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Tests: add spec-guided TDD support conftest Add tests/conftest.py from the spec-guided-tdd skill, formatted to ProteoPy's black/flake8 standards. It only affects test modules marked `pytestmark = pytest.mark.spec_guided` (e.g. tests/pl/test_upset.py); all other tests run unchanged. - `pytest` (default, CI) runs the holdout and randomized tests and deselects the `_IMP` mirrors - `pytest --implementer` runs the `_IMP` and randomized tests with obscured failure output, for implementation sessions - `--seed N` reproduces randomized inputs (seed printed in the header) - provides the `rng` and `report_input` fixtures - checks test naming and holdout/_IMP pairing
Tests: pl.var_detected_by_cat_upset() Add a spec-guided test suite for var_detected_by_cat_upset() (module marked `spec_guided`, run by tests/conftest.py): - TestVarDetectedByCatUpset: 75 holdout tests plus 9 randomized property and metamorphic tests - TestVarDetectedByCatUpsetIMP: 75 _IMP mirrors on different inputs, run only with `pytest --implementer` Coverage: intersection counts and thresholds (min_count / min_fraction, inclusivity, per-category denominators, empty categories, float edge cases), zero/NaN detection, category order and str coercion, sparse input, non-mutation (incl. views), UpSet construction and rendered axes, print_stats tables (incl. column-name collisions), verbose output, save/show, and argument validation. UpSet calls are observed through spies on the upsetplot class; randomized tests use the seeded rng fixture (reproduce with `--seed N`).
Feature: pl.var_detected_by_cat_upset() Add an UpSet plot of which features (.var) are detected in which categories of an .obs column, e.g. which proteins are found in which tissues. - A feature is a member of a category when it is detected (non-NaN in .X; with zero_to_na=True also non-zero) in enough of that category's observations: min_count (default 1) or min_fraction, inclusive, per category. Setting both raises ValueError. - Features that are members of no category form a "No category" set, always included, also with a count of 0. - Categories follow the default pl order: category order for a Categorical column (unused categories kept), else lexicographic order of the str-coerced values. Values colliding after str coercion raise ValueError. - print_stats prints global, per-intersection and per-category tables; verbose reports the input matrix, threshold and sizes. - Sparse .X is densified with a UserWarning; adata is never modified. - Returns the axes dict of upsetplot's UpSet.plot(). Add upsetplot>=0.9.0,<0.10 as a core dependency. upsetplot 0.9.0 is broken on pandas 3 / numpy >= 2.4, so proteopy.pl.upset patches it on import (dot style defaults, single-category aggregation, count-label positions, all-empty totals warning). The upper bound keeps these patches from hitting an untested upsetplot release. Export via pr.pl, list it under Quality Control in the plotting API docs, and add a HISTORY.md entry.
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leventetn
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Implemented sort_by with "degree", "cardinality", "-degree" and "-cardinality". New tests cover all modes, equal counts and degrees, repeatability, bar/dot alignment, and invalid inputs.
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upset_test_spec.md
upset_function_spec.md