1 2 /* 3 Defines the basic matrix operations for the AIJ (compressed row) 4 matrix storage format. 5 */ 6 7 8 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petscbt.h> 11 #include <petsc/private/kernels/blocktranspose.h> 12 13 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 14 { 15 PetscErrorCode ierr; 16 PetscInt i,m,n; 17 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 18 19 PetscFunctionBegin; 20 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 21 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 22 if (type == NORM_2) { 23 for (i=0; i<aij->i[m]; i++) { 24 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 25 } 26 } else if (type == NORM_1) { 27 for (i=0; i<aij->i[m]; i++) { 28 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 29 } 30 } else if (type == NORM_INFINITY) { 31 for (i=0; i<aij->i[m]; i++) { 32 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 33 } 34 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 35 36 if (type == NORM_2) { 37 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 38 } 39 PetscFunctionReturn(0); 40 } 41 42 PetscErrorCode MatFindOffBlockDiagonalEntries_SeqAIJ(Mat A,IS *is) 43 { 44 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 45 PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; 46 const PetscInt *jj = a->j,*ii = a->i; 47 PetscInt *rows; 48 PetscErrorCode ierr; 49 50 PetscFunctionBegin; 51 for (i=0; i<m; i++) { 52 if ((ii[i] != ii[i+1]) && ((jj[ii[i]] < bs*(i/bs)) || (jj[ii[i+1]-1] > bs*((i+bs)/bs)-1))) { 53 cnt++; 54 } 55 } 56 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 57 cnt = 0; 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 rows[cnt] = i; 61 cnt++; 62 } 63 } 64 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); 65 PetscFunctionReturn(0); 66 } 67 68 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 69 { 70 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 71 const MatScalar *aa = a->a; 72 PetscInt i,m=A->rmap->n,cnt = 0; 73 const PetscInt *ii = a->i,*jj = a->j,*diag; 74 PetscInt *rows; 75 PetscErrorCode ierr; 76 77 PetscFunctionBegin; 78 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 79 diag = a->diag; 80 for (i=0; i<m; i++) { 81 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 82 cnt++; 83 } 84 } 85 ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); 86 cnt = 0; 87 for (i=0; i<m; i++) { 88 if ((diag[i] >= ii[i+1]) || (jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 89 rows[cnt++] = i; 90 } 91 } 92 *nrows = cnt; 93 *zrows = rows; 94 PetscFunctionReturn(0); 95 } 96 97 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 98 { 99 PetscInt nrows,*rows; 100 PetscErrorCode ierr; 101 102 PetscFunctionBegin; 103 *zrows = NULL; 104 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 105 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 106 PetscFunctionReturn(0); 107 } 108 109 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 110 { 111 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 112 const MatScalar *aa; 113 PetscInt m=A->rmap->n,cnt = 0; 114 const PetscInt *ii; 115 PetscInt n,i,j,*rows; 116 PetscErrorCode ierr; 117 118 PetscFunctionBegin; 119 *keptrows = 0; 120 ii = a->i; 121 for (i=0; i<m; i++) { 122 n = ii[i+1] - ii[i]; 123 if (!n) { 124 cnt++; 125 goto ok1; 126 } 127 aa = a->a + ii[i]; 128 for (j=0; j<n; j++) { 129 if (aa[j] != 0.0) goto ok1; 130 } 131 cnt++; 132 ok1:; 133 } 134 if (!cnt) PetscFunctionReturn(0); 135 ierr = PetscMalloc1(A->rmap->n-cnt,&rows);CHKERRQ(ierr); 136 cnt = 0; 137 for (i=0; i<m; i++) { 138 n = ii[i+1] - ii[i]; 139 if (!n) continue; 140 aa = a->a + ii[i]; 141 for (j=0; j<n; j++) { 142 if (aa[j] != 0.0) { 143 rows[cnt++] = i; 144 break; 145 } 146 } 147 } 148 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 149 PetscFunctionReturn(0); 150 } 151 152 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 153 { 154 PetscErrorCode ierr; 155 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 156 PetscInt i,m = Y->rmap->n; 157 const PetscInt *diag; 158 MatScalar *aa = aij->a; 159 const PetscScalar *v; 160 PetscBool missing; 161 162 PetscFunctionBegin; 163 if (Y->assembled) { 164 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 165 if (!missing) { 166 diag = aij->diag; 167 ierr = VecGetArrayRead(D,&v);CHKERRQ(ierr); 168 if (is == INSERT_VALUES) { 169 for (i=0; i<m; i++) { 170 aa[diag[i]] = v[i]; 171 } 172 } else { 173 for (i=0; i<m; i++) { 174 aa[diag[i]] += v[i]; 175 } 176 } 177 ierr = VecRestoreArrayRead(D,&v);CHKERRQ(ierr); 178 PetscFunctionReturn(0); 179 } 180 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 181 } 182 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 183 PetscFunctionReturn(0); 184 } 185 186 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 187 { 188 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 189 PetscErrorCode ierr; 190 PetscInt i,ishift; 191 192 PetscFunctionBegin; 193 *m = A->rmap->n; 194 if (!ia) PetscFunctionReturn(0); 195 ishift = 0; 196 if (symmetric && !A->structurally_symmetric) { 197 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 198 } else if (oshift == 1) { 199 PetscInt *tia; 200 PetscInt nz = a->i[A->rmap->n]; 201 /* malloc space and add 1 to i and j indices */ 202 ierr = PetscMalloc1(A->rmap->n+1,&tia);CHKERRQ(ierr); 203 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 204 *ia = tia; 205 if (ja) { 206 PetscInt *tja; 207 ierr = PetscMalloc1(nz+1,&tja);CHKERRQ(ierr); 208 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 209 *ja = tja; 210 } 211 } else { 212 *ia = a->i; 213 if (ja) *ja = a->j; 214 } 215 PetscFunctionReturn(0); 216 } 217 218 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 219 { 220 PetscErrorCode ierr; 221 222 PetscFunctionBegin; 223 if (!ia) PetscFunctionReturn(0); 224 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 225 ierr = PetscFree(*ia);CHKERRQ(ierr); 226 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 227 } 228 PetscFunctionReturn(0); 229 } 230 231 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 232 { 233 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 234 PetscErrorCode ierr; 235 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 236 PetscInt nz = a->i[m],row,*jj,mr,col; 237 238 PetscFunctionBegin; 239 *nn = n; 240 if (!ia) PetscFunctionReturn(0); 241 if (symmetric) { 242 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,PETSC_TRUE,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 243 } else { 244 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 245 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 246 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 247 jj = a->j; 248 for (i=0; i<nz; i++) { 249 collengths[jj[i]]++; 250 } 251 cia[0] = oshift; 252 for (i=0; i<n; i++) { 253 cia[i+1] = cia[i] + collengths[i]; 254 } 255 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 256 jj = a->j; 257 for (row=0; row<m; row++) { 258 mr = a->i[row+1] - a->i[row]; 259 for (i=0; i<mr; i++) { 260 col = *jj++; 261 262 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 263 } 264 } 265 ierr = PetscFree(collengths);CHKERRQ(ierr); 266 *ia = cia; *ja = cja; 267 } 268 PetscFunctionReturn(0); 269 } 270 271 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 272 { 273 PetscErrorCode ierr; 274 275 PetscFunctionBegin; 276 if (!ia) PetscFunctionReturn(0); 277 278 ierr = PetscFree(*ia);CHKERRQ(ierr); 279 ierr = PetscFree(*ja);CHKERRQ(ierr); 280 PetscFunctionReturn(0); 281 } 282 283 /* 284 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 285 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 286 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() 287 */ 288 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 289 { 290 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 291 PetscErrorCode ierr; 292 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 293 PetscInt nz = a->i[m],row,*jj,mr,col; 294 PetscInt *cspidx; 295 296 PetscFunctionBegin; 297 *nn = n; 298 if (!ia) PetscFunctionReturn(0); 299 300 ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); 301 ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); 302 ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); 303 ierr = PetscMalloc1(nz+1,&cspidx);CHKERRQ(ierr); 304 jj = a->j; 305 for (i=0; i<nz; i++) { 306 collengths[jj[i]]++; 307 } 308 cia[0] = oshift; 309 for (i=0; i<n; i++) { 310 cia[i+1] = cia[i] + collengths[i]; 311 } 312 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 313 jj = a->j; 314 for (row=0; row<m; row++) { 315 mr = a->i[row+1] - a->i[row]; 316 for (i=0; i<mr; i++) { 317 col = *jj++; 318 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 319 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 320 } 321 } 322 ierr = PetscFree(collengths);CHKERRQ(ierr); 323 *ia = cia; *ja = cja; 324 *spidx = cspidx; 325 PetscFunctionReturn(0); 326 } 327 328 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 329 { 330 PetscErrorCode ierr; 331 332 PetscFunctionBegin; 333 ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); 334 ierr = PetscFree(*spidx);CHKERRQ(ierr); 335 PetscFunctionReturn(0); 336 } 337 338 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 339 { 340 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 341 PetscInt *ai = a->i; 342 PetscErrorCode ierr; 343 344 PetscFunctionBegin; 345 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 346 PetscFunctionReturn(0); 347 } 348 349 /* 350 MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions 351 352 - a single row of values is set with each call 353 - no row or column indices are negative or (in error) larger than the number of rows or columns 354 - the values are always added to the matrix, not set 355 - no new locations are introduced in the nonzero structure of the matrix 356 357 This does NOT assume the global column indices are sorted 358 359 */ 360 361 #include <petsc/private/isimpl.h> 362 PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 363 { 364 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 365 PetscInt low,high,t,row,nrow,i,col,l; 366 const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; 367 PetscInt lastcol = -1; 368 MatScalar *ap,value,*aa = a->a; 369 const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; 370 371 row = ridx[im[0]]; 372 rp = aj + ai[row]; 373 ap = aa + ai[row]; 374 nrow = ailen[row]; 375 low = 0; 376 high = nrow; 377 for (l=0; l<n; l++) { /* loop over added columns */ 378 col = cidx[in[l]]; 379 value = v[l]; 380 381 if (col <= lastcol) low = 0; 382 else high = nrow; 383 lastcol = col; 384 while (high-low > 5) { 385 t = (low+high)/2; 386 if (rp[t] > col) high = t; 387 else low = t; 388 } 389 for (i=low; i<high; i++) { 390 if (rp[i] == col) { 391 ap[i] += value; 392 low = i + 1; 393 break; 394 } 395 } 396 } 397 return 0; 398 } 399 400 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 401 { 402 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 403 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 404 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 405 PetscErrorCode ierr; 406 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 407 MatScalar *ap=NULL,value=0.0,*aa = a->a; 408 PetscBool ignorezeroentries = a->ignorezeroentries; 409 PetscBool roworiented = a->roworiented; 410 411 PetscFunctionBegin; 412 for (k=0; k<m; k++) { /* loop over added rows */ 413 row = im[k]; 414 if (row < 0) continue; 415 #if defined(PETSC_USE_DEBUG) 416 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); 417 #endif 418 rp = aj + ai[row]; 419 if (!A->structure_only) ap = aa + ai[row]; 420 rmax = imax[row]; nrow = ailen[row]; 421 low = 0; 422 high = nrow; 423 for (l=0; l<n; l++) { /* loop over added columns */ 424 if (in[l] < 0) continue; 425 #if defined(PETSC_USE_DEBUG) 426 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); 427 #endif 428 col = in[l]; 429 if (!A->structure_only) { 430 if (roworiented) { 431 value = v[l + k*n]; 432 } else { 433 value = v[k + l*m]; 434 } 435 } else { /* A->structure_only */ 436 value = 1; /* avoid 'continue' below? */ 437 } 438 if ((value == 0.0 && ignorezeroentries) && (is == ADD_VALUES) && row != col) continue; 439 440 if (col <= lastcol) low = 0; 441 else high = nrow; 442 lastcol = col; 443 while (high-low > 5) { 444 t = (low+high)/2; 445 if (rp[t] > col) high = t; 446 else low = t; 447 } 448 for (i=low; i<high; i++) { 449 if (rp[i] > col) break; 450 if (rp[i] == col) { 451 if (!A->structure_only) { 452 if (is == ADD_VALUES) ap[i] += value; 453 else ap[i] = value; 454 } 455 low = i + 1; 456 goto noinsert; 457 } 458 } 459 if (value == 0.0 && ignorezeroentries && row != col) goto noinsert; 460 if (nonew == 1) goto noinsert; 461 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 462 if (A->structure_only) { 463 MatSeqXAIJReallocateAIJ_structure_only(A,A->rmap->n,1,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar); 464 } else { 465 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 466 } 467 N = nrow++ - 1; a->nz++; high++; 468 /* shift up all the later entries in this row */ 469 for (ii=N; ii>=i; ii--) { 470 rp[ii+1] = rp[ii]; 471 if (!A->structure_only) ap[ii+1] = ap[ii]; 472 } 473 rp[i] = col; 474 if (!A->structure_only) ap[i] = value; 475 low = i + 1; 476 A->nonzerostate++; 477 noinsert:; 478 } 479 ailen[row] = nrow; 480 } 481 PetscFunctionReturn(0); 482 } 483 484 485 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 486 { 487 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 488 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 489 PetscInt *ai = a->i,*ailen = a->ilen; 490 MatScalar *ap,*aa = a->a; 491 492 PetscFunctionBegin; 493 for (k=0; k<m; k++) { /* loop over rows */ 494 row = im[k]; 495 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 496 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); 497 rp = aj + ai[row]; ap = aa + ai[row]; 498 nrow = ailen[row]; 499 for (l=0; l<n; l++) { /* loop over columns */ 500 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 501 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); 502 col = in[l]; 503 high = nrow; low = 0; /* assume unsorted */ 504 while (high-low > 5) { 505 t = (low+high)/2; 506 if (rp[t] > col) high = t; 507 else low = t; 508 } 509 for (i=low; i<high; i++) { 510 if (rp[i] > col) break; 511 if (rp[i] == col) { 512 *v++ = ap[i]; 513 goto finished; 514 } 515 } 516 *v++ = 0.0; 517 finished:; 518 } 519 } 520 PetscFunctionReturn(0); 521 } 522 523 524 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 525 { 526 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 527 PetscErrorCode ierr; 528 PetscInt i,*col_lens; 529 int fd; 530 FILE *file; 531 532 PetscFunctionBegin; 533 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 534 ierr = PetscMalloc1(4+A->rmap->n,&col_lens);CHKERRQ(ierr); 535 536 col_lens[0] = MAT_FILE_CLASSID; 537 col_lens[1] = A->rmap->n; 538 col_lens[2] = A->cmap->n; 539 col_lens[3] = a->nz; 540 541 /* store lengths of each row and write (including header) to file */ 542 for (i=0; i<A->rmap->n; i++) { 543 col_lens[4+i] = a->i[i+1] - a->i[i]; 544 } 545 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 546 ierr = PetscFree(col_lens);CHKERRQ(ierr); 547 548 /* store column indices (zero start index) */ 549 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 550 551 /* store nonzero values */ 552 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 553 554 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 555 if (file) { 556 fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); 557 } 558 PetscFunctionReturn(0); 559 } 560 561 static PetscErrorCode MatView_SeqAIJ_ASCII_structonly(Mat A,PetscViewer viewer) 562 { 563 PetscErrorCode ierr; 564 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 565 PetscInt i,k,m=A->rmap->N; 566 567 PetscFunctionBegin; 568 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 569 for (i=0; i<m; i++) { 570 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 571 for (k=a->i[i]; k<a->i[i+1]; k++) { 572 ierr = PetscViewerASCIIPrintf(viewer," (%D) ",a->j[k]);CHKERRQ(ierr); 573 } 574 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 575 } 576 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 577 PetscFunctionReturn(0); 578 } 579 580 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 581 582 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 583 { 584 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 585 PetscErrorCode ierr; 586 PetscInt i,j,m = A->rmap->n; 587 const char *name; 588 PetscViewerFormat format; 589 590 PetscFunctionBegin; 591 if (A->structure_only) { 592 ierr = MatView_SeqAIJ_ASCII_structonly(A,viewer);CHKERRQ(ierr); 593 PetscFunctionReturn(0); 594 } 595 596 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 597 if (format == PETSC_VIEWER_ASCII_MATLAB) { 598 PetscInt nofinalvalue = 0; 599 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { 600 /* Need a dummy value to ensure the dimension of the matrix. */ 601 nofinalvalue = 1; 602 } 603 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 604 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 605 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 606 #if defined(PETSC_USE_COMPLEX) 607 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 608 #else 609 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 610 #endif 611 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 612 613 for (i=0; i<m; i++) { 614 for (j=a->i[i]; j<a->i[i+1]; j++) { 615 #if defined(PETSC_USE_COMPLEX) 616 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); 617 #else 618 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); 619 #endif 620 } 621 } 622 if (nofinalvalue) { 623 #if defined(PETSC_USE_COMPLEX) 624 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); 625 #else 626 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 627 #endif 628 } 629 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 630 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 631 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 632 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 633 PetscFunctionReturn(0); 634 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 635 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 636 for (i=0; i<m; i++) { 637 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 638 for (j=a->i[i]; j<a->i[i+1]; j++) { 639 #if defined(PETSC_USE_COMPLEX) 640 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 641 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 642 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 643 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 644 } else if (PetscRealPart(a->a[j]) != 0.0) { 645 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 646 } 647 #else 648 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} 649 #endif 650 } 651 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 652 } 653 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 654 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 655 PetscInt nzd=0,fshift=1,*sptr; 656 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 657 ierr = PetscMalloc1(m+1,&sptr);CHKERRQ(ierr); 658 for (i=0; i<m; i++) { 659 sptr[i] = nzd+1; 660 for (j=a->i[i]; j<a->i[i+1]; j++) { 661 if (a->j[j] >= i) { 662 #if defined(PETSC_USE_COMPLEX) 663 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 664 #else 665 if (a->a[j] != 0.0) nzd++; 666 #endif 667 } 668 } 669 } 670 sptr[m] = nzd+1; 671 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 672 for (i=0; i<m+1; i+=6) { 673 if (i+4<m) { 674 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); 675 } else if (i+3<m) { 676 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); 677 } else if (i+2<m) { 678 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 679 } else if (i+1<m) { 680 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 681 } else if (i<m) { 682 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 683 } else { 684 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 685 } 686 } 687 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 688 ierr = PetscFree(sptr);CHKERRQ(ierr); 689 for (i=0; i<m; i++) { 690 for (j=a->i[i]; j<a->i[i+1]; j++) { 691 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 692 } 693 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 694 } 695 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 696 for (i=0; i<m; i++) { 697 for (j=a->i[i]; j<a->i[i+1]; j++) { 698 if (a->j[j] >= i) { 699 #if defined(PETSC_USE_COMPLEX) 700 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 701 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 702 } 703 #else 704 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} 705 #endif 706 } 707 } 708 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 709 } 710 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 711 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 712 PetscInt cnt = 0,jcnt; 713 PetscScalar value; 714 #if defined(PETSC_USE_COMPLEX) 715 PetscBool realonly = PETSC_TRUE; 716 717 for (i=0; i<a->i[m]; i++) { 718 if (PetscImaginaryPart(a->a[i]) != 0.0) { 719 realonly = PETSC_FALSE; 720 break; 721 } 722 } 723 #endif 724 725 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 726 for (i=0; i<m; i++) { 727 jcnt = 0; 728 for (j=0; j<A->cmap->n; j++) { 729 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 730 value = a->a[cnt++]; 731 jcnt++; 732 } else { 733 value = 0.0; 734 } 735 #if defined(PETSC_USE_COMPLEX) 736 if (realonly) { 737 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); 738 } else { 739 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); 740 } 741 #else 742 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); 743 #endif 744 } 745 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 746 } 747 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 748 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 749 PetscInt fshift=1; 750 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 751 #if defined(PETSC_USE_COMPLEX) 752 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");CHKERRQ(ierr); 753 #else 754 ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");CHKERRQ(ierr); 755 #endif 756 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 757 for (i=0; i<m; i++) { 758 for (j=a->i[i]; j<a->i[i+1]; j++) { 759 #if defined(PETSC_USE_COMPLEX) 760 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); 761 #else 762 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); 763 #endif 764 } 765 } 766 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 767 } else { 768 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 769 if (A->factortype) { 770 for (i=0; i<m; i++) { 771 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 772 /* L part */ 773 for (j=a->i[i]; j<a->i[i+1]; j++) { 774 #if defined(PETSC_USE_COMPLEX) 775 if (PetscImaginaryPart(a->a[j]) > 0.0) { 776 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 777 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 778 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 779 } else { 780 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 781 } 782 #else 783 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 784 #endif 785 } 786 /* diagonal */ 787 j = a->diag[i]; 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(1.0/a->a[j]),(double)PetscImaginaryPart(1.0/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(1.0/a->a[j]),(double)(-PetscImaginaryPart(1.0/a->a[j])));CHKERRQ(ierr); 793 } else { 794 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 795 } 796 #else 797 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); 798 #endif 799 800 /* U part */ 801 for (j=a->diag[i+1]+1; j<a->diag[i]; j++) { 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(a->a[j]),(double)PetscImaginaryPart(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(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); 807 } else { 808 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 809 } 810 #else 811 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 812 #endif 813 } 814 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 815 } 816 } else { 817 for (i=0; i<m; i++) { 818 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 819 for (j=a->i[i]; j<a->i[i+1]; j++) { 820 #if defined(PETSC_USE_COMPLEX) 821 if (PetscImaginaryPart(a->a[j]) > 0.0) { 822 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 823 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 824 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 825 } else { 826 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); 827 } 828 #else 829 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); 830 #endif 831 } 832 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 833 } 834 } 835 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 836 } 837 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 838 PetscFunctionReturn(0); 839 } 840 841 #include <petscdraw.h> 842 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 843 { 844 Mat A = (Mat) Aa; 845 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 846 PetscErrorCode ierr; 847 PetscInt i,j,m = A->rmap->n; 848 int color; 849 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r; 850 PetscViewer viewer; 851 PetscViewerFormat format; 852 853 PetscFunctionBegin; 854 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 855 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 856 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 857 858 /* loop over matrix elements drawing boxes */ 859 860 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 861 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 862 /* Blue for negative, Cyan for zero and Red for positive */ 863 color = PETSC_DRAW_BLUE; 864 for (i=0; i<m; i++) { 865 y_l = m - i - 1.0; y_r = y_l + 1.0; 866 for (j=a->i[i]; j<a->i[i+1]; j++) { 867 x_l = a->j[j]; x_r = x_l + 1.0; 868 if (PetscRealPart(a->a[j]) >= 0.) continue; 869 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 870 } 871 } 872 color = PETSC_DRAW_CYAN; 873 for (i=0; i<m; i++) { 874 y_l = m - i - 1.0; y_r = y_l + 1.0; 875 for (j=a->i[i]; j<a->i[i+1]; j++) { 876 x_l = a->j[j]; x_r = x_l + 1.0; 877 if (a->a[j] != 0.) continue; 878 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 879 } 880 } 881 color = PETSC_DRAW_RED; 882 for (i=0; i<m; i++) { 883 y_l = m - i - 1.0; y_r = y_l + 1.0; 884 for (j=a->i[i]; j<a->i[i+1]; j++) { 885 x_l = a->j[j]; x_r = x_l + 1.0; 886 if (PetscRealPart(a->a[j]) <= 0.) continue; 887 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 888 } 889 } 890 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 891 } else { 892 /* use contour shading to indicate magnitude of values */ 893 /* first determine max of all nonzero values */ 894 PetscReal minv = 0.0, maxv = 0.0; 895 PetscInt nz = a->nz, count = 0; 896 PetscDraw popup; 897 898 for (i=0; i<nz; i++) { 899 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 900 } 901 if (minv >= maxv) maxv = minv + PETSC_SMALL; 902 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 903 ierr = PetscDrawScalePopup(popup,minv,maxv);CHKERRQ(ierr); 904 905 ierr = PetscDrawCollectiveBegin(draw);CHKERRQ(ierr); 906 for (i=0; i<m; i++) { 907 y_l = m - i - 1.0; 908 y_r = y_l + 1.0; 909 for (j=a->i[i]; j<a->i[i+1]; j++) { 910 x_l = a->j[j]; 911 x_r = x_l + 1.0; 912 color = PetscDrawRealToColor(PetscAbsScalar(a->a[count]),minv,maxv); 913 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 914 count++; 915 } 916 } 917 ierr = PetscDrawCollectiveEnd(draw);CHKERRQ(ierr); 918 } 919 PetscFunctionReturn(0); 920 } 921 922 #include <petscdraw.h> 923 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 924 { 925 PetscErrorCode ierr; 926 PetscDraw draw; 927 PetscReal xr,yr,xl,yl,h,w; 928 PetscBool isnull; 929 930 PetscFunctionBegin; 931 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 932 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 933 if (isnull) PetscFunctionReturn(0); 934 935 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 936 xr += w; yr += h; xl = -w; yl = -h; 937 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 938 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 939 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 940 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 941 ierr = PetscDrawSave(draw);CHKERRQ(ierr); 942 PetscFunctionReturn(0); 943 } 944 945 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 946 { 947 PetscErrorCode ierr; 948 PetscBool iascii,isbinary,isdraw; 949 950 PetscFunctionBegin; 951 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 952 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 953 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 954 if (iascii) { 955 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 956 } else if (isbinary) { 957 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 958 } else if (isdraw) { 959 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 960 } 961 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 962 PetscFunctionReturn(0); 963 } 964 965 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 966 { 967 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 968 PetscErrorCode ierr; 969 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 970 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 971 MatScalar *aa = a->a,*ap; 972 PetscReal ratio = 0.6; 973 974 PetscFunctionBegin; 975 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 976 977 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 978 for (i=1; i<m; i++) { 979 /* move each row back by the amount of empty slots (fshift) before it*/ 980 fshift += imax[i-1] - ailen[i-1]; 981 rmax = PetscMax(rmax,ailen[i]); 982 if (fshift) { 983 ip = aj + ai[i]; 984 ap = aa + ai[i]; 985 N = ailen[i]; 986 for (j=0; j<N; j++) { 987 ip[j-fshift] = ip[j]; 988 if (!A->structure_only) ap[j-fshift] = ap[j]; 989 } 990 } 991 ai[i] = ai[i-1] + ailen[i-1]; 992 } 993 if (m) { 994 fshift += imax[m-1] - ailen[m-1]; 995 ai[m] = ai[m-1] + ailen[m-1]; 996 } 997 998 /* reset ilen and imax for each row */ 999 a->nonzerorowcnt = 0; 1000 if (A->structure_only) { 1001 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1002 } else { /* !A->structure_only */ 1003 for (i=0; i<m; i++) { 1004 ailen[i] = imax[i] = ai[i+1] - ai[i]; 1005 a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0); 1006 } 1007 } 1008 a->nz = ai[m]; 1009 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); 1010 1011 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1012 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 1013 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 1014 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 1015 1016 A->info.mallocs += a->reallocs; 1017 a->reallocs = 0; 1018 A->info.nz_unneeded = (PetscReal)fshift; 1019 a->rmax = rmax; 1020 1021 if (!A->structure_only) { 1022 ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 1023 } 1024 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 1025 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1026 PetscFunctionReturn(0); 1027 } 1028 1029 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 1030 { 1031 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1032 PetscInt i,nz = a->nz; 1033 MatScalar *aa = a->a; 1034 PetscErrorCode ierr; 1035 1036 PetscFunctionBegin; 1037 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1038 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1039 PetscFunctionReturn(0); 1040 } 1041 1042 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 1043 { 1044 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1045 PetscInt i,nz = a->nz; 1046 MatScalar *aa = a->a; 1047 PetscErrorCode ierr; 1048 1049 PetscFunctionBegin; 1050 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1051 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1052 PetscFunctionReturn(0); 1053 } 1054 1055 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1056 { 1057 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1058 PetscErrorCode ierr; 1059 1060 PetscFunctionBegin; 1061 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1062 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1063 PetscFunctionReturn(0); 1064 } 1065 1066 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1067 { 1068 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1069 PetscErrorCode ierr; 1070 1071 PetscFunctionBegin; 1072 #if defined(PETSC_USE_LOG) 1073 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1074 #endif 1075 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1076 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1077 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1078 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1079 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1080 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1081 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1082 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1083 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1084 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1085 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1086 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1087 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1088 1089 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1090 ierr = PetscFree(A->data);CHKERRQ(ierr); 1091 1092 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1093 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1094 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1095 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1096 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1097 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1098 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1099 #if defined(PETSC_HAVE_ELEMENTAL) 1100 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); 1101 #endif 1102 #if defined(PETSC_HAVE_HYPRE) 1103 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_hypre_C",NULL);CHKERRQ(ierr); 1104 ierr = PetscObjectComposeFunction((PetscObject)A,"MatMatMatMult_transpose_seqaij_seqaij_C",NULL);CHKERRQ(ierr); 1105 #endif 1106 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); 1107 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1108 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1109 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1110 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1111 PetscFunctionReturn(0); 1112 } 1113 1114 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1115 { 1116 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1117 PetscErrorCode ierr; 1118 1119 PetscFunctionBegin; 1120 switch (op) { 1121 case MAT_ROW_ORIENTED: 1122 a->roworiented = flg; 1123 break; 1124 case MAT_KEEP_NONZERO_PATTERN: 1125 a->keepnonzeropattern = flg; 1126 break; 1127 case MAT_NEW_NONZERO_LOCATIONS: 1128 a->nonew = (flg ? 0 : 1); 1129 break; 1130 case MAT_NEW_NONZERO_LOCATION_ERR: 1131 a->nonew = (flg ? -1 : 0); 1132 break; 1133 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1134 a->nonew = (flg ? -2 : 0); 1135 break; 1136 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1137 a->nounused = (flg ? -1 : 0); 1138 break; 1139 case MAT_IGNORE_ZERO_ENTRIES: 1140 a->ignorezeroentries = flg; 1141 break; 1142 case MAT_SPD: 1143 case MAT_SYMMETRIC: 1144 case MAT_STRUCTURALLY_SYMMETRIC: 1145 case MAT_HERMITIAN: 1146 case MAT_SYMMETRY_ETERNAL: 1147 case MAT_STRUCTURE_ONLY: 1148 /* These options are handled directly by MatSetOption() */ 1149 break; 1150 case MAT_NEW_DIAGONALS: 1151 case MAT_IGNORE_OFF_PROC_ENTRIES: 1152 case MAT_USE_HASH_TABLE: 1153 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1154 break; 1155 case MAT_USE_INODES: 1156 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1157 break; 1158 case MAT_SUBMAT_SINGLEIS: 1159 A->submat_singleis = flg; 1160 break; 1161 default: 1162 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1163 } 1164 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1165 PetscFunctionReturn(0); 1166 } 1167 1168 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1169 { 1170 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1171 PetscErrorCode ierr; 1172 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1173 PetscScalar *aa=a->a,*x,zero=0.0; 1174 1175 PetscFunctionBegin; 1176 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1177 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1178 1179 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1180 PetscInt *diag=a->diag; 1181 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1182 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1183 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1184 PetscFunctionReturn(0); 1185 } 1186 1187 ierr = VecSet(v,zero);CHKERRQ(ierr); 1188 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1189 for (i=0; i<n; i++) { 1190 nz = ai[i+1] - ai[i]; 1191 if (!nz) x[i] = 0.0; 1192 for (j=ai[i]; j<ai[i+1]; j++) { 1193 if (aj[j] == i) { 1194 x[i] = aa[j]; 1195 break; 1196 } 1197 } 1198 } 1199 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1200 PetscFunctionReturn(0); 1201 } 1202 1203 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1204 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1205 { 1206 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1207 PetscScalar *y; 1208 const PetscScalar *x; 1209 PetscErrorCode ierr; 1210 PetscInt m = A->rmap->n; 1211 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1212 const MatScalar *v; 1213 PetscScalar alpha; 1214 PetscInt n,i,j; 1215 const PetscInt *idx,*ii,*ridx=NULL; 1216 Mat_CompressedRow cprow = a->compressedrow; 1217 PetscBool usecprow = cprow.use; 1218 #endif 1219 1220 PetscFunctionBegin; 1221 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1222 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1223 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1224 1225 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1226 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1227 #else 1228 if (usecprow) { 1229 m = cprow.nrows; 1230 ii = cprow.i; 1231 ridx = cprow.rindex; 1232 } else { 1233 ii = a->i; 1234 } 1235 for (i=0; i<m; i++) { 1236 idx = a->j + ii[i]; 1237 v = a->a + ii[i]; 1238 n = ii[i+1] - ii[i]; 1239 if (usecprow) { 1240 alpha = x[ridx[i]]; 1241 } else { 1242 alpha = x[i]; 1243 } 1244 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1245 } 1246 #endif 1247 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1248 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1249 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1250 PetscFunctionReturn(0); 1251 } 1252 1253 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1254 { 1255 PetscErrorCode ierr; 1256 1257 PetscFunctionBegin; 1258 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1259 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1260 PetscFunctionReturn(0); 1261 } 1262 1263 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1264 1265 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1266 { 1267 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1268 PetscScalar *y; 1269 const PetscScalar *x; 1270 const MatScalar *aa; 1271 PetscErrorCode ierr; 1272 PetscInt m=A->rmap->n; 1273 const PetscInt *aj,*ii,*ridx=NULL; 1274 PetscInt n,i; 1275 PetscScalar sum; 1276 PetscBool usecprow=a->compressedrow.use; 1277 1278 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1279 #pragma disjoint(*x,*y,*aa) 1280 #endif 1281 1282 PetscFunctionBegin; 1283 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1284 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1285 ii = a->i; 1286 if (usecprow) { /* use compressed row format */ 1287 ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1288 m = a->compressedrow.nrows; 1289 ii = a->compressedrow.i; 1290 ridx = a->compressedrow.rindex; 1291 for (i=0; i<m; i++) { 1292 n = ii[i+1] - ii[i]; 1293 aj = a->j + ii[i]; 1294 aa = a->a + ii[i]; 1295 sum = 0.0; 1296 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1297 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1298 y[*ridx++] = sum; 1299 } 1300 } else { /* do not use compressed row format */ 1301 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1302 aj = a->j; 1303 aa = a->a; 1304 fortranmultaij_(&m,x,ii,aj,aa,y); 1305 #else 1306 for (i=0; i<m; i++) { 1307 n = ii[i+1] - ii[i]; 1308 aj = a->j + ii[i]; 1309 aa = a->a + ii[i]; 1310 sum = 0.0; 1311 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1312 y[i] = sum; 1313 } 1314 #endif 1315 } 1316 ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); 1317 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1318 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1319 PetscFunctionReturn(0); 1320 } 1321 1322 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1323 { 1324 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1325 PetscScalar *y; 1326 const PetscScalar *x; 1327 const MatScalar *aa; 1328 PetscErrorCode ierr; 1329 PetscInt m=A->rmap->n; 1330 const PetscInt *aj,*ii,*ridx=NULL; 1331 PetscInt n,i,nonzerorow=0; 1332 PetscScalar sum; 1333 PetscBool usecprow=a->compressedrow.use; 1334 1335 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1336 #pragma disjoint(*x,*y,*aa) 1337 #endif 1338 1339 PetscFunctionBegin; 1340 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1341 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1342 if (usecprow) { /* use compressed row format */ 1343 m = a->compressedrow.nrows; 1344 ii = a->compressedrow.i; 1345 ridx = a->compressedrow.rindex; 1346 for (i=0; i<m; i++) { 1347 n = ii[i+1] - ii[i]; 1348 aj = a->j + ii[i]; 1349 aa = a->a + ii[i]; 1350 sum = 0.0; 1351 nonzerorow += (n>0); 1352 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1353 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1354 y[*ridx++] = sum; 1355 } 1356 } else { /* do not use compressed row format */ 1357 ii = a->i; 1358 for (i=0; i<m; i++) { 1359 n = ii[i+1] - ii[i]; 1360 aj = a->j + ii[i]; 1361 aa = a->a + ii[i]; 1362 sum = 0.0; 1363 nonzerorow += (n>0); 1364 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1365 y[i] = sum; 1366 } 1367 } 1368 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1369 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1370 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1371 PetscFunctionReturn(0); 1372 } 1373 1374 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1375 { 1376 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1377 PetscScalar *y,*z; 1378 const PetscScalar *x; 1379 const MatScalar *aa; 1380 PetscErrorCode ierr; 1381 PetscInt m = A->rmap->n,*aj,*ii; 1382 PetscInt n,i,*ridx=NULL; 1383 PetscScalar sum; 1384 PetscBool usecprow=a->compressedrow.use; 1385 1386 PetscFunctionBegin; 1387 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1388 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1389 if (usecprow) { /* use compressed row format */ 1390 if (zz != yy) { 1391 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1392 } 1393 m = a->compressedrow.nrows; 1394 ii = a->compressedrow.i; 1395 ridx = a->compressedrow.rindex; 1396 for (i=0; i<m; i++) { 1397 n = ii[i+1] - ii[i]; 1398 aj = a->j + ii[i]; 1399 aa = a->a + ii[i]; 1400 sum = y[*ridx]; 1401 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1402 z[*ridx++] = sum; 1403 } 1404 } else { /* do not use compressed row format */ 1405 ii = a->i; 1406 for (i=0; i<m; i++) { 1407 n = ii[i+1] - ii[i]; 1408 aj = a->j + ii[i]; 1409 aa = a->a + ii[i]; 1410 sum = y[i]; 1411 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1412 z[i] = sum; 1413 } 1414 } 1415 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1416 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1417 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1418 PetscFunctionReturn(0); 1419 } 1420 1421 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1422 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1423 { 1424 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1425 PetscScalar *y,*z; 1426 const PetscScalar *x; 1427 const MatScalar *aa; 1428 PetscErrorCode ierr; 1429 const PetscInt *aj,*ii,*ridx=NULL; 1430 PetscInt m = A->rmap->n,n,i; 1431 PetscScalar sum; 1432 PetscBool usecprow=a->compressedrow.use; 1433 1434 PetscFunctionBegin; 1435 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1436 ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1437 if (usecprow) { /* use compressed row format */ 1438 if (zz != yy) { 1439 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1440 } 1441 m = a->compressedrow.nrows; 1442 ii = a->compressedrow.i; 1443 ridx = a->compressedrow.rindex; 1444 for (i=0; i<m; i++) { 1445 n = ii[i+1] - ii[i]; 1446 aj = a->j + ii[i]; 1447 aa = a->a + ii[i]; 1448 sum = y[*ridx]; 1449 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1450 z[*ridx++] = sum; 1451 } 1452 } else { /* do not use compressed row format */ 1453 ii = a->i; 1454 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1455 aj = a->j; 1456 aa = a->a; 1457 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1458 #else 1459 for (i=0; i<m; i++) { 1460 n = ii[i+1] - ii[i]; 1461 aj = a->j + ii[i]; 1462 aa = a->a + ii[i]; 1463 sum = y[i]; 1464 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1465 z[i] = sum; 1466 } 1467 #endif 1468 } 1469 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1470 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1471 ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); 1472 #if defined(PETSC_HAVE_CUSP) 1473 /* 1474 ierr = VecView(xx,0);CHKERRQ(ierr); 1475 ierr = VecView(zz,0);CHKERRQ(ierr); 1476 ierr = MatView(A,0);CHKERRQ(ierr); 1477 */ 1478 #endif 1479 PetscFunctionReturn(0); 1480 } 1481 1482 /* 1483 Adds diagonal pointers to sparse matrix structure. 1484 */ 1485 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1486 { 1487 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1488 PetscErrorCode ierr; 1489 PetscInt i,j,m = A->rmap->n; 1490 1491 PetscFunctionBegin; 1492 if (!a->diag) { 1493 ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); 1494 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1495 } 1496 for (i=0; i<A->rmap->n; i++) { 1497 a->diag[i] = a->i[i+1]; 1498 for (j=a->i[i]; j<a->i[i+1]; j++) { 1499 if (a->j[j] == i) { 1500 a->diag[i] = j; 1501 break; 1502 } 1503 } 1504 } 1505 PetscFunctionReturn(0); 1506 } 1507 1508 /* 1509 Checks for missing diagonals 1510 */ 1511 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1512 { 1513 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1514 PetscInt *diag,*ii = a->i,i; 1515 1516 PetscFunctionBegin; 1517 *missing = PETSC_FALSE; 1518 if (A->rmap->n > 0 && !ii) { 1519 *missing = PETSC_TRUE; 1520 if (d) *d = 0; 1521 PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n"); 1522 } else { 1523 diag = a->diag; 1524 for (i=0; i<A->rmap->n; i++) { 1525 if (diag[i] >= ii[i+1]) { 1526 *missing = PETSC_TRUE; 1527 if (d) *d = i; 1528 PetscInfo1(A,"Matrix is missing diagonal number %D\n",i); 1529 break; 1530 } 1531 } 1532 } 1533 PetscFunctionReturn(0); 1534 } 1535 1536 /* 1537 Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways 1538 */ 1539 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1540 { 1541 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1542 PetscErrorCode ierr; 1543 PetscInt i,*diag,m = A->rmap->n; 1544 MatScalar *v = a->a; 1545 PetscScalar *idiag,*mdiag; 1546 1547 PetscFunctionBegin; 1548 if (a->idiagvalid) PetscFunctionReturn(0); 1549 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1550 diag = a->diag; 1551 if (!a->idiag) { 1552 ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); 1553 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1554 v = a->a; 1555 } 1556 mdiag = a->mdiag; 1557 idiag = a->idiag; 1558 1559 if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { 1560 for (i=0; i<m; i++) { 1561 mdiag[i] = v[diag[i]]; 1562 if (!PetscAbsScalar(mdiag[i])) { /* zero diagonal */ 1563 if (PetscRealPart(fshift)) { 1564 ierr = PetscInfo1(A,"Zero diagonal on row %D\n",i);CHKERRQ(ierr); 1565 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 1566 A->factorerror_zeropivot_value = 0.0; 1567 A->factorerror_zeropivot_row = i; 1568 } SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1569 } 1570 idiag[i] = 1.0/v[diag[i]]; 1571 } 1572 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1573 } else { 1574 for (i=0; i<m; i++) { 1575 mdiag[i] = v[diag[i]]; 1576 idiag[i] = omega/(fshift + v[diag[i]]); 1577 } 1578 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1579 } 1580 a->idiagvalid = PETSC_TRUE; 1581 PetscFunctionReturn(0); 1582 } 1583 1584 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1585 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1586 { 1587 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1588 PetscScalar *x,d,sum,*t,scale; 1589 const MatScalar *v,*idiag=0,*mdiag; 1590 const PetscScalar *b, *bs,*xb, *ts; 1591 PetscErrorCode ierr; 1592 PetscInt n,m = A->rmap->n,i; 1593 const PetscInt *idx,*diag; 1594 1595 PetscFunctionBegin; 1596 its = its*lits; 1597 1598 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1599 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1600 a->fshift = fshift; 1601 a->omega = omega; 1602 1603 diag = a->diag; 1604 t = a->ssor_work; 1605 idiag = a->idiag; 1606 mdiag = a->mdiag; 1607 1608 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1609 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1610 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1611 if (flag == SOR_APPLY_UPPER) { 1612 /* apply (U + D/omega) to the vector */ 1613 bs = b; 1614 for (i=0; i<m; i++) { 1615 d = fshift + mdiag[i]; 1616 n = a->i[i+1] - diag[i] - 1; 1617 idx = a->j + diag[i] + 1; 1618 v = a->a + diag[i] + 1; 1619 sum = b[i]*d/omega; 1620 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1621 x[i] = sum; 1622 } 1623 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1624 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1625 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1626 PetscFunctionReturn(0); 1627 } 1628 1629 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1630 else if (flag & SOR_EISENSTAT) { 1631 /* Let A = L + U + D; where L is lower trianglar, 1632 U is upper triangular, E = D/omega; This routine applies 1633 1634 (L + E)^{-1} A (U + E)^{-1} 1635 1636 to a vector efficiently using Eisenstat's trick. 1637 */ 1638 scale = (2.0/omega) - 1.0; 1639 1640 /* x = (E + U)^{-1} b */ 1641 for (i=m-1; i>=0; i--) { 1642 n = a->i[i+1] - diag[i] - 1; 1643 idx = a->j + diag[i] + 1; 1644 v = a->a + diag[i] + 1; 1645 sum = b[i]; 1646 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1647 x[i] = sum*idiag[i]; 1648 } 1649 1650 /* t = b - (2*E - D)x */ 1651 v = a->a; 1652 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1653 1654 /* t = (E + L)^{-1}t */ 1655 ts = t; 1656 diag = a->diag; 1657 for (i=0; i<m; i++) { 1658 n = diag[i] - a->i[i]; 1659 idx = a->j + a->i[i]; 1660 v = a->a + a->i[i]; 1661 sum = t[i]; 1662 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1663 t[i] = sum*idiag[i]; 1664 /* x = x + t */ 1665 x[i] += t[i]; 1666 } 1667 1668 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1669 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1670 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1671 PetscFunctionReturn(0); 1672 } 1673 if (flag & SOR_ZERO_INITIAL_GUESS) { 1674 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1675 for (i=0; i<m; i++) { 1676 n = diag[i] - a->i[i]; 1677 idx = a->j + a->i[i]; 1678 v = a->a + a->i[i]; 1679 sum = b[i]; 1680 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1681 t[i] = sum; 1682 x[i] = sum*idiag[i]; 1683 } 1684 xb = t; 1685 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1686 } else xb = b; 1687 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1688 for (i=m-1; i>=0; i--) { 1689 n = a->i[i+1] - diag[i] - 1; 1690 idx = a->j + diag[i] + 1; 1691 v = a->a + diag[i] + 1; 1692 sum = xb[i]; 1693 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1694 if (xb == b) { 1695 x[i] = sum*idiag[i]; 1696 } else { 1697 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1698 } 1699 } 1700 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1701 } 1702 its--; 1703 } 1704 while (its--) { 1705 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1706 for (i=0; i<m; i++) { 1707 /* lower */ 1708 n = diag[i] - a->i[i]; 1709 idx = a->j + a->i[i]; 1710 v = a->a + a->i[i]; 1711 sum = b[i]; 1712 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1713 t[i] = sum; /* save application of the lower-triangular part */ 1714 /* upper */ 1715 n = a->i[i+1] - diag[i] - 1; 1716 idx = a->j + diag[i] + 1; 1717 v = a->a + diag[i] + 1; 1718 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1719 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1720 } 1721 xb = t; 1722 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1723 } else xb = b; 1724 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1725 for (i=m-1; i>=0; i--) { 1726 sum = xb[i]; 1727 if (xb == b) { 1728 /* whole matrix (no checkpointing available) */ 1729 n = a->i[i+1] - a->i[i]; 1730 idx = a->j + a->i[i]; 1731 v = a->a + a->i[i]; 1732 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1733 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1734 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1735 n = a->i[i+1] - diag[i] - 1; 1736 idx = a->j + diag[i] + 1; 1737 v = a->a + diag[i] + 1; 1738 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1739 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1740 } 1741 } 1742 if (xb == b) { 1743 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1744 } else { 1745 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1746 } 1747 } 1748 } 1749 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1750 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1751 PetscFunctionReturn(0); 1752 } 1753 1754 1755 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1756 { 1757 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1758 1759 PetscFunctionBegin; 1760 info->block_size = 1.0; 1761 info->nz_allocated = (double)a->maxnz; 1762 info->nz_used = (double)a->nz; 1763 info->nz_unneeded = (double)(a->maxnz - a->nz); 1764 info->assemblies = (double)A->num_ass; 1765 info->mallocs = (double)A->info.mallocs; 1766 info->memory = ((PetscObject)A)->mem; 1767 if (A->factortype) { 1768 info->fill_ratio_given = A->info.fill_ratio_given; 1769 info->fill_ratio_needed = A->info.fill_ratio_needed; 1770 info->factor_mallocs = A->info.factor_mallocs; 1771 } else { 1772 info->fill_ratio_given = 0; 1773 info->fill_ratio_needed = 0; 1774 info->factor_mallocs = 0; 1775 } 1776 PetscFunctionReturn(0); 1777 } 1778 1779 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1780 { 1781 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1782 PetscInt i,m = A->rmap->n - 1; 1783 PetscErrorCode ierr; 1784 const PetscScalar *xx; 1785 PetscScalar *bb; 1786 PetscInt d = 0; 1787 1788 PetscFunctionBegin; 1789 if (x && b) { 1790 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1791 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1792 for (i=0; i<N; i++) { 1793 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1794 bb[rows[i]] = diag*xx[rows[i]]; 1795 } 1796 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1797 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1798 } 1799 1800 if (a->keepnonzeropattern) { 1801 for (i=0; i<N; i++) { 1802 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1803 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1804 } 1805 if (diag != 0.0) { 1806 for (i=0; i<N; i++) { 1807 d = rows[i]; 1808 if (a->diag[d] >= a->i[d+1]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in the zeroed row %D",d); 1809 } 1810 for (i=0; i<N; i++) { 1811 a->a[a->diag[rows[i]]] = diag; 1812 } 1813 } 1814 } else { 1815 if (diag != 0.0) { 1816 for (i=0; i<N; i++) { 1817 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1818 if (a->ilen[rows[i]] > 0) { 1819 a->ilen[rows[i]] = 1; 1820 a->a[a->i[rows[i]]] = diag; 1821 a->j[a->i[rows[i]]] = rows[i]; 1822 } else { /* in case row was completely empty */ 1823 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1824 } 1825 } 1826 } else { 1827 for (i=0; i<N; i++) { 1828 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1829 a->ilen[rows[i]] = 0; 1830 } 1831 } 1832 A->nonzerostate++; 1833 } 1834 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1835 PetscFunctionReturn(0); 1836 } 1837 1838 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1839 { 1840 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1841 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1842 PetscErrorCode ierr; 1843 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1844 const PetscScalar *xx; 1845 PetscScalar *bb; 1846 1847 PetscFunctionBegin; 1848 if (x && b) { 1849 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1850 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1851 vecs = PETSC_TRUE; 1852 } 1853 ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); 1854 for (i=0; i<N; i++) { 1855 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1856 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1857 1858 zeroed[rows[i]] = PETSC_TRUE; 1859 } 1860 for (i=0; i<A->rmap->n; i++) { 1861 if (!zeroed[i]) { 1862 for (j=a->i[i]; j<a->i[i+1]; j++) { 1863 if (zeroed[a->j[j]]) { 1864 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1865 a->a[j] = 0.0; 1866 } 1867 } 1868 } else if (vecs) bb[i] = diag*xx[i]; 1869 } 1870 if (x && b) { 1871 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1872 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1873 } 1874 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1875 if (diag != 0.0) { 1876 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1877 if (missing) { 1878 if (a->nonew) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1879 else { 1880 for (i=0; i<N; i++) { 1881 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1882 } 1883 } 1884 } else { 1885 for (i=0; i<N; i++) { 1886 a->a[a->diag[rows[i]]] = diag; 1887 } 1888 } 1889 } 1890 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1891 PetscFunctionReturn(0); 1892 } 1893 1894 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1895 { 1896 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1897 PetscInt *itmp; 1898 1899 PetscFunctionBegin; 1900 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1901 1902 *nz = a->i[row+1] - a->i[row]; 1903 if (v) *v = a->a + a->i[row]; 1904 if (idx) { 1905 itmp = a->j + a->i[row]; 1906 if (*nz) *idx = itmp; 1907 else *idx = 0; 1908 } 1909 PetscFunctionReturn(0); 1910 } 1911 1912 /* remove this function? */ 1913 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1914 { 1915 PetscFunctionBegin; 1916 PetscFunctionReturn(0); 1917 } 1918 1919 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1920 { 1921 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1922 MatScalar *v = a->a; 1923 PetscReal sum = 0.0; 1924 PetscErrorCode ierr; 1925 PetscInt i,j; 1926 1927 PetscFunctionBegin; 1928 if (type == NORM_FROBENIUS) { 1929 #if defined(PETSC_USE_REAL___FP16) 1930 PetscBLASInt one = 1,nz = a->nz; 1931 *nrm = BLASnrm2_(&nz,v,&one); 1932 #else 1933 for (i=0; i<a->nz; i++) { 1934 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1935 } 1936 *nrm = PetscSqrtReal(sum); 1937 #endif 1938 ierr = PetscLogFlops(2*a->nz);CHKERRQ(ierr); 1939 } else if (type == NORM_1) { 1940 PetscReal *tmp; 1941 PetscInt *jj = a->j; 1942 ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); 1943 *nrm = 0.0; 1944 for (j=0; j<a->nz; j++) { 1945 tmp[*jj++] += PetscAbsScalar(*v); v++; 1946 } 1947 for (j=0; j<A->cmap->n; j++) { 1948 if (tmp[j] > *nrm) *nrm = tmp[j]; 1949 } 1950 ierr = PetscFree(tmp);CHKERRQ(ierr); 1951 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1952 } else if (type == NORM_INFINITY) { 1953 *nrm = 0.0; 1954 for (j=0; j<A->rmap->n; j++) { 1955 v = a->a + a->i[j]; 1956 sum = 0.0; 1957 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 1958 sum += PetscAbsScalar(*v); v++; 1959 } 1960 if (sum > *nrm) *nrm = sum; 1961 } 1962 ierr = PetscLogFlops(PetscMax(a->nz-1,0));CHKERRQ(ierr); 1963 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 1964 PetscFunctionReturn(0); 1965 } 1966 1967 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 1968 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 1969 { 1970 PetscErrorCode ierr; 1971 PetscInt i,j,anzj; 1972 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 1973 PetscInt an=A->cmap->N,am=A->rmap->N; 1974 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 1975 1976 PetscFunctionBegin; 1977 /* Allocate space for symbolic transpose info and work array */ 1978 ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); 1979 ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); 1980 ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); 1981 1982 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 1983 /* Note: offset by 1 for fast conversion into csr format. */ 1984 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 1985 /* Form ati for csr format of A^T. */ 1986 for (i=0;i<an;i++) ati[i+1] += ati[i]; 1987 1988 /* Copy ati into atfill so we have locations of the next free space in atj */ 1989 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 1990 1991 /* Walk through A row-wise and mark nonzero entries of A^T. */ 1992 for (i=0;i<am;i++) { 1993 anzj = ai[i+1] - ai[i]; 1994 for (j=0;j<anzj;j++) { 1995 atj[atfill[*aj]] = i; 1996 atfill[*aj++] += 1; 1997 } 1998 } 1999 2000 /* Clean up temporary space and complete requests. */ 2001 ierr = PetscFree(atfill);CHKERRQ(ierr); 2002 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2003 ierr = MatSetBlockSizes(*B,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2004 2005 b = (Mat_SeqAIJ*)((*B)->data); 2006 b->free_a = PETSC_FALSE; 2007 b->free_ij = PETSC_TRUE; 2008 b->nonew = 0; 2009 PetscFunctionReturn(0); 2010 } 2011 2012 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2013 { 2014 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2015 Mat C; 2016 PetscErrorCode ierr; 2017 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2018 MatScalar *array = a->a; 2019 2020 PetscFunctionBegin; 2021 if (reuse == MAT_INPLACE_MATRIX && m != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2022 2023 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) { 2024 ierr = PetscCalloc1(1+A->cmap->n,&col);CHKERRQ(ierr); 2025 2026 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2027 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2028 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2029 ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); 2030 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2031 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2032 ierr = PetscFree(col);CHKERRQ(ierr); 2033 } else { 2034 C = *B; 2035 } 2036 2037 for (i=0; i<m; i++) { 2038 len = ai[i+1]-ai[i]; 2039 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2040 array += len; 2041 aj += len; 2042 } 2043 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2044 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2045 2046 if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) { 2047 *B = C; 2048 } else { 2049 ierr = MatHeaderMerge(A,&C);CHKERRQ(ierr); 2050 } 2051 PetscFunctionReturn(0); 2052 } 2053 2054 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2055 { 2056 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2057 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2058 MatScalar *va,*vb; 2059 PetscErrorCode ierr; 2060 PetscInt ma,na,mb,nb, i; 2061 2062 PetscFunctionBegin; 2063 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2064 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2065 if (ma!=nb || na!=mb) { 2066 *f = PETSC_FALSE; 2067 PetscFunctionReturn(0); 2068 } 2069 aii = aij->i; bii = bij->i; 2070 adx = aij->j; bdx = bij->j; 2071 va = aij->a; vb = bij->a; 2072 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2073 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2074 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2075 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2076 2077 *f = PETSC_TRUE; 2078 for (i=0; i<ma; i++) { 2079 while (aptr[i]<aii[i+1]) { 2080 PetscInt idc,idr; 2081 PetscScalar vc,vr; 2082 /* column/row index/value */ 2083 idc = adx[aptr[i]]; 2084 idr = bdx[bptr[idc]]; 2085 vc = va[aptr[i]]; 2086 vr = vb[bptr[idc]]; 2087 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2088 *f = PETSC_FALSE; 2089 goto done; 2090 } else { 2091 aptr[i]++; 2092 if (B || i!=idc) bptr[idc]++; 2093 } 2094 } 2095 } 2096 done: 2097 ierr = PetscFree(aptr);CHKERRQ(ierr); 2098 ierr = PetscFree(bptr);CHKERRQ(ierr); 2099 PetscFunctionReturn(0); 2100 } 2101 2102 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2103 { 2104 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) B->data; 2105 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2106 MatScalar *va,*vb; 2107 PetscErrorCode ierr; 2108 PetscInt ma,na,mb,nb, i; 2109 2110 PetscFunctionBegin; 2111 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2112 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2113 if (ma!=nb || na!=mb) { 2114 *f = PETSC_FALSE; 2115 PetscFunctionReturn(0); 2116 } 2117 aii = aij->i; bii = bij->i; 2118 adx = aij->j; bdx = bij->j; 2119 va = aij->a; vb = bij->a; 2120 ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); 2121 ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); 2122 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2123 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2124 2125 *f = PETSC_TRUE; 2126 for (i=0; i<ma; i++) { 2127 while (aptr[i]<aii[i+1]) { 2128 PetscInt idc,idr; 2129 PetscScalar vc,vr; 2130 /* column/row index/value */ 2131 idc = adx[aptr[i]]; 2132 idr = bdx[bptr[idc]]; 2133 vc = va[aptr[i]]; 2134 vr = vb[bptr[idc]]; 2135 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2136 *f = PETSC_FALSE; 2137 goto done; 2138 } else { 2139 aptr[i]++; 2140 if (B || i!=idc) bptr[idc]++; 2141 } 2142 } 2143 } 2144 done: 2145 ierr = PetscFree(aptr);CHKERRQ(ierr); 2146 ierr = PetscFree(bptr);CHKERRQ(ierr); 2147 PetscFunctionReturn(0); 2148 } 2149 2150 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2151 { 2152 PetscErrorCode ierr; 2153 2154 PetscFunctionBegin; 2155 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2156 PetscFunctionReturn(0); 2157 } 2158 2159 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2160 { 2161 PetscErrorCode ierr; 2162 2163 PetscFunctionBegin; 2164 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2165 PetscFunctionReturn(0); 2166 } 2167 2168 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2169 { 2170 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2171 const PetscScalar *l,*r; 2172 PetscScalar x; 2173 MatScalar *v; 2174 PetscErrorCode ierr; 2175 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz; 2176 const PetscInt *jj; 2177 2178 PetscFunctionBegin; 2179 if (ll) { 2180 /* The local size is used so that VecMPI can be passed to this routine 2181 by MatDiagonalScale_MPIAIJ */ 2182 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2183 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2184 ierr = VecGetArrayRead(ll,&l);CHKERRQ(ierr); 2185 v = a->a; 2186 for (i=0; i<m; i++) { 2187 x = l[i]; 2188 M = a->i[i+1] - a->i[i]; 2189 for (j=0; j<M; j++) (*v++) *= x; 2190 } 2191 ierr = VecRestoreArrayRead(ll,&l);CHKERRQ(ierr); 2192 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2193 } 2194 if (rr) { 2195 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2196 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2197 ierr = VecGetArrayRead(rr,&r);CHKERRQ(ierr); 2198 v = a->a; jj = a->j; 2199 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2200 ierr = VecRestoreArrayRead(rr,&r);CHKERRQ(ierr); 2201 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2202 } 2203 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2204 PetscFunctionReturn(0); 2205 } 2206 2207 PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2208 { 2209 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2210 PetscErrorCode ierr; 2211 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2212 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2213 const PetscInt *irow,*icol; 2214 PetscInt nrows,ncols; 2215 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2216 MatScalar *a_new,*mat_a; 2217 Mat C; 2218 PetscBool stride; 2219 2220 PetscFunctionBegin; 2221 2222 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2223 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2224 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2225 2226 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2227 if (stride) { 2228 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2229 } else { 2230 first = 0; 2231 step = 0; 2232 } 2233 if (stride && step == 1) { 2234 /* special case of contiguous rows */ 2235 ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); 2236 /* loop over new rows determining lens and starting points */ 2237 for (i=0; i<nrows; i++) { 2238 kstart = ai[irow[i]]; 2239 kend = kstart + ailen[irow[i]]; 2240 starts[i] = kstart; 2241 for (k=kstart; k<kend; k++) { 2242 if (aj[k] >= first) { 2243 starts[i] = k; 2244 break; 2245 } 2246 } 2247 sum = 0; 2248 while (k < kend) { 2249 if (aj[k++] >= first+ncols) break; 2250 sum++; 2251 } 2252 lens[i] = sum; 2253 } 2254 /* create submatrix */ 2255 if (scall == MAT_REUSE_MATRIX) { 2256 PetscInt n_cols,n_rows; 2257 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2258 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2259 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2260 C = *B; 2261 } else { 2262 PetscInt rbs,cbs; 2263 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2264 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2265 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2266 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2267 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2268 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2269 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2270 } 2271 c = (Mat_SeqAIJ*)C->data; 2272 2273 /* loop over rows inserting into submatrix */ 2274 a_new = c->a; 2275 j_new = c->j; 2276 i_new = c->i; 2277 2278 for (i=0; i<nrows; i++) { 2279 ii = starts[i]; 2280 lensi = lens[i]; 2281 for (k=0; k<lensi; k++) { 2282 *j_new++ = aj[ii+k] - first; 2283 } 2284 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2285 a_new += lensi; 2286 i_new[i+1] = i_new[i] + lensi; 2287 c->ilen[i] = lensi; 2288 } 2289 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2290 } else { 2291 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2292 ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); 2293 ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); 2294 for (i=0; i<ncols; i++) { 2295 #if defined(PETSC_USE_DEBUG) 2296 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); 2297 #endif 2298 smap[icol[i]] = i+1; 2299 } 2300 2301 /* determine lens of each row */ 2302 for (i=0; i<nrows; i++) { 2303 kstart = ai[irow[i]]; 2304 kend = kstart + a->ilen[irow[i]]; 2305 lens[i] = 0; 2306 for (k=kstart; k<kend; k++) { 2307 if (smap[aj[k]]) { 2308 lens[i]++; 2309 } 2310 } 2311 } 2312 /* Create and fill new matrix */ 2313 if (scall == MAT_REUSE_MATRIX) { 2314 PetscBool equal; 2315 2316 c = (Mat_SeqAIJ*)((*B)->data); 2317 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2318 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2319 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2320 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2321 C = *B; 2322 } else { 2323 PetscInt rbs,cbs; 2324 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2325 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2326 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2327 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2328 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2329 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2330 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2331 } 2332 c = (Mat_SeqAIJ*)(C->data); 2333 for (i=0; i<nrows; i++) { 2334 row = irow[i]; 2335 kstart = ai[row]; 2336 kend = kstart + a->ilen[row]; 2337 mat_i = c->i[i]; 2338 mat_j = c->j + mat_i; 2339 mat_a = c->a + mat_i; 2340 mat_ilen = c->ilen + i; 2341 for (k=kstart; k<kend; k++) { 2342 if ((tcol=smap[a->j[k]])) { 2343 *mat_j++ = tcol - 1; 2344 *mat_a++ = a->a[k]; 2345 (*mat_ilen)++; 2346 2347 } 2348 } 2349 } 2350 /* Free work space */ 2351 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2352 ierr = PetscFree(smap);CHKERRQ(ierr); 2353 ierr = PetscFree(lens);CHKERRQ(ierr); 2354 /* sort */ 2355 for (i = 0; i < nrows; i++) { 2356 PetscInt ilen; 2357 2358 mat_i = c->i[i]; 2359 mat_j = c->j + mat_i; 2360 mat_a = c->a + mat_i; 2361 ilen = c->ilen[i]; 2362 ierr = PetscSortIntWithScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); 2363 } 2364 } 2365 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2366 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2367 2368 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2369 *B = C; 2370 PetscFunctionReturn(0); 2371 } 2372 2373 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2374 { 2375 PetscErrorCode ierr; 2376 Mat B; 2377 2378 PetscFunctionBegin; 2379 if (scall == MAT_INITIAL_MATRIX) { 2380 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2381 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2382 ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); 2383 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2384 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2385 *subMat = B; 2386 } else { 2387 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2388 } 2389 PetscFunctionReturn(0); 2390 } 2391 2392 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2393 { 2394 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2395 PetscErrorCode ierr; 2396 Mat outA; 2397 PetscBool row_identity,col_identity; 2398 2399 PetscFunctionBegin; 2400 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2401 2402 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2403 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2404 2405 outA = inA; 2406 outA->factortype = MAT_FACTOR_LU; 2407 ierr = PetscFree(inA->solvertype);CHKERRQ(ierr); 2408 ierr = PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);CHKERRQ(ierr); 2409 2410 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2411 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2412 2413 a->row = row; 2414 2415 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2416 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2417 2418 a->col = col; 2419 2420 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2421 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2422 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2423 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2424 2425 if (!a->solve_work) { /* this matrix may have been factored before */ 2426 ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); 2427 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2428 } 2429 2430 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2431 if (row_identity && col_identity) { 2432 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2433 } else { 2434 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2435 } 2436 PetscFunctionReturn(0); 2437 } 2438 2439 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2440 { 2441 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2442 PetscScalar oalpha = alpha; 2443 PetscErrorCode ierr; 2444 PetscBLASInt one = 1,bnz; 2445 2446 PetscFunctionBegin; 2447 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2448 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2449 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2450 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2451 PetscFunctionReturn(0); 2452 } 2453 2454 PetscErrorCode MatDestroySubMatrices_Private(Mat_SubSppt *submatj) 2455 { 2456 PetscErrorCode ierr; 2457 PetscInt i; 2458 2459 PetscFunctionBegin; 2460 if (!submatj->id) { /* delete data that are linked only to submats[id=0] */ 2461 ierr = PetscFree4(submatj->sbuf1,submatj->ptr,submatj->tmp,submatj->ctr);CHKERRQ(ierr); 2462 2463 for (i=0; i<submatj->nrqr; ++i) { 2464 ierr = PetscFree(submatj->sbuf2[i]);CHKERRQ(ierr); 2465 } 2466 ierr = PetscFree3(submatj->sbuf2,submatj->req_size,submatj->req_source1);CHKERRQ(ierr); 2467 2468 if (submatj->rbuf1) { 2469 ierr = PetscFree(submatj->rbuf1[0]);CHKERRQ(ierr); 2470 ierr = PetscFree(submatj->rbuf1);CHKERRQ(ierr); 2471 } 2472 2473 for (i=0; i<submatj->nrqs; ++i) { 2474 ierr = PetscFree(submatj->rbuf3[i]);CHKERRQ(ierr); 2475 } 2476 ierr = PetscFree3(submatj->req_source2,submatj->rbuf2,submatj->rbuf3);CHKERRQ(ierr); 2477 ierr = PetscFree(submatj->pa);CHKERRQ(ierr); 2478 } 2479 2480 #if defined(PETSC_USE_CTABLE) 2481 ierr = PetscTableDestroy((PetscTable*)&submatj->rmap);CHKERRQ(ierr); 2482 if (submatj->cmap_loc) {ierr = PetscFree(submatj->cmap_loc);CHKERRQ(ierr);} 2483 ierr = PetscFree(submatj->rmap_loc);CHKERRQ(ierr); 2484 #else 2485 ierr = PetscFree(submatj->rmap);CHKERRQ(ierr); 2486 #endif 2487 2488 if (!submatj->allcolumns) { 2489 #if defined(PETSC_USE_CTABLE) 2490 ierr = PetscTableDestroy((PetscTable*)&submatj->cmap);CHKERRQ(ierr); 2491 #else 2492 ierr = PetscFree(submatj->cmap);CHKERRQ(ierr); 2493 #endif 2494 } 2495 ierr = PetscFree(submatj->row2proc);CHKERRQ(ierr); 2496 2497 ierr = PetscFree(submatj);CHKERRQ(ierr); 2498 PetscFunctionReturn(0); 2499 } 2500 2501 PetscErrorCode MatDestroy_SeqAIJ_Submatrices(Mat C) 2502 { 2503 PetscErrorCode ierr; 2504 Mat_SeqAIJ *c = (Mat_SeqAIJ*)C->data; 2505 Mat_SubSppt *submatj = c->submatis1; 2506 2507 PetscFunctionBegin; 2508 ierr = submatj->destroy(C);CHKERRQ(ierr); 2509 ierr = MatDestroySubMatrices_Private(submatj);CHKERRQ(ierr); 2510 PetscFunctionReturn(0); 2511 } 2512 2513 PetscErrorCode MatCreateSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2514 { 2515 PetscErrorCode ierr; 2516 PetscInt i; 2517 2518 PetscFunctionBegin; 2519 if (scall == MAT_INITIAL_MATRIX) { 2520 ierr = PetscCalloc1(n+1,B);CHKERRQ(ierr); 2521 } 2522 2523 for (i=0; i<n; i++) { 2524 ierr = MatCreateSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2525 } 2526 PetscFunctionReturn(0); 2527 } 2528 2529 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2530 { 2531 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2532 PetscErrorCode ierr; 2533 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2534 const PetscInt *idx; 2535 PetscInt start,end,*ai,*aj; 2536 PetscBT table; 2537 2538 PetscFunctionBegin; 2539 m = A->rmap->n; 2540 ai = a->i; 2541 aj = a->j; 2542 2543 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2544 2545 ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); 2546 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2547 2548 for (i=0; i<is_max; i++) { 2549 /* Initialize the two local arrays */ 2550 isz = 0; 2551 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2552 2553 /* Extract the indices, assume there can be duplicate entries */ 2554 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2555 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2556 2557 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2558 for (j=0; j<n; ++j) { 2559 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2560 } 2561 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2562 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2563 2564 k = 0; 2565 for (j=0; j<ov; j++) { /* for each overlap */ 2566 n = isz; 2567 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2568 row = nidx[k]; 2569 start = ai[row]; 2570 end = ai[row+1]; 2571 for (l = start; l<end; l++) { 2572 val = aj[l]; 2573 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2574 } 2575 } 2576 } 2577 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2578 } 2579 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2580 ierr = PetscFree(nidx);CHKERRQ(ierr); 2581 PetscFunctionReturn(0); 2582 } 2583 2584 /* -------------------------------------------------------------- */ 2585 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2586 { 2587 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2588 PetscErrorCode ierr; 2589 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2590 const PetscInt *row,*col; 2591 PetscInt *cnew,j,*lens; 2592 IS icolp,irowp; 2593 PetscInt *cwork = NULL; 2594 PetscScalar *vwork = NULL; 2595 2596 PetscFunctionBegin; 2597 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2598 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2599 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2600 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2601 2602 /* determine lengths of permuted rows */ 2603 ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); 2604 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2605 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2606 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2607 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 2608 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2609 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2610 ierr = PetscFree(lens);CHKERRQ(ierr); 2611 2612 ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); 2613 for (i=0; i<m; i++) { 2614 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2615 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2616 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2617 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2618 } 2619 ierr = PetscFree(cnew);CHKERRQ(ierr); 2620 2621 (*B)->assembled = PETSC_FALSE; 2622 2623 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2624 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2625 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2626 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2627 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2628 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2629 PetscFunctionReturn(0); 2630 } 2631 2632 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2633 { 2634 PetscErrorCode ierr; 2635 2636 PetscFunctionBegin; 2637 /* If the two matrices have the same copy implementation, use fast copy. */ 2638 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2639 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2640 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2641 2642 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"); 2643 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2644 } else { 2645 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2646 } 2647 PetscFunctionReturn(0); 2648 } 2649 2650 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2651 { 2652 PetscErrorCode ierr; 2653 2654 PetscFunctionBegin; 2655 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2656 PetscFunctionReturn(0); 2657 } 2658 2659 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2660 { 2661 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2662 2663 PetscFunctionBegin; 2664 *array = a->a; 2665 PetscFunctionReturn(0); 2666 } 2667 2668 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2669 { 2670 PetscFunctionBegin; 2671 PetscFunctionReturn(0); 2672 } 2673 2674 /* 2675 Computes the number of nonzeros per row needed for preallocation when X and Y 2676 have different nonzero structure. 2677 */ 2678 PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) 2679 { 2680 PetscInt i,j,k,nzx,nzy; 2681 2682 PetscFunctionBegin; 2683 /* Set the number of nonzeros in the new matrix */ 2684 for (i=0; i<m; i++) { 2685 const PetscInt *xjj = xj+xi[i],*yjj = yj+yi[i]; 2686 nzx = xi[i+1] - xi[i]; 2687 nzy = yi[i+1] - yi[i]; 2688 nnz[i] = 0; 2689 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2690 for (; k<nzy && yjj[k]<xjj[j]; k++) nnz[i]++; /* Catch up to X */ 2691 if (k<nzy && yjj[k]==xjj[j]) k++; /* Skip duplicate */ 2692 nnz[i]++; 2693 } 2694 for (; k<nzy; k++) nnz[i]++; 2695 } 2696 PetscFunctionReturn(0); 2697 } 2698 2699 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2700 { 2701 PetscInt m = Y->rmap->N; 2702 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2703 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2704 PetscErrorCode ierr; 2705 2706 PetscFunctionBegin; 2707 /* Set the number of nonzeros in the new matrix */ 2708 ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); 2709 PetscFunctionReturn(0); 2710 } 2711 2712 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2713 { 2714 PetscErrorCode ierr; 2715 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 2716 PetscBLASInt one=1,bnz; 2717 2718 PetscFunctionBegin; 2719 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 2720 if (str == SAME_NONZERO_PATTERN) { 2721 PetscScalar alpha = a; 2722 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 2723 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 2724 ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); 2725 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2726 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2727 } else { 2728 Mat B; 2729 PetscInt *nnz; 2730 ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); 2731 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 2732 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 2733 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 2734 ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); 2735 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 2736 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 2737 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 2738 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2739 ierr = MatHeaderReplace(Y,&B);CHKERRQ(ierr); 2740 ierr = PetscFree(nnz);CHKERRQ(ierr); 2741 } 2742 PetscFunctionReturn(0); 2743 } 2744 2745 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 2746 { 2747 #if defined(PETSC_USE_COMPLEX) 2748 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 2749 PetscInt i,nz; 2750 PetscScalar *a; 2751 2752 PetscFunctionBegin; 2753 nz = aij->nz; 2754 a = aij->a; 2755 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 2756 #else 2757 PetscFunctionBegin; 2758 #endif 2759 PetscFunctionReturn(0); 2760 } 2761 2762 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2763 { 2764 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2765 PetscErrorCode ierr; 2766 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2767 PetscReal atmp; 2768 PetscScalar *x; 2769 MatScalar *aa; 2770 2771 PetscFunctionBegin; 2772 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2773 aa = a->a; 2774 ai = a->i; 2775 aj = a->j; 2776 2777 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2778 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2779 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2780 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2781 for (i=0; i<m; i++) { 2782 ncols = ai[1] - ai[0]; ai++; 2783 x[i] = 0.0; 2784 for (j=0; j<ncols; j++) { 2785 atmp = PetscAbsScalar(*aa); 2786 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2787 aa++; aj++; 2788 } 2789 } 2790 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2791 PetscFunctionReturn(0); 2792 } 2793 2794 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2795 { 2796 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2797 PetscErrorCode ierr; 2798 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2799 PetscScalar *x; 2800 MatScalar *aa; 2801 2802 PetscFunctionBegin; 2803 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2804 aa = a->a; 2805 ai = a->i; 2806 aj = a->j; 2807 2808 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2809 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2810 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2811 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2812 for (i=0; i<m; i++) { 2813 ncols = ai[1] - ai[0]; ai++; 2814 if (ncols == A->cmap->n) { /* row is dense */ 2815 x[i] = *aa; if (idx) idx[i] = 0; 2816 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2817 x[i] = 0.0; 2818 if (idx) { 2819 idx[i] = 0; /* in case ncols is zero */ 2820 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2821 if (aj[j] > j) { 2822 idx[i] = j; 2823 break; 2824 } 2825 } 2826 } 2827 } 2828 for (j=0; j<ncols; j++) { 2829 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2830 aa++; aj++; 2831 } 2832 } 2833 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2834 PetscFunctionReturn(0); 2835 } 2836 2837 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2838 { 2839 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2840 PetscErrorCode ierr; 2841 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2842 PetscReal atmp; 2843 PetscScalar *x; 2844 MatScalar *aa; 2845 2846 PetscFunctionBegin; 2847 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2848 aa = a->a; 2849 ai = a->i; 2850 aj = a->j; 2851 2852 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2853 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2854 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2855 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); 2856 for (i=0; i<m; i++) { 2857 ncols = ai[1] - ai[0]; ai++; 2858 if (ncols) { 2859 /* Get first nonzero */ 2860 for (j = 0; j < ncols; j++) { 2861 atmp = PetscAbsScalar(aa[j]); 2862 if (atmp > 1.0e-12) { 2863 x[i] = atmp; 2864 if (idx) idx[i] = aj[j]; 2865 break; 2866 } 2867 } 2868 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 2869 } else { 2870 x[i] = 0.0; if (idx) idx[i] = 0; 2871 } 2872 for (j = 0; j < ncols; j++) { 2873 atmp = PetscAbsScalar(*aa); 2874 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2875 aa++; aj++; 2876 } 2877 } 2878 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2879 PetscFunctionReturn(0); 2880 } 2881 2882 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2883 { 2884 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2885 PetscErrorCode ierr; 2886 PetscInt i,j,m = A->rmap->n,ncols,n; 2887 const PetscInt *ai,*aj; 2888 PetscScalar *x; 2889 const MatScalar *aa; 2890 2891 PetscFunctionBegin; 2892 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2893 aa = a->a; 2894 ai = a->i; 2895 aj = a->j; 2896 2897 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2898 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2899 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2900 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2901 for (i=0; i<m; i++) { 2902 ncols = ai[1] - ai[0]; ai++; 2903 if (ncols == A->cmap->n) { /* row is dense */ 2904 x[i] = *aa; if (idx) idx[i] = 0; 2905 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2906 x[i] = 0.0; 2907 if (idx) { /* find first implicit 0.0 in the row */ 2908 idx[i] = 0; /* in case ncols is zero */ 2909 for (j=0; j<ncols; j++) { 2910 if (aj[j] > j) { 2911 idx[i] = j; 2912 break; 2913 } 2914 } 2915 } 2916 } 2917 for (j=0; j<ncols; j++) { 2918 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2919 aa++; aj++; 2920 } 2921 } 2922 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2923 PetscFunctionReturn(0); 2924 } 2925 2926 #include <petscblaslapack.h> 2927 #include <petsc/private/kernels/blockinvert.h> 2928 2929 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 2930 { 2931 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 2932 PetscErrorCode ierr; 2933 PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 2934 MatScalar *diag,work[25],*v_work; 2935 PetscReal shift = 0.0; 2936 PetscBool allowzeropivot,zeropivotdetected=PETSC_FALSE; 2937 2938 PetscFunctionBegin; 2939 allowzeropivot = PetscNot(A->erroriffailure); 2940 if (a->ibdiagvalid) { 2941 if (values) *values = a->ibdiag; 2942 PetscFunctionReturn(0); 2943 } 2944 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 2945 if (!a->ibdiag) { 2946 ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); 2947 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 2948 } 2949 diag = a->ibdiag; 2950 if (values) *values = a->ibdiag; 2951 /* factor and invert each block */ 2952 switch (bs) { 2953 case 1: 2954 for (i=0; i<mbs; i++) { 2955 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 2956 if (PetscAbsScalar(diag[i] + shift) < PETSC_MACHINE_EPSILON) { 2957 if (allowzeropivot) { 2958 A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2959 A->factorerror_zeropivot_value = PetscAbsScalar(diag[i]); 2960 A->factorerror_zeropivot_row = i; 2961 ierr = PetscInfo3(A,"Zero pivot, row %D pivot %g tolerance %g\n",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON);CHKERRQ(ierr); 2962 } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D pivot %g tolerance %g",i,(double)PetscAbsScalar(diag[i]),(double)PETSC_MACHINE_EPSILON); 2963 } 2964 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 2965 } 2966 break; 2967 case 2: 2968 for (i=0; i<mbs; i++) { 2969 ij[0] = 2*i; ij[1] = 2*i + 1; 2970 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 2971 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 2972 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2973 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 2974 diag += 4; 2975 } 2976 break; 2977 case 3: 2978 for (i=0; i<mbs; i++) { 2979 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 2980 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 2981 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 2982 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2983 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 2984 diag += 9; 2985 } 2986 break; 2987 case 4: 2988 for (i=0; i<mbs; i++) { 2989 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 2990 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 2991 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 2992 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 2993 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 2994 diag += 16; 2995 } 2996 break; 2997 case 5: 2998 for (i=0; i<mbs; i++) { 2999 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3000 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3001 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3002 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3003 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3004 diag += 25; 3005 } 3006 break; 3007 case 6: 3008 for (i=0; i<mbs; i++) { 3009 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; 3010 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3011 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3012 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3013 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3014 diag += 36; 3015 } 3016 break; 3017 case 7: 3018 for (i=0; i<mbs; i++) { 3019 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; 3020 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3021 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3022 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3023 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3024 diag += 49; 3025 } 3026 break; 3027 default: 3028 ierr = PetscMalloc3(bs,&v_work,bs,&v_pivots,bs,&IJ);CHKERRQ(ierr); 3029 for (i=0; i<mbs; i++) { 3030 for (j=0; j<bs; j++) { 3031 IJ[j] = bs*i + j; 3032 } 3033 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3034 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);CHKERRQ(ierr); 3035 if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT; 3036 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3037 diag += bs2; 3038 } 3039 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3040 } 3041 a->ibdiagvalid = PETSC_TRUE; 3042 PetscFunctionReturn(0); 3043 } 3044 3045 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3046 { 3047 PetscErrorCode ierr; 3048 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3049 PetscScalar a; 3050 PetscInt m,n,i,j,col; 3051 3052 PetscFunctionBegin; 3053 if (!x->assembled) { 3054 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3055 for (i=0; i<m; i++) { 3056 for (j=0; j<aij->imax[i]; j++) { 3057 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3058 col = (PetscInt)(n*PetscRealPart(a)); 3059 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3060 } 3061 } 3062 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3063 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3064 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3065 PetscFunctionReturn(0); 3066 } 3067 3068 PetscErrorCode MatShift_SeqAIJ(Mat Y,PetscScalar a) 3069 { 3070 PetscErrorCode ierr; 3071 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)Y->data; 3072 3073 PetscFunctionBegin; 3074 if (!Y->preallocated || !aij->nz) { 3075 ierr = MatSeqAIJSetPreallocation(Y,1,NULL);CHKERRQ(ierr); 3076 } 3077 ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); 3078 PetscFunctionReturn(0); 3079 } 3080 3081 /* -------------------------------------------------------------------*/ 3082 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3083 MatGetRow_SeqAIJ, 3084 MatRestoreRow_SeqAIJ, 3085 MatMult_SeqAIJ, 3086 /* 4*/ MatMultAdd_SeqAIJ, 3087 MatMultTranspose_SeqAIJ, 3088 MatMultTransposeAdd_SeqAIJ, 3089 0, 3090 0, 3091 0, 3092 /* 10*/ 0, 3093 MatLUFactor_SeqAIJ, 3094 0, 3095 MatSOR_SeqAIJ, 3096 MatTranspose_SeqAIJ, 3097 /*1 5*/ MatGetInfo_SeqAIJ, 3098 MatEqual_SeqAIJ, 3099 MatGetDiagonal_SeqAIJ, 3100 MatDiagonalScale_SeqAIJ, 3101 MatNorm_SeqAIJ, 3102 /* 20*/ 0, 3103 MatAssemblyEnd_SeqAIJ, 3104 MatSetOption_SeqAIJ, 3105 MatZeroEntries_SeqAIJ, 3106 /* 24*/ MatZeroRows_SeqAIJ, 3107 0, 3108 0, 3109 0, 3110 0, 3111 /* 29*/ MatSetUp_SeqAIJ, 3112 0, 3113 0, 3114 0, 3115 0, 3116 /* 34*/ MatDuplicate_SeqAIJ, 3117 0, 3118 0, 3119 MatILUFactor_SeqAIJ, 3120 0, 3121 /* 39*/ MatAXPY_SeqAIJ, 3122 MatCreateSubMatrices_SeqAIJ, 3123 MatIncreaseOverlap_SeqAIJ, 3124 MatGetValues_SeqAIJ, 3125 MatCopy_SeqAIJ, 3126 /* 44*/ MatGetRowMax_SeqAIJ, 3127 MatScale_SeqAIJ, 3128 MatShift_SeqAIJ, 3129 MatDiagonalSet_SeqAIJ, 3130 MatZeroRowsColumns_SeqAIJ, 3131 /* 49*/ MatSetRandom_SeqAIJ, 3132 MatGetRowIJ_SeqAIJ, 3133 MatRestoreRowIJ_SeqAIJ, 3134 MatGetColumnIJ_SeqAIJ, 3135 MatRestoreColumnIJ_SeqAIJ, 3136 /* 54*/ MatFDColoringCreate_SeqXAIJ, 3137 0, 3138 0, 3139 MatPermute_SeqAIJ, 3140 0, 3141 /* 59*/ 0, 3142 MatDestroy_SeqAIJ, 3143 MatView_SeqAIJ, 3144 0, 3145 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3146 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3147 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3148 0, 3149 0, 3150 0, 3151 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3152 MatGetRowMinAbs_SeqAIJ, 3153 0, 3154 0, 3155 0, 3156 /* 74*/ 0, 3157 MatFDColoringApply_AIJ, 3158 0, 3159 0, 3160 0, 3161 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3162 0, 3163 0, 3164 0, 3165 MatLoad_SeqAIJ, 3166 /* 84*/ MatIsSymmetric_SeqAIJ, 3167 MatIsHermitian_SeqAIJ, 3168 0, 3169 0, 3170 0, 3171 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3172 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3173 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3174 MatPtAP_SeqAIJ_SeqAIJ, 3175 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3176 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3177 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3178 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3179 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3180 0, 3181 /* 99*/ 0, 3182 0, 3183 0, 3184 MatConjugate_SeqAIJ, 3185 0, 3186 /*104*/ MatSetValuesRow_SeqAIJ, 3187 MatRealPart_SeqAIJ, 3188 MatImaginaryPart_SeqAIJ, 3189 0, 3190 0, 3191 /*109*/ MatMatSolve_SeqAIJ, 3192 0, 3193 MatGetRowMin_SeqAIJ, 3194 0, 3195 MatMissingDiagonal_SeqAIJ, 3196 /*114*/ 0, 3197 0, 3198 0, 3199 0, 3200 0, 3201 /*119*/ 0, 3202 0, 3203 0, 3204 0, 3205 MatGetMultiProcBlock_SeqAIJ, 3206 /*124*/ MatFindNonzeroRows_SeqAIJ, 3207 MatGetColumnNorms_SeqAIJ, 3208 MatInvertBlockDiagonal_SeqAIJ, 3209 0, 3210 0, 3211 /*129*/ 0, 3212 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3213 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3214 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3215 MatTransposeColoringCreate_SeqAIJ, 3216 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3217 MatTransColoringApplyDenToSp_SeqAIJ, 3218 MatRARt_SeqAIJ_SeqAIJ, 3219 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3220 MatRARtNumeric_SeqAIJ_SeqAIJ, 3221 /*139*/0, 3222 0, 3223 0, 3224 MatFDColoringSetUp_SeqXAIJ, 3225 MatFindOffBlockDiagonalEntries_SeqAIJ, 3226 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ 3227 }; 3228 3229 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3230 { 3231 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3232 PetscInt i,nz,n; 3233 3234 PetscFunctionBegin; 3235 nz = aij->maxnz; 3236 n = mat->rmap->n; 3237 for (i=0; i<nz; i++) { 3238 aij->j[i] = indices[i]; 3239 } 3240 aij->nz = nz; 3241 for (i=0; i<n; i++) { 3242 aij->ilen[i] = aij->imax[i]; 3243 } 3244 PetscFunctionReturn(0); 3245 } 3246 3247 /*@ 3248 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3249 in the matrix. 3250 3251 Input Parameters: 3252 + mat - the SeqAIJ matrix 3253 - indices - the column indices 3254 3255 Level: advanced 3256 3257 Notes: 3258 This can be called if you have precomputed the nonzero structure of the 3259 matrix and want to provide it to the matrix object to improve the performance 3260 of the MatSetValues() operation. 3261 3262 You MUST have set the correct numbers of nonzeros per row in the call to 3263 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3264 3265 MUST be called before any calls to MatSetValues(); 3266 3267 The indices should start with zero, not one. 3268 3269 @*/ 3270 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3271 { 3272 PetscErrorCode ierr; 3273 3274 PetscFunctionBegin; 3275 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3276 PetscValidPointer(indices,2); 3277 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3278 PetscFunctionReturn(0); 3279 } 3280 3281 /* ----------------------------------------------------------------------------------------*/ 3282 3283 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3284 { 3285 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3286 PetscErrorCode ierr; 3287 size_t nz = aij->i[mat->rmap->n]; 3288 3289 PetscFunctionBegin; 3290 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3291 3292 /* allocate space for values if not already there */ 3293 if (!aij->saved_values) { 3294 ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); 3295 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3296 } 3297 3298 /* copy values over */ 3299 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3300 PetscFunctionReturn(0); 3301 } 3302 3303 /*@ 3304 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3305 example, reuse of the linear part of a Jacobian, while recomputing the 3306 nonlinear portion. 3307 3308 Collect on Mat 3309 3310 Input Parameters: 3311 . mat - the matrix (currently only AIJ matrices support this option) 3312 3313 Level: advanced 3314 3315 Common Usage, with SNESSolve(): 3316 $ Create Jacobian matrix 3317 $ Set linear terms into matrix 3318 $ Apply boundary conditions to matrix, at this time matrix must have 3319 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3320 $ boundary conditions again will not change the nonzero structure 3321 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3322 $ ierr = MatStoreValues(mat); 3323 $ Call SNESSetJacobian() with matrix 3324 $ In your Jacobian routine 3325 $ ierr = MatRetrieveValues(mat); 3326 $ Set nonlinear terms in matrix 3327 3328 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3329 $ // build linear portion of Jacobian 3330 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3331 $ ierr = MatStoreValues(mat); 3332 $ loop over nonlinear iterations 3333 $ ierr = MatRetrieveValues(mat); 3334 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3335 $ // call MatAssemblyBegin/End() on matrix 3336 $ Solve linear system with Jacobian 3337 $ endloop 3338 3339 Notes: 3340 Matrix must already be assemblied before calling this routine 3341 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3342 calling this routine. 3343 3344 When this is called multiple times it overwrites the previous set of stored values 3345 and does not allocated additional space. 3346 3347 .seealso: MatRetrieveValues() 3348 3349 @*/ 3350 PetscErrorCode MatStoreValues(Mat mat) 3351 { 3352 PetscErrorCode ierr; 3353 3354 PetscFunctionBegin; 3355 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3356 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3357 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3358 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3359 PetscFunctionReturn(0); 3360 } 3361 3362 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3363 { 3364 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3365 PetscErrorCode ierr; 3366 PetscInt nz = aij->i[mat->rmap->n]; 3367 3368 PetscFunctionBegin; 3369 if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3370 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3371 /* copy values over */ 3372 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3373 PetscFunctionReturn(0); 3374 } 3375 3376 /*@ 3377 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3378 example, reuse of the linear part of a Jacobian, while recomputing the 3379 nonlinear portion. 3380 3381 Collect on Mat 3382 3383 Input Parameters: 3384 . mat - the matrix (currently only AIJ matrices support this option) 3385 3386 Level: advanced 3387 3388 .seealso: MatStoreValues() 3389 3390 @*/ 3391 PetscErrorCode MatRetrieveValues(Mat mat) 3392 { 3393 PetscErrorCode ierr; 3394 3395 PetscFunctionBegin; 3396 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3397 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3398 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3399 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3400 PetscFunctionReturn(0); 3401 } 3402 3403 3404 /* --------------------------------------------------------------------------------*/ 3405 /*@C 3406 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3407 (the default parallel PETSc format). For good matrix assembly performance 3408 the user should preallocate the matrix storage by setting the parameter nz 3409 (or the array nnz). By setting these parameters accurately, performance 3410 during matrix assembly can be increased by more than a factor of 50. 3411 3412 Collective on MPI_Comm 3413 3414 Input Parameters: 3415 + comm - MPI communicator, set to PETSC_COMM_SELF 3416 . m - number of rows 3417 . n - number of columns 3418 . nz - number of nonzeros per row (same for all rows) 3419 - nnz - array containing the number of nonzeros in the various rows 3420 (possibly different for each row) or NULL 3421 3422 Output Parameter: 3423 . A - the matrix 3424 3425 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3426 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3427 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3428 3429 Notes: 3430 If nnz is given then nz is ignored 3431 3432 The AIJ format (also called the Yale sparse matrix format or 3433 compressed row storage), is fully compatible with standard Fortran 77 3434 storage. That is, the stored row and column indices can begin at 3435 either one (as in Fortran) or zero. See the users' manual for details. 3436 3437 Specify the preallocated storage with either nz or nnz (not both). 3438 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3439 allocation. For large problems you MUST preallocate memory or you 3440 will get TERRIBLE performance, see the users' manual chapter on matrices. 3441 3442 By default, this format uses inodes (identical nodes) when possible, to 3443 improve numerical efficiency of matrix-vector products and solves. We 3444 search for consecutive rows with the same nonzero structure, thereby 3445 reusing matrix information to achieve increased efficiency. 3446 3447 Options Database Keys: 3448 + -mat_no_inode - Do not use inodes 3449 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3450 3451 Level: intermediate 3452 3453 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3454 3455 @*/ 3456 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3457 { 3458 PetscErrorCode ierr; 3459 3460 PetscFunctionBegin; 3461 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3462 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3463 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3464 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3465 PetscFunctionReturn(0); 3466 } 3467 3468 /*@C 3469 MatSeqAIJSetPreallocation - For good matrix assembly performance 3470 the user should preallocate the matrix storage by setting the parameter nz 3471 (or the array nnz). By setting these parameters accurately, performance 3472 during matrix assembly can be increased by more than a factor of 50. 3473 3474 Collective on MPI_Comm 3475 3476 Input Parameters: 3477 + B - The matrix 3478 . nz - number of nonzeros per row (same for all rows) 3479 - nnz - array containing the number of nonzeros in the various rows 3480 (possibly different for each row) or NULL 3481 3482 Notes: 3483 If nnz is given then nz is ignored 3484 3485 The AIJ format (also called the Yale sparse matrix format or 3486 compressed row storage), is fully compatible with standard Fortran 77 3487 storage. That is, the stored row and column indices can begin at 3488 either one (as in Fortran) or zero. See the users' manual for details. 3489 3490 Specify the preallocated storage with either nz or nnz (not both). 3491 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3492 allocation. For large problems you MUST preallocate memory or you 3493 will get TERRIBLE performance, see the users' manual chapter on matrices. 3494 3495 You can call MatGetInfo() to get information on how effective the preallocation was; 3496 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3497 You can also run with the option -info and look for messages with the string 3498 malloc in them to see if additional memory allocation was needed. 3499 3500 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3501 entries or columns indices 3502 3503 By default, this format uses inodes (identical nodes) when possible, to 3504 improve numerical efficiency of matrix-vector products and solves. We 3505 search for consecutive rows with the same nonzero structure, thereby 3506 reusing matrix information to achieve increased efficiency. 3507 3508 Options Database Keys: 3509 + -mat_no_inode - Do not use inodes 3510 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3511 - -mat_aij_oneindex - Internally use indexing starting at 1 3512 rather than 0. Note that when calling MatSetValues(), 3513 the user still MUST index entries starting at 0! 3514 3515 Level: intermediate 3516 3517 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3518 3519 @*/ 3520 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3521 { 3522 PetscErrorCode ierr; 3523 3524 PetscFunctionBegin; 3525 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3526 PetscValidType(B,1); 3527 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3528 PetscFunctionReturn(0); 3529 } 3530 3531 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3532 { 3533 Mat_SeqAIJ *b; 3534 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3535 PetscErrorCode ierr; 3536 PetscInt i; 3537 3538 PetscFunctionBegin; 3539 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3540 if (nz == MAT_SKIP_ALLOCATION) { 3541 skipallocation = PETSC_TRUE; 3542 nz = 0; 3543 } 3544 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3545 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3546 3547 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3548 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); 3549 if (nnz) { 3550 for (i=0; i<B->rmap->n; i++) { 3551 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]); 3552 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); 3553 } 3554 } 3555 3556 B->preallocated = PETSC_TRUE; 3557 3558 b = (Mat_SeqAIJ*)B->data; 3559 3560 if (!skipallocation) { 3561 if (!b->imax) { 3562 ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); 3563 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3564 } 3565 if (!nnz) { 3566 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3567 else if (nz < 0) nz = 1; 3568 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3569 nz = nz*B->rmap->n; 3570 } else { 3571 nz = 0; 3572 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3573 } 3574 /* b->ilen will count nonzeros in each row so far. */ 3575 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3576 3577 /* allocate the matrix space */ 3578 /* FIXME: should B's old memory be unlogged? */ 3579 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3580 if (B->structure_only) { 3581 ierr = PetscMalloc1(nz,&b->j);CHKERRQ(ierr); 3582 ierr = PetscMalloc1(B->rmap->n+1,&b->i);CHKERRQ(ierr); 3583 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));CHKERRQ(ierr); 3584 } else { 3585 ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); 3586 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3587 } 3588 b->i[0] = 0; 3589 for (i=1; i<B->rmap->n+1; i++) { 3590 b->i[i] = b->i[i-1] + b->imax[i-1]; 3591 } 3592 if (B->structure_only) { 3593 b->singlemalloc = PETSC_FALSE; 3594 b->free_a = PETSC_FALSE; 3595 } else { 3596 b->singlemalloc = PETSC_TRUE; 3597 b->free_a = PETSC_TRUE; 3598 } 3599 b->free_ij = PETSC_TRUE; 3600 } else { 3601 b->free_a = PETSC_FALSE; 3602 b->free_ij = PETSC_FALSE; 3603 } 3604 3605 b->nz = 0; 3606 b->maxnz = nz; 3607 B->info.nz_unneeded = (double)b->maxnz; 3608 if (realalloc) { 3609 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3610 } 3611 B->was_assembled = PETSC_FALSE; 3612 B->assembled = PETSC_FALSE; 3613 PetscFunctionReturn(0); 3614 } 3615 3616 /*@ 3617 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3618 3619 Input Parameters: 3620 + B - the matrix 3621 . i - the indices into j for the start of each row (starts with zero) 3622 . j - the column indices for each row (starts with zero) these must be sorted for each row 3623 - v - optional values in the matrix 3624 3625 Level: developer 3626 3627 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3628 3629 .keywords: matrix, aij, compressed row, sparse, sequential 3630 3631 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3632 @*/ 3633 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3634 { 3635 PetscErrorCode ierr; 3636 3637 PetscFunctionBegin; 3638 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3639 PetscValidType(B,1); 3640 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3641 PetscFunctionReturn(0); 3642 } 3643 3644 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3645 { 3646 PetscInt i; 3647 PetscInt m,n; 3648 PetscInt nz; 3649 PetscInt *nnz, nz_max = 0; 3650 PetscScalar *values; 3651 PetscErrorCode ierr; 3652 3653 PetscFunctionBegin; 3654 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3655 3656 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3657 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3658 3659 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3660 ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); 3661 for (i = 0; i < m; i++) { 3662 nz = Ii[i+1]- Ii[i]; 3663 nz_max = PetscMax(nz_max, nz); 3664 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3665 nnz[i] = nz; 3666 } 3667 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3668 ierr = PetscFree(nnz);CHKERRQ(ierr); 3669 3670 if (v) { 3671 values = (PetscScalar*) v; 3672 } else { 3673 ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); 3674 } 3675 3676 for (i = 0; i < m; i++) { 3677 nz = Ii[i+1] - Ii[i]; 3678 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3679 } 3680 3681 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3682 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3683 3684 if (!v) { 3685 ierr = PetscFree(values);CHKERRQ(ierr); 3686 } 3687 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3688 PetscFunctionReturn(0); 3689 } 3690 3691 #include <../src/mat/impls/dense/seq/dense.h> 3692 #include <petsc/private/kernels/petscaxpy.h> 3693 3694 /* 3695 Computes (B'*A')' since computing B*A directly is untenable 3696 3697 n p p 3698 ( ) ( ) ( ) 3699 m ( A ) * n ( B ) = m ( C ) 3700 ( ) ( ) ( ) 3701 3702 */ 3703 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3704 { 3705 PetscErrorCode ierr; 3706 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3707 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3708 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3709 PetscInt i,n,m,q,p; 3710 const PetscInt *ii,*idx; 3711 const PetscScalar *b,*a,*a_q; 3712 PetscScalar *c,*c_q; 3713 3714 PetscFunctionBegin; 3715 m = A->rmap->n; 3716 n = A->cmap->n; 3717 p = B->cmap->n; 3718 a = sub_a->v; 3719 b = sub_b->a; 3720 c = sub_c->v; 3721 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3722 3723 ii = sub_b->i; 3724 idx = sub_b->j; 3725 for (i=0; i<n; i++) { 3726 q = ii[i+1] - ii[i]; 3727 while (q-->0) { 3728 c_q = c + m*(*idx); 3729 a_q = a + m*i; 3730 PetscKernelAXPY(c_q,*b,a_q,m); 3731 idx++; 3732 b++; 3733 } 3734 } 3735 PetscFunctionReturn(0); 3736 } 3737 3738 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3739 { 3740 PetscErrorCode ierr; 3741 PetscInt m=A->rmap->n,n=B->cmap->n; 3742 Mat Cmat; 3743 3744 PetscFunctionBegin; 3745 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); 3746 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 3747 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3748 ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); 3749 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3750 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 3751 3752 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 3753 3754 *C = Cmat; 3755 PetscFunctionReturn(0); 3756 } 3757 3758 /* ----------------------------------------------------------------*/ 3759 PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3760 { 3761 PetscErrorCode ierr; 3762 3763 PetscFunctionBegin; 3764 if (scall == MAT_INITIAL_MATRIX) { 3765 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3766 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3767 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 3768 } 3769 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3770 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3771 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 3772 PetscFunctionReturn(0); 3773 } 3774 3775 3776 /*MC 3777 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3778 based on compressed sparse row format. 3779 3780 Options Database Keys: 3781 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3782 3783 Level: beginner 3784 3785 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3786 M*/ 3787 3788 /*MC 3789 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 3790 3791 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 3792 and MATMPIAIJ otherwise. As a result, for single process communicators, 3793 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 3794 for communicators controlling multiple processes. It is recommended that you call both of 3795 the above preallocation routines for simplicity. 3796 3797 Options Database Keys: 3798 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 3799 3800 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 3801 enough exist. 3802 3803 Level: beginner 3804 3805 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 3806 M*/ 3807 3808 /*MC 3809 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 3810 3811 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 3812 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 3813 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 3814 for communicators controlling multiple processes. It is recommended that you call both of 3815 the above preallocation routines for simplicity. 3816 3817 Options Database Keys: 3818 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 3819 3820 Level: beginner 3821 3822 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 3823 M*/ 3824 3825 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3826 #if defined(PETSC_HAVE_ELEMENTAL) 3827 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); 3828 #endif 3829 #if defined(PETSC_HAVE_HYPRE) 3830 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat A,MatType,MatReuse,Mat*); 3831 PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*); 3832 #endif 3833 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); 3834 3835 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3836 PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 3837 PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 3838 #endif 3839 3840 3841 /*@C 3842 MatSeqAIJGetArray - gives access to the array where the data for a MATSEQAIJ matrix is stored 3843 3844 Not Collective 3845 3846 Input Parameter: 3847 . mat - a MATSEQAIJ matrix 3848 3849 Output Parameter: 3850 . array - pointer to the data 3851 3852 Level: intermediate 3853 3854 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3855 @*/ 3856 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 3857 { 3858 PetscErrorCode ierr; 3859 3860 PetscFunctionBegin; 3861 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3862 PetscFunctionReturn(0); 3863 } 3864 3865 /*@C 3866 MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row 3867 3868 Not Collective 3869 3870 Input Parameter: 3871 . mat - a MATSEQAIJ matrix 3872 3873 Output Parameter: 3874 . nz - the maximum number of nonzeros in any row 3875 3876 Level: intermediate 3877 3878 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 3879 @*/ 3880 PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) 3881 { 3882 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 3883 3884 PetscFunctionBegin; 3885 *nz = aij->rmax; 3886 PetscFunctionReturn(0); 3887 } 3888 3889 /*@C 3890 MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() 3891 3892 Not Collective 3893 3894 Input Parameters: 3895 . mat - a MATSEQAIJ matrix 3896 . array - pointer to the data 3897 3898 Level: intermediate 3899 3900 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 3901 @*/ 3902 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 3903 { 3904 PetscErrorCode ierr; 3905 3906 PetscFunctionBegin; 3907 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 3908 PetscFunctionReturn(0); 3909 } 3910 3911 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 3912 { 3913 Mat_SeqAIJ *b; 3914 PetscErrorCode ierr; 3915 PetscMPIInt size; 3916 3917 PetscFunctionBegin; 3918 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 3919 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3920 3921 ierr = PetscNewLog(B,&b);CHKERRQ(ierr); 3922 3923 B->data = (void*)b; 3924 3925 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3926 3927 b->row = 0; 3928 b->col = 0; 3929 b->icol = 0; 3930 b->reallocs = 0; 3931 b->ignorezeroentries = PETSC_FALSE; 3932 b->roworiented = PETSC_TRUE; 3933 b->nonew = 0; 3934 b->diag = 0; 3935 b->solve_work = 0; 3936 B->spptr = 0; 3937 b->saved_values = 0; 3938 b->idiag = 0; 3939 b->mdiag = 0; 3940 b->ssor_work = 0; 3941 b->omega = 1.0; 3942 b->fshift = 0.0; 3943 b->idiagvalid = PETSC_FALSE; 3944 b->ibdiagvalid = PETSC_FALSE; 3945 b->keepnonzeropattern = PETSC_FALSE; 3946 3947 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3948 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 3949 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 3950 3951 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3952 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 3953 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 3954 #endif 3955 3956 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 3957 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 3958 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 3959 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 3960 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 3961 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 3962 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 3963 #if defined(PETSC_HAVE_ELEMENTAL) 3964 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); 3965 #endif 3966 #if defined(PETSC_HAVE_HYPRE) 3967 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_hypre_C",MatConvert_AIJ_HYPRE);CHKERRQ(ierr); 3968 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMatMult_transpose_seqaij_seqaij_C",MatMatMatMult_Transpose_AIJ_AIJ);CHKERRQ(ierr); 3969 #endif 3970 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); 3971 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3972 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3973 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 3974 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 3975 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 3976 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 3977 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 3978 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 3979 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 3980 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3981 PetscFunctionReturn(0); 3982 } 3983 3984 /* 3985 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 3986 */ 3987 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 3988 { 3989 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 3990 PetscErrorCode ierr; 3991 PetscInt i,m = A->rmap->n; 3992 3993 PetscFunctionBegin; 3994 c = (Mat_SeqAIJ*)C->data; 3995 3996 C->factortype = A->factortype; 3997 c->row = 0; 3998 c->col = 0; 3999 c->icol = 0; 4000 c->reallocs = 0; 4001 4002 C->assembled = PETSC_TRUE; 4003 4004 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4005 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4006 4007 ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); 4008 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4009 for (i=0; i<m; i++) { 4010 c->imax[i] = a->imax[i]; 4011 c->ilen[i] = a->ilen[i]; 4012 } 4013 4014 /* allocate the matrix space */ 4015 if (mallocmatspace) { 4016 ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); 4017 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4018 4019 c->singlemalloc = PETSC_TRUE; 4020 4021 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4022 if (m > 0) { 4023 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4024 if (cpvalues == MAT_COPY_VALUES) { 4025 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4026 } else { 4027 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4028 } 4029 } 4030 } 4031 4032 c->ignorezeroentries = a->ignorezeroentries; 4033 c->roworiented = a->roworiented; 4034 c->nonew = a->nonew; 4035 if (a->diag) { 4036 ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); 4037 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4038 for (i=0; i<m; i++) { 4039 c->diag[i] = a->diag[i]; 4040 } 4041 } else c->diag = 0; 4042 4043 c->solve_work = 0; 4044 c->saved_values = 0; 4045 c->idiag = 0; 4046 c->ssor_work = 0; 4047 c->keepnonzeropattern = a->keepnonzeropattern; 4048 c->free_a = PETSC_TRUE; 4049 c->free_ij = PETSC_TRUE; 4050 4051 c->rmax = a->rmax; 4052 c->nz = a->nz; 4053 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4054 C->preallocated = PETSC_TRUE; 4055 4056 c->compressedrow.use = a->compressedrow.use; 4057 c->compressedrow.nrows = a->compressedrow.nrows; 4058 if (a->compressedrow.use) { 4059 i = a->compressedrow.nrows; 4060 ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); 4061 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4062 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4063 } else { 4064 c->compressedrow.use = PETSC_FALSE; 4065 c->compressedrow.i = NULL; 4066 c->compressedrow.rindex = NULL; 4067 } 4068 c->nonzerorowcnt = a->nonzerorowcnt; 4069 C->nonzerostate = A->nonzerostate; 4070 4071 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4072 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4073 PetscFunctionReturn(0); 4074 } 4075 4076 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4077 { 4078 PetscErrorCode ierr; 4079 4080 PetscFunctionBegin; 4081 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4082 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4083 if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { 4084 ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); 4085 } 4086 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4087 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4088 PetscFunctionReturn(0); 4089 } 4090 4091 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4092 { 4093 Mat_SeqAIJ *a; 4094 PetscErrorCode ierr; 4095 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4096 int fd; 4097 PetscMPIInt size; 4098 MPI_Comm comm; 4099 PetscInt bs = newMat->rmap->bs; 4100 4101 PetscFunctionBegin; 4102 /* force binary viewer to load .info file if it has not yet done so */ 4103 ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); 4104 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4105 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4106 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4107 4108 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4109 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4110 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4111 if (bs < 0) bs = 1; 4112 ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); 4113 4114 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4115 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4116 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4117 M = header[1]; N = header[2]; nz = header[3]; 4118 4119 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4120 4121 /* read in row lengths */ 4122 ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); 4123 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4124 4125 /* check if sum of rowlengths is same as nz */ 4126 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4127 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); 4128 4129 /* set global size if not set already*/ 4130 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4131 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4132 } else { 4133 /* if sizes and type are already set, check if the matrix global sizes are correct */ 4134 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4135 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4136 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4137 } 4138 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); 4139 } 4140 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4141 a = (Mat_SeqAIJ*)newMat->data; 4142 4143 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4144 4145 /* read in nonzero values */ 4146 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4147 4148 /* set matrix "i" values */ 4149 a->i[0] = 0; 4150 for (i=1; i<= M; i++) { 4151 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4152 a->ilen[i-1] = rowlengths[i-1]; 4153 } 4154 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4155 4156 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4157 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4158 PetscFunctionReturn(0); 4159 } 4160 4161 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4162 { 4163 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4164 PetscErrorCode ierr; 4165 #if defined(PETSC_USE_COMPLEX) 4166 PetscInt k; 4167 #endif 4168 4169 PetscFunctionBegin; 4170 /* If the matrix dimensions are not equal,or no of nonzeros */ 4171 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4172 *flg = PETSC_FALSE; 4173 PetscFunctionReturn(0); 4174 } 4175 4176 /* if the a->i are the same */ 4177 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4178 if (!*flg) PetscFunctionReturn(0); 4179 4180 /* if a->j are the same */ 4181 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4182 if (!*flg) PetscFunctionReturn(0); 4183 4184 /* if a->a are the same */ 4185 #if defined(PETSC_USE_COMPLEX) 4186 for (k=0; k<a->nz; k++) { 4187 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4188 *flg = PETSC_FALSE; 4189 PetscFunctionReturn(0); 4190 } 4191 } 4192 #else 4193 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4194 #endif 4195 PetscFunctionReturn(0); 4196 } 4197 4198 /*@ 4199 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4200 provided by the user. 4201 4202 Collective on MPI_Comm 4203 4204 Input Parameters: 4205 + comm - must be an MPI communicator of size 1 4206 . m - number of rows 4207 . n - number of columns 4208 . i - row indices 4209 . j - column indices 4210 - a - matrix values 4211 4212 Output Parameter: 4213 . mat - the matrix 4214 4215 Level: intermediate 4216 4217 Notes: 4218 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4219 once the matrix is destroyed and not before 4220 4221 You cannot set new nonzero locations into this matrix, that will generate an error. 4222 4223 The i and j indices are 0 based 4224 4225 The format which is used for the sparse matrix input, is equivalent to a 4226 row-major ordering.. i.e for the following matrix, the input data expected is 4227 as shown 4228 4229 $ 1 0 0 4230 $ 2 0 3 4231 $ 4 5 6 4232 $ 4233 $ i = {0,1,3,6} [size = nrow+1 = 3+1] 4234 $ j = {0,0,2,0,1,2} [size = 6]; values must be sorted for each row 4235 $ v = {1,2,3,4,5,6} [size = 6] 4236 4237 4238 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4239 4240 @*/ 4241 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat) 4242 { 4243 PetscErrorCode ierr; 4244 PetscInt ii; 4245 Mat_SeqAIJ *aij; 4246 #if defined(PETSC_USE_DEBUG) 4247 PetscInt jj; 4248 #endif 4249 4250 PetscFunctionBegin; 4251 if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4252 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4253 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4254 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4255 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4256 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4257 aij = (Mat_SeqAIJ*)(*mat)->data; 4258 ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); 4259 4260 aij->i = i; 4261 aij->j = j; 4262 aij->a = a; 4263 aij->singlemalloc = PETSC_FALSE; 4264 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4265 aij->free_a = PETSC_FALSE; 4266 aij->free_ij = PETSC_FALSE; 4267 4268 for (ii=0; ii<m; ii++) { 4269 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4270 #if defined(PETSC_USE_DEBUG) 4271 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]); 4272 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4273 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); 4274 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); 4275 } 4276 #endif 4277 } 4278 #if defined(PETSC_USE_DEBUG) 4279 for (ii=0; ii<aij->i[m]; ii++) { 4280 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 4281 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]); 4282 } 4283 #endif 4284 4285 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4286 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4287 PetscFunctionReturn(0); 4288 } 4289 /*@C 4290 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4291 provided by the user. 4292 4293 Collective on MPI_Comm 4294 4295 Input Parameters: 4296 + comm - must be an MPI communicator of size 1 4297 . m - number of rows 4298 . n - number of columns 4299 . i - row indices 4300 . j - column indices 4301 . a - matrix values 4302 . nz - number of nonzeros 4303 - idx - 0 or 1 based 4304 4305 Output Parameter: 4306 . mat - the matrix 4307 4308 Level: intermediate 4309 4310 Notes: 4311 The i and j indices are 0 based 4312 4313 The format which is used for the sparse matrix input, is equivalent to a 4314 row-major ordering.. i.e for the following matrix, the input data expected is 4315 as shown: 4316 4317 1 0 0 4318 2 0 3 4319 4 5 6 4320 4321 i = {0,1,1,2,2,2} 4322 j = {0,0,2,0,1,2} 4323 v = {1,2,3,4,5,6} 4324 4325 4326 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4327 4328 @*/ 4329 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat,PetscInt nz,PetscBool idx) 4330 { 4331 PetscErrorCode ierr; 4332 PetscInt ii, *nnz, one = 1,row,col; 4333 4334 4335 PetscFunctionBegin; 4336 ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); 4337 for (ii = 0; ii < nz; ii++) { 4338 nnz[i[ii] - !!idx] += 1; 4339 } 4340 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4341 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4342 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4343 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4344 for (ii = 0; ii < nz; ii++) { 4345 if (idx) { 4346 row = i[ii] - 1; 4347 col = j[ii] - 1; 4348 } else { 4349 row = i[ii]; 4350 col = j[ii]; 4351 } 4352 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4353 } 4354 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4355 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4356 ierr = PetscFree(nnz);CHKERRQ(ierr); 4357 PetscFunctionReturn(0); 4358 } 4359 4360 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4361 { 4362 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4363 PetscErrorCode ierr; 4364 4365 PetscFunctionBegin; 4366 a->idiagvalid = PETSC_FALSE; 4367 a->ibdiagvalid = PETSC_FALSE; 4368 4369 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4370 PetscFunctionReturn(0); 4371 } 4372 4373 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) 4374 { 4375 PetscErrorCode ierr; 4376 PetscMPIInt size; 4377 4378 PetscFunctionBegin; 4379 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4380 if (size == 1 && scall == MAT_REUSE_MATRIX) { 4381 ierr = MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 4382 } else { 4383 ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); 4384 } 4385 PetscFunctionReturn(0); 4386 } 4387 4388 /* 4389 Permute A into C's *local* index space using rowemb,colemb. 4390 The embedding are supposed to be injections and the above implies that the range of rowemb is a subset 4391 of [0,m), colemb is in [0,n). 4392 If pattern == DIFFERENT_NONZERO_PATTERN, C is preallocated according to A. 4393 */ 4394 PetscErrorCode MatSetSeqMat_SeqAIJ(Mat C,IS rowemb,IS colemb,MatStructure pattern,Mat B) 4395 { 4396 /* If making this function public, change the error returned in this function away from _PLIB. */ 4397 PetscErrorCode ierr; 4398 Mat_SeqAIJ *Baij; 4399 PetscBool seqaij; 4400 PetscInt m,n,*nz,i,j,count; 4401 PetscScalar v; 4402 const PetscInt *rowindices,*colindices; 4403 4404 PetscFunctionBegin; 4405 if (!B) PetscFunctionReturn(0); 4406 /* Check to make sure the target matrix (and embeddings) are compatible with C and each other. */ 4407 ierr = PetscObjectTypeCompare((PetscObject)B,MATSEQAIJ,&seqaij);CHKERRQ(ierr); 4408 if (!seqaij) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is of wrong type"); 4409 if (rowemb) { 4410 ierr = ISGetLocalSize(rowemb,&m);CHKERRQ(ierr); 4411 if (m != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Row IS of size %D is incompatible with matrix row size %D",m,B->rmap->n); 4412 } else { 4413 if (C->rmap->n != B->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is row-incompatible with the target matrix"); 4414 } 4415 if (colemb) { 4416 ierr = ISGetLocalSize(colemb,&n);CHKERRQ(ierr); 4417 if (n != B->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Diag col IS of size %D is incompatible with input matrix col size %D",n,B->cmap->n); 4418 } else { 4419 if (C->cmap->n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Input matrix is col-incompatible with the target matrix"); 4420 } 4421 4422 Baij = (Mat_SeqAIJ*)(B->data); 4423 if (pattern == DIFFERENT_NONZERO_PATTERN) { 4424 ierr = PetscMalloc1(B->rmap->n,&nz);CHKERRQ(ierr); 4425 for (i=0; i<B->rmap->n; i++) { 4426 nz[i] = Baij->i[i+1] - Baij->i[i]; 4427 } 4428 ierr = MatSeqAIJSetPreallocation(C,0,nz);CHKERRQ(ierr); 4429 ierr = PetscFree(nz);CHKERRQ(ierr); 4430 } 4431 if (pattern == SUBSET_NONZERO_PATTERN) { 4432 ierr = MatZeroEntries(C);CHKERRQ(ierr); 4433 } 4434 count = 0; 4435 rowindices = NULL; 4436 colindices = NULL; 4437 if (rowemb) { 4438 ierr = ISGetIndices(rowemb,&rowindices);CHKERRQ(ierr); 4439 } 4440 if (colemb) { 4441 ierr = ISGetIndices(colemb,&colindices);CHKERRQ(ierr); 4442 } 4443 for (i=0; i<B->rmap->n; i++) { 4444 PetscInt row; 4445 row = i; 4446 if (rowindices) row = rowindices[i]; 4447 for (j=Baij->i[i]; j<Baij->i[i+1]; j++) { 4448 PetscInt col; 4449 col = Baij->j[count]; 4450 if (colindices) col = colindices[col]; 4451 v = Baij->a[count]; 4452 ierr = MatSetValues(C,1,&row,1,&col,&v,INSERT_VALUES);CHKERRQ(ierr); 4453 ++count; 4454 } 4455 } 4456 /* FIXME: set C's nonzerostate correctly. */ 4457 /* Assembly for C is necessary. */ 4458 C->preallocated = PETSC_TRUE; 4459 C->assembled = PETSC_TRUE; 4460 C->was_assembled = PETSC_FALSE; 4461 PetscFunctionReturn(0); 4462 } 4463 4464 4465 /* 4466 Special version for direct calls from Fortran 4467 */ 4468 #include <petsc/private/fortranimpl.h> 4469 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4470 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4471 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4472 #define matsetvaluesseqaij_ matsetvaluesseqaij 4473 #endif 4474 4475 /* Change these macros so can be used in void function */ 4476 #undef CHKERRQ 4477 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4478 #undef SETERRQ2 4479 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4480 #undef SETERRQ3 4481 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4482 4483 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) 4484 { 4485 Mat A = *AA; 4486 PetscInt m = *mm, n = *nn; 4487 InsertMode is = *isis; 4488 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4489 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4490 PetscInt *imax,*ai,*ailen; 4491 PetscErrorCode ierr; 4492 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4493 MatScalar *ap,value,*aa; 4494 PetscBool ignorezeroentries = a->ignorezeroentries; 4495 PetscBool roworiented = a->roworiented; 4496 4497 PetscFunctionBegin; 4498 MatCheckPreallocated(A,1); 4499 imax = a->imax; 4500 ai = a->i; 4501 ailen = a->ilen; 4502 aj = a->j; 4503 aa = a->a; 4504 4505 for (k=0; k<m; k++) { /* loop over added rows */ 4506 row = im[k]; 4507 if (row < 0) continue; 4508 #if defined(PETSC_USE_DEBUG) 4509 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4510 #endif 4511 rp = aj + ai[row]; ap = aa + ai[row]; 4512 rmax = imax[row]; nrow = ailen[row]; 4513 low = 0; 4514 high = nrow; 4515 for (l=0; l<n; l++) { /* loop over added columns */ 4516 if (in[l] < 0) continue; 4517 #if defined(PETSC_USE_DEBUG) 4518 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4519 #endif 4520 col = in[l]; 4521 if (roworiented) value = v[l + k*n]; 4522 else value = v[k + l*m]; 4523 4524 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4525 4526 if (col <= lastcol) low = 0; 4527 else high = nrow; 4528 lastcol = col; 4529 while (high-low > 5) { 4530 t = (low+high)/2; 4531 if (rp[t] > col) high = t; 4532 else low = t; 4533 } 4534 for (i=low; i<high; i++) { 4535 if (rp[i] > col) break; 4536 if (rp[i] == col) { 4537 if (is == ADD_VALUES) ap[i] += value; 4538 else ap[i] = value; 4539 goto noinsert; 4540 } 4541 } 4542 if (value == 0.0 && ignorezeroentries) goto noinsert; 4543 if (nonew == 1) goto noinsert; 4544 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4545 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4546 N = nrow++ - 1; a->nz++; high++; 4547 /* shift up all the later entries in this row */ 4548 for (ii=N; ii>=i; ii--) { 4549 rp[ii+1] = rp[ii]; 4550 ap[ii+1] = ap[ii]; 4551 } 4552 rp[i] = col; 4553 ap[i] = value; 4554 A->nonzerostate++; 4555 noinsert:; 4556 low = i + 1; 4557 } 4558 ailen[row] = nrow; 4559 } 4560 PetscFunctionReturnVoid(); 4561 } 4562 4563