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