1 2 /* 3 Defines the basic matrix operations for the AIJ (compressed row) 4 matrix storage format. 5 */ 6 7 8 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petscbt.h> 11 #include <petsc/private/kernels/blocktranspose.h> 12 13 PetscErrorCode MatSeqAIJSetTypeFromOptions(Mat A) 14 { 15 PetscErrorCode ierr; 16 PetscBool flg; 17 char type[256]; 18 19 PetscFunctionBegin; 20 ierr = PetscObjectOptionsBegin((PetscObject)A); 21 ierr = PetscOptionsFList("-mat_seqaij_type","Matrix SeqAIJ type","MatSeqAIJSetType",MatSeqAIJList,"seqaij",type,256,&flg);CHKERRQ(ierr); 22 if (flg) { 23 ierr = MatSeqAIJSetType(A,type);CHKERRQ(ierr); 24 } 25 ierr = PetscOptionsEnd();CHKERRQ(ierr); 26 PetscFunctionReturn(0); 27 } 28 29 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 30 { 31 PetscErrorCode ierr; 32 PetscInt i,m,n; 33 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 34 35 PetscFunctionBegin; 36 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 37 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 38 if (type == NORM_2) { 39 for (i=0; i<aij->i[m]; i++) { 40 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 41 } 42 } else if (type == NORM_1) { 43 for (i=0; i<aij->i[m]; i++) { 44 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 45 } 46 } else if (type == NORM_INFINITY) { 47 for (i=0; i<aij->i[m]; i++) { 48 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 49 } 50 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 51 52 if (type == NORM_2) { 53 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 54 } 55 PetscFunctionReturn(0); 56 } 57 58 PetscErrorCode MatFindOffBlockDiagonalEntries_SeqAIJ(Mat A,IS *is) 59 { 60 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 61 PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; 62 const PetscInt *jj = a->j,*ii = a->i; 63 PetscInt *rows; 64 PetscErrorCode ierr; 65 66 PetscFunctionBegin; 67 for (i=0; i<m; i++) { 68 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 69 cnt++; 70 } 71 } 72 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 73 cnt = 0; 74 for (i=0; i<m; i++) { 75 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 76 rows[cnt] = i; 77 cnt++; 78 } 79 } 80 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 81 PetscFunctionReturn(0); 82 } 83 84 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 85 { 86 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 87 const MatScalar *aa = a->a; 88 PetscInt i,m=A->rmap->n,cnt = 0; 89 const PetscInt *ii = a->i,*jj = a->j,*diag; 90 PetscInt *rows; 91 PetscErrorCode ierr; 92 93 PetscFunctionBegin; 94 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 95 diag = a->diag; 96 for (i=0; i<m; i++) { 97 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 98 cnt++; 99 } 100 } 101 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 102 cnt = 0; 103 for (i=0; i<m; i++) { 104 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 105 rows[cnt++] = i; 106 } 107 } 108 *nrows = cnt; 109 *zrows = rows; 110 PetscFunctionReturn(0); 111 } 112 113 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 114 { 115 PetscInt nrows,*rows; 116 PetscErrorCode ierr; 117 118 PetscFunctionBegin; 119 *zrows = NULL; 120 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 121 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 122 PetscFunctionReturn(0); 123 } 124 125 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 126 { 127 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 128 const MatScalar *aa; 129 PetscInt m=A->rmap->n,cnt = 0; 130 const PetscInt *ii; 131 PetscInt n,i,j,*rows; 132 PetscErrorCode ierr; 133 134 PetscFunctionBegin; 135 *keptrows = 0; 136 ii = a->i; 137 for (i=0; i<m; i++) { 138 n = ii[i+1] - ii[i]; 139 if (!n) { 140 cnt++; 141 goto ok1; 142 } 143 aa = a->a + ii[i]; 144 for (j=0; j<n; j++) { 145 if (aa[j] != 0.0) goto ok1; 146 } 147 cnt++; 148 ok1:; 149 } 150 if (!cnt) PetscFunctionReturn(0); 151 ierr = PetscMalloc1(A->rmap->n-cnt,&rows);CHKERRQ(ierr); 152 cnt = 0; 153 for (i=0; i<m; i++) { 154 n = ii[i+1] - ii[i]; 155 if (!n) continue; 156 aa = a->a + ii[i]; 157 for (j=0; j<n; j++) { 158 if (aa[j] != 0.0) { 159 rows[cnt++] = i; 160 break; 161 } 162 } 163 } 164 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 165 PetscFunctionReturn(0); 166 } 167 168 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 169 { 170 PetscErrorCode ierr; 171 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 172 PetscInt i,m = Y->rmap->n; 173 const PetscInt *diag; 174 MatScalar *aa = aij->a; 175 const PetscScalar *v; 176 PetscBool missing; 177 178 PetscFunctionBegin; 179 if (Y->assembled) { 180 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 181 if (!missing) { 182 diag = aij->diag; 183 ierr = VecGetArrayRead(D,&v);CHKERRQ(ierr); 184 if (is == INSERT_VALUES) { 185 for (i=0; i<m; i++) { 186 aa[diag[i]] = v[i]; 187 } 188 } else { 189 for (i=0; i<m; i++) { 190 aa[diag[i]] += v[i]; 191 } 192 } 193 ierr = VecRestoreArrayRead(D,&v);CHKERRQ(ierr); 194 PetscFunctionReturn(0); 195 } 196 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 197 } 198 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 199 PetscFunctionReturn(0); 200 } 201 202 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 203 { 204 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 205 PetscErrorCode ierr; 206 PetscInt i,ishift; 207 208 PetscFunctionBegin; 209 *m = A->rmap->n; 210 if (!ia) PetscFunctionReturn(0); 211 ishift = 0; 212 if (symmetric && !A->structurally_symmetric) { 213 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 214 } else if (oshift == 1) { 215 PetscInt *tia; 216 PetscInt nz = a->i[A->rmap->n]; 217 /* malloc space and add 1 to i and j indices */ 218 ierr = PetscMalloc1(A->rmap->n+1,&tia);CHKERRQ(ierr); 219 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 220 *ia = tia; 221 if (ja) { 222 PetscInt *tja; 223 ierr = PetscMalloc1(nz+1,&tja);CHKERRQ(ierr); 224 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 225 *ja = tja; 226 } 227 } else { 228 *ia = a->i; 229 if (ja) *ja = a->j; 230 } 231 PetscFunctionReturn(0); 232 } 233 234 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 235 { 236 PetscErrorCode ierr; 237 238 PetscFunctionBegin; 239 if (!ia) PetscFunctionReturn(0); 240 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 241 ierr = PetscFree(*ia);CHKERRQ(ierr); 242 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 243 } 244 PetscFunctionReturn(0); 245 } 246 247 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 248 { 249 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 250 PetscErrorCode ierr; 251 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 252 PetscInt nz = a->i[m],row,*jj,mr,col; 253 254 PetscFunctionBegin; 255 *nn = n; 256 if (!ia) PetscFunctionReturn(0); 257 if (symmetric) { 258 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 259 } else { 260 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 261 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 262 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 263 jj = a->j; 264 for (i=0; i<nz; i++) { 265 collengths[jj[i]]++; 266 } 267 cia[0] = oshift; 268 for (i=0; i<n; i++) { 269 cia[i+1] = cia[i] + collengths[i]; 270 } 271 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 272 jj = a->j; 273 for (row=0; row<m; row++) { 274 mr = a->i[row+1] - a->i[row]; 275 for (i=0; i<mr; i++) { 276 col = *jj++; 277 278 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 279 } 280 } 281 ierr = PetscFree(collengths);CHKERRQ(ierr); 282 *ia = cia; *ja = cja; 283 } 284 PetscFunctionReturn(0); 285 } 286 287 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 288 { 289 PetscErrorCode ierr; 290 291 PetscFunctionBegin; 292 if (!ia) PetscFunctionReturn(0); 293 294 ierr = PetscFree(*ia);CHKERRQ(ierr); 295 ierr = PetscFree(*ja);CHKERRQ(ierr); 296 PetscFunctionReturn(0); 297 } 298 299 /* 300 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 301 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 302 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() 303 */ 304 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 305 { 306 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 307 PetscErrorCode ierr; 308 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 309 PetscInt nz = a->i[m],row,*jj,mr,col; 310 PetscInt *cspidx; 311 312 PetscFunctionBegin; 313 *nn = n; 314 if (!ia) PetscFunctionReturn(0); 315 316 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 317 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 318 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 319 ierr = PetscMalloc1(nz+1,&cspidx);CHKERRQ(ierr); 320 jj = a->j; 321 for (i=0; i<nz; i++) { 322 collengths[jj[i]]++; 323 } 324 cia[0] = oshift; 325 for (i=0; i<n; i++) { 326 cia[i+1] = cia[i] + collengths[i]; 327 } 328 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 329 jj = a->j; 330 for (row=0; row<m; row++) { 331 mr = a->i[row+1] - a->i[row]; 332 for (i=0; i<mr; i++) { 333 col = *jj++; 334 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 335 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 336 } 337 } 338 ierr = PetscFree(collengths);CHKERRQ(ierr); 339 *ia = cia; *ja = cja; 340 *spidx = cspidx; 341 PetscFunctionReturn(0); 342 } 343 344 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 345 { 346 PetscErrorCode ierr; 347 348 PetscFunctionBegin; 349 ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 350 ierr = PetscFree(*spidx);CHKERRQ(ierr); 351 PetscFunctionReturn(0); 352 } 353 354 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 355 { 356 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 357 PetscInt *ai = a->i; 358 PetscErrorCode ierr; 359 360 PetscFunctionBegin; 361 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 362 PetscFunctionReturn(0); 363 } 364 365 /* 366 MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions 367 368 - a single row of values is set with each call 369 - no row or column indices are negative or (in error) larger than the number of rows or columns 370 - the values are always added to the matrix, not set 371 - no new locations are introduced in the nonzero structure of the matrix 372 373 This does NOT assume the global column indices are sorted 374 375 */ 376 377 #include <petsc/private/isimpl.h> 378 PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 379 { 380 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 381 PetscInt low,high,t,row,nrow,i,col,l; 382 const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; 383 PetscInt lastcol = -1; 384 MatScalar *ap,value,*aa = a->a; 385 const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; 386 387 row = ridx[im[0]]; 388 rp = aj + ai[row]; 389 ap = aa + ai[row]; 390 nrow = ailen[row]; 391 low = 0; 392 high = nrow; 393 for (l=0; l<n; l++) { /* loop over added columns */ 394 col = cidx[in[l]]; 395 value = v[l]; 396 397 if (col <= lastcol) low = 0; 398 else high = nrow; 399 lastcol = col; 400 while (high-low > 5) { 401 t = (low+high)/2; 402 if (rp[t] > col) high = t; 403 else low = t; 404 } 405 for (i=low; i<high; i++) { 406 if (rp[i] == col) { 407 ap[i] += value; 408 low = i + 1; 409 break; 410 } 411 } 412 } 413 return 0; 414 } 415 416 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 417 { 418 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 419 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 420 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 421 PetscErrorCode ierr; 422 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 423 MatScalar *ap=NULL,value=0.0,*aa = a->a; 424 PetscBool ignorezeroentries = a->ignorezeroentries; 425 PetscBool roworiented = a->roworiented; 426 427 PetscFunctionBegin; 428 for (k=0; k<m; k++) { /* loop over added rows */ 429 row = im[k]; 430 if (row < 0) continue; 431 #if defined(PETSC_USE_DEBUG) 432 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 433 #endif 434 rp = aj + ai[row]; 435 if (!A->structure_only) ap = aa + ai[row]; 436 rmax = imax[row]; nrow = ailen[row]; 437 low = 0; 438 high = nrow; 439 for (l=0; l<n; l++) { /* loop over added columns */ 440 if (in[l] < 0) continue; 441 #if defined(PETSC_USE_DEBUG) 442 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 443 #endif 444 col = in[l]; 445 if (!A->structure_only) { 446 if (roworiented) { 447 value = v[l + k*n]; 448 } else { 449 value = v[k + l*m]; 450 } 451 } else { /* A->structure_only */ 452 value = 1; /* avoid 'continue' below? */ 453 } 454 if ((value == 0.0 && ignorezeroentries) && (is == ADD_VALUES) && row != col) continue; 455 456 if (col <= lastcol) low = 0; 457 else high = nrow; 458 lastcol = col; 459 while (high-low > 5) { 460 t = (low+high)/2; 461 if (rp[t] > col) high = t; 462 else low = t; 463 } 464 for (i=low; i<high; i++) { 465 if (rp[i] > col) break; 466 if (rp[i] == col) { 467 if (!A->structure_only) { 468 if (is == ADD_VALUES) ap[i] += value; 469 else ap[i] = value; 470 } 471 low = i + 1; 472 goto noinsert; 473 } 474 } 475 if (value == 0.0 && ignorezeroentries && row != col) goto noinsert; 476 if (nonew == 1) goto noinsert; 477 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 478 if (A->structure_only) { 479 MatSeqXAIJReallocateAIJ_structure_only(A,A->rmap->n,1,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar); 480 } else { 481 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 482 } 483 N = nrow++ - 1; a->nz++; high++; 484 /* shift up all the later entries in this row */ 485 for (ii=N; ii>=i; ii--) { 486 rp[ii+1] = rp[ii]; 487 if (!A->structure_only) ap[ii+1] = ap[ii]; 488 } 489 rp[i] = col; 490 if (!A->structure_only) ap[i] = value; 491 low = i + 1; 492 A->nonzerostate++; 493 noinsert:; 494 } 495 ailen[row] = nrow; 496 } 497 PetscFunctionReturn(0); 498 } 499 500 501 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 502 { 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 504 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 505 PetscInt *ai = a->i,*ailen = a->ilen; 506 MatScalar *ap,*aa = a->a; 507 508 PetscFunctionBegin; 509 for (k=0; k<m; k++) { /* loop over rows */ 510 row = im[k]; 511 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 512 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 513 rp = aj + ai[row]; ap = aa + ai[row]; 514 nrow = ailen[row]; 515 for (l=0; l<n; l++) { /* loop over columns */ 516 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 517 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 518 col = in[l]; 519 high = nrow; low = 0; /* assume unsorted */ 520 while (high-low > 5) { 521 t = (low+high)/2; 522 if (rp[t] > col) high = t; 523 else low = t; 524 } 525 for (i=low; i<high; i++) { 526 if (rp[i] > col) break; 527 if (rp[i] == col) { 528 *v++ = ap[i]; 529 goto finished; 530 } 531 } 532 *v++ = 0.0; 533 finished:; 534 } 535 } 536 PetscFunctionReturn(0); 537 } 538 539 540 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 541 { 542 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 543 PetscErrorCode ierr; 544 PetscInt i,*col_lens; 545 int fd; 546 FILE *file; 547 548 PetscFunctionBegin; 549 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 550 ierr = PetscMalloc1(4+A->rmap->n,&col_lens);CHKERRQ(ierr); 551 552 col_lens[0] = MAT_FILE_CLASSID; 553 col_lens[1] = A->rmap->n; 554 col_lens[2] = A->cmap->n; 555 col_lens[3] = a->nz; 556 557 /* store lengths of each row and write (including header) to file */ 558 for (i=0; i<A->rmap->n; i++) { 559 col_lens[4+i] = a->i[i+1] - a->i[i]; 560 } 561 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 562 ierr = PetscFree(col_lens);CHKERRQ(ierr); 563 564 /* store column indices (zero start index) */ 565 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 566 567 /* store nonzero values */ 568 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 569 570 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 571 if (file) { 572 fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); 573 } 574 PetscFunctionReturn(0); 575 } 576 577 static PetscErrorCode MatView_SeqAIJ_ASCII_structonly(Mat A,PetscViewer viewer) 578 { 579 PetscErrorCode ierr; 580 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 581 PetscInt i,k,m=A->rmap->N; 582 583 PetscFunctionBegin; 584 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 585 for (i=0; i<m; i++) { 586 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 587 for (k=a->i[i]; k<a->i[i+1]; k++) { 588 ierr = PetscViewerASCIIPrintf(viewer," (%D) ",a->j[k]);CHKERRQ(ierr); 589 } 590 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 591 } 592 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 593 PetscFunctionReturn(0); 594 } 595 596 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 597 598 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 599 { 600 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 601 PetscErrorCode ierr; 602 PetscInt i,j,m = A->rmap->n; 603 const char *name; 604 PetscViewerFormat format; 605 606 PetscFunctionBegin; 607 if (A->structure_only) { 608 ierr = MatView_SeqAIJ_ASCII_structonly(A,viewer);CHKERRQ(ierr); 609 PetscFunctionReturn(0); 610 } 611 612 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 613 if (format == PETSC_VIEWER_ASCII_MATLAB) { 614 PetscInt nofinalvalue = 0; 615 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 616 /* Need a dummy value to ensure the dimension of the matrix. */ 617 nofinalvalue = 1; 618 } 619 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 620 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 621 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 622 #if defined(PETSC_USE_COMPLEX) 623 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 624 #else 625 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 626 #endif 627 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 628 629 for (i=0; i<m; i++) { 630 for (j=a->i[i]; j<a->i[i+1]; j++) { 631 #if defined(PETSC_USE_COMPLEX) 632 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",i+1,a->j[j]+1,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 633 #else 634 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 635 #endif 636 } 637 } 638 if (nofinalvalue) { 639 #if defined(PETSC_USE_COMPLEX) 640 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 641 #else 642 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 643 #endif 644 } 645 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 646 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 647 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 648 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 649 PetscFunctionReturn(0); 650 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 651 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 652 for (i=0; i<m; i++) { 653 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 654 for (j=a->i[i]; j<a->i[i+1]; j++) { 655 #if defined(PETSC_USE_COMPLEX) 656 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 657 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 658 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 659 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 660 } else if (PetscRealPart(a->a[j]) != 0.0) { 661 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 662 } 663 #else 664 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 665 #endif 666 } 667 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 668 } 669 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 670 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 671 PetscInt nzd=0,fshift=1,*sptr; 672 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 673 ierr = PetscMalloc1(m+1,&sptr);CHKERRQ(ierr); 674 for (i=0; i<m; i++) { 675 sptr[i] = nzd+1; 676 for (j=a->i[i]; j<a->i[i+1]; j++) { 677 if (a->j[j] >= i) { 678 #if defined(PETSC_USE_COMPLEX) 679 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 680 #else 681 if (a->a[j] != 0.0) nzd++; 682 #endif 683 } 684 } 685 } 686 sptr[m] = nzd+1; 687 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 688 for (i=0; i<m+1; i+=6) { 689 if (i+4<m) { 690 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4],sptr[i+5]);CHKERRQ(ierr); 691 } else if (i+3<m) { 692 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4]);CHKERRQ(ierr); 693 } else if (i+2<m) { 694 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 695 } else if (i+1<m) { 696 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 697 } else if (i<m) { 698 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 699 } else { 700 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 701 } 702 } 703 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 704 ierr = PetscFree(sptr);CHKERRQ(ierr); 705 for (i=0; i<m; i++) { 706 for (j=a->i[i]; j<a->i[i+1]; j++) { 707 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 708 } 709 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 710 } 711 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 712 for (i=0; i<m; i++) { 713 for (j=a->i[i]; j<a->i[i+1]; j++) { 714 if (a->j[j] >= i) { 715 #if defined(PETSC_USE_COMPLEX) 716 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 717 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 718 } 719 #else 720 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 721 #endif 722 } 723 } 724 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 725 } 726 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 727 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 728 PetscInt cnt = 0,jcnt; 729 PetscScalar value; 730 #if defined(PETSC_USE_COMPLEX) 731 PetscBool realonly = PETSC_TRUE; 732 733 for (i=0; i<a->i[m]; i++) { 734 if (PetscImaginaryPart(a->a[i]) != 0.0) { 735 realonly = PETSC_FALSE; 736 break; 737 } 738 } 739 #endif 740 741 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 742 for (i=0; i<m; i++) { 743 jcnt = 0; 744 for (j=0; j<A->cmap->n; j++) { 745 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 746 value = a->a[cnt++]; 747 jcnt++; 748 } else { 749 value = 0.0; 750 } 751 #if defined(PETSC_USE_COMPLEX) 752 if (realonly) { 753 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 754 } else { 755 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 756 } 757 #else 758 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 759 #endif 760 } 761 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 762 } 763 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 764 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 765 PetscInt fshift=1; 766 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 767 #if defined(PETSC_USE_COMPLEX) 768 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");CHKERRQ(ierr); 769 #else 770 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");CHKERRQ(ierr); 771 #endif 772 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 773 for (i=0; i<m; i++) { 774 for (j=a->i[i]; j<a->i[i+1]; j++) { 775 #if defined(PETSC_USE_COMPLEX) 776 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 777 #else 778 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 779 #endif 780 } 781 } 782 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 783 } else { 784 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 785 if (A->factortype) { 786 for (i=0; i<m; i++) { 787 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 788 /* L part */ 789 for (j=a->i[i]; j<a->i[i+1]; j++) { 790 #if defined(PETSC_USE_COMPLEX) 791 if (PetscImaginaryPart(a->a[j]) > 0.0) { 792 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 793 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 794 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 795 } else { 796 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 797 } 798 #else 799 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 800 #endif 801 } 802 /* diagonal */ 803 j = a->diag[i]; 804 #if defined(PETSC_USE_COMPLEX) 805 if (PetscImaginaryPart(a->a[j]) > 0.0) { 806 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 807 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 808 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)(-PetscImaginaryPart(1.0/a->a[j])));CHKERRQ(ierr); 809 } else { 810 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 811 } 812 #else 813 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 814 #endif 815 816 /* U part */ 817 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 818 #if defined(PETSC_USE_COMPLEX) 819 if (PetscImaginaryPart(a->a[j]) > 0.0) { 820 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 821 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 822 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 823 } else { 824 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 825 } 826 #else 827 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 828 #endif 829 } 830 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 831 } 832 } else { 833 for (i=0; i<m; i++) { 834 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 835 for (j=a->i[i]; j<a->i[i+1]; j++) { 836 #if defined(PETSC_USE_COMPLEX) 837 if (PetscImaginaryPart(a->a[j]) > 0.0) { 838 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 839 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 840 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 841 } else { 842 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 843 } 844 #else 845 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 846 #endif 847 } 848 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 849 } 850 } 851 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 852 } 853 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 854 PetscFunctionReturn(0); 855 } 856 857 #include <petscdraw.h> 858 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 859 { 860 Mat A = (Mat) Aa; 861 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 862 PetscErrorCode ierr; 863 PetscInt i,j,m = A->rmap->n; 864 int color; 865 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 866 PetscViewer viewer; 867 PetscViewerFormat format; 868 869 PetscFunctionBegin; 870 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 871 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 872 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 873 874 /* loop over matrix elements drawing boxes */ 875 876 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 877 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 878 /* Blue for negative, Cyan for zero and Red for positive */ 879 color = PETSC_DRAW_BLUE; 880 for (i=0; i<m; i++) { 881 y_l = m - i - 1.0; y_r = y_l + 1.0; 882 for (j=a->i[i]; j<a->i[i+1]; j++) { 883 x_l = a->j[j]; x_r = x_l + 1.0; 884 if (PetscRealPart(a->a[j]) >= 0.) continue; 885 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 886 } 887 } 888 color = PETSC_DRAW_CYAN; 889 for (i=0; i<m; i++) { 890 y_l = m - i - 1.0; y_r = y_l + 1.0; 891 for (j=a->i[i]; j<a->i[i+1]; j++) { 892 x_l = a->j[j]; x_r = x_l + 1.0; 893 if (a->a[j] != 0.) continue; 894 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 895 } 896 } 897 color = PETSC_DRAW_RED; 898 for (i=0; i<m; i++) { 899 y_l = m - i - 1.0; y_r = y_l + 1.0; 900 for (j=a->i[i]; j<a->i[i+1]; j++) { 901 x_l = a->j[j]; x_r = x_l + 1.0; 902 if (PetscRealPart(a->a[j]) <= 0.) continue; 903 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 904 } 905 } 906 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 907 } else { 908 /* use contour shading to indicate magnitude of values */ 909 /* first determine max of all nonzero values */ 910 PetscReal minv = 0.0, maxv = 0.0; 911 PetscInt nz = a->nz, count = 0; 912 PetscDraw popup; 913 914 for (i=0; i<nz; i++) { 915 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 916 } 917 if (minv >= maxv) maxv = minv + PETSC_SMALL; 918 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 919 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 920 921 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 922 for (i=0; i<m; i++) { 923 y_l = m - i - 1.0; 924 y_r = y_l + 1.0; 925 for (j=a->i[i]; j<a->i[i+1]; j++) { 926 x_l = a->j[j]; 927 x_r = x_l + 1.0; 928 color = PetscDrawRealToColor(PetscAbsScalar(a->a[count]),minv,maxv); 929 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 930 count++; 931 } 932 } 933 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 934 } 935 PetscFunctionReturn(0); 936 } 937 938 #include <petscdraw.h> 939 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 940 { 941 PetscErrorCode ierr; 942 PetscDraw draw; 943 PetscReal xr,yr,xl,yl,h,w; 944 PetscBool isnull; 945 946 PetscFunctionBegin; 947 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 948 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 949 if (isnull) PetscFunctionReturn(0); 950 951 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 952 xr += w; yr += h; xl = -w; yl = -h; 953 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 954 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 955 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 956 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 957 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 958 PetscFunctionReturn(0); 959 } 960 961 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 962 { 963 PetscErrorCode ierr; 964 PetscBool iascii,isbinary,isdraw; 965 966 PetscFunctionBegin; 967 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 968 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 969 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 970 if (iascii) { 971 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 972 } else if (isbinary) { 973 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 974 } else if (isdraw) { 975 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 976 } 977 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 978 PetscFunctionReturn(0); 979 } 980 981 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 982 { 983 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 984 PetscErrorCode ierr; 985 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 986 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 987 MatScalar *aa = a->a,*ap; 988 PetscReal ratio = 0.6; 989 990 PetscFunctionBegin; 991 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 992 993 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 994 for (i=1; i<m; i++) { 995 /* move each row back by the amount of empty slots (fshift) before it*/ 996 fshift += imax[i-1] - ailen[i-1]; 997 rmax = PetscMax(rmax,ailen[i]); 998 if (fshift) { 999 ip = aj + ai[i]; 1000 ap = aa + ai[i]; 1001 N = ailen[i]; 1002 for (j=0; j<N; j++) { 1003 ip[j-fshift] = ip[j]; 1004 if (!A->structure_only) ap[j-fshift] = ap[j]; 1005 } 1006 } 1007 ai[i] = ai[i-1] + ailen[i-1]; 1008 } 1009 if (m) { 1010 fshift += imax[m-1] - ailen[m-1]; 1011 ai[m] = ai[m-1] + ailen[m-1]; 1012 } 1013 1014 /* reset ilen and imax for each row */ 1015 a->nonzerorowcnt = 0; 1016 if (A->structure_only) { 1017 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1018 } else { /* !A->structure_only */ 1019 for (i=0; i<m; i++) { 1020 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1021 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1022 } 1023 } 1024 a->nz = ai[m]; 1025 if (fshift && a->nounused == -1) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D, %D unneeded", m, A->cmap->n, fshift); 1026 1027 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1028 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1029 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1030 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1031 1032 A->info.mallocs += a->reallocs; 1033 a->reallocs = 0; 1034 A->info.nz_unneeded = (PetscReal)fshift; 1035 a->rmax = rmax; 1036 1037 if (!A->structure_only) { 1038 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1039 } 1040 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1041 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1042 PetscFunctionReturn(0); 1043 } 1044 1045 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1046 { 1047 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1048 PetscInt i,nz = a->nz; 1049 MatScalar *aa = a->a; 1050 PetscErrorCode ierr; 1051 1052 PetscFunctionBegin; 1053 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1054 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } 1057 1058 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1059 { 1060 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1061 PetscInt i,nz = a->nz; 1062 MatScalar *aa = a->a; 1063 PetscErrorCode ierr; 1064 1065 PetscFunctionBegin; 1066 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1067 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1068 PetscFunctionReturn(0); 1069 } 1070 1071 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1072 { 1073 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1074 PetscErrorCode ierr; 1075 1076 PetscFunctionBegin; 1077 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1078 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1079 PetscFunctionReturn(0); 1080 } 1081 1082 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1083 { 1084 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1085 PetscErrorCode ierr; 1086 1087 PetscFunctionBegin; 1088 #if defined(PETSC_USE_LOG) 1089 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1090 #endif 1091 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1092 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1093 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1094 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1095 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1096 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1097 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1098 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1099 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1100 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1101 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1102 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1103 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1104 1105 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1106 ierr = PetscFree(A->data);CHKERRQ(ierr); 1107 1108 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1109 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1110 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1111 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1112 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1115 #if defined(PETSC_HAVE_ELEMENTAL) 1116 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); 1117 #endif 1118 #if defined(PETSC_HAVE_HYPRE) 1119 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_hypre_C",NULL);CHKERRQ(ierr); 1120 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMatMatMult_transpose_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1121 #endif 1122 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1123 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1124 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1125 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1126 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1127 PetscFunctionReturn(0); 1128 } 1129 1130 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1131 { 1132 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1133 PetscErrorCode ierr; 1134 1135 PetscFunctionBegin; 1136 switch (op) { 1137 case MAT_ROW_ORIENTED: 1138 a->roworiented = flg; 1139 break; 1140 case MAT_KEEP_NONZERO_PATTERN: 1141 a->keepnonzeropattern = flg; 1142 break; 1143 case MAT_NEW_NONZERO_LOCATIONS: 1144 a->nonew = (flg ? 0 : 1); 1145 break; 1146 case MAT_NEW_NONZERO_LOCATION_ERR: 1147 a->nonew = (flg ? -1 : 0); 1148 break; 1149 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1150 a->nonew = (flg ? -2 : 0); 1151 break; 1152 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1153 a->nounused = (flg ? -1 : 0); 1154 break; 1155 case MAT_IGNORE_ZERO_ENTRIES: 1156 a->ignorezeroentries = flg; 1157 break; 1158 case MAT_SPD: 1159 case MAT_SYMMETRIC: 1160 case MAT_STRUCTURALLY_SYMMETRIC: 1161 case MAT_HERMITIAN: 1162 case MAT_SYMMETRY_ETERNAL: 1163 case MAT_STRUCTURE_ONLY: 1164 /* These options are handled directly by MatSetOption() */ 1165 break; 1166 case MAT_NEW_DIAGONALS: 1167 case MAT_IGNORE_OFF_PROC_ENTRIES: 1168 case MAT_USE_HASH_TABLE: 1169 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1170 break; 1171 case MAT_USE_INODES: 1172 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1173 break; 1174 case MAT_SUBMAT_SINGLEIS: 1175 A->submat_singleis = flg; 1176 break; 1177 default: 1178 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1179 } 1180 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1181 PetscFunctionReturn(0); 1182 } 1183 1184 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1185 { 1186 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1187 PetscErrorCode ierr; 1188 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1189 PetscScalar *aa=a->a,*x,zero=0.0; 1190 1191 PetscFunctionBegin; 1192 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1193 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1194 1195 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1196 PetscInt *diag=a->diag; 1197 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1198 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1199 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1200 PetscFunctionReturn(0); 1201 } 1202 1203 ierr = VecSet(v,zero);CHKERRQ(ierr); 1204 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1205 for (i=0; i<n; i++) { 1206 nz = ai[i+1] - ai[i]; 1207 if (!nz) x[i] = 0.0; 1208 for (j=ai[i]; j<ai[i+1]; j++) { 1209 if (aj[j] == i) { 1210 x[i] = aa[j]; 1211 break; 1212 } 1213 } 1214 } 1215 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1216 PetscFunctionReturn(0); 1217 } 1218 1219 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1220 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1221 { 1222 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1223 PetscScalar *y; 1224 const PetscScalar *x; 1225 PetscErrorCode ierr; 1226 PetscInt m = A->rmap->n; 1227 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1228 const MatScalar *v; 1229 PetscScalar alpha; 1230 PetscInt n,i,j; 1231 const PetscInt *idx,*ii,*ridx=NULL; 1232 Mat_CompressedRow cprow = a->compressedrow; 1233 PetscBool usecprow = cprow.use; 1234 #endif 1235 1236 PetscFunctionBegin; 1237 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1238 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1239 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1240 1241 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1242 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1243 #else 1244 if (usecprow) { 1245 m = cprow.nrows; 1246 ii = cprow.i; 1247 ridx = cprow.rindex; 1248 } else { 1249 ii = a->i; 1250 } 1251 for (i=0; i<m; i++) { 1252 idx = a->j + ii[i]; 1253 v = a->a + ii[i]; 1254 n = ii[i+1] - ii[i]; 1255 if (usecprow) { 1256 alpha = x[ridx[i]]; 1257 } else { 1258 alpha = x[i]; 1259 } 1260 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1261 } 1262 #endif 1263 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1264 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1265 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1266 PetscFunctionReturn(0); 1267 } 1268 1269 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1270 { 1271 PetscErrorCode ierr; 1272 1273 PetscFunctionBegin; 1274 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1275 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1276 PetscFunctionReturn(0); 1277 } 1278 1279 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1280 1281 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1282 { 1283 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1284 PetscScalar *y; 1285 const PetscScalar *x; 1286 const MatScalar *aa; 1287 PetscErrorCode ierr; 1288 PetscInt m=A->rmap->n; 1289 const PetscInt *aj,*ii,*ridx=NULL; 1290 PetscInt n,i; 1291 PetscScalar sum; 1292 PetscBool usecprow=a->compressedrow.use; 1293 1294 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1295 #pragma disjoint(*x,*y,*aa) 1296 #endif 1297 1298 PetscFunctionBegin; 1299 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1300 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1301 ii = a->i; 1302 if (usecprow) { /* use compressed row format */ 1303 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1304 m = a->compressedrow.nrows; 1305 ii = a->compressedrow.i; 1306 ridx = a->compressedrow.rindex; 1307 for (i=0; i<m; i++) { 1308 n = ii[i+1] - ii[i]; 1309 aj = a->j + ii[i]; 1310 aa = a->a + ii[i]; 1311 sum = 0.0; 1312 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1313 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1314 y[*ridx++] = sum; 1315 } 1316 } else { /* do not use compressed row format */ 1317 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1318 aj = a->j; 1319 aa = a->a; 1320 fortranmultaij_(&m,x,ii,aj,aa,y); 1321 #else 1322 for (i=0; i<m; i++) { 1323 n = ii[i+1] - ii[i]; 1324 aj = a->j + ii[i]; 1325 aa = a->a + ii[i]; 1326 sum = 0.0; 1327 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1328 y[i] = sum; 1329 } 1330 #endif 1331 } 1332 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1333 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1334 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1335 PetscFunctionReturn(0); 1336 } 1337 1338 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1339 { 1340 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1341 PetscScalar *y; 1342 const PetscScalar *x; 1343 const MatScalar *aa; 1344 PetscErrorCode ierr; 1345 PetscInt m=A->rmap->n; 1346 const PetscInt *aj,*ii,*ridx=NULL; 1347 PetscInt n,i,nonzerorow=0; 1348 PetscScalar sum; 1349 PetscBool usecprow=a->compressedrow.use; 1350 1351 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1352 #pragma disjoint(*x,*y,*aa) 1353 #endif 1354 1355 PetscFunctionBegin; 1356 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1357 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1358 if (usecprow) { /* use compressed row format */ 1359 m = a->compressedrow.nrows; 1360 ii = a->compressedrow.i; 1361 ridx = a->compressedrow.rindex; 1362 for (i=0; i<m; i++) { 1363 n = ii[i+1] - ii[i]; 1364 aj = a->j + ii[i]; 1365 aa = a->a + ii[i]; 1366 sum = 0.0; 1367 nonzerorow += (n>0); 1368 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1369 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1370 y[*ridx++] = sum; 1371 } 1372 } else { /* do not use compressed row format */ 1373 ii = a->i; 1374 for (i=0; i<m; i++) { 1375 n = ii[i+1] - ii[i]; 1376 aj = a->j + ii[i]; 1377 aa = a->a + ii[i]; 1378 sum = 0.0; 1379 nonzerorow += (n>0); 1380 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1381 y[i] = sum; 1382 } 1383 } 1384 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1385 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1386 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1387 PetscFunctionReturn(0); 1388 } 1389 1390 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1391 { 1392 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1393 PetscScalar *y,*z; 1394 const PetscScalar *x; 1395 const MatScalar *aa; 1396 PetscErrorCode ierr; 1397 PetscInt m = A->rmap->n,*aj,*ii; 1398 PetscInt n,i,*ridx=NULL; 1399 PetscScalar sum; 1400 PetscBool usecprow=a->compressedrow.use; 1401 1402 PetscFunctionBegin; 1403 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1404 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1405 if (usecprow) { /* use compressed row format */ 1406 if (zz != yy) { 1407 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1408 } 1409 m = a->compressedrow.nrows; 1410 ii = a->compressedrow.i; 1411 ridx = a->compressedrow.rindex; 1412 for (i=0; i<m; i++) { 1413 n = ii[i+1] - ii[i]; 1414 aj = a->j + ii[i]; 1415 aa = a->a + ii[i]; 1416 sum = y[*ridx]; 1417 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1418 z[*ridx++] = sum; 1419 } 1420 } else { /* do not use compressed row format */ 1421 ii = a->i; 1422 for (i=0; i<m; i++) { 1423 n = ii[i+1] - ii[i]; 1424 aj = a->j + ii[i]; 1425 aa = a->a + ii[i]; 1426 sum = y[i]; 1427 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1428 z[i] = sum; 1429 } 1430 } 1431 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1432 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1433 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1434 PetscFunctionReturn(0); 1435 } 1436 1437 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1438 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1439 { 1440 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1441 PetscScalar *y,*z; 1442 const PetscScalar *x; 1443 const MatScalar *aa; 1444 PetscErrorCode ierr; 1445 const PetscInt *aj,*ii,*ridx=NULL; 1446 PetscInt m = A->rmap->n,n,i; 1447 PetscScalar sum; 1448 PetscBool usecprow=a->compressedrow.use; 1449 1450 PetscFunctionBegin; 1451 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1452 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1453 if (usecprow) { /* use compressed row format */ 1454 if (zz != yy) { 1455 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1456 } 1457 m = a->compressedrow.nrows; 1458 ii = a->compressedrow.i; 1459 ridx = a->compressedrow.rindex; 1460 for (i=0; i<m; i++) { 1461 n = ii[i+1] - ii[i]; 1462 aj = a->j + ii[i]; 1463 aa = a->a + ii[i]; 1464 sum = y[*ridx]; 1465 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1466 z[*ridx++] = sum; 1467 } 1468 } else { /* do not use compressed row format */ 1469 ii = a->i; 1470 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1471 aj = a->j; 1472 aa = a->a; 1473 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1474 #else 1475 for (i=0; i<m; i++) { 1476 n = ii[i+1] - ii[i]; 1477 aj = a->j + ii[i]; 1478 aa = a->a + ii[i]; 1479 sum = y[i]; 1480 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1481 z[i] = sum; 1482 } 1483 #endif 1484 } 1485 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1486 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1487 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1488 #if defined(PETSC_HAVE_CUSP) 1489 /* 1490 ierr = VecView(xx,0);CHKERRQ(ierr); 1491 ierr = VecView(zz,0);CHKERRQ(ierr); 1492 ierr = MatView(A,0);CHKERRQ(ierr); 1493 */ 1494 #endif 1495 PetscFunctionReturn(0); 1496 } 1497 1498 /* 1499 Adds diagonal pointers to sparse matrix structure. 1500 */ 1501 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1502 { 1503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1504 PetscErrorCode ierr; 1505 PetscInt i,j,m = A->rmap->n; 1506 1507 PetscFunctionBegin; 1508 if (!a->diag) { 1509 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1510 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1511 } 1512 for (i=0; i<A->rmap->n; i++) { 1513 a->diag[i] = a->i[i+1]; 1514 for (j=a->i[i]; j<a->i[i+1]; j++) { 1515 if (a->j[j] == i) { 1516 a->diag[i] = j; 1517 break; 1518 } 1519 } 1520 } 1521 PetscFunctionReturn(0); 1522 } 1523 1524 /* 1525 Checks for missing diagonals 1526 */ 1527 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1528 { 1529 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1530 PetscInt *diag,*ii = a->i,i; 1531 1532 PetscFunctionBegin; 1533 *missing = PETSC_FALSE; 1534 if (A->rmap->n > 0 && !ii) { 1535 *missing = PETSC_TRUE; 1536 if (d) *d = 0; 1537 PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n"); 1538 } else { 1539 diag = a->diag; 1540 for (i=0; i<A->rmap->n; i++) { 1541 if (diag[i] >= ii[i+1]) { 1542 *missing = PETSC_TRUE; 1543 if (d) *d = i; 1544 PetscInfo1(A,"Matrix is missing diagonal number %D\n",i); 1545 break; 1546 } 1547 } 1548 } 1549 PetscFunctionReturn(0); 1550 } 1551 1552 /* 1553 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1554 */ 1555 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1556 { 1557 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1558 PetscErrorCode ierr; 1559 PetscInt i,*diag,m = A->rmap->n; 1560 MatScalar *v = a->a; 1561 PetscScalar *idiag,*mdiag; 1562 1563 PetscFunctionBegin; 1564 if (a->idiagvalid) PetscFunctionReturn(0); 1565 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1566 diag = a->diag; 1567 if (!a->idiag) { 1568 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1569 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1570 v = a->a; 1571 } 1572 mdiag = a->mdiag; 1573 idiag = a->idiag; 1574 1575 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1576 for (i=0; i<m; i++) { 1577 mdiag[i] = v[diag[i]]; 1578 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1579 if (PetscRealPart(fshift)) { 1580 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1581 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1582 A->factorerror_zeropivot_value = 0.0; 1583 A->factorerror_zeropivot_row = i; 1584 } SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1585 } 1586 idiag[i] = 1.0/v[diag[i]]; 1587 } 1588 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1589 } else { 1590 for (i=0; i<m; i++) { 1591 mdiag[i] = v[diag[i]]; 1592 idiag[i] = omega/(fshift + v[diag[i]]); 1593 } 1594 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1595 } 1596 a->idiagvalid = PETSC_TRUE; 1597 PetscFunctionReturn(0); 1598 } 1599 1600 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1601 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1602 { 1603 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1604 PetscScalar *x,d,sum,*t,scale; 1605 const MatScalar *v,*idiag=0,*mdiag; 1606 const PetscScalar *b, *bs,*xb, *ts; 1607 PetscErrorCode ierr; 1608 PetscInt n,m = A->rmap->n,i; 1609 const PetscInt *idx,*diag; 1610 1611 PetscFunctionBegin; 1612 its = its*lits; 1613 1614 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1615 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1616 a->fshift = fshift; 1617 a->omega = omega; 1618 1619 diag = a->diag; 1620 t = a->ssor_work; 1621 idiag = a->idiag; 1622 mdiag = a->mdiag; 1623 1624 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1625 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1626 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1627 if (flag == SOR_APPLY_UPPER) { 1628 /* apply (U + D/omega) to the vector */ 1629 bs = b; 1630 for (i=0; i<m; i++) { 1631 d = fshift + mdiag[i]; 1632 n = a->i[i+1] - diag[i] - 1; 1633 idx = a->j + diag[i] + 1; 1634 v = a->a + diag[i] + 1; 1635 sum = b[i]*d/omega; 1636 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1637 x[i] = sum; 1638 } 1639 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1640 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1641 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1642 PetscFunctionReturn(0); 1643 } 1644 1645 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1646 else if (flag & SOR_EISENSTAT) { 1647 /* Let A = L + U + D; where L is lower trianglar, 1648 U is upper triangular, E = D/omega; This routine applies 1649 1650 (L + E)^{-1} A (U + E)^{-1} 1651 1652 to a vector efficiently using Eisenstat's trick. 1653 */ 1654 scale = (2.0/omega) - 1.0; 1655 1656 /* x = (E + U)^{-1} b */ 1657 for (i=m-1; i>=0; i--) { 1658 n = a->i[i+1] - diag[i] - 1; 1659 idx = a->j + diag[i] + 1; 1660 v = a->a + diag[i] + 1; 1661 sum = b[i]; 1662 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1663 x[i] = sum*idiag[i]; 1664 } 1665 1666 /* t = b - (2*E - D)x */ 1667 v = a->a; 1668 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1669 1670 /* t = (E + L)^{-1}t */ 1671 ts = t; 1672 diag = a->diag; 1673 for (i=0; i<m; i++) { 1674 n = diag[i] - a->i[i]; 1675 idx = a->j + a->i[i]; 1676 v = a->a + a->i[i]; 1677 sum = t[i]; 1678 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1679 t[i] = sum*idiag[i]; 1680 /* x = x + t */ 1681 x[i] += t[i]; 1682 } 1683 1684 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1685 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1686 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1687 PetscFunctionReturn(0); 1688 } 1689 if (flag & SOR_ZERO_INITIAL_GUESS) { 1690 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1691 for (i=0; i<m; i++) { 1692 n = diag[i] - a->i[i]; 1693 idx = a->j + a->i[i]; 1694 v = a->a + a->i[i]; 1695 sum = b[i]; 1696 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1697 t[i] = sum; 1698 x[i] = sum*idiag[i]; 1699 } 1700 xb = t; 1701 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1702 } else xb = b; 1703 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1704 for (i=m-1; i>=0; i--) { 1705 n = a->i[i+1] - diag[i] - 1; 1706 idx = a->j + diag[i] + 1; 1707 v = a->a + diag[i] + 1; 1708 sum = xb[i]; 1709 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1710 if (xb == b) { 1711 x[i] = sum*idiag[i]; 1712 } else { 1713 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1714 } 1715 } 1716 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1717 } 1718 its--; 1719 } 1720 while (its--) { 1721 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1722 for (i=0; i<m; i++) { 1723 /* lower */ 1724 n = diag[i] - a->i[i]; 1725 idx = a->j + a->i[i]; 1726 v = a->a + a->i[i]; 1727 sum = b[i]; 1728 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1729 t[i] = sum; /* save application of the lower-triangular part */ 1730 /* upper */ 1731 n = a->i[i+1] - diag[i] - 1; 1732 idx = a->j + diag[i] + 1; 1733 v = a->a + diag[i] + 1; 1734 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1735 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1736 } 1737 xb = t; 1738 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1739 } else xb = b; 1740 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1741 for (i=m-1; i>=0; i--) { 1742 sum = xb[i]; 1743 if (xb == b) { 1744 /* whole matrix (no checkpointing available) */ 1745 n = a->i[i+1] - a->i[i]; 1746 idx = a->j + a->i[i]; 1747 v = a->a + a->i[i]; 1748 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1749 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1750 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1751 n = a->i[i+1] - diag[i] - 1; 1752 idx = a->j + diag[i] + 1; 1753 v = a->a + diag[i] + 1; 1754 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1755 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1756 } 1757 } 1758 if (xb == b) { 1759 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1760 } else { 1761 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1762 } 1763 } 1764 } 1765 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1766 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1767 PetscFunctionReturn(0); 1768 } 1769 1770 1771 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1772 { 1773 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1774 1775 PetscFunctionBegin; 1776 info->block_size = 1.0; 1777 info->nz_allocated = (double)a->maxnz; 1778 info->nz_used = (double)a->nz; 1779 info->nz_unneeded = (double)(a->maxnz - a->nz); 1780 info->assemblies = (double)A->num_ass; 1781 info->mallocs = (double)A->info.mallocs; 1782 info->memory = ((PetscObject)A)->mem; 1783 if (A->factortype) { 1784 info->fill_ratio_given = A->info.fill_ratio_given; 1785 info->fill_ratio_needed = A->info.fill_ratio_needed; 1786 info->factor_mallocs = A->info.factor_mallocs; 1787 } else { 1788 info->fill_ratio_given = 0; 1789 info->fill_ratio_needed = 0; 1790 info->factor_mallocs = 0; 1791 } 1792 PetscFunctionReturn(0); 1793 } 1794 1795 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1796 { 1797 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1798 PetscInt i,m = A->rmap->n - 1; 1799 PetscErrorCode ierr; 1800 const PetscScalar *xx; 1801 PetscScalar *bb; 1802 PetscInt d = 0; 1803 1804 PetscFunctionBegin; 1805 if (x && b) { 1806 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1807 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1808 for (i=0; i<N; i++) { 1809 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1810 bb[rows[i]] = diag*xx[rows[i]]; 1811 } 1812 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1813 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1814 } 1815 1816 if (a->keepnonzeropattern) { 1817 for (i=0; i<N; i++) { 1818 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1819 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1820 } 1821 if (diag != 0.0) { 1822 for (i=0; i<N; i++) { 1823 d = rows[i]; 1824 if (a->diag[d] >= a->i[d+1]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in the zeroed row %D",d); 1825 } 1826 for (i=0; i<N; i++) { 1827 a->a[a->diag[rows[i]]] = diag; 1828 } 1829 } 1830 } else { 1831 if (diag != 0.0) { 1832 for (i=0; i<N; i++) { 1833 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1834 if (a->ilen[rows[i]] > 0) { 1835 a->ilen[rows[i]] = 1; 1836 a->a[a->i[rows[i]]] = diag; 1837 a->j[a->i[rows[i]]] = rows[i]; 1838 } else { /* in case row was completely empty */ 1839 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1840 } 1841 } 1842 } else { 1843 for (i=0; i<N; i++) { 1844 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1845 a->ilen[rows[i]] = 0; 1846 } 1847 } 1848 A->nonzerostate++; 1849 } 1850 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1851 PetscFunctionReturn(0); 1852 } 1853 1854 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1855 { 1856 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1857 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1858 PetscErrorCode ierr; 1859 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1860 const PetscScalar *xx; 1861 PetscScalar *bb; 1862 1863 PetscFunctionBegin; 1864 if (x && b) { 1865 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1866 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1867 vecs = PETSC_TRUE; 1868 } 1869 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 1870 for (i=0; i<N; i++) { 1871 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1872 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1873 1874 zeroed[rows[i]] = PETSC_TRUE; 1875 } 1876 for (i=0; i<A->rmap->n; i++) { 1877 if (!zeroed[i]) { 1878 for (j=a->i[i]; j<a->i[i+1]; j++) { 1879 if (zeroed[a->j[j]]) { 1880 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1881 a->a[j] = 0.0; 1882 } 1883 } 1884 } else if (vecs) bb[i] = diag*xx[i]; 1885 } 1886 if (x && b) { 1887 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1888 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1889 } 1890 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1891 if (diag != 0.0) { 1892 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1893 if (missing) { 1894 if (a->nonew) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1895 else { 1896 for (i=0; i<N; i++) { 1897 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1898 } 1899 } 1900 } else { 1901 for (i=0; i<N; i++) { 1902 a->a[a->diag[rows[i]]] = diag; 1903 } 1904 } 1905 } 1906 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1907 PetscFunctionReturn(0); 1908 } 1909 1910 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1911 { 1912 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1913 PetscInt *itmp; 1914 1915 PetscFunctionBegin; 1916 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1917 1918 *nz = a->i[row+1] - a->i[row]; 1919 if (v) *v = a->a + a->i[row]; 1920 if (idx) { 1921 itmp = a->j + a->i[row]; 1922 if (*nz) *idx = itmp; 1923 else *idx = 0; 1924 } 1925 PetscFunctionReturn(0); 1926 } 1927 1928 /* remove this function? */ 1929 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1930 { 1931 PetscFunctionBegin; 1932 PetscFunctionReturn(0); 1933 } 1934 1935 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1936 { 1937 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1938 MatScalar *v = a->a; 1939 PetscReal sum = 0.0; 1940 PetscErrorCode ierr; 1941 PetscInt i,j; 1942 1943 PetscFunctionBegin; 1944 if (type == NORM_FROBENIUS) { 1945 #if defined(PETSC_USE_REAL___FP16) 1946 PetscBLASInt one = 1,nz = a->nz; 1947 *nrm = BLASnrm2_(&nz,v,&one); 1948 #else 1949 for (i=0; i<a->nz; i++) { 1950 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1951 } 1952 *nrm = PetscSqrtReal(sum); 1953 #endif 1954 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 1955 } else if (type == NORM_1) { 1956 PetscReal *tmp; 1957 PetscInt *jj = a->j; 1958 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 1959 *nrm = 0.0; 1960 for (j=0; j<a->nz; j++) { 1961 tmp[*jj++] += PetscAbsScalar(*v); v++; 1962 } 1963 for (j=0; j<A->cmap->n; j++) { 1964 if (tmp[j] > *nrm) *nrm = tmp[j]; 1965 } 1966 ierr = PetscFree(tmp);CHKERRQ(ierr); 1967 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1968 } else if (type == NORM_INFINITY) { 1969 *nrm = 0.0; 1970 for (j=0; j<A->rmap->n; j++) { 1971 v = a->a + a->i[j]; 1972 sum = 0.0; 1973 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 1974 sum += PetscAbsScalar(*v); v++; 1975 } 1976 if (sum > *nrm) *nrm = sum; 1977 } 1978 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1979 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 1980 PetscFunctionReturn(0); 1981 } 1982 1983 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 1984 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 1985 { 1986 PetscErrorCode ierr; 1987 PetscInt i,j,anzj; 1988 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 1989 PetscInt an=A->cmap->N,am=A->rmap->N; 1990 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 1991 1992 PetscFunctionBegin; 1993 /* Allocate space for symbolic transpose info and work array */ 1994 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 1995 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 1996 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 1997 1998 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 1999 /* Note: offset by 1 for fast conversion into csr format. */ 2000 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2001 /* Form ati for csr format of A^T. */ 2002 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2003 2004 /* Copy ati into atfill so we have locations of the next free space in atj */ 2005 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2006 2007 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2008 for (i=0;i<am;i++) { 2009 anzj = ai[i+1] - ai[i]; 2010 for (j=0;j<anzj;j++) { 2011 atj[atfill[*aj]] = i; 2012 atfill[*aj++] += 1; 2013 } 2014 } 2015 2016 /* Clean up temporary space and complete requests. */ 2017 ierr = PetscFree(atfill);CHKERRQ(ierr); 2018 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2019 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2020 2021 b = (Mat_SeqAIJ*)((*B)->data); 2022 b->free_a = PETSC_FALSE; 2023 b->free_ij = PETSC_TRUE; 2024 b->nonew = 0; 2025 PetscFunctionReturn(0); 2026 } 2027 2028 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2029 { 2030 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2031 Mat C; 2032 PetscErrorCode ierr; 2033 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2034 MatScalar *array = a->a; 2035 2036 PetscFunctionBegin; 2037 if (reuse == MAT_INPLACE_MATRIX && m != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2038 2039 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { 2040 ierr = PetscCalloc1(1+A->cmap->n,&col);CHKERRQ(ierr); 2041 2042 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2043 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2044 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2045 ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2046 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2047 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2048 ierr = PetscFree(col);CHKERRQ(ierr); 2049 } else { 2050 C = *B; 2051 } 2052 2053 for (i=0; i<m; i++) { 2054 len = ai[i+1]-ai[i]; 2055 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2056 array += len; 2057 aj += len; 2058 } 2059 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2060 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2061 2062 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 2063 *B = C; 2064 } else { 2065 ierr = MatHeaderMerge(A,&C);CHKERRQ(ierr); 2066 } 2067 PetscFunctionReturn(0); 2068 } 2069 2070 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2071 { 2072 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2073 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2074 MatScalar *va,*vb; 2075 PetscErrorCode ierr; 2076 PetscInt ma,na,mb,nb, i; 2077 2078 PetscFunctionBegin; 2079 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2080 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2081 if (ma!=nb || na!=mb) { 2082 *f = PETSC_FALSE; 2083 PetscFunctionReturn(0); 2084 } 2085 aii = aij->i; bii = bij->i; 2086 adx = aij->j; bdx = bij->j; 2087 va = aij->a; vb = bij->a; 2088 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2089 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2090 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2091 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2092 2093 *f = PETSC_TRUE; 2094 for (i=0; i<ma; i++) { 2095 while (aptr[i]<aii[i+1]) { 2096 PetscInt idc,idr; 2097 PetscScalar vc,vr; 2098 /* column/row index/value */ 2099 idc = adx[aptr[i]]; 2100 idr = bdx[bptr[idc]]; 2101 vc = va[aptr[i]]; 2102 vr = vb[bptr[idc]]; 2103 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2104 *f = PETSC_FALSE; 2105 goto done; 2106 } else { 2107 aptr[i]++; 2108 if (B || i!=idc) bptr[idc]++; 2109 } 2110 } 2111 } 2112 done: 2113 ierr = PetscFree(aptr);CHKERRQ(ierr); 2114 ierr = PetscFree(bptr);CHKERRQ(ierr); 2115 PetscFunctionReturn(0); 2116 } 2117 2118 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2119 { 2120 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2121 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2122 MatScalar *va,*vb; 2123 PetscErrorCode ierr; 2124 PetscInt ma,na,mb,nb, i; 2125 2126 PetscFunctionBegin; 2127 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2128 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2129 if (ma!=nb || na!=mb) { 2130 *f = PETSC_FALSE; 2131 PetscFunctionReturn(0); 2132 } 2133 aii = aij->i; bii = bij->i; 2134 adx = aij->j; bdx = bij->j; 2135 va = aij->a; vb = bij->a; 2136 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2137 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2138 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2139 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2140 2141 *f = PETSC_TRUE; 2142 for (i=0; i<ma; i++) { 2143 while (aptr[i]<aii[i+1]) { 2144 PetscInt idc,idr; 2145 PetscScalar vc,vr; 2146 /* column/row index/value */ 2147 idc = adx[aptr[i]]; 2148 idr = bdx[bptr[idc]]; 2149 vc = va[aptr[i]]; 2150 vr = vb[bptr[idc]]; 2151 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2152 *f = PETSC_FALSE; 2153 goto done; 2154 } else { 2155 aptr[i]++; 2156 if (B || i!=idc) bptr[idc]++; 2157 } 2158 } 2159 } 2160 done: 2161 ierr = PetscFree(aptr);CHKERRQ(ierr); 2162 ierr = PetscFree(bptr);CHKERRQ(ierr); 2163 PetscFunctionReturn(0); 2164 } 2165 2166 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2167 { 2168 PetscErrorCode ierr; 2169 2170 PetscFunctionBegin; 2171 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2172 PetscFunctionReturn(0); 2173 } 2174 2175 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2176 { 2177 PetscErrorCode ierr; 2178 2179 PetscFunctionBegin; 2180 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2181 PetscFunctionReturn(0); 2182 } 2183 2184 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2185 { 2186 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2187 const PetscScalar *l,*r; 2188 PetscScalar x; 2189 MatScalar *v; 2190 PetscErrorCode ierr; 2191 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz; 2192 const PetscInt *jj; 2193 2194 PetscFunctionBegin; 2195 if (ll) { 2196 /* The local size is used so that VecMPI can be passed to this routine 2197 by MatDiagonalScale_MPIAIJ */ 2198 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2199 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2200 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 2201 v = a->a; 2202 for (i=0; i<m; i++) { 2203 x = l[i]; 2204 M = a->i[i+1] - a->i[i]; 2205 for (j=0; j<M; j++) (*v++) *= x; 2206 } 2207 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 2208 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2209 } 2210 if (rr) { 2211 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2212 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2213 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 2214 v = a->a; jj = a->j; 2215 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2216 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 2217 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2218 } 2219 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2220 PetscFunctionReturn(0); 2221 } 2222 2223 PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2224 { 2225 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2226 PetscErrorCode ierr; 2227 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2228 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2229 const PetscInt *irow,*icol; 2230 PetscInt nrows,ncols; 2231 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2232 MatScalar *a_new,*mat_a; 2233 Mat C; 2234 PetscBool stride; 2235 2236 PetscFunctionBegin; 2237 2238 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2239 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2240 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2241 2242 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2243 if (stride) { 2244 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2245 } else { 2246 first = 0; 2247 step = 0; 2248 } 2249 if (stride && step == 1) { 2250 /* special case of contiguous rows */ 2251 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2252 /* loop over new rows determining lens and starting points */ 2253 for (i=0; i<nrows; i++) { 2254 kstart = ai[irow[i]]; 2255 kend = kstart + ailen[irow[i]]; 2256 starts[i] = kstart; 2257 for (k=kstart; k<kend; k++) { 2258 if (aj[k] >= first) { 2259 starts[i] = k; 2260 break; 2261 } 2262 } 2263 sum = 0; 2264 while (k < kend) { 2265 if (aj[k++] >= first+ncols) break; 2266 sum++; 2267 } 2268 lens[i] = sum; 2269 } 2270 /* create submatrix */ 2271 if (scall == MAT_REUSE_MATRIX) { 2272 PetscInt n_cols,n_rows; 2273 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2274 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2275 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2276 C = *B; 2277 } else { 2278 PetscInt rbs,cbs; 2279 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2280 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2281 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2282 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2283 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2284 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2285 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2286 } 2287 c = (Mat_SeqAIJ*)C->data; 2288 2289 /* loop over rows inserting into submatrix */ 2290 a_new = c->a; 2291 j_new = c->j; 2292 i_new = c->i; 2293 2294 for (i=0; i<nrows; i++) { 2295 ii = starts[i]; 2296 lensi = lens[i]; 2297 for (k=0; k<lensi; k++) { 2298 *j_new++ = aj[ii+k] - first; 2299 } 2300 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2301 a_new += lensi; 2302 i_new[i+1] = i_new[i] + lensi; 2303 c->ilen[i] = lensi; 2304 } 2305 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2306 } else { 2307 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2308 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2309 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2310 for (i=0; i<ncols; i++) { 2311 #if defined(PETSC_USE_DEBUG) 2312 if (icol[i] >= oldcols) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Requesting column beyond largest column icol[%D] %D <= A->cmap->n %D",i,icol[i],oldcols); 2313 #endif 2314 smap[icol[i]] = i+1; 2315 } 2316 2317 /* determine lens of each row */ 2318 for (i=0; i<nrows; i++) { 2319 kstart = ai[irow[i]]; 2320 kend = kstart + a->ilen[irow[i]]; 2321 lens[i] = 0; 2322 for (k=kstart; k<kend; k++) { 2323 if (smap[aj[k]]) { 2324 lens[i]++; 2325 } 2326 } 2327 } 2328 /* Create and fill new matrix */ 2329 if (scall == MAT_REUSE_MATRIX) { 2330 PetscBool equal; 2331 2332 c = (Mat_SeqAIJ*)((*B)->data); 2333 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2334 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2335 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2336 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2337 C = *B; 2338 } else { 2339 PetscInt rbs,cbs; 2340 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2341 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2342 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2343 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2344 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2345 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2346 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2347 } 2348 c = (Mat_SeqAIJ*)(C->data); 2349 for (i=0; i<nrows; i++) { 2350 row = irow[i]; 2351 kstart = ai[row]; 2352 kend = kstart + a->ilen[row]; 2353 mat_i = c->i[i]; 2354 mat_j = c->j + mat_i; 2355 mat_a = c->a + mat_i; 2356 mat_ilen = c->ilen + i; 2357 for (k=kstart; k<kend; k++) { 2358 if ((tcol=smap[a->j[k]])) { 2359 *mat_j++ = tcol - 1; 2360 *mat_a++ = a->a[k]; 2361 (*mat_ilen)++; 2362 2363 } 2364 } 2365 } 2366 /* Free work space */ 2367 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2368 ierr = PetscFree(smap);CHKERRQ(ierr); 2369 ierr = PetscFree(lens);CHKERRQ(ierr); 2370 /* sort */ 2371 for (i = 0; i < nrows; i++) { 2372 PetscInt ilen; 2373 2374 mat_i = c->i[i]; 2375 mat_j = c->j + mat_i; 2376 mat_a = c->a + mat_i; 2377 ilen = c->ilen[i]; 2378 ierr = PetscSortIntWithScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2379 } 2380 } 2381 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2382 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2383 2384 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2385 *B = C; 2386 PetscFunctionReturn(0); 2387 } 2388 2389 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2390 { 2391 PetscErrorCode ierr; 2392 Mat B; 2393 2394 PetscFunctionBegin; 2395 if (scall == MAT_INITIAL_MATRIX) { 2396 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2397 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2398 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2399 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2400 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2401 *subMat = B; 2402 } else { 2403 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2404 } 2405 PetscFunctionReturn(0); 2406 } 2407 2408 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2409 { 2410 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2411 PetscErrorCode ierr; 2412 Mat outA; 2413 PetscBool row_identity,col_identity; 2414 2415 PetscFunctionBegin; 2416 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2417 2418 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2419 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2420 2421 outA = inA; 2422 outA->factortype = MAT_FACTOR_LU; 2423 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2424 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2425 2426 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2427 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2428 2429 a->row = row; 2430 2431 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2432 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2433 2434 a->col = col; 2435 2436 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2437 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2438 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2439 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2440 2441 if (!a->solve_work) { /* this matrix may have been factored before */ 2442 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2443 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2444 } 2445 2446 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2447 if (row_identity && col_identity) { 2448 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2449 } else { 2450 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2451 } 2452 PetscFunctionReturn(0); 2453 } 2454 2455 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2456 { 2457 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2458 PetscScalar oalpha = alpha; 2459 PetscErrorCode ierr; 2460 PetscBLASInt one = 1,bnz; 2461 2462 PetscFunctionBegin; 2463 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2464 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2465 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2466 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2467 PetscFunctionReturn(0); 2468 } 2469 2470 PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *submatj) 2471 { 2472 PetscErrorCode ierr; 2473 PetscInt i; 2474 2475 PetscFunctionBegin; 2476 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2477 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2478 2479 for (i=0; i<submatj->nrqr; ++i) { 2480 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2481 } 2482 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2483 2484 if (submatj->rbuf1) { 2485 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2486 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2487 } 2488 2489 for (i=0; i<submatj->nrqs; ++i) { 2490 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2491 } 2492 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2493 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2494 } 2495 2496 #if defined(PETSC_USE_CTABLE) 2497 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2498 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2499 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2500 #else 2501 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2502 #endif 2503 2504 if (!submatj->allcolumns) { 2505 #if defined(PETSC_USE_CTABLE) 2506 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2507 #else 2508 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2509 #endif 2510 } 2511 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2512 2513 ierr = PetscFree(submatj);CHKERRQ(ierr); 2514 PetscFunctionReturn(0); 2515 } 2516 2517 PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat C) 2518 { 2519 PetscErrorCode ierr; 2520 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2521 Mat_SubSppt *submatj = c->submatis1; 2522 2523 PetscFunctionBegin; 2524 ierr = submatj->destroy(C);CHKERRQ(ierr); 2525 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2526 PetscFunctionReturn(0); 2527 } 2528 2529 PetscErrorCode MatDestroySubMatrices_SeqAIJ(PetscInt n,Mat *mat[]) 2530 { 2531 PetscErrorCode ierr; 2532 PetscInt i; 2533 Mat C; 2534 Mat_SeqAIJ *c; 2535 Mat_SubSppt *submatj; 2536 2537 PetscFunctionBegin; 2538 for (i=0; i<n; i++) { 2539 C = (*mat)[i]; 2540 c = (Mat_SeqAIJ*)C->data; 2541 submatj = c->submatis1; 2542 if (submatj) { 2543 if (--((PetscObject)C)->refct <= 0) { 2544 ierr = (submatj->destroy)(C);CHKERRQ(ierr); 2545 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2546 ierr = PetscLayoutDestroy(&C->rmap);CHKERRQ(ierr); 2547 ierr = PetscLayoutDestroy(&C->cmap);CHKERRQ(ierr); 2548 ierr = PetscHeaderDestroy(&C);CHKERRQ(ierr); 2549 } 2550 } else { 2551 ierr = MatDestroy(&C);CHKERRQ(ierr); 2552 } 2553 } 2554 2555 ierr = PetscFree(*mat);CHKERRQ(ierr); 2556 PetscFunctionReturn(0); 2557 } 2558 2559 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2560 { 2561 PetscErrorCode ierr; 2562 PetscInt i; 2563 2564 PetscFunctionBegin; 2565 if (scall == MAT_INITIAL_MATRIX) { 2566 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2567 } 2568 2569 for (i=0; i<n; i++) { 2570 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2571 } 2572 PetscFunctionReturn(0); 2573 } 2574 2575 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2576 { 2577 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2578 PetscErrorCode ierr; 2579 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2580 const PetscInt *idx; 2581 PetscInt start,end,*ai,*aj; 2582 PetscBT table; 2583 2584 PetscFunctionBegin; 2585 m = A->rmap->n; 2586 ai = a->i; 2587 aj = a->j; 2588 2589 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2590 2591 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2592 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2593 2594 for (i=0; i<is_max; i++) { 2595 /* Initialize the two local arrays */ 2596 isz = 0; 2597 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2598 2599 /* Extract the indices, assume there can be duplicate entries */ 2600 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2601 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2602 2603 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2604 for (j=0; j<n; ++j) { 2605 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2606 } 2607 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2608 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2609 2610 k = 0; 2611 for (j=0; j<ov; j++) { /* for each overlap */ 2612 n = isz; 2613 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2614 row = nidx[k]; 2615 start = ai[row]; 2616 end = ai[row+1]; 2617 for (l = start; l<end; l++) { 2618 val = aj[l]; 2619 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2620 } 2621 } 2622 } 2623 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2624 } 2625 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2626 ierr = PetscFree(nidx);CHKERRQ(ierr); 2627 PetscFunctionReturn(0); 2628 } 2629 2630 /* -------------------------------------------------------------- */ 2631 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2632 { 2633 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2634 PetscErrorCode ierr; 2635 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2636 const PetscInt *row,*col; 2637 PetscInt *cnew,j,*lens; 2638 IS icolp,irowp; 2639 PetscInt *cwork = NULL; 2640 PetscScalar *vwork = NULL; 2641 2642 PetscFunctionBegin; 2643 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2644 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2645 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2646 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2647 2648 /* determine lengths of permuted rows */ 2649 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2650 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2651 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2652 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2653 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2654 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2655 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2656 ierr = PetscFree(lens);CHKERRQ(ierr); 2657 2658 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2659 for (i=0; i<m; i++) { 2660 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2661 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2662 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2663 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2664 } 2665 ierr = PetscFree(cnew);CHKERRQ(ierr); 2666 2667 (*B)->assembled = PETSC_FALSE; 2668 2669 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2670 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2671 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2672 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2673 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2674 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2675 PetscFunctionReturn(0); 2676 } 2677 2678 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2679 { 2680 PetscErrorCode ierr; 2681 2682 PetscFunctionBegin; 2683 /* If the two matrices have the same copy implementation, use fast copy. */ 2684 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2685 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2686 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2687 2688 if (a->i[A->rmap->n] != b->i[B->rmap->n]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different"); 2689 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2690 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 2691 } else { 2692 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2693 } 2694 PetscFunctionReturn(0); 2695 } 2696 2697 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2698 { 2699 PetscErrorCode ierr; 2700 2701 PetscFunctionBegin; 2702 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2703 PetscFunctionReturn(0); 2704 } 2705 2706 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2707 { 2708 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2709 2710 PetscFunctionBegin; 2711 *array = a->a; 2712 PetscFunctionReturn(0); 2713 } 2714 2715 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2716 { 2717 PetscFunctionBegin; 2718 PetscFunctionReturn(0); 2719 } 2720 2721 /* 2722 Computes the number of nonzeros per row needed for preallocation when X and Y 2723 have different nonzero structure. 2724 */ 2725 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2726 { 2727 PetscInt i,j,k,nzx,nzy; 2728 2729 PetscFunctionBegin; 2730 /* Set the number of nonzeros in the new matrix */ 2731 for (i=0; i<m; i++) { 2732 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2733 nzx = xi[i+1] - xi[i]; 2734 nzy = yi[i+1] - yi[i]; 2735 nnz[i] = 0; 2736 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2737 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2738 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2739 nnz[i]++; 2740 } 2741 for (; k<nzy; k++) nnz[i]++; 2742 } 2743 PetscFunctionReturn(0); 2744 } 2745 2746 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2747 { 2748 PetscInt m = Y->rmap->N; 2749 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2750 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2751 PetscErrorCode ierr; 2752 2753 PetscFunctionBegin; 2754 /* Set the number of nonzeros in the new matrix */ 2755 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2756 PetscFunctionReturn(0); 2757 } 2758 2759 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2760 { 2761 PetscErrorCode ierr; 2762 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2763 PetscBLASInt one=1,bnz; 2764 2765 PetscFunctionBegin; 2766 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2767 if (str == SAME_NONZERO_PATTERN) { 2768 PetscScalar alpha = a; 2769 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2770 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2771 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2772 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2773 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2774 } else { 2775 Mat B; 2776 PetscInt *nnz; 2777 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2778 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2779 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2780 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2781 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2782 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2783 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2784 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2785 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2786 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2787 ierr = PetscFree(nnz);CHKERRQ(ierr); 2788 } 2789 PetscFunctionReturn(0); 2790 } 2791 2792 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2793 { 2794 #if defined(PETSC_USE_COMPLEX) 2795 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2796 PetscInt i,nz; 2797 PetscScalar *a; 2798 2799 PetscFunctionBegin; 2800 nz = aij->nz; 2801 a = aij->a; 2802 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2803 #else 2804 PetscFunctionBegin; 2805 #endif 2806 PetscFunctionReturn(0); 2807 } 2808 2809 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2810 { 2811 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2812 PetscErrorCode ierr; 2813 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2814 PetscReal atmp; 2815 PetscScalar *x; 2816 MatScalar *aa; 2817 2818 PetscFunctionBegin; 2819 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2820 aa = a->a; 2821 ai = a->i; 2822 aj = a->j; 2823 2824 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2825 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2826 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2827 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2828 for (i=0; i<m; i++) { 2829 ncols = ai[1] - ai[0]; ai++; 2830 x[i] = 0.0; 2831 for (j=0; j<ncols; j++) { 2832 atmp = PetscAbsScalar(*aa); 2833 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2834 aa++; aj++; 2835 } 2836 } 2837 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2838 PetscFunctionReturn(0); 2839 } 2840 2841 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2842 { 2843 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2844 PetscErrorCode ierr; 2845 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2846 PetscScalar *x; 2847 MatScalar *aa; 2848 2849 PetscFunctionBegin; 2850 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2851 aa = a->a; 2852 ai = a->i; 2853 aj = a->j; 2854 2855 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2856 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2857 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2858 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2859 for (i=0; i<m; i++) { 2860 ncols = ai[1] - ai[0]; ai++; 2861 if (ncols == A->cmap->n) { /* row is dense */ 2862 x[i] = *aa; if (idx) idx[i] = 0; 2863 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2864 x[i] = 0.0; 2865 if (idx) { 2866 idx[i] = 0; /* in case ncols is zero */ 2867 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2868 if (aj[j] > j) { 2869 idx[i] = j; 2870 break; 2871 } 2872 } 2873 } 2874 } 2875 for (j=0; j<ncols; j++) { 2876 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2877 aa++; aj++; 2878 } 2879 } 2880 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2881 PetscFunctionReturn(0); 2882 } 2883 2884 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2885 { 2886 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2887 PetscErrorCode ierr; 2888 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2889 PetscReal atmp; 2890 PetscScalar *x; 2891 MatScalar *aa; 2892 2893 PetscFunctionBegin; 2894 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2895 aa = a->a; 2896 ai = a->i; 2897 aj = a->j; 2898 2899 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2900 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2901 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2902 if (n != A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector, %D vs. %D rows", A->rmap->n, n); 2903 for (i=0; i<m; i++) { 2904 ncols = ai[1] - ai[0]; ai++; 2905 if (ncols) { 2906 /* Get first nonzero */ 2907 for (j = 0; j < ncols; j++) { 2908 atmp = PetscAbsScalar(aa[j]); 2909 if (atmp > 1.0e-12) { 2910 x[i] = atmp; 2911 if (idx) idx[i] = aj[j]; 2912 break; 2913 } 2914 } 2915 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 2916 } else { 2917 x[i] = 0.0; if (idx) idx[i] = 0; 2918 } 2919 for (j = 0; j < ncols; j++) { 2920 atmp = PetscAbsScalar(*aa); 2921 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2922 aa++; aj++; 2923 } 2924 } 2925 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2926 PetscFunctionReturn(0); 2927 } 2928 2929 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2930 { 2931 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2932 PetscErrorCode ierr; 2933 PetscInt i,j,m = A->rmap->n,ncols,n; 2934 const PetscInt *ai,*aj; 2935 PetscScalar *x; 2936 const MatScalar *aa; 2937 2938 PetscFunctionBegin; 2939 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2940 aa = a->a; 2941 ai = a->i; 2942 aj = a->j; 2943 2944 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2945 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2946 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2947 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2948 for (i=0; i<m; i++) { 2949 ncols = ai[1] - ai[0]; ai++; 2950 if (ncols == A->cmap->n) { /* row is dense */ 2951 x[i] = *aa; if (idx) idx[i] = 0; 2952 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2953 x[i] = 0.0; 2954 if (idx) { /* find first implicit 0.0 in the row */ 2955 idx[i] = 0; /* in case ncols is zero */ 2956 for (j=0; j<ncols; j++) { 2957 if (aj[j] > j) { 2958 idx[i] = j; 2959 break; 2960 } 2961 } 2962 } 2963 } 2964 for (j=0; j<ncols; j++) { 2965 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2966 aa++; aj++; 2967 } 2968 } 2969 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2970 PetscFunctionReturn(0); 2971 } 2972 2973 #include <petscblaslapack.h> 2974 #include <petsc/private/kernels/blockinvert.h> 2975 2976 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 2977 { 2978 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 2979 PetscErrorCode ierr; 2980 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 2981 MatScalar *diag,work[25],*v_work; 2982 PetscReal shift = 0.0; 2983 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 2984 2985 PetscFunctionBegin; 2986 allowzeropivot = PetscNot(A->erroriffailure); 2987 if (a->ibdiagvalid) { 2988 if (values) *values = a->ibdiag; 2989 PetscFunctionReturn(0); 2990 } 2991 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 2992 if (!a->ibdiag) { 2993 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 2994 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 2995 } 2996 diag = a->ibdiag; 2997 if (values) *values = a->ibdiag; 2998 /* factor and invert each block */ 2999 switch (bs) { 3000 case 1: 3001 for (i=0; i<mbs; i++) { 3002 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3003 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 3004 if (allowzeropivot) { 3005 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3006 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 3007 A->factorerror_zeropivot_row = i; 3008 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 3009 } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D pivot %g tolerance %g",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON); 3010 } 3011 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3012 } 3013 break; 3014 case 2: 3015 for (i=0; i<mbs; i++) { 3016 ij[0] = 2*i; ij[1] = 2*i + 1; 3017 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3018 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3019 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3020 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3021 diag += 4; 3022 } 3023 break; 3024 case 3: 3025 for (i=0; i<mbs; i++) { 3026 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3027 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3028 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3029 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3030 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3031 diag += 9; 3032 } 3033 break; 3034 case 4: 3035 for (i=0; i<mbs; i++) { 3036 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3037 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3038 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3039 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3040 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3041 diag += 16; 3042 } 3043 break; 3044 case 5: 3045 for (i=0; i<mbs; i++) { 3046 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3047 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3048 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3049 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3050 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3051 diag += 25; 3052 } 3053 break; 3054 case 6: 3055 for (i=0; i<mbs; i++) { 3056 ij[0] = 6*i; ij[1] = 6*i + 1; ij[2] = 6*i + 2; ij[3] = 6*i + 3; ij[4] = 6*i + 4; ij[5] = 6*i + 5; 3057 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3058 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3059 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3060 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3061 diag += 36; 3062 } 3063 break; 3064 case 7: 3065 for (i=0; i<mbs; i++) { 3066 ij[0] = 7*i; ij[1] = 7*i + 1; ij[2] = 7*i + 2; ij[3] = 7*i + 3; ij[4] = 7*i + 4; ij[5] = 7*i + 5; ij[5] = 7*i + 6; 3067 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3068 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3069 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3070 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3071 diag += 49; 3072 } 3073 break; 3074 default: 3075 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3076 for (i=0; i<mbs; i++) { 3077 for (j=0; j<bs; j++) { 3078 IJ[j] = bs*i + j; 3079 } 3080 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3081 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3082 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3083 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3084 diag += bs2; 3085 } 3086 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3087 } 3088 a->ibdiagvalid = PETSC_TRUE; 3089 PetscFunctionReturn(0); 3090 } 3091 3092 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3093 { 3094 PetscErrorCode ierr; 3095 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3096 PetscScalar a; 3097 PetscInt m,n,i,j,col; 3098 3099 PetscFunctionBegin; 3100 if (!x->assembled) { 3101 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3102 for (i=0; i<m; i++) { 3103 for (j=0; j<aij->imax[i]; j++) { 3104 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3105 col = (PetscInt)(n*PetscRealPart(a)); 3106 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3107 } 3108 } 3109 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3110 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3111 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3112 PetscFunctionReturn(0); 3113 } 3114 3115 PetscErrorCode MatShift_SeqAIJ(Mat Y,PetscScalar a) 3116 { 3117 PetscErrorCode ierr; 3118 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)Y->data; 3119 3120 PetscFunctionBegin; 3121 if (!Y->preallocated || !aij->nz) { 3122 ierr = MatSeqAIJSetPreallocation(Y,1,NULL);CHKERRQ(ierr); 3123 } 3124 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 3125 PetscFunctionReturn(0); 3126 } 3127 3128 /* -------------------------------------------------------------------*/ 3129 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3130 MatGetRow_SeqAIJ, 3131 MatRestoreRow_SeqAIJ, 3132 MatMult_SeqAIJ, 3133 /* 4*/ MatMultAdd_SeqAIJ, 3134 MatMultTranspose_SeqAIJ, 3135 MatMultTransposeAdd_SeqAIJ, 3136 0, 3137 0, 3138 0, 3139 /* 10*/ 0, 3140 MatLUFactor_SeqAIJ, 3141 0, 3142 MatSOR_SeqAIJ, 3143 MatTranspose_SeqAIJ, 3144 /*1 5*/ MatGetInfo_SeqAIJ, 3145 MatEqual_SeqAIJ, 3146 MatGetDiagonal_SeqAIJ, 3147 MatDiagonalScale_SeqAIJ, 3148 MatNorm_SeqAIJ, 3149 /* 20*/ 0, 3150 MatAssemblyEnd_SeqAIJ, 3151 MatSetOption_SeqAIJ, 3152 MatZeroEntries_SeqAIJ, 3153 /* 24*/ MatZeroRows_SeqAIJ, 3154 0, 3155 0, 3156 0, 3157 0, 3158 /* 29*/ MatSetUp_SeqAIJ, 3159 0, 3160 0, 3161 0, 3162 0, 3163 /* 34*/ MatDuplicate_SeqAIJ, 3164 0, 3165 0, 3166 MatILUFactor_SeqAIJ, 3167 0, 3168 /* 39*/ MatAXPY_SeqAIJ, 3169 MatCreateSubMatrices_SeqAIJ, 3170 MatIncreaseOverlap_SeqAIJ, 3171 MatGetValues_SeqAIJ, 3172 MatCopy_SeqAIJ, 3173 /* 44*/ MatGetRowMax_SeqAIJ, 3174 MatScale_SeqAIJ, 3175 MatShift_SeqAIJ, 3176 MatDiagonalSet_SeqAIJ, 3177 MatZeroRowsColumns_SeqAIJ, 3178 /* 49*/ MatSetRandom_SeqAIJ, 3179 MatGetRowIJ_SeqAIJ, 3180 MatRestoreRowIJ_SeqAIJ, 3181 MatGetColumnIJ_SeqAIJ, 3182 MatRestoreColumnIJ_SeqAIJ, 3183 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3184 0, 3185 0, 3186 MatPermute_SeqAIJ, 3187 0, 3188 /* 59*/ 0, 3189 MatDestroy_SeqAIJ, 3190 MatView_SeqAIJ, 3191 0, 3192 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3193 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3194 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3195 0, 3196 0, 3197 0, 3198 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3199 MatGetRowMinAbs_SeqAIJ, 3200 0, 3201 0, 3202 0, 3203 /* 74*/ 0, 3204 MatFDColoringApply_AIJ, 3205 0, 3206 0, 3207 0, 3208 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3209 0, 3210 0, 3211 0, 3212 MatLoad_SeqAIJ, 3213 /* 84*/ MatIsSymmetric_SeqAIJ, 3214 MatIsHermitian_SeqAIJ, 3215 0, 3216 0, 3217 0, 3218 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3219 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3220 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3221 MatPtAP_SeqAIJ_SeqAIJ, 3222 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3223 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3224 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3225 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3226 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3227 0, 3228 /* 99*/ 0, 3229 0, 3230 0, 3231 MatConjugate_SeqAIJ, 3232 0, 3233 /*104*/ MatSetValuesRow_SeqAIJ, 3234 MatRealPart_SeqAIJ, 3235 MatImaginaryPart_SeqAIJ, 3236 0, 3237 0, 3238 /*109*/ MatMatSolve_SeqAIJ, 3239 0, 3240 MatGetRowMin_SeqAIJ, 3241 0, 3242 MatMissingDiagonal_SeqAIJ, 3243 /*114*/ 0, 3244 0, 3245 0, 3246 0, 3247 0, 3248 /*119*/ 0, 3249 0, 3250 0, 3251 0, 3252 MatGetMultiProcBlock_SeqAIJ, 3253 /*124*/ MatFindNonzeroRows_SeqAIJ, 3254 MatGetColumnNorms_SeqAIJ, 3255 MatInvertBlockDiagonal_SeqAIJ, 3256 0, 3257 0, 3258 /*129*/ 0, 3259 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3260 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3261 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3262 MatTransposeColoringCreate_SeqAIJ, 3263 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3264 MatTransColoringApplyDenToSp_SeqAIJ, 3265 MatRARt_SeqAIJ_SeqAIJ, 3266 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3267 MatRARtNumeric_SeqAIJ_SeqAIJ, 3268 /*139*/0, 3269 0, 3270 0, 3271 MatFDColoringSetUp_SeqXAIJ, 3272 MatFindOffBlockDiagonalEntries_SeqAIJ, 3273 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ, 3274 MatDestroySubMatrices_SeqAIJ 3275 }; 3276 3277 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3278 { 3279 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3280 PetscInt i,nz,n; 3281 3282 PetscFunctionBegin; 3283 nz = aij->maxnz; 3284 n = mat->rmap->n; 3285 for (i=0; i<nz; i++) { 3286 aij->j[i] = indices[i]; 3287 } 3288 aij->nz = nz; 3289 for (i=0; i<n; i++) { 3290 aij->ilen[i] = aij->imax[i]; 3291 } 3292 PetscFunctionReturn(0); 3293 } 3294 3295 /*@ 3296 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3297 in the matrix. 3298 3299 Input Parameters: 3300 + mat - the SeqAIJ matrix 3301 - indices - the column indices 3302 3303 Level: advanced 3304 3305 Notes: 3306 This can be called if you have precomputed the nonzero structure of the 3307 matrix and want to provide it to the matrix object to improve the performance 3308 of the MatSetValues() operation. 3309 3310 You MUST have set the correct numbers of nonzeros per row in the call to 3311 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3312 3313 MUST be called before any calls to MatSetValues(); 3314 3315 The indices should start with zero, not one. 3316 3317 @*/ 3318 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3319 { 3320 PetscErrorCode ierr; 3321 3322 PetscFunctionBegin; 3323 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3324 PetscValidPointer(indices,2); 3325 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3326 PetscFunctionReturn(0); 3327 } 3328 3329 /* ----------------------------------------------------------------------------------------*/ 3330 3331 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3332 { 3333 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3334 PetscErrorCode ierr; 3335 size_t nz = aij->i[mat->rmap->n]; 3336 3337 PetscFunctionBegin; 3338 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3339 3340 /* allocate space for values if not already there */ 3341 if (!aij->saved_values) { 3342 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3343 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3344 } 3345 3346 /* copy values over */ 3347 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3348 PetscFunctionReturn(0); 3349 } 3350 3351 /*@ 3352 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3353 example, reuse of the linear part of a Jacobian, while recomputing the 3354 nonlinear portion. 3355 3356 Collect on Mat 3357 3358 Input Parameters: 3359 . mat - the matrix (currently only AIJ matrices support this option) 3360 3361 Level: advanced 3362 3363 Common Usage, with SNESSolve(): 3364 $ Create Jacobian matrix 3365 $ Set linear terms into matrix 3366 $ Apply boundary conditions to matrix, at this time matrix must have 3367 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3368 $ boundary conditions again will not change the nonzero structure 3369 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3370 $ ierr = MatStoreValues(mat); 3371 $ Call SNESSetJacobian() with matrix 3372 $ In your Jacobian routine 3373 $ ierr = MatRetrieveValues(mat); 3374 $ Set nonlinear terms in matrix 3375 3376 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3377 $ // build linear portion of Jacobian 3378 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3379 $ ierr = MatStoreValues(mat); 3380 $ loop over nonlinear iterations 3381 $ ierr = MatRetrieveValues(mat); 3382 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3383 $ // call MatAssemblyBegin/End() on matrix 3384 $ Solve linear system with Jacobian 3385 $ endloop 3386 3387 Notes: 3388 Matrix must already be assemblied before calling this routine 3389 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3390 calling this routine. 3391 3392 When this is called multiple times it overwrites the previous set of stored values 3393 and does not allocated additional space. 3394 3395 .seealso: MatRetrieveValues() 3396 3397 @*/ 3398 PetscErrorCode MatStoreValues(Mat mat) 3399 { 3400 PetscErrorCode ierr; 3401 3402 PetscFunctionBegin; 3403 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3404 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3405 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3406 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3407 PetscFunctionReturn(0); 3408 } 3409 3410 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3411 { 3412 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3413 PetscErrorCode ierr; 3414 PetscInt nz = aij->i[mat->rmap->n]; 3415 3416 PetscFunctionBegin; 3417 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3418 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3419 /* copy values over */ 3420 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3421 PetscFunctionReturn(0); 3422 } 3423 3424 /*@ 3425 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3426 example, reuse of the linear part of a Jacobian, while recomputing the 3427 nonlinear portion. 3428 3429 Collect on Mat 3430 3431 Input Parameters: 3432 . mat - the matrix (currently only AIJ matrices support this option) 3433 3434 Level: advanced 3435 3436 .seealso: MatStoreValues() 3437 3438 @*/ 3439 PetscErrorCode MatRetrieveValues(Mat mat) 3440 { 3441 PetscErrorCode ierr; 3442 3443 PetscFunctionBegin; 3444 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3445 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3446 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3447 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3448 PetscFunctionReturn(0); 3449 } 3450 3451 3452 /* --------------------------------------------------------------------------------*/ 3453 /*@C 3454 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3455 (the default parallel PETSc format). For good matrix assembly performance 3456 the user should preallocate the matrix storage by setting the parameter nz 3457 (or the array nnz). By setting these parameters accurately, performance 3458 during matrix assembly can be increased by more than a factor of 50. 3459 3460 Collective on MPI_Comm 3461 3462 Input Parameters: 3463 + comm - MPI communicator, set to PETSC_COMM_SELF 3464 . m - number of rows 3465 . n - number of columns 3466 . nz - number of nonzeros per row (same for all rows) 3467 - nnz - array containing the number of nonzeros in the various rows 3468 (possibly different for each row) or NULL 3469 3470 Output Parameter: 3471 . A - the matrix 3472 3473 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3474 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3475 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3476 3477 Notes: 3478 If nnz is given then nz is ignored 3479 3480 The AIJ format (also called the Yale sparse matrix format or 3481 compressed row storage), is fully compatible with standard Fortran 77 3482 storage. That is, the stored row and column indices can begin at 3483 either one (as in Fortran) or zero. See the users' manual for details. 3484 3485 Specify the preallocated storage with either nz or nnz (not both). 3486 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3487 allocation. For large problems you MUST preallocate memory or you 3488 will get TERRIBLE performance, see the users' manual chapter on matrices. 3489 3490 By default, this format uses inodes (identical nodes) when possible, to 3491 improve numerical efficiency of matrix-vector products and solves. We 3492 search for consecutive rows with the same nonzero structure, thereby 3493 reusing matrix information to achieve increased efficiency. 3494 3495 Options Database Keys: 3496 + -mat_no_inode - Do not use inodes 3497 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3498 3499 Level: intermediate 3500 3501 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3502 3503 @*/ 3504 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3505 { 3506 PetscErrorCode ierr; 3507 3508 PetscFunctionBegin; 3509 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3510 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3511 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3512 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3513 PetscFunctionReturn(0); 3514 } 3515 3516 /*@C 3517 MatSeqAIJSetPreallocation - For good matrix assembly performance 3518 the user should preallocate the matrix storage by setting the parameter nz 3519 (or the array nnz). By setting these parameters accurately, performance 3520 during matrix assembly can be increased by more than a factor of 50. 3521 3522 Collective on MPI_Comm 3523 3524 Input Parameters: 3525 + B - The matrix 3526 . nz - number of nonzeros per row (same for all rows) 3527 - nnz - array containing the number of nonzeros in the various rows 3528 (possibly different for each row) or NULL 3529 3530 Notes: 3531 If nnz is given then nz is ignored 3532 3533 The AIJ format (also called the Yale sparse matrix format or 3534 compressed row storage), is fully compatible with standard Fortran 77 3535 storage. That is, the stored row and column indices can begin at 3536 either one (as in Fortran) or zero. See the users' manual for details. 3537 3538 Specify the preallocated storage with either nz or nnz (not both). 3539 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3540 allocation. For large problems you MUST preallocate memory or you 3541 will get TERRIBLE performance, see the users' manual chapter on matrices. 3542 3543 You can call MatGetInfo() to get information on how effective the preallocation was; 3544 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3545 You can also run with the option -info and look for messages with the string 3546 malloc in them to see if additional memory allocation was needed. 3547 3548 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3549 entries or columns indices 3550 3551 By default, this format uses inodes (identical nodes) when possible, to 3552 improve numerical efficiency of matrix-vector products and solves. We 3553 search for consecutive rows with the same nonzero structure, thereby 3554 reusing matrix information to achieve increased efficiency. 3555 3556 Options Database Keys: 3557 + -mat_no_inode - Do not use inodes 3558 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3559 - -mat_aij_oneindex - Internally use indexing starting at 1 3560 rather than 0. Note that when calling MatSetValues(), 3561 the user still MUST index entries starting at 0! 3562 3563 Level: intermediate 3564 3565 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3566 3567 @*/ 3568 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3569 { 3570 PetscErrorCode ierr; 3571 3572 PetscFunctionBegin; 3573 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3574 PetscValidType(B,1); 3575 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3576 PetscFunctionReturn(0); 3577 } 3578 3579 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3580 { 3581 Mat_SeqAIJ *b; 3582 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3583 PetscErrorCode ierr; 3584 PetscInt i; 3585 3586 PetscFunctionBegin; 3587 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3588 if (nz == MAT_SKIP_ALLOCATION) { 3589 skipallocation = PETSC_TRUE; 3590 nz = 0; 3591 } 3592 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3593 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3594 3595 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3596 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3597 if (nnz) { 3598 for (i=0; i<B->rmap->n; i++) { 3599 if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]); 3600 if (nnz[i] > B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than row length: local row %D value %d rowlength %D",i,nnz[i],B->cmap->n); 3601 } 3602 } 3603 3604 B->preallocated = PETSC_TRUE; 3605 3606 b = (Mat_SeqAIJ*)B->data; 3607 3608 if (!skipallocation) { 3609 if (!b->imax) { 3610 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3611 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3612 } 3613 if (!nnz) { 3614 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3615 else if (nz < 0) nz = 1; 3616 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3617 nz = nz*B->rmap->n; 3618 } else { 3619 nz = 0; 3620 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3621 } 3622 /* b->ilen will count nonzeros in each row so far. */ 3623 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3624 3625 /* allocate the matrix space */ 3626 /* FIXME: should B's old memory be unlogged? */ 3627 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3628 if (B->structure_only) { 3629 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3630 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3631 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3632 } else { 3633 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3634 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3635 } 3636 b->i[0] = 0; 3637 for (i=1; i<B->rmap->n+1; i++) { 3638 b->i[i] = b->i[i-1] + b->imax[i-1]; 3639 } 3640 if (B->structure_only) { 3641 b->singlemalloc = PETSC_FALSE; 3642 b->free_a = PETSC_FALSE; 3643 } else { 3644 b->singlemalloc = PETSC_TRUE; 3645 b->free_a = PETSC_TRUE; 3646 } 3647 b->free_ij = PETSC_TRUE; 3648 } else { 3649 b->free_a = PETSC_FALSE; 3650 b->free_ij = PETSC_FALSE; 3651 } 3652 3653 b->nz = 0; 3654 b->maxnz = nz; 3655 B->info.nz_unneeded = (double)b->maxnz; 3656 if (realalloc) { 3657 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3658 } 3659 B->was_assembled = PETSC_FALSE; 3660 B->assembled = PETSC_FALSE; 3661 PetscFunctionReturn(0); 3662 } 3663 3664 /*@ 3665 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3666 3667 Input Parameters: 3668 + B - the matrix 3669 . i - the indices into j for the start of each row (starts with zero) 3670 . j - the column indices for each row (starts with zero) these must be sorted for each row 3671 - v - optional values in the matrix 3672 3673 Level: developer 3674 3675 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3676 3677 .keywords: matrix, aij, compressed row, sparse, sequential 3678 3679 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3680 @*/ 3681 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3682 { 3683 PetscErrorCode ierr; 3684 3685 PetscFunctionBegin; 3686 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3687 PetscValidType(B,1); 3688 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3689 PetscFunctionReturn(0); 3690 } 3691 3692 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3693 { 3694 PetscInt i; 3695 PetscInt m,n; 3696 PetscInt nz; 3697 PetscInt *nnz, nz_max = 0; 3698 PetscScalar *values; 3699 PetscErrorCode ierr; 3700 3701 PetscFunctionBegin; 3702 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3703 3704 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3705 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3706 3707 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3708 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 3709 for (i = 0; i < m; i++) { 3710 nz = Ii[i+1]- Ii[i]; 3711 nz_max = PetscMax(nz_max, nz); 3712 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3713 nnz[i] = nz; 3714 } 3715 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3716 ierr = PetscFree(nnz);CHKERRQ(ierr); 3717 3718 if (v) { 3719 values = (PetscScalar*) v; 3720 } else { 3721 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3722 } 3723 3724 for (i = 0; i < m; i++) { 3725 nz = Ii[i+1] - Ii[i]; 3726 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3727 } 3728 3729 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3730 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3731 3732 if (!v) { 3733 ierr = PetscFree(values);CHKERRQ(ierr); 3734 } 3735 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3736 PetscFunctionReturn(0); 3737 } 3738 3739 #include <../src/mat/impls/dense/seq/dense.h> 3740 #include <petsc/private/kernels/petscaxpy.h> 3741 3742 /* 3743 Computes (B'*A')' since computing B*A directly is untenable 3744 3745 n p p 3746 ( ) ( ) ( ) 3747 m ( A ) * n ( B ) = m ( C ) 3748 ( ) ( ) ( ) 3749 3750 */ 3751 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3752 { 3753 PetscErrorCode ierr; 3754 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3755 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3756 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3757 PetscInt i,n,m,q,p; 3758 const PetscInt *ii,*idx; 3759 const PetscScalar *b,*a,*a_q; 3760 PetscScalar *c,*c_q; 3761 3762 PetscFunctionBegin; 3763 m = A->rmap->n; 3764 n = A->cmap->n; 3765 p = B->cmap->n; 3766 a = sub_a->v; 3767 b = sub_b->a; 3768 c = sub_c->v; 3769 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3770 3771 ii = sub_b->i; 3772 idx = sub_b->j; 3773 for (i=0; i<n; i++) { 3774 q = ii[i+1] - ii[i]; 3775 while (q-->0) { 3776 c_q = c + m*(*idx); 3777 a_q = a + m*i; 3778 PetscKernelAXPY(c_q,*b,a_q,m); 3779 idx++; 3780 b++; 3781 } 3782 } 3783 PetscFunctionReturn(0); 3784 } 3785 3786 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3787 { 3788 PetscErrorCode ierr; 3789 PetscInt m=A->rmap->n,n=B->cmap->n; 3790 Mat Cmat; 3791 3792 PetscFunctionBegin; 3793 if (A->cmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->cmap->n %D != B->rmap->n %D\n",A->cmap->n,B->rmap->n); 3794 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3795 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3796 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3797 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3798 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3799 3800 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3801 3802 *C = Cmat; 3803 PetscFunctionReturn(0); 3804 } 3805 3806 /* ----------------------------------------------------------------*/ 3807 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3808 { 3809 PetscErrorCode ierr; 3810 3811 PetscFunctionBegin; 3812 if (scall == MAT_INITIAL_MATRIX) { 3813 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3814 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3815 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3816 } 3817 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3818 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3819 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3820 PetscFunctionReturn(0); 3821 } 3822 3823 3824 /*MC 3825 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3826 based on compressed sparse row format. 3827 3828 Options Database Keys: 3829 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3830 3831 Level: beginner 3832 3833 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3834 M*/ 3835 3836 /*MC 3837 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3838 3839 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3840 and MATMPIAIJ otherwise. As a result, for single process communicators, 3841 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3842 for communicators controlling multiple processes. It is recommended that you call both of 3843 the above preallocation routines for simplicity. 3844 3845 Options Database Keys: 3846 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3847 3848 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when 3849 enough exist. 3850 3851 Level: beginner 3852 3853 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3854 M*/ 3855 3856 /*MC 3857 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3858 3859 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3860 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3861 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3862 for communicators controlling multiple processes. It is recommended that you call both of 3863 the above preallocation routines for simplicity. 3864 3865 Options Database Keys: 3866 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3867 3868 Level: beginner 3869 3870 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3871 M*/ 3872 3873 /*@C 3874 MatSeqAIJGetArray - gives access to the array where the data for a MATSEQAIJ matrix is stored 3875 3876 Not Collective 3877 3878 Input Parameter: 3879 . mat - a MATSEQAIJ matrix 3880 3881 Output Parameter: 3882 . array - pointer to the data 3883 3884 Level: intermediate 3885 3886 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3887 @*/ 3888 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 3889 { 3890 PetscErrorCode ierr; 3891 3892 PetscFunctionBegin; 3893 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3894 PetscFunctionReturn(0); 3895 } 3896 3897 /*@C 3898 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 3899 3900 Not Collective 3901 3902 Input Parameter: 3903 . mat - a MATSEQAIJ matrix 3904 3905 Output Parameter: 3906 . nz - the maximum number of nonzeros in any row 3907 3908 Level: intermediate 3909 3910 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3911 @*/ 3912 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 3913 { 3914 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 3915 3916 PetscFunctionBegin; 3917 *nz = aij->rmax; 3918 PetscFunctionReturn(0); 3919 } 3920 3921 /*@C 3922 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 3923 3924 Not Collective 3925 3926 Input Parameters: 3927 . mat - a MATSEQAIJ matrix 3928 . array - pointer to the data 3929 3930 Level: intermediate 3931 3932 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 3933 @*/ 3934 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 3935 { 3936 PetscErrorCode ierr; 3937 3938 PetscFunctionBegin; 3939 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3940 PetscFunctionReturn(0); 3941 } 3942 3943 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 3944 { 3945 Mat_SeqAIJ *b; 3946 PetscErrorCode ierr; 3947 PetscMPIInt size; 3948 3949 PetscFunctionBegin; 3950 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 3951 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3952 3953 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3954 3955 B->data = (void*)b; 3956 3957 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3958 3959 b->row = 0; 3960 b->col = 0; 3961 b->icol = 0; 3962 b->reallocs = 0; 3963 b->ignorezeroentries = PETSC_FALSE; 3964 b->roworiented = PETSC_TRUE; 3965 b->nonew = 0; 3966 b->diag = 0; 3967 b->solve_work = 0; 3968 B->spptr = 0; 3969 b->saved_values = 0; 3970 b->idiag = 0; 3971 b->mdiag = 0; 3972 b->ssor_work = 0; 3973 b->omega = 1.0; 3974 b->fshift = 0.0; 3975 b->idiagvalid = PETSC_FALSE; 3976 b->ibdiagvalid = PETSC_FALSE; 3977 b->keepnonzeropattern = PETSC_FALSE; 3978 3979 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3980 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 3981 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 3982 3983 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3984 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 3985 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 3986 #endif 3987 3988 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 3989 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 3990 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 3991 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 3992 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 3993 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 3994 #if defined(PETSC_HAVE_MKL_SPARSE) 3995 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijmkl_C",MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 3996 #endif 3997 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 3998 #if defined(PETSC_HAVE_ELEMENTAL) 3999 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4000 #endif 4001 #if defined(PETSC_HAVE_HYPRE) 4002 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4003 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4004 #endif 4005 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4006 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4007 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4008 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4009 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4010 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4011 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4012 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4013 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4014 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4015 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4016 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4017 PetscFunctionReturn(0); 4018 } 4019 4020 /* 4021 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4022 */ 4023 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4024 { 4025 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4026 PetscErrorCode ierr; 4027 PetscInt i,m = A->rmap->n; 4028 4029 PetscFunctionBegin; 4030 c = (Mat_SeqAIJ*)C->data; 4031 4032 C->factortype = A->factortype; 4033 c->row = 0; 4034 c->col = 0; 4035 c->icol = 0; 4036 c->reallocs = 0; 4037 4038 C->assembled = PETSC_TRUE; 4039 4040 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4041 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4042 4043 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4044 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4045 for (i=0; i<m; i++) { 4046 c->imax[i] = a->imax[i]; 4047 c->ilen[i] = a->ilen[i]; 4048 } 4049 4050 /* allocate the matrix space */ 4051 if (mallocmatspace) { 4052 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4053 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4054 4055 c->singlemalloc = PETSC_TRUE; 4056 4057 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4058 if (m > 0) { 4059 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4060 if (cpvalues == MAT_COPY_VALUES) { 4061 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4062 } else { 4063 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4064 } 4065 } 4066 } 4067 4068 c->ignorezeroentries = a->ignorezeroentries; 4069 c->roworiented = a->roworiented; 4070 c->nonew = a->nonew; 4071 if (a->diag) { 4072 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4073 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4074 for (i=0; i<m; i++) { 4075 c->diag[i] = a->diag[i]; 4076 } 4077 } else c->diag = 0; 4078 4079 c->solve_work = 0; 4080 c->saved_values = 0; 4081 c->idiag = 0; 4082 c->ssor_work = 0; 4083 c->keepnonzeropattern = a->keepnonzeropattern; 4084 c->free_a = PETSC_TRUE; 4085 c->free_ij = PETSC_TRUE; 4086 4087 c->rmax = a->rmax; 4088 c->nz = a->nz; 4089 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4090 C->preallocated = PETSC_TRUE; 4091 4092 c->compressedrow.use = a->compressedrow.use; 4093 c->compressedrow.nrows = a->compressedrow.nrows; 4094 if (a->compressedrow.use) { 4095 i = a->compressedrow.nrows; 4096 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4097 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4098 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4099 } else { 4100 c->compressedrow.use = PETSC_FALSE; 4101 c->compressedrow.i = NULL; 4102 c->compressedrow.rindex = NULL; 4103 } 4104 c->nonzerorowcnt = a->nonzerorowcnt; 4105 C->nonzerostate = A->nonzerostate; 4106 4107 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4108 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4109 PetscFunctionReturn(0); 4110 } 4111 4112 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4113 { 4114 PetscErrorCode ierr; 4115 4116 PetscFunctionBegin; 4117 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4118 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4119 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4120 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4121 } 4122 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4123 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4124 PetscFunctionReturn(0); 4125 } 4126 4127 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4128 { 4129 Mat_SeqAIJ *a; 4130 PetscErrorCode ierr; 4131 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4132 int fd; 4133 PetscMPIInt size; 4134 MPI_Comm comm; 4135 PetscInt bs = newMat->rmap->bs; 4136 4137 PetscFunctionBegin; 4138 /* force binary viewer to load .info file if it has not yet done so */ 4139 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4140 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4141 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4142 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4143 4144 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4145 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4146 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4147 if (bs < 0) bs = 1; 4148 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4149 4150 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4151 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4152 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4153 M = header[1]; N = header[2]; nz = header[3]; 4154 4155 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4156 4157 /* read in row lengths */ 4158 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4159 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4160 4161 /* check if sum of rowlengths is same as nz */ 4162 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4163 if (sum != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_READ,"Inconsistant matrix data in file. no-nonzeros = %dD, sum-row-lengths = %D\n",nz,sum); 4164 4165 /* set global size if not set already*/ 4166 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4167 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4168 } else { 4169 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4170 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4171 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4172 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4173 } 4174 if (M != rows || N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different length (%D, %D) than the input matrix (%D, %D)",M,N,rows,cols); 4175 } 4176 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4177 a = (Mat_SeqAIJ*)newMat->data; 4178 4179 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4180 4181 /* read in nonzero values */ 4182 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4183 4184 /* set matrix "i" values */ 4185 a->i[0] = 0; 4186 for (i=1; i<= M; i++) { 4187 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4188 a->ilen[i-1] = rowlengths[i-1]; 4189 } 4190 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4191 4192 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4193 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4194 PetscFunctionReturn(0); 4195 } 4196 4197 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4198 { 4199 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4200 PetscErrorCode ierr; 4201 #if defined(PETSC_USE_COMPLEX) 4202 PetscInt k; 4203 #endif 4204 4205 PetscFunctionBegin; 4206 /* If the matrix dimensions are not equal,or no of nonzeros */ 4207 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4208 *flg = PETSC_FALSE; 4209 PetscFunctionReturn(0); 4210 } 4211 4212 /* if the a->i are the same */ 4213 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4214 if (!*flg) PetscFunctionReturn(0); 4215 4216 /* if a->j are the same */ 4217 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4218 if (!*flg) PetscFunctionReturn(0); 4219 4220 /* if a->a are the same */ 4221 #if defined(PETSC_USE_COMPLEX) 4222 for (k=0; k<a->nz; k++) { 4223 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4224 *flg = PETSC_FALSE; 4225 PetscFunctionReturn(0); 4226 } 4227 } 4228 #else 4229 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4230 #endif 4231 PetscFunctionReturn(0); 4232 } 4233 4234 /*@ 4235 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4236 provided by the user. 4237 4238 Collective on MPI_Comm 4239 4240 Input Parameters: 4241 + comm - must be an MPI communicator of size 1 4242 . m - number of rows 4243 . n - number of columns 4244 . i - row indices 4245 . j - column indices 4246 - a - matrix values 4247 4248 Output Parameter: 4249 . mat - the matrix 4250 4251 Level: intermediate 4252 4253 Notes: 4254 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4255 once the matrix is destroyed and not before 4256 4257 You cannot set new nonzero locations into this matrix, that will generate an error. 4258 4259 The i and j indices are 0 based 4260 4261 The format which is used for the sparse matrix input, is equivalent to a 4262 row-major ordering.. i.e for the following matrix, the input data expected is 4263 as shown 4264 4265 $ 1 0 0 4266 $ 2 0 3 4267 $ 4 5 6 4268 $ 4269 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4270 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4271 $ v = {1,2,3,4,5,6} [size = 6] 4272 4273 4274 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4275 4276 @*/ 4277 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4278 { 4279 PetscErrorCode ierr; 4280 PetscInt ii; 4281 Mat_SeqAIJ *aij; 4282 #if defined(PETSC_USE_DEBUG) 4283 PetscInt jj; 4284 #endif 4285 4286 PetscFunctionBegin; 4287 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4288 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4289 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4290 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4291 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4292 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4293 aij = (Mat_SeqAIJ*)(*mat)->data; 4294 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4295 4296 aij->i = i; 4297 aij->j = j; 4298 aij->a = a; 4299 aij->singlemalloc = PETSC_FALSE; 4300 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4301 aij->free_a = PETSC_FALSE; 4302 aij->free_ij = PETSC_FALSE; 4303 4304 for (ii=0; ii<m; ii++) { 4305 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4306 #if defined(PETSC_USE_DEBUG) 4307 if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %D length = %D",ii,i[ii+1] - i[ii]); 4308 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4309 if (j[jj] < j[jj-1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual colum %D) in row %D is not sorted",jj-i[ii],j[jj],ii); 4310 if (j[jj] == j[jj]-1) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual colum %D) in row %D is identical to previous entry",jj-i[ii],j[jj],ii); 4311 } 4312 #endif 4313 } 4314 #if defined(PETSC_USE_DEBUG) 4315 for (ii=0; ii<aij->i[m]; ii++) { 4316 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4317 if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %D index = %D",ii,j[ii]); 4318 } 4319 #endif 4320 4321 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4322 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4323 PetscFunctionReturn(0); 4324 } 4325 /*@C 4326 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4327 provided by the user. 4328 4329 Collective on MPI_Comm 4330 4331 Input Parameters: 4332 + comm - must be an MPI communicator of size 1 4333 . m - number of rows 4334 . n - number of columns 4335 . i - row indices 4336 . j - column indices 4337 . a - matrix values 4338 . nz - number of nonzeros 4339 - idx - 0 or 1 based 4340 4341 Output Parameter: 4342 . mat - the matrix 4343 4344 Level: intermediate 4345 4346 Notes: 4347 The i and j indices are 0 based 4348 4349 The format which is used for the sparse matrix input, is equivalent to a 4350 row-major ordering.. i.e for the following matrix, the input data expected is 4351 as shown: 4352 4353 1 0 0 4354 2 0 3 4355 4 5 6 4356 4357 i = {0,1,1,2,2,2} 4358 j = {0,0,2,0,1,2} 4359 v = {1,2,3,4,5,6} 4360 4361 4362 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4363 4364 @*/ 4365 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4366 { 4367 PetscErrorCode ierr; 4368 PetscInt ii, *nnz, one = 1,row,col; 4369 4370 4371 PetscFunctionBegin; 4372 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4373 for (ii = 0; ii < nz; ii++) { 4374 nnz[i[ii] - !!idx] += 1; 4375 } 4376 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4377 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4378 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4379 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4380 for (ii = 0; ii < nz; ii++) { 4381 if (idx) { 4382 row = i[ii] - 1; 4383 col = j[ii] - 1; 4384 } else { 4385 row = i[ii]; 4386 col = j[ii]; 4387 } 4388 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4389 } 4390 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4391 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4392 ierr = PetscFree(nnz);CHKERRQ(ierr); 4393 PetscFunctionReturn(0); 4394 } 4395 4396 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4397 { 4398 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4399 PetscErrorCode ierr; 4400 4401 PetscFunctionBegin; 4402 a->idiagvalid = PETSC_FALSE; 4403 a->ibdiagvalid = PETSC_FALSE; 4404 4405 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4406 PetscFunctionReturn(0); 4407 } 4408 4409 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4410 { 4411 PetscErrorCode ierr; 4412 PetscMPIInt size; 4413 4414 PetscFunctionBegin; 4415 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4416 if (size == 1) { 4417 if (scall == MAT_INITIAL_MATRIX) { 4418 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4419 } else { 4420 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4421 } 4422 } else { 4423 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4424 } 4425 PetscFunctionReturn(0); 4426 } 4427 4428 /* 4429 Permute A into C's *local* index space using rowemb,colemb. 4430 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4431 of [0,m), colemb is in [0,n). 4432 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4433 */ 4434 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4435 { 4436 /* If making this function public, change the error returned in this function away from _PLIB. */ 4437 PetscErrorCode ierr; 4438 Mat_SeqAIJ *Baij; 4439 PetscBool seqaij; 4440 PetscInt m,n,*nz,i,j,count; 4441 PetscScalar v; 4442 const PetscInt *rowindices,*colindices; 4443 4444 PetscFunctionBegin; 4445 if (!B) PetscFunctionReturn(0); 4446 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4447 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4448 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4449 if (rowemb) { 4450 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4451 if (m != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Row IS of size %D is incompatible with matrix row size %D",m,B->rmap->n); 4452 } else { 4453 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4454 } 4455 if (colemb) { 4456 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4457 if (n != B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Diag col IS of size %D is incompatible with input matrix col size %D",n,B->cmap->n); 4458 } else { 4459 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4460 } 4461 4462 Baij = (Mat_SeqAIJ*)(B->data); 4463 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4464 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4465 for (i=0; i<B->rmap->n; i++) { 4466 nz[i] = Baij->i[i+1] - Baij->i[i]; 4467 } 4468 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4469 ierr = PetscFree(nz);CHKERRQ(ierr); 4470 } 4471 if (pattern == SUBSET_NONZERO_PATTERN) { 4472 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4473 } 4474 count = 0; 4475 rowindices = NULL; 4476 colindices = NULL; 4477 if (rowemb) { 4478 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4479 } 4480 if (colemb) { 4481 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4482 } 4483 for (i=0; i<B->rmap->n; i++) { 4484 PetscInt row; 4485 row = i; 4486 if (rowindices) row = rowindices[i]; 4487 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4488 PetscInt col; 4489 col = Baij->j[count]; 4490 if (colindices) col = colindices[col]; 4491 v = Baij->a[count]; 4492 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4493 ++count; 4494 } 4495 } 4496 /* FIXME: set C's nonzerostate correctly. */ 4497 /* Assembly for C is necessary. */ 4498 C->preallocated = PETSC_TRUE; 4499 C->assembled = PETSC_TRUE; 4500 C->was_assembled = PETSC_FALSE; 4501 PetscFunctionReturn(0); 4502 } 4503 4504 PetscFunctionList MatSeqAIJList = NULL; 4505 4506 /*@C 4507 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 4508 4509 Collective on Mat 4510 4511 Input Parameters: 4512 + mat - the matrix object 4513 - matype - matrix type 4514 4515 Options Database Key: 4516 . -mat_seqai_type <method> - for example seqaijcrl 4517 4518 4519 Level: intermediate 4520 4521 .keywords: Mat, MatType, set, method 4522 4523 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 4524 @*/ 4525 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 4526 { 4527 PetscErrorCode ierr,(*r)(Mat,const MatType,MatReuse,Mat*); 4528 PetscBool sametype; 4529 4530 PetscFunctionBegin; 4531 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 4532 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 4533 if (sametype) PetscFunctionReturn(0); 4534 4535 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 4536 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 4537 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 4538 PetscFunctionReturn(0); 4539 } 4540 4541 4542 /*@C 4543 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 4544 4545 Not Collective 4546 4547 Input Parameters: 4548 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 4549 - function - routine to convert to subtype 4550 4551 Notes: 4552 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 4553 4554 4555 Then, your matrix can be chosen with the procedural interface at runtime via the option 4556 $ -mat_seqaij_type my_mat 4557 4558 Level: advanced 4559 4560 .keywords: Mat, register 4561 4562 .seealso: MatSeqAIJRegisterAll() 4563 4564 4565 Level: advanced 4566 @*/ 4567 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,MatType,MatReuse,Mat *)) 4568 { 4569 PetscErrorCode ierr; 4570 4571 PetscFunctionBegin; 4572 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 4573 PetscFunctionReturn(0); 4574 } 4575 4576 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 4577 4578 /*@C 4579 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 4580 4581 Not Collective 4582 4583 Level: advanced 4584 4585 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 4586 4587 .keywords: KSP, register, all 4588 4589 .seealso: MatRegisterAll(), MatSeqAIJRegister() 4590 @*/ 4591 PetscErrorCode MatSeqAIJRegisterAll(void) 4592 { 4593 PetscErrorCode ierr; 4594 4595 PetscFunctionBegin; 4596 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 4597 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 4598 4599 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4600 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4601 #if defined(PETSC_HAVE_MKL_SPARSE) 4602 ierr = MatSeqAIJRegister(MATSEQAIJMKL, MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4603 #endif 4604 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4605 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 4606 #endif 4607 PetscFunctionReturn(0); 4608 } 4609 4610 /* 4611 Special version for direct calls from Fortran 4612 */ 4613 #include <petsc/private/fortranimpl.h> 4614 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4615 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4616 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4617 #define matsetvaluesseqaij_ matsetvaluesseqaij 4618 #endif 4619 4620 /* Change these macros so can be used in void function */ 4621 #undef CHKERRQ 4622 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4623 #undef SETERRQ2 4624 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4625 #undef SETERRQ3 4626 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4627 4628 PETSC_EXTERN void PETSC_STDCALL matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 4629 { 4630 Mat A = *AA; 4631 PetscInt m = *mm, n = *nn; 4632 InsertMode is = *isis; 4633 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4634 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4635 PetscInt *imax,*ai,*ailen; 4636 PetscErrorCode ierr; 4637 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4638 MatScalar *ap,value,*aa; 4639 PetscBool ignorezeroentries = a->ignorezeroentries; 4640 PetscBool roworiented = a->roworiented; 4641 4642 PetscFunctionBegin; 4643 MatCheckPreallocated(A,1); 4644 imax = a->imax; 4645 ai = a->i; 4646 ailen = a->ilen; 4647 aj = a->j; 4648 aa = a->a; 4649 4650 for (k=0; k<m; k++) { /* loop over added rows */ 4651 row = im[k]; 4652 if (row < 0) continue; 4653 #if defined(PETSC_USE_DEBUG) 4654 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4655 #endif 4656 rp = aj + ai[row]; ap = aa + ai[row]; 4657 rmax = imax[row]; nrow = ailen[row]; 4658 low = 0; 4659 high = nrow; 4660 for (l=0; l<n; l++) { /* loop over added columns */ 4661 if (in[l] < 0) continue; 4662 #if defined(PETSC_USE_DEBUG) 4663 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4664 #endif 4665 col = in[l]; 4666 if (roworiented) value = v[l + k*n]; 4667 else value = v[k + l*m]; 4668 4669 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4670 4671 if (col <= lastcol) low = 0; 4672 else high = nrow; 4673 lastcol = col; 4674 while (high-low > 5) { 4675 t = (low+high)/2; 4676 if (rp[t] > col) high = t; 4677 else low = t; 4678 } 4679 for (i=low; i<high; i++) { 4680 if (rp[i] > col) break; 4681 if (rp[i] == col) { 4682 if (is == ADD_VALUES) ap[i] += value; 4683 else ap[i] = value; 4684 goto noinsert; 4685 } 4686 } 4687 if (value == 0.0 && ignorezeroentries) goto noinsert; 4688 if (nonew == 1) goto noinsert; 4689 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4690 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4691 N = nrow++ - 1; a->nz++; high++; 4692 /* shift up all the later entries in this row */ 4693 for (ii=N; ii>=i; ii--) { 4694 rp[ii+1] = rp[ii]; 4695 ap[ii+1] = ap[ii]; 4696 } 4697 rp[i] = col; 4698 ap[i] = value; 4699 A->nonzerostate++; 4700 noinsert:; 4701 low = i + 1; 4702 } 4703 ailen[row] = nrow; 4704 } 4705 PetscFunctionReturnVoid(); 4706 } 4707 4708