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)