Actual source code: ex45.c

slepc-3.21.1 2024-04-26
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  1: /*
  2:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  3:    SLEPc - Scalable Library for Eigenvalue Problem Computations
  4:    Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain

  6:    This file is part of SLEPc.
  7:    SLEPc is distributed under a 2-clause BSD license (see LICENSE).
  8:    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
  9: */

 11: static char help[] = "Computes a partial generalized singular value decomposition (GSVD).\n"
 12:   "The command line options are:\n"
 13:   "  -m <m>, where <m> = number of rows of A.\n"
 14:   "  -n <n>, where <n> = number of columns of A.\n"
 15:   "  -p <p>, where <p> = number of rows of B.\n\n";

 17: #include <slepcsvd.h>

 19: int main(int argc,char **argv)
 20: {
 21:   Mat            A,B;             /* operator matrices */
 22:   Vec            u,v,x;           /* singular vectors */
 23:   SVD            svd;             /* singular value problem solver context */
 24:   SVDType        type;
 25:   Vec            uv,aux[2],*U,*V;
 26:   PetscReal      error,tol,sigma,lev1=0.0,lev2=0.0;
 27:   PetscInt       m=100,n,p=14,i,j,d,Istart,Iend,nsv,maxit,its,nconv;
 28:   PetscBool      flg,skiporth=PETSC_FALSE;

 30:   PetscFunctionBeginUser;
 31:   PetscCall(SlepcInitialize(&argc,&argv,(char*)0,help));

 33:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
 34:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,&flg));
 35:   if (!flg) n = m;
 36:   PetscCall(PetscOptionsGetInt(NULL,NULL,"-p",&p,&flg));
 37:   PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nGeneralized singular value decomposition, (%" PetscInt_FMT "+%" PetscInt_FMT ")x%" PetscInt_FMT "\n\n",m,p,n));
 38:   PetscCall(PetscOptionsGetBool(NULL,NULL,"-skiporth",&skiporth,NULL));

 40:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 41:                           Build the matrices
 42:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 44:   PetscCall(MatCreate(PETSC_COMM_WORLD,&A));
 45:   PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n));
 46:   PetscCall(MatSetFromOptions(A));

 48:   PetscCall(MatGetOwnershipRange(A,&Istart,&Iend));
 49:   for (i=Istart;i<Iend;i++) {
 50:     if (i>0 && i-1<n) PetscCall(MatSetValue(A,i,i-1,-1.0,INSERT_VALUES));
 51:     if (i+1<n) PetscCall(MatSetValue(A,i,i+1,-1.0,INSERT_VALUES));
 52:     if (i<n) PetscCall(MatSetValue(A,i,i,2.0,INSERT_VALUES));
 53:     if (i>n) PetscCall(MatSetValue(A,i,n-1,1.0,INSERT_VALUES));
 54:   }
 55:   PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY));
 56:   PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY));

 58:   PetscCall(MatCreate(PETSC_COMM_WORLD,&B));
 59:   PetscCall(MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,p,n));
 60:   PetscCall(MatSetFromOptions(B));

 62:   PetscCall(MatGetOwnershipRange(B,&Istart,&Iend));
 63:   d = PetscMax(0,n-p);
 64:   for (i=Istart;i<Iend;i++) {
 65:     for (j=0;j<=PetscMin(i,n-1);j++) PetscCall(MatSetValue(B,i,j+d,1.0,INSERT_VALUES));
 66:   }
 67:   PetscCall(MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY));
 68:   PetscCall(MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY));

 70:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 71:           Create the singular value solver and set various options
 72:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 74:   /*
 75:      Create singular value solver context
 76:   */
 77:   PetscCall(SVDCreate(PETSC_COMM_WORLD,&svd));

 79:   /*
 80:      Set operators and problem type
 81:   */
 82:   PetscCall(SVDSetOperators(svd,A,B));
 83:   PetscCall(SVDSetProblemType(svd,SVD_GENERALIZED));

 85:   /*
 86:      Set solver parameters at runtime
 87:   */
 88:   PetscCall(SVDSetFromOptions(svd));

 90:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
 91:                       Solve the singular value system
 92:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

 94:   PetscCall(SVDSolve(svd));
 95:   PetscCall(SVDGetIterationNumber(svd,&its));
 96:   PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of iterations of the method: %" PetscInt_FMT "\n",its));

 98:   /*
 99:      Optional: Get some information from the solver and display it
100:   */
101:   PetscCall(SVDGetType(svd,&type));
102:   PetscCall(PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type));
103:   PetscCall(SVDGetDimensions(svd,&nsv,NULL,NULL));
104:   PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of requested generalized singular values: %" PetscInt_FMT "\n",nsv));
105:   PetscCall(SVDGetTolerances(svd,&tol,&maxit));
106:   PetscCall(PetscPrintf(PETSC_COMM_WORLD," Stopping condition: tol=%.4g, maxit=%" PetscInt_FMT "\n",(double)tol,maxit));

108:   /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
109:                     Display solution and clean up
110:      - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

112:   /*
113:      Get number of converged singular triplets
114:   */
115:   PetscCall(SVDGetConverged(svd,&nconv));
116:   PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of converged approximate singular triplets: %" PetscInt_FMT "\n\n",nconv));

118:   if (nconv>0) {
119:     /*
120:        Create vectors. The interface returns u and v as stacked on top of each other
121:        [u;v] so need to create a special vector (VecNest) to extract them
122:     */
123:     PetscCall(MatCreateVecs(A,&x,&u));
124:     PetscCall(MatCreateVecs(B,NULL,&v));
125:     aux[0] = u;
126:     aux[1] = v;
127:     PetscCall(VecCreateNest(PETSC_COMM_WORLD,2,NULL,aux,&uv));

129:     PetscCall(VecDuplicateVecs(u,nconv,&U));
130:     PetscCall(VecDuplicateVecs(v,nconv,&V));

132:     /*
133:        Display singular values and errors relative to the norms
134:     */
135:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,
136:          "          sigma           ||r||/||[A;B]||\n"
137:          "  --------------------- ------------------\n"));
138:     for (i=0;i<nconv;i++) {
139:       /*
140:          Get converged singular triplets: i-th singular value is stored in sigma
141:       */
142:       PetscCall(SVDGetSingularTriplet(svd,i,&sigma,uv,x));

144:       /* at this point, u and v can be used normally as individual vectors */
145:       PetscCall(VecCopy(u,U[i]));
146:       PetscCall(VecCopy(v,V[i]));

148:       /*
149:          Compute the error associated to each singular triplet
150:       */
151:       PetscCall(SVDComputeError(svd,i,SVD_ERROR_NORM,&error));

153:       PetscCall(PetscPrintf(PETSC_COMM_WORLD,"       % 6f      ",(double)sigma));
154:       PetscCall(PetscPrintf(PETSC_COMM_WORLD,"   % 12g\n",(double)error));
155:     }
156:     PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\n"));

158:     if (!skiporth) {
159:       PetscCall(VecCheckOrthonormality(U,nconv,NULL,nconv,NULL,NULL,&lev1));
160:       PetscCall(VecCheckOrthonormality(V,nconv,NULL,nconv,NULL,NULL,&lev2));
161:     }
162:     if (lev1+lev2<20*tol) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Level of orthogonality below the tolerance\n"));
163:     else PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Level of orthogonality: %g (U) %g (V)\n",(double)lev1,(double)lev2));
164:     PetscCall(VecDestroyVecs(nconv,&U));
165:     PetscCall(VecDestroyVecs(nconv,&V));
166:     PetscCall(VecDestroy(&x));
167:     PetscCall(VecDestroy(&u));
168:     PetscCall(VecDestroy(&v));
169:     PetscCall(VecDestroy(&uv));
170:   }

172:   /*
173:      Free work space
174:   */
175:   PetscCall(SVDDestroy(&svd));
176:   PetscCall(MatDestroy(&A));
177:   PetscCall(MatDestroy(&B));
178:   PetscCall(SlepcFinalize());
179:   return 0;
180: }

182: /*TEST

184:    testset:
185:       filter: grep -v "Solution method" | grep -v "Number of iterations" | sed -e "s/, maxit=1[0]*$//" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
186:       requires: double
187:       test:
188:          args: -svd_type lapack -m 20 -n 10 -p 6
189:          suffix: 1
190:       test:
191:          args: -svd_type lapack -m 15 -n 20 -p 10 -svd_smallest
192:          suffix: 2
193:       test:
194:          args: -svd_type lapack -m 15 -n 20 -p 21
195:          suffix: 3
196:       test:
197:          args: -svd_type lapack -m 20 -n 15 -p 21
198:          suffix: 4

200:    testset:
201:       args: -m 25 -n 20 -p 21 -svd_smallest -svd_nsv 2
202:       filter: grep -v "Solution method" | grep -v "Number of iterations" | sed -e "s/, maxit=1[0]*$//" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
203:       requires: double
204:       output_file: output/ex45_5.out
205:       test:
206:          args: -svd_type trlanczos -svd_ncv 8 -svd_trlanczos_gbidiag {{upper lower}} -svd_trlanczos_oneside {{0 1}}
207:          suffix: 5
208:       test:
209:          args: -svd_type cross -svd_ncv 10 -svd_cross_explicitmatrix
210:          suffix: 5_cross
211:       test:
212:          args: -svd_type cross -svd_ncv 10 -svd_cross_eps_type krylovschur -svd_cross_st_type sinvert -svd_cross_eps_target 0 -svd_cross_st_ksp_type gmres -svd_cross_st_pc_type jacobi
213:          suffix: 5_cross_implicit
214:       test:
215:          args: -svd_type cyclic -svd_ncv 12 -svd_cyclic_explicitmatrix {{0 1}}
216:          suffix: 5_cyclic
217:          requires: !complex

219:    testset:
220:       args: -m 15 -n 20 -p 21 -svd_nsv 4 -svd_ncv 9
221:       filter: grep -v "Solution method" | grep -v "Number of iterations" | sed -e "s/7.884967/7.884968/" | sed -e "s/, maxit=1[0]*$//" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
222:       requires: double
223:       output_file: output/ex45_6.out
224:       test:
225:          args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single upper lower}} -svd_trlanczos_locking {{0 1}} -svd_trlanczos_oneside {{0 1}}
226:          suffix: 6
227:       test:
228:          args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
229:          suffix: 6_cross

231:    test:
232:       args: -m 15 -n 20 -p 21 -svd_nsv 4 -svd_ncv 9 -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
233:       filter: grep -v "Number of iterations" | sed -e "s/7.884967/7.884968/" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
234:       requires: double
235:       suffix: 6_cyclic
236:       output_file: output/ex45_6_cyclic.out

238:    testset:
239:       args: -m 20 -n 15 -p 21 -svd_nsv 4 -svd_ncv 9
240:       filter: grep -v "Solution method" | grep -v "Number of iterations" | sed -e "s/, maxit=1[0]*$//" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
241:       requires: double
242:       output_file: output/ex45_7.out
243:       test:
244:          args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single upper lower}} -svd_trlanczos_restart 0.4 -svd_trlanczos_oneside {{0 1}}
245:          suffix: 7
246:       test:
247:          args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
248:          suffix: 7_cross

250:    test:
251:       args: -m 20 -n 15 -p 21 -svd_nsv 4 -svd_ncv 16 -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
252:       filter: grep -v "Number of iterations" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
253:       requires: double
254:       suffix: 7_cyclic
255:       output_file: output/ex45_7_cyclic.out

257:    test:
258:        args: -m 25 -n 20 -p 21 -svd_smallest -svd_nsv 2 -svd_ncv 5 -svd_type trlanczos -svd_trlanczos_gbidiag {{upper lower}} -svd_trlanczos_scale {{0.1 -20}}
259:        filter: grep -v "Solution method" | grep -v "Number of iterations" | grep -v "Stopping condition" | sed -e "s/, maxit=1[0]*$//" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
260:        suffix: 8

262: TEST*/