xref: /petsc/src/mat/matfd/fdmatrix.c (revision 85740eac76d20a0cac9a36a21d5752ff4c70535a)
1 
2 /*
3    This is where the abstract matrix operations are defined that are
4   used for finite difference computations of Jacobians using coloring.
5 */
6 
7 #include <petsc-private/matimpl.h>        /*I "petscmat.h" I*/
8 
9 #undef __FUNCT__
10 #define __FUNCT__ "MatFDColoringSetF"
11 PetscErrorCode  MatFDColoringSetF(MatFDColoring fd,Vec F)
12 {
13   PetscErrorCode ierr;
14 
15   PetscFunctionBegin;
16   if (F) {
17     ierr     = VecCopy(F,fd->w1);CHKERRQ(ierr);
18     fd->fset = PETSC_TRUE;
19   } else {
20     fd->fset = PETSC_FALSE;
21   }
22   PetscFunctionReturn(0);
23 }
24 
25 #include <petscdraw.h>
26 #undef __FUNCT__
27 #define __FUNCT__ "MatFDColoringView_Draw_Zoom"
28 static PetscErrorCode MatFDColoringView_Draw_Zoom(PetscDraw draw,void *Aa)
29 {
30   MatFDColoring  fd = (MatFDColoring)Aa;
31   PetscErrorCode ierr;
32   PetscInt       i,j;
33   PetscReal      x,y;
34 
35   PetscFunctionBegin;
36   /* loop over colors  */
37   for (i=0; i<fd->ncolors; i++) {
38     for (j=0; j<fd->nrows[i]; j++) {
39       y    = fd->M - fd->rows[i][j] - fd->rstart;
40       x    = fd->columnsforrow[i][j];
41       ierr = PetscDrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr);
42     }
43   }
44   PetscFunctionReturn(0);
45 }
46 
47 #undef __FUNCT__
48 #define __FUNCT__ "MatFDColoringView_Draw"
49 static PetscErrorCode MatFDColoringView_Draw(MatFDColoring fd,PetscViewer viewer)
50 {
51   PetscErrorCode ierr;
52   PetscBool      isnull;
53   PetscDraw      draw;
54   PetscReal      xr,yr,xl,yl,h,w;
55 
56   PetscFunctionBegin;
57   ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
58   ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
59 
60   ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr);
61 
62   xr   = fd->N; yr  = fd->M; h = yr/10.0; w = xr/10.0;
63   xr  += w;     yr += h;    xl = -w;     yl = -h;
64   ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr);
65   ierr = PetscDrawZoom(draw,MatFDColoringView_Draw_Zoom,fd);CHKERRQ(ierr);
66   ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",NULL);CHKERRQ(ierr);
67   PetscFunctionReturn(0);
68 }
69 
70 #undef __FUNCT__
71 #define __FUNCT__ "MatFDColoringView"
72 /*@C
73    MatFDColoringView - Views a finite difference coloring context.
74 
75    Collective on MatFDColoring
76 
77    Input  Parameters:
78 +  c - the coloring context
79 -  viewer - visualization context
80 
81    Level: intermediate
82 
83    Notes:
84    The available visualization contexts include
85 +     PETSC_VIEWER_STDOUT_SELF - standard output (default)
86 .     PETSC_VIEWER_STDOUT_WORLD - synchronized standard
87         output where only the first processor opens
88         the file.  All other processors send their
89         data to the first processor to print.
90 -     PETSC_VIEWER_DRAW_WORLD - graphical display of nonzero structure
91 
92    Notes:
93      Since PETSc uses only a small number of basic colors (currently 33), if the coloring
94    involves more than 33 then some seemingly identical colors are displayed making it look
95    like an illegal coloring. This is just a graphical artifact.
96 
97 .seealso: MatFDColoringCreate()
98 
99 .keywords: Mat, finite differences, coloring, view
100 @*/
101 PetscErrorCode  MatFDColoringView(MatFDColoring c,PetscViewer viewer)
102 {
103   PetscErrorCode    ierr;
104   PetscInt          i,j;
105   PetscBool         isdraw,iascii;
106   PetscViewerFormat format;
107 
108   PetscFunctionBegin;
109   PetscValidHeaderSpecific(c,MAT_FDCOLORING_CLASSID,1);
110   if (!viewer) {
111     ierr = PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)c),&viewer);CHKERRQ(ierr);
112   }
113   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2);
114   PetscCheckSameComm(c,1,viewer,2);
115 
116   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
117   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
118   if (isdraw) {
119     ierr = MatFDColoringView_Draw(c,viewer);CHKERRQ(ierr);
120   } else if (iascii) {
121     ierr = PetscObjectPrintClassNamePrefixType((PetscObject)c,viewer);CHKERRQ(ierr);
122     ierr = PetscViewerASCIIPrintf(viewer,"  Error tolerance=%G\n",c->error_rel);CHKERRQ(ierr);
123     ierr = PetscViewerASCIIPrintf(viewer,"  Umin=%G\n",c->umin);CHKERRQ(ierr);
124     ierr = PetscViewerASCIIPrintf(viewer,"  Number of colors=%D\n",c->ncolors);CHKERRQ(ierr);
125 
126     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
127     if (format != PETSC_VIEWER_ASCII_INFO) {
128       for (i=0; i<c->ncolors; i++) {
129         ierr = PetscViewerASCIIPrintf(viewer,"  Information for color %D\n",i);CHKERRQ(ierr);
130         ierr = PetscViewerASCIIPrintf(viewer,"    Number of columns %D\n",c->ncolumns[i]);CHKERRQ(ierr);
131         for (j=0; j<c->ncolumns[i]; j++) {
132           ierr = PetscViewerASCIIPrintf(viewer,"      %D\n",c->columns[i][j]);CHKERRQ(ierr);
133         }
134         ierr = PetscViewerASCIIPrintf(viewer,"    Number of rows %D\n",c->nrows[i]);CHKERRQ(ierr);
135         for (j=0; j<c->nrows[i]; j++) {
136           ierr = PetscViewerASCIIPrintf(viewer,"      %D %D \n",c->rows[i][j],c->columnsforrow[i][j]);CHKERRQ(ierr);
137         }
138       }
139     }
140     ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
141   }
142   PetscFunctionReturn(0);
143 }
144 
145 #undef __FUNCT__
146 #define __FUNCT__ "MatFDColoringSetParameters"
147 /*@
148    MatFDColoringSetParameters - Sets the parameters for the sparse approximation of
149    a Jacobian matrix using finite differences.
150 
151    Logically Collective on MatFDColoring
152 
153    The Jacobian is estimated with the differencing approximation
154 .vb
155        F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
156        h = error_rel*u[i]                 if  abs(u[i]) > umin
157          = +/- error_rel*umin             otherwise, with +/- determined by the sign of u[i]
158        dx_{i} = (0, ... 1, .... 0)
159 .ve
160 
161    Input Parameters:
162 +  coloring - the coloring context
163 .  error_rel - relative error
164 -  umin - minimum allowable u-value magnitude
165 
166    Level: advanced
167 
168 .keywords: Mat, finite differences, coloring, set, parameters
169 
170 .seealso: MatFDColoringCreate(), MatFDColoringSetFromOptions()
171 
172 @*/
173 PetscErrorCode  MatFDColoringSetParameters(MatFDColoring matfd,PetscReal error,PetscReal umin)
174 {
175   PetscFunctionBegin;
176   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
177   PetscValidLogicalCollectiveReal(matfd,error,2);
178   PetscValidLogicalCollectiveReal(matfd,umin,3);
179   if (error != PETSC_DEFAULT) matfd->error_rel = error;
180   if (umin != PETSC_DEFAULT)  matfd->umin      = umin;
181   PetscFunctionReturn(0);
182 }
183 
184 
185 
186 #undef __FUNCT__
187 #define __FUNCT__ "MatFDColoringGetFunction"
188 /*@C
189    MatFDColoringGetFunction - Gets the function to use for computing the Jacobian.
190 
191    Not Collective
192 
193    Input Parameters:
194 .  coloring - the coloring context
195 
196    Output Parameters:
197 +  f - the function
198 -  fctx - the optional user-defined function context
199 
200    Level: intermediate
201 
202 .keywords: Mat, Jacobian, finite differences, set, function
203 
204 .seealso: MatFDColoringCreate(), MatFDColoringSetFunction(), MatFDColoringSetFromOptions()
205 
206 @*/
207 PetscErrorCode  MatFDColoringGetFunction(MatFDColoring matfd,PetscErrorCode (**f)(void),void **fctx)
208 {
209   PetscFunctionBegin;
210   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
211   if (f) *f = matfd->f;
212   if (fctx) *fctx = matfd->fctx;
213   PetscFunctionReturn(0);
214 }
215 
216 #undef __FUNCT__
217 #define __FUNCT__ "MatFDColoringSetFunction"
218 /*@C
219    MatFDColoringSetFunction - Sets the function to use for computing the Jacobian.
220 
221    Logically Collective on MatFDColoring
222 
223    Input Parameters:
224 +  coloring - the coloring context
225 .  f - the function
226 -  fctx - the optional user-defined function context
227 
228    Calling sequence of (*f) function:
229     For SNES:    PetscErrorCode (*f)(SNES,Vec,Vec,void*)
230     If not using SNES: PetscErrorCode (*f)(void *dummy,Vec,Vec,void*) and dummy is ignored
231 
232    Level: advanced
233 
234    Notes: This function is usually used automatically by SNES (when one uses SNESSetJacobian() with the argument
235      SNESComputeJacobianDefaultColor()) and only needs to be used by someone computing a matrix via coloring directly by
236      calling MatFDColoringApply()
237 
238    Fortran Notes:
239     In Fortran you must call MatFDColoringSetFunction() for a coloring object to
240   be used without SNES or within the SNES solvers.
241 
242 .keywords: Mat, Jacobian, finite differences, set, function
243 
244 .seealso: MatFDColoringCreate(), MatFDColoringGetFunction(), MatFDColoringSetFromOptions()
245 
246 @*/
247 PetscErrorCode  MatFDColoringSetFunction(MatFDColoring matfd,PetscErrorCode (*f)(void),void *fctx)
248 {
249   PetscFunctionBegin;
250   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
251   matfd->f    = f;
252   matfd->fctx = fctx;
253   PetscFunctionReturn(0);
254 }
255 
256 #undef __FUNCT__
257 #define __FUNCT__ "MatFDColoringSetFromOptions"
258 /*@
259    MatFDColoringSetFromOptions - Sets coloring finite difference parameters from
260    the options database.
261 
262    Collective on MatFDColoring
263 
264    The Jacobian, F'(u), is estimated with the differencing approximation
265 .vb
266        F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
267        h = error_rel*u[i]                 if  abs(u[i]) > umin
268          = +/- error_rel*umin             otherwise, with +/- determined by the sign of u[i]
269        dx_{i} = (0, ... 1, .... 0)
270 .ve
271 
272    Input Parameter:
273 .  coloring - the coloring context
274 
275    Options Database Keys:
276 +  -mat_fd_coloring_err <err> - Sets <err> (square root
277            of relative error in the function)
278 .  -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude
279 .  -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS)
280 .  -mat_fd_coloring_view - Activates basic viewing
281 .  -mat_fd_coloring_view ::ascii_info - Activates viewing info
282 -  -mat_fd_coloring_view draw - Activates drawing
283 
284     Level: intermediate
285 
286 .keywords: Mat, finite differences, parameters
287 
288 .seealso: MatFDColoringCreate(), MatFDColoringView(), MatFDColoringSetParameters()
289 
290 @*/
291 PetscErrorCode  MatFDColoringSetFromOptions(MatFDColoring matfd)
292 {
293   PetscErrorCode ierr;
294   PetscBool      flg;
295   char           value[3];
296 
297   PetscFunctionBegin;
298   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
299 
300   ierr = PetscObjectOptionsBegin((PetscObject)matfd);CHKERRQ(ierr);
301   ierr = PetscOptionsReal("-mat_fd_coloring_err","Square root of relative error in function","MatFDColoringSetParameters",matfd->error_rel,&matfd->error_rel,0);CHKERRQ(ierr);
302   ierr = PetscOptionsReal("-mat_fd_coloring_umin","Minimum allowable u magnitude","MatFDColoringSetParameters",matfd->umin,&matfd->umin,0);CHKERRQ(ierr);
303   ierr = PetscOptionsString("-mat_fd_type","Algorithm to compute h, wp or ds","MatFDColoringCreate",matfd->htype,value,3,&flg);CHKERRQ(ierr);
304   if (flg) {
305     if (value[0] == 'w' && value[1] == 'p') matfd->htype = "wp";
306     else if (value[0] == 'd' && value[1] == 's') matfd->htype = "ds";
307     else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Unknown finite differencing type %s",value);
308   }
309   /* process any options handlers added with PetscObjectAddOptionsHandler() */
310   ierr = PetscObjectProcessOptionsHandlers((PetscObject)matfd);CHKERRQ(ierr);
311   PetscOptionsEnd();CHKERRQ(ierr);
312   PetscFunctionReturn(0);
313 }
314 
315 #undef __FUNCT__
316 #define __FUNCT__ "MatFDColoringViewFromOptions"
317 PetscErrorCode MatFDColoringViewFromOptions(MatFDColoring fd,const char prefix[],const char optionname[])
318 {
319   PetscErrorCode    ierr;
320   PetscBool         flg;
321   PetscViewer       viewer;
322   PetscViewerFormat format;
323 
324   PetscFunctionBegin;
325   if (prefix) {
326     ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)fd),prefix,optionname,&viewer,&format,&flg);CHKERRQ(ierr);
327   } else {
328     ierr = PetscOptionsGetViewer(PetscObjectComm((PetscObject)fd),((PetscObject)fd)->prefix,optionname,&viewer,&format,&flg);CHKERRQ(ierr);
329   }
330   if (flg) {
331     ierr = PetscViewerPushFormat(viewer,format);CHKERRQ(ierr);
332     ierr = MatFDColoringView(fd,viewer);CHKERRQ(ierr);
333     ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr);
334     ierr = PetscViewerDestroy(&viewer);CHKERRQ(ierr);
335   }
336   PetscFunctionReturn(0);
337 }
338 
339 #undef __FUNCT__
340 #define __FUNCT__ "MatFDColoringCreate"
341 /*@
342    MatFDColoringCreate - Creates a matrix coloring context for finite difference
343    computation of Jacobians.
344 
345    Collective on Mat
346 
347    Input Parameters:
348 +  mat - the matrix containing the nonzero structure of the Jacobian
349 -  iscoloring - the coloring of the matrix; usually obtained with MatGetColoring() or DMCreateColoring()
350 
351     Output Parameter:
352 .   color - the new coloring context
353 
354     Level: intermediate
355 
356 .seealso: MatFDColoringDestroy(),SNESComputeJacobianDefaultColor(), ISColoringCreate(),
357           MatFDColoringSetFunction(), MatFDColoringSetFromOptions(), MatFDColoringApply(),
358           MatFDColoringView(), MatFDColoringSetParameters(), MatGetColoring(), DMCreateColoring()
359 @*/
360 PetscErrorCode  MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color)
361 {
362   MatFDColoring  c;
363   MPI_Comm       comm;
364   PetscErrorCode ierr;
365   PetscInt       M,N;
366 
367   PetscFunctionBegin;
368   if (!mat->assembled) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Matrix must be assembled by calls to MatAssemblyBegin/End();");
369   ierr = PetscLogEventBegin(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr);
370   ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr);
371   if (M != N) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"Only for square matrices");
372   ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
373   ierr = PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_CLASSID,"MatFDColoring","Jacobian computation via finite differences with coloring","Mat",comm,MatFDColoringDestroy,MatFDColoringView);CHKERRQ(ierr);
374 
375   c->ctype = iscoloring->ctype;
376 
377   if (mat->ops->fdcoloringcreate) {
378     ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr);
379   } else SETERRQ1(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"Code not yet written for matrix type %s",((PetscObject)mat)->type_name);
380 
381   ierr = MatGetVecs(mat,NULL,&c->w1);CHKERRQ(ierr);
382   ierr = PetscLogObjectParent((PetscObject)c,(PetscObject)c->w1);CHKERRQ(ierr);
383   ierr = VecDuplicate(c->w1,&c->w2);CHKERRQ(ierr);
384   ierr = PetscLogObjectParent((PetscObject)c,(PetscObject)c->w2);CHKERRQ(ierr);
385 
386   c->error_rel    = PETSC_SQRT_MACHINE_EPSILON;
387   c->umin         = 100.0*PETSC_SQRT_MACHINE_EPSILON;
388   c->currentcolor = -1;
389   c->htype        = "wp";
390   c->fset         = PETSC_FALSE;
391 
392   *color = c;
393   ierr   = PetscObjectCompose((PetscObject)mat,"SNESMatFDColoring",(PetscObject)c);CHKERRQ(ierr);
394   ierr   = PetscLogEventEnd(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr);
395   PetscFunctionReturn(0);
396 }
397 
398 #undef __FUNCT__
399 #define __FUNCT__ "MatFDColoringDestroy"
400 /*@
401     MatFDColoringDestroy - Destroys a matrix coloring context that was created
402     via MatFDColoringCreate().
403 
404     Collective on MatFDColoring
405 
406     Input Parameter:
407 .   c - coloring context
408 
409     Level: intermediate
410 
411 .seealso: MatFDColoringCreate()
412 @*/
413 PetscErrorCode  MatFDColoringDestroy(MatFDColoring *c)
414 {
415   PetscErrorCode ierr;
416   PetscInt       i;
417 
418   PetscFunctionBegin;
419   if (!*c) PetscFunctionReturn(0);
420   if (--((PetscObject)(*c))->refct > 0) {*c = 0; PetscFunctionReturn(0);}
421 
422   for (i=0; i<(*c)->ncolors; i++) {
423     ierr = PetscFree((*c)->columns[i]);CHKERRQ(ierr);
424     ierr = PetscFree((*c)->rows[i]);CHKERRQ(ierr);
425     ierr = PetscFree((*c)->columnsforrow[i]);CHKERRQ(ierr);
426     if ((*c)->vscaleforrow) {ierr = PetscFree((*c)->vscaleforrow[i]);CHKERRQ(ierr);}
427   }
428   ierr = PetscFree((*c)->ncolumns);CHKERRQ(ierr);
429   ierr = PetscFree((*c)->columns);CHKERRQ(ierr);
430   ierr = PetscFree((*c)->nrows);CHKERRQ(ierr);
431   ierr = PetscFree((*c)->rows);CHKERRQ(ierr);
432   ierr = PetscFree((*c)->columnsforrow);CHKERRQ(ierr);
433   ierr = PetscFree((*c)->vscaleforrow);CHKERRQ(ierr);
434   ierr = PetscFree((*c)->den2sp);CHKERRQ(ierr);
435   ierr = PetscFree2((*c)->colorforrow,(*c)->colorforcolumn);CHKERRQ(ierr);
436   ierr = PetscFree((*c)->rowcolden2sp3);CHKERRQ(ierr);
437   ierr = VecDestroy(&(*c)->vscale);CHKERRQ(ierr);
438   ierr = VecDestroy(&(*c)->w1);CHKERRQ(ierr);
439   ierr = VecDestroy(&(*c)->w2);CHKERRQ(ierr);
440   ierr = VecDestroy(&(*c)->w3);CHKERRQ(ierr);
441   ierr = PetscHeaderDestroy(c);CHKERRQ(ierr);
442   PetscFunctionReturn(0);
443 }
444 
445 #undef __FUNCT__
446 #define __FUNCT__ "MatFDColoringGetPerturbedColumns"
447 /*@C
448     MatFDColoringGetPerturbedColumns - Returns the indices of the columns that
449       that are currently being perturbed.
450 
451     Not Collective
452 
453     Input Parameters:
454 .   coloring - coloring context created with MatFDColoringCreate()
455 
456     Output Parameters:
457 +   n - the number of local columns being perturbed
458 -   cols - the column indices, in global numbering
459 
460    Level: intermediate
461 
462 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringApply()
463 
464 .keywords: coloring, Jacobian, finite differences
465 @*/
466 PetscErrorCode  MatFDColoringGetPerturbedColumns(MatFDColoring coloring,PetscInt *n,PetscInt *cols[])
467 {
468   PetscFunctionBegin;
469   if (coloring->currentcolor >= 0) {
470     *n    = coloring->ncolumns[coloring->currentcolor];
471     *cols = coloring->columns[coloring->currentcolor];
472   } else {
473     *n = 0;
474   }
475   PetscFunctionReturn(0);
476 }
477 
478 #undef __FUNCT__
479 #define __FUNCT__ "MatFDColoringApply"
480 /*@
481     MatFDColoringApply - Given a matrix for which a MatFDColoring context
482     has been created, computes the Jacobian for a function via finite differences.
483 
484     Collective on MatFDColoring
485 
486     Input Parameters:
487 +   mat - location to store Jacobian
488 .   coloring - coloring context created with MatFDColoringCreate()
489 .   x1 - location at which Jacobian is to be computed
490 -   sctx - context required by function, if this is being used with the SNES solver then it is SNES object, otherwise it is null
491 
492     Options Database Keys:
493 +    -mat_fd_type - "wp" or "ds"  (see MATMFFD_WP or MATMFFD_DS)
494 .    -mat_fd_coloring_view - Activates basic viewing or coloring
495 .    -mat_fd_coloring_view draw - Activates drawing of coloring
496 -    -mat_fd_coloring_view ::ascii_info - Activates viewing of coloring info
497 
498     Level: intermediate
499 
500 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringSetFunction()
501 
502 .keywords: coloring, Jacobian, finite differences
503 @*/
504 PetscErrorCode  MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx)
505 {
506   PetscErrorCode ierr;
507 
508   PetscFunctionBegin;
509   PetscValidHeaderSpecific(J,MAT_CLASSID,1);
510   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_CLASSID,2);
511   PetscValidHeaderSpecific(x1,VEC_CLASSID,3);
512   if (!coloring->f) SETERRQ(PetscObjectComm((PetscObject)J),PETSC_ERR_ARG_WRONGSTATE,"Must call MatFDColoringSetFunction()");
513   if (!J->ops->fdcoloringapply) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not supported for this matrix type %s",((PetscObject)J)->type_name);
514   ierr = PetscLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
515   ierr = (*J->ops->fdcoloringapply)(J,coloring,x1,flag,sctx);CHKERRQ(ierr);
516   ierr = PetscLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
517   PetscFunctionReturn(0);
518 }
519 
520 /* #define JACOBIANCOLOROPT */
521 #if defined(JACOBIANCOLOROPT)
522 #include <petsctime.h>
523 #endif
524 #undef __FUNCT__
525 #define __FUNCT__ "MatFDColoringApply_AIJ"
526 PetscErrorCode  MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx)
527 {
528   PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f;
529   PetscErrorCode ierr;
530   PetscInt       k,start,end,l,row,col,srow,**vscaleforrow;
531   PetscScalar    dx,*y,*xx,*w3_array;
532   PetscScalar    *vscale_array;
533   PetscReal      epsilon = coloring->error_rel,umin = coloring->umin,unorm;
534   Vec            w1      = coloring->w1,w2=coloring->w2,w3;
535   void           *fctx   = coloring->fctx;
536   PetscBool      flg     = PETSC_FALSE;
537   PetscInt       ctype   = coloring->ctype,N,col_start=0,col_end=0;
538   Vec            x1_tmp;
539 #if defined(JACOBIANCOLOROPT)
540   PetscLogDouble t0,t1,time_setvalues=0.0;
541 #endif
542 
543   PetscFunctionBegin;
544   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
545   ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr);
546   if (flg) {
547     ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr);
548   } else {
549     PetscBool assembled;
550     ierr = MatAssembled(J,&assembled);CHKERRQ(ierr);
551     if (assembled) {
552       ierr = MatZeroEntries(J);CHKERRQ(ierr);
553     }
554   }
555 
556   x1_tmp = x1;
557   if (!coloring->vscale) {
558     ierr = VecDuplicate(x1_tmp,&coloring->vscale);CHKERRQ(ierr);
559   }
560 
561   if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/
562     ierr = VecNorm(x1_tmp,NORM_2,&unorm);CHKERRQ(ierr);
563   }
564   ierr = VecGetOwnershipRange(w1,&start,&end);CHKERRQ(ierr); /* OwnershipRange is used by ghosted x! */
565 
566   /* Set w1 = F(x1) */
567   if (!coloring->fset) {
568     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
569     ierr = (*f)(sctx,x1_tmp,w1,fctx);CHKERRQ(ierr);
570     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
571   } else {
572     coloring->fset = PETSC_FALSE;
573   }
574 
575   if (!coloring->w3) {
576     ierr = VecDuplicate(x1_tmp,&coloring->w3);CHKERRQ(ierr);
577     ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr);
578   }
579   w3 = coloring->w3;
580 
581   /* Compute all the local scale factors, including ghost points */
582   ierr = VecGetLocalSize(x1_tmp,&N);CHKERRQ(ierr);
583   ierr = VecGetArray(x1_tmp,&xx);CHKERRQ(ierr);
584   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
585   if (ctype == IS_COLORING_GHOSTED) {
586     col_start = 0; col_end = N;
587   } else if (ctype == IS_COLORING_GLOBAL) {
588     xx           = xx - start;
589     vscale_array = vscale_array - start;
590     col_start    = start; col_end = N + start;
591   }
592   for (col=col_start; col<col_end; col++) {
593     /* Loop over each local column, vscale[col] = 1./(epsilon*dx[col]) */
594     if (coloring->htype[0] == 'w') {
595       dx = 1.0 + unorm;
596     } else {
597       dx = xx[col];
598     }
599     if (dx == (PetscScalar)0.0) dx = 1.0;
600     if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
601     else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
602     dx               *= epsilon;
603     vscale_array[col] = (PetscScalar)1.0/dx;
604   }
605   if (ctype == IS_COLORING_GLOBAL) vscale_array = vscale_array + start;
606   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
607   if (ctype == IS_COLORING_GLOBAL) {
608     ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
609     ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
610   }
611 
612   if (coloring->vscaleforrow) {
613     vscaleforrow = coloring->vscaleforrow;
614   } else SETERRQ(PetscObjectComm((PetscObject)J),PETSC_ERR_ARG_NULL,"Null Object: coloring->vscaleforrow");
615 
616   /*
617     Loop over each color
618   */
619   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
620   for (k=0; k<coloring->ncolors; k++) {
621     coloring->currentcolor = k;
622 
623     ierr = VecCopy(x1_tmp,w3);CHKERRQ(ierr);
624     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);
625     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array - start;
626     /*
627       Loop over each column associated with color
628       adding the perturbation to the vector w3.
629     */
630     for (l=0; l<coloring->ncolumns[k]; l++) {
631       col = coloring->columns[k][l];    /* local column of the matrix we are probing for */
632       if (coloring->htype[0] == 'w') {
633         dx = 1.0 + unorm;
634       } else {
635         dx = xx[col];
636       }
637       if (dx == (PetscScalar)0.0) dx = 1.0;
638       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
639       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
640       dx            *= epsilon;
641       if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter");
642       w3_array[col] += dx;
643     }
644     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array + start;
645     ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
646 
647     /*
648       Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations)
649                            w2 = F(x1 + dx) - F(x1)
650     */
651     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
652     ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
653     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
654     ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
655 
656     /*
657       Loop over rows of vector, putting results into Jacobian matrix
658     */
659 #if defined(JACOBIANCOLOROPT)
660     ierr = PetscTime(&t0);CHKERRQ(ierr);
661 #endif
662     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
663     for (l=0; l<coloring->nrows[k]; l++) {
664       row     = coloring->rows[k][l];            /* local row index */
665       col     = coloring->columnsforrow[k][l];   /* global column index */
666       y[row] *= vscale_array[vscaleforrow[k][l]];
667       srow    = row + start;
668       ierr    = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr);
669     }
670     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
671 #if defined(JACOBIANCOLOROPT)
672     ierr = PetscTime(&t1);CHKERRQ(ierr);
673     time_setvalues += t1-t0;
674 #endif
675   } /* endof for each color */
676 #if defined(JACOBIANCOLOROPT)
677   printf("     MatFDColoringApply_AIJ: time_setvalues %g\n",time_setvalues);
678 #endif
679   if (ctype == IS_COLORING_GLOBAL) xx = xx + start;
680   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
681   ierr = VecRestoreArray(x1_tmp,&xx);CHKERRQ(ierr);
682 
683   coloring->currentcolor = -1;
684 
685   ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
686   ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
687 
688   ierr = MatFDColoringViewFromOptions(coloring,NULL,"-mat_fd_coloring_view");CHKERRQ(ierr);
689   PetscFunctionReturn(0);
690 }
691