1 2 /* 3 Defines the basic matrix operations for the AIJ (compressed row) 4 matrix storage format. 5 */ 6 7 8 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petscbt.h> 11 #include <petsc/private/kernels/blocktranspose.h> 12 13 PetscErrorCode MatSeqAIJSetTypeFromOptions(Mat A) 14 { 15 PetscErrorCode ierr; 16 PetscBool flg; 17 char type[256]; 18 19 PetscFunctionBegin; 20 ierr = PetscObjectOptionsBegin((PetscObject)A); 21 ierr = PetscOptionsFList("-mat_seqaij_type","Matrix SeqAIJ type","MatSeqAIJSetType",MatSeqAIJList,"seqaij",type,256,&flg);CHKERRQ(ierr); 22 if (flg) { 23 ierr = MatSeqAIJSetType(A,type);CHKERRQ(ierr); 24 } 25 ierr = PetscOptionsEnd();CHKERRQ(ierr); 26 PetscFunctionReturn(0); 27 } 28 29 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 30 { 31 PetscErrorCode ierr; 32 PetscInt i,m,n; 33 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 34 35 PetscFunctionBegin; 36 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 37 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 38 if (type == NORM_2) { 39 for (i=0; i<aij->i[m]; i++) { 40 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 41 } 42 } else if (type == NORM_1) { 43 for (i=0; i<aij->i[m]; i++) { 44 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 45 } 46 } else if (type == NORM_INFINITY) { 47 for (i=0; i<aij->i[m]; i++) { 48 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 49 } 50 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 51 52 if (type == NORM_2) { 53 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 54 } 55 PetscFunctionReturn(0); 56 } 57 58 PetscErrorCode MatFindOffBlockDiagonalEntries_SeqAIJ(Mat A,IS *is) 59 { 60 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 61 PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; 62 const PetscInt *jj = a->j,*ii = a->i; 63 PetscInt *rows; 64 PetscErrorCode ierr; 65 66 PetscFunctionBegin; 67 for (i=0; i<m; i++) { 68 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 69 cnt++; 70 } 71 } 72 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 73 cnt = 0; 74 for (i=0; i<m; i++) { 75 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 76 rows[cnt] = i; 77 cnt++; 78 } 79 } 80 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 81 PetscFunctionReturn(0); 82 } 83 84 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 85 { 86 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 87 const MatScalar *aa = a->a; 88 PetscInt i,m=A->rmap->n,cnt = 0; 89 const PetscInt *ii = a->i,*jj = a->j,*diag; 90 PetscInt *rows; 91 PetscErrorCode ierr; 92 93 PetscFunctionBegin; 94 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 95 diag = a->diag; 96 for (i=0; i<m; i++) { 97 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 98 cnt++; 99 } 100 } 101 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 102 cnt = 0; 103 for (i=0; i<m; i++) { 104 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 105 rows[cnt++] = i; 106 } 107 } 108 *nrows = cnt; 109 *zrows = rows; 110 PetscFunctionReturn(0); 111 } 112 113 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 114 { 115 PetscInt nrows,*rows; 116 PetscErrorCode ierr; 117 118 PetscFunctionBegin; 119 *zrows = NULL; 120 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 121 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 122 PetscFunctionReturn(0); 123 } 124 125 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 126 { 127 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 128 const MatScalar *aa; 129 PetscInt m=A->rmap->n,cnt = 0; 130 const PetscInt *ii; 131 PetscInt n,i,j,*rows; 132 PetscErrorCode ierr; 133 134 PetscFunctionBegin; 135 *keptrows = 0; 136 ii = a->i; 137 for (i=0; i<m; i++) { 138 n = ii[i+1] - ii[i]; 139 if (!n) { 140 cnt++; 141 goto ok1; 142 } 143 aa = a->a + ii[i]; 144 for (j=0; j<n; j++) { 145 if (aa[j] != 0.0) goto ok1; 146 } 147 cnt++; 148 ok1:; 149 } 150 if (!cnt) PetscFunctionReturn(0); 151 ierr = PetscMalloc1(A->rmap->n-cnt,&rows);CHKERRQ(ierr); 152 cnt = 0; 153 for (i=0; i<m; i++) { 154 n = ii[i+1] - ii[i]; 155 if (!n) continue; 156 aa = a->a + ii[i]; 157 for (j=0; j<n; j++) { 158 if (aa[j] != 0.0) { 159 rows[cnt++] = i; 160 break; 161 } 162 } 163 } 164 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 165 PetscFunctionReturn(0); 166 } 167 168 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 169 { 170 PetscErrorCode ierr; 171 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 172 PetscInt i,m = Y->rmap->n; 173 const PetscInt *diag; 174 MatScalar *aa = aij->a; 175 const PetscScalar *v; 176 PetscBool missing; 177 178 PetscFunctionBegin; 179 if (Y->assembled) { 180 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 181 if (!missing) { 182 diag = aij->diag; 183 ierr = VecGetArrayRead(D,&v);CHKERRQ(ierr); 184 if (is == INSERT_VALUES) { 185 for (i=0; i<m; i++) { 186 aa[diag[i]] = v[i]; 187 } 188 } else { 189 for (i=0; i<m; i++) { 190 aa[diag[i]] += v[i]; 191 } 192 } 193 ierr = VecRestoreArrayRead(D,&v);CHKERRQ(ierr); 194 PetscFunctionReturn(0); 195 } 196 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 197 } 198 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 199 PetscFunctionReturn(0); 200 } 201 202 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 203 { 204 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 205 PetscErrorCode ierr; 206 PetscInt i,ishift; 207 208 PetscFunctionBegin; 209 *m = A->rmap->n; 210 if (!ia) PetscFunctionReturn(0); 211 ishift = 0; 212 if (symmetric && !A->structurally_symmetric) { 213 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 214 } else if (oshift == 1) { 215 PetscInt *tia; 216 PetscInt nz = a->i[A->rmap->n]; 217 /* malloc space and add 1 to i and j indices */ 218 ierr = PetscMalloc1(A->rmap->n+1,&tia);CHKERRQ(ierr); 219 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 220 *ia = tia; 221 if (ja) { 222 PetscInt *tja; 223 ierr = PetscMalloc1(nz+1,&tja);CHKERRQ(ierr); 224 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 225 *ja = tja; 226 } 227 } else { 228 *ia = a->i; 229 if (ja) *ja = a->j; 230 } 231 PetscFunctionReturn(0); 232 } 233 234 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 235 { 236 PetscErrorCode ierr; 237 238 PetscFunctionBegin; 239 if (!ia) PetscFunctionReturn(0); 240 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 241 ierr = PetscFree(*ia);CHKERRQ(ierr); 242 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 243 } 244 PetscFunctionReturn(0); 245 } 246 247 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 248 { 249 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 250 PetscErrorCode ierr; 251 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 252 PetscInt nz = a->i[m],row,*jj,mr,col; 253 254 PetscFunctionBegin; 255 *nn = n; 256 if (!ia) PetscFunctionReturn(0); 257 if (symmetric) { 258 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 259 } else { 260 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 261 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 262 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 263 jj = a->j; 264 for (i=0; i<nz; i++) { 265 collengths[jj[i]]++; 266 } 267 cia[0] = oshift; 268 for (i=0; i<n; i++) { 269 cia[i+1] = cia[i] + collengths[i]; 270 } 271 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 272 jj = a->j; 273 for (row=0; row<m; row++) { 274 mr = a->i[row+1] - a->i[row]; 275 for (i=0; i<mr; i++) { 276 col = *jj++; 277 278 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 279 } 280 } 281 ierr = PetscFree(collengths);CHKERRQ(ierr); 282 *ia = cia; *ja = cja; 283 } 284 PetscFunctionReturn(0); 285 } 286 287 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 288 { 289 PetscErrorCode ierr; 290 291 PetscFunctionBegin; 292 if (!ia) PetscFunctionReturn(0); 293 294 ierr = PetscFree(*ia);CHKERRQ(ierr); 295 ierr = PetscFree(*ja);CHKERRQ(ierr); 296 PetscFunctionReturn(0); 297 } 298 299 /* 300 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 301 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 302 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() 303 */ 304 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 305 { 306 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 307 PetscErrorCode ierr; 308 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 309 PetscInt nz = a->i[m],row,*jj,mr,col; 310 PetscInt *cspidx; 311 312 PetscFunctionBegin; 313 *nn = n; 314 if (!ia) PetscFunctionReturn(0); 315 316 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 317 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 318 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 319 ierr = PetscMalloc1(nz+1,&cspidx);CHKERRQ(ierr); 320 jj = a->j; 321 for (i=0; i<nz; i++) { 322 collengths[jj[i]]++; 323 } 324 cia[0] = oshift; 325 for (i=0; i<n; i++) { 326 cia[i+1] = cia[i] + collengths[i]; 327 } 328 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 329 jj = a->j; 330 for (row=0; row<m; row++) { 331 mr = a->i[row+1] - a->i[row]; 332 for (i=0; i<mr; i++) { 333 col = *jj++; 334 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 335 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 336 } 337 } 338 ierr = PetscFree(collengths);CHKERRQ(ierr); 339 *ia = cia; *ja = cja; 340 *spidx = cspidx; 341 PetscFunctionReturn(0); 342 } 343 344 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 345 { 346 PetscErrorCode ierr; 347 348 PetscFunctionBegin; 349 ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 350 ierr = PetscFree(*spidx);CHKERRQ(ierr); 351 PetscFunctionReturn(0); 352 } 353 354 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 355 { 356 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 357 PetscInt *ai = a->i; 358 PetscErrorCode ierr; 359 360 PetscFunctionBegin; 361 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 362 PetscFunctionReturn(0); 363 } 364 365 /* 366 MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions 367 368 - a single row of values is set with each call 369 - no row or column indices are negative or (in error) larger than the number of rows or columns 370 - the values are always added to the matrix, not set 371 - no new locations are introduced in the nonzero structure of the matrix 372 373 This does NOT assume the global column indices are sorted 374 375 */ 376 377 #include <petsc/private/isimpl.h> 378 PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 379 { 380 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 381 PetscInt low,high,t,row,nrow,i,col,l; 382 const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; 383 PetscInt lastcol = -1; 384 MatScalar *ap,value,*aa = a->a; 385 const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; 386 387 row = ridx[im[0]]; 388 rp = aj + ai[row]; 389 ap = aa + ai[row]; 390 nrow = ailen[row]; 391 low = 0; 392 high = nrow; 393 for (l=0; l<n; l++) { /* loop over added columns */ 394 col = cidx[in[l]]; 395 value = v[l]; 396 397 if (col <= lastcol) low = 0; 398 else high = nrow; 399 lastcol = col; 400 while (high-low > 5) { 401 t = (low+high)/2; 402 if (rp[t] > col) high = t; 403 else low = t; 404 } 405 for (i=low; i<high; i++) { 406 if (rp[i] == col) { 407 ap[i] += value; 408 low = i + 1; 409 break; 410 } 411 } 412 } 413 return 0; 414 } 415 416 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 417 { 418 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 419 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 420 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 421 PetscErrorCode ierr; 422 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 423 MatScalar *ap=NULL,value=0.0,*aa = a->a; 424 PetscBool ignorezeroentries = a->ignorezeroentries; 425 PetscBool roworiented = a->roworiented; 426 427 PetscFunctionBegin; 428 for (k=0; k<m; k++) { /* loop over added rows */ 429 row = im[k]; 430 if (row < 0) continue; 431 #if defined(PETSC_USE_DEBUG) 432 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 433 #endif 434 rp = aj + ai[row]; 435 if (!A->structure_only) ap = aa + ai[row]; 436 rmax = imax[row]; nrow = ailen[row]; 437 low = 0; 438 high = nrow; 439 for (l=0; l<n; l++) { /* loop over added columns */ 440 if (in[l] < 0) continue; 441 #if defined(PETSC_USE_DEBUG) 442 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 443 #endif 444 col = in[l]; 445 if (!A->structure_only) { 446 if (roworiented) { 447 value = v[l + k*n]; 448 } else { 449 value = v[k + l*m]; 450 } 451 } else { /* A->structure_only */ 452 value = 1; /* avoid 'continue' below? */ 453 } 454 if ((value == 0.0 && ignorezeroentries) && (is == ADD_VALUES) && row != col) continue; 455 456 if (col <= lastcol) low = 0; 457 else high = nrow; 458 lastcol = col; 459 while (high-low > 5) { 460 t = (low+high)/2; 461 if (rp[t] > col) high = t; 462 else low = t; 463 } 464 for (i=low; i<high; i++) { 465 if (rp[i] > col) break; 466 if (rp[i] == col) { 467 if (!A->structure_only) { 468 if (is == ADD_VALUES) ap[i] += value; 469 else ap[i] = value; 470 } 471 low = i + 1; 472 goto noinsert; 473 } 474 } 475 if (value == 0.0 && ignorezeroentries && row != col) goto noinsert; 476 if (nonew == 1) goto noinsert; 477 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 478 if (A->structure_only) { 479 MatSeqXAIJReallocateAIJ_structure_only(A,A->rmap->n,1,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar); 480 } else { 481 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 482 } 483 N = nrow++ - 1; a->nz++; high++; 484 /* shift up all the later entries in this row */ 485 for (ii=N; ii>=i; ii--) { 486 rp[ii+1] = rp[ii]; 487 if (!A->structure_only) ap[ii+1] = ap[ii]; 488 } 489 rp[i] = col; 490 if (!A->structure_only) ap[i] = value; 491 low = i + 1; 492 A->nonzerostate++; 493 noinsert:; 494 } 495 ailen[row] = nrow; 496 } 497 PetscFunctionReturn(0); 498 } 499 500 501 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 502 { 503 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 504 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 505 PetscInt *ai = a->i,*ailen = a->ilen; 506 MatScalar *ap,*aa = a->a; 507 508 PetscFunctionBegin; 509 for (k=0; k<m; k++) { /* loop over rows */ 510 row = im[k]; 511 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 512 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 513 rp = aj + ai[row]; ap = aa + ai[row]; 514 nrow = ailen[row]; 515 for (l=0; l<n; l++) { /* loop over columns */ 516 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 517 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 518 col = in[l]; 519 high = nrow; low = 0; /* assume unsorted */ 520 while (high-low > 5) { 521 t = (low+high)/2; 522 if (rp[t] > col) high = t; 523 else low = t; 524 } 525 for (i=low; i<high; i++) { 526 if (rp[i] > col) break; 527 if (rp[i] == col) { 528 *v++ = ap[i]; 529 goto finished; 530 } 531 } 532 *v++ = 0.0; 533 finished:; 534 } 535 } 536 PetscFunctionReturn(0); 537 } 538 539 540 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 541 { 542 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 543 PetscErrorCode ierr; 544 PetscInt i,*col_lens; 545 int fd; 546 FILE *file; 547 548 PetscFunctionBegin; 549 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 550 ierr = PetscMalloc1(4+A->rmap->n,&col_lens);CHKERRQ(ierr); 551 552 col_lens[0] = MAT_FILE_CLASSID; 553 col_lens[1] = A->rmap->n; 554 col_lens[2] = A->cmap->n; 555 col_lens[3] = a->nz; 556 557 /* store lengths of each row and write (including header) to file */ 558 for (i=0; i<A->rmap->n; i++) { 559 col_lens[4+i] = a->i[i+1] - a->i[i]; 560 } 561 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 562 ierr = PetscFree(col_lens);CHKERRQ(ierr); 563 564 /* store column indices (zero start index) */ 565 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 566 567 /* store nonzero values */ 568 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 569 570 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 571 if (file) { 572 fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); 573 } 574 PetscFunctionReturn(0); 575 } 576 577 static PetscErrorCode MatView_SeqAIJ_ASCII_structonly(Mat A,PetscViewer viewer) 578 { 579 PetscErrorCode ierr; 580 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 581 PetscInt i,k,m=A->rmap->N; 582 583 PetscFunctionBegin; 584 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 585 for (i=0; i<m; i++) { 586 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 587 for (k=a->i[i]; k<a->i[i+1]; k++) { 588 ierr = PetscViewerASCIIPrintf(viewer," (%D) ",a->j[k]);CHKERRQ(ierr); 589 } 590 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 591 } 592 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 593 PetscFunctionReturn(0); 594 } 595 596 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 597 598 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 599 { 600 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 601 PetscErrorCode ierr; 602 PetscInt i,j,m = A->rmap->n; 603 const char *name; 604 PetscViewerFormat format; 605 606 PetscFunctionBegin; 607 if (A->structure_only) { 608 ierr = MatView_SeqAIJ_ASCII_structonly(A,viewer);CHKERRQ(ierr); 609 PetscFunctionReturn(0); 610 } 611 612 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 613 if (format == PETSC_VIEWER_ASCII_MATLAB) { 614 PetscInt nofinalvalue = 0; 615 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 616 /* Need a dummy value to ensure the dimension of the matrix. */ 617 nofinalvalue = 1; 618 } 619 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 620 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 621 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 622 #if defined(PETSC_USE_COMPLEX) 623 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 624 #else 625 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 626 #endif 627 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 628 629 for (i=0; i<m; i++) { 630 for (j=a->i[i]; j<a->i[i+1]; j++) { 631 #if defined(PETSC_USE_COMPLEX) 632 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",i+1,a->j[j]+1,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 633 #else 634 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 635 #endif 636 } 637 } 638 if (nofinalvalue) { 639 #if defined(PETSC_USE_COMPLEX) 640 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 641 #else 642 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 643 #endif 644 } 645 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 646 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 647 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 648 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 649 PetscFunctionReturn(0); 650 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 651 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 652 for (i=0; i<m; i++) { 653 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 654 for (j=a->i[i]; j<a->i[i+1]; j++) { 655 #if defined(PETSC_USE_COMPLEX) 656 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 657 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 658 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 659 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 660 } else if (PetscRealPart(a->a[j]) != 0.0) { 661 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 662 } 663 #else 664 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 665 #endif 666 } 667 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 668 } 669 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 670 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 671 PetscInt nzd=0,fshift=1,*sptr; 672 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 673 ierr = PetscMalloc1(m+1,&sptr);CHKERRQ(ierr); 674 for (i=0; i<m; i++) { 675 sptr[i] = nzd+1; 676 for (j=a->i[i]; j<a->i[i+1]; j++) { 677 if (a->j[j] >= i) { 678 #if defined(PETSC_USE_COMPLEX) 679 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 680 #else 681 if (a->a[j] != 0.0) nzd++; 682 #endif 683 } 684 } 685 } 686 sptr[m] = nzd+1; 687 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 688 for (i=0; i<m+1; i+=6) { 689 if (i+4<m) { 690 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4],sptr[i+5]);CHKERRQ(ierr); 691 } else if (i+3<m) { 692 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4]);CHKERRQ(ierr); 693 } else if (i+2<m) { 694 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 695 } else if (i+1<m) { 696 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 697 } else if (i<m) { 698 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 699 } else { 700 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 701 } 702 } 703 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 704 ierr = PetscFree(sptr);CHKERRQ(ierr); 705 for (i=0; i<m; i++) { 706 for (j=a->i[i]; j<a->i[i+1]; j++) { 707 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 708 } 709 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 710 } 711 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 712 for (i=0; i<m; i++) { 713 for (j=a->i[i]; j<a->i[i+1]; j++) { 714 if (a->j[j] >= i) { 715 #if defined(PETSC_USE_COMPLEX) 716 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 717 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 718 } 719 #else 720 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 721 #endif 722 } 723 } 724 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 725 } 726 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 727 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 728 PetscInt cnt = 0,jcnt; 729 PetscScalar value; 730 #if defined(PETSC_USE_COMPLEX) 731 PetscBool realonly = PETSC_TRUE; 732 733 for (i=0; i<a->i[m]; i++) { 734 if (PetscImaginaryPart(a->a[i]) != 0.0) { 735 realonly = PETSC_FALSE; 736 break; 737 } 738 } 739 #endif 740 741 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 742 for (i=0; i<m; i++) { 743 jcnt = 0; 744 for (j=0; j<A->cmap->n; j++) { 745 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 746 value = a->a[cnt++]; 747 jcnt++; 748 } else { 749 value = 0.0; 750 } 751 #if defined(PETSC_USE_COMPLEX) 752 if (realonly) { 753 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 754 } else { 755 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 756 } 757 #else 758 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 759 #endif 760 } 761 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 762 } 763 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 764 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 765 PetscInt fshift=1; 766 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 767 #if defined(PETSC_USE_COMPLEX) 768 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");CHKERRQ(ierr); 769 #else 770 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");CHKERRQ(ierr); 771 #endif 772 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 773 for (i=0; i<m; i++) { 774 for (j=a->i[i]; j<a->i[i+1]; j++) { 775 #if defined(PETSC_USE_COMPLEX) 776 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 777 #else 778 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 779 #endif 780 } 781 } 782 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 783 } else { 784 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 785 if (A->factortype) { 786 for (i=0; i<m; i++) { 787 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 788 /* L part */ 789 for (j=a->i[i]; j<a->i[i+1]; j++) { 790 #if defined(PETSC_USE_COMPLEX) 791 if (PetscImaginaryPart(a->a[j]) > 0.0) { 792 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 793 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 794 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 795 } else { 796 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 797 } 798 #else 799 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 800 #endif 801 } 802 /* diagonal */ 803 j = a->diag[i]; 804 #if defined(PETSC_USE_COMPLEX) 805 if (PetscImaginaryPart(a->a[j]) > 0.0) { 806 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 807 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 808 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)(-PetscImaginaryPart(1.0/a->a[j])));CHKERRQ(ierr); 809 } else { 810 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 811 } 812 #else 813 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 814 #endif 815 816 /* U part */ 817 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 818 #if defined(PETSC_USE_COMPLEX) 819 if (PetscImaginaryPart(a->a[j]) > 0.0) { 820 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 821 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 822 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 823 } else { 824 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 825 } 826 #else 827 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 828 #endif 829 } 830 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 831 } 832 } else { 833 for (i=0; i<m; i++) { 834 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 835 for (j=a->i[i]; j<a->i[i+1]; j++) { 836 #if defined(PETSC_USE_COMPLEX) 837 if (PetscImaginaryPart(a->a[j]) > 0.0) { 838 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 839 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 840 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 841 } else { 842 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 843 } 844 #else 845 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 846 #endif 847 } 848 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 849 } 850 } 851 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 852 } 853 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 854 PetscFunctionReturn(0); 855 } 856 857 #include <petscdraw.h> 858 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 859 { 860 Mat A = (Mat) Aa; 861 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 862 PetscErrorCode ierr; 863 PetscInt i,j,m = A->rmap->n; 864 int color; 865 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 866 PetscViewer viewer; 867 PetscViewerFormat format; 868 869 PetscFunctionBegin; 870 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 871 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 872 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 873 874 /* loop over matrix elements drawing boxes */ 875 876 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 877 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 878 /* Blue for negative, Cyan for zero and Red for positive */ 879 color = PETSC_DRAW_BLUE; 880 for (i=0; i<m; i++) { 881 y_l = m - i - 1.0; y_r = y_l + 1.0; 882 for (j=a->i[i]; j<a->i[i+1]; j++) { 883 x_l = a->j[j]; x_r = x_l + 1.0; 884 if (PetscRealPart(a->a[j]) >= 0.) continue; 885 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 886 } 887 } 888 color = PETSC_DRAW_CYAN; 889 for (i=0; i<m; i++) { 890 y_l = m - i - 1.0; y_r = y_l + 1.0; 891 for (j=a->i[i]; j<a->i[i+1]; j++) { 892 x_l = a->j[j]; x_r = x_l + 1.0; 893 if (a->a[j] != 0.) continue; 894 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 895 } 896 } 897 color = PETSC_DRAW_RED; 898 for (i=0; i<m; i++) { 899 y_l = m - i - 1.0; y_r = y_l + 1.0; 900 for (j=a->i[i]; j<a->i[i+1]; j++) { 901 x_l = a->j[j]; x_r = x_l + 1.0; 902 if (PetscRealPart(a->a[j]) <= 0.) continue; 903 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 904 } 905 } 906 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 907 } else { 908 /* use contour shading to indicate magnitude of values */ 909 /* first determine max of all nonzero values */ 910 PetscReal minv = 0.0, maxv = 0.0; 911 PetscInt nz = a->nz, count = 0; 912 PetscDraw popup; 913 914 for (i=0; i<nz; i++) { 915 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 916 } 917 if (minv >= maxv) maxv = minv + PETSC_SMALL; 918 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 919 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 920 921 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 922 for (i=0; i<m; i++) { 923 y_l = m - i - 1.0; 924 y_r = y_l + 1.0; 925 for (j=a->i[i]; j<a->i[i+1]; j++) { 926 x_l = a->j[j]; 927 x_r = x_l + 1.0; 928 color = PetscDrawRealToColor(PetscAbsScalar(a->a[count]),minv,maxv); 929 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 930 count++; 931 } 932 } 933 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 934 } 935 PetscFunctionReturn(0); 936 } 937 938 #include <petscdraw.h> 939 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 940 { 941 PetscErrorCode ierr; 942 PetscDraw draw; 943 PetscReal xr,yr,xl,yl,h,w; 944 PetscBool isnull; 945 946 PetscFunctionBegin; 947 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 948 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 949 if (isnull) PetscFunctionReturn(0); 950 951 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 952 xr += w; yr += h; xl = -w; yl = -h; 953 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 954 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 955 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 956 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 957 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 958 PetscFunctionReturn(0); 959 } 960 961 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 962 { 963 PetscErrorCode ierr; 964 PetscBool iascii,isbinary,isdraw; 965 966 PetscFunctionBegin; 967 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 968 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 969 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 970 if (iascii) { 971 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 972 } else if (isbinary) { 973 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 974 } else if (isdraw) { 975 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 976 } 977 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 978 PetscFunctionReturn(0); 979 } 980 981 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 982 { 983 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 984 PetscErrorCode ierr; 985 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 986 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 987 MatScalar *aa = a->a,*ap; 988 PetscReal ratio = 0.6; 989 990 PetscFunctionBegin; 991 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 992 993 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 994 for (i=1; i<m; i++) { 995 /* move each row back by the amount of empty slots (fshift) before it*/ 996 fshift += imax[i-1] - ailen[i-1]; 997 rmax = PetscMax(rmax,ailen[i]); 998 if (fshift) { 999 ip = aj + ai[i]; 1000 ap = aa + ai[i]; 1001 N = ailen[i]; 1002 for (j=0; j<N; j++) { 1003 ip[j-fshift] = ip[j]; 1004 if (!A->structure_only) ap[j-fshift] = ap[j]; 1005 } 1006 } 1007 ai[i] = ai[i-1] + ailen[i-1]; 1008 } 1009 if (m) { 1010 fshift += imax[m-1] - ailen[m-1]; 1011 ai[m] = ai[m-1] + ailen[m-1]; 1012 } 1013 1014 /* reset ilen and imax for each row */ 1015 a->nonzerorowcnt = 0; 1016 if (A->structure_only) { 1017 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1018 } else { /* !A->structure_only */ 1019 for (i=0; i<m; i++) { 1020 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1021 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1022 } 1023 } 1024 a->nz = ai[m]; 1025 if (fshift && a->nounused == -1) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D, %D unneeded", m, A->cmap->n, fshift); 1026 1027 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1028 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1029 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1030 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1031 1032 A->info.mallocs += a->reallocs; 1033 a->reallocs = 0; 1034 A->info.nz_unneeded = (PetscReal)fshift; 1035 a->rmax = rmax; 1036 1037 if (!A->structure_only) { 1038 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1039 } 1040 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1041 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1042 PetscFunctionReturn(0); 1043 } 1044 1045 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1046 { 1047 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1048 PetscInt i,nz = a->nz; 1049 MatScalar *aa = a->a; 1050 PetscErrorCode ierr; 1051 1052 PetscFunctionBegin; 1053 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1054 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1055 PetscFunctionReturn(0); 1056 } 1057 1058 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1059 { 1060 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1061 PetscInt i,nz = a->nz; 1062 MatScalar *aa = a->a; 1063 PetscErrorCode ierr; 1064 1065 PetscFunctionBegin; 1066 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1067 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1068 PetscFunctionReturn(0); 1069 } 1070 1071 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1072 { 1073 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1074 PetscErrorCode ierr; 1075 1076 PetscFunctionBegin; 1077 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1078 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1079 PetscFunctionReturn(0); 1080 } 1081 1082 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1083 { 1084 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1085 PetscErrorCode ierr; 1086 1087 PetscFunctionBegin; 1088 #if defined(PETSC_USE_LOG) 1089 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1090 #endif 1091 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1092 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1093 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1094 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1095 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1096 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1097 ierr = PetscFree(a->ipre);CHKERRQ(ierr); 1098 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1099 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1100 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1101 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1102 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1103 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1104 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1105 1106 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1107 ierr = PetscFree(A->data);CHKERRQ(ierr); 1108 1109 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1110 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1111 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1112 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1113 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1116 #if defined(PETSC_HAVE_ELEMENTAL) 1117 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); 1118 #endif 1119 #if defined(PETSC_HAVE_HYPRE) 1120 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_hypre_C",NULL);CHKERRQ(ierr); 1121 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMatMatMult_transpose_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1122 #endif 1123 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1124 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsell_C",NULL);CHKERRQ(ierr); 1125 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_is_C",NULL);CHKERRQ(ierr); 1126 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1127 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1128 ierr = PetscObjectComposeFunction((PetscObject)A,"MatResetPreallocation_C",NULL);CHKERRQ(ierr); 1129 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1130 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1131 ierr = PetscObjectComposeFunction((PetscObject)A,"MatPtAP_is_seqaij_C",NULL);CHKERRQ(ierr); 1132 PetscFunctionReturn(0); 1133 } 1134 1135 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1136 { 1137 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1138 PetscErrorCode ierr; 1139 1140 PetscFunctionBegin; 1141 switch (op) { 1142 case MAT_ROW_ORIENTED: 1143 a->roworiented = flg; 1144 break; 1145 case MAT_KEEP_NONZERO_PATTERN: 1146 a->keepnonzeropattern = flg; 1147 break; 1148 case MAT_NEW_NONZERO_LOCATIONS: 1149 a->nonew = (flg ? 0 : 1); 1150 break; 1151 case MAT_NEW_NONZERO_LOCATION_ERR: 1152 a->nonew = (flg ? -1 : 0); 1153 break; 1154 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1155 a->nonew = (flg ? -2 : 0); 1156 break; 1157 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1158 a->nounused = (flg ? -1 : 0); 1159 break; 1160 case MAT_IGNORE_ZERO_ENTRIES: 1161 a->ignorezeroentries = flg; 1162 break; 1163 case MAT_SPD: 1164 case MAT_SYMMETRIC: 1165 case MAT_STRUCTURALLY_SYMMETRIC: 1166 case MAT_HERMITIAN: 1167 case MAT_SYMMETRY_ETERNAL: 1168 case MAT_STRUCTURE_ONLY: 1169 /* These options are handled directly by MatSetOption() */ 1170 break; 1171 case MAT_NEW_DIAGONALS: 1172 case MAT_IGNORE_OFF_PROC_ENTRIES: 1173 case MAT_USE_HASH_TABLE: 1174 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1175 break; 1176 case MAT_USE_INODES: 1177 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1178 break; 1179 case MAT_SUBMAT_SINGLEIS: 1180 A->submat_singleis = flg; 1181 break; 1182 default: 1183 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1184 } 1185 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1186 PetscFunctionReturn(0); 1187 } 1188 1189 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1190 { 1191 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1192 PetscErrorCode ierr; 1193 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1194 PetscScalar *aa=a->a,*x,zero=0.0; 1195 1196 PetscFunctionBegin; 1197 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1198 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1199 1200 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1201 PetscInt *diag=a->diag; 1202 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1203 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1204 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1205 PetscFunctionReturn(0); 1206 } 1207 1208 ierr = VecSet(v,zero);CHKERRQ(ierr); 1209 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1210 for (i=0; i<n; i++) { 1211 nz = ai[i+1] - ai[i]; 1212 if (!nz) x[i] = 0.0; 1213 for (j=ai[i]; j<ai[i+1]; j++) { 1214 if (aj[j] == i) { 1215 x[i] = aa[j]; 1216 break; 1217 } 1218 } 1219 } 1220 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1221 PetscFunctionReturn(0); 1222 } 1223 1224 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1225 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1226 { 1227 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1228 PetscScalar *y; 1229 const PetscScalar *x; 1230 PetscErrorCode ierr; 1231 PetscInt m = A->rmap->n; 1232 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1233 const MatScalar *v; 1234 PetscScalar alpha; 1235 PetscInt n,i,j; 1236 const PetscInt *idx,*ii,*ridx=NULL; 1237 Mat_CompressedRow cprow = a->compressedrow; 1238 PetscBool usecprow = cprow.use; 1239 #endif 1240 1241 PetscFunctionBegin; 1242 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1243 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1244 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1245 1246 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1247 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1248 #else 1249 if (usecprow) { 1250 m = cprow.nrows; 1251 ii = cprow.i; 1252 ridx = cprow.rindex; 1253 } else { 1254 ii = a->i; 1255 } 1256 for (i=0; i<m; i++) { 1257 idx = a->j + ii[i]; 1258 v = a->a + ii[i]; 1259 n = ii[i+1] - ii[i]; 1260 if (usecprow) { 1261 alpha = x[ridx[i]]; 1262 } else { 1263 alpha = x[i]; 1264 } 1265 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1266 } 1267 #endif 1268 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1269 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1270 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1271 PetscFunctionReturn(0); 1272 } 1273 1274 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1275 { 1276 PetscErrorCode ierr; 1277 1278 PetscFunctionBegin; 1279 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1280 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1281 PetscFunctionReturn(0); 1282 } 1283 1284 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1285 1286 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1287 { 1288 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1289 PetscScalar *y; 1290 const PetscScalar *x; 1291 const MatScalar *aa; 1292 PetscErrorCode ierr; 1293 PetscInt m=A->rmap->n; 1294 const PetscInt *aj,*ii,*ridx=NULL; 1295 PetscInt n,i; 1296 PetscScalar sum; 1297 PetscBool usecprow=a->compressedrow.use; 1298 1299 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1300 #pragma disjoint(*x,*y,*aa) 1301 #endif 1302 1303 PetscFunctionBegin; 1304 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1305 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1306 ii = a->i; 1307 if (usecprow) { /* use compressed row format */ 1308 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1309 m = a->compressedrow.nrows; 1310 ii = a->compressedrow.i; 1311 ridx = a->compressedrow.rindex; 1312 for (i=0; i<m; i++) { 1313 n = ii[i+1] - ii[i]; 1314 aj = a->j + ii[i]; 1315 aa = a->a + ii[i]; 1316 sum = 0.0; 1317 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1318 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1319 y[*ridx++] = sum; 1320 } 1321 } else { /* do not use compressed row format */ 1322 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1323 aj = a->j; 1324 aa = a->a; 1325 fortranmultaij_(&m,x,ii,aj,aa,y); 1326 #else 1327 for (i=0; i<m; i++) { 1328 n = ii[i+1] - ii[i]; 1329 aj = a->j + ii[i]; 1330 aa = a->a + ii[i]; 1331 sum = 0.0; 1332 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1333 y[i] = sum; 1334 } 1335 #endif 1336 } 1337 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1338 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1339 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1340 PetscFunctionReturn(0); 1341 } 1342 1343 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1344 { 1345 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1346 PetscScalar *y; 1347 const PetscScalar *x; 1348 const MatScalar *aa; 1349 PetscErrorCode ierr; 1350 PetscInt m=A->rmap->n; 1351 const PetscInt *aj,*ii,*ridx=NULL; 1352 PetscInt n,i,nonzerorow=0; 1353 PetscScalar sum; 1354 PetscBool usecprow=a->compressedrow.use; 1355 1356 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1357 #pragma disjoint(*x,*y,*aa) 1358 #endif 1359 1360 PetscFunctionBegin; 1361 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1362 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1363 if (usecprow) { /* use compressed row format */ 1364 m = a->compressedrow.nrows; 1365 ii = a->compressedrow.i; 1366 ridx = a->compressedrow.rindex; 1367 for (i=0; i<m; i++) { 1368 n = ii[i+1] - ii[i]; 1369 aj = a->j + ii[i]; 1370 aa = a->a + ii[i]; 1371 sum = 0.0; 1372 nonzerorow += (n>0); 1373 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1374 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1375 y[*ridx++] = sum; 1376 } 1377 } else { /* do not use compressed row format */ 1378 ii = a->i; 1379 for (i=0; i<m; i++) { 1380 n = ii[i+1] - ii[i]; 1381 aj = a->j + ii[i]; 1382 aa = a->a + ii[i]; 1383 sum = 0.0; 1384 nonzerorow += (n>0); 1385 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1386 y[i] = sum; 1387 } 1388 } 1389 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1390 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1391 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1392 PetscFunctionReturn(0); 1393 } 1394 1395 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1396 { 1397 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1398 PetscScalar *y,*z; 1399 const PetscScalar *x; 1400 const MatScalar *aa; 1401 PetscErrorCode ierr; 1402 PetscInt m = A->rmap->n,*aj,*ii; 1403 PetscInt n,i,*ridx=NULL; 1404 PetscScalar sum; 1405 PetscBool usecprow=a->compressedrow.use; 1406 1407 PetscFunctionBegin; 1408 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1409 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1410 if (usecprow) { /* use compressed row format */ 1411 if (zz != yy) { 1412 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1413 } 1414 m = a->compressedrow.nrows; 1415 ii = a->compressedrow.i; 1416 ridx = a->compressedrow.rindex; 1417 for (i=0; i<m; i++) { 1418 n = ii[i+1] - ii[i]; 1419 aj = a->j + ii[i]; 1420 aa = a->a + ii[i]; 1421 sum = y[*ridx]; 1422 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1423 z[*ridx++] = sum; 1424 } 1425 } else { /* do not use compressed row format */ 1426 ii = a->i; 1427 for (i=0; i<m; i++) { 1428 n = ii[i+1] - ii[i]; 1429 aj = a->j + ii[i]; 1430 aa = a->a + ii[i]; 1431 sum = y[i]; 1432 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1433 z[i] = sum; 1434 } 1435 } 1436 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1437 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1438 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1439 PetscFunctionReturn(0); 1440 } 1441 1442 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1443 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1444 { 1445 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1446 PetscScalar *y,*z; 1447 const PetscScalar *x; 1448 const MatScalar *aa; 1449 PetscErrorCode ierr; 1450 const PetscInt *aj,*ii,*ridx=NULL; 1451 PetscInt m = A->rmap->n,n,i; 1452 PetscScalar sum; 1453 PetscBool usecprow=a->compressedrow.use; 1454 1455 PetscFunctionBegin; 1456 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1457 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1458 if (usecprow) { /* use compressed row format */ 1459 if (zz != yy) { 1460 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1461 } 1462 m = a->compressedrow.nrows; 1463 ii = a->compressedrow.i; 1464 ridx = a->compressedrow.rindex; 1465 for (i=0; i<m; i++) { 1466 n = ii[i+1] - ii[i]; 1467 aj = a->j + ii[i]; 1468 aa = a->a + ii[i]; 1469 sum = y[*ridx]; 1470 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1471 z[*ridx++] = sum; 1472 } 1473 } else { /* do not use compressed row format */ 1474 ii = a->i; 1475 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1476 aj = a->j; 1477 aa = a->a; 1478 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1479 #else 1480 for (i=0; i<m; i++) { 1481 n = ii[i+1] - ii[i]; 1482 aj = a->j + ii[i]; 1483 aa = a->a + ii[i]; 1484 sum = y[i]; 1485 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1486 z[i] = sum; 1487 } 1488 #endif 1489 } 1490 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1491 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1492 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1493 PetscFunctionReturn(0); 1494 } 1495 1496 /* 1497 Adds diagonal pointers to sparse matrix structure. 1498 */ 1499 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1500 { 1501 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1502 PetscErrorCode ierr; 1503 PetscInt i,j,m = A->rmap->n; 1504 1505 PetscFunctionBegin; 1506 if (!a->diag) { 1507 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1508 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1509 } 1510 for (i=0; i<A->rmap->n; i++) { 1511 a->diag[i] = a->i[i+1]; 1512 for (j=a->i[i]; j<a->i[i+1]; j++) { 1513 if (a->j[j] == i) { 1514 a->diag[i] = j; 1515 break; 1516 } 1517 } 1518 } 1519 PetscFunctionReturn(0); 1520 } 1521 1522 PetscErrorCode MatShift_SeqAIJ(Mat A,PetscScalar v) 1523 { 1524 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1525 const PetscInt *diag = (const PetscInt*)a->diag; 1526 const PetscInt *ii = (const PetscInt*) a->i; 1527 PetscInt i,*mdiag = NULL; 1528 PetscErrorCode ierr; 1529 PetscInt cnt = 0; /* how many diagonals are missing */ 1530 1531 PetscFunctionBegin; 1532 if (!A->preallocated || !a->nz) { 1533 ierr = MatSeqAIJSetPreallocation(A,1,NULL);CHKERRQ(ierr); 1534 ierr = MatShift_Basic(A,v);CHKERRQ(ierr); 1535 PetscFunctionReturn(0); 1536 } 1537 1538 if (a->diagonaldense) { 1539 cnt = 0; 1540 } else { 1541 ierr = PetscCalloc1(A->rmap->n,&mdiag);CHKERRQ(ierr); 1542 for (i=0; i<A->rmap->n; i++) { 1543 if (diag[i] >= ii[i+1]) { 1544 cnt++; 1545 mdiag[i] = 1; 1546 } 1547 } 1548 } 1549 if (!cnt) { 1550 ierr = MatShift_Basic(A,v);CHKERRQ(ierr); 1551 } else { 1552 PetscScalar *olda = a->a; /* preserve pointers to current matrix nonzeros structure and values */ 1553 PetscInt *oldj = a->j, *oldi = a->i; 1554 PetscBool singlemalloc = a->singlemalloc,free_a = a->free_a,free_ij = a->free_ij; 1555 1556 a->a = NULL; 1557 a->j = NULL; 1558 a->i = NULL; 1559 /* increase the values in imax for each row where a diagonal is being inserted then reallocate the matrix data structures */ 1560 for (i=0; i<A->rmap->n; i++) { 1561 a->imax[i] += mdiag[i]; 1562 a->imax[i] = PetscMin(a->imax[i],A->cmap->n); 1563 } 1564 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,0,a->imax);CHKERRQ(ierr); 1565 1566 /* copy old values into new matrix data structure */ 1567 for (i=0; i<A->rmap->n; i++) { 1568 ierr = MatSetValues(A,1,&i,a->imax[i] - mdiag[i],&oldj[oldi[i]],&olda[oldi[i]],ADD_VALUES);CHKERRQ(ierr); 1569 if (i < A->cmap->n) { 1570 ierr = MatSetValue(A,i,i,v,ADD_VALUES);CHKERRQ(ierr); 1571 } 1572 } 1573 ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1574 ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1575 if (singlemalloc) { 1576 ierr = PetscFree3(olda,oldj,oldi);CHKERRQ(ierr); 1577 } else { 1578 if (free_a) {ierr = PetscFree(olda);CHKERRQ(ierr);} 1579 if (free_ij) {ierr = PetscFree(oldj);CHKERRQ(ierr);} 1580 if (free_ij) {ierr = PetscFree(oldi);CHKERRQ(ierr);} 1581 } 1582 } 1583 ierr = PetscFree(mdiag);CHKERRQ(ierr); 1584 a->diagonaldense = PETSC_TRUE; 1585 PetscFunctionReturn(0); 1586 } 1587 1588 /* 1589 Checks for missing diagonals 1590 */ 1591 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1592 { 1593 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1594 PetscInt *diag,*ii = a->i,i; 1595 PetscErrorCode ierr; 1596 1597 PetscFunctionBegin; 1598 *missing = PETSC_FALSE; 1599 if (A->rmap->n > 0 && !ii) { 1600 *missing = PETSC_TRUE; 1601 if (d) *d = 0; 1602 ierr = PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");CHKERRQ(ierr); 1603 } else { 1604 diag = a->diag; 1605 for (i=0; i<A->rmap->n; i++) { 1606 if (diag[i] >= ii[i+1]) { 1607 *missing = PETSC_TRUE; 1608 if (d) *d = i; 1609 ierr = PetscInfo1(A,"Matrix is missing diagonal number %D\n",i);CHKERRQ(ierr); 1610 break; 1611 } 1612 } 1613 } 1614 PetscFunctionReturn(0); 1615 } 1616 1617 #include <petscblaslapack.h> 1618 #include <petsc/private/kernels/blockinvert.h> 1619 1620 /* 1621 Note that values is allocated externally by the PC and then passed into this routine 1622 */ 1623 PetscErrorCode MatInvertVariableBlockDiagonal_SeqAIJ(Mat A,PetscInt nblocks,const PetscInt *bsizes,PetscScalar *diag) 1624 { 1625 PetscErrorCode ierr; 1626 PetscInt n = A->rmap->n, i, ncnt = 0, *indx,j,bsizemax = 0,*v_pivots; 1627 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 1628 const PetscReal shift = 0.0; 1629 PetscInt ipvt[5]; 1630 PetscScalar work[25],*v_work; 1631 1632 PetscFunctionBegin; 1633 allowzeropivot = PetscNot(A->erroriffailure); 1634 for (i=0; i<nblocks; i++) ncnt += bsizes[i]; 1635 if (ncnt != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Total blocksizes %D doesn't match number matrix rows %D",ncnt,n); 1636 for (i=0; i<nblocks; i++) { 1637 bsizemax = PetscMax(bsizemax,bsizes[i]); 1638 } 1639 ierr = PetscMalloc1(bsizemax,&indx);CHKERRQ(ierr); 1640 if (bsizemax > 7) { 1641 ierr = PetscMalloc2(bsizemax,&v_work,bsizemax,&v_pivots);CHKERRQ(ierr); 1642 } 1643 ncnt = 0; 1644 for (i=0; i<nblocks; i++) { 1645 for (j=0; j<bsizes[i]; j++) indx[j] = ncnt+j; 1646 ierr = MatGetValues(A,bsizes[i],indx,bsizes[i],indx,diag);CHKERRQ(ierr); 1647 switch (bsizes[i]) { 1648 case 1: 1649 *diag = 1.0/(*diag); 1650 break; 1651 case 2: 1652 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1653 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1654 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 1655 break; 1656 case 3: 1657 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1658 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1659 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 1660 break; 1661 case 4: 1662 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1663 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1664 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 1665 break; 1666 case 5: 1667 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1668 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1669 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 1670 break; 1671 case 6: 1672 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1673 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1674 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 1675 break; 1676 case 7: 1677 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1678 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1679 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 1680 break; 1681 default: 1682 ierr = PetscKernel_A_gets_inverse_A(bsizes[i],diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 1683 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1684 ierr = PetscKernel_A_gets_transpose_A_N(diag,bsizes[i]);CHKERRQ(ierr); 1685 } 1686 ncnt += bsizes[i]; 1687 diag += bsizes[i]*bsizes[i]; 1688 } 1689 if (bsizemax > 7) { 1690 ierr = PetscFree2(v_work,v_pivots);CHKERRQ(ierr); 1691 } 1692 ierr = PetscFree(indx);CHKERRQ(ierr); 1693 PetscFunctionReturn(0); 1694 } 1695 1696 /* 1697 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1698 */ 1699 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1700 { 1701 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1702 PetscErrorCode ierr; 1703 PetscInt i,*diag,m = A->rmap->n; 1704 MatScalar *v = a->a; 1705 PetscScalar *idiag,*mdiag; 1706 1707 PetscFunctionBegin; 1708 if (a->idiagvalid) PetscFunctionReturn(0); 1709 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1710 diag = a->diag; 1711 if (!a->idiag) { 1712 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1713 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1714 v = a->a; 1715 } 1716 mdiag = a->mdiag; 1717 idiag = a->idiag; 1718 1719 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1720 for (i=0; i<m; i++) { 1721 mdiag[i] = v[diag[i]]; 1722 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1723 if (PetscRealPart(fshift)) { 1724 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1725 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1726 A->factorerror_zeropivot_value = 0.0; 1727 A->factorerror_zeropivot_row = i; 1728 } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1729 } 1730 idiag[i] = 1.0/v[diag[i]]; 1731 } 1732 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1733 } else { 1734 for (i=0; i<m; i++) { 1735 mdiag[i] = v[diag[i]]; 1736 idiag[i] = omega/(fshift + v[diag[i]]); 1737 } 1738 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1739 } 1740 a->idiagvalid = PETSC_TRUE; 1741 PetscFunctionReturn(0); 1742 } 1743 1744 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1745 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1746 { 1747 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1748 PetscScalar *x,d,sum,*t,scale; 1749 const MatScalar *v,*idiag=0,*mdiag; 1750 const PetscScalar *b, *bs,*xb, *ts; 1751 PetscErrorCode ierr; 1752 PetscInt n,m = A->rmap->n,i; 1753 const PetscInt *idx,*diag; 1754 1755 PetscFunctionBegin; 1756 its = its*lits; 1757 1758 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1759 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1760 a->fshift = fshift; 1761 a->omega = omega; 1762 1763 diag = a->diag; 1764 t = a->ssor_work; 1765 idiag = a->idiag; 1766 mdiag = a->mdiag; 1767 1768 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1769 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1770 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1771 if (flag == SOR_APPLY_UPPER) { 1772 /* apply (U + D/omega) to the vector */ 1773 bs = b; 1774 for (i=0; i<m; i++) { 1775 d = fshift + mdiag[i]; 1776 n = a->i[i+1] - diag[i] - 1; 1777 idx = a->j + diag[i] + 1; 1778 v = a->a + diag[i] + 1; 1779 sum = b[i]*d/omega; 1780 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1781 x[i] = sum; 1782 } 1783 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1784 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1785 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1786 PetscFunctionReturn(0); 1787 } 1788 1789 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1790 else if (flag & SOR_EISENSTAT) { 1791 /* Let A = L + U + D; where L is lower trianglar, 1792 U is upper triangular, E = D/omega; This routine applies 1793 1794 (L + E)^{-1} A (U + E)^{-1} 1795 1796 to a vector efficiently using Eisenstat's trick. 1797 */ 1798 scale = (2.0/omega) - 1.0; 1799 1800 /* x = (E + U)^{-1} b */ 1801 for (i=m-1; i>=0; i--) { 1802 n = a->i[i+1] - diag[i] - 1; 1803 idx = a->j + diag[i] + 1; 1804 v = a->a + diag[i] + 1; 1805 sum = b[i]; 1806 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1807 x[i] = sum*idiag[i]; 1808 } 1809 1810 /* t = b - (2*E - D)x */ 1811 v = a->a; 1812 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1813 1814 /* t = (E + L)^{-1}t */ 1815 ts = t; 1816 diag = a->diag; 1817 for (i=0; i<m; i++) { 1818 n = diag[i] - a->i[i]; 1819 idx = a->j + a->i[i]; 1820 v = a->a + a->i[i]; 1821 sum = t[i]; 1822 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1823 t[i] = sum*idiag[i]; 1824 /* x = x + t */ 1825 x[i] += t[i]; 1826 } 1827 1828 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1829 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1830 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1831 PetscFunctionReturn(0); 1832 } 1833 if (flag & SOR_ZERO_INITIAL_GUESS) { 1834 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1835 for (i=0; i<m; i++) { 1836 n = diag[i] - a->i[i]; 1837 idx = a->j + a->i[i]; 1838 v = a->a + a->i[i]; 1839 sum = b[i]; 1840 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1841 t[i] = sum; 1842 x[i] = sum*idiag[i]; 1843 } 1844 xb = t; 1845 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1846 } else xb = b; 1847 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1848 for (i=m-1; i>=0; i--) { 1849 n = a->i[i+1] - diag[i] - 1; 1850 idx = a->j + diag[i] + 1; 1851 v = a->a + diag[i] + 1; 1852 sum = xb[i]; 1853 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1854 if (xb == b) { 1855 x[i] = sum*idiag[i]; 1856 } else { 1857 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1858 } 1859 } 1860 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1861 } 1862 its--; 1863 } 1864 while (its--) { 1865 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1866 for (i=0; i<m; i++) { 1867 /* lower */ 1868 n = diag[i] - a->i[i]; 1869 idx = a->j + a->i[i]; 1870 v = a->a + a->i[i]; 1871 sum = b[i]; 1872 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1873 t[i] = sum; /* save application of the lower-triangular part */ 1874 /* upper */ 1875 n = a->i[i+1] - diag[i] - 1; 1876 idx = a->j + diag[i] + 1; 1877 v = a->a + diag[i] + 1; 1878 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1879 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1880 } 1881 xb = t; 1882 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1883 } else xb = b; 1884 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1885 for (i=m-1; i>=0; i--) { 1886 sum = xb[i]; 1887 if (xb == b) { 1888 /* whole matrix (no checkpointing available) */ 1889 n = a->i[i+1] - a->i[i]; 1890 idx = a->j + a->i[i]; 1891 v = a->a + a->i[i]; 1892 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1893 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1894 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1895 n = a->i[i+1] - diag[i] - 1; 1896 idx = a->j + diag[i] + 1; 1897 v = a->a + diag[i] + 1; 1898 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1899 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1900 } 1901 } 1902 if (xb == b) { 1903 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1904 } else { 1905 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1906 } 1907 } 1908 } 1909 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1910 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1911 PetscFunctionReturn(0); 1912 } 1913 1914 1915 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1916 { 1917 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1918 1919 PetscFunctionBegin; 1920 info->block_size = 1.0; 1921 info->nz_allocated = (double)a->maxnz; 1922 info->nz_used = (double)a->nz; 1923 info->nz_unneeded = (double)(a->maxnz - a->nz); 1924 info->assemblies = (double)A->num_ass; 1925 info->mallocs = (double)A->info.mallocs; 1926 info->memory = ((PetscObject)A)->mem; 1927 if (A->factortype) { 1928 info->fill_ratio_given = A->info.fill_ratio_given; 1929 info->fill_ratio_needed = A->info.fill_ratio_needed; 1930 info->factor_mallocs = A->info.factor_mallocs; 1931 } else { 1932 info->fill_ratio_given = 0; 1933 info->fill_ratio_needed = 0; 1934 info->factor_mallocs = 0; 1935 } 1936 PetscFunctionReturn(0); 1937 } 1938 1939 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1940 { 1941 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1942 PetscInt i,m = A->rmap->n - 1; 1943 PetscErrorCode ierr; 1944 const PetscScalar *xx; 1945 PetscScalar *bb; 1946 PetscInt d = 0; 1947 1948 PetscFunctionBegin; 1949 if (x && b) { 1950 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1951 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1952 for (i=0; i<N; i++) { 1953 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1954 if (rows[i] >= A->cmap->n) continue; 1955 bb[rows[i]] = diag*xx[rows[i]]; 1956 } 1957 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1958 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1959 } 1960 1961 if (a->keepnonzeropattern) { 1962 for (i=0; i<N; i++) { 1963 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1964 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1965 } 1966 if (diag != 0.0) { 1967 for (i=0; i<N; i++) { 1968 d = rows[i]; 1969 if (rows[i] >= A->cmap->n) continue; 1970 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); 1971 } 1972 for (i=0; i<N; i++) { 1973 if (rows[i] >= A->cmap->n) continue; 1974 a->a[a->diag[rows[i]]] = diag; 1975 } 1976 } 1977 } else { 1978 if (diag != 0.0) { 1979 for (i=0; i<N; i++) { 1980 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1981 if (a->ilen[rows[i]] > 0) { 1982 if (rows[i] >= A->cmap->n) { 1983 a->ilen[rows[i]] = 0; 1984 } else { 1985 a->ilen[rows[i]] = 1; 1986 a->a[a->i[rows[i]]] = diag; 1987 a->j[a->i[rows[i]]] = rows[i]; 1988 } 1989 } else if (rows[i] < A->cmap->n) { /* in case row was completely empty */ 1990 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1991 } 1992 } 1993 } else { 1994 for (i=0; i<N; i++) { 1995 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1996 a->ilen[rows[i]] = 0; 1997 } 1998 } 1999 A->nonzerostate++; 2000 } 2001 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2002 PetscFunctionReturn(0); 2003 } 2004 2005 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 2006 { 2007 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2008 PetscInt i,j,m = A->rmap->n - 1,d = 0; 2009 PetscErrorCode ierr; 2010 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 2011 const PetscScalar *xx; 2012 PetscScalar *bb; 2013 2014 PetscFunctionBegin; 2015 if (x && b) { 2016 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2017 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2018 vecs = PETSC_TRUE; 2019 } 2020 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 2021 for (i=0; i<N; i++) { 2022 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2023 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 2024 2025 zeroed[rows[i]] = PETSC_TRUE; 2026 } 2027 for (i=0; i<A->rmap->n; i++) { 2028 if (!zeroed[i]) { 2029 for (j=a->i[i]; j<a->i[i+1]; j++) { 2030 if (a->j[j] < A->rmap->n && zeroed[a->j[j]]) { 2031 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 2032 a->a[j] = 0.0; 2033 } 2034 } 2035 } else if (vecs && i < A->cmap->N) bb[i] = diag*xx[i]; 2036 } 2037 if (x && b) { 2038 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2039 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2040 } 2041 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2042 if (diag != 0.0) { 2043 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 2044 if (missing) { 2045 for (i=0; i<N; i++) { 2046 if (rows[i] >= A->cmap->N) continue; 2047 if (a->nonew && rows[i] >= d) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D (%D)",d,rows[i]); 2048 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 2049 } 2050 } else { 2051 for (i=0; i<N; i++) { 2052 a->a[a->diag[rows[i]]] = diag; 2053 } 2054 } 2055 } 2056 ierr = (*A->ops->assemblyend)(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2057 PetscFunctionReturn(0); 2058 } 2059 2060 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2061 { 2062 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2063 PetscInt *itmp; 2064 2065 PetscFunctionBegin; 2066 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 2067 2068 *nz = a->i[row+1] - a->i[row]; 2069 if (v) *v = a->a + a->i[row]; 2070 if (idx) { 2071 itmp = a->j + a->i[row]; 2072 if (*nz) *idx = itmp; 2073 else *idx = 0; 2074 } 2075 PetscFunctionReturn(0); 2076 } 2077 2078 /* remove this function? */ 2079 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2080 { 2081 PetscFunctionBegin; 2082 PetscFunctionReturn(0); 2083 } 2084 2085 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 2086 { 2087 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2088 MatScalar *v = a->a; 2089 PetscReal sum = 0.0; 2090 PetscErrorCode ierr; 2091 PetscInt i,j; 2092 2093 PetscFunctionBegin; 2094 if (type == NORM_FROBENIUS) { 2095 #if defined(PETSC_USE_REAL___FP16) 2096 PetscBLASInt one = 1,nz = a->nz; 2097 *nrm = BLASnrm2_(&nz,v,&one); 2098 #else 2099 for (i=0; i<a->nz; i++) { 2100 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2101 } 2102 *nrm = PetscSqrtReal(sum); 2103 #endif 2104 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 2105 } else if (type == NORM_1) { 2106 PetscReal *tmp; 2107 PetscInt *jj = a->j; 2108 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 2109 *nrm = 0.0; 2110 for (j=0; j<a->nz; j++) { 2111 tmp[*jj++] += PetscAbsScalar(*v); v++; 2112 } 2113 for (j=0; j<A->cmap->n; j++) { 2114 if (tmp[j] > *nrm) *nrm = tmp[j]; 2115 } 2116 ierr = PetscFree(tmp);CHKERRQ(ierr); 2117 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 2118 } else if (type == NORM_INFINITY) { 2119 *nrm = 0.0; 2120 for (j=0; j<A->rmap->n; j++) { 2121 v = a->a + a->i[j]; 2122 sum = 0.0; 2123 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2124 sum += PetscAbsScalar(*v); v++; 2125 } 2126 if (sum > *nrm) *nrm = sum; 2127 } 2128 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 2129 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2130 PetscFunctionReturn(0); 2131 } 2132 2133 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2134 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2135 { 2136 PetscErrorCode ierr; 2137 PetscInt i,j,anzj; 2138 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2139 PetscInt an=A->cmap->N,am=A->rmap->N; 2140 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2141 2142 PetscFunctionBegin; 2143 /* Allocate space for symbolic transpose info and work array */ 2144 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 2145 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 2146 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 2147 2148 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2149 /* Note: offset by 1 for fast conversion into csr format. */ 2150 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2151 /* Form ati for csr format of A^T. */ 2152 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2153 2154 /* Copy ati into atfill so we have locations of the next free space in atj */ 2155 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2156 2157 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2158 for (i=0;i<am;i++) { 2159 anzj = ai[i+1] - ai[i]; 2160 for (j=0;j<anzj;j++) { 2161 atj[atfill[*aj]] = i; 2162 atfill[*aj++] += 1; 2163 } 2164 } 2165 2166 /* Clean up temporary space and complete requests. */ 2167 ierr = PetscFree(atfill);CHKERRQ(ierr); 2168 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2169 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2170 2171 b = (Mat_SeqAIJ*)((*B)->data); 2172 b->free_a = PETSC_FALSE; 2173 b->free_ij = PETSC_TRUE; 2174 b->nonew = 0; 2175 PetscFunctionReturn(0); 2176 } 2177 2178 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2179 { 2180 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2181 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2182 MatScalar *va,*vb; 2183 PetscErrorCode ierr; 2184 PetscInt ma,na,mb,nb, i; 2185 2186 PetscFunctionBegin; 2187 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2188 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2189 if (ma!=nb || na!=mb) { 2190 *f = PETSC_FALSE; 2191 PetscFunctionReturn(0); 2192 } 2193 aii = aij->i; bii = bij->i; 2194 adx = aij->j; bdx = bij->j; 2195 va = aij->a; vb = bij->a; 2196 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2197 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2198 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2199 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2200 2201 *f = PETSC_TRUE; 2202 for (i=0; i<ma; i++) { 2203 while (aptr[i]<aii[i+1]) { 2204 PetscInt idc,idr; 2205 PetscScalar vc,vr; 2206 /* column/row index/value */ 2207 idc = adx[aptr[i]]; 2208 idr = bdx[bptr[idc]]; 2209 vc = va[aptr[i]]; 2210 vr = vb[bptr[idc]]; 2211 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2212 *f = PETSC_FALSE; 2213 goto done; 2214 } else { 2215 aptr[i]++; 2216 if (B || i!=idc) bptr[idc]++; 2217 } 2218 } 2219 } 2220 done: 2221 ierr = PetscFree(aptr);CHKERRQ(ierr); 2222 ierr = PetscFree(bptr);CHKERRQ(ierr); 2223 PetscFunctionReturn(0); 2224 } 2225 2226 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2227 { 2228 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2229 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2230 MatScalar *va,*vb; 2231 PetscErrorCode ierr; 2232 PetscInt ma,na,mb,nb, i; 2233 2234 PetscFunctionBegin; 2235 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2236 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2237 if (ma!=nb || na!=mb) { 2238 *f = PETSC_FALSE; 2239 PetscFunctionReturn(0); 2240 } 2241 aii = aij->i; bii = bij->i; 2242 adx = aij->j; bdx = bij->j; 2243 va = aij->a; vb = bij->a; 2244 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2245 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2246 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2247 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2248 2249 *f = PETSC_TRUE; 2250 for (i=0; i<ma; i++) { 2251 while (aptr[i]<aii[i+1]) { 2252 PetscInt idc,idr; 2253 PetscScalar vc,vr; 2254 /* column/row index/value */ 2255 idc = adx[aptr[i]]; 2256 idr = bdx[bptr[idc]]; 2257 vc = va[aptr[i]]; 2258 vr = vb[bptr[idc]]; 2259 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2260 *f = PETSC_FALSE; 2261 goto done; 2262 } else { 2263 aptr[i]++; 2264 if (B || i!=idc) bptr[idc]++; 2265 } 2266 } 2267 } 2268 done: 2269 ierr = PetscFree(aptr);CHKERRQ(ierr); 2270 ierr = PetscFree(bptr);CHKERRQ(ierr); 2271 PetscFunctionReturn(0); 2272 } 2273 2274 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2275 { 2276 PetscErrorCode ierr; 2277 2278 PetscFunctionBegin; 2279 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2280 PetscFunctionReturn(0); 2281 } 2282 2283 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2284 { 2285 PetscErrorCode ierr; 2286 2287 PetscFunctionBegin; 2288 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2289 PetscFunctionReturn(0); 2290 } 2291 2292 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2293 { 2294 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2295 const PetscScalar *l,*r; 2296 PetscScalar x; 2297 MatScalar *v; 2298 PetscErrorCode ierr; 2299 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz; 2300 const PetscInt *jj; 2301 2302 PetscFunctionBegin; 2303 if (ll) { 2304 /* The local size is used so that VecMPI can be passed to this routine 2305 by MatDiagonalScale_MPIAIJ */ 2306 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2307 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2308 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 2309 v = a->a; 2310 for (i=0; i<m; i++) { 2311 x = l[i]; 2312 M = a->i[i+1] - a->i[i]; 2313 for (j=0; j<M; j++) (*v++) *= x; 2314 } 2315 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 2316 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2317 } 2318 if (rr) { 2319 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2320 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2321 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 2322 v = a->a; jj = a->j; 2323 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2324 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 2325 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2326 } 2327 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2328 PetscFunctionReturn(0); 2329 } 2330 2331 PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2332 { 2333 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2334 PetscErrorCode ierr; 2335 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2336 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2337 const PetscInt *irow,*icol; 2338 PetscInt nrows,ncols; 2339 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2340 MatScalar *a_new,*mat_a; 2341 Mat C; 2342 PetscBool stride; 2343 2344 PetscFunctionBegin; 2345 2346 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2347 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2348 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2349 2350 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2351 if (stride) { 2352 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2353 } else { 2354 first = 0; 2355 step = 0; 2356 } 2357 if (stride && step == 1) { 2358 /* special case of contiguous rows */ 2359 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2360 /* loop over new rows determining lens and starting points */ 2361 for (i=0; i<nrows; i++) { 2362 kstart = ai[irow[i]]; 2363 kend = kstart + ailen[irow[i]]; 2364 starts[i] = kstart; 2365 for (k=kstart; k<kend; k++) { 2366 if (aj[k] >= first) { 2367 starts[i] = k; 2368 break; 2369 } 2370 } 2371 sum = 0; 2372 while (k < kend) { 2373 if (aj[k++] >= first+ncols) break; 2374 sum++; 2375 } 2376 lens[i] = sum; 2377 } 2378 /* create submatrix */ 2379 if (scall == MAT_REUSE_MATRIX) { 2380 PetscInt n_cols,n_rows; 2381 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2382 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2383 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2384 C = *B; 2385 } else { 2386 PetscInt rbs,cbs; 2387 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2388 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2389 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2390 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2391 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2392 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2393 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2394 } 2395 c = (Mat_SeqAIJ*)C->data; 2396 2397 /* loop over rows inserting into submatrix */ 2398 a_new = c->a; 2399 j_new = c->j; 2400 i_new = c->i; 2401 2402 for (i=0; i<nrows; i++) { 2403 ii = starts[i]; 2404 lensi = lens[i]; 2405 for (k=0; k<lensi; k++) { 2406 *j_new++ = aj[ii+k] - first; 2407 } 2408 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2409 a_new += lensi; 2410 i_new[i+1] = i_new[i] + lensi; 2411 c->ilen[i] = lensi; 2412 } 2413 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2414 } else { 2415 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2416 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2417 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2418 for (i=0; i<ncols; i++) { 2419 #if defined(PETSC_USE_DEBUG) 2420 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); 2421 #endif 2422 smap[icol[i]] = i+1; 2423 } 2424 2425 /* determine lens of each row */ 2426 for (i=0; i<nrows; i++) { 2427 kstart = ai[irow[i]]; 2428 kend = kstart + a->ilen[irow[i]]; 2429 lens[i] = 0; 2430 for (k=kstart; k<kend; k++) { 2431 if (smap[aj[k]]) { 2432 lens[i]++; 2433 } 2434 } 2435 } 2436 /* Create and fill new matrix */ 2437 if (scall == MAT_REUSE_MATRIX) { 2438 PetscBool equal; 2439 2440 c = (Mat_SeqAIJ*)((*B)->data); 2441 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2442 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2443 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2444 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2445 C = *B; 2446 } else { 2447 PetscInt rbs,cbs; 2448 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2449 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2450 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2451 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2452 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2453 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2454 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2455 } 2456 c = (Mat_SeqAIJ*)(C->data); 2457 for (i=0; i<nrows; i++) { 2458 row = irow[i]; 2459 kstart = ai[row]; 2460 kend = kstart + a->ilen[row]; 2461 mat_i = c->i[i]; 2462 mat_j = c->j + mat_i; 2463 mat_a = c->a + mat_i; 2464 mat_ilen = c->ilen + i; 2465 for (k=kstart; k<kend; k++) { 2466 if ((tcol=smap[a->j[k]])) { 2467 *mat_j++ = tcol - 1; 2468 *mat_a++ = a->a[k]; 2469 (*mat_ilen)++; 2470 2471 } 2472 } 2473 } 2474 /* Free work space */ 2475 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2476 ierr = PetscFree(smap);CHKERRQ(ierr); 2477 ierr = PetscFree(lens);CHKERRQ(ierr); 2478 /* sort */ 2479 for (i = 0; i < nrows; i++) { 2480 PetscInt ilen; 2481 2482 mat_i = c->i[i]; 2483 mat_j = c->j + mat_i; 2484 mat_a = c->a + mat_i; 2485 ilen = c->ilen[i]; 2486 ierr = PetscSortIntWithScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2487 } 2488 } 2489 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2490 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2491 2492 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2493 *B = C; 2494 PetscFunctionReturn(0); 2495 } 2496 2497 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2498 { 2499 PetscErrorCode ierr; 2500 Mat B; 2501 2502 PetscFunctionBegin; 2503 if (scall == MAT_INITIAL_MATRIX) { 2504 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2505 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2506 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2507 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2508 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2509 *subMat = B; 2510 } else { 2511 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2512 } 2513 PetscFunctionReturn(0); 2514 } 2515 2516 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2517 { 2518 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2519 PetscErrorCode ierr; 2520 Mat outA; 2521 PetscBool row_identity,col_identity; 2522 2523 PetscFunctionBegin; 2524 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2525 2526 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2527 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2528 2529 outA = inA; 2530 outA->factortype = MAT_FACTOR_LU; 2531 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2532 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2533 2534 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2535 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2536 2537 a->row = row; 2538 2539 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2540 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2541 2542 a->col = col; 2543 2544 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2545 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2546 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2547 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2548 2549 if (!a->solve_work) { /* this matrix may have been factored before */ 2550 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2551 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2552 } 2553 2554 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2555 if (row_identity && col_identity) { 2556 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2557 } else { 2558 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2559 } 2560 PetscFunctionReturn(0); 2561 } 2562 2563 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2564 { 2565 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2566 PetscScalar oalpha = alpha; 2567 PetscErrorCode ierr; 2568 PetscBLASInt one = 1,bnz; 2569 2570 PetscFunctionBegin; 2571 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2572 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2573 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2574 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2575 PetscFunctionReturn(0); 2576 } 2577 2578 PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *submatj) 2579 { 2580 PetscErrorCode ierr; 2581 PetscInt i; 2582 2583 PetscFunctionBegin; 2584 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2585 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2586 2587 for (i=0; i<submatj->nrqr; ++i) { 2588 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2589 } 2590 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2591 2592 if (submatj->rbuf1) { 2593 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2594 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2595 } 2596 2597 for (i=0; i<submatj->nrqs; ++i) { 2598 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2599 } 2600 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2601 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2602 } 2603 2604 #if defined(PETSC_USE_CTABLE) 2605 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2606 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2607 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2608 #else 2609 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2610 #endif 2611 2612 if (!submatj->allcolumns) { 2613 #if defined(PETSC_USE_CTABLE) 2614 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2615 #else 2616 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2617 #endif 2618 } 2619 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2620 2621 ierr = PetscFree(submatj);CHKERRQ(ierr); 2622 PetscFunctionReturn(0); 2623 } 2624 2625 PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat C) 2626 { 2627 PetscErrorCode ierr; 2628 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2629 Mat_SubSppt *submatj = c->submatis1; 2630 2631 PetscFunctionBegin; 2632 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2633 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2634 PetscFunctionReturn(0); 2635 } 2636 2637 PetscErrorCode MatDestroySubMatrices_SeqAIJ(PetscInt n,Mat *mat[]) 2638 { 2639 PetscErrorCode ierr; 2640 PetscInt i; 2641 Mat C; 2642 Mat_SeqAIJ *c; 2643 Mat_SubSppt *submatj; 2644 2645 PetscFunctionBegin; 2646 for (i=0; i<n; i++) { 2647 C = (*mat)[i]; 2648 c = (Mat_SeqAIJ*)C->data; 2649 submatj = c->submatis1; 2650 if (submatj) { 2651 if (--((PetscObject)C)->refct <= 0) { 2652 ierr = (*submatj->destroy)(C);CHKERRQ(ierr); 2653 ierr = MatDestroySubMatrix_Private(submatj);CHKERRQ(ierr); 2654 ierr = PetscFree(C->defaultvectype);CHKERRQ(ierr); 2655 ierr = PetscLayoutDestroy(&C->rmap);CHKERRQ(ierr); 2656 ierr = PetscLayoutDestroy(&C->cmap);CHKERRQ(ierr); 2657 ierr = PetscHeaderDestroy(&C);CHKERRQ(ierr); 2658 } 2659 } else { 2660 ierr = MatDestroy(&C);CHKERRQ(ierr); 2661 } 2662 } 2663 2664 /* Destroy Dummy submatrices created for reuse */ 2665 ierr = MatDestroySubMatrices_Dummy(n,mat);CHKERRQ(ierr); 2666 2667 ierr = PetscFree(*mat);CHKERRQ(ierr); 2668 PetscFunctionReturn(0); 2669 } 2670 2671 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2672 { 2673 PetscErrorCode ierr; 2674 PetscInt i; 2675 2676 PetscFunctionBegin; 2677 if (scall == MAT_INITIAL_MATRIX) { 2678 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2679 } 2680 2681 for (i=0; i<n; i++) { 2682 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2683 } 2684 PetscFunctionReturn(0); 2685 } 2686 2687 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2688 { 2689 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2690 PetscErrorCode ierr; 2691 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2692 const PetscInt *idx; 2693 PetscInt start,end,*ai,*aj; 2694 PetscBT table; 2695 2696 PetscFunctionBegin; 2697 m = A->rmap->n; 2698 ai = a->i; 2699 aj = a->j; 2700 2701 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2702 2703 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2704 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2705 2706 for (i=0; i<is_max; i++) { 2707 /* Initialize the two local arrays */ 2708 isz = 0; 2709 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2710 2711 /* Extract the indices, assume there can be duplicate entries */ 2712 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2713 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2714 2715 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2716 for (j=0; j<n; ++j) { 2717 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2718 } 2719 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2720 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2721 2722 k = 0; 2723 for (j=0; j<ov; j++) { /* for each overlap */ 2724 n = isz; 2725 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2726 row = nidx[k]; 2727 start = ai[row]; 2728 end = ai[row+1]; 2729 for (l = start; l<end; l++) { 2730 val = aj[l]; 2731 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2732 } 2733 } 2734 } 2735 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2736 } 2737 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2738 ierr = PetscFree(nidx);CHKERRQ(ierr); 2739 PetscFunctionReturn(0); 2740 } 2741 2742 /* -------------------------------------------------------------- */ 2743 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2744 { 2745 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2746 PetscErrorCode ierr; 2747 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2748 const PetscInt *row,*col; 2749 PetscInt *cnew,j,*lens; 2750 IS icolp,irowp; 2751 PetscInt *cwork = NULL; 2752 PetscScalar *vwork = NULL; 2753 2754 PetscFunctionBegin; 2755 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2756 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2757 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2758 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2759 2760 /* determine lengths of permuted rows */ 2761 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2762 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2763 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2764 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2765 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2766 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2767 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2768 ierr = PetscFree(lens);CHKERRQ(ierr); 2769 2770 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2771 for (i=0; i<m; i++) { 2772 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2773 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2774 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2775 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2776 } 2777 ierr = PetscFree(cnew);CHKERRQ(ierr); 2778 2779 (*B)->assembled = PETSC_FALSE; 2780 2781 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2782 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2783 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2784 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2785 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2786 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2787 PetscFunctionReturn(0); 2788 } 2789 2790 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2791 { 2792 PetscErrorCode ierr; 2793 2794 PetscFunctionBegin; 2795 /* If the two matrices have the same copy implementation, use fast copy. */ 2796 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2797 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2798 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2799 2800 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"); 2801 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2802 ierr = PetscObjectStateIncrease((PetscObject)B);CHKERRQ(ierr); 2803 } else { 2804 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2805 } 2806 PetscFunctionReturn(0); 2807 } 2808 2809 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2810 { 2811 PetscErrorCode ierr; 2812 2813 PetscFunctionBegin; 2814 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2815 PetscFunctionReturn(0); 2816 } 2817 2818 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2819 { 2820 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2821 2822 PetscFunctionBegin; 2823 *array = a->a; 2824 PetscFunctionReturn(0); 2825 } 2826 2827 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2828 { 2829 PetscFunctionBegin; 2830 PetscFunctionReturn(0); 2831 } 2832 2833 /* 2834 Computes the number of nonzeros per row needed for preallocation when X and Y 2835 have different nonzero structure. 2836 */ 2837 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2838 { 2839 PetscInt i,j,k,nzx,nzy; 2840 2841 PetscFunctionBegin; 2842 /* Set the number of nonzeros in the new matrix */ 2843 for (i=0; i<m; i++) { 2844 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2845 nzx = xi[i+1] - xi[i]; 2846 nzy = yi[i+1] - yi[i]; 2847 nnz[i] = 0; 2848 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2849 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2850 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2851 nnz[i]++; 2852 } 2853 for (; k<nzy; k++) nnz[i]++; 2854 } 2855 PetscFunctionReturn(0); 2856 } 2857 2858 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2859 { 2860 PetscInt m = Y->rmap->N; 2861 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2862 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2863 PetscErrorCode ierr; 2864 2865 PetscFunctionBegin; 2866 /* Set the number of nonzeros in the new matrix */ 2867 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2868 PetscFunctionReturn(0); 2869 } 2870 2871 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2872 { 2873 PetscErrorCode ierr; 2874 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2875 PetscBLASInt one=1,bnz; 2876 2877 PetscFunctionBegin; 2878 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2879 if (str == SAME_NONZERO_PATTERN) { 2880 PetscScalar alpha = a; 2881 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2882 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2883 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2884 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2885 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2886 } else { 2887 Mat B; 2888 PetscInt *nnz; 2889 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2890 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2891 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2892 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2893 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2894 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2895 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2896 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2897 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2898 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2899 ierr = PetscFree(nnz);CHKERRQ(ierr); 2900 } 2901 PetscFunctionReturn(0); 2902 } 2903 2904 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2905 { 2906 #if defined(PETSC_USE_COMPLEX) 2907 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2908 PetscInt i,nz; 2909 PetscScalar *a; 2910 2911 PetscFunctionBegin; 2912 nz = aij->nz; 2913 a = aij->a; 2914 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2915 #else 2916 PetscFunctionBegin; 2917 #endif 2918 PetscFunctionReturn(0); 2919 } 2920 2921 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2922 { 2923 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2924 PetscErrorCode ierr; 2925 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2926 PetscReal atmp; 2927 PetscScalar *x; 2928 MatScalar *aa; 2929 2930 PetscFunctionBegin; 2931 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2932 aa = a->a; 2933 ai = a->i; 2934 aj = a->j; 2935 2936 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2937 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2938 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2939 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2940 for (i=0; i<m; i++) { 2941 ncols = ai[1] - ai[0]; ai++; 2942 x[i] = 0.0; 2943 for (j=0; j<ncols; j++) { 2944 atmp = PetscAbsScalar(*aa); 2945 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2946 aa++; aj++; 2947 } 2948 } 2949 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2950 PetscFunctionReturn(0); 2951 } 2952 2953 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2954 { 2955 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2956 PetscErrorCode ierr; 2957 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2958 PetscScalar *x; 2959 MatScalar *aa; 2960 2961 PetscFunctionBegin; 2962 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2963 aa = a->a; 2964 ai = a->i; 2965 aj = a->j; 2966 2967 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2968 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2969 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2970 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2971 for (i=0; i<m; i++) { 2972 ncols = ai[1] - ai[0]; ai++; 2973 if (ncols == A->cmap->n) { /* row is dense */ 2974 x[i] = *aa; if (idx) idx[i] = 0; 2975 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2976 x[i] = 0.0; 2977 if (idx) { 2978 idx[i] = 0; /* in case ncols is zero */ 2979 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2980 if (aj[j] > j) { 2981 idx[i] = j; 2982 break; 2983 } 2984 } 2985 } 2986 } 2987 for (j=0; j<ncols; j++) { 2988 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2989 aa++; aj++; 2990 } 2991 } 2992 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2993 PetscFunctionReturn(0); 2994 } 2995 2996 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2997 { 2998 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2999 PetscErrorCode ierr; 3000 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3001 PetscReal atmp; 3002 PetscScalar *x; 3003 MatScalar *aa; 3004 3005 PetscFunctionBegin; 3006 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3007 aa = a->a; 3008 ai = a->i; 3009 aj = a->j; 3010 3011 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3012 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3013 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3014 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); 3015 for (i=0; i<m; i++) { 3016 ncols = ai[1] - ai[0]; ai++; 3017 if (ncols) { 3018 /* Get first nonzero */ 3019 for (j = 0; j < ncols; j++) { 3020 atmp = PetscAbsScalar(aa[j]); 3021 if (atmp > 1.0e-12) { 3022 x[i] = atmp; 3023 if (idx) idx[i] = aj[j]; 3024 break; 3025 } 3026 } 3027 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3028 } else { 3029 x[i] = 0.0; if (idx) idx[i] = 0; 3030 } 3031 for (j = 0; j < ncols; j++) { 3032 atmp = PetscAbsScalar(*aa); 3033 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3034 aa++; aj++; 3035 } 3036 } 3037 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3038 PetscFunctionReturn(0); 3039 } 3040 3041 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3042 { 3043 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3044 PetscErrorCode ierr; 3045 PetscInt i,j,m = A->rmap->n,ncols,n; 3046 const PetscInt *ai,*aj; 3047 PetscScalar *x; 3048 const MatScalar *aa; 3049 3050 PetscFunctionBegin; 3051 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3052 aa = a->a; 3053 ai = a->i; 3054 aj = a->j; 3055 3056 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3057 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3058 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3059 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3060 for (i=0; i<m; i++) { 3061 ncols = ai[1] - ai[0]; ai++; 3062 if (ncols == A->cmap->n) { /* row is dense */ 3063 x[i] = *aa; if (idx) idx[i] = 0; 3064 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3065 x[i] = 0.0; 3066 if (idx) { /* find first implicit 0.0 in the row */ 3067 idx[i] = 0; /* in case ncols is zero */ 3068 for (j=0; j<ncols; j++) { 3069 if (aj[j] > j) { 3070 idx[i] = j; 3071 break; 3072 } 3073 } 3074 } 3075 } 3076 for (j=0; j<ncols; j++) { 3077 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3078 aa++; aj++; 3079 } 3080 } 3081 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3082 PetscFunctionReturn(0); 3083 } 3084 3085 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3086 { 3087 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3088 PetscErrorCode ierr; 3089 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3090 MatScalar *diag,work[25],*v_work; 3091 const PetscReal shift = 0.0; 3092 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 3093 3094 PetscFunctionBegin; 3095 allowzeropivot = PetscNot(A->erroriffailure); 3096 if (a->ibdiagvalid) { 3097 if (values) *values = a->ibdiag; 3098 PetscFunctionReturn(0); 3099 } 3100 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3101 if (!a->ibdiag) { 3102 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3103 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3104 } 3105 diag = a->ibdiag; 3106 if (values) *values = a->ibdiag; 3107 /* factor and invert each block */ 3108 switch (bs) { 3109 case 1: 3110 for (i=0; i<mbs; i++) { 3111 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3112 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 3113 if (allowzeropivot) { 3114 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3115 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 3116 A->factorerror_zeropivot_row = i; 3117 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 3118 } 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); 3119 } 3120 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3121 } 3122 break; 3123 case 2: 3124 for (i=0; i<mbs; i++) { 3125 ij[0] = 2*i; ij[1] = 2*i + 1; 3126 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3127 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3128 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3129 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3130 diag += 4; 3131 } 3132 break; 3133 case 3: 3134 for (i=0; i<mbs; i++) { 3135 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3136 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3137 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3138 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3139 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3140 diag += 9; 3141 } 3142 break; 3143 case 4: 3144 for (i=0; i<mbs; i++) { 3145 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3146 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3147 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3148 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3149 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3150 diag += 16; 3151 } 3152 break; 3153 case 5: 3154 for (i=0; i<mbs; i++) { 3155 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3156 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3157 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3158 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3159 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3160 diag += 25; 3161 } 3162 break; 3163 case 6: 3164 for (i=0; i<mbs; i++) { 3165 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; 3166 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3167 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3168 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3169 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3170 diag += 36; 3171 } 3172 break; 3173 case 7: 3174 for (i=0; i<mbs; i++) { 3175 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; 3176 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3177 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3178 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3179 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3180 diag += 49; 3181 } 3182 break; 3183 default: 3184 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3185 for (i=0; i<mbs; i++) { 3186 for (j=0; j<bs; j++) { 3187 IJ[j] = bs*i + j; 3188 } 3189 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3190 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3191 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3192 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3193 diag += bs2; 3194 } 3195 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3196 } 3197 a->ibdiagvalid = PETSC_TRUE; 3198 PetscFunctionReturn(0); 3199 } 3200 3201 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3202 { 3203 PetscErrorCode ierr; 3204 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3205 PetscScalar a; 3206 PetscInt m,n,i,j,col; 3207 3208 PetscFunctionBegin; 3209 if (!x->assembled) { 3210 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3211 for (i=0; i<m; i++) { 3212 for (j=0; j<aij->imax[i]; j++) { 3213 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3214 col = (PetscInt)(n*PetscRealPart(a)); 3215 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3216 } 3217 } 3218 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3219 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3220 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3221 PetscFunctionReturn(0); 3222 } 3223 3224 /* -------------------------------------------------------------------*/ 3225 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3226 MatGetRow_SeqAIJ, 3227 MatRestoreRow_SeqAIJ, 3228 MatMult_SeqAIJ, 3229 /* 4*/ MatMultAdd_SeqAIJ, 3230 MatMultTranspose_SeqAIJ, 3231 MatMultTransposeAdd_SeqAIJ, 3232 0, 3233 0, 3234 0, 3235 /* 10*/ 0, 3236 MatLUFactor_SeqAIJ, 3237 0, 3238 MatSOR_SeqAIJ, 3239 MatTranspose_SeqAIJ, 3240 /*1 5*/ MatGetInfo_SeqAIJ, 3241 MatEqual_SeqAIJ, 3242 MatGetDiagonal_SeqAIJ, 3243 MatDiagonalScale_SeqAIJ, 3244 MatNorm_SeqAIJ, 3245 /* 20*/ 0, 3246 MatAssemblyEnd_SeqAIJ, 3247 MatSetOption_SeqAIJ, 3248 MatZeroEntries_SeqAIJ, 3249 /* 24*/ MatZeroRows_SeqAIJ, 3250 0, 3251 0, 3252 0, 3253 0, 3254 /* 29*/ MatSetUp_SeqAIJ, 3255 0, 3256 0, 3257 0, 3258 0, 3259 /* 34*/ MatDuplicate_SeqAIJ, 3260 0, 3261 0, 3262 MatILUFactor_SeqAIJ, 3263 0, 3264 /* 39*/ MatAXPY_SeqAIJ, 3265 MatCreateSubMatrices_SeqAIJ, 3266 MatIncreaseOverlap_SeqAIJ, 3267 MatGetValues_SeqAIJ, 3268 MatCopy_SeqAIJ, 3269 /* 44*/ MatGetRowMax_SeqAIJ, 3270 MatScale_SeqAIJ, 3271 MatShift_SeqAIJ, 3272 MatDiagonalSet_SeqAIJ, 3273 MatZeroRowsColumns_SeqAIJ, 3274 /* 49*/ MatSetRandom_SeqAIJ, 3275 MatGetRowIJ_SeqAIJ, 3276 MatRestoreRowIJ_SeqAIJ, 3277 MatGetColumnIJ_SeqAIJ, 3278 MatRestoreColumnIJ_SeqAIJ, 3279 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3280 0, 3281 0, 3282 MatPermute_SeqAIJ, 3283 0, 3284 /* 59*/ 0, 3285 MatDestroy_SeqAIJ, 3286 MatView_SeqAIJ, 3287 0, 3288 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3289 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3290 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3291 0, 3292 0, 3293 0, 3294 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3295 MatGetRowMinAbs_SeqAIJ, 3296 0, 3297 0, 3298 0, 3299 /* 74*/ 0, 3300 MatFDColoringApply_AIJ, 3301 0, 3302 0, 3303 0, 3304 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3305 0, 3306 0, 3307 0, 3308 MatLoad_SeqAIJ, 3309 /* 84*/ MatIsSymmetric_SeqAIJ, 3310 MatIsHermitian_SeqAIJ, 3311 0, 3312 0, 3313 0, 3314 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3315 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3316 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3317 MatPtAP_SeqAIJ_SeqAIJ, 3318 MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy, 3319 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy, 3320 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3321 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3322 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3323 0, 3324 /* 99*/ 0, 3325 0, 3326 0, 3327 MatConjugate_SeqAIJ, 3328 0, 3329 /*104*/ MatSetValuesRow_SeqAIJ, 3330 MatRealPart_SeqAIJ, 3331 MatImaginaryPart_SeqAIJ, 3332 0, 3333 0, 3334 /*109*/ MatMatSolve_SeqAIJ, 3335 0, 3336 MatGetRowMin_SeqAIJ, 3337 0, 3338 MatMissingDiagonal_SeqAIJ, 3339 /*114*/ 0, 3340 0, 3341 0, 3342 0, 3343 0, 3344 /*119*/ 0, 3345 0, 3346 0, 3347 0, 3348 MatGetMultiProcBlock_SeqAIJ, 3349 /*124*/ MatFindNonzeroRows_SeqAIJ, 3350 MatGetColumnNorms_SeqAIJ, 3351 MatInvertBlockDiagonal_SeqAIJ, 3352 MatInvertVariableBlockDiagonal_SeqAIJ, 3353 0, 3354 /*129*/ 0, 3355 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3356 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3357 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3358 MatTransposeColoringCreate_SeqAIJ, 3359 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3360 MatTransColoringApplyDenToSp_SeqAIJ, 3361 MatRARt_SeqAIJ_SeqAIJ, 3362 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3363 MatRARtNumeric_SeqAIJ_SeqAIJ, 3364 /*139*/0, 3365 0, 3366 0, 3367 MatFDColoringSetUp_SeqXAIJ, 3368 MatFindOffBlockDiagonalEntries_SeqAIJ, 3369 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ, 3370 MatDestroySubMatrices_SeqAIJ 3371 }; 3372 3373 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3374 { 3375 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3376 PetscInt i,nz,n; 3377 3378 PetscFunctionBegin; 3379 nz = aij->maxnz; 3380 n = mat->rmap->n; 3381 for (i=0; i<nz; i++) { 3382 aij->j[i] = indices[i]; 3383 } 3384 aij->nz = nz; 3385 for (i=0; i<n; i++) { 3386 aij->ilen[i] = aij->imax[i]; 3387 } 3388 PetscFunctionReturn(0); 3389 } 3390 3391 /* 3392 * When a sparse matrix has many zero columns, we should compact them out to save the space 3393 * This happens in MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable() 3394 * */ 3395 PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat mat, ISLocalToGlobalMapping *mapping) 3396 { 3397 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3398 PetscTable gid1_lid1; 3399 PetscTablePosition tpos; 3400 PetscInt gid,lid,i,j,ncols,ec; 3401 PetscInt *garray; 3402 PetscErrorCode ierr; 3403 3404 PetscFunctionBegin; 3405 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3406 PetscValidPointer(mapping,2); 3407 /* use a table */ 3408 ierr = PetscTableCreate(mat->rmap->n,mat->cmap->N+1,&gid1_lid1);CHKERRQ(ierr); 3409 ec = 0; 3410 for (i=0; i<mat->rmap->n; i++) { 3411 ncols = aij->i[i+1] - aij->i[i]; 3412 for (j=0; j<ncols; j++) { 3413 PetscInt data,gid1 = aij->j[aij->i[i] + j] + 1; 3414 ierr = PetscTableFind(gid1_lid1,gid1,&data);CHKERRQ(ierr); 3415 if (!data) { 3416 /* one based table */ 3417 ierr = PetscTableAdd(gid1_lid1,gid1,++ec,INSERT_VALUES);CHKERRQ(ierr); 3418 } 3419 } 3420 } 3421 /* form array of columns we need */ 3422 ierr = PetscMalloc1(ec+1,&garray);CHKERRQ(ierr); 3423 ierr = PetscTableGetHeadPosition(gid1_lid1,&tpos);CHKERRQ(ierr); 3424 while (tpos) { 3425 ierr = PetscTableGetNext(gid1_lid1,&tpos,&gid,&lid);CHKERRQ(ierr); 3426 gid--; 3427 lid--; 3428 garray[lid] = gid; 3429 } 3430 ierr = PetscSortInt(ec,garray);CHKERRQ(ierr); /* sort, and rebuild */ 3431 ierr = PetscTableRemoveAll(gid1_lid1);CHKERRQ(ierr); 3432 for (i=0; i<ec; i++) { 3433 ierr = PetscTableAdd(gid1_lid1,garray[i]+1,i+1,INSERT_VALUES);CHKERRQ(ierr); 3434 } 3435 /* compact out the extra columns in B */ 3436 for (i=0; i<mat->rmap->n; i++) { 3437 ncols = aij->i[i+1] - aij->i[i]; 3438 for (j=0; j<ncols; j++) { 3439 PetscInt gid1 = aij->j[aij->i[i] + j] + 1; 3440 ierr = PetscTableFind(gid1_lid1,gid1,&lid);CHKERRQ(ierr); 3441 lid--; 3442 aij->j[aij->i[i] + j] = lid; 3443 } 3444 } 3445 mat->cmap->n = mat->cmap->N = ec; 3446 mat->cmap->bs = 1; 3447 3448 ierr = PetscTableDestroy(&gid1_lid1);CHKERRQ(ierr); 3449 ierr = PetscLayoutSetUp((mat->cmap));CHKERRQ(ierr); 3450 ierr = ISLocalToGlobalMappingCreate(PETSC_COMM_SELF,mat->cmap->bs,mat->cmap->n,garray,PETSC_OWN_POINTER,mapping);CHKERRQ(ierr); 3451 ierr = ISLocalToGlobalMappingSetType(*mapping,ISLOCALTOGLOBALMAPPINGHASH);CHKERRQ(ierr); 3452 PetscFunctionReturn(0); 3453 } 3454 3455 /*@ 3456 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3457 in the matrix. 3458 3459 Input Parameters: 3460 + mat - the SeqAIJ matrix 3461 - indices - the column indices 3462 3463 Level: advanced 3464 3465 Notes: 3466 This can be called if you have precomputed the nonzero structure of the 3467 matrix and want to provide it to the matrix object to improve the performance 3468 of the MatSetValues() operation. 3469 3470 You MUST have set the correct numbers of nonzeros per row in the call to 3471 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3472 3473 MUST be called before any calls to MatSetValues(); 3474 3475 The indices should start with zero, not one. 3476 3477 @*/ 3478 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3479 { 3480 PetscErrorCode ierr; 3481 3482 PetscFunctionBegin; 3483 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3484 PetscValidPointer(indices,2); 3485 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3486 PetscFunctionReturn(0); 3487 } 3488 3489 /* ----------------------------------------------------------------------------------------*/ 3490 3491 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3492 { 3493 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3494 PetscErrorCode ierr; 3495 size_t nz = aij->i[mat->rmap->n]; 3496 3497 PetscFunctionBegin; 3498 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3499 3500 /* allocate space for values if not already there */ 3501 if (!aij->saved_values) { 3502 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3503 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3504 } 3505 3506 /* copy values over */ 3507 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3508 PetscFunctionReturn(0); 3509 } 3510 3511 /*@ 3512 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3513 example, reuse of the linear part of a Jacobian, while recomputing the 3514 nonlinear portion. 3515 3516 Collect on Mat 3517 3518 Input Parameters: 3519 . mat - the matrix (currently only AIJ matrices support this option) 3520 3521 Level: advanced 3522 3523 Common Usage, with SNESSolve(): 3524 $ Create Jacobian matrix 3525 $ Set linear terms into matrix 3526 $ Apply boundary conditions to matrix, at this time matrix must have 3527 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3528 $ boundary conditions again will not change the nonzero structure 3529 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3530 $ ierr = MatStoreValues(mat); 3531 $ Call SNESSetJacobian() with matrix 3532 $ In your Jacobian routine 3533 $ ierr = MatRetrieveValues(mat); 3534 $ Set nonlinear terms in matrix 3535 3536 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3537 $ // build linear portion of Jacobian 3538 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3539 $ ierr = MatStoreValues(mat); 3540 $ loop over nonlinear iterations 3541 $ ierr = MatRetrieveValues(mat); 3542 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3543 $ // call MatAssemblyBegin/End() on matrix 3544 $ Solve linear system with Jacobian 3545 $ endloop 3546 3547 Notes: 3548 Matrix must already be assemblied before calling this routine 3549 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3550 calling this routine. 3551 3552 When this is called multiple times it overwrites the previous set of stored values 3553 and does not allocated additional space. 3554 3555 .seealso: MatRetrieveValues() 3556 3557 @*/ 3558 PetscErrorCode MatStoreValues(Mat mat) 3559 { 3560 PetscErrorCode ierr; 3561 3562 PetscFunctionBegin; 3563 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3564 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3565 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3566 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3567 PetscFunctionReturn(0); 3568 } 3569 3570 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3571 { 3572 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3573 PetscErrorCode ierr; 3574 PetscInt nz = aij->i[mat->rmap->n]; 3575 3576 PetscFunctionBegin; 3577 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3578 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3579 /* copy values over */ 3580 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3581 PetscFunctionReturn(0); 3582 } 3583 3584 /*@ 3585 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3586 example, reuse of the linear part of a Jacobian, while recomputing the 3587 nonlinear portion. 3588 3589 Collect on Mat 3590 3591 Input Parameters: 3592 . mat - the matrix (currently only AIJ matrices support this option) 3593 3594 Level: advanced 3595 3596 .seealso: MatStoreValues() 3597 3598 @*/ 3599 PetscErrorCode MatRetrieveValues(Mat mat) 3600 { 3601 PetscErrorCode ierr; 3602 3603 PetscFunctionBegin; 3604 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3605 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3606 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3607 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3608 PetscFunctionReturn(0); 3609 } 3610 3611 3612 /* --------------------------------------------------------------------------------*/ 3613 /*@C 3614 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3615 (the default parallel PETSc format). For good matrix assembly performance 3616 the user should preallocate the matrix storage by setting the parameter nz 3617 (or the array nnz). By setting these parameters accurately, performance 3618 during matrix assembly can be increased by more than a factor of 50. 3619 3620 Collective on MPI_Comm 3621 3622 Input Parameters: 3623 + comm - MPI communicator, set to PETSC_COMM_SELF 3624 . m - number of rows 3625 . n - number of columns 3626 . nz - number of nonzeros per row (same for all rows) 3627 - nnz - array containing the number of nonzeros in the various rows 3628 (possibly different for each row) or NULL 3629 3630 Output Parameter: 3631 . A - the matrix 3632 3633 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3634 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3635 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3636 3637 Notes: 3638 If nnz is given then nz is ignored 3639 3640 The AIJ format (also called the Yale sparse matrix format or 3641 compressed row storage), is fully compatible with standard Fortran 77 3642 storage. That is, the stored row and column indices can begin at 3643 either one (as in Fortran) or zero. See the users' manual for details. 3644 3645 Specify the preallocated storage with either nz or nnz (not both). 3646 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3647 allocation. For large problems you MUST preallocate memory or you 3648 will get TERRIBLE performance, see the users' manual chapter on matrices. 3649 3650 By default, this format uses inodes (identical nodes) when possible, to 3651 improve numerical efficiency of matrix-vector products and solves. We 3652 search for consecutive rows with the same nonzero structure, thereby 3653 reusing matrix information to achieve increased efficiency. 3654 3655 Options Database Keys: 3656 + -mat_no_inode - Do not use inodes 3657 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3658 3659 Level: intermediate 3660 3661 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3662 3663 @*/ 3664 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3665 { 3666 PetscErrorCode ierr; 3667 3668 PetscFunctionBegin; 3669 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3670 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3671 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3672 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3673 PetscFunctionReturn(0); 3674 } 3675 3676 /*@C 3677 MatSeqAIJSetPreallocation - For good matrix assembly performance 3678 the user should preallocate the matrix storage by setting the parameter nz 3679 (or the array nnz). By setting these parameters accurately, performance 3680 during matrix assembly can be increased by more than a factor of 50. 3681 3682 Collective on MPI_Comm 3683 3684 Input Parameters: 3685 + B - The matrix 3686 . nz - number of nonzeros per row (same for all rows) 3687 - nnz - array containing the number of nonzeros in the various rows 3688 (possibly different for each row) or NULL 3689 3690 Notes: 3691 If nnz is given then nz is ignored 3692 3693 The AIJ format (also called the Yale sparse matrix format or 3694 compressed row storage), is fully compatible with standard Fortran 77 3695 storage. That is, the stored row and column indices can begin at 3696 either one (as in Fortran) or zero. See the users' manual for details. 3697 3698 Specify the preallocated storage with either nz or nnz (not both). 3699 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3700 allocation. For large problems you MUST preallocate memory or you 3701 will get TERRIBLE performance, see the users' manual chapter on matrices. 3702 3703 You can call MatGetInfo() to get information on how effective the preallocation was; 3704 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3705 You can also run with the option -info and look for messages with the string 3706 malloc in them to see if additional memory allocation was needed. 3707 3708 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3709 entries or columns indices 3710 3711 By default, this format uses inodes (identical nodes) when possible, to 3712 improve numerical efficiency of matrix-vector products and solves. We 3713 search for consecutive rows with the same nonzero structure, thereby 3714 reusing matrix information to achieve increased efficiency. 3715 3716 Options Database Keys: 3717 + -mat_no_inode - Do not use inodes 3718 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3719 3720 Level: intermediate 3721 3722 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3723 3724 @*/ 3725 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3726 { 3727 PetscErrorCode ierr; 3728 3729 PetscFunctionBegin; 3730 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3731 PetscValidType(B,1); 3732 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3733 PetscFunctionReturn(0); 3734 } 3735 3736 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3737 { 3738 Mat_SeqAIJ *b; 3739 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3740 PetscErrorCode ierr; 3741 PetscInt i; 3742 3743 PetscFunctionBegin; 3744 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3745 if (nz == MAT_SKIP_ALLOCATION) { 3746 skipallocation = PETSC_TRUE; 3747 nz = 0; 3748 } 3749 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3750 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3751 3752 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3753 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3754 if (nnz) { 3755 for (i=0; i<B->rmap->n; i++) { 3756 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]); 3757 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); 3758 } 3759 } 3760 3761 B->preallocated = PETSC_TRUE; 3762 3763 b = (Mat_SeqAIJ*)B->data; 3764 3765 if (!skipallocation) { 3766 if (!b->imax) { 3767 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3768 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3769 } 3770 if (!b->ipre) { 3771 ierr = PetscMalloc1(B->rmap->n,&b->ipre);CHKERRQ(ierr); 3772 ierr = PetscLogObjectMemory((PetscObject)B,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3773 } 3774 if (!nnz) { 3775 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3776 else if (nz < 0) nz = 1; 3777 nz = PetscMin(nz,B->cmap->n); 3778 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3779 nz = nz*B->rmap->n; 3780 } else { 3781 nz = 0; 3782 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3783 } 3784 /* b->ilen will count nonzeros in each row so far. */ 3785 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3786 3787 /* allocate the matrix space */ 3788 /* FIXME: should B's old memory be unlogged? */ 3789 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3790 if (B->structure_only) { 3791 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3792 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3793 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3794 } else { 3795 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3796 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3797 } 3798 b->i[0] = 0; 3799 for (i=1; i<B->rmap->n+1; i++) { 3800 b->i[i] = b->i[i-1] + b->imax[i-1]; 3801 } 3802 if (B->structure_only) { 3803 b->singlemalloc = PETSC_FALSE; 3804 b->free_a = PETSC_FALSE; 3805 } else { 3806 b->singlemalloc = PETSC_TRUE; 3807 b->free_a = PETSC_TRUE; 3808 } 3809 b->free_ij = PETSC_TRUE; 3810 } else { 3811 b->free_a = PETSC_FALSE; 3812 b->free_ij = PETSC_FALSE; 3813 } 3814 3815 if (b->ipre && nnz != b->ipre && b->imax) { 3816 /* reserve user-requested sparsity */ 3817 ierr = PetscMemcpy(b->ipre,b->imax,B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3818 } 3819 3820 3821 b->nz = 0; 3822 b->maxnz = nz; 3823 B->info.nz_unneeded = (double)b->maxnz; 3824 if (realalloc) { 3825 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3826 } 3827 B->was_assembled = PETSC_FALSE; 3828 B->assembled = PETSC_FALSE; 3829 PetscFunctionReturn(0); 3830 } 3831 3832 3833 PetscErrorCode MatResetPreallocation_SeqAIJ(Mat A) 3834 { 3835 Mat_SeqAIJ *a; 3836 PetscInt i; 3837 PetscErrorCode ierr; 3838 3839 PetscFunctionBegin; 3840 PetscValidHeaderSpecific(A,MAT_CLASSID,1); 3841 a = (Mat_SeqAIJ*)A->data; 3842 /* if no saved info, we error out */ 3843 if (!a->ipre) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_ARG_NULL,"No saved preallocation info \n"); 3844 3845 if (!a->i || !a->j || !a->a || !a->imax || !a->ilen) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_ARG_NULL,"Memory info is incomplete, and can not reset preallocation \n"); 3846 3847 ierr = PetscMemcpy(a->imax,a->ipre,A->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3848 ierr = PetscMemzero(a->ilen,A->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3849 a->i[0] = 0; 3850 for (i=1; i<A->rmap->n+1; i++) { 3851 a->i[i] = a->i[i-1] + a->imax[i-1]; 3852 } 3853 A->preallocated = PETSC_TRUE; 3854 a->nz = 0; 3855 a->maxnz = a->i[A->rmap->n]; 3856 A->info.nz_unneeded = (double)a->maxnz; 3857 A->was_assembled = PETSC_FALSE; 3858 A->assembled = PETSC_FALSE; 3859 PetscFunctionReturn(0); 3860 } 3861 3862 /*@ 3863 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3864 3865 Input Parameters: 3866 + B - the matrix 3867 . i - the indices into j for the start of each row (starts with zero) 3868 . j - the column indices for each row (starts with zero) these must be sorted for each row 3869 - v - optional values in the matrix 3870 3871 Level: developer 3872 3873 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3874 3875 .keywords: matrix, aij, compressed row, sparse, sequential 3876 3877 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), MATSEQAIJ 3878 @*/ 3879 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3880 { 3881 PetscErrorCode ierr; 3882 3883 PetscFunctionBegin; 3884 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3885 PetscValidType(B,1); 3886 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3887 PetscFunctionReturn(0); 3888 } 3889 3890 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3891 { 3892 PetscInt i; 3893 PetscInt m,n; 3894 PetscInt nz; 3895 PetscInt *nnz, nz_max = 0; 3896 PetscScalar *values; 3897 PetscErrorCode ierr; 3898 3899 PetscFunctionBegin; 3900 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3901 3902 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3903 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3904 3905 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3906 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 3907 for (i = 0; i < m; i++) { 3908 nz = Ii[i+1]- Ii[i]; 3909 nz_max = PetscMax(nz_max, nz); 3910 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3911 nnz[i] = nz; 3912 } 3913 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3914 ierr = PetscFree(nnz);CHKERRQ(ierr); 3915 3916 if (v) { 3917 values = (PetscScalar*) v; 3918 } else { 3919 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3920 } 3921 3922 for (i = 0; i < m; i++) { 3923 nz = Ii[i+1] - Ii[i]; 3924 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3925 } 3926 3927 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3928 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3929 3930 if (!v) { 3931 ierr = PetscFree(values);CHKERRQ(ierr); 3932 } 3933 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3934 PetscFunctionReturn(0); 3935 } 3936 3937 #include <../src/mat/impls/dense/seq/dense.h> 3938 #include <petsc/private/kernels/petscaxpy.h> 3939 3940 /* 3941 Computes (B'*A')' since computing B*A directly is untenable 3942 3943 n p p 3944 ( ) ( ) ( ) 3945 m ( A ) * n ( B ) = m ( C ) 3946 ( ) ( ) ( ) 3947 3948 */ 3949 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3950 { 3951 PetscErrorCode ierr; 3952 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3953 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3954 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3955 PetscInt i,n,m,q,p; 3956 const PetscInt *ii,*idx; 3957 const PetscScalar *b,*a,*a_q; 3958 PetscScalar *c,*c_q; 3959 3960 PetscFunctionBegin; 3961 m = A->rmap->n; 3962 n = A->cmap->n; 3963 p = B->cmap->n; 3964 a = sub_a->v; 3965 b = sub_b->a; 3966 c = sub_c->v; 3967 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3968 3969 ii = sub_b->i; 3970 idx = sub_b->j; 3971 for (i=0; i<n; i++) { 3972 q = ii[i+1] - ii[i]; 3973 while (q-->0) { 3974 c_q = c + m*(*idx); 3975 a_q = a + m*i; 3976 PetscKernelAXPY(c_q,*b,a_q,m); 3977 idx++; 3978 b++; 3979 } 3980 } 3981 PetscFunctionReturn(0); 3982 } 3983 3984 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3985 { 3986 PetscErrorCode ierr; 3987 PetscInt m=A->rmap->n,n=B->cmap->n; 3988 Mat Cmat; 3989 3990 PetscFunctionBegin; 3991 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); 3992 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3993 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3994 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3995 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3996 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3997 3998 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3999 4000 *C = Cmat; 4001 PetscFunctionReturn(0); 4002 } 4003 4004 /* ----------------------------------------------------------------*/ 4005 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4006 { 4007 PetscErrorCode ierr; 4008 4009 PetscFunctionBegin; 4010 if (scall == MAT_INITIAL_MATRIX) { 4011 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4012 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4013 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4014 } 4015 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4016 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4017 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4018 PetscFunctionReturn(0); 4019 } 4020 4021 4022 /*MC 4023 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4024 based on compressed sparse row format. 4025 4026 Options Database Keys: 4027 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4028 4029 Level: beginner 4030 4031 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4032 M*/ 4033 4034 /*MC 4035 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4036 4037 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4038 and MATMPIAIJ otherwise. As a result, for single process communicators, 4039 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 4040 for communicators controlling multiple processes. It is recommended that you call both of 4041 the above preallocation routines for simplicity. 4042 4043 Options Database Keys: 4044 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4045 4046 Developer Notes: 4047 Subclasses include MATAIJCUSPARSE, MATAIJPERM, MATAIJSELL, MATAIJMKL, MATAIJCRL, and also automatically switches over to use inodes when 4048 enough exist. 4049 4050 Level: beginner 4051 4052 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4053 M*/ 4054 4055 /*MC 4056 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4057 4058 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4059 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4060 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4061 for communicators controlling multiple processes. It is recommended that you call both of 4062 the above preallocation routines for simplicity. 4063 4064 Options Database Keys: 4065 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4066 4067 Level: beginner 4068 4069 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4070 M*/ 4071 4072 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4073 #if defined(PETSC_HAVE_ELEMENTAL) 4074 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 4075 #endif 4076 #if defined(PETSC_HAVE_HYPRE) 4077 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 4078 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 4079 #endif 4080 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 4081 4082 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqSELL(Mat,MatType,MatReuse,Mat*); 4083 PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*); 4084 PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*); 4085 4086 /*@C 4087 MatSeqAIJGetArray - gives access to the array where the data for a MATSEQAIJ matrix is stored 4088 4089 Not Collective 4090 4091 Input Parameter: 4092 . mat - a MATSEQAIJ matrix 4093 4094 Output Parameter: 4095 . array - pointer to the data 4096 4097 Level: intermediate 4098 4099 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4100 @*/ 4101 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4102 { 4103 PetscErrorCode ierr; 4104 4105 PetscFunctionBegin; 4106 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4107 PetscFunctionReturn(0); 4108 } 4109 4110 /*@C 4111 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 4112 4113 Not Collective 4114 4115 Input Parameter: 4116 . mat - a MATSEQAIJ matrix 4117 4118 Output Parameter: 4119 . nz - the maximum number of nonzeros in any row 4120 4121 Level: intermediate 4122 4123 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4124 @*/ 4125 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 4126 { 4127 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 4128 4129 PetscFunctionBegin; 4130 *nz = aij->rmax; 4131 PetscFunctionReturn(0); 4132 } 4133 4134 /*@C 4135 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 4136 4137 Not Collective 4138 4139 Input Parameters: 4140 . mat - a MATSEQAIJ matrix 4141 . array - pointer to the data 4142 4143 Level: intermediate 4144 4145 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4146 @*/ 4147 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4148 { 4149 PetscErrorCode ierr; 4150 4151 PetscFunctionBegin; 4152 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4153 PetscFunctionReturn(0); 4154 } 4155 4156 #if defined(PETSC_HAVE_CUDA) 4157 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCUSPARSE(Mat); 4158 #endif 4159 4160 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4161 { 4162 Mat_SeqAIJ *b; 4163 PetscErrorCode ierr; 4164 PetscMPIInt size; 4165 4166 PetscFunctionBegin; 4167 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4168 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4169 4170 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4171 4172 B->data = (void*)b; 4173 4174 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4175 4176 b->row = 0; 4177 b->col = 0; 4178 b->icol = 0; 4179 b->reallocs = 0; 4180 b->ignorezeroentries = PETSC_FALSE; 4181 b->roworiented = PETSC_TRUE; 4182 b->nonew = 0; 4183 b->diag = 0; 4184 b->solve_work = 0; 4185 B->spptr = 0; 4186 b->saved_values = 0; 4187 b->idiag = 0; 4188 b->mdiag = 0; 4189 b->ssor_work = 0; 4190 b->omega = 1.0; 4191 b->fshift = 0.0; 4192 b->idiagvalid = PETSC_FALSE; 4193 b->ibdiagvalid = PETSC_FALSE; 4194 b->keepnonzeropattern = PETSC_FALSE; 4195 4196 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4197 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4198 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4199 4200 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4201 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4202 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4203 #endif 4204 4205 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4206 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4207 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4208 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4209 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4210 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4211 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijsell_C",MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 4212 #if defined(PETSC_HAVE_MKL_SPARSE) 4213 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijmkl_C",MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4214 #endif 4215 #if defined(PETSC_HAVE_CUDA) 4216 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcusparse_C",MatConvert_SeqAIJ_SeqAIJCUSPARSE);CHKERRQ(ierr); 4217 #endif 4218 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4219 #if defined(PETSC_HAVE_ELEMENTAL) 4220 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4221 #endif 4222 #if defined(PETSC_HAVE_HYPRE) 4223 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 4224 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 4225 #endif 4226 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4227 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsell_C",MatConvert_SeqAIJ_SeqSELL);CHKERRQ(ierr); 4228 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_is_C",MatConvert_XAIJ_IS);CHKERRQ(ierr); 4229 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4230 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4231 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4232 ierr = PetscObjectComposeFunction((PetscObject)B,"MatResetPreallocation_C",MatResetPreallocation_SeqAIJ);CHKERRQ(ierr); 4233 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4234 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4235 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4236 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4237 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4238 ierr = PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_seqaij_C",MatPtAP_IS_XAIJ);CHKERRQ(ierr); 4239 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4240 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4241 ierr = MatSeqAIJSetTypeFromOptions(B);CHKERRQ(ierr); /* this allows changing the matrix subtype to say MATSEQAIJPERM */ 4242 PetscFunctionReturn(0); 4243 } 4244 4245 /* 4246 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4247 */ 4248 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4249 { 4250 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4251 PetscErrorCode ierr; 4252 PetscInt i,m = A->rmap->n; 4253 4254 PetscFunctionBegin; 4255 c = (Mat_SeqAIJ*)C->data; 4256 4257 C->factortype = A->factortype; 4258 c->row = 0; 4259 c->col = 0; 4260 c->icol = 0; 4261 c->reallocs = 0; 4262 4263 C->assembled = PETSC_TRUE; 4264 4265 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4266 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4267 4268 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4269 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4270 for (i=0; i<m; i++) { 4271 c->imax[i] = a->imax[i]; 4272 c->ilen[i] = a->ilen[i]; 4273 } 4274 4275 /* allocate the matrix space */ 4276 if (mallocmatspace) { 4277 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4278 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4279 4280 c->singlemalloc = PETSC_TRUE; 4281 4282 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4283 if (m > 0) { 4284 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4285 if (cpvalues == MAT_COPY_VALUES) { 4286 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4287 } else { 4288 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4289 } 4290 } 4291 } 4292 4293 c->ignorezeroentries = a->ignorezeroentries; 4294 c->roworiented = a->roworiented; 4295 c->nonew = a->nonew; 4296 if (a->diag) { 4297 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4298 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4299 for (i=0; i<m; i++) { 4300 c->diag[i] = a->diag[i]; 4301 } 4302 } else c->diag = 0; 4303 4304 c->solve_work = 0; 4305 c->saved_values = 0; 4306 c->idiag = 0; 4307 c->ssor_work = 0; 4308 c->keepnonzeropattern = a->keepnonzeropattern; 4309 c->free_a = PETSC_TRUE; 4310 c->free_ij = PETSC_TRUE; 4311 4312 c->rmax = a->rmax; 4313 c->nz = a->nz; 4314 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4315 C->preallocated = PETSC_TRUE; 4316 4317 c->compressedrow.use = a->compressedrow.use; 4318 c->compressedrow.nrows = a->compressedrow.nrows; 4319 if (a->compressedrow.use) { 4320 i = a->compressedrow.nrows; 4321 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4322 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4323 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4324 } else { 4325 c->compressedrow.use = PETSC_FALSE; 4326 c->compressedrow.i = NULL; 4327 c->compressedrow.rindex = NULL; 4328 } 4329 c->nonzerorowcnt = a->nonzerorowcnt; 4330 C->nonzerostate = A->nonzerostate; 4331 4332 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4333 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4334 PetscFunctionReturn(0); 4335 } 4336 4337 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4338 { 4339 PetscErrorCode ierr; 4340 4341 PetscFunctionBegin; 4342 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4343 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4344 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4345 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4346 } 4347 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4348 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4349 PetscFunctionReturn(0); 4350 } 4351 4352 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4353 { 4354 PetscBool isbinary, ishdf5; 4355 PetscErrorCode ierr; 4356 4357 PetscFunctionBegin; 4358 PetscValidHeaderSpecific(newMat,MAT_CLASSID,1); 4359 PetscValidHeaderSpecific(viewer,PETSC_VIEWER_CLASSID,2); 4360 /* force binary viewer to load .info file if it has not yet done so */ 4361 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4362 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 4363 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERHDF5, &ishdf5);CHKERRQ(ierr); 4364 if (isbinary) { 4365 ierr = MatLoad_SeqAIJ_Binary(newMat,viewer);CHKERRQ(ierr); 4366 } else if (ishdf5) { 4367 #if defined(PETSC_HAVE_HDF5) 4368 ierr = MatLoad_AIJ_HDF5(newMat,viewer);CHKERRQ(ierr); 4369 #else 4370 SETERRQ(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"HDF5 not supported in this build.\nPlease reconfigure using --download-hdf5"); 4371 #endif 4372 } else { 4373 SETERRQ2(PetscObjectComm((PetscObject)newMat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newMat)->type_name); 4374 } 4375 PetscFunctionReturn(0); 4376 } 4377 4378 PetscErrorCode MatLoad_SeqAIJ_Binary(Mat newMat, PetscViewer viewer) 4379 { 4380 Mat_SeqAIJ *a; 4381 PetscErrorCode ierr; 4382 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4383 int fd; 4384 PetscMPIInt size; 4385 MPI_Comm comm; 4386 PetscInt bs = newMat->rmap->bs; 4387 4388 PetscFunctionBegin; 4389 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4390 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4391 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4392 4393 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4394 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4395 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4396 if (bs < 0) bs = 1; 4397 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4398 4399 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4400 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4401 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4402 M = header[1]; N = header[2]; nz = header[3]; 4403 4404 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4405 4406 /* read in row lengths */ 4407 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4408 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4409 4410 /* check if sum of rowlengths is same as nz */ 4411 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4412 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); 4413 4414 /* set global size if not set already*/ 4415 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4416 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4417 } else { 4418 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4419 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4420 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4421 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4422 } 4423 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); 4424 } 4425 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4426 a = (Mat_SeqAIJ*)newMat->data; 4427 4428 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4429 4430 /* read in nonzero values */ 4431 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4432 4433 /* set matrix "i" values */ 4434 a->i[0] = 0; 4435 for (i=1; i<= M; i++) { 4436 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4437 a->ilen[i-1] = rowlengths[i-1]; 4438 } 4439 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4440 4441 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4442 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4443 PetscFunctionReturn(0); 4444 } 4445 4446 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4447 { 4448 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4449 PetscErrorCode ierr; 4450 #if defined(PETSC_USE_COMPLEX) 4451 PetscInt k; 4452 #endif 4453 4454 PetscFunctionBegin; 4455 /* If the matrix dimensions are not equal,or no of nonzeros */ 4456 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4457 *flg = PETSC_FALSE; 4458 PetscFunctionReturn(0); 4459 } 4460 4461 /* if the a->i are the same */ 4462 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4463 if (!*flg) PetscFunctionReturn(0); 4464 4465 /* if a->j are the same */ 4466 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4467 if (!*flg) PetscFunctionReturn(0); 4468 4469 /* if a->a are the same */ 4470 #if defined(PETSC_USE_COMPLEX) 4471 for (k=0; k<a->nz; k++) { 4472 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4473 *flg = PETSC_FALSE; 4474 PetscFunctionReturn(0); 4475 } 4476 } 4477 #else 4478 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4479 #endif 4480 PetscFunctionReturn(0); 4481 } 4482 4483 /*@ 4484 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4485 provided by the user. 4486 4487 Collective on MPI_Comm 4488 4489 Input Parameters: 4490 + comm - must be an MPI communicator of size 1 4491 . m - number of rows 4492 . n - number of columns 4493 . i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row of the matrix 4494 . j - column indices 4495 - a - matrix values 4496 4497 Output Parameter: 4498 . mat - the matrix 4499 4500 Level: intermediate 4501 4502 Notes: 4503 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4504 once the matrix is destroyed and not before 4505 4506 You cannot set new nonzero locations into this matrix, that will generate an error. 4507 4508 The i and j indices are 0 based 4509 4510 The format which is used for the sparse matrix input, is equivalent to a 4511 row-major ordering.. i.e for the following matrix, the input data expected is 4512 as shown 4513 4514 $ 1 0 0 4515 $ 2 0 3 4516 $ 4 5 6 4517 $ 4518 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4519 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4520 $ v = {1,2,3,4,5,6} [size = 6] 4521 4522 4523 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4524 4525 @*/ 4526 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4527 { 4528 PetscErrorCode ierr; 4529 PetscInt ii; 4530 Mat_SeqAIJ *aij; 4531 #if defined(PETSC_USE_DEBUG) 4532 PetscInt jj; 4533 #endif 4534 4535 PetscFunctionBegin; 4536 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4537 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4538 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4539 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4540 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4541 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4542 aij = (Mat_SeqAIJ*)(*mat)->data; 4543 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4544 4545 aij->i = i; 4546 aij->j = j; 4547 aij->a = a; 4548 aij->singlemalloc = PETSC_FALSE; 4549 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4550 aij->free_a = PETSC_FALSE; 4551 aij->free_ij = PETSC_FALSE; 4552 4553 for (ii=0; ii<m; ii++) { 4554 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4555 #if defined(PETSC_USE_DEBUG) 4556 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]); 4557 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4558 if (j[jj] < j[jj-1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual column %D) in row %D is not sorted",jj-i[ii],j[jj],ii); 4559 if (j[jj] == j[jj-1]) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column entry number %D (actual column %D) in row %D is identical to previous entry",jj-i[ii],j[jj],ii); 4560 } 4561 #endif 4562 } 4563 #if defined(PETSC_USE_DEBUG) 4564 for (ii=0; ii<aij->i[m]; ii++) { 4565 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4566 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]); 4567 } 4568 #endif 4569 4570 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4571 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4572 PetscFunctionReturn(0); 4573 } 4574 /*@C 4575 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4576 provided by the user. 4577 4578 Collective on MPI_Comm 4579 4580 Input Parameters: 4581 + comm - must be an MPI communicator of size 1 4582 . m - number of rows 4583 . n - number of columns 4584 . i - row indices 4585 . j - column indices 4586 . a - matrix values 4587 . nz - number of nonzeros 4588 - idx - 0 or 1 based 4589 4590 Output Parameter: 4591 . mat - the matrix 4592 4593 Level: intermediate 4594 4595 Notes: 4596 The i and j indices are 0 based 4597 4598 The format which is used for the sparse matrix input, is equivalent to a 4599 row-major ordering.. i.e for the following matrix, the input data expected is 4600 as shown: 4601 4602 1 0 0 4603 2 0 3 4604 4 5 6 4605 4606 i = {0,1,1,2,2,2} 4607 j = {0,0,2,0,1,2} 4608 v = {1,2,3,4,5,6} 4609 4610 4611 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4612 4613 @*/ 4614 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4615 { 4616 PetscErrorCode ierr; 4617 PetscInt ii, *nnz, one = 1,row,col; 4618 4619 4620 PetscFunctionBegin; 4621 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4622 for (ii = 0; ii < nz; ii++) { 4623 nnz[i[ii] - !!idx] += 1; 4624 } 4625 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4626 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4627 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4628 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4629 for (ii = 0; ii < nz; ii++) { 4630 if (idx) { 4631 row = i[ii] - 1; 4632 col = j[ii] - 1; 4633 } else { 4634 row = i[ii]; 4635 col = j[ii]; 4636 } 4637 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4638 } 4639 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4640 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4641 ierr = PetscFree(nnz);CHKERRQ(ierr); 4642 PetscFunctionReturn(0); 4643 } 4644 4645 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4646 { 4647 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4648 PetscErrorCode ierr; 4649 4650 PetscFunctionBegin; 4651 a->idiagvalid = PETSC_FALSE; 4652 a->ibdiagvalid = PETSC_FALSE; 4653 4654 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4655 PetscFunctionReturn(0); 4656 } 4657 4658 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4659 { 4660 PetscErrorCode ierr; 4661 PetscMPIInt size; 4662 4663 PetscFunctionBegin; 4664 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4665 if (size == 1) { 4666 if (scall == MAT_INITIAL_MATRIX) { 4667 ierr = MatDuplicate(inmat,MAT_COPY_VALUES,outmat);CHKERRQ(ierr); 4668 } else { 4669 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4670 } 4671 } else { 4672 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4673 } 4674 PetscFunctionReturn(0); 4675 } 4676 4677 /* 4678 Permute A into C's *local* index space using rowemb,colemb. 4679 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4680 of [0,m), colemb is in [0,n). 4681 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4682 */ 4683 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4684 { 4685 /* If making this function public, change the error returned in this function away from _PLIB. */ 4686 PetscErrorCode ierr; 4687 Mat_SeqAIJ *Baij; 4688 PetscBool seqaij; 4689 PetscInt m,n,*nz,i,j,count; 4690 PetscScalar v; 4691 const PetscInt *rowindices,*colindices; 4692 4693 PetscFunctionBegin; 4694 if (!B) PetscFunctionReturn(0); 4695 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4696 ierr = PetscObjectBaseTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4697 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4698 if (rowemb) { 4699 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4700 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); 4701 } else { 4702 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4703 } 4704 if (colemb) { 4705 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4706 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); 4707 } else { 4708 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4709 } 4710 4711 Baij = (Mat_SeqAIJ*)(B->data); 4712 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4713 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4714 for (i=0; i<B->rmap->n; i++) { 4715 nz[i] = Baij->i[i+1] - Baij->i[i]; 4716 } 4717 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4718 ierr = PetscFree(nz);CHKERRQ(ierr); 4719 } 4720 if (pattern == SUBSET_NONZERO_PATTERN) { 4721 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4722 } 4723 count = 0; 4724 rowindices = NULL; 4725 colindices = NULL; 4726 if (rowemb) { 4727 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4728 } 4729 if (colemb) { 4730 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4731 } 4732 for (i=0; i<B->rmap->n; i++) { 4733 PetscInt row; 4734 row = i; 4735 if (rowindices) row = rowindices[i]; 4736 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4737 PetscInt col; 4738 col = Baij->j[count]; 4739 if (colindices) col = colindices[col]; 4740 v = Baij->a[count]; 4741 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4742 ++count; 4743 } 4744 } 4745 /* FIXME: set C's nonzerostate correctly. */ 4746 /* Assembly for C is necessary. */ 4747 C->preallocated = PETSC_TRUE; 4748 C->assembled = PETSC_TRUE; 4749 C->was_assembled = PETSC_FALSE; 4750 PetscFunctionReturn(0); 4751 } 4752 4753 PetscFunctionList MatSeqAIJList = NULL; 4754 4755 /*@C 4756 MatSeqAIJSetType - Converts a MATSEQAIJ matrix to a subtype 4757 4758 Collective on Mat 4759 4760 Input Parameters: 4761 + mat - the matrix object 4762 - matype - matrix type 4763 4764 Options Database Key: 4765 . -mat_seqai_type <method> - for example seqaijcrl 4766 4767 4768 Level: intermediate 4769 4770 .keywords: Mat, MatType, set, method 4771 4772 .seealso: PCSetType(), VecSetType(), MatCreate(), MatType, Mat 4773 @*/ 4774 PetscErrorCode MatSeqAIJSetType(Mat mat, MatType matype) 4775 { 4776 PetscErrorCode ierr,(*r)(Mat,MatType,MatReuse,Mat*); 4777 PetscBool sametype; 4778 4779 PetscFunctionBegin; 4780 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 4781 ierr = PetscObjectTypeCompare((PetscObject)mat,matype,&sametype);CHKERRQ(ierr); 4782 if (sametype) PetscFunctionReturn(0); 4783 4784 ierr = PetscFunctionListFind(MatSeqAIJList,matype,&r);CHKERRQ(ierr); 4785 if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown Mat type given: %s",matype); 4786 ierr = (*r)(mat,matype,MAT_INPLACE_MATRIX,&mat);CHKERRQ(ierr); 4787 PetscFunctionReturn(0); 4788 } 4789 4790 4791 /*@C 4792 MatSeqAIJRegister - - Adds a new sub-matrix type for sequential AIJ matrices 4793 4794 Not Collective 4795 4796 Input Parameters: 4797 + name - name of a new user-defined matrix type, for example MATSEQAIJCRL 4798 - function - routine to convert to subtype 4799 4800 Notes: 4801 MatSeqAIJRegister() may be called multiple times to add several user-defined solvers. 4802 4803 4804 Then, your matrix can be chosen with the procedural interface at runtime via the option 4805 $ -mat_seqaij_type my_mat 4806 4807 Level: advanced 4808 4809 .keywords: Mat, register 4810 4811 .seealso: MatSeqAIJRegisterAll() 4812 4813 4814 Level: advanced 4815 @*/ 4816 PetscErrorCode MatSeqAIJRegister(const char sname[],PetscErrorCode (*function)(Mat,MatType,MatReuse,Mat *)) 4817 { 4818 PetscErrorCode ierr; 4819 4820 PetscFunctionBegin; 4821 ierr = MatInitializePackage();CHKERRQ(ierr); 4822 ierr = PetscFunctionListAdd(&MatSeqAIJList,sname,function);CHKERRQ(ierr); 4823 PetscFunctionReturn(0); 4824 } 4825 4826 PetscBool MatSeqAIJRegisterAllCalled = PETSC_FALSE; 4827 4828 /*@C 4829 MatSeqAIJRegisterAll - Registers all of the matrix subtypes of SeqAIJ 4830 4831 Not Collective 4832 4833 Level: advanced 4834 4835 Developers Note: CUSP and CUSPARSE do not yet support the MatConvert_SeqAIJ..() paradigm and thus cannot be registered here 4836 4837 .keywords: KSP, register, all 4838 4839 .seealso: MatRegisterAll(), MatSeqAIJRegister() 4840 @*/ 4841 PetscErrorCode MatSeqAIJRegisterAll(void) 4842 { 4843 PetscErrorCode ierr; 4844 4845 PetscFunctionBegin; 4846 if (MatSeqAIJRegisterAllCalled) PetscFunctionReturn(0); 4847 MatSeqAIJRegisterAllCalled = PETSC_TRUE; 4848 4849 ierr = MatSeqAIJRegister(MATSEQAIJCRL, MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4850 ierr = MatSeqAIJRegister(MATSEQAIJPERM, MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4851 ierr = MatSeqAIJRegister(MATSEQAIJSELL, MatConvert_SeqAIJ_SeqAIJSELL);CHKERRQ(ierr); 4852 #if defined(PETSC_HAVE_MKL_SPARSE) 4853 ierr = MatSeqAIJRegister(MATSEQAIJMKL, MatConvert_SeqAIJ_SeqAIJMKL);CHKERRQ(ierr); 4854 #endif 4855 #if defined(PETSC_HAVE_VIENNACL) && defined(PETSC_HAVE_VIENNACL_NO_CUDA) 4856 ierr = MatSeqAIJRegister(MATMPIAIJVIENNACL, MatConvert_SeqAIJ_SeqAIJViennaCL);CHKERRQ(ierr); 4857 #endif 4858 PetscFunctionReturn(0); 4859 } 4860 4861 /* 4862 Special version for direct calls from Fortran 4863 */ 4864 #include <petsc/private/fortranimpl.h> 4865 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4866 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4867 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4868 #define matsetvaluesseqaij_ matsetvaluesseqaij 4869 #endif 4870 4871 /* Change these macros so can be used in void function */ 4872 #undef CHKERRQ 4873 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4874 #undef SETERRQ2 4875 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4876 #undef SETERRQ3 4877 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4878 4879 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) 4880 { 4881 Mat A = *AA; 4882 PetscInt m = *mm, n = *nn; 4883 InsertMode is = *isis; 4884 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4885 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4886 PetscInt *imax,*ai,*ailen; 4887 PetscErrorCode ierr; 4888 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4889 MatScalar *ap,value,*aa; 4890 PetscBool ignorezeroentries = a->ignorezeroentries; 4891 PetscBool roworiented = a->roworiented; 4892 4893 PetscFunctionBegin; 4894 MatCheckPreallocated(A,1); 4895 imax = a->imax; 4896 ai = a->i; 4897 ailen = a->ilen; 4898 aj = a->j; 4899 aa = a->a; 4900 4901 for (k=0; k<m; k++) { /* loop over added rows */ 4902 row = im[k]; 4903 if (row < 0) continue; 4904 #if defined(PETSC_USE_DEBUG) 4905 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4906 #endif 4907 rp = aj + ai[row]; ap = aa + ai[row]; 4908 rmax = imax[row]; nrow = ailen[row]; 4909 low = 0; 4910 high = nrow; 4911 for (l=0; l<n; l++) { /* loop over added columns */ 4912 if (in[l] < 0) continue; 4913 #if defined(PETSC_USE_DEBUG) 4914 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4915 #endif 4916 col = in[l]; 4917 if (roworiented) value = v[l + k*n]; 4918 else value = v[k + l*m]; 4919 4920 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4921 4922 if (col <= lastcol) low = 0; 4923 else high = nrow; 4924 lastcol = col; 4925 while (high-low > 5) { 4926 t = (low+high)/2; 4927 if (rp[t] > col) high = t; 4928 else low = t; 4929 } 4930 for (i=low; i<high; i++) { 4931 if (rp[i] > col) break; 4932 if (rp[i] == col) { 4933 if (is == ADD_VALUES) ap[i] += value; 4934 else ap[i] = value; 4935 goto noinsert; 4936 } 4937 } 4938 if (value == 0.0 && ignorezeroentries) goto noinsert; 4939 if (nonew == 1) goto noinsert; 4940 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4941 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4942 N = nrow++ - 1; a->nz++; high++; 4943 /* shift up all the later entries in this row */ 4944 for (ii=N; ii>=i; ii--) { 4945 rp[ii+1] = rp[ii]; 4946 ap[ii+1] = ap[ii]; 4947 } 4948 rp[i] = col; 4949 ap[i] = value; 4950 A->nonzerostate++; 4951 noinsert:; 4952 low = i + 1; 4953 } 4954 ailen[row] = nrow; 4955 } 4956 PetscFunctionReturnVoid(); 4957 } 4958