Actual source code: ex45.c
slepc-3.20.2 2024-03-15
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));
47: PetscCall(MatSetUp(A));
49: PetscCall(MatGetOwnershipRange(A,&Istart,&Iend));
50: for (i=Istart;i<Iend;i++) {
51: if (i>0 && i-1<n) PetscCall(MatSetValue(A,i,i-1,-1.0,INSERT_VALUES));
52: if (i+1<n) PetscCall(MatSetValue(A,i,i+1,-1.0,INSERT_VALUES));
53: if (i<n) PetscCall(MatSetValue(A,i,i,2.0,INSERT_VALUES));
54: if (i>n) PetscCall(MatSetValue(A,i,n-1,1.0,INSERT_VALUES));
55: }
56: PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY));
57: PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY));
59: PetscCall(MatCreate(PETSC_COMM_WORLD,&B));
60: PetscCall(MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,p,n));
61: PetscCall(MatSetFromOptions(B));
62: PetscCall(MatSetUp(B));
64: PetscCall(MatGetOwnershipRange(B,&Istart,&Iend));
65: d = PetscMax(0,n-p);
66: for (i=Istart;i<Iend;i++) {
67: for (j=0;j<=PetscMin(i,n-1);j++) PetscCall(MatSetValue(B,i,j+d,1.0,INSERT_VALUES));
68: }
69: PetscCall(MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY));
70: PetscCall(MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY));
72: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
73: Create the singular value solver and set various options
74: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
76: /*
77: Create singular value solver context
78: */
79: PetscCall(SVDCreate(PETSC_COMM_WORLD,&svd));
81: /*
82: Set operators and problem type
83: */
84: PetscCall(SVDSetOperators(svd,A,B));
85: PetscCall(SVDSetProblemType(svd,SVD_GENERALIZED));
87: /*
88: Set solver parameters at runtime
89: */
90: PetscCall(SVDSetFromOptions(svd));
92: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
93: Solve the singular value system
94: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
96: PetscCall(SVDSolve(svd));
97: PetscCall(SVDGetIterationNumber(svd,&its));
98: PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of iterations of the method: %" PetscInt_FMT "\n",its));
100: /*
101: Optional: Get some information from the solver and display it
102: */
103: PetscCall(SVDGetType(svd,&type));
104: PetscCall(PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type));
105: PetscCall(SVDGetDimensions(svd,&nsv,NULL,NULL));
106: PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of requested generalized singular values: %" PetscInt_FMT "\n",nsv));
107: PetscCall(SVDGetTolerances(svd,&tol,&maxit));
108: PetscCall(PetscPrintf(PETSC_COMM_WORLD," Stopping condition: tol=%.4g, maxit=%" PetscInt_FMT "\n",(double)tol,maxit));
110: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
111: Display solution and clean up
112: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
114: /*
115: Get number of converged singular triplets
116: */
117: PetscCall(SVDGetConverged(svd,&nconv));
118: PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of converged approximate singular triplets: %" PetscInt_FMT "\n\n",nconv));
120: if (nconv>0) {
121: /*
122: Create vectors. The interface returns u and v as stacked on top of each other
123: [u;v] so need to create a special vector (VecNest) to extract them
124: */
125: PetscCall(MatCreateVecs(A,&x,&u));
126: PetscCall(MatCreateVecs(B,NULL,&v));
127: aux[0] = u;
128: aux[1] = v;
129: PetscCall(VecCreateNest(PETSC_COMM_WORLD,2,NULL,aux,&uv));
131: PetscCall(VecDuplicateVecs(u,nconv,&U));
132: PetscCall(VecDuplicateVecs(v,nconv,&V));
134: /*
135: Display singular values and errors relative to the norms
136: */
137: PetscCall(PetscPrintf(PETSC_COMM_WORLD,
138: " sigma ||r||/||[A;B]||\n"
139: " --------------------- ------------------\n"));
140: for (i=0;i<nconv;i++) {
141: /*
142: Get converged singular triplets: i-th singular value is stored in sigma
143: */
144: PetscCall(SVDGetSingularTriplet(svd,i,&sigma,uv,x));
146: /* at this point, u and v can be used normally as individual vectors */
147: PetscCall(VecCopy(u,U[i]));
148: PetscCall(VecCopy(v,V[i]));
150: /*
151: Compute the error associated to each singular triplet
152: */
153: PetscCall(SVDComputeError(svd,i,SVD_ERROR_NORM,&error));
155: PetscCall(PetscPrintf(PETSC_COMM_WORLD," % 6f ",(double)sigma));
156: PetscCall(PetscPrintf(PETSC_COMM_WORLD," % 12g\n",(double)error));
157: }
158: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\n"));
160: if (!skiporth) {
161: PetscCall(VecCheckOrthonormality(U,nconv,NULL,nconv,NULL,NULL,&lev1));
162: PetscCall(VecCheckOrthonormality(V,nconv,NULL,nconv,NULL,NULL,&lev2));
163: }
164: if (lev1+lev2<20*tol) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Level of orthogonality below the tolerance\n"));
165: else PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Level of orthogonality: %g (U) %g (V)\n",(double)lev1,(double)lev2));
166: PetscCall(VecDestroyVecs(nconv,&U));
167: PetscCall(VecDestroyVecs(nconv,&V));
168: PetscCall(VecDestroy(&x));
169: PetscCall(VecDestroy(&u));
170: PetscCall(VecDestroy(&v));
171: PetscCall(VecDestroy(&uv));
172: }
174: /*
175: Free work space
176: */
177: PetscCall(SVDDestroy(&svd));
178: PetscCall(MatDestroy(&A));
179: PetscCall(MatDestroy(&B));
180: PetscCall(SlepcFinalize());
181: return 0;
182: }
184: /*TEST
186: testset:
187: 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"
188: requires: double
189: test:
190: args: -svd_type lapack -m 20 -n 10 -p 6
191: suffix: 1
192: test:
193: args: -svd_type lapack -m 15 -n 20 -p 10 -svd_smallest
194: suffix: 2
195: test:
196: args: -svd_type lapack -m 15 -n 20 -p 21
197: suffix: 3
198: test:
199: args: -svd_type lapack -m 20 -n 15 -p 21
200: suffix: 4
202: testset:
203: args: -m 25 -n 20 -p 21 -svd_smallest -svd_nsv 2
204: 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"
205: requires: double
206: output_file: output/ex45_5.out
207: test:
208: args: -svd_type trlanczos -svd_ncv 8 -svd_trlanczos_gbidiag {{upper lower}} -svd_trlanczos_oneside {{0 1}}
209: suffix: 5
210: test:
211: args: -svd_type cross -svd_ncv 10 -svd_cross_explicitmatrix
212: suffix: 5_cross
213: test:
214: 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
215: suffix: 5_cross_implicit
216: test:
217: args: -svd_type cyclic -svd_ncv 12 -svd_cyclic_explicitmatrix {{0 1}}
218: suffix: 5_cyclic
219: requires: !complex
221: testset:
222: args: -m 15 -n 20 -p 21 -svd_nsv 4 -svd_ncv 9
223: 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"
224: requires: double
225: output_file: output/ex45_6.out
226: test:
227: args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single upper lower}} -svd_trlanczos_locking {{0 1}} -svd_trlanczos_oneside {{0 1}}
228: suffix: 6
229: test:
230: args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
231: suffix: 6_cross
233: test:
234: args: -m 15 -n 20 -p 21 -svd_nsv 4 -svd_ncv 9 -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
235: 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"
236: requires: double
237: suffix: 6_cyclic
238: output_file: output/ex45_6_cyclic.out
240: testset:
241: args: -m 20 -n 15 -p 21 -svd_nsv 4 -svd_ncv 9
242: 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"
243: requires: double
244: output_file: output/ex45_7.out
245: test:
246: args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single upper lower}} -svd_trlanczos_restart 0.4 -svd_trlanczos_oneside {{0 1}}
247: suffix: 7
248: test:
249: args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
250: suffix: 7_cross
252: test:
253: args: -m 20 -n 15 -p 21 -svd_nsv 4 -svd_ncv 16 -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
254: filter: grep -v "Number of iterations" | sed -e "s/[0-9]\.[0-9]*e[+-]\([0-9]*\)/removed/g"
255: requires: double
256: suffix: 7_cyclic
257: output_file: output/ex45_7_cyclic.out
259: test:
260: 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}}
261: 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"
262: suffix: 8
264: TEST*/