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 #if defined(PETSC_THREADCOMM_ACTIVE) 13 #include <petscthreadcomm.h> 14 #endif 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetColumnNorms_SeqAIJ" 18 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 19 { 20 PetscErrorCode ierr; 21 PetscInt i,m,n; 22 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 23 24 PetscFunctionBegin; 25 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 26 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 27 if (type == NORM_2) { 28 for (i=0; i<aij->i[m]; i++) { 29 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 30 } 31 } else if (type == NORM_1) { 32 for (i=0; i<aij->i[m]; i++) { 33 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 34 } 35 } else if (type == NORM_INFINITY) { 36 for (i=0; i<aij->i[m]; i++) { 37 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 38 } 39 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 40 41 if (type == NORM_2) { 42 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 43 } 44 PetscFunctionReturn(0); 45 } 46 47 #undef __FUNCT__ 48 #define __FUNCT__ "MatFindOffBlockDiagonalEntries_SeqAIJ" 49 PetscErrorCode MatFindOffBlockDiagonalEntries_SeqAIJ(Mat A,IS *is) 50 { 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 52 PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; 53 const PetscInt *jj = a->j,*ii = a->i; 54 PetscInt *rows; 55 PetscErrorCode ierr; 56 57 PetscFunctionBegin; 58 for (i=0; i<m; i++) { 59 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 60 cnt++; 61 } 62 } 63 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 64 cnt = 0; 65 for (i=0; i<m; i++) { 66 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 67 rows[cnt] = i; 68 cnt++; 69 } 70 } 71 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 72 PetscFunctionReturn(0); 73 } 74 75 #undef __FUNCT__ 76 #define __FUNCT__ "MatFindZeroDiagonals_SeqAIJ_Private" 77 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 78 { 79 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 80 const MatScalar *aa = a->a; 81 PetscInt i,m=A->rmap->n,cnt = 0; 82 const PetscInt *jj = a->j,*diag; 83 PetscInt *rows; 84 PetscErrorCode ierr; 85 86 PetscFunctionBegin; 87 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 88 diag = a->diag; 89 for (i=0; i<m; i++) { 90 if ((jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 91 cnt++; 92 } 93 } 94 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 95 cnt = 0; 96 for (i=0; i<m; i++) { 97 if ((jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 98 rows[cnt++] = i; 99 } 100 } 101 *nrows = cnt; 102 *zrows = rows; 103 PetscFunctionReturn(0); 104 } 105 106 #undef __FUNCT__ 107 #define __FUNCT__ "MatFindZeroDiagonals_SeqAIJ" 108 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 109 { 110 PetscInt nrows,*rows; 111 PetscErrorCode ierr; 112 113 PetscFunctionBegin; 114 *zrows = NULL; 115 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 116 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 117 PetscFunctionReturn(0); 118 } 119 120 #undef __FUNCT__ 121 #define __FUNCT__ "MatFindNonzeroRows_SeqAIJ" 122 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 123 { 124 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 125 const MatScalar *aa; 126 PetscInt m=A->rmap->n,cnt = 0; 127 const PetscInt *ii; 128 PetscInt n,i,j,*rows; 129 PetscErrorCode ierr; 130 131 PetscFunctionBegin; 132 *keptrows = 0; 133 ii = a->i; 134 for (i=0; i<m; i++) { 135 n = ii[i+1] - ii[i]; 136 if (!n) { 137 cnt++; 138 goto ok1; 139 } 140 aa = a->a + ii[i]; 141 for (j=0; j<n; j++) { 142 if (aa[j] != 0.0) goto ok1; 143 } 144 cnt++; 145 ok1:; 146 } 147 if (!cnt) PetscFunctionReturn(0); 148 ierr = PetscMalloc1((A->rmap->n-cnt),&rows);CHKERRQ(ierr); 149 cnt = 0; 150 for (i=0; i<m; i++) { 151 n = ii[i+1] - ii[i]; 152 if (!n) continue; 153 aa = a->a + ii[i]; 154 for (j=0; j<n; j++) { 155 if (aa[j] != 0.0) { 156 rows[cnt++] = i; 157 break; 158 } 159 } 160 } 161 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 162 PetscFunctionReturn(0); 163 } 164 165 #undef __FUNCT__ 166 #define __FUNCT__ "MatDiagonalSet_SeqAIJ" 167 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 168 { 169 PetscErrorCode ierr; 170 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 171 PetscInt i,*diag, m = Y->rmap->n; 172 MatScalar *aa = aij->a; 173 PetscScalar *v; 174 PetscBool missing; 175 176 PetscFunctionBegin; 177 if (Y->assembled) { 178 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 179 if (!missing) { 180 diag = aij->diag; 181 ierr = VecGetArray(D,&v);CHKERRQ(ierr); 182 if (is == INSERT_VALUES) { 183 for (i=0; i<m; i++) { 184 aa[diag[i]] = v[i]; 185 } 186 } else { 187 for (i=0; i<m; i++) { 188 aa[diag[i]] += v[i]; 189 } 190 } 191 ierr = VecRestoreArray(D,&v);CHKERRQ(ierr); 192 PetscFunctionReturn(0); 193 } 194 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 195 } 196 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 197 PetscFunctionReturn(0); 198 } 199 200 #undef __FUNCT__ 201 #define __FUNCT__ "MatGetRowIJ_SeqAIJ" 202 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 203 { 204 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 205 PetscErrorCode ierr; 206 PetscInt i,ishift; 207 208 PetscFunctionBegin; 209 *m = A->rmap->n; 210 if (!ia) PetscFunctionReturn(0); 211 ishift = 0; 212 if (symmetric && !A->structurally_symmetric) { 213 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 214 } else if (oshift == 1) { 215 PetscInt *tia; 216 PetscInt nz = a->i[A->rmap->n]; 217 /* malloc space and add 1 to i and j indices */ 218 ierr = PetscMalloc1((A->rmap->n+1),&tia);CHKERRQ(ierr); 219 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 220 *ia = tia; 221 if (ja) { 222 PetscInt *tja; 223 ierr = PetscMalloc1((nz+1),&tja);CHKERRQ(ierr); 224 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 225 *ja = tja; 226 } 227 } else { 228 *ia = a->i; 229 if (ja) *ja = a->j; 230 } 231 PetscFunctionReturn(0); 232 } 233 234 #undef __FUNCT__ 235 #define __FUNCT__ "MatRestoreRowIJ_SeqAIJ" 236 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 237 { 238 PetscErrorCode ierr; 239 240 PetscFunctionBegin; 241 if (!ia) PetscFunctionReturn(0); 242 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 243 ierr = PetscFree(*ia);CHKERRQ(ierr); 244 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 245 } 246 PetscFunctionReturn(0); 247 } 248 249 #undef __FUNCT__ 250 #define __FUNCT__ "MatGetColumnIJ_SeqAIJ" 251 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 252 { 253 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 254 PetscErrorCode ierr; 255 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 256 PetscInt nz = a->i[m],row,*jj,mr,col; 257 258 PetscFunctionBegin; 259 *nn = n; 260 if (!ia) PetscFunctionReturn(0); 261 if (symmetric) { 262 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 263 } else { 264 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 265 ierr = PetscMalloc1((n+1),&cia);CHKERRQ(ierr); 266 ierr = PetscMalloc1((nz+1),&cja);CHKERRQ(ierr); 267 jj = a->j; 268 for (i=0; i<nz; i++) { 269 collengths[jj[i]]++; 270 } 271 cia[0] = oshift; 272 for (i=0; i<n; i++) { 273 cia[i+1] = cia[i] + collengths[i]; 274 } 275 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 276 jj = a->j; 277 for (row=0; row<m; row++) { 278 mr = a->i[row+1] - a->i[row]; 279 for (i=0; i<mr; i++) { 280 col = *jj++; 281 282 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 283 } 284 } 285 ierr = PetscFree(collengths);CHKERRQ(ierr); 286 *ia = cia; *ja = cja; 287 } 288 PetscFunctionReturn(0); 289 } 290 291 #undef __FUNCT__ 292 #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ" 293 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 294 { 295 PetscErrorCode ierr; 296 297 PetscFunctionBegin; 298 if (!ia) PetscFunctionReturn(0); 299 300 ierr = PetscFree(*ia);CHKERRQ(ierr); 301 ierr = PetscFree(*ja);CHKERRQ(ierr); 302 PetscFunctionReturn(0); 303 } 304 305 /* 306 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 307 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 308 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() 309 */ 310 #undef __FUNCT__ 311 #define __FUNCT__ "MatGetColumnIJ_SeqAIJ_Color" 312 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 313 { 314 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 315 PetscErrorCode ierr; 316 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 317 PetscInt nz = a->i[m],row,*jj,mr,col; 318 PetscInt *cspidx; 319 320 PetscFunctionBegin; 321 *nn = n; 322 if (!ia) PetscFunctionReturn(0); 323 324 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 325 ierr = PetscMalloc1((n+1),&cia);CHKERRQ(ierr); 326 ierr = PetscMalloc1((nz+1),&cja);CHKERRQ(ierr); 327 ierr = PetscMalloc1((nz+1),&cspidx);CHKERRQ(ierr); 328 jj = a->j; 329 for (i=0; i<nz; i++) { 330 collengths[jj[i]]++; 331 } 332 cia[0] = oshift; 333 for (i=0; i<n; i++) { 334 cia[i+1] = cia[i] + collengths[i]; 335 } 336 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 337 jj = a->j; 338 for (row=0; row<m; row++) { 339 mr = a->i[row+1] - a->i[row]; 340 for (i=0; i<mr; i++) { 341 col = *jj++; 342 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 343 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 344 } 345 } 346 ierr = PetscFree(collengths);CHKERRQ(ierr); 347 *ia = cia; *ja = cja; 348 *spidx = cspidx; 349 PetscFunctionReturn(0); 350 } 351 352 #undef __FUNCT__ 353 #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ_Color" 354 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 355 { 356 PetscErrorCode ierr; 357 358 PetscFunctionBegin; 359 ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 360 ierr = PetscFree(*spidx);CHKERRQ(ierr); 361 PetscFunctionReturn(0); 362 } 363 364 #undef __FUNCT__ 365 #define __FUNCT__ "MatSetValuesRow_SeqAIJ" 366 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 367 { 368 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 369 PetscInt *ai = a->i; 370 PetscErrorCode ierr; 371 372 PetscFunctionBegin; 373 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 374 PetscFunctionReturn(0); 375 } 376 377 /* 378 MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions 379 380 - a single row of values is set with each call 381 - no row or column indices are negative or (in error) larger than the number of rows or columns 382 - the values are always added to the matrix, not set 383 - no new locations are introduced in the nonzero structure of the matrix 384 385 This does NOT assume the global column indices are sorted 386 387 */ 388 389 #include <petsc-private/isimpl.h> 390 #undef __FUNCT__ 391 #define __FUNCT__ "MatSeqAIJSetValuesLocalFast" 392 PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 393 { 394 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 395 PetscInt low,high,t,row,nrow,i,col,l; 396 const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; 397 PetscInt lastcol = -1; 398 MatScalar *ap,value,*aa = a->a; 399 const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; 400 401 row = ridx[im[0]]; 402 rp = aj + ai[row]; 403 ap = aa + ai[row]; 404 nrow = ailen[row]; 405 low = 0; 406 high = nrow; 407 for (l=0; l<n; l++) { /* loop over added columns */ 408 col = cidx[in[l]]; 409 value = v[l]; 410 411 if (col <= lastcol) low = 0; 412 else high = nrow; 413 lastcol = col; 414 while (high-low > 5) { 415 t = (low+high)/2; 416 if (rp[t] > col) high = t; 417 else low = t; 418 } 419 for (i=low; i<high; i++) { 420 if (rp[i] == col) { 421 ap[i] += value; 422 low = i + 1; 423 break; 424 } 425 } 426 } 427 return 0; 428 } 429 430 #undef __FUNCT__ 431 #define __FUNCT__ "MatSetValues_SeqAIJ" 432 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 433 { 434 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 435 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 436 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 437 PetscErrorCode ierr; 438 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 439 MatScalar *ap,value,*aa = a->a; 440 PetscBool ignorezeroentries = a->ignorezeroentries; 441 PetscBool roworiented = a->roworiented; 442 443 PetscFunctionBegin; 444 for (k=0; k<m; k++) { /* loop over added rows */ 445 row = im[k]; 446 if (row < 0) continue; 447 #if defined(PETSC_USE_DEBUG) 448 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); 449 #endif 450 rp = aj + ai[row]; ap = aa + ai[row]; 451 rmax = imax[row]; nrow = ailen[row]; 452 low = 0; 453 high = nrow; 454 for (l=0; l<n; l++) { /* loop over added columns */ 455 if (in[l] < 0) continue; 456 #if defined(PETSC_USE_DEBUG) 457 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); 458 #endif 459 col = in[l]; 460 if (roworiented) { 461 value = v[l + k*n]; 462 } else { 463 value = v[k + l*m]; 464 } 465 if ((value == 0.0 && ignorezeroentries) && (is == ADD_VALUES)) continue; 466 467 if (col <= lastcol) low = 0; 468 else high = nrow; 469 lastcol = col; 470 while (high-low > 5) { 471 t = (low+high)/2; 472 if (rp[t] > col) high = t; 473 else low = t; 474 } 475 for (i=low; i<high; i++) { 476 if (rp[i] > col) break; 477 if (rp[i] == col) { 478 if (is == ADD_VALUES) ap[i] += value; 479 else ap[i] = value; 480 low = i + 1; 481 goto noinsert; 482 } 483 } 484 if (value == 0.0 && ignorezeroentries) goto noinsert; 485 if (nonew == 1) goto noinsert; 486 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 487 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 488 N = nrow++ - 1; a->nz++; high++; 489 /* shift up all the later entries in this row */ 490 for (ii=N; ii>=i; ii--) { 491 rp[ii+1] = rp[ii]; 492 ap[ii+1] = ap[ii]; 493 } 494 rp[i] = col; 495 ap[i] = value; 496 low = i + 1; 497 A->nonzerostate++; 498 noinsert:; 499 } 500 ailen[row] = nrow; 501 } 502 PetscFunctionReturn(0); 503 } 504 505 506 #undef __FUNCT__ 507 #define __FUNCT__ "MatGetValues_SeqAIJ" 508 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 509 { 510 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 511 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 512 PetscInt *ai = a->i,*ailen = a->ilen; 513 MatScalar *ap,*aa = a->a; 514 515 PetscFunctionBegin; 516 for (k=0; k<m; k++) { /* loop over rows */ 517 row = im[k]; 518 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 519 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); 520 rp = aj + ai[row]; ap = aa + ai[row]; 521 nrow = ailen[row]; 522 for (l=0; l<n; l++) { /* loop over columns */ 523 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 524 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); 525 col = in[l]; 526 high = nrow; low = 0; /* assume unsorted */ 527 while (high-low > 5) { 528 t = (low+high)/2; 529 if (rp[t] > col) high = t; 530 else low = t; 531 } 532 for (i=low; i<high; i++) { 533 if (rp[i] > col) break; 534 if (rp[i] == col) { 535 *v++ = ap[i]; 536 goto finished; 537 } 538 } 539 *v++ = 0.0; 540 finished:; 541 } 542 } 543 PetscFunctionReturn(0); 544 } 545 546 547 #undef __FUNCT__ 548 #define __FUNCT__ "MatView_SeqAIJ_Binary" 549 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 550 { 551 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 552 PetscErrorCode ierr; 553 PetscInt i,*col_lens; 554 int fd; 555 FILE *file; 556 557 PetscFunctionBegin; 558 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 559 ierr = PetscMalloc1((4+A->rmap->n),&col_lens);CHKERRQ(ierr); 560 561 col_lens[0] = MAT_FILE_CLASSID; 562 col_lens[1] = A->rmap->n; 563 col_lens[2] = A->cmap->n; 564 col_lens[3] = a->nz; 565 566 /* store lengths of each row and write (including header) to file */ 567 for (i=0; i<A->rmap->n; i++) { 568 col_lens[4+i] = a->i[i+1] - a->i[i]; 569 } 570 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 571 ierr = PetscFree(col_lens);CHKERRQ(ierr); 572 573 /* store column indices (zero start index) */ 574 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 575 576 /* store nonzero values */ 577 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 578 579 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 580 if (file) { 581 fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); 582 } 583 PetscFunctionReturn(0); 584 } 585 586 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 587 588 #undef __FUNCT__ 589 #define __FUNCT__ "MatView_SeqAIJ_ASCII" 590 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 591 { 592 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 593 PetscErrorCode ierr; 594 PetscInt i,j,m = A->rmap->n; 595 const char *name; 596 PetscViewerFormat format; 597 598 PetscFunctionBegin; 599 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 600 if (format == PETSC_VIEWER_ASCII_MATLAB) { 601 PetscInt nofinalvalue = 0; 602 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 603 /* Need a dummy value to ensure the dimension of the matrix. */ 604 nofinalvalue = 1; 605 } 606 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 607 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 608 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 609 #if defined(PETSC_USE_COMPLEX) 610 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 611 #else 612 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 613 #endif 614 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 615 616 for (i=0; i<m; i++) { 617 for (j=a->i[i]; j<a->i[i+1]; j++) { 618 #if defined(PETSC_USE_COMPLEX) 619 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); 620 #else 621 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 622 #endif 623 } 624 } 625 if (nofinalvalue) { 626 #if defined(PETSC_USE_COMPLEX) 627 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 628 #else 629 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 630 #endif 631 } 632 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 633 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 634 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 635 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 636 PetscFunctionReturn(0); 637 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 638 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 639 for (i=0; i<m; i++) { 640 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 641 for (j=a->i[i]; j<a->i[i+1]; j++) { 642 #if defined(PETSC_USE_COMPLEX) 643 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 (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 646 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 647 } else if (PetscRealPart(a->a[j]) != 0.0) { 648 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 649 } 650 #else 651 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 652 #endif 653 } 654 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 655 } 656 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 657 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 658 PetscInt nzd=0,fshift=1,*sptr; 659 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 660 ierr = PetscMalloc1((m+1),&sptr);CHKERRQ(ierr); 661 for (i=0; i<m; i++) { 662 sptr[i] = nzd+1; 663 for (j=a->i[i]; j<a->i[i+1]; j++) { 664 if (a->j[j] >= i) { 665 #if defined(PETSC_USE_COMPLEX) 666 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 667 #else 668 if (a->a[j] != 0.0) nzd++; 669 #endif 670 } 671 } 672 } 673 sptr[m] = nzd+1; 674 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 675 for (i=0; i<m+1; i+=6) { 676 if (i+4<m) { 677 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); 678 } else if (i+3<m) { 679 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); 680 } else if (i+2<m) { 681 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 682 } else if (i+1<m) { 683 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 684 } else if (i<m) { 685 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 686 } else { 687 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 688 } 689 } 690 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 691 ierr = PetscFree(sptr);CHKERRQ(ierr); 692 for (i=0; i<m; i++) { 693 for (j=a->i[i]; j<a->i[i+1]; j++) { 694 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 695 } 696 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 697 } 698 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 699 for (i=0; i<m; i++) { 700 for (j=a->i[i]; j<a->i[i+1]; j++) { 701 if (a->j[j] >= i) { 702 #if defined(PETSC_USE_COMPLEX) 703 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 704 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 705 } 706 #else 707 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 708 #endif 709 } 710 } 711 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 712 } 713 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 714 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 715 PetscInt cnt = 0,jcnt; 716 PetscScalar value; 717 #if defined(PETSC_USE_COMPLEX) 718 PetscBool realonly = PETSC_TRUE; 719 720 for (i=0; i<a->i[m]; i++) { 721 if (PetscImaginaryPart(a->a[i]) != 0.0) { 722 realonly = PETSC_FALSE; 723 break; 724 } 725 } 726 #endif 727 728 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 729 for (i=0; i<m; i++) { 730 jcnt = 0; 731 for (j=0; j<A->cmap->n; j++) { 732 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 733 value = a->a[cnt++]; 734 jcnt++; 735 } else { 736 value = 0.0; 737 } 738 #if defined(PETSC_USE_COMPLEX) 739 if (realonly) { 740 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 741 } else { 742 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 743 } 744 #else 745 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 746 #endif 747 } 748 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 749 } 750 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 751 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 752 PetscInt fshift=1; 753 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 754 #if defined(PETSC_USE_COMPLEX) 755 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix complex general\n");CHKERRQ(ierr); 756 #else 757 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix real general\n");CHKERRQ(ierr); 758 #endif 759 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 760 for (i=0; i<m; i++) { 761 for (j=a->i[i]; j<a->i[i+1]; j++) { 762 #if defined(PETSC_USE_COMPLEX) 763 if (PetscImaginaryPart(a->a[j]) > 0.0) { 764 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); 765 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 766 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); 767 } else { 768 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 769 } 770 #else 771 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 772 #endif 773 } 774 } 775 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 776 } else { 777 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 778 if (A->factortype) { 779 for (i=0; i<m; i++) { 780 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 781 /* L part */ 782 for (j=a->i[i]; j<a->i[i+1]; j++) { 783 #if defined(PETSC_USE_COMPLEX) 784 if (PetscImaginaryPart(a->a[j]) > 0.0) { 785 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 786 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 787 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 788 } else { 789 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 790 } 791 #else 792 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 793 #endif 794 } 795 /* diagonal */ 796 j = a->diag[i]; 797 #if defined(PETSC_USE_COMPLEX) 798 if (PetscImaginaryPart(a->a[j]) > 0.0) { 799 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); 800 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 801 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); 802 } else { 803 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 804 } 805 #else 806 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 807 #endif 808 809 /* U part */ 810 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 811 #if defined(PETSC_USE_COMPLEX) 812 if (PetscImaginaryPart(a->a[j]) > 0.0) { 813 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 814 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 815 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 816 } else { 817 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 818 } 819 #else 820 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 821 #endif 822 } 823 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 824 } 825 } else { 826 for (i=0; i<m; i++) { 827 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 828 for (j=a->i[i]; j<a->i[i+1]; j++) { 829 #if defined(PETSC_USE_COMPLEX) 830 if (PetscImaginaryPart(a->a[j]) > 0.0) { 831 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 832 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 833 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 834 } else { 835 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 836 } 837 #else 838 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 839 #endif 840 } 841 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 842 } 843 } 844 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 845 } 846 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 847 PetscFunctionReturn(0); 848 } 849 850 #include <petscdraw.h> 851 #undef __FUNCT__ 852 #define __FUNCT__ "MatView_SeqAIJ_Draw_Zoom" 853 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 854 { 855 Mat A = (Mat) Aa; 856 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 857 PetscErrorCode ierr; 858 PetscInt i,j,m = A->rmap->n,color; 859 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r,maxv = 0.0; 860 PetscViewer viewer; 861 PetscViewerFormat format; 862 863 PetscFunctionBegin; 864 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 865 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 866 867 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 868 /* loop over matrix elements drawing boxes */ 869 870 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 871 /* Blue for negative, Cyan for zero and Red for positive */ 872 color = PETSC_DRAW_BLUE; 873 for (i=0; i<m; i++) { 874 y_l = m - i - 1.0; y_r = y_l + 1.0; 875 for (j=a->i[i]; j<a->i[i+1]; j++) { 876 x_l = a->j[j]; x_r = x_l + 1.0; 877 if (PetscRealPart(a->a[j]) >= 0.) continue; 878 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 879 } 880 } 881 color = PETSC_DRAW_CYAN; 882 for (i=0; i<m; i++) { 883 y_l = m - i - 1.0; y_r = y_l + 1.0; 884 for (j=a->i[i]; j<a->i[i+1]; j++) { 885 x_l = a->j[j]; x_r = x_l + 1.0; 886 if (a->a[j] != 0.) continue; 887 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 888 } 889 } 890 color = PETSC_DRAW_RED; 891 for (i=0; i<m; i++) { 892 y_l = m - i - 1.0; y_r = y_l + 1.0; 893 for (j=a->i[i]; j<a->i[i+1]; j++) { 894 x_l = a->j[j]; x_r = x_l + 1.0; 895 if (PetscRealPart(a->a[j]) <= 0.) continue; 896 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 897 } 898 } 899 } else { 900 /* use contour shading to indicate magnitude of values */ 901 /* first determine max of all nonzero values */ 902 PetscInt nz = a->nz,count; 903 PetscDraw popup; 904 PetscReal scale; 905 906 for (i=0; i<nz; i++) { 907 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 908 } 909 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 910 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 911 if (popup) { 912 ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); 913 } 914 count = 0; 915 for (i=0; i<m; i++) { 916 y_l = m - i - 1.0; y_r = y_l + 1.0; 917 for (j=a->i[i]; j<a->i[i+1]; j++) { 918 x_l = a->j[j]; x_r = x_l + 1.0; 919 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(a->a[count])); 920 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 921 count++; 922 } 923 } 924 } 925 PetscFunctionReturn(0); 926 } 927 928 #include <petscdraw.h> 929 #undef __FUNCT__ 930 #define __FUNCT__ "MatView_SeqAIJ_Draw" 931 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 932 { 933 PetscErrorCode ierr; 934 PetscDraw draw; 935 PetscReal xr,yr,xl,yl,h,w; 936 PetscBool isnull; 937 938 PetscFunctionBegin; 939 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 940 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 941 if (isnull) PetscFunctionReturn(0); 942 943 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 944 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 945 xr += w; yr += h; xl = -w; yl = -h; 946 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 947 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 948 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 949 PetscFunctionReturn(0); 950 } 951 952 #undef __FUNCT__ 953 #define __FUNCT__ "MatView_SeqAIJ" 954 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 955 { 956 PetscErrorCode ierr; 957 PetscBool iascii,isbinary,isdraw; 958 959 PetscFunctionBegin; 960 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 961 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 962 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 963 if (iascii) { 964 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 965 } else if (isbinary) { 966 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 967 } else if (isdraw) { 968 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 969 } 970 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 971 PetscFunctionReturn(0); 972 } 973 974 #undef __FUNCT__ 975 #define __FUNCT__ "MatAssemblyEnd_SeqAIJ" 976 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 977 { 978 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 979 PetscErrorCode ierr; 980 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 981 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 982 MatScalar *aa = a->a,*ap; 983 PetscReal ratio = 0.6; 984 985 PetscFunctionBegin; 986 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 987 988 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 989 for (i=1; i<m; i++) { 990 /* move each row back by the amount of empty slots (fshift) before it*/ 991 fshift += imax[i-1] - ailen[i-1]; 992 rmax = PetscMax(rmax,ailen[i]); 993 if (fshift) { 994 ip = aj + ai[i]; 995 ap = aa + ai[i]; 996 N = ailen[i]; 997 for (j=0; j<N; j++) { 998 ip[j-fshift] = ip[j]; 999 ap[j-fshift] = ap[j]; 1000 } 1001 } 1002 ai[i] = ai[i-1] + ailen[i-1]; 1003 } 1004 if (m) { 1005 fshift += imax[m-1] - ailen[m-1]; 1006 ai[m] = ai[m-1] + ailen[m-1]; 1007 } 1008 1009 /* reset ilen and imax for each row */ 1010 a->nonzerorowcnt = 0; 1011 for (i=0; i<m; i++) { 1012 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1013 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1014 } 1015 a->nz = ai[m]; 1016 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); 1017 1018 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1019 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1020 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1021 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1022 1023 A->info.mallocs += a->reallocs; 1024 a->reallocs = 0; 1025 A->info.nz_unneeded = (PetscReal)fshift; 1026 a->rmax = rmax; 1027 1028 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1029 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1030 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1031 PetscFunctionReturn(0); 1032 } 1033 1034 #undef __FUNCT__ 1035 #define __FUNCT__ "MatRealPart_SeqAIJ" 1036 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1037 { 1038 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1039 PetscInt i,nz = a->nz; 1040 MatScalar *aa = a->a; 1041 PetscErrorCode ierr; 1042 1043 PetscFunctionBegin; 1044 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1045 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1046 PetscFunctionReturn(0); 1047 } 1048 1049 #undef __FUNCT__ 1050 #define __FUNCT__ "MatImaginaryPart_SeqAIJ" 1051 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1052 { 1053 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1054 PetscInt i,nz = a->nz; 1055 MatScalar *aa = a->a; 1056 PetscErrorCode ierr; 1057 1058 PetscFunctionBegin; 1059 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1060 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1061 PetscFunctionReturn(0); 1062 } 1063 1064 #if defined(PETSC_THREADCOMM_ACTIVE) 1065 PetscErrorCode MatZeroEntries_SeqAIJ_Kernel(PetscInt thread_id,Mat A) 1066 { 1067 PetscErrorCode ierr; 1068 PetscInt *trstarts=A->rmap->trstarts; 1069 PetscInt n,start,end; 1070 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1071 1072 start = trstarts[thread_id]; 1073 end = trstarts[thread_id+1]; 1074 n = a->i[end] - a->i[start]; 1075 ierr = PetscMemzero(a->a+a->i[start],n*sizeof(PetscScalar));CHKERRQ(ierr); 1076 return 0; 1077 } 1078 1079 #undef __FUNCT__ 1080 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 1081 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1082 { 1083 PetscErrorCode ierr; 1084 1085 PetscFunctionBegin; 1086 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatZeroEntries_SeqAIJ_Kernel,1,A);CHKERRQ(ierr); 1087 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1088 PetscFunctionReturn(0); 1089 } 1090 #else 1091 #undef __FUNCT__ 1092 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 1093 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1094 { 1095 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1096 PetscErrorCode ierr; 1097 1098 PetscFunctionBegin; 1099 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1100 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1101 PetscFunctionReturn(0); 1102 } 1103 #endif 1104 1105 extern PetscErrorCode MatDestroy_Redundant(Mat_Redundant **); 1106 1107 #undef __FUNCT__ 1108 #define __FUNCT__ "MatDestroy_SeqAIJ" 1109 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1110 { 1111 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1112 PetscErrorCode ierr; 1113 1114 PetscFunctionBegin; 1115 #if defined(PETSC_USE_LOG) 1116 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1117 #endif 1118 ierr = MatDestroy_Redundant(&a->redundant);CHKERRQ(ierr); 1119 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1120 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1121 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1122 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1123 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1124 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1125 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1126 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1127 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1128 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1129 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1130 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 1131 ierr = MatDestroy(&a->XtoY);CHKERRQ(ierr); 1132 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1133 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1134 1135 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1136 ierr = PetscFree(A->data);CHKERRQ(ierr); 1137 1138 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1139 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1140 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1141 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1142 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1143 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1144 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1145 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1146 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1147 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1148 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1149 PetscFunctionReturn(0); 1150 } 1151 1152 #undef __FUNCT__ 1153 #define __FUNCT__ "MatSetOption_SeqAIJ" 1154 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1155 { 1156 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1157 PetscErrorCode ierr; 1158 1159 PetscFunctionBegin; 1160 switch (op) { 1161 case MAT_ROW_ORIENTED: 1162 a->roworiented = flg; 1163 break; 1164 case MAT_KEEP_NONZERO_PATTERN: 1165 a->keepnonzeropattern = flg; 1166 break; 1167 case MAT_NEW_NONZERO_LOCATIONS: 1168 a->nonew = (flg ? 0 : 1); 1169 break; 1170 case MAT_NEW_NONZERO_LOCATION_ERR: 1171 a->nonew = (flg ? -1 : 0); 1172 break; 1173 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1174 a->nonew = (flg ? -2 : 0); 1175 break; 1176 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1177 a->nounused = (flg ? -1 : 0); 1178 break; 1179 case MAT_IGNORE_ZERO_ENTRIES: 1180 a->ignorezeroentries = flg; 1181 break; 1182 case MAT_SPD: 1183 case MAT_SYMMETRIC: 1184 case MAT_STRUCTURALLY_SYMMETRIC: 1185 case MAT_HERMITIAN: 1186 case MAT_SYMMETRY_ETERNAL: 1187 /* These options are handled directly by MatSetOption() */ 1188 break; 1189 case MAT_NEW_DIAGONALS: 1190 case MAT_IGNORE_OFF_PROC_ENTRIES: 1191 case MAT_USE_HASH_TABLE: 1192 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1193 break; 1194 case MAT_USE_INODES: 1195 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1196 break; 1197 default: 1198 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1199 } 1200 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1201 PetscFunctionReturn(0); 1202 } 1203 1204 #undef __FUNCT__ 1205 #define __FUNCT__ "MatGetDiagonal_SeqAIJ" 1206 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1207 { 1208 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1209 PetscErrorCode ierr; 1210 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1211 PetscScalar *aa=a->a,*x,zero=0.0; 1212 1213 PetscFunctionBegin; 1214 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1215 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1216 1217 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1218 PetscInt *diag=a->diag; 1219 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1220 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1221 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1222 PetscFunctionReturn(0); 1223 } 1224 1225 ierr = VecSet(v,zero);CHKERRQ(ierr); 1226 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1227 for (i=0; i<n; i++) { 1228 nz = ai[i+1] - ai[i]; 1229 if (!nz) x[i] = 0.0; 1230 for (j=ai[i]; j<ai[i+1]; j++) { 1231 if (aj[j] == i) { 1232 x[i] = aa[j]; 1233 break; 1234 } 1235 } 1236 } 1237 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1238 PetscFunctionReturn(0); 1239 } 1240 1241 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1242 #undef __FUNCT__ 1243 #define __FUNCT__ "MatMultTransposeAdd_SeqAIJ" 1244 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1245 { 1246 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1247 PetscScalar *x,*y; 1248 PetscErrorCode ierr; 1249 PetscInt m = A->rmap->n; 1250 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1251 MatScalar *v; 1252 PetscScalar alpha; 1253 PetscInt n,i,j,*idx,*ii,*ridx=NULL; 1254 Mat_CompressedRow cprow = a->compressedrow; 1255 PetscBool usecprow = cprow.use; 1256 #endif 1257 1258 PetscFunctionBegin; 1259 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1260 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1261 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1262 1263 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1264 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1265 #else 1266 if (usecprow) { 1267 m = cprow.nrows; 1268 ii = cprow.i; 1269 ridx = cprow.rindex; 1270 } else { 1271 ii = a->i; 1272 } 1273 for (i=0; i<m; i++) { 1274 idx = a->j + ii[i]; 1275 v = a->a + ii[i]; 1276 n = ii[i+1] - ii[i]; 1277 if (usecprow) { 1278 alpha = x[ridx[i]]; 1279 } else { 1280 alpha = x[i]; 1281 } 1282 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1283 } 1284 #endif 1285 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1286 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1287 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1288 PetscFunctionReturn(0); 1289 } 1290 1291 #undef __FUNCT__ 1292 #define __FUNCT__ "MatMultTranspose_SeqAIJ" 1293 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1294 { 1295 PetscErrorCode ierr; 1296 1297 PetscFunctionBegin; 1298 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1299 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1300 PetscFunctionReturn(0); 1301 } 1302 1303 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1304 #if defined(PETSC_THREADCOMM_ACTIVE) 1305 PetscErrorCode MatMult_SeqAIJ_Kernel(PetscInt thread_id,Mat A,Vec xx,Vec yy) 1306 { 1307 PetscErrorCode ierr; 1308 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1309 PetscScalar *y; 1310 const PetscScalar *x; 1311 const MatScalar *aa; 1312 PetscInt *trstarts=A->rmap->trstarts; 1313 PetscInt n,start,end,i; 1314 const PetscInt *aj,*ai; 1315 PetscScalar sum; 1316 1317 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1318 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1319 start = trstarts[thread_id]; 1320 end = trstarts[thread_id+1]; 1321 aj = a->j; 1322 aa = a->a; 1323 ai = a->i; 1324 for (i=start; i<end; i++) { 1325 n = ai[i+1] - ai[i]; 1326 aj = a->j + ai[i]; 1327 aa = a->a + ai[i]; 1328 sum = 0.0; 1329 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1330 y[i] = sum; 1331 } 1332 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1333 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1334 return 0; 1335 } 1336 1337 #undef __FUNCT__ 1338 #define __FUNCT__ "MatMult_SeqAIJ" 1339 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1340 { 1341 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1342 PetscScalar *y; 1343 const PetscScalar *x; 1344 const MatScalar *aa; 1345 PetscErrorCode ierr; 1346 PetscInt m=A->rmap->n; 1347 const PetscInt *aj,*ii,*ridx=NULL; 1348 PetscInt n,i; 1349 PetscScalar sum; 1350 PetscBool usecprow=a->compressedrow.use; 1351 1352 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1353 #pragma disjoint(*x,*y,*aa) 1354 #endif 1355 1356 PetscFunctionBegin; 1357 aj = a->j; 1358 aa = a->a; 1359 ii = a->i; 1360 if (usecprow) { /* use compressed row format */ 1361 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1362 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1363 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1364 m = a->compressedrow.nrows; 1365 ii = a->compressedrow.i; 1366 ridx = a->compressedrow.rindex; 1367 for (i=0; i<m; i++) { 1368 n = ii[i+1] - ii[i]; 1369 aj = a->j + ii[i]; 1370 aa = a->a + ii[i]; 1371 sum = 0.0; 1372 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1373 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1374 y[*ridx++] = sum; 1375 } 1376 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1377 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1378 } else { /* do not use compressed row format */ 1379 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1380 fortranmultaij_(&m,x,ii,aj,aa,y); 1381 #else 1382 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatMult_SeqAIJ_Kernel,3,A,xx,yy);CHKERRQ(ierr); 1383 #endif 1384 } 1385 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1386 PetscFunctionReturn(0); 1387 } 1388 #else 1389 #undef __FUNCT__ 1390 #define __FUNCT__ "MatMult_SeqAIJ" 1391 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1392 { 1393 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1394 PetscScalar *y; 1395 const PetscScalar *x; 1396 const MatScalar *aa; 1397 PetscErrorCode ierr; 1398 PetscInt m=A->rmap->n; 1399 const PetscInt *aj,*ii,*ridx=NULL; 1400 PetscInt n,i; 1401 PetscScalar sum; 1402 PetscBool usecprow=a->compressedrow.use; 1403 1404 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1405 #pragma disjoint(*x,*y,*aa) 1406 #endif 1407 1408 PetscFunctionBegin; 1409 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1410 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1411 aj = a->j; 1412 aa = a->a; 1413 ii = a->i; 1414 if (usecprow) { /* use compressed row format */ 1415 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1416 m = a->compressedrow.nrows; 1417 ii = a->compressedrow.i; 1418 ridx = a->compressedrow.rindex; 1419 for (i=0; i<m; i++) { 1420 n = ii[i+1] - ii[i]; 1421 aj = a->j + ii[i]; 1422 aa = a->a + ii[i]; 1423 sum = 0.0; 1424 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1425 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1426 y[*ridx++] = sum; 1427 } 1428 } else { /* do not use compressed row format */ 1429 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1430 fortranmultaij_(&m,x,ii,aj,aa,y); 1431 #else 1432 #if defined(PETSC_THREADCOMM_ACTIVE) 1433 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatMult_SeqAIJ_Kernel,3,A,xx,yy);CHKERRQ(ierr); 1434 #else 1435 for (i=0; i<m; i++) { 1436 n = ii[i+1] - ii[i]; 1437 aj = a->j + ii[i]; 1438 aa = a->a + ii[i]; 1439 sum = 0.0; 1440 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1441 y[i] = sum; 1442 } 1443 #endif 1444 #endif 1445 } 1446 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1447 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1448 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1449 PetscFunctionReturn(0); 1450 } 1451 #endif 1452 1453 #undef __FUNCT__ 1454 #define __FUNCT__ "MatMultMax_SeqAIJ" 1455 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1456 { 1457 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1458 PetscScalar *y; 1459 const PetscScalar *x; 1460 const MatScalar *aa; 1461 PetscErrorCode ierr; 1462 PetscInt m=A->rmap->n; 1463 const PetscInt *aj,*ii,*ridx=NULL; 1464 PetscInt n,i,nonzerorow=0; 1465 PetscScalar sum; 1466 PetscBool usecprow=a->compressedrow.use; 1467 1468 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1469 #pragma disjoint(*x,*y,*aa) 1470 #endif 1471 1472 PetscFunctionBegin; 1473 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1474 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1475 aj = a->j; 1476 aa = a->a; 1477 ii = a->i; 1478 if (usecprow) { /* use compressed row format */ 1479 m = a->compressedrow.nrows; 1480 ii = a->compressedrow.i; 1481 ridx = a->compressedrow.rindex; 1482 for (i=0; i<m; i++) { 1483 n = ii[i+1] - ii[i]; 1484 aj = a->j + ii[i]; 1485 aa = a->a + ii[i]; 1486 sum = 0.0; 1487 nonzerorow += (n>0); 1488 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1489 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1490 y[*ridx++] = sum; 1491 } 1492 } else { /* do not use compressed row format */ 1493 for (i=0; i<m; i++) { 1494 n = ii[i+1] - ii[i]; 1495 aj = a->j + ii[i]; 1496 aa = a->a + ii[i]; 1497 sum = 0.0; 1498 nonzerorow += (n>0); 1499 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1500 y[i] = sum; 1501 } 1502 } 1503 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1504 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1505 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1506 PetscFunctionReturn(0); 1507 } 1508 1509 #undef __FUNCT__ 1510 #define __FUNCT__ "MatMultAddMax_SeqAIJ" 1511 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1512 { 1513 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1514 PetscScalar *y,*z; 1515 const PetscScalar *x; 1516 const MatScalar *aa; 1517 PetscErrorCode ierr; 1518 PetscInt m = A->rmap->n,*aj,*ii; 1519 PetscInt n,i,*ridx=NULL; 1520 PetscScalar sum; 1521 PetscBool usecprow=a->compressedrow.use; 1522 1523 PetscFunctionBegin; 1524 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1525 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1526 if (zz != yy) { 1527 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 1528 } else { 1529 z = y; 1530 } 1531 1532 aj = a->j; 1533 aa = a->a; 1534 ii = a->i; 1535 if (usecprow) { /* use compressed row format */ 1536 if (zz != yy) { 1537 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1538 } 1539 m = a->compressedrow.nrows; 1540 ii = a->compressedrow.i; 1541 ridx = a->compressedrow.rindex; 1542 for (i=0; i<m; i++) { 1543 n = ii[i+1] - ii[i]; 1544 aj = a->j + ii[i]; 1545 aa = a->a + ii[i]; 1546 sum = y[*ridx]; 1547 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1548 z[*ridx++] = sum; 1549 } 1550 } else { /* do not use compressed row format */ 1551 for (i=0; i<m; i++) { 1552 n = ii[i+1] - ii[i]; 1553 aj = a->j + ii[i]; 1554 aa = a->a + ii[i]; 1555 sum = y[i]; 1556 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1557 z[i] = sum; 1558 } 1559 } 1560 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1561 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1562 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1563 if (zz != yy) { 1564 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 1565 } 1566 PetscFunctionReturn(0); 1567 } 1568 1569 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1570 #undef __FUNCT__ 1571 #define __FUNCT__ "MatMultAdd_SeqAIJ" 1572 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1573 { 1574 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1575 PetscScalar *y,*z; 1576 const PetscScalar *x; 1577 const MatScalar *aa; 1578 PetscErrorCode ierr; 1579 PetscInt m = A->rmap->n,*aj,*ii; 1580 PetscInt n,i,*ridx=NULL; 1581 PetscScalar sum; 1582 PetscBool usecprow=a->compressedrow.use; 1583 1584 PetscFunctionBegin; 1585 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1586 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1587 if (zz != yy) { 1588 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 1589 } else { 1590 z = y; 1591 } 1592 1593 aj = a->j; 1594 aa = a->a; 1595 ii = a->i; 1596 if (usecprow) { /* use compressed row format */ 1597 if (zz != yy) { 1598 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1599 } 1600 m = a->compressedrow.nrows; 1601 ii = a->compressedrow.i; 1602 ridx = a->compressedrow.rindex; 1603 for (i=0; i<m; i++) { 1604 n = ii[i+1] - ii[i]; 1605 aj = a->j + ii[i]; 1606 aa = a->a + ii[i]; 1607 sum = y[*ridx]; 1608 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1609 z[*ridx++] = sum; 1610 } 1611 } else { /* do not use compressed row format */ 1612 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1613 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1614 #else 1615 for (i=0; i<m; i++) { 1616 n = ii[i+1] - ii[i]; 1617 aj = a->j + ii[i]; 1618 aa = a->a + ii[i]; 1619 sum = y[i]; 1620 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1621 z[i] = sum; 1622 } 1623 #endif 1624 } 1625 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1626 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1627 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1628 if (zz != yy) { 1629 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 1630 } 1631 #if defined(PETSC_HAVE_CUSP) 1632 /* 1633 ierr = VecView(xx,0);CHKERRQ(ierr); 1634 ierr = VecView(zz,0);CHKERRQ(ierr); 1635 ierr = MatView(A,0);CHKERRQ(ierr); 1636 */ 1637 #endif 1638 PetscFunctionReturn(0); 1639 } 1640 1641 /* 1642 Adds diagonal pointers to sparse matrix structure. 1643 */ 1644 #undef __FUNCT__ 1645 #define __FUNCT__ "MatMarkDiagonal_SeqAIJ" 1646 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1647 { 1648 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1649 PetscErrorCode ierr; 1650 PetscInt i,j,m = A->rmap->n; 1651 1652 PetscFunctionBegin; 1653 if (!a->diag) { 1654 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1655 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1656 } 1657 for (i=0; i<A->rmap->n; i++) { 1658 a->diag[i] = a->i[i+1]; 1659 for (j=a->i[i]; j<a->i[i+1]; j++) { 1660 if (a->j[j] == i) { 1661 a->diag[i] = j; 1662 break; 1663 } 1664 } 1665 } 1666 PetscFunctionReturn(0); 1667 } 1668 1669 /* 1670 Checks for missing diagonals 1671 */ 1672 #undef __FUNCT__ 1673 #define __FUNCT__ "MatMissingDiagonal_SeqAIJ" 1674 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1675 { 1676 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1677 PetscInt *diag,*ii = a->i,i; 1678 1679 PetscFunctionBegin; 1680 *missing = PETSC_FALSE; 1681 if (A->rmap->n > 0 && !ii) { 1682 *missing = PETSC_TRUE; 1683 if (d) *d = 0; 1684 PetscInfo(A,"Matrix has no entries therefore is missing diagonal"); 1685 } else { 1686 diag = a->diag; 1687 for (i=0; i<A->rmap->n; i++) { 1688 if (diag[i] >= ii[i+1]) { 1689 *missing = PETSC_TRUE; 1690 if (d) *d = i; 1691 PetscInfo1(A,"Matrix is missing diagonal number %D",i); 1692 break; 1693 } 1694 } 1695 } 1696 PetscFunctionReturn(0); 1697 } 1698 1699 #undef __FUNCT__ 1700 #define __FUNCT__ "MatInvertDiagonal_SeqAIJ" 1701 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1702 { 1703 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1704 PetscErrorCode ierr; 1705 PetscInt i,*diag,m = A->rmap->n; 1706 MatScalar *v = a->a; 1707 PetscScalar *idiag,*mdiag; 1708 1709 PetscFunctionBegin; 1710 if (a->idiagvalid) PetscFunctionReturn(0); 1711 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1712 diag = a->diag; 1713 if (!a->idiag) { 1714 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1715 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1716 v = a->a; 1717 } 1718 mdiag = a->mdiag; 1719 idiag = a->idiag; 1720 1721 if (omega == 1.0 && !PetscAbsScalar(fshift)) { 1722 for (i=0; i<m; i++) { 1723 mdiag[i] = v[diag[i]]; 1724 if (!PetscAbsScalar(mdiag[i])) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1725 idiag[i] = 1.0/v[diag[i]]; 1726 } 1727 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1728 } else { 1729 for (i=0; i<m; i++) { 1730 mdiag[i] = v[diag[i]]; 1731 idiag[i] = omega/(fshift + v[diag[i]]); 1732 } 1733 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1734 } 1735 a->idiagvalid = PETSC_TRUE; 1736 PetscFunctionReturn(0); 1737 } 1738 1739 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1740 #undef __FUNCT__ 1741 #define __FUNCT__ "MatSOR_SeqAIJ" 1742 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1743 { 1744 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1745 PetscScalar *x,d,sum,*t,scale; 1746 const MatScalar *v = a->a,*idiag=0,*mdiag; 1747 const PetscScalar *b, *bs,*xb, *ts; 1748 PetscErrorCode ierr; 1749 PetscInt n = A->cmap->n,m = A->rmap->n,i; 1750 const PetscInt *idx,*diag; 1751 1752 PetscFunctionBegin; 1753 its = its*lits; 1754 1755 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1756 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1757 a->fshift = fshift; 1758 a->omega = omega; 1759 1760 diag = a->diag; 1761 t = a->ssor_work; 1762 idiag = a->idiag; 1763 mdiag = a->mdiag; 1764 1765 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1766 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1767 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1768 if (flag == SOR_APPLY_UPPER) { 1769 /* apply (U + D/omega) to the vector */ 1770 bs = b; 1771 for (i=0; i<m; i++) { 1772 d = fshift + mdiag[i]; 1773 n = a->i[i+1] - diag[i] - 1; 1774 idx = a->j + diag[i] + 1; 1775 v = a->a + diag[i] + 1; 1776 sum = b[i]*d/omega; 1777 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1778 x[i] = sum; 1779 } 1780 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1781 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1782 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1783 PetscFunctionReturn(0); 1784 } 1785 1786 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1787 else if (flag & SOR_EISENSTAT) { 1788 /* Let A = L + U + D; where L is lower trianglar, 1789 U is upper triangular, E = D/omega; This routine applies 1790 1791 (L + E)^{-1} A (U + E)^{-1} 1792 1793 to a vector efficiently using Eisenstat's trick. 1794 */ 1795 scale = (2.0/omega) - 1.0; 1796 1797 /* x = (E + U)^{-1} b */ 1798 for (i=m-1; i>=0; i--) { 1799 n = a->i[i+1] - diag[i] - 1; 1800 idx = a->j + diag[i] + 1; 1801 v = a->a + diag[i] + 1; 1802 sum = b[i]; 1803 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1804 x[i] = sum*idiag[i]; 1805 } 1806 1807 /* t = b - (2*E - D)x */ 1808 v = a->a; 1809 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1810 1811 /* t = (E + L)^{-1}t */ 1812 ts = t; 1813 diag = a->diag; 1814 for (i=0; i<m; i++) { 1815 n = diag[i] - a->i[i]; 1816 idx = a->j + a->i[i]; 1817 v = a->a + a->i[i]; 1818 sum = t[i]; 1819 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1820 t[i] = sum*idiag[i]; 1821 /* x = x + t */ 1822 x[i] += t[i]; 1823 } 1824 1825 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1826 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1827 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1828 PetscFunctionReturn(0); 1829 } 1830 if (flag & SOR_ZERO_INITIAL_GUESS) { 1831 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1832 for (i=0; i<m; i++) { 1833 n = diag[i] - a->i[i]; 1834 idx = a->j + a->i[i]; 1835 v = a->a + a->i[i]; 1836 sum = b[i]; 1837 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1838 t[i] = sum; 1839 x[i] = sum*idiag[i]; 1840 } 1841 xb = t; 1842 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1843 } else xb = b; 1844 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1845 for (i=m-1; i>=0; i--) { 1846 n = a->i[i+1] - diag[i] - 1; 1847 idx = a->j + diag[i] + 1; 1848 v = a->a + diag[i] + 1; 1849 sum = xb[i]; 1850 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1851 if (xb == b) { 1852 x[i] = sum*idiag[i]; 1853 } else { 1854 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1855 } 1856 } 1857 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1858 } 1859 its--; 1860 } 1861 while (its--) { 1862 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1863 for (i=0; i<m; i++) { 1864 /* lower */ 1865 n = diag[i] - a->i[i]; 1866 idx = a->j + a->i[i]; 1867 v = a->a + a->i[i]; 1868 sum = b[i]; 1869 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1870 t[i] = sum; /* save application of the lower-triangular part */ 1871 /* upper */ 1872 n = a->i[i+1] - diag[i] - 1; 1873 idx = a->j + diag[i] + 1; 1874 v = a->a + diag[i] + 1; 1875 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1876 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1877 } 1878 xb = t; 1879 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1880 } else xb = b; 1881 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1882 for (i=m-1; i>=0; i--) { 1883 sum = xb[i]; 1884 if (xb == b) { 1885 /* whole matrix (no checkpointing available) */ 1886 n = a->i[i+1] - a->i[i]; 1887 idx = a->j + a->i[i]; 1888 v = a->a + a->i[i]; 1889 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1890 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1891 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1892 n = a->i[i+1] - diag[i] - 1; 1893 idx = a->j + diag[i] + 1; 1894 v = a->a + diag[i] + 1; 1895 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1896 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1897 } 1898 } 1899 if (xb == b) { 1900 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1901 } else { 1902 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1903 } 1904 } 1905 } 1906 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1907 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1908 PetscFunctionReturn(0); 1909 } 1910 1911 1912 #undef __FUNCT__ 1913 #define __FUNCT__ "MatGetInfo_SeqAIJ" 1914 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1915 { 1916 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1917 1918 PetscFunctionBegin; 1919 info->block_size = 1.0; 1920 info->nz_allocated = (double)a->maxnz; 1921 info->nz_used = (double)a->nz; 1922 info->nz_unneeded = (double)(a->maxnz - a->nz); 1923 info->assemblies = (double)A->num_ass; 1924 info->mallocs = (double)A->info.mallocs; 1925 info->memory = ((PetscObject)A)->mem; 1926 if (A->factortype) { 1927 info->fill_ratio_given = A->info.fill_ratio_given; 1928 info->fill_ratio_needed = A->info.fill_ratio_needed; 1929 info->factor_mallocs = A->info.factor_mallocs; 1930 } else { 1931 info->fill_ratio_given = 0; 1932 info->fill_ratio_needed = 0; 1933 info->factor_mallocs = 0; 1934 } 1935 PetscFunctionReturn(0); 1936 } 1937 1938 #undef __FUNCT__ 1939 #define __FUNCT__ "MatZeroRows_SeqAIJ" 1940 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1941 { 1942 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1943 PetscInt i,m = A->rmap->n - 1,d = 0; 1944 PetscErrorCode ierr; 1945 const PetscScalar *xx; 1946 PetscScalar *bb; 1947 PetscBool missing; 1948 1949 PetscFunctionBegin; 1950 if (x && b) { 1951 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1952 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1953 for (i=0; i<N; i++) { 1954 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1955 bb[rows[i]] = diag*xx[rows[i]]; 1956 } 1957 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1958 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1959 } 1960 1961 if (a->keepnonzeropattern) { 1962 for (i=0; i<N; i++) { 1963 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1964 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1965 } 1966 if (diag != 0.0) { 1967 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1968 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1969 for (i=0; i<N; i++) { 1970 a->a[a->diag[rows[i]]] = diag; 1971 } 1972 } 1973 } else { 1974 if (diag != 0.0) { 1975 for (i=0; i<N; i++) { 1976 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1977 if (a->ilen[rows[i]] > 0) { 1978 a->ilen[rows[i]] = 1; 1979 a->a[a->i[rows[i]]] = diag; 1980 a->j[a->i[rows[i]]] = rows[i]; 1981 } else { /* in case row was completely empty */ 1982 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1983 } 1984 } 1985 } else { 1986 for (i=0; i<N; i++) { 1987 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1988 a->ilen[rows[i]] = 0; 1989 } 1990 } 1991 A->nonzerostate++; 1992 } 1993 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatZeroRowsColumns_SeqAIJ" 1999 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 2000 { 2001 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2002 PetscInt i,j,m = A->rmap->n - 1,d = 0; 2003 PetscErrorCode ierr; 2004 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 2005 const PetscScalar *xx; 2006 PetscScalar *bb; 2007 2008 PetscFunctionBegin; 2009 if (x && b) { 2010 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2011 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2012 vecs = PETSC_TRUE; 2013 } 2014 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 2015 for (i=0; i<N; i++) { 2016 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2017 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 2018 2019 zeroed[rows[i]] = PETSC_TRUE; 2020 } 2021 for (i=0; i<A->rmap->n; i++) { 2022 if (!zeroed[i]) { 2023 for (j=a->i[i]; j<a->i[i+1]; j++) { 2024 if (zeroed[a->j[j]]) { 2025 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 2026 a->a[j] = 0.0; 2027 } 2028 } 2029 } else if (vecs) bb[i] = diag*xx[i]; 2030 } 2031 if (x && b) { 2032 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2033 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2034 } 2035 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2036 if (diag != 0.0) { 2037 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 2038 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 2039 for (i=0; i<N; i++) { 2040 a->a[a->diag[rows[i]]] = diag; 2041 } 2042 } 2043 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2044 PetscFunctionReturn(0); 2045 } 2046 2047 #undef __FUNCT__ 2048 #define __FUNCT__ "MatGetRow_SeqAIJ" 2049 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2050 { 2051 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2052 PetscInt *itmp; 2053 2054 PetscFunctionBegin; 2055 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 2056 2057 *nz = a->i[row+1] - a->i[row]; 2058 if (v) *v = a->a + a->i[row]; 2059 if (idx) { 2060 itmp = a->j + a->i[row]; 2061 if (*nz) *idx = itmp; 2062 else *idx = 0; 2063 } 2064 PetscFunctionReturn(0); 2065 } 2066 2067 /* remove this function? */ 2068 #undef __FUNCT__ 2069 #define __FUNCT__ "MatRestoreRow_SeqAIJ" 2070 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2071 { 2072 PetscFunctionBegin; 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatNorm_SeqAIJ" 2078 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 2079 { 2080 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2081 MatScalar *v = a->a; 2082 PetscReal sum = 0.0; 2083 PetscErrorCode ierr; 2084 PetscInt i,j; 2085 2086 PetscFunctionBegin; 2087 if (type == NORM_FROBENIUS) { 2088 for (i=0; i<a->nz; i++) { 2089 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2090 } 2091 *nrm = PetscSqrtReal(sum); 2092 } else if (type == NORM_1) { 2093 PetscReal *tmp; 2094 PetscInt *jj = a->j; 2095 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 2096 *nrm = 0.0; 2097 for (j=0; j<a->nz; j++) { 2098 tmp[*jj++] += PetscAbsScalar(*v); v++; 2099 } 2100 for (j=0; j<A->cmap->n; j++) { 2101 if (tmp[j] > *nrm) *nrm = tmp[j]; 2102 } 2103 ierr = PetscFree(tmp);CHKERRQ(ierr); 2104 } else if (type == NORM_INFINITY) { 2105 *nrm = 0.0; 2106 for (j=0; j<A->rmap->n; j++) { 2107 v = a->a + a->i[j]; 2108 sum = 0.0; 2109 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2110 sum += PetscAbsScalar(*v); v++; 2111 } 2112 if (sum > *nrm) *nrm = sum; 2113 } 2114 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2115 PetscFunctionReturn(0); 2116 } 2117 2118 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2119 #undef __FUNCT__ 2120 #define __FUNCT__ "MatTransposeSymbolic_SeqAIJ" 2121 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2122 { 2123 PetscErrorCode ierr; 2124 PetscInt i,j,anzj; 2125 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2126 PetscInt an=A->cmap->N,am=A->rmap->N; 2127 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2128 2129 PetscFunctionBegin; 2130 /* Allocate space for symbolic transpose info and work array */ 2131 ierr = PetscCalloc1((an+1),&ati);CHKERRQ(ierr); 2132 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 2133 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 2134 2135 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2136 /* Note: offset by 1 for fast conversion into csr format. */ 2137 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2138 /* Form ati for csr format of A^T. */ 2139 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2140 2141 /* Copy ati into atfill so we have locations of the next free space in atj */ 2142 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2143 2144 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2145 for (i=0;i<am;i++) { 2146 anzj = ai[i+1] - ai[i]; 2147 for (j=0;j<anzj;j++) { 2148 atj[atfill[*aj]] = i; 2149 atfill[*aj++] += 1; 2150 } 2151 } 2152 2153 /* Clean up temporary space and complete requests. */ 2154 ierr = PetscFree(atfill);CHKERRQ(ierr); 2155 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2156 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2157 2158 b = (Mat_SeqAIJ*)((*B)->data); 2159 b->free_a = PETSC_FALSE; 2160 b->free_ij = PETSC_TRUE; 2161 b->nonew = 0; 2162 PetscFunctionReturn(0); 2163 } 2164 2165 #undef __FUNCT__ 2166 #define __FUNCT__ "MatTranspose_SeqAIJ" 2167 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2168 { 2169 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2170 Mat C; 2171 PetscErrorCode ierr; 2172 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2173 MatScalar *array = a->a; 2174 2175 PetscFunctionBegin; 2176 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"); 2177 2178 if (reuse == MAT_INITIAL_MATRIX || *B == A) { 2179 ierr = PetscCalloc1((1+A->cmap->n),&col);CHKERRQ(ierr); 2180 2181 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2182 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2183 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2184 ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2185 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2186 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2187 ierr = PetscFree(col);CHKERRQ(ierr); 2188 } else { 2189 C = *B; 2190 } 2191 2192 for (i=0; i<m; i++) { 2193 len = ai[i+1]-ai[i]; 2194 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2195 array += len; 2196 aj += len; 2197 } 2198 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2199 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2200 2201 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 2202 *B = C; 2203 } else { 2204 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 2205 } 2206 PetscFunctionReturn(0); 2207 } 2208 2209 #undef __FUNCT__ 2210 #define __FUNCT__ "MatIsTranspose_SeqAIJ" 2211 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2212 { 2213 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2214 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2215 MatScalar *va,*vb; 2216 PetscErrorCode ierr; 2217 PetscInt ma,na,mb,nb, i; 2218 2219 PetscFunctionBegin; 2220 bij = (Mat_SeqAIJ*) B->data; 2221 2222 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2223 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2224 if (ma!=nb || na!=mb) { 2225 *f = PETSC_FALSE; 2226 PetscFunctionReturn(0); 2227 } 2228 aii = aij->i; bii = bij->i; 2229 adx = aij->j; bdx = bij->j; 2230 va = aij->a; vb = bij->a; 2231 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2232 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2233 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2234 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2235 2236 *f = PETSC_TRUE; 2237 for (i=0; i<ma; i++) { 2238 while (aptr[i]<aii[i+1]) { 2239 PetscInt idc,idr; 2240 PetscScalar vc,vr; 2241 /* column/row index/value */ 2242 idc = adx[aptr[i]]; 2243 idr = bdx[bptr[idc]]; 2244 vc = va[aptr[i]]; 2245 vr = vb[bptr[idc]]; 2246 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2247 *f = PETSC_FALSE; 2248 goto done; 2249 } else { 2250 aptr[i]++; 2251 if (B || i!=idc) bptr[idc]++; 2252 } 2253 } 2254 } 2255 done: 2256 ierr = PetscFree(aptr);CHKERRQ(ierr); 2257 ierr = PetscFree(bptr);CHKERRQ(ierr); 2258 PetscFunctionReturn(0); 2259 } 2260 2261 #undef __FUNCT__ 2262 #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" 2263 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2264 { 2265 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2266 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2267 MatScalar *va,*vb; 2268 PetscErrorCode ierr; 2269 PetscInt ma,na,mb,nb, i; 2270 2271 PetscFunctionBegin; 2272 bij = (Mat_SeqAIJ*) B->data; 2273 2274 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2275 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2276 if (ma!=nb || na!=mb) { 2277 *f = PETSC_FALSE; 2278 PetscFunctionReturn(0); 2279 } 2280 aii = aij->i; bii = bij->i; 2281 adx = aij->j; bdx = bij->j; 2282 va = aij->a; vb = bij->a; 2283 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2284 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2285 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2286 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2287 2288 *f = PETSC_TRUE; 2289 for (i=0; i<ma; i++) { 2290 while (aptr[i]<aii[i+1]) { 2291 PetscInt idc,idr; 2292 PetscScalar vc,vr; 2293 /* column/row index/value */ 2294 idc = adx[aptr[i]]; 2295 idr = bdx[bptr[idc]]; 2296 vc = va[aptr[i]]; 2297 vr = vb[bptr[idc]]; 2298 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2299 *f = PETSC_FALSE; 2300 goto done; 2301 } else { 2302 aptr[i]++; 2303 if (B || i!=idc) bptr[idc]++; 2304 } 2305 } 2306 } 2307 done: 2308 ierr = PetscFree(aptr);CHKERRQ(ierr); 2309 ierr = PetscFree(bptr);CHKERRQ(ierr); 2310 PetscFunctionReturn(0); 2311 } 2312 2313 #undef __FUNCT__ 2314 #define __FUNCT__ "MatIsSymmetric_SeqAIJ" 2315 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2316 { 2317 PetscErrorCode ierr; 2318 2319 PetscFunctionBegin; 2320 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2321 PetscFunctionReturn(0); 2322 } 2323 2324 #undef __FUNCT__ 2325 #define __FUNCT__ "MatIsHermitian_SeqAIJ" 2326 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2327 { 2328 PetscErrorCode ierr; 2329 2330 PetscFunctionBegin; 2331 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2332 PetscFunctionReturn(0); 2333 } 2334 2335 #undef __FUNCT__ 2336 #define __FUNCT__ "MatDiagonalScale_SeqAIJ" 2337 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2338 { 2339 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2340 PetscScalar *l,*r,x; 2341 MatScalar *v; 2342 PetscErrorCode ierr; 2343 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; 2344 2345 PetscFunctionBegin; 2346 if (ll) { 2347 /* The local size is used so that VecMPI can be passed to this routine 2348 by MatDiagonalScale_MPIAIJ */ 2349 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2350 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2351 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 2352 v = a->a; 2353 for (i=0; i<m; i++) { 2354 x = l[i]; 2355 M = a->i[i+1] - a->i[i]; 2356 for (j=0; j<M; j++) (*v++) *= x; 2357 } 2358 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 2359 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2360 } 2361 if (rr) { 2362 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2363 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2364 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 2365 v = a->a; jj = a->j; 2366 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2367 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 2368 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2369 } 2370 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2371 PetscFunctionReturn(0); 2372 } 2373 2374 #undef __FUNCT__ 2375 #define __FUNCT__ "MatGetSubMatrix_SeqAIJ" 2376 PetscErrorCode MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2377 { 2378 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2379 PetscErrorCode ierr; 2380 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2381 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2382 const PetscInt *irow,*icol; 2383 PetscInt nrows,ncols; 2384 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2385 MatScalar *a_new,*mat_a; 2386 Mat C; 2387 PetscBool stride,sorted; 2388 2389 PetscFunctionBegin; 2390 ierr = ISSorted(isrow,&sorted);CHKERRQ(ierr); 2391 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted"); 2392 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); 2393 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted"); 2394 2395 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2396 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2397 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2398 2399 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2400 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2401 if (stride && step == 1) { 2402 /* special case of contiguous rows */ 2403 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2404 /* loop over new rows determining lens and starting points */ 2405 for (i=0; i<nrows; i++) { 2406 kstart = ai[irow[i]]; 2407 kend = kstart + ailen[irow[i]]; 2408 for (k=kstart; k<kend; k++) { 2409 if (aj[k] >= first) { 2410 starts[i] = k; 2411 break; 2412 } 2413 } 2414 sum = 0; 2415 while (k < kend) { 2416 if (aj[k++] >= first+ncols) break; 2417 sum++; 2418 } 2419 lens[i] = sum; 2420 } 2421 /* create submatrix */ 2422 if (scall == MAT_REUSE_MATRIX) { 2423 PetscInt n_cols,n_rows; 2424 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2425 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2426 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2427 C = *B; 2428 } else { 2429 PetscInt rbs,cbs; 2430 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2431 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2432 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2433 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2434 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2435 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2436 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2437 } 2438 c = (Mat_SeqAIJ*)C->data; 2439 2440 /* loop over rows inserting into submatrix */ 2441 a_new = c->a; 2442 j_new = c->j; 2443 i_new = c->i; 2444 2445 for (i=0; i<nrows; i++) { 2446 ii = starts[i]; 2447 lensi = lens[i]; 2448 for (k=0; k<lensi; k++) { 2449 *j_new++ = aj[ii+k] - first; 2450 } 2451 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2452 a_new += lensi; 2453 i_new[i+1] = i_new[i] + lensi; 2454 c->ilen[i] = lensi; 2455 } 2456 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2457 } else { 2458 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2459 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2460 ierr = PetscMalloc1((1+nrows),&lens);CHKERRQ(ierr); 2461 for (i=0; i<ncols; i++) { 2462 #if defined(PETSC_USE_DEBUG) 2463 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); 2464 #endif 2465 smap[icol[i]] = i+1; 2466 } 2467 2468 /* determine lens of each row */ 2469 for (i=0; i<nrows; i++) { 2470 kstart = ai[irow[i]]; 2471 kend = kstart + a->ilen[irow[i]]; 2472 lens[i] = 0; 2473 for (k=kstart; k<kend; k++) { 2474 if (smap[aj[k]]) { 2475 lens[i]++; 2476 } 2477 } 2478 } 2479 /* Create and fill new matrix */ 2480 if (scall == MAT_REUSE_MATRIX) { 2481 PetscBool equal; 2482 2483 c = (Mat_SeqAIJ*)((*B)->data); 2484 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2485 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2486 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2487 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2488 C = *B; 2489 } else { 2490 PetscInt rbs,cbs; 2491 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2492 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2493 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2494 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2495 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2496 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2497 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2498 } 2499 c = (Mat_SeqAIJ*)(C->data); 2500 for (i=0; i<nrows; i++) { 2501 row = irow[i]; 2502 kstart = ai[row]; 2503 kend = kstart + a->ilen[row]; 2504 mat_i = c->i[i]; 2505 mat_j = c->j + mat_i; 2506 mat_a = c->a + mat_i; 2507 mat_ilen = c->ilen + i; 2508 for (k=kstart; k<kend; k++) { 2509 if ((tcol=smap[a->j[k]])) { 2510 *mat_j++ = tcol - 1; 2511 *mat_a++ = a->a[k]; 2512 (*mat_ilen)++; 2513 2514 } 2515 } 2516 } 2517 /* Free work space */ 2518 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2519 ierr = PetscFree(smap);CHKERRQ(ierr); 2520 ierr = PetscFree(lens);CHKERRQ(ierr); 2521 } 2522 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2523 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2524 2525 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2526 *B = C; 2527 PetscFunctionReturn(0); 2528 } 2529 2530 #undef __FUNCT__ 2531 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 2532 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2533 { 2534 PetscErrorCode ierr; 2535 Mat B; 2536 2537 PetscFunctionBegin; 2538 if (scall == MAT_INITIAL_MATRIX) { 2539 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2540 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2541 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2542 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2543 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2544 *subMat = B; 2545 } else { 2546 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2547 } 2548 PetscFunctionReturn(0); 2549 } 2550 2551 #undef __FUNCT__ 2552 #define __FUNCT__ "MatILUFactor_SeqAIJ" 2553 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2554 { 2555 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2556 PetscErrorCode ierr; 2557 Mat outA; 2558 PetscBool row_identity,col_identity; 2559 2560 PetscFunctionBegin; 2561 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2562 2563 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2564 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2565 2566 outA = inA; 2567 outA->factortype = MAT_FACTOR_LU; 2568 2569 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2570 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2571 2572 a->row = row; 2573 2574 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2575 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2576 2577 a->col = col; 2578 2579 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2580 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2581 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2582 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2583 2584 if (!a->solve_work) { /* this matrix may have been factored before */ 2585 ierr = PetscMalloc1((inA->rmap->n+1),&a->solve_work);CHKERRQ(ierr); 2586 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2587 } 2588 2589 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2590 if (row_identity && col_identity) { 2591 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2592 } else { 2593 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2594 } 2595 PetscFunctionReturn(0); 2596 } 2597 2598 #undef __FUNCT__ 2599 #define __FUNCT__ "MatScale_SeqAIJ" 2600 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2601 { 2602 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2603 PetscScalar oalpha = alpha; 2604 PetscErrorCode ierr; 2605 PetscBLASInt one = 1,bnz; 2606 2607 PetscFunctionBegin; 2608 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2609 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2610 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2611 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2612 PetscFunctionReturn(0); 2613 } 2614 2615 #undef __FUNCT__ 2616 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 2617 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2618 { 2619 PetscErrorCode ierr; 2620 PetscInt i; 2621 2622 PetscFunctionBegin; 2623 if (scall == MAT_INITIAL_MATRIX) { 2624 ierr = PetscMalloc1((n+1),B);CHKERRQ(ierr); 2625 } 2626 2627 for (i=0; i<n; i++) { 2628 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2629 } 2630 PetscFunctionReturn(0); 2631 } 2632 2633 #undef __FUNCT__ 2634 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 2635 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2636 { 2637 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2638 PetscErrorCode ierr; 2639 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2640 const PetscInt *idx; 2641 PetscInt start,end,*ai,*aj; 2642 PetscBT table; 2643 2644 PetscFunctionBegin; 2645 m = A->rmap->n; 2646 ai = a->i; 2647 aj = a->j; 2648 2649 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2650 2651 ierr = PetscMalloc1((m+1),&nidx);CHKERRQ(ierr); 2652 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2653 2654 for (i=0; i<is_max; i++) { 2655 /* Initialize the two local arrays */ 2656 isz = 0; 2657 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2658 2659 /* Extract the indices, assume there can be duplicate entries */ 2660 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2661 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2662 2663 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2664 for (j=0; j<n; ++j) { 2665 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2666 } 2667 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2668 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2669 2670 k = 0; 2671 for (j=0; j<ov; j++) { /* for each overlap */ 2672 n = isz; 2673 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2674 row = nidx[k]; 2675 start = ai[row]; 2676 end = ai[row+1]; 2677 for (l = start; l<end; l++) { 2678 val = aj[l]; 2679 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2680 } 2681 } 2682 } 2683 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2684 } 2685 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2686 ierr = PetscFree(nidx);CHKERRQ(ierr); 2687 PetscFunctionReturn(0); 2688 } 2689 2690 /* -------------------------------------------------------------- */ 2691 #undef __FUNCT__ 2692 #define __FUNCT__ "MatPermute_SeqAIJ" 2693 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2694 { 2695 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2696 PetscErrorCode ierr; 2697 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2698 const PetscInt *row,*col; 2699 PetscInt *cnew,j,*lens; 2700 IS icolp,irowp; 2701 PetscInt *cwork = NULL; 2702 PetscScalar *vwork = NULL; 2703 2704 PetscFunctionBegin; 2705 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2706 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2707 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2708 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2709 2710 /* determine lengths of permuted rows */ 2711 ierr = PetscMalloc1((m+1),&lens);CHKERRQ(ierr); 2712 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2713 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2714 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2715 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2716 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2717 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2718 ierr = PetscFree(lens);CHKERRQ(ierr); 2719 2720 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2721 for (i=0; i<m; i++) { 2722 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2723 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2724 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2725 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2726 } 2727 ierr = PetscFree(cnew);CHKERRQ(ierr); 2728 2729 (*B)->assembled = PETSC_FALSE; 2730 2731 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2732 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2733 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2734 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2735 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2736 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2737 PetscFunctionReturn(0); 2738 } 2739 2740 #undef __FUNCT__ 2741 #define __FUNCT__ "MatCopy_SeqAIJ" 2742 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2743 { 2744 PetscErrorCode ierr; 2745 2746 PetscFunctionBegin; 2747 /* If the two matrices have the same copy implementation, use fast copy. */ 2748 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2749 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2750 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2751 2752 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"); 2753 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2754 } else { 2755 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2756 } 2757 PetscFunctionReturn(0); 2758 } 2759 2760 #undef __FUNCT__ 2761 #define __FUNCT__ "MatSetUp_SeqAIJ" 2762 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2763 { 2764 PetscErrorCode ierr; 2765 2766 PetscFunctionBegin; 2767 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2768 PetscFunctionReturn(0); 2769 } 2770 2771 #undef __FUNCT__ 2772 #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" 2773 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2774 { 2775 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2776 2777 PetscFunctionBegin; 2778 *array = a->a; 2779 PetscFunctionReturn(0); 2780 } 2781 2782 #undef __FUNCT__ 2783 #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" 2784 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2785 { 2786 PetscFunctionBegin; 2787 PetscFunctionReturn(0); 2788 } 2789 2790 /* 2791 Computes the number of nonzeros per row needed for preallocation when X and Y 2792 have different nonzero structure. 2793 */ 2794 #undef __FUNCT__ 2795 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 2796 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2797 { 2798 PetscInt i,m=Y->rmap->N; 2799 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2800 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2801 const PetscInt *xi = x->i,*yi = y->i; 2802 2803 PetscFunctionBegin; 2804 /* Set the number of nonzeros in the new matrix */ 2805 for (i=0; i<m; i++) { 2806 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2807 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2808 nnz[i] = 0; 2809 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2810 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 2811 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 2812 nnz[i]++; 2813 } 2814 for (; k<nzy; k++) nnz[i]++; 2815 } 2816 PetscFunctionReturn(0); 2817 } 2818 2819 #undef __FUNCT__ 2820 #define __FUNCT__ "MatAXPY_SeqAIJ" 2821 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2822 { 2823 PetscErrorCode ierr; 2824 PetscInt i; 2825 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2826 PetscBLASInt one=1,bnz; 2827 2828 PetscFunctionBegin; 2829 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2830 if (str == SAME_NONZERO_PATTERN) { 2831 PetscScalar alpha = a; 2832 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2833 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2834 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2835 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2836 if (y->xtoy && y->XtoY != X) { 2837 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2838 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2839 } 2840 if (!y->xtoy) { /* get xtoy */ 2841 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 2842 y->XtoY = X; 2843 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2844 } 2845 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2846 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2847 ierr = PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %D/%D = %g\n",x->nz,y->nz,(double)((PetscReal)(x->nz)/(y->nz+1)));CHKERRQ(ierr); 2848 } else { 2849 Mat B; 2850 PetscInt *nnz; 2851 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2852 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2853 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2854 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2855 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2856 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2857 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2858 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2859 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2860 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2861 ierr = PetscFree(nnz);CHKERRQ(ierr); 2862 } 2863 PetscFunctionReturn(0); 2864 } 2865 2866 #undef __FUNCT__ 2867 #define __FUNCT__ "MatConjugate_SeqAIJ" 2868 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2869 { 2870 #if defined(PETSC_USE_COMPLEX) 2871 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2872 PetscInt i,nz; 2873 PetscScalar *a; 2874 2875 PetscFunctionBegin; 2876 nz = aij->nz; 2877 a = aij->a; 2878 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2879 #else 2880 PetscFunctionBegin; 2881 #endif 2882 PetscFunctionReturn(0); 2883 } 2884 2885 #undef __FUNCT__ 2886 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 2887 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2888 { 2889 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2890 PetscErrorCode ierr; 2891 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2892 PetscReal atmp; 2893 PetscScalar *x; 2894 MatScalar *aa; 2895 2896 PetscFunctionBegin; 2897 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2898 aa = a->a; 2899 ai = a->i; 2900 aj = a->j; 2901 2902 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2903 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2904 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2905 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2906 for (i=0; i<m; i++) { 2907 ncols = ai[1] - ai[0]; ai++; 2908 x[i] = 0.0; 2909 for (j=0; j<ncols; j++) { 2910 atmp = PetscAbsScalar(*aa); 2911 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2912 aa++; aj++; 2913 } 2914 } 2915 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2916 PetscFunctionReturn(0); 2917 } 2918 2919 #undef __FUNCT__ 2920 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 2921 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2922 { 2923 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2924 PetscErrorCode ierr; 2925 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2926 PetscScalar *x; 2927 MatScalar *aa; 2928 2929 PetscFunctionBegin; 2930 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2931 aa = a->a; 2932 ai = a->i; 2933 aj = a->j; 2934 2935 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2936 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2937 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2938 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2939 for (i=0; i<m; i++) { 2940 ncols = ai[1] - ai[0]; ai++; 2941 if (ncols == A->cmap->n) { /* row is dense */ 2942 x[i] = *aa; if (idx) idx[i] = 0; 2943 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2944 x[i] = 0.0; 2945 if (idx) { 2946 idx[i] = 0; /* in case ncols is zero */ 2947 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2948 if (aj[j] > j) { 2949 idx[i] = j; 2950 break; 2951 } 2952 } 2953 } 2954 } 2955 for (j=0; j<ncols; j++) { 2956 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2957 aa++; aj++; 2958 } 2959 } 2960 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2961 PetscFunctionReturn(0); 2962 } 2963 2964 #undef __FUNCT__ 2965 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 2966 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2967 { 2968 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2969 PetscErrorCode ierr; 2970 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2971 PetscReal atmp; 2972 PetscScalar *x; 2973 MatScalar *aa; 2974 2975 PetscFunctionBegin; 2976 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2977 aa = a->a; 2978 ai = a->i; 2979 aj = a->j; 2980 2981 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2982 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2983 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2984 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); 2985 for (i=0; i<m; i++) { 2986 ncols = ai[1] - ai[0]; ai++; 2987 if (ncols) { 2988 /* Get first nonzero */ 2989 for (j = 0; j < ncols; j++) { 2990 atmp = PetscAbsScalar(aa[j]); 2991 if (atmp > 1.0e-12) { 2992 x[i] = atmp; 2993 if (idx) idx[i] = aj[j]; 2994 break; 2995 } 2996 } 2997 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 2998 } else { 2999 x[i] = 0.0; if (idx) idx[i] = 0; 3000 } 3001 for (j = 0; j < ncols; j++) { 3002 atmp = PetscAbsScalar(*aa); 3003 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3004 aa++; aj++; 3005 } 3006 } 3007 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3008 PetscFunctionReturn(0); 3009 } 3010 3011 #undef __FUNCT__ 3012 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3013 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3014 { 3015 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3016 PetscErrorCode ierr; 3017 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3018 PetscScalar *x; 3019 MatScalar *aa; 3020 3021 PetscFunctionBegin; 3022 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3023 aa = a->a; 3024 ai = a->i; 3025 aj = a->j; 3026 3027 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3028 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3029 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3030 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3031 for (i=0; i<m; i++) { 3032 ncols = ai[1] - ai[0]; ai++; 3033 if (ncols == A->cmap->n) { /* row is dense */ 3034 x[i] = *aa; if (idx) idx[i] = 0; 3035 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3036 x[i] = 0.0; 3037 if (idx) { /* find first implicit 0.0 in the row */ 3038 idx[i] = 0; /* in case ncols is zero */ 3039 for (j=0; j<ncols; j++) { 3040 if (aj[j] > j) { 3041 idx[i] = j; 3042 break; 3043 } 3044 } 3045 } 3046 } 3047 for (j=0; j<ncols; j++) { 3048 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3049 aa++; aj++; 3050 } 3051 } 3052 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3053 PetscFunctionReturn(0); 3054 } 3055 3056 #include <petscblaslapack.h> 3057 #include <petsc-private/kernels/blockinvert.h> 3058 3059 #undef __FUNCT__ 3060 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3061 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3062 { 3063 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3064 PetscErrorCode ierr; 3065 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3066 MatScalar *diag,work[25],*v_work; 3067 PetscReal shift = 0.0; 3068 3069 PetscFunctionBegin; 3070 if (a->ibdiagvalid) { 3071 if (values) *values = a->ibdiag; 3072 PetscFunctionReturn(0); 3073 } 3074 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3075 if (!a->ibdiag) { 3076 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3077 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3078 } 3079 diag = a->ibdiag; 3080 if (values) *values = a->ibdiag; 3081 /* factor and invert each block */ 3082 switch (bs) { 3083 case 1: 3084 for (i=0; i<mbs; i++) { 3085 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3086 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3087 } 3088 break; 3089 case 2: 3090 for (i=0; i<mbs; i++) { 3091 ij[0] = 2*i; ij[1] = 2*i + 1; 3092 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3093 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3094 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3095 diag += 4; 3096 } 3097 break; 3098 case 3: 3099 for (i=0; i<mbs; i++) { 3100 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3101 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3102 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3103 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3104 diag += 9; 3105 } 3106 break; 3107 case 4: 3108 for (i=0; i<mbs; i++) { 3109 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3110 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3111 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3112 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3113 diag += 16; 3114 } 3115 break; 3116 case 5: 3117 for (i=0; i<mbs; i++) { 3118 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3119 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3120 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3121 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3122 diag += 25; 3123 } 3124 break; 3125 case 6: 3126 for (i=0; i<mbs; i++) { 3127 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; 3128 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3129 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3130 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3131 diag += 36; 3132 } 3133 break; 3134 case 7: 3135 for (i=0; i<mbs; i++) { 3136 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; 3137 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3138 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3139 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3140 diag += 49; 3141 } 3142 break; 3143 default: 3144 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3145 for (i=0; i<mbs; i++) { 3146 for (j=0; j<bs; j++) { 3147 IJ[j] = bs*i + j; 3148 } 3149 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3150 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3151 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3152 diag += bs2; 3153 } 3154 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3155 } 3156 a->ibdiagvalid = PETSC_TRUE; 3157 PetscFunctionReturn(0); 3158 } 3159 3160 #undef __FUNCT__ 3161 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3162 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3163 { 3164 PetscErrorCode ierr; 3165 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3166 PetscScalar a; 3167 PetscInt m,n,i,j,col; 3168 3169 PetscFunctionBegin; 3170 if (!x->assembled) { 3171 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3172 for (i=0; i<m; i++) { 3173 for (j=0; j<aij->imax[i]; j++) { 3174 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3175 col = (PetscInt)(n*PetscRealPart(a)); 3176 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3177 } 3178 } 3179 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3180 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3181 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3182 PetscFunctionReturn(0); 3183 } 3184 3185 /* -------------------------------------------------------------------*/ 3186 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3187 MatGetRow_SeqAIJ, 3188 MatRestoreRow_SeqAIJ, 3189 MatMult_SeqAIJ, 3190 /* 4*/ MatMultAdd_SeqAIJ, 3191 MatMultTranspose_SeqAIJ, 3192 MatMultTransposeAdd_SeqAIJ, 3193 0, 3194 0, 3195 0, 3196 /* 10*/ 0, 3197 MatLUFactor_SeqAIJ, 3198 0, 3199 MatSOR_SeqAIJ, 3200 MatTranspose_SeqAIJ, 3201 /*1 5*/ MatGetInfo_SeqAIJ, 3202 MatEqual_SeqAIJ, 3203 MatGetDiagonal_SeqAIJ, 3204 MatDiagonalScale_SeqAIJ, 3205 MatNorm_SeqAIJ, 3206 /* 20*/ 0, 3207 MatAssemblyEnd_SeqAIJ, 3208 MatSetOption_SeqAIJ, 3209 MatZeroEntries_SeqAIJ, 3210 /* 24*/ MatZeroRows_SeqAIJ, 3211 0, 3212 0, 3213 0, 3214 0, 3215 /* 29*/ MatSetUp_SeqAIJ, 3216 0, 3217 0, 3218 0, 3219 0, 3220 /* 34*/ MatDuplicate_SeqAIJ, 3221 0, 3222 0, 3223 MatILUFactor_SeqAIJ, 3224 0, 3225 /* 39*/ MatAXPY_SeqAIJ, 3226 MatGetSubMatrices_SeqAIJ, 3227 MatIncreaseOverlap_SeqAIJ, 3228 MatGetValues_SeqAIJ, 3229 MatCopy_SeqAIJ, 3230 /* 44*/ MatGetRowMax_SeqAIJ, 3231 MatScale_SeqAIJ, 3232 0, 3233 MatDiagonalSet_SeqAIJ, 3234 MatZeroRowsColumns_SeqAIJ, 3235 /* 49*/ MatSetRandom_SeqAIJ, 3236 MatGetRowIJ_SeqAIJ, 3237 MatRestoreRowIJ_SeqAIJ, 3238 MatGetColumnIJ_SeqAIJ, 3239 MatRestoreColumnIJ_SeqAIJ, 3240 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3241 0, 3242 0, 3243 MatPermute_SeqAIJ, 3244 0, 3245 /* 59*/ 0, 3246 MatDestroy_SeqAIJ, 3247 MatView_SeqAIJ, 3248 0, 3249 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3250 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3251 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3252 0, 3253 0, 3254 0, 3255 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3256 MatGetRowMinAbs_SeqAIJ, 3257 0, 3258 MatSetColoring_SeqAIJ, 3259 0, 3260 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3261 MatFDColoringApply_AIJ, 3262 0, 3263 0, 3264 0, 3265 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3266 0, 3267 0, 3268 0, 3269 MatLoad_SeqAIJ, 3270 /* 84*/ MatIsSymmetric_SeqAIJ, 3271 MatIsHermitian_SeqAIJ, 3272 0, 3273 0, 3274 0, 3275 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3276 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3277 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3278 MatPtAP_SeqAIJ_SeqAIJ, 3279 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3280 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3281 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3282 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3283 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3284 0, 3285 /* 99*/ 0, 3286 0, 3287 0, 3288 MatConjugate_SeqAIJ, 3289 0, 3290 /*104*/ MatSetValuesRow_SeqAIJ, 3291 MatRealPart_SeqAIJ, 3292 MatImaginaryPart_SeqAIJ, 3293 0, 3294 0, 3295 /*109*/ MatMatSolve_SeqAIJ, 3296 0, 3297 MatGetRowMin_SeqAIJ, 3298 0, 3299 MatMissingDiagonal_SeqAIJ, 3300 /*114*/ 0, 3301 0, 3302 0, 3303 0, 3304 0, 3305 /*119*/ 0, 3306 0, 3307 0, 3308 0, 3309 MatGetMultiProcBlock_SeqAIJ, 3310 /*124*/ MatFindNonzeroRows_SeqAIJ, 3311 MatGetColumnNorms_SeqAIJ, 3312 MatInvertBlockDiagonal_SeqAIJ, 3313 0, 3314 0, 3315 /*129*/ 0, 3316 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3317 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3318 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3319 MatTransposeColoringCreate_SeqAIJ, 3320 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3321 MatTransColoringApplyDenToSp_SeqAIJ, 3322 MatRARt_SeqAIJ_SeqAIJ, 3323 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3324 MatRARtNumeric_SeqAIJ_SeqAIJ, 3325 /*139*/0, 3326 0, 3327 0, 3328 MatFDColoringSetUp_SeqXAIJ, 3329 MatFindOffBlockDiagonalEntries_SeqAIJ 3330 }; 3331 3332 #undef __FUNCT__ 3333 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3334 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3335 { 3336 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3337 PetscInt i,nz,n; 3338 3339 PetscFunctionBegin; 3340 nz = aij->maxnz; 3341 n = mat->rmap->n; 3342 for (i=0; i<nz; i++) { 3343 aij->j[i] = indices[i]; 3344 } 3345 aij->nz = nz; 3346 for (i=0; i<n; i++) { 3347 aij->ilen[i] = aij->imax[i]; 3348 } 3349 PetscFunctionReturn(0); 3350 } 3351 3352 #undef __FUNCT__ 3353 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3354 /*@ 3355 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3356 in the matrix. 3357 3358 Input Parameters: 3359 + mat - the SeqAIJ matrix 3360 - indices - the column indices 3361 3362 Level: advanced 3363 3364 Notes: 3365 This can be called if you have precomputed the nonzero structure of the 3366 matrix and want to provide it to the matrix object to improve the performance 3367 of the MatSetValues() operation. 3368 3369 You MUST have set the correct numbers of nonzeros per row in the call to 3370 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3371 3372 MUST be called before any calls to MatSetValues(); 3373 3374 The indices should start with zero, not one. 3375 3376 @*/ 3377 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3378 { 3379 PetscErrorCode ierr; 3380 3381 PetscFunctionBegin; 3382 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3383 PetscValidPointer(indices,2); 3384 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3385 PetscFunctionReturn(0); 3386 } 3387 3388 /* ----------------------------------------------------------------------------------------*/ 3389 3390 #undef __FUNCT__ 3391 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3392 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3393 { 3394 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3395 PetscErrorCode ierr; 3396 size_t nz = aij->i[mat->rmap->n]; 3397 3398 PetscFunctionBegin; 3399 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3400 3401 /* allocate space for values if not already there */ 3402 if (!aij->saved_values) { 3403 ierr = PetscMalloc1((nz+1),&aij->saved_values);CHKERRQ(ierr); 3404 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3405 } 3406 3407 /* copy values over */ 3408 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3409 PetscFunctionReturn(0); 3410 } 3411 3412 #undef __FUNCT__ 3413 #define __FUNCT__ "MatStoreValues" 3414 /*@ 3415 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3416 example, reuse of the linear part of a Jacobian, while recomputing the 3417 nonlinear portion. 3418 3419 Collect on Mat 3420 3421 Input Parameters: 3422 . mat - the matrix (currently only AIJ matrices support this option) 3423 3424 Level: advanced 3425 3426 Common Usage, with SNESSolve(): 3427 $ Create Jacobian matrix 3428 $ Set linear terms into matrix 3429 $ Apply boundary conditions to matrix, at this time matrix must have 3430 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3431 $ boundary conditions again will not change the nonzero structure 3432 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3433 $ ierr = MatStoreValues(mat); 3434 $ Call SNESSetJacobian() with matrix 3435 $ In your Jacobian routine 3436 $ ierr = MatRetrieveValues(mat); 3437 $ Set nonlinear terms in matrix 3438 3439 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3440 $ // build linear portion of Jacobian 3441 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3442 $ ierr = MatStoreValues(mat); 3443 $ loop over nonlinear iterations 3444 $ ierr = MatRetrieveValues(mat); 3445 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3446 $ // call MatAssemblyBegin/End() on matrix 3447 $ Solve linear system with Jacobian 3448 $ endloop 3449 3450 Notes: 3451 Matrix must already be assemblied before calling this routine 3452 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3453 calling this routine. 3454 3455 When this is called multiple times it overwrites the previous set of stored values 3456 and does not allocated additional space. 3457 3458 .seealso: MatRetrieveValues() 3459 3460 @*/ 3461 PetscErrorCode MatStoreValues(Mat mat) 3462 { 3463 PetscErrorCode ierr; 3464 3465 PetscFunctionBegin; 3466 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3467 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3468 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3469 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3470 PetscFunctionReturn(0); 3471 } 3472 3473 #undef __FUNCT__ 3474 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3475 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3476 { 3477 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3478 PetscErrorCode ierr; 3479 PetscInt nz = aij->i[mat->rmap->n]; 3480 3481 PetscFunctionBegin; 3482 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3483 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3484 /* copy values over */ 3485 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3486 PetscFunctionReturn(0); 3487 } 3488 3489 #undef __FUNCT__ 3490 #define __FUNCT__ "MatRetrieveValues" 3491 /*@ 3492 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3493 example, reuse of the linear part of a Jacobian, while recomputing the 3494 nonlinear portion. 3495 3496 Collect on Mat 3497 3498 Input Parameters: 3499 . mat - the matrix (currently on AIJ matrices support this option) 3500 3501 Level: advanced 3502 3503 .seealso: MatStoreValues() 3504 3505 @*/ 3506 PetscErrorCode MatRetrieveValues(Mat mat) 3507 { 3508 PetscErrorCode ierr; 3509 3510 PetscFunctionBegin; 3511 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3512 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3513 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3514 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3515 PetscFunctionReturn(0); 3516 } 3517 3518 3519 /* --------------------------------------------------------------------------------*/ 3520 #undef __FUNCT__ 3521 #define __FUNCT__ "MatCreateSeqAIJ" 3522 /*@C 3523 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3524 (the default parallel PETSc format). For good matrix assembly performance 3525 the user should preallocate the matrix storage by setting the parameter nz 3526 (or the array nnz). By setting these parameters accurately, performance 3527 during matrix assembly can be increased by more than a factor of 50. 3528 3529 Collective on MPI_Comm 3530 3531 Input Parameters: 3532 + comm - MPI communicator, set to PETSC_COMM_SELF 3533 . m - number of rows 3534 . n - number of columns 3535 . nz - number of nonzeros per row (same for all rows) 3536 - nnz - array containing the number of nonzeros in the various rows 3537 (possibly different for each row) or NULL 3538 3539 Output Parameter: 3540 . A - the matrix 3541 3542 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3543 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3544 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3545 3546 Notes: 3547 If nnz is given then nz is ignored 3548 3549 The AIJ format (also called the Yale sparse matrix format or 3550 compressed row storage), is fully compatible with standard Fortran 77 3551 storage. That is, the stored row and column indices can begin at 3552 either one (as in Fortran) or zero. See the users' manual for details. 3553 3554 Specify the preallocated storage with either nz or nnz (not both). 3555 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3556 allocation. For large problems you MUST preallocate memory or you 3557 will get TERRIBLE performance, see the users' manual chapter on matrices. 3558 3559 By default, this format uses inodes (identical nodes) when possible, to 3560 improve numerical efficiency of matrix-vector products and solves. We 3561 search for consecutive rows with the same nonzero structure, thereby 3562 reusing matrix information to achieve increased efficiency. 3563 3564 Options Database Keys: 3565 + -mat_no_inode - Do not use inodes 3566 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3567 3568 Level: intermediate 3569 3570 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3571 3572 @*/ 3573 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3574 { 3575 PetscErrorCode ierr; 3576 3577 PetscFunctionBegin; 3578 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3579 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3580 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3581 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3582 PetscFunctionReturn(0); 3583 } 3584 3585 #undef __FUNCT__ 3586 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3587 /*@C 3588 MatSeqAIJSetPreallocation - For good matrix assembly performance 3589 the user should preallocate the matrix storage by setting the parameter nz 3590 (or the array nnz). By setting these parameters accurately, performance 3591 during matrix assembly can be increased by more than a factor of 50. 3592 3593 Collective on MPI_Comm 3594 3595 Input Parameters: 3596 + B - The matrix-free 3597 . nz - number of nonzeros per row (same for all rows) 3598 - nnz - array containing the number of nonzeros in the various rows 3599 (possibly different for each row) or NULL 3600 3601 Notes: 3602 If nnz is given then nz is ignored 3603 3604 The AIJ format (also called the Yale sparse matrix format or 3605 compressed row storage), is fully compatible with standard Fortran 77 3606 storage. That is, the stored row and column indices can begin at 3607 either one (as in Fortran) or zero. See the users' manual for details. 3608 3609 Specify the preallocated storage with either nz or nnz (not both). 3610 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3611 allocation. For large problems you MUST preallocate memory or you 3612 will get TERRIBLE performance, see the users' manual chapter on matrices. 3613 3614 You can call MatGetInfo() to get information on how effective the preallocation was; 3615 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3616 You can also run with the option -info and look for messages with the string 3617 malloc in them to see if additional memory allocation was needed. 3618 3619 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3620 entries or columns indices 3621 3622 By default, this format uses inodes (identical nodes) when possible, to 3623 improve numerical efficiency of matrix-vector products and solves. We 3624 search for consecutive rows with the same nonzero structure, thereby 3625 reusing matrix information to achieve increased efficiency. 3626 3627 Options Database Keys: 3628 + -mat_no_inode - Do not use inodes 3629 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3630 - -mat_aij_oneindex - Internally use indexing starting at 1 3631 rather than 0. Note that when calling MatSetValues(), 3632 the user still MUST index entries starting at 0! 3633 3634 Level: intermediate 3635 3636 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3637 3638 @*/ 3639 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3640 { 3641 PetscErrorCode ierr; 3642 3643 PetscFunctionBegin; 3644 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3645 PetscValidType(B,1); 3646 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3647 PetscFunctionReturn(0); 3648 } 3649 3650 #undef __FUNCT__ 3651 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3652 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3653 { 3654 Mat_SeqAIJ *b; 3655 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3656 PetscErrorCode ierr; 3657 PetscInt i; 3658 3659 PetscFunctionBegin; 3660 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3661 if (nz == MAT_SKIP_ALLOCATION) { 3662 skipallocation = PETSC_TRUE; 3663 nz = 0; 3664 } 3665 3666 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3667 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3668 3669 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3670 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3671 if (nnz) { 3672 for (i=0; i<B->rmap->n; i++) { 3673 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]); 3674 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); 3675 } 3676 } 3677 3678 B->preallocated = PETSC_TRUE; 3679 3680 b = (Mat_SeqAIJ*)B->data; 3681 3682 if (!skipallocation) { 3683 if (!b->imax) { 3684 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3685 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3686 } 3687 if (!nnz) { 3688 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3689 else if (nz < 0) nz = 1; 3690 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3691 nz = nz*B->rmap->n; 3692 } else { 3693 nz = 0; 3694 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3695 } 3696 /* b->ilen will count nonzeros in each row so far. */ 3697 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3698 3699 /* allocate the matrix space */ 3700 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3701 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3702 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3703 b->i[0] = 0; 3704 for (i=1; i<B->rmap->n+1; i++) { 3705 b->i[i] = b->i[i-1] + b->imax[i-1]; 3706 } 3707 b->singlemalloc = PETSC_TRUE; 3708 b->free_a = PETSC_TRUE; 3709 b->free_ij = PETSC_TRUE; 3710 #if defined(PETSC_THREADCOMM_ACTIVE) 3711 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3712 #endif 3713 } else { 3714 b->free_a = PETSC_FALSE; 3715 b->free_ij = PETSC_FALSE; 3716 } 3717 3718 b->nz = 0; 3719 b->maxnz = nz; 3720 B->info.nz_unneeded = (double)b->maxnz; 3721 if (realalloc) { 3722 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3723 } 3724 PetscFunctionReturn(0); 3725 } 3726 3727 #undef __FUNCT__ 3728 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3729 /*@ 3730 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3731 3732 Input Parameters: 3733 + B - the matrix 3734 . i - the indices into j for the start of each row (starts with zero) 3735 . j - the column indices for each row (starts with zero) these must be sorted for each row 3736 - v - optional values in the matrix 3737 3738 Level: developer 3739 3740 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3741 3742 .keywords: matrix, aij, compressed row, sparse, sequential 3743 3744 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3745 @*/ 3746 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3747 { 3748 PetscErrorCode ierr; 3749 3750 PetscFunctionBegin; 3751 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3752 PetscValidType(B,1); 3753 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3754 PetscFunctionReturn(0); 3755 } 3756 3757 #undef __FUNCT__ 3758 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3759 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3760 { 3761 PetscInt i; 3762 PetscInt m,n; 3763 PetscInt nz; 3764 PetscInt *nnz, nz_max = 0; 3765 PetscScalar *values; 3766 PetscErrorCode ierr; 3767 3768 PetscFunctionBegin; 3769 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3770 3771 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3772 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3773 3774 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3775 ierr = PetscMalloc1((m+1), &nnz);CHKERRQ(ierr); 3776 for (i = 0; i < m; i++) { 3777 nz = Ii[i+1]- Ii[i]; 3778 nz_max = PetscMax(nz_max, nz); 3779 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3780 nnz[i] = nz; 3781 } 3782 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3783 ierr = PetscFree(nnz);CHKERRQ(ierr); 3784 3785 if (v) { 3786 values = (PetscScalar*) v; 3787 } else { 3788 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3789 } 3790 3791 for (i = 0; i < m; i++) { 3792 nz = Ii[i+1] - Ii[i]; 3793 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3794 } 3795 3796 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3797 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3798 3799 if (!v) { 3800 ierr = PetscFree(values);CHKERRQ(ierr); 3801 } 3802 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3803 PetscFunctionReturn(0); 3804 } 3805 3806 #include <../src/mat/impls/dense/seq/dense.h> 3807 #include <petsc-private/kernels/petscaxpy.h> 3808 3809 #undef __FUNCT__ 3810 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3811 /* 3812 Computes (B'*A')' since computing B*A directly is untenable 3813 3814 n p p 3815 ( ) ( ) ( ) 3816 m ( A ) * n ( B ) = m ( C ) 3817 ( ) ( ) ( ) 3818 3819 */ 3820 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3821 { 3822 PetscErrorCode ierr; 3823 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3824 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3825 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3826 PetscInt i,n,m,q,p; 3827 const PetscInt *ii,*idx; 3828 const PetscScalar *b,*a,*a_q; 3829 PetscScalar *c,*c_q; 3830 3831 PetscFunctionBegin; 3832 m = A->rmap->n; 3833 n = A->cmap->n; 3834 p = B->cmap->n; 3835 a = sub_a->v; 3836 b = sub_b->a; 3837 c = sub_c->v; 3838 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3839 3840 ii = sub_b->i; 3841 idx = sub_b->j; 3842 for (i=0; i<n; i++) { 3843 q = ii[i+1] - ii[i]; 3844 while (q-->0) { 3845 c_q = c + m*(*idx); 3846 a_q = a + m*i; 3847 PetscKernelAXPY(c_q,*b,a_q,m); 3848 idx++; 3849 b++; 3850 } 3851 } 3852 PetscFunctionReturn(0); 3853 } 3854 3855 #undef __FUNCT__ 3856 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 3857 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3858 { 3859 PetscErrorCode ierr; 3860 PetscInt m=A->rmap->n,n=B->cmap->n; 3861 Mat Cmat; 3862 3863 PetscFunctionBegin; 3864 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); 3865 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3866 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3867 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3868 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3869 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3870 3871 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3872 3873 *C = Cmat; 3874 PetscFunctionReturn(0); 3875 } 3876 3877 /* ----------------------------------------------------------------*/ 3878 #undef __FUNCT__ 3879 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 3880 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3881 { 3882 PetscErrorCode ierr; 3883 3884 PetscFunctionBegin; 3885 if (scall == MAT_INITIAL_MATRIX) { 3886 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3887 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3888 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3889 } 3890 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3891 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3892 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3893 PetscFunctionReturn(0); 3894 } 3895 3896 3897 /*MC 3898 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3899 based on compressed sparse row format. 3900 3901 Options Database Keys: 3902 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3903 3904 Level: beginner 3905 3906 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3907 M*/ 3908 3909 /*MC 3910 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3911 3912 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3913 and MATMPIAIJ otherwise. As a result, for single process communicators, 3914 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3915 for communicators controlling multiple processes. It is recommended that you call both of 3916 the above preallocation routines for simplicity. 3917 3918 Options Database Keys: 3919 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3920 3921 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 3922 enough exist. 3923 3924 Level: beginner 3925 3926 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3927 M*/ 3928 3929 /*MC 3930 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3931 3932 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3933 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3934 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3935 for communicators controlling multiple processes. It is recommended that you call both of 3936 the above preallocation routines for simplicity. 3937 3938 Options Database Keys: 3939 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3940 3941 Level: beginner 3942 3943 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3944 M*/ 3945 3946 #if defined(PETSC_HAVE_PASTIX) 3947 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 3948 #endif 3949 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 3950 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 3951 #endif 3952 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3953 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 3954 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 3955 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 3956 #if defined(PETSC_HAVE_MUMPS) 3957 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 3958 #endif 3959 #if defined(PETSC_HAVE_SUPERLU) 3960 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 3961 #endif 3962 #if defined(PETSC_HAVE_MKL_PARDISO) 3963 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat,MatFactorType,Mat*); 3964 #endif 3965 #if defined(PETSC_HAVE_SUPERLU_DIST) 3966 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 3967 #endif 3968 #if defined(PETSC_HAVE_SUITESPARSE) 3969 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 3970 #endif 3971 #if defined(PETSC_HAVE_SUITESPARSE) 3972 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 3973 #endif 3974 #if defined(PETSC_HAVE_SUITESPARSE) 3975 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_klu(Mat,MatFactorType,Mat*); 3976 #endif 3977 #if defined(PETSC_HAVE_LUSOL) 3978 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 3979 #endif 3980 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3981 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 3982 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 3983 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 3984 #endif 3985 #if defined(PETSC_HAVE_CLIQUE) 3986 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 3987 #endif 3988 3989 3990 #undef __FUNCT__ 3991 #define __FUNCT__ "MatSeqAIJGetArray" 3992 /*@C 3993 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 3994 3995 Not Collective 3996 3997 Input Parameter: 3998 . mat - a MATSEQDENSE matrix 3999 4000 Output Parameter: 4001 . array - pointer to the data 4002 4003 Level: intermediate 4004 4005 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4006 @*/ 4007 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4008 { 4009 PetscErrorCode ierr; 4010 4011 PetscFunctionBegin; 4012 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4013 PetscFunctionReturn(0); 4014 } 4015 4016 #undef __FUNCT__ 4017 #define __FUNCT__ "MatSeqAIJRestoreArray" 4018 /*@C 4019 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4020 4021 Not Collective 4022 4023 Input Parameters: 4024 . mat - a MATSEQDENSE matrix 4025 . array - pointer to the data 4026 4027 Level: intermediate 4028 4029 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4030 @*/ 4031 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4032 { 4033 PetscErrorCode ierr; 4034 4035 PetscFunctionBegin; 4036 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4037 PetscFunctionReturn(0); 4038 } 4039 4040 #undef __FUNCT__ 4041 #define __FUNCT__ "MatCreate_SeqAIJ" 4042 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4043 { 4044 Mat_SeqAIJ *b; 4045 PetscErrorCode ierr; 4046 PetscMPIInt size; 4047 4048 PetscFunctionBegin; 4049 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4050 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4051 4052 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4053 4054 B->data = (void*)b; 4055 4056 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4057 4058 b->row = 0; 4059 b->col = 0; 4060 b->icol = 0; 4061 b->reallocs = 0; 4062 b->ignorezeroentries = PETSC_FALSE; 4063 b->roworiented = PETSC_TRUE; 4064 b->nonew = 0; 4065 b->diag = 0; 4066 b->solve_work = 0; 4067 B->spptr = 0; 4068 b->saved_values = 0; 4069 b->idiag = 0; 4070 b->mdiag = 0; 4071 b->ssor_work = 0; 4072 b->omega = 1.0; 4073 b->fshift = 0.0; 4074 b->idiagvalid = PETSC_FALSE; 4075 b->ibdiagvalid = PETSC_FALSE; 4076 b->keepnonzeropattern = PETSC_FALSE; 4077 b->xtoy = 0; 4078 b->XtoY = 0; 4079 4080 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4081 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4082 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4083 4084 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4085 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4086 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4087 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4088 #endif 4089 #if defined(PETSC_HAVE_PASTIX) 4090 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4091 #endif 4092 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4093 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4094 #endif 4095 #if defined(PETSC_HAVE_SUPERLU) 4096 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4097 #endif 4098 #if defined(PETSC_HAVE_MKL_PARDISO) 4099 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mkl_pardiso_C",MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 4100 #endif 4101 #if defined(PETSC_HAVE_SUPERLU_DIST) 4102 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4103 #endif 4104 #if defined(PETSC_HAVE_MUMPS) 4105 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4106 #endif 4107 #if defined(PETSC_HAVE_SUITESPARSE) 4108 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4109 #endif 4110 #if defined(PETSC_HAVE_SUITESPARSE) 4111 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4112 #endif 4113 #if defined(PETSC_HAVE_SUITESPARSE) 4114 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_klu_C",MatGetFactor_seqaij_klu);CHKERRQ(ierr); 4115 #endif 4116 #if defined(PETSC_HAVE_LUSOL) 4117 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4118 #endif 4119 #if defined(PETSC_HAVE_CLIQUE) 4120 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4121 #endif 4122 4123 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4124 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4125 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4126 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4127 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4128 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4129 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4130 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4131 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4132 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4133 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4134 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4135 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4136 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4137 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4138 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4139 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4140 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4141 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4142 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4143 PetscFunctionReturn(0); 4144 } 4145 4146 #undef __FUNCT__ 4147 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4148 /* 4149 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4150 */ 4151 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4152 { 4153 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4154 PetscErrorCode ierr; 4155 PetscInt i,m = A->rmap->n; 4156 4157 PetscFunctionBegin; 4158 c = (Mat_SeqAIJ*)C->data; 4159 4160 C->factortype = A->factortype; 4161 c->row = 0; 4162 c->col = 0; 4163 c->icol = 0; 4164 c->reallocs = 0; 4165 4166 C->assembled = PETSC_TRUE; 4167 4168 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4169 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4170 4171 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4172 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4173 for (i=0; i<m; i++) { 4174 c->imax[i] = a->imax[i]; 4175 c->ilen[i] = a->ilen[i]; 4176 } 4177 4178 /* allocate the matrix space */ 4179 if (mallocmatspace) { 4180 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4181 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4182 4183 c->singlemalloc = PETSC_TRUE; 4184 4185 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4186 if (m > 0) { 4187 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4188 if (cpvalues == MAT_COPY_VALUES) { 4189 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4190 } else { 4191 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4192 } 4193 } 4194 } 4195 4196 c->ignorezeroentries = a->ignorezeroentries; 4197 c->roworiented = a->roworiented; 4198 c->nonew = a->nonew; 4199 if (a->diag) { 4200 ierr = PetscMalloc1((m+1),&c->diag);CHKERRQ(ierr); 4201 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4202 for (i=0; i<m; i++) { 4203 c->diag[i] = a->diag[i]; 4204 } 4205 } else c->diag = 0; 4206 4207 c->solve_work = 0; 4208 c->saved_values = 0; 4209 c->idiag = 0; 4210 c->ssor_work = 0; 4211 c->keepnonzeropattern = a->keepnonzeropattern; 4212 c->free_a = PETSC_TRUE; 4213 c->free_ij = PETSC_TRUE; 4214 c->xtoy = 0; 4215 c->XtoY = 0; 4216 4217 c->rmax = a->rmax; 4218 c->nz = a->nz; 4219 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4220 C->preallocated = PETSC_TRUE; 4221 4222 c->compressedrow.use = a->compressedrow.use; 4223 c->compressedrow.nrows = a->compressedrow.nrows; 4224 if (a->compressedrow.use) { 4225 i = a->compressedrow.nrows; 4226 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4227 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4228 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4229 } else { 4230 c->compressedrow.use = PETSC_FALSE; 4231 c->compressedrow.i = NULL; 4232 c->compressedrow.rindex = NULL; 4233 } 4234 C->nonzerostate = A->nonzerostate; 4235 4236 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4237 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4238 PetscFunctionReturn(0); 4239 } 4240 4241 #undef __FUNCT__ 4242 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4243 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4244 { 4245 PetscErrorCode ierr; 4246 4247 PetscFunctionBegin; 4248 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4249 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4250 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4251 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4252 } 4253 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4254 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4255 PetscFunctionReturn(0); 4256 } 4257 4258 #undef __FUNCT__ 4259 #define __FUNCT__ "MatLoad_SeqAIJ" 4260 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4261 { 4262 Mat_SeqAIJ *a; 4263 PetscErrorCode ierr; 4264 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4265 int fd; 4266 PetscMPIInt size; 4267 MPI_Comm comm; 4268 PetscInt bs = 1; 4269 4270 PetscFunctionBegin; 4271 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4272 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4273 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4274 4275 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4276 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4277 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4278 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4279 4280 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4281 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4282 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4283 M = header[1]; N = header[2]; nz = header[3]; 4284 4285 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4286 4287 /* read in row lengths */ 4288 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4289 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4290 4291 /* check if sum of rowlengths is same as nz */ 4292 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4293 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); 4294 4295 /* set global size if not set already*/ 4296 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4297 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4298 } else { 4299 /* if sizes and type are already set, check if the vector global sizes are correct */ 4300 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4301 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4302 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4303 } 4304 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); 4305 } 4306 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4307 a = (Mat_SeqAIJ*)newMat->data; 4308 4309 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4310 4311 /* read in nonzero values */ 4312 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4313 4314 /* set matrix "i" values */ 4315 a->i[0] = 0; 4316 for (i=1; i<= M; i++) { 4317 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4318 a->ilen[i-1] = rowlengths[i-1]; 4319 } 4320 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4321 4322 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4323 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4324 PetscFunctionReturn(0); 4325 } 4326 4327 #undef __FUNCT__ 4328 #define __FUNCT__ "MatEqual_SeqAIJ" 4329 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4330 { 4331 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4332 PetscErrorCode ierr; 4333 #if defined(PETSC_USE_COMPLEX) 4334 PetscInt k; 4335 #endif 4336 4337 PetscFunctionBegin; 4338 /* If the matrix dimensions are not equal,or no of nonzeros */ 4339 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4340 *flg = PETSC_FALSE; 4341 PetscFunctionReturn(0); 4342 } 4343 4344 /* if the a->i are the same */ 4345 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4346 if (!*flg) PetscFunctionReturn(0); 4347 4348 /* if a->j are the same */ 4349 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4350 if (!*flg) PetscFunctionReturn(0); 4351 4352 /* if a->a are the same */ 4353 #if defined(PETSC_USE_COMPLEX) 4354 for (k=0; k<a->nz; k++) { 4355 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4356 *flg = PETSC_FALSE; 4357 PetscFunctionReturn(0); 4358 } 4359 } 4360 #else 4361 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4362 #endif 4363 PetscFunctionReturn(0); 4364 } 4365 4366 #undef __FUNCT__ 4367 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4368 /*@ 4369 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4370 provided by the user. 4371 4372 Collective on MPI_Comm 4373 4374 Input Parameters: 4375 + comm - must be an MPI communicator of size 1 4376 . m - number of rows 4377 . n - number of columns 4378 . i - row indices 4379 . j - column indices 4380 - a - matrix values 4381 4382 Output Parameter: 4383 . mat - the matrix 4384 4385 Level: intermediate 4386 4387 Notes: 4388 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4389 once the matrix is destroyed and not before 4390 4391 You cannot set new nonzero locations into this matrix, that will generate an error. 4392 4393 The i and j indices are 0 based 4394 4395 The format which is used for the sparse matrix input, is equivalent to a 4396 row-major ordering.. i.e for the following matrix, the input data expected is 4397 as shown: 4398 4399 1 0 0 4400 2 0 3 4401 4 5 6 4402 4403 i = {0,1,3,6} [size = nrow+1 = 3+1] 4404 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4405 v = {1,2,3,4,5,6} [size = nz = 6] 4406 4407 4408 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4409 4410 @*/ 4411 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4412 { 4413 PetscErrorCode ierr; 4414 PetscInt ii; 4415 Mat_SeqAIJ *aij; 4416 #if defined(PETSC_USE_DEBUG) 4417 PetscInt jj; 4418 #endif 4419 4420 PetscFunctionBegin; 4421 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4422 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4423 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4424 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4425 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4426 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4427 aij = (Mat_SeqAIJ*)(*mat)->data; 4428 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4429 4430 aij->i = i; 4431 aij->j = j; 4432 aij->a = a; 4433 aij->singlemalloc = PETSC_FALSE; 4434 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4435 aij->free_a = PETSC_FALSE; 4436 aij->free_ij = PETSC_FALSE; 4437 4438 for (ii=0; ii<m; ii++) { 4439 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4440 #if defined(PETSC_USE_DEBUG) 4441 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]); 4442 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4443 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); 4444 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); 4445 } 4446 #endif 4447 } 4448 #if defined(PETSC_USE_DEBUG) 4449 for (ii=0; ii<aij->i[m]; ii++) { 4450 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4451 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]); 4452 } 4453 #endif 4454 4455 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4456 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4457 PetscFunctionReturn(0); 4458 } 4459 #undef __FUNCT__ 4460 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4461 /*@C 4462 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4463 provided by the user. 4464 4465 Collective on MPI_Comm 4466 4467 Input Parameters: 4468 + comm - must be an MPI communicator of size 1 4469 . m - number of rows 4470 . n - number of columns 4471 . i - row indices 4472 . j - column indices 4473 . a - matrix values 4474 . nz - number of nonzeros 4475 - idx - 0 or 1 based 4476 4477 Output Parameter: 4478 . mat - the matrix 4479 4480 Level: intermediate 4481 4482 Notes: 4483 The i and j indices are 0 based 4484 4485 The format which is used for the sparse matrix input, is equivalent to a 4486 row-major ordering.. i.e for the following matrix, the input data expected is 4487 as shown: 4488 4489 1 0 0 4490 2 0 3 4491 4 5 6 4492 4493 i = {0,1,1,2,2,2} 4494 j = {0,0,2,0,1,2} 4495 v = {1,2,3,4,5,6} 4496 4497 4498 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4499 4500 @*/ 4501 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4502 { 4503 PetscErrorCode ierr; 4504 PetscInt ii, *nnz, one = 1,row,col; 4505 4506 4507 PetscFunctionBegin; 4508 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4509 for (ii = 0; ii < nz; ii++) { 4510 nnz[i[ii] - !!idx] += 1; 4511 } 4512 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4513 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4514 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4515 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4516 for (ii = 0; ii < nz; ii++) { 4517 if (idx) { 4518 row = i[ii] - 1; 4519 col = j[ii] - 1; 4520 } else { 4521 row = i[ii]; 4522 col = j[ii]; 4523 } 4524 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4525 } 4526 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4527 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4528 ierr = PetscFree(nnz);CHKERRQ(ierr); 4529 PetscFunctionReturn(0); 4530 } 4531 4532 #undef __FUNCT__ 4533 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4534 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4535 { 4536 PetscErrorCode ierr; 4537 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4538 4539 PetscFunctionBegin; 4540 if (coloring->ctype == IS_COLORING_GLOBAL) { 4541 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4542 a->coloring = coloring; 4543 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4544 PetscInt i,*larray; 4545 ISColoring ocoloring; 4546 ISColoringValue *colors; 4547 4548 /* set coloring for diagonal portion */ 4549 ierr = PetscMalloc1(A->cmap->n,&larray);CHKERRQ(ierr); 4550 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4551 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4552 ierr = PetscMalloc1(A->cmap->n,&colors);CHKERRQ(ierr); 4553 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4554 ierr = PetscFree(larray);CHKERRQ(ierr); 4555 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4556 a->coloring = ocoloring; 4557 } 4558 PetscFunctionReturn(0); 4559 } 4560 4561 #undef __FUNCT__ 4562 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4563 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4564 { 4565 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4566 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4567 MatScalar *v = a->a; 4568 PetscScalar *values = (PetscScalar*)advalues; 4569 ISColoringValue *color; 4570 4571 PetscFunctionBegin; 4572 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4573 color = a->coloring->colors; 4574 /* loop over rows */ 4575 for (i=0; i<m; i++) { 4576 nz = ii[i+1] - ii[i]; 4577 /* loop over columns putting computed value into matrix */ 4578 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4579 values += nl; /* jump to next row of derivatives */ 4580 } 4581 PetscFunctionReturn(0); 4582 } 4583 4584 #undef __FUNCT__ 4585 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4586 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4587 { 4588 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4589 PetscErrorCode ierr; 4590 4591 PetscFunctionBegin; 4592 a->idiagvalid = PETSC_FALSE; 4593 a->ibdiagvalid = PETSC_FALSE; 4594 4595 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4596 PetscFunctionReturn(0); 4597 } 4598 4599 /* 4600 Special version for direct calls from Fortran 4601 */ 4602 #include <petsc-private/fortranimpl.h> 4603 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4604 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4605 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4606 #define matsetvaluesseqaij_ matsetvaluesseqaij 4607 #endif 4608 4609 /* Change these macros so can be used in void function */ 4610 #undef CHKERRQ 4611 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4612 #undef SETERRQ2 4613 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4614 #undef SETERRQ3 4615 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4616 4617 #undef __FUNCT__ 4618 #define __FUNCT__ "matsetvaluesseqaij_" 4619 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) 4620 { 4621 Mat A = *AA; 4622 PetscInt m = *mm, n = *nn; 4623 InsertMode is = *isis; 4624 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4625 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4626 PetscInt *imax,*ai,*ailen; 4627 PetscErrorCode ierr; 4628 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4629 MatScalar *ap,value,*aa; 4630 PetscBool ignorezeroentries = a->ignorezeroentries; 4631 PetscBool roworiented = a->roworiented; 4632 4633 PetscFunctionBegin; 4634 MatCheckPreallocated(A,1); 4635 imax = a->imax; 4636 ai = a->i; 4637 ailen = a->ilen; 4638 aj = a->j; 4639 aa = a->a; 4640 4641 for (k=0; k<m; k++) { /* loop over added rows */ 4642 row = im[k]; 4643 if (row < 0) continue; 4644 #if defined(PETSC_USE_DEBUG) 4645 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4646 #endif 4647 rp = aj + ai[row]; ap = aa + ai[row]; 4648 rmax = imax[row]; nrow = ailen[row]; 4649 low = 0; 4650 high = nrow; 4651 for (l=0; l<n; l++) { /* loop over added columns */ 4652 if (in[l] < 0) continue; 4653 #if defined(PETSC_USE_DEBUG) 4654 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4655 #endif 4656 col = in[l]; 4657 if (roworiented) value = v[l + k*n]; 4658 else value = v[k + l*m]; 4659 4660 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4661 4662 if (col <= lastcol) low = 0; 4663 else high = nrow; 4664 lastcol = col; 4665 while (high-low > 5) { 4666 t = (low+high)/2; 4667 if (rp[t] > col) high = t; 4668 else low = t; 4669 } 4670 for (i=low; i<high; i++) { 4671 if (rp[i] > col) break; 4672 if (rp[i] == col) { 4673 if (is == ADD_VALUES) ap[i] += value; 4674 else ap[i] = value; 4675 goto noinsert; 4676 } 4677 } 4678 if (value == 0.0 && ignorezeroentries) goto noinsert; 4679 if (nonew == 1) goto noinsert; 4680 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4681 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4682 N = nrow++ - 1; a->nz++; high++; 4683 /* shift up all the later entries in this row */ 4684 for (ii=N; ii>=i; ii--) { 4685 rp[ii+1] = rp[ii]; 4686 ap[ii+1] = ap[ii]; 4687 } 4688 rp[i] = col; 4689 ap[i] = value; 4690 A->nonzerostate++; 4691 noinsert:; 4692 low = i + 1; 4693 } 4694 ailen[row] = nrow; 4695 } 4696 PetscFunctionReturnVoid(); 4697 } 4698 4699 4700