def __init__(self, A, **kwargs):
PysparseDirectSolver.__init__(self, A, **kwargs)
if 'strategy' in kwargs.keys():
strategy = upper(kwargs.get('strategy'))
if strategy not in ['AUTO', 'UNSYMMETRIC', 'SYMMETRIC', '2BY2']:
strategy = 'AUTO'
kwargs['strategy'] = 'UMFPACK_STRATEGY_' + strategy
if 'scale' in kwargs.keys():
scale = upper(kwargs.get('scale'))
if scale not in ['NONE', 'SUM', 'MAX']: scale = 'SUM'
kwargs['scale'] = 'UMFPACK_SCALE_' + scale
self.type = numpy.float
self.nrow, self.ncol = A.getShape()
t = cputime()
self.LU = umfpack.factorize(A.matrix, **kwargs)
self.factorizationTime = cputime() - t
self.solutionTime = 0.0
self.sol = None
self.L = self.U = None
self.P = self.Q = self.R = None
self.do_recip = False
self.lnz = self.unz = self.nz_udiag = None
return
def SolveNextTime(self):
r"""
Calculate the next time (factorization)
and update the time stack grids
"""
try:
self.tstep += 1
except:
self.tstep = 0
self.LinearSystem()
self.mUtLU = umfpack.factorize(
self.mUt, strategy="UMFPACK_STRATEGY_SYMMETRIC")
# gets the m factor from the solved system
# As t is in [0, 1, 2] (2nd order)
# time t in this case is Utime[2]
# the independent term of the matrix, due the pressure field
v = self.Independent()
result = np.empty(self.Nx * self.Nz)
self.mUtLU.solve(v, result)
# reshape the vector to become a matrix again
self.Ufuture = np.reshape(result, (self.Nz, self.Nx))
# make the update in the time stack
# before [t-2, t-1, t]
# after [t-1, t, t+1]
# so t-2 receive t-1 and etc.
# make the update in the time stack
self.Uprevious[:][:] = self.Ucurrent[:][:]
self.Ucurrent[:][:] = self.Ufuture[:][:]
return self.Ufuture
def __init__(self, A, **kwargs):
PysparseDirectSolver.__init__(self, A, **kwargs)
if 'strategy' in kwargs.keys():
strategy = upper(kwargs.get('strategy'))
if strategy not in ['AUTO', 'UNSYMMETRIC', 'SYMMETRIC', '2BY2']:
strategy = 'AUTO'
kwargs['strategy'] = 'UMFPACK_STRATEGY_' + strategy
if 'scale' in kwargs.keys():
scale = upper(kwargs.get('scale'))
if scale not in ['NONE', 'SUM', 'MAX']: scale = 'SUM'
kwargs['scale'] = 'UMFPACK_SCALE_' + scale
self.type = numpy.float
self.nrow, self.ncol = A.getShape()
t = cputime()
self.LU = umfpack.factorize(A.matrix, **kwargs)
self.factorizationTime = cputime() - t
self.solutionTime = 0.0
self.sol = None
self.L = self.U = None
self.P = self.Q = self.R = None
self.do_recip = False
self.lnz = self.unz = self.nz_udiag = None
return
def SolveNextTime(self):
r"""
Calculate the next time (factorization)
and update the time stack grids
"""
try:
self.tstep += 1
except :
self.tstep = 0
self.LinearSystem()
self.mUtLU = umfpack.factorize(self.mUt, strategy="UMFPACK_STRATEGY_SYMMETRIC")
# gets the m factor from the solved system
# As t is in [0, 1, 2] (2nd order)
# time t in this case is Utime[2]
# the independent term of the matrix, due the pressure field
v = self.Independent()
result = np.empty(self.Nx*self.Nz)
self.mUtLU.solve(v, result)
# reshape the vector to become a matrix again
self.Ufuture = np.reshape(result, (self.Nz, self.Nx))
# make the update in the time stack
# before [t-2, t-1, t]
# after [t-1, t, t+1]
# so t-2 receive t-1 and etc.
# make the update in the time stack
self.Uprevious[:][:] = self.Ucurrent[:][:]
self.Ucurrent[:][:] = self.Ufuture[:][:]
return self.Ufuture
l[0,0] = 2.0 l[0,1] = 3.0 l[1,4] = 6.0 l[1,0] = 3.0 l[1,2] = 4.0 l[2,1] = -1.0 l[2,2] = -3.0 l[2,3] = 2.0 l[3,2] = 1.0 l[4,1] = 4.0 l[4,2] = 2.0 l[4,4] = 1.0 b = np.array([8.0, 45.0, -3.0, 3.0, 19.0], "d") x = np.zeros(5, "d") umf = umfpack.factorize(l) umf.solve(b, x, 'UMFPACK_A') print umf.getlists() print x print "------------------------------" n = 50 L = poisson2d_vec_sym_blk(n) b = np.ones(n * n, 'd') x = np.empty(n * n, 'd') umf = umfpack.factorize(L) umf.solve(b, x, 'UMFPACK_A') r = np.empty(n * n, 'd') L.matvec(x, r)
from pysparse.sparse import spmatrix from pysparse.direct import umfpack import numpy n = 100 A = poisson2d_sym_blk(n) b = numpy.ones(n*n) x = numpy.empty(n*n) LU = umfpack.factorize(A, strategy="UMFPACK_STRATEGY_SYMMETRIC") LU.solve(b, x)
l[0, 0] = 2.0 l[0, 1] = 3.0 l[1, 4] = 6.0 l[1, 0] = 3.0 l[1, 2] = 4.0 l[2, 1] = -1.0 l[2, 2] = -3.0 l[2, 3] = 2.0 l[3, 2] = 1.0 l[4, 1] = 4.0 l[4, 2] = 2.0 l[4, 4] = 1.0 b = np.array([8.0, 45.0, -3.0, 3.0, 19.0], "d") x = np.zeros(5, "d") umf = umfpack.factorize(l) umf.solve(b, x, 'UMFPACK_A') print umf.getlists() print x print "------------------------------" n = 50 L = poisson2d_vec_sym_blk(n) b = np.ones(n * n, 'd') x = np.empty(n * n, 'd') umf = umfpack.factorize(L) umf.solve(b, x, 'UMFPACK_A') r = np.empty(n * n, 'd') L.matvec(x, r)
from pysparse.sparse import spmatrix from pysparse.direct import umfpack import numpy n = 100 A = poisson2d_sym_blk(n) b = numpy.ones(n * n) x = numpy.empty(n * n) LU = umfpack.factorize(A, strategy="UMFPACK_STRATEGY_SYMMETRIC") LU.solve(b, x)
