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 __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 __init__(self, A, **kwargs):
PysparseDirectSolver.__init__(self, A, **kwargs)
self.type = numpy.float
self.nrow, self.ncol = A.getShape()
t = cputime()
self.LU = superlu.factorize(A.matrix.to_csr(), **kwargs)
self.factorizationTime = cputime() - t
self.solutionTime = 0.0
self.sol = None
self.L = self.U = None
return
