def make_inv_mat(self, idx, inv):
ro = np.hstack([0, np.cumsum(np.array(self.lsize)[idx])])
row = mfem.intArray(list(ro))
col = mfem.intArray(list(ro))
mat = mfem.BlockOperator(row, col)
for ii, i in enumerate(idx):
mat.SetBlock(ii, ii, inv[i])
return mat
def get_global_blkmat_interleave(self):
'''
This routine ordered unkonws in the following order
Re FFE1, Im FES1, ReFES2, Im FES2, ...
If self.complex is False, it assembles a nomal block
matrix FES1, FES2...
'''
roffsets, coffsets = self.get_local_partitioning(convert_real=True,
interleave=True)
dprint1("offsets", roffsets, coffsets)
ro = mfem.intArray(list(roffsets))
co = mfem.intArray(list(coffsets))
glcsr = mfem.BlockOperator(ro, co)
ii = 0
for i in range(self.shape[0]):
jj = 0
for j in range(self.shape[1]):
if self[i, j] is not None:
if use_parallel:
if isinstance(self[i, j], chypre.CHypreMat):
gcsr = self[i, j]
cp = self[i, j].GetColPartArray()
rp = self[i, j].GetRowPartArray()
s = self[i, j].shape
#if (cp == rp).all() and s[0] == s[1]:
if gcsr[0] is not None:
csr = ToScipyCoo(gcsr[0]).tocsr()
gcsr[0] = ToHypreParCSR(csr, col_starts=cp)
if gcsr[1] is not None:
csr = ToScipyCoo(gcsr[1]).tocsr()
gcsr[1] = ToHypreParCSR(csr, col_starts=cp)
gcsrm = ToHypreParCSR(-csr, col_starts=cp)
dprint2(i, j, s, rp, cp)
else:
assert False, "unsupported block element " + str(
type(self[i, j]))
else:
if isinstance(self[i, j], ScipyCoo):
gcsr = self[i, j].get_mfem_sparsemat()
if gcsr[1] is not None:
gcsrm = mfem.SparseMatrix(gcsr[1])
gcsrm *= -1.
else:
assert False, "unsupported block element " + type(
self[i, j])
glcsr.SetBlock(ii, jj, gcsr[0])
if self.complex:
glcsr.SetBlock(ii + 1, jj + 1, gcsr[0])
if gcsr[1] is not None:
glcsr.SetBlock(ii + 1, jj, gcsr[1])
glcsr.SetBlock(ii, jj + 1, gcsrm)
jj = jj + 2 if self.complex else jj + 1
ii = ii + 2 if self.complex else ii + 1
return glcsr
def make_sub_matrix(self, src_mat, roffset, coffset, row_idx, col_idx):
ro = mfem.intArray(list(roffset))
co = mfem.intArray(list(coffset))
mat = mfem.BlockOperator(ro, co)
for ii, i in enumerate(row_idx):
for jj, j in enumerate(col_idx):
m = get_block(src_mat, i, j)
if m is None: continue
mat.SetBlock(ii, jj, m)
return mat
true_s1 = xhat_space.TrueVSize()
true_s_test = test_space.TrueVSize()
true_offsets = mfem.intArray([0, true_s0, true_s0 + true_s1])
true_offsets_test = mfem.intArray([0, true_s_test])
x = mfem.BlockVector(true_offsets)
b = mfem.BlockVector(true_offsets)
x.Assign(0.0)
b.Assign(0.0)
# 10. Set up the 1x2 block Least Squares DPG operator, B = [B0 Bhat],
# the normal equation operator, A = B^t Sinv B, and
# the normal equation right-hand-size, b = B^t Sinv F.
B = mfem.BlockOperator(true_offsets_test, true_offsets)
B.SetBlock(0, 0, matB0)
B.SetBlock(0, 1, matBhat)
A = mfem.RAPOperator(B, matSinv, B)
trueF = F.ParallelAssemble()
SinvF = mfem.HypreParVector(test_space)
matSinv.Mult(trueF, SinvF)
B.MultTranspose(SinvF, b)
# 11. Set up a block-diagonal preconditioner for the 2x2 normal equation
#
# [ S0^{-1} 0 ]
# [ 0 Shat^{-1} ] Shat = (Bhat^T Sinv Bhat)
mVarf = mfem.ParBilinearForm(R_space)
bVarf = mfem.ParMixedBilinearForm(R_space, W_space)
mVarf.AddDomainIntegrator(mfem.VectorFEMassIntegrator(k))
mVarf.Assemble()
mVarf.Finalize()
M = mVarf.ParallelAssemble()
bVarf.AddDomainIntegrator(mfem.VectorFEDivergenceIntegrator())
bVarf.Assemble()
bVarf.Finalize()
B = bVarf.ParallelAssemble()
B *= -1
BT = B.Transpose()
darcyOp = mfem.BlockOperator(block_trueOffsets)
darcyOp.SetBlock(0, 0, M)
darcyOp.SetBlock(0, 1, BT)
darcyOp.SetBlock(1, 0, B)
#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)
def get_global_blkmat_merged(self, symmetric=False):
'''
This routine ordered unkonws in the following order
Re FFE1, Im FES1, ReFES2, Im FES2, ...
matrix FES1, FES2...
'''
assert self.complex, "this format is complex only"
roffsets, coffsets = self.get_local_partitioning()
roffsets = np.sum(np.diff(roffsets).reshape(-1, 2), 1)
coffsets = np.sum(np.diff(coffsets).reshape(-1, 2), 1)
roffsets = np.hstack([0, np.cumsum(roffsets)])
coffsets = np.hstack([0, np.cumsum(coffsets)])
dprint1("Generating MFEM BlockMatrix: shape = " +
str((len(roffsets) - 1, len(coffsets) - 1)))
dprint1("Generating MFEM BlockMatrix: roffset/coffset = ", roffsets,
coffsets)
ro = mfem.intArray(list(roffsets))
co = mfem.intArray(list(coffsets))
glcsr = mfem.BlockOperator(ro, co)
ii = 0
for j in range(self.shape[1]):
jfirst = True
for i in range(self.shape[0]):
if self[i, j] is not None:
if use_parallel:
if isinstance(self[i, j], chypre.CHypreMat):
gcsr = self[i, j]
cp = self[i, j].GetColPartArray()
rp = self[i, j].GetRowPartArray()
rsize_local = rp[1] - rp[0]
if jfirst:
csize_local = cp[1] - cp[0]
csize = allgather(csize_local)
cstarts = np.hstack([0, np.cumsum(csize)])
jfirst = False
s = self[i, j].shape
# if (cp == rp).all() and s[0] == s[1]:
'''
if gcsr[0] is not None:
csc = ToScipyCoo(gcsr[0]).tocsc()
csc1 = [csc[:,cstarts[k]:cstarts[k+1]] for k in range(len(cstarts)-1)]
if symmetric:
csc1m = [-csc[:,cstarts[k]:cstarts[k+1]] for k in range(len(cstarts)-1)]
else:
csc1 = [None]*len(csize)
csc1m = [None]*len(csize)
if gcsr[1] is not None:
csc = ToScipyCoo(gcsr[1]).tocsc()
if not symmetric:
csc2 = [ csc[:,cstarts[k]:cstarts[k+1]] for k in range(len(cstarts)-1)]
csc2m = [-csc[:,cstarts[k]:cstarts[k+1]] for k in range(len(cstarts)-1)]
else:
csc2 = [None]*len(csize)
csc2m = [None]*len(csize)
if symmetric:
csr = scipy.sparse.bmat([sum(zip(csc1, csc2m), ()),
sum(zip(csc2m, csc1m), ())]).tocsr()
else:
csr = scipy.sparse.bmat([sum(zip(csc1, csc2m), ()),
sum(zip(csc2, csc1), ())]).tocsr()
cp2 = [(cp*2)[0], (cp*2)[1], np.sum(csize)*2]
#gcsr[1] = ToHypreParCSR(csr, col_starts =cp)
gcsr = ToHypreParCSR(csr, col_starts =cp2)
'''
if gcsr[0] is None:
csr = scipy.sparse.csr_matrix(
(rsize_local, cstarts[-1]),
dtype=np.float64)
cp3 = [cp[0], cp[1], cstarts[-1]]
gcsa = ToHypreParCSR(csr, col_starts=cp3)
else:
gcsa = gcsr[0]
if gcsr[1] is None:
csr = scipy.sparse.csr_matrix(
(rsize_local, cstarts[-1]),
dtype=np.float64)
cp3 = [cp[0], cp[1], cstarts[-1]]
gcsb = ToHypreParCSR(csr, col_starts=cp3)
else:
gcsb = gcsr[1]
else:
assert False, "unsupported block element " + \
str(type(self[i, j]))
else:
if isinstance(self[i, j], ScipyCoo):
'''
if symmetric:
tmp = scipy.sparse.bmat([[ self[i, j].real, -self[i, j].imag],
[-self[i, j].imag, -self[i, j].real]])
else:
tmp = scipy.sparse.bmat([[self[i, j].real, -self[i, j].imag],
[self[i, j].imag, self[i, j].real]])
'''
csra = self[i, j].real.tocsr()
csrb = self[i, j].imag.tocsr()
csra.eliminate_zeros()
csrb.eliminate_zeros()
gcsa = mfem.SparseMatrix(csra)
gcsb = mfem.SparseMatrix(csrb)
else:
assert False, "unsupported block element " + \
type(self[i, j])
Hermitian = False if symmetric else True
gcsr = mfem.ComplexOperator(gcsa, gcsb, False, False,
Hermitian)
gcsr._real_operator = gcsa
gcsr._imag_operator = gcsb
glcsr.SetBlock(i, j, gcsr)
return glcsr
def fill_prolongation_operator(engine, level, blk_opr):
engine.access_idx = 0
P = None
diags = []
A, _X, _RHS, _Ae, _B, _M, _dep_vars = engine.assembled_blocks
use_complex_opr = A.complex and (A.shape[0] == blk_opr.NumRowBlocks())
hights = A.get_local_row_heights()
widths = A.get_local_col_widths()
print(hights, widths)
cols = [0]
rows = [0]
for dep_var in engine.r_dep_vars:
offset = engine.r_dep_var_offset(dep_var)
tmp_cols = []
tmp_rows = []
tmp_diags = []
if use_complex_opr:
mat = blk_opr._linked_op[(offset, offset)]
conv = mat.GetConvention()
conv == (1 if mfem.ComplexOperator.HERMITIAN else -1)
else:
conv = 1
if engine.r_isFESvar(dep_var):
h = engine.fespaces.get_hierarchy(dep_var)
P = h.GetProlongationAtLevel(level)
tmp_cols.append(P.Width())
tmp_rows.append(P.Height())
tmp_diags.append(P)
if A.complex:
tmp_cols.append(P.Width())
tmp_rows.append(P.Height())
if conv == -1:
oo2 = mfem.ScaleOperator(P, -1)
oo2._opr = P
tmp_diags.append(oo2)
else:
tmp_diags.append(P)
else:
tmp_cols.append(widths[offset])
tmp_rows.append(widths[offset])
tmp_diags.append(mfem.IdentityOperator(widths[offset]))
if A.complex:
tmp_cols.append(widths[offset])
tmp_rows.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
tmp_rows = [0] + tmp_rows
offset_c = mfem.intArray(tmp_cols)
offset_r = mfem.intArray(tmp_rows)
offset_c.PartialSum()
offset_r.PartialSum()
smoother = mfem.BlockOperator(offset_r, offset_c)
smoother.SetDiagonalBlock(0, tmp_diags[0])
smoother.SetDiagonalBlock(1, tmp_diags[1])
smoother._smoother = tmp_diags
cols.append(tmp_cols[1]*2)
rows.append(tmp_rows[1]*2)
diags.append(smoother)
else:
cols.extend(tmp_cols)
rows.extend(tmp_rows)
diags.extend(tmp_diags)
ro = mfem.intArray(rows)
co = mfem.intArray(cols)
ro.PartialSum()
co.PartialSum()
P = mfem.BlockOperator(ro, co)
for i, d in enumerate(diags):
P.SetBlock(i, i, d)
P._diags = diags
return P
def fill_prolongation_operator(engine, level, XX, AA, ls_type, phys_real):
engine.access_idx = 0
P = None
diags = []
use_complex_opr = ls_type in ['blk_merged', 'blk_merged_s']
widths = [XX.BlockSize(i) for i in range(XX.NumBlocks())]
if not phys_real:
if use_complex_opr:
widths = [x // 2 for x in widths]
else:
widths = [widths[i * 2] for i in range(len(widths) // 2)]
cols = [0]
rows = [0]
for dep_var in engine.r_dep_vars:
offset = engine.r_dep_var_offset(dep_var)
tmp_cols = []
tmp_rows = []
tmp_diags = []
# if use_complex_opr:
# mat = AA._linked_op[(offset, offset)]
# conv = mat.GetConvention()
# conv = (1 if mfem.ComplexOperator.HERMITIAN else -1)
# else:
# conv = 1
if engine.r_isFESvar(dep_var):
h = engine.fespaces.get_hierarchy(dep_var)
P = h.GetProlongationAtLevel(level)
tmp_cols.append(P.Width())
tmp_rows.append(P.Height())
tmp_diags.append(P)
if not phys_real:
tmp_cols.append(P.Width())
tmp_rows.append(P.Height())
# if conv == -1:
# oo2 = mfem.ScaledOperator(P, -1)
# oo2._opr = P
# tmp_diags.append(oo2)
# else:
tmp_diags.append(P)
else:
tmp_cols.append(widths[offset])
tmp_rows.append(widths[offset])
tmp_diags.append(mfem.IdentityOperator(widths[offset]))
if not phys_real:
tmp_cols.append(widths[offset])
tmp_rows.append(widths[offset])
oo = mfem.IdentityOperator(widths[offset])
# if conv == -1:
# oo2 = mfem.ScaledOperator(oo, -1)
# oo2._opr = oo
# tmp_diags.append(oo2)
# else:
tmp_diags.append(oo)
if use_complex_opr:
tmp_cols = [0] + tmp_cols
tmp_rows = [0] + tmp_rows
offset_c = mfem.intArray(tmp_cols)
offset_r = mfem.intArray(tmp_rows)
offset_c.PartialSum()
offset_r.PartialSum()
smoother = mfem.BlockOperator(offset_r, offset_c)
smoother.SetDiagonalBlock(0, tmp_diags[0])
smoother.SetDiagonalBlock(1, tmp_diags[1])
smoother._smoother = tmp_diags
cols.append(tmp_cols[1] * 2)
rows.append(tmp_rows[1] * 2)
diags.append(smoother)
else:
cols.extend(tmp_cols)
rows.extend(tmp_rows)
diags.extend(tmp_diags)
ro = mfem.intArray(rows)
co = mfem.intArray(cols)
ro.PartialSum()
co.PartialSum()
P = mfem.BlockOperator(ro, co)
for i, d in enumerate(diags):
P.SetBlock(i, i, d)
P._diags = diags
return P
