Actual source code: schurm.c
petsc-3.4.2 2013-07-02
2: #include <petsc-private/matimpl.h>
3: #include <petscksp.h> /*I "petscksp.h" I*/
5: typedef struct {
6: Mat A,Ap,B,C,D;
7: KSP ksp;
8: Vec work1,work2;
9: } Mat_SchurComplement;
13: PetscErrorCode MatGetVecs_SchurComplement(Mat N,Vec *right,Vec *left)
14: {
15: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
16: PetscErrorCode ierr;
19: if (Na->D) {
20: MatGetVecs(Na->D,right,left);
21: return(0);
22: }
23: if (right) {
24: MatGetVecs(Na->B,right,NULL);
25: }
26: if (left) {
27: MatGetVecs(Na->C,NULL,left);
28: }
29: return(0);
30: }
34: PetscErrorCode MatView_SchurComplement(Mat N,PetscViewer viewer)
35: {
36: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
37: PetscErrorCode ierr;
40: PetscViewerASCIIPrintf(viewer,"Schur complement A11 - A10 inv(A00) A01\n");
41: if (Na->D) {
42: PetscViewerASCIIPrintf(viewer,"A11\n");
43: PetscViewerASCIIPushTab(viewer);
44: MatView(Na->D,viewer);
45: PetscViewerASCIIPopTab(viewer);
46: } else {
47: PetscViewerASCIIPrintf(viewer,"A11 = 0\n");
48: }
49: PetscViewerASCIIPrintf(viewer,"A10\n");
50: PetscViewerASCIIPushTab(viewer);
51: MatView(Na->C,viewer);
52: PetscViewerASCIIPopTab(viewer);
53: PetscViewerASCIIPrintf(viewer,"KSP of A00\n");
54: PetscViewerASCIIPushTab(viewer);
55: KSPView(Na->ksp,viewer);
56: PetscViewerASCIIPopTab(viewer);
57: PetscViewerASCIIPrintf(viewer,"A01\n");
58: PetscViewerASCIIPushTab(viewer);
59: MatView(Na->B,viewer);
60: PetscViewerASCIIPopTab(viewer);
61: return(0);
62: }
65: /*
66: A11 - A10 ksp(A00,Ap00) A01
67: */
70: PetscErrorCode MatMult_SchurComplement(Mat N,Vec x,Vec y)
71: {
72: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
73: PetscErrorCode ierr;
76: if (!Na->work1) {MatGetVecs(Na->A,&Na->work1,NULL);}
77: if (!Na->work2) {MatGetVecs(Na->A,&Na->work2,NULL);}
78: MatMult(Na->B,x,Na->work1);
79: KSPSolve(Na->ksp,Na->work1,Na->work2);
80: MatMult(Na->C,Na->work2,y);
81: VecScale(y,-1.0);
82: if (Na->D) {
83: MatMultAdd(Na->D,x,y,y);
84: }
85: return(0);
86: }
88: /*
89: A11 - A10 ksp(A00,Ap00) A01
90: */
93: PetscErrorCode MatMultAdd_SchurComplement(Mat N,Vec x,Vec y,Vec z)
94: {
95: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
96: PetscErrorCode ierr;
99: if (!Na->work1) {MatGetVecs(Na->A,&Na->work1,NULL);}
100: if (!Na->work2) {MatGetVecs(Na->A,&Na->work2,NULL);}
101: MatMult(Na->B,x,Na->work1);
102: KSPSolve(Na->ksp,Na->work1,Na->work2);
103: if (y == z) {
104: VecScale(Na->work2,-1.0);
105: MatMultAdd(Na->C,Na->work2,z,z);
106: } else {
107: MatMult(Na->C,Na->work2,z);
108: VecAYPX(z,-1.0,y);
109: }
110: if (Na->D) {
111: MatMultAdd(Na->D,x,z,z);
112: }
113: return(0);
114: }
118: PetscErrorCode MatSetFromOptions_SchurComplement(Mat N)
119: {
120: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
121: PetscErrorCode ierr;
124: KSPSetFromOptions(Na->ksp);
125: return(0);
126: }
130: PetscErrorCode MatDestroy_SchurComplement(Mat N)
131: {
132: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
133: PetscErrorCode ierr;
136: MatDestroy(&Na->A);
137: MatDestroy(&Na->Ap);
138: MatDestroy(&Na->B);
139: MatDestroy(&Na->C);
140: MatDestroy(&Na->D);
141: VecDestroy(&Na->work1);
142: VecDestroy(&Na->work2);
143: KSPDestroy(&Na->ksp);
144: PetscFree(N->data);
145: return(0);
146: }
150: /*@
151: MatCreateSchurComplement - Creates a new matrix object that behaves like the Schur complement of a matrix
153: Collective on Mat
155: Input Parameter:
156: . A00,A01,A10,A11 - the four parts of the original matrix (A00 is optional)
158: Output Parameter:
159: . N - the matrix that the Schur complement A11 - A10 ksp(A00) A01
161: Level: intermediate
163: Notes: The Schur complement is NOT actually formed! Rather this
164: object performs the matrix-vector product by using the the formula for
165: the Schur complement and a KSP solver to approximate the action of inv(A)
167: All four matrices must have the same MPI communicator
169: A00 and A11 must be square matrices
171: .seealso: MatCreateNormal(), MatMult(), MatCreate(), MatSchurComplementGetKSP(), MatSchurComplementUpdate(), MatCreateTranspose(), MatGetSchurComplement()
173: @*/
174: PetscErrorCode MatCreateSchurComplement(Mat A00,Mat Ap00,Mat A01,Mat A10,Mat A11,Mat *N)
175: {
179: MatCreate(((PetscObject)A00)->comm,N);
180: MatSetType(*N,MATSCHURCOMPLEMENT);
181: MatSchurComplementSet(*N,A00,Ap00,A01,A10,A11);
182: return(0);
183: }
187: /*@
188: MatSchurComplementSet - Sets the matrices that define the Schur complement
190: Collective on Mat
192: Input Parameter:
193: + N - matrix obtained with MatCreate() and MatSetType(MATSCHURCOMPLEMENT);
194: - A00,A01,A10,A11 - the four parts of the original matrix (A00 is optional)
196: Level: intermediate
198: Notes: The Schur complement is NOT actually formed! Rather this
199: object performs the matrix-vector product by using the the formula for
200: the Schur complement and a KSP solver to approximate the action of inv(A)
202: All four matrices must have the same MPI communicator
204: A00 and A11 must be square matrices
206: .seealso: MatCreateNormal(), MatMult(), MatCreate(), MatSchurComplementGetKSP(), MatSchurComplementUpdate(), MatCreateTranspose(), MatGetSchurComplement()
208: @*/
209: PetscErrorCode MatSchurComplementSet(Mat N,Mat A00,Mat Ap00,Mat A01,Mat A10,Mat A11)
210: {
211: PetscErrorCode ierr;
212: PetscInt m,n;
213: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
216: if (N->assembled) SETERRQ(PetscObjectComm((PetscObject)N),PETSC_ERR_ARG_WRONGSTATE,"Use MatSchurComplementUpdate() for already used matrix");
224: if (A00->rmap->n != A00->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of A00 %D do not equal local columns %D",A00->rmap->n,A00->cmap->n);
225: if (A00->rmap->n != Ap00->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of A00 %D do not equal local rows of Ap00 %D",A00->rmap->n,Ap00->rmap->n);
226: if (Ap00->rmap->n != Ap00->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of Ap00 %D do not equal local columns %D",Ap00->rmap->n,Ap00->cmap->n);
227: if (A00->cmap->n != A01->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local columns of A00 %D do not equal local rows of A01 %D",A00->cmap->n,A01->rmap->n);
228: if (A10->cmap->n != A00->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local columns of A10 %D do not equal local rows of A00 %D",A10->cmap->n,A00->rmap->n);
229: if (A11) {
232: if (A11->rmap->n != A11->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of A11 %D do not equal local columns %D",A11->rmap->n,A11->cmap->n);
233: if (A10->rmap->n != A11->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of A10 %D do not equal local rows A11 %D",A10->rmap->n,A11->rmap->n);
234: }
236: MatGetLocalSize(A01,NULL,&n);
237: MatGetLocalSize(A10,&m,NULL);
238: MatSetSizes(N,m,n,PETSC_DECIDE,PETSC_DECIDE);
239: PetscObjectReference((PetscObject)A00);
240: PetscObjectReference((PetscObject)Ap00);
241: PetscObjectReference((PetscObject)A01);
242: PetscObjectReference((PetscObject)A10);
243: Na->A = A00;
244: Na->Ap = Ap00;
245: Na->B = A01;
246: Na->C = A10;
247: Na->D = A11;
248: if (A11) {
249: PetscObjectReference((PetscObject)A11);
250: }
251: N->assembled = PETSC_TRUE;
252: N->preallocated = PETSC_TRUE;
254: PetscLayoutSetUp((N)->rmap);
255: PetscLayoutSetUp((N)->cmap);
256: KSPSetOperators(Na->ksp,A00,Ap00,SAME_NONZERO_PATTERN);
257: return(0);
258: }
262: /*@
263: MatSchurComplementGetKSP - Gets the KSP object that is used to invert A in the Schur complement matrix S = C A^{-1} B
265: Not Collective
267: Input Parameter:
268: . A - matrix created with MatCreateSchurComplement()
270: Output Parameter:
271: . ksp - the linear solver object
273: Options Database:
274: . -fieldsplit_0_XXX sets KSP and PC options for the A block solver inside the Schur complement
276: Level: intermediate
278: .seealso: MatSchurComplementSetKSP(), MatCreateSchurComplement(), MatCreateNormal(), MatMult(), MatCreate()
279: @*/
280: PetscErrorCode MatSchurComplementGetKSP(Mat A, KSP *ksp)
281: {
282: Mat_SchurComplement *Na;
287: Na = (Mat_SchurComplement*) A->data;
288: *ksp = Na->ksp;
289: return(0);
290: }
294: /*@
295: MatSchurComplementSetKSP - Sets the KSP object that is used to invert A in the Schur complement matrix S = C A^{-1} B
297: Not Collective
299: Input Parameters:
300: + A - matrix created with MatCreateSchurComplement()
301: - ksp - the linear solver object
303: Level: developer
305: Developer Notes:
306: There is likely no use case for this function.
308: .seealso: MatSchurComplementGetKSP(), MatCreateSchurComplement(), MatCreateNormal(), MatMult(), MatCreate(), MATSCHURCOMPLEMENT
309: @*/
310: PetscErrorCode MatSchurComplementSetKSP(Mat A, KSP ksp)
311: {
312: Mat_SchurComplement *Na;
313: PetscErrorCode ierr;
318: Na = (Mat_SchurComplement*) A->data;
319: PetscObjectReference((PetscObject)ksp);
320: KSPDestroy(&Na->ksp);
321: Na->ksp = ksp;
322: KSPSetOperators(Na->ksp, Na->A, Na->Ap, SAME_NONZERO_PATTERN);
323: return(0);
324: }
328: /*@
329: MatSchurComplementUpdate - Updates the Schur complement matrix object with new submatrices
331: Collective on Mat
333: Input Parameters:
334: + N - the matrix obtained with MatCreateSchurComplement()
335: . A,B,C,D - the four parts of the original matrix (D is optional)
336: - str - either SAME_NONZERO_PATTERN,DIFFERENT_NONZERO_PATTERN,SAME_PRECONDITIONER
339: Level: intermediate
341: Notes: All four matrices must have the same MPI communicator
343: A and D must be square matrices
345: All of the matrices provided must have the same sizes as was used with MatCreateSchurComplement() or MatSchurComplementSet()
346: though they need not be the same matrices
348: .seealso: MatCreateNormal(), MatMult(), MatCreate(), MatSchurComplementGetKSP(), MatCreateSchurComplement()
350: @*/
351: PetscErrorCode MatSchurComplementUpdate(Mat N,Mat A,Mat Ap,Mat B,Mat C,Mat D,MatStructure str)
352: {
353: PetscErrorCode ierr;
354: Mat_SchurComplement *Na = (Mat_SchurComplement*)N->data;
357: if (!N->assembled) SETERRQ(PetscObjectComm((PetscObject)N),PETSC_ERR_ARG_WRONGSTATE,"Use MatSchurComplementSet() for new matrix");
364: if (A->rmap->n != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of A %D do not equal local columns %D",A->rmap->n,A->cmap->n);
365: if (A->rmap->n != Ap->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of A %D do not equal local rows of Ap %D",A->rmap->n,Ap->rmap->n);
366: if (Ap->rmap->n != Ap->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of Ap %D do not equal local columns %D",Ap->rmap->n,Ap->cmap->n);
367: if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local columns of A %D do not equal local rows of B %D",A->cmap->n,B->rmap->n);
368: if (C->cmap->n != A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local columns of C %D do not equal local rows of A %D",C->cmap->n,A->rmap->n);
369: if (D) {
372: if (D->rmap->n != D->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of D %D do not equal local columns %D",D->rmap->n,D->cmap->n);
373: if (C->rmap->n != D->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local rows of C %D do not equal local rows D %D",C->rmap->n,D->rmap->n);
374: }
376: PetscObjectReference((PetscObject)A);
377: PetscObjectReference((PetscObject)Ap);
378: PetscObjectReference((PetscObject)B);
379: PetscObjectReference((PetscObject)C);
380: if (D) {
381: PetscObjectReference((PetscObject)D);
382: }
384: MatDestroy(&Na->A);
385: MatDestroy(&Na->Ap);
386: MatDestroy(&Na->B);
387: MatDestroy(&Na->C);
388: MatDestroy(&Na->D);
390: Na->A = A;
391: Na->Ap = Ap;
392: Na->B = B;
393: Na->C = C;
394: Na->D = D;
396: KSPSetOperators(Na->ksp,A,Ap,str);
397: return(0);
398: }
403: /*@C
404: MatSchurComplementGetSubmatrices - Get the individual submatrices in the Schur complement
406: Collective on Mat
408: Input Parameters:
409: + N - the matrix obtained with MatCreateSchurComplement()
410: - A,B,C,D - the four parts of the original matrix (D is optional)
412: Note:
413: D is optional, and thus can be NULL
415: Level: intermediate
417: .seealso: MatCreateNormal(), MatMult(), MatCreate(), MatSchurComplementGetKSP(), MatCreateSchurComplement(), MatSchurComplementUpdate()
418: @*/
419: PetscErrorCode MatSchurComplementGetSubmatrices(Mat N,Mat *A,Mat *Ap,Mat *B,Mat *C,Mat *D)
420: {
421: Mat_SchurComplement *Na = (Mat_SchurComplement*) N->data;
422: PetscErrorCode ierr;
423: PetscBool flg;
427: PetscObjectTypeCompare((PetscObject)N,MATSCHURCOMPLEMENT,&flg);
428: if (flg) {
429: if (A) *A = Na->A;
430: if (Ap) *Ap = Na->Ap;
431: if (B) *B = Na->B;
432: if (C) *C = Na->C;
433: if (D) *D = Na->D;
434: } else {
435: if (A) *A = 0;
436: if (Ap) *Ap = 0;
437: if (B) *B = 0;
438: if (C) *C = 0;
439: if (D) *D = 0;
440: }
441: return(0);
442: }
446: /* Developer Notes: This should be implemented with a MatCreate_SchurComplement() as that is the standard design for new Mat classes. */
447: PetscErrorCode MatGetSchurComplement_Basic(Mat mat,IS isrow0,IS iscol0,IS isrow1,IS iscol1,MatReuse mreuse,Mat *newmat,MatReuse preuse,Mat *newpmat)
448: {
450: Mat A=0,Ap=0,B=0,C=0,D=0;
461: if (mat->factortype) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
463: if (mreuse != MAT_IGNORE_MATRIX) {
464: /* Use MatSchurComplement */
465: if (mreuse == MAT_REUSE_MATRIX) {
466: MatSchurComplementGetSubmatrices(*newmat,&A,&Ap,&B,&C,&D);
467: if (!A || !Ap || !B || !C) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Attempting to reuse matrix but Schur complement matrices unset");
468: if (A != Ap) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Preconditioning matrix does not match operator");
469: MatDestroy(&Ap); /* get rid of extra reference */
470: }
471: MatGetSubMatrix(mat,isrow0,iscol0,mreuse,&A);
472: MatGetSubMatrix(mat,isrow0,iscol1,mreuse,&B);
473: MatGetSubMatrix(mat,isrow1,iscol0,mreuse,&C);
474: MatGetSubMatrix(mat,isrow1,iscol1,mreuse,&D);
475: switch (mreuse) {
476: case MAT_INITIAL_MATRIX:
477: MatCreateSchurComplement(A,A,B,C,D,newmat);
478: break;
479: case MAT_REUSE_MATRIX:
480: MatSchurComplementUpdate(*newmat,A,A,B,C,D,DIFFERENT_NONZERO_PATTERN);
481: break;
482: default:
483: SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"Unrecognized value of mreuse");
484: }
485: }
486: if (preuse != MAT_IGNORE_MATRIX) {
487: /* Use the diagonal part of A to form D - C inv(diag(A)) B */
488: Mat Ad,AdB,S;
489: Vec diag;
490: PetscInt i,m,n,mstart,mend;
491: PetscScalar *x;
493: /* We could compose these with newpmat so that the matrices can be reused. */
494: if (!A) {MatGetSubMatrix(mat,isrow0,iscol0,MAT_INITIAL_MATRIX,&A);}
495: if (!B) {MatGetSubMatrix(mat,isrow0,iscol1,MAT_INITIAL_MATRIX,&B);}
496: if (!C) {MatGetSubMatrix(mat,isrow1,iscol0,MAT_INITIAL_MATRIX,&C);}
497: if (!D) {MatGetSubMatrix(mat,isrow1,iscol1,MAT_INITIAL_MATRIX,&D);}
499: MatGetVecs(A,&diag,NULL);
500: MatGetDiagonal(A,diag);
501: VecReciprocal(diag);
502: MatGetLocalSize(A,&m,&n);
503: /* We need to compute S = D - C inv(diag(A)) B. For row-oriented formats, it is easy to scale the rows of B and
504: * for column-oriented formats the columns of C can be scaled. Would skip creating a silly diagonal matrix. */
505: MatCreate(PetscObjectComm((PetscObject)A),&Ad);
506: MatSetSizes(Ad,m,n,PETSC_DETERMINE,PETSC_DETERMINE);
507: MatSetOptionsPrefix(Ad,((PetscObject)mat)->prefix);
508: MatAppendOptionsPrefix(Ad,"diag_");
509: MatSetFromOptions(Ad);
510: MatSeqAIJSetPreallocation(Ad,1,NULL);
511: MatMPIAIJSetPreallocation(Ad,1,NULL,0,NULL);
512: MatGetOwnershipRange(Ad,&mstart,&mend);
513: VecGetArray(diag,&x);
514: for (i=mstart; i<mend; i++) {
515: MatSetValue(Ad,i,i,x[i-mstart],INSERT_VALUES);
516: }
517: VecRestoreArray(diag,&x);
518: MatAssemblyBegin(Ad,MAT_FINAL_ASSEMBLY);
519: MatAssemblyEnd(Ad,MAT_FINAL_ASSEMBLY);
520: VecDestroy(&diag);
522: MatMatMult(Ad,B,MAT_INITIAL_MATRIX,1,&AdB);
523: S = (preuse == MAT_REUSE_MATRIX) ? *newpmat : (Mat)0;
524: MatMatMult(C,AdB,preuse,PETSC_DEFAULT,&S);
525: MatAYPX(S,-1,D,DIFFERENT_NONZERO_PATTERN);
526: *newpmat = S;
527: MatDestroy(&Ad);
528: MatDestroy(&AdB);
529: }
530: MatDestroy(&A);
531: MatDestroy(&B);
532: MatDestroy(&C);
533: MatDestroy(&D);
534: return(0);
535: }
539: /*@
540: MatGetSchurComplement - Obtain the Schur complement from eliminating part of the matrix in another part.
542: Collective on Mat
544: Input Parameters:
545: + mat - Matrix in which the complement is to be taken
546: . isrow0 - rows to eliminate
547: . iscol0 - columns to eliminate, (isrow0,iscol0) should be square and nonsingular
548: . isrow1 - rows in which the Schur complement is formed
549: . iscol1 - columns in which the Schur complement is formed
550: . mreuse - MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX, use MAT_IGNORE_MATRIX to put nothing in newmat
551: - preuse - MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX, use MAT_IGNORE_MATRIX to put nothing in newpmat
553: Output Parameters:
554: + newmat - exact Schur complement, often of type MATSCHURCOMPLEMENT which is difficult to use for preconditioning
555: - newpmat - approximate Schur complement suitable for preconditioning
557: Note:
558: Since the real Schur complement is usually dense, providing a good approximation to newpmat usually requires
559: application-specific information. The default for assembled matrices is to use the diagonal of the (0,0) block
560: which will rarely produce a scalable algorithm.
562: Sometimes users would like to provide problem-specific data in the Schur complement, usually only for special row
563: and column index sets. In that case, the user should call PetscObjectComposeFunction() to set
564: "MatNestGetSubMat_C" to their function. If their function needs to fall back to the default implementation, it
565: should call MatGetSchurComplement_Basic().
567: Level: advanced
569: Concepts: matrices^submatrices
571: .seealso: MatGetSubMatrix(), PCFIELDSPLIT, MatCreateSchurComplement()
572: @*/
573: PetscErrorCode MatGetSchurComplement(Mat mat,IS isrow0,IS iscol0,IS isrow1,IS iscol1,MatReuse mreuse,Mat *newmat,MatReuse preuse,Mat *newpmat)
574: {
575: PetscErrorCode ierr,(*f)(Mat,IS,IS,IS,IS,MatReuse,Mat*,MatReuse,Mat*);
586: if (mat->factortype) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
588: PetscObjectQueryFunction((PetscObject)mat,"MatGetSchurComplement_C",&f);
589: if (f) {
590: (*f)(mat,isrow0,iscol0,isrow1,iscol1,mreuse,newmat,preuse,newpmat);
591: } else {
592: MatGetSchurComplement_Basic(mat,isrow0,iscol0,isrow1,iscol1,mreuse,newmat,preuse,newpmat);
593: }
594: return(0);
595: }
599: PETSC_EXTERN PetscErrorCode MatCreate_SchurComplement(Mat N)
600: {
601: PetscErrorCode ierr;
602: Mat_SchurComplement *Na;
605: PetscNewLog(N,Mat_SchurComplement,&Na);
606: N->data = (void*) Na;
608: N->ops->destroy = MatDestroy_SchurComplement;
609: N->ops->getvecs = MatGetVecs_SchurComplement;
610: N->ops->view = MatView_SchurComplement;
611: N->ops->mult = MatMult_SchurComplement;
612: N->ops->multadd = MatMultAdd_SchurComplement;
613: N->ops->setfromoptions = MatSetFromOptions_SchurComplement;
614: N->assembled = PETSC_FALSE;
615: N->preallocated = PETSC_FALSE;
617: KSPCreate(PetscObjectComm((PetscObject)N),&Na->ksp);
618: PetscObjectChangeTypeName((PetscObject)N,MATSCHURCOMPLEMENT);
619: return(0);
620: }
622: static PetscBool KSPMatRegisterAllCalled;
626: /*@C
627: KSPMatRegisterAll - Registers all matrix implementations in the KSP package.
629: Not Collective
631: Level: advanced
633: .keywords: Mat, KSP, register, all
635: .seealso: MatRegisterAll(), MatRegisterDestroy(), KSPInitializePackage()
636: @*/
637: PetscErrorCode KSPMatRegisterAll()
638: {
642: if (KSPMatRegisterAllCalled) return(0);
643: KSPMatRegisterAllCalled = PETSC_TRUE;
644: MatRegister(MATSCHURCOMPLEMENT,MatCreate_SchurComplement);
645: return(0);
646: }