GCC Code Coverage Report

Directory: ./
File: src/pep/tutorials/nlevp/pdde_stability.c
Date: 2025-12-10 04:20:18
Exec Total Coverage
Lines: 60 64 93.8%
Functions: 2 2 100.0%
Branches: 146 240 60.8%
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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 This example implements one of the problems found at
12 NLEVP: A Collection of Nonlinear Eigenvalue Problems,
13 The University of Manchester.
14 The details of the collection can be found at:
15 [1] T. Betcke et al., "NLEVP: A Collection of Nonlinear Eigenvalue
16 Problems", ACM Trans. Math. Software 39(2), Article 7, 2013.
17
18 The pdde_stability problem is a complex-symmetric QEP from the stability
19 analysis of a discretized partial delay-differential equation. It requires
20 complex scalars.
21 */
22
23 static char help[] = "Stability analysis of a discretized partial delay-differential equation.\n\n"
24 "The command line options are:\n"
25 " -m <m>, grid size, the matrices have dimension n=m*m.\n"
26 " -c <a0,b0,a1,b1,a2,b2,phi1>, comma-separated list of 7 real parameters.\n\n";
27
28 #include <slepcpep.h>
29
30 #define NMAT 3
31
32 /*
33 Function for user-defined eigenvalue ordering criterion.
34
35 Given two eigenvalues ar+i*ai and br+i*bi, the subroutine must choose
36 one of them as the preferred one according to the criterion.
37 In this example, the preferred value is the one with absolute value closest to 1.
38 */
39 83150 PetscErrorCode MyEigenSort(PetscScalar ar,PetscScalar ai,PetscScalar br,PetscScalar bi,PetscInt *r,void *ctx)
40 {
41 83150 PetscReal aa,ab;
42
43
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 83150 PetscFunctionBeginUser;
44 83150 aa = PetscAbsReal(SlepcAbsEigenvalue(ar,ai)-PetscRealConstant(1.0));
45 83150 ab = PetscAbsReal(SlepcAbsEigenvalue(br,bi)-PetscRealConstant(1.0));
46
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 83150 *r = aa > ab ? 1 : (aa < ab ? -1 : 0);
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 83150 PetscFunctionReturn(PETSC_SUCCESS);
48 }
49
50 15 int main(int argc,char **argv)
51 {
52 15 Mat A[NMAT]; /* problem matrices */
53 15 PEP pep; /* polynomial eigenproblem solver context */
54 15 PetscInt m=15,n,II,Istart,Iend,i,j,k;
55 15 PetscReal h,xi,xj,c[7] = { 2, .3, -2, .2, -2, -.3, -PETSC_PI/2 };
56 15 PetscScalar alpha,beta,gamma;
57 15 PetscBool flg,terse;
58
59
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 15 PetscFunctionBeginUser;
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 15 PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
61 #if !defined(PETSC_USE_COMPLEX)
62 SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"This example requires complex scalars");
63 #endif
64
65
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 15 PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
66 15 n = m*m;
67 15 h = PETSC_PI/(m+1);
68 15 gamma = PetscExpScalar(PETSC_i*c[6]);
69 15 gamma = gamma/PetscAbsScalar(gamma);
70 15 k = 7;
71
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 15 PetscCall(PetscOptionsGetRealArray(NULL,NULL,"-c",c,&k,&flg));
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 15 PetscCheck(!flg || k==7,PETSC_COMM_WORLD,PETSC_ERR_USER,"The number of parameters -c should be 7, you provided %" PetscInt_FMT,k);
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 15 PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nPDDE stability, n=%" PetscInt_FMT " (m=%" PetscInt_FMT ")\n\n",n,m));
74
75 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
76 Compute the polynomial matrices
77 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
78
79 /* initialize matrices */
80
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 60 for (i=0;i<NMAT;i++) {
81
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 45 PetscCall(MatCreate(PETSC_COMM_WORLD,&A[i]));
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 45 PetscCall(MatSetSizes(A[i],PETSC_DECIDE,PETSC_DECIDE,n,n));
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 45 PetscCall(MatSetFromOptions(A[i]));
84 }
85
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 15 PetscCall(MatGetOwnershipRange(A[0],&Istart,&Iend));
86
87 /* A[1] has a pattern similar to the 2D Laplacian */
88
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 3390 for (II=Istart;II<Iend;II++) {
89 3375 i = II/m; j = II-i*m;
90 3375 xi = (i+1)*h; xj = (j+1)*h;
91 3375 alpha = c[0]+c[1]*PetscSinReal(xi)+gamma*(c[2]+c[3]*xi*(1.0-PetscExpReal(xi-PETSC_PI)));
92 3375 beta = c[0]+c[1]*PetscSinReal(xj)-gamma*(c[2]+c[3]*xj*(1.0-PetscExpReal(xj-PETSC_PI)));
93
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 3375 PetscCall(MatSetValue(A[1],II,II,alpha+beta-4.0/(h*h),INSERT_VALUES));
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 3375 if (j>0) PetscCall(MatSetValue(A[1],II,II-1,1.0/(h*h),INSERT_VALUES));
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 3375 if (j<m-1) PetscCall(MatSetValue(A[1],II,II+1,1.0/(h*h),INSERT_VALUES));
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 3375 if (i>0) PetscCall(MatSetValue(A[1],II,II-m,1.0/(h*h),INSERT_VALUES));
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 3375 if (i<m-1) PetscCall(MatSetValue(A[1],II,II+m,1.0/(h*h),INSERT_VALUES));
98 }
99
100 /* A[0] and A[2] are diagonal */
101
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 3390 for (II=Istart;II<Iend;II++) {
102 3375 i = II/m; j = II-i*m;
103 3375 xi = (i+1)*h; xj = (j+1)*h;
104 3375 alpha = c[4]+c[5]*xi*(PETSC_PI-xi);
105 3375 beta = c[4]+c[5]*xj*(PETSC_PI-xj);
106
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 3375 PetscCall(MatSetValue(A[0],II,II,alpha,INSERT_VALUES));
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 3375 PetscCall(MatSetValue(A[2],II,II,beta,INSERT_VALUES));
108 }
109
110 /* assemble matrices */
111
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 60 for (i=0;i<NMAT;i++) PetscCall(MatAssemblyBegin(A[i],MAT_FINAL_ASSEMBLY));
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 60 for (i=0;i<NMAT;i++) PetscCall(MatAssemblyEnd(A[i],MAT_FINAL_ASSEMBLY));
113
114 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
115 Create the eigensolver and solve the problem
116 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
117
118
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 15 PetscCall(PEPCreate(PETSC_COMM_WORLD,&pep));
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 15 PetscCall(PEPSetOperators(pep,NMAT,A));
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 15 PetscCall(PEPSetEigenvalueComparison(pep,MyEigenSort,NULL));
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 15 PetscCall(PEPSetDimensions(pep,4,PETSC_DETERMINE,PETSC_DETERMINE));
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 15 PetscCall(PEPSetFromOptions(pep));
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 15 PetscCall(PEPSolve(pep));
124
125 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
126 Display solution and clean up
127 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
128
129 /* show detailed info unless -terse option is given by user */
130
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 15 PetscCall(PetscOptionsHasName(NULL,NULL,"-terse",&terse));
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 15 if (terse) PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,NULL));
132 else {
133 ✗ PetscCall(PetscViewerPushFormat(PETSC_VIEWER_STDOUT_WORLD,PETSC_VIEWER_ASCII_INFO_DETAIL));
134 ✗ PetscCall(PEPConvergedReasonView(pep,PETSC_VIEWER_STDOUT_WORLD));
135 ✗ PetscCall(PEPErrorView(pep,PEP_ERROR_BACKWARD,PETSC_VIEWER_STDOUT_WORLD));
136 ✗ PetscCall(PetscViewerPopFormat(PETSC_VIEWER_STDOUT_WORLD));
137 }
138
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 15 PetscCall(PEPDestroy(&pep));
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 60 for (i=0;i<NMAT;i++) PetscCall(MatDestroy(&A[i]));
140
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 15 PetscCall(SlepcFinalize());
141 return 0;
142 }
143
144 /*TEST
145
146 build:
147 requires: complex
148
149 test:
150 suffix: 1
151 args: -pep_type {{toar qarnoldi linear}} -pep_ncv 25 -terse
152 requires: complex double
153
154 TEST*/
155