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