Example #1
0
def minres(*args, **kwargs):
    return  krylov.minres(*args, **kwargs)
Example #2
0
            nof += 1
            if nof >= nofPrimes:
                break
        i = i+2
    return primes

n = 20000
print 'Generating first %d primes...' % n
primes = get_primes(n)

print 'Assembling coefficient matrix...'
A = spmatrix.ll_mat_sym(n, n*8)
d = 1
while d < n:
    for i in range(d, n):
        A[i,i-d] = 1.0
    d *= 2
for i in range(n):
    A[i,i] = 1.0 * primes[i]

A = A.to_sss()
K = precon.ssor(A)

print 'Solving linear system...'
b = np.zeros(n); b[0] = 1.0
x = np.empty(n)
info, iter, relres = minres(A, b, x, 1e-16, n, K)

print info, iter, relres
print '%.16e' % x[0]
Example #3
0
b = np.arange(n).astype(np.Float)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000)
print 'pcg, K_none: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000, K_diag)
print 'pcg, K_diag: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000, K_jac)
print 'pcg, K_jac: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000, K_ssor)
print 'pcg, K_ssor: ', info, iter, relres, resid(A, b, x)

x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000)
print 'minres, K_none: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000, K_diag)
print 'minres, K_diag: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000, K_jac)
print 'minres, K_jac: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000, K_ssor)
print 'minres, K_ssor: ', info, iter, relres, resid(A, b, x)

x = np.zeros(n, 'd')
info, iter, relres = qmrs(A, b, x, 1e-6, 1000)
print 'qmrs, K_none: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
Example #4
0
def minres(*args, **kwargs):
    return krylov.minres(*args, **kwargs)
Example #5
0
b = np.arange(n).astype(np.Float)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000)
print 'pcg, K_none: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000, K_diag)
print 'pcg, K_diag: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000, K_jac)
print 'pcg, K_jac: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = pcg(A, b, x, 1e-6, 1000, K_ssor)
print 'pcg, K_ssor: ', info, iter, relres, resid(A, b, x)

x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000)
print 'minres, K_none: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000, K_diag)
print 'minres, K_diag: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000, K_jac)
print 'minres, K_jac: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
info, iter, relres = minres(A, b, x, 1e-6, 1000, K_ssor)
print 'minres, K_ssor: ', info, iter, relres, resid(A, b, x)

x = np.zeros(n, 'd')
info, iter, relres = qmrs(A, b, x, 1e-6, 1000)
print 'qmrs, K_none: ', info, iter, relres, resid(A, b, x)
x = np.zeros(n, 'd')
Example #6
0
                break
        i = i + 2
    return primes


n = 20000
print 'Generating first %d primes...' % n
primes = get_primes(n)

print 'Assembling coefficient matrix...'
A = spmatrix.ll_mat_sym(n, n * 8)
d = 1
while d < n:
    for i in range(d, n):
        A[i, i - d] = 1.0
    d *= 2
for i in range(n):
    A[i, i] = 1.0 * primes[i]

A = A.to_sss()
K = precon.ssor(A)

print 'Solving linear system...'
b = np.zeros(n)
b[0] = 1.0
x = np.empty(n)
info, iter, relres = minres(A, b, x, 1e-16, n, K)

print info, iter, relres
print '%.16e' % x[0]