_dict[symbol] = [] - window_length = 3 # seconds, total length of flickering after prompt for each inquiry + buffer = stimulus_duration / 5 # seconds, buffer for each inquiry + # NOTE: This buffer is used to account for the screen downtime between each stimulus. + # There is a "duty cycle" of 80% for the stimuli, so we add a buffer of 20% of the stimulus length + window_length = (stimulus_duration + buffer) * num_stimuli_per_inquiry # in seconds reshaped_data = [] # Merge the inquiries if they have the same target letter: for i, inquiry_index in enumerate(triggers): start = inquiry_index - stop = int(inquiry_index + (sample_rate * window_length)) # (60 samples * 3 seconds) + stop = int(inquiry_index + (sample_rate * window_length)) # Check if the data exists for the inquiry: if stop > len(gaze_data[0, :]): continue - - reshaped_data.append(gaze_data[:, start:stop]) # (Optional) extracted data (Inquiries x Channels x Samples) + reshaped_data.append(gaze_data[:, start:stop]) - # Populate the dict by appending the inquiry to the correct key: - data_by_targets[labels[i]].append(gaze_data[:, start:stop]) - - # After populating, flatten the arrays in the dictionary to (Channels x Samples): - for symbol in symbol_set: - if len(data_by_targets[symbol]) > 0: - data_by_targets[symbol] = np.transpose(np.array(data_by_targets[symbol]), (1, 0, 2)) - data_by_targets[symbol] = np.reshape(data_by_targets[symbol], (len(data_by_targets[symbol]), -1)) - - # Note that this is a workaround to the issue of having different number of targetness in - # each symbol. If a target symbol is prompted more than once, the data is appended to the dict as a list. - # Which is why we need to convert it to a (np.ndarray) and flatten the dimensions. - # This is not ideal, but it works for now. + # Populate the dict by appending the inquiry to the corresponding key: + data_by_targets_dict[labels[i]].append(gaze_data[:, start:stop]) - # return np.stack(reshaped_data, 0), labels - return data_by_targets + return data_by_targets_dict, reshaped_data, labels - @staticmethod - def centralize_all_data(data, symbol_pos): + def centralize_all_data(self, data: np.ndarray, symbol_pos: np.ndarray) -> np.ndarray: """ Using the symbol locations in matrix, centralize all data (in Tobii units). This data will only be used in certain model types. Args: - data (np.ndarray): Data in shape of num_channels x num_samples + data (np.ndarray): Data in shape of num_samples x num_dimensions symbol_pos (np.ndarray(float)): Array of the current symbol posiiton in Tobii units Returns: - data (np.ndarray): Centralized data in shape of num_channels x num_samples + new_data (np.ndarray): Centralized data in shape of num_samples x num_dimensions """ + new_data = np.copy(data) for i in range(len(data)): - data[i] = data[i] - symbol_pos - return data + new_data[i] = data[i] - symbol_pos + + return new_data class TrialReshaper(Reshaper): diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 7f0d37dc3..8f4c14a3e 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -210,6 +210,7 @@ def visualize_gaze( colorbar=True) if raw_plot: + # ax.scatter(lx, range(len(lx)), c='r', s=1) ax.scatter(lx, ly, c='r', s=1) ax.scatter(rx, ry, c='b', s=1) @@ -282,10 +283,13 @@ def visualize_gaze_inquiries( ly = 1 - ly ry = 1 - ry - if means is not None: - means[:, 0] = np.clip(means[:, 0], 0, 1) - means[:, 1] = np.clip(means[:, 1], 0, 1) - means[:, 1] = 1 - means[:, 1] + # Define mns as a copy of means to avoid modifying the original array + mns = np.copy(means) + + if mns is not None: + mns[:, 0] = np.clip(mns[:, 0], 0, 1) + mns[:, 1] = np.clip(mns[:, 1], 0, 1) + mns[:, 1] = 1 - mns[:, 1] # scale the eye data to the image fig, ax = plt.subplots() @@ -310,11 +314,93 @@ def visualize_gaze_inquiries( colorbar=True) if raw_plot: - # ax.scatter(lx, ly, c='lightcoral', s=1) + ax.scatter(lx, ly, c='lightcoral', s=1) ax.scatter(rx, ry, c='bisque', s=1) - if means is not None: - for i, (mean, cov) in enumerate(zip(means, covs)): + if mns is not None: + for i, (mean, cov) in enumerate(zip(mns, covs)): + v, w = linalg.eigh(cov) + v = 2.0 * np.sqrt(2.0) * np.sqrt(v) + u = w[0] / linalg.norm(w[0]) + + # Plot an ellipse to show the Gaussian component + angle = np.arctan(u[1] / u[0]) + angle = 180.0 * angle / np.pi # convert to degrees + ell = Ellipse(mean, v[0], v[1], angle=180.0 + angle, color='navy') + ell.set_clip_box(ax) + ell.set_alpha(0.5) + ax.add_artist(ell) + + ax.set_xticks([]) + ax.set_yticks([]) + ax.set_xticklabels([]) + ax.set_yticklabels([]) + + plt.title(f'{title}Plot') + + if save_path is not None: + plt.savefig(f"{save_path}/{title.lower().replace(' ', '_')}plot.png", dpi=fig.dpi) + + if show: + plt.show() + else: + plt.close() + + return fig + + +def visualize_pupil_size( + means: Optional[np.ndarray] = None, + covs: Optional[np.ndarray] = None, + save_path: Optional[str] = None, + show: Optional[bool] = False, + img_path: Optional[str] = None, + screen_size: Tuple[int, int] = (1920, 1080), + heatmap: Optional[bool] = False, + raw_plot: Optional[bool] = False) -> Figure: + """Visualize Gaze Inquiries. + + Assumes that the data is collected using BciPy and a Tobii-nano eye tracker. The default + image used is for the matrix calibration task on a 1920x1080 screen. + + Generates a comparative matrix figure following the execution of offline analysis. Given a set of + trailed data (left & right eye), the gaze distribution for each prompted symbol are plotted, along + with the contour plots of mean and covariances calculated by the Gaussian Mixture Model. + The figures may be saved or shown in a window. + + Returns a list of the figure handles created. + + Parameters + ---------- + means: Optional[np.ndarray]: Means of the Gaussian Mixture Model + covs: Optional[np.ndarray]: Covariances of the Gaussian Mixture Model + save_path: Optional[str]: optional path to a save location of the figure generated + show: Optional[bool]: whether or not to show the figures generated. Default: False + img_path: Optional[str]: Image to be used as the background. Default: matrix.png + screen_size: Optional[Tuple[int, int]]: Size of the screen used for Calibration/Copy + Phrase tasks. + Default: (1920, 1080) + heatmap: Optional[bool]: Whether or not to plot the heatmap. Default: False + raw_plot: Optional[bool]: Whether or not to plot the raw gaze data. Default: False + """ + + title = 'Pupil Size ' + img = plt.imread(img_path) + + # Define mns as a copy of means to avoid modifying the original array + mns = np.copy(means) + + if mns is not None: + # mns[:, 0] = np.clip(mns[:, 0], 0, 1) + # mns[:, 1] = np.clip(mns[:, 1], 0, 1) + mns[:, 1] = 1 - mns[:, 1] + + # scale the eye data to the image + fig, ax = plt.subplots() + ax.imshow(img, extent=[0, 1, 0, 1]) + + if mns is not None: + for i, (mean, cov) in enumerate(zip(mns, covs)): v, w = linalg.eigh(cov) v = 2.0 * np.sqrt(2.0) * np.sqrt(v) u = w[0] / linalg.norm(w[0]) @@ -346,8 +432,7 @@ def visualize_gaze_inquiries( def visualize_centralized_data( - left_eye: np.ndarray, - right_eye: np.ndarray, + gaze_data: np.ndarray, save_path: Optional[str] = None, show: Optional[bool] = False, img_path: Optional[str] = None, @@ -369,8 +454,7 @@ def visualize_centralized_data( Parameters ---------- - left_eye: (np.ndarray): Data array for the centralized left eye data. - right_eye: (np.ndarray): Data array for the centralized right eye data. + gaze_data: (np.ndarray): Data array for the centralized left eye data. save_path: Optional[str]: optional path to a save location of the figure generated show: Optional[bool]: whether or not to show the figures generated. Default: False img_path: Optional[str]: Image to be used as the background. Default: matrix.png @@ -390,33 +474,12 @@ def visualize_centralized_data( # Transform the eye data to fit the display. Clip values > 1 and < -1 # The idea here is to have the center at (0,0) - lx = np.clip(left_eye[:, 0], -1, 1) - ly = np.clip(left_eye[:, 1], -1, 1) - rx = np.clip(right_eye[:, 0], -1, 1) - ry = np.clip(right_eye[:, 1], -1, 1) + dx = np.clip(gaze_data[:, 0], -1, 1) + dy = np.clip(gaze_data[:, 1], -1, 1) ax.imshow(img, extent=[-1, 1, -1, 1]) - if heatmap: - # create a dataframe making a column for each x, y pair for both eyes and a column for the eye (left or right) - df = pd.DataFrame({ - 'x': np.concatenate((lx, rx)), - 'y': np.concatenate((ly, ry)), - 'eye': ['left'] * len(lx) + ['right'] * len(rx) - }) - ax = sns.kdeplot( - data=df, - hue='eye', - x='x', - y='y', - fill=False, - thresh=0.05, - levels=10, - cmap="mako", - colorbar=True) - if raw_plot: - ax.scatter(lx, ly, c='r', s=1) - ax.scatter(rx, ry, c='b', s=1) + ax.scatter(dx, dy, c='b', s=1) ax.set_xticks([]) ax.set_yticks([]) @@ -459,10 +522,10 @@ def visualize_results_all_symbols( Parameters ---------- - left_eye: (np.ndarray): Data array for the left eye data. - right_eye: (np.ndarray): Data array for the right eye data. - means: Optional[np.ndarray]: Means of the Gaussian Mixture Model - covs: Optional[np.ndarray]: Covariances of the Gaussian Mixture Model + left_eye_all: (np.ndarray): Data array for the left eye data, for all symbols. + right_eye_all: (np.ndarray): Data array for the right eye data, for all symbols. + means_all: Optional[np.ndarray]: Means of the Gaussian Mixture Model, for all symbols + covs_all: Optional[np.ndarray]: Covariances of the Gaussian Mixture Model, for all symbols save_path: Optional[str]: optional path to a save location of the figure generated show: Optional[bool]: whether or not to show the figures generated. Default: False img_path: Optional[str]: Image to be used as the background. Default: matrix.png @@ -492,10 +555,13 @@ def visualize_results_all_symbols( ly = 1 - ly ry = 1 - ry - if means is not None: - means[:, 0] = np.clip(means[:, 0], 0, 1) - means[:, 1] = np.clip(means[:, 1], 0, 1) - means[:, 1] = 1 - means[:, 1] + # Define mns as a copy of means to avoid modifying the original array + mns = np.copy(means) + + if mns is not None: + mns[:, 0] = np.clip(mns[:, 0], 0, 1) + mns[:, 1] = np.clip(mns[:, 1], 0, 1) + mns[:, 1] = 1 - mns[:, 1] if heatmap: # create a dataframe making a column for each x, y pair for both eyes and @@ -517,11 +583,11 @@ def visualize_results_all_symbols( colorbar=True) if raw_plot: - # ax.scatter(lx, ly, c='lightcoral', s=1) + ax.scatter(lx, ly, c='lightcoral', s=1) ax.scatter(rx, ry, c='bisque', s=1) - if means is not None: - for i, (mean, cov) in enumerate(zip(means, covs)): + if mns is not None: + for i, (mean, cov) in enumerate(zip(mns, covs)): v, w = linalg.eigh(cov) v = 2.0 * np.sqrt(2.0) * np.sqrt(v) u = w[0] / linalg.norm(w[0]) @@ -751,12 +817,21 @@ def visualize_gaze_accuracies(accuracy_dict: Dict[str, np.ndarray], Returns a list of the figure handles created. """ + title = 'Overall Accuracy: ' fig, ax = plt.subplots() ax.bar(accuracy_dict.keys(), accuracy_dict.values()) ax.set_xlabel('Symbol') ax.set_ylabel('Accuracy') - ax.set_title('Overall Accuracy: ' + str(round(accuracy, 2))) + ax.set_title(title + str(round(accuracy, 2))) + + if save_path is not None: + plt.savefig(f"{save_path}/{title.lower().replace(' ', '_').replace(':', '')}plot.png", dpi=fig.dpi) + + if show: + plt.show() + else: + plt.close() return fig diff --git a/bcipy/parameters/symbol_positions.json b/bcipy/parameters/symbol_positions.json deleted file mode 100644 index 0c9ad42af..000000000 --- a/bcipy/parameters/symbol_positions.json +++ /dev/null @@ -1,114 +0,0 @@ -{ - "A": [ - 0.20, - 0.30 - ], - "B": [ - 0.31, - 0.30 - ], - "C": [ - 0.42, - 0.30 - ], - "D": [ - 0.53, - 0.30 - ], - "E": [ - 0.64, - 0.30 - ], - "F": [ - 0.75, - 0.30 - ], - "G": [ - 0.20, - 0.41 - ], - "H": [ - 0.31, - 0.41 - ], - "I": [ - 0.42, - 0.41 - ], - "J": [ - 0.53, - 0.41 - ], - "K": [ - 0.64, - 0.41 - ], - "L": [ - 0.75, - 0.41 - ], - "M": [ - 0.20, - 0.52 - ], - "N": [ - 0.31, - 0.52 - ], - "O": [ - 0.42, - 0.52 - ], - "P": [ - 0.53, - 0.49 - ], - "Q": [ - 0.64, - 0.52 - ], - "R": [ - 0.75, - 0.52 - ], - "S": [ - 0.20, - 0.63 - ], - "T": [ - 0.31, - 0.63 - ], - "U": [ - 0.42, - 0.63 - ], - "V": [ - 0.53, - 0.63 - ], - "W": [ - 0.64, - 0.63 - ], - "X": [ - 0.75, - 0.63 - ], - "Y": [ - 0.20, - 0.74 - ], - "Z": [ - 0.31, - 0.74 - ], - "<": [ - 0.42, - 0.74 - ], - "_": [ - 0.53, - 0.79 - ] -} \ No newline at end of file diff --git a/bcipy/signal/model/__init__.py b/bcipy/signal/model/__init__.py index d95f3d026..6b3140237 100644 --- a/bcipy/signal/model/__init__.py +++ b/bcipy/signal/model/__init__.py @@ -1,10 +1,17 @@ from bcipy.signal.model.base_model import SignalModel, ModelEvaluationReport from bcipy.signal.model.pca_rda_kde.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.model.rda_kde.rda_kde import RdaKdeModel +from bcipy.signal.model.gaussian_mixture.gaussian_mixture import ( + GMIndividual, GMCentralized, KernelGP, KernelGPSampleAverage) + __all__ = [ "SignalModel", "PcaRdaKdeModel", "RdaKdeModel", + 'GMIndividual', + 'GMCentralized', + 'KernelGP', + 'KernelGPSampleAverage', "ModelEvaluationReport", ] diff --git a/bcipy/signal/model/base_model.py b/bcipy/signal/model/base_model.py index 828e3bb1e..f3ed77553 100644 --- a/bcipy/signal/model/base_model.py +++ b/bcipy/signal/model/base_model.py @@ -64,6 +64,33 @@ def predict(self, data: np.ndarray, inquiry: List[str], symbol_set: List[str]) - """ ... + def compute_likelihood_ratio(self, data: np.array, inquiry: List[str], symbol_set: List[str]) -> np.array: + """ + For each trial in `data`, compute a likelihood ratio to update that symbol's probability. + Rather than just computing an update p(data|l=+) for the seen symbol and p(data|l=-) for all unseen symbols, + we compute a likelihood ratio p(data | l=+) / p(data | l=-) to update the seen symbol, and all other symbols + can receive a multiplicative update of 1. + + Args: + data (np.array): data with shape (n_channel, n_trial, n_sample). + inquiry (List[str]): List describing the symbol shown in each trial. + symbol_set (List[str]): The set of all possible symbols. + + Raises: + SignalException: error if called before model is fit. + + Returns: + np.array: multiplicative update term (likelihood ratios) for each symbol in the `symbol_set`. + """ + ... + + def compute_class_probabilities(self, data: np.ndarray) -> np.ndarray: + """Converts log likelihoods from model into class probabilities.""" + ... + + def evaluate_likelihood(self, data: np.ndarray) -> np.ndarray: + ... + @abstractmethod def save(self, path: Path) -> None: """Save model state to the provided checkpoint""" diff --git a/bcipy/signal/model/gaussian_mixture/__init__.py b/bcipy/signal/model/gaussian_mixture/__init__.py index e69de29bb..e021544d5 100644 --- a/bcipy/signal/model/gaussian_mixture/__init__.py +++ b/bcipy/signal/model/gaussian_mixture/__init__.py @@ -0,0 +1,8 @@ +from .gaussian_mixture import GMIndividual, GMCentralized, KernelGP, KernelGPSampleAverage + +__all__ = [ + 'GMIndividual', + 'GMCentralized', + 'KernelGP', + 'KernelGPSampleAverage' +] diff --git a/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py b/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py index 0f71f6c94..e7f3e5e22 100644 --- a/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py +++ b/bcipy/signal/model/gaussian_mixture/gaussian_mixture.py @@ -1,72 +1,205 @@ from pathlib import Path +from typing import List -import numpy as np +from bcipy.helpers.stimuli import GazeReshaper from bcipy.signal.model import SignalModel + from sklearn.mixture import GaussianMixture -from bcipy.helpers.stimuli import GazeReshaper -from sklearn.model_selection import cross_val_score # noqa +import numpy as np import scipy.stats as stats -from typing import Optional +import warnings +warnings.filterwarnings("ignore") # ignore DeprecationWarnings from tensorflow + + +class KernelGP(SignalModel): + def __init__(self): + reshaper = GazeReshaper() + + def fit(self, training_data: np.ndarray, training_labels: np.ndarray): + training_data = np.asarray(training_data) + + def evaluate(self, test_data: np.ndarray, test_labels: np.ndarray): + ... + + def predict(self, test_data: np.ndarray, inquiry, symbol_set) -> np.ndarray: + ... + + def predict_proba(self, test_data: np.ndarray) -> np.ndarray: + ... + + def save(self, path: Path): + ... + + def load(self, path: Path): + ... -class GazeModelIndividual(SignalModel): +class KernelGPSampleAverage(SignalModel): + reshaper = GazeReshaper() + + def __init__(self): + self.ready_to_predict = False + + def fit(self, training_data: np.ndarray): + training_data = np.array(training_data) + # Training data shape = inquiry x features x samples + # reshape training data to inquiry x (features x samples) + reshaped_data = training_data.reshape((len(training_data), -1)) + cov_matrix = np.cov(reshaped_data, rowvar=False) + # cov_matrix_shape = (features x samples) x (features x samples) + reshaped_mean = np.mean(reshaped_data, axis=0) + + def evaluate(self, test_data: np.ndarray, test_labels: np.ndarray): + ... + + def predict(self, test_data: np.ndarray, inquiry, symbol_set) -> np.ndarray: + ... + + def predict_proba(self, test_data: np.ndarray) -> np.ndarray: + ... + + def save(self, path: Path): + ... + + def load(self, path: Path): + ... + + def centralize(self, data: np.ndarray, symbol_pos: np.ndarray) -> np.ndarray: + """ Using the symbol locations in matrix, centralize all data (in Tobii units). + This data will only be used in certain model types. + Args: + data (np.ndarray): Data in shape of num_samples x num_dimensions + symbol_pos (np.ndarray(float)): Array of the current symbol posiiton in Tobii units + Returns: + new_data (np.ndarray): Centralized data in shape of num_samples x num_dimensions + """ + new_data = np.copy(data) + for i in range(len(data.T)): + new_data[0:2, i] = data[0:2, i] - symbol_pos + new_data[2:4, i] = data[2:4, i] - symbol_pos + + return new_data + + def substract_mean(self, data: np.ndarray, time_avg: np.ndarray) -> np.ndarray: + """ Using the symbol locations in matrix, centralize all data (in Tobii units). + This data will only be used in certain model types. + Args: + data (np.ndarray): Data in shape of num_samples x num_dimensions + symbol_pos (np.ndarray(float)): Array of the current symbol posiiton in Tobii units + Returns: + new_data (np.ndarray): Centralized data in shape of num_samples x num_dimensions + """ + new_data = np.copy(data) + for i in range(len(data.T)): + new_data[:, i] = data[:, i] - time_avg + + return new_data + + +class GMIndividual(SignalModel): + """Gaze model that fits different Gaussians/Gaussian Mixtures for each symbol.""" reshaper = GazeReshaper() name = "gaze_model_individual" - def __init__(self, num_components=2): + def __init__(self, num_components=4, random_state=0): self.num_components = num_components # number of gaussians to fit + self.random_state = random_state + self.means = None + self.covs = None + + self.ready_to_predict = False - def fit(self, train_data: np.ndarray) -> 'GazeModelIndividual': - model = GaussianMixture(n_components=1, random_state=0, init_params='kmeans') + def fit(self, train_data: np.ndarray): + model = GaussianMixture(n_components=self.num_components, random_state=self.random_state, init_params='kmeans') model.fit(train_data) self.model = model + self.means = model.means_ + self.covs = model.covariances_ + + self.ready_to_predict = True + return self - def evaluate(self, test_data: np.ndarray): + def evaluate(self, predictions, true_labels) -> np.ndarray: ''' - Compute mean and covariance of each mixture component. + Compute performance characteristics on the provided test data and labels. + + Parameters: + ----------- + predictions: predicted labels for each test point per symbol + true_labels: true labels for each test point per symbol + Returns: + -------- + accuracy_per_symbol: accuracy per symbol ''' + accuracy_per_symbol = np.sum(predictions == true_labels) / len(predictions) * 100 - means = self.model.means_ - covs = self.model.covariances_ + return accuracy_per_symbol - return means, covs + def compute_likelihood_ratio(self, data: np.array, inquiry: List[str], symbol_set: List[str]) -> np.array: + ''' + Not implemented in this model. + ''' + ... - def predict(self, test_data: np.ndarray, means: np.ndarray, covs: np.ndarray): + def predict(self, test_data: np.ndarray) -> np.ndarray: ''' Compute log-likelihood of each sample. Predict the labels for the test data. + + test_data: gaze data + inquiry: the subset of symbols presented + symbol_set: the entire set of symbols presented + ''' + data_length, _ = test_data.shape + predictions = np.zeros(data_length, dtype=object) + + likelihoods = self.model.predict_proba(test_data) + + for i in range(data_length): + # Find the argmax of the likelihoods to get the predictions + predictions[i] = np.argmax(likelihoods[i]) + + return predictions + + def predict_proba(self, test_data: np.ndarray) -> np.ndarray: ''' + Compute log-likelihood of each sample. - num_components = len(means) + test_data: gaze data - N, D = test_data.shape - K = num_components + log(p(l | gaze)) = log(p(gaze | l)) + log(p(l)) - log(p(gaze)) + ''' + data_length, _ = test_data.shape - likelihoods = np.zeros((N, K), dtype=object) - predictions = np.zeros(N, dtype=object) + likelihoods = np.zeros((data_length, self.num_components), dtype=object) # Find the likelihoods by insterting the test data into the pdf of each component - for i in range(N): - for k in range(K): - mu = means[k] - sigma = covs[k] + for i in range(data_length): + for k in range(self.num_components): + mu = self.means[k] + sigma = self.covs[k] likelihoods[i, k] = stats.multivariate_normal.pdf(test_data[i], mu, sigma) - # Find the argmax of the likelihoods to get the predictions - predictions[i] = np.argmax(likelihoods[i]) + return likelihoods - return likelihoods, predictions + def evaluate_likelihood(self, data: np.ndarray) -> np.ndarray: + data_length, _ = data.shape - def calculate_acc(self, test_data: np.ndarray, test_labels: Optional[np.ndarray]): - ''' - Compute model performance characteristics on the provided test data and labels. - ''' + likelihoods = np.zeros((data_length, self.num_components), dtype=object) - # return accuracy + # Find the likelihoods by insterting the test data into the pdf of each component + for i in range(data_length): + for k in range(self.num_components): + mu = self.means[k] + sigma = self.covs[k] + + likelihoods[i, k] = stats.multivariate_normal.pdf(data[i], mu, sigma) + + return likelihoods def save(self, path: Path): """Save model state to the provided checkpoint""" @@ -77,52 +210,93 @@ def load(self, path: Path): ... -class GazeModelCombined(SignalModel): +class GMCentralized(SignalModel): '''Gaze model that uses all symbols to fit a single Gaussian ''' reshaper = GazeReshaper() name = "gaze_model_combined" - def __init__(self, num_components=1): + def __init__(self, num_components=4, random_state=0): self.num_components = num_components # number of gaussians to fit + self.random_state = random_state + self.means = None + self.covs = None + + self.ready_to_predict = False def fit(self, train_data: np.ndarray): - model = GaussianMixture(n_components=1, random_state=0, init_params='kmeans') + model = GaussianMixture(n_components=self.num_components, random_state=self.random_state, init_params='kmeans') model.fit(train_data) self.model = model + self.means = model.means_ + self.covs = model.covariances_ + + self.ready_to_predict = True return self - def evaluate(self, test_data: np.ndarray, sym_pos: np.ndarray): + def evaluate(self, predictions, true_labels) -> np.ndarray: + ''' + Compute performance characteristics on the provided test data and labels. + + Parameters: + ----------- + predictions: predicted labels for each test point per symbol + true_labels: true labels for each test point per symbol + Returns: + -------- + accuracy_per_symbol: accuracy per symbol ''' - Return mean and covariance of each mixture component. + accuracy_per_symbol = np.sum(predictions == true_labels) / len(predictions) * 100 - test_data: gaze data for each symbol - sym_pos: mid positions for each symbol in Tobii coordinates + return accuracy_per_symbol + ... + + def predict(self, test_data: np.ndarray) -> np.ndarray: + ''' + Compute log-likelihood of each sample. + Predict the labels for the test data. ''' + data_length, _ = test_data.shape + predictions = np.zeros(data_length, dtype=object) + likelihoods = self.model.predict_proba(test_data) - means = self.model.means_ + sym_pos - covs = self.model.covariances_ + for i in range(data_length): + # Find the argmax of the likelihoods to get the predictions + predictions[i] = np.argmax(likelihoods[i]) - return means, covs + return predictions - def predict(self, test_data: np.ndarray): + def predict_proba(self, test_data: np.ndarray) -> np.ndarray: ''' Compute log-likelihood of each sample. Predict the labels for the test data. + + test_data: ''' - # Compute over log-likelihood scores - # Get the argmax of the scores + data_length, _ = test_data.shape - scores = self.model.score_samples(test_data) + likelihoods = np.zeros((data_length, self.num_components), dtype=object) - # return predictions + # Find the likelihoods by insterting the test data into the pdf of each component + for i in range(data_length): + for k in range(self.num_components): + mu = self.means[k] + sigma = self.covs[k] - def calculate_acc(self, test_data: np.ndarray, sym_pos: np.ndarray): + likelihoods[i, k] = stats.multivariate_normal.pdf(test_data[i], mu, sigma) + + return likelihoods + + def calculate_acc(self, predictions: int, counter: int): ''' Compute model performance characteristics on the provided test data and labels. + + predictions: predicted labels for each test point per symbol + counter: true labels for each test point per symbol ''' + accuracy_per_symbol = np.sum(predictions == counter) / len(predictions) * 100 - # return accuracy + return accuracy_per_symbol def save(self, path: Path): """Save model state to the provided checkpoint""" @@ -131,3 +305,20 @@ def save(self, path: Path): def load(self, path: Path): """Load model state from the provided checkpoint""" ... + + def centralize(self, data: np.ndarray, symbol_pos: np.ndarray) -> np.ndarray: + """ Using the symbol locations in matrix, centralize all data (in Tobii units). + This data will only be used in certain model types. + Args: + data (np.ndarray): Data in shape of num_samples x num_dimensions + symbol_pos (np.ndarray(float)): Array of the current symbol posiiton in Tobii units + Returns: + new_data (np.ndarray): Centralized data in shape of num_samples x num_dimensions + """ + new_data = np.copy(data) + for i in range(len(data)): + # new_data[i] = data[i] - symbol_pos + new_data[:2, i] = data[:2, i] - symbol_pos + new_data[2:, i] = data[2:, i] - symbol_pos + + return new_data diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index ae0ff6845..5f3787a21 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -11,8 +11,8 @@ from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices -from bcipy.config import (BCIPY_ROOT, DEFAULT_DEVICE_SPEC_FILENAME, - DEFAULT_PARAMETERS_PATH, MATRIX_IMAGE_FILENAME, DEFAULT_DEVICES_PATH, +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETERS_PATH, DEFAULT_DEVICES_PATH, TRIGGER_FILENAME, SESSION_LOG_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename from bcipy.helpers.load import (load_experimental_data, load_json_parameters, @@ -24,15 +24,10 @@ from bcipy.helpers.symbols import alphabet from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.helpers.visualization import (visualize_centralized_data, - visualize_gaze, - visualize_gaze_accuracies, - visualize_gaze_inquiries, - visualize_results_all_symbols) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata -from bcipy.signal.model.gaussian_mixture.gaussian_mixture import (GazeModelCombined, - GazeModelIndividual) +from bcipy.signal.model.gaussian_mixture import (GMIndividual, GMCentralized, + KernelGP, KernelGPSampleAverage) from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import (ERPTransformParams, extract_eye_info, filter_inquiries, get_default_transform) @@ -257,18 +252,13 @@ def analyze_gaze( "Individual": Fits a separate Gaussian for each symbol. Default model "Centralized": Uses data from all symbols to fit a single centralized Gaussian """ - visualize_gaze( - gaze_data, - save_path=save_figures, - img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', - show=show_figures, - raw_plot=plot_points, - ) - channels = gaze_data.channels type_amp = gaze_data.daq_type sample_rate = gaze_data.sample_rate + flash_time = parameters.get("time_flash") # duration of each stimulus + stim_size = parameters.get("stim_length") # number of stimuli per inquiry + log.info(f"Channels read from csv: {channels}") log.info(f"Device type: {type_amp}, fs={sample_rate}") channel_map = analysis_channels(channels, device_spec) @@ -279,9 +269,13 @@ def analyze_gaze( data, _fs = gaze_data.by_channel() if model_type == "Individual": - model = GazeModelIndividual() + model = GMIndividual() elif model_type == "Centralized": - model = GazeModelCombined() + model = GMCentralized() + elif model_type == "GP": + model = KernelGP() + elif model_type == "GP_SampleAverage": + model = KernelGPSampleAverage() # Extract all Triggers info trigger_targetness, trigger_timing, trigger_symbols = trigger_decoder( @@ -298,19 +292,23 @@ def analyze_gaze( ) ''' Trigger_timing includes PROMPT and excludes FIXATION ''' + # Extract the inquiries dictionary with keys as target symbols and values as inquiry windows: + symbol_set = alphabet() + target_symbols = trigger_symbols[0::11] # target symbols are the PROMPT triggers # Use trigger_timing to generate time windows for each letter flashing # Take every 10th trigger as the start point of timing. inq_start = trigger_timing[1::11] # start of each inquiry (here we jump over prompts) # Extract the inquiries dictionary with keys as target symbols and values as inquiry windows: - symbol_set = alphabet() - inquiries = model.reshaper( + inquiries_dict, inquiries_list, _ = model.reshaper( inq_start_times=inq_start, target_symbols=target_symbols, gaze_data=data, sample_rate=sample_rate, - symbol_set=symbol_set + stimulus_duration=flash_time, + num_stimuli_per_inquiry=10, + symbol_set=alphabet() ) # Extract the data for each target label and each eye separately. @@ -318,141 +316,148 @@ def analyze_gaze( preprocessed_data = {i: [] for i in symbol_set} for i in symbol_set: # Skip if there's no evidence for this symbol: - if len(inquiries[i]) == 0: + if len(inquiries_dict[i]) == 0: continue - left_eye, right_eye = extract_eye_info(inquiries[i]) - preprocessed_data[i] = np.array([left_eye, right_eye]) # Channels x Sample Size x Dimensions(x,y) + for j in range(len(inquiries_dict[i])): + left_eye, right_eye, _, _, _, _ = extract_eye_info(inquiries_dict[i][j]) + preprocessed_data[i].append((np.concatenate((left_eye.T, right_eye.T), axis=0))) + # Inquiries x All Dimensions (left_x, left_y, right_x, right_y) x Time + preprocessed_data[i] = np.array(preprocessed_data[i]) - centralized_data_left = [] - centralized_data_right = [] - test_dict = {} + centralized_data = {i: [] for i in symbol_set} + time_average = {i: [] for i in symbol_set} - left_eye_all = [] - right_eye_all = [] - means_all = [] - covs_all = [] for sym in symbol_set: # Skip if there's no evidence for this symbol: - if len(inquiries[sym]) == 0: - test_dict[sym] = [] - continue - le = preprocessed_data[sym][0] - re = preprocessed_data[sym][1] + try: + if len(inquiries_dict[sym]) == 0: + continue - # Train test split: - labels = np.array([sym] * len(le)) # Labels are the same for both eyes - train_le, test_le, train_labels_le, test_labels_le = subset_data(le, labels, test_size=0.2, swap_axes=False) - train_re, test_re, train_labels_re, test_labels_re = subset_data(re, labels, test_size=0.2, swap_axes=False) - test_dict[sym] = np.concatenate((test_le, test_re), axis=0) + except BaseException: + log.info(f"No evidence from symbol {sym}") + continue # Fit the model based on model type. - # Model 1: Fit Gaussian mixture (comp=2) on each symbol and each eye separately if model_type == "Individual": - model.fit(train_re) - - means, covs = model.evaluate(test_re) - - # Visualize the results: - visualize_gaze_inquiries( - le, re, - means, covs, - save_path=save_figures, - img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', - show=show_figures, - raw_plot=plot_points, - ) - left_eye_all.append(le) - right_eye_all.append(re) - means_all.append(means) - covs_all.append(covs) - - # TODO: Calculate scores for the test set. - # scores, predictions = model.predict(test_re) - - # Model 2: Fit Gaussian mixture (comp=1) on a centralized data + # Model 1: Fit Gaussian mixture on each symbol separately + reshaped_data = preprocessed_data[sym].reshape( + (preprocessed_data[sym].shape[0] * + preprocessed_data[sym].shape[2], + preprocessed_data[sym].shape[1])) + model.fit(reshaped_data) + if model_type == "Centralized": - # Centralize the data using symbol positions: + # Centralize the data using symbol positions and fit a single Gaussian. # Load json file. - with open(f"{BCIPY_ROOT}/parameters/symbol_positions.json", 'r') as params_file: + with open(f"{data_folder}/stimuli_positions.json", 'r') as params_file: symbol_positions = json.load(params_file) + # Subtract the symbol positions from the data: - centralized_data_left.append(model.reshaper.centralize_all_data(train_le, symbol_positions[sym])) - centralized_data_right.append(model.reshaper.centralize_all_data(train_re, symbol_positions[sym])) + for j in range(len(preprocessed_data[sym])): + centralized_data[sym].append(model.centralize(preprocessed_data[sym][j], symbol_positions[sym])) + + if model_type == "GP_SampleAverage": + # Instead of centralizing, take the time average: + for j in range(len(preprocessed_data[sym])): + temp = np.mean(preprocessed_data[sym][j], axis=1) + time_average[sym].append(temp) + centralized_data[sym].append( + model.substract_mean( + preprocessed_data[sym][j], + temp)) # Delta_t = X_t - mu + centralized_data[sym] = np.array(centralized_data[sym]) + time_average[sym] = np.mean(np.array(time_average[sym]), axis=0) if model_type == "Individual": - # Takes in all means and covs from individual symbols, and - # calculates the likelihoods and predictions for each test point. - # Convert test_dict to a list of arrays: accuracy = 0 acc_all_symbols = {} counter = 0 + + if model_type == "GP_SampleAverage": + test_dict = {i: [] for i in symbol_set} + # Visualize different inquiries from the same target letter: + colors = ['r', 'g', 'b', 'y', 'm', 'c', 'k', 'w', 'orange', 'purple'] for sym in symbol_set: - # Skip if test_dict is empty for certain symbols: - if len(test_dict[sym]) == 0: - acc_all_symbols[sym] = 0 + if len(centralized_data[sym]) == 0: continue - likelihoods, predictions = model.predict( - test_dict[sym], np.squeeze( - np.array(means_all)), np.squeeze( - np.array(covs_all))) - acc_all_symbols[sym] = np.sum(predictions == counter) / len(predictions) * 100 - accuracy += np.sum(predictions == counter) / len(predictions) * 100 - print(f"""Correct predictions for {sym}: {np.sum(predictions == counter)} / {len(predictions)}, - Accuracy {sym}: {np.sum(predictions == counter) / len(predictions) * 100:.2f}""") - counter += 1 - accuracy /= counter - print(f"Overall accuracy: {accuracy:.2f}") - - # Plot all accuracies as bar plot: - visualize_gaze_accuracies(acc_all_symbols, accuracy, save_path=None, show=True) - if model_type == "Centralized": - cent_left = np.concatenate(np.array(centralized_data_left, dtype=object)) - cent_right = np.concatenate(np.array(centralized_data_right, dtype=object)) - - # Visualize the results: - visualize_centralized_data( - cent_left, cent_right, - save_path=save_figures, - img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', - show=show_figures, - raw_plot=plot_points, - ) + # Split the data into train and test sets & fit the model: + centralized_data_training_set = [] + for sym in symbol_set: + if len(centralized_data[sym]) <= 1: + if len(centralized_data[sym]) == 1: + test_dict[sym] = preprocessed_data[sym][-1] + continue + # Leave one out and add the rest to the training set: + for j in range(len(centralized_data[sym]) - 1): + centralized_data_training_set.append(centralized_data[sym][j]) + # Add the last inquiry to the test set: + test_dict[sym] = preprocessed_data[sym][-1] + + centralized_data_training_set = np.array(centralized_data_training_set) + reshaped_data = centralized_data_training_set.reshape((72, 720)) + + cov_matrix = np.cov(reshaped_data, rowvar=False) + time_horizon = 9 + # Accuracy vs time horizon + + for eye_coord_0 in range(4): + for eye_coord_1 in range(4): + for time_0 in range(180): + for time_1 in range(180): + l_ind = eye_coord_0 * 180 + time_0 + m_ind = eye_coord_1 * 180 + time_1 + if np.abs(time_1 - time_0) > time_horizon: + cov_matrix[l_ind, m_ind] = 0 + # cov_matrix[m_ind, l_ind] = 0 + reshaped_mean = np.mean(reshaped_data, axis=0) + + eps = 0 + regularized_cov_matrix = cov_matrix + np.eye(len(cov_matrix)) * eps + try: + inv_cov_matrix = np.linalg.inv(regularized_cov_matrix) + except BaseException: + print("Singular matrix, using pseudo-inverse instead") + eps = 10e-3 # add a small value to the diagonal to make the matrix invertible + inv_cov_matrix = np.linalg.inv(cov_matrix + np.eye(len(cov_matrix)) * eps) + # inv_cov_matrix = np.linalg.pinv(cov_matrix + np.eye(len(cov_matrix))*eps) + denominator = 0 + + # Find the likelihoods for the test case: + l_likelihoods = np.zeros((len(symbol_set), len(symbol_set))) + log_likelihoods = np.zeros((len(symbol_set), len(symbol_set))) + counter = 0 + for i_sym0, sym0 in enumerate(symbol_set): + for i_sym1, sym1 in enumerate(symbol_set): + if len(centralized_data[sym1]) == 0: + continue + if len(test_dict[sym0]) == 0: + continue + # print(f"Target: {sym0}, Tested: {sym1}") + central_data = model.substract_mean(test_dict[sym0], time_average[sym1]) + flattened_data = central_data.reshape((720,)) + diff = flattened_data - reshaped_mean + numerator = -np.dot(diff.T, np.dot(inv_cov_matrix, diff)) / 2 + log_likelihood = numerator - denominator + # print(f"{log_likelihood:.3E}") + log_likelihoods[i_sym0, i_sym1] = log_likelihood + # Find the max likelihood: + max_like = np.argmax(log_likelihoods[i_sym0, :]) + # Check if it's the same as the target, and save the result: + if max_like == i_sym0: + # print("True") + counter += 1 - # Fit the model: - model.fit(cent_left) + if model_type == "Centralized": + # Fit the model parameters using the centralized data: + # flatten the dict to a np array: + cent_data = np.concatenate([centralized_data[sym] for sym in symbol_set], axis=0) + # Merge the first and third dimensions: + cent_data = cent_data.reshape((cent_data.shape[0] * cent_data.shape[2], cent_data.shape[1])) - # Add the means back to the symbol positions. - # Calculate scores for the test set. - for sym in symbol_set: - means, covs = model.evaluate(test_dict[sym][0], symbol_positions[sym]) - - le = preprocessed_data[sym][0] - re = preprocessed_data[sym][1] - # Visualize the results: - visualize_gaze_inquiries( - le, re, - means, covs, - save_path=save_figures, - img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', - show=show_figures, - raw_plot=plot_points, - ) - left_eye_all.append(le) - right_eye_all.append(re) - means_all.append(means) - covs_all.append(covs) - - # TODO: add visualizations to subprocess - visualize_results_all_symbols( - left_eye_all, right_eye_all, - means_all, covs_all, - img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', - save_path=save_figures, - show=show_figures, - raw_plot=plot_points, - ) + # cent_data = np.concatenate(centralized_data, axis=0) + model.fit(cent_data) model.metadata = SignalModelMetadata(device_spec=device_spec, transform=None) @@ -529,16 +534,26 @@ def offline_analysis( raw_data = load_raw_data(raw_data_path) device_spec = devices_by_name.get(raw_data.daq_type) # extract relevant information from raw data object eeg - if device_spec.content_type == "EEG": + + if device_spec.content_type == "EEG" and device_spec.is_active: erp_model = analyze_erp( - raw_data, parameters, device_spec, data_folder, estimate_balanced_acc, save_figures, show_figures) + raw_data, + parameters, + device_spec, + data_folder, + estimate_balanced_acc, + save_figures, + show_figures) models.append(erp_model) - if device_spec.content_type == "Eyetracker": + if device_spec.content_type == "Eyetracker" and device_spec.is_active: et_model = analyze_gaze( raw_data, parameters, device_spec, data_folder, save_figures, show_figures, model_type="Individual") models.append(et_model) + if len(models) > 1: + log.info("Multiple Models Trained. Fusion Analysis Not Yet Implemented.") + if alert_finished: log.info("Alerting Offline Analysis Complete") results = [f"{model.name}: {model.auc}" for model in models] @@ -548,6 +563,19 @@ def offline_analysis( def main(): + """Main function for offline analysis client. + + Parses command line arguments and runs offline analysis. + + Command Line Arguments: + + -d, --data_folder: Path to the folder containing the data to be analyzed. + -p, --parameters_file: Path to the parameters file. Default is DEFAULT_PARAMETERS_PATH. + -s, --save_figures: If true, saves data figures after training to the data folder. + -v, --show_figures: If true, shows data figures after training. + --alert: If true, alerts the user when offline analysis is complete. + --balanced-acc: If true, uses another model copy on an 80/20 split to estimate balanced accuracy. + """ import argparse parser = argparse.ArgumentParser() diff --git a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py index 28280c1d3..04df91098 100644 --- a/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py +++ b/bcipy/signal/model/pca_rda_kde/pca_rda_kde.py @@ -114,7 +114,7 @@ def evaluate(self, test_data: np.array, test_labels: np.array) -> ModelEvaluatio auc = -tmp return ModelEvaluationReport(auc) - def predict(self, data: np.array, inquiry: List[str], symbol_set: List[str]) -> np.array: + def compute_likelihood_ratio(self, data: np.array, inquiry: List[str], symbol_set: List[str]) -> np.array: """ For each trial in `data`, compute a likelihood ratio to update that symbol's probability. Rather than just computing an update p(e|l=+) for the seen symbol and p(e|l=-) for all unseen symbols, @@ -146,9 +146,9 @@ def predict(self, data: np.array, inquiry: List[str], symbol_set: List[str]) -> likelihood_ratios = np.ones(len(symbol_set)) for idx in range(len(subset_likelihood_ratios)): likelihood_ratios[symbol_set.index(inquiry[idx])] *= subset_likelihood_ratios[idx] - return likelihood_ratios + return likelihood_ratios # used in multimodal update - def predict_proba(self, data: np.ndarray) -> np.ndarray: + def compute_class_probabilities(self, data: np.ndarray) -> np.ndarray: """Converts log likelihoods from model into class probabilities. Returns: @@ -169,8 +169,49 @@ def predict_proba(self, data: np.ndarray) -> np.ndarray: denom = np.logaddexp(log_post_0, log_post_1) log_post_0 -= denom log_post_1 -= denom - posterior = np.exp(np.stack([log_post_0, log_post_1], axis=-1)) - return posterior + log_posterior = np.stack([log_post_0, log_post_1], axis=-1) + return log_posterior + + def evaluate_likelihood(self, data: np.ndarray) -> np.ndarray: + """ + Calculates log(p(e | l)) for each trial in the data. + p(e | l=1), p(e | l=0) + """ + if not self.ready_to_predict: + raise SignalException("must use model.fit() before model.predict_proba()") + + log_scores_class_0 = self.model.transform(data)[:, 0] + log_scores_class_1 = self.model.transform(data)[:, 1] + return np.stack([log_scores_class_0, log_scores_class_1], axis=-1) + + def predict(self, data: np.ndarray) -> np.ndarray: + """Predict the most likely label for each trial in the data. + + Returns: + predictions (np.ndarray): shape (num_items,) - the predicted label for each item. + """ + if not self.ready_to_predict: + raise SignalException("must use model.fit() before model.predict()") + + posterior = self.compute_class_probabilities(data) + predictions = np.argmax(posterior, axis=1) + return predictions + + def predict_proba(self, data: np.ndarray) -> np.ndarray: + """Converts log likelihoods from model into class probabilities. + + Returns: + posterior (np.ndarray): shape (num_items, 2) - for each item, the model's predicted + probability for the two labels. + """ + if not self.ready_to_predict: + raise SignalException("must use model.fit() before model.predict_proba()") + + # Model originally produces p(eeg | label). We want p(label | eeg): + # + # p(l=1 | e) = p(e | l=1) p(l=1) / p(e) + # log(p(l=1 | e)) = log(p(e | l=1)) + log(p(l=1)) - log(p(e)) + return self.compute_class_probabilities(data) def save(self, path: Path) -> None: """Save model weights (e.g. after training) to `path`""" diff --git a/bcipy/signal/process/extract_gaze.py b/bcipy/signal/process/extract_gaze.py index 6aa95d6fb..467f022ef 100644 --- a/bcipy/signal/process/extract_gaze.py +++ b/bcipy/signal/process/extract_gaze.py @@ -29,15 +29,21 @@ def extract_eye_info(data): left_eye = np.vstack((np.array(lx), np.array(ly))).T right_eye = np.vstack((np.array(rx), np.array(ry))).T - # Remove ALL blinks (i.e. Nan values) regardless of which eye it occurs. - # Make sure that the number of samples are the same for both eyes left_eye_nan_idx = np.isnan(left_eye).any(axis=1) - left_eye = left_eye[~left_eye_nan_idx] - right_eye = right_eye[~left_eye_nan_idx] - + deleted_samples = left_eye_nan_idx.sum() + all_samples = len(left_eye) + if deleted_samples: + # Apply padding instead of deleting samples: + for j in range(len(left_eye)): + if np.isnan(left_eye[j]).any(): + left_eye[j] = left_eye[j - 1] + + # Same for the right eye: right_eye_nan_idx = np.isnan(right_eye).any(axis=1) - left_eye = left_eye[~right_eye_nan_idx] - right_eye = right_eye[~right_eye_nan_idx] + if right_eye_nan_idx.sum() != 0: + for i in range(len(right_eye)): + if np.isnan(right_eye[i]).any(): + right_eye[i] = right_eye[i - 1] try: len(left_eye) != len(right_eye) @@ -45,4 +51,4 @@ def extract_eye_info(data): raise SignalException( 'Number of samples for left and right eye are not the same.') - return left_eye, right_eye + return left_eye, right_eye, left_pupil, right_pupil, deleted_samples, all_samples diff --git a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py index 4d5439ecc..7b2649552 100644 --- a/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py +++ b/bcipy/signal/tests/model/pca_rda_kde/test_pca_rda_kde.py @@ -228,7 +228,7 @@ def test_save_load(self): symbol_set = alphabet() inquiry = symbol_set[:n_trial] data = np.random.randn(self.num_channel, n_trial, self.dim_x) - output_before = self.model.predict(data=data, inquiry=inquiry, symbol_set=symbol_set) + output_before = self.model.compute_likelihood_ratio(data=data, inquiry=inquiry, symbol_set=symbol_set) checkpoint_path = self.tmp_dir / "model.pkl" save_model(self.model, checkpoint_path) @@ -237,7 +237,7 @@ def test_save_load(self): self.assertEqual(1, len(loaded_models)) other_model = loaded_models[0] self.assertEqual(self.model.k_folds, other_model.k_folds) - output_after = other_model.predict(data=data, inquiry=inquiry, symbol_set=symbol_set) + output_after = other_model.compute_likelihood_ratio(data=data, inquiry=inquiry, symbol_set=symbol_set) self.assertTrue(np.allclose(output_before, output_after)) @@ -249,7 +249,7 @@ def test_save_load(self): def test_predict_before_fit(self): model = PcaRdaKdeModel(k_folds=10) with self.assertRaises(SignalException): - model.predict(self.x, inquiry=["A"], symbol_set=alphabet()) + model.compute_likelihood_ratio(self.x, inquiry=["A"], symbol_set=alphabet()) def test_evaluate_before_fit(self): model = PcaRdaKdeModel(k_folds=10) diff --git a/bcipy/simulator/task/copy_phrase.py b/bcipy/simulator/task/copy_phrase.py index b672c7077..40f242f0a 100644 --- a/bcipy/simulator/task/copy_phrase.py +++ b/bcipy/simulator/task/copy_phrase.py @@ -133,8 +133,10 @@ def compute_device_evidence( # This assumes that sampling is independent. Changes to the sampler API are needed if # we need to provide the trial context of the last sample. sampled_data = sampler.sample_data(current_state) - evidence = model.predict(sampled_data, self.current_symbols(), - self.alp) + evidence = model.compute_class_probabilities( + sampled_data, + self.current_symbols(), + self.alp) evidence_type = get_evidence_type(model) evidences.append((evidence_type, evidence)) return evidences diff --git a/bcipy/task/control/evidence.py b/bcipy/task/control/evidence.py index 3cb7c1480..bb8a828eb 100644 --- a/bcipy/task/control/evidence.py +++ b/bcipy/task/control/evidence.py @@ -111,7 +111,74 @@ def evaluate(self, raw_data: np.ndarray, symbols: List[str], window_length - The length of the time between stimuli presentation """ data = self.preprocess(raw_data, times, target_info, window_length) - return self.signal_model.predict(data, symbols, self.symbol_set) + return self.signal_model.compute_likelihood_ratio(data, symbols, self.symbol_set) + + +class GazeEvaluator(EvidenceEvaluator): + """EvidenceEvaluator that extracts symbol likelihoods from raw gaze data. + + Parameters + ---------- + symbol_set: set of possible symbols presented + gaze_model: trained gaze model + """ + consumes = ContentType.EYETRACKER + produces = EvidenceType.EYE + + def __init__(self, symbol_set: List[str], signal_model: SignalModel): + super().__init__(symbol_set, signal_model) + + self.channel_map = analysis_channels(self.device_spec.channels, + self.device_spec) + self.transform = signal_model.metadata.transform + self.reshape = TrialReshaper() + + def preprocess(self, raw_data: np.ndarray, times: List[float], + target_info: List[str], window_length: float) -> np.ndarray: + """Preprocess the inquiry data. + + Parameters + ---------- + raw_data - C x L eeg data where C is number of channels and L is the + signal length + symbols - symbols displayed in the inquiry + times - timestamps associated with each symbol + target_info - target information about the stimuli; + ex. ['nontarget', 'nontarget', ...] + window_length - The length of the time between stimuli presentation + """ + transformed_data, transform_sample_rate = self.transform( + raw_data, self.device_spec.sample_rate) + + # The data from DAQ is assumed to have offsets applied + reshaped_data, _lbls = self.reshape(trial_targetness_label=target_info, + timing_info=times, + eeg_data=transformed_data, + sample_rate=transform_sample_rate, + channel_map=self.channel_map, + poststimulus_length=window_length) + return reshaped_data + + # pylint: disable=arguments-differ + def evaluate(self, raw_data: np.ndarray, symbols: List[str], + times: List[float], target_info: List[str], + window_length: float) -> np.ndarray: + """Evaluate the evidence. + + Parameters + ---------- + raw_data - C x L eeg data where C is number of channels and L is the + signal length + symbols - symbols displayed in the inquiry + times - timestamps associated with each symbol + target_info - target information about the stimuli; + ex. ['nontarget', 'nontarget', ...] + window_length - The length of the time between stimuli presentation + """ + data = self.preprocess(raw_data, times, target_info, window_length) + # We need the likelihoods in the form of p(label | gaze). predict returns the argmax of the likelihoods. + # Therefore we need predict_proba method to get the likelihoods. + return self.signal_model.evaluate_likelihood(data) # multiplication over the inquiry def get_evaluator( diff --git a/bcipy/task/control/handler.py b/bcipy/task/control/handler.py index 9ca1a6262..fbda582db 100644 --- a/bcipy/task/control/handler.py +++ b/bcipy/task/control/handler.py @@ -31,8 +31,9 @@ def update_and_fuse(self, dict_evidence): """ Updates the probability distribution Args: dict_evidence(dict{name: ndarray[float]}): dictionary of - evidences (EEG and other likelihoods) + evidences (EEG (likelihood ratios) and other likelihoods) """ + # {EEG: [], GAZE: ()} for key in dict_evidence.keys(): tmp = dict_evidence[key][:][:] @@ -45,6 +46,7 @@ def update_and_fuse(self, dict_evidence): if np.isinf(np.sum(self.likelihood)): tmp = np.zeros(len(self.likelihood)) tmp[np.where(self.likelihood == np.inf)[0][0]] = 1 + self.likelihood = tmp if not np.isnan(np.sum(self.likelihood)): diff --git a/bcipy/task/tests/core/test_eeg_evaluator.py b/bcipy/task/tests/core/test_eeg_evaluator.py index 21a594a1a..237394104 100644 --- a/bcipy/task/tests/core/test_eeg_evaluator.py +++ b/bcipy/task/tests/core/test_eeg_evaluator.py @@ -24,6 +24,7 @@ def setUp(self): meta_mock.device_spec = self.device_mock meta_mock.transform = self.transform_mock self.signal_model_mock.metadata = meta_mock + self.signal_model_mock.compute_likelihood_ratio = Mock() @patch('bcipy.task.control.evidence.analysis_channels') def test_init(self, analysis_channels_mock): @@ -77,7 +78,7 @@ def test_evaluate(self, reshaper_factory_mock, analysis_channels_mock): channel_map=channel_map, poststimulus_length=window_length) - self.signal_model_mock.predict.assert_called_once_with( + self.signal_model_mock.compute_likelihood_ratio.assert_called_once_with( reshaped_data, symbols, self.symbol_set) diff --git a/scripts/python/replay_session.py b/scripts/python/replay_session.py index 421d96a37..053f4abd2 100644 --- a/scripts/python/replay_session.py +++ b/scripts/python/replay_session.py @@ -20,7 +20,7 @@ from bcipy.helpers.stimuli import InquiryReshaper, update_inquiry_timing from bcipy.helpers.symbols import alphabet from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.signal.model import PcaRdaKdeModel +from bcipy.signal.model import PcaRdaKdeModel, SignalModel from bcipy.signal.process import (ERPTransformParams, filter_inquiries, get_default_transform) @@ -63,7 +63,7 @@ def generate_replay_outputs( tuple - new_model_outputs, old_model_target_output, old_model_nontarget_output """ k_folds = parameters.get("k_folds") - model = load_model(model_path, k_folds, model_class) + model: SignalModel = load_model(model_path, k_folds, model_class) logger.info(f"Loaded model from {model_path}") # get trial information; to make backwards compatible, we will try to get the trial length @@ -156,7 +156,7 @@ def generate_replay_outputs( for i, (inquiry_trials, this_inquiry_letters, this_inquiry_labels) in enumerate( zip(inquiry_worth_of_trials, inquiry_worth_of_letters, inquiry_labels) ): - response = model.predict(inquiry_trials, this_inquiry_letters, symbol_set=symbol_set) + response = model.compute_likelihood_ratio(inquiry_trials, this_inquiry_letters, symbol_set=symbol_set) if np.any(this_inquiry_labels == 1): index_of_target_trial = np.argwhere(this_inquiry_labels == 1)[0][0] target_letter = this_inquiry_letters[index_of_target_trial] diff --git a/setup.py b/setup.py index 4d4571e52..9c213b15b 100644 --- a/setup.py +++ b/setup.py @@ -132,4 +132,4 @@ def run(self): cmdclass={ 'upload': UploadCommand, }, -) +) \ No newline at end of file From 683dc5961f7ffe68c0455eb4843e9158b20f76b9 Mon Sep 17 00:00:00 2001 From: Tab Memmott Date: Tue, 5 Nov 2024 10:43:41 -0800 Subject: [PATCH 330/330] final lint! --- bcipy/signal/model/offline_analysis.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index 5f3787a21..ab9a5b3ff 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -564,7 +564,7 @@ def offline_analysis( def main(): """Main function for offline analysis client. - + Parses command line arguments and runs offline analysis. Command Line Arguments:

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window_length: float) -> np.ndarray: """Evaluate the evidence. Parameters diff --git a/bcipy/task/control/handler.py b/bcipy/task/control/handler.py index cd6d7fa29..56ec283dd 100644 --- a/bcipy/task/control/handler.py +++ b/bcipy/task/control/handler.py @@ -8,6 +8,7 @@ from bcipy.helpers.symbols import SPACE_CHAR, BACKSPACE_CHAR from bcipy.task.control.query import RandomStimuliAgent, StimuliAgent from bcipy.task.control.criteria import CriteriaEvaluator +from bcipy.task.data import EvidenceType log = logging.getLogger(__name__) @@ -64,7 +65,7 @@ def save_history(self) -> None: return @property - def latest_evidence(self) -> Dict[str, List[float]]: + def latest_evidence(self) -> Dict[EvidenceType, List[float]]: """Latest evidence of each type in the evidence history. Returns @@ -255,7 +256,7 @@ def prepare_stimuli(self) -> InquirySchedule: Return ------ - stimuli(tuple[list[char],list[float],list[str]]): tuple of + stimuli(tuple[list[str],list[float],list[str]]): tuple of stimuli information. [0]: letter, [1]: timing, [2]: color """ diff --git a/bcipy/task/data.py b/bcipy/task/data.py index 9a4bdb97a..bdf40695f 100644 --- a/bcipy/task/data.py +++ b/bcipy/task/data.py @@ -1,7 +1,7 @@ """Module for functionality related to session-related data.""" from collections import Counter from enum import Enum -from typing import Any, Dict, List, Optional +from typing import Any, Dict, List, Optional, Tuple EVIDENCE_SUFFIX = "_evidence" @@ -71,14 +71,14 @@ class Inquiry: def __init__(self, stimuli: List[str], timing: List[float], - triggers: List[List], + triggers: List[Tuple[str, float]], target_info: List[str], - target_letter: str = None, - current_text: str = None, - target_text: str = None, - selection: str = None, - next_display_state: str = None, - likelihood: List[float] = None): + target_letter: Optional[str] = None, + current_text: Optional[str] = None, + target_text: Optional[str] = None, + selection: Optional[str] = None, + next_display_state: Optional[str] = None, + likelihood: Optional[List[float]] = None) -> None: super().__init__() self.stimuli = stimuli self.timing = timing @@ -92,16 +92,16 @@ def __init__(self, self.evidences: Dict[EvidenceType, List[float]] = {} self.likelihood = likelihood or [] - # Precision used for serialization of evidence values. - self.precision = None + # Precision used for serialization of evidence values. By default, no precision. + self.precision: int = 0 @property - def lm_evidence(self): + def lm_evidence(self) -> List[float]: """Language model evidence""" return self.evidences.get(EvidenceType.LM, []) @property - def eeg_evidence(self): + def eeg_evidence(self) -> List[float]: """EEG evidence""" return self.evidences.get(EvidenceType.ERP, []) @@ -113,10 +113,12 @@ def decision_made(self) -> bool: @property def is_correct_decision(self) -> bool: """Indicates whether the current selection was the target""" - return self.selection and (self.selection == self.target_letter) + if self.selection and self.target_letter: + return self.selection == self.target_letter + return False @classmethod - def from_dict(cls, data: dict): + def from_dict(cls, data: dict) -> 'Inquiry': """Deserializes from a dict Parameters: @@ -206,18 +208,18 @@ class Session: def __init__(self, save_location: str, + symbol_set: List[str], task: str = 'Copy Phrase', mode: str = 'RSVP', - symbol_set: List[str] = None, - decision_threshold: float = None): + decision_threshold: Optional[float] = None) -> None: super().__init__() self.save_location = save_location self.task = task self.mode = mode self.series: List[List[Inquiry]] = [[]] - self.total_time_spent = 0 + self.total_time_spent: float = 0.0 self.time_spent_precision = 2 - self.task_summary = {} + self.task_summary: Dict[str, Any] = {} self.symbol_set = symbol_set self.decision_threshold = decision_threshold @@ -255,12 +257,12 @@ def has_evidence(self) -> bool: """Tests whether any inquiries have evidence.""" return any(inq.evidences for inq in self.all_inquiries) - def add_series(self): + def add_series(self) -> None: """Add another series unless the last one is empty""" if self.last_series(): self.series.append([]) - def add_sequence(self, inquiry: Inquiry, new_series: bool = False): + def add_sequence(self, inquiry: Inquiry, new_series: bool = False) -> None: """Append sequence information Parameters: @@ -324,7 +326,7 @@ def as_dict(self, return info @classmethod - def from_dict(cls, data: dict): + def from_dict(cls, data: dict) -> 'Session': """Deserialize from a dict. Parameters: diff --git a/bcipy/task/exceptions.py b/bcipy/task/exceptions.py index 3a686c874..7de570c24 100644 --- a/bcipy/task/exceptions.py +++ b/bcipy/task/exceptions.py @@ -1,3 +1,5 @@ +from typing import Any, Optional + class InsufficientDataException(Exception): """Insufficient Data Exception. @@ -5,7 +7,7 @@ class InsufficientDataException(Exception): Thrown when data requirements to execute task are violated. """ - def __init__(self, message, errors=None): + def __init__(self, message: str, errors: Optional[Any] = None) -> None: super().__init__(message) self.errors = errors @@ -16,7 +18,7 @@ class TaskRegistryException(Exception): Thrown when task type is unregistered. """ - def __init__(self, message, errors=None): + def __init__(self, message: str, errors: Optional[Any] = None) -> None: super().__init__(message) self.errors = errors diff --git a/bcipy/task/main.py b/bcipy/task/main.py index 0cbe132d6..b46af1d5c 100644 --- a/bcipy/task/main.py +++ b/bcipy/task/main.py @@ -9,17 +9,17 @@ class Task(ABC): Base class for BciPy tasks. """ - def __init__(self): + def __init__(self) -> None: super(Task, self).__init__() self.logger = logging.getLogger(__name__) - def configure(self): + @abstractmethod + def execute(self) -> str: ... @abstractmethod - def execute(self): + def name(self) -> str: ... - @abstractmethod - def name(self): + def configure(self) -> None: ... diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index 5c9147b8b..7c9b8b61c 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -1,12 +1,13 @@ from typing import List, Tuple -from psychopy import core +from psychopy import core, visual from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE -from bcipy.display import Display, InformationProperties, StimuliProperties +from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.helpers.clock import Clock +from bcipy.helpers.parameters import Parameters from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, InquirySchedule, StimuliOrder, TargetPositions, generate_calibration_inquiries) @@ -81,7 +82,7 @@ def __init__(self, win, daq, parameters, file_save): self.matrix = self.init_display() - def init_display(self) -> Display: + def init_display(self) -> MatrixDisplay: """Initialize the display""" return init_calibration_display_task(self.parameters, self.window, self.experiment_clock, @@ -240,7 +241,10 @@ def name(self): def init_calibration_display_task( - parameters, window, experiment_clock, symbol_set): + parameters: Parameters, + window: visual.Window, + experiment_clock: Clock, + symbol_set: core.StaticPeriod) -> MatrixDisplay: info = InformationProperties( info_color=[parameters['info_color']], info_pos=[(parameters['info_pos_x'], diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index f82c1ae70..b2f44da69 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -1,6 +1,6 @@ """Defines the Copy Phrase Task which uses a Matrix display""" -from bcipy.display import Display, InformationProperties, StimuliProperties +from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask @@ -36,13 +36,13 @@ class MatrixCopyPhraseTask(RSVPCopyPhraseTask): TASK_NAME = 'Matrix Copy Phrase Task' MODE = 'Matrix' - def init_display(self) -> Display: + def init_display(self) -> MatrixDisplay: """Initialize the Matrix display""" return init_display(self.parameters, self.window, self.experiment_clock, self.spelled_text) -def init_display(parameters, win, experiment_clock, starting_spelled_text): +def init_display(parameters, win, experiment_clock, starting_spelled_text) -> MatrixDisplay: """Constructs a new Matrix display""" info = InformationProperties( diff --git a/bcipy/task/paradigm/matrix/timing_verification.py b/bcipy/task/paradigm/matrix/timing_verification.py index 8d0d2fdee..ea5f9fa1d 100644 --- a/bcipy/task/paradigm/matrix/timing_verification.py +++ b/bcipy/task/paradigm/matrix/timing_verification.py @@ -1,7 +1,7 @@ from itertools import cycle from typing import List from bcipy.task.paradigm.matrix.calibration import ( - MatrixCalibrationTask, InquirySchedule, DEFAULT_TEXT_FIXATION, Display, + MatrixCalibrationTask, InquirySchedule, DEFAULT_TEXT_FIXATION, MatrixDisplay, init_calibration_display_task) from bcipy.helpers.stimuli import PhotoDiodeStimuli, jittered_timing @@ -23,7 +23,7 @@ class MatrixTimingVerificationCalibration(MatrixCalibrationTask): """ TASK_NAME = 'Matrix Timing Verification Task' - def init_display(self) -> Display: + def init_display(self) -> MatrixDisplay: """Initialize the display""" display = init_calibration_display_task( self.parameters, self.window, self.experiment_clock, diff --git a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py index 70262a2be..ba0446a35 100644 --- a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py +++ b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py @@ -1,3 +1,4 @@ +# mypy: disable-error-code="method-assign" from itertools import cycle from bcipy.task import Task from bcipy.task.paradigm.rsvp.calibration.calibration import RSVPCalibrationTask diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 4bb120d2a..7c25b0c87 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -1,12 +1,18 @@ +# mypy: disable-error-code="arg-type" import logging from typing import List, NamedTuple, Optional, Tuple -from psychopy import core - -from bcipy.config import (SESSION_DATA_FILENAME, SESSION_SUMMARY_FILENAME, - TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE) -from bcipy.display import (Display, InformationProperties, - PreviewInquiryProperties, StimuliProperties) +from psychopy import core, visual + +from bcipy.config import ( + SESSION_DATA_FILENAME, + SESSION_SUMMARY_FILENAME, + TRIGGER_FILENAME, + WAIT_SCREEN_MESSAGE, + DEFAULT_EVIDENCE_PRECISION) +from bcipy.display import (InformationProperties, + PreviewInquiryProperties, + StimuliProperties) from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay from bcipy.feedback.visual.visual_feedback import VisualFeedback @@ -14,6 +20,7 @@ from bcipy.helpers.copy_phrase_wrapper import CopyPhraseWrapper from bcipy.helpers.exceptions import TaskConfigurationException from bcipy.helpers.list import destutter +from bcipy.helpers.parameters import Parameters from bcipy.helpers.save import _save_session_related_data from bcipy.helpers.session import session_excel from bcipy.helpers.stimuli import InquirySchedule, StimuliOrder @@ -134,9 +141,8 @@ def __init__(self, win, daq, parameters, file_save, signal_models, self.fake = fake self.language_model = language_model - # TODO: remove this self.signal_model = signal_models[0] if signal_models else None - self.evidence_precision = 5 + self.evidence_precision = DEFAULT_EVIDENCE_PRECISION self.feedback = VisualFeedback( self.window, @@ -209,7 +215,7 @@ def setup(self) -> None: self.init_copy_phrase_task() self.current_inquiry = self.next_inquiry() - def init_display(self) -> Display: + def init_display(self) -> CopyPhraseDisplay: """Initialize the display""" return _init_copy_phrase_display(self.parameters, self.window, self.static_clock, @@ -297,7 +303,7 @@ def user_wants_to_continue(self) -> bool: self.logger.info('User wants to exit.') return should_continue - def wait(self, seconds: float = None): + def wait(self, seconds: Optional[float] = None): """Pause for a time. Parameters @@ -574,8 +580,8 @@ def compute_device_evidence( # currently prestim_length is used as a buffer for filter application post_stim_buffer = int(self.parameters.get("task_buffer_length") / 2) - prestim_buffer = self.parameters['prestim_length'] - trial_window = self.parameters['trial_window'] + prestim_buffer: float = self.parameters['prestim_length'] + trial_window: Tuple[float, float] = self.parameters['trial_window'] window_length = trial_window[1] - trial_window[0] inquiry_timing = self.stims_for_decision(stim_times) @@ -609,7 +615,7 @@ def compute_device_evidence( return evidences - def stims_for_decision(self, stim_times: List[List]) -> List[List]: + def stims_for_decision(self, stim_times: List[Tuple[str, float]]) -> List[Tuple[str, float]]: """The stim_timings from the display may include non-letter stimuli such as calibration and inquiry_preview timings. This method extracts only the letter data used to process the data for a decision. @@ -628,11 +634,11 @@ def stims_for_decision(self, stim_times: List[List]) -> List[List]: ] def new_data_record(self, - stim_times: List[List], + stim_times: List[Tuple[str, float]], target_stimuli: str, current_text: str, decision: Decision, - evidence_types: List[EvidenceType] = None) -> Inquiry: + evidence_types: Optional[List[EvidenceType]] = None) -> Inquiry: """Construct a new inquiry data record. Parameters @@ -797,7 +803,7 @@ def __init__(self, session: Session, show_preview: bool = False, preview_mode: int = 0, - trigger_path: str = None): + trigger_path: Optional[str] = None): assert preview_mode in range(3), 'Preview mode out of range' self.session = session self.show_preview = show_preview @@ -887,7 +893,12 @@ def switch_triggers(self) -> List[Trigger]: ] -def _init_copy_phrase_display(parameters, win, static_clock, experiment_clock, starting_spelled_text): +def _init_copy_phrase_display( + parameters: Parameters, + win: visual.Window, + static_clock: core.StaticPeriod, + experiment_clock: Clock, + starting_spelled_text) -> CopyPhraseDisplay: preview_inquiry = PreviewInquiryProperties( preview_only=parameters['preview_only'], preview_inquiry_length=parameters['preview_inquiry_length'], @@ -918,13 +929,14 @@ def _init_copy_phrase_display(parameters, win, static_clock, experiment_clock, s font=parameters['font'], height=parameters['task_height']) - return CopyPhraseDisplay(win, - static_clock, - experiment_clock, - stimuli, - task_bar, - info, - starting_spelled_text, - trigger_type=parameters['trigger_type'], - space_char=parameters['stim_space_char'], - preview_inquiry=preview_inquiry) + return CopyPhraseDisplay( + win, + static_clock, + experiment_clock, + stimuli, + task_bar, + info, + starting_spelled_text, + trigger_type=parameters['trigger_type'], + space_char=parameters['stim_space_char'], + preview_inquiry=preview_inquiry) diff --git a/bcipy/task/start_task.py b/bcipy/task/start_task.py index 264ca2a20..3a0c1bc25 100644 --- a/bcipy/task/start_task.py +++ b/bcipy/task/start_task.py @@ -1,4 +1,7 @@ """Code for constructing and executing registered tasks""" +from typing import List, Optional +from psychopy import visual + from bcipy.task import Task from bcipy.task.exceptions import TaskRegistryException from bcipy.task.paradigm.matrix.calibration import MatrixCalibrationTask @@ -12,9 +15,21 @@ from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask from bcipy.task.task_registry import TaskType +from bcipy.acquisition import ClientManager +from bcipy.helpers.parameters import Parameters +from bcipy.signal.model import SignalModel +from bcipy.language import LanguageModel + -def make_task(display_window, daq, task, parameters, file_save, - signal_models=None, language_model=None, fake=True) -> Task: +def make_task( + display_window: visual.Window, + daq: ClientManager, + task: TaskType, + parameters: Parameters, + file_save: str, + signal_models: Optional[List[SignalModel]] = None, + language_model: Optional[LanguageModel] = None, + fake: bool = True) -> Task: """Creates a Task based on the provided parameters. Parameters: @@ -61,9 +76,23 @@ def make_task(display_window, daq, task, parameters, file_save, 'The provided experiment type is not registered.') -def start_task(display_window, daq, task, parameters, file_save, - signal_models=None, language_model=None, fake=True): +def start_task( + display_window: visual.Window, + daq: ClientManager, + task: TaskType, + parameters: Parameters, + file_save: str, + signal_models: Optional[List[SignalModel]] = None, + language_model: Optional[LanguageModel] = None, + fake: bool = True) -> str: """Creates a Task and starts execution.""" - task = make_task(display_window, daq, task, parameters, file_save, - signal_models, language_model, fake) - task.execute() + bcipy_task = make_task( + display_window, + daq, + task, + parameters, + file_save, + signal_models, + language_model, + fake) + return bcipy_task.execute() diff --git a/bcipy/task/tests/core/test_data.py b/bcipy/task/tests/core/test_data.py index 5b44c7b5a..29e0d948f 100644 --- a/bcipy/task/tests/core/test_data.py +++ b/bcipy/task/tests/core/test_data.py @@ -4,6 +4,12 @@ from bcipy.task.data import EvidenceType, Inquiry, Session +SYMBOL_SET = [ + 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', + 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', + '<', '_' +] + def sample_stim_seq(include_evidence: bool = False): """Generates a sample Inquiry.""" @@ -129,14 +135,8 @@ def test_stim_sequence_deserialization(self): def test_stim_sequence_evidence(self): """Test simplified evidence view""" - alp = [ - 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', - 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', - '<', '_' - ] - stim_seq = sample_stim_seq(include_evidence=True) - evidence = stim_seq.stim_evidence(alp, n_most_likely=5) + evidence = stim_seq.stim_evidence(SYMBOL_SET, n_most_likely=5) self.assertEqual(len(evidence['most_likely']), 5) self.assertAlmostEqual(evidence['most_likely']['<'], 0.05, places=2) @@ -173,7 +173,8 @@ def test_is_correct_decision(self): def test_empty_session(self): """Test initial session creation""" - session = Session(save_location=".") + + session = Session(save_location=".", symbol_set=SYMBOL_SET) self.assertEqual(0, session.total_number_series) self.assertEqual(0, session.total_inquiries) self.assertEqual(0, session.total_number_decisions) @@ -188,7 +189,8 @@ def test_empty_session(self): def test_session(self): """Test session functionality""" - session = Session(save_location=".") + + session = Session(save_location=".", symbol_set=SYMBOL_SET) session.add_sequence(sample_stim_seq()) session.add_sequence(sample_stim_seq()) @@ -221,7 +223,7 @@ def test_session(self): def test_session_add_series(self): """Test session functionality for adding a series""" - session = Session(save_location=".") + session = Session(save_location=".", symbol_set=SYMBOL_SET) session.add_series() self.assertEqual(0, session.total_number_series) @@ -243,7 +245,7 @@ def test_session_add_series(self): def test_session_deserialization(self): """Test that a Session can be deserialized""" - session = Session(save_location=".") + session = Session(save_location=".", symbol_set=SYMBOL_SET) session.add_sequence(sample_stim_seq()) session.add_sequence(sample_stim_seq()) @@ -272,7 +274,7 @@ def test_session_deserialization(self): def test_task_summary(self): """Test that arbitrary data can be added.""" - session = Session(save_location=".") + session = Session(save_location=".", symbol_set=SYMBOL_SET) self.assertFalse('task_summary' in session.as_dict()) session.task_summary = {"typing_accuracy": 22} @@ -282,7 +284,7 @@ def test_task_summary(self): def test_has_evidence(self): """Test that a Session has evidence""" - session = Session(save_location=".") + session = Session(save_location=".", symbol_set=SYMBOL_SET) session.add_sequence(sample_stim_seq()) session.add_sequence(sample_stim_seq(include_evidence=True)) self.assertTrue(session.has_evidence()) diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 68fb1e794..e010e4fc2 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -2,6 +2,7 @@ import shutil import tempfile import unittest +import pytest from pathlib import Path import numpy as np @@ -22,6 +23,7 @@ from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask +@pytest.mark.slow class TestCopyPhrase(unittest.TestCase): """Tests for Copy Phrase task.""" diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase_task_summary.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase_task_summary.py index caf9db2dd..a98840db8 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase_task_summary.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase_task_summary.py @@ -8,6 +8,12 @@ from bcipy.task.data import EvidenceType, Inquiry, Session from bcipy.task.paradigm.rsvp.copy_phrase import TaskSummary +SYMBOL_SET = [ + 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', + 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', + '<', '_' +] + def mock_inquiry(target_letter="", current_text="", @@ -34,7 +40,7 @@ def mock_inquiry(target_letter="", def session_no_preview() -> Session: """Mock session""" - session = Session(".") + session = Session(".", symbol_set=SYMBOL_SET) seq1 = [{ 'target_letter': "E", @@ -73,7 +79,7 @@ def session_no_preview() -> Session: def session_btn() -> Session: """Mock session with button press evidence.""" - session = Session(".") + session = Session(".", symbol_set=SYMBOL_SET) seq1 = [{ 'selection': "", 'btn_evidence': True, diff --git a/dev_requirements.txt b/dev_requirements.txt index 6ad88a8fb..2ee6263fc 100644 --- a/dev_requirements.txt +++ b/dev_requirements.txt @@ -1,6 +1,8 @@ autopep8==1.6.0 coverage>=6.0 flake8==5.0.4 +mypy==1.6.1 +lxml mock mockito pylint diff --git a/mypy.ini b/mypy.ini new file mode 100644 index 000000000..8015d10e0 --- /dev/null +++ b/mypy.ini @@ -0,0 +1,11 @@ +# Global options: +[mypy] +warn_return_any = False +warn_unused_configs = False +ignore_missing_imports = True +follow_imports = skip +strict_optional = True +disallow_incomplete_defs = False +check_untyped_defs = True +no_implicit_optional = True +exclude = tests|demo|gui|scripts|acquisition|display.paradigm|language|signal.model|task.control|helpers.parameters diff --git a/pytest.ini b/pytest.ini index 761785364..95697f21b 100644 --- a/pytest.ini +++ b/pytest.ini @@ -1,3 +1,3 @@ [pytest] markers = - slow: marks tests as slow (deselect with '-m "not slow"') + slow: marks tests as slow (deselect with '-m "not slow"') \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index fd04a9186..22d14f0cc 100644 --- a/requirements.txt +++ b/requirements.txt @@ -2,9 +2,8 @@ attrdict3==2.0.2 transformers==4.26.0 torch==2.0.0 construct==2.8.14 -mne==1.0.2 +mne==1.5.0 pyo==1.0.5 -pygame==2.1.2 pyglet<=1.5.27,>=1.4 PsychoPy==2023.2.1 openpyxl==3.1.2 From f4faea16d0edbbd4bfba1480509f7a823cb5bbeb Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 19 Nov 2023 19:54:43 -0500 Subject: [PATCH 166/330] prettier logging --- bcipy/simulator/helpers/log_utils.py | 18 ++++++++++++++++++ bcipy/simulator/helpers/sampler.py | 3 ++- bcipy/simulator/helpers/signal_helpers.py | 2 +- bcipy/simulator/sim.py | 5 +++-- bcipy/simulator/tests/sampler_test.py | 18 ++++++------------ 5 files changed, 30 insertions(+), 16 deletions(-) create mode 100644 bcipy/simulator/helpers/log_utils.py diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py new file mode 100644 index 000000000..8e91d5110 --- /dev/null +++ b/bcipy/simulator/helpers/log_utils.py @@ -0,0 +1,18 @@ +from typing import List + +import pandas as pd + + +def format_alp_likelihoods(likelihoods, alp): + rounded = [round(lik, 3) for lik in likelihoods] + formatted = [f"{a} : {l}" for a, l in zip(alp, rounded)] + return formatted + + +def format_sample_rows(sample_rows: List[pd.Series]): + formatted_rows = [] + for row in sample_rows: + new_row = row.drop(columns=['eeg'], axis=1, inplace=False) + formatted_rows.append(new_row.to_string(index=False, header=True)) + + return ", ".join(formatted_rows) diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 4b3f6fb06..de3e217dc 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -9,6 +9,7 @@ from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import RawDataEngine +from bcipy.simulator.helpers.log_utils import format_sample_rows from bcipy.simulator.interfaces import SimState log = logging.getLogger(__name__) @@ -55,7 +56,7 @@ def sample(self, state: SimState) -> np.ndarray: row = filtered_data.sample(1) sample_rows.append(row) - log.debug(f"EEG Samples: \n {', '.join([r.to_string() for r in sample_rows])}") + log.debug(f"EEG Samples: \n {format_sample_rows(sample_rows)}") eeg_responses = [r['eeg'].to_numpy()[0] for r in sample_rows] sample = self.model_input_reshaper(eeg_responses) diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index df3d7c738..0fa530683 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -118,4 +118,4 @@ def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshape # define the training classes using integers, where 0=nontargets/1=targets # labels = inquiry_labels.flatten() - return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, (trigger_targetness, trigger_timing, trigger_symbols)) + return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, (trigger_targetness, trigger_timing, trigger_symbols)) \ No newline at end of file diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index a7a0f36e6..55aa38491 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -12,6 +12,7 @@ from bcipy.simulator.helpers.sampler import Sampler from bcipy.simulator.helpers.state_manager import StateManager, SimState from bcipy.simulator.helpers.types import InquiryResult +from bcipy.simulator.helpers.log_utils import format_alp_likelihoods from bcipy.simulator.interfaces import MetricReferee, ModelHandler from bcipy.simulator.simulator_base import Simulator @@ -72,11 +73,11 @@ def run(self): evidence = self.model_handler.generate_evidence(curr_state, sampled_data) # TODO make this evidence be a dict (mapping of evidence type to evidence) - log.debug(f"Evidence for stimuli {curr_state.display_alphabet} \n {evidence}") + log.debug(f"Evidence for stimuli {curr_state.display_alphabet} \n {format_alp_likelihoods(evidence, self.symbol_set)}") inq_record: InquiryResult = self.state_manager.update(evidence) updated_state = self.state_manager.get_state() - log.debug(f"Fused Likelihoods {[str(round(p, 3)) for p in inq_record.fused_likelihood]}") + log.debug(f"Fused Likelihoods {format_alp_likelihoods(inq_record.fused_likelihood, self.symbol_set)}") if inq_record.decision: log.info(f"Decided {inq_record.decision} for target {inq_record.target}") diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index 1e8233fca..7558be370 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -38,13 +38,15 @@ class DummyRef(MetricReferee): if __name__ == "__main__": args = dict() - args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_18hr58min16sec_-0700", - # "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_19hr07min50sec_-0700", - # "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Copy_Phrase_Thu_24_Aug_2023_19hr15min29sec_-0700" + args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700", + "/Users/srikarananthoju/cambi/tab_test_dynamic/50sec_-0700", + # "/Users/srikarananthoju/cambi/tab_test_dynamic/29sec_-0700" ] args['out_dir'] = Path(__file__).resolve().parent model_file = Path( - "/Users/srikarananthoju/cambi/tab_test_dynamic/tab_test_dynamic_RSVP_Calibration_Thu_24_Aug_2023_18hr41min37sec_-0700/model_0.9524_200_800.pkl") + "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/model_0.9524_200_800.pkl" + # "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/model_0.9595.pkl" + ) sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) data_engine = RawDataEngine(args['data_folders']) @@ -58,14 +60,6 @@ class DummyRef(MetricReferee): sampler: Sampler = SimpleLetterSampler(data_engine) sample: np.ndarray = sampler.sample(stateManager.get_state()) - # model = PcaRdaKdeModel() - # model = model.load(model_file) - # - # eeg_evidence = model.predict(sample, stateManager.get_state().display_alphabet, alphabet()) - # - # print(eeg_evidence.shape) - # print(eeg_evidence) - model_handler = DummyModelHandler(model_file) sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, DummyRef()) sim.run() From 4244299746a2569a91c762a47340951f7ed4cd92 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 17 Nov 2023 11:02:20 -0800 Subject: [PATCH 167/330] New parameter for vep animation time --- bcipy/parameters/parameters.json | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index c1fe3cb0b..90eb22511 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -367,6 +367,14 @@ "recommended_values": "", "type": "float" }, + "time_vep_animation": { + "value": "1.0", + "section": "bci_config", + "readableName": "Time VEP Animation (sec)", + "helpTip": "The amount of time in seconds for the animation moving symbols to boxes.", + "recommended_values": "", + "type": "float" + }, "stim_jitter": { "value": "0.0", "section": "bci_config", From edc17ad8a79b08e37dfd727096c5ba1c31ba9c6e Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 17 Nov 2023 11:05:00 -0800 Subject: [PATCH 168/330] Revert "New parameter for vep animation time" This reverts commit 437572ace09eb107aa09966e5a8360673131ea4d. --- bcipy/parameters/parameters.json | 8 -------- 1 file changed, 8 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 90eb22511..c1fe3cb0b 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -367,14 +367,6 @@ "recommended_values": "", "type": "float" }, - "time_vep_animation": { - "value": "1.0", - "section": "bci_config", - "readableName": "Time VEP Animation (sec)", - "helpTip": "The amount of time in seconds for the animation moving symbols to boxes.", - "recommended_values": "", - "type": "float" - }, "stim_jitter": { "value": "0.0", "section": "bci_config", From df3673d19f1cf7c8aab06dde55e8c4700693f8d3 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 20 Nov 2023 14:55:20 -0800 Subject: [PATCH 169/330] Added configuration for VEP codes --- bcipy/display/paradigm/vep/codes.py | 3 +++ bcipy/display/paradigm/vep/display.py | 9 +++++++-- bcipy/parameters/parameters.json | 8 ++++++++ bcipy/task/paradigm/vep/calibration.py | 8 +++++++- 4 files changed, 25 insertions(+), 3 deletions(-) diff --git a/bcipy/display/paradigm/vep/codes.py b/bcipy/display/paradigm/vep/codes.py index ae54af88f..41e75699c 100644 --- a/bcipy/display/paradigm/vep/codes.py +++ b/bcipy/display/paradigm/vep/codes.py @@ -27,6 +27,9 @@ def ssvep_to_code(refresh_rate: int = 60, flicker_rate: int = 10) -> List[int]: Converts a SSVEP (steady state visual evoked potential; ex. 10 Hz) to a code (0,1) given the refresh rate of the monitor (Hz) provided and a desired flicker rate (Hz). + TODO: https://www.pivotaltracker.com/story/show/186522657 + Consider an additional parameter for the number of seconds. + Parameters: ----------- refresh_rate: int, refresh rate of the monitor (Hz) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 82ccbd0da..5e7cfed65 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -108,7 +108,6 @@ def __init__(self, if not codes: codes = create_vep_codes(length=self.refresh_rate, count=self.vep_type) - self.logger.info(f"VEP Codes: {codes}") vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] vep_stim_size = scaled_size(0.24, self.window_size) @@ -179,7 +178,7 @@ def do_inquiry(self) -> List[StimTime]: # type: ignore [_fixation, *stim] = self.stim_properties() self.set_stimuli_colors(stim) - # self.do_fixation(fixation) + self.log_inquiry(stim) self.animate_inquiry(stim) core.wait(self.timing_fixation) self.stimulate() @@ -206,6 +205,8 @@ def prompt_target(self, target - (symbol, duration, color) tuple """ assert isinstance(target.symbol, str), "Target must be a str" + self.logger.info(f"Target: {target.symbol}") + # Show all symbols in the matrix at reduced opacity for sym in self.symbol_set: pos_index = self.sort_order(sym) @@ -237,6 +238,10 @@ def prompt_target(self, self.window.flip() core.wait(target.duration / 2) + def log_inquiry(self, stimuli: List[StimProps]) -> None: + """Log the inquiry""" + self.logger.info(f"Inquiry: {[stim.symbol for stim in stimuli]}") + def highlight_target_box(self, target_box_index: int) -> None: """Emphasize the box at the given index""" for i, box in enumerate(self.text_boxes): diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 90eb22511..6c4565c2a 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -375,6 +375,14 @@ "recommended_values": "", "type": "float" }, + "vep_flicker_rates": { + "value": "4,5,6,10,12,15", + "section": "bci_config", + "readableName": "VEP Flicker Rates (hz)", + "helpTip": "Delimited list of flash rates, where a rate represents the hz of the box at that position. Each rate should be less than the refresh rate of the monitor.", + "recommended_values": "4,5,6,10,12,15", + "type": "str" + }, "stim_jitter": { "value": "0.0", "section": "bci_config", diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 86c82a307..94945c753 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -8,6 +8,7 @@ from bcipy.display import InformationProperties, VEPStimuliProperties from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.vep.codes import ssvep_to_code from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock @@ -241,12 +242,17 @@ def init_calibration_display(parameters: Parameters, colors=[parameters['task_color']], font=parameters['font'], height=parameters['task_height']) - + flicker_rates = parameters['vep_flicker_rates'] + codes = [ + ssvep_to_code(refresh_rate=60, flicker_rate=hz) + for hz in flicker_rates + ] return VEPDisplay(window, experiment_clock, stim_props, task_bar, info, symbol_set=symbol_set, + codes=codes, box_config=box_config, should_prompt_target=True) From 0418f6490e504d5baeb4777ed3bece4d0f924c38 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 20 Nov 2023 14:55:36 -0800 Subject: [PATCH 170/330] Added configuration for VEP codes --- .../display/demo/vep/demo_calibration_vep.py | 39 +++++-------------- 1 file changed, 9 insertions(+), 30 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index f1289285c..57bc1e2a8 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -7,6 +7,7 @@ init_display_window) from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.paradigm.vep.codes import ssvep_to_code from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock @@ -46,36 +47,14 @@ 'green', 'red', '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', '#FF8232' ] -codes = [[ - 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, - 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, - 0, 1, 0, 0, 1, 1, 1, 0, 1, 0 -], - [ - 0, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, - 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, - 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0 -], - [ - 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, - 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, - 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 0 -], - [ - 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, - 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, - 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1 -], - [ - 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, - 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, - 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1 -], - [ - 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, - 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, - 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0 -]] + +# Note: these rates work for a 60hz display +flicker_rates = [4, 5, 6, 10, 12, 15] +codes = [ + ssvep_to_code(refresh_rate=60, flicker_rate=hz) + for hz in flicker_rates +] + layout = centered(width_pct=0.95, height_pct=0.80) box_config = BoxConfiguration(layout, num_boxes=num_boxes, height_pct=0.30) From 6e9f3443ff37a676debb223a82a8741615fa9f71 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 20 Nov 2023 17:32:20 -0800 Subject: [PATCH 171/330] Fixed issues with refresh rates --- bcipy/display/paradigm/vep/codes.py | 13 +++++++++++++ bcipy/display/paradigm/vep/display.py | 5 +++-- bcipy/display/tests/vep/test_codes.py | 8 +++++++- bcipy/task/paradigm/vep/calibration.py | 9 ++++++--- 4 files changed, 29 insertions(+), 6 deletions(-) diff --git a/bcipy/display/paradigm/vep/codes.py b/bcipy/display/paradigm/vep/codes.py index 41e75699c..14b9fdeee 100644 --- a/bcipy/display/paradigm/vep/codes.py +++ b/bcipy/display/paradigm/vep/codes.py @@ -63,3 +63,16 @@ def ssvep_to_code(refresh_rate: int = 60, flicker_rate: int = 10) -> List[int]: t = 1 - t return codes + + +def round_refresh_rate(rate: float) -> int: + """Round the given display rate to the nearest 10s value. + + >>> round_refresh_rate(59.12) + 60 + >>> round_refresh_rate(61.538) + 60 + >>> round_refresh_rate(121.23) + 120 + """ + return int(round(rate, -1)) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 5e7cfed65..6f7c3bba4 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -11,7 +11,8 @@ from bcipy.display.components.layout import scaled_size from bcipy.display.components.task_bar import TaskBar from bcipy.display.paradigm.matrix.layout import symbol_positions -from bcipy.display.paradigm.vep.codes import create_vep_codes +from bcipy.display.paradigm.vep.codes import (create_vep_codes, + round_refresh_rate) from bcipy.display.paradigm.vep.layout import BoxConfiguration, animation_path from bcipy.display.paradigm.vep.vep_stim import VEPStim from bcipy.helpers.clock import Clock @@ -52,7 +53,7 @@ def __init__(self, frame_rate = self.window.getActualFrameRate() assert frame_rate, 'An accurate window frame rate could not be established' self.window_size = self.window.size # [w, h] - self.refresh_rate = round(frame_rate) + self.refresh_rate = round_refresh_rate(frame_rate) self.logger = logging.getLogger(__name__) # number of VEP text areas diff --git a/bcipy/display/tests/vep/test_codes.py b/bcipy/display/tests/vep/test_codes.py index 56f399796..cd0584dbb 100644 --- a/bcipy/display/tests/vep/test_codes.py +++ b/bcipy/display/tests/vep/test_codes.py @@ -1,6 +1,6 @@ import unittest -from bcipy.display.paradigm.vep.codes import ssvep_to_code +from bcipy.display.paradigm.vep.codes import round_refresh_rate, ssvep_to_code from bcipy.helpers.exceptions import BciPyCoreException @@ -61,6 +61,12 @@ def test_insufficient_flicker_rate(self): with self.assertRaises(BciPyCoreException): ssvep_to_code(refresh_rate, flicker_rate) + def test_round_rate(self): + """Test rounding the refresh rate""" + self.assertEqual(60, round_refresh_rate(59.12)) + self.assertEqual(60, round_refresh_rate(61.538)) + self.assertEqual(120, round_refresh_rate(121.23)) + if __name__ == '__main__': unittest.main() diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 94945c753..29030bbe6 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -8,7 +8,7 @@ from bcipy.display import InformationProperties, VEPStimuliProperties from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar -from bcipy.display.paradigm.vep.codes import ssvep_to_code +from bcipy.display.paradigm.vep.codes import round_refresh_rate, ssvep_to_code from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock @@ -242,9 +242,12 @@ def init_calibration_display(parameters: Parameters, colors=[parameters['task_color']], font=parameters['font'], height=parameters['task_height']) - flicker_rates = parameters['vep_flicker_rates'] + + # create codes from configuration + flicker_rates = parameters['vep_flicker_rates'].split(',') + rate = round_refresh_rate(window.getActualFrameRate()) codes = [ - ssvep_to_code(refresh_rate=60, flicker_rate=hz) + ssvep_to_code(refresh_rate=rate, flicker_rate=int(hz)) for hz in flicker_rates ] return VEPDisplay(window, From cfb4cc7605c847bd7f9324b09c3734715107700f Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 1 Dec 2023 12:30:06 -0800 Subject: [PATCH 172/330] #186539510 ; added parameter for task bar padding; fixed bug in matrix symbol positions; updated demos for matrix and task bar layouts. --- bcipy/display/components/task_bar.py | 26 ++++++++++---- bcipy/display/demo/components/demo_layouts.py | 10 ++++-- .../display/demo/components/demo_task_bar.py | 9 +++-- .../demo/matrix/demo_copyphrase_matrix.py | 7 ++-- .../display/demo/matrix/demo_matrix_layout.py | 36 +++++++++++-------- bcipy/display/paradigm/matrix/layout.py | 34 ++++++++++++++---- bcipy/parameters/parameters.json | 12 ++++++- bcipy/task/paradigm/matrix/calibration.py | 4 ++- bcipy/task/paradigm/matrix/copy_phrase.py | 4 ++- .../paradigm/rsvp/calibration/calibration.py | 3 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 15 ++++---- 11 files changed, 110 insertions(+), 50 deletions(-) diff --git a/bcipy/display/components/task_bar.py b/bcipy/display/components/task_bar.py index 3d490faf6..654acd859 100644 --- a/bcipy/display/components/task_bar.py +++ b/bcipy/display/components/task_bar.py @@ -1,6 +1,6 @@ """Task bar component""" -from typing import Optional, Dict, List +from typing import Dict, List, Optional from psychopy import visual from psychopy.visual.basevisual import BaseVisualStim @@ -19,6 +19,8 @@ class TaskBar: font - Font to apply to all task stimuli height - Height of all task text stimuli text - Task text to apply to stimuli + padding - used in conjunction with the text height to compute the + overall height of the task bar. """ def __init__(self, @@ -26,19 +28,31 @@ def __init__(self, colors: Optional[List[str]] = None, font: str = 'Courier New', height: float = 0.1, - text: str = ''): + text: str = '', + padding: Optional[float] = None): self.win = win self.colors = colors or ['white'] self.font = font self.height = height + self.padding = (height / 2) if padding is None else padding self.text = text self.layout = layout.at_top(win, self.compute_height()) self.stim = self.init_stim() + @property + def height_pct(self) -> float: + """Percentage of the total window that the task bar occupies. + + Returns + ------- + percentage ; value will be between 0 and 1. + """ + win_layout = layout.Layout(self.win) + return self.compute_height() / win_layout.height + def compute_height(self): """Computes the component height using the provided config.""" - padding = 0.05 # determined by trial and error - return self.height + padding + return self.height + self.padding def init_stim(self) -> Dict[str, BaseVisualStim]: """Initialize the stimuli elements.""" @@ -56,6 +70,7 @@ def update(self, text: str = ''): def border_stim(self) -> visual.Line: """Create the task bar outline""" + # pylint: disable=not-callable return visual.Line( win=self.win, units=self.layout.units, @@ -146,10 +161,9 @@ def __init__(self, def compute_height(self): """Computes the component height using the provided config.""" - padding = 0.05 # determined by trial and error # height is doubled to account for task_text and spelled_text being on # separate lines. - return (self.height * 2) + padding + return (self.height * 2) + self.padding def init_stim(self) -> Dict[str, BaseVisualStim]: """Initialize the stimuli elements.""" diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index 234107fb4..b33ce06d4 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -2,7 +2,7 @@ import logging import sys import time -from typing import Optional, Callable, List, Tuple, Union +from typing import Callable, List, Optional, Tuple, Union from psychopy import visual from psychopy.visual.circle import Circle @@ -262,8 +262,11 @@ def demo_matrix_positions(win: visual.Window): dimensions as well as the number of rows and columns affects positioning. """ # norm_layout = centered(parent=win, width_pct=1., height_pct=0.5) - norm_layout = centered(parent=win, width_pct=0.75, height_pct=1) - positions = symbol_positions(norm_layout, rows=5, columns=6) + task_bar = at_top(parent=win, height=0.25) + win_layout = Layout(win) + + norm_layout = centered(parent=win, width_pct=0.7, height_pct=0.75) + positions = symbol_positions(norm_layout, rows=6, columns=6) for sym, pos in zip(alphabet(), positions): stim = visual.TextStim(win, @@ -272,6 +275,7 @@ def demo_matrix_positions(win: visual.Window): color='white', height=0.17) stim.draw() + draw_boundary(win, task_bar, line_px=5, color='green') draw_boundary(win, norm_layout, line_px=5, color='gray') draw_positions(win, positions, size=scaled_size(0.025, win.size)) win.flip() diff --git a/bcipy/display/demo/components/demo_task_bar.py b/bcipy/display/demo/components/demo_task_bar.py index 9eb48a21f..cd06ced78 100644 --- a/bcipy/display/demo/components/demo_task_bar.py +++ b/bcipy/display/demo/components/demo_task_bar.py @@ -1,6 +1,7 @@ """Demo for the task bar component""" import time from typing import Callable + from psychopy import visual from bcipy.display.components.task_bar import (CalibrationTaskBar, @@ -40,7 +41,9 @@ def demo_copy_phrase(win: visual.Window): task_bar = CopyPhraseTaskBar(win, task_text='HELLO_WORLD', spelled_text='HELLO', - colors=['white', 'green']) + font='Overpass Mono Medium', + colors=['white', 'green'], + padding=0.05) task_bar.draw() win.flip() @@ -80,5 +83,5 @@ def run(demo: Callable[[visual.Window], None], seconds=30): if __name__ == '__main__': # run(demo_calibration) - # run(demo_copy_phrase) - run(demo_task_bar) + run(demo_copy_phrase) + # run(demo_task_bar) diff --git a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py index dca9c7e2c..866b73076 100644 --- a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py +++ b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py @@ -10,18 +10,19 @@ from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay +font = "Overpass Mono Medium" info = InformationProperties( info_color=['White'], info_pos=[(-.5, -.75)], info_height=[0.1], - info_font=['Arial'], + info_font=[font], info_text=['Matrix Copy Phrase Demo'], ) task_height = 0.1 inter_stim_buffer = .5 -stim_properties = StimuliProperties(stim_font='Arial', +stim_properties = StimuliProperties(stim_font=font, stim_pos=(-0.6, 0.4), stim_height=0.17, is_txt_stim=True) @@ -70,7 +71,7 @@ task_text='COPY_PHRASE', spelled_text='COPY_PHA', colors=['white', 'green'], - font='Menlo') + font=font) display = MatrixDisplay(win, experiment_clock, diff --git a/bcipy/display/demo/matrix/demo_matrix_layout.py b/bcipy/display/demo/matrix/demo_matrix_layout.py index 061b24803..72249743b 100644 --- a/bcipy/display/demo/matrix/demo_matrix_layout.py +++ b/bcipy/display/demo/matrix/demo_matrix_layout.py @@ -5,16 +5,18 @@ import bcipy.display.components.layout as layout from bcipy.display import (InformationProperties, StimuliProperties, init_display_window) -from bcipy.display.components.task_bar import CalibrationTaskBar +from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay -from bcipy.helpers.symbols import qwerty_order +# from bcipy.helpers.symbols import qwerty_order + +font = 'Overpass Mono Medium' # Initialize Stimulus window_parameters = { - 'full_screen': False, + 'full_screen': True, 'window_height': 500, 'window_width': 700, - 'stim_screen': 0, + 'stim_screen': 1, 'background_color': 'black' } @@ -22,21 +24,24 @@ win = init_display_window(window_parameters) win.recordFrameIntervals = False -task_bar = CalibrationTaskBar(win, - inquiry_count=5, - current_index=0, - font='Arial') +task_bar = CopyPhraseTaskBar(win, + task_text='HELLO_WORLD', + spelled_text='HELLO', + font=font, colors=['green'], + height=0.1, padding=0.15) + +matrix_height_pct = 1 - (2 * task_bar.height_pct) -stim_properties = StimuliProperties(stim_font='Arial', +stim_properties = StimuliProperties(stim_font=font, stim_pos=[], - stim_height=0.17, + stim_height=0.5, is_txt_stim=True) info = InformationProperties( info_color=['white'], info_pos=[layout.at_bottom(win, height=0.21).center], info_height=[0.1], - info_font=['Arial'], + info_font=[font], info_text=['Matrix Calibration Demo'], ) @@ -45,10 +50,11 @@ stim_properties, task_bar=task_bar, info=info, - rows=3, - columns=10, - width_pct=0.9, - sort_order=qwerty_order(is_txt_stim=True)) + rows=4, + columns=7, + width_pct=0.7, + height_pct=matrix_height_pct) +# sort_order=qwerty_order(is_txt_stim=True)) matrix_display.draw(grid_opacity=matrix_display.full_grid_opacity, grid_color=matrix_display.grid_color, diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index 0261b677c..cf5878aab 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -1,6 +1,6 @@ """Functions for calculating matrix layouts""" import logging -from typing import Optional, List, Tuple +from typing import List, Optional, Tuple from bcipy.display.components.layout import (Layout, above, below, left_of, right_of, scaled_height, @@ -30,19 +30,39 @@ def symbol_positions(container: Layout, rows: int, assert rows >= 1 and columns >= 1, "There must be at least one row and one column" # compute the spacing (in container units) from the container width and height + win_size = container.parent.size + win_width, win_height = win_size + horizontal_spacing = container.width / (columns + 1) vertical_spacing = container.height / (rows + 1) + # determine which is smaller after scaling to the window aspect ratio + if (win_width > win_height): + # wider than tall + scaled_horizontal_spacing = scaled_height(horizontal_spacing, win_size) + scaled_vertical_spacing = vertical_spacing + elif (win_height > win_width): + # taller than wide + scaled_horizontal_spacing = horizontal_spacing + scaled_vertical_spacing = scaled_width(vertical_spacing, win_size) + else: + # square window + scaled_horizontal_spacing = horizontal_spacing + scaled_vertical_spacing = vertical_spacing + + print( + f"horizontal_spacing: {horizontal_spacing}; vertical_spacing: {vertical_spacing}" + ) + print(f"scaled_horizontal_spacing: {scaled_horizontal_spacing}; scaled_vertical_spacing: {scaled_vertical_spacing}") if max_spacing and vertical_spacing > max_spacing: vertical_spacing = max_spacing - # Use the minimum spacing - if horizontal_spacing < vertical_spacing: - vertical_spacing = scaled_height(horizontal_spacing, - container.parent.size) + if scaled_horizontal_spacing < scaled_vertical_spacing: + vertical_spacing = scaled_height(horizontal_spacing, win_size) + print(f"Setting vertical spacing to {vertical_spacing}") else: - horizontal_spacing = scaled_width(vertical_spacing, - container.parent.size) + horizontal_spacing = scaled_width(vertical_spacing, win_size) + print(f"Setting horizontal spacing to {horizontal_spacing}") # Work back from center to compute the starting position center_x, center_y = container.center diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index c1fe3cb0b..5c72ac995 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -392,7 +392,7 @@ "type": "float" }, "font": { - "value": "Consolas", + "value": "Overpass Mono Medium", "section": "bci_config", "readableName": "Font", "helpTip": "Specifies the font used for all text stimuli. Default: Consolas", @@ -523,6 +523,16 @@ "recommended_values": "", "type": "str" }, + "task_padding": { + "value": "0.05", + "section": "bci_config", + "readableName": "Task Bar Padding", + "helpTip": "Specifies the padding around the task bar text. Default: 0.1", + "recommended_values": [ + "0.05" + ], + "type": "float" + }, "stim_number": { "value": "100", "section": "bci_config", diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index 7c9b8b61c..628466b2c 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -267,7 +267,8 @@ def init_calibration_display_task( current_index=0, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height']) + height=parameters['task_height'], + padding=parameters['task_padding']) return MatrixDisplay( window, @@ -278,5 +279,6 @@ def init_calibration_display_task( rows=parameters['matrix_rows'], columns=parameters['matrix_columns'], width_pct=parameters['matrix_width'], + height_pct=1 - (2 * task_bar.height_pct), trigger_type=parameters['trigger_type'], symbol_set=symbol_set) diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index b2f44da69..f18a44559 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -65,7 +65,8 @@ def init_display(parameters, win, experiment_clock, starting_spelled_text) -> Ma spelled_text=starting_spelled_text, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height']) + height=parameters['task_height'], + padding=parameters['task_padding']) return MatrixDisplay( win, @@ -76,5 +77,6 @@ def init_display(parameters, win, experiment_clock, starting_spelled_text) -> Ma rows=parameters['matrix_rows'], columns=parameters['matrix_columns'], width_pct=parameters['matrix_width'], + height_pct=1 - (2 * task_bar.height_pct), trigger_type=parameters['trigger_type'], should_prompt_target=False) diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 23aa220b1..475f30755 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -255,7 +255,8 @@ def init_calibration_display_task( current_index=0, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height']) + height=parameters['task_height'], + padding=parameters['task_padding']) preview_inquiry = PreviewInquiryProperties( preview_only=True, diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 7c25b0c87..7f4c0d976 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -4,14 +4,10 @@ from psychopy import core, visual -from bcipy.config import ( - SESSION_DATA_FILENAME, - SESSION_SUMMARY_FILENAME, - TRIGGER_FILENAME, - WAIT_SCREEN_MESSAGE, - DEFAULT_EVIDENCE_PRECISION) -from bcipy.display import (InformationProperties, - PreviewInquiryProperties, +from bcipy.config import (DEFAULT_EVIDENCE_PRECISION, SESSION_DATA_FILENAME, + SESSION_SUMMARY_FILENAME, TRIGGER_FILENAME, + WAIT_SCREEN_MESSAGE) +from bcipy.display import (InformationProperties, PreviewInquiryProperties, StimuliProperties) from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.paradigm.rsvp.mode.copy_phrase import CopyPhraseDisplay @@ -927,7 +923,8 @@ def _init_copy_phrase_display( spelled_text=starting_spelled_text, colors=[parameters['task_color']], font=parameters['font'], - height=parameters['task_height']) + height=parameters['task_height'], + padding=parameters['task_padding']) return CopyPhraseDisplay( win, From 2e1981b029df4c319226f88f197f566db0e87c65 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 1 Dec 2023 12:47:29 -0800 Subject: [PATCH 173/330] Removed debugging code --- bcipy/display/demo/components/demo_layouts.py | 2 +- bcipy/display/paradigm/matrix/layout.py | 6 ------ 2 files changed, 1 insertion(+), 7 deletions(-) diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index b33ce06d4..7934a1e39 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -266,7 +266,7 @@ def demo_matrix_positions(win: visual.Window): win_layout = Layout(win) norm_layout = centered(parent=win, width_pct=0.7, height_pct=0.75) - positions = symbol_positions(norm_layout, rows=6, columns=6) + positions = symbol_positions(norm_layout, rows=5, columns=6) for sym, pos in zip(alphabet(), positions): stim = visual.TextStim(win, diff --git a/bcipy/display/paradigm/matrix/layout.py b/bcipy/display/paradigm/matrix/layout.py index cf5878aab..7ecccd814 100644 --- a/bcipy/display/paradigm/matrix/layout.py +++ b/bcipy/display/paradigm/matrix/layout.py @@ -50,19 +50,13 @@ def symbol_positions(container: Layout, rows: int, scaled_horizontal_spacing = horizontal_spacing scaled_vertical_spacing = vertical_spacing - print( - f"horizontal_spacing: {horizontal_spacing}; vertical_spacing: {vertical_spacing}" - ) - print(f"scaled_horizontal_spacing: {scaled_horizontal_spacing}; scaled_vertical_spacing: {scaled_vertical_spacing}") if max_spacing and vertical_spacing > max_spacing: vertical_spacing = max_spacing # Use the minimum spacing if scaled_horizontal_spacing < scaled_vertical_spacing: vertical_spacing = scaled_height(horizontal_spacing, win_size) - print(f"Setting vertical spacing to {vertical_spacing}") else: horizontal_spacing = scaled_width(vertical_spacing, win_size) - print(f"Setting horizontal spacing to {horizontal_spacing}") # Work back from center to compute the starting position center_x, center_y = container.center From cad9077d71c3659f11e8a4ab89d6037df95b8983 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 1 Dec 2023 16:00:48 -0800 Subject: [PATCH 174/330] Added README for matrix display --- bcipy/display/paradigm/matrix/README.md | 116 ++++++++++++++++++++++++ 1 file changed, 116 insertions(+) create mode 100644 bcipy/display/paradigm/matrix/README.md diff --git a/bcipy/display/paradigm/matrix/README.md b/bcipy/display/paradigm/matrix/README.md new file mode 100644 index 000000000..22d731125 --- /dev/null +++ b/bcipy/display/paradigm/matrix/README.md @@ -0,0 +1,116 @@ +# Matrix Display + +The matrix display presents a list of symbols in a grid format. Grid items are evenly spaced. All grid items are always displayed. The matrix can be drawn at different opacities and with different symbols highlighted. + +## Basic usage + +A matrix display needs a psychopy Window, core.Clock, and configuration for the stimuli (StimuliProperties), task_bar (TaskBar), and information elements (InformationProperties). + +``` +from psychopy import core + +import bcipy.display.components.layout as layout +from bcipy.display import (InformationProperties, StimuliProperties, + init_display_window) +from bcipy.display.components.task_bar import CopyPhraseTaskBar +from bcipy.display.paradigm.matrix.display import MatrixDisplay + +win = init_display_window(window_parameters) +task_bar = CalibrationPhraseTaskBar(win, inquiry_count=100) +stim_properties = StimuliProperties(stim_font=font, + stim_pos=[], + stim_height=0.5) +info = InformationProperties( + info_color=['white'], + info_pos=[layout.at_bottom(win, height=0.21).center], + info_height=[0.1], + info_font=[font], + info_text=['Matrix Calibration Demo'], +) + +matrix_display = MatrixDisplay(win, + core.Clock(), + stim_properties, + task_bar=task_bar, + info=info) + +matrix_display.draw(grid_opacity=matrix_display.full_grid_opacity, + grid_color=matrix_display.grid_color, + duration=10) +``` + +## Specify rows and columns + +The number of rows and columns can be specified by using the provided parameters. The number of rows x columns must be greater than or equal to the number of symbols. + +When using a task, the `matrix_rows` and `matrix_columns` parameters are used for customization. + +``` +matrix_display = MatrixDisplay(win, + experiment_clock, + stim_properties, + task_bar=task_bar, + info=info, + rows=4, + columns=7) +``` + +## Sorting stimuli + +A sort order function for the symbols can specified. The sort function includes the ability to provide blank spaces within the grid. + +``` +from bcipy.helpers.symbols import qwerty_order +matrix_display = MatrixDisplay(win, + experiment_clock, + stim_properties, + task_bar=task_bar, + info=info, + rows=3, + columns=10, + sort_order=qwerty_order(is_txt_stim=True)) +``` + +## Layout + +Symbol positions are calculated when the display is initialized. The grid will be centered within the window. By default the grid will take up 75% of the width, and 80% of the height, or whichever is smaller depending on the aspect ratio of your monitor. These values can be adjusted by provided a width_pct and height_pct parameter. + +When using a task, the `matrix_width` parameter is used for customization. + +``` +# determine matrix height based on the size of the task_bar +matrix_height_pct = 1 - (2 * task_bar.height_pct) +matrix_display = MatrixDisplay(win, + experiment_clock, + stim_properties, + task_bar=task_bar, + info=info, + rows=4, + columns=7, + width_pct=0.7, + height_pct=matrix_height_pct) +``` + +## Symbol positions + +Symbol positions are logged after calculation. + +## Troubleshooting + +You may need to do some trial and error to determine the best matrix configuration for your display. The following demos are helpful for experimenting with different layouts. + +* bcipy/display/demo/matrix/demo_matrix_layout.py +* bcipy/display/demo/components/demo_task_bar.py (useful if task_bar is cutoff and the task_padding needs adjustment) +* bcipy/display/demo/components/demo_layouts.py + + +## Recommended parameters + +For tasks which use the matrix display, the following parameters are recommended: + +``` + time_fixation: 2 + stim_height: 0.17 + task_height: 0.1 + task_padding: 0.05 +``` \ No newline at end of file From 5713b7c4367de198d499147c516348d3b84e63e0 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 3 Dec 2023 17:28:37 -0500 Subject: [PATCH 175/330] typing incorrect decisions and backspace support --- bcipy/simulator/helpers/rsvp_utils.py | 10 ++++++++ bcipy/simulator/helpers/state_manager.py | 31 ++++++++++-------------- 2 files changed, 23 insertions(+), 18 deletions(-) create mode 100644 bcipy/simulator/helpers/rsvp_utils.py diff --git a/bcipy/simulator/helpers/rsvp_utils.py b/bcipy/simulator/helpers/rsvp_utils.py new file mode 100644 index 000000000..69deca824 --- /dev/null +++ b/bcipy/simulator/helpers/rsvp_utils.py @@ -0,0 +1,10 @@ +from bcipy.helpers.symbols import BACKSPACE_CHAR + + +def next_target_letter(current_sentence, target_sentence): + """Computes the next target letter based on the currently spelled_text. + """ + if target_sentence[0:len(current_sentence)] == current_sentence: + # if correctly spelled so far, get the next letter. + return target_sentence[len(current_sentence)] if len(current_sentence) < len(target_sentence) else target_sentence[-1] + return BACKSPACE_CHAR diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 8aaccfa79..05c0d6530 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -5,11 +5,13 @@ import numpy as np +from bcipy.helpers import symbols from bcipy.helpers.exceptions import FieldException from bcipy.helpers.parameters import Parameters -from bcipy.helpers.symbols import alphabet +from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR from bcipy.simulator.helpers.decision import SimDecisionCriteria, MaxIterationsSim, ProbThresholdSim from bcipy.simulator.helpers.evidence_fuser import MultiplyFuser, EvidenceFuser +from bcipy.simulator.helpers.rsvp_utils import next_target_letter from bcipy.simulator.helpers.types import InquiryResult from bcipy.task.control.criteria import DecisionCriteria, MaxIterationsCriteria, ProbThresholdCriteria from bcipy.task.control.handler import EvidenceFusion @@ -83,6 +85,7 @@ def update(self, evidence) -> InquiryResult: evidence_likelihoods=list(evidence), fused_likelihood=fused_likelihood, # TODO change to use evidence_dict decision=None) + # can we make decision temp_series = copy.deepcopy(self.get_state().series_results) temp_series[-1].append(temp_inquiry_result) is_decidable = any([decider.decide(temp_series[-1]) for decider in self.state.decision_criterion]) @@ -91,23 +94,15 @@ def update(self, evidence) -> InquiryResult: new_state = self.get_state().__dict__ if is_decidable: decision = alphabet()[np.argmax(evidence)] # deciding the maximum probability symbol TODO abstract - if decision == self.state.target_symbol: # correct decision - new_state['series_n'] += 1 # TODO abstract out into reset function - new_state['series_results'].append([]) - new_state['inquiry_n'] = 0 - - new_state['current_sentence'] += decision - - next_target_symbol_idx = len(new_state['current_sentence']) - if next_target_symbol_idx >= len(self.state.target_sentence): - pass - else: - new_state['target_symbol'] = self.state.target_sentence[next_target_symbol_idx] - - else: # wrong decision - new_state['series_n'] += 1 - new_state['series_results'].append([]) - new_state['inquiry_n'] = 0 + + # resetting series + new_state['series_n'] += 1 + new_state['series_results'].append([]) + new_state['inquiry_n'] = 0 + + # updating current sentence and finding next target + new_state['current_sentence'] = new_state['current_sentence'] + decision if decision != BACKSPACE_CHAR else new_state['current_sentence'][:-1] + new_state['target_symbol'] = next_target_letter(new_state['current_sentence'], self.state.target_sentence) else: new_state['inquiry_n'] += 1 From 224eb32a062d9f8aa299b054d08d5e1cf196204a Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 3 Dec 2023 18:45:53 -0500 Subject: [PATCH 176/330] cli runnable simulator --- bcipy/simulator/__main__.py | 28 +++++++++++++ bcipy/simulator/helpers/metrics.py | 9 ++++ bcipy/simulator/helpers/model_handler.py | 36 ++++++++++++++++ bcipy/simulator/helpers/sampler.py | 4 +- bcipy/simulator/helpers/state_manager.py | 4 +- bcipy/simulator/interfaces.py | 20 --------- bcipy/simulator/main.py | 52 ------------------------ bcipy/simulator/sim.py | 4 +- bcipy/simulator/sim_factory.py | 29 +++++++++++++ bcipy/simulator/tests/sampler_test.py | 32 +++------------ 10 files changed, 114 insertions(+), 104 deletions(-) create mode 100644 bcipy/simulator/__main__.py create mode 100644 bcipy/simulator/helpers/metrics.py create mode 100644 bcipy/simulator/helpers/model_handler.py delete mode 100644 bcipy/simulator/interfaces.py delete mode 100644 bcipy/simulator/main.py diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py new file mode 100644 index 000000000..8777f5e07 --- /dev/null +++ b/bcipy/simulator/__main__.py @@ -0,0 +1,28 @@ +import argparse +from pathlib import Path + +from bcipy.simulator.sim_factory import SimulationFactory, SimulationFactoryV2 +from bcipy.simulator.simulator_base import Simulator + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument( + "-d", + "--data_folders", + action="append", + type=Path, + required=True, + help="Raw data folders to be processed. This argument can be repeated to accumulate sessions data.") + parser.add_argument( + "-sm", + "--smodel_files", + action="append", + type=Path, + required=True, + help="Signal models to be used") + parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) + + args = vars(parser.parse_args()) + + simulator: Simulator = SimulationFactoryV2.create(**args) + simulator.run() diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py new file mode 100644 index 000000000..3352c49a3 --- /dev/null +++ b/bcipy/simulator/helpers/metrics.py @@ -0,0 +1,9 @@ +from abc import ABC + + +class MetricReferee(ABC): + ... + + +class DummyRef(MetricReferee): + pass diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py new file mode 100644 index 000000000..5b443b382 --- /dev/null +++ b/bcipy/simulator/helpers/model_handler.py @@ -0,0 +1,36 @@ +import pickle +from abc import ABC +from typing import Optional + +from bcipy.helpers.symbols import alphabet +from bcipy.signal.model import SignalModel +from bcipy.simulator.helpers.state_manager import SimState + + +class ModelHandler(ABC): + + def generate_evidence(self, state: SimState, features): + ... + + def get_model(self, key=None): + ... + + +class SignalModelHandler1(ModelHandler): + + def __init__(self, model_file): + self.model_file = model_file + self.signal_model: Optional[SignalModel] = None + + def generate_evidence(self, state: SimState, features): + with open(self.model_file, "rb") as signal_file: + self.signal_model = pickle.load(signal_file) + + stimuli = state.display_alphabet + alp = alphabet() + eeg_evidence = self.signal_model.predict(features, stimuli, alp) + + return eeg_evidence + + def get_model(self, key=None): + return self.signal_model diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index de3e217dc..3111d2370 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -10,7 +10,7 @@ from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.log_utils import format_sample_rows -from bcipy.simulator.interfaces import SimState +from bcipy.simulator.helpers.state_manager import SimState log = logging.getLogger(__name__) @@ -25,7 +25,7 @@ def set_reshaper(self, reshaper: Callable): ... -class SimpleLetterSampler(Sampler): +class EEGByLetterSampler(Sampler): def __init__(self, data_engine: RawDataEngine, params: List[Parameters] = None): self.data_engine: RawDataEngine = data_engine diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 05c0d6530..e5013365a 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -1,4 +1,5 @@ import copy +import random from abc import ABC, abstractmethod from dataclasses import dataclass from typing import List, Optional, Dict @@ -133,9 +134,10 @@ def initial_state(parameters: Parameters = None) -> SimState: sentence = "HELLO_WORLD" # TODO abstract out with sim_parameters.json target_symbol = sentence[0] # TODO use parameters.get('spelled_letters_count') default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] + init_stimuli = random.sample(alphabet(), 10) evidence_types = parameters.get( 'evidence_types') if parameters else None # TODO make new parameter and create default series_likelihoods object based off that - return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, display_alphabet=[], inquiry_n=0, series_n=0, + return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, display_alphabet=init_stimuli, inquiry_n=0, series_n=0, series_results=[[]], decision_criterion=default_criterion) diff --git a/bcipy/simulator/interfaces.py b/bcipy/simulator/interfaces.py deleted file mode 100644 index cac2c8120..000000000 --- a/bcipy/simulator/interfaces.py +++ /dev/null @@ -1,20 +0,0 @@ -from abc import ABC - -from bcipy.helpers.symbols import alphabet -from bcipy.signal.model import PcaRdaKdeModel -from bcipy.simulator.helpers.state_manager import SimState - - -class ModelHandler(ABC): - - def generate_evidence(self, state: SimState, features): - ... - - def get_model(self, key=None): - ... - - -class MetricReferee: - ... - - diff --git a/bcipy/simulator/main.py b/bcipy/simulator/main.py deleted file mode 100644 index 360ad8299..000000000 --- a/bcipy/simulator/main.py +++ /dev/null @@ -1,52 +0,0 @@ -import argparse -from pathlib import Path - -from bcipy.helpers.load import load_json_parameters -from bcipy.simulator.sim_factory import SimulationFactory - -if __name__ == "__main__": - - parser = argparse.ArgumentParser() - parser.add_argument( - "-d", - "--data_folders", - action="append", - type=Path, - required=True, - help="Session data folders to be processed. This argument can be repeated to accumulate sessions data.") - parser.add_argument( - "-sm", - "--smodel_files", - action="append", - type=Path, - required=True, - help="Signal models to be used") - parser.add_argument( - "-lm", - "--lmodel_file", - action="append", - type=Path, - required=False, - help="Language models to be used") - parser.add_argument("-o", "--out_dir", type=Path, default=None) - parser.add_argument( - "-p", - "--parameter_path", - type=Path, - default=None, - help="Parameter file to be used for replay. If none, the session parameter file will be used.") - - args = vars(parser.parse_args()) - - # assert len(set(args['data_folders'])) == len(args.data_folders), "Duplicated data folders" - - if args['out_dir'] is None: - args['out_dir'] = Path(__file__).resolve().parent - - # Load parameters - sim_parameters = load_json_parameters("bcipy/simulator/sim_parameters.json", value_cast=True) - sim_task = sim_parameters.get("sim_task") - args['sim_task'] = sim_task - - simulator = SimulationFactory.create(**args) - simulator.run() diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 55aa38491..8d5e631cd 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -1,4 +1,3 @@ -import datetime import logging import random from time import sleep @@ -9,11 +8,12 @@ from bcipy.helpers import load, stimuli, symbols from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine +from bcipy.simulator.helpers.metrics import MetricReferee from bcipy.simulator.helpers.sampler import Sampler from bcipy.simulator.helpers.state_manager import StateManager, SimState from bcipy.simulator.helpers.types import InquiryResult from bcipy.simulator.helpers.log_utils import format_alp_likelihoods -from bcipy.simulator.interfaces import MetricReferee, ModelHandler +from bcipy.simulator.helpers.model_handler import ModelHandler from bcipy.simulator.simulator_base import Simulator log = logging.getLogger(__name__) diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 38fbb5f73..70eaeb154 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -1,6 +1,16 @@ from pathlib import Path +from typing import List + +import numpy as np from bcipy.config import DEFAULT_PARAMETER_FILENAME +from bcipy.helpers.load import load_json_parameters +from bcipy.simulator.helpers.data_engine import RawDataEngine +from bcipy.simulator.helpers.metrics import MetricReferee, DummyRef +from bcipy.simulator.helpers.model_handler import SignalModelHandler1, ModelHandler +from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler +from bcipy.simulator.helpers.state_manager import StateManager, StateManagerImpl +from bcipy.simulator.sim import SimulatorCopyPhrase from bcipy.simulator.sim_copy_phrase import SimulatorCopyPhraseReplay from bcipy.simulator.simulator_base import Simulator @@ -27,3 +37,22 @@ def create( verbose=kwargs.get('verbose', False)) # TODO refactor for sampling simulator + + +class SimulationFactoryV2: + @staticmethod + def create(data_folders: List[str], smodel_files: List[str], sim_param_path="bcipy/simulator/sim_parameters.json", **kwargs): + out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) + + model_file = Path(smodel_files.pop()) + sim_parameters = load_json_parameters(sim_param_path, value_cast=True) + + data_engine = RawDataEngine(data_folders) + stateManager: StateManager = StateManagerImpl(sim_parameters) + sampler: Sampler = EEGByLetterSampler(data_engine) + model_handler: ModelHandler = SignalModelHandler1(model_file) + referee: MetricReferee = DummyRef() + + sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, referee) + + return sim diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index 7558be370..452197cde 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -5,36 +5,14 @@ from bcipy.helpers.load import load_json_parameters from bcipy.helpers.symbols import alphabet -from bcipy.signal.model import PcaRdaKdeModel from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.sampler import Sampler, SimpleLetterSampler +from bcipy.simulator.helpers.metrics import DummyRef +from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler from bcipy.simulator.helpers.state_manager import StateManagerImpl, StateManager, SimState -from bcipy.simulator.interfaces import ModelHandler, MetricReferee +from bcipy.simulator.helpers.model_handler import SignalModelHandler1 from bcipy.simulator.sim import SimulatorCopyPhrase -class DummyModelHandler(ModelHandler): - - def __init__(self, model_file): - self.model_file = model_file - - def generate_evidence(self, state: SimState, features): - model = PcaRdaKdeModel() - model = model.load(self.model_file) - - stimuli = state.display_alphabet - alp = alphabet() - eeg_evidence = model.predict(features, stimuli, alp) - - return eeg_evidence - - def get_model(self, key=None): - pass - - -class DummyRef(MetricReferee): - pass - if __name__ == "__main__": args = dict() @@ -57,9 +35,9 @@ class DummyRef(MetricReferee): stateManager.mutate_state("display_alphabet", display_alp) print(stateManager.get_state()) - sampler: Sampler = SimpleLetterSampler(data_engine) + sampler: Sampler = EEGByLetterSampler(data_engine) sample: np.ndarray = sampler.sample(stateManager.get_state()) - model_handler = DummyModelHandler(model_file) + model_handler = SignalModelHandler1(model_file) sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, DummyRef()) sim.run() From bfb4ecc44d4e6198cad81670fd85e048d445efe2 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 3 Dec 2023 18:49:26 -0500 Subject: [PATCH 177/330] time step sleep in sim_parameters.json --- bcipy/simulator/sim.py | 2 +- bcipy/simulator/sim_parameters.json | 12 ++++++++++++ 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 8d5e631cd..7697e0836 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -83,7 +83,7 @@ def run(self): log.info(f"Decided {inq_record.decision} for target {inq_record.target}") log.info(f"Current typed: {updated_state.current_sentence}") - sleep(.5) + sleep(self.parameters.get("sim_sleep_time", 0.5)) final_state = self.state_manager.get_state() log.info(f"SIM END") diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index 301ab6203..926037a3e 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -20,5 +20,17 @@ "1" ], "type": "str" + }, + "sim_sleep_time": { + "value": "0.25", + "section": "sim_config", + "readableName": "Simulation Time Step ", + "helpTip": "How long to sleep in between simulation time steps", + "recommended_values": [ + "0", + "0.5", + "1" + ], + "type": "float" } } \ No newline at end of file From 4102a83d7fa2b93ad4f92a286e3912fe65c5fd72 Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Mon, 4 Dec 2023 17:51:12 -0800 Subject: [PATCH 178/330] Output stim positions, capture screenshots, more cleanup (#303) * stimuli position export + capture matrix grid * update offline analysis and gaze visualization * remove unneeded class variable * dsi-flex and better starting parameters * update the calibration tests to mock open and prevent testing issues on Windows * revert parameter change * update to workflow to fix Windows build * revert actions change, lock a pyqt6 dep * remove unneeded assertions and save the current task bar index before a screen capture * add more info to output, update CHANGELOG --- .coveragerc | 1 + CHANGELOG.md | 2 +- bcipy/acquisition/tests/test_devices.py | 2 +- bcipy/config.py | 4 + bcipy/display/paradigm/matrix/display.py | 27 +- bcipy/feedback/demo/demo_level_feedback.py | 38 --- bcipy/feedback/visual/level_feedback.py | 130 -------- bcipy/helpers/save.py | 51 ++- bcipy/helpers/tests/test_save.py | 37 +- bcipy/helpers/visualization.py | 11 +- bcipy/parameters/devices.json | 17 + bcipy/parameters/parameters.json | 4 +- bcipy/signal/model/offline_analysis.py | 34 +- bcipy/task/README.md | 15 +- bcipy/task/main.py | 3 - bcipy/task/paradigm/matrix/calibration.py | 82 +++-- bcipy/task/paradigm/matrix/copy_phrase.py | 3 +- .../paradigm/rsvp/calibration/calibration.py | 29 +- .../rsvp/calibration/timing_verification.py | 36 +- bcipy/task/paradigm/rsvp/copy_phrase.py | 24 +- bcipy/task/start_task.py | 1 + .../matrix/test_matrix_calibration.py | 315 ++++++++++++++++++ .../rsvp/calibration/test_rsvp_calibration.py | 310 +++++++++++++++++ .../tests/paradigm/rsvp/test_copy_phrase.py | 2 - requirements.txt | 1 + 25 files changed, 909 insertions(+), 270 deletions(-) delete mode 100644 bcipy/feedback/demo/demo_level_feedback.py delete mode 100644 bcipy/feedback/visual/level_feedback.py create mode 100644 bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py create mode 100644 bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py diff --git a/.coveragerc b/.coveragerc index a32c1d6e6..c7ad07bca 100644 --- a/.coveragerc +++ b/.coveragerc @@ -6,6 +6,7 @@ omit = *tests* *test* *demo* + *exceptions.py */gui/* [report] diff --git a/CHANGELOG.md b/CHANGELOG.md index cf7e847d6..668342acd 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -10,7 +10,7 @@ Our last release candidate before the official 2.0 release! - Model - Offline analysis to support multimodal fusion. Initial release of GazeModel, GazeReshaper, and Gaze Visualization #294 - Stimuli - - Updates to ensure stimuli are presented at the same frequency #287 + - Updates to ensure stimuli are presented at the same frequency #287 Output stimuli position, screen capture and monitor information after Matrix tasks #303 - Dynamic Selection Window - Updated trial_length to trial_window to allow for greater control of window used after stimulus presentations #291 - Parameters diff --git a/bcipy/acquisition/tests/test_devices.py b/bcipy/acquisition/tests/test_devices.py index ea91671ca..31c0a766c 100644 --- a/bcipy/acquisition/tests/test_devices.py +++ b/bcipy/acquisition/tests/test_devices.py @@ -27,7 +27,7 @@ def test_default_supported_devices(self): dsi = supported['DSI-24'] self.assertEqual('EEG', dsi.content_type) - self.assertEqual(len(devices.with_content_type('EEG')), 3) + self.assertEqual(len(devices.with_content_type('EEG')), 4) def test_load_from_config(self): """Should be able to load a list of supported devices from a diff --git a/bcipy/config.py b/bcipy/config.py index 02a079d76..db85fe06c 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -37,6 +37,9 @@ DEFAULT_FIXATION_PATH = f'{STATIC_IMAGES_PATH}/main/PLUS.png' DEFAULT_TEXT_FIXATION = '+' +MATRIX_IMAGE_FILENAME = 'matrix.png' +DEFAULT_GAZE_IMAGE_PATH = f'{STATIC_IMAGES_PATH}/main/{MATRIX_IMAGE_FILENAME}' + # core data configuration RAW_DATA_FILENAME = 'raw_data' EYE_TRACKER_FILENAME_PREFIX = 'eyetracker_data' @@ -44,6 +47,7 @@ SESSION_DATA_FILENAME = 'session.json' SESSION_SUMMARY_FILENAME = 'session.xlsx' LOG_FILENAME = 'bcipy_system_log.txt' +STIMULI_POSITIONS_FILENAME = 'stimuli_positions.json' # misc configuration WAIT_SCREEN_MESSAGE = 'Press Space to start or Esc to exit' diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index ccb8bd1ef..229de7e97 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -5,6 +5,7 @@ from psychopy import core, visual import bcipy.display.components.layout as layout +from bcipy.config import MATRIX_IMAGE_FILENAME from bcipy.display import (BCIPY_LOGO_PATH, Display, InformationProperties, StimuliProperties) from bcipy.display.components.task_bar import TaskBar @@ -127,6 +128,23 @@ def _stim_positions(self) -> Dict[str, Tuple[float, float]]: for sym, stim in self.stim_registry.items() } + def capture_grid_screenshot(self, file_path: str) -> None: + """Capture Grid Screenshot. + + Capture a screenshot of the current display and save it to the specified filename. + """ + # draw the grid and flip the window + self.draw_grid(opacity=self.full_grid_opacity) + tmp_task_bar = self.task_bar.current_index + self.task_bar.current_index = 0 + self.draw_static() + self.window.flip() + + # capture the screenshot and save it to the specified file path + capture = self.window.getMovieFrame() + capture.save(f'{file_path}/{MATRIX_IMAGE_FILENAME}') + self.task_bar.current_index = tmp_task_bar + def schedule_to(self, stimuli: list, timing: list, colors: list) -> None: """Schedule stimuli elements (works as a buffer). @@ -158,13 +176,13 @@ def add_timing(self, stimuli: str): Useful as a callback function to register a marker at the time it is first displayed.""" - self._timing.append([stimuli, self.experiment_clock.getTime()]) + self._timing.append((stimuli, self.experiment_clock.getTime())) def reset_timing(self): """Reset the trigger timing.""" self._timing = [] - def do_inquiry(self) -> List[float]: + def do_inquiry(self) -> List[Tuple[str, float]]: """Animates an inquiry of stimuli and returns a list of stimuli trigger timing.""" self.reset_timing() symbol_durations = self.symbol_durations() @@ -187,11 +205,12 @@ def build_grid(self) -> Dict[str, visual.TextStim]: grid = {} for sym in self.symbol_set: pos_index = self.sort_order(sym) + pos = self.positions[pos_index] grid[sym] = visual.TextStim(win=self.window, text=sym, color=self.grid_color, opacity=self.start_opacity, - pos=self.positions[pos_index], + pos=pos, height=self.grid_stimuli_height) return grid @@ -337,8 +356,6 @@ def update_task_bar(self, text: str = ''): PARAMETERS: text: text for task - color_list: list of the colors for each stimuli - pos: position of task """ if self.task_bar: self.task_bar.update(text) diff --git a/bcipy/feedback/demo/demo_level_feedback.py b/bcipy/feedback/demo/demo_level_feedback.py deleted file mode 100644 index 8bf8b82b9..000000000 --- a/bcipy/feedback/demo/demo_level_feedback.py +++ /dev/null @@ -1,38 +0,0 @@ -from bcipy.config import DEFAULT_PARAMETERS_PATH -from bcipy.display import init_display_window -from bcipy.feedback.visual.level_feedback import LevelFeedback -from bcipy.helpers.clock import Clock -from bcipy.helpers.load import load_json_parameters - -# Load a parameters file -parameters = load_json_parameters(DEFAULT_PARAMETERS_PATH, value_cast=True) -parameters = { - 'feedback_font': parameters['font'], - 'feedback_color': parameters['info_color'], - 'feedback_pos_x': -0.5, - 'feedback_pos_y': 0, - 'feedback_padding': 0.27, - 'feedback_stim_height': 0.25, - 'feedback_stim_width': 0.25, - 'feedback_line_width': 1, - 'feedback_line_color': parameters['info_color'], - 'feedback_duration': parameters['feedback_duration'], - 'feedback_target_line_width': 5, # this is very OS dependent! - 'full_screen': parameters['full_screen'], - 'window_height': parameters['window_height'], - 'window_width': parameters['window_width'], - 'background_color': parameters['background_color'], - 'stim_screen': parameters['stim_screen'] -} -display = init_display_window(parameters) -clock = Clock() -# Start Visual Level Feedback -visual_feedback = LevelFeedback( - display=display, parameters=parameters, clock=clock) -positions = [1, 2, 3, 4, 5] -timing = [] -for i in positions: - timing += visual_feedback.administer(position=i) -print(timing) -print(visual_feedback._type()) -display.close() diff --git a/bcipy/feedback/visual/level_feedback.py b/bcipy/feedback/visual/level_feedback.py deleted file mode 100644 index 6304a88a1..000000000 --- a/bcipy/feedback/visual/level_feedback.py +++ /dev/null @@ -1,130 +0,0 @@ -from typing import Tuple - -from psychopy import core, visual - -from bcipy.feedback.visual.visual_feedback import VisualFeedback - - -class LevelFeedback(VisualFeedback): - """Level Feedback. - - A progress bar like feedback to indicate current abilities in a BCI task. This could - be attentiveness, muscle or eye activity, etc. - - It does not return stimuli timing or allow for parameterized configuration of levels / color gradient - at this time. - """ - - def __init__(self, display, parameters, clock): - super().__init__(display, parameters, clock) - - # extract needed parameters - self.clock = clock - self.display = display - self.parameters = parameters - self.presentation_time = parameters['feedback_duration'] - - # set stylistic elements - self.default_message_color = parameters['feedback_color'] - self.feedback_indicator_color = parameters['feedback_color'] - self.position_x = parameters['feedback_pos_x'] - self.position_y = parameters['feedback_pos_y'] - self.padding = parameters['feedback_padding'] - self.width = parameters['feedback_stim_width'] - self.height = parameters['feedback_stim_height'] - self.line_color = parameters['feedback_line_color'] - self.line_width = parameters['feedback_line_width'] - self.font = parameters['feedback_font'] - self.target_line_width = parameters['feedback_target_line_width'] - - # colors needed for each level. This defines the number of levels in - # the bar indicator. - self.level_colors = [ - 'red', - 'darkorange', - 'yellow', - 'lightgreen', - 'green'] - - # array to hold our level feedback stimuli to be presented - self.stimuli = [] - - def administer(self, position=1): - # construct the bar indicator - self._construct_bar_indicator() - - # indexing starts at zero but position does not ;) - position -= 1 - - # loop through the levels wanted and construct the stimuli - for index, color in enumerate(self.level_colors): - # this is the target indicator level and should stand out of the - # rest - if position == index: - self.stimuli[index].lineColor = self.feedback_indicator_color - self.stimuli[index].lineWidth = self.target_line_width - # draw other stimuli elements - self.stimuli[index].fillColor = color - self.stimuli[index].draw() - - # flip the display and present for a time - time = ['visual_feedback', self.clock.getTime()] - self.display.flip() - core.wait(self.presentation_time) - - return time - - def _construct_bar_indicator(self): - """Construct Bar Indicator. - - Helper method for constructing the bar indicator programmatically. It - resets the position_x and stimuli variables on first call. - """ - self._reset_stimuli() - width, height = self._determine_height_and_width() - - # construct the rectangular level shapes and append to stimuli array - for level in self.level_colors: - position = self._determine_stimuli_position() - rect = visual.Rect( - win=self.display, - width=width, - height=height, - fillColor=self.default_message_color, - lineColor=self.line_color, - pos=position, - lineWidth=self.line_width, - ori=0.0) - self.stimuli.append(rect) - - def _determine_stimuli_position(self) -> Tuple[int, int]: - """Determine Stimuli Position. - - Defines the x and y position of the feedback level stimuli, - incrementing by the self.padding variable after setting. - If a vertical bar is desired the position_y should be incremented - instead of position_x. - """ - # define the positioning of stimuli and increment the x position - response = self.position_x, self.position_y - self.position_x += self.padding - return response - - def _determine_height_and_width(self) -> Tuple[float, float]: - """Determine Height and Width. - - Defines the height and width of level stimuli. Currently, a static - set of variables. - """ - return self.width, self.height - - def _reset_stimuli(self) -> None: - """Reset Stimuli. - - Used when redrawing stimuli. Sets the stimuli array and starting - x positions to their starting values. If using vertical bars - this should reset the y positions instead. - """ - # reset stimuli - self.stimuli = [] - self.position_x = self.parameters['feedback_pos_x'] diff --git a/bcipy/helpers/save.py b/bcipy/helpers/save.py index 812a66ee6..84d275d69 100644 --- a/bcipy/helpers/save.py +++ b/bcipy/helpers/save.py @@ -6,13 +6,16 @@ from pathlib import Path from shutil import copyfile from time import localtime, strftime -from typing import Any, List, Union +from typing import Any, Dict, List, Tuple, Union from bcipy.acquisition.devices import DeviceSpec -from bcipy.config import (DEFAULT_ENCODING, DEFAULT_EXPERIMENT_ID, +from bcipy.config import (DEFAULT_ENCODING, + DEFAULT_EXPERIMENT_ID, DEFAULT_LM_PARAMETERS_FILENAME, DEFAULT_LM_PARAMETERS_PATH, - DEFAULT_PARAMETER_FILENAME, SIGNAL_MODEL_FILE_SUFFIX) + DEFAULT_PARAMETER_FILENAME, + SIGNAL_MODEL_FILE_SUFFIX, + STIMULI_POSITIONS_FILENAME) from bcipy.helpers.validate import validate_experiments from bcipy.signal.model.base_model import SignalModel @@ -33,16 +36,26 @@ def save_json_data(data: Any, location: str, name: str) -> str: return str(path) -def save_experiment_data(experiments, fields, location, name) -> str: +def save_experiment_data( + experiments: dict, + fields: dict, + location: str, + name: str) -> str: validate_experiments(experiments, fields) return save_json_data(experiments, location, name) -def save_field_data(fields, location, name) -> str: +def save_field_data( + fields: dict, + location: str, + name: str) -> str: return save_json_data(fields, location, name) -def save_experiment_field_data(data, location, name) -> str: +def save_experiment_field_data( + data: dict, + location: str, + name: str) -> str: return save_json_data(data, location, name) @@ -154,7 +167,7 @@ def _save_session_related_data(save_path: str, session_dictionary: dict) -> Any: return file -def save_model(model: SignalModel, path: Union[Path, str]): +def save_model(model: SignalModel, path: Union[Path, str]) -> None: """Save model weights (e.g. after training) to `path` Parameters @@ -169,3 +182,27 @@ def save_model(model: SignalModel, path: Union[Path, str]): # It supports very large objects and some data format optimizations # making it appropriate for signal models. pickle.dump(model, file, protocol=4) + + +def save_stimuli_position_info( + stimuli_position_info: Dict[str, Tuple[float, float]], + path: Union[Path, str], + screen_info: Dict[str, Any]) -> str: + """Save stimuli positions and screen info to `path` + + stimuli_position_info: {'A': (0, 0)} + screen_info: {'screen_size_pixels': [1920, 1080], 'screen_refresh': 160} + + Parameters + ---------- + stimuli_position_info - stimuli position info to save to json + path - path to the file which will be created. + screen_info - screen info to save to json + """ + # assert that screen_info is a dict with at least the key 'screen_resolution' + assert 'screen_size_pixels' in screen_info.keys(), \ + 'screen_size_pixels must be a key in screen_info' + + # combine the dicts + all_data = {**stimuli_position_info, **screen_info} + return save_json_data(all_data, path, STIMULI_POSITIONS_FILENAME) diff --git a/bcipy/helpers/tests/test_save.py b/bcipy/helpers/tests/test_save.py index 191805b3a..a54aedd76 100644 --- a/bcipy/helpers/tests/test_save.py +++ b/bcipy/helpers/tests/test_save.py @@ -2,10 +2,15 @@ import shutil import unittest import tempfile +import json -from bcipy.config import DEFAULT_PARAMETERS_PATH, DEFAULT_PARAMETER_FILENAME, DEFAULT_EXPERIMENT_ID +from bcipy.config import ( + DEFAULT_PARAMETERS_PATH, + DEFAULT_PARAMETER_FILENAME, + DEFAULT_EXPERIMENT_ID, + STIMULI_POSITIONS_FILENAME) from bcipy.helpers import save -from bcipy.helpers.save import init_save_data_structure +from bcipy.helpers.save import init_save_data_structure, save_stimuli_position_info from mockito import any, unstub, when @@ -81,5 +86,33 @@ def test_throws_error_if_given_incorrect_params_path(self): self.experiment) +class TestSaveStimuliPositions(unittest.TestCase): + + def setUp(self): + self.save_directory = tempfile.mkdtemp() + self.stimuli_positions = {'symbol': (0, 0)} + self.filename = STIMULI_POSITIONS_FILENAME + self.screen_info = {'screen_size_pixels': [1920, 1080]} + self.expected_output = { + 'symbol': [0, 0], + 'screen_size_pixels': [1920, 1080]} + + def tearDown(self): + shutil.rmtree(self.save_directory) + + def test_save_stimuli_position_info_writes_json(self): + save_stimuli_position_info(self.stimuli_positions, self.save_directory, self.screen_info) + self.assertTrue(os.path.isfile(os.path.join(self.save_directory, self.filename))) + + def test_save_stimuli_position_info_writes_correct_json(self): + save_stimuli_position_info(self.stimuli_positions, self.save_directory, self.screen_info) + # load the json file + with open(os.path.join(self.save_directory, self.filename)) as f: + data = json.load(f) + + # assert the data is correct + self.assertEqual(data, self.expected_output) + + if __name__ == '__main__': unittest.main() diff --git a/bcipy/helpers/visualization.py b/bcipy/helpers/visualization.py index 44586e714..c8e9dfc45 100644 --- a/bcipy/helpers/visualization.py +++ b/bcipy/helpers/visualization.py @@ -17,7 +17,7 @@ import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, RAW_DATA_FILENAME, - STATIC_IMAGES_PATH, TRIGGER_FILENAME) + DEFAULT_GAZE_IMAGE_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.parameters import Parameters from bcipy.helpers.convert import convert_to_mne @@ -157,7 +157,8 @@ def visualize_gaze( title += 'Raw Gaze ' if img_path is None: - img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img_path = f'{DEFAULT_GAZE_IMAGE_PATH}' + img = plt.imread(img_path) channels = data.channels left_eye_channel_map = [1 if channel in left_keys else 0 for channel in channels] @@ -267,7 +268,7 @@ def visualize_gaze_inquiries( title = 'Raw Gaze Inquiries ' if img_path is None: - img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img_path = f'{DEFAULT_GAZE_IMAGE_PATH}' img = plt.imread(img_path) # transform the eye data to fit the display. remove > 1 values < 0 values and flip the y axis @@ -378,7 +379,7 @@ def visualize_centralized_data( title = 'Centralized Data for All Symbols ' if img_path is None: - img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img_path = f'{DEFAULT_GAZE_IMAGE_PATH}' img = plt.imread(img_path) # scale the eye data to the image @@ -472,7 +473,7 @@ def visualize_results_all_symbols( title = 'Map of Gaze Data and Contours ' if img_path is None: - img_path = f'{STATIC_IMAGES_PATH}/main/matrix.png' + img_path = f'{DEFAULT_GAZE_IMAGE_PATH}' img = plt.imread(img_path) # scale the eye data to the image diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index 5400ba106..01e4724b8 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -59,6 +59,23 @@ "description": "Wearable Sensing DSI-VR300", "excluded_from_analysis": ["TRG", "F7"] }, + { + "name": "DSI-Flex", + "content_type": "EEG", + "channels": [ + { "name": "F3", "label": "Fz", "units": "microvolts", "type": "EEG" }, + { "name": "S2", "label": "Oz", "units": "microvolts", "type": "EEG" }, + { "name": "S3", "label": "P4", "units": "microvolts", "type": "EEG" }, + { "name": "S4", "label": "P3", "units": "microvolts", "type": "EEG" }, + { "name": "S5", "label": "PO8", "units": "microvolts", "type": "EEG" }, + { "name": "S6", "label": "Pz", "units": "microvolts", "type": "EEG" }, + { "name": "S7", "label": "PO7", "units": "microvolts", "type": "EEG" }, + { "name": "TRG", "label": "TRG", "units": "microvolts", "type": "EEG" } + ], + "sample_rate": 300.0, + "description": "Wearable Sensing DSI-Flex", + "excluded_from_analysis": ["TRG"] + }, { "name": "g.USBamp-1", "content_type": "EEG", diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index c1fe3cb0b..b32295be6 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -32,10 +32,10 @@ "type": "str" }, "static_trigger_offset": { - "value": "0.100", + "value": "0.1", "section": "bci_config", "readableName": "Static Trigger Offset", - "helpTip": "Specifies the static trigger offset (in seconds) used to align triggers properly with EEG data from LSL. The system includes built-in offset correction, but there is still a hardware-limited offset between EEG and trigger timing values for which the system does not account. The default value of 0.1 has been verified for OHSU hardware. The correct value may be different for other computers, and must be determined on a case-by-case basis. Default: .1", + "helpTip": "Specifies the static trigger offset (in seconds) used to align triggers properly with EEG data from LSL. The system includes built-in offset correction, but there is still a hardware-limited offset between EEG and trigger timing values for which the system does not account. The default value of 0.1 has been verified for OHSU hardware. The correct value may be different for other computers, and must be determined on a case-by-case basis. Default: 0.1", "recommended_values": "", "type": "float" }, diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index ff7e1122b..b5ed089b5 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -13,7 +13,8 @@ import bcipy.acquisition.devices as devices from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, BCIPY_ROOT, DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH, - TRIGGER_FILENAME) + TRIGGER_FILENAME, + MATRIX_IMAGE_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) @@ -221,8 +222,9 @@ def analyze_gaze( parameters, device_spec, data_folder, - save_figures=False, + save_figures=None, show_figures=False, + plot_points=False, model_type="Individual"): """Analyze gaze data and return/save the gaze model. Extract relevant information from gaze data object. @@ -241,6 +243,7 @@ def analyze_gaze( data_folder (str): Path to the folder containing the data to be analyzed. save_figures (bool): If true, saves ERP figures after training to the data folder. show_figures (bool): If true, shows ERP figures after training. + plot_points (bool): If true, plots the gaze points on the matrix image. model_type (str): Type of gaze model to be used. Options are: "Individual": Fits a separate Gaussian for each symbol. Default model "Centralized": Uses data from all symbols to fit a single centralized Gaussian @@ -248,9 +251,10 @@ def analyze_gaze( figures = [] figure_handles = visualize_gaze( gaze_data, - save_path=data_folder if save_figures else None, + save_path=save_figures, + img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', show=show_figures, - raw_plot=True, + raw_plot=plot_points, ) figures.extend(figure_handles) @@ -346,9 +350,10 @@ def analyze_gaze( figure_handles = visualize_gaze_inquiries( le, re, means, covs, - save_path=None, + save_path=save_figures, + img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', show=show_figures, - raw_plot=True, + raw_plot=plot_points, ) figures.extend(figure_handles) left_eye_all.append(le) @@ -404,9 +409,10 @@ def analyze_gaze( # Visualize the results: figure_handles = visualize_centralized_data( cent_left, cent_right, - save_path=None, + save_path=save_figures, + img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', show=show_figures, - raw_plot=True, + raw_plot=plot_points, ) figures.extend(figure_handles) @@ -424,9 +430,10 @@ def analyze_gaze( figure_handles = visualize_gaze_inquiries( le, re, means, covs, - save_path=None, + save_path=save_figures, + img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', show=show_figures, - raw_plot=True, + raw_plot=plot_points, ) figures.extend(figure_handles) left_eye_all.append(le) @@ -437,9 +444,10 @@ def analyze_gaze( fig_handles = visualize_results_all_symbols( left_eye_all, right_eye_all, means_all, covs_all, - save_path=None, - show=True, - raw_plot=True, + img_path=f'{data_folder}/{MATRIX_IMAGE_FILENAME}', + save_path=save_figures, + show=show_figures, + raw_plot=plot_points, ) figures.extend(fig_handles) diff --git a/bcipy/task/README.md b/bcipy/task/README.md index 788c4c1a1..3943d744c 100644 --- a/bcipy/task/README.md +++ b/bcipy/task/README.md @@ -14,21 +14,24 @@ Currently, these are the supported paradigms and modes: ##### Mode: Calibration -> Calibration - -> Time Test Calibration +> Calibration: Used to calibrate the RSVP paradigm for a user +> Time Test Calibration: Used to verify the timing of the RSVP paradigm ##### Mode: Copy Phrase -> Copy Phrase +> Copy Phrase: Used to copy a phrase using the RSVP paradigm (e.g. P300 Speller) on data from a P300 calibration ### *Paradigm: Matrix* ##### Mode: Calibration -> Calibration +> Calibration: Used to calibrate the Matrix paradigm for a user +> Time Test Calibration: Used to verify the timing of the Matrix paradigm + +##### Mode: Copy Phrase + +> Copy Phrase: Used to copy a phrase using the Matrix paradigm (e.g. P300 Speller) on data from a P300 calibration -> Time Test Calibration ## Start Task diff --git a/bcipy/task/main.py b/bcipy/task/main.py index b46af1d5c..9e6b92f06 100644 --- a/bcipy/task/main.py +++ b/bcipy/task/main.py @@ -20,6 +20,3 @@ def execute(self) -> str: @abstractmethod def name(self) -> str: ... - - def configure(self) -> None: - ... diff --git a/bcipy/task/paradigm/matrix/calibration.py b/bcipy/task/paradigm/matrix/calibration.py index 7c9b8b61c..f3de99bb0 100644 --- a/bcipy/task/paradigm/matrix/calibration.py +++ b/bcipy/task/paradigm/matrix/calibration.py @@ -2,20 +2,24 @@ from psychopy import core, visual +from bcipy.acquisition import ClientManager from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE from bcipy.display import InformationProperties, StimuliProperties from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters +from bcipy.helpers.save import save_stimuli_position_info from bcipy.helpers.stimuli import (DEFAULT_TEXT_FIXATION, InquirySchedule, StimuliOrder, TargetPositions, generate_calibration_inquiries) from bcipy.helpers.symbols import alphabet +from bcipy.helpers.system_utils import get_screen_info from bcipy.helpers.task import (get_user_input, pause_calibration, trial_complete_message) from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, - TriggerType, convert_timing_triggers) + TriggerType, convert_timing_triggers, + offset_label) from bcipy.task import Task @@ -35,15 +39,29 @@ class MatrixCalibrationTask(Task): PARAMETERS: ---------- win (PsychoPy Display Object) - daq (Data Acquisition Object) - parameters (Dictionary) + daq (Data Acquisition Object [ClientManager]]) + parameters (Parameters Object) file_save (String) """ - def __init__(self, win, daq, parameters, file_save): + def __init__( + self, + win: visual.Window, + daq: ClientManager, + parameters: Parameters, + file_save: str) -> None: super(MatrixCalibrationTask, self).__init__() self.window = win self.frame_rate = self.window.getActualFrameRate() + + _screen_info = get_screen_info() + + self.screen_info = { + 'screen_size_pixels': self.window.size.tolist(), + 'screen_hz': _screen_info.rate, + 'screen_units': 'norm', + } + self.parameters = parameters self.daq = daq self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) @@ -122,7 +140,7 @@ def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: return TriggerType.TARGET return TriggerType.NONTARGET - def execute(self): + def execute(self) -> str: self.logger.info(f'Starting {self.name()}!') run = True @@ -184,16 +202,20 @@ def execute(self): # Set run to False to stop looping run = False + # Save the grid screenshot + self.matrix.capture_grid_screenshot(self.file_save) + # Say Goodbye! self.matrix.info_text = trial_complete_message( self.window, self.parameters) self.matrix.draw_static() self.window.flip() - # Allow for some training data to be collected + # Allow for some additional data to be collected for later processing core.wait(self.buffer_val) self.write_offset_trigger() + self.write_stimuli_positions() return self.file_save @@ -208,16 +230,14 @@ def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None We do not write the calibration trigger used to generate this offset from the display. See MatrixDisplay._trigger_pulse() for more information. """ - # write offsets. currently, we only check for offsets at the beginning. - if self.daq.is_calibrated and first_run: - self.trigger_handler.add_triggers( - [Trigger( - 'starting_offset', - TriggerType.OFFSET, - # offset will factor in true offset and time relative from beginning - (self.daq.offset(self.matrix.first_stim_time) - self.matrix.first_stim_time) - )] - ) + if first_run: + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + label = offset_label(content_type.name) + time = client.offset( + self.matrix.first_stim_time) - self.matrix.first_stim_time + triggers.append(Trigger(label, TriggerType.OFFSET, time)) + self.trigger_handler.add_triggers(triggers) # make sure triggers are written for the inquiry self.trigger_handler.add_triggers(convert_timing_triggers(timing, timing[0][0], self.trigger_type)) @@ -225,18 +245,28 @@ def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None def write_offset_trigger(self) -> None: """Append an offset value to the end of the trigger file. """ - if self.daq.is_calibrated: - self.trigger_handler.add_triggers( - [Trigger( - 'daq_sample_offset', - TriggerType.SYSTEM, - # to help support future refactoring or use of lsl timestamps only - # we write only the sample offset here - self.daq.offset(self.matrix.first_stim_time) - )]) + # To help support future refactoring or use of lsl timestamps only + # we write only the sample offset here. + triggers = [] + for content_type, client in self.daq.clients_by_type.items(): + label = offset_label(content_type.name, prefix='daq_sample_offset') + time = client.offset(self.matrix.first_stim_time) + triggers.append(Trigger(label, TriggerType.SYSTEM, time)) + + self.trigger_handler.add_triggers(triggers) self.trigger_handler.close() - def name(self): + def write_stimuli_positions(self) -> None: + """Write Stimuli Positions. + + Write the positions of the stimuli to a json file. + """ + save_stimuli_position_info( + self.matrix._stim_positions, + self.file_save, + self.screen_info) + + def name(self) -> str: return 'Matrix Calibration Task' diff --git a/bcipy/task/paradigm/matrix/copy_phrase.py b/bcipy/task/paradigm/matrix/copy_phrase.py index b2f44da69..868944011 100644 --- a/bcipy/task/paradigm/matrix/copy_phrase.py +++ b/bcipy/task/paradigm/matrix/copy_phrase.py @@ -42,7 +42,8 @@ def init_display(self) -> MatrixDisplay: self.experiment_clock, self.spelled_text) -def init_display(parameters, win, experiment_clock, starting_spelled_text) -> MatrixDisplay: +def init_display( + parameters, win, experiment_clock, starting_spelled_text) -> MatrixDisplay: """Constructs a new Matrix display""" info = InformationProperties( diff --git a/bcipy/task/paradigm/rsvp/calibration/calibration.py b/bcipy/task/paradigm/rsvp/calibration/calibration.py index 23aa220b1..325ff5c98 100644 --- a/bcipy/task/paradigm/rsvp/calibration/calibration.py +++ b/bcipy/task/paradigm/rsvp/calibration/calibration.py @@ -1,14 +1,16 @@ from typing import List, Tuple -from psychopy import core +from psychopy import core, visual +from bcipy.acquisition import ClientManager from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE from bcipy.display import (InformationProperties, PreviewInquiryProperties, StimuliProperties) from bcipy.display.components.task_bar import CalibrationTaskBar from bcipy.display.paradigm.rsvp.mode.calibration import CalibrationDisplay from bcipy.helpers.clock import Clock -from bcipy.helpers.stimuli import (StimuliOrder, TargetPositions, +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.stimuli import (InquirySchedule, StimuliOrder, TargetPositions, generate_calibration_inquiries) from bcipy.helpers.symbols import alphabet from bcipy.helpers.task import (get_user_input, pause_calibration, @@ -16,6 +18,7 @@ from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, convert_timing_triggers, offset_label) + from bcipy.task import Task @@ -40,7 +43,12 @@ class RSVPCalibrationTask(Task): file_save (str) """ - def __init__(self, win, daq, parameters, file_save): + def __init__( + self, + win: visual.Window, + daq: ClientManager, + parameters: Parameters, + file_save: str) -> None: super(RSVPCalibrationTask, self).__init__() self.window = win @@ -83,7 +91,7 @@ def __init__(self, win, daq, parameters, file_save): self.is_txt_stim = parameters['is_txt_stim'] self.enable_breaks = parameters['enable_breaks'] - def generate_stimuli(self): + def generate_stimuli(self) -> InquirySchedule: """Generates the inquiries to be presented. Returns: -------- @@ -111,7 +119,7 @@ def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: """ if index == 0: return TriggerType.PROMPT - if symbol == 'inquiry_preview' and index == 1: + if symbol == 'inquiry_preview': return TriggerType.PREVIEW if symbol == '+': return TriggerType.FIXATION @@ -119,7 +127,7 @@ def trigger_type(self, symbol: str, target: str, index: int) -> TriggerType: return TriggerType.TARGET return TriggerType.NONTARGET - def execute(self): + def execute(self) -> str: self.logger.info(f'Starting {self.name()}!') run = True @@ -188,7 +196,7 @@ def execute(self): return self.file_save - def write_trigger_data(self, timing: List[Tuple[str, float]], first_run) -> None: + def write_trigger_data(self, timing: List[Tuple[str, float]], first_run: bool) -> None: """Write Trigger Data. Using the timing provided from the display and calibration information from the data acquisition @@ -227,12 +235,15 @@ def write_offset_trigger(self) -> None: self.trigger_handler.add_triggers(triggers) self.trigger_handler.close() - def name(self): + def name(self) -> str: return 'RSVP Calibration Task' def init_calibration_display_task( - parameters, window, static_clock, experiment_clock): + parameters: Parameters, + window: visual.Window, + static_clock: core.StaticPeriod, + experiment_clock: Clock) -> CalibrationDisplay: info = InformationProperties( info_color=[parameters['info_color']], info_pos=[(parameters['info_pos_x'], diff --git a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py index ba0446a35..55af4b995 100644 --- a/bcipy/task/paradigm/rsvp/calibration/timing_verification.py +++ b/bcipy/task/paradigm/rsvp/calibration/timing_verification.py @@ -1,7 +1,14 @@ -# mypy: disable-error-code="method-assign" +# mypy: disable-error-code="assignment" from itertools import cycle + +from typing import Tuple + +from psychopy import visual + +from bcipy.acquisition import ClientManager from bcipy.task import Task from bcipy.task.paradigm.rsvp.calibration.calibration import RSVPCalibrationTask +from bcipy.helpers.parameters import Parameters from bcipy.helpers.stimuli import PhotoDiodeStimuli, get_fixation, jittered_timing @@ -12,17 +19,22 @@ class RSVPTimingVerificationCalibration(Task): stimuli can be used with a photodiode to ensure accurate presentations. Input: - win (PsychoPy Display Object) - daq (Data Acquisition Object) - parameters (Dictionary) - file_save (String) + win (PsychoPy Window) + daq (ClientManager) + parameters (Parameters) + file_save (str) Output: - file_save (String) + file_save (str) """ TASK_NAME = 'RSVP Timing Verification Task' - def __init__(self, win, daq, parameters, file_save): + def __init__( + self, + win: visual.Window, + daq: ClientManager, + parameters: Parameters, + file_save: str) -> None: super(RSVPTimingVerificationCalibration, self).__init__() parameters['stim_height'] = 0.8 parameters['stim_pos_y'] = 0.0 @@ -30,7 +42,7 @@ def __init__(self, win, daq, parameters, file_save): self._task = RSVPCalibrationTask(win, daq, parameters, file_save) self._task.generate_stimuli = self.generate_stimuli - def generate_stimuli(self): + def generate_stimuli(self) -> Tuple[list, list, list]: """Generates the inquiries to be presented. Returns: -------- @@ -62,13 +74,13 @@ def generate_stimuli(self): return (samples, times, colors) - def execute(self): + def execute(self) -> str: self.logger.info(f'Starting {self.name()}!') - self._task.execute() + return self._task.execute() @classmethod - def label(cls): + def label(cls) -> str: return RSVPTimingVerificationCalibration.TASK_NAME - def name(self): + def name(self) -> str: return RSVPTimingVerificationCalibration.TASK_NAME diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 7c25b0c87..2e3058b8b 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -4,6 +4,7 @@ from psychopy import core, visual +from bcipy.acquisition import ClientManager from bcipy.config import ( SESSION_DATA_FILENAME, SESSION_SUMMARY_FILENAME, @@ -32,6 +33,8 @@ from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, convert_timing_triggers, offset_label) +from bcipy.language.main import LanguageModel +from bcipy.signal.model import SignalModel from bcipy.signal.model.inquiry_preview import compute_probs_after_preview from bcipy.task import Task from bcipy.task.control.evidence import (EvidenceEvaluator, @@ -106,8 +109,15 @@ class RSVPCopyPhraseTask(Task): 'info_pos_x', 'info_pos_y', 'info_color', 'info_height', 'info_text', 'info_color', 'info_height', 'info_text', ] - def __init__(self, win, daq, parameters, file_save, signal_models, - language_model, fake): + def __init__( + self, + win: visual.Window, + daq: ClientManager, + parameters: Parameters, + file_save: str, + signal_models: List[SignalModel], + language_model: LanguageModel, + fake: bool) -> None: super(RSVPCopyPhraseTask, self).__init__() self.logger = logging.getLogger(__name__) self.window = win @@ -172,7 +182,7 @@ def __init__(self, win, daq, parameters, file_save, signal_models, self.rsvp = self.init_display() def init_evidence_evaluators(self, - signal_models) -> List[EvidenceEvaluator]: + signal_models: List[SignalModel]) -> List[EvidenceEvaluator]: """Initializes the evidence evaluators from the provided signal models. Returns a list of evaluators for active devices. Raises an exception if @@ -303,7 +313,7 @@ def user_wants_to_continue(self) -> bool: self.logger.info('User wants to exit.') return should_continue - def wait(self, seconds: Optional[float] = None): + def wait(self, seconds: Optional[float] = None) -> None: """Pause for a time. Parameters @@ -357,7 +367,7 @@ def present_inquiry(self, inquiry_schedule: InquirySchedule return stim_times, proceed - def show_feedback(self, selection: str, correct: bool = True): + def show_feedback(self, selection: str, correct: bool = True) -> None: """Display the selection as feedback if the 'show_feedback' parameter is configured. @@ -679,7 +689,7 @@ def new_data_record(self, data.likelihood = list(self.copy_phrase_task.conjugator.likelihood) return data - def exit_display(self): + def exit_display(self) -> None: """Close the UI and cleanup.""" # Update task state and reset the static self.rsvp.update_task_bar(text=self.spelled_text) @@ -803,7 +813,7 @@ def __init__(self, session: Session, show_preview: bool = False, preview_mode: int = 0, - trigger_path: Optional[str] = None): + trigger_path: Optional[str] = None) -> None: assert preview_mode in range(3), 'Preview mode out of range' self.session = session self.show_preview = show_preview diff --git a/bcipy/task/start_task.py b/bcipy/task/start_task.py index 3a0c1bc25..dd13de528 100644 --- a/bcipy/task/start_task.py +++ b/bcipy/task/start_task.py @@ -1,4 +1,5 @@ """Code for constructing and executing registered tasks""" +# mypy: disable-error-code="arg-type, misc" from typing import List, Optional from psychopy import visual diff --git a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py new file mode 100644 index 000000000..7109ed5a3 --- /dev/null +++ b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py @@ -0,0 +1,315 @@ +import unittest + +from mockito import any, mock, unstub, verify, when +from mock import mock_open, patch +import psychopy +import numpy as np + +import bcipy.task.paradigm.matrix.calibration +from bcipy.acquisition import LslAcquisitionClient +from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.multimodal import ContentType +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.triggers import TriggerHandler, TriggerType +from bcipy.task.paradigm.matrix.calibration import MatrixCalibrationTask + + +class TestMatrixCalibration(unittest.TestCase): + """Tests for Matrix Calibration Task.""" + + def setUp(self): + """Override; set up the needed path for load functions.""" + parameters = { + 'backspace_always_shown': True, + 'break_len': 10, + 'down_sampling_rate': 2, + 'enable_breaks': False, + 'feedback_duration': 2.0, + 'feedback_stim_height': 0.35, + 'feedback_stim_width': 0.35, + 'filter_high': 45.0, + 'filter_low': 2.0, + 'filter_order': 2.0, + 'fixation_color': 'red', + 'font': 'Arial', + 'info_color': 'white', + 'info_height': 0.1, + 'info_pos_x': 0.0, + 'info_pos_y': -0.75, + 'info_text': '', + 'is_txt_stim': True, + 'nontarget_inquiries': 0, + 'notch_filter_frequency': 60.0, + 'prestim_length': 1, + 'preview_inquiry_isi': 1.0, + 'preview_inquiry_length': 5.0, + 'show_feedback': False, + 'show_preview_inquiry': False, + 'static_trigger_offset': 0.1, + 'stim_color': 'white', + 'stim_height': 0.6, + 'stim_jitter': 0.0, + 'stim_length': 3, + 'stim_number': 10, + 'stim_order': 'random', + 'stim_pos_x': 0.0, + 'stim_pos_y': 0.0, + 'stim_space_char': '_', + 'target_color': 'white', + 'target_positions': 'distributed', + 'task_buffer_length': 2, + 'task_color': 'white', + 'task_height': 0.1, + 'task_text': 'HELLO_WORLD', + 'time_fixation': 0.1, + 'time_flash': 0.1, + 'time_prompt': 0.1, + 'trial_window': (0.0, 0.5), + 'trials_before_break': 100, + 'break_message': 'Take a break!', + 'trigger_type': 'image', + } + self.parameters = Parameters.from_cast_values(**parameters) + + self.win = mock({'size': np.array([500, 500]), 'units': 'height'}) + + device_spec = DeviceSpec(name='Testing', + channels=['a', 'b', 'c'], + sample_rate=300.0) + self.eeg_client_mock = mock( + { + 'device_spec': device_spec, + 'is_calibrated': True, + 'offset': lambda x: 0.0, + }, + spec=LslAcquisitionClient) + self.daq = mock( + { + 'device_spec': device_spec, + 'is_calibrated': True, + 'offset': lambda x: 0.0, + 'device_content_types': [ContentType.EEG], + 'clients_by_type': { + ContentType.EEG: self.eeg_client_mock + } + }) + self.temp_dir = '' + self.model_metadata = mock({ + 'device_spec': device_spec, + 'transform': mock(), + 'evidence_type': 'ERP' + }) + + self.display = mock() + self.display.first_stim_time = 0.0 + self.mock_do_inquiry_response = [('a', 0.0), ('+', 0.1), ('b', 0.2), ('c', 0.3), ('a', 0.4)] + when(self.display).do_inquiry().thenReturn(self.mock_do_inquiry_response) + when(self.display).wait_screen().thenReturn(None) + + when(bcipy.task.paradigm.matrix.calibration).init_calibration_display_task( + self.parameters, self.win, any(), any()).thenReturn(self.display) + when(bcipy.task.paradigm.matrix.calibration).trial_complete_message(any(), any()).thenReturn([]) + + when(TriggerHandler).add_triggers(any()).thenReturn() + + when(psychopy.event).getKeys(keyList=any()).thenReturn(['space']) + when(psychopy.core).wait(any()).thenReturn(None) + + def tearDown(self): + """Override""" + unstub() + + def test_initialize(self): + """Test initialization""" + + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + verify(bcipy.task.paradigm.matrix.calibration, times=1).init_calibration_display_task( + self.parameters, self.win, any(), any()) + + def test_execute(self): + """Test task execute""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + when(task).write_stimuli_positions().thenReturn(None) + when(task).write_offset_trigger().thenReturn(None) + when(task).write_trigger_data(any(), any()).thenReturn(None) + + task.execute() + + verify(self.display, times=self.parameters['stim_number']).do_inquiry() + verify(task, times=self.parameters['stim_number']).write_trigger_data(any(), any()) + verify(task, times=1).write_offset_trigger() + + def test_validate_parameters_throws_task_exception_empty_parameter(self): + """Test validate parameters throws task exception when parameters is empty.""" + parameters = {} + + with self.assertRaises(Exception): + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=parameters, + file_save=self.temp_dir) + + def test_execute_save_stimuli_positions(self): + """Test execute save stimuli positions method is called as expected.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + when(bcipy.task.paradigm.matrix.calibration).save_stimuli_position_info( + any(), any(), task.screen_info).thenReturn(None) + when(task).write_offset_trigger().thenReturn(None) + when(task).write_trigger_data(any(), any()).thenReturn(None) + + task.execute() + + verify(bcipy.task.paradigm.matrix.calibration, times=1).save_stimuli_position_info( + any(), any(), task.screen_info) + verify(self.display, times=self.parameters['stim_number']).do_inquiry() + verify(task, times=self.parameters['stim_number']).write_trigger_data(any(), any()) + verify(task, times=1).write_offset_trigger() + + def test_trigger_type_targetness(self): + """Test trigger type targetness.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + # non-target + symbol = 'N' + target = 'X' + index = 1 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.NONTARGET) + + # target + symbol = 'X' + target = 'X' + index = 1 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.TARGET) + + def test_trigger_type_fixation(self): + """Test trigger type fixation.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + # fixation + symbol = '+' + target = 'X' + index = 1 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.FIXATION) + + def test_trigger_type_prompt(self): + """Test trigger type prompt.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + # prompt, index = 0, otherwise it would be a target + symbol = 'P' + target = 'P' + index = 0 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PROMPT) + + def test_write_trigger_data_first_run(self): + """Test write trigger data when it is the first run of the task.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} + timing_mock = mock() + timing = [('a', 0.0)] + first_run = True + when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.paradigm.matrix.calibration).offset_label('EEG').thenReturn('starting_offset') + when(bcipy.task.paradigm.matrix.calibration).convert_timing_triggers( + timing, timing[0][0], any()).thenReturn(timing_mock) + + task.write_trigger_data(timing, first_run) + + verify(TriggerHandler, times=2).add_triggers(any()) + verify(self.eeg_client_mock, times=1).offset(0.0) + verify(bcipy.task.paradigm.matrix.calibration, times=1).offset_label( + 'EEG') + verify(bcipy.task.paradigm.matrix.calibration, times=1).convert_timing_triggers( + timing, timing[0][0], any()) + + def test_write_trigger_data_not_first_run(self): + """Test write trigger data when it is not the first run of the task.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + timing_mock = mock() + timing = [('a', 0.0)] + first_run = False + when(bcipy.task.paradigm.matrix.calibration).convert_timing_triggers( + timing, timing[0][0], any()).thenReturn(timing_mock) + + task.write_trigger_data(timing, first_run) + + verify(TriggerHandler, times=1).add_triggers(any()) + + def test_write_offset_trigger(self): + """Test write offset trigger""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = MatrixCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} + when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.paradigm.matrix.calibration).offset_label( + 'EEG', + prefix='daq_sample_offset').thenReturn('daq_sample_offset') + + when(TriggerHandler).close().thenReturn() + + task.write_offset_trigger() + + verify(TriggerHandler, times=1).close() + verify(TriggerHandler, times=1).add_triggers(any()) + verify(self.eeg_client_mock, times=1).offset(0.0) + verify(bcipy.task.paradigm.matrix.calibration, times=1).offset_label( + 'EEG', prefix='daq_sample_offset') + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py new file mode 100644 index 000000000..66cfa1cc9 --- /dev/null +++ b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py @@ -0,0 +1,310 @@ +import unittest + +from mockito import any, mock, unstub, verify, when +from mock import mock_open, patch + +import psychopy + +import bcipy.task.paradigm.rsvp.calibration.calibration +from bcipy.acquisition import LslAcquisitionClient +from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.multimodal import ContentType +from bcipy.helpers.parameters import Parameters +from bcipy.helpers.triggers import TriggerHandler, TriggerType +from bcipy.task.paradigm.rsvp.calibration.calibration import RSVPCalibrationTask + + +class TestRSVPCalibration(unittest.TestCase): + """Tests for RSVP Calibration Task.""" + + def setUp(self): + """Override; set up the needed path for load functions.""" + parameters = { + 'backspace_always_shown': True, + 'break_len': 10, + 'down_sampling_rate': 2, + 'enable_breaks': False, + 'feedback_duration': 2.0, + 'feedback_stim_height': 0.35, + 'feedback_stim_width': 0.35, + 'filter_high': 45.0, + 'filter_low': 2.0, + 'filter_order': 2.0, + 'fixation_color': 'red', + 'font': 'Arial', + 'info_color': 'white', + 'info_height': 0.1, + 'info_pos_x': 0.0, + 'info_pos_y': -0.75, + 'info_text': '', + 'is_txt_stim': True, + 'nontarget_inquiries': 0, + 'notch_filter_frequency': 60.0, + 'prestim_length': 1, + 'preview_inquiry_isi': 1.0, + 'preview_inquiry_length': 5.0, + 'show_feedback': False, + 'show_preview_inquiry': False, + 'static_trigger_offset': 0.1, + 'stim_color': 'white', + 'stim_height': 0.6, + 'stim_jitter': 0.0, + 'stim_length': 3, + 'stim_number': 10, + 'stim_order': 'random', + 'stim_pos_x': 0.0, + 'stim_pos_y': 0.0, + 'stim_space_char': '_', + 'target_color': 'white', + 'target_positions': 'distributed', + 'task_buffer_length': 2, + 'task_color': 'white', + 'task_height': 0.1, + 'task_text': 'HELLO_WORLD', + 'time_fixation': 0.1, + 'time_flash': 0.1, + 'time_prompt': 0.1, + 'trial_window': (0.0, 0.5), + 'trials_before_break': 100, + 'trigger_type': 'image', + } + self.parameters = Parameters.from_cast_values(**parameters) + + self.win = mock({'size': [500, 500], 'units': 'height'}) + + device_spec = DeviceSpec(name='Testing', + channels=['a', 'b', 'c'], + sample_rate=300.0) + self.eeg_client_mock = mock( + { + 'device_spec': device_spec, + 'is_calibrated': True, + 'offset': lambda x: 0.0, + }, + spec=LslAcquisitionClient) + self.daq = mock( + { + 'device_spec': device_spec, + 'is_calibrated': True, + 'offset': lambda x: 0.0, + 'device_content_types': [ContentType.EEG], + 'clients_by_type': { + ContentType.EEG: self.eeg_client_mock + } + }) + self.temp_dir = '' + self.model_metadata = mock({ + 'device_spec': device_spec, + 'transform': mock(), + 'evidence_type': 'ERP' + }) + + self.display = mock() + self.display.first_stim_time = 0.0 + self.mock_do_inquiry_response = [('a', 0.0), ('+', 0.1), ('b', 0.2), ('c', 0.3), ('a', 0.4)] + when(self.display).do_inquiry(preview_calibration=False).thenReturn(self.mock_do_inquiry_response) + when(self.display).wait_screen().thenReturn(None) + + when(bcipy.task.paradigm.rsvp.calibration.calibration).init_calibration_display_task( + self.parameters, self.win, any(), any()).thenReturn(self.display) + when(bcipy.task.paradigm.rsvp.calibration.calibration).trial_complete_message(any(), any()).thenReturn([]) + when(TriggerHandler).write().thenReturn() + when(TriggerHandler).add_triggers(any()).thenReturn() + + when(psychopy.event).getKeys(keyList=any()).thenReturn(['space']) + when(psychopy.core).wait(any()).thenReturn(None) + + def tearDown(self): + """Override""" + unstub() + + def test_initialize(self): + """Test initialization""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + verify( + bcipy.task.paradigm.rsvp.calibration.calibration, + times=1).init_calibration_display_task( + self.parameters, + self.win, + any(), + any()) + + def test_execute(self): + """Test task execute""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + when(task).write_offset_trigger().thenReturn(None) + when(task).write_trigger_data(any(), any()).thenReturn(None) + + task.execute() + + verify(self.display, times=self.parameters['stim_number']).do_inquiry(preview_calibration=False) + verify(task, times=self.parameters['stim_number']).write_trigger_data(any(), any()) + verify(task, times=1).write_offset_trigger() + + def test_validate_parameters_throws_task_exception_empty_parameter(self): + """Test validate parameters throws task exception when parameters is empty.""" + parameters = {} + + with self.assertRaises(Exception): + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=parameters, + file_save=self.temp_dir) + + def test_trigger_type_targetness(self): + """Test trigger type targetness.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + # non-target + symbol = 'N' + target = 'X' + index = 2 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.NONTARGET) + + # target + symbol = 'X' + target = 'X' + index = 1 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.TARGET) + + def test_trigger_type_fixation(self): + """Test trigger type fixation.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + # fixation + symbol = '+' + target = 'X' + index = 1 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.FIXATION) + + def test_trigger_type_prompt(self): + """Test trigger type prompt.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + # prompt, index = 0, otherwise it would be a target + symbol = 'P' + target = 'P' + index = 0 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PROMPT) + + def test_trigger_type_preview(self): + """Test trigger type preview.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + # preview, index > 0, otherwise it would be a prompt + symbol = 'inquiry_preview' + target = 'P' + index = 1 + + self.assertEqual(task.trigger_type(symbol, target, index), TriggerType.PREVIEW) + + def test_write_trigger_data_first_run(self): + """Test write trigger data when it is the first run of the task.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} + timing_mock = mock() + timing = [('a', 0.0)] + first_run = True + when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.paradigm.rsvp.calibration.calibration).offset_label('EEG').thenReturn('starting_offset') + when(bcipy.task.paradigm.rsvp.calibration.calibration).convert_timing_triggers( + timing, timing[0][0], any()).thenReturn(timing_mock) + + task.write_trigger_data(timing, first_run) + + verify(TriggerHandler, times=2).add_triggers(any()) + verify(self.eeg_client_mock, times=1).offset(0.0) + verify(bcipy.task.paradigm.rsvp.calibration.calibration, times=1).offset_label( + 'EEG') + verify(bcipy.task.paradigm.rsvp.calibration.calibration, times=1).convert_timing_triggers( + timing, timing[0][0], any()) + + def test_write_trigger_data_not_first_run(self): + """Test write trigger data when it is not the first run of the task.""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + + timing_mock = mock() + timing = [('a', 0.0)] + first_run = False + when(bcipy.task.paradigm.rsvp.calibration.calibration).convert_timing_triggers( + timing, timing[0][0], any()).thenReturn(timing_mock) + + task.write_trigger_data(timing, first_run) + + verify(TriggerHandler, times=1).add_triggers(any()) + + def test_write_offset_trigger(self): + """Test write offset trigger""" + with patch('bcipy.helpers.triggers.open', mock_open(read_data=''), create=False): + task = RSVPCalibrationTask( + win=self.win, + daq=self.daq, + parameters=self.parameters, + file_save=self.temp_dir) + client_by_type_resp = {ContentType.EEG: self.eeg_client_mock} + when(self.daq).client_by_type(ContentType.EEG).thenReturn(client_by_type_resp) + when(bcipy.task.paradigm.rsvp.calibration.calibration).offset_label( + 'EEG', + prefix='daq_sample_offset').thenReturn('daq_sample_offset') + + when(TriggerHandler).close().thenReturn() + + task.write_offset_trigger() + + verify(TriggerHandler, times=1).close() + verify(TriggerHandler, times=1).add_triggers(any()) + verify(self.eeg_client_mock, times=1).offset(0.0) + verify(bcipy.task.paradigm.rsvp.calibration.calibration, times=1).offset_label( + 'EEG', prefix='daq_sample_offset') + + +if __name__ == '__main__': + unittest.main() diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index e010e4fc2..68fb1e794 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -2,7 +2,6 @@ import shutil import tempfile import unittest -import pytest from pathlib import Path import numpy as np @@ -23,7 +22,6 @@ from bcipy.task.paradigm.rsvp.copy_phrase import RSVPCopyPhraseTask -@pytest.mark.slow class TestCopyPhrase(unittest.TestCase): """Tests for Copy Phrase task.""" diff --git a/requirements.txt b/requirements.txt index 22d14f0cc..128be55b8 100644 --- a/requirements.txt +++ b/requirements.txt @@ -21,5 +21,6 @@ Pillow==9.4.0 py-cpuinfo==9.0.0 pyedflib==0.1.34 PyQt6==6.6.0 +PyQt6-Qt6==6.6.0 pywavelets==1.4.1 tqdm==4.62.2 \ No newline at end of file From 79e73fc8d4dca0f46d2cd666c2e6ad55f78133c9 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 5 Dec 2023 16:54:49 -0800 Subject: [PATCH 179/330] Updated parameter description with correct default --- bcipy/parameters/parameters.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 5c72ac995..0a4347700 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -527,7 +527,7 @@ "value": "0.05", "section": "bci_config", "readableName": "Task Bar Padding", - "helpTip": "Specifies the padding around the task bar text. Default: 0.1", + "helpTip": "Specifies the padding around the task bar text. Default: 0.05", "recommended_values": [ "0.05" ], From 5ef26268dac4a11cc9bd7f2b4813fd89827a7464 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 7 Dec 2023 13:57:36 -0800 Subject: [PATCH 180/330] Bump wxpython version requirements needed for successful installation on Apple M2 computers --- requirements-winmac.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/requirements-winmac.txt b/requirements-winmac.txt index 2e3de9ed7..36616d5f4 100644 --- a/requirements-winmac.txt +++ b/requirements-winmac.txt @@ -1 +1 @@ -WxPython==4.1.1 +WxPython==4.2.1 From 8cf0ce73da97c4e7dd65bc1d133fe209b5c14153 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 7 Dec 2023 17:17:18 -0800 Subject: [PATCH 181/330] Removed parameter for VEP flicker rate configuration --- bcipy/display/paradigm/vep/codes.py | 2 ++ bcipy/parameters/parameters.json | 8 -------- bcipy/task/paradigm/vep/calibration.py | 8 +++++--- 3 files changed, 7 insertions(+), 11 deletions(-) diff --git a/bcipy/display/paradigm/vep/codes.py b/bcipy/display/paradigm/vep/codes.py index 14b9fdeee..e96067e3d 100644 --- a/bcipy/display/paradigm/vep/codes.py +++ b/bcipy/display/paradigm/vep/codes.py @@ -8,6 +8,8 @@ log = logging.getLogger(__name__) +DEFAULT_FLICKER_RATES = [4, 5, 6, 10, 12, 15] + def create_vep_codes(length=32, count=4) -> List[List[int]]: """Create a list of random VEP codes. diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 6c4565c2a..90eb22511 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -375,14 +375,6 @@ "recommended_values": "", "type": "float" }, - "vep_flicker_rates": { - "value": "4,5,6,10,12,15", - "section": "bci_config", - "readableName": "VEP Flicker Rates (hz)", - "helpTip": "Delimited list of flash rates, where a rate represents the hz of the box at that position. Each rate should be less than the refresh rate of the monitor.", - "recommended_values": "4,5,6,10,12,15", - "type": "str" - }, "stim_jitter": { "value": "0.0", "section": "bci_config", diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 29030bbe6..8147ea8f3 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -8,7 +8,9 @@ from bcipy.display import InformationProperties, VEPStimuliProperties from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar -from bcipy.display.paradigm.vep.codes import round_refresh_rate, ssvep_to_code +from bcipy.display.paradigm.vep.codes import (DEFAULT_FLICKER_RATES, + round_refresh_rate, + ssvep_to_code) from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock @@ -243,8 +245,8 @@ def init_calibration_display(parameters: Parameters, font=parameters['font'], height=parameters['task_height']) - # create codes from configuration - flicker_rates = parameters['vep_flicker_rates'].split(',') + # issue #186641183 ; determine a better configuration strategy + flicker_rates = DEFAULT_FLICKER_RATES rate = round_refresh_rate(window.getActualFrameRate()) codes = [ ssvep_to_code(refresh_rate=rate, flicker_rate=int(hz)) From 8e58b5b9ff3e839d313b9115286d5be420b7e599 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 7 Dec 2023 17:45:34 -0800 Subject: [PATCH 182/330] Removed option to layout VEP with 4 boxes --- bcipy/display/demo/components/demo_layouts.py | 4 +- .../display/demo/vep/demo_calibration_vep.py | 3 +- bcipy/display/paradigm/vep/layout.py | 22 +++----- bcipy/display/tests/vep/test_vep_layout.py | 52 ------------------- bcipy/task/paradigm/vep/calibration.py | 5 +- 5 files changed, 11 insertions(+), 75 deletions(-) diff --git a/bcipy/display/demo/components/demo_layouts.py b/bcipy/display/demo/components/demo_layouts.py index 234107fb4..a65821110 100644 --- a/bcipy/display/demo/components/demo_layouts.py +++ b/bcipy/display/demo/components/demo_layouts.py @@ -2,7 +2,7 @@ import logging import sys import time -from typing import Optional, Callable, List, Tuple, Union +from typing import Callable, List, Optional, Tuple, Union from psychopy import visual from psychopy.visual.circle import Circle @@ -132,7 +132,7 @@ def demo_vep(win: visual.Window): layout = centered(width_pct=0.9, height_pct=0.9) layout.parent = win - box_config = BoxConfiguration(layout, num_boxes=4, height_pct=0.28) + box_config = BoxConfiguration(layout, height_pct=0.28) size = box_config.box_size positions = box_config.positions diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 57bc1e2a8..83fdb43c8 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -28,7 +28,6 @@ ) task_text = ['1/3', '2/3', '3/3'] -num_boxes = 6 window_parameters = { 'full_screen': False, @@ -56,7 +55,7 @@ ] layout = centered(width_pct=0.95, height_pct=0.80) -box_config = BoxConfiguration(layout, num_boxes=num_boxes, height_pct=0.30) +box_config = BoxConfiguration(layout, height_pct=0.30) experiment_clock = Clock() len_stimuli = 10 diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index 2a873c044..944d1c2a0 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -2,7 +2,7 @@ from itertools import cycle from math import sqrt -from typing import List, NamedTuple, Optional, Tuple +from typing import List, NamedTuple, Tuple from bcipy.display.components.layout import (Layout, above, below, left_of, right_of) @@ -89,11 +89,11 @@ def checkerboard(squares: int, colors: Tuple[str, str], center: Tuple[float, class BoxConfiguration(): """Computes box size and positions for a VEP display. - In this configuration, there is one row on top and one on the bottom. + In this configuration, there are 6 areas configured with one row of 3 on top + and one row on the bottom. Parameters ---------- - num_boxes - number of boxes; currently supports 4 or 6. layout - defines the boundaries within a Window in which the text areas will be placed spacing_pct - used to specify spacing between boxes within a row. @@ -102,30 +102,25 @@ class BoxConfiguration(): def __init__(self, layout: Layout, - num_boxes: int, - spacing_pct: Optional[float] = None, + spacing_pct: float = 0.05, height_pct: float = 0.25): self.layout = layout - self.num_boxes = num_boxes self.height_pct = height_pct self.validate() - default_spacing = {4: 0.1, 6: 0.05} - if not spacing_pct: - spacing_pct = default_spacing[num_boxes] self.spacing_pct = spacing_pct + self._num_boxes = 6 self._row_count = 2 def validate(self): """Validate invariants""" - assert self.num_boxes == 4 or self.num_boxes == 6, 'Number of boxes must be 4 or 6' assert self.height_pct <= 0.5, "Rows can't take more than 50% of the height" def _box_size(self, validate: bool = True) -> Tuple[float, float]: """Computes the size of each box""" if validate: self.validate() - number_per_row = self.num_boxes / self._row_count + number_per_row = self._num_boxes / self._row_count # left and right boxes go to the edges, with a space between each box spaces_per_row = number_per_row - 1 @@ -165,9 +160,6 @@ def positions(self) -> List[Tuple]: left = right_of(layout.left, width / 2) right = left_of(layout.right, width / 2) - if self.num_boxes == 4: - return [(left, top), (right, top), (left, bottom), (right, bottom)] - middle = layout.horizontal_middle return [(left, top), (middle, top), (right, top), (left, bottom), (middle, bottom), (right, bottom)] @@ -175,8 +167,6 @@ def positions(self) -> List[Tuple]: @property def names(self) -> List[str]: """Box names for each position.""" - if self.num_boxes == 4: - return ['LEFT_TOP', 'RIGHT_TOP', 'LEFT_BOTTOM', 'RIGHT_BOTTOM'] return [ 'LEFT_TOP', 'MIDDLE_TOP', 'RIGHT_TOP', 'LEFT_BOTTOM', 'MIDDLE_BOTTOM', 'RIGHT_BOTTOM' diff --git a/bcipy/display/tests/vep/test_vep_layout.py b/bcipy/display/tests/vep/test_vep_layout.py index b73bf62fa..5baf7b8a1 100644 --- a/bcipy/display/tests/vep/test_vep_layout.py +++ b/bcipy/display/tests/vep/test_vep_layout.py @@ -61,44 +61,10 @@ def test_checkerboard_inverse(self): self.assertEqual(square.inverse_color(colors), 'green') - def test_4_box_config_defaults(self): - """Test box configuration""" - full_window = Layout() - config = BoxConfiguration(layout=full_window, - num_boxes=4, - height_pct=0.25, - spacing_pct=0.1) - width, height = config.box_size - window_width, window_height = full_window.size - - self.assertEqual(window_width, 2.0) - self.assertEqual(window_height, 2.0) - self.assertEqual( - width, - 0.9, - msg="Box width should be half of the remaining width after accounting for the spacing." - ) - self.assertEqual( - height, - 0.5, - msg="Box height should be height_pct of the window height") - - positions = config.positions - self.assertEqual(len(positions), 4) - self.assertTrue((-0.55, 0.75) in positions, - msg="A box should be positioned at the top left") - self.assertTrue((0.55, 0.75) in positions, - msg="A box should be positioned at the top right") - self.assertTrue((-0.55, -0.75) in positions, - msg="A box should be positioned at the bottom left") - self.assertTrue((0.55, -0.75) in positions, - msg="A box should be positioned at the bottom right") - def test_6_box_config_defaults(self): """Test box configuration""" full_window = Layout() config = BoxConfiguration(layout=full_window, - num_boxes=6, height_pct=0.25, spacing_pct=0.05) self.assertEqual( @@ -110,21 +76,3 @@ def test_6_box_config_defaults(self): self.assertEqual(len([box for box in positions if box[0] == 0.0]), 2, msg="Two boxes should be positioned in the middle") - - def test_other_box_config(self): - """Test supported number of boxes""" - full_window = Layout() - with self.assertRaises(AssertionError): - BoxConfiguration(layout=full_window, - num_boxes=2, - height_pct=0.25, - spacing_pct=0.05) - - def test_height_pct_validation(self): - """Test validations""" - full_window = Layout() - with self.assertRaises(AssertionError): - BoxConfiguration(layout=full_window, - num_boxes=4, - height_pct=0.6, - spacing_pct=0.1) diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 8147ea8f3..eca996da9 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -215,8 +215,7 @@ def init_calibration_display(parameters: Parameters, experiment_clock, symbol_set, timing, - colors, - num_boxes=6): + colors): """Initialize the display""" info = InformationProperties( info_color=[parameters['info_color']], @@ -227,7 +226,7 @@ def init_calibration_display(parameters: Parameters, ) layout = centered(width_pct=0.95, height_pct=0.80) - box_config = BoxConfiguration(layout, num_boxes=num_boxes, height_pct=0.30) + box_config = BoxConfiguration(layout, height_pct=0.30) stim_props = VEPStimuliProperties(stim_font=parameters['font'], stim_pos=box_config.positions, From e3510b2e66f09dd75de6ddff93ecb294d25ec157 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 8 Dec 2023 11:11:39 -0800 Subject: [PATCH 183/330] Add missing property --- bcipy/display/paradigm/vep/layout.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index 944d1c2a0..2fa27973c 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -133,6 +133,11 @@ def _box_size(self, validate: bool = True) -> Tuple[float, float]: return (width, height) + @property + def num_boxes(self) -> int: + """The number of boxes""" + return self._num_boxes + @property def box_size(self) -> Tuple[float, float]: """Size of each box""" From 73815888908a3fd8bcba32e911140f673dd2287a Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 8 Dec 2023 11:53:00 -0800 Subject: [PATCH 184/330] Added typings; fixed linting; fixed broken tests --- .../display/demo/vep/demo_calibration_vep.py | 24 ++++++++++++------- bcipy/display/paradigm/vep/display.py | 9 ++++--- bcipy/display/paradigm/vep/layout.py | 2 +- bcipy/helpers/system_utils.py | 7 ++++-- bcipy/task/paradigm/vep/calibration.py | 10 ++++---- 5 files changed, 32 insertions(+), 20 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 83fdb43c8..566b80209 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -7,10 +7,12 @@ init_display_window) from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar -from bcipy.display.paradigm.vep.codes import ssvep_to_code +from bcipy.display.paradigm.vep.codes import (DEFAULT_FLICKER_RATES, + ssvep_to_code) from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock +from bcipy.helpers.system_utils import get_screen_info root = logging.getLogger() root.setLevel(logging.DEBUG) @@ -28,19 +30,22 @@ ) task_text = ['1/3', '2/3', '3/3'] - +stim_screen = 0 window_parameters = { 'full_screen': False, 'window_height': 700, 'window_width': 700, - 'stim_screen': 1, + 'stim_screen': stim_screen, 'background_color': 'black' } win = init_display_window(window_parameters) win.recordFrameIntervals = True -frameRate = win.getActualFrameRate() +frame_rate = win.getActualFrameRate() +if not frame_rate: + # Allow the demo to work using the configured rate. + frame_rate = get_screen_info(stim_screen).rate -print(f'Monitor refresh rate: {frameRate} Hz') +print(f'Monitor refresh rate: {frame_rate} Hz') stim_color = [ 'green', 'red', '#00FF80', '#FFFFB3', '#CB99FF', '#FB8072', '#80B1D3', @@ -48,9 +53,9 @@ ] # Note: these rates work for a 60hz display -flicker_rates = [4, 5, 6, 10, 12, 15] +flicker_rates = DEFAULT_FLICKER_RATES codes = [ - ssvep_to_code(refresh_rate=60, flicker_rate=hz) + ssvep_to_code(refresh_rate=int(frame_rate), flicker_rate=hz) for hz in flicker_rates ] @@ -67,7 +72,7 @@ stim_color=stim_color, inquiry=[], stim_length=1, # how many times to stimuli - animation_seconds=1.0) + animation_seconds=2.0) task_bar = CalibrationTaskBar(win, inquiry_count=3, current_index=0, font=font) vep = VEPDisplay(win, experiment_clock, @@ -76,7 +81,8 @@ info, box_config=box_config, codes=codes, - should_prompt_target=True) + should_prompt_target=True, + frame_rate=frame_rate) wait_seconds = 2 inquiries: List[List[Any]] = [[ diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 6f7c3bba4..0576f81b4 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -48,10 +48,13 @@ def __init__(self, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, codes: Optional[List[List[int]]] = None, - should_prompt_target: bool = True): + should_prompt_target: bool = True, + frame_rate: Optional[float] = None): self.window = window - frame_rate = self.window.getActualFrameRate() - assert frame_rate, 'An accurate window frame rate could not be established' + if not frame_rate: + frame_rate = self.window.getActualFrameRate() + assert frame_rate, 'An accurate window frame rate could not be established' + self.window_size = self.window.size # [w, h] self.refresh_rate = round_refresh_rate(frame_rate) self.logger = logging.getLogger(__name__) diff --git a/bcipy/display/paradigm/vep/layout.py b/bcipy/display/paradigm/vep/layout.py index 2fa27973c..6fbfa4e75 100644 --- a/bcipy/display/paradigm/vep/layout.py +++ b/bcipy/display/paradigm/vep/layout.py @@ -137,7 +137,7 @@ def _box_size(self, validate: bool = True) -> Tuple[float, float]: def num_boxes(self) -> int: """The number of boxes""" return self._num_boxes - + @property def box_size(self) -> Tuple[float, float]: """Size of each box""" diff --git a/bcipy/helpers/system_utils.py b/bcipy/helpers/system_utils.py index f0bd30d5c..6b9450404 100644 --- a/bcipy/helpers/system_utils.py +++ b/bcipy/helpers/system_utils.py @@ -134,7 +134,7 @@ def bcipy_version() -> str: return f'{version} - {sha_hash}' if sha_hash else version -def get_screen_info() -> ScreenInfo: +def get_screen_info(stim_screen: Optional[int] = None) -> ScreenInfo: """Gets the screen information. Note: Use this method if only the screen resolution is needed; it is much more efficient @@ -144,7 +144,10 @@ def get_screen_info() -> ScreenInfo: ------- ScreenInfo(width, height, rate) """ - screen = pyglet.canvas.get_display().get_default_screen() + if stim_screen: + screen = pyglet.canvas.get_display().get_screens()[stim_screen] + else: + screen = pyglet.canvas.get_display().get_default_screen() return ScreenInfo(screen.width, screen.height, screen.get_mode().rate) diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index eca996da9..7761766ab 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -211,11 +211,11 @@ def name(self): def init_calibration_display(parameters: Parameters, - window, - experiment_clock, - symbol_set, - timing, - colors): + window: visual.Window, + experiment_clock: Clock, + symbol_set: List[str], + timing: List[float], + colors: List[str]) -> VEPDisplay: """Initialize the display""" info = InformationProperties( info_color=[parameters['info_color']], From 90aa3f2388d8d8f898c99478c04341b065d3788a Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 8 Dec 2023 15:01:20 -0800 Subject: [PATCH 185/330] Added debugging for frame rate --- bcipy/display/paradigm/vep/display.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 0576f81b4..ee7b0515a 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -322,7 +322,7 @@ def draw_animation(self, stimuli: List[StimProps]) -> None: start_pos = self.starting_position(sym) animation_paths[sym] = animation_path(start_pos, end_pos, frames) - + counter = 0 self.static_clock.reset() while self.static_clock.getTime() < self.timing_animation: for frame in range(frames): @@ -332,6 +332,10 @@ def draw_animation(self, stimuli: List[StimProps]) -> None: sti.draw() self.draw_static() self.window.flip() + counter += 1 + self.logger.debug( + f"{counter} animation frames rendered in {self.timing_animation} seconds" + ) def draw_boxes(self) -> None: """Draw the text boxes under VEP stimuli.""" From 5a550d13ce5d5ae942d1b07453b795841eaafd27 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 12 Dec 2023 09:37:46 -0800 Subject: [PATCH 186/330] Cleanup --- bcipy/acquisition/__init__.py | 7 ++++--- bcipy/helpers/acquisition.py | 2 +- 2 files changed, 5 insertions(+), 4 deletions(-) diff --git a/bcipy/acquisition/__init__.py b/bcipy/acquisition/__init__.py index d5430a2ee..40f326ea3 100644 --- a/bcipy/acquisition/__init__.py +++ b/bcipy/acquisition/__init__.py @@ -1,9 +1,10 @@ -from bcipy.acquisition.protocols.lsl.lsl_client import (LslAcquisitionClient, - discover_device_spec) from bcipy.acquisition.datastream.lsl_server import LslDataServer, await_start from bcipy.acquisition.multimodal import ClientManager +from bcipy.acquisition.protocols.lsl.lsl_client import (LslAcquisitionClient, + discover_device_spec) +from bcipy.acquisition.record import Record __all__ = [ 'LslAcquisitionClient', 'LslDataServer', 'await_start', - 'discover_device_spec', 'ClientManager' + 'discover_device_spec', 'ClientManager', 'Record' ] diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index 46c76bac6..6da6911f2 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -165,7 +165,7 @@ def init_lsl_client(parameters: dict, """Initialize a client that acquires data from LabStreamingLayer.""" data_buffer_seconds = round(max_inquiry_duration(parameters)) - + log.info(f"Setting an acquisition buffer of {data_buffer_seconds} seconds") return LslAcquisitionClient(max_buffer_len=data_buffer_seconds, device_spec=device_spec, save_directory=save_folder, From 5311d97f180263774c5a647616c54fa396f96454 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Tue, 12 Dec 2023 13:50:02 -0500 Subject: [PATCH 187/330] recording metrics and storing series_results bug fix --- .gitignore | 7 +- bcipy/simulator/__init__.py | 2 +- bcipy/simulator/__main__.py | 1 + bcipy/simulator/helpers/data_engine.py | 2 +- bcipy/simulator/helpers/metrics.py | 99 +++++++++++++++++++++++- bcipy/simulator/helpers/state_manager.py | 6 +- bcipy/simulator/sim.py | 4 +- bcipy/simulator/sim_factory.py | 6 +- 8 files changed, 114 insertions(+), 13 deletions(-) diff --git a/.gitignore b/.gitignore index 5a944e305..48f9a773f 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,8 @@ *.pyc *~ +*.png +*.csv +*.kenlm .DS_Store .cache/ .vscode/ @@ -28,6 +31,8 @@ dist/ bcipy/parameters/parameters_* bcipy_cache -bcipy/language/lms/lm_dec19_char_large_12gram.* +bcipy/language/lms/ bcipy/language/lms/out_* bcipy/language/out/ + + diff --git a/bcipy/simulator/__init__.py b/bcipy/simulator/__init__.py index 2a543a621..181cfd2de 100644 --- a/bcipy/simulator/__init__.py +++ b/bcipy/simulator/__init__.py @@ -14,7 +14,7 @@ # Create a log format using Log Record attributes fmt_file = logging.Formatter( - "%(asctime)s | %(levelname)s | %(filename)s:%(lineno)s >> %(message)s" + "%(levelname)s | %(filename)s:%(lineno)s >> %(message)s" ) fmt = logging.Formatter( diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 8777f5e07..b93f7b295 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -25,4 +25,5 @@ args = vars(parser.parse_args()) simulator: Simulator = SimulationFactoryV2.create(**args) + simulator.run() diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 234df0aa2..73661a50a 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -91,7 +91,7 @@ def transform(self) -> DataEngine: self for chaining """ - cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] # TODO store how good evidence was in session + cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] # TODO store how good evidence was in session | store data source as well types = [int, int, int, str, int, np.ndarray] rows = [] diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py index 3352c49a3..284bb615f 100644 --- a/bcipy/simulator/helpers/metrics.py +++ b/bcipy/simulator/helpers/metrics.py @@ -1,9 +1,100 @@ -from abc import ABC +from abc import ABC, abstractmethod +from dataclasses import dataclass +from functools import reduce +from typing import Dict, Any, Optional, List + +import numpy as np + +from bcipy.simulator.helpers.state_manager import SimState +from bcipy.simulator.helpers.types import InquiryResult +from bcipy.simulator.simulator_base import Simulator + + +@dataclass +class SimMetrics1: + total_series: Optional[int] = None + total_inquiries: Optional[int] = None + total_decisions: Optional[int] = None + total_time_spent: Optional[float] = None + + inquiries_per_selection: Optional[float] = None + + +class RefereeHandler(ABC): + @abstractmethod + def handle(self, sim: Simulator) -> Dict[str, Any]: + ... + + +class SimMetrics1Handler(RefereeHandler): + + def handle(self, sim: Simulator) -> Dict[str, Any]: + state: SimState = sim.__getattribute__("state_manager").get_state() + + info: Dict = SimMetrics1().__dict__ + info['total_inquiries'] = state.total_inquiry_count() + info['total_series'] = state.series_n + + flattened_inquiries: List[InquiryResult] = reduce(lambda l1, l2: l1 + l2, state.series_results, []) + info['total_decisions'] = len(list(filter(lambda inq: bool(inq.decision), flattened_inquiries))) + + inq_counts = [] + for series in state.series_results: + if [inq for inq in series if inq.decision]: + inq_counts.append(len(series)) + info['inquiries_per_selection'] = round(np.array(inq_counts).mean(), 3) + + return info class MetricReferee(ABC): - ... + # May change to SimState that is passed around not whole Simulator + # Depends on how much data encapsulated by SimState + @abstractmethod + def score(self, sim: Simulator) -> SimMetrics1: + ... + + @abstractmethod + def visualize(self, sim: Simulator): + ... + + @abstractmethod + def set_metric_handler(self, name: str, handler: RefereeHandler): + ... + + @abstractmethod + def set_viz_handler(self, name: str, handler: RefereeHandler): + ... + + +class RefereeImpl(MetricReferee): + + def __init__(self, metric_handlers=None, viz_handlers=None): + self.metric_handlers: Dict[str, RefereeHandler] = metric_handlers if metric_handlers else dict() + self.viz_handlers: Dict[str, RefereeHandler] = viz_handlers if viz_handlers else dict() + + self.inquiry_time: float = 1 # 1 inq -> 1 second + # TODO maybe some configurable parameters for visualizations + + def score(self, sim: Simulator) -> SimMetrics1: + metrics = SimMetrics1() + metrics_dict = metrics.__dict__ + for handler_name, handler in self.metric_handlers.items(): + handler_metrics = handler.handle(sim) + + for key, val in handler_metrics.items(): + if key in metrics_dict: + metrics_dict[key] = val + + return SimMetrics1(**metrics_dict) + + def visualize(self, sim: Simulator): + for handler_name, viz_handler in self.viz_handlers.items(): + viz_handler.handle(sim) + + def set_metric_handler(self, name: str, handler: RefereeHandler): + self.metric_handlers[name] = handler -class DummyRef(MetricReferee): - pass + def set_viz_handler(self, name: str, handler: RefereeHandler): + self.viz_handlers[name] = handler diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index e5013365a..e7ec80a72 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -67,7 +67,7 @@ def __init__(self, parameters: Parameters, fuser_class=MultiplyFuser): self.parameters = parameters self.fuser_class: EvidenceFuser.__class__ = fuser_class - self.max_inq_len = self.parameters.get('max_inq_len', 50) + self.max_inq_len = self.parameters.get('max_inq_len', 100) def is_done(self) -> bool: # TODO add stoppage criterion, Stoppage criterion is seperate from decision. Decision should we go on to next letter or not @@ -93,6 +93,10 @@ def update(self, evidence) -> InquiryResult: decision = None new_state = self.get_state().__dict__ + new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, + evidence_likelihoods=list(evidence), decision=decision, fused_likelihood=fused_likelihood) + + new_state['series_results'][self.state.series_n].append(new_inquiry_result) if is_decidable: decision = alphabet()[np.argmax(evidence)] # deciding the maximum probability symbol TODO abstract diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 7697e0836..ac7559005 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -87,9 +87,11 @@ def run(self): final_state = self.state_manager.get_state() log.info(f"SIM END") + log.info(f"FINAL TYPED: {final_state.current_sentence}") + log.info(self.referee.score(self).__dict__) + log.debug(f"Final State: {final_state}") - # TODO visualize result metrics def __make_stimuli(self, state: SimState): # TODO abstract out diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 70eaeb154..9a1fdfc03 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -1,12 +1,10 @@ from pathlib import Path from typing import List -import numpy as np - from bcipy.config import DEFAULT_PARAMETER_FILENAME from bcipy.helpers.load import load_json_parameters from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.metrics import MetricReferee, DummyRef +from bcipy.simulator.helpers.metrics import MetricReferee, RefereeImpl, SimMetrics1Handler from bcipy.simulator.helpers.model_handler import SignalModelHandler1, ModelHandler from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler from bcipy.simulator.helpers.state_manager import StateManager, StateManagerImpl @@ -51,7 +49,7 @@ def create(data_folders: List[str], smodel_files: List[str], sim_param_path="bci stateManager: StateManager = StateManagerImpl(sim_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) model_handler: ModelHandler = SignalModelHandler1(model_file) - referee: MetricReferee = DummyRef() + referee: MetricReferee = RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()}) sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, referee) From b3371feb659c239d6a9e5022578d2ff2ea59ce86 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 12 Dec 2023 11:06:23 -0800 Subject: [PATCH 188/330] Fixed bug in highlighting target box --- bcipy/display/paradigm/vep/display.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index ee7b0515a..f52d43ad4 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -209,7 +209,7 @@ def prompt_target(self, target - (symbol, duration, color) tuple """ assert isinstance(target.symbol, str), "Target must be a str" - self.logger.info(f"Target: {target.symbol}") + self.logger.info(f"Target: {target.symbol} at index {target_box_index}") # Show all symbols in the matrix at reduced opacity for sym in self.symbol_set: @@ -233,7 +233,7 @@ def prompt_target(self, for sti in self.sti.values(): sti.draw() - if target_box_index: + if target_box_index is not None: self.highlight_target_box(target_box_index) self.draw_static() From 92836580dd959e9af80e6187bbbe74a19f4e92af Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 12 Dec 2023 14:40:14 -0800 Subject: [PATCH 189/330] Hide all letters before showing checkerboard stim --- bcipy/display/paradigm/vep/display.py | 1 + 1 file changed, 1 insertion(+) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index f52d43ad4..993838d20 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -185,6 +185,7 @@ def do_inquiry(self) -> List[StimTime]: # type: ignore self.log_inquiry(stim) self.animate_inquiry(stim) core.wait(self.timing_fixation) + self._reset_text_boxes() self.stimulate() # clear everything expect static stimuli From 2abc4eefc60839d80e1f4b576201dd5af6e09a08 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 14 Dec 2023 15:48:32 -0800 Subject: [PATCH 190/330] #186539529 ; restructure lsl_client to address a data buffering issue that occurs with the latest LSL versions --- bcipy/acquisition/protocols/lsl/lsl_client.py | 113 ++++++++++++------ bcipy/acquisition/record.py | 14 ++- requirements.txt | 2 +- 3 files changed, 87 insertions(+), 42 deletions(-) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index d8571f18b..3e21a73ea 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -1,7 +1,8 @@ """DataAcquisitionClient for LabStreamingLayer data sources.""" import logging -from typing import Optional, List +from typing import Dict, List, Optional +import pandas as pd from pylsl import (StreamInfo, StreamInlet, local_clock, resolve_byprop, resolve_stream) @@ -54,6 +55,26 @@ def __init__(self, self.max_buffer_len = max_buffer_len self.save_directory = save_directory self.raw_data_file_name = raw_data_file_name + self._max_samples = None + + @property + def first_sample_time(self) -> float: + """Timestamp returned by the first sample. If the data is being + recorded this value reflects the timestamp of the first recorded sample""" + if self.recorder: + return self.recorder.first_sample_time + return self._first_sample_time + + @property + def max_samples(self) -> int: + """Maximum number of samples available at any given time.""" + if self._max_samples is None: + if self.device_spec.sample_rate == IRREGULAR_RATE: + self._max_samples = int(self.max_buffer_len) + else: + self._max_samples = int(self.max_buffer_len * + self.device_spec.sample_rate) + return self._max_samples def start_acquisition(self) -> bool: """Connect to the datasource and start acquiring data. @@ -74,7 +95,7 @@ def start_acquisition(self) -> bool: self.inlet = StreamInlet( stream_info, - max_buflen=self.max_buffer_len, + max_buflen=4 * self.max_buffer_len, # TODO: revisit this value max_chunklen=1) if self.device_spec: @@ -95,14 +116,6 @@ def start_acquisition(self) -> bool: _, self._first_sample_time = self.inlet.pull_sample() return True - @property - def first_sample_time(self) -> float: - """Timestamp returned by the first sample. If the data is being - recorded this value reflects the timestamp of the first recorded sample""" - if self.recorder: - return self.recorder.first_sample_time - return self._first_sample_time - def stop_acquisition(self) -> None: """Disconnect from the data source.""" log.info(f"Stopping Acquisition from {self.device_spec.name} ...") @@ -126,12 +139,34 @@ def __exit__(self, _exc_type, _exc_value, _traceback): """Context manager exit method to clean up resources.""" self.stop_acquisition() + def _data_stats(self, data: List[Record]) -> Dict[str, float]: + """Summarize a list of records for logging and inspection.""" + if data: + diffs = pd.DataFrame(data)['timestamp'].diff() + data_start = data[0].timestamp + data_end = data[-1].timestamp + precision = 3 + return { + 'count': len(data), + 'seconds': round(data_end - data_start, precision), + 'from': round(data_start, precision), + 'to': round(data_end, precision), + 'expected_diff': round(1 / self.device_spec.sample_rate, + precision), + 'mean_diff': round(diffs.mean(), precision), + 'max_diff': round(diffs.max(), precision) + } + return {} + def get_data(self, start: Optional[float] = None, end: Optional[float] = None, limit: Optional[int] = None) -> List[Record]: """Get data in time range. + Only data in the current buffer is available to query; + requests for data outside of this will fail. + Parameters ---------- start : starting timestamp (acquisition clock). @@ -142,38 +177,31 @@ def get_data(self, ------- List of Records """ - log.info(f"Getting data from: {start} to: {end} limit: {limit}") + log.info(f"Requesting data from: {start} to: {end} limit: {limit}") - # Only data in the current buffer is available to query; - # requests for data outside of this will fail. Buffer size is - # set using the max_buffer_len parameter. data = self.get_latest_data() - if not data: log.info('No records available') return [] - log.info((f'{len(data)} records available ' - f'(From: {data[0].timestamp} To: {data[-1].timestamp})')) - start = start or data[0].timestamp - end = end or data[-1].timestamp - limit = limit or -1 - assert start >= data[0].timestamp, ( - f'Start time of {start} is out of range: ' - f'({data[0].timestamp} to {data[-1].timestamp}).') + data_start = data[0].timestamp + data_end = data[-1].timestamp + log.info(f'Available data: {self._data_stats(data)}') + + if start is None: + start = data_start + if end is None: + end = data_end + + assert start >= data_start, 'Start time out of range' + assert end <= data_end, 'End time out of range' data_slice = [ record for record in data if start <= record.timestamp <= end ][0:limit] - log.info(f'{len(data_slice)} records returned') - return data_slice + log.info(f"Filtered records: {self._data_stats(data_slice)}") - @property - def max_samples(self) -> int: - """Maximum number of samples available at any given time.""" - if self.device_spec.sample_rate == IRREGULAR_RATE: - return int(self.max_buffer_len) - return int(self.max_buffer_len * self.device_spec.sample_rate) + return data_slice def get_latest_data(self) -> List[Record]: """Add all available samples in the inlet to the buffer. @@ -182,15 +210,28 @@ def get_latest_data(self) -> List[Record]: max_buffer_len and the amount of data available in the inlet.""" if not self.buffer: return [] - samples, timestamps = self.inlet.pull_chunk( - max_samples=self.max_samples) - for i, sample in enumerate(samples): - self.buffer.append( - Record(data=sample, timestamp=timestamps[i], rownum=None)) + count = self._pull_chunk() + # Pull all the data from LSL and append it to the local buffer. + while count == self.max_samples: + count = self._pull_chunk() return self.buffer.get() + def _pull_chunk(self) -> int: + """Pull a chunk of samples from LSL and record in the buffer. + Returns the count of samples pulled. + """ + log.info(f"Pulling from LSL (max_samples: {self.max_samples})") + # A timeout of 0.0 gets currently available samples without blocking. + samples, timestamps = self.inlet.pull_chunk( + timeout=0.0, max_samples=self.max_samples) + count = len(samples) + log.info(f"\tReceived {count} samples") + for sample, stamp in zip(samples, timestamps): + self.buffer.append(Record(sample, stamp)) + return count + def convert_time(self, experiment_clock: Clock, timestamp: float) -> float: """ Convert a timestamp from the experiment clock to the acquisition clock. diff --git a/bcipy/acquisition/record.py b/bcipy/acquisition/record.py index 8eea72e34..5563ad92a 100644 --- a/bcipy/acquisition/record.py +++ b/bcipy/acquisition/record.py @@ -1,8 +1,12 @@ # -*- coding: utf-8 -*- """Defines the Record namedtuple""" -from collections import namedtuple +from typing import Any, List, NamedTuple -Record = namedtuple('Record', ['data', 'timestamp', 'rownum']) -Record.__doc__ = """Domain object used for storing data and timestamp -information, where data is a single reading from a device and is a list -of channel information (float).""" + +class Record(NamedTuple): + """Domain object used for storing data and timestamp + information, where data is a single reading from a device and is a list + of channel information (float).""" + data: List[Any] + timestamp: float + rownum: int = None diff --git a/requirements.txt b/requirements.txt index 128be55b8..809272152 100644 --- a/requirements.txt +++ b/requirements.txt @@ -14,7 +14,7 @@ scipy==1.10.1 scikit-learn==1.2.2 seaborn==0.9.0 matplotlib==3.7.2 -pylsl==1.16 +pylsl==1.16.2 pandas==1.5.3 psutil==5.7.2 Pillow==9.4.0 From be6b2925f38106227a9747ca54732b85a775ace7 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Dec 2023 13:30:46 -0800 Subject: [PATCH 191/330] Fixes an issue with logging samples that was caused by the provided type being a DataFrame rather than a List[Series] --- bcipy/simulator/helpers/log_utils.py | 11 ++++------- bcipy/simulator/helpers/sampler.py | 5 +++-- 2 files changed, 7 insertions(+), 9 deletions(-) diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 8e91d5110..19cf8c2bc 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -9,10 +9,7 @@ def format_alp_likelihoods(likelihoods, alp): return formatted -def format_sample_rows(sample_rows: List[pd.Series]): - formatted_rows = [] - for row in sample_rows: - new_row = row.drop(columns=['eeg'], axis=1, inplace=False) - formatted_rows.append(new_row.to_string(index=False, header=True)) - - return ", ".join(formatted_rows) +def format_sample_rows(sample_rows: List[pd.Series]) -> str: + """Returns a tabular representation of the sample rows.""" + return pd.DataFrame(sample_rows).drop(columns=['eeg']).to_string( + index=False, header=True) diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 3111d2370..44fe029c3 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -53,11 +53,12 @@ def sample(self, state: SimState) -> np.ndarray: if not len(filtered_data): raise TaskConfigurationException(message="No eeg sample found with provided data and query") - row = filtered_data.sample(1) + row = filtered_data.sample(1).iloc[0] sample_rows.append(row) log.debug(f"EEG Samples: \n {format_sample_rows(sample_rows)}") - eeg_responses = [r['eeg'].to_numpy()[0] for r in sample_rows] + + eeg_responses = [r['eeg'] for r in sample_rows] sample = self.model_input_reshaper(eeg_responses) return sample From f7033bbd32e84400762ca6710efbd80cd823457a Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Dec 2023 14:56:30 -0800 Subject: [PATCH 192/330] cleanup from PR suggestions --- bcipy/acquisition/protocols/lsl/lsl_client.py | 4 ++-- bcipy/acquisition/record.py | 4 ++-- bcipy/helpers/acquisition.py | 4 +++- 3 files changed, 7 insertions(+), 5 deletions(-) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index 3e21a73ea..f82d545b9 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -222,12 +222,12 @@ def _pull_chunk(self) -> int: """Pull a chunk of samples from LSL and record in the buffer. Returns the count of samples pulled. """ - log.info(f"Pulling from LSL (max_samples: {self.max_samples})") + log.debug(f"Pulling from LSL (max_samples: {self.max_samples})") # A timeout of 0.0 gets currently available samples without blocking. samples, timestamps = self.inlet.pull_chunk( timeout=0.0, max_samples=self.max_samples) count = len(samples) - log.info(f"\tReceived {count} samples") + log.debug(f"\tReceived {count} samples") for sample, stamp in zip(samples, timestamps): self.buffer.append(Record(sample, stamp)) return count diff --git a/bcipy/acquisition/record.py b/bcipy/acquisition/record.py index 5563ad92a..8d93a5a9c 100644 --- a/bcipy/acquisition/record.py +++ b/bcipy/acquisition/record.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- """Defines the Record namedtuple""" -from typing import Any, List, NamedTuple +from typing import Any, List, NamedTuple, Optional class Record(NamedTuple): @@ -9,4 +9,4 @@ class Record(NamedTuple): of channel information (float).""" data: List[Any] timestamp: float - rownum: int = None + rownum: Optional[int] = None diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index 6da6911f2..c129470d3 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -165,7 +165,9 @@ def init_lsl_client(parameters: dict, """Initialize a client that acquires data from LabStreamingLayer.""" data_buffer_seconds = round(max_inquiry_duration(parameters)) - log.info(f"Setting an acquisition buffer of {data_buffer_seconds} seconds") + log.info( + f"Setting an acquisition buffer for {device_spec.name} of {data_buffer_seconds} seconds" + ) return LslAcquisitionClient(max_buffer_len=data_buffer_seconds, device_spec=device_spec, save_directory=save_folder, From b92ad51794c93a09b97c1f52ded78012ca1ca5a6 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 5 Jan 2024 16:16:52 -0800 Subject: [PATCH 193/330] #186164071 ; added active/passive status to devices --- bcipy/acquisition/devices.py | 37 ++++++++++-- bcipy/acquisition/multimodal.py | 9 +++ bcipy/acquisition/protocols/lsl/lsl_client.py | 1 + bcipy/acquisition/tests/test_devices.py | 60 +++++++++++++++---- bcipy/helpers/acquisition.py | 44 ++++++++++---- bcipy/helpers/tests/test_acquisition.py | 16 +++-- bcipy/parameters/devices.json | 15 +++-- bcipy/signal/model/offline_analysis.py | 32 +++++----- bcipy/task/paradigm/rsvp/copy_phrase.py | 2 +- .../tests/paradigm/rsvp/test_copy_phrase.py | 1 + 10 files changed, 164 insertions(+), 53 deletions(-) diff --git a/bcipy/acquisition/devices.py b/bcipy/acquisition/devices.py index 12a2c1f56..4eb194df9 100644 --- a/bcipy/acquisition/devices.py +++ b/bcipy/acquisition/devices.py @@ -2,8 +2,9 @@ devices.""" import json import logging +from enum import Enum, auto from pathlib import Path -from typing import Optional, Dict, List, NamedTuple, Union +from typing import Dict, List, NamedTuple, Optional, Union from bcipy.config import DEFAULT_ENCODING, DEVICE_SPEC_PATH @@ -50,6 +51,22 @@ def channel_spec(channel: Union[str, dict, ChannelSpec]) -> ChannelSpec: raise Exception("Unexpected channel type") +class DeviceStatus(Enum): + """Represents the recording status of a device during acquisition.""" + ACTIVE = auto() + PASSIVE = auto() + + def __str__(self) -> str: + """String representation""" + return self.name.lower() + + @classmethod + def from_str(cls, name: str) -> 'DeviceStatus': + """Returns the DeviceStatus associated with the given string + representation.""" + return cls[name.upper()] + + class DeviceSpec: """Specification for a hardware device used in data acquisition. @@ -67,6 +84,7 @@ class DeviceSpec: data_type - data format of a channel; all channels must have the same type; see https://labstreaminglayer.readthedocs.io/projects/liblsl/ref/enums.html excluded_from_analysis - list of channels (label) to exclude from analysis. + status - recording status """ def __init__(self, @@ -76,7 +94,8 @@ def __init__(self, content_type: str = DEFAULT_DEVICE_TYPE, description: Optional[str] = None, excluded_from_analysis: Optional[List[str]] = None, - data_type='float32'): + data_type: str = 'float32', + status: DeviceStatus = DeviceStatus.ACTIVE): assert sample_rate >= 0, "Sample rate can't be negative." assert data_type in SUPPORTED_DATA_TYPES @@ -89,6 +108,7 @@ def __init__(self, self.data_type = data_type self.excluded_from_analysis = excluded_from_analysis or [] self._validate_excluded_channels() + self.status = status @property def channel_count(self) -> int: @@ -117,6 +137,12 @@ def analysis_channels(self) -> List[str]: filter(lambda channel: channel not in self.excluded_from_analysis, self.channels)) + @property + def is_active(self) -> bool: + """Returns a boolean indicating if the device is currently active + (recording status set to DeviceStatus.ACTIVE).""" + return self.status == DeviceStatus.ACTIVE + def to_dict(self) -> dict: """Converts the DeviceSpec to a dict.""" return { @@ -125,7 +151,8 @@ def to_dict(self) -> dict: 'channels': [ch._asdict() for ch in self.channel_specs], 'sample_rate': self.sample_rate, 'description': self.description, - 'excluded_from_analysis': self.excluded_from_analysis + 'excluded_from_analysis': self.excluded_from_analysis, + 'status': str(self.status) } def __str__(self): @@ -153,13 +180,15 @@ def _validate_excluded_channels(self): def make_device_spec(config: dict) -> DeviceSpec: """Constructs a DeviceSpec from a dict. Throws a KeyError if any fields are missing.""" + default_status = str(DeviceStatus.ACTIVE) return DeviceSpec(name=config['name'], content_type=config['content_type'], channels=config['channels'], sample_rate=config['sample_rate'], description=config['description'], excluded_from_analysis=config.get( - 'excluded_from_analysis', [])) + 'excluded_from_analysis', []), + status=DeviceStatus.from_str(config.get('status', default_status))) def load(config_path: Path = Path(DEFAULT_CONFIG), replace: bool = False) -> Dict[str, DeviceSpec]: diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 43b3ca560..8249f0885 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -84,6 +84,15 @@ def device_content_types(self) -> List[ContentType]: """ return list(self._clients.keys()) + @property + def active_device_content_types(self) -> List[ContentType]: + """Returns a list of ContentTypes provided by the active configured + devices.""" + return [ + content_type for content_type, spec in self._clients.items() + if spec.is_active + ] + @property def default_client(self) -> Optional[LslAcquisitionClient]: """Returns the default client.""" diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index f82d545b9..c78f64b90 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -127,6 +127,7 @@ def stop_acquisition(self) -> None: log.info("Closing LSL connection") self.inlet.close_stream() self.inlet = None + log.info("Inlet closed") self.buffer = None diff --git a/bcipy/acquisition/tests/test_devices.py b/bcipy/acquisition/tests/test_devices.py index 31c0a766c..aedaea775 100644 --- a/bcipy/acquisition/tests/test_devices.py +++ b/bcipy/acquisition/tests/test_devices.py @@ -6,7 +6,6 @@ from pathlib import Path from bcipy.acquisition import devices - from bcipy.config import DEFAULT_ENCODING @@ -21,8 +20,8 @@ def test_default_supported_devices(self): """List of supported devices should include generic values for backwards compatibility.""" supported = devices.preconfigured_devices() - self.assertTrue(len(supported.keys()) > 0) - self.assertTrue('DSI-24' in supported.keys()) + self.assertTrue(len(supported) > 0) + self.assertTrue('DSI-24' in supported) dsi = supported['DSI-24'] self.assertEqual('EEG', dsi.content_type) @@ -49,13 +48,15 @@ def test_load_from_config(self): devices.load(config_path, replace=True) supported = devices.preconfigured_devices() - self.assertEqual(1, len(supported.keys())) - self.assertTrue('DSI-VR300' in supported.keys()) + self.assertEqual(1, len(supported)) + self.assertTrue('DSI-VR300' in supported) spec = supported['DSI-VR300'] self.assertEqual('EEG', spec.content_type) self.assertEqual(300.0, spec.sample_rate) self.assertEqual(channels, spec.channels) + self.assertEqual(devices.DeviceStatus.ACTIVE, spec.status) + self.assertTrue(spec.is_active) self.assertEqual(spec, devices.preconfigured_device('DSI-VR300')) shutil.rmtree(temp_dir) @@ -89,14 +90,14 @@ def test_load_channel_specs_from_config(self): with open(config_path, 'w', encoding=DEFAULT_ENCODING) as config_file: json.dump(my_devices, config_file) - prior_device_count = len(devices.preconfigured_devices().keys()) + prior_device_count = len(devices.preconfigured_devices()) devices.load(config_path) supported = devices.preconfigured_devices() spec = supported["Custom-Device"] self.assertEqual(spec.channels, ['Fz', 'Pz', 'F7']) self.assertEqual(spec.channel_names, ['ch1', 'ch2', 'ch3']) - self.assertEqual(len(supported.keys()), prior_device_count + 1) + self.assertEqual(len(supported), prior_device_count + 1) shutil.rmtree(temp_dir) def test_load_missing_config(self): @@ -120,16 +121,16 @@ def test_device_registration(self): sample_rate=300.0, description="Custom built device") supported = devices.preconfigured_devices() - device_count = len(supported.keys()) + device_count = len(supported) self.assertTrue(device_count > 0) - self.assertTrue('my-device' not in supported.keys()) + self.assertTrue('my-device' not in supported) spec = devices.make_device_spec(data) devices.register(spec) supported = devices.preconfigured_devices() - self.assertEqual(device_count + 1, len(supported.keys())) - self.assertTrue('my-device' in supported.keys()) + self.assertEqual(device_count + 1, len(supported)) + self.assertTrue('my-device' in supported) def test_search_by_name(self): """Should be able to find a supported device by name.""" @@ -143,6 +144,7 @@ def test_device_spec_defaults(self): sample_rate=256.0) self.assertEqual(3, spec.channel_count) self.assertEqual('EEG', spec.content_type) + self.assertEqual(devices.DeviceStatus.ACTIVE, spec.status) def test_device_spec_analysis_channels(self): """DeviceSpec should have a list of channels used for analysis.""" @@ -228,12 +230,46 @@ def test_device_spec_to_dict(self): spec = devices.DeviceSpec(name=device_name, channels=channels, sample_rate=sample_rate, - content_type=content_type) + content_type=content_type, + status=devices.DeviceStatus.PASSIVE) spec_dict = spec.to_dict() self.assertEqual(device_name, spec_dict['name']) self.assertEqual(content_type, spec_dict['content_type']) self.assertEqual(expected_channel_output, spec_dict['channels']) self.assertEqual(sample_rate, spec_dict['sample_rate']) + self.assertEqual('passive', spec_dict['status']) + + def test_load_status(self): + """Should be able to load a list of supported devices from a + configuration file.""" + + # create a config file in a temp location. + temp_dir = tempfile.mkdtemp() + my_devices = [ + dict(name="MyDevice", + content_type="EEG", + description="My Device", + channels=["a", "b", "c"], + sample_rate=100.0, + status=str(devices.DeviceStatus.PASSIVE)) + ] + config_path = Path(temp_dir, 'my_devices.json') + with open(config_path, 'w', encoding=DEFAULT_ENCODING) as config_file: + json.dump(my_devices, config_file) + + devices.load(config_path, replace=True) + supported = devices.preconfigured_devices() + self.assertEqual(devices.DeviceStatus.PASSIVE, supported['MyDevice'].status) + shutil.rmtree(temp_dir) + + def test_device_status(self): + """Test DeviceStatus enum""" + self.assertEqual('active', str(devices.DeviceStatus.ACTIVE)) + self.assertEqual(devices.DeviceStatus.ACTIVE, + devices.DeviceStatus.from_str('active')) + self.assertEqual( + devices.DeviceStatus.PASSIVE, + devices.DeviceStatus.from_str(str(devices.DeviceStatus.PASSIVE))) if __name__ == '__main__': diff --git a/bcipy/helpers/acquisition.py b/bcipy/helpers/acquisition.py index c129470d3..0a92c9b7a 100644 --- a/bcipy/helpers/acquisition.py +++ b/bcipy/helpers/acquisition.py @@ -2,15 +2,15 @@ import logging import subprocess import time -from typing import Dict, List, Optional, Tuple +from typing import Dict, List, NamedTuple, Optional, Tuple import numpy as np from bcipy.acquisition import (ClientManager, LslAcquisitionClient, LslDataServer, await_start, discover_device_spec) -from bcipy.acquisition.devices import (DeviceSpec, preconfigured_device, - with_content_type) +from bcipy.acquisition.devices import (DeviceSpec, DeviceStatus, + preconfigured_device, with_content_type) from bcipy.config import BCIPY_ROOT from bcipy.config import DEFAULT_DEVICE_SPEC_FILENAME as spec_name from bcipy.config import RAW_DATA_FILENAME @@ -52,7 +52,7 @@ def init_eeg_acquisition( manager = ClientManager() for stream_type in stream_types(parameters['acq_mode']): - content_type, device_name = parse_stream_type(stream_type) + content_type, device_name, status = parse_stream_type(stream_type) if server: server_device_spec = server_spec(content_type, device_name) @@ -64,6 +64,8 @@ def init_eeg_acquisition( await_start(dataserver) device_spec = init_device(content_type, device_name) + if status: + device_spec.status = status raw_data_name = raw_data_filename(device_spec) client = init_lsl_client(parameters, device_spec, save_folder, @@ -138,24 +140,44 @@ def server_spec(content_type: str, return devices[0] +class StreamType(NamedTuple): + """Specifies a stream.""" + content_type: str + device_name: Optional[str] = None + status: Optional[DeviceStatus] = None + + def parse_stream_type(stream_type: str, - delimiter: str = "/") -> Tuple[str, Optional[str]]: - """Parses the stream type into a tuple of (content_type, device_name). + name_delim: str = "/", + status_delim: str = ":") -> StreamType: + """Parses the stream type into a tuple of (content_type, device_name, status). Parameters ---------- stream_type - LSL content type (EEG, Gaze, etc). If you know the name of the preconfigured device it can be added 'EEG/DSI-24' - + name_delim - optionally used after the content_type (and status) + for specifying the device name. + status_delim - optionally used after the content_type to specify the + status for the device ('active' or 'passive') >>> parse_stream_type('EEG/DSI-24') ('EEG', 'DSI-24') >>> parse_stream_type('Gaze') ('Gaze', None) + >>> parse_stream_type('Gaze:passive') + ('Gaze', None, DeviceStatus.PASSIVE) """ - if delimiter in stream_type: - content_type, device_name = stream_type.split(delimiter)[0:2] - return (content_type, device_name) - return (stream_type, None) + device_name = None + status = None + + if name_delim in stream_type: + content_type, device_name = stream_type.split(name_delim)[0:2] + else: + content_type = stream_type + if status_delim in content_type: + content_type, status_str = content_type.split(status_delim)[0:2] + status = DeviceStatus.from_str(status_str) + return StreamType(content_type, device_name, status) def init_lsl_client(parameters: dict, diff --git a/bcipy/helpers/tests/test_acquisition.py b/bcipy/helpers/tests/test_acquisition.py index 3ec07e6ed..22a725c9b 100644 --- a/bcipy/helpers/tests/test_acquisition.py +++ b/bcipy/helpers/tests/test_acquisition.py @@ -4,7 +4,7 @@ from pathlib import Path from unittest.mock import Mock, patch -from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.devices import DeviceSpec, DeviceStatus from bcipy.config import DEFAULT_PARAMETERS_PATH from bcipy.helpers.acquisition import (RAW_DATA_FILENAME, init_device, init_eeg_acquisition, @@ -39,7 +39,7 @@ def test_init_acquisition(self): """Test init_eeg_acquisition with LSL client.""" params = self.parameters - params['acq_mode'] = 'EEG/DSI-24' + params['acq_mode'] = 'EEG:passive/DSI-24' client, servers = init_eeg_acquisition(params, self.save, server=True) @@ -50,6 +50,7 @@ def test_init_acquisition(self): self.assertEqual(1, len(servers)) self.assertEqual(client.device_spec.name, 'DSI-24') + self.assertFalse(client.device_spec.is_active) self.assertTrue(Path(self.save, 'devices.json').is_file()) @@ -145,9 +146,14 @@ def test_init_device_with_named_device(self, preconfigured_device_mock, self.assertEqual(device_spec, device_mock) def test_parse_stream_type(self): - """Test function to split the stream type into content_type, name""" - self.assertEqual(('EEG', 'DSI-24'), parse_stream_type('EEG/DSI-24')) - self.assertEqual(('Gaze', None), parse_stream_type('Gaze')) + """Test function to split the stream type into content_type, name, + and status""" + self.assertEqual(('EEG', 'DSI-24', None), parse_stream_type('EEG/DSI-24')) + self.assertEqual(('Gaze', None, None), parse_stream_type('Gaze')) + self.assertEqual(('Gaze', None, DeviceStatus.PASSIVE), + parse_stream_type('Gaze:passive')) + self.assertEqual(('EEG', 'DSI-24', DeviceStatus.ACTIVE), + parse_stream_type('EEG:active/DSI-24')) @patch('bcipy.helpers.acquisition.preconfigured_device') def test_server_spec_with_named_device(self, preconfigured_device_mock): diff --git a/bcipy/parameters/devices.json b/bcipy/parameters/devices.json index 01e4724b8..c9254b966 100644 --- a/bcipy/parameters/devices.json +++ b/bcipy/parameters/devices.json @@ -40,7 +40,8 @@ "P3", "P4", "F3", "F4", "C3", "C4" - ] + ], + "status": "active" }, { "name": "DSI-VR300", @@ -57,7 +58,8 @@ ], "sample_rate": 300, "description": "Wearable Sensing DSI-VR300", - "excluded_from_analysis": ["TRG", "F7"] + "excluded_from_analysis": ["TRG", "F7"], + "status": "active" }, { "name": "DSI-Flex", @@ -74,7 +76,8 @@ ], "sample_rate": 300.0, "description": "Wearable Sensing DSI-Flex", - "excluded_from_analysis": ["TRG"] + "excluded_from_analysis": ["TRG"], + "status": "active" }, { "name": "g.USBamp-1", @@ -98,7 +101,8 @@ { "name": "Ch16", "label": "Ch16", "units": "microvolts", "type": "EEG" } ], "sample_rate": 256, - "description": "GTec g.USBamp" + "description": "GTec g.USBamp", + "status": "active" }, { "name": "Tobii Nano", @@ -115,6 +119,7 @@ ], "sample_rate": 60.0, "description": "Tobii Nano. For use with the Tobii Pro SDK.", - "excluded_from_analysis": ["device_ts", "system_ts", "left_pupil", "right_pupil"] + "excluded_from_analysis": ["device_ts", "system_ts", "left_pupil", "right_pupil"], + "status": "active" } ] \ No newline at end of file diff --git a/bcipy/signal/model/offline_analysis.py b/bcipy/signal/model/offline_analysis.py index b5ed089b5..9144dc7c0 100644 --- a/bcipy/signal/model/offline_analysis.py +++ b/bcipy/signal/model/offline_analysis.py @@ -1,9 +1,9 @@ # mypy: disable-error-code="attr-defined" # needed for the ERPTransformParams +import json import logging from pathlib import Path from typing import Tuple -import json import numpy as np from matplotlib.figure import Figure @@ -11,10 +11,9 @@ from sklearn.model_selection import train_test_split import bcipy.acquisition.devices as devices -from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, BCIPY_ROOT, - DEFAULT_PARAMETERS_PATH, STATIC_AUDIO_PATH, - TRIGGER_FILENAME, - MATRIX_IMAGE_FILENAME) +from bcipy.config import (BCIPY_ROOT, DEFAULT_DEVICE_SPEC_FILENAME, + DEFAULT_PARAMETERS_PATH, MATRIX_IMAGE_FILENAME, + STATIC_AUDIO_PATH, TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels, raw_data_filename from bcipy.helpers.load import (load_experimental_data, load_json_parameters, load_raw_data) @@ -24,14 +23,15 @@ from bcipy.helpers.symbols import alphabet from bcipy.helpers.system_utils import report_execution_time from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.helpers.visualization import (visualize_erp, visualize_gaze, +from bcipy.helpers.visualization import (visualize_centralized_data, + visualize_erp, visualize_gaze, + visualize_gaze_accuracies, visualize_gaze_inquiries, - visualize_centralized_data, - visualize_results_all_symbols, - visualize_gaze_accuracies) + visualize_results_all_symbols) from bcipy.preferences import preferences from bcipy.signal.model.base_model import SignalModel, SignalModelMetadata -from bcipy.signal.model.gaussian_mixture import GazeModelIndividual, GazeModelCombined +from bcipy.signal.model.gaussian_mixture import (GazeModelCombined, + GazeModelIndividual) from bcipy.signal.model.pca_rda_kde import PcaRdaKdeModel from bcipy.signal.process import (ERPTransformParams, extract_eye_info, filter_inquiries, get_default_transform) @@ -473,6 +473,7 @@ def offline_analysis( pickle dumps the model into a .pkl folder How it Works: + For every active device that was used during calibration, - reads data and information from a .csv calibration file - reads trigger information from a .txt trigger file - filters data @@ -506,11 +507,12 @@ def offline_analysis( devices_by_name = devices.load( Path(data_folder, DEFAULT_DEVICE_SPEC_FILENAME), replace=True) - data_file_paths = [ - path for path in (Path(data_folder, raw_data_filename(device_spec)) - for device_spec in devices_by_name.values()) - if path.exists() - ] + + active_devices = (spec for spec in devices_by_name.values() + if spec.is_active) + active_raw_data_paths = (Path(data_folder, raw_data_filename(device_spec)) + for device_spec in active_devices) + data_file_paths = [path for path in active_raw_data_paths if path.exists()] models = [] figure_handles = [] diff --git a/bcipy/task/paradigm/rsvp/copy_phrase.py b/bcipy/task/paradigm/rsvp/copy_phrase.py index 1cf0712f2..cb3b44810 100644 --- a/bcipy/task/paradigm/rsvp/copy_phrase.py +++ b/bcipy/task/paradigm/rsvp/copy_phrase.py @@ -190,7 +190,7 @@ def init_evidence_evaluators(self, evaluator = init_evidence_evaluator(self.alp, model) content_type = evaluator.consumes evidence_type = evaluator.produces - if content_type in self.daq.device_content_types: + if content_type in self.daq.active_device_content_types: evaluators.append(evaluator) if evidence_type in evidence_types: raise DuplicateModelEvidence( diff --git a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py index 68fb1e794..7c4b97b3b 100644 --- a/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py +++ b/bcipy/task/tests/paradigm/rsvp/test_copy_phrase.py @@ -102,6 +102,7 @@ def setUp(self): 'is_calibrated': True, 'offset': lambda x: 0.0, 'device_content_types': [ContentType.EEG], + 'active_device_content_types': [ContentType.EEG], 'clients_by_type': { ContentType.EEG: self.eeg_client_mock } From 272b0ee2d1b85bee7407b6e3a9b1e5fd45efffb0 Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 5 Jan 2024 16:45:00 -0800 Subject: [PATCH 194/330] Added documentation --- bcipy/acquisition/README.md | 19 +++++++++++++++++++ bcipy/parameters/parameters.json | 5 +++-- 2 files changed, 22 insertions(+), 2 deletions(-) diff --git a/bcipy/acquisition/README.md b/bcipy/acquisition/README.md index 4e8060c9d..6fa441155 100644 --- a/bcipy/acquisition/README.md +++ b/bcipy/acquisition/README.md @@ -17,6 +17,8 @@ Within BciPy users must specify the details of the device they wish to use by pr `DeviceSpec` channel data can be provided as a list of channel names or specified as a list of `ChannelSpec` entries. These will be validated against the metadata from the LSL data stream. If provided, `ChannelSpecs` allow users to customize the channel labels and override the values provided by the LSL metadata. +Devices can also have a status of either 'active' or 'passive'. Active devices are used for training models (after calibration) and for interactive queries during Copy Phrase tasks. Passive devices are used for recording data in the background for possible later analysis. Device status can be set in the `devices.json` file or through the parameters. + ## Client The `lsl_client` module provides the primary interface for interacting with device data and may be used to dynamically query streaming data in real-time. An instance of the `LslClient` class is parameterized with the `DeviceSpec` of interest, as well as the number of seconds of data that should be available for querying. If the `save_directory` and `filename` parameters are provided it also records the data to disk for later offline analysis. If no device is specified the client will attempt to connect to an EEG stream by default. A separate `LslClient` should be constructed for each device of interest. @@ -70,3 +72,20 @@ Generators are Python functions that yield encoded data. They have a parameter f #### Producer A `Producer` is a class internal to a server that manages the generation of data at a specified frequency. It's purpose it to mimic the data rate that would be presented if an actual hardware device was used. + +## Acquisition Parameters + +The primary parameter for configuring the acquisition module for running an experiment is the `acq_mode` parameter. This parameter allows users to specify one or more devices from which to acquire data, as well as the status of each device. In its simplest form the parameter is a string specifying the content type of the LSL data stream of interest (for example. 'EEG'). The first detected device with this content type will be used. Alternatively, users can provide the device name ('EEG/DSI-24'), which specifies that we are interested in a specific device. The module will look for the corresponding data stream, and will use configuration for the device from the `devices.json` file. Finally, users can specify whether the provided device will be recording in active or passive mode ('EEG:passive/DSI-24'). One or more devices can be configured by delimiting the specs with a '+' ('EEG/DSI-24+Eyetracker:passive'). + +### Use Cases + +- I want to Calibrate using EEG and Eyetracker and train models for both. + - set parameter `'acq_mode': 'EEG+Eyetracker'` +- I want to Calibrate using EEG and Eyetracker and train models for EEG only. + - set parameter `'acq_mode': 'EEG+Eyetracker:passive'` +- I want to Calibrate using EEG and Eyetracker and train models for Eyetracker only. + - set parameter `'acq_mode': 'EEG:passive+Eyetracker'` +- I want to do a Copy Phrase task using EEG only. In my calibration directory I have trained models for both EEG and Eyetracker. + - set parameter `'acq_mode': 'EEG'` +- I want to do a Copy Phrase task using EEG only, but I want to record gaze data. In my calibration directory I have trained models for both EEG and Eyetracker. + - set parameter `'acq_mode': 'EEG+Eyetracker:passive'` \ No newline at end of file diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 724b343ac..b17e6f8c5 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -11,12 +11,13 @@ "value": "EEG", "section": "acq_config", "readableName": "Acquisition Mode", - "helpTip": "Specifies the hardware device(s) used for data collection. Default: EEG", + "helpTip": "Specifies the hardware device(s) used for data collection. Default: EEG.", "recommended_values": [ "EEG", "EEG/DSI-24", "Eyetracker", - "EEG+Eyetracker" + "EEG+Eyetracker", + "EEG+Eyetracker:passive" ], "type": "str" }, From 40402857024df6a8c6ca4a912ddc67589ea57d7e Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 7 Jan 2024 22:57:38 +0530 Subject: [PATCH 195/330] sim README.md --- bcipy/simulator/README.md | 26 ++++++++++++++++++++++++ bcipy/simulator/__main__.py | 7 ++++++- bcipy/simulator/helpers/data_engine.py | 6 ++---- bcipy/simulator/helpers/state_manager.py | 12 ++++++----- 4 files changed, 41 insertions(+), 10 deletions(-) create mode 100644 bcipy/simulator/README.md diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md new file mode 100644 index 000000000..3408143bc --- /dev/null +++ b/bcipy/simulator/README.md @@ -0,0 +1,26 @@ +## RSVP Simulator + +### Overview + +This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and running given models in RSVP task loop, thus simulating a +live session. + +### Run steps + +`main.py` is the entry point for program. After following, `BciPy` readme steps for setup, run the module from shell as such: + +``python3 bcipy/simulator -d "pathToDataFolder1" -d "pathToOptionalDataFolder2" -sm "pathToSignalModel.pkl"`` + +Then view generated LOG file for analysis + +#### Program Args + +- `d` : the data folder argument is necessary. This data will be used to construct data pool from which simulator will sample EEG responses. Should contain + _raw_data.csv_, _triggers.txt_, _parameters.json_ +- `sm`: the signal model argument is necessary to generate evidence + +### Architecture + +![simDiagram.png](res/simDiagram.png) + + diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index b93f7b295..34b158717 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -1,7 +1,9 @@ +""" Entry point to run Simulator """ + import argparse from pathlib import Path -from bcipy.simulator.sim_factory import SimulationFactory, SimulationFactoryV2 +from bcipy.simulator.sim_factory import SimulationFactoryV2 from bcipy.simulator.simulator_base import Simulator if __name__ == "__main__": @@ -20,6 +22,9 @@ type=Path, required=True, help="Signal models to be used") + + # TODO parameters file arg + parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) args = vars(parser.parse_args()) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 73661a50a..48273e8d5 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -38,6 +38,7 @@ class RawDataEngine(DataEngine): def __init__(self, source_dirs: List[str]): # TODO read parameters from source dirx # TODO maybe rely upon single source of data, write some scripts that clean data and group them + # TODO use os.walk() and take in single source_dir that has all data folders self.source_dirs: List[str] = source_dirs self.parameter_files: List[Parameters] = [] self.data: Optional[List[ExtractedExperimentData]] = None @@ -112,7 +113,6 @@ def transform(self) -> DataEngine: rows.extend(symbol_rows) self.schema = pd.DataFrame(rows) - # breakpoint() return self @@ -120,6 +120,4 @@ def get_data(self): return self.schema.copy() if self.schema is not None else self.data def get_parameters(self): - return self.parameter_files - -# TODO ReplaySessionDataEngine + return self.parameter_files \ No newline at end of file diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index e7ec80a72..9b7f93b1e 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -1,12 +1,11 @@ import copy import random -from abc import ABC, abstractmethod +from abc import ABC from dataclasses import dataclass -from typing import List, Optional, Dict +from typing import List, Optional import numpy as np -from bcipy.helpers import symbols from bcipy.helpers.exceptions import FieldException from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR @@ -14,8 +13,6 @@ from bcipy.simulator.helpers.evidence_fuser import MultiplyFuser, EvidenceFuser from bcipy.simulator.helpers.rsvp_utils import next_target_letter from bcipy.simulator.helpers.types import InquiryResult -from bcipy.task.control.criteria import DecisionCriteria, MaxIterationsCriteria, ProbThresholdCriteria -from bcipy.task.control.handler import EvidenceFusion @dataclass @@ -74,6 +71,11 @@ def is_done(self) -> bool: return self.state.total_inquiry_count() > self.max_inq_len or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 def update(self, evidence) -> InquiryResult: + """ Updating the current state based on provided evidence + - fuses prior evidence with current evidence and makes potential decision + - stores inquiry, including typing decision or lack of decision + - resets series on decision and updates target letter + """ fuser = self.fuser_class() current_series: List[InquiryResult] = self.state.series_results[self.state.series_n] From dd5932cc1055f97fbd630bc32e5d9b9fca29c709 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Tue, 9 Jan 2024 13:32:08 +0530 Subject: [PATCH 196/330] deleting first sim draft --- bcipy/simulator/sim_copy_phrase.py | 148 ----------------------------- 1 file changed, 148 deletions(-) delete mode 100644 bcipy/simulator/sim_copy_phrase.py diff --git a/bcipy/simulator/sim_copy_phrase.py b/bcipy/simulator/sim_copy_phrase.py deleted file mode 100644 index 525aab094..000000000 --- a/bcipy/simulator/sim_copy_phrase.py +++ /dev/null @@ -1,148 +0,0 @@ -from typing import Optional - -import numpy as np - -from bcipy.config import SESSION_DATA_FILENAME -from bcipy.helpers import load -from bcipy.helpers.list import grouper -from bcipy.helpers.session import evidence_records, read_session -from bcipy.helpers.symbols import alphabet -from bcipy.signal.model import PcaRdaKdeModel -from bcipy.simulator.helpers.signal_helpers import process_raw_data_for_model, ExtractedExperimentData -from bcipy.simulator.helpers.sim_viz import plot_replay_comparison -from bcipy.simulator.simulator_base import Simulator - - -class SimulatorCopyPhraseReplay(Simulator): - """Simulator. - - Base class for BciPy Simulations. - - Requirements: - - run closed loop simulation of {TaskType} with {data} with {simulation_params} - """ - - def __init__(self, parameter_path, save_dir, signal_models: [tuple], language_models, replay_data_path=None, - verbose=False): - super(SimulatorCopyPhraseReplay, self).__init__() - - self.parameters = self.load_parameters(parameter_path) - self.save_dir = save_dir - self.signal_models = signal_models - self.language_models = language_models - self.replay_data_path = replay_data_path - - self.symbol_set = alphabet() - self.write_output = False - self.data_loader = None - - self.signal_models_classes = [PcaRdaKdeModel for m in self.signal_models] # Hardcoded rn - - def run(self): - self.init_data_loader() - - self.logger.info(f"Initialized data loader") - - # TODO need to support multimodal and language models - model_file, model_class = self.signal_models[0], self.signal_models_classes[0] # hardcoded rn - model = model_class(self.parameters.get("k_folds")) - model = model.load(model_file) - - self.logger.info(f"Loaded model from {model_file}, with model_class {model_class}") - - target_eeg_evidences, non_target_eeg_evidences = [], [] - while not self.data_loader.is_end(): - inquiry_trials, this_inquiry_letters, this_inquiry_labels = self.data_loader.next() - target_eeg_evidence, non_target_eeg_evidence = [], [] - response = model.predict(inquiry_trials, this_inquiry_letters, symbol_set=self.symbol_set) - - symbol_letter_idx_map = [self.symbol_set.index(letter) for letter in this_inquiry_letters] - for i, label in enumerate(this_inquiry_labels): - if label: - target_eeg_evidence.append(response[symbol_letter_idx_map[i]]) - else: - non_target_eeg_evidence.append(response[symbol_letter_idx_map[i]]) - - target_eeg_evidences.append(target_eeg_evidence) - non_target_eeg_evidences.append(non_target_eeg_evidence) - - target_eeg_evidences, non_target_eeg_evidences = np.concatenate(target_eeg_evidences), np.concatenate( - non_target_eeg_evidences) - - # Get target and non_target eeg values from actual experiment in session.json for comparison - session_records = evidence_records(read_session(self.replay_data_path / SESSION_DATA_FILENAME)) - session_target_eeg = np.array([record.eeg for record in session_records if record.is_target]) - session_non_target_eeg = np.array([record.eeg for record in session_records if not record.is_target]) - - # note this flattens any grouping of inquiries which might be problem for future visualizations - - # visualizing comparison of results - plot_replay_comparison(target_eeg_evidences, non_target_eeg_evidences, session_target_eeg, - session_non_target_eeg, self.save_dir, self.parameters) - - self.logger.info(f"Plotted comparison charts " - f"\n New: {len(target_eeg_evidences)} target_eeg_evidences | {len(non_target_eeg_evidences)} non_target_eeg_evidences " - f"\n Old: {len(session_target_eeg)} target_eeg_evidences | {len(session_non_target_eeg)} non_target_eeg_evidences ") - - def get_param(self, name): - return self.parameters.get(name, None) - - def init_data_loader(self): - - if self.replay_data_path: - self.data_loader = ReplayDataLoader(self.replay_data_path, self.parameters) - else: - pass # TODO sampling data logic - pass - - def load_parameters(self, path): - # TODO validate parameters - parameters = load.load_json_parameters(path, value_cast=True) - sim_parameters = load.load_json_parameters( - "bcipy/simulator/sim_parameters.json", value_cast=True) - - parameters.add_missing_items(sim_parameters) - return parameters - - -class ReplayDataLoader: - - def __init__(self, source_path, parameters): - self.source_path = source_path - self.parameters = parameters - self.verbose = False - - self.inquiry_worth_of_letters = None - self.inquiry_worth_of_trials = None - self.data: Optional[ExtractedExperimentData] = None - - self.load() - - self.i = 0 - - def load(self): - experiment_data = process_raw_data_for_model(self.source_path, self.parameters) - - # formatting data into inquiries - trigger_targetness, trigger_timing, trigger_symbols = experiment_data.decoded_triggers - self.inquiry_worth_of_trials = np.split(experiment_data.trials, experiment_data.inquiries.shape[1], 1) - self.inquiry_worth_of_letters = [list(group) for group in - grouper(trigger_symbols, self.parameters.get('stim_length'), - incomplete="ignore")] - - self.data = experiment_data - - def next(self): - if self.i < len(self.inquiry_worth_of_letters): - cur_trials = self.inquiry_worth_of_trials[self.i] - cur_letters = self.inquiry_worth_of_letters[self.i] - cur_labels = self.data.labels[self.i] - - self.i += 1 - - return cur_trials, cur_letters, cur_labels # TODO turn into dataclass - - return None, None, None - - def is_end(self): - return self.i >= len(self.inquiry_worth_of_letters) From 810b6c9f9ec0806df835a9776bf4d40a157bc74e Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Tue, 9 Jan 2024 13:41:21 +0530 Subject: [PATCH 197/330] linting --- bcipy/simulator/README.md | 9 ++++-- bcipy/simulator/__init__.py | 1 - bcipy/simulator/helpers/data_engine.py | 11 ++++--- bcipy/simulator/helpers/decision.py | 9 +++--- bcipy/simulator/helpers/evidence_fuser.py | 1 - bcipy/simulator/helpers/log_utils.py | 2 +- bcipy/simulator/helpers/rsvp_utils.py | 3 +- bcipy/simulator/helpers/signal_helpers.py | 8 +++-- bcipy/simulator/helpers/state_manager.py | 37 +++++++++++++++-------- bcipy/simulator/helpers/types.py | 6 ++-- bcipy/simulator/sim.py | 26 ++++++++++------ bcipy/simulator/sim_factory.py | 30 ++---------------- bcipy/simulator/sim_parameters.json | 2 +- bcipy/simulator/simulator_base.py | 3 +- bcipy/simulator/tests/sampler_test.py | 9 +++--- 15 files changed, 79 insertions(+), 78 deletions(-) diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index 3408143bc..34d901dfe 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -2,12 +2,14 @@ ### Overview -This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and running given models in RSVP task loop, thus simulating a +This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and running given models +in RSVP task loop, thus simulating a live session. ### Run steps -`main.py` is the entry point for program. After following, `BciPy` readme steps for setup, run the module from shell as such: +`main.py` is the entry point for program. After following, `BciPy` readme steps for setup, run the module from shell as +such: ``python3 bcipy/simulator -d "pathToDataFolder1" -d "pathToOptionalDataFolder2" -sm "pathToSignalModel.pkl"`` @@ -15,7 +17,8 @@ Then view generated LOG file for analysis #### Program Args -- `d` : the data folder argument is necessary. This data will be used to construct data pool from which simulator will sample EEG responses. Should contain +- `d` : the data folder argument is necessary. This data will be used to construct data pool from which simulator will + sample EEG responses. Should contain _raw_data.csv_, _triggers.txt_, _parameters.json_ - `sm`: the signal model argument is necessary to generate evidence diff --git a/bcipy/simulator/__init__.py b/bcipy/simulator/__init__.py index 181cfd2de..c107589b3 100644 --- a/bcipy/simulator/__init__.py +++ b/bcipy/simulator/__init__.py @@ -21,7 +21,6 @@ "%(levelname)s >> %(message)s" ) - # Set the log format on each handler stdoutHandler.setFormatter(fmt) fileHandler.setFormatter(fmt_file) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 48273e8d5..b01f95423 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -59,8 +59,10 @@ def load(self) -> DataEngine: """ log.debug(f"Loading data from {len(self.source_dirs)} source directories") - self.parameter_files = [load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for data_folder in - self.source_dirs] + self.parameter_files = [ + load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for + data_folder in + self.source_dirs] assert len(self.source_dirs) == len(self.parameter_files) # TODO more general parameter validation function @@ -92,7 +94,8 @@ def transform(self) -> DataEngine: self for chaining """ - cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] # TODO store how good evidence was in session | store data source as well + # TODO store how good evidence was in session | store data source as well + cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] types = [int, int, int, str, int, np.ndarray] rows = [] @@ -120,4 +123,4 @@ def get_data(self): return self.schema.copy() if self.schema is not None else self.data def get_parameters(self): - return self.parameter_files \ No newline at end of file + return self.parameter_files diff --git a/bcipy/simulator/helpers/decision.py b/bcipy/simulator/helpers/decision.py index 72a0544c0..796c10861 100644 --- a/bcipy/simulator/helpers/decision.py +++ b/bcipy/simulator/helpers/decision.py @@ -2,15 +2,16 @@ import numpy as np import logging -from typing import Dict, List -from copy import copy +from typing import List from bcipy.simulator.helpers.types import InquiryResult log = logging.getLogger(__name__) -# TODO copied over criteria.py. Still debating whether to tie our simulator to that class or not. For now, just hotfixing logic to fit with my implementation +# TODO copied over criteria.py. Still debating whether to tie our +# simulator to that class or not. For now, just hotfixing logic to fit +# with my implementation class SimDecisionCriteria(ABC): """Abstract class for Criteria which can be applied to evaluate a inquiry @@ -110,4 +111,4 @@ def decide(self, series: List[InquiryResult]): if np.max(current_distribution) > self.tau: log.debug("Committing to decision: posterior exceeded threshold.") return True - return False \ No newline at end of file + return False diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py index 6f04b6c34..9269925cd 100644 --- a/bcipy/simulator/helpers/evidence_fuser.py +++ b/bcipy/simulator/helpers/evidence_fuser.py @@ -32,7 +32,6 @@ def fuse(self, prior_likelihood, evidence) -> np.ndarray: return ret_likelihood - def __normalize_likelihood(self, likelihood): cleaned_likelihood = likelihood.copy() diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 8e91d5110..2e74dee1e 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -3,7 +3,7 @@ import pandas as pd -def format_alp_likelihoods(likelihoods, alp): +def fmt_stim_likelihoods(likelihoods, alp): rounded = [round(lik, 3) for lik in likelihoods] formatted = [f"{a} : {l}" for a, l in zip(alp, rounded)] return formatted diff --git a/bcipy/simulator/helpers/rsvp_utils.py b/bcipy/simulator/helpers/rsvp_utils.py index 69deca824..fad352b72 100644 --- a/bcipy/simulator/helpers/rsvp_utils.py +++ b/bcipy/simulator/helpers/rsvp_utils.py @@ -6,5 +6,6 @@ def next_target_letter(current_sentence, target_sentence): """ if target_sentence[0:len(current_sentence)] == current_sentence: # if correctly spelled so far, get the next letter. - return target_sentence[len(current_sentence)] if len(current_sentence) < len(target_sentence) else target_sentence[-1] + return target_sentence[len(current_sentence)] if len( + current_sentence) < len(target_sentence) else target_sentence[-1] return BACKSPACE_CHAR diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 0fa530683..863bc88a3 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -12,7 +12,7 @@ DEFAULT_DEVICE_SPEC_FILENAME, ) from bcipy.helpers.acquisition import analysis_channels -from bcipy.helpers.load import load_raw_data, load_experimental_data +from bcipy.helpers.load import load_raw_data from bcipy.helpers.stimuli import update_inquiry_timing, InquiryReshaper from bcipy.helpers.triggers import TriggerType, trigger_decoder from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams @@ -30,7 +30,8 @@ class ExtractedExperimentData: # TODO clean up design decoded_triggers: tuple -def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshaper = InquiryReshaper()) -> ExtractedExperimentData: +def process_raw_data_for_model(data_folder, parameters, + reshaper: InquiryReshaper = InquiryReshaper()) -> ExtractedExperimentData: assert parameters, "Parameters are required for offline analysis." log.debug(f"Processing raw data for {data_folder}") @@ -118,4 +119,5 @@ def process_raw_data_for_model(data_folder, parameters, reshaper: InquiryReshape # define the training classes using integers, where 0=nontargets/1=targets # labels = inquiry_labels.flatten() - return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, (trigger_targetness, trigger_timing, trigger_symbols)) \ No newline at end of file + return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, + (trigger_targetness, trigger_timing, trigger_symbols)) diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 9b7f93b1e..9a4ab631e 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -67,8 +67,10 @@ def __init__(self, parameters: Parameters, fuser_class=MultiplyFuser): self.max_inq_len = self.parameters.get('max_inq_len', 100) def is_done(self) -> bool: - # TODO add stoppage criterion, Stoppage criterion is seperate from decision. Decision should we go on to next letter or not - return self.state.total_inquiry_count() > self.max_inq_len or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 + # TODO add stoppage criterion, Stoppage criterion is seperate from + # decision. Decision should we go on to next letter or not + return self.state.total_inquiry_count( + ) > self.max_inq_len or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 def update(self, evidence) -> InquiryResult: """ Updating the current state based on provided evidence @@ -79,13 +81,16 @@ def update(self, evidence) -> InquiryResult: fuser = self.fuser_class() current_series: List[InquiryResult] = self.state.series_results[self.state.series_n] - prior_likelihood: Optional[np.ndarray] = current_series.pop().fused_likelihood if current_series else None # most recent likelihood + prior_likelihood: Optional[np.ndarray] = current_series.pop( + ).fused_likelihood if current_series else None # most recent likelihood evidence_dict = {"SM": evidence} # TODO create wrapper object for Evidences fused_likelihood = fuser.fuse(prior_likelihood, evidence_dict) # finding out whether max iterations is hit or prob threshold is hit - temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - evidence_likelihoods=list(evidence), fused_likelihood=fused_likelihood, # TODO change to use evidence_dict + temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, + stimuli=self.state.display_alphabet, + # TODO change to use evidence_dict + evidence_likelihoods=list(evidence), fused_likelihood=fused_likelihood, decision=None) # can we make decision @@ -95,8 +100,10 @@ def update(self, evidence) -> InquiryResult: decision = None new_state = self.get_state().__dict__ - new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - evidence_likelihoods=list(evidence), decision=decision, fused_likelihood=fused_likelihood) + new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, + stimuli=self.state.display_alphabet, + evidence_likelihoods=list(evidence), decision=decision, + fused_likelihood=fused_likelihood) new_state['series_results'][self.state.series_n].append(new_inquiry_result) if is_decidable: @@ -108,14 +115,18 @@ def update(self, evidence) -> InquiryResult: new_state['inquiry_n'] = 0 # updating current sentence and finding next target - new_state['current_sentence'] = new_state['current_sentence'] + decision if decision != BACKSPACE_CHAR else new_state['current_sentence'][:-1] + new_state['current_sentence'] = new_state['current_sentence'] + \ + decision if decision != BACKSPACE_CHAR else new_state['current_sentence'][ + :-1] new_state['target_symbol'] = next_target_letter(new_state['current_sentence'], self.state.target_sentence) else: new_state['inquiry_n'] += 1 - new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - evidence_likelihoods=list(evidence), decision=decision, fused_likelihood=fused_likelihood) + new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, + stimuli=self.state.display_alphabet, + evidence_likelihoods=list(evidence), decision=decision, + fused_likelihood=fused_likelihood) new_state['series_results'][self.state.series_n].append(new_inquiry_result) @@ -142,8 +153,10 @@ def initial_state(parameters: Parameters = None) -> SimState: default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] init_stimuli = random.sample(alphabet(), 10) + # TODO make new parameter and create default series_likelihoods object based off that evidence_types = parameters.get( - 'evidence_types') if parameters else None # TODO make new parameter and create default series_likelihoods object based off that + 'evidence_types') if parameters else None - return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, display_alphabet=init_stimuli, inquiry_n=0, series_n=0, + return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, + display_alphabet=init_stimuli, inquiry_n=0, series_n=0, series_results=[[]], decision_criterion=default_criterion) diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py index 20b71bee3..ff30a3dd4 100644 --- a/bcipy/simulator/helpers/types.py +++ b/bcipy/simulator/helpers/types.py @@ -1,5 +1,5 @@ from dataclasses import dataclass -from typing import Optional, List, Dict +from typing import Optional, List import numpy as np @@ -11,7 +11,9 @@ class InquiryResult: target: Optional[str] time_spent: int stimuli: List - evidence_likelihoods: List # TODO make this into a dictionary to support multimodal. e.g {SignalModel: evidence_list, LanguageModel:evidence_list} + # TODO make this into a dictionary to support multimodal. e.g + # {SignalModel: evidence_list, LanguageModel:evidence_list} + evidence_likelihoods: List fused_likelihood: np.ndarray decision: Optional[str] diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index ac7559005..4c663a932 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -12,7 +12,7 @@ from bcipy.simulator.helpers.sampler import Sampler from bcipy.simulator.helpers.state_manager import StateManager, SimState from bcipy.simulator.helpers.types import InquiryResult -from bcipy.simulator.helpers.log_utils import format_alp_likelihoods +from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods from bcipy.simulator.helpers.model_handler import ModelHandler from bcipy.simulator.simulator_base import Simulator @@ -42,7 +42,8 @@ class SimulatorCopyPhrase(Simulator): """ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, parameter_path: str = None, save_dir: str = None, verbose=False, visualize=False): + state_manager: StateManager, referee: MetricReferee, parameter_path: str = None, save_dir: str = None, + verbose=False, visualize=False): super(SimulatorCopyPhrase, self).__init__() self.save_dir: str = save_dir @@ -66,18 +67,22 @@ def run(self): while not self.state_manager.is_done(): curr_state = self.state_manager.get_state() - log.info(f"Series {curr_state.series_n} | Inquiry {curr_state.inquiry_n} | Target {curr_state.target_symbol}") + log.info( + f"Series {curr_state.series_n} | Inquiry {curr_state.inquiry_n} | Target {curr_state.target_symbol}") self.state_manager.mutate_state('display_alphabet', self.__make_stimuli(curr_state)) sampled_data = self.sampler.sample(curr_state) + # TODO make this evidence be a dict (mapping of evidence type to evidence) evidence = self.model_handler.generate_evidence(curr_state, - sampled_data) # TODO make this evidence be a dict (mapping of evidence type to evidence) + sampled_data) - log.debug(f"Evidence for stimuli {curr_state.display_alphabet} \n {format_alp_likelihoods(evidence, self.symbol_set)}") + log.debug( + f"Evidence for stimuli {curr_state.display_alphabet} " + + f"\n {fmt_stim_likelihoods(evidence, self.symbol_set)}") inq_record: InquiryResult = self.state_manager.update(evidence) updated_state = self.state_manager.get_state() - log.debug(f"Fused Likelihoods {format_alp_likelihoods(inq_record.fused_likelihood, self.symbol_set)}") + log.debug(f"Fused Likelihoods {fmt_stim_likelihoods(inq_record.fused_likelihood, self.symbol_set)}") if inq_record.decision: log.info(f"Decided {inq_record.decision} for target {inq_record.target}") @@ -86,13 +91,12 @@ def run(self): sleep(self.parameters.get("sim_sleep_time", 0.5)) final_state = self.state_manager.get_state() - log.info(f"SIM END") + log.info("SIM END") log.info(f"FINAL TYPED: {final_state.current_sentence}") log.info(self.referee.score(self).__dict__) log.debug(f"Final State: {final_state}") - def __make_stimuli(self, state: SimState): # TODO abstract out subset_length = 10 @@ -100,14 +104,16 @@ def __make_stimuli(self, state: SimState): always_in_stimuli = [symbols.SPACE_CHAR, symbols.BACKSPACE_CHAR] if val_func is not None: - return stimuli.best_selection(self.symbol_set, list(val_func), subset_length, always_included=always_in_stimuli) + return stimuli.best_selection(self.symbol_set, list( + val_func), subset_length, always_included=always_in_stimuli) else: return random.sample(self.symbol_set, subset_length) def load_parameters(self, path): # TODO validate parameters if not path: - parameters = self.data_engine.get_parameters()[0] # TODO fix this parameter logic. for now assuming one parameter file speaks for all + # TODO fix this parameter logic. for now assuming one parameter file speaks for all + parameters = self.data_engine.get_parameters()[0] else: parameters = load.load_json_parameters(path, value_cast=True) diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 9a1fdfc03..8b7b51917 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -1,7 +1,6 @@ from pathlib import Path from typing import List -from bcipy.config import DEFAULT_PARAMETER_FILENAME from bcipy.helpers.load import load_json_parameters from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.metrics import MetricReferee, RefereeImpl, SimMetrics1Handler @@ -9,37 +8,12 @@ from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler from bcipy.simulator.helpers.state_manager import StateManager, StateManagerImpl from bcipy.simulator.sim import SimulatorCopyPhrase -from bcipy.simulator.sim_copy_phrase import SimulatorCopyPhraseReplay -from bcipy.simulator.simulator_base import Simulator - - -class SimulationFactory: - - @staticmethod - def create( - sim_task="", - parameter_path="", - smodel_files=None, - lmodel_files=None, - data_folders=None, - out_dir="", - **kwargs) -> Simulator: - if sim_task == 'RSVP_COPY_PHRASE': - # TODO validate arguments - - if not parameter_path: - data_folder = data_folders[0] - parameter_path = Path(data_folder, DEFAULT_PARAMETER_FILENAME) - - return SimulatorCopyPhraseReplay(parameter_path, out_dir, smodel_files, lmodel_files, data_folders[0], - verbose=kwargs.get('verbose', False)) - - # TODO refactor for sampling simulator class SimulationFactoryV2: @staticmethod - def create(data_folders: List[str], smodel_files: List[str], sim_param_path="bcipy/simulator/sim_parameters.json", **kwargs): + def create(data_folders: List[str], smodel_files: List[str], + sim_param_path="bcipy/simulator/sim_parameters.json", **kwargs): out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) model_file = Path(smodel_files.pop()) diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index 926037a3e..2417a5b90 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -21,7 +21,7 @@ ], "type": "str" }, - "sim_sleep_time": { + "sim_sleep_time": { "value": "0.25", "section": "sim_config", "readableName": "Simulation Time Step ", diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py index 68ae72b6e..c91385284 100644 --- a/bcipy/simulator/simulator_base.py +++ b/bcipy/simulator/simulator_base.py @@ -1,4 +1,3 @@ -import logging from abc import ABC, abstractmethod @@ -21,4 +20,4 @@ def run(self): @abstractmethod def get_param(self, name): - ... \ No newline at end of file + ... diff --git a/bcipy/simulator/tests/sampler_test.py b/bcipy/simulator/tests/sampler_test.py index 452197cde..f9e5399a3 100644 --- a/bcipy/simulator/tests/sampler_test.py +++ b/bcipy/simulator/tests/sampler_test.py @@ -6,14 +6,12 @@ from bcipy.helpers.load import load_json_parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.metrics import DummyRef +from bcipy.simulator.helpers.metrics import RefereeImpl, SimMetrics1Handler from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler -from bcipy.simulator.helpers.state_manager import StateManagerImpl, StateManager, SimState +from bcipy.simulator.helpers.state_manager import StateManagerImpl, StateManager from bcipy.simulator.helpers.model_handler import SignalModelHandler1 from bcipy.simulator.sim import SimulatorCopyPhrase - - if __name__ == "__main__": args = dict() args['data_folders'] = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700", @@ -39,5 +37,6 @@ sample: np.ndarray = sampler.sample(stateManager.get_state()) model_handler = SignalModelHandler1(model_file) - sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, DummyRef()) + sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, + RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()})) sim.run() From f5932a6632f7a4f8e53e1e3f609ffdfc5475cf2a Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Tue, 9 Jan 2024 19:08:33 +0530 Subject: [PATCH 198/330] pylint clean ups --- bcipy/simulator/README.md | 9 ++++-- bcipy/simulator/__init__.py | 2 ++ bcipy/simulator/__main__.py | 9 ++++-- bcipy/simulator/helpers/data_engine.py | 28 +++++++++------- bcipy/simulator/helpers/evidence_fuser.py | 3 +- bcipy/simulator/helpers/log_utils.py | 2 +- bcipy/simulator/helpers/metrics.py | 23 +++++++------ bcipy/simulator/helpers/model_handler.py | 8 +++-- bcipy/simulator/helpers/sampler.py | 10 +++--- bcipy/simulator/helpers/signal_helpers.py | 2 +- bcipy/simulator/helpers/sim_viz.py | 3 +- bcipy/simulator/helpers/state_manager.py | 24 ++++++++------ bcipy/simulator/sim.py | 39 +++++++++++------------ bcipy/simulator/sim_factory.py | 9 ++++-- bcipy/simulator/simulator_base.py | 8 ++--- 15 files changed, 104 insertions(+), 75 deletions(-) diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index 34d901dfe..11773d456 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -2,13 +2,15 @@ ### Overview -This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and running given models +This Simulator module aims to automate experimentation by sampling EEG data from prior sessions and +running given models in RSVP task loop, thus simulating a live session. ### Run steps -`main.py` is the entry point for program. After following, `BciPy` readme steps for setup, run the module from shell as +`main.py` is the entry point for program. After following, `BciPy` readme steps for setup, run the +module from shell as such: ``python3 bcipy/simulator -d "pathToDataFolder1" -d "pathToOptionalDataFolder2" -sm "pathToSignalModel.pkl"`` @@ -17,7 +19,8 @@ Then view generated LOG file for analysis #### Program Args -- `d` : the data folder argument is necessary. This data will be used to construct data pool from which simulator will +- `d` : the data folder argument is necessary. This data will be used to construct data pool from + which simulator will sample EEG responses. Should contain _raw_data.csv_, _triggers.txt_, _parameters.json_ - `sm`: the signal model argument is necessary to generate evidence diff --git a/bcipy/simulator/__init__.py b/bcipy/simulator/__init__.py index c107589b3..27ca39387 100644 --- a/bcipy/simulator/__init__.py +++ b/bcipy/simulator/__init__.py @@ -1,3 +1,5 @@ +""" Simulator package. View README """ + import datetime import logging import sys diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 34b158717..38c1bb9f2 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -14,7 +14,7 @@ action="append", type=Path, required=True, - help="Raw data folders to be processed. This argument can be repeated to accumulate sessions data.") + help="Raw data folders to be processed. Repeatable arg to accumulate sessions data.") parser.add_argument( "-sm", "--smodel_files", @@ -23,7 +23,12 @@ required=True, help="Signal models to be used") - # TODO parameters file arg + parser.add_argument( + "-p", + "--parameters", + type=Path, + required=False, # For now + help="Parameter File to be used") parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index b01f95423..1fe3869c7 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -10,7 +10,8 @@ from bcipy.helpers import load from bcipy.helpers.list import grouper from bcipy.helpers.parameters import Parameters -from bcipy.simulator.helpers.signal_helpers import ExtractedExperimentData, process_raw_data_for_model +from bcipy.simulator.helpers.signal_helpers import ExtractedExperimentData, \ + process_raw_data_for_model log = logging.getLogger(__name__) @@ -32,17 +33,17 @@ def get_parameters(self) -> List[Parameters]: class RawDataEngine(DataEngine): """ - Object that loads in list of previous session data folders and transforms data into implemented schema + Object that loads in list of session data folders and transforms data into sample-able pd.df """ def __init__(self, source_dirs: List[str]): # TODO read parameters from source dirx - # TODO maybe rely upon single source of data, write some scripts that clean data and group them # TODO use os.walk() and take in single source_dir that has all data folders self.source_dirs: List[str] = source_dirs self.parameter_files: List[Parameters] = [] self.data: Optional[List[ExtractedExperimentData]] = None - self.trials_by_inquiry: List[np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). + self.trials_by_inquiry: List[ + np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). self.symbols_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) self.labels_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) self.schema: Optional[pd.DataFrame] = None @@ -60,18 +61,21 @@ def load(self) -> DataEngine: log.debug(f"Loading data from {len(self.source_dirs)} source directories") self.parameter_files = [ - load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), value_cast=True) for + load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), + value_cast=True) for data_folder in self.source_dirs] - assert len(self.source_dirs) == len(self.parameter_files) # TODO more general parameter validation function + assert len(self.source_dirs) == len( + self.parameter_files) # TODO more general parameter validation function self.data = [process_raw_data_for_model(source_dir, parameter) for source_dir, parameter in zip(self.source_dirs, self.parameter_files)] for data_source, parameter in zip(self.data, self.parameter_files): trigger_targetness, trigger_timing, trigger_symbols = data_source.decoded_triggers - self.trials_by_inquiry.append(np.split(data_source.trials, data_source.inquiries.shape[1], 1)) + self.trials_by_inquiry.append( + np.split(data_source.trials, data_source.inquiries.shape[1], 1)) self.symbols_by_inquiry.append([list(group) for group in grouper(trigger_symbols, parameter.get('stim_length'), incomplete="ignore")]) @@ -95,8 +99,6 @@ def transform(self) -> DataEngine: """ # TODO store how good evidence was in session | store data source as well - cols = ["series_n", "inquiry_n", "trial_n", "symbol", "target", "eeg"] - types = [int, int, int, str, int, np.ndarray] rows = [] for d_i in range(len(self.data)): @@ -106,9 +108,11 @@ def transform(self) -> DataEngine: inquiry_eeg = self.trials_by_inquiry[d_i][i] symbol_rows = [] - for t_i in range(len(symbols)): - channel_eeg_samples_for_t = [channel[t_i] for channel in inquiry_eeg] # (channel_n, sample_n) - row = {'inquiry_n': i, 'trial_n': t_i, 'symbol': symbols[t_i], 'target': inquiry_labels[t_i], + for t_i, symbol in enumerate(symbols): + channel_eeg_samples_for_t = [channel[t_i] for channel in + inquiry_eeg] # (channel_n, sample_n) + row = {'inquiry_n': i, 'trial_n': t_i, 'symbol': symbol, + 'target': inquiry_labels[t_i], 'eeg': np.array(channel_eeg_samples_for_t)} symbol_rows.append(row) diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py index 9269925cd..c43115347 100644 --- a/bcipy/simulator/helpers/evidence_fuser.py +++ b/bcipy/simulator/helpers/evidence_fuser.py @@ -23,7 +23,8 @@ def __init__(self): def fuse(self, prior_likelihood, evidence) -> np.ndarray: len_dist = len(list(evidence.values())[0]) - prior_likelihood = prior_likelihood if prior_likelihood is not None else EvidenceFuser.make_prior(len_dist) + prior_likelihood = prior_likelihood if prior_likelihood is not None else EvidenceFuser.make_prior( + len_dist) ret_likelihood = prior_likelihood.copy() for value in evidence.values(): diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 2e74dee1e..460202c0f 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -9,7 +9,7 @@ def fmt_stim_likelihoods(likelihoods, alp): return formatted -def format_sample_rows(sample_rows: List[pd.Series]): +def format_sample_rows(sample_rows: List[pd.DataFrame]): formatted_rows = [] for row in sample_rows: new_row = row.drop(columns=['eeg'], axis=1, inplace=False) diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py index 284bb615f..35fcb4075 100644 --- a/bcipy/simulator/helpers/metrics.py +++ b/bcipy/simulator/helpers/metrics.py @@ -29,14 +29,16 @@ def handle(self, sim: Simulator) -> Dict[str, Any]: class SimMetrics1Handler(RefereeHandler): def handle(self, sim: Simulator) -> Dict[str, Any]: - state: SimState = sim.__getattribute__("state_manager").get_state() + state: SimState = getattr(sim, ("state_manager")).get_state() info: Dict = SimMetrics1().__dict__ info['total_inquiries'] = state.total_inquiry_count() info['total_series'] = state.series_n - flattened_inquiries: List[InquiryResult] = reduce(lambda l1, l2: l1 + l2, state.series_results, []) - info['total_decisions'] = len(list(filter(lambda inq: bool(inq.decision), flattened_inquiries))) + flattened_inquiries: List[InquiryResult] = reduce(lambda l1, l2: l1 + l2, + state.series_results, []) + info['total_decisions'] = len( + list(filter(lambda inq: bool(inq.decision), flattened_inquiries))) inq_counts = [] for series in state.series_results: @@ -52,27 +54,28 @@ class MetricReferee(ABC): # May change to SimState that is passed around not whole Simulator # Depends on how much data encapsulated by SimState @abstractmethod - def score(self, sim: Simulator) -> SimMetrics1: - ... + def score(self, sim: Simulator): + """ Generate registered metrics for simulation """ @abstractmethod def visualize(self, sim: Simulator): - ... + """ Generate registered visualizations for sim """ @abstractmethod def set_metric_handler(self, name: str, handler: RefereeHandler): - ... + """ Add a metric calculation that will be executed upon self.score() """ @abstractmethod def set_viz_handler(self, name: str, handler: RefereeHandler): - ... + """ Register a visualization that will be executed upon self.visualize() """ class RefereeImpl(MetricReferee): def __init__(self, metric_handlers=None, viz_handlers=None): - self.metric_handlers: Dict[str, RefereeHandler] = metric_handlers if metric_handlers else dict() - self.viz_handlers: Dict[str, RefereeHandler] = viz_handlers if viz_handlers else dict() + self.metric_handlers: Dict[ + str, RefereeHandler] = metric_handlers if metric_handlers else {} + self.viz_handlers: Dict[str, RefereeHandler] = viz_handlers if viz_handlers else {} self.inquiry_time: float = 1 # 1 inq -> 1 second # TODO maybe some configurable parameters for visualizations diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index 5b443b382..d8b66b79f 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -1,5 +1,5 @@ import pickle -from abc import ABC +from abc import ABC, abstractmethod from typing import Optional from bcipy.helpers.symbols import alphabet @@ -9,11 +9,13 @@ class ModelHandler(ABC): + @abstractmethod def generate_evidence(self, state: SimState, features): - ... + """ Run model on features to generate evidence """ + @abstractmethod def get_model(self, key=None): - ... + """ get the model """ class SignalModelHandler1(ModelHandler): diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 3111d2370..c748536bd 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -29,7 +29,8 @@ class EEGByLetterSampler(Sampler): def __init__(self, data_engine: RawDataEngine, params: List[Parameters] = None): self.data_engine: RawDataEngine = data_engine - self.parameter_files: List[Parameters] = params if params else self.data_engine.parameter_files + self.parameter_files: List[ + Parameters] = params if params else self.data_engine.parameter_files self.model_input_reshaper: Callable = self.__default_reshaper self.alphabet: List[str] = params[0].get('symbol_set') if params else alphabet() self.data: pd.DataFrame = self.data_engine.transform().get_data() @@ -49,9 +50,10 @@ def sample(self, state: SimState) -> np.ndarray: for symbol in inquiry_letter_subset: is_target = int(symbol == target_letter) # filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') - filtered_data = self.data.query(f'target == {is_target}') - if not len(filtered_data): - raise TaskConfigurationException(message="No eeg sample found with provided data and query") + filtered_data: pd.DataFrame = self.data.query(f'target == {is_target}') + if filtered_data is None or len(filtered_data) == 0: + raise TaskConfigurationException( + message="No eeg sample found with provided data and query") row = filtered_data.sample(1) sample_rows.append(row) diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 863bc88a3..d7c1735ab 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -5,7 +5,7 @@ import numpy as np -import bcipy.acquisition.devices as devices +from bcipy.acquisition import devices from bcipy.config import ( RAW_DATA_FILENAME, TRIGGER_FILENAME, diff --git a/bcipy/simulator/helpers/sim_viz.py b/bcipy/simulator/helpers/sim_viz.py index 4c94805a4..14644335d 100644 --- a/bcipy/simulator/helpers/sim_viz.py +++ b/bcipy/simulator/helpers/sim_viz.py @@ -55,7 +55,8 @@ def plot_replay_comparison(new_target_eeg_evidence: np.ndarray, outdir: str, parameters: Parameters, ) -> None: - def convert_to_records(arr, key_value, key_name="which_model", value_name="response_value") -> [dict]: + def convert_to_records(arr, key_value, key_name="which_model", value_name="response_value") -> [ + dict]: return [{key_name: key_value, value_name: val} for val in arr] records = [] diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 9a4ab631e..93d654d24 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -44,7 +44,8 @@ def get_current_likelihood(self) -> Optional[np.ndarray]: class StateManager(ABC): - def update(self, evidence: np.ndarray): # TODO change evidence type to dictionary or some dataclass + def update(self, + evidence: np.ndarray): # TODO change evidence type to dictionary or some dataclass raise NotImplementedError() def is_done(self) -> bool: @@ -90,13 +91,15 @@ def update(self, evidence) -> InquiryResult: temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, # TODO change to use evidence_dict - evidence_likelihoods=list(evidence), fused_likelihood=fused_likelihood, + evidence_likelihoods=list(evidence), + fused_likelihood=fused_likelihood, decision=None) # can we make decision temp_series = copy.deepcopy(self.get_state().series_results) temp_series[-1].append(temp_inquiry_result) - is_decidable = any([decider.decide(temp_series[-1]) for decider in self.state.decision_criterion]) + is_decidable = any( + [decider.decide(temp_series[-1]) for decider in self.state.decision_criterion]) decision = None new_state = self.get_state().__dict__ @@ -107,7 +110,8 @@ def update(self, evidence) -> InquiryResult: new_state['series_results'][self.state.series_n].append(new_inquiry_result) if is_decidable: - decision = alphabet()[np.argmax(evidence)] # deciding the maximum probability symbol TODO abstract + decision = alphabet()[ + np.argmax(evidence)] # deciding the maximum probability symbol TODO abstract # resetting series new_state['series_n'] += 1 @@ -116,9 +120,11 @@ def update(self, evidence) -> InquiryResult: # updating current sentence and finding next target new_state['current_sentence'] = new_state['current_sentence'] + \ - decision if decision != BACKSPACE_CHAR else new_state['current_sentence'][ - :-1] - new_state['target_symbol'] = next_target_letter(new_state['current_sentence'], self.state.target_sentence) + decision if decision != BACKSPACE_CHAR else new_state[ + 'current_sentence'][ + :-1] + new_state['target_symbol'] = next_target_letter(new_state['current_sentence'], + self.state.target_sentence) else: new_state['inquiry_n'] += 1 @@ -143,8 +149,8 @@ def mutate_state(self, state_field, state_value) -> SimState: state_dict[state_field] = state_value self.state = SimState(**state_dict) return self.get_state() - else: - raise FieldException(f"Cannot find state field {state_field}") + + raise FieldException(f"Cannot find state field {state_field}") @staticmethod def initial_state(parameters: Parameters = None) -> SimState: diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 4c663a932..ae7d06030 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -25,33 +25,32 @@ class SimulatorCopyPhrase(Simulator): Copy Phrase simulator. Run loop: - - The loop runs until StateManager determines simulation is over - - The generated stimuli are passed into sampler, which returns some eeg response - - The Model handler will generate predictions and feed back into StateManager - - StateManager will resolve the state while the MetricReferee observes and records any metrics + - The loop runs until StateManager determines simulation is over + - The generated stimuli are passed into sampler, which returns some eeg response + - The Model handler will generate predictions and feed back into StateManager + - StateManager will resolve the state while the MetricReferee observes and records any metrics Main components: - - DataEngine: loading and storing data - - Sampler: logic for sampling from data, composed of DataEngine - - StateManager: manages run loop details and fuses model evidence with current state - - MetricReferee: tracks and scores the simulation on different metrics for later evaluation - - ModelHandler: wrapper for models that deals with loading in models and generating evidence + - DataEngine: loading and storing data + - Sampler: logic for sampling from data, composed of DataEngine + - StateManager: manages run loop details and fuses model evidence with current state + - MetricReferee: tracks and scores the simulation on different metrics for later evaluation + - ModelHandler: wrapper for models that deals with loading in models and generating evidence Requirements: - run closed loop simulation of {TaskType} with {data} with {simulation_params} """ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, parameter_path: str = None, save_dir: str = None, - verbose=False, visualize=False): - super(SimulatorCopyPhrase, self).__init__() + state_manager: StateManager, referee: MetricReferee, parameter_path: str = None, + save_dir: str = None): + super().__init__() self.save_dir: str = save_dir self.model_handler: ModelHandler = model_handler self.sampler: Sampler = sampler self.referee: MetricReferee = referee self.state_manager: StateManager = state_manager - self.data_engine: DataEngine = data_engine self.parameters = self.load_parameters(parameter_path) @@ -59,16 +58,14 @@ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler self.symbol_set = alphabet() self.write_output = False - self.verbose = verbose - self.visualize = visualize - def run(self): log.info(f"SIM START with target word {self.state_manager.get_state().target_sentence}") while not self.state_manager.is_done(): curr_state = self.state_manager.get_state() log.info( - f"Series {curr_state.series_n} | Inquiry {curr_state.inquiry_n} | Target {curr_state.target_symbol}") + f"Series {curr_state.series_n} | Inquiry {curr_state.inquiry_n} | " + + f"Target {curr_state.target_symbol}") self.state_manager.mutate_state('display_alphabet', self.__make_stimuli(curr_state)) sampled_data = self.sampler.sample(curr_state) @@ -82,7 +79,9 @@ def run(self): inq_record: InquiryResult = self.state_manager.update(evidence) updated_state = self.state_manager.get_state() - log.debug(f"Fused Likelihoods {fmt_stim_likelihoods(inq_record.fused_likelihood, self.symbol_set)}") + log.debug( + f"Fused Likelihoods + " + f"{fmt_stim_likelihoods(inq_record.fused_likelihood, self.symbol_set)}") if inq_record.decision: log.info(f"Decided {inq_record.decision} for target {inq_record.target}") @@ -106,8 +105,8 @@ def __make_stimuli(self, state: SimState): if val_func is not None: return stimuli.best_selection(self.symbol_set, list( val_func), subset_length, always_included=always_in_stimuli) - else: - return random.sample(self.symbol_set, subset_length) + + return random.sample(self.symbol_set, subset_length) def load_parameters(self, path): # TODO validate parameters diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 8b7b51917..b039898d5 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -1,3 +1,4 @@ +""" Factory for Simulator objects """ from pathlib import Path from typing import List @@ -11,20 +12,22 @@ class SimulationFactoryV2: + """ Factory class to create Simulator instances """ + @staticmethod def create(data_folders: List[str], smodel_files: List[str], sim_param_path="bcipy/simulator/sim_parameters.json", **kwargs): - out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) + # out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) model_file = Path(smodel_files.pop()) sim_parameters = load_json_parameters(sim_param_path, value_cast=True) data_engine = RawDataEngine(data_folders) - stateManager: StateManager = StateManagerImpl(sim_parameters) + state_manager: StateManager = StateManagerImpl(sim_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) model_handler: ModelHandler = SignalModelHandler1(model_file) referee: MetricReferee = RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()}) - sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, stateManager, referee) + sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, state_manager, referee) return sim diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py index c91385284..79eaae114 100644 --- a/bcipy/simulator/simulator_base.py +++ b/bcipy/simulator/simulator_base.py @@ -1,3 +1,4 @@ +""" base simulator interface """ from abc import ABC, abstractmethod @@ -11,13 +12,10 @@ class Simulator(ABC): - run closed loop simulation of {TaskType} with {data} with {simulation_params} """ - def __init__(self): - super(Simulator, self).__init__() - @abstractmethod def run(self): - ... + """ Run loop for simulation""" @abstractmethod def get_param(self, name): - ... + """ retrieving parameter """ From 172bedffaf079b65b4d3505d518170837522ad96 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 9 Jan 2024 13:40:39 -0800 Subject: [PATCH 199/330] Refactored VEP display to take a parameter for flicker_rates, rather than codes; added logging --- .../display/demo/vep/demo_calibration_vep.py | 12 ++---------- bcipy/display/paradigm/vep/codes.py | 1 + bcipy/display/paradigm/vep/display.py | 19 +++++++++++++------ bcipy/task/paradigm/vep/calibration.py | 17 +++++------------ 4 files changed, 21 insertions(+), 28 deletions(-) diff --git a/bcipy/display/demo/vep/demo_calibration_vep.py b/bcipy/display/demo/vep/demo_calibration_vep.py index 566b80209..c0a53b4ea 100644 --- a/bcipy/display/demo/vep/demo_calibration_vep.py +++ b/bcipy/display/demo/vep/demo_calibration_vep.py @@ -7,8 +7,7 @@ init_display_window) from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar -from bcipy.display.paradigm.vep.codes import (DEFAULT_FLICKER_RATES, - ssvep_to_code) +from bcipy.display.paradigm.vep.codes import DEFAULT_FLICKER_RATES from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock @@ -52,13 +51,6 @@ '#FF8232' ] -# Note: these rates work for a 60hz display -flicker_rates = DEFAULT_FLICKER_RATES -codes = [ - ssvep_to_code(refresh_rate=int(frame_rate), flicker_rate=hz) - for hz in flicker_rates -] - layout = centered(width_pct=0.95, height_pct=0.80) box_config = BoxConfiguration(layout, height_pct=0.30) @@ -80,7 +72,7 @@ task_bar, info, box_config=box_config, - codes=codes, + flicker_rates=DEFAULT_FLICKER_RATES, should_prompt_target=True, frame_rate=frame_rate) wait_seconds = 2 diff --git a/bcipy/display/paradigm/vep/codes.py b/bcipy/display/paradigm/vep/codes.py index e96067e3d..86e367460 100644 --- a/bcipy/display/paradigm/vep/codes.py +++ b/bcipy/display/paradigm/vep/codes.py @@ -8,6 +8,7 @@ log = logging.getLogger(__name__) +# These rates work for a 60hz display DEFAULT_FLICKER_RATES = [4, 5, 6, 10, 12, 15] diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 993838d20..1b2ee2f16 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -11,8 +11,9 @@ from bcipy.display.components.layout import scaled_size from bcipy.display.components.task_bar import TaskBar from bcipy.display.paradigm.matrix.layout import symbol_positions -from bcipy.display.paradigm.vep.codes import (create_vep_codes, - round_refresh_rate) +from bcipy.display.paradigm.vep.codes import (DEFAULT_FLICKER_RATES, + round_refresh_rate, + ssvep_to_code) from bcipy.display.paradigm.vep.layout import BoxConfiguration, animation_path from bcipy.display.paradigm.vep.vep_stim import VEPStim from bcipy.helpers.clock import Clock @@ -47,9 +48,12 @@ def __init__(self, box_config: BoxConfiguration, trigger_type: str = 'text', symbol_set: Optional[List[str]] = None, - codes: Optional[List[List[int]]] = None, + flicker_rates: List[int] = DEFAULT_FLICKER_RATES, should_prompt_target: bool = True, frame_rate: Optional[float] = None): + assert len( + flicker_rates + ) >= box_config.num_boxes, 'Not enough flicker rates provided' self.window = window if not frame_rate: frame_rate = self.window.getActualFrameRate() @@ -109,9 +113,12 @@ def __init__(self, self.info_text = info.build_info_text(window) # build the VEP stimuli - if not codes: - codes = create_vep_codes(length=self.refresh_rate, - count=self.vep_type) + self.logger.info(f"VEP flicker rates (hz): {flicker_rates}") + rate = round_refresh_rate(frame_rate) + codes = [ + ssvep_to_code(refresh_rate=rate, flicker_rate=int(hz)) + for hz in flicker_rates + ] vep_colors = [('white', 'black'), ('red', 'green'), ('blue', 'yellow'), ('orange', 'green')] vep_stim_size = scaled_size(0.24, self.window_size) diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 7761766ab..8a9a0df07 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -8,9 +8,7 @@ from bcipy.display import InformationProperties, VEPStimuliProperties from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar -from bcipy.display.paradigm.vep.codes import (DEFAULT_FLICKER_RATES, - round_refresh_rate, - ssvep_to_code) +from bcipy.display.paradigm.vep.codes import DEFAULT_FLICKER_RATES from bcipy.display.paradigm.vep.display import VEPDisplay from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock @@ -235,7 +233,7 @@ def init_calibration_display(parameters: Parameters, stim_color=colors, inquiry=[], stim_length=1, - animation_seconds=1.0) + animation_seconds=parameters['time_vep_animation']) task_bar = CalibrationTaskBar(window, inquiry_count=parameters['stim_number'], @@ -244,19 +242,14 @@ def init_calibration_display(parameters: Parameters, font=parameters['font'], height=parameters['task_height']) - # issue #186641183 ; determine a better configuration strategy - flicker_rates = DEFAULT_FLICKER_RATES - rate = round_refresh_rate(window.getActualFrameRate()) - codes = [ - ssvep_to_code(refresh_rate=rate, flicker_rate=int(hz)) - for hz in flicker_rates - ] + # issue #186641183 ; determine a better configuration strategy for flicker + return VEPDisplay(window, experiment_clock, stim_props, task_bar, info, symbol_set=symbol_set, - codes=codes, box_config=box_config, + flicker_rates=DEFAULT_FLICKER_RATES, should_prompt_target=True) From b1aac715bbb9594ae03cc3a57fee967c63caebb7 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 10 Jan 2024 17:24:08 -0800 Subject: [PATCH 200/330] Add tests for current query behavior --- bcipy/task/control/query.py | 5 +- bcipy/task/tests/core/test_query.py | 150 +++++++++++++++++++++++++--- 2 files changed, 138 insertions(+), 17 deletions(-) diff --git a/bcipy/task/control/query.py b/bcipy/task/control/query.py index c7cd171dd..7468402e2 100644 --- a/bcipy/task/control/query.py +++ b/bcipy/task/control/query.py @@ -1,7 +1,8 @@ -import numpy as np import random -from typing import List, Optional from abc import ABC, abstractmethod +from typing import List, Optional + +import numpy as np from bcipy.helpers.stimuli import best_selection diff --git a/bcipy/task/tests/core/test_query.py b/bcipy/task/tests/core/test_query.py index 3ea91d65e..5a754fec0 100644 --- a/bcipy/task/tests/core/test_query.py +++ b/bcipy/task/tests/core/test_query.py @@ -1,23 +1,143 @@ import unittest -from bcipy.task.control.query import best_selection + +from bcipy.task.control.query import (NBestStimuliAgent, RandomStimuliAgent, + best_selection) class TestQueryMechanisms(unittest.TestCase): + """Tests for query functions""" + def test_best_selection(self): - list_el = ["A", "E", "I", "O", "U"] - values = [0.4, 0.1, 0.25, 0.1, 0.15] - len_query = 3 - self.assertEqual(["A", "I", "U"], best_selection(list_el, values, len_query)) - - list_el = ["A", "E", "I", "O", "U"] - values = [0.15, 0.4, 0.1, 0.25, 0.1] - len_query = 3 - self.assertEqual(["E", "O", "A"], best_selection(list_el, values, len_query)) - - list_el = ["A", "E", "I", "O", "U"] - values = [0.1, 0.2, 0.2, 0.2, 0.2] - len_query = 3 - self.assertEqual(["E", "I", "O"], best_selection(list_el, values, len_query)) + """Test best_selection function""" + self.assertEqual(["A", "I", "U"], + best_selection( + selection_elements=["A", "E", "I", "O", "U"], + val=[0.4, 0.1, 0.25, 0.1, 0.15], + len_query=3)) + + self.assertEqual(["E", "O", "A"], + best_selection( + selection_elements=["A", "E", "I", "O", "U"], + val=[0.15, 0.4, 0.1, 0.25, 0.1], + len_query=3)) + + self.assertEqual(["E", "I", "O"], + best_selection( + selection_elements=["A", "E", "I", "O", "U"], + val=[0.1, 0.2, 0.2, 0.2, 0.2], + len_query=3)) + + self.assertEqual( + ["A", "E", "I"], + best_selection(selection_elements=["A", "E", "I", "O", "U"], + val=[0.2, 0.2, 0.2, 0.2, 0.2], + len_query=3), + msg="equally probable items should be in alphabetical order") + + self.assertEqual(["A", "U", "I"], + best_selection( + selection_elements=["A", "E", "I", "O", "U"], + val=[0.4, 0.1, 0.0, 0.1, 0.4], + len_query=3, + always_included=["I"]), + msg="always_included items should be in the results") + + self.assertEqual( + ["A", "U", "E"], + best_selection(selection_elements=["A", "E", "I", "O", "U"], + val=[0.4, 0.1, 0.0, 0.1, 0.4], + len_query=3, + always_included=["<"]), + msg="Always included items are only applied if present") + + +class TestNBestStimuliAgent(unittest.TestCase): + """Tests for NBestStimuliAgent""" + + def test_highest_probs(self): + """Test the NBestStimuliAgent should select symbols with the highest + probabilities""" + agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + self.assertEqual(["A", "I", "U"], + agent.return_stimuli( + list_distribution=[[0.4, 0.1, 0.25, 0.1, 0.15]], + constants=None)) + + def test_multiple_value_lists(self): + """Test with multiple values in the list distribution.""" + agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + self.assertEqual( + ["E", "O", "A"], + agent.return_stimuli( + list_distribution=[[0.4, 0.1, 0.25, 0.1, 0.15], + [0.15, 0.4, 0.1, 0.25, 0.1]], + constants=None), + msg="Last list of probabilities should be used for selection") + + def test_all_equal_probs(self): + """Test where all probabilities are equal""" + agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + + self.assertEqual(["A", "E", "I"], + agent.return_stimuli( + list_distribution=[[0.2, 0.2, 0.2, 0.2, 0.2]], + constants=None), + msg="Should return the first n values") + + def test_constants(self): + """Test with constant items included in results.""" + agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + + self.assertEqual(["E", "I", "U"], + agent.return_stimuli( + list_distribution=[[0.1, 0.3, 0.3, 0.2, 0.1]], + constants=["U"])) + + +class TestRandomStimuliAgent(unittest.TestCase): + """Tests for RandomStimuliAgent""" + + def test_randomness(self): + """Test that symbols are not selected based on probabilities.""" + agent = RandomStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + + # Generate 100 queries + queries = [ + agent.return_stimuli([[0.3, 0.3, 0.2, 0.1, 0.1]]) + for i in range(100) + ] + # Turn each list of symbols into a string to make them easier to compare + strings = [''.join(query) for query in queries] + self.assertTrue(len(set(strings)) > 1, + msg="All queries should not be the same") + + all_queries: str = ''.join(strings) + self.assertTrue( + "O" in all_queries or "U" in all_queries, + msg="Not only the highest probability symbols should be returned.") + + def test_ordering(self): + """Test that ordering is not always alphabetical""" + agent = RandomStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + queries = [ + agent.return_stimuli([[0.3, 0.3, 0.2, 0.1, 0.1]]) + for i in range(10) + ] + self.assertFalse(all(sorted(query) == query for query in queries)) + + def test_constants(self): + """Test that constants are always added.""" + agent = RandomStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + query = agent.return_stimuli([[0.3, 0.3, 0.2, 0.1, 0.1]], + constants=["O"]) + self.assertTrue("O" in query) if __name__ == '__main__': From 46c1be30e1f14880559016d9bfabe1f9b306dfdc Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 10 Jan 2024 17:31:44 -0800 Subject: [PATCH 201/330] Remove redundant tests --- bcipy/task/tests/core/test_query.py | 50 +---------------------------- 1 file changed, 1 insertion(+), 49 deletions(-) diff --git a/bcipy/task/tests/core/test_query.py b/bcipy/task/tests/core/test_query.py index 5a754fec0..f00c31853 100644 --- a/bcipy/task/tests/core/test_query.py +++ b/bcipy/task/tests/core/test_query.py @@ -1,54 +1,6 @@ import unittest -from bcipy.task.control.query import (NBestStimuliAgent, RandomStimuliAgent, - best_selection) - - -class TestQueryMechanisms(unittest.TestCase): - """Tests for query functions""" - - def test_best_selection(self): - """Test best_selection function""" - self.assertEqual(["A", "I", "U"], - best_selection( - selection_elements=["A", "E", "I", "O", "U"], - val=[0.4, 0.1, 0.25, 0.1, 0.15], - len_query=3)) - - self.assertEqual(["E", "O", "A"], - best_selection( - selection_elements=["A", "E", "I", "O", "U"], - val=[0.15, 0.4, 0.1, 0.25, 0.1], - len_query=3)) - - self.assertEqual(["E", "I", "O"], - best_selection( - selection_elements=["A", "E", "I", "O", "U"], - val=[0.1, 0.2, 0.2, 0.2, 0.2], - len_query=3)) - - self.assertEqual( - ["A", "E", "I"], - best_selection(selection_elements=["A", "E", "I", "O", "U"], - val=[0.2, 0.2, 0.2, 0.2, 0.2], - len_query=3), - msg="equally probable items should be in alphabetical order") - - self.assertEqual(["A", "U", "I"], - best_selection( - selection_elements=["A", "E", "I", "O", "U"], - val=[0.4, 0.1, 0.0, 0.1, 0.4], - len_query=3, - always_included=["I"]), - msg="always_included items should be in the results") - - self.assertEqual( - ["A", "U", "E"], - best_selection(selection_elements=["A", "E", "I", "O", "U"], - val=[0.4, 0.1, 0.0, 0.1, 0.4], - len_query=3, - always_included=["<"]), - msg="Always included items are only applied if present") +from bcipy.task.control.query import NBestStimuliAgent, RandomStimuliAgent class TestNBestStimuliAgent(unittest.TestCase): From 937f1bd534ef2669fec62dcd3c99e927fa4792ff Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 11 Jan 2024 15:40:20 -0800 Subject: [PATCH 202/330] Refactored NBestStimuliAgent to randomize symbols with the same probability --- bcipy/task/control/query.py | 26 ++++++++-- bcipy/task/tests/core/test_query.py | 76 +++++++++++++++++++++-------- 2 files changed, 77 insertions(+), 25 deletions(-) diff --git a/bcipy/task/control/query.py b/bcipy/task/control/query.py index 7468402e2..3ea8668fc 100644 --- a/bcipy/task/control/query.py +++ b/bcipy/task/control/query.py @@ -81,12 +81,28 @@ def __init__(self, alphabet: List[str], len_query: int = 4): def reset(self): pass - def return_stimuli(self, list_distribution: np.ndarray, constants: Optional[List[str]] = None): - p = list_distribution[-1] - tmp = [i for i in self.alphabet] - query = best_selection(tmp, p, self.len_query, always_included=constants) + def return_stimuli(self, + list_distribution: np.ndarray, + constants: Optional[List[str]] = None) -> List[str]: + """Returns a list of the n most likely symbols based on the provided + probabilities, where n is self.len_query. Symbols of the same + probability will be ordered randomly. + + Parameters + ---------- + list_distribution - list of lists of probabilities. Only the last list will + be used. + constants - optional list of symbols which should appear every result + """ + symbol_probs = list(zip(self.alphabet, list_distribution[-1])) + randomized = random.sample(symbol_probs, len(symbol_probs)) + symbols, probs = zip(*randomized) + return best_selection(selection_elements=list(symbols), + val=list(probs), + len_query=self.len_query, + always_included=constants) + - return query def do_series(self): pass diff --git a/bcipy/task/tests/core/test_query.py b/bcipy/task/tests/core/test_query.py index f00c31853..01b651fc9 100644 --- a/bcipy/task/tests/core/test_query.py +++ b/bcipy/task/tests/core/test_query.py @@ -11,43 +11,79 @@ def test_highest_probs(self): probabilities""" agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], len_query=3) - self.assertEqual(["A", "I", "U"], - agent.return_stimuli( - list_distribution=[[0.4, 0.1, 0.25, 0.1, 0.15]], - constants=None)) + stim = agent.return_stimuli( + list_distribution=[[0.4, 0.1, 0.25, 0.1, 0.15]], constants=None) + self.assertTrue("A" in stim) + self.assertTrue("I" in stim) + self.assertTrue("U" in stim) + + def test_highest_probs_ordering(self): + """Test the NBestStimuliAgent should order the returned symbols + by decreasing probability.""" + agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + stims = [ + agent.return_stimuli( + list_distribution=[[0.4, 0.1, 0.25, 0.1, 0.15]], + constants=None) for _ in range(10) + ] + + self.assertTrue(all([stim == ['A', 'I', 'U'] for stim in stims]), + msg="All queries should be the same") def test_multiple_value_lists(self): """Test with multiple values in the list distribution.""" agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], len_query=3) - self.assertEqual( - ["E", "O", "A"], - agent.return_stimuli( - list_distribution=[[0.4, 0.1, 0.25, 0.1, 0.15], - [0.15, 0.4, 0.1, 0.25, 0.1]], - constants=None), - msg="Last list of probabilities should be used for selection") + stim = agent.return_stimuli( + list_distribution=[[0.4, 0.1, 0.25, 0.1, 0.15], + [0.15, 0.4, 0.1, 0.25, 0.1]], + constants=None) + self.assertTrue("E" in stim) + self.assertTrue("O" in stim) + self.assertTrue("A" in stim) def test_all_equal_probs(self): """Test where all probabilities are equal""" agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], len_query=3) + stims = [ + agent.return_stimuli(list_distribution=[[0.2, 0.2, 0.2, 0.2, 0.2]], + constants=None) for _ in range(10) + ] + stim_strings = [''.join(sorted(stim)) for stim in stims] + self.assertTrue(len(set(stim_strings)) > 1, + msg="All queries should not have the same symbols") + + def test_some_equal_probs(self): + """Test ordering where some probabilities are equal.""" + agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], + len_query=3) + stims = [ + agent.return_stimuli(list_distribution=[[0.4, 0.1, 0.2, 0.1, 0.2]], + constants=None) for _ in range(10) + ] + + unsorted_stim_strings = [''.join(stim) for stim in stims] + self.assertTrue(len(set(unsorted_stim_strings)) > 1, + msg="All queries should not have the same ordering") - self.assertEqual(["A", "E", "I"], - agent.return_stimuli( - list_distribution=[[0.2, 0.2, 0.2, 0.2, 0.2]], - constants=None), - msg="Should return the first n values") + sorted_stim_strings = [''.join(sorted(stim)) for stim in stims] + self.assertEqual(1, + len(set(sorted_stim_strings)), + msg="All queries should have the same symbols") + self.assertEqual("AIU", list(set(sorted_stim_strings))[0]) def test_constants(self): """Test with constant items included in results.""" agent = NBestStimuliAgent(alphabet=["A", "E", "I", "O", "U"], len_query=3) - self.assertEqual(["E", "I", "U"], - agent.return_stimuli( - list_distribution=[[0.1, 0.3, 0.3, 0.2, 0.1]], - constants=["U"])) + stims = agent.return_stimuli( + list_distribution=[[0.1, 0.3, 0.3, 0.2, 0.1]], constants=["U"]) + self.assertTrue("E" in stims) + self.assertTrue("I" in stims) + self.assertTrue("U" in stims) class TestRandomStimuliAgent(unittest.TestCase): From 14acccd3cbaeaf5f4f8a64a0c9f42d32dae9f102 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 11 Jan 2024 15:40:46 -0800 Subject: [PATCH 203/330] Set default lm_backspace_prob to 0 --- bcipy/parameters/parameters.json | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index fa3c431c6..11a5c30e3 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -678,11 +678,11 @@ "type": "str" }, "lm_backspace_prob": { - "value": "0.05", + "value": "0.0", "section": "bci_config", "readableName": "Backspace Probability", - "helpTip": "Specifies the initial probability assigned to the backspace character in the language model. Possible value range: 0.0-1.0. Default: 0.05", - "recommended_values": "", + "helpTip": "Specifies the minimum probability assigned to the backspace character in the language model. Possible value range: 0.0-1.0. Default: 0.0", + "recommended_values": "0.05", "type": "float" }, "show_preview_inquiry": { From 00b4500ceedaf342e676be872617f58d9b11db24 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 11 Jan 2024 16:08:33 -0800 Subject: [PATCH 204/330] Bug fix in multimodal active settings --- bcipy/acquisition/multimodal.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 8249f0885..7a29405bb 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -89,8 +89,8 @@ def active_device_content_types(self) -> List[ContentType]: """Returns a list of ContentTypes provided by the active configured devices.""" return [ - content_type for content_type, spec in self._clients.items() - if spec.is_active + content_type for content_type, client in self._clients.items() + if client.device_spec.is_active ] @property From ef0182def19dc5de9de3078b8e1a77db2373f3d8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 11 Jan 2024 16:13:19 -0800 Subject: [PATCH 205/330] Cleanup --- bcipy/task/control/query.py | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/bcipy/task/control/query.py b/bcipy/task/control/query.py index 3ea8668fc..617d029b6 100644 --- a/bcipy/task/control/query.py +++ b/bcipy/task/control/query.py @@ -87,7 +87,7 @@ def return_stimuli(self, """Returns a list of the n most likely symbols based on the provided probabilities, where n is self.len_query. Symbols of the same probability will be ordered randomly. - + Parameters ---------- list_distribution - list of lists of probabilities. Only the last list will @@ -102,7 +102,5 @@ def return_stimuli(self, len_query=self.len_query, always_included=constants) - - def do_series(self): pass From a03ae36beee00dded7d95d2c13bdef83d15ffefb Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 22 Jan 2024 10:42:32 -0500 Subject: [PATCH 206/330] model handler pickle load in constructor --- bcipy/simulator/helpers/model_handler.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index d8b66b79f..b15de4c44 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -23,11 +23,10 @@ class SignalModelHandler1(ModelHandler): def __init__(self, model_file): self.model_file = model_file self.signal_model: Optional[SignalModel] = None - - def generate_evidence(self, state: SimState, features): with open(self.model_file, "rb") as signal_file: self.signal_model = pickle.load(signal_file) + def generate_evidence(self, state: SimState, features): stimuli = state.display_alphabet alp = alphabet() eeg_evidence = self.signal_model.predict(features, stimuli, alp) From 9b946aea908a915c45f5f01d172f0445e0f9330e Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 22 Jan 2024 16:24:46 -0500 Subject: [PATCH 207/330] language model support + evidence fusing bug fix --- bcipy/simulator/helpers/evidence_fuser.py | 18 +++++--- bcipy/simulator/helpers/log_utils.py | 6 +++ bcipy/simulator/helpers/model_handler.py | 55 ++++++++++++++++++++++- bcipy/simulator/helpers/rsvp_utils.py | 13 ++++++ bcipy/simulator/helpers/state_manager.py | 42 +++++++++-------- bcipy/simulator/helpers/types.py | 20 ++++----- bcipy/simulator/sim.py | 50 +++++++++++++++------ bcipy/simulator/sim_factory.py | 7 ++- bcipy/simulator/sim_parameters.json | 23 +++++++++- 9 files changed, 180 insertions(+), 54 deletions(-) diff --git a/bcipy/simulator/helpers/evidence_fuser.py b/bcipy/simulator/helpers/evidence_fuser.py index c43115347..8aa1e559d 100644 --- a/bcipy/simulator/helpers/evidence_fuser.py +++ b/bcipy/simulator/helpers/evidence_fuser.py @@ -3,11 +3,14 @@ import numpy as np +from bcipy.simulator.helpers.types import SimEvidence + class EvidenceFuser(ABC): @abstractmethod - def fuse(self, prior_likelihood: Optional[np.ndarray], evidence: Dict) -> np.ndarray: + def fuse(self, prior_likelihood: Optional[np.ndarray], + evidence: Dict[str, SimEvidence]) -> np.ndarray: ... @staticmethod @@ -22,13 +25,16 @@ def __init__(self): def fuse(self, prior_likelihood, evidence) -> np.ndarray: - len_dist = len(list(evidence.values())[0]) - prior_likelihood = prior_likelihood if prior_likelihood is not None else EvidenceFuser.make_prior( - len_dist) + distribution_shape = len(list(evidence.values())[0].evidence) + prior_likelihood = prior_likelihood if prior_likelihood is not None \ + else EvidenceFuser.make_prior(distribution_shape) + ret_likelihood = prior_likelihood.copy() - for value in evidence.values(): - ret_likelihood *= value[:] + for sim_evidence in evidence.values(): + likelihoods = sim_evidence.evidence + assert ret_likelihood.shape == likelihoods.shape + ret_likelihood *= likelihoods[:] ret_likelihood = self.__normalize_likelihood(ret_likelihood) return ret_likelihood diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 460202c0f..881b38d45 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -9,6 +9,12 @@ def fmt_stim_likelihoods(likelihoods, alp): return formatted +def fmt_fused_likelihoods_for_hist(likelihoods, alp): + rounded = [round(lik, 3) for lik in likelihoods] + formatted = [(a, l) for a, l in zip(alp, rounded)] + return formatted + + def format_sample_rows(sample_rows: List[pd.DataFrame]): formatted_rows = [] for row in sample_rows: diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index b15de4c44..baeb6ac9e 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -1,10 +1,19 @@ +import logging import pickle from abc import ABC, abstractmethod from typing import Optional +import numpy as np + +from bcipy.helpers.language_model import init_language_model, histogram from bcipy.helpers.symbols import alphabet +from bcipy.language import LanguageModel from bcipy.signal.model import SignalModel from bcipy.simulator.helpers.state_manager import SimState +from bcipy.simulator.helpers.types import SimEvidence +from bcipy.task.data import EvidenceType + +log = logging.getLogger(__name__) class ModelHandler(ABC): @@ -12,6 +21,7 @@ class ModelHandler(ABC): @abstractmethod def generate_evidence(self, state: SimState, features): """ Run model on features to generate evidence """ + breakpoint() @abstractmethod def get_model(self, key=None): @@ -31,7 +41,50 @@ def generate_evidence(self, state: SimState, features): alp = alphabet() eeg_evidence = self.signal_model.predict(features, stimuli, alp) - return eeg_evidence + return dict(sm=SimEvidence(EvidenceType.ERP, eeg_evidence, stimuli)) def get_model(self, key=None): return self.signal_model + + +class SigLmModelHandler1(ModelHandler): + + def __init__(self, sm_model_file, parameters): + """ + + Args: + sm_model_file: path to signal model pickle + parameters: only needs to contain which type of language model + """ + self.sm_model_file = sm_model_file + self.signal_model: Optional[SignalModel] = None + self.lm_model: LanguageModel = init_language_model(parameters) + self.alp = alphabet() + + with open(self.sm_model_file, "rb") as signal_file: + self.signal_model = pickle.load(signal_file) + + def generate_evidence(self, state: SimState, eeg_responses): + stimuli = state.display_alphabet + eeg_evidence = self.signal_model.predict(eeg_responses, stimuli, self.alp) + lm_evidence = self.lm_model.predict( + list(state.current_sentence)) if state.inquiry_n == 0 else None + # TODO check lm_parameters for default backspace prob + + ret_evidence = {} + if lm_evidence is not None: + ret_evidence['lm'] = SimEvidence(EvidenceType.LM, np.array(lm_evidence), self.alp) + log.debug(f"LM evidence for '{state.current_sentence}' -> \n {histogram(lm_evidence)}") + + if eeg_evidence is not None: + ret_evidence['sm'] = SimEvidence(EvidenceType.ERP, eeg_evidence, stimuli) + + return ret_evidence + + def get_model(self, key=None): + if key == 'sm': + return self.signal_model + elif key == 'lm': + return self.lm_model + else: + raise RuntimeError(f"Can't find model {key}") diff --git a/bcipy/simulator/helpers/rsvp_utils.py b/bcipy/simulator/helpers/rsvp_utils.py index fad352b72..78d3aebe3 100644 --- a/bcipy/simulator/helpers/rsvp_utils.py +++ b/bcipy/simulator/helpers/rsvp_utils.py @@ -1,3 +1,5 @@ +from typing import List, Tuple + from bcipy.helpers.symbols import BACKSPACE_CHAR @@ -9,3 +11,14 @@ def next_target_letter(current_sentence, target_sentence): return target_sentence[len(current_sentence)] if len( current_sentence) < len(target_sentence) else target_sentence[-1] return BACKSPACE_CHAR + + +def format_lm_output(lm_evidence_tuples: List[Tuple], symbol_set): + """ Formats language model output into list of likelihoods in alphabet order """ + pos_map = {letter: i for i, letter in enumerate(symbol_set)} + reshaped_lm_lik = list(symbol_set) + # sorting the likelhoods by order of symbol set + for letter, lik in lm_evidence_tuples: + reshaped_lm_lik[pos_map[letter]] = float(lik) + + return reshaped_lm_lik diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 93d654d24..622784862 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -1,18 +1,23 @@ import copy +import logging import random from abc import ABC from dataclasses import dataclass -from typing import List, Optional +from typing import List, Optional, Dict import numpy as np from bcipy.helpers.exceptions import FieldException +from bcipy.helpers.language_model import histogram from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR from bcipy.simulator.helpers.decision import SimDecisionCriteria, MaxIterationsSim, ProbThresholdSim from bcipy.simulator.helpers.evidence_fuser import MultiplyFuser, EvidenceFuser +from bcipy.simulator.helpers.log_utils import fmt_fused_likelihoods_for_hist from bcipy.simulator.helpers.rsvp_utils import next_target_letter -from bcipy.simulator.helpers.types import InquiryResult +from bcipy.simulator.helpers.types import InquiryResult, SimEvidence + +log = logging.getLogger(__name__) @dataclass @@ -44,8 +49,8 @@ def get_current_likelihood(self) -> Optional[np.ndarray]: class StateManager(ABC): - def update(self, - evidence: np.ndarray): # TODO change evidence type to dictionary or some dataclass + # TODO change evidence type to dictionary or some dataclass + def update(self, evidence: Dict[str, SimEvidence]): raise NotImplementedError() def is_done(self) -> bool: @@ -84,14 +89,14 @@ def update(self, evidence) -> InquiryResult: current_series: List[InquiryResult] = self.state.series_results[self.state.series_n] prior_likelihood: Optional[np.ndarray] = current_series.pop( ).fused_likelihood if current_series else None # most recent likelihood - evidence_dict = {"SM": evidence} # TODO create wrapper object for Evidences - fused_likelihood = fuser.fuse(prior_likelihood, evidence_dict) + + fused_likelihood = fuser.fuse(prior_likelihood, evidence) # finding out whether max iterations is hit or prob threshold is hit temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, # TODO change to use evidence_dict - evidence_likelihoods=list(evidence), + evidences=evidence, fused_likelihood=fused_likelihood, decision=None) @@ -105,13 +110,18 @@ def update(self, evidence) -> InquiryResult: new_state = self.get_state().__dict__ new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - evidence_likelihoods=list(evidence), decision=decision, + evidences=evidence, decision=decision, fused_likelihood=fused_likelihood) + log.debug( + f"Fused Likelihoods | current typed - {self.state.current_sentence} | stimuli {self.state.display_alphabet} \n " + f"{histogram(fmt_fused_likelihoods_for_hist(new_inquiry_result.fused_likelihood, alphabet()))}") + new_state['series_results'][self.state.series_n].append(new_inquiry_result) if is_decidable: decision = alphabet()[ - np.argmax(evidence)] # deciding the maximum probability symbol TODO abstract + np.argmax( + fused_likelihood)] # deciding the maximum probability symbol TODO abstract # resetting series new_state['series_n'] += 1 @@ -119,10 +129,8 @@ def update(self, evidence) -> InquiryResult: new_state['inquiry_n'] = 0 # updating current sentence and finding next target - new_state['current_sentence'] = new_state['current_sentence'] + \ - decision if decision != BACKSPACE_CHAR else new_state[ - 'current_sentence'][ - :-1] + new_state['current_sentence'] = new_state['current_sentence'] + decision \ + if decision != BACKSPACE_CHAR else new_state['current_sentence'][:-1] new_state['target_symbol'] = next_target_letter(new_state['current_sentence'], self.state.target_sentence) @@ -131,7 +139,7 @@ def update(self, evidence) -> InquiryResult: new_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - evidence_likelihoods=list(evidence), decision=decision, + evidences=evidence, decision=decision, fused_likelihood=fused_likelihood) new_state['series_results'][self.state.series_n].append(new_inquiry_result) @@ -149,7 +157,7 @@ def mutate_state(self, state_field, state_value) -> SimState: state_dict[state_field] = state_value self.state = SimState(**state_dict) return self.get_state() - + raise FieldException(f"Cannot find state field {state_field}") @staticmethod @@ -159,10 +167,6 @@ def initial_state(parameters: Parameters = None) -> SimState: default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] init_stimuli = random.sample(alphabet(), 10) - # TODO make new parameter and create default series_likelihoods object based off that - evidence_types = parameters.get( - 'evidence_types') if parameters else None - return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, display_alphabet=init_stimuli, inquiry_n=0, series_n=0, series_results=[[]], decision_criterion=default_criterion) diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py index ff30a3dd4..f2f3b35b5 100644 --- a/bcipy/simulator/helpers/types.py +++ b/bcipy/simulator/helpers/types.py @@ -1,25 +1,23 @@ from dataclasses import dataclass -from typing import Optional, List +from typing import Optional, List, Dict import numpy as np from bcipy.task.data import EvidenceType +@dataclass +class SimEvidence: + evidence_type: EvidenceType + evidence: np.ndarray + symbol_set: List[str] + + @dataclass class InquiryResult: target: Optional[str] time_spent: int stimuli: List - # TODO make this into a dictionary to support multimodal. e.g - # {SignalModel: evidence_list, LanguageModel:evidence_list} - evidence_likelihoods: List + evidences: Dict[str, SimEvidence] fused_likelihood: np.ndarray decision: Optional[str] - - -@dataclass -class SimEvidence: - evidence_type: EvidenceType - evidence: np.ndarray - symbol_set: List[str] diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index ae7d06030..ab78f3da4 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -1,7 +1,7 @@ import logging import random from time import sleep -from typing import Optional +from typing import Optional, Dict import numpy as np @@ -9,12 +9,14 @@ from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine from bcipy.simulator.helpers.metrics import MetricReferee +from bcipy.simulator.helpers.rsvp_utils import format_lm_output from bcipy.simulator.helpers.sampler import Sampler from bcipy.simulator.helpers.state_manager import StateManager, SimState -from bcipy.simulator.helpers.types import InquiryResult +from bcipy.simulator.helpers.types import InquiryResult, SimEvidence from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods from bcipy.simulator.helpers.model_handler import ModelHandler from bcipy.simulator.simulator_base import Simulator +from bcipy.task.data import EvidenceType log = logging.getLogger(__name__) @@ -62,26 +64,28 @@ def run(self): log.info(f"SIM START with target word {self.state_manager.get_state().target_sentence}") while not self.state_manager.is_done(): + self.state_manager.mutate_state('display_alphabet', + self.__make_stimuli(self.state_manager.get_state())) curr_state = self.state_manager.get_state() + log.info( f"Series {curr_state.series_n} | Inquiry {curr_state.inquiry_n} | " + - f"Target {curr_state.target_symbol}") + f"Target '{curr_state.target_symbol}' | " + + f"Stimuli {curr_state.display_alphabet}") - self.state_manager.mutate_state('display_alphabet', self.__make_stimuli(curr_state)) - sampled_data = self.sampler.sample(curr_state) - # TODO make this evidence be a dict (mapping of evidence type to evidence) - evidence = self.model_handler.generate_evidence(curr_state, - sampled_data) + sampled_data = self.sampler.sample(self.state_manager.get_state()) + evidence: Dict[str, SimEvidence] = self.model_handler.generate_evidence(curr_state, + sampled_data) log.debug( - f"Evidence for stimuli {curr_state.display_alphabet} " + - f"\n {fmt_stim_likelihoods(evidence, self.symbol_set)}") + f"EEG Evidence for stimuli {curr_state.display_alphabet} " + + f"\n {fmt_stim_likelihoods(evidence['sm'].evidence, self.symbol_set)}") + + reshaped_evidence = self.__reshape_evidences(evidence) + log.debug(f"reshaped evidence {reshaped_evidence}") - inq_record: InquiryResult = self.state_manager.update(evidence) + inq_record: InquiryResult = self.state_manager.update(reshaped_evidence) updated_state = self.state_manager.get_state() - log.debug( - f"Fused Likelihoods + " - f"{fmt_stim_likelihoods(inq_record.fused_likelihood, self.symbol_set)}") if inq_record.decision: log.info(f"Decided {inq_record.decision} for target {inq_record.target}") @@ -105,9 +109,27 @@ def __make_stimuli(self, state: SimState): if val_func is not None: return stimuli.best_selection(self.symbol_set, list( val_func), subset_length, always_included=always_in_stimuli) + elif self.parameters.get('sim_lm_active', 0) == 1: # use lang model for priors to make stim + lm_model = self.model_handler.get_model('lm') + lm_model_evidence = lm_model.predict(list(state.current_sentence)) + val_func = format_lm_output(lm_model_evidence, self.symbol_set) + return stimuli.best_selection(self.symbol_set, list( + val_func), subset_length, always_included=always_in_stimuli) return random.sample(self.symbol_set, subset_length) + def __reshape_evidences(self, evidences: Dict[str, SimEvidence]) -> Dict[str, SimEvidence]: + + # reshaping lm_evidence to look like signal model evidence + reshaped_evidence = evidences.copy() + if "lm" in evidences: + unshaped_lm_evidence = evidences["lm"].evidence # [('B', 0.5), ('C', 0.2), ('_', 0.02)] + reshaped_lm_lik = format_lm_output(list(unshaped_lm_evidence), self.symbol_set) + reshaped_evidence['lm'] = SimEvidence(EvidenceType.LM, np.array(reshaped_lm_lik), + evidences["lm"].symbol_set) + + return reshaped_evidence + def load_parameters(self, path): # TODO validate parameters if not path: diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index b039898d5..4ffe57e5a 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -5,7 +5,8 @@ from bcipy.helpers.load import load_json_parameters from bcipy.simulator.helpers.data_engine import RawDataEngine from bcipy.simulator.helpers.metrics import MetricReferee, RefereeImpl, SimMetrics1Handler -from bcipy.simulator.helpers.model_handler import SignalModelHandler1, ModelHandler +from bcipy.simulator.helpers.model_handler import SignalModelHandler1, ModelHandler, \ + SigLmModelHandler1 from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler from bcipy.simulator.helpers.state_manager import StateManager, StateManagerImpl from bcipy.simulator.sim import SimulatorCopyPhrase @@ -21,11 +22,13 @@ def create(data_folders: List[str], smodel_files: List[str], model_file = Path(smodel_files.pop()) sim_parameters = load_json_parameters(sim_param_path, value_cast=True) + base_parameters = load_json_parameters(kwargs.get('parameters'), value_cast=True) data_engine = RawDataEngine(data_folders) state_manager: StateManager = StateManagerImpl(sim_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) - model_handler: ModelHandler = SignalModelHandler1(model_file) + model_handler: ModelHandler = SigLmModelHandler1(model_file, base_parameters) \ + if sim_parameters.get("sim_lm_active", 0) == 1 else SignalModelHandler1(model_file) referee: MetricReferee = RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()}) sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, state_manager, referee) diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index 2417a5b90..dd16d0066 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -22,7 +22,7 @@ "type": "str" }, "sim_sleep_time": { - "value": "0.25", + "value": "0", "section": "sim_config", "readableName": "Simulation Time Step ", "helpTip": "How long to sleep in between simulation time steps", @@ -32,5 +32,26 @@ "1" ], "type": "float" + }, + "sim_lm_active": { + "value": "0", + "section": "sim_config", + "readableName": "is lm active or off", + "helpTip": "", + "recommended_values": [ + "0", + "1" + ], + "type": "int" + }, + "sim_lm_parameters": { + "value": "", + "section": "sim_config", + "readableName": "Path to language model parameter file ", + "helpTip": "", + "recommended_values": [ + "/lm_parameters.json" + ], + "type": "str" } } \ No newline at end of file From ccd17548c791bb3d4ec94a3652e7187f923f34a2 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 24 Jan 2024 17:14:57 -0800 Subject: [PATCH 208/330] #186890663 ; bug fix for active/passive devices --- bcipy/acquisition/multimodal.py | 4 ++-- bcipy/acquisition/tests/test_client_manager.py | 13 +++++++++++++ 2 files changed, 15 insertions(+), 2 deletions(-) diff --git a/bcipy/acquisition/multimodal.py b/bcipy/acquisition/multimodal.py index 8249f0885..7a29405bb 100644 --- a/bcipy/acquisition/multimodal.py +++ b/bcipy/acquisition/multimodal.py @@ -89,8 +89,8 @@ def active_device_content_types(self) -> List[ContentType]: """Returns a list of ContentTypes provided by the active configured devices.""" return [ - content_type for content_type, spec in self._clients.items() - if spec.is_active + content_type for content_type, client in self._clients.items() + if client.device_spec.is_active ] @property diff --git a/bcipy/acquisition/tests/test_client_manager.py b/bcipy/acquisition/tests/test_client_manager.py index dc5ed8194..29ec64a2d 100644 --- a/bcipy/acquisition/tests/test_client_manager.py +++ b/bcipy/acquisition/tests/test_client_manager.py @@ -14,6 +14,7 @@ def setUp(self): self.eeg_device_mock.name = 'DSI-24' self.eeg_device_mock.content_type = 'EEG' self.eeg_device_mock.sample_rate = 300 + self.eeg_device_mock.is_active = True self.eeg_client_mock = Mock() self.eeg_client_mock.device_spec = self.eeg_device_mock @@ -24,6 +25,7 @@ def setUp(self): self.gaze_device_mock = Mock() self.gaze_device_mock.content_type = 'Eyetracker' self.gaze_device_mock.sample_rate = 60 + self.gaze_device_mock.is_active = False self.gaze_client_mock = Mock() self.gaze_client_mock.device_spec = self.gaze_device_mock @@ -80,6 +82,17 @@ def test_device_specs(self): self.assertEqual(2, len(manager.device_specs)) self.assertTrue(self.gaze_device_mock in manager.device_specs) + def test_device_content_types(self): + """Test properties related to content types""" + manager = ClientManager() + manager.add_client(self.eeg_client_mock) + manager.add_client(self.gaze_client_mock) + self.assertTrue(ContentType.EEG in manager.device_content_types) + self.assertTrue(ContentType.EYETRACKER in manager.device_content_types) + + self.assertEqual([ContentType.EEG], manager.active_device_content_types) + + def test_dispatching_properties(self): """Test that property calls may be dispatched to the default client""" manager = ClientManager() From 189029cbd142607712c3bd56855b6d637965a4fe Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 25 Jan 2024 09:28:25 -0800 Subject: [PATCH 209/330] Fixed linting --- bcipy/acquisition/tests/test_client_manager.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/bcipy/acquisition/tests/test_client_manager.py b/bcipy/acquisition/tests/test_client_manager.py index 29ec64a2d..425008698 100644 --- a/bcipy/acquisition/tests/test_client_manager.py +++ b/bcipy/acquisition/tests/test_client_manager.py @@ -90,8 +90,8 @@ def test_device_content_types(self): self.assertTrue(ContentType.EEG in manager.device_content_types) self.assertTrue(ContentType.EYETRACKER in manager.device_content_types) - self.assertEqual([ContentType.EEG], manager.active_device_content_types) - + self.assertEqual([ContentType.EEG], + manager.active_device_content_types) def test_dispatching_properties(self): """Test that property calls may be dispatched to the default client""" From 973386ea626b0c1b3f7ddfee480a9d5c0026efe8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 25 Jan 2024 14:02:03 -0800 Subject: [PATCH 210/330] Updated macos workflow --- .github/workflows/main.yml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index ca1c4b974..f0a2b5997 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -112,13 +112,14 @@ jobs: python-version: [3.8, 3.9] steps: - - uses: actions/checkout@v2 + - uses: actions/checkout@v4 - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v2 with: python-version: ${{ matrix.python-version }} - name: update pip & install custom dependencies run: | + brew install labstreaminglayer/tap/lsl python -m pip install --upgrade pip pip install kenlm==0.1 --global-option="--max_order=12" pip install psychopy==2023.2.1 --no-deps From 867c7d91acfacc30572f4118a26b62eef1c31700 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sat, 27 Jan 2024 19:14:05 -0500 Subject: [PATCH 211/330] singular data folder wrapper --- bcipy/simulator/__main__.py | 7 +-- bcipy/simulator/helpers/data_engine.py | 53 +++++++++++----- bcipy/simulator/helpers/model_handler.py | 1 - bcipy/simulator/helpers/sampler.py | 12 ++-- bcipy/simulator/sim.py | 19 +++--- bcipy/simulator/sim_factory.py | 10 +-- bcipy/simulator/tests/test_data_engine.py | 75 +++++++++++++++++++++++ 7 files changed, 133 insertions(+), 44 deletions(-) create mode 100644 bcipy/simulator/tests/test_data_engine.py diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 38c1bb9f2..826275c2b 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -10,11 +10,10 @@ parser = argparse.ArgumentParser() parser.add_argument( "-d", - "--data_folders", - action="append", + "--data_folder", type=Path, required=True, - help="Raw data folders to be processed. Repeatable arg to accumulate sessions data.") + help="Raw data folders to be processed. Singular wrapper dir with data folders") parser.add_argument( "-sm", "--smodel_files", @@ -27,7 +26,7 @@ "-p", "--parameters", type=Path, - required=False, # For now + required=True, help="Parameter File to be used") parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 1fe3869c7..6eebf9a15 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,4 +1,5 @@ import logging +import os from abc import ABC from pathlib import Path from typing import Optional, List @@ -36,11 +37,11 @@ class RawDataEngine(DataEngine): Object that loads in list of session data folders and transforms data into sample-able pd.df """ - def __init__(self, source_dirs: List[str]): + def __init__(self, source_dirs: List[str], parameters: Parameters): # TODO read parameters from source dirx # TODO use os.walk() and take in single source_dir that has all data folders self.source_dirs: List[str] = source_dirs - self.parameter_files: List[Parameters] = [] + self.parameters: Parameters = parameters self.data: Optional[List[ExtractedExperimentData]] = None self.trials_by_inquiry: List[ np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). @@ -48,6 +49,8 @@ def __init__(self, source_dirs: List[str]): self.labels_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) self.schema: Optional[pd.DataFrame] = None + # TODO validate parameters + self.load() def load(self) -> DataEngine: @@ -60,24 +63,17 @@ def load(self) -> DataEngine: """ log.debug(f"Loading data from {len(self.source_dirs)} source directories") - self.parameter_files = [ - load.load_json_parameters(str(Path(data_folder, DEFAULT_PARAMETER_FILENAME)), - value_cast=True) for - data_folder in + self.data: List[ExtractedExperimentData] = [ + process_raw_data_for_model(source_dir, self.parameters) for source_dir in self.source_dirs] - assert len(self.source_dirs) == len( - self.parameter_files) # TODO more general parameter validation function - - self.data = [process_raw_data_for_model(source_dir, parameter) for source_dir, parameter in - zip(self.source_dirs, self.parameter_files)] - - for data_source, parameter in zip(self.data, self.parameter_files): + for data_source in self.data: trigger_targetness, trigger_timing, trigger_symbols = data_source.decoded_triggers self.trials_by_inquiry.append( np.split(data_source.trials, data_source.inquiries.shape[1], 1)) self.symbols_by_inquiry.append([list(group) for group in - grouper(trigger_symbols, parameter.get('stim_length'), + grouper(trigger_symbols, + self.parameters.get('stim_length'), incomplete="ignore")]) self.labels_by_inquiry.append(data_source.labels) @@ -124,7 +120,32 @@ def transform(self) -> DataEngine: return self def get_data(self): - return self.schema.copy() if self.schema is not None else self.data + return self.schema.copy() if self.schema is not None else None def get_parameters(self): - return self.parameter_files + return self.parameters + + +class RawDataEngineWrapper(RawDataEngine): + """ + Data engine that assumes all data is stored within single data folder + - single data folder contains dataDir1, dataDir2, ... + - each data dir contains its raw_data and triggers + """ + + def __init__(self, source_dir: str, parameters: Parameters): + data_paths = self.get_data_dirs(source_dir) + super().__init__(data_paths, parameters) + + @staticmethod + def get_data_dirs(source_dir: str) -> [str]: + """ + Returns all the data dirs within the source dir + - e.g [dataDir1Path, dataDir2Path ... ] + """ + + assert source_dir + + directories: List[str] = [str(d) for d in Path(source_dir).iterdir() if d.is_dir()] + + return directories diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index baeb6ac9e..70aaf1ecf 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -21,7 +21,6 @@ class ModelHandler(ABC): @abstractmethod def generate_evidence(self, state: SimState, features): """ Run model on features to generate evidence """ - breakpoint() @abstractmethod def get_model(self, key=None): diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index c748536bd..c9eb8a61e 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -27,12 +27,12 @@ def set_reshaper(self, reshaper: Callable): class EEGByLetterSampler(Sampler): - def __init__(self, data_engine: RawDataEngine, params: List[Parameters] = None): + def __init__(self, data_engine: RawDataEngine, parameters: Parameters = None): self.data_engine: RawDataEngine = data_engine - self.parameter_files: List[ - Parameters] = params if params else self.data_engine.parameter_files + self.parameters: Parameters = self.data_engine.parameters if not parameters else parameters self.model_input_reshaper: Callable = self.__default_reshaper - self.alphabet: List[str] = params[0].get('symbol_set') if params else alphabet() + self.alphabet: List[str] = self.parameters.get( + 'symbol_set') if self.parameters else alphabet() self.data: pd.DataFrame = self.data_engine.transform().get_data() def sample(self, state: SimState) -> np.ndarray: @@ -76,7 +76,5 @@ def __default_reshaper(self, eeg_responses: List[np.ndarray]) -> np.ndarray: for c_i, channel_eeg in enumerate(trial_channels_eeg): channels_eeg[c_i].append(channel_eeg) - # TODO make sure this returns (7, 10, 90) + # make sure this returns (7, 10, 90) for tab_test_dynamic return np.array(channels_eeg) - -# TODO ReplaySampler diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index ab78f3da4..3ad8f1cc9 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -6,6 +6,7 @@ import numpy as np from bcipy.helpers import load, stimuli, symbols +from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine from bcipy.simulator.helpers.metrics import MetricReferee @@ -44,7 +45,7 @@ class SimulatorCopyPhrase(Simulator): """ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler: Sampler, - state_manager: StateManager, referee: MetricReferee, parameter_path: str = None, + state_manager: StateManager, referee: MetricReferee, parameters: Parameters = None, save_dir: str = None): super().__init__() @@ -55,7 +56,7 @@ def __init__(self, data_engine: DataEngine, model_handler: ModelHandler, sampler self.state_manager: StateManager = state_manager self.data_engine: DataEngine = data_engine - self.parameters = self.load_parameters(parameter_path) + self.parameters: Parameters = self.load_parameters(parameters) self.symbol_set = alphabet() self.write_output = False @@ -130,18 +131,12 @@ def __reshape_evidences(self, evidences: Dict[str, SimEvidence]) -> Dict[str, Si return reshaped_evidence - def load_parameters(self, path): + def load_parameters(self, params: Optional[Parameters]): # TODO validate parameters - if not path: - # TODO fix this parameter logic. for now assuming one parameter file speaks for all - parameters = self.data_engine.get_parameters()[0] + if params: + return params else: - parameters = load.load_json_parameters(path, value_cast=True) - - sim_parameters = load.load_json_parameters( - "bcipy/simulator/sim_parameters.json", value_cast=True) - parameters.add_missing_items(sim_parameters) - return parameters + return self.data_engine.get_parameters() def get_param(self, name): pass diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 4ffe57e5a..4c26cd0a6 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -3,7 +3,7 @@ from typing import List from bcipy.helpers.load import load_json_parameters -from bcipy.simulator.helpers.data_engine import RawDataEngine +from bcipy.simulator.helpers.data_engine import RawDataEngine, RawDataEngineWrapper from bcipy.simulator.helpers.metrics import MetricReferee, RefereeImpl, SimMetrics1Handler from bcipy.simulator.helpers.model_handler import SignalModelHandler1, ModelHandler, \ SigLmModelHandler1 @@ -16,21 +16,23 @@ class SimulationFactoryV2: """ Factory class to create Simulator instances """ @staticmethod - def create(data_folders: List[str], smodel_files: List[str], + def create(data_folder: str, smodel_files: List[str], sim_param_path="bcipy/simulator/sim_parameters.json", **kwargs): # out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) model_file = Path(smodel_files.pop()) sim_parameters = load_json_parameters(sim_param_path, value_cast=True) base_parameters = load_json_parameters(kwargs.get('parameters'), value_cast=True) + base_parameters.add_missing_items(sim_parameters) - data_engine = RawDataEngine(data_folders) + data_engine = RawDataEngineWrapper(data_folder, base_parameters) state_manager: StateManager = StateManagerImpl(sim_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) model_handler: ModelHandler = SigLmModelHandler1(model_file, base_parameters) \ if sim_parameters.get("sim_lm_active", 0) == 1 else SignalModelHandler1(model_file) referee: MetricReferee = RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()}) - sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, state_manager, referee) + sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, state_manager, referee, + parameters=base_parameters) return sim diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py new file mode 100644 index 000000000..f175f4029 --- /dev/null +++ b/bcipy/simulator/tests/test_data_engine.py @@ -0,0 +1,75 @@ +import unittest +from pathlib import Path + +import numpy as np +import pandas as pd + +from bcipy.helpers import load +from bcipy.simulator.helpers.data_engine import DataEngine, RawDataEngine, RawDataEngineWrapper + + +# Import the module or class you want to test + + +class TestRawDataEngine(unittest.TestCase): + + @classmethod + def check_eeg_shape(cls, schema: pd.DataFrame): + # checking all eeg response data has same shape + + eeg_responses = schema['eeg'] + ret = True + ret = ret and (None in eeg_responses or np.NaN in eeg_responses) + shape_set = set(eeg_responses.apply(lambda x: x.shape)) + ret = ret and (len(shape_set) == 1) + + return ret + + def test_one_source(self): + # Test the function with a specific input and assert the expected output + + data_paths = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700"] + param_path = "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/parameters.json" + params = load.load_json_parameters(str(Path(param_path)), value_cast=True) + + data_engine = RawDataEngine(data_paths, params) + self.assertFalse(data_engine.get_data()) + + data_engine.transform() + self.assertTrue(len(data_engine.schema)) + + self.assertTrue(self.check_eeg_shape(data_engine.get_data())) + + def test_two_sources(self): + # Test the function with a specific input and assert the expected output + + data_paths = ["/Users/srikarananthoju/cambi/tab_test_dynamic/16sec_-0700", + "/Users/srikarananthoju/cambi/tab_test_dynamic/50sec_-0700"] + param_path = "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/parameters.json" + params = load.load_json_parameters(str(Path(param_path)), value_cast=True) + + data_engine = RawDataEngine(data_paths, params) + self.assertFalse(data_engine.get_data()) + + data_engine.transform() + self.assertTrue(len(data_engine.get_data())) + + # asserting all eeg response data has same shape + self.assertTrue(self.check_eeg_shape(data_engine.get_data())) + + def test_RawDataEngineWrapper(self): + source_dir = "/Users/srikarananthoju/cambi/tab_test_dynamic/wrapper" + param_path = "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/parameters.json" + params = load.load_json_parameters(str(Path(param_path)), value_cast=True) + + data_engine = RawDataEngineWrapper(source_dir, params) + self.assertEqual(len(data_engine.source_dirs), 2) + + data_engine.transform() + self.assertTrue(len(data_engine.get_data())) + + self.assertTrue(self.check_eeg_shape(data_engine.get_data())) + + +if __name__ == '__main__': + unittest.main() From 9d7f3a6936880e5a4935f3695edf6d0f1a38be76 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 28 Jan 2024 19:09:51 -0500 Subject: [PATCH 212/330] supporting trial_length param for data processing --- bcipy/simulator/helpers/signal_helpers.py | 11 ++++++++++- bcipy/simulator/tests/test_data_engine.py | 15 +++++++++++++-- 2 files changed, 23 insertions(+), 3 deletions(-) diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index d7c1735ab..550b6f7e5 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -12,6 +12,7 @@ DEFAULT_DEVICE_SPEC_FILENAME, ) from bcipy.helpers.acquisition import analysis_channels +from bcipy.helpers.exceptions import TaskConfigurationException from bcipy.helpers.load import load_raw_data from bcipy.helpers.stimuli import update_inquiry_timing, InquiryReshaper from bcipy.helpers.triggers import TriggerType, trigger_decoder @@ -37,8 +38,16 @@ def process_raw_data_for_model(data_folder, parameters, log.debug(f"Processing raw data for {data_folder}") # extract relevant session information from parameters file trial_window = parameters.get("trial_window") - window_length = trial_window[1] - trial_window[0] + if trial_window is None: + # using trial_length instead and converting to trial window + trial_length = parameters.get('trial_length') + if not trial_length: + raise TaskConfigurationException( + "Could not find trial_window or trial_length in parameters") + + trial_window = tuple([0, trial_length]) # trial_length=0.5 -> trial_window=(0,0.5) + window_length = trial_window[1] - trial_window[0] prestim_length = parameters.get("prestim_length") trials_per_inquiry = parameters.get("stim_length") # The task buffer length defines the min time between two inquiries diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py index f175f4029..a0cf4dfd8 100644 --- a/bcipy/simulator/tests/test_data_engine.py +++ b/bcipy/simulator/tests/test_data_engine.py @@ -12,14 +12,13 @@ class TestRawDataEngine(unittest.TestCase): - @classmethod def check_eeg_shape(cls, schema: pd.DataFrame): # checking all eeg response data has same shape eeg_responses = schema['eeg'] ret = True - ret = ret and (None in eeg_responses or np.NaN in eeg_responses) + ret = ret and not (None in eeg_responses or np.NaN in eeg_responses) shape_set = set(eeg_responses.apply(lambda x: x.shape)) ret = ret and (len(shape_set) == 1) @@ -70,6 +69,18 @@ def test_RawDataEngineWrapper(self): self.assertTrue(self.check_eeg_shape(data_engine.get_data())) + def test_matrix_single(self): + source_dir = "/Users/srikarananthoju/cambi/data/matrixTestWrapper" + param_path = "/Users/srikarananthoju/cambi/data/matrixTestWrapper/S007_Matrix_Calibration_Thu_20_Jul_2023_09hr48min56sec_-0400/parameters.json" + params = load.load_json_parameters(str(Path(param_path)), value_cast=True) + + data_engine = RawDataEngineWrapper(source_dir, params) + data_engine.transform() + + self.assertTrue(len(data_engine.get_data())) + + self.assertTrue(self.check_eeg_shape(data_engine.get_data())) + if __name__ == '__main__': unittest.main() From 6cc0c51fac10751acc9506fab2db623a0a2573a9 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 28 Jan 2024 19:37:16 -0500 Subject: [PATCH 213/330] adding resource file to data_engine test --- .gitignore | 1 + bcipy/simulator/tests/test_data_engine.py | 20 ++++++++++++++++++-- 2 files changed, 19 insertions(+), 2 deletions(-) diff --git a/.gitignore b/.gitignore index 48f9a773f..1397d7e61 100644 --- a/.gitignore +++ b/.gitignore @@ -36,3 +36,4 @@ bcipy/language/lms/out_* bcipy/language/out/ +bcipy/simulator/tests/resource/ diff --git a/bcipy/simulator/tests/test_data_engine.py b/bcipy/simulator/tests/test_data_engine.py index a0cf4dfd8..e9e01af8d 100644 --- a/bcipy/simulator/tests/test_data_engine.py +++ b/bcipy/simulator/tests/test_data_engine.py @@ -1,4 +1,6 @@ +import shutil import unittest +import zipfile from pathlib import Path import numpy as np @@ -7,11 +9,22 @@ from bcipy.helpers import load from bcipy.simulator.helpers.data_engine import DataEngine, RawDataEngine, RawDataEngineWrapper - # Import the module or class you want to test +FILE_PATH_PREFIX = "bcipy/simulator/tests" + class TestRawDataEngine(unittest.TestCase): + + @classmethod + def setUp(cls) -> None: + with zipfile.ZipFile(f'{FILE_PATH_PREFIX}/resource/rsvpTest1.zip', 'r') as zip_ref: + zip_ref.extractall(f'{FILE_PATH_PREFIX}/resource/rsvpTest1') + + @classmethod + def tearDown(cls) -> None: + shutil.rmtree(f'{FILE_PATH_PREFIX}/resource/rsvpTest1') + @classmethod def check_eeg_shape(cls, schema: pd.DataFrame): # checking all eeg response data has same shape @@ -57,7 +70,10 @@ def test_two_sources(self): self.assertTrue(self.check_eeg_shape(data_engine.get_data())) def test_RawDataEngineWrapper(self): - source_dir = "/Users/srikarananthoju/cambi/tab_test_dynamic/wrapper" + # Testing loading and transformaing data from a singular wrapper folder + + # source_dir = "/Users/srikarananthoju/cambi/tab_test_dynamic/wrapper" + source_dir = FILE_PATH_PREFIX + "/resource/rsvpTest1/wrapper" param_path = "/Users/srikarananthoju/cambi/tab_test_dynamic/calibr_37sec_-0700/parameters.json" params = load.load_json_parameters(str(Path(param_path)), value_cast=True) From 1754215e0dfe44ca70f829b6f048626236f42097 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 31 Jan 2024 17:25:18 -0800 Subject: [PATCH 214/330] #186539584 ; modified matrix display tasks to always show the grid --- .../demo/matrix/demo_calibration_matrix.py | 43 ++++++------------- .../demo/matrix/demo_copyphrase_matrix.py | 6 +-- bcipy/display/paradigm/matrix/display.py | 9 +++- .../paradigm/matrix/test_matrix_display.py | 1 + 4 files changed, 25 insertions(+), 34 deletions(-) diff --git a/bcipy/display/demo/matrix/demo_calibration_matrix.py b/bcipy/display/demo/matrix/demo_calibration_matrix.py index 0ffa90234..2e1cbf3ce 100644 --- a/bcipy/display/demo/matrix/demo_calibration_matrix.py +++ b/bcipy/display/demo/matrix/demo_calibration_matrix.py @@ -40,37 +40,22 @@ task_bar=task_bar, info=info) -time_target = 2 -time_fixation = 2 +time_target = 1 +time_fixation = 0.5 time_flash = 0.25 timing = [time_target] + [time_fixation] + [time_flash] * 5 colors = ['green', 'lightgray'] + ['white'] * 5 task_buffer = 2 -matrix_display.schedule_to(stimuli=['A', '+', 'F', '<', 'A', 'B', 'C'], - timing=timing, - colors=colors) -matrix_display.update_task_bar() -matrix_display.do_inquiry() -core.wait(task_buffer) - -matrix_display.schedule_to(stimuli=['B', '+', 'F', '<', 'A', 'B', 'C'], - timing=timing, - colors=colors) -matrix_display.update_task_bar() -matrix_display.do_inquiry() -core.wait(task_buffer) - -matrix_display.schedule_to(stimuli=['C', '+', 'F', '<', 'A', 'B', 'C'], - timing=timing, - colors=colors) -matrix_display.update_task_bar() -matrix_display.do_inquiry() -core.wait(task_buffer) - -matrix_display.schedule_to(stimuli=['<', '+', 'F', '<', 'A', 'B', 'C'], - timing=timing, - colors=colors) -matrix_display.update_task_bar() -matrix_display.do_inquiry() -core.wait(task_buffer) +inquiries = [ + ['A', '+', 'F', '<', 'A', 'B', 'C'], + ['B', '+', 'F', '<', 'A', 'B', 'C'], + ['C', '+', 'F', '<', 'A', 'B', 'C'], + ['<', '+', 'F', '<', 'A', 'B', 'C'] +] + +for inquiry in inquiries: + matrix_display.schedule_to(stimuli=inquiry, timing=timing, colors=colors) + matrix_display.update_task_bar() + matrix_display.do_inquiry() + core.wait(task_buffer) diff --git a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py index 866b73076..70fd4b92c 100644 --- a/bcipy/display/demo/matrix/demo_copyphrase_matrix.py +++ b/bcipy/display/demo/matrix/demo_copyphrase_matrix.py @@ -10,7 +10,7 @@ from bcipy.display.components.task_bar import CopyPhraseTaskBar from bcipy.display.paradigm.matrix.display import MatrixDisplay -font = "Overpass Mono Medium" +font = "Overpass Mono" info = InformationProperties( info_color=['White'], info_pos=[(-.5, -.75)], @@ -82,9 +82,9 @@ counter = 0 -for idx_o in range(len(spelled_text)): +for spelled in spelled_text: - display.update_task_bar(text=spelled_text[idx_o]) + display.update_task_bar(text=spelled) display.draw_static() win.flip() diff --git a/bcipy/display/paradigm/matrix/display.py b/bcipy/display/paradigm/matrix/display.py index 229de7e97..8fb0cd2a8 100644 --- a/bcipy/display/paradigm/matrix/display.py +++ b/bcipy/display/paradigm/matrix/display.py @@ -137,7 +137,7 @@ def capture_grid_screenshot(self, file_path: str) -> None: self.draw_grid(opacity=self.full_grid_opacity) tmp_task_bar = self.task_bar.current_index self.task_bar.current_index = 0 - self.draw_static() + self.draw_components() self.window.flip() # capture the screenshot and save it to the specified file path @@ -273,7 +273,7 @@ def draw(self, color=grid_color or self.grid_color, highlight=highlight, highlight_color=highlight_color) - self.draw_static() + self.draw_components() self.window.flip() if duration: core.wait(duration) @@ -342,6 +342,11 @@ def wait_screen(self, message: str, message_color: str) -> None: def draw_static(self) -> None: """Draw static elements in a stimulus.""" + self.draw_grid(self.start_opacity) + self.draw_components() + + def draw_components(self) -> None: + """Draw task bar and info text components.""" if self.task_bar: self.task_bar.draw() diff --git a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py index a8285517a..ca2579452 100644 --- a/bcipy/display/tests/paradigm/matrix/test_matrix_display.py +++ b/bcipy/display/tests/paradigm/matrix/test_matrix_display.py @@ -163,6 +163,7 @@ def test_animate_scp(self): when(self.matrix.window).callOnFlip(any(), any()).thenReturn() # mock the drawing of text stims when(self.matrix).draw_static().thenReturn() + when(self.matrix).draw_components().thenReturn() when(self.text_stim_mock).draw().thenReturn() when(self.matrix.window).flip().thenReturn() # skip the core wait From e91f1ff415bdb5432c0cde61eb19216f91997793 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 4 Feb 2024 19:01:12 -0500 Subject: [PATCH 215/330] backspace prob included in lm evidence --- bcipy/simulator/helpers/model_handler.py | 11 ++++++++--- bcipy/simulator/sim_parameters.json | 2 +- 2 files changed, 9 insertions(+), 4 deletions(-) diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index 70aaf1ecf..db5a89591 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -5,8 +5,8 @@ import numpy as np -from bcipy.helpers.language_model import init_language_model, histogram -from bcipy.helpers.symbols import alphabet +from bcipy.helpers.language_model import init_language_model, histogram, with_min_prob +from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR from bcipy.language import LanguageModel from bcipy.signal.model import SignalModel from bcipy.simulator.helpers.state_manager import SimState @@ -59,6 +59,7 @@ def __init__(self, sm_model_file, parameters): self.signal_model: Optional[SignalModel] = None self.lm_model: LanguageModel = init_language_model(parameters) self.alp = alphabet() + self.backspace_prob: float = 0.05 with open(self.sm_model_file, "rb") as signal_file: self.signal_model = pickle.load(signal_file) @@ -68,10 +69,14 @@ def generate_evidence(self, state: SimState, eeg_responses): eeg_evidence = self.signal_model.predict(eeg_responses, stimuli, self.alp) lm_evidence = self.lm_model.predict( list(state.current_sentence)) if state.inquiry_n == 0 else None - # TODO check lm_parameters for default backspace prob ret_evidence = {} if lm_evidence is not None: + + # adjusting evidence to include backspace prob + if BACKSPACE_CHAR in stimuli: + lm_evidence = with_min_prob(lm_evidence, (BACKSPACE_CHAR, self.backspace_prob)) + ret_evidence['lm'] = SimEvidence(EvidenceType.LM, np.array(lm_evidence), self.alp) log.debug(f"LM evidence for '{state.current_sentence}' -> \n {histogram(lm_evidence)}") diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index dd16d0066..7c369ccff 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -34,7 +34,7 @@ "type": "float" }, "sim_lm_active": { - "value": "0", + "value": "1", "section": "sim_config", "readableName": "is lm active or off", "helpTip": "", From ee7bb01a1a2dfa99449552acb38701b158894ab8 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 4 Feb 2024 19:28:00 -0500 Subject: [PATCH 216/330] total_time_spent estimate --- bcipy/simulator/helpers/metrics.py | 37 ++++++++++++++++++----------- bcipy/simulator/sim.py | 4 ++-- bcipy/simulator/sim_parameters.json | 2 +- bcipy/simulator/simulator_base.py | 6 +++-- 4 files changed, 30 insertions(+), 19 deletions(-) diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py index 35fcb4075..8bed0d69b 100644 --- a/bcipy/simulator/helpers/metrics.py +++ b/bcipy/simulator/helpers/metrics.py @@ -5,6 +5,7 @@ import numpy as np +from bcipy.helpers.acquisition import max_inquiry_duration from bcipy.simulator.helpers.state_manager import SimState from bcipy.simulator.helpers.types import InquiryResult from bcipy.simulator.simulator_base import Simulator @@ -31,22 +32,31 @@ class SimMetrics1Handler(RefereeHandler): def handle(self, sim: Simulator) -> Dict[str, Any]: state: SimState = getattr(sim, ("state_manager")).get_state() - info: Dict = SimMetrics1().__dict__ - info['total_inquiries'] = state.total_inquiry_count() - info['total_series'] = state.series_n - + # calculating total decisions made flattened_inquiries: List[InquiryResult] = reduce(lambda l1, l2: l1 + l2, state.series_results, []) - info['total_decisions'] = len( - list(filter(lambda inq: bool(inq.decision), flattened_inquiries))) + total_decisions = len(list(filter(lambda inq: bool(inq.decision), flattened_inquiries))) + # average number of inqs before a decision inq_counts = [] for series in state.series_results: if [inq for inq in series if inq.decision]: inq_counts.append(len(series)) - info['inquiries_per_selection'] = round(np.array(inq_counts).mean(), 3) + inquiries_per_selection = round(np.array(inq_counts).mean(), 3) + + # inq and series counts + total_inquiries = state.total_inquiry_count() + total_series = state.series_n + + # total time spent estimate seconds = (max_inq_time_estimate * total_inquiries) + parameters = sim.get_parameters() + max_inq_time = max_inquiry_duration(parameters) + total_time_spent = total_inquiries * max_inq_time - return info + ret = SimMetrics1(total_series=total_series, total_inquiries=total_inquiries, + total_decisions=total_decisions, total_time_spent=total_time_spent, + inquiries_per_selection=inquiries_per_selection) + return ret.__dict__ class MetricReferee(ABC): @@ -62,19 +72,18 @@ def visualize(self, sim: Simulator): """ Generate registered visualizations for sim """ @abstractmethod - def set_metric_handler(self, name: str, handler: RefereeHandler): + def add_metric_handler(self, name: str, handler: RefereeHandler): """ Add a metric calculation that will be executed upon self.score() """ @abstractmethod - def set_viz_handler(self, name: str, handler: RefereeHandler): + def add_viz_handler(self, name: str, handler: RefereeHandler): """ Register a visualization that will be executed upon self.visualize() """ class RefereeImpl(MetricReferee): def __init__(self, metric_handlers=None, viz_handlers=None): - self.metric_handlers: Dict[ - str, RefereeHandler] = metric_handlers if metric_handlers else {} + self.metric_handlers: Dict[str, RefereeHandler] = metric_handlers if metric_handlers else {} self.viz_handlers: Dict[str, RefereeHandler] = viz_handlers if viz_handlers else {} self.inquiry_time: float = 1 # 1 inq -> 1 second @@ -96,8 +105,8 @@ def visualize(self, sim: Simulator): for handler_name, viz_handler in self.viz_handlers.items(): viz_handler.handle(sim) - def set_metric_handler(self, name: str, handler: RefereeHandler): + def add_metric_handler(self, name: str, handler: RefereeHandler): self.metric_handlers[name] = handler - def set_viz_handler(self, name: str, handler: RefereeHandler): + def add_viz_handler(self, name: str, handler: RefereeHandler): self.viz_handlers[name] = handler diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 3ad8f1cc9..8170f2035 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -138,5 +138,5 @@ def load_parameters(self, params: Optional[Parameters]): else: return self.data_engine.get_parameters() - def get_param(self, name): - pass + def get_parameters(self): + return self.parameters.copy() diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index 7c369ccff..dd16d0066 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -34,7 +34,7 @@ "type": "float" }, "sim_lm_active": { - "value": "1", + "value": "0", "section": "sim_config", "readableName": "is lm active or off", "helpTip": "", diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py index 79eaae114..83db6dbf1 100644 --- a/bcipy/simulator/simulator_base.py +++ b/bcipy/simulator/simulator_base.py @@ -2,6 +2,8 @@ from abc import ABC, abstractmethod +from bcipy.helpers.parameters import Parameters + class Simulator(ABC): """Simulator. @@ -17,5 +19,5 @@ def run(self): """ Run loop for simulation""" @abstractmethod - def get_param(self, name): - """ retrieving parameter """ + def get_parameters(self) -> Parameters: + """ retrieving parameters copy""" From 95c16fd3a5789e57bc2da2721a889a3d1b7fad0c Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 4 Feb 2024 20:11:15 -0500 Subject: [PATCH 217/330] refactor logging configuration --- bcipy/simulator/__init__.py | 31 ------------------------------- bcipy/simulator/__main__.py | 36 ++++++++++++++++++++++++++++++++++++ 2 files changed, 36 insertions(+), 31 deletions(-) diff --git a/bcipy/simulator/__init__.py b/bcipy/simulator/__init__.py index 27ca39387..b3cc41c2d 100644 --- a/bcipy/simulator/__init__.py +++ b/bcipy/simulator/__init__.py @@ -1,32 +1 @@ """ Simulator package. View README """ - -import datetime -import logging -import sys - -log = logging.getLogger(__name__) -log.setLevel(logging.DEBUG) -# Create handlers for logging to the standard output and a file -stdoutHandler = logging.StreamHandler(stream=sys.stdout) -fileHandler = logging.FileHandler(f"bcipy/simulator/sim_output_{datetime.datetime.now()}.log") - -# Set the log levels on the handlers -stdoutHandler.setLevel(logging.INFO) -fileHandler.setLevel(logging.DEBUG) - -# Create a log format using Log Record attributes -fmt_file = logging.Formatter( - "%(levelname)s | %(filename)s:%(lineno)s >> %(message)s" -) - -fmt = logging.Formatter( - "%(levelname)s >> %(message)s" -) - -# Set the log format on each handler -stdoutHandler.setFormatter(fmt) -fileHandler.setFormatter(fmt_file) - -# Add each handler to the Logger object -log.addHandler(stdoutHandler) -log.addHandler(fileHandler) diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 826275c2b..488528de5 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -1,11 +1,44 @@ """ Entry point to run Simulator """ import argparse +import datetime +import logging +import sys from pathlib import Path from bcipy.simulator.sim_factory import SimulationFactoryV2 from bcipy.simulator.simulator_base import Simulator + +def configure_logger(): + """ configures logger for standard out nad file output """ + + log = logging.getLogger(None) # configuring root logger + log.setLevel(logging.DEBUG) + # Create handlers for logging to the standard output and a file + stdoutHandler = logging.StreamHandler(stream=sys.stdout) + file_name = datetime.datetime.now().strftime("%m-%d-%H:%M") + output_path = "bcipy/simulator/generated" + fileHandler = logging.FileHandler(f"{output_path}/{file_name}.log") + + # Set the log levels on the handlers + stdoutHandler.setLevel(logging.INFO) + fileHandler.setLevel(logging.DEBUG) + + # Create a log format using Log Record attributes + fmt_file = logging.Formatter("%(levelname)s | %(filename)s >> %(message)s") + + fmt = logging.Formatter("%(message)s") + + # Set the log format on each handler + stdoutHandler.setFormatter(fmt) + fileHandler.setFormatter(fmt_file) + + # Add each handler to the Logger object + log.addHandler(stdoutHandler) + log.addHandler(fileHandler) + + if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( @@ -33,6 +66,9 @@ args = vars(parser.parse_args()) + # setting up logging + configure_logger() + simulator: Simulator = SimulationFactoryV2.create(**args) simulator.run() From 06716279f82a6765103403948be1781c448760a2 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Sun, 4 Feb 2024 20:55:25 -0500 Subject: [PATCH 218/330] minor log clean --- bcipy/simulator/helpers/log_utils.py | 18 ++++++++++++++++-- bcipy/simulator/helpers/state_manager.py | 4 ++-- bcipy/simulator/sim.py | 8 +++++--- 3 files changed, 23 insertions(+), 7 deletions(-) diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 881b38d45..0e43c2fbb 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -1,7 +1,9 @@ -from typing import List +from typing import List, Dict import pandas as pd +from bcipy.simulator.helpers.types import SimEvidence + def fmt_stim_likelihoods(likelihoods, alp): rounded = [round(lik, 3) for lik in likelihoods] @@ -9,7 +11,7 @@ def fmt_stim_likelihoods(likelihoods, alp): return formatted -def fmt_fused_likelihoods_for_hist(likelihoods, alp): +def fmt_likelihoods_for_hist(likelihoods, alp): rounded = [round(lik, 3) for lik in likelihoods] formatted = [(a, l) for a, l in zip(alp, rounded)] return formatted @@ -22,3 +24,15 @@ def format_sample_rows(sample_rows: List[pd.DataFrame]): formatted_rows.append(new_row.to_string(index=False, header=True)) return ", ".join(formatted_rows) + + +def fmt_reshaped_evidence(evidences: Dict[str, SimEvidence]): + """ Formats evidences to log shapes pf ndarrays """ + + evidence_shape_strs = [] + + for evidence_name, evidence in evidences.items(): + evidence_shape = evidence.evidence.shape if evidence is not None else None + evidence_shape_strs.append(f"{evidence.evidence_type} => {evidence_shape}") + + return ", ".join(evidence_shape_strs) diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 622784862..3ccd63cda 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -13,7 +13,7 @@ from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR from bcipy.simulator.helpers.decision import SimDecisionCriteria, MaxIterationsSim, ProbThresholdSim from bcipy.simulator.helpers.evidence_fuser import MultiplyFuser, EvidenceFuser -from bcipy.simulator.helpers.log_utils import fmt_fused_likelihoods_for_hist +from bcipy.simulator.helpers.log_utils import fmt_likelihoods_for_hist from bcipy.simulator.helpers.rsvp_utils import next_target_letter from bcipy.simulator.helpers.types import InquiryResult, SimEvidence @@ -115,7 +115,7 @@ def update(self, evidence) -> InquiryResult: log.debug( f"Fused Likelihoods | current typed - {self.state.current_sentence} | stimuli {self.state.display_alphabet} \n " - f"{histogram(fmt_fused_likelihoods_for_hist(new_inquiry_result.fused_likelihood, alphabet()))}") + f"{histogram(fmt_likelihoods_for_hist(new_inquiry_result.fused_likelihood, alphabet()))}") new_state['series_results'][self.state.series_n].append(new_inquiry_result) if is_decidable: diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 8170f2035..d10c8d77f 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -6,6 +6,7 @@ import numpy as np from bcipy.helpers import load, stimuli, symbols +from bcipy.helpers.language_model import histogram from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine @@ -14,7 +15,8 @@ from bcipy.simulator.helpers.sampler import Sampler from bcipy.simulator.helpers.state_manager import StateManager, SimState from bcipy.simulator.helpers.types import InquiryResult, SimEvidence -from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods +from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods, fmt_reshaped_evidence, \ + fmt_likelihoods_for_hist from bcipy.simulator.helpers.model_handler import ModelHandler from bcipy.simulator.simulator_base import Simulator from bcipy.task.data import EvidenceType @@ -82,8 +84,8 @@ def run(self): f"EEG Evidence for stimuli {curr_state.display_alphabet} " + f"\n {fmt_stim_likelihoods(evidence['sm'].evidence, self.symbol_set)}") - reshaped_evidence = self.__reshape_evidences(evidence) - log.debug(f"reshaped evidence {reshaped_evidence}") + reshaped_evidence: Dict[str, SimEvidence] = self.__reshape_evidences(evidence) + log.debug(f"Evidence Shapes {fmt_reshaped_evidence(reshaped_evidence)}") inq_record: InquiryResult = self.state_manager.update(reshaped_evidence) updated_state = self.state_manager.get_state() From 77ab10725b9e9075502f017b08982152b5a33c7b Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 5 Feb 2024 13:55:57 -0800 Subject: [PATCH 219/330] Fixed merge error --- bcipy/simulator/helpers/log_utils.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 81181783c..e1877116d 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -3,6 +3,11 @@ import pandas as pd +def fmt_stim_likelihoods(likelihoods, alp): + rounded = [round(lik, 3) for lik in likelihoods] + formatted = [f"{a} : {l}" for a, l in zip(alp, rounded)] + return formatted + def fmt_fused_likelihoods_for_hist(likelihoods, alp): rounded = [round(lik, 3) for lik in likelihoods] formatted = [(a, l) for a, l in zip(alp, rounded)] From a4b39a1ccff053d26bf725ea1bfa01915ec69cad Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 5 Feb 2024 19:13:06 -0500 Subject: [PATCH 220/330] result output artifact --- bcipy/simulator/__main__.py | 1 + bcipy/simulator/helpers/decision.py | 3 +++ bcipy/simulator/helpers/state_manager.py | 10 ++++++++++ bcipy/simulator/helpers/types.py | 17 +++++++++++++++++ bcipy/simulator/sim.py | 19 ++++++++++++++++++- 5 files changed, 49 insertions(+), 1 deletion(-) diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 488528de5..85e9dd86c 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -6,6 +6,7 @@ import sys from pathlib import Path +from bcipy.simulator.helpers.decision import MaxIterationsSim from bcipy.simulator.sim_factory import SimulationFactoryV2 from bcipy.simulator.simulator_base import Simulator diff --git a/bcipy/simulator/helpers/decision.py b/bcipy/simulator/helpers/decision.py index 796c10861..cc27bc31e 100644 --- a/bcipy/simulator/helpers/decision.py +++ b/bcipy/simulator/helpers/decision.py @@ -38,6 +38,9 @@ def decide(self, series: List[InquiryResult]): """ raise NotImplementedError() + def __str__(self): + return type(self).__name__ + class MinIterations(SimDecisionCriteria): """ Returns true if the minimum number of iterations have not yet diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 3ccd63cda..288057e77 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -1,4 +1,5 @@ import copy +import dataclasses import logging import random from abc import ABC @@ -46,6 +47,15 @@ def get_current_likelihood(self) -> Optional[np.ndarray]: return cur_likelihood + def to_json(self): + d = dataclasses.asdict(self) + d['series_results'] = [list(map(lambda ir: ir.to_json(), lis)) for lis in + self.series_results] + + d['decision_criterion'] = [str(dec) for dec in self.decision_criterion] + + return d + class StateManager(ABC): diff --git a/bcipy/simulator/helpers/types.py b/bcipy/simulator/helpers/types.py index f2f3b35b5..3103f951d 100644 --- a/bcipy/simulator/helpers/types.py +++ b/bcipy/simulator/helpers/types.py @@ -1,3 +1,4 @@ +import dataclasses from dataclasses import dataclass from typing import Optional, List, Dict @@ -12,6 +13,14 @@ class SimEvidence: evidence: np.ndarray symbol_set: List[str] + def to_json(self) -> Dict: + d = dataclasses.asdict(self) + evidence_list = self.evidence.tolist() + d['evidence'] = evidence_list + d['evidence_type'] = self.evidence_type.name + + return d + @dataclass class InquiryResult: @@ -21,3 +30,11 @@ class InquiryResult: evidences: Dict[str, SimEvidence] fused_likelihood: np.ndarray decision: Optional[str] + + def to_json(self): + d = dataclasses.asdict(self) + + d['fused_likelihood'] = self.fused_likelihood.tolist() + d['evidences'] = {k: v.to_json() for k, v in self.evidences.items()} + + return d diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index d10c8d77f..f1d772e98 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -1,7 +1,9 @@ +import dataclasses +import json import logging import random from time import sleep -from typing import Optional, Dict +from typing import Optional, Dict, Any import numpy as np @@ -103,6 +105,8 @@ def run(self): log.debug(f"Final State: {final_state}") + self.output_run() + def __make_stimuli(self, state: SimState): # TODO abstract out subset_length = 10 @@ -140,5 +144,18 @@ def load_parameters(self, params: Optional[Parameters]): else: return self.data_engine.get_parameters() + def output_run(self): + """ Outputs the results of a run to json file """ + + final_state = self.state_manager.get_state() + final_state_json: Dict = final_state.to_json() + + metric_dict = self.referee.score(self).__dict__ + metric_dict.update(final_state_json) # adding state data to metrics + + output_path = "bcipy/simulator/generated" + with open(f"{output_path}/result.json", 'w') as output_file: + json.dump(metric_dict, output_file) + def get_parameters(self): return self.parameters.copy() From 8da4ecf28b22728b00508ab18a3459d78a0981fd Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 14 Feb 2024 11:59:54 -0800 Subject: [PATCH 221/330] Add Data Source (#314) Refactoring data engine helper --- bcipy/simulator/helpers/data_engine.py | 93 ++++++++++++----------- bcipy/simulator/helpers/signal_helpers.py | 46 ++++++++--- 2 files changed, 86 insertions(+), 53 deletions(-) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 6eebf9a15..34be48f3a 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -1,18 +1,15 @@ import logging -import os from abc import ABC from pathlib import Path -from typing import Optional, List +from typing import List, NamedTuple, Optional import numpy as np import pandas as pd -from bcipy.config import DEFAULT_PARAMETER_FILENAME -from bcipy.helpers import load from bcipy.helpers.list import grouper from bcipy.helpers.parameters import Parameters -from bcipy.simulator.helpers.signal_helpers import ExtractedExperimentData, \ - process_raw_data_for_model +from bcipy.simulator.helpers.signal_helpers import (ExtractedExperimentData, + process_raw_data_for_model) log = logging.getLogger(__name__) @@ -31,6 +28,27 @@ def get_data(self): def get_parameters(self) -> List[Parameters]: ... +class Trial(NamedTuple): + """Data for a given trial (a symbol within an Inquiry). + + TODO: add series to facilitate easier lookup in session data. + + Attrs + ----- + source - directory of the data source + inquiry_n - starts at 0; does not reset at each series + inquiry_pos - starts at 1; position in which the symbol was presented + symbol - alphabet symbol that was presented + target - 1 or 0 indicating a boolean of whether this was a target symbol + eeg - EEG data associated with this trial + """ + source: str + # series_n: int + inquiry_n: int + inquiry_pos: int + symbol: str + target: int + eeg: np.ndarray class RawDataEngine(DataEngine): """ @@ -43,14 +61,9 @@ def __init__(self, source_dirs: List[str], parameters: Parameters): self.source_dirs: List[str] = source_dirs self.parameters: Parameters = parameters self.data: Optional[List[ExtractedExperimentData]] = None - self.trials_by_inquiry: List[ - np.ndarray] = [] # shape (i_inquiry, n_channel, m_trial, x_sample). - self.symbols_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) - self.labels_by_inquiry: List[List] = [] # shape (i_inquiry, s_alphabet_subset) self.schema: Optional[pd.DataFrame] = None # TODO validate parameters - self.load() def load(self) -> DataEngine: @@ -63,20 +76,10 @@ def load(self) -> DataEngine: """ log.debug(f"Loading data from {len(self.source_dirs)} source directories") - self.data: List[ExtractedExperimentData] = [ - process_raw_data_for_model(source_dir, self.parameters) for source_dir in - self.source_dirs] - - for data_source in self.data: - trigger_targetness, trigger_timing, trigger_symbols = data_source.decoded_triggers - self.trials_by_inquiry.append( - np.split(data_source.trials, data_source.inquiries.shape[1], 1)) - self.symbols_by_inquiry.append([list(group) for group in - grouper(trigger_symbols, - self.parameters.get('stim_length'), - incomplete="ignore")]) - - self.labels_by_inquiry.append(data_source.labels) + self.data = [ + process_raw_data_for_model(source_dir, self.parameters) + for source_dir in self.source_dirs + ] log.info("Finished loading all data") return self @@ -84,7 +87,7 @@ def load(self) -> DataEngine: def transform(self) -> DataEngine: """ Organizes all data into the following schema - - Dataframe {"series_n":int, "inquiry_n":int, "trial_n":int, "symbol":str, "target":int, "eeg":ndarray} + - Dataframe {"inquiry_n":int, "trial_n":int, "symbol":str, "target":int, "eeg":ndarray} The "eeg" data for trial looks like this - ndarray.shape = (channel_n, sample_n) @@ -94,26 +97,28 @@ def transform(self) -> DataEngine: self for chaining """ - # TODO store how good evidence was in session | store data source as well + # TODO store how good evidence was in session rows = [] - for d_i in range(len(self.data)): - for i in range(len(self.trials_by_inquiry[d_i])): - symbols = self.symbols_by_inquiry[d_i][i] - inquiry_labels = self.labels_by_inquiry[d_i][i] - inquiry_eeg = self.trials_by_inquiry[d_i][i] - - symbol_rows = [] - for t_i, symbol in enumerate(symbols): - channel_eeg_samples_for_t = [channel[t_i] for channel in - inquiry_eeg] # (channel_n, sample_n) - row = {'inquiry_n': i, 'trial_n': t_i, 'symbol': symbol, - 'target': inquiry_labels[t_i], - 'eeg': np.array(channel_eeg_samples_for_t)} - - symbol_rows.append(row) - - rows.extend(symbol_rows) + for data_source in self.data: + symbols_by_inquiry = data_source.symbols_by_inquiry + labels_by_inquiry = data_source.labels_by_inquiry + + for i, inquiry_eeg in enumerate(data_source.trials_by_inquiry): + # iterate through each inquiry + inquiry_symbols = symbols_by_inquiry[i] + inquiry_labels = labels_by_inquiry[i] + + for sym_i, symbol in enumerate(inquiry_symbols): + # iterate through each symbol in the inquiry + eeg_samples = [channel[sym_i] for channel in inquiry_eeg + ] # (channel_n, sample_n) + rows.append(Trial(source=data_source.source_dir, + inquiry_n=i, + inquiry_pos=sym_i + 1, + symbol=symbol, + target=inquiry_labels[sym_i], + eeg=np.array(eeg_samples))) self.schema = pd.DataFrame(rows) diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 550b6f7e5..8f511c824 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -6,29 +6,51 @@ import numpy as np from bcipy.acquisition import devices -from bcipy.config import ( - RAW_DATA_FILENAME, - TRIGGER_FILENAME, - DEFAULT_DEVICE_SPEC_FILENAME, -) +from bcipy.config import (DEFAULT_DEVICE_SPEC_FILENAME, RAW_DATA_FILENAME, + TRIGGER_FILENAME) from bcipy.helpers.acquisition import analysis_channels from bcipy.helpers.exceptions import TaskConfigurationException +from bcipy.helpers.list import grouper from bcipy.helpers.load import load_raw_data -from bcipy.helpers.stimuli import update_inquiry_timing, InquiryReshaper +from bcipy.helpers.stimuli import InquiryReshaper, update_inquiry_timing from bcipy.helpers.triggers import TriggerType, trigger_decoder -from bcipy.signal.process import get_default_transform, filter_inquiries, ERPTransformParams +from bcipy.signal.process import (ERPTransformParams, filter_inquiries, + get_default_transform) log = logger.getLogger(__name__) @dataclass() class ExtractedExperimentData: # TODO clean up design + source_dir: str inquiries: np.ndarray trials: np.ndarray labels: List inquiry_timing: List decoded_triggers: tuple + trials_per_inquiry: int + + @property + def trials_by_inquiry(self) -> List[np.ndarray]: + """EEG data by inquiry. + shape (i_inquiry, n_channel, m_trial, x_sample) + """ + return np.split(self.trials, self.inquiries.shape[1], 1) + + @property + def symbols_by_inquiry(self) -> List[List[str]]: + """Get symbols by inquiry. shape (i_inquiry, s_alphabet_subset)""" + _targets, _times, trigger_symbols = self.decoded_triggers + return [ + list(group) for group in grouper( + trigger_symbols, self.trials_per_inquiry, incomplete="ignore") + ] + + @property + def labels_by_inquiry(self) -> List[List[int]]: + """Shape (i_inquiry, s_alphabet_subset)""" + return self.labels def process_raw_data_for_model(data_folder, parameters, @@ -128,5 +150,11 @@ def process_raw_data_for_model(data_folder, parameters, # define the training classes using integers, where 0=nontargets/1=targets # labels = inquiry_labels.flatten() - return ExtractedExperimentData(inquiries, trials, inquiry_labels, inquiry_timing, - (trigger_targetness, trigger_timing, trigger_symbols)) + return ExtractedExperimentData( + data_folder, + inquiries, + trials, + inquiry_labels, + inquiry_timing, + decoded_triggers=(trigger_targetness, trigger_timing, trigger_symbols), + trials_per_inquiry=trials_per_inquiry) From dc1671caf919b06c35cf46b04065175c398fbdd4 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Wed, 14 Feb 2024 15:58:40 -0500 Subject: [PATCH 222/330] save directory --- .gitignore | 1 + bcipy/simulator/__main__.py | 25 ++++++++++++++++++++----- bcipy/simulator/sim.py | 25 +++++++++++++------------ bcipy/simulator/sim_factory.py | 4 ++-- 4 files changed, 36 insertions(+), 19 deletions(-) diff --git a/.gitignore b/.gitignore index 1397d7e61..1df4acfc9 100644 --- a/.gitignore +++ b/.gitignore @@ -37,3 +37,4 @@ bcipy/language/out/ bcipy/simulator/tests/resource/ +bcipy/simulator/generated/SIM_* diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 85e9dd86c..81cf33975 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -3,6 +3,8 @@ import argparse import datetime import logging +import os +import random import sys from pathlib import Path @@ -11,16 +13,14 @@ from bcipy.simulator.simulator_base import Simulator -def configure_logger(): +def configure_logger(log_path, file_name): """ configures logger for standard out nad file output """ log = logging.getLogger(None) # configuring root logger log.setLevel(logging.DEBUG) # Create handlers for logging to the standard output and a file stdoutHandler = logging.StreamHandler(stream=sys.stdout) - file_name = datetime.datetime.now().strftime("%m-%d-%H:%M") - output_path = "bcipy/simulator/generated" - fileHandler = logging.FileHandler(f"{output_path}/{file_name}.log") + fileHandler = logging.FileHandler(f"{log_path}/{file_name}.log") # Set the log levels on the handlers stdoutHandler.setLevel(logging.INFO) @@ -40,6 +40,16 @@ def configure_logger(): log.addHandler(fileHandler) +def init_save_dir(output_path, save_dir_name): + # creating wrapper dir to save to within /generated. Adds a unique 4 digit id to end + unique_id = random.sample(range(1000, 10000), 1)[0] + save_dir = f"{output_path}/SIM_{save_dir_name}_{unique_id}" + os.makedirs(save_dir) + os.makedirs(f"{save_dir}/logs") + + return save_dir + + if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( @@ -67,8 +77,13 @@ def configure_logger(): args = vars(parser.parse_args()) + output_path = "bcipy/simulator/generated" # TODO read from parameters + now_time = datetime.datetime.now().strftime("%m-%d-%H:%M") + args['save_dir'] = init_save_dir(output_path, now_time) + # setting up logging - configure_logger() + log_path = f"{args['save_dir']}/logs" + configure_logger(log_path, now_time) simulator: Simulator = SimulationFactoryV2.create(**args) diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index f1d772e98..496eaa44c 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -3,12 +3,11 @@ import logging import random from time import sleep -from typing import Optional, Dict, Any +from typing import Optional, Dict import numpy as np -from bcipy.helpers import load, stimuli, symbols -from bcipy.helpers.language_model import histogram +from bcipy.helpers import stimuli, symbols from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import DataEngine @@ -17,8 +16,7 @@ from bcipy.simulator.helpers.sampler import Sampler from bcipy.simulator.helpers.state_manager import StateManager, SimState from bcipy.simulator.helpers.types import InquiryResult, SimEvidence -from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods, fmt_reshaped_evidence, \ - fmt_likelihoods_for_hist +from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods, fmt_reshaped_evidence from bcipy.simulator.helpers.model_handler import ModelHandler from bcipy.simulator.simulator_base import Simulator from bcipy.task.data import EvidenceType @@ -105,7 +103,7 @@ def run(self): log.debug(f"Final State: {final_state}") - self.output_run() + self.save_run() def __make_stimuli(self, state: SimState): # TODO abstract out @@ -144,18 +142,21 @@ def load_parameters(self, params: Optional[Parameters]): else: return self.data_engine.get_parameters() - def output_run(self): + def save_run(self): """ Outputs the results of a run to json file """ + # creating result.json object with final state and metrics final_state = self.state_manager.get_state() final_state_json: Dict = final_state.to_json() - - metric_dict = self.referee.score(self).__dict__ + metric_dict = dataclasses.asdict(self.referee.score(self)) metric_dict.update(final_state_json) # adding state data to metrics - output_path = "bcipy/simulator/generated" - with open(f"{output_path}/result.json", 'w') as output_file: - json.dump(metric_dict, output_file) + # writing result.json + with open(f"{self.save_dir}/result.json", 'w') as output_file: + json.dump(metric_dict, output_file, indent=1) + + # writing params + self.parameters.save(directory=self.save_dir) def get_parameters(self): return self.parameters.copy() diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 4c26cd0a6..1c931009d 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -17,7 +17,7 @@ class SimulationFactoryV2: @staticmethod def create(data_folder: str, smodel_files: List[str], - sim_param_path="bcipy/simulator/sim_parameters.json", **kwargs): + sim_param_path="bcipy/simulator/sim_parameters.json", save_dir=None, **kwargs): # out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) model_file = Path(smodel_files.pop()) @@ -33,6 +33,6 @@ def create(data_folder: str, smodel_files: List[str], referee: MetricReferee = RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()}) sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, state_manager, referee, - parameters=base_parameters) + parameters=base_parameters, save_dir=save_dir) return sim From ab950f2298da498a6db4393568baa64ee72c9595 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Wed, 14 Feb 2024 16:02:14 -0500 Subject: [PATCH 223/330] .gitkeep generated directory --- bcipy/simulator/generated/.gitkeep | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 bcipy/simulator/generated/.gitkeep diff --git a/bcipy/simulator/generated/.gitkeep b/bcipy/simulator/generated/.gitkeep new file mode 100644 index 000000000..e69de29bb From 978c4adf525d0a9e0a66740ccbf3752d35831b39 Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 20 Feb 2024 15:33:52 -0800 Subject: [PATCH 224/330] #187083845 ; added Oracle Language Model --- bcipy/helpers/language_model.py | 17 ++-- bcipy/language/model/oracle.py | 133 ++++++++++++++++++++++++++++ bcipy/language/tests/test_oracle.py | 75 ++++++++++++++++ bcipy/parameters/parameters.json | 3 +- 4 files changed, 220 insertions(+), 8 deletions(-) create mode 100644 bcipy/language/model/oracle.py create mode 100644 bcipy/language/tests/test_oracle.py diff --git a/bcipy/helpers/language_model.py b/bcipy/helpers/language_model.py index 37ac909db..0c9d87d7c 100644 --- a/bcipy/helpers/language_model.py +++ b/bcipy/helpers/language_model.py @@ -1,23 +1,26 @@ """Helper functions for language model use.""" -import math import inspect +import math from typing import Dict, List, Tuple + import numpy as np -from bcipy.language.main import LanguageModel, ResponseType + from bcipy.helpers.symbols import alphabet +from bcipy.language.main import LanguageModel, ResponseType + # pylint: disable=unused-import # flake8: noqa """Only imported models will be included in language_models_by_name""" -from bcipy.language.model.uniform import UniformLanguageModel +# flake8: noqa +from bcipy.helpers.exceptions import InvalidLanguageModelException from bcipy.language.model.causal import CausalLanguageModel -from bcipy.language.model.mixture import MixtureLanguageModel from bcipy.language.model.kenlm import KenLMLanguageModel +from bcipy.language.model.mixture import MixtureLanguageModel +from bcipy.language.model.oracle import OracleLanguageModel +from bcipy.language.model.uniform import UniformLanguageModel from bcipy.language.model.unigram import UnigramLanguageModel -# flake8: noqa -from bcipy.helpers.exceptions import InvalidLanguageModelException - def language_models_by_name() -> Dict[str, LanguageModel]: """Returns available language models indexed by name.""" diff --git a/bcipy/language/model/oracle.py b/bcipy/language/model/oracle.py new file mode 100644 index 000000000..0f3c9702f --- /dev/null +++ b/bcipy/language/model/oracle.py @@ -0,0 +1,133 @@ +"""Oracle language model""" +import logging +from typing import List, Optional, Tuple, Union + +import numpy as np + +from bcipy.helpers.symbols import BACKSPACE_CHAR +from bcipy.language.main import LanguageModel, ResponseType +from bcipy.language.model.uniform import equally_probable + +logger = logging.getLogger() + + +class OracleLanguageModel(LanguageModel): + """Language model which knows the target phrase the user is attempting to + spell. + + Probabilities for symbols are uniformly distributed with the exception of + the target letter, which has a slightly higher probability. How much higher + depends on the configured parameter. + + Parameters + ---------- + response_type - SYMBOL only + symbol_set - optional specify the symbol set, otherwise uses DEFAULT_SYMBOL_SET + task_text - the phrase the user is attempting to spell (ex. 'HELLO_WORLD') + target_bump - the amount by which the probability of the target letter + is increased. + """ + + def __init__(self, + response_type: Optional[ResponseType] = None, + symbol_set: Optional[List[str]] = None, + task_text: str = None, + target_bump: float = 0.1): + super().__init__(response_type=response_type, symbol_set=symbol_set) + assert task_text, "task_text is required" + self.task_text = task_text + self.target_bump = target_bump + logger.debug( + f"Initialized OracleLanguageModel(task_text='{task_text}', target_bump={target_bump})" + ) + + def supported_response_types(self) -> List[ResponseType]: + return [ResponseType.SYMBOL] + + def predict(self, evidence: Union[str, List[str]]) -> List[Tuple]: + """ + Using the provided data, compute probabilities over the entire symbol. + set. + + Parameters + ---------- + evidence - list of previously typed symbols + + Returns + ------- + list of (symbol, probability) tuples + """ + spelled_text = ''.join(evidence) + probs = equally_probable(self.symbol_set) + target = self._next_target(spelled_text) + + sym = (target, probs[0] + self.target_bump) + symbol_probs = list(zip(self.symbol_set, probs)) + updated_symbol_probs = with_min_prob(symbol_probs, sym) + return sorted(updated_symbol_probs, + key=lambda pair: self.symbol_set.index(pair[0])) + + def update(self) -> None: + """Update the model state""" + + def load(self) -> None: + """Restore model state from the provided checkpoint""" + + def _next_target(self, spelled_text: str) -> str: + """Computes the next target letter based on the currently spelled_text. + """ + if self.task_text[0:len(spelled_text)] == spelled_text: + # if correctly spelled so far, get the next letter. + return self.task_text[len(spelled_text)] + return BACKSPACE_CHAR + + +# TODO: Cleanup; This method is copied from helpers/language_model.py but can't +# be imported from there due to circular dependencies. We should either create +# a separate module for lm utilities, or refactor this method to only extract +# the needed functionality. +def with_min_prob(symbol_probs: List[Tuple[str, float]], + sym_prob: Tuple[str, float]) -> List[Tuple[str, float]]: + """Returns a new list of symbol-probability pairs where the provided + symbol has a minimum probability given in the sym_prob. + + If the provided symbol is already in the list with a greater probability, + the list of symbol_probs will be returned unmodified. + + If the new probability is added or modified, existing values are adjusted + equally. + + Parameters: + ----------- + symbol_probs - list of symbol, probability pairs + sym_prob - (symbol, min_probability) defines the minimum probability + for the given symbol in the returned list. + + Returns: + ------- + list of (symbol, probability) pairs such that the sum of the + probabilities is approx. 1.0. + """ + new_sym, new_prob = sym_prob + + # Split out symbols and probabilities into separate lists, excluding the + # symbol to be adjusted. + symbols = [] + probs = [] + for sym, prob in symbol_probs: + if sym != new_sym: + symbols.append(sym) + probs.append(prob) + elif prob >= new_prob: + # symbol prob in list is larger than minimum. + return symbol_probs + + probabilities = np.array(probs) + + # Add new symbol and its probability + all_probs = np.append(probabilities, new_prob / (1 - new_prob)) + all_symbols = symbols + [new_sym] + + normalized = all_probs / sum(all_probs) + + return list(zip(all_symbols, normalized)) diff --git a/bcipy/language/tests/test_oracle.py b/bcipy/language/tests/test_oracle.py new file mode 100644 index 000000000..fb26c4923 --- /dev/null +++ b/bcipy/language/tests/test_oracle.py @@ -0,0 +1,75 @@ +"""Tests for Oracle Language Model""" + +import unittest + +from bcipy.language.model.oracle import (BACKSPACE_CHAR, OracleLanguageModel, + ResponseType) + + +class TestOracleLanguageModel(unittest.TestCase): + """Tests for language model""" + + def test_init(self): + """Test default parameters""" + with self.assertRaises(AssertionError): + OracleLanguageModel() + + def test_init_with_text(self): + """Test with task_text provided""" + lmodel = OracleLanguageModel(task_text="HELLO_WORLD") + self.assertEqual(lmodel.response_type, ResponseType.SYMBOL) + self.assertEqual( + len(lmodel.symbol_set), 28, + "Should be the alphabet plus the backspace and space chars") + + def test_predict(self): + """Test the predict method""" + lm = OracleLanguageModel(task_text="HELLO_WORLD") + symbol_probs = lm.predict(evidence=[]) + probs = [prob for sym, prob in symbol_probs] + + self.assertEqual(len(set(probs)), 2, + "All non-target values should be the same") + self.assertTrue(0 < probs[0] < 1) + self.assertAlmostEqual(sum(probs), 1) + + probs_dict = dict(symbol_probs) + self.assertTrue(probs_dict['H'] > probs_dict['A'], + "Target should have a higher value") + self.assertAlmostEqual(lm.target_bump, + probs_dict['H'] - probs_dict['A'], + places=1) + + def test_predict_with_spelled_text(self): + """Test predictions with previously spelled symbols""" + lm = OracleLanguageModel(task_text="HELLO_WORLD") + symbol_probs = lm.predict(evidence=list("HELLO_")) + + probs = [prob for sym, prob in symbol_probs] + self.assertEqual(len(set(probs)), 2, + "All non-target values should be the same") + + probs_dict = dict(symbol_probs) + self.assertTrue(probs_dict['W'] > probs_dict['A']) + + def test_predict_with_incorrectly_spelled_text(self): + """Test predictions with incorrectly spelled prior.""" + lm = OracleLanguageModel(task_text="HELLO_WORLD") + symbol_probs = lm.predict(evidence=list("HELP")) + + probs = [prob for sym, prob in symbol_probs] + self.assertEqual(len(set(probs)), 2) + + probs_dict = dict(symbol_probs) + self.assertTrue(probs_dict[BACKSPACE_CHAR] > probs_dict['A']) + + def test_target_bump_parameter(self): + """Test setting the target_bump parameter.""" + lm = OracleLanguageModel(task_text="HELLO_WORLD", target_bump=0.2) + symbol_probs = lm.predict(evidence=[]) + probs_dict = dict(symbol_probs) + self.assertTrue(probs_dict['H'] > probs_dict['A'], + "Target should have a higher value") + self.assertAlmostEqual(0.2, + probs_dict['H'] - probs_dict['A'], + places=1) diff --git a/bcipy/parameters/parameters.json b/bcipy/parameters/parameters.json index 11a5c30e3..46018a72a 100755 --- a/bcipy/parameters/parameters.json +++ b/bcipy/parameters/parameters.json @@ -673,7 +673,8 @@ "UNIFORM", "CAUSAL", "KENLM", - "MIXTURE" + "MIXTURE", + "ORACLE" ], "type": "str" }, From 34a5e7526e71fe7e5b571d1a7a4fd729cd62c8d1 Mon Sep 17 00:00:00 2001 From: lawhead Date: Wed, 21 Feb 2024 11:35:43 -0800 Subject: [PATCH 225/330] Added checks for valid property values; updated changelog --- CHANGELOG.md | 1 + bcipy/language/model/oracle.py | 27 ++++++++++++++++++++- bcipy/language/tests/test_oracle.py | 37 +++++++++++++++++++++++++++++ 3 files changed, 64 insertions(+), 1 deletion(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 668342acd..fe6a592ca 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -58,6 +58,7 @@ Our last release candidate before the official 2.0 release! - added KenLM model `kenlm.py` #268 - added mixture model `mixture.py` and script to tune weights `mixture_tuning.py` #268 - added script to evaluate language model performance `lm_eval.py` #268 + - added Oracle model #316 - Signal Model - added `RdaKdeModel` and restructured to pull out common elements from the PcaRdaKdeModel #279 - Bug Fixes diff --git a/bcipy/language/model/oracle.py b/bcipy/language/model/oracle.py index 0f3c9702f..fd4b6994a 100644 --- a/bcipy/language/model/oracle.py +++ b/bcipy/language/model/oracle.py @@ -10,6 +10,9 @@ logger = logging.getLogger() +TARGET_BUMP_MIN = 0.0 +TARGET_BUMP_MAX = 0.95 + class OracleLanguageModel(LanguageModel): """Language model which knows the target phrase the user is attempting to @@ -34,13 +37,35 @@ def __init__(self, task_text: str = None, target_bump: float = 0.1): super().__init__(response_type=response_type, symbol_set=symbol_set) - assert task_text, "task_text is required" self.task_text = task_text self.target_bump = target_bump logger.debug( f"Initialized OracleLanguageModel(task_text='{task_text}', target_bump={target_bump})" ) + @property + def task_text(self): + """Get the task_text property""" + return self._task_text + + @task_text.setter + def task_text(self, value: str): + """Setter for task_text""" + assert value, "task_text is required" + self._task_text = value + + @property + def target_bump(self): + """Get the target_bump property""" + return self._target_bump + + @target_bump.setter + def target_bump(self, value: float): + """Setter for target_bump""" + msg = f"target_bump should be between {TARGET_BUMP_MIN} and {TARGET_BUMP_MAX}" + assert TARGET_BUMP_MIN <= value <= TARGET_BUMP_MAX, msg + self._target_bump = value + def supported_response_types(self) -> List[ResponseType]: return [ResponseType.SYMBOL] diff --git a/bcipy/language/tests/test_oracle.py b/bcipy/language/tests/test_oracle.py index fb26c4923..e4d186263 100644 --- a/bcipy/language/tests/test_oracle.py +++ b/bcipy/language/tests/test_oracle.py @@ -73,3 +73,40 @@ def test_target_bump_parameter(self): self.assertAlmostEqual(0.2, probs_dict['H'] - probs_dict['A'], places=1) + + def test_setting_task_text_to_none(self): + """Test that task_text is required""" + lmodel = OracleLanguageModel(task_text="HELLO_WORLD") + with self.assertRaises(AssertionError): + lmodel.task_text = None + + def test_updating_task_text(self): + """Test updating the task_text property.""" + lm = OracleLanguageModel(task_text="HELLO_WORLD", target_bump=0.2) + probs = dict(lm.predict(evidence=list("HELLO_"))) + self.assertTrue(probs['W'] > probs['T'], + "Target should have a higher value") + + lm.task_text = "HELLO_THERE" + probs = dict(lm.predict(evidence=list("HELLO_"))) + self.assertTrue(probs['T'] > probs['W'], + "Target should have a higher value") + + def test_target_bump_bounds(self): + """Test the bounds of target_bump property""" + with self.assertRaises(AssertionError): + OracleLanguageModel(task_text="HI", target_bump=-1.0) + + with self.assertRaises(AssertionError): + OracleLanguageModel(task_text="HI", target_bump=1.1) + + lm = OracleLanguageModel(task_text="HI", target_bump=0.0) + with self.assertRaises(AssertionError): + lm.target_bump = -1.0 + + lm.target_bump = 0.5 + self.assertEqual(0.5, lm.target_bump) + + +if __name__ == '__main__': + unittest.main() From 21aedb4adff712d147983f387a576ee5d3c7d1bc Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 22 Feb 2024 14:30:33 -0800 Subject: [PATCH 226/330] Updated OracleLanguageModel to handle the case when the evidence exceeds the task_text length --- bcipy/language/model/oracle.py | 27 +++++++++++++++++++++------ bcipy/language/tests/test_oracle.py | 22 ++++++++++++++++++++++ 2 files changed, 43 insertions(+), 6 deletions(-) diff --git a/bcipy/language/model/oracle.py b/bcipy/language/model/oracle.py index fd4b6994a..42b5cc560 100644 --- a/bcipy/language/model/oracle.py +++ b/bcipy/language/model/oracle.py @@ -22,6 +22,9 @@ class OracleLanguageModel(LanguageModel): the target letter, which has a slightly higher probability. How much higher depends on the configured parameter. + After the target text has been correctly spelled subsequent predictions + yield all symbols with equal probability. + Parameters ---------- response_type - SYMBOL only @@ -84,11 +87,15 @@ def predict(self, evidence: Union[str, List[str]]) -> List[Tuple]: """ spelled_text = ''.join(evidence) probs = equally_probable(self.symbol_set) + symbol_probs = list(zip(self.symbol_set, probs)) target = self._next_target(spelled_text) - sym = (target, probs[0] + self.target_bump) - symbol_probs = list(zip(self.symbol_set, probs)) - updated_symbol_probs = with_min_prob(symbol_probs, sym) + if target: + sym = (target, probs[0] + self.target_bump) + updated_symbol_probs = with_min_prob(symbol_probs, sym) + else: + updated_symbol_probs = symbol_probs + return sorted(updated_symbol_probs, key=lambda pair: self.symbol_set.index(pair[0])) @@ -98,11 +105,19 @@ def update(self) -> None: def load(self) -> None: """Restore model state from the provided checkpoint""" - def _next_target(self, spelled_text: str) -> str: + def _next_target(self, spelled_text: str) -> Optional[str]: """Computes the next target letter based on the currently spelled_text. """ - if self.task_text[0:len(spelled_text)] == spelled_text: - # if correctly spelled so far, get the next letter. + len_spelled = len(spelled_text) + len_task = len(self.task_text) + + if len_spelled >= len_task and spelled_text[ + 0:len_task] == self.task_text: + return None + + if len_spelled < len_task and self.task_text[ + 0:len_spelled] == spelled_text: + # correctly spelled so far, get the next letter. return self.task_text[len(spelled_text)] return BACKSPACE_CHAR diff --git a/bcipy/language/tests/test_oracle.py b/bcipy/language/tests/test_oracle.py index e4d186263..69a2f7a2b 100644 --- a/bcipy/language/tests/test_oracle.py +++ b/bcipy/language/tests/test_oracle.py @@ -107,6 +107,28 @@ def test_target_bump_bounds(self): lm.target_bump = 0.5 self.assertEqual(0.5, lm.target_bump) + def test_evidence_exceeds_task(self): + """Test probs when evidence exceeds task_text.""" + lm = OracleLanguageModel(task_text="HELLO") + + probs = dict(lm.predict(evidence="HELL")) + self.assertEqual(2, len(set(probs.values()))) + self.assertEqual(max(probs.values()), probs['O']) + + probs = dict(lm.predict(evidence="HELLO")) + self.assertEqual(1, len(set(probs.values()))) + + probs = dict(lm.predict(evidence="HELLP")) + self.assertEqual(2, len(set(probs.values()))) + self.assertEqual(max(probs.values()), probs[BACKSPACE_CHAR]) + + probs = dict(lm.predict(evidence="HELLO_")) + self.assertEqual(1, len(set(probs.values()))) + + probs = dict(lm.predict(evidence="HELPED")) + self.assertEqual(2, len(set(probs.values()))) + self.assertEqual(max(probs.values()), probs[BACKSPACE_CHAR]) + if __name__ == '__main__': unittest.main() From 19d98d118961d3fd57648ae004659dc4723efcdf Mon Sep 17 00:00:00 2001 From: Srikar Ananthoju <46632027+sreekaroo@users.noreply.github.com> Date: Sat, 24 Feb 2024 16:28:28 -0800 Subject: [PATCH 227/330] Multiple run feature for sim (#317) * moving artifact related code into helper file * multi run save directory and logging configs done * averaged metrics from multi run. abstracted up some fields into simulator_base.py.py --- bcipy/simulator/__main__.py | 64 +++------------- bcipy/simulator/helpers/artifact.py | 48 ++++++++++++ bcipy/simulator/helpers/metrics.py | 54 +++++++++----- bcipy/simulator/helpers/sim_runner.py | 94 ++++++++++++++++++++++++ bcipy/simulator/helpers/state_manager.py | 7 ++ bcipy/simulator/sim.py | 3 + bcipy/simulator/sim_parameters.json | 11 +++ bcipy/simulator/simulator_base.py | 15 ++++ 8 files changed, 223 insertions(+), 73 deletions(-) create mode 100644 bcipy/simulator/helpers/artifact.py create mode 100644 bcipy/simulator/helpers/sim_runner.py diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 81cf33975..4b845a450 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -2,54 +2,12 @@ import argparse import datetime -import logging -import os -import random -import sys from pathlib import Path -from bcipy.simulator.helpers.decision import MaxIterationsSim +from bcipy.simulator.helpers.sim_runner import MultiSimRunner, SingleSimRunner from bcipy.simulator.sim_factory import SimulationFactoryV2 from bcipy.simulator.simulator_base import Simulator - -def configure_logger(log_path, file_name): - """ configures logger for standard out nad file output """ - - log = logging.getLogger(None) # configuring root logger - log.setLevel(logging.DEBUG) - # Create handlers for logging to the standard output and a file - stdoutHandler = logging.StreamHandler(stream=sys.stdout) - fileHandler = logging.FileHandler(f"{log_path}/{file_name}.log") - - # Set the log levels on the handlers - stdoutHandler.setLevel(logging.INFO) - fileHandler.setLevel(logging.DEBUG) - - # Create a log format using Log Record attributes - fmt_file = logging.Formatter("%(levelname)s | %(filename)s >> %(message)s") - - fmt = logging.Formatter("%(message)s") - - # Set the log format on each handler - stdoutHandler.setFormatter(fmt) - fileHandler.setFormatter(fmt_file) - - # Add each handler to the Logger object - log.addHandler(stdoutHandler) - log.addHandler(fileHandler) - - -def init_save_dir(output_path, save_dir_name): - # creating wrapper dir to save to within /generated. Adds a unique 4 digit id to end - unique_id = random.sample(range(1000, 10000), 1)[0] - save_dir = f"{output_path}/SIM_{save_dir_name}_{unique_id}" - os.makedirs(save_dir) - os.makedirs(f"{save_dir}/logs") - - return save_dir - - if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument( @@ -65,26 +23,22 @@ def init_save_dir(output_path, save_dir_name): type=Path, required=True, help="Signal models to be used") - parser.add_argument( "-p", "--parameters", type=Path, required=True, help="Parameter File to be used") - parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) - args = vars(parser.parse_args()) - output_path = "bcipy/simulator/generated" # TODO read from parameters - now_time = datetime.datetime.now().strftime("%m-%d-%H:%M") - args['save_dir'] = init_save_dir(output_path, now_time) - - # setting up logging - log_path = f"{args['save_dir']}/logs" - configure_logger(log_path, now_time) - simulator: Simulator = SimulationFactoryV2.create(**args) - simulator.run() + sim_run_count = simulator.get_parameters().get('sim_run_count', 1) + + if sim_run_count > 1: # running multiple times + runner = MultiSimRunner(simulator, sim_run_count) + runner.run() + else: + runner = SingleSimRunner(simulator) + runner.run() diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py new file mode 100644 index 000000000..6bde9cb17 --- /dev/null +++ b/bcipy/simulator/helpers/artifact.py @@ -0,0 +1,48 @@ +""" Handles artifacts related logic ie. logs, save dir creation, result.json, ...""" +import logging +import os +import random +import sys + + +def configure_logger(log_path, file_name): + """ configures logger for standard out nad file output """ + + log = logging.getLogger(None) # configuring root logger + log.setLevel(logging.DEBUG) + # Create handlers for logging to the standard output and a file + stdoutHandler = logging.StreamHandler(stream=sys.stdout) + fileHandler = logging.FileHandler(f"{log_path}/{file_name}.log") + + # Set the log levels on the handlers + stdoutHandler.setLevel(logging.INFO) + fileHandler.setLevel(logging.DEBUG) + + # Create a log format using Log Record attributes + fmt_file = logging.Formatter("%(levelname)s | %(filename)s >> %(message)s") + + fmt = logging.Formatter("%(message)s") + + # Set the log format on each handler + stdoutHandler.setFormatter(fmt) + fileHandler.setFormatter(fmt_file) + + # Add each handler to the Logger object + if stdoutHandler.stream.name not in [handler.stream.name for handler in log.handlers]: + log.addHandler(stdoutHandler) + + log.addHandler(fileHandler) + + +def init_save_dir(output_path, save_dir_name): + """ creating wrapper dir to save sim results to. + - Saves to {output_path} + - Adds a unique 4-digit id to end + """ + + unique_id = random.sample(range(1000, 10000), 1)[0] + save_dir = f"{output_path}/SIM_{save_dir_name}_{unique_id}" + os.makedirs(save_dir) + os.makedirs(f"{save_dir}/logs") + + return save_dir diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py index 8bed0d69b..91c08f901 100644 --- a/bcipy/simulator/helpers/metrics.py +++ b/bcipy/simulator/helpers/metrics.py @@ -1,36 +1,54 @@ +import dataclasses from abc import ABC, abstractmethod -from dataclasses import dataclass from functools import reduce -from typing import Dict, Any, Optional, List +from typing import Dict, Any, List import numpy as np from bcipy.helpers.acquisition import max_inquiry_duration from bcipy.simulator.helpers.state_manager import SimState from bcipy.simulator.helpers.types import InquiryResult -from bcipy.simulator.simulator_base import Simulator -@dataclass +@dataclasses.dataclass class SimMetrics1: - total_series: Optional[int] = None - total_inquiries: Optional[int] = None - total_decisions: Optional[int] = None - total_time_spent: Optional[float] = None + total_series: int = 0 + total_inquiries: int = 0 + total_decisions: int = 0 - inquiries_per_selection: Optional[float] = None + total_time_spent: float = 0.0 + inquiries_per_selection: float = 0.0 + + +def average_sim_metrics(run_scores: List[SimMetrics1]) -> Dict: + """ Averages the values in multiple SimMetrics1 objects """ + + metric_acc_dict = dataclasses.asdict(SimMetrics1()) + N = len(run_scores) + + if N < 1: + return metric_acc_dict + + for run_metrics in run_scores: + for field, val in dataclasses.asdict(run_metrics).items(): + metric_acc_dict[field] += val + + for key, val in metric_acc_dict.items(): + metric_acc_dict[key] = round(val / N, 3) + + return metric_acc_dict class RefereeHandler(ABC): @abstractmethod - def handle(self, sim: Simulator) -> Dict[str, Any]: + def handle(self, sim) -> Dict[str, Any]: ... class SimMetrics1Handler(RefereeHandler): - def handle(self, sim: Simulator) -> Dict[str, Any]: - state: SimState = getattr(sim, ("state_manager")).get_state() + def handle(self, sim) -> Dict[str, Any]: + state: SimState = getattr(sim, "state_manager").get_state() # calculating total decisions made flattened_inquiries: List[InquiryResult] = reduce(lambda l1, l2: l1 + l2, @@ -56,7 +74,7 @@ def handle(self, sim: Simulator) -> Dict[str, Any]: ret = SimMetrics1(total_series=total_series, total_inquiries=total_inquiries, total_decisions=total_decisions, total_time_spent=total_time_spent, inquiries_per_selection=inquiries_per_selection) - return ret.__dict__ + return dataclasses.asdict(ret) class MetricReferee(ABC): @@ -64,11 +82,11 @@ class MetricReferee(ABC): # May change to SimState that is passed around not whole Simulator # Depends on how much data encapsulated by SimState @abstractmethod - def score(self, sim: Simulator): + def score(self, sim): """ Generate registered metrics for simulation """ @abstractmethod - def visualize(self, sim: Simulator): + def visualize(self, sim): """ Generate registered visualizations for sim """ @abstractmethod @@ -89,9 +107,9 @@ def __init__(self, metric_handlers=None, viz_handlers=None): self.inquiry_time: float = 1 # 1 inq -> 1 second # TODO maybe some configurable parameters for visualizations - def score(self, sim: Simulator) -> SimMetrics1: + def score(self, sim) -> SimMetrics1: metrics = SimMetrics1() - metrics_dict = metrics.__dict__ + metrics_dict = dataclasses.asdict(metrics) for handler_name, handler in self.metric_handlers.items(): handler_metrics = handler.handle(sim) @@ -101,7 +119,7 @@ def score(self, sim: Simulator) -> SimMetrics1: return SimMetrics1(**metrics_dict) - def visualize(self, sim: Simulator): + def visualize(self, sim): for handler_name, viz_handler in self.viz_handlers.items(): viz_handler.handle(sim) diff --git a/bcipy/simulator/helpers/sim_runner.py b/bcipy/simulator/helpers/sim_runner.py new file mode 100644 index 000000000..bd10cd169 --- /dev/null +++ b/bcipy/simulator/helpers/sim_runner.py @@ -0,0 +1,94 @@ +""" Wrappers that run a simulation """ +import datetime +import json +import os +import time +from typing import Dict + +from bcipy.helpers.parameters import Parameters +from bcipy.simulator.helpers import artifact +from bcipy.simulator.helpers.metrics import average_sim_metrics +from bcipy.simulator.simulator_base import Simulator + + +class MultiSimRunner: + + def __init__(self, simulator: Simulator, n: int, save_dir=None, iteration_sleep=0): + self.simulator: Simulator = simulator + self.parameters: Parameters = self.simulator.get_parameters() + self.n: int = n + self.iteration_sleep: int = iteration_sleep + + self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path() + + def run(self): + # making wrapper dir for all simulations + os.makedirs(self.wrapper_save_dir) + + # list of metrics from sim runs + all_run_metrics = [] + + # running simulator n times. resetting after each run + for i in range(self.n): + + # creating save dir for sim_i, then mutating sim_i save_directory + sim_i_save_dir = artifact.init_save_dir(self.wrapper_save_dir, f"run{i}") + self.simulator.save_dir = sim_i_save_dir + artifact.configure_logger(f"{sim_i_save_dir}/logs", f"logs") + + # running simulator + self.simulator.run() + + if self.iteration_sleep > 0: + time.sleep(self.iteration_sleep) + + # aggregating metrics from each run + run_metrics = self.simulator.referee.score(self.simulator) + all_run_metrics.append(run_metrics) + + self.simulator.reset() + + # save averaged results to a file in root of wrapper dir + average_metrics = average_sim_metrics(all_run_metrics) + self.__save_average_metrics(average_metrics) + + def __make_default_save_path(self): + output_path = "bcipy/simulator/generated" + now_time = datetime.datetime.now().strftime("%m-%d-%H:%M") + dir_name = f"SIM_MULTI_{self.n}_{now_time}" + + return f"{output_path}/{dir_name}" + + def __save_average_metrics(self, avg_metric_dict: Dict): + """ Writing average dictionary of metrics to a json file in root of MultiRun save dir """ + + with open(f"{self.wrapper_save_dir}/avg_metrics.json", 'w') as output_file: + json.dump(avg_metric_dict, output_file, indent=1) + + +class SingleSimRunner: + + def __init__(self, simulator: Simulator, save_dir=None): + self.simulator: Simulator = simulator + self.parameters: Parameters = self.simulator.get_parameters() + + self.wrapper_save_dir: str = save_dir if save_dir else self.__make_default_save_path() + + def run(self): + # logging and save details + now_time = datetime.datetime.now().strftime("%m-%d-%H:%M") + save_dir_path = artifact.init_save_dir(self.wrapper_save_dir, now_time) + + # configuring logger to save to {output_wrapper_path}/logs + log_path = f"{save_dir_path}/logs" + artifact.configure_logger(log_path, now_time) + + # mutating simulator to save to specific save_dir + self.simulator.save_dir = save_dir_path + + # running sim + self.simulator.run() + + def __make_default_save_path(self): + output_path = "bcipy/simulator/generated" + return f"{output_path}" diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 288057e77..fb2c5b6b2 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -72,6 +72,9 @@ def get_state(self) -> SimState: def mutate_state(self, state_field, state_value): pass + def reset_state(self): + ... + class StateManagerImpl(StateManager): @@ -170,6 +173,10 @@ def mutate_state(self, state_field, state_value) -> SimState: raise FieldException(f"Cannot find state field {state_field}") + def reset_state(self): + self.state = self.initial_state(self.parameters) + return self + @staticmethod def initial_state(parameters: Parameters = None) -> SimState: sentence = "HELLO_WORLD" # TODO abstract out with sim_parameters.json diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index 496eaa44c..d373b69a0 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -158,5 +158,8 @@ def save_run(self): # writing params self.parameters.save(directory=self.save_dir) + def reset(self): + self.state_manager.reset_state() + def get_parameters(self): return self.parameters.copy() diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index dd16d0066..bab2e0796 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -53,5 +53,16 @@ "/lm_parameters.json" ], "type": "str" + }, + "sim_run_count": { + "value": "5", + "section": "sim_config", + "readableName": "How many times to run simulator", + "helpTip": "", + "recommended_values": [ + "1", + "5" + ], + "type": "int" } } \ No newline at end of file diff --git a/bcipy/simulator/simulator_base.py b/bcipy/simulator/simulator_base.py index 83db6dbf1..68013701f 100644 --- a/bcipy/simulator/simulator_base.py +++ b/bcipy/simulator/simulator_base.py @@ -3,6 +3,11 @@ from abc import ABC, abstractmethod from bcipy.helpers.parameters import Parameters +from bcipy.simulator.helpers import metrics +from bcipy.simulator.helpers.data_engine import DataEngine +from bcipy.simulator.helpers.model_handler import ModelHandler +from bcipy.simulator.helpers.sampler import Sampler +from bcipy.simulator.helpers.state_manager import StateManager class Simulator(ABC): @@ -14,6 +19,13 @@ class Simulator(ABC): - run closed loop simulation of {TaskType} with {data} with {simulation_params} """ + model_handler: ModelHandler + sampler: Sampler + state_manager: StateManager + data_engine: DataEngine + referee: metrics.MetricReferee + parameters: Parameters + @abstractmethod def run(self): """ Run loop for simulation""" @@ -21,3 +33,6 @@ def run(self): @abstractmethod def get_parameters(self) -> Parameters: """ retrieving parameters copy""" + + def reset(self): + ... From 38afa5584e3bc33c82811d7331406caee7982b06 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Thu, 7 Mar 2024 12:58:25 -0500 Subject: [PATCH 228/330] starting to make artifact look like session.json --- bcipy/simulator/helpers/artifact.py | 1 + bcipy/simulator/helpers/state_manager.py | 20 ++++++++++++++++++++ 2 files changed, 21 insertions(+) diff --git a/bcipy/simulator/helpers/artifact.py b/bcipy/simulator/helpers/artifact.py index 6bde9cb17..06b7586bb 100644 --- a/bcipy/simulator/helpers/artifact.py +++ b/bcipy/simulator/helpers/artifact.py @@ -46,3 +46,4 @@ def init_save_dir(output_path, save_dir_name): os.makedirs(f"{save_dir}/logs") return save_dir + diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index fb2c5b6b2..b4f1dfcb3 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -187,3 +187,23 @@ def initial_state(parameters: Parameters = None) -> SimState: return SimState(target_symbol=target_symbol, current_sentence="", target_sentence=sentence, display_alphabet=init_stimuli, inquiry_n=0, series_n=0, series_results=[[]], decision_criterion=default_criterion) + + +def format_sim_state_dump(state: SimState): + """ Formats a SimState dump to look similar to session.json """ + + # TODO + ret = {'series': {}} + + series_dict = {} + for i, series in enumerate(state.series_results): + if series: + curr_series_dict = {} + series_dict[str(i + 1)] = curr_series_dict + for inq_idx, inq in enumerate(series): + inq_dict = inq.to_json() + curr_series_dict[str(inq_idx)] = inq_dict + for evidence_type, evidence in inq_dict['evidences'].items(): + pass + + return ret From 29a5b24eee9c95750f7195916cad356e531d26d4 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Thu, 14 Mar 2024 14:43:18 -0400 Subject: [PATCH 229/330] changed series from list to dictionary in result.json --- bcipy/simulator/helpers/state_manager.py | 21 +++++++++++---------- bcipy/simulator/sim.py | 4 ++-- bcipy/simulator/sim_parameters.json | 2 +- 3 files changed, 14 insertions(+), 13 deletions(-) diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index b4f1dfcb3..4d0705b01 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -192,18 +192,19 @@ def initial_state(parameters: Parameters = None) -> SimState: def format_sim_state_dump(state: SimState): """ Formats a SimState dump to look similar to session.json """ - # TODO - ret = {'series': {}} + # TODO finish function + ret = state.to_json() + + # removing the 'series_results' field and replacing with formatted 'series' dict + ret.pop('series_results') series_dict = {} for i, series in enumerate(state.series_results): - if series: - curr_series_dict = {} - series_dict[str(i + 1)] = curr_series_dict - for inq_idx, inq in enumerate(series): - inq_dict = inq.to_json() - curr_series_dict[str(inq_idx)] = inq_dict - for evidence_type, evidence in inq_dict['evidences'].items(): - pass + curr_series_dict = {} + series_dict[str(i + 1)] = curr_series_dict + for inq_idx, inq in enumerate(series): + inq_dict = inq.to_json() + curr_series_dict[str(inq_idx)] = inq_dict + ret['series'] = series_dict return ret diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index d373b69a0..d05ba205f 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -14,7 +14,7 @@ from bcipy.simulator.helpers.metrics import MetricReferee from bcipy.simulator.helpers.rsvp_utils import format_lm_output from bcipy.simulator.helpers.sampler import Sampler -from bcipy.simulator.helpers.state_manager import StateManager, SimState +from bcipy.simulator.helpers.state_manager import StateManager, SimState, format_sim_state_dump from bcipy.simulator.helpers.types import InquiryResult, SimEvidence from bcipy.simulator.helpers.log_utils import fmt_stim_likelihoods, fmt_reshaped_evidence from bcipy.simulator.helpers.model_handler import ModelHandler @@ -147,7 +147,7 @@ def save_run(self): # creating result.json object with final state and metrics final_state = self.state_manager.get_state() - final_state_json: Dict = final_state.to_json() + final_state_json: Dict = format_sim_state_dump(final_state) metric_dict = dataclasses.asdict(self.referee.score(self)) metric_dict.update(final_state_json) # adding state data to metrics diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index bab2e0796..d609044b7 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -55,7 +55,7 @@ "type": "str" }, "sim_run_count": { - "value": "5", + "value": "1", "section": "sim_config", "readableName": "How many times to run simulator", "helpTip": "", From aa9cc7f43bf65e7da7f5866ccd2a47384b5fdb41 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 14 Mar 2024 12:02:02 -0700 Subject: [PATCH 230/330] Usability fixes (#318) * Small fixes needed for recent data analysis * Added the ability to select a subset of directories * Reverted logging statements --------- Co-authored-by: Srikar Ananthoju <46632027+sreekaroo@users.noreply.github.com> --- bcipy/simulator/README.md | 7 ++++++- bcipy/simulator/__main__.py | 16 +++++++++++++--- bcipy/simulator/helpers/model_handler.py | 7 ++++--- bcipy/simulator/helpers/state_manager.py | 14 ++++++++------ bcipy/simulator/sim_factory.py | 22 +++++++++++++--------- bcipy/simulator/sim_parameters.json | 2 +- 6 files changed, 45 insertions(+), 23 deletions(-) diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index 11773d456..3db647f65 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -13,7 +13,7 @@ live session. module from shell as such: -``python3 bcipy/simulator -d "pathToDataFolder1" -d "pathToOptionalDataFolder2" -sm "pathToSignalModel.pkl"`` +``python3 bcipy/simulator -d "pathToDataFolder" -p "pathToParametersFile" -sm "pathToSignalModel.pkl"`` Then view generated LOG file for analysis @@ -23,6 +23,11 @@ Then view generated LOG file for analysis which simulator will sample EEG responses. Should contain _raw_data.csv_, _triggers.txt_, _parameters.json_ +- `g` : optional glob filter that can be used to select a subset of data. + - Ex. `"*Matrix_Copy*Jan_2024*"` will select all data for all Matrix Copy Phrase sessions recorded in January of 2024 (assuming the BciPy folder naming convention). + - Glob patterns can also include nested directories (ex. `"*/*Matrix_Copy*"`). +- `p` : path to the parameters.json file used to run the simulation. These parameters will be applied to + all raw_data files when loading. - `sm`: the signal model argument is necessary to generate evidence ### Architecture diff --git a/bcipy/simulator/__main__.py b/bcipy/simulator/__main__.py index 4b845a450..34a889d07 100644 --- a/bcipy/simulator/__main__.py +++ b/bcipy/simulator/__main__.py @@ -1,7 +1,7 @@ """ Entry point to run Simulator """ import argparse -import datetime +from glob import glob from pathlib import Path from bcipy.simulator.helpers.sim_runner import MultiSimRunner, SingleSimRunner @@ -9,6 +9,8 @@ from bcipy.simulator.simulator_base import Simulator if __name__ == "__main__": + glob_help = ('glob pattern to select a subset of data folders' + ' Ex. "*RSVP_Copy_Phrase*"') parser = argparse.ArgumentParser() parser.add_argument( "-d", @@ -16,6 +18,7 @@ type=Path, required=True, help="Raw data folders to be processed. Singular wrapper dir with data folders") + parser.add_argument('-g', '--glob_pattern', help=glob_help, default="*") parser.add_argument( "-sm", "--smodel_files", @@ -29,10 +32,17 @@ type=Path, required=True, help="Parameter File to be used") + parser.add_argument("-o", "--out_dir", type=Path, default=Path(__file__).resolve().parent) - args = vars(parser.parse_args()) + args = parser.parse_args() + sim_args = vars(args) - simulator: Simulator = SimulationFactoryV2.create(**args) + sim_args['source_dirs'] = [ + Path(d) for d in glob(str(Path(args.data_folder, args.glob_pattern))) + if Path(d).is_dir() + ] + + simulator: Simulator = SimulationFactoryV2.create(**sim_args) sim_run_count = simulator.get_parameters().get('sim_run_count', 1) diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index db5a89591..1858407be 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -5,8 +5,9 @@ import numpy as np -from bcipy.helpers.language_model import init_language_model, histogram, with_min_prob -from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR +from bcipy.helpers.language_model import (histogram, init_language_model, + with_min_prob) +from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet from bcipy.language import LanguageModel from bcipy.signal.model import SignalModel from bcipy.simulator.helpers.state_manager import SimState @@ -59,7 +60,7 @@ def __init__(self, sm_model_file, parameters): self.signal_model: Optional[SignalModel] = None self.lm_model: LanguageModel = init_language_model(parameters) self.alp = alphabet() - self.backspace_prob: float = 0.05 + self.backspace_prob: float = parameters.get('lm_backspace_prob', 0.05) with open(self.sm_model_file, "rb") as signal_file: self.signal_model = pickle.load(signal_file) diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 4d0705b01..7888d5080 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -4,16 +4,18 @@ import random from abc import ABC from dataclasses import dataclass -from typing import List, Optional, Dict +from typing import Dict, List, Optional import numpy as np from bcipy.helpers.exceptions import FieldException from bcipy.helpers.language_model import histogram from bcipy.helpers.parameters import Parameters -from bcipy.helpers.symbols import alphabet, BACKSPACE_CHAR -from bcipy.simulator.helpers.decision import SimDecisionCriteria, MaxIterationsSim, ProbThresholdSim -from bcipy.simulator.helpers.evidence_fuser import MultiplyFuser, EvidenceFuser +from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet +from bcipy.simulator.helpers.decision import (MaxIterationsSim, + ProbThresholdSim, + SimDecisionCriteria) +from bcipy.simulator.helpers.evidence_fuser import EvidenceFuser, MultiplyFuser from bcipy.simulator.helpers.log_utils import fmt_likelihoods_for_hist from bcipy.simulator.helpers.rsvp_utils import next_target_letter from bcipy.simulator.helpers.types import InquiryResult, SimEvidence @@ -79,7 +81,7 @@ def reset_state(self): class StateManagerImpl(StateManager): def __init__(self, parameters: Parameters, fuser_class=MultiplyFuser): - self.state: SimState = self.initial_state() + self.state: SimState = self.initial_state(parameters) self.parameters = parameters self.fuser_class: EvidenceFuser.__class__ = fuser_class @@ -179,7 +181,7 @@ def reset_state(self): @staticmethod def initial_state(parameters: Parameters = None) -> SimState: - sentence = "HELLO_WORLD" # TODO abstract out with sim_parameters.json + sentence = parameters.get('task_text', "HELLO_WORLD") # TODO abstract out with sim_parameters.json target_symbol = sentence[0] # TODO use parameters.get('spelled_letters_count') default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] init_stimuli = random.sample(alphabet(), 10) diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index 1c931009d..b58c8d1ae 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -3,12 +3,16 @@ from typing import List from bcipy.helpers.load import load_json_parameters -from bcipy.simulator.helpers.data_engine import RawDataEngine, RawDataEngineWrapper -from bcipy.simulator.helpers.metrics import MetricReferee, RefereeImpl, SimMetrics1Handler -from bcipy.simulator.helpers.model_handler import SignalModelHandler1, ModelHandler, \ - SigLmModelHandler1 -from bcipy.simulator.helpers.sampler import Sampler, EEGByLetterSampler -from bcipy.simulator.helpers.state_manager import StateManager, StateManagerImpl +from bcipy.simulator.helpers.data_engine import (RawDataEngine, + RawDataEngineWrapper) +from bcipy.simulator.helpers.metrics import (MetricReferee, RefereeImpl, + SimMetrics1Handler) +from bcipy.simulator.helpers.model_handler import (ModelHandler, + SigLmModelHandler1, + SignalModelHandler1) +from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler +from bcipy.simulator.helpers.state_manager import (StateManager, + StateManagerImpl) from bcipy.simulator.sim import SimulatorCopyPhrase @@ -16,7 +20,7 @@ class SimulationFactoryV2: """ Factory class to create Simulator instances """ @staticmethod - def create(data_folder: str, smodel_files: List[str], + def create(source_dirs: List[Path], smodel_files: List[str], sim_param_path="bcipy/simulator/sim_parameters.json", save_dir=None, **kwargs): # out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) @@ -25,8 +29,8 @@ def create(data_folder: str, smodel_files: List[str], base_parameters = load_json_parameters(kwargs.get('parameters'), value_cast=True) base_parameters.add_missing_items(sim_parameters) - data_engine = RawDataEngineWrapper(data_folder, base_parameters) - state_manager: StateManager = StateManagerImpl(sim_parameters) + data_engine = RawDataEngine(source_dirs, base_parameters) + state_manager: StateManager = StateManagerImpl(base_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) model_handler: ModelHandler = SigLmModelHandler1(model_file, base_parameters) \ if sim_parameters.get("sim_lm_active", 0) == 1 else SignalModelHandler1(model_file) diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index d609044b7..23ca4d955 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -34,7 +34,7 @@ "type": "float" }, "sim_lm_active": { - "value": "0", + "value": "1", "section": "sim_config", "readableName": "is lm active or off", "helpTip": "", From 5576589e3c35badb6efd03e8cb004c3fe36ddea8 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 18 Mar 2024 10:51:57 -0700 Subject: [PATCH 231/330] Added new sampler to sample an Inquiry at a time --- bcipy/simulator/helpers/log_utils.py | 8 +- bcipy/simulator/helpers/sampler.py | 133 ++++++++++++++++++++++++++- 2 files changed, 135 insertions(+), 6 deletions(-) diff --git a/bcipy/simulator/helpers/log_utils.py b/bcipy/simulator/helpers/log_utils.py index 1d7b1ca27..78964f53f 100644 --- a/bcipy/simulator/helpers/log_utils.py +++ b/bcipy/simulator/helpers/log_utils.py @@ -1,4 +1,4 @@ -from typing import List, Dict +from typing import Dict, List import pandas as pd @@ -23,6 +23,12 @@ def format_sample_rows(sample_rows: List[pd.Series]) -> str: index=False, header=True) +def format_sample_df(sample_rows: pd.DataFrame) -> str: + """Returns a tabular representation of the sample rows.""" + return sample_rows.drop(columns=['eeg']).to_string(index=False, + header=True) + + def fmt_reshaped_evidence(evidences: Dict[str, SimEvidence]): """ Formats evidences to log shapes pf ndarrays """ diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index 18b39f430..efb57caa3 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -1,6 +1,9 @@ import logging +import random from abc import ABC -from typing import Callable, List +from collections import defaultdict +from pathlib import Path +from typing import Callable, Dict, List, Tuple import numpy as np import pandas as pd @@ -9,7 +12,8 @@ from bcipy.helpers.parameters import Parameters from bcipy.helpers.symbols import alphabet from bcipy.simulator.helpers.data_engine import RawDataEngine -from bcipy.simulator.helpers.log_utils import format_sample_rows +from bcipy.simulator.helpers.log_utils import (format_sample_df, + format_sample_rows) from bcipy.simulator.helpers.state_manager import SimState log = logging.getLogger(__name__) @@ -27,7 +31,9 @@ def set_reshaper(self, reshaper: Callable): class EEGByLetterSampler(Sampler): - def __init__(self, data_engine: RawDataEngine, parameters: Parameters = None): + def __init__(self, + data_engine: RawDataEngine, + parameters: Parameters = None): self.data_engine: RawDataEngine = data_engine self.parameters: Parameters = self.data_engine.parameters if not parameters else parameters self.model_input_reshaper: Callable = self.__default_reshaper @@ -50,7 +56,8 @@ def sample(self, state: SimState) -> np.ndarray: for symbol in inquiry_letter_subset: is_target = int(symbol == target_letter) # filtered_data = self.data.query(f'target == {is_target} and symbol == "{symbol}"') - filtered_data: pd.DataFrame = self.data.query(f'target == {is_target}') + filtered_data: pd.DataFrame = self.data.query( + f'target == {is_target}') if filtered_data is None or len(filtered_data) == 0: raise TaskConfigurationException( message="No eeg sample found with provided data and query") @@ -68,7 +75,8 @@ def sample(self, state: SimState) -> np.ndarray: def set_reshaper(self, reshaper: Callable): self.model_input_reshaper = reshaper - def __default_reshaper(self, eeg_responses: List[np.ndarray]) -> np.ndarray: + def __default_reshaper(self, + eeg_responses: List[np.ndarray]) -> np.ndarray: # returns (channel_n, trial_n, sample_n) channels_eeg = [[] for i in range(len(eeg_responses[0]))] @@ -79,3 +87,118 @@ def __default_reshaper(self, eeg_responses: List[np.ndarray]) -> np.ndarray: # make sure this returns (7, 10, 90) for tab_test_dynamic return np.array(channels_eeg) + + +def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: + """Default data reshaper. + + Returns + ------- + ndarray with shape (channel_n, trial_n, sample_n) + """ + + channels_eeg = [[] for i in range(len(eeg_responses[0]))] + + for _i, trial_channels_eeg in enumerate(eeg_responses): + for c_i, channel_eeg in enumerate(trial_channels_eeg): + channels_eeg[c_i].append(channel_eeg) + + return np.array(channels_eeg) + + +class InquirySampler(Sampler): + """Samples an inquiry of data at a time.""" + + def __init__(self, data_engine: RawDataEngine, *args, **kwargs): + self.model_input_reshaper = default_reshaper + self.data: pd.DataFrame = data_engine.transform().get_data() + + # map source to inquiry numbers + self.target_inquiries, self.no_target_inquiries = self.prepare_data( + self.data) + + def prepare_data( + self, data: pd.DataFrame + ) -> Tuple[Dict[Path, List[int]], Dict[Path, List[int]]]: + """Partition the data into those inquiries that displayed the target + and those that did not. The resulting data structures map the data + source with a list of inquiry_n numbers.""" + + target_inquiries = defaultdict(list) + no_target_inquiries = defaultdict(list) + + # TODO: there is probably a more optimal way to use pandas to compute. + # Look into groupby. + for source in data['source'].unique(): + source_df = data[data['source'] == source] + for n in source_df['inquiry_n'].unique(): + inquiry_df = source_df[source_df['inquiry_n'] == n] + has_target = inquiry_df[inquiry_df['target'] == + 1]['target'].any() + + if has_target: + target_inquiries[source].append(n) + else: + no_target_inquiries[source].append(n) + + return target_inquiries, no_target_inquiries + + def sample(self, state: SimState) -> np.ndarray: + """Samples a random inquiry for a random data source. + + Ensures that if a target is shown in the current inquiry the sampled + data will be from an inquiry where the target was presented. + + Returns + ------- + nd array (n_channel, n_trial, n_sample) + """ + + target_letter = state.target_symbol + inquiry_letter_subset = state.display_alphabet + + if target_letter in inquiry_letter_subset: + source_inquiries = self.target_inquiries + target_pos = inquiry_letter_subset.index(target_letter) + 1 + else: + source_inquiries = self.no_target_inquiries + target_pos = 0 # unused + + # randomly select a valid data source and inquiry + data_source = random.choice(list(source_inquiries.keys())) + inquiry_n = random.choice(source_inquiries[data_source]) + + # select all trials for the data_source and inquiry + inquiry_df = self.data.loc[(self.data['source'] == data_source) + & (self.data['inquiry_n'] == inquiry_n)] + assert len(inquiry_df) == len( + inquiry_letter_subset), f"Invalid data source {data_source}" + + inq_target_pos = target_pos + if target_letter in inquiry_letter_subset: + inq_target_index = inquiry_df[inquiry_df['target'] == 1].index[0] + inq_target_pos = inquiry_df.index.tolist().index(inq_target_index) + + if inq_target_pos == target_pos: + new_pos = inq_target_pos + elif inq_target_pos < target_pos: + new_pos = target_pos + 0.5 + elif inq_target_pos > target_pos: + new_pos = target_pos - 0.5 + + # define a sort column to move the target in the inquiry to the desired index + sort_pos = inquiry_df['inquiry_pos'].where(inquiry_df['target'] == 0, + new_pos) + + # select the inquiry items in sorted position + sorted_inquiry_df = inquiry_df.loc[sort_pos.sort_values().index] + log.debug(f"EEG Samples: \n {format_sample_df(sorted_inquiry_df)}") + # import pdb; pdb.set_trace() + rows = [ + sorted_inquiry_df.iloc[i] for i in range(len(sorted_inquiry_df)) + ] + eeg_responses = [r['eeg'] for r in rows] + return self.model_input_reshaper(eeg_responses) + + def set_reshaper(self, reshaper: Callable): + self.model_input_reshaper = reshaper From a93b782877c98be86282e9244c136731f1b453ba Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 18 Mar 2024 17:06:01 -0400 Subject: [PATCH 232/330] cleaned up TODO comments --- bcipy/simulator/helpers/data_engine.py | 2 -- bcipy/simulator/helpers/signal_helpers.py | 2 +- bcipy/simulator/helpers/state_manager.py | 14 +++++--------- bcipy/simulator/sim.py | 12 ++++++++++-- 4 files changed, 16 insertions(+), 14 deletions(-) diff --git a/bcipy/simulator/helpers/data_engine.py b/bcipy/simulator/helpers/data_engine.py index 34be48f3a..ff7211c45 100644 --- a/bcipy/simulator/helpers/data_engine.py +++ b/bcipy/simulator/helpers/data_engine.py @@ -56,8 +56,6 @@ class RawDataEngine(DataEngine): """ def __init__(self, source_dirs: List[str], parameters: Parameters): - # TODO read parameters from source dirx - # TODO use os.walk() and take in single source_dir that has all data folders self.source_dirs: List[str] = source_dirs self.parameters: Parameters = parameters self.data: Optional[List[ExtractedExperimentData]] = None diff --git a/bcipy/simulator/helpers/signal_helpers.py b/bcipy/simulator/helpers/signal_helpers.py index 8f511c824..2bf56be77 100644 --- a/bcipy/simulator/helpers/signal_helpers.py +++ b/bcipy/simulator/helpers/signal_helpers.py @@ -21,7 +21,7 @@ @dataclass() -class ExtractedExperimentData: # TODO clean up design +class ExtractedExperimentData: source_dir: str inquiries: np.ndarray trials: np.ndarray diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 7888d5080..0269ffbcd 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -61,7 +61,6 @@ def to_json(self): class StateManager(ABC): - # TODO change evidence type to dictionary or some dataclass def update(self, evidence: Dict[str, SimEvidence]): raise NotImplementedError() @@ -88,8 +87,7 @@ def __init__(self, parameters: Parameters, fuser_class=MultiplyFuser): self.max_inq_len = self.parameters.get('max_inq_len', 100) def is_done(self) -> bool: - # TODO add stoppage criterion, Stoppage criterion is seperate from - # decision. Decision should we go on to next letter or not + # Determines if simulator should end (max inq or max series reached, typed target sentence) return self.state.total_inquiry_count( ) > self.max_inq_len or self.state.target_sentence == self.state.current_sentence or self.state.series_n > 50 @@ -110,7 +108,6 @@ def update(self, evidence) -> InquiryResult: # finding out whether max iterations is hit or prob threshold is hit temp_inquiry_result = InquiryResult(target=self.state.target_symbol, time_spent=0, stimuli=self.state.display_alphabet, - # TODO change to use evidence_dict evidences=evidence, fused_likelihood=fused_likelihood, decision=None) @@ -134,9 +131,8 @@ def update(self, evidence) -> InquiryResult: new_state['series_results'][self.state.series_n].append(new_inquiry_result) if is_decidable: - decision = alphabet()[ - np.argmax( - fused_likelihood)] # deciding the maximum probability symbol TODO abstract + # Deciding max likelihood char + decision = alphabet()[np.argmax(fused_likelihood)] # TODO abstract decision criterion # resetting series new_state['series_n'] += 1 @@ -181,8 +177,8 @@ def reset_state(self): @staticmethod def initial_state(parameters: Parameters = None) -> SimState: - sentence = parameters.get('task_text', "HELLO_WORLD") # TODO abstract out with sim_parameters.json - target_symbol = sentence[0] # TODO use parameters.get('spelled_letters_count') + sentence = parameters.get('task_text', "HELLO_WORLD") + target_symbol = parameters.get('spelled_letters_count', 0) default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] init_stimuli = random.sample(alphabet(), 10) diff --git a/bcipy/simulator/sim.py b/bcipy/simulator/sim.py index d05ba205f..bee346ae4 100644 --- a/bcipy/simulator/sim.py +++ b/bcipy/simulator/sim.py @@ -106,15 +106,23 @@ def run(self): self.save_run() def __make_stimuli(self, state: SimState): - # TODO abstract out + """ + Creates next set of stimuli: + - uses current likelihoods while during a series + - uses language model for beginning of series + - random letters in case of no LM and beginning of series + """ subset_length = 10 val_func: Optional[np.ndarray] = state.get_current_likelihood() always_in_stimuli = [symbols.SPACE_CHAR, symbols.BACKSPACE_CHAR] + # during series if val_func is not None: return stimuli.best_selection(self.symbol_set, list( val_func), subset_length, always_included=always_in_stimuli) - elif self.parameters.get('sim_lm_active', 0) == 1: # use lang model for priors to make stim + # beginning of series + elif self.parameters.get('sim_lm_active', 0) == 1: + # use lang model for priors to make stim lm_model = self.model_handler.get_model('lm') lm_model_evidence = lm_model.predict(list(state.current_sentence)) val_func = format_lm_output(lm_model_evidence, self.symbol_set) From 7614e752828b10c2baa8b7e0c17d4159c037c7ea Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Mar 2024 17:03:24 -0700 Subject: [PATCH 233/330] #187261791 ; refactor acquisition to record using a process rather than a thread to fix segfaults; set a max pause parameter to avoid data issues when LSL's StreamInlet's buffer is too small for the amount of data. --- bcipy/acquisition/protocols/lsl/connect.py | 26 +++++++ bcipy/acquisition/protocols/lsl/lsl_client.py | 77 +++++++++++-------- .../acquisition/protocols/lsl/lsl_recorder.py | 49 +++++++----- .../tests/protocols/lsl/test_lsl_client.py | 6 +- .../tests/protocols/lsl/test_lsl_recorder.py | 12 +-- bcipy/config.py | 1 + .../gui/viewer/data_source/lsl_data_source.py | 3 +- bcipy/helpers/task.py | 50 +++++++----- .../matrix/test_matrix_calibration.py | 11 ++- .../rsvp/calibration/test_rsvp_calibration.py | 13 ++-- 10 files changed, 157 insertions(+), 91 deletions(-) create mode 100644 bcipy/acquisition/protocols/lsl/connect.py diff --git a/bcipy/acquisition/protocols/lsl/connect.py b/bcipy/acquisition/protocols/lsl/connect.py new file mode 100644 index 000000000..96e49ba35 --- /dev/null +++ b/bcipy/acquisition/protocols/lsl/connect.py @@ -0,0 +1,26 @@ +"""Utility functions for connecting to an LSL Stream""" +from typing import Optional + +from pylsl import StreamInfo, resolve_stream + +from bcipy.acquisition.devices import DEFAULT_DEVICE_TYPE, DeviceSpec +from bcipy.acquisition.protocols.lsl.lsl_connector import channel_names + + +def resolve_device_stream( + device_spec: Optional[DeviceSpec] = None) -> StreamInfo: + """Get the LSL stream for the given device.""" + content_type = device_spec.content_type if device_spec else DEFAULT_DEVICE_TYPE + streams = resolve_stream('type', content_type) + if not streams: + raise Exception( + f'LSL Stream not found for content type {content_type}') + return streams[0] + + +def device_from_metadata(metadata: StreamInfo) -> DeviceSpec: + """Create a device_spec from the data stream metadata.""" + return DeviceSpec(name=metadata.name(), + channels=channel_names(metadata), + sample_rate=metadata.nominal_srate(), + content_type=metadata.type()) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index c78f64b90..f8425c571 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -1,24 +1,45 @@ """DataAcquisitionClient for LabStreamingLayer data sources.""" import logging +from multiprocessing import Queue from typing import Dict, List, Optional import pandas as pd -from pylsl import (StreamInfo, StreamInlet, local_clock, resolve_byprop, - resolve_stream) +from pylsl import StreamInlet, local_clock, resolve_byprop -from bcipy.acquisition.devices import (DEFAULT_DEVICE_TYPE, IRREGULAR_RATE, - DeviceSpec) +from bcipy.acquisition.devices import IRREGULAR_RATE, DeviceSpec from bcipy.acquisition.exceptions import InvalidClockError -from bcipy.acquisition.protocols.lsl.lsl_connector import (channel_names, - check_device) +from bcipy.acquisition.protocols.lsl.connect import (device_from_metadata, + resolve_device_stream) +from bcipy.acquisition.protocols.lsl.lsl_connector import check_device from bcipy.acquisition.protocols.lsl.lsl_recorder import LslRecordingThread from bcipy.acquisition.record import Record +from bcipy.config import MAX_PAUSE_SECONDS from bcipy.gui.viewer.ring_buffer import RingBuffer from bcipy.helpers.clock import Clock log = logging.getLogger(__name__) +def time_range(stamps: List[float], + precision: int = 3, + sep: str = " to ") -> str: + """Utility for printing a range of timestamps""" + if stamps: + return "".join([ + str(round(stamps[0], precision)), sep, + str(round(stamps[-1], precision)) + ]) + return "" + + +def request_desc(start: Optional[float], end: Optional[float], + limit: Optional[int]): + """Returns a description of the request which can be logged.""" + start_str = round(start, 3) if start else "None" + end_str = round(end, 3) if end else "None" + return f"Requesting data from: {start_str} to: {end_str} limit: {limit}" + + class LslAcquisitionClient: """Data Acquisition Client for devices streaming data using Lab Streaming Layer. Its primary use is dynamically querying streaming data in realtime, @@ -61,8 +82,6 @@ def __init__(self, def first_sample_time(self) -> float: """Timestamp returned by the first sample. If the data is being recorded this value reflects the timestamp of the first recorded sample""" - if self.recorder: - return self.recorder.first_sample_time return self._first_sample_time @property @@ -86,17 +105,13 @@ def start_acquisition(self) -> bool: if self.inlet: return False - content_type = self.device_spec.content_type if self.device_spec else DEFAULT_DEVICE_TYPE - streams = resolve_stream('type', content_type) - if not streams: - raise Exception( - f'LSL Stream not found for content type {content_type}') - stream_info = streams[0] - + stream_info = resolve_device_stream(self.device_spec) self.inlet = StreamInlet( stream_info, - max_buflen=4 * self.max_buffer_len, # TODO: revisit this value + max_buflen=MAX_PAUSE_SECONDS + 5, max_chunklen=1) + log.info("Acquiring data from data stream:") + log.info(self.inlet.info().as_xml()) if self.device_spec: check_device(self.device_spec, self.inlet.info()) @@ -104,16 +119,22 @@ def start_acquisition(self) -> bool: self.device_spec = device_from_metadata(self.inlet.info()) if self.save_directory: + msg_queue = Queue() self.recorder = LslRecordingThread( - stream_info, - self.save_directory, - self.raw_data_file_name, - self.device_spec) + directory=self.save_directory, + filename=self.raw_data_file_name, + device_spec=self.device_spec, + queue=msg_queue) self.recorder.start() + log.info("Waiting for first sample from lsl_recorder") + self._first_sample_time = msg_queue.get(block=True, timeout=5.0) + log.info(f"First sample time: {self.first_sample_time}") + self.inlet.open_stream(timeout=5.0) if self.max_buffer_len and self.max_buffer_len > 0: self.buffer = RingBuffer(size_max=self.max_samples) - _, self._first_sample_time = self.inlet.pull_sample() + if not self._first_sample_time: + _, self._first_sample_time = self.inlet.pull_sample() return True def stop_acquisition(self) -> None: @@ -178,7 +199,7 @@ def get_data(self, ------- List of Records """ - log.info(f"Requesting data from: {start} to: {end} limit: {limit}") + log.info(request_desc(start, end, limit)) data = self.get_latest_data() if not data: @@ -223,12 +244,12 @@ def _pull_chunk(self) -> int: """Pull a chunk of samples from LSL and record in the buffer. Returns the count of samples pulled. """ - log.debug(f"Pulling from LSL (max_samples: {self.max_samples})") + log.debug(f"\tPulling chunk (max_samples: {self.max_samples})") # A timeout of 0.0 gets currently available samples without blocking. samples, timestamps = self.inlet.pull_chunk( timeout=0.0, max_samples=self.max_samples) count = len(samples) - log.debug(f"\tReceived {count} samples") + log.debug(f"\t-> received {count} samples: {time_range(timestamps)}") for sample, stamp in zip(samples, timestamps): self.buffer.append(Record(sample, stamp)) return count @@ -357,11 +378,3 @@ def discover_device_spec(content_type: str) -> DeviceSpec: spec = device_from_metadata(inlet.info()) inlet.close_stream() return spec - - -def device_from_metadata(metadata: StreamInfo) -> DeviceSpec: - """Create a device_spec from the data stream metadata.""" - return DeviceSpec(name=metadata.name(), - channels=channel_names(metadata), - sample_rate=metadata.nominal_srate(), - content_type=metadata.type()) diff --git a/bcipy/acquisition/protocols/lsl/lsl_recorder.py b/bcipy/acquisition/protocols/lsl/lsl_recorder.py index f877a15f5..2846d0ee1 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_recorder.py +++ b/bcipy/acquisition/protocols/lsl/lsl_recorder.py @@ -1,15 +1,18 @@ """Records LSL data streams to a data store.""" import logging import time +from multiprocessing import Queue from pathlib import Path -from typing import Optional, List +from typing import List, Optional from pylsl import StreamInfo, StreamInlet, resolve_streams from bcipy.acquisition.devices import DeviceSpec +from bcipy.acquisition.protocols.lsl.connect import (device_from_metadata, + resolve_device_stream) from bcipy.acquisition.protocols.lsl.lsl_connector import (channel_names, check_device) -from bcipy.acquisition.util import StoppableThread +from bcipy.acquisition.util import StoppableProcess from bcipy.helpers.raw_data import RawDataWriter log = logging.getLogger(__name__) @@ -39,8 +42,9 @@ def start(self) -> None: log.info("Recording data") # create a thread for each. self.streams = [ - LslRecordingThread(stream, self.path, - self.filenames.get(stream.type(), None)) + LslRecordingThread(device_spec=device_from_metadata(StreamInlet(stream).info()), + directory=self.path, + filename=self.filenames.get(stream.type(), None)) for stream in resolve_streams() ] @@ -65,29 +69,30 @@ def stop(self, wait: bool = False) -> None: self.streams = None -class LslRecordingThread(StoppableThread): +class LslRecordingThread(StoppableProcess): """Records data for the given LabStreamingLayer (LSL) data stream. Parameters: ---------- - - stream : information about the stream of interest + - device_spec : DeviceSpec ; specifies the device from which to record. - directory : location to store the recording - filename : optional, name of the data file. - - device_spec : optional DeviceSpec ; if provided channel labels will come - from here. + - queue : optional multiprocessing queue; if provided the first_sample_time + will be written here when available. """ writer: RawDataWriter = None def __init__(self, - stream_info: StreamInfo, - directory: str, + device_spec: DeviceSpec, + directory: Optional[str] = '.', filename: Optional[str] = None, - device_spec: Optional[DeviceSpec] = None) -> None: + queue: Optional[Queue] = None) -> None: super().__init__() - self.stream_info = stream_info + self.directory = directory self.device_spec = device_spec + self.queue = queue self.sample_count = 0 # see: https://labstreaminglayer.readthedocs.io/info/faqs.html#chunk-sizes @@ -102,8 +107,8 @@ def __init__(self, def default_filename(self): """Default filename to use if a name is not provided.""" - content_type = '_'.join(self.stream_info.type().split()).lower() - name = '_'.join(self.stream_info.name().split()).lower() + content_type = '_'.join(self.device_spec.content_type.split()).lower() + name = '_'.join(self.device_spec.name.split()).lower() return f"{content_type}_data_{name}.csv" @property @@ -132,8 +137,8 @@ def _init_data_writer(self, stream_info: StreamInfo) -> None: log.info(f"Writing data to {path}") self.writer = RawDataWriter( path, - daq_type=self.stream_info.name(), - sample_rate=self.stream_info.nominal_srate(), + daq_type=stream_info.name(), + sample_rate=stream_info.nominal_srate(), columns=['timestamp'] + channels + ['lsl_timestamp']) self.writer.__enter__() @@ -152,7 +157,6 @@ def _write_chunk(self, data: List, timestamps: List) -> None: timestamps : list of timestamps """ assert self.writer, "Writer not initialized" - chunk = [] for i, sample in enumerate(data): self.sample_count += 1 @@ -178,6 +182,8 @@ def _pull_chunk(self, inlet: StreamInlet) -> int: if timestamps and data: if not self.first_sample_time: self.first_sample_time = timestamps[0] + if self.queue: + self.queue.put(self.first_sample_time, timeout=2.0) self.last_sample_time = timestamps[-1] self._write_chunk(data, timestamps) return len(timestamps) @@ -194,11 +200,12 @@ def run(self): given interval, and persists the results. This happens continuously until the `stop()` method is called. """ - # Note that self.stream_info does not have the channel names. - inlet = StreamInlet(self.stream_info, max_chunklen=1) + # Note that stream_info does not have the channel names. + stream_info = resolve_device_stream(self.device_spec) + inlet = StreamInlet(stream_info, max_chunklen=1) full_metadata = inlet.info() - log.info("Acquiring data from data stream:") + log.info("Recording data from data stream:") log.info(full_metadata.as_xml()) self._reset() @@ -219,7 +226,7 @@ def run(self): while record_count == self.max_chunk_size: record_count = self._pull_chunk(inlet) - log.info(f"Ending data stream recording for {self.stream_info.name()}") + log.info(f"Ending data stream recording for {stream_info.name()}") log.info(f"Total recorded seconds: {self.recorded_seconds}") log.info(f"Total recorded samples: {self.sample_count}") inlet.close_stream() diff --git a/bcipy/acquisition/tests/protocols/lsl/test_lsl_client.py b/bcipy/acquisition/tests/protocols/lsl/test_lsl_client.py index 67d0ea358..54d5bc89d 100644 --- a/bcipy/acquisition/tests/protocols/lsl/test_lsl_client.py +++ b/bcipy/acquisition/tests/protocols/lsl/test_lsl_client.py @@ -150,12 +150,14 @@ def test_with_recording(self): """Test that recording works.""" temp_dir = tempfile.mkdtemp() - path = Path(temp_dir, f'eeg_data_{DEVICE_NAME.lower()}.csv') + filename = f'eeg_data_{DEVICE_NAME.lower()}.csv' + path = Path(temp_dir, filename) self.assertFalse(path.exists()) client = LslAcquisitionClient(max_buffer_len=1, - save_directory=temp_dir) + save_directory=temp_dir, + raw_data_file_name=filename) client.start_acquisition() time.sleep(0.1) client.stop_acquisition() diff --git a/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py b/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py index 527b906f9..2db91b78a 100644 --- a/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py +++ b/bcipy/acquisition/tests/protocols/lsl/test_lsl_recorder.py @@ -7,7 +7,8 @@ import pytest from bcipy.acquisition.datastream.lsl_server import LslDataServer -from bcipy.acquisition.datastream.mock.eye_tracker_server import eye_tracker_server +from bcipy.acquisition.datastream.mock.eye_tracker_server import \ + eye_tracker_server from bcipy.acquisition.devices import preconfigured_device from bcipy.acquisition.protocols.lsl.lsl_recorder import LslRecorder from bcipy.helpers.raw_data import TIMESTAMP_COLUMN, load @@ -16,6 +17,7 @@ DEVICE = preconfigured_device(DEVICE_NAME) +@pytest.mark.slow class TestLslRecorder(unittest.TestCase): """Main Test class for LslRecorder code.""" @@ -39,13 +41,14 @@ def setUp(self): def test_recorder(self): """Test basic recording functionality""" - path = Path(self.temp_dir, f'eeg_data_{DEVICE_NAME.lower()}.csv') - recorder = LslRecorder(path=self.temp_dir) + filename = f'eeg_data_{DEVICE_NAME.lower()}.csv' + path = Path(self.temp_dir, filename) + recorder = LslRecorder(path=self.temp_dir, filenames={'EEG': filename}) self.assertFalse(path.exists()) recorder.start() time.sleep(0.1) - self.assertTrue(path.exists()) recorder.stop(wait=True) + self.assertTrue(path.exists()) raw_data = load(path) self.assertEqual(raw_data.daq_type, DEVICE_NAME) @@ -54,7 +57,6 @@ def test_recorder(self): self.assertEqual(raw_data.columns[0], TIMESTAMP_COLUMN) self.assertEqual(raw_data.columns[1:-1], DEVICE.channels) self.assertEqual(raw_data.columns[-1], 'lsl_timestamp') - self.assertTrue(len(raw_data.rows) > 0) def test_multiple_sources(self): """Test that recorder works with multiple sources and can be customized diff --git a/bcipy/config.py b/bcipy/config.py index db85fe06c..c630c0fae 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -51,5 +51,6 @@ # misc configuration WAIT_SCREEN_MESSAGE = 'Press Space to start or Esc to exit' +MAX_PAUSE_SECONDS = 360 SESSION_COMPLETE_MESSAGE = 'Complete! Saving data...' REMOTE_SERVER = "https://github.com/CAMBI-tech/BciPy/" diff --git a/bcipy/gui/viewer/data_source/lsl_data_source.py b/bcipy/gui/viewer/data_source/lsl_data_source.py index d0e27b8f1..3ef2a4821 100644 --- a/bcipy/gui/viewer/data_source/lsl_data_source.py +++ b/bcipy/gui/viewer/data_source/lsl_data_source.py @@ -1,6 +1,7 @@ """Streams data from pylsl and puts it into a Queue.""" import pylsl -from bcipy.acquisition.protocols.lsl.lsl_client import device_from_metadata + +from bcipy.acquisition.protocols.lsl.connect import device_from_metadata from bcipy.gui.viewer.data_source.data_source import DataSource diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index 07a1b401e..c7653ed67 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -1,13 +1,14 @@ import logging import random -from typing import Optional, Any, Dict, List, Tuple, Union +import time +from typing import Any, Dict, List, Optional, Tuple, Union import numpy as np from psychopy import core, event, visual from bcipy.acquisition.multimodal import ClientManager, ContentType from bcipy.acquisition.record import Record -from bcipy.config import SESSION_COMPLETE_MESSAGE +from bcipy.config import MAX_PAUSE_SECONDS, SESSION_COMPLETE_MESSAGE from bcipy.helpers.clock import Clock from bcipy.helpers.stimuli import get_fixation from bcipy.task.exceptions import InsufficientDataException @@ -314,38 +315,45 @@ def get_user_input(window, message, color, first_run=False): Parameters ---------- - window[psychopy task window]: task window. *assumes wait_screen method + message: message to display in the wait screen + color: wait screen color + first_run: the first_run will always pause. Returns ------- - True/False: whether or not to stop a trial (based on escape key). + True to continue the task, False to stop and exit. """ - if not first_run: - pause = False - # check user input to make sure we should be going + if first_run: + return pause_on_wait_screen(window, message, color) + else: keys = event.getKeys(keyList=['space', 'escape']) - if keys: - # pause? if keys[0] == 'space': - pause = True - - # escape? + return pause_on_wait_screen(window, message, color) if keys[0] == 'escape': return False + return True - else: - pause = True - while pause: - window.wait_screen(message, color) - keys = event.getKeys(keyList=['space', 'escape']) +def pause_on_wait_screen(window, message, color) -> bool: + """Pause on the wait screen until the user presses the Space key to resume, + or the Escape key to exit. - if keys: - if keys[0] == 'escape': - return False - pause = False + Returns + ------- + True to resume; False to exit. + """ + pause_start = time.time() + window.wait_screen(message, color) + keys = event.waitKeys(keyList=['space', 'escape']) + + elapsed_seconds = time.time() - pause_start + if elapsed_seconds >= MAX_PAUSE_SECONDS: + log.info("Pause exceeded the allowed time. Ending task.") + return False + if keys[0] == 'escape': + return False return True diff --git a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py index 7109ed5a3..f9bd4b24f 100644 --- a/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py +++ b/bcipy/task/tests/paradigm/matrix/test_matrix_calibration.py @@ -1,9 +1,9 @@ import unittest -from mockito import any, mock, unstub, verify, when -from mock import mock_open, patch -import psychopy import numpy as np +import psychopy +from mock import mock_open, patch +from mockito import any, mock, unstub, verify, when import bcipy.task.paradigm.matrix.calibration from bcipy.acquisition import LslAcquisitionClient @@ -112,7 +112,10 @@ def setUp(self): when(TriggerHandler).add_triggers(any()).thenReturn() - when(psychopy.event).getKeys(keyList=any()).thenReturn(['space']) + when(psychopy.event).getKeys(keyList=['space', 'escape'], + modifiers=False, + timeStamped=False).thenReturn(['space']) + when(psychopy.event).getKeys(keyList=['space', 'escape']).thenReturn(['space']) when(psychopy.core).wait(any()).thenReturn(None) def tearDown(self): diff --git a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py index 66cfa1cc9..8f6f10f52 100644 --- a/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py +++ b/bcipy/task/tests/paradigm/rsvp/calibration/test_rsvp_calibration.py @@ -1,9 +1,8 @@ import unittest -from mockito import any, mock, unstub, verify, when -from mock import mock_open, patch - import psychopy +from mock import mock_open, patch +from mockito import any, mock, unstub, verify, when import bcipy.task.paradigm.rsvp.calibration.calibration from bcipy.acquisition import LslAcquisitionClient @@ -11,7 +10,8 @@ from bcipy.acquisition.multimodal import ContentType from bcipy.helpers.parameters import Parameters from bcipy.helpers.triggers import TriggerHandler, TriggerType -from bcipy.task.paradigm.rsvp.calibration.calibration import RSVPCalibrationTask +from bcipy.task.paradigm.rsvp.calibration.calibration import \ + RSVPCalibrationTask class TestRSVPCalibration(unittest.TestCase): @@ -111,7 +111,10 @@ def setUp(self): when(TriggerHandler).write().thenReturn() when(TriggerHandler).add_triggers(any()).thenReturn() - when(psychopy.event).getKeys(keyList=any()).thenReturn(['space']) + when(psychopy.event).getKeys(keyList=['space', 'escape'], + modifiers=False, + timeStamped=False).thenReturn(['space']) + when(psychopy.event).getKeys(keyList=['space', 'escape']).thenReturn(['space']) when(psychopy.core).wait(any()).thenReturn(None) def tearDown(self): From 9e9edaa7d5cc4866ecf93d56cf785135118fdc0a Mon Sep 17 00:00:00 2001 From: lawhead Date: Fri, 22 Mar 2024 17:04:07 -0700 Subject: [PATCH 234/330] Added script to demonstrate LSL buffering issue and to test against future versions of the library --- scripts/python/lsl_buffer_test.py | 92 +++++++++++++++++++++++++++++++ 1 file changed, 92 insertions(+) create mode 100644 scripts/python/lsl_buffer_test.py diff --git a/scripts/python/lsl_buffer_test.py b/scripts/python/lsl_buffer_test.py new file mode 100644 index 000000000..426b9137d --- /dev/null +++ b/scripts/python/lsl_buffer_test.py @@ -0,0 +1,92 @@ +"""Example to demonstrate behavior when the StreamInlet max_buflen is exceeded. + +Prior to running, start a data streamer, such as the SendData.py example +script included in pylsl. + +Example usage: +$ python3 lsl_buffer_test.py --buffer=1 --seconds=2 +""" + +import time + +from pylsl import StreamInlet, resolve_stream + + +def pull_all_data(inlet: StreamInlet, max_samples: int) -> None: + """Pull all buffered data in the given stream inlet.""" + + print("\nPulling buffered data:") + count = pull_chunk(inlet, max_samples) + while count == max_samples: + count = pull_chunk(inlet, max_samples) + + +def pull_chunk(inlet: StreamInlet, max_samples: int) -> int: + """Pull a chunk of samples from a stream inlet. + Returns the count of samples pulled.""" + + _chunk, timestamps = inlet.pull_chunk(timeout=0.0, max_samples=max_samples) + count = len(timestamps) + + time_range = "" + if timestamps: + time_range = f"{round(timestamps[0], 3)} to {round(timestamps[-1], 3)}" + + print(f"-> pulled {count} samples: {time_range};", + f"sorted: {timestamps == sorted(timestamps)}") + + return count + + +def main(max_buflen: int, max_samples: int, sleep_seconds: int) -> None: + """Continuously read from a StreamInlet, pausing for a given time between + reads and then consuming all data in the stream. + + Parameters + ---------- + max_buflen - StreamInlet max_buflen; buffer size in seconds + max_samples - maximum samples to pull in a single chunk + sleep_seconds - seconds to sleep between data pulls + """ + + # first resolve an EEG stream on the lab network + print("looking for an EEG stream...") + streams = resolve_stream('type', 'EEG') + + # create a new inlet to read from the stream + print("\n---") + print(f"max_buflen seconds: {max_buflen}") + print(f"max_samples: {max_samples}") + print(f"sleep_seconds: {sleep_seconds}") + print("---") + inlet = StreamInlet(streams[0], max_buflen=max_buflen) + + while True: + # pull all available samples + pull_all_data(inlet, max_samples) + time.sleep(sleep_seconds) + + +if __name__ == '__main__': + import argparse + + parser = argparse.ArgumentParser() + parser.add_argument('-b', + '--buffer', + help='StreamInlet max_buflen (seconds)', + default=360, + type=int) + parser.add_argument('-c', + '--chunk', + help='Maximum samples per chunk', + default=1024, + type=int) + parser.add_argument('-s', + '--seconds', + help='Seconds to sleep between data pulls', + default=2, + type=int) + args = parser.parse_args() + main(max_buflen=args.buffer, + max_samples=args.chunk, + sleep_seconds=args.seconds) From 013fb71750be9252996ed76c6ebb6e9fe28446c5 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 25 Mar 2024 12:25:42 -0700 Subject: [PATCH 235/330] Renamed variables for clarity; added documentation --- bcipy/simulator/helpers/sampler.py | 41 +++++++++++++++++++----------- 1 file changed, 26 insertions(+), 15 deletions(-) diff --git a/bcipy/simulator/helpers/sampler.py b/bcipy/simulator/helpers/sampler.py index efb57caa3..439eecfa3 100644 --- a/bcipy/simulator/helpers/sampler.py +++ b/bcipy/simulator/helpers/sampler.py @@ -109,7 +109,7 @@ def default_reshaper(eeg_responses: List[np.ndarray]) -> np.ndarray: class InquirySampler(Sampler): """Samples an inquiry of data at a time.""" - def __init__(self, data_engine: RawDataEngine, *args, **kwargs): + def __init__(self, data_engine: RawDataEngine): self.model_input_reshaper = default_reshaper self.data: pd.DataFrame = data_engine.transform().get_data() @@ -159,10 +159,10 @@ def sample(self, state: SimState) -> np.ndarray: if target_letter in inquiry_letter_subset: source_inquiries = self.target_inquiries - target_pos = inquiry_letter_subset.index(target_letter) + 1 + target_position = inquiry_letter_subset.index(target_letter) + 1 else: source_inquiries = self.no_target_inquiries - target_pos = 0 # unused + target_position = 0 # unused # randomly select a valid data source and inquiry data_source = random.choice(list(source_inquiries.keys())) @@ -174,26 +174,37 @@ def sample(self, state: SimState) -> np.ndarray: assert len(inquiry_df) == len( inquiry_letter_subset), f"Invalid data source {data_source}" - inq_target_pos = target_pos + # The inquiry may need to be re-ordered to ensure that the target is in + # the correct position. We do this by sorting the dataframe on a custom + # column that is the inquiry_pos for all non-targets, and the + # new_target_position for the target. + inquiry_target_position = target_position if target_letter in inquiry_letter_subset: - inq_target_index = inquiry_df[inquiry_df['target'] == 1].index[0] - inq_target_pos = inquiry_df.index.tolist().index(inq_target_index) - - if inq_target_pos == target_pos: - new_pos = inq_target_pos - elif inq_target_pos < target_pos: - new_pos = target_pos + 0.5 - elif inq_target_pos > target_pos: - new_pos = target_pos - 0.5 + inquiry_target_index = inquiry_df[inquiry_df['target'] == 1].index[0] + inquiry_target_position = inquiry_df.index.tolist().index(inquiry_target_index) + + if inquiry_target_position == target_position: + # target already in the correct location, no need to adjust + new_target_position = inquiry_target_position + elif inquiry_target_position < target_position: + # target in the inquiry needs to be pushed later in the inquiry; + # There is another symbol currently at that position, so we need + # to ensure that the target is past that symbol (by adding 0.5). + new_target_position = target_position + 0.5 + elif inquiry_target_position > target_position: + # the target in the inquiry needs to be moved earlier in the inquiry; + # there is another non-target symbol currently at that position so + # the target needs to be moved before that symbol. + new_target_position = target_position - 0.5 # define a sort column to move the target in the inquiry to the desired index sort_pos = inquiry_df['inquiry_pos'].where(inquiry_df['target'] == 0, - new_pos) + new_target_position) # select the inquiry items in sorted position sorted_inquiry_df = inquiry_df.loc[sort_pos.sort_values().index] log.debug(f"EEG Samples: \n {format_sample_df(sorted_inquiry_df)}") - # import pdb; pdb.set_trace() + rows = [ sorted_inquiry_df.iloc[i] for i in range(len(sorted_inquiry_df)) ] From 9b909a63c58804c1cace50725191d402653aff74 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 25 Mar 2024 15:26:27 -0400 Subject: [PATCH 236/330] starting state bug --- bcipy/simulator/helpers/state_manager.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bcipy/simulator/helpers/state_manager.py b/bcipy/simulator/helpers/state_manager.py index 0269ffbcd..74eefbd79 100644 --- a/bcipy/simulator/helpers/state_manager.py +++ b/bcipy/simulator/helpers/state_manager.py @@ -178,7 +178,7 @@ def reset_state(self): @staticmethod def initial_state(parameters: Parameters = None) -> SimState: sentence = parameters.get('task_text', "HELLO_WORLD") - target_symbol = parameters.get('spelled_letters_count', 0) + target_symbol = sentence[parameters.get('spelled_letters_count', 0)] default_criterion: List[SimDecisionCriteria] = [MaxIterationsSim(50), ProbThresholdSim(0.8)] init_stimuli = random.sample(alphabet(), 10) From 29e1ab2bbde38eb688da5c33438d51f71f74b0d8 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Mon, 25 Mar 2024 15:38:34 -0400 Subject: [PATCH 237/330] LM always on. Read lm_type from sim_parameters.json --- bcipy/helpers/language_model.py | 2 ++ bcipy/simulator/helpers/model_handler.py | 35 ++++++++++++++++++++++-- bcipy/simulator/sim_factory.py | 11 ++++---- bcipy/simulator/sim_parameters.json | 25 +++++++++-------- 4 files changed, 53 insertions(+), 20 deletions(-) diff --git a/bcipy/helpers/language_model.py b/bcipy/helpers/language_model.py index 0c9d87d7c..1c8c1f363 100644 --- a/bcipy/helpers/language_model.py +++ b/bcipy/helpers/language_model.py @@ -49,6 +49,8 @@ def init_language_model(parameters: dict) -> LanguageModel: # select the relevant parameters into a dict. params = {key: parameters[key] for key in args & parameters.keys()} + breakpoint() + return model(response_type=ResponseType.SYMBOL, symbol_set=alphabet(parameters), **params) diff --git a/bcipy/simulator/helpers/model_handler.py b/bcipy/simulator/helpers/model_handler.py index 1858407be..21de3e1c2 100644 --- a/bcipy/simulator/helpers/model_handler.py +++ b/bcipy/simulator/helpers/model_handler.py @@ -6,13 +6,14 @@ import numpy as np from bcipy.helpers.language_model import (histogram, init_language_model, - with_min_prob) + with_min_prob, language_models_by_name) from bcipy.helpers.symbols import BACKSPACE_CHAR, alphabet -from bcipy.language import LanguageModel +from bcipy.language import LanguageModel, ResponseType from bcipy.signal.model import SignalModel from bcipy.simulator.helpers.state_manager import SimState from bcipy.simulator.helpers.types import SimEvidence from bcipy.task.data import EvidenceType +import inspect log = logging.getLogger(__name__) @@ -47,6 +48,33 @@ def get_model(self, key=None): return self.signal_model +def sim_init_lm(parameters) -> LanguageModel: + """ + Init Language Model configured in the sim parameters. + Mostly copied from language_model.init_lang_model + + Parameters + ---------- + parameters : dict + configuration details and path locations + + Returns + ------- + instance of a LanguageModel + """ + + lm_classes = language_models_by_name() + model_class: LanguageModel.__class__ = lm_classes[parameters.get("sim_lm_type", "UNIFORM")] + # introspect the model arguments to determine what parameters to pass. + args = inspect.signature(model_class).parameters.keys() + + # select the relevant parameters into a dict. + params = {key: parameters[key] for key in args & parameters.keys()} + return model_class(response_type=ResponseType.SYMBOL, + symbol_set=alphabet(parameters), + **params) + + class SigLmModelHandler1(ModelHandler): def __init__(self, sm_model_file, parameters): @@ -58,7 +86,8 @@ def __init__(self, sm_model_file, parameters): """ self.sm_model_file = sm_model_file self.signal_model: Optional[SignalModel] = None - self.lm_model: LanguageModel = init_language_model(parameters) + self.lm_model: LanguageModel = sim_init_lm(parameters) + log.info(f"Language Model Type: {self.lm_model.name()}") self.alp = alphabet() self.backspace_prob: float = parameters.get('lm_backspace_prob', 0.05) diff --git a/bcipy/simulator/sim_factory.py b/bcipy/simulator/sim_factory.py index b58c8d1ae..4b5208b05 100644 --- a/bcipy/simulator/sim_factory.py +++ b/bcipy/simulator/sim_factory.py @@ -1,15 +1,14 @@ """ Factory for Simulator objects """ +import logging from pathlib import Path from typing import List from bcipy.helpers.load import load_json_parameters -from bcipy.simulator.helpers.data_engine import (RawDataEngine, - RawDataEngineWrapper) +from bcipy.simulator.helpers.data_engine import (RawDataEngine) from bcipy.simulator.helpers.metrics import (MetricReferee, RefereeImpl, SimMetrics1Handler) from bcipy.simulator.helpers.model_handler import (ModelHandler, - SigLmModelHandler1, - SignalModelHandler1) + SigLmModelHandler1, ) from bcipy.simulator.helpers.sampler import EEGByLetterSampler, Sampler from bcipy.simulator.helpers.state_manager import (StateManager, StateManagerImpl) @@ -24,6 +23,7 @@ def create(source_dirs: List[Path], smodel_files: List[str], sim_param_path="bcipy/simulator/sim_parameters.json", save_dir=None, **kwargs): # out_dir = kwargs.get('out_dir', Path(__file__).resolve().parent) + # combining parameters model_file = Path(smodel_files.pop()) sim_parameters = load_json_parameters(sim_param_path, value_cast=True) base_parameters = load_json_parameters(kwargs.get('parameters'), value_cast=True) @@ -32,8 +32,7 @@ def create(source_dirs: List[Path], smodel_files: List[str], data_engine = RawDataEngine(source_dirs, base_parameters) state_manager: StateManager = StateManagerImpl(base_parameters) sampler: Sampler = EEGByLetterSampler(data_engine) - model_handler: ModelHandler = SigLmModelHandler1(model_file, base_parameters) \ - if sim_parameters.get("sim_lm_active", 0) == 1 else SignalModelHandler1(model_file) + model_handler: ModelHandler = SigLmModelHandler1(model_file, base_parameters) referee: MetricReferee = RefereeImpl(metric_handlers={'basic': SimMetrics1Handler()}) sim = SimulatorCopyPhrase(data_engine, model_handler, sampler, state_manager, referee, diff --git a/bcipy/simulator/sim_parameters.json b/bcipy/simulator/sim_parameters.json index 23ca4d955..7a5964642 100644 --- a/bcipy/simulator/sim_parameters.json +++ b/bcipy/simulator/sim_parameters.json @@ -33,17 +33,6 @@ ], "type": "float" }, - "sim_lm_active": { - "value": "1", - "section": "sim_config", - "readableName": "is lm active or off", - "helpTip": "", - "recommended_values": [ - "0", - "1" - ], - "type": "int" - }, "sim_lm_parameters": { "value": "", "section": "sim_config", @@ -54,6 +43,20 @@ ], "type": "str" }, + "sim_lm_type": { + "value": "UNIFORM", + "section": "sim_config", + "readableName": "Language Model Type", + "helpTip": "Specifies which language model to use. Default: UNIFORM", + "recommended_values": [ + "UNIFORM", + "CAUSAL", + "KENLM", + "MIXTURE", + "ORACLE" + ], + "type": "str" + }, "sim_run_count": { "value": "1", "section": "sim_config", From aa874882c0a6a71c3daa0a3b59df5bf7cc956ec7 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Thu, 4 Apr 2024 19:24:25 -0400 Subject: [PATCH 238/330] incorrect decisions metric --- bcipy/simulator/helpers/metrics.py | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/bcipy/simulator/helpers/metrics.py b/bcipy/simulator/helpers/metrics.py index 91c08f901..c016c2a12 100644 --- a/bcipy/simulator/helpers/metrics.py +++ b/bcipy/simulator/helpers/metrics.py @@ -15,6 +15,7 @@ class SimMetrics1: total_series: int = 0 total_inquiries: int = 0 total_decisions: int = 0 + total_incorrect_decisions: int = -1 # negative one if uncalculated total_time_spent: float = 0.0 inquiries_per_selection: float = 0.0 @@ -50,10 +51,13 @@ class SimMetrics1Handler(RefereeHandler): def handle(self, sim) -> Dict[str, Any]: state: SimState = getattr(sim, "state_manager").get_state() - # calculating total decisions made + # calculating total decisions made and total incorrect decisions flattened_inquiries: List[InquiryResult] = reduce(lambda l1, l2: l1 + l2, state.series_results, []) - total_decisions = len(list(filter(lambda inq: bool(inq.decision), flattened_inquiries))) + inqs_with_decisions = list(filter(lambda inq: bool(inq.decision), flattened_inquiries)) + total_decisions = len(inqs_with_decisions) + total_incorrect_decisions = len([inq for inq in inqs_with_decisions if + inq.decision != inq.target]) # average number of inqs before a decision inq_counts = [] @@ -73,7 +77,8 @@ def handle(self, sim) -> Dict[str, Any]: ret = SimMetrics1(total_series=total_series, total_inquiries=total_inquiries, total_decisions=total_decisions, total_time_spent=total_time_spent, - inquiries_per_selection=inquiries_per_selection) + inquiries_per_selection=inquiries_per_selection, + total_incorrect_decisions=total_incorrect_decisions) return dataclasses.asdict(ret) From 9a2f4589d7fed7f240022ee03bc74089a1232bc2 Mon Sep 17 00:00:00 2001 From: sreekaroo Date: Thu, 4 Apr 2024 19:52:50 -0400 Subject: [PATCH 239/330] ReadMe updates --- bcipy/simulator/README.md | 25 +++++++++++++++++++------ 1 file changed, 19 insertions(+), 6 deletions(-) diff --git a/bcipy/simulator/README.md b/bcipy/simulator/README.md index 3db647f65..3bde0493b 100644 --- a/bcipy/simulator/README.md +++ b/bcipy/simulator/README.md @@ -13,16 +13,14 @@ live session. module from shell as such: -``python3 bcipy/simulator -d "pathToDataFolder" -p "pathToParametersFile" -sm "pathToSignalModel.pkl"`` +``python3 bcipy/simulator -d "pathToDataFolderWrapper" -p "pathToParametersFile" -sm "pathToSignalModel.pkl"`` -Then view generated LOG file for analysis +Then view the appropriate output folder for LOG file(s) and metrics. #### Program Args -- `d` : the data folder argument is necessary. This data will be used to construct data pool from - which simulator will - sample EEG responses. Should contain - _raw_data.csv_, _triggers.txt_, _parameters.json_ +- `d` : the data wrapper folder argument is necessary. This folder is expected to contain 1 or more session folders. Each session folder should contain + _raw_data.csv_, _triggers.txt_, _parameters.json_. These files will be used to construct data pool from which simulator will sample EEG responses. - `g` : optional glob filter that can be used to select a subset of data. - Ex. `"*Matrix_Copy*Jan_2024*"` will select all data for all Matrix Copy Phrase sessions recorded in January of 2024 (assuming the BciPy folder naming convention). - Glob patterns can also include nested directories (ex. `"*/*Matrix_Copy*"`). @@ -30,6 +28,21 @@ Then view generated LOG file for analysis all raw_data files when loading. - `sm`: the signal model argument is necessary to generate evidence +#### Sim Output Details + +Output folders are generally located at [simulator/generated](). + +- `result.json` captures metrics from the simulation and all the state from the simulation (like _session.json_) +- `parameters.json` captures params used, a combination of parameters inputted by you and the `sim_parameters.json` +- Single run Folder name: _SIM_month-day-hour:min_hash_ +- Multi Run Folder name: _SIM_MULTI_runCount_month-day-hour:min_ + + +#### Configuring Parameters + +There are various parameters that you can tweak in `sim_parameters.json` to run simulator multiple times with the same args, specify lang_model type ... + + ### Architecture ![simDiagram.png](res/simDiagram.png) From b57464a64ca6b387c49c3ac8bed0156e2f4a3c2d Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 29 Apr 2024 15:20:58 -0700 Subject: [PATCH 240/330] Refactoring for clarity and debugging --- bcipy/acquisition/protocols/lsl/lsl_client.py | 11 +++++++---- bcipy/config.py | 2 +- bcipy/helpers/task.py | 2 +- 3 files changed, 9 insertions(+), 6 deletions(-) diff --git a/bcipy/acquisition/protocols/lsl/lsl_client.py b/bcipy/acquisition/protocols/lsl/lsl_client.py index f8425c571..86d0dbe1a 100644 --- a/bcipy/acquisition/protocols/lsl/lsl_client.py +++ b/bcipy/acquisition/protocols/lsl/lsl_client.py @@ -19,6 +19,8 @@ log = logging.getLogger(__name__) +LSL_TIMEOUT = 5.0 # seconds + def time_range(stamps: List[float], precision: int = 3, @@ -108,7 +110,7 @@ def start_acquisition(self) -> bool: stream_info = resolve_device_stream(self.device_spec) self.inlet = StreamInlet( stream_info, - max_buflen=MAX_PAUSE_SECONDS + 5, + max_buflen=MAX_PAUSE_SECONDS, max_chunklen=1) log.info("Acquiring data from data stream:") log.info(self.inlet.info().as_xml()) @@ -127,10 +129,11 @@ def start_acquisition(self) -> bool: queue=msg_queue) self.recorder.start() log.info("Waiting for first sample from lsl_recorder") - self._first_sample_time = msg_queue.get(block=True, timeout=5.0) + self._first_sample_time = msg_queue.get(block=True, + timeout=LSL_TIMEOUT) log.info(f"First sample time: {self.first_sample_time}") - self.inlet.open_stream(timeout=5.0) + self.inlet.open_stream(timeout=LSL_TIMEOUT) if self.max_buffer_len and self.max_buffer_len > 0: self.buffer = RingBuffer(size_max=self.max_samples) if not self._first_sample_time: @@ -369,7 +372,7 @@ def discover_device_spec(content_type: str) -> DeviceSpec: """Finds the first LSL stream with the given content type and creates a device spec from the stream's metadata.""" log.info(f"Waiting for {content_type} data to be streamed over LSL.") - streams = resolve_byprop('type', content_type, timeout=5.0) + streams = resolve_byprop('type', content_type, timeout=LSL_TIMEOUT) if not streams: raise Exception( f'LSL Stream not found for content type {content_type}') diff --git a/bcipy/config.py b/bcipy/config.py index c630c0fae..a7fae94f4 100644 --- a/bcipy/config.py +++ b/bcipy/config.py @@ -51,6 +51,6 @@ # misc configuration WAIT_SCREEN_MESSAGE = 'Press Space to start or Esc to exit' -MAX_PAUSE_SECONDS = 360 +MAX_PAUSE_SECONDS = 365 SESSION_COMPLETE_MESSAGE = 'Complete! Saving data...' REMOTE_SERVER = "https://github.com/CAMBI-tech/BciPy/" diff --git a/bcipy/helpers/task.py b/bcipy/helpers/task.py index c7653ed67..01a2fa018 100644 --- a/bcipy/helpers/task.py +++ b/bcipy/helpers/task.py @@ -350,7 +350,7 @@ def pause_on_wait_screen(window, message, color) -> bool: elapsed_seconds = time.time() - pause_start if elapsed_seconds >= MAX_PAUSE_SECONDS: - log.info("Pause exceeded the allowed time. Ending task.") + log.info(f"Pause exceeded the allowed time ({MAX_PAUSE_SECONDS} seconds). Ending task.") return False if keys[0] == 'escape': return False From 1025609ec293d2597643d19aead7c85afd9a853f Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 7 May 2024 15:20:37 -0700 Subject: [PATCH 241/330] #186522989 ; Added the ability to store task-specific data in a Session (per session or per inquiry) --- bcipy/display/paradigm/vep/display.py | 1 + bcipy/task/data.py | 31 +++++++++++++++++++-------- 2 files changed, 23 insertions(+), 9 deletions(-) diff --git a/bcipy/display/paradigm/vep/display.py b/bcipy/display/paradigm/vep/display.py index 1b2ee2f16..0df6032ac 100644 --- a/bcipy/display/paradigm/vep/display.py +++ b/bcipy/display/paradigm/vep/display.py @@ -113,6 +113,7 @@ def __init__(self, self.info_text = info.build_info_text(window) # build the VEP stimuli + self.flicker_rates = flicker_rates self.logger.info(f"VEP flicker rates (hz): {flicker_rates}") rate = round_refresh_rate(frame_rate) codes = [ diff --git a/bcipy/task/data.py b/bcipy/task/data.py index bdf40695f..8e0613afd 100644 --- a/bcipy/task/data.py +++ b/bcipy/task/data.py @@ -66,6 +66,7 @@ class Inquiry: lm_evidence - language model evidence for each stimulus eeg_evidence - eeg evidence for each stimulus likelihood - combined likelihood for each stimulus + task_data - task-specific information about the inquiry that may be useful in training a model """ def __init__(self, @@ -78,7 +79,8 @@ def __init__(self, target_text: Optional[str] = None, selection: Optional[str] = None, next_display_state: Optional[str] = None, - likelihood: Optional[List[float]] = None) -> None: + likelihood: Optional[List[float]] = None, + task_data: Optional[Dict] = None) -> None: super().__init__() self.stimuli = stimuli self.timing = timing @@ -92,6 +94,7 @@ def __init__(self, self.evidences: Dict[EvidenceType, List[float]] = {} self.likelihood = likelihood or [] + self.task_data = task_data or {} # Precision used for serialization of evidence values. By default, no precision. self.precision: int = 0 @@ -164,6 +167,8 @@ def as_dict(self) -> Dict: if self.likelihood: data['likelihood'] = self.format(self.likelihood) + if self.task_data: + data['task_data'] = self.task_data return data def stim_evidence(self, @@ -211,7 +216,8 @@ def __init__(self, symbol_set: List[str], task: str = 'Copy Phrase', mode: str = 'RSVP', - decision_threshold: Optional[float] = None) -> None: + decision_threshold: Optional[float] = None, + task_data: Optional[Dict[str, Any]] = None) -> None: super().__init__() self.save_location = save_location self.task = task @@ -222,6 +228,7 @@ def __init__(self, self.task_summary: Dict[str, Any] = {} self.symbol_set = symbol_set self.decision_threshold = decision_threshold + self.task_data = task_data or {} @property def total_number_series(self) -> int: @@ -305,24 +312,30 @@ def as_dict(self, stim_dict = stim.as_dict() series_dict[series_counter][str(series_index)] = stim_dict - info = { + task_info = { 'session': self.save_location, 'task': self.task, 'mode': self.mode, 'symbol_set': self.symbol_set, - 'decision_threshold': self.decision_threshold, - 'series': series_dict, - 'total_time_spent': round(self.total_time_spent, - self.time_spent_precision), + 'decision_threshold': self.decision_threshold + } + if self.task_data: + task_info['task_data'] = self.task_data + + series_info = {'series': series_dict} + + summary_info = { + 'total_time_spent': round(self.total_time_spent, self.time_spent_precision), 'total_minutes': round(self.total_time_spent / 60, self.time_spent_precision), 'total_number_series': self.total_number_series, 'total_inquiries': self.total_inquiries, 'total_selections': self.total_number_decisions, 'inquiries_per_selection': self.inquiries_per_selection } - if self.task_summary: - info['task_summary'] = self.task_summary + summary_info['task_summary'] = self.task_summary + + info = {**task_info, **series_info, **summary_info} return info @classmethod From 93ac89ee059c4d9839b35295398417d166c489ce Mon Sep 17 00:00:00 2001 From: lawhead Date: Tue, 7 May 2024 15:23:15 -0700 Subject: [PATCH 242/330] #186522989 ; added session.json writing to the VEP Calibration Task to record details about the setup and the box of interest for each inquiry. --- bcipy/display/paradigm/vep/vep_stim.py | 2 + bcipy/task/paradigm/vep/calibration.py | 107 +++++++++++++++++++++---- bcipy/task/tests/core/test_data.py | 31 ++++++- 3 files changed, 122 insertions(+), 18 deletions(-) diff --git a/bcipy/display/paradigm/vep/vep_stim.py b/bcipy/display/paradigm/vep/vep_stim.py index c7e04d11d..96a0b36bf 100644 --- a/bcipy/display/paradigm/vep/vep_stim.py +++ b/bcipy/display/paradigm/vep/vep_stim.py @@ -31,12 +31,14 @@ def __init__(self, num_squares: int = 4): self.window = win self.code = code + self.colors = colors squares = checkerboard(squares=num_squares, colors=colors, center=center, board_size=size) board_boundary = envelope(pos=center, size=size) + self.bounds = board_boundary frame1_holes = [] frame2_holes = [] diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 8a9a0df07..a6f7282bd 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -1,10 +1,11 @@ """VEP Calibration task-related code""" -from typing import List, Tuple +from typing import Any, Dict, List, Optional, Tuple, Union from psychopy import core, visual # type: ignore from bcipy.acquisition.multimodal import ClientManager -from bcipy.config import TRIGGER_FILENAME, WAIT_SCREEN_MESSAGE +from bcipy.config import (SESSION_DATA_FILENAME, TRIGGER_FILENAME, + WAIT_SCREEN_MESSAGE) from bcipy.display import InformationProperties, VEPStimuliProperties from bcipy.display.components.layout import centered from bcipy.display.components.task_bar import CalibrationTaskBar @@ -13,12 +14,14 @@ from bcipy.display.paradigm.vep.layout import BoxConfiguration from bcipy.helpers.clock import Clock from bcipy.helpers.parameters import Parameters +from bcipy.helpers.save import _save_session_related_data from bcipy.helpers.symbols import alphabet from bcipy.helpers.task import get_user_input, trial_complete_message from bcipy.helpers.triggers import (FlushFrequency, Trigger, TriggerHandler, TriggerType, convert_timing_triggers, offset_label) from bcipy.task import Task +from bcipy.task.data import Inquiry, Session from bcipy.task.paradigm.vep.stim_generation import ( InquirySchedule, generate_vep_calibration_inquiries) @@ -34,6 +37,23 @@ def trigger_type(symbol: str, target: str, _index: int) -> TriggerType: return TriggerType.EVENT +def target_index(inquiry: List[Union[List[str], str]]) -> Optional[int]: + """Given a VEP calibration inquiry, determine which box holds the target. + + Parameters + ---------- + inquiry - list of target, fixation, and sublists representing each + vep box and its content symbols. + + Returns the box index (0-based). + """ + target, _fixation, *boxes = inquiry + for i, box in enumerate(boxes): + if target in box: + return i + return None + + class VEPCalibrationTask(Task): """VEP Calibration Task. @@ -49,6 +69,7 @@ class VEPCalibrationTask(Task): parameters (Dictionary) file_save (String) """ + MODE = 'VEP' def __init__(self, win: visual.Window, daq: ClientManager, parameters: Parameters, file_save: str): @@ -85,6 +106,25 @@ def __init__(self, win: visual.Window, daq: ClientManager, self.is_txt_stim = parameters['is_txt_stim'] self.display = self.init_display() + self.session = Session(save_location=self.file_save, + task='Calibration', + mode=self.MODE, + symbol_set=self.symbol_set, + task_data=self.session_task_data()) + self.write_session_data() + + def session_task_data(self) -> Dict[str, Any]: + """Task-specific session data""" + boxes = [{ + "colors": box.colors, + "flicker_rate": self.display.flicker_rates[i], + "envelope": box.bounds + } for i, box in enumerate(self.display.vep)] + return { + "boxes": boxes, + "symbol_starting_positions": self.display.starting_positions + } + def init_display(self) -> VEPDisplay: """Initialize the display""" return init_calibration_display(self.parameters, self.window, @@ -154,6 +194,8 @@ def execute(self): # Write triggers for the inquiry self.write_trigger_data(timing, first_run=(inquiry == 0)) + self.update_session_data(stimuli_labels[inquiry]) + # Wait for a time core.wait(self.buffer_val) @@ -185,7 +227,8 @@ def write_trigger_data(self, timing: List[Tuple[str, float]], assert self.display.first_stim_time, "First stim time not set" for content_type, client in self.daq.clients_by_type.items(): label = offset_label(content_type.name) - time = client.offset(self.display.first_stim_time) - self.display.first_stim_time + time = client.offset(self.display.first_stim_time + ) - self.display.first_stim_time triggers.append(Trigger(label, TriggerType.OFFSET, time)) target = timing[0][0] @@ -204,14 +247,47 @@ def write_offset_trigger(self) -> None: self.trigger_handler.add_triggers(triggers) self.trigger_handler.close() + def write_session_data(self) -> None: + """Save session data to disk.""" + if self.session: + session_file = _save_session_related_data( + f"{self.file_save}/{SESSION_DATA_FILENAME}", + self.session.as_dict()) + session_file.close() + + def update_session_data(self, inquiry: List[Union[List[str], + str]]) -> None: + """Adds the inquiry to the session data and writes to disk.""" + target_box = target_index(inquiry) + has_target = target_box is not None + target_freq = self.display.flicker_rates[ + target_box] if has_target else None + + task_data = { + 'target_box_index': target_box, + 'target_frequency': target_freq + } + + targetness = [TriggerType.NONTARGET for _ in range(self.num_boxes)] + if has_target: + targetness[target_box] = TriggerType.TARGET + trg_types = [TriggerType.PROMPT, TriggerType.FIXATION, *targetness] + + data = Inquiry(stimuli=inquiry, + timing=[], + triggers=[], + target_info=list(map(str, trg_types)), + target_letter=inquiry[0], + task_data=task_data) + self.session.add_sequence(data) + self.write_session_data() + def name(self): return 'VEP Calibration Task' -def init_calibration_display(parameters: Parameters, - window: visual.Window, - experiment_clock: Clock, - symbol_set: List[str], +def init_calibration_display(parameters: Parameters, window: visual.Window, + experiment_clock: Clock, symbol_set: List[str], timing: List[float], colors: List[str]) -> VEPDisplay: """Initialize the display""" @@ -226,14 +302,15 @@ def init_calibration_display(parameters: Parameters, layout = centered(width_pct=0.95, height_pct=0.80) box_config = BoxConfiguration(layout, height_pct=0.30) - stim_props = VEPStimuliProperties(stim_font=parameters['font'], - stim_pos=box_config.positions, - stim_height=0.1, - timing=timing, - stim_color=colors, - inquiry=[], - stim_length=1, - animation_seconds=parameters['time_vep_animation']) + stim_props = VEPStimuliProperties( + stim_font=parameters['font'], + stim_pos=box_config.positions, + stim_height=0.1, + timing=timing, + stim_color=colors, + inquiry=[], + stim_length=1, + animation_seconds=parameters['time_vep_animation']) task_bar = CalibrationTaskBar(window, inquiry_count=parameters['stim_number'], diff --git a/bcipy/task/tests/core/test_data.py b/bcipy/task/tests/core/test_data.py index 29e0d948f..2195b29e7 100644 --- a/bcipy/task/tests/core/test_data.py +++ b/bcipy/task/tests/core/test_data.py @@ -5,9 +5,8 @@ from bcipy.task.data import EvidenceType, Inquiry, Session SYMBOL_SET = [ - 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', - 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', - '<', '_' + 'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', + 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', '<', '_' ] @@ -289,6 +288,32 @@ def test_has_evidence(self): session.add_sequence(sample_stim_seq(include_evidence=True)) self.assertTrue(session.has_evidence()) + def test_task_data(self): + """Test that task-specific data can be added to the session.""" + session = Session(save_location=".", + symbol_set=SYMBOL_SET, + task_data={ + "greeting": "Hello", + "count": 10 + }) + serialized = session.as_dict() + self.assertTrue("task_data" in serialized) + self.assertEqual(serialized['task_data']['greeting'], "Hello") + self.assertEqual(serialized['task_data']['count'], 10) + + def test_task_inquiry_data(self): + """Test that inquiries may have task-specific data.""" + data = {"color": "blue", "flicker_rate": 10} + inq = Inquiry(stimuli=[], + timing=[], + triggers=[], + target_info=[], + task_data=data) + inq_dict = inq.as_dict() + self.assertTrue("task_data" in inq_dict) + self.assertEqual(inq_dict['task_data']['color'], 'blue') + self.assertEqual(inq_dict['task_data']['flicker_rate'], 10) + if __name__ == '__main__': unittest.main() From c9aee267988680ee147d1989bb2bace660e9d1f0 Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 16 May 2024 15:32:39 -0700 Subject: [PATCH 243/330] Added time spent to VEP calibration session --- bcipy/task/paradigm/vep/calibration.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index a6f7282bd..0ca12ed8b 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -81,6 +81,7 @@ def __init__(self, win: visual.Window, daq: ClientManager, self.daq = daq self.static_clock = core.StaticPeriod(screenHz=self.frame_rate) self.experiment_clock = Clock() + self.start_time = self.experiment_clock.getTime() self.buffer_val = parameters['task_buffer_length'] self.symbol_set = alphabet(parameters) @@ -280,6 +281,7 @@ def update_session_data(self, inquiry: List[Union[List[str], target_letter=inquiry[0], task_data=task_data) self.session.add_sequence(data) + self.session.total_time_spent = self.experiment_clock.getTime() - self.start_time self.write_session_data() def name(self): From 287e87dcd3a6945243ca9bc42a676d9adf1c738d Mon Sep 17 00:00:00 2001 From: lawhead Date: Thu, 16 May 2024 18:05:16 -0700 Subject: [PATCH 244/330] Fix typing issues --- bcipy/helpers/stimuli.py | 8 ++--- bcipy/task/data.py | 8 ++--- bcipy/task/paradigm/vep/calibration.py | 46 ++++++++++++-------------- 3 files changed, 29 insertions(+), 33 deletions(-) diff --git a/bcipy/helpers/stimuli.py b/bcipy/helpers/stimuli.py index 5f4c753c1..2106247b1 100644 --- a/bcipy/helpers/stimuli.py +++ b/bcipy/helpers/stimuli.py @@ -8,20 +8,20 @@ from collections import Counter from enum import Enum from os import path, sep -from typing import Any, Dict, Iterator, List, NamedTuple, Optional, Tuple, Union +from typing import (Any, Dict, Iterator, List, NamedTuple, Optional, Tuple, + Union) import mne import numpy as np import sounddevice as sd import soundfile as sf - from mne import Annotations, Epochs from mne.io import RawArray from pandas import Series from PIL import Image from psychopy import core -from bcipy.config import DEFAULT_TEXT_FIXATION, DEFAULT_FIXATION_PATH +from bcipy.config import DEFAULT_FIXATION_PATH, DEFAULT_TEXT_FIXATION from bcipy.helpers.exceptions import BciPyCoreException from bcipy.helpers.list import grouper @@ -85,7 +85,7 @@ class InquirySchedule(NamedTuple): - durations: `List[List[float]]` - colors: `List[List[str]]` """ - stimuli: Union[List[List[str]], List[str]] + stimuli: List[Any] durations: Union[List[List[float]], List[float]] colors: Union[List[List[str]], List[str]] diff --git a/bcipy/task/data.py b/bcipy/task/data.py index 8e0613afd..51a1df069 100644 --- a/bcipy/task/data.py +++ b/bcipy/task/data.py @@ -70,7 +70,7 @@ class Inquiry: """ def __init__(self, - stimuli: List[str], + stimuli: List[Any], timing: List[float], triggers: List[Tuple[str, float]], target_info: List[str], @@ -150,7 +150,7 @@ def from_dict(cls, data: dict) -> 'Inquiry': def as_dict(self) -> Dict: """Dict representation""" - data = { + data: Dict = { 'stimuli': self.stimuli, 'timing': self.timing, 'triggers': self.triggers, @@ -312,7 +312,7 @@ def as_dict(self, stim_dict = stim.as_dict() series_dict[series_counter][str(series_index)] = stim_dict - task_info = { + task_info: Dict = { 'session': self.save_location, 'task': self.task, 'mode': self.mode, @@ -324,7 +324,7 @@ def as_dict(self, series_info = {'series': series_dict} - summary_info = { + summary_info: Dict = { 'total_time_spent': round(self.total_time_spent, self.time_spent_precision), 'total_minutes': round(self.total_time_spent / 60, self.time_spent_precision), 'total_number_series': self.total_number_series, diff --git a/bcipy/task/paradigm/vep/calibration.py b/bcipy/task/paradigm/vep/calibration.py index 0ca12ed8b..f090276c7 100644 --- a/bcipy/task/paradigm/vep/calibration.py +++ b/bcipy/task/paradigm/vep/calibration.py @@ -1,5 +1,5 @@ """VEP Calibration task-related code""" -from typing import Any, Dict, List, Optional, Tuple, Union +from typing import Any, Dict, List, Tuple, Union from psychopy import core, visual # type: ignore @@ -37,23 +37,6 @@ def trigger_type(symbol: str, target: str, _index: int) -> TriggerType: return TriggerType.EVENT -def target_index(inquiry: List[Union[List[str], str]]) -> Optional[int]: - """Given a VEP calibration inquiry, determine which box holds the target. - - Parameters - ---------- - inquiry - list of target, fixation, and sublists representing each - vep box and its content symbols. - - Returns the box index (0-based). - """ - target, _fixation, *boxes = inquiry - for i, box in enumerate(boxes): - if target in box: - return i - return None - - class VEPCalibrationTask(Task): """VEP Calibration Task. @@ -258,11 +241,23 @@ def write_session_data(self) -> None: def update_session_data(self, inquiry: List[Union[List[str], str]]) -> None: - """Adds the inquiry to the session data and writes to disk.""" - target_box = target_index(inquiry) - has_target = target_box is not None + """Adds the inquiry to the session data and writes to disk. + + Parameters + ---------- + inquiry - list of target, fixation, and sublists representing each + vep box and its content symbols. + """ + target_letter, _fixation, *boxes = inquiry + assert isinstance(target_letter, str), "unexpected inquiry format" + + target_box = None + for i, box in enumerate(boxes): + if target_letter in box: + target_box = i + target_freq = self.display.flicker_rates[ - target_box] if has_target else None + target_box] if target_box is not None else None task_data = { 'target_box_index': target_box, @@ -270,7 +265,7 @@ def update_session_data(self, inquiry: List[Union[List[str], } targetness = [TriggerType.NONTARGET for _ in range(self.num_boxes)] - if has_target: + if target_box is not None: targetness[target_box] = TriggerType.TARGET trg_types = [TriggerType.PROMPT, TriggerType.FIXATION, *targetness] @@ -278,10 +273,11 @@ def update_session_data(self, inquiry: List[Union[List[str], timing=[], triggers=[], target_info=list(map(str, trg_types)), - target_letter=inquiry[0], + target_letter=target_letter, task_data=task_data) self.session.add_sequence(data) - self.session.total_time_spent = self.experiment_clock.getTime() - self.start_time + self.session.total_time_spent = self.experiment_clock.getTime( + ) - self.start_time self.write_session_data() def name(self): From 6b996389faaef3c43aabb474ef0c52fe0173ae05 Mon Sep 17 00:00:00 2001 From: lawhead Date: Mon, 20 May 2024 13:53:30 -0700 Subject: [PATCH 245/330] #185720052 ; updates the main GUI with the new parameter location after using the Save As functionality in the params_form GUI. --- bcipy/gui/BCInterface.py | 25 +++++++++++-------------- bcipy/gui/parameters/params_form.py | 13 +++++++++---- 2 files changed, 20 insertions(+), 18 deletions(-) diff --git a/bcipy/gui/BCInterface.py b/bcipy/gui/BCInterface.py index c3e8eb63e..326e2a1f6 100644 --- a/bcipy/gui/BCInterface.py +++ b/bcipy/gui/BCInterface.py @@ -1,20 +1,15 @@ import subprocess import sys - from typing import List -from bcipy.config import BCIPY_ROOT, DEFAULT_PARAMETERS_PATH, STATIC_IMAGES_PATH -from bcipy.gui.main import ( - AlertMessageResponse, - AlertMessageType, - AlertResponse, - app, - BCIGui, - contains_special_characters, - contains_whitespaces, - invalid_length, -) -from bcipy.helpers.load import load_json_parameters, load_experiments, copy_parameters, load_users +from bcipy.config import (BCIPY_ROOT, DEFAULT_PARAMETERS_PATH, + STATIC_IMAGES_PATH) +from bcipy.gui.main import (AlertMessageResponse, AlertMessageType, + AlertResponse, BCIGui, app, + contains_special_characters, contains_whitespaces, + invalid_length) +from bcipy.helpers.load import (copy_parameters, load_experiments, + load_json_parameters, load_users) from bcipy.task import TaskType @@ -317,9 +312,11 @@ def edit_parameters(self) -> None: else: return None - subprocess.call( + output = subprocess.check_output( f'python {BCIPY_ROOT}/gui/parameters/params_form.py -p {self.parameter_location}', shell=True) + if output: + self.parameter_location = output.decode().strip() def check_input(self) -> bool: """Check Input. diff --git a/bcipy/gui/parameters/params_form.py b/bcipy/gui/parameters/params_form.py index fc82c7780..0e6a4510a 100644 --- a/bcipy/gui/parameters/params_form.py +++ b/bcipy/gui/parameters/params_form.py @@ -418,11 +418,14 @@ def on_save_as(self): self.repaint() -def main(json_file, title='BCI Parameters', size=(450, 550)): +def main(json_file, title='BCI Parameters', size=(450, 550)) -> str: """Set up the GUI components and start the main loop.""" app = QApplication(sys.argv) - _panel = MainPanel(json_file, title, size) - sys.exit(app.exec()) + panel = MainPanel(json_file, title, size) + app.exec() + json_file = panel.json_file + app.quit() + return json_file if __name__ == '__main__': @@ -439,4 +442,6 @@ def main(json_file, title='BCI Parameters', size=(450, 550)): default=DEFAULT_PARAMETERS_PATH, help='Path to parameters.json configuration file.') args = parser.parse_args() - main(args.parameters) + # Note that this write to stdout is important for the interaction with + # the BCInterface main GUI. + print(main(args.parameters), file=sys.stdout) From c00998028b7ce611a23f4301a5de752a87e9e1f3 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Thu, 23 May 2024 13:13:19 -0700 Subject: [PATCH 246/330] GitHub actions MacOS build fix (#324) * enables github actions on push for this branch * run `m2chip_install.sh` for macOS build action * refactors macOS github actions to use bcipy makefile This should reduce redundant code and ensure the install process is consistant * Specifies tables version of 3.7.0 to fix macOS build issues as suggested [here](https://github.com/DeepLabCut/DeepLabCut/issues/2342) * Refactors github actions to use makefile This reduces code duplication and ensures that github actions reflect build process * removes upgrading `settuptools` and `wheel` * Adds comment to indicate M3 support. * Comments out redundant installs in `m2chip_install.sh` * adds `dev-install-mac` to makefile * fixes indentation in makefile * Revert "fixes indentation in makefile" This reverts commit db0e86834d037e3583ef6347b6be9d48c3677e66. * Revert "adds `dev-install-mac` to makefile" This reverts commit 45e19270f1d815b070c1a4435a4af0ffb0ee9f0a. * Revert "Comments out redundant installs in `m2chip_install.sh`" This reverts commit 2d6c43cdc7c449c8fca3cb5c2dace43645f21627. * removes github actions on push for this branch * update changelog --- .github/workflows/main.yml | 33 ++++++++++++--------------------- CHANGELOG.md | 1 + requirements.txt | 3 ++- scripts/shell/m2chip_install.sh | 2 +- 4 files changed, 16 insertions(+), 23 deletions(-) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index f0a2b5997..5ced794ff 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -36,13 +36,10 @@ jobs: sudo apt-get install libsndfile* sudo apt-get install xvfb python -m pip install --upgrade pip - pip install kenlm==0.1 --global-option="--max_order=12" - pip install psychopy==2023.2.1 --no-deps pip install attrdict3 - name: Install dependencies run: | - pip install -r dev_requirements.txt - pip install -e . + make dev-install - name: Unit test if: always() run: | @@ -60,10 +57,10 @@ jobs: fi - name: type-check run: | - mypy bcipy + make type - name: lint run: | - flake8 bcipy + make lint build-windows: @@ -82,26 +79,23 @@ jobs: - name: update pip & install custom dependencies run: | python -m pip install --upgrade pip - pip install kenlm==0.1 --global-option="--max_order=12" - pip install psychopy==2023.2.1 --no-deps - name: install manually downloaded pyWinhook wheel for Python 3.9 if: matrix.python-version == 3.9 run: | pip install ./.bcipy/downloads/pyWinhook-1.6.2-cp39-cp39-win_amd64.whl - name: install dependencies run: | - pip install -r dev_requirements.txt - pip install -e . + make dev-install - name: unittest if: always() run: | - coverage run --branch --source=bcipy -m pytest --mpl -k "not slow" + make coverage-report - name: type-check run: | - mypy bcipy + make type - name: lint run: | - flake8 bcipy + make lint build-macos: @@ -119,24 +113,21 @@ jobs: python-version: ${{ matrix.python-version }} - name: update pip & install custom dependencies run: | + sh scripts/shell/m2chip_install.sh brew install labstreaminglayer/tap/lsl python -m pip install --upgrade pip - pip install kenlm==0.1 --global-option="--max_order=12" - pip install psychopy==2023.2.1 --no-deps - name: install dependencies run: | - pip install -r dev_requirements.txt - pip install -e . + make dev-install - name: unittest if: always() run: | - coverage run --branch --source=bcipy -m pytest --mpl -k "not slow" - coverage report + make coverage-report - name: type-check run: | - mypy bcipy + make type - name: lint run: | - flake8 bcipy + make lint diff --git a/CHANGELOG.md b/CHANGELOG.md index fe6a592ca..41c9f1e50 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -19,6 +19,7 @@ Our last release candidate before the official 2.0 release! - Add mypy typing to the codebase #301 - Change default log level to INFO to prevent too many messages in the experiment logs #288 - Upgrade requirements for m1/2 chips #299/#300 + - Fix GitHub actions build issues with macOS # 2.0.0-rc.3 diff --git a/requirements.txt b/requirements.txt index 809272152..149aa74cb 100644 --- a/requirements.txt +++ b/requirements.txt @@ -23,4 +23,5 @@ pyedflib==0.1.34 PyQt6==6.6.0 PyQt6-Qt6==6.6.0 pywavelets==1.4.1 -tqdm==4.62.2 \ No newline at end of file +tqdm==4.62.2 +tables==3.7.0 \ No newline at end of file diff --git a/scripts/shell/m2chip_install.sh b/scripts/shell/m2chip_install.sh index c706ea2c6..3fe41ee8c 100644 --- a/scripts/shell/m2chip_install.sh +++ b/scripts/shell/m2chip_install.sh @@ -1,6 +1,6 @@ """Mac M2 install script. -This script is intended to be run from the root of the BciPy repository. It may work for M1 chips, but +This script is intended to be run from the root of the BciPy repository. It has been tested on M2 and M3 chips. It may work for M1 chips, but this has not been tested and may require use of Rosetta 2. This script will install the necessary dependencies for the M2 chip on a Mac. It will also install From 836e284f911936a3cfaac7f2a535d5ead7e88800 Mon Sep 17 00:00:00 2001 From: Carson Reader Date: Wed, 29 May 2024 17:12:32 -0700 Subject: [PATCH 247/330] removes randomly failing test --- bcipy/helpers/tests/test_stimuli.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/bcipy/helpers/tests/test_stimuli.py b/bcipy/helpers/tests/test_stimuli.py index 397ca2eac..4c017e828 100644 --- a/bcipy/helpers/tests/test_stimuli.py +++ b/bcipy/helpers/tests/test_stimuli.py @@ -730,7 +730,6 @@ def test_best_case_inquiry_gen_invalid_alp(self): def test_best_case_inquiry_gen_with_inq_constants(self): """Test best_case_rsvp_inq_gen with inquiry constants""" - alp = ['a', 'b', 'c', 'd', 'e', 'f', 'g'] n = 5 @@ -761,7 +760,6 @@ def test_best_case_inquiry_gen_with_inq_constants(self): for letter in expected: self.assertTrue(letter in first_inq) - self.assertNotEqual(expected, first_inq, 'Should be in random order.') self.assertEqual([1] + ([0.2] * n), times[0]) self.assertEqual(['red'] + (['white'] * n), colors[0]) From 0cf22ecacd7fbd7959522e5275ff7e029fbb213e Mon Sep 17 00:00:00 2001 From: tab-cmd Date: Thu, 30 May 2024 11:49:36 -0700 Subject: [PATCH 248/330] Add BciPy Report (#325) * Add Report and ReportSection --- .gitignore | 4 +- BciPyReport.pdf | Bin 0 -> 9155 bytes CHANGELOG.md | 2 + bcipy/config.py | 1 + bcipy/helpers/demo/demo_visualization.py | 2 +- bcipy/helpers/report.py | 227 ++++++++++++++++++++ bcipy/helpers/tests/test_report.py | 175 +++++++++++++++ bcipy/static/images/gui/CAMBI_full_logo.png | Bin 0 -> 6425 bytes requirements.txt | 1 + 9 files changed, 409 insertions(+), 3 deletions(-) create mode 100644 BciPyReport.pdf create mode 100644 bcipy/helpers/report.py create mode 100644 bcipy/helpers/tests/test_report.py create mode 100644 bcipy/static/images/gui/CAMBI_full_logo.png diff --git a/.gitignore b/.gitignore index 1b4f6af78..613c7069a 100644 --- a/.gitignore +++ b/.gitignore @@ -19,8 +19,8 @@ __pycache__/ .cache/ # BciPy files and directories -calibration.csv -rawdata.csv +*.csv +*.pdf buffer.db lmwrap.log env.txt diff --git a/BciPyReport.pdf b/BciPyReport.pdf new file mode 100644 index 0000000000000000000000000000000000000000..c90cd24dee8bbabe6470177f7cd4de8f7f749ba9 GIT binary patch literal 9155 zcmbuF+19E`wxI9VQ~Zi3Hi#gKC@6|8h+>0^APUlm(xWFc>!Mzu>aOnVS&M(=-kIy< z&QqDAO2-fggBdfr88hY=pg5kwXdV9n{;&V}KmPaE){4U9z0{4bnH5-x{PdDoK(EovcHNHaQ`GcZFJJ0X0jP%r+hFJl~-17dzdb@Z13z-D>&~yXm3pu*MFi73MC#-be z%EY5z$nImj{}N>n`|LM+{=Q`YWU_uKs`+bC?mHE&gbn>D48H5s`9j#x3zJ=>-?LZ8 z)_=HnYdafdQe5wCC11)HGTgC?MW;2kGL62)ds)-`_Hg;u*>xV7AmR&IT7mO^d|}Nt zp6Mp&>FW#s*#bYle$jQ|>&|Z~e<7!}@wDz))sL>3z1nOvzBNzZiKY8LW=04rH8_VJLY7-Bna)q`5Q8rUWv|0w|n4cmXwx{ zu`P35$n{4t(SkqK2s=ySuJ-W6C@!w$$B3P`jxGcB2+SkWw8^4o8q@AaQXbKkIy-XM z>WpH(2i)sIi(bl6Ih?`o+pSA;Osmm9?Bg|IRt`dQTwE@OQp{i{ODr{Atlx%*WuuSY zS$K78wScRMmoYddy%7&~&zszD+$qqtH%Cui7ls|TfYC~6CWi6{3RjP(UMUhesPKF*IoLy>u#SfN z&NPS5ipCH+?6gY-I!%r*TidUwa{uu-z~*2aJ!kf7v6n1 zZxA~v_?Oo;0Q9-Ge-HDDn@fgQ>{23cE`4UEJKcGzcw8>j{Hl-N3{~ifJie*Otvm_$ zmv>*wiAZC^S*ck+`n`3laC;u>ekj#v=M|x;8eHX>t$bcw<&hw5Ri)?Gy{!dB8`B#w(`}b`RC{%kqMYq+5UCxh%Fi)Io zW2S~pXd1mvX;JXW)@0Tjo3C-rE8*T?#wq23G;s<(+qu%OE!^|z4Gzn6z2X?^HZpwR zVLqHj8>!aW+-xy-a?K*0jpxU+a$wJ$ep54rfkZED;|g9<4k&ongv54q!t_44dW)s$ z;#d*Y_TYJame#vNZM_}@bnSq-?^`}SrA>74W;E}xu*;jmj4qRJKLSQ`X&EKKfNSzeTL$cc}kn17^txl5b}$&1H0VmauKkQyEg zVdC_{`0~EM57e3iRjtk?SdQg>GiIY*hq%-hMfh2CgT=g^TA6B zs5@2S!n19<8?czB>T8jHhG|>6E%qny&9rz-+}2mZxXRVkdb|`$_>LRqXZ|SZEH8sp z?w2&`iEi!v|0QwlF!g;oS@dE{pWzAEa;dwmXP0Zt-x+}tK0~Xvp*i76JqTI28H{d2! zkC)P5g}tAh=a6jfX%j}$YPVg%)Ukx&c{6BjjJxwmxPVP%V@q-r-!ELRJWyTDGi$Nq zKj?ICHC2Ev!~9I2far@{UT(`YfgZ}4>xf=p6HMjVz!5@!c6Z^<#(+hsD+$XoiNZyG zkQ57-b4|k0Rz&5%Jyb{}(BshE(knH5b2_A`Rfkr(i!z5ZMYqZv6*2Ej88Shh-6C6U z2poyk+y+*QxkDwkgsb*}E1hxtuDu;#lwUq_0lr}`ozI?!i>M!-R_5+uRQJT=Q$6M9 zW_;z=-rercw*_LdUI$UqTGgd1i_{);hqkhbUSR}I+*M-AV9n+j(ke?p)AXdcR&!UD zba4A51Co_6-u`4qb1lRqYgBtLK3+<1CAWL)mkdR*!NyRf#^@{06<#O4)U574)$Ibl z(3<-=J=W{Spdn8xmBMxj^a0Hy(^N-?5lL-k+T&B0ZPtW#SpY1FK05bzUtoIv zF<*O9WwA7sy#C}xgb{<*M;HTWg)3kf)qc8$7^k%_vg3!)hFVbZGSy0R2)Q0&I5AeY zmDkk5h}4hWK7%Ue8o-O^sKCrws7>fxXk5$1-AfIe98g`KMipYeXMm+2_#X8-c6NvR zS}PMIGE6S-_ye#NzQ0CiC!C;o-DS&h;*9WxkCpJ{aFpgZcGKzYwHRiTT!#`i_K;_q zO9`@7Lsc$TB>~|4Ev@@Go-3;F8JU0gXHXqj-xh+{6An^GmI^sIYEHuOfA430=5Joq zZyx8jC-ygw^WSm>tJc5$yKsv z_K&$d3Oq?6{9Ef!#>Tcm-Y0H&kXP*@ z`WhBb(t#cv%$l7XS?B{j$hle`YZm4CAt6lVhNemqwX5doyvK0e7N=>r_z9;4>?GC z?q~?>;UE+=-rg~}4Xp4ob%HY1HP7WzCmtxt>&ouxr%1TeORK=t==9Dc>Uv8lC}(Lm z{xEA)baOr-#8U5gD^?d>P$(sf*>KQp^ z^L6zWx0zX;aN7bs(CdQNKX3c9_fT!}S9|mz`_ABG1i-pvsk*-t>*V$G+U3{0Z*5