def test_gradients_returned_by_xi(self):
# verifies that gradients with respect to xi are returned if cached
points, values, func, df = self._get_sample_2d()
np.random.seed(4321)
for method in self.valid_methods:
interp = InterpND(points, values, method)
x = np.array([0.9, 0.1])
interp._xi = x
dy = np.array([0.997901, 0.08915])
interp._d_dx = dy
assert_almost_equal(interp.gradient(x), dy)
def test_gradients_returned_by_xi(self):
# verifies that gradients with respect to xi are returned if cached
points, values, func, df = self._get_sample_2d()
np.random.seed(4321)
for method in self.interp_methods:
interp = InterpND(method=method, points=points, values=values)
x = np.array([0.9, 0.1])
interp._xi = x
dy = np.array([0.997901, 0.08915])
interp._d_dx = dy
assert_near_equal(interp.gradient(x), dy, tolerance=1e-7)
