xref: /petsc/src/mat/matfd/fdmatrix.c (revision 031bc83f04c73a0da6b2e5fae0ad28311009dfcf)
1 /*$Id: fdmatrix.c,v 1.68 2000/05/16 17:50:59 bsmith Exp bsmith $*/
2 
3 /*
4    This is where the abstract matrix operations are defined that are
5   used for finite difference computations of Jacobians using coloring.
6 */
7 
8 #include "petsc.h"
9 #include "src/mat/matimpl.h"        /*I "petscmat.h" I*/
10 
11 #undef __FUNC__
12 #define __FUNC__ /*<a name="MatFDColoringView_Draw_Zoom"></a>*/"MatFDColoringView_Draw_Zoom"
13 static int MatFDColoringView_Draw_Zoom(Draw draw,void *Aa)
14 {
15   MatFDColoring fd = (MatFDColoring)Aa;
16   int           ierr,i,j;
17   PetscReal     x,y;
18 
19   PetscFunctionBegin;
20 
21   /* loop over colors  */
22   for (i=0; i<fd->ncolors; i++) {
23     for (j=0; j<fd->nrows[i]; j++) {
24       y = fd->M - fd->rows[i][j] - fd->rstart;
25       x = fd->columnsforrow[i][j];
26       ierr = DrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr);
27     }
28   }
29   PetscFunctionReturn(0);
30 }
31 
32 #undef __FUNC__
33 #define __FUNC__ /*<a name="MatFDColoringView_Draw"></a>*/"MatFDColoringView_Draw"
34 static int MatFDColoringView_Draw(MatFDColoring fd,Viewer viewer)
35 {
36   int         ierr;
37   PetscTruth  isnull;
38   Draw        draw;
39   PetscReal   xr,yr,xl,yl,h,w;
40 
41   PetscFunctionBegin;
42   ierr = ViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
43   ierr = DrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
44 
45   ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr);
46 
47   xr  = fd->N; yr = fd->M; h = yr/10.0; w = xr/10.0;
48   xr += w;     yr += h;    xl = -w;     yl = -h;
49   ierr = DrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr);
50   ierr = DrawZoom(draw,MatFDColoringView_Draw_Zoom,fd);CHKERRQ(ierr);
51   ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr);
52   PetscFunctionReturn(0);
53 }
54 
55 #undef __FUNC__
56 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringView"
57 /*@C
58    MatFDColoringView - Views a finite difference coloring context.
59 
60    Collective on MatFDColoring
61 
62    Input  Parameters:
63 +  c - the coloring context
64 -  viewer - visualization context
65 
66    Level: intermediate
67 
68    Notes:
69    The available visualization contexts include
70 +     VIEWER_STDOUT_SELF - standard output (default)
71 .     VIEWER_STDOUT_WORLD - synchronized standard
72         output where only the first processor opens
73         the file.  All other processors send their
74         data to the first processor to print.
75 -     VIEWER_DRAW_WORLD - graphical display of nonzero structure
76 
77    Notes:
78      Since PETSc uses only a small number of basic colors (currently 33), if the coloring
79    involves moe than 33 then some seemingly identical colors are displayed making it look
80    like an illegal coloring. This is just a graphical artifact.
81 
82 .seealso: MatFDColoringCreate()
83 
84 .keywords: Mat, finite differences, coloring, view
85 @*/
86 int MatFDColoringView(MatFDColoring c,Viewer viewer)
87 {
88   int        i,j,format,ierr;
89   PetscTruth isdraw,isascii;
90 
91   PetscFunctionBegin;
92   PetscValidHeaderSpecific(c,MAT_FDCOLORING_COOKIE);
93   if (!viewer) viewer = VIEWER_STDOUT_(c->comm);
94   PetscValidHeaderSpecific(viewer,VIEWER_COOKIE);
95   PetscCheckSameComm(c,viewer);
96 
97   ierr  = PetscTypeCompare((PetscObject)viewer,DRAW_VIEWER,&isdraw);CHKERRQ(ierr);
98   ierr = PetscTypeCompare((PetscObject)viewer,ASCII_VIEWER,&isascii);CHKERRQ(ierr);
99   if (isdraw) {
100     ierr = MatFDColoringView_Draw(c,viewer);CHKERRQ(ierr);
101   } else if (isascii) {
102     ierr = ViewerASCIIPrintf(viewer,"MatFDColoring Object:\n");CHKERRQ(ierr);
103     ierr = ViewerASCIIPrintf(viewer,"  Error tolerance=%g\n",c->error_rel);CHKERRQ(ierr);
104     ierr = ViewerASCIIPrintf(viewer,"  Umin=%g\n",c->umin);CHKERRQ(ierr);
105     ierr = ViewerASCIIPrintf(viewer,"  Number of colors=%d\n",c->ncolors);CHKERRQ(ierr);
106 
107     ierr = ViewerGetFormat(viewer,&format);CHKERRQ(ierr);
108     if (format != VIEWER_FORMAT_ASCII_INFO) {
109       for (i=0; i<c->ncolors; i++) {
110         ierr = ViewerASCIIPrintf(viewer,"  Information for color %d\n",i);CHKERRQ(ierr);
111         ierr = ViewerASCIIPrintf(viewer,"    Number of columns %d\n",c->ncolumns[i]);CHKERRQ(ierr);
112         for (j=0; j<c->ncolumns[i]; j++) {
113           ierr = ViewerASCIIPrintf(viewer,"      %d\n",c->columns[i][j]);CHKERRQ(ierr);
114         }
115         ierr = ViewerASCIIPrintf(viewer,"    Number of rows %d\n",c->nrows[i]);CHKERRQ(ierr);
116         for (j=0; j<c->nrows[i]; j++) {
117           ierr = ViewerASCIIPrintf(viewer,"      %d %d \n",c->rows[i][j],c->columnsforrow[i][j]);CHKERRQ(ierr);
118         }
119       }
120     }
121     ierr = ViewerFlush(viewer);CHKERRQ(ierr);
122   } else {
123     SETERRQ1(1,1,"Viewer type %s not supported for MatFDColoring",((PetscObject)viewer)->type_name);
124   }
125   PetscFunctionReturn(0);
126 }
127 
128 #undef __FUNC__
129 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringSetParameters"
130 /*@
131    MatFDColoringSetParameters - Sets the parameters for the sparse approximation of
132    a Jacobian matrix using finite differences.
133 
134    Collective on MatFDColoring
135 
136    The Jacobian is estimated with the differencing approximation
137 .vb
138        F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
139        h = error_rel*u[i]                 if  abs(u[i]) > umin
140          = +/- error_rel*umin             otherwise, with +/- determined by the sign of u[i]
141        dx_{i} = (0, ... 1, .... 0)
142 .ve
143 
144    Input Parameters:
145 +  coloring - the coloring context
146 .  error_rel - relative error
147 -  umin - minimum allowable u-value magnitude
148 
149    Level: advanced
150 
151 .keywords: Mat, finite differences, coloring, set, parameters
152 
153 .seealso: MatFDColoringCreate()
154 @*/
155 int MatFDColoringSetParameters(MatFDColoring matfd,PetscReal error,PetscReal umin)
156 {
157   PetscFunctionBegin;
158   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE);
159 
160   if (error != PETSC_DEFAULT) matfd->error_rel = error;
161   if (umin != PETSC_DEFAULT)  matfd->umin      = umin;
162   PetscFunctionReturn(0);
163 }
164 
165 #undef __FUNC__
166 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringSetFrequency"
167 /*@
168    MatFDColoringSetFrequency - Sets the frequency for computing new Jacobian
169    matrices.
170 
171    Collective on MatFDColoring
172 
173    Input Parameters:
174 +  coloring - the coloring context
175 -  freq - frequency (default is 1)
176 
177    Options Database Keys:
178 .  -mat_fd_coloring_freq <freq>  - Sets coloring frequency
179 
180    Level: advanced
181 
182    Notes:
183    Using a modified Newton strategy, where the Jacobian remains fixed for several
184    iterations, can be cost effective in terms of overall nonlinear solution
185    efficiency.  This parameter indicates that a new Jacobian will be computed every
186    <freq> nonlinear iterations.
187 
188 .keywords: Mat, finite differences, coloring, set, frequency
189 
190 .seealso: MatFDColoringCreate(), MatFDColoringGetFrequency()
191 @*/
192 int MatFDColoringSetFrequency(MatFDColoring matfd,int freq)
193 {
194   PetscFunctionBegin;
195   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE);
196 
197   matfd->freq = freq;
198   PetscFunctionReturn(0);
199 }
200 
201 #undef __FUNC__
202 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringGetFrequency"
203 /*@
204    MatFDColoringGetFrequency - Gets the frequency for computing new Jacobian
205    matrices.
206 
207    Not Collective
208 
209    Input Parameters:
210 .  coloring - the coloring context
211 
212    Output Parameters:
213 .  freq - frequency (default is 1)
214 
215    Options Database Keys:
216 .  -mat_fd_coloring_freq <freq> - Sets coloring frequency
217 
218    Level: advanced
219 
220    Notes:
221    Using a modified Newton strategy, where the Jacobian remains fixed for several
222    iterations, can be cost effective in terms of overall nonlinear solution
223    efficiency.  This parameter indicates that a new Jacobian will be computed every
224    <freq> nonlinear iterations.
225 
226 .keywords: Mat, finite differences, coloring, get, frequency
227 
228 .seealso: MatFDColoringSetFrequency()
229 @*/
230 int MatFDColoringGetFrequency(MatFDColoring matfd,int *freq)
231 {
232   PetscFunctionBegin;
233   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE);
234 
235   *freq = matfd->freq;
236   PetscFunctionReturn(0);
237 }
238 
239 #undef __FUNC__
240 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringSetFunction"
241 /*@C
242    MatFDColoringSetFunction - Sets the function to use for computing the Jacobian.
243 
244    Collective on MatFDColoring
245 
246    Input Parameters:
247 +  coloring - the coloring context
248 .  f - the function
249 -  fctx - the optional user-defined function context
250 
251    Level: intermediate
252 
253    Notes:
254     In Fortran you must call MatFDColoringSetFunctionSNES() for a coloring object to
255   be used with the SNES solvers and MatFDColoringSetFunctionTS() if it is to be used
256   with the TS solvers.
257 
258 .keywords: Mat, Jacobian, finite differences, set, function
259 @*/
260 int MatFDColoringSetFunction(MatFDColoring matfd,int (*f)(void),void *fctx)
261 {
262   PetscFunctionBegin;
263   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE);
264 
265   matfd->f    = f;
266   matfd->fctx = fctx;
267 
268   PetscFunctionReturn(0);
269 }
270 
271 #undef __FUNC__
272 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringSetFromOptions"
273 /*@
274    MatFDColoringSetFromOptions - Sets coloring finite difference parameters from
275    the options database.
276 
277    Collective on MatFDColoring
278 
279    The Jacobian, F'(u), is estimated with the differencing approximation
280 .vb
281        F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
282        h = error_rel*u[i]                 if  abs(u[i]) > umin
283          = +/- error_rel*umin             otherwise, with +/- determined by the sign of u[i]
284        dx_{i} = (0, ... 1, .... 0)
285 .ve
286 
287    Input Parameter:
288 .  coloring - the coloring context
289 
290    Options Database Keys:
291 +  -mat_fd_coloring_error <err> - Sets <err> (square root
292            of relative error in the function)
293 .  -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude
294 .  -mat_fd_coloring_freq <freq> - Sets frequency of computing a new Jacobian
295 .  -mat_fd_coloring_view - Activates basic viewing
296 .  -mat_fd_coloring_view_info - Activates viewing info
297 -  -mat_fd_coloring_view_draw - Activates drawing
298 
299     Level: intermediate
300 
301 .keywords: Mat, finite differences, parameters
302 @*/
303 int MatFDColoringSetFromOptions(MatFDColoring matfd)
304 {
305   int        ierr,freq = 1;
306   PetscReal  error = PETSC_DEFAULT,umin = PETSC_DEFAULT;
307   PetscTruth flag;
308 
309   PetscFunctionBegin;
310   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE);
311 
312   ierr = OptionsGetDouble(matfd->prefix,"-mat_fd_coloring_err",&error,PETSC_NULL);CHKERRQ(ierr);
313   ierr = OptionsGetDouble(matfd->prefix,"-mat_fd_coloring_umin",&umin,PETSC_NULL);CHKERRQ(ierr);
314   ierr = MatFDColoringSetParameters(matfd,error,umin);CHKERRQ(ierr);
315   ierr = OptionsGetInt(matfd->prefix,"-mat_fd_coloring_freq",&freq,PETSC_NULL);CHKERRQ(ierr);
316   ierr = MatFDColoringSetFrequency(matfd,freq);CHKERRQ(ierr);
317   ierr = OptionsHasName(PETSC_NULL,"-help",&flag);CHKERRQ(ierr);
318   if (flag) {
319     ierr = MatFDColoringPrintHelp(matfd);CHKERRQ(ierr);
320   }
321   PetscFunctionReturn(0);
322 }
323 
324 #undef __FUNC__
325 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringPrintHelp"
326 /*@
327     MatFDColoringPrintHelp - Prints help message for matrix finite difference calculations
328     using coloring.
329 
330     Collective on MatFDColoring
331 
332     Input Parameter:
333 .   fdcoloring - the MatFDColoring context
334 
335     Level: intermediate
336 
337 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringSetFromOptions()
338 @*/
339 int MatFDColoringPrintHelp(MatFDColoring fd)
340 {
341   int ierr;
342 
343   PetscFunctionBegin;
344   PetscValidHeaderSpecific(fd,MAT_FDCOLORING_COOKIE);
345 
346   ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_err <err>: set sqrt rel tol in function, defaults to %g\n",fd->error_rel);CHKERRQ(ierr);
347   ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_umin <umin>: see users manual, defaults to %d\n",fd->umin);CHKERRQ(ierr);
348   ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_freq <freq>: frequency that Jacobian is recomputed, defaults to %d\n",fd->freq);CHKERRQ(ierr);
349   ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view\n");CHKERRQ(ierr);
350   ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view_draw\n");CHKERRQ(ierr);
351   ierr = (*PetscHelpPrintf)(fd->comm,"-mat_fd_coloring_view_info\n");CHKERRQ(ierr);
352   PetscFunctionReturn(0);
353 }
354 
355 #undef __FUNC__
356 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringView_Private"
357 int MatFDColoringView_Private(MatFDColoring fd)
358 {
359   int        ierr;
360   PetscTruth flg;
361 
362   PetscFunctionBegin;
363   ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view",&flg);CHKERRQ(ierr);
364   if (flg) {
365     ierr = MatFDColoringView(fd,VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr);
366   }
367   ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view_info",&flg);CHKERRQ(ierr);
368   if (flg) {
369     ierr = ViewerPushFormat(VIEWER_STDOUT_(fd->comm),VIEWER_FORMAT_ASCII_INFO,PETSC_NULL);CHKERRQ(ierr);
370     ierr = MatFDColoringView(fd,VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr);
371     ierr = ViewerPopFormat(VIEWER_STDOUT_(fd->comm));CHKERRQ(ierr);
372   }
373   ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_view_draw",&flg);CHKERRQ(ierr);
374   if (flg) {
375     ierr = MatFDColoringView(fd,VIEWER_DRAW_(fd->comm));CHKERRQ(ierr);
376     ierr = ViewerFlush(VIEWER_DRAW_(fd->comm));CHKERRQ(ierr);
377   }
378   PetscFunctionReturn(0);
379 }
380 
381 #undef __FUNC__
382 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringCreate"
383 /*@C
384    MatFDColoringCreate - Creates a matrix coloring context for finite difference
385    computation of Jacobians.
386 
387    Collective on Mat
388 
389    Input Parameters:
390 +  mat - the matrix containing the nonzero structure of the Jacobian
391 -  iscoloring - the coloring of the matrix
392 
393     Output Parameter:
394 .   color - the new coloring context
395 
396     Options Database Keys:
397 +    -mat_fd_coloring_view - Activates basic viewing or coloring
398 .    -mat_fd_coloring_view_draw - Activates drawing of coloring
399 -    -mat_fd_coloring_view_info - Activates viewing of coloring info
400 
401     Level: intermediate
402 
403 .seealso: MatFDColoringDestroy(),SNESDefaultComputeJacobianColor(), ISColoringCreate(),
404           MatFDColoringSetFunction(), MatFDColoringSetFromOptions()
405 @*/
406 int MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color)
407 {
408   MatFDColoring c;
409   MPI_Comm      comm;
410   int           ierr,M,N;
411 
412   PetscFunctionBegin;
413   PLogEventBegin(MAT_FDColoringCreate,mat,0,0,0);
414   ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr);
415   if (M != N) SETERRQ(PETSC_ERR_SUP,0,"Only for square matrices");
416 
417   ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
418   PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_COOKIE,0,"MatFDColoring",comm,MatFDColoringDestroy,MatFDColoringView);
419   PLogObjectCreate(c);
420 
421   if (mat->ops->fdcoloringcreate) {
422     ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr);
423   } else {
424     SETERRQ(PETSC_ERR_SUP,0,"Code not yet written for this matrix type");
425   }
426 
427   c->error_rel = 1.e-8;
428   c->umin      = 1.e-6;
429   c->freq      = 1;
430 
431   ierr = MatFDColoringView_Private(c);CHKERRQ(ierr);
432 
433   *color = c;
434   PLogEventEnd(MAT_FDColoringCreate,mat,0,0,0);
435   PetscFunctionReturn(0);
436 }
437 
438 #undef __FUNC__
439 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringDestroy"
440 /*@C
441     MatFDColoringDestroy - Destroys a matrix coloring context that was created
442     via MatFDColoringCreate().
443 
444     Collective on MatFDColoring
445 
446     Input Parameter:
447 .   c - coloring context
448 
449     Level: intermediate
450 
451 .seealso: MatFDColoringCreate()
452 @*/
453 int MatFDColoringDestroy(MatFDColoring c)
454 {
455   int i,ierr;
456 
457   PetscFunctionBegin;
458   if (--c->refct > 0) PetscFunctionReturn(0);
459 
460   for (i=0; i<c->ncolors; i++) {
461     if (c->columns[i])         {ierr = PetscFree(c->columns[i]);CHKERRQ(ierr);}
462     if (c->rows[i])            {ierr = PetscFree(c->rows[i]);CHKERRQ(ierr);}
463     if (c->columnsforrow[i])   {ierr = PetscFree(c->columnsforrow[i]);CHKERRQ(ierr);}
464     if (c->vscaleforrow && c->vscaleforrow[i]) {ierr = PetscFree(c->vscaleforrow[i]);CHKERRQ(ierr);}
465   }
466   ierr = PetscFree(c->ncolumns);CHKERRQ(ierr);
467   ierr = PetscFree(c->columns);CHKERRQ(ierr);
468   ierr = PetscFree(c->nrows);CHKERRQ(ierr);
469   ierr = PetscFree(c->rows);CHKERRQ(ierr);
470   ierr = PetscFree(c->columnsforrow);CHKERRQ(ierr);
471   if (c->vscaleforrow) {ierr = PetscFree(c->vscaleforrow);CHKERRQ(ierr);}
472   if (c->vscale)       {ierr = VecDestroy(c->vscale);CHKERRQ(ierr);}
473   if (c->w1) {
474     ierr = VecDestroy(c->w1);CHKERRQ(ierr);
475     ierr = VecDestroy(c->w2);CHKERRQ(ierr);
476     ierr = VecDestroy(c->w3);CHKERRQ(ierr);
477   }
478   PLogObjectDestroy(c);
479   PetscHeaderDestroy(c);
480   PetscFunctionReturn(0);
481 }
482 
483 
484 #undef __FUNC__
485 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringApply"
486 /*@
487     MatFDColoringApply - Given a matrix for which a MatFDColoring context
488     has been created, computes the Jacobian for a function via finite differences.
489 
490     Collective on MatFDColoring
491 
492     Input Parameters:
493 +   mat - location to store Jacobian
494 .   coloring - coloring context created with MatFDColoringCreate()
495 .   x1 - location at which Jacobian is to be computed
496 -   sctx - optional context required by function (actually a SNES context)
497 
498    Options Database Keys:
499 .  -mat_fd_coloring_freq <freq> - Sets coloring frequency
500 
501    Level: intermediate
502 
503 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView()
504 
505 .keywords: coloring, Jacobian, finite differences
506 @*/
507 int MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx)
508 {
509   int           (*f)(void *,Vec,Vec,void*)= (int (*)(void *,Vec,Vec,void *))coloring->f;
510   int           k,ierr,N,start,end,l,row,col,srow,**vscaleforrow;
511   Scalar        dx,mone = -1.0,*y,*xx,*w3_array;
512   Scalar        *vscale_array;
513   PetscReal     epsilon = coloring->error_rel,umin = coloring->umin;
514   MPI_Comm      comm = coloring->comm;
515   Vec           w1,w2,w3;
516   void          *fctx = coloring->fctx;
517   PetscTruth    flg;
518 
519   PetscFunctionBegin;
520   PetscValidHeaderSpecific(J,MAT_COOKIE);
521   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE);
522   PetscValidHeaderSpecific(x1,VEC_COOKIE);
523 
524   PLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);
525   if (!coloring->w1) {
526     ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr);
527     PLogObjectParent(coloring,coloring->w1);
528     ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr);
529     PLogObjectParent(coloring,coloring->w2);
530     ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr);
531     PLogObjectParent(coloring,coloring->w3);
532   }
533   w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3;
534 
535   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
536   ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&flg);CHKERRQ(ierr);
537   if (flg) {
538     PLogInfo(coloring,"MatFDColoringApply: Not calling MatZeroEntries()\n");
539   } else {
540     ierr = MatZeroEntries(J);CHKERRQ(ierr);
541   }
542 
543   ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr);
544   ierr = VecGetSize(x1,&N);CHKERRQ(ierr);
545   ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr);
546 
547   /*
548       Compute all the scale factors and share with other processors
549   */
550   ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start;
551   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start;
552   for (k=0; k<coloring->ncolors; k++) {
553     /*
554        Loop over each column associated with color adding the
555        perturbation to the vector w3.
556     */
557     for (l=0; l<coloring->ncolumns[k]; l++) {
558       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
559       dx  = xx[col];
560       if (dx == 0.0) dx = 1.0;
561 #if !defined(PETSC_USE_COMPLEX)
562       if (dx < umin && dx >= 0.0)      dx = umin;
563       else if (dx < 0.0 && dx > -umin) dx = -umin;
564 #else
565       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
566       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
567 #endif
568       dx                *= epsilon;
569       vscale_array[col] = 1.0/dx;
570     }
571   }
572   vscale_array = vscale_array - start;ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
573   ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
574   ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
575 
576   if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow;
577   else                        vscaleforrow = coloring->columnsforrow;
578 
579   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
580   /*
581       Loop over each color
582   */
583   for (k=0; k<coloring->ncolors; k++) {
584     ierr = VecCopy(x1,w3);CHKERRQ(ierr);
585     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start;
586     /*
587        Loop over each column associated with color adding the
588        perturbation to the vector w3.
589     */
590     for (l=0; l<coloring->ncolumns[k]; l++) {
591       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
592       dx  = xx[col];
593       if (dx == 0.0) dx = 1.0;
594 #if !defined(PETSC_USE_COMPLEX)
595       if (dx < umin && dx >= 0.0)      dx = umin;
596       else if (dx < 0.0 && dx > -umin) dx = -umin;
597 #else
598       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
599       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
600 #endif
601       dx            *= epsilon;
602       w3_array[col] += dx;
603     }
604     w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
605 
606     /*
607        Evaluate function at x1 + dx (here dx is a vector of perturbations)
608     */
609     ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
610     ierr = VecAXPY(&mone,w1,w2);CHKERRQ(ierr);
611 
612     /*
613        Loop over rows of vector, putting results into Jacobian matrix
614     */
615     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
616     for (l=0; l<coloring->nrows[k]; l++) {
617       row    = coloring->rows[k][l];
618       col    = coloring->columnsforrow[k][l];
619       y[row] *= vscale_array[vscaleforrow[k][l]];
620       srow   = row + start;
621       ierr   = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr);
622     }
623     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
624   }
625   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
626   xx = xx + start; ierr  = VecRestoreArray(x1,&xx);CHKERRQ(ierr);
627   ierr  = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
628   ierr  = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
629   PLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);
630   PetscFunctionReturn(0);
631 }
632 
633 #undef __FUNC__
634 #define __FUNC__ /*<a name=""></a>*/"MatFDColoringApplyTS"
635 /*@
636     MatFDColoringApplyTS - Given a matrix for which a MatFDColoring context
637     has been created, computes the Jacobian for a function via finite differences.
638 
639    Collective on Mat, MatFDColoring, and Vec
640 
641     Input Parameters:
642 +   mat - location to store Jacobian
643 .   coloring - coloring context created with MatFDColoringCreate()
644 .   x1 - location at which Jacobian is to be computed
645 -   sctx - optional context required by function (actually a SNES context)
646 
647    Options Database Keys:
648 .  -mat_fd_coloring_freq <freq> - Sets coloring frequency
649 
650    Level: intermediate
651 
652 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView()
653 
654 .keywords: coloring, Jacobian, finite differences
655 @*/
656 int MatFDColoringApplyTS(Mat J,MatFDColoring coloring,PetscReal t,Vec x1,MatStructure *flag,void *sctx)
657 {
658   int           (*f)(void *,PetscReal,Vec,Vec,void*)= (int (*)(void *,PetscReal,Vec,Vec,void *))coloring->f;
659   int           k,ierr,N,start,end,l,row,col,srow,**vscaleforrow;
660   Scalar        dx,mone = -1.0,*y,*xx,*w3_array;
661   Scalar        *vscale_array;
662   PetscReal     epsilon = coloring->error_rel,umin = coloring->umin;
663   MPI_Comm      comm = coloring->comm;
664   Vec           w1,w2,w3;
665   void          *fctx = coloring->fctx;
666   PetscTruth    flg;
667 
668   PetscFunctionBegin;
669   PetscValidHeaderSpecific(J,MAT_COOKIE);
670   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE);
671   PetscValidHeaderSpecific(x1,VEC_COOKIE);
672 
673   PLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);
674   if (!coloring->w1) {
675     ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr);
676     PLogObjectParent(coloring,coloring->w1);
677     ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr);
678     PLogObjectParent(coloring,coloring->w2);
679     ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr);
680     PLogObjectParent(coloring,coloring->w3);
681   }
682   w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3;
683 
684   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
685   ierr = OptionsHasName(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&flg);CHKERRQ(ierr);
686   if (flg) {
687     PLogInfo(coloring,"MatFDColoringApply: Not calling MatZeroEntries()\n");
688   } else {
689     ierr = MatZeroEntries(J);CHKERRQ(ierr);
690   }
691 
692   ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr);
693   ierr = VecGetSize(x1,&N);CHKERRQ(ierr);
694   ierr = (*f)(sctx,t,x1,w1,fctx);CHKERRQ(ierr);
695 
696   /*
697       Compute all the scale factors and share with other processors
698   */
699   ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start;
700   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start;
701   for (k=0; k<coloring->ncolors; k++) {
702     /*
703        Loop over each column associated with color adding the
704        perturbation to the vector w3.
705     */
706     for (l=0; l<coloring->ncolumns[k]; l++) {
707       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
708       dx  = xx[col];
709       if (dx == 0.0) dx = 1.0;
710 #if !defined(PETSC_USE_COMPLEX)
711       if (dx < umin && dx >= 0.0)      dx = umin;
712       else if (dx < 0.0 && dx > -umin) dx = -umin;
713 #else
714       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
715       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
716 #endif
717       dx                *= epsilon;
718       vscale_array[col] = 1.0/dx;
719     }
720   }
721   vscale_array = vscale_array - start;ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
722   ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
723   ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
724 
725   if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow;
726   else                        vscaleforrow = coloring->columnsforrow;
727 
728   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
729   /*
730       Loop over each color
731   */
732   for (k=0; k<coloring->ncolors; k++) {
733     ierr = VecCopy(x1,w3);CHKERRQ(ierr);
734     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start;
735     /*
736        Loop over each column associated with color adding the
737        perturbation to the vector w3.
738     */
739     for (l=0; l<coloring->ncolumns[k]; l++) {
740       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
741       dx  = xx[col];
742       if (dx == 0.0) dx = 1.0;
743 #if !defined(PETSC_USE_COMPLEX)
744       if (dx < umin && dx >= 0.0)      dx = umin;
745       else if (dx < 0.0 && dx > -umin) dx = -umin;
746 #else
747       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
748       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
749 #endif
750       dx            *= epsilon;
751       w3_array[col] += dx;
752     }
753     w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
754 
755     /*
756        Evaluate function at x1 + dx (here dx is a vector of perturbations)
757     */
758     ierr = (*f)(sctx,t,w3,w2,fctx);CHKERRQ(ierr);
759     ierr = VecAXPY(&mone,w1,w2);CHKERRQ(ierr);
760 
761     /*
762        Loop over rows of vector, putting results into Jacobian matrix
763     */
764     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
765     for (l=0; l<coloring->nrows[k]; l++) {
766       row    = coloring->rows[k][l];
767       col    = coloring->columnsforrow[k][l];
768       y[row] *= vscale_array[vscaleforrow[k][l]];
769       srow   = row + start;
770       ierr   = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr);
771     }
772     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
773   }
774   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
775   xx = xx + start; ierr  = VecRestoreArray(x1,&xx);CHKERRQ(ierr);
776   ierr  = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
777   PLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);
778   ierr  = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
779   PetscFunctionReturn(0);
780 }
781 
782 
783 
784