| 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 | #include <slepc/private/dsimpl.h> /*I "slepcds.h" I*/ | ||
| 11 | #include <slepcblaslapack.h> | ||
| 12 | |||
| 13 | typedef struct { | ||
| 14 | PetscInt m; /* number of columns */ | ||
| 15 | PetscInt p; /* number of rows of B */ | ||
| 16 | PetscInt tm; /* number of rows of X after truncating */ | ||
| 17 | PetscInt tp; /* number of rows of V after truncating */ | ||
| 18 | } DS_GSVD; | ||
| 19 | |||
| 20 | 684 | static PetscErrorCode DSAllocate_GSVD(DS ds,PetscInt ld) | |
| 21 | { | ||
| 22 |
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684 | PetscFunctionBegin; |
| 23 |
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684 | PetscCall(DSAllocateMat_Private(ds,DS_MAT_A)); |
| 24 |
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684 | PetscCall(DSAllocateMat_Private(ds,DS_MAT_B)); |
| 25 |
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684 | PetscCall(DSAllocateMat_Private(ds,DS_MAT_X)); |
| 26 |
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684 | PetscCall(DSAllocateMat_Private(ds,DS_MAT_U)); |
| 27 |
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684 | PetscCall(DSAllocateMat_Private(ds,DS_MAT_V)); |
| 28 |
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684 | PetscCall(DSAllocateMat_Private(ds,DS_MAT_T)); |
| 29 |
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684 | PetscCall(DSAllocateMat_Private(ds,DS_MAT_D)); |
| 30 |
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684 | PetscCall(PetscFree(ds->perm)); |
| 31 |
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684 | PetscCall(PetscMalloc1(ld,&ds->perm)); |
| 32 |
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140 | PetscFunctionReturn(PETSC_SUCCESS); |
| 33 | } | ||
| 34 | |||
| 35 | /* | ||
| 36 | In compact form, A is either in form (a) or (b): | ||
| 37 | |||
| 38 | (a) (b) | ||
| 39 | lower bidiagonal with upper arrow (n=m+1) square upper bidiagonal with upper arrow (n=m) | ||
| 40 | 0 l k m-1 | ||
| 41 | ----------------------------------------- 0 l k m-1 | ||
| 42 | |* . | ----------------------------------------- | ||
| 43 | | * . | |* . | | ||
| 44 | | * . | | * . | | ||
| 45 | | * . | | * . | | ||
| 46 | l |. . . . o o | l |. . . o o | | ||
| 47 | | o o | | o o | | ||
| 48 | | o o | | o o | | ||
| 49 | | o o | | o o | | ||
| 50 | | o o | | o o | | ||
| 51 | | o o | | o o | | ||
| 52 | k |. . . . . . . . . . o | k |. . . . . . . . . o x | | ||
| 53 | | x x | | x x | | ||
| 54 | | x x | | x x | | ||
| 55 | | x x | | x x | | ||
| 56 | | x x | | x x | | ||
| 57 | | x x | | x x | | ||
| 58 | | x x | | x x | | ||
| 59 | | x x | | x x | | ||
| 60 | | x x | | x x | | ||
| 61 | | x x| | x x| | ||
| 62 | n-1 | x| n-1 | x| | ||
| 63 | ----------------------------------------- ----------------------------------------- | ||
| 64 | |||
| 65 | and B is square bidiagonal with upper arrow (p=m) | ||
| 66 | |||
| 67 | 0 l k m-1 | ||
| 68 | ----------------------------------------- | ||
| 69 | |* . | | ||
| 70 | | * . | | ||
| 71 | | * . | | ||
| 72 | | * . | | ||
| 73 | l |. . . . o o | | ||
| 74 | | o o | | ||
| 75 | | o o | | ||
| 76 | | o o | | ||
| 77 | | o o | | ||
| 78 | | o o | | ||
| 79 | k |. . . . . . . . . . o x | | ||
| 80 | | x x | | ||
| 81 | | x x | | ||
| 82 | | x x | | ||
| 83 | | x x | | ||
| 84 | | x x | | ||
| 85 | | x x | | ||
| 86 | | x x | | ||
| 87 | | x x| | ||
| 88 | p-1 | x| | ||
| 89 | ---------------------------------------- | ||
| 90 | */ | ||
| 91 | 300 | static PetscErrorCode DSView_GSVD(DS ds,PetscViewer viewer) | |
| 92 | { | ||
| 93 | 300 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 94 | 300 | PetscViewerFormat format; | |
| 95 | 300 | PetscInt i,j,r,k=ds->k,n=ds->n,m=ctx->m,p=ctx->p,rowsa,rowsb,colsa,colsb; | |
| 96 | 300 | PetscReal *T,*S,value; | |
| 97 | |||
| 98 |
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300 | PetscFunctionBegin; |
| 99 |
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300 | PetscCall(PetscViewerGetFormat(viewer,&format)); |
| 100 |
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300 | if (format == PETSC_VIEWER_ASCII_INFO) PetscFunctionReturn(PETSC_SUCCESS); |
| 101 |
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300 | if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) { |
| 102 |
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170 | PetscCall(PetscViewerASCIIPrintf(viewer,"number of columns: %" PetscInt_FMT "\n",m)); |
| 103 |
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170 | PetscCall(PetscViewerASCIIPrintf(viewer,"number of rows of B: %" PetscInt_FMT "\n",p)); |
| 104 |
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34 | PetscFunctionReturn(PETSC_SUCCESS); |
| 105 | } | ||
| 106 |
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130 | PetscCheck(ctx->m,PetscObjectComm((PetscObject)ds),PETSC_ERR_ORDER,"You should set the other dimensions with DSGSVDSetDimensions()"); |
| 107 |
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130 | if (ds->compact) { |
| 108 |
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10 | PetscCall(DSGetArrayReal(ds,DS_MAT_T,&T)); |
| 109 |
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10 | PetscCall(DSGetArrayReal(ds,DS_MAT_D,&S)); |
| 110 |
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10 | PetscCall(PetscViewerASCIIUseTabs(viewer,PETSC_FALSE)); |
| 111 | 10 | rowsa = n; | |
| 112 |
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10 | colsa = ds->extrarow? m+1: m; |
| 113 | 10 | rowsb = p; | |
| 114 | 10 | colsb = ds->extrarow? m+1: m; | |
| 115 |
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10 | if (format == PETSC_VIEWER_ASCII_MATLAB) { |
| 116 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"%% Size = %" PetscInt_FMT " %" PetscInt_FMT "\n",rowsa,colsa)); | |
| 117 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"zzz = zeros(%" PetscInt_FMT ",3);\n",2*ds->n)); | |
| 118 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"zzz = [\n")); | |
| 119 | ✗ | for (i=0;i<PetscMin(rowsa,colsa);i++) PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n",i+1,i+1,(double)T[i])); | |
| 120 | ✗ | for (i=0;i<k;i++) PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n",i+1,k+1,(double)T[i+ds->ld])); | |
| 121 | ✗ | if (n>m) { /* A lower bidiagonal */ | |
| 122 | ✗ | for (i=k;i<rowsa-1;i++) PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n",i+2,i+1,(double)T[i+ds->ld])); | |
| 123 | } else { /* A (square) upper bidiagonal */ | ||
| 124 | ✗ | for (i=k;i<colsa-1;i++) PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n",i+1,i+2,(double)T[i+ds->ld])); | |
| 125 | } | ||
| 126 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"];\n%s = spconvert(zzz);\n",DSMatName[DS_MAT_T])); | |
| 127 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"%% Size = %" PetscInt_FMT " %" PetscInt_FMT "\n",rowsb,colsb)); | |
| 128 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"zzz = zeros(%" PetscInt_FMT ",3);\n",2*ds->n)); | |
| 129 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"zzz = [\n")); | |
| 130 | ✗ | for (i=0;i<rowsb;i++) PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n",i+1,i+1,(double)S[i])); | |
| 131 | ✗ | for (i=0;i<colsb-1;i++) { | |
| 132 | ✗ | r = PetscMax(i+2,ds->k+1); | |
| 133 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"%" PetscInt_FMT " %" PetscInt_FMT " %18.16e\n",i+1,r,(double)T[i+2*ds->ld])); | |
| 134 | } | ||
| 135 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"];\n%s = spconvert(zzz);\n",DSMatName[DS_MAT_D])); | |
| 136 | } else { | ||
| 137 |
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10 | PetscCall(PetscViewerASCIIPrintf(viewer,"Matrix %s =\n",DSMatName[DS_MAT_T])); |
| 138 |
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110 | for (i=0;i<rowsa;i++) { |
| 139 |
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1100 | for (j=0;j<colsa;j++) { |
| 140 |
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1000 | if (i==j) value = T[i]; |
| 141 |
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900 | else if (i<ds->k && j==ds->k) value = T[i+ds->ld]; |
| 142 |
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900 | else if (n>m && i==j+1 && i>ds->k) value = T[j+ds->ld]; |
| 143 |
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900 | else if (n<=m && i+1==j && i>=ds->k) value = T[i+ds->ld]; |
| 144 | else value = 0.0; | ||
| 145 |
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1000 | PetscCall(PetscViewerASCIIPrintf(viewer," %18.16e ",(double)value)); |
| 146 | } | ||
| 147 |
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100 | PetscCall(PetscViewerASCIIPrintf(viewer,"\n")); |
| 148 | } | ||
| 149 |
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10 | PetscCall(PetscViewerASCIIPrintf(viewer,"Matrix %s =\n",DSMatName[DS_MAT_D])); |
| 150 |
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110 | for (i=0;i<rowsb;i++) { |
| 151 |
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1100 | for (j=0;j<colsb;j++) { |
| 152 |
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1000 | if (i==j) value = S[i]; |
| 153 |
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900 | else if (i<ds->k && j==ds->k) value = T[PetscMin(i,j)+2*ds->ld]; |
| 154 |
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900 | else if (i+1==j && i>=ds->k) value = T[i+2*ds->ld]; |
| 155 | else value = 0.0; | ||
| 156 |
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1000 | PetscCall(PetscViewerASCIIPrintf(viewer," %18.16e ",(double)value)); |
| 157 | } | ||
| 158 |
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100 | PetscCall(PetscViewerASCIIPrintf(viewer,"\n")); |
| 159 | } | ||
| 160 | } | ||
| 161 |
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10 | PetscCall(PetscViewerASCIIUseTabs(viewer,PETSC_TRUE)); |
| 162 |
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10 | PetscCall(PetscViewerFlush(viewer)); |
| 163 |
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10 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_T,&T)); |
| 164 |
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10 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_D,&S)); |
| 165 | } else { | ||
| 166 |
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120 | PetscCall(DSViewMat(ds,viewer,DS_MAT_A)); |
| 167 |
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120 | PetscCall(DSViewMat(ds,viewer,DS_MAT_B)); |
| 168 | } | ||
| 169 |
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130 | if (ds->state>DS_STATE_INTERMEDIATE) { |
| 170 | ✗ | PetscCall(DSViewMat(ds,viewer,DS_MAT_X)); | |
| 171 | ✗ | PetscCall(DSViewMat(ds,viewer,DS_MAT_U)); | |
| 172 | ✗ | PetscCall(DSViewMat(ds,viewer,DS_MAT_V)); | |
| 173 | } | ||
| 174 |
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26 | PetscFunctionReturn(PETSC_SUCCESS); |
| 175 | } | ||
| 176 | |||
| 177 | 170 | static PetscErrorCode DSVectors_GSVD(DS ds,DSMatType mat,PetscInt *j,PetscReal *rnorm) | |
| 178 | { | ||
| 179 |
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170 | PetscFunctionBegin; |
| 180 |
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170 | switch (mat) { |
| 181 | ✗ | case DS_MAT_U: | |
| 182 | case DS_MAT_V: | ||
| 183 | ✗ | if (rnorm) *rnorm = 0.0; | |
| 184 | break; | ||
| 185 | case DS_MAT_X: | ||
| 186 | break; | ||
| 187 | ✗ | default: | |
| 188 | − | SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid mat parameter"); | |
| 189 | } | ||
| 190 |
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34 | PetscFunctionReturn(PETSC_SUCCESS); |
| 191 | } | ||
| 192 | |||
| 193 | 6350 | static PetscErrorCode DSSort_GSVD(DS ds,PetscScalar *wr,PetscScalar *wi,PetscScalar *rr,PetscScalar *ri,PetscInt *k) | |
| 194 | { | ||
| 195 | 6350 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 196 | 6350 | PetscInt t,l,ld=ds->ld,i,*perm,*perm2; | |
| 197 | 6350 | PetscReal *T=NULL,*D=NULL,*eig; | |
| 198 | 6350 | PetscScalar *A=NULL,*B=NULL; | |
| 199 | 6350 | PetscBool compact=ds->compact; | |
| 200 | |||
| 201 |
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6350 | PetscFunctionBegin; |
| 202 |
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6350 | if (!ds->sc) PetscFunctionReturn(PETSC_SUCCESS); |
| 203 |
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6350 | PetscCheck(ctx->m,PetscObjectComm((PetscObject)ds),PETSC_ERR_ORDER,"You should set the other dimensions with DSGSVDSetDimensions()"); |
| 204 | 6350 | l = ds->l; | |
| 205 | 6350 | t = ds->t; | |
| 206 | 6350 | perm = ds->perm; | |
| 207 |
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6350 | PetscCall(PetscMalloc2(t,&eig,t,&perm2)); |
| 208 |
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6350 | if (compact) { |
| 209 |
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6160 | PetscCall(DSGetArrayReal(ds,DS_MAT_T,&T)); |
| 210 |
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6160 | PetscCall(DSGetArrayReal(ds,DS_MAT_D,&D)); |
| 211 |
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64050 | for (i=0;i<t;i++) eig[i] = (D[i]==0)?PETSC_INFINITY:T[i]/D[i]; |
| 212 | } else { | ||
| 213 |
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190 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A)); |
| 214 |
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190 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&B)); |
| 215 |
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2300 | for (i=0;i<t;i++) eig[i] = (B[i+i*ld]==0)?PETSC_INFINITY:PetscRealPart(A[i+i*ld])/PetscRealPart(B[i*(1+ld)]); |
| 216 | } | ||
| 217 |
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6350 | PetscCall(DSSortEigenvaluesReal_Private(ds,eig,perm)); |
| 218 |
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6350 | PetscCall(PetscArraycpy(perm2,perm,t)); |
| 219 |
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62837 | for (i=l;i<t;i++) wr[i] = eig[perm[i]]; |
| 220 |
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6350 | if (compact) { |
| 221 |
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6160 | PetscCall(PetscArraycpy(eig,T,t)); |
| 222 |
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60537 | for (i=l;i<t;i++) T[i] = eig[perm[i]]; |
| 223 |
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6160 | PetscCall(PetscArraycpy(eig,D,t)); |
| 224 |
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60537 | for (i=l;i<t;i++) D[i] = eig[perm[i]]; |
| 225 |
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6160 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_T,&T)); |
| 226 |
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6160 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_D,&D)); |
| 227 | } else { | ||
| 228 |
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2300 | for (i=l;i<t;i++) eig[i] = PetscRealPart(A[i*(1+ld)]); |
| 229 |
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2300 | for (i=l;i<t;i++) A[i*(1+ld)] = eig[perm[i]]; |
| 230 |
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2300 | for (i=l;i<t;i++) eig[i] = PetscRealPart(B[i*(1+ld)]); |
| 231 |
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2300 | for (i=l;i<t;i++) B[i*(1+ld)] = eig[perm[i]]; |
| 232 |
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190 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A)); |
| 233 |
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190 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&B)); |
| 234 | } | ||
| 235 |
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|
6350 | PetscCall(DSPermuteColumns_Private(ds,l,t,ds->n,DS_MAT_U,perm2)); |
| 236 |
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6350 | PetscCall(PetscArraycpy(perm2,perm,t)); |
| 237 |
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6350 | PetscCall(DSPermuteColumns_Private(ds,l,t,ctx->m,DS_MAT_X,perm2)); |
| 238 |
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6350 | PetscCall(DSPermuteColumns_Private(ds,l,t,ctx->p,DS_MAT_V,perm)); |
| 239 |
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6350 | PetscCall(PetscFree2(eig,perm2)); |
| 240 |
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|
1262 | PetscFunctionReturn(PETSC_SUCCESS); |
| 241 | } | ||
| 242 | |||
| 243 | 6130 | static PetscErrorCode DSUpdateExtraRow_GSVD(DS ds) | |
| 244 | { | ||
| 245 | 6130 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 246 | 6130 | PetscInt i; | |
| 247 | 6130 | PetscBLASInt n=0,m=0,ld=0; | |
| 248 | 6130 | const PetscScalar *U,*V; | |
| 249 | 6130 | PetscReal *T,*e,*f,alpha,beta,betah; | |
| 250 | |||
| 251 |
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6130 | PetscFunctionBegin; |
| 252 |
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6130 | PetscCheck(ctx->m,PetscObjectComm((PetscObject)ds),PETSC_ERR_ORDER,"You should set the other dimensions with DSGSVDSetDimensions()"); |
| 253 |
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6130 | PetscCheck(ds->compact,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented for non-compact storage"); |
| 254 |
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6130 | PetscCall(PetscBLASIntCast(ds->n,&n)); |
| 255 |
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6130 | PetscCall(PetscBLASIntCast(ctx->m,&m)); |
| 256 |
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6130 | PetscCall(PetscBLASIntCast(ds->ld,&ld)); |
| 257 |
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6130 | PetscCall(DSGetArrayReal(ds,DS_MAT_T,&T)); |
| 258 | 6130 | e = T+ld; | |
| 259 | 6130 | f = T+2*ld; | |
| 260 |
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6130 | PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_U],&U)); |
| 261 |
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6130 | PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_V],&V)); |
| 262 |
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6130 | if (n<=m) { /* upper variant, A is square upper bidiagonal */ |
| 263 | 2499 | beta = e[m-1]; /* in compact, we assume all entries are zero except the last one */ | |
| 264 | 2499 | betah = f[m-1]; | |
| 265 |
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25247 | for (i=0;i<m;i++) { |
| 266 | 22748 | e[i] = PetscRealPart(beta*U[m-1+i*ld]); | |
| 267 | 22748 | f[i] = PetscRealPart(betah*V[m-1+i*ld]); | |
| 268 | } | ||
| 269 | } else { /* lower variant, A is (m+1)xm lower bidiagonal */ | ||
| 270 | 3631 | alpha = T[m]; | |
| 271 | 3631 | betah = f[m-1]; | |
| 272 |
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38473 | for (i=0;i<m;i++) { |
| 273 | 34842 | e[i] = PetscRealPart(alpha*U[m+i*ld]); | |
| 274 | 34842 | f[i] = PetscRealPart(betah*V[m-1+i*ld]); | |
| 275 | } | ||
| 276 | 3631 | T[m] = PetscRealPart(alpha*U[m+m*ld]); | |
| 277 | } | ||
| 278 | 6130 | ds->k = m; | |
| 279 |
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6130 | PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_U],&U)); |
| 280 |
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6130 | PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_V],&V)); |
| 281 |
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6130 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_T,&T)); |
| 282 |
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1218 | PetscFunctionReturn(PETSC_SUCCESS); |
| 283 | } | ||
| 284 | |||
| 285 | 6005 | static PetscErrorCode DSTruncate_GSVD(DS ds,PetscInt n,PetscBool trim) | |
| 286 | { | ||
| 287 | 6005 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 288 | 6005 | PetscScalar *U; | |
| 289 | 6005 | PetscReal *T; | |
| 290 | 6005 | PetscInt i,m=ctx->m,ld=ds->ld; | |
| 291 | 6005 | PetscBool lower=(ds->n>ctx->m)?PETSC_TRUE:PETSC_FALSE; | |
| 292 | |||
| 293 |
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6005 | PetscFunctionBegin; |
| 294 |
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6005 | PetscCheck(ds->compact,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Not implemented for non-compact storage"); |
| 295 |
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6005 | if (trim) { |
| 296 | 508 | ds->l = 0; | |
| 297 | 508 | ds->k = 0; | |
| 298 |
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508 | ds->n = lower? n+1: n; |
| 299 | 508 | ctx->m = n; | |
| 300 | 508 | ctx->p = n; | |
| 301 | 508 | ds->t = ds->n; /* truncated length equal to the new dimension */ | |
| 302 | 508 | ctx->tm = ctx->m; /* must also keep the previous dimension of X */ | |
| 303 | 508 | ctx->tp = ctx->p; /* must also keep the previous dimension of V */ | |
| 304 | } else { | ||
| 305 |
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5497 | if (lower) { |
| 306 | /* move value of diagonal element of arrow (alpha) */ | ||
| 307 |
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3201 | PetscCall(DSGetArrayReal(ds,DS_MAT_T,&T)); |
| 308 | 3201 | T[n] = T[m]; | |
| 309 |
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3201 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_T,&T)); |
| 310 | /* copy last column of U so that it updates the next initial vector of U1 */ | ||
| 311 |
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3201 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_U],&U)); |
| 312 |
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36884 | for (i=0;i<=m;i++) U[i+n*ld] = U[i+m*ld]; |
| 313 |
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3201 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_U],&U)); |
| 314 | } | ||
| 315 |
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5497 | ds->k = (ds->extrarow)? n: 0; |
| 316 | 5497 | ds->t = ds->n; /* truncated length equal to previous dimension */ | |
| 317 | 5497 | ctx->tm = ctx->m; /* must also keep the previous dimension of X */ | |
| 318 | 5497 | ctx->tp = ctx->p; /* must also keep the previous dimension of V */ | |
| 319 |
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5497 | ds->n = lower? n+1: n; |
| 320 | 5497 | ctx->m = n; | |
| 321 | 5497 | ctx->p = n; | |
| 322 | } | ||
| 323 |
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1193 | PetscFunctionReturn(PETSC_SUCCESS); |
| 324 | } | ||
| 325 | |||
| 326 | 6280 | static PetscErrorCode DSSwitchFormat_GSVD(DS ds) | |
| 327 | { | ||
| 328 | 6280 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 329 | 6280 | PetscReal *T,*D; | |
| 330 | 6280 | PetscScalar *A,*B; | |
| 331 | 6280 | PetscInt i,n=ds->n,k=ds->k,ld=ds->ld,m=ctx->m; | |
| 332 | |||
| 333 |
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6280 | PetscFunctionBegin; |
| 334 |
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6280 | PetscCheck(ctx->m,PetscObjectComm((PetscObject)ds),PETSC_ERR_ORDER,"You should set the other dimensions with DSGSVDSetDimensions()"); |
| 335 | /* switch from compact (arrow) to dense storage */ | ||
| 336 | /* bidiagonal associated to B is stored in D and T+2*ld */ | ||
| 337 |
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6280 | PetscCall(MatDenseGetArrayWrite(ds->omat[DS_MAT_A],&A)); |
| 338 |
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6280 | PetscCall(MatDenseGetArrayWrite(ds->omat[DS_MAT_B],&B)); |
| 339 |
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6280 | PetscCall(DSGetArrayReal(ds,DS_MAT_T,&T)); |
| 340 |
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6280 | PetscCall(DSGetArrayReal(ds,DS_MAT_D,&D)); |
| 341 |
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6280 | PetscCall(PetscArrayzero(A,ld*ld)); |
| 342 |
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6280 | PetscCall(PetscArrayzero(B,ld*ld)); |
| 343 |
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31146 | for (i=0;i<k;i++) { |
| 344 | 24866 | A[i+i*ld] = T[i]; | |
| 345 | 24866 | A[i+k*ld] = T[i+ld]; | |
| 346 | 24866 | B[i+i*ld] = D[i]; | |
| 347 | 24866 | B[i+k*ld] = T[i+2*ld]; | |
| 348 | } | ||
| 349 | /* B is upper bidiagonal */ | ||
| 350 | 6280 | B[k+k*ld] = D[k]; | |
| 351 |
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33994 | for (i=k+1;i<m;i++) { |
| 352 | 27714 | B[i+i*ld] = D[i]; | |
| 353 | 27714 | B[i-1+i*ld] = T[i-1+2*ld]; | |
| 354 | } | ||
| 355 | /* A can be upper (square) or lower bidiagonal */ | ||
| 356 |
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40204 | for (i=k;i<m;i++) A[i+i*ld] = T[i]; |
| 357 |
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26771 | if (n>m) for (i=k;i<m;i++) A[i+1+i*ld] = T[i+ld]; |
| 358 |
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13433 | else for (i=k+1;i<m;i++) A[i-1+i*ld] = T[i-1+ld]; |
| 359 |
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6280 | PetscCall(MatDenseRestoreArrayWrite(ds->omat[DS_MAT_A],&A)); |
| 360 |
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6280 | PetscCall(MatDenseRestoreArrayWrite(ds->omat[DS_MAT_B],&B)); |
| 361 |
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6280 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_T,&T)); |
| 362 |
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6280 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_D,&D)); |
| 363 |
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1248 | PetscFunctionReturn(PETSC_SUCCESS); |
| 364 | } | ||
| 365 | |||
| 366 | /* | ||
| 367 | Compact format is used when [A;B] has orthonormal columns. | ||
| 368 | In this case R=I and the GSVD of (A,B) is the CS decomposition | ||
| 369 | */ | ||
| 370 | 6350 | static PetscErrorCode DSSolve_GSVD(DS ds,PetscScalar *wr,PetscScalar *wi) | |
| 371 | { | ||
| 372 | 6350 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 373 | 6350 | PetscInt i,j; | |
| 374 | 6350 | PetscBLASInt n1,m1,lc = 0,n = 0,m = 0,p = 0,p1,l,k,q,ld,off,lwork,r; | |
| 375 | 6350 | PetscScalar *A,*B,*X,*U,*V,sone=1.0,smone=-1.0; | |
| 376 | 6350 | PetscReal *alpha,*beta,*T,*D; | |
| 377 | #if !defined(SLEPC_MISSING_LAPACK_GGSVD3) | ||
| 378 | 6350 | PetscScalar a,dummy; | |
| 379 | 6350 | PetscReal rdummy; | |
| 380 | 6350 | PetscBLASInt idummy; | |
| 381 | #endif | ||
| 382 | |||
| 383 |
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6350 | PetscFunctionBegin; |
| 384 |
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6350 | PetscCheck(ctx->m,PetscObjectComm((PetscObject)ds),PETSC_ERR_ORDER,"You should set the other dimensions with DSGSVDSetDimensions()"); |
| 385 |
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6350 | PetscCall(PetscBLASIntCast(ds->n,&m)); |
| 386 |
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6350 | PetscCall(PetscBLASIntCast(ctx->m,&n)); |
| 387 |
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6350 | PetscCall(PetscBLASIntCast(ctx->p,&p)); |
| 388 |
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6350 | PetscCall(PetscBLASIntCast(ds->l,&lc)); |
| 389 |
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6350 | PetscCheck(ds->compact || lc==0,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"DSGSVD with non-compact format does not support locking"); |
| 390 | /* In compact storage B is always nxn and A can be either nxn or (n+1)xn */ | ||
| 391 |
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6350 | PetscCheck(!ds->compact || (p==n && (m==p || m==p+1)),PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"Dimensions not supported in compact format"); |
| 392 |
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6350 | PetscCall(PetscBLASIntCast(ds->ld,&ld)); |
| 393 | 6350 | n1 = n-lc; /* n1 = size of leading block, excl. locked + size of trailing block */ | |
| 394 | 6350 | m1 = m-lc; | |
| 395 | 6350 | p1 = p-lc; | |
| 396 | 6350 | off = lc+lc*ld; | |
| 397 |
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6350 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A)); |
| 398 |
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6350 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_B],&B)); |
| 399 |
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6350 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_X],&X)); |
| 400 |
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6350 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_U],&U)); |
| 401 |
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6350 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_V],&V)); |
| 402 |
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6350 | PetscCall(PetscArrayzero(X,ld*ld)); |
| 403 |
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9863 | for (i=0;i<lc;i++) X[i+i*ld] = 1.0; |
| 404 |
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6350 | PetscCall(PetscArrayzero(U,ld*ld)); |
| 405 |
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9863 | for (i=0;i<lc;i++) U[i+i*ld] = 1.0; |
| 406 |
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6350 | PetscCall(PetscArrayzero(V,ld*ld)); |
| 407 |
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9863 | for (i=0;i<lc;i++) V[i+i*ld] = 1.0; |
| 408 |
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6350 | if (ds->compact) PetscCall(DSSwitchFormat_GSVD(ds)); |
| 409 | |||
| 410 | #if !defined(SLEPC_MISSING_LAPACK_GGSVD3) | ||
| 411 | /* workspace query and memory allocation */ | ||
| 412 | 6350 | lwork = -1; | |
| 413 | #if !defined(PETSC_USE_COMPLEX) | ||
| 414 |
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3534 | PetscCallLAPACKInfo("LAPACKggsvd3",LAPACKggsvd3_("U","V","Q",&m1,&n1,&p1,&k,&l,&dummy,&ld,&dummy,&ld,&rdummy,&rdummy,&dummy,&ld,&dummy,&ld,&dummy,&ld,&a,&lwork,&idummy,&info)); |
| 415 |
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3534 | PetscCall(PetscBLASIntCast((PetscInt)a,&lwork)); |
| 416 | #else | ||
| 417 |
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2816 | PetscCallLAPACKInfo("LAPACKggsvd3",LAPACKggsvd3_("U","V","Q",&m1,&n1,&p1,&k,&l,&dummy,&ld,&dummy,&ld,&rdummy,&rdummy,&dummy,&ld,&dummy,&ld,&dummy,&ld,&a,&lwork,&rdummy,&idummy,&info)); |
| 418 |
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2816 | PetscCall(PetscBLASIntCast((PetscInt)PetscRealPart(a),&lwork)); |
| 419 | #endif | ||
| 420 | |||
| 421 | #if !defined(PETSC_USE_COMPLEX) | ||
| 422 |
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3534 | PetscCall(DSAllocateWork_Private(ds,lwork,2*ds->ld,ds->ld)); |
| 423 | 3534 | alpha = ds->rwork; | |
| 424 | 3534 | beta = ds->rwork+ds->ld; | |
| 425 |
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3534 | PetscCallLAPACKInfo("LAPACKggsvd3",LAPACKggsvd3_("U","V","Q",&m1,&n1,&p1,&k,&l,A+off,&ld,B+off,&ld,alpha,beta,U+off,&ld,V+off,&ld,X+off,&ld,ds->work,&lwork,ds->iwork,&info)); |
| 426 | #else | ||
| 427 |
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2816 | PetscCall(DSAllocateWork_Private(ds,lwork,4*ds->ld,ds->ld)); |
| 428 | 2816 | alpha = ds->rwork+2*ds->ld; | |
| 429 | 2816 | beta = ds->rwork+3*ds->ld; | |
| 430 |
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2816 | PetscCallLAPACKInfo("LAPACKggsvd3",LAPACKggsvd3_("U","V","Q",&m1,&n1,&p1,&k,&l,A+off,&ld,B+off,&ld,alpha,beta,U+off,&ld,V+off,&ld,X+off,&ld,ds->work,&lwork,ds->rwork,ds->iwork,&info)); |
| 431 | #endif | ||
| 432 | |||
| 433 | #else /* defined(SLEPC_MISSING_LAPACK_GGSVD3) */ | ||
| 434 | |||
| 435 | lwork = PetscMax(PetscMax(3*n,m),p)+n; | ||
| 436 | #if !defined(PETSC_USE_COMPLEX) | ||
| 437 | PetscCall(DSAllocateWork_Private(ds,lwork,2*ds->ld,ds->ld)); | ||
| 438 | alpha = ds->rwork; | ||
| 439 | beta = ds->rwork+ds->ld; | ||
| 440 | PetscCallLAPACKInfo("LAPACKggsvd",LAPACKggsvd_("U","V","Q",&m1,&n1,&p1,&k,&l,A+off,&ld,B+off,&ld,alpha,beta,U+off,&ld,V+off,&ld,X+off,&ld,ds->work,ds->iwork,&info)); | ||
| 441 | #else | ||
| 442 | PetscCall(DSAllocateWork_Private(ds,lwork,4*ds->ld,ds->ld)); | ||
| 443 | alpha = ds->rwork+2*ds->ld; | ||
| 444 | beta = ds->rwork+3*ds->ld; | ||
| 445 | PetscCallLAPACKInfo("LAPACKggsvd",LAPACKggsvd_("U","V","Q",&m1,&n1,&p1,&k,&l,A+off,&ld,B+off,&ld,alpha,beta,U+off,&ld,V+off,&ld,X+off,&ld,ds->work,ds->rwork,ds->iwork,&info)); | ||
| 446 | #endif | ||
| 447 | |||
| 448 | #endif | ||
| 449 | |||
| 450 |
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6350 | PetscCheck(k+l>=n1,PetscObjectComm((PetscObject)ds),PETSC_ERR_SUP,"The rank deficient case not supported yet"); |
| 451 |
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6350 | if (ds->compact) { |
| 452 |
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6160 | PetscCall(DSGetArrayReal(ds,DS_MAT_T,&T)); |
| 453 |
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6160 | PetscCall(DSGetArrayReal(ds,DS_MAT_D,&D)); |
| 454 | /* R is the identity matrix (except the sign) */ | ||
| 455 |
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60537 | for (i=lc;i<n;i++) { |
| 456 |
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54377 | if (PetscRealPart(A[i+i*ld])<0.0) { /* scale column i */ |
| 457 |
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321008 | for (j=lc;j<n;j++) X[j+i*ld] = -X[j+i*ld]; |
| 458 | } | ||
| 459 | } | ||
| 460 |
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6160 | PetscCall(PetscArrayzero(T+ld,m-1)); |
| 461 |
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6160 | PetscCall(PetscArrayzero(T+2*ld,n-1)); |
| 462 |
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60537 | for (i=lc;i<n;i++) { |
| 463 | 54377 | T[i] = alpha[i-lc]; | |
| 464 | 54377 | D[i] = beta[i-lc]; | |
| 465 |
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54377 | if (D[i]==0.0) wr[i] = PETSC_INFINITY; |
| 466 | 54377 | else wr[i] = T[i]/D[i]; | |
| 467 | } | ||
| 468 | 6160 | ds->t = n; | |
| 469 |
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6160 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_D,&D)); |
| 470 |
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6160 | PetscCall(DSRestoreArrayReal(ds,DS_MAT_T,&T)); |
| 471 | } else { | ||
| 472 | /* X = X*inv(R) */ | ||
| 473 | 190 | q = PetscMin(m,n); | |
| 474 |
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190 | PetscCallBLAS("BLAStrsm",BLAStrsm_("R","U","N","N",&n,&q,&sone,A,&ld,X,&ld)); |
| 475 |
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190 | if (m<n) { |
| 476 | 40 | r = n-m; | |
| 477 |
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40 | PetscCallBLAS("BLASgemm",BLASgemm_("N","N",&n,&r,&m,&sone,X,&ld,A,&ld,&smone,X+m*ld,&ld)); |
| 478 |
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40 | PetscCallBLAS("BLAStrsm",BLAStrsm_("R","U","N","N",&n,&r,&sone,B+m*ld,&ld,X+m*ld,&ld)); |
| 479 | } | ||
| 480 |
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190 | if (k>0) { |
| 481 |
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130 | for (i=k;i<PetscMin(m,k+l);i++) { |
| 482 |
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110 | PetscCall(PetscArraycpy(X+(i-k)*ld,X+i*ld,ld)); |
| 483 |
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110 | PetscCall(PetscArraycpy(U+(i-k)*ld,U+i*ld,ld)); |
| 484 | } | ||
| 485 | } | ||
| 486 | /* singular values */ | ||
| 487 |
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190 | PetscCall(PetscArrayzero(A,ld*ld)); |
| 488 |
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190 | PetscCall(PetscArrayzero(B,ld*ld)); |
| 489 |
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2300 | for (j=k;j<PetscMin(m,k+l);j++) { |
| 490 | 2110 | A[(j-k)*(1+ld)] = alpha[j]; | |
| 491 | 2110 | B[(j-k)*(1+ld)] = beta[j]; | |
| 492 | 2110 | wr[j-k] = alpha[j]/beta[j]; | |
| 493 | } | ||
| 494 | 190 | ds->t = PetscMin(m,k+l)-k; /* set number of computed values */ | |
| 495 | } | ||
| 496 |
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6350 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A)); |
| 497 |
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6350 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_B],&B)); |
| 498 |
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6350 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_X],&X)); |
| 499 |
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6350 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_U],&U)); |
| 500 |
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6350 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_V],&V)); |
| 501 |
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1262 | PetscFunctionReturn(PETSC_SUCCESS); |
| 502 | } | ||
| 503 | |||
| 504 | 240 | static PetscErrorCode DSCond_GSVD(DS ds,PetscReal *cond) | |
| 505 | { | ||
| 506 | 240 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 507 | 240 | PetscBLASInt lwork,lrwork=0,m,n,p,ld; | |
| 508 | 240 | PetscScalar *A,*work; | |
| 509 | 240 | const PetscScalar *M; | |
| 510 | 240 | PetscReal *sigma,conda,condb; | |
| 511 | #if defined(PETSC_USE_COMPLEX) | ||
| 512 | 120 | PetscReal *rwork; | |
| 513 | #endif | ||
| 514 | |||
| 515 |
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240 | PetscFunctionBegin; |
| 516 |
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240 | PetscCall(PetscBLASIntCast(ds->n,&m)); |
| 517 |
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240 | PetscCall(PetscBLASIntCast(ctx->m,&n)); |
| 518 |
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240 | PetscCall(PetscBLASIntCast(ctx->p,&p)); |
| 519 |
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240 | PetscCall(PetscBLASIntCast(ds->ld,&ld)); |
| 520 | 240 | lwork = 5*n; | |
| 521 | #if defined(PETSC_USE_COMPLEX) | ||
| 522 | 120 | lrwork = 5*n; | |
| 523 | #endif | ||
| 524 |
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240 | PetscCall(DSAllocateWork_Private(ds,ld*n+lwork,n+lrwork,0)); |
| 525 | 240 | A = ds->work; | |
| 526 | 240 | work = ds->work+ld*n; | |
| 527 | 240 | sigma = ds->rwork; | |
| 528 | #if defined(PETSC_USE_COMPLEX) | ||
| 529 | 120 | rwork = ds->rwork+n; | |
| 530 | #endif | ||
| 531 |
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240 | if (ds->compact) PetscCall(DSSwitchFormat_GSVD(ds)); |
| 532 | |||
| 533 |
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240 | PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_A],&M)); |
| 534 |
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240 | PetscCall(PetscArraycpy(A,M,ld*n)); |
| 535 |
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240 | PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_A],&M)); |
| 536 | #if defined(PETSC_USE_COMPLEX) | ||
| 537 |
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120 | PetscCallLAPACKInfo("LAPACKgesvd",LAPACKgesvd_("N","N",&m,&n,A,&ld,sigma,NULL,&ld,NULL,&ld,work,&lwork,rwork,&info)); |
| 538 | #else | ||
| 539 |
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120 | PetscCallLAPACKInfo("LAPACKgesvd",LAPACKgesvd_("N","N",&m,&n,A,&ld,sigma,NULL,&ld,NULL,&ld,work,&lwork,&info)); |
| 540 | #endif | ||
| 541 |
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240 | conda = sigma[0]/sigma[PetscMin(m,n)-1]; |
| 542 | |||
| 543 |
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240 | PetscCall(MatDenseGetArrayRead(ds->omat[DS_MAT_B],&M)); |
| 544 |
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240 | PetscCall(PetscArraycpy(A,M,ld*n)); |
| 545 |
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240 | PetscCall(MatDenseRestoreArrayRead(ds->omat[DS_MAT_B],&M)); |
| 546 | #if defined(PETSC_USE_COMPLEX) | ||
| 547 |
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120 | PetscCallLAPACKInfo("LAPACKgesvd",LAPACKgesvd_("N","N",&p,&n,A,&ld,sigma,NULL,&ld,NULL,&ld,work,&lwork,rwork,&info)); |
| 548 | #else | ||
| 549 |
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120 | PetscCallLAPACKInfo("LAPACKgesvd",LAPACKgesvd_("N","N",&p,&n,A,&ld,sigma,NULL,&ld,NULL,&ld,work,&lwork,&info)); |
| 550 | #endif | ||
| 551 |
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240 | condb = sigma[0]/sigma[PetscMin(p,n)-1]; |
| 552 | |||
| 553 |
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240 | *cond = PetscMax(conda,condb); |
| 554 |
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240 | PetscFunctionReturn(PETSC_SUCCESS); |
| 555 | } | ||
| 556 | |||
| 557 | #if !defined(PETSC_HAVE_MPIUNI) | ||
| 558 | 300 | static PetscErrorCode DSSynchronize_GSVD(DS ds,PetscScalar eigr[],PetscScalar eigi[]) | |
| 559 | { | ||
| 560 | 300 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 561 | 300 | PetscInt ld=ds->ld,l=ds->l,k=0,kr=0; | |
| 562 | 300 | PetscMPIInt m,rank,off=0,size,n,ldn,ld3; | |
| 563 | 300 | PetscScalar *A,*U,*V,*X; | |
| 564 | 300 | PetscReal *T; | |
| 565 | |||
| 566 |
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300 | PetscFunctionBegin; |
| 567 |
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300 | PetscCall(PetscMPIIntCast(ctx->m,&m)); |
| 568 |
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300 | if (ds->compact) kr = 3*ld; |
| 569 | 50 | else k = 2*(m-l)*ld; | |
| 570 |
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300 | if (ds->state>DS_STATE_RAW) k += 3*(m-l)*ld; |
| 571 |
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300 | if (eigr) k += m-l; |
| 572 |
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300 | PetscCall(DSAllocateWork_Private(ds,k+kr,0,0)); |
| 573 |
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300 | PetscCall(PetscMPIIntCast(k*sizeof(PetscScalar)+kr*sizeof(PetscReal),&size)); |
| 574 |
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300 | PetscCall(PetscMPIIntCast(m-l,&n)); |
| 575 |
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300 | PetscCall(PetscMPIIntCast(ld*(m-l),&ldn)); |
| 576 |
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300 | PetscCall(PetscMPIIntCast(3*ld,&ld3)); |
| 577 |
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300 | if (ds->compact) PetscCall(DSGetArrayReal(ds,DS_MAT_T,&T)); |
| 578 |
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50 | else PetscCall(MatDenseGetArray(ds->omat[DS_MAT_A],&A)); |
| 579 |
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300 | if (ds->state>DS_STATE_RAW) { |
| 580 |
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300 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_U],&U)); |
| 581 |
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300 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_V],&V)); |
| 582 |
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300 | PetscCall(MatDenseGetArray(ds->omat[DS_MAT_X],&X)); |
| 583 | } | ||
| 584 |
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300 | PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)ds),&rank)); |
| 585 |
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300 | if (!rank) { |
| 586 |
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145 | if (ds->compact) PetscCallMPI(MPI_Pack(T,ld3,MPIU_REAL,ds->work,size,&off,PetscObjectComm((PetscObject)ds))); |
| 587 |
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20 | else PetscCallMPI(MPI_Pack(A+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds))); |
| 588 |
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145 | if (ds->state>DS_STATE_RAW) { |
| 589 |
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145 | PetscCallMPI(MPI_Pack(U+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds))); |
| 590 |
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145 | PetscCallMPI(MPI_Pack(V+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds))); |
| 591 |
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145 | PetscCallMPI(MPI_Pack(X+l*ld,ldn,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds))); |
| 592 | } | ||
| 593 |
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145 | if (eigr) PetscCallMPI(MPI_Pack(eigr+l,n,MPIU_SCALAR,ds->work,size,&off,PetscObjectComm((PetscObject)ds))); |
| 594 | } | ||
| 595 |
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600 | PetscCallMPI(MPI_Bcast(ds->work,size,MPI_BYTE,0,PetscObjectComm((PetscObject)ds))); |
| 596 |
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300 | if (rank) { |
| 597 |
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155 | if (ds->compact) PetscCallMPI(MPI_Unpack(ds->work,size,&off,T,ld3,MPIU_REAL,PetscObjectComm((PetscObject)ds))); |
| 598 |
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30 | else PetscCallMPI(MPI_Unpack(ds->work,size,&off,A+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds))); |
| 599 |
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155 | if (ds->state>DS_STATE_RAW) { |
| 600 |
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155 | PetscCallMPI(MPI_Unpack(ds->work,size,&off,U+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds))); |
| 601 |
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155 | PetscCallMPI(MPI_Unpack(ds->work,size,&off,V+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds))); |
| 602 |
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155 | PetscCallMPI(MPI_Unpack(ds->work,size,&off,X+l*ld,ldn,MPIU_SCALAR,PetscObjectComm((PetscObject)ds))); |
| 603 | } | ||
| 604 |
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155 | if (eigr) PetscCallMPI(MPI_Unpack(ds->work,size,&off,eigr+l,n,MPIU_SCALAR,PetscObjectComm((PetscObject)ds))); |
| 605 | } | ||
| 606 |
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|
300 | if (ds->compact) PetscCall(DSRestoreArrayReal(ds,DS_MAT_T,&T)); |
| 607 |
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50 | else PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_A],&A)); |
| 608 |
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300 | if (ds->state>DS_STATE_RAW) { |
| 609 |
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300 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_U],&U)); |
| 610 |
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300 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_V],&V)); |
| 611 |
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300 | PetscCall(MatDenseRestoreArray(ds->omat[DS_MAT_X],&X)); |
| 612 | } | ||
| 613 |
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|
60 | PetscFunctionReturn(PETSC_SUCCESS); |
| 614 | } | ||
| 615 | #endif | ||
| 616 | |||
| 617 | 18905 | static PetscErrorCode DSMatGetSize_GSVD(DS ds,DSMatType t,PetscInt *rows,PetscInt *cols) | |
| 618 | { | ||
| 619 | 18905 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 620 | |||
| 621 |
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18905 | PetscFunctionBegin; |
| 622 |
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18905 | PetscCheck(ctx->m,PetscObjectComm((PetscObject)ds),PETSC_ERR_ORDER,"You should set the other dimensions with DSGSVDSetDimensions()"); |
| 623 |
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18905 | switch (t) { |
| 624 | 190 | case DS_MAT_A: | |
| 625 | 190 | *rows = ds->n; | |
| 626 |
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190 | *cols = ds->extrarow? ctx->m+1: ctx->m; |
| 627 | 190 | break; | |
| 628 | 190 | case DS_MAT_B: | |
| 629 | 190 | *rows = ctx->p; | |
| 630 |
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190 | *cols = ds->extrarow? ctx->m+1: ctx->m; |
| 631 | 190 | break; | |
| 632 | ✗ | case DS_MAT_T: | |
| 633 | ✗ | *rows = ds->n; | |
| 634 | ✗ | *cols = PetscDefined(USE_COMPLEX)? 2: 3; | |
| 635 | ✗ | break; | |
| 636 | ✗ | case DS_MAT_D: | |
| 637 | ✗ | *rows = ctx->p; | |
| 638 | ✗ | *cols = 1; | |
| 639 | ✗ | break; | |
| 640 | 6175 | case DS_MAT_U: | |
| 641 |
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6175 | *rows = ds->state==DS_STATE_TRUNCATED? ds->t: ds->n; |
| 642 | 6175 | *cols = ds->n; | |
| 643 | 6175 | break; | |
| 644 | 6175 | case DS_MAT_V: | |
| 645 |
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6175 | *rows = ds->state==DS_STATE_TRUNCATED? ctx->tp: ctx->p; |
| 646 | 6175 | *cols = ctx->p; | |
| 647 | 6175 | break; | |
| 648 | 6175 | case DS_MAT_X: | |
| 649 |
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6175 | *rows = ds->state==DS_STATE_TRUNCATED? ctx->tm: ctx->m; |
| 650 | 6175 | *cols = ctx->m; | |
| 651 | 6175 | break; | |
| 652 | ✗ | default: | |
| 653 | − | SETERRQ(PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Invalid t parameter"); | |
| 654 | } | ||
| 655 |
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|
3757 | PetscFunctionReturn(PETSC_SUCCESS); |
| 656 | } | ||
| 657 | |||
| 658 | 6350 | static PetscErrorCode DSGSVDSetDimensions_GSVD(DS ds,PetscInt m,PetscInt p) | |
| 659 | { | ||
| 660 | 6350 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 661 | |||
| 662 |
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6350 | PetscFunctionBegin; |
| 663 |
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6350 | DSCheckAlloc(ds,1); |
| 664 |
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6350 | if (m == PETSC_DETERMINE) { |
| 665 | ✗ | ctx->m = ds->ld; | |
| 666 |
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6350 | } else if (m != PETSC_CURRENT) { |
| 667 |
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6350 | PetscCheck(m>0 && m<=ds->ld,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of m. Must be between 1 and ld"); |
| 668 | 6350 | ctx->m = m; | |
| 669 | } | ||
| 670 |
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6350 | if (p == PETSC_DETERMINE) { |
| 671 | 30 | ctx->p = ds->n; | |
| 672 |
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6320 | } else if (p != PETSC_CURRENT) { |
| 673 |
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6320 | PetscCheck(p>0 && p<=ds->ld,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_OUTOFRANGE,"Illegal value of p. Must be between 1 and ld"); |
| 674 | 6320 | ctx->p = p; | |
| 675 | } | ||
| 676 |
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|
1262 | PetscFunctionReturn(PETSC_SUCCESS); |
| 677 | } | ||
| 678 | |||
| 679 | /*@ | ||
| 680 | DSGSVDSetDimensions - Sets the number of columns and rows for a `DSGSVD`. | ||
| 681 | |||
| 682 | Logically Collective | ||
| 683 | |||
| 684 | Input Parameters: | ||
| 685 | + ds - the direct solver context | ||
| 686 | . m - the number of columns | ||
| 687 | - p - the number of rows for the second matrix (`DS_MAT_B`) | ||
| 688 | |||
| 689 | Notes: | ||
| 690 | This call is complementary to `DSSetDimensions()`, to provide two dimensions | ||
| 691 | that are specific to this `DS` type. The number of rows for the first matrix | ||
| 692 | (`DS_MAT_A`) is set by `DSSetDimensions()`. | ||
| 693 | |||
| 694 | Use `PETSC_CURRENT` to leave any of the values unchanged. Use `PETSC_DETERMINE` | ||
| 695 | to set `m` to the leading dimension and `p` to the number of columns of $B$. | ||
| 696 | |||
| 697 | Level: intermediate | ||
| 698 | |||
| 699 | .seealso: [](sec:ds), `DSGSVD`, `DSGSVDGetDimensions()`, `DSSetDimensions()` | ||
| 700 | @*/ | ||
| 701 | 6350 | PetscErrorCode DSGSVDSetDimensions(DS ds,PetscInt m,PetscInt p) | |
| 702 | { | ||
| 703 |
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6350 | PetscFunctionBegin; |
| 704 |
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6350 | PetscValidHeaderSpecific(ds,DS_CLASSID,1); |
| 705 |
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6350 | PetscValidLogicalCollectiveInt(ds,m,2); |
| 706 |
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6350 | PetscValidLogicalCollectiveInt(ds,p,3); |
| 707 |
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6350 | PetscTryMethod(ds,"DSGSVDSetDimensions_C",(DS,PetscInt,PetscInt),(ds,m,p)); |
| 708 |
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6350 | PetscFunctionReturn(PETSC_SUCCESS); |
| 709 | } | ||
| 710 | |||
| 711 | 120 | static PetscErrorCode DSGSVDGetDimensions_GSVD(DS ds,PetscInt *m,PetscInt *p) | |
| 712 | { | ||
| 713 | 120 | DS_GSVD *ctx = (DS_GSVD*)ds->data; | |
| 714 | |||
| 715 |
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120 | PetscFunctionBegin; |
| 716 |
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120 | if (m) *m = ctx->m; |
| 717 |
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120 | if (p) *p = ctx->p; |
| 718 |
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120 | PetscFunctionReturn(PETSC_SUCCESS); |
| 719 | } | ||
| 720 | |||
| 721 | /*@ | ||
| 722 | DSGSVDGetDimensions - Returns the number of columns and rows for a `DSGSVD`. | ||
| 723 | |||
| 724 | Not Collective | ||
| 725 | |||
| 726 | Input Parameter: | ||
| 727 | . ds - the direct solver context | ||
| 728 | |||
| 729 | Output Parameters: | ||
| 730 | + m - the number of columns | ||
| 731 | - p - the number of rows for the second problem matrix (`DS_MAT_B`) | ||
| 732 | |||
| 733 | Level: intermediate | ||
| 734 | |||
| 735 | .seealso: [](sec:ds), `DSGSVD`, `DSGSVDSetDimensions()` | ||
| 736 | @*/ | ||
| 737 | 120 | PetscErrorCode DSGSVDGetDimensions(DS ds,PetscInt *m,PetscInt *p) | |
| 738 | { | ||
| 739 |
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120 | PetscFunctionBegin; |
| 740 |
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120 | PetscValidHeaderSpecific(ds,DS_CLASSID,1); |
| 741 |
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120 | PetscUseMethod(ds,"DSGSVDGetDimensions_C",(DS,PetscInt*,PetscInt*),(ds,m,p)); |
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120 | PetscFunctionReturn(PETSC_SUCCESS); |
| 743 | } | ||
| 744 | |||
| 745 | 684 | static PetscErrorCode DSDestroy_GSVD(DS ds) | |
| 746 | { | ||
| 747 |
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684 | PetscFunctionBegin; |
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684 | PetscCall(PetscFree(ds->data)); |
| 749 |
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684 | PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSGSVDSetDimensions_C",NULL)); |
| 750 |
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684 | PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSGSVDGetDimensions_C",NULL)); |
| 751 |
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140 | PetscFunctionReturn(PETSC_SUCCESS); |
| 752 | } | ||
| 753 | |||
| 754 | 16 | static PetscErrorCode DSReallocate_GSVD(DS ds,PetscInt ld) | |
| 755 | { | ||
| 756 | 16 | PetscInt i,*perm=ds->perm; | |
| 757 | |||
| 758 |
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16 | PetscFunctionBegin; |
| 759 |
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368 | for (i=0;i<DS_NUM_MAT;i++) { |
| 760 |
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352 | if (i!=DS_MAT_A && i!=DS_MAT_B && i!=DS_MAT_X && i!=DS_MAT_U && i!=DS_MAT_V && i!=DS_MAT_T && i!=DS_MAT_D) PetscCall(MatDestroy(&ds->omat[i])); |
| 761 | } | ||
| 762 | |||
| 763 |
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16 | PetscCall(DSReallocateMat_Private(ds,DS_MAT_A,ld)); |
| 764 |
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16 | PetscCall(DSReallocateMat_Private(ds,DS_MAT_B,ld)); |
| 765 |
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16 | PetscCall(DSReallocateMat_Private(ds,DS_MAT_X,ld)); |
| 766 |
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16 | PetscCall(DSReallocateMat_Private(ds,DS_MAT_U,ld)); |
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16 | PetscCall(DSReallocateMat_Private(ds,DS_MAT_V,ld)); |
| 768 |
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16 | PetscCall(DSReallocateMat_Private(ds,DS_MAT_T,ld)); |
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16 | PetscCall(DSReallocateMat_Private(ds,DS_MAT_D,ld)); |
| 770 | |||
| 771 |
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16 | PetscCall(PetscMalloc1(ld,&ds->perm)); |
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16 | PetscCall(PetscArraycpy(ds->perm,perm,ds->ld)); |
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16 | PetscCall(PetscFree(perm)); |
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4 | PetscFunctionReturn(PETSC_SUCCESS); |
| 775 | } | ||
| 776 | |||
| 777 | /*MC | ||
| 778 | DSGSVD - Dense Generalized Singular Value Decomposition. | ||
| 779 | |||
| 780 | Notes: | ||
| 781 | The problem is expressed as $AX = UC$, $BX = VS$, where $A$ and $B$ are | ||
| 782 | matrices with the same number of columns, $m$, $U$ and $V$ are orthogonal | ||
| 783 | (unitary), and $X$ is an $m\times m$ invertible matrix. The `DS` object does not | ||
| 784 | expose matrices $C$ and $S$, instead the singular values $\sigma_i$, which are | ||
| 785 | the ratios $c_i/s_i$, are returned in the arguments of `DSSolve()`. | ||
| 786 | Note that the number of columns of the returned $X$, $U$, $V$ may be smaller | ||
| 787 | in the case that some $c_i$ or $s_i$ are zero. | ||
| 788 | |||
| 789 | The number of rows of $A$ (and $U$) is the value $n$ passed with `DSSetDimensions()`. | ||
| 790 | The number of columns $m$ and the number of rows of $B$ (and $V$) must be | ||
| 791 | set via `DSGSVDSetDimensions()`. | ||
| 792 | |||
| 793 | Internally, LAPACK's representation is used, $U^*AQ = C[0,R]$, $V^*BQ = S[0, R]$, | ||
| 794 | where $X = QR^{-1}$ is computed at the end of `DSSolve()`. | ||
| 795 | |||
| 796 | If the compact storage format is selected, then a simplified problem is | ||
| 797 | solved, where $A$ and $B$ are bidiagonal (possibly with an arrow), and the | ||
| 798 | stacked matrix $\begin{bmatrix}A^* &B^*\end{bmatrix}^*$ | ||
| 799 | is assumed to have orthonormal columns. We consider two cases, | ||
| 800 | |||
| 801 | 1. $A$ and $B$ are square $m\times m$ upper bidiagonal, or | ||
| 802 | 2. $A$ is lower bidiagonal with $m+1$ rows and $B$ is square upper bidiagonal. | ||
| 803 | |||
| 804 | In these cases, $R=I$ so it corresponds to the CS decomposition {cite:p}`Gol96`. | ||
| 805 | The first matrix is stored in two diagonals of `DS_MAT_T`, while the second matrix | ||
| 806 | is stored in `DS_MAT_D` and the remaining diagonal of `DS_MAT_T`. | ||
| 807 | |||
| 808 | Allowed arguments of `DSVectors()` are `DS_MAT_U`, `DS_MAT_V` and `DS_MAT_X`. | ||
| 809 | |||
| 810 | Used DS matrices: | ||
| 811 | + `DS_MAT_A` - first problem matrix | ||
| 812 | . `DS_MAT_B` - second problem matrix | ||
| 813 | . `DS_MAT_T` - first upper bidiagonal matrix (if compact storage is selected) | ||
| 814 | . `DS_MAT_D` - second upper bidiagonal matrix (if compact storage is selected) | ||
| 815 | . `DS_MAT_U` - (upper) left generalized singular vectors | ||
| 816 | . `DS_MAT_V` - (lower) left generalized singular vectors | ||
| 817 | - `DS_MAT_X` - right generalized singular vectors | ||
| 818 | |||
| 819 | Implemented methods: | ||
| 820 | . 0 - Lapack (`_ggsvd3` if available, or `_ggsvd`) | ||
| 821 | |||
| 822 | Level: beginner | ||
| 823 | |||
| 824 | .seealso: [](sec:ds), `DSCreate()`, `DSSetType()`, `DSType`, `DSGSVDSetDimensions()` | ||
| 825 | M*/ | ||
| 826 | 684 | SLEPC_EXTERN PetscErrorCode DSCreate_GSVD(DS ds) | |
| 827 | { | ||
| 828 | 684 | DS_GSVD *ctx; | |
| 829 | |||
| 830 |
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684 | PetscFunctionBegin; |
| 831 |
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684 | PetscCall(PetscNew(&ctx)); |
| 832 | 684 | ds->data = (void*)ctx; | |
| 833 | |||
| 834 | 684 | ds->ops->allocate = DSAllocate_GSVD; | |
| 835 | 684 | ds->ops->view = DSView_GSVD; | |
| 836 | 684 | ds->ops->vectors = DSVectors_GSVD; | |
| 837 | 684 | ds->ops->sort = DSSort_GSVD; | |
| 838 | 684 | ds->ops->solve[0] = DSSolve_GSVD; | |
| 839 | #if !defined(PETSC_HAVE_MPIUNI) | ||
| 840 | 684 | ds->ops->synchronize = DSSynchronize_GSVD; | |
| 841 | #endif | ||
| 842 | 684 | ds->ops->truncate = DSTruncate_GSVD; | |
| 843 | 684 | ds->ops->update = DSUpdateExtraRow_GSVD; | |
| 844 | 684 | ds->ops->cond = DSCond_GSVD; | |
| 845 | 684 | ds->ops->matgetsize = DSMatGetSize_GSVD; | |
| 846 | 684 | ds->ops->destroy = DSDestroy_GSVD; | |
| 847 | 684 | ds->ops->reallocate = DSReallocate_GSVD; | |
| 848 |
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684 | PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSGSVDSetDimensions_C",DSGSVDSetDimensions_GSVD)); |
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684 | PetscCall(PetscObjectComposeFunction((PetscObject)ds,"DSGSVDGetDimensions_C",DSGSVDGetDimensions_GSVD)); |
| 850 |
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140 | PetscFunctionReturn(PETSC_SUCCESS); |
| 851 | } | ||
| 852 |