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 MatDestroySubMatrices_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 MatDestroy_SeqAIJ_Submatrices(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 = MatDestroySubMatrices_Private(submatj);CHKERRQ(ierr); 2526 PetscFunctionReturn(0); 2527 } 2528 2529 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2530 { 2531 PetscErrorCode ierr; 2532 PetscInt i; 2533 2534 PetscFunctionBegin; 2535 if (scall == MAT_INITIAL_MATRIX) { 2536 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2537 } 2538 2539 for (i=0; i<n; i++) { 2540 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2541 } 2542 PetscFunctionReturn(0); 2543 } 2544 2545 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2546 { 2547 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2548 PetscErrorCode ierr; 2549 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2550 const PetscInt *idx; 2551 PetscInt start,end,*ai,*aj; 2552 PetscBT table; 2553 2554 PetscFunctionBegin; 2555 m = A->rmap->n; 2556 ai = a->i; 2557 aj = a->j; 2558 2559 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2560 2561 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2562 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2563 2564 for (i=0; i<is_max; i++) { 2565 /* Initialize the two local arrays */ 2566 isz = 0; 2567 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2568 2569 /* Extract the indices, assume there can be duplicate entries */ 2570 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2571 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2572 2573 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2574 for (j=0; j<n; ++j) { 2575 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2576 } 2577 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2578 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2579 2580 k = 0; 2581 for (j=0; j<ov; j++) { /* for each overlap */ 2582 n = isz; 2583 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2584 row = nidx[k]; 2585 start = ai[row]; 2586 end = ai[row+1]; 2587 for (l = start; l<end; l++) { 2588 val = aj[l]; 2589 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2590 } 2591 } 2592 } 2593 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2594 } 2595 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2596 ierr = PetscFree(nidx);CHKERRQ(ierr); 2597 PetscFunctionReturn(0); 2598 } 2599 2600 /* -------------------------------------------------------------- */ 2601 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2602 { 2603 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2604 PetscErrorCode ierr; 2605 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2606 const PetscInt *row,*col; 2607 PetscInt *cnew,j,*lens; 2608 IS icolp,irowp; 2609 PetscInt *cwork = NULL; 2610 PetscScalar *vwork = NULL; 2611 2612 PetscFunctionBegin; 2613 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2614 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2615 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2616 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2617 2618 /* determine lengths of permuted rows */ 2619 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2620 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2621 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2622 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2623 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2624 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2625 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2626 ierr = PetscFree(lens);CHKERRQ(ierr); 2627 2628 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2629 for (i=0; i<m; i++) { 2630 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2631 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2632 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2633 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2634 } 2635 ierr = PetscFree(cnew);CHKERRQ(ierr); 2636 2637 (*B)->assembled = PETSC_FALSE; 2638 2639 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2640 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2641 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2642 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2643 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2644 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2645 PetscFunctionReturn(0); 2646 } 2647 2648 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2649 { 2650 PetscErrorCode ierr; 2651 2652 PetscFunctionBegin; 2653 /* If the two matrices have the same copy implementation, use fast copy. */ 2654 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2655 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2656 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2657 2658 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"); 2659 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2660 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 2661 } else { 2662 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2663 } 2664 PetscFunctionReturn(0); 2665 } 2666 2667 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2668 { 2669 PetscErrorCode ierr; 2670 2671 PetscFunctionBegin; 2672 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2673 PetscFunctionReturn(0); 2674 } 2675 2676 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2677 { 2678 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2679 2680 PetscFunctionBegin; 2681 *array = a->a; 2682 PetscFunctionReturn(0); 2683 } 2684 2685 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2686 { 2687 PetscFunctionBegin; 2688 PetscFunctionReturn(0); 2689 } 2690 2691 /* 2692 Computes the number of nonzeros per row needed for preallocation when X and Y 2693 have different nonzero structure. 2694 */ 2695 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2696 { 2697 PetscInt i,j,k,nzx,nzy; 2698 2699 PetscFunctionBegin; 2700 /* Set the number of nonzeros in the new matrix */ 2701 for (i=0; i<m; i++) { 2702 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2703 nzx = xi[i+1] - xi[i]; 2704 nzy = yi[i+1] - yi[i]; 2705 nnz[i] = 0; 2706 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2707 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2708 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2709 nnz[i]++; 2710 } 2711 for (; k<nzy; k++) nnz[i]++; 2712 } 2713 PetscFunctionReturn(0); 2714 } 2715 2716 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2717 { 2718 PetscInt m = Y->rmap->N; 2719 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2720 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2721 PetscErrorCode ierr; 2722 2723 PetscFunctionBegin; 2724 /* Set the number of nonzeros in the new matrix */ 2725 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2726 PetscFunctionReturn(0); 2727 } 2728 2729 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2730 { 2731 PetscErrorCode ierr; 2732 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2733 PetscBLASInt one=1,bnz; 2734 2735 PetscFunctionBegin; 2736 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2737 if (str == SAME_NONZERO_PATTERN) { 2738 PetscScalar alpha = a; 2739 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2740 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2741 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2742 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2743 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2744 } else { 2745 Mat B; 2746 PetscInt *nnz; 2747 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2748 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2749 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2750 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2751 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2752 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2753 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2754 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2755 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2756 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2757 ierr = PetscFree(nnz);CHKERRQ(ierr); 2758 } 2759 PetscFunctionReturn(0); 2760 } 2761 2762 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2763 { 2764 #if defined(PETSC_USE_COMPLEX) 2765 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2766 PetscInt i,nz; 2767 PetscScalar *a; 2768 2769 PetscFunctionBegin; 2770 nz = aij->nz; 2771 a = aij->a; 2772 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2773 #else 2774 PetscFunctionBegin; 2775 #endif 2776 PetscFunctionReturn(0); 2777 } 2778 2779 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2780 { 2781 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2782 PetscErrorCode ierr; 2783 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2784 PetscReal atmp; 2785 PetscScalar *x; 2786 MatScalar *aa; 2787 2788 PetscFunctionBegin; 2789 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2790 aa = a->a; 2791 ai = a->i; 2792 aj = a->j; 2793 2794 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2795 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2796 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2797 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2798 for (i=0; i<m; i++) { 2799 ncols = ai[1] - ai[0]; ai++; 2800 x[i] = 0.0; 2801 for (j=0; j<ncols; j++) { 2802 atmp = PetscAbsScalar(*aa); 2803 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2804 aa++; aj++; 2805 } 2806 } 2807 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2808 PetscFunctionReturn(0); 2809 } 2810 2811 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2812 { 2813 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2814 PetscErrorCode ierr; 2815 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2816 PetscScalar *x; 2817 MatScalar *aa; 2818 2819 PetscFunctionBegin; 2820 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2821 aa = a->a; 2822 ai = a->i; 2823 aj = a->j; 2824 2825 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2826 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2827 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2828 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2829 for (i=0; i<m; i++) { 2830 ncols = ai[1] - ai[0]; ai++; 2831 if (ncols == A->cmap->n) { /* row is dense */ 2832 x[i] = *aa; if (idx) idx[i] = 0; 2833 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2834 x[i] = 0.0; 2835 if (idx) { 2836 idx[i] = 0; /* in case ncols is zero */ 2837 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2838 if (aj[j] > j) { 2839 idx[i] = j; 2840 break; 2841 } 2842 } 2843 } 2844 } 2845 for (j=0; j<ncols; j++) { 2846 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2847 aa++; aj++; 2848 } 2849 } 2850 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2851 PetscFunctionReturn(0); 2852 } 2853 2854 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2855 { 2856 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2857 PetscErrorCode ierr; 2858 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2859 PetscReal atmp; 2860 PetscScalar *x; 2861 MatScalar *aa; 2862 2863 PetscFunctionBegin; 2864 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2865 aa = a->a; 2866 ai = a->i; 2867 aj = a->j; 2868 2869 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2870 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2871 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2872 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); 2873 for (i=0; i<m; i++) { 2874 ncols = ai[1] - ai[0]; ai++; 2875 if (ncols) { 2876 /* Get first nonzero */ 2877 for (j = 0; j < ncols; j++) { 2878 atmp = PetscAbsScalar(aa[j]); 2879 if (atmp > 1.0e-12) { 2880 x[i] = atmp; 2881 if (idx) idx[i] = aj[j]; 2882 break; 2883 } 2884 } 2885 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 2886 } else { 2887 x[i] = 0.0; if (idx) idx[i] = 0; 2888 } 2889 for (j = 0; j < ncols; j++) { 2890 atmp = PetscAbsScalar(*aa); 2891 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2892 aa++; aj++; 2893 } 2894 } 2895 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2896 PetscFunctionReturn(0); 2897 } 2898 2899 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2900 { 2901 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2902 PetscErrorCode ierr; 2903 PetscInt i,j,m = A->rmap->n,ncols,n; 2904 const PetscInt *ai,*aj; 2905 PetscScalar *x; 2906 const MatScalar *aa; 2907 2908 PetscFunctionBegin; 2909 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2910 aa = a->a; 2911 ai = a->i; 2912 aj = a->j; 2913 2914 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2915 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2916 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2917 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2918 for (i=0; i<m; i++) { 2919 ncols = ai[1] - ai[0]; ai++; 2920 if (ncols == A->cmap->n) { /* row is dense */ 2921 x[i] = *aa; if (idx) idx[i] = 0; 2922 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2923 x[i] = 0.0; 2924 if (idx) { /* find first implicit 0.0 in the row */ 2925 idx[i] = 0; /* in case ncols is zero */ 2926 for (j=0; j<ncols; j++) { 2927 if (aj[j] > j) { 2928 idx[i] = j; 2929 break; 2930 } 2931 } 2932 } 2933 } 2934 for (j=0; j<ncols; j++) { 2935 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2936 aa++; aj++; 2937 } 2938 } 2939 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2940 PetscFunctionReturn(0); 2941 } 2942 2943 #include <petscblaslapack.h> 2944 #include <petsc/private/kernels/blockinvert.h> 2945 2946 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 2947 { 2948 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 2949 PetscErrorCode ierr; 2950 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 2951 MatScalar *diag,work[25],*v_work; 2952 PetscReal shift = 0.0; 2953 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 2954 2955 PetscFunctionBegin; 2956 allowzeropivot = PetscNot(A->erroriffailure); 2957 if (a->ibdiagvalid) { 2958 if (values) *values = a->ibdiag; 2959 PetscFunctionReturn(0); 2960 } 2961 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 2962 if (!a->ibdiag) { 2963 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 2964 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 2965 } 2966 diag = a->ibdiag; 2967 if (values) *values = a->ibdiag; 2968 /* factor and invert each block */ 2969 switch (bs) { 2970 case 1: 2971 for (i=0; i<mbs; i++) { 2972 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 2973 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 2974 if (allowzeropivot) { 2975 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2976 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 2977 A->factorerror_zeropivot_row = i; 2978 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 2979 } 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); 2980 } 2981 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 2982 } 2983 break; 2984 case 2: 2985 for (i=0; i<mbs; i++) { 2986 ij[0] = 2*i; ij[1] = 2*i + 1; 2987 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 2988 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 2989 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2990 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 2991 diag += 4; 2992 } 2993 break; 2994 case 3: 2995 for (i=0; i<mbs; i++) { 2996 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 2997 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 2998 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 2999 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3000 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3001 diag += 9; 3002 } 3003 break; 3004 case 4: 3005 for (i=0; i<mbs; i++) { 3006 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3007 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3008 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3009 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3010 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3011 diag += 16; 3012 } 3013 break; 3014 case 5: 3015 for (i=0; i<mbs; i++) { 3016 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3017 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3018 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3019 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3020 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3021 diag += 25; 3022 } 3023 break; 3024 case 6: 3025 for (i=0; i<mbs; i++) { 3026 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; 3027 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3028 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3029 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3030 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3031 diag += 36; 3032 } 3033 break; 3034 case 7: 3035 for (i=0; i<mbs; i++) { 3036 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; 3037 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3038 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3039 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3040 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3041 diag += 49; 3042 } 3043 break; 3044 default: 3045 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3046 for (i=0; i<mbs; i++) { 3047 for (j=0; j<bs; j++) { 3048 IJ[j] = bs*i + j; 3049 } 3050 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3051 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3052 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3053 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3054 diag += bs2; 3055 } 3056 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3057 } 3058 a->ibdiagvalid = PETSC_TRUE; 3059 PetscFunctionReturn(0); 3060 } 3061 3062 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3063 { 3064 PetscErrorCode ierr; 3065 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3066 PetscScalar a; 3067 PetscInt m,n,i,j,col; 3068 3069 PetscFunctionBegin; 3070 if (!x->assembled) { 3071 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3072 for (i=0; i<m; i++) { 3073 for (j=0; j<aij->imax[i]; j++) { 3074 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3075 col = (PetscInt)(n*PetscRealPart(a)); 3076 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3077 } 3078 } 3079 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3080 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3081 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3082 PetscFunctionReturn(0); 3083 } 3084 3085 PetscErrorCode MatShift_SeqAIJ(Mat Y,PetscScalar a) 3086 { 3087 PetscErrorCode ierr; 3088 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)Y->data; 3089 3090 PetscFunctionBegin; 3091 if (!Y->preallocated || !aij->nz) { 3092 ierr = MatSeqAIJSetPreallocation(Y,1,NULL);CHKERRQ(ierr); 3093 } 3094 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 3095 PetscFunctionReturn(0); 3096 } 3097 3098 /* -------------------------------------------------------------------*/ 3099 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3100 MatGetRow_SeqAIJ, 3101 MatRestoreRow_SeqAIJ, 3102 MatMult_SeqAIJ, 3103 /* 4*/ MatMultAdd_SeqAIJ, 3104 MatMultTranspose_SeqAIJ, 3105 MatMultTransposeAdd_SeqAIJ, 3106 0, 3107 0, 3108 0, 3109 /* 10*/ 0, 3110 MatLUFactor_SeqAIJ, 3111 0, 3112 MatSOR_SeqAIJ, 3113 MatTranspose_SeqAIJ, 3114 /*1 5*/ MatGetInfo_SeqAIJ, 3115 MatEqual_SeqAIJ, 3116 MatGetDiagonal_SeqAIJ, 3117 MatDiagonalScale_SeqAIJ, 3118 MatNorm_SeqAIJ, 3119 /* 20*/ 0, 3120 MatAssemblyEnd_SeqAIJ, 3121 MatSetOption_SeqAIJ, 3122 MatZeroEntries_SeqAIJ, 3123 /* 24*/ MatZeroRows_SeqAIJ, 3124 0, 3125 0, 3126 0, 3127 0, 3128 /* 29*/ MatSetUp_SeqAIJ, 3129 0, 3130 0, 3131 0, 3132 0, 3133 /* 34*/ MatDuplicate_SeqAIJ, 3134 0, 3135 0, 3136 MatILUFactor_SeqAIJ, 3137 0, 3138 /* 39*/ MatAXPY_SeqAIJ, 3139 MatCreateSubMatrices_SeqAIJ, 3140 MatIncreaseOverlap_SeqAIJ, 3141 MatGetValues_SeqAIJ, 3142 MatCopy_SeqAIJ, 3143 /* 44*/ MatGetRowMax_SeqAIJ, 3144 MatScale_SeqAIJ, 3145 MatShift_SeqAIJ, 3146 MatDiagonalSet_SeqAIJ, 3147 MatZeroRowsColumns_SeqAIJ, 3148 /* 49*/ MatSetRandom_SeqAIJ, 3149 MatGetRowIJ_SeqAIJ, 3150 MatRestoreRowIJ_SeqAIJ, 3151 MatGetColumnIJ_SeqAIJ, 3152 MatRestoreColumnIJ_SeqAIJ, 3153 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3154 0, 3155 0, 3156 MatPermute_SeqAIJ, 3157 0, 3158 /* 59*/ 0, 3159 MatDestroy_SeqAIJ, 3160 MatView_SeqAIJ, 3161 0, 3162 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3163 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3164 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3165 0, 3166 0, 3167 0, 3168 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3169 MatGetRowMinAbs_SeqAIJ, 3170 0, 3171 0, 3172 0, 3173 /* 74*/ 0, 3174 MatFDColoringApply_AIJ, 3175 0, 3176 0, 3177 0, 3178 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3179 0, 3180 0, 3181 0, 3182 MatLoad_SeqAIJ, 3183 /* 84*/ MatIsSymmetric_SeqAIJ, 3184 MatIsHermitian_SeqAIJ, 3185 0, 3186 0, 3187 0, 3188 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3189 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3190 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3191 MatPtAP_SeqAIJ_SeqAIJ, 3192 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3193 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3194 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3195 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3196 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3197 0, 3198 /* 99*/ 0, 3199 0, 3200 0, 3201 MatConjugate_SeqAIJ, 3202 0, 3203 /*104*/ MatSetValuesRow_SeqAIJ, 3204 MatRealPart_SeqAIJ, 3205 MatImaginaryPart_SeqAIJ, 3206 0, 3207 0, 3208 /*109*/ MatMatSolve_SeqAIJ, 3209 0, 3210 MatGetRowMin_SeqAIJ, 3211 0, 3212 MatMissingDiagonal_SeqAIJ, 3213 /*114*/ 0, 3214 0, 3215 0, 3216 0, 3217 0, 3218 /*119*/ 0, 3219 0, 3220 0, 3221 0, 3222 MatGetMultiProcBlock_SeqAIJ, 3223 /*124*/ MatFindNonzeroRows_SeqAIJ, 3224 MatGetColumnNorms_SeqAIJ, 3225 MatInvertBlockDiagonal_SeqAIJ, 3226 0, 3227 0, 3228 /*129*/ 0, 3229 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3230 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3231 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3232 MatTransposeColoringCreate_SeqAIJ, 3233 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3234 MatTransColoringApplyDenToSp_SeqAIJ, 3235 MatRARt_SeqAIJ_SeqAIJ, 3236 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3237 MatRARtNumeric_SeqAIJ_SeqAIJ, 3238 /*139*/0, 3239 0, 3240 0, 3241 MatFDColoringSetUp_SeqXAIJ, 3242 MatFindOffBlockDiagonalEntries_SeqAIJ, 3243 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ 3244 }; 3245 3246 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3247 { 3248 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3249 PetscInt i,nz,n; 3250 3251 PetscFunctionBegin; 3252 nz = aij->maxnz; 3253 n = mat->rmap->n; 3254 for (i=0; i<nz; i++) { 3255 aij->j[i] = indices[i]; 3256 } 3257 aij->nz = nz; 3258 for (i=0; i<n; i++) { 3259 aij->ilen[i] = aij->imax[i]; 3260 } 3261 PetscFunctionReturn(0); 3262 } 3263 3264 /*@ 3265 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3266 in the matrix. 3267 3268 Input Parameters: 3269 + mat - the SeqAIJ matrix 3270 - indices - the column indices 3271 3272 Level: advanced 3273 3274 Notes: 3275 This can be called if you have precomputed the nonzero structure of the 3276 matrix and want to provide it to the matrix object to improve the performance 3277 of the MatSetValues() operation. 3278 3279 You MUST have set the correct numbers of nonzeros per row in the call to 3280 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3281 3282 MUST be called before any calls to MatSetValues(); 3283 3284 The indices should start with zero, not one. 3285 3286 @*/ 3287 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3288 { 3289 PetscErrorCode ierr; 3290 3291 PetscFunctionBegin; 3292 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3293 PetscValidPointer(indices,2); 3294 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3295 PetscFunctionReturn(0); 3296 } 3297 3298 /* ----------------------------------------------------------------------------------------*/ 3299 3300 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3301 { 3302 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3303 PetscErrorCode ierr; 3304 size_t nz = aij->i[mat->rmap->n]; 3305 3306 PetscFunctionBegin; 3307 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3308 3309 /* allocate space for values if not already there */ 3310 if (!aij->saved_values) { 3311 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3312 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3313 } 3314 3315 /* copy values over */ 3316 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3317 PetscFunctionReturn(0); 3318 } 3319 3320 /*@ 3321 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3322 example, reuse of the linear part of a Jacobian, while recomputing the 3323 nonlinear portion. 3324 3325 Collect on Mat 3326 3327 Input Parameters: 3328 . mat - the matrix (currently only AIJ matrices support this option) 3329 3330 Level: advanced 3331 3332 Common Usage, with SNESSolve(): 3333 $ Create Jacobian matrix 3334 $ Set linear terms into matrix 3335 $ Apply boundary conditions to matrix, at this time matrix must have 3336 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3337 $ boundary conditions again will not change the nonzero structure 3338 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3339 $ ierr = MatStoreValues(mat); 3340 $ Call SNESSetJacobian() with matrix 3341 $ In your Jacobian routine 3342 $ ierr = MatRetrieveValues(mat); 3343 $ Set nonlinear terms in matrix 3344 3345 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3346 $ // build linear portion of Jacobian 3347 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3348 $ ierr = MatStoreValues(mat); 3349 $ loop over nonlinear iterations 3350 $ ierr = MatRetrieveValues(mat); 3351 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3352 $ // call MatAssemblyBegin/End() on matrix 3353 $ Solve linear system with Jacobian 3354 $ endloop 3355 3356 Notes: 3357 Matrix must already be assemblied before calling this routine 3358 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3359 calling this routine. 3360 3361 When this is called multiple times it overwrites the previous set of stored values 3362 and does not allocated additional space. 3363 3364 .seealso: MatRetrieveValues() 3365 3366 @*/ 3367 PetscErrorCode MatStoreValues(Mat mat) 3368 { 3369 PetscErrorCode ierr; 3370 3371 PetscFunctionBegin; 3372 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3373 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3374 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3375 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3376 PetscFunctionReturn(0); 3377 } 3378 3379 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3380 { 3381 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3382 PetscErrorCode ierr; 3383 PetscInt nz = aij->i[mat->rmap->n]; 3384 3385 PetscFunctionBegin; 3386 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3387 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3388 /* copy values over */ 3389 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3390 PetscFunctionReturn(0); 3391 } 3392 3393 /*@ 3394 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3395 example, reuse of the linear part of a Jacobian, while recomputing the 3396 nonlinear portion. 3397 3398 Collect on Mat 3399 3400 Input Parameters: 3401 . mat - the matrix (currently only AIJ matrices support this option) 3402 3403 Level: advanced 3404 3405 .seealso: MatStoreValues() 3406 3407 @*/ 3408 PetscErrorCode MatRetrieveValues(Mat mat) 3409 { 3410 PetscErrorCode ierr; 3411 3412 PetscFunctionBegin; 3413 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3414 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3415 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3416 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3417 PetscFunctionReturn(0); 3418 } 3419 3420 3421 /* --------------------------------------------------------------------------------*/ 3422 /*@C 3423 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3424 (the default parallel PETSc format). For good matrix assembly performance 3425 the user should preallocate the matrix storage by setting the parameter nz 3426 (or the array nnz). By setting these parameters accurately, performance 3427 during matrix assembly can be increased by more than a factor of 50. 3428 3429 Collective on MPI_Comm 3430 3431 Input Parameters: 3432 + comm - MPI communicator, set to PETSC_COMM_SELF 3433 . m - number of rows 3434 . n - number of columns 3435 . nz - number of nonzeros per row (same for all rows) 3436 - nnz - array containing the number of nonzeros in the various rows 3437 (possibly different for each row) or NULL 3438 3439 Output Parameter: 3440 . A - the matrix 3441 3442 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3443 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3444 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3445 3446 Notes: 3447 If nnz is given then nz is ignored 3448 3449 The AIJ format (also called the Yale sparse matrix format or 3450 compressed row storage), is fully compatible with standard Fortran 77 3451 storage. That is, the stored row and column indices can begin at 3452 either one (as in Fortran) or zero. See the users' manual for details. 3453 3454 Specify the preallocated storage with either nz or nnz (not both). 3455 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3456 allocation. For large problems you MUST preallocate memory or you 3457 will get TERRIBLE performance, see the users' manual chapter on matrices. 3458 3459 By default, this format uses inodes (identical nodes) when possible, to 3460 improve numerical efficiency of matrix-vector products and solves. We 3461 search for consecutive rows with the same nonzero structure, thereby 3462 reusing matrix information to achieve increased efficiency. 3463 3464 Options Database Keys: 3465 + -mat_no_inode - Do not use inodes 3466 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3467 3468 Level: intermediate 3469 3470 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3471 3472 @*/ 3473 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3474 { 3475 PetscErrorCode ierr; 3476 3477 PetscFunctionBegin; 3478 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3479 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3480 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3481 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3482 PetscFunctionReturn(0); 3483 } 3484 3485 /*@C 3486 MatSeqAIJSetPreallocation - For good matrix assembly performance 3487 the user should preallocate the matrix storage by setting the parameter nz 3488 (or the array nnz). By setting these parameters accurately, performance 3489 during matrix assembly can be increased by more than a factor of 50. 3490 3491 Collective on MPI_Comm 3492 3493 Input Parameters: 3494 + B - The matrix 3495 . nz - number of nonzeros per row (same for all rows) 3496 - nnz - array containing the number of nonzeros in the various rows 3497 (possibly different for each row) or NULL 3498 3499 Notes: 3500 If nnz is given then nz is ignored 3501 3502 The AIJ format (also called the Yale sparse matrix format or 3503 compressed row storage), is fully compatible with standard Fortran 77 3504 storage. That is, the stored row and column indices can begin at 3505 either one (as in Fortran) or zero. See the users' manual for details. 3506 3507 Specify the preallocated storage with either nz or nnz (not both). 3508 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3509 allocation. For large problems you MUST preallocate memory or you 3510 will get TERRIBLE performance, see the users' manual chapter on matrices. 3511 3512 You can call MatGetInfo() to get information on how effective the preallocation was; 3513 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3514 You can also run with the option -info and look for messages with the string 3515 malloc in them to see if additional memory allocation was needed. 3516 3517 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3518 entries or columns indices 3519 3520 By default, this format uses inodes (identical nodes) when possible, to 3521 improve numerical efficiency of matrix-vector products and solves. We 3522 search for consecutive rows with the same nonzero structure, thereby 3523 reusing matrix information to achieve increased efficiency. 3524 3525 Options Database Keys: 3526 + -mat_no_inode - Do not use inodes 3527 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3528 - -mat_aij_oneindex - Internally use indexing starting at 1 3529 rather than 0. Note that when calling MatSetValues(), 3530 the user still MUST index entries starting at 0! 3531 3532 Level: intermediate 3533 3534 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3535 3536 @*/ 3537 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3538 { 3539 PetscErrorCode ierr; 3540 3541 PetscFunctionBegin; 3542 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3543 PetscValidType(B,1); 3544 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3545 PetscFunctionReturn(0); 3546 } 3547 3548 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3549 { 3550 Mat_SeqAIJ *b; 3551 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3552 PetscErrorCode ierr; 3553 PetscInt i; 3554 3555 PetscFunctionBegin; 3556 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3557 if (nz == MAT_SKIP_ALLOCATION) { 3558 skipallocation = PETSC_TRUE; 3559 nz = 0; 3560 } 3561 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3562 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3563 3564 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3565 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3566 if (nnz) { 3567 for (i=0; i<B->rmap->n; i++) { 3568 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]); 3569 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); 3570 } 3571 } 3572 3573 B->preallocated = PETSC_TRUE; 3574 3575 b = (Mat_SeqAIJ*)B->data; 3576 3577 if (!skipallocation) { 3578 if (!b->imax) { 3579 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3580 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3581 } 3582 if (!nnz) { 3583 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3584 else if (nz < 0) nz = 1; 3585 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3586 nz = nz*B->rmap->n; 3587 } else { 3588 nz = 0; 3589 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3590 } 3591 /* b->ilen will count nonzeros in each row so far. */ 3592 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3593 3594 /* allocate the matrix space */ 3595 /* FIXME: should B's old memory be unlogged? */ 3596 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3597 if (B->structure_only) { 3598 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3599 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3600 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3601 } else { 3602 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3603 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3604 } 3605 b->i[0] = 0; 3606 for (i=1; i<B->rmap->n+1; i++) { 3607 b->i[i] = b->i[i-1] + b->imax[i-1]; 3608 } 3609 if (B->structure_only) { 3610 b->singlemalloc = PETSC_FALSE; 3611 b->free_a = PETSC_FALSE; 3612 } else { 3613 b->singlemalloc = PETSC_TRUE; 3614 b->free_a = PETSC_TRUE; 3615 } 3616 b->free_ij = PETSC_TRUE; 3617 } else { 3618 b->free_a = PETSC_FALSE; 3619 b->free_ij = PETSC_FALSE; 3620 } 3621 3622 b->nz = 0; 3623 b->maxnz = nz; 3624 B->info.nz_unneeded = (double)b->maxnz; 3625 if (realalloc) { 3626 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3627 } 3628 B->was_assembled = PETSC_FALSE; 3629 B->assembled = PETSC_FALSE; 3630 PetscFunctionReturn(0); 3631 } 3632 3633 /*@ 3634 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3635 3636 Input Parameters: 3637 + B - the matrix 3638 . i - the indices into j for the start of each row (starts with zero) 3639 . j - the column indices for each row (starts with zero) these must be sorted for each row 3640 - v - optional values in the matrix 3641 3642 Level: developer 3643 3644 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3645 3646 .keywords: matrix, aij, compressed row, sparse, sequential 3647 3648 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3649 @*/ 3650 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3651 { 3652 PetscErrorCode ierr; 3653 3654 PetscFunctionBegin; 3655 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3656 PetscValidType(B,1); 3657 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3658 PetscFunctionReturn(0); 3659 } 3660 3661 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3662 { 3663 PetscInt i; 3664 PetscInt m,n; 3665 PetscInt nz; 3666 PetscInt *nnz, nz_max = 0; 3667 PetscScalar *values; 3668 PetscErrorCode ierr; 3669 3670 PetscFunctionBegin; 3671 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3672 3673 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3674 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3675 3676 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3677 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 3678 for (i = 0; i < m; i++) { 3679 nz = Ii[i+1]- Ii[i]; 3680 nz_max = PetscMax(nz_max, nz); 3681 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3682 nnz[i] = nz; 3683 } 3684 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3685 ierr = PetscFree(nnz);CHKERRQ(ierr); 3686 3687 if (v) { 3688 values = (PetscScalar*) v; 3689 } else { 3690 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3691 } 3692 3693 for (i = 0; i < m; i++) { 3694 nz = Ii[i+1] - Ii[i]; 3695 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3696 } 3697 3698 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3699 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3700 3701 if (!v) { 3702 ierr = PetscFree(values);CHKERRQ(ierr); 3703 } 3704 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3705 PetscFunctionReturn(0); 3706 } 3707 3708 #include <../src/mat/impls/dense/seq/dense.h> 3709 #include <petsc/private/kernels/petscaxpy.h> 3710 3711 /* 3712 Computes (B'*A')' since computing B*A directly is untenable 3713 3714 n p p 3715 ( ) ( ) ( ) 3716 m ( A ) * n ( B ) = m ( C ) 3717 ( ) ( ) ( ) 3718 3719 */ 3720 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3721 { 3722 PetscErrorCode ierr; 3723 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3724 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3725 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3726 PetscInt i,n,m,q,p; 3727 const PetscInt *ii,*idx; 3728 const PetscScalar *b,*a,*a_q; 3729 PetscScalar *c,*c_q; 3730 3731 PetscFunctionBegin; 3732 m = A->rmap->n; 3733 n = A->cmap->n; 3734 p = B->cmap->n; 3735 a = sub_a->v; 3736 b = sub_b->a; 3737 c = sub_c->v; 3738 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3739 3740 ii = sub_b->i; 3741 idx = sub_b->j; 3742 for (i=0; i<n; i++) { 3743 q = ii[i+1] - ii[i]; 3744 while (q-->0) { 3745 c_q = c + m*(*idx); 3746 a_q = a + m*i; 3747 PetscKernelAXPY(c_q,*b,a_q,m); 3748 idx++; 3749 b++; 3750 } 3751 } 3752 PetscFunctionReturn(0); 3753 } 3754 3755 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3756 { 3757 PetscErrorCode ierr; 3758 PetscInt m=A->rmap->n,n=B->cmap->n; 3759 Mat Cmat; 3760 3761 PetscFunctionBegin; 3762 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); 3763 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3764 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3765 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3766 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3767 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3768 3769 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3770 3771 *C = Cmat; 3772 PetscFunctionReturn(0); 3773 } 3774 3775 /* ----------------------------------------------------------------*/ 3776 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3777 { 3778 PetscErrorCode ierr; 3779 3780 PetscFunctionBegin; 3781 if (scall == MAT_INITIAL_MATRIX) { 3782 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3783 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3784 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3785 } 3786 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3787 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3788 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3789 PetscFunctionReturn(0); 3790 } 3791 3792 3793 /*MC 3794 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3795 based on compressed sparse row format. 3796 3797 Options Database Keys: 3798 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3799 3800 Level: beginner 3801 3802 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3803 M*/ 3804 3805 /*MC 3806 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3807 3808 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3809 and MATMPIAIJ otherwise. As a result, for single process communicators, 3810 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3811 for communicators controlling multiple processes. It is recommended that you call both of 3812 the above preallocation routines for simplicity. 3813 3814 Options Database Keys: 3815 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3816 3817 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 3818 enough exist. 3819 3820 Level: beginner 3821 3822 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3823 M*/ 3824 3825 /*MC 3826 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3827 3828 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3829 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3830 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3831 for communicators controlling multiple processes. It is recommended that you call both of 3832 the above preallocation routines for simplicity. 3833 3834 Options Database Keys: 3835 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3836 3837 Level: beginner 3838 3839 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3840 M*/ 3841 3842 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3843 #if defined(PETSC_HAVE_ELEMENTAL) 3844 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 3845 #endif 3846 #if defined(PETSC_HAVE_HYPRE) 3847 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 3848 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 3849 #endif 3850 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 3851 3852 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3853 PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 3854 PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 3855 #endif 3856 3857 3858 /*@C 3859 MatSeqAIJGetArray - gives access to the array where the data for a MATSEQAIJ matrix is stored 3860 3861 Not Collective 3862 3863 Input Parameter: 3864 . mat - a MATSEQAIJ matrix 3865 3866 Output Parameter: 3867 . array - pointer to the data 3868 3869 Level: intermediate 3870 3871 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3872 @*/ 3873 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 3874 { 3875 PetscErrorCode ierr; 3876 3877 PetscFunctionBegin; 3878 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3879 PetscFunctionReturn(0); 3880 } 3881 3882 /*@C 3883 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 3884 3885 Not Collective 3886 3887 Input Parameter: 3888 . mat - a MATSEQAIJ matrix 3889 3890 Output Parameter: 3891 . nz - the maximum number of nonzeros in any row 3892 3893 Level: intermediate 3894 3895 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3896 @*/ 3897 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 3898 { 3899 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 3900 3901 PetscFunctionBegin; 3902 *nz = aij->rmax; 3903 PetscFunctionReturn(0); 3904 } 3905 3906 /*@C 3907 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 3908 3909 Not Collective 3910 3911 Input Parameters: 3912 . mat - a MATSEQAIJ matrix 3913 . array - pointer to the data 3914 3915 Level: intermediate 3916 3917 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 3918 @*/ 3919 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 3920 { 3921 PetscErrorCode ierr; 3922 3923 PetscFunctionBegin; 3924 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3925 PetscFunctionReturn(0); 3926 } 3927 3928 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 3929 { 3930 Mat_SeqAIJ *b; 3931 PetscErrorCode ierr; 3932 PetscMPIInt size; 3933 3934 PetscFunctionBegin; 3935 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 3936 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3937 3938 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3939 3940 B->data = (void*)b; 3941 3942 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3943 3944 b->row = 0; 3945 b->col = 0; 3946 b->icol = 0; 3947 b->reallocs = 0; 3948 b->ignorezeroentries = PETSC_FALSE; 3949 b->roworiented = PETSC_TRUE; 3950 b->nonew = 0; 3951 b->diag = 0; 3952 b->solve_work = 0; 3953 B->spptr = 0; 3954 b->saved_values = 0; 3955 b->idiag = 0; 3956 b->mdiag = 0; 3957 b->ssor_work = 0; 3958 b->omega = 1.0; 3959 b->fshift = 0.0; 3960 b->idiagvalid = PETSC_FALSE; 3961 b->ibdiagvalid = PETSC_FALSE; 3962 b->keepnonzeropattern = PETSC_FALSE; 3963 3964 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3965 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 3966 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 3967 3968 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3969 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 3970 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 3971 #endif 3972 3973 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 3974 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 3975 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 3976 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 3977 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 3978 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 3979 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 3980 #if defined(PETSC_HAVE_ELEMENTAL) 3981 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 3982 #endif 3983 #if defined(PETSC_HAVE_HYPRE) 3984 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 3985 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 3986 #endif 3987 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 3988 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3989 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3990 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 3991 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 3992 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 3993 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 3994 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 3995 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 3996 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 3997 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3998 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 3999 PetscFunctionReturn(0); 4000 } 4001 4002 /* 4003 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4004 */ 4005 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4006 { 4007 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4008 PetscErrorCode ierr; 4009 PetscInt i,m = A->rmap->n; 4010 4011 PetscFunctionBegin; 4012 c = (Mat_SeqAIJ*)C->data; 4013 4014 C->factortype = A->factortype; 4015 c->row = 0; 4016 c->col = 0; 4017 c->icol = 0; 4018 c->reallocs = 0; 4019 4020 C->assembled = PETSC_TRUE; 4021 4022 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4023 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4024 4025 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4026 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4027 for (i=0; i<m; i++) { 4028 c->imax[i] = a->imax[i]; 4029 c->ilen[i] = a->ilen[i]; 4030 } 4031 4032 /* allocate the matrix space */ 4033 if (mallocmatspace) { 4034 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4035 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4036 4037 c->singlemalloc = PETSC_TRUE; 4038 4039 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4040 if (m > 0) { 4041 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4042 if (cpvalues == MAT_COPY_VALUES) { 4043 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4044 } else { 4045 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4046 } 4047 } 4048 } 4049 4050 c->ignorezeroentries = a->ignorezeroentries; 4051 c->roworiented = a->roworiented; 4052 c->nonew = a->nonew; 4053 if (a->diag) { 4054 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4055 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4056 for (i=0; i<m; i++) { 4057 c->diag[i] = a->diag[i]; 4058 } 4059 } else c->diag = 0; 4060 4061 c->solve_work = 0; 4062 c->saved_values = 0; 4063 c->idiag = 0; 4064 c->ssor_work = 0; 4065 c->keepnonzeropattern = a->keepnonzeropattern; 4066 c->free_a = PETSC_TRUE; 4067 c->free_ij = PETSC_TRUE; 4068 4069 c->rmax = a->rmax; 4070 c->nz = a->nz; 4071 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4072 C->preallocated = PETSC_TRUE; 4073 4074 c->compressedrow.use = a->compressedrow.use; 4075 c->compressedrow.nrows = a->compressedrow.nrows; 4076 if (a->compressedrow.use) { 4077 i = a->compressedrow.nrows; 4078 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4079 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4080 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4081 } else { 4082 c->compressedrow.use = PETSC_FALSE; 4083 c->compressedrow.i = NULL; 4084 c->compressedrow.rindex = NULL; 4085 } 4086 c->nonzerorowcnt = a->nonzerorowcnt; 4087 C->nonzerostate = A->nonzerostate; 4088 4089 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4090 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4091 PetscFunctionReturn(0); 4092 } 4093 4094 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4095 { 4096 PetscErrorCode ierr; 4097 4098 PetscFunctionBegin; 4099 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4100 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4101 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4102 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4103 } 4104 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4105 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4106 PetscFunctionReturn(0); 4107 } 4108 4109 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4110 { 4111 Mat_SeqAIJ *a; 4112 PetscErrorCode ierr; 4113 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4114 int fd; 4115 PetscMPIInt size; 4116 MPI_Comm comm; 4117 PetscInt bs = newMat->rmap->bs; 4118 4119 PetscFunctionBegin; 4120 /* force binary viewer to load .info file if it has not yet done so */ 4121 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4122 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4123 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4124 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4125 4126 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4127 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4128 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4129 if (bs < 0) bs = 1; 4130 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4131 4132 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4133 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4134 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4135 M = header[1]; N = header[2]; nz = header[3]; 4136 4137 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4138 4139 /* read in row lengths */ 4140 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4141 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4142 4143 /* check if sum of rowlengths is same as nz */ 4144 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4145 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); 4146 4147 /* set global size if not set already*/ 4148 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4149 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4150 } else { 4151 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4152 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4153 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4154 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4155 } 4156 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); 4157 } 4158 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4159 a = (Mat_SeqAIJ*)newMat->data; 4160 4161 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4162 4163 /* read in nonzero values */ 4164 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4165 4166 /* set matrix "i" values */ 4167 a->i[0] = 0; 4168 for (i=1; i<= M; i++) { 4169 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4170 a->ilen[i-1] = rowlengths[i-1]; 4171 } 4172 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4173 4174 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4175 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4176 PetscFunctionReturn(0); 4177 } 4178 4179 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4180 { 4181 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4182 PetscErrorCode ierr; 4183 #if defined(PETSC_USE_COMPLEX) 4184 PetscInt k; 4185 #endif 4186 4187 PetscFunctionBegin; 4188 /* If the matrix dimensions are not equal,or no of nonzeros */ 4189 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4190 *flg = PETSC_FALSE; 4191 PetscFunctionReturn(0); 4192 } 4193 4194 /* if the a->i are the same */ 4195 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4196 if (!*flg) PetscFunctionReturn(0); 4197 4198 /* if a->j are the same */ 4199 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4200 if (!*flg) PetscFunctionReturn(0); 4201 4202 /* if a->a are the same */ 4203 #if defined(PETSC_USE_COMPLEX) 4204 for (k=0; k<a->nz; k++) { 4205 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4206 *flg = PETSC_FALSE; 4207 PetscFunctionReturn(0); 4208 } 4209 } 4210 #else 4211 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4212 #endif 4213 PetscFunctionReturn(0); 4214 } 4215 4216 /*@ 4217 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4218 provided by the user. 4219 4220 Collective on MPI_Comm 4221 4222 Input Parameters: 4223 + comm - must be an MPI communicator of size 1 4224 . m - number of rows 4225 . n - number of columns 4226 . i - row indices 4227 . j - column indices 4228 - a - matrix values 4229 4230 Output Parameter: 4231 . mat - the matrix 4232 4233 Level: intermediate 4234 4235 Notes: 4236 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4237 once the matrix is destroyed and not before 4238 4239 You cannot set new nonzero locations into this matrix, that will generate an error. 4240 4241 The i and j indices are 0 based 4242 4243 The format which is used for the sparse matrix input, is equivalent to a 4244 row-major ordering.. i.e for the following matrix, the input data expected is 4245 as shown 4246 4247 $ 1 0 0 4248 $ 2 0 3 4249 $ 4 5 6 4250 $ 4251 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4252 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4253 $ v = {1,2,3,4,5,6} [size = 6] 4254 4255 4256 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4257 4258 @*/ 4259 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4260 { 4261 PetscErrorCode ierr; 4262 PetscInt ii; 4263 Mat_SeqAIJ *aij; 4264 #if defined(PETSC_USE_DEBUG) 4265 PetscInt jj; 4266 #endif 4267 4268 PetscFunctionBegin; 4269 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4270 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4271 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4272 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4273 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4274 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4275 aij = (Mat_SeqAIJ*)(*mat)->data; 4276 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4277 4278 aij->i = i; 4279 aij->j = j; 4280 aij->a = a; 4281 aij->singlemalloc = PETSC_FALSE; 4282 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4283 aij->free_a = PETSC_FALSE; 4284 aij->free_ij = PETSC_FALSE; 4285 4286 for (ii=0; ii<m; ii++) { 4287 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4288 #if defined(PETSC_USE_DEBUG) 4289 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]); 4290 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4291 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); 4292 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); 4293 } 4294 #endif 4295 } 4296 #if defined(PETSC_USE_DEBUG) 4297 for (ii=0; ii<aij->i[m]; ii++) { 4298 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4299 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]); 4300 } 4301 #endif 4302 4303 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4304 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4305 PetscFunctionReturn(0); 4306 } 4307 /*@C 4308 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4309 provided by the user. 4310 4311 Collective on MPI_Comm 4312 4313 Input Parameters: 4314 + comm - must be an MPI communicator of size 1 4315 . m - number of rows 4316 . n - number of columns 4317 . i - row indices 4318 . j - column indices 4319 . a - matrix values 4320 . nz - number of nonzeros 4321 - idx - 0 or 1 based 4322 4323 Output Parameter: 4324 . mat - the matrix 4325 4326 Level: intermediate 4327 4328 Notes: 4329 The i and j indices are 0 based 4330 4331 The format which is used for the sparse matrix input, is equivalent to a 4332 row-major ordering.. i.e for the following matrix, the input data expected is 4333 as shown: 4334 4335 1 0 0 4336 2 0 3 4337 4 5 6 4338 4339 i = {0,1,1,2,2,2} 4340 j = {0,0,2,0,1,2} 4341 v = {1,2,3,4,5,6} 4342 4343 4344 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4345 4346 @*/ 4347 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4348 { 4349 PetscErrorCode ierr; 4350 PetscInt ii, *nnz, one = 1,row,col; 4351 4352 4353 PetscFunctionBegin; 4354 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4355 for (ii = 0; ii < nz; ii++) { 4356 nnz[i[ii] - !!idx] += 1; 4357 } 4358 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4359 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4360 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4361 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4362 for (ii = 0; ii < nz; ii++) { 4363 if (idx) { 4364 row = i[ii] - 1; 4365 col = j[ii] - 1; 4366 } else { 4367 row = i[ii]; 4368 col = j[ii]; 4369 } 4370 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4371 } 4372 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4373 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4374 ierr = PetscFree(nnz);CHKERRQ(ierr); 4375 PetscFunctionReturn(0); 4376 } 4377 4378 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4379 { 4380 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4381 PetscErrorCode ierr; 4382 4383 PetscFunctionBegin; 4384 a->idiagvalid = PETSC_FALSE; 4385 a->ibdiagvalid = PETSC_FALSE; 4386 4387 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4388 PetscFunctionReturn(0); 4389 } 4390 4391 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4392 { 4393 PetscErrorCode ierr; 4394 PetscMPIInt size; 4395 4396 PetscFunctionBegin; 4397 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4398 if (size == 1 && scall == MAT_REUSE_MATRIX) { 4399 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4400 } else { 4401 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4402 } 4403 PetscFunctionReturn(0); 4404 } 4405 4406 /* 4407 Permute A into C's *local* index space using rowemb,colemb. 4408 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4409 of [0,m), colemb is in [0,n). 4410 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4411 */ 4412 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4413 { 4414 /* If making this function public, change the error returned in this function away from _PLIB. */ 4415 PetscErrorCode ierr; 4416 Mat_SeqAIJ *Baij; 4417 PetscBool seqaij; 4418 PetscInt m,n,*nz,i,j,count; 4419 PetscScalar v; 4420 const PetscInt *rowindices,*colindices; 4421 4422 PetscFunctionBegin; 4423 if (!B) PetscFunctionReturn(0); 4424 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4425 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4426 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4427 if (rowemb) { 4428 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4429 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); 4430 } else { 4431 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4432 } 4433 if (colemb) { 4434 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4435 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); 4436 } else { 4437 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4438 } 4439 4440 Baij = (Mat_SeqAIJ*)(B->data); 4441 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4442 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4443 for (i=0; i<B->rmap->n; i++) { 4444 nz[i] = Baij->i[i+1] - Baij->i[i]; 4445 } 4446 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4447 ierr = PetscFree(nz);CHKERRQ(ierr); 4448 } 4449 if (pattern == SUBSET_NONZERO_PATTERN) { 4450 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4451 } 4452 count = 0; 4453 rowindices = NULL; 4454 colindices = NULL; 4455 if (rowemb) { 4456 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4457 } 4458 if (colemb) { 4459 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4460 } 4461 for (i=0; i<B->rmap->n; i++) { 4462 PetscInt row; 4463 row = i; 4464 if (rowindices) row = rowindices[i]; 4465 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4466 PetscInt col; 4467 col = Baij->j[count]; 4468 if (colindices) col = colindices[col]; 4469 v = Baij->a[count]; 4470 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4471 ++count; 4472 } 4473 } 4474 /* FIXME: set C's nonzerostate correctly. */ 4475 /* Assembly for C is necessary. */ 4476 C->preallocated = PETSC_TRUE; 4477 C->assembled = PETSC_TRUE; 4478 C->was_assembled = PETSC_FALSE; 4479 PetscFunctionReturn(0); 4480 } 4481 4482 PetscFunctionList MatSeqAIJList = NULL; 4483 4484 /*@C 4485 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 4486 4487 Collective on Mat 4488 4489 Input Parameters: 4490 + mat - the matrix object 4491 - matype - matrix type 4492 4493 Options Database Key: 4494 . -mat_seqai_type <method> - for example seqaijcrl 4495 4496 4497 Level: intermediate 4498 4499 .keywords: Mat, MatType, set, method 4500 4501 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 4502 @*/ 4503 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 4504 { 4505 PetscErrorCode ierr,(*r)(Mat,const MatType,MatReuse,Mat*); 4506 PetscBool sametype; 4507 4508 PetscFunctionBegin; 4509 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 4510 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 4511 if (sametype) PetscFunctionReturn(0); 4512 4513 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 4514 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 4515 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 4516 PetscFunctionReturn(0); 4517 } 4518 4519 4520 /*@C 4521 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 4522 4523 Not Collective 4524 4525 Input Parameters: 4526 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 4527 - function - routine to convert to subtype 4528 4529 Notes: 4530 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 4531 4532 4533 Then, your matrix can be chosen with the procedural interface at runtime via the option 4534 $ -mat_seqaij_type my_mat 4535 4536 Level: advanced 4537 4538 .keywords: Mat, register 4539 4540 .seealso: MatSeqAIJRegisterAll() 4541 4542 4543 Level: advanced 4544 @*/ 4545 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,const MatType,MatReuse,Mat *)) 4546 { 4547 PetscErrorCode ierr; 4548 4549 PetscFunctionBegin; 4550 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 4551 PetscFunctionReturn(0); 4552 } 4553 4554 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 4555 4556 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,const MatType,MatReuse,Mat*); 4557 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat,const MatType,MatReuse,Mat*); 4558 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4559 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat,const MatType,MatReuse,Mat*); 4560 #endif 4561 4562 /*@C 4563 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 4564 4565 Not Collective 4566 4567 Level: advanced 4568 4569 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 4570 4571 .keywords: KSP, register, all 4572 4573 .seealso: MatRegisterAll(), MatSeqAIJRegister() 4574 @*/ 4575 PetscErrorCode MatSeqAIJRegisterAll(void) 4576 { 4577 PetscErrorCode ierr; 4578 4579 PetscFunctionBegin; 4580 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 4581 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 4582 4583 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4584 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4585 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4586 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 4587 #endif 4588 PetscFunctionReturn(0); 4589 } 4590 4591 /* 4592 Special version for direct calls from Fortran 4593 */ 4594 #include <petsc/private/fortranimpl.h> 4595 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4596 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4597 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4598 #define matsetvaluesseqaij_ matsetvaluesseqaij 4599 #endif 4600 4601 /* Change these macros so can be used in void function */ 4602 #undef CHKERRQ 4603 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4604 #undef SETERRQ2 4605 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4606 #undef SETERRQ3 4607 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4608 4609 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) 4610 { 4611 Mat A = *AA; 4612 PetscInt m = *mm, n = *nn; 4613 InsertMode is = *isis; 4614 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4615 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4616 PetscInt *imax,*ai,*ailen; 4617 PetscErrorCode ierr; 4618 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4619 MatScalar *ap,value,*aa; 4620 PetscBool ignorezeroentries = a->ignorezeroentries; 4621 PetscBool roworiented = a->roworiented; 4622 4623 PetscFunctionBegin; 4624 MatCheckPreallocated(A,1); 4625 imax = a->imax; 4626 ai = a->i; 4627 ailen = a->ilen; 4628 aj = a->j; 4629 aa = a->a; 4630 4631 for (k=0; k<m; k++) { /* loop over added rows */ 4632 row = im[k]; 4633 if (row < 0) continue; 4634 #if defined(PETSC_USE_DEBUG) 4635 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4636 #endif 4637 rp = aj + ai[row]; ap = aa + ai[row]; 4638 rmax = imax[row]; nrow = ailen[row]; 4639 low = 0; 4640 high = nrow; 4641 for (l=0; l<n; l++) { /* loop over added columns */ 4642 if (in[l] < 0) continue; 4643 #if defined(PETSC_USE_DEBUG) 4644 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4645 #endif 4646 col = in[l]; 4647 if (roworiented) value = v[l + k*n]; 4648 else value = v[k + l*m]; 4649 4650 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4651 4652 if (col <= lastcol) low = 0; 4653 else high = nrow; 4654 lastcol = col; 4655 while (high-low > 5) { 4656 t = (low+high)/2; 4657 if (rp[t] > col) high = t; 4658 else low = t; 4659 } 4660 for (i=low; i<high; i++) { 4661 if (rp[i] > col) break; 4662 if (rp[i] == col) { 4663 if (is == ADD_VALUES) ap[i] += value; 4664 else ap[i] = value; 4665 goto noinsert; 4666 } 4667 } 4668 if (value == 0.0 && ignorezeroentries) goto noinsert; 4669 if (nonew == 1) goto noinsert; 4670 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4671 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4672 N = nrow++ - 1; a->nz++; high++; 4673 /* shift up all the later entries in this row */ 4674 for (ii=N; ii>=i; ii--) { 4675 rp[ii+1] = rp[ii]; 4676 ap[ii+1] = ap[ii]; 4677 } 4678 rp[i] = col; 4679 ap[i] = value; 4680 A->nonzerostate++; 4681 noinsert:; 4682 low = i + 1; 4683 } 4684 ailen[row] = nrow; 4685 } 4686 PetscFunctionReturnVoid(); 4687 } 4688 4689