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 if (v) PetscValidScalarPointer(v,6); 445 for (k=0; k<m; k++) { /* loop over added rows */ 446 row = im[k]; 447 if (row < 0) continue; 448 #if defined(PETSC_USE_DEBUG) 449 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); 450 #endif 451 rp = aj + ai[row]; ap = aa + ai[row]; 452 rmax = imax[row]; nrow = ailen[row]; 453 low = 0; 454 high = nrow; 455 for (l=0; l<n; l++) { /* loop over added columns */ 456 if (in[l] < 0) continue; 457 #if defined(PETSC_USE_DEBUG) 458 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); 459 #endif 460 col = in[l]; 461 if (v) { 462 if (roworiented) { 463 value = v[l + k*n]; 464 } else { 465 value = v[k + l*m]; 466 } 467 } else { 468 value = 0.; 469 } 470 if ((value == 0.0 && ignorezeroentries) && (is == ADD_VALUES)) continue; 471 472 if (col <= lastcol) low = 0; 473 else high = nrow; 474 lastcol = col; 475 while (high-low > 5) { 476 t = (low+high)/2; 477 if (rp[t] > col) high = t; 478 else low = t; 479 } 480 for (i=low; i<high; i++) { 481 if (rp[i] > col) break; 482 if (rp[i] == col) { 483 if (is == ADD_VALUES) ap[i] += value; 484 else ap[i] = value; 485 low = i + 1; 486 goto noinsert; 487 } 488 } 489 if (value == 0.0 && ignorezeroentries) goto noinsert; 490 if (nonew == 1) goto noinsert; 491 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 492 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 493 N = nrow++ - 1; a->nz++; high++; 494 /* shift up all the later entries in this row */ 495 for (ii=N; ii>=i; ii--) { 496 rp[ii+1] = rp[ii]; 497 ap[ii+1] = ap[ii]; 498 } 499 rp[i] = col; 500 ap[i] = value; 501 low = i + 1; 502 A->nonzerostate++; 503 noinsert:; 504 } 505 ailen[row] = nrow; 506 } 507 PetscFunctionReturn(0); 508 } 509 510 511 #undef __FUNCT__ 512 #define __FUNCT__ "MatGetValues_SeqAIJ" 513 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 514 { 515 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 516 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 517 PetscInt *ai = a->i,*ailen = a->ilen; 518 MatScalar *ap,*aa = a->a; 519 520 PetscFunctionBegin; 521 for (k=0; k<m; k++) { /* loop over rows */ 522 row = im[k]; 523 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 524 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); 525 rp = aj + ai[row]; ap = aa + ai[row]; 526 nrow = ailen[row]; 527 for (l=0; l<n; l++) { /* loop over columns */ 528 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 529 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); 530 col = in[l]; 531 high = nrow; low = 0; /* assume unsorted */ 532 while (high-low > 5) { 533 t = (low+high)/2; 534 if (rp[t] > col) high = t; 535 else low = t; 536 } 537 for (i=low; i<high; i++) { 538 if (rp[i] > col) break; 539 if (rp[i] == col) { 540 *v++ = ap[i]; 541 goto finished; 542 } 543 } 544 *v++ = 0.0; 545 finished:; 546 } 547 } 548 PetscFunctionReturn(0); 549 } 550 551 552 #undef __FUNCT__ 553 #define __FUNCT__ "MatView_SeqAIJ_Binary" 554 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 555 { 556 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 557 PetscErrorCode ierr; 558 PetscInt i,*col_lens; 559 int fd; 560 FILE *file; 561 562 PetscFunctionBegin; 563 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 564 ierr = PetscMalloc1((4+A->rmap->n),&col_lens);CHKERRQ(ierr); 565 566 col_lens[0] = MAT_FILE_CLASSID; 567 col_lens[1] = A->rmap->n; 568 col_lens[2] = A->cmap->n; 569 col_lens[3] = a->nz; 570 571 /* store lengths of each row and write (including header) to file */ 572 for (i=0; i<A->rmap->n; i++) { 573 col_lens[4+i] = a->i[i+1] - a->i[i]; 574 } 575 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 576 ierr = PetscFree(col_lens);CHKERRQ(ierr); 577 578 /* store column indices (zero start index) */ 579 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 580 581 /* store nonzero values */ 582 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 583 584 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 585 if (file) { 586 fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); 587 } 588 PetscFunctionReturn(0); 589 } 590 591 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 592 593 #undef __FUNCT__ 594 #define __FUNCT__ "MatView_SeqAIJ_ASCII" 595 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 596 { 597 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 598 PetscErrorCode ierr; 599 PetscInt i,j,m = A->rmap->n; 600 const char *name; 601 PetscViewerFormat format; 602 603 PetscFunctionBegin; 604 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 605 if (format == PETSC_VIEWER_ASCII_MATLAB) { 606 PetscInt nofinalvalue = 0; 607 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 608 /* Need a dummy value to ensure the dimension of the matrix. */ 609 nofinalvalue = 1; 610 } 611 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 612 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 613 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 614 #if defined(PETSC_USE_COMPLEX) 615 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 616 #else 617 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 618 #endif 619 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 620 621 for (i=0; i<m; i++) { 622 for (j=a->i[i]; j<a->i[i+1]; j++) { 623 #if defined(PETSC_USE_COMPLEX) 624 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); 625 #else 626 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 627 #endif 628 } 629 } 630 if (nofinalvalue) { 631 #if defined(PETSC_USE_COMPLEX) 632 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 633 #else 634 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 635 #endif 636 } 637 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 638 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 639 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 640 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 641 PetscFunctionReturn(0); 642 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 643 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 644 for (i=0; i<m; i++) { 645 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 646 for (j=a->i[i]; j<a->i[i+1]; j++) { 647 #if defined(PETSC_USE_COMPLEX) 648 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 649 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 650 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 651 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 652 } else if (PetscRealPart(a->a[j]) != 0.0) { 653 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 654 } 655 #else 656 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 657 #endif 658 } 659 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 660 } 661 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 662 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 663 PetscInt nzd=0,fshift=1,*sptr; 664 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 665 ierr = PetscMalloc1((m+1),&sptr);CHKERRQ(ierr); 666 for (i=0; i<m; i++) { 667 sptr[i] = nzd+1; 668 for (j=a->i[i]; j<a->i[i+1]; j++) { 669 if (a->j[j] >= i) { 670 #if defined(PETSC_USE_COMPLEX) 671 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 672 #else 673 if (a->a[j] != 0.0) nzd++; 674 #endif 675 } 676 } 677 } 678 sptr[m] = nzd+1; 679 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 680 for (i=0; i<m+1; i+=6) { 681 if (i+4<m) { 682 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); 683 } else if (i+3<m) { 684 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); 685 } else if (i+2<m) { 686 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 687 } else if (i+1<m) { 688 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 689 } else if (i<m) { 690 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 691 } else { 692 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 693 } 694 } 695 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 696 ierr = PetscFree(sptr);CHKERRQ(ierr); 697 for (i=0; i<m; i++) { 698 for (j=a->i[i]; j<a->i[i+1]; j++) { 699 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 700 } 701 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 702 } 703 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 704 for (i=0; i<m; i++) { 705 for (j=a->i[i]; j<a->i[i+1]; j++) { 706 if (a->j[j] >= i) { 707 #if defined(PETSC_USE_COMPLEX) 708 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 709 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 710 } 711 #else 712 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 713 #endif 714 } 715 } 716 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 717 } 718 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 719 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 720 PetscInt cnt = 0,jcnt; 721 PetscScalar value; 722 #if defined(PETSC_USE_COMPLEX) 723 PetscBool realonly = PETSC_TRUE; 724 725 for (i=0; i<a->i[m]; i++) { 726 if (PetscImaginaryPart(a->a[i]) != 0.0) { 727 realonly = PETSC_FALSE; 728 break; 729 } 730 } 731 #endif 732 733 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 734 for (i=0; i<m; i++) { 735 jcnt = 0; 736 for (j=0; j<A->cmap->n; j++) { 737 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 738 value = a->a[cnt++]; 739 jcnt++; 740 } else { 741 value = 0.0; 742 } 743 #if defined(PETSC_USE_COMPLEX) 744 if (realonly) { 745 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 746 } else { 747 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 748 } 749 #else 750 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 751 #endif 752 } 753 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 754 } 755 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 756 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 757 PetscInt fshift=1; 758 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 759 #if defined(PETSC_USE_COMPLEX) 760 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix complex general\n");CHKERRQ(ierr); 761 #else 762 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix real general\n");CHKERRQ(ierr); 763 #endif 764 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 765 for (i=0; i<m; i++) { 766 for (j=a->i[i]; j<a->i[i+1]; j++) { 767 #if defined(PETSC_USE_COMPLEX) 768 if (PetscImaginaryPart(a->a[j]) > 0.0) { 769 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); 770 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 771 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); 772 } else { 773 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 774 } 775 #else 776 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 777 #endif 778 } 779 } 780 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 781 } else { 782 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 783 if (A->factortype) { 784 for (i=0; i<m; i++) { 785 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 786 /* L part */ 787 for (j=a->i[i]; j<a->i[i+1]; j++) { 788 #if defined(PETSC_USE_COMPLEX) 789 if (PetscImaginaryPart(a->a[j]) > 0.0) { 790 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 791 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 792 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 793 } else { 794 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 795 } 796 #else 797 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 798 #endif 799 } 800 /* diagonal */ 801 j = a->diag[i]; 802 #if defined(PETSC_USE_COMPLEX) 803 if (PetscImaginaryPart(a->a[j]) > 0.0) { 804 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); 805 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 806 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)(-PetscImaginaryPart(1.0/a->a[j])));CHKERRQ(ierr); 807 } else { 808 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 809 } 810 #else 811 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 812 #endif 813 814 /* U part */ 815 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 816 #if defined(PETSC_USE_COMPLEX) 817 if (PetscImaginaryPart(a->a[j]) > 0.0) { 818 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 819 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 820 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 821 } else { 822 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 823 } 824 #else 825 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 826 #endif 827 } 828 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 829 } 830 } else { 831 for (i=0; i<m; i++) { 832 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 833 for (j=a->i[i]; j<a->i[i+1]; j++) { 834 #if defined(PETSC_USE_COMPLEX) 835 if (PetscImaginaryPart(a->a[j]) > 0.0) { 836 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 837 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 838 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 839 } else { 840 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 841 } 842 #else 843 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 844 #endif 845 } 846 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 847 } 848 } 849 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 850 } 851 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 852 PetscFunctionReturn(0); 853 } 854 855 #include <petscdraw.h> 856 #undef __FUNCT__ 857 #define __FUNCT__ "MatView_SeqAIJ_Draw_Zoom" 858 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 859 { 860 Mat A = (Mat) Aa; 861 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 862 PetscErrorCode ierr; 863 PetscInt i,j,m = A->rmap->n,color; 864 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r,maxv = 0.0; 865 PetscViewer viewer; 866 PetscViewerFormat format; 867 868 PetscFunctionBegin; 869 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 870 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 871 872 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 873 /* loop over matrix elements drawing boxes */ 874 875 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 876 /* Blue for negative, Cyan for zero and Red for positive */ 877 color = PETSC_DRAW_BLUE; 878 for (i=0; i<m; i++) { 879 y_l = m - i - 1.0; y_r = y_l + 1.0; 880 for (j=a->i[i]; j<a->i[i+1]; j++) { 881 x_l = a->j[j]; x_r = x_l + 1.0; 882 if (PetscRealPart(a->a[j]) >= 0.) continue; 883 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 884 } 885 } 886 color = PETSC_DRAW_CYAN; 887 for (i=0; i<m; i++) { 888 y_l = m - i - 1.0; y_r = y_l + 1.0; 889 for (j=a->i[i]; j<a->i[i+1]; j++) { 890 x_l = a->j[j]; x_r = x_l + 1.0; 891 if (a->a[j] != 0.) continue; 892 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 893 } 894 } 895 color = PETSC_DRAW_RED; 896 for (i=0; i<m; i++) { 897 y_l = m - i - 1.0; y_r = y_l + 1.0; 898 for (j=a->i[i]; j<a->i[i+1]; j++) { 899 x_l = a->j[j]; x_r = x_l + 1.0; 900 if (PetscRealPart(a->a[j]) <= 0.) continue; 901 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 902 } 903 } 904 } else { 905 /* use contour shading to indicate magnitude of values */ 906 /* first determine max of all nonzero values */ 907 PetscInt nz = a->nz,count; 908 PetscDraw popup; 909 PetscReal scale; 910 911 for (i=0; i<nz; i++) { 912 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 913 } 914 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 915 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 916 if (popup) { 917 ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); 918 } 919 count = 0; 920 for (i=0; i<m; i++) { 921 y_l = m - i - 1.0; y_r = y_l + 1.0; 922 for (j=a->i[i]; j<a->i[i+1]; j++) { 923 x_l = a->j[j]; x_r = x_l + 1.0; 924 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(a->a[count])); 925 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 926 count++; 927 } 928 } 929 } 930 PetscFunctionReturn(0); 931 } 932 933 #include <petscdraw.h> 934 #undef __FUNCT__ 935 #define __FUNCT__ "MatView_SeqAIJ_Draw" 936 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 937 { 938 PetscErrorCode ierr; 939 PetscDraw draw; 940 PetscReal xr,yr,xl,yl,h,w; 941 PetscBool isnull; 942 943 PetscFunctionBegin; 944 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 945 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 946 if (isnull) PetscFunctionReturn(0); 947 948 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 949 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 950 xr += w; yr += h; xl = -w; yl = -h; 951 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 952 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 953 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 954 PetscFunctionReturn(0); 955 } 956 957 #undef __FUNCT__ 958 #define __FUNCT__ "MatView_SeqAIJ" 959 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 960 { 961 PetscErrorCode ierr; 962 PetscBool iascii,isbinary,isdraw; 963 964 PetscFunctionBegin; 965 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 966 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 967 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 968 if (iascii) { 969 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 970 } else if (isbinary) { 971 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 972 } else if (isdraw) { 973 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 974 } 975 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 976 PetscFunctionReturn(0); 977 } 978 979 #undef __FUNCT__ 980 #define __FUNCT__ "MatAssemblyEnd_SeqAIJ" 981 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 982 { 983 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 984 PetscErrorCode ierr; 985 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 986 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 987 MatScalar *aa = a->a,*ap; 988 PetscReal ratio = 0.6; 989 990 PetscFunctionBegin; 991 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 992 993 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 994 for (i=1; i<m; i++) { 995 /* move each row back by the amount of empty slots (fshift) before it*/ 996 fshift += imax[i-1] - ailen[i-1]; 997 rmax = PetscMax(rmax,ailen[i]); 998 if (fshift) { 999 ip = aj + ai[i]; 1000 ap = aa + ai[i]; 1001 N = ailen[i]; 1002 for (j=0; j<N; j++) { 1003 ip[j-fshift] = ip[j]; 1004 ap[j-fshift] = ap[j]; 1005 } 1006 } 1007 ai[i] = ai[i-1] + ailen[i-1]; 1008 } 1009 if (m) { 1010 fshift += imax[m-1] - ailen[m-1]; 1011 ai[m] = ai[m-1] + ailen[m-1]; 1012 } 1013 1014 /* reset ilen and imax for each row */ 1015 a->nonzerorowcnt = 0; 1016 for (i=0; i<m; i++) { 1017 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1018 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1019 } 1020 a->nz = ai[m]; 1021 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); 1022 1023 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1024 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1025 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1026 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1027 1028 A->info.mallocs += a->reallocs; 1029 a->reallocs = 0; 1030 A->info.nz_unneeded = (PetscReal)fshift; 1031 a->rmax = rmax; 1032 1033 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1034 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1035 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1036 PetscFunctionReturn(0); 1037 } 1038 1039 #undef __FUNCT__ 1040 #define __FUNCT__ "MatRealPart_SeqAIJ" 1041 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1042 { 1043 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1044 PetscInt i,nz = a->nz; 1045 MatScalar *aa = a->a; 1046 PetscErrorCode ierr; 1047 1048 PetscFunctionBegin; 1049 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1050 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1051 PetscFunctionReturn(0); 1052 } 1053 1054 #undef __FUNCT__ 1055 #define __FUNCT__ "MatImaginaryPart_SeqAIJ" 1056 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1057 { 1058 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1059 PetscInt i,nz = a->nz; 1060 MatScalar *aa = a->a; 1061 PetscErrorCode ierr; 1062 1063 PetscFunctionBegin; 1064 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1065 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1066 PetscFunctionReturn(0); 1067 } 1068 1069 #if defined(PETSC_THREADCOMM_ACTIVE) 1070 PetscErrorCode MatZeroEntries_SeqAIJ_Kernel(PetscInt thread_id,Mat A) 1071 { 1072 PetscErrorCode ierr; 1073 PetscInt *trstarts=A->rmap->trstarts; 1074 PetscInt n,start,end; 1075 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1076 1077 start = trstarts[thread_id]; 1078 end = trstarts[thread_id+1]; 1079 n = a->i[end] - a->i[start]; 1080 ierr = PetscMemzero(a->a+a->i[start],n*sizeof(PetscScalar));CHKERRQ(ierr); 1081 return 0; 1082 } 1083 1084 #undef __FUNCT__ 1085 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 1086 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1087 { 1088 PetscErrorCode ierr; 1089 1090 PetscFunctionBegin; 1091 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatZeroEntries_SeqAIJ_Kernel,1,A);CHKERRQ(ierr); 1092 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1093 PetscFunctionReturn(0); 1094 } 1095 #else 1096 #undef __FUNCT__ 1097 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 1098 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1099 { 1100 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1101 PetscErrorCode ierr; 1102 1103 PetscFunctionBegin; 1104 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1105 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1106 PetscFunctionReturn(0); 1107 } 1108 #endif 1109 1110 #undef __FUNCT__ 1111 #define __FUNCT__ "MatDestroy_SeqAIJ" 1112 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1113 { 1114 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1115 PetscErrorCode ierr; 1116 1117 PetscFunctionBegin; 1118 #if defined(PETSC_USE_LOG) 1119 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1120 #endif 1121 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1122 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1123 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1124 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1125 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1126 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1127 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1128 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1129 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1130 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1131 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1132 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 1133 ierr = MatDestroy(&a->XtoY);CHKERRQ(ierr); 1134 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1135 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1136 1137 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1138 ierr = PetscFree(A->data);CHKERRQ(ierr); 1139 1140 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1141 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1142 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1143 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1144 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1145 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1146 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1147 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1148 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1149 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1150 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1151 PetscFunctionReturn(0); 1152 } 1153 1154 #undef __FUNCT__ 1155 #define __FUNCT__ "MatSetOption_SeqAIJ" 1156 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1157 { 1158 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1159 PetscErrorCode ierr; 1160 1161 PetscFunctionBegin; 1162 switch (op) { 1163 case MAT_ROW_ORIENTED: 1164 a->roworiented = flg; 1165 break; 1166 case MAT_KEEP_NONZERO_PATTERN: 1167 a->keepnonzeropattern = flg; 1168 break; 1169 case MAT_NEW_NONZERO_LOCATIONS: 1170 a->nonew = (flg ? 0 : 1); 1171 break; 1172 case MAT_NEW_NONZERO_LOCATION_ERR: 1173 a->nonew = (flg ? -1 : 0); 1174 break; 1175 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1176 a->nonew = (flg ? -2 : 0); 1177 break; 1178 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1179 a->nounused = (flg ? -1 : 0); 1180 break; 1181 case MAT_IGNORE_ZERO_ENTRIES: 1182 a->ignorezeroentries = flg; 1183 break; 1184 case MAT_SPD: 1185 case MAT_SYMMETRIC: 1186 case MAT_STRUCTURALLY_SYMMETRIC: 1187 case MAT_HERMITIAN: 1188 case MAT_SYMMETRY_ETERNAL: 1189 /* These options are handled directly by MatSetOption() */ 1190 break; 1191 case MAT_NEW_DIAGONALS: 1192 case MAT_IGNORE_OFF_PROC_ENTRIES: 1193 case MAT_USE_HASH_TABLE: 1194 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1195 break; 1196 case MAT_USE_INODES: 1197 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1198 break; 1199 default: 1200 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1201 } 1202 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1203 PetscFunctionReturn(0); 1204 } 1205 1206 #undef __FUNCT__ 1207 #define __FUNCT__ "MatGetDiagonal_SeqAIJ" 1208 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1209 { 1210 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1211 PetscErrorCode ierr; 1212 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1213 PetscScalar *aa=a->a,*x,zero=0.0; 1214 1215 PetscFunctionBegin; 1216 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1217 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1218 1219 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1220 PetscInt *diag=a->diag; 1221 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1222 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1223 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1224 PetscFunctionReturn(0); 1225 } 1226 1227 ierr = VecSet(v,zero);CHKERRQ(ierr); 1228 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1229 for (i=0; i<n; i++) { 1230 nz = ai[i+1] - ai[i]; 1231 if (!nz) x[i] = 0.0; 1232 for (j=ai[i]; j<ai[i+1]; j++) { 1233 if (aj[j] == i) { 1234 x[i] = aa[j]; 1235 break; 1236 } 1237 } 1238 } 1239 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1240 PetscFunctionReturn(0); 1241 } 1242 1243 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1244 #undef __FUNCT__ 1245 #define __FUNCT__ "MatMultTransposeAdd_SeqAIJ" 1246 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1247 { 1248 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1249 PetscScalar *x,*y; 1250 PetscErrorCode ierr; 1251 PetscInt m = A->rmap->n; 1252 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1253 MatScalar *v; 1254 PetscScalar alpha; 1255 PetscInt n,i,j,*idx,*ii,*ridx=NULL; 1256 Mat_CompressedRow cprow = a->compressedrow; 1257 PetscBool usecprow = cprow.use; 1258 #endif 1259 1260 PetscFunctionBegin; 1261 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1262 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1263 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1264 1265 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1266 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1267 #else 1268 if (usecprow) { 1269 m = cprow.nrows; 1270 ii = cprow.i; 1271 ridx = cprow.rindex; 1272 } else { 1273 ii = a->i; 1274 } 1275 for (i=0; i<m; i++) { 1276 idx = a->j + ii[i]; 1277 v = a->a + ii[i]; 1278 n = ii[i+1] - ii[i]; 1279 if (usecprow) { 1280 alpha = x[ridx[i]]; 1281 } else { 1282 alpha = x[i]; 1283 } 1284 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1285 } 1286 #endif 1287 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1288 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1289 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1290 PetscFunctionReturn(0); 1291 } 1292 1293 #undef __FUNCT__ 1294 #define __FUNCT__ "MatMultTranspose_SeqAIJ" 1295 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1296 { 1297 PetscErrorCode ierr; 1298 1299 PetscFunctionBegin; 1300 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1301 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1302 PetscFunctionReturn(0); 1303 } 1304 1305 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1306 #if defined(PETSC_THREADCOMM_ACTIVE) 1307 PetscErrorCode MatMult_SeqAIJ_Kernel(PetscInt thread_id,Mat A,Vec xx,Vec yy) 1308 { 1309 PetscErrorCode ierr; 1310 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1311 PetscScalar *y; 1312 const PetscScalar *x; 1313 const MatScalar *aa; 1314 PetscInt *trstarts=A->rmap->trstarts; 1315 PetscInt n,start,end,i; 1316 const PetscInt *aj,*ai; 1317 PetscScalar sum; 1318 1319 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1320 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1321 start = trstarts[thread_id]; 1322 end = trstarts[thread_id+1]; 1323 aj = a->j; 1324 aa = a->a; 1325 ai = a->i; 1326 for (i=start; i<end; i++) { 1327 n = ai[i+1] - ai[i]; 1328 aj = a->j + ai[i]; 1329 aa = a->a + ai[i]; 1330 sum = 0.0; 1331 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1332 y[i] = sum; 1333 } 1334 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1335 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1336 return 0; 1337 } 1338 1339 #undef __FUNCT__ 1340 #define __FUNCT__ "MatMult_SeqAIJ" 1341 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1342 { 1343 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1344 PetscScalar *y; 1345 const PetscScalar *x; 1346 const MatScalar *aa; 1347 PetscErrorCode ierr; 1348 PetscInt m=A->rmap->n; 1349 const PetscInt *aj,*ii,*ridx=NULL; 1350 PetscInt n,i; 1351 PetscScalar sum; 1352 PetscBool usecprow=a->compressedrow.use; 1353 1354 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1355 #pragma disjoint(*x,*y,*aa) 1356 #endif 1357 1358 PetscFunctionBegin; 1359 aj = a->j; 1360 aa = a->a; 1361 ii = a->i; 1362 if (usecprow) { /* use compressed row format */ 1363 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1364 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1365 m = a->compressedrow.nrows; 1366 ii = a->compressedrow.i; 1367 ridx = a->compressedrow.rindex; 1368 for (i=0; i<m; i++) { 1369 n = ii[i+1] - ii[i]; 1370 aj = a->j + ii[i]; 1371 aa = a->a + ii[i]; 1372 sum = 0.0; 1373 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1374 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1375 y[*ridx++] = sum; 1376 } 1377 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1378 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1379 } else { /* do not use compressed row format */ 1380 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1381 fortranmultaij_(&m,x,ii,aj,aa,y); 1382 #else 1383 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatMult_SeqAIJ_Kernel,3,A,xx,yy);CHKERRQ(ierr); 1384 #endif 1385 } 1386 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1387 PetscFunctionReturn(0); 1388 } 1389 #else 1390 #undef __FUNCT__ 1391 #define __FUNCT__ "MatMult_SeqAIJ" 1392 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1393 { 1394 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1395 PetscScalar *y; 1396 const PetscScalar *x; 1397 const MatScalar *aa; 1398 PetscErrorCode ierr; 1399 PetscInt m=A->rmap->n; 1400 const PetscInt *aj,*ii,*ridx=NULL; 1401 PetscInt n,i; 1402 PetscScalar sum; 1403 PetscBool usecprow=a->compressedrow.use; 1404 1405 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1406 #pragma disjoint(*x,*y,*aa) 1407 #endif 1408 1409 PetscFunctionBegin; 1410 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1411 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1412 aj = a->j; 1413 aa = a->a; 1414 ii = a->i; 1415 if (usecprow) { /* use compressed row format */ 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,*jj = a->j,i; 1678 1679 PetscFunctionBegin; 1680 *missing = PETSC_FALSE; 1681 if (A->rmap->n > 0 && !jj) { 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 (jj[diag[i]] != i) { 1689 *missing = PETSC_TRUE; 1690 if (d) *d = i; 1691 PetscInfo1(A,"Matrix is missing diagonal number %D",i); 1692 break; 1693 } 1694 } 1695 } 1696 PetscFunctionReturn(0); 1697 } 1698 1699 #undef __FUNCT__ 1700 #define __FUNCT__ "MatInvertDiagonal_SeqAIJ" 1701 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1702 { 1703 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1704 PetscErrorCode ierr; 1705 PetscInt i,*diag,m = A->rmap->n; 1706 MatScalar *v = a->a; 1707 PetscScalar *idiag,*mdiag; 1708 1709 PetscFunctionBegin; 1710 if (a->idiagvalid) PetscFunctionReturn(0); 1711 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1712 diag = a->diag; 1713 if (!a->idiag) { 1714 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1715 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1716 v = a->a; 1717 } 1718 mdiag = a->mdiag; 1719 idiag = a->idiag; 1720 1721 if (omega == 1.0 && !PetscAbsScalar(fshift)) { 1722 for (i=0; i<m; i++) { 1723 mdiag[i] = v[diag[i]]; 1724 if (!PetscAbsScalar(mdiag[i])) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1725 idiag[i] = 1.0/v[diag[i]]; 1726 } 1727 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1728 } else { 1729 for (i=0; i<m; i++) { 1730 mdiag[i] = v[diag[i]]; 1731 idiag[i] = omega/(fshift + v[diag[i]]); 1732 } 1733 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1734 } 1735 a->idiagvalid = PETSC_TRUE; 1736 PetscFunctionReturn(0); 1737 } 1738 1739 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1740 #undef __FUNCT__ 1741 #define __FUNCT__ "MatSOR_SeqAIJ" 1742 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1743 { 1744 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1745 PetscScalar *x,d,sum,*t,scale; 1746 const MatScalar *v = a->a,*idiag=0,*mdiag; 1747 const PetscScalar *b, *bs,*xb, *ts; 1748 PetscErrorCode ierr; 1749 PetscInt n = A->cmap->n,m = A->rmap->n,i; 1750 const PetscInt *idx,*diag; 1751 1752 PetscFunctionBegin; 1753 its = its*lits; 1754 1755 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1756 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1757 a->fshift = fshift; 1758 a->omega = omega; 1759 1760 diag = a->diag; 1761 t = a->ssor_work; 1762 idiag = a->idiag; 1763 mdiag = a->mdiag; 1764 1765 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1766 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1767 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1768 if (flag == SOR_APPLY_UPPER) { 1769 /* apply (U + D/omega) to the vector */ 1770 bs = b; 1771 for (i=0; i<m; i++) { 1772 d = fshift + mdiag[i]; 1773 n = a->i[i+1] - diag[i] - 1; 1774 idx = a->j + diag[i] + 1; 1775 v = a->a + diag[i] + 1; 1776 sum = b[i]*d/omega; 1777 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1778 x[i] = sum; 1779 } 1780 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1781 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1782 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1783 PetscFunctionReturn(0); 1784 } 1785 1786 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1787 else if (flag & SOR_EISENSTAT) { 1788 /* Let A = L + U + D; where L is lower trianglar, 1789 U is upper triangular, E = D/omega; This routine applies 1790 1791 (L + E)^{-1} A (U + E)^{-1} 1792 1793 to a vector efficiently using Eisenstat's trick. 1794 */ 1795 scale = (2.0/omega) - 1.0; 1796 1797 /* x = (E + U)^{-1} b */ 1798 for (i=m-1; i>=0; i--) { 1799 n = a->i[i+1] - diag[i] - 1; 1800 idx = a->j + diag[i] + 1; 1801 v = a->a + diag[i] + 1; 1802 sum = b[i]; 1803 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1804 x[i] = sum*idiag[i]; 1805 } 1806 1807 /* t = b - (2*E - D)x */ 1808 v = a->a; 1809 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1810 1811 /* t = (E + L)^{-1}t */ 1812 ts = t; 1813 diag = a->diag; 1814 for (i=0; i<m; i++) { 1815 n = diag[i] - a->i[i]; 1816 idx = a->j + a->i[i]; 1817 v = a->a + a->i[i]; 1818 sum = t[i]; 1819 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1820 t[i] = sum*idiag[i]; 1821 /* x = x + t */ 1822 x[i] += t[i]; 1823 } 1824 1825 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1826 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1827 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1828 PetscFunctionReturn(0); 1829 } 1830 if (flag & SOR_ZERO_INITIAL_GUESS) { 1831 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1832 for (i=0; i<m; i++) { 1833 n = diag[i] - a->i[i]; 1834 idx = a->j + a->i[i]; 1835 v = a->a + a->i[i]; 1836 sum = b[i]; 1837 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1838 t[i] = sum; 1839 x[i] = sum*idiag[i]; 1840 } 1841 xb = t; 1842 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1843 } else xb = b; 1844 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1845 for (i=m-1; i>=0; i--) { 1846 n = a->i[i+1] - diag[i] - 1; 1847 idx = a->j + diag[i] + 1; 1848 v = a->a + diag[i] + 1; 1849 sum = xb[i]; 1850 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1851 if (xb == b) { 1852 x[i] = sum*idiag[i]; 1853 } else { 1854 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1855 } 1856 } 1857 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1858 } 1859 its--; 1860 } 1861 while (its--) { 1862 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1863 for (i=0; i<m; i++) { 1864 /* lower */ 1865 n = diag[i] - a->i[i]; 1866 idx = a->j + a->i[i]; 1867 v = a->a + a->i[i]; 1868 sum = b[i]; 1869 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1870 t[i] = sum; /* save application of the lower-triangular part */ 1871 /* upper */ 1872 n = a->i[i+1] - diag[i] - 1; 1873 idx = a->j + diag[i] + 1; 1874 v = a->a + diag[i] + 1; 1875 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1876 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1877 } 1878 xb = t; 1879 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1880 } else xb = b; 1881 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1882 for (i=m-1; i>=0; i--) { 1883 sum = xb[i]; 1884 if (xb == b) { 1885 /* whole matrix (no checkpointing available) */ 1886 n = a->i[i+1] - a->i[i]; 1887 idx = a->j + a->i[i]; 1888 v = a->a + a->i[i]; 1889 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1890 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1891 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1892 n = a->i[i+1] - diag[i] - 1; 1893 idx = a->j + diag[i] + 1; 1894 v = a->a + diag[i] + 1; 1895 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1896 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1897 } 1898 } 1899 if (xb == b) { 1900 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1901 } else { 1902 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1903 } 1904 } 1905 } 1906 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1907 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1908 PetscFunctionReturn(0); 1909 } 1910 1911 1912 #undef __FUNCT__ 1913 #define __FUNCT__ "MatGetInfo_SeqAIJ" 1914 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1915 { 1916 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1917 1918 PetscFunctionBegin; 1919 info->block_size = 1.0; 1920 info->nz_allocated = (double)a->maxnz; 1921 info->nz_used = (double)a->nz; 1922 info->nz_unneeded = (double)(a->maxnz - a->nz); 1923 info->assemblies = (double)A->num_ass; 1924 info->mallocs = (double)A->info.mallocs; 1925 info->memory = ((PetscObject)A)->mem; 1926 if (A->factortype) { 1927 info->fill_ratio_given = A->info.fill_ratio_given; 1928 info->fill_ratio_needed = A->info.fill_ratio_needed; 1929 info->factor_mallocs = A->info.factor_mallocs; 1930 } else { 1931 info->fill_ratio_given = 0; 1932 info->fill_ratio_needed = 0; 1933 info->factor_mallocs = 0; 1934 } 1935 PetscFunctionReturn(0); 1936 } 1937 1938 #undef __FUNCT__ 1939 #define __FUNCT__ "MatZeroRows_SeqAIJ" 1940 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1941 { 1942 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1943 PetscInt i,m = A->rmap->n - 1,d = 0; 1944 PetscErrorCode ierr; 1945 const PetscScalar *xx; 1946 PetscScalar *bb; 1947 PetscBool missing; 1948 1949 PetscFunctionBegin; 1950 if (x && b) { 1951 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1952 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1953 for (i=0; i<N; i++) { 1954 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1955 bb[rows[i]] = diag*xx[rows[i]]; 1956 } 1957 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1958 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1959 } 1960 1961 if (a->keepnonzeropattern) { 1962 for (i=0; i<N; i++) { 1963 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1964 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1965 } 1966 if (diag != 0.0) { 1967 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1968 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1969 for (i=0; i<N; i++) { 1970 a->a[a->diag[rows[i]]] = diag; 1971 } 1972 } 1973 } else { 1974 if (diag != 0.0) { 1975 for (i=0; i<N; i++) { 1976 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1977 if (a->ilen[rows[i]] > 0) { 1978 a->ilen[rows[i]] = 1; 1979 a->a[a->i[rows[i]]] = diag; 1980 a->j[a->i[rows[i]]] = rows[i]; 1981 } else { /* in case row was completely empty */ 1982 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1983 } 1984 } 1985 } else { 1986 for (i=0; i<N; i++) { 1987 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1988 a->ilen[rows[i]] = 0; 1989 } 1990 } 1991 A->nonzerostate++; 1992 } 1993 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1994 PetscFunctionReturn(0); 1995 } 1996 1997 #undef __FUNCT__ 1998 #define __FUNCT__ "MatZeroRowsColumns_SeqAIJ" 1999 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 2000 { 2001 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2002 PetscInt i,j,m = A->rmap->n - 1,d = 0; 2003 PetscErrorCode ierr; 2004 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 2005 const PetscScalar *xx; 2006 PetscScalar *bb; 2007 2008 PetscFunctionBegin; 2009 if (x && b) { 2010 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 2011 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 2012 vecs = PETSC_TRUE; 2013 } 2014 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 2015 for (i=0; i<N; i++) { 2016 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 2017 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 2018 2019 zeroed[rows[i]] = PETSC_TRUE; 2020 } 2021 for (i=0; i<A->rmap->n; i++) { 2022 if (!zeroed[i]) { 2023 for (j=a->i[i]; j<a->i[i+1]; j++) { 2024 if (zeroed[a->j[j]]) { 2025 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 2026 a->a[j] = 0.0; 2027 } 2028 } 2029 } else if (vecs) bb[i] = diag*xx[i]; 2030 } 2031 if (x && b) { 2032 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 2033 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 2034 } 2035 ierr = PetscFree(zeroed);CHKERRQ(ierr); 2036 if (diag != 0.0) { 2037 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 2038 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 2039 for (i=0; i<N; i++) { 2040 a->a[a->diag[rows[i]]] = diag; 2041 } 2042 } 2043 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2044 PetscFunctionReturn(0); 2045 } 2046 2047 #undef __FUNCT__ 2048 #define __FUNCT__ "MatGetRow_SeqAIJ" 2049 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2050 { 2051 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2052 PetscInt *itmp; 2053 2054 PetscFunctionBegin; 2055 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 2056 2057 *nz = a->i[row+1] - a->i[row]; 2058 if (v) *v = a->a + a->i[row]; 2059 if (idx) { 2060 itmp = a->j + a->i[row]; 2061 if (*nz) *idx = itmp; 2062 else *idx = 0; 2063 } 2064 PetscFunctionReturn(0); 2065 } 2066 2067 /* remove this function? */ 2068 #undef __FUNCT__ 2069 #define __FUNCT__ "MatRestoreRow_SeqAIJ" 2070 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 2071 { 2072 PetscFunctionBegin; 2073 PetscFunctionReturn(0); 2074 } 2075 2076 #undef __FUNCT__ 2077 #define __FUNCT__ "MatNorm_SeqAIJ" 2078 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 2079 { 2080 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2081 MatScalar *v = a->a; 2082 PetscReal sum = 0.0; 2083 PetscErrorCode ierr; 2084 PetscInt i,j; 2085 2086 PetscFunctionBegin; 2087 if (type == NORM_FROBENIUS) { 2088 for (i=0; i<a->nz; i++) { 2089 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2090 } 2091 *nrm = PetscSqrtReal(sum); 2092 } else if (type == NORM_1) { 2093 PetscReal *tmp; 2094 PetscInt *jj = a->j; 2095 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 2096 *nrm = 0.0; 2097 for (j=0; j<a->nz; j++) { 2098 tmp[*jj++] += PetscAbsScalar(*v); v++; 2099 } 2100 for (j=0; j<A->cmap->n; j++) { 2101 if (tmp[j] > *nrm) *nrm = tmp[j]; 2102 } 2103 ierr = PetscFree(tmp);CHKERRQ(ierr); 2104 } else if (type == NORM_INFINITY) { 2105 *nrm = 0.0; 2106 for (j=0; j<A->rmap->n; j++) { 2107 v = a->a + a->i[j]; 2108 sum = 0.0; 2109 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2110 sum += PetscAbsScalar(*v); v++; 2111 } 2112 if (sum > *nrm) *nrm = sum; 2113 } 2114 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2115 PetscFunctionReturn(0); 2116 } 2117 2118 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2119 #undef __FUNCT__ 2120 #define __FUNCT__ "MatTransposeSymbolic_SeqAIJ" 2121 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2122 { 2123 PetscErrorCode ierr; 2124 PetscInt i,j,anzj; 2125 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2126 PetscInt an=A->cmap->N,am=A->rmap->N; 2127 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2128 2129 PetscFunctionBegin; 2130 /* Allocate space for symbolic transpose info and work array */ 2131 ierr = PetscCalloc1((an+1),&ati);CHKERRQ(ierr); 2132 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 2133 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 2134 2135 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2136 /* Note: offset by 1 for fast conversion into csr format. */ 2137 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2138 /* Form ati for csr format of A^T. */ 2139 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2140 2141 /* Copy ati into atfill so we have locations of the next free space in atj */ 2142 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2143 2144 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2145 for (i=0;i<am;i++) { 2146 anzj = ai[i+1] - ai[i]; 2147 for (j=0;j<anzj;j++) { 2148 atj[atfill[*aj]] = i; 2149 atfill[*aj++] += 1; 2150 } 2151 } 2152 2153 /* Clean up temporary space and complete requests. */ 2154 ierr = PetscFree(atfill);CHKERRQ(ierr); 2155 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2156 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2157 2158 b = (Mat_SeqAIJ*)((*B)->data); 2159 b->free_a = PETSC_FALSE; 2160 b->free_ij = PETSC_TRUE; 2161 b->nonew = 0; 2162 PetscFunctionReturn(0); 2163 } 2164 2165 #undef __FUNCT__ 2166 #define __FUNCT__ "MatTranspose_SeqAIJ" 2167 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2168 { 2169 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2170 Mat C; 2171 PetscErrorCode ierr; 2172 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2173 MatScalar *array = a->a; 2174 2175 PetscFunctionBegin; 2176 if (reuse == MAT_REUSE_MATRIX && A == *B && m != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2177 2178 if (reuse == MAT_INITIAL_MATRIX || *B == A) { 2179 ierr = PetscCalloc1((1+A->cmap->n),&col);CHKERRQ(ierr); 2180 2181 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2182 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2183 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2184 ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2185 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2186 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2187 ierr = PetscFree(col);CHKERRQ(ierr); 2188 } else { 2189 C = *B; 2190 } 2191 2192 for (i=0; i<m; i++) { 2193 len = ai[i+1]-ai[i]; 2194 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2195 array += len; 2196 aj += len; 2197 } 2198 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2199 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2200 2201 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 2202 *B = C; 2203 } else { 2204 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 2205 } 2206 PetscFunctionReturn(0); 2207 } 2208 2209 #undef __FUNCT__ 2210 #define __FUNCT__ "MatIsTranspose_SeqAIJ" 2211 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2212 { 2213 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2214 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2215 MatScalar *va,*vb; 2216 PetscErrorCode ierr; 2217 PetscInt ma,na,mb,nb, i; 2218 2219 PetscFunctionBegin; 2220 bij = (Mat_SeqAIJ*) B->data; 2221 2222 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2223 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2224 if (ma!=nb || na!=mb) { 2225 *f = PETSC_FALSE; 2226 PetscFunctionReturn(0); 2227 } 2228 aii = aij->i; bii = bij->i; 2229 adx = aij->j; bdx = bij->j; 2230 va = aij->a; vb = bij->a; 2231 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2232 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2233 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2234 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2235 2236 *f = PETSC_TRUE; 2237 for (i=0; i<ma; i++) { 2238 while (aptr[i]<aii[i+1]) { 2239 PetscInt idc,idr; 2240 PetscScalar vc,vr; 2241 /* column/row index/value */ 2242 idc = adx[aptr[i]]; 2243 idr = bdx[bptr[idc]]; 2244 vc = va[aptr[i]]; 2245 vr = vb[bptr[idc]]; 2246 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2247 *f = PETSC_FALSE; 2248 goto done; 2249 } else { 2250 aptr[i]++; 2251 if (B || i!=idc) bptr[idc]++; 2252 } 2253 } 2254 } 2255 done: 2256 ierr = PetscFree(aptr);CHKERRQ(ierr); 2257 ierr = PetscFree(bptr);CHKERRQ(ierr); 2258 PetscFunctionReturn(0); 2259 } 2260 2261 #undef __FUNCT__ 2262 #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" 2263 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2264 { 2265 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2266 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2267 MatScalar *va,*vb; 2268 PetscErrorCode ierr; 2269 PetscInt ma,na,mb,nb, i; 2270 2271 PetscFunctionBegin; 2272 bij = (Mat_SeqAIJ*) B->data; 2273 2274 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2275 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2276 if (ma!=nb || na!=mb) { 2277 *f = PETSC_FALSE; 2278 PetscFunctionReturn(0); 2279 } 2280 aii = aij->i; bii = bij->i; 2281 adx = aij->j; bdx = bij->j; 2282 va = aij->a; vb = bij->a; 2283 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2284 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2285 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2286 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2287 2288 *f = PETSC_TRUE; 2289 for (i=0; i<ma; i++) { 2290 while (aptr[i]<aii[i+1]) { 2291 PetscInt idc,idr; 2292 PetscScalar vc,vr; 2293 /* column/row index/value */ 2294 idc = adx[aptr[i]]; 2295 idr = bdx[bptr[idc]]; 2296 vc = va[aptr[i]]; 2297 vr = vb[bptr[idc]]; 2298 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2299 *f = PETSC_FALSE; 2300 goto done; 2301 } else { 2302 aptr[i]++; 2303 if (B || i!=idc) bptr[idc]++; 2304 } 2305 } 2306 } 2307 done: 2308 ierr = PetscFree(aptr);CHKERRQ(ierr); 2309 ierr = PetscFree(bptr);CHKERRQ(ierr); 2310 PetscFunctionReturn(0); 2311 } 2312 2313 #undef __FUNCT__ 2314 #define __FUNCT__ "MatIsSymmetric_SeqAIJ" 2315 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2316 { 2317 PetscErrorCode ierr; 2318 2319 PetscFunctionBegin; 2320 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2321 PetscFunctionReturn(0); 2322 } 2323 2324 #undef __FUNCT__ 2325 #define __FUNCT__ "MatIsHermitian_SeqAIJ" 2326 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2327 { 2328 PetscErrorCode ierr; 2329 2330 PetscFunctionBegin; 2331 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2332 PetscFunctionReturn(0); 2333 } 2334 2335 #undef __FUNCT__ 2336 #define __FUNCT__ "MatDiagonalScale_SeqAIJ" 2337 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2338 { 2339 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2340 PetscScalar *l,*r,x; 2341 MatScalar *v; 2342 PetscErrorCode ierr; 2343 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; 2344 2345 PetscFunctionBegin; 2346 if (ll) { 2347 /* The local size is used so that VecMPI can be passed to this routine 2348 by MatDiagonalScale_MPIAIJ */ 2349 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2350 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2351 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 2352 v = a->a; 2353 for (i=0; i<m; i++) { 2354 x = l[i]; 2355 M = a->i[i+1] - a->i[i]; 2356 for (j=0; j<M; j++) (*v++) *= x; 2357 } 2358 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 2359 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2360 } 2361 if (rr) { 2362 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2363 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2364 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 2365 v = a->a; jj = a->j; 2366 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2367 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 2368 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2369 } 2370 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2371 PetscFunctionReturn(0); 2372 } 2373 2374 #undef __FUNCT__ 2375 #define __FUNCT__ "MatGetSubMatrix_SeqAIJ" 2376 PetscErrorCode MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2377 { 2378 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2379 PetscErrorCode ierr; 2380 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2381 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2382 const PetscInt *irow,*icol; 2383 PetscInt nrows,ncols; 2384 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2385 MatScalar *a_new,*mat_a; 2386 Mat C; 2387 PetscBool stride,sorted; 2388 2389 PetscFunctionBegin; 2390 ierr = ISSorted(isrow,&sorted);CHKERRQ(ierr); 2391 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted"); 2392 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); 2393 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted"); 2394 2395 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2396 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2397 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2398 2399 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2400 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2401 if (stride && step == 1) { 2402 /* special case of contiguous rows */ 2403 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2404 /* loop over new rows determining lens and starting points */ 2405 for (i=0; i<nrows; i++) { 2406 kstart = ai[irow[i]]; 2407 kend = kstart + ailen[irow[i]]; 2408 for (k=kstart; k<kend; k++) { 2409 if (aj[k] >= first) { 2410 starts[i] = k; 2411 break; 2412 } 2413 } 2414 sum = 0; 2415 while (k < kend) { 2416 if (aj[k++] >= first+ncols) break; 2417 sum++; 2418 } 2419 lens[i] = sum; 2420 } 2421 /* create submatrix */ 2422 if (scall == MAT_REUSE_MATRIX) { 2423 PetscInt n_cols,n_rows; 2424 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2425 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2426 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2427 C = *B; 2428 } else { 2429 PetscInt rbs,cbs; 2430 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2431 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2432 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2433 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2434 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2435 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2436 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2437 } 2438 c = (Mat_SeqAIJ*)C->data; 2439 2440 /* loop over rows inserting into submatrix */ 2441 a_new = c->a; 2442 j_new = c->j; 2443 i_new = c->i; 2444 2445 for (i=0; i<nrows; i++) { 2446 ii = starts[i]; 2447 lensi = lens[i]; 2448 for (k=0; k<lensi; k++) { 2449 *j_new++ = aj[ii+k] - first; 2450 } 2451 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2452 a_new += lensi; 2453 i_new[i+1] = i_new[i] + lensi; 2454 c->ilen[i] = lensi; 2455 } 2456 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2457 } else { 2458 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2459 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2460 ierr = PetscMalloc1((1+nrows),&lens);CHKERRQ(ierr); 2461 for (i=0; i<ncols; i++) { 2462 #if defined(PETSC_USE_DEBUG) 2463 if (icol[i] >= oldcols) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Requesting column beyond largest column icol[%D] %D <= A->cmap->n %D",i,icol[i],oldcols); 2464 #endif 2465 smap[icol[i]] = i+1; 2466 } 2467 2468 /* determine lens of each row */ 2469 for (i=0; i<nrows; i++) { 2470 kstart = ai[irow[i]]; 2471 kend = kstart + a->ilen[irow[i]]; 2472 lens[i] = 0; 2473 for (k=kstart; k<kend; k++) { 2474 if (smap[aj[k]]) { 2475 lens[i]++; 2476 } 2477 } 2478 } 2479 /* Create and fill new matrix */ 2480 if (scall == MAT_REUSE_MATRIX) { 2481 PetscBool equal; 2482 2483 c = (Mat_SeqAIJ*)((*B)->data); 2484 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2485 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2486 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2487 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2488 C = *B; 2489 } else { 2490 PetscInt rbs,cbs; 2491 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2492 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2493 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2494 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2495 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2496 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2497 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2498 } 2499 c = (Mat_SeqAIJ*)(C->data); 2500 for (i=0; i<nrows; i++) { 2501 row = irow[i]; 2502 kstart = ai[row]; 2503 kend = kstart + a->ilen[row]; 2504 mat_i = c->i[i]; 2505 mat_j = c->j + mat_i; 2506 mat_a = c->a + mat_i; 2507 mat_ilen = c->ilen + i; 2508 for (k=kstart; k<kend; k++) { 2509 if ((tcol=smap[a->j[k]])) { 2510 *mat_j++ = tcol - 1; 2511 *mat_a++ = a->a[k]; 2512 (*mat_ilen)++; 2513 2514 } 2515 } 2516 } 2517 /* Free work space */ 2518 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2519 ierr = PetscFree(smap);CHKERRQ(ierr); 2520 ierr = PetscFree(lens);CHKERRQ(ierr); 2521 } 2522 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2523 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2524 2525 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2526 *B = C; 2527 PetscFunctionReturn(0); 2528 } 2529 2530 #undef __FUNCT__ 2531 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 2532 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2533 { 2534 PetscErrorCode ierr; 2535 Mat B; 2536 2537 PetscFunctionBegin; 2538 if (scall == MAT_INITIAL_MATRIX) { 2539 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2540 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2541 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2542 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2543 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2544 *subMat = B; 2545 } else { 2546 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2547 } 2548 PetscFunctionReturn(0); 2549 } 2550 2551 #undef __FUNCT__ 2552 #define __FUNCT__ "MatILUFactor_SeqAIJ" 2553 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2554 { 2555 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2556 PetscErrorCode ierr; 2557 Mat outA; 2558 PetscBool row_identity,col_identity; 2559 2560 PetscFunctionBegin; 2561 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2562 2563 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2564 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2565 2566 outA = inA; 2567 outA->factortype = MAT_FACTOR_LU; 2568 2569 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2570 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2571 2572 a->row = row; 2573 2574 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2575 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2576 2577 a->col = col; 2578 2579 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2580 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2581 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2582 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2583 2584 if (!a->solve_work) { /* this matrix may have been factored before */ 2585 ierr = PetscMalloc1((inA->rmap->n+1),&a->solve_work);CHKERRQ(ierr); 2586 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2587 } 2588 2589 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2590 if (row_identity && col_identity) { 2591 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2592 } else { 2593 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2594 } 2595 PetscFunctionReturn(0); 2596 } 2597 2598 #undef __FUNCT__ 2599 #define __FUNCT__ "MatScale_SeqAIJ" 2600 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2601 { 2602 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2603 PetscScalar oalpha = alpha; 2604 PetscErrorCode ierr; 2605 PetscBLASInt one = 1,bnz; 2606 2607 PetscFunctionBegin; 2608 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2609 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2610 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2611 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2612 PetscFunctionReturn(0); 2613 } 2614 2615 #undef __FUNCT__ 2616 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 2617 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2618 { 2619 PetscErrorCode ierr; 2620 PetscInt i; 2621 2622 PetscFunctionBegin; 2623 if (scall == MAT_INITIAL_MATRIX) { 2624 ierr = PetscMalloc1((n+1),B);CHKERRQ(ierr); 2625 } 2626 2627 for (i=0; i<n; i++) { 2628 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2629 } 2630 PetscFunctionReturn(0); 2631 } 2632 2633 #undef __FUNCT__ 2634 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 2635 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2636 { 2637 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2638 PetscErrorCode ierr; 2639 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2640 const PetscInt *idx; 2641 PetscInt start,end,*ai,*aj; 2642 PetscBT table; 2643 2644 PetscFunctionBegin; 2645 m = A->rmap->n; 2646 ai = a->i; 2647 aj = a->j; 2648 2649 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2650 2651 ierr = PetscMalloc1((m+1),&nidx);CHKERRQ(ierr); 2652 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2653 2654 for (i=0; i<is_max; i++) { 2655 /* Initialize the two local arrays */ 2656 isz = 0; 2657 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2658 2659 /* Extract the indices, assume there can be duplicate entries */ 2660 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2661 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2662 2663 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2664 for (j=0; j<n; ++j) { 2665 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2666 } 2667 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2668 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2669 2670 k = 0; 2671 for (j=0; j<ov; j++) { /* for each overlap */ 2672 n = isz; 2673 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2674 row = nidx[k]; 2675 start = ai[row]; 2676 end = ai[row+1]; 2677 for (l = start; l<end; l++) { 2678 val = aj[l]; 2679 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2680 } 2681 } 2682 } 2683 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2684 } 2685 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2686 ierr = PetscFree(nidx);CHKERRQ(ierr); 2687 PetscFunctionReturn(0); 2688 } 2689 2690 /* -------------------------------------------------------------- */ 2691 #undef __FUNCT__ 2692 #define __FUNCT__ "MatPermute_SeqAIJ" 2693 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2694 { 2695 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2696 PetscErrorCode ierr; 2697 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2698 const PetscInt *row,*col; 2699 PetscInt *cnew,j,*lens; 2700 IS icolp,irowp; 2701 PetscInt *cwork = NULL; 2702 PetscScalar *vwork = NULL; 2703 2704 PetscFunctionBegin; 2705 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2706 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2707 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2708 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2709 2710 /* determine lengths of permuted rows */ 2711 ierr = PetscMalloc1((m+1),&lens);CHKERRQ(ierr); 2712 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2713 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2714 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2715 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2716 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2717 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2718 ierr = PetscFree(lens);CHKERRQ(ierr); 2719 2720 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2721 for (i=0; i<m; i++) { 2722 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2723 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2724 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2725 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2726 } 2727 ierr = PetscFree(cnew);CHKERRQ(ierr); 2728 2729 (*B)->assembled = PETSC_FALSE; 2730 2731 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2732 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2733 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2734 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2735 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2736 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2737 PetscFunctionReturn(0); 2738 } 2739 2740 #undef __FUNCT__ 2741 #define __FUNCT__ "MatCopy_SeqAIJ" 2742 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2743 { 2744 PetscErrorCode ierr; 2745 2746 PetscFunctionBegin; 2747 /* If the two matrices have the same copy implementation, use fast copy. */ 2748 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2749 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2750 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2751 2752 if (a->i[A->rmap->n] != b->i[B->rmap->n]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different"); 2753 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2754 } else { 2755 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2756 } 2757 PetscFunctionReturn(0); 2758 } 2759 2760 #undef __FUNCT__ 2761 #define __FUNCT__ "MatSetUp_SeqAIJ" 2762 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2763 { 2764 PetscErrorCode ierr; 2765 2766 PetscFunctionBegin; 2767 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2768 PetscFunctionReturn(0); 2769 } 2770 2771 #undef __FUNCT__ 2772 #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" 2773 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2774 { 2775 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2776 2777 PetscFunctionBegin; 2778 *array = a->a; 2779 PetscFunctionReturn(0); 2780 } 2781 2782 #undef __FUNCT__ 2783 #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" 2784 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2785 { 2786 PetscFunctionBegin; 2787 PetscFunctionReturn(0); 2788 } 2789 2790 /* 2791 Computes the number of nonzeros per row needed for preallocation when X and Y 2792 have different nonzero structure. 2793 */ 2794 #undef __FUNCT__ 2795 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 2796 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2797 { 2798 PetscInt i,m=Y->rmap->N; 2799 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2800 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2801 const PetscInt *xi = x->i,*yi = y->i; 2802 2803 PetscFunctionBegin; 2804 /* Set the number of nonzeros in the new matrix */ 2805 for (i=0; i<m; i++) { 2806 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2807 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2808 nnz[i] = 0; 2809 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2810 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 2811 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 2812 nnz[i]++; 2813 } 2814 for (; k<nzy; k++) nnz[i]++; 2815 } 2816 PetscFunctionReturn(0); 2817 } 2818 2819 #undef __FUNCT__ 2820 #define __FUNCT__ "MatAXPY_SeqAIJ" 2821 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2822 { 2823 PetscErrorCode ierr; 2824 PetscInt i; 2825 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2826 PetscBLASInt one=1,bnz; 2827 2828 PetscFunctionBegin; 2829 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2830 if (str == SAME_NONZERO_PATTERN) { 2831 PetscScalar alpha = a; 2832 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2833 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2834 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2835 if (y->xtoy && y->XtoY != X) { 2836 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2837 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 2838 } 2839 if (!y->xtoy) { /* get xtoy */ 2840 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 2841 y->XtoY = X; 2842 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2843 } 2844 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2845 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); 2846 } else { 2847 Mat B; 2848 PetscInt *nnz; 2849 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2850 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2851 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2852 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2853 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2854 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2855 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2856 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2857 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2858 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2859 ierr = PetscFree(nnz);CHKERRQ(ierr); 2860 } 2861 PetscFunctionReturn(0); 2862 } 2863 2864 #undef __FUNCT__ 2865 #define __FUNCT__ "MatConjugate_SeqAIJ" 2866 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2867 { 2868 #if defined(PETSC_USE_COMPLEX) 2869 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2870 PetscInt i,nz; 2871 PetscScalar *a; 2872 2873 PetscFunctionBegin; 2874 nz = aij->nz; 2875 a = aij->a; 2876 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2877 #else 2878 PetscFunctionBegin; 2879 #endif 2880 PetscFunctionReturn(0); 2881 } 2882 2883 #undef __FUNCT__ 2884 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 2885 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2886 { 2887 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2888 PetscErrorCode ierr; 2889 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2890 PetscReal atmp; 2891 PetscScalar *x; 2892 MatScalar *aa; 2893 2894 PetscFunctionBegin; 2895 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2896 aa = a->a; 2897 ai = a->i; 2898 aj = a->j; 2899 2900 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2901 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2902 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2903 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2904 for (i=0; i<m; i++) { 2905 ncols = ai[1] - ai[0]; ai++; 2906 x[i] = 0.0; 2907 for (j=0; j<ncols; j++) { 2908 atmp = PetscAbsScalar(*aa); 2909 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2910 aa++; aj++; 2911 } 2912 } 2913 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2914 PetscFunctionReturn(0); 2915 } 2916 2917 #undef __FUNCT__ 2918 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 2919 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2920 { 2921 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2922 PetscErrorCode ierr; 2923 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2924 PetscScalar *x; 2925 MatScalar *aa; 2926 2927 PetscFunctionBegin; 2928 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2929 aa = a->a; 2930 ai = a->i; 2931 aj = a->j; 2932 2933 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2934 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2935 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2936 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2937 for (i=0; i<m; i++) { 2938 ncols = ai[1] - ai[0]; ai++; 2939 if (ncols == A->cmap->n) { /* row is dense */ 2940 x[i] = *aa; if (idx) idx[i] = 0; 2941 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2942 x[i] = 0.0; 2943 if (idx) { 2944 idx[i] = 0; /* in case ncols is zero */ 2945 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2946 if (aj[j] > j) { 2947 idx[i] = j; 2948 break; 2949 } 2950 } 2951 } 2952 } 2953 for (j=0; j<ncols; j++) { 2954 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2955 aa++; aj++; 2956 } 2957 } 2958 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2959 PetscFunctionReturn(0); 2960 } 2961 2962 #undef __FUNCT__ 2963 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 2964 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2965 { 2966 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2967 PetscErrorCode ierr; 2968 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2969 PetscReal atmp; 2970 PetscScalar *x; 2971 MatScalar *aa; 2972 2973 PetscFunctionBegin; 2974 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2975 aa = a->a; 2976 ai = a->i; 2977 aj = a->j; 2978 2979 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2980 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2981 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2982 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); 2983 for (i=0; i<m; i++) { 2984 ncols = ai[1] - ai[0]; ai++; 2985 if (ncols) { 2986 /* Get first nonzero */ 2987 for (j = 0; j < ncols; j++) { 2988 atmp = PetscAbsScalar(aa[j]); 2989 if (atmp > 1.0e-12) { 2990 x[i] = atmp; 2991 if (idx) idx[i] = aj[j]; 2992 break; 2993 } 2994 } 2995 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 2996 } else { 2997 x[i] = 0.0; if (idx) idx[i] = 0; 2998 } 2999 for (j = 0; j < ncols; j++) { 3000 atmp = PetscAbsScalar(*aa); 3001 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3002 aa++; aj++; 3003 } 3004 } 3005 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3006 PetscFunctionReturn(0); 3007 } 3008 3009 #undef __FUNCT__ 3010 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3011 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3012 { 3013 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3014 PetscErrorCode ierr; 3015 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3016 PetscScalar *x; 3017 MatScalar *aa; 3018 3019 PetscFunctionBegin; 3020 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3021 aa = a->a; 3022 ai = a->i; 3023 aj = a->j; 3024 3025 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3026 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3027 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3028 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3029 for (i=0; i<m; i++) { 3030 ncols = ai[1] - ai[0]; ai++; 3031 if (ncols == A->cmap->n) { /* row is dense */ 3032 x[i] = *aa; if (idx) idx[i] = 0; 3033 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3034 x[i] = 0.0; 3035 if (idx) { /* find first implicit 0.0 in the row */ 3036 idx[i] = 0; /* in case ncols is zero */ 3037 for (j=0; j<ncols; j++) { 3038 if (aj[j] > j) { 3039 idx[i] = j; 3040 break; 3041 } 3042 } 3043 } 3044 } 3045 for (j=0; j<ncols; j++) { 3046 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3047 aa++; aj++; 3048 } 3049 } 3050 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3051 PetscFunctionReturn(0); 3052 } 3053 3054 #include <petscblaslapack.h> 3055 #include <petsc-private/kernels/blockinvert.h> 3056 3057 #undef __FUNCT__ 3058 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3059 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3060 { 3061 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3062 PetscErrorCode ierr; 3063 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3064 MatScalar *diag,work[25],*v_work; 3065 PetscReal shift = 0.0; 3066 3067 PetscFunctionBegin; 3068 if (a->ibdiagvalid) { 3069 if (values) *values = a->ibdiag; 3070 PetscFunctionReturn(0); 3071 } 3072 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3073 if (!a->ibdiag) { 3074 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 3075 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3076 } 3077 diag = a->ibdiag; 3078 if (values) *values = a->ibdiag; 3079 /* factor and invert each block */ 3080 switch (bs) { 3081 case 1: 3082 for (i=0; i<mbs; i++) { 3083 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3084 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3085 } 3086 break; 3087 case 2: 3088 for (i=0; i<mbs; i++) { 3089 ij[0] = 2*i; ij[1] = 2*i + 1; 3090 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3091 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3092 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3093 diag += 4; 3094 } 3095 break; 3096 case 3: 3097 for (i=0; i<mbs; i++) { 3098 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3099 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3100 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3101 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3102 diag += 9; 3103 } 3104 break; 3105 case 4: 3106 for (i=0; i<mbs; i++) { 3107 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3108 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3109 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3110 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3111 diag += 16; 3112 } 3113 break; 3114 case 5: 3115 for (i=0; i<mbs; i++) { 3116 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3117 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3118 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3119 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3120 diag += 25; 3121 } 3122 break; 3123 case 6: 3124 for (i=0; i<mbs; i++) { 3125 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; 3126 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3127 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3128 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3129 diag += 36; 3130 } 3131 break; 3132 case 7: 3133 for (i=0; i<mbs; i++) { 3134 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; 3135 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3136 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3137 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3138 diag += 49; 3139 } 3140 break; 3141 default: 3142 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3143 for (i=0; i<mbs; i++) { 3144 for (j=0; j<bs; j++) { 3145 IJ[j] = bs*i + j; 3146 } 3147 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3148 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3149 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3150 diag += bs2; 3151 } 3152 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3153 } 3154 a->ibdiagvalid = PETSC_TRUE; 3155 PetscFunctionReturn(0); 3156 } 3157 3158 #undef __FUNCT__ 3159 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3160 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3161 { 3162 PetscErrorCode ierr; 3163 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3164 PetscScalar a; 3165 PetscInt m,n,i,j,col; 3166 3167 PetscFunctionBegin; 3168 if (!x->assembled) { 3169 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3170 for (i=0; i<m; i++) { 3171 for (j=0; j<aij->imax[i]; j++) { 3172 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3173 col = (PetscInt)(n*PetscRealPart(a)); 3174 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3175 } 3176 } 3177 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3178 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3179 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3180 PetscFunctionReturn(0); 3181 } 3182 3183 /* -------------------------------------------------------------------*/ 3184 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3185 MatGetRow_SeqAIJ, 3186 MatRestoreRow_SeqAIJ, 3187 MatMult_SeqAIJ, 3188 /* 4*/ MatMultAdd_SeqAIJ, 3189 MatMultTranspose_SeqAIJ, 3190 MatMultTransposeAdd_SeqAIJ, 3191 0, 3192 0, 3193 0, 3194 /* 10*/ 0, 3195 MatLUFactor_SeqAIJ, 3196 0, 3197 MatSOR_SeqAIJ, 3198 MatTranspose_SeqAIJ, 3199 /*1 5*/ MatGetInfo_SeqAIJ, 3200 MatEqual_SeqAIJ, 3201 MatGetDiagonal_SeqAIJ, 3202 MatDiagonalScale_SeqAIJ, 3203 MatNorm_SeqAIJ, 3204 /* 20*/ 0, 3205 MatAssemblyEnd_SeqAIJ, 3206 MatSetOption_SeqAIJ, 3207 MatZeroEntries_SeqAIJ, 3208 /* 24*/ MatZeroRows_SeqAIJ, 3209 0, 3210 0, 3211 0, 3212 0, 3213 /* 29*/ MatSetUp_SeqAIJ, 3214 0, 3215 0, 3216 0, 3217 0, 3218 /* 34*/ MatDuplicate_SeqAIJ, 3219 0, 3220 0, 3221 MatILUFactor_SeqAIJ, 3222 0, 3223 /* 39*/ MatAXPY_SeqAIJ, 3224 MatGetSubMatrices_SeqAIJ, 3225 MatIncreaseOverlap_SeqAIJ, 3226 MatGetValues_SeqAIJ, 3227 MatCopy_SeqAIJ, 3228 /* 44*/ MatGetRowMax_SeqAIJ, 3229 MatScale_SeqAIJ, 3230 0, 3231 MatDiagonalSet_SeqAIJ, 3232 MatZeroRowsColumns_SeqAIJ, 3233 /* 49*/ MatSetRandom_SeqAIJ, 3234 MatGetRowIJ_SeqAIJ, 3235 MatRestoreRowIJ_SeqAIJ, 3236 MatGetColumnIJ_SeqAIJ, 3237 MatRestoreColumnIJ_SeqAIJ, 3238 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3239 0, 3240 0, 3241 MatPermute_SeqAIJ, 3242 0, 3243 /* 59*/ 0, 3244 MatDestroy_SeqAIJ, 3245 MatView_SeqAIJ, 3246 0, 3247 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3248 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3249 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3250 0, 3251 0, 3252 0, 3253 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3254 MatGetRowMinAbs_SeqAIJ, 3255 0, 3256 MatSetColoring_SeqAIJ, 3257 0, 3258 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3259 MatFDColoringApply_AIJ, 3260 0, 3261 0, 3262 0, 3263 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3264 0, 3265 0, 3266 0, 3267 MatLoad_SeqAIJ, 3268 /* 84*/ MatIsSymmetric_SeqAIJ, 3269 MatIsHermitian_SeqAIJ, 3270 0, 3271 0, 3272 0, 3273 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3274 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3275 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3276 MatPtAP_SeqAIJ_SeqAIJ, 3277 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3278 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3279 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3280 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3281 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3282 0, 3283 /* 99*/ 0, 3284 0, 3285 0, 3286 MatConjugate_SeqAIJ, 3287 0, 3288 /*104*/ MatSetValuesRow_SeqAIJ, 3289 MatRealPart_SeqAIJ, 3290 MatImaginaryPart_SeqAIJ, 3291 0, 3292 0, 3293 /*109*/ MatMatSolve_SeqAIJ, 3294 0, 3295 MatGetRowMin_SeqAIJ, 3296 0, 3297 MatMissingDiagonal_SeqAIJ, 3298 /*114*/ 0, 3299 0, 3300 0, 3301 0, 3302 0, 3303 /*119*/ 0, 3304 0, 3305 0, 3306 0, 3307 MatGetMultiProcBlock_SeqAIJ, 3308 /*124*/ MatFindNonzeroRows_SeqAIJ, 3309 MatGetColumnNorms_SeqAIJ, 3310 MatInvertBlockDiagonal_SeqAIJ, 3311 0, 3312 0, 3313 /*129*/ 0, 3314 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3315 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3316 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3317 MatTransposeColoringCreate_SeqAIJ, 3318 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3319 MatTransColoringApplyDenToSp_SeqAIJ, 3320 MatRARt_SeqAIJ_SeqAIJ, 3321 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3322 MatRARtNumeric_SeqAIJ_SeqAIJ, 3323 /*139*/0, 3324 0, 3325 0, 3326 MatFDColoringSetUp_SeqXAIJ, 3327 MatFindOffBlockDiagonalEntries_SeqAIJ 3328 }; 3329 3330 #undef __FUNCT__ 3331 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3332 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3333 { 3334 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3335 PetscInt i,nz,n; 3336 3337 PetscFunctionBegin; 3338 nz = aij->maxnz; 3339 n = mat->rmap->n; 3340 for (i=0; i<nz; i++) { 3341 aij->j[i] = indices[i]; 3342 } 3343 aij->nz = nz; 3344 for (i=0; i<n; i++) { 3345 aij->ilen[i] = aij->imax[i]; 3346 } 3347 PetscFunctionReturn(0); 3348 } 3349 3350 #undef __FUNCT__ 3351 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3352 /*@ 3353 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3354 in the matrix. 3355 3356 Input Parameters: 3357 + mat - the SeqAIJ matrix 3358 - indices - the column indices 3359 3360 Level: advanced 3361 3362 Notes: 3363 This can be called if you have precomputed the nonzero structure of the 3364 matrix and want to provide it to the matrix object to improve the performance 3365 of the MatSetValues() operation. 3366 3367 You MUST have set the correct numbers of nonzeros per row in the call to 3368 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3369 3370 MUST be called before any calls to MatSetValues(); 3371 3372 The indices should start with zero, not one. 3373 3374 @*/ 3375 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3376 { 3377 PetscErrorCode ierr; 3378 3379 PetscFunctionBegin; 3380 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3381 PetscValidPointer(indices,2); 3382 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3383 PetscFunctionReturn(0); 3384 } 3385 3386 /* ----------------------------------------------------------------------------------------*/ 3387 3388 #undef __FUNCT__ 3389 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3390 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3391 { 3392 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3393 PetscErrorCode ierr; 3394 size_t nz = aij->i[mat->rmap->n]; 3395 3396 PetscFunctionBegin; 3397 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3398 3399 /* allocate space for values if not already there */ 3400 if (!aij->saved_values) { 3401 ierr = PetscMalloc1((nz+1),&aij->saved_values);CHKERRQ(ierr); 3402 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3403 } 3404 3405 /* copy values over */ 3406 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3407 PetscFunctionReturn(0); 3408 } 3409 3410 #undef __FUNCT__ 3411 #define __FUNCT__ "MatStoreValues" 3412 /*@ 3413 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3414 example, reuse of the linear part of a Jacobian, while recomputing the 3415 nonlinear portion. 3416 3417 Collect on Mat 3418 3419 Input Parameters: 3420 . mat - the matrix (currently only AIJ matrices support this option) 3421 3422 Level: advanced 3423 3424 Common Usage, with SNESSolve(): 3425 $ Create Jacobian matrix 3426 $ Set linear terms into matrix 3427 $ Apply boundary conditions to matrix, at this time matrix must have 3428 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3429 $ boundary conditions again will not change the nonzero structure 3430 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3431 $ ierr = MatStoreValues(mat); 3432 $ Call SNESSetJacobian() with matrix 3433 $ In your Jacobian routine 3434 $ ierr = MatRetrieveValues(mat); 3435 $ Set nonlinear terms in matrix 3436 3437 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3438 $ // build linear portion of Jacobian 3439 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3440 $ ierr = MatStoreValues(mat); 3441 $ loop over nonlinear iterations 3442 $ ierr = MatRetrieveValues(mat); 3443 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3444 $ // call MatAssemblyBegin/End() on matrix 3445 $ Solve linear system with Jacobian 3446 $ endloop 3447 3448 Notes: 3449 Matrix must already be assemblied before calling this routine 3450 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3451 calling this routine. 3452 3453 When this is called multiple times it overwrites the previous set of stored values 3454 and does not allocated additional space. 3455 3456 .seealso: MatRetrieveValues() 3457 3458 @*/ 3459 PetscErrorCode MatStoreValues(Mat mat) 3460 { 3461 PetscErrorCode ierr; 3462 3463 PetscFunctionBegin; 3464 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3465 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3466 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3467 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3468 PetscFunctionReturn(0); 3469 } 3470 3471 #undef __FUNCT__ 3472 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3473 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3474 { 3475 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3476 PetscErrorCode ierr; 3477 PetscInt nz = aij->i[mat->rmap->n]; 3478 3479 PetscFunctionBegin; 3480 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3481 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3482 /* copy values over */ 3483 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3484 PetscFunctionReturn(0); 3485 } 3486 3487 #undef __FUNCT__ 3488 #define __FUNCT__ "MatRetrieveValues" 3489 /*@ 3490 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3491 example, reuse of the linear part of a Jacobian, while recomputing the 3492 nonlinear portion. 3493 3494 Collect on Mat 3495 3496 Input Parameters: 3497 . mat - the matrix (currently on AIJ matrices support this option) 3498 3499 Level: advanced 3500 3501 .seealso: MatStoreValues() 3502 3503 @*/ 3504 PetscErrorCode MatRetrieveValues(Mat mat) 3505 { 3506 PetscErrorCode ierr; 3507 3508 PetscFunctionBegin; 3509 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3510 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3511 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3512 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3513 PetscFunctionReturn(0); 3514 } 3515 3516 3517 /* --------------------------------------------------------------------------------*/ 3518 #undef __FUNCT__ 3519 #define __FUNCT__ "MatCreateSeqAIJ" 3520 /*@C 3521 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3522 (the default parallel PETSc format). For good matrix assembly performance 3523 the user should preallocate the matrix storage by setting the parameter nz 3524 (or the array nnz). By setting these parameters accurately, performance 3525 during matrix assembly can be increased by more than a factor of 50. 3526 3527 Collective on MPI_Comm 3528 3529 Input Parameters: 3530 + comm - MPI communicator, set to PETSC_COMM_SELF 3531 . m - number of rows 3532 . n - number of columns 3533 . nz - number of nonzeros per row (same for all rows) 3534 - nnz - array containing the number of nonzeros in the various rows 3535 (possibly different for each row) or NULL 3536 3537 Output Parameter: 3538 . A - the matrix 3539 3540 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3541 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3542 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3543 3544 Notes: 3545 If nnz is given then nz is ignored 3546 3547 The AIJ format (also called the Yale sparse matrix format or 3548 compressed row storage), is fully compatible with standard Fortran 77 3549 storage. That is, the stored row and column indices can begin at 3550 either one (as in Fortran) or zero. See the users' manual for details. 3551 3552 Specify the preallocated storage with either nz or nnz (not both). 3553 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3554 allocation. For large problems you MUST preallocate memory or you 3555 will get TERRIBLE performance, see the users' manual chapter on matrices. 3556 3557 By default, this format uses inodes (identical nodes) when possible, to 3558 improve numerical efficiency of matrix-vector products and solves. We 3559 search for consecutive rows with the same nonzero structure, thereby 3560 reusing matrix information to achieve increased efficiency. 3561 3562 Options Database Keys: 3563 + -mat_no_inode - Do not use inodes 3564 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3565 3566 Level: intermediate 3567 3568 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3569 3570 @*/ 3571 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3572 { 3573 PetscErrorCode ierr; 3574 3575 PetscFunctionBegin; 3576 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3577 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3578 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3579 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3580 PetscFunctionReturn(0); 3581 } 3582 3583 #undef __FUNCT__ 3584 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3585 /*@C 3586 MatSeqAIJSetPreallocation - For good matrix assembly performance 3587 the user should preallocate the matrix storage by setting the parameter nz 3588 (or the array nnz). By setting these parameters accurately, performance 3589 during matrix assembly can be increased by more than a factor of 50. 3590 3591 Collective on MPI_Comm 3592 3593 Input Parameters: 3594 + B - The matrix-free 3595 . nz - number of nonzeros per row (same for all rows) 3596 - nnz - array containing the number of nonzeros in the various rows 3597 (possibly different for each row) or NULL 3598 3599 Notes: 3600 If nnz is given then nz is ignored 3601 3602 The AIJ format (also called the Yale sparse matrix format or 3603 compressed row storage), is fully compatible with standard Fortran 77 3604 storage. That is, the stored row and column indices can begin at 3605 either one (as in Fortran) or zero. See the users' manual for details. 3606 3607 Specify the preallocated storage with either nz or nnz (not both). 3608 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3609 allocation. For large problems you MUST preallocate memory or you 3610 will get TERRIBLE performance, see the users' manual chapter on matrices. 3611 3612 You can call MatGetInfo() to get information on how effective the preallocation was; 3613 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3614 You can also run with the option -info and look for messages with the string 3615 malloc in them to see if additional memory allocation was needed. 3616 3617 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3618 entries or columns indices 3619 3620 By default, this format uses inodes (identical nodes) when possible, to 3621 improve numerical efficiency of matrix-vector products and solves. We 3622 search for consecutive rows with the same nonzero structure, thereby 3623 reusing matrix information to achieve increased efficiency. 3624 3625 Options Database Keys: 3626 + -mat_no_inode - Do not use inodes 3627 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3628 - -mat_aij_oneindex - Internally use indexing starting at 1 3629 rather than 0. Note that when calling MatSetValues(), 3630 the user still MUST index entries starting at 0! 3631 3632 Level: intermediate 3633 3634 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3635 3636 @*/ 3637 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3638 { 3639 PetscErrorCode ierr; 3640 3641 PetscFunctionBegin; 3642 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3643 PetscValidType(B,1); 3644 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3645 PetscFunctionReturn(0); 3646 } 3647 3648 #undef __FUNCT__ 3649 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3650 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3651 { 3652 Mat_SeqAIJ *b; 3653 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3654 PetscErrorCode ierr; 3655 PetscInt i; 3656 3657 PetscFunctionBegin; 3658 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3659 if (nz == MAT_SKIP_ALLOCATION) { 3660 skipallocation = PETSC_TRUE; 3661 nz = 0; 3662 } 3663 3664 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3665 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3666 3667 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3668 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3669 if (nnz) { 3670 for (i=0; i<B->rmap->n; i++) { 3671 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]); 3672 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); 3673 } 3674 } 3675 3676 B->preallocated = PETSC_TRUE; 3677 3678 b = (Mat_SeqAIJ*)B->data; 3679 3680 if (!skipallocation) { 3681 if (!b->imax) { 3682 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3683 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3684 } 3685 if (!nnz) { 3686 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3687 else if (nz < 0) nz = 1; 3688 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3689 nz = nz*B->rmap->n; 3690 } else { 3691 nz = 0; 3692 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3693 } 3694 /* b->ilen will count nonzeros in each row so far. */ 3695 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3696 3697 /* allocate the matrix space */ 3698 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3699 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3700 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3701 b->i[0] = 0; 3702 for (i=1; i<B->rmap->n+1; i++) { 3703 b->i[i] = b->i[i-1] + b->imax[i-1]; 3704 } 3705 b->singlemalloc = PETSC_TRUE; 3706 b->free_a = PETSC_TRUE; 3707 b->free_ij = PETSC_TRUE; 3708 #if defined(PETSC_THREADCOMM_ACTIVE) 3709 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3710 #endif 3711 } else { 3712 b->free_a = PETSC_FALSE; 3713 b->free_ij = PETSC_FALSE; 3714 } 3715 3716 b->nz = 0; 3717 b->maxnz = nz; 3718 B->info.nz_unneeded = (double)b->maxnz; 3719 if (realalloc) { 3720 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3721 } 3722 PetscFunctionReturn(0); 3723 } 3724 3725 #undef __FUNCT__ 3726 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3727 /*@ 3728 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3729 3730 Input Parameters: 3731 + B - the matrix 3732 . i - the indices into j for the start of each row (starts with zero) 3733 . j - the column indices for each row (starts with zero) these must be sorted for each row 3734 - v - optional values in the matrix 3735 3736 Level: developer 3737 3738 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3739 3740 .keywords: matrix, aij, compressed row, sparse, sequential 3741 3742 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3743 @*/ 3744 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3745 { 3746 PetscErrorCode ierr; 3747 3748 PetscFunctionBegin; 3749 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3750 PetscValidType(B,1); 3751 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3752 PetscFunctionReturn(0); 3753 } 3754 3755 #undef __FUNCT__ 3756 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3757 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3758 { 3759 PetscInt i; 3760 PetscInt m,n; 3761 PetscInt nz; 3762 PetscInt *nnz, nz_max = 0; 3763 PetscScalar *values; 3764 PetscErrorCode ierr; 3765 3766 PetscFunctionBegin; 3767 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3768 3769 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3770 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3771 3772 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3773 ierr = PetscMalloc1((m+1), &nnz);CHKERRQ(ierr); 3774 for (i = 0; i < m; i++) { 3775 nz = Ii[i+1]- Ii[i]; 3776 nz_max = PetscMax(nz_max, nz); 3777 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3778 nnz[i] = nz; 3779 } 3780 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3781 ierr = PetscFree(nnz);CHKERRQ(ierr); 3782 3783 if (v) { 3784 values = (PetscScalar*) v; 3785 } else { 3786 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3787 } 3788 3789 for (i = 0; i < m; i++) { 3790 nz = Ii[i+1] - Ii[i]; 3791 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3792 } 3793 3794 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3795 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3796 3797 if (!v) { 3798 ierr = PetscFree(values);CHKERRQ(ierr); 3799 } 3800 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3801 PetscFunctionReturn(0); 3802 } 3803 3804 #include <../src/mat/impls/dense/seq/dense.h> 3805 #include <petsc-private/kernels/petscaxpy.h> 3806 3807 #undef __FUNCT__ 3808 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3809 /* 3810 Computes (B'*A')' since computing B*A directly is untenable 3811 3812 n p p 3813 ( ) ( ) ( ) 3814 m ( A ) * n ( B ) = m ( C ) 3815 ( ) ( ) ( ) 3816 3817 */ 3818 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3819 { 3820 PetscErrorCode ierr; 3821 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3822 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3823 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3824 PetscInt i,n,m,q,p; 3825 const PetscInt *ii,*idx; 3826 const PetscScalar *b,*a,*a_q; 3827 PetscScalar *c,*c_q; 3828 3829 PetscFunctionBegin; 3830 m = A->rmap->n; 3831 n = A->cmap->n; 3832 p = B->cmap->n; 3833 a = sub_a->v; 3834 b = sub_b->a; 3835 c = sub_c->v; 3836 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3837 3838 ii = sub_b->i; 3839 idx = sub_b->j; 3840 for (i=0; i<n; i++) { 3841 q = ii[i+1] - ii[i]; 3842 while (q-->0) { 3843 c_q = c + m*(*idx); 3844 a_q = a + m*i; 3845 PetscKernelAXPY(c_q,*b,a_q,m); 3846 idx++; 3847 b++; 3848 } 3849 } 3850 PetscFunctionReturn(0); 3851 } 3852 3853 #undef __FUNCT__ 3854 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 3855 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3856 { 3857 PetscErrorCode ierr; 3858 PetscInt m=A->rmap->n,n=B->cmap->n; 3859 Mat Cmat; 3860 3861 PetscFunctionBegin; 3862 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); 3863 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3864 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3865 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3866 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3867 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3868 3869 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3870 3871 *C = Cmat; 3872 PetscFunctionReturn(0); 3873 } 3874 3875 /* ----------------------------------------------------------------*/ 3876 #undef __FUNCT__ 3877 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 3878 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3879 { 3880 PetscErrorCode ierr; 3881 3882 PetscFunctionBegin; 3883 if (scall == MAT_INITIAL_MATRIX) { 3884 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3885 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3886 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3887 } 3888 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3889 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3890 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3891 PetscFunctionReturn(0); 3892 } 3893 3894 3895 /*MC 3896 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3897 based on compressed sparse row format. 3898 3899 Options Database Keys: 3900 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3901 3902 Level: beginner 3903 3904 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3905 M*/ 3906 3907 /*MC 3908 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3909 3910 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3911 and MATMPIAIJ otherwise. As a result, for single process communicators, 3912 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3913 for communicators controlling multiple processes. It is recommended that you call both of 3914 the above preallocation routines for simplicity. 3915 3916 Options Database Keys: 3917 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3918 3919 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 3920 enough exist. 3921 3922 Level: beginner 3923 3924 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3925 M*/ 3926 3927 /*MC 3928 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3929 3930 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3931 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3932 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3933 for communicators controlling multiple processes. It is recommended that you call both of 3934 the above preallocation routines for simplicity. 3935 3936 Options Database Keys: 3937 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3938 3939 Level: beginner 3940 3941 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3942 M*/ 3943 3944 #if defined(PETSC_HAVE_PASTIX) 3945 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 3946 #endif 3947 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 3948 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 3949 #endif 3950 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3951 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 3952 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 3953 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 3954 #if defined(PETSC_HAVE_MUMPS) 3955 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 3956 #endif 3957 #if defined(PETSC_HAVE_SUPERLU) 3958 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 3959 #endif 3960 #if defined(PETSC_HAVE_SUPERLU_DIST) 3961 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 3962 #endif 3963 #if defined(PETSC_HAVE_SUITESPARSE) 3964 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 3965 #endif 3966 #if defined(PETSC_HAVE_SUITESPARSE) 3967 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 3968 #endif 3969 #if defined(PETSC_HAVE_SUITESPARSE) 3970 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_klu(Mat,MatFactorType,Mat*); 3971 #endif 3972 #if defined(PETSC_HAVE_LUSOL) 3973 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 3974 #endif 3975 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3976 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 3977 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 3978 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 3979 #endif 3980 #if defined(PETSC_HAVE_CLIQUE) 3981 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 3982 #endif 3983 3984 3985 #undef __FUNCT__ 3986 #define __FUNCT__ "MatSeqAIJGetArray" 3987 /*@C 3988 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 3989 3990 Not Collective 3991 3992 Input Parameter: 3993 . mat - a MATSEQDENSE matrix 3994 3995 Output Parameter: 3996 . array - pointer to the data 3997 3998 Level: intermediate 3999 4000 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4001 @*/ 4002 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4003 { 4004 PetscErrorCode ierr; 4005 4006 PetscFunctionBegin; 4007 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4008 PetscFunctionReturn(0); 4009 } 4010 4011 #undef __FUNCT__ 4012 #define __FUNCT__ "MatSeqAIJRestoreArray" 4013 /*@C 4014 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4015 4016 Not Collective 4017 4018 Input Parameters: 4019 . mat - a MATSEQDENSE matrix 4020 . array - pointer to the data 4021 4022 Level: intermediate 4023 4024 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4025 @*/ 4026 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4027 { 4028 PetscErrorCode ierr; 4029 4030 PetscFunctionBegin; 4031 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4032 PetscFunctionReturn(0); 4033 } 4034 4035 #undef __FUNCT__ 4036 #define __FUNCT__ "MatCreate_SeqAIJ" 4037 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4038 { 4039 Mat_SeqAIJ *b; 4040 PetscErrorCode ierr; 4041 PetscMPIInt size; 4042 4043 PetscFunctionBegin; 4044 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4045 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4046 4047 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 4048 4049 B->data = (void*)b; 4050 4051 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4052 4053 b->row = 0; 4054 b->col = 0; 4055 b->icol = 0; 4056 b->reallocs = 0; 4057 b->ignorezeroentries = PETSC_FALSE; 4058 b->roworiented = PETSC_TRUE; 4059 b->nonew = 0; 4060 b->diag = 0; 4061 b->solve_work = 0; 4062 B->spptr = 0; 4063 b->saved_values = 0; 4064 b->idiag = 0; 4065 b->mdiag = 0; 4066 b->ssor_work = 0; 4067 b->omega = 1.0; 4068 b->fshift = 0.0; 4069 b->idiagvalid = PETSC_FALSE; 4070 b->ibdiagvalid = PETSC_FALSE; 4071 b->keepnonzeropattern = PETSC_FALSE; 4072 b->xtoy = 0; 4073 b->XtoY = 0; 4074 4075 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4076 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4077 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4078 4079 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4080 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4081 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4082 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4083 #endif 4084 #if defined(PETSC_HAVE_PASTIX) 4085 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4086 #endif 4087 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4088 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4089 #endif 4090 #if defined(PETSC_HAVE_SUPERLU) 4091 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4092 #endif 4093 #if defined(PETSC_HAVE_SUPERLU_DIST) 4094 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4095 #endif 4096 #if defined(PETSC_HAVE_MUMPS) 4097 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4098 #endif 4099 #if defined(PETSC_HAVE_SUITESPARSE) 4100 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4101 #endif 4102 #if defined(PETSC_HAVE_SUITESPARSE) 4103 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4104 #endif 4105 #if defined(PETSC_HAVE_SUITESPARSE) 4106 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_klu_C",MatGetFactor_seqaij_klu);CHKERRQ(ierr); 4107 #endif 4108 #if defined(PETSC_HAVE_LUSOL) 4109 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4110 #endif 4111 #if defined(PETSC_HAVE_CLIQUE) 4112 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4113 #endif 4114 4115 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4116 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4117 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4118 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4119 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4120 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4121 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4122 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4123 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4124 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4125 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4126 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4127 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4128 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4129 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4130 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4131 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4132 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4133 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4134 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4135 PetscFunctionReturn(0); 4136 } 4137 4138 #undef __FUNCT__ 4139 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4140 /* 4141 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4142 */ 4143 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4144 { 4145 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4146 PetscErrorCode ierr; 4147 PetscInt i,m = A->rmap->n; 4148 4149 PetscFunctionBegin; 4150 c = (Mat_SeqAIJ*)C->data; 4151 4152 C->factortype = A->factortype; 4153 c->row = 0; 4154 c->col = 0; 4155 c->icol = 0; 4156 c->reallocs = 0; 4157 4158 C->assembled = PETSC_TRUE; 4159 4160 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4161 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4162 4163 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4164 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4165 for (i=0; i<m; i++) { 4166 c->imax[i] = a->imax[i]; 4167 c->ilen[i] = a->ilen[i]; 4168 } 4169 4170 /* allocate the matrix space */ 4171 if (mallocmatspace) { 4172 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4173 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4174 4175 c->singlemalloc = PETSC_TRUE; 4176 4177 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4178 if (m > 0) { 4179 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4180 if (cpvalues == MAT_COPY_VALUES) { 4181 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4182 } else { 4183 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4184 } 4185 } 4186 } 4187 4188 c->ignorezeroentries = a->ignorezeroentries; 4189 c->roworiented = a->roworiented; 4190 c->nonew = a->nonew; 4191 if (a->diag) { 4192 ierr = PetscMalloc1((m+1),&c->diag);CHKERRQ(ierr); 4193 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4194 for (i=0; i<m; i++) { 4195 c->diag[i] = a->diag[i]; 4196 } 4197 } else c->diag = 0; 4198 4199 c->solve_work = 0; 4200 c->saved_values = 0; 4201 c->idiag = 0; 4202 c->ssor_work = 0; 4203 c->keepnonzeropattern = a->keepnonzeropattern; 4204 c->free_a = PETSC_TRUE; 4205 c->free_ij = PETSC_TRUE; 4206 c->xtoy = 0; 4207 c->XtoY = 0; 4208 4209 c->rmax = a->rmax; 4210 c->nz = a->nz; 4211 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4212 C->preallocated = PETSC_TRUE; 4213 4214 c->compressedrow.use = a->compressedrow.use; 4215 c->compressedrow.nrows = a->compressedrow.nrows; 4216 if (a->compressedrow.use) { 4217 i = a->compressedrow.nrows; 4218 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4219 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4220 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4221 } else { 4222 c->compressedrow.use = PETSC_FALSE; 4223 c->compressedrow.i = NULL; 4224 c->compressedrow.rindex = NULL; 4225 } 4226 C->nonzerostate = A->nonzerostate; 4227 4228 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4229 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4230 PetscFunctionReturn(0); 4231 } 4232 4233 #undef __FUNCT__ 4234 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4235 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4236 { 4237 PetscErrorCode ierr; 4238 4239 PetscFunctionBegin; 4240 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4241 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4242 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4243 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4244 } 4245 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4246 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4247 PetscFunctionReturn(0); 4248 } 4249 4250 #undef __FUNCT__ 4251 #define __FUNCT__ "MatLoad_SeqAIJ" 4252 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4253 { 4254 Mat_SeqAIJ *a; 4255 PetscErrorCode ierr; 4256 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4257 int fd; 4258 PetscMPIInt size; 4259 MPI_Comm comm; 4260 PetscInt bs = 1; 4261 4262 PetscFunctionBegin; 4263 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4264 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4265 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4266 4267 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4268 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4269 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4270 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4271 4272 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4273 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4274 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4275 M = header[1]; N = header[2]; nz = header[3]; 4276 4277 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4278 4279 /* read in row lengths */ 4280 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4281 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4282 4283 /* check if sum of rowlengths is same as nz */ 4284 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4285 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); 4286 4287 /* set global size if not set already*/ 4288 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4289 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4290 } else { 4291 /* if sizes and type are already set, check if the vector global sizes are correct */ 4292 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4293 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4294 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4295 } 4296 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); 4297 } 4298 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4299 a = (Mat_SeqAIJ*)newMat->data; 4300 4301 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4302 4303 /* read in nonzero values */ 4304 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4305 4306 /* set matrix "i" values */ 4307 a->i[0] = 0; 4308 for (i=1; i<= M; i++) { 4309 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4310 a->ilen[i-1] = rowlengths[i-1]; 4311 } 4312 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4313 4314 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4315 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4316 PetscFunctionReturn(0); 4317 } 4318 4319 #undef __FUNCT__ 4320 #define __FUNCT__ "MatEqual_SeqAIJ" 4321 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4322 { 4323 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4324 PetscErrorCode ierr; 4325 #if defined(PETSC_USE_COMPLEX) 4326 PetscInt k; 4327 #endif 4328 4329 PetscFunctionBegin; 4330 /* If the matrix dimensions are not equal,or no of nonzeros */ 4331 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4332 *flg = PETSC_FALSE; 4333 PetscFunctionReturn(0); 4334 } 4335 4336 /* if the a->i are the same */ 4337 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4338 if (!*flg) PetscFunctionReturn(0); 4339 4340 /* if a->j are the same */ 4341 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4342 if (!*flg) PetscFunctionReturn(0); 4343 4344 /* if a->a are the same */ 4345 #if defined(PETSC_USE_COMPLEX) 4346 for (k=0; k<a->nz; k++) { 4347 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4348 *flg = PETSC_FALSE; 4349 PetscFunctionReturn(0); 4350 } 4351 } 4352 #else 4353 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4354 #endif 4355 PetscFunctionReturn(0); 4356 } 4357 4358 #undef __FUNCT__ 4359 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4360 /*@ 4361 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4362 provided by the user. 4363 4364 Collective on MPI_Comm 4365 4366 Input Parameters: 4367 + comm - must be an MPI communicator of size 1 4368 . m - number of rows 4369 . n - number of columns 4370 . i - row indices 4371 . j - column indices 4372 - a - matrix values 4373 4374 Output Parameter: 4375 . mat - the matrix 4376 4377 Level: intermediate 4378 4379 Notes: 4380 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4381 once the matrix is destroyed and not before 4382 4383 You cannot set new nonzero locations into this matrix, that will generate an error. 4384 4385 The i and j indices are 0 based 4386 4387 The format which is used for the sparse matrix input, is equivalent to a 4388 row-major ordering.. i.e for the following matrix, the input data expected is 4389 as shown: 4390 4391 1 0 0 4392 2 0 3 4393 4 5 6 4394 4395 i = {0,1,3,6} [size = nrow+1 = 3+1] 4396 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4397 v = {1,2,3,4,5,6} [size = nz = 6] 4398 4399 4400 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4401 4402 @*/ 4403 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4404 { 4405 PetscErrorCode ierr; 4406 PetscInt ii; 4407 Mat_SeqAIJ *aij; 4408 #if defined(PETSC_USE_DEBUG) 4409 PetscInt jj; 4410 #endif 4411 4412 PetscFunctionBegin; 4413 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4414 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4415 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4416 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4417 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4418 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4419 aij = (Mat_SeqAIJ*)(*mat)->data; 4420 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4421 4422 aij->i = i; 4423 aij->j = j; 4424 aij->a = a; 4425 aij->singlemalloc = PETSC_FALSE; 4426 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4427 aij->free_a = PETSC_FALSE; 4428 aij->free_ij = PETSC_FALSE; 4429 4430 for (ii=0; ii<m; ii++) { 4431 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4432 #if defined(PETSC_USE_DEBUG) 4433 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]); 4434 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4435 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); 4436 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); 4437 } 4438 #endif 4439 } 4440 #if defined(PETSC_USE_DEBUG) 4441 for (ii=0; ii<aij->i[m]; ii++) { 4442 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4443 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]); 4444 } 4445 #endif 4446 4447 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4448 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4449 PetscFunctionReturn(0); 4450 } 4451 #undef __FUNCT__ 4452 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4453 /*@C 4454 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4455 provided by the user. 4456 4457 Collective on MPI_Comm 4458 4459 Input Parameters: 4460 + comm - must be an MPI communicator of size 1 4461 . m - number of rows 4462 . n - number of columns 4463 . i - row indices 4464 . j - column indices 4465 . a - matrix values 4466 . nz - number of nonzeros 4467 - idx - 0 or 1 based 4468 4469 Output Parameter: 4470 . mat - the matrix 4471 4472 Level: intermediate 4473 4474 Notes: 4475 The i and j indices are 0 based 4476 4477 The format which is used for the sparse matrix input, is equivalent to a 4478 row-major ordering.. i.e for the following matrix, the input data expected is 4479 as shown: 4480 4481 1 0 0 4482 2 0 3 4483 4 5 6 4484 4485 i = {0,1,1,2,2,2} 4486 j = {0,0,2,0,1,2} 4487 v = {1,2,3,4,5,6} 4488 4489 4490 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4491 4492 @*/ 4493 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4494 { 4495 PetscErrorCode ierr; 4496 PetscInt ii, *nnz, one = 1,row,col; 4497 4498 4499 PetscFunctionBegin; 4500 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4501 for (ii = 0; ii < nz; ii++) { 4502 nnz[i[ii] - !!idx] += 1; 4503 } 4504 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4505 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4506 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4507 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4508 for (ii = 0; ii < nz; ii++) { 4509 if (idx) { 4510 row = i[ii] - 1; 4511 col = j[ii] - 1; 4512 } else { 4513 row = i[ii]; 4514 col = j[ii]; 4515 } 4516 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4517 } 4518 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4519 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4520 ierr = PetscFree(nnz);CHKERRQ(ierr); 4521 PetscFunctionReturn(0); 4522 } 4523 4524 #undef __FUNCT__ 4525 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4526 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4527 { 4528 PetscErrorCode ierr; 4529 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4530 4531 PetscFunctionBegin; 4532 if (coloring->ctype == IS_COLORING_GLOBAL) { 4533 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4534 a->coloring = coloring; 4535 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4536 PetscInt i,*larray; 4537 ISColoring ocoloring; 4538 ISColoringValue *colors; 4539 4540 /* set coloring for diagonal portion */ 4541 ierr = PetscMalloc1(A->cmap->n,&larray);CHKERRQ(ierr); 4542 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4543 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4544 ierr = PetscMalloc1(A->cmap->n,&colors);CHKERRQ(ierr); 4545 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4546 ierr = PetscFree(larray);CHKERRQ(ierr); 4547 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4548 a->coloring = ocoloring; 4549 } 4550 PetscFunctionReturn(0); 4551 } 4552 4553 #undef __FUNCT__ 4554 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4555 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4556 { 4557 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4558 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4559 MatScalar *v = a->a; 4560 PetscScalar *values = (PetscScalar*)advalues; 4561 ISColoringValue *color; 4562 4563 PetscFunctionBegin; 4564 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4565 color = a->coloring->colors; 4566 /* loop over rows */ 4567 for (i=0; i<m; i++) { 4568 nz = ii[i+1] - ii[i]; 4569 /* loop over columns putting computed value into matrix */ 4570 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4571 values += nl; /* jump to next row of derivatives */ 4572 } 4573 PetscFunctionReturn(0); 4574 } 4575 4576 #undef __FUNCT__ 4577 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4578 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4579 { 4580 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4581 PetscErrorCode ierr; 4582 4583 PetscFunctionBegin; 4584 a->idiagvalid = PETSC_FALSE; 4585 a->ibdiagvalid = PETSC_FALSE; 4586 4587 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4588 PetscFunctionReturn(0); 4589 } 4590 4591 /* 4592 Special version for direct calls from Fortran 4593 */ 4594 #include <petsc-private/fortranimpl.h> 4595 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4596 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4597 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4598 #define matsetvaluesseqaij_ matsetvaluesseqaij 4599 #endif 4600 4601 /* Change these macros so can be used in void function */ 4602 #undef CHKERRQ 4603 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4604 #undef SETERRQ2 4605 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4606 #undef SETERRQ3 4607 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4608 4609 #undef __FUNCT__ 4610 #define __FUNCT__ "matsetvaluesseqaij_" 4611 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) 4612 { 4613 Mat A = *AA; 4614 PetscInt m = *mm, n = *nn; 4615 InsertMode is = *isis; 4616 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4617 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4618 PetscInt *imax,*ai,*ailen; 4619 PetscErrorCode ierr; 4620 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4621 MatScalar *ap,value,*aa; 4622 PetscBool ignorezeroentries = a->ignorezeroentries; 4623 PetscBool roworiented = a->roworiented; 4624 4625 PetscFunctionBegin; 4626 MatCheckPreallocated(A,1); 4627 imax = a->imax; 4628 ai = a->i; 4629 ailen = a->ilen; 4630 aj = a->j; 4631 aa = a->a; 4632 4633 for (k=0; k<m; k++) { /* loop over added rows */ 4634 row = im[k]; 4635 if (row < 0) continue; 4636 #if defined(PETSC_USE_DEBUG) 4637 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4638 #endif 4639 rp = aj + ai[row]; ap = aa + ai[row]; 4640 rmax = imax[row]; nrow = ailen[row]; 4641 low = 0; 4642 high = nrow; 4643 for (l=0; l<n; l++) { /* loop over added columns */ 4644 if (in[l] < 0) continue; 4645 #if defined(PETSC_USE_DEBUG) 4646 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4647 #endif 4648 col = in[l]; 4649 if (roworiented) value = v[l + k*n]; 4650 else value = v[k + l*m]; 4651 4652 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4653 4654 if (col <= lastcol) low = 0; 4655 else high = nrow; 4656 lastcol = col; 4657 while (high-low > 5) { 4658 t = (low+high)/2; 4659 if (rp[t] > col) high = t; 4660 else low = t; 4661 } 4662 for (i=low; i<high; i++) { 4663 if (rp[i] > col) break; 4664 if (rp[i] == col) { 4665 if (is == ADD_VALUES) ap[i] += value; 4666 else ap[i] = value; 4667 goto noinsert; 4668 } 4669 } 4670 if (value == 0.0 && ignorezeroentries) goto noinsert; 4671 if (nonew == 1) goto noinsert; 4672 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4673 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4674 N = nrow++ - 1; a->nz++; high++; 4675 /* shift up all the later entries in this row */ 4676 for (ii=N; ii>=i; ii--) { 4677 rp[ii+1] = rp[ii]; 4678 ap[ii+1] = ap[ii]; 4679 } 4680 rp[i] = col; 4681 ap[i] = value; 4682 A->nonzerostate++; 4683 noinsert:; 4684 low = i + 1; 4685 } 4686 ailen[row] = nrow; 4687 } 4688 PetscFunctionReturnVoid(); 4689 } 4690 4691 4692