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1298 slepc 1
/*                      
2
 
3
   SLEPc singular value solver: "trlanczos"
4
 
5
   Method: Golub-Kahan-Lanczos bidiagonalization with thick-restart
6
 
1397 slepc 7
   Last update: Jun 2007
1298 slepc 8
 
1376 slepc 9
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
10
      SLEPc - Scalable Library for Eigenvalue Problem Computations
11
      Copyright (c) 2002-2007, Universidad Politecnica de Valencia, Spain
12
 
13
      This file is part of SLEPc. See the README file for conditions of use
14
      and additional information.
15
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
1298 slepc 16
*/
1376 slepc 17
 
1298 slepc 18
#include "src/svd/svdimpl.h"                /*I "slepcsvd.h" I*/
1414 slepc 19
#include "src/ip/ipimpl.h"
1298 slepc 20
#include "slepcblaslapack.h"
21
 
22
typedef struct {
23
  PetscTruth oneside;
24
} SVD_TRLANCZOS;
25
 
26
#undef __FUNCT__  
27
#define __FUNCT__ "SVDSetUp_TRLANCZOS"
28
PetscErrorCode SVDSetUp_TRLANCZOS(SVD svd)
29
{
30
  PetscErrorCode  ierr;
1504 slepc 31
  PetscInt        i,N;
1298 slepc 32
 
33
  PetscFunctionBegin;
1314 slepc 34
  ierr = SVDMatGetSize(svd,PETSC_NULL,&N);CHKERRQ(ierr);
1298 slepc 35
  if (svd->ncv == PETSC_DECIDE)
1314 slepc 36
    svd->ncv = PetscMin(N,PetscMax(2*svd->nsv,10));
1298 slepc 37
  if (svd->max_it == PETSC_DECIDE)
1314 slepc 38
    svd->max_it = PetscMax(N/svd->ncv,100);
39
  if (svd->ncv!=svd->n) {  
40
    if (svd->U) {
41
      for (i=0;i<svd->n;i++) { ierr = VecDestroy(svd->U[i]); CHKERRQ(ierr); }
42
      ierr = PetscFree(svd->U);CHKERRQ(ierr);
43
    }
44
    ierr = PetscMalloc(sizeof(Vec)*svd->ncv,&svd->U);CHKERRQ(ierr);
45
    for (i=0;i<svd->ncv;i++) { ierr = SVDMatGetVecs(svd,PETSC_NULL,svd->U+i);CHKERRQ(ierr); }
46
  }
1298 slepc 47
  PetscFunctionReturn(0);
48
}
49
 
50
#undef __FUNCT__  
1431 slepc 51
#define __FUNCT__ "SVDOneSideTRLanczosMGS"
1504 slepc 52
static PetscErrorCode SVDOneSideTRLanczosMGS(SVD svd,PetscReal *alpha,PetscReal *beta,PetscScalar* bb,Vec *V,Vec v,Vec* U,PetscInt nconv,PetscInt l,PetscInt n,PetscScalar* work,Vec wv,Vec wu)
1431 slepc 53
{
54
  PetscErrorCode ierr;
55
  PetscReal      a,b;
1504 slepc 56
  PetscInt       i,k=nconv+l;
1431 slepc 57
 
58
  PetscFunctionBegin;
59
  ierr = SVDMatMult(svd,PETSC_FALSE,V[k],U[k]);CHKERRQ(ierr);
60
  if (l>0) {
61
    ierr = VecSet(wu,0.0);CHKERRQ(ierr);
62
    ierr = VecMAXPY(wu,l,bb,U+nconv);CHKERRQ(ierr);
63
    ierr = VecAXPY(U[k],-1.0,wu);CHKERRQ(ierr);
64
  }
65
  ierr = IPNorm(svd->ip,U[k],&a);CHKERRQ(ierr);
66
  ierr = VecScale(U[k],1.0/a);CHKERRQ(ierr);
67
  alpha[0] = a;
68
  for (i=k+1;i<n;i++) {
69
    ierr = SVDMatMult(svd,PETSC_TRUE,U[i-1],V[i]);CHKERRQ(ierr);
70
    ierr = IPOrthogonalize(svd->ip,i,PETSC_NULL,V,V[i],work,&b,PETSC_NULL,wv);CHKERRQ(ierr);  
71
    ierr = VecScale(V[i],1.0/b);CHKERRQ(ierr);
72
    beta[i-k-1] = b;
73
 
74
    ierr = SVDMatMult(svd,PETSC_FALSE,V[i],U[i]);CHKERRQ(ierr);
75
    ierr = VecAXPY(U[i],-b,U[i-1]);CHKERRQ(ierr);
76
    ierr = IPNorm(svd->ip,U[i],&a);CHKERRQ(ierr);
77
    ierr = VecScale(U[i],1.0/a);CHKERRQ(ierr);
78
    alpha[i-k] = a;
79
  }
80
  ierr = SVDMatMult(svd,PETSC_TRUE,U[n-1],v);CHKERRQ(ierr);
81
  ierr = IPOrthogonalize(svd->ip,n,PETSC_NULL,V,v,work,&b,PETSC_NULL,wv);CHKERRQ(ierr);      
82
  beta[n-k-1] = b;
83
  PetscFunctionReturn(0);
84
}
85
 
86
#undef __FUNCT__  
1489 slepc 87
#define __FUNCT__ "SVDOneSideTRLanczosCGS"
1504 slepc 88
static PetscErrorCode SVDOneSideTRLanczosCGS(SVD svd,PetscReal *alpha,PetscReal *beta,PetscScalar* bb,Vec *V,Vec v,Vec* U,PetscInt nconv,PetscInt l,PetscInt n,PetscScalar* work,Vec wv,Vec wu)
1328 slepc 89
{
90
  PetscErrorCode ierr;
1414 slepc 91
  PetscReal      a,b,sum,onorm;
92
  PetscScalar    dot;
1504 slepc 93
  PetscInt       i,j,k=nconv+l;
1328 slepc 94
 
95
  PetscFunctionBegin;
96
  ierr = SVDMatMult(svd,PETSC_FALSE,V[k],U[k]);CHKERRQ(ierr);
97
  if (l>0) {
98
    ierr = VecSet(wu,0.0);CHKERRQ(ierr);
99
    ierr = VecMAXPY(wu,l,bb,U+nconv);CHKERRQ(ierr);
100
    ierr = VecAXPY(U[k],-1.0,wu);CHKERRQ(ierr);
101
  }
102
  for (i=k+1;i<n;i++) {
103
    ierr = SVDMatMult(svd,PETSC_TRUE,U[i-1],V[i]);CHKERRQ(ierr);
1352 slepc 104
    ierr = IPNormBegin(svd->ip,U[i-1],&a);CHKERRQ(ierr);
1414 slepc 105
    if (svd->ip->orthog_ref == IP_ORTH_REFINE_IFNEEDED) {
106
      ierr = IPInnerProductBegin(svd->ip,V[i],V[i],&dot);CHKERRQ(ierr);
107
    }
1381 slepc 108
    ierr = IPMInnerProductBegin(svd->ip,V[i],i,V,work);CHKERRQ(ierr);
1352 slepc 109
    ierr = IPNormEnd(svd->ip,U[i-1],&a);CHKERRQ(ierr);
1414 slepc 110
    if (svd->ip->orthog_ref == IP_ORTH_REFINE_IFNEEDED) {
111
      ierr = IPInnerProductEnd(svd->ip,V[i],V[i],&dot);CHKERRQ(ierr);
112
    }
1381 slepc 113
    ierr = IPMInnerProductEnd(svd->ip,V[i],i,V,work);CHKERRQ(ierr);
1328 slepc 114
 
115
    ierr = VecScale(U[i-1],1.0/a);CHKERRQ(ierr);
116
    ierr = VecScale(V[i],1.0/a);CHKERRQ(ierr);
117
    for (j=0;j<i;j++) work[j] = - work[j] / a;
118
    ierr = VecMAXPY(V[i],i,work,V);CHKERRQ(ierr);
119
 
1414 slepc 120
    switch (svd->ip->orthog_ref) {
121
    case IP_ORTH_REFINE_NEVER:
122
      ierr = IPNorm(svd->ip,V[i],&b);CHKERRQ(ierr);
123
      break;      
124
    case IP_ORTH_REFINE_ALWAYS:
125
      ierr = IPOrthogonalizeCGS(svd->ip,i,PETSC_NULL,V,V[i],work,PETSC_NULL,&b,wv);CHKERRQ(ierr);
126
      break;
127
    case IP_ORTH_REFINE_IFNEEDED:
128
      onorm = sqrt(PetscRealPart(dot)) / a;
129
      sum = 0.0;
130
      for (j=0;j<i;j++) {
131
        sum += PetscRealPart(work[j] * PetscConj(work[j]));
132
      }
133
      b = PetscRealPart(dot)/(a*a) - sum;
134
      if (b>0.0) b = sqrt(b);
135
      else {
136
        ierr = IPNorm(svd->ip,V[i],&b);CHKERRQ(ierr);
137
      }
138
      if (b < svd->ip->orthog_eta * onorm) {
139
        ierr = IPOrthogonalizeCGS(svd->ip,i,PETSC_NULL,V,V[i],work,PETSC_NULL,&b,wv);CHKERRQ(ierr);
140
      }
141
      break;
142
    }
143
 
1328 slepc 144
    ierr = VecScale(V[i],1.0/b);CHKERRQ(ierr);
145
 
146
    ierr = SVDMatMult(svd,PETSC_FALSE,V[i],U[i]);CHKERRQ(ierr);
147
    ierr = VecAXPY(U[i],-b,U[i-1]);CHKERRQ(ierr);
148
 
149
    alpha[i-k-1] = a;
150
    beta[i-k-1] = b;
151
  }
152
  ierr = SVDMatMult(svd,PETSC_TRUE,U[n-1],v);CHKERRQ(ierr);
1352 slepc 153
  ierr = IPNormBegin(svd->ip,U[n-1],&a);CHKERRQ(ierr);
1415 slepc 154
  if (svd->ip->orthog_ref == IP_ORTH_REFINE_IFNEEDED) {
155
    ierr = IPInnerProductBegin(svd->ip,v,v,&dot);CHKERRQ(ierr);
156
  }
1381 slepc 157
  ierr = IPMInnerProductBegin(svd->ip,v,n,V,work);CHKERRQ(ierr);
1352 slepc 158
  ierr = IPNormEnd(svd->ip,U[n-1],&a);CHKERRQ(ierr);
1415 slepc 159
  if (svd->ip->orthog_ref == IP_ORTH_REFINE_IFNEEDED) {
160
    ierr = IPInnerProductEnd(svd->ip,v,v,&dot);CHKERRQ(ierr);
161
  }
1381 slepc 162
  ierr = IPMInnerProductEnd(svd->ip,v,n,V,work);CHKERRQ(ierr);
1328 slepc 163
 
164
  ierr = VecScale(U[n-1],1.0/a);CHKERRQ(ierr);
165
  ierr = VecScale(v,1.0/a);CHKERRQ(ierr);
166
  for (j=0;j<n;j++) work[j] = - work[j] / a;
167
  ierr = VecMAXPY(v,n,work,V);CHKERRQ(ierr);
168
 
1415 slepc 169
  switch (svd->ip->orthog_ref) {
170
  case IP_ORTH_REFINE_NEVER:
171
    ierr = IPNorm(svd->ip,v,&b);CHKERRQ(ierr);
172
    break;      
173
  case IP_ORTH_REFINE_ALWAYS:
174
    ierr = IPOrthogonalizeCGS(svd->ip,n,PETSC_NULL,V,v,work,PETSC_NULL,&b,wv);CHKERRQ(ierr);
175
    break;
176
  case IP_ORTH_REFINE_IFNEEDED:
177
    onorm = sqrt(PetscRealPart(dot)) / a;
178
    sum = 0.0;
179
    for (j=0;j<i;j++) {
180
      sum += PetscRealPart(work[j] * PetscConj(work[j]));
181
    }
182
    b = PetscRealPart(dot)/(a*a) - sum;
183
    if (b>0.0) b = sqrt(b);
184
    else {
185
      ierr = IPNorm(svd->ip,v,&b);CHKERRQ(ierr);
186
    }
187
    if (b < svd->ip->orthog_eta * onorm) {
188
      ierr = IPOrthogonalizeCGS(svd->ip,n,PETSC_NULL,V,v,work,PETSC_NULL,&b,wv);CHKERRQ(ierr);
189
    }
190
    break;
191
  }
192
 
1328 slepc 193
  alpha[n-k-1] = a;
194
  beta[n-k-1] = b;
195
  PetscFunctionReturn(0);
196
}
197
 
198
#undef __FUNCT__  
1298 slepc 199
#define __FUNCT__ "SVDSolve_TRLANCZOS"
200
PetscErrorCode SVDSolve_TRLANCZOS(SVD svd)
201
{
202
  PetscErrorCode ierr;
203
  SVD_TRLANCZOS  *lanczos = (SVD_TRLANCZOS *)svd->data;
1328 slepc 204
  PetscReal      *alpha,*beta,norm;
1341 slepc 205
  PetscScalar    *b,*Q,*PT,*swork;
1504 slepc 206
  PetscInt       *perm,i,j,k,l,m,n,nwork=0;
1328 slepc 207
  Vec            v,wv,wu,*workV,*workU,*permV,*permU;
208
  PetscTruth     conv;
1431 slepc 209
  IPOrthogonalizationType orthog;
1298 slepc 210
 
211
  PetscFunctionBegin;
212
  /* allocate working space */
1307 slepc 213
  ierr = PetscMalloc(sizeof(PetscReal)*svd->n,&alpha);CHKERRQ(ierr);
214
  ierr = PetscMalloc(sizeof(PetscReal)*svd->n,&beta);CHKERRQ(ierr);
215
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n,&b);CHKERRQ(ierr);
216
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n*svd->n,&Q);CHKERRQ(ierr);
217
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n*svd->n,&PT);CHKERRQ(ierr);
1341 slepc 218
  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n,&swork);CHKERRQ(ierr);
1328 slepc 219
  ierr = VecDuplicate(svd->V[0],&v);CHKERRQ(ierr);
220
  ierr = VecDuplicate(svd->V[0],&wv);CHKERRQ(ierr);
221
  ierr = VecDuplicate(svd->U[0],&wu);CHKERRQ(ierr);
222
  ierr = PetscMalloc(sizeof(Vec)*svd->n,&workV);CHKERRQ(ierr);
223
  ierr = PetscMalloc(sizeof(Vec)*svd->n,&workU);CHKERRQ(ierr);
1431 slepc 224
  ierr = IPGetOrthogonalization(svd->ip,&orthog,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr);
1298 slepc 225
 
226
  /* normalize start vector */
1328 slepc 227
  ierr = VecCopy(svd->vec_initial,svd->V[0]);CHKERRQ(ierr);
228
  ierr = VecNormalize(svd->V[0],&norm);CHKERRQ(ierr);
1298 slepc 229
 
230
  l = 0;
231
  while (svd->reason == SVD_CONVERGED_ITERATING) {
232
    svd->its++;
233
 
234
    /* inner loop */
1328 slepc 235
    if (lanczos->oneside) {
1431 slepc 236
      if (orthog == IP_MGS_ORTH) {
237
        ierr = SVDOneSideTRLanczosMGS(svd,alpha,beta,b+svd->nconv,svd->V,v,svd->U,svd->nconv,l,svd->n,swork,wv,wu);CHKERRQ(ierr);
238
      } else {
1489 slepc 239
        ierr = SVDOneSideTRLanczosCGS(svd,alpha,beta,b+svd->nconv,svd->V,v,svd->U,svd->nconv,l,svd->n,swork,wv,wu);CHKERRQ(ierr);
1431 slepc 240
      }
1328 slepc 241
    } else {
1341 slepc 242
      ierr = SVDTwoSideLanczos(svd,alpha,beta,svd->V,v,svd->U,svd->nconv+l,svd->n,swork,wv,wu);CHKERRQ(ierr);
1298 slepc 243
    }
1328 slepc 244
    ierr = VecScale(v,1.0/beta[svd->n-svd->nconv-l-1]);CHKERRQ(ierr);
245
 
1298 slepc 246
    /* compute SVD of general matrix */
1328 slepc 247
    n = svd->n - svd->nconv;
1298 slepc 248
    /* first l columns */
249
    for (j=0;j<l;j++) {
250
      for (i=0;i<j;i++) Q[j*n+i] = 0.0;    
1328 slepc 251
      Q[j*n+j] = svd->sigma[svd->nconv+j];
1298 slepc 252
      for (i=j+1;i<n;i++) Q[j*n+i] = 0.0;
253
    }
254
    /* l+1 column */
1328 slepc 255
    for (i=0;i<l;i++) Q[l*n+i] = b[i+svd->nconv];
256
    Q[l*n+l] = alpha[0];
1298 slepc 257
    for (i=l+1;i<n;i++) Q[l*n+i] = 0.0;
258
    /* rest of matrix */
259
    for (j=l+1;j<n;j++) {
260
      for (i=0;i<j-1;i++) Q[j*n+i] = 0.0;
1328 slepc 261
      Q[j*n+j-1] = beta[j-l-1];
262
      Q[j*n+j] = alpha[j-l];
1298 slepc 263
      for (i=j+1;i<n;i++) Q[j*n+i] = 0.0;
264
    }
1328 slepc 265
    ierr = SVDDense(n,n,Q,alpha,PETSC_NULL,PT);CHKERRQ(ierr);
1298 slepc 266
 
267
    /* compute error estimates */
1328 slepc 268
    k = 0;
269
    conv = PETSC_TRUE;
270
    for (i=svd->nconv;i<svd->n;i++) {
271
      if (svd->which == SVD_SMALLEST) j = n-i+svd->nconv-1;
272
      else j = i-svd->nconv;
273
      svd->sigma[i] = alpha[j];
274
      b[i] = Q[j*n+n-1]*beta[n-l-1];
275
      svd->errest[i] = PetscAbsScalar(b[i]);
276
      if (alpha[j] > svd->tol) svd->errest[i] /= alpha[j];
277
      if (conv) {
278
        if (svd->errest[i] < svd->tol) k++;
279
        else conv = PETSC_FALSE;
1304 slepc 280
      }
1298 slepc 281
    }
282
 
1328 slepc 283
    /* check convergence and update l */
284
    if (svd->its >= svd->max_it) svd->reason = SVD_DIVERGED_ITS;
285
    if (svd->nconv+k >= svd->nsv) svd->reason = SVD_CONVERGED_TOL;
286
    if (svd->reason != SVD_CONVERGED_ITERATING) l = 0;
287
    else l = PetscMax((svd->n - svd->nconv - k) / 2,1);
1300 slepc 288
 
1328 slepc 289
    /* allocate work space for converged singular and restart vectors */
290
    if (nwork<k+l) {
291
      for (i=nwork;i<k+l;i++) {
292
        ierr = SVDMatGetVecs(svd,workV+i,workU+i);CHKERRQ(ierr);
1300 slepc 293
      }
1328 slepc 294
      nwork = k+l;
1298 slepc 295
    }
296
 
1328 slepc 297
    /* compute converged singular vectors and restart vectors*/
298
    for (i=0;i<k+l;i++) {
299
      if (svd->which == SVD_SMALLEST) j = n-i-1;
300
      else j = i;
301
      ierr = VecSet(workV[i],0.0);CHKERRQ(ierr);
1341 slepc 302
      for (m=0;m<n;m++) swork[m] = PT[m*n+j];
303
      ierr = VecMAXPY(workV[i],n,swork,svd->V+svd->nconv);CHKERRQ(ierr);
1328 slepc 304
      ierr = VecSet(workU[i],0.0);CHKERRQ(ierr);
305
      ierr = VecMAXPY(workU[i],n,Q+j*n,svd->U+svd->nconv);CHKERRQ(ierr);
306
    }
307
 
1298 slepc 308
    /* copy the last vector to be the next initial vector */
309
    if (svd->reason == SVD_CONVERGED_ITERATING) {
1328 slepc 310
      ierr = VecCopy(v,svd->V[svd->nconv+k+l]);CHKERRQ(ierr);
1298 slepc 311
    }
312
 
1328 slepc 313
    /* copy converged singular vectors and restart vectors from temporary space */
314
    for (i=0;i<k+l;i++) {
315
      ierr = VecCopy(workV[i],svd->V[i+svd->nconv]);CHKERRQ(ierr);
316
      ierr = VecCopy(workU[i],svd->U[i+svd->nconv]);CHKERRQ(ierr);
317
    }
318
 
319
    svd->nconv += k;
320
    SVDMonitor(svd,svd->its,svd->nconv,svd->sigma,svd->errest,svd->n);
1298 slepc 321
  }
322
 
323
  /* sort singular triplets */
324
  ierr = PetscMalloc(sizeof(PetscInt)*svd->nconv,&perm);CHKERRQ(ierr);
1328 slepc 325
  ierr = PetscMalloc(sizeof(Vec)*svd->nconv,&permV);CHKERRQ(ierr);
326
  ierr = PetscMalloc(sizeof(Vec)*svd->nconv,&permU);CHKERRQ(ierr);
1298 slepc 327
  for (i=0;i<svd->nconv;i++) {
328
    alpha[i] = svd->sigma[i];
329
    beta[i] = svd->errest[i];
1328 slepc 330
    permV[i] = svd->V[i];
331
    permU[i] = svd->U[i];
1298 slepc 332
    perm[i] = i;
333
  }
1328 slepc 334
  ierr = PetscSortRealWithPermutation(svd->nconv,svd->sigma,perm);CHKERRQ(ierr);
335
  for (i=0;i<svd->nconv;i++) {
1298 slepc 336
    if (svd->which == SVD_SMALLEST) j = perm[i];
1300 slepc 337
    else j = perm[svd->nconv-i-1];
1328 slepc 338
    svd->sigma[i] = alpha[j];
339
    svd->errest[i] = beta[j];
340
    svd->V[i] = permV[j];
341
    svd->U[i] = permU[j];
1489 slepc 342
    if (lanczos->oneside) {
343
      ierr = IPOrthogonalize(svd->ip,i,PETSC_NULL,svd->U,svd->U[i],PETSC_NULL,&norm,PETSC_NULL,PETSC_NULL);CHKERRQ(ierr);
344
      ierr = VecScale(svd->U[i],1.0/norm);CHKERRQ(ierr);
345
    }
1298 slepc 346
  }
347
 
348
  /* free working space */
1328 slepc 349
  ierr = VecDestroy(v);CHKERRQ(ierr);
350
  ierr = VecDestroy(wv);CHKERRQ(ierr);
351
  ierr = VecDestroy(wu);CHKERRQ(ierr);
352
  for (i=0;i<nwork;i++) { ierr = VecDestroy(workV[i]);CHKERRQ(ierr); }
353
  ierr = PetscFree(workV);CHKERRQ(ierr);
354
  for (i=0;i<nwork;i++) { ierr = VecDestroy(workU[i]);CHKERRQ(ierr); }
355
  ierr = PetscFree(workU);CHKERRQ(ierr);
1298 slepc 356
 
357
  ierr = PetscFree(alpha);CHKERRQ(ierr);
358
  ierr = PetscFree(beta);CHKERRQ(ierr);
359
  ierr = PetscFree(b);CHKERRQ(ierr);
360
  ierr = PetscFree(Q);CHKERRQ(ierr);
361
  ierr = PetscFree(PT);CHKERRQ(ierr);
1341 slepc 362
  ierr = PetscFree(swork);CHKERRQ(ierr);
1298 slepc 363
  ierr = PetscFree(perm);CHKERRQ(ierr);
1328 slepc 364
  ierr = PetscFree(permV);CHKERRQ(ierr);
365
  ierr = PetscFree(permU);CHKERRQ(ierr);
1298 slepc 366
  PetscFunctionReturn(0);
367
}
368
 
369
#undef __FUNCT__  
370
#define __FUNCT__ "SVDSetFromOptions_TRLANCZOS"
371
PetscErrorCode SVDSetFromOptions_TRLANCZOS(SVD svd)
372
{
373
  PetscErrorCode ierr;
374
  SVD_TRLANCZOS  *lanczos = (SVD_TRLANCZOS *)svd->data;
375
 
376
  PetscFunctionBegin;
1422 slepc 377
  ierr = PetscOptionsBegin(((PetscObject)svd)->comm,((PetscObject)svd)->prefix,"TRLANCZOS Singular Value Solver Options","SVD");CHKERRQ(ierr);
1359 slepc 378
  ierr = PetscOptionsTruth("-svd_trlanczos_oneside","Lanczos one-side reorthogonalization","SVDTRLanczosSetOneSide",PETSC_FALSE,&lanczos->oneside,PETSC_NULL);CHKERRQ(ierr);
1298 slepc 379
  ierr = PetscOptionsEnd();CHKERRQ(ierr);
380
  PetscFunctionReturn(0);
381
}
1370 slepc 382
 
1298 slepc 383
EXTERN_C_BEGIN
384
#undef __FUNCT__  
1359 slepc 385
#define __FUNCT__ "SVDTRLanczosSetOneSide_TRLANCZOS"
386
PetscErrorCode SVDTRLanczosSetOneSide_TRLANCZOS(SVD svd,PetscTruth oneside)
1298 slepc 387
{
388
  SVD_TRLANCZOS *lanczos = (SVD_TRLANCZOS *)svd->data;
389
 
390
  PetscFunctionBegin;
391
  lanczos->oneside = oneside;
392
  PetscFunctionReturn(0);
393
}
1370 slepc 394
EXTERN_C_END
1298 slepc 395
 
396
#undef __FUNCT__
1359 slepc 397
#define __FUNCT__ "SVDTRLanczosSetOneSide"
1393 slepc 398
/*@
399
   SVDTRLanczosSetOneSide - Indicate if the variant of the Lanczos method
400
   to be used is one-sided or two-sided.
401
 
402
   Collective on SVD
403
 
404
   Input Parameters:
405
+  svd     - singular value solver
406
-  oneside - boolean flag indicating if the method is one-sided or not
407
 
408
   Options Database Key:
409
.  -svd_trlanczos_oneside <boolean> - Indicates the boolean flag
410
 
411
   Note:
412
   By default, a two-sided variant is selected, which is sometimes slightly
413
   more robust. However, the one-sided variant is faster because it avoids
414
   the orthogonalization associated to left singular vectors.
415
 
416
   Level: advanced
417
 
418
.seealso: SVDLanczosSetOneSide()
419
@*/
1359 slepc 420
PetscErrorCode SVDTRLanczosSetOneSide(SVD svd,PetscTruth oneside)
1298 slepc 421
{
422
  PetscErrorCode ierr, (*f)(SVD,PetscTruth);
423
 
424
  PetscFunctionBegin;
425
  PetscValidHeaderSpecific(svd,SVD_COOKIE,1);
1359 slepc 426
  ierr = PetscObjectQueryFunction((PetscObject)svd,"SVDTRLanczosSetOneSide_C",(void (**)())&f);CHKERRQ(ierr);
1298 slepc 427
  if (f) {
428
    ierr = (*f)(svd,oneside);CHKERRQ(ierr);
429
  }
430
  PetscFunctionReturn(0);
431
}
432
 
433
#undef __FUNCT__  
434
#define __FUNCT__ "SVDView_TRLANCZOS"
435
PetscErrorCode SVDView_TRLANCZOS(SVD svd,PetscViewer viewer)
436
{
437
  PetscErrorCode ierr;
438
  SVD_TRLANCZOS  *lanczos = (SVD_TRLANCZOS *)svd->data;
439
 
440
  PetscFunctionBegin;
441
  ierr = PetscViewerASCIIPrintf(viewer,"Lanczos reorthogonalization: %s\n",lanczos->oneside ? "one-side" : "two-side");CHKERRQ(ierr);
442
  PetscFunctionReturn(0);
443
}
444
 
445
EXTERN_C_BEGIN
446
#undef __FUNCT__  
447
#define __FUNCT__ "SVDCreate_TRLANCZOS"
448
PetscErrorCode SVDCreate_TRLANCZOS(SVD svd)
449
{
450
  PetscErrorCode ierr;
451
  SVD_TRLANCZOS  *lanczos;
452
 
453
  PetscFunctionBegin;
454
  ierr = PetscNew(SVD_TRLANCZOS,&lanczos);CHKERRQ(ierr);
455
  PetscLogObjectMemory(svd,sizeof(SVD_TRLANCZOS));
456
  svd->data                = (void *)lanczos;
457
  svd->ops->setup          = SVDSetUp_TRLANCZOS;
458
  svd->ops->solve          = SVDSolve_TRLANCZOS;
1391 slepc 459
  svd->ops->destroy        = SVDDestroy_Default;
1298 slepc 460
  svd->ops->setfromoptions = SVDSetFromOptions_TRLANCZOS;
461
  svd->ops->view           = SVDView_TRLANCZOS;
462
  lanczos->oneside         = PETSC_FALSE;
1359 slepc 463
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)svd,"SVDTRLanczosSetOneSide_C","SVDTRLanczosSetOneSide_TRLANCZOS",SVDTRLanczosSetOneSide_TRLANCZOS);CHKERRQ(ierr);
1298 slepc 464
  PetscFunctionReturn(0);
465
}
466
EXTERN_C_END