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import pandas as pd
import pytest
from pandas.testing import assert_frame_equal, assert_series_equal
from upsetplot import generate_counts, generate_samples, query
# `query` is mostly tested through plotting tests, especially tests of
# `_process_data` which cover sort_by, sort_categories_by, subset_size
# and sum_over.
@pytest.mark.parametrize(
"data",
[
generate_counts(),
generate_samples(),
],
)
@pytest.mark.parametrize(
"param_set",
[
[{"present": "cat1"}, {"absent": "cat1"}],
[{"max_degree": 0}, {"min_degree": 1, "max_degree": 2}, {"min_degree": 3}],
[{"max_subset_size": 30}, {"min_subset_size": 31}],
[
{"present": "cat1", "max_subset_size": 30},
{"absent": "cat1", "max_subset_size": 30},
{"present": "cat1", "min_subset_size": 31},
{"absent": "cat1", "min_subset_size": 31},
],
],
)
def test_mece_queries(data, param_set):
unfiltered_results = query(data)
all_results = [query(data, **params) for params in param_set]
# category_totals is unaffected by filter
for results in all_results:
assert_series_equal(unfiltered_results.category_totals, results.category_totals)
combined_data = pd.concat([results.data for results in all_results])
combined_data.sort_index(inplace=True)
assert_frame_equal(unfiltered_results.data.sort_index(), combined_data)
combined_sizes = pd.concat([results.subset_sizes for results in all_results])
combined_sizes.sort_index(inplace=True)
assert_series_equal(unfiltered_results.subset_sizes.sort_index(), combined_sizes)
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