def test_DAD(self):
A = poisson((50, 50), format='csr')
x = sp.rand(A.shape[0])
b = sp.rand(A.shape[0])
D = diag_sparse(1.0 /
np.sqrt(10**(12 * sp.rand(A.shape[0]) - 6))).tocsr()
D_inv = diag_sparse(1.0 / D.data)
# DAD = D * A * D
B = np.ones((A.shape[0], 1))
# TODO force 2 level method and check that result is the same
kwargs = {'max_coarse': 1, 'max_levels': 2, 'coarse_solver': 'splu'}
sa = smoothed_aggregation_solver(D * A * D, D_inv * B, **kwargs)
residuals = []
x_sol = sa.solve(b, x0=x, maxiter=10, tol=1e-12, residuals=residuals)
del x_sol
avg_convergence_ratio =\
(residuals[-1] / residuals[0]) ** (1.0 / len(residuals))
# print "Diagonal Scaling Test: %1.3e, %1.3e" %
# (avg_convergence_ratio, 0.25)
assert (avg_convergence_ratio < 0.25)
def test_DAD(self):
A = poisson((50, 50), format='csr')
x = rand(A.shape[0])
b = rand(A.shape[0])
D = diag_sparse(1.0 / sqrt(10 ** (12 * rand(A.shape[0]) - 6))).tocsr()
D_inv = diag_sparse(1.0 / D.data)
DAD = D * A * D
B = ones((A.shape[0], 1))
# TODO force 2 level method and check that result is the same
kwargs = {'max_coarse': 1, 'max_levels': 2, 'coarse_solver': 'splu'}
sa = rootnode_solver(D * A * D, D_inv * B, **kwargs)
residuals = []
x_sol = sa.solve(b, x0=x, maxiter=10, tol=1e-12, residuals=residuals)
avg_convergence_ratio =\
(residuals[-1] / residuals[0]) ** (1.0 / len(residuals))
# print "Diagonal Scaling Test: %1.3e, %1.3e" %
# (avg_convergence_ratio, 0.4)
assert(avg_convergence_ratio < 0.4)
def test_DAD(self):
A = poisson((50, 50), format="csr")
x = rand(A.shape[0])
b = rand(A.shape[0])
D = diag_sparse(1.0 / sqrt(10 ** (12 * rand(A.shape[0]) - 6))).tocsr()
D_inv = diag_sparse(1.0 / D.data)
DAD = D * A * D
B = ones((A.shape[0], 1))
# TODO force 2 level method and check that result is the same
kwargs = {"max_coarse": 1, "max_levels": 2, "coarse_solver": "splu"}
sa = smoothed_aggregation_solver(D * A * D, D_inv * B, **kwargs)
residuals = []
x_sol = sa.solve(b, x0=x, maxiter=10, tol=1e-12, residuals=residuals)
avg_convergence_ratio = (residuals[-1] / residuals[0]) ** (1.0 / len(residuals))
# print "Diagonal Scaling Test: %1.3e, %1.3e" %
# (avg_convergence_ratio, 0.25)
assert avg_convergence_ratio < 0.25
