def test_targets(with_std, with_value):
expl = Explanation(
estimator='some estimator',
targets=[
TargetExplanation(
'y',
feature_weights=FeatureWeights(
pos=[
FeatureWeight('a',
13,
std=0.13 if with_std else None,
value=2 if with_value else None),
FeatureWeight('b',
5,
std=0.5 if with_std else None,
value=1 if with_value else None)
],
neg=[
FeatureWeight('neg1',
-10,
std=0.2 if with_std else None,
value=5 if with_value else None),
FeatureWeight('neg2',
-1,
std=0.3 if with_std else None,
value=4 if with_value else None)
],
)),
TargetExplanation('y2',
feature_weights=FeatureWeights(
pos=[FeatureWeight('f', 1)],
neg=[],
)),
],
)
df_dict = format_as_dataframes(expl)
assert isinstance(df_dict, dict)
assert list(df_dict) == ['targets']
df = df_dict['targets']
expected_df = pd.DataFrame(
{
'target': ['y', 'y', 'y', 'y', 'y2'],
'feature': ['a', 'b', 'neg2', 'neg1', 'f'],
'weight': [13, 5, -1, -10, 1]
},
columns=['target', 'feature', 'weight'])
if with_std:
expected_df['std'] = [0.13, 0.5, 0.3, 0.2, None]
if with_value:
expected_df['value'] = [2, 1, 4, 5, None]
print(df, expected_df, sep='\n')
assert expected_df.equals(df)
single_df = format_as_dataframe(expl)
assert expected_df.equals(single_df)
def test_transition_features():
expl = Explanation(
estimator='some estimator',
targets=[
TargetExplanation('class1',
feature_weights=FeatureWeights(
pos=[FeatureWeight('pos', 13, value=1)],
neg=[],
)),
TargetExplanation('class2',
feature_weights=FeatureWeights(
pos=[FeatureWeight('pos', 13, value=1)],
neg=[],
)),
],
transition_features=TransitionFeatureWeights(
class_names=['class2', 'class1'], # reverse on purpose
coef=np.array([[1.5, 2.5], [3.5, 4.5]]),
))
df_dict = format_as_dataframes(expl)
assert isinstance(df_dict, dict)
assert set(df_dict) == {'targets', 'transition_features'}
assert df_dict['targets'].equals(format_as_dataframe(expl.targets))
df = df_dict['transition_features']
print(df)
print(format_as_text(expl))
expected = pd.DataFrame([
{
'from': 'class2',
'to': 'class2',
'coef': 1.5
},
{
'from': 'class2',
'to': 'class1',
'coef': 2.5
},
{
'from': 'class1',
'to': 'class2',
'coef': 3.5
},
{
'from': 'class1',
'to': 'class1',
'coef': 4.5
},
],
columns=['from', 'to', 'coef'])
assert df.equals(expected)
with pytest.warns(UserWarning):
single_df = format_as_dataframe(expl)
assert single_df.equals(df)
