def test_compute__multiple_df_set_names(global_mock_summary_df,
global_mock_aggregate_summary_dfs):
inspector = InspectorShap(model=MockModel(),
algotype='kmeans',
cluster_probability=False)
inspector.hasmultiple_dfs = True
inspector.set_names = ['suf1', 'suf2']
report_value = global_mock_summary_df
inspector.agg_summary_dfs = global_mock_aggregate_summary_dfs
expected_result = pd.DataFrame([[1, 2, 3, 2], [2, 3, 3, 3]],
columns=[
'cluster_id', 'column_a',
'column_a_suf1', 'column_a_suf2'
])
def mock_compute_report(self):
self.agg_summary_df = report_value
with patch.object(InspectorShap, '_compute_report',
mock_compute_report):
output = inspector.compute()
# Check output and side effects
pd.testing.assert_frame_equal(output, expected_result)
pd.testing.assert_frame_equal(inspector.cluster_report,
expected_result)
pd.testing.assert_frame_equal(inspector.agg_summary_df, report_value)
def test_compute__multiple_df(global_mock_summary_df,
global_mock_aggregate_summary_dfs):
inspector = InspectorShap(model=MockModel(),
algotype="kmeans",
cluster_probability=False)
inspector.hasmultiple_dfs = True
report_value = global_mock_summary_df
inspector.agg_summary_dfs = global_mock_aggregate_summary_dfs
expected_result = pd.DataFrame([[1, 2, 3, 2], [2, 3, 3, 3]],
columns=[
"cluster_id", "column_a",
"column_a_sample_1",
"column_a_sample_2"
])
def mock_compute_report(self):
self.agg_summary_df = report_value
with patch.object(InspectorShap, "_compute_report",
mock_compute_report):
output = inspector.compute()
# Check output and side effects
pd.testing.assert_frame_equal(output, expected_result)
pd.testing.assert_frame_equal(inspector.cluster_report,
expected_result)
pd.testing.assert_frame_equal(inspector.agg_summary_df, report_value)
