| Line | Branch | Exec | Source |
|---|---|---|---|
| 1 | /* | ||
| 2 | - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - | ||
| 3 | SLEPc - Scalable Library for Eigenvalue Problem Computations | ||
| 4 | Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain | ||
| 5 | |||
| 6 | This file is part of SLEPc. | ||
| 7 | SLEPc is distributed under a 2-clause BSD license (see LICENSE). | ||
| 8 | - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - | ||
| 9 | */ | ||
| 10 | /* | ||
| 11 | SLEPc polynomial eigensolver: "stoar" | ||
| 12 | |||
| 13 | Method: S-TOAR | ||
| 14 | |||
| 15 | Algorithm: | ||
| 16 | |||
| 17 | Symmetric Two-Level Orthogonal Arnoldi. | ||
| 18 | |||
| 19 | References: | ||
| 20 | |||
| 21 | [1] C. Campos and J.E. Roman, "Restarted Q-Arnoldi-type methods | ||
| 22 | exploiting symmetry in quadratic eigenvalue problems", BIT | ||
| 23 | Numer. Math. 56(4):1213-1236, 2016. | ||
| 24 | */ | ||
| 25 | |||
| 26 | #include <slepc/private/pepimpl.h> /*I "slepcpep.h" I*/ | ||
| 27 | #include "../src/pep/impls/krylov/pepkrylov.h" | ||
| 28 | #include <slepcblaslapack.h> | ||
| 29 | |||
| 30 | static PetscBool cited = PETSC_FALSE; | ||
| 31 | static const char citation[] = | ||
| 32 | "@Article{slepc-stoar,\n" | ||
| 33 | " author = \"C. Campos and J. E. Roman\",\n" | ||
| 34 | " title = \"Restarted {Q-Arnoldi-type} methods exploiting symmetry in quadratic eigenvalue problems\",\n" | ||
| 35 | " journal = \"{BIT} Numer. Math.\",\n" | ||
| 36 | " volume = \"56\",\n" | ||
| 37 | " number = \"4\",\n" | ||
| 38 | " pages = \"1213--1236\",\n" | ||
| 39 | " year = \"2016,\"\n" | ||
| 40 | " doi = \"https://doi.org/10.1007/s10543-016-0601-5\"\n" | ||
| 41 | "}\n"; | ||
| 42 | |||
| 43 | typedef struct { | ||
| 44 | PetscReal scal[2]; | ||
| 45 | Mat A[2]; | ||
| 46 | Vec t; | ||
| 47 | } PEP_STOAR_MATSHELL; | ||
| 48 | |||
| 49 | 75236 | static PetscErrorCode MatMult_STOAR(Mat A,Vec x,Vec y) | |
| 50 | { | ||
| 51 | 75236 | PEP_STOAR_MATSHELL *ctx; | |
| 52 | |||
| 53 |
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75236 | PetscFunctionBegin; |
| 54 |
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75236 | PetscCall(MatShellGetContext(A,&ctx)); |
| 55 |
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75236 | PetscCall(MatMult(ctx->A[0],x,y)); |
| 56 |
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75236 | PetscCall(VecScale(y,ctx->scal[0])); |
| 57 |
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75236 | if (ctx->scal[1]) { |
| 58 |
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224 | PetscCall(MatMult(ctx->A[1],x,ctx->t)); |
| 59 |
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224 | PetscCall(VecAXPY(y,ctx->scal[1],ctx->t)); |
| 60 | } | ||
| 61 |
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18084 | PetscFunctionReturn(PETSC_SUCCESS); |
| 62 | } | ||
| 63 | |||
| 64 | 486 | static PetscErrorCode MatDestroy_STOAR(Mat A) | |
| 65 | { | ||
| 66 | 486 | PEP_STOAR_MATSHELL *ctx; | |
| 67 | |||
| 68 |
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486 | PetscFunctionBegin; |
| 69 |
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486 | PetscCall(MatShellGetContext(A,&ctx)); |
| 70 |
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486 | PetscCall(VecDestroy(&ctx->t)); |
| 71 |
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486 | PetscCall(PetscFree(ctx)); |
| 72 |
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120 | PetscFunctionReturn(PETSC_SUCCESS); |
| 73 | } | ||
| 74 | |||
| 75 | 162 | PetscErrorCode PEPSTOARSetUpInnerMatrix(PEP pep,Mat *B) | |
| 76 | { | ||
| 77 | 162 | Mat pB[4],Bs[3],D[3]; | |
| 78 | 162 | PetscInt i,j,n,m; | |
| 79 | 162 | PEP_STOAR_MATSHELL *ctxMat[3]; | |
| 80 | 162 | PEP_STOAR *ctx=(PEP_STOAR*)pep->data; | |
| 81 | |||
| 82 |
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162 | PetscFunctionBegin; |
| 83 |
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648 | for (i=0;i<3;i++) { |
| 84 |
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486 | PetscCall(STGetMatrixTransformed(pep->st,i,&D[i])); /* D[2] = M */ |
| 85 | } | ||
| 86 |
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162 | PetscCall(MatGetLocalSize(D[2],&m,&n)); |
| 87 | |||
| 88 |
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648 | for (j=0;j<3;j++) { |
| 89 |
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486 | PetscCall(PetscNew(ctxMat+j)); |
| 90 |
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486 | PetscCall(MatCreateShell(PetscObjectComm((PetscObject)pep),m,n,PETSC_DETERMINE,PETSC_DETERMINE,ctxMat[j],&Bs[j])); |
| 91 |
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486 | PetscCall(MatShellSetOperation(Bs[j],MATOP_MULT,(PetscErrorCodeFn*)MatMult_STOAR)); |
| 92 |
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486 | PetscCall(MatShellSetOperation(Bs[j],MATOP_DESTROY,(PetscErrorCodeFn*)MatDestroy_STOAR)); |
| 93 | } | ||
| 94 |
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810 | for (i=0;i<4;i++) pB[i] = NULL; |
| 95 |
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162 | if (ctx->alpha) { |
| 96 | 154 | ctxMat[0]->A[0] = D[0]; ctxMat[0]->scal[0] = ctx->alpha; ctxMat[0]->scal[1] = 0.0; | |
| 97 | 154 | ctxMat[2]->A[0] = D[2]; ctxMat[2]->scal[0] = -ctx->alpha*pep->sfactor*pep->sfactor; ctxMat[2]->scal[1] = 0.0; | |
| 98 | 154 | pB[0] = Bs[0]; pB[3] = Bs[2]; | |
| 99 | } | ||
| 100 |
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162 | if (ctx->beta) { |
| 101 | 16 | i = (ctx->alpha)?1:0; | |
| 102 | 16 | ctxMat[0]->scal[1] = 0.0; | |
| 103 | 16 | ctxMat[0]->A[i] = D[1]; ctxMat[0]->scal[i] = -ctx->beta*pep->sfactor; | |
| 104 | 16 | ctxMat[1]->A[0] = D[2]; ctxMat[1]->scal[0] = -ctx->beta*pep->sfactor*pep->sfactor; ctxMat[1]->scal[1] = 0.0; | |
| 105 | 16 | pB[0] = Bs[0]; pB[1] = pB[2] = Bs[1]; | |
| 106 | } | ||
| 107 |
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162 | PetscCall(BVCreateVec(pep->V,&ctxMat[0]->t)); |
| 108 |
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162 | PetscCall(MatCreateNest(PetscObjectComm((PetscObject)pep),2,NULL,2,NULL,pB,B)); |
| 109 |
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648 | for (j=0;j<3;j++) PetscCall(MatDestroy(&Bs[j])); |
| 110 |
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40 | PetscFunctionReturn(PETSC_SUCCESS); |
| 111 | } | ||
| 112 | |||
| 113 | 170 | static PetscErrorCode PEPSetUp_STOAR(PEP pep) | |
| 114 | { | ||
| 115 | 170 | PetscBool sinv,flg; | |
| 116 | 170 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 117 | 170 | PetscInt ld,i; | |
| 118 | 170 | PetscReal eta; | |
| 119 | 170 | BVOrthogType otype; | |
| 120 | 170 | BVOrthogBlockType obtype; | |
| 121 | |||
| 122 |
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170 | PetscFunctionBegin; |
| 123 |
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170 | PEPCheckHermitian(pep); |
| 124 |
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170 | PEPCheckQuadratic(pep); |
| 125 |
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170 | PEPCheckShiftSinvert(pep); |
| 126 | /* spectrum slicing requires special treatment of default values */ | ||
| 127 |
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170 | if (pep->which==PEP_ALL) { |
| 128 | 66 | pep->ops->solve = PEPSolve_STOAR_QSlice; | |
| 129 | 66 | pep->ops->extractvectors = NULL; | |
| 130 | 66 | pep->ops->setdefaultst = NULL; | |
| 131 |
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66 | PetscCall(PEPSetUp_STOAR_QSlice(pep)); |
| 132 | } else { | ||
| 133 |
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104 | PetscCall(PEPSetDimensions_Default(pep,pep->nev,&pep->ncv,&pep->mpd)); |
| 134 |
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104 | PetscCheck(ctx->lock || pep->mpd>=pep->ncv,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"Should not use mpd parameter in non-locking variant"); |
| 135 |
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104 | if (pep->max_it==PETSC_DETERMINE) pep->max_it = PetscMax(100,2*(pep->nmat-1)*pep->n/pep->ncv); |
| 136 | 104 | pep->ops->solve = PEPSolve_STOAR; | |
| 137 | 104 | ld = pep->ncv+2; | |
| 138 |
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104 | PetscCall(DSSetType(pep->ds,DSGHIEP)); |
| 139 |
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104 | PetscCall(DSSetCompact(pep->ds,PETSC_TRUE)); |
| 140 |
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104 | PetscCall(DSSetExtraRow(pep->ds,PETSC_TRUE)); |
| 141 |
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104 | PetscCall(DSAllocate(pep->ds,ld)); |
| 142 |
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104 | PetscCall(PEPBasisCoefficients(pep,pep->pbc)); |
| 143 |
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104 | PetscCall(STGetTransform(pep->st,&flg)); |
| 144 |
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104 | if (!flg) { |
| 145 |
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88 | PetscCall(PetscFree(pep->solvematcoeffs)); |
| 146 |
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88 | PetscCall(PetscMalloc1(pep->nmat,&pep->solvematcoeffs)); |
| 147 |
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88 | PetscCall(PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&sinv)); |
| 148 |
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88 | if (sinv) PetscCall(PEPEvaluateBasis(pep,pep->target,0,pep->solvematcoeffs,NULL)); |
| 149 | else { | ||
| 150 |
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120 | for (i=0;i<pep->nmat-1;i++) pep->solvematcoeffs[i] = 0.0; |
| 151 | 40 | pep->solvematcoeffs[pep->nmat-1] = 1.0; | |
| 152 | } | ||
| 153 | } | ||
| 154 | } | ||
| 155 |
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170 | if (!pep->which) PetscCall(PEPSetWhichEigenpairs_Default(pep)); |
| 156 |
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170 | PEPCheckUnsupported(pep,PEP_FEATURE_NONMONOMIAL | PEP_FEATURE_REGION); |
| 157 | |||
| 158 |
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170 | PetscCall(PEPAllocateSolution(pep,2)); |
| 159 |
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170 | PetscCall(PEPSetWorkVecs(pep,4)); |
| 160 |
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170 | PetscCall(BVDestroy(&ctx->V)); |
| 161 |
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170 | PetscCall(BVCreateTensor(pep->V,pep->nmat-1,&ctx->V)); |
| 162 |
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170 | PetscCall(BVGetOrthogonalization(pep->V,&otype,NULL,&eta,&obtype)); |
| 163 |
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170 | PetscCall(BVSetOrthogonalization(ctx->V,otype,BV_ORTHOG_REFINE_ALWAYS,eta,obtype)); |
| 164 |
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42 | PetscFunctionReturn(PETSC_SUCCESS); |
| 165 | } | ||
| 166 | |||
| 167 | /* | ||
| 168 | Compute a run of Lanczos iterations. dim(work)=(ctx->ld)*4 | ||
| 169 | */ | ||
| 170 | 896 | static PetscErrorCode PEPSTOARrun(PEP pep,PetscReal *a,PetscReal *b,PetscReal *omega,PetscInt k,PetscInt *M,PetscBool *breakdown,PetscBool *symmlost,Vec *t_) | |
| 171 | { | ||
| 172 | 896 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 173 | 896 | PetscInt i,j,m=*M,l,lock; | |
| 174 | 896 | PetscInt lds,d,ld,offq,nqt,ldds; | |
| 175 | 896 | Vec v=t_[0],t=t_[1],q=t_[2]; | |
| 176 | 896 | PetscReal norm,sym=0.0,fro=0.0,*f; | |
| 177 | 896 | PetscScalar *y,*S,*x,sigma; | |
| 178 | 896 | PetscBLASInt j_,one=1; | |
| 179 | 896 | PetscBool lindep,flg,sinvert=PETSC_FALSE; | |
| 180 | 896 | Mat MS; | |
| 181 | |||
| 182 |
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896 | PetscFunctionBegin; |
| 183 |
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896 | PetscCall(PetscMalloc1(*M,&y)); |
| 184 |
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896 | PetscCall(BVGetSizes(pep->V,NULL,NULL,&ld)); |
| 185 |
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896 | PetscCall(BVTensorGetDegree(ctx->V,&d)); |
| 186 |
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|
896 | PetscCall(BVGetActiveColumns(pep->V,&lock,&nqt)); |
| 187 | 896 | lds = d*ld; | |
| 188 | 896 | offq = ld; | |
| 189 |
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896 | PetscCall(DSGetLeadingDimension(pep->ds,&ldds)); |
| 190 | 896 | *breakdown = PETSC_FALSE; /* ----- */ | |
| 191 |
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896 | PetscCall(DSGetDimensions(pep->ds,NULL,&l,NULL,NULL)); |
| 192 |
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896 | PetscCall(BVSetActiveColumns(ctx->V,0,m)); |
| 193 |
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896 | PetscCall(BVSetActiveColumns(pep->V,0,nqt)); |
| 194 |
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896 | PetscCall(STGetTransform(pep->st,&flg)); |
| 195 |
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896 | if (!flg) { |
| 196 | /* spectral transformation handled by the solver */ | ||
| 197 |
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848 | PetscCall(PetscObjectTypeCompareAny((PetscObject)pep->st,&flg,STSINVERT,STSHIFT,"")); |
| 198 |
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848 | PetscCheck(flg,PetscObjectComm((PetscObject)pep),PETSC_ERR_SUP,"ST type not supported for TOAR without transforming matrices"); |
| 199 |
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848 | PetscCall(PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&sinvert)); |
| 200 |
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848 | PetscCall(STGetShift(pep->st,&sigma)); |
| 201 | } | ||
| 202 |
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9892 | for (j=k;j<m;j++) { |
| 203 | /* apply operator */ | ||
| 204 |
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8996 | PetscCall(BVTensorGetFactors(ctx->V,NULL,&MS)); |
| 205 |
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8996 | PetscCall(MatDenseGetArray(MS,&S)); |
| 206 |
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8996 | PetscCall(BVGetColumn(pep->V,nqt,&t)); |
| 207 |
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8996 | PetscCall(BVMultVec(pep->V,1.0,0.0,v,S+j*lds)); |
| 208 |
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8996 | if (!sinvert) { |
| 209 |
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6728 | PetscCall(STMatMult(pep->st,0,v,q)); |
| 210 |
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6728 | PetscCall(BVMultVec(pep->V,1.0,0.0,v,S+offq+j*lds)); |
| 211 |
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6728 | PetscCall(STMatMult(pep->st,1,v,t)); |
| 212 |
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6728 | PetscCall(VecAXPY(q,pep->sfactor,t)); |
| 213 |
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6728 | if (ctx->beta && ctx->alpha) { |
| 214 | ✗ | PetscCall(STMatMult(pep->st,2,v,t)); | |
| 215 | ✗ | PetscCall(VecAXPY(q,-pep->sfactor*pep->sfactor*ctx->beta/ctx->alpha,t)); | |
| 216 | } | ||
| 217 |
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6728 | PetscCall(STMatSolve(pep->st,q,t)); |
| 218 |
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6728 | PetscCall(VecScale(t,-1.0/(pep->sfactor*pep->sfactor))); |
| 219 | } else { | ||
| 220 |
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2268 | PetscCall(STMatMult(pep->st,1,v,q)); |
| 221 |
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2268 | PetscCall(STMatMult(pep->st,2,v,t)); |
| 222 |
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2268 | PetscCall(VecAXPY(q,sigma*pep->sfactor,t)); |
| 223 |
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2268 | PetscCall(VecScale(q,pep->sfactor)); |
| 224 |
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2268 | PetscCall(BVMultVec(pep->V,1.0,0.0,v,S+offq+j*lds)); |
| 225 |
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2268 | PetscCall(STMatMult(pep->st,2,v,t)); |
| 226 |
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2268 | PetscCall(VecAXPY(q,pep->sfactor*pep->sfactor,t)); |
| 227 |
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2268 | PetscCall(STMatSolve(pep->st,q,t)); |
| 228 |
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2268 | PetscCall(VecScale(t,-1.0)); |
| 229 | } | ||
| 230 |
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8996 | PetscCall(BVRestoreColumn(pep->V,nqt,&t)); |
| 231 | |||
| 232 | /* orthogonalize */ | ||
| 233 |
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8996 | if (!sinvert) x = S+offq+(j+1)*lds; |
| 234 | 2268 | else x = S+(j+1)*lds; | |
| 235 |
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8996 | PetscCall(BVOrthogonalizeColumn(pep->V,nqt,x,&norm,&lindep)); |
| 236 | |||
| 237 |
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8996 | if (!lindep) { |
| 238 |
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8996 | if (!sinvert) *(S+offq+(j+1)*lds+nqt) = norm; |
| 239 | 2268 | else *(S+(j+1)*lds+nqt) = norm; | |
| 240 |
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8996 | PetscCall(BVScaleColumn(pep->V,nqt,1.0/norm)); |
| 241 | 8996 | nqt++; | |
| 242 | } | ||
| 243 |
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8996 | if (!sinvert) { |
| 244 |
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110728 | for (i=0;i<=nqt-1;i++) *(S+(j+1)*lds+i) = *(S+offq+j*lds+i); |
| 245 |
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6728 | if (ctx->beta && ctx->alpha) { |
| 246 | ✗ | for (i=0;i<=nqt-1;i++) *(S+(j+1)*lds+offq+i) -= *(S+(j+1)*lds+i)*ctx->beta/ctx->alpha; | |
| 247 | } | ||
| 248 |
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36000 | } else for (i=0;i<nqt;i++) *(S+(j+1)*lds+offq+i) = *(S+j*lds+i)+sigma*(*(S+(j+1)*lds+i)); |
| 249 |
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8996 | PetscCall(BVSetActiveColumns(pep->V,0,nqt)); |
| 250 |
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8996 | PetscCall(MatDenseRestoreArray(MS,&S)); |
| 251 |
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8996 | PetscCall(BVTensorRestoreFactors(ctx->V,NULL,&MS)); |
| 252 | |||
| 253 | /* level-2 orthogonalization */ | ||
| 254 |
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8996 | PetscCall(BVOrthogonalizeColumn(ctx->V,j+1,y,&norm,&lindep)); |
| 255 | 8996 | a[j] = PetscRealPart(y[j]); | |
| 256 |
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8996 | omega[j+1] = (norm > 0)?1.0:-1.0; |
| 257 |
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8996 | PetscCall(BVScaleColumn(ctx->V,j+1,1.0/norm)); |
| 258 | 8996 | b[j] = PetscAbsReal(norm); | |
| 259 | |||
| 260 | /* check symmetry */ | ||
| 261 |
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8996 | PetscCall(DSGetArrayReal(pep->ds,DS_MAT_T,&f)); |
| 262 |
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8996 | if (j==k) { |
| 263 |
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7192 | for (i=l;i<j-1;i++) y[i] = PetscAbsScalar(y[i])-PetscAbsReal(f[2*ldds+i]); |
| 264 |
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1056 | for (i=0;i<l;i++) y[i] = 0.0; |
| 265 | } | ||
| 266 |
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8996 | PetscCall(DSRestoreArrayReal(pep->ds,DS_MAT_T,&f)); |
| 267 |
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8996 | if (j>0) y[j-1] = PetscAbsScalar(y[j-1])-PetscAbsReal(b[j-1]); |
| 268 |
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8996 | PetscCall(PetscBLASIntCast(j,&j_)); |
| 269 | 8996 | sym = SlepcAbs(BLASnrm2_(&j_,y,&one),sym); | |
| 270 | 8996 | fro = SlepcAbs(fro,SlepcAbs(a[j],b[j])); | |
| 271 |
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8996 | if (j>0) fro = SlepcAbs(fro,b[j-1]); |
| 272 |
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15668 | if (sym/fro>PetscMax(PETSC_SQRT_MACHINE_EPSILON,10*pep->tol)) { |
| 273 | ✗ | *symmlost = PETSC_TRUE; | |
| 274 | ✗ | *M=j; | |
| 275 | ✗ | break; | |
| 276 | } | ||
| 277 | } | ||
| 278 |
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896 | PetscCall(BVSetActiveColumns(pep->V,lock,nqt)); |
| 279 |
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896 | PetscCall(BVSetActiveColumns(ctx->V,0,*M)); |
| 280 |
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896 | PetscCall(PetscFree(y)); |
| 281 |
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|
224 | PetscFunctionReturn(PETSC_SUCCESS); |
| 282 | } | ||
| 283 | |||
| 284 | #if 0 | ||
| 285 | static PetscErrorCode PEPSTOARpreKConvergence(PEP pep,PetscInt nv,PetscReal *norm,Vec *w) | ||
| 286 | { | ||
| 287 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | ||
| 288 | PetscBLASInt n_,one=1; | ||
| 289 | PetscInt lds=2*ctx->ld; | ||
| 290 | PetscReal t1,t2; | ||
| 291 | PetscScalar *S=ctx->S; | ||
| 292 | |||
| 293 | PetscFunctionBegin; | ||
| 294 | PetscCall(PetscBLASIntCast(nv+2,&n_)); | ||
| 295 | t1 = BLASnrm2_(&n_,S+nv*2*ctx->ld,&one); | ||
| 296 | t2 = BLASnrm2_(&n_,S+(nv*2+1)*ctx->ld,&one); | ||
| 297 | *norm = SlepcAbs(t1,t2); | ||
| 298 | PetscCall(BVSetActiveColumns(pep->V,0,nv+2)); | ||
| 299 | PetscCall(BVMultVec(pep->V,1.0,0.0,w[1],S+nv*lds)); | ||
| 300 | PetscCall(STMatMult(pep->st,0,w[1],w[2])); | ||
| 301 | PetscCall(VecNorm(w[2],NORM_2,&t1)); | ||
| 302 | PetscCall(BVMultVec(pep->V,1.0,0.0,w[1],S+ctx->ld+nv*lds)); | ||
| 303 | PetscCall(STMatMult(pep->st,2,w[1],w[2])); | ||
| 304 | PetscCall(VecNorm(w[2],NORM_2,&t2)); | ||
| 305 | t2 *= pep->sfactor*pep->sfactor; | ||
| 306 | *norm = PetscMax(*norm,SlepcAbs(t1,t2)); | ||
| 307 | PetscFunctionReturn(PETSC_SUCCESS); | ||
| 308 | } | ||
| 309 | #endif | ||
| 310 | |||
| 311 | 104 | PetscErrorCode PEPSolve_STOAR(PEP pep) | |
| 312 | { | ||
| 313 | 104 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 314 | 104 | PetscInt j,k,l,nv=0,ld,ldds,t,nq=0; | |
| 315 | 104 | PetscInt nconv=0,deg=pep->nmat-1; | |
| 316 | 104 | PetscScalar sigma; | |
| 317 | 104 | PetscReal beta,norm=1.0,*omega,*a,*b; | |
| 318 | 104 | PetscBool breakdown,symmlost=PETSC_FALSE,sinv=PETSC_FALSE,falselock=PETSC_TRUE,flg; | |
| 319 | 104 | Mat MQ,A,D; | |
| 320 | 104 | Vec vomega; | |
| 321 | |||
| 322 |
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104 | PetscFunctionBegin; |
| 323 |
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104 | PetscCall(PetscCitationsRegister(citation,&cited)); |
| 324 |
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104 | PetscCall(PEPSTOARSetUpInnerMatrix(pep,&A)); |
| 325 |
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104 | PetscCall(BVSetMatrix(ctx->V,A,PETSC_TRUE)); |
| 326 |
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104 | PetscCall(MatDestroy(&A)); |
| 327 |
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104 | if (ctx->lock) { |
| 328 | /* undocumented option to use a cheaper locking instead of the true locking */ | ||
| 329 |
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96 | PetscCall(PetscOptionsGetBool(NULL,NULL,"-pep_stoar_falselocking",&falselock,NULL)); |
| 330 | } | ||
| 331 |
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104 | PetscCall(BVGetSizes(pep->V,NULL,NULL,&ld)); |
| 332 |
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104 | PetscCall(STGetShift(pep->st,&sigma)); |
| 333 |
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104 | PetscCall(STGetTransform(pep->st,&flg)); |
| 334 |
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104 | if (pep->sfactor!=1.0) { |
| 335 |
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40 | if (!flg) { |
| 336 | 32 | pep->target /= pep->sfactor; | |
| 337 |
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32 | PetscCall(RGPushScale(pep->rg,1.0/pep->sfactor)); |
| 338 |
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32 | PetscCall(STScaleShift(pep->st,1.0/pep->sfactor)); |
| 339 | 32 | sigma /= pep->sfactor; | |
| 340 | } else { | ||
| 341 |
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8 | PetscCall(PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&sinv)); |
| 342 |
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8 | pep->target = sinv?pep->target*pep->sfactor:pep->target/pep->sfactor; |
| 343 |
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8 | PetscCall(RGPushScale(pep->rg,sinv?pep->sfactor:1.0/pep->sfactor)); |
| 344 |
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8 | PetscCall(STScaleShift(pep->st,sinv?pep->sfactor:1.0/pep->sfactor)); |
| 345 | } | ||
| 346 | } | ||
| 347 |
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104 | if (flg) sigma = 0.0; |
| 348 | |||
| 349 | /* Get the starting Arnoldi vector */ | ||
| 350 |
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104 | PetscCall(BVTensorBuildFirstColumn(ctx->V,pep->nini)); |
| 351 |
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104 | PetscCall(DSSetDimensions(pep->ds,1,PETSC_DETERMINE,PETSC_DETERMINE)); |
| 352 |
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104 | PetscCall(BVSetActiveColumns(ctx->V,0,1)); |
| 353 |
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104 | PetscCall(DSGetMatAndColumn(pep->ds,DS_MAT_D,0,&D,&vomega)); |
| 354 |
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104 | PetscCall(BVGetSignature(ctx->V,vomega)); |
| 355 |
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104 | PetscCall(DSRestoreMatAndColumn(pep->ds,DS_MAT_D,0,&D,&vomega)); |
| 356 | |||
| 357 | /* Restart loop */ | ||
| 358 | 104 | l = 0; | |
| 359 |
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104 | PetscCall(DSGetLeadingDimension(pep->ds,&ldds)); |
| 360 | 1000 | while (pep->reason == PEP_CONVERGED_ITERATING) { | |
| 361 | 896 | pep->its++; | |
| 362 |
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896 | PetscCall(DSGetArrayReal(pep->ds,DS_MAT_T,&a)); |
| 363 | 896 | b = a+ldds; | |
| 364 |
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896 | PetscCall(DSGetArrayReal(pep->ds,DS_MAT_D,&omega)); |
| 365 | |||
| 366 | /* Compute an nv-step Lanczos factorization */ | ||
| 367 | 896 | nv = PetscMin(pep->nconv+pep->mpd,pep->ncv); | |
| 368 |
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896 | PetscCall(DSSetDimensions(pep->ds,nv,pep->nconv,pep->nconv+l)); |
| 369 |
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896 | PetscCall(PEPSTOARrun(pep,a,b,omega,pep->nconv+l,&nv,&breakdown,&symmlost,pep->work)); |
| 370 | 896 | beta = b[nv-1]; | |
| 371 |
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896 | if (symmlost && nv==pep->nconv+l) { |
| 372 | ✗ | pep->reason = PEP_DIVERGED_SYMMETRY_LOST; | |
| 373 | ✗ | pep->nconv = nconv; | |
| 374 | ✗ | if (falselock || !ctx->lock) { | |
| 375 | ✗ | PetscCall(BVSetActiveColumns(ctx->V,0,pep->nconv)); | |
| 376 | ✗ | PetscCall(BVTensorCompress(ctx->V,0)); | |
| 377 | } | ||
| 378 | break; | ||
| 379 | } | ||
| 380 |
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896 | PetscCall(DSRestoreArrayReal(pep->ds,DS_MAT_T,&a)); |
| 381 |
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896 | PetscCall(DSRestoreArrayReal(pep->ds,DS_MAT_D,&omega)); |
| 382 |
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896 | PetscCall(DSSetDimensions(pep->ds,nv,pep->nconv,pep->nconv+l)); |
| 383 |
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896 | if (l==0) PetscCall(DSSetState(pep->ds,DS_STATE_INTERMEDIATE)); |
| 384 |
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792 | else PetscCall(DSSetState(pep->ds,DS_STATE_RAW)); |
| 385 | |||
| 386 | /* Solve projected problem */ | ||
| 387 |
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896 | PetscCall(DSSolve(pep->ds,pep->eigr,pep->eigi)); |
| 388 |
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896 | PetscCall(DSSort(pep->ds,pep->eigr,pep->eigi,NULL,NULL,NULL)); |
| 389 |
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896 | PetscCall(DSUpdateExtraRow(pep->ds)); |
| 390 |
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896 | PetscCall(DSSynchronize(pep->ds,pep->eigr,pep->eigi)); |
| 391 | |||
| 392 | /* Check convergence */ | ||
| 393 | /* PetscCall(PEPSTOARpreKConvergence(pep,nv,&norm,pep->work));*/ | ||
| 394 | 896 | norm = 1.0; | |
| 395 |
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896 | PetscCall(DSGetDimensions(pep->ds,NULL,NULL,NULL,&t)); |
| 396 |
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896 | PetscCall(PEPKrylovConvergence(pep,PETSC_FALSE,pep->nconv,t-pep->nconv,PetscAbsReal(beta)*norm,&k)); |
| 397 |
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896 | PetscCall((*pep->stopping)(pep,pep->its,pep->max_it,k,pep->nev,&pep->reason,pep->stoppingctx)); |
| 398 | |||
| 399 | /* Update l */ | ||
| 400 |
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896 | if (pep->reason != PEP_CONVERGED_ITERATING || breakdown) l = 0; |
| 401 | else { | ||
| 402 |
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792 | l = PetscMax(1,(PetscInt)((nv-k)/2)); |
| 403 | 792 | l = PetscMin(l,t); | |
| 404 |
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792 | PetscCall(DSGetTruncateSize(pep->ds,k,t,&l)); |
| 405 |
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792 | if (!breakdown) { |
| 406 | /* Prepare the Rayleigh quotient for restart */ | ||
| 407 |
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792 | PetscCall(DSTruncate(pep->ds,k+l,PETSC_FALSE)); |
| 408 | } | ||
| 409 | } | ||
| 410 | 896 | nconv = k; | |
| 411 |
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896 | if (!ctx->lock && pep->reason == PEP_CONVERGED_ITERATING && !breakdown) { l += k; k = 0; } /* non-locking variant: reset no. of converged pairs */ |
| 412 |
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896 | if (l) PetscCall(PetscInfo(pep,"Preparing to restart keeping l=%" PetscInt_FMT " vectors\n",l)); |
| 413 | |||
| 414 | /* Update S */ | ||
| 415 |
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896 | PetscCall(DSGetMat(pep->ds,DS_MAT_Q,&MQ)); |
| 416 |
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896 | PetscCall(BVMultInPlace(ctx->V,MQ,pep->nconv,k+l)); |
| 417 |
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896 | PetscCall(DSRestoreMat(pep->ds,DS_MAT_Q,&MQ)); |
| 418 | |||
| 419 | /* Copy last column of S */ | ||
| 420 |
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896 | PetscCall(BVCopyColumn(ctx->V,nv,k+l)); |
| 421 |
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896 | PetscCall(BVSetActiveColumns(ctx->V,0,k+l)); |
| 422 |
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896 | PetscCall(DSSetDimensions(pep->ds,k+l,PETSC_DETERMINE,PETSC_DETERMINE)); |
| 423 |
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896 | PetscCall(DSGetMatAndColumn(pep->ds,DS_MAT_D,0,&D,&vomega)); |
| 424 |
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896 | PetscCall(BVSetSignature(ctx->V,vomega)); |
| 425 |
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896 | PetscCall(DSRestoreMatAndColumn(pep->ds,DS_MAT_D,0,&D,&vomega)); |
| 426 | |||
| 427 |
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896 | if (breakdown && pep->reason == PEP_CONVERGED_ITERATING) { |
| 428 | /* stop if breakdown */ | ||
| 429 | ✗ | PetscCall(PetscInfo(pep,"Breakdown TOAR method (it=%" PetscInt_FMT " norm=%g)\n",pep->its,(double)beta)); | |
| 430 | ✗ | pep->reason = PEP_DIVERGED_BREAKDOWN; | |
| 431 | } | ||
| 432 |
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896 | if (pep->reason != PEP_CONVERGED_ITERATING) l--; |
| 433 |
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896 | PetscCall(BVGetActiveColumns(pep->V,NULL,&nq)); |
| 434 |
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896 | if (k+l+deg<=nq) { |
| 435 |
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896 | PetscCall(BVSetActiveColumns(ctx->V,pep->nconv,k+l+1)); |
| 436 |
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896 | if (!falselock && ctx->lock) PetscCall(BVTensorCompress(ctx->V,k-pep->nconv)); |
| 437 |
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896 | else PetscCall(BVTensorCompress(ctx->V,0)); |
| 438 | } | ||
| 439 | 896 | pep->nconv = k; | |
| 440 |
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1000 | PetscCall(PEPMonitor(pep,pep->its,nconv,pep->eigr,pep->eigi,pep->errest,nv)); |
| 441 | } | ||
| 442 | |||
| 443 |
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104 | if (pep->nconv>0) { |
| 444 |
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104 | PetscCall(BVSetActiveColumns(ctx->V,0,pep->nconv)); |
| 445 |
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104 | PetscCall(BVGetActiveColumns(pep->V,NULL,&nq)); |
| 446 |
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104 | PetscCall(BVSetActiveColumns(pep->V,0,nq)); |
| 447 |
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104 | if (nq>pep->nconv) { |
| 448 |
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104 | PetscCall(BVTensorCompress(ctx->V,pep->nconv)); |
| 449 |
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104 | PetscCall(BVSetActiveColumns(pep->V,0,pep->nconv)); |
| 450 | } | ||
| 451 | } | ||
| 452 |
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104 | PetscCall(STGetTransform(pep->st,&flg)); |
| 453 |
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104 | if (!flg) PetscTryTypeMethod(pep,backtransform); |
| 454 |
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104 | if (pep->sfactor!=1.0) { |
| 455 |
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160 | for (j=0;j<pep->nconv;j++) { |
| 456 | 120 | pep->eigr[j] *= pep->sfactor; | |
| 457 | 120 | pep->eigi[j] *= pep->sfactor; | |
| 458 | } | ||
| 459 | } | ||
| 460 | /* restore original values */ | ||
| 461 |
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104 | if (!flg) { |
| 462 | 88 | pep->target *= pep->sfactor; | |
| 463 |
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88 | PetscCall(STScaleShift(pep->st,pep->sfactor)); |
| 464 | } else { | ||
| 465 |
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16 | PetscCall(STScaleShift(pep->st,sinv?1.0/pep->sfactor:pep->sfactor)); |
| 466 |
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16 | pep->target = (sinv)?pep->target/pep->sfactor:pep->target*pep->sfactor; |
| 467 | } | ||
| 468 |
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104 | if (pep->sfactor!=1.0) PetscCall(RGPopScale(pep->rg)); |
| 469 | |||
| 470 |
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104 | PetscCall(DSTruncate(pep->ds,pep->nconv,PETSC_TRUE)); |
| 471 |
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26 | PetscFunctionReturn(PETSC_SUCCESS); |
| 472 | } | ||
| 473 | |||
| 474 | 162 | static PetscErrorCode PEPSetFromOptions_STOAR(PEP pep,PetscOptionItems PetscOptionsObject) | |
| 475 | { | ||
| 476 | 162 | PetscBool flg,lock,b,f1,f2,f3; | |
| 477 | 162 | PetscInt i,j,k; | |
| 478 | 162 | PetscReal array[2]={0,0}; | |
| 479 | 162 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 480 | |||
| 481 |
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162 | PetscFunctionBegin; |
| 482 |
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162 | PetscOptionsHeadBegin(PetscOptionsObject,"PEP STOAR Options"); |
| 483 | |||
| 484 |
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162 | PetscCall(PetscOptionsBool("-pep_stoar_locking","Choose between locking and non-locking variants","PEPSTOARSetLocking",PETSC_FALSE,&lock,&flg)); |
| 485 |
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162 | if (flg) PetscCall(PEPSTOARSetLocking(pep,lock)); |
| 486 | |||
| 487 | 162 | b = ctx->detect; | |
| 488 |
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162 | PetscCall(PetscOptionsBool("-pep_stoar_detect_zeros","Check zeros during factorizations at interval boundaries","PEPSTOARSetDetectZeros",ctx->detect,&b,&flg)); |
| 489 |
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162 | if (flg) PetscCall(PEPSTOARSetDetectZeros(pep,b)); |
| 490 | |||
| 491 | 162 | i = 1; | |
| 492 | 162 | j = k = PETSC_DECIDE; | |
| 493 |
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162 | PetscCall(PetscOptionsInt("-pep_stoar_nev","Number of eigenvalues to compute in each subsolve (only for spectrum slicing)","PEPSTOARSetDimensions",20,&i,&f1)); |
| 494 |
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162 | PetscCall(PetscOptionsInt("-pep_stoar_ncv","Number of basis vectors in each subsolve (only for spectrum slicing)","PEPSTOARSetDimensions",40,&j,&f2)); |
| 495 |
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162 | PetscCall(PetscOptionsInt("-pep_stoar_mpd","Maximum dimension of projected problem in each subsolve (only for spectrum slicing)","PEPSTOARSetDimensions",40,&k,&f3)); |
| 496 |
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162 | if (f1 || f2 || f3) PetscCall(PEPSTOARSetDimensions(pep,i,j,k)); |
| 497 | |||
| 498 | 162 | k = 2; | |
| 499 |
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162 | PetscCall(PetscOptionsRealArray("-pep_stoar_linearization","Parameters of the linearization","PEPSTOARSetLinearization",array,&k,&flg)); |
| 500 |
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162 | if (flg) PetscCall(PEPSTOARSetLinearization(pep,array[0],array[1])); |
| 501 | |||
| 502 | 162 | b = ctx->checket; | |
| 503 |
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162 | PetscCall(PetscOptionsBool("-pep_stoar_check_eigenvalue_type","Check eigenvalue type during spectrum slicing","PEPSTOARSetCheckEigenvalueType",ctx->checket,&b,&flg)); |
| 504 |
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162 | if (flg) PetscCall(PEPSTOARSetCheckEigenvalueType(pep,b)); |
| 505 | |||
| 506 |
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162 | PetscOptionsHeadEnd(); |
| 507 |
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40 | PetscFunctionReturn(PETSC_SUCCESS); |
| 508 | } | ||
| 509 | |||
| 510 | 16 | static PetscErrorCode PEPSTOARSetLocking_STOAR(PEP pep,PetscBool lock) | |
| 511 | { | ||
| 512 | 16 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 513 | |||
| 514 |
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16 | PetscFunctionBegin; |
| 515 | 16 | ctx->lock = lock; | |
| 516 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 517 | } | ||
| 518 | |||
| 519 | /*@ | ||
| 520 | PEPSTOARSetLocking - Choose between locking and non-locking variants of | ||
| 521 | the STOAR method. | ||
| 522 | |||
| 523 | Logically Collective | ||
| 524 | |||
| 525 | Input Parameters: | ||
| 526 | + pep - the polynomial eigensolver context | ||
| 527 | - lock - `PETSC_TRUE` if the locking variant must be selected | ||
| 528 | |||
| 529 | Options Database Key: | ||
| 530 | . -pep_stoar_locking - sets the locking flag | ||
| 531 | |||
| 532 | Note: | ||
| 533 | The default is to lock converged eigenpairs when the method restarts. | ||
| 534 | This behavior can be changed so that all directions are kept in the | ||
| 535 | working subspace even if already converged to working accuracy (the | ||
| 536 | non-locking variant). | ||
| 537 | |||
| 538 | Level: advanced | ||
| 539 | |||
| 540 | .seealso: [](ch:pep), `PEPSTOAR`, `PEPSTOARGetLocking()` | ||
| 541 | @*/ | ||
| 542 | 16 | PetscErrorCode PEPSTOARSetLocking(PEP pep,PetscBool lock) | |
| 543 | { | ||
| 544 |
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16 | PetscFunctionBegin; |
| 545 |
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16 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 546 |
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16 | PetscValidLogicalCollectiveBool(pep,lock,2); |
| 547 |
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16 | PetscTryMethod(pep,"PEPSTOARSetLocking_C",(PEP,PetscBool),(pep,lock)); |
| 548 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 549 | } | ||
| 550 | |||
| 551 | 16 | static PetscErrorCode PEPSTOARGetLocking_STOAR(PEP pep,PetscBool *lock) | |
| 552 | { | ||
| 553 | 16 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 554 | |||
| 555 |
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16 | PetscFunctionBegin; |
| 556 | 16 | *lock = ctx->lock; | |
| 557 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 558 | } | ||
| 559 | |||
| 560 | /*@ | ||
| 561 | PEPSTOARGetLocking - Gets the locking flag used in the STOAR method. | ||
| 562 | |||
| 563 | Not Collective | ||
| 564 | |||
| 565 | Input Parameter: | ||
| 566 | . pep - the polynomial eigensolver context | ||
| 567 | |||
| 568 | Output Parameter: | ||
| 569 | . lock - the locking flag | ||
| 570 | |||
| 571 | Level: advanced | ||
| 572 | |||
| 573 | .seealso: [](ch:pep), `PEPSTOAR`, `PEPSTOARSetLocking()` | ||
| 574 | @*/ | ||
| 575 | 16 | PetscErrorCode PEPSTOARGetLocking(PEP pep,PetscBool *lock) | |
| 576 | { | ||
| 577 |
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16 | PetscFunctionBegin; |
| 578 |
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16 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 579 |
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16 | PetscAssertPointer(lock,2); |
| 580 |
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16 | PetscUseMethod(pep,"PEPSTOARGetLocking_C",(PEP,PetscBool*),(pep,lock)); |
| 581 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 582 | } | ||
| 583 | |||
| 584 | 16 | static PetscErrorCode PEPSTOARGetInertias_STOAR(PEP pep,PetscInt *n,PetscReal *shifts[],PetscInt *inertias[]) | |
| 585 | { | ||
| 586 | 16 | PetscInt i,numsh; | |
| 587 | 16 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 588 | 16 | PEP_SR sr = ctx->sr; | |
| 589 | |||
| 590 |
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16 | PetscFunctionBegin; |
| 591 |
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16 | PetscCheck(pep->state,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_WRONGSTATE,"Must call PEPSetUp() first"); |
| 592 |
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16 | PetscCheck(ctx->sr,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_WRONGSTATE,"Only available in interval computations, see PEPSetInterval()"); |
| 593 |
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16 | switch (pep->state) { |
| 594 | case PEP_STATE_INITIAL: | ||
| 595 | break; | ||
| 596 | 16 | case PEP_STATE_SETUP: | |
| 597 |
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16 | if (n) *n = 2; |
| 598 |
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16 | if (shifts) { |
| 599 |
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16 | PetscCall(PetscMalloc1(2,shifts)); |
| 600 | 16 | (*shifts)[0] = pep->inta; | |
| 601 | 16 | (*shifts)[1] = pep->intb; | |
| 602 | } | ||
| 603 |
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16 | if (inertias) { |
| 604 |
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16 | PetscCall(PetscMalloc1(2,inertias)); |
| 605 |
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16 | (*inertias)[0] = (sr->dir==1)?sr->inertia0:sr->inertia1; |
| 606 |
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16 | (*inertias)[1] = (sr->dir==1)?sr->inertia1:sr->inertia0; |
| 607 | } | ||
| 608 | break; | ||
| 609 | ✗ | case PEP_STATE_SOLVED: | |
| 610 | case PEP_STATE_EIGENVECTORS: | ||
| 611 | ✗ | numsh = ctx->nshifts; | |
| 612 | ✗ | if (n) *n = numsh; | |
| 613 | ✗ | if (shifts) { | |
| 614 | ✗ | PetscCall(PetscMalloc1(numsh,shifts)); | |
| 615 | ✗ | for (i=0;i<numsh;i++) (*shifts)[i] = ctx->shifts[i]; | |
| 616 | } | ||
| 617 | ✗ | if (inertias) { | |
| 618 | ✗ | PetscCall(PetscMalloc1(numsh,inertias)); | |
| 619 | ✗ | for (i=0;i<numsh;i++) (*inertias)[i] = ctx->inertias[i]; | |
| 620 | } | ||
| 621 | break; | ||
| 622 | } | ||
| 623 |
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4 | PetscFunctionReturn(PETSC_SUCCESS); |
| 624 | } | ||
| 625 | |||
| 626 | /*@C | ||
| 627 | PEPSTOARGetInertias - Gets the values of the shifts and their | ||
| 628 | corresponding inertias in case of doing spectrum slicing for a | ||
| 629 | computational interval. | ||
| 630 | |||
| 631 | Not Collective | ||
| 632 | |||
| 633 | Input Parameter: | ||
| 634 | . pep - the polynomial eigensolver context | ||
| 635 | |||
| 636 | Output Parameters: | ||
| 637 | + n - number of shifts, including the endpoints of the interval | ||
| 638 | . shifts - the values of the shifts used internally in the solver | ||
| 639 | - inertias - the values of the inertia in each shift | ||
| 640 | |||
| 641 | Notes: | ||
| 642 | If called after `PEPSolve()`, all shifts used internally by the solver are | ||
| 643 | returned (including both endpoints and any intermediate ones). If called | ||
| 644 | before `PEPSolve()` and after `PEPSetUp()` then only the information of the | ||
| 645 | endpoints of subintervals is available. | ||
| 646 | |||
| 647 | This function is only available for spectrum slicing runs, that is, when | ||
| 648 | an interval has been given with `PEPSetInterval()` and `STSINVERT` is set. | ||
| 649 | See more details in section [](#sec:qslice). | ||
| 650 | |||
| 651 | The returned arrays should be freed by the user. Can pass `NULL` in any of | ||
| 652 | the two arrays if not required. | ||
| 653 | |||
| 654 | Fortran Notes: | ||
| 655 | The calling sequence from Fortran is | ||
| 656 | .vb | ||
| 657 | PEPSTOARGetInertias(pep,n,shifts,inertias,ierr) | ||
| 658 | PetscInt n | ||
| 659 | PetscReal shifts(*) | ||
| 660 | PetscInt inertias(*) | ||
| 661 | .ve | ||
| 662 | The arrays should be at least of length `n`. The value of `n` can be determined | ||
| 663 | by an initial call | ||
| 664 | .vb | ||
| 665 | PEPSTOARGetInertias(pep,n,PETSC_NULL_REAL_ARRAY,PETSC_NULL_INTEGER_ARRAY,ierr) | ||
| 666 | .ve | ||
| 667 | |||
| 668 | Level: advanced | ||
| 669 | |||
| 670 | .seealso: [](ch:pep), [](#sec:qslice), `PEPSTOAR`, `PEPSetInterval()` | ||
| 671 | @*/ | ||
| 672 | 16 | PetscErrorCode PEPSTOARGetInertias(PEP pep,PetscInt *n,PetscReal *shifts[],PetscInt *inertias[]) PeNS | |
| 673 | { | ||
| 674 |
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16 | PetscFunctionBegin; |
| 675 |
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16 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 676 |
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16 | PetscAssertPointer(n,2); |
| 677 |
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16 | PetscUseMethod(pep,"PEPSTOARGetInertias_C",(PEP,PetscInt*,PetscReal**,PetscInt**),(pep,n,shifts,inertias)); |
| 678 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 679 | } | ||
| 680 | |||
| 681 | 10 | static PetscErrorCode PEPSTOARSetDetectZeros_STOAR(PEP pep,PetscBool detect) | |
| 682 | { | ||
| 683 | 10 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 684 | |||
| 685 |
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10 | PetscFunctionBegin; |
| 686 | 10 | ctx->detect = detect; | |
| 687 | 10 | pep->state = PEP_STATE_INITIAL; | |
| 688 |
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10 | PetscFunctionReturn(PETSC_SUCCESS); |
| 689 | } | ||
| 690 | |||
| 691 | /*@ | ||
| 692 | PEPSTOARSetDetectZeros - Sets a flag to enforce detection of | ||
| 693 | zeros during the factorizations throughout the spectrum slicing computation. | ||
| 694 | |||
| 695 | Logically Collective | ||
| 696 | |||
| 697 | Input Parameters: | ||
| 698 | + pep - the polynomial eigensolver context | ||
| 699 | - detect - check for zeros | ||
| 700 | |||
| 701 | Options Database Key: | ||
| 702 | . -pep_stoar_detect_zeros - toggle the zero detection | ||
| 703 | |||
| 704 | Notes: | ||
| 705 | This flag makes sense only for spectrum slicing runs, that is, when | ||
| 706 | an interval has been given with `PEPSetInterval()` and `STSINVERT` is set. | ||
| 707 | See more details in section [](#sec:qslice). | ||
| 708 | |||
| 709 | A zero in the factorization indicates that a shift coincides with an eigenvalue. | ||
| 710 | |||
| 711 | This flag is turned off by default, and may be necessary in some cases. | ||
| 712 | This feature currently requires an external package for factorizations | ||
| 713 | with support for zero detection, e.g. MUMPS. | ||
| 714 | |||
| 715 | Level: advanced | ||
| 716 | |||
| 717 | .seealso: [](ch:pep), [](#sec:qslice), `PEPSTOAR`, `PEPSetInterval()` | ||
| 718 | @*/ | ||
| 719 | 10 | PetscErrorCode PEPSTOARSetDetectZeros(PEP pep,PetscBool detect) | |
| 720 | { | ||
| 721 |
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10 | PetscFunctionBegin; |
| 722 |
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10 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 723 |
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10 | PetscValidLogicalCollectiveBool(pep,detect,2); |
| 724 |
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10 | PetscTryMethod(pep,"PEPSTOARSetDetectZeros_C",(PEP,PetscBool),(pep,detect)); |
| 725 |
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|
10 | PetscFunctionReturn(PETSC_SUCCESS); |
| 726 | } | ||
| 727 | |||
| 728 | 16 | static PetscErrorCode PEPSTOARGetDetectZeros_STOAR(PEP pep,PetscBool *detect) | |
| 729 | { | ||
| 730 | 16 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 731 | |||
| 732 |
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16 | PetscFunctionBegin; |
| 733 | 16 | *detect = ctx->detect; | |
| 734 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 735 | } | ||
| 736 | |||
| 737 | /*@ | ||
| 738 | PEPSTOARGetDetectZeros - Gets the flag that enforces zero detection | ||
| 739 | in spectrum slicing. | ||
| 740 | |||
| 741 | Not Collective | ||
| 742 | |||
| 743 | Input Parameter: | ||
| 744 | . pep - the polynomial eigensolver context | ||
| 745 | |||
| 746 | Output Parameter: | ||
| 747 | . detect - whether zeros detection is enforced during factorizations | ||
| 748 | |||
| 749 | Level: advanced | ||
| 750 | |||
| 751 | .seealso: [](ch:pep), `PEPSTOAR`, `PEPSTOARSetDetectZeros()` | ||
| 752 | @*/ | ||
| 753 | 16 | PetscErrorCode PEPSTOARGetDetectZeros(PEP pep,PetscBool *detect) | |
| 754 | { | ||
| 755 |
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16 | PetscFunctionBegin; |
| 756 |
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16 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 757 |
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16 | PetscAssertPointer(detect,2); |
| 758 |
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16 | PetscUseMethod(pep,"PEPSTOARGetDetectZeros_C",(PEP,PetscBool*),(pep,detect)); |
| 759 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 760 | } | ||
| 761 | |||
| 762 | 32 | static PetscErrorCode PEPSTOARSetLinearization_STOAR(PEP pep,PetscReal alpha,PetscReal beta) | |
| 763 | { | ||
| 764 | 32 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 765 | |||
| 766 |
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32 | PetscFunctionBegin; |
| 767 |
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32 | PetscCheck(beta!=0.0 || alpha!=0.0,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_WRONG,"Parameters alpha and beta cannot be zero simultaneously"); |
| 768 | 32 | ctx->alpha = alpha; | |
| 769 | 32 | ctx->beta = beta; | |
| 770 |
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32 | PetscFunctionReturn(PETSC_SUCCESS); |
| 771 | } | ||
| 772 | |||
| 773 | /*@ | ||
| 774 | PEPSTOARSetLinearization - Set the coefficients that define the | ||
| 775 | symmetric linearization of a quadratic eigenproblem used in STOAR. | ||
| 776 | |||
| 777 | Logically Collective | ||
| 778 | |||
| 779 | Input Parameters: | ||
| 780 | + pep - the polynomial eigensolver context | ||
| 781 | . alpha - first parameter of the linearization | ||
| 782 | - beta - second parameter of the linearization | ||
| 783 | |||
| 784 | Options Database Key: | ||
| 785 | . -pep_stoar_linearization <alpha,beta> - sets the coefficients | ||
| 786 | |||
| 787 | Notes: | ||
| 788 | See section [](#sec:linearization) for the general expression of | ||
| 789 | the symmetric linearization. | ||
| 790 | |||
| 791 | Cannot pass zero for both `alpha` and `beta`. The default values are | ||
| 792 | `alpha`=1 and `beta`=0. | ||
| 793 | |||
| 794 | Level: advanced | ||
| 795 | |||
| 796 | .seealso: [](ch:pep), [](#sec:linearization), `PEPSTOAR`, `PEPSTOARGetLinearization()` | ||
| 797 | @*/ | ||
| 798 | 32 | PetscErrorCode PEPSTOARSetLinearization(PEP pep,PetscReal alpha,PetscReal beta) | |
| 799 | { | ||
| 800 |
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32 | PetscFunctionBegin; |
| 801 |
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32 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 802 |
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32 | PetscValidLogicalCollectiveReal(pep,alpha,2); |
| 803 |
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32 | PetscValidLogicalCollectiveReal(pep,beta,3); |
| 804 |
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32 | PetscTryMethod(pep,"PEPSTOARSetLinearization_C",(PEP,PetscReal,PetscReal),(pep,alpha,beta)); |
| 805 |
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32 | PetscFunctionReturn(PETSC_SUCCESS); |
| 806 | } | ||
| 807 | |||
| 808 | 8 | static PetscErrorCode PEPSTOARGetLinearization_STOAR(PEP pep,PetscReal *alpha,PetscReal *beta) | |
| 809 | { | ||
| 810 | 8 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 811 | |||
| 812 |
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8 | PetscFunctionBegin; |
| 813 |
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8 | if (alpha) *alpha = ctx->alpha; |
| 814 |
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8 | if (beta) *beta = ctx->beta; |
| 815 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 816 | } | ||
| 817 | |||
| 818 | /*@ | ||
| 819 | PEPSTOARGetLinearization - Returns the coefficients that define | ||
| 820 | the linearization of a quadratic eigenproblem. | ||
| 821 | |||
| 822 | Not Collective | ||
| 823 | |||
| 824 | Input Parameter: | ||
| 825 | . pep - the polynomial eigensolver context | ||
| 826 | |||
| 827 | Output Parameters: | ||
| 828 | + alpha - the first parameter of the linearization | ||
| 829 | - beta - the second parameter of the linearization | ||
| 830 | |||
| 831 | Level: advanced | ||
| 832 | |||
| 833 | .seealso: [](ch:pep), `PEPSTOAR`, `PEPSTOARSetLinearization()` | ||
| 834 | @*/ | ||
| 835 | 8 | PetscErrorCode PEPSTOARGetLinearization(PEP pep,PetscReal *alpha,PetscReal *beta) | |
| 836 | { | ||
| 837 |
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8 | PetscFunctionBegin; |
| 838 |
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8 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 839 |
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8 | PetscUseMethod(pep,"PEPSTOARGetLinearization_C",(PEP,PetscReal*,PetscReal*),(pep,alpha,beta)); |
| 840 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 841 | } | ||
| 842 | |||
| 843 | 24 | static PetscErrorCode PEPSTOARSetDimensions_STOAR(PEP pep,PetscInt nev,PetscInt ncv,PetscInt mpd) | |
| 844 | { | ||
| 845 | 24 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 846 | |||
| 847 |
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24 | PetscFunctionBegin; |
| 848 |
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24 | if (nev != PETSC_CURRENT) { |
| 849 |
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24 | PetscCheck(nev>0,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of nev. Must be > 0"); |
| 850 | 24 | ctx->nev = nev; | |
| 851 | } | ||
| 852 |
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24 | if (ncv == PETSC_DETERMINE) { |
| 853 | 16 | ctx->ncv = PETSC_DETERMINE; | |
| 854 |
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8 | } else if (ncv != PETSC_CURRENT) { |
| 855 |
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8 | PetscCheck(ncv>0,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of ncv. Must be > 0"); |
| 856 | 8 | ctx->ncv = ncv; | |
| 857 | } | ||
| 858 |
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24 | if (mpd == PETSC_DETERMINE) { |
| 859 | 16 | ctx->mpd = PETSC_DETERMINE; | |
| 860 |
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8 | } else if (mpd != PETSC_CURRENT) { |
| 861 |
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8 | PetscCheck(mpd>0,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of mpd. Must be > 0"); |
| 862 | 8 | ctx->mpd = mpd; | |
| 863 | } | ||
| 864 | 24 | pep->state = PEP_STATE_INITIAL; | |
| 865 |
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24 | PetscFunctionReturn(PETSC_SUCCESS); |
| 866 | } | ||
| 867 | |||
| 868 | /*@ | ||
| 869 | PEPSTOARSetDimensions - Sets the dimensions used for each subsolve | ||
| 870 | step in case of doing spectrum slicing for a computational interval. | ||
| 871 | |||
| 872 | Logically Collective | ||
| 873 | |||
| 874 | Input Parameters: | ||
| 875 | + pep - the polynomial eigensolver context | ||
| 876 | . nev - number of eigenvalues to compute | ||
| 877 | . ncv - the maximum dimension of the subspace to be used by the subsolve | ||
| 878 | - mpd - the maximum dimension allowed for the projected problem | ||
| 879 | |||
| 880 | Options Database Keys: | ||
| 881 | + -pep_stoar_nev \<nev\> - sets the number of eigenvalues | ||
| 882 | . -pep_stoar_ncv \<ncv\> - sets the dimension of the subspace | ||
| 883 | - -pep_stoar_mpd \<mpd\> - sets the maximum projected dimension | ||
| 884 | |||
| 885 | Notes: | ||
| 886 | These parameters are relevant only for spectrum slicing runs, that is, when | ||
| 887 | an interval has been given with `PEPSetInterval()` and `STSINVERT` is set. | ||
| 888 | See more details in section [](#sec:qslice). | ||
| 889 | |||
| 890 | The meaning of the parameters is the same as in `PEPSetDimensions()`, but | ||
| 891 | the ones here apply to every subsolve done by the child `PEP` object. | ||
| 892 | |||
| 893 | Use `PETSC_DETERMINE` for `ncv` and `mpd` to assign a default value. For any | ||
| 894 | of the arguments, use `PETSC_CURRENT` to preserve the current value. | ||
| 895 | |||
| 896 | Level: advanced | ||
| 897 | |||
| 898 | .seealso: [](ch:pep), [](#sec:qslice), `PEPSTOAR`, `PEPSTOARGetDimensions()`, `PEPSetDimensions()`, `PEPSetInterval()` | ||
| 899 | @*/ | ||
| 900 | 24 | PetscErrorCode PEPSTOARSetDimensions(PEP pep,PetscInt nev,PetscInt ncv,PetscInt mpd) | |
| 901 | { | ||
| 902 |
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24 | PetscFunctionBegin; |
| 903 |
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24 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 904 |
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|
24 | PetscValidLogicalCollectiveInt(pep,nev,2); |
| 905 |
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24 | PetscValidLogicalCollectiveInt(pep,ncv,3); |
| 906 |
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24 | PetscValidLogicalCollectiveInt(pep,mpd,4); |
| 907 |
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24 | PetscTryMethod(pep,"PEPSTOARSetDimensions_C",(PEP,PetscInt,PetscInt,PetscInt),(pep,nev,ncv,mpd)); |
| 908 |
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24 | PetscFunctionReturn(PETSC_SUCCESS); |
| 909 | } | ||
| 910 | |||
| 911 | 16 | static PetscErrorCode PEPSTOARGetDimensions_STOAR(PEP pep,PetscInt *nev,PetscInt *ncv,PetscInt *mpd) | |
| 912 | { | ||
| 913 | 16 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 914 | |||
| 915 |
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16 | PetscFunctionBegin; |
| 916 |
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16 | if (nev) *nev = ctx->nev; |
| 917 |
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16 | if (ncv) *ncv = ctx->ncv; |
| 918 |
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16 | if (mpd) *mpd = ctx->mpd; |
| 919 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 920 | } | ||
| 921 | |||
| 922 | /*@ | ||
| 923 | PEPSTOARGetDimensions - Gets the dimensions used for each subsolve | ||
| 924 | step in case of doing spectrum slicing for a computational interval. | ||
| 925 | |||
| 926 | Not Collective | ||
| 927 | |||
| 928 | Input Parameter: | ||
| 929 | . pep - the polynomial eigensolver context | ||
| 930 | |||
| 931 | Output Parameters: | ||
| 932 | + nev - number of eigenvalues to compute | ||
| 933 | . ncv - the maximum dimension of the subspace to be used by the subsolve | ||
| 934 | - mpd - the maximum dimension allowed for the projected problem | ||
| 935 | |||
| 936 | Level: advanced | ||
| 937 | |||
| 938 | .seealso: [](ch:pep), `PEPSTOAR`, `PEPSTOARSetDimensions()` | ||
| 939 | @*/ | ||
| 940 | 16 | PetscErrorCode PEPSTOARGetDimensions(PEP pep,PetscInt *nev,PetscInt *ncv,PetscInt *mpd) | |
| 941 | { | ||
| 942 |
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16 | PetscFunctionBegin; |
| 943 |
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16 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 944 |
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16 | PetscUseMethod(pep,"PEPSTOARGetDimensions_C",(PEP,PetscInt*,PetscInt*,PetscInt*),(pep,nev,ncv,mpd)); |
| 945 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 946 | } | ||
| 947 | |||
| 948 | 8 | static PetscErrorCode PEPSTOARSetCheckEigenvalueType_STOAR(PEP pep,PetscBool checket) | |
| 949 | { | ||
| 950 | 8 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 951 | |||
| 952 |
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8 | PetscFunctionBegin; |
| 953 | 8 | ctx->checket = checket; | |
| 954 | 8 | pep->state = PEP_STATE_INITIAL; | |
| 955 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 956 | } | ||
| 957 | |||
| 958 | /*@ | ||
| 959 | PEPSTOARSetCheckEigenvalueType - Sets a flag to check that all the eigenvalues | ||
| 960 | obtained throughout the spectrum slicing computation have the same definite type. | ||
| 961 | |||
| 962 | Logically Collective | ||
| 963 | |||
| 964 | Input Parameters: | ||
| 965 | + pep - the polynomial eigensolver context | ||
| 966 | - checket - check eigenvalue type | ||
| 967 | |||
| 968 | Options Database Key: | ||
| 969 | . -pep_stoar_check_eigenvalue_type - toggles the check of eigenvalue type | ||
| 970 | |||
| 971 | Notes: | ||
| 972 | This option is relevant only for spectrum slicing computations, but it is | ||
| 973 | ignored if the problem type is `PEP_HYPERBOLIC`. | ||
| 974 | |||
| 975 | This flag is turned on by default, to guarantee that the computed eigenvalues | ||
| 976 | have the same type (otherwise the computed solution might be wrong). But since | ||
| 977 | the check is computationally quite expensive, the check may be turned off if | ||
| 978 | the user knows for sure that all eigenvalues in the requested interval have | ||
| 979 | the same type. | ||
| 980 | |||
| 981 | Level: advanced | ||
| 982 | |||
| 983 | .seealso: [](ch:pep), `PEPSTOAR`, `PEPSetProblemType()`, `PEPSetInterval()` | ||
| 984 | @*/ | ||
| 985 | 8 | PetscErrorCode PEPSTOARSetCheckEigenvalueType(PEP pep,PetscBool checket) | |
| 986 | { | ||
| 987 |
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8 | PetscFunctionBegin; |
| 988 |
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8 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 989 |
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8 | PetscValidLogicalCollectiveBool(pep,checket,2); |
| 990 |
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8 | PetscTryMethod(pep,"PEPSTOARSetCheckEigenvalueType_C",(PEP,PetscBool),(pep,checket)); |
| 991 |
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8 | PetscFunctionReturn(PETSC_SUCCESS); |
| 992 | } | ||
| 993 | |||
| 994 | 16 | static PetscErrorCode PEPSTOARGetCheckEigenvalueType_STOAR(PEP pep,PetscBool *checket) | |
| 995 | { | ||
| 996 | 16 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 997 | |||
| 998 |
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16 | PetscFunctionBegin; |
| 999 | 16 | *checket = ctx->checket; | |
| 1000 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 1001 | } | ||
| 1002 | |||
| 1003 | /*@ | ||
| 1004 | PEPSTOARGetCheckEigenvalueType - Gets the flag for the eigenvalue type | ||
| 1005 | check in spectrum slicing. | ||
| 1006 | |||
| 1007 | Not Collective | ||
| 1008 | |||
| 1009 | Input Parameter: | ||
| 1010 | . pep - the polynomial eigensolver context | ||
| 1011 | |||
| 1012 | Output Parameter: | ||
| 1013 | . checket - whether eigenvalue type must be checked during spectrum slcing | ||
| 1014 | |||
| 1015 | Level: advanced | ||
| 1016 | |||
| 1017 | .seealso: [](ch:pep), `PEPSTOAR`, `PEPSTOARSetCheckEigenvalueType()` | ||
| 1018 | @*/ | ||
| 1019 | 16 | PetscErrorCode PEPSTOARGetCheckEigenvalueType(PEP pep,PetscBool *checket) | |
| 1020 | { | ||
| 1021 |
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16 | PetscFunctionBegin; |
| 1022 |
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16 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 1023 |
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16 | PetscAssertPointer(checket,2); |
| 1024 |
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16 | PetscUseMethod(pep,"PEPSTOARGetCheckEigenvalueType_C",(PEP,PetscBool*),(pep,checket)); |
| 1025 |
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16 | PetscFunctionReturn(PETSC_SUCCESS); |
| 1026 | } | ||
| 1027 | |||
| 1028 | ✗ | static PetscErrorCode PEPView_STOAR(PEP pep,PetscViewer viewer) | |
| 1029 | { | ||
| 1030 | ✗ | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 1031 | ✗ | PetscBool isascii; | |
| 1032 | |||
| 1033 | ✗ | PetscFunctionBegin; | |
| 1034 | ✗ | PetscCall(PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii)); | |
| 1035 | ✗ | if (isascii) { | |
| 1036 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer," using the %slocking variant\n",ctx->lock?"":"non-")); | |
| 1037 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer," linearization parameters: alpha=%g beta=%g\n",(double)ctx->alpha,(double)ctx->beta)); | |
| 1038 | ✗ | if (pep->which==PEP_ALL && !ctx->hyperbolic) PetscCall(PetscViewerASCIIPrintf(viewer," checking eigenvalue type: %s\n",ctx->checket?"enabled":"disabled")); | |
| 1039 | } | ||
| 1040 | ✗ | PetscFunctionReturn(PETSC_SUCCESS); | |
| 1041 | } | ||
| 1042 | |||
| 1043 | 170 | static PetscErrorCode PEPReset_STOAR(PEP pep) | |
| 1044 | { | ||
| 1045 |
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170 | PetscFunctionBegin; |
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170 | if (pep->which==PEP_ALL) PetscCall(PEPReset_STOAR_QSlice(pep)); |
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42 | PetscFunctionReturn(PETSC_SUCCESS); |
| 1048 | } | ||
| 1049 | |||
| 1050 | 162 | static PetscErrorCode PEPDestroy_STOAR(PEP pep) | |
| 1051 | { | ||
| 1052 | 162 | PEP_STOAR *ctx = (PEP_STOAR*)pep->data; | |
| 1053 | |||
| 1054 |
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162 | PetscFunctionBegin; |
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162 | PetscCall(BVDestroy(&ctx->V)); |
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162 | PetscCall(PetscFree(pep->data)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetLocking_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetLocking_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetDetectZeros_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetDetectZeros_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetInertias_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetDimensions_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetDimensions_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetLinearization_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetLinearization_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetCheckEigenvalueType_C",NULL)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetCheckEigenvalueType_C",NULL)); |
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40 | PetscFunctionReturn(PETSC_SUCCESS); |
| 1069 | } | ||
| 1070 | |||
| 1071 | /*MC | ||
| 1072 | PEPSTOAR - PEPSTOAR = "stoar" - A symmetric variant of TOAR. | ||
| 1073 | |||
| 1074 | Notes: | ||
| 1075 | This solver is available for quadratic eigenproblems only. | ||
| 1076 | |||
| 1077 | It is an alternative to `PEPTOAR` in the case of `PEP_HERMITIAN` | ||
| 1078 | problems. It tries to exploit the symmetry of the matrices by working | ||
| 1079 | with a special linearization where the matrices are Hermitian. However, | ||
| 1080 | this pencil in indefinite, so it uses a pseudo-Lanczos recurrence that | ||
| 1081 | may become numerically unstable. The method is described in {cite:p}`Cam16c`. | ||
| 1082 | |||
| 1083 | The solver incorporates support for interval computation with `PEPSetInterval()`. | ||
| 1084 | Then it will proceed with a spectrum slicing scheme as described in | ||
| 1085 | {cite:p}`Cam20b`. This is particularly useful in the case of `PEP_HYPERBOLIC` | ||
| 1086 | problems. | ||
| 1087 | |||
| 1088 | Level: beginner | ||
| 1089 | |||
| 1090 | .seealso: [](ch:pep), `PEP`, `PEPType`, `PEPSetType()` | ||
| 1091 | M*/ | ||
| 1092 | 162 | SLEPC_EXTERN PetscErrorCode PEPCreate_STOAR(PEP pep) | |
| 1093 | { | ||
| 1094 | 162 | PEP_STOAR *ctx; | |
| 1095 | |||
| 1096 |
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162 | PetscFunctionBegin; |
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162 | PetscCall(PetscNew(&ctx)); |
| 1098 | 162 | pep->data = (void*)ctx; | |
| 1099 | |||
| 1100 | 162 | pep->lineariz = PETSC_TRUE; | |
| 1101 | 162 | ctx->lock = PETSC_TRUE; | |
| 1102 | 162 | ctx->nev = 1; | |
| 1103 | 162 | ctx->ncv = PETSC_DETERMINE; | |
| 1104 | 162 | ctx->mpd = PETSC_DETERMINE; | |
| 1105 | 162 | ctx->alpha = 1.0; | |
| 1106 | 162 | ctx->beta = 0.0; | |
| 1107 | 162 | ctx->checket = PETSC_TRUE; | |
| 1108 | |||
| 1109 | 162 | pep->ops->setup = PEPSetUp_STOAR; | |
| 1110 | 162 | pep->ops->setfromoptions = PEPSetFromOptions_STOAR; | |
| 1111 | 162 | pep->ops->destroy = PEPDestroy_STOAR; | |
| 1112 | 162 | pep->ops->view = PEPView_STOAR; | |
| 1113 | 162 | pep->ops->backtransform = PEPBackTransform_Default; | |
| 1114 | 162 | pep->ops->computevectors = PEPComputeVectors_Default; | |
| 1115 | 162 | pep->ops->extractvectors = PEPExtractVectors_TOAR; | |
| 1116 | 162 | pep->ops->reset = PEPReset_STOAR; | |
| 1117 | |||
| 1118 |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetLocking_C",PEPSTOARSetLocking_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetLocking_C",PEPSTOARGetLocking_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetDetectZeros_C",PEPSTOARSetDetectZeros_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetDetectZeros_C",PEPSTOARGetDetectZeros_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetInertias_C",PEPSTOARGetInertias_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetDimensions_C",PEPSTOARGetDimensions_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetDimensions_C",PEPSTOARSetDimensions_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetLinearization_C",PEPSTOARSetLinearization_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetLinearization_C",PEPSTOARGetLinearization_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARSetCheckEigenvalueType_C",PEPSTOARSetCheckEigenvalueType_STOAR)); |
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162 | PetscCall(PetscObjectComposeFunction((PetscObject)pep,"PEPSTOARGetCheckEigenvalueType_C",PEPSTOARGetCheckEigenvalueType_STOAR)); |
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40 | PetscFunctionReturn(PETSC_SUCCESS); |
| 1130 | } | ||
| 1131 |