Date: 2023-01-26T12:19:14+00:00

Actual source code: peputils.c
slepc-3.18.2 2023-01-26
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      1: /*
      2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
      4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

      6:    This file is part of SLEPc.
      7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
      8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      9: */
     10: /*
     11:    Common subroutines for several PEP solvers
     12: */

     14: #include <slepc/private/pepimpl.h>
     15: #include <slepcblaslapack.h>

     17: /*
     18:   Computes T_j=phy_idx(T) for a matrix T.
     19:     Tp (if j>0) and Tpp (if j>1) are the evaluation
     20:     of phy_(j-1) and phy(j-2)respectively.
     21: */
     22: PetscErrorCode PEPEvaluateBasisMat(PEP pep,PetscInt k,PetscScalar *T,PetscInt ldt,PetscInt idx,PetscScalar *Tpp,PetscInt ldtpp,PetscScalar *Tp,PetscInt ldtp,PetscScalar *Tj,PetscInt ldtj)
     23: {
     24:   PetscInt       i;
     25:   PetscReal      *ca,*cb,*cg;
     26:   PetscScalar    g,a;
     27:   PetscBLASInt   k_,ldt_,ldtj_,ldtp_;

     29:   if (idx==0) {
     30:     for (i=0;i<k;i++) {
     31:       PetscArrayzero(Tj+i*ldtj,k);
     32:       Tj[i+i*ldtj] = 1.0;
     33:     }
     34:   } else {
     35:     PetscBLASIntCast(ldt,&ldt_);
     36:     PetscBLASIntCast(ldtj,&ldtj_);
     37:     PetscBLASIntCast(ldtp,&ldtp_);
     38:     PetscBLASIntCast(k,&k_);
     39:     ca = pep->pbc; cb = pep->pbc+pep->nmat; cg = pep->pbc+2*pep->nmat;
     40:     for (i=0;i<k;i++) T[i*ldt+i] -= cb[idx-1];
     41:     if (idx>1) {
     42:       for (i=0;i<k;i++) PetscArraycpy(Tj+i*ldtj,Tpp+i*ldtpp,k);
     43:     }
     44:     a = 1/ca[idx-1];
     45:     g = (idx==1)?0.0:-cg[idx-1]/ca[idx-1];
     46:     PetscCallBLAS("BLASgemm",BLASgemm_("N","N",&k_,&k_,&k_,&a,T,&ldt_,Tp,&ldtp_,&g,Tj,&ldtj_));
     47:     for (i=0;i<k;i++) T[i*ldt+i] += cb[idx-1];
     48:   }
     49:   return 0;
     50: }

     52: /*
     53:    PEPEvaluateBasis - evaluate the polynomial basis on a given parameter sigma
     54: */
     55: PetscErrorCode PEPEvaluateBasis(PEP pep,PetscScalar sigma,PetscScalar isigma,PetscScalar *vals,PetscScalar *ivals)
     56: {
     57:   PetscInt   nmat=pep->nmat,k;
     58:   PetscReal  *a=pep->pbc,*b=pep->pbc+nmat,*g=pep->pbc+2*nmat;

     60:   if (ivals) for (k=0;k<nmat;k++) ivals[k] = 0.0;
     61:   vals[0] = 1.0;
     62:   vals[1] = (sigma-b[0])/a[0];
     63: #if !defined(PETSC_USE_COMPLEX)
     64:   if (ivals) ivals[1] = isigma/a[0];
     65: #endif
     66:   for (k=2;k<nmat;k++) {
     67:     vals[k] = ((sigma-b[k-1])*vals[k-1]-g[k-1]*vals[k-2])/a[k-1];
     68:     if (ivals) vals[k] -= isigma*ivals[k-1]/a[k-1];
     69: #if !defined(PETSC_USE_COMPLEX)
     70:     if (ivals) ivals[k] = ((sigma-b[k-1])*ivals[k-1]+isigma*vals[k-1]-g[k-1]*ivals[k-2])/a[k-1];
     71: #endif
     72:   }
     73:   return 0;
     74: }

     76: /*
     77:    PEPEvaluateBasisDerivative - evaluate the derivative of the polynomial basis on a given parameter sigma
     78: */
     79: PetscErrorCode PEPEvaluateBasisDerivative(PEP pep,PetscScalar sigma,PetscScalar isigma,PetscScalar *vals,PetscScalar *ivals)
     80: {
     81:   PetscInt       nmat=pep->nmat,k;
     82:   PetscReal      *a=pep->pbc,*b=pep->pbc+nmat,*g=pep->pbc+2*nmat;

     84:   PEPEvaluateBasis(pep,sigma,isigma,vals,ivals);
     85:   for (k=nmat-1;k>0;k--) {
     86:     vals[k] = vals[k-1];
     87:     if (ivals) ivals[k] = ivals[k-1];
     88:   }
     89:   vals[0] = 0.0;
     90:   vals[1] = vals[1]/a[0];
     91: #if !defined(PETSC_USE_COMPLEX)
     92:   if (ivals) ivals[1] = ivals[1]/a[0];
     93: #endif
     94:   for (k=2;k<nmat;k++) {
     95:     vals[k] += (sigma-b[k-1])*vals[k-1]-g[k-1]*vals[k-2];
     96:     if (ivals) vals[k] -= isigma*ivals[k-1];
     97:     vals[k] /= a[k-1];
     98: #if !defined(PETSC_USE_COMPLEX)
     99:     if (ivals) {
    100:       ivals[k] += (sigma-b[k-1])*ivals[k-1]+isigma*vals[k-1]-g[k-1]*ivals[k-2];
    101:       ivals[k] /= a[k-1];
    102:     }
    103: #endif
    104:   }
    105:   return 0;
    106: }