xref: /petsc/src/mat/matfd/fdmatrix.c (revision 5a586d828132823a7f656d0d7f79985f923612fa)
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_CLASSID,1);
104   if (!viewer) {
105     ierr = PetscViewerASCIIGetStdout(((PetscObject)c)->comm,&viewer);CHKERRQ(ierr);
106   }
107   PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2);
108   PetscCheckSameComm(c,1,viewer,2);
109 
110   ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
111   ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&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_COMM_SELF,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(), MatFDColoringSetFromOptions()
167 
168 @*/
169 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringSetParameters(MatFDColoring matfd,PetscReal error,PetscReal umin)
170 {
171   PetscFunctionBegin;
172   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
173 
174   if (error != PETSC_DEFAULT) matfd->error_rel = error;
175   if (umin != PETSC_DEFAULT)  matfd->umin      = umin;
176   PetscFunctionReturn(0);
177 }
178 
179 
180 
181 #undef __FUNCT__
182 #define __FUNCT__ "MatFDColoringGetFunction"
183 /*@C
184    MatFDColoringGetFunction - Gets the function to use for computing the Jacobian.
185 
186    Collective on MatFDColoring
187 
188    Input Parameters:
189 .  coloring - the coloring context
190 
191    Output Parameters:
192 +  f - the function
193 -  fctx - the optional user-defined function context
194 
195    Level: intermediate
196 
197 .keywords: Mat, Jacobian, finite differences, set, function
198 
199 .seealso: MatFDColoringCreate(), MatFDColoringSetFunction(), MatFDColoringSetFromOptions()
200 
201 @*/
202 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringGetFunction(MatFDColoring matfd,PetscErrorCode (**f)(void),void **fctx)
203 {
204   PetscFunctionBegin;
205   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
206   if (f) *f = matfd->f;
207   if (fctx) *fctx = matfd->fctx;
208   PetscFunctionReturn(0);
209 }
210 
211 #undef __FUNCT__
212 #define __FUNCT__ "MatFDColoringSetFunction"
213 /*@C
214    MatFDColoringSetFunction - Sets the function to use for computing the Jacobian.
215 
216    Collective on MatFDColoring
217 
218    Input Parameters:
219 +  coloring - the coloring context
220 .  f - the function
221 -  fctx - the optional user-defined function context
222 
223    Calling sequence of (*f) function:
224     For SNES:    PetscErrorCode (*f)(SNES,Vec,Vec,void*)
225     For TS:      PetscErrorCode (*f)(TS,PetscReal,Vec,Vec,void*)
226     If not using SNES or TS: PetscErrorCode (*f)(void *dummy,Vec,Vec,void*) and dummy is ignored
227 
228    Level: advanced
229 
230    Notes: This function is usually used automatically by SNES or TS (when one uses SNESSetJacobian() with the argument
231      SNESDefaultComputeJacobianColor() or TSSetRHSJacobian() with the argument TSDefaultComputeJacobianColor()) and only needs to be used
232      by someone computing a matrix via coloring directly by calling MatFDColoringApply()
233 
234    Fortran Notes:
235     In Fortran you must call MatFDColoringSetFunction() for a coloring object to
236   be used without SNES or TS or within the SNES solvers and MatFDColoringSetFunctionTS() if it is to be used
237   within the TS solvers.
238 
239 .keywords: Mat, Jacobian, finite differences, set, function
240 
241 .seealso: MatFDColoringCreate(), MatFDColoringGetFunction(), MatFDColoringSetFromOptions()
242 
243 @*/
244 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringSetFunction(MatFDColoring matfd,PetscErrorCode (*f)(void),void *fctx)
245 {
246   PetscFunctionBegin;
247   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
248   matfd->f    = f;
249   matfd->fctx = fctx;
250   PetscFunctionReturn(0);
251 }
252 
253 #undef __FUNCT__
254 #define __FUNCT__ "MatFDColoringSetFromOptions"
255 /*@
256    MatFDColoringSetFromOptions - Sets coloring finite difference parameters from
257    the options database.
258 
259    Collective on MatFDColoring
260 
261    The Jacobian, F'(u), is estimated with the differencing approximation
262 .vb
263        F'(u)_{:,i} = [F(u+h*dx_{i}) - F(u)]/h where
264        h = error_rel*u[i]                 if  abs(u[i]) > umin
265          = +/- error_rel*umin             otherwise, with +/- determined by the sign of u[i]
266        dx_{i} = (0, ... 1, .... 0)
267 .ve
268 
269    Input Parameter:
270 .  coloring - the coloring context
271 
272    Options Database Keys:
273 +  -mat_fd_coloring_err <err> - Sets <err> (square root
274            of relative error in the function)
275 .  -mat_fd_coloring_umin <umin> - Sets umin, the minimum allowable u-value magnitude
276 .  -mat_fd_type - "wp" or "ds" (see MATMFFD_WP or MATMFFD_DS)
277 .  -mat_fd_coloring_view - Activates basic viewing
278 .  -mat_fd_coloring_view_info - Activates viewing info
279 -  -mat_fd_coloring_view_draw - Activates drawing
280 
281     Level: intermediate
282 
283 .keywords: Mat, finite differences, parameters
284 
285 .seealso: MatFDColoringCreate(), MatFDColoringView(), MatFDColoringSetParameters()
286 
287 @*/
288 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringSetFromOptions(MatFDColoring matfd)
289 {
290   PetscErrorCode ierr;
291   PetscTruth     flg;
292   char           value[3];
293 
294   PetscFunctionBegin;
295   PetscValidHeaderSpecific(matfd,MAT_FDCOLORING_CLASSID,1);
296 
297   ierr = PetscOptionsBegin(((PetscObject)matfd)->comm,((PetscObject)matfd)->prefix,"Jacobian computation via finite differences option","MatFD");CHKERRQ(ierr);
298     ierr = PetscOptionsReal("-mat_fd_coloring_err","Square root of relative error in function","MatFDColoringSetParameters",matfd->error_rel,&matfd->error_rel,0);CHKERRQ(ierr);
299     ierr = PetscOptionsReal("-mat_fd_coloring_umin","Minimum allowable u magnitude","MatFDColoringSetParameters",matfd->umin,&matfd->umin,0);CHKERRQ(ierr);
300     ierr = PetscOptionsString("-mat_fd_type","Algorithm to compute h, wp or ds","MatFDColoringCreate",matfd->htype,value,3,&flg);CHKERRQ(ierr);
301     if (flg) {
302       if (value[0] == 'w' && value[1] == 'p') matfd->htype = "wp";
303       else if (value[0] == 'd' && value[1] == 's') matfd->htype = "ds";
304       else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Unknown finite differencing type %s",value);
305     }
306     /* not used here; but so they are presented in the GUI */
307     ierr = PetscOptionsName("-mat_fd_coloring_view","Print entire datastructure used for Jacobian","None",0);CHKERRQ(ierr);
308     ierr = PetscOptionsName("-mat_fd_coloring_view_info","Print number of colors etc for Jacobian","None",0);CHKERRQ(ierr);
309     ierr = PetscOptionsName("-mat_fd_coloring_view_draw","Plot nonzero structure ofJacobian","None",0);CHKERRQ(ierr);
310   PetscOptionsEnd();CHKERRQ(ierr);
311   PetscFunctionReturn(0);
312 }
313 
314 #undef __FUNCT__
315 #define __FUNCT__ "MatFDColoringView_Private"
316 PetscErrorCode MatFDColoringView_Private(MatFDColoring fd)
317 {
318   PetscErrorCode ierr;
319   PetscTruth     flg = PETSC_FALSE;
320   PetscViewer    viewer;
321 
322   PetscFunctionBegin;
323   ierr = PetscViewerASCIIGetStdout(((PetscObject)fd)->comm,&viewer);CHKERRQ(ierr);
324   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_view",&flg,PETSC_NULL);CHKERRQ(ierr);
325   if (flg) {
326     ierr = MatFDColoringView(fd,viewer);CHKERRQ(ierr);
327   }
328   flg  = PETSC_FALSE;
329   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_view_info",&flg,PETSC_NULL);CHKERRQ(ierr);
330   if (flg) {
331     ierr = PetscViewerPushFormat(viewer,PETSC_VIEWER_ASCII_INFO);CHKERRQ(ierr);
332     ierr = MatFDColoringView(fd,viewer);CHKERRQ(ierr);
333     ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr);
334   }
335   flg  = PETSC_FALSE;
336   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_view_draw",&flg,PETSC_NULL);CHKERRQ(ierr);
337   if (flg) {
338     ierr = MatFDColoringView(fd,PETSC_VIEWER_DRAW_(((PetscObject)fd)->comm));CHKERRQ(ierr);
339     ierr = PetscViewerFlush(PETSC_VIEWER_DRAW_(((PetscObject)fd)->comm));CHKERRQ(ierr);
340   }
341   PetscFunctionReturn(0);
342 }
343 
344 #undef __FUNCT__
345 #define __FUNCT__ "MatFDColoringCreate"
346 /*@
347    MatFDColoringCreate - Creates a matrix coloring context for finite difference
348    computation of Jacobians.
349 
350    Collective on Mat
351 
352    Input Parameters:
353 +  mat - the matrix containing the nonzero structure of the Jacobian
354 -  iscoloring - the coloring of the matrix; usually obtained with MatGetColoring() or DAGetColoring()
355 
356     Output Parameter:
357 .   color - the new coloring context
358 
359     Level: intermediate
360 
361 .seealso: MatFDColoringDestroy(),SNESDefaultComputeJacobianColor(), ISColoringCreate(),
362           MatFDColoringSetFunction(), MatFDColoringSetFromOptions(), MatFDColoringApply(),
363           MatFDColoringView(), MatFDColoringSetParameters(), MatGetColoring(), DAGetColoring()
364 @*/
365 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringCreate(Mat mat,ISColoring iscoloring,MatFDColoring *color)
366 {
367   MatFDColoring  c;
368   MPI_Comm       comm;
369   PetscErrorCode ierr;
370   PetscInt       M,N;
371 
372   PetscFunctionBegin;
373   ierr = PetscLogEventBegin(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr);
374   ierr = MatGetSize(mat,&M,&N);CHKERRQ(ierr);
375   if (M != N) SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_SUP,"Only for square matrices");
376 
377   ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
378   ierr = PetscHeaderCreate(c,_p_MatFDColoring,int,MAT_FDCOLORING_CLASSID,0,"MatFDColoring",comm,MatFDColoringDestroy,MatFDColoringView);CHKERRQ(ierr);
379 
380   c->ctype = iscoloring->ctype;
381 
382   if (mat->ops->fdcoloringcreate) {
383     ierr = (*mat->ops->fdcoloringcreate)(mat,iscoloring,c);CHKERRQ(ierr);
384   } else SETERRQ(((PetscObject)mat)->comm,PETSC_ERR_SUP,"Code not yet written for this matrix type");
385 
386   ierr = MatGetVecs(mat,PETSC_NULL,&c->w1);CHKERRQ(ierr);
387   ierr = PetscLogObjectParent(c,c->w1);CHKERRQ(ierr);
388   ierr = VecDuplicate(c->w1,&c->w2);CHKERRQ(ierr);
389   ierr = PetscLogObjectParent(c,c->w2);CHKERRQ(ierr);
390 
391   c->error_rel         = PETSC_SQRT_MACHINE_EPSILON;
392   c->umin              = 100.0*PETSC_SQRT_MACHINE_EPSILON;
393   c->currentcolor      = -1;
394   c->htype             = "wp";
395 
396   *color = c;
397   ierr = PetscLogEventEnd(MAT_FDColoringCreate,mat,0,0,0);CHKERRQ(ierr);
398   PetscFunctionReturn(0);
399 }
400 
401 #undef __FUNCT__
402 #define __FUNCT__ "MatFDColoringDestroy"
403 /*@
404     MatFDColoringDestroy - Destroys a matrix coloring context that was created
405     via MatFDColoringCreate().
406 
407     Collective on MatFDColoring
408 
409     Input Parameter:
410 .   c - coloring context
411 
412     Level: intermediate
413 
414 .seealso: MatFDColoringCreate()
415 @*/
416 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringDestroy(MatFDColoring c)
417 {
418   PetscErrorCode ierr;
419   PetscInt       i;
420 
421   PetscFunctionBegin;
422   if (--((PetscObject)c)->refct > 0) PetscFunctionReturn(0);
423 
424   for (i=0; i<c->ncolors; i++) {
425     ierr = PetscFree(c->columns[i]);CHKERRQ(ierr);
426     ierr = PetscFree(c->rows[i]);CHKERRQ(ierr);
427     ierr = PetscFree(c->columnsforrow[i]);CHKERRQ(ierr);
428     if (c->vscaleforrow) {ierr = PetscFree(c->vscaleforrow[i]);CHKERRQ(ierr);}
429   }
430   ierr = PetscFree(c->ncolumns);CHKERRQ(ierr);
431   ierr = PetscFree(c->columns);CHKERRQ(ierr);
432   ierr = PetscFree(c->nrows);CHKERRQ(ierr);
433   ierr = PetscFree(c->rows);CHKERRQ(ierr);
434   ierr = PetscFree(c->columnsforrow);CHKERRQ(ierr);
435   ierr = PetscFree(c->vscaleforrow);CHKERRQ(ierr);
436   if (c->vscale)       {ierr = VecDestroy(c->vscale);CHKERRQ(ierr);}
437   if (c->w1) {
438     ierr = VecDestroy(c->w1);CHKERRQ(ierr);
439     ierr = VecDestroy(c->w2);CHKERRQ(ierr);
440   }
441   if (c->w3){
442     ierr = VecDestroy(c->w3);CHKERRQ(ierr);
443   }
444   ierr = PetscHeaderDestroy(c);CHKERRQ(ierr);
445   PetscFunctionReturn(0);
446 }
447 
448 #undef __FUNCT__
449 #define __FUNCT__ "MatFDColoringGetPerturbedColumns"
450 /*@C
451     MatFDColoringGetPerturbedColumns - Returns the indices of the columns that
452       that are currently being perturbed.
453 
454     Not Collective
455 
456     Input Parameters:
457 .   coloring - coloring context created with MatFDColoringCreate()
458 
459     Output Parameters:
460 +   n - the number of local columns being perturbed
461 -   cols - the column indices, in global numbering
462 
463    Level: intermediate
464 
465 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringApply()
466 
467 .keywords: coloring, Jacobian, finite differences
468 @*/
469 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringGetPerturbedColumns(MatFDColoring coloring,PetscInt *n,PetscInt *cols[])
470 {
471   PetscFunctionBegin;
472   if (coloring->currentcolor >= 0) {
473     *n    = coloring->ncolumns[coloring->currentcolor];
474     *cols = coloring->columns[coloring->currentcolor];
475   } else {
476     *n = 0;
477   }
478   PetscFunctionReturn(0);
479 }
480 
481 #undef __FUNCT__
482 #define __FUNCT__ "MatFDColoringApply"
483 /*@
484     MatFDColoringApply - Given a matrix for which a MatFDColoring context
485     has been created, computes the Jacobian for a function via finite differences.
486 
487     Collective on MatFDColoring
488 
489     Input Parameters:
490 +   mat - location to store Jacobian
491 .   coloring - coloring context created with MatFDColoringCreate()
492 .   x1 - location at which Jacobian is to be computed
493 -   sctx - context required by function, if this is being used with the SNES solver then it is SNES object, otherwise it is null
494 
495     Options Database Keys:
496 +    -mat_fd_type - "wp" or "ds"  (see MATMFFD_WP or MATMFFD_DS)
497 .    -mat_fd_coloring_view - Activates basic viewing or coloring
498 .    -mat_fd_coloring_view_draw - Activates drawing of coloring
499 -    -mat_fd_coloring_view_info - Activates viewing of coloring info
500 
501     Level: intermediate
502 
503 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringSetFunction()
504 
505 .keywords: coloring, Jacobian, finite differences
506 @*/
507 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApply(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx)
508 {
509   PetscErrorCode ierr;
510 
511   PetscFunctionBegin;
512   PetscValidHeaderSpecific(J,MAT_CLASSID,1);
513   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_CLASSID,2);
514   PetscValidHeaderSpecific(x1,VEC_CLASSID,3);
515   if (!coloring->f) SETERRQ(((PetscObject)J)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must call MatFDColoringSetFunction()");
516   if (!J->ops->fdcoloringapply) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not supported for this matrix type %s",((PetscObject)J)->type_name);
517   ierr = (*J->ops->fdcoloringapply)(J,coloring,x1,flag,sctx);CHKERRQ(ierr);
518   PetscFunctionReturn(0);
519 }
520 
521 #undef __FUNCT__
522 #define __FUNCT__ "MatFDColoringApply_AIJ"
523 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx)
524 {
525   PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void *))coloring->f;
526   PetscErrorCode ierr;
527   PetscInt       k,start,end,l,row,col,srow,**vscaleforrow,m1,m2;
528   PetscScalar    dx,*y,*xx,*w3_array;
529   PetscScalar    *vscale_array;
530   PetscReal      epsilon = coloring->error_rel,umin = coloring->umin,unorm;
531   Vec            w1=coloring->w1,w2=coloring->w2,w3;
532   void           *fctx = coloring->fctx;
533   PetscTruth     flg = PETSC_FALSE;
534   PetscInt       ctype=coloring->ctype,N,col_start=0,col_end=0;
535   Vec            x1_tmp;
536 
537   PetscFunctionBegin;
538   PetscValidHeaderSpecific(J,MAT_CLASSID,1);
539   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_CLASSID,2);
540   PetscValidHeaderSpecific(x1,VEC_CLASSID,3);
541   if (!f) SETERRQ(((PetscObject)J)->comm,PETSC_ERR_ARG_WRONGSTATE,"Must call MatFDColoringSetFunction()");
542 
543   ierr = PetscLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
544   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
545   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&flg,PETSC_NULL);CHKERRQ(ierr);
546   if (flg) {
547     ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr);
548   } else {
549     PetscTruth 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   /*
562     This is a horrible, horrible, hack. See DMMGComputeJacobian_Multigrid() it inproperly sets
563     coloring->F for the coarser grids from the finest
564   */
565   if (coloring->F) {
566     ierr = VecGetLocalSize(coloring->F,&m1);CHKERRQ(ierr);
567     ierr = VecGetLocalSize(w1,&m2);CHKERRQ(ierr);
568     if (m1 != m2) {
569       coloring->F = 0;
570       }
571     }
572 
573   if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/
574     ierr = VecNorm(x1_tmp,NORM_2,&unorm);CHKERRQ(ierr);
575   }
576   ierr = VecGetOwnershipRange(w1,&start,&end);CHKERRQ(ierr); /* OwnershipRange is used by ghosted x! */
577 
578   /* Set w1 = F(x1) */
579   if (coloring->F) {
580     w1          = coloring->F; /* use already computed value of function */
581     coloring->F = 0;
582   } else {
583     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
584     ierr = (*f)(sctx,x1_tmp,w1,fctx);CHKERRQ(ierr);
585     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
586   }
587 
588   if (!coloring->w3) {
589     ierr = VecDuplicate(x1_tmp,&coloring->w3);CHKERRQ(ierr);
590     ierr = PetscLogObjectParent(coloring,coloring->w3);CHKERRQ(ierr);
591   }
592   w3 = coloring->w3;
593 
594     /* Compute all the local scale factors, including ghost points */
595   ierr = VecGetLocalSize(x1_tmp,&N);CHKERRQ(ierr);
596   ierr = VecGetArray(x1_tmp,&xx);CHKERRQ(ierr);
597   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
598   if (ctype == IS_COLORING_GHOSTED){
599     col_start = 0; col_end = N;
600   } else if (ctype == IS_COLORING_GLOBAL){
601     xx = xx - start;
602     vscale_array = vscale_array - start;
603     col_start = start; col_end = N + start;
604   }
605   for (col=col_start; col<col_end; col++){
606     /* Loop over each local column, vscale[col] = 1./(epsilon*dx[col]) */
607     if (coloring->htype[0] == 'w') {
608       dx = 1.0 + unorm;
609     } else {
610       dx  = xx[col];
611     }
612     if (dx == 0.0) dx = 1.0;
613 #if !defined(PETSC_USE_COMPLEX)
614     if (dx < umin && dx >= 0.0)      dx = umin;
615     else if (dx < 0.0 && dx > -umin) dx = -umin;
616 #else
617     if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
618     else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
619 #endif
620     dx               *= epsilon;
621     vscale_array[col] = 1.0/dx;
622   }
623   if (ctype == IS_COLORING_GLOBAL)  vscale_array = vscale_array + start;
624   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
625   if (ctype == IS_COLORING_GLOBAL){
626     ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
627     ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
628   }
629 
630   if (coloring->vscaleforrow) {
631     vscaleforrow = coloring->vscaleforrow;
632   } else SETERRQ(((PetscObject)J)->comm,PETSC_ERR_ARG_NULL,"Null Object: coloring->vscaleforrow");
633 
634   /*
635     Loop over each color
636   */
637   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
638   for (k=0; k<coloring->ncolors; k++) {
639     coloring->currentcolor = k;
640     ierr = VecCopy(x1_tmp,w3);CHKERRQ(ierr);
641     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);
642     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array - start;
643     /*
644       Loop over each column associated with color
645       adding the perturbation to the vector w3.
646     */
647     for (l=0; l<coloring->ncolumns[k]; l++) {
648       col = coloring->columns[k][l];    /* local column of the matrix we are probing for */
649       if (coloring->htype[0] == 'w') {
650         dx = 1.0 + unorm;
651       } else {
652         dx  = xx[col];
653       }
654       if (dx == 0.0) dx = 1.0;
655 #if !defined(PETSC_USE_COMPLEX)
656       if (dx < umin && dx >= 0.0)      dx = umin;
657       else if (dx < 0.0 && dx > -umin) dx = -umin;
658 #else
659       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
660       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
661 #endif
662       dx            *= epsilon;
663       if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter");
664       w3_array[col] += dx;
665     }
666     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array + start;
667     ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
668 
669     /*
670       Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations)
671                            w2 = F(x1 + dx) - F(x1)
672     */
673     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
674     ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
675     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
676     ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
677 
678     /*
679       Loop over rows of vector, putting results into Jacobian matrix
680     */
681     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
682     for (l=0; l<coloring->nrows[k]; l++) {
683       row    = coloring->rows[k][l];             /* local row index */
684       col    = coloring->columnsforrow[k][l];    /* global column index */
685       y[row] *= vscale_array[vscaleforrow[k][l]];
686       srow   = row + start;
687       ierr   = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr);
688     }
689     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
690   } /* endof for each color */
691   if (ctype == IS_COLORING_GLOBAL) xx = xx + start;
692   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
693   ierr = VecRestoreArray(x1_tmp,&xx);CHKERRQ(ierr);
694 
695   coloring->currentcolor = -1;
696   ierr  = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
697   ierr  = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
698   ierr = PetscLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
699 
700   flg  = PETSC_FALSE;
701   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_null_space_test",&flg,PETSC_NULL);CHKERRQ(ierr);
702   if (flg) {
703     ierr = MatNullSpaceTest(J->nullsp,J,PETSC_NULL);CHKERRQ(ierr);
704   }
705   ierr = MatFDColoringView_Private(coloring);CHKERRQ(ierr);
706   PetscFunctionReturn(0);
707 }
708 
709 #undef __FUNCT__
710 #define __FUNCT__ "MatFDColoringApplyTS"
711 /*@
712     MatFDColoringApplyTS - Given a matrix for which a MatFDColoring context
713     has been created, computes the Jacobian for a function via finite differences.
714 
715    Collective on Mat, MatFDColoring, and Vec
716 
717     Input Parameters:
718 +   mat - location to store Jacobian
719 .   coloring - coloring context created with MatFDColoringCreate()
720 .   x1 - location at which Jacobian is to be computed
721 -   sctx - context required by function, if this is being used with the TS solver then it is TS object, otherwise it is null
722 
723    Level: intermediate
724 
725 .seealso: MatFDColoringCreate(), MatFDColoringDestroy(), MatFDColoringView(), MatFDColoringSetFunction()
726 
727 .keywords: coloring, Jacobian, finite differences
728 @*/
729 PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApplyTS(Mat J,MatFDColoring coloring,PetscReal t,Vec x1,MatStructure *flag,void *sctx)
730 {
731   PetscErrorCode (*f)(void*,PetscReal,Vec,Vec,void*)=(PetscErrorCode (*)(void*,PetscReal,Vec,Vec,void *))coloring->f;
732   PetscErrorCode ierr;
733   PetscInt       k,N,start,end,l,row,col,srow,**vscaleforrow;
734   PetscScalar    dx,*y,*xx,*w3_array;
735   PetscScalar    *vscale_array;
736   PetscReal      epsilon = coloring->error_rel,umin = coloring->umin;
737   Vec            w1=coloring->w1,w2=coloring->w2,w3;
738   void           *fctx = coloring->fctx;
739   PetscTruth     flg;
740 
741   PetscFunctionBegin;
742   PetscValidHeaderSpecific(J,MAT_CLASSID,1);
743   PetscValidHeaderSpecific(coloring,MAT_FDCOLORING_CLASSID,2);
744   PetscValidHeaderSpecific(x1,VEC_CLASSID,4);
745 
746   ierr = PetscLogEventBegin(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
747   if (!coloring->w3) {
748     ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr);
749     ierr = PetscLogObjectParent(coloring,coloring->w3);CHKERRQ(ierr);
750   }
751   w3 = coloring->w3;
752 
753   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
754   flg  = PETSC_FALSE;
755   ierr = PetscOptionsGetTruth(PETSC_NULL,"-mat_fd_coloring_dont_rezero",&flg,PETSC_NULL);CHKERRQ(ierr);
756   if (flg) {
757     ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr);
758   } else {
759     PetscTruth assembled;
760     ierr = MatAssembled(J,&assembled);CHKERRQ(ierr);
761     if (assembled) {
762       ierr = MatZeroEntries(J);CHKERRQ(ierr);
763     }
764   }
765 
766   ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr);
767   ierr = VecGetSize(x1,&N);CHKERRQ(ierr);
768   ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
769   ierr = (*f)(sctx,t,x1,w1,fctx);CHKERRQ(ierr);
770   ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
771 
772   /*
773       Compute all the scale factors and share with other processors
774   */
775   ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start;
776   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start;
777   for (k=0; k<coloring->ncolors; k++) {
778     /*
779        Loop over each column associated with color adding the
780        perturbation to the vector w3.
781     */
782     for (l=0; l<coloring->ncolumns[k]; l++) {
783       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
784       dx  = xx[col];
785       if (dx == 0.0) dx = 1.0;
786 #if !defined(PETSC_USE_COMPLEX)
787       if (dx < umin && dx >= 0.0)      dx = umin;
788       else if (dx < 0.0 && dx > -umin) dx = -umin;
789 #else
790       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
791       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
792 #endif
793       dx                *= epsilon;
794       vscale_array[col] = 1.0/dx;
795     }
796   }
797   vscale_array = vscale_array - start;ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
798   ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
799   ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
800 
801   if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow;
802   else                        vscaleforrow = coloring->columnsforrow;
803 
804   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
805   /*
806       Loop over each color
807   */
808   for (k=0; k<coloring->ncolors; k++) {
809     ierr = VecCopy(x1,w3);CHKERRQ(ierr);
810     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start;
811     /*
812        Loop over each column associated with color adding the
813        perturbation to the vector w3.
814     */
815     for (l=0; l<coloring->ncolumns[k]; l++) {
816       col = coloring->columns[k][l];    /* column of the matrix we are probing for */
817       dx  = xx[col];
818       if (dx == 0.0) dx = 1.0;
819 #if !defined(PETSC_USE_COMPLEX)
820       if (dx < umin && dx >= 0.0)      dx = umin;
821       else if (dx < 0.0 && dx > -umin) dx = -umin;
822 #else
823       if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0)     dx = umin;
824       else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin;
825 #endif
826       dx            *= epsilon;
827       w3_array[col] += dx;
828     }
829     w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
830 
831     /*
832        Evaluate function at x1 + dx (here dx is a vector of perturbations)
833     */
834     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
835     ierr = (*f)(sctx,t,w3,w2,fctx);CHKERRQ(ierr);
836     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
837     ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
838 
839     /*
840        Loop over rows of vector, putting results into Jacobian matrix
841     */
842     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
843     for (l=0; l<coloring->nrows[k]; l++) {
844       row    = coloring->rows[k][l];
845       col    = coloring->columnsforrow[k][l];
846       y[row] *= vscale_array[vscaleforrow[k][l]];
847       srow   = row + start;
848       ierr   = MatSetValues(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr);
849     }
850     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
851   }
852   ierr  = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
853   xx    = xx + start; ierr  = VecRestoreArray(x1,&xx);CHKERRQ(ierr);
854   ierr  = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
855   ierr  = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
856   ierr  = PetscLogEventEnd(MAT_FDColoringApply,coloring,J,x1,0);CHKERRQ(ierr);
857   PetscFunctionReturn(0);
858 }
859 
860 
861 
862