v0.3.0

Fixes

• Allow is_strict_moderation to be inferred from not just API data, but file data.
• Better handle numpy divide-by-zero edge-cases in two-property test. (#28)
• Fix bug where vote_matrix was modified directly, leading to subtle side-effects.
• Fix bug in select_representative_statements() where mod-out statements weren't ignored.

Changes

• Fixed participant projections to map more closely to Polis with utils.pca.sparsity_aware_project_ptpt().
• Add simple Polis implementation in reddwarf.implementations.polis.
• Add singular polis_id arg as recommended way to download (auto-detect report_id vs converation_id).
• Calculate group-aware consensus stats. (#28)
• Removed scale_projected_data() in PolisClient (now happens in run_pca()).
• Deprecate PolisClient().
• Add inverse_transform() to SparsityAwareScaler.
• Add data loader support for local math data files.
• Add support to easily flip signs in generate_figure().
• Modify generate_figure() to accept more effective args.
  • Use numpy args of coord_data, coord_labels and cluster_labels
    individually, rather than using DataFrames.
  • Allow passing extra coord_data beyond what's labelled.
• Add automatic padding to polis implementation when cluster centroid guesses are provided.
• Add PolisKMeans scikit-learn estimator with:
  • cluster initialization strategy matching Polis,
  • new init_centers argument with more versatility for being given more/less guesses than needed, and
  • new instance variable init_centers_used_ to allow inspection of guesses used.
• Allow passing KMeans init strategy into find_optimal_k().
• Remove pad_centroid_list_to_length helper function.
• Add GridSearchNonCV to find optimal K via silhouette scores.
• For interal util functions, replace max_group_count args with k_bounds for upper and lower k bounds.
• Add PolisKMeansDownsampler transformer to support base clustering.
• Update get_corrected_centroid_guesses() to also extract from base clusters.
• Remove extraneous return values from PolisClusteringResult.
• Add data_presenter.generate_figure_polis() for making graphs from PolisClusteringResult.
• Add group_aware_consensus dataframe to PolisClusteringResult of polis implementation.
• Add group statement stats to MultiIndex DataFrame.
• Add reddwarf.data_presenter.print_repress() for printing representative statements.
• Add support for Loader() importing data from alternative Polis instances via polis_instance_url arg.
• Patch sklearn with a simple PatchedPipeline, to allow pipeline steps to access other steps.
• Modify SparsityAwareScaler to be able to use captured output from SparsityAware Capture.
• Remove ported Polis PCA functions that are no longer used.
• Remove old impute_missing_votes() function that's no longer used.
• In PolisClusteringResult, created new statements_df and participants_df with all raw calculation values.

Chores

• Moved agora implementation from reddwarf.agora to reddwarf.implementations.agora (deprecation warning).
• Add missing conversation.json fixture file.
• Extract statement processing from polis class-based client to pure util function.
• Add types to fully describe polismath object. (#28)
• Add new fixture for large convo without meta statements. (#28)
• Add ability to filter unit tests and avoid running whole suite. (#44)
• Improve test fixture to download remote Polis data.
• Add helper to support simple sign-flips in Polis test data.
• Remove usage of PolisClient in tests, in favour of [data] Loader.
• Start storing keep_participant_ids in fixtures.
• Add solid unit test for expected variance, which is stablest measure we can derive.
• Use dataclasses for polis_convo_data test fixture.
• Add utils.polismath.get_corrected_centroid_guesses() to initiate centroid guesses from Polis API.
• Remove unused init_cluster() helper.

v0.2.0

Fixed

• Relax seaborn version constraint to be compatible with TabPFN. (#16)
• Data loader was not downloading last participant's votes, so most PCA results slightly off. (#29)

Changes

• Implement utils.calculate_representativeness() function. (#22)
• Add color legend for labels in data_presenter.generate_figure(). d55f535 (#22)
• Implement calculations of all comment statistics. (#25)
• Implement utils.select_representative_statements() to reproduce polismath output. (#25)
• Migrate from red-dwarf-democracy PyPI project namespace to red-dwarf.

Chores

• Restructure utils.py into separate files. (#26)
• Add unit tests for utils.run_pca() to test against real polismath data.
• Add unit tests for agora.run_clustering().
• Parametrize unit tests for real polis convo data.
• Add testing for notebook examples. (#34)

v0.1.1

Bugfixes

• Fix publishing issue with missing license file. (#19)
  • Workaround for pypa/setuptools#4769.
• Change package name from reddwarf to red-dwarf-democracy.

v0.1.0

• Add Agora/ZKorum to README as sponsor.
• Add low-level stateless functions in reddwarf.utils.
  • Add first-pass unit test coverage, and CI.
• Add mid-level stateless reddwarf.agora implementation.
  • Add preferred types/modules and function definitions.
• Add code coverage reports for unit tests.
• Document library usage in Jupyter notebooks.
• Create documentation website using mkdocs.
• Add make targets for common development tasks, and default help target.
• Experimental
  • Add high-level stateful Polis client class implementation.
  • Add high-level stateful data loader class.
    • Support loading from JSON API, CSV export API, local files, and remote directory.
    • Support rate-limiting.
    • Support request caching.
    • Support bypass of Cloudflare for all API endpoints.
  • Add high-level stateful data presenter class.
  • Add integration tests.