v0.2.8 -- Documentation Overhaul, New Statistical Tests

Major Updates

• Full documentation overhaul, including common use-cases, motivations, quick-start instructions, demos on real diabetes data to fit models and test for heterogeneity, and formal descriptions of the underlying statistical framework.
• Find individual contexts driving heterogeneity and test their significance with contextualized.analysis.pvals.test_each_context.
• New demo for test_each_context: Finding Drivers of Heterogeneous Effects.
• Added API reference for test_each_context, select_good_bootstraps, and print_acc_by_covars
• Added maximum stable version torch<2.2.0

Minor Updates

• Fixed bug in easy correlation networks prediction when indivudal_preds=False
• Increased overall test coverage to 87%, only leaving out visualization utilities.
• Added tests for correctness to all analysis tools. Models must identify the significance of known heterogeneous and homogeneous effects to pass integration tests.

Auto-generated release notes

• create sequential context testing utility function by @aaron10l in #220
• Sequential testing bugfixes, updated docs by @cnellington in #227
• sequential testing function unittest by @aaron10l in #234
• add network quicktests to main test file, fix bug with averaged correlation networks by @cnellington in #236
• Website cleaning by @cnellington in #239
• clean up easy regression notebook by @aaron10l in #240
• add link to comparison with linear interpretability methods by @cnellington in #241

Full Changelog: v0.2.7...v0.2.8