def _compare(x_raw, n_state):
basis = discretize(n_state=n_state)
return pipe(
np.linspace(0, 1, n_state),
lambda h: np.sum(basis(x_raw) * h[None, None, None, :], axis=-1),
lambda x: np.allclose(x_raw, x),
)
def _mks_fcoeff(x_data, n_space, n_state):
return fit(
x_data,
_response(x_data, n_space, n_state),
discretize(n_state=n_state),
redundancy_func=redundancy,
)
def test_error():
"""Test data outside the bounds
If the local state values in the microstructure are outside of the
domain they are remapped inside of the domain
"""
basis = discretize(n_state=2)
assert np.allclose(basis(np.array([-1, 1])), [[1, 0], [0, 1]])
def test_local_min_max():
"""Local state example with varying min and max.
An example where the local state space domain is between `[-1,
1]`.
"""
basis = discretize(n_state=3, min_=-1)
assert np.allclose(
basis(np.array([-1, 0, 1, 0.5])),
[[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 0.5, 0.5]],
)
def test():
"""Very simple example."""
assert np.allclose(
fit(
_get_x(),
_get_x().swapaxes(1, 2),
discretize(n_state=2),
redundancy_func=redundancy,
),
[[[0.5, 0.5], [-2, 0]], [[-0.5, 0], [-1, 0]]],
)
def _test_data(n_state):
basis = discretize(n_state=n_state)
states = lambda: np.linspace(0, 1, n_state)[None, None, None, :]
return np.sum(basis(_x_data()) * states(), axis=-1)
