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