def test_prepare_X(self):
lor = LinearOrdinalRegression(None, None)
X = np.array([[-1, 0, 1], [0, 1, -1], [1, -1, 0], [-3, 3, -3],
[3, -3, 3]])
X_data, X_scale, X_mean, X_std = lor._prepare_X(X)
assert_array_equal(X_data, X)
assert_array_equal(X_scale, X / 2.0)
assert_array_equal(X_mean, np.array([0, 0, 0]))
assert_array_equal(X_std, np.array([2, 2, 2]))
assert lor.N == 5
assert lor.n_attributes == 3
def test_vanishing_variance_raises_error(self):
lor = LinearOrdinalRegression(None, None)
X = np.array([[1, 1], [1, 2], [1, 3]])
with pytest.raises(ValueError):
lor._prepare_X(X)
def test_prepare_X_from_single_column_dataframe(self, X_ucla, y_ucla):
X_ucla = X_ucla.iloc[:, 0]
lor = LinearOrdinalRegression(None, None)
lor._prepare_X(X_ucla)
assert lor.n_attributes == 1