def test_from_dict_nofit(self):
eta = 1
for kernel in kernels_dict.values():
k = kernel(2)
for tail in tails_dict.values():
t = tail()
input_dict = {
"eta": eta,
"kernel": k.to_dict(),
"tail": t.to_dict()
}
if t.degree >= k.dmin:
model = RBF.from_dict(input_dict)
assert model._eta == eta
assert isinstance(model._kernel, kernel)
assert model._kernel.param == 2
assert isinstance(model._tail, tail)
else:
with pytest.raises(ValueError):
model = RBF.from_dict(input_dict)
def test_from_dict_fit_1d(self):
x = np.linspace(0, 2 * np.pi, num=8)
y = func_1d(x)
eta = 1e-3
p = 3
for kernel in kernels_dict.values():
k = kernel(2)
for tail in tails_dict.values():
t = tail()
if t.degree >= k.dmin:
_model = RBF(k, t, eta)
_model.fit(x, y, p)
input_dict = {
"X": x.reshape((-1, 1)).tolist(),
"y": y.tolist(),
"eta": eta,
"kernel": k.to_dict(),
"lambda": _model._lambda.tolist(),
"LU": _model._LU.tolist(),
"piv": _model._piv.tolist(),
"loo": _model._loo_residuals.tolist(),
"tail": _model._tail.to_dict()
}
model = RBF.from_dict(input_dict)
assert model._X.shape == (8, 1)
assert np.allclose(model._X.ravel(), x)
assert model._y.shape == (8, )
assert np.allclose(model._y, y)
assert model._eta == eta
assert isinstance(model._kernel, kernel)
assert model._kernel.param == p
assert np.allclose(model._lambda, _model._lambda)
assert np.allclose(model._LU, _model._LU)
assert np.allclose(model._piv, _model._piv)
assert np.allclose(model._loo_residuals,
_model._loo_residuals)
assert isinstance(model._tail, _model._tail.__class__)
assert np.all(model._tail.params == _model._tail.params)