def case_spd_linsys(
spd_matrix: Union[np.ndarray, scipy.sparse.spmatrix,
linops.LinearOperator],
rng: np.random.Generator,
) -> problems.LinearSystem:
"""Linear system with symmetric positive definite matrix."""
return random_linear_system(rng=rng, matrix=spd_matrix)
def test_custom_solution_randvar(rng: np.random.Generator):
n = 5
x = randvars.Normal(mean=np.ones(n), cov=np.eye(n))
_ = random_linear_system(rng=rng,
matrix=random_spd_matrix,
solution_rv=x,
dim=n)
def test_incompatible_matrix_and_solution(rng: np.random.Generator):
with pytest.raises(ValueError):
_ = random_linear_system(
rng=rng,
matrix=random_spd_matrix,
solution_rv=randvars.Normal(np.ones(2), np.eye(2)),
dim=5,
)
"""Probabilistic linear solver state test cases."""
import numpy as np
from pytest_cases import case
from probnum import linalg, linops, randvars
from probnum.problems.zoo.linalg import random_linear_system, random_spd_matrix
# Problem
n = 10
linsys = random_linear_system(
rng=np.random.default_rng(42), matrix=random_spd_matrix, dim=n
)
# Prior
Ainv = randvars.Normal(
mean=linops.Identity(n), cov=linops.SymmetricKronecker(linops.Identity(n))
)
b = randvars.Constant(linsys.b)
prior = linalg.solvers.beliefs.LinearSystemBelief(
A=randvars.Constant(linsys.A),
Ainv=Ainv,
x=(Ainv @ b[:, None]).reshape(
(n,)
), # TODO: This can be replaced by Ainv @ b once https://github.com/probabilistic-numerics/probnum/issues/456 is fixed
b=b,
)
@case(tags=["initial"])
def case_initial_state(
def case_linsys(
matrix: Union[np.ndarray, scipy.sparse.spmatrix, linops.LinearOperator],
rng: np.random.Generator,
) -> problems.LinearSystem:
"""Linear system."""
return random_linear_system(rng=rng, matrix=matrix)
def test_custom_random_matrix(rng: np.random.Generator):
random_unitary_matrix = lambda rng, dim: scipy.stats.unitary_group.rvs(
dim=dim, random_state=rng)
_ = random_linear_system(rng, random_unitary_matrix, dim=5)
