def test_predict_input_wrong(self):
indev = IndividualDeviation(w_martingale=15, non_conformity="median", k=20, dev_threshold=0.6)
indev.fit(np.array([[1,2,3], [4,5,6], [7,8,9]]))
with self.assertRaises(InputValidationError):
indev.predict(None, [])
with self.assertRaises(InputValidationError):
indev.predict(None, "foo")
def test_init(self):
with self.assertRaises(InputValidationError):
IndividualDeviation(w_martingale=0, non_conformity="median", k=20, dev_threshold=0.6)
with self.assertRaises(InputValidationError):
IndividualDeviation(w_martingale=-1, non_conformity="median", k=20, dev_threshold=0.6)
with self.assertRaises(InputValidationError):
IndividualDeviation(w_martingale=15, non_conformity="foo", k=20, dev_threshold=0.6)
with self.assertRaises(InputValidationError):
IndividualDeviation(w_martingale=15, non_conformity="knn", k=0, dev_threshold=0.6)
with self.assertRaises(InputValidationError):
IndividualDeviation(w_martingale=15, non_conformity="knn", k=-1, dev_threshold=0.6)
with self.assertRaises(InputValidationError):
IndividualDeviation(w_martingale=15, non_conformity="median", k=20, dev_threshold=-1)
with self.assertRaises(InputValidationError):
IndividualDeviation(w_martingale=15, non_conformity="median", k=20, dev_threshold=2)
def test_predict_not_fitted(self):
indev = IndividualDeviation(w_martingale=15, non_conformity="median", k=20, dev_threshold=0.6)
with self.assertRaises(NotFittedError):
indev.predict(None, [1,1,1])
def test_predict_median_w3(self):
indev = IndividualDeviation(w_martingale=3, non_conformity="median", k=20, dev_threshold=0.6)
indev.fit(np.array([[1,2,3], [4,5,6], [7,8,9]]))
res = indev.predict(None, [1,1,1])
expected = DeviationContext((3**2+4**2+5**2)**0.5, 0, 1/3, False)
self.assertEqual(res, expected)
def test_fit_knn_k2(self):
indev = IndividualDeviation(w_martingale=15, non_conformity="knn", k=2, dev_threshold=0.6)
indev.fit(np.array([[1,2,3], [4,5,6], [7,8,9]]))
expected = [ (0 + 3**(3/2)) / 2, (3**(3/2) + 0) / 2, (3**(3/2) + 0) / 2 ]
self.assertEqual(indev.scores, expected)
self.assertTrue(np.allclose(indev.scores, expected))
def test_fit_median(self):
indev = IndividualDeviation(w_martingale=15, non_conformity="median", k=20, dev_threshold=0.6)
indev.fit(np.array([[1,2,3], [4,5,6], [7,8,9]]))
expected = [3**(3/2), 0, 3**(3/2)]
self.assertEqual(indev.scores, expected)
self.assertTrue(np.allclose(indev.scores, expected))
def test_fit_input_empty(self):
indev = IndividualDeviation(w_martingale=15, non_conformity="median", k=20, dev_threshold=0.6)
with self.assertRaises(InputValidationError):
indev.fit([])