class TestRidgeIntegration(TestCase): def setUp(self): df = pd.read_csv(path.join(BASE_DIR, '../models/categorical-test.csv')) Xte = df.iloc[:, 1:] Xte = pd.get_dummies(Xte, prefix_sep='') del Xte['age(20,30]'] yte = df.iloc[:, 0] self.test = (Xte, yte) pmml = path.join(BASE_DIR, '../models/linear-model-ridge.pmml') self.clf = PMMLRidge(pmml) def test_predict(self): Xte, _ = self.test ref = np.array([0.56707253, 0.44086932, 0.70106631, 0.63462966, 0.75552995, 0.60126409, 0.4352619 , 0.55362532, 0.40207959, 0.68526355, 0.77666758, 0.53249166, 0.61717879, 0.51593912, 0.49949509, 0.49068951, 0.26094857, 0.71970929, 0.57488419, 0.61499657, 0.6551319 , 0.59615382, 0.42850703, 0.52000645, 0.44016652, 0.42641415, 0.56069061, 0.21493887, 0.17195355, 0.33184511, 0.4237941 , 0.08433666, 0.34454511, 0.26253933, 0.23076609, 0.39833734, 0.35012744, 0.36532649, 0.42733187, 0.42595108, 0.18051046, 0.28151586, 0.25718191, 0.38083643, 0.43149017, 0.46942765, 0.29962233, 0.31491245, 0.49074276, 0.19720312, 0.36989965, 0.41818817]) assert np.allclose(ref, self.clf.predict(Xte)) def test_score(self): Xte, yte = self.test ref = 0.3286660932879891 assert ref == self.clf.score(Xte, yte == 'Yes') def test_fit_exception(self): with self.assertRaises(Exception) as cm: self.clf.fit(np.array([[]]), np.array([])) assert str(cm.exception) == 'Not supported.'
class TestGeneralRegressionIntegration(TestCase): def setUp(self): df = pd.read_csv(path.join(BASE_DIR, '../models/categorical-test.csv')) Xte = df.iloc[:, 1:] yte = df.iloc[:, 0] self.test = (Xte, yte) pmml = path.join(BASE_DIR, '../models/linear-model-glm.pmml') self.clf = PMMLRidge(pmml) def test_predict(self): Xte, _ = self.test ref = np.array([ 0.76984714, 0.62777417, 0.97269501, 0.92573904, 1.07729711, 0.84270291, 0.49553349, 0.71685506, 0.47088161, 0.97486390, 1.05130371, 0.61683889, 0.91572548, 0.77157660, 0.62100866, 0.58980751, 0.23293754, 1.05549000, 0.73136668, 0.91028562, 0.98442322, 0.76697277, 0.54041194, 0.66282497, 0.55121962, 0.50143919, 0.76523718, 0.14555227, 0.05832986, 0.33383867, 0.53914144, -0.11052323, 0.40016843, 0.22597578, 0.14323672, 0.51625628, 0.36130025, 0.39572621, 0.46020273, 0.52182059, -0.00768403, 0.26640930, 0.20815075, 0.38098647, 0.49802258, 0.56473838, 0.24103994, 0.26506002, 0.52001876, 0.14958276, 0.38839055, 0.46138168 ]) assert np.allclose(ref, self.clf.predict(Xte)) def test_score(self): Xte, yte = self.test ref = 0.4791710734180739 assert ref == self.clf.score(Xte, yte == 'Yes')