1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: aij.c,v 1.319 1999/04/19 22:11:59 bsmith Exp bsmith $"; 3 #endif 4 5 /* 6 Defines the basic matrix operations for the AIJ (compressed row) 7 matrix storage format. 8 */ 9 10 #include "sys.h" 11 #include "src/mat/impls/aij/seq/aij.h" 12 #include "src/vec/vecimpl.h" 13 #include "src/inline/spops.h" 14 #include "src/inline/dot.h" 15 #include "bitarray.h" 16 17 /* 18 Basic AIJ format ILU based on drop tolerance 19 */ 20 #undef __FUNC__ 21 #define __FUNC__ "MatILUDTFactor_SeqAIJ" 22 int MatILUDTFactor_SeqAIJ(Mat A,double dt,int maxnz,IS row,IS col,Mat *fact) 23 { 24 /* Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; */ 25 26 PetscFunctionBegin; 27 SETERRQ(1,0,"Not implemented"); 28 #if !defined(USE_PETSC_DEBUG) 29 PetscFunctionReturn(0); 30 #endif 31 } 32 33 extern int MatToSymmetricIJ_SeqAIJ(int,int*,int*,int,int,int**,int**); 34 35 #undef __FUNC__ 36 #define __FUNC__ "MatGetRowIJ_SeqAIJ" 37 int MatGetRowIJ_SeqAIJ(Mat A,int oshift,PetscTruth symmetric,int *m,int **ia,int **ja, 38 PetscTruth *done) 39 { 40 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 41 int ierr,i,ishift; 42 43 PetscFunctionBegin; 44 *m = A->m; 45 if (!ia) PetscFunctionReturn(0); 46 ishift = a->indexshift; 47 if (symmetric) { 48 ierr = MatToSymmetricIJ_SeqAIJ(a->m,a->i,a->j,ishift,oshift,ia,ja); CHKERRQ(ierr); 49 } else if (oshift == 0 && ishift == -1) { 50 int nz = a->i[a->m]; 51 /* malloc space and subtract 1 from i and j indices */ 52 *ia = (int *) PetscMalloc( (a->m+1)*sizeof(int) ); CHKPTRQ(*ia); 53 *ja = (int *) PetscMalloc( (nz+1)*sizeof(int) ); CHKPTRQ(*ja); 54 for ( i=0; i<nz; i++ ) (*ja)[i] = a->j[i] - 1; 55 for ( i=0; i<a->m+1; i++ ) (*ia)[i] = a->i[i] - 1; 56 } else if (oshift == 1 && ishift == 0) { 57 int nz = a->i[a->m] + 1; 58 /* malloc space and add 1 to i and j indices */ 59 *ia = (int *) PetscMalloc( (a->m+1)*sizeof(int) ); CHKPTRQ(*ia); 60 *ja = (int *) PetscMalloc( (nz+1)*sizeof(int) ); CHKPTRQ(*ja); 61 for ( i=0; i<nz; i++ ) (*ja)[i] = a->j[i] + 1; 62 for ( i=0; i<a->m+1; i++ ) (*ia)[i] = a->i[i] + 1; 63 } else { 64 *ia = a->i; *ja = a->j; 65 } 66 67 PetscFunctionReturn(0); 68 } 69 70 #undef __FUNC__ 71 #define __FUNC__ "MatRestoreRowIJ_SeqAIJ" 72 int MatRestoreRowIJ_SeqAIJ(Mat A,int oshift,PetscTruth symmetric,int *n,int **ia,int **ja, 73 PetscTruth *done) 74 { 75 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 76 int ishift = a->indexshift; 77 78 PetscFunctionBegin; 79 if (!ia) PetscFunctionReturn(0); 80 if (symmetric || (oshift == 0 && ishift == -1) || (oshift == 1 && ishift == 0)) { 81 PetscFree(*ia); 82 PetscFree(*ja); 83 } 84 PetscFunctionReturn(0); 85 } 86 87 #undef __FUNC__ 88 #define __FUNC__ "MatGetColumnIJ_SeqAIJ" 89 int MatGetColumnIJ_SeqAIJ(Mat A,int oshift,PetscTruth symmetric,int *nn,int **ia,int **ja, 90 PetscTruth *done) 91 { 92 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 93 int ierr,i,ishift = a->indexshift,*collengths,*cia,*cja,n = A->n,m = A->m; 94 int nz = a->i[m]+ishift,row,*jj,mr,col; 95 96 PetscFunctionBegin; 97 *nn = A->n; 98 if (!ia) PetscFunctionReturn(0); 99 if (symmetric) { 100 ierr = MatToSymmetricIJ_SeqAIJ(a->m,a->i,a->j,ishift,oshift,ia,ja); CHKERRQ(ierr); 101 } else { 102 collengths = (int *) PetscMalloc( (n+1)*sizeof(int) ); CHKPTRQ(collengths); 103 PetscMemzero(collengths,n*sizeof(int)); 104 cia = (int *) PetscMalloc( (n+1)*sizeof(int) ); CHKPTRQ(cia); 105 cja = (int *) PetscMalloc( (nz+1)*sizeof(int) ); CHKPTRQ(cja); 106 jj = a->j; 107 for ( i=0; i<nz; i++ ) { 108 collengths[jj[i] + ishift]++; 109 } 110 cia[0] = oshift; 111 for ( i=0; i<n; i++) { 112 cia[i+1] = cia[i] + collengths[i]; 113 } 114 PetscMemzero(collengths,n*sizeof(int)); 115 jj = a->j; 116 for ( row=0; row<m; row++ ) { 117 mr = a->i[row+1] - a->i[row]; 118 for ( i=0; i<mr; i++ ) { 119 col = *jj++ + ishift; 120 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 121 } 122 } 123 PetscFree(collengths); 124 *ia = cia; *ja = cja; 125 } 126 127 PetscFunctionReturn(0); 128 } 129 130 #undef __FUNC__ 131 #define __FUNC__ "MatRestoreColumnIJ_SeqAIJ" 132 int MatRestoreColumnIJ_SeqAIJ(Mat A,int oshift,PetscTruth symmetric,int *n,int **ia, 133 int **ja,PetscTruth *done) 134 { 135 PetscFunctionBegin; 136 if (!ia) PetscFunctionReturn(0); 137 138 PetscFree(*ia); 139 PetscFree(*ja); 140 141 PetscFunctionReturn(0); 142 } 143 144 #define CHUNKSIZE 15 145 146 #undef __FUNC__ 147 #define __FUNC__ "MatSetValues_SeqAIJ" 148 int MatSetValues_SeqAIJ(Mat A,int m,int *im,int n,int *in,Scalar *v,InsertMode is) 149 { 150 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 151 int *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax, N, sorted = a->sorted; 152 int *imax = a->imax, *ai = a->i, *ailen = a->ilen,roworiented = a->roworiented; 153 int *aj = a->j, nonew = a->nonew,shift = a->indexshift; 154 Scalar *ap,value, *aa = a->a; 155 156 PetscFunctionBegin; 157 for ( k=0; k<m; k++ ) { /* loop over added rows */ 158 row = im[k]; 159 if (row < 0) continue; 160 #if defined(USE_PETSC_BOPT_g) 161 if (row >= a->m) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large: row %d max %d",row,a->m); 162 #endif 163 rp = aj + ai[row] + shift; ap = aa + ai[row] + shift; 164 rmax = imax[row]; nrow = ailen[row]; 165 low = 0; 166 for ( l=0; l<n; l++ ) { /* loop over added columns */ 167 if (in[l] < 0) continue; 168 #if defined(USE_PETSC_BOPT_g) 169 if (in[l] >= a->n) SETERRQ2(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large: col %d max %d",in[l],a->n); 170 #endif 171 col = in[l] - shift; 172 if (roworiented) { 173 value = v[l + k*n]; 174 } else { 175 value = v[k + l*m]; 176 } 177 if (!sorted) low = 0; high = nrow; 178 while (high-low > 5) { 179 t = (low+high)/2; 180 if (rp[t] > col) high = t; 181 else low = t; 182 } 183 for ( i=low; i<high; i++ ) { 184 if (rp[i] > col) break; 185 if (rp[i] == col) { 186 if (is == ADD_VALUES) ap[i] += value; 187 else ap[i] = value; 188 goto noinsert; 189 } 190 } 191 if (nonew == 1) goto noinsert; 192 else if (nonew == -1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); 193 if (nrow >= rmax) { 194 /* there is no extra room in row, therefore enlarge */ 195 int new_nz = ai[a->m] + CHUNKSIZE,len,*new_i,*new_j; 196 Scalar *new_a; 197 198 if (nonew == -2) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Inserting a new nonzero in the matrix"); 199 200 /* malloc new storage space */ 201 len = new_nz*(sizeof(int)+sizeof(Scalar))+(a->m+1)*sizeof(int); 202 new_a = (Scalar *) PetscMalloc( len ); CHKPTRQ(new_a); 203 new_j = (int *) (new_a + new_nz); 204 new_i = new_j + new_nz; 205 206 /* copy over old data into new slots */ 207 for ( ii=0; ii<row+1; ii++ ) {new_i[ii] = ai[ii];} 208 for ( ii=row+1; ii<a->m+1; ii++ ) {new_i[ii] = ai[ii]+CHUNKSIZE;} 209 PetscMemcpy(new_j,aj,(ai[row]+nrow+shift)*sizeof(int)); 210 len = (new_nz - CHUNKSIZE - ai[row] - nrow - shift); 211 PetscMemcpy(new_j+ai[row]+shift+nrow+CHUNKSIZE,aj+ai[row]+shift+nrow,len*sizeof(int)); 212 PetscMemcpy(new_a,aa,(ai[row]+nrow+shift)*sizeof(Scalar)); 213 PetscMemcpy(new_a+ai[row]+shift+nrow+CHUNKSIZE,aa+ai[row]+shift+nrow,len*sizeof(Scalar)); 214 /* free up old matrix storage */ 215 PetscFree(a->a); 216 if (!a->singlemalloc) {PetscFree(a->i);PetscFree(a->j);} 217 aa = a->a = new_a; ai = a->i = new_i; aj = a->j = new_j; 218 a->singlemalloc = 1; 219 220 rp = aj + ai[row] + shift; ap = aa + ai[row] + shift; 221 rmax = imax[row] = imax[row] + CHUNKSIZE; 222 PLogObjectMemory(A,CHUNKSIZE*(sizeof(int) + sizeof(Scalar))); 223 a->maxnz += CHUNKSIZE; 224 a->reallocs++; 225 } 226 N = nrow++ - 1; a->nz++; 227 /* shift up all the later entries in this row */ 228 for ( ii=N; ii>=i; ii-- ) { 229 rp[ii+1] = rp[ii]; 230 ap[ii+1] = ap[ii]; 231 } 232 rp[i] = col; 233 ap[i] = value; 234 noinsert:; 235 low = i + 1; 236 } 237 ailen[row] = nrow; 238 } 239 PetscFunctionReturn(0); 240 } 241 242 #undef __FUNC__ 243 #define __FUNC__ "MatGetValues_SeqAIJ" 244 int MatGetValues_SeqAIJ(Mat A,int m,int *im,int n,int *in,Scalar *v) 245 { 246 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 247 int *rp, k, low, high, t, row, nrow, i, col, l, *aj = a->j; 248 int *ai = a->i, *ailen = a->ilen, shift = a->indexshift; 249 Scalar *ap, *aa = a->a, zero = 0.0; 250 251 PetscFunctionBegin; 252 for ( k=0; k<m; k++ ) { /* loop over rows */ 253 row = im[k]; 254 if (row < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative row"); 255 if (row >= a->m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row too large"); 256 rp = aj + ai[row] + shift; ap = aa + ai[row] + shift; 257 nrow = ailen[row]; 258 for ( l=0; l<n; l++ ) { /* loop over columns */ 259 if (in[l] < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Negative column"); 260 if (in[l] >= a->n) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Column too large"); 261 col = in[l] - shift; 262 high = nrow; low = 0; /* assume unsorted */ 263 while (high-low > 5) { 264 t = (low+high)/2; 265 if (rp[t] > col) high = t; 266 else low = t; 267 } 268 for ( i=low; i<high; i++ ) { 269 if (rp[i] > col) break; 270 if (rp[i] == col) { 271 *v++ = ap[i]; 272 goto finished; 273 } 274 } 275 *v++ = zero; 276 finished:; 277 } 278 } 279 PetscFunctionReturn(0); 280 } 281 282 283 #undef __FUNC__ 284 #define __FUNC__ "MatView_SeqAIJ_Binary" 285 int MatView_SeqAIJ_Binary(Mat A,Viewer viewer) 286 { 287 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 288 int i, fd, *col_lens, ierr; 289 290 PetscFunctionBegin; 291 ierr = ViewerBinaryGetDescriptor(viewer,&fd); CHKERRQ(ierr); 292 col_lens = (int *) PetscMalloc( (4+a->m)*sizeof(int) ); CHKPTRQ(col_lens); 293 col_lens[0] = MAT_COOKIE; 294 col_lens[1] = a->m; 295 col_lens[2] = a->n; 296 col_lens[3] = a->nz; 297 298 /* store lengths of each row and write (including header) to file */ 299 for ( i=0; i<a->m; i++ ) { 300 col_lens[4+i] = a->i[i+1] - a->i[i]; 301 } 302 ierr = PetscBinaryWrite(fd,col_lens,4+a->m,PETSC_INT,1); CHKERRQ(ierr); 303 PetscFree(col_lens); 304 305 /* store column indices (zero start index) */ 306 if (a->indexshift) { 307 for ( i=0; i<a->nz; i++ ) a->j[i]--; 308 } 309 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,0); CHKERRQ(ierr); 310 if (a->indexshift) { 311 for ( i=0; i<a->nz; i++ ) a->j[i]++; 312 } 313 314 /* store nonzero values */ 315 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,0); CHKERRQ(ierr); 316 PetscFunctionReturn(0); 317 } 318 319 #undef __FUNC__ 320 #define __FUNC__ "MatView_SeqAIJ_ASCII" 321 int MatView_SeqAIJ_ASCII(Mat A,Viewer viewer) 322 { 323 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 324 int ierr, i,j, m = a->m, shift = a->indexshift, format, flg1,flg2; 325 FILE *fd; 326 char *outputname; 327 328 PetscFunctionBegin; 329 ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr); 330 ierr = ViewerGetOutputname(viewer,&outputname); CHKERRQ(ierr); 331 ierr = ViewerGetFormat(viewer,&format); 332 if (format == VIEWER_FORMAT_ASCII_INFO) { 333 PetscFunctionReturn(0); 334 } else if (format == VIEWER_FORMAT_ASCII_INFO_LONG) { 335 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_no_inode",&flg1); CHKERRQ(ierr); 336 ierr = OptionsHasName(PETSC_NULL,"-mat_no_unroll",&flg2); CHKERRQ(ierr); 337 if (flg1 || flg2) {ierr = ViewerASCIIPrintf(viewer," not using I-node routines\n");CHKERRQ(ierr);} 338 else {ierr = ViewerASCIIPrintf(viewer," using I-node routines: found %d nodes, limit used is %d\n",a->inode.node_count,a->inode.limit);CHKERRQ(ierr);} 339 } else if (format == VIEWER_FORMAT_ASCII_MATLAB) { 340 int nofinalvalue = 0; 341 if ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != a->n-!shift)) { 342 nofinalvalue = 1; 343 } 344 fprintf(fd,"%% Size = %d %d \n",m,a->n); 345 fprintf(fd,"%% Nonzeros = %d \n",a->nz); 346 fprintf(fd,"zzz = zeros(%d,3);\n",a->nz+nofinalvalue); 347 fprintf(fd,"zzz = [\n"); 348 349 for (i=0; i<m; i++) { 350 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 351 #if defined(USE_PETSC_COMPLEX) 352 fprintf(fd,"%d %d %18.16e + %18.16e i \n",i+1,a->j[j]+!shift,PetscReal(a->a[j]),PetscImaginary(a->a[j])); 353 #else 354 fprintf(fd,"%d %d %18.16e\n", i+1, a->j[j]+!shift, a->a[j]); 355 #endif 356 } 357 } 358 if (nofinalvalue) { 359 fprintf(fd,"%d %d %18.16e\n", m, a->n, 0.0); 360 } 361 if (outputname) fprintf(fd,"];\n %s = spconvert(zzz);\n",outputname); 362 else fprintf(fd,"];\n M = spconvert(zzz);\n"); 363 } else if (format == VIEWER_FORMAT_ASCII_COMMON) { 364 for ( i=0; i<m; i++ ) { 365 fprintf(fd,"row %d:",i); 366 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 367 #if defined(USE_PETSC_COMPLEX) 368 if (PetscImaginary(a->a[j]) > 0.0 && PetscReal(a->a[j]) != 0.0) 369 fprintf(fd," %d %g + %g i",a->j[j]+shift,PetscReal(a->a[j]),PetscImaginary(a->a[j])); 370 else if (PetscImaginary(a->a[j]) < 0.0 && PetscReal(a->a[j]) != 0.0) 371 fprintf(fd," %d %g - %g i",a->j[j]+shift,PetscReal(a->a[j]),-PetscImaginary(a->a[j])); 372 else if (PetscReal(a->a[j]) != 0.0) 373 fprintf(fd," %d %g ",a->j[j]+shift,PetscReal(a->a[j])); 374 #else 375 if (a->a[j] != 0.0) fprintf(fd," %d %g ",a->j[j]+shift,a->a[j]); 376 #endif 377 } 378 fprintf(fd,"\n"); 379 } 380 } else if (format == VIEWER_FORMAT_ASCII_SYMMODU) { 381 int nzd=0, fshift=1, *sptr; 382 sptr = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(sptr); 383 for ( i=0; i<m; i++ ) { 384 sptr[i] = nzd+1; 385 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 386 if (a->j[j] >= i) { 387 #if defined(USE_PETSC_COMPLEX) 388 if (PetscImaginary(a->a[j]) != 0.0 || PetscReal(a->a[j]) != 0.0) nzd++; 389 #else 390 if (a->a[j] != 0.0) nzd++; 391 #endif 392 } 393 } 394 } 395 sptr[m] = nzd+1; 396 fprintf(fd," %d %d\n\n",m,nzd); 397 for ( i=0; i<m+1; i+=6 ) { 398 if (i+4<m) fprintf(fd," %d %d %d %d %d %d\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4],sptr[i+5]); 399 else if (i+3<m) fprintf(fd," %d %d %d %d %d\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4]); 400 else if (i+2<m) fprintf(fd," %d %d %d %d\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]); 401 else if (i+1<m) fprintf(fd," %d %d %d\n",sptr[i],sptr[i+1],sptr[i+2]); 402 else if (i<m) fprintf(fd," %d %d\n",sptr[i],sptr[i+1]); 403 else fprintf(fd," %d\n",sptr[i]); 404 } 405 fprintf(fd,"\n"); 406 PetscFree(sptr); 407 for ( i=0; i<m; i++ ) { 408 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 409 if (a->j[j] >= i) fprintf(fd," %d ",a->j[j]+fshift); 410 } 411 fprintf(fd,"\n"); 412 } 413 fprintf(fd,"\n"); 414 for ( i=0; i<m; i++ ) { 415 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 416 if (a->j[j] >= i) { 417 #if defined(USE_PETSC_COMPLEX) 418 if (PetscImaginary(a->a[j]) != 0.0 || PetscReal(a->a[j]) != 0.0) 419 fprintf(fd," %18.16e %18.16e ",PetscReal(a->a[j]),PetscImaginary(a->a[j])); 420 #else 421 if (a->a[j] != 0.0) fprintf(fd," %18.16e ",a->a[j]); 422 #endif 423 } 424 } 425 fprintf(fd,"\n"); 426 } 427 } else if (format == VIEWER_FORMAT_ASCII_DENSE) { 428 int cnt = 0,jcnt; 429 Scalar value; 430 431 for ( i=0; i<m; i++ ) { 432 jcnt = 0; 433 for ( j=0; j<a->n; j++ ) { 434 if ( jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 435 value = a->a[cnt++]; 436 jcnt++; 437 } else { 438 value = 0.0; 439 } 440 #if defined(USE_PETSC_COMPLEX) 441 fprintf(fd," %7.5e+%7.5e i ",PetscReal(value),PetscImaginary(value)); 442 #else 443 fprintf(fd," %7.5e ",value); 444 #endif 445 } 446 fprintf(fd,"\n"); 447 } 448 } else { 449 for ( i=0; i<m; i++ ) { 450 fprintf(fd,"row %d:",i); 451 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 452 #if defined(USE_PETSC_COMPLEX) 453 if (PetscImaginary(a->a[j]) > 0.0) { 454 fprintf(fd," %d %g + %g i",a->j[j]+shift,PetscReal(a->a[j]),PetscImaginary(a->a[j])); 455 } else if (PetscImaginary(a->a[j]) < 0.0) { 456 fprintf(fd," %d %g - %g i",a->j[j]+shift,PetscReal(a->a[j]),-PetscImaginary(a->a[j])); 457 } else { 458 fprintf(fd," %d %g ",a->j[j]+shift,PetscReal(a->a[j])); 459 } 460 #else 461 fprintf(fd," %d %g ",a->j[j]+shift,a->a[j]); 462 #endif 463 } 464 fprintf(fd,"\n"); 465 } 466 } 467 fflush(fd); 468 PetscFunctionReturn(0); 469 } 470 471 #undef __FUNC__ 472 #define __FUNC__ "MatView_SeqAIJ_Draw_Zoom" 473 int MatView_SeqAIJ_Draw_Zoom(Draw draw,void *Aa) 474 { 475 Mat A = (Mat) Aa; 476 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 477 int ierr, i,j, m = a->m, shift = a->indexshift,color,rank; 478 int format; 479 double xl,yl,xr,yr,x_l,x_r,y_l,y_r,maxv = 0.0; 480 Viewer viewer; 481 MPI_Comm comm; 482 483 PetscFunctionBegin; 484 /* 485 This is nasty. If this is called from an originally parallel matrix 486 then all processes call this, but only the first has the matrix so the 487 rest should return immediately. 488 */ 489 ierr = PetscObjectGetComm((PetscObject)draw,&comm);CHKERRQ(ierr); 490 ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr); 491 if (rank) PetscFunctionReturn(0); 492 493 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*) &viewer);CHKERRQ(ierr); 494 ierr = ViewerGetFormat(viewer,&format); CHKERRQ(ierr); 495 496 ierr = DrawGetCoordinates(draw,&xl,&yl,&xr,&yr); CHKERRQ(ierr); 497 /* loop over matrix elements drawing boxes */ 498 499 if (format != VIEWER_FORMAT_DRAW_CONTOUR) { 500 /* Blue for negative, Cyan for zero and Red for positive */ 501 color = DRAW_BLUE; 502 for ( i=0; i<m; i++ ) { 503 y_l = m - i - 1.0; y_r = y_l + 1.0; 504 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 505 x_l = a->j[j] + shift; x_r = x_l + 1.0; 506 #if defined(USE_PETSC_COMPLEX) 507 if (PetscReal(a->a[j]) >= 0.) continue; 508 #else 509 if (a->a[j] >= 0.) continue; 510 #endif 511 ierr = DrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 512 } 513 } 514 color = DRAW_CYAN; 515 for ( i=0; i<m; i++ ) { 516 y_l = m - i - 1.0; y_r = y_l + 1.0; 517 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 518 x_l = a->j[j] + shift; x_r = x_l + 1.0; 519 if (a->a[j] != 0.) continue; 520 ierr = DrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 521 } 522 } 523 color = DRAW_RED; 524 for ( i=0; i<m; i++ ) { 525 y_l = m - i - 1.0; y_r = y_l + 1.0; 526 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 527 x_l = a->j[j] + shift; x_r = x_l + 1.0; 528 #if defined(USE_PETSC_COMPLEX) 529 if (PetscReal(a->a[j]) <= 0.) continue; 530 #else 531 if (a->a[j] <= 0.) continue; 532 #endif 533 ierr = DrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 534 } 535 } 536 } else { 537 /* use contour shading to indicate magnitude of values */ 538 /* first determine max of all nonzero values */ 539 int nz = a->nz,count; 540 Draw popup; 541 double scale; 542 543 for ( i=0; i<nz; i++ ) { 544 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 545 } 546 scale = (245.0 - DRAW_BASIC_COLORS)/maxv; 547 ierr = DrawGetPopup(draw,&popup); CHKERRQ(ierr); 548 ierr = DrawScalePopup(popup,0.0,maxv); CHKERRQ(ierr); 549 count = 0; 550 for ( i=0; i<m; i++ ) { 551 y_l = m - i - 1.0; y_r = y_l + 1.0; 552 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 553 x_l = a->j[j] + shift; x_r = x_l + 1.0; 554 color = DRAW_BASIC_COLORS + (int)(scale*PetscAbsScalar(a->a[count])); 555 ierr = DrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 556 count++; 557 } 558 } 559 } 560 PetscFunctionReturn(0); 561 } 562 563 #undef __FUNC__ 564 #define __FUNC__ "MatView_SeqAIJ_Draw" 565 int MatView_SeqAIJ_Draw(Mat A,Viewer viewer) 566 { 567 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 568 int ierr; 569 Draw draw; 570 double xr,yr,xl,yl,h,w; 571 PetscTruth isnull; 572 573 PetscFunctionBegin; 574 ierr = ViewerDrawGetDraw(viewer,0,&draw); CHKERRQ(ierr); 575 ierr = DrawIsNull(draw,&isnull); CHKERRQ(ierr); 576 if (isnull) PetscFunctionReturn(0); 577 578 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 579 xr = a->n; yr = a->m; h = yr/10.0; w = xr/10.0; 580 xr += w; yr += h; xl = -w; yl = -h; 581 ierr = DrawSetCoordinates(draw,xl,yl,xr,yr); CHKERRQ(ierr); 582 ierr = DrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A); CHKERRQ(ierr); 583 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); 584 PetscFunctionReturn(0); 585 } 586 587 #undef __FUNC__ 588 #define __FUNC__ "MatView_SeqAIJ" 589 int MatView_SeqAIJ(Mat A,Viewer viewer) 590 { 591 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 592 ViewerType vtype; 593 int ierr; 594 595 PetscFunctionBegin; 596 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 597 if (PetscTypeCompare(vtype,SOCKET_VIEWER)) { 598 ierr = ViewerSocketPutSparse_Private(viewer,a->m,a->n,a->nz,a->a,a->i,a->j);CHKERRQ(ierr); 599 } else if (PetscTypeCompare(vtype,ASCII_VIEWER)){ 600 ierr = MatView_SeqAIJ_ASCII(A,viewer); CHKERRQ(ierr); 601 } else if (PetscTypeCompare(vtype,BINARY_VIEWER)) { 602 ierr = MatView_SeqAIJ_Binary(A,viewer); CHKERRQ(ierr); 603 } else if (PetscTypeCompare(vtype,DRAW_VIEWER)) { 604 ierr = MatView_SeqAIJ_Draw(A,viewer); CHKERRQ(ierr); 605 } else { 606 SETERRQ(1,1,"Viewer type not supported by PETSc object"); 607 } 608 PetscFunctionReturn(0); 609 } 610 611 extern int Mat_AIJ_CheckInode(Mat); 612 #undef __FUNC__ 613 #define __FUNC__ "MatAssemblyEnd_SeqAIJ" 614 int MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 615 { 616 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 617 int fshift = 0,i,j,*ai = a->i, *aj = a->j, *imax = a->imax,ierr; 618 int m = a->m, *ip, N, *ailen = a->ilen,shift = a->indexshift,rmax = 0; 619 Scalar *aa = a->a, *ap; 620 621 PetscFunctionBegin; 622 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 623 624 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 625 for ( i=1; i<m; i++ ) { 626 /* move each row back by the amount of empty slots (fshift) before it*/ 627 fshift += imax[i-1] - ailen[i-1]; 628 rmax = PetscMax(rmax,ailen[i]); 629 if (fshift) { 630 ip = aj + ai[i] + shift; ap = aa + ai[i] + shift; 631 N = ailen[i]; 632 for ( j=0; j<N; j++ ) { 633 ip[j-fshift] = ip[j]; 634 ap[j-fshift] = ap[j]; 635 } 636 } 637 ai[i] = ai[i-1] + ailen[i-1]; 638 } 639 if (m) { 640 fshift += imax[m-1] - ailen[m-1]; 641 ai[m] = ai[m-1] + ailen[m-1]; 642 } 643 /* reset ilen and imax for each row */ 644 for ( i=0; i<m; i++ ) { 645 ailen[i] = imax[i] = ai[i+1] - ai[i]; 646 } 647 a->nz = ai[m] + shift; 648 649 /* diagonals may have moved, so kill the diagonal pointers */ 650 if (fshift && a->diag) { 651 PetscFree(a->diag); 652 PLogObjectMemory(A,-(m+1)*sizeof(int)); 653 a->diag = 0; 654 } 655 PLogInfo(A,"MatAssemblyEnd_SeqAIJ:Matrix size: %d X %d; storage space: %d unneeded, %d used\n", 656 m,a->n,fshift,a->nz); 657 PLogInfo(A,"MatAssemblyEnd_SeqAIJ:Number of mallocs during MatSetValues() is %d\n", 658 a->reallocs); 659 PLogInfo(A,"MatAssemblyEnd_SeqAIJ:Most nonzeros in any row is %d\n",rmax); 660 a->reallocs = 0; 661 A->info.nz_unneeded = (double)fshift; 662 663 /* check out for identical nodes. If found, use inode functions */ 664 ierr = Mat_AIJ_CheckInode(A); CHKERRQ(ierr); 665 PetscFunctionReturn(0); 666 } 667 668 #undef __FUNC__ 669 #define __FUNC__ "MatZeroEntries_SeqAIJ" 670 int MatZeroEntries_SeqAIJ(Mat A) 671 { 672 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 673 674 PetscFunctionBegin; 675 PetscMemzero(a->a,(a->i[a->m]+a->indexshift)*sizeof(Scalar)); 676 PetscFunctionReturn(0); 677 } 678 679 #undef __FUNC__ 680 #define __FUNC__ "MatDestroy_SeqAIJ" 681 int MatDestroy_SeqAIJ(Mat A) 682 { 683 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 684 int ierr; 685 686 PetscFunctionBegin; 687 if (--A->refct > 0) PetscFunctionReturn(0); 688 689 if (A->mapping) { 690 ierr = ISLocalToGlobalMappingDestroy(A->mapping); CHKERRQ(ierr); 691 } 692 if (A->bmapping) { 693 ierr = ISLocalToGlobalMappingDestroy(A->bmapping); CHKERRQ(ierr); 694 } 695 if (A->rmap) { 696 ierr = MapDestroy(A->rmap);CHKERRQ(ierr); 697 } 698 if (A->cmap) { 699 ierr = MapDestroy(A->cmap);CHKERRQ(ierr); 700 } 701 if (a->idiag) PetscFree(a->idiag); 702 #if defined(USE_PETSC_LOG) 703 PLogObjectState((PetscObject)A,"Rows=%d, Cols=%d, NZ=%d",a->m,a->n,a->nz); 704 #endif 705 PetscFree(a->a); 706 if (!a->singlemalloc) { PetscFree(a->i); PetscFree(a->j);} 707 if (a->diag) PetscFree(a->diag); 708 if (a->ilen) PetscFree(a->ilen); 709 if (a->imax) PetscFree(a->imax); 710 if (a->solve_work) PetscFree(a->solve_work); 711 if (a->inode.size) PetscFree(a->inode.size); 712 if (a->icol) {ierr = ISDestroy(a->icol);CHKERRQ(ierr);} 713 if (a->saved_values) PetscFree(a->saved_values); 714 PetscFree(a); 715 716 PLogObjectDestroy(A); 717 PetscHeaderDestroy(A); 718 PetscFunctionReturn(0); 719 } 720 721 #undef __FUNC__ 722 #define __FUNC__ "MatCompress_SeqAIJ" 723 int MatCompress_SeqAIJ(Mat A) 724 { 725 PetscFunctionBegin; 726 PetscFunctionReturn(0); 727 } 728 729 #undef __FUNC__ 730 #define __FUNC__ "MatSetOption_SeqAIJ" 731 int MatSetOption_SeqAIJ(Mat A,MatOption op) 732 { 733 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 734 735 PetscFunctionBegin; 736 if (op == MAT_ROW_ORIENTED) a->roworiented = 1; 737 else if (op == MAT_COLUMN_ORIENTED) a->roworiented = 0; 738 else if (op == MAT_COLUMNS_SORTED) a->sorted = 1; 739 else if (op == MAT_COLUMNS_UNSORTED) a->sorted = 0; 740 else if (op == MAT_NO_NEW_NONZERO_LOCATIONS) a->nonew = 1; 741 else if (op == MAT_NEW_NONZERO_LOCATION_ERR) a->nonew = -1; 742 else if (op == MAT_NEW_NONZERO_ALLOCATION_ERR) a->nonew = -2; 743 else if (op == MAT_YES_NEW_NONZERO_LOCATIONS) a->nonew = 0; 744 else if (op == MAT_ROWS_SORTED || 745 op == MAT_ROWS_UNSORTED || 746 op == MAT_SYMMETRIC || 747 op == MAT_STRUCTURALLY_SYMMETRIC || 748 op == MAT_YES_NEW_DIAGONALS || 749 op == MAT_IGNORE_OFF_PROC_ENTRIES|| 750 op == MAT_USE_HASH_TABLE) 751 PLogInfo(A,"MatSetOption_SeqAIJ:Option ignored\n"); 752 else if (op == MAT_NO_NEW_DIAGONALS) { 753 SETERRQ(PETSC_ERR_SUP,0,"MAT_NO_NEW_DIAGONALS"); 754 } else if (op == MAT_INODE_LIMIT_1) a->inode.limit = 1; 755 else if (op == MAT_INODE_LIMIT_2) a->inode.limit = 2; 756 else if (op == MAT_INODE_LIMIT_3) a->inode.limit = 3; 757 else if (op == MAT_INODE_LIMIT_4) a->inode.limit = 4; 758 else if (op == MAT_INODE_LIMIT_5) a->inode.limit = 5; 759 else SETERRQ(PETSC_ERR_SUP,0,"unknown option"); 760 PetscFunctionReturn(0); 761 } 762 763 #undef __FUNC__ 764 #define __FUNC__ "MatGetDiagonal_SeqAIJ" 765 int MatGetDiagonal_SeqAIJ(Mat A,Vec v) 766 { 767 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 768 int i,j, n,shift = a->indexshift,ierr; 769 Scalar *x, zero = 0.0; 770 771 PetscFunctionBegin; 772 ierr = VecSet(&zero,v);CHKERRQ(ierr); 773 ierr = VecGetArray(v,&x);;CHKERRQ(ierr); 774 ierr = VecGetLocalSize(v,&n);;CHKERRQ(ierr); 775 if (n != a->m) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Nonconforming matrix and vector"); 776 for ( i=0; i<a->m; i++ ) { 777 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 778 if (a->j[j]+shift == i) { 779 x[i] = a->a[j]; 780 break; 781 } 782 } 783 } 784 ierr = VecRestoreArray(v,&x);;CHKERRQ(ierr); 785 PetscFunctionReturn(0); 786 } 787 788 /* -------------------------------------------------------*/ 789 /* Should check that shapes of vectors and matrices match */ 790 /* -------------------------------------------------------*/ 791 #undef __FUNC__ 792 #define __FUNC__ "MatMultTrans_SeqAIJ" 793 int MatMultTrans_SeqAIJ(Mat A,Vec xx,Vec yy) 794 { 795 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 796 Scalar *x, *y, *v, alpha; 797 int ierr,m = a->m, n, i, *idx, shift = a->indexshift; 798 799 PetscFunctionBegin; 800 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 801 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 802 PetscMemzero(y,a->n*sizeof(Scalar)); 803 y = y + shift; /* shift for Fortran start by 1 indexing */ 804 for ( i=0; i<m; i++ ) { 805 idx = a->j + a->i[i] + shift; 806 v = a->a + a->i[i] + shift; 807 n = a->i[i+1] - a->i[i]; 808 alpha = x[i]; 809 while (n-->0) {y[*idx++] += alpha * *v++;} 810 } 811 PLogFlops(2*a->nz - a->n); 812 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 813 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 814 PetscFunctionReturn(0); 815 } 816 817 #undef __FUNC__ 818 #define __FUNC__ "MatMultTransAdd_SeqAIJ" 819 int MatMultTransAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 820 { 821 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 822 Scalar *x, *y, *v, alpha; 823 int ierr,m = a->m, n, i, *idx,shift = a->indexshift; 824 825 PetscFunctionBegin; 826 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 827 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 828 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 829 y = y + shift; /* shift for Fortran start by 1 indexing */ 830 for ( i=0; i<m; i++ ) { 831 idx = a->j + a->i[i] + shift; 832 v = a->a + a->i[i] + shift; 833 n = a->i[i+1] - a->i[i]; 834 alpha = x[i]; 835 while (n-->0) {y[*idx++] += alpha * *v++;} 836 } 837 PLogFlops(2*a->nz); 838 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 839 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 840 PetscFunctionReturn(0); 841 } 842 843 #undef __FUNC__ 844 #define __FUNC__ "MatMult_SeqAIJ" 845 int MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 846 { 847 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 848 Scalar *x, *y, *v, sum; 849 int ierr,m = a->m, *idx, shift = a->indexshift,*ii; 850 #if !defined(USE_FORTRAN_KERNEL_MULTAIJ) 851 int n, i, jrow,j; 852 #endif 853 854 #if defined(HAVE_PRAGMA_DISJOINT) 855 #pragma disjoint(*x,*y,*v) 856 #endif 857 858 PetscFunctionBegin; 859 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 860 ierr = VecGetArray(yy,&y); CHKERRQ(ierr); 861 x = x + shift; /* shift for Fortran start by 1 indexing */ 862 idx = a->j; 863 v = a->a; 864 ii = a->i; 865 #if defined(USE_FORTRAN_KERNEL_MULTAIJ) 866 fortranmultaij_(&m,x,ii,idx+shift,v+shift,y); 867 #else 868 v += shift; /* shift for Fortran start by 1 indexing */ 869 idx += shift; 870 for ( i=0; i<m; i++ ) { 871 jrow = ii[i]; 872 n = ii[i+1] - jrow; 873 sum = 0.0; 874 for ( j=0; j<n; j++) { 875 sum += v[jrow]*x[idx[jrow]]; jrow++; 876 } 877 y[i] = sum; 878 } 879 #endif 880 PLogFlops(2*a->nz - m); 881 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 882 ierr = VecRestoreArray(yy,&y); CHKERRQ(ierr); 883 PetscFunctionReturn(0); 884 } 885 886 #undef __FUNC__ 887 #define __FUNC__ "MatMultAdd_SeqAIJ" 888 int MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 889 { 890 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 891 Scalar *x, *y, *z, *v, sum; 892 int ierr,m = a->m, *idx, shift = a->indexshift,*ii; 893 #if !defined(USE_FORTRAN_KERNEL_MULTADDAIJ) 894 int n,i,jrow,j; 895 #endif 896 897 PetscFunctionBegin; 898 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 899 ierr = VecGetArray(yy,&y); CHKERRQ(ierr); 900 if (zz != yy) { 901 ierr = VecGetArray(zz,&z); CHKERRQ(ierr); 902 } else { 903 z = y; 904 } 905 x = x + shift; /* shift for Fortran start by 1 indexing */ 906 idx = a->j; 907 v = a->a; 908 ii = a->i; 909 #if defined(USE_FORTRAN_KERNEL_MULTADDAIJ) 910 fortranmultaddaij_(&m,x,ii,idx+shift,v+shift,y,z); 911 #else 912 v += shift; /* shift for Fortran start by 1 indexing */ 913 idx += shift; 914 for ( i=0; i<m; i++ ) { 915 jrow = ii[i]; 916 n = ii[i+1] - jrow; 917 sum = y[i]; 918 for ( j=0; j<n; j++) { 919 sum += v[jrow]*x[idx[jrow]]; jrow++; 920 } 921 z[i] = sum; 922 } 923 #endif 924 PLogFlops(2*a->nz); 925 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 926 ierr = VecRestoreArray(yy,&y); CHKERRQ(ierr); 927 if (zz != yy) { 928 ierr = VecRestoreArray(zz,&z); CHKERRQ(ierr); 929 } 930 PetscFunctionReturn(0); 931 } 932 933 /* 934 Adds diagonal pointers to sparse matrix structure. 935 */ 936 #undef __FUNC__ 937 #define __FUNC__ "MatMarkDiag_SeqAIJ" 938 int MatMarkDiag_SeqAIJ(Mat A) 939 { 940 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 941 int i,j, *diag, m = a->m,shift = a->indexshift; 942 943 PetscFunctionBegin; 944 diag = (int *) PetscMalloc( (m+1)*sizeof(int)); CHKPTRQ(diag); 945 PLogObjectMemory(A,(m+1)*sizeof(int)); 946 for ( i=0; i<a->m; i++ ) { 947 diag[i] = a->i[i+1]; 948 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 949 if (a->j[j]+shift == i) { 950 diag[i] = j - shift; 951 break; 952 } 953 } 954 } 955 a->diag = diag; 956 PetscFunctionReturn(0); 957 } 958 959 /* 960 Checks for missing diagonals 961 */ 962 #undef __FUNC__ 963 #define __FUNC__ "MatMissingDiag_SeqAIJ" 964 int MatMissingDiag_SeqAIJ(Mat A) 965 { 966 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 967 int *diag = a->diag, *jj = a->j,i,shift = a->indexshift; 968 969 PetscFunctionBegin; 970 for ( i=0; i<a->m; i++ ) { 971 if (jj[diag[i]+shift] != i-shift) { 972 SETERRQ1(1,1,"Matrix is missing diagonal number %d",i); 973 } 974 } 975 PetscFunctionReturn(0); 976 } 977 978 #undef __FUNC__ 979 #define __FUNC__ "MatRelax_SeqAIJ" 980 int MatRelax_SeqAIJ(Mat A,Vec bb,double omega,MatSORType flag,double fshift,int its,Vec xx) 981 { 982 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 983 Scalar *x, *b, *bs, d, *xs, sum, *v = a->a,*t=0,scale,*ts, *xb,*idiag=0; 984 int ierr, *idx, *diag,n = a->n, m = a->m, i, shift = a->indexshift; 985 986 PetscFunctionBegin; 987 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 988 if (xx != bb) { 989 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 990 } else { 991 b = x; 992 } 993 994 if (!a->diag) {ierr = MatMarkDiag_SeqAIJ(A);CHKERRQ(ierr);} 995 diag = a->diag; 996 xs = x + shift; /* shifted by one for index start of a or a->j*/ 997 if (flag == SOR_APPLY_UPPER) { 998 /* apply ( U + D/omega) to the vector */ 999 bs = b + shift; 1000 for ( i=0; i<m; i++ ) { 1001 d = fshift + a->a[diag[i] + shift]; 1002 n = a->i[i+1] - diag[i] - 1; 1003 PLogFlops(2*n-1); 1004 idx = a->j + diag[i] + (!shift); 1005 v = a->a + diag[i] + (!shift); 1006 sum = b[i]*d/omega; 1007 SPARSEDENSEDOT(sum,bs,v,idx,n); 1008 x[i] = sum; 1009 } 1010 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1011 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1012 PetscFunctionReturn(0); 1013 } 1014 1015 /* setup workspace for Eisenstat */ 1016 if (flag & SOR_EISENSTAT) { 1017 if (!a->idiag) { 1018 a->idiag = (Scalar *) PetscMalloc(2*m*sizeof(Scalar));CHKPTRQ(a->idiag); 1019 a->ssor = a->idiag + m; 1020 v = a->a; 1021 for ( i=0; i<m; i++ ) { a->idiag[i] = 1.0/v[diag[i]];} 1022 } 1023 t = a->ssor; 1024 idiag = a->idiag; 1025 } 1026 /* Let A = L + U + D; where L is lower trianglar, 1027 U is upper triangular, E is diagonal; This routine applies 1028 1029 (L + E)^{-1} A (U + E)^{-1} 1030 1031 to a vector efficiently using Eisenstat's trick. This is for 1032 the case of SSOR preconditioner, so E is D/omega where omega 1033 is the relaxation factor. 1034 */ 1035 1036 if (flag == SOR_APPLY_LOWER) { 1037 SETERRQ(PETSC_ERR_SUP,0,"SOR_APPLY_LOWER is not done"); 1038 } else if ((flag & SOR_EISENSTAT) && omega == 1.0 && shift == 0 && fshift == 0.0) { 1039 /* special case for omega = 1.0 saves flops and some integer ops */ 1040 Scalar *v2; 1041 1042 v2 = a->a; 1043 /* x = (E + U)^{-1} b */ 1044 for ( i=m-1; i>=0; i-- ) { 1045 n = a->i[i+1] - diag[i] - 1; 1046 idx = a->j + diag[i] + 1; 1047 v = a->a + diag[i] + 1; 1048 sum = b[i]; 1049 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1050 x[i] = sum*idiag[i]; 1051 1052 /* t = b - (2*E - D)x */ 1053 t[i] = b[i] - (v2[diag[i]])*x[i]; 1054 } 1055 1056 /* t = (E + L)^{-1}t */ 1057 diag = a->diag; 1058 for ( i=0; i<m; i++ ) { 1059 n = diag[i] - a->i[i]; 1060 idx = a->j + a->i[i]; 1061 v = a->a + a->i[i]; 1062 sum = t[i]; 1063 SPARSEDENSEMDOT(sum,t,v,idx,n); 1064 t[i] = sum*idiag[i]; 1065 1066 /* x = x + t */ 1067 x[i] += t[i]; 1068 } 1069 1070 PLogFlops(3*m-1 + 2*a->nz); 1071 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1072 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1073 PetscFunctionReturn(0); 1074 } else if (flag & SOR_EISENSTAT) { 1075 /* Let A = L + U + D; where L is lower trianglar, 1076 U is upper triangular, E is diagonal; This routine applies 1077 1078 (L + E)^{-1} A (U + E)^{-1} 1079 1080 to a vector efficiently using Eisenstat's trick. This is for 1081 the case of SSOR preconditioner, so E is D/omega where omega 1082 is the relaxation factor. 1083 */ 1084 scale = (2.0/omega) - 1.0; 1085 1086 /* x = (E + U)^{-1} b */ 1087 for ( i=m-1; i>=0; i-- ) { 1088 d = fshift + a->a[diag[i] + shift]; 1089 n = a->i[i+1] - diag[i] - 1; 1090 idx = a->j + diag[i] + (!shift); 1091 v = a->a + diag[i] + (!shift); 1092 sum = b[i]; 1093 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1094 x[i] = omega*(sum/d); 1095 } 1096 1097 /* t = b - (2*E - D)x */ 1098 v = a->a; 1099 for ( i=0; i<m; i++ ) { t[i] = b[i] - scale*(v[*diag++ + shift])*x[i]; } 1100 1101 /* t = (E + L)^{-1}t */ 1102 ts = t + shift; /* shifted by one for index start of a or a->j*/ 1103 diag = a->diag; 1104 for ( i=0; i<m; i++ ) { 1105 d = fshift + a->a[diag[i]+shift]; 1106 n = diag[i] - a->i[i]; 1107 idx = a->j + a->i[i] + shift; 1108 v = a->a + a->i[i] + shift; 1109 sum = t[i]; 1110 SPARSEDENSEMDOT(sum,ts,v,idx,n); 1111 t[i] = omega*(sum/d); 1112 /* x = x + t */ 1113 x[i] += t[i]; 1114 } 1115 1116 PLogFlops(6*m-1 + 2*a->nz); 1117 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1118 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1119 PetscFunctionReturn(0); 1120 } 1121 if (flag & SOR_ZERO_INITIAL_GUESS) { 1122 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 1123 for ( i=0; i<m; i++ ) { 1124 d = fshift + a->a[diag[i]+shift]; 1125 n = diag[i] - a->i[i]; 1126 PLogFlops(2*n-1); 1127 idx = a->j + a->i[i] + shift; 1128 v = a->a + a->i[i] + shift; 1129 sum = b[i]; 1130 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1131 x[i] = omega*(sum/d); 1132 } 1133 xb = x; 1134 } else xb = b; 1135 if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) && 1136 (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) { 1137 for ( i=0; i<m; i++ ) { 1138 x[i] *= a->a[diag[i]+shift]; 1139 } 1140 PLogFlops(m); 1141 } 1142 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 1143 for ( i=m-1; i>=0; i-- ) { 1144 d = fshift + a->a[diag[i] + shift]; 1145 n = a->i[i+1] - diag[i] - 1; 1146 PLogFlops(2*n-1); 1147 idx = a->j + diag[i] + (!shift); 1148 v = a->a + diag[i] + (!shift); 1149 sum = xb[i]; 1150 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1151 x[i] = omega*(sum/d); 1152 } 1153 } 1154 its--; 1155 } 1156 while (its--) { 1157 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 1158 for ( i=0; i<m; i++ ) { 1159 d = fshift + a->a[diag[i]+shift]; 1160 n = a->i[i+1] - a->i[i]; 1161 PLogFlops(2*n-1); 1162 idx = a->j + a->i[i] + shift; 1163 v = a->a + a->i[i] + shift; 1164 sum = b[i]; 1165 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1166 x[i] = (1. - omega)*x[i] + omega*(sum + a->a[diag[i]+shift]*x[i])/d; 1167 } 1168 } 1169 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 1170 for ( i=m-1; i>=0; i-- ) { 1171 d = fshift + a->a[diag[i] + shift]; 1172 n = a->i[i+1] - a->i[i]; 1173 PLogFlops(2*n-1); 1174 idx = a->j + a->i[i] + shift; 1175 v = a->a + a->i[i] + shift; 1176 sum = b[i]; 1177 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1178 x[i] = (1. - omega)*x[i] + omega*(sum + a->a[diag[i]+shift]*x[i])/d; 1179 } 1180 } 1181 } 1182 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1183 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1184 PetscFunctionReturn(0); 1185 } 1186 1187 #undef __FUNC__ 1188 #define __FUNC__ "MatGetInfo_SeqAIJ" 1189 int MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1190 { 1191 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1192 1193 PetscFunctionBegin; 1194 info->rows_global = (double)a->m; 1195 info->columns_global = (double)a->n; 1196 info->rows_local = (double)a->m; 1197 info->columns_local = (double)a->n; 1198 info->block_size = 1.0; 1199 info->nz_allocated = (double)a->maxnz; 1200 info->nz_used = (double)a->nz; 1201 info->nz_unneeded = (double)(a->maxnz - a->nz); 1202 info->assemblies = (double)A->num_ass; 1203 info->mallocs = (double)a->reallocs; 1204 info->memory = A->mem; 1205 if (A->factor) { 1206 info->fill_ratio_given = A->info.fill_ratio_given; 1207 info->fill_ratio_needed = A->info.fill_ratio_needed; 1208 info->factor_mallocs = A->info.factor_mallocs; 1209 } else { 1210 info->fill_ratio_given = 0; 1211 info->fill_ratio_needed = 0; 1212 info->factor_mallocs = 0; 1213 } 1214 PetscFunctionReturn(0); 1215 } 1216 1217 extern int MatLUFactorSymbolic_SeqAIJ(Mat,IS,IS,double,Mat*); 1218 extern int MatLUFactorNumeric_SeqAIJ(Mat,Mat*); 1219 extern int MatLUFactor_SeqAIJ(Mat,IS,IS,double); 1220 extern int MatSolve_SeqAIJ(Mat,Vec,Vec); 1221 extern int MatSolveAdd_SeqAIJ(Mat,Vec,Vec,Vec); 1222 extern int MatSolveTrans_SeqAIJ(Mat,Vec,Vec); 1223 extern int MatSolveTransAdd_SeqAIJ(Mat,Vec,Vec,Vec); 1224 1225 #undef __FUNC__ 1226 #define __FUNC__ "MatZeroRows_SeqAIJ" 1227 int MatZeroRows_SeqAIJ(Mat A,IS is,Scalar *diag) 1228 { 1229 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1230 int i,ierr,N, *rows,m = a->m - 1,shift = a->indexshift; 1231 1232 PetscFunctionBegin; 1233 ierr = ISGetSize(is,&N); CHKERRQ(ierr); 1234 ierr = ISGetIndices(is,&rows); CHKERRQ(ierr); 1235 if (diag) { 1236 for ( i=0; i<N; i++ ) { 1237 if (rows[i] < 0 || rows[i] > m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"row out of range"); 1238 if (a->ilen[rows[i]] > 0) { 1239 a->ilen[rows[i]] = 1; 1240 a->a[a->i[rows[i]]+shift] = *diag; 1241 a->j[a->i[rows[i]]+shift] = rows[i]+shift; 1242 } else { /* in case row was completely empty */ 1243 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],diag,INSERT_VALUES);CHKERRQ(ierr); 1244 } 1245 } 1246 } else { 1247 for ( i=0; i<N; i++ ) { 1248 if (rows[i] < 0 || rows[i] > m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"row out of range"); 1249 a->ilen[rows[i]] = 0; 1250 } 1251 } 1252 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1253 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1254 PetscFunctionReturn(0); 1255 } 1256 1257 #undef __FUNC__ 1258 #define __FUNC__ "MatGetSize_SeqAIJ" 1259 int MatGetSize_SeqAIJ(Mat A,int *m,int *n) 1260 { 1261 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1262 1263 PetscFunctionBegin; 1264 if (m) *m = a->m; 1265 if (n) *n = a->n; 1266 PetscFunctionReturn(0); 1267 } 1268 1269 #undef __FUNC__ 1270 #define __FUNC__ "MatGetOwnershipRange_SeqAIJ" 1271 int MatGetOwnershipRange_SeqAIJ(Mat A,int *m,int *n) 1272 { 1273 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1274 1275 PetscFunctionBegin; 1276 *m = 0; *n = a->m; 1277 PetscFunctionReturn(0); 1278 } 1279 1280 #undef __FUNC__ 1281 #define __FUNC__ "MatGetRow_SeqAIJ" 1282 int MatGetRow_SeqAIJ(Mat A,int row,int *nz,int **idx,Scalar **v) 1283 { 1284 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1285 int *itmp,i,shift = a->indexshift; 1286 1287 PetscFunctionBegin; 1288 if (row < 0 || row >= a->m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row out of range"); 1289 1290 *nz = a->i[row+1] - a->i[row]; 1291 if (v) *v = a->a + a->i[row] + shift; 1292 if (idx) { 1293 itmp = a->j + a->i[row] + shift; 1294 if (*nz && shift) { 1295 *idx = (int *) PetscMalloc( (*nz)*sizeof(int) ); CHKPTRQ(*idx); 1296 for ( i=0; i<(*nz); i++ ) {(*idx)[i] = itmp[i] + shift;} 1297 } else if (*nz) { 1298 *idx = itmp; 1299 } 1300 else *idx = 0; 1301 } 1302 PetscFunctionReturn(0); 1303 } 1304 1305 #undef __FUNC__ 1306 #define __FUNC__ "MatRestoreRow_SeqAIJ" 1307 int MatRestoreRow_SeqAIJ(Mat A,int row,int *nz,int **idx,Scalar **v) 1308 { 1309 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1310 1311 PetscFunctionBegin; 1312 if (idx) {if (*idx && a->indexshift) PetscFree(*idx);} 1313 PetscFunctionReturn(0); 1314 } 1315 1316 #undef __FUNC__ 1317 #define __FUNC__ "MatNorm_SeqAIJ" 1318 int MatNorm_SeqAIJ(Mat A,NormType type,double *norm) 1319 { 1320 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1321 Scalar *v = a->a; 1322 double sum = 0.0; 1323 int i, j,shift = a->indexshift; 1324 1325 PetscFunctionBegin; 1326 if (type == NORM_FROBENIUS) { 1327 for (i=0; i<a->nz; i++ ) { 1328 #if defined(USE_PETSC_COMPLEX) 1329 sum += PetscReal(PetscConj(*v)*(*v)); v++; 1330 #else 1331 sum += (*v)*(*v); v++; 1332 #endif 1333 } 1334 *norm = sqrt(sum); 1335 } else if (type == NORM_1) { 1336 double *tmp; 1337 int *jj = a->j; 1338 tmp = (double *) PetscMalloc( (a->n+1)*sizeof(double) ); CHKPTRQ(tmp); 1339 PetscMemzero(tmp,a->n*sizeof(double)); 1340 *norm = 0.0; 1341 for ( j=0; j<a->nz; j++ ) { 1342 tmp[*jj++ + shift] += PetscAbsScalar(*v); v++; 1343 } 1344 for ( j=0; j<a->n; j++ ) { 1345 if (tmp[j] > *norm) *norm = tmp[j]; 1346 } 1347 PetscFree(tmp); 1348 } else if (type == NORM_INFINITY) { 1349 *norm = 0.0; 1350 for ( j=0; j<a->m; j++ ) { 1351 v = a->a + a->i[j] + shift; 1352 sum = 0.0; 1353 for ( i=0; i<a->i[j+1]-a->i[j]; i++ ) { 1354 sum += PetscAbsScalar(*v); v++; 1355 } 1356 if (sum > *norm) *norm = sum; 1357 } 1358 } else { 1359 SETERRQ(PETSC_ERR_SUP,0,"No support for two norm"); 1360 } 1361 PetscFunctionReturn(0); 1362 } 1363 1364 #undef __FUNC__ 1365 #define __FUNC__ "MatTranspose_SeqAIJ" 1366 int MatTranspose_SeqAIJ(Mat A,Mat *B) 1367 { 1368 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1369 Mat C; 1370 int i, ierr, *aj = a->j, *ai = a->i, m = a->m, len, *col; 1371 int shift = a->indexshift; 1372 Scalar *array = a->a; 1373 1374 PetscFunctionBegin; 1375 if (B == PETSC_NULL && m != a->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Square matrix only for in-place"); 1376 col = (int *) PetscMalloc((1+a->n)*sizeof(int)); CHKPTRQ(col); 1377 PetscMemzero(col,(1+a->n)*sizeof(int)); 1378 if (shift) { 1379 for ( i=0; i<ai[m]-1; i++ ) aj[i] -= 1; 1380 } 1381 for ( i=0; i<ai[m]+shift; i++ ) col[aj[i]] += 1; 1382 ierr = MatCreateSeqAIJ(A->comm,a->n,m,0,col,&C); CHKERRQ(ierr); 1383 PetscFree(col); 1384 for ( i=0; i<m; i++ ) { 1385 len = ai[i+1]-ai[i]; 1386 ierr = MatSetValues(C,len,aj,1,&i,array,INSERT_VALUES); CHKERRQ(ierr); 1387 array += len; aj += len; 1388 } 1389 if (shift) { 1390 for ( i=0; i<ai[m]-1; i++ ) aj[i] += 1; 1391 } 1392 1393 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1394 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1395 1396 if (B != PETSC_NULL) { 1397 *B = C; 1398 } else { 1399 PetscOps *Abops; 1400 MatOps Aops; 1401 1402 /* This isn't really an in-place transpose */ 1403 PetscFree(a->a); 1404 if (!a->singlemalloc) {PetscFree(a->i); PetscFree(a->j);} 1405 if (a->diag) PetscFree(a->diag); 1406 if (a->ilen) PetscFree(a->ilen); 1407 if (a->imax) PetscFree(a->imax); 1408 if (a->solve_work) PetscFree(a->solve_work); 1409 if (a->inode.size) PetscFree(a->inode.size); 1410 PetscFree(a); 1411 1412 1413 ierr = MapDestroy(A->rmap);CHKERRQ(ierr); 1414 ierr = MapDestroy(A->cmap);CHKERRQ(ierr); 1415 1416 /* 1417 This is horrible, horrible code. We need to keep the 1418 the bops and ops Structures, copy everything from C 1419 including the function pointers.. 1420 */ 1421 PetscMemcpy(A->ops,C->ops,sizeof(struct _MatOps)); 1422 PetscMemcpy(A->bops,C->bops,sizeof(PetscOps)); 1423 Abops = A->bops; 1424 Aops = A->ops; 1425 PetscMemcpy(A,C,sizeof(struct _p_Mat)); 1426 A->bops = Abops; 1427 A->ops = Aops; 1428 A->qlist = 0; 1429 1430 PetscHeaderDestroy(C); 1431 } 1432 PetscFunctionReturn(0); 1433 } 1434 1435 #undef __FUNC__ 1436 #define __FUNC__ "MatDiagonalScale_SeqAIJ" 1437 int MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 1438 { 1439 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1440 Scalar *l,*r,x,*v; 1441 int ierr,i,j,m = a->m, n = a->n, M, nz = a->nz, *jj,shift = a->indexshift; 1442 1443 PetscFunctionBegin; 1444 if (ll) { 1445 /* The local size is used so that VecMPI can be passed to this routine 1446 by MatDiagonalScale_MPIAIJ */ 1447 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 1448 if (m != a->m) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Left scaling vector wrong length"); 1449 ierr = VecGetArray(ll,&l); CHKERRQ(ierr); 1450 v = a->a; 1451 for ( i=0; i<m; i++ ) { 1452 x = l[i]; 1453 M = a->i[i+1] - a->i[i]; 1454 for ( j=0; j<M; j++ ) { (*v++) *= x;} 1455 } 1456 ierr = VecRestoreArray(ll,&l); CHKERRQ(ierr); 1457 PLogFlops(nz); 1458 } 1459 if (rr) { 1460 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 1461 if (n != a->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Right scaling vector wrong length"); 1462 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 1463 v = a->a; jj = a->j; 1464 for ( i=0; i<nz; i++ ) { 1465 (*v++) *= r[*jj++ + shift]; 1466 } 1467 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 1468 PLogFlops(nz); 1469 } 1470 PetscFunctionReturn(0); 1471 } 1472 1473 #undef __FUNC__ 1474 #define __FUNC__ "MatGetSubMatrix_SeqAIJ" 1475 int MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,int csize,MatReuse scall,Mat *B) 1476 { 1477 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data,*c; 1478 int *smap, i, k, kstart, kend, ierr, oldcols = a->n,*lens; 1479 int row,mat_i,*mat_j,tcol,first,step,*mat_ilen; 1480 register int sum,lensi; 1481 int *irow, *icol, nrows, ncols, shift = a->indexshift,*ssmap; 1482 int *starts,*j_new,*i_new,*aj = a->j, *ai = a->i,ii,*ailen = a->ilen; 1483 Scalar *a_new,*mat_a; 1484 Mat C; 1485 PetscTruth stride; 1486 1487 PetscFunctionBegin; 1488 ierr = ISSorted(isrow,(PetscTruth*)&i);CHKERRQ(ierr); 1489 if (!i) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"ISrow is not sorted"); 1490 ierr = ISSorted(iscol,(PetscTruth*)&i);CHKERRQ(ierr); 1491 if (!i) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"IScol is not sorted"); 1492 1493 ierr = ISGetIndices(isrow,&irow); CHKERRQ(ierr); 1494 ierr = ISGetSize(isrow,&nrows); CHKERRQ(ierr); 1495 ierr = ISGetSize(iscol,&ncols); CHKERRQ(ierr); 1496 1497 ierr = ISStrideGetInfo(iscol,&first,&step); CHKERRQ(ierr); 1498 ierr = ISStride(iscol,&stride); CHKERRQ(ierr); 1499 if (stride && step == 1) { 1500 /* special case of contiguous rows */ 1501 lens = (int *) PetscMalloc((ncols+nrows+1)*sizeof(int)); CHKPTRQ(lens); 1502 starts = lens + ncols; 1503 /* loop over new rows determining lens and starting points */ 1504 for (i=0; i<nrows; i++) { 1505 kstart = ai[irow[i]]+shift; 1506 kend = kstart + ailen[irow[i]]; 1507 for ( k=kstart; k<kend; k++ ) { 1508 if (aj[k]+shift >= first) { 1509 starts[i] = k; 1510 break; 1511 } 1512 } 1513 sum = 0; 1514 while (k < kend) { 1515 if (aj[k++]+shift >= first+ncols) break; 1516 sum++; 1517 } 1518 lens[i] = sum; 1519 } 1520 /* create submatrix */ 1521 if (scall == MAT_REUSE_MATRIX) { 1522 int n_cols,n_rows; 1523 ierr = MatGetSize(*B,&n_rows,&n_cols); CHKERRQ(ierr); 1524 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Reused submatrix wrong size"); 1525 ierr = MatZeroEntries(*B); CHKERRQ(ierr); 1526 C = *B; 1527 } else { 1528 ierr = MatCreateSeqAIJ(A->comm,nrows,ncols,0,lens,&C);CHKERRQ(ierr); 1529 } 1530 c = (Mat_SeqAIJ*) C->data; 1531 1532 /* loop over rows inserting into submatrix */ 1533 a_new = c->a; 1534 j_new = c->j; 1535 i_new = c->i; 1536 i_new[0] = -shift; 1537 for (i=0; i<nrows; i++) { 1538 ii = starts[i]; 1539 lensi = lens[i]; 1540 for ( k=0; k<lensi; k++ ) { 1541 *j_new++ = aj[ii+k] - first; 1542 } 1543 PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(Scalar)); 1544 a_new += lensi; 1545 i_new[i+1] = i_new[i] + lensi; 1546 c->ilen[i] = lensi; 1547 } 1548 PetscFree(lens); 1549 } else { 1550 ierr = ISGetIndices(iscol,&icol); CHKERRQ(ierr); 1551 smap = (int *) PetscMalloc((1+oldcols)*sizeof(int)); CHKPTRQ(smap); 1552 ssmap = smap + shift; 1553 lens = (int *) PetscMalloc((1+nrows)*sizeof(int)); CHKPTRQ(lens); 1554 PetscMemzero(smap,oldcols*sizeof(int)); 1555 for ( i=0; i<ncols; i++ ) smap[icol[i]] = i+1; 1556 /* determine lens of each row */ 1557 for (i=0; i<nrows; i++) { 1558 kstart = ai[irow[i]]+shift; 1559 kend = kstart + a->ilen[irow[i]]; 1560 lens[i] = 0; 1561 for ( k=kstart; k<kend; k++ ) { 1562 if (ssmap[aj[k]]) { 1563 lens[i]++; 1564 } 1565 } 1566 } 1567 /* Create and fill new matrix */ 1568 if (scall == MAT_REUSE_MATRIX) { 1569 c = (Mat_SeqAIJ *)((*B)->data); 1570 if (c->m != nrows || c->n != ncols) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Cannot reuse matrix. wrong size"); 1571 if (PetscMemcmp(c->ilen,lens, c->m *sizeof(int))) { 1572 SETERRQ(PETSC_ERR_ARG_SIZ,0,"Cannot reuse matrix. wrong no of nonzeros"); 1573 } 1574 PetscMemzero(c->ilen,c->m*sizeof(int)); 1575 C = *B; 1576 } else { 1577 ierr = MatCreateSeqAIJ(A->comm,nrows,ncols,0,lens,&C);CHKERRQ(ierr); 1578 } 1579 c = (Mat_SeqAIJ *)(C->data); 1580 for (i=0; i<nrows; i++) { 1581 row = irow[i]; 1582 kstart = ai[row]+shift; 1583 kend = kstart + a->ilen[row]; 1584 mat_i = c->i[i]+shift; 1585 mat_j = c->j + mat_i; 1586 mat_a = c->a + mat_i; 1587 mat_ilen = c->ilen + i; 1588 for ( k=kstart; k<kend; k++ ) { 1589 if ((tcol=ssmap[a->j[k]])) { 1590 *mat_j++ = tcol - (!shift); 1591 *mat_a++ = a->a[k]; 1592 (*mat_ilen)++; 1593 1594 } 1595 } 1596 } 1597 /* Free work space */ 1598 ierr = ISRestoreIndices(iscol,&icol); CHKERRQ(ierr); 1599 PetscFree(smap); PetscFree(lens); 1600 } 1601 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1602 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1603 1604 ierr = ISRestoreIndices(isrow,&irow); CHKERRQ(ierr); 1605 *B = C; 1606 PetscFunctionReturn(0); 1607 } 1608 1609 /* 1610 */ 1611 #undef __FUNC__ 1612 #define __FUNC__ "MatILUFactor_SeqAIJ" 1613 int MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,MatILUInfo *info) 1614 { 1615 Mat_SeqAIJ *a = (Mat_SeqAIJ *) inA->data; 1616 int ierr; 1617 Mat outA; 1618 PetscTruth row_identity, col_identity; 1619 1620 PetscFunctionBegin; 1621 if (info && info->levels != 0) SETERRQ(PETSC_ERR_SUP,0,"Only levels=0 supported for in-place ilu"); 1622 ierr = ISIdentity(row,&row_identity); CHKERRQ(ierr); 1623 ierr = ISIdentity(col,&col_identity); CHKERRQ(ierr); 1624 if (!row_identity || !col_identity) { 1625 SETERRQ(1,1,"Row and column permutations must be identity for in-place ILU"); 1626 } 1627 1628 outA = inA; 1629 inA->factor = FACTOR_LU; 1630 a->row = row; 1631 a->col = col; 1632 1633 /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ 1634 ierr = ISInvertPermutation(col,&(a->icol)); CHKERRQ(ierr); 1635 PLogObjectParent(inA,a->icol); 1636 1637 if (!a->solve_work) { /* this matrix may have been factored before */ 1638 a->solve_work = (Scalar *) PetscMalloc( (a->m+1)*sizeof(Scalar));CHKPTRQ(a->solve_work); 1639 } 1640 1641 if (!a->diag) { 1642 ierr = MatMarkDiag_SeqAIJ(inA); CHKERRQ(ierr); 1643 } 1644 ierr = MatLUFactorNumeric_SeqAIJ(inA,&outA); CHKERRQ(ierr); 1645 PetscFunctionReturn(0); 1646 } 1647 1648 #include "pinclude/blaslapack.h" 1649 #undef __FUNC__ 1650 #define __FUNC__ "MatScale_SeqAIJ" 1651 int MatScale_SeqAIJ(Scalar *alpha,Mat inA) 1652 { 1653 Mat_SeqAIJ *a = (Mat_SeqAIJ *) inA->data; 1654 int one = 1; 1655 1656 PetscFunctionBegin; 1657 BLscal_( &a->nz, alpha, a->a, &one ); 1658 PLogFlops(a->nz); 1659 PetscFunctionReturn(0); 1660 } 1661 1662 #undef __FUNC__ 1663 #define __FUNC__ "MatGetSubMatrices_SeqAIJ" 1664 int MatGetSubMatrices_SeqAIJ(Mat A,int n, IS *irow,IS *icol,MatReuse scall,Mat **B) 1665 { 1666 int ierr,i; 1667 1668 PetscFunctionBegin; 1669 if (scall == MAT_INITIAL_MATRIX) { 1670 *B = (Mat *) PetscMalloc( (n+1)*sizeof(Mat) ); CHKPTRQ(*B); 1671 } 1672 1673 for ( i=0; i<n; i++ ) { 1674 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1675 } 1676 PetscFunctionReturn(0); 1677 } 1678 1679 #undef __FUNC__ 1680 #define __FUNC__ "MatGetBlockSize_SeqAIJ" 1681 int MatGetBlockSize_SeqAIJ(Mat A, int *bs) 1682 { 1683 PetscFunctionBegin; 1684 *bs = 1; 1685 PetscFunctionReturn(0); 1686 } 1687 1688 #undef __FUNC__ 1689 #define __FUNC__ "MatIncreaseOverlap_SeqAIJ" 1690 int MatIncreaseOverlap_SeqAIJ(Mat A, int is_max, IS *is, int ov) 1691 { 1692 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1693 int shift, row, i,j,k,l,m,n, *idx,ierr, *nidx, isz, val; 1694 int start, end, *ai, *aj; 1695 BT table; 1696 1697 PetscFunctionBegin; 1698 shift = a->indexshift; 1699 m = a->m; 1700 ai = a->i; 1701 aj = a->j+shift; 1702 1703 if (ov < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"illegal overlap value used"); 1704 1705 nidx = (int *) PetscMalloc((m+1)*sizeof(int)); CHKPTRQ(nidx); 1706 ierr = BTCreate(m,table); CHKERRQ(ierr); 1707 1708 for ( i=0; i<is_max; i++ ) { 1709 /* Initialize the two local arrays */ 1710 isz = 0; 1711 BTMemzero(m,table); 1712 1713 /* Extract the indices, assume there can be duplicate entries */ 1714 ierr = ISGetIndices(is[i],&idx); CHKERRQ(ierr); 1715 ierr = ISGetSize(is[i],&n); CHKERRQ(ierr); 1716 1717 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 1718 for ( j=0; j<n ; ++j){ 1719 if(!BTLookupSet(table, idx[j])) { nidx[isz++] = idx[j];} 1720 } 1721 ierr = ISRestoreIndices(is[i],&idx); CHKERRQ(ierr); 1722 ierr = ISDestroy(is[i]); CHKERRQ(ierr); 1723 1724 k = 0; 1725 for ( j=0; j<ov; j++){ /* for each overlap */ 1726 n = isz; 1727 for ( ; k<n ; k++){ /* do only those rows in nidx[k], which are not done yet */ 1728 row = nidx[k]; 1729 start = ai[row]; 1730 end = ai[row+1]; 1731 for ( l = start; l<end ; l++){ 1732 val = aj[l] + shift; 1733 if (!BTLookupSet(table,val)) {nidx[isz++] = val;} 1734 } 1735 } 1736 } 1737 ierr = ISCreateGeneral(PETSC_COMM_SELF, isz, nidx, (is+i)); CHKERRQ(ierr); 1738 } 1739 BTDestroy(table); 1740 PetscFree(nidx); 1741 PetscFunctionReturn(0); 1742 } 1743 1744 /* -------------------------------------------------------------- */ 1745 #undef __FUNC__ 1746 #define __FUNC__ "MatPermute_SeqAIJ" 1747 int MatPermute_SeqAIJ(Mat A, IS rowp, IS colp, Mat *B) 1748 { 1749 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1750 Scalar *vwork; 1751 int i, ierr, nz, m = a->m, n = a->n, *cwork; 1752 int *row,*col,*cnew,j,*lens; 1753 IS icolp,irowp; 1754 1755 PetscFunctionBegin; 1756 ierr = ISInvertPermutation(rowp,&irowp); CHKERRQ(ierr); 1757 ierr = ISGetIndices(irowp,&row); CHKERRQ(ierr); 1758 ierr = ISInvertPermutation(colp,&icolp); CHKERRQ(ierr); 1759 ierr = ISGetIndices(icolp,&col); CHKERRQ(ierr); 1760 1761 /* determine lengths of permuted rows */ 1762 lens = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(lens); 1763 for (i=0; i<m; i++ ) { 1764 lens[row[i]] = a->i[i+1] - a->i[i]; 1765 } 1766 ierr = MatCreateSeqAIJ(A->comm,m,n,0,lens,B);CHKERRQ(ierr); 1767 PetscFree(lens); 1768 1769 cnew = (int *) PetscMalloc( n*sizeof(int) ); CHKPTRQ(cnew); 1770 for (i=0; i<m; i++) { 1771 ierr = MatGetRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr); 1772 for (j=0; j<nz; j++ ) { cnew[j] = col[cwork[j]];} 1773 ierr = MatSetValues(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES); CHKERRQ(ierr); 1774 ierr = MatRestoreRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr); 1775 } 1776 PetscFree(cnew); 1777 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1778 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1779 ierr = ISRestoreIndices(irowp,&row); CHKERRQ(ierr); 1780 ierr = ISRestoreIndices(icolp,&col); CHKERRQ(ierr); 1781 ierr = ISDestroy(irowp); CHKERRQ(ierr); 1782 ierr = ISDestroy(icolp); CHKERRQ(ierr); 1783 PetscFunctionReturn(0); 1784 } 1785 1786 #undef __FUNC__ 1787 #define __FUNC__ "MatPrintHelp_SeqAIJ" 1788 int MatPrintHelp_SeqAIJ(Mat A) 1789 { 1790 static int called = 0; 1791 MPI_Comm comm = A->comm; 1792 int ierr; 1793 1794 PetscFunctionBegin; 1795 if (called) {PetscFunctionReturn(0);} else called = 1; 1796 ierr = (*PetscHelpPrintf)(comm," Options for MATSEQAIJ and MATMPIAIJ matrix formats (the defaults):\n");CHKERRQ(ierr); 1797 ierr = (*PetscHelpPrintf)(comm," -mat_lu_pivotthreshold <threshold>: Set pivoting threshold\n");CHKERRQ(ierr); 1798 ierr = (*PetscHelpPrintf)(comm," -mat_aij_oneindex: internal indices begin at 1 instead of the default 0.\n");CHKERRQ(ierr); 1799 ierr = (*PetscHelpPrintf)(comm," -mat_aij_no_inode: Do not use inodes\n");CHKERRQ(ierr); 1800 ierr = (*PetscHelpPrintf)(comm," -mat_aij_inode_limit <limit>: Set inode limit (max limit=5)\n");CHKERRQ(ierr); 1801 #if defined(HAVE_ESSL) 1802 ierr = (*PetscHelpPrintf)(comm," -mat_aij_essl: Use IBM sparse LU factorization and solve.\n");CHKERRQ(ierr); 1803 #endif 1804 PetscFunctionReturn(0); 1805 } 1806 extern int MatEqual_SeqAIJ(Mat A,Mat B, PetscTruth* flg); 1807 extern int MatFDColoringCreate_SeqAIJ(Mat,ISColoring,MatFDColoring); 1808 extern int MatColoringPatch_SeqAIJ(Mat,int,int *,ISColoring *); 1809 1810 #undef __FUNC__ 1811 #define __FUNC__ "MatCopy_SeqAIJ" 1812 int MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 1813 { 1814 int ierr; 1815 1816 PetscFunctionBegin; 1817 if (str == SAME_NONZERO_PATTERN && B->type == MATSEQAIJ) { 1818 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1819 Mat_SeqAIJ *b = (Mat_SeqAIJ *) B->data; 1820 1821 if (a->i[a->m]+a->indexshift != b->i[b->m]+a->indexshift) { 1822 SETERRQ(1,1,"Number of nonzeros in two matrices are different"); 1823 } 1824 PetscMemcpy(b->a,a->a,(a->i[a->m]+a->indexshift)*sizeof(Scalar)); 1825 } else { 1826 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1827 } 1828 PetscFunctionReturn(0); 1829 } 1830 1831 /* -------------------------------------------------------------------*/ 1832 static struct _MatOps MatOps_Values = {MatSetValues_SeqAIJ, 1833 MatGetRow_SeqAIJ, 1834 MatRestoreRow_SeqAIJ, 1835 MatMult_SeqAIJ, 1836 MatMultAdd_SeqAIJ, 1837 MatMultTrans_SeqAIJ, 1838 MatMultTransAdd_SeqAIJ, 1839 MatSolve_SeqAIJ, 1840 MatSolveAdd_SeqAIJ, 1841 MatSolveTrans_SeqAIJ, 1842 MatSolveTransAdd_SeqAIJ, 1843 MatLUFactor_SeqAIJ, 1844 0, 1845 MatRelax_SeqAIJ, 1846 MatTranspose_SeqAIJ, 1847 MatGetInfo_SeqAIJ, 1848 MatEqual_SeqAIJ, 1849 MatGetDiagonal_SeqAIJ, 1850 MatDiagonalScale_SeqAIJ, 1851 MatNorm_SeqAIJ, 1852 0, 1853 MatAssemblyEnd_SeqAIJ, 1854 MatCompress_SeqAIJ, 1855 MatSetOption_SeqAIJ, 1856 MatZeroEntries_SeqAIJ, 1857 MatZeroRows_SeqAIJ, 1858 MatLUFactorSymbolic_SeqAIJ, 1859 MatLUFactorNumeric_SeqAIJ, 1860 0, 1861 0, 1862 MatGetSize_SeqAIJ, 1863 MatGetSize_SeqAIJ, 1864 MatGetOwnershipRange_SeqAIJ, 1865 MatILUFactorSymbolic_SeqAIJ, 1866 0, 1867 0, 1868 0, 1869 MatDuplicate_SeqAIJ, 1870 0, 1871 0, 1872 MatILUFactor_SeqAIJ, 1873 0, 1874 0, 1875 MatGetSubMatrices_SeqAIJ, 1876 MatIncreaseOverlap_SeqAIJ, 1877 MatGetValues_SeqAIJ, 1878 MatCopy_SeqAIJ, 1879 MatPrintHelp_SeqAIJ, 1880 MatScale_SeqAIJ, 1881 0, 1882 0, 1883 MatILUDTFactor_SeqAIJ, 1884 MatGetBlockSize_SeqAIJ, 1885 MatGetRowIJ_SeqAIJ, 1886 MatRestoreRowIJ_SeqAIJ, 1887 MatGetColumnIJ_SeqAIJ, 1888 MatRestoreColumnIJ_SeqAIJ, 1889 MatFDColoringCreate_SeqAIJ, 1890 MatColoringPatch_SeqAIJ, 1891 0, 1892 MatPermute_SeqAIJ, 1893 0, 1894 0, 1895 0, 1896 0, 1897 MatGetMaps_Petsc}; 1898 1899 extern int MatUseSuperLU_SeqAIJ(Mat); 1900 extern int MatUseEssl_SeqAIJ(Mat); 1901 extern int MatUseDXML_SeqAIJ(Mat); 1902 1903 EXTERN_C_BEGIN 1904 #undef __FUNC__ 1905 #define __FUNC__ "MatSeqAIJSetColumnIndices_SeqAIJ" 1906 1907 int MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,int *indices) 1908 { 1909 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 1910 int i,nz,n; 1911 1912 PetscFunctionBegin; 1913 if (aij->indexshift) SETERRQ(1,1,"No support with 1 based indexing"); 1914 1915 nz = aij->maxnz; 1916 n = aij->n; 1917 for (i=0; i<nz; i++) { 1918 aij->j[i] = indices[i]; 1919 } 1920 aij->nz = nz; 1921 for ( i=0; i<n; i++ ) { 1922 aij->ilen[i] = aij->imax[i]; 1923 } 1924 1925 PetscFunctionReturn(0); 1926 } 1927 EXTERN_C_END 1928 1929 #undef __FUNC__ 1930 #define __FUNC__ "MatSeqAIJSetColumnIndices" 1931 /*@ 1932 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 1933 in the matrix. 1934 1935 Input Parameters: 1936 + mat - the SeqAIJ matrix 1937 - indices - the column indices 1938 1939 Level: advanced 1940 1941 Notes: 1942 This can be called if you have precomputed the nonzero structure of the 1943 matrix and want to provide it to the matrix object to improve the performance 1944 of the MatSetValues() operation. 1945 1946 You MUST have set the correct numbers of nonzeros per row in the call to 1947 MatCreateSeqAIJ(). 1948 1949 MUST be called before any calls to MatSetValues(); 1950 1951 @*/ 1952 int MatSeqAIJSetColumnIndices(Mat mat,int *indices) 1953 { 1954 int ierr,(*f)(Mat,int *); 1955 1956 PetscFunctionBegin; 1957 PetscValidHeaderSpecific(mat,MAT_COOKIE); 1958 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqAIJSetColumnIndices_C",(void **)&f); 1959 CHKERRQ(ierr); 1960 if (f) { 1961 ierr = (*f)(mat,indices);CHKERRQ(ierr); 1962 } else { 1963 SETERRQ(1,1,"Wrong type of matrix to set column indices"); 1964 } 1965 PetscFunctionReturn(0); 1966 } 1967 1968 /* ----------------------------------------------------------------------------------------*/ 1969 1970 EXTERN_C_BEGIN 1971 #undef __FUNC__ 1972 #define __FUNC__ "MatStoreValues_SeqAIJ" 1973 int MatStoreValues_SeqAIJ(Mat mat) 1974 { 1975 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 1976 int nz = aij->i[aij->m]+aij->indexshift; 1977 1978 PetscFunctionBegin; 1979 if (aij->nonew != 1) { 1980 SETERRQ(1,1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 1981 } 1982 1983 /* allocate space for values if not already there */ 1984 if (!aij->saved_values) { 1985 aij->saved_values = (Scalar *) PetscMalloc(nz*sizeof(Scalar));CHKPTRQ(aij->saved_values); 1986 } 1987 1988 /* copy values over */ 1989 PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(Scalar)); 1990 PetscFunctionReturn(0); 1991 } 1992 EXTERN_C_END 1993 1994 #undef __FUNC__ 1995 #define __FUNC__ "MatStoreValues" 1996 /*@ 1997 MatStoreValues - Stashes a copy of the matrix values; this allows, for 1998 example, reuse of the linear part of a Jacobian, while recomputing the 1999 nonlinear portion. 2000 2001 Collect on Mat 2002 2003 Input Parameters: 2004 . mat - the matrix (currently on AIJ matrices support this option) 2005 2006 Level: advanced 2007 2008 Common Usage, with SNESSolve(): 2009 $ Create Jacobian matrix 2010 $ Set linear terms into matrix 2011 $ Apply boundary conditions to matrix, at this time matrix must have 2012 $ final nonzero structure (i.e. setting the nonlinear terms and applying 2013 $ boundary conditions again will not change the nonzero structure 2014 $ ierr = MatSetOption(mat,MAT_NO_NEW_NONZERO_LOCATIONS); 2015 $ ierr = MatStoreValues(mat); 2016 $ Call SNESSetJacobian() with matrix 2017 $ In your Jacobian routine 2018 $ ierr = MatRetrieveValues(mat); 2019 $ Set nonlinear terms in matrix 2020 2021 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 2022 $ // build linear portion of Jacobian 2023 $ ierr = MatSetOption(mat,MAT_NO_NEW_NONZERO_LOCATIONS); 2024 $ ierr = MatStoreValues(mat); 2025 $ loop over nonlinear iterations 2026 $ ierr = MatRetrieveValues(mat); 2027 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 2028 $ // call MatAssemblyBegin/End() on matrix 2029 $ Solve linear system with Jacobian 2030 $ endloop 2031 2032 Notes: 2033 Matrix must already be assemblied before calling this routine 2034 Must set the matrix option MatSetOption(mat,MAT_NO_NEW_NONZERO_LOCATIONS); before 2035 calling this routine. 2036 2037 .seealso: MatRetrieveValues() 2038 2039 @*/ 2040 int MatStoreValues(Mat mat) 2041 { 2042 int ierr,(*f)(Mat); 2043 2044 PetscFunctionBegin; 2045 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2046 if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix"); 2047 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 2048 2049 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatStoreValues_C",(void **)&f);CHKERRQ(ierr); 2050 if (f) { 2051 ierr = (*f)(mat);CHKERRQ(ierr); 2052 } else { 2053 SETERRQ(1,1,"Wrong type of matrix to store values"); 2054 } 2055 PetscFunctionReturn(0); 2056 } 2057 2058 EXTERN_C_BEGIN 2059 #undef __FUNC__ 2060 #define __FUNC__ "MatRetrieveValues_SeqAIJ" 2061 int MatRetrieveValues_SeqAIJ(Mat mat) 2062 { 2063 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2064 int nz = aij->i[aij->m]+aij->indexshift; 2065 2066 PetscFunctionBegin; 2067 if (aij->nonew != 1) { 2068 SETERRQ(1,1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 2069 } 2070 if (!aij->saved_values) { 2071 SETERRQ(1,1,"Must call MatStoreValues(A);first"); 2072 } 2073 2074 /* copy values over */ 2075 PetscMemcpy(aij->a, aij->saved_values,nz*sizeof(Scalar)); 2076 PetscFunctionReturn(0); 2077 } 2078 EXTERN_C_END 2079 2080 #undef __FUNC__ 2081 #define __FUNC__ "MatRetrieveValues" 2082 /*@ 2083 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 2084 example, reuse of the linear part of a Jacobian, while recomputing the 2085 nonlinear portion. 2086 2087 Collect on Mat 2088 2089 Input Parameters: 2090 . mat - the matrix (currently on AIJ matrices support this option) 2091 2092 Level: advanced 2093 2094 .seealso: MatStoreValues() 2095 2096 @*/ 2097 int MatRetrieveValues(Mat mat) 2098 { 2099 int ierr,(*f)(Mat); 2100 2101 PetscFunctionBegin; 2102 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2103 if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix"); 2104 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 2105 2106 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatRetrieveValues_C",(void **)&f);CHKERRQ(ierr); 2107 if (f) { 2108 ierr = (*f)(mat);CHKERRQ(ierr); 2109 } else { 2110 SETERRQ(1,1,"Wrong type of matrix to retrieve values"); 2111 } 2112 PetscFunctionReturn(0); 2113 } 2114 2115 /* --------------------------------------------------------------------------------*/ 2116 2117 #undef __FUNC__ 2118 #define __FUNC__ "MatCreateSeqAIJ" 2119 /*@C 2120 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 2121 (the default parallel PETSc format). For good matrix assembly performance 2122 the user should preallocate the matrix storage by setting the parameter nz 2123 (or the array nnz). By setting these parameters accurately, performance 2124 during matrix assembly can be increased by more than a factor of 50. 2125 2126 Collective on MPI_Comm 2127 2128 Input Parameters: 2129 + comm - MPI communicator, set to PETSC_COMM_SELF 2130 . m - number of rows 2131 . n - number of columns 2132 . nz - number of nonzeros per row (same for all rows) 2133 - nnz - array containing the number of nonzeros in the various rows 2134 (possibly different for each row) or PETSC_NULL 2135 2136 Output Parameter: 2137 . A - the matrix 2138 2139 Notes: 2140 The AIJ format (also called the Yale sparse matrix format or 2141 compressed row storage), is fully compatible with standard Fortran 77 2142 storage. That is, the stored row and column indices can begin at 2143 either one (as in Fortran) or zero. See the users' manual for details. 2144 2145 Specify the preallocated storage with either nz or nnz (not both). 2146 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2147 allocation. For large problems you MUST preallocate memory or you 2148 will get TERRIBLE performance, see the users' manual chapter on matrices. 2149 2150 By default, this format uses inodes (identical nodes) when possible, to 2151 improve numerical efficiency of matrix-vector products and solves. We 2152 search for consecutive rows with the same nonzero structure, thereby 2153 reusing matrix information to achieve increased efficiency. 2154 2155 Options Database Keys: 2156 + -mat_aij_no_inode - Do not use inodes 2157 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2158 - -mat_aij_oneindex - Internally use indexing starting at 1 2159 rather than 0. Note that when calling MatSetValues(), 2160 the user still MUST index entries starting at 0! 2161 2162 Level: intermediate 2163 2164 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices() 2165 @*/ 2166 int MatCreateSeqAIJ(MPI_Comm comm,int m,int n,int nz,int *nnz, Mat *A) 2167 { 2168 Mat B; 2169 Mat_SeqAIJ *b; 2170 int i, len, ierr, flg,size; 2171 2172 PetscFunctionBegin; 2173 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2174 if (size > 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Comm must be of size 1"); 2175 2176 *A = 0; 2177 PetscHeaderCreate(B,_p_Mat,struct _MatOps,MAT_COOKIE,MATSEQAIJ,"Mat",comm,MatDestroy,MatView); 2178 PLogObjectCreate(B); 2179 B->data = (void *) (b = PetscNew(Mat_SeqAIJ)); CHKPTRQ(b); 2180 PetscMemzero(b,sizeof(Mat_SeqAIJ)); 2181 PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps)); 2182 B->ops->destroy = MatDestroy_SeqAIJ; 2183 B->ops->view = MatView_SeqAIJ; 2184 B->factor = 0; 2185 B->lupivotthreshold = 1.0; 2186 B->mapping = 0; 2187 ierr = OptionsGetDouble(PETSC_NULL,"-mat_lu_pivotthreshold",&B->lupivotthreshold,&flg);CHKERRQ(ierr); 2188 b->ilu_preserve_row_sums = PETSC_FALSE; 2189 ierr = OptionsHasName(PETSC_NULL,"-pc_ilu_preserve_row_sums",(int*)&b->ilu_preserve_row_sums);CHKERRQ(ierr); 2190 b->row = 0; 2191 b->col = 0; 2192 b->icol = 0; 2193 b->indexshift = 0; 2194 b->reallocs = 0; 2195 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_oneindex", &flg); CHKERRQ(ierr); 2196 if (flg) b->indexshift = -1; 2197 2198 b->m = m; B->m = m; B->M = m; 2199 b->n = n; B->n = n; B->N = n; 2200 2201 ierr = MapCreateMPI(comm,m,m,&B->rmap);CHKERRQ(ierr); 2202 ierr = MapCreateMPI(comm,n,n,&B->cmap);CHKERRQ(ierr); 2203 2204 b->imax = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(b->imax); 2205 if (nnz == PETSC_NULL) { 2206 if (nz == PETSC_DEFAULT) nz = 10; 2207 else if (nz <= 0) nz = 1; 2208 for ( i=0; i<m; i++ ) b->imax[i] = nz; 2209 nz = nz*m; 2210 } else { 2211 nz = 0; 2212 for ( i=0; i<m; i++ ) {b->imax[i] = nnz[i]; nz += nnz[i];} 2213 } 2214 2215 /* allocate the matrix space */ 2216 len = nz*(sizeof(int) + sizeof(Scalar)) + (b->m+1)*sizeof(int); 2217 b->a = (Scalar *) PetscMalloc( len ); CHKPTRQ(b->a); 2218 b->j = (int *) (b->a + nz); 2219 PetscMemzero(b->j,nz*sizeof(int)); 2220 b->i = b->j + nz; 2221 b->singlemalloc = 1; 2222 2223 b->i[0] = -b->indexshift; 2224 for (i=1; i<m+1; i++) { 2225 b->i[i] = b->i[i-1] + b->imax[i-1]; 2226 } 2227 2228 /* b->ilen will count nonzeros in each row so far. */ 2229 b->ilen = (int *) PetscMalloc((m+1)*sizeof(int)); 2230 PLogObjectMemory(B,len+2*(m+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqAIJ)); 2231 for ( i=0; i<b->m; i++ ) { b->ilen[i] = 0;} 2232 2233 b->nz = 0; 2234 b->maxnz = nz; 2235 b->sorted = 0; 2236 b->roworiented = 1; 2237 b->nonew = 0; 2238 b->diag = 0; 2239 b->solve_work = 0; 2240 b->spptr = 0; 2241 b->inode.node_count = 0; 2242 b->inode.size = 0; 2243 b->inode.limit = 5; 2244 b->inode.max_limit = 5; 2245 b->saved_values = 0; 2246 B->info.nz_unneeded = (double)b->maxnz; 2247 b->idiag = 0; 2248 b->ssor = 0; 2249 2250 *A = B; 2251 2252 /* SuperLU is not currently supported through PETSc */ 2253 #if defined(HAVE_SUPERLU) 2254 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_superlu", &flg); CHKERRQ(ierr); 2255 if (flg) { ierr = MatUseSuperLU_SeqAIJ(B); CHKERRQ(ierr); } 2256 #endif 2257 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_essl", &flg); CHKERRQ(ierr); 2258 if (flg) { ierr = MatUseEssl_SeqAIJ(B); CHKERRQ(ierr); } 2259 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_dxml", &flg); CHKERRQ(ierr); 2260 if (flg) { 2261 if (!b->indexshift) SETERRQ( PETSC_ERR_LIB,0,"need -mat_aij_oneindex with -mat_aij_dxml"); 2262 ierr = MatUseDXML_SeqAIJ(B); CHKERRQ(ierr); 2263 } 2264 ierr = OptionsHasName(PETSC_NULL,"-help", &flg); CHKERRQ(ierr); 2265 if (flg) {ierr = MatPrintHelp(B); CHKERRQ(ierr); } 2266 2267 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C", 2268 "MatSeqAIJSetColumnIndices_SeqAIJ", 2269 (void*)MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 2270 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C", 2271 "MatStoreValues_SeqAIJ", 2272 (void*)MatStoreValues_SeqAIJ);CHKERRQ(ierr); 2273 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C", 2274 "MatRetrieveValues_SeqAIJ", 2275 (void*)MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 2276 PetscFunctionReturn(0); 2277 } 2278 2279 #undef __FUNC__ 2280 #define __FUNC__ "MatDuplicate_SeqAIJ" 2281 int MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 2282 { 2283 Mat C; 2284 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ *) A->data; 2285 int i,len, m = a->m,shift = a->indexshift,ierr; 2286 2287 PetscFunctionBegin; 2288 *B = 0; 2289 PetscHeaderCreate(C,_p_Mat,struct _MatOps,MAT_COOKIE,MATSEQAIJ,"Mat",A->comm,MatDestroy,MatView); 2290 PLogObjectCreate(C); 2291 C->data = (void *) (c = PetscNew(Mat_SeqAIJ)); CHKPTRQ(c); 2292 PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps)); 2293 C->ops->destroy = MatDestroy_SeqAIJ; 2294 C->ops->view = MatView_SeqAIJ; 2295 C->factor = A->factor; 2296 c->row = 0; 2297 c->col = 0; 2298 c->icol = 0; 2299 c->indexshift = shift; 2300 C->assembled = PETSC_TRUE; 2301 2302 c->m = C->m = a->m; 2303 c->n = C->n = a->n; 2304 C->M = a->m; 2305 C->N = a->n; 2306 2307 c->imax = (int *) PetscMalloc((m+1)*sizeof(int)); CHKPTRQ(c->imax); 2308 c->ilen = (int *) PetscMalloc((m+1)*sizeof(int)); CHKPTRQ(c->ilen); 2309 for ( i=0; i<m; i++ ) { 2310 c->imax[i] = a->imax[i]; 2311 c->ilen[i] = a->ilen[i]; 2312 } 2313 2314 /* allocate the matrix space */ 2315 c->singlemalloc = 1; 2316 len = (m+1)*sizeof(int)+(a->i[m])*(sizeof(Scalar)+sizeof(int)); 2317 c->a = (Scalar *) PetscMalloc( len ); CHKPTRQ(c->a); 2318 c->j = (int *) (c->a + a->i[m] + shift); 2319 c->i = c->j + a->i[m] + shift; 2320 PetscMemcpy(c->i,a->i,(m+1)*sizeof(int)); 2321 if (m > 0) { 2322 PetscMemcpy(c->j,a->j,(a->i[m]+shift)*sizeof(int)); 2323 if (cpvalues == MAT_COPY_VALUES) { 2324 PetscMemcpy(c->a,a->a,(a->i[m]+shift)*sizeof(Scalar)); 2325 } else { 2326 PetscMemzero(c->a,(a->i[m]+shift)*sizeof(Scalar)); 2327 } 2328 } 2329 2330 PLogObjectMemory(C,len+2*(m+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqAIJ)); 2331 c->sorted = a->sorted; 2332 c->roworiented = a->roworiented; 2333 c->nonew = a->nonew; 2334 c->ilu_preserve_row_sums = a->ilu_preserve_row_sums; 2335 c->saved_values = 0; 2336 c->idiag = 0; 2337 c->ssor = 0; 2338 2339 if (a->diag) { 2340 c->diag = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(c->diag); 2341 PLogObjectMemory(C,(m+1)*sizeof(int)); 2342 for ( i=0; i<m; i++ ) { 2343 c->diag[i] = a->diag[i]; 2344 } 2345 } else c->diag = 0; 2346 c->inode.limit = a->inode.limit; 2347 c->inode.max_limit = a->inode.max_limit; 2348 if (a->inode.size){ 2349 c->inode.size = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(c->inode.size); 2350 c->inode.node_count = a->inode.node_count; 2351 PetscMemcpy( c->inode.size, a->inode.size, (m+1)*sizeof(int)); 2352 } else { 2353 c->inode.size = 0; 2354 c->inode.node_count = 0; 2355 } 2356 c->nz = a->nz; 2357 c->maxnz = a->maxnz; 2358 c->solve_work = 0; 2359 c->spptr = 0; /* Dangerous -I'm throwing away a->spptr */ 2360 2361 *B = C; 2362 ierr = FListDuplicate(A->qlist,&C->qlist);CHKERRQ(ierr); 2363 PetscFunctionReturn(0); 2364 } 2365 2366 #undef __FUNC__ 2367 #define __FUNC__ "MatLoad_SeqAIJ" 2368 int MatLoad_SeqAIJ(Viewer viewer,MatType type,Mat *A) 2369 { 2370 Mat_SeqAIJ *a; 2371 Mat B; 2372 int i, nz, ierr, fd, header[4],size,*rowlengths = 0,M,N,shift; 2373 MPI_Comm comm; 2374 2375 PetscFunctionBegin; 2376 ierr = PetscObjectGetComm((PetscObject) viewer,&comm);CHKERRQ(ierr); 2377 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 2378 if (size > 1) SETERRQ(PETSC_ERR_ARG_SIZ,0,"view must have one processor"); 2379 ierr = ViewerBinaryGetDescriptor(viewer,&fd); CHKERRQ(ierr); 2380 ierr = PetscBinaryRead(fd,header,4,PETSC_INT); CHKERRQ(ierr); 2381 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"not matrix object in file"); 2382 M = header[1]; N = header[2]; nz = header[3]; 2383 2384 if (nz < 0) { 2385 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,1,"Matrix stored in special format on disk, cannot load as SeqAIJ"); 2386 } 2387 2388 /* read in row lengths */ 2389 rowlengths = (int*) PetscMalloc( M*sizeof(int) ); CHKPTRQ(rowlengths); 2390 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT); CHKERRQ(ierr); 2391 2392 /* create our matrix */ 2393 ierr = MatCreateSeqAIJ(comm,M,N,0,rowlengths,A); CHKERRQ(ierr); 2394 B = *A; 2395 a = (Mat_SeqAIJ *) B->data; 2396 shift = a->indexshift; 2397 2398 /* read in column indices and adjust for Fortran indexing*/ 2399 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT); CHKERRQ(ierr); 2400 if (shift) { 2401 for ( i=0; i<nz; i++ ) { 2402 a->j[i] += 1; 2403 } 2404 } 2405 2406 /* read in nonzero values */ 2407 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR); CHKERRQ(ierr); 2408 2409 /* set matrix "i" values */ 2410 a->i[0] = -shift; 2411 for ( i=1; i<= M; i++ ) { 2412 a->i[i] = a->i[i-1] + rowlengths[i-1]; 2413 a->ilen[i-1] = rowlengths[i-1]; 2414 } 2415 PetscFree(rowlengths); 2416 2417 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2418 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2419 PetscFunctionReturn(0); 2420 } 2421 2422 #undef __FUNC__ 2423 #define __FUNC__ "MatEqual_SeqAIJ" 2424 int MatEqual_SeqAIJ(Mat A,Mat B, PetscTruth* flg) 2425 { 2426 Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data, *b = (Mat_SeqAIJ *)B->data; 2427 2428 PetscFunctionBegin; 2429 if (B->type !=MATSEQAIJ)SETERRQ(PETSC_ERR_ARG_INCOMP,0,"Matrices must be same type"); 2430 2431 /* If the matrix dimensions are not equal, or no of nonzeros or shift */ 2432 if ((a->m != b->m ) || (a->n !=b->n) ||( a->nz != b->nz)|| 2433 (a->indexshift != b->indexshift)) { 2434 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2435 } 2436 2437 /* if the a->i are the same */ 2438 if (PetscMemcmp(a->i,b->i,(a->m+1)*sizeof(int))) { 2439 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2440 } 2441 2442 /* if a->j are the same */ 2443 if (PetscMemcmp(a->j, b->j, (a->nz)*sizeof(int))) { 2444 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2445 } 2446 2447 /* if a->a are the same */ 2448 if (PetscMemcmp(a->a, b->a, (a->nz)*sizeof(Scalar))) { 2449 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2450 } 2451 *flg = PETSC_TRUE; 2452 PetscFunctionReturn(0); 2453 2454 } 2455