GCC Code Coverage Report

Directory: ./
File: src/svd/tests/test16.c
Date: 2025-12-10 04:20:18
Exec Total Coverage
Lines: 54 54 100.0%
Functions: 1 1 100.0%
Branches: 173 272 63.6%
Line Branch Exec Source
1 /*
2 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
3 SLEPc - Scalable Library for Eigenvalue Problem Computations
4 Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain
5
6 This file is part of SLEPc.
7 SLEPc is distributed under a 2-clause BSD license (see LICENSE).
8 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
9 */
10
11 static char help[] = "Tests multiple calls to SVDSolve with equal matrix size (GSVD).\n\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";
16
17 #include <slepcsvd.h>
18
19 /*
20 This example solves two GSVD problems for the bidiagonal matrices
21
22 | 1 2 | | 1 |
23 | 1 2 | | 2 1 |
24 | 1 2 | | 2 1 |
25 A1 = | . . | A2 = | . . |
26 | . . | | . . |
27 | 1 2 | | 2 1 |
28 | 1 2 | | 2 1 |
29
30 with B = tril(ones(p,n))
31 */
32
33 134 int main(int argc,char **argv)
34 {
35 134 Mat A1,A2,B;
36 134 SVD svd;
37 134 PetscInt m=15,n=20,p=21,Istart,Iend,i,j,d,col[2];
38 134 PetscScalar valsa[] = { 1, 2 }, valsb[] = { 2, 1 };
39
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 134 PetscFunctionBeginUser;
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 134 PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
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 134 PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
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 134 PetscCall(PetscOptionsGetInt(NULL,NULL,"-n",&n,NULL));
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 134 PetscCall(PetscOptionsGetInt(NULL,NULL,"-p",&p,NULL));
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 134 PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nGeneralized singular value decomposition, (%" PetscInt_FMT "+%" PetscInt_FMT ")x%" PetscInt_FMT "\n\n",m,p,n));
46
47 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
48 Generate the matrices
49 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
50
51
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 134 PetscCall(MatCreate(PETSC_COMM_WORLD,&A1));
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 134 PetscCall(MatSetSizes(A1,PETSC_DECIDE,PETSC_DECIDE,m,n));
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 134 PetscCall(MatSetFromOptions(A1));
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 134 PetscCall(MatGetOwnershipRange(A1,&Istart,&Iend));
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 1844 for (i=Istart;i<Iend;i++) {
56 1710 col[0]=i; col[1]=i+1;
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 1710 if (i<n-1) PetscCall(MatSetValues(A1,1,&i,2,col,valsa,INSERT_VALUES));
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 1710 else if (i==n-1) PetscCall(MatSetValue(A1,i,col[0],valsa[0],INSERT_VALUES));
59 }
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 134 PetscCall(MatAssemblyBegin(A1,MAT_FINAL_ASSEMBLY));
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 134 PetscCall(MatAssemblyEnd(A1,MAT_FINAL_ASSEMBLY));
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 134 PetscCall(MatCreate(PETSC_COMM_WORLD,&A2));
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 134 PetscCall(MatSetSizes(A2,PETSC_DECIDE,PETSC_DECIDE,m,n));
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 134 PetscCall(MatSetFromOptions(A2));
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 134 PetscCall(MatGetOwnershipRange(A2,&Istart,&Iend));
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 1844 for (i=Istart;i<Iend;i++) {
68 1710 col[0]=i-1; col[1]=i;
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 1710 if (i==0) PetscCall(MatSetValue(A2,i,col[1],valsb[1],INSERT_VALUES));
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 1596 else if (i<n) PetscCall(MatSetValues(A2,1,&i,2,col,valsb,INSERT_VALUES));
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 1710 else if (i==n) PetscCall(MatSetValue(A2,i,col[0],valsb[0],INSERT_VALUES));
72 }
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 134 PetscCall(MatAssemblyBegin(A2,MAT_FINAL_ASSEMBLY));
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 134 PetscCall(MatAssemblyEnd(A2,MAT_FINAL_ASSEMBLY));
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 134 PetscCall(MatCreate(PETSC_COMM_WORLD,&B));
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 134 PetscCall(MatSetSizes(B,PETSC_DECIDE,PETSC_DECIDE,p,n));
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 134 PetscCall(MatSetFromOptions(B));
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 134 PetscCall(MatGetOwnershipRange(B,&Istart,&Iend));
80 134 d = PetscMax(0,n-p);
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 14934 for (j=PetscMax(0,i-5);j<=PetscMin(i,n-1);j++) PetscCall(MatSetValue(B,i,j+d,1.0,INSERT_VALUES));
83 }
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 134 PetscCall(MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY));
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 134 PetscCall(MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY));
86
87 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
88 Create the singular value solver, set options and solve
89 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
90
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 134 PetscCall(SVDCreate(PETSC_COMM_WORLD,&svd));
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 134 PetscCall(SVDSetOperators(svd,A1,B));
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 134 PetscCall(SVDSetFromOptions(svd));
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 134 PetscCall(SVDSolve(svd));
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 134 PetscCall(SVDErrorView(svd,SVD_ERROR_NORM,NULL));
96
97 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
98 Solve second problem
99 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
100
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 134 PetscCall(SVDSetOperators(svd,A2,B));
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 134 PetscCall(SVDSolve(svd));
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 134 PetscCall(SVDErrorView(svd,SVD_ERROR_NORM,NULL));
104
105 /* Free work space */
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 134 PetscCall(SVDDestroy(&svd));
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 134 PetscCall(MatDestroy(&A1));
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 134 PetscCall(MatDestroy(&A2));
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 134 PetscCall(MatDestroy(&B));
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 134 PetscCall(SlepcFinalize());
111 return 0;
112 }
113
114 /*TEST
115
116 testset:
117 args: -svd_nsv 3
118 requires: !single
119 output_file: output/test16_1.out
120 test:
121 suffix: 1_lapack
122 args: -svd_type lapack
123 test:
124 suffix: 1_cross
125 args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
126 test:
127 suffix: 1_cyclic
128 args: -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
129 test:
130 suffix: 1_trlanczos
131 args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single lower}} -svd_trlanczos_ksp_rtol 1e-10
132 requires: double
133 test:
134 suffix: 1_trlanczos_par
135 nsize: 2
136 args: -svd_type trlanczos -ds_parallel {{redundant synchronized}}
137
138 testset:
139 args: -svd_nsv 3 -mat_type aijcusparse
140 requires: cuda !single
141 output_file: output/test16_1.out
142 test:
143 suffix: 2_cross
144 args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
145 test:
146 suffix: 2_cyclic
147 args: -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
148 test:
149 suffix: 2_trlanczos
150 args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single lower}} -svd_trlanczos_ksp_rtol 1e-10
151 requires: double
152
153 testset:
154 args: -svd_nsv 3 -mat_type aijhipsparse
155 requires: hip !single
156 output_file: output/test16_1.out
157 test:
158 suffix: 2_hip_cross
159 args: -svd_type cross -svd_cross_explicitmatrix {{0 1}}
160 test:
161 suffix: 2_hip_cyclic
162 args: -svd_type cyclic -svd_cyclic_explicitmatrix {{0 1}}
163 test:
164 suffix: 2_hip_trlanczos
165 args: -svd_type trlanczos -svd_trlanczos_gbidiag {{single lower}} -svd_trlanczos_ksp_rtol 1e-10
166 requires: double
167
168 TEST*/
169