# x0 = random((4,1))
# %timeit -n 15 (x,flag) = gmres(A,b,x0,tol=1e-8,maxiter=100)
from pyamg.gallery import poisson
from numpy.random import random
from pyamg.util.linalg import norm
A = poisson((125, 125), dtype=float, format='csr')
# A.data = A.data + 0.001j*rand(A.data.shape[0])
b = random((A.shape[0], ))
x0 = random((A.shape[0], ))
import time
from scipy.sparse.linalg.isolve import gmres as igmres
print('\n\nTesting GMRES with %d x %d 2D Laplace Matrix' %
(A.shape[0], A.shape[0]))
t1 = time.time()
(x, flag) = gmres_mgs(A, b, x0, tol=1e-8, maxiter=500)
t2 = time.time()
print('%s took %0.3f ms' % ('gmres', (t2 - t1) * 1000.0))
print('norm = %g' % (norm(b - A * x)))
print('info flag = %d' % (flag))
t1 = time.time()
# DON"T Enforce a maxiter as scipy gmres can't handle it correctly
(y, flag) = igmres(A, b, x0, tol=1e-8)
t2 = time.time()
print('\n%s took %0.3f ms' % ('linalg gmres', (t2 - t1) * 1000.0))
print('norm = %g' % (norm(b - A * y)))
print('info flag = %d' % (flag))
# x0 = random((4,1))
# %timeit -n 15 (x,flag) = gmres(A,b,x0,tol=1e-8,maxiter=100)
from pyamg.gallery import poisson
from numpy.random import random
from pyamg.util.linalg import norm
A = poisson((125, 125), dtype=float, format='csr')
# A.data = A.data + 0.001j*rand(A.data.shape[0])
b = random((A.shape[0],))
x0 = random((A.shape[0],))
import time
from scipy.sparse.linalg.isolve import gmres as igmres
print('\n\nTesting GMRES with %d x %d 2D Laplace Matrix' %
(A.shape[0], A.shape[0]))
t1 = time.time()
(x, flag) = gmres_mgs(A, b, x0, tol=1e-8, maxiter=500)
t2 = time.time()
print('%s took %0.3f ms' % ('gmres', (t2-t1)*1000.0))
print('norm = %g' % (norm(b - A*x)))
print('info flag = %d' % (flag))
t1 = time.time()
# DON"T Enforce a maxiter as scipy gmres can't handle it correctly
(y, flag) = igmres(A, b, x0, tol=1e-8)
t2 = time.time()
print('\n%s took %0.3f ms' % ('linalg gmres', (t2-t1)*1000.0))
print('norm = %g' % (norm(b - A*y)))
print('info flag = %d' % (flag))