Actual source code: ex74.c
petsc-3.12.5 2020-03-29
2: static char help[] = "Tests the various sequential routines in MatSBAIJ format.\n";
4: #include <petscmat.h>
6: int main(int argc,char **args)
7: {
8: PetscMPIInt size;
10: Vec x,y,b,s1,s2;
11: Mat A; /* linear system matrix */
12: Mat sA,sB,sFactor; /* symmetric matrices */
13: PetscInt n,mbs=16,bs=1,nz=3,prob=1,i,j,k1,k2,col[3],lf,block, row,Ii,J,n1,inc;
14: PetscReal norm1,norm2,rnorm,tol=10*PETSC_SMALL;
15: PetscScalar neg_one = -1.0,four=4.0,value[3];
16: IS perm, iscol;
17: PetscRandom rdm;
18: PetscBool doIcc=PETSC_TRUE,equal;
19: MatInfo minfo1,minfo2;
20: MatFactorInfo factinfo;
21: MatType type;
23: PetscInitialize(&argc,&args,(char*)0,help);if (ierr) return ierr;
24: MPI_Comm_size(PETSC_COMM_WORLD,&size);
25: if (size != 1) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_SUP,"This is a uniprocessor example only!");
26: PetscOptionsGetInt(NULL,NULL,"-bs",&bs,NULL);
27: PetscOptionsGetInt(NULL,NULL,"-mbs",&mbs,NULL);
29: n = mbs*bs;
30: MatCreate(PETSC_COMM_SELF,&A);
31: MatSetSizes(A,n,n,PETSC_DETERMINE,PETSC_DETERMINE);
32: MatSetType(A,MATSEQBAIJ);
33: MatSetFromOptions(A);
34: MatSeqBAIJSetPreallocation(A,bs,nz,NULL);
36: MatCreate(PETSC_COMM_SELF,&sA);
37: MatSetSizes(sA,n,n,PETSC_DETERMINE,PETSC_DETERMINE);
38: MatSetType(sA,MATSEQSBAIJ);
39: MatSetFromOptions(sA);
40: MatGetType(sA,&type);
41: PetscObjectTypeCompare((PetscObject)sA,MATSEQSBAIJ,&doIcc);
42: MatSeqSBAIJSetPreallocation(sA,bs,nz,NULL);
43: MatSetOption(sA,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);
45: /* Test MatGetOwnershipRange() */
46: MatGetOwnershipRange(A,&Ii,&J);
47: MatGetOwnershipRange(sA,&i,&j);
48: if (i-Ii || j-J) {
49: PetscPrintf(PETSC_COMM_SELF,"Error: MatGetOwnershipRange() in MatSBAIJ format\n");
50: }
52: /* Assemble matrix */
53: if (bs == 1) {
54: PetscOptionsGetInt(NULL,NULL,"-test_problem",&prob,NULL);
55: if (prob == 1) { /* tridiagonal matrix */
56: value[0] = -1.0; value[1] = 2.0; value[2] = -1.0;
57: for (i=1; i<n-1; i++) {
58: col[0] = i-1; col[1] = i; col[2] = i+1;
59: MatSetValues(A,1,&i,3,col,value,INSERT_VALUES);
60: MatSetValues(sA,1,&i,3,col,value,INSERT_VALUES);
61: }
62: i = n - 1; col[0]=0; col[1] = n - 2; col[2] = n - 1;
64: value[0]= 0.1; value[1]=-1; value[2]=2;
66: MatSetValues(A,1,&i,3,col,value,INSERT_VALUES);
67: MatSetValues(sA,1,&i,3,col,value,INSERT_VALUES);
69: i = 0;
70: col[0] = n-1; col[1] = 1; col[2] = 0;
71: value[0] = 0.1; value[1] = -1.0; value[2] = 2;
73: MatSetValues(A,1,&i,3,col,value,INSERT_VALUES);
74: MatSetValues(sA,1,&i,3,col,value,INSERT_VALUES);
76: } else if (prob ==2) { /* matrix for the five point stencil */
77: n1 = (PetscInt) (PetscSqrtReal((PetscReal)n) + 0.001);
78: if (n1*n1 - n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"sqrt(n) must be a positive integer!");
79: for (i=0; i<n1; i++) {
80: for (j=0; j<n1; j++) {
81: Ii = j + n1*i;
82: if (i>0) {
83: J = Ii - n1;
84: MatSetValues(A,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
85: MatSetValues(sA,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
86: }
87: if (i<n1-1) {
88: J = Ii + n1;
89: MatSetValues(A,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
90: MatSetValues(sA,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
91: }
92: if (j>0) {
93: J = Ii - 1;
94: MatSetValues(A,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
95: MatSetValues(sA,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
96: }
97: if (j<n1-1) {
98: J = Ii + 1;
99: MatSetValues(A,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
100: MatSetValues(sA,1,&Ii,1,&J,&neg_one,INSERT_VALUES);
101: }
102: MatSetValues(A,1,&Ii,1,&Ii,&four,INSERT_VALUES);
103: MatSetValues(sA,1,&Ii,1,&Ii,&four,INSERT_VALUES);
104: }
105: }
106: }
108: } else { /* bs > 1 */
109: for (block=0; block<n/bs; block++) {
110: /* diagonal blocks */
111: value[0] = -1.0; value[1] = 4.0; value[2] = -1.0;
112: for (i=1+block*bs; i<bs-1+block*bs; i++) {
113: col[0] = i-1; col[1] = i; col[2] = i+1;
114: MatSetValues(A,1,&i,3,col,value,INSERT_VALUES);
115: MatSetValues(sA,1,&i,3,col,value,INSERT_VALUES);
116: }
117: i = bs - 1+block*bs; col[0] = bs - 2+block*bs; col[1] = bs - 1+block*bs;
119: value[0]=-1.0; value[1]=4.0;
121: MatSetValues(A,1,&i,2,col,value,INSERT_VALUES);
122: MatSetValues(sA,1,&i,2,col,value,INSERT_VALUES);
124: i = 0+block*bs; col[0] = 0+block*bs; col[1] = 1+block*bs;
126: value[0]=4.0; value[1] = -1.0;
128: MatSetValues(A,1,&i,2,col,value,INSERT_VALUES);
129: MatSetValues(sA,1,&i,2,col,value,INSERT_VALUES);
130: }
131: /* off-diagonal blocks */
132: value[0]=-1.0;
133: for (i=0; i<(n/bs-1)*bs; i++) {
134: col[0]=i+bs;
136: MatSetValues(A,1,&i,1,col,value,INSERT_VALUES);
137: MatSetValues(sA,1,&i,1,col,value,INSERT_VALUES);
139: col[0]=i; row=i+bs;
141: MatSetValues(A,1,&row,1,col,value,INSERT_VALUES);
142: MatSetValues(sA,1,&row,1,col,value,INSERT_VALUES);
143: }
144: }
145: MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
146: MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
148: MatAssemblyBegin(sA,MAT_FINAL_ASSEMBLY);
149: MatAssemblyEnd(sA,MAT_FINAL_ASSEMBLY);
151: /* Test MatGetInfo() of A and sA */
152: MatGetInfo(A,MAT_LOCAL,&minfo1);
153: MatGetInfo(sA,MAT_LOCAL,&minfo2);
154: /*
155: printf("A matrix nonzeros (BAIJ format) = %d, allocated nonzeros= %d\n", (int)minfo1.nz_used,(int)minfo1.nz_allocated);
156: printf("sA matrix nonzeros(SBAIJ format) = %d, allocated nonzeros= %d\n", (int)minfo2.nz_used,(int)minfo2.nz_allocated);
157: */
158: i = (int) (minfo1.nz_used - minfo2.nz_used);
159: j = (int) (minfo1.nz_allocated - minfo2.nz_allocated);
160: k1 = (int) (minfo1.nz_allocated - minfo1.nz_used);
161: k2 = (int) (minfo2.nz_allocated - minfo2.nz_used);
162: if (i < 0 || j < 0 || k1 < 0 || k2 < 0) {
163: PetscPrintf(PETSC_COMM_SELF,"Error (compare A and sA): MatGetInfo()\n");
164: }
166: /* Test MatDuplicate() */
167: MatNorm(A,NORM_FROBENIUS,&norm1);
168: MatDuplicate(sA,MAT_COPY_VALUES,&sB);
169: MatEqual(sA,sB,&equal);
170: if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMETYPE,"Error in MatDuplicate()");
172: /* Test MatNorm() */
173: MatNorm(A,NORM_FROBENIUS,&norm1);
174: MatNorm(sB,NORM_FROBENIUS,&norm2);
175: rnorm = PetscAbsReal(norm1-norm2)/norm2;
176: if (rnorm > tol) {
177: PetscPrintf(PETSC_COMM_SELF,"Error: MatNorm_FROBENIUS, NormA=%16.14e NormsB=%16.14e\n",norm1,norm2);
178: }
179: MatNorm(A,NORM_INFINITY,&norm1);
180: MatNorm(sB,NORM_INFINITY,&norm2);
181: rnorm = PetscAbsReal(norm1-norm2)/norm2;
182: if (rnorm > tol) {
183: PetscPrintf(PETSC_COMM_SELF,"Error: MatNorm_INFINITY(), NormA=%16.14e NormsB=%16.14e\n",norm1,norm2);
184: }
185: MatNorm(A,NORM_1,&norm1);
186: MatNorm(sB,NORM_1,&norm2);
187: rnorm = PetscAbsReal(norm1-norm2)/norm2;
188: if (rnorm > tol) {
189: PetscPrintf(PETSC_COMM_SELF,"Error: MatNorm_INFINITY(), NormA=%16.14e NormsB=%16.14e\n",norm1,norm2);
190: }
192: /* Test MatGetInfo(), MatGetSize(), MatGetBlockSize() */
193: MatGetInfo(A,MAT_LOCAL,&minfo1);
194: MatGetInfo(sB,MAT_LOCAL,&minfo2);
195: /*
196: printf("matrix nonzeros (BAIJ format) = %d, allocated nonzeros= %d\n", (int)minfo1.nz_used,(int)minfo1.nz_allocated);
197: printf("matrix nonzeros(SBAIJ format) = %d, allocated nonzeros= %d\n", (int)minfo2.nz_used,(int)minfo2.nz_allocated);
198: */
199: i = (int) (minfo1.nz_used - minfo2.nz_used);
200: j = (int) (minfo1.nz_allocated - minfo2.nz_allocated);
201: k1 = (int) (minfo1.nz_allocated - minfo1.nz_used);
202: k2 = (int) (minfo2.nz_allocated - minfo2.nz_used);
203: if (i < 0 || j < 0 || k1 < 0 || k2 < 0) {
204: PetscPrintf(PETSC_COMM_SELF,"Error(compare A and sB): MatGetInfo()\n");
205: }
207: MatGetSize(A,&Ii,&J);
208: MatGetSize(sB,&i,&j);
209: if (i-Ii || j-J) {
210: PetscPrintf(PETSC_COMM_SELF,"Error: MatGetSize()\n");
211: }
213: MatGetBlockSize(A, &Ii);
214: MatGetBlockSize(sB, &i);
215: if (i-Ii) {
216: PetscPrintf(PETSC_COMM_SELF,"Error: MatGetBlockSize()\n");
217: }
219: PetscRandomCreate(PETSC_COMM_SELF,&rdm);
220: PetscRandomSetFromOptions(rdm);
221: VecCreateSeq(PETSC_COMM_SELF,n,&x);
222: VecDuplicate(x,&s1);
223: VecDuplicate(x,&s2);
224: VecDuplicate(x,&y);
225: VecDuplicate(x,&b);
226: VecSetRandom(x,rdm);
228: /* Test MatDiagonalScale(), MatGetDiagonal(), MatScale() */
229: #if !defined(PETSC_USE_COMPLEX)
230: /* Scaling matrix with complex numbers results non-spd matrix,
231: causing crash of MatForwardSolve() and MatBackwardSolve() */
232: MatDiagonalScale(A,x,x);
233: MatDiagonalScale(sB,x,x);
234: MatMultEqual(A,sB,10,&equal);
235: if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_NOTSAMETYPE,"Error in MatDiagonalScale");
237: MatGetDiagonal(A,s1);
238: MatGetDiagonal(sB,s2);
239: VecAXPY(s2,neg_one,s1);
240: VecNorm(s2,NORM_1,&norm1);
241: if (norm1>tol) {
242: PetscPrintf(PETSC_COMM_SELF,"Error:MatGetDiagonal(), ||s1-s2||=%g\n",(double)norm1);
243: }
245: {
246: PetscScalar alpha=0.1;
247: MatScale(A,alpha);
248: MatScale(sB,alpha);
249: }
250: #endif
252: /* Test MatGetRowMaxAbs() */
253: MatGetRowMaxAbs(A,s1,NULL);
254: MatGetRowMaxAbs(sB,s2,NULL);
255: VecNorm(s1,NORM_1,&norm1);
256: VecNorm(s2,NORM_1,&norm2);
257: norm1 -= norm2;
258: if (norm1<-tol || norm1>tol) {
259: PetscPrintf(PETSC_COMM_SELF,"Error:MatGetRowMaxAbs() \n");
260: }
262: /* Test MatMult() */
263: for (i=0; i<40; i++) {
264: VecSetRandom(x,rdm);
265: MatMult(A,x,s1);
266: MatMult(sB,x,s2);
267: VecNorm(s1,NORM_1,&norm1);
268: VecNorm(s2,NORM_1,&norm2);
269: norm1 -= norm2;
270: if (norm1<-tol || norm1>tol) {
271: PetscPrintf(PETSC_COMM_SELF,"Error: MatMult(), norm1-norm2: %g\n",(double)norm1);
272: }
273: }
275: /* MatMultAdd() */
276: for (i=0; i<40; i++) {
277: VecSetRandom(x,rdm);
278: VecSetRandom(y,rdm);
279: MatMultAdd(A,x,y,s1);
280: MatMultAdd(sB,x,y,s2);
281: VecNorm(s1,NORM_1,&norm1);
282: VecNorm(s2,NORM_1,&norm2);
283: norm1 -= norm2;
284: if (norm1<-tol || norm1>tol) {
285: PetscPrintf(PETSC_COMM_SELF,"Error:MatMultAdd(), norm1-norm2: %g\n",(double)norm1);
286: }
287: }
289: /* Test MatCholeskyFactor(), MatICCFactor() with natural ordering */
290: MatGetOrdering(A,MATORDERINGNATURAL,&perm,&iscol);
291: ISDestroy(&iscol);
292: norm1 = tol;
293: inc = bs;
295: /* initialize factinfo */
296: PetscMemzero(&factinfo,sizeof(MatFactorInfo));
298: for (lf=-1; lf<10; lf += inc) {
299: if (lf==-1) { /* Cholesky factor of sB (duplicate sA) */
300: factinfo.fill = 5.0;
302: MatGetFactor(sB,MATSOLVERPETSC,MAT_FACTOR_CHOLESKY,&sFactor);
303: MatCholeskyFactorSymbolic(sFactor,sB,perm,&factinfo);
304: } else if (!doIcc) break;
305: else { /* incomplete Cholesky factor */
306: factinfo.fill = 5.0;
307: factinfo.levels = lf;
309: MatGetFactor(sB,MATSOLVERPETSC,MAT_FACTOR_ICC,&sFactor);
310: MatICCFactorSymbolic(sFactor,sB,perm,&factinfo);
311: }
312: MatCholeskyFactorNumeric(sFactor,sB,&factinfo);
313: /* MatView(sFactor, PETSC_VIEWER_DRAW_WORLD); */
315: /* test MatGetDiagonal on numeric factor */
316: /*
317: if (lf == -1) {
318: MatGetDiagonal(sFactor,s1);
319: printf(" in ex74.c, diag: \n");
320: VecView(s1,PETSC_VIEWER_STDOUT_SELF);
321: }
322: */
324: MatMult(sB,x,b);
326: /* test MatForwardSolve() and MatBackwardSolve() */
327: if (lf == -1) {
328: MatForwardSolve(sFactor,b,s1);
329: MatBackwardSolve(sFactor,s1,s2);
330: VecAXPY(s2,neg_one,x);
331: VecNorm(s2,NORM_2,&norm2);
332: if (10*norm1 < norm2) {
333: PetscPrintf(PETSC_COMM_SELF,"MatForwardSolve and BackwardSolve: Norm of error=%g, bs=%D\n",(double)norm2,bs);
334: }
335: }
337: /* test MatSolve() */
338: MatSolve(sFactor,b,y);
339: MatDestroy(&sFactor);
340: /* Check the error */
341: VecAXPY(y,neg_one,x);
342: VecNorm(y,NORM_2,&norm2);
343: if (10*norm1 < norm2 && lf-inc != -1) {
344: PetscPrintf(PETSC_COMM_SELF,"lf=%D, %D, Norm of error=%g, %g\n",lf-inc,lf,(double)norm1,(double)norm2);
345: }
346: norm1 = norm2;
347: if (norm2 < tol && lf != -1) break;
348: }
350: #if defined(PETSC_HAVE_MUMPS)
351: MatGetFactor(sA,MATSOLVERMUMPS,MAT_FACTOR_CHOLESKY,&sFactor);
352: MatCholeskyFactorSymbolic(sFactor,sA,NULL,NULL);
353: MatCholeskyFactorNumeric(sFactor,sA,NULL);
354: for (i=0; i<10; i++) {
355: VecSetRandom(b,rdm);
356: MatSolve(sFactor,b,y);
357: /* Check the error */
358: MatMult(sA,y,x);
359: VecAXPY(x,neg_one,b);
360: VecNorm(x,NORM_2,&norm2);
361: if (norm2>tol) {
362: PetscPrintf(PETSC_COMM_SELF,"Error:MatSolve(), norm2: %g\n",(double)norm2);
363: }
364: }
365: MatDestroy(&sFactor);
366: #endif
368: ISDestroy(&perm);
370: MatDestroy(&A);
371: MatDestroy(&sB);
372: MatDestroy(&sA);
373: VecDestroy(&x);
374: VecDestroy(&y);
375: VecDestroy(&s1);
376: VecDestroy(&s2);
377: VecDestroy(&b);
378: PetscRandomDestroy(&rdm);
380: PetscFinalize();
381: return ierr;
382: }
385: /*TEST
387: test:
388: args: -bs {{1 2 3 4 5 6 7 8}}
390: TEST*/