1 #ifdef PETSC_RCS_HEADER 2 static char vcid[] = "$Id: aij.c,v 1.315 1999/03/24 15:20:47 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) ViewerASCIIPrintf(viewer," not using I-node routines\n"); 338 else ViewerASCIIPrintf(viewer," using I-node routines: found %d nodes, limit used is %d\n",a->inode.node_count,a->inode.limit); 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 MPI_Comm_rank(comm,&rank); 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; 571 572 PetscTruth isnull; 573 574 PetscFunctionBegin; 575 ierr = ViewerDrawGetDraw(viewer,0,&draw); CHKERRQ(ierr); 576 ierr = DrawIsNull(draw,&isnull); CHKERRQ(ierr); 577 if (isnull) PetscFunctionReturn(0); 578 579 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 580 xr = a->n; yr = a->m; h = yr/10.0; w = xr/10.0; 581 xr += w; yr += h; xl = -w; yl = -h; 582 ierr = DrawSetCoordinates(draw,xl,yl,xr,yr); CHKERRQ(ierr); 583 ierr = DrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A); CHKERRQ(ierr); 584 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); 585 PetscFunctionReturn(0); 586 } 587 588 #undef __FUNC__ 589 #define __FUNC__ "MatView_SeqAIJ" 590 int MatView_SeqAIJ(Mat A,Viewer viewer) 591 { 592 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 593 ViewerType vtype; 594 int ierr; 595 596 PetscFunctionBegin; 597 ierr = ViewerGetType(viewer,&vtype); CHKERRQ(ierr); 598 if (PetscTypeCompare(vtype,SOCKET_VIEWER)) { 599 ierr = ViewerSocketPutSparse_Private(viewer,a->m,a->n,a->nz,a->a,a->i,a->j);CHKERRQ(ierr); 600 } else if (PetscTypeCompare(vtype,ASCII_VIEWER)){ 601 ierr = MatView_SeqAIJ_ASCII(A,viewer); CHKERRQ(ierr); 602 } else if (PetscTypeCompare(vtype,BINARY_VIEWER)) { 603 ierr = MatView_SeqAIJ_Binary(A,viewer); CHKERRQ(ierr); 604 } else if (PetscTypeCompare(vtype,DRAW_VIEWER)) { 605 ierr = MatView_SeqAIJ_Draw(A,viewer); CHKERRQ(ierr); 606 } else { 607 SETERRQ(1,1,"Viewer type not supported by PETSc object"); 608 } 609 PetscFunctionReturn(0); 610 } 611 612 extern int Mat_AIJ_CheckInode(Mat); 613 #undef __FUNC__ 614 #define __FUNC__ "MatAssemblyEnd_SeqAIJ" 615 int MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 616 { 617 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 618 int fshift = 0,i,j,*ai = a->i, *aj = a->j, *imax = a->imax,ierr; 619 int m = a->m, *ip, N, *ailen = a->ilen,shift = a->indexshift,rmax = 0; 620 Scalar *aa = a->a, *ap; 621 622 PetscFunctionBegin; 623 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 624 625 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 626 for ( i=1; i<m; i++ ) { 627 /* move each row back by the amount of empty slots (fshift) before it*/ 628 fshift += imax[i-1] - ailen[i-1]; 629 rmax = PetscMax(rmax,ailen[i]); 630 if (fshift) { 631 ip = aj + ai[i] + shift; ap = aa + ai[i] + shift; 632 N = ailen[i]; 633 for ( j=0; j<N; j++ ) { 634 ip[j-fshift] = ip[j]; 635 ap[j-fshift] = ap[j]; 636 } 637 } 638 ai[i] = ai[i-1] + ailen[i-1]; 639 } 640 if (m) { 641 fshift += imax[m-1] - ailen[m-1]; 642 ai[m] = ai[m-1] + ailen[m-1]; 643 } 644 /* reset ilen and imax for each row */ 645 for ( i=0; i<m; i++ ) { 646 ailen[i] = imax[i] = ai[i+1] - ai[i]; 647 } 648 a->nz = ai[m] + shift; 649 650 /* diagonals may have moved, so kill the diagonal pointers */ 651 if (fshift && a->diag) { 652 PetscFree(a->diag); 653 PLogObjectMemory(A,-(m+1)*sizeof(int)); 654 a->diag = 0; 655 } 656 PLogInfo(A,"MatAssemblyEnd_SeqAIJ:Matrix size: %d X %d; storage space: %d unneeded, %d used\n", 657 m,a->n,fshift,a->nz); 658 PLogInfo(A,"MatAssemblyEnd_SeqAIJ:Number of mallocs during MatSetValues() is %d\n", 659 a->reallocs); 660 PLogInfo(A,"MatAssemblyEnd_SeqAIJ:Most nonzeros in any row is %d\n",rmax); 661 a->reallocs = 0; 662 A->info.nz_unneeded = (double)fshift; 663 664 /* check out for identical nodes. If found, use inode functions */ 665 ierr = Mat_AIJ_CheckInode(A); CHKERRQ(ierr); 666 PetscFunctionReturn(0); 667 } 668 669 #undef __FUNC__ 670 #define __FUNC__ "MatZeroEntries_SeqAIJ" 671 int MatZeroEntries_SeqAIJ(Mat A) 672 { 673 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 674 675 PetscFunctionBegin; 676 PetscMemzero(a->a,(a->i[a->m]+a->indexshift)*sizeof(Scalar)); 677 PetscFunctionReturn(0); 678 } 679 680 #undef __FUNC__ 681 #define __FUNC__ "MatDestroy_SeqAIJ" 682 int MatDestroy_SeqAIJ(Mat A) 683 { 684 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 685 int ierr; 686 687 PetscFunctionBegin; 688 if (--A->refct > 0) PetscFunctionReturn(0); 689 690 if (A->mapping) { 691 ierr = ISLocalToGlobalMappingDestroy(A->mapping); CHKERRQ(ierr); 692 } 693 if (A->bmapping) { 694 ierr = ISLocalToGlobalMappingDestroy(A->bmapping); CHKERRQ(ierr); 695 } 696 if (A->rmap) { 697 ierr = MapDestroy(A->rmap);CHKERRQ(ierr); 698 } 699 if (A->cmap) { 700 ierr = MapDestroy(A->cmap);CHKERRQ(ierr); 701 } 702 if (a->idiag) PetscFree(a->idiag); 703 #if defined(USE_PETSC_LOG) 704 PLogObjectState((PetscObject)A,"Rows=%d, Cols=%d, NZ=%d",a->m,a->n,a->nz); 705 #endif 706 PetscFree(a->a); 707 if (!a->singlemalloc) { PetscFree(a->i); PetscFree(a->j);} 708 if (a->diag) PetscFree(a->diag); 709 if (a->ilen) PetscFree(a->ilen); 710 if (a->imax) PetscFree(a->imax); 711 if (a->solve_work) PetscFree(a->solve_work); 712 if (a->inode.size) PetscFree(a->inode.size); 713 if (a->icol) {ierr = ISDestroy(a->icol);CHKERRQ(ierr);} 714 if (a->saved_values) PetscFree(a->saved_values); 715 PetscFree(a); 716 717 PLogObjectDestroy(A); 718 PetscHeaderDestroy(A); 719 PetscFunctionReturn(0); 720 } 721 722 #undef __FUNC__ 723 #define __FUNC__ "MatCompress_SeqAIJ" 724 int MatCompress_SeqAIJ(Mat A) 725 { 726 PetscFunctionBegin; 727 PetscFunctionReturn(0); 728 } 729 730 #undef __FUNC__ 731 #define __FUNC__ "MatSetOption_SeqAIJ" 732 int MatSetOption_SeqAIJ(Mat A,MatOption op) 733 { 734 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 735 736 PetscFunctionBegin; 737 if (op == MAT_ROW_ORIENTED) a->roworiented = 1; 738 else if (op == MAT_COLUMN_ORIENTED) a->roworiented = 0; 739 else if (op == MAT_COLUMNS_SORTED) a->sorted = 1; 740 else if (op == MAT_COLUMNS_UNSORTED) a->sorted = 0; 741 else if (op == MAT_NO_NEW_NONZERO_LOCATIONS) a->nonew = 1; 742 else if (op == MAT_NEW_NONZERO_LOCATION_ERR) a->nonew = -1; 743 else if (op == MAT_NEW_NONZERO_ALLOCATION_ERR) a->nonew = -2; 744 else if (op == MAT_YES_NEW_NONZERO_LOCATIONS) a->nonew = 0; 745 else if (op == MAT_ROWS_SORTED || 746 op == MAT_ROWS_UNSORTED || 747 op == MAT_SYMMETRIC || 748 op == MAT_STRUCTURALLY_SYMMETRIC || 749 op == MAT_YES_NEW_DIAGONALS || 750 op == MAT_IGNORE_OFF_PROC_ENTRIES|| 751 op == MAT_USE_HASH_TABLE) 752 PLogInfo(A,"MatSetOption_SeqAIJ:Option ignored\n"); 753 else if (op == MAT_NO_NEW_DIAGONALS) { 754 SETERRQ(PETSC_ERR_SUP,0,"MAT_NO_NEW_DIAGONALS"); 755 } else if (op == MAT_INODE_LIMIT_1) a->inode.limit = 1; 756 else if (op == MAT_INODE_LIMIT_2) a->inode.limit = 2; 757 else if (op == MAT_INODE_LIMIT_3) a->inode.limit = 3; 758 else if (op == MAT_INODE_LIMIT_4) a->inode.limit = 4; 759 else if (op == MAT_INODE_LIMIT_5) a->inode.limit = 5; 760 else SETERRQ(PETSC_ERR_SUP,0,"unknown option"); 761 PetscFunctionReturn(0); 762 } 763 764 #undef __FUNC__ 765 #define __FUNC__ "MatGetDiagonal_SeqAIJ" 766 int MatGetDiagonal_SeqAIJ(Mat A,Vec v) 767 { 768 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 769 int i,j, n,shift = a->indexshift,ierr; 770 Scalar *x, zero = 0.0; 771 772 PetscFunctionBegin; 773 ierr = VecSet(&zero,v);CHKERRQ(ierr); 774 ierr = VecGetArray(v,&x);;CHKERRQ(ierr); 775 ierr = VecGetLocalSize(v,&n);;CHKERRQ(ierr); 776 if (n != a->m) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Nonconforming matrix and vector"); 777 for ( i=0; i<a->m; i++ ) { 778 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 779 if (a->j[j]+shift == i) { 780 x[i] = a->a[j]; 781 break; 782 } 783 } 784 } 785 ierr = VecRestoreArray(v,&x);;CHKERRQ(ierr); 786 PetscFunctionReturn(0); 787 } 788 789 /* -------------------------------------------------------*/ 790 /* Should check that shapes of vectors and matrices match */ 791 /* -------------------------------------------------------*/ 792 #undef __FUNC__ 793 #define __FUNC__ "MatMultTrans_SeqAIJ" 794 int MatMultTrans_SeqAIJ(Mat A,Vec xx,Vec yy) 795 { 796 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 797 Scalar *x, *y, *v, alpha; 798 int ierr,m = a->m, n, i, *idx, shift = a->indexshift; 799 800 PetscFunctionBegin; 801 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 802 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 803 PetscMemzero(y,a->n*sizeof(Scalar)); 804 y = y + shift; /* shift for Fortran start by 1 indexing */ 805 for ( i=0; i<m; i++ ) { 806 idx = a->j + a->i[i] + shift; 807 v = a->a + a->i[i] + shift; 808 n = a->i[i+1] - a->i[i]; 809 alpha = x[i]; 810 while (n-->0) {y[*idx++] += alpha * *v++;} 811 } 812 PLogFlops(2*a->nz - a->n); 813 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 814 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 815 PetscFunctionReturn(0); 816 } 817 818 #undef __FUNC__ 819 #define __FUNC__ "MatMultTransAdd_SeqAIJ" 820 int MatMultTransAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 821 { 822 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 823 Scalar *x, *y, *v, alpha; 824 int ierr,m = a->m, n, i, *idx,shift = a->indexshift; 825 826 PetscFunctionBegin; 827 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 828 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 829 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 830 y = y + shift; /* shift for Fortran start by 1 indexing */ 831 for ( i=0; i<m; i++ ) { 832 idx = a->j + a->i[i] + shift; 833 v = a->a + a->i[i] + shift; 834 n = a->i[i+1] - a->i[i]; 835 alpha = x[i]; 836 while (n-->0) {y[*idx++] += alpha * *v++;} 837 } 838 PLogFlops(2*a->nz); 839 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 840 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 841 PetscFunctionReturn(0); 842 } 843 844 #undef __FUNC__ 845 #define __FUNC__ "MatMult_SeqAIJ" 846 int MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 847 { 848 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 849 Scalar *x, *y, *v, sum; 850 int ierr,m = a->m, *idx, shift = a->indexshift,*ii; 851 #if !defined(USE_FORTRAN_KERNEL_MULTAIJ) 852 int n, i, jrow,j; 853 #endif 854 855 #if defined(HAVE_PRAGMA_DISJOINT) 856 #pragma disjoint(*x,*y,*v) 857 #endif 858 859 PetscFunctionBegin; 860 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 861 ierr = VecGetArray(yy,&y); CHKERRQ(ierr); 862 x = x + shift; /* shift for Fortran start by 1 indexing */ 863 idx = a->j; 864 v = a->a; 865 ii = a->i; 866 #if defined(USE_FORTRAN_KERNEL_MULTAIJ) 867 fortranmultaij_(&m,x,ii,idx+shift,v+shift,y); 868 #else 869 v += shift; /* shift for Fortran start by 1 indexing */ 870 idx += shift; 871 for ( i=0; i<m; i++ ) { 872 jrow = ii[i]; 873 n = ii[i+1] - jrow; 874 sum = 0.0; 875 for ( j=0; j<n; j++) { 876 sum += v[jrow]*x[idx[jrow]]; jrow++; 877 } 878 y[i] = sum; 879 } 880 #endif 881 PLogFlops(2*a->nz - m); 882 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 883 ierr = VecRestoreArray(yy,&y); CHKERRQ(ierr); 884 PetscFunctionReturn(0); 885 } 886 887 #undef __FUNC__ 888 #define __FUNC__ "MatMultAdd_SeqAIJ" 889 int MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 890 { 891 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 892 Scalar *x, *y, *z, *v, sum; 893 int ierr,m = a->m, *idx, shift = a->indexshift,*ii; 894 #if !defined(USE_FORTRAN_KERNEL_MULTADDAIJ) 895 int n,i,jrow,j; 896 #endif 897 898 PetscFunctionBegin; 899 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 900 ierr = VecGetArray(yy,&y); CHKERRQ(ierr); 901 if (zz != yy) { 902 ierr = VecGetArray(zz,&z); CHKERRQ(ierr); 903 } else { 904 z = y; 905 } 906 x = x + shift; /* shift for Fortran start by 1 indexing */ 907 idx = a->j; 908 v = a->a; 909 ii = a->i; 910 #if defined(USE_FORTRAN_KERNEL_MULTADDAIJ) 911 fortranmultaddaij_(&m,x,ii,idx+shift,v+shift,y,z); 912 #else 913 v += shift; /* shift for Fortran start by 1 indexing */ 914 idx += shift; 915 for ( i=0; i<m; i++ ) { 916 jrow = ii[i]; 917 n = ii[i+1] - jrow; 918 sum = y[i]; 919 for ( j=0; j<n; j++) { 920 sum += v[jrow]*x[idx[jrow]]; jrow++; 921 } 922 z[i] = sum; 923 } 924 #endif 925 PLogFlops(2*a->nz); 926 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 927 ierr = VecRestoreArray(yy,&y); CHKERRQ(ierr); 928 if (zz != yy) { 929 ierr = VecRestoreArray(zz,&z); CHKERRQ(ierr); 930 } 931 PetscFunctionReturn(0); 932 } 933 934 /* 935 Adds diagonal pointers to sparse matrix structure. 936 */ 937 #undef __FUNC__ 938 #define __FUNC__ "MatMarkDiag_SeqAIJ" 939 int MatMarkDiag_SeqAIJ(Mat A) 940 { 941 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 942 int i,j, *diag, m = a->m,shift = a->indexshift; 943 944 PetscFunctionBegin; 945 diag = (int *) PetscMalloc( (m+1)*sizeof(int)); CHKPTRQ(diag); 946 PLogObjectMemory(A,(m+1)*sizeof(int)); 947 for ( i=0; i<a->m; i++ ) { 948 diag[i] = a->i[i+1]; 949 for ( j=a->i[i]+shift; j<a->i[i+1]+shift; j++ ) { 950 if (a->j[j]+shift == i) { 951 diag[i] = j - shift; 952 break; 953 } 954 } 955 } 956 a->diag = diag; 957 PetscFunctionReturn(0); 958 } 959 960 /* 961 Checks for missing diagonals 962 */ 963 #undef __FUNC__ 964 #define __FUNC__ "MatMissingDiag_SeqAIJ" 965 int MatMissingDiag_SeqAIJ(Mat A) 966 { 967 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 968 int *diag = a->diag, *jj = a->j,i,shift = a->indexshift; 969 970 PetscFunctionBegin; 971 for ( i=0; i<a->m; i++ ) { 972 if (jj[diag[i]+shift] != i-shift) { 973 SETERRQ1(1,1,"Matrix is missing diagonal number %d",i); 974 } 975 } 976 PetscFunctionReturn(0); 977 } 978 979 #undef __FUNC__ 980 #define __FUNC__ "MatRelax_SeqAIJ" 981 int MatRelax_SeqAIJ(Mat A,Vec bb,double omega,MatSORType flag,double fshift,int its,Vec xx) 982 { 983 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 984 Scalar *x, *b, *bs, d, *xs, sum, *v = a->a,*t=0,scale,*ts, *xb,*idiag=0; 985 int ierr, *idx, *diag,n = a->n, m = a->m, i, shift = a->indexshift; 986 987 PetscFunctionBegin; 988 ierr = VecGetArray(xx,&x); CHKERRQ(ierr); 989 if (xx != bb) { 990 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 991 } else { 992 b = x; 993 } 994 995 if (!a->diag) {ierr = MatMarkDiag_SeqAIJ(A);CHKERRQ(ierr);} 996 diag = a->diag; 997 xs = x + shift; /* shifted by one for index start of a or a->j*/ 998 if (flag == SOR_APPLY_UPPER) { 999 /* apply ( U + D/omega) to the vector */ 1000 bs = b + shift; 1001 for ( i=0; i<m; i++ ) { 1002 d = fshift + a->a[diag[i] + shift]; 1003 n = a->i[i+1] - diag[i] - 1; 1004 PLogFlops(2*n-1); 1005 idx = a->j + diag[i] + (!shift); 1006 v = a->a + diag[i] + (!shift); 1007 sum = b[i]*d/omega; 1008 SPARSEDENSEDOT(sum,bs,v,idx,n); 1009 x[i] = sum; 1010 } 1011 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1012 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1013 PetscFunctionReturn(0); 1014 } 1015 1016 /* setup workspace for Eisenstat */ 1017 if (flag & SOR_EISENSTAT) { 1018 if (!a->idiag) { 1019 a->idiag = (Scalar *) PetscMalloc(2*m*sizeof(Scalar));CHKPTRQ(a->idiag); 1020 a->ssor = a->idiag + m; 1021 v = a->a; 1022 for ( i=0; i<m; i++ ) { a->idiag[i] = 1.0/v[diag[i]];} 1023 } 1024 t = a->ssor; 1025 idiag = a->idiag; 1026 } 1027 /* Let A = L + U + D; where L is lower trianglar, 1028 U is upper triangular, E is diagonal; This routine applies 1029 1030 (L + E)^{-1} A (U + E)^{-1} 1031 1032 to a vector efficiently using Eisenstat's trick. This is for 1033 the case of SSOR preconditioner, so E is D/omega where omega 1034 is the relaxation factor. 1035 */ 1036 1037 if (flag == SOR_APPLY_LOWER) { 1038 SETERRQ(PETSC_ERR_SUP,0,"SOR_APPLY_LOWER is not done"); 1039 } else if ((flag & SOR_EISENSTAT) && omega == 1.0 && shift == 0 && fshift == 0.0) { 1040 /* special case for omega = 1.0 saves flops and some integer ops */ 1041 Scalar *v2; 1042 1043 v2 = a->a; 1044 /* x = (E + U)^{-1} b */ 1045 for ( i=m-1; i>=0; i-- ) { 1046 n = a->i[i+1] - diag[i] - 1; 1047 idx = a->j + diag[i] + 1; 1048 v = a->a + diag[i] + 1; 1049 sum = b[i]; 1050 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1051 x[i] = sum*idiag[i]; 1052 1053 /* t = b - (2*E - D)x */ 1054 t[i] = b[i] - (v2[diag[i]])*x[i]; 1055 } 1056 1057 /* t = (E + L)^{-1}t */ 1058 diag = a->diag; 1059 for ( i=0; i<m; i++ ) { 1060 n = diag[i] - a->i[i]; 1061 idx = a->j + a->i[i]; 1062 v = a->a + a->i[i]; 1063 sum = t[i]; 1064 SPARSEDENSEMDOT(sum,t,v,idx,n); 1065 t[i] = sum*idiag[i]; 1066 1067 /* x = x + t */ 1068 x[i] += t[i]; 1069 } 1070 1071 PLogFlops(3*m-1 + 2*a->nz); 1072 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1073 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1074 PetscFunctionReturn(0); 1075 } else if (flag & SOR_EISENSTAT) { 1076 /* Let A = L + U + D; where L is lower trianglar, 1077 U is upper triangular, E is diagonal; This routine applies 1078 1079 (L + E)^{-1} A (U + E)^{-1} 1080 1081 to a vector efficiently using Eisenstat's trick. This is for 1082 the case of SSOR preconditioner, so E is D/omega where omega 1083 is the relaxation factor. 1084 */ 1085 scale = (2.0/omega) - 1.0; 1086 1087 /* x = (E + U)^{-1} b */ 1088 for ( i=m-1; i>=0; i-- ) { 1089 d = fshift + a->a[diag[i] + shift]; 1090 n = a->i[i+1] - diag[i] - 1; 1091 idx = a->j + diag[i] + (!shift); 1092 v = a->a + diag[i] + (!shift); 1093 sum = b[i]; 1094 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1095 x[i] = omega*(sum/d); 1096 } 1097 1098 /* t = b - (2*E - D)x */ 1099 v = a->a; 1100 for ( i=0; i<m; i++ ) { t[i] = b[i] - scale*(v[*diag++ + shift])*x[i]; } 1101 1102 /* t = (E + L)^{-1}t */ 1103 ts = t + shift; /* shifted by one for index start of a or a->j*/ 1104 diag = a->diag; 1105 for ( i=0; i<m; i++ ) { 1106 d = fshift + a->a[diag[i]+shift]; 1107 n = diag[i] - a->i[i]; 1108 idx = a->j + a->i[i] + shift; 1109 v = a->a + a->i[i] + shift; 1110 sum = t[i]; 1111 SPARSEDENSEMDOT(sum,ts,v,idx,n); 1112 t[i] = omega*(sum/d); 1113 /* x = x + t */ 1114 x[i] += t[i]; 1115 } 1116 1117 PLogFlops(6*m-1 + 2*a->nz); 1118 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1119 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1120 PetscFunctionReturn(0); 1121 } 1122 if (flag & SOR_ZERO_INITIAL_GUESS) { 1123 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 1124 for ( i=0; i<m; i++ ) { 1125 d = fshift + a->a[diag[i]+shift]; 1126 n = diag[i] - a->i[i]; 1127 PLogFlops(2*n-1); 1128 idx = a->j + a->i[i] + shift; 1129 v = a->a + a->i[i] + shift; 1130 sum = b[i]; 1131 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1132 x[i] = omega*(sum/d); 1133 } 1134 xb = x; 1135 } else xb = b; 1136 if ((flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) && 1137 (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP)) { 1138 for ( i=0; i<m; i++ ) { 1139 x[i] *= a->a[diag[i]+shift]; 1140 } 1141 PLogFlops(m); 1142 } 1143 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 1144 for ( i=m-1; i>=0; i-- ) { 1145 d = fshift + a->a[diag[i] + shift]; 1146 n = a->i[i+1] - diag[i] - 1; 1147 PLogFlops(2*n-1); 1148 idx = a->j + diag[i] + (!shift); 1149 v = a->a + diag[i] + (!shift); 1150 sum = xb[i]; 1151 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1152 x[i] = omega*(sum/d); 1153 } 1154 } 1155 its--; 1156 } 1157 while (its--) { 1158 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 1159 for ( i=0; i<m; i++ ) { 1160 d = fshift + a->a[diag[i]+shift]; 1161 n = a->i[i+1] - a->i[i]; 1162 PLogFlops(2*n-1); 1163 idx = a->j + a->i[i] + shift; 1164 v = a->a + a->i[i] + shift; 1165 sum = b[i]; 1166 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1167 x[i] = (1. - omega)*x[i] + omega*(sum + a->a[diag[i]+shift]*x[i])/d; 1168 } 1169 } 1170 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 1171 for ( i=m-1; i>=0; i-- ) { 1172 d = fshift + a->a[diag[i] + shift]; 1173 n = a->i[i+1] - a->i[i]; 1174 PLogFlops(2*n-1); 1175 idx = a->j + a->i[i] + shift; 1176 v = a->a + a->i[i] + shift; 1177 sum = b[i]; 1178 SPARSEDENSEMDOT(sum,xs,v,idx,n); 1179 x[i] = (1. - omega)*x[i] + omega*(sum + a->a[diag[i]+shift]*x[i])/d; 1180 } 1181 } 1182 } 1183 ierr = VecRestoreArray(xx,&x); CHKERRQ(ierr); 1184 if (bb != xx) {ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr);} 1185 PetscFunctionReturn(0); 1186 } 1187 1188 #undef __FUNC__ 1189 #define __FUNC__ "MatGetInfo_SeqAIJ" 1190 int MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1191 { 1192 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1193 1194 PetscFunctionBegin; 1195 info->rows_global = (double)a->m; 1196 info->columns_global = (double)a->n; 1197 info->rows_local = (double)a->m; 1198 info->columns_local = (double)a->n; 1199 info->block_size = 1.0; 1200 info->nz_allocated = (double)a->maxnz; 1201 info->nz_used = (double)a->nz; 1202 info->nz_unneeded = (double)(a->maxnz - a->nz); 1203 info->assemblies = (double)A->num_ass; 1204 info->mallocs = (double)a->reallocs; 1205 info->memory = A->mem; 1206 if (A->factor) { 1207 info->fill_ratio_given = A->info.fill_ratio_given; 1208 info->fill_ratio_needed = A->info.fill_ratio_needed; 1209 info->factor_mallocs = A->info.factor_mallocs; 1210 } else { 1211 info->fill_ratio_given = 0; 1212 info->fill_ratio_needed = 0; 1213 info->factor_mallocs = 0; 1214 } 1215 PetscFunctionReturn(0); 1216 } 1217 1218 extern int MatLUFactorSymbolic_SeqAIJ(Mat,IS,IS,double,Mat*); 1219 extern int MatLUFactorNumeric_SeqAIJ(Mat,Mat*); 1220 extern int MatLUFactor_SeqAIJ(Mat,IS,IS,double); 1221 extern int MatSolve_SeqAIJ(Mat,Vec,Vec); 1222 extern int MatSolveAdd_SeqAIJ(Mat,Vec,Vec,Vec); 1223 extern int MatSolveTrans_SeqAIJ(Mat,Vec,Vec); 1224 extern int MatSolveTransAdd_SeqAIJ(Mat,Vec,Vec,Vec); 1225 1226 #undef __FUNC__ 1227 #define __FUNC__ "MatZeroRows_SeqAIJ" 1228 int MatZeroRows_SeqAIJ(Mat A,IS is,Scalar *diag) 1229 { 1230 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1231 int i,ierr,N, *rows,m = a->m - 1,shift = a->indexshift; 1232 1233 PetscFunctionBegin; 1234 ierr = ISGetSize(is,&N); CHKERRQ(ierr); 1235 ierr = ISGetIndices(is,&rows); CHKERRQ(ierr); 1236 if (diag) { 1237 for ( i=0; i<N; i++ ) { 1238 if (rows[i] < 0 || rows[i] > m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"row out of range"); 1239 if (a->ilen[rows[i]] > 0) { 1240 a->ilen[rows[i]] = 1; 1241 a->a[a->i[rows[i]]+shift] = *diag; 1242 a->j[a->i[rows[i]]+shift] = rows[i]+shift; 1243 } else { /* in case row was completely empty */ 1244 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],diag,INSERT_VALUES);CHKERRQ(ierr); 1245 } 1246 } 1247 } else { 1248 for ( i=0; i<N; i++ ) { 1249 if (rows[i] < 0 || rows[i] > m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"row out of range"); 1250 a->ilen[rows[i]] = 0; 1251 } 1252 } 1253 ierr = ISRestoreIndices(is,&rows);CHKERRQ(ierr); 1254 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1255 PetscFunctionReturn(0); 1256 } 1257 1258 #undef __FUNC__ 1259 #define __FUNC__ "MatGetSize_SeqAIJ" 1260 int MatGetSize_SeqAIJ(Mat A,int *m,int *n) 1261 { 1262 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1263 1264 PetscFunctionBegin; 1265 if (m) *m = a->m; 1266 if (n) *n = a->n; 1267 PetscFunctionReturn(0); 1268 } 1269 1270 #undef __FUNC__ 1271 #define __FUNC__ "MatGetOwnershipRange_SeqAIJ" 1272 int MatGetOwnershipRange_SeqAIJ(Mat A,int *m,int *n) 1273 { 1274 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1275 1276 PetscFunctionBegin; 1277 *m = 0; *n = a->m; 1278 PetscFunctionReturn(0); 1279 } 1280 1281 #undef __FUNC__ 1282 #define __FUNC__ "MatGetRow_SeqAIJ" 1283 int MatGetRow_SeqAIJ(Mat A,int row,int *nz,int **idx,Scalar **v) 1284 { 1285 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1286 int *itmp,i,shift = a->indexshift; 1287 1288 PetscFunctionBegin; 1289 if (row < 0 || row >= a->m) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Row out of range"); 1290 1291 *nz = a->i[row+1] - a->i[row]; 1292 if (v) *v = a->a + a->i[row] + shift; 1293 if (idx) { 1294 itmp = a->j + a->i[row] + shift; 1295 if (*nz && shift) { 1296 *idx = (int *) PetscMalloc( (*nz)*sizeof(int) ); CHKPTRQ(*idx); 1297 for ( i=0; i<(*nz); i++ ) {(*idx)[i] = itmp[i] + shift;} 1298 } else if (*nz) { 1299 *idx = itmp; 1300 } 1301 else *idx = 0; 1302 } 1303 PetscFunctionReturn(0); 1304 } 1305 1306 #undef __FUNC__ 1307 #define __FUNC__ "MatRestoreRow_SeqAIJ" 1308 int MatRestoreRow_SeqAIJ(Mat A,int row,int *nz,int **idx,Scalar **v) 1309 { 1310 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1311 1312 PetscFunctionBegin; 1313 if (idx) {if (*idx && a->indexshift) PetscFree(*idx);} 1314 PetscFunctionReturn(0); 1315 } 1316 1317 #undef __FUNC__ 1318 #define __FUNC__ "MatNorm_SeqAIJ" 1319 int MatNorm_SeqAIJ(Mat A,NormType type,double *norm) 1320 { 1321 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1322 Scalar *v = a->a; 1323 double sum = 0.0; 1324 int i, j,shift = a->indexshift; 1325 1326 PetscFunctionBegin; 1327 if (type == NORM_FROBENIUS) { 1328 for (i=0; i<a->nz; i++ ) { 1329 #if defined(USE_PETSC_COMPLEX) 1330 sum += PetscReal(PetscConj(*v)*(*v)); v++; 1331 #else 1332 sum += (*v)*(*v); v++; 1333 #endif 1334 } 1335 *norm = sqrt(sum); 1336 } else if (type == NORM_1) { 1337 double *tmp; 1338 int *jj = a->j; 1339 tmp = (double *) PetscMalloc( (a->n+1)*sizeof(double) ); CHKPTRQ(tmp); 1340 PetscMemzero(tmp,a->n*sizeof(double)); 1341 *norm = 0.0; 1342 for ( j=0; j<a->nz; j++ ) { 1343 tmp[*jj++ + shift] += PetscAbsScalar(*v); v++; 1344 } 1345 for ( j=0; j<a->n; j++ ) { 1346 if (tmp[j] > *norm) *norm = tmp[j]; 1347 } 1348 PetscFree(tmp); 1349 } else if (type == NORM_INFINITY) { 1350 *norm = 0.0; 1351 for ( j=0; j<a->m; j++ ) { 1352 v = a->a + a->i[j] + shift; 1353 sum = 0.0; 1354 for ( i=0; i<a->i[j+1]-a->i[j]; i++ ) { 1355 sum += PetscAbsScalar(*v); v++; 1356 } 1357 if (sum > *norm) *norm = sum; 1358 } 1359 } else { 1360 SETERRQ(PETSC_ERR_SUP,0,"No support for two norm"); 1361 } 1362 PetscFunctionReturn(0); 1363 } 1364 1365 #undef __FUNC__ 1366 #define __FUNC__ "MatTranspose_SeqAIJ" 1367 int MatTranspose_SeqAIJ(Mat A,Mat *B) 1368 { 1369 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1370 Mat C; 1371 int i, ierr, *aj = a->j, *ai = a->i, m = a->m, len, *col; 1372 int shift = a->indexshift; 1373 Scalar *array = a->a; 1374 1375 PetscFunctionBegin; 1376 if (B == PETSC_NULL && m != a->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Square matrix only for in-place"); 1377 col = (int *) PetscMalloc((1+a->n)*sizeof(int)); CHKPTRQ(col); 1378 PetscMemzero(col,(1+a->n)*sizeof(int)); 1379 if (shift) { 1380 for ( i=0; i<ai[m]-1; i++ ) aj[i] -= 1; 1381 } 1382 for ( i=0; i<ai[m]+shift; i++ ) col[aj[i]] += 1; 1383 ierr = MatCreateSeqAIJ(A->comm,a->n,m,0,col,&C); CHKERRQ(ierr); 1384 PetscFree(col); 1385 for ( i=0; i<m; i++ ) { 1386 len = ai[i+1]-ai[i]; 1387 ierr = MatSetValues(C,len,aj,1,&i,array,INSERT_VALUES); CHKERRQ(ierr); 1388 array += len; aj += len; 1389 } 1390 if (shift) { 1391 for ( i=0; i<ai[m]-1; i++ ) aj[i] += 1; 1392 } 1393 1394 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1395 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1396 1397 if (B != PETSC_NULL) { 1398 *B = C; 1399 } else { 1400 PetscOps *Abops; 1401 MatOps Aops; 1402 1403 /* This isn't really an in-place transpose */ 1404 PetscFree(a->a); 1405 if (!a->singlemalloc) {PetscFree(a->i); PetscFree(a->j);} 1406 if (a->diag) PetscFree(a->diag); 1407 if (a->ilen) PetscFree(a->ilen); 1408 if (a->imax) PetscFree(a->imax); 1409 if (a->solve_work) PetscFree(a->solve_work); 1410 if (a->inode.size) PetscFree(a->inode.size); 1411 PetscFree(a); 1412 1413 1414 ierr = MapDestroy(A->rmap);CHKERRQ(ierr); 1415 ierr = MapDestroy(A->cmap);CHKERRQ(ierr); 1416 1417 /* 1418 This is horrible, horrible code. We need to keep the 1419 the bops and ops Structures, copy everything from C 1420 including the function pointers.. 1421 */ 1422 PetscMemcpy(A->ops,C->ops,sizeof(struct _MatOps)); 1423 PetscMemcpy(A->bops,C->bops,sizeof(PetscOps)); 1424 Abops = A->bops; 1425 Aops = A->ops; 1426 PetscMemcpy(A,C,sizeof(struct _p_Mat)); 1427 A->bops = Abops; 1428 A->ops = Aops; 1429 A->qlist = 0; 1430 1431 PetscHeaderDestroy(C); 1432 } 1433 PetscFunctionReturn(0); 1434 } 1435 1436 #undef __FUNC__ 1437 #define __FUNC__ "MatDiagonalScale_SeqAIJ" 1438 int MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 1439 { 1440 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1441 Scalar *l,*r,x,*v; 1442 int ierr,i,j,m = a->m, n = a->n, M, nz = a->nz, *jj,shift = a->indexshift; 1443 1444 PetscFunctionBegin; 1445 if (ll) { 1446 /* The local size is used so that VecMPI can be passed to this routine 1447 by MatDiagonalScale_MPIAIJ */ 1448 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 1449 if (m != a->m) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Left scaling vector wrong length"); 1450 ierr = VecGetArray(ll,&l); CHKERRQ(ierr); 1451 v = a->a; 1452 for ( i=0; i<m; i++ ) { 1453 x = l[i]; 1454 M = a->i[i+1] - a->i[i]; 1455 for ( j=0; j<M; j++ ) { (*v++) *= x;} 1456 } 1457 ierr = VecRestoreArray(ll,&l); CHKERRQ(ierr); 1458 PLogFlops(nz); 1459 } 1460 if (rr) { 1461 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 1462 if (n != a->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Right scaling vector wrong length"); 1463 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 1464 v = a->a; jj = a->j; 1465 for ( i=0; i<nz; i++ ) { 1466 (*v++) *= r[*jj++ + shift]; 1467 } 1468 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 1469 PLogFlops(nz); 1470 } 1471 PetscFunctionReturn(0); 1472 } 1473 1474 #undef __FUNC__ 1475 #define __FUNC__ "MatGetSubMatrix_SeqAIJ" 1476 int MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,int csize,MatReuse scall,Mat *B) 1477 { 1478 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data,*c; 1479 int *smap, i, k, kstart, kend, ierr, oldcols = a->n,*lens; 1480 int row,mat_i,*mat_j,tcol,first,step,*mat_ilen; 1481 register int sum,lensi; 1482 int *irow, *icol, nrows, ncols, shift = a->indexshift,*ssmap; 1483 int *starts,*j_new,*i_new,*aj = a->j, *ai = a->i,ii,*ailen = a->ilen; 1484 Scalar *a_new,*mat_a; 1485 Mat C; 1486 PetscTruth stride; 1487 1488 PetscFunctionBegin; 1489 ierr = ISSorted(isrow,(PetscTruth*)&i);CHKERRQ(ierr); 1490 if (!i) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"ISrow is not sorted"); 1491 ierr = ISSorted(iscol,(PetscTruth*)&i);CHKERRQ(ierr); 1492 if (!i) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"IScol is not sorted"); 1493 1494 ierr = ISGetIndices(isrow,&irow); CHKERRQ(ierr); 1495 ierr = ISGetSize(isrow,&nrows); CHKERRQ(ierr); 1496 ierr = ISGetSize(iscol,&ncols); CHKERRQ(ierr); 1497 1498 ierr = ISStrideGetInfo(iscol,&first,&step); CHKERRQ(ierr); 1499 ierr = ISStride(iscol,&stride); CHKERRQ(ierr); 1500 if (stride && step == 1) { 1501 /* special case of contiguous rows */ 1502 lens = (int *) PetscMalloc((ncols+nrows+1)*sizeof(int)); CHKPTRQ(lens); 1503 starts = lens + ncols; 1504 /* loop over new rows determining lens and starting points */ 1505 for (i=0; i<nrows; i++) { 1506 kstart = ai[irow[i]]+shift; 1507 kend = kstart + ailen[irow[i]]; 1508 for ( k=kstart; k<kend; k++ ) { 1509 if (aj[k]+shift >= first) { 1510 starts[i] = k; 1511 break; 1512 } 1513 } 1514 sum = 0; 1515 while (k < kend) { 1516 if (aj[k++]+shift >= first+ncols) break; 1517 sum++; 1518 } 1519 lens[i] = sum; 1520 } 1521 /* create submatrix */ 1522 if (scall == MAT_REUSE_MATRIX) { 1523 int n_cols,n_rows; 1524 ierr = MatGetSize(*B,&n_rows,&n_cols); CHKERRQ(ierr); 1525 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Reused submatrix wrong size"); 1526 ierr = MatZeroEntries(*B); CHKERRQ(ierr); 1527 C = *B; 1528 } else { 1529 ierr = MatCreateSeqAIJ(A->comm,nrows,ncols,0,lens,&C);CHKERRQ(ierr); 1530 } 1531 c = (Mat_SeqAIJ*) C->data; 1532 1533 /* loop over rows inserting into submatrix */ 1534 a_new = c->a; 1535 j_new = c->j; 1536 i_new = c->i; 1537 i_new[0] = -shift; 1538 for (i=0; i<nrows; i++) { 1539 ii = starts[i]; 1540 lensi = lens[i]; 1541 for ( k=0; k<lensi; k++ ) { 1542 *j_new++ = aj[ii+k] - first; 1543 } 1544 PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(Scalar)); 1545 a_new += lensi; 1546 i_new[i+1] = i_new[i] + lensi; 1547 c->ilen[i] = lensi; 1548 } 1549 PetscFree(lens); 1550 } else { 1551 ierr = ISGetIndices(iscol,&icol); CHKERRQ(ierr); 1552 smap = (int *) PetscMalloc((1+oldcols)*sizeof(int)); CHKPTRQ(smap); 1553 ssmap = smap + shift; 1554 lens = (int *) PetscMalloc((1+nrows)*sizeof(int)); CHKPTRQ(lens); 1555 PetscMemzero(smap,oldcols*sizeof(int)); 1556 for ( i=0; i<ncols; i++ ) smap[icol[i]] = i+1; 1557 /* determine lens of each row */ 1558 for (i=0; i<nrows; i++) { 1559 kstart = ai[irow[i]]+shift; 1560 kend = kstart + a->ilen[irow[i]]; 1561 lens[i] = 0; 1562 for ( k=kstart; k<kend; k++ ) { 1563 if (ssmap[aj[k]]) { 1564 lens[i]++; 1565 } 1566 } 1567 } 1568 /* Create and fill new matrix */ 1569 if (scall == MAT_REUSE_MATRIX) { 1570 c = (Mat_SeqAIJ *)((*B)->data); 1571 if (c->m != nrows || c->n != ncols) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Cannot reuse matrix. wrong size"); 1572 if (PetscMemcmp(c->ilen,lens, c->m *sizeof(int))) { 1573 SETERRQ(PETSC_ERR_ARG_SIZ,0,"Cannot reuse matrix. wrong no of nonzeros"); 1574 } 1575 PetscMemzero(c->ilen,c->m*sizeof(int)); 1576 C = *B; 1577 } else { 1578 ierr = MatCreateSeqAIJ(A->comm,nrows,ncols,0,lens,&C);CHKERRQ(ierr); 1579 } 1580 c = (Mat_SeqAIJ *)(C->data); 1581 for (i=0; i<nrows; i++) { 1582 row = irow[i]; 1583 kstart = ai[row]+shift; 1584 kend = kstart + a->ilen[row]; 1585 mat_i = c->i[i]+shift; 1586 mat_j = c->j + mat_i; 1587 mat_a = c->a + mat_i; 1588 mat_ilen = c->ilen + i; 1589 for ( k=kstart; k<kend; k++ ) { 1590 if ((tcol=ssmap[a->j[k]])) { 1591 *mat_j++ = tcol - (!shift); 1592 *mat_a++ = a->a[k]; 1593 (*mat_ilen)++; 1594 1595 } 1596 } 1597 } 1598 /* Free work space */ 1599 ierr = ISRestoreIndices(iscol,&icol); CHKERRQ(ierr); 1600 PetscFree(smap); PetscFree(lens); 1601 } 1602 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1603 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1604 1605 ierr = ISRestoreIndices(isrow,&irow); CHKERRQ(ierr); 1606 *B = C; 1607 PetscFunctionReturn(0); 1608 } 1609 1610 /* 1611 note: This can only work for identity for row and col. It would 1612 be good to check this and otherwise generate an error. 1613 */ 1614 #undef __FUNC__ 1615 #define __FUNC__ "MatILUFactor_SeqAIJ" 1616 int MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,MatILUInfo *info) 1617 { 1618 Mat_SeqAIJ *a = (Mat_SeqAIJ *) inA->data; 1619 int ierr; 1620 Mat outA; 1621 1622 PetscFunctionBegin; 1623 if (info && info->levels != 0) SETERRQ(PETSC_ERR_SUP,0,"Only levels=0 supported"); 1624 1625 outA = inA; 1626 inA->factor = FACTOR_LU; 1627 a->row = row; 1628 a->col = col; 1629 1630 /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */ 1631 ierr = ISInvertPermutation(col,&(a->icol)); CHKERRQ(ierr); 1632 PLogObjectParent(inA,a->icol); 1633 1634 if (!a->solve_work) { /* this matrix may have been factored before */ 1635 a->solve_work = (Scalar *) PetscMalloc( (a->m+1)*sizeof(Scalar));CHKPTRQ(a->solve_work); 1636 } 1637 1638 if (!a->diag) { 1639 ierr = MatMarkDiag_SeqAIJ(inA); CHKERRQ(ierr); 1640 } 1641 ierr = MatLUFactorNumeric_SeqAIJ(inA,&outA); CHKERRQ(ierr); 1642 PetscFunctionReturn(0); 1643 } 1644 1645 #include "pinclude/blaslapack.h" 1646 #undef __FUNC__ 1647 #define __FUNC__ "MatScale_SeqAIJ" 1648 int MatScale_SeqAIJ(Scalar *alpha,Mat inA) 1649 { 1650 Mat_SeqAIJ *a = (Mat_SeqAIJ *) inA->data; 1651 int one = 1; 1652 1653 PetscFunctionBegin; 1654 BLscal_( &a->nz, alpha, a->a, &one ); 1655 PLogFlops(a->nz); 1656 PetscFunctionReturn(0); 1657 } 1658 1659 #undef __FUNC__ 1660 #define __FUNC__ "MatGetSubMatrices_SeqAIJ" 1661 int MatGetSubMatrices_SeqAIJ(Mat A,int n, IS *irow,IS *icol,MatReuse scall,Mat **B) 1662 { 1663 int ierr,i; 1664 1665 PetscFunctionBegin; 1666 if (scall == MAT_INITIAL_MATRIX) { 1667 *B = (Mat *) PetscMalloc( (n+1)*sizeof(Mat) ); CHKPTRQ(*B); 1668 } 1669 1670 for ( i=0; i<n; i++ ) { 1671 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1672 } 1673 PetscFunctionReturn(0); 1674 } 1675 1676 #undef __FUNC__ 1677 #define __FUNC__ "MatGetBlockSize_SeqAIJ" 1678 int MatGetBlockSize_SeqAIJ(Mat A, int *bs) 1679 { 1680 PetscFunctionBegin; 1681 *bs = 1; 1682 PetscFunctionReturn(0); 1683 } 1684 1685 #undef __FUNC__ 1686 #define __FUNC__ "MatIncreaseOverlap_SeqAIJ" 1687 int MatIncreaseOverlap_SeqAIJ(Mat A, int is_max, IS *is, int ov) 1688 { 1689 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1690 int shift, row, i,j,k,l,m,n, *idx,ierr, *nidx, isz, val; 1691 int start, end, *ai, *aj; 1692 BT table; 1693 1694 PetscFunctionBegin; 1695 shift = a->indexshift; 1696 m = a->m; 1697 ai = a->i; 1698 aj = a->j+shift; 1699 1700 if (ov < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"illegal overlap value used"); 1701 1702 nidx = (int *) PetscMalloc((m+1)*sizeof(int)); CHKPTRQ(nidx); 1703 ierr = BTCreate(m,table); CHKERRQ(ierr); 1704 1705 for ( i=0; i<is_max; i++ ) { 1706 /* Initialize the two local arrays */ 1707 isz = 0; 1708 BTMemzero(m,table); 1709 1710 /* Extract the indices, assume there can be duplicate entries */ 1711 ierr = ISGetIndices(is[i],&idx); CHKERRQ(ierr); 1712 ierr = ISGetSize(is[i],&n); CHKERRQ(ierr); 1713 1714 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 1715 for ( j=0; j<n ; ++j){ 1716 if(!BTLookupSet(table, idx[j])) { nidx[isz++] = idx[j];} 1717 } 1718 ierr = ISRestoreIndices(is[i],&idx); CHKERRQ(ierr); 1719 ierr = ISDestroy(is[i]); CHKERRQ(ierr); 1720 1721 k = 0; 1722 for ( j=0; j<ov; j++){ /* for each overlap */ 1723 n = isz; 1724 for ( ; k<n ; k++){ /* do only those rows in nidx[k], which are not done yet */ 1725 row = nidx[k]; 1726 start = ai[row]; 1727 end = ai[row+1]; 1728 for ( l = start; l<end ; l++){ 1729 val = aj[l] + shift; 1730 if (!BTLookupSet(table,val)) {nidx[isz++] = val;} 1731 } 1732 } 1733 } 1734 ierr = ISCreateGeneral(PETSC_COMM_SELF, isz, nidx, (is+i)); CHKERRQ(ierr); 1735 } 1736 BTDestroy(table); 1737 PetscFree(nidx); 1738 PetscFunctionReturn(0); 1739 } 1740 1741 /* -------------------------------------------------------------- */ 1742 #undef __FUNC__ 1743 #define __FUNC__ "MatPermute_SeqAIJ" 1744 int MatPermute_SeqAIJ(Mat A, IS rowp, IS colp, Mat *B) 1745 { 1746 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1747 Scalar *vwork; 1748 int i, ierr, nz, m = a->m, n = a->n, *cwork; 1749 int *row,*col,*cnew,j,*lens; 1750 IS icolp,irowp; 1751 1752 PetscFunctionBegin; 1753 ierr = ISInvertPermutation(rowp,&irowp); CHKERRQ(ierr); 1754 ierr = ISGetIndices(irowp,&row); CHKERRQ(ierr); 1755 ierr = ISInvertPermutation(colp,&icolp); CHKERRQ(ierr); 1756 ierr = ISGetIndices(icolp,&col); CHKERRQ(ierr); 1757 1758 /* determine lengths of permuted rows */ 1759 lens = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(lens); 1760 for (i=0; i<m; i++ ) { 1761 lens[row[i]] = a->i[i+1] - a->i[i]; 1762 } 1763 ierr = MatCreateSeqAIJ(A->comm,m,n,0,lens,B);CHKERRQ(ierr); 1764 PetscFree(lens); 1765 1766 cnew = (int *) PetscMalloc( n*sizeof(int) ); CHKPTRQ(cnew); 1767 for (i=0; i<m; i++) { 1768 ierr = MatGetRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr); 1769 for (j=0; j<nz; j++ ) { cnew[j] = col[cwork[j]];} 1770 ierr = MatSetValues(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES); CHKERRQ(ierr); 1771 ierr = MatRestoreRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr); 1772 } 1773 PetscFree(cnew); 1774 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1775 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 1776 ierr = ISRestoreIndices(irowp,&row); CHKERRQ(ierr); 1777 ierr = ISRestoreIndices(icolp,&col); CHKERRQ(ierr); 1778 ierr = ISDestroy(irowp); CHKERRQ(ierr); 1779 ierr = ISDestroy(icolp); CHKERRQ(ierr); 1780 PetscFunctionReturn(0); 1781 } 1782 1783 #undef __FUNC__ 1784 #define __FUNC__ "MatPrintHelp_SeqAIJ" 1785 int MatPrintHelp_SeqAIJ(Mat A) 1786 { 1787 static int called = 0; 1788 MPI_Comm comm = A->comm; 1789 1790 PetscFunctionBegin; 1791 if (called) {PetscFunctionReturn(0);} else called = 1; 1792 (*PetscHelpPrintf)(comm," Options for MATSEQAIJ and MATMPIAIJ matrix formats (the defaults):\n"); 1793 (*PetscHelpPrintf)(comm," -mat_lu_pivotthreshold <threshold>: Set pivoting threshold\n"); 1794 (*PetscHelpPrintf)(comm," -mat_aij_oneindex: internal indices begin at 1 instead of the default 0.\n"); 1795 (*PetscHelpPrintf)(comm," -mat_aij_no_inode: Do not use inodes\n"); 1796 (*PetscHelpPrintf)(comm," -mat_aij_inode_limit <limit>: Set inode limit (max limit=5)\n"); 1797 #if defined(HAVE_ESSL) 1798 (*PetscHelpPrintf)(comm," -mat_aij_essl: Use IBM sparse LU factorization and solve.\n"); 1799 #endif 1800 PetscFunctionReturn(0); 1801 } 1802 extern int MatEqual_SeqAIJ(Mat A,Mat B, PetscTruth* flg); 1803 extern int MatFDColoringCreate_SeqAIJ(Mat,ISColoring,MatFDColoring); 1804 extern int MatColoringPatch_SeqAIJ(Mat,int,int *,ISColoring *); 1805 1806 #undef __FUNC__ 1807 #define __FUNC__ "MatCopy_SeqAIJ" 1808 int MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 1809 { 1810 int ierr; 1811 1812 PetscFunctionBegin; 1813 if (str == SAME_NONZERO_PATTERN && B->type == MATSEQAIJ) { 1814 Mat_SeqAIJ *a = (Mat_SeqAIJ *) A->data; 1815 Mat_SeqAIJ *b = (Mat_SeqAIJ *) B->data; 1816 1817 if (a->i[a->m]+a->indexshift != b->i[b->m]+a->indexshift) { 1818 SETERRQ(1,1,"Number of nonzeros in two matrices are different"); 1819 } 1820 PetscMemcpy(b->a,a->a,(a->i[a->m]+a->indexshift)*sizeof(Scalar)); 1821 } else { 1822 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1823 } 1824 PetscFunctionReturn(0); 1825 } 1826 1827 /* -------------------------------------------------------------------*/ 1828 static struct _MatOps MatOps_Values = {MatSetValues_SeqAIJ, 1829 MatGetRow_SeqAIJ, 1830 MatRestoreRow_SeqAIJ, 1831 MatMult_SeqAIJ, 1832 MatMultAdd_SeqAIJ, 1833 MatMultTrans_SeqAIJ, 1834 MatMultTransAdd_SeqAIJ, 1835 MatSolve_SeqAIJ, 1836 MatSolveAdd_SeqAIJ, 1837 MatSolveTrans_SeqAIJ, 1838 MatSolveTransAdd_SeqAIJ, 1839 MatLUFactor_SeqAIJ, 1840 0, 1841 MatRelax_SeqAIJ, 1842 MatTranspose_SeqAIJ, 1843 MatGetInfo_SeqAIJ, 1844 MatEqual_SeqAIJ, 1845 MatGetDiagonal_SeqAIJ, 1846 MatDiagonalScale_SeqAIJ, 1847 MatNorm_SeqAIJ, 1848 0, 1849 MatAssemblyEnd_SeqAIJ, 1850 MatCompress_SeqAIJ, 1851 MatSetOption_SeqAIJ, 1852 MatZeroEntries_SeqAIJ, 1853 MatZeroRows_SeqAIJ, 1854 MatLUFactorSymbolic_SeqAIJ, 1855 MatLUFactorNumeric_SeqAIJ, 1856 0, 1857 0, 1858 MatGetSize_SeqAIJ, 1859 MatGetSize_SeqAIJ, 1860 MatGetOwnershipRange_SeqAIJ, 1861 MatILUFactorSymbolic_SeqAIJ, 1862 0, 1863 0, 1864 0, 1865 MatDuplicate_SeqAIJ, 1866 0, 1867 0, 1868 MatILUFactor_SeqAIJ, 1869 0, 1870 0, 1871 MatGetSubMatrices_SeqAIJ, 1872 MatIncreaseOverlap_SeqAIJ, 1873 MatGetValues_SeqAIJ, 1874 MatCopy_SeqAIJ, 1875 MatPrintHelp_SeqAIJ, 1876 MatScale_SeqAIJ, 1877 0, 1878 0, 1879 MatILUDTFactor_SeqAIJ, 1880 MatGetBlockSize_SeqAIJ, 1881 MatGetRowIJ_SeqAIJ, 1882 MatRestoreRowIJ_SeqAIJ, 1883 MatGetColumnIJ_SeqAIJ, 1884 MatRestoreColumnIJ_SeqAIJ, 1885 MatFDColoringCreate_SeqAIJ, 1886 MatColoringPatch_SeqAIJ, 1887 0, 1888 MatPermute_SeqAIJ, 1889 0, 1890 0, 1891 0, 1892 0, 1893 MatGetMaps_Petsc}; 1894 1895 extern int MatUseSuperLU_SeqAIJ(Mat); 1896 extern int MatUseEssl_SeqAIJ(Mat); 1897 extern int MatUseDXML_SeqAIJ(Mat); 1898 1899 EXTERN_C_BEGIN 1900 #undef __FUNC__ 1901 #define __FUNC__ "MatSeqAIJSetColumnIndices_SeqAIJ" 1902 1903 int MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,int *indices) 1904 { 1905 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 1906 int i,nz,n; 1907 1908 PetscFunctionBegin; 1909 if (aij->indexshift) SETERRQ(1,1,"No support with 1 based indexing"); 1910 1911 nz = aij->maxnz; 1912 n = aij->n; 1913 for (i=0; i<nz; i++) { 1914 aij->j[i] = indices[i]; 1915 } 1916 aij->nz = nz; 1917 for ( i=0; i<n; i++ ) { 1918 aij->ilen[i] = aij->imax[i]; 1919 } 1920 1921 PetscFunctionReturn(0); 1922 } 1923 EXTERN_C_END 1924 1925 #undef __FUNC__ 1926 #define __FUNC__ "MatSeqAIJSetColumnIndices" 1927 /*@ 1928 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 1929 in the matrix. 1930 1931 Input Parameters: 1932 + mat - the SeqAIJ matrix 1933 - indices - the column indices 1934 1935 Level: advanced 1936 1937 Notes: 1938 This can be called if you have precomputed the nonzero structure of the 1939 matrix and want to provide it to the matrix object to improve the performance 1940 of the MatSetValues() operation. 1941 1942 You MUST have set the correct numbers of nonzeros per row in the call to 1943 MatCreateSeqAIJ(). 1944 1945 MUST be called before any calls to MatSetValues(); 1946 1947 @*/ 1948 int MatSeqAIJSetColumnIndices(Mat mat,int *indices) 1949 { 1950 int ierr,(*f)(Mat,int *); 1951 1952 PetscFunctionBegin; 1953 PetscValidHeaderSpecific(mat,MAT_COOKIE); 1954 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqAIJSetColumnIndices_C",(void **)&f); 1955 CHKERRQ(ierr); 1956 if (f) { 1957 ierr = (*f)(mat,indices);CHKERRQ(ierr); 1958 } else { 1959 SETERRQ(1,1,"Wrong type of matrix to set column indices"); 1960 } 1961 PetscFunctionReturn(0); 1962 } 1963 1964 /* ----------------------------------------------------------------------------------------*/ 1965 1966 EXTERN_C_BEGIN 1967 #undef __FUNC__ 1968 #define __FUNC__ "MatStoreValues_SeqAIJ" 1969 int MatStoreValues_SeqAIJ(Mat mat) 1970 { 1971 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 1972 int nz = aij->i[aij->m]+aij->indexshift; 1973 1974 PetscFunctionBegin; 1975 if (aij->nonew != 1) { 1976 SETERRQ(1,1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 1977 } 1978 1979 /* allocate space for values if not already there */ 1980 if (!aij->saved_values) { 1981 aij->saved_values = (Scalar *) PetscMalloc(nz*sizeof(Scalar));CHKPTRQ(aij->saved_values); 1982 } 1983 1984 /* copy values over */ 1985 PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(Scalar)); 1986 PetscFunctionReturn(0); 1987 } 1988 EXTERN_C_END 1989 1990 #undef __FUNC__ 1991 #define __FUNC__ "MatStoreValues" 1992 /*@ 1993 MatStoreValues - Stashes a copy of the matrix values; this allows, for 1994 example, reuse of the linear part of a Jacobian, while recomputing the 1995 nonlinear portion. 1996 1997 Collect on Mat 1998 1999 Input Parameters: 2000 . mat - the matrix (currently on AIJ matrices support this option) 2001 2002 Level: advanced 2003 2004 Common Usage, with SNESSolve(): 2005 $ Create Jacobian matrix 2006 $ Set linear terms into matrix 2007 $ Apply boundary conditions to matrix, at this time matrix must have 2008 $ final nonzero structure (i.e. setting the nonlinear terms and applying 2009 $ boundary conditions again will not change the nonzero structure 2010 $ ierr = MatSetOption(mat,MAT_NO_NEW_NONZERO_LOCATIONS); 2011 $ ierr = MatStoreValues(mat); 2012 $ Call SNESSetJacobian() with matrix 2013 $ In your Jacobian routine 2014 $ ierr = MatRetrieveValues(mat); 2015 $ Set nonlinear terms in matrix 2016 2017 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 2018 $ // build linear portion of Jacobian 2019 $ ierr = MatSetOption(mat,MAT_NO_NEW_NONZERO_LOCATIONS); 2020 $ ierr = MatStoreValues(mat); 2021 $ loop over nonlinear iterations 2022 $ ierr = MatRetrieveValues(mat); 2023 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 2024 $ // call MatAssemblyBegin/End() on matrix 2025 $ Solve linear system with Jacobian 2026 $ endloop 2027 2028 Notes: 2029 Matrix must already be assemblied before calling this routine 2030 Must set the matrix option MatSetOption(mat,MAT_NO_NEW_NONZERO_LOCATIONS); before 2031 calling this routine. 2032 2033 .seealso: MatRetrieveValues() 2034 2035 @*/ 2036 int MatStoreValues(Mat mat) 2037 { 2038 int ierr,(*f)(Mat); 2039 2040 PetscFunctionBegin; 2041 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2042 if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix"); 2043 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 2044 2045 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatStoreValues_C",(void **)&f);CHKERRQ(ierr); 2046 if (f) { 2047 ierr = (*f)(mat);CHKERRQ(ierr); 2048 } else { 2049 SETERRQ(1,1,"Wrong type of matrix to store values"); 2050 } 2051 PetscFunctionReturn(0); 2052 } 2053 2054 EXTERN_C_BEGIN 2055 #undef __FUNC__ 2056 #define __FUNC__ "MatRetrieveValues_SeqAIJ" 2057 int MatRetrieveValues_SeqAIJ(Mat mat) 2058 { 2059 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2060 int nz = aij->i[aij->m]+aij->indexshift; 2061 2062 PetscFunctionBegin; 2063 if (aij->nonew != 1) { 2064 SETERRQ(1,1,"Must call MatSetOption(A,MAT_NO_NEW_NONZERO_LOCATIONS);first"); 2065 } 2066 if (!aij->saved_values) { 2067 SETERRQ(1,1,"Must call MatStoreValues(A);first"); 2068 } 2069 2070 /* copy values over */ 2071 PetscMemcpy(aij->a, aij->saved_values,nz*sizeof(Scalar)); 2072 PetscFunctionReturn(0); 2073 } 2074 EXTERN_C_END 2075 2076 #undef __FUNC__ 2077 #define __FUNC__ "MatRetrieveValues" 2078 /*@ 2079 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 2080 example, reuse of the linear part of a Jacobian, while recomputing the 2081 nonlinear portion. 2082 2083 Collect on Mat 2084 2085 Input Parameters: 2086 . mat - the matrix (currently on AIJ matrices support this option) 2087 2088 Level: advanced 2089 2090 .seealso: MatStoreValues() 2091 2092 @*/ 2093 int MatRetrieveValues(Mat mat) 2094 { 2095 int ierr,(*f)(Mat); 2096 2097 PetscFunctionBegin; 2098 PetscValidHeaderSpecific(mat,MAT_COOKIE); 2099 if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix"); 2100 if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 2101 2102 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatRetrieveValues_C",(void **)&f);CHKERRQ(ierr); 2103 if (f) { 2104 ierr = (*f)(mat);CHKERRQ(ierr); 2105 } else { 2106 SETERRQ(1,1,"Wrong type of matrix to retrieve values"); 2107 } 2108 PetscFunctionReturn(0); 2109 } 2110 2111 /* --------------------------------------------------------------------------------*/ 2112 2113 #undef __FUNC__ 2114 #define __FUNC__ "MatCreateSeqAIJ" 2115 /*@C 2116 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 2117 (the default parallel PETSc format). For good matrix assembly performance 2118 the user should preallocate the matrix storage by setting the parameter nz 2119 (or the array nzz). By setting these parameters accurately, performance 2120 during matrix assembly can be increased by more than a factor of 50. 2121 2122 Collective on MPI_Comm 2123 2124 Input Parameters: 2125 + comm - MPI communicator, set to PETSC_COMM_SELF 2126 . m - number of rows 2127 . n - number of columns 2128 . nz - number of nonzeros per row (same for all rows) 2129 - nzz - array containing the number of nonzeros in the various rows 2130 (possibly different for each row) or PETSC_NULL 2131 2132 Output Parameter: 2133 . A - the matrix 2134 2135 Notes: 2136 The AIJ format (also called the Yale sparse matrix format or 2137 compressed row storage), is fully compatible with standard Fortran 77 2138 storage. That is, the stored row and column indices can begin at 2139 either one (as in Fortran) or zero. See the users' manual for details. 2140 2141 Specify the preallocated storage with either nz or nnz (not both). 2142 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2143 allocation. For large problems you MUST preallocate memory or you 2144 will get TERRIBLE performance, see the users' manual chapter on matrices. 2145 2146 By default, this format uses inodes (identical nodes) when possible, to 2147 improve numerical efficiency of matrix-vector products and solves. We 2148 search for consecutive rows with the same nonzero structure, thereby 2149 reusing matrix information to achieve increased efficiency. 2150 2151 Options Database Keys: 2152 + -mat_aij_no_inode - Do not use inodes 2153 . -mat_aij_inode_limit <limit> - Sets inode limit (max limit=5) 2154 - -mat_aij_oneindex - Internally use indexing starting at 1 2155 rather than 0. Note that when calling MatSetValues(), 2156 the user still MUST index entries starting at 0! 2157 2158 Level: intermediate 2159 2160 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices() 2161 @*/ 2162 int MatCreateSeqAIJ(MPI_Comm comm,int m,int n,int nz,int *nnz, Mat *A) 2163 { 2164 Mat B; 2165 Mat_SeqAIJ *b; 2166 int i, len, ierr, flg,size; 2167 2168 PetscFunctionBegin; 2169 MPI_Comm_size(comm,&size); 2170 if (size > 1) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Comm must be of size 1"); 2171 2172 *A = 0; 2173 PetscHeaderCreate(B,_p_Mat,struct _MatOps,MAT_COOKIE,MATSEQAIJ,"Mat",comm,MatDestroy,MatView); 2174 PLogObjectCreate(B); 2175 B->data = (void *) (b = PetscNew(Mat_SeqAIJ)); CHKPTRQ(b); 2176 PetscMemzero(b,sizeof(Mat_SeqAIJ)); 2177 PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps)); 2178 B->ops->destroy = MatDestroy_SeqAIJ; 2179 B->ops->view = MatView_SeqAIJ; 2180 B->factor = 0; 2181 B->lupivotthreshold = 1.0; 2182 B->mapping = 0; 2183 ierr = OptionsGetDouble(PETSC_NULL,"-mat_lu_pivotthreshold",&B->lupivotthreshold,&flg);CHKERRQ(ierr); 2184 b->ilu_preserve_row_sums = PETSC_FALSE; 2185 ierr = OptionsHasName(PETSC_NULL,"-pc_ilu_preserve_row_sums",(int*)&b->ilu_preserve_row_sums);CHKERRQ(ierr); 2186 b->row = 0; 2187 b->col = 0; 2188 b->icol = 0; 2189 b->indexshift = 0; 2190 b->reallocs = 0; 2191 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_oneindex", &flg); CHKERRQ(ierr); 2192 if (flg) b->indexshift = -1; 2193 2194 b->m = m; B->m = m; B->M = m; 2195 b->n = n; B->n = n; B->N = n; 2196 2197 ierr = MapCreateMPI(comm,m,m,&B->rmap);CHKERRQ(ierr); 2198 ierr = MapCreateMPI(comm,n,n,&B->cmap);CHKERRQ(ierr); 2199 2200 b->imax = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(b->imax); 2201 if (nnz == PETSC_NULL) { 2202 if (nz == PETSC_DEFAULT) nz = 10; 2203 else if (nz <= 0) nz = 1; 2204 for ( i=0; i<m; i++ ) b->imax[i] = nz; 2205 nz = nz*m; 2206 } else { 2207 nz = 0; 2208 for ( i=0; i<m; i++ ) {b->imax[i] = nnz[i]; nz += nnz[i];} 2209 } 2210 2211 /* allocate the matrix space */ 2212 len = nz*(sizeof(int) + sizeof(Scalar)) + (b->m+1)*sizeof(int); 2213 b->a = (Scalar *) PetscMalloc( len ); CHKPTRQ(b->a); 2214 b->j = (int *) (b->a + nz); 2215 PetscMemzero(b->j,nz*sizeof(int)); 2216 b->i = b->j + nz; 2217 b->singlemalloc = 1; 2218 2219 b->i[0] = -b->indexshift; 2220 for (i=1; i<m+1; i++) { 2221 b->i[i] = b->i[i-1] + b->imax[i-1]; 2222 } 2223 2224 /* b->ilen will count nonzeros in each row so far. */ 2225 b->ilen = (int *) PetscMalloc((m+1)*sizeof(int)); 2226 PLogObjectMemory(B,len+2*(m+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqAIJ)); 2227 for ( i=0; i<b->m; i++ ) { b->ilen[i] = 0;} 2228 2229 b->nz = 0; 2230 b->maxnz = nz; 2231 b->sorted = 0; 2232 b->roworiented = 1; 2233 b->nonew = 0; 2234 b->diag = 0; 2235 b->solve_work = 0; 2236 b->spptr = 0; 2237 b->inode.node_count = 0; 2238 b->inode.size = 0; 2239 b->inode.limit = 5; 2240 b->inode.max_limit = 5; 2241 b->saved_values = 0; 2242 B->info.nz_unneeded = (double)b->maxnz; 2243 b->idiag = 0; 2244 b->ssor = 0; 2245 2246 *A = B; 2247 2248 /* SuperLU is not currently supported through PETSc */ 2249 #if defined(HAVE_SUPERLU) 2250 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_superlu", &flg); CHKERRQ(ierr); 2251 if (flg) { ierr = MatUseSuperLU_SeqAIJ(B); CHKERRQ(ierr); } 2252 #endif 2253 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_essl", &flg); CHKERRQ(ierr); 2254 if (flg) { ierr = MatUseEssl_SeqAIJ(B); CHKERRQ(ierr); } 2255 ierr = OptionsHasName(PETSC_NULL,"-mat_aij_dxml", &flg); CHKERRQ(ierr); 2256 if (flg) { 2257 if (!b->indexshift) SETERRQ( PETSC_ERR_LIB,0,"need -mat_aij_oneindex with -mat_aij_dxml"); 2258 ierr = MatUseDXML_SeqAIJ(B); CHKERRQ(ierr); 2259 } 2260 ierr = OptionsHasName(PETSC_NULL,"-help", &flg); CHKERRQ(ierr); 2261 if (flg) {ierr = MatPrintHelp(B); CHKERRQ(ierr); } 2262 2263 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C", 2264 "MatSeqAIJSetColumnIndices_SeqAIJ", 2265 (void*)MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 2266 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C", 2267 "MatStoreValues_SeqAIJ", 2268 (void*)MatStoreValues_SeqAIJ);CHKERRQ(ierr); 2269 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C", 2270 "MatRetrieveValues_SeqAIJ", 2271 (void*)MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 2272 PetscFunctionReturn(0); 2273 } 2274 2275 #undef __FUNC__ 2276 #define __FUNC__ "MatDuplicate_SeqAIJ" 2277 int MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 2278 { 2279 Mat C; 2280 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ *) A->data; 2281 int i,len, m = a->m,shift = a->indexshift,ierr; 2282 2283 PetscFunctionBegin; 2284 *B = 0; 2285 PetscHeaderCreate(C,_p_Mat,struct _MatOps,MAT_COOKIE,MATSEQAIJ,"Mat",A->comm,MatDestroy,MatView); 2286 PLogObjectCreate(C); 2287 C->data = (void *) (c = PetscNew(Mat_SeqAIJ)); CHKPTRQ(c); 2288 PetscMemcpy(C->ops,A->ops,sizeof(struct _MatOps)); 2289 C->ops->destroy = MatDestroy_SeqAIJ; 2290 C->ops->view = MatView_SeqAIJ; 2291 C->factor = A->factor; 2292 c->row = 0; 2293 c->col = 0; 2294 c->icol = 0; 2295 c->indexshift = shift; 2296 C->assembled = PETSC_TRUE; 2297 2298 c->m = C->m = a->m; 2299 c->n = C->n = a->n; 2300 C->M = a->m; 2301 C->N = a->n; 2302 2303 c->imax = (int *) PetscMalloc((m+1)*sizeof(int)); CHKPTRQ(c->imax); 2304 c->ilen = (int *) PetscMalloc((m+1)*sizeof(int)); CHKPTRQ(c->ilen); 2305 for ( i=0; i<m; i++ ) { 2306 c->imax[i] = a->imax[i]; 2307 c->ilen[i] = a->ilen[i]; 2308 } 2309 2310 /* allocate the matrix space */ 2311 c->singlemalloc = 1; 2312 len = (m+1)*sizeof(int)+(a->i[m])*(sizeof(Scalar)+sizeof(int)); 2313 c->a = (Scalar *) PetscMalloc( len ); CHKPTRQ(c->a); 2314 c->j = (int *) (c->a + a->i[m] + shift); 2315 c->i = c->j + a->i[m] + shift; 2316 PetscMemcpy(c->i,a->i,(m+1)*sizeof(int)); 2317 if (m > 0) { 2318 PetscMemcpy(c->j,a->j,(a->i[m]+shift)*sizeof(int)); 2319 if (cpvalues == MAT_COPY_VALUES) { 2320 PetscMemcpy(c->a,a->a,(a->i[m]+shift)*sizeof(Scalar)); 2321 } else { 2322 PetscMemzero(c->a,(a->i[m]+shift)*sizeof(Scalar)); 2323 } 2324 } 2325 2326 PLogObjectMemory(C,len+2*(m+1)*sizeof(int)+sizeof(struct _p_Mat)+sizeof(Mat_SeqAIJ)); 2327 c->sorted = a->sorted; 2328 c->roworiented = a->roworiented; 2329 c->nonew = a->nonew; 2330 c->ilu_preserve_row_sums = a->ilu_preserve_row_sums; 2331 c->saved_values = 0; 2332 c->idiag = 0; 2333 c->ssor = 0; 2334 2335 if (a->diag) { 2336 c->diag = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(c->diag); 2337 PLogObjectMemory(C,(m+1)*sizeof(int)); 2338 for ( i=0; i<m; i++ ) { 2339 c->diag[i] = a->diag[i]; 2340 } 2341 } else c->diag = 0; 2342 c->inode.limit = a->inode.limit; 2343 c->inode.max_limit = a->inode.max_limit; 2344 if (a->inode.size){ 2345 c->inode.size = (int *) PetscMalloc( (m+1)*sizeof(int) ); CHKPTRQ(c->inode.size); 2346 c->inode.node_count = a->inode.node_count; 2347 PetscMemcpy( c->inode.size, a->inode.size, (m+1)*sizeof(int)); 2348 } else { 2349 c->inode.size = 0; 2350 c->inode.node_count = 0; 2351 } 2352 c->nz = a->nz; 2353 c->maxnz = a->maxnz; 2354 c->solve_work = 0; 2355 c->spptr = 0; /* Dangerous -I'm throwing away a->spptr */ 2356 2357 *B = C; 2358 ierr = FListDuplicate(A->qlist,&C->qlist);CHKERRQ(ierr); 2359 PetscFunctionReturn(0); 2360 } 2361 2362 #undef __FUNC__ 2363 #define __FUNC__ "MatLoad_SeqAIJ" 2364 int MatLoad_SeqAIJ(Viewer viewer,MatType type,Mat *A) 2365 { 2366 Mat_SeqAIJ *a; 2367 Mat B; 2368 int i, nz, ierr, fd, header[4],size,*rowlengths = 0,M,N,shift; 2369 MPI_Comm comm; 2370 2371 PetscFunctionBegin; 2372 ierr = PetscObjectGetComm((PetscObject) viewer,&comm);CHKERRQ(ierr); 2373 MPI_Comm_size(comm,&size); 2374 if (size > 1) SETERRQ(PETSC_ERR_ARG_SIZ,0,"view must have one processor"); 2375 ierr = ViewerBinaryGetDescriptor(viewer,&fd); CHKERRQ(ierr); 2376 ierr = PetscBinaryRead(fd,header,4,PETSC_INT); CHKERRQ(ierr); 2377 if (header[0] != MAT_COOKIE) SETERRQ(PETSC_ERR_FILE_UNEXPECTED,0,"not matrix object in file"); 2378 M = header[1]; N = header[2]; nz = header[3]; 2379 2380 if (nz < 0) { 2381 SETERRQ(PETSC_ERR_FILE_UNEXPECTED,1,"Matrix stored in special format on disk, cannot load as SeqAIJ"); 2382 } 2383 2384 /* read in row lengths */ 2385 rowlengths = (int*) PetscMalloc( M*sizeof(int) ); CHKPTRQ(rowlengths); 2386 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT); CHKERRQ(ierr); 2387 2388 /* create our matrix */ 2389 ierr = MatCreateSeqAIJ(comm,M,N,0,rowlengths,A); CHKERRQ(ierr); 2390 B = *A; 2391 a = (Mat_SeqAIJ *) B->data; 2392 shift = a->indexshift; 2393 2394 /* read in column indices and adjust for Fortran indexing*/ 2395 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT); CHKERRQ(ierr); 2396 if (shift) { 2397 for ( i=0; i<nz; i++ ) { 2398 a->j[i] += 1; 2399 } 2400 } 2401 2402 /* read in nonzero values */ 2403 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR); CHKERRQ(ierr); 2404 2405 /* set matrix "i" values */ 2406 a->i[0] = -shift; 2407 for ( i=1; i<= M; i++ ) { 2408 a->i[i] = a->i[i-1] + rowlengths[i-1]; 2409 a->ilen[i-1] = rowlengths[i-1]; 2410 } 2411 PetscFree(rowlengths); 2412 2413 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2414 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr); 2415 PetscFunctionReturn(0); 2416 } 2417 2418 #undef __FUNC__ 2419 #define __FUNC__ "MatEqual_SeqAIJ" 2420 int MatEqual_SeqAIJ(Mat A,Mat B, PetscTruth* flg) 2421 { 2422 Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data, *b = (Mat_SeqAIJ *)B->data; 2423 2424 PetscFunctionBegin; 2425 if (B->type !=MATSEQAIJ)SETERRQ(PETSC_ERR_ARG_INCOMP,0,"Matrices must be same type"); 2426 2427 /* If the matrix dimensions are not equal, or no of nonzeros or shift */ 2428 if ((a->m != b->m ) || (a->n !=b->n) ||( a->nz != b->nz)|| 2429 (a->indexshift != b->indexshift)) { 2430 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2431 } 2432 2433 /* if the a->i are the same */ 2434 if (PetscMemcmp(a->i,b->i,(a->m+1)*sizeof(int))) { 2435 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2436 } 2437 2438 /* if a->j are the same */ 2439 if (PetscMemcmp(a->j, b->j, (a->nz)*sizeof(int))) { 2440 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2441 } 2442 2443 /* if a->a are the same */ 2444 if (PetscMemcmp(a->a, b->a, (a->nz)*sizeof(Scalar))) { 2445 *flg = PETSC_FALSE; PetscFunctionReturn(0); 2446 } 2447 *flg = PETSC_TRUE; 2448 PetscFunctionReturn(0); 2449 2450 } 2451