| 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 | Private DS routines | ||
| 12 | */ | ||
| 13 | |||
| 14 | #include <slepc/private/dsimpl.h> /*I "slepcds.h" I*/ | ||
| 15 | #include <slepcblaslapack.h> | ||
| 16 | |||
| 17 | 108234 | PetscErrorCode DSAllocateMat_Private(DS ds,DSMatType m) | |
| 18 | { | ||
| 19 | 108234 | PetscInt n,d,rows=0,cols; | |
| 20 | 108234 | PetscBool ispep,isnep; | |
| 21 | |||
| 22 |
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108234 | PetscFunctionBegin; |
| 23 | 108234 | n = ds->ld; | |
| 24 |
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108234 | PetscCall(PetscObjectTypeCompare((PetscObject)ds,DSPEP,&ispep)); |
| 25 |
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108234 | if (ispep) { |
| 26 |
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13377 | if (m==DS_MAT_A || m==DS_MAT_B || m==DS_MAT_W || m==DS_MAT_U || m==DS_MAT_X || m==DS_MAT_Y) { |
| 27 |
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12742 | PetscCall(DSPEPGetDegree(ds,&d)); |
| 28 | 12742 | n = d*ds->ld; | |
| 29 | } | ||
| 30 | } else { | ||
| 31 |
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94857 | PetscCall(PetscObjectTypeCompare((PetscObject)ds,DSNEP,&isnep)); |
| 32 |
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94857 | if (isnep) { |
| 33 |
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7033 | if (m==DS_MAT_Q || m==DS_MAT_Z || m==DS_MAT_U || m==DS_MAT_V || m==DS_MAT_X || m==DS_MAT_Y) { |
| 34 |
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849 | PetscCall(DSNEPGetMinimality(ds,&d)); |
| 35 | 849 | n = d*ds->ld; | |
| 36 | } | ||
| 37 | } | ||
| 38 | } | ||
| 39 | 108234 | cols = n; | |
| 40 | |||
| 41 |
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108234 | switch (m) { |
| 42 | case DS_MAT_T: | ||
| 43 | cols = PetscDefined(USE_COMPLEX)? 2: 3; | ||
| 44 | rows = n; | ||
| 45 | break; | ||
| 46 | 1449 | case DS_MAT_D: | |
| 47 | 1449 | cols = 1; | |
| 48 | 1449 | rows = n; | |
| 49 | 1449 | break; | |
| 50 | 19903 | case DS_MAT_X: | |
| 51 | 19903 | rows = ds->ld; | |
| 52 | 19903 | break; | |
| 53 | 912 | case DS_MAT_Y: | |
| 54 | 912 | rows = ds->ld; | |
| 55 | 912 | break; | |
| 56 | 79783 | default: | |
| 57 | 79783 | rows = n; | |
| 58 | } | ||
| 59 |
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108234 | if (ds->omat[m]) PetscCall(MatZeroEntries(ds->omat[m])); |
| 60 | else { | ||
| 61 |
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46625 | PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,rows,cols,NULL,&ds->omat[m])); |
| 62 | } | ||
| 63 |
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21437 | PetscFunctionReturn(PETSC_SUCCESS); |
| 64 | } | ||
| 65 | |||
| 66 | 331 | PetscErrorCode DSReallocateMat_Private(DS ds,DSMatType mat,PetscInt ld) | |
| 67 | { | ||
| 68 | 331 | Mat M; | |
| 69 | 331 | PetscInt i,m,n,rows,cols; | |
| 70 | 331 | PetscScalar *dst; | |
| 71 | 331 | PetscReal *rdst; | |
| 72 | 331 | const PetscScalar *src; | |
| 73 | 331 | const PetscReal *rsrc; | |
| 74 | |||
| 75 |
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331 | PetscFunctionBegin; |
| 76 |
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331 | PetscCall(MatGetSize(ds->omat[mat],&m,&n)); |
| 77 | 331 | rows = ld; | |
| 78 |
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331 | cols = m==n? ld: n; |
| 79 |
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331 | PetscCall(MatCreateSeqDense(PETSC_COMM_SELF,rows,cols,NULL,&M)); |
| 80 |
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331 | PetscCall(MatDenseGetArrayRead(ds->omat[mat],&src)); |
| 81 |
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331 | PetscCall(MatDenseGetArray(M,&dst)); |
| 82 |
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126 | if (mat==DS_MAT_T && PetscDefined(USE_COMPLEX)) { |
| 83 | 47 | rsrc = (const PetscReal*)src; | |
| 84 | 47 | rdst = (PetscReal*)dst; | |
| 85 |
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188 | for (i=0;i<3;i++) PetscCall(PetscArraycpy(rdst+i*ld,rsrc+i*ds->ld,ds->ld)); |
| 86 | } else { | ||
| 87 |
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2973 | for (i=0;i<n;i++) PetscCall(PetscArraycpy(dst+i*ld,src+i*ds->ld,ds->ld)); |
| 88 | } | ||
| 89 |
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331 | PetscCall(MatDenseRestoreArrayRead(ds->omat[mat],&src)); |
| 90 |
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331 | PetscCall(MatDenseRestoreArray(M,&dst)); |
| 91 |
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331 | PetscCall(MatDestroy(&ds->omat[mat])); |
| 92 | 331 | ds->omat[mat] = M; | |
| 93 |
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331 | PetscFunctionReturn(PETSC_SUCCESS); |
| 94 | } | ||
| 95 | |||
| 96 | 833869 | PetscErrorCode DSAllocateWork_Private(DS ds,PetscInt s,PetscInt r,PetscInt i) | |
| 97 | { | ||
| 98 |
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833869 | PetscFunctionBegin; |
| 99 |
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833869 | if (s>ds->lwork) { |
| 100 |
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16528 | PetscCall(PetscFree(ds->work)); |
| 101 |
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16528 | PetscCall(PetscMalloc1(s,&ds->work)); |
| 102 | 16528 | ds->lwork = s; | |
| 103 | } | ||
| 104 |
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833869 | if (r>ds->lrwork) { |
| 105 |
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10401 | PetscCall(PetscFree(ds->rwork)); |
| 106 |
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10401 | PetscCall(PetscMalloc1(r,&ds->rwork)); |
| 107 | 10401 | ds->lrwork = r; | |
| 108 | } | ||
| 109 |
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833869 | if (i>ds->liwork) { |
| 110 |
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6695 | PetscCall(PetscFree(ds->iwork)); |
| 111 |
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6695 | PetscCall(PetscMalloc1(i,&ds->iwork)); |
| 112 | 6695 | ds->liwork = i; | |
| 113 | } | ||
| 114 |
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161225 | PetscFunctionReturn(PETSC_SUCCESS); |
| 115 | } | ||
| 116 | |||
| 117 | /*@ | ||
| 118 | DSViewMat - Prints one of the internal `DS` matrices. | ||
| 119 | |||
| 120 | Collective | ||
| 121 | |||
| 122 | Input Parameters: | ||
| 123 | + ds - the direct solver context | ||
| 124 | . viewer - visualization context | ||
| 125 | - m - matrix to display | ||
| 126 | |||
| 127 | Note: | ||
| 128 | Works only for `ascii` viewers. Set the viewer to Matlab format if | ||
| 129 | you want to paste the output into Matlab. | ||
| 130 | |||
| 131 | Level: developer | ||
| 132 | |||
| 133 | .seealso: [](sec:ds), `DSView()` | ||
| 134 | @*/ | ||
| 135 | 300 | PetscErrorCode DSViewMat(DS ds,PetscViewer viewer,DSMatType m) | |
| 136 | { | ||
| 137 | 300 | PetscInt i,j,rows,cols; | |
| 138 | 300 | const PetscScalar *M=NULL,*v; | |
| 139 | 300 | PetscViewerFormat format; | |
| 140 | #if defined(PETSC_USE_COMPLEX) | ||
| 141 | 150 | PetscBool allreal = PETSC_TRUE; | |
| 142 | 150 | const PetscReal *vr; | |
| 143 | #endif | ||
| 144 | |||
| 145 |
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300 | PetscFunctionBegin; |
| 146 |
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300 | PetscValidHeaderSpecific(ds,DS_CLASSID,1); |
| 147 |
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300 | PetscValidLogicalCollectiveEnum(ds,m,3); |
| 148 |
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300 | DSCheckValidMat(ds,m,3); |
| 149 |
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300 | if (!viewer) PetscCall(PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)ds),&viewer)); |
| 150 |
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300 | PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); |
| 151 |
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300 | PetscCheckSameComm(ds,1,viewer,2); |
| 152 |
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300 | PetscCall(PetscViewerGetFormat(viewer,&format)); |
| 153 |
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300 | if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) PetscFunctionReturn(PETSC_SUCCESS); |
| 154 |
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300 | PetscCall(PetscViewerASCIIUseTabs(viewer,PETSC_FALSE)); |
| 155 |
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300 | PetscCall(DSMatGetSize(ds,m,&rows,&cols)); |
| 156 |
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300 | PetscCall(MatDenseGetArrayRead(ds->omat[m],&M)); |
| 157 | #if defined(PETSC_USE_COMPLEX) | ||
| 158 | /* determine if matrix has all real values */ | ||
| 159 |
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150 | if (m!=DS_MAT_T && m!=DS_MAT_D) { |
| 160 | /* determine if matrix has all real values */ | ||
| 161 | 145 | v = M; | |
| 162 |
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2020 | for (i=0;i<rows;i++) |
| 163 |
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20775 | for (j=0;j<cols;j++) |
| 164 |
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18900 | if (PetscImaginaryPart(v[i+j*ds->ld])) { allreal = PETSC_FALSE; break; } |
| 165 | } | ||
| 166 |
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150 | if (m==DS_MAT_T) cols=3; |
| 167 | #endif | ||
| 168 |
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300 | if (format == PETSC_VIEWER_ASCII_MATLAB) { |
| 169 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"%% Size = %" PetscInt_FMT " %" PetscInt_FMT "\n",rows,cols)); | |
| 170 | ✗ | PetscCall(PetscViewerASCIIPrintf(viewer,"%s = [\n",DSMatName[m])); | |
| 171 |
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300 | } else PetscCall(PetscViewerASCIIPrintf(viewer,"Matrix %s =\n",DSMatName[m])); |
| 172 | |||
| 173 |
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4200 | for (i=0;i<rows;i++) { |
| 174 | 3900 | v = M+i; | |
| 175 | #if defined(PETSC_USE_COMPLEX) | ||
| 176 | 1950 | vr = (const PetscReal*)M+i; /* handle compact storage, 2nd column is in imaginary part of 1st column */ | |
| 177 | #endif | ||
| 178 |
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41850 | for (j=0;j<cols;j++) { |
| 179 | #if defined(PETSC_USE_COMPLEX) | ||
| 180 |
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18975 | if (m!=DS_MAT_T && m!=DS_MAT_D) { |
| 181 |
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18900 | if (allreal) PetscCall(PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)PetscRealPart(*v))); |
| 182 | ✗ | else PetscCall(PetscViewerASCIIPrintf(viewer,"%18.16e%+18.16ei ",(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v))); | |
| 183 |
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75 | } else PetscCall(PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*vr)); |
| 184 | #else | ||
| 185 |
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18975 | PetscCall(PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*v)); |
| 186 | #endif | ||
| 187 | 37950 | v += ds->ld; | |
| 188 | #if defined(PETSC_USE_COMPLEX) | ||
| 189 |
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18975 | if (m==DS_MAT_T) vr += ds->ld; |
| 190 | #endif | ||
| 191 | } | ||
| 192 |
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3900 | PetscCall(PetscViewerASCIIPrintf(viewer,"\n")); |
| 193 | } | ||
| 194 |
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300 | PetscCall(MatDenseRestoreArrayRead(ds->omat[m],&M)); |
| 195 | |||
| 196 |
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300 | if (format == PETSC_VIEWER_ASCII_MATLAB) PetscCall(PetscViewerASCIIPrintf(viewer,"];\n")); |
| 197 |
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300 | PetscCall(PetscViewerASCIIUseTabs(viewer,PETSC_TRUE)); |
| 198 |
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300 | PetscCall(PetscViewerFlush(viewer)); |
| 199 |
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60 | PetscFunctionReturn(PETSC_SUCCESS); |
| 200 | } | ||
| 201 | |||
| 202 | 190948 | PetscErrorCode DSSortEigenvalues_Private(DS ds,PetscScalar *wr,PetscScalar *wi,PetscInt *perm,PetscBool isghiep) | |
| 203 | { | ||
| 204 | 190948 | PetscScalar re,im,wi0; | |
| 205 | 190948 | PetscInt n,i,j,result,tmp1,tmp2=0,d=1; | |
| 206 | |||
| 207 |
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190948 | PetscFunctionBegin; |
| 208 | 190948 | n = ds->t; /* sort only first t pairs if truncated */ | |
| 209 | /* insertion sort */ | ||
| 210 | 190948 | i=ds->l+1; | |
| 211 | #if !defined(PETSC_USE_COMPLEX) | ||
| 212 |
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93876 | if (wi && wi[perm[i-1]]!=0.0) i++; /* initial value is complex */ |
| 213 | #else | ||
| 214 |
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97072 | if (isghiep && PetscImaginaryPart(wr[perm[i-1]])!=0.0) i++; |
| 215 | #endif | ||
| 216 |
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2360068 | for (;i<n;i+=d) { |
| 217 | 2169120 | re = wr[perm[i]]; | |
| 218 |
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2169120 | if (wi) im = wi[perm[i]]; |
| 219 | else im = 0.0; | ||
| 220 | 2169120 | tmp1 = perm[i]; | |
| 221 | #if !defined(PETSC_USE_COMPLEX) | ||
| 222 |
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1130839 | if (im!=0.0) { d = 2; tmp2 = perm[i+1]; } |
| 223 | else d = 1; | ||
| 224 | #else | ||
| 225 |
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1038281 | if (isghiep && PetscImaginaryPart(re)!=0.0) { d = 2; tmp2 = perm[i+1]; } |
| 226 | else d = 1; | ||
| 227 | #endif | ||
| 228 | 2169120 | j = i-1; | |
| 229 |
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2169120 | if (wi) wi0 = wi[perm[j]]; |
| 230 | else wi0 = 0.0; | ||
| 231 |
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2169120 | PetscCall(SlepcSCCompare(ds->sc,re,im,wr[perm[j]],wi0,&result)); |
| 232 |
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8363602 | while (result<0 && j>=ds->l) { |
| 233 | 7741868 | perm[j+d] = perm[j]; | |
| 234 | 7741868 | j--; | |
| 235 | #if !defined(PETSC_USE_COMPLEX) | ||
| 236 |
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4929491 | if (wi && wi[perm[j+1]]!=0) |
| 237 | #else | ||
| 238 |
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2812377 | if (isghiep && PetscImaginaryPart(wr[perm[j+1]])!=0) |
| 239 | #endif | ||
| 240 | 206053 | { perm[j+d] = perm[j]; j--; } | |
| 241 | |||
| 242 |
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7741868 | if (j>=ds->l) { |
| 243 |
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7120134 | if (wi) wi0 = wi[perm[j]]; |
| 244 | else wi0 = 0.0; | ||
| 245 |
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17031122 | PetscCall(SlepcSCCompare(ds->sc,re,im,wr[perm[j]],wi0,&result)); |
| 246 | } | ||
| 247 | } | ||
| 248 | 2169120 | perm[j+1] = tmp1; | |
| 249 |
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2169120 | if (d==2) perm[j+2] = tmp2; |
| 250 | } | ||
| 251 |
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37000 | PetscFunctionReturn(PETSC_SUCCESS); |
| 252 | } | ||
| 253 | |||
| 254 | 69651 | PetscErrorCode DSSortEigenvaluesReal_Private(DS ds,PetscReal *eig,PetscInt *perm) | |
| 255 | { | ||
| 256 | 69651 | PetscScalar re; | |
| 257 | 69651 | PetscInt i,j,result,tmp,l,n; | |
| 258 | |||
| 259 |
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69651 | PetscFunctionBegin; |
| 260 | 69651 | n = ds->t; /* sort only first t pairs if truncated */ | |
| 261 | 69651 | l = ds->l; | |
| 262 | /* insertion sort */ | ||
| 263 |
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961310 | for (i=l+1;i<n;i++) { |
| 264 | 891659 | re = eig[perm[i]]; | |
| 265 | 891659 | j = i-1; | |
| 266 |
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891659 | PetscCall(SlepcSCCompare(ds->sc,re,0.0,eig[perm[j]],0.0,&result)); |
| 267 |
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5326463 | while (result<0 && j>=l) { |
| 268 | 4986341 | tmp = perm[j]; perm[j] = perm[j+1]; perm[j+1] = tmp; j--; | |
| 269 |
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10864341 | if (j>=l) PetscCall(SlepcSCCompare(ds->sc,re,0.0,eig[perm[j]],0.0,&result)); |
| 270 | } | ||
| 271 | } | ||
| 272 |
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13420 | PetscFunctionReturn(PETSC_SUCCESS); |
| 273 | } | ||
| 274 | |||
| 275 | /* | ||
| 276 | Permute comumns [istart..iend-1] of [mat] according to perm. Columns have length n | ||
| 277 | */ | ||
| 278 | 218910 | PetscErrorCode DSPermuteColumns_Private(DS ds,PetscInt istart,PetscInt iend,PetscInt n,DSMatType mat,PetscInt *perm) | |
| 279 | { | ||
| 280 | 218910 | PetscInt i,j,k,p,ld; | |
| 281 | 218910 | PetscScalar *Q,rtmp; | |
| 282 | |||
| 283 |
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218910 | PetscFunctionBegin; |
| 284 | 218910 | ld = ds->ld; | |
| 285 |
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218910 | PetscCall(MatDenseGetArray(ds->omat[mat],&Q)); |
| 286 |
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3012022 | for (i=istart;i<iend;i++) { |
| 287 | 2793112 | p = perm[i]; | |
| 288 |
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2793112 | if (p != i) { |
| 289 | 987847 | j = i + 1; | |
| 290 |
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8187907 | while (perm[j] != i) j++; |
| 291 | 987847 | perm[j] = p; perm[i] = i; | |
| 292 | /* swap columns i and j */ | ||
| 293 |
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27258048 | for (k=0;k<n;k++) { |
| 294 | 26270201 | rtmp = Q[k+p*ld]; Q[k+p*ld] = Q[k+i*ld]; Q[k+i*ld] = rtmp; | |
| 295 | } | ||
| 296 | } | ||
| 297 | } | ||
| 298 |
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218910 | PetscCall(MatDenseRestoreArray(ds->omat[mat],&Q)); |
| 299 |
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42417 | PetscFunctionReturn(PETSC_SUCCESS); |
| 300 | } | ||
| 301 | |||
| 302 | /* | ||
| 303 | The same as DSPermuteColumns_Private but for two matrices [mat1] and [mat2] | ||
| 304 | */ | ||
| 305 | 3093 | PetscErrorCode DSPermuteColumnsTwo_Private(DS ds,PetscInt istart,PetscInt iend,PetscInt n,DSMatType mat1,DSMatType mat2,PetscInt *perm) | |
| 306 | { | ||
| 307 | 3093 | PetscInt i,j,k,p,ld; | |
| 308 | 3093 | PetscScalar *Q,*Z,rtmp,rtmp2; | |
| 309 | |||
| 310 |
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3093 | PetscFunctionBegin; |
| 311 | 3093 | ld = ds->ld; | |
| 312 |
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3093 | PetscCall(MatDenseGetArray(ds->omat[mat1],&Q)); |
| 313 |
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3093 | PetscCall(MatDenseGetArray(ds->omat[mat2],&Z)); |
| 314 |
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75144 | for (i=istart;i<iend;i++) { |
| 315 | 72051 | p = perm[i]; | |
| 316 |
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72051 | if (p != i) { |
| 317 | 51289 | j = i + 1; | |
| 318 |
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504889 | while (perm[j] != i) j++; |
| 319 | 51289 | perm[j] = p; perm[i] = i; | |
| 320 | /* swap columns i and j */ | ||
| 321 |
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837685 | for (k=0;k<n;k++) { |
| 322 | 786396 | rtmp = Q[k+p*ld]; Q[k+p*ld] = Q[k+i*ld]; Q[k+i*ld] = rtmp; | |
| 323 | 786396 | rtmp2 = Z[k+p*ld]; Z[k+p*ld] = Z[k+i*ld]; Z[k+i*ld] = rtmp2; | |
| 324 | } | ||
| 325 | } | ||
| 326 | } | ||
| 327 |
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3093 | PetscCall(MatDenseRestoreArray(ds->omat[mat1],&Q)); |
| 328 |
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3093 | PetscCall(MatDenseRestoreArray(ds->omat[mat2],&Z)); |
| 329 |
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618 | PetscFunctionReturn(PETSC_SUCCESS); |
| 330 | } | ||
| 331 | |||
| 332 | /* | ||
| 333 | Permute rows [istart..iend-1] of [mat] according to perm. Rows have length m | ||
| 334 | */ | ||
| 335 | ✗ | PetscErrorCode DSPermuteRows_Private(DS ds,PetscInt istart,PetscInt iend,PetscInt m,DSMatType mat,PetscInt *perm) | |
| 336 | { | ||
| 337 | ✗ | PetscInt i,j,k,p,ld; | |
| 338 | ✗ | PetscScalar *Q,rtmp; | |
| 339 | |||
| 340 | ✗ | PetscFunctionBegin; | |
| 341 | ✗ | ld = ds->ld; | |
| 342 | ✗ | PetscCall(MatDenseGetArray(ds->omat[mat],&Q)); | |
| 343 | ✗ | for (i=istart;i<iend;i++) { | |
| 344 | ✗ | p = perm[i]; | |
| 345 | ✗ | if (p != i) { | |
| 346 | ✗ | j = i + 1; | |
| 347 | ✗ | while (perm[j] != i) j++; | |
| 348 | ✗ | perm[j] = p; perm[i] = i; | |
| 349 | /* swap rows i and j */ | ||
| 350 | ✗ | for (k=0;k<m;k++) { | |
| 351 | ✗ | rtmp = Q[p+k*ld]; Q[p+k*ld] = Q[i+k*ld]; Q[i+k*ld] = rtmp; | |
| 352 | } | ||
| 353 | } | ||
| 354 | } | ||
| 355 | ✗ | PetscCall(MatDenseRestoreArray(ds->omat[mat],&Q)); | |
| 356 | ✗ | PetscFunctionReturn(PETSC_SUCCESS); | |
| 357 | } | ||
| 358 | |||
| 359 | /* | ||
| 360 | Permute columns [istart..iend-1] of [mat1] and [mat2] according to perm. | ||
| 361 | Columns of [mat1] have length n, columns of [mat2] have length m | ||
| 362 | */ | ||
| 363 | 25859 | PetscErrorCode DSPermuteBoth_Private(DS ds,PetscInt istart,PetscInt iend,PetscInt n,PetscInt m,DSMatType mat1,DSMatType mat2,PetscInt *perm) | |
| 364 | { | ||
| 365 | 25859 | PetscInt i,j,k,p,ld; | |
| 366 | 25859 | PetscScalar *U,*V,rtmp; | |
| 367 | |||
| 368 |
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25859 | PetscFunctionBegin; |
| 369 | 25859 | ld = ds->ld; | |
| 370 |
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25859 | PetscCall(MatDenseGetArray(ds->omat[mat1],&U)); |
| 371 |
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25859 | PetscCall(MatDenseGetArray(ds->omat[mat2],&V)); |
| 372 |
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315545 | for (i=istart;i<iend;i++) { |
| 373 | 289686 | p = perm[i]; | |
| 374 |
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289686 | if (p != i) { |
| 375 | 67617 | j = i + 1; | |
| 376 |
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651017 | while (perm[j] != i) j++; |
| 377 | 67617 | perm[j] = p; perm[i] = i; | |
| 378 | /* swap columns i and j of U */ | ||
| 379 |
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3357219 | for (k=0;k<n;k++) { |
| 380 | 3289602 | rtmp = U[k+p*ld]; U[k+p*ld] = U[k+i*ld]; U[k+i*ld] = rtmp; | |
| 381 | } | ||
| 382 | /* swap columns i and j of V */ | ||
| 383 |
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2143293 | for (k=0;k<m;k++) { |
| 384 | 2075676 | rtmp = V[k+p*ld]; V[k+p*ld] = V[k+i*ld]; V[k+i*ld] = rtmp; | |
| 385 | } | ||
| 386 | } | ||
| 387 | } | ||
| 388 |
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25859 | PetscCall(MatDenseRestoreArray(ds->omat[mat1],&U)); |
| 389 |
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25859 | PetscCall(MatDenseRestoreArray(ds->omat[mat2],&V)); |
| 390 |
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4922 | PetscFunctionReturn(PETSC_SUCCESS); |
| 391 | } | ||
| 392 | |||
| 393 | /*@ | ||
| 394 | DSSetIdentity - Copy the identity (a diagonal matrix with ones on the | ||
| 395 | diagonal) on the active part of a matrix. | ||
| 396 | |||
| 397 | Logically Collective | ||
| 398 | |||
| 399 | Input Parameters: | ||
| 400 | + ds - the direct solver context | ||
| 401 | - mat - the matrix to modify | ||
| 402 | |||
| 403 | Level: intermediate | ||
| 404 | |||
| 405 | .seealso: [](sec:ds), `DSGetMat()` | ||
| 406 | @*/ | ||
| 407 | 106700 | PetscErrorCode DSSetIdentity(DS ds,DSMatType mat) | |
| 408 | { | ||
| 409 | 106700 | PetscScalar *A; | |
| 410 | 106700 | PetscInt i,ld,n,l; | |
| 411 | |||
| 412 |
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106700 | PetscFunctionBegin; |
| 413 |
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106700 | PetscValidHeaderSpecific(ds,DS_CLASSID,1); |
| 414 |
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106700 | PetscValidLogicalCollectiveEnum(ds,mat,2); |
| 415 |
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106700 | DSCheckValidMat(ds,mat,2); |
| 416 | |||
| 417 |
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106700 | PetscCall(DSGetDimensions(ds,&n,&l,NULL,NULL)); |
| 418 |
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106700 | PetscCall(DSGetLeadingDimension(ds,&ld)); |
| 419 |
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106700 | PetscCall(PetscLogEventBegin(DS_Other,ds,0,0,0)); |
| 420 |
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106700 | PetscCall(MatDenseGetArray(ds->omat[mat],&A)); |
| 421 |
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106700 | PetscCall(PetscArrayzero(A+l*ld,ld*(n-l))); |
| 422 |
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1487662 | for (i=l;i<n;i++) A[i+i*ld] = 1.0; |
| 423 |
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106700 | PetscCall(MatDenseRestoreArray(ds->omat[mat],&A)); |
| 424 |
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106700 | PetscCall(PetscLogEventEnd(DS_Other,ds,0,0,0)); |
| 425 |
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|
20545 | PetscFunctionReturn(PETSC_SUCCESS); |
| 426 | } | ||
| 427 | |||
| 428 | /*@ | ||
| 429 | DSOrthogonalize - Orthogonalize the columns of a matrix. | ||
| 430 | |||
| 431 | Logically Collective | ||
| 432 | |||
| 433 | Input Parameters: | ||
| 434 | + ds - the direct solver context | ||
| 435 | . mat - a matrix | ||
| 436 | - cols - number of columns to orthogonalize (starting from column zero) | ||
| 437 | |||
| 438 | Output Parameter: | ||
| 439 | . lindcols - (optional) number of linearly independent columns of the matrix | ||
| 440 | |||
| 441 | Level: developer | ||
| 442 | |||
| 443 | .seealso: [](sec:ds), `DSPseudoOrthogonalize()` | ||
| 444 | @*/ | ||
| 445 | 16854 | PetscErrorCode DSOrthogonalize(DS ds,DSMatType mat,PetscInt cols,PetscInt *lindcols) | |
| 446 | { | ||
| 447 | 16854 | PetscInt n,l,ld; | |
| 448 | 16854 | PetscBLASInt ld_,rA,cA,info,ltau,lw; | |
| 449 | 16854 | PetscScalar *A,*tau,*w,saux,dummy; | |
| 450 | |||
| 451 |
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16854 | PetscFunctionBegin; |
| 452 |
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16854 | PetscValidHeaderSpecific(ds,DS_CLASSID,1); |
| 453 |
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16854 | DSCheckAlloc(ds,1); |
| 454 |
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16854 | PetscValidLogicalCollectiveEnum(ds,mat,2); |
| 455 |
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16854 | DSCheckValidMat(ds,mat,2); |
| 456 |
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16854 | PetscValidLogicalCollectiveInt(ds,cols,3); |
| 457 | |||
| 458 |
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16854 | PetscCall(DSGetDimensions(ds,&n,&l,NULL,NULL)); |
| 459 |
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16854 | PetscCall(DSGetLeadingDimension(ds,&ld)); |
| 460 | 16854 | n = n - l; | |
| 461 |
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16854 | PetscCheck(cols<=n,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONG,"Invalid number of columns"); |
| 462 |
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16854 | if (n == 0 || cols == 0) PetscFunctionReturn(PETSC_SUCCESS); |
| 463 | |||
| 464 |
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16854 | PetscCall(PetscLogEventBegin(DS_Other,ds,0,0,0)); |
| 465 |
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16854 | PetscCall(PetscFPTrapPush(PETSC_FP_TRAP_OFF)); |
| 466 |
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16854 | PetscCall(MatDenseGetArray(ds->omat[mat],&A)); |
| 467 |
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16854 | PetscCall(PetscBLASIntCast(PetscMin(cols,n),<au)); |
| 468 |
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16854 | PetscCall(PetscBLASIntCast(ld,&ld_)); |
| 469 |
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16854 | PetscCall(PetscBLASIntCast(n,&rA)); |
| 470 |
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16854 | PetscCall(PetscBLASIntCast(cols,&cA)); |
| 471 | 16854 | lw = -1; | |
| 472 |
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16854 | PetscCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&rA,&cA,A,&ld_,&dummy,&saux,&lw,&info)); |
| 473 |
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16854 | SlepcCheckLapackInfo("geqrf",info); |
| 474 | 16854 | lw = (PetscBLASInt)PetscRealPart(saux); | |
| 475 |
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16854 | PetscCall(DSAllocateWork_Private(ds,lw+ltau,0,0)); |
| 476 | 16854 | tau = ds->work; | |
| 477 | 16854 | w = &tau[ltau]; | |
| 478 |
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16854 | PetscCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&rA,&cA,&A[ld*l+l],&ld_,tau,w,&lw,&info)); |
| 479 |
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16854 | SlepcCheckLapackInfo("geqrf",info); |
| 480 |
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16854 | PetscCallBLAS("LAPACKorgqr",LAPACKorgqr_(&rA,<au,<au,&A[ld*l+l],&ld_,tau,w,&lw,&info)); |
| 481 |
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16854 | SlepcCheckLapackInfo("orgqr",info); |
| 482 |
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16854 | if (lindcols) *lindcols = ltau; |
| 483 |
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16854 | PetscCall(PetscFPTrapPop()); |
| 484 |
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16854 | PetscCall(MatDenseRestoreArray(ds->omat[mat],&A)); |
| 485 |
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16854 | PetscCall(PetscLogEventEnd(DS_Other,ds,0,0,0)); |
| 486 |
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16854 | PetscCall(PetscObjectStateIncrease((PetscObject)ds)); |
| 487 |
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16854 | PetscFunctionReturn(PETSC_SUCCESS); |
| 488 | } | ||
| 489 | |||
| 490 | /* | ||
| 491 | Compute C <- a*A*B + b*C, where | ||
| 492 | ldC, the leading dimension of C, | ||
| 493 | ldA, the leading dimension of A, | ||
| 494 | rA, cA, rows and columns of A, | ||
| 495 | At, if true use the transpose of A instead, | ||
| 496 | ldB, the leading dimension of B, | ||
| 497 | rB, cB, rows and columns of B, | ||
| 498 | Bt, if true use the transpose of B instead | ||
| 499 | */ | ||
| 500 | 550 | static PetscErrorCode SlepcMatDenseMult(PetscScalar *C,PetscInt _ldC,PetscScalar b,PetscScalar a,const PetscScalar *A,PetscInt _ldA,PetscInt rA,PetscInt cA,PetscBool At,const PetscScalar *B,PetscInt _ldB,PetscInt rB,PetscInt cB,PetscBool Bt) | |
| 501 | { | ||
| 502 | 550 | PetscInt tmp; | |
| 503 | 550 | PetscBLASInt m, n, k, ldA, ldB, ldC; | |
| 504 | 550 | const char *N = "N", *T = "C", *qA = N, *qB = N; | |
| 505 | |||
| 506 |
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550 | PetscFunctionBegin; |
| 507 |
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550 | if ((rA == 0) || (cB == 0)) PetscFunctionReturn(PETSC_SUCCESS); |
| 508 |
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550 | PetscAssertPointer(C,1); |
| 509 |
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550 | PetscAssertPointer(A,5); |
| 510 |
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550 | PetscAssertPointer(B,10); |
| 511 |
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550 | PetscCall(PetscBLASIntCast(_ldA,&ldA)); |
| 512 |
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550 | PetscCall(PetscBLASIntCast(_ldB,&ldB)); |
| 513 |
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550 | PetscCall(PetscBLASIntCast(_ldC,&ldC)); |
| 514 | |||
| 515 | /* Transpose if needed */ | ||
| 516 |
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550 | if (At) tmp = rA, rA = cA, cA = tmp, qA = T; |
| 517 |
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550 | if (Bt) tmp = rB, rB = cB, cB = tmp, qB = T; |
| 518 | |||
| 519 | /* Check size */ | ||
| 520 |
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550 | PetscCheck(cA==rB,PETSC_COMM_SELF,PETSC_ERR_PLIB,"Matrix dimensions do not match"); |
| 521 | |||
| 522 | /* Do stub */ | ||
| 523 |
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550 | if ((rA == 1) && (cA == 1) && (cB == 1)) { |
| 524 | ✗ | if (!At && !Bt) *C = *A * *B; | |
| 525 | ✗ | else if (At && !Bt) *C = PetscConj(*A) * *B; | |
| 526 | ✗ | else if (!At && Bt) *C = *A * PetscConj(*B); | |
| 527 | ✗ | else *C = PetscConj(*A) * PetscConj(*B); | |
| 528 | ✗ | m = n = k = 1; | |
| 529 | } else { | ||
| 530 |
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550 | PetscCall(PetscBLASIntCast(rA,&m)); |
| 531 |
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550 | PetscCall(PetscBLASIntCast(cB,&n)); |
| 532 |
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550 | PetscCall(PetscBLASIntCast(cA,&k)); |
| 533 |
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550 | PetscCallBLAS("BLASgemm",BLASgemm_(qA,qB,&m,&n,&k,&a,(PetscScalar*)A,&ldA,(PetscScalar*)B,&ldB,&b,C,&ldC)); |
| 534 | } | ||
| 535 | |||
| 536 |
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550 | PetscCall(PetscLogFlops(2.0*m*n*k)); |
| 537 |
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550 | PetscFunctionReturn(PETSC_SUCCESS); |
| 538 | } | ||
| 539 | |||
| 540 | /*@ | ||
| 541 | DSPseudoOrthogonalize - Orthogonalize the columns of a matrix with Modified | ||
| 542 | Gram-Schmidt in an indefinite inner product space defined by a signature. | ||
| 543 | |||
| 544 | Logically Collective | ||
| 545 | |||
| 546 | Input Parameters: | ||
| 547 | + ds - the direct solver context | ||
| 548 | . mat - the matrix | ||
| 549 | . cols - number of columns to orthogonalize (starting from column zero) | ||
| 550 | - s - the signature that defines the inner product | ||
| 551 | |||
| 552 | Output Parameters: | ||
| 553 | + lindcols - (optional) linearly independent columns of the matrix | ||
| 554 | - ns - (optional) the new signature of the vectors | ||
| 555 | |||
| 556 | Note: | ||
| 557 | After the call the matrix satisfies $A^*\Omega A = \tilde\Omega$, where | ||
| 558 | $\Omega$ is the input signature, represented as a list of $\pm 1$ values | ||
| 559 | in `s`, and the new signature $\tilde\Omega$ is stored similarly in `ns`. | ||
| 560 | |||
| 561 | Level: developer | ||
| 562 | |||
| 563 | .seealso: [](sec:ds), `DSOrthogonalize()` | ||
| 564 | @*/ | ||
| 565 | 10 | PetscErrorCode DSPseudoOrthogonalize(DS ds,DSMatType mat,PetscInt cols,PetscReal s[],PetscInt *lindcols,PetscReal ns[]) | |
| 566 | { | ||
| 567 | 10 | PetscInt i,j,k,l,n,ld; | |
| 568 | 10 | PetscBLASInt info,one=1,zero=0,rA_,ld_; | |
| 569 | 10 | PetscScalar *A,*A_,*m,*h,nr0; | |
| 570 | 10 | PetscReal nr_o,nr,nr_abs,*ns_,done=1.0; | |
| 571 | |||
| 572 |
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10 | PetscFunctionBegin; |
| 573 |
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10 | PetscValidHeaderSpecific(ds,DS_CLASSID,1); |
| 574 |
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10 | DSCheckAlloc(ds,1); |
| 575 |
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10 | PetscValidLogicalCollectiveEnum(ds,mat,2); |
| 576 |
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10 | DSCheckValidMat(ds,mat,2); |
| 577 |
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10 | PetscValidLogicalCollectiveInt(ds,cols,3); |
| 578 |
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10 | PetscAssertPointer(s,4); |
| 579 |
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10 | PetscCall(DSGetDimensions(ds,&n,&l,NULL,NULL)); |
| 580 |
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10 | PetscCall(DSGetLeadingDimension(ds,&ld)); |
| 581 | 10 | n = n - l; | |
| 582 |
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10 | PetscCheck(cols<=n,PetscObjectComm((PetscObject)ds),PETSC_ERR_ARG_WRONG,"Invalid number of columns"); |
| 583 |
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10 | if (n == 0 || cols == 0) PetscFunctionReturn(PETSC_SUCCESS); |
| 584 |
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10 | PetscCall(PetscLogEventBegin(DS_Other,ds,0,0,0)); |
| 585 |
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10 | PetscCall(PetscBLASIntCast(n,&rA_)); |
| 586 |
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10 | PetscCall(PetscBLASIntCast(ld,&ld_)); |
| 587 |
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10 | PetscCall(MatDenseGetArray(ds->omat[mat],&A_)); |
| 588 | 10 | A = &A_[ld*l+l]; | |
| 589 |
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20 | PetscCall(DSAllocateWork_Private(ds,n+cols,ns?0:cols,0)); |
| 590 | 10 | m = ds->work; | |
| 591 | 10 | h = &m[n]; | |
| 592 |
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10 | ns_ = ns ? ns : ds->rwork; |
| 593 |
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110 | for (i=0; i<cols; i++) { |
| 594 | /* m <- diag(s)*A[i] */ | ||
| 595 |
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1100 | for (k=0; k<n; k++) m[k] = s[k]*A[k+i*ld]; |
| 596 | /* nr_o <- mynorm(A[i]'*m), mynorm(x) = sign(x)*sqrt(|x|) */ | ||
| 597 |
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100 | PetscCall(SlepcMatDenseMult(&nr0,1,0.0,1.0,&A[ld*i],ld,n,1,PETSC_TRUE,m,n,n,1,PETSC_FALSE)); |
| 598 |
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100 | nr = nr_o = PetscSign(PetscRealPart(nr0))*PetscSqrtReal(PetscAbsScalar(nr0)); |
| 599 |
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160 | for (j=0; j<3 && i>0; j++) { |
| 600 | /* h <- A[0:i-1]'*m */ | ||
| 601 |
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150 | PetscCall(SlepcMatDenseMult(h,i,0.0,1.0,A,ld,n,i,PETSC_TRUE,m,n,n,1,PETSC_FALSE)); |
| 602 | /* h <- diag(ns)*h */ | ||
| 603 |
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990 | for (k=0; k<i; k++) h[k] *= ns_[k]; |
| 604 | /* A[i] <- A[i] - A[0:i-1]*h */ | ||
| 605 |
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150 | PetscCall(SlepcMatDenseMult(&A[ld*i],ld,1.0,-1.0,A,ld,n,i,PETSC_FALSE,h,i,i,1,PETSC_FALSE)); |
| 606 | /* m <- diag(s)*A[i] */ | ||
| 607 |
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1650 | for (k=0; k<n; k++) m[k] = s[k]*A[k+i*ld]; |
| 608 | /* nr_o <- mynorm(A[i]'*m) */ | ||
| 609 |
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150 | PetscCall(SlepcMatDenseMult(&nr0,1,0.0,1.0,&A[ld*i],ld,n,1,PETSC_TRUE,m,n,n,1,PETSC_FALSE)); |
| 610 |
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150 | nr = PetscSign(PetscRealPart(nr0))*PetscSqrtReal(PetscAbsScalar(nr0)); |
| 611 |
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150 | PetscCheck(PetscAbs(nr)>PETSC_MACHINE_EPSILON,PETSC_COMM_SELF,PETSC_ERR_CONV_FAILED,"Linear dependency detected"); |
| 612 |
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150 | if (PetscAbs(nr) > 0.7*PetscAbs(nr_o)) break; |
| 613 | 60 | nr_o = nr; | |
| 614 | } | ||
| 615 |
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100 | ns_[i] = PetscSign(nr); |
| 616 | /* A[i] <- A[i]/|nr| */ | ||
| 617 |
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100 | nr_abs = PetscAbs(nr); |
| 618 |
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100 | PetscCallBLAS("LAPACKlascl",LAPACKlascl_("G",&zero,&zero,&nr_abs,&done,&rA_,&one,A+i*ld,&ld_,&info)); |
| 619 |
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100 | SlepcCheckLapackInfo("lascl",info); |
| 620 | } | ||
| 621 |
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10 | PetscCall(MatDenseRestoreArray(ds->omat[mat],&A_)); |
| 622 |
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10 | PetscCall(PetscLogEventEnd(DS_Other,ds,0,0,0)); |
| 623 |
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10 | PetscCall(PetscObjectStateIncrease((PetscObject)ds)); |
| 624 |
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10 | if (lindcols) *lindcols = cols; |
| 625 |
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2 | PetscFunctionReturn(PETSC_SUCCESS); |
| 626 | } | ||
| 627 |