def test_adapt_contributions_2(self):
"""
Unit test 1 adapt_contributions
Classification with one contribution pd.DataFrame
"""
xpl = SmartExplainer()
contrib = pd.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]],
columns=[
'contribution_0', 'contribution_1',
'contribution_2', 'contribution_3'
],
index=[0, 1, 2])
xpl._case = "regression"
output = xpl.adapt_contributions(contrib)
pd.testing.assert_frame_equal(contrib, output)
def test_adapt_contributions_1(self):
"""
Unit test 1 adapt_contributions
Classification with one contribution pd.DataFrame
"""
xpl = SmartExplainer()
contrib = pd.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]],
columns=[
'contribution_0', 'contribution_1',
'contribution_2', 'contribution_3'
],
index=[0, 1, 2])
model = Mock()
model._classes = np.array([1, 3])
model.predict = types.MethodType(self.predict, model)
model.predict_proba = types.MethodType(self.predict_proba, model)
xpl.model = model
xpl._case, xpl._classes = xpl.check_model()
output = xpl.adapt_contributions(contrib)
assert isinstance(output, list)
assert len(output) == 2
