def test_interp_1Dflat_list_x(self):
x = np.array([0., 1., 2., 3., 4.])
y = x**2
f = InterpND(points=x, values=y)
computed = f.interpolate([np.array([2.5]), np.array([3.5])])
assert_equal_arrays(computed, np.array([6.5, 12.5]))
def test_spline_deriv_xi1d(self):
# tests gradient values
points, values, func, df = self._get_sample_2d()
np.random.seed(1234)
test_pt = np.random.uniform(0, 3, 2)
actual = np.array(df(*test_pt))
for method in self.interp_methods:
interp = InterpND(method=method, points=points, values=values)
computed = interp.gradient(test_pt)
r_err = rel_error(actual, computed)
assert r_err < 2.5 * self.tol[method]
# test that gradients have been cached
assert_equal_arrays(interp._xi.flatten(), test_pt.flatten())
assert_equal_arrays(interp._d_dx.flatten(), computed.flatten())
def assert_equal_arrays(self, a1, a2):
assert_equal_arrays(a1, a2)
def assert_equal_arrays(self, a1, a2):
assert_equal_arrays(a1, a2)