def test_compute__report_done():
inspector = InspectorShap(model=MockModel(),
algotype='kmeans',
cluster_probability=False)
report_value = pd.DataFrame([[1, 2], [2, 3]],
columns=['cluster_id', 'column_a'])
inspector.cluster_report = report_value
pd.testing.assert_frame_equal(inspector.compute(), report_value)
def test_slice_cluster_no_inputs_not_complementary(global_summary_df,
global_X_shap, global_y,
global_predicted_proba):
inspector = InspectorShap(model=MockModel(), algotype='kmeans')
summary = global_summary_df
inspector.summary_df = summary
inspector.cluster_report = summary
inspector.X_shap = X_shap = global_X_shap
inspector.y = y = global_y
inspector.predicted_proba = predicted_proba = global_predicted_proba
target_cluster_id = 1
correct_mask = returned_mask = [
True, False, False, False, True, False, False, False
]
inspector.get_cluster_mask.return_value = correct_mask
with patch.object(InspectorShap, 'compute') as mocked_compute:
with patch.object(InspectorShap,
'get_cluster_mask') as mock_get_cluster_mask:
mock_get_cluster_mask.return_value = returned_mask
shap_out, y_out, pred_out = inspector.slice_cluster(
target_cluster_id, complementary=False)
# Ensure mocked_compute not called
mocked_compute.accert_not_called()
# Ensure mock_get_cluster_mask called with correct arguments
mock_get_cluster_mask.assert_called_once()
pd.testing.assert_frame_equal(
mock_get_cluster_mask.call_args[0][0], summary)
assert mock_get_cluster_mask.call_args[0][
1] == target_cluster_id
# Check outputs
pd.testing.assert_frame_equal(shap_out, X_shap[correct_mask])
pd.testing.assert_series_equal(y_out, y[correct_mask])
pd.testing.assert_series_equal(pred_out, predicted_proba[correct_mask])
