def _solve_(self, L, x, b):
diag = L.takeDiagonal()
maxdiag = max(numerix.absolute(diag))
L = L * (1 / maxdiag)
b = b * (1 / maxdiag)
LU = superlu.factorize(L.matrix.to_csr())
if DEBUG:
import sys
print(L.matrix, file=sys.stderr)
error0 = numerix.sqrt(numerix.sum((L * x - b)**2))
for iteration in range(self.iterations):
errorVector = L * x - b
if (numerix.sqrt(numerix.sum(errorVector**2)) / error0) <= self.tolerance:
break
xError = numerix.zeros(len(b), 'd')
LU.solve(errorVector, xError)
x[:] = x - xError
if 'FIPY_VERBOSE_SOLVER' in os.environ:
from fipy.tools.debug import PRINT
PRINT('iterations: %d / %d' % (iteration+1, self.iterations))
PRINT('residual:', numerix.sqrt(numerix.sum(errorVector**2)))
def _solve_(self, L, x, b):
diag = L.takeDiagonal()
maxdiag = max(numerix.absolute(diag))
L = L * (1 / maxdiag)
b = b * (1 / maxdiag)
LU = splu(L.matrix.asformat("csc"), diag_pivot_thresh=1.,
relax=1,
panel_size=10,
permc_spec=3)
error0 = numerix.sqrt(numerix.sum((L * x - b)**2))
for iteration in range(min(self.iterations, 10)):
errorVector = L * x - b
if (numerix.sqrt(numerix.sum(errorVector**2)) / error0) <= self.tolerance:
break
xError = LU.solve(errorVector)
x[:] = x - xError
if 'FIPY_VERBOSE_SOLVER' in os.environ:
from fipy.tools.debug import PRINT
PRINT('iterations: %d / %d' % (iteration+1, self.iterations))
PRINT('residual:', numerix.sqrt(numerix.sum(errorVector**2)))
return x
def _solve_(self, L, x, b):
diag = L.takeDiagonal()
maxdiag = max(numerix.absolute(diag))
L = L * (1 / maxdiag)
b = b * (1 / maxdiag)
LU = splu(L.matrix.asformat("csc"),
diag_pivot_thresh=1.,
drop_tol=0.,
relax=1,
panel_size=10,
permc_spec=3)
error0 = numerix.sqrt(numerix.sum((L * x - b)**2))
for iteration in range(min(self.iterations, 10)):
errorVector = L * x - b
if (numerix.sqrt(numerix.sum(errorVector**2)) /
error0) <= self.tolerance:
break
xError = LU.solve(errorVector)
x[:] = x - xError
if 'FIPY_VERBOSE_SOLVER' in os.environ:
from fipy.tools.debug import PRINT
PRINT('iterations: %d / %d' % (iteration + 1, self.iterations))
PRINT('residual:', numerix.sqrt(numerix.sum(errorVector**2)))
return x
def _solve_(self, L, x, b):
diag = L.takeDiagonal()
maxdiag = max(numerix.absolute(diag))
L = L * (1 / maxdiag)
b = b * (1 / maxdiag)
LU = superlu.factorize(L.matrix.to_csr())
if DEBUG:
import sys
print >> sys.stderr, L.matrix
error0 = numerix.sqrt(numerix.sum((L * x - b)**2))
for iteration in range(self.iterations):
errorVector = L * x - b
if (numerix.sqrt(numerix.sum(errorVector**2)) / error0) <= self.tolerance:
break
xError = numerix.zeros(len(b),'d')
LU.solve(errorVector, xError)
x[:] = x - xError
if 'FIPY_VERBOSE_SOLVER' in os.environ:
from fipy.tools.debug import PRINT
PRINT('iterations: %d / %d' % (iteration+1, self.iterations))
PRINT('residual:', numerix.sqrt(numerix.sum(errorVector**2)))
def _solve_(self, L, x, b):
diag = L.takeDiagonal()
maxdiag = max(numerix.absolute(diag))
L = L * (1 / maxdiag)
b = b * (1 / maxdiag)
LU = superlu.factorize(L._getMatrix().to_csr())
error0 = numerix.sqrt(numerix.sum((L * x - b)**2))
for iteration in range(self.iterations):
errorVector = L * x - b
if (numerix.sqrt(numerix.sum(errorVector**2)) / error0) <= self.tolerance:
break
xError = numerix.zeros(len(b),'d')
LU.solve(errorVector, xError)
x[:] = x - xError
def _solve_(self, L, x, b):
for iteration in range(self.iterations):
# errorVector = L*x - b
errorVector = Epetra.Vector(L.RowMap())
L.Multiply(False, x, errorVector)
errorVector = errorVector - b
tol = max(numerix.absolute(_trilinosToNumpyVector(errorVector)))
if iteration == 0:
tol0 = tol
if (tol / tol0) <= self.tolerance:
break
xError = _numpyToTrilinosVector(numerix.zeros(errorVector.GlobalLength(), 'd'), L.RowMap())
Problem = Epetra.LinearProblem(L, xError, errorVector)
Solver = self.Factory.Create("Klu", Problem)
Solver.Solve()
x[:] = x - xError
