void LagMultTerm::get(MElement *ele, int npts, IntPt *GP,
fullMatrix<double> &m) const
{
int nbFF1 = BilinearTerm<SVector3, SVector3>::space1.getNumKeys(
ele); // nbVertices*nbcomp of parent
int nbFF2 = BilinearTerm<SVector3, SVector3>::space2.getNumKeys(
ele); // nbVertices of boundary
double jac[3][3];
m.resize(nbFF1, nbFF2);
m.setAll(0.);
for(int i = 0; i < npts; i++) {
double u = GP[i].pt[0];
double v = GP[i].pt[1];
double w = GP[i].pt[2];
const double weight = GP[i].weight;
const double detJ = ele->getJacobian(u, v, w, jac);
std::vector<TensorialTraits<SVector3>::ValType> Vals;
std::vector<TensorialTraits<SVector3>::ValType> ValsT;
BilinearTerm<SVector3, SVector3>::space1.f(ele, u, v, w, Vals);
BilinearTerm<SVector3, SVector3>::space2.f(ele, u, v, w, ValsT);
for(int j = 0; j < nbFF1; j++) {
for(int k = 0; k < nbFF2; k++) {
m(j, k) += _eqfac * dot(Vals[j], ValsT[k]) * weight * detJ;
}
}
}
}
bool fullMatrix<double>::invert(fullMatrix<double> &result) const
{
int M = size1(), N = size2(), lda = size1(), info;
int *ipiv = new int[std::min(M, N)];
if (result.size2() != M || result.size1() != N) {
if (result._own_data || !result._data)
result.resize(M,N,false);
else
Msg::Fatal("FullMatrix: Bad dimension, I cannot write in proxy");
}
result.setAll(*this);
F77NAME(dgetrf)(&M, &N, result._data, &lda, ipiv, &info);
if(info == 0){
int lwork = M * 4;
double *work = new double[lwork];
F77NAME(dgetri)(&M, result._data, &lda, ipiv, work, &lwork, &info);
delete [] work;
}
delete [] ipiv;
if(info == 0) return true;
else if(info > 0)
Msg::Error("U(%d,%d)=0 in matrix inversion", info, info);
else
Msg::Error("Wrong %d-th argument in matrix inversion", -info);
return false;
}
template<class T2> void BilinearTermContract<T2>::get(MElement *ele, int npts, IntPt *GP, fullMatrix<double> &m) const
{
fullVector<T2> va;
fullVector<T2> vb;
a->get(ele,npts,GP,va);
b->get(ele,npts,GP,vb);
m.resize(va.size(), vb.size());
m.setAll(0.);
for (int i=0;i<va.size();++i)
for (int j=0;j<vb.size();++j)
m(i,j)=dot(va(i),vb(j));
}
void BilinearTermBase::get(MElement *ele, int npts, IntPt *GP, fullMatrix<double> &m) const
{
std::vector<fullMatrix<double> > mv(npts);
get(ele,npts,GP,mv);
m.resize(mv[0].size1(), mv[0].size2());
m.setAll(0.);
double jac[3][3];
for (int k=0;k<npts;k++)
{
const double u = GP[k].pt[0]; const double v = GP[k].pt[1]; const double w = GP[k].pt[2];
const double weight = GP[k].weight; const double detJ = ele->getJacobian(u, v, w, jac);
const double coeff=weight*detJ;
for (int i=0;i<mv[k].size1();++i)
for (int j=0;j<mv[k].size2();++j)
m(i,j)+=mv[k](i,j)*coeff;
}
}
template<class T1> void LaplaceTerm<T1, T1>::get(MElement *ele, int npts, IntPt *GP, fullMatrix<double> &m) const
{
int nbFF = BilinearTerm<T1, T1>::space1.getNumKeys(ele);
double jac[3][3];
m.resize(nbFF, nbFF);
m.setAll(0.);
for(int i = 0; i < npts; i++){
const double u = GP[i].pt[0]; const double v = GP[i].pt[1]; const double w = GP[i].pt[2];
const double weight = GP[i].weight; const double detJ = ele->getJacobian(u, v, w, jac);
std::vector<typename TensorialTraits<T1>::GradType> Grads;
BilinearTerm<T1, T1>::space1.gradf(ele, u, v, w, Grads);
for(int j = 0; j < nbFF; j++)
{
for(int k = j; k < nbFF; k++)
{
double contrib = weight * detJ * dot(Grads[j], Grads[k]) * diffusivity;
m(j, k) += contrib;
if(j != k) m(k, j) += contrib;
}
}
}
}
void IsotropicElasticTerm::get(MElement *ele, int npts, IntPt *GP,
fullMatrix<double> &m) const
{
if(ele->getParent()) ele = ele->getParent();
if(sym) {
int nbFF = BilinearTerm<SVector3, SVector3>::space1.getNumKeys(ele);
double jac[3][3];
fullMatrix<double> B(6, nbFF);
fullMatrix<double> BTH(nbFF, 6);
fullMatrix<double> BT(nbFF, 6);
m.resize(nbFF, nbFF);
m.setAll(0.);
// std::cout << m.size1() << " " << m.size2() << std::endl;
for(int i = 0; i < npts; i++) {
const double u = GP[i].pt[0];
const double v = GP[i].pt[1];
const double w = GP[i].pt[2];
const double weight = GP[i].weight;
const double detJ = ele->getJacobian(u, v, w, jac);
std::vector<TensorialTraits<SVector3>::GradType> Grads;
BilinearTerm<SVector3, SVector3>::space1.gradf(ele, u, v, w,
Grads); // a optimiser ??
for(int j = 0; j < nbFF; j++) {
BT(j, 0) = B(0, j) = Grads[j](0, 0);
BT(j, 1) = B(1, j) = Grads[j](1, 1);
BT(j, 2) = B(2, j) = Grads[j](2, 2);
BT(j, 3) = B(3, j) = Grads[j](0, 1) + Grads[j](1, 0);
BT(j, 4) = B(4, j) = Grads[j](1, 2) + Grads[j](2, 1);
BT(j, 5) = B(5, j) = Grads[j](0, 2) + Grads[j](2, 0);
}
BTH.setAll(0.);
BTH.gemm(BT, H);
m.gemm(BTH, B, weight * detJ, 1.); // m = m + w*detJ*BT*H*B
}
}
else {
int nbFF1 = BilinearTerm<SVector3, SVector3>::space1.getNumKeys(ele);
int nbFF2 = BilinearTerm<SVector3, SVector3>::space2.getNumKeys(ele);
double jac[3][3];
fullMatrix<double> B(6, nbFF2);
fullMatrix<double> BTH(nbFF2, 6);
fullMatrix<double> BT(nbFF1, 6);
m.resize(nbFF1, nbFF2);
m.setAll(0.);
// Sum on Gauss Points i
for(int i = 0; i < npts; i++) {
const double u = GP[i].pt[0];
const double v = GP[i].pt[1];
const double w = GP[i].pt[2];
const double weight = GP[i].weight;
const double detJ = ele->getJacobian(u, v, w, jac);
std::vector<TensorialTraits<SVector3>::GradType>
Grads; // tableau de matrices...
std::vector<TensorialTraits<SVector3>::GradType>
GradsT; // tableau de matrices...
BilinearTerm<SVector3, SVector3>::space1.gradf(ele, u, v, w, Grads);
BilinearTerm<SVector3, SVector3>::space2.gradf(ele, u, v, w, GradsT);
for(int j = 0; j < nbFF1; j++) {
BT(j, 0) = Grads[j](0, 0);
BT(j, 1) = Grads[j](1, 1);
BT(j, 2) = Grads[j](2, 2);
BT(j, 3) = Grads[j](0, 1) + Grads[j](1, 0);
BT(j, 4) = Grads[j](1, 2) + Grads[j](2, 1);
BT(j, 5) = Grads[j](0, 2) + Grads[j](2, 0);
}
for(int j = 0; j < nbFF2; j++) {
B(0, j) = GradsT[j](0, 0);
B(1, j) = GradsT[j](1, 1);
B(2, j) = GradsT[j](2, 2);
B(3, j) = GradsT[j](0, 1) + GradsT[j](1, 0);
B(4, j) = GradsT[j](1, 2) + GradsT[j](2, 1);
B(5, j) = GradsT[j](0, 2) + GradsT[j](2, 0);
}
BTH.setAll(0.);
BTH.gemm(BT, H);
// gemm add the product to m so there is a sum on gauss' points here
m.gemm(BTH, B, weight * detJ, 1.);
}
}
}