Date: 2022-10-01T06:40:10+00:00

Actual source code: svdsetup.c
slepc-3.18.0 2022-10-01
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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:    SVD routines for setting up the solver
     12: */

     14: #include <slepc/private/svdimpl.h>

     16: /*@
     17:    SVDSetOperators - Set the matrices associated with the singular value problem.

     19:    Collective on svd

     21:    Input Parameters:
     22: +  svd - the singular value solver context
     23: .  A   - the matrix associated with the singular value problem
     24: -  B   - the second matrix in the case of GSVD

     26:    Level: beginner

     28: .seealso: SVDSolve(), SVDGetOperators()
     29: @*/
     30: PetscErrorCode SVDSetOperators(SVD svd,Mat A,Mat B)
     31: {
     32:   PetscInt       Ma,Na,Mb,Nb,ma,na,mb,nb,M0,N0,m0,n0;
     33:   PetscBool      samesize=PETSC_TRUE;

     41:   /* Check matrix sizes */
     42:   MatGetSize(A,&Ma,&Na);
     43:   MatGetLocalSize(A,&ma,&na);
     44:   if (svd->OP) {
     45:     MatGetSize(svd->OP,&M0,&N0);
     46:     MatGetLocalSize(svd->OP,&m0,&n0);
     47:     if (M0!=Ma || N0!=Na || m0!=ma || n0!=na) samesize = PETSC_FALSE;
     48:   }
     49:   if (B) {
     50:     MatGetSize(B,&Mb,&Nb);
     51:     MatGetLocalSize(B,&mb,&nb);
     54:     if (svd->OPb) {
     55:       MatGetSize(svd->OPb,&M0,&N0);
     56:       MatGetLocalSize(svd->OPb,&m0,&n0);
     57:       if (M0!=Mb || N0!=Nb || m0!=mb || n0!=nb) samesize = PETSC_FALSE;
     58:     }
     59:   }

     61:   PetscObjectReference((PetscObject)A);
     62:   if (B) PetscObjectReference((PetscObject)B);
     63:   if (svd->state && !samesize) SVDReset(svd);
     64:   else {
     65:     MatDestroy(&svd->OP);
     66:     MatDestroy(&svd->OPb);
     67:     MatDestroy(&svd->A);
     68:     MatDestroy(&svd->B);
     69:     MatDestroy(&svd->AT);
     70:     MatDestroy(&svd->BT);
     71:   }
     72:   svd->nrma = 0.0;
     73:   svd->nrmb = 0.0;
     74:   svd->OP   = A;
     75:   svd->OPb  = B;
     76:   svd->state = SVD_STATE_INITIAL;
     77:   return 0;
     78: }

     80: /*@
     81:    SVDGetOperators - Get the matrices associated with the singular value problem.

     83:    Collective on svd

     85:    Input Parameter:
     86: .  svd - the singular value solver context

     88:    Output Parameters:
     89: +  A  - the matrix associated with the singular value problem
     90: -  B  - the second matrix in the case of GSVD

     92:    Level: intermediate

     94: .seealso: SVDSolve(), SVDSetOperators()
     95: @*/
     96: PetscErrorCode SVDGetOperators(SVD svd,Mat *A,Mat *B)
     97: {
     99:   if (A) *A = svd->OP;
    100:   if (B) *B = svd->OPb;
    101:   return 0;
    102: }

    104: /*@
    105:    SVDSetSignature - Set the signature matrix defining a hyperbolic singular value problem.

    107:    Collective on svd

    109:    Input Parameters:
    110: +  svd   - the singular value solver context
    111: -  omega - a vector containing the diagonal elements of the signature matrix (or NULL)

    113:    Notes:
    114:    The signature matrix is relevant only for hyperbolic problems (HSVD).
    115:    Use NULL to reset a previously set signature.

    117:    Level: intermediate

    119: .seealso: SVDSetProblemType(), SVDSetOperators(), SVDGetSignature()
    120: @*/
    121: PetscErrorCode SVDSetSignature(SVD svd,Vec omega)
    122: {
    123:   PetscInt N,Ma,n,ma;

    126:   if (omega) {
    129:   }

    131:   if (omega && svd->OP) {  /* Check sizes */
    132:     VecGetSize(omega,&N);
    133:     VecGetLocalSize(omega,&n);
    134:     MatGetSize(svd->OP,&Ma,NULL);
    135:     MatGetLocalSize(svd->OP,&ma,NULL);
    138:   }

    140:   if (omega) PetscObjectReference((PetscObject)omega);
    141:   VecDestroy(&svd->omega);
    142:   svd->omega = omega;
    143:   svd->state = SVD_STATE_INITIAL;
    144:   return 0;
    145: }

    147: /*@
    148:    SVDGetSignature - Get the signature matrix defining a hyperbolic singular value problem.

    150:    Collective on svd

    152:    Input Parameter:
    153: .  svd - the singular value solver context

    155:    Output Parameter:
    156: .  omega - a vector containing the diagonal elements of the signature matrix

    158:    Level: intermediate

    160: .seealso: SVDSetSignature()
    161: @*/
    162: PetscErrorCode SVDGetSignature(SVD svd,Vec *omega)
    163: {
    166:   *omega = svd->omega;
    167:   return 0;
    168: }

    170: /*@
    171:    SVDSetUp - Sets up all the internal data structures necessary for the
    172:    execution of the singular value solver.

    174:    Collective on svd

    176:    Input Parameter:
    177: .  svd   - singular value solver context

    179:    Notes:
    180:    This function need not be called explicitly in most cases, since SVDSolve()
    181:    calls it. It can be useful when one wants to measure the set-up time
    182:    separately from the solve time.

    184:    Level: developer

    186: .seealso: SVDCreate(), SVDSolve(), SVDDestroy()
    187: @*/
    188: PetscErrorCode SVDSetUp(SVD svd)
    189: {
    190:   PetscBool      flg;
    191:   PetscInt       M,N,P=0,k,maxnsol;
    192:   SlepcSC        sc;
    193:   Vec            *T;
    194:   BV             bv;

    197:   if (svd->state) return 0;
    198:   PetscLogEventBegin(SVD_SetUp,svd,0,0,0);

    200:   /* reset the convergence flag from the previous solves */
    201:   svd->reason = SVD_CONVERGED_ITERATING;

    203:   /* set default solver type (SVDSetFromOptions was not called) */
    204:   if (!((PetscObject)svd)->type_name) SVDSetType(svd,SVDCROSS);
    205:   if (!svd->ds) SVDGetDS(svd,&svd->ds);

    207:   /* check matrices */

    210:   if (!svd->problem_type) {  /* set default problem type */
    211:     if (svd->OPb) {
    213:       SVDSetProblemType(svd,SVD_GENERALIZED);
    214:     } else {
    215:       if (svd->omega) SVDSetProblemType(svd,SVD_HYPERBOLIC);
    216:       else SVDSetProblemType(svd,SVD_STANDARD);
    217:     }
    218:   } else {  /* check consistency of problem type set by user */
    219:     if (svd->OPb) {
    222:     } else {
    226:     }
    227:   }

    229:   /* determine how to handle the transpose */
    230:   svd->expltrans = PETSC_TRUE;
    231:   if (svd->impltrans) svd->expltrans = PETSC_FALSE;
    232:   else {
    233:     MatHasOperation(svd->OP,MATOP_TRANSPOSE,&flg);
    234:     if (!flg) svd->expltrans = PETSC_FALSE;
    235:     else {
    236:       PetscObjectTypeCompareAny((PetscObject)svd,&flg,SVDLAPACK,SVDSCALAPACK,SVDELEMENTAL,"");
    237:       if (flg) svd->expltrans = PETSC_FALSE;
    238:     }
    239:   }

    241:   /* get matrix dimensions */
    242:   MatGetSize(svd->OP,&M,&N);
    243:   if (svd->isgeneralized) {
    244:     MatGetSize(svd->OPb,&P,NULL);
    246:   }

    248:   /* build transpose matrix */
    249:   MatDestroy(&svd->A);
    250:   MatDestroy(&svd->AT);
    251:   PetscObjectReference((PetscObject)svd->OP);
    252:   if (svd->expltrans) {
    253:     if (svd->isgeneralized || M>=N) {
    254:       svd->A = svd->OP;
    255:       MatHermitianTranspose(svd->OP,MAT_INITIAL_MATRIX,&svd->AT);
    256:     } else {
    257:       MatHermitianTranspose(svd->OP,MAT_INITIAL_MATRIX,&svd->A);
    258:       svd->AT = svd->OP;
    259:     }
    260:   } else {
    261:     if (svd->isgeneralized || M>=N) {
    262:       svd->A = svd->OP;
    263:       MatCreateHermitianTranspose(svd->OP,&svd->AT);
    264:     } else {
    265:       MatCreateHermitianTranspose(svd->OP,&svd->A);
    266:       svd->AT = svd->OP;
    267:     }
    268:   }

    270:   /* build transpose matrix B for GSVD */
    271:   if (svd->isgeneralized) {
    272:     MatDestroy(&svd->B);
    273:     MatDestroy(&svd->BT);
    274:     PetscObjectReference((PetscObject)svd->OPb);
    275:     if (svd->expltrans) {
    276:       svd->B = svd->OPb;
    277:       MatHermitianTranspose(svd->OPb,MAT_INITIAL_MATRIX,&svd->BT);
    278:     } else {
    279:       svd->B = svd->OPb;
    280:       MatCreateHermitianTranspose(svd->OPb,&svd->BT);
    281:     }
    282:   }

    284:   if (!svd->isgeneralized && M<N) {
    285:     /* swap initial vectors */
    286:     if (svd->nini || svd->ninil) {
    287:       T=svd->ISL; svd->ISL=svd->IS; svd->IS=T;
    288:       k=svd->ninil; svd->ninil=svd->nini; svd->nini=k;
    289:     }
    290:     /* swap basis vectors */
    291:     if (!svd->swapped) {  /* only the first time in case of multiple calls */
    292:       bv=svd->V; svd->V=svd->U; svd->U=bv;
    293:       svd->swapped = PETSC_TRUE;
    294:     }
    295:   }

    297:   maxnsol = svd->isgeneralized? PetscMin(PetscMin(M,N),P): PetscMin(M,N);
    298:   svd->ncv = PetscMin(svd->ncv,maxnsol);
    299:   svd->nsv = PetscMin(svd->nsv,maxnsol);

    302:   /* relative convergence criterion is not allowed in GSVD */
    303:   if (svd->conv==(SVDConv)-1) SVDSetConvergenceTest(svd,svd->isgeneralized?SVD_CONV_NORM:SVD_CONV_REL);

    306:   /* initialization of matrix norm (stardard case only, for GSVD it is done inside setup()) */
    307:   if (!svd->isgeneralized && svd->conv==SVD_CONV_NORM && !svd->nrma) MatNorm(svd->OP,NORM_INFINITY,&svd->nrma);

    309:   /* call specific solver setup */
    310:   PetscUseTypeMethod(svd,setup);

    312:   /* set tolerance if not yet set */
    313:   if (svd->tol==PETSC_DEFAULT) svd->tol = SLEPC_DEFAULT_TOL;

    315:   /* fill sorting criterion context */
    316:   DSGetSlepcSC(svd->ds,&sc);
    317:   sc->comparison    = (svd->which==SVD_LARGEST)? SlepcCompareLargestReal: SlepcCompareSmallestReal;
    318:   sc->comparisonctx = NULL;
    319:   sc->map           = NULL;
    320:   sc->mapobj        = NULL;

    322:   /* process initial vectors */
    323:   if (svd->nini<0) {
    324:     k = -svd->nini;
    326:     BVInsertVecs(svd->V,0,&k,svd->IS,PETSC_TRUE);
    327:     SlepcBasisDestroy_Private(&svd->nini,&svd->IS);
    328:     svd->nini = k;
    329:   }
    330:   if (svd->ninil<0) {
    331:     k = 0;
    332:     if (svd->leftbasis) {
    333:       k = -svd->ninil;
    335:       BVInsertVecs(svd->U,0,&k,svd->ISL,PETSC_TRUE);
    336:     } else PetscInfo(svd,"Ignoring initial left vectors\n");
    337:     SlepcBasisDestroy_Private(&svd->ninil,&svd->ISL);
    338:     svd->ninil = k;
    339:   }

    341:   PetscLogEventEnd(SVD_SetUp,svd,0,0,0);
    342:   svd->state = SVD_STATE_SETUP;
    343:   return 0;
    344: }

    346: /*@C
    347:    SVDSetInitialSpaces - Specify two basis of vectors that constitute the initial
    348:    right and/or left spaces.

    350:    Collective on svd

    352:    Input Parameters:
    353: +  svd   - the singular value solver context
    354: .  nr    - number of right vectors
    355: .  isr   - set of basis vectors of the right initial space
    356: .  nl    - number of left vectors
    357: -  isl   - set of basis vectors of the left initial space

    359:    Notes:
    360:    The initial right and left spaces are rough approximations to the right and/or
    361:    left singular subspaces from which the solver starts to iterate.
    362:    It is not necessary to provide both sets of vectors.

    364:    Some solvers start to iterate on a single vector (initial vector). In that case,
    365:    the other vectors are ignored.

    367:    These vectors do not persist from one SVDSolve() call to the other, so the
    368:    initial space should be set every time.

    370:    The vectors do not need to be mutually orthonormal, since they are explicitly
    371:    orthonormalized internally.

    373:    Common usage of this function is when the user can provide a rough approximation
    374:    of the wanted singular space. Then, convergence may be faster.

    376:    Level: intermediate

    378: .seealso: SVDSetUp()
    379: @*/
    380: PetscErrorCode SVDSetInitialSpaces(SVD svd,PetscInt nr,Vec isr[],PetscInt nl,Vec isl[])
    381: {
    386:   if (nr>0) {
    389:   }
    391:   if (nl>0) {
    394:   }
    395:   SlepcBasisReference_Private(nr,isr,&svd->nini,&svd->IS);
    396:   SlepcBasisReference_Private(nl,isl,&svd->ninil,&svd->ISL);
    397:   if (nr>0 || nl>0) svd->state = SVD_STATE_INITIAL;
    398:   return 0;
    399: }

    401: /*
    402:   SVDSetDimensions_Default - Set reasonable values for ncv, mpd if not set
    403:   by the user. This is called at setup.
    404:  */
    405: PetscErrorCode SVDSetDimensions_Default(SVD svd)
    406: {
    407:   PetscInt       N,M,P,maxnsol;

    409:   MatGetSize(svd->OP,&M,&N);
    410:   maxnsol = PetscMin(M,N);
    411:   if (svd->isgeneralized) {
    412:     MatGetSize(svd->OPb,&P,NULL);
    413:     maxnsol = PetscMin(maxnsol,P);
    414:   }
    415:   if (svd->ncv!=PETSC_DEFAULT) { /* ncv set */
    417:   } else if (svd->mpd!=PETSC_DEFAULT) { /* mpd set */
    418:     svd->ncv = PetscMin(maxnsol,svd->nsv+svd->mpd);
    419:   } else { /* neither set: defaults depend on nsv being small or large */
    420:     if (svd->nsv<500) svd->ncv = PetscMin(maxnsol,PetscMax(2*svd->nsv,10));
    421:     else {
    422:       svd->mpd = 500;
    423:       svd->ncv = PetscMin(maxnsol,svd->nsv+svd->mpd);
    424:     }
    425:   }
    426:   if (svd->mpd==PETSC_DEFAULT) svd->mpd = svd->ncv;
    427:   return 0;
    428: }

    430: /*@
    431:    SVDAllocateSolution - Allocate memory storage for common variables such
    432:    as the singular values and the basis vectors.

    434:    Collective on svd

    436:    Input Parameters:
    437: +  svd   - eigensolver context
    438: -  extra - number of additional positions, used for methods that require a
    439:            working basis slightly larger than ncv

    441:    Developer Notes:
    442:    This is SLEPC_EXTERN because it may be required by user plugin SVD
    443:    implementations.

    445:    This is called at setup after setting the value of ncv and the flag leftbasis.

    447:    Level: developer

    449: .seealso: SVDSetUp()
    450: @*/
    451: PetscErrorCode SVDAllocateSolution(SVD svd,PetscInt extra)
    452: {
    453:   PetscInt       oldsize,requested;
    454:   Vec            tr,tl;

    456:   requested = svd->ncv + extra;

    458:   /* oldsize is zero if this is the first time setup is called */
    459:   BVGetSizes(svd->V,NULL,NULL,&oldsize);

    461:   /* allocate sigma */
    462:   if (requested != oldsize || !svd->sigma) {
    463:     PetscFree3(svd->sigma,svd->perm,svd->errest);
    464:     if (svd->sign) PetscFree(svd->sign);
    465:     PetscMalloc3(requested,&svd->sigma,requested,&svd->perm,requested,&svd->errest);
    466:     if (svd->ishyperbolic) PetscMalloc1(requested,&svd->sign);
    467:   }
    468:   /* allocate V */
    469:   if (!svd->V) SVDGetBV(svd,&svd->V,NULL);
    470:   if (!oldsize) {
    471:     if (!((PetscObject)(svd->V))->type_name) BVSetType(svd->V,BVSVEC);
    472:     MatCreateVecsEmpty(svd->A,&tr,NULL);
    473:     BVSetSizesFromVec(svd->V,tr,requested);
    474:     VecDestroy(&tr);
    475:   } else BVResize(svd->V,requested,PETSC_FALSE);
    476:   /* allocate U */
    477:   if (svd->leftbasis && !svd->isgeneralized) {
    478:     if (!svd->U) SVDGetBV(svd,NULL,&svd->U);
    479:     if (!oldsize) {
    480:       if (!((PetscObject)(svd->U))->type_name) BVSetType(svd->U,((PetscObject)(svd->V))->type_name);
    481:       MatCreateVecsEmpty(svd->A,NULL,&tl);
    482:       BVSetSizesFromVec(svd->U,tl,requested);
    483:       VecDestroy(&tl);
    484:     } else BVResize(svd->U,requested,PETSC_FALSE);
    485:   } else if (svd->isgeneralized) {  /* left basis for the GSVD */
    486:     if (!svd->U) SVDGetBV(svd,NULL,&svd->U);
    487:     if (!oldsize) {
    488:       if (!((PetscObject)(svd->U))->type_name) BVSetType(svd->U,((PetscObject)(svd->V))->type_name);
    489:       SVDCreateLeftTemplate(svd,&tl);
    490:       BVSetSizesFromVec(svd->U,tl,requested);
    491:       VecDestroy(&tl);
    492:     } else BVResize(svd->U,requested,PETSC_FALSE);
    493:   }
    494:   return 0;
    495: }