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[Getfem-commits] [getfem-commits] branch devel-logari81-internal-variabl
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From: |
Konstantinos Poulios |
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Subject: |
[Getfem-commits] [getfem-commits] branch devel-logari81-internal-variables updated: Fixes and simplifications in internal variable condensation |
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Date: |
Sat, 01 Feb 2020 04:55:19 -0500 |
This is an automated email from the git hooks/post-receive script.
logari81 pushed a commit to branch devel-logari81-internal-variables
in repository getfem.
The following commit(s) were added to
refs/heads/devel-logari81-internal-variables by this push:
new 10f5553 Fixes and simplifications in internal variable condensation
10f5553 is described below
commit 10f555331ca0fccee34131427d55da398c6148c5
Author: Konstantinos Poulios <address@hidden>
AuthorDate: Sat Feb 1 10:55:10 2020 +0100
Fixes and simplifications in internal variable condensation
- First working version
---
src/getfem/getfem_generic_assembly.h | 3 +-
src/getfem_generic_assembly_compile_and_exec.cc | 186 ++++++++----------------
src/getfem_generic_assembly_workspace.cc | 28 ++--
3 files changed, 79 insertions(+), 138 deletions(-)
diff --git a/src/getfem/getfem_generic_assembly.h
b/src/getfem/getfem_generic_assembly.h
index 367d227..f4b973f 100644
--- a/src/getfem/getfem_generic_assembly.h
+++ b/src/getfem/getfem_generic_assembly.h
@@ -372,7 +372,7 @@ namespace getfem {
model_real_sparse_matrix col_unreduced_K,
row_unreduced_K,
row_col_unreduced_K;
- base_vector unreduced_V;
+ base_vector unreduced_V, cached_V;
base_tensor assemb_t;
bool include_empty_int_pts = false;
@@ -391,6 +391,7 @@ namespace getfem {
model_real_sparse_matrix &assembled_matrix() { return *K; }
const base_vector &assembled_vector() const { return *V; }
base_vector &assembled_vector() { return *V; }
+ const base_vector &cached_vector() const { return cached_V; }
const base_tensor &assembled_tensor() const { return assemb_t; }
base_tensor &assembled_tensor() { return assemb_t; }
const scalar_type &assembled_potential() const {
diff --git a/src/getfem_generic_assembly_compile_and_exec.cc
b/src/getfem_generic_assembly_compile_and_exec.cc
index 1657e86..333e35a 100644
--- a/src/getfem_generic_assembly_compile_and_exec.cc
+++ b/src/getfem_generic_assembly_compile_and_exec.cc
@@ -5028,10 +5028,10 @@ namespace getfem {
gmm::dense_matrix<base_tensor *> KQJprime;
std::vector<base_tensor *> RQprime;
gmm::dense_matrix<base_tensor const *> KQQloc, KQJloc;
- std::vector<base_tensor const *> RQloc;
base_tensor invKqqqq, Kqqjj;
base_vector Rqq;
std::vector<std::array<size_type,3>> partQ, partJ;
+ const scalar_type &coeff; // &alpha1, &alpha2 ?
virtual int exec() { // implementation can be optimized
GA_DEBUG_INFO("Instruction: variable cluster subdiagonal condensation");
// copy from KQQ to invKqqqq
@@ -5081,7 +5081,7 @@ namespace getfem {
gmm::clear(Kqqjj.as_vector());
gmm::clear(Rqq);
- // multiply invKqqqq with all submatrices in KQJloc and RQloc and store
+ // multiply invKqqqq with all submatrices in KQJloc and RQprime and store
// the results in Kqqjj and Rqq
for (const auto &jjj : partJ) {
size_type j = jjj[0], jjstart = jjj[1], jjend = jjj[2];
@@ -5103,13 +5103,13 @@ namespace getfem {
} // in partJ
for (const auto &qqq2 : partQ) {
size_type q2 = qqq2[0], qq2start = qqq2[1], qq2end = qqq2[2];
- if (RQloc[q2]) {
- auto itr = RQloc[q2]->cbegin();
+ if (RQprime[q2]) {
+ auto itr = RQprime[q2]->cbegin();
for (size_type qq2=qq2start; qq2 < qq2end; ++qq2, ++itr) {
for (size_type qq1=0; qq1 < invKqqqq.size(0); ++qq1)
Rqq[qq1] += invKqqqq(qq1,qq2)*(*itr);
} // for qq2
- GMM_ASSERT1(itr == RQloc[q2]->cend(), "Internal error");
+ GMM_ASSERT1(itr == RQprime[q2]->cend(), "Internal error");
}
} // in partQ
@@ -5120,7 +5120,7 @@ namespace getfem {
{ // writing into RQprime
auto itw = RQprime[q1]->begin();
for (size_type qq1=qq1start; qq1 < qq1end; ++qq1)
- *itw++ = Rqq[qq1];
+ *itw++ = Rqq[qq1]/coeff;
}
for (const auto &jjj2 : partJ) {
size_type j2 = jjj2[0], jj2start = jjj2[1], jj2end = jjj2[2];
@@ -5134,20 +5134,18 @@ namespace getfem {
}
ga_instruction_condensation_sub(gmm::dense_matrix<base_tensor *> &KQJpr,
- std::vector<base_tensor *> &RQpr,
+ std::vector<base_tensor *> &RQpr, //
input/output
const gmm::dense_matrix<base_tensor *>
&KQQ,
const gmm::dense_matrix<base_tensor *>
&KQJ,
- const std::vector<base_tensor *> &RQ,
- const std::set<size_type> &Qset)
- : KQJprime(KQJpr), RQprime(RQpr)
+ const std::set<size_type> &Qset,
+ const scalar_type &coeff_)
+ : KQJprime(KQJpr), RQprime(RQpr), coeff(coeff_)
{
// * to const *
KQQloc.resize(KQQ.nrows(), KQQ.ncols());
KQJloc.resize(KQJ.nrows(), KQJ.ncols());
- RQloc.resize(RQ.size());
for (size_type i=0; i < KQQ.as_vector().size(); ++i) KQQloc[i] = KQQ[i];
for (size_type i=0; i < KQJ.as_vector().size(); ++i) KQJloc[i] = KQJ[i];
- for (size_type i=0; i < RQ.size(); ++i) RQloc[i] = RQ[i];
for (size_type j=0; j < KQJ.ncols(); ++j)
for (const size_type &q : Qset)
@@ -5219,7 +5217,7 @@ namespace getfem {
struct ga_instruction_condensation_super_R : public ga_instruction {
base_tensor &Ri;
- std::vector<base_tensor *> KiQ, RQ; // indexed wrt q in Q
+ std::vector<base_tensor *> KiQ, RQpr; // indexed wrt q in Q
size_type Qsize;
virtual int exec() {
@@ -5229,7 +5227,7 @@ namespace getfem {
Ri.adjust_sizes(m);
gmm::clear(Ri.as_vector());
for (size_type k=0; k < Qsize; ++k) {
- const base_tensor &K1 = *KiQ[k], &R2 = *RQ[k];
+ const base_tensor &K1 = *KiQ[k], &R2 = *RQpr[k];
size_type qqsize = K1.size(1);
GMM_ASSERT1(K1.size(0) == m && R2.size(0) == qqsize, "Internal error");
base_tensor::iterator it = Ri.begin();
@@ -5242,11 +5240,11 @@ namespace getfem {
}
ga_instruction_condensation_super_R(base_tensor &Ri_,
const std::vector<base_tensor *> KiQ_,
- const std::vector<base_tensor *> RQ_)
- : Ri(Ri_), KiQ(KiQ_), RQ(RQ_)
+ const std::vector<base_tensor *> RQpr_)
+ : Ri(Ri_), KiQ(KiQ_), RQpr(RQpr_)
{
Qsize = KiQ.size();
- GMM_ASSERT1(KiQ.size() == RQ.size(), "Internal error");
+ GMM_ASSERT1(KiQ.size() == RQpr.size(), "Internal error");
}
};
@@ -7348,12 +7346,8 @@ namespace getfem {
KQJ, KQJpr, // subdiagonal
KIQ, // superdiagonal
KIJ; // outcome
- gmm::dense_matrix<size_type> KQQ_sparsity, // diagonal
- KQJ_sparsity, // subdiagonal
- KIQ_sparsity; // superdiagonal
- std::vector<base_tensor *> RQ, // res. vector of condensed variables
- RI, // res. vector of coupled primary
variables
- RQpr; // partial solution for condensed
variables
+ std::vector<base_tensor *> RI, // res. vector of coupled primary
variables
+ RQpr; // partial solution for condensed
variables (initially stores residuals)
};
void ga_compile(ga_workspace &workspace,
@@ -7448,17 +7442,12 @@ namespace getfem {
// Qclusters: definition of clusters of intercoupled variables of Qvars
// cluster_of_Qvar: dictionary for which cluster each variable belongs
to
CC.KQQ.resize(Qsize, Qsize);
- CC.KQQ_sparsity.resize(Qsize, Qsize);
- CC.RQ.resize(Qsize);
CC.RQpr.resize(Qsize);
for (size_type q=0; q < Qsize; ++q) {
bgeot::multi_index mi(1);
mi[0] = workspace.associated_im_data(CC.Qvars[q]) ->nb_tensor_elem();
gis.condensation_tensors.push_back // memory allocation
(std::make_shared<base_tensor>(mi));
- CC.RQ[q] = gis.condensation_tensors.back().get();
- gis.condensation_tensors.push_back // memory allocation
- (std::make_shared<base_tensor>(mi));
CC.RQpr[q] = gis.condensation_tensors.back().get();
}
}
@@ -7684,37 +7673,19 @@ namespace getfem {
"Internal error");
size_type q1 = CC.Qvars[root->name_test1],
q2 = CC.Qvars[root->name_test2];
- auto &Kqq = CC.KQQ(q1,q2);
- auto &Kqq_sparsity = CC.KQQ_sparsity(q1,q2);
- if (Kqq_sparsity == 0) {
- // Just point to the current term result root->tensor()
- GMM_ASSERT1(!Kqq, "Internal error");
- Kqq_sparsity = 1;
- Kqq = &(root->tensor());
- } else if (Kqq_sparsity == 1) {
- // Kqq already points to the result tensor of another
- // term. To avoid altering that tensor a new matrix is
- // allocated to gather contributions from multiple terms
- GMM_ASSERT1(Kqq, "Internal error");
+ if (!CC.KQQ(q1,q2)) {
// allocate a new matrix
gis.condensation_tensors.push_back
(std::make_shared<base_tensor>(s1,s2));
- // addition instruction to the newly allocated matrix
- pgai = std::make_shared<ga_instruction_add>
- (*gis.condensation_tensors.back(),
- *Kqq, root->tensor());
- rmi.instructions.push_back(std::move(pgai));
- Kqq = gis.condensation_tensors.back().get();
- Kqq_sparsity = 2;
- } else if (Kqq_sparsity > 1) {
- // an extra matrix for this entry has already been
- // allocated, so just add the current tensor to it
- GMM_ASSERT1(Kqq, "Internal error");
+ CC.KQQ(q1,q2) = gis.condensation_tensors.back().get();
+ pgai = std::make_shared<ga_instruction_copy_vect>
+ (CC.KQQ(q1,q2)->as_vector(), root->tensor().as_vector());
+ } else {
+ // addition instruction to the previously allocated matrix
pgai = std::make_shared<ga_instruction_add_to>
- (*Kqq, root->tensor());
- rmi.instructions.push_back(std::move(pgai));
- Kqq_sparsity += 1;
+ (*CC.KQQ(q1,q2), root->tensor());
}
+ rmi.instructions.push_back(std::move(pgai));
} else if (condensation &&
workspace.is_internal_variable(root->name_test1)) {
// subdiagonal condensation matrix KQJ
@@ -7730,45 +7701,26 @@ namespace getfem {
size_type q1 = CC.Qvars[root->name_test1],
j2 = CC.Jvars[root->name_test2];
CC.Jclusters[CC.cluster_of_Qvar[q1]].insert(j2);
- if (q1 >= CC.KQJ.nrows() || j2 >= CC.KQJ.ncols()) {
+ if (q1 >= CC.KQJ.nrows() || j2 >= CC.KQJ.ncols())
CC.KQJ.resize(std::max(CC.KQJ.nrows(), q1+1),
std::max(CC.KQJ.ncols(), j2+1));
- CC.KQJ_sparsity.resize(CC.KQJ.nrows(), CC.KQJ.ncols());
- }
- auto &Kqj = CC.KQJ(q1,j2);
- auto &Kqj_sparsity = CC.KQJ_sparsity(q1,j2);
- if (Kqj_sparsity == 0) {
- // Just point to the current term result root->tensor()
- GMM_ASSERT1(!Kqj, "Internal error");
- Kqj_sparsity = 1;
- Kqj = &(root->tensor());
- } else if (Kqj_sparsity == 1) {
- // Kqj already points to the result tensor of another
- // term. To avoid altering that tensor a new matrix is
- // allocated to gather contributions from multiple terms
- GMM_ASSERT1(Kqj, "Internal error");
+ if (!CC.KQJ(q1,j2)) {
// allocate a new matrix. Here we do not know the size as
// it may change dynamically, but for now, just use the
// size of root->tensor()
gis.condensation_tensors.push_back
(std::make_shared<base_tensor>(root->tensor()));
GMM_ASSERT1(root->tensor().size(0) == s1, "Internal
error");
- // addition instruction to the newly allocated matrix
- pgai = std::make_shared<ga_instruction_add>
- (*gis.condensation_tensors.back(),
- *Kqj, root->tensor());
- rmi.instructions.push_back(std::move(pgai));
- Kqj = gis.condensation_tensors.back().get();
- Kqj_sparsity = 2;
- } else if (Kqj_sparsity > 1) {
+ CC.KQJ(q1,j2) = gis.condensation_tensors.back().get();
+ pgai = std::make_shared<ga_instruction_copy_vect>
+ (CC.KQJ(q1,j2)->as_vector(), root->tensor().as_vector());
+ } else {
// an extra matrix for this entry has already been
// allocated, so just add the current tensor to it
- GMM_ASSERT1(Kqj, "Internal error");
pgai = std::make_shared<ga_instruction_add_to>
- (*Kqj, root->tensor());
- rmi.instructions.push_back(std::move(pgai));
- Kqj_sparsity += 1;
+ (*CC.KQJ(q1,j2), root->tensor());
}
+ rmi.instructions.push_back(std::move(pgai));
} else if (condensation &&
workspace.is_internal_variable(root->name_test2)) {
// superdiagonal condensation matrix KIQ
@@ -7783,23 +7735,10 @@ namespace getfem {
"Internal error");
size_type i1 = CC.Ivars[root->name_test1],
q2 = CC.Qvars[root->name_test2];
- if (i1 >= CC.KIQ.nrows() || q2 >= CC.KIQ.ncols()) {
+ if (i1 >= CC.KIQ.nrows() || q2 >= CC.KIQ.ncols())
CC.KIQ.resize(std::max(CC.KIQ.nrows(), i1+1),
std::max(CC.KIQ.ncols(), q2+1));
- CC.KIQ_sparsity.resize(CC.KIQ.nrows(), CC.KIQ.ncols());
- }
- auto &Kiq = CC.KIQ(i1,q2);
- auto &Kiq_sparsity = CC.KIQ_sparsity(i1,q2);
- if (Kiq_sparsity == 0) {
- // Just point to the current term result root->tensor()
- GMM_ASSERT1(!Kiq, "Internal error");
- Kiq_sparsity = 1;
- Kiq = &(root->tensor());
- } else if (Kiq_sparsity == 1) {
- // Kiq already points to the result tensor of another
- // term. To avoid altering that tensor a new matrix is
- // allocated to gather contributions from multiple terms
- GMM_ASSERT1(Kiq, "Internal error");
+ if (!CC.KIQ(i1,q2)) {
// allocate a new matrix. Here we do not know the size as
// it may change dynamically, but for now, just use the
// size of root->tensor()
@@ -7807,22 +7746,16 @@ namespace getfem {
(std::make_shared<base_tensor>(root->tensor()));
GMM_ASSERT1(root->tensor().size(1) == s2,
"Internal error");
- // addition instruction to the newly allocated matrix
- pgai = std::make_shared<ga_instruction_add>
- (*gis.condensation_tensors.back(),
- *Kiq, root->tensor());
- rmi.instructions.push_back(std::move(pgai));
- Kiq = gis.condensation_tensors.back().get();
- Kiq_sparsity = 2;
- } else if (Kiq_sparsity > 1) {
+ CC.KIQ(i1,q2) = gis.condensation_tensors.back().get();
+ pgai = std::make_shared<ga_instruction_copy_vect>
+ (CC.KIQ(i1,q2)->as_vector(), root->tensor().as_vector());
+ } else {
// an extra matrix for this entry has already been
// allocated, so just add the current tensor to it
- GMM_ASSERT1(Kiq, "Internal error");
pgai = std::make_shared<ga_instruction_add_to>
- (*Kiq, root->tensor());
- rmi.instructions.push_back(std::move(pgai));
- Kiq_sparsity += 1;
+ (*CC.KIQ(i1,q2), root->tensor());
}
+ rmi.instructions.push_back(std::move(pgai));
} else if (!workspace.is_internal_variable(root->name_test1) &&
!workspace.is_internal_variable(root->name_test2)) {
@@ -7957,7 +7890,7 @@ namespace getfem {
// Add one diagonal/subdiagonal condensation instruction per cluster
for (size_type k=0; k < CC.Qclusters.size(); ++k) {
// extract condensed variables residuals from
- // workspace.assembled_vector() into RQ
+ // workspace.assembled_vector() into RQpr
for (size_type q1 : CC.Qclusters[k]) {
std::string name_test1 = CC.Qvars[q1];
const im_data *imd1 = workspace.associated_im_data(name_test1);
@@ -7965,7 +7898,7 @@ namespace getfem {
&I1 = workspace.interval_of_variable(name_test1);
pgai =
std::make_shared<ga_instruction_extract_residual_on_imd_dofs>
- (*(CC.RQ[q1]), workspace.assembled_vector(), // --> CC.RQ[q1]
+ (*(CC.RQpr[q1]), workspace.cached_vector(), // cached_V -->
CC.RQpr[q1]
gis.ctx, I1, *imd1, gis.ipt);
rmi.instructions.push_back(std::move(pgai));
}
@@ -7974,7 +7907,7 @@ namespace getfem {
// necessary size update to match the sizes of KQJ, upon size
change
// of primary variables J
pgai = std::make_shared<ga_instruction_condensation_sub>
- (CC.KQJpr, CC.RQpr, CC.KQQ, CC.KQJ, CC.RQ, CC.Qclusters[k]);
+ (CC.KQJpr, CC.RQpr, CC.KQQ, CC.KQJ, CC.Qclusters[k], gis.coeff);
// factor_of_variable()?
rmi.instructions.push_back(std::move(pgai));
// assemble/store KQJpr/RQpr matrices/vectors into the
@@ -7982,8 +7915,8 @@ namespace getfem {
for (size_type q1 : CC.Qclusters[k]) {
std::string name_test1 = CC.Qvars[q1];
const im_data *imd1 = workspace.associated_im_data(name_test1);
- const scalar_type
- &alpha1 = workspace.factor_of_variable(name_test1);
+// const scalar_type
+// &alpha1 = workspace.factor_of_variable(name_test1); // TODO
const gmm::sub_interval
&I1 = workspace.interval_of_variable(name_test1);
GMM_ASSERT1(imd1, "Internal error");
@@ -7995,20 +7928,17 @@ namespace getfem {
// GMM_ASSERT1(intn2.empty(), "Coupling of internal variables "
// "with interpolated variables not "
// "implemented yet");
- const scalar_type
- &alpha2 = workspace.factor_of_variable(name_test2);
+// const scalar_type
+// &alpha2 = workspace.factor_of_variable(name_test2); // TODO
const gmm::sub_interval
- &I2 = workspace.interval_of_variable(name_test2);
+ &I2 = mf2 && mf2->is_reduced()
+ ? workspace.temporary_interval_of_variable(name_test2)
+ : workspace.interval_of_variable(name_test2);
const base_tensor &Kq1j2pr = *(CC.KQJpr(q1,j2)); // <- input
model_real_sparse_matrix
- &KQJpr = workspace.internal_coupling_matrix(); // <- output
- GMM_ASSERT1(
- gmm::mat_nrows(KQJpr) == workspace.nb_primary_dof()
- +workspace.nb_internal_dof() &&
- gmm::mat_ncols(KQJpr) == workspace.nb_primary_dof(),
- "The internal coupling matrix needs to be allocated with "
- "nb_primary_dof()+nb_internal_dof() number of rows, even if "
- "only the last nb_internal_dof() rows are filled in.");
+ &KQJpr = mf2 && mf2->is_reduced()
+ ? workspace.col_unreduced_matrix()
+ : workspace.internal_coupling_matrix(); // <- output
if (mf2) {
pgai =
std::make_shared<ga_instruction_matrix_assembly_imd_mf>
@@ -8027,7 +7957,7 @@ namespace getfem {
const bool initialize = true;
pgai = std::make_shared<ga_instruction_vector_assembly_imd>
(*(CC.RQpr[q1]), workspace.assembled_vector(), // <-
overwriting internal variables residual with internal solution
- gis.ctx, I1, *imd1, gis.coeff, gis.ipt, initialize);
+ gis.ctx, I1, *imd1, gis.ONE, gis.ipt, initialize); // without
gis.coeff
rmi.instructions.push_back(std::move(pgai));
} // for q1
}
@@ -8120,17 +8050,17 @@ namespace getfem {
} // for j2
// RHS condensation instructions
- std::vector<base_tensor *> Ki1Q, RQ;
+ std::vector<base_tensor *> Ki1Q, RQpr;
for (size_type q=0; q < CC.Qvars.size(); ++q)
if (CC.KIQ(i1,q)) {
Ki1Q.push_back(CC.KIQ(i1,q));
- RQ.push_back(CC.RQ[q]);
+ RQpr.push_back(CC.RQpr[q]);
}
gis.condensation_tensors.push_back
(std::make_shared<base_tensor>());
base_tensor &Ri = *gis.condensation_tensors.back();
pgai = std::make_shared<ga_instruction_condensation_super_R>
- (Ri, Ki1Q, RQ);
+ (Ri, Ki1Q, RQpr);
rmi.instructions.push_back(std::move(pgai));
base_vector &R = mf1->is_reduced() ? workspace.unreduced_vector()
diff --git a/src/getfem_generic_assembly_workspace.cc
b/src/getfem_generic_assembly_workspace.cc
index 221088e..8efa030 100644
--- a/src/getfem_generic_assembly_workspace.cc
+++ b/src/getfem_generic_assembly_workspace.cc
@@ -789,22 +789,30 @@ namespace getfem {
// gmm::mat_ncols(*K) == nb_prim_dof, "Wrong sizes");
if (KQJpr.use_count()) {
gmm::clear(*KQJpr);
- gmm::resize(*KQJpr, nb_prim_dof+nb_intern_dof, nb_prim_dof); //
redundant if condensation == false
+ if (condensation)
+ gmm::resize(*KQJpr, nb_tot_dof, nb_prim_dof);
} else if (condensation)
- GMM_ASSERT1(gmm::mat_nrows(*KQJpr) == nb_prim_dof+nb_intern_dof &&
+ GMM_ASSERT1(gmm::mat_nrows(*KQJpr) == nb_tot_dof &&
gmm::mat_ncols(*KQJpr) == nb_prim_dof, "Wrong sizes");
gmm::clear(col_unreduced_K);
gmm::clear(row_unreduced_K);
gmm::clear(row_col_unreduced_K);
gmm::resize(col_unreduced_K, nb_tot_dof, nb_tmp_dof);
- gmm::resize(row_unreduced_K, nb_tmp_dof, nb_tot_dof);
+ gmm::resize(row_unreduced_K, nb_tmp_dof, nb_prim_dof);
gmm::resize(row_col_unreduced_K, nb_tmp_dof, nb_tmp_dof);
if (condensation) {
gmm::clear(unreduced_V);
gmm::resize(unreduced_V, nb_tmp_dof);
}
- } else if (order == 1) {
- if (V.use_count()) {
+ }
+
+ if (order == 1 || (order == 2 && condensation)) {
+ if (order == 2 && condensation) {
+ GMM_ASSERT1(V->size() == nb_tot_dof, "Wrong size");
+ gmm::resize(cached_V, nb_tot_dof);
+ gmm::copy(*V, cached_V); // current residual is used in condensation
+ gmm::fill(*V, scalar_type(0));
+ } else if (V.use_count()) {
gmm::clear(*V);
gmm::resize(*V, nb_tot_dof);
} else
@@ -876,10 +884,12 @@ namespace getfem {
gmm::sub_vector(*V, I1));
vars_vec_done.insert(vname1);
}
- model_real_sparse_matrix M(I1.size(), I2.size());
- gmm::mult(gmm::transposed(mf1->extension_matrix()),
- gmm::sub_matrix(row_unreduced_K, uI1, I2), M);
- gmm::add(M, gmm::sub_matrix(*K, I1, I2));
+ if (I2.first() < nb_prim_dof) { //
!is_internal_variable(vname2)
+ model_real_sparse_matrix M(I1.size(), I2.size());
+ gmm::mult(gmm::transposed(mf1->extension_matrix()),
+ gmm::sub_matrix(row_unreduced_K, uI1, I2), M);
+ gmm::add(M, gmm::sub_matrix(*K, I1, I2));
+ }
} else {
model_real_row_sparse_matrix M(I1.size(), I2.size());
gmm::mult(gmm::sub_matrix(col_unreduced_K, I1, uI2),
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- [Getfem-commits] [getfem-commits] branch devel-logari81-internal-variables updated: Fixes and simplifications in internal variable condensation,
Konstantinos Poulios <=