def test_coarse_grid_solver(self):
cases = []
cases.append(csr_matrix(diag(arange(1, 5, dtype=float))))
cases.append(poisson((4, ), format='csr'))
cases.append(poisson((4, 4), format='csr'))
from pyamg.krylov import cg
def fn(A, b):
return cg(A, b)[0]
# method should be almost exact for small matrices
for A in cases:
for solver in [
'splu', 'pinv', 'pinv2', 'lu', 'cholesky', 'cg', fn
]:
s = coarse_grid_solver(solver)
b = arange(A.shape[0], dtype=A.dtype)
x = s(A, b)
assert_almost_equal(A * x, b)
# subsequent calls use cached data
x = s(A, b)
assert_almost_equal(A * x, b)
def test_coarse_grid_solver(self):
cases = []
cases.append(csr_matrix(diag(arange(1, 5, dtype=float))))
cases.append(poisson((4,), format='csr'))
cases.append(poisson((4, 4), format='csr'))
from pyamg.krylov import cg
def fn(A, b):
return cg(A, b)[0]
# method should be almost exact for small matrices
for A in cases:
for solver in ['splu', 'pinv', 'pinv2', 'lu', 'cholesky',
'cg', fn]:
s = coarse_grid_solver(solver)
b = arange(A.shape[0], dtype=A.dtype)
x = s(A, b)
assert_almost_equal(A*x, b)
# subsequent calls use cached data
x = s(A, b)
assert_almost_equal(A*x, b)
def test_coarse_grid_solver(self):
cases = []
cases.append(csr_matrix(diag(arange(1, 5))))
cases.append(poisson((4, ), format='csr'))
cases.append(poisson((4, 4), format='csr'))
# Make cases complex
cases = [G + 1e-5j * G for G in cases]
cases = [0.5 * (G + G.H) for G in cases]
# method should be almost exact for small matrices
for A in cases:
for solver in ['splu', 'pinv', 'pinv2', 'lu', 'cholesky', 'cg']:
s = coarse_grid_solver(solver)
b = arange(A.shape[0], dtype=A.dtype)
x = s(A, b)
assert_almost_equal(A * x, b)
# subsequent calls use cached data
x = s(A, b)
assert_almost_equal(A * x, b)
def test_coarse_grid_solver(self):
cases = []
cases.append(csr_matrix(diag(arange(1, 5))))
cases.append(poisson((4,), format='csr'))
cases.append(poisson((4, 4), format='csr'))
# Make cases complex
cases = [G+1e-5j*G for G in cases]
cases = [0.5*(G + G.H) for G in cases]
# method should be almost exact for small matrices
for A in cases:
for solver in ['splu', 'pinv', 'pinv2', 'lu', 'cholesky', 'cg']:
s = coarse_grid_solver(solver)
b = arange(A.shape[0], dtype=A.dtype)
x = s(A, b)
assert_almost_equal(A*x, b)
# subsequent calls use cached data
x = s(A, b)
assert_almost_equal(A*x, b)
