def test_solve_dposv(problem):
A, b, size = problem
# square values of A
A = A * A
# and solve
xexp, resid, rank, s = np.linalg.lstsq(A, b, rcond=None)
F = A.T @ A
x = A.T @ b
dposv(F, x, True)
assert x == approx(xexp, rel=1.0e-3)
def test_solve_dposv():
size = np.random.randint(5, 50)
A = np.random.randn(size, size)
b = np.random.randn(size)
# square values of A
A = A * A
# and solve
xexp, resid, rank, s = np.linalg.lstsq(A, b, rcond=None)
F = A.T @ A
x = A.T @ b
dposv(F, x, True)
assert x == approx(xexp, rel=1.0e-3)