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 *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 ((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 ((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 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1114 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1115 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1116 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1117 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1118 PetscFunctionReturn(0); 1119 } 1120 1121 #undef __FUNCT__ 1122 #define __FUNCT__ "MatSetOption_SeqAIJ" 1123 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1124 { 1125 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1126 PetscErrorCode ierr; 1127 1128 PetscFunctionBegin; 1129 switch (op) { 1130 case MAT_ROW_ORIENTED: 1131 a->roworiented = flg; 1132 break; 1133 case MAT_KEEP_NONZERO_PATTERN: 1134 a->keepnonzeropattern = flg; 1135 break; 1136 case MAT_NEW_NONZERO_LOCATIONS: 1137 a->nonew = (flg ? 0 : 1); 1138 break; 1139 case MAT_NEW_NONZERO_LOCATION_ERR: 1140 a->nonew = (flg ? -1 : 0); 1141 break; 1142 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1143 a->nonew = (flg ? -2 : 0); 1144 break; 1145 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1146 a->nounused = (flg ? -1 : 0); 1147 break; 1148 case MAT_IGNORE_ZERO_ENTRIES: 1149 a->ignorezeroentries = flg; 1150 break; 1151 case MAT_SPD: 1152 case MAT_SYMMETRIC: 1153 case MAT_STRUCTURALLY_SYMMETRIC: 1154 case MAT_HERMITIAN: 1155 case MAT_SYMMETRY_ETERNAL: 1156 /* These options are handled directly by MatSetOption() */ 1157 break; 1158 case MAT_NEW_DIAGONALS: 1159 case MAT_IGNORE_OFF_PROC_ENTRIES: 1160 case MAT_USE_HASH_TABLE: 1161 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1162 break; 1163 case MAT_USE_INODES: 1164 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1165 break; 1166 default: 1167 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1168 } 1169 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1170 PetscFunctionReturn(0); 1171 } 1172 1173 #undef __FUNCT__ 1174 #define __FUNCT__ "MatGetDiagonal_SeqAIJ" 1175 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1176 { 1177 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1178 PetscErrorCode ierr; 1179 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1180 PetscScalar *aa=a->a,*x,zero=0.0; 1181 1182 PetscFunctionBegin; 1183 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1184 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1185 1186 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1187 PetscInt *diag=a->diag; 1188 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1189 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1190 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1191 PetscFunctionReturn(0); 1192 } 1193 1194 ierr = VecSet(v,zero);CHKERRQ(ierr); 1195 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1196 for (i=0; i<n; i++) { 1197 nz = ai[i+1] - ai[i]; 1198 if (!nz) x[i] = 0.0; 1199 for (j=ai[i]; j<ai[i+1]; j++) { 1200 if (aj[j] == i) { 1201 x[i] = aa[j]; 1202 break; 1203 } 1204 } 1205 } 1206 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1207 PetscFunctionReturn(0); 1208 } 1209 1210 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1211 #undef __FUNCT__ 1212 #define __FUNCT__ "MatMultTransposeAdd_SeqAIJ" 1213 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1214 { 1215 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1216 PetscScalar *y; 1217 const PetscScalar *x; 1218 PetscErrorCode ierr; 1219 PetscInt m = A->rmap->n; 1220 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1221 const MatScalar *v; 1222 PetscScalar alpha; 1223 PetscInt n,i,j; 1224 const PetscInt *idx,*ii,*ridx=NULL; 1225 Mat_CompressedRow cprow = a->compressedrow; 1226 PetscBool usecprow = cprow.use; 1227 #endif 1228 1229 PetscFunctionBegin; 1230 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1231 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1232 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1233 1234 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1235 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1236 #else 1237 if (usecprow) { 1238 m = cprow.nrows; 1239 ii = cprow.i; 1240 ridx = cprow.rindex; 1241 } else { 1242 ii = a->i; 1243 } 1244 for (i=0; i<m; i++) { 1245 idx = a->j + ii[i]; 1246 v = a->a + ii[i]; 1247 n = ii[i+1] - ii[i]; 1248 if (usecprow) { 1249 alpha = x[ridx[i]]; 1250 } else { 1251 alpha = x[i]; 1252 } 1253 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1254 } 1255 #endif 1256 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1257 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1258 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1259 PetscFunctionReturn(0); 1260 } 1261 1262 #undef __FUNCT__ 1263 #define __FUNCT__ "MatMultTranspose_SeqAIJ" 1264 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1265 { 1266 PetscErrorCode ierr; 1267 1268 PetscFunctionBegin; 1269 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1270 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1271 PetscFunctionReturn(0); 1272 } 1273 1274 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1275 1276 #undef __FUNCT__ 1277 #define __FUNCT__ "MatMult_SeqAIJ" 1278 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1279 { 1280 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1281 PetscScalar *y; 1282 const PetscScalar *x; 1283 const MatScalar *aa; 1284 PetscErrorCode ierr; 1285 PetscInt m=A->rmap->n; 1286 const PetscInt *aj,*ii,*ridx=NULL; 1287 PetscInt n,i; 1288 PetscScalar sum; 1289 PetscBool usecprow=a->compressedrow.use; 1290 1291 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1292 #pragma disjoint(*x,*y,*aa) 1293 #endif 1294 1295 PetscFunctionBegin; 1296 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1297 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1298 ii = a->i; 1299 if (usecprow) { /* use compressed row format */ 1300 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1301 m = a->compressedrow.nrows; 1302 ii = a->compressedrow.i; 1303 ridx = a->compressedrow.rindex; 1304 for (i=0; i<m; i++) { 1305 n = ii[i+1] - ii[i]; 1306 aj = a->j + ii[i]; 1307 aa = a->a + ii[i]; 1308 sum = 0.0; 1309 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1310 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1311 y[*ridx++] = sum; 1312 } 1313 } else { /* do not use compressed row format */ 1314 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1315 aj = a->j; 1316 aa = a->a; 1317 fortranmultaij_(&m,x,ii,aj,aa,y); 1318 #else 1319 for (i=0; i<m; i++) { 1320 n = ii[i+1] - ii[i]; 1321 aj = a->j + ii[i]; 1322 aa = a->a + ii[i]; 1323 sum = 0.0; 1324 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1325 y[i] = sum; 1326 } 1327 #endif 1328 } 1329 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1330 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1331 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1332 PetscFunctionReturn(0); 1333 } 1334 1335 #undef __FUNCT__ 1336 #define __FUNCT__ "MatMultMax_SeqAIJ" 1337 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1338 { 1339 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1340 PetscScalar *y; 1341 const PetscScalar *x; 1342 const MatScalar *aa; 1343 PetscErrorCode ierr; 1344 PetscInt m=A->rmap->n; 1345 const PetscInt *aj,*ii,*ridx=NULL; 1346 PetscInt n,i,nonzerorow=0; 1347 PetscScalar sum; 1348 PetscBool usecprow=a->compressedrow.use; 1349 1350 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1351 #pragma disjoint(*x,*y,*aa) 1352 #endif 1353 1354 PetscFunctionBegin; 1355 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1356 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1357 if (usecprow) { /* use compressed row format */ 1358 m = a->compressedrow.nrows; 1359 ii = a->compressedrow.i; 1360 ridx = a->compressedrow.rindex; 1361 for (i=0; i<m; i++) { 1362 n = ii[i+1] - ii[i]; 1363 aj = a->j + ii[i]; 1364 aa = a->a + ii[i]; 1365 sum = 0.0; 1366 nonzerorow += (n>0); 1367 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1368 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1369 y[*ridx++] = sum; 1370 } 1371 } else { /* do not use compressed row format */ 1372 ii = a->i; 1373 for (i=0; i<m; i++) { 1374 n = ii[i+1] - ii[i]; 1375 aj = a->j + ii[i]; 1376 aa = a->a + ii[i]; 1377 sum = 0.0; 1378 nonzerorow += (n>0); 1379 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1380 y[i] = sum; 1381 } 1382 } 1383 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1384 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1385 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1386 PetscFunctionReturn(0); 1387 } 1388 1389 #undef __FUNCT__ 1390 #define __FUNCT__ "MatMultAddMax_SeqAIJ" 1391 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1392 { 1393 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1394 PetscScalar *y,*z; 1395 const PetscScalar *x; 1396 const MatScalar *aa; 1397 PetscErrorCode ierr; 1398 PetscInt m = A->rmap->n,*aj,*ii; 1399 PetscInt n,i,*ridx=NULL; 1400 PetscScalar sum; 1401 PetscBool usecprow=a->compressedrow.use; 1402 1403 PetscFunctionBegin; 1404 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1405 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1406 if (usecprow) { /* use compressed row format */ 1407 if (zz != yy) { 1408 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1409 } 1410 m = a->compressedrow.nrows; 1411 ii = a->compressedrow.i; 1412 ridx = a->compressedrow.rindex; 1413 for (i=0; i<m; i++) { 1414 n = ii[i+1] - ii[i]; 1415 aj = a->j + ii[i]; 1416 aa = a->a + ii[i]; 1417 sum = y[*ridx]; 1418 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1419 z[*ridx++] = sum; 1420 } 1421 } else { /* do not use compressed row format */ 1422 ii = a->i; 1423 for (i=0; i<m; i++) { 1424 n = ii[i+1] - ii[i]; 1425 aj = a->j + ii[i]; 1426 aa = a->a + ii[i]; 1427 sum = y[i]; 1428 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1429 z[i] = sum; 1430 } 1431 } 1432 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1433 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1434 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1435 PetscFunctionReturn(0); 1436 } 1437 1438 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1439 #undef __FUNCT__ 1440 #define __FUNCT__ "MatMultAdd_SeqAIJ" 1441 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1442 { 1443 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1444 PetscScalar *y,*z; 1445 const PetscScalar *x; 1446 const MatScalar *aa; 1447 PetscErrorCode ierr; 1448 const PetscInt *aj,*ii,*ridx=NULL; 1449 PetscInt m = A->rmap->n,n,i; 1450 PetscScalar sum; 1451 PetscBool usecprow=a->compressedrow.use; 1452 1453 PetscFunctionBegin; 1454 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1455 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1456 if (usecprow) { /* use compressed row format */ 1457 if (zz != yy) { 1458 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1459 } 1460 m = a->compressedrow.nrows; 1461 ii = a->compressedrow.i; 1462 ridx = a->compressedrow.rindex; 1463 for (i=0; i<m; i++) { 1464 n = ii[i+1] - ii[i]; 1465 aj = a->j + ii[i]; 1466 aa = a->a + ii[i]; 1467 sum = y[*ridx]; 1468 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1469 z[*ridx++] = sum; 1470 } 1471 } else { /* do not use compressed row format */ 1472 ii = a->i; 1473 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1474 aj = a->j; 1475 aa = a->a; 1476 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1477 #else 1478 for (i=0; i<m; i++) { 1479 n = ii[i+1] - ii[i]; 1480 aj = a->j + ii[i]; 1481 aa = a->a + ii[i]; 1482 sum = y[i]; 1483 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1484 z[i] = sum; 1485 } 1486 #endif 1487 } 1488 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1489 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1490 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1491 #if defined(PETSC_HAVE_CUSP) 1492 /* 1493 ierr = VecView(xx,0);CHKERRQ(ierr); 1494 ierr = VecView(zz,0);CHKERRQ(ierr); 1495 ierr = MatView(A,0);CHKERRQ(ierr); 1496 */ 1497 #endif 1498 PetscFunctionReturn(0); 1499 } 1500 1501 /* 1502 Adds diagonal pointers to sparse matrix structure. 1503 */ 1504 #undef __FUNCT__ 1505 #define __FUNCT__ "MatMarkDiagonal_SeqAIJ" 1506 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1507 { 1508 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1509 PetscErrorCode ierr; 1510 PetscInt i,j,m = A->rmap->n; 1511 1512 PetscFunctionBegin; 1513 if (!a->diag) { 1514 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1515 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1516 } 1517 for (i=0; i<A->rmap->n; i++) { 1518 a->diag[i] = a->i[i+1]; 1519 for (j=a->i[i]; j<a->i[i+1]; j++) { 1520 if (a->j[j] == i) { 1521 a->diag[i] = j; 1522 break; 1523 } 1524 } 1525 } 1526 PetscFunctionReturn(0); 1527 } 1528 1529 /* 1530 Checks for missing diagonals 1531 */ 1532 #undef __FUNCT__ 1533 #define __FUNCT__ "MatMissingDiagonal_SeqAIJ" 1534 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1535 { 1536 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1537 PetscInt *diag,*ii = a->i,i; 1538 1539 PetscFunctionBegin; 1540 *missing = PETSC_FALSE; 1541 if (A->rmap->n > 0 && !ii) { 1542 *missing = PETSC_TRUE; 1543 if (d) *d = 0; 1544 PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n"); 1545 } else { 1546 diag = a->diag; 1547 for (i=0; i<A->rmap->n; i++) { 1548 if (diag[i] >= ii[i+1]) { 1549 *missing = PETSC_TRUE; 1550 if (d) *d = i; 1551 PetscInfo1(A,"Matrix is missing diagonal number %D\n",i); 1552 break; 1553 } 1554 } 1555 } 1556 PetscFunctionReturn(0); 1557 } 1558 1559 #undef __FUNCT__ 1560 #define __FUNCT__ "MatInvertDiagonal_SeqAIJ" 1561 /* 1562 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1563 */ 1564 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1565 { 1566 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1567 PetscErrorCode ierr; 1568 PetscInt i,*diag,m = A->rmap->n; 1569 MatScalar *v = a->a; 1570 PetscScalar *idiag,*mdiag; 1571 1572 PetscFunctionBegin; 1573 if (a->idiagvalid) PetscFunctionReturn(0); 1574 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1575 diag = a->diag; 1576 if (!a->idiag) { 1577 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1578 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1579 v = a->a; 1580 } 1581 mdiag = a->mdiag; 1582 idiag = a->idiag; 1583 1584 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1585 for (i=0; i<m; i++) { 1586 mdiag[i] = v[diag[i]]; 1587 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1588 if (PetscRealPart(fshift)) { 1589 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1590 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1591 A->factorerror_zeropivot_value = 0.0; 1592 A->factorerror_zeropivot_row = i; 1593 } SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1594 } 1595 idiag[i] = 1.0/v[diag[i]]; 1596 } 1597 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1598 } else { 1599 for (i=0; i<m; i++) { 1600 mdiag[i] = v[diag[i]]; 1601 idiag[i] = omega/(fshift + v[diag[i]]); 1602 } 1603 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1604 } 1605 a->idiagvalid = PETSC_TRUE; 1606 PetscFunctionReturn(0); 1607 } 1608 1609 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1610 #undef __FUNCT__ 1611 #define __FUNCT__ "MatSOR_SeqAIJ" 1612 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1613 { 1614 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1615 PetscScalar *x,d,sum,*t,scale; 1616 const MatScalar *v,*idiag=0,*mdiag; 1617 const PetscScalar *b, *bs,*xb, *ts; 1618 PetscErrorCode ierr; 1619 PetscInt n,m = A->rmap->n,i; 1620 const PetscInt *idx,*diag; 1621 1622 PetscFunctionBegin; 1623 its = its*lits; 1624 1625 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1626 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1627 a->fshift = fshift; 1628 a->omega = omega; 1629 1630 diag = a->diag; 1631 t = a->ssor_work; 1632 idiag = a->idiag; 1633 mdiag = a->mdiag; 1634 1635 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1636 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1637 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1638 if (flag == SOR_APPLY_UPPER) { 1639 /* apply (U + D/omega) to the vector */ 1640 bs = b; 1641 for (i=0; i<m; i++) { 1642 d = fshift + mdiag[i]; 1643 n = a->i[i+1] - diag[i] - 1; 1644 idx = a->j + diag[i] + 1; 1645 v = a->a + diag[i] + 1; 1646 sum = b[i]*d/omega; 1647 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1648 x[i] = sum; 1649 } 1650 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1651 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1652 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1653 PetscFunctionReturn(0); 1654 } 1655 1656 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1657 else if (flag & SOR_EISENSTAT) { 1658 /* Let A = L + U + D; where L is lower trianglar, 1659 U is upper triangular, E = D/omega; This routine applies 1660 1661 (L + E)^{-1} A (U + E)^{-1} 1662 1663 to a vector efficiently using Eisenstat's trick. 1664 */ 1665 scale = (2.0/omega) - 1.0; 1666 1667 /* x = (E + U)^{-1} b */ 1668 for (i=m-1; i>=0; i--) { 1669 n = a->i[i+1] - diag[i] - 1; 1670 idx = a->j + diag[i] + 1; 1671 v = a->a + diag[i] + 1; 1672 sum = b[i]; 1673 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1674 x[i] = sum*idiag[i]; 1675 } 1676 1677 /* t = b - (2*E - D)x */ 1678 v = a->a; 1679 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1680 1681 /* t = (E + L)^{-1}t */ 1682 ts = t; 1683 diag = a->diag; 1684 for (i=0; i<m; i++) { 1685 n = diag[i] - a->i[i]; 1686 idx = a->j + a->i[i]; 1687 v = a->a + a->i[i]; 1688 sum = t[i]; 1689 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1690 t[i] = sum*idiag[i]; 1691 /* x = x + t */ 1692 x[i] += t[i]; 1693 } 1694 1695 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1696 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1697 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1698 PetscFunctionReturn(0); 1699 } 1700 if (flag & SOR_ZERO_INITIAL_GUESS) { 1701 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1702 for (i=0; i<m; i++) { 1703 n = diag[i] - a->i[i]; 1704 idx = a->j + a->i[i]; 1705 v = a->a + a->i[i]; 1706 sum = b[i]; 1707 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1708 t[i] = sum; 1709 x[i] = sum*idiag[i]; 1710 } 1711 xb = t; 1712 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1713 } else xb = b; 1714 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1715 for (i=m-1; i>=0; i--) { 1716 n = a->i[i+1] - diag[i] - 1; 1717 idx = a->j + diag[i] + 1; 1718 v = a->a + diag[i] + 1; 1719 sum = xb[i]; 1720 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1721 if (xb == b) { 1722 x[i] = sum*idiag[i]; 1723 } else { 1724 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1725 } 1726 } 1727 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1728 } 1729 its--; 1730 } 1731 while (its--) { 1732 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1733 for (i=0; i<m; i++) { 1734 /* lower */ 1735 n = diag[i] - a->i[i]; 1736 idx = a->j + a->i[i]; 1737 v = a->a + a->i[i]; 1738 sum = b[i]; 1739 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1740 t[i] = sum; /* save application of the lower-triangular part */ 1741 /* upper */ 1742 n = a->i[i+1] - diag[i] - 1; 1743 idx = a->j + diag[i] + 1; 1744 v = a->a + diag[i] + 1; 1745 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1746 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1747 } 1748 xb = t; 1749 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1750 } else xb = b; 1751 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1752 for (i=m-1; i>=0; i--) { 1753 sum = xb[i]; 1754 if (xb == b) { 1755 /* whole matrix (no checkpointing available) */ 1756 n = a->i[i+1] - a->i[i]; 1757 idx = a->j + a->i[i]; 1758 v = a->a + a->i[i]; 1759 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1760 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1761 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1762 n = a->i[i+1] - diag[i] - 1; 1763 idx = a->j + diag[i] + 1; 1764 v = a->a + diag[i] + 1; 1765 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1766 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1767 } 1768 } 1769 if (xb == b) { 1770 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1771 } else { 1772 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1773 } 1774 } 1775 } 1776 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1777 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1778 PetscFunctionReturn(0); 1779 } 1780 1781 1782 #undef __FUNCT__ 1783 #define __FUNCT__ "MatGetInfo_SeqAIJ" 1784 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1785 { 1786 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1787 1788 PetscFunctionBegin; 1789 info->block_size = 1.0; 1790 info->nz_allocated = (double)a->maxnz; 1791 info->nz_used = (double)a->nz; 1792 info->nz_unneeded = (double)(a->maxnz - a->nz); 1793 info->assemblies = (double)A->num_ass; 1794 info->mallocs = (double)A->info.mallocs; 1795 info->memory = ((PetscObject)A)->mem; 1796 if (A->factortype) { 1797 info->fill_ratio_given = A->info.fill_ratio_given; 1798 info->fill_ratio_needed = A->info.fill_ratio_needed; 1799 info->factor_mallocs = A->info.factor_mallocs; 1800 } else { 1801 info->fill_ratio_given = 0; 1802 info->fill_ratio_needed = 0; 1803 info->factor_mallocs = 0; 1804 } 1805 PetscFunctionReturn(0); 1806 } 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatZeroRows_SeqAIJ" 1810 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1811 { 1812 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1813 PetscInt i,m = A->rmap->n - 1,d = 0; 1814 PetscErrorCode ierr; 1815 const PetscScalar *xx; 1816 PetscScalar *bb; 1817 PetscBool missing; 1818 1819 PetscFunctionBegin; 1820 if (x && b) { 1821 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1822 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1823 for (i=0; i<N; i++) { 1824 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1825 bb[rows[i]] = diag*xx[rows[i]]; 1826 } 1827 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1828 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1829 } 1830 1831 if (a->keepnonzeropattern) { 1832 for (i=0; i<N; i++) { 1833 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1834 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1835 } 1836 if (diag != 0.0) { 1837 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1838 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1839 for (i=0; i<N; i++) { 1840 a->a[a->diag[rows[i]]] = diag; 1841 } 1842 } 1843 } else { 1844 if (diag != 0.0) { 1845 for (i=0; i<N; i++) { 1846 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1847 if (a->ilen[rows[i]] > 0) { 1848 a->ilen[rows[i]] = 1; 1849 a->a[a->i[rows[i]]] = diag; 1850 a->j[a->i[rows[i]]] = rows[i]; 1851 } else { /* in case row was completely empty */ 1852 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1853 } 1854 } 1855 } else { 1856 for (i=0; i<N; i++) { 1857 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1858 a->ilen[rows[i]] = 0; 1859 } 1860 } 1861 A->nonzerostate++; 1862 } 1863 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1864 PetscFunctionReturn(0); 1865 } 1866 1867 #undef __FUNCT__ 1868 #define __FUNCT__ "MatZeroRowsColumns_SeqAIJ" 1869 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1870 { 1871 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1872 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1873 PetscErrorCode ierr; 1874 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1875 const PetscScalar *xx; 1876 PetscScalar *bb; 1877 1878 PetscFunctionBegin; 1879 if (x && b) { 1880 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1881 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1882 vecs = PETSC_TRUE; 1883 } 1884 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 1885 for (i=0; i<N; i++) { 1886 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1887 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1888 1889 zeroed[rows[i]] = PETSC_TRUE; 1890 } 1891 for (i=0; i<A->rmap->n; i++) { 1892 if (!zeroed[i]) { 1893 for (j=a->i[i]; j<a->i[i+1]; j++) { 1894 if (zeroed[a->j[j]]) { 1895 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1896 a->a[j] = 0.0; 1897 } 1898 } 1899 } else if (vecs) bb[i] = diag*xx[i]; 1900 } 1901 if (x && b) { 1902 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1903 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1904 } 1905 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1906 if (diag != 0.0) { 1907 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1908 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1909 for (i=0; i<N; i++) { 1910 a->a[a->diag[rows[i]]] = diag; 1911 } 1912 } 1913 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1914 PetscFunctionReturn(0); 1915 } 1916 1917 #undef __FUNCT__ 1918 #define __FUNCT__ "MatGetRow_SeqAIJ" 1919 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1920 { 1921 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1922 PetscInt *itmp; 1923 1924 PetscFunctionBegin; 1925 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1926 1927 *nz = a->i[row+1] - a->i[row]; 1928 if (v) *v = a->a + a->i[row]; 1929 if (idx) { 1930 itmp = a->j + a->i[row]; 1931 if (*nz) *idx = itmp; 1932 else *idx = 0; 1933 } 1934 PetscFunctionReturn(0); 1935 } 1936 1937 /* remove this function? */ 1938 #undef __FUNCT__ 1939 #define __FUNCT__ "MatRestoreRow_SeqAIJ" 1940 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1941 { 1942 PetscFunctionBegin; 1943 PetscFunctionReturn(0); 1944 } 1945 1946 #undef __FUNCT__ 1947 #define __FUNCT__ "MatNorm_SeqAIJ" 1948 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1949 { 1950 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1951 MatScalar *v = a->a; 1952 PetscReal sum = 0.0; 1953 PetscErrorCode ierr; 1954 PetscInt i,j; 1955 1956 PetscFunctionBegin; 1957 if (type == NORM_FROBENIUS) { 1958 for (i=0; i<a->nz; i++) { 1959 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1960 } 1961 *nrm = PetscSqrtReal(sum); 1962 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 1963 } else if (type == NORM_1) { 1964 PetscReal *tmp; 1965 PetscInt *jj = a->j; 1966 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 1967 *nrm = 0.0; 1968 for (j=0; j<a->nz; j++) { 1969 tmp[*jj++] += PetscAbsScalar(*v); v++; 1970 } 1971 for (j=0; j<A->cmap->n; j++) { 1972 if (tmp[j] > *nrm) *nrm = tmp[j]; 1973 } 1974 ierr = PetscFree(tmp);CHKERRQ(ierr); 1975 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1976 } else if (type == NORM_INFINITY) { 1977 *nrm = 0.0; 1978 for (j=0; j<A->rmap->n; j++) { 1979 v = a->a + a->i[j]; 1980 sum = 0.0; 1981 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 1982 sum += PetscAbsScalar(*v); v++; 1983 } 1984 if (sum > *nrm) *nrm = sum; 1985 } 1986 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1987 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 1988 PetscFunctionReturn(0); 1989 } 1990 1991 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 1992 #undef __FUNCT__ 1993 #define __FUNCT__ "MatTransposeSymbolic_SeqAIJ" 1994 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 1995 { 1996 PetscErrorCode ierr; 1997 PetscInt i,j,anzj; 1998 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 1999 PetscInt an=A->cmap->N,am=A->rmap->N; 2000 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2001 2002 PetscFunctionBegin; 2003 /* Allocate space for symbolic transpose info and work array */ 2004 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 2005 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 2006 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 2007 2008 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2009 /* Note: offset by 1 for fast conversion into csr format. */ 2010 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2011 /* Form ati for csr format of A^T. */ 2012 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2013 2014 /* Copy ati into atfill so we have locations of the next free space in atj */ 2015 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2016 2017 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2018 for (i=0;i<am;i++) { 2019 anzj = ai[i+1] - ai[i]; 2020 for (j=0;j<anzj;j++) { 2021 atj[atfill[*aj]] = i; 2022 atfill[*aj++] += 1; 2023 } 2024 } 2025 2026 /* Clean up temporary space and complete requests. */ 2027 ierr = PetscFree(atfill);CHKERRQ(ierr); 2028 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2029 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2030 2031 b = (Mat_SeqAIJ*)((*B)->data); 2032 b->free_a = PETSC_FALSE; 2033 b->free_ij = PETSC_TRUE; 2034 b->nonew = 0; 2035 PetscFunctionReturn(0); 2036 } 2037 2038 #undef __FUNCT__ 2039 #define __FUNCT__ "MatTranspose_SeqAIJ" 2040 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2041 { 2042 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2043 Mat C; 2044 PetscErrorCode ierr; 2045 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2046 MatScalar *array = a->a; 2047 2048 PetscFunctionBegin; 2049 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"); 2050 2051 if (reuse == MAT_INITIAL_MATRIX || *B == A) { 2052 ierr = PetscCalloc1(1+A->cmap->n,&col);CHKERRQ(ierr); 2053 2054 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2055 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2056 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2057 ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2058 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2059 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2060 ierr = PetscFree(col);CHKERRQ(ierr); 2061 } else { 2062 C = *B; 2063 } 2064 2065 for (i=0; i<m; i++) { 2066 len = ai[i+1]-ai[i]; 2067 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2068 array += len; 2069 aj += len; 2070 } 2071 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2072 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2073 2074 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 2075 *B = C; 2076 } else { 2077 ierr = MatHeaderMerge(A,&C);CHKERRQ(ierr); 2078 } 2079 PetscFunctionReturn(0); 2080 } 2081 2082 #undef __FUNCT__ 2083 #define __FUNCT__ "MatIsTranspose_SeqAIJ" 2084 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2085 { 2086 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2087 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2088 MatScalar *va,*vb; 2089 PetscErrorCode ierr; 2090 PetscInt ma,na,mb,nb, i; 2091 2092 PetscFunctionBegin; 2093 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2094 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2095 if (ma!=nb || na!=mb) { 2096 *f = PETSC_FALSE; 2097 PetscFunctionReturn(0); 2098 } 2099 aii = aij->i; bii = bij->i; 2100 adx = aij->j; bdx = bij->j; 2101 va = aij->a; vb = bij->a; 2102 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2103 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2104 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2105 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2106 2107 *f = PETSC_TRUE; 2108 for (i=0; i<ma; i++) { 2109 while (aptr[i]<aii[i+1]) { 2110 PetscInt idc,idr; 2111 PetscScalar vc,vr; 2112 /* column/row index/value */ 2113 idc = adx[aptr[i]]; 2114 idr = bdx[bptr[idc]]; 2115 vc = va[aptr[i]]; 2116 vr = vb[bptr[idc]]; 2117 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2118 *f = PETSC_FALSE; 2119 goto done; 2120 } else { 2121 aptr[i]++; 2122 if (B || i!=idc) bptr[idc]++; 2123 } 2124 } 2125 } 2126 done: 2127 ierr = PetscFree(aptr);CHKERRQ(ierr); 2128 ierr = PetscFree(bptr);CHKERRQ(ierr); 2129 PetscFunctionReturn(0); 2130 } 2131 2132 #undef __FUNCT__ 2133 #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" 2134 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2135 { 2136 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2137 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2138 MatScalar *va,*vb; 2139 PetscErrorCode ierr; 2140 PetscInt ma,na,mb,nb, i; 2141 2142 PetscFunctionBegin; 2143 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2144 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2145 if (ma!=nb || na!=mb) { 2146 *f = PETSC_FALSE; 2147 PetscFunctionReturn(0); 2148 } 2149 aii = aij->i; bii = bij->i; 2150 adx = aij->j; bdx = bij->j; 2151 va = aij->a; vb = bij->a; 2152 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2153 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2154 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2155 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2156 2157 *f = PETSC_TRUE; 2158 for (i=0; i<ma; i++) { 2159 while (aptr[i]<aii[i+1]) { 2160 PetscInt idc,idr; 2161 PetscScalar vc,vr; 2162 /* column/row index/value */ 2163 idc = adx[aptr[i]]; 2164 idr = bdx[bptr[idc]]; 2165 vc = va[aptr[i]]; 2166 vr = vb[bptr[idc]]; 2167 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2168 *f = PETSC_FALSE; 2169 goto done; 2170 } else { 2171 aptr[i]++; 2172 if (B || i!=idc) bptr[idc]++; 2173 } 2174 } 2175 } 2176 done: 2177 ierr = PetscFree(aptr);CHKERRQ(ierr); 2178 ierr = PetscFree(bptr);CHKERRQ(ierr); 2179 PetscFunctionReturn(0); 2180 } 2181 2182 #undef __FUNCT__ 2183 #define __FUNCT__ "MatIsSymmetric_SeqAIJ" 2184 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2185 { 2186 PetscErrorCode ierr; 2187 2188 PetscFunctionBegin; 2189 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2190 PetscFunctionReturn(0); 2191 } 2192 2193 #undef __FUNCT__ 2194 #define __FUNCT__ "MatIsHermitian_SeqAIJ" 2195 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2196 { 2197 PetscErrorCode ierr; 2198 2199 PetscFunctionBegin; 2200 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2201 PetscFunctionReturn(0); 2202 } 2203 2204 #undef __FUNCT__ 2205 #define __FUNCT__ "MatDiagonalScale_SeqAIJ" 2206 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2207 { 2208 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2209 PetscScalar *l,*r,x; 2210 MatScalar *v; 2211 PetscErrorCode ierr; 2212 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; 2213 2214 PetscFunctionBegin; 2215 if (ll) { 2216 /* The local size is used so that VecMPI can be passed to this routine 2217 by MatDiagonalScale_MPIAIJ */ 2218 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2219 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2220 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 2221 v = a->a; 2222 for (i=0; i<m; i++) { 2223 x = l[i]; 2224 M = a->i[i+1] - a->i[i]; 2225 for (j=0; j<M; j++) (*v++) *= x; 2226 } 2227 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 2228 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2229 } 2230 if (rr) { 2231 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2232 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2233 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 2234 v = a->a; jj = a->j; 2235 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2236 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 2237 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2238 } 2239 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2240 PetscFunctionReturn(0); 2241 } 2242 2243 #undef __FUNCT__ 2244 #define __FUNCT__ "MatGetSubMatrix_SeqAIJ" 2245 PetscErrorCode MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2246 { 2247 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2248 PetscErrorCode ierr; 2249 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2250 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2251 const PetscInt *irow,*icol; 2252 PetscInt nrows,ncols; 2253 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2254 MatScalar *a_new,*mat_a; 2255 Mat C; 2256 PetscBool stride; 2257 2258 PetscFunctionBegin; 2259 2260 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2261 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2262 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2263 2264 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2265 if (stride) { 2266 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2267 } else { 2268 first = 0; 2269 step = 0; 2270 } 2271 if (stride && step == 1) { 2272 /* special case of contiguous rows */ 2273 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2274 /* loop over new rows determining lens and starting points */ 2275 for (i=0; i<nrows; i++) { 2276 kstart = ai[irow[i]]; 2277 kend = kstart + ailen[irow[i]]; 2278 starts[i] = kstart; 2279 for (k=kstart; k<kend; k++) { 2280 if (aj[k] >= first) { 2281 starts[i] = k; 2282 break; 2283 } 2284 } 2285 sum = 0; 2286 while (k < kend) { 2287 if (aj[k++] >= first+ncols) break; 2288 sum++; 2289 } 2290 lens[i] = sum; 2291 } 2292 /* create submatrix */ 2293 if (scall == MAT_REUSE_MATRIX) { 2294 PetscInt n_cols,n_rows; 2295 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2296 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2297 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2298 C = *B; 2299 } else { 2300 PetscInt rbs,cbs; 2301 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2302 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2303 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2304 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2305 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2306 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2307 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2308 } 2309 c = (Mat_SeqAIJ*)C->data; 2310 2311 /* loop over rows inserting into submatrix */ 2312 a_new = c->a; 2313 j_new = c->j; 2314 i_new = c->i; 2315 2316 for (i=0; i<nrows; i++) { 2317 ii = starts[i]; 2318 lensi = lens[i]; 2319 for (k=0; k<lensi; k++) { 2320 *j_new++ = aj[ii+k] - first; 2321 } 2322 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2323 a_new += lensi; 2324 i_new[i+1] = i_new[i] + lensi; 2325 c->ilen[i] = lensi; 2326 } 2327 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2328 } else { 2329 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2330 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2331 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2332 for (i=0; i<ncols; i++) { 2333 #if defined(PETSC_USE_DEBUG) 2334 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); 2335 #endif 2336 smap[icol[i]] = i+1; 2337 } 2338 2339 /* determine lens of each row */ 2340 for (i=0; i<nrows; i++) { 2341 kstart = ai[irow[i]]; 2342 kend = kstart + a->ilen[irow[i]]; 2343 lens[i] = 0; 2344 for (k=kstart; k<kend; k++) { 2345 if (smap[aj[k]]) { 2346 lens[i]++; 2347 } 2348 } 2349 } 2350 /* Create and fill new matrix */ 2351 if (scall == MAT_REUSE_MATRIX) { 2352 PetscBool equal; 2353 2354 c = (Mat_SeqAIJ*)((*B)->data); 2355 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2356 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2357 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2358 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2359 C = *B; 2360 } else { 2361 PetscInt rbs,cbs; 2362 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2363 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2364 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2365 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2366 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2367 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2368 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2369 } 2370 c = (Mat_SeqAIJ*)(C->data); 2371 for (i=0; i<nrows; i++) { 2372 row = irow[i]; 2373 kstart = ai[row]; 2374 kend = kstart + a->ilen[row]; 2375 mat_i = c->i[i]; 2376 mat_j = c->j + mat_i; 2377 mat_a = c->a + mat_i; 2378 mat_ilen = c->ilen + i; 2379 for (k=kstart; k<kend; k++) { 2380 if ((tcol=smap[a->j[k]])) { 2381 *mat_j++ = tcol - 1; 2382 *mat_a++ = a->a[k]; 2383 (*mat_ilen)++; 2384 2385 } 2386 } 2387 } 2388 /* Free work space */ 2389 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2390 ierr = PetscFree(smap);CHKERRQ(ierr); 2391 ierr = PetscFree(lens);CHKERRQ(ierr); 2392 /* sort */ 2393 for (i = 0; i < nrows; i++) { 2394 PetscInt ilen; 2395 2396 mat_i = c->i[i]; 2397 mat_j = c->j + mat_i; 2398 mat_a = c->a + mat_i; 2399 ilen = c->ilen[i]; 2400 ierr = PetscSortIntWithMatScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2401 } 2402 } 2403 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2404 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2405 2406 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2407 *B = C; 2408 PetscFunctionReturn(0); 2409 } 2410 2411 #undef __FUNCT__ 2412 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 2413 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2414 { 2415 PetscErrorCode ierr; 2416 Mat B; 2417 2418 PetscFunctionBegin; 2419 if (scall == MAT_INITIAL_MATRIX) { 2420 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2421 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2422 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2423 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2424 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2425 *subMat = B; 2426 } else { 2427 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2428 } 2429 PetscFunctionReturn(0); 2430 } 2431 2432 #undef __FUNCT__ 2433 #define __FUNCT__ "MatILUFactor_SeqAIJ" 2434 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2435 { 2436 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2437 PetscErrorCode ierr; 2438 Mat outA; 2439 PetscBool row_identity,col_identity; 2440 2441 PetscFunctionBegin; 2442 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2443 2444 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2445 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2446 2447 outA = inA; 2448 outA->factortype = MAT_FACTOR_LU; 2449 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2450 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2451 2452 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2453 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2454 2455 a->row = row; 2456 2457 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2458 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2459 2460 a->col = col; 2461 2462 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2463 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2464 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2465 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2466 2467 if (!a->solve_work) { /* this matrix may have been factored before */ 2468 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2469 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2470 } 2471 2472 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2473 if (row_identity && col_identity) { 2474 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2475 } else { 2476 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2477 } 2478 PetscFunctionReturn(0); 2479 } 2480 2481 #undef __FUNCT__ 2482 #define __FUNCT__ "MatScale_SeqAIJ" 2483 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2484 { 2485 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2486 PetscScalar oalpha = alpha; 2487 PetscErrorCode ierr; 2488 PetscBLASInt one = 1,bnz; 2489 2490 PetscFunctionBegin; 2491 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2492 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2493 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2494 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2495 PetscFunctionReturn(0); 2496 } 2497 2498 #undef __FUNCT__ 2499 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 2500 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2501 { 2502 PetscErrorCode ierr; 2503 PetscInt i; 2504 2505 PetscFunctionBegin; 2506 if (scall == MAT_INITIAL_MATRIX) { 2507 ierr = PetscMalloc1(n+1,B);CHKERRQ(ierr); 2508 } 2509 2510 for (i=0; i<n; i++) { 2511 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2512 } 2513 PetscFunctionReturn(0); 2514 } 2515 2516 #undef __FUNCT__ 2517 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 2518 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2519 { 2520 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2521 PetscErrorCode ierr; 2522 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2523 const PetscInt *idx; 2524 PetscInt start,end,*ai,*aj; 2525 PetscBT table; 2526 2527 PetscFunctionBegin; 2528 m = A->rmap->n; 2529 ai = a->i; 2530 aj = a->j; 2531 2532 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2533 2534 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2535 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2536 2537 for (i=0; i<is_max; i++) { 2538 /* Initialize the two local arrays */ 2539 isz = 0; 2540 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2541 2542 /* Extract the indices, assume there can be duplicate entries */ 2543 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2544 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2545 2546 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2547 for (j=0; j<n; ++j) { 2548 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2549 } 2550 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2551 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2552 2553 k = 0; 2554 for (j=0; j<ov; j++) { /* for each overlap */ 2555 n = isz; 2556 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2557 row = nidx[k]; 2558 start = ai[row]; 2559 end = ai[row+1]; 2560 for (l = start; l<end; l++) { 2561 val = aj[l]; 2562 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2563 } 2564 } 2565 } 2566 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2567 } 2568 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2569 ierr = PetscFree(nidx);CHKERRQ(ierr); 2570 PetscFunctionReturn(0); 2571 } 2572 2573 /* -------------------------------------------------------------- */ 2574 #undef __FUNCT__ 2575 #define __FUNCT__ "MatPermute_SeqAIJ" 2576 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2577 { 2578 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2579 PetscErrorCode ierr; 2580 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2581 const PetscInt *row,*col; 2582 PetscInt *cnew,j,*lens; 2583 IS icolp,irowp; 2584 PetscInt *cwork = NULL; 2585 PetscScalar *vwork = NULL; 2586 2587 PetscFunctionBegin; 2588 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2589 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2590 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2591 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2592 2593 /* determine lengths of permuted rows */ 2594 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2595 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2596 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2597 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2598 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2599 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2600 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2601 ierr = PetscFree(lens);CHKERRQ(ierr); 2602 2603 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2604 for (i=0; i<m; i++) { 2605 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2606 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2607 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2608 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2609 } 2610 ierr = PetscFree(cnew);CHKERRQ(ierr); 2611 2612 (*B)->assembled = PETSC_FALSE; 2613 2614 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2615 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2616 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2617 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2618 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2619 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2620 PetscFunctionReturn(0); 2621 } 2622 2623 #undef __FUNCT__ 2624 #define __FUNCT__ "MatCopy_SeqAIJ" 2625 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2626 { 2627 PetscErrorCode ierr; 2628 2629 PetscFunctionBegin; 2630 /* If the two matrices have the same copy implementation, use fast copy. */ 2631 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2632 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2633 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2634 2635 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"); 2636 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2637 } else { 2638 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2639 } 2640 PetscFunctionReturn(0); 2641 } 2642 2643 #undef __FUNCT__ 2644 #define __FUNCT__ "MatSetUp_SeqAIJ" 2645 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2646 { 2647 PetscErrorCode ierr; 2648 2649 PetscFunctionBegin; 2650 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2651 PetscFunctionReturn(0); 2652 } 2653 2654 #undef __FUNCT__ 2655 #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" 2656 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2657 { 2658 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2659 2660 PetscFunctionBegin; 2661 *array = a->a; 2662 PetscFunctionReturn(0); 2663 } 2664 2665 #undef __FUNCT__ 2666 #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" 2667 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2668 { 2669 PetscFunctionBegin; 2670 PetscFunctionReturn(0); 2671 } 2672 2673 /* 2674 Computes the number of nonzeros per row needed for preallocation when X and Y 2675 have different nonzero structure. 2676 */ 2677 #undef __FUNCT__ 2678 #define __FUNCT__ "MatAXPYGetPreallocation_SeqX_private" 2679 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2680 { 2681 PetscInt i,j,k,nzx,nzy; 2682 2683 PetscFunctionBegin; 2684 /* Set the number of nonzeros in the new matrix */ 2685 for (i=0; i<m; i++) { 2686 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2687 nzx = xi[i+1] - xi[i]; 2688 nzy = yi[i+1] - yi[i]; 2689 nnz[i] = 0; 2690 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2691 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2692 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2693 nnz[i]++; 2694 } 2695 for (; k<nzy; k++) nnz[i]++; 2696 } 2697 PetscFunctionReturn(0); 2698 } 2699 2700 #undef __FUNCT__ 2701 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 2702 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2703 { 2704 PetscInt m = Y->rmap->N; 2705 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2706 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2707 PetscErrorCode ierr; 2708 2709 PetscFunctionBegin; 2710 /* Set the number of nonzeros in the new matrix */ 2711 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2712 PetscFunctionReturn(0); 2713 } 2714 2715 #undef __FUNCT__ 2716 #define __FUNCT__ "MatAXPY_SeqAIJ" 2717 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2718 { 2719 PetscErrorCode ierr; 2720 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2721 PetscBLASInt one=1,bnz; 2722 2723 PetscFunctionBegin; 2724 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2725 if (str == SAME_NONZERO_PATTERN) { 2726 PetscScalar alpha = a; 2727 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2728 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2729 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2730 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2731 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2732 } else { 2733 Mat B; 2734 PetscInt *nnz; 2735 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2736 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2737 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2738 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2739 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2740 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2741 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2742 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2743 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2744 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2745 ierr = PetscFree(nnz);CHKERRQ(ierr); 2746 } 2747 PetscFunctionReturn(0); 2748 } 2749 2750 #undef __FUNCT__ 2751 #define __FUNCT__ "MatConjugate_SeqAIJ" 2752 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2753 { 2754 #if defined(PETSC_USE_COMPLEX) 2755 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2756 PetscInt i,nz; 2757 PetscScalar *a; 2758 2759 PetscFunctionBegin; 2760 nz = aij->nz; 2761 a = aij->a; 2762 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2763 #else 2764 PetscFunctionBegin; 2765 #endif 2766 PetscFunctionReturn(0); 2767 } 2768 2769 #undef __FUNCT__ 2770 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 2771 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2772 { 2773 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2774 PetscErrorCode ierr; 2775 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2776 PetscReal atmp; 2777 PetscScalar *x; 2778 MatScalar *aa; 2779 2780 PetscFunctionBegin; 2781 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2782 aa = a->a; 2783 ai = a->i; 2784 aj = a->j; 2785 2786 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2787 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2788 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2789 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2790 for (i=0; i<m; i++) { 2791 ncols = ai[1] - ai[0]; ai++; 2792 x[i] = 0.0; 2793 for (j=0; j<ncols; j++) { 2794 atmp = PetscAbsScalar(*aa); 2795 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2796 aa++; aj++; 2797 } 2798 } 2799 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2800 PetscFunctionReturn(0); 2801 } 2802 2803 #undef __FUNCT__ 2804 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 2805 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2806 { 2807 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2808 PetscErrorCode ierr; 2809 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2810 PetscScalar *x; 2811 MatScalar *aa; 2812 2813 PetscFunctionBegin; 2814 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2815 aa = a->a; 2816 ai = a->i; 2817 aj = a->j; 2818 2819 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2820 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2821 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2822 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2823 for (i=0; i<m; i++) { 2824 ncols = ai[1] - ai[0]; ai++; 2825 if (ncols == A->cmap->n) { /* row is dense */ 2826 x[i] = *aa; if (idx) idx[i] = 0; 2827 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2828 x[i] = 0.0; 2829 if (idx) { 2830 idx[i] = 0; /* in case ncols is zero */ 2831 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2832 if (aj[j] > j) { 2833 idx[i] = j; 2834 break; 2835 } 2836 } 2837 } 2838 } 2839 for (j=0; j<ncols; j++) { 2840 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2841 aa++; aj++; 2842 } 2843 } 2844 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2845 PetscFunctionReturn(0); 2846 } 2847 2848 #undef __FUNCT__ 2849 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 2850 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2851 { 2852 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2853 PetscErrorCode ierr; 2854 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2855 PetscReal atmp; 2856 PetscScalar *x; 2857 MatScalar *aa; 2858 2859 PetscFunctionBegin; 2860 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2861 aa = a->a; 2862 ai = a->i; 2863 aj = a->j; 2864 2865 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2866 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2867 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2868 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); 2869 for (i=0; i<m; i++) { 2870 ncols = ai[1] - ai[0]; ai++; 2871 if (ncols) { 2872 /* Get first nonzero */ 2873 for (j = 0; j < ncols; j++) { 2874 atmp = PetscAbsScalar(aa[j]); 2875 if (atmp > 1.0e-12) { 2876 x[i] = atmp; 2877 if (idx) idx[i] = aj[j]; 2878 break; 2879 } 2880 } 2881 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 2882 } else { 2883 x[i] = 0.0; if (idx) idx[i] = 0; 2884 } 2885 for (j = 0; j < ncols; j++) { 2886 atmp = PetscAbsScalar(*aa); 2887 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2888 aa++; aj++; 2889 } 2890 } 2891 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2892 PetscFunctionReturn(0); 2893 } 2894 2895 #undef __FUNCT__ 2896 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 2897 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2898 { 2899 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2900 PetscErrorCode ierr; 2901 PetscInt i,j,m = A->rmap->n,ncols,n; 2902 const PetscInt *ai,*aj; 2903 PetscScalar *x; 2904 const MatScalar *aa; 2905 2906 PetscFunctionBegin; 2907 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2908 aa = a->a; 2909 ai = a->i; 2910 aj = a->j; 2911 2912 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2913 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2914 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2915 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2916 for (i=0; i<m; i++) { 2917 ncols = ai[1] - ai[0]; ai++; 2918 if (ncols == A->cmap->n) { /* row is dense */ 2919 x[i] = *aa; if (idx) idx[i] = 0; 2920 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2921 x[i] = 0.0; 2922 if (idx) { /* find first implicit 0.0 in the row */ 2923 idx[i] = 0; /* in case ncols is zero */ 2924 for (j=0; j<ncols; j++) { 2925 if (aj[j] > j) { 2926 idx[i] = j; 2927 break; 2928 } 2929 } 2930 } 2931 } 2932 for (j=0; j<ncols; j++) { 2933 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2934 aa++; aj++; 2935 } 2936 } 2937 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2938 PetscFunctionReturn(0); 2939 } 2940 2941 #include <petscblaslapack.h> 2942 #include <petsc/private/kernels/blockinvert.h> 2943 2944 #undef __FUNCT__ 2945 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 2946 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 2947 { 2948 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 2949 PetscErrorCode ierr; 2950 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 2951 MatScalar *diag,work[25],*v_work; 2952 PetscReal shift = 0.0; 2953 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 2954 2955 PetscFunctionBegin; 2956 allowzeropivot = PetscNot(A->erroriffailure); 2957 if (a->ibdiagvalid) { 2958 if (values) *values = a->ibdiag; 2959 PetscFunctionReturn(0); 2960 } 2961 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 2962 if (!a->ibdiag) { 2963 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 2964 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 2965 } 2966 diag = a->ibdiag; 2967 if (values) *values = a->ibdiag; 2968 /* factor and invert each block */ 2969 switch (bs) { 2970 case 1: 2971 for (i=0; i<mbs; i++) { 2972 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 2973 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 2974 if (allowzeropivot) { 2975 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2976 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 2977 A->factorerror_zeropivot_row = i; 2978 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 2979 } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D pivot %g tolerance %g",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON); 2980 } 2981 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 2982 } 2983 break; 2984 case 2: 2985 for (i=0; i<mbs; i++) { 2986 ij[0] = 2*i; ij[1] = 2*i + 1; 2987 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 2988 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 2989 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2990 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 2991 diag += 4; 2992 } 2993 break; 2994 case 3: 2995 for (i=0; i<mbs; i++) { 2996 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 2997 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 2998 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 2999 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3000 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3001 diag += 9; 3002 } 3003 break; 3004 case 4: 3005 for (i=0; i<mbs; i++) { 3006 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3007 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3008 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3009 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3010 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3011 diag += 16; 3012 } 3013 break; 3014 case 5: 3015 for (i=0; i<mbs; i++) { 3016 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3017 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3018 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3019 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3020 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3021 diag += 25; 3022 } 3023 break; 3024 case 6: 3025 for (i=0; i<mbs; i++) { 3026 ij[0] = 6*i; ij[1] = 6*i + 1; ij[2] = 6*i + 2; ij[3] = 6*i + 3; ij[4] = 6*i + 4; ij[5] = 6*i + 5; 3027 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3028 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3029 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3030 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3031 diag += 36; 3032 } 3033 break; 3034 case 7: 3035 for (i=0; i<mbs; i++) { 3036 ij[0] = 7*i; ij[1] = 7*i + 1; ij[2] = 7*i + 2; ij[3] = 7*i + 3; ij[4] = 7*i + 4; ij[5] = 7*i + 5; ij[5] = 7*i + 6; 3037 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3038 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3039 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3040 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3041 diag += 49; 3042 } 3043 break; 3044 default: 3045 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3046 for (i=0; i<mbs; i++) { 3047 for (j=0; j<bs; j++) { 3048 IJ[j] = bs*i + j; 3049 } 3050 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3051 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3052 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3053 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3054 diag += bs2; 3055 } 3056 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3057 } 3058 a->ibdiagvalid = PETSC_TRUE; 3059 PetscFunctionReturn(0); 3060 } 3061 3062 #undef __FUNCT__ 3063 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3064 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3065 { 3066 PetscErrorCode ierr; 3067 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3068 PetscScalar a; 3069 PetscInt m,n,i,j,col; 3070 3071 PetscFunctionBegin; 3072 if (!x->assembled) { 3073 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3074 for (i=0; i<m; i++) { 3075 for (j=0; j<aij->imax[i]; j++) { 3076 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3077 col = (PetscInt)(n*PetscRealPart(a)); 3078 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3079 } 3080 } 3081 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3082 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3083 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3084 PetscFunctionReturn(0); 3085 } 3086 3087 #undef __FUNCT__ 3088 #define __FUNCT__ "MatShift_SeqAIJ" 3089 PetscErrorCode MatShift_SeqAIJ(Mat Y,PetscScalar a) 3090 { 3091 PetscErrorCode ierr; 3092 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)Y->data; 3093 3094 PetscFunctionBegin; 3095 if (!Y->preallocated || !aij->nz) { 3096 ierr = MatSeqAIJSetPreallocation(Y,1,NULL);CHKERRQ(ierr); 3097 } 3098 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 3099 PetscFunctionReturn(0); 3100 } 3101 3102 /* -------------------------------------------------------------------*/ 3103 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3104 MatGetRow_SeqAIJ, 3105 MatRestoreRow_SeqAIJ, 3106 MatMult_SeqAIJ, 3107 /* 4*/ MatMultAdd_SeqAIJ, 3108 MatMultTranspose_SeqAIJ, 3109 MatMultTransposeAdd_SeqAIJ, 3110 0, 3111 0, 3112 0, 3113 /* 10*/ 0, 3114 MatLUFactor_SeqAIJ, 3115 0, 3116 MatSOR_SeqAIJ, 3117 MatTranspose_SeqAIJ, 3118 /*1 5*/ MatGetInfo_SeqAIJ, 3119 MatEqual_SeqAIJ, 3120 MatGetDiagonal_SeqAIJ, 3121 MatDiagonalScale_SeqAIJ, 3122 MatNorm_SeqAIJ, 3123 /* 20*/ 0, 3124 MatAssemblyEnd_SeqAIJ, 3125 MatSetOption_SeqAIJ, 3126 MatZeroEntries_SeqAIJ, 3127 /* 24*/ MatZeroRows_SeqAIJ, 3128 0, 3129 0, 3130 0, 3131 0, 3132 /* 29*/ MatSetUp_SeqAIJ, 3133 0, 3134 0, 3135 0, 3136 0, 3137 /* 34*/ MatDuplicate_SeqAIJ, 3138 0, 3139 0, 3140 MatILUFactor_SeqAIJ, 3141 0, 3142 /* 39*/ MatAXPY_SeqAIJ, 3143 MatGetSubMatrices_SeqAIJ, 3144 MatIncreaseOverlap_SeqAIJ, 3145 MatGetValues_SeqAIJ, 3146 MatCopy_SeqAIJ, 3147 /* 44*/ MatGetRowMax_SeqAIJ, 3148 MatScale_SeqAIJ, 3149 MatShift_SeqAIJ, 3150 MatDiagonalSet_SeqAIJ, 3151 MatZeroRowsColumns_SeqAIJ, 3152 /* 49*/ MatSetRandom_SeqAIJ, 3153 MatGetRowIJ_SeqAIJ, 3154 MatRestoreRowIJ_SeqAIJ, 3155 MatGetColumnIJ_SeqAIJ, 3156 MatRestoreColumnIJ_SeqAIJ, 3157 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3158 0, 3159 0, 3160 MatPermute_SeqAIJ, 3161 0, 3162 /* 59*/ 0, 3163 MatDestroy_SeqAIJ, 3164 MatView_SeqAIJ, 3165 0, 3166 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3167 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3168 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3169 0, 3170 0, 3171 0, 3172 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3173 MatGetRowMinAbs_SeqAIJ, 3174 0, 3175 0, 3176 0, 3177 /* 74*/ 0, 3178 MatFDColoringApply_AIJ, 3179 0, 3180 0, 3181 0, 3182 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3183 0, 3184 0, 3185 0, 3186 MatLoad_SeqAIJ, 3187 /* 84*/ MatIsSymmetric_SeqAIJ, 3188 MatIsHermitian_SeqAIJ, 3189 0, 3190 0, 3191 0, 3192 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3193 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3194 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3195 MatPtAP_SeqAIJ_SeqAIJ, 3196 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3197 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3198 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3199 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3200 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3201 0, 3202 /* 99*/ 0, 3203 0, 3204 0, 3205 MatConjugate_SeqAIJ, 3206 0, 3207 /*104*/ MatSetValuesRow_SeqAIJ, 3208 MatRealPart_SeqAIJ, 3209 MatImaginaryPart_SeqAIJ, 3210 0, 3211 0, 3212 /*109*/ MatMatSolve_SeqAIJ, 3213 0, 3214 MatGetRowMin_SeqAIJ, 3215 0, 3216 MatMissingDiagonal_SeqAIJ, 3217 /*114*/ 0, 3218 0, 3219 0, 3220 0, 3221 0, 3222 /*119*/ 0, 3223 0, 3224 0, 3225 0, 3226 MatGetMultiProcBlock_SeqAIJ, 3227 /*124*/ MatFindNonzeroRows_SeqAIJ, 3228 MatGetColumnNorms_SeqAIJ, 3229 MatInvertBlockDiagonal_SeqAIJ, 3230 0, 3231 0, 3232 /*129*/ 0, 3233 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3234 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3235 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3236 MatTransposeColoringCreate_SeqAIJ, 3237 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3238 MatTransColoringApplyDenToSp_SeqAIJ, 3239 MatRARt_SeqAIJ_SeqAIJ, 3240 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3241 MatRARtNumeric_SeqAIJ_SeqAIJ, 3242 /*139*/0, 3243 0, 3244 0, 3245 MatFDColoringSetUp_SeqXAIJ, 3246 MatFindOffBlockDiagonalEntries_SeqAIJ, 3247 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ 3248 }; 3249 3250 #undef __FUNCT__ 3251 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3252 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3253 { 3254 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3255 PetscInt i,nz,n; 3256 3257 PetscFunctionBegin; 3258 nz = aij->maxnz; 3259 n = mat->rmap->n; 3260 for (i=0; i<nz; i++) { 3261 aij->j[i] = indices[i]; 3262 } 3263 aij->nz = nz; 3264 for (i=0; i<n; i++) { 3265 aij->ilen[i] = aij->imax[i]; 3266 } 3267 PetscFunctionReturn(0); 3268 } 3269 3270 #undef __FUNCT__ 3271 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3272 /*@ 3273 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3274 in the matrix. 3275 3276 Input Parameters: 3277 + mat - the SeqAIJ matrix 3278 - indices - the column indices 3279 3280 Level: advanced 3281 3282 Notes: 3283 This can be called if you have precomputed the nonzero structure of the 3284 matrix and want to provide it to the matrix object to improve the performance 3285 of the MatSetValues() operation. 3286 3287 You MUST have set the correct numbers of nonzeros per row in the call to 3288 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3289 3290 MUST be called before any calls to MatSetValues(); 3291 3292 The indices should start with zero, not one. 3293 3294 @*/ 3295 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3296 { 3297 PetscErrorCode ierr; 3298 3299 PetscFunctionBegin; 3300 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3301 PetscValidPointer(indices,2); 3302 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3303 PetscFunctionReturn(0); 3304 } 3305 3306 /* ----------------------------------------------------------------------------------------*/ 3307 3308 #undef __FUNCT__ 3309 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3310 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3311 { 3312 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3313 PetscErrorCode ierr; 3314 size_t nz = aij->i[mat->rmap->n]; 3315 3316 PetscFunctionBegin; 3317 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3318 3319 /* allocate space for values if not already there */ 3320 if (!aij->saved_values) { 3321 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3322 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3323 } 3324 3325 /* copy values over */ 3326 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3327 PetscFunctionReturn(0); 3328 } 3329 3330 #undef __FUNCT__ 3331 #define __FUNCT__ "MatStoreValues" 3332 /*@ 3333 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3334 example, reuse of the linear part of a Jacobian, while recomputing the 3335 nonlinear portion. 3336 3337 Collect on Mat 3338 3339 Input Parameters: 3340 . mat - the matrix (currently only AIJ matrices support this option) 3341 3342 Level: advanced 3343 3344 Common Usage, with SNESSolve(): 3345 $ Create Jacobian matrix 3346 $ Set linear terms into matrix 3347 $ Apply boundary conditions to matrix, at this time matrix must have 3348 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3349 $ boundary conditions again will not change the nonzero structure 3350 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3351 $ ierr = MatStoreValues(mat); 3352 $ Call SNESSetJacobian() with matrix 3353 $ In your Jacobian routine 3354 $ ierr = MatRetrieveValues(mat); 3355 $ Set nonlinear terms in matrix 3356 3357 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3358 $ // build linear portion of Jacobian 3359 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3360 $ ierr = MatStoreValues(mat); 3361 $ loop over nonlinear iterations 3362 $ ierr = MatRetrieveValues(mat); 3363 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3364 $ // call MatAssemblyBegin/End() on matrix 3365 $ Solve linear system with Jacobian 3366 $ endloop 3367 3368 Notes: 3369 Matrix must already be assemblied before calling this routine 3370 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3371 calling this routine. 3372 3373 When this is called multiple times it overwrites the previous set of stored values 3374 and does not allocated additional space. 3375 3376 .seealso: MatRetrieveValues() 3377 3378 @*/ 3379 PetscErrorCode MatStoreValues(Mat mat) 3380 { 3381 PetscErrorCode ierr; 3382 3383 PetscFunctionBegin; 3384 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3385 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3386 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3387 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3388 PetscFunctionReturn(0); 3389 } 3390 3391 #undef __FUNCT__ 3392 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3393 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3394 { 3395 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3396 PetscErrorCode ierr; 3397 PetscInt nz = aij->i[mat->rmap->n]; 3398 3399 PetscFunctionBegin; 3400 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3401 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3402 /* copy values over */ 3403 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3404 PetscFunctionReturn(0); 3405 } 3406 3407 #undef __FUNCT__ 3408 #define __FUNCT__ "MatRetrieveValues" 3409 /*@ 3410 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3411 example, reuse of the linear part of a Jacobian, while recomputing the 3412 nonlinear portion. 3413 3414 Collect on Mat 3415 3416 Input Parameters: 3417 . mat - the matrix (currently on AIJ matrices support this option) 3418 3419 Level: advanced 3420 3421 .seealso: MatStoreValues() 3422 3423 @*/ 3424 PetscErrorCode MatRetrieveValues(Mat mat) 3425 { 3426 PetscErrorCode ierr; 3427 3428 PetscFunctionBegin; 3429 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3430 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3431 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3432 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3433 PetscFunctionReturn(0); 3434 } 3435 3436 3437 /* --------------------------------------------------------------------------------*/ 3438 #undef __FUNCT__ 3439 #define __FUNCT__ "MatCreateSeqAIJ" 3440 /*@C 3441 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3442 (the default parallel PETSc format). For good matrix assembly performance 3443 the user should preallocate the matrix storage by setting the parameter nz 3444 (or the array nnz). By setting these parameters accurately, performance 3445 during matrix assembly can be increased by more than a factor of 50. 3446 3447 Collective on MPI_Comm 3448 3449 Input Parameters: 3450 + comm - MPI communicator, set to PETSC_COMM_SELF 3451 . m - number of rows 3452 . n - number of columns 3453 . nz - number of nonzeros per row (same for all rows) 3454 - nnz - array containing the number of nonzeros in the various rows 3455 (possibly different for each row) or NULL 3456 3457 Output Parameter: 3458 . A - the matrix 3459 3460 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3461 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3462 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3463 3464 Notes: 3465 If nnz is given then nz is ignored 3466 3467 The AIJ format (also called the Yale sparse matrix format or 3468 compressed row storage), is fully compatible with standard Fortran 77 3469 storage. That is, the stored row and column indices can begin at 3470 either one (as in Fortran) or zero. See the users' manual for details. 3471 3472 Specify the preallocated storage with either nz or nnz (not both). 3473 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3474 allocation. For large problems you MUST preallocate memory or you 3475 will get TERRIBLE performance, see the users' manual chapter on matrices. 3476 3477 By default, this format uses inodes (identical nodes) when possible, to 3478 improve numerical efficiency of matrix-vector products and solves. We 3479 search for consecutive rows with the same nonzero structure, thereby 3480 reusing matrix information to achieve increased efficiency. 3481 3482 Options Database Keys: 3483 + -mat_no_inode - Do not use inodes 3484 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3485 3486 Level: intermediate 3487 3488 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3489 3490 @*/ 3491 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3492 { 3493 PetscErrorCode ierr; 3494 3495 PetscFunctionBegin; 3496 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3497 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3498 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3499 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3500 PetscFunctionReturn(0); 3501 } 3502 3503 #undef __FUNCT__ 3504 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3505 /*@C 3506 MatSeqAIJSetPreallocation - For good matrix assembly performance 3507 the user should preallocate the matrix storage by setting the parameter nz 3508 (or the array nnz). By setting these parameters accurately, performance 3509 during matrix assembly can be increased by more than a factor of 50. 3510 3511 Collective on MPI_Comm 3512 3513 Input Parameters: 3514 + B - The matrix 3515 . nz - number of nonzeros per row (same for all rows) 3516 - nnz - array containing the number of nonzeros in the various rows 3517 (possibly different for each row) or NULL 3518 3519 Notes: 3520 If nnz is given then nz is ignored 3521 3522 The AIJ format (also called the Yale sparse matrix format or 3523 compressed row storage), is fully compatible with standard Fortran 77 3524 storage. That is, the stored row and column indices can begin at 3525 either one (as in Fortran) or zero. See the users' manual for details. 3526 3527 Specify the preallocated storage with either nz or nnz (not both). 3528 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3529 allocation. For large problems you MUST preallocate memory or you 3530 will get TERRIBLE performance, see the users' manual chapter on matrices. 3531 3532 You can call MatGetInfo() to get information on how effective the preallocation was; 3533 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3534 You can also run with the option -info and look for messages with the string 3535 malloc in them to see if additional memory allocation was needed. 3536 3537 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3538 entries or columns indices 3539 3540 By default, this format uses inodes (identical nodes) when possible, to 3541 improve numerical efficiency of matrix-vector products and solves. We 3542 search for consecutive rows with the same nonzero structure, thereby 3543 reusing matrix information to achieve increased efficiency. 3544 3545 Options Database Keys: 3546 + -mat_no_inode - Do not use inodes 3547 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3548 - -mat_aij_oneindex - Internally use indexing starting at 1 3549 rather than 0. Note that when calling MatSetValues(), 3550 the user still MUST index entries starting at 0! 3551 3552 Level: intermediate 3553 3554 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3555 3556 @*/ 3557 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3558 { 3559 PetscErrorCode ierr; 3560 3561 PetscFunctionBegin; 3562 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3563 PetscValidType(B,1); 3564 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3565 PetscFunctionReturn(0); 3566 } 3567 3568 #undef __FUNCT__ 3569 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3570 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3571 { 3572 Mat_SeqAIJ *b; 3573 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3574 PetscErrorCode ierr; 3575 PetscInt i; 3576 3577 PetscFunctionBegin; 3578 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3579 if (nz == MAT_SKIP_ALLOCATION) { 3580 skipallocation = PETSC_TRUE; 3581 nz = 0; 3582 } 3583 3584 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3585 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3586 3587 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3588 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3589 if (nnz) { 3590 for (i=0; i<B->rmap->n; i++) { 3591 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]); 3592 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); 3593 } 3594 } 3595 3596 B->preallocated = PETSC_TRUE; 3597 3598 b = (Mat_SeqAIJ*)B->data; 3599 3600 if (!skipallocation) { 3601 if (!b->imax) { 3602 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3603 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3604 } 3605 if (!nnz) { 3606 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3607 else if (nz < 0) nz = 1; 3608 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3609 nz = nz*B->rmap->n; 3610 } else { 3611 nz = 0; 3612 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3613 } 3614 /* b->ilen will count nonzeros in each row so far. */ 3615 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3616 3617 /* allocate the matrix space */ 3618 /* FIXME: should B's old memory be unlogged? */ 3619 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3620 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3621 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3622 b->i[0] = 0; 3623 for (i=1; i<B->rmap->n+1; i++) { 3624 b->i[i] = b->i[i-1] + b->imax[i-1]; 3625 } 3626 b->singlemalloc = PETSC_TRUE; 3627 b->free_a = PETSC_TRUE; 3628 b->free_ij = PETSC_TRUE; 3629 } else { 3630 b->free_a = PETSC_FALSE; 3631 b->free_ij = PETSC_FALSE; 3632 } 3633 3634 b->nz = 0; 3635 b->maxnz = nz; 3636 B->info.nz_unneeded = (double)b->maxnz; 3637 if (realalloc) { 3638 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3639 } 3640 PetscFunctionReturn(0); 3641 } 3642 3643 #undef __FUNCT__ 3644 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3645 /*@ 3646 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3647 3648 Input Parameters: 3649 + B - the matrix 3650 . i - the indices into j for the start of each row (starts with zero) 3651 . j - the column indices for each row (starts with zero) these must be sorted for each row 3652 - v - optional values in the matrix 3653 3654 Level: developer 3655 3656 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3657 3658 .keywords: matrix, aij, compressed row, sparse, sequential 3659 3660 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3661 @*/ 3662 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3663 { 3664 PetscErrorCode ierr; 3665 3666 PetscFunctionBegin; 3667 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3668 PetscValidType(B,1); 3669 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3670 PetscFunctionReturn(0); 3671 } 3672 3673 #undef __FUNCT__ 3674 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3675 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3676 { 3677 PetscInt i; 3678 PetscInt m,n; 3679 PetscInt nz; 3680 PetscInt *nnz, nz_max = 0; 3681 PetscScalar *values; 3682 PetscErrorCode ierr; 3683 3684 PetscFunctionBegin; 3685 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3686 3687 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3688 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3689 3690 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3691 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 3692 for (i = 0; i < m; i++) { 3693 nz = Ii[i+1]- Ii[i]; 3694 nz_max = PetscMax(nz_max, nz); 3695 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3696 nnz[i] = nz; 3697 } 3698 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3699 ierr = PetscFree(nnz);CHKERRQ(ierr); 3700 3701 if (v) { 3702 values = (PetscScalar*) v; 3703 } else { 3704 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3705 } 3706 3707 for (i = 0; i < m; i++) { 3708 nz = Ii[i+1] - Ii[i]; 3709 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3710 } 3711 3712 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3713 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3714 3715 if (!v) { 3716 ierr = PetscFree(values);CHKERRQ(ierr); 3717 } 3718 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3719 PetscFunctionReturn(0); 3720 } 3721 3722 #include <../src/mat/impls/dense/seq/dense.h> 3723 #include <petsc/private/kernels/petscaxpy.h> 3724 3725 #undef __FUNCT__ 3726 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3727 /* 3728 Computes (B'*A')' since computing B*A directly is untenable 3729 3730 n p p 3731 ( ) ( ) ( ) 3732 m ( A ) * n ( B ) = m ( C ) 3733 ( ) ( ) ( ) 3734 3735 */ 3736 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3737 { 3738 PetscErrorCode ierr; 3739 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3740 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3741 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3742 PetscInt i,n,m,q,p; 3743 const PetscInt *ii,*idx; 3744 const PetscScalar *b,*a,*a_q; 3745 PetscScalar *c,*c_q; 3746 3747 PetscFunctionBegin; 3748 m = A->rmap->n; 3749 n = A->cmap->n; 3750 p = B->cmap->n; 3751 a = sub_a->v; 3752 b = sub_b->a; 3753 c = sub_c->v; 3754 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3755 3756 ii = sub_b->i; 3757 idx = sub_b->j; 3758 for (i=0; i<n; i++) { 3759 q = ii[i+1] - ii[i]; 3760 while (q-->0) { 3761 c_q = c + m*(*idx); 3762 a_q = a + m*i; 3763 PetscKernelAXPY(c_q,*b,a_q,m); 3764 idx++; 3765 b++; 3766 } 3767 } 3768 PetscFunctionReturn(0); 3769 } 3770 3771 #undef __FUNCT__ 3772 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 3773 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3774 { 3775 PetscErrorCode ierr; 3776 PetscInt m=A->rmap->n,n=B->cmap->n; 3777 Mat Cmat; 3778 3779 PetscFunctionBegin; 3780 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); 3781 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3782 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3783 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3784 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3785 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3786 3787 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3788 3789 *C = Cmat; 3790 PetscFunctionReturn(0); 3791 } 3792 3793 /* ----------------------------------------------------------------*/ 3794 #undef __FUNCT__ 3795 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 3796 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3797 { 3798 PetscErrorCode ierr; 3799 3800 PetscFunctionBegin; 3801 if (scall == MAT_INITIAL_MATRIX) { 3802 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3803 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3804 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3805 } 3806 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3807 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3808 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3809 PetscFunctionReturn(0); 3810 } 3811 3812 3813 /*MC 3814 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3815 based on compressed sparse row format. 3816 3817 Options Database Keys: 3818 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3819 3820 Level: beginner 3821 3822 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3823 M*/ 3824 3825 /*MC 3826 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3827 3828 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3829 and MATMPIAIJ otherwise. As a result, for single process communicators, 3830 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3831 for communicators controlling multiple processes. It is recommended that you call both of 3832 the above preallocation routines for simplicity. 3833 3834 Options Database Keys: 3835 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3836 3837 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 3838 enough exist. 3839 3840 Level: beginner 3841 3842 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3843 M*/ 3844 3845 /*MC 3846 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3847 3848 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3849 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3850 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3851 for communicators controlling multiple processes. It is recommended that you call both of 3852 the above preallocation routines for simplicity. 3853 3854 Options Database Keys: 3855 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3856 3857 Level: beginner 3858 3859 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3860 M*/ 3861 3862 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3863 #if defined(PETSC_HAVE_ELEMENTAL) 3864 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 3865 #endif 3866 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 3867 3868 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3869 PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 3870 PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 3871 #endif 3872 3873 3874 #undef __FUNCT__ 3875 #define __FUNCT__ "MatSeqAIJGetArray" 3876 /*@C 3877 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 3878 3879 Not Collective 3880 3881 Input Parameter: 3882 . mat - a MATSEQAIJ matrix 3883 3884 Output Parameter: 3885 . array - pointer to the data 3886 3887 Level: intermediate 3888 3889 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3890 @*/ 3891 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 3892 { 3893 PetscErrorCode ierr; 3894 3895 PetscFunctionBegin; 3896 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3897 PetscFunctionReturn(0); 3898 } 3899 3900 #undef __FUNCT__ 3901 #define __FUNCT__ "MatSeqAIJGetMaxRowNonzeros" 3902 /*@C 3903 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 3904 3905 Not Collective 3906 3907 Input Parameter: 3908 . mat - a MATSEQAIJ matrix 3909 3910 Output Parameter: 3911 . nz - the maximum number of nonzeros in any row 3912 3913 Level: intermediate 3914 3915 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3916 @*/ 3917 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 3918 { 3919 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 3920 3921 PetscFunctionBegin; 3922 *nz = aij->rmax; 3923 PetscFunctionReturn(0); 3924 } 3925 3926 #undef __FUNCT__ 3927 #define __FUNCT__ "MatSeqAIJRestoreArray" 3928 /*@C 3929 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 3930 3931 Not Collective 3932 3933 Input Parameters: 3934 . mat - a MATSEQAIJ matrix 3935 . array - pointer to the data 3936 3937 Level: intermediate 3938 3939 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 3940 @*/ 3941 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 3942 { 3943 PetscErrorCode ierr; 3944 3945 PetscFunctionBegin; 3946 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3947 PetscFunctionReturn(0); 3948 } 3949 3950 #undef __FUNCT__ 3951 #define __FUNCT__ "MatCreate_SeqAIJ" 3952 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 3953 { 3954 Mat_SeqAIJ *b; 3955 PetscErrorCode ierr; 3956 PetscMPIInt size; 3957 3958 PetscFunctionBegin; 3959 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 3960 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3961 3962 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3963 3964 B->data = (void*)b; 3965 3966 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3967 3968 b->row = 0; 3969 b->col = 0; 3970 b->icol = 0; 3971 b->reallocs = 0; 3972 b->ignorezeroentries = PETSC_FALSE; 3973 b->roworiented = PETSC_TRUE; 3974 b->nonew = 0; 3975 b->diag = 0; 3976 b->solve_work = 0; 3977 B->spptr = 0; 3978 b->saved_values = 0; 3979 b->idiag = 0; 3980 b->mdiag = 0; 3981 b->ssor_work = 0; 3982 b->omega = 1.0; 3983 b->fshift = 0.0; 3984 b->idiagvalid = PETSC_FALSE; 3985 b->ibdiagvalid = PETSC_FALSE; 3986 b->keepnonzeropattern = PETSC_FALSE; 3987 3988 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3989 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 3990 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 3991 3992 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3993 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 3994 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 3995 #endif 3996 3997 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 3998 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 3999 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4000 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4001 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4002 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4003 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4004 #if defined(PETSC_HAVE_ELEMENTAL) 4005 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 4006 #endif 4007 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 4008 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4009 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4010 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4011 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4012 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4013 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4014 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4015 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4016 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4017 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4018 PetscFunctionReturn(0); 4019 } 4020 4021 #undef __FUNCT__ 4022 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4023 /* 4024 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4025 */ 4026 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4027 { 4028 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4029 PetscErrorCode ierr; 4030 PetscInt i,m = A->rmap->n; 4031 4032 PetscFunctionBegin; 4033 c = (Mat_SeqAIJ*)C->data; 4034 4035 C->factortype = A->factortype; 4036 c->row = 0; 4037 c->col = 0; 4038 c->icol = 0; 4039 c->reallocs = 0; 4040 4041 C->assembled = PETSC_TRUE; 4042 4043 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4044 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4045 4046 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4047 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4048 for (i=0; i<m; i++) { 4049 c->imax[i] = a->imax[i]; 4050 c->ilen[i] = a->ilen[i]; 4051 } 4052 4053 /* allocate the matrix space */ 4054 if (mallocmatspace) { 4055 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4056 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4057 4058 c->singlemalloc = PETSC_TRUE; 4059 4060 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4061 if (m > 0) { 4062 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4063 if (cpvalues == MAT_COPY_VALUES) { 4064 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4065 } else { 4066 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4067 } 4068 } 4069 } 4070 4071 c->ignorezeroentries = a->ignorezeroentries; 4072 c->roworiented = a->roworiented; 4073 c->nonew = a->nonew; 4074 if (a->diag) { 4075 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4076 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4077 for (i=0; i<m; i++) { 4078 c->diag[i] = a->diag[i]; 4079 } 4080 } else c->diag = 0; 4081 4082 c->solve_work = 0; 4083 c->saved_values = 0; 4084 c->idiag = 0; 4085 c->ssor_work = 0; 4086 c->keepnonzeropattern = a->keepnonzeropattern; 4087 c->free_a = PETSC_TRUE; 4088 c->free_ij = PETSC_TRUE; 4089 4090 c->rmax = a->rmax; 4091 c->nz = a->nz; 4092 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4093 C->preallocated = PETSC_TRUE; 4094 4095 c->compressedrow.use = a->compressedrow.use; 4096 c->compressedrow.nrows = a->compressedrow.nrows; 4097 if (a->compressedrow.use) { 4098 i = a->compressedrow.nrows; 4099 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4100 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4101 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4102 } else { 4103 c->compressedrow.use = PETSC_FALSE; 4104 c->compressedrow.i = NULL; 4105 c->compressedrow.rindex = NULL; 4106 } 4107 c->nonzerorowcnt = a->nonzerorowcnt; 4108 C->nonzerostate = A->nonzerostate; 4109 4110 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4111 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4112 PetscFunctionReturn(0); 4113 } 4114 4115 #undef __FUNCT__ 4116 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4117 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4118 { 4119 PetscErrorCode ierr; 4120 4121 PetscFunctionBegin; 4122 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4123 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4124 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4125 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4126 } 4127 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4128 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4129 PetscFunctionReturn(0); 4130 } 4131 4132 #undef __FUNCT__ 4133 #define __FUNCT__ "MatLoad_SeqAIJ" 4134 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4135 { 4136 Mat_SeqAIJ *a; 4137 PetscErrorCode ierr; 4138 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4139 int fd; 4140 PetscMPIInt size; 4141 MPI_Comm comm; 4142 PetscInt bs = newMat->rmap->bs; 4143 4144 PetscFunctionBegin; 4145 /* force binary viewer to load .info file if it has not yet done so */ 4146 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4147 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4148 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4149 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4150 4151 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4152 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4153 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4154 if (bs < 0) bs = 1; 4155 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4156 4157 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4158 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4159 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4160 M = header[1]; N = header[2]; nz = header[3]; 4161 4162 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4163 4164 /* read in row lengths */ 4165 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4166 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4167 4168 /* check if sum of rowlengths is same as nz */ 4169 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4170 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); 4171 4172 /* set global size if not set already*/ 4173 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4174 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4175 } else { 4176 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4177 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4178 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4179 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4180 } 4181 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); 4182 } 4183 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4184 a = (Mat_SeqAIJ*)newMat->data; 4185 4186 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4187 4188 /* read in nonzero values */ 4189 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4190 4191 /* set matrix "i" values */ 4192 a->i[0] = 0; 4193 for (i=1; i<= M; i++) { 4194 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4195 a->ilen[i-1] = rowlengths[i-1]; 4196 } 4197 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4198 4199 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4200 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4201 PetscFunctionReturn(0); 4202 } 4203 4204 #undef __FUNCT__ 4205 #define __FUNCT__ "MatEqual_SeqAIJ" 4206 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4207 { 4208 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4209 PetscErrorCode ierr; 4210 #if defined(PETSC_USE_COMPLEX) 4211 PetscInt k; 4212 #endif 4213 4214 PetscFunctionBegin; 4215 /* If the matrix dimensions are not equal,or no of nonzeros */ 4216 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4217 *flg = PETSC_FALSE; 4218 PetscFunctionReturn(0); 4219 } 4220 4221 /* if the a->i are the same */ 4222 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4223 if (!*flg) PetscFunctionReturn(0); 4224 4225 /* if a->j are the same */ 4226 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4227 if (!*flg) PetscFunctionReturn(0); 4228 4229 /* if a->a are the same */ 4230 #if defined(PETSC_USE_COMPLEX) 4231 for (k=0; k<a->nz; k++) { 4232 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4233 *flg = PETSC_FALSE; 4234 PetscFunctionReturn(0); 4235 } 4236 } 4237 #else 4238 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4239 #endif 4240 PetscFunctionReturn(0); 4241 } 4242 4243 #undef __FUNCT__ 4244 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4245 /*@ 4246 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4247 provided by the user. 4248 4249 Collective on MPI_Comm 4250 4251 Input Parameters: 4252 + comm - must be an MPI communicator of size 1 4253 . m - number of rows 4254 . n - number of columns 4255 . i - row indices 4256 . j - column indices 4257 - a - matrix values 4258 4259 Output Parameter: 4260 . mat - the matrix 4261 4262 Level: intermediate 4263 4264 Notes: 4265 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4266 once the matrix is destroyed and not before 4267 4268 You cannot set new nonzero locations into this matrix, that will generate an error. 4269 4270 The i and j indices are 0 based 4271 4272 The format which is used for the sparse matrix input, is equivalent to a 4273 row-major ordering.. i.e for the following matrix, the input data expected is 4274 as shown 4275 4276 $ 1 0 0 4277 $ 2 0 3 4278 $ 4 5 6 4279 $ 4280 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4281 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4282 $ v = {1,2,3,4,5,6} [size = 6] 4283 4284 4285 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4286 4287 @*/ 4288 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4289 { 4290 PetscErrorCode ierr; 4291 PetscInt ii; 4292 Mat_SeqAIJ *aij; 4293 #if defined(PETSC_USE_DEBUG) 4294 PetscInt jj; 4295 #endif 4296 4297 PetscFunctionBegin; 4298 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4299 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4300 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4301 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4302 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4303 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4304 aij = (Mat_SeqAIJ*)(*mat)->data; 4305 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4306 4307 aij->i = i; 4308 aij->j = j; 4309 aij->a = a; 4310 aij->singlemalloc = PETSC_FALSE; 4311 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4312 aij->free_a = PETSC_FALSE; 4313 aij->free_ij = PETSC_FALSE; 4314 4315 for (ii=0; ii<m; ii++) { 4316 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4317 #if defined(PETSC_USE_DEBUG) 4318 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]); 4319 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4320 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); 4321 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); 4322 } 4323 #endif 4324 } 4325 #if defined(PETSC_USE_DEBUG) 4326 for (ii=0; ii<aij->i[m]; ii++) { 4327 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4328 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]); 4329 } 4330 #endif 4331 4332 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4333 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4334 PetscFunctionReturn(0); 4335 } 4336 #undef __FUNCT__ 4337 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4338 /*@C 4339 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4340 provided by the user. 4341 4342 Collective on MPI_Comm 4343 4344 Input Parameters: 4345 + comm - must be an MPI communicator of size 1 4346 . m - number of rows 4347 . n - number of columns 4348 . i - row indices 4349 . j - column indices 4350 . a - matrix values 4351 . nz - number of nonzeros 4352 - idx - 0 or 1 based 4353 4354 Output Parameter: 4355 . mat - the matrix 4356 4357 Level: intermediate 4358 4359 Notes: 4360 The i and j indices are 0 based 4361 4362 The format which is used for the sparse matrix input, is equivalent to a 4363 row-major ordering.. i.e for the following matrix, the input data expected is 4364 as shown: 4365 4366 1 0 0 4367 2 0 3 4368 4 5 6 4369 4370 i = {0,1,1,2,2,2} 4371 j = {0,0,2,0,1,2} 4372 v = {1,2,3,4,5,6} 4373 4374 4375 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4376 4377 @*/ 4378 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4379 { 4380 PetscErrorCode ierr; 4381 PetscInt ii, *nnz, one = 1,row,col; 4382 4383 4384 PetscFunctionBegin; 4385 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4386 for (ii = 0; ii < nz; ii++) { 4387 nnz[i[ii] - !!idx] += 1; 4388 } 4389 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4390 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4391 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4392 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4393 for (ii = 0; ii < nz; ii++) { 4394 if (idx) { 4395 row = i[ii] - 1; 4396 col = j[ii] - 1; 4397 } else { 4398 row = i[ii]; 4399 col = j[ii]; 4400 } 4401 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4402 } 4403 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4404 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4405 ierr = PetscFree(nnz);CHKERRQ(ierr); 4406 PetscFunctionReturn(0); 4407 } 4408 4409 #undef __FUNCT__ 4410 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4411 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4412 { 4413 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4414 PetscErrorCode ierr; 4415 4416 PetscFunctionBegin; 4417 a->idiagvalid = PETSC_FALSE; 4418 a->ibdiagvalid = PETSC_FALSE; 4419 4420 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4421 PetscFunctionReturn(0); 4422 } 4423 4424 #undef __FUNCT__ 4425 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_SeqAIJ" 4426 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4427 { 4428 PetscErrorCode ierr; 4429 4430 PetscFunctionBegin; 4431 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4432 PetscFunctionReturn(0); 4433 } 4434 4435 /* 4436 Permute A into C's *local* index space using rowemb,colemb. 4437 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4438 of [0,m), colemb is in [0,n). 4439 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4440 */ 4441 #undef __FUNCT__ 4442 #define __FUNCT__ "MatSetSeqMat_SeqAIJ" 4443 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4444 { 4445 /* If making this function public, change the error returned in this function away from _PLIB. */ 4446 PetscErrorCode ierr; 4447 Mat_SeqAIJ *Baij; 4448 PetscBool seqaij; 4449 PetscInt m,n,*nz,i,j,count; 4450 PetscScalar v; 4451 const PetscInt *rowindices,*colindices; 4452 4453 PetscFunctionBegin; 4454 if (!B) PetscFunctionReturn(0); 4455 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4456 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4457 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4458 if (rowemb) { 4459 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4460 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); 4461 } else { 4462 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4463 } 4464 if (colemb) { 4465 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4466 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); 4467 } else { 4468 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4469 } 4470 4471 Baij = (Mat_SeqAIJ*)(B->data); 4472 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4473 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4474 for (i=0; i<B->rmap->n; i++) { 4475 nz[i] = Baij->i[i+1] - Baij->i[i]; 4476 } 4477 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4478 ierr = PetscFree(nz);CHKERRQ(ierr); 4479 } 4480 if (pattern == SUBSET_NONZERO_PATTERN) { 4481 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4482 } 4483 count = 0; 4484 rowindices = NULL; 4485 colindices = NULL; 4486 if (rowemb) { 4487 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4488 } 4489 if (colemb) { 4490 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4491 } 4492 for (i=0; i<B->rmap->n; i++) { 4493 PetscInt row; 4494 row = i; 4495 if (rowindices) row = rowindices[i]; 4496 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4497 PetscInt col; 4498 col = Baij->j[count]; 4499 if (colindices) col = colindices[col]; 4500 v = Baij->a[count]; 4501 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4502 ++count; 4503 } 4504 } 4505 /* FIXME: set C's nonzerostate correctly. */ 4506 /* Assembly for C is necessary. */ 4507 C->preallocated = PETSC_TRUE; 4508 C->assembled = PETSC_TRUE; 4509 C->was_assembled = PETSC_FALSE; 4510 PetscFunctionReturn(0); 4511 } 4512 4513 4514 /* 4515 Special version for direct calls from Fortran 4516 */ 4517 #include <petsc/private/fortranimpl.h> 4518 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4519 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4520 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4521 #define matsetvaluesseqaij_ matsetvaluesseqaij 4522 #endif 4523 4524 /* Change these macros so can be used in void function */ 4525 #undef CHKERRQ 4526 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4527 #undef SETERRQ2 4528 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4529 #undef SETERRQ3 4530 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4531 4532 #undef __FUNCT__ 4533 #define __FUNCT__ "matsetvaluesseqaij_" 4534 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) 4535 { 4536 Mat A = *AA; 4537 PetscInt m = *mm, n = *nn; 4538 InsertMode is = *isis; 4539 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4540 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4541 PetscInt *imax,*ai,*ailen; 4542 PetscErrorCode ierr; 4543 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4544 MatScalar *ap,value,*aa; 4545 PetscBool ignorezeroentries = a->ignorezeroentries; 4546 PetscBool roworiented = a->roworiented; 4547 4548 PetscFunctionBegin; 4549 MatCheckPreallocated(A,1); 4550 imax = a->imax; 4551 ai = a->i; 4552 ailen = a->ilen; 4553 aj = a->j; 4554 aa = a->a; 4555 4556 for (k=0; k<m; k++) { /* loop over added rows */ 4557 row = im[k]; 4558 if (row < 0) continue; 4559 #if defined(PETSC_USE_DEBUG) 4560 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4561 #endif 4562 rp = aj + ai[row]; ap = aa + ai[row]; 4563 rmax = imax[row]; nrow = ailen[row]; 4564 low = 0; 4565 high = nrow; 4566 for (l=0; l<n; l++) { /* loop over added columns */ 4567 if (in[l] < 0) continue; 4568 #if defined(PETSC_USE_DEBUG) 4569 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4570 #endif 4571 col = in[l]; 4572 if (roworiented) value = v[l + k*n]; 4573 else value = v[k + l*m]; 4574 4575 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4576 4577 if (col <= lastcol) low = 0; 4578 else high = nrow; 4579 lastcol = col; 4580 while (high-low > 5) { 4581 t = (low+high)/2; 4582 if (rp[t] > col) high = t; 4583 else low = t; 4584 } 4585 for (i=low; i<high; i++) { 4586 if (rp[i] > col) break; 4587 if (rp[i] == col) { 4588 if (is == ADD_VALUES) ap[i] += value; 4589 else ap[i] = value; 4590 goto noinsert; 4591 } 4592 } 4593 if (value == 0.0 && ignorezeroentries) goto noinsert; 4594 if (nonew == 1) goto noinsert; 4595 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4596 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4597 N = nrow++ - 1; a->nz++; high++; 4598 /* shift up all the later entries in this row */ 4599 for (ii=N; ii>=i; ii--) { 4600 rp[ii+1] = rp[ii]; 4601 ap[ii+1] = ap[ii]; 4602 } 4603 rp[i] = col; 4604 ap[i] = value; 4605 A->nonzerostate++; 4606 noinsert:; 4607 low = i + 1; 4608 } 4609 ailen[row] = nrow; 4610 } 4611 PetscFunctionReturnVoid(); 4612 } 4613 4614