int XC::SymBandEigenSolver::solve(int nModes)
{
if(!theSOE)
{
std::cerr << "SymBandEigenSolver::solve() -- no XC::EigenSOE has been set yet\n";
return -1;
}
// Set number of modes
numModes= nModes;
// Number of equations
int n= theSOE->size;
// Check for quick return
if(numModes < 1)
{
numModes= 0;
return 0;
}
// Simple check
if(numModes > n)
numModes= n;
// Allocate storage for eigenvalues
eigenvalue.resize(n);
// Real work array (see LAPACK dsbevx subroutine documentation)
work.resize(7*n);
// Integer work array (see LAPACK dsbevx subroutine documentation)
std::vector<int> iwork(5*n);
// Leading dimension of eigenvectors
int ldz = n;
// Allocate storage for eigenvectors
eigenvector.resize(ldz*numModes);
// Number of superdiagonals
int kd= theSOE->numSuperD;
// Matrix data
double *ab= theSOE->A.getDataPtr();
// Leading dimension of the matrix
int ldab= kd + 1;
// Leading dimension of q
int ldq= n;
// Orthogonal matrix used in reduction to tridiagonal form
// (see LAPACK dsbevx subroutine documentation)
std::vector<double> q(ldq*n);
// Index ranges [1,numModes] of eigenpairs to compute
int il = 1;
int iu = numModes;
// Compute eigenvalues and eigenvectors
char jobz[] = "V";
// Selected eigenpairs are based on index range [il,iu]
char range[] = "I";
// Upper triagle of matrix is stored
char uplo[] = "U";
// Return value
std::vector<int> ifail(n);
int info= 0;
// Number of eigenvalues returned
int m= 0;
// Not used
double vl = 0.0;
double vu = 1.0;
// Not used ... I think!
double abstol = -1.0;
// if Mass matrix we make modifications to A:
// A -> M^(-1/2) A M^(-1/2)
double *M= theSOE->M.getDataPtr();
double *A= theSOE->A.getDataPtr();
int numSuperD = theSOE->numSuperD;
int size = n;
if(M) //Its seems that the M matrix must be DIAGONAL.
{
int i,j;
bool singular = false;
// form M^(-1/2) and check for singular mass matrix
for(int k=0; k<size; k++)
{
if(M[k] == 0.0)
{
singular = true;
// alternative is to set as a small no ~ 1e-10 times smallest m(i,i) != 0.0
std::cerr << "SymBandEigenSolver::solve() - M matrix singular\n";
return -1;
}
else
{
M[k] = 1.0/sqrt(M[k]);
}
}
// make modifications to A
// Aij -> Mi Aij Mj (based on new_ M)
for(i=0; i<size; i++)
{
double *AijPtr = A +(i+1)*(numSuperD+1) - 1;
int minColRow = i - numSuperD;
if(minColRow < 0) minColRow = 0;
for(j=i; j>=minColRow; j--)
{
*AijPtr *= M[j]*M[i];
AijPtr--;
}
}
}
// Calls the LAPACK routine that computes the eigenvalues and eigenvectors
// of the matrix A previously transforme.
dsbevx_(jobz, range, uplo, &n, &kd, ab, &ldab,
&q[0], &ldq, &vl, &vu, &il, &iu, &abstol, &m,
eigenvalue.getDataPtr(), eigenvector.getDataPtr(), &ldz, work.getDataPtr(), &iwork[0], &ifail[0], &info);
if(info < 0)
{
std::cerr << "SymBandEigenSolver::solve() -- invalid argument number " << -info << " passed to LAPACK dsbevx\n";
return info;
}
if(info > 0)
{
std::cerr << "SymBandEigenSolver::solve() -- LAPACK dsbevx returned error code " << info << std::endl;
return -info;
}
if(m < numModes)
{
std::cerr << "SymBandEigenSolver::solve() -- LAPACK dsbevx only computed " << m << " eigenvalues, " <<
numModes << "were requested\n";
numModes = m;
}
theSOE->factored = true;
// make modifications to the eigenvectors
// Eij -> Mi Eij (based on new_ M)
M= theSOE->M.getDataPtr();
if(M)
{
for(int j=0; j<numModes; j++)
{
double *eigVectJptr = &eigenvector[j*ldz];
double *MPtr = M;
for(int i=0; i<size; i++)
*eigVectJptr++ *= *MPtr++;
}
}
return 0;
}
int
SymBandEigenSolver::solve(int nModes, bool generalized, bool findSmallest)
{
if (generalized == true) {
opserr << "SymBandEigenSolver::solve() - only does standard problem\n";
return -1;
}
if (theSOE == 0) {
opserr << "SymBandEigenSolver::solve() -- no EigenSOE has been set yet\n";
return -1;
}
// Set number of modes
numModes = nModes;
// Number of equations
int n = theSOE->size;
// Check for quick return
if (numModes < 1) {
numModes = 0;
return 0;
}
// Simple check
if (numModes > n)
numModes = n;
// Allocate storage for eigenvalues
if (eigenvalue != 0)
delete [] eigenvalue;
eigenvalue = new double [n];
// Real work array (see LAPACK dsbevx subroutine documentation)
double *work = new double [7*n];
// Integer work array (see LAPACK dsbevx subroutine documentation)
int *iwork = new int [5*n];
// Leading dimension of eigenvectors
int ldz = n;
// Allocate storage for eigenvectors
if (eigenvector != 0)
delete [] eigenvector;
eigenvector = new double [ldz*numModes];
// Number of superdiagonals
int kd = theSOE->numSuperD;
// Matrix data
double *ab = theSOE->A;
// Leading dimension of the matrix
int ldab = kd + 1;
// Leading dimension of q
int ldq = n;
// Orthogonal matrix used in reduction to tridiagonal form
// (see LAPACK dsbevx subroutine documentation)
double *q = new double [ldq*n];
// Index ranges [1,numModes] of eigenpairs to compute
int il = 1;
int iu = numModes;
// Compute eigenvalues and eigenvectors
char *jobz = "V";
// Selected eigenpairs are based on index range [il,iu]
char *range = "I";
// Upper triagle of matrix is stored
char *uplo = "U";
// Return value
int *ifail = new int [n];
int info = 0;
// Number of eigenvalues returned
int m = 0;
// Not used
double vl = 0.0;
double vu = 1.0;
// Not used ... I think!
double abstol = -1.0;
// if Mass matrix we make modifications to A:
// A -> M^(-1/2) A M^(-1/2)
double *M = theSOE->M;
double *A = theSOE->A;
int numSuperD = theSOE->numSuperD;
int size = n;
if (M != 0) {
int i,j;
bool singular = false;
// form M^(-1/2) and check for singular mass matrix
for (int k=0; k<size; k++) {
if (M[k] == 0.0) {
singular = true;
// alternative is to set as a small no ~ 1e-10 times smallest m(i,i) != 0.0
opserr << "SymBandEigenSolver::solve() - M matrix singular\n";
return -1;
} else {
M[k] = 1.0/sqrt(M[k]);
}
}
// make modifications to A
// Aij -> Mi Aij Mj (based on new M)
for (i=0; i<size; i++) {
double *AijPtr = A +(i+1)*(numSuperD+1) - 1;
int minColRow = i - numSuperD;
if (minColRow < 0) minColRow = 0;
for (j=i; j>=minColRow; j--) {
*AijPtr *= M[j]*M[i];
AijPtr--;
}
}
}
// Call the LAPACK eigenvalue subroutine
#ifdef _WIN32
unsigned int sizeC = 1;
DSBEVX(jobz, range, uplo, &n, &kd, ab, &ldab,
q, &ldq, &vl, &vu, &il, &iu, &abstol, &m,
eigenvalue, eigenvector, &ldz, work, iwork, ifail, &info);
#else
dsbevx_(jobz, range, uplo, &n, &kd, ab, &ldab,
q, &ldq, &vl, &vu, &il, &iu, &abstol, &m,
eigenvalue, eigenvector, &ldz, work, iwork, ifail, &info);
#endif
delete [] q;
delete [] work;
delete [] iwork;
delete [] ifail;
if (info < 0) {
opserr << "SymBandEigenSolver::solve() -- invalid argument number " << -info << " passed to LAPACK dsbevx\n";
return info;
}
if (info > 0) {
opserr << "SymBandEigenSolver::solve() -- LAPACK dsbevx returned error code " << info << endln;
return -info;
}
if (m < numModes) {
opserr << "SymBandEigenSolver::solve() -- LAPACK dsbevx only computed " << m << " eigenvalues, " <<
numModes << "were requested\n";
numModes = m;
}
theSOE->factored = true;
// make modifications to the eigenvectors
// Eij -> Mi Eij (based on new M)
M = theSOE->M;
if (M != 0) {
for (int j=0; j<numModes; j++) {
double *eigVectJptr = &eigenvector[j*ldz];
double *MPtr = M;
for (int i=0; i<size; i++)
*eigVectJptr++ *= *MPtr++;
}
}
return 0;
}
int MatrixOperations::performEigenAnalysis(int pBeginMod, int pEndMod)
{
beginMod=pBeginMod;
endMod = pEndMod;
Matrix * A = theMatrix;
// opserr<< "hessian:"<< * theMatrix<<endln;
if (A ==0) {opserr<<"error, Hessian does not exist in MatrixOperator::performEigenAnalysis !"<<endln; exit(-1);}
// Number of equations
int n = A->noRows();
if (n != A->noCols()) {
opserr<<"MatrixOperations::performEigenAnalysis wrong. m!=n"<<endln;
exit(-1);
}
numModes = endMod - beginMod +1; //Q
// Check for quick return
if (numModes < 1) {
numModes = 0;
return 0;
}
// Simple check
if (numModes > n)
numModes = n;
// Allocate storage for eigenvalues
if (eigenvalue != 0)
delete [] eigenvalue;
eigenvalue = new double [n];
// Real work array (see LAPACK dsbevx subroutine documentation)
double *work = new double [7*n];
// Integer work array (see LAPACK dsbevx subroutine documentation)
int *iwork = new int [5*n];
// Leading dimension of eigenvectors
int ldz = n;
setSizeOfEigenVector(ldz); // alloc memory here.
// Allocate storage for eigenvectors
if (eigenvector != 0)
delete [] eigenvector;
eigenvector = new double [ldz*numModes];
// Number of superdiagonals
int kd = n-1;
// Matrix data
//double *ab = theSOE->A; //
double *ab = new double [n*n];
int i;
for (i=0; i<n*n; i++)
ab[i]=0.0;
for (i=0; i<n; i++)
for (int j=i; j<n; j++)
ab[kd+i-j+n*j]= (*A)(i,j);
// opserr<<"Hessian:"<<(*A)<<endln;
//opserr<<"ab:"<<endln;
/* for (i=0; i<n; i++)
for (int j=0; j<n; j++)
opserr<< ab[n*i+j]<<endln;*/
// Leading dimension of the matrix
int ldab = kd + 1;
// Leading dimension of q
int ldq = n;
// Orthogonal matrix used in reduction to tridiagonal form
// (see LAPACK dsbevx subroutine documentation)
double *q = new double [ldq*n];
// Index ranges [1,numModes] of eigenpairs to compute
int il = beginMod;
int iu = endMod;
// Compute eigenvalues and eigenvectors
char jobz[3] = "V";
// Selected eigenpairs are based on index range [il,iu]
char range[3] = "I";
// Upper triagle of matrix is stored
char uplo[3] = "U";
// Return value
int *ifail = new int [n];
int info = 0;
// Number of eigenvalues returned
int m = 0;
// Not used
double vl = 0.0;
double vu = 1.0;
// Not used
double abstol = -1.0;
// Call the LAPACK eigenvalue subroutine
#ifdef _WIN32
unsigned int sizeC = 1;
DSBEVX(jobz, range, uplo, &n, &kd, ab, &ldab,
q, &ldq, &vl, &vu, &il, &iu, &abstol, &m,
eigenvalue, eigenvector, &ldz, work, iwork, ifail, &info);
#else
dsbevx_(jobz, range, uplo, &n, &kd, ab, &ldab,
q, &ldq, &vl, &vu, &il, &iu, &abstol, &m,
eigenvalue, eigenvector, &ldz, work, iwork, ifail, &info);
#endif
delete [] q;
delete [] work;
delete [] iwork;
delete [] ifail;
if (info < 0) {
opserr << "Hessian::performEigenAnalysis() -- invalid argument number " << -info << " passed to LAPACK dsbevx\n";
return info;
}
if (info > 0) {
opserr << "Hessian::performEigenAnalysis() -- LAPACK dsbevx returned error code " << info << endln;
return -info;
}
if (m < numModes) {
opserr << "Hessian::performEigenAnalysis() -- LAPACK dsbevx only computed " << m << " eigenvalues, " <<
numModes << "were requested\n";
numModes = m;
}
return 0;
}