Actual source code: ex128.c
petsc-3.3-p6 2013-02-11
2: static char help[] = "Tests ILU and ICC factorization with and without matrix ordering on seqsbaij format. Modified from ex30.c\n\
3: Input parameters are:\n\
4: -lf <level> : level of fill for ILU (default is 0)\n\
5: -lu : use full LU or Cholesky factorization\n\
6: -m <value>,-n <value> : grid dimensions\n\
7: Note that most users should employ the KSP interface to the\n\
8: linear solvers instead of using the factorization routines\n\
9: directly.\n\n";
11: #include <petscmat.h>
15: int main(int argc,char **args)
16: {
17: Mat C,sC,sA;
18: PetscInt i,j,m = 5,n = 5,Ii,J,lf = 0;
20: PetscBool CHOLESKY=PETSC_FALSE,TRIANGULAR=PETSC_FALSE,flg;
21: PetscScalar v;
22: IS row,col;
23: MatFactorInfo info;
24: Vec x,y,b,ytmp;
25: PetscReal norm2;
26: PetscRandom rdm;
27: PetscMPIInt size;
29: PetscInitialize(&argc,&args,(char *)0,help);
30: MPI_Comm_size(PETSC_COMM_WORLD,&size);
31: if (size != 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"This is a uniprocessor example only!");
32: PetscOptionsGetInt(PETSC_NULL,"-m",&m,PETSC_NULL);
33: PetscOptionsGetInt(PETSC_NULL,"-n",&n,PETSC_NULL);
34: PetscOptionsGetInt(PETSC_NULL,"-lf",&lf,PETSC_NULL);
36: MatCreate(PETSC_COMM_SELF,&C);
37: MatSetSizes(C,m*n,m*n,m*n,m*n);
38: MatSetFromOptions(C);
39: MatSetUp(C);
41: /* Create matrix C in seqaij format and sC in seqsbaij. (This is five-point stencil with some extra elements) */
42: for (i=0; i<m; i++) {
43: for (j=0; j<n; j++) {
44: v = -1.0; Ii = j + n*i;
45: J = Ii - n; if (J>=0) {MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES);}
46: J = Ii + n; if (J<m*n) {MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES);}
47: J = Ii - 1; if (J>=0) {MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES);}
48: J = Ii + 1; if (J<m*n) {MatSetValues(C,1,&Ii,1,&J,&v,INSERT_VALUES);}
49: v = 4.0; MatSetValues(C,1,&Ii,1,&Ii,&v,INSERT_VALUES);
50: }
51: }
52: MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
53: MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);
55: MatIsSymmetric(C,0.0,&flg);
56: if (!flg) SETERRQ(PETSC_COMM_SELF,1,"C is non-symmetric");
57: MatConvert(C,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&sC);
59: /* Create vectors for error checking */
60: MatGetVecs(C,&x,&b);
61: VecDuplicate(x,&y);
62: VecDuplicate(x,&ytmp);
63: PetscRandomCreate(PETSC_COMM_SELF,&rdm);
64: PetscRandomSetFromOptions(rdm);
65: VecSetRandom(x,rdm);
66: MatMult(C,x,b);
68: MatGetOrdering(C,MATORDERINGNATURAL,&row,&col);
70: /* Compute CHOLESKY or ICC factor sA */
71: MatFactorInfoInitialize(&info);
72: info.fill = 1.0;
73: info.diagonal_fill = 0;
74: info.zeropivot = 0.0;
75: PetscOptionsHasName(PETSC_NULL,"-cholesky",&CHOLESKY);
76: if (CHOLESKY){
77: printf("Test CHOLESKY...\n");
78: MatGetFactor(sC,MATSOLVERPETSC,MAT_FACTOR_CHOLESKY,&sA);
79: MatCholeskyFactorSymbolic(sA,sC,row,&info);
80: } else {
81: printf("Test ICC...\n");
82: info.levels = lf;
83: MatGetFactor(sC,MATSOLVERPETSC,MAT_FACTOR_ICC,&sA);
84: MatICCFactorSymbolic(sA,sC,row,&info);
85: }
86: MatCholeskyFactorNumeric(sA,sC,&info);
88: /* test MatForwardSolve() and MatBackwardSolve() with matrix reordering on aij matrix C */
89: if (CHOLESKY){
90: PetscOptionsHasName(PETSC_NULL,"-triangular_solve",&TRIANGULAR);
91: if (TRIANGULAR){
92: printf("Test MatForwardSolve...\n");
93: MatForwardSolve(sA,b,ytmp);
94: printf("Test MatBackwardSolve...\n");
95: MatBackwardSolve(sA,ytmp,y);
96: VecAXPY(y,-1.0,x);
97: VecNorm(y,NORM_2,&norm2);
98: if (norm2 > 1.e-14){
99: PetscPrintf(PETSC_COMM_SELF,"MatForwardSolve and BackwardSolve: Norm of error=%G\n",norm2);
100: }
101: }
102: }
104: MatSolve(sA,b,y);
105: MatDestroy(&sC);
106: MatDestroy(&sA);
107: VecAXPY(y,-1.0,x);
108: VecNorm(y,NORM_2,&norm2);
109: if (lf == -1 && norm2 > 1.e-14){
110: PetscPrintf(PETSC_COMM_SELF, " reordered SEQAIJ: Cholesky/ICC levels %d, residual %g\n",lf,norm2);
111: }
112:
113: /* Free data structures */
114: MatDestroy(&C);
115: ISDestroy(&row);
116: ISDestroy(&col);
117: PetscRandomDestroy(&rdm);
118: VecDestroy(&x);
119: VecDestroy(&y);
120: VecDestroy(&ytmp);
121: VecDestroy(&b);
122: PetscFinalize();
123: return 0;
124: }