Esempio n. 1
0
             nu.value += max(int(-hpddm.optionVal(opt, b'geneo_nu') + 1), (-1)**rankWorld * rankWorld)
         threshold = hpddm.underlying(max(0, hpddm.optionVal(opt, b'geneo_threshold')))
         hpddm.schwarzSolveGEVP(A, MatNeumann, ctypes.byref(nu), threshold)
         addr = hpddm.optionAddr(opt, b'geneo_nu')
         addr.contents.value = nu.value
     else:
         nu = 1
         deflation = numpy.ones((dof, nu), order = 'F', dtype = hpddm.scalar)
         hpddm.setVectors(hpddm.schwarzPreconditioner(A), nu, deflation)
     hpddm.initializeCoarseOperator(hpddm.schwarzPreconditioner(A), nu)
     hpddm.schwarzBuildCoarseOperator(A, hpddm.MPI_Comm.from_address(MPI._addressof(MPI.COMM_WORLD)))
 hpddm.schwarzCallNumfact(A)
 if rankWorld != 0:
     hpddm.optionRemove(opt, b'verbosity')
 comm = hpddm.getCommunicator(hpddm.schwarzPreconditioner(A))
 it = hpddm.solve(A, f, sol, comm)
 storage = numpy.empty(2 * mu, order = 'F', dtype = hpddm.underlying)
 hpddm.schwarzComputeError(A, sol, f, storage)
 if rankWorld == 0:
     for nu in xrange(mu):
         if nu == 0:
             print(' --- error = ', end = '')
         else:
             print('             ', end = '')
         print('{:e} / {:e}'.format(storage[1 + 2 * nu], storage[2 * nu]), end = '')
         if mu > 1:
             print(' (rhs #{:d})'.format(nu + 1), end = '')
         print('')
 if it > 45:
     status = 1
 else:
Esempio n. 2
0
lu = scipy.sparse.linalg.spilu(csr.tocsc(), drop_tol = hpddm.optionApp(opt, b'drop_tol'), fill_factor = hpddm.optionApp(opt, b'fill_factor'))
@hpddm.precondFunc
def precond(y, x, n, m):
    if m == 1:
        x._shape_ = (n,)
        y._shape_ = (n,)
        x = numpy.ctypeslib.as_array(x, (n,))
        y = numpy.ctypeslib.as_array(y, (n,))
    else:
        x._shape_ = (m, n)
        y._shape_ = (m, n)
        x = numpy.ctypeslib.as_array(x, (m, n)).transpose()
        y = numpy.ctypeslib.as_array(y, (m, n)).transpose()
    x[:] = lu.solve(y[:])

it = hpddm.solve(Mat, precond, f, sol)

status = 0
nrmb = numpy.linalg.norm(f, axis = 0)
tmp = numpy.empty_like(f)
hpddm.csrmv(Mat, sol, tmp)
tmp -= f
nrmAx = numpy.linalg.norm(tmp, axis = 0)
if mu == 1:
    nrmb = [ nrmb ]
    nrmAx = [ nrmAx ]
for nu in xrange(mu):
    if nu == 0:
        print(' --- residual = ', end = '')
    else:
        print('                ', end = '')
Esempio n. 3
0
     if nu.value > 0:
         if hpddm.optionApp(opt, b'nonuniform'):
             addr.contents.value += max(int(-addr.contents.value + 1), (-1)**rankWorld * rankWorld)
         hpddm.schwarzSolveGEVP(A, MatNeumann)
         nu = int(hpddm.optionVal(opt, b'geneo_nu'))
     else:
         nu = 1
         deflation = numpy.ones((dof, nu), order = 'F', dtype = hpddm.scalar)
         hpddm.setVectors(hpddm.schwarzPreconditioner(A), nu, deflation)
     hpddm.initializeCoarseOperator(hpddm.schwarzPreconditioner(A), nu)
     hpddm.schwarzBuildCoarseOperator(A, hpddm.MPI_Comm.from_address(MPI._addressof(MPI.COMM_WORLD)))
 hpddm.schwarzCallNumfact(A)
 if rankWorld != 0:
     hpddm.optionRemove(opt, b'verbosity')
 comm = hpddm.getCommunicator(hpddm.schwarzPreconditioner(A))
 it = hpddm.solve(A, f, sol, comm)
 storage = numpy.empty(2 * mu, order = 'F', dtype = hpddm.underlying)
 hpddm.schwarzComputeResidual(A, sol, f, storage)
 if rankWorld == 0:
     for nu in xrange(mu):
         if nu == 0:
             print(' --- residual = ', end = '')
         else:
             print('                ', end = '')
         print('{:e} / {:e}'.format(storage[1 + 2 * nu], storage[2 * nu]), end = '')
         if mu > 1:
             print(' (rhs #{:d})'.format(nu + 1), end = '')
         print('')
 if it > (60 if int(hpddm.optionVal(opt, b'krylov_method')) == 6 else 45):
     status = 1
 else: