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1278 slepc 1
/*                      
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   SLEPc singular value solver: "lanczos"
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1281 slepc 5
   Method: Golub-Kahan-Lanczos bidiagonalization
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   Last update: Nov 2006
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*/
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#include "src/svd/svdimpl.h"                /*I "slepcsvd.h" I*/
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#include "slepcblaslapack.h"
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1298 slepc 13
typedef struct {
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  PetscTruth oneside;
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} SVD_LANCZOS;
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#undef __FUNCT__  
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#define __FUNCT__ "SVDSetUp_LANCZOS"
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PetscErrorCode SVDSetUp_LANCZOS(SVD svd)
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{
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  PetscErrorCode  ierr;
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  PetscInt        M,N;
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  PetscFunctionBegin;
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  ierr = MatGetSize(svd->A,&M,&N);CHKERRQ(ierr);
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  if (svd->ncv == PETSC_DECIDE)
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    svd->ncv = PetscMin(PetscMin(M,N),PetscMax(2*svd->nsv,10));
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  if (svd->max_it == PETSC_DECIDE)
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    svd->max_it = PetscMax(PetscMin(M,N)/svd->ncv,100);
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  PetscFunctionReturn(0);
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}
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#undef __FUNCT__  
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#define __FUNCT__ "SVDSolve_LANCZOS"
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PetscErrorCode SVDSolve_LANCZOS(SVD svd)
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{
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  PetscErrorCode ierr;
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  SVD_LANCZOS    *lanczos = (SVD_LANCZOS *)svd->data;
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  PetscReal      *alpha,*beta,norm,*work;
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  PetscScalar    *Q,*PT;
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  PetscInt       *perm;
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  int            i,j,k,l,n,zero=0,info;
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  Vec            *V,*U;
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  PetscTruth     conv;
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  PetscFunctionBegin;
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  /* allocate working space */
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  ierr = PetscMalloc(sizeof(PetscReal)*svd->n,&alpha);CHKERRQ(ierr);
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  ierr = PetscMalloc(sizeof(PetscReal)*svd->n,&beta);CHKERRQ(ierr);
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  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n*svd->n,&Q);CHKERRQ(ierr);
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  ierr = PetscMalloc(sizeof(PetscScalar)*svd->n*svd->n,&PT);CHKERRQ(ierr);
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  ierr = PetscMalloc(sizeof(PetscReal)*4*svd->n,&work);CHKERRQ(ierr);
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  ierr = VecDuplicateVecs(svd->V[0],svd->n+1,&V);CHKERRQ(ierr);
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  ierr = VecDuplicateVecs(svd->U[0],svd->n,&U);CHKERRQ(ierr);
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1293 slepc 56
  /* normalize start vector */
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  ierr = VecCopy(svd->vec_initial,V[0]);CHKERRQ(ierr);
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  ierr = VecNormalize(V[0],&norm);CHKERRQ(ierr);
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  while (svd->reason == SVD_CONVERGED_ITERATING) {
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    svd->its++;
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1293 slepc 63
    /* inner loop */
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    for (i=svd->nconv;i<svd->n;i++) {
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      svd->matvecs++;
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      ierr = MatMult(svd->A,V[i],U[i]);CHKERRQ(ierr);
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      if (lanczos->oneside) {
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        if (i>svd->nconv) { ierr = VecAXPY(U[i],-beta[i-svd->nconv-1],U[i-1]);CHKERRQ(ierr); }
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      } else {
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        svd->dots += i;
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        ierr = IPOrthogonalize(svd->ip,i,PETSC_NULL,U,U[i],PT,alpha+i-svd->nconv,PETSC_NULL);CHKERRQ(ierr);
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        ierr = VecScale(U[i],1.0/alpha[i-svd->nconv]);CHKERRQ(ierr);
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      }
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      svd->matvecs++;
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      if (svd->AT) {
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        ierr = MatMult(svd->AT,U[i],V[i+1]);CHKERRQ(ierr);
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      } else {
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        ierr = MatMultTranspose(svd->A,U[i],V[i+1]);CHKERRQ(ierr);
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      }
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      if (lanczos->oneside) {
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        svd->dots += i+1;
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        ierr = VecNormBegin(U[i],NORM_2,alpha+i-svd->nconv);CHKERRQ(ierr);
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        ierr = VecMDotBegin(V[i+1],i+1,V,PT);CHKERRQ(ierr);
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        ierr = VecNormEnd(U[i],NORM_2,alpha+i-svd->nconv);CHKERRQ(ierr);
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        ierr = VecMDotEnd(V[i+1],i+1,V,PT);CHKERRQ(ierr);
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88
        ierr = VecScale(U[i],1.0/alpha[i-svd->nconv]);CHKERRQ(ierr);
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        ierr = VecScale(V[i+1],1.0/alpha[i-svd->nconv]);CHKERRQ(ierr);
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        for (j=0;j<=i;j++) PT[j] = - PT[j] / alpha[i-svd->nconv];
91
        ierr = VecMAXPY(V[i+1],i+1,PT,V);CHKERRQ(ierr);
92
 
1307 slepc 93
        ierr = IPOrthogonalizeGS(svd->ip,i+1,PETSC_NULL,V,V[i+1],PT,PETSC_NULL,beta+i-svd->nconv);CHKERRQ(ierr);
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        ierr = VecScale(V[i+1],1.0/beta[i-svd->nconv]);CHKERRQ(ierr);
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      } else {
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        svd->dots += i+1;
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        ierr = IPOrthogonalize(svd->ip,i+1,PETSC_NULL,V,V[i+1],PT,beta+i-svd->nconv,PETSC_NULL);CHKERRQ(ierr);
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        ierr = VecScale(V[i+1],1.0/beta[i-svd->nconv]);CHKERRQ(ierr);
99
      }
1278 slepc 100
    }
101
 
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    /* compute SVD of bidiagonal matrix */
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    n = svd->n - svd->nconv;
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    ierr = PetscMemzero(PT,sizeof(PetscScalar)*n*n);CHKERRQ(ierr);
105
    ierr = PetscMemzero(Q,sizeof(PetscScalar)*n*n);CHKERRQ(ierr);
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    for (i=0;i<n;i++)
107
      PT[i*n+i] = Q[i*n+i] = 1.0;
1285 slepc 108
    LAPACKbdsqr_("U",&n,&n,&n,&zero,alpha,beta,PT,&n,Q,&n,PETSC_NULL,&n,work,&info,1);
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1293 slepc 110
    /* compute error estimates and converged singular vectors */
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    k = svd->nconv;
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    conv = PETSC_TRUE;
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    for (i=svd->nconv;i<svd->n;i++) {
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      if (svd->which == SVD_SMALLEST) j = n-i+svd->nconv-1;
115
      else j = i-svd->nconv;
116
      svd->sigma[i] = alpha[j];
1312 slepc 117
      svd->errest[i] = PetscAbsReal(Q[j*n+n-1])*beta[n-1] / alpha[j];
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      if (conv) {
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        if (svd->errest[i] < svd->tol) {
120
          ierr = VecSet(svd->V[i],0.0);CHKERRQ(ierr);
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          for (l=0;l<n;l++) {
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            ierr = VecAXPY(svd->V[i],PT[l*n+j],V[l+svd->nconv]);CHKERRQ(ierr);
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          }      
124
          ierr = VecSet(svd->U[i],0.0);CHKERRQ(ierr);
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          ierr = VecMAXPY(svd->U[i],n,Q+j*n,U+svd->nconv);CHKERRQ(ierr);
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          k++;
127
        } else conv = PETSC_FALSE;
1278 slepc 128
      }
129
    }
1293 slepc 130
 
131
    if (svd->its > svd->max_it) svd->reason = SVD_DIVERGED_ITS;
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    if (k >= svd->nsv) svd->reason = SVD_CONVERGED_TOL;
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    if (svd->reason == SVD_CONVERGED_ITERATING) {
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      /* compute restart vector */
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      if (svd->which == SVD_SMALLEST) j = n-k+svd->nconv-1;
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      else j = k-svd->nconv;
137
      ierr = VecSet(svd->V[k],0.0);CHKERRQ(ierr);
138
      for (l=0;l<n;l++) {
139
        ierr = VecAXPY(svd->V[k],PT[l*n+j],V[l+svd->nconv]);CHKERRQ(ierr);
140
      }      
141
      ierr = VecCopy(svd->V[k],V[k]);CHKERRQ(ierr);
142
    }
143
 
144
    /* copy converged singular vectors from temporary space */
1281 slepc 145
    for (i=svd->nconv;i<k;i++) {
146
      ierr = VecCopy(svd->V[i],V[i]);CHKERRQ(ierr);
147
      ierr = VecCopy(svd->U[i],U[i]);CHKERRQ(ierr);
148
    }
1278 slepc 149
    svd->nconv = k;
1293 slepc 150
 
151
    SVDMonitor(svd,svd->its,svd->nconv,svd->sigma,svd->errest,svd->n);
1278 slepc 152
  }
153
 
1293 slepc 154
  /* sort singular triplets */
155
  ierr = PetscMalloc(sizeof(PetscInt)*svd->nconv,&perm);CHKERRQ(ierr);
156
  for (i=0;i<svd->nconv;i++) {
157
    alpha[i] = svd->sigma[i];
158
    beta[i] = svd->errest[i];
159
    perm[i] = i;
160
  }
161
  ierr = PetscSortRealWithPermutation(svd->nconv,svd->sigma,perm);CHKERRQ(ierr);
162
  for (i=0;i<svd->nconv;i++) {
163
    if (svd->which == SVD_SMALLEST) j = perm[i];
164
    else j = perm[svd->nconv-i-1];
165
    svd->sigma[i] = alpha[j];
166
    svd->errest[i] = beta[j];
167
    ierr = VecCopy(V[j],svd->V[i]);CHKERRQ(ierr);
168
    ierr = VecCopy(U[j],svd->U[i]);CHKERRQ(ierr);
169
  }
170
 
171
  /* free working space */
1302 slepc 172
  ierr = VecDestroyVecs(V,svd->n+1);CHKERRQ(ierr);
173
  ierr = VecDestroyVecs(U,svd->n);CHKERRQ(ierr);
1278 slepc 174
 
175
  ierr = PetscFree(alpha);CHKERRQ(ierr);
176
  ierr = PetscFree(beta);CHKERRQ(ierr);
177
  ierr = PetscFree(Q);CHKERRQ(ierr);
178
  ierr = PetscFree(PT);CHKERRQ(ierr);
179
  ierr = PetscFree(work);CHKERRQ(ierr);
1293 slepc 180
  ierr = PetscFree(perm);CHKERRQ(ierr);
1278 slepc 181
  PetscFunctionReturn(0);
182
}
183
 
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#undef __FUNCT__  
185
#define __FUNCT__ "SVDSetFromOptions_LANCZOS"
186
PetscErrorCode SVDSetFromOptions_LANCZOS(SVD svd)
187
{
188
  PetscErrorCode ierr;
189
  SVD_LANCZOS    *lanczos = (SVD_LANCZOS *)svd->data;
190
 
191
  PetscFunctionBegin;
192
  ierr = PetscOptionsBegin(svd->comm,svd->prefix,"LANCZOS Singular Value Solver Options","SVD");CHKERRQ(ierr);
1312 slepc 193
  ierr = PetscOptionsTruth("-svd_lanczos_oneside","Lanczos one-side reorthogonalization","SVDLanczosSetOneSideReorthogonalization",PETSC_FALSE,&lanczos->oneside,PETSC_NULL);CHKERRQ(ierr);
1298 slepc 194
  ierr = PetscOptionsEnd();CHKERRQ(ierr);
195
  PetscFunctionReturn(0);
196
}
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EXTERN_C_BEGIN
1298 slepc 198
 
1278 slepc 199
#undef __FUNCT__  
1298 slepc 200
#define __FUNCT__ "SVDLanczosSetOneSideReorthogonalization_LANCZOS"
201
PetscErrorCode SVDLanczosSetOneSideReorthogonalization_LANCZOS(SVD svd,PetscTruth oneside)
202
{
203
  SVD_LANCZOS    *lanczos = (SVD_LANCZOS *)svd->data;
204
 
205
  PetscFunctionBegin;
206
  lanczos->oneside = oneside;
207
  PetscFunctionReturn(0);
208
}
209
EXTERN_C_BEGIN
210
 
211
#undef __FUNCT__
212
#define __FUNCT__ "SVDLanczosSetOneSideReorthogonalization"
213
PetscErrorCode SVDLanczosSetOneSideReorthogonalization(SVD svd,PetscTruth oneside)
214
{
215
  PetscErrorCode ierr, (*f)(SVD,PetscTruth);
216
 
217
  PetscFunctionBegin;
218
  PetscValidHeaderSpecific(svd,SVD_COOKIE,1);
219
  ierr = PetscObjectQueryFunction((PetscObject)svd,"SVDLanczosSetOneSideReorthogonalization_C",(void (**)())&f);CHKERRQ(ierr);
220
  if (f) {
221
    ierr = (*f)(svd,oneside);CHKERRQ(ierr);
222
  }
223
  PetscFunctionReturn(0);
224
}
225
 
226
#undef __FUNCT__  
227
#define __FUNCT__ "SVDView_LANCZOS"
228
PetscErrorCode SVDView_LANCZOS(SVD svd,PetscViewer viewer)
229
{
230
  PetscErrorCode ierr;
231
  SVD_LANCZOS    *lanczos = (SVD_LANCZOS *)svd->data;
232
 
233
  PetscFunctionBegin;
234
  ierr = PetscViewerASCIIPrintf(viewer,"Lanczos reorthogonalization: %s\n",lanczos->oneside ? "one-side" : "two-side");CHKERRQ(ierr);
235
  PetscFunctionReturn(0);
236
}
237
 
238
EXTERN_C_BEGIN
239
#undef __FUNCT__  
1278 slepc 240
#define __FUNCT__ "SVDCreate_LANCZOS"
241
PetscErrorCode SVDCreate_LANCZOS(SVD svd)
242
{
1298 slepc 243
  PetscErrorCode ierr;
244
  SVD_LANCZOS    *lanczos;
245
 
1278 slepc 246
  PetscFunctionBegin;
1298 slepc 247
  ierr = PetscNew(SVD_LANCZOS,&lanczos);CHKERRQ(ierr);
248
  PetscLogObjectMemory(svd,sizeof(SVD_LANCZOS));
249
  svd->data                = (void *)lanczos;
250
  svd->ops->setup          = SVDSetUp_LANCZOS;
251
  svd->ops->solve          = SVDSolve_LANCZOS;
252
  svd->ops->setfromoptions = SVDSetFromOptions_LANCZOS;
253
  svd->ops->view           = SVDView_LANCZOS;
254
  lanczos->oneside         = PETSC_FALSE;
255
  ierr = PetscObjectComposeFunctionDynamic((PetscObject)svd,"SVDLanczosSetOneSideReorthogonalization_C","SVDLanczosSetOneSideReorthogonalization_LANCZOS",SVDLanczosSetOneSideReorthogonalization_LANCZOS);CHKERRQ(ierr);
1278 slepc 256
  PetscFunctionReturn(0);
257
}
258
EXTERN_C_END