| 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 | Simple default routines for common PEP operations | ||
| 12 | */ | ||
| 13 | |||
| 14 | #include <slepc/private/pepimpl.h> /*I "slepcpep.h" I*/ | ||
| 15 | |||
| 16 | /*@ | ||
| 17 | PEPSetWorkVecs - Sets a number of work vectors into a PEP object. | ||
| 18 | |||
| 19 | Collective | ||
| 20 | |||
| 21 | Input Parameters: | ||
| 22 | + pep - polynomial eigensolver context | ||
| 23 | - nw - number of work vectors to allocate | ||
| 24 | |||
| 25 | Developer Notes: | ||
| 26 | This is SLEPC_EXTERN because it may be required by user plugin PEP | ||
| 27 | implementations. | ||
| 28 | |||
| 29 | Level: developer | ||
| 30 | |||
| 31 | .seealso: PEPSetUp() | ||
| 32 | @*/ | ||
| 33 | 12135 | PetscErrorCode PEPSetWorkVecs(PEP pep,PetscInt nw) | |
| 34 | { | ||
| 35 | 12135 | Vec t; | |
| 36 | |||
| 37 |
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12135 | PetscFunctionBegin; |
| 38 |
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12135 | PetscValidHeaderSpecific(pep,PEP_CLASSID,1); |
| 39 |
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12135 | PetscValidLogicalCollectiveInt(pep,nw,2); |
| 40 |
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12135 | PetscCheck(nw>0,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_OUTOFRANGE,"nw must be > 0: nw = %" PetscInt_FMT,nw); |
| 41 |
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12135 | if (pep->nwork < nw) { |
| 42 |
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2597 | PetscCall(VecDestroyVecs(pep->nwork,&pep->work)); |
| 43 | 2597 | pep->nwork = nw; | |
| 44 |
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2597 | PetscCall(BVGetColumn(pep->V,0,&t)); |
| 45 |
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2597 | PetscCall(VecDuplicateVecs(t,nw,&pep->work)); |
| 46 |
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2597 | PetscCall(BVRestoreColumn(pep->V,0,&t)); |
| 47 | } | ||
| 48 |
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2378 | PetscFunctionReturn(PETSC_SUCCESS); |
| 49 | } | ||
| 50 | |||
| 51 | /* | ||
| 52 | PEPConvergedRelative - Checks convergence relative to the eigenvalue. | ||
| 53 | */ | ||
| 54 | 26849 | PetscErrorCode PEPConvergedRelative(PEP pep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx) | |
| 55 | { | ||
| 56 | 26849 | PetscReal w; | |
| 57 | |||
| 58 |
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26849 | PetscFunctionBegin; |
| 59 | 26849 | w = SlepcAbsEigenvalue(eigr,eigi); | |
| 60 |
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26849 | *errest = (w!=0.0)? res/w: PETSC_MAX_REAL; |
| 61 |
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26849 | PetscFunctionReturn(PETSC_SUCCESS); |
| 62 | } | ||
| 63 | |||
| 64 | /* | ||
| 65 | PEPConvergedNorm - Checks convergence relative to the matrix norms. | ||
| 66 | */ | ||
| 67 | 145 | PetscErrorCode PEPConvergedNorm(PEP pep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx) | |
| 68 | { | ||
| 69 | 145 | PetscReal w=0.0,t; | |
| 70 | 145 | PetscInt j; | |
| 71 | 145 | PetscBool flg; | |
| 72 | |||
| 73 |
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145 | PetscFunctionBegin; |
| 74 | /* initialization of matrix norms */ | ||
| 75 |
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145 | if (!pep->nrma[pep->nmat-1]) { |
| 76 |
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60 | for (j=0;j<pep->nmat;j++) { |
| 77 |
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45 | PetscCall(MatHasOperation(pep->A[j],MATOP_NORM,&flg)); |
| 78 |
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45 | PetscCheck(flg,PetscObjectComm((PetscObject)pep),PETSC_ERR_ARG_WRONG,"The convergence test related to the matrix norms requires a matrix norm operation"); |
| 79 |
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45 | PetscCall(MatNorm(pep->A[j],NORM_INFINITY,&pep->nrma[j])); |
| 80 | } | ||
| 81 | } | ||
| 82 | 145 | t = SlepcAbsEigenvalue(eigr,eigi); | |
| 83 |
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580 | for (j=pep->nmat-1;j>=0;j--) { |
| 84 | 435 | w = w*t+pep->nrma[j]; | |
| 85 | } | ||
| 86 | 145 | *errest = res/w; | |
| 87 |
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145 | PetscFunctionReturn(PETSC_SUCCESS); |
| 88 | } | ||
| 89 | |||
| 90 | /* | ||
| 91 | PEPSetWhichEigenpairs_Default - Sets the default value for which, | ||
| 92 | depending on the ST. | ||
| 93 | */ | ||
| 94 | 768 | PetscErrorCode PEPSetWhichEigenpairs_Default(PEP pep) | |
| 95 | { | ||
| 96 | 768 | PetscBool target; | |
| 97 | |||
| 98 |
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768 | PetscFunctionBegin; |
| 99 |
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768 | PetscCall(PetscObjectTypeCompare((PetscObject)pep->st,STSINVERT,&target)); |
| 100 |
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768 | if (target) pep->which = PEP_TARGET_MAGNITUDE; |
| 101 | 588 | else pep->which = PEP_LARGEST_MAGNITUDE; | |
| 102 |
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149 | PetscFunctionReturn(PETSC_SUCCESS); |
| 103 | } | ||
| 104 | |||
| 105 | /* | ||
| 106 | PEPConvergedAbsolute - Checks convergence absolutely. | ||
| 107 | */ | ||
| 108 | 351 | PetscErrorCode PEPConvergedAbsolute(PEP pep,PetscScalar eigr,PetscScalar eigi,PetscReal res,PetscReal *errest,void *ctx) | |
| 109 | { | ||
| 110 |
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351 | PetscFunctionBegin; |
| 111 | 351 | *errest = res; | |
| 112 |
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351 | PetscFunctionReturn(PETSC_SUCCESS); |
| 113 | } | ||
| 114 | |||
| 115 | /*@C | ||
| 116 | PEPStoppingBasic - Default routine to determine whether the outer eigensolver | ||
| 117 | iteration must be stopped. | ||
| 118 | |||
| 119 | Collective | ||
| 120 | |||
| 121 | Input Parameters: | ||
| 122 | + pep - eigensolver context obtained from PEPCreate() | ||
| 123 | . its - current number of iterations | ||
| 124 | . max_it - maximum number of iterations | ||
| 125 | . nconv - number of currently converged eigenpairs | ||
| 126 | . nev - number of requested eigenpairs | ||
| 127 | - ctx - context (not used here) | ||
| 128 | |||
| 129 | Output Parameter: | ||
| 130 | . reason - result of the stopping test | ||
| 131 | |||
| 132 | Notes: | ||
| 133 | A positive value of reason indicates that the iteration has finished successfully | ||
| 134 | (converged), and a negative value indicates an error condition (diverged). If | ||
| 135 | the iteration needs to be continued, reason must be set to PEP_CONVERGED_ITERATING | ||
| 136 | (zero). | ||
| 137 | |||
| 138 | PEPStoppingBasic() will stop if all requested eigenvalues are converged, or if | ||
| 139 | the maximum number of iterations has been reached. | ||
| 140 | |||
| 141 | Use PEPSetStoppingTest() to provide your own test instead of using this one. | ||
| 142 | |||
| 143 | Level: advanced | ||
| 144 | |||
| 145 | .seealso: PEPSetStoppingTest(), PEPConvergedReason, PEPGetConvergedReason() | ||
| 146 | @*/ | ||
| 147 | 16404 | PetscErrorCode PEPStoppingBasic(PEP pep,PetscInt its,PetscInt max_it,PetscInt nconv,PetscInt nev,PEPConvergedReason *reason,void *ctx) | |
| 148 | { | ||
| 149 |
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16404 | PetscFunctionBegin; |
| 150 | 16404 | *reason = PEP_CONVERGED_ITERATING; | |
| 151 |
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16404 | if (nconv >= nev) { |
| 152 |
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1625 | PetscCall(PetscInfo(pep,"Polynomial eigensolver finished successfully: %" PetscInt_FMT " eigenpairs converged at iteration %" PetscInt_FMT "\n",nconv,its)); |
| 153 | 1625 | *reason = PEP_CONVERGED_TOL; | |
| 154 |
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14779 | } else if (its >= max_it) { |
| 155 | 10 | *reason = PEP_DIVERGED_ITS; | |
| 156 |
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10 | PetscCall(PetscInfo(pep,"Polynomial eigensolver iteration reached maximum number of iterations (%" PetscInt_FMT ")\n",its)); |
| 157 | } | ||
| 158 |
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3228 | PetscFunctionReturn(PETSC_SUCCESS); |
| 159 | } | ||
| 160 | |||
| 161 | 1183 | PetscErrorCode PEPBackTransform_Default(PEP pep) | |
| 162 | { | ||
| 163 |
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1183 | PetscFunctionBegin; |
| 164 |
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1183 | PetscCall(STBackTransform(pep->st,pep->nconv,pep->eigr,pep->eigi)); |
| 165 |
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229 | PetscFunctionReturn(PETSC_SUCCESS); |
| 166 | } | ||
| 167 | |||
| 168 | 1756 | PetscErrorCode PEPComputeVectors_Default(PEP pep) | |
| 169 | { | ||
| 170 | 1756 | PetscInt i; | |
| 171 | 1756 | Vec v; | |
| 172 | |||
| 173 |
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1756 | PetscFunctionBegin; |
| 174 |
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1756 | PetscCall(PEPExtractVectors(pep)); |
| 175 | |||
| 176 | /* Fix eigenvectors if balancing was used */ | ||
| 177 |
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1756 | if ((pep->scale==PEP_SCALE_DIAGONAL || pep->scale==PEP_SCALE_BOTH) && pep->Dr && (pep->refine!=PEP_REFINE_MULTIPLE)) { |
| 178 |
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972 | for (i=0;i<pep->nconv;i++) { |
| 179 |
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828 | PetscCall(BVGetColumn(pep->V,i,&v)); |
| 180 |
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828 | PetscCall(VecPointwiseMult(v,v,pep->Dr)); |
| 181 |
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828 | PetscCall(BVRestoreColumn(pep->V,i,&v)); |
| 182 | } | ||
| 183 | } | ||
| 184 | |||
| 185 | /* normalization */ | ||
| 186 |
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1756 | PetscCall(BVNormalize(pep->V,pep->eigi)); |
| 187 |
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342 | PetscFunctionReturn(PETSC_SUCCESS); |
| 188 | } | ||
| 189 | |||
| 190 | /* | ||
| 191 | PEPBuildDiagonalScaling - compute two diagonal matrices to be applied for balancing | ||
| 192 | in polynomial eigenproblems. | ||
| 193 | */ | ||
| 194 | 184 | PetscErrorCode PEPBuildDiagonalScaling(PEP pep) | |
| 195 | { | ||
| 196 | 184 | PetscInt it,i,j,k,nmat,nr,e,nz,lst,lend,nc=0,*cols,emax,emin,emaxl,eminl; | |
| 197 | 184 | const PetscInt *cidx,*ridx; | |
| 198 | 184 | Mat M,*T,A; | |
| 199 | 184 | PetscMPIInt n; | |
| 200 | 184 | PetscBool cont=PETSC_TRUE,flg=PETSC_FALSE; | |
| 201 | 184 | PetscScalar *array,*Dr,*Dl,t; | |
| 202 | 184 | PetscReal l2,d,*rsum,*aux,*csum,w=1.0; | |
| 203 | 184 | MatStructure str; | |
| 204 | 184 | MatInfo info; | |
| 205 | |||
| 206 |
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184 | PetscFunctionBegin; |
| 207 | 184 | l2 = 2*PetscLogReal(2.0); | |
| 208 | 184 | nmat = pep->nmat; | |
| 209 |
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184 | PetscCall(PetscMPIIntCast(pep->n,&n)); |
| 210 |
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184 | PetscCall(STGetMatStructure(pep->st,&str)); |
| 211 |
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184 | PetscCall(PetscMalloc1(nmat,&T)); |
| 212 |
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736 | for (k=0;k<nmat;k++) PetscCall(STGetMatrixTransformed(pep->st,k,&T[k])); |
| 213 | /* Form local auxiliary matrix M */ | ||
| 214 |
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184 | PetscCall(PetscObjectBaseTypeCompareAny((PetscObject)T[0],&cont,MATMPIAIJ,MATSEQAIJ,"")); |
| 215 |
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184 | PetscCheck(cont,PetscObjectComm((PetscObject)T[0]),PETSC_ERR_SUP,"Only for MPIAIJ or SEQAIJ matrix types"); |
| 216 |
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184 | PetscCall(PetscObjectBaseTypeCompare((PetscObject)T[0],MATMPIAIJ,&cont)); |
| 217 |
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184 | if (cont) { |
| 218 |
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120 | PetscCall(MatMPIAIJGetLocalMat(T[0],MAT_INITIAL_MATRIX,&M)); |
| 219 | flg = PETSC_TRUE; | ||
| 220 |
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64 | } else PetscCall(MatDuplicate(T[0],MAT_COPY_VALUES,&M)); |
| 221 |
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184 | PetscCall(MatGetInfo(M,MAT_LOCAL,&info)); |
| 222 | 184 | nz = (PetscInt)info.nz_used; | |
| 223 |
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184 | PetscCall(MatSeqAIJGetArray(M,&array)); |
| 224 |
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8284 | for (i=0;i<nz;i++) { |
| 225 | 8100 | t = PetscAbsScalar(array[i]); | |
| 226 | 8100 | array[i] = t*t; | |
| 227 | } | ||
| 228 |
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184 | PetscCall(MatSeqAIJRestoreArray(M,&array)); |
| 229 |
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552 | for (k=1;k<nmat;k++) { |
| 230 |
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368 | if (flg) PetscCall(MatMPIAIJGetLocalMat(T[k],MAT_INITIAL_MATRIX,&A)); |
| 231 | else { | ||
| 232 |
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128 | if (str==SAME_NONZERO_PATTERN) PetscCall(MatCopy(T[k],A,SAME_NONZERO_PATTERN)); |
| 233 |
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128 | else PetscCall(MatDuplicate(T[k],MAT_COPY_VALUES,&A)); |
| 234 | } | ||
| 235 |
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368 | PetscCall(MatGetInfo(A,MAT_LOCAL,&info)); |
| 236 | 368 | nz = (PetscInt)info.nz_used; | |
| 237 |
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368 | PetscCall(MatSeqAIJGetArray(A,&array)); |
| 238 |
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12444 | for (i=0;i<nz;i++) { |
| 239 | 12076 | t = PetscAbsScalar(array[i]); | |
| 240 | 12076 | array[i] = t*t; | |
| 241 | } | ||
| 242 |
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368 | PetscCall(MatSeqAIJRestoreArray(A,&array)); |
| 243 | 368 | w *= pep->slambda*pep->slambda*pep->sfactor; | |
| 244 |
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368 | PetscCall(MatAXPY(M,w,A,str)); |
| 245 |
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368 | if (flg || str!=SAME_NONZERO_PATTERN || k==nmat-2) PetscCall(MatDestroy(&A)); |
| 246 | } | ||
| 247 |
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184 | PetscCall(MatGetRowIJ(M,0,PETSC_FALSE,PETSC_FALSE,&nr,&ridx,&cidx,&cont)); |
| 248 |
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184 | PetscCheck(cont,PetscObjectComm((PetscObject)T[0]),PETSC_ERR_SUP,"It is not possible to compute scaling diagonals for these PEP matrices"); |
| 249 |
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184 | PetscCall(MatGetInfo(M,MAT_LOCAL,&info)); |
| 250 | 184 | nz = (PetscInt)info.nz_used; | |
| 251 |
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184 | PetscCall(VecGetOwnershipRange(pep->Dl,&lst,&lend)); |
| 252 |
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184 | PetscCall(PetscMalloc4(nr,&rsum,pep->n,&csum,pep->n,&aux,PetscMin(pep->n-lend+lst,nz),&cols)); |
| 253 |
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184 | PetscCall(VecSet(pep->Dr,1.0)); |
| 254 |
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184 | PetscCall(VecSet(pep->Dl,1.0)); |
| 255 |
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184 | PetscCall(VecGetArray(pep->Dl,&Dl)); |
| 256 |
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184 | PetscCall(VecGetArray(pep->Dr,&Dr)); |
| 257 |
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184 | PetscCall(MatSeqAIJGetArray(M,&array)); |
| 258 |
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184 | PetscCall(PetscArrayzero(aux,pep->n)); |
| 259 |
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8744 | for (j=0;j<nz;j++) { |
| 260 | /* Search non-zero columns outsize lst-lend */ | ||
| 261 |
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|
8560 | if (aux[cidx[j]]==0 && (cidx[j]<lst || lend<=cidx[j])) cols[nc++] = cidx[j]; |
| 262 | /* Local column sums */ | ||
| 263 | 8560 | aux[cidx[j]] += PetscAbsScalar(array[j]); | |
| 264 | } | ||
| 265 |
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552 | for (it=0;it<pep->sits && cont;it++) { |
| 266 | 368 | emaxl = 0; eminl = 0; | |
| 267 | /* Column sum */ | ||
| 268 |
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368 | if (it>0) { /* it=0 has been already done*/ |
| 269 |
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184 | PetscCall(MatSeqAIJGetArray(M,&array)); |
| 270 |
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184 | PetscCall(PetscArrayzero(aux,pep->n)); |
| 271 |
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8744 | for (j=0;j<nz;j++) aux[cidx[j]] += PetscAbsScalar(array[j]); |
| 272 |
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184 | PetscCall(MatSeqAIJRestoreArray(M,&array)); |
| 273 | } | ||
| 274 |
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368 | PetscCallMPI(MPIU_Allreduce(aux,csum,n,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)pep->Dr))); |
| 275 | /* Update Dr */ | ||
| 276 |
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6480 | for (j=lst;j<lend;j++) { |
| 277 | 6112 | d = PetscLogReal(csum[j])/l2; | |
| 278 |
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6112 | e = -(PetscInt)((d < 0)?(d-0.5):(d+0.5)); |
| 279 | 6112 | d = PetscPowReal(2.0,e); | |
| 280 | 6112 | Dr[j-lst] *= d; | |
| 281 | 6112 | aux[j] = d*d; | |
| 282 | 6112 | emaxl = PetscMax(emaxl,e); | |
| 283 | 6112 | eminl = PetscMin(eminl,e); | |
| 284 | } | ||
| 285 |
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648 | for (j=0;j<nc;j++) { |
| 286 | 280 | d = PetscLogReal(csum[cols[j]])/l2; | |
| 287 |
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280 | e = -(PetscInt)((d < 0)?(d-0.5):(d+0.5)); |
| 288 | 280 | d = PetscPowReal(2.0,e); | |
| 289 | 280 | aux[cols[j]] = d*d; | |
| 290 | 280 | emaxl = PetscMax(emaxl,e); | |
| 291 | 280 | eminl = PetscMin(eminl,e); | |
| 292 | } | ||
| 293 | /* Scale M */ | ||
| 294 |
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368 | PetscCall(MatSeqAIJGetArray(M,&array)); |
| 295 |
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17488 | for (j=0;j<nz;j++) { |
| 296 | 17120 | array[j] *= aux[cidx[j]]; | |
| 297 | } | ||
| 298 |
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368 | PetscCall(MatSeqAIJRestoreArray(M,&array)); |
| 299 | /* Row sum */ | ||
| 300 |
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368 | PetscCall(PetscArrayzero(rsum,nr)); |
| 301 |
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368 | PetscCall(MatSeqAIJGetArray(M,&array)); |
| 302 |
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6480 | for (i=0;i<nr;i++) { |
| 303 |
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23232 | for (j=ridx[i];j<ridx[i+1];j++) rsum[i] += PetscAbsScalar(array[j]); |
| 304 | /* Update Dl */ | ||
| 305 | 6112 | d = PetscLogReal(rsum[i])/l2; | |
| 306 |
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6112 | e = -(PetscInt)((d < 0)?(d-0.5):(d+0.5)); |
| 307 | 6112 | d = PetscPowReal(2.0,e); | |
| 308 | 6112 | Dl[i] *= d; | |
| 309 | /* Scale M */ | ||
| 310 |
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23232 | for (j=ridx[i];j<ridx[i+1];j++) array[j] *= d*d; |
| 311 | 6112 | emaxl = PetscMax(emaxl,e); | |
| 312 | 6112 | eminl = PetscMin(eminl,e); | |
| 313 | } | ||
| 314 |
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368 | PetscCall(MatSeqAIJRestoreArray(M,&array)); |
| 315 | /* Compute global max and min */ | ||
| 316 |
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368 | PetscCallMPI(MPIU_Allreduce(&emaxl,&emax,1,MPIU_INT,MPI_MAX,PetscObjectComm((PetscObject)pep->Dl))); |
| 317 |
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368 | PetscCallMPI(MPIU_Allreduce(&eminl,&emin,1,MPIU_INT,MPI_MIN,PetscObjectComm((PetscObject)pep->Dl))); |
| 318 |
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368 | if (emax<=emin+2) cont = PETSC_FALSE; |
| 319 | } | ||
| 320 |
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184 | PetscCall(VecRestoreArray(pep->Dr,&Dr)); |
| 321 |
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184 | PetscCall(VecRestoreArray(pep->Dl,&Dl)); |
| 322 | /* Free memory*/ | ||
| 323 |
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184 | PetscCall(MatDestroy(&M)); |
| 324 |
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184 | PetscCall(PetscFree4(rsum,csum,aux,cols)); |
| 325 |
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184 | PetscCall(PetscFree(T)); |
| 326 |
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36 | PetscFunctionReturn(PETSC_SUCCESS); |
| 327 | } | ||
| 328 | |||
| 329 | /* | ||
| 330 | PEPComputeScaleFactor - compute sfactor as described in [Betcke 2008]. | ||
| 331 | */ | ||
| 332 | 2369 | PetscErrorCode PEPComputeScaleFactor(PEP pep) | |
| 333 | { | ||
| 334 | 2369 | PetscBool has0,has1,flg; | |
| 335 | 2369 | PetscReal norm0,norm1; | |
| 336 | 2369 | Mat T[2]; | |
| 337 | 2369 | PEPBasis basis; | |
| 338 | 2369 | PetscInt i; | |
| 339 | |||
| 340 |
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2369 | PetscFunctionBegin; |
| 341 |
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2369 | if (pep->scale==PEP_SCALE_NONE || pep->scale==PEP_SCALE_DIAGONAL) { /* no scalar scaling */ |
| 342 | 2248 | pep->sfactor = 1.0; | |
| 343 | 2248 | pep->dsfactor = 1.0; | |
| 344 |
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2248 | PetscFunctionReturn(PETSC_SUCCESS); |
| 345 | } | ||
| 346 |
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121 | if (pep->sfactor_set) PetscFunctionReturn(PETSC_SUCCESS); /* user provided value */ |
| 347 | 105 | pep->sfactor = 1.0; | |
| 348 | 105 | pep->dsfactor = 1.0; | |
| 349 |
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105 | PetscCall(PEPGetBasis(pep,&basis)); |
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105 | if (basis==PEP_BASIS_MONOMIAL) { |
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105 | PetscCall(STGetTransform(pep->st,&flg)); |
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105 | if (flg) { |
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15 | PetscCall(STGetMatrixTransformed(pep->st,0,&T[0])); |
| 354 |
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15 | PetscCall(STGetMatrixTransformed(pep->st,pep->nmat-1,&T[1])); |
| 355 | } else { | ||
| 356 | 90 | T[0] = pep->A[0]; | |
| 357 | 90 | T[1] = pep->A[pep->nmat-1]; | |
| 358 | } | ||
| 359 |
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105 | if (pep->nmat>2) { |
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105 | PetscCall(MatHasOperation(T[0],MATOP_NORM,&has0)); |
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105 | PetscCall(MatHasOperation(T[1],MATOP_NORM,&has1)); |
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105 | if (has0 && has1) { |
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105 | PetscCall(MatNorm(T[0],NORM_INFINITY,&norm0)); |
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105 | PetscCall(MatNorm(T[1],NORM_INFINITY,&norm1)); |
| 365 | 105 | pep->sfactor = PetscPowReal(norm0/norm1,1.0/(pep->nmat-1)); | |
| 366 | 105 | pep->dsfactor = norm1; | |
| 367 |
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210 | for (i=pep->nmat-2;i>0;i--) { |
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105 | PetscCall(STGetMatrixTransformed(pep->st,i,&T[1])); |
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105 | PetscCall(MatHasOperation(T[1],MATOP_NORM,&has1)); |
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105 | if (has1) { |
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105 | PetscCall(MatNorm(T[1],NORM_INFINITY,&norm1)); |
| 372 | 105 | pep->dsfactor = pep->dsfactor*pep->sfactor+norm1; | |
| 373 | } else break; | ||
| 374 | } | ||
| 375 |
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105 | if (has1) { |
| 376 | 105 | pep->dsfactor = pep->dsfactor*pep->sfactor+norm0; | |
| 377 | 105 | pep->dsfactor = pep->nmat/pep->dsfactor; | |
| 378 | ✗ | } else pep->dsfactor = 1.0; | |
| 379 | } | ||
| 380 | } | ||
| 381 | } | ||
| 382 |
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21 | PetscFunctionReturn(PETSC_SUCCESS); |
| 383 | } | ||
| 384 | |||
| 385 | /* | ||
| 386 | PEPBasisCoefficients - compute polynomial basis coefficients | ||
| 387 | */ | ||
| 388 | 1458 | PetscErrorCode PEPBasisCoefficients(PEP pep,PetscReal *pbc) | |
| 389 | { | ||
| 390 | 1458 | PetscReal *ca,*cb,*cg; | |
| 391 | 1458 | PetscInt k,nmat=pep->nmat; | |
| 392 | |||
| 393 |
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1458 | PetscFunctionBegin; |
| 394 | 1458 | ca = pbc; | |
| 395 | 1458 | cb = pbc+nmat; | |
| 396 | 1458 | cg = pbc+2*nmat; | |
| 397 |
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1458 | switch (pep->basis) { |
| 398 | case PEP_BASIS_MONOMIAL: | ||
| 399 |
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4908 | for (k=0;k<nmat;k++) { |
| 400 | 3716 | ca[k] = 1.0; cb[k] = 0.0; cg[k] = 0.0; | |
| 401 | } | ||
| 402 | break; | ||
| 403 | 266 | case PEP_BASIS_CHEBYSHEV1: | |
| 404 | 266 | ca[0] = 1.0; cb[0] = 0.0; cg[0] = 0.0; | |
| 405 |
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2056 | for (k=1;k<nmat;k++) { |
| 406 | 1790 | ca[k] = .5; cb[k] = 0.0; cg[k] = .5; | |
| 407 | } | ||
| 408 | break; | ||
| 409 | ✗ | case PEP_BASIS_CHEBYSHEV2: | |
| 410 | ✗ | ca[0] = .5; cb[0] = 0.0; cg[0] = 0.0; | |
| 411 | ✗ | for (k=1;k<nmat;k++) { | |
| 412 | ✗ | ca[k] = .5; cb[k] = 0.0; cg[k] = .5; | |
| 413 | } | ||
| 414 | break; | ||
| 415 | ✗ | case PEP_BASIS_LEGENDRE: | |
| 416 | ✗ | ca[0] = 1.0; cb[0] = 0.0; cg[0] = 0.0; | |
| 417 | ✗ | for (k=1;k<nmat;k++) { | |
| 418 | ✗ | ca[k] = k+1; cb[k] = -2*k; cg[k] = k; | |
| 419 | } | ||
| 420 | break; | ||
| 421 | ✗ | case PEP_BASIS_LAGUERRE: | |
| 422 | ✗ | ca[0] = -1.0; cb[0] = 0.0; cg[0] = 0.0; | |
| 423 | ✗ | for (k=1;k<nmat;k++) { | |
| 424 | ✗ | ca[k] = -(k+1); cb[k] = 2*k+1; cg[k] = -k; | |
| 425 | } | ||
| 426 | break; | ||
| 427 | ✗ | case PEP_BASIS_HERMITE: | |
| 428 | ✗ | ca[0] = .5; cb[0] = 0.0; cg[0] = 0.0; | |
| 429 | ✗ | for (k=1;k<nmat;k++) { | |
| 430 | ✗ | ca[k] = .5; cb[k] = 0.0; cg[k] = -k; | |
| 431 | } | ||
| 432 | break; | ||
| 433 | } | ||
| 434 |
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1458 | PetscFunctionReturn(PETSC_SUCCESS); |
| 435 | } | ||
| 436 |