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 = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2400 if (stride) { 2401 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2402 } else { 2403 first = 0; 2404 step = 0; 2405 } 2406 if (stride && step == 1) { 2407 /* special case of contiguous rows */ 2408 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2409 /* loop over new rows determining lens and starting points */ 2410 for (i=0; i<nrows; i++) { 2411 kstart = ai[irow[i]]; 2412 kend = kstart + ailen[irow[i]]; 2413 for (k=kstart; k<kend; k++) { 2414 if (aj[k] >= first) { 2415 starts[i] = k; 2416 break; 2417 } 2418 } 2419 sum = 0; 2420 while (k < kend) { 2421 if (aj[k++] >= first+ncols) break; 2422 sum++; 2423 } 2424 lens[i] = sum; 2425 } 2426 /* create submatrix */ 2427 if (scall == MAT_REUSE_MATRIX) { 2428 PetscInt n_cols,n_rows; 2429 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2430 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2431 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2432 C = *B; 2433 } else { 2434 PetscInt rbs,cbs; 2435 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2436 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2437 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2438 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2439 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2440 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2441 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2442 } 2443 c = (Mat_SeqAIJ*)C->data; 2444 2445 /* loop over rows inserting into submatrix */ 2446 a_new = c->a; 2447 j_new = c->j; 2448 i_new = c->i; 2449 2450 for (i=0; i<nrows; i++) { 2451 ii = starts[i]; 2452 lensi = lens[i]; 2453 for (k=0; k<lensi; k++) { 2454 *j_new++ = aj[ii+k] - first; 2455 } 2456 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2457 a_new += lensi; 2458 i_new[i+1] = i_new[i] + lensi; 2459 c->ilen[i] = lensi; 2460 } 2461 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2462 } else { 2463 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2464 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2465 ierr = PetscMalloc1((1+nrows),&lens);CHKERRQ(ierr); 2466 for (i=0; i<ncols; i++) { 2467 #if defined(PETSC_USE_DEBUG) 2468 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); 2469 #endif 2470 smap[icol[i]] = i+1; 2471 } 2472 2473 /* determine lens of each row */ 2474 for (i=0; i<nrows; i++) { 2475 kstart = ai[irow[i]]; 2476 kend = kstart + a->ilen[irow[i]]; 2477 lens[i] = 0; 2478 for (k=kstart; k<kend; k++) { 2479 if (smap[aj[k]]) { 2480 lens[i]++; 2481 } 2482 } 2483 } 2484 /* Create and fill new matrix */ 2485 if (scall == MAT_REUSE_MATRIX) { 2486 PetscBool equal; 2487 2488 c = (Mat_SeqAIJ*)((*B)->data); 2489 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2490 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2491 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2492 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2493 C = *B; 2494 } else { 2495 PetscInt rbs,cbs; 2496 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2497 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2498 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2499 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2500 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2501 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2502 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2503 } 2504 c = (Mat_SeqAIJ*)(C->data); 2505 for (i=0; i<nrows; i++) { 2506 row = irow[i]; 2507 kstart = ai[row]; 2508 kend = kstart + a->ilen[row]; 2509 mat_i = c->i[i]; 2510 mat_j = c->j + mat_i; 2511 mat_a = c->a + mat_i; 2512 mat_ilen = c->ilen + i; 2513 for (k=kstart; k<kend; k++) { 2514 if ((tcol=smap[a->j[k]])) { 2515 *mat_j++ = tcol - 1; 2516 *mat_a++ = a->a[k]; 2517 (*mat_ilen)++; 2518 2519 } 2520 } 2521 } 2522 /* Free work space */ 2523 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2524 ierr = PetscFree(smap);CHKERRQ(ierr); 2525 ierr = PetscFree(lens);CHKERRQ(ierr); 2526 } 2527 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2528 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2529 2530 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2531 *B = C; 2532 PetscFunctionReturn(0); 2533 } 2534 2535 #undef __FUNCT__ 2536 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 2537 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2538 { 2539 PetscErrorCode ierr; 2540 Mat B; 2541 2542 PetscFunctionBegin; 2543 if (scall == MAT_INITIAL_MATRIX) { 2544 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2545 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2546 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2547 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2548 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2549 *subMat = B; 2550 } else { 2551 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2552 } 2553 PetscFunctionReturn(0); 2554 } 2555 2556 #undef __FUNCT__ 2557 #define __FUNCT__ "MatILUFactor_SeqAIJ" 2558 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2559 { 2560 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2561 PetscErrorCode ierr; 2562 Mat outA; 2563 PetscBool row_identity,col_identity; 2564 2565 PetscFunctionBegin; 2566 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2567 2568 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2569 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2570 2571 outA = inA; 2572 outA->factortype = MAT_FACTOR_LU; 2573 2574 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2575 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2576 2577 a->row = row; 2578 2579 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2580 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2581 2582 a->col = col; 2583 2584 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2585 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2586 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2587 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2588 2589 if (!a->solve_work) { /* this matrix may have been factored before */ 2590 ierr = PetscMalloc1((inA->rmap->n+1),&a->solve_work);CHKERRQ(ierr); 2591 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2592 } 2593 2594 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2595 if (row_identity && col_identity) { 2596 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2597 } else { 2598 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2599 } 2600 PetscFunctionReturn(0); 2601 } 2602 2603 #undef __FUNCT__ 2604 #define __FUNCT__ "MatScale_SeqAIJ" 2605 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2606 { 2607 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2608 PetscScalar oalpha = alpha; 2609 PetscErrorCode ierr; 2610 PetscBLASInt one = 1,bnz; 2611 2612 PetscFunctionBegin; 2613 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2614 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2615 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2616 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2617 PetscFunctionReturn(0); 2618 } 2619 2620 #undef __FUNCT__ 2621 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 2622 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2623 { 2624 PetscErrorCode ierr; 2625 PetscInt i; 2626 2627 PetscFunctionBegin; 2628 if (scall == MAT_INITIAL_MATRIX) { 2629 ierr = PetscMalloc1((n+1),B);CHKERRQ(ierr); 2630 } 2631 2632 for (i=0; i<n; i++) { 2633 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2634 } 2635 PetscFunctionReturn(0); 2636 } 2637 2638 #undef __FUNCT__ 2639 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 2640 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2641 { 2642 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2643 PetscErrorCode ierr; 2644 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2645 const PetscInt *idx; 2646 PetscInt start,end,*ai,*aj; 2647 PetscBT table; 2648 2649 PetscFunctionBegin; 2650 m = A->rmap->n; 2651 ai = a->i; 2652 aj = a->j; 2653 2654 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2655 2656 ierr = PetscMalloc1((m+1),&nidx);CHKERRQ(ierr); 2657 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2658 2659 for (i=0; i<is_max; i++) { 2660 /* Initialize the two local arrays */ 2661 isz = 0; 2662 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2663 2664 /* Extract the indices, assume there can be duplicate entries */ 2665 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2666 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2667 2668 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2669 for (j=0; j<n; ++j) { 2670 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2671 } 2672 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2673 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2674 2675 k = 0; 2676 for (j=0; j<ov; j++) { /* for each overlap */ 2677 n = isz; 2678 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2679 row = nidx[k]; 2680 start = ai[row]; 2681 end = ai[row+1]; 2682 for (l = start; l<end; l++) { 2683 val = aj[l]; 2684 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2685 } 2686 } 2687 } 2688 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2689 } 2690 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2691 ierr = PetscFree(nidx);CHKERRQ(ierr); 2692 PetscFunctionReturn(0); 2693 } 2694 2695 /* -------------------------------------------------------------- */ 2696 #undef __FUNCT__ 2697 #define __FUNCT__ "MatPermute_SeqAIJ" 2698 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2699 { 2700 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2701 PetscErrorCode ierr; 2702 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2703 const PetscInt *row,*col; 2704 PetscInt *cnew,j,*lens; 2705 IS icolp,irowp; 2706 PetscInt *cwork = NULL; 2707 PetscScalar *vwork = NULL; 2708 2709 PetscFunctionBegin; 2710 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2711 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2712 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2713 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2714 2715 /* determine lengths of permuted rows */ 2716 ierr = PetscMalloc1((m+1),&lens);CHKERRQ(ierr); 2717 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2718 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2719 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2720 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2721 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2722 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2723 ierr = PetscFree(lens);CHKERRQ(ierr); 2724 2725 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2726 for (i=0; i<m; i++) { 2727 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2728 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2729 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2730 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2731 } 2732 ierr = PetscFree(cnew);CHKERRQ(ierr); 2733 2734 (*B)->assembled = PETSC_FALSE; 2735 2736 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2737 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2738 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2739 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2740 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2741 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2742 PetscFunctionReturn(0); 2743 } 2744 2745 #undef __FUNCT__ 2746 #define __FUNCT__ "MatCopy_SeqAIJ" 2747 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2748 { 2749 PetscErrorCode ierr; 2750 2751 PetscFunctionBegin; 2752 /* If the two matrices have the same copy implementation, use fast copy. */ 2753 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2754 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2755 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2756 2757 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"); 2758 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2759 } else { 2760 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2761 } 2762 PetscFunctionReturn(0); 2763 } 2764 2765 #undef __FUNCT__ 2766 #define __FUNCT__ "MatSetUp_SeqAIJ" 2767 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2768 { 2769 PetscErrorCode ierr; 2770 2771 PetscFunctionBegin; 2772 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2773 PetscFunctionReturn(0); 2774 } 2775 2776 #undef __FUNCT__ 2777 #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" 2778 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2779 { 2780 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2781 2782 PetscFunctionBegin; 2783 *array = a->a; 2784 PetscFunctionReturn(0); 2785 } 2786 2787 #undef __FUNCT__ 2788 #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" 2789 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2790 { 2791 PetscFunctionBegin; 2792 PetscFunctionReturn(0); 2793 } 2794 2795 /* 2796 Computes the number of nonzeros per row needed for preallocation when X and Y 2797 have different nonzero structure. 2798 */ 2799 #undef __FUNCT__ 2800 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 2801 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2802 { 2803 PetscInt i,m=Y->rmap->N; 2804 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2805 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2806 const PetscInt *xi = x->i,*yi = y->i; 2807 2808 PetscFunctionBegin; 2809 /* Set the number of nonzeros in the new matrix */ 2810 for (i=0; i<m; i++) { 2811 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2812 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2813 nnz[i] = 0; 2814 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2815 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 2816 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 2817 nnz[i]++; 2818 } 2819 for (; k<nzy; k++) nnz[i]++; 2820 } 2821 PetscFunctionReturn(0); 2822 } 2823 2824 #include <petsctime.h> 2825 #undef __FUNCT__ 2826 #define __FUNCT__ "MatAXPY_SeqAIJ" 2827 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2828 { 2829 PetscErrorCode ierr; 2830 PetscInt i; 2831 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2832 PetscBLASInt one=1,bnz; 2833 2834 PetscFunctionBegin; 2835 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2836 if (str == SAME_NONZERO_PATTERN) { 2837 PetscScalar alpha = a; 2838 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2839 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2840 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2841 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2842 if (y->xtoy && y->XtoY != X) { 2843 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2844 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2845 } 2846 if (!y->xtoy) { /* get xtoy */ 2847 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 2848 y->XtoY = X; 2849 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2850 } 2851 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2852 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2853 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); 2854 } else { 2855 Mat B; 2856 PetscInt *nnz; 2857 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2858 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2859 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2860 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2861 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2862 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2863 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2864 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2865 2866 PetscLogDouble t0,t1; 2867 ierr = PetscTime(&t0);CHKERRQ(ierr); 2868 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2869 ierr = PetscTime(&t1);CHKERRQ(ierr); 2870 printf("Time for aij MatAXPY_BasicWithPreallocation: %g\n",t1-t0); 2871 2872 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2873 ierr = PetscFree(nnz);CHKERRQ(ierr); 2874 } 2875 PetscFunctionReturn(0); 2876 } 2877 2878 #undef __FUNCT__ 2879 #define __FUNCT__ "MatConjugate_SeqAIJ" 2880 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2881 { 2882 #if defined(PETSC_USE_COMPLEX) 2883 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2884 PetscInt i,nz; 2885 PetscScalar *a; 2886 2887 PetscFunctionBegin; 2888 nz = aij->nz; 2889 a = aij->a; 2890 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2891 #else 2892 PetscFunctionBegin; 2893 #endif 2894 PetscFunctionReturn(0); 2895 } 2896 2897 #undef __FUNCT__ 2898 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 2899 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2900 { 2901 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2902 PetscErrorCode ierr; 2903 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2904 PetscReal atmp; 2905 PetscScalar *x; 2906 MatScalar *aa; 2907 2908 PetscFunctionBegin; 2909 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2910 aa = a->a; 2911 ai = a->i; 2912 aj = a->j; 2913 2914 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2915 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2916 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2917 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2918 for (i=0; i<m; i++) { 2919 ncols = ai[1] - ai[0]; ai++; 2920 x[i] = 0.0; 2921 for (j=0; j<ncols; j++) { 2922 atmp = PetscAbsScalar(*aa); 2923 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2924 aa++; aj++; 2925 } 2926 } 2927 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2928 PetscFunctionReturn(0); 2929 } 2930 2931 #undef __FUNCT__ 2932 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 2933 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2934 { 2935 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2936 PetscErrorCode ierr; 2937 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2938 PetscScalar *x; 2939 MatScalar *aa; 2940 2941 PetscFunctionBegin; 2942 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2943 aa = a->a; 2944 ai = a->i; 2945 aj = a->j; 2946 2947 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2948 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2949 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2950 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2951 for (i=0; i<m; i++) { 2952 ncols = ai[1] - ai[0]; ai++; 2953 if (ncols == A->cmap->n) { /* row is dense */ 2954 x[i] = *aa; if (idx) idx[i] = 0; 2955 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2956 x[i] = 0.0; 2957 if (idx) { 2958 idx[i] = 0; /* in case ncols is zero */ 2959 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2960 if (aj[j] > j) { 2961 idx[i] = j; 2962 break; 2963 } 2964 } 2965 } 2966 } 2967 for (j=0; j<ncols; j++) { 2968 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2969 aa++; aj++; 2970 } 2971 } 2972 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2973 PetscFunctionReturn(0); 2974 } 2975 2976 #undef __FUNCT__ 2977 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 2978 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2979 { 2980 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2981 PetscErrorCode ierr; 2982 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2983 PetscReal atmp; 2984 PetscScalar *x; 2985 MatScalar *aa; 2986 2987 PetscFunctionBegin; 2988 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2989 aa = a->a; 2990 ai = a->i; 2991 aj = a->j; 2992 2993 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2994 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2995 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2996 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); 2997 for (i=0; i<m; i++) { 2998 ncols = ai[1] - ai[0]; ai++; 2999 if (ncols) { 3000 /* Get first nonzero */ 3001 for (j = 0; j < ncols; j++) { 3002 atmp = PetscAbsScalar(aa[j]); 3003 if (atmp > 1.0e-12) { 3004 x[i] = atmp; 3005 if (idx) idx[i] = aj[j]; 3006 break; 3007 } 3008 } 3009 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3010 } else { 3011 x[i] = 0.0; if (idx) idx[i] = 0; 3012 } 3013 for (j = 0; j < ncols; j++) { 3014 atmp = PetscAbsScalar(*aa); 3015 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3016 aa++; aj++; 3017 } 3018 } 3019 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3020 PetscFunctionReturn(0); 3021 } 3022 3023 #undef __FUNCT__ 3024 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3025 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3026 { 3027 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3028 PetscErrorCode ierr; 3029 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3030 PetscScalar *x; 3031 MatScalar *aa; 3032 3033 PetscFunctionBegin; 3034 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3035 aa = a->a; 3036 ai = a->i; 3037 aj = a->j; 3038 3039 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3040 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3041 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3042 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3043 for (i=0; i<m; i++) { 3044 ncols = ai[1] - ai[0]; ai++; 3045 if (ncols == A->cmap->n) { /* row is dense */ 3046 x[i] = *aa; if (idx) idx[i] = 0; 3047 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3048 x[i] = 0.0; 3049 if (idx) { /* find first implicit 0.0 in the row */ 3050 idx[i] = 0; /* in case ncols is zero */ 3051 for (j=0; j<ncols; j++) { 3052 if (aj[j] > j) { 3053 idx[i] = j; 3054 break; 3055 } 3056 } 3057 } 3058 } 3059 for (j=0; j<ncols; j++) { 3060 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3061 aa++; aj++; 3062 } 3063 } 3064 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3065 PetscFunctionReturn(0); 3066 } 3067 3068 #include <petscblaslapack.h> 3069 #include <petsc-private/kernels/blockinvert.h> 3070 3071 #undef __FUNCT__ 3072 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3073 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3074 { 3075 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3076 PetscErrorCode ierr; 3077 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3078 MatScalar *diag,work[25],*v_work; 3079 PetscReal shift = 0.0; 3080 3081 PetscFunctionBegin; 3082 if (a->ibdiagvalid) { 3083 if (values) *values = a->ibdiag; 3084 PetscFunctionReturn(0); 3085 } 3086 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3087 if (!a->ibdiag) { 3088 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3089 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3090 } 3091 diag = a->ibdiag; 3092 if (values) *values = a->ibdiag; 3093 /* factor and invert each block */ 3094 switch (bs) { 3095 case 1: 3096 for (i=0; i<mbs; i++) { 3097 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3098 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3099 } 3100 break; 3101 case 2: 3102 for (i=0; i<mbs; i++) { 3103 ij[0] = 2*i; ij[1] = 2*i + 1; 3104 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3105 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3106 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3107 diag += 4; 3108 } 3109 break; 3110 case 3: 3111 for (i=0; i<mbs; i++) { 3112 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3113 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3114 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3115 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3116 diag += 9; 3117 } 3118 break; 3119 case 4: 3120 for (i=0; i<mbs; i++) { 3121 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3122 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3123 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3124 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3125 diag += 16; 3126 } 3127 break; 3128 case 5: 3129 for (i=0; i<mbs; i++) { 3130 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3131 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3132 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3133 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3134 diag += 25; 3135 } 3136 break; 3137 case 6: 3138 for (i=0; i<mbs; i++) { 3139 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; 3140 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3141 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3142 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3143 diag += 36; 3144 } 3145 break; 3146 case 7: 3147 for (i=0; i<mbs; i++) { 3148 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; 3149 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3150 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3151 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3152 diag += 49; 3153 } 3154 break; 3155 default: 3156 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3157 for (i=0; i<mbs; i++) { 3158 for (j=0; j<bs; j++) { 3159 IJ[j] = bs*i + j; 3160 } 3161 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3162 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3163 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3164 diag += bs2; 3165 } 3166 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3167 } 3168 a->ibdiagvalid = PETSC_TRUE; 3169 PetscFunctionReturn(0); 3170 } 3171 3172 #undef __FUNCT__ 3173 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3174 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3175 { 3176 PetscErrorCode ierr; 3177 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3178 PetscScalar a; 3179 PetscInt m,n,i,j,col; 3180 3181 PetscFunctionBegin; 3182 if (!x->assembled) { 3183 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3184 for (i=0; i<m; i++) { 3185 for (j=0; j<aij->imax[i]; j++) { 3186 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3187 col = (PetscInt)(n*PetscRealPart(a)); 3188 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3189 } 3190 } 3191 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3192 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3193 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3194 PetscFunctionReturn(0); 3195 } 3196 3197 /* -------------------------------------------------------------------*/ 3198 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3199 MatGetRow_SeqAIJ, 3200 MatRestoreRow_SeqAIJ, 3201 MatMult_SeqAIJ, 3202 /* 4*/ MatMultAdd_SeqAIJ, 3203 MatMultTranspose_SeqAIJ, 3204 MatMultTransposeAdd_SeqAIJ, 3205 0, 3206 0, 3207 0, 3208 /* 10*/ 0, 3209 MatLUFactor_SeqAIJ, 3210 0, 3211 MatSOR_SeqAIJ, 3212 MatTranspose_SeqAIJ, 3213 /*1 5*/ MatGetInfo_SeqAIJ, 3214 MatEqual_SeqAIJ, 3215 MatGetDiagonal_SeqAIJ, 3216 MatDiagonalScale_SeqAIJ, 3217 MatNorm_SeqAIJ, 3218 /* 20*/ 0, 3219 MatAssemblyEnd_SeqAIJ, 3220 MatSetOption_SeqAIJ, 3221 MatZeroEntries_SeqAIJ, 3222 /* 24*/ MatZeroRows_SeqAIJ, 3223 0, 3224 0, 3225 0, 3226 0, 3227 /* 29*/ MatSetUp_SeqAIJ, 3228 0, 3229 0, 3230 0, 3231 0, 3232 /* 34*/ MatDuplicate_SeqAIJ, 3233 0, 3234 0, 3235 MatILUFactor_SeqAIJ, 3236 0, 3237 /* 39*/ MatAXPY_SeqAIJ, 3238 MatGetSubMatrices_SeqAIJ, 3239 MatIncreaseOverlap_SeqAIJ, 3240 MatGetValues_SeqAIJ, 3241 MatCopy_SeqAIJ, 3242 /* 44*/ MatGetRowMax_SeqAIJ, 3243 MatScale_SeqAIJ, 3244 0, 3245 MatDiagonalSet_SeqAIJ, 3246 MatZeroRowsColumns_SeqAIJ, 3247 /* 49*/ MatSetRandom_SeqAIJ, 3248 MatGetRowIJ_SeqAIJ, 3249 MatRestoreRowIJ_SeqAIJ, 3250 MatGetColumnIJ_SeqAIJ, 3251 MatRestoreColumnIJ_SeqAIJ, 3252 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3253 0, 3254 0, 3255 MatPermute_SeqAIJ, 3256 0, 3257 /* 59*/ 0, 3258 MatDestroy_SeqAIJ, 3259 MatView_SeqAIJ, 3260 0, 3261 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3262 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3263 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3264 0, 3265 0, 3266 0, 3267 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3268 MatGetRowMinAbs_SeqAIJ, 3269 0, 3270 MatSetColoring_SeqAIJ, 3271 0, 3272 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3273 MatFDColoringApply_AIJ, 3274 0, 3275 0, 3276 0, 3277 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3278 0, 3279 0, 3280 0, 3281 MatLoad_SeqAIJ, 3282 /* 84*/ MatIsSymmetric_SeqAIJ, 3283 MatIsHermitian_SeqAIJ, 3284 0, 3285 0, 3286 0, 3287 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3288 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3289 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3290 MatPtAP_SeqAIJ_SeqAIJ, 3291 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3292 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3293 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3294 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3295 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3296 0, 3297 /* 99*/ 0, 3298 0, 3299 0, 3300 MatConjugate_SeqAIJ, 3301 0, 3302 /*104*/ MatSetValuesRow_SeqAIJ, 3303 MatRealPart_SeqAIJ, 3304 MatImaginaryPart_SeqAIJ, 3305 0, 3306 0, 3307 /*109*/ MatMatSolve_SeqAIJ, 3308 0, 3309 MatGetRowMin_SeqAIJ, 3310 0, 3311 MatMissingDiagonal_SeqAIJ, 3312 /*114*/ 0, 3313 0, 3314 0, 3315 0, 3316 0, 3317 /*119*/ 0, 3318 0, 3319 0, 3320 0, 3321 MatGetMultiProcBlock_SeqAIJ, 3322 /*124*/ MatFindNonzeroRows_SeqAIJ, 3323 MatGetColumnNorms_SeqAIJ, 3324 MatInvertBlockDiagonal_SeqAIJ, 3325 0, 3326 0, 3327 /*129*/ 0, 3328 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3329 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3330 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3331 MatTransposeColoringCreate_SeqAIJ, 3332 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3333 MatTransColoringApplyDenToSp_SeqAIJ, 3334 MatRARt_SeqAIJ_SeqAIJ, 3335 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3336 MatRARtNumeric_SeqAIJ_SeqAIJ, 3337 /*139*/0, 3338 0, 3339 0, 3340 MatFDColoringSetUp_SeqXAIJ, 3341 MatFindOffBlockDiagonalEntries_SeqAIJ 3342 }; 3343 3344 #undef __FUNCT__ 3345 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3346 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3347 { 3348 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3349 PetscInt i,nz,n; 3350 3351 PetscFunctionBegin; 3352 nz = aij->maxnz; 3353 n = mat->rmap->n; 3354 for (i=0; i<nz; i++) { 3355 aij->j[i] = indices[i]; 3356 } 3357 aij->nz = nz; 3358 for (i=0; i<n; i++) { 3359 aij->ilen[i] = aij->imax[i]; 3360 } 3361 PetscFunctionReturn(0); 3362 } 3363 3364 #undef __FUNCT__ 3365 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3366 /*@ 3367 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3368 in the matrix. 3369 3370 Input Parameters: 3371 + mat - the SeqAIJ matrix 3372 - indices - the column indices 3373 3374 Level: advanced 3375 3376 Notes: 3377 This can be called if you have precomputed the nonzero structure of the 3378 matrix and want to provide it to the matrix object to improve the performance 3379 of the MatSetValues() operation. 3380 3381 You MUST have set the correct numbers of nonzeros per row in the call to 3382 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3383 3384 MUST be called before any calls to MatSetValues(); 3385 3386 The indices should start with zero, not one. 3387 3388 @*/ 3389 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3390 { 3391 PetscErrorCode ierr; 3392 3393 PetscFunctionBegin; 3394 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3395 PetscValidPointer(indices,2); 3396 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3397 PetscFunctionReturn(0); 3398 } 3399 3400 /* ----------------------------------------------------------------------------------------*/ 3401 3402 #undef __FUNCT__ 3403 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3404 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3405 { 3406 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3407 PetscErrorCode ierr; 3408 size_t nz = aij->i[mat->rmap->n]; 3409 3410 PetscFunctionBegin; 3411 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3412 3413 /* allocate space for values if not already there */ 3414 if (!aij->saved_values) { 3415 ierr = PetscMalloc1((nz+1),&aij->saved_values);CHKERRQ(ierr); 3416 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3417 } 3418 3419 /* copy values over */ 3420 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3421 PetscFunctionReturn(0); 3422 } 3423 3424 #undef __FUNCT__ 3425 #define __FUNCT__ "MatStoreValues" 3426 /*@ 3427 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3428 example, reuse of the linear part of a Jacobian, while recomputing the 3429 nonlinear portion. 3430 3431 Collect on Mat 3432 3433 Input Parameters: 3434 . mat - the matrix (currently only AIJ matrices support this option) 3435 3436 Level: advanced 3437 3438 Common Usage, with SNESSolve(): 3439 $ Create Jacobian matrix 3440 $ Set linear terms into matrix 3441 $ Apply boundary conditions to matrix, at this time matrix must have 3442 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3443 $ boundary conditions again will not change the nonzero structure 3444 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3445 $ ierr = MatStoreValues(mat); 3446 $ Call SNESSetJacobian() with matrix 3447 $ In your Jacobian routine 3448 $ ierr = MatRetrieveValues(mat); 3449 $ Set nonlinear terms in matrix 3450 3451 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3452 $ // build linear portion of Jacobian 3453 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3454 $ ierr = MatStoreValues(mat); 3455 $ loop over nonlinear iterations 3456 $ ierr = MatRetrieveValues(mat); 3457 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3458 $ // call MatAssemblyBegin/End() on matrix 3459 $ Solve linear system with Jacobian 3460 $ endloop 3461 3462 Notes: 3463 Matrix must already be assemblied before calling this routine 3464 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3465 calling this routine. 3466 3467 When this is called multiple times it overwrites the previous set of stored values 3468 and does not allocated additional space. 3469 3470 .seealso: MatRetrieveValues() 3471 3472 @*/ 3473 PetscErrorCode MatStoreValues(Mat mat) 3474 { 3475 PetscErrorCode ierr; 3476 3477 PetscFunctionBegin; 3478 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3479 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3480 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3481 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3482 PetscFunctionReturn(0); 3483 } 3484 3485 #undef __FUNCT__ 3486 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3487 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3488 { 3489 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3490 PetscErrorCode ierr; 3491 PetscInt nz = aij->i[mat->rmap->n]; 3492 3493 PetscFunctionBegin; 3494 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3495 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3496 /* copy values over */ 3497 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3498 PetscFunctionReturn(0); 3499 } 3500 3501 #undef __FUNCT__ 3502 #define __FUNCT__ "MatRetrieveValues" 3503 /*@ 3504 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3505 example, reuse of the linear part of a Jacobian, while recomputing the 3506 nonlinear portion. 3507 3508 Collect on Mat 3509 3510 Input Parameters: 3511 . mat - the matrix (currently on AIJ matrices support this option) 3512 3513 Level: advanced 3514 3515 .seealso: MatStoreValues() 3516 3517 @*/ 3518 PetscErrorCode MatRetrieveValues(Mat mat) 3519 { 3520 PetscErrorCode ierr; 3521 3522 PetscFunctionBegin; 3523 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3524 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3525 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3526 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3527 PetscFunctionReturn(0); 3528 } 3529 3530 3531 /* --------------------------------------------------------------------------------*/ 3532 #undef __FUNCT__ 3533 #define __FUNCT__ "MatCreateSeqAIJ" 3534 /*@C 3535 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3536 (the default parallel PETSc format). For good matrix assembly performance 3537 the user should preallocate the matrix storage by setting the parameter nz 3538 (or the array nnz). By setting these parameters accurately, performance 3539 during matrix assembly can be increased by more than a factor of 50. 3540 3541 Collective on MPI_Comm 3542 3543 Input Parameters: 3544 + comm - MPI communicator, set to PETSC_COMM_SELF 3545 . m - number of rows 3546 . n - number of columns 3547 . nz - number of nonzeros per row (same for all rows) 3548 - nnz - array containing the number of nonzeros in the various rows 3549 (possibly different for each row) or NULL 3550 3551 Output Parameter: 3552 . A - the matrix 3553 3554 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3555 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3556 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3557 3558 Notes: 3559 If nnz is given then nz is ignored 3560 3561 The AIJ format (also called the Yale sparse matrix format or 3562 compressed row storage), is fully compatible with standard Fortran 77 3563 storage. That is, the stored row and column indices can begin at 3564 either one (as in Fortran) or zero. See the users' manual for details. 3565 3566 Specify the preallocated storage with either nz or nnz (not both). 3567 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3568 allocation. For large problems you MUST preallocate memory or you 3569 will get TERRIBLE performance, see the users' manual chapter on matrices. 3570 3571 By default, this format uses inodes (identical nodes) when possible, to 3572 improve numerical efficiency of matrix-vector products and solves. We 3573 search for consecutive rows with the same nonzero structure, thereby 3574 reusing matrix information to achieve increased efficiency. 3575 3576 Options Database Keys: 3577 + -mat_no_inode - Do not use inodes 3578 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3579 3580 Level: intermediate 3581 3582 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3583 3584 @*/ 3585 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3586 { 3587 PetscErrorCode ierr; 3588 3589 PetscFunctionBegin; 3590 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3591 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3592 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3593 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3594 PetscFunctionReturn(0); 3595 } 3596 3597 #undef __FUNCT__ 3598 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3599 /*@C 3600 MatSeqAIJSetPreallocation - For good matrix assembly performance 3601 the user should preallocate the matrix storage by setting the parameter nz 3602 (or the array nnz). By setting these parameters accurately, performance 3603 during matrix assembly can be increased by more than a factor of 50. 3604 3605 Collective on MPI_Comm 3606 3607 Input Parameters: 3608 + B - The matrix 3609 . nz - number of nonzeros per row (same for all rows) 3610 - nnz - array containing the number of nonzeros in the various rows 3611 (possibly different for each row) or NULL 3612 3613 Notes: 3614 If nnz is given then nz is ignored 3615 3616 The AIJ format (also called the Yale sparse matrix format or 3617 compressed row storage), is fully compatible with standard Fortran 77 3618 storage. That is, the stored row and column indices can begin at 3619 either one (as in Fortran) or zero. See the users' manual for details. 3620 3621 Specify the preallocated storage with either nz or nnz (not both). 3622 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3623 allocation. For large problems you MUST preallocate memory or you 3624 will get TERRIBLE performance, see the users' manual chapter on matrices. 3625 3626 You can call MatGetInfo() to get information on how effective the preallocation was; 3627 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3628 You can also run with the option -info and look for messages with the string 3629 malloc in them to see if additional memory allocation was needed. 3630 3631 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3632 entries or columns indices 3633 3634 By default, this format uses inodes (identical nodes) when possible, to 3635 improve numerical efficiency of matrix-vector products and solves. We 3636 search for consecutive rows with the same nonzero structure, thereby 3637 reusing matrix information to achieve increased efficiency. 3638 3639 Options Database Keys: 3640 + -mat_no_inode - Do not use inodes 3641 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3642 - -mat_aij_oneindex - Internally use indexing starting at 1 3643 rather than 0. Note that when calling MatSetValues(), 3644 the user still MUST index entries starting at 0! 3645 3646 Level: intermediate 3647 3648 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3649 3650 @*/ 3651 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3652 { 3653 PetscErrorCode ierr; 3654 3655 PetscFunctionBegin; 3656 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3657 PetscValidType(B,1); 3658 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3659 PetscFunctionReturn(0); 3660 } 3661 3662 #undef __FUNCT__ 3663 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3664 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3665 { 3666 Mat_SeqAIJ *b; 3667 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3668 PetscErrorCode ierr; 3669 PetscInt i; 3670 3671 PetscFunctionBegin; 3672 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3673 if (nz == MAT_SKIP_ALLOCATION) { 3674 skipallocation = PETSC_TRUE; 3675 nz = 0; 3676 } 3677 3678 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3679 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3680 3681 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3682 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3683 if (nnz) { 3684 for (i=0; i<B->rmap->n; i++) { 3685 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]); 3686 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); 3687 } 3688 } 3689 3690 B->preallocated = PETSC_TRUE; 3691 3692 b = (Mat_SeqAIJ*)B->data; 3693 3694 if (!skipallocation) { 3695 if (!b->imax) { 3696 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3697 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3698 } 3699 if (!nnz) { 3700 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3701 else if (nz < 0) nz = 1; 3702 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3703 nz = nz*B->rmap->n; 3704 } else { 3705 nz = 0; 3706 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3707 } 3708 /* b->ilen will count nonzeros in each row so far. */ 3709 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3710 3711 /* allocate the matrix space */ 3712 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3713 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3714 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3715 b->i[0] = 0; 3716 for (i=1; i<B->rmap->n+1; i++) { 3717 b->i[i] = b->i[i-1] + b->imax[i-1]; 3718 } 3719 b->singlemalloc = PETSC_TRUE; 3720 b->free_a = PETSC_TRUE; 3721 b->free_ij = PETSC_TRUE; 3722 #if defined(PETSC_THREADCOMM_ACTIVE) 3723 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3724 #endif 3725 } else { 3726 b->free_a = PETSC_FALSE; 3727 b->free_ij = PETSC_FALSE; 3728 } 3729 3730 b->nz = 0; 3731 b->maxnz = nz; 3732 B->info.nz_unneeded = (double)b->maxnz; 3733 if (realalloc) { 3734 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3735 } 3736 PetscFunctionReturn(0); 3737 } 3738 3739 #undef __FUNCT__ 3740 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3741 /*@ 3742 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3743 3744 Input Parameters: 3745 + B - the matrix 3746 . i - the indices into j for the start of each row (starts with zero) 3747 . j - the column indices for each row (starts with zero) these must be sorted for each row 3748 - v - optional values in the matrix 3749 3750 Level: developer 3751 3752 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3753 3754 .keywords: matrix, aij, compressed row, sparse, sequential 3755 3756 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3757 @*/ 3758 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3759 { 3760 PetscErrorCode ierr; 3761 3762 PetscFunctionBegin; 3763 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3764 PetscValidType(B,1); 3765 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3766 PetscFunctionReturn(0); 3767 } 3768 3769 #undef __FUNCT__ 3770 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3771 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3772 { 3773 PetscInt i; 3774 PetscInt m,n; 3775 PetscInt nz; 3776 PetscInt *nnz, nz_max = 0; 3777 PetscScalar *values; 3778 PetscErrorCode ierr; 3779 3780 PetscFunctionBegin; 3781 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3782 3783 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3784 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3785 3786 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3787 ierr = PetscMalloc1((m+1), &nnz);CHKERRQ(ierr); 3788 for (i = 0; i < m; i++) { 3789 nz = Ii[i+1]- Ii[i]; 3790 nz_max = PetscMax(nz_max, nz); 3791 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3792 nnz[i] = nz; 3793 } 3794 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3795 ierr = PetscFree(nnz);CHKERRQ(ierr); 3796 3797 if (v) { 3798 values = (PetscScalar*) v; 3799 } else { 3800 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3801 } 3802 3803 for (i = 0; i < m; i++) { 3804 nz = Ii[i+1] - Ii[i]; 3805 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3806 } 3807 3808 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3809 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3810 3811 if (!v) { 3812 ierr = PetscFree(values);CHKERRQ(ierr); 3813 } 3814 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3815 PetscFunctionReturn(0); 3816 } 3817 3818 #include <../src/mat/impls/dense/seq/dense.h> 3819 #include <petsc-private/kernels/petscaxpy.h> 3820 3821 #undef __FUNCT__ 3822 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3823 /* 3824 Computes (B'*A')' since computing B*A directly is untenable 3825 3826 n p p 3827 ( ) ( ) ( ) 3828 m ( A ) * n ( B ) = m ( C ) 3829 ( ) ( ) ( ) 3830 3831 */ 3832 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3833 { 3834 PetscErrorCode ierr; 3835 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3836 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3837 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3838 PetscInt i,n,m,q,p; 3839 const PetscInt *ii,*idx; 3840 const PetscScalar *b,*a,*a_q; 3841 PetscScalar *c,*c_q; 3842 3843 PetscFunctionBegin; 3844 m = A->rmap->n; 3845 n = A->cmap->n; 3846 p = B->cmap->n; 3847 a = sub_a->v; 3848 b = sub_b->a; 3849 c = sub_c->v; 3850 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3851 3852 ii = sub_b->i; 3853 idx = sub_b->j; 3854 for (i=0; i<n; i++) { 3855 q = ii[i+1] - ii[i]; 3856 while (q-->0) { 3857 c_q = c + m*(*idx); 3858 a_q = a + m*i; 3859 PetscKernelAXPY(c_q,*b,a_q,m); 3860 idx++; 3861 b++; 3862 } 3863 } 3864 PetscFunctionReturn(0); 3865 } 3866 3867 #undef __FUNCT__ 3868 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 3869 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3870 { 3871 PetscErrorCode ierr; 3872 PetscInt m=A->rmap->n,n=B->cmap->n; 3873 Mat Cmat; 3874 3875 PetscFunctionBegin; 3876 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); 3877 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3878 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3879 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3880 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3881 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3882 3883 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3884 3885 *C = Cmat; 3886 PetscFunctionReturn(0); 3887 } 3888 3889 /* ----------------------------------------------------------------*/ 3890 #undef __FUNCT__ 3891 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 3892 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3893 { 3894 PetscErrorCode ierr; 3895 3896 PetscFunctionBegin; 3897 if (scall == MAT_INITIAL_MATRIX) { 3898 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3899 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3900 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3901 } 3902 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3903 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3904 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3905 PetscFunctionReturn(0); 3906 } 3907 3908 3909 /*MC 3910 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3911 based on compressed sparse row format. 3912 3913 Options Database Keys: 3914 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3915 3916 Level: beginner 3917 3918 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3919 M*/ 3920 3921 /*MC 3922 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3923 3924 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3925 and MATMPIAIJ otherwise. As a result, for single process communicators, 3926 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3927 for communicators controlling multiple processes. It is recommended that you call both of 3928 the above preallocation routines for simplicity. 3929 3930 Options Database Keys: 3931 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3932 3933 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 3934 enough exist. 3935 3936 Level: beginner 3937 3938 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3939 M*/ 3940 3941 /*MC 3942 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3943 3944 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3945 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3946 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3947 for communicators controlling multiple processes. It is recommended that you call both of 3948 the above preallocation routines for simplicity. 3949 3950 Options Database Keys: 3951 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3952 3953 Level: beginner 3954 3955 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3956 M*/ 3957 3958 #if defined(PETSC_HAVE_PASTIX) 3959 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 3960 #endif 3961 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 3962 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 3963 #endif 3964 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3965 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 3966 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 3967 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 3968 #if defined(PETSC_HAVE_MUMPS) 3969 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 3970 #endif 3971 #if defined(PETSC_HAVE_SUPERLU) 3972 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 3973 #endif 3974 #if defined(PETSC_HAVE_MKL_PARDISO) 3975 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mkl_pardiso(Mat,MatFactorType,Mat*); 3976 #endif 3977 #if defined(PETSC_HAVE_SUPERLU_DIST) 3978 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 3979 #endif 3980 #if defined(PETSC_HAVE_SUITESPARSE) 3981 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 3982 #endif 3983 #if defined(PETSC_HAVE_SUITESPARSE) 3984 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 3985 #endif 3986 #if defined(PETSC_HAVE_SUITESPARSE) 3987 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_klu(Mat,MatFactorType,Mat*); 3988 #endif 3989 #if defined(PETSC_HAVE_LUSOL) 3990 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 3991 #endif 3992 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3993 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 3994 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 3995 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 3996 #endif 3997 #if defined(PETSC_HAVE_CLIQUE) 3998 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 3999 #endif 4000 4001 4002 #undef __FUNCT__ 4003 #define __FUNCT__ "MatSeqAIJGetArray" 4004 /*@C 4005 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 4006 4007 Not Collective 4008 4009 Input Parameter: 4010 . mat - a MATSEQDENSE matrix 4011 4012 Output Parameter: 4013 . array - pointer to the data 4014 4015 Level: intermediate 4016 4017 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4018 @*/ 4019 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4020 { 4021 PetscErrorCode ierr; 4022 4023 PetscFunctionBegin; 4024 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4025 PetscFunctionReturn(0); 4026 } 4027 4028 #undef __FUNCT__ 4029 #define __FUNCT__ "MatSeqAIJGetMaxRowNonzeros" 4030 /*@C 4031 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 4032 4033 Not Collective 4034 4035 Input Parameter: 4036 . mat - a MATSEQDENSE matrix 4037 4038 Output Parameter: 4039 . nz - the maximum number of nonzeros in any row 4040 4041 Level: intermediate 4042 4043 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4044 @*/ 4045 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 4046 { 4047 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 4048 4049 PetscFunctionBegin; 4050 *nz = aij->rmax; 4051 PetscFunctionReturn(0); 4052 } 4053 4054 #undef __FUNCT__ 4055 #define __FUNCT__ "MatSeqAIJRestoreArray" 4056 /*@C 4057 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4058 4059 Not Collective 4060 4061 Input Parameters: 4062 . mat - a MATSEQDENSE matrix 4063 . array - pointer to the data 4064 4065 Level: intermediate 4066 4067 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4068 @*/ 4069 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4070 { 4071 PetscErrorCode ierr; 4072 4073 PetscFunctionBegin; 4074 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4075 PetscFunctionReturn(0); 4076 } 4077 4078 #undef __FUNCT__ 4079 #define __FUNCT__ "MatCreate_SeqAIJ" 4080 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4081 { 4082 Mat_SeqAIJ *b; 4083 PetscErrorCode ierr; 4084 PetscMPIInt size; 4085 4086 PetscFunctionBegin; 4087 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4088 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4089 4090 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4091 4092 B->data = (void*)b; 4093 4094 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4095 4096 b->row = 0; 4097 b->col = 0; 4098 b->icol = 0; 4099 b->reallocs = 0; 4100 b->ignorezeroentries = PETSC_FALSE; 4101 b->roworiented = PETSC_TRUE; 4102 b->nonew = 0; 4103 b->diag = 0; 4104 b->solve_work = 0; 4105 B->spptr = 0; 4106 b->saved_values = 0; 4107 b->idiag = 0; 4108 b->mdiag = 0; 4109 b->ssor_work = 0; 4110 b->omega = 1.0; 4111 b->fshift = 0.0; 4112 b->idiagvalid = PETSC_FALSE; 4113 b->ibdiagvalid = PETSC_FALSE; 4114 b->keepnonzeropattern = PETSC_FALSE; 4115 b->xtoy = 0; 4116 b->XtoY = 0; 4117 4118 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4119 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4120 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4121 4122 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4123 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4124 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4125 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4126 #endif 4127 #if defined(PETSC_HAVE_PASTIX) 4128 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4129 #endif 4130 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4131 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4132 #endif 4133 #if defined(PETSC_HAVE_SUPERLU) 4134 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4135 #endif 4136 #if defined(PETSC_HAVE_MKL_PARDISO) 4137 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mkl_pardiso_C",MatGetFactor_aij_mkl_pardiso);CHKERRQ(ierr); 4138 #endif 4139 #if defined(PETSC_HAVE_SUPERLU_DIST) 4140 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4141 #endif 4142 #if defined(PETSC_HAVE_MUMPS) 4143 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4144 #endif 4145 #if defined(PETSC_HAVE_SUITESPARSE) 4146 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4147 #endif 4148 #if defined(PETSC_HAVE_SUITESPARSE) 4149 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4150 #endif 4151 #if defined(PETSC_HAVE_SUITESPARSE) 4152 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_klu_C",MatGetFactor_seqaij_klu);CHKERRQ(ierr); 4153 #endif 4154 #if defined(PETSC_HAVE_LUSOL) 4155 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4156 #endif 4157 #if defined(PETSC_HAVE_CLIQUE) 4158 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4159 #endif 4160 4161 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4162 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4163 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4164 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4165 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4166 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4167 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4168 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4169 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4170 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4171 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4172 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4173 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4174 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4175 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4176 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4177 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4178 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4179 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4180 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4181 PetscFunctionReturn(0); 4182 } 4183 4184 #undef __FUNCT__ 4185 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4186 /* 4187 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4188 */ 4189 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4190 { 4191 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4192 PetscErrorCode ierr; 4193 PetscInt i,m = A->rmap->n; 4194 4195 PetscFunctionBegin; 4196 c = (Mat_SeqAIJ*)C->data; 4197 4198 C->factortype = A->factortype; 4199 c->row = 0; 4200 c->col = 0; 4201 c->icol = 0; 4202 c->reallocs = 0; 4203 4204 C->assembled = PETSC_TRUE; 4205 4206 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4207 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4208 4209 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4210 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4211 for (i=0; i<m; i++) { 4212 c->imax[i] = a->imax[i]; 4213 c->ilen[i] = a->ilen[i]; 4214 } 4215 4216 /* allocate the matrix space */ 4217 if (mallocmatspace) { 4218 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4219 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4220 4221 c->singlemalloc = PETSC_TRUE; 4222 4223 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4224 if (m > 0) { 4225 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4226 if (cpvalues == MAT_COPY_VALUES) { 4227 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4228 } else { 4229 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4230 } 4231 } 4232 } 4233 4234 c->ignorezeroentries = a->ignorezeroentries; 4235 c->roworiented = a->roworiented; 4236 c->nonew = a->nonew; 4237 if (a->diag) { 4238 ierr = PetscMalloc1((m+1),&c->diag);CHKERRQ(ierr); 4239 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4240 for (i=0; i<m; i++) { 4241 c->diag[i] = a->diag[i]; 4242 } 4243 } else c->diag = 0; 4244 4245 c->solve_work = 0; 4246 c->saved_values = 0; 4247 c->idiag = 0; 4248 c->ssor_work = 0; 4249 c->keepnonzeropattern = a->keepnonzeropattern; 4250 c->free_a = PETSC_TRUE; 4251 c->free_ij = PETSC_TRUE; 4252 c->xtoy = 0; 4253 c->XtoY = 0; 4254 4255 c->rmax = a->rmax; 4256 c->nz = a->nz; 4257 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4258 C->preallocated = PETSC_TRUE; 4259 4260 c->compressedrow.use = a->compressedrow.use; 4261 c->compressedrow.nrows = a->compressedrow.nrows; 4262 if (a->compressedrow.use) { 4263 i = a->compressedrow.nrows; 4264 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4265 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4266 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4267 } else { 4268 c->compressedrow.use = PETSC_FALSE; 4269 c->compressedrow.i = NULL; 4270 c->compressedrow.rindex = NULL; 4271 } 4272 C->nonzerostate = A->nonzerostate; 4273 4274 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4275 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4276 PetscFunctionReturn(0); 4277 } 4278 4279 #undef __FUNCT__ 4280 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4281 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4282 { 4283 PetscErrorCode ierr; 4284 4285 PetscFunctionBegin; 4286 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4287 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4288 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4289 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4290 } 4291 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4292 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4293 PetscFunctionReturn(0); 4294 } 4295 4296 #undef __FUNCT__ 4297 #define __FUNCT__ "MatLoad_SeqAIJ" 4298 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4299 { 4300 Mat_SeqAIJ *a; 4301 PetscErrorCode ierr; 4302 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4303 int fd; 4304 PetscMPIInt size; 4305 MPI_Comm comm; 4306 PetscInt bs = 1; 4307 4308 PetscFunctionBegin; 4309 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4310 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4311 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4312 4313 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4314 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4315 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4316 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4317 4318 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4319 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4320 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4321 M = header[1]; N = header[2]; nz = header[3]; 4322 4323 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4324 4325 /* read in row lengths */ 4326 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4327 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4328 4329 /* check if sum of rowlengths is same as nz */ 4330 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4331 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); 4332 4333 /* set global size if not set already*/ 4334 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4335 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4336 } else { 4337 /* if sizes and type are already set, check if the vector global sizes are correct */ 4338 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4339 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4340 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4341 } 4342 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); 4343 } 4344 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4345 a = (Mat_SeqAIJ*)newMat->data; 4346 4347 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4348 4349 /* read in nonzero values */ 4350 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4351 4352 /* set matrix "i" values */ 4353 a->i[0] = 0; 4354 for (i=1; i<= M; i++) { 4355 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4356 a->ilen[i-1] = rowlengths[i-1]; 4357 } 4358 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4359 4360 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4361 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4362 PetscFunctionReturn(0); 4363 } 4364 4365 #undef __FUNCT__ 4366 #define __FUNCT__ "MatEqual_SeqAIJ" 4367 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4368 { 4369 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4370 PetscErrorCode ierr; 4371 #if defined(PETSC_USE_COMPLEX) 4372 PetscInt k; 4373 #endif 4374 4375 PetscFunctionBegin; 4376 /* If the matrix dimensions are not equal,or no of nonzeros */ 4377 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4378 *flg = PETSC_FALSE; 4379 PetscFunctionReturn(0); 4380 } 4381 4382 /* if the a->i are the same */ 4383 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4384 if (!*flg) PetscFunctionReturn(0); 4385 4386 /* if a->j are the same */ 4387 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4388 if (!*flg) PetscFunctionReturn(0); 4389 4390 /* if a->a are the same */ 4391 #if defined(PETSC_USE_COMPLEX) 4392 for (k=0; k<a->nz; k++) { 4393 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4394 *flg = PETSC_FALSE; 4395 PetscFunctionReturn(0); 4396 } 4397 } 4398 #else 4399 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4400 #endif 4401 PetscFunctionReturn(0); 4402 } 4403 4404 #undef __FUNCT__ 4405 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4406 /*@ 4407 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4408 provided by the user. 4409 4410 Collective on MPI_Comm 4411 4412 Input Parameters: 4413 + comm - must be an MPI communicator of size 1 4414 . m - number of rows 4415 . n - number of columns 4416 . i - row indices 4417 . j - column indices 4418 - a - matrix values 4419 4420 Output Parameter: 4421 . mat - the matrix 4422 4423 Level: intermediate 4424 4425 Notes: 4426 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4427 once the matrix is destroyed and not before 4428 4429 You cannot set new nonzero locations into this matrix, that will generate an error. 4430 4431 The i and j indices are 0 based 4432 4433 The format which is used for the sparse matrix input, is equivalent to a 4434 row-major ordering.. i.e for the following matrix, the input data expected is 4435 as shown: 4436 4437 1 0 0 4438 2 0 3 4439 4 5 6 4440 4441 i = {0,1,3,6} [size = nrow+1 = 3+1] 4442 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4443 v = {1,2,3,4,5,6} [size = nz = 6] 4444 4445 4446 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4447 4448 @*/ 4449 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4450 { 4451 PetscErrorCode ierr; 4452 PetscInt ii; 4453 Mat_SeqAIJ *aij; 4454 #if defined(PETSC_USE_DEBUG) 4455 PetscInt jj; 4456 #endif 4457 4458 PetscFunctionBegin; 4459 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4460 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4461 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4462 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4463 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4464 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4465 aij = (Mat_SeqAIJ*)(*mat)->data; 4466 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4467 4468 aij->i = i; 4469 aij->j = j; 4470 aij->a = a; 4471 aij->singlemalloc = PETSC_FALSE; 4472 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4473 aij->free_a = PETSC_FALSE; 4474 aij->free_ij = PETSC_FALSE; 4475 4476 for (ii=0; ii<m; ii++) { 4477 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4478 #if defined(PETSC_USE_DEBUG) 4479 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]); 4480 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4481 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); 4482 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); 4483 } 4484 #endif 4485 } 4486 #if defined(PETSC_USE_DEBUG) 4487 for (ii=0; ii<aij->i[m]; ii++) { 4488 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4489 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]); 4490 } 4491 #endif 4492 4493 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4494 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4495 PetscFunctionReturn(0); 4496 } 4497 #undef __FUNCT__ 4498 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4499 /*@C 4500 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4501 provided by the user. 4502 4503 Collective on MPI_Comm 4504 4505 Input Parameters: 4506 + comm - must be an MPI communicator of size 1 4507 . m - number of rows 4508 . n - number of columns 4509 . i - row indices 4510 . j - column indices 4511 . a - matrix values 4512 . nz - number of nonzeros 4513 - idx - 0 or 1 based 4514 4515 Output Parameter: 4516 . mat - the matrix 4517 4518 Level: intermediate 4519 4520 Notes: 4521 The i and j indices are 0 based 4522 4523 The format which is used for the sparse matrix input, is equivalent to a 4524 row-major ordering.. i.e for the following matrix, the input data expected is 4525 as shown: 4526 4527 1 0 0 4528 2 0 3 4529 4 5 6 4530 4531 i = {0,1,1,2,2,2} 4532 j = {0,0,2,0,1,2} 4533 v = {1,2,3,4,5,6} 4534 4535 4536 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4537 4538 @*/ 4539 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4540 { 4541 PetscErrorCode ierr; 4542 PetscInt ii, *nnz, one = 1,row,col; 4543 4544 4545 PetscFunctionBegin; 4546 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4547 for (ii = 0; ii < nz; ii++) { 4548 nnz[i[ii] - !!idx] += 1; 4549 } 4550 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4551 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4552 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4553 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4554 for (ii = 0; ii < nz; ii++) { 4555 if (idx) { 4556 row = i[ii] - 1; 4557 col = j[ii] - 1; 4558 } else { 4559 row = i[ii]; 4560 col = j[ii]; 4561 } 4562 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4563 } 4564 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4565 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4566 ierr = PetscFree(nnz);CHKERRQ(ierr); 4567 PetscFunctionReturn(0); 4568 } 4569 4570 #undef __FUNCT__ 4571 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4572 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4573 { 4574 PetscErrorCode ierr; 4575 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4576 4577 PetscFunctionBegin; 4578 if (coloring->ctype == IS_COLORING_GLOBAL) { 4579 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4580 a->coloring = coloring; 4581 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4582 PetscInt i,*larray; 4583 ISColoring ocoloring; 4584 ISColoringValue *colors; 4585 4586 /* set coloring for diagonal portion */ 4587 ierr = PetscMalloc1(A->cmap->n,&larray);CHKERRQ(ierr); 4588 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4589 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4590 ierr = PetscMalloc1(A->cmap->n,&colors);CHKERRQ(ierr); 4591 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4592 ierr = PetscFree(larray);CHKERRQ(ierr); 4593 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4594 a->coloring = ocoloring; 4595 } 4596 PetscFunctionReturn(0); 4597 } 4598 4599 #undef __FUNCT__ 4600 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4601 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4602 { 4603 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4604 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4605 MatScalar *v = a->a; 4606 PetscScalar *values = (PetscScalar*)advalues; 4607 ISColoringValue *color; 4608 4609 PetscFunctionBegin; 4610 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4611 color = a->coloring->colors; 4612 /* loop over rows */ 4613 for (i=0; i<m; i++) { 4614 nz = ii[i+1] - ii[i]; 4615 /* loop over columns putting computed value into matrix */ 4616 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4617 values += nl; /* jump to next row of derivatives */ 4618 } 4619 PetscFunctionReturn(0); 4620 } 4621 4622 #undef __FUNCT__ 4623 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4624 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4625 { 4626 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4627 PetscErrorCode ierr; 4628 4629 PetscFunctionBegin; 4630 a->idiagvalid = PETSC_FALSE; 4631 a->ibdiagvalid = PETSC_FALSE; 4632 4633 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4634 PetscFunctionReturn(0); 4635 } 4636 4637 /* 4638 Special version for direct calls from Fortran 4639 */ 4640 #include <petsc-private/fortranimpl.h> 4641 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4642 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4643 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4644 #define matsetvaluesseqaij_ matsetvaluesseqaij 4645 #endif 4646 4647 /* Change these macros so can be used in void function */ 4648 #undef CHKERRQ 4649 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4650 #undef SETERRQ2 4651 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4652 #undef SETERRQ3 4653 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4654 4655 #undef __FUNCT__ 4656 #define __FUNCT__ "matsetvaluesseqaij_" 4657 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) 4658 { 4659 Mat A = *AA; 4660 PetscInt m = *mm, n = *nn; 4661 InsertMode is = *isis; 4662 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4663 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4664 PetscInt *imax,*ai,*ailen; 4665 PetscErrorCode ierr; 4666 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4667 MatScalar *ap,value,*aa; 4668 PetscBool ignorezeroentries = a->ignorezeroentries; 4669 PetscBool roworiented = a->roworiented; 4670 4671 PetscFunctionBegin; 4672 MatCheckPreallocated(A,1); 4673 imax = a->imax; 4674 ai = a->i; 4675 ailen = a->ilen; 4676 aj = a->j; 4677 aa = a->a; 4678 4679 for (k=0; k<m; k++) { /* loop over added rows */ 4680 row = im[k]; 4681 if (row < 0) continue; 4682 #if defined(PETSC_USE_DEBUG) 4683 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4684 #endif 4685 rp = aj + ai[row]; ap = aa + ai[row]; 4686 rmax = imax[row]; nrow = ailen[row]; 4687 low = 0; 4688 high = nrow; 4689 for (l=0; l<n; l++) { /* loop over added columns */ 4690 if (in[l] < 0) continue; 4691 #if defined(PETSC_USE_DEBUG) 4692 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4693 #endif 4694 col = in[l]; 4695 if (roworiented) value = v[l + k*n]; 4696 else value = v[k + l*m]; 4697 4698 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4699 4700 if (col <= lastcol) low = 0; 4701 else high = nrow; 4702 lastcol = col; 4703 while (high-low > 5) { 4704 t = (low+high)/2; 4705 if (rp[t] > col) high = t; 4706 else low = t; 4707 } 4708 for (i=low; i<high; i++) { 4709 if (rp[i] > col) break; 4710 if (rp[i] == col) { 4711 if (is == ADD_VALUES) ap[i] += value; 4712 else ap[i] = value; 4713 goto noinsert; 4714 } 4715 } 4716 if (value == 0.0 && ignorezeroentries) goto noinsert; 4717 if (nonew == 1) goto noinsert; 4718 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4719 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4720 N = nrow++ - 1; a->nz++; high++; 4721 /* shift up all the later entries in this row */ 4722 for (ii=N; ii>=i; ii--) { 4723 rp[ii+1] = rp[ii]; 4724 ap[ii+1] = ap[ii]; 4725 } 4726 rp[i] = col; 4727 ap[i] = value; 4728 A->nonzerostate++; 4729 noinsert:; 4730 low = i + 1; 4731 } 4732 ailen[row] = nrow; 4733 } 4734 PetscFunctionReturnVoid(); 4735 } 4736 4737 4738