1 2 /* 3 Defines the basic matrix operations for the AIJ (compressed row) 4 matrix storage format. 5 */ 6 7 8 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petscbt.h> 11 #include <petsc-private/kernels/blocktranspose.h> 12 #if defined(PETSC_THREADCOMM_ACTIVE) 13 #include <petscthreadcomm.h> 14 #endif 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetColumnNorms_SeqAIJ" 18 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 19 { 20 PetscErrorCode ierr; 21 PetscInt i,m,n; 22 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 23 24 PetscFunctionBegin; 25 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 26 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 27 if (type == NORM_2) { 28 for (i=0; i<aij->i[m]; i++) { 29 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 30 } 31 } else if (type == NORM_1) { 32 for (i=0; i<aij->i[m]; i++) { 33 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 34 } 35 } else if (type == NORM_INFINITY) { 36 for (i=0; i<aij->i[m]; i++) { 37 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 38 } 39 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 40 41 if (type == NORM_2) { 42 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 43 } 44 PetscFunctionReturn(0); 45 } 46 47 #undef __FUNCT__ 48 #define __FUNCT__ "MatFindZeroDiagonals_SeqAIJ_Private" 49 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 50 { 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 52 const MatScalar *aa = a->a; 53 PetscInt i,m=A->rmap->n,cnt = 0; 54 const PetscInt *jj = a->j,*diag; 55 PetscInt *rows; 56 PetscErrorCode ierr; 57 58 PetscFunctionBegin; 59 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 60 diag = a->diag; 61 for (i=0; i<m; i++) { 62 if ((jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 63 cnt++; 64 } 65 } 66 ierr = PetscMalloc(cnt*sizeof(PetscInt),&rows);CHKERRQ(ierr); 67 cnt = 0; 68 for (i=0; i<m; i++) { 69 if ((jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 70 rows[cnt++] = i; 71 } 72 } 73 *nrows = cnt; 74 *zrows = rows; 75 PetscFunctionReturn(0); 76 } 77 78 #undef __FUNCT__ 79 #define __FUNCT__ "MatFindZeroDiagonals_SeqAIJ" 80 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 81 { 82 PetscInt nrows,*rows; 83 PetscErrorCode ierr; 84 85 PetscFunctionBegin; 86 *zrows = NULL; 87 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 88 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 89 PetscFunctionReturn(0); 90 } 91 92 #undef __FUNCT__ 93 #define __FUNCT__ "MatFindNonzeroRows_SeqAIJ" 94 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 95 { 96 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 97 const MatScalar *aa; 98 PetscInt m=A->rmap->n,cnt = 0; 99 const PetscInt *ii; 100 PetscInt n,i,j,*rows; 101 PetscErrorCode ierr; 102 103 PetscFunctionBegin; 104 *keptrows = 0; 105 ii = a->i; 106 for (i=0; i<m; i++) { 107 n = ii[i+1] - ii[i]; 108 if (!n) { 109 cnt++; 110 goto ok1; 111 } 112 aa = a->a + ii[i]; 113 for (j=0; j<n; j++) { 114 if (aa[j] != 0.0) goto ok1; 115 } 116 cnt++; 117 ok1:; 118 } 119 if (!cnt) PetscFunctionReturn(0); 120 ierr = PetscMalloc((A->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 121 cnt = 0; 122 for (i=0; i<m; i++) { 123 n = ii[i+1] - ii[i]; 124 if (!n) continue; 125 aa = a->a + ii[i]; 126 for (j=0; j<n; j++) { 127 if (aa[j] != 0.0) { 128 rows[cnt++] = i; 129 break; 130 } 131 } 132 } 133 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 134 PetscFunctionReturn(0); 135 } 136 137 #undef __FUNCT__ 138 #define __FUNCT__ "MatDiagonalSet_SeqAIJ" 139 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 140 { 141 PetscErrorCode ierr; 142 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 143 PetscInt i,*diag, m = Y->rmap->n; 144 MatScalar *aa = aij->a; 145 PetscScalar *v; 146 PetscBool missing; 147 148 PetscFunctionBegin; 149 if (Y->assembled) { 150 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 151 if (!missing) { 152 diag = aij->diag; 153 ierr = VecGetArray(D,&v);CHKERRQ(ierr); 154 if (is == INSERT_VALUES) { 155 for (i=0; i<m; i++) { 156 aa[diag[i]] = v[i]; 157 } 158 } else { 159 for (i=0; i<m; i++) { 160 aa[diag[i]] += v[i]; 161 } 162 } 163 ierr = VecRestoreArray(D,&v);CHKERRQ(ierr); 164 PetscFunctionReturn(0); 165 } 166 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 167 } 168 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 169 PetscFunctionReturn(0); 170 } 171 172 #undef __FUNCT__ 173 #define __FUNCT__ "MatGetRowIJ_SeqAIJ" 174 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 175 { 176 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 177 PetscErrorCode ierr; 178 PetscInt i,ishift; 179 180 PetscFunctionBegin; 181 *m = A->rmap->n; 182 if (!ia) PetscFunctionReturn(0); 183 ishift = 0; 184 if (symmetric && !A->structurally_symmetric) { 185 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 186 } else if (oshift == 1) { 187 PetscInt *tia; 188 PetscInt nz = a->i[A->rmap->n]; 189 /* malloc space and add 1 to i and j indices */ 190 ierr = PetscMalloc((A->rmap->n+1)*sizeof(PetscInt),&tia);CHKERRQ(ierr); 191 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 192 *ia = tia; 193 if (ja) { 194 PetscInt *tja; 195 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&tja);CHKERRQ(ierr); 196 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 197 *ja = tja; 198 } 199 } else { 200 *ia = a->i; 201 if (ja) *ja = a->j; 202 } 203 PetscFunctionReturn(0); 204 } 205 206 #undef __FUNCT__ 207 #define __FUNCT__ "MatRestoreRowIJ_SeqAIJ" 208 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 209 { 210 PetscErrorCode ierr; 211 212 PetscFunctionBegin; 213 if (!ia) PetscFunctionReturn(0); 214 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 215 ierr = PetscFree(*ia);CHKERRQ(ierr); 216 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 217 } 218 PetscFunctionReturn(0); 219 } 220 221 #undef __FUNCT__ 222 #define __FUNCT__ "MatGetColumnIJ_SeqAIJ" 223 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 224 { 225 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 226 PetscErrorCode ierr; 227 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 228 PetscInt nz = a->i[m],row,*jj,mr,col; 229 230 PetscFunctionBegin; 231 *nn = n; 232 if (!ia) PetscFunctionReturn(0); 233 if (symmetric) { 234 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 235 } else { 236 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&collengths);CHKERRQ(ierr); 237 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 238 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&cia);CHKERRQ(ierr); 239 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cja);CHKERRQ(ierr); 240 jj = a->j; 241 for (i=0; i<nz; i++) { 242 collengths[jj[i]]++; 243 } 244 cia[0] = oshift; 245 for (i=0; i<n; i++) { 246 cia[i+1] = cia[i] + collengths[i]; 247 } 248 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 249 jj = a->j; 250 for (row=0; row<m; row++) { 251 mr = a->i[row+1] - a->i[row]; 252 for (i=0; i<mr; i++) { 253 col = *jj++; 254 255 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 256 } 257 } 258 ierr = PetscFree(collengths);CHKERRQ(ierr); 259 *ia = cia; *ja = cja; 260 } 261 PetscFunctionReturn(0); 262 } 263 264 #undef __FUNCT__ 265 #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ" 266 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 267 { 268 PetscErrorCode ierr; 269 270 PetscFunctionBegin; 271 if (!ia) PetscFunctionReturn(0); 272 273 ierr = PetscFree(*ia);CHKERRQ(ierr); 274 ierr = PetscFree(*ja);CHKERRQ(ierr); 275 PetscFunctionReturn(0); 276 } 277 278 /* 279 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 280 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 281 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqAIJ() 282 */ 283 #undef __FUNCT__ 284 #define __FUNCT__ "MatGetColumnIJ_SeqAIJ_Color" 285 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 286 { 287 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 288 PetscErrorCode ierr; 289 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 290 PetscInt nz = a->i[m],row,*jj,mr,col; 291 PetscInt *cspidx; 292 293 PetscFunctionBegin; 294 *nn = n; 295 if (!ia) PetscFunctionReturn(0); 296 if (symmetric) { 297 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"MatGetColumnIJ_SeqAIJ_Color() not supported for the case symmetric"); 298 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 299 } else { 300 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&collengths);CHKERRQ(ierr); 301 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 302 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&cia);CHKERRQ(ierr); 303 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cja);CHKERRQ(ierr); 304 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cspidx);CHKERRQ(ierr); 305 jj = a->j; 306 for (i=0; i<nz; i++) { 307 collengths[jj[i]]++; 308 } 309 cia[0] = oshift; 310 for (i=0; i<n; i++) { 311 cia[i+1] = cia[i] + collengths[i]; 312 } 313 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 314 jj = a->j; 315 for (row=0; row<m; row++) { 316 mr = a->i[row+1] - a->i[row]; 317 for (i=0; i<mr; i++) { 318 col = *jj++; 319 320 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 321 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 322 } 323 } 324 ierr = PetscFree(collengths);CHKERRQ(ierr); 325 *ia = cia; *ja = cja; 326 *spidx = cspidx; 327 } 328 PetscFunctionReturn(0); 329 } 330 331 #undef __FUNCT__ 332 #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ_Color" 333 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 334 { 335 PetscErrorCode ierr; 336 337 PetscFunctionBegin; 338 if (!ia) PetscFunctionReturn(0); 339 340 ierr = PetscFree(*ia);CHKERRQ(ierr); 341 ierr = PetscFree(*ja);CHKERRQ(ierr); 342 ierr = PetscFree(*spidx);CHKERRQ(ierr); 343 PetscFunctionReturn(0); 344 } 345 346 #undef __FUNCT__ 347 #define __FUNCT__ "MatSetValuesRow_SeqAIJ" 348 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 349 { 350 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 351 PetscInt *ai = a->i; 352 PetscErrorCode ierr; 353 354 PetscFunctionBegin; 355 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 356 PetscFunctionReturn(0); 357 } 358 359 #undef __FUNCT__ 360 #define __FUNCT__ "MatSetValues_SeqAIJ" 361 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 362 { 363 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 364 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 365 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 366 PetscErrorCode ierr; 367 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 368 MatScalar *ap,value,*aa = a->a; 369 PetscBool ignorezeroentries = a->ignorezeroentries; 370 PetscBool roworiented = a->roworiented; 371 372 PetscFunctionBegin; 373 if (v) PetscValidScalarPointer(v,6); 374 for (k=0; k<m; k++) { /* loop over added rows */ 375 row = im[k]; 376 if (row < 0) continue; 377 #if defined(PETSC_USE_DEBUG) 378 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); 379 #endif 380 rp = aj + ai[row]; ap = aa + ai[row]; 381 rmax = imax[row]; nrow = ailen[row]; 382 low = 0; 383 high = nrow; 384 for (l=0; l<n; l++) { /* loop over added columns */ 385 if (in[l] < 0) continue; 386 #if defined(PETSC_USE_DEBUG) 387 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); 388 #endif 389 col = in[l]; 390 if (v) { 391 if (roworiented) { 392 value = v[l + k*n]; 393 } else { 394 value = v[k + l*m]; 395 } 396 } else { 397 value = 0.; 398 } 399 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 400 401 if (col <= lastcol) low = 0; 402 else high = nrow; 403 lastcol = col; 404 while (high-low > 5) { 405 t = (low+high)/2; 406 if (rp[t] > col) high = t; 407 else low = t; 408 } 409 for (i=low; i<high; i++) { 410 if (rp[i] > col) break; 411 if (rp[i] == col) { 412 if (is == ADD_VALUES) ap[i] += value; 413 else ap[i] = value; 414 low = i + 1; 415 goto noinsert; 416 } 417 } 418 if (value == 0.0 && ignorezeroentries) goto noinsert; 419 if (nonew == 1) goto noinsert; 420 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 421 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 422 N = nrow++ - 1; a->nz++; high++; 423 /* shift up all the later entries in this row */ 424 for (ii=N; ii>=i; ii--) { 425 rp[ii+1] = rp[ii]; 426 ap[ii+1] = ap[ii]; 427 } 428 rp[i] = col; 429 ap[i] = value; 430 low = i + 1; 431 noinsert:; 432 } 433 ailen[row] = nrow; 434 } 435 A->same_nonzero = PETSC_FALSE; 436 PetscFunctionReturn(0); 437 } 438 439 440 #undef __FUNCT__ 441 #define __FUNCT__ "MatGetValues_SeqAIJ" 442 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 443 { 444 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 445 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 446 PetscInt *ai = a->i,*ailen = a->ilen; 447 MatScalar *ap,*aa = a->a; 448 449 PetscFunctionBegin; 450 for (k=0; k<m; k++) { /* loop over rows */ 451 row = im[k]; 452 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 453 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); 454 rp = aj + ai[row]; ap = aa + ai[row]; 455 nrow = ailen[row]; 456 for (l=0; l<n; l++) { /* loop over columns */ 457 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 458 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 459 col = in[l]; 460 high = nrow; low = 0; /* assume unsorted */ 461 while (high-low > 5) { 462 t = (low+high)/2; 463 if (rp[t] > col) high = t; 464 else low = t; 465 } 466 for (i=low; i<high; i++) { 467 if (rp[i] > col) break; 468 if (rp[i] == col) { 469 *v++ = ap[i]; 470 goto finished; 471 } 472 } 473 *v++ = 0.0; 474 finished:; 475 } 476 } 477 PetscFunctionReturn(0); 478 } 479 480 481 #undef __FUNCT__ 482 #define __FUNCT__ "MatView_SeqAIJ_Binary" 483 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 484 { 485 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 486 PetscErrorCode ierr; 487 PetscInt i,*col_lens; 488 int fd; 489 FILE *file; 490 491 PetscFunctionBegin; 492 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 493 ierr = PetscMalloc((4+A->rmap->n)*sizeof(PetscInt),&col_lens);CHKERRQ(ierr); 494 495 col_lens[0] = MAT_FILE_CLASSID; 496 col_lens[1] = A->rmap->n; 497 col_lens[2] = A->cmap->n; 498 col_lens[3] = a->nz; 499 500 /* store lengths of each row and write (including header) to file */ 501 for (i=0; i<A->rmap->n; i++) { 502 col_lens[4+i] = a->i[i+1] - a->i[i]; 503 } 504 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 505 ierr = PetscFree(col_lens);CHKERRQ(ierr); 506 507 /* store column indices (zero start index) */ 508 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 509 510 /* store nonzero values */ 511 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 512 513 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 514 if (file) { 515 fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs); 516 } 517 PetscFunctionReturn(0); 518 } 519 520 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 521 522 #undef __FUNCT__ 523 #define __FUNCT__ "MatView_SeqAIJ_ASCII" 524 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 525 { 526 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 527 PetscErrorCode ierr; 528 PetscInt i,j,m = A->rmap->n,shift=0; 529 const char *name; 530 PetscViewerFormat format; 531 532 PetscFunctionBegin; 533 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 534 if (format == PETSC_VIEWER_ASCII_MATLAB) { 535 PetscInt nofinalvalue = 0; 536 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-!shift))) { 537 nofinalvalue = 1; 538 } 539 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 540 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 541 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 542 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 543 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 544 545 for (i=0; i<m; i++) { 546 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 547 #if defined(PETSC_USE_COMPLEX) 548 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e + %18.16ei \n",i+1,a->j[j]+!shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 549 #else 550 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+!shift,a->a[j]);CHKERRQ(ierr); 551 #endif 552 } 553 } 554 if (nofinalvalue) { 555 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 556 } 557 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 558 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 559 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 560 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 561 PetscFunctionReturn(0); 562 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 563 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 564 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 565 for (i=0; i<m; i++) { 566 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 567 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 568 #if defined(PETSC_USE_COMPLEX) 569 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 570 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 571 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 572 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 573 } else if (PetscRealPart(a->a[j]) != 0.0) { 574 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 575 } 576 #else 577 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr);} 578 #endif 579 } 580 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 581 } 582 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 583 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 584 PetscInt nzd=0,fshift=1,*sptr; 585 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 586 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 587 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&sptr);CHKERRQ(ierr); 588 for (i=0; i<m; i++) { 589 sptr[i] = nzd+1; 590 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 591 if (a->j[j] >= i) { 592 #if defined(PETSC_USE_COMPLEX) 593 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 594 #else 595 if (a->a[j] != 0.0) nzd++; 596 #endif 597 } 598 } 599 } 600 sptr[m] = nzd+1; 601 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 602 for (i=0; i<m+1; i+=6) { 603 if (i+4<m) { 604 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); 605 } else if (i+3<m) { 606 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); 607 } else if (i+2<m) { 608 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 609 } else if (i+1<m) { 610 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 611 } else if (i<m) { 612 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 613 } else { 614 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 615 } 616 } 617 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 618 ierr = PetscFree(sptr);CHKERRQ(ierr); 619 for (i=0; i<m; i++) { 620 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 621 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 622 } 623 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 624 } 625 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 626 for (i=0; i<m; i++) { 627 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 628 if (a->j[j] >= i) { 629 #if defined(PETSC_USE_COMPLEX) 630 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 631 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 632 } 633 #else 634 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",a->a[j]);CHKERRQ(ierr);} 635 #endif 636 } 637 } 638 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 639 } 640 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 641 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 642 PetscInt cnt = 0,jcnt; 643 PetscScalar value; 644 645 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 646 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 647 for (i=0; i<m; i++) { 648 jcnt = 0; 649 for (j=0; j<A->cmap->n; j++) { 650 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 651 value = a->a[cnt++]; 652 jcnt++; 653 } else { 654 value = 0.0; 655 } 656 #if defined(PETSC_USE_COMPLEX) 657 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",PetscRealPart(value),PetscImaginaryPart(value));CHKERRQ(ierr); 658 #else 659 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",value);CHKERRQ(ierr); 660 #endif 661 } 662 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 663 } 664 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 665 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 666 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 667 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 668 #if defined(PETSC_USE_COMPLEX) 669 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix complex general\n");CHKERRQ(ierr); 670 #else 671 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix real general\n");CHKERRQ(ierr); 672 #endif 673 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 674 for (i=0; i<m; i++) { 675 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 676 #if defined(PETSC_USE_COMPLEX) 677 if (PetscImaginaryPart(a->a[j]) > 0.0) { 678 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g %g\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 679 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 680 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g -%g\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 681 } else { 682 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 683 } 684 #else 685 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+shift, a->j[j]+shift, (double)a->a[j]);CHKERRQ(ierr); 686 #endif 687 } 688 } 689 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 690 } else { 691 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 692 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 693 if (A->factortype) { 694 for (i=0; i<m; i++) { 695 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 696 /* L part */ 697 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 698 #if defined(PETSC_USE_COMPLEX) 699 if (PetscImaginaryPart(a->a[j]) > 0.0) { 700 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 701 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 702 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 703 } else { 704 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 705 } 706 #else 707 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr); 708 #endif 709 } 710 /* diagonal */ 711 j = a->diag[i]; 712 #if defined(PETSC_USE_COMPLEX) 713 if (PetscImaginaryPart(a->a[j]) > 0.0) { 714 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(1.0/a->a[j]),PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 715 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 716 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(1.0/a->a[j]),-PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 717 } else { 718 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 719 } 720 #else 721 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)1.0/a->a[j]);CHKERRQ(ierr); 722 #endif 723 724 /* U part */ 725 for (j=a->diag[i+1]+1+shift; j<a->diag[i]+shift; j++) { 726 #if defined(PETSC_USE_COMPLEX) 727 if (PetscImaginaryPart(a->a[j]) > 0.0) { 728 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 729 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 730 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 731 } else { 732 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 733 } 734 #else 735 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr); 736 #endif 737 } 738 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 739 } 740 } else { 741 for (i=0; i<m; i++) { 742 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 743 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 744 #if defined(PETSC_USE_COMPLEX) 745 if (PetscImaginaryPart(a->a[j]) > 0.0) { 746 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 747 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 748 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 749 } else { 750 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 751 } 752 #else 753 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr); 754 #endif 755 } 756 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 757 } 758 } 759 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 760 } 761 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 762 PetscFunctionReturn(0); 763 } 764 765 #include <petscdraw.h> 766 #undef __FUNCT__ 767 #define __FUNCT__ "MatView_SeqAIJ_Draw_Zoom" 768 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 769 { 770 Mat A = (Mat) Aa; 771 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 772 PetscErrorCode ierr; 773 PetscInt i,j,m = A->rmap->n,color; 774 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r,maxv = 0.0; 775 PetscViewer viewer; 776 PetscViewerFormat format; 777 778 PetscFunctionBegin; 779 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 780 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 781 782 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 783 /* loop over matrix elements drawing boxes */ 784 785 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 786 /* Blue for negative, Cyan for zero and Red for positive */ 787 color = PETSC_DRAW_BLUE; 788 for (i=0; i<m; i++) { 789 y_l = m - i - 1.0; y_r = y_l + 1.0; 790 for (j=a->i[i]; j<a->i[i+1]; j++) { 791 x_l = a->j[j]; x_r = x_l + 1.0; 792 if (PetscRealPart(a->a[j]) >= 0.) continue; 793 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 794 } 795 } 796 color = PETSC_DRAW_CYAN; 797 for (i=0; i<m; i++) { 798 y_l = m - i - 1.0; y_r = y_l + 1.0; 799 for (j=a->i[i]; j<a->i[i+1]; j++) { 800 x_l = a->j[j]; x_r = x_l + 1.0; 801 if (a->a[j] != 0.) continue; 802 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 803 } 804 } 805 color = PETSC_DRAW_RED; 806 for (i=0; i<m; i++) { 807 y_l = m - i - 1.0; y_r = y_l + 1.0; 808 for (j=a->i[i]; j<a->i[i+1]; j++) { 809 x_l = a->j[j]; x_r = x_l + 1.0; 810 if (PetscRealPart(a->a[j]) <= 0.) continue; 811 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 812 } 813 } 814 } else { 815 /* use contour shading to indicate magnitude of values */ 816 /* first determine max of all nonzero values */ 817 PetscInt nz = a->nz,count; 818 PetscDraw popup; 819 PetscReal scale; 820 821 for (i=0; i<nz; i++) { 822 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 823 } 824 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 825 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 826 if (popup) { 827 ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); 828 } 829 count = 0; 830 for (i=0; i<m; i++) { 831 y_l = m - i - 1.0; y_r = y_l + 1.0; 832 for (j=a->i[i]; j<a->i[i+1]; j++) { 833 x_l = a->j[j]; x_r = x_l + 1.0; 834 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(a->a[count])); 835 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 836 count++; 837 } 838 } 839 } 840 PetscFunctionReturn(0); 841 } 842 843 #include <petscdraw.h> 844 #undef __FUNCT__ 845 #define __FUNCT__ "MatView_SeqAIJ_Draw" 846 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 847 { 848 PetscErrorCode ierr; 849 PetscDraw draw; 850 PetscReal xr,yr,xl,yl,h,w; 851 PetscBool isnull; 852 853 PetscFunctionBegin; 854 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 855 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 856 if (isnull) PetscFunctionReturn(0); 857 858 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 859 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 860 xr += w; yr += h; xl = -w; yl = -h; 861 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 862 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 863 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 864 PetscFunctionReturn(0); 865 } 866 867 #undef __FUNCT__ 868 #define __FUNCT__ "MatView_SeqAIJ" 869 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 870 { 871 PetscErrorCode ierr; 872 PetscBool iascii,isbinary,isdraw; 873 874 PetscFunctionBegin; 875 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 876 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 877 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 878 if (iascii) { 879 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 880 } else if (isbinary) { 881 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 882 } else if (isdraw) { 883 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 884 } 885 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 886 PetscFunctionReturn(0); 887 } 888 889 #undef __FUNCT__ 890 #define __FUNCT__ "MatAssemblyEnd_SeqAIJ" 891 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 892 { 893 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 894 PetscErrorCode ierr; 895 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 896 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 897 MatScalar *aa = a->a,*ap; 898 PetscReal ratio = 0.6; 899 900 PetscFunctionBegin; 901 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 902 903 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 904 for (i=1; i<m; i++) { 905 /* move each row back by the amount of empty slots (fshift) before it*/ 906 fshift += imax[i-1] - ailen[i-1]; 907 rmax = PetscMax(rmax,ailen[i]); 908 if (fshift) { 909 ip = aj + ai[i]; 910 ap = aa + ai[i]; 911 N = ailen[i]; 912 for (j=0; j<N; j++) { 913 ip[j-fshift] = ip[j]; 914 ap[j-fshift] = ap[j]; 915 } 916 } 917 ai[i] = ai[i-1] + ailen[i-1]; 918 } 919 if (m) { 920 fshift += imax[m-1] - ailen[m-1]; 921 ai[m] = ai[m-1] + ailen[m-1]; 922 } 923 /* reset ilen and imax for each row */ 924 for (i=0; i<m; i++) { 925 ailen[i] = imax[i] = ai[i+1] - ai[i]; 926 } 927 a->nz = ai[m]; 928 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); 929 930 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 931 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 932 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 933 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 934 935 A->info.mallocs += a->reallocs; 936 a->reallocs = 0; 937 A->info.nz_unneeded = (double)fshift; 938 a->rmax = rmax; 939 940 ierr = MatCheckCompressedRow(A,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 941 942 A->same_nonzero = PETSC_TRUE; 943 944 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 945 946 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 947 PetscFunctionReturn(0); 948 } 949 950 #undef __FUNCT__ 951 #define __FUNCT__ "MatRealPart_SeqAIJ" 952 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 953 { 954 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 955 PetscInt i,nz = a->nz; 956 MatScalar *aa = a->a; 957 PetscErrorCode ierr; 958 959 PetscFunctionBegin; 960 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 961 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 962 PetscFunctionReturn(0); 963 } 964 965 #undef __FUNCT__ 966 #define __FUNCT__ "MatImaginaryPart_SeqAIJ" 967 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 968 { 969 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 970 PetscInt i,nz = a->nz; 971 MatScalar *aa = a->a; 972 PetscErrorCode ierr; 973 974 PetscFunctionBegin; 975 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 976 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 977 PetscFunctionReturn(0); 978 } 979 980 #if defined(PETSC_THREADCOMM_ACTIVE) 981 PetscErrorCode MatZeroEntries_SeqAIJ_Kernel(PetscInt thread_id,Mat A) 982 { 983 PetscErrorCode ierr; 984 PetscInt *trstarts=A->rmap->trstarts; 985 PetscInt n,start,end; 986 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 987 988 start = trstarts[thread_id]; 989 end = trstarts[thread_id+1]; 990 n = a->i[end] - a->i[start]; 991 ierr = PetscMemzero(a->a+a->i[start],n*sizeof(PetscScalar));CHKERRQ(ierr); 992 return 0; 993 } 994 995 #undef __FUNCT__ 996 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 997 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 998 { 999 PetscErrorCode ierr; 1000 1001 PetscFunctionBegin; 1002 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatZeroEntries_SeqAIJ_Kernel,1,A);CHKERRQ(ierr); 1003 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1004 PetscFunctionReturn(0); 1005 } 1006 #else 1007 #undef __FUNCT__ 1008 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 1009 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1010 { 1011 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1012 PetscErrorCode ierr; 1013 1014 PetscFunctionBegin; 1015 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1016 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1017 PetscFunctionReturn(0); 1018 } 1019 #endif 1020 1021 #undef __FUNCT__ 1022 #define __FUNCT__ "MatDestroy_SeqAIJ" 1023 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1024 { 1025 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1026 PetscErrorCode ierr; 1027 1028 PetscFunctionBegin; 1029 #if defined(PETSC_USE_LOG) 1030 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1031 #endif 1032 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1033 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1034 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1035 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1036 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1037 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1038 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1039 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1040 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1041 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1042 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1043 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 1044 ierr = MatDestroy(&a->XtoY);CHKERRQ(ierr); 1045 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1046 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1047 1048 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1049 ierr = PetscFree(A->data);CHKERRQ(ierr); 1050 1051 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1052 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1053 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1054 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1055 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1056 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1057 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1058 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1059 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1060 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1061 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1062 PetscFunctionReturn(0); 1063 } 1064 1065 #undef __FUNCT__ 1066 #define __FUNCT__ "MatSetOption_SeqAIJ" 1067 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1068 { 1069 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1070 PetscErrorCode ierr; 1071 1072 PetscFunctionBegin; 1073 switch (op) { 1074 case MAT_ROW_ORIENTED: 1075 a->roworiented = flg; 1076 break; 1077 case MAT_KEEP_NONZERO_PATTERN: 1078 a->keepnonzeropattern = flg; 1079 break; 1080 case MAT_NEW_NONZERO_LOCATIONS: 1081 a->nonew = (flg ? 0 : 1); 1082 break; 1083 case MAT_NEW_NONZERO_LOCATION_ERR: 1084 a->nonew = (flg ? -1 : 0); 1085 break; 1086 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1087 a->nonew = (flg ? -2 : 0); 1088 break; 1089 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1090 a->nounused = (flg ? -1 : 0); 1091 break; 1092 case MAT_IGNORE_ZERO_ENTRIES: 1093 a->ignorezeroentries = flg; 1094 break; 1095 case MAT_CHECK_COMPRESSED_ROW: 1096 a->compressedrow.check = flg; 1097 break; 1098 case MAT_SPD: 1099 case MAT_SYMMETRIC: 1100 case MAT_STRUCTURALLY_SYMMETRIC: 1101 case MAT_HERMITIAN: 1102 case MAT_SYMMETRY_ETERNAL: 1103 /* These options are handled directly by MatSetOption() */ 1104 break; 1105 case MAT_NEW_DIAGONALS: 1106 case MAT_IGNORE_OFF_PROC_ENTRIES: 1107 case MAT_USE_HASH_TABLE: 1108 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1109 break; 1110 case MAT_USE_INODES: 1111 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1112 break; 1113 default: 1114 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1115 } 1116 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1117 PetscFunctionReturn(0); 1118 } 1119 1120 #undef __FUNCT__ 1121 #define __FUNCT__ "MatGetDiagonal_SeqAIJ" 1122 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1123 { 1124 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1125 PetscErrorCode ierr; 1126 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1127 PetscScalar *aa=a->a,*x,zero=0.0; 1128 1129 PetscFunctionBegin; 1130 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1131 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1132 1133 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1134 PetscInt *diag=a->diag; 1135 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1136 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1137 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1138 PetscFunctionReturn(0); 1139 } 1140 1141 ierr = VecSet(v,zero);CHKERRQ(ierr); 1142 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1143 for (i=0; i<n; i++) { 1144 nz = ai[i+1] - ai[i]; 1145 if (!nz) x[i] = 0.0; 1146 for (j=ai[i]; j<ai[i+1]; j++) { 1147 if (aj[j] == i) { 1148 x[i] = aa[j]; 1149 break; 1150 } 1151 } 1152 } 1153 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1154 PetscFunctionReturn(0); 1155 } 1156 1157 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1158 #undef __FUNCT__ 1159 #define __FUNCT__ "MatMultTransposeAdd_SeqAIJ" 1160 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1161 { 1162 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1163 PetscScalar *x,*y; 1164 PetscErrorCode ierr; 1165 PetscInt m = A->rmap->n; 1166 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1167 MatScalar *v; 1168 PetscScalar alpha; 1169 PetscInt n,i,j,*idx,*ii,*ridx=NULL; 1170 Mat_CompressedRow cprow = a->compressedrow; 1171 PetscBool usecprow = cprow.use; 1172 #endif 1173 1174 PetscFunctionBegin; 1175 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1176 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1177 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1178 1179 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1180 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1181 #else 1182 if (usecprow) { 1183 m = cprow.nrows; 1184 ii = cprow.i; 1185 ridx = cprow.rindex; 1186 } else { 1187 ii = a->i; 1188 } 1189 for (i=0; i<m; i++) { 1190 idx = a->j + ii[i]; 1191 v = a->a + ii[i]; 1192 n = ii[i+1] - ii[i]; 1193 if (usecprow) { 1194 alpha = x[ridx[i]]; 1195 } else { 1196 alpha = x[i]; 1197 } 1198 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1199 } 1200 #endif 1201 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1202 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1203 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1204 PetscFunctionReturn(0); 1205 } 1206 1207 #undef __FUNCT__ 1208 #define __FUNCT__ "MatMultTranspose_SeqAIJ" 1209 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1210 { 1211 PetscErrorCode ierr; 1212 1213 PetscFunctionBegin; 1214 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1215 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1216 PetscFunctionReturn(0); 1217 } 1218 1219 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1220 #if defined(PETSC_THREADCOMM_ACTIVE) 1221 PetscErrorCode MatMult_SeqAIJ_Kernel(PetscInt thread_id,Mat A,Vec xx,Vec yy) 1222 { 1223 PetscErrorCode ierr; 1224 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1225 PetscScalar *y; 1226 const PetscScalar *x; 1227 const MatScalar *aa; 1228 PetscInt *trstarts=A->rmap->trstarts; 1229 PetscInt n,start,end,i; 1230 const PetscInt *aj,*ai; 1231 PetscScalar sum; 1232 1233 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1234 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1235 start = trstarts[thread_id]; 1236 end = trstarts[thread_id+1]; 1237 aj = a->j; 1238 aa = a->a; 1239 ai = a->i; 1240 for (i=start; i<end; i++) { 1241 n = ai[i+1] - ai[i]; 1242 aj = a->j + ai[i]; 1243 aa = a->a + ai[i]; 1244 sum = 0.0; 1245 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1246 y[i] = sum; 1247 } 1248 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1249 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1250 return 0; 1251 } 1252 1253 #undef __FUNCT__ 1254 #define __FUNCT__ "MatMult_SeqAIJ" 1255 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1256 { 1257 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1258 PetscScalar *y; 1259 const PetscScalar *x; 1260 const MatScalar *aa; 1261 PetscErrorCode ierr; 1262 PetscInt m=A->rmap->n; 1263 const PetscInt *aj,*ii,*ridx=NULL; 1264 PetscInt n,i,nonzerorow=0; 1265 PetscScalar sum; 1266 PetscBool usecprow=a->compressedrow.use; 1267 1268 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1269 #pragma disjoint(*x,*y,*aa) 1270 #endif 1271 1272 PetscFunctionBegin; 1273 aj = a->j; 1274 aa = a->a; 1275 ii = a->i; 1276 if (usecprow) { /* use compressed row format */ 1277 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1278 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1279 m = a->compressedrow.nrows; 1280 ii = a->compressedrow.i; 1281 ridx = a->compressedrow.rindex; 1282 for (i=0; i<m; i++) { 1283 n = ii[i+1] - ii[i]; 1284 aj = a->j + ii[i]; 1285 aa = a->a + ii[i]; 1286 sum = 0.0; 1287 nonzerorow += (n>0); 1288 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1289 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1290 y[*ridx++] = sum; 1291 } 1292 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1293 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1294 } else { /* do not use compressed row format */ 1295 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1296 fortranmultaij_(&m,x,ii,aj,aa,y); 1297 #else 1298 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatMult_SeqAIJ_Kernel,3,A,xx,yy);CHKERRQ(ierr); 1299 #endif 1300 } 1301 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1302 PetscFunctionReturn(0); 1303 } 1304 #else 1305 #undef __FUNCT__ 1306 #define __FUNCT__ "MatMult_SeqAIJ" 1307 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1308 { 1309 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1310 PetscScalar *y; 1311 const PetscScalar *x; 1312 const MatScalar *aa; 1313 PetscErrorCode ierr; 1314 PetscInt m=A->rmap->n; 1315 const PetscInt *aj,*ii,*ridx=NULL; 1316 PetscInt n,i,nonzerorow=0; 1317 PetscScalar sum; 1318 PetscBool usecprow=a->compressedrow.use; 1319 1320 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1321 #pragma disjoint(*x,*y,*aa) 1322 #endif 1323 1324 PetscFunctionBegin; 1325 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1326 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1327 aj = a->j; 1328 aa = a->a; 1329 ii = a->i; 1330 if (usecprow) { /* use compressed row format */ 1331 m = a->compressedrow.nrows; 1332 ii = a->compressedrow.i; 1333 ridx = a->compressedrow.rindex; 1334 for (i=0; i<m; i++) { 1335 n = ii[i+1] - ii[i]; 1336 aj = a->j + ii[i]; 1337 aa = a->a + ii[i]; 1338 sum = 0.0; 1339 nonzerorow += (n>0); 1340 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1341 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1342 y[*ridx++] = sum; 1343 } 1344 } else { /* do not use compressed row format */ 1345 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1346 fortranmultaij_(&m,x,ii,aj,aa,y); 1347 #else 1348 #if defined(PETSC_THREADCOMM_ACTIVE) 1349 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatMult_SeqAIJ_Kernel,3,A,xx,yy);CHKERRQ(ierr); 1350 #else 1351 for (i=0; i<m; i++) { 1352 n = ii[i+1] - ii[i]; 1353 aj = a->j + ii[i]; 1354 aa = a->a + ii[i]; 1355 sum = 0.0; 1356 nonzerorow += (n>0); 1357 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1358 y[i] = sum; 1359 } 1360 #endif 1361 #endif 1362 } 1363 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1364 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1365 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1366 PetscFunctionReturn(0); 1367 } 1368 #endif 1369 1370 #undef __FUNCT__ 1371 #define __FUNCT__ "MatMultMax_SeqAIJ" 1372 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1373 { 1374 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1375 PetscScalar *y; 1376 const PetscScalar *x; 1377 const MatScalar *aa; 1378 PetscErrorCode ierr; 1379 PetscInt m=A->rmap->n; 1380 const PetscInt *aj,*ii,*ridx=NULL; 1381 PetscInt n,i,nonzerorow=0; 1382 PetscScalar sum; 1383 PetscBool usecprow=a->compressedrow.use; 1384 1385 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1386 #pragma disjoint(*x,*y,*aa) 1387 #endif 1388 1389 PetscFunctionBegin; 1390 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1391 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1392 aj = a->j; 1393 aa = a->a; 1394 ii = a->i; 1395 if (usecprow) { /* use compressed row format */ 1396 m = a->compressedrow.nrows; 1397 ii = a->compressedrow.i; 1398 ridx = a->compressedrow.rindex; 1399 for (i=0; i<m; i++) { 1400 n = ii[i+1] - ii[i]; 1401 aj = a->j + ii[i]; 1402 aa = a->a + ii[i]; 1403 sum = 0.0; 1404 nonzerorow += (n>0); 1405 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1406 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1407 y[*ridx++] = sum; 1408 } 1409 } else { /* do not use compressed row format */ 1410 for (i=0; i<m; i++) { 1411 n = ii[i+1] - ii[i]; 1412 aj = a->j + ii[i]; 1413 aa = a->a + ii[i]; 1414 sum = 0.0; 1415 nonzerorow += (n>0); 1416 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1417 y[i] = sum; 1418 } 1419 } 1420 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1421 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1422 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1423 PetscFunctionReturn(0); 1424 } 1425 1426 #undef __FUNCT__ 1427 #define __FUNCT__ "MatMultAddMax_SeqAIJ" 1428 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1429 { 1430 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1431 PetscScalar *y,*z; 1432 const PetscScalar *x; 1433 const MatScalar *aa; 1434 PetscErrorCode ierr; 1435 PetscInt m = A->rmap->n,*aj,*ii; 1436 PetscInt n,i,*ridx=NULL; 1437 PetscScalar sum; 1438 PetscBool usecprow=a->compressedrow.use; 1439 1440 PetscFunctionBegin; 1441 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1442 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1443 if (zz != yy) { 1444 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 1445 } else { 1446 z = y; 1447 } 1448 1449 aj = a->j; 1450 aa = a->a; 1451 ii = a->i; 1452 if (usecprow) { /* use compressed row format */ 1453 if (zz != yy) { 1454 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1455 } 1456 m = a->compressedrow.nrows; 1457 ii = a->compressedrow.i; 1458 ridx = a->compressedrow.rindex; 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[*ridx]; 1464 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1465 z[*ridx++] = sum; 1466 } 1467 } else { /* do not use compressed row format */ 1468 for (i=0; i<m; i++) { 1469 n = ii[i+1] - ii[i]; 1470 aj = a->j + ii[i]; 1471 aa = a->a + ii[i]; 1472 sum = y[i]; 1473 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1474 z[i] = sum; 1475 } 1476 } 1477 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1478 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1479 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1480 if (zz != yy) { 1481 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 1482 } 1483 PetscFunctionReturn(0); 1484 } 1485 1486 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1487 #undef __FUNCT__ 1488 #define __FUNCT__ "MatMultAdd_SeqAIJ" 1489 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1490 { 1491 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1492 PetscScalar *y,*z; 1493 const PetscScalar *x; 1494 const MatScalar *aa; 1495 PetscErrorCode ierr; 1496 PetscInt m = A->rmap->n,*aj,*ii; 1497 PetscInt n,i,*ridx=NULL; 1498 PetscScalar sum; 1499 PetscBool usecprow=a->compressedrow.use; 1500 1501 PetscFunctionBegin; 1502 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1503 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1504 if (zz != yy) { 1505 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 1506 } else { 1507 z = y; 1508 } 1509 1510 aj = a->j; 1511 aa = a->a; 1512 ii = a->i; 1513 if (usecprow) { /* use compressed row format */ 1514 if (zz != yy) { 1515 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1516 } 1517 m = a->compressedrow.nrows; 1518 ii = a->compressedrow.i; 1519 ridx = a->compressedrow.rindex; 1520 for (i=0; i<m; i++) { 1521 n = ii[i+1] - ii[i]; 1522 aj = a->j + ii[i]; 1523 aa = a->a + ii[i]; 1524 sum = y[*ridx]; 1525 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1526 z[*ridx++] = sum; 1527 } 1528 } else { /* do not use compressed row format */ 1529 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1530 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1531 #else 1532 for (i=0; i<m; i++) { 1533 n = ii[i+1] - ii[i]; 1534 aj = a->j + ii[i]; 1535 aa = a->a + ii[i]; 1536 sum = y[i]; 1537 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1538 z[i] = sum; 1539 } 1540 #endif 1541 } 1542 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1543 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1544 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1545 if (zz != yy) { 1546 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 1547 } 1548 #if defined(PETSC_HAVE_CUSP) 1549 /* 1550 ierr = VecView(xx,0);CHKERRQ(ierr); 1551 ierr = VecView(zz,0);CHKERRQ(ierr); 1552 ierr = MatView(A,0);CHKERRQ(ierr); 1553 */ 1554 #endif 1555 PetscFunctionReturn(0); 1556 } 1557 1558 /* 1559 Adds diagonal pointers to sparse matrix structure. 1560 */ 1561 #undef __FUNCT__ 1562 #define __FUNCT__ "MatMarkDiagonal_SeqAIJ" 1563 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1564 { 1565 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1566 PetscErrorCode ierr; 1567 PetscInt i,j,m = A->rmap->n; 1568 1569 PetscFunctionBegin; 1570 if (!a->diag) { 1571 ierr = PetscMalloc(m*sizeof(PetscInt),&a->diag);CHKERRQ(ierr); 1572 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1573 } 1574 for (i=0; i<A->rmap->n; i++) { 1575 a->diag[i] = a->i[i+1]; 1576 for (j=a->i[i]; j<a->i[i+1]; j++) { 1577 if (a->j[j] == i) { 1578 a->diag[i] = j; 1579 break; 1580 } 1581 } 1582 } 1583 PetscFunctionReturn(0); 1584 } 1585 1586 /* 1587 Checks for missing diagonals 1588 */ 1589 #undef __FUNCT__ 1590 #define __FUNCT__ "MatMissingDiagonal_SeqAIJ" 1591 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1592 { 1593 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1594 PetscInt *diag,*jj = a->j,i; 1595 1596 PetscFunctionBegin; 1597 *missing = PETSC_FALSE; 1598 if (A->rmap->n > 0 && !jj) { 1599 *missing = PETSC_TRUE; 1600 if (d) *d = 0; 1601 PetscInfo(A,"Matrix has no entries therefore is missing diagonal"); 1602 } else { 1603 diag = a->diag; 1604 for (i=0; i<A->rmap->n; i++) { 1605 if (jj[diag[i]] != i) { 1606 *missing = PETSC_TRUE; 1607 if (d) *d = i; 1608 PetscInfo1(A,"Matrix is missing diagonal number %D",i); 1609 break; 1610 } 1611 } 1612 } 1613 PetscFunctionReturn(0); 1614 } 1615 1616 #undef __FUNCT__ 1617 #define __FUNCT__ "MatInvertDiagonal_SeqAIJ" 1618 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1619 { 1620 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1621 PetscErrorCode ierr; 1622 PetscInt i,*diag,m = A->rmap->n; 1623 MatScalar *v = a->a; 1624 PetscScalar *idiag,*mdiag; 1625 1626 PetscFunctionBegin; 1627 if (a->idiagvalid) PetscFunctionReturn(0); 1628 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1629 diag = a->diag; 1630 if (!a->idiag) { 1631 ierr = PetscMalloc3(m,PetscScalar,&a->idiag,m,PetscScalar,&a->mdiag,m,PetscScalar,&a->ssor_work);CHKERRQ(ierr); 1632 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1633 v = a->a; 1634 } 1635 mdiag = a->mdiag; 1636 idiag = a->idiag; 1637 1638 if (omega == 1.0 && !PetscAbsScalar(fshift)) { 1639 for (i=0; i<m; i++) { 1640 mdiag[i] = v[diag[i]]; 1641 if (!PetscAbsScalar(mdiag[i])) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1642 idiag[i] = 1.0/v[diag[i]]; 1643 } 1644 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1645 } else { 1646 for (i=0; i<m; i++) { 1647 mdiag[i] = v[diag[i]]; 1648 idiag[i] = omega/(fshift + v[diag[i]]); 1649 } 1650 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1651 } 1652 a->idiagvalid = PETSC_TRUE; 1653 PetscFunctionReturn(0); 1654 } 1655 1656 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1657 #undef __FUNCT__ 1658 #define __FUNCT__ "MatSOR_SeqAIJ" 1659 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1660 { 1661 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1662 PetscScalar *x,d,sum,*t,scale; 1663 const MatScalar *v = a->a,*idiag=0,*mdiag; 1664 const PetscScalar *b, *bs,*xb, *ts; 1665 PetscErrorCode ierr; 1666 PetscInt n = A->cmap->n,m = A->rmap->n,i; 1667 const PetscInt *idx,*diag; 1668 1669 PetscFunctionBegin; 1670 its = its*lits; 1671 1672 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1673 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1674 a->fshift = fshift; 1675 a->omega = omega; 1676 1677 diag = a->diag; 1678 t = a->ssor_work; 1679 idiag = a->idiag; 1680 mdiag = a->mdiag; 1681 1682 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1683 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1684 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1685 if (flag == SOR_APPLY_UPPER) { 1686 /* apply (U + D/omega) to the vector */ 1687 bs = b; 1688 for (i=0; i<m; i++) { 1689 d = fshift + mdiag[i]; 1690 n = a->i[i+1] - diag[i] - 1; 1691 idx = a->j + diag[i] + 1; 1692 v = a->a + diag[i] + 1; 1693 sum = b[i]*d/omega; 1694 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1695 x[i] = sum; 1696 } 1697 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1698 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1699 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1700 PetscFunctionReturn(0); 1701 } 1702 1703 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1704 else if (flag & SOR_EISENSTAT) { 1705 /* Let A = L + U + D; where L is lower trianglar, 1706 U is upper triangular, E = D/omega; This routine applies 1707 1708 (L + E)^{-1} A (U + E)^{-1} 1709 1710 to a vector efficiently using Eisenstat's trick. 1711 */ 1712 scale = (2.0/omega) - 1.0; 1713 1714 /* x = (E + U)^{-1} b */ 1715 for (i=m-1; i>=0; i--) { 1716 n = a->i[i+1] - diag[i] - 1; 1717 idx = a->j + diag[i] + 1; 1718 v = a->a + diag[i] + 1; 1719 sum = b[i]; 1720 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1721 x[i] = sum*idiag[i]; 1722 } 1723 1724 /* t = b - (2*E - D)x */ 1725 v = a->a; 1726 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1727 1728 /* t = (E + L)^{-1}t */ 1729 ts = t; 1730 diag = a->diag; 1731 for (i=0; i<m; i++) { 1732 n = diag[i] - a->i[i]; 1733 idx = a->j + a->i[i]; 1734 v = a->a + a->i[i]; 1735 sum = t[i]; 1736 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1737 t[i] = sum*idiag[i]; 1738 /* x = x + t */ 1739 x[i] += t[i]; 1740 } 1741 1742 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1743 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1744 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1745 PetscFunctionReturn(0); 1746 } 1747 if (flag & SOR_ZERO_INITIAL_GUESS) { 1748 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1749 for (i=0; i<m; i++) { 1750 n = diag[i] - a->i[i]; 1751 idx = a->j + a->i[i]; 1752 v = a->a + a->i[i]; 1753 sum = b[i]; 1754 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1755 t[i] = sum; 1756 x[i] = sum*idiag[i]; 1757 } 1758 xb = t; 1759 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1760 } else xb = b; 1761 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1762 for (i=m-1; i>=0; i--) { 1763 n = a->i[i+1] - diag[i] - 1; 1764 idx = a->j + diag[i] + 1; 1765 v = a->a + diag[i] + 1; 1766 sum = xb[i]; 1767 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1768 if (xb == b) { 1769 x[i] = sum*idiag[i]; 1770 } else { 1771 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1772 } 1773 } 1774 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1775 } 1776 its--; 1777 } 1778 while (its--) { 1779 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1780 for (i=0; i<m; i++) { 1781 /* lower */ 1782 n = diag[i] - a->i[i]; 1783 idx = a->j + a->i[i]; 1784 v = a->a + a->i[i]; 1785 sum = b[i]; 1786 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1787 t[i] = sum; /* save application of the lower-triangular part */ 1788 /* upper */ 1789 n = a->i[i+1] - diag[i] - 1; 1790 idx = a->j + diag[i] + 1; 1791 v = a->a + diag[i] + 1; 1792 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1793 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1794 } 1795 xb = t; 1796 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1797 } else xb = b; 1798 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1799 for (i=m-1; i>=0; i--) { 1800 sum = xb[i]; 1801 if (xb == b) { 1802 /* whole matrix (no checkpointing available) */ 1803 n = a->i[i+1] - a->i[i]; 1804 idx = a->j + a->i[i]; 1805 v = a->a + a->i[i]; 1806 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1807 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1808 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1809 n = a->i[i+1] - diag[i] - 1; 1810 idx = a->j + diag[i] + 1; 1811 v = a->a + diag[i] + 1; 1812 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1813 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1814 } 1815 } 1816 if (xb == b) { 1817 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1818 } else { 1819 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1820 } 1821 } 1822 } 1823 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1824 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1825 PetscFunctionReturn(0); 1826 } 1827 1828 1829 #undef __FUNCT__ 1830 #define __FUNCT__ "MatGetInfo_SeqAIJ" 1831 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1832 { 1833 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1834 1835 PetscFunctionBegin; 1836 info->block_size = 1.0; 1837 info->nz_allocated = (double)a->maxnz; 1838 info->nz_used = (double)a->nz; 1839 info->nz_unneeded = (double)(a->maxnz - a->nz); 1840 info->assemblies = (double)A->num_ass; 1841 info->mallocs = (double)A->info.mallocs; 1842 info->memory = ((PetscObject)A)->mem; 1843 if (A->factortype) { 1844 info->fill_ratio_given = A->info.fill_ratio_given; 1845 info->fill_ratio_needed = A->info.fill_ratio_needed; 1846 info->factor_mallocs = A->info.factor_mallocs; 1847 } else { 1848 info->fill_ratio_given = 0; 1849 info->fill_ratio_needed = 0; 1850 info->factor_mallocs = 0; 1851 } 1852 PetscFunctionReturn(0); 1853 } 1854 1855 #undef __FUNCT__ 1856 #define __FUNCT__ "MatZeroRows_SeqAIJ" 1857 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1858 { 1859 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1860 PetscInt i,m = A->rmap->n - 1,d = 0; 1861 PetscErrorCode ierr; 1862 const PetscScalar *xx; 1863 PetscScalar *bb; 1864 PetscBool missing; 1865 1866 PetscFunctionBegin; 1867 if (x && b) { 1868 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1869 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1870 for (i=0; i<N; i++) { 1871 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1872 bb[rows[i]] = diag*xx[rows[i]]; 1873 } 1874 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1875 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1876 } 1877 1878 if (a->keepnonzeropattern) { 1879 for (i=0; i<N; i++) { 1880 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1881 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1882 } 1883 if (diag != 0.0) { 1884 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1885 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1886 for (i=0; i<N; i++) { 1887 a->a[a->diag[rows[i]]] = diag; 1888 } 1889 } 1890 A->same_nonzero = PETSC_TRUE; 1891 } else { 1892 if (diag != 0.0) { 1893 for (i=0; i<N; i++) { 1894 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1895 if (a->ilen[rows[i]] > 0) { 1896 a->ilen[rows[i]] = 1; 1897 a->a[a->i[rows[i]]] = diag; 1898 a->j[a->i[rows[i]]] = rows[i]; 1899 } else { /* in case row was completely empty */ 1900 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1901 } 1902 } 1903 } else { 1904 for (i=0; i<N; i++) { 1905 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1906 a->ilen[rows[i]] = 0; 1907 } 1908 } 1909 A->same_nonzero = PETSC_FALSE; 1910 } 1911 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1912 PetscFunctionReturn(0); 1913 } 1914 1915 #undef __FUNCT__ 1916 #define __FUNCT__ "MatZeroRowsColumns_SeqAIJ" 1917 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1918 { 1919 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1920 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1921 PetscErrorCode ierr; 1922 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1923 const PetscScalar *xx; 1924 PetscScalar *bb; 1925 1926 PetscFunctionBegin; 1927 if (x && b) { 1928 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1929 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1930 vecs = PETSC_TRUE; 1931 } 1932 ierr = PetscMalloc(A->rmap->n*sizeof(PetscBool),&zeroed);CHKERRQ(ierr); 1933 ierr = PetscMemzero(zeroed,A->rmap->n*sizeof(PetscBool));CHKERRQ(ierr); 1934 for (i=0; i<N; i++) { 1935 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1936 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1937 1938 zeroed[rows[i]] = PETSC_TRUE; 1939 } 1940 for (i=0; i<A->rmap->n; i++) { 1941 if (!zeroed[i]) { 1942 for (j=a->i[i]; j<a->i[i+1]; j++) { 1943 if (zeroed[a->j[j]]) { 1944 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1945 a->a[j] = 0.0; 1946 } 1947 } 1948 } else if (vecs) bb[i] = diag*xx[i]; 1949 } 1950 if (x && b) { 1951 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1952 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1953 } 1954 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1955 if (diag != 0.0) { 1956 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1957 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1958 for (i=0; i<N; i++) { 1959 a->a[a->diag[rows[i]]] = diag; 1960 } 1961 } 1962 A->same_nonzero = PETSC_TRUE; 1963 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1964 PetscFunctionReturn(0); 1965 } 1966 1967 #undef __FUNCT__ 1968 #define __FUNCT__ "MatGetRow_SeqAIJ" 1969 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1970 { 1971 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1972 PetscInt *itmp; 1973 1974 PetscFunctionBegin; 1975 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1976 1977 *nz = a->i[row+1] - a->i[row]; 1978 if (v) *v = a->a + a->i[row]; 1979 if (idx) { 1980 itmp = a->j + a->i[row]; 1981 if (*nz) *idx = itmp; 1982 else *idx = 0; 1983 } 1984 PetscFunctionReturn(0); 1985 } 1986 1987 /* remove this function? */ 1988 #undef __FUNCT__ 1989 #define __FUNCT__ "MatRestoreRow_SeqAIJ" 1990 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1991 { 1992 PetscFunctionBegin; 1993 PetscFunctionReturn(0); 1994 } 1995 1996 #undef __FUNCT__ 1997 #define __FUNCT__ "MatNorm_SeqAIJ" 1998 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1999 { 2000 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2001 MatScalar *v = a->a; 2002 PetscReal sum = 0.0; 2003 PetscErrorCode ierr; 2004 PetscInt i,j; 2005 2006 PetscFunctionBegin; 2007 if (type == NORM_FROBENIUS) { 2008 for (i=0; i<a->nz; i++) { 2009 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2010 } 2011 *nrm = PetscSqrtReal(sum); 2012 } else if (type == NORM_1) { 2013 PetscReal *tmp; 2014 PetscInt *jj = a->j; 2015 ierr = PetscMalloc((A->cmap->n+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2016 ierr = PetscMemzero(tmp,A->cmap->n*sizeof(PetscReal));CHKERRQ(ierr); 2017 *nrm = 0.0; 2018 for (j=0; j<a->nz; j++) { 2019 tmp[*jj++] += PetscAbsScalar(*v); v++; 2020 } 2021 for (j=0; j<A->cmap->n; j++) { 2022 if (tmp[j] > *nrm) *nrm = tmp[j]; 2023 } 2024 ierr = PetscFree(tmp);CHKERRQ(ierr); 2025 } else if (type == NORM_INFINITY) { 2026 *nrm = 0.0; 2027 for (j=0; j<A->rmap->n; j++) { 2028 v = a->a + a->i[j]; 2029 sum = 0.0; 2030 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2031 sum += PetscAbsScalar(*v); v++; 2032 } 2033 if (sum > *nrm) *nrm = sum; 2034 } 2035 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2036 PetscFunctionReturn(0); 2037 } 2038 2039 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2040 #undef __FUNCT__ 2041 #define __FUNCT__ "MatTransposeSymbolic_SeqAIJ" 2042 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2043 { 2044 PetscErrorCode ierr; 2045 PetscInt i,j,anzj; 2046 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2047 PetscInt an=A->cmap->N,am=A->rmap->N; 2048 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2049 2050 PetscFunctionBegin; 2051 /* Allocate space for symbolic transpose info and work array */ 2052 ierr = PetscMalloc((an+1)*sizeof(PetscInt),&ati);CHKERRQ(ierr); 2053 ierr = PetscMalloc(ai[am]*sizeof(PetscInt),&atj);CHKERRQ(ierr); 2054 ierr = PetscMalloc(an*sizeof(PetscInt),&atfill);CHKERRQ(ierr); 2055 ierr = PetscMemzero(ati,(an+1)*sizeof(PetscInt));CHKERRQ(ierr); 2056 2057 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2058 /* Note: offset by 1 for fast conversion into csr format. */ 2059 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2060 /* Form ati for csr format of A^T. */ 2061 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2062 2063 /* Copy ati into atfill so we have locations of the next free space in atj */ 2064 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2065 2066 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2067 for (i=0;i<am;i++) { 2068 anzj = ai[i+1] - ai[i]; 2069 for (j=0;j<anzj;j++) { 2070 atj[atfill[*aj]] = i; 2071 atfill[*aj++] += 1; 2072 } 2073 } 2074 2075 /* Clean up temporary space and complete requests. */ 2076 ierr = PetscFree(atfill);CHKERRQ(ierr); 2077 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2078 2079 (*B)->rmap->bs = A->cmap->bs; 2080 (*B)->cmap->bs = A->rmap->bs; 2081 2082 b = (Mat_SeqAIJ*)((*B)->data); 2083 b->free_a = PETSC_FALSE; 2084 b->free_ij = PETSC_TRUE; 2085 b->nonew = 0; 2086 PetscFunctionReturn(0); 2087 } 2088 2089 #undef __FUNCT__ 2090 #define __FUNCT__ "MatTranspose_SeqAIJ" 2091 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2092 { 2093 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2094 Mat C; 2095 PetscErrorCode ierr; 2096 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2097 MatScalar *array = a->a; 2098 2099 PetscFunctionBegin; 2100 if (reuse == MAT_REUSE_MATRIX && A == *B && m != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2101 2102 if (reuse == MAT_INITIAL_MATRIX || *B == A) { 2103 ierr = PetscMalloc((1+A->cmap->n)*sizeof(PetscInt),&col);CHKERRQ(ierr); 2104 ierr = PetscMemzero(col,(1+A->cmap->n)*sizeof(PetscInt));CHKERRQ(ierr); 2105 2106 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2107 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2108 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2109 ierr = MatSetBlockSizes(C,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2110 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2111 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2112 ierr = PetscFree(col);CHKERRQ(ierr); 2113 } else { 2114 C = *B; 2115 } 2116 2117 for (i=0; i<m; i++) { 2118 len = ai[i+1]-ai[i]; 2119 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2120 array += len; 2121 aj += len; 2122 } 2123 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2124 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2125 2126 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 2127 *B = C; 2128 } else { 2129 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 2130 } 2131 PetscFunctionReturn(0); 2132 } 2133 2134 #undef __FUNCT__ 2135 #define __FUNCT__ "MatIsTranspose_SeqAIJ" 2136 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2137 { 2138 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2139 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2140 MatScalar *va,*vb; 2141 PetscErrorCode ierr; 2142 PetscInt ma,na,mb,nb, i; 2143 2144 PetscFunctionBegin; 2145 bij = (Mat_SeqAIJ*) B->data; 2146 2147 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2148 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2149 if (ma!=nb || na!=mb) { 2150 *f = PETSC_FALSE; 2151 PetscFunctionReturn(0); 2152 } 2153 aii = aij->i; bii = bij->i; 2154 adx = aij->j; bdx = bij->j; 2155 va = aij->a; vb = bij->a; 2156 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 2157 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 2158 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2159 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2160 2161 *f = PETSC_TRUE; 2162 for (i=0; i<ma; i++) { 2163 while (aptr[i]<aii[i+1]) { 2164 PetscInt idc,idr; 2165 PetscScalar vc,vr; 2166 /* column/row index/value */ 2167 idc = adx[aptr[i]]; 2168 idr = bdx[bptr[idc]]; 2169 vc = va[aptr[i]]; 2170 vr = vb[bptr[idc]]; 2171 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2172 *f = PETSC_FALSE; 2173 goto done; 2174 } else { 2175 aptr[i]++; 2176 if (B || i!=idc) bptr[idc]++; 2177 } 2178 } 2179 } 2180 done: 2181 ierr = PetscFree(aptr);CHKERRQ(ierr); 2182 ierr = PetscFree(bptr);CHKERRQ(ierr); 2183 PetscFunctionReturn(0); 2184 } 2185 2186 #undef __FUNCT__ 2187 #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" 2188 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2189 { 2190 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2191 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2192 MatScalar *va,*vb; 2193 PetscErrorCode ierr; 2194 PetscInt ma,na,mb,nb, i; 2195 2196 PetscFunctionBegin; 2197 bij = (Mat_SeqAIJ*) B->data; 2198 2199 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2200 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2201 if (ma!=nb || na!=mb) { 2202 *f = PETSC_FALSE; 2203 PetscFunctionReturn(0); 2204 } 2205 aii = aij->i; bii = bij->i; 2206 adx = aij->j; bdx = bij->j; 2207 va = aij->a; vb = bij->a; 2208 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 2209 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 2210 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2211 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2212 2213 *f = PETSC_TRUE; 2214 for (i=0; i<ma; i++) { 2215 while (aptr[i]<aii[i+1]) { 2216 PetscInt idc,idr; 2217 PetscScalar vc,vr; 2218 /* column/row index/value */ 2219 idc = adx[aptr[i]]; 2220 idr = bdx[bptr[idc]]; 2221 vc = va[aptr[i]]; 2222 vr = vb[bptr[idc]]; 2223 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2224 *f = PETSC_FALSE; 2225 goto done; 2226 } else { 2227 aptr[i]++; 2228 if (B || i!=idc) bptr[idc]++; 2229 } 2230 } 2231 } 2232 done: 2233 ierr = PetscFree(aptr);CHKERRQ(ierr); 2234 ierr = PetscFree(bptr);CHKERRQ(ierr); 2235 PetscFunctionReturn(0); 2236 } 2237 2238 #undef __FUNCT__ 2239 #define __FUNCT__ "MatIsSymmetric_SeqAIJ" 2240 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2241 { 2242 PetscErrorCode ierr; 2243 2244 PetscFunctionBegin; 2245 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2246 PetscFunctionReturn(0); 2247 } 2248 2249 #undef __FUNCT__ 2250 #define __FUNCT__ "MatIsHermitian_SeqAIJ" 2251 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2252 { 2253 PetscErrorCode ierr; 2254 2255 PetscFunctionBegin; 2256 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2257 PetscFunctionReturn(0); 2258 } 2259 2260 #undef __FUNCT__ 2261 #define __FUNCT__ "MatDiagonalScale_SeqAIJ" 2262 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2263 { 2264 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2265 PetscScalar *l,*r,x; 2266 MatScalar *v; 2267 PetscErrorCode ierr; 2268 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; 2269 2270 PetscFunctionBegin; 2271 if (ll) { 2272 /* The local size is used so that VecMPI can be passed to this routine 2273 by MatDiagonalScale_MPIAIJ */ 2274 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2275 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2276 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 2277 v = a->a; 2278 for (i=0; i<m; i++) { 2279 x = l[i]; 2280 M = a->i[i+1] - a->i[i]; 2281 for (j=0; j<M; j++) (*v++) *= x; 2282 } 2283 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 2284 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2285 } 2286 if (rr) { 2287 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2288 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2289 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 2290 v = a->a; jj = a->j; 2291 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2292 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 2293 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2294 } 2295 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2296 PetscFunctionReturn(0); 2297 } 2298 2299 #undef __FUNCT__ 2300 #define __FUNCT__ "MatGetSubMatrix_SeqAIJ" 2301 PetscErrorCode MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2302 { 2303 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2304 PetscErrorCode ierr; 2305 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2306 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2307 const PetscInt *irow,*icol; 2308 PetscInt nrows,ncols; 2309 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2310 MatScalar *a_new,*mat_a; 2311 Mat C; 2312 PetscBool stride,sorted; 2313 2314 PetscFunctionBegin; 2315 ierr = ISSorted(isrow,&sorted);CHKERRQ(ierr); 2316 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted"); 2317 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); 2318 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted"); 2319 2320 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2321 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2322 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2323 2324 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2325 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2326 if (stride && step == 1) { 2327 /* special case of contiguous rows */ 2328 ierr = PetscMalloc2(nrows,PetscInt,&lens,nrows,PetscInt,&starts);CHKERRQ(ierr); 2329 /* loop over new rows determining lens and starting points */ 2330 for (i=0; i<nrows; i++) { 2331 kstart = ai[irow[i]]; 2332 kend = kstart + ailen[irow[i]]; 2333 for (k=kstart; k<kend; k++) { 2334 if (aj[k] >= first) { 2335 starts[i] = k; 2336 break; 2337 } 2338 } 2339 sum = 0; 2340 while (k < kend) { 2341 if (aj[k++] >= first+ncols) break; 2342 sum++; 2343 } 2344 lens[i] = sum; 2345 } 2346 /* create submatrix */ 2347 if (scall == MAT_REUSE_MATRIX) { 2348 PetscInt n_cols,n_rows; 2349 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2350 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2351 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2352 C = *B; 2353 } else { 2354 PetscInt rbs,cbs; 2355 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2356 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2357 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2358 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2359 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2360 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2361 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2362 } 2363 c = (Mat_SeqAIJ*)C->data; 2364 2365 /* loop over rows inserting into submatrix */ 2366 a_new = c->a; 2367 j_new = c->j; 2368 i_new = c->i; 2369 2370 for (i=0; i<nrows; i++) { 2371 ii = starts[i]; 2372 lensi = lens[i]; 2373 for (k=0; k<lensi; k++) { 2374 *j_new++ = aj[ii+k] - first; 2375 } 2376 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2377 a_new += lensi; 2378 i_new[i+1] = i_new[i] + lensi; 2379 c->ilen[i] = lensi; 2380 } 2381 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2382 } else { 2383 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2384 ierr = PetscMalloc(oldcols*sizeof(PetscInt),&smap);CHKERRQ(ierr); 2385 ierr = PetscMemzero(smap,oldcols*sizeof(PetscInt));CHKERRQ(ierr); 2386 ierr = PetscMalloc((1+nrows)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2387 for (i=0; i<ncols; i++) { 2388 #if defined(PETSC_USE_DEBUG) 2389 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); 2390 #endif 2391 smap[icol[i]] = i+1; 2392 } 2393 2394 /* determine lens of each row */ 2395 for (i=0; i<nrows; i++) { 2396 kstart = ai[irow[i]]; 2397 kend = kstart + a->ilen[irow[i]]; 2398 lens[i] = 0; 2399 for (k=kstart; k<kend; k++) { 2400 if (smap[aj[k]]) { 2401 lens[i]++; 2402 } 2403 } 2404 } 2405 /* Create and fill new matrix */ 2406 if (scall == MAT_REUSE_MATRIX) { 2407 PetscBool equal; 2408 2409 c = (Mat_SeqAIJ*)((*B)->data); 2410 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2411 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2412 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2413 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2414 C = *B; 2415 } else { 2416 PetscInt rbs,cbs; 2417 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2418 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2419 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2420 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2421 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2422 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2423 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2424 } 2425 c = (Mat_SeqAIJ*)(C->data); 2426 for (i=0; i<nrows; i++) { 2427 row = irow[i]; 2428 kstart = ai[row]; 2429 kend = kstart + a->ilen[row]; 2430 mat_i = c->i[i]; 2431 mat_j = c->j + mat_i; 2432 mat_a = c->a + mat_i; 2433 mat_ilen = c->ilen + i; 2434 for (k=kstart; k<kend; k++) { 2435 if ((tcol=smap[a->j[k]])) { 2436 *mat_j++ = tcol - 1; 2437 *mat_a++ = a->a[k]; 2438 (*mat_ilen)++; 2439 2440 } 2441 } 2442 } 2443 /* Free work space */ 2444 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2445 ierr = PetscFree(smap);CHKERRQ(ierr); 2446 ierr = PetscFree(lens);CHKERRQ(ierr); 2447 } 2448 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2449 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2450 2451 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2452 *B = C; 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 2458 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2459 { 2460 PetscErrorCode ierr; 2461 Mat B; 2462 2463 PetscFunctionBegin; 2464 if (scall == MAT_INITIAL_MATRIX) { 2465 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2466 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2467 ierr = MatSetBlockSizes(B,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2468 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2469 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2470 *subMat = B; 2471 } else { 2472 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2473 } 2474 PetscFunctionReturn(0); 2475 } 2476 2477 #undef __FUNCT__ 2478 #define __FUNCT__ "MatILUFactor_SeqAIJ" 2479 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2480 { 2481 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2482 PetscErrorCode ierr; 2483 Mat outA; 2484 PetscBool row_identity,col_identity; 2485 2486 PetscFunctionBegin; 2487 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2488 2489 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2490 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2491 2492 outA = inA; 2493 outA->factortype = MAT_FACTOR_LU; 2494 2495 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2496 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2497 2498 a->row = row; 2499 2500 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2501 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2502 2503 a->col = col; 2504 2505 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2506 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2507 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2508 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2509 2510 if (!a->solve_work) { /* this matrix may have been factored before */ 2511 ierr = PetscMalloc((inA->rmap->n+1)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); 2512 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2513 } 2514 2515 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2516 if (row_identity && col_identity) { 2517 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2518 } else { 2519 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2520 } 2521 PetscFunctionReturn(0); 2522 } 2523 2524 #undef __FUNCT__ 2525 #define __FUNCT__ "MatScale_SeqAIJ" 2526 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2527 { 2528 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2529 PetscScalar oalpha = alpha; 2530 PetscErrorCode ierr; 2531 PetscBLASInt one = 1,bnz; 2532 2533 PetscFunctionBegin; 2534 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2535 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2536 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2537 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2538 PetscFunctionReturn(0); 2539 } 2540 2541 #undef __FUNCT__ 2542 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 2543 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2544 { 2545 PetscErrorCode ierr; 2546 PetscInt i; 2547 2548 PetscFunctionBegin; 2549 if (scall == MAT_INITIAL_MATRIX) { 2550 ierr = PetscMalloc((n+1)*sizeof(Mat),B);CHKERRQ(ierr); 2551 } 2552 2553 for (i=0; i<n; i++) { 2554 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2555 } 2556 PetscFunctionReturn(0); 2557 } 2558 2559 #undef __FUNCT__ 2560 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 2561 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2562 { 2563 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2564 PetscErrorCode ierr; 2565 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2566 const PetscInt *idx; 2567 PetscInt start,end,*ai,*aj; 2568 PetscBT table; 2569 2570 PetscFunctionBegin; 2571 m = A->rmap->n; 2572 ai = a->i; 2573 aj = a->j; 2574 2575 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2576 2577 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&nidx);CHKERRQ(ierr); 2578 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2579 2580 for (i=0; i<is_max; i++) { 2581 /* Initialize the two local arrays */ 2582 isz = 0; 2583 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2584 2585 /* Extract the indices, assume there can be duplicate entries */ 2586 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2587 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2588 2589 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2590 for (j=0; j<n; ++j) { 2591 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2592 } 2593 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2594 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2595 2596 k = 0; 2597 for (j=0; j<ov; j++) { /* for each overlap */ 2598 n = isz; 2599 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2600 row = nidx[k]; 2601 start = ai[row]; 2602 end = ai[row+1]; 2603 for (l = start; l<end; l++) { 2604 val = aj[l]; 2605 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2606 } 2607 } 2608 } 2609 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2610 } 2611 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2612 ierr = PetscFree(nidx);CHKERRQ(ierr); 2613 PetscFunctionReturn(0); 2614 } 2615 2616 /* -------------------------------------------------------------- */ 2617 #undef __FUNCT__ 2618 #define __FUNCT__ "MatPermute_SeqAIJ" 2619 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2620 { 2621 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2622 PetscErrorCode ierr; 2623 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2624 const PetscInt *row,*col; 2625 PetscInt *cnew,j,*lens; 2626 IS icolp,irowp; 2627 PetscInt *cwork = NULL; 2628 PetscScalar *vwork = NULL; 2629 2630 PetscFunctionBegin; 2631 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2632 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2633 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2634 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2635 2636 /* determine lengths of permuted rows */ 2637 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2638 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2639 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2640 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2641 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2642 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2643 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2644 ierr = PetscFree(lens);CHKERRQ(ierr); 2645 2646 ierr = PetscMalloc(n*sizeof(PetscInt),&cnew);CHKERRQ(ierr); 2647 for (i=0; i<m; i++) { 2648 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2649 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2650 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2651 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2652 } 2653 ierr = PetscFree(cnew);CHKERRQ(ierr); 2654 2655 (*B)->assembled = PETSC_FALSE; 2656 2657 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2658 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2659 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2660 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2661 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2662 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2663 PetscFunctionReturn(0); 2664 } 2665 2666 #undef __FUNCT__ 2667 #define __FUNCT__ "MatCopy_SeqAIJ" 2668 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2669 { 2670 PetscErrorCode ierr; 2671 2672 PetscFunctionBegin; 2673 /* If the two matrices have the same copy implementation, use fast copy. */ 2674 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2675 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2676 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2677 2678 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"); 2679 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2680 } else { 2681 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2682 } 2683 PetscFunctionReturn(0); 2684 } 2685 2686 #undef __FUNCT__ 2687 #define __FUNCT__ "MatSetUp_SeqAIJ" 2688 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2689 { 2690 PetscErrorCode ierr; 2691 2692 PetscFunctionBegin; 2693 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2694 PetscFunctionReturn(0); 2695 } 2696 2697 #undef __FUNCT__ 2698 #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" 2699 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2700 { 2701 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2702 2703 PetscFunctionBegin; 2704 *array = a->a; 2705 PetscFunctionReturn(0); 2706 } 2707 2708 #undef __FUNCT__ 2709 #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" 2710 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2711 { 2712 PetscFunctionBegin; 2713 PetscFunctionReturn(0); 2714 } 2715 2716 /* Optimize MatFDColoringApply_AIJ() by using array den2sp to skip calling MatSetValues() */ 2717 /* #define JACOBIANCOLOROPT */ 2718 #if defined(JACOBIANCOLOROPT) 2719 #include <petsctime.h> 2720 #endif 2721 #undef __FUNCT__ 2722 #define __FUNCT__ "MatFDColoringApply_SeqAIJ" 2723 PetscErrorCode MatFDColoringApply_SeqAIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2724 { 2725 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2726 PetscErrorCode ierr; 2727 PetscInt k,l,row,col,N; 2728 PetscScalar dx,*y,*xx,*w3_array; 2729 PetscScalar *vscale_array; 2730 PetscReal epsilon=coloring->error_rel,umin = coloring->umin,unorm; 2731 Vec w1=coloring->w1,w2=coloring->w2,w3; 2732 void *fctx=coloring->fctx; 2733 PetscBool flg=PETSC_FALSE; 2734 Mat_SeqAIJ *csp=(Mat_SeqAIJ*)J->data; 2735 PetscScalar *ca=csp->a; 2736 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 2737 PetscInt *den2sp=coloring->den2sp,*idx; 2738 PetscInt **rows=coloring->rows,**columns=coloring->columns,ncolumns_k,nrows_k,**columnsforrow=coloring->columnsforrow; 2739 #if defined(JACOBIANCOLOROPT) 2740 PetscLogDouble t0,t1,time_setvalues=0.0; 2741 #endif 2742 2743 PetscFunctionBegin; 2744 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2745 ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2746 if (flg) { 2747 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2748 } else { 2749 PetscBool assembled; 2750 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2751 if (assembled) { 2752 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2753 } 2754 } 2755 2756 if (!coloring->vscale) { 2757 ierr = VecDuplicate(x1,&coloring->vscale);CHKERRQ(ierr); 2758 } 2759 2760 if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/ 2761 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 2762 } 2763 2764 /* Set w1 = F(x1) */ 2765 if (!coloring->fset) { 2766 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2767 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2768 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2769 } else { 2770 coloring->fset = PETSC_FALSE; 2771 } 2772 2773 if (!coloring->w3) { 2774 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2775 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2776 } 2777 w3 = coloring->w3; 2778 2779 /* Compute scale factors: vscale = 1./dx = 1./(epsilon*xx) */ 2780 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 2781 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2782 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2783 for (col=0; col<N; col++) { 2784 if (coloring->htype[0] == 'w') { 2785 dx = 1.0 + unorm; 2786 } else { 2787 dx = xx[col]; 2788 } 2789 if (dx == (PetscScalar)0.0) dx = 1.0; 2790 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2791 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2792 dx *= epsilon; 2793 //vscale_array[col] = (PetscScalar)1.0/dx; 2794 vscale_array[col] = (PetscScalar)dx; 2795 } 2796 2797 idx = den2sp; 2798 for (k=0; k<ncolors; k++) { /* loop over colors */ 2799 coloring->currentcolor = k; 2800 2801 /* 2802 Loop over each column associated with color 2803 adding the perturbation to the vector w3 = x1 + dx. 2804 */ 2805 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2806 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 2807 ncolumns_k = ncolumns[k]; 2808 for (l=0; l<ncolumns_k; l++) { /* loop over columns */ 2809 col = columns[k][l]; 2810 //w3_array[col] += 1/vscale_array[col]; 2811 w3_array[col] += vscale_array[col]; 2812 } 2813 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2814 2815 /* 2816 Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 2817 w2 = F(x1 + dx) - F(x1) 2818 */ 2819 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2820 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2821 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2822 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2823 2824 /* 2825 Loop over rows of vector, putting w2/dx into Jacobian matrix 2826 */ 2827 #if defined(JACOBIANCOLOROPT) 2828 ierr = PetscTime(&t0);CHKERRQ(ierr); 2829 #endif 2830 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2831 nrows_k = nrows[k]; 2832 for (l=0; l<nrows_k; l++) { /* loop over rows */ 2833 row = rows[k][l]; /* row index */ 2834 //y[row] *= vscale_array[columnsforrow[k][l]]; 2835 y[row] /= vscale_array[columnsforrow[k][l]]; 2836 ca[idx[l]] = y[row]; 2837 } 2838 idx += nrows_k; 2839 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2840 #if defined(JACOBIANCOLOROPT) 2841 ierr = PetscTime(&t1);CHKERRQ(ierr); 2842 time_setvalues += t1-t0; 2843 #endif 2844 } /* endof for each color */ 2845 #if defined(JACOBIANCOLOROPT) 2846 printf(" MatFDColoringApply_SeqAIJ: time_setvalues %g\n",time_setvalues); 2847 #endif 2848 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2849 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2850 2851 coloring->currentcolor = -1; 2852 PetscFunctionReturn(0); 2853 } 2854 /* --------------------------------------------------------*/ 2855 2856 #undef __FUNCT__ 2857 #define __FUNCT__ "MatFDColoringApply_SeqAIJ_old" 2858 PetscErrorCode MatFDColoringApply_SeqAIJ_old(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2859 { 2860 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2861 PetscErrorCode ierr; 2862 PetscInt k,N,start,end,l,row,col,srow,**vscaleforrow; 2863 PetscScalar dx,*y,*xx,*w3_array; 2864 PetscScalar *vscale_array; 2865 PetscReal epsilon = coloring->error_rel,umin = coloring->umin; 2866 Vec w1,w2,w3; 2867 void *fctx = coloring->fctx; 2868 PetscBool flg = PETSC_FALSE; 2869 2870 PetscFunctionBegin; 2871 printf("MatFDColoringApply_SeqAIJ ...\n"); 2872 if (!coloring->w1) { 2873 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 2874 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w1);CHKERRQ(ierr); 2875 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 2876 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w2);CHKERRQ(ierr); 2877 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2878 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2879 } 2880 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 2881 2882 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2883 ierr = PetscOptionsGetBool(((PetscObject)coloring)->prefix,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2884 if (flg) { 2885 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2886 } else { 2887 PetscBool assembled; 2888 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2889 if (assembled) { 2890 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2891 } 2892 } 2893 2894 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 2895 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2896 2897 if (!coloring->fset) { 2898 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2899 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2900 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2901 } else { 2902 coloring->fset = PETSC_FALSE; 2903 } 2904 2905 /* 2906 Compute all the scale factors and share with other processors 2907 */ 2908 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start; 2909 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start; 2910 for (k=0; k<coloring->ncolors; k++) { 2911 /* 2912 Loop over each column associated with color adding the 2913 perturbation to the vector w3. 2914 */ 2915 for (l=0; l<coloring->ncolumns[k]; l++) { 2916 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2917 dx = xx[col]; 2918 if (dx == 0.0) dx = 1.0; 2919 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2920 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2921 dx *= epsilon; 2922 vscale_array[col] = 1.0/dx; 2923 } 2924 } 2925 vscale_array = vscale_array + start; 2926 2927 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2928 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2929 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2930 2931 /* ierr = VecView(coloring->vscale,PETSC_VIEWER_STDOUT_WORLD); 2932 ierr = VecView(x1,PETSC_VIEWER_STDOUT_WORLD);*/ 2933 2934 if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow; 2935 else vscaleforrow = coloring->columnsforrow; 2936 2937 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2938 /* 2939 Loop over each color 2940 */ 2941 for (k=0; k<coloring->ncolors; k++) { 2942 coloring->currentcolor = k; 2943 2944 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2945 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start; 2946 /* 2947 Loop over each column associated with color adding the 2948 perturbation to the vector w3. 2949 */ 2950 for (l=0; l<coloring->ncolumns[k]; l++) { 2951 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2952 dx = xx[col]; 2953 if (dx == 0.0) dx = 1.0; 2954 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2955 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2956 dx *= epsilon; 2957 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 2958 w3_array[col] += dx; 2959 } 2960 w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2961 2962 /* 2963 Evaluate function at x1 + dx (here dx is a vector of perturbations) 2964 */ 2965 2966 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2967 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2968 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2969 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2970 2971 /* 2972 Loop over rows of vector, putting results into Jacobian matrix 2973 */ 2974 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2975 for (l=0; l<coloring->nrows[k]; l++) { 2976 row = coloring->rows[k][l]; 2977 col = coloring->columnsforrow[k][l]; 2978 y[row] *= vscale_array[vscaleforrow[k][l]]; 2979 srow = row + start; 2980 ierr = MatSetValues_SeqAIJ(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 2981 } 2982 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2983 } 2984 coloring->currentcolor = k; 2985 2986 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2987 xx = xx + start; 2988 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2989 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2990 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2991 PetscFunctionReturn(0); 2992 } 2993 2994 /* 2995 Computes the number of nonzeros per row needed for preallocation when X and Y 2996 have different nonzero structure. 2997 */ 2998 #undef __FUNCT__ 2999 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 3000 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 3001 { 3002 PetscInt i,m=Y->rmap->N; 3003 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 3004 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 3005 const PetscInt *xi = x->i,*yi = y->i; 3006 3007 PetscFunctionBegin; 3008 /* Set the number of nonzeros in the new matrix */ 3009 for (i=0; i<m; i++) { 3010 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 3011 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 3012 nnz[i] = 0; 3013 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 3014 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 3015 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 3016 nnz[i]++; 3017 } 3018 for (; k<nzy; k++) nnz[i]++; 3019 } 3020 PetscFunctionReturn(0); 3021 } 3022 3023 #undef __FUNCT__ 3024 #define __FUNCT__ "MatAXPY_SeqAIJ" 3025 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 3026 { 3027 PetscErrorCode ierr; 3028 PetscInt i; 3029 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 3030 PetscBLASInt one=1,bnz; 3031 3032 PetscFunctionBegin; 3033 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 3034 if (str == SAME_NONZERO_PATTERN) { 3035 PetscScalar alpha = a; 3036 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 3037 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 3038 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 3039 if (y->xtoy && y->XtoY != X) { 3040 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 3041 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 3042 } 3043 if (!y->xtoy) { /* get xtoy */ 3044 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 3045 y->XtoY = X; 3046 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 3047 } 3048 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 3049 ierr = PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %d/%d = %g\n",x->nz,y->nz,(double)(PetscReal)(x->nz)/(y->nz+1));CHKERRQ(ierr); 3050 } else { 3051 Mat B; 3052 PetscInt *nnz; 3053 ierr = PetscMalloc(Y->rmap->N*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 3054 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 3055 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 3056 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 3057 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 3058 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 3059 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 3060 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 3061 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 3062 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 3063 ierr = PetscFree(nnz);CHKERRQ(ierr); 3064 } 3065 PetscFunctionReturn(0); 3066 } 3067 3068 #undef __FUNCT__ 3069 #define __FUNCT__ "MatConjugate_SeqAIJ" 3070 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 3071 { 3072 #if defined(PETSC_USE_COMPLEX) 3073 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3074 PetscInt i,nz; 3075 PetscScalar *a; 3076 3077 PetscFunctionBegin; 3078 nz = aij->nz; 3079 a = aij->a; 3080 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3081 #else 3082 PetscFunctionBegin; 3083 #endif 3084 PetscFunctionReturn(0); 3085 } 3086 3087 #undef __FUNCT__ 3088 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 3089 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3090 { 3091 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3092 PetscErrorCode ierr; 3093 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3094 PetscReal atmp; 3095 PetscScalar *x; 3096 MatScalar *aa; 3097 3098 PetscFunctionBegin; 3099 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3100 aa = a->a; 3101 ai = a->i; 3102 aj = a->j; 3103 3104 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3105 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3106 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3107 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3108 for (i=0; i<m; i++) { 3109 ncols = ai[1] - ai[0]; ai++; 3110 x[i] = 0.0; 3111 for (j=0; j<ncols; j++) { 3112 atmp = PetscAbsScalar(*aa); 3113 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3114 aa++; aj++; 3115 } 3116 } 3117 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3118 PetscFunctionReturn(0); 3119 } 3120 3121 #undef __FUNCT__ 3122 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 3123 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3124 { 3125 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3126 PetscErrorCode ierr; 3127 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3128 PetscScalar *x; 3129 MatScalar *aa; 3130 3131 PetscFunctionBegin; 3132 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3133 aa = a->a; 3134 ai = a->i; 3135 aj = a->j; 3136 3137 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3138 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3139 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3140 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3141 for (i=0; i<m; i++) { 3142 ncols = ai[1] - ai[0]; ai++; 3143 if (ncols == A->cmap->n) { /* row is dense */ 3144 x[i] = *aa; if (idx) idx[i] = 0; 3145 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3146 x[i] = 0.0; 3147 if (idx) { 3148 idx[i] = 0; /* in case ncols is zero */ 3149 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3150 if (aj[j] > j) { 3151 idx[i] = j; 3152 break; 3153 } 3154 } 3155 } 3156 } 3157 for (j=0; j<ncols; j++) { 3158 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3159 aa++; aj++; 3160 } 3161 } 3162 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3163 PetscFunctionReturn(0); 3164 } 3165 3166 #undef __FUNCT__ 3167 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 3168 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3169 { 3170 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3171 PetscErrorCode ierr; 3172 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3173 PetscReal atmp; 3174 PetscScalar *x; 3175 MatScalar *aa; 3176 3177 PetscFunctionBegin; 3178 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3179 aa = a->a; 3180 ai = a->i; 3181 aj = a->j; 3182 3183 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3184 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3185 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3186 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); 3187 for (i=0; i<m; i++) { 3188 ncols = ai[1] - ai[0]; ai++; 3189 if (ncols) { 3190 /* Get first nonzero */ 3191 for (j = 0; j < ncols; j++) { 3192 atmp = PetscAbsScalar(aa[j]); 3193 if (atmp > 1.0e-12) { 3194 x[i] = atmp; 3195 if (idx) idx[i] = aj[j]; 3196 break; 3197 } 3198 } 3199 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3200 } else { 3201 x[i] = 0.0; if (idx) idx[i] = 0; 3202 } 3203 for (j = 0; j < ncols; j++) { 3204 atmp = PetscAbsScalar(*aa); 3205 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3206 aa++; aj++; 3207 } 3208 } 3209 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3210 PetscFunctionReturn(0); 3211 } 3212 3213 #undef __FUNCT__ 3214 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3215 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3216 { 3217 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3218 PetscErrorCode ierr; 3219 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3220 PetscScalar *x; 3221 MatScalar *aa; 3222 3223 PetscFunctionBegin; 3224 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3225 aa = a->a; 3226 ai = a->i; 3227 aj = a->j; 3228 3229 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3230 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3231 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3232 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3233 for (i=0; i<m; i++) { 3234 ncols = ai[1] - ai[0]; ai++; 3235 if (ncols == A->cmap->n) { /* row is dense */ 3236 x[i] = *aa; if (idx) idx[i] = 0; 3237 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3238 x[i] = 0.0; 3239 if (idx) { /* find first implicit 0.0 in the row */ 3240 idx[i] = 0; /* in case ncols is zero */ 3241 for (j=0; j<ncols; j++) { 3242 if (aj[j] > j) { 3243 idx[i] = j; 3244 break; 3245 } 3246 } 3247 } 3248 } 3249 for (j=0; j<ncols; j++) { 3250 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3251 aa++; aj++; 3252 } 3253 } 3254 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3255 PetscFunctionReturn(0); 3256 } 3257 3258 #include <petscblaslapack.h> 3259 #include <petsc-private/kernels/blockinvert.h> 3260 3261 #undef __FUNCT__ 3262 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3263 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3264 { 3265 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3266 PetscErrorCode ierr; 3267 PetscInt i,bs = A->rmap->bs,mbs = A->rmap->n/A->rmap->bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3268 MatScalar *diag,work[25],*v_work; 3269 PetscReal shift = 0.0; 3270 3271 PetscFunctionBegin; 3272 if (a->ibdiagvalid) { 3273 if (values) *values = a->ibdiag; 3274 PetscFunctionReturn(0); 3275 } 3276 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3277 if (!a->ibdiag) { 3278 ierr = PetscMalloc(bs2*mbs*sizeof(PetscScalar),&a->ibdiag);CHKERRQ(ierr); 3279 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3280 } 3281 diag = a->ibdiag; 3282 if (values) *values = a->ibdiag; 3283 /* factor and invert each block */ 3284 switch (bs) { 3285 case 1: 3286 for (i=0; i<mbs; i++) { 3287 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3288 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3289 } 3290 break; 3291 case 2: 3292 for (i=0; i<mbs; i++) { 3293 ij[0] = 2*i; ij[1] = 2*i + 1; 3294 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3295 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3296 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3297 diag += 4; 3298 } 3299 break; 3300 case 3: 3301 for (i=0; i<mbs; i++) { 3302 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3303 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3304 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3305 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3306 diag += 9; 3307 } 3308 break; 3309 case 4: 3310 for (i=0; i<mbs; i++) { 3311 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3312 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3313 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3314 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3315 diag += 16; 3316 } 3317 break; 3318 case 5: 3319 for (i=0; i<mbs; i++) { 3320 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3321 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3322 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3323 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3324 diag += 25; 3325 } 3326 break; 3327 case 6: 3328 for (i=0; i<mbs; i++) { 3329 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; 3330 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3331 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3332 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3333 diag += 36; 3334 } 3335 break; 3336 case 7: 3337 for (i=0; i<mbs; i++) { 3338 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; 3339 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3340 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3341 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3342 diag += 49; 3343 } 3344 break; 3345 default: 3346 ierr = PetscMalloc3(bs,MatScalar,&v_work,bs,PetscInt,&v_pivots,bs,PetscInt,&IJ);CHKERRQ(ierr); 3347 for (i=0; i<mbs; i++) { 3348 for (j=0; j<bs; j++) { 3349 IJ[j] = bs*i + j; 3350 } 3351 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3352 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3353 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3354 diag += bs2; 3355 } 3356 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3357 } 3358 a->ibdiagvalid = PETSC_TRUE; 3359 PetscFunctionReturn(0); 3360 } 3361 3362 #undef __FUNCT__ 3363 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3364 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3365 { 3366 PetscErrorCode ierr; 3367 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3368 PetscScalar a; 3369 PetscInt m,n,i,j,col; 3370 3371 PetscFunctionBegin; 3372 if (!x->assembled) { 3373 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3374 for (i=0; i<m; i++) { 3375 for (j=0; j<aij->imax[i]; j++) { 3376 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3377 col = (PetscInt)(n*PetscRealPart(a)); 3378 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3379 } 3380 } 3381 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3382 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3383 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3384 PetscFunctionReturn(0); 3385 } 3386 3387 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3388 /* -------------------------------------------------------------------*/ 3389 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3390 MatGetRow_SeqAIJ, 3391 MatRestoreRow_SeqAIJ, 3392 MatMult_SeqAIJ, 3393 /* 4*/ MatMultAdd_SeqAIJ, 3394 MatMultTranspose_SeqAIJ, 3395 MatMultTransposeAdd_SeqAIJ, 3396 0, 3397 0, 3398 0, 3399 /* 10*/ 0, 3400 MatLUFactor_SeqAIJ, 3401 0, 3402 MatSOR_SeqAIJ, 3403 MatTranspose_SeqAIJ, 3404 /*1 5*/ MatGetInfo_SeqAIJ, 3405 MatEqual_SeqAIJ, 3406 MatGetDiagonal_SeqAIJ, 3407 MatDiagonalScale_SeqAIJ, 3408 MatNorm_SeqAIJ, 3409 /* 20*/ 0, 3410 MatAssemblyEnd_SeqAIJ, 3411 MatSetOption_SeqAIJ, 3412 MatZeroEntries_SeqAIJ, 3413 /* 24*/ MatZeroRows_SeqAIJ, 3414 0, 3415 0, 3416 0, 3417 0, 3418 /* 29*/ MatSetUp_SeqAIJ, 3419 0, 3420 0, 3421 0, 3422 0, 3423 /* 34*/ MatDuplicate_SeqAIJ, 3424 0, 3425 0, 3426 MatILUFactor_SeqAIJ, 3427 0, 3428 /* 39*/ MatAXPY_SeqAIJ, 3429 MatGetSubMatrices_SeqAIJ, 3430 MatIncreaseOverlap_SeqAIJ, 3431 MatGetValues_SeqAIJ, 3432 MatCopy_SeqAIJ, 3433 /* 44*/ MatGetRowMax_SeqAIJ, 3434 MatScale_SeqAIJ, 3435 0, 3436 MatDiagonalSet_SeqAIJ, 3437 MatZeroRowsColumns_SeqAIJ, 3438 /* 49*/ MatSetRandom_SeqAIJ, 3439 MatGetRowIJ_SeqAIJ, 3440 MatRestoreRowIJ_SeqAIJ, 3441 MatGetColumnIJ_SeqAIJ, 3442 MatRestoreColumnIJ_SeqAIJ, 3443 /* 54*/ MatFDColoringCreate_SeqAIJ, 3444 0, 3445 0, 3446 MatPermute_SeqAIJ, 3447 0, 3448 /* 59*/ 0, 3449 MatDestroy_SeqAIJ, 3450 MatView_SeqAIJ, 3451 0, 3452 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3453 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3454 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3455 0, 3456 0, 3457 0, 3458 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3459 MatGetRowMinAbs_SeqAIJ, 3460 0, 3461 MatSetColoring_SeqAIJ, 3462 0, 3463 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3464 MatFDColoringApply_AIJ, 3465 0, 3466 0, 3467 0, 3468 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3469 0, 3470 0, 3471 0, 3472 MatLoad_SeqAIJ, 3473 /* 84*/ MatIsSymmetric_SeqAIJ, 3474 MatIsHermitian_SeqAIJ, 3475 0, 3476 0, 3477 0, 3478 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3479 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3480 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3481 MatPtAP_SeqAIJ_SeqAIJ, 3482 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3483 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3484 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3485 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3486 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3487 0, 3488 /* 99*/ 0, 3489 0, 3490 0, 3491 MatConjugate_SeqAIJ, 3492 0, 3493 /*104*/ MatSetValuesRow_SeqAIJ, 3494 MatRealPart_SeqAIJ, 3495 MatImaginaryPart_SeqAIJ, 3496 0, 3497 0, 3498 /*109*/ MatMatSolve_SeqAIJ, 3499 0, 3500 MatGetRowMin_SeqAIJ, 3501 0, 3502 MatMissingDiagonal_SeqAIJ, 3503 /*114*/ 0, 3504 0, 3505 0, 3506 0, 3507 0, 3508 /*119*/ 0, 3509 0, 3510 0, 3511 0, 3512 MatGetMultiProcBlock_SeqAIJ, 3513 /*124*/ MatFindNonzeroRows_SeqAIJ, 3514 MatGetColumnNorms_SeqAIJ, 3515 MatInvertBlockDiagonal_SeqAIJ, 3516 0, 3517 0, 3518 /*129*/ 0, 3519 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3520 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3521 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3522 MatTransposeColoringCreate_SeqAIJ, 3523 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3524 MatTransColoringApplyDenToSp_SeqAIJ, 3525 MatRARt_SeqAIJ_SeqAIJ, 3526 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3527 MatRARtNumeric_SeqAIJ_SeqAIJ, 3528 /*139*/0, 3529 0 3530 }; 3531 3532 #undef __FUNCT__ 3533 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3534 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3535 { 3536 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3537 PetscInt i,nz,n; 3538 3539 PetscFunctionBegin; 3540 nz = aij->maxnz; 3541 n = mat->rmap->n; 3542 for (i=0; i<nz; i++) { 3543 aij->j[i] = indices[i]; 3544 } 3545 aij->nz = nz; 3546 for (i=0; i<n; i++) { 3547 aij->ilen[i] = aij->imax[i]; 3548 } 3549 PetscFunctionReturn(0); 3550 } 3551 3552 #undef __FUNCT__ 3553 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3554 /*@ 3555 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3556 in the matrix. 3557 3558 Input Parameters: 3559 + mat - the SeqAIJ matrix 3560 - indices - the column indices 3561 3562 Level: advanced 3563 3564 Notes: 3565 This can be called if you have precomputed the nonzero structure of the 3566 matrix and want to provide it to the matrix object to improve the performance 3567 of the MatSetValues() operation. 3568 3569 You MUST have set the correct numbers of nonzeros per row in the call to 3570 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3571 3572 MUST be called before any calls to MatSetValues(); 3573 3574 The indices should start with zero, not one. 3575 3576 @*/ 3577 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3578 { 3579 PetscErrorCode ierr; 3580 3581 PetscFunctionBegin; 3582 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3583 PetscValidPointer(indices,2); 3584 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3585 PetscFunctionReturn(0); 3586 } 3587 3588 /* ----------------------------------------------------------------------------------------*/ 3589 3590 #undef __FUNCT__ 3591 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3592 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3593 { 3594 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3595 PetscErrorCode ierr; 3596 size_t nz = aij->i[mat->rmap->n]; 3597 3598 PetscFunctionBegin; 3599 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3600 3601 /* allocate space for values if not already there */ 3602 if (!aij->saved_values) { 3603 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 3604 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3605 } 3606 3607 /* copy values over */ 3608 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3609 PetscFunctionReturn(0); 3610 } 3611 3612 #undef __FUNCT__ 3613 #define __FUNCT__ "MatStoreValues" 3614 /*@ 3615 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3616 example, reuse of the linear part of a Jacobian, while recomputing the 3617 nonlinear portion. 3618 3619 Collect on Mat 3620 3621 Input Parameters: 3622 . mat - the matrix (currently only AIJ matrices support this option) 3623 3624 Level: advanced 3625 3626 Common Usage, with SNESSolve(): 3627 $ Create Jacobian matrix 3628 $ Set linear terms into matrix 3629 $ Apply boundary conditions to matrix, at this time matrix must have 3630 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3631 $ boundary conditions again will not change the nonzero structure 3632 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3633 $ ierr = MatStoreValues(mat); 3634 $ Call SNESSetJacobian() with matrix 3635 $ In your Jacobian routine 3636 $ ierr = MatRetrieveValues(mat); 3637 $ Set nonlinear terms in matrix 3638 3639 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3640 $ // build linear portion of Jacobian 3641 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3642 $ ierr = MatStoreValues(mat); 3643 $ loop over nonlinear iterations 3644 $ ierr = MatRetrieveValues(mat); 3645 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3646 $ // call MatAssemblyBegin/End() on matrix 3647 $ Solve linear system with Jacobian 3648 $ endloop 3649 3650 Notes: 3651 Matrix must already be assemblied before calling this routine 3652 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3653 calling this routine. 3654 3655 When this is called multiple times it overwrites the previous set of stored values 3656 and does not allocated additional space. 3657 3658 .seealso: MatRetrieveValues() 3659 3660 @*/ 3661 PetscErrorCode MatStoreValues(Mat mat) 3662 { 3663 PetscErrorCode ierr; 3664 3665 PetscFunctionBegin; 3666 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3667 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3668 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3669 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3670 PetscFunctionReturn(0); 3671 } 3672 3673 #undef __FUNCT__ 3674 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3675 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3676 { 3677 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3678 PetscErrorCode ierr; 3679 PetscInt nz = aij->i[mat->rmap->n]; 3680 3681 PetscFunctionBegin; 3682 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3683 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3684 /* copy values over */ 3685 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3686 PetscFunctionReturn(0); 3687 } 3688 3689 #undef __FUNCT__ 3690 #define __FUNCT__ "MatRetrieveValues" 3691 /*@ 3692 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3693 example, reuse of the linear part of a Jacobian, while recomputing the 3694 nonlinear portion. 3695 3696 Collect on Mat 3697 3698 Input Parameters: 3699 . mat - the matrix (currently on AIJ matrices support this option) 3700 3701 Level: advanced 3702 3703 .seealso: MatStoreValues() 3704 3705 @*/ 3706 PetscErrorCode MatRetrieveValues(Mat mat) 3707 { 3708 PetscErrorCode ierr; 3709 3710 PetscFunctionBegin; 3711 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3712 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3713 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3714 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3715 PetscFunctionReturn(0); 3716 } 3717 3718 3719 /* --------------------------------------------------------------------------------*/ 3720 #undef __FUNCT__ 3721 #define __FUNCT__ "MatCreateSeqAIJ" 3722 /*@C 3723 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3724 (the default parallel PETSc format). For good matrix assembly performance 3725 the user should preallocate the matrix storage by setting the parameter nz 3726 (or the array nnz). By setting these parameters accurately, performance 3727 during matrix assembly can be increased by more than a factor of 50. 3728 3729 Collective on MPI_Comm 3730 3731 Input Parameters: 3732 + comm - MPI communicator, set to PETSC_COMM_SELF 3733 . m - number of rows 3734 . n - number of columns 3735 . nz - number of nonzeros per row (same for all rows) 3736 - nnz - array containing the number of nonzeros in the various rows 3737 (possibly different for each row) or NULL 3738 3739 Output Parameter: 3740 . A - the matrix 3741 3742 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3743 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3744 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3745 3746 Notes: 3747 If nnz is given then nz is ignored 3748 3749 The AIJ format (also called the Yale sparse matrix format or 3750 compressed row storage), is fully compatible with standard Fortran 77 3751 storage. That is, the stored row and column indices can begin at 3752 either one (as in Fortran) or zero. See the users' manual for details. 3753 3754 Specify the preallocated storage with either nz or nnz (not both). 3755 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3756 allocation. For large problems you MUST preallocate memory or you 3757 will get TERRIBLE performance, see the users' manual chapter on matrices. 3758 3759 By default, this format uses inodes (identical nodes) when possible, to 3760 improve numerical efficiency of matrix-vector products and solves. We 3761 search for consecutive rows with the same nonzero structure, thereby 3762 reusing matrix information to achieve increased efficiency. 3763 3764 Options Database Keys: 3765 + -mat_no_inode - Do not use inodes 3766 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3767 3768 Level: intermediate 3769 3770 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3771 3772 @*/ 3773 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3774 { 3775 PetscErrorCode ierr; 3776 3777 PetscFunctionBegin; 3778 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3779 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3780 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3781 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3782 PetscFunctionReturn(0); 3783 } 3784 3785 #undef __FUNCT__ 3786 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3787 /*@C 3788 MatSeqAIJSetPreallocation - For good matrix assembly performance 3789 the user should preallocate the matrix storage by setting the parameter nz 3790 (or the array nnz). By setting these parameters accurately, performance 3791 during matrix assembly can be increased by more than a factor of 50. 3792 3793 Collective on MPI_Comm 3794 3795 Input Parameters: 3796 + B - The matrix-free 3797 . nz - number of nonzeros per row (same for all rows) 3798 - nnz - array containing the number of nonzeros in the various rows 3799 (possibly different for each row) or NULL 3800 3801 Notes: 3802 If nnz is given then nz is ignored 3803 3804 The AIJ format (also called the Yale sparse matrix format or 3805 compressed row storage), is fully compatible with standard Fortran 77 3806 storage. That is, the stored row and column indices can begin at 3807 either one (as in Fortran) or zero. See the users' manual for details. 3808 3809 Specify the preallocated storage with either nz or nnz (not both). 3810 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3811 allocation. For large problems you MUST preallocate memory or you 3812 will get TERRIBLE performance, see the users' manual chapter on matrices. 3813 3814 You can call MatGetInfo() to get information on how effective the preallocation was; 3815 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3816 You can also run with the option -info and look for messages with the string 3817 malloc in them to see if additional memory allocation was needed. 3818 3819 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3820 entries or columns indices 3821 3822 By default, this format uses inodes (identical nodes) when possible, to 3823 improve numerical efficiency of matrix-vector products and solves. We 3824 search for consecutive rows with the same nonzero structure, thereby 3825 reusing matrix information to achieve increased efficiency. 3826 3827 Options Database Keys: 3828 + -mat_no_inode - Do not use inodes 3829 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3830 - -mat_aij_oneindex - Internally use indexing starting at 1 3831 rather than 0. Note that when calling MatSetValues(), 3832 the user still MUST index entries starting at 0! 3833 3834 Level: intermediate 3835 3836 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3837 3838 @*/ 3839 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3840 { 3841 PetscErrorCode ierr; 3842 3843 PetscFunctionBegin; 3844 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3845 PetscValidType(B,1); 3846 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3847 PetscFunctionReturn(0); 3848 } 3849 3850 #undef __FUNCT__ 3851 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3852 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3853 { 3854 Mat_SeqAIJ *b; 3855 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3856 PetscErrorCode ierr; 3857 PetscInt i; 3858 3859 PetscFunctionBegin; 3860 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3861 if (nz == MAT_SKIP_ALLOCATION) { 3862 skipallocation = PETSC_TRUE; 3863 nz = 0; 3864 } 3865 3866 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3867 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3868 3869 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3870 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3871 if (nnz) { 3872 for (i=0; i<B->rmap->n; i++) { 3873 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]); 3874 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); 3875 } 3876 } 3877 3878 B->preallocated = PETSC_TRUE; 3879 3880 b = (Mat_SeqAIJ*)B->data; 3881 3882 if (!skipallocation) { 3883 if (!b->imax) { 3884 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3885 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3886 } 3887 if (!nnz) { 3888 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3889 else if (nz < 0) nz = 1; 3890 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3891 nz = nz*B->rmap->n; 3892 } else { 3893 nz = 0; 3894 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3895 } 3896 /* b->ilen will count nonzeros in each row so far. */ 3897 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3898 3899 /* allocate the matrix space */ 3900 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3901 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3902 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3903 b->i[0] = 0; 3904 for (i=1; i<B->rmap->n+1; i++) { 3905 b->i[i] = b->i[i-1] + b->imax[i-1]; 3906 } 3907 b->singlemalloc = PETSC_TRUE; 3908 b->free_a = PETSC_TRUE; 3909 b->free_ij = PETSC_TRUE; 3910 #if defined(PETSC_THREADCOMM_ACTIVE) 3911 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3912 #endif 3913 } else { 3914 b->free_a = PETSC_FALSE; 3915 b->free_ij = PETSC_FALSE; 3916 } 3917 3918 b->nz = 0; 3919 b->maxnz = nz; 3920 B->info.nz_unneeded = (double)b->maxnz; 3921 if (realalloc) { 3922 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3923 } 3924 PetscFunctionReturn(0); 3925 } 3926 3927 #undef __FUNCT__ 3928 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3929 /*@ 3930 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3931 3932 Input Parameters: 3933 + B - the matrix 3934 . i - the indices into j for the start of each row (starts with zero) 3935 . j - the column indices for each row (starts with zero) these must be sorted for each row 3936 - v - optional values in the matrix 3937 3938 Level: developer 3939 3940 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3941 3942 .keywords: matrix, aij, compressed row, sparse, sequential 3943 3944 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3945 @*/ 3946 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3947 { 3948 PetscErrorCode ierr; 3949 3950 PetscFunctionBegin; 3951 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3952 PetscValidType(B,1); 3953 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3954 PetscFunctionReturn(0); 3955 } 3956 3957 #undef __FUNCT__ 3958 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3959 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3960 { 3961 PetscInt i; 3962 PetscInt m,n; 3963 PetscInt nz; 3964 PetscInt *nnz, nz_max = 0; 3965 PetscScalar *values; 3966 PetscErrorCode ierr; 3967 3968 PetscFunctionBegin; 3969 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3970 3971 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3972 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3973 3974 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3975 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 3976 for (i = 0; i < m; i++) { 3977 nz = Ii[i+1]- Ii[i]; 3978 nz_max = PetscMax(nz_max, nz); 3979 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3980 nnz[i] = nz; 3981 } 3982 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3983 ierr = PetscFree(nnz);CHKERRQ(ierr); 3984 3985 if (v) { 3986 values = (PetscScalar*) v; 3987 } else { 3988 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 3989 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3990 } 3991 3992 for (i = 0; i < m; i++) { 3993 nz = Ii[i+1] - Ii[i]; 3994 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3995 } 3996 3997 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3998 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3999 4000 if (!v) { 4001 ierr = PetscFree(values);CHKERRQ(ierr); 4002 } 4003 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4004 PetscFunctionReturn(0); 4005 } 4006 4007 #include <../src/mat/impls/dense/seq/dense.h> 4008 #include <petsc-private/kernels/petscaxpy.h> 4009 4010 #undef __FUNCT__ 4011 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 4012 /* 4013 Computes (B'*A')' since computing B*A directly is untenable 4014 4015 n p p 4016 ( ) ( ) ( ) 4017 m ( A ) * n ( B ) = m ( C ) 4018 ( ) ( ) ( ) 4019 4020 */ 4021 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4022 { 4023 PetscErrorCode ierr; 4024 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4025 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4026 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4027 PetscInt i,n,m,q,p; 4028 const PetscInt *ii,*idx; 4029 const PetscScalar *b,*a,*a_q; 4030 PetscScalar *c,*c_q; 4031 4032 PetscFunctionBegin; 4033 m = A->rmap->n; 4034 n = A->cmap->n; 4035 p = B->cmap->n; 4036 a = sub_a->v; 4037 b = sub_b->a; 4038 c = sub_c->v; 4039 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 4040 4041 ii = sub_b->i; 4042 idx = sub_b->j; 4043 for (i=0; i<n; i++) { 4044 q = ii[i+1] - ii[i]; 4045 while (q-->0) { 4046 c_q = c + m*(*idx); 4047 a_q = a + m*i; 4048 PetscKernelAXPY(c_q,*b,a_q,m); 4049 idx++; 4050 b++; 4051 } 4052 } 4053 PetscFunctionReturn(0); 4054 } 4055 4056 #undef __FUNCT__ 4057 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 4058 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4059 { 4060 PetscErrorCode ierr; 4061 PetscInt m=A->rmap->n,n=B->cmap->n; 4062 Mat Cmat; 4063 4064 PetscFunctionBegin; 4065 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); 4066 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4067 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4068 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 4069 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4070 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4071 4072 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4073 4074 *C = Cmat; 4075 PetscFunctionReturn(0); 4076 } 4077 4078 /* ----------------------------------------------------------------*/ 4079 #undef __FUNCT__ 4080 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 4081 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4082 { 4083 PetscErrorCode ierr; 4084 4085 PetscFunctionBegin; 4086 if (scall == MAT_INITIAL_MATRIX) { 4087 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4088 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4089 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4090 } 4091 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4092 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4093 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4094 PetscFunctionReturn(0); 4095 } 4096 4097 4098 /*MC 4099 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4100 based on compressed sparse row format. 4101 4102 Options Database Keys: 4103 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4104 4105 Level: beginner 4106 4107 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4108 M*/ 4109 4110 /*MC 4111 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4112 4113 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4114 and MATMPIAIJ otherwise. As a result, for single process communicators, 4115 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 4116 for communicators controlling multiple processes. It is recommended that you call both of 4117 the above preallocation routines for simplicity. 4118 4119 Options Database Keys: 4120 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4121 4122 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 4123 enough exist. 4124 4125 Level: beginner 4126 4127 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4128 M*/ 4129 4130 /*MC 4131 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4132 4133 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4134 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4135 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4136 for communicators controlling multiple processes. It is recommended that you call both of 4137 the above preallocation routines for simplicity. 4138 4139 Options Database Keys: 4140 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4141 4142 Level: beginner 4143 4144 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4145 M*/ 4146 4147 #if defined(PETSC_HAVE_PASTIX) 4148 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 4149 #endif 4150 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4151 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 4152 #endif 4153 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4154 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 4155 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 4156 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 4157 #if defined(PETSC_HAVE_MUMPS) 4158 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 4159 #endif 4160 #if defined(PETSC_HAVE_SUPERLU) 4161 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 4162 #endif 4163 #if defined(PETSC_HAVE_SUPERLU_DIST) 4164 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 4165 #endif 4166 #if defined(PETSC_HAVE_UMFPACK) 4167 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 4168 #endif 4169 #if defined(PETSC_HAVE_CHOLMOD) 4170 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 4171 #endif 4172 #if defined(PETSC_HAVE_LUSOL) 4173 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 4174 #endif 4175 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4176 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 4177 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 4178 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 4179 #endif 4180 #if defined(PETSC_HAVE_CLIQUE) 4181 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 4182 #endif 4183 4184 4185 #undef __FUNCT__ 4186 #define __FUNCT__ "MatSeqAIJGetArray" 4187 /*@C 4188 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 4189 4190 Not Collective 4191 4192 Input Parameter: 4193 . mat - a MATSEQDENSE matrix 4194 4195 Output Parameter: 4196 . array - pointer to the data 4197 4198 Level: intermediate 4199 4200 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4201 @*/ 4202 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4203 { 4204 PetscErrorCode ierr; 4205 4206 PetscFunctionBegin; 4207 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4208 PetscFunctionReturn(0); 4209 } 4210 4211 #undef __FUNCT__ 4212 #define __FUNCT__ "MatSeqAIJRestoreArray" 4213 /*@C 4214 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4215 4216 Not Collective 4217 4218 Input Parameters: 4219 . mat - a MATSEQDENSE matrix 4220 . array - pointer to the data 4221 4222 Level: intermediate 4223 4224 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4225 @*/ 4226 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4227 { 4228 PetscErrorCode ierr; 4229 4230 PetscFunctionBegin; 4231 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4232 PetscFunctionReturn(0); 4233 } 4234 4235 #undef __FUNCT__ 4236 #define __FUNCT__ "MatCreate_SeqAIJ" 4237 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4238 { 4239 Mat_SeqAIJ *b; 4240 PetscErrorCode ierr; 4241 PetscMPIInt size; 4242 4243 PetscFunctionBegin; 4244 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4245 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4246 4247 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 4248 4249 B->data = (void*)b; 4250 4251 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4252 4253 b->row = 0; 4254 b->col = 0; 4255 b->icol = 0; 4256 b->reallocs = 0; 4257 b->ignorezeroentries = PETSC_FALSE; 4258 b->roworiented = PETSC_TRUE; 4259 b->nonew = 0; 4260 b->diag = 0; 4261 b->solve_work = 0; 4262 B->spptr = 0; 4263 b->saved_values = 0; 4264 b->idiag = 0; 4265 b->mdiag = 0; 4266 b->ssor_work = 0; 4267 b->omega = 1.0; 4268 b->fshift = 0.0; 4269 b->idiagvalid = PETSC_FALSE; 4270 b->ibdiagvalid = PETSC_FALSE; 4271 b->keepnonzeropattern = PETSC_FALSE; 4272 b->xtoy = 0; 4273 b->XtoY = 0; 4274 B->same_nonzero = PETSC_FALSE; 4275 4276 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4277 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4278 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4279 4280 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4281 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4282 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4283 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4284 #endif 4285 #if defined(PETSC_HAVE_PASTIX) 4286 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4287 #endif 4288 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4289 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4290 #endif 4291 #if defined(PETSC_HAVE_SUPERLU) 4292 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4293 #endif 4294 #if defined(PETSC_HAVE_SUPERLU_DIST) 4295 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4296 #endif 4297 #if defined(PETSC_HAVE_MUMPS) 4298 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4299 #endif 4300 #if defined(PETSC_HAVE_UMFPACK) 4301 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4302 #endif 4303 #if defined(PETSC_HAVE_CHOLMOD) 4304 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4305 #endif 4306 #if defined(PETSC_HAVE_LUSOL) 4307 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4308 #endif 4309 #if defined(PETSC_HAVE_CLIQUE) 4310 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4311 #endif 4312 4313 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4314 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4315 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4316 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4317 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4318 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4319 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4320 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4321 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4322 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4323 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4324 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4325 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4326 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4327 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4328 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4329 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4330 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4331 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4332 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4333 PetscFunctionReturn(0); 4334 } 4335 4336 #undef __FUNCT__ 4337 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4338 /* 4339 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4340 */ 4341 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4342 { 4343 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4344 PetscErrorCode ierr; 4345 PetscInt i,m = A->rmap->n; 4346 4347 PetscFunctionBegin; 4348 c = (Mat_SeqAIJ*)C->data; 4349 4350 C->factortype = A->factortype; 4351 c->row = 0; 4352 c->col = 0; 4353 c->icol = 0; 4354 c->reallocs = 0; 4355 4356 C->assembled = PETSC_TRUE; 4357 4358 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4359 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4360 4361 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 4362 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4363 for (i=0; i<m; i++) { 4364 c->imax[i] = a->imax[i]; 4365 c->ilen[i] = a->ilen[i]; 4366 } 4367 4368 /* allocate the matrix space */ 4369 if (mallocmatspace) { 4370 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 4371 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4372 4373 c->singlemalloc = PETSC_TRUE; 4374 4375 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4376 if (m > 0) { 4377 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4378 if (cpvalues == MAT_COPY_VALUES) { 4379 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4380 } else { 4381 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4382 } 4383 } 4384 } 4385 4386 c->ignorezeroentries = a->ignorezeroentries; 4387 c->roworiented = a->roworiented; 4388 c->nonew = a->nonew; 4389 if (a->diag) { 4390 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 4391 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4392 for (i=0; i<m; i++) { 4393 c->diag[i] = a->diag[i]; 4394 } 4395 } else c->diag = 0; 4396 4397 c->solve_work = 0; 4398 c->saved_values = 0; 4399 c->idiag = 0; 4400 c->ssor_work = 0; 4401 c->keepnonzeropattern = a->keepnonzeropattern; 4402 c->free_a = PETSC_TRUE; 4403 c->free_ij = PETSC_TRUE; 4404 c->xtoy = 0; 4405 c->XtoY = 0; 4406 4407 c->rmax = a->rmax; 4408 c->nz = a->nz; 4409 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4410 C->preallocated = PETSC_TRUE; 4411 4412 c->compressedrow.use = a->compressedrow.use; 4413 c->compressedrow.nrows = a->compressedrow.nrows; 4414 c->compressedrow.check = a->compressedrow.check; 4415 if (a->compressedrow.use) { 4416 i = a->compressedrow.nrows; 4417 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 4418 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4419 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4420 } else { 4421 c->compressedrow.use = PETSC_FALSE; 4422 c->compressedrow.i = NULL; 4423 c->compressedrow.rindex = NULL; 4424 } 4425 C->same_nonzero = A->same_nonzero; 4426 4427 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4428 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4429 PetscFunctionReturn(0); 4430 } 4431 4432 #undef __FUNCT__ 4433 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4434 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4435 { 4436 PetscErrorCode ierr; 4437 4438 PetscFunctionBegin; 4439 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4440 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4441 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4442 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4443 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4444 PetscFunctionReturn(0); 4445 } 4446 4447 #undef __FUNCT__ 4448 #define __FUNCT__ "MatLoad_SeqAIJ" 4449 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4450 { 4451 Mat_SeqAIJ *a; 4452 PetscErrorCode ierr; 4453 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4454 int fd; 4455 PetscMPIInt size; 4456 MPI_Comm comm; 4457 PetscInt bs = 1; 4458 4459 PetscFunctionBegin; 4460 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4461 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4462 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4463 4464 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4465 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4466 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4467 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4468 4469 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4470 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4471 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4472 M = header[1]; N = header[2]; nz = header[3]; 4473 4474 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4475 4476 /* read in row lengths */ 4477 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 4478 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4479 4480 /* check if sum of rowlengths is same as nz */ 4481 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4482 if (sum != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_READ,"Inconsistant matrix data in file. no-nonzeros = %d, sum-row-lengths = %d\n",nz,sum); 4483 4484 /* set global size if not set already*/ 4485 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4486 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4487 } else { 4488 /* if sizes and type are already set, check if the vector global sizes are correct */ 4489 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4490 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4491 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4492 } 4493 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); 4494 } 4495 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4496 a = (Mat_SeqAIJ*)newMat->data; 4497 4498 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4499 4500 /* read in nonzero values */ 4501 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4502 4503 /* set matrix "i" values */ 4504 a->i[0] = 0; 4505 for (i=1; i<= M; i++) { 4506 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4507 a->ilen[i-1] = rowlengths[i-1]; 4508 } 4509 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4510 4511 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4512 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4513 PetscFunctionReturn(0); 4514 } 4515 4516 #undef __FUNCT__ 4517 #define __FUNCT__ "MatEqual_SeqAIJ" 4518 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4519 { 4520 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4521 PetscErrorCode ierr; 4522 #if defined(PETSC_USE_COMPLEX) 4523 PetscInt k; 4524 #endif 4525 4526 PetscFunctionBegin; 4527 /* If the matrix dimensions are not equal,or no of nonzeros */ 4528 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4529 *flg = PETSC_FALSE; 4530 PetscFunctionReturn(0); 4531 } 4532 4533 /* if the a->i are the same */ 4534 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4535 if (!*flg) PetscFunctionReturn(0); 4536 4537 /* if a->j are the same */ 4538 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4539 if (!*flg) PetscFunctionReturn(0); 4540 4541 /* if a->a are the same */ 4542 #if defined(PETSC_USE_COMPLEX) 4543 for (k=0; k<a->nz; k++) { 4544 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4545 *flg = PETSC_FALSE; 4546 PetscFunctionReturn(0); 4547 } 4548 } 4549 #else 4550 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4551 #endif 4552 PetscFunctionReturn(0); 4553 } 4554 4555 #undef __FUNCT__ 4556 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4557 /*@ 4558 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4559 provided by the user. 4560 4561 Collective on MPI_Comm 4562 4563 Input Parameters: 4564 + comm - must be an MPI communicator of size 1 4565 . m - number of rows 4566 . n - number of columns 4567 . i - row indices 4568 . j - column indices 4569 - a - matrix values 4570 4571 Output Parameter: 4572 . mat - the matrix 4573 4574 Level: intermediate 4575 4576 Notes: 4577 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4578 once the matrix is destroyed and not before 4579 4580 You cannot set new nonzero locations into this matrix, that will generate an error. 4581 4582 The i and j indices are 0 based 4583 4584 The format which is used for the sparse matrix input, is equivalent to a 4585 row-major ordering.. i.e for the following matrix, the input data expected is 4586 as shown: 4587 4588 1 0 0 4589 2 0 3 4590 4 5 6 4591 4592 i = {0,1,3,6} [size = nrow+1 = 3+1] 4593 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4594 v = {1,2,3,4,5,6} [size = nz = 6] 4595 4596 4597 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4598 4599 @*/ 4600 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4601 { 4602 PetscErrorCode ierr; 4603 PetscInt ii; 4604 Mat_SeqAIJ *aij; 4605 #if defined(PETSC_USE_DEBUG) 4606 PetscInt jj; 4607 #endif 4608 4609 PetscFunctionBegin; 4610 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4611 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4612 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4613 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4614 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4615 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4616 aij = (Mat_SeqAIJ*)(*mat)->data; 4617 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 4618 4619 aij->i = i; 4620 aij->j = j; 4621 aij->a = a; 4622 aij->singlemalloc = PETSC_FALSE; 4623 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4624 aij->free_a = PETSC_FALSE; 4625 aij->free_ij = PETSC_FALSE; 4626 4627 for (ii=0; ii<m; ii++) { 4628 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4629 #if defined(PETSC_USE_DEBUG) 4630 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]); 4631 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4632 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); 4633 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); 4634 } 4635 #endif 4636 } 4637 #if defined(PETSC_USE_DEBUG) 4638 for (ii=0; ii<aij->i[m]; ii++) { 4639 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 4640 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]); 4641 } 4642 #endif 4643 4644 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4645 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4646 PetscFunctionReturn(0); 4647 } 4648 #undef __FUNCT__ 4649 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4650 /*@C 4651 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4652 provided by the user. 4653 4654 Collective on MPI_Comm 4655 4656 Input Parameters: 4657 + comm - must be an MPI communicator of size 1 4658 . m - number of rows 4659 . n - number of columns 4660 . i - row indices 4661 . j - column indices 4662 . a - matrix values 4663 . nz - number of nonzeros 4664 - idx - 0 or 1 based 4665 4666 Output Parameter: 4667 . mat - the matrix 4668 4669 Level: intermediate 4670 4671 Notes: 4672 The i and j indices are 0 based 4673 4674 The format which is used for the sparse matrix input, is equivalent to a 4675 row-major ordering.. i.e for the following matrix, the input data expected is 4676 as shown: 4677 4678 1 0 0 4679 2 0 3 4680 4 5 6 4681 4682 i = {0,1,1,2,2,2} 4683 j = {0,0,2,0,1,2} 4684 v = {1,2,3,4,5,6} 4685 4686 4687 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4688 4689 @*/ 4690 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4691 { 4692 PetscErrorCode ierr; 4693 PetscInt ii, *nnz, one = 1,row,col; 4694 4695 4696 PetscFunctionBegin; 4697 ierr = PetscMalloc(m*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 4698 ierr = PetscMemzero(nnz,m*sizeof(PetscInt));CHKERRQ(ierr); 4699 for (ii = 0; ii < nz; ii++) { 4700 nnz[i[ii]] += 1; 4701 } 4702 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4703 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4704 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4705 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4706 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4707 for (ii = 0; ii < nz; ii++) { 4708 if (idx) { 4709 row = i[ii] - 1; 4710 col = j[ii] - 1; 4711 } else { 4712 row = i[ii]; 4713 col = j[ii]; 4714 } 4715 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4716 } 4717 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4718 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4719 ierr = PetscFree(nnz);CHKERRQ(ierr); 4720 PetscFunctionReturn(0); 4721 } 4722 4723 #undef __FUNCT__ 4724 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4725 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4726 { 4727 PetscErrorCode ierr; 4728 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4729 4730 PetscFunctionBegin; 4731 if (coloring->ctype == IS_COLORING_GLOBAL) { 4732 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4733 a->coloring = coloring; 4734 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4735 PetscInt i,*larray; 4736 ISColoring ocoloring; 4737 ISColoringValue *colors; 4738 4739 /* set coloring for diagonal portion */ 4740 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4741 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4742 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4743 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4744 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4745 ierr = PetscFree(larray);CHKERRQ(ierr); 4746 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4747 a->coloring = ocoloring; 4748 } 4749 PetscFunctionReturn(0); 4750 } 4751 4752 #undef __FUNCT__ 4753 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4754 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4755 { 4756 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4757 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4758 MatScalar *v = a->a; 4759 PetscScalar *values = (PetscScalar*)advalues; 4760 ISColoringValue *color; 4761 4762 PetscFunctionBegin; 4763 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4764 color = a->coloring->colors; 4765 /* loop over rows */ 4766 for (i=0; i<m; i++) { 4767 nz = ii[i+1] - ii[i]; 4768 /* loop over columns putting computed value into matrix */ 4769 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4770 values += nl; /* jump to next row of derivatives */ 4771 } 4772 PetscFunctionReturn(0); 4773 } 4774 4775 #undef __FUNCT__ 4776 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4777 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4778 { 4779 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4780 PetscErrorCode ierr; 4781 4782 PetscFunctionBegin; 4783 a->idiagvalid = PETSC_FALSE; 4784 a->ibdiagvalid = PETSC_FALSE; 4785 4786 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4787 PetscFunctionReturn(0); 4788 } 4789 4790 /* 4791 Special version for direct calls from Fortran 4792 */ 4793 #include <petsc-private/fortranimpl.h> 4794 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4795 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4796 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4797 #define matsetvaluesseqaij_ matsetvaluesseqaij 4798 #endif 4799 4800 /* Change these macros so can be used in void function */ 4801 #undef CHKERRQ 4802 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4803 #undef SETERRQ2 4804 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4805 #undef SETERRQ3 4806 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4807 4808 #undef __FUNCT__ 4809 #define __FUNCT__ "matsetvaluesseqaij_" 4810 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) 4811 { 4812 Mat A = *AA; 4813 PetscInt m = *mm, n = *nn; 4814 InsertMode is = *isis; 4815 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4816 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4817 PetscInt *imax,*ai,*ailen; 4818 PetscErrorCode ierr; 4819 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4820 MatScalar *ap,value,*aa; 4821 PetscBool ignorezeroentries = a->ignorezeroentries; 4822 PetscBool roworiented = a->roworiented; 4823 4824 PetscFunctionBegin; 4825 MatCheckPreallocated(A,1); 4826 imax = a->imax; 4827 ai = a->i; 4828 ailen = a->ilen; 4829 aj = a->j; 4830 aa = a->a; 4831 4832 for (k=0; k<m; k++) { /* loop over added rows */ 4833 row = im[k]; 4834 if (row < 0) continue; 4835 #if defined(PETSC_USE_DEBUG) 4836 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4837 #endif 4838 rp = aj + ai[row]; ap = aa + ai[row]; 4839 rmax = imax[row]; nrow = ailen[row]; 4840 low = 0; 4841 high = nrow; 4842 for (l=0; l<n; l++) { /* loop over added columns */ 4843 if (in[l] < 0) continue; 4844 #if defined(PETSC_USE_DEBUG) 4845 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4846 #endif 4847 col = in[l]; 4848 if (roworiented) value = v[l + k*n]; 4849 else value = v[k + l*m]; 4850 4851 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4852 4853 if (col <= lastcol) low = 0; 4854 else high = nrow; 4855 lastcol = col; 4856 while (high-low > 5) { 4857 t = (low+high)/2; 4858 if (rp[t] > col) high = t; 4859 else low = t; 4860 } 4861 for (i=low; i<high; i++) { 4862 if (rp[i] > col) break; 4863 if (rp[i] == col) { 4864 if (is == ADD_VALUES) ap[i] += value; 4865 else ap[i] = value; 4866 goto noinsert; 4867 } 4868 } 4869 if (value == 0.0 && ignorezeroentries) goto noinsert; 4870 if (nonew == 1) goto noinsert; 4871 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4872 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4873 N = nrow++ - 1; a->nz++; high++; 4874 /* shift up all the later entries in this row */ 4875 for (ii=N; ii>=i; ii--) { 4876 rp[ii+1] = rp[ii]; 4877 ap[ii+1] = ap[ii]; 4878 } 4879 rp[i] = col; 4880 ap[i] = value; 4881 noinsert:; 4882 low = i + 1; 4883 } 4884 ailen[row] = nrow; 4885 } 4886 A->same_nonzero = PETSC_FALSE; 4887 PetscFunctionReturnVoid(); 4888 } 4889 4890 4891