def solve(self, x, b):
if not isinstance(x, (function.Function, vector.Vector)):
raise TypeError("Provided solution is a '%s', not a Function or Vector" % type(x).__name__)
if isinstance(b, vector.Vector):
b = b.function
if not isinstance(b, function.Function):
raise TypeError("Provided RHS is a '%s', not a Function" % type(b).__name__)
if len(self.trial_space) > 1 and self.nullspace is not None:
self.nullspace._apply(self.trial_space.dof_dset.field_ises)
if len(self.test_space) > 1 and self.transpose_nullspace is not None:
self.transpose_nullspace._apply(self.test_space.dof_dset.field_ises,
transpose=True)
if len(self.trial_space) > 1 and self.near_nullspace is not None:
self.near_nullspace._apply(self.trial_space.dof_dset.field_ises, near=True)
if self.A.has_bcs:
b = self._lifted(b)
if self.ksp.getInitialGuessNonzero():
acc = x.dat.vec
else:
acc = x.dat.vec_wo
with self.inserted_options(), b.dat.vec_ro as rhs, acc as solution, dmhooks.add_hooks(self.ksp.dm, self):
self.ksp.solve(rhs, solution)
r = self.ksp.getConvergedReason()
if r < 0:
raise ConvergenceError("LinearSolver failed to converge after %d iterations with reason: %s", self.ksp.getIterationNumber(), solving_utils.KSPReasons[r])
def solve(self, x, b):
if not isinstance(x, (function.Function, vector.Vector)):
raise TypeError("Provided solution is a '%s', not a Function or Vector" % type(x).__name__)
if not isinstance(b, function.Function):
raise TypeError("Provided RHS is a '%s', not a Function" % type(b).__name__)
if len(self._W) > 1 and self.nullspace is not None:
self.nullspace._apply(self._W.dof_dset.field_ises)
if len(self._W) > 1 and self.transpose_nullspace is not None:
self.transpose_nullspace._apply(self._W.dof_dset.field_ises, transpose=True)
if len(self._W) > 1 and self.near_nullspace is not None:
self.near_nullspace._apply(self._W.dof_dset.field_ises, near=True)
if self.A.has_bcs:
b_bc = self._b
# rhs = b - action(A, zero_function_with_bcs_applied)
b_bc.assign(b - self._Abcs)
# Now we need to apply the boundary conditions to the "RHS"
for bc in self.A.bcs:
bc.apply(b_bc)
# don't want to write into b itself, because that would confuse user
b = b_bc
with self.inserted_options():
with b.dat.vec_ro as rhs:
with x.dat.vec as solution:
self.ksp.solve(rhs, solution)
r = self.ksp.getConvergedReason()
if r < 0:
raise ConvergenceError("LinearSolver failed to converge after %d iterations with reason: %s", self.ksp.getIterationNumber(), solving_utils.KSPReasons[r])
def check_ts_convergence(ts):
r = ts.getConvergedReason()
# TODO: submit PR to petsc4py to add the following reasons
# TSFORWARD_DIVERGED_LINEAR_SOLVE = -3,
# TSADJOINT_DIVERGED_LINEAR_SOLVE = -4
if r == -3:
raise ConvergenceError(
f"TS solve failed to converge. Reason: TSFORWARD_DIVERGED_LINEAR_SOLVE"
)
if r == -4:
raise ConvergenceError(
f"TS solve failed to converge. Reason: TSADJOINT_DIVERGED_LINEAR_SOLVE"
)
reason = TSReasons[r]
if r < 0:
raise ConvergenceError(
f"TS solve failed to converge after {ts.getStepNumber()} iterations. Reason: {reason}"
)
def check_snes_convergence(snes):
r = snes.getConvergedReason()
try:
reason = SNESReasons[r]
inner = False
except KeyError:
r = snes.getKSP().getConvergedReason()
try:
inner = True
reason = KSPReasons[r]
except KeyError:
reason = "unknown reason (petsc4py enum incomplete?), try with -snes_converged_reason and -ksp_converged_reason"
if r < 0:
if inner:
msg = "Inner linear solve failed to converge after %d iterations with reason: %s" % \
(snes.getKSP().getIterationNumber(), reason)
else:
msg = reason
raise ConvergenceError(r"""Nonlinear solve failed to converge after %d nonlinear iterations.
Reason:
%s""" % (snes.getIterationNumber(), msg))
