def test_reconstruct_f_biharmonic(self):
x, y, xx, yy = sample_data()
nd.reconstruct_f(original_input=x,
original_output=y,
rbf_input=xx,
rbf_output=yy,
basis='multi_quadratic_biharmonic_spline',
radius=10.)
# assert that the argmin(xx) nearest to point x=4.5 is the same index
# for argmin(yy) nearest to point y=20.25, where y=x*x
idx = (np.abs(xx - 4.5)).argmin()
idx2 = (np.abs(yy - 20.25)).argmin()
assert idx == idx2
def test_reconstruct_f_wendland(self):
x, y, xx, yy = sample_data()
nd.reconstruct_f(original_input=x,
original_output=y,
rbf_input=xx,
rbf_output=yy,
basis='beckert_wendland_c2_basis',
radius=20.)
# assert that the argmin(xx) nearest to point x=4.5 is the same index
# for argmin(yy) nearest to point y=20.25, where y=x*x
idx = (np.abs(xx - 4.5)).argmin()
idx2 = (np.abs(yy - 20.25)).argmin()
assert idx == idx2
def test_reconstruct_f_vectorial(self):
x = np.arange(10).reshape(5, 2)
y = np.square(x)
x_rbf = np.arange(8).reshape(4, 2)
y_rbf = np.zeros(x_rbf.shape)
nd.reconstruct_f(original_input=x,
original_output=y,
rbf_input=x_rbf,
rbf_output=y_rbf,
radius=1.0,
basis='beckert_wendland_c2_basis')
y_rbf_expected = np.asarray([[0., 1.], [4., 9.], [16., 25.],
[36., 49.]])
np.testing.assert_almost_equal(y_rbf, y_rbf_expected)
def test_reconstruct_f_scalar(self):
x = np.arange(10)
y = x * x
x_rbf = np.linspace(0, 9, 5)
y_rbf = np.zeros(5)
nd.reconstruct_f(original_input=x,
original_output=y,
rbf_input=x_rbf,
rbf_output=y_rbf,
basis='beckert_wendland_c2_basis',
radius=2.)
y_rbf_expected = np.asarray(
[0., 4.85579754, 19.1322168, 44.53940674, 81.])
np.testing.assert_almost_equal(y_rbf, y_rbf_expected)