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 = PetscFree(a->ipre);CHKERRQ(ierr); 1098 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1099 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1100 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1101 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1102 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1103 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1104 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1105 1106 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1107 ierr = PetscFree(A->data);CHKERRQ(ierr); 1108 1109 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1110 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1111 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1112 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1116 #if defined(PETSC_HAVE_ELEMENTAL) 1117 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); 1118 #endif 1119 #if defined(PETSC_HAVE_HYPRE) 1120 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_hypre_C",NULL);CHKERRQ(ierr); 1121 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMatMatMult_transpose_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1122 #endif 1123 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1124 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1125 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1126 ierr = PetscObjectComposeFunction((PetscObject)A,"MatResetPreallocation_C",NULL);CHKERRQ(ierr); 1127 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1128 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1129 PetscFunctionReturn(0); 1130 } 1131 1132 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1133 { 1134 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1135 PetscErrorCode ierr; 1136 1137 PetscFunctionBegin; 1138 switch (op) { 1139 case MAT_ROW_ORIENTED: 1140 a->roworiented = flg; 1141 break; 1142 case MAT_KEEP_NONZERO_PATTERN: 1143 a->keepnonzeropattern = flg; 1144 break; 1145 case MAT_NEW_NONZERO_LOCATIONS: 1146 a->nonew = (flg ? 0 : 1); 1147 break; 1148 case MAT_NEW_NONZERO_LOCATION_ERR: 1149 a->nonew = (flg ? -1 : 0); 1150 break; 1151 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1152 a->nonew = (flg ? -2 : 0); 1153 break; 1154 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1155 a->nounused = (flg ? -1 : 0); 1156 break; 1157 case MAT_IGNORE_ZERO_ENTRIES: 1158 a->ignorezeroentries = flg; 1159 break; 1160 case MAT_SPD: 1161 case MAT_SYMMETRIC: 1162 case MAT_STRUCTURALLY_SYMMETRIC: 1163 case MAT_HERMITIAN: 1164 case MAT_SYMMETRY_ETERNAL: 1165 case MAT_STRUCTURE_ONLY: 1166 /* These options are handled directly by MatSetOption() */ 1167 break; 1168 case MAT_NEW_DIAGONALS: 1169 case MAT_IGNORE_OFF_PROC_ENTRIES: 1170 case MAT_USE_HASH_TABLE: 1171 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1172 break; 1173 case MAT_USE_INODES: 1174 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1175 break; 1176 case MAT_SUBMAT_SINGLEIS: 1177 A->submat_singleis = flg; 1178 break; 1179 default: 1180 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1181 } 1182 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1183 PetscFunctionReturn(0); 1184 } 1185 1186 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1187 { 1188 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1189 PetscErrorCode ierr; 1190 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1191 PetscScalar *aa=a->a,*x,zero=0.0; 1192 1193 PetscFunctionBegin; 1194 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1195 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1196 1197 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1198 PetscInt *diag=a->diag; 1199 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1200 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1201 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1202 PetscFunctionReturn(0); 1203 } 1204 1205 ierr = VecSet(v,zero);CHKERRQ(ierr); 1206 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1207 for (i=0; i<n; i++) { 1208 nz = ai[i+1] - ai[i]; 1209 if (!nz) x[i] = 0.0; 1210 for (j=ai[i]; j<ai[i+1]; j++) { 1211 if (aj[j] == i) { 1212 x[i] = aa[j]; 1213 break; 1214 } 1215 } 1216 } 1217 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1218 PetscFunctionReturn(0); 1219 } 1220 1221 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1222 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1223 { 1224 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1225 PetscScalar *y; 1226 const PetscScalar *x; 1227 PetscErrorCode ierr; 1228 PetscInt m = A->rmap->n; 1229 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1230 const MatScalar *v; 1231 PetscScalar alpha; 1232 PetscInt n,i,j; 1233 const PetscInt *idx,*ii,*ridx=NULL; 1234 Mat_CompressedRow cprow = a->compressedrow; 1235 PetscBool usecprow = cprow.use; 1236 #endif 1237 1238 PetscFunctionBegin; 1239 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1240 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1241 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1242 1243 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1244 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1245 #else 1246 if (usecprow) { 1247 m = cprow.nrows; 1248 ii = cprow.i; 1249 ridx = cprow.rindex; 1250 } else { 1251 ii = a->i; 1252 } 1253 for (i=0; i<m; i++) { 1254 idx = a->j + ii[i]; 1255 v = a->a + ii[i]; 1256 n = ii[i+1] - ii[i]; 1257 if (usecprow) { 1258 alpha = x[ridx[i]]; 1259 } else { 1260 alpha = x[i]; 1261 } 1262 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1263 } 1264 #endif 1265 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1266 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1267 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1268 PetscFunctionReturn(0); 1269 } 1270 1271 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1272 { 1273 PetscErrorCode ierr; 1274 1275 PetscFunctionBegin; 1276 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1277 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1278 PetscFunctionReturn(0); 1279 } 1280 1281 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1282 1283 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1284 { 1285 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1286 PetscScalar *y; 1287 const PetscScalar *x; 1288 const MatScalar *aa; 1289 PetscErrorCode ierr; 1290 PetscInt m=A->rmap->n; 1291 const PetscInt *aj,*ii,*ridx=NULL; 1292 PetscInt n,i; 1293 PetscScalar sum; 1294 PetscBool usecprow=a->compressedrow.use; 1295 1296 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1297 #pragma disjoint(*x,*y,*aa) 1298 #endif 1299 1300 PetscFunctionBegin; 1301 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1302 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1303 ii = a->i; 1304 if (usecprow) { /* use compressed row format */ 1305 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1306 m = a->compressedrow.nrows; 1307 ii = a->compressedrow.i; 1308 ridx = a->compressedrow.rindex; 1309 for (i=0; i<m; i++) { 1310 n = ii[i+1] - ii[i]; 1311 aj = a->j + ii[i]; 1312 aa = a->a + ii[i]; 1313 sum = 0.0; 1314 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1315 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1316 y[*ridx++] = sum; 1317 } 1318 } else { /* do not use compressed row format */ 1319 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1320 aj = a->j; 1321 aa = a->a; 1322 fortranmultaij_(&m,x,ii,aj,aa,y); 1323 #else 1324 for (i=0; i<m; i++) { 1325 n = ii[i+1] - ii[i]; 1326 aj = a->j + ii[i]; 1327 aa = a->a + ii[i]; 1328 sum = 0.0; 1329 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1330 y[i] = sum; 1331 } 1332 #endif 1333 } 1334 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1335 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1336 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1337 PetscFunctionReturn(0); 1338 } 1339 1340 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1341 { 1342 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1343 PetscScalar *y; 1344 const PetscScalar *x; 1345 const MatScalar *aa; 1346 PetscErrorCode ierr; 1347 PetscInt m=A->rmap->n; 1348 const PetscInt *aj,*ii,*ridx=NULL; 1349 PetscInt n,i,nonzerorow=0; 1350 PetscScalar sum; 1351 PetscBool usecprow=a->compressedrow.use; 1352 1353 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1354 #pragma disjoint(*x,*y,*aa) 1355 #endif 1356 1357 PetscFunctionBegin; 1358 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1359 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1360 if (usecprow) { /* use compressed row format */ 1361 m = a->compressedrow.nrows; 1362 ii = a->compressedrow.i; 1363 ridx = a->compressedrow.rindex; 1364 for (i=0; i<m; i++) { 1365 n = ii[i+1] - ii[i]; 1366 aj = a->j + ii[i]; 1367 aa = a->a + ii[i]; 1368 sum = 0.0; 1369 nonzerorow += (n>0); 1370 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1371 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1372 y[*ridx++] = sum; 1373 } 1374 } else { /* do not use compressed row format */ 1375 ii = a->i; 1376 for (i=0; i<m; i++) { 1377 n = ii[i+1] - ii[i]; 1378 aj = a->j + ii[i]; 1379 aa = a->a + ii[i]; 1380 sum = 0.0; 1381 nonzerorow += (n>0); 1382 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1383 y[i] = sum; 1384 } 1385 } 1386 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1387 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1388 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1389 PetscFunctionReturn(0); 1390 } 1391 1392 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1393 { 1394 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1395 PetscScalar *y,*z; 1396 const PetscScalar *x; 1397 const MatScalar *aa; 1398 PetscErrorCode ierr; 1399 PetscInt m = A->rmap->n,*aj,*ii; 1400 PetscInt n,i,*ridx=NULL; 1401 PetscScalar sum; 1402 PetscBool usecprow=a->compressedrow.use; 1403 1404 PetscFunctionBegin; 1405 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1406 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1407 if (usecprow) { /* use compressed row format */ 1408 if (zz != yy) { 1409 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1410 } 1411 m = a->compressedrow.nrows; 1412 ii = a->compressedrow.i; 1413 ridx = a->compressedrow.rindex; 1414 for (i=0; i<m; i++) { 1415 n = ii[i+1] - ii[i]; 1416 aj = a->j + ii[i]; 1417 aa = a->a + ii[i]; 1418 sum = y[*ridx]; 1419 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1420 z[*ridx++] = sum; 1421 } 1422 } else { /* do not use compressed row format */ 1423 ii = a->i; 1424 for (i=0; i<m; i++) { 1425 n = ii[i+1] - ii[i]; 1426 aj = a->j + ii[i]; 1427 aa = a->a + ii[i]; 1428 sum = y[i]; 1429 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1430 z[i] = sum; 1431 } 1432 } 1433 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1434 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1435 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1436 PetscFunctionReturn(0); 1437 } 1438 1439 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1440 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1441 { 1442 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1443 PetscScalar *y,*z; 1444 const PetscScalar *x; 1445 const MatScalar *aa; 1446 PetscErrorCode ierr; 1447 const PetscInt *aj,*ii,*ridx=NULL; 1448 PetscInt m = A->rmap->n,n,i; 1449 PetscScalar sum; 1450 PetscBool usecprow=a->compressedrow.use; 1451 1452 PetscFunctionBegin; 1453 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1454 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1455 if (usecprow) { /* use compressed row format */ 1456 if (zz != yy) { 1457 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1458 } 1459 m = a->compressedrow.nrows; 1460 ii = a->compressedrow.i; 1461 ridx = a->compressedrow.rindex; 1462 for (i=0; i<m; i++) { 1463 n = ii[i+1] - ii[i]; 1464 aj = a->j + ii[i]; 1465 aa = a->a + ii[i]; 1466 sum = y[*ridx]; 1467 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1468 z[*ridx++] = sum; 1469 } 1470 } else { /* do not use compressed row format */ 1471 ii = a->i; 1472 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1473 aj = a->j; 1474 aa = a->a; 1475 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1476 #else 1477 for (i=0; i<m; i++) { 1478 n = ii[i+1] - ii[i]; 1479 aj = a->j + ii[i]; 1480 aa = a->a + ii[i]; 1481 sum = y[i]; 1482 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1483 z[i] = sum; 1484 } 1485 #endif 1486 } 1487 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1488 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1489 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1490 #if defined(PETSC_HAVE_CUSP) 1491 /* 1492 ierr = VecView(xx,0);CHKERRQ(ierr); 1493 ierr = VecView(zz,0);CHKERRQ(ierr); 1494 ierr = MatView(A,0);CHKERRQ(ierr); 1495 */ 1496 #endif 1497 PetscFunctionReturn(0); 1498 } 1499 1500 /* 1501 Adds diagonal pointers to sparse matrix structure. 1502 */ 1503 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1504 { 1505 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1506 PetscErrorCode ierr; 1507 PetscInt i,j,m = A->rmap->n; 1508 1509 PetscFunctionBegin; 1510 if (!a->diag) { 1511 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1512 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1513 } 1514 for (i=0; i<A->rmap->n; i++) { 1515 a->diag[i] = a->i[i+1]; 1516 for (j=a->i[i]; j<a->i[i+1]; j++) { 1517 if (a->j[j] == i) { 1518 a->diag[i] = j; 1519 break; 1520 } 1521 } 1522 } 1523 PetscFunctionReturn(0); 1524 } 1525 1526 /* 1527 Checks for missing diagonals 1528 */ 1529 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1530 { 1531 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1532 PetscInt *diag,*ii = a->i,i; 1533 1534 PetscFunctionBegin; 1535 *missing = PETSC_FALSE; 1536 if (A->rmap->n > 0 && !ii) { 1537 *missing = PETSC_TRUE; 1538 if (d) *d = 0; 1539 PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n"); 1540 } else { 1541 diag = a->diag; 1542 for (i=0; i<A->rmap->n; i++) { 1543 if (diag[i] >= ii[i+1]) { 1544 *missing = PETSC_TRUE; 1545 if (d) *d = i; 1546 PetscInfo1(A,"Matrix is missing diagonal number %D\n",i); 1547 break; 1548 } 1549 } 1550 } 1551 PetscFunctionReturn(0); 1552 } 1553 1554 /* 1555 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1556 */ 1557 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1558 { 1559 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1560 PetscErrorCode ierr; 1561 PetscInt i,*diag,m = A->rmap->n; 1562 MatScalar *v = a->a; 1563 PetscScalar *idiag,*mdiag; 1564 1565 PetscFunctionBegin; 1566 if (a->idiagvalid) PetscFunctionReturn(0); 1567 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1568 diag = a->diag; 1569 if (!a->idiag) { 1570 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1571 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1572 v = a->a; 1573 } 1574 mdiag = a->mdiag; 1575 idiag = a->idiag; 1576 1577 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1578 for (i=0; i<m; i++) { 1579 mdiag[i] = v[diag[i]]; 1580 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1581 if (PetscRealPart(fshift)) { 1582 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1583 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1584 A->factorerror_zeropivot_value = 0.0; 1585 A->factorerror_zeropivot_row = i; 1586 } SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1587 } 1588 idiag[i] = 1.0/v[diag[i]]; 1589 } 1590 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1591 } else { 1592 for (i=0; i<m; i++) { 1593 mdiag[i] = v[diag[i]]; 1594 idiag[i] = omega/(fshift + v[diag[i]]); 1595 } 1596 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1597 } 1598 a->idiagvalid = PETSC_TRUE; 1599 PetscFunctionReturn(0); 1600 } 1601 1602 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1603 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1604 { 1605 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1606 PetscScalar *x,d,sum,*t,scale; 1607 const MatScalar *v,*idiag=0,*mdiag; 1608 const PetscScalar *b, *bs,*xb, *ts; 1609 PetscErrorCode ierr; 1610 PetscInt n,m = A->rmap->n,i; 1611 const PetscInt *idx,*diag; 1612 1613 PetscFunctionBegin; 1614 its = its*lits; 1615 1616 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1617 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1618 a->fshift = fshift; 1619 a->omega = omega; 1620 1621 diag = a->diag; 1622 t = a->ssor_work; 1623 idiag = a->idiag; 1624 mdiag = a->mdiag; 1625 1626 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1627 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1628 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1629 if (flag == SOR_APPLY_UPPER) { 1630 /* apply (U + D/omega) to the vector */ 1631 bs = b; 1632 for (i=0; i<m; i++) { 1633 d = fshift + mdiag[i]; 1634 n = a->i[i+1] - diag[i] - 1; 1635 idx = a->j + diag[i] + 1; 1636 v = a->a + diag[i] + 1; 1637 sum = b[i]*d/omega; 1638 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1639 x[i] = sum; 1640 } 1641 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1642 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1643 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1644 PetscFunctionReturn(0); 1645 } 1646 1647 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1648 else if (flag & SOR_EISENSTAT) { 1649 /* Let A = L + U + D; where L is lower trianglar, 1650 U is upper triangular, E = D/omega; This routine applies 1651 1652 (L + E)^{-1} A (U + E)^{-1} 1653 1654 to a vector efficiently using Eisenstat's trick. 1655 */ 1656 scale = (2.0/omega) - 1.0; 1657 1658 /* x = (E + U)^{-1} b */ 1659 for (i=m-1; i>=0; i--) { 1660 n = a->i[i+1] - diag[i] - 1; 1661 idx = a->j + diag[i] + 1; 1662 v = a->a + diag[i] + 1; 1663 sum = b[i]; 1664 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1665 x[i] = sum*idiag[i]; 1666 } 1667 1668 /* t = b - (2*E - D)x */ 1669 v = a->a; 1670 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1671 1672 /* t = (E + L)^{-1}t */ 1673 ts = t; 1674 diag = a->diag; 1675 for (i=0; i<m; i++) { 1676 n = diag[i] - a->i[i]; 1677 idx = a->j + a->i[i]; 1678 v = a->a + a->i[i]; 1679 sum = t[i]; 1680 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1681 t[i] = sum*idiag[i]; 1682 /* x = x + t */ 1683 x[i] += t[i]; 1684 } 1685 1686 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1687 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1688 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1689 PetscFunctionReturn(0); 1690 } 1691 if (flag & SOR_ZERO_INITIAL_GUESS) { 1692 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1693 for (i=0; i<m; i++) { 1694 n = diag[i] - a->i[i]; 1695 idx = a->j + a->i[i]; 1696 v = a->a + a->i[i]; 1697 sum = b[i]; 1698 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1699 t[i] = sum; 1700 x[i] = sum*idiag[i]; 1701 } 1702 xb = t; 1703 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1704 } else xb = b; 1705 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1706 for (i=m-1; i>=0; i--) { 1707 n = a->i[i+1] - diag[i] - 1; 1708 idx = a->j + diag[i] + 1; 1709 v = a->a + diag[i] + 1; 1710 sum = xb[i]; 1711 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1712 if (xb == b) { 1713 x[i] = sum*idiag[i]; 1714 } else { 1715 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1716 } 1717 } 1718 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1719 } 1720 its--; 1721 } 1722 while (its--) { 1723 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1724 for (i=0; i<m; i++) { 1725 /* lower */ 1726 n = diag[i] - a->i[i]; 1727 idx = a->j + a->i[i]; 1728 v = a->a + a->i[i]; 1729 sum = b[i]; 1730 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1731 t[i] = sum; /* save application of the lower-triangular part */ 1732 /* upper */ 1733 n = a->i[i+1] - diag[i] - 1; 1734 idx = a->j + diag[i] + 1; 1735 v = a->a + diag[i] + 1; 1736 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1737 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1738 } 1739 xb = t; 1740 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1741 } else xb = b; 1742 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1743 for (i=m-1; i>=0; i--) { 1744 sum = xb[i]; 1745 if (xb == b) { 1746 /* whole matrix (no checkpointing available) */ 1747 n = a->i[i+1] - a->i[i]; 1748 idx = a->j + a->i[i]; 1749 v = a->a + a->i[i]; 1750 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1751 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1752 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1753 n = a->i[i+1] - diag[i] - 1; 1754 idx = a->j + diag[i] + 1; 1755 v = a->a + diag[i] + 1; 1756 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1757 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1758 } 1759 } 1760 if (xb == b) { 1761 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1762 } else { 1763 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1764 } 1765 } 1766 } 1767 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1768 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1769 PetscFunctionReturn(0); 1770 } 1771 1772 1773 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1774 { 1775 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1776 1777 PetscFunctionBegin; 1778 info->block_size = 1.0; 1779 info->nz_allocated = (double)a->maxnz; 1780 info->nz_used = (double)a->nz; 1781 info->nz_unneeded = (double)(a->maxnz - a->nz); 1782 info->assemblies = (double)A->num_ass; 1783 info->mallocs = (double)A->info.mallocs; 1784 info->memory = ((PetscObject)A)->mem; 1785 if (A->factortype) { 1786 info->fill_ratio_given = A->info.fill_ratio_given; 1787 info->fill_ratio_needed = A->info.fill_ratio_needed; 1788 info->factor_mallocs = A->info.factor_mallocs; 1789 } else { 1790 info->fill_ratio_given = 0; 1791 info->fill_ratio_needed = 0; 1792 info->factor_mallocs = 0; 1793 } 1794 PetscFunctionReturn(0); 1795 } 1796 1797 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1798 { 1799 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1800 PetscInt i,m = A->rmap->n - 1; 1801 PetscErrorCode ierr; 1802 const PetscScalar *xx; 1803 PetscScalar *bb; 1804 PetscInt d = 0; 1805 1806 PetscFunctionBegin; 1807 if (x && b) { 1808 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1809 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1810 for (i=0; i<N; i++) { 1811 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1812 bb[rows[i]] = diag*xx[rows[i]]; 1813 } 1814 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1815 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1816 } 1817 1818 if (a->keepnonzeropattern) { 1819 for (i=0; i<N; i++) { 1820 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1821 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1822 } 1823 if (diag != 0.0) { 1824 for (i=0; i<N; i++) { 1825 d = rows[i]; 1826 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); 1827 } 1828 for (i=0; i<N; i++) { 1829 a->a[a->diag[rows[i]]] = diag; 1830 } 1831 } 1832 } else { 1833 if (diag != 0.0) { 1834 for (i=0; i<N; i++) { 1835 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1836 if (a->ilen[rows[i]] > 0) { 1837 a->ilen[rows[i]] = 1; 1838 a->a[a->i[rows[i]]] = diag; 1839 a->j[a->i[rows[i]]] = rows[i]; 1840 } else { /* in case row was completely empty */ 1841 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1842 } 1843 } 1844 } else { 1845 for (i=0; i<N; i++) { 1846 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1847 a->ilen[rows[i]] = 0; 1848 } 1849 } 1850 A->nonzerostate++; 1851 } 1852 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1853 PetscFunctionReturn(0); 1854 } 1855 1856 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1857 { 1858 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1859 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1860 PetscErrorCode ierr; 1861 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1862 const PetscScalar *xx; 1863 PetscScalar *bb; 1864 1865 PetscFunctionBegin; 1866 if (x && b) { 1867 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1868 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1869 vecs = PETSC_TRUE; 1870 } 1871 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 1872 for (i=0; i<N; i++) { 1873 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1874 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1875 1876 zeroed[rows[i]] = PETSC_TRUE; 1877 } 1878 for (i=0; i<A->rmap->n; i++) { 1879 if (!zeroed[i]) { 1880 for (j=a->i[i]; j<a->i[i+1]; j++) { 1881 if (zeroed[a->j[j]]) { 1882 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1883 a->a[j] = 0.0; 1884 } 1885 } 1886 } else if (vecs) bb[i] = diag*xx[i]; 1887 } 1888 if (x && b) { 1889 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1890 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1891 } 1892 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1893 if (diag != 0.0) { 1894 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1895 if (missing) { 1896 if (a->nonew) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1897 else { 1898 for (i=0; i<N; i++) { 1899 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1900 } 1901 } 1902 } else { 1903 for (i=0; i<N; i++) { 1904 a->a[a->diag[rows[i]]] = diag; 1905 } 1906 } 1907 } 1908 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1909 PetscFunctionReturn(0); 1910 } 1911 1912 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1913 { 1914 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1915 PetscInt *itmp; 1916 1917 PetscFunctionBegin; 1918 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1919 1920 *nz = a->i[row+1] - a->i[row]; 1921 if (v) *v = a->a + a->i[row]; 1922 if (idx) { 1923 itmp = a->j + a->i[row]; 1924 if (*nz) *idx = itmp; 1925 else *idx = 0; 1926 } 1927 PetscFunctionReturn(0); 1928 } 1929 1930 /* remove this function? */ 1931 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1932 { 1933 PetscFunctionBegin; 1934 PetscFunctionReturn(0); 1935 } 1936 1937 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1938 { 1939 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1940 MatScalar *v = a->a; 1941 PetscReal sum = 0.0; 1942 PetscErrorCode ierr; 1943 PetscInt i,j; 1944 1945 PetscFunctionBegin; 1946 if (type == NORM_FROBENIUS) { 1947 #if defined(PETSC_USE_REAL___FP16) 1948 PetscBLASInt one = 1,nz = a->nz; 1949 *nrm = BLASnrm2_(&nz,v,&one); 1950 #else 1951 for (i=0; i<a->nz; i++) { 1952 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1953 } 1954 *nrm = PetscSqrtReal(sum); 1955 #endif 1956 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 1957 } else if (type == NORM_1) { 1958 PetscReal *tmp; 1959 PetscInt *jj = a->j; 1960 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 1961 *nrm = 0.0; 1962 for (j=0; j<a->nz; j++) { 1963 tmp[*jj++] += PetscAbsScalar(*v); v++; 1964 } 1965 for (j=0; j<A->cmap->n; j++) { 1966 if (tmp[j] > *nrm) *nrm = tmp[j]; 1967 } 1968 ierr = PetscFree(tmp);CHKERRQ(ierr); 1969 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1970 } else if (type == NORM_INFINITY) { 1971 *nrm = 0.0; 1972 for (j=0; j<A->rmap->n; j++) { 1973 v = a->a + a->i[j]; 1974 sum = 0.0; 1975 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 1976 sum += PetscAbsScalar(*v); v++; 1977 } 1978 if (sum > *nrm) *nrm = sum; 1979 } 1980 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1981 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 1982 PetscFunctionReturn(0); 1983 } 1984 1985 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 1986 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 1987 { 1988 PetscErrorCode ierr; 1989 PetscInt i,j,anzj; 1990 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 1991 PetscInt an=A->cmap->N,am=A->rmap->N; 1992 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 1993 1994 PetscFunctionBegin; 1995 /* Allocate space for symbolic transpose info and work array */ 1996 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 1997 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 1998 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 1999 2000 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2001 /* Note: offset by 1 for fast conversion into csr format. */ 2002 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2003 /* Form ati for csr format of A^T. */ 2004 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2005 2006 /* Copy ati into atfill so we have locations of the next free space in atj */ 2007 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2008 2009 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2010 for (i=0;i<am;i++) { 2011 anzj = ai[i+1] - ai[i]; 2012 for (j=0;j<anzj;j++) { 2013 atj[atfill[*aj]] = i; 2014 atfill[*aj++] += 1; 2015 } 2016 } 2017 2018 /* Clean up temporary space and complete requests. */ 2019 ierr = PetscFree(atfill);CHKERRQ(ierr); 2020 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2021 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2022 2023 b = (Mat_SeqAIJ*)((*B)->data); 2024 b->free_a = PETSC_FALSE; 2025 b->free_ij = PETSC_TRUE; 2026 b->nonew = 0; 2027 PetscFunctionReturn(0); 2028 } 2029 2030 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2031 { 2032 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2033 Mat C; 2034 PetscErrorCode ierr; 2035 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2036 MatScalar *array = a->a; 2037 2038 PetscFunctionBegin; 2039 if (reuse == MAT_INPLACE_MATRIX && m != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2040 2041 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { 2042 ierr = PetscCalloc1(1+A->cmap->n,&col);CHKERRQ(ierr); 2043 2044 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2045 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2046 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2047 ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2048 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2049 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2050 ierr = PetscFree(col);CHKERRQ(ierr); 2051 } else { 2052 C = *B; 2053 } 2054 2055 for (i=0; i<m; i++) { 2056 len = ai[i+1]-ai[i]; 2057 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2058 array += len; 2059 aj += len; 2060 } 2061 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2062 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2063 2064 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 2065 *B = C; 2066 } else { 2067 ierr = MatHeaderMerge(A,&C);CHKERRQ(ierr); 2068 } 2069 PetscFunctionReturn(0); 2070 } 2071 2072 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2073 { 2074 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2075 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2076 MatScalar *va,*vb; 2077 PetscErrorCode ierr; 2078 PetscInt ma,na,mb,nb, i; 2079 2080 PetscFunctionBegin; 2081 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2082 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2083 if (ma!=nb || na!=mb) { 2084 *f = PETSC_FALSE; 2085 PetscFunctionReturn(0); 2086 } 2087 aii = aij->i; bii = bij->i; 2088 adx = aij->j; bdx = bij->j; 2089 va = aij->a; vb = bij->a; 2090 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2091 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2092 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2093 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2094 2095 *f = PETSC_TRUE; 2096 for (i=0; i<ma; i++) { 2097 while (aptr[i]<aii[i+1]) { 2098 PetscInt idc,idr; 2099 PetscScalar vc,vr; 2100 /* column/row index/value */ 2101 idc = adx[aptr[i]]; 2102 idr = bdx[bptr[idc]]; 2103 vc = va[aptr[i]]; 2104 vr = vb[bptr[idc]]; 2105 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2106 *f = PETSC_FALSE; 2107 goto done; 2108 } else { 2109 aptr[i]++; 2110 if (B || i!=idc) bptr[idc]++; 2111 } 2112 } 2113 } 2114 done: 2115 ierr = PetscFree(aptr);CHKERRQ(ierr); 2116 ierr = PetscFree(bptr);CHKERRQ(ierr); 2117 PetscFunctionReturn(0); 2118 } 2119 2120 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2121 { 2122 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2123 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2124 MatScalar *va,*vb; 2125 PetscErrorCode ierr; 2126 PetscInt ma,na,mb,nb, i; 2127 2128 PetscFunctionBegin; 2129 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2130 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2131 if (ma!=nb || na!=mb) { 2132 *f = PETSC_FALSE; 2133 PetscFunctionReturn(0); 2134 } 2135 aii = aij->i; bii = bij->i; 2136 adx = aij->j; bdx = bij->j; 2137 va = aij->a; vb = bij->a; 2138 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2139 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2140 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2141 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2142 2143 *f = PETSC_TRUE; 2144 for (i=0; i<ma; i++) { 2145 while (aptr[i]<aii[i+1]) { 2146 PetscInt idc,idr; 2147 PetscScalar vc,vr; 2148 /* column/row index/value */ 2149 idc = adx[aptr[i]]; 2150 idr = bdx[bptr[idc]]; 2151 vc = va[aptr[i]]; 2152 vr = vb[bptr[idc]]; 2153 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2154 *f = PETSC_FALSE; 2155 goto done; 2156 } else { 2157 aptr[i]++; 2158 if (B || i!=idc) bptr[idc]++; 2159 } 2160 } 2161 } 2162 done: 2163 ierr = PetscFree(aptr);CHKERRQ(ierr); 2164 ierr = PetscFree(bptr);CHKERRQ(ierr); 2165 PetscFunctionReturn(0); 2166 } 2167 2168 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2169 { 2170 PetscErrorCode ierr; 2171 2172 PetscFunctionBegin; 2173 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2174 PetscFunctionReturn(0); 2175 } 2176 2177 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2178 { 2179 PetscErrorCode ierr; 2180 2181 PetscFunctionBegin; 2182 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2183 PetscFunctionReturn(0); 2184 } 2185 2186 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2187 { 2188 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2189 const PetscScalar *l,*r; 2190 PetscScalar x; 2191 MatScalar *v; 2192 PetscErrorCode ierr; 2193 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz; 2194 const PetscInt *jj; 2195 2196 PetscFunctionBegin; 2197 if (ll) { 2198 /* The local size is used so that VecMPI can be passed to this routine 2199 by MatDiagonalScale_MPIAIJ */ 2200 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2201 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2202 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 2203 v = a->a; 2204 for (i=0; i<m; i++) { 2205 x = l[i]; 2206 M = a->i[i+1] - a->i[i]; 2207 for (j=0; j<M; j++) (*v++) *= x; 2208 } 2209 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 2210 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2211 } 2212 if (rr) { 2213 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2214 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2215 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 2216 v = a->a; jj = a->j; 2217 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2218 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 2219 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2220 } 2221 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2222 PetscFunctionReturn(0); 2223 } 2224 2225 PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2226 { 2227 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2228 PetscErrorCode ierr; 2229 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2230 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2231 const PetscInt *irow,*icol; 2232 PetscInt nrows,ncols; 2233 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2234 MatScalar *a_new,*mat_a; 2235 Mat C; 2236 PetscBool stride; 2237 2238 PetscFunctionBegin; 2239 2240 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2241 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2242 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2243 2244 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2245 if (stride) { 2246 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2247 } else { 2248 first = 0; 2249 step = 0; 2250 } 2251 if (stride && step == 1) { 2252 /* special case of contiguous rows */ 2253 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2254 /* loop over new rows determining lens and starting points */ 2255 for (i=0; i<nrows; i++) { 2256 kstart = ai[irow[i]]; 2257 kend = kstart + ailen[irow[i]]; 2258 starts[i] = kstart; 2259 for (k=kstart; k<kend; k++) { 2260 if (aj[k] >= first) { 2261 starts[i] = k; 2262 break; 2263 } 2264 } 2265 sum = 0; 2266 while (k < kend) { 2267 if (aj[k++] >= first+ncols) break; 2268 sum++; 2269 } 2270 lens[i] = sum; 2271 } 2272 /* create submatrix */ 2273 if (scall == MAT_REUSE_MATRIX) { 2274 PetscInt n_cols,n_rows; 2275 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2276 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2277 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2278 C = *B; 2279 } else { 2280 PetscInt rbs,cbs; 2281 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2282 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2283 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2284 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2285 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2286 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2287 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2288 } 2289 c = (Mat_SeqAIJ*)C->data; 2290 2291 /* loop over rows inserting into submatrix */ 2292 a_new = c->a; 2293 j_new = c->j; 2294 i_new = c->i; 2295 2296 for (i=0; i<nrows; i++) { 2297 ii = starts[i]; 2298 lensi = lens[i]; 2299 for (k=0; k<lensi; k++) { 2300 *j_new++ = aj[ii+k] - first; 2301 } 2302 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2303 a_new += lensi; 2304 i_new[i+1] = i_new[i] + lensi; 2305 c->ilen[i] = lensi; 2306 } 2307 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2308 } else { 2309 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2310 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2311 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2312 for (i=0; i<ncols; i++) { 2313 #if defined(PETSC_USE_DEBUG) 2314 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); 2315 #endif 2316 smap[icol[i]] = i+1; 2317 } 2318 2319 /* determine lens of each row */ 2320 for (i=0; i<nrows; i++) { 2321 kstart = ai[irow[i]]; 2322 kend = kstart + a->ilen[irow[i]]; 2323 lens[i] = 0; 2324 for (k=kstart; k<kend; k++) { 2325 if (smap[aj[k]]) { 2326 lens[i]++; 2327 } 2328 } 2329 } 2330 /* Create and fill new matrix */ 2331 if (scall == MAT_REUSE_MATRIX) { 2332 PetscBool equal; 2333 2334 c = (Mat_SeqAIJ*)((*B)->data); 2335 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2336 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2337 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2338 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2339 C = *B; 2340 } else { 2341 PetscInt rbs,cbs; 2342 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2343 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2344 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2345 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2346 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2347 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2348 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2349 } 2350 c = (Mat_SeqAIJ*)(C->data); 2351 for (i=0; i<nrows; i++) { 2352 row = irow[i]; 2353 kstart = ai[row]; 2354 kend = kstart + a->ilen[row]; 2355 mat_i = c->i[i]; 2356 mat_j = c->j + mat_i; 2357 mat_a = c->a + mat_i; 2358 mat_ilen = c->ilen + i; 2359 for (k=kstart; k<kend; k++) { 2360 if ((tcol=smap[a->j[k]])) { 2361 *mat_j++ = tcol - 1; 2362 *mat_a++ = a->a[k]; 2363 (*mat_ilen)++; 2364 2365 } 2366 } 2367 } 2368 /* Free work space */ 2369 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2370 ierr = PetscFree(smap);CHKERRQ(ierr); 2371 ierr = PetscFree(lens);CHKERRQ(ierr); 2372 /* sort */ 2373 for (i = 0; i < nrows; i++) { 2374 PetscInt ilen; 2375 2376 mat_i = c->i[i]; 2377 mat_j = c->j + mat_i; 2378 mat_a = c->a + mat_i; 2379 ilen = c->ilen[i]; 2380 ierr = PetscSortIntWithScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2381 } 2382 } 2383 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2384 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2385 2386 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2387 *B = C; 2388 PetscFunctionReturn(0); 2389 } 2390 2391 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2392 { 2393 PetscErrorCode ierr; 2394 Mat B; 2395 2396 PetscFunctionBegin; 2397 if (scall == MAT_INITIAL_MATRIX) { 2398 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2399 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2400 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2401 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2402 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2403 *subMat = B; 2404 } else { 2405 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2406 } 2407 PetscFunctionReturn(0); 2408 } 2409 2410 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2411 { 2412 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2413 PetscErrorCode ierr; 2414 Mat outA; 2415 PetscBool row_identity,col_identity; 2416 2417 PetscFunctionBegin; 2418 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2419 2420 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2421 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2422 2423 outA = inA; 2424 outA->factortype = MAT_FACTOR_LU; 2425 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2426 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2427 2428 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2429 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2430 2431 a->row = row; 2432 2433 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2434 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2435 2436 a->col = col; 2437 2438 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2439 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2440 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2441 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2442 2443 if (!a->solve_work) { /* this matrix may have been factored before */ 2444 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2445 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2446 } 2447 2448 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2449 if (row_identity && col_identity) { 2450 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2451 } else { 2452 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2453 } 2454 PetscFunctionReturn(0); 2455 } 2456 2457 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2458 { 2459 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2460 PetscScalar oalpha = alpha; 2461 PetscErrorCode ierr; 2462 PetscBLASInt one = 1,bnz; 2463 2464 PetscFunctionBegin; 2465 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2466 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2467 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2468 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2469 PetscFunctionReturn(0); 2470 } 2471 2472 PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *submatj) 2473 { 2474 PetscErrorCode ierr; 2475 PetscInt i; 2476 2477 PetscFunctionBegin; 2478 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2479 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2480 2481 for (i=0; i<submatj->nrqr; ++i) { 2482 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2483 } 2484 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2485 2486 if (submatj->rbuf1) { 2487 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2488 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2489 } 2490 2491 for (i=0; i<submatj->nrqs; ++i) { 2492 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2493 } 2494 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2495 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2496 } 2497 2498 #if defined(PETSC_USE_CTABLE) 2499 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2500 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2501 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2502 #else 2503 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2504 #endif 2505 2506 if (!submatj->allcolumns) { 2507 #if defined(PETSC_USE_CTABLE) 2508 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2509 #else 2510 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2511 #endif 2512 } 2513 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2514 2515 ierr = PetscFree(submatj);CHKERRQ(ierr); 2516 PetscFunctionReturn(0); 2517 } 2518 2519 PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat C) 2520 { 2521 PetscErrorCode ierr; 2522 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2523 Mat_SubSppt *submatj = c->submatis1; 2524 2525 PetscFunctionBegin; 2526 ierr = submatj->destroy(C);CHKERRQ(ierr); 2527 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2528 PetscFunctionReturn(0); 2529 } 2530 2531 PetscErrorCode MatDestroySubMatrices_SeqAIJ(PetscInt n,Mat *mat[]) 2532 { 2533 PetscErrorCode ierr; 2534 PetscInt i; 2535 Mat C; 2536 Mat_SeqAIJ *c; 2537 Mat_SubSppt *submatj; 2538 2539 PetscFunctionBegin; 2540 for (i=0; i<n; i++) { 2541 C = (*mat)[i]; 2542 c = (Mat_SeqAIJ*)C->data; 2543 submatj = c->submatis1; 2544 if (submatj) { 2545 ierr = submatj->destroy(C);CHKERRQ(ierr); 2546 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2547 ierr = PetscLayoutDestroy(&C->rmap);CHKERRQ(ierr); 2548 ierr = PetscLayoutDestroy(&C->cmap);CHKERRQ(ierr); 2549 ierr = PetscHeaderDestroy(&C);CHKERRQ(ierr); 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 (!b->ipre) { 3614 ierr = PetscMalloc1(B->rmap->n,&b->ipre);CHKERRQ(ierr); 3615 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3616 } 3617 if (!nnz) { 3618 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3619 else if (nz < 0) nz = 1; 3620 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3621 nz = nz*B->rmap->n; 3622 } else { 3623 nz = 0; 3624 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3625 } 3626 /* b->ilen will count nonzeros in each row so far. */ 3627 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3628 3629 /* allocate the matrix space */ 3630 /* FIXME: should B's old memory be unlogged? */ 3631 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3632 if (B->structure_only) { 3633 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3634 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3635 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3636 } else { 3637 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3638 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3639 } 3640 b->i[0] = 0; 3641 for (i=1; i<B->rmap->n+1; i++) { 3642 b->i[i] = b->i[i-1] + b->imax[i-1]; 3643 } 3644 if (B->structure_only) { 3645 b->singlemalloc = PETSC_FALSE; 3646 b->free_a = PETSC_FALSE; 3647 } else { 3648 b->singlemalloc = PETSC_TRUE; 3649 b->free_a = PETSC_TRUE; 3650 } 3651 b->free_ij = PETSC_TRUE; 3652 } else { 3653 b->free_a = PETSC_FALSE; 3654 b->free_ij = PETSC_FALSE; 3655 } 3656 3657 if (b->ipre && nnz != b->ipre && b->imax) { 3658 /* reserve user-requested sparsity */ 3659 ierr = PetscMemcpy(b->ipre,b->imax,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3660 } 3661 3662 3663 b->nz = 0; 3664 b->maxnz = nz; 3665 B->info.nz_unneeded = (double)b->maxnz; 3666 if (realalloc) { 3667 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3668 } 3669 B->was_assembled = PETSC_FALSE; 3670 B->assembled = PETSC_FALSE; 3671 PetscFunctionReturn(0); 3672 } 3673 3674 3675 PetscErrorCode MatResetPreallocation_SeqAIJ(Mat A) 3676 { 3677 Mat_SeqAIJ *a; 3678 PetscInt i; 3679 PetscErrorCode ierr; 3680 3681 PetscFunctionBegin; 3682 PetscValidHeaderSpecific(A,MAT_CLASSID,1); 3683 a = (Mat_SeqAIJ*)A->data; 3684 /* if no saved info, we just return without doing anything */ 3685 if (!a->ipre) { 3686 ierr = PetscInfo(A, "No saved preallocation info \n");CHKERRQ(ierr); 3687 PetscFunctionReturn(0); 3688 } 3689 if (!a->i || !a->j || !a->a || !a->imax || !a->ilen) { 3690 ierr = PetscInfo(A, "Memory info is incomplete, and can not reset preallocation \n");CHKERRQ(ierr); 3691 PetscFunctionReturn(0); 3692 } 3693 ierr = PetscMemcpy(a->imax,a->ipre,A->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3694 ierr = PetscMemzero(a->ilen,A->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3695 a->i[0] = 0; 3696 for (i=1; i<A->rmap->n+1; i++) { 3697 a->i[i] = a->i[i-1] + a->imax[i-1]; 3698 } 3699 A->preallocated = PETSC_TRUE; 3700 a->nz = 0; 3701 a->maxnz = a->i[A->rmap->n]; 3702 A->info.nz_unneeded = (double)a->maxnz; 3703 A->was_assembled = PETSC_FALSE; 3704 A->assembled = PETSC_FALSE; 3705 PetscFunctionReturn(0); 3706 } 3707 3708 /*@ 3709 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3710 3711 Input Parameters: 3712 + B - the matrix 3713 . i - the indices into j for the start of each row (starts with zero) 3714 . j - the column indices for each row (starts with zero) these must be sorted for each row 3715 - v - optional values in the matrix 3716 3717 Level: developer 3718 3719 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3720 3721 .keywords: matrix, aij, compressed row, sparse, sequential 3722 3723 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3724 @*/ 3725 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3726 { 3727 PetscErrorCode ierr; 3728 3729 PetscFunctionBegin; 3730 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3731 PetscValidType(B,1); 3732 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3733 PetscFunctionReturn(0); 3734 } 3735 3736 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3737 { 3738 PetscInt i; 3739 PetscInt m,n; 3740 PetscInt nz; 3741 PetscInt *nnz, nz_max = 0; 3742 PetscScalar *values; 3743 PetscErrorCode ierr; 3744 3745 PetscFunctionBegin; 3746 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3747 3748 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3749 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3750 3751 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3752 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 3753 for (i = 0; i < m; i++) { 3754 nz = Ii[i+1]- Ii[i]; 3755 nz_max = PetscMax(nz_max, nz); 3756 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3757 nnz[i] = nz; 3758 } 3759 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3760 ierr = PetscFree(nnz);CHKERRQ(ierr); 3761 3762 if (v) { 3763 values = (PetscScalar*) v; 3764 } else { 3765 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3766 } 3767 3768 for (i = 0; i < m; i++) { 3769 nz = Ii[i+1] - Ii[i]; 3770 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3771 } 3772 3773 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3774 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3775 3776 if (!v) { 3777 ierr = PetscFree(values);CHKERRQ(ierr); 3778 } 3779 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3780 PetscFunctionReturn(0); 3781 } 3782 3783 #include <../src/mat/impls/dense/seq/dense.h> 3784 #include <petsc/private/kernels/petscaxpy.h> 3785 3786 /* 3787 Computes (B'*A')' since computing B*A directly is untenable 3788 3789 n p p 3790 ( ) ( ) ( ) 3791 m ( A ) * n ( B ) = m ( C ) 3792 ( ) ( ) ( ) 3793 3794 */ 3795 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3796 { 3797 PetscErrorCode ierr; 3798 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3799 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3800 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3801 PetscInt i,n,m,q,p; 3802 const PetscInt *ii,*idx; 3803 const PetscScalar *b,*a,*a_q; 3804 PetscScalar *c,*c_q; 3805 3806 PetscFunctionBegin; 3807 m = A->rmap->n; 3808 n = A->cmap->n; 3809 p = B->cmap->n; 3810 a = sub_a->v; 3811 b = sub_b->a; 3812 c = sub_c->v; 3813 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3814 3815 ii = sub_b->i; 3816 idx = sub_b->j; 3817 for (i=0; i<n; i++) { 3818 q = ii[i+1] - ii[i]; 3819 while (q-->0) { 3820 c_q = c + m*(*idx); 3821 a_q = a + m*i; 3822 PetscKernelAXPY(c_q,*b,a_q,m); 3823 idx++; 3824 b++; 3825 } 3826 } 3827 PetscFunctionReturn(0); 3828 } 3829 3830 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3831 { 3832 PetscErrorCode ierr; 3833 PetscInt m=A->rmap->n,n=B->cmap->n; 3834 Mat Cmat; 3835 3836 PetscFunctionBegin; 3837 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); 3838 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3839 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3840 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3841 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3842 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3843 3844 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3845 3846 *C = Cmat; 3847 PetscFunctionReturn(0); 3848 } 3849 3850 /* ----------------------------------------------------------------*/ 3851 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3852 { 3853 PetscErrorCode ierr; 3854 3855 PetscFunctionBegin; 3856 if (scall == MAT_INITIAL_MATRIX) { 3857 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3858 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3859 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3860 } 3861 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3862 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3863 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3864 PetscFunctionReturn(0); 3865 } 3866 3867 3868 /*MC 3869 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3870 based on compressed sparse row format. 3871 3872 Options Database Keys: 3873 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3874 3875 Level: beginner 3876 3877 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3878 M*/ 3879 3880 /*MC 3881 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3882 3883 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3884 and MATMPIAIJ otherwise. As a result, for single process communicators, 3885 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3886 for communicators controlling multiple processes. It is recommended that you call both of 3887 the above preallocation routines for simplicity. 3888 3889 Options Database Keys: 3890 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3891 3892 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when 3893 enough exist. 3894 3895 Level: beginner 3896 3897 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3898 M*/ 3899 3900 /*MC 3901 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3902 3903 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3904 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3905 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3906 for communicators controlling multiple processes. It is recommended that you call both of 3907 the above preallocation routines for simplicity. 3908 3909 Options Database Keys: 3910 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3911 3912 Level: beginner 3913 3914 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3915 M*/ 3916 3917 /*@C 3918 MatSeqAIJGetArray - gives access to the array where the data for a MATSEQAIJ matrix is stored 3919 3920 Not Collective 3921 3922 Input Parameter: 3923 . mat - a MATSEQAIJ matrix 3924 3925 Output Parameter: 3926 . array - pointer to the data 3927 3928 Level: intermediate 3929 3930 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3931 @*/ 3932 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 3933 { 3934 PetscErrorCode ierr; 3935 3936 PetscFunctionBegin; 3937 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3938 PetscFunctionReturn(0); 3939 } 3940 3941 /*@C 3942 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 3943 3944 Not Collective 3945 3946 Input Parameter: 3947 . mat - a MATSEQAIJ matrix 3948 3949 Output Parameter: 3950 . nz - the maximum number of nonzeros in any row 3951 3952 Level: intermediate 3953 3954 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3955 @*/ 3956 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 3957 { 3958 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 3959 3960 PetscFunctionBegin; 3961 *nz = aij->rmax; 3962 PetscFunctionReturn(0); 3963 } 3964 3965 /*@C 3966 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 3967 3968 Not Collective 3969 3970 Input Parameters: 3971 . mat - a MATSEQAIJ matrix 3972 . array - pointer to the data 3973 3974 Level: intermediate 3975 3976 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 3977 @*/ 3978 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 3979 { 3980 PetscErrorCode ierr; 3981 3982 PetscFunctionBegin; 3983 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3984 PetscFunctionReturn(0); 3985 } 3986 3987 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 3988 { 3989 Mat_SeqAIJ *b; 3990 PetscErrorCode ierr; 3991 PetscMPIInt size; 3992 3993 PetscFunctionBegin; 3994 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 3995 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3996 3997 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3998 3999 B->data = (void*)b; 4000 4001 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4002 4003 b->row = 0; 4004 b->col = 0; 4005 b->icol = 0; 4006 b->reallocs = 0; 4007 b->ignorezeroentries = PETSC_FALSE; 4008 b->roworiented = PETSC_TRUE; 4009 b->nonew = 0; 4010 b->diag = 0; 4011 b->solve_work = 0; 4012 B->spptr = 0; 4013 b->saved_values = 0; 4014 b->idiag = 0; 4015 b->mdiag = 0; 4016 b->ssor_work = 0; 4017 b->omega = 1.0; 4018 b->fshift = 0.0; 4019 b->idiagvalid = PETSC_FALSE; 4020 b->ibdiagvalid = PETSC_FALSE; 4021 b->keepnonzeropattern = PETSC_FALSE; 4022 4023 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4024 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4025 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4026 4027 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4028 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4029 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4030 #endif 4031 4032 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4033 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4034 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4035 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4036 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4037 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4038 #if defined(PETSC_HAVE_MKL) 4039 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijmkl_C",MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4040 #endif 4041 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4042 #if defined(PETSC_HAVE_ELEMENTAL) 4043 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4044 #endif 4045 #if defined(PETSC_HAVE_HYPRE) 4046 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4047 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4048 #endif 4049 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4050 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4051 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4052 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4053 ierr = PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_SeqAIJ);CHKERRQ(ierr); 4054 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4055 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4056 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4057 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4058 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4059 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4060 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4061 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4062 PetscFunctionReturn(0); 4063 } 4064 4065 /* 4066 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4067 */ 4068 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4069 { 4070 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4071 PetscErrorCode ierr; 4072 PetscInt i,m = A->rmap->n; 4073 4074 PetscFunctionBegin; 4075 c = (Mat_SeqAIJ*)C->data; 4076 4077 C->factortype = A->factortype; 4078 c->row = 0; 4079 c->col = 0; 4080 c->icol = 0; 4081 c->reallocs = 0; 4082 4083 C->assembled = PETSC_TRUE; 4084 4085 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4086 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4087 4088 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4089 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4090 for (i=0; i<m; i++) { 4091 c->imax[i] = a->imax[i]; 4092 c->ilen[i] = a->ilen[i]; 4093 } 4094 4095 /* allocate the matrix space */ 4096 if (mallocmatspace) { 4097 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4098 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4099 4100 c->singlemalloc = PETSC_TRUE; 4101 4102 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4103 if (m > 0) { 4104 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4105 if (cpvalues == MAT_COPY_VALUES) { 4106 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4107 } else { 4108 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4109 } 4110 } 4111 } 4112 4113 c->ignorezeroentries = a->ignorezeroentries; 4114 c->roworiented = a->roworiented; 4115 c->nonew = a->nonew; 4116 if (a->diag) { 4117 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4118 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4119 for (i=0; i<m; i++) { 4120 c->diag[i] = a->diag[i]; 4121 } 4122 } else c->diag = 0; 4123 4124 c->solve_work = 0; 4125 c->saved_values = 0; 4126 c->idiag = 0; 4127 c->ssor_work = 0; 4128 c->keepnonzeropattern = a->keepnonzeropattern; 4129 c->free_a = PETSC_TRUE; 4130 c->free_ij = PETSC_TRUE; 4131 4132 c->rmax = a->rmax; 4133 c->nz = a->nz; 4134 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4135 C->preallocated = PETSC_TRUE; 4136 4137 c->compressedrow.use = a->compressedrow.use; 4138 c->compressedrow.nrows = a->compressedrow.nrows; 4139 if (a->compressedrow.use) { 4140 i = a->compressedrow.nrows; 4141 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4142 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4143 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4144 } else { 4145 c->compressedrow.use = PETSC_FALSE; 4146 c->compressedrow.i = NULL; 4147 c->compressedrow.rindex = NULL; 4148 } 4149 c->nonzerorowcnt = a->nonzerorowcnt; 4150 C->nonzerostate = A->nonzerostate; 4151 4152 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4153 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4154 PetscFunctionReturn(0); 4155 } 4156 4157 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4158 { 4159 PetscErrorCode ierr; 4160 4161 PetscFunctionBegin; 4162 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4163 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4164 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4165 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4166 } 4167 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4168 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4169 PetscFunctionReturn(0); 4170 } 4171 4172 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4173 { 4174 Mat_SeqAIJ *a; 4175 PetscErrorCode ierr; 4176 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4177 int fd; 4178 PetscMPIInt size; 4179 MPI_Comm comm; 4180 PetscInt bs = newMat->rmap->bs; 4181 4182 PetscFunctionBegin; 4183 /* force binary viewer to load .info file if it has not yet done so */ 4184 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4185 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4186 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4187 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4188 4189 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4190 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4191 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4192 if (bs < 0) bs = 1; 4193 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4194 4195 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4196 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4197 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4198 M = header[1]; N = header[2]; nz = header[3]; 4199 4200 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4201 4202 /* read in row lengths */ 4203 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4204 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4205 4206 /* check if sum of rowlengths is same as nz */ 4207 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4208 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); 4209 4210 /* set global size if not set already*/ 4211 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4212 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4213 } else { 4214 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4215 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4216 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4217 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4218 } 4219 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); 4220 } 4221 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4222 a = (Mat_SeqAIJ*)newMat->data; 4223 4224 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4225 4226 /* read in nonzero values */ 4227 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4228 4229 /* set matrix "i" values */ 4230 a->i[0] = 0; 4231 for (i=1; i<= M; i++) { 4232 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4233 a->ilen[i-1] = rowlengths[i-1]; 4234 } 4235 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4236 4237 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4238 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4239 PetscFunctionReturn(0); 4240 } 4241 4242 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4243 { 4244 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4245 PetscErrorCode ierr; 4246 #if defined(PETSC_USE_COMPLEX) 4247 PetscInt k; 4248 #endif 4249 4250 PetscFunctionBegin; 4251 /* If the matrix dimensions are not equal,or no of nonzeros */ 4252 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4253 *flg = PETSC_FALSE; 4254 PetscFunctionReturn(0); 4255 } 4256 4257 /* if the a->i are the same */ 4258 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4259 if (!*flg) PetscFunctionReturn(0); 4260 4261 /* if a->j are the same */ 4262 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4263 if (!*flg) PetscFunctionReturn(0); 4264 4265 /* if a->a are the same */ 4266 #if defined(PETSC_USE_COMPLEX) 4267 for (k=0; k<a->nz; k++) { 4268 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4269 *flg = PETSC_FALSE; 4270 PetscFunctionReturn(0); 4271 } 4272 } 4273 #else 4274 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4275 #endif 4276 PetscFunctionReturn(0); 4277 } 4278 4279 /*@ 4280 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4281 provided by the user. 4282 4283 Collective on MPI_Comm 4284 4285 Input Parameters: 4286 + comm - must be an MPI communicator of size 1 4287 . m - number of rows 4288 . n - number of columns 4289 . i - row indices 4290 . j - column indices 4291 - a - matrix values 4292 4293 Output Parameter: 4294 . mat - the matrix 4295 4296 Level: intermediate 4297 4298 Notes: 4299 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4300 once the matrix is destroyed and not before 4301 4302 You cannot set new nonzero locations into this matrix, that will generate an error. 4303 4304 The i and j indices are 0 based 4305 4306 The format which is used for the sparse matrix input, is equivalent to a 4307 row-major ordering.. i.e for the following matrix, the input data expected is 4308 as shown 4309 4310 $ 1 0 0 4311 $ 2 0 3 4312 $ 4 5 6 4313 $ 4314 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4315 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4316 $ v = {1,2,3,4,5,6} [size = 6] 4317 4318 4319 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4320 4321 @*/ 4322 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4323 { 4324 PetscErrorCode ierr; 4325 PetscInt ii; 4326 Mat_SeqAIJ *aij; 4327 #if defined(PETSC_USE_DEBUG) 4328 PetscInt jj; 4329 #endif 4330 4331 PetscFunctionBegin; 4332 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4333 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4334 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4335 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4336 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4337 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4338 aij = (Mat_SeqAIJ*)(*mat)->data; 4339 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4340 4341 aij->i = i; 4342 aij->j = j; 4343 aij->a = a; 4344 aij->singlemalloc = PETSC_FALSE; 4345 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4346 aij->free_a = PETSC_FALSE; 4347 aij->free_ij = PETSC_FALSE; 4348 4349 for (ii=0; ii<m; ii++) { 4350 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4351 #if defined(PETSC_USE_DEBUG) 4352 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]); 4353 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4354 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); 4355 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); 4356 } 4357 #endif 4358 } 4359 #if defined(PETSC_USE_DEBUG) 4360 for (ii=0; ii<aij->i[m]; ii++) { 4361 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4362 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]); 4363 } 4364 #endif 4365 4366 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4367 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4368 PetscFunctionReturn(0); 4369 } 4370 /*@C 4371 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4372 provided by the user. 4373 4374 Collective on MPI_Comm 4375 4376 Input Parameters: 4377 + comm - must be an MPI communicator of size 1 4378 . m - number of rows 4379 . n - number of columns 4380 . i - row indices 4381 . j - column indices 4382 . a - matrix values 4383 . nz - number of nonzeros 4384 - idx - 0 or 1 based 4385 4386 Output Parameter: 4387 . mat - the matrix 4388 4389 Level: intermediate 4390 4391 Notes: 4392 The i and j indices are 0 based 4393 4394 The format which is used for the sparse matrix input, is equivalent to a 4395 row-major ordering.. i.e for the following matrix, the input data expected is 4396 as shown: 4397 4398 1 0 0 4399 2 0 3 4400 4 5 6 4401 4402 i = {0,1,1,2,2,2} 4403 j = {0,0,2,0,1,2} 4404 v = {1,2,3,4,5,6} 4405 4406 4407 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4408 4409 @*/ 4410 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4411 { 4412 PetscErrorCode ierr; 4413 PetscInt ii, *nnz, one = 1,row,col; 4414 4415 4416 PetscFunctionBegin; 4417 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4418 for (ii = 0; ii < nz; ii++) { 4419 nnz[i[ii] - !!idx] += 1; 4420 } 4421 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4422 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4423 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4424 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4425 for (ii = 0; ii < nz; ii++) { 4426 if (idx) { 4427 row = i[ii] - 1; 4428 col = j[ii] - 1; 4429 } else { 4430 row = i[ii]; 4431 col = j[ii]; 4432 } 4433 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4434 } 4435 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4436 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4437 ierr = PetscFree(nnz);CHKERRQ(ierr); 4438 PetscFunctionReturn(0); 4439 } 4440 4441 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4442 { 4443 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4444 PetscErrorCode ierr; 4445 4446 PetscFunctionBegin; 4447 a->idiagvalid = PETSC_FALSE; 4448 a->ibdiagvalid = PETSC_FALSE; 4449 4450 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4451 PetscFunctionReturn(0); 4452 } 4453 4454 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4455 { 4456 PetscErrorCode ierr; 4457 PetscMPIInt size; 4458 4459 PetscFunctionBegin; 4460 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4461 if (size == 1) { 4462 if (scall == MAT_INITIAL_MATRIX) { 4463 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4464 } else { 4465 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4466 } 4467 } else { 4468 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4469 } 4470 PetscFunctionReturn(0); 4471 } 4472 4473 /* 4474 Permute A into C's *local* index space using rowemb,colemb. 4475 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4476 of [0,m), colemb is in [0,n). 4477 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4478 */ 4479 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4480 { 4481 /* If making this function public, change the error returned in this function away from _PLIB. */ 4482 PetscErrorCode ierr; 4483 Mat_SeqAIJ *Baij; 4484 PetscBool seqaij; 4485 PetscInt m,n,*nz,i,j,count; 4486 PetscScalar v; 4487 const PetscInt *rowindices,*colindices; 4488 4489 PetscFunctionBegin; 4490 if (!B) PetscFunctionReturn(0); 4491 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4492 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4493 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4494 if (rowemb) { 4495 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4496 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); 4497 } else { 4498 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4499 } 4500 if (colemb) { 4501 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4502 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); 4503 } else { 4504 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4505 } 4506 4507 Baij = (Mat_SeqAIJ*)(B->data); 4508 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4509 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4510 for (i=0; i<B->rmap->n; i++) { 4511 nz[i] = Baij->i[i+1] - Baij->i[i]; 4512 } 4513 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4514 ierr = PetscFree(nz);CHKERRQ(ierr); 4515 } 4516 if (pattern == SUBSET_NONZERO_PATTERN) { 4517 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4518 } 4519 count = 0; 4520 rowindices = NULL; 4521 colindices = NULL; 4522 if (rowemb) { 4523 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4524 } 4525 if (colemb) { 4526 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4527 } 4528 for (i=0; i<B->rmap->n; i++) { 4529 PetscInt row; 4530 row = i; 4531 if (rowindices) row = rowindices[i]; 4532 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4533 PetscInt col; 4534 col = Baij->j[count]; 4535 if (colindices) col = colindices[col]; 4536 v = Baij->a[count]; 4537 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4538 ++count; 4539 } 4540 } 4541 /* FIXME: set C's nonzerostate correctly. */ 4542 /* Assembly for C is necessary. */ 4543 C->preallocated = PETSC_TRUE; 4544 C->assembled = PETSC_TRUE; 4545 C->was_assembled = PETSC_FALSE; 4546 PetscFunctionReturn(0); 4547 } 4548 4549 PetscFunctionList MatSeqAIJList = NULL; 4550 4551 /*@C 4552 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 4553 4554 Collective on Mat 4555 4556 Input Parameters: 4557 + mat - the matrix object 4558 - matype - matrix type 4559 4560 Options Database Key: 4561 . -mat_seqai_type <method> - for example seqaijcrl 4562 4563 4564 Level: intermediate 4565 4566 .keywords: Mat, MatType, set, method 4567 4568 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 4569 @*/ 4570 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 4571 { 4572 PetscErrorCode ierr,(*r)(Mat,const MatType,MatReuse,Mat*); 4573 PetscBool sametype; 4574 4575 PetscFunctionBegin; 4576 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 4577 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 4578 if (sametype) PetscFunctionReturn(0); 4579 4580 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 4581 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 4582 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 4583 PetscFunctionReturn(0); 4584 } 4585 4586 4587 /*@C 4588 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 4589 4590 Not Collective 4591 4592 Input Parameters: 4593 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 4594 - function - routine to convert to subtype 4595 4596 Notes: 4597 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 4598 4599 4600 Then, your matrix can be chosen with the procedural interface at runtime via the option 4601 $ -mat_seqaij_type my_mat 4602 4603 Level: advanced 4604 4605 .keywords: Mat, register 4606 4607 .seealso: MatSeqAIJRegisterAll() 4608 4609 4610 Level: advanced 4611 @*/ 4612 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,MatType,MatReuse,Mat *)) 4613 { 4614 PetscErrorCode ierr; 4615 4616 PetscFunctionBegin; 4617 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 4618 PetscFunctionReturn(0); 4619 } 4620 4621 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 4622 4623 /*@C 4624 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 4625 4626 Not Collective 4627 4628 Level: advanced 4629 4630 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 4631 4632 .keywords: KSP, register, all 4633 4634 .seealso: MatRegisterAll(), MatSeqAIJRegister() 4635 @*/ 4636 PetscErrorCode MatSeqAIJRegisterAll(void) 4637 { 4638 PetscErrorCode ierr; 4639 4640 PetscFunctionBegin; 4641 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 4642 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 4643 4644 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4645 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4646 #if defined(PETSC_HAVE_MKL) 4647 ierr = MatSeqAIJRegister(MATSEQAIJMKL, MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4648 #endif 4649 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4650 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 4651 #endif 4652 PetscFunctionReturn(0); 4653 } 4654 4655 /* 4656 Special version for direct calls from Fortran 4657 */ 4658 #include <petsc/private/fortranimpl.h> 4659 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4660 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4661 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4662 #define matsetvaluesseqaij_ matsetvaluesseqaij 4663 #endif 4664 4665 /* Change these macros so can be used in void function */ 4666 #undef CHKERRQ 4667 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4668 #undef SETERRQ2 4669 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4670 #undef SETERRQ3 4671 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4672 4673 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) 4674 { 4675 Mat A = *AA; 4676 PetscInt m = *mm, n = *nn; 4677 InsertMode is = *isis; 4678 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4679 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4680 PetscInt *imax,*ai,*ailen; 4681 PetscErrorCode ierr; 4682 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4683 MatScalar *ap,value,*aa; 4684 PetscBool ignorezeroentries = a->ignorezeroentries; 4685 PetscBool roworiented = a->roworiented; 4686 4687 PetscFunctionBegin; 4688 MatCheckPreallocated(A,1); 4689 imax = a->imax; 4690 ai = a->i; 4691 ailen = a->ilen; 4692 aj = a->j; 4693 aa = a->a; 4694 4695 for (k=0; k<m; k++) { /* loop over added rows */ 4696 row = im[k]; 4697 if (row < 0) continue; 4698 #if defined(PETSC_USE_DEBUG) 4699 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4700 #endif 4701 rp = aj + ai[row]; ap = aa + ai[row]; 4702 rmax = imax[row]; nrow = ailen[row]; 4703 low = 0; 4704 high = nrow; 4705 for (l=0; l<n; l++) { /* loop over added columns */ 4706 if (in[l] < 0) continue; 4707 #if defined(PETSC_USE_DEBUG) 4708 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4709 #endif 4710 col = in[l]; 4711 if (roworiented) value = v[l + k*n]; 4712 else value = v[k + l*m]; 4713 4714 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4715 4716 if (col <= lastcol) low = 0; 4717 else high = nrow; 4718 lastcol = col; 4719 while (high-low > 5) { 4720 t = (low+high)/2; 4721 if (rp[t] > col) high = t; 4722 else low = t; 4723 } 4724 for (i=low; i<high; i++) { 4725 if (rp[i] > col) break; 4726 if (rp[i] == col) { 4727 if (is == ADD_VALUES) ap[i] += value; 4728 else ap[i] = value; 4729 goto noinsert; 4730 } 4731 } 4732 if (value == 0.0 && ignorezeroentries) goto noinsert; 4733 if (nonew == 1) goto noinsert; 4734 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4735 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4736 N = nrow++ - 1; a->nz++; high++; 4737 /* shift up all the later entries in this row */ 4738 for (ii=N; ii>=i; ii--) { 4739 rp[ii+1] = rp[ii]; 4740 ap[ii+1] = ap[ii]; 4741 } 4742 rp[i] = col; 4743 ap[i] = value; 4744 A->nonzerostate++; 4745 noinsert:; 4746 low = i + 1; 4747 } 4748 ailen[row] = nrow; 4749 } 4750 PetscFunctionReturnVoid(); 4751 } 4752 4753