diff --git a/README.md b/README.md index 797243d..c3cbf9a 100644 --- a/README.md +++ b/README.md @@ -25,7 +25,7 @@ pytest ## Quickstart -[View the template yaml here for a minimially working example with our supplied sample data to get started.](https://github.com/deepskies/DeepDiagnostics/blob/main/config.yml.template) +[View the template yaml here for a minimally working example with our supplied sample data to get started.](https://github.com/deepskies/DeepDiagnostics/blob/main/config.yml.template) ### Pipeline `DeepDiagnostics` includes a CLI tool for analysis. @@ -53,11 +53,11 @@ It is encouraged, but not required. ``` py -from DeepDiagnostics.utils.configuration import Config -from DeepDiagnostics.model import SBIModel -from DeepDiagnostics.data import H5Data +from deepdiagnostics.utils.configuration import Config +from deepdiagnostics.model import SBIModel +from deepdiagnostics.data import H5Data -from DeepDiagnostics.plots import LocalTwoSampleTest, Ranks +from deepdiagnostics.plots import LocalTwoSampleTest, Ranks Config({configuration_path}) model = SBIModel({model_path}) @@ -177,7 +177,7 @@ For this example, we will add a new metric, but an identicial workflow takes pla 1. Add the name and mapping to the submodule `__init__.py`. -##### `src/deepdiagonstics/metrics/__init__.py` +##### `src/deepdiagnostics/metrics/__init__.py` ``` py ... @@ -193,7 +193,7 @@ Metrics = { 2. Add the name and defaults to the `Defaults.py` -##### `src/deepdiagonstics/utils/Defaults.py` +##### `src/deepdiagnostics/utils/Defaults.py` ``` py Defaults = { @@ -211,7 +211,7 @@ Defaults = { ##### `tests/test_metrics.py` ``` py -from deepdaigonstics.metrics import NewMetric +from deepdiagnostics.metrics import NewMetric ... @@ -237,7 +237,7 @@ python3 -m pytest tests/test_metrics.py::test_newmetric ##### `docs/source/metrics.rst` ``` rst -from deepdaigonstics.metrics import NewMetric +from deepdiagnostics.metrics import NewMetric .. _metrics: @@ -248,7 +248,7 @@ Metrics :members: ... -.. autoclass:: deepdiagonstics.metrics.newmetric.NewMetric +.. autoclass:: deepdiagnostics.metrics.newmetric.NewMetric :members: calculate .. bibliography:: diff --git a/poetry.lock b/poetry.lock index 4ac30e3..66f1796 100644 --- a/poetry.lock +++ b/poetry.lock @@ -24,96 +24,31 @@ files = [ [[package]] name = "arviz" -version = "0.17.1" +version = "0.18.0" description = "Exploratory analysis of 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"jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"] - [metadata] lock-version = "2.0" -python-versions = ">=3.9,<3.12" -content-hash = "aa2cda22540612ead3f0392e01b20d6749ee5b480e7bc66629561a2bd26bb20d" +python-versions = ">=3.10,<4.0" +content-hash = "f60fc4442b1aaa42f9a5e41ad1fbe65d429f9c9daa157624620dbbdd66540960" diff --git a/pyproject.toml b/pyproject.toml index a51ae81..62ad64b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,16 +1,16 @@ [tool.poetry] name = "deepdiagnostics" packages = [{include = "*", from="src"}] -version = "0.2.0.alpha" +version = "1.0.0" description = "a package for diagnosing posterior quality from inference methods" -authors = ["Becky Nevin "] +authors = ["Becky Nevin ", "M Voetberg "] license = "MIT" [tool.poetry.scripts] diagnose = "deepdiagnostics.client.client:main" [tool.poetry.dependencies] -python = ">=3.9,<3.12" +python = ">=3.10,<4.0" sbi = "^0.22.0" pyarrow = "^15.0.0" getdist = "^1.4.7" @@ -19,7 +19,7 @@ numpy = ">=1.18.5,<1.26.0" matplotlib = "^3.8.3" tarp = "^0.1.1" deprecation = "^2.1.0" -scipy = ">=1.6.0, <1.9.2" +scipy = ">=1.6.0, <1.12.0" [tool.poetry.group.dev.dependencies] @@ -30,7 +30,6 @@ pytest = "^7.3.2" black = "^24.3.0" ruff = "^0.3.5" sphinx = "^7.2.6" -deepbench = "^0.2.2" sphinxcontrib-bibtex = "^2.6.2" sphinx-autodoc-typehints = "^2.2.1" diff --git a/src/deepdiagnostics/plots/cdf_ranks.py b/src/deepdiagnostics/plots/cdf_ranks.py index 99827a0..57281fd 100644 --- a/src/deepdiagnostics/plots/cdf_ranks.py +++ b/src/deepdiagnostics/plots/cdf_ranks.py @@ -53,6 +53,7 @@ def plot_settings(self): def plot(self): """ + Make the CDF Ranks plot """ sbc_rank_plot( self.ranks, diff --git a/src/deepdiagnostics/plots/local_two_sample.py b/src/deepdiagnostics/plots/local_two_sample.py index 2a4234c..f6e2591 100644 --- a/src/deepdiagnostics/plots/local_two_sample.py +++ b/src/deepdiagnostics/plots/local_two_sample.py @@ -27,15 +27,10 @@ class LocalTwoSampleTest(Display): .. code-block:: python from deepdiagnostics.plots import LC2ST - + LC2ST(model, data, save=False, show=True).plot(use_intensity_plot=True, n_alpha_samples=100, linear_classifier="MLP", n_null_hypothesis_trials=20) """ - # Plots to make - - # pp_plot_lc2st: https://github.com/JuliaLinhart/lc2st/blob/e221cc326480cb0daadfd2ba50df4eefd374793b/lc2st/graphical_diagnostics.py#L49 - # eval_space_with_proba_intensity: https://github.com/JuliaLinhart/lc2st/blob/e221cc326480cb0daadfd2ba50df4eefd374793b/lc2st/graphical_diagnostics.py#L133 - - # https://github.com/JuliaLinhart/lc2st/blob/e221cc326480cb0daadfd2ba50df4eefd374793b/lc2st/graphical_diagnostics.py#L133 def __init__( self, @@ -93,7 +88,6 @@ def lc2st_pairplot(self, subplot, confidence_region_alpha=0.2): label=f"{percentile}% Conf. region", ) - for prob, label, color in zip(self.probability, self.parameter_names, self.parameter_colors): pairplot_values = self._make_pairplot_values(prob) subplot.plot(self.cdf_alphas, pairplot_values, label=label, color=color) @@ -240,7 +234,6 @@ def plot( self.plot_name = "local_c2st_pp_plot.png" self._finish() - if use_intensity_plot: fig, subplots = plt.subplots(len(self.parameter_names), len(self.parameter_names), figsize=(self.figure_size[0]*1.2, self.figure_size[1])) diff --git a/tests/conftest.py b/tests/conftest.py index 736cf13..de3b515 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -3,7 +3,6 @@ import pytest import yaml import numpy as np -from deepbench.astro_object import StarObject from deepdiagnostics.data import H5Data from deepdiagnostics.data.simulator import Simulator @@ -43,12 +42,17 @@ def simulate(self, theta: np.ndarray, context_samples: np.ndarray) -> np.ndarray return y.T class Mock2DSimulator(Simulator): + def __init__(self) -> None: + import subprocess + subprocess.check_call(["python3", "-m", "pip", "install", "deepbench"]) + def generate_context(self, n_samples: int) -> np.ndarray: return np.linspace(0, 28, n_samples) def simulate(self, theta, context_samples: np.ndarray): - generated_stars = [] + from deepbench.astro_object import StarObject + generated_stars = [] if len(theta.shape) == 1: theta = [theta]