def test_kernel_transform_feature_mismatch(make_data): data, _ = make_data() t = ClinicalKernelTransform() t.fit(data) with pytest.raises(ValueError, match='expected array with 4 features, but got 17'): t.transform(numpy.zeros((2, 17), dtype=float))
def test_kernel_transform(make_data): data, expected = make_data() t = ClinicalKernelTransform() t.fit(data) mat = t.transform(t.X_fit_) assert_array_almost_equal(expected, mat, 4)
def test_kernel_transform(self): t = ClinicalKernelTransform() t.fit(self.data) mat = t.transform(t.X_fit_) expected = _get_expected_matrix() assert_array_almost_equal(expected, mat, 4)
def test_kernel_transform_x_and_y(self): t = ClinicalKernelTransform(fit_once=True) t.prepare(self.data) x_num = t.X_fit_.copy() t.fit(x_num[:3, :]) mat = t.transform(x_num[3:, :]) m = _get_expected_matrix() expected = m[:3, 3:].T assert_array_almost_equal(expected, mat, 4)
def test_kernel_transform_x_and_y(make_data): data, m = make_data() t = ClinicalKernelTransform(fit_once=True) t.prepare(data) x_num = t.X_fit_.copy() t.fit(x_num[:3, :]) mat = t.transform(x_num[3:, :]) expected = m[:3, 3:].T assert_array_almost_equal(expected, mat, 4)