minor log clean

bcipy/simulator/helpers/log_utils.py

@@ -1,15 +1,17 @@
-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]
     formatted = [f"{a} : {l}" for a, l in zip(alp, rounded)]
     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)

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:

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()