def test_compute_report_multiple_df(
global_clusters,
global_y,
global_predicted_proba,
global_summary_df,
global_aggregate_summary_df,
global_summary_dfs,
global_ys,
global_predicted_probas,
global_aggregate_summary_dfs_eval_set,
):
inspector = InspectorShap(model=MockModel(), algotype="kmeans")
inspector.hasmultiple_dfs = True
inspector.normalize_proba = False
inspector.clusters = global_clusters
inspector.y = global_y
inspector.predicted_proba = global_predicted_proba
inspector.ys = global_ys
inspector.predicted_probas = global_predicted_probas
target_summary_df = global_summary_df
target_summary_dfs = global_summary_dfs
aggregated_summary_df = global_aggregate_summary_df
aggregated_summary_dfs = global_aggregate_summary_dfs_eval_set
with patch.object(InspectorShap,
"create_summary_df") as mock_create_summary_df:
with patch.object(
InspectorShap,
"aggregate_summary_df") as mock_aggregate_summary_df:
# Set returns for each call of methods
mock_create_summary_df.side_effect = [
target_summary_df, target_summary_dfs[0],
target_summary_dfs[1]
]
mock_aggregate_summary_df.side_effect = [
aggregated_summary_df,
aggregated_summary_dfs[0],
aggregated_summary_dfs[1],
]
inspector._compute_report()
assert inspector.agg_summary_df.equals(aggregated_summary_df)
assert inspector.summary_df.equals(target_summary_df)
for index, item in inspector.agg_summary_dfs:
assert item.equals(aggregated_summary_dfs[index])
for index, item in inspector.summary_dfs:
assert item.equals(target_summary_dfs[index])
def test_compute_report_single_df(global_clusters, global_y,
global_predicted_proba,
global_summary_df,
global_aggregate_summary_df):
inspector = InspectorShap(model=MockModel(), algotype='kmeans')
inspector.hasmultiple_dfs = False
inspector.normalize_proba = target_normalize = False
inspector.clusters = input_clust = global_clusters
inspector.y = input_y = global_y
inspector.predicted_proba = input_predicted_proba = global_predicted_proba
target_summary_df = global_summary_df
aggregated_summary = global_aggregate_summary_df
with patch.object(InspectorShap,
'create_summary_df') as mock_create_summary_df:
with patch.object(
InspectorShap,
'aggregate_summary_df') as mock_aggregate_summary_df:
mock_create_summary_df.return_value = target_summary_df
mock_aggregate_summary_df.return_value = aggregated_summary
inspector._compute_report()
#check if the methods were called with correct arguments
pd.testing.assert_frame_equal(
mock_aggregate_summary_df.call_args[0][0],
target_summary_df)
pd.testing.assert_series_equal(
mock_create_summary_df.call_args[0][0], input_clust)
pd.testing.assert_series_equal(
mock_create_summary_df.call_args[0][1], input_y)
pd.testing.assert_series_equal(
mock_create_summary_df.call_args[0][2],
input_predicted_proba)
assert mock_create_summary_df.call_args[1][
'normalize'] == target_normalize
# Check if the function correctly stored variables
pd.testing.assert_frame_equal(inspector.agg_summary_df,
aggregated_summary)
pd.testing.assert_frame_equal(inspector.summary_df, target_summary_df)
