bool DenseGenMatrix::ComputeEigenVectors(const DenseSymMatrix& M,
DenseVector& Evalues)
{
Index dim = M.Dim();
DBG_ASSERT(Evalues.Dim()==dim);
DBG_ASSERT(NRows()==dim);
DBG_ASSERT(NCols()==dim);
// First we copy the content of the matrix into Q
const Number* Mvalues = M.Values();
for (Index j=0; j<dim; j++) {
for (Index i=j; i<dim; i++) {
values_[i+j*dim] = Mvalues[i+j*dim];
}
}
bool compute_eigenvectors = true;
Number* Evals = Evalues.Values();
Index info;
IpLapackDsyev(compute_eigenvectors, dim, values_,
dim, Evals, info);
initialized_ = (info==0);
ObjectChanged();
return (info==0);
}
void DenseSymMatrix::AddMatrix(Number alpha, const DenseSymMatrix& A,
Number beta)
{
DBG_ASSERT(beta==0. || initialized_);
DBG_ASSERT(Dim()==A.Dim());
if (alpha==0.)
return;
const Number* Avalues = A.Values();
const Index dim = Dim();
if (beta==0.) {
for (Index j=0; j<dim; j++) {
for (Index i=j; i<dim; i++) {
values_[i+j*dim] = alpha*Avalues[i+j*dim];
}
}
}
else if (beta==1.) {
for (Index j=0; j<dim; j++) {
for (Index i=j; i<dim; i++) {
values_[i+j*dim] += alpha*Avalues[i+j*dim];
}
}
}
else {
for (Index j=0; j<dim; j++) {
for (Index i=j; i<dim; i++) {
values_[i+j*dim] = alpha*Avalues[i+j*dim] + beta*values_[i+j*dim];
}
}
}
ObjectChanged();
initialized_ = true;
}
bool DenseGenMatrix::ComputeCholeskyFactor(const DenseSymMatrix& M)
{
Index dim = M.Dim();
DBG_ASSERT(dim==NCols());
DBG_ASSERT(dim==NRows());
ObjectChanged();
// First we copy the content of the symmetric matrix into J
const Number* Mvalues = M.Values();
for (Index j=0; j<dim; j++) {
for (Index i=j; i<dim; i++) {
values_[i+j*dim] = Mvalues[i+j*dim];
}
}
// Now call the lapack subroutine to perform the factorization
Index info;
IpLapackDpotrf(dim, values_, dim, info);
DBG_ASSERT(info>=0);
if (info!=0) {
initialized_ = false;
return false;
}
// We set all strictly upper values to zero
// ToDo: This might not be necessary?!?
for (Index j=1; j<dim; j++) {
for (Index i=0; i<j; i++) {
values_[i+j*dim] = 0.;
}
}
factorization_ = CHOL;
initialized_ = true;
return true;
}
