xref: /petsc/src/mat/interface/matrix.c (revision 7d1a2b2bfed25720a23dbf396311effb795425c3)
1 #ifndef lint
2 static char vcid[] = "$Id: matrix.c,v 1.158 1996/03/26 23:12:14 bsmith Exp bsmith $";
3 #endif
4 
5 /*
6    This is where the abstract matrix operations are defined
7 */
8 
9 #include "petsc.h"
10 #include "matimpl.h"        /*I "mat.h" I*/
11 #include "vec/vecimpl.h"
12 #include "pinclude/pviewer.h"
13 #include "draw.h"
14 
15 /*@C
16    MatGetReordering - Gets a reordering for a matrix to reduce fill or to
17    improve numerical stability of LU factorization.
18 
19    Input Parameters:
20 .  mat - the matrix
21 .  type - type of reordering, one of the following:
22 $      ORDER_NATURAL - Natural
23 $      ORDER_ND - Nested Dissection
24 $      ORDER_1WD - One-way Dissection
25 $      ORDER_RCM - Reverse Cuthill-McGee
26 $      ORDER_QMD - Quotient Minimum Degree
27 
28    Output Parameters:
29 .  rperm - row permutation indices
30 .  cperm - column permutation indices
31 
32    Options Database Keys:
33    To specify the ordering through the options database, use one of
34    the following
35 $    -mat_order natural, -mat_order nd, -mat_order 1wd,
36 $    -mat_order rcm, -mat_order qmd
37 
38    Notes:
39    If the column permutations and row permutations are the same,
40    then MatGetReordering() returns 0 in cperm.
41 
42    The user can define additional orderings; see MatReorderingRegister().
43 
44 .keywords: matrix, set, ordering, factorization, direct, ILU, LU,
45            fill, reordering, natural, Nested Dissection,
46            One-way Dissection, Cholesky, Reverse Cuthill-McGee,
47            Quotient Minimum Degree
48 
49 .seealso:  MatGetReorderingTypeFromOptions(), MatReorderingRegister()
50 @*/
51 int MatGetReordering(Mat mat,MatOrdering type,IS *rperm,IS *cperm)
52 {
53   int         ierr;
54   PetscValidHeaderSpecific(mat,MAT_COOKIE);
55   if (!mat->assembled) SETERRQ(1,"MatGetReordering:Not for unassembled matrix");
56 
57   if (!mat->ops.getreordering) {*rperm = 0; *cperm = 0; return 0;}
58   PLogEventBegin(MAT_GetReordering,mat,0,0,0);
59   ierr = MatGetReorderingTypeFromOptions(0,&type); CHKERRQ(ierr);
60   ierr = (*mat->ops.getreordering)(mat,type,rperm,cperm); CHKERRQ(ierr);
61   PLogEventEnd(MAT_GetReordering,mat,0,0,0);
62   return 0;
63 }
64 
65 /*@C
66    MatGetRow - Gets a row of a matrix.  You MUST call MatRestoreRow()
67    for each row that you get to ensure that your application does
68    not bleed memory.
69 
70    Input Parameters:
71 .  mat - the matrix
72 .  row - the row to get
73 
74    Output Parameters:
75 .  ncols -  the number of nonzeros in the row
76 .  cols - if nonzero, the column numbers
77 .  vals - if nonzero, the values
78 
79    Notes:
80    This routine is provided for people who need to have direct access
81    to the structure of a matrix.  We hope that we provide enough
82    high-level matrix routines that few users will need it.
83 
84    For better efficiency, set cols and/or vals to PETSC_NULL if you do
85    not wish to extract these quantities.
86 
87    The user can only examine the values extracted with MatGetRow();
88    the values cannot be altered.  To change the matrix entries, one
89    must use MatSetValues().
90 
91    Caution:
92    Do not try to chnage the contents of the output arrays (cols and vals).
93    In some cases, this may corrupt the matrix.
94 
95 .keywords: matrix, row, get, extract
96 
97 .seealso: MatRestoreRow(), MatSetValues()
98 @*/
99 int MatGetRow(Mat mat,int row,int *ncols,int **cols,Scalar **vals)
100 {
101   int   ierr;
102   PetscValidHeaderSpecific(mat,MAT_COOKIE);
103   if (!mat->assembled) SETERRQ(1,"MatGetRow:Not for unassembled matrix");
104   PLogEventBegin(MAT_GetRow,mat,0,0,0);
105   ierr = (*mat->ops.getrow)(mat,row,ncols,cols,vals); CHKERRQ(ierr);
106   PLogEventEnd(MAT_GetRow,mat,0,0,0);
107   return 0;
108 }
109 
110 /*@C
111    MatRestoreRow - Frees any temporary space allocated by MatGetRow().
112 
113    Input Parameters:
114 .  mat - the matrix
115 .  row - the row to get
116 .  ncols, cols - the number of nonzeros and their columns
117 .  vals - if nonzero the column values
118 
119 .keywords: matrix, row, restore
120 
121 .seealso:  MatGetRow()
122 @*/
123 int MatRestoreRow(Mat mat,int row,int *ncols,int **cols,Scalar **vals)
124 {
125   PetscValidHeaderSpecific(mat,MAT_COOKIE);
126   if (!mat->assembled) SETERRQ(1,"MatRestoreRow:Not for unassembled matrix");
127   if (!mat->ops.restorerow) return 0;
128   return (*mat->ops.restorerow)(mat,row,ncols,cols,vals);
129 }
130 /*@
131    MatView - Visualizes a matrix object.
132 
133    Input Parameters:
134 .  mat - the matrix
135 .  ptr - visualization context
136 
137    Notes:
138    The available visualization contexts include
139 $     STDOUT_VIEWER_SELF - standard output (default)
140 $     STDOUT_VIEWER_WORLD - synchronized standard
141 $       output where only the first processor opens
142 $       the file.  All other processors send their
143 $       data to the first processor to print.
144 
145    The user can open alternative vistualization contexts with
146 $    ViewerFileOpenASCII() - output to a specified file
147 $    ViewerFileOpenBinary() - output in binary to a
148 $         specified file; corresponding input uses MatLoad()
149 $    ViewerDrawOpenX() - output nonzero matrix structure to
150 $         an X window display
151 $    ViewerMatlabOpen() - output matrix to Matlab viewer.
152 $         Currently only the sequential dense and AIJ
153 $         matrix types support the Matlab viewer.
154 
155    The user can call ViewerSetFormat() to specify the output
156    format of ASCII printed objects (when using STDOUT_VIEWER_SELF,
157    STDOUT_VIEWER_WORLD and ViewerFileOpenASCII).  Available formats include
158 $    ASCII_FORMAT_DEFAULT - default, prints matrix contents
159 $    ASCII_FORMAT_MATLAB - Matlab format
160 $    ASCII_FORMAT_IMPL - implementation-specific format
161 $      (which is in many cases the same as the default)
162 $    ASCII_FORMAT_INFO - basic information about the matrix
163 $      size and structure (not the matrix entries)
164 $    ASCII_FORMAT_INFO_DETAILED - more detailed information about the
165 $      matrix structure
166 
167 .keywords: matrix, view, visualize, output, print, write, draw
168 
169 .seealso: ViewerSetFormat(), ViewerFileOpenASCII(), ViewerDrawOpenX(),
170           ViewerMatlabOpen(), ViewerFileOpenBinary(), MatLoad()
171 @*/
172 int MatView(Mat mat,Viewer viewer)
173 {
174   int          format, ierr, rows, cols,nz, nzalloc, mem;
175   FILE         *fd;
176   char         *cstr;
177   ViewerType   vtype;
178   MPI_Comm     comm = mat->comm;
179 
180   PetscValidHeaderSpecific(mat,MAT_COOKIE);
181   if (!mat->assembled) SETERRQ(1,"MatView:Not for unassembled matrix");
182 
183   if (!viewer) {
184     viewer = STDOUT_VIEWER_SELF;
185   }
186 
187   ierr = ViewerGetType(viewer,&vtype);
188   if (vtype == ASCII_FILE_VIEWER || vtype == ASCII_FILES_VIEWER) {
189     ierr = ViewerGetFormat(viewer,&format); CHKERRQ(ierr);
190     ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr);
191     if (format == ASCII_FORMAT_INFO || format == ASCII_FORMAT_INFO_DETAILED) {
192       PetscFPrintf(comm,fd,"Matrix Object:\n");
193       ierr = MatGetType(mat,PETSC_NULL,&cstr); CHKERRQ(ierr);
194       ierr = MatGetSize(mat,&rows,&cols); CHKERRQ(ierr);
195       PetscFPrintf(comm,fd,"  type=%s, rows=%d, cols=%d\n",cstr,rows,cols);
196       if (mat->ops.getinfo) {
197         ierr = MatGetInfo(mat,MAT_GLOBAL_SUM,&nz,&nzalloc,&mem); CHKERRQ(ierr);
198         PetscFPrintf(comm,fd,"  total: nonzeros=%d, allocated nonzeros=%d\n",nz,
199                      nzalloc);
200       }
201     }
202   }
203   if (mat->view) {ierr = (*mat->view)((PetscObject)mat,viewer); CHKERRQ(ierr);}
204   return 0;
205 }
206 
207 /*@C
208    MatDestroy - Frees space taken by a matrix.
209 
210    Input Parameter:
211 .  mat - the matrix
212 
213 .keywords: matrix, destroy
214 @*/
215 int MatDestroy(Mat mat)
216 {
217   int ierr;
218   PetscValidHeaderSpecific(mat,MAT_COOKIE);
219   ierr = (*mat->destroy)((PetscObject)mat); CHKERRQ(ierr);
220   return 0;
221 }
222 /*@
223    MatValid - Checks whether a matrix object is valid.
224 
225    Input Parameter:
226 .  m - the matrix to check
227 
228    Output Parameter:
229    flg - flag indicating matrix status, either
230 $     PETSC_TRUE if matrix is valid;
231 $     PETSC_FALSE otherwise.
232 
233 .keywords: matrix, valid
234 @*/
235 int MatValid(Mat m,PetscTruth *flg)
236 {
237   if (!m)                           *flg = PETSC_FALSE;
238   else if (m->cookie != MAT_COOKIE) *flg = PETSC_FALSE;
239   else                              *flg = PETSC_TRUE;
240   return 0;
241 }
242 
243 /*@
244    MatSetValues - Inserts or adds a block of values into a matrix.
245    These values may be cached, so MatAssemblyBegin() and MatAssemblyEnd()
246    MUST be called after all calls to MatSetValues() have been completed.
247 
248    Input Parameters:
249 .  mat - the matrix
250 .  v - a logically two-dimensional array of values
251 .  m, indexm - the number of rows and their global indices
252 .  n, indexn - the number of columns and their global indices
253 .  addv - either ADD_VALUES or INSERT_VALUES, where
254 $     ADD_VALUES - adds values to any existing entries
255 $     INSERT_VALUES - replaces existing entries with new values
256 
257    Notes:
258    By default the values, v, are row-oriented and unsorted.
259    See MatSetOptions() for other options.
260 
261    Calls to MatSetValues() with the INSERT_VALUES and ADD_VALUES
262    options cannot be mixed without intervening calls to the assembly
263    routines.
264 
265 .keywords: matrix, insert, add, set, values
266 
267 .seealso: MatSetOptions(), MatAssemblyBegin(), MatAssemblyEnd()
268 @*/
269 int MatSetValues(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v,
270                                                         InsertMode addv)
271 {
272   int ierr;
273   PetscValidHeaderSpecific(mat,MAT_COOKIE);
274   if (mat->assembled) {
275     mat->was_assembled = PETSC_TRUE;
276     mat->assembled     = PETSC_FALSE;
277   }
278   PLogEventBegin(MAT_SetValues,mat,0,0,0);
279   ierr = (*mat->ops.setvalues)(mat,m,idxm,n,idxn,v,addv);CHKERRQ(ierr);
280   PLogEventEnd(MAT_SetValues,mat,0,0,0);
281   return 0;
282 }
283 
284 /*@
285    MatGetValues - Gets a block of values from a matrix.
286 
287    Input Parameters:
288 .  mat - the matrix
289 .  v - a logically two-dimensional array for storing the values
290 .  m, indexm - the number of rows and their global indices
291 .  n, indexn - the number of columns and their global indices
292 
293    Notes:
294    The user must allocate space (m*n Scalars) for the values, v.
295    The values, v, are then returned in a row-oriented format,
296    analogous to that used by default in MatSetValues().
297 
298 .keywords: matrix, get, values
299 
300 .seealso: MatGetRow(), MatGetSubmatrix(), MatGetSubmatrices(), MatSetValues()
301 @*/
302 int MatGetValues(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v)
303 {
304   int ierr;
305 
306   PetscValidHeaderSpecific(mat,MAT_COOKIE);
307   if (!mat->assembled) SETERRQ(1,"MatGetValues:Not for unassembled matrix");
308 
309   PLogEventBegin(MAT_GetValues,mat,0,0,0);
310   ierr = (*mat->ops.getvalues)(mat,m,idxm,n,idxn,v); CHKERRQ(ierr);
311   PLogEventEnd(MAT_GetValues,mat,0,0,0);
312   return 0;
313 }
314 
315 /* --------------------------------------------------------*/
316 /*@
317    MatMult - Computes matrix-vector product.
318 
319    Input Parameters:
320 .  mat - the matrix
321 .  x   - the vector to be multilplied
322 
323    Output Parameters:
324 .  y - the result
325 
326 .keywords: matrix, multiply, matrix-vector product
327 
328 .seealso: MatMultTrans(), MatMultAdd(), MatMultTransAdd()
329 @*/
330 int MatMult(Mat mat,Vec x,Vec y)
331 {
332   int ierr;
333   PetscValidHeaderSpecific(mat,MAT_COOKIE);
334   PetscValidHeaderSpecific(x,VEC_COOKIE);PetscValidHeaderSpecific(y,VEC_COOKIE);
335   if (!mat->assembled) SETERRQ(1,"MatMult:Not for unassembled matrix");
336   if (x == y) SETERRQ(1,"MatMult:x and y must be different vectors");
337 
338   PLogEventBegin(MAT_Mult,mat,x,y,0);
339   ierr = (*mat->ops.mult)(mat,x,y); CHKERRQ(ierr);
340   PLogEventEnd(MAT_Mult,mat,x,y,0);
341   return 0;
342 }
343 /*@
344    MatMultTrans - Computes matrix transpose times a vector.
345 
346    Input Parameters:
347 .  mat - the matrix
348 .  x   - the vector to be multilplied
349 
350    Output Parameters:
351 .  y - the result
352 
353 .keywords: matrix, multiply, matrix-vector product, transpose
354 
355 .seealso: MatMult(), MatMultAdd(), MatMultTransAdd()
356 @*/
357 int MatMultTrans(Mat mat,Vec x,Vec y)
358 {
359   int ierr;
360   PetscValidHeaderSpecific(mat,MAT_COOKIE);
361   PetscValidHeaderSpecific(x,VEC_COOKIE); PetscValidHeaderSpecific(y,VEC_COOKIE);
362   if (!mat->assembled) SETERRQ(1,"MatMultTrans:Not for unassembled matrix");
363   if (x == y) SETERRQ(1,"MatMultTrans:x and y must be different vectors");
364 
365   PLogEventBegin(MAT_MultTrans,mat,x,y,0);
366   ierr = (*mat->ops.multtrans)(mat,x,y); CHKERRQ(ierr);
367   PLogEventEnd(MAT_MultTrans,mat,x,y,0);
368   return 0;
369 }
370 /*@
371     MatMultAdd -  Computes v3 = v2 + A * v1.
372 
373   Input Parameters:
374 .    mat - the matrix
375 .    v1, v2 - the vectors
376 
377   Output Parameters:
378 .    v3 - the result
379 
380 .keywords: matrix, multiply, matrix-vector product, add
381 
382 .seealso: MatMultTrans(), MatMult(), MatMultTransAdd()
383 @*/
384 int MatMultAdd(Mat mat,Vec v1,Vec v2,Vec v3)
385 {
386   int ierr;
387   PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(v1,VEC_COOKIE);
388   PetscValidHeaderSpecific(v2,VEC_COOKIE); PetscValidHeaderSpecific(v3,VEC_COOKIE);
389   if (!mat->assembled) SETERRQ(1,"MatMultAdd:Not for unassembled matrix");
390 
391   PLogEventBegin(MAT_MultAdd,mat,v1,v2,v3);
392   if (v1 == v3) SETERRQ(1,"MatMultAdd:v1 and v3 must be different vectors");
393   ierr = (*mat->ops.multadd)(mat,v1,v2,v3); CHKERRQ(ierr);
394   PLogEventEnd(MAT_MultAdd,mat,v1,v2,v3);
395   return 0;
396 }
397 /*@
398     MatMultTransAdd - Computes v3 = v2 + A' * v1.
399 
400   Input Parameters:
401 .    mat - the matrix
402 .    v1, v2 - the vectors
403 
404   Output Parameters:
405 .    v3 - the result
406 
407 .keywords: matrix, multiply, matrix-vector product, transpose, add
408 
409 .seealso: MatMultTrans(), MatMultAdd(), MatMult()
410 @*/
411 int MatMultTransAdd(Mat mat,Vec v1,Vec v2,Vec v3)
412 {
413   int ierr;
414   PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(v1,VEC_COOKIE);
415   PetscValidHeaderSpecific(v2,VEC_COOKIE);PetscValidHeaderSpecific(v3,VEC_COOKIE);
416   if (!mat->assembled) SETERRQ(1,"MatMultTransAdd:Not for unassembled matrix");
417   if (!mat->ops.multtransadd) SETERRQ(PETSC_ERR_SUP,"MatMultTransAdd");
418   if (v1 == v3) SETERRQ(1,"MatMultTransAdd:v1 and v2 must be different vectors");
419 
420   PLogEventBegin(MAT_MultTransAdd,mat,v1,v2,v3);
421   ierr = (*mat->ops.multtransadd)(mat,v1,v2,v3); CHKERRQ(ierr);
422   PLogEventEnd(MAT_MultTransAdd,mat,v1,v2,v3);
423   return 0;
424 }
425 /* ------------------------------------------------------------*/
426 /*@C
427    MatGetInfo - Returns information about matrix storage (number of
428    nonzeros, memory).
429 
430    Input Parameters:
431 .  mat - the matrix
432 
433    Output Parameters:
434 .  flag - flag indicating the type of parameters to be returned
435 $    flag = MAT_LOCAL: local matrix
436 $    flag = MAT_GLOBAL_MAX: maximum over all processors
437 $    flag = MAT_GLOBAL_SUM: sum over all processors
438 .   nz - the number of nonzeros [or PETSC_NULL]
439 .   nzalloc - the number of allocated nonzeros [or PETSC_NULL]
440 .   mem - the memory used (in bytes)  [or PETSC_NULL]
441 
442 .keywords: matrix, get, info, storage, nonzeros, memory
443 @*/
444 int MatGetInfo(Mat mat,MatInfoType flag,int *nz,int *nzalloc,int *mem)
445 {
446   PetscValidHeaderSpecific(mat,MAT_COOKIE);
447   if (!mat->ops.getinfo) SETERRQ(PETSC_ERR_SUP,"MatGetInfo");
448   return  (*mat->ops.getinfo)(mat,flag,nz,nzalloc,mem);
449 }
450 /* ----------------------------------------------------------*/
451 /*@
452    MatLUFactor - Performs in-place LU factorization of matrix.
453 
454    Input Parameters:
455 .  mat - the matrix
456 .  row - row permutation
457 .  col - column permutation
458 .  f - expected fill as ratio of original fill.
459 
460 .keywords: matrix, factor, LU, in-place
461 
462 .seealso: MatLUFactorSymbolic(), MatLUFactorNumeric(), MatCholeskyFactor()
463 @*/
464 int MatLUFactor(Mat mat,IS row,IS col,double f)
465 {
466   int ierr;
467   PetscValidHeaderSpecific(mat,MAT_COOKIE);
468   if (!mat->ops.lufactor) SETERRQ(PETSC_ERR_SUP,"MatLUFactor");
469   if (!mat->assembled) SETERRQ(1,"MatLUFactor:Not for unassembled matrix");
470 
471   PLogEventBegin(MAT_LUFactor,mat,row,col,0);
472   ierr = (*mat->ops.lufactor)(mat,row,col,f); CHKERRQ(ierr);
473   PLogEventEnd(MAT_LUFactor,mat,row,col,0);
474   return 0;
475 }
476 /*@
477    MatILUFactor - Performs in-place ILU factorization of matrix.
478 
479    Input Parameters:
480 .  mat - the matrix
481 .  row - row permutation
482 .  col - column permutation
483 .  f - expected fill as ratio of original fill.
484 .  level - number of levels of fill.
485 
486    Note: probably really only in-place when level is zero.
487 .keywords: matrix, factor, ILU, in-place
488 
489 .seealso: MatILUFactorSymbolic(), MatLUFactorNumeric(), MatCholeskyFactor()
490 @*/
491 int MatILUFactor(Mat mat,IS row,IS col,double f,int level)
492 {
493   int ierr;
494   PetscValidHeaderSpecific(mat,MAT_COOKIE);
495   if (!mat->ops.ilufactor) SETERRQ(PETSC_ERR_SUP,"MatILUFactor");
496   if (!mat->assembled) SETERRQ(1,"MatILUFactor:Not for unassembled matrix");
497 
498   PLogEventBegin(MAT_ILUFactor,mat,row,col,0);
499   ierr = (*mat->ops.ilufactor)(mat,row,col,f,level); CHKERRQ(ierr);
500   PLogEventEnd(MAT_ILUFactor,mat,row,col,0);
501   return 0;
502 }
503 
504 /*@
505    MatLUFactorSymbolic - Performs symbolic LU factorization of matrix.
506    Call this routine before calling MatLUFactorNumeric().
507 
508    Input Parameters:
509 .  mat - the matrix
510 .  row, col - row and column permutations
511 .  f - expected fill as ratio of the original number of nonzeros,
512        for example 3.0; choosing this parameter well can result in
513        more efficient use of time and space.
514 
515    Output Parameter:
516 .  fact - new matrix that has been symbolically factored
517 
518    Options Database Key:
519 $     -mat_lu_fill <f>, where f is the fill ratio
520 
521    Notes:
522    See the file $(PETSC_DIR)/Performace for additional information about
523    choosing the fill factor for better efficiency.
524 
525 .keywords: matrix, factor, LU, symbolic, fill
526 
527 .seealso: MatLUFactor(), MatLUFactorNumeric(), MatCholeskyFactor()
528 @*/
529 int MatLUFactorSymbolic(Mat mat,IS row,IS col,double f,Mat *fact)
530 {
531   int ierr,flg;
532   PetscValidHeaderSpecific(mat,MAT_COOKIE);
533   if (!fact) SETERRQ(1,"MatLUFactorSymbolic:Missing factor matrix argument");
534   if (!mat->ops.lufactorsymbolic) SETERRQ(PETSC_ERR_SUP,"MatLUFactorSymbolic");
535   if (!mat->assembled) SETERRQ(1,"MatLUFactorSymbolic:Not for unassembled matrix");
536 
537   ierr = OptionsGetDouble(PETSC_NULL,"-mat_lu_fill",&f,&flg); CHKERRQ(ierr);
538   PLogEventBegin(MAT_LUFactorSymbolic,mat,row,col,0);
539   ierr = (*mat->ops.lufactorsymbolic)(mat,row,col,f,fact); CHKERRQ(ierr);
540   PLogEventEnd(MAT_LUFactorSymbolic,mat,row,col,0);
541   return 0;
542 }
543 /*@
544    MatLUFactorNumeric - Performs numeric LU factorization of a matrix.
545    Call this routine after first calling MatLUFactorSymbolic().
546 
547    Input Parameters:
548 .  mat - the matrix
549 .  row, col - row and  column permutations
550 
551    Output Parameters:
552 .  fact - symbolically factored matrix that must have been generated
553           by MatLUFactorSymbolic()
554 
555    Notes:
556    See MatLUFactor() for in-place factorization.  See
557    MatCholeskyFactorNumeric() for the symmetric, positive definite case.
558 
559 .keywords: matrix, factor, LU, numeric
560 
561 .seealso: MatLUFactorSymbolic(), MatLUFactor(), MatCholeskyFactor()
562 @*/
563 int MatLUFactorNumeric(Mat mat,Mat *fact)
564 {
565   int ierr,flg;
566 
567   PetscValidHeaderSpecific(mat,MAT_COOKIE);
568   if (!fact) SETERRQ(1,"MatLUFactorNumeric:Missing factor matrix argument");
569   if (!mat->ops.lufactornumeric) SETERRQ(PETSC_ERR_SUP,"MatLUFactorNumeric");
570   if (!mat->assembled) SETERRQ(1,"MatLUFactorNumeric:Not for unassembled matrix");
571 
572   PLogEventBegin(MAT_LUFactorNumeric,mat,*fact,0,0);
573   ierr = (*mat->ops.lufactornumeric)(mat,fact); CHKERRQ(ierr);
574   PLogEventEnd(MAT_LUFactorNumeric,mat,*fact,0,0);
575   ierr = OptionsHasName(PETSC_NULL,"-mat_view_draw",&flg); CHKERRQ(ierr);
576   if (flg) {
577     Viewer  viewer;
578     ierr = ViewerDrawOpenX((*fact)->comm,0,0,0,0,300,300,&viewer);CHKERRQ(ierr);
579     ierr = MatView(*fact,viewer); CHKERRQ(ierr);
580     ierr = ViewerFlush(viewer); CHKERRQ(ierr);
581     ierr = ViewerDestroy(viewer); CHKERRQ(ierr);
582   }
583   return 0;
584 }
585 /*@
586    MatCholeskyFactor - Performs in-place Cholesky factorization of a
587    symmetric matrix.
588 
589    Input Parameters:
590 .  mat - the matrix
591 .  perm - row and column permutations
592 .  f - expected fill as ratio of original fill
593 
594    Notes:
595    See MatLUFactor() for the nonsymmetric case.  See also
596    MatCholeskyFactorSymbolic(), and MatCholeskyFactorNumeric().
597 
598 .keywords: matrix, factor, in-place, Cholesky
599 
600 .seealso: MatLUFactor(), MatCholeskyFactorSymbolic(), MatCholeskyFactorNumeric()
601 @*/
602 int MatCholeskyFactor(Mat mat,IS perm,double f)
603 {
604   int ierr;
605   PetscValidHeaderSpecific(mat,MAT_COOKIE);
606   if (!mat->ops.choleskyfactor) SETERRQ(PETSC_ERR_SUP,"MatCholeskyFactor");
607   if (!mat->assembled) SETERRQ(1,"MatCholeskyFactor:Not for unassembled matrix");
608 
609   PLogEventBegin(MAT_CholeskyFactor,mat,perm,0,0);
610   ierr = (*mat->ops.choleskyfactor)(mat,perm,f); CHKERRQ(ierr);
611   PLogEventEnd(MAT_CholeskyFactor,mat,perm,0,0);
612   return 0;
613 }
614 /*@
615    MatCholeskyFactorSymbolic - Performs symbolic Cholesky factorization
616    of a symmetric matrix.
617 
618    Input Parameters:
619 .  mat - the matrix
620 .  perm - row and column permutations
621 .  f - expected fill as ratio of original
622 
623    Output Parameter:
624 .  fact - the factored matrix
625 
626    Notes:
627    See MatLUFactorSymbolic() for the nonsymmetric case.  See also
628    MatCholeskyFactor() and MatCholeskyFactorNumeric().
629 
630 .keywords: matrix, factor, factorization, symbolic, Cholesky
631 
632 .seealso: MatLUFactorSymbolic(), MatCholeskyFactor(), MatCholeskyFactorNumeric()
633 @*/
634 int MatCholeskyFactorSymbolic(Mat mat,IS perm,double f,Mat *fact)
635 {
636   int ierr;
637   PetscValidHeaderSpecific(mat,MAT_COOKIE);
638   if (!fact) SETERRQ(1,"MatCholeskyFactorSymbolic:Missing factor matrix argument");
639   if (!mat->ops.choleskyfactorsymbolic)SETERRQ(PETSC_ERR_SUP,"MatCholeskyFactorSymbolic");
640   if (!mat->assembled) SETERRQ(1,"MatCholeskyFactorSymbolic:Not for unassembled matrix");
641 
642   PLogEventBegin(MAT_CholeskyFactorSymbolic,mat,perm,0,0);
643   ierr = (*mat->ops.choleskyfactorsymbolic)(mat,perm,f,fact); CHKERRQ(ierr);
644   PLogEventEnd(MAT_CholeskyFactorSymbolic,mat,perm,0,0);
645   return 0;
646 }
647 /*@
648    MatCholeskyFactorNumeric - Performs numeric Cholesky factorization
649    of a symmetric matrix. Call this routine after first calling
650    MatCholeskyFactorSymbolic().
651 
652    Input Parameter:
653 .  mat - the initial matrix
654 
655    Output Parameter:
656 .  fact - the factored matrix
657 
658 .keywords: matrix, factor, numeric, Cholesky
659 
660 .seealso: MatCholeskyFactorSymbolic(), MatCholeskyFactor(), MatLUFactorNumeric()
661 @*/
662 int MatCholeskyFactorNumeric(Mat mat,Mat *fact)
663 {
664   int ierr;
665   PetscValidHeaderSpecific(mat,MAT_COOKIE);
666   if (!fact) SETERRQ(1,"MatCholeskyFactorNumeric:Missing factor matrix argument");
667   if (!mat->ops.choleskyfactornumeric) SETERRQ(PETSC_ERR_SUP,"MatCholeskyFactorNumeric");
668   if (!mat->assembled) SETERRQ(1,"MatCholeskyFactorNumeric:Not for unassembled matrix");
669 
670   PLogEventBegin(MAT_CholeskyFactorNumeric,mat,*fact,0,0);
671   ierr = (*mat->ops.choleskyfactornumeric)(mat,fact); CHKERRQ(ierr);
672   PLogEventEnd(MAT_CholeskyFactorNumeric,mat,*fact,0,0);
673   return 0;
674 }
675 /* ----------------------------------------------------------------*/
676 /*@
677    MatSolve - Solves A x = b, given a factored matrix.
678 
679    Input Parameters:
680 .  mat - the factored matrix
681 .  b - the right-hand-side vector
682 
683    Output Parameter:
684 .  x - the result vector
685 
686 .keywords: matrix, linear system, solve, LU, Cholesky, triangular solve
687 
688 .seealso: MatSolveAdd(), MatSolveTrans(), MatSolveTransAdd()
689 @*/
690 int MatSolve(Mat mat,Vec b,Vec x)
691 {
692   int ierr;
693   PetscValidHeaderSpecific(mat,MAT_COOKIE);
694   PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
695   if (x == b) SETERRQ(1,"MatSolve:x and y must be different vectors");
696   if (!mat->factor) SETERRQ(1,"MatSolve:Unfactored matrix");
697 
698   if (!mat->ops.solve) SETERRQ(PETSC_ERR_SUP,"MatSolve");
699   PLogEventBegin(MAT_Solve,mat,b,x,0);
700   ierr = (*mat->ops.solve)(mat,b,x); CHKERRQ(ierr);
701   PLogEventEnd(MAT_Solve,mat,b,x,0);
702   return 0;
703 }
704 
705 /* @
706    MatForwardSolve - Solves L x = b, given a factored matrix, A = LU.
707 
708    Input Parameters:
709 .  mat - the factored matrix
710 .  b - the right-hand-side vector
711 
712    Output Parameter:
713 .  x - the result vector
714 
715    Notes:
716    MatSolve() should be used for most applications, as it performs
717    a forward solve followed by a backward solve.
718 
719 .keywords: matrix, forward, LU, Cholesky, triangular solve
720 
721 .seealso: MatSolve(), MatBackwardSolve()
722 @ */
723 int MatForwardSolve(Mat mat,Vec b,Vec x)
724 {
725   int ierr;
726   PetscValidHeaderSpecific(mat,MAT_COOKIE);
727   PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
728   if (x == b) SETERRQ(1,"MatForwardSolve:x and y must be different vectors");
729   if (!mat->factor) SETERRQ(1,"MatForwardSolve:Unfactored matrix");
730   if (!mat->ops.forwardsolve) SETERRQ(PETSC_ERR_SUP,"MatForwardSolve");
731 
732   PLogEventBegin(MAT_ForwardSolve,mat,b,x,0);
733   ierr = (*mat->ops.forwardsolve)(mat,b,x); CHKERRQ(ierr);
734   PLogEventEnd(MAT_ForwardSolve,mat,b,x,0);
735   return 0;
736 }
737 
738 /* @
739    MatBackwardSolve - Solves U x = b, given a factored matrix, A = LU.
740 
741    Input Parameters:
742 .  mat - the factored matrix
743 .  b - the right-hand-side vector
744 
745    Output Parameter:
746 .  x - the result vector
747 
748    Notes:
749    MatSolve() should be used for most applications, as it performs
750    a forward solve followed by a backward solve.
751 
752 .keywords: matrix, backward, LU, Cholesky, triangular solve
753 
754 .seealso: MatSolve(), MatForwardSolve()
755 @ */
756 int MatBackwardSolve(Mat mat,Vec b,Vec x)
757 {
758   int ierr;
759   PetscValidHeaderSpecific(mat,MAT_COOKIE);
760   PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
761   if (x == b) SETERRQ(1,"MatBackwardSolve:x and b must be different vectors");
762   if (!mat->factor) SETERRQ(1,"MatBackwardSolve:Unfactored matrix");
763   if (!mat->ops.backwardsolve) SETERRQ(PETSC_ERR_SUP,"MatBackwardSolve");
764 
765   PLogEventBegin(MAT_BackwardSolve,mat,b,x,0);
766   ierr = (*mat->ops.backwardsolve)(mat,b,x); CHKERRQ(ierr);
767   PLogEventEnd(MAT_BackwardSolve,mat,b,x,0);
768   return 0;
769 }
770 
771 /*@
772    MatSolveAdd - Computes x = y + inv(A)*b, given a factored matrix.
773 
774    Input Parameters:
775 .  mat - the factored matrix
776 .  b - the right-hand-side vector
777 .  y - the vector to be added to
778 
779    Output Parameter:
780 .  x - the result vector
781 
782 .keywords: matrix, linear system, solve, LU, Cholesky, add
783 
784 .seealso: MatSolve(), MatSolveTrans(), MatSolveTransAdd()
785 @*/
786 int MatSolveAdd(Mat mat,Vec b,Vec y,Vec x)
787 {
788   Scalar one = 1.0;
789   Vec    tmp;
790   int    ierr;
791   PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(y,VEC_COOKIE);
792   PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
793   if (x == b) SETERRQ(1,"MatSolveAdd:x and b must be different vectors");
794   if (!mat->factor) SETERRQ(1,"MatSolveAdd:Unfactored matrix");
795 
796   PLogEventBegin(MAT_SolveAdd,mat,b,x,y);
797   if (mat->ops.solveadd)  {
798     ierr = (*mat->ops.solveadd)(mat,b,y,x); CHKERRQ(ierr);
799   }
800   else {
801     /* do the solve then the add manually */
802     if (x != y) {
803       ierr = MatSolve(mat,b,x); CHKERRQ(ierr);
804       ierr = VecAXPY(&one,y,x); CHKERRQ(ierr);
805     }
806     else {
807       ierr = VecDuplicate(x,&tmp); CHKERRQ(ierr);
808       PLogObjectParent(mat,tmp);
809       ierr = VecCopy(x,tmp); CHKERRQ(ierr);
810       ierr = MatSolve(mat,b,x); CHKERRQ(ierr);
811       ierr = VecAXPY(&one,tmp,x); CHKERRQ(ierr);
812       ierr = VecDestroy(tmp); CHKERRQ(ierr);
813     }
814   }
815   PLogEventEnd(MAT_SolveAdd,mat,b,x,y);
816   return 0;
817 }
818 /*@
819    MatSolveTrans - Solves A' x = b, given a factored matrix.
820 
821    Input Parameters:
822 .  mat - the factored matrix
823 .  b - the right-hand-side vector
824 
825    Output Parameter:
826 .  x - the result vector
827 
828 .keywords: matrix, linear system, solve, LU, Cholesky, transpose
829 
830 .seealso: MatSolve(), MatSolveAdd(), MatSolveTransAdd()
831 @*/
832 int MatSolveTrans(Mat mat,Vec b,Vec x)
833 {
834   int ierr;
835   PetscValidHeaderSpecific(mat,MAT_COOKIE);
836   PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
837   if (!mat->factor) SETERRQ(1,"MatSolveTrans:Unfactored matrix");
838   if (x == b) SETERRQ(1,"MatSolveTrans:x and b must be different vectors");
839   if (!mat->ops.solvetrans) SETERRQ(PETSC_ERR_SUP,"MatSolveTrans");
840 
841   PLogEventBegin(MAT_SolveTrans,mat,b,x,0);
842   ierr = (*mat->ops.solvetrans)(mat,b,x); CHKERRQ(ierr);
843   PLogEventEnd(MAT_SolveTrans,mat,b,x,0);
844   return 0;
845 }
846 /*@
847    MatSolveTransAdd - Computes x = y + inv(trans(A)) b, given a
848                       factored matrix.
849 
850    Input Parameters:
851 .  mat - the factored matrix
852 .  b - the right-hand-side vector
853 .  y - the vector to be added to
854 
855    Output Parameter:
856 .  x - the result vector
857 
858 .keywords: matrix, linear system, solve, LU, Cholesky, transpose, add
859 
860 .seealso: MatSolve(), MatSolveAdd(), MatSolveTrans()
861 @*/
862 int MatSolveTransAdd(Mat mat,Vec b,Vec y,Vec x)
863 {
864   Scalar one = 1.0;
865   int    ierr;
866   Vec    tmp;
867   PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(y,VEC_COOKIE);
868   PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
869   if (x == b) SETERRQ(1,"MatSolveTransAdd:x and b must be different vectors");
870   if (!mat->factor) SETERRQ(1,"MatSolveTransAdd:Unfactored matrix");
871 
872   PLogEventBegin(MAT_SolveTransAdd,mat,b,x,y);
873   if (mat->ops.solvetransadd) {
874     ierr = (*mat->ops.solvetransadd)(mat,b,y,x); CHKERRQ(ierr);
875   }
876   else {
877     /* do the solve then the add manually */
878     if (x != y) {
879       ierr = MatSolveTrans(mat,b,x); CHKERRQ(ierr);
880       ierr = VecAXPY(&one,y,x); CHKERRQ(ierr);
881     }
882     else {
883       ierr = VecDuplicate(x,&tmp); CHKERRQ(ierr);
884       PLogObjectParent(mat,tmp);
885       ierr = VecCopy(x,tmp); CHKERRQ(ierr);
886       ierr = MatSolveTrans(mat,b,x); CHKERRQ(ierr);
887       ierr = VecAXPY(&one,tmp,x); CHKERRQ(ierr);
888       ierr = VecDestroy(tmp); CHKERRQ(ierr);
889     }
890   }
891   PLogEventEnd(MAT_SolveTransAdd,mat,b,x,y);
892   return 0;
893 }
894 /* ----------------------------------------------------------------*/
895 
896 /*@
897    MatRelax - Computes one relaxation sweep.
898 
899    Input Parameters:
900 .  mat - the matrix
901 .  b - the right hand side
902 .  omega - the relaxation factor
903 .  flag - flag indicating the type of SOR, one of
904 $     SOR_FORWARD_SWEEP
905 $     SOR_BACKWARD_SWEEP
906 $     SOR_SYMMETRIC_SWEEP (SSOR method)
907 $     SOR_LOCAL_FORWARD_SWEEP
908 $     SOR_LOCAL_BACKWARD_SWEEP
909 $     SOR_LOCAL_SYMMETRIC_SWEEP (local SSOR)
910 $     SOR_APPLY_UPPER, SOR_APPLY_LOWER - applies
911 $       upper/lower triangular part of matrix to
912 $       vector (with omega)
913 $     SOR_ZERO_INITIAL_GUESS - zero initial guess
914 .  shift -  diagonal shift
915 .  its - the number of iterations
916 
917    Output Parameters:
918 .  x - the solution (can contain an initial guess)
919 
920    Notes:
921    SOR_LOCAL_FORWARD_SWEEP, SOR_LOCAL_BACKWARD_SWEEP, and
922    SOR_LOCAL_SYMMETRIC_SWEEP perform seperate independent smoothings
923    on each processor.
924 
925    Application programmers will not generally use MatRelax() directly,
926    but instead will employ the SLES/PC interface.
927 
928    Notes for Advanced Users:
929    The flags are implemented as bitwise inclusive or operations.
930    For example, use (SOR_ZERO_INITIAL_GUESS | SOR_SYMMETRIC_SWEEP)
931    to specify a zero initial guess for SSOR.
932 
933 .keywords: matrix, relax, relaxation, sweep
934 @*/
935 int MatRelax(Mat mat,Vec b,double omega,MatSORType flag,double shift,
936              int its,Vec x)
937 {
938   int ierr;
939   PetscValidHeaderSpecific(mat,MAT_COOKIE);
940   PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
941   if (!mat->ops.relax) SETERRQ(PETSC_ERR_SUP,"MatRelax");
942   if (!mat->assembled) SETERRQ(1,"MatRelax:Not for unassembled matrix");
943 
944   PLogEventBegin(MAT_Relax,mat,b,x,0);
945   ierr =(*mat->ops.relax)(mat,b,omega,flag,shift,its,x); CHKERRQ(ierr);
946   PLogEventEnd(MAT_Relax,mat,b,x,0);
947   return 0;
948 }
949 
950 /*
951       Default matrix copy routine.
952 */
953 int MatCopy_Basic(Mat A,Mat B)
954 {
955   int    ierr,i,rstart,rend,nz,*cwork;
956   Scalar *vwork;
957 
958   ierr = MatZeroEntries(B); CHKERRQ(ierr);
959   ierr = MatGetOwnershipRange(A,&rstart,&rend); CHKERRQ(ierr);
960   for (i=rstart; i<rend; i++) {
961     ierr = MatGetRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr);
962     ierr = MatSetValues(B,1,&i,nz,cwork,vwork,INSERT_VALUES); CHKERRQ(ierr);
963     ierr = MatRestoreRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr);
964   }
965   ierr = MatAssemblyBegin(B,FINAL_ASSEMBLY); CHKERRQ(ierr);
966   ierr = MatAssemblyEnd(B,FINAL_ASSEMBLY); CHKERRQ(ierr);
967   return 0;
968 }
969 
970 /*@C
971    MatCopy - Copys a matrix to another matrix.
972 
973    Input Parameters:
974 .  A - the matrix
975 
976    Output Parameter:
977 .  B - where the copy is put
978 
979    Notes:
980    MatCopy() copies the matrix entries of a matrix to another existing
981    matrix (after first zeroing the second matrix).  A related routine is
982    MatConvert(), which first creates a new matrix and then copies the data.
983 
984 .keywords: matrix, copy, convert
985 
986 .seealso: MatConvert()
987 @*/
988 int MatCopy(Mat A,Mat B)
989 {
990   int ierr;
991   PetscValidHeaderSpecific(A,MAT_COOKIE);PetscValidHeaderSpecific(B,MAT_COOKIE);
992   if (!A->assembled) SETERRQ(1,"MatCopy:Not for unassembled matrix");
993 
994   PLogEventBegin(MAT_Copy,A,B,0,0);
995   if (A->ops.copy) {
996     ierr = (*A->ops.copy)(A,B); CHKERRQ(ierr);
997   }
998   else { /* generic conversion */
999     ierr = MatCopy_Basic(A,B); CHKERRQ(ierr);
1000   }
1001   PLogEventEnd(MAT_Copy,A,B,0,0);
1002   return 0;
1003 }
1004 
1005 /*@C
1006    MatConvert - Converts a matrix to another matrix, either of the same
1007    or different type.
1008 
1009    Input Parameters:
1010 .  mat - the matrix
1011 .  newtype - new matrix type.  Use MATSAME to create a new matrix of the
1012    same type as the original matrix.
1013 
1014    Output Parameter:
1015 .  M - pointer to place new matrix
1016 
1017    Notes:
1018    MatConvert() first creates a new matrix and then copies the data from
1019    the first matrix.  A related routine is MatCopy(), which copies the matrix
1020    entries of one matrix to another already existing matrix context.
1021 
1022 .keywords: matrix, copy, convert
1023 
1024 .seealso: MatCopy()
1025 @*/
1026 int MatConvert(Mat mat,MatType newtype,Mat *M)
1027 {
1028   int ierr;
1029   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1030   if (!M) SETERRQ(1,"MatConvert:Bad new matrix address");
1031   if (!mat->assembled) SETERRQ(1,"MatConvert:Not for unassembled matrix");
1032 
1033   PLogEventBegin(MAT_Convert,mat,0,0,0);
1034   if (newtype == mat->type || newtype == MATSAME) {
1035     if (mat->ops.convertsametype) { /* customized copy */
1036       ierr = (*mat->ops.convertsametype)(mat,M,COPY_VALUES); CHKERRQ(ierr);
1037     }
1038   }
1039   else if (mat->ops.convert) { /* customized conversion */
1040     ierr = (*mat->ops.convert)(mat,newtype,M); CHKERRQ(ierr);
1041   }
1042   else { /* generic conversion */
1043     ierr = MatConvert_Basic(mat,newtype,M); CHKERRQ(ierr);
1044   }
1045   PLogEventEnd(MAT_Convert,mat,0,0,0);
1046   return 0;
1047 }
1048 
1049 /*@
1050    MatGetDiagonal - Gets the diagonal of a matrix.
1051 
1052    Input Parameters:
1053 .  mat - the matrix
1054 
1055    Output Parameters:
1056 .  v - the vector for storing the diagonal
1057 
1058 .keywords: matrix, get, diagonal
1059 @*/
1060 int MatGetDiagonal(Mat mat,Vec v)
1061 {
1062   PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(v,VEC_COOKIE);
1063   if (!mat->assembled) SETERRQ(1,"MatGetDiagonal:Not for unassembled matrix");
1064   if (mat->ops.getdiagonal) return (*mat->ops.getdiagonal)(mat,v);
1065   SETERRQ(PETSC_ERR_SUP,"MatGetDiagonal");
1066 }
1067 
1068 /*@C
1069    MatTranspose - Computes an in-place or out-of-place transpose of a matrix.
1070 
1071    Input Parameters:
1072 .  mat - the matrix to transpose
1073 
1074    Output Parameters:
1075 .  B - the transpose (or pass in PETSC_NULL for an in-place transpose)
1076 
1077 .keywords: matrix, transpose
1078 @*/
1079 int MatTranspose(Mat mat,Mat *B)
1080 {
1081   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1082   if (!mat->assembled) SETERRQ(1,"MatTranspose:Not for unassembled matrix");
1083   if (mat->ops.transpose) return (*mat->ops.transpose)(mat,B);
1084   SETERRQ(PETSC_ERR_SUP,"MatTranspose");
1085 }
1086 
1087 /*@
1088    MatEqual - Compares two matrices.
1089 
1090    Input Parameters:
1091 .  mat1 - the first matrix
1092 .  mat2 - the second matrix
1093 
1094    Output Parameter:
1095 .  flg : PETSC_TRUE if the matrices are equal;
1096          PETSC_FALSE otherwise.
1097 
1098 .keywords: matrix, equal, equivalent
1099 @*/
1100 int MatEqual(Mat mat1,Mat mat2,PetscTruth *flg)
1101 {
1102   PetscValidHeaderSpecific(mat1,MAT_COOKIE); PetscValidHeaderSpecific(mat2,MAT_COOKIE);
1103   if (!mat1->assembled) SETERRQ(1,"MatEqual:Not for unassembled matrix");
1104   if (!mat2->assembled) SETERRQ(1,"MatEqual:Not for unassembled matrix");
1105   if (mat1->ops.equal) return (*mat1->ops.equal)(mat1,mat2, flg);
1106   SETERRQ(PETSC_ERR_SUP,"MatEqual");
1107 }
1108 
1109 /*@
1110    MatDiagonalScale - Scales a matrix on the left and right by diagonal
1111    matrices that are stored as vectors.  Either of the two scaling
1112    matrices can be null.
1113 
1114    Input Parameters:
1115 .  mat - the matrix to be scaled
1116 .  l - the left scaling vector
1117 .  r - the right scaling vector
1118 
1119 .keywords: matrix, scale
1120 @*/
1121 int MatDiagonalScale(Mat mat,Vec l,Vec r)
1122 {
1123   int ierr;
1124   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1125   if (!mat->ops.scale) SETERRQ(PETSC_ERR_SUP,"MatDiagonalScale");
1126   if (l) PetscValidHeaderSpecific(l,VEC_COOKIE);
1127   if (r) PetscValidHeaderSpecific(r,VEC_COOKIE);
1128   if (!mat->assembled) SETERRQ(1,"MatDiagonalScale:Not for unassembled matrix");
1129 
1130   PLogEventBegin(MAT_Scale,mat,0,0,0);
1131   ierr = (*mat->ops.diagonalscale)(mat,l,r); CHKERRQ(ierr);
1132   PLogEventEnd(MAT_Scale,mat,0,0,0);
1133   return 0;
1134 }
1135 
1136 /*@
1137    MatScale - Scales a matrix by a number.
1138 
1139    Input Parameters:
1140 .  mat - the matrix to be scaled
1141 .   a  - the number
1142 
1143    Note: the name of this routine MUST change.
1144 .keywords: matrix, scale
1145 @*/
1146 int MatScale(Scalar *a,Mat mat)
1147 {
1148   int ierr;
1149   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1150   if (!mat->ops.scale) SETERRQ(PETSC_ERR_SUP,"MatScale");
1151   if (!mat->assembled) SETERRQ(1,"MatScale:Not for unassembled matrix");
1152 
1153   PLogEventBegin(MAT_Scale,mat,0,0,0);
1154   ierr = (*mat->ops.scale)(a,mat); CHKERRQ(ierr);
1155   PLogEventEnd(MAT_Scale,mat,0,0,0);
1156   return 0;
1157 }
1158 
1159 /*@
1160    MatNorm - Calculates various norms of a matrix.
1161 
1162    Input Parameters:
1163 .  mat - the matrix
1164 .  type - the type of norm, NORM_1, NORM_2, NORM_FROBENIUS, NORM_INFINITY
1165 
1166    Output Parameters:
1167 .  norm - the resulting norm
1168 
1169 .keywords: matrix, norm, Frobenius
1170 @*/
1171 int MatNorm(Mat mat,NormType type,double *norm)
1172 {
1173   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1174   if (!norm) SETERRQ(1,"MatNorm:bad addess for value");
1175   if (!mat->assembled) SETERRQ(1,"MatNorm:Not for unassembled matrix");
1176   if (mat->ops.norm) return (*mat->ops.norm)(mat,type,norm);
1177   SETERRQ(PETSC_ERR_SUP,"MatNorm:Not for this matrix type");
1178 }
1179 
1180 /*@
1181    MatAssemblyBegin - Begins assembling the matrix.  This routine should
1182    be called after completing all calls to MatSetValues().
1183 
1184    Input Parameters:
1185 .  mat - the matrix
1186 .  type - type of assembly, either FLUSH_ASSEMBLY or FINAL_ASSEMBLY
1187 
1188    Notes:
1189    MatSetValues() generally caches the values.  The matrix is ready to
1190    use only after MatAssemblyBegin() and MatAssemblyEnd() have been called.
1191    Use FLUSH_ASSEMBLY when switching between ADD_VALUES and SetValues; use
1192    FINAL_ASSEMBLY for the final assembly before the matrix is used.
1193 
1194 .keywords: matrix, assembly, assemble, begin
1195 
1196 .seealso: MatAssemblyEnd(), MatSetValues()
1197 @*/
1198 int MatAssemblyBegin(Mat mat,MatAssemblyType type)
1199 {
1200   int ierr;
1201   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1202   PLogEventBegin(MAT_AssemblyBegin,mat,0,0,0);
1203   if (mat->ops.assemblybegin){ierr = (*mat->ops.assemblybegin)(mat,type);CHKERRQ(ierr);}
1204   PLogEventEnd(MAT_AssemblyBegin,mat,0,0,0);
1205   return 0;
1206 }
1207 
1208 /*@
1209    MatAssemblyEnd - Completes assembling the matrix.  This routine should
1210    be called after all calls to MatSetValues() and after MatAssemblyBegin().
1211 
1212    Input Parameters:
1213 .  mat - the matrix
1214 .  type - type of assembly, either FLUSH_ASSEMBLY or FINAL_ASSEMBLY
1215 
1216    Options Database Keys:
1217 $  -mat_view_draw : Draw nonzero structure of matrix at conclusion of MatEndAssembly(),
1218                using MatView() and DrawOpenX().
1219 $  -mat_view_info : Prints info on matrix.
1220 $  -mat_view_info_detailed: More detailed information.
1221 $  -mat_view : Prints matrix out in ascii.
1222 $  -mat_view_matlab : Prints matrix out suitable for Matlab(TM).
1223 $  -display <name> : Set display name (default is host)
1224 $  -draw_pause <sec> : Set number of seconds to pause after display
1225 
1226    Note:
1227    MatSetValues() generally caches the values.  The matrix is ready to
1228    use only after MatAssemblyBegin() and MatAssemblyEnd() have been called.
1229    Use FLUSH_ASSEMBLY when switching between ADD_VALUES and SetValues; use
1230    FINAL_ASSEMBLY for the final assembly before the matrix is used.
1231 
1232 .keywords: matrix, assembly, assemble, end
1233 
1234 .seealso: MatAssemblyBegin(), MatSetValues()
1235 @*/
1236 int MatAssemblyEnd(Mat mat,MatAssemblyType type)
1237 {
1238   int        ierr,flg;
1239   static int inassm = 0;
1240 
1241   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1242   inassm++;
1243   PLogEventBegin(MAT_AssemblyEnd,mat,0,0,0);
1244   if (mat->ops.assemblyend) {ierr = (*mat->ops.assemblyend)(mat,type); CHKERRQ(ierr);}
1245   mat->assembled = PETSC_TRUE; mat->num_ass++;
1246   PLogEventEnd(MAT_AssemblyEnd,mat,0,0,0);
1247 
1248   if (inassm == 1) {
1249     ierr = OptionsHasName(PETSC_NULL,"-mat_view_info",&flg); CHKERRQ(ierr);
1250     if (flg) {
1251       Viewer viewer;
1252       ierr = ViewerFileOpenASCII(mat->comm,"stdout",&viewer);CHKERRQ(ierr);
1253       ierr = ViewerSetFormat(viewer,ASCII_FORMAT_INFO,0);CHKERRQ(ierr);
1254       ierr = MatView(mat,viewer); CHKERRQ(ierr);
1255       ierr = ViewerDestroy(viewer); CHKERRQ(ierr);
1256     }
1257     ierr = OptionsHasName(PETSC_NULL,"-mat_view_info_detailed",&flg);CHKERRQ(ierr);
1258     if (flg) {
1259       Viewer viewer;
1260       ierr = ViewerFileOpenASCII(mat->comm,"stdout",&viewer);CHKERRQ(ierr);
1261       ierr = ViewerSetFormat(viewer,ASCII_FORMAT_INFO_DETAILED,0);CHKERRQ(ierr);
1262       ierr = MatView(mat,viewer); CHKERRQ(ierr);
1263       ierr = ViewerDestroy(viewer); CHKERRQ(ierr);
1264     }
1265     ierr = OptionsHasName(PETSC_NULL,"-mat_view",&flg); CHKERRQ(ierr);
1266     if (flg) {
1267       Viewer viewer;
1268       ierr = ViewerFileOpenASCII(mat->comm,"stdout",&viewer);CHKERRQ(ierr);
1269       ierr = MatView(mat,viewer); CHKERRQ(ierr);
1270       ierr = ViewerDestroy(viewer); CHKERRQ(ierr);
1271     }
1272     ierr = OptionsHasName(PETSC_NULL,"-mat_view_matlab",&flg); CHKERRQ(ierr);
1273     if (flg) {
1274       Viewer viewer;
1275       ierr = ViewerFileOpenASCII(mat->comm,"stdout",&viewer);CHKERRQ(ierr);
1276       ierr = ViewerSetFormat(viewer,ASCII_FORMAT_MATLAB,"M");CHKERRQ(ierr);
1277       ierr = MatView(mat,viewer); CHKERRQ(ierr);
1278       ierr = ViewerDestroy(viewer); CHKERRQ(ierr);
1279     }
1280     ierr = OptionsHasName(PETSC_NULL,"-mat_view_draw",&flg); CHKERRQ(ierr);
1281     if (flg) {
1282       Viewer    viewer;
1283       ierr = ViewerDrawOpenX(mat->comm,0,0,0,0,300,300,&viewer); CHKERRQ(ierr);
1284       ierr = MatView(mat,viewer); CHKERRQ(ierr);
1285       ierr = ViewerFlush(viewer); CHKERRQ(ierr);
1286       ierr = ViewerDestroy(viewer); CHKERRQ(ierr);
1287     }
1288   }
1289   inassm--;
1290   return 0;
1291 }
1292 
1293 /*@
1294    MatCompress - Tries to store the matrix in as little space as
1295    possible.  May fail if memory is already fully used, since it
1296    tries to allocate new space.
1297 
1298    Input Parameters:
1299 .  mat - the matrix
1300 
1301 .keywords: matrix, compress
1302 @*/
1303 int MatCompress(Mat mat)
1304 {
1305   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1306   if (mat->ops.compress) return (*mat->ops.compress)(mat);
1307   return 0;
1308 }
1309 /*@
1310    MatSetOption - Sets a parameter option for a matrix. Some options
1311    may be specific to certain storage formats.  Some options
1312    determine how values will be inserted (or added). Sorted,
1313    row-oriented input will generally assemble the fastest. The default
1314    is row-oriented, nonsorted input.
1315 
1316    Input Parameters:
1317 .  mat - the matrix
1318 .  option - the option, one of the following:
1319 $    ROW_ORIENTED
1320 $    COLUMN_ORIENTED,
1321 $    ROWS_SORTED,
1322 $    COLUMNS_SORTED,
1323 $    NO_NEW_NONZERO_LOCATIONS,
1324 $    YES_NEW_NONZERO_LOCATIONS,
1325 $    SYMMETRIC_MATRIX,
1326 $    STRUCTURALLY_SYMMETRIC_MATRIX,
1327 $    NO_NEW_DIAGONALS,
1328 $    YES_NEW_DIAGONALS,
1329 $    and possibly others.
1330 
1331    Notes:
1332    Some options are relevant only for particular matrix types and
1333    are thus ignored by others.  Other options are not supported by
1334    certain matrix types and will generate an error message if set.
1335 
1336    If using a Fortran 77 module to compute a matrix, one may need to
1337    use the column-oriented option (or convert to the row-oriented
1338    format).
1339 
1340    NO_NEW_NONZERO_LOCATIONS indicates that any add or insertion
1341    that will generate a new entry in the nonzero structure is ignored.
1342    What this means is if memory is not allocated for this particular
1343    lot, then the insertion is ignored. For dense matrices, where
1344    the entire array is allocated, no entries are ever ignored.
1345 
1346 .keywords: matrix, option, row-oriented, column-oriented, sorted, nonzero
1347 @*/
1348 int MatSetOption(Mat mat,MatOption op)
1349 {
1350   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1351   if (mat->ops.setoption) return (*mat->ops.setoption)(mat,op);
1352   return 0;
1353 }
1354 
1355 /*@
1356    MatZeroEntries - Zeros all entries of a matrix.  For sparse matrices
1357    this routine retains the old nonzero structure.
1358 
1359    Input Parameters:
1360 .  mat - the matrix
1361 
1362 .keywords: matrix, zero, entries
1363 
1364 .seealso: MatZeroRows()
1365 @*/
1366 int MatZeroEntries(Mat mat)
1367 {
1368   int ierr;
1369   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1370   if (!mat->ops.zeroentries) SETERRQ(PETSC_ERR_SUP,"MatZeroEntries");
1371 
1372   PLogEventBegin(MAT_ZeroEntries,mat,0,0,0);
1373   ierr = (*mat->ops.zeroentries)(mat); CHKERRQ(ierr);
1374   PLogEventEnd(MAT_ZeroEntries,mat,0,0,0);
1375   return 0;
1376 }
1377 
1378 /*@
1379    MatZeroRows - Zeros all entries (except possibly the main diagonal)
1380    of a set of rows of a matrix.
1381 
1382    Input Parameters:
1383 .  mat - the matrix
1384 .  is - index set of rows to remove
1385 .  diag - pointer to value put in all diagonals of eliminated rows.
1386           Note that diag is not a pointer to an array, but merely a
1387           pointer to a single value.
1388 
1389    Notes:
1390    For the AIJ matrix formats this removes the old nonzero structure,
1391    but does not release memory.  For the dense and block diagonal
1392    formats this does not alter the nonzero structure.
1393 
1394    The user can set a value in the diagonal entry (or for the AIJ and
1395    row formats can optionally remove the main diagonal entry from the
1396    nonzero structure as well, by passing a null pointer as the final
1397    argument).
1398 
1399 .keywords: matrix, zero, rows, boundary conditions
1400 
1401 .seealso: MatZeroEntries(), MatGetSubMatrix(), MatGetSubMatrixInPlace()
1402 @*/
1403 int MatZeroRows(Mat mat,IS is, Scalar *diag)
1404 {
1405   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1406   if (!mat->assembled) SETERRQ(1,"MatZeroRows:Not for unassembled matrix");
1407   if (mat->ops.zerorows) return (*mat->ops.zerorows)(mat,is,diag);
1408   SETERRQ(PETSC_ERR_SUP,"MatZeroRows");
1409 }
1410 
1411 /*@
1412    MatGetSize - Returns the numbers of rows and columns in a matrix.
1413 
1414    Input Parameter:
1415 .  mat - the matrix
1416 
1417    Output Parameters:
1418 .  m - the number of global rows
1419 .  n - the number of global columns
1420 
1421 .keywords: matrix, dimension, size, rows, columns, global, get
1422 
1423 .seealso: MatGetLocalSize()
1424 @*/
1425 int MatGetSize(Mat mat,int *m,int* n)
1426 {
1427   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1428   if (!m || !n) SETERRQ(1,"MatGetSize:Bad address for result");
1429   return (*mat->ops.getsize)(mat,m,n);
1430 }
1431 
1432 /*@
1433    MatGetLocalSize - Returns the number of rows and columns in a matrix
1434    stored locally.  This information may be implementation dependent, so
1435    use with care.
1436 
1437    Input Parameters:
1438 .  mat - the matrix
1439 
1440    Output Parameters:
1441 .  m - the number of local rows
1442 .  n - the number of local columns
1443 
1444 .keywords: matrix, dimension, size, local, rows, columns, get
1445 
1446 .seealso: MatGetSize()
1447 @*/
1448 int MatGetLocalSize(Mat mat,int *m,int* n)
1449 {
1450   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1451   if (!m || !n) SETERRQ(1,"MatGetLocalSize:Bad address for result");
1452   return (*mat->ops.getlocalsize)(mat,m,n);
1453 }
1454 
1455 /*@
1456    MatGetOwnershipRange - Returns the range of matrix rows owned by
1457    this processor, assuming that the matrix is laid out with the first
1458    n1 rows on the first processor, the next n2 rows on the second, etc.
1459    For certain parallel layouts this range may not be well-defined.
1460 
1461    Input Parameters:
1462 .  mat - the matrix
1463 
1464    Output Parameters:
1465 .  m - the first local row
1466 .  n - one more then the last local row
1467 
1468 .keywords: matrix, get, range, ownership
1469 @*/
1470 int MatGetOwnershipRange(Mat mat,int *m,int* n)
1471 {
1472   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1473   if (!m || !n) SETERRQ(1,"MatGetOwnershipRange:Bad address for result");
1474   if (mat->ops.getownershiprange) return (*mat->ops.getownershiprange)(mat,m,n);
1475   SETERRQ(PETSC_ERR_SUP,"MatGetOwnershipRange");
1476 }
1477 
1478 /*@
1479    MatILUFactorSymbolic - Performs symbolic ILU factorization of a matrix.
1480    Uses levels of fill only, not drop tolerance. Use MatLUFactorNumeric()
1481    to complete the factorization.
1482 
1483    Input Parameters:
1484 .  mat - the matrix
1485 .  row - row permutation
1486 .  column - column permutation
1487 .  fill - number of levels of fill
1488 .  f - expected fill as ratio of the original number of nonzeros,
1489        for example 3.0; choosing this parameter well can result in
1490        more efficient use of time and space.
1491 
1492    Output Parameters:
1493 .  fact - new matrix that has been symbolically factored
1494 
1495    Options Database Key:
1496 $   -mat_ilu_fill <f>, where f is the fill ratio
1497 
1498    Notes:
1499    See the file $(PETSC_DIR)/Performace for additional information about
1500    choosing the fill factor for better efficiency.
1501 
1502 .keywords: matrix, factor, incomplete, ILU, symbolic, fill
1503 
1504 .seealso: MatLUFactorSymbolic(), MatLUFactorNumeric()
1505 @*/
1506 int MatILUFactorSymbolic(Mat mat,IS row,IS col,double f,int fill,Mat *fact)
1507 {
1508   int ierr,flg;
1509 
1510   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1511   if (fill < 0) SETERRQ(1,"MatILUFactorSymbolic:Levels of fill negative");
1512   if (!fact) SETERRQ(1,"MatILUFactorSymbolic:Fact argument is missing");
1513   if (!mat->ops.ilufactorsymbolic) SETERRQ(PETSC_ERR_SUP,"MatILUFactorSymbolic");
1514   if (!mat->assembled) SETERRQ(1,"MatILUFactorSymbolic:Not for unassembled matrix");
1515 
1516   ierr = OptionsGetDouble(PETSC_NULL,"-mat_ilu_fill",&f,&flg); CHKERRQ(ierr);
1517   PLogEventBegin(MAT_ILUFactorSymbolic,mat,row,col,0);
1518   ierr = (*mat->ops.ilufactorsymbolic)(mat,row,col,f,fill,fact); CHKERRQ(ierr);
1519   PLogEventEnd(MAT_ILUFactorSymbolic,mat,row,col,0);
1520   return 0;
1521 }
1522 
1523 /*@
1524    MatIncompleteCholeskyFactorSymbolic - Performs symbolic incomplete
1525    Cholesky factorization for a symmetric matrix.  Use
1526    MatCholeskyFactorNumeric() to complete the factorization.
1527 
1528    Input Parameters:
1529 .  mat - the matrix
1530 .  perm - row and column permutation
1531 .  fill - levels of fill
1532 .  f - expected fill as ratio of original fill
1533 
1534    Output Parameter:
1535 .  fact - the factored matrix
1536 
1537    Note:  Currently only no-fill factorization is supported.
1538 
1539 .keywords: matrix, factor, incomplete, ICC, Cholesky, symbolic, fill
1540 
1541 .seealso: MatCholeskyFactorNumeric(), MatCholeskyFactor()
1542 @*/
1543 int MatIncompleteCholeskyFactorSymbolic(Mat mat,IS perm,double f,int fill,
1544                                         Mat *fact)
1545 {
1546   int ierr;
1547   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1548   if (fill < 0) SETERRQ(1,"MatIncompleteCholeskyFactorSymbolic:Fill negative");
1549   if (!fact) SETERRQ(1,"MatIncompleteCholeskyFactorSymbolic:Missing fact argument");
1550   if (!mat->ops.incompletecholeskyfactorsymbolic)
1551      SETERRQ(PETSC_ERR_SUP,"MatIncompleteCholeskyFactorSymbolic");
1552   if (!mat->assembled)
1553      SETERRQ(1,"MatIncompleteCholeskyFactorSymbolic:Not for unassembled matrix");
1554 
1555   PLogEventBegin(MAT_IncompleteCholeskyFactorSymbolic,mat,perm,0,0);
1556   ierr = (*mat->ops.incompletecholeskyfactorsymbolic)(mat,perm,f,fill,fact);CHKERRQ(ierr);
1557   PLogEventEnd(MAT_IncompleteCholeskyFactorSymbolic,mat,perm,0,0);
1558   return 0;
1559 }
1560 
1561 /*@C
1562    MatGetArray - Returns a pointer to the element values in the matrix.
1563    This routine  is implementation dependent, and may not even work for
1564    certain matrix types. You MUST call MatRestoreArray() when you no
1565    longer need to access the array.
1566 
1567    Input Parameter:
1568 .  mat - the matrix
1569 
1570    Output Parameter:
1571 .  v - the location of the values
1572 
1573    Fortran Note:
1574    The Fortran interface is slightly different from that given below.
1575    See the users manual and petsc/src/mat/examples for details.
1576 
1577 .keywords: matrix, array, elements, values
1578 
1579 .seeaols: MatRestoreArray()
1580 @*/
1581 int MatGetArray(Mat mat,Scalar **v)
1582 {
1583   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1584   if (!v) SETERRQ(1,"MatGetArray:Bad input, array pointer location");
1585   if (!mat->ops.getarray) SETERRQ(PETSC_ERR_SUP,"MatGetArray");
1586   return (*mat->ops.getarray)(mat,v);
1587 }
1588 
1589 /*@C
1590    MatRestoreArray - Restores the matrix after MatGetArray has been called.
1591 
1592    Input Parameter:
1593 .  mat - the matrix
1594 .  v - the location of the values
1595 
1596    Fortran Note:
1597    The Fortran interface is slightly different from that given below.
1598    See the users manual and petsc/src/mat/examples for details.
1599 
1600 .keywords: matrix, array, elements, values, resrore
1601 
1602 .seealso: MatGetArray()
1603 @*/
1604 int MatRestoreArray(Mat mat,Scalar **v)
1605 {
1606   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1607   if (!v) SETERRQ(1,"MatRestoreArray:Bad input, array pointer location");
1608   if (!mat->ops.restorearray) SETERRQ(PETSC_ERR_SUP,"MatResroreArray");
1609   return (*mat->ops.restorearray)(mat,v);
1610 }
1611 
1612 /*@C
1613    MatGetSubMatrix - Extracts a submatrix from a matrix. If submat points
1614                      to a valid matrix, it may be reused.
1615 
1616    Input Parameters:
1617 .  mat - the matrix
1618 .  irow, icol - index sets of rows and columns to extract
1619 .  scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
1620 
1621    Output Parameter:
1622 .  submat - the submatrix
1623 
1624    Notes:
1625    MatGetSubMatrix() can be useful in setting boundary conditions.
1626 
1627    Use MatGetSubMatrices() to extract multiple submatrices.
1628 
1629 .keywords: matrix, get, submatrix, boundary conditions
1630 
1631 .seealso: MatZeroRows(), MatGetSubMatrixInPlace(), MatGetSubMatrices()
1632 @*/
1633 int MatGetSubMatrix(Mat mat,IS irow,IS icol,MatGetSubMatrixCall scall,Mat *submat)
1634 {
1635   int ierr;
1636   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1637   if (scall == MAT_REUSE_MATRIX) {
1638     PetscValidHeaderSpecific(*submat,MAT_COOKIE);
1639   }
1640   if (!mat->ops.getsubmatrix) SETERRQ(PETSC_ERR_SUP,"MatGetSubMatrix");
1641   if (!mat->assembled) SETERRQ(1,"MatGetSubMatrix:Not for unassembled matrix");
1642 
1643   /* PLogEventBegin(MAT_GetSubMatrix,mat,irow,icol,0); */
1644   ierr = (*mat->ops.getsubmatrix)(mat,irow,icol,scall,submat); CHKERRQ(ierr);
1645   /* PLogEventEnd(MAT_GetSubMatrix,mat,irow,icol,0); */
1646   return 0;
1647 }
1648 
1649 /*@C
1650    MatGetSubMatrices - Extracts several submatrices from a matrix. If submat
1651    points to an array of valid matrices, it may be reused.
1652 
1653    Input Parameters:
1654 .  mat - the matrix
1655 .  irow, icol - index sets of rows and columns to extract
1656 
1657    Output Parameter:
1658 .  submat - the submatrices
1659 
1660    Note:
1661    Use MatGetSubMatrix() for extracting a sinble submatrix.
1662 
1663 .keywords: matrix, get, submatrix, submatrices
1664 
1665 .seealso: MatGetSubMatrix()
1666 @*/
1667 int MatGetSubMatrices(Mat mat,int n, IS *irow,IS *icol,MatGetSubMatrixCall scall,
1668                       Mat **submat)
1669 {
1670   int ierr;
1671   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1672   if (!mat->ops.getsubmatrices) SETERRQ(PETSC_ERR_SUP,"MatGetSubMatrices");
1673   if (!mat->assembled) SETERRQ(1,"MatGetSubMatrices:Not for unassembled matrix");
1674 
1675   PLogEventBegin(MAT_GetSubMatrices,mat,0,0,0);
1676   ierr = (*mat->ops.getsubmatrices)(mat,n,irow,icol,scall,submat); CHKERRQ(ierr);
1677   PLogEventEnd(MAT_GetSubMatrices,mat,0,0,0);
1678   return 0;
1679 }
1680 
1681 /*@
1682    MatGetSubMatrixInPlace - Extracts a submatrix from a matrix, returning
1683    the submatrix in place of the original matrix.
1684 
1685    Input Parameters:
1686 .  mat - the matrix
1687 .  irow, icol - index sets of rows and columns to extract
1688 
1689 .keywords: matrix, get, submatrix, boundary conditions, in-place
1690 
1691 .seealso: MatZeroRows(), MatGetSubMatrix()
1692 @*/
1693 int MatGetSubMatrixInPlace(Mat mat,IS irow,IS icol)
1694 {
1695   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1696   if (!mat->assembled) SETERRQ(1,"MatGetSubMatrixInPlace:Not for unassembled matrix");
1697 
1698   if (!mat->ops.getsubmatrixinplace) SETERRQ(PETSC_ERR_SUP,"MatGetSubmatrixInPlace");
1699   return (*mat->ops.getsubmatrixinplace)(mat,irow,icol);
1700 }
1701 
1702 /*@
1703    MatIncreaseOverlap - Given a set of submatrices indicated by index sets,
1704    replaces the index by larger ones that represent submatrices with more
1705    overlap.
1706 
1707    Input Parameters:
1708 .  mat - the matrix
1709 .  n   - the number of index sets
1710 .  is  - the array of pointers to index sets
1711 .  ov  - the additional overlap requested
1712 
1713 .keywords: matrix, overlap, Schwarz
1714 
1715 .seealso: MatGetSubMatrices()
1716 @*/
1717 int MatIncreaseOverlap(Mat mat,int n, IS *is, int ov)
1718 {
1719   int ierr;
1720   PetscValidHeaderSpecific(mat,MAT_COOKIE);
1721   if (!mat->assembled) SETERRQ(1,"MatIncreaseOverlap:Not for unassembled matrix");
1722 
1723   if (ov == 0) return 0;
1724   if (!mat->ops.increaseoverlap) SETERRQ(PETSC_ERR_SUP,"MatIncreaseOverlap");
1725   PLogEventBegin(MAT_IncreaseOverlap,mat,0,0,0);
1726   ierr = (*mat->ops.increaseoverlap)(mat,n,is,ov); CHKERRQ(ierr);
1727   PLogEventEnd(MAT_IncreaseOverlap,mat,0,0,0);
1728   return 0;
1729 }
1730 
1731 /*@
1732    MatPrintHelp - Prints all the options for the matrix.
1733 
1734    Input Parameter:
1735 .  mat - the matrix
1736 
1737    Options Database Keys:
1738 $  -help, -h
1739 
1740 .keywords: mat, help
1741 
1742 .seealso: MatCreate(), MatCreateXXX()
1743 @*/
1744 int MatPrintHelp(Mat mat)
1745 {
1746   static int called = 0;
1747   MPI_Comm   comm = mat->comm;
1748 
1749   if (!called) {
1750     PetscPrintf(comm,"General matrix options:\n");
1751     PetscPrintf(comm,"  -mat_view_info : view basic matrix info during MatAssemblyEnd()\n");
1752     PetscPrintf(comm,"  -mat_view_info_detailed : view detailed matrix info during MatAssemblyEnd()\n");
1753     PetscPrintf(comm,"  -mat_view_draw : draw nonzero matrix structure during MatAssemblyEnd()\n");
1754     PetscPrintf(comm,"      -draw_pause <sec> : set seconds of display pause\n");
1755     PetscPrintf(comm,"      -display <name> : set alternate display\n");
1756     called = 1;
1757   }
1758   if (mat->ops.printhelp) (*mat->ops.printhelp)(mat);
1759   return 0;
1760 }
1761 
1762