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)