Actual source code: ex91.c

petsc-3.13.6 2020-09-29
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  2: static char help[] = "Tests MatIncreaseOverlap(), MatCreateSubMatrices() for sequential MatSBAIJ format. Derived from ex51.c\n";

  4:  #include <petscmat.h>

  6: int main(int argc,char **args)
  7: {
  8:   Mat            A,Atrans,sA,*submatA,*submatsA;
  9:   PetscInt       bs=1,m=43,ov=1,i,j,k,*rows,*cols,M,nd=5,*idx,mm,nn;
 11:   PetscMPIInt    size;
 12:   PetscScalar    *vals,rval,one=1.0;
 13:   IS             *is1,*is2;
 14:   PetscRandom    rand;
 15:   Vec            xx,s1,s2;
 16:   PetscReal      s1norm,s2norm,rnorm,tol = 10*PETSC_SMALL;
 17:   PetscBool      flg;

 19:   PetscInitialize(&argc,&args,(char*)0,help);if (ierr) return ierr;
 20:   PetscOptionsGetInt(NULL,NULL,"-mat_block_size",&bs,NULL);
 21:   PetscOptionsGetInt(NULL,NULL,"-mat_size",&m,NULL);
 22:   PetscOptionsGetInt(NULL,NULL,"-ov",&ov,NULL);
 23:   PetscOptionsGetInt(NULL,NULL,"-nd",&nd,NULL);

 25:   /* create a SeqBAIJ matrix A */
 26:   M    = m*bs;
 27:   MatCreateSeqBAIJ(PETSC_COMM_SELF,bs,M,M,1,NULL,&A);
 28:   MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE);
 29:   PetscRandomCreate(PETSC_COMM_SELF,&rand);
 30:   PetscRandomSetFromOptions(rand);

 32:   PetscMalloc1(bs,&rows);
 33:   PetscMalloc1(bs,&cols);
 34:   PetscMalloc1(bs*bs,&vals);
 35:   PetscMalloc1(M,&idx);

 37:   /* Now set blocks of random values */
 38:   /* first, set diagonal blocks as zero */
 39:   for (j=0; j<bs*bs; j++) vals[j] = 0.0;
 40:   for (i=0; i<m; i++) {
 41:     cols[0] = i*bs; rows[0] = i*bs;
 42:     for (j=1; j<bs; j++) {
 43:       rows[j] = rows[j-1]+1;
 44:       cols[j] = cols[j-1]+1;
 45:     }
 46:     MatSetValues(A,bs,rows,bs,cols,vals,ADD_VALUES);
 47:   }
 48:   /* second, add random blocks */
 49:   for (i=0; i<20*bs; i++) {
 50:     PetscRandomGetValue(rand,&rval);
 51:     cols[0] = bs*(int)(PetscRealPart(rval)*m);
 52:     PetscRandomGetValue(rand,&rval);
 53:     rows[0] = bs*(int)(PetscRealPart(rval)*m);
 54:     for (j=1; j<bs; j++) {
 55:       rows[j] = rows[j-1]+1;
 56:       cols[j] = cols[j-1]+1;
 57:     }

 59:     for (j=0; j<bs*bs; j++) {
 60:       PetscRandomGetValue(rand,&rval);
 61:       vals[j] = rval;
 62:     }
 63:     MatSetValues(A,bs,rows,bs,cols,vals,ADD_VALUES);
 64:   }

 66:   MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
 67:   MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);

 69:   /* make A a symmetric matrix: A <- A^T + A */
 70:   MatTranspose(A,MAT_INITIAL_MATRIX, &Atrans);
 71:   MatAXPY(A,one,Atrans,DIFFERENT_NONZERO_PATTERN);
 72:   MatDestroy(&Atrans);
 73:   MatTranspose(A,MAT_INITIAL_MATRIX, &Atrans);
 74:   MatEqual(A, Atrans, &flg);
 75:   if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"A+A^T is non-symmetric");
 76:   MatDestroy(&Atrans);

 78:   /* create a SeqSBAIJ matrix sA (= A) */
 79:   MatSetOption(A,MAT_SYMMETRIC,PETSC_TRUE);
 80:   MatConvert(A,MATSEQSBAIJ,MAT_INITIAL_MATRIX,&sA);

 82:   /* Test sA==A through MatMult() */
 83:   for (i=0; i<nd; i++) {
 84:     MatGetSize(A,&mm,&nn);
 85:     VecCreateSeq(PETSC_COMM_SELF,mm,&xx);
 86:     VecDuplicate(xx,&s1);
 87:     VecDuplicate(xx,&s2);
 88:     for (j=0; j<3; j++) {
 89:       VecSetRandom(xx,rand);
 90:       MatMult(A,xx,s1);
 91:       MatMult(sA,xx,s2);
 92:       VecNorm(s1,NORM_2,&s1norm);
 93:       VecNorm(s2,NORM_2,&s2norm);
 94:       rnorm = s2norm-s1norm;
 95:       if (rnorm<-tol || rnorm>tol) {
 96:         PetscPrintf(PETSC_COMM_SELF,"Error:MatMult - Norm1=%16.14e Norm2=%16.14e\n",s1norm,s2norm);
 97:       }
 98:     }
 99:     VecDestroy(&xx);
100:     VecDestroy(&s1);
101:     VecDestroy(&s2);
102:   }

104:   /* Test MatIncreaseOverlap() */
105:   PetscMalloc1(nd,&is1);
106:   PetscMalloc1(nd,&is2);


109:   for (i=0; i<nd; i++) {
110:     PetscRandomGetValue(rand,&rval);
111:     size = (int)(PetscRealPart(rval)*m);
112:     for (j=0; j<size; j++) {
113:       PetscRandomGetValue(rand,&rval);
114:       idx[j*bs] = bs*(int)(PetscRealPart(rval)*m);
115:       for (k=1; k<bs; k++) idx[j*bs+k] = idx[j*bs]+k;
116:     }
117:     ISCreateGeneral(PETSC_COMM_SELF,size*bs,idx,PETSC_COPY_VALUES,is1+i);
118:     ISCreateGeneral(PETSC_COMM_SELF,size*bs,idx,PETSC_COPY_VALUES,is2+i);
119:   }
120:   /* for debugging */
121:   /*
122:   MatView(A,PETSC_VIEWER_STDOUT_SELF);
123:   MatView(sA,PETSC_VIEWER_STDOUT_SELF);
124:   */

126:   MatIncreaseOverlap(A,nd,is1,ov);
127:   MatIncreaseOverlap(sA,nd,is2,ov);

129:   for (i=0; i<nd; ++i) {
130:     ISSort(is1[i]);
131:     ISSort(is2[i]);
132:   }

134:   for (i=0; i<nd; ++i) {
135:     ISEqual(is1[i],is2[i],&flg);
136:     if (!flg) SETERRQ1(PETSC_COMM_SELF,1,"i=%d, is1 != is2",i);
137:   }

139:   MatCreateSubMatrices(A,nd,is1,is1,MAT_INITIAL_MATRIX,&submatA);
140:   MatCreateSubMatrices(sA,nd,is2,is2,MAT_INITIAL_MATRIX,&submatsA);

142:   /* Test MatMult() */
143:   for (i=0; i<nd; i++) {
144:     MatGetSize(submatA[i],&mm,&nn);
145:     VecCreateSeq(PETSC_COMM_SELF,mm,&xx);
146:     VecDuplicate(xx,&s1);
147:     VecDuplicate(xx,&s2);
148:     for (j=0; j<3; j++) {
149:       VecSetRandom(xx,rand);
150:       MatMult(submatA[i],xx,s1);
151:       MatMult(submatsA[i],xx,s2);
152:       VecNorm(s1,NORM_2,&s1norm);
153:       VecNorm(s2,NORM_2,&s2norm);
154:       rnorm = s2norm-s1norm;
155:       if (rnorm<-tol || rnorm>tol) {
156:         PetscPrintf(PETSC_COMM_SELF,"Error:MatMult - Norm1=%16.14e Norm2=%16.14e\n",s1norm,s2norm);
157:       }
158:     }
159:     VecDestroy(&xx);
160:     VecDestroy(&s1);
161:     VecDestroy(&s2);
162:   }

164:   /* Now test MatCreateSubmatrices with MAT_REUSE_MATRIX option */
165:   MatCreateSubMatrices(A,nd,is1,is1,MAT_REUSE_MATRIX,&submatA);
166:   MatCreateSubMatrices(sA,nd,is2,is2,MAT_REUSE_MATRIX,&submatsA);

168:   /* Test MatMult() */
169:   for (i=0; i<nd; i++) {
170:     MatGetSize(submatA[i],&mm,&nn);
171:     VecCreateSeq(PETSC_COMM_SELF,mm,&xx);
172:     VecDuplicate(xx,&s1);
173:     VecDuplicate(xx,&s2);
174:     for (j=0; j<3; j++) {
175:       VecSetRandom(xx,rand);
176:       MatMult(submatA[i],xx,s1);
177:       MatMult(submatsA[i],xx,s2);
178:       VecNorm(s1,NORM_2,&s1norm);
179:       VecNorm(s2,NORM_2,&s2norm);
180:       rnorm = s2norm-s1norm;
181:       if (rnorm<-tol || rnorm>tol) {
182:         PetscPrintf(PETSC_COMM_SELF,"Error:MatMult - Norm1=%16.14e Norm2=%16.14e\n",s1norm,s2norm);
183:       }
184:     }
185:     VecDestroy(&xx);
186:     VecDestroy(&s1);
187:     VecDestroy(&s2);
188:   }

190:   /* Free allocated memory */
191:   for (i=0; i<nd; ++i) {
192:     ISDestroy(&is1[i]);
193:     ISDestroy(&is2[i]);
194:   }
195:   MatDestroySubMatrices(nd,&submatA);
196:   MatDestroySubMatrices(nd,&submatsA);

198:   PetscFree(is1);
199:   PetscFree(is2);
200:   PetscFree(idx);
201:   PetscFree(rows);
202:   PetscFree(cols);
203:   PetscFree(vals);
204:   MatDestroy(&A);
205:   MatDestroy(&sA);
206:   PetscRandomDestroy(&rand);
207:   PetscFinalize();
208:   return ierr;
209: }


212: /*TEST

214:    test:
215:       args: -ov 2

217: TEST*/