Actual source code: test21.c
slepc-3.21.2 2024-09-25
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[] = "Test DSGSVD.\n\n";
13: #include <slepcds.h>
15: int main(int argc,char **argv)
16: {
17: DS ds;
18: SlepcSC sc;
19: Mat X;
20: Vec x0;
21: PetscReal sigma,rnorm,cond;
22: PetscScalar *A,*B,*w;
23: PetscInt i,j,k,n=15,m=10,p=10,m1,p1,ld;
24: PetscViewer viewer;
25: PetscBool verbose;
27: PetscFunctionBeginUser;
28: PetscCall(SlepcInitialize(&argc,&argv,(char*)0,help));
29: PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
30: PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
31: PetscCall(PetscOptionsGetInt(NULL,NULL,"-p",&p,NULL));
32: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Solve a Dense System of type GSVD - dimension (%" PetscInt_FMT "+%" PetscInt_FMT ")x%" PetscInt_FMT ".\n",n,p,m));
33: PetscCall(PetscOptionsHasName(NULL,NULL,"-verbose",&verbose));
35: /* Create DS object */
36: PetscCall(DSCreate(PETSC_COMM_WORLD,&ds));
37: PetscCall(DSSetType(ds,DSGSVD));
38: PetscCall(DSSetFromOptions(ds));
39: ld = PetscMax(PetscMax(p,m),n)+2; /* test leading dimension larger than n */
40: PetscCall(DSAllocate(ds,ld));
41: PetscCall(DSSetDimensions(ds,n,0,0));
42: PetscCall(DSGSVDSetDimensions(ds,m,p));
43: PetscCall(DSGSVDGetDimensions(ds,&m1,&p1));
44: PetscCheck(m1==m && p1==p,PETSC_COMM_WORLD,PETSC_ERR_PLIB,"Inconsistent dimension values");
46: /* Set up viewer */
47: PetscCall(PetscViewerASCIIGetStdout(PETSC_COMM_WORLD,&viewer));
48: PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO_DETAIL));
49: PetscCall(DSView(ds,viewer));
50: PetscCall(PetscViewerPopFormat(viewer));
52: k = PetscMin(n,m);
53: /* Fill A with a rectangular Toeplitz matrix */
54: PetscCall(DSGetArray(ds,DS_MAT_A,&A));
55: for (i=0;i<k;i++) A[i+i*ld]=1.0;
56: for (j=1;j<3;j++) {
57: for (i=0;i<n-j;i++) { if ((i+j)<m) A[i+(i+j)*ld]=(PetscScalar)(j+1); }
58: }
59: for (j=1;j<n/2;j++) {
60: for (i=0;i<n-j;i++) { if ((i+j)<n && i<m) A[(i+j)+i*ld]=-1.0; }
61: }
62: PetscCall(DSRestoreArray(ds,DS_MAT_A,&A));
64: k = PetscMin(p,m);
65: /* Fill B with a shifted bidiagonal matrix */
66: PetscCall(DSGetArray(ds,DS_MAT_B,&B));
67: for (i=m-k;i<m;i++) {
68: B[i-m+k+i*ld]=2.0-1.0/(PetscScalar)(i+1);
69: if (i) B[i-1-m+k+i*ld]=1.0;
70: }
71: PetscCall(DSRestoreArray(ds,DS_MAT_B,&B));
73: PetscCall(DSSetState(ds,DS_STATE_RAW));
74: if (verbose) {
75: PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_MATLAB));
76: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Initial - - - - - - - - -\n"));
77: }
78: PetscCall(DSView(ds,viewer));
80: /* Condition number */
81: PetscCall(DSCond(ds,&cond));
82: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Condition number = %.3f\n",(double)cond));
84: /* Solve */
85: PetscCall(PetscMalloc1(m,&w));
86: PetscCall(DSGetSlepcSC(ds,&sc));
87: sc->comparison = SlepcCompareLargestReal;
88: sc->comparisonctx = NULL;
89: sc->map = NULL;
90: sc->mapobj = NULL;
91: PetscCall(DSSolve(ds,w,NULL));
92: PetscCall(DSSort(ds,w,NULL,NULL,NULL,NULL));
93: PetscCall(DSSynchronize(ds,w,NULL));
94: if (verbose) {
95: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"After solve - - - - - - - - -\n"));
96: PetscCall(DSView(ds,viewer));
97: }
98: /* Print singular values */
99: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Computed singular values =\n"));
100: PetscCall(DSGetDimensions(ds,NULL,NULL,NULL,&k));
101: for (i=0;i<k;i++) {
102: sigma = PetscRealPart(w[i]);
103: PetscCall(PetscViewerASCIIPrintf(viewer," %g\n",(double)sigma));
104: }
106: /* Singular vectors */
107: PetscCall(DSVectors(ds,DS_MAT_X,NULL,NULL)); /* all singular vectors */
108: PetscCall(DSGetMat(ds,DS_MAT_X,&X));
109: PetscCall(MatCreateVecs(X,NULL,&x0));
110: PetscCall(MatGetColumnVector(X,x0,0));
111: PetscCall(VecNorm(x0,NORM_2,&rnorm));
112: PetscCall(DSRestoreMat(ds,DS_MAT_X,&X));
113: PetscCall(VecDestroy(&x0));
114: PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Norm of 1st X vector = %.3f\n",(double)rnorm));
116: PetscCall(DSGetMat(ds,DS_MAT_U,&X));
117: PetscCall(MatCreateVecs(X,NULL,&x0));
118: PetscCall(MatGetColumnVector(X,x0,0));
119: PetscCall(VecNorm(x0,NORM_2,&rnorm));
120: PetscCall(DSRestoreMat(ds,DS_MAT_U,&X));
121: PetscCall(VecDestroy(&x0));
122: if (PetscAbs(rnorm-1.0)>10*PETSC_MACHINE_EPSILON) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Warning: the 1st U vector has norm %g\n",(double)rnorm));
124: PetscCall(DSGetMat(ds,DS_MAT_V,&X));
125: PetscCall(MatCreateVecs(X,NULL,&x0));
126: PetscCall(MatGetColumnVector(X,x0,0));
127: PetscCall(VecNorm(x0,NORM_2,&rnorm));
128: PetscCall(DSRestoreMat(ds,DS_MAT_V,&X));
129: PetscCall(VecDestroy(&x0));
130: if (PetscAbs(rnorm-1.0)>10*PETSC_MACHINE_EPSILON) PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Warning: the 1st V vector has norm %g\n",(double)rnorm));
132: PetscCall(PetscFree(w));
133: PetscCall(DSDestroy(&ds));
134: PetscCall(SlepcFinalize());
135: return 0;
136: }
138: /*TEST
140: testset:
141: output_file: output/test21_1.out
142: requires: !single
143: nsize: {{1 2 3}}
144: filter: grep -v "parallel operation mode" | grep -v " MPI process"
145: test:
146: suffix: 1
147: args: -ds_parallel redundant
148: test:
149: suffix: 2
150: args: -ds_parallel synchronized
152: TEST*/