def mfem_smoother(name, **kwargs):
prc = kwargs.pop('prc')
blockname = kwargs.pop('blockname')
row = prc.get_row_by_name(blockname)
col = prc.get_col_by_name(blockname)
mat = prc.get_operator_block(row, col)
if isinstance(mat, mfem.ComplexOperator):
conv = mat.GetConvention()
blockOffsets = mfem.intArray()
blockOffsets.SetSize(3)
blockOffsets[0] = 0
blockOffsets[1] = mat.Height() // 2
blockOffsets[2] = mat.Height() // 2
blockOffsets.PartialSum()
smoother = mfem.BlockDiagonalPreconditioner(blockOffsets)
m_r = mat._real_operator
#m_i = mat._imag_operator
pc_r = _create_smoother(name, m_r)
pc_i = mfem.ScaledOperator(
pc_r, 1 if conv == mfem.ComplexOperator.HERMITIAN else -1)
smoother.SetDiagonalBlock(0, pc_r)
smoother.SetDiagonalBlock(1, pc_i)
smoother._smoothers = (pc_r, pc_i)
else:
smoother = _create_smoother(name, mat)
return smoother
# [ S0^{-1} 0 ]
# [ 0 Shat^{-1} ] Shat = (Bhat^T Sinv Bhat)
#
# corresponding to the primal (x0) and interfacial (xhat) unknowns.
# Since the Shat operator is equivalent to an H(div) matrix reduced to
# the interfacial skeleton, we approximate its inverse with one V-cycle
# of the ADS preconditioner from the hypre library (in 2D we use AMS for
# the rotated H(curl) problem).
S0inv = mfem.HypreBoomerAMG(matS0)
S0inv.SetPrintLevel(0)
Shat = mfem.RAP(matSinv, matBhat)
if (dim == 2): Shatinv = mfem.HypreAMS(Shat, xhat_space)
else: Shatinv = mfem.HypreADS(Shat, xhat_space)
P = mfem.BlockDiagonalPreconditioner(true_offsets)
P.SetDiagonalBlock(0, S0inv)
P.SetDiagonalBlock(1, Shatinv)
# 12. Solve the normal equation system using the PCG iterative solver.
# Check the weighted norm of residual for the DPG least square problem.
# Wrap the primal variable in a GridFunction for visualization purposes.
pcg = mfem.CGSolver(MPI.COMM_WORLD)
pcg.SetOperator(A)
pcg.SetPreconditioner(P)
pcg.SetRelTol(1e-6)
pcg.SetMaxIter(200)
pcg.SetPrintLevel(1)
pcg.Mult(b, x)
LSres = mfem.HypreParVector(test_space)
#M2 = M.Transpose()
#M3 = M2.Transpose()
MinvBt = B.Transpose()
Md = mfem.HypreParVector(MPI.COMM_WORLD, M.GetGlobalNumRows(),
M.GetRowStarts())
M.GetDiag(Md)
MinvBt.InvScaleRows(Md)
S = mfem.hypre.ParMult(B, MinvBt)
invM = mfem.HypreDiagScale(M)
invS = mfem.HypreBoomerAMG(S)
invM.iterative_mode = False
invS.iterative_mode = False
darcyPr = mfem.BlockDiagonalPreconditioner(block_trueOffsets)
darcyPr.SetDiagonalBlock(0, invM)
darcyPr.SetDiagonalBlock(1, invS)
maxIter = 500
rtol = 1e-6
atol = 1e-10
import time
stime = time.clock()
solver = mfem.MINRESSolver(MPI.COMM_WORLD)
solver.SetAbsTol(atol)
solver.SetRelTol(rtol)
solver.SetMaxIter(maxIter)
solver.SetOperator(darcyOp)
def genearate_smoother(engine, level, blk_opr):
from petram.engine import ParallelEngine
assert not isinstance(
engine, ParallelEngine), "Parallel is not supported"
engine.access_idx = 0
P = None
diags = []
cols = [0]
ess_tdofs = []
A, _X, _RHS, _Ae, _B, _M, _dep_vars = engine.assembled_blocks
widths = A.get_local_col_widths()
use_complex_opr = A.complex and (A.shape[0] == blk_opr.NumRowBlocks())
for dep_var in engine.r_dep_vars:
offset = engine.r_dep_var_offset(dep_var)
tmp_cols = []
tmp_diags = []
if engine.r_isFESvar(dep_var):
ess_tdof = mfem.intArray(engine.ess_tdofs[dep_var])
ess_tdofs.append(ess_tdofs)
opr = A[offset, offset]
if use_complex_opr:
mat = blk_opr._linked_op[(offset, offset)]
conv = mat.GetConvention()
conv == 1 if mfem.ComplexOperator.HERMITIAN else -1
mat1 = mat._real_operator
mat2 = mat._imag_operator
else:
conv = 1
if A.complex:
mat1 = blk_opr.GetBlock(offset*2, offset*2)
mat2 = blk_opr.GetBlock(offset*2 + 1, offset*2 + 1)
else:
mat1 = blk_opr.GetBlock(offset, offset)
if A.complex:
dd = opr.diagonal()
diag = mfem.Vector(list(dd.real))
print("real", dd.real)
rsmoother = mfem.OperatorChebyshevSmoother(mat1,
diag,
ess_tdof,
2)
dd = opr.diagonal()*conv
diag = mfem.Vector(list(dd.real))
print("imag", dd.imag)
ismoother = mfem.OperatorChebyshevSmoother(mat1,
diag,
ess_tdof,
2)
tmp_cols.append(opr.shape[0])
tmp_cols.append(opr.shape[0])
tmp_diags.append(rsmoother)
tmp_diags.append(ismoother)
else:
dd = opr.diagonal()
diag = mfem.Vector(list(dd))
smoother = mfem.OperatorChebyshevSmoother(mat1,
diag,
ess_tdof,
2)
tmp_diags.append(smoother)
tmp_cols.append(opr.shape[0])
else:
print("Non FESvar", dep_var, offset)
tmp_cols.append(widths[offset])
tmp_diags.append(mfem.IdentityOperator(widths[offset]))
if A.complex:
tmp_cols.append(widths[offset])
oo = mfem.IdentityOperator(widths[offset])
if conv == -1:
oo2 = mfem.ScaleOperator(oo, -1)
oo2._opr = oo
tmp_diags.append(oo2)
else:
tmp_diags.append(oo)
if use_complex_opr:
tmp_cols = [0] + tmp_cols
blockOffsets = mfem.intArray(tmp_cols)
blockOffsets.PartialSum()
smoother = mfem.BlockDiagonalPreconditioner(blockOffsets)
smoother.SetDiagonalBlock(0, tmp_diags[0])
smoother.SetDiagonalBlock(1, tmp_diags[1])
smoother._smoother = tmp_diags
cols.append(tmp_cols[1]*2)
diags.append(smoother)
else:
cols.extend(tmp_cols)
diags.extend(tmp_diags)
co = mfem.intArray(cols)
co.PartialSum()
P = mfem.BlockDiagonalPreconditioner(co)
for i, d in enumerate(diags):
P.SetDiagonalBlock(i, d)
P._diags = diags
P._ess_tdofs = ess_tdofs
return P
def solve_serial(self, A, b, x=None):
def get_block(Op, i, j):
try:
return Op._linked_op[(i, j)]
except KeyError:
return None
offset = A.RowOffsets()
rows = A.NumRowBlocks()
cols = A.NumColBlocks()
if self.gui.write_mat:
for i in range(cols):
for j in range(rows):
m = get_block(A, i, j)
if m is None: continue
m.Print('matrix_' + str(i) + '_' + str(j))
for i, bb in enumerate(b):
for j in range(rows):
v = bb.GetBlock(j)
v.Print('rhs_' + str(i) + '_' + str(j))
M = mfem.BlockDiagonalPreconditioner(offset)
prcs = dict(self.gui.preconditioners)
name = self.Aname
assert not self.gui.parent.is_complex(), "can not solve complex"
if self.gui.parent.is_converted_from_complex():
name = sum([[n, n] for n in name], [])
'''
this if block does a generalized version of this...
M1 = mfem.GSSmoother(get_block(A, 0, 0))
M1.iterative_mode = False
M.SetDiagonalBlock(0, M1)
'''
for k, n in enumerate(name):
prc = prcs[n][0]
if prc == "None": continue
name = "".join([tmp for tmp in prc if not tmp.isdigit()])
A0 = get_block(A, k, k)
cls = SparseSmootherCls[name][0]
arg = SparseSmootherCls[name][1]
if name == 'MUMPS':
invA0 = cls(A0, gui=self.gui[prc], engine=self.engine)
else:
invA0 = cls(A0, arg)
invA0.iterative_mode = False
M.SetDiagonalBlock(k, invA0)
'''
We should support Shur complement type preconditioner
if offset.Size() > 2:
B = get_block(A, 1, 0)
MinvBt = get_block(A, 0, 1)
Md = mfem.Vector(get_block(A, 0, 0).Height())
get_block(A, 0, 0).GetDiag(Md)
for i in range(Md.Size()):
if Md[i] != 0.:
MinvBt.ScaleRow(i, 1/Md[i])
else:
assert False, "diagnal element of matrix is zero"
S = mfem.Mult(B, MinvBt)
S.iterative_mode = False
SS = mfem.DSmoother(S)
SS.iterative_mode = False
M.SetDiagonalBlock(1, SS)
'''
'''
int GMRES(const Operator &A, Vector &x, const Vector &b, Solver &M,
int &max_iter, int m, double &tol, double atol, int printit)
'''
maxiter = int(self.maxiter)
atol = self.abstol
rtol = self.reltol
kdim = int(self.kdim)
printit = 1
sol = []
solver = mfem.GMRESSolver()
solver.SetKDim(kdim)
#solver = mfem.MINRESSolver()
solver.SetAbsTol(atol)
solver.SetRelTol(rtol)
solver.SetMaxIter(maxiter)
solver.SetOperator(A)
solver.SetPreconditioner(M)
solver.SetPrintLevel(1)
for bb in b:
if x is None:
xx = mfem.Vector(bb.Size())
xx.Assign(0.0)
else:
xx = x
#for j in range(cols):
# print x.GetBlock(j).Size()
# print x.GetBlock(j).GetDataArray()
#assert False, "must implement this"
solver.Mult(bb, xx)
sol.append(xx.GetDataArray().copy())
sol = np.transpose(np.vstack(sol))
return sol
def solve_parallel(self, A, b, x=None):
from mpi4py import MPI
myid = MPI.COMM_WORLD.rank
nproc = MPI.COMM_WORLD.size
from petram.helper.mpi_recipes import gather_vector
def get_block(Op, i, j):
try:
return Op._linked_op[(i, j)]
except KeyError:
return None
offset = A.RowOffsets()
rows = A.NumRowBlocks()
cols = A.NumColBlocks()
if self.gui.write_mat:
for i in range(cols):
for j in range(rows):
m = get_block(A, i, j)
if m is None: continue
m.Print('matrix_' + str(i) + '_' + str(j))
for i, bb in enumerate(b):
for j in range(rows):
v = bb.GetBlock(j)
v.Print('rhs_' + str(i) + '_' + str(j) + '.' + smyid)
if x is not None:
for j in range(rows):
xx = x.GetBlock(j)
xx.Print('x_' + str(i) + '_' + str(j) + '.' + smyid)
M = mfem.BlockDiagonalPreconditioner(offset)
prcs = dict(self.gui.preconditioners)
name = self.Aname
assert not self.gui.parent.is_complex(), "can not solve complex"
if self.gui.parent.is_converted_from_complex():
name = sum([[n, n] for n in name], [])
for k, n in enumerate(name):
prc = prcs[n][1]
if prc == "None": continue
name = "".join([tmp for tmp in prc if not tmp.isdigit()])
A0 = get_block(A, k, k)
if A0 is None and not name.startswith('schur'): continue
if hasattr(mfem.HypreSmoother, prc):
invA0 = mfem.HypreSmoother(A0)
invA0.SetType(getattr(mfem.HypreSmoother, prc))
elif prc == 'ams':
depvar = self.engine.r_dep_vars[k]
dprint1("setting up AMS for ", depvar)
prec_fespace = self.engine.fespaces[depvar]
invA0 = mfem.HypreAMS(A0, prec_fespace)
invA0.SetSingularProblem()
elif name == 'MUMPS':
cls = SparseSmootherCls[name][0]
invA0 = cls(A0, gui=self.gui[prc], engine=self.engine)
elif name.startswith('schur'):
args = name.split("(")[-1].split(")")[0].split(",")
dprint1("setting up schur for ", args)
if len(args) > 1:
assert False, "not yet supported"
for arg in args:
r1 = self.engine.dep_var_offset(arg.strip())
c1 = self.engine.r_dep_var_offset(arg.strip())
B = get_block(A, k, c1)
Bt = get_block(A, r1, k).Transpose()
Bt = Bt.Transpose()
B0 = get_block(A, r1, c1)
Md = mfem.HypreParVector(MPI.COMM_WORLD,
B0.GetGlobalNumRows(),
B0.GetColStarts())
B0.GetDiag(Md)
Bt.InvScaleRows(Md)
S = mfem.ParMult(B, Bt)
invA0 = mfem.HypreBoomerAMG(S)
invA0.iterative_mode = False
else:
cls = SparseSmootherCls[name][0]
invA0 = cls(A0, gui=self.gui[prc])
invA0.iterative_mode = False
M.SetDiagonalBlock(k, invA0)
'''
We should support Shur complement type preconditioner
if offset.Size() > 2:
B = get_block(A, 1, 0)
MinvBt = get_block(A, 0, 1)
#Md = mfem.HypreParVector(MPI.COMM_WORLD,
# A0.GetGlobalNumRows(),
# A0.GetRowStarts())
Md = mfem.Vector()
A0.GetDiag(Md)
MinvBt.InvScaleRows(Md)
S = mfem.ParMult(B, MinvBt)
invS = mfem.HypreBoomerAMG(S)
invS.iterative_mode = False
M.SetDiagonalBlock(1, invS)
'''
maxiter = int(self.maxiter)
atol = self.abstol
rtol = self.reltol
kdim = int(self.kdim)
printit = 1
sol = []
solver = mfem.GMRESSolver(MPI.COMM_WORLD)
solver.SetKDim(kdim)
#solver = mfem.MINRESSolver(MPI.COMM_WORLD)
#solver.SetOperator(A)
#solver = mfem.CGSolver(MPI.COMM_WORLD)
solver.SetOperator(A)
solver.SetAbsTol(atol)
solver.SetRelTol(rtol)
solver.SetMaxIter(maxiter)
solver.SetPreconditioner(M)
solver.SetPrintLevel(1)
# solve the problem and gather solution to head node...
# may not be the best approach
for bb in b:
rows = MPI.COMM_WORLD.allgather(np.int32(bb.Size()))
rowstarts = np.hstack((0, np.cumsum(rows)))
dprint1("rowstarts/offser", rowstarts, offset.ToList())
if x is None:
xx = mfem.BlockVector(offset)
xx.Assign(0.0)
else:
xx = x
#for j in range(cols):
# dprint1(x.GetBlock(j).Size())
# dprint1(x.GetBlock(j).GetDataArray())
#assert False, "must implement this"
solver.Mult(bb, xx)
s = []
for i in range(offset.Size() - 1):
v = xx.GetBlock(i).GetDataArray()
vv = gather_vector(v)
if myid == 0:
s.append(vv)
else:
pass
if myid == 0:
sol.append(np.hstack(s))
if myid == 0:
sol = np.transpose(np.vstack(sol))
return sol
else:
return None
def __call__(self, *args, **kwargs):
offset = self.opr.RowOffsets()
D = mfem.BlockDiagonalPreconditioner(offset)
if self.func is not None:
self.func(D, self, *args, **kwargs)
return D
