xref: /petsc/src/mat/matfd/fdmatrix.c (revision e3caeda681d93b7b1d053090fe6dee7657faa56d)
1 #define PETSCMAT_DLL
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 "private/matimpl.h"        /*I "petscmat.h" I*/
9 
10 #undef __FUNCT__
11 #define __FUNCT__ "MatFDColoringSetF"
12 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringSetF(MatFDColoring fd,Vec F)
13 {
14   PetscFunctionBegin;
15   fd->F = F;
16   PetscFunctionReturn(0);
17 }
18 
19 #undef __FUNCT__
20 #define __FUNCT__ "MatFDColoringView_Draw_Zoom"
21 static PetscErrorCode MatFDColoringView_Draw_Zoom(PetscDraw draw,void *Aa)
22 {
23   MatFDColoring  fd = (MatFDColoring)Aa;
24   PetscErrorCode ierr;
25   PetscInt       i,j;
26   PetscReal      x,y;
27 
28   PetscFunctionBegin;
29 
30   /* loop over colors  */
31   for (i=0; i<fd->ncolors; i++) {
32     for (j=0; j<fd->nrows[i]; j++) {
33       y = fd->M - fd->rows[i][j] - fd->rstart;
34       x = fd->columnsforrow[i][j];
35       ierr = PetscDrawRectangle(draw,x,y,x+1,y+1,i+1,i+1,i+1,i+1);CHKERRQ(ierr);
36     }
37   }
38   PetscFunctionReturn(0);
39 }
40 
41 #undef __FUNCT__
42 #define __FUNCT__ "MatFDColoringView_Draw"
43 static PetscErrorCode MatFDColoringView_Draw(MatFDColoring fd,PetscViewer viewer)
44 {
45   PetscErrorCode ierr;
46   PetscTruth     isnull;
47   PetscDraw      draw;
48   PetscReal      xr,yr,xl,yl,h,w;
49 
50   PetscFunctionBegin;
51   ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
52   ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
53 
54   ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr);
55 
56   xr  = fd->N; yr = fd->M; h = yr/10.0; w = xr/10.0;
57   xr += w;     yr += h;    xl = -w;     yl = -h;
58   ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr);
59   ierr = PetscDrawZoom(draw,MatFDColoringView_Draw_Zoom,fd);CHKERRQ(ierr);
60   ierr = PetscObjectCompose((PetscObject)fd,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr);
61   PetscFunctionReturn(0);
62 }
63 
64 #undef __FUNCT__
65 #define __FUNCT__ "MatFDColoringView"
66 /*@C
67    MatFDColoringView - Views a finite difference coloring context.
68 
69    Collective on MatFDColoring
70 
71    Input  Parameters:
72 +  c - the coloring context
73 -  viewer - visualization context
74 
75    Level: intermediate
76 
77    Notes:
78    The available visualization contexts include
79 +     PETSC_VIEWER_STDOUT_SELF - standard output (default)
80 .     PETSC_VIEWER_STDOUT_WORLD - synchronized standard
81         output where only the first processor opens
82         the file.  All other processors send their
83         data to the first processor to print.
84 -     PETSC_VIEWER_DRAW_WORLD - graphical display of nonzero structure
85 
86    Notes:
87      Since PETSc uses only a small number of basic colors (currently 33), if the coloring
88    involves more than 33 then some seemingly identical colors are displayed making it look
89    like an illegal coloring. This is just a graphical artifact.
90 
91 .seealso: MatFDColoringCreate()
92 
93 .keywords: Mat, finite differences, coloring, view
94 @*/
95 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringView(MatFDColoring c,PetscViewer viewer)
96 {
97   PetscErrorCode    ierr;
98   PetscInt          i,j;
99   PetscTruth        isdraw,iascii;
100   PetscViewerFormat format;
101 
102   PetscFunctionBegin;
103   PetscValidHeaderSpecific(c,MAT_FDCOLORING_COOKIE,1);
104   if (!viewer) {
105     ierr = PetscViewerASCIIGetStdout(((PetscObject)c)->comm,&viewer);CHKERRQ(ierr);
106   }
107   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_COOKIE,2);
108   PetscCheckSameComm(c,1,viewer,2);
109 
110   ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_DRAW,&isdraw);CHKERRQ(ierr);
111   ierr = PetscTypeCompare((PetscObject)viewer,PETSC_VIEWER_ASCII,&iascii);CHKERRQ(ierr);
112   if (isdraw) {
113     ierr = MatFDColoringView_Draw(c,viewer);CHKERRQ(ierr);
114   } else if (iascii) {
115     ierr = PetscViewerASCIIPrintf(viewer,"MatFDColoring Object:\n");CHKERRQ(ierr);
116     ierr = PetscViewerASCIIPrintf(viewer,"  Error tolerance=%G\n",c->error_rel);CHKERRQ(ierr);
117     ierr = PetscViewerASCIIPrintf(viewer,"  Umin=%G\n",c->umin);CHKERRQ(ierr);
118     ierr = PetscViewerASCIIPrintf(viewer,"  Number of colors=%D\n",c->ncolors);CHKERRQ(ierr);
119 
120     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
121     if (format != PETSC_VIEWER_ASCII_INFO) {
122       for (i=0; i<c->ncolors; i++) {
123         ierr = PetscViewerASCIIPrintf(viewer,"  Information for color %D\n",i);CHKERRQ(ierr);
124         ierr = PetscViewerASCIIPrintf(viewer,"    Number of columns %D\n",c->ncolumns[i]);CHKERRQ(ierr);
125         for (j=0; j<c->ncolumns[i]; j++) {
126           ierr = PetscViewerASCIIPrintf(viewer,"      %D\n",c->columns[i][j]);CHKERRQ(ierr);
127         }
128         ierr = PetscViewerASCIIPrintf(viewer,"    Number of rows %D\n",c->nrows[i]);CHKERRQ(ierr);
129         for (j=0; j<c->nrows[i]; j++) {
130           ierr = PetscViewerASCIIPrintf(viewer,"      %D %D \n",c->rows[i][j],c->columnsforrow[i][j]);CHKERRQ(ierr);
131         }
132       }
133     }
134     ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
135   } else {
136     SETERRQ1(PETSC_ERR_SUP,"Viewer type %s not supported for MatFDColoring",((PetscObject)viewer)->type_name);
137   }
138   PetscFunctionReturn(0);
139 }
140 
141 #undef __FUNCT__
142 #define __FUNCT__ "MatFDColoringSetParameters"
143 /*@
144    MatFDColoringSetParameters - Sets the parameters for the sparse approximation of
145    a Jacobian matrix using finite differences.
146 
147    Collective on MatFDColoring
148 
149    The Jacobian is estimated with the differencing approximation
150 .vb
151        F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
152        h = error_rel*u[i]                 if  abs(u[i]) > umin
153          = +/- error_rel*umin             otherwise, with +/- determined by the sign of u[i]
154        dx_{i} = (0, ... 1, .... 0)
155 .ve
156 
157    Input Parameters:
158 +  coloring - the coloring context
159 .  error_rel - relative error
160 -  umin - minimum allowable u-value magnitude
161 
162    Level: advanced
163 
164 .keywords: Mat, finite differences, coloring, set, parameters
165 
166 .seealso: MatFDColoringCreate()
167 @*/
168 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringSetParameters(MatFDColoring matfd,PetscReal error,PetscReal umin)
169 {
170   PetscFunctionBegin;
171   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE,1);
172 
173   if (error != PETSC_DEFAULT) matfd->error_rel = error;
174   if (umin != PETSC_DEFAULT)  matfd->umin      = umin;
175   PetscFunctionReturn(0);
176 }
177 
178 
179 
180 #undef __FUNCT__
181 #define __FUNCT__ "MatFDColoringGetFunction"
182 /*@C
183    MatFDColoringGetFunction - Gets the function to use for computing the Jacobian.
184 
185    Collective on MatFDColoring
186 
187    Input Parameters:
188 .  coloring - the coloring context
189 
190    Output Parameters:
191 +  f - the function
192 -  fctx - the optional user-defined function context
193 
194    Level: intermediate
195 
196 .keywords: Mat, Jacobian, finite differences, set, function
197 @*/
198 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringGetFunction(MatFDColoring matfd,PetscErrorCode (**f)(void),void **fctx)
199 {
200   PetscFunctionBegin;
201   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE,1);
202   if (f) *f = matfd->f;
203   if (fctx) *fctx = matfd->fctx;
204   PetscFunctionReturn(0);
205 }
206 
207 #undef __FUNCT__
208 #define __FUNCT__ "MatFDColoringSetFunction"
209 /*@C
210    MatFDColoringSetFunction - Sets the function to use for computing the Jacobian.
211 
212    Collective on MatFDColoring
213 
214    Input Parameters:
215 +  coloring - the coloring context
216 .  f - the function
217 -  fctx - the optional user-defined function context
218 
219    Calling sequence of (*f) function:
220     For SNES:    PetscErrorCode (*f)(SNES,Vec,Vec,void*)
221     For TS:      PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*)
222     If not using SNES or TS: PetscErrorCode (*f)(void *dummy,Vec,Vec,void*) and dummy is ignored
223 
224    Level: advanced
225 
226    Notes: This function is usually used automatically by SNES or TS (when one uses SNESSetJacobian() with the argument
227      SNESDefaultComputeJacobianColor() or TSSetRHSJacobian() with the argument TSDefaultComputeJacobianColor()) and only needs to be used
228      by someone computing a matrix via coloring directly by calling MatFDColoringApply()
229 
230    Fortran Notes:
231     In Fortran you must call MatFDColoringSetFunction() for a coloring object to
232   be used without SNES or TS or within the SNES solvers and MatFDColoringSetFunctionTS() if it is to be used
233   within the TS solvers.
234 
235 .keywords: Mat, Jacobian, finite differences, set, function
236 @*/
237 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringSetFunction(MatFDColoring matfd,PetscErrorCode (*f)(void),void *fctx)
238 {
239   PetscFunctionBegin;
240   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE,1);
241   matfd->f    = f;
242   matfd->fctx = fctx;
243   PetscFunctionReturn(0);
244 }
245 
246 #undef __FUNCT__
247 #define __FUNCT__ "MatFDColoringSetFromOptions"
248 /*@
249    MatFDColoringSetFromOptions - Sets coloring finite difference parameters from
250    the options database.
251 
252    Collective on MatFDColoring
253 
254    The Jacobian, F'(u), is estimated with the differencing approximation
255 .vb
256        F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
257        h = error_rel*u[i]                 if  abs(u[i]) > umin
258          = +/- error_rel*umin             otherwise, with +/- determined by the sign of u[i]
259        dx_{i} = (0, ... 1, .... 0)
260 .ve
261 
262    Input Parameter:
263 .  coloring - the coloring context
264 
265    Options Database Keys:
266 +  -mat_fd_coloring_err <err> - Sets <err> (square root
267            of relative error in the function)
268 .  -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude
269 .  -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS)
270 .  -mat_fd_coloring_view - Activates basic viewing
271 .  -mat_fd_coloring_view_info - Activates viewing info
272 -  -mat_fd_coloring_view_draw - Activates drawing
273 
274     Level: intermediate
275 
276 .keywords: Mat, finite differences, parameters
277 
278 .seealso: MatFDColoringCreate(), MatFDColoringView(), MatFDColoringSetParameters()
279 
280 @*/
281 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringSetFromOptions(MatFDColoring matfd)
282 {
283   PetscErrorCode ierr;
284   PetscTruth     flg;
285   char           value[3];
286 
287   PetscFunctionBegin;
288   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_COOKIE,1);
289 
290   ierr = PetscOptionsBegin(((PetscObject)matfd)->comm,((PetscObject)matfd)->prefix,"Jacobian computation via finite differences option","MatFD");CHKERRQ(ierr);
291     ierr = PetscOptionsReal("-mat_fd_coloring_err","Square root of relative error in function","MatFDColoringSetParameters",matfd->error_rel,&matfd->error_rel,0);CHKERRQ(ierr);
292     ierr = PetscOptionsReal("-mat_fd_coloring_umin","Minimum allowable u magnitude","MatFDColoringSetParameters",matfd->umin,&matfd->umin,0);CHKERRQ(ierr);
293     ierr = PetscOptionsString("-mat_fd_type","Algorithm to compute h, wp or ds","MatFDColoringCreate",matfd->htype,value,2,&flg);CHKERRQ(ierr);
294     if (flg) {
295       if (value[0] == 'w' && value[1] == 'p') matfd->htype = "wp";
296       else if (value[0] == 'd' && value[1] == 's') matfd->htype = "ds";
297       else SETERRQ1(PETSC_ERR_ARG_OUTOFRANGE,"Unknown finite differencing type %s",value);
298     }
299     /* not used here; but so they are presented in the GUI */
300     ierr = PetscOptionsName("-mat_fd_coloring_view","Print entire datastructure used for Jacobian","None",0);CHKERRQ(ierr);
301     ierr = PetscOptionsName("-mat_fd_coloring_view_info","Print number of colors etc for Jacobian","None",0);CHKERRQ(ierr);
302     ierr = PetscOptionsName("-mat_fd_coloring_view_draw","Plot nonzero structure ofJacobian","None",0);CHKERRQ(ierr);
303   PetscOptionsEnd();CHKERRQ(ierr);
304   PetscFunctionReturn(0);
305 }
306 
307 #undef __FUNCT__
308 #define __FUNCT__ "MatFDColoringView_Private"
309 PetscErrorCode MatFDColoringView_Private(MatFDColoring fd)
310 {
311   PetscErrorCode ierr;
312   PetscTruth     flg = PETSC_FALSE;
313   PetscViewer    viewer;
314 
315   PetscFunctionBegin;
316   ierr = PetscViewerASCIIGetStdout(((PetscObject)fd)->comm,&viewer);CHKERRQ(ierr);
317   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_view",&flg,PETSC_NULL);CHKERRQ(ierr);
318   if (flg) {
319     ierr = MatFDColoringView(fd,viewer);CHKERRQ(ierr);
320   }
321   flg  = PETSC_FALSE;
322   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_view_info",&flg,PETSC_NULL);CHKERRQ(ierr);
323   if (flg) {
324     ierr = PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO);CHKERRQ(ierr);
325     ierr = MatFDColoringView(fd,viewer);CHKERRQ(ierr);
326     ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr);
327   }
328   flg  = PETSC_FALSE;
329   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_view_draw",&flg,PETSC_NULL);CHKERRQ(ierr);
330   if (flg) {
331     ierr = MatFDColoringView(fd,PETSC_VIEWER_DRAW_(((PetscObject)fd)->comm));CHKERRQ(ierr);
332     ierr = PetscViewerFlush(PETSC_VIEWER_DRAW_(((PetscObject)fd)->comm));CHKERRQ(ierr);
333   }
334   PetscFunctionReturn(0);
335 }
336 
337 #undef __FUNCT__
338 #define __FUNCT__ "MatFDColoringCreate"
339 /*@
340    MatFDColoringCreate - Creates a matrix coloring context for finite difference
341    computation of Jacobians.
342 
343    Collective on Mat
344 
345    Input Parameters:
346 +  mat - the matrix containing the nonzero structure of the Jacobian
347 -  iscoloring - the coloring of the matrix
348 
349     Output Parameter:
350 .   color - the new coloring context
351 
352     Level: intermediate
353 
354 .seealso: MatFDColoringDestroy(),SNESDefaultComputeJacobianColor(), ISColoringCreate(),
355           MatFDColoringSetFunction(), MatFDColoringSetFromOptions(), MatFDColoringApply(),
356           MatFDColoringView(), MatFDColoringSetParameters()
357 @*/
358 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color)
359 {
360   MatFDColoring  c;
361   MPI_Comm       comm;
362   PetscErrorCode ierr;
363   PetscInt       M,N;
364   PetscMPIInt    size;
365 
366   PetscFunctionBegin;
367   ierr = PetscLogEventBegin(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr);
368   ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr);
369   if (M != N) SETERRQ(PETSC_ERR_SUP,"Only for square matrices");
370 
371   ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
372   ierr = PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_COOKIE,0,"MatFDColoring",comm,MatFDColoringDestroy,MatFDColoringView);CHKERRQ(ierr);
373 
374   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
375   c->ctype = iscoloring->ctype;
376 
377   if (mat->ops->fdcoloringcreate) {
378     ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr);
379   } else {
380     SETERRQ(PETSC_ERR_SUP,"Code not yet written for this matrix type");
381   }
382 
383   ierr = MatGetVecs(mat,PETSC_NULL,&c->w1);CHKERRQ(ierr);
384   ierr = PetscLogObjectParent(c,c->w1);CHKERRQ(ierr);
385   ierr = VecDuplicate(c->w1,&c->w2);CHKERRQ(ierr);
386   ierr = PetscLogObjectParent(c,c->w2);CHKERRQ(ierr);
387 
388   c->error_rel         = PETSC_SQRT_MACHINE_EPSILON;
389   c->umin              = 100.0*PETSC_SQRT_MACHINE_EPSILON;
390   c->currentcolor      = -1;
391   c->htype             = "wp";
392 
393   *color = c;
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 PETSCMAT_DLLEXPORT MatFDColoringDestroy(MatFDColoring c)
414 {
415   PetscErrorCode ierr;
416   PetscInt       i;
417 
418   PetscFunctionBegin;
419   if (--((PetscObject)c)->refct > 0) PetscFunctionReturn(0);
420 
421   for (i=0; i<c->ncolors; i++) {
422     ierr = PetscFree(c->columns[i]);CHKERRQ(ierr);
423     ierr = PetscFree(c->rows[i]);CHKERRQ(ierr);
424     ierr = PetscFree(c->columnsforrow[i]);CHKERRQ(ierr);
425     if (c->vscaleforrow) {ierr = PetscFree(c->vscaleforrow[i]);CHKERRQ(ierr);}
426   }
427   ierr = PetscFree(c->ncolumns);CHKERRQ(ierr);
428   ierr = PetscFree(c->columns);CHKERRQ(ierr);
429   ierr = PetscFree(c->nrows);CHKERRQ(ierr);
430   ierr = PetscFree(c->rows);CHKERRQ(ierr);
431   ierr = PetscFree(c->columnsforrow);CHKERRQ(ierr);
432   ierr = PetscFree(c->vscaleforrow);CHKERRQ(ierr);
433   if (c->vscale)       {ierr = VecDestroy(c->vscale);CHKERRQ(ierr);}
434   if (c->w1) {
435     ierr = VecDestroy(c->w1);CHKERRQ(ierr);
436     ierr = VecDestroy(c->w2);CHKERRQ(ierr);
437   }
438   if (c->w3){
439     ierr = VecDestroy(c->w3);CHKERRQ(ierr);
440   }
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 PETSCMAT_DLLEXPORT 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 #include "petscda.h"      /*I      "petscda.h"    I*/
479 
480 #undef __FUNCT__
481 #define __FUNCT__ "MatFDColoringApply"
482 /*@
483     MatFDColoringApply - Given a matrix for which a MatFDColoring context
484     has been created, computes the Jacobian for a function via finite differences.
485 
486     Collective on MatFDColoring
487 
488     Input Parameters:
489 +   mat - location to store Jacobian
490 .   coloring - coloring context created with MatFDColoringCreate()
491 .   x1 - location at which Jacobian is to be computed
492 -   sctx - context required by function, if this is being used with the SNES solver then it is SNES object, otherwise it is null
493 
494     Options Database Keys:
495 +    -mat_fd_type - "wp" or "ds"  (see MATMFFD_WP or MATMFFD_DS)
496 .    -mat_fd_coloring_view - Activates basic viewing or coloring
497 .    -mat_fd_coloring_view_draw - Activates drawing of coloring
498 -    -mat_fd_coloring_view_info - Activates viewing of coloring info
499 
500     Level: intermediate
501 
502 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringSetFunction()
503 
504 .keywords: coloring, Jacobian, finite differences
505 @*/
506 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx)
507 {
508   PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void *))coloring->f;
509   PetscErrorCode ierr;
510   PetscInt       k,start,end,l,row,col,srow,**vscaleforrow,m1,m2;
511   PetscScalar    dx,*y,*xx,*w3_array;
512   PetscScalar    *vscale_array;
513   PetscReal      epsilon = coloring->error_rel,umin = coloring->umin,unorm;
514   Vec            w1=coloring->w1,w2=coloring->w2,w3;
515   void           *fctx = coloring->fctx;
516   PetscTruth     flg = PETSC_FALSE;
517   PetscInt       ctype=coloring->ctype,N,col_start=0,col_end=0;
518   Vec            x1_tmp;
519 
520   PetscFunctionBegin;
521   PetscValidHeaderSpecific(J,MAT_COOKIE,1);
522   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE,2);
523   PetscValidHeaderSpecific(x1,VEC_COOKIE,3);
524   if (!f) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,"Must call MatFDColoringSetFunction()");
525 
526   ierr = PetscLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
527   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
528   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&flg,PETSC_NULL);CHKERRQ(ierr);
529   if (flg) {
530     ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr);
531   } else {
532     PetscTruth assembled;
533     ierr = MatAssembled(J,&assembled);CHKERRQ(ierr);
534     if (assembled) {
535       ierr = MatZeroEntries(J);CHKERRQ(ierr);
536     }
537   }
538 
539   x1_tmp = x1;
540   if (!coloring->vscale){
541     ierr = VecDuplicate(x1_tmp,&coloring->vscale);CHKERRQ(ierr);
542   }
543 
544   /*
545     This is a horrible, horrible, hack. See DMMGComputeJacobian_Multigrid() it inproperly sets
546     coloring->F for the coarser grids from the finest
547   */
548   if (coloring->F) {
549     ierr = VecGetLocalSize(coloring->F,&m1);CHKERRQ(ierr);
550     ierr = VecGetLocalSize(w1,&m2);CHKERRQ(ierr);
551     if (m1 != m2) {
552       coloring->F = 0;
553       }
554     }
555 
556   if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/
557     ierr = VecNorm(x1_tmp,NORM_2,&unorm);CHKERRQ(ierr);
558   }
559   ierr = VecGetOwnershipRange(w1,&start,&end);CHKERRQ(ierr); /* OwnershipRange is used by ghosted x! */
560 
561   /* Set w1 = F(x1) */
562   if (coloring->F) {
563     w1          = coloring->F; /* use already computed value of function */
564     coloring->F = 0;
565   } else {
566     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
567     ierr = (*f)(sctx,x1_tmp,w1,fctx);CHKERRQ(ierr);
568     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
569   }
570 
571   if (!coloring->w3) {
572     ierr = VecDuplicate(x1_tmp,&coloring->w3);CHKERRQ(ierr);
573     ierr = PetscLogObjectParent(coloring,coloring->w3);CHKERRQ(ierr);
574   }
575   w3 = coloring->w3;
576 
577     /* Compute all the local scale factors, including ghost points */
578   ierr = VecGetLocalSize(x1_tmp,&N);CHKERRQ(ierr);
579   ierr = VecGetArray(x1_tmp,&xx);CHKERRQ(ierr);
580   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
581   if (ctype == IS_COLORING_GHOSTED){
582     col_start = 0; col_end = N;
583   } else if (ctype == IS_COLORING_GLOBAL){
584     xx = xx - start;
585     vscale_array = vscale_array - start;
586     col_start = start; col_end = N + start;
587   }
588   for (col=col_start; col<col_end; col++){
589     /* Loop over each local column, vscale[col] = 1./(epsilon*dx[col]) */
590     if (coloring->htype[0] == 'w') {
591       dx = 1.0 + unorm;
592     } else {
593       dx  = xx[col];
594     }
595     if (dx == 0.0) dx = 1.0;
596 #if !defined(PETSC_USE_COMPLEX)
597     if (dx < umin && dx >= 0.0)      dx = umin;
598     else if (dx < 0.0 && dx > -umin) dx = -umin;
599 #else
600     if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
601     else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
602 #endif
603     dx               *= epsilon;
604     vscale_array[col] = 1.0/dx;
605   }
606   if (ctype == IS_COLORING_GLOBAL)  vscale_array = vscale_array + start;
607   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
608   if (ctype == IS_COLORING_GLOBAL){
609     ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
610     ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
611   }
612 
613   if (coloring->vscaleforrow) {
614     vscaleforrow = coloring->vscaleforrow;
615   } else {
616     SETERRQ(PETSC_ERR_ARG_NULL,"Null Object: coloring->vscaleforrow");
617   }
618 
619   /*
620     Loop over each color
621   */
622   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
623   for (k=0; k<coloring->ncolors; k++) {
624     coloring->currentcolor = k;
625     ierr = VecCopy(x1_tmp,w3);CHKERRQ(ierr);
626     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);
627     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array - start;
628     /*
629       Loop over each column associated with color
630       adding the perturbation to the vector w3.
631     */
632     for (l=0; l<coloring->ncolumns[k]; l++) {
633       col = coloring->columns[k][l];    /* local column of the matrix we are probing for */
634       if (coloring->htype[0] == 'w') {
635         dx = 1.0 + unorm;
636       } else {
637         dx  = xx[col];
638       }
639       if (dx == 0.0) dx = 1.0;
640 #if !defined(PETSC_USE_COMPLEX)
641       if (dx < umin && dx >= 0.0)      dx = umin;
642       else if (dx < 0.0 && dx > -umin) dx = -umin;
643 #else
644       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
645       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
646 #endif
647       dx            *= epsilon;
648       if (!PetscAbsScalar(dx)) SETERRQ(PETSC_ERR_PLIB,"Computed 0 differencing parameter");
649       w3_array[col] += dx;
650     }
651     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array + start;
652     ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
653 
654     /*
655       Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations)
656                            w2 = F(x1 + dx) - F(x1)
657     */
658     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
659     ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
660     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
661     ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
662 
663     /*
664       Loop over rows of vector, putting results into Jacobian matrix
665     */
666     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
667     for (l=0; l<coloring->nrows[k]; l++) {
668       row    = coloring->rows[k][l];             /* local row index */
669       col    = coloring->columnsforrow[k][l];    /* global column index */
670       y[row] *= vscale_array[vscaleforrow[k][l]];
671       srow   = row + start;
672       ierr   = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr);
673     }
674     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
675   } /* endof for each color */
676   if (ctype == IS_COLORING_GLOBAL) xx = xx + start;
677   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
678   ierr = VecRestoreArray(x1_tmp,&xx);CHKERRQ(ierr);
679 
680   coloring->currentcolor = -1;
681   ierr  = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
682   ierr  = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
683   ierr = PetscLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
684 
685   flg  = PETSC_FALSE;
686   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_null_space_test",&flg,PETSC_NULL);CHKERRQ(ierr);
687   if (flg) {
688     ierr = MatNullSpaceTest(J->nullsp,J,PETSC_NULL);CHKERRQ(ierr);
689   }
690   ierr = MatFDColoringView_Private(coloring);CHKERRQ(ierr);
691   PetscFunctionReturn(0);
692 }
693 
694 #undef __FUNCT__
695 #define __FUNCT__ "MatFDColoringApplyTS"
696 /*@
697     MatFDColoringApplyTS - Given a matrix for which a MatFDColoring context
698     has been created, computes the Jacobian for a function via finite differences.
699 
700    Collective on Mat, MatFDColoring, and Vec
701 
702     Input Parameters:
703 +   mat - location to store Jacobian
704 .   coloring - coloring context created with MatFDColoringCreate()
705 .   x1 - location at which Jacobian is to be computed
706 -   sctx - context required by function, if this is being used with the TS solver then it is TS object, otherwise it is null
707 
708    Level: intermediate
709 
710 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringSetFunction()
711 
712 .keywords: coloring, Jacobian, finite differences
713 @*/
714 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApplyTS(Mat J,MatFDColoring coloring,PetscReal t,Vec x1,MatStructure *flag,void *sctx)
715 {
716   PetscErrorCode (*f)(void*,PetscReal,Vec,Vec,void*)=(PetscErrorCode (*)(void*,PetscReal,Vec,Vec,void *))coloring->f;
717   PetscErrorCode ierr;
718   PetscInt       k,N,start,end,l,row,col,srow,**vscaleforrow;
719   PetscScalar    dx,*y,*xx,*w3_array;
720   PetscScalar    *vscale_array;
721   PetscReal      epsilon = coloring->error_rel,umin = coloring->umin;
722   Vec            w1=coloring->w1,w2=coloring->w2,w3;
723   void           *fctx = coloring->fctx;
724   PetscTruth     flg;
725 
726   PetscFunctionBegin;
727   PetscValidHeaderSpecific(J,MAT_COOKIE,1);
728   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_COOKIE,2);
729   PetscValidHeaderSpecific(x1,VEC_COOKIE,4);
730 
731   ierr = PetscLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
732   if (!coloring->w3) {
733     ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr);
734     ierr = PetscLogObjectParent(coloring,coloring->w3);CHKERRQ(ierr);
735   }
736   w3 = coloring->w3;
737 
738   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
739   flg  = PETSC_FALSE;
740   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&flg,PETSC_NULL);CHKERRQ(ierr);
741   if (flg) {
742     ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr);
743   } else {
744     PetscTruth assembled;
745     ierr = MatAssembled(J,&assembled);CHKERRQ(ierr);
746     if (assembled) {
747       ierr = MatZeroEntries(J);CHKERRQ(ierr);
748     }
749   }
750 
751   ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr);
752   ierr = VecGetSize(x1,&N);CHKERRQ(ierr);
753   ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
754   ierr = (*f)(sctx,t,x1,w1,fctx);CHKERRQ(ierr);
755   ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
756 
757   /*
758       Compute all the scale factors and share with other processors
759   */
760   ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start;
761   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start;
762   for (k=0; k<coloring->ncolors; k++) {
763     /*
764        Loop over each column associated with color adding the
765        perturbation to the vector w3.
766     */
767     for (l=0; l<coloring->ncolumns[k]; l++) {
768       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
769       dx  = xx[col];
770       if (dx == 0.0) dx = 1.0;
771 #if !defined(PETSC_USE_COMPLEX)
772       if (dx < umin && dx >= 0.0)      dx = umin;
773       else if (dx < 0.0 && dx > -umin) dx = -umin;
774 #else
775       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
776       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
777 #endif
778       dx                *= epsilon;
779       vscale_array[col] = 1.0/dx;
780     }
781   }
782   vscale_array = vscale_array - start;ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
783   ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
784   ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
785 
786   if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow;
787   else                        vscaleforrow = coloring->columnsforrow;
788 
789   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
790   /*
791       Loop over each color
792   */
793   for (k=0; k<coloring->ncolors; k++) {
794     ierr = VecCopy(x1,w3);CHKERRQ(ierr);
795     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start;
796     /*
797        Loop over each column associated with color adding the
798        perturbation to the vector w3.
799     */
800     for (l=0; l<coloring->ncolumns[k]; l++) {
801       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
802       dx  = xx[col];
803       if (dx == 0.0) dx = 1.0;
804 #if !defined(PETSC_USE_COMPLEX)
805       if (dx < umin && dx >= 0.0)      dx = umin;
806       else if (dx < 0.0 && dx > -umin) dx = -umin;
807 #else
808       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
809       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
810 #endif
811       dx            *= epsilon;
812       w3_array[col] += dx;
813     }
814     w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
815 
816     /*
817        Evaluate function at x1 + dx (here dx is a vector of perturbations)
818     */
819     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
820     ierr = (*f)(sctx,t,w3,w2,fctx);CHKERRQ(ierr);
821     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
822     ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
823 
824     /*
825        Loop over rows of vector, putting results into Jacobian matrix
826     */
827     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
828     for (l=0; l<coloring->nrows[k]; l++) {
829       row    = coloring->rows[k][l];
830       col    = coloring->columnsforrow[k][l];
831       y[row] *= vscale_array[vscaleforrow[k][l]];
832       srow   = row + start;
833       ierr   = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr);
834     }
835     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
836   }
837   ierr  = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
838   xx    = xx + start; ierr  = VecRestoreArray(x1,&xx);CHKERRQ(ierr);
839   ierr  = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
840   ierr  = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
841   ierr  = PetscLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
842   PetscFunctionReturn(0);
843 }
844 
845 
846 
847