GCC Code Coverage Report

Directory:	./
File:	src/eps/tutorials/ex18.c
Date:	2025-11-19 04:19:03

	Exec	Total	Coverage
Lines:	76	82	92.7%
Functions:	3	3	100.0%
Branches:	176	296	59.5%

  
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      /*
    
         - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    
         SLEPc - Scalable Library for Eigenvalue Problem Computations
    
         Copyright (c) 2002-, Universitat Politecnica de Valencia, Spain
    
         This file is part of SLEPc.
    
         SLEPc is distributed under a 2-clause BSD license (see LICENSE).
    
         - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    
      */
    
      static char help[] = "Solves the same problem as in ex5, but with a user-defined sorting criterion.\n\n"
    
        "It is a standard nonsymmetric eigenproblem with real eigenvalues and the rightmost eigenvalue is known to be 1.\n"
    
        "This example illustrates how the user can set a custom spectrum selection.\n\n"
    
        "The command line options are:\n"
    
        "  -m <m>, where <m> = number of grid subdivisions in each dimension.\n\n";
    
      #include <slepceps.h>
    
      /*
    
         User-defined routines
    
      */
    
      PetscErrorCode MyEigenSort(PetscScalar ar,PetscScalar ai,PetscScalar br,PetscScalar bi,PetscInt *r,void *ctx);
    
      PetscErrorCode MatMarkovModel(PetscInt m,Mat A);
    
      10
      int main(int argc,char **argv)
    
      {
    
      10
        Mat            A;               /* operator matrix */
    
      10
        EPS            eps;             /* eigenproblem solver context */
    
      10
        EPSType        type;
    
      10
        PetscScalar    target=0.5;
    
      10
        PetscInt       N,m=15,nev;
    
      10
        PetscBool      terse;
    
      10
        PetscViewer    viewer;
    
      10
        char           str[50];
    
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      10
        PetscFunctionBeginUser;
    
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      10
        PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
    
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      10
        PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
    
      10
        N = m*(m+1)/2;
    
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      10
        PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nMarkov Model, N=%" PetscInt_FMT " (m=%" PetscInt_FMT ")\n",N,m));
    
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      10
        PetscCall(PetscOptionsGetScalar(NULL,NULL,"-target",&target,NULL));
    
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      10
        PetscCall(SlepcSNPrintfScalar(str,sizeof(str),target,PETSC_FALSE));
    
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      10
        PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Searching closest eigenvalues to the right of %s.\n\n",str));
    
        /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    
           Compute the operator matrix that defines the eigensystem, Ax=kx
    
           - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    
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      10
        PetscCall(MatCreate(PETSC_COMM_WORLD,&A));
    
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      10
        PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N));
    
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      10
        PetscCall(MatSetFromOptions(A));
    
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      10
        PetscCall(MatMarkovModel(m,A));
    
        /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    
                      Create the eigensolver and set various options
    
           - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    
        /*
    
           Create eigensolver context
    
        */
    
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      10
        PetscCall(EPSCreate(PETSC_COMM_WORLD,&eps));
    
        /*
    
           Set operators. In this case, it is a standard eigenvalue problem
    
        */
    
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      10
        PetscCall(EPSSetOperators(eps,A,NULL));
    
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      10
        PetscCall(EPSSetProblemType(eps,EPS_NHEP));
    
        /*
    
           Set the custom comparing routine in order to obtain the eigenvalues
    
           closest to the target on the right only
    
        */
    
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      10
        PetscCall(EPSSetEigenvalueComparison(eps,MyEigenSort,&target));
    
        /*
    
           Set solver parameters at runtime
    
        */
    
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      10
        PetscCall(EPSSetFromOptions(eps));
    
        /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    
                            Solve the eigensystem
    
           - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    
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      10
        PetscCall(EPSSolve(eps));
    
        /*
    
           Optional: Get some information from the solver and display it
    
        */
    
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      10
        PetscCall(EPSGetType(eps,&type));
    
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      10
        PetscCall(PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type));
    
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      10
        PetscCall(EPSGetDimensions(eps,&nev,NULL,NULL));
    
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      10
        PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of requested eigenvalues: %" PetscInt_FMT "\n",nev));
    
        /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    
                          Display solution and clean up
    
           - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
    
        /* show detailed info unless -terse option is given by user */
    
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      10
        PetscCall(PetscOptionsHasName(NULL,NULL,"-terse",&terse));
    
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      10
        if (terse) PetscCall(EPSErrorView(eps,EPS_ERROR_RELATIVE,NULL));
    
        else {
    
      ✗
          PetscCall(PetscViewerASCIIGetStdout(PETSC_COMM_WORLD,&viewer));
    
      ✗
          PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO_DETAIL));
    
      ✗
          PetscCall(EPSConvergedReasonView(eps,viewer));
    
      ✗
          PetscCall(EPSErrorView(eps,EPS_ERROR_RELATIVE,viewer));
    
      ✗
          PetscCall(PetscViewerPopFormat(viewer));
    
        }
    
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      10
        PetscCall(EPSDestroy(&eps));
    
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      10
        PetscCall(MatDestroy(&A));
    
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      10
        PetscCall(SlepcFinalize());
    
        return 0;
    
      }
    
      /*
    
          Matrix generator for a Markov model of a random walk on a triangular grid.
    
          This subroutine generates a test matrix that models a random walk on a
    
          triangular grid. This test example was used by G. W. Stewart ["{SRRIT} - a
    
          FORTRAN subroutine to calculate the dominant invariant subspaces of a real
    
          matrix", Tech. report. TR-514, University of Maryland (1978).] and in a few
    
          papers on eigenvalue problems by Y. Saad [see e.g. LAA, vol. 34, pp. 269-295
    
          (1980) ]. These matrices provide reasonably easy test problems for eigenvalue
    
          algorithms. The transpose of the matrix  is stochastic and so it is known
    
          that one is an exact eigenvalue. One seeks the eigenvector of the transpose
    
          associated with the eigenvalue unity. The problem is to calculate the steady
    
          state probability distribution of the system, which is the eigevector
    
          associated with the eigenvalue one and scaled in such a way that the sum all
    
          the components is equal to one.
    
          Note: the code will actually compute the transpose of the stochastic matrix
    
          that contains the transition probabilities.
    
      */
    
      10
      PetscErrorCode MatMarkovModel(PetscInt m,Mat A)
    
      {
    
      10
        const PetscReal cst = 0.5/(PetscReal)(m-1);
    
      10
        PetscReal       pd,pu;
    
      10
        PetscInt        Istart,Iend,i,j,jmax,ix=0;
    
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      10
        PetscFunctionBeginUser;
    
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      10
        PetscCall(MatGetOwnershipRange(A,&Istart,&Iend));
    
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      160
        for (i=1;i<=m;i++) {
    
      150
          jmax = m-i+1;
    
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      1350
          for (j=1;j<=jmax;j++) {
    
      1200
            ix = ix + 1;
    
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      1200
            if (ix-1<Istart || ix>Iend) continue;  /* compute only owned rows */
    
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      1200
            if (j!=jmax) {
    
      1050
              pd = cst*(PetscReal)(i+j-1);
    
              /* north */
    
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      1050
              if (i==1) PetscCall(MatSetValue(A,ix-1,ix,2*pd,INSERT_VALUES));
    
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      910
              else PetscCall(MatSetValue(A,ix-1,ix,pd,INSERT_VALUES));
    
              /* east */
    
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      1050
              if (j==1) PetscCall(MatSetValue(A,ix-1,ix+jmax-1,2*pd,INSERT_VALUES));
    
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      910
              else PetscCall(MatSetValue(A,ix-1,ix+jmax-1,pd,INSERT_VALUES));
    
            }
    
            /* south */
    
      1200
            pu = 0.5 - cst*(PetscReal)(i+j-3);
    
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      1200
            if (j>1) PetscCall(MatSetValue(A,ix-1,ix-2,pu,INSERT_VALUES));
    
            /* west */
    
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      1200
            if (i>1) PetscCall(MatSetValue(A,ix-1,ix-jmax-2,pu,INSERT_VALUES));
    
          }
    
        }
    
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      10
        PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY));
    
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      10
        PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY));
    
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      2
        PetscFunctionReturn(PETSC_SUCCESS);
    
      }
    
      /*
    
          Function for user-defined eigenvalue ordering criterion.
    
          Given two eigenvalues ar+i*ai and br+i*bi, the subroutine must choose
    
          one of them as the preferred one according to the criterion.
    
          In this example, the preferred value is the one closest to the target,
    
          but on the right side.
    
      */
    
      68705
      PetscErrorCode MyEigenSort(PetscScalar ar,PetscScalar ai,PetscScalar br,PetscScalar bi,PetscInt *r,void *ctx)
    
      {
    
      68705
        PetscScalar target = *(PetscScalar*)ctx;
    
      68705
        PetscReal   da,db;
    
      68705
        PetscBool   aisright,bisright;
    
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      68705
        PetscFunctionBeginUser;
    
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      68705
        if (PetscRealPart(target) < PetscRealPart(ar)) aisright = PETSC_TRUE;
    
      38066
        else aisright = PETSC_FALSE;
    
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      68705
        if (PetscRealPart(target) < PetscRealPart(br)) bisright = PETSC_TRUE;
    
      38630
        else bisright = PETSC_FALSE;
    
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      68705
        if (aisright == bisright) {
    
          /* both are on the same side of the target */
    
      58671
          da = SlepcAbsEigenvalue(ar-target,ai);
    
      58671
          db = SlepcAbsEigenvalue(br-target,bi);
    
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      58671
          if (da < db) *r = -1;
    
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      51186
          else if (da > db) *r = 1;
    
      ✗
          else *r = 0;
    
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      10034
        } else if (aisright && !bisright) *r = -1; /* 'a' is on the right */
    
      4735
        else *r = 1;  /* 'b' is on the right */
    
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      68705
        PetscFunctionReturn(PETSC_SUCCESS);
    
      }
    
      /*TEST
    
         test:
    
            suffix: 1
    
            args: -eps_nev 4 -terse
    
            requires: !single
    
            filter: sed -e "s/[+-]0\.0*i//g"
    
      TEST*/

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[] = "Solves the same problem as in ex5, but with a user-defined sorting criterion.\n\n"
12			"It is a standard nonsymmetric eigenproblem with real eigenvalues and the rightmost eigenvalue is known to be 1.\n"
13			"This example illustrates how the user can set a custom spectrum selection.\n\n"
14			"The command line options are:\n"
15			" -m <m>, where <m> = number of grid subdivisions in each dimension.\n\n";
16
17			#include <slepceps.h>
18
19			/*
20			User-defined routines
21			*/
22
23			PetscErrorCode MyEigenSort(PetscScalar ar,PetscScalar ai,PetscScalar br,PetscScalar bi,PetscInt r,void ctx);
24			PetscErrorCode MatMarkovModel(PetscInt m,Mat A);
25
26		10	int main(int argc,char **argv)
27			{
28		10	Mat A; /* operator matrix */
29		10	EPS eps; /* eigenproblem solver context */
30		10	EPSType type;
31		10	PetscScalar target=0.5;
32		10	PetscInt N,m=15,nev;
33		10	PetscBool terse;
34		10	PetscViewer viewer;
35		10	char str[50];
36
37	1/2 ✓ Branch 0 taken 2 times. ✗ Branch 1 not taken.	10	PetscFunctionBeginUser;
38	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(SlepcInitialize(&argc,&argv,NULL,help));
39
40	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(PetscOptionsGetInt(NULL,NULL,"-m",&m,NULL));
41		10	N = m*(m+1)/2;
42	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(PetscPrintf(PETSC_COMM_WORLD,"\nMarkov Model, N=%" PetscInt_FMT " (m=%" PetscInt_FMT ")\n",N,m));
43	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(PetscOptionsGetScalar(NULL,NULL,"-target",&target,NULL));
44	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(SlepcSNPrintfScalar(str,sizeof(str),target,PETSC_FALSE));
45	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(PetscPrintf(PETSC_COMM_WORLD,"Searching closest eigenvalues to the right of %s.\n\n",str));
46
47			/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
48			Compute the operator matrix that defines the eigensystem, Ax=kx
49			- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
50
51	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatCreate(PETSC_COMM_WORLD,&A));
52	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,N,N));
53	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatSetFromOptions(A));
54	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatMarkovModel(m,A));
55
56			/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
57			Create the eigensolver and set various options
58			- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
59
60			/*
61			Create eigensolver context
62			*/
63	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSCreate(PETSC_COMM_WORLD,&eps));
64
65			/*
66			Set operators. In this case, it is a standard eigenvalue problem
67			*/
68	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSSetOperators(eps,A,NULL));
69	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSSetProblemType(eps,EPS_NHEP));
70
71			/*
72			Set the custom comparing routine in order to obtain the eigenvalues
73			closest to the target on the right only
74			*/
75	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSSetEigenvalueComparison(eps,MyEigenSort,&target));
76
77			/*
78			Set solver parameters at runtime
79			*/
80	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSSetFromOptions(eps));
81
82			/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
83			Solve the eigensystem
84			- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
85
86	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSSolve(eps));
87
88			/*
89			Optional: Get some information from the solver and display it
90			*/
91	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSGetType(eps,&type));
92	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(PetscPrintf(PETSC_COMM_WORLD," Solution method: %s\n\n",type));
93	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSGetDimensions(eps,&nev,NULL,NULL));
94	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(PetscPrintf(PETSC_COMM_WORLD," Number of requested eigenvalues: %" PetscInt_FMT "\n",nev));
95
96			/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
97			Display solution and clean up
98			- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
99
100			/* show detailed info unless -terse option is given by user */
101	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(PetscOptionsHasName(NULL,NULL,"-terse",&terse));
102	5/8 ✓ Branch 0 taken 10 times. ✗ Branch 1 not taken. ✓ Branch 2 taken 2 times. ✓ Branch 3 taken 8 times. ✓ Branch 4 taken 2 times. ✗ Branch 5 not taken. ✗ Branch 6 not taken. ✓ Branch 7 taken 2 times.	10	if (terse) PetscCall(EPSErrorView(eps,EPS_ERROR_RELATIVE,NULL));
103			else {
104		✗	PetscCall(PetscViewerASCIIGetStdout(PETSC_COMM_WORLD,&viewer));
105		✗	PetscCall(PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO_DETAIL));
106		✗	PetscCall(EPSConvergedReasonView(eps,viewer));
107		✗	PetscCall(EPSErrorView(eps,EPS_ERROR_RELATIVE,viewer));
108		✗	PetscCall(PetscViewerPopFormat(viewer));
109			}
110	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(EPSDestroy(&eps));
111	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatDestroy(&A));
112	3/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 2 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✗ Branch 5 not taken.	10	PetscCall(SlepcFinalize());
113			return 0;
114			}
115
116			/*
117			Matrix generator for a Markov model of a random walk on a triangular grid.
118
119			This subroutine generates a test matrix that models a random walk on a
120			triangular grid. This test example was used by G. W. Stewart ["{SRRIT} - a
121			FORTRAN subroutine to calculate the dominant invariant subspaces of a real
122			matrix", Tech. report. TR-514, University of Maryland (1978).] and in a few
123			papers on eigenvalue problems by Y. Saad [see e.g. LAA, vol. 34, pp. 269-295
124			(1980) ]. These matrices provide reasonably easy test problems for eigenvalue
125			algorithms. The transpose of the matrix is stochastic and so it is known
126			that one is an exact eigenvalue. One seeks the eigenvector of the transpose
127			associated with the eigenvalue unity. The problem is to calculate the steady
128			state probability distribution of the system, which is the eigevector
129			associated with the eigenvalue one and scaled in such a way that the sum all
130			the components is equal to one.
131
132			Note: the code will actually compute the transpose of the stochastic matrix
133			that contains the transition probabilities.
134			*/
135		10	PetscErrorCode MatMarkovModel(PetscInt m,Mat A)
136			{
137		10	const PetscReal cst = 0.5/(PetscReal)(m-1);
138		10	PetscReal pd,pu;
139		10	PetscInt Istart,Iend,i,j,jmax,ix=0;
140
141	1/2 ✓ Branch 0 taken 2 times. ✗ Branch 1 not taken.	10	PetscFunctionBeginUser;
142	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatGetOwnershipRange(A,&Istart,&Iend));
143	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	160	for (i=1;i<=m;i++) {
144		150	jmax = m-i+1;
145	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	1350	for (j=1;j<=jmax;j++) {
146		1200	ix = ix + 1;
147	2/4 ✓ Branch 0 taken 10 times. ✗ Branch 1 not taken. ✗ Branch 2 not taken. ✓ Branch 3 taken 10 times.	1200	if (ix-1<Istart \|\| ix>Iend) continue; /* compute only owned rows */
148	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	1200	if (j!=jmax) {
149		1050	pd = cst*(PetscReal)(i+j-1);
150			/* north */
151	6/8 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times. ✓ Branch 2 taken 2 times. ✓ Branch 3 taken 8 times. ✓ Branch 4 taken 2 times. ✗ Branch 5 not taken. ✗ Branch 6 not taken. ✓ Branch 7 taken 2 times.	1050	if (i==1) PetscCall(MatSetValue(A,ix-1,ix,2*pd,INSERT_VALUES));
152	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	910	else PetscCall(MatSetValue(A,ix-1,ix,pd,INSERT_VALUES));
153			/* east */
154	6/8 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times. ✓ Branch 2 taken 2 times. ✓ Branch 3 taken 8 times. ✓ Branch 4 taken 2 times. ✗ Branch 5 not taken. ✗ Branch 6 not taken. ✓ Branch 7 taken 2 times.	1050	if (j==1) PetscCall(MatSetValue(A,ix-1,ix+jmax-1,2*pd,INSERT_VALUES));
155	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	910	else PetscCall(MatSetValue(A,ix-1,ix+jmax-1,pd,INSERT_VALUES));
156			}
157			/* south */
158		1200	pu = 0.5 - cst*(PetscReal)(i+j-3);
159	6/8 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times. ✓ Branch 2 taken 2 times. ✓ Branch 3 taken 8 times. ✓ Branch 4 taken 2 times. ✗ Branch 5 not taken. ✗ Branch 6 not taken. ✓ Branch 7 taken 2 times.	1200	if (j>1) PetscCall(MatSetValue(A,ix-1,ix-2,pu,INSERT_VALUES));
160			/* west */
161	6/8 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times. ✓ Branch 2 taken 2 times. ✓ Branch 3 taken 8 times. ✓ Branch 4 taken 2 times. ✗ Branch 5 not taken. ✗ Branch 6 not taken. ✓ Branch 7 taken 2 times.	1200	if (i>1) PetscCall(MatSetValue(A,ix-1,ix-jmax-2,pu,INSERT_VALUES));
162			}
163			}
164	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY));
165	4/6 ✓ Branch 0 taken 2 times. ✓ Branch 1 taken 8 times. ✓ Branch 2 taken 2 times. ✗ Branch 3 not taken. ✗ Branch 4 not taken. ✓ Branch 5 taken 2 times.	10	PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY));
166	5/12 ✓ Branch 0 taken 2 times. ✗ Branch 1 not taken. ✗ Branch 2 not taken. ✓ Branch 3 taken 2 times. ✓ Branch 4 taken 2 times. ✗ Branch 5 not taken. ✓ Branch 6 taken 2 times. ✗ Branch 7 not taken. ✗ Branch 8 not taken. ✓ Branch 9 taken 2 times. ✗ Branch 10 not taken. ✗ Branch 11 not taken.	2	PetscFunctionReturn(PETSC_SUCCESS);
167			}
168
169			/*
170			Function for user-defined eigenvalue ordering criterion.
171
172			Given two eigenvalues ar+iai and br+ibi, the subroutine must choose
173			one of them as the preferred one according to the criterion.
174			In this example, the preferred value is the one closest to the target,
175			but on the right side.
176			*/
177		68705	PetscErrorCode MyEigenSort(PetscScalar ar,PetscScalar ai,PetscScalar br,PetscScalar bi,PetscInt r,void ctx)
178			{
179		68705	PetscScalar target = (PetscScalar)ctx;
180		68705	PetscReal da,db;
181		68705	PetscBool aisright,bisright;
182
183	1/2 ✓ Branch 0 taken 2 times. ✗ Branch 1 not taken.	68705	PetscFunctionBeginUser;
184	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	68705	if (PetscRealPart(target) < PetscRealPart(ar)) aisright = PETSC_TRUE;
185		38066	else aisright = PETSC_FALSE;
186	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	68705	if (PetscRealPart(target) < PetscRealPart(br)) bisright = PETSC_TRUE;
187		38630	else bisright = PETSC_FALSE;
188	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	68705	if (aisright == bisright) {
189			/* both are on the same side of the target */
190		58671	da = SlepcAbsEigenvalue(ar-target,ai);
191		58671	db = SlepcAbsEigenvalue(br-target,bi);
192	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	58671	if (da < db) *r = -1;
193	1/2 ✓ Branch 0 taken 10 times. ✗ Branch 1 not taken.	51186	else if (da > db) *r = 1;
194		✗	else *r = 0;
195	2/2 ✓ Branch 0 taken 10 times. ✓ Branch 1 taken 10 times.	10034	} else if (aisright && !bisright) r = -1; / 'a' is on the right */
196		4735	else r = 1; / 'b' is on the right */
197	5/12 ✓ Branch 0 taken 2 times. ✗ Branch 1 not taken. ✗ Branch 2 not taken. ✓ Branch 3 taken 2 times. ✓ Branch 4 taken 2 times. ✗ Branch 5 not taken. ✓ Branch 6 taken 2 times. ✗ Branch 7 not taken. ✗ Branch 8 not taken. ✓ Branch 9 taken 2 times. ✗ Branch 10 not taken. ✗ Branch 11 not taken.	68705	PetscFunctionReturn(PETSC_SUCCESS);
198			}
199
200			/*TEST
201
202			test:
203			suffix: 1
204			args: -eps_nev 4 -terse
205			requires: !single
206			filter: sed -e "s/[+-]0\.0*i//g"
207
208			TEST*/
209

Function (Line)	Call count	Block coverage
MatMarkovModel (line 135)	called 10 times	82.0%
MyEigenSort (line 177)	called 68705 times	94.0%
main (line 26)	called 10 times	70.0%