def test_pos_class(self):
X = np.array([0.50, 0.75, 1.00])
y = np.array([0, 1, 2])
X = X[:, np.newaxis]
with self.assertRaises(ValueError):
_logistic_regression_path(X,
y,
epsilon=1,
data_norm=1.0,
Cs=[1e5],
pos_class=None)
def test_coef(self):
_logistic_regression_path(self.X,
self.y,
epsilon=1,
data_norm=1.0,
Cs=[1e5],
coef=np.ones(2))
with self.assertRaises(ValueError):
_logistic_regression_path(self.X,
self.y,
epsilon=1,
data_norm=1.0,
Cs=[1e5],
coef=np.ones(3))
def test_with_dataset(self):
output = _logistic_regression_path(self.X,
self.y,
epsilon=1,
data_norm=1,
Cs=[1e5])
self.assertIsInstance(output, tuple)
def test_Cs(self):
coefs, Cs, n_iter = _logistic_regression_path(self.X,
self.y,
epsilon=1,
data_norm=1,
Cs=3)
self.assertEqual(len(coefs), 3)
self.assertEqual(len(Cs), 3)
self.assertEqual(len(n_iter), 3)
def test_with_dataset(self):
output = _logistic_regression_path(self.X, self.y, Cs=[1e5])
self.assertTrue(isinstance(output, tuple))
def test_no_norm(self):
with self.assertRaises(TypeError):
_logistic_regression_path(self.X, self.y, Cs=[1e5], epsilon=1)