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]; 1772 } 1773 } 1774 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 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 n = a->i[i+1] - a->i[i]; 1782 idx = a->j + a->i[i]; 1783 v = a->a + a->i[i]; 1784 sum = b[i]; 1785 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1786 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1787 } 1788 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1789 } 1790 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1791 for (i=m-1; i>=0; i--) { 1792 n = a->i[i+1] - a->i[i]; 1793 idx = a->j + a->i[i]; 1794 v = a->a + a->i[i]; 1795 sum = b[i]; 1796 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1797 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1798 } 1799 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1800 } 1801 } 1802 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1803 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1804 PetscFunctionReturn(0); 1805 } 1806 1807 1808 #undef __FUNCT__ 1809 #define __FUNCT__ "MatGetInfo_SeqAIJ" 1810 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1811 { 1812 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1813 1814 PetscFunctionBegin; 1815 info->block_size = 1.0; 1816 info->nz_allocated = (double)a->maxnz; 1817 info->nz_used = (double)a->nz; 1818 info->nz_unneeded = (double)(a->maxnz - a->nz); 1819 info->assemblies = (double)A->num_ass; 1820 info->mallocs = (double)A->info.mallocs; 1821 info->memory = ((PetscObject)A)->mem; 1822 if (A->factortype) { 1823 info->fill_ratio_given = A->info.fill_ratio_given; 1824 info->fill_ratio_needed = A->info.fill_ratio_needed; 1825 info->factor_mallocs = A->info.factor_mallocs; 1826 } else { 1827 info->fill_ratio_given = 0; 1828 info->fill_ratio_needed = 0; 1829 info->factor_mallocs = 0; 1830 } 1831 PetscFunctionReturn(0); 1832 } 1833 1834 #undef __FUNCT__ 1835 #define __FUNCT__ "MatZeroRows_SeqAIJ" 1836 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1837 { 1838 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1839 PetscInt i,m = A->rmap->n - 1,d = 0; 1840 PetscErrorCode ierr; 1841 const PetscScalar *xx; 1842 PetscScalar *bb; 1843 PetscBool missing; 1844 1845 PetscFunctionBegin; 1846 if (x && b) { 1847 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1848 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1849 for (i=0; i<N; i++) { 1850 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1851 bb[rows[i]] = diag*xx[rows[i]]; 1852 } 1853 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1854 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1855 } 1856 1857 if (a->keepnonzeropattern) { 1858 for (i=0; i<N; i++) { 1859 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1860 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1861 } 1862 if (diag != 0.0) { 1863 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1864 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1865 for (i=0; i<N; i++) { 1866 a->a[a->diag[rows[i]]] = diag; 1867 } 1868 } 1869 A->same_nonzero = PETSC_TRUE; 1870 } else { 1871 if (diag != 0.0) { 1872 for (i=0; i<N; i++) { 1873 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1874 if (a->ilen[rows[i]] > 0) { 1875 a->ilen[rows[i]] = 1; 1876 a->a[a->i[rows[i]]] = diag; 1877 a->j[a->i[rows[i]]] = rows[i]; 1878 } else { /* in case row was completely empty */ 1879 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1880 } 1881 } 1882 } else { 1883 for (i=0; i<N; i++) { 1884 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1885 a->ilen[rows[i]] = 0; 1886 } 1887 } 1888 A->same_nonzero = PETSC_FALSE; 1889 } 1890 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1891 PetscFunctionReturn(0); 1892 } 1893 1894 #undef __FUNCT__ 1895 #define __FUNCT__ "MatZeroRowsColumns_SeqAIJ" 1896 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1897 { 1898 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1899 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1900 PetscErrorCode ierr; 1901 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1902 const PetscScalar *xx; 1903 PetscScalar *bb; 1904 1905 PetscFunctionBegin; 1906 if (x && b) { 1907 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1908 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1909 vecs = PETSC_TRUE; 1910 } 1911 ierr = PetscMalloc(A->rmap->n*sizeof(PetscBool),&zeroed);CHKERRQ(ierr); 1912 ierr = PetscMemzero(zeroed,A->rmap->n*sizeof(PetscBool));CHKERRQ(ierr); 1913 for (i=0; i<N; i++) { 1914 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1915 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1916 1917 zeroed[rows[i]] = PETSC_TRUE; 1918 } 1919 for (i=0; i<A->rmap->n; i++) { 1920 if (!zeroed[i]) { 1921 for (j=a->i[i]; j<a->i[i+1]; j++) { 1922 if (zeroed[a->j[j]]) { 1923 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1924 a->a[j] = 0.0; 1925 } 1926 } 1927 } else if (vecs) bb[i] = diag*xx[i]; 1928 } 1929 if (x && b) { 1930 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1931 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1932 } 1933 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1934 if (diag != 0.0) { 1935 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1936 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1937 for (i=0; i<N; i++) { 1938 a->a[a->diag[rows[i]]] = diag; 1939 } 1940 } 1941 A->same_nonzero = PETSC_TRUE; 1942 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1943 PetscFunctionReturn(0); 1944 } 1945 1946 #undef __FUNCT__ 1947 #define __FUNCT__ "MatGetRow_SeqAIJ" 1948 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1949 { 1950 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1951 PetscInt *itmp; 1952 1953 PetscFunctionBegin; 1954 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1955 1956 *nz = a->i[row+1] - a->i[row]; 1957 if (v) *v = a->a + a->i[row]; 1958 if (idx) { 1959 itmp = a->j + a->i[row]; 1960 if (*nz) *idx = itmp; 1961 else *idx = 0; 1962 } 1963 PetscFunctionReturn(0); 1964 } 1965 1966 /* remove this function? */ 1967 #undef __FUNCT__ 1968 #define __FUNCT__ "MatRestoreRow_SeqAIJ" 1969 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1970 { 1971 PetscFunctionBegin; 1972 PetscFunctionReturn(0); 1973 } 1974 1975 #undef __FUNCT__ 1976 #define __FUNCT__ "MatNorm_SeqAIJ" 1977 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1978 { 1979 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1980 MatScalar *v = a->a; 1981 PetscReal sum = 0.0; 1982 PetscErrorCode ierr; 1983 PetscInt i,j; 1984 1985 PetscFunctionBegin; 1986 if (type == NORM_FROBENIUS) { 1987 for (i=0; i<a->nz; i++) { 1988 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1989 } 1990 *nrm = PetscSqrtReal(sum); 1991 } else if (type == NORM_1) { 1992 PetscReal *tmp; 1993 PetscInt *jj = a->j; 1994 ierr = PetscMalloc((A->cmap->n+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1995 ierr = PetscMemzero(tmp,A->cmap->n*sizeof(PetscReal));CHKERRQ(ierr); 1996 *nrm = 0.0; 1997 for (j=0; j<a->nz; j++) { 1998 tmp[*jj++] += PetscAbsScalar(*v); v++; 1999 } 2000 for (j=0; j<A->cmap->n; j++) { 2001 if (tmp[j] > *nrm) *nrm = tmp[j]; 2002 } 2003 ierr = PetscFree(tmp);CHKERRQ(ierr); 2004 } else if (type == NORM_INFINITY) { 2005 *nrm = 0.0; 2006 for (j=0; j<A->rmap->n; j++) { 2007 v = a->a + a->i[j]; 2008 sum = 0.0; 2009 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2010 sum += PetscAbsScalar(*v); v++; 2011 } 2012 if (sum > *nrm) *nrm = sum; 2013 } 2014 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2015 PetscFunctionReturn(0); 2016 } 2017 2018 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2019 #undef __FUNCT__ 2020 #define __FUNCT__ "MatTransposeSymbolic_SeqAIJ" 2021 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2022 { 2023 PetscErrorCode ierr; 2024 PetscInt i,j,anzj; 2025 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2026 PetscInt an=A->cmap->N,am=A->rmap->N; 2027 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2028 2029 PetscFunctionBegin; 2030 /* Allocate space for symbolic transpose info and work array */ 2031 ierr = PetscMalloc((an+1)*sizeof(PetscInt),&ati);CHKERRQ(ierr); 2032 ierr = PetscMalloc(ai[am]*sizeof(PetscInt),&atj);CHKERRQ(ierr); 2033 ierr = PetscMalloc(an*sizeof(PetscInt),&atfill);CHKERRQ(ierr); 2034 ierr = PetscMemzero(ati,(an+1)*sizeof(PetscInt));CHKERRQ(ierr); 2035 2036 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2037 /* Note: offset by 1 for fast conversion into csr format. */ 2038 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2039 /* Form ati for csr format of A^T. */ 2040 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2041 2042 /* Copy ati into atfill so we have locations of the next free space in atj */ 2043 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2044 2045 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2046 for (i=0;i<am;i++) { 2047 anzj = ai[i+1] - ai[i]; 2048 for (j=0;j<anzj;j++) { 2049 atj[atfill[*aj]] = i; 2050 atfill[*aj++] += 1; 2051 } 2052 } 2053 2054 /* Clean up temporary space and complete requests. */ 2055 ierr = PetscFree(atfill);CHKERRQ(ierr); 2056 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2057 2058 (*B)->rmap->bs = A->cmap->bs; 2059 (*B)->cmap->bs = A->rmap->bs; 2060 2061 b = (Mat_SeqAIJ*)((*B)->data); 2062 b->free_a = PETSC_FALSE; 2063 b->free_ij = PETSC_TRUE; 2064 b->nonew = 0; 2065 PetscFunctionReturn(0); 2066 } 2067 2068 #undef __FUNCT__ 2069 #define __FUNCT__ "MatTranspose_SeqAIJ" 2070 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2071 { 2072 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2073 Mat C; 2074 PetscErrorCode ierr; 2075 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2076 MatScalar *array = a->a; 2077 2078 PetscFunctionBegin; 2079 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"); 2080 2081 if (reuse == MAT_INITIAL_MATRIX || *B == A) { 2082 ierr = PetscMalloc((1+A->cmap->n)*sizeof(PetscInt),&col);CHKERRQ(ierr); 2083 ierr = PetscMemzero(col,(1+A->cmap->n)*sizeof(PetscInt));CHKERRQ(ierr); 2084 2085 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2086 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2087 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2088 ierr = MatSetBlockSizes(C,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2089 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2090 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2091 ierr = PetscFree(col);CHKERRQ(ierr); 2092 } else { 2093 C = *B; 2094 } 2095 2096 for (i=0; i<m; i++) { 2097 len = ai[i+1]-ai[i]; 2098 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2099 array += len; 2100 aj += len; 2101 } 2102 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2103 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2104 2105 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 2106 *B = C; 2107 } else { 2108 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 2109 } 2110 PetscFunctionReturn(0); 2111 } 2112 2113 #undef __FUNCT__ 2114 #define __FUNCT__ "MatIsTranspose_SeqAIJ" 2115 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2116 { 2117 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2118 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2119 MatScalar *va,*vb; 2120 PetscErrorCode ierr; 2121 PetscInt ma,na,mb,nb, i; 2122 2123 PetscFunctionBegin; 2124 bij = (Mat_SeqAIJ*) B->data; 2125 2126 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2127 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2128 if (ma!=nb || na!=mb) { 2129 *f = PETSC_FALSE; 2130 PetscFunctionReturn(0); 2131 } 2132 aii = aij->i; bii = bij->i; 2133 adx = aij->j; bdx = bij->j; 2134 va = aij->a; vb = bij->a; 2135 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 2136 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 2137 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2138 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2139 2140 *f = PETSC_TRUE; 2141 for (i=0; i<ma; i++) { 2142 while (aptr[i]<aii[i+1]) { 2143 PetscInt idc,idr; 2144 PetscScalar vc,vr; 2145 /* column/row index/value */ 2146 idc = adx[aptr[i]]; 2147 idr = bdx[bptr[idc]]; 2148 vc = va[aptr[i]]; 2149 vr = vb[bptr[idc]]; 2150 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2151 *f = PETSC_FALSE; 2152 goto done; 2153 } else { 2154 aptr[i]++; 2155 if (B || i!=idc) bptr[idc]++; 2156 } 2157 } 2158 } 2159 done: 2160 ierr = PetscFree(aptr);CHKERRQ(ierr); 2161 ierr = PetscFree(bptr);CHKERRQ(ierr); 2162 PetscFunctionReturn(0); 2163 } 2164 2165 #undef __FUNCT__ 2166 #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" 2167 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2168 { 2169 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2170 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2171 MatScalar *va,*vb; 2172 PetscErrorCode ierr; 2173 PetscInt ma,na,mb,nb, i; 2174 2175 PetscFunctionBegin; 2176 bij = (Mat_SeqAIJ*) B->data; 2177 2178 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2179 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2180 if (ma!=nb || na!=mb) { 2181 *f = PETSC_FALSE; 2182 PetscFunctionReturn(0); 2183 } 2184 aii = aij->i; bii = bij->i; 2185 adx = aij->j; bdx = bij->j; 2186 va = aij->a; vb = bij->a; 2187 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 2188 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 2189 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2190 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2191 2192 *f = PETSC_TRUE; 2193 for (i=0; i<ma; i++) { 2194 while (aptr[i]<aii[i+1]) { 2195 PetscInt idc,idr; 2196 PetscScalar vc,vr; 2197 /* column/row index/value */ 2198 idc = adx[aptr[i]]; 2199 idr = bdx[bptr[idc]]; 2200 vc = va[aptr[i]]; 2201 vr = vb[bptr[idc]]; 2202 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2203 *f = PETSC_FALSE; 2204 goto done; 2205 } else { 2206 aptr[i]++; 2207 if (B || i!=idc) bptr[idc]++; 2208 } 2209 } 2210 } 2211 done: 2212 ierr = PetscFree(aptr);CHKERRQ(ierr); 2213 ierr = PetscFree(bptr);CHKERRQ(ierr); 2214 PetscFunctionReturn(0); 2215 } 2216 2217 #undef __FUNCT__ 2218 #define __FUNCT__ "MatIsSymmetric_SeqAIJ" 2219 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2220 { 2221 PetscErrorCode ierr; 2222 2223 PetscFunctionBegin; 2224 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2225 PetscFunctionReturn(0); 2226 } 2227 2228 #undef __FUNCT__ 2229 #define __FUNCT__ "MatIsHermitian_SeqAIJ" 2230 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2231 { 2232 PetscErrorCode ierr; 2233 2234 PetscFunctionBegin; 2235 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2236 PetscFunctionReturn(0); 2237 } 2238 2239 #undef __FUNCT__ 2240 #define __FUNCT__ "MatDiagonalScale_SeqAIJ" 2241 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2242 { 2243 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2244 PetscScalar *l,*r,x; 2245 MatScalar *v; 2246 PetscErrorCode ierr; 2247 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; 2248 2249 PetscFunctionBegin; 2250 if (ll) { 2251 /* The local size is used so that VecMPI can be passed to this routine 2252 by MatDiagonalScale_MPIAIJ */ 2253 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2254 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2255 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 2256 v = a->a; 2257 for (i=0; i<m; i++) { 2258 x = l[i]; 2259 M = a->i[i+1] - a->i[i]; 2260 for (j=0; j<M; j++) (*v++) *= x; 2261 } 2262 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 2263 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2264 } 2265 if (rr) { 2266 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2267 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2268 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 2269 v = a->a; jj = a->j; 2270 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2271 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 2272 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2273 } 2274 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2275 PetscFunctionReturn(0); 2276 } 2277 2278 #undef __FUNCT__ 2279 #define __FUNCT__ "MatGetSubMatrix_SeqAIJ" 2280 PetscErrorCode MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2281 { 2282 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2283 PetscErrorCode ierr; 2284 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2285 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2286 const PetscInt *irow,*icol; 2287 PetscInt nrows,ncols; 2288 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2289 MatScalar *a_new,*mat_a; 2290 Mat C; 2291 PetscBool stride,sorted; 2292 2293 PetscFunctionBegin; 2294 ierr = ISSorted(isrow,&sorted);CHKERRQ(ierr); 2295 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted"); 2296 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); 2297 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted"); 2298 2299 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2300 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2301 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2302 2303 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2304 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2305 if (stride && step == 1) { 2306 /* special case of contiguous rows */ 2307 ierr = PetscMalloc2(nrows,PetscInt,&lens,nrows,PetscInt,&starts);CHKERRQ(ierr); 2308 /* loop over new rows determining lens and starting points */ 2309 for (i=0; i<nrows; i++) { 2310 kstart = ai[irow[i]]; 2311 kend = kstart + ailen[irow[i]]; 2312 for (k=kstart; k<kend; k++) { 2313 if (aj[k] >= first) { 2314 starts[i] = k; 2315 break; 2316 } 2317 } 2318 sum = 0; 2319 while (k < kend) { 2320 if (aj[k++] >= first+ncols) break; 2321 sum++; 2322 } 2323 lens[i] = sum; 2324 } 2325 /* create submatrix */ 2326 if (scall == MAT_REUSE_MATRIX) { 2327 PetscInt n_cols,n_rows; 2328 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2329 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2330 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2331 C = *B; 2332 } else { 2333 PetscInt rbs,cbs; 2334 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2335 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2336 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2337 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2338 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2339 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2340 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2341 } 2342 c = (Mat_SeqAIJ*)C->data; 2343 2344 /* loop over rows inserting into submatrix */ 2345 a_new = c->a; 2346 j_new = c->j; 2347 i_new = c->i; 2348 2349 for (i=0; i<nrows; i++) { 2350 ii = starts[i]; 2351 lensi = lens[i]; 2352 for (k=0; k<lensi; k++) { 2353 *j_new++ = aj[ii+k] - first; 2354 } 2355 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2356 a_new += lensi; 2357 i_new[i+1] = i_new[i] + lensi; 2358 c->ilen[i] = lensi; 2359 } 2360 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2361 } else { 2362 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2363 ierr = PetscMalloc(oldcols*sizeof(PetscInt),&smap);CHKERRQ(ierr); 2364 ierr = PetscMemzero(smap,oldcols*sizeof(PetscInt));CHKERRQ(ierr); 2365 ierr = PetscMalloc((1+nrows)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2366 for (i=0; i<ncols; i++) { 2367 #if defined(PETSC_USE_DEBUG) 2368 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); 2369 #endif 2370 smap[icol[i]] = i+1; 2371 } 2372 2373 /* determine lens of each row */ 2374 for (i=0; i<nrows; i++) { 2375 kstart = ai[irow[i]]; 2376 kend = kstart + a->ilen[irow[i]]; 2377 lens[i] = 0; 2378 for (k=kstart; k<kend; k++) { 2379 if (smap[aj[k]]) { 2380 lens[i]++; 2381 } 2382 } 2383 } 2384 /* Create and fill new matrix */ 2385 if (scall == MAT_REUSE_MATRIX) { 2386 PetscBool equal; 2387 2388 c = (Mat_SeqAIJ*)((*B)->data); 2389 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2390 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2391 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2392 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2393 C = *B; 2394 } else { 2395 PetscInt rbs,cbs; 2396 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2397 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2398 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2399 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2400 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2401 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2402 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2403 } 2404 c = (Mat_SeqAIJ*)(C->data); 2405 for (i=0; i<nrows; i++) { 2406 row = irow[i]; 2407 kstart = ai[row]; 2408 kend = kstart + a->ilen[row]; 2409 mat_i = c->i[i]; 2410 mat_j = c->j + mat_i; 2411 mat_a = c->a + mat_i; 2412 mat_ilen = c->ilen + i; 2413 for (k=kstart; k<kend; k++) { 2414 if ((tcol=smap[a->j[k]])) { 2415 *mat_j++ = tcol - 1; 2416 *mat_a++ = a->a[k]; 2417 (*mat_ilen)++; 2418 2419 } 2420 } 2421 } 2422 /* Free work space */ 2423 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2424 ierr = PetscFree(smap);CHKERRQ(ierr); 2425 ierr = PetscFree(lens);CHKERRQ(ierr); 2426 } 2427 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2428 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2429 2430 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2431 *B = C; 2432 PetscFunctionReturn(0); 2433 } 2434 2435 #undef __FUNCT__ 2436 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 2437 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2438 { 2439 PetscErrorCode ierr; 2440 Mat B; 2441 2442 PetscFunctionBegin; 2443 if (scall == MAT_INITIAL_MATRIX) { 2444 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2445 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2446 ierr = MatSetBlockSizes(B,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2447 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2448 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2449 *subMat = B; 2450 } else { 2451 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2452 } 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatILUFactor_SeqAIJ" 2458 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2459 { 2460 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2461 PetscErrorCode ierr; 2462 Mat outA; 2463 PetscBool row_identity,col_identity; 2464 2465 PetscFunctionBegin; 2466 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2467 2468 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2469 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2470 2471 outA = inA; 2472 outA->factortype = MAT_FACTOR_LU; 2473 2474 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2475 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2476 2477 a->row = row; 2478 2479 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2480 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2481 2482 a->col = col; 2483 2484 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2485 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2486 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2487 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2488 2489 if (!a->solve_work) { /* this matrix may have been factored before */ 2490 ierr = PetscMalloc((inA->rmap->n+1)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); 2491 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2492 } 2493 2494 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2495 if (row_identity && col_identity) { 2496 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2497 } else { 2498 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2499 } 2500 PetscFunctionReturn(0); 2501 } 2502 2503 #undef __FUNCT__ 2504 #define __FUNCT__ "MatScale_SeqAIJ" 2505 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2506 { 2507 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2508 PetscScalar oalpha = alpha; 2509 PetscErrorCode ierr; 2510 PetscBLASInt one = 1,bnz; 2511 2512 PetscFunctionBegin; 2513 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2514 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2515 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2516 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2517 PetscFunctionReturn(0); 2518 } 2519 2520 #undef __FUNCT__ 2521 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 2522 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2523 { 2524 PetscErrorCode ierr; 2525 PetscInt i; 2526 2527 PetscFunctionBegin; 2528 if (scall == MAT_INITIAL_MATRIX) { 2529 ierr = PetscMalloc((n+1)*sizeof(Mat),B);CHKERRQ(ierr); 2530 } 2531 2532 for (i=0; i<n; i++) { 2533 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2534 } 2535 PetscFunctionReturn(0); 2536 } 2537 2538 #undef __FUNCT__ 2539 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 2540 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2541 { 2542 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2543 PetscErrorCode ierr; 2544 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2545 const PetscInt *idx; 2546 PetscInt start,end,*ai,*aj; 2547 PetscBT table; 2548 2549 PetscFunctionBegin; 2550 m = A->rmap->n; 2551 ai = a->i; 2552 aj = a->j; 2553 2554 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2555 2556 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&nidx);CHKERRQ(ierr); 2557 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2558 2559 for (i=0; i<is_max; i++) { 2560 /* Initialize the two local arrays */ 2561 isz = 0; 2562 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2563 2564 /* Extract the indices, assume there can be duplicate entries */ 2565 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2566 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2567 2568 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2569 for (j=0; j<n; ++j) { 2570 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2571 } 2572 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2573 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2574 2575 k = 0; 2576 for (j=0; j<ov; j++) { /* for each overlap */ 2577 n = isz; 2578 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2579 row = nidx[k]; 2580 start = ai[row]; 2581 end = ai[row+1]; 2582 for (l = start; l<end; l++) { 2583 val = aj[l]; 2584 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2585 } 2586 } 2587 } 2588 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2589 } 2590 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2591 ierr = PetscFree(nidx);CHKERRQ(ierr); 2592 PetscFunctionReturn(0); 2593 } 2594 2595 /* -------------------------------------------------------------- */ 2596 #undef __FUNCT__ 2597 #define __FUNCT__ "MatPermute_SeqAIJ" 2598 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2599 { 2600 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2601 PetscErrorCode ierr; 2602 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2603 const PetscInt *row,*col; 2604 PetscInt *cnew,j,*lens; 2605 IS icolp,irowp; 2606 PetscInt *cwork = NULL; 2607 PetscScalar *vwork = NULL; 2608 2609 PetscFunctionBegin; 2610 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2611 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2612 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2613 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2614 2615 /* determine lengths of permuted rows */ 2616 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2617 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2618 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2619 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2620 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2621 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2622 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2623 ierr = PetscFree(lens);CHKERRQ(ierr); 2624 2625 ierr = PetscMalloc(n*sizeof(PetscInt),&cnew);CHKERRQ(ierr); 2626 for (i=0; i<m; i++) { 2627 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2628 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2629 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2630 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2631 } 2632 ierr = PetscFree(cnew);CHKERRQ(ierr); 2633 2634 (*B)->assembled = PETSC_FALSE; 2635 2636 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2637 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2638 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2639 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2640 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2641 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2642 PetscFunctionReturn(0); 2643 } 2644 2645 #undef __FUNCT__ 2646 #define __FUNCT__ "MatCopy_SeqAIJ" 2647 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2648 { 2649 PetscErrorCode ierr; 2650 2651 PetscFunctionBegin; 2652 /* If the two matrices have the same copy implementation, use fast copy. */ 2653 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2654 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2655 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2656 2657 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"); 2658 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2659 } else { 2660 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2661 } 2662 PetscFunctionReturn(0); 2663 } 2664 2665 #undef __FUNCT__ 2666 #define __FUNCT__ "MatSetUp_SeqAIJ" 2667 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2668 { 2669 PetscErrorCode ierr; 2670 2671 PetscFunctionBegin; 2672 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2673 PetscFunctionReturn(0); 2674 } 2675 2676 #undef __FUNCT__ 2677 #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" 2678 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2679 { 2680 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2681 2682 PetscFunctionBegin; 2683 *array = a->a; 2684 PetscFunctionReturn(0); 2685 } 2686 2687 #undef __FUNCT__ 2688 #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" 2689 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2690 { 2691 PetscFunctionBegin; 2692 PetscFunctionReturn(0); 2693 } 2694 2695 /* Optimize MatFDColoringApply_AIJ() by using array den2sp to skip calling MatSetValues() */ 2696 /* #define JACOBIANCOLOROPT */ 2697 #if defined(JACOBIANCOLOROPT) 2698 #include <petsctime.h> 2699 #endif 2700 #undef __FUNCT__ 2701 #define __FUNCT__ "MatFDColoringApply_SeqAIJ" 2702 PetscErrorCode MatFDColoringApply_SeqAIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2703 { 2704 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2705 PetscErrorCode ierr; 2706 PetscInt k,l,row,col,N; 2707 PetscScalar dx,*y,*xx,*w3_array; 2708 PetscScalar *vscale_array; 2709 PetscReal epsilon=coloring->error_rel,umin = coloring->umin,unorm; 2710 Vec w1=coloring->w1,w2=coloring->w2,w3; 2711 void *fctx=coloring->fctx; 2712 PetscBool flg=PETSC_FALSE; 2713 Mat_SeqAIJ *csp=(Mat_SeqAIJ*)J->data; 2714 PetscScalar *ca=csp->a; 2715 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 2716 PetscInt *den2sp=coloring->den2sp,*idx; 2717 PetscInt **rows=coloring->rows,**columns=coloring->columns,ncolumns_k,nrows_k,**columnsforrow=coloring->columnsforrow; 2718 #if defined(JACOBIANCOLOROPT) 2719 PetscLogDouble t0,t1,time_setvalues=0.0; 2720 #endif 2721 2722 PetscFunctionBegin; 2723 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2724 ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2725 if (flg) { 2726 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2727 } else { 2728 PetscBool assembled; 2729 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2730 if (assembled) { 2731 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2732 } 2733 } 2734 2735 if (!coloring->vscale) { 2736 ierr = VecDuplicate(x1,&coloring->vscale);CHKERRQ(ierr); 2737 } 2738 2739 if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/ 2740 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 2741 } 2742 2743 /* Set w1 = F(x1) */ 2744 if (!coloring->fset) { 2745 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2746 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2747 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2748 } else { 2749 coloring->fset = PETSC_FALSE; 2750 } 2751 2752 if (!coloring->w3) { 2753 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2754 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2755 } 2756 w3 = coloring->w3; 2757 2758 /* Compute scale factors: vscale = 1./dx = 1./(epsilon*xx) */ 2759 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 2760 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2761 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2762 for (col=0; col<N; col++) { 2763 if (coloring->htype[0] == 'w') { 2764 dx = 1.0 + unorm; 2765 } else { 2766 dx = xx[col]; 2767 } 2768 if (dx == (PetscScalar)0.0) dx = 1.0; 2769 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2770 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2771 dx *= epsilon; 2772 vscale_array[col] = (PetscScalar)1.0/dx; 2773 } 2774 2775 idx = den2sp; 2776 for (k=0; k<ncolors; k++) { /* loop over colors */ 2777 coloring->currentcolor = k; 2778 2779 /* 2780 Loop over each column associated with color 2781 adding the perturbation to the vector w3 = x1 + dx. 2782 */ 2783 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2784 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 2785 ncolumns_k = ncolumns[k]; 2786 for (l=0; l<ncolumns_k; l++) { /* loop over columns */ 2787 col = columns[k][l]; 2788 w3_array[col] += 1/vscale_array[col]; 2789 } 2790 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2791 2792 /* 2793 Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 2794 w2 = F(x1 + dx) - F(x1) 2795 */ 2796 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2797 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2798 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2799 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2800 2801 /* 2802 Loop over rows of vector, putting w2/dx into Jacobian matrix 2803 */ 2804 #if defined(JACOBIANCOLOROPT) 2805 ierr = PetscTime(&t0);CHKERRQ(ierr); 2806 #endif 2807 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2808 nrows_k = nrows[k]; 2809 for (l=0; l<nrows_k; l++) { /* loop over rows */ 2810 row = rows[k][l]; /* row index */ 2811 y[row] *= vscale_array[columnsforrow[k][l]]; 2812 ca[idx[l]] = y[row]; 2813 } 2814 idx += nrows_k; 2815 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2816 #if defined(JACOBIANCOLOROPT) 2817 ierr = PetscTime(&t1);CHKERRQ(ierr); 2818 time_setvalues += t1-t0; 2819 #endif 2820 } /* endof for each color */ 2821 #if defined(JACOBIANCOLOROPT) 2822 printf(" MatFDColoringApply_SeqAIJ: time_setvalues %g\n",time_setvalues); 2823 #endif 2824 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2825 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2826 2827 coloring->currentcolor = -1; 2828 PetscFunctionReturn(0); 2829 } 2830 /* --------------------------------------------------------*/ 2831 2832 #undef __FUNCT__ 2833 #define __FUNCT__ "MatFDColoringApply_SeqAIJ_old" 2834 PetscErrorCode MatFDColoringApply_SeqAIJ_old(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2835 { 2836 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2837 PetscErrorCode ierr; 2838 PetscInt k,N,start,end,l,row,col,srow,**vscaleforrow; 2839 PetscScalar dx,*y,*xx,*w3_array; 2840 PetscScalar *vscale_array; 2841 PetscReal epsilon = coloring->error_rel,umin = coloring->umin; 2842 Vec w1,w2,w3; 2843 void *fctx = coloring->fctx; 2844 PetscBool flg = PETSC_FALSE; 2845 2846 PetscFunctionBegin; 2847 printf("MatFDColoringApply_SeqAIJ ...\n"); 2848 if (!coloring->w1) { 2849 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 2850 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w1);CHKERRQ(ierr); 2851 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 2852 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w2);CHKERRQ(ierr); 2853 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2854 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2855 } 2856 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 2857 2858 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2859 ierr = PetscOptionsGetBool(((PetscObject)coloring)->prefix,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2860 if (flg) { 2861 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2862 } else { 2863 PetscBool assembled; 2864 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2865 if (assembled) { 2866 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2867 } 2868 } 2869 2870 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 2871 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2872 2873 if (!coloring->fset) { 2874 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2875 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2876 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2877 } else { 2878 coloring->fset = PETSC_FALSE; 2879 } 2880 2881 /* 2882 Compute all the scale factors and share with other processors 2883 */ 2884 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start; 2885 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start; 2886 for (k=0; k<coloring->ncolors; k++) { 2887 /* 2888 Loop over each column associated with color adding the 2889 perturbation to the vector w3. 2890 */ 2891 for (l=0; l<coloring->ncolumns[k]; l++) { 2892 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2893 dx = xx[col]; 2894 if (dx == 0.0) dx = 1.0; 2895 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2896 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2897 dx *= epsilon; 2898 vscale_array[col] = 1.0/dx; 2899 } 2900 } 2901 vscale_array = vscale_array + start; 2902 2903 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2904 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2905 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2906 2907 /* ierr = VecView(coloring->vscale,PETSC_VIEWER_STDOUT_WORLD); 2908 ierr = VecView(x1,PETSC_VIEWER_STDOUT_WORLD);*/ 2909 2910 if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow; 2911 else vscaleforrow = coloring->columnsforrow; 2912 2913 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2914 /* 2915 Loop over each color 2916 */ 2917 for (k=0; k<coloring->ncolors; k++) { 2918 coloring->currentcolor = k; 2919 2920 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2921 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start; 2922 /* 2923 Loop over each column associated with color adding the 2924 perturbation to the vector w3. 2925 */ 2926 for (l=0; l<coloring->ncolumns[k]; l++) { 2927 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2928 dx = xx[col]; 2929 if (dx == 0.0) dx = 1.0; 2930 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2931 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2932 dx *= epsilon; 2933 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 2934 w3_array[col] += dx; 2935 } 2936 w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2937 2938 /* 2939 Evaluate function at x1 + dx (here dx is a vector of perturbations) 2940 */ 2941 2942 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2943 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2944 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2945 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2946 2947 /* 2948 Loop over rows of vector, putting results into Jacobian matrix 2949 */ 2950 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2951 for (l=0; l<coloring->nrows[k]; l++) { 2952 row = coloring->rows[k][l]; 2953 col = coloring->columnsforrow[k][l]; 2954 y[row] *= vscale_array[vscaleforrow[k][l]]; 2955 srow = row + start; 2956 ierr = MatSetValues_SeqAIJ(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 2957 } 2958 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2959 } 2960 coloring->currentcolor = k; 2961 2962 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2963 xx = xx + start; 2964 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2965 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2966 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2967 PetscFunctionReturn(0); 2968 } 2969 2970 /* 2971 Computes the number of nonzeros per row needed for preallocation when X and Y 2972 have different nonzero structure. 2973 */ 2974 #undef __FUNCT__ 2975 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 2976 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2977 { 2978 PetscInt i,m=Y->rmap->N; 2979 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2980 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2981 const PetscInt *xi = x->i,*yi = y->i; 2982 2983 PetscFunctionBegin; 2984 /* Set the number of nonzeros in the new matrix */ 2985 for (i=0; i<m; i++) { 2986 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2987 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2988 nnz[i] = 0; 2989 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2990 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 2991 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 2992 nnz[i]++; 2993 } 2994 for (; k<nzy; k++) nnz[i]++; 2995 } 2996 PetscFunctionReturn(0); 2997 } 2998 2999 #undef __FUNCT__ 3000 #define __FUNCT__ "MatAXPY_SeqAIJ" 3001 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 3002 { 3003 PetscErrorCode ierr; 3004 PetscInt i; 3005 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 3006 PetscBLASInt one=1,bnz; 3007 3008 PetscFunctionBegin; 3009 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 3010 if (str == SAME_NONZERO_PATTERN) { 3011 PetscScalar alpha = a; 3012 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 3013 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 3014 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 3015 if (y->xtoy && y->XtoY != X) { 3016 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 3017 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 3018 } 3019 if (!y->xtoy) { /* get xtoy */ 3020 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 3021 y->XtoY = X; 3022 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 3023 } 3024 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 3025 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); 3026 } else { 3027 Mat B; 3028 PetscInt *nnz; 3029 ierr = PetscMalloc(Y->rmap->N*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 3030 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 3031 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 3032 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 3033 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 3034 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 3035 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 3036 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 3037 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 3038 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 3039 ierr = PetscFree(nnz);CHKERRQ(ierr); 3040 } 3041 PetscFunctionReturn(0); 3042 } 3043 3044 #undef __FUNCT__ 3045 #define __FUNCT__ "MatConjugate_SeqAIJ" 3046 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 3047 { 3048 #if defined(PETSC_USE_COMPLEX) 3049 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3050 PetscInt i,nz; 3051 PetscScalar *a; 3052 3053 PetscFunctionBegin; 3054 nz = aij->nz; 3055 a = aij->a; 3056 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3057 #else 3058 PetscFunctionBegin; 3059 #endif 3060 PetscFunctionReturn(0); 3061 } 3062 3063 #undef __FUNCT__ 3064 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 3065 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3066 { 3067 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3068 PetscErrorCode ierr; 3069 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3070 PetscReal atmp; 3071 PetscScalar *x; 3072 MatScalar *aa; 3073 3074 PetscFunctionBegin; 3075 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3076 aa = a->a; 3077 ai = a->i; 3078 aj = a->j; 3079 3080 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3081 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3082 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3083 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3084 for (i=0; i<m; i++) { 3085 ncols = ai[1] - ai[0]; ai++; 3086 x[i] = 0.0; 3087 for (j=0; j<ncols; j++) { 3088 atmp = PetscAbsScalar(*aa); 3089 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3090 aa++; aj++; 3091 } 3092 } 3093 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3094 PetscFunctionReturn(0); 3095 } 3096 3097 #undef __FUNCT__ 3098 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 3099 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3100 { 3101 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3102 PetscErrorCode ierr; 3103 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3104 PetscScalar *x; 3105 MatScalar *aa; 3106 3107 PetscFunctionBegin; 3108 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3109 aa = a->a; 3110 ai = a->i; 3111 aj = a->j; 3112 3113 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3114 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3115 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3116 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3117 for (i=0; i<m; i++) { 3118 ncols = ai[1] - ai[0]; ai++; 3119 if (ncols == A->cmap->n) { /* row is dense */ 3120 x[i] = *aa; if (idx) idx[i] = 0; 3121 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3122 x[i] = 0.0; 3123 if (idx) { 3124 idx[i] = 0; /* in case ncols is zero */ 3125 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3126 if (aj[j] > j) { 3127 idx[i] = j; 3128 break; 3129 } 3130 } 3131 } 3132 } 3133 for (j=0; j<ncols; j++) { 3134 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3135 aa++; aj++; 3136 } 3137 } 3138 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3139 PetscFunctionReturn(0); 3140 } 3141 3142 #undef __FUNCT__ 3143 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 3144 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3145 { 3146 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3147 PetscErrorCode ierr; 3148 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3149 PetscReal atmp; 3150 PetscScalar *x; 3151 MatScalar *aa; 3152 3153 PetscFunctionBegin; 3154 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3155 aa = a->a; 3156 ai = a->i; 3157 aj = a->j; 3158 3159 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3160 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3161 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3162 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); 3163 for (i=0; i<m; i++) { 3164 ncols = ai[1] - ai[0]; ai++; 3165 if (ncols) { 3166 /* Get first nonzero */ 3167 for (j = 0; j < ncols; j++) { 3168 atmp = PetscAbsScalar(aa[j]); 3169 if (atmp > 1.0e-12) { 3170 x[i] = atmp; 3171 if (idx) idx[i] = aj[j]; 3172 break; 3173 } 3174 } 3175 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3176 } else { 3177 x[i] = 0.0; if (idx) idx[i] = 0; 3178 } 3179 for (j = 0; j < ncols; j++) { 3180 atmp = PetscAbsScalar(*aa); 3181 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3182 aa++; aj++; 3183 } 3184 } 3185 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3186 PetscFunctionReturn(0); 3187 } 3188 3189 #undef __FUNCT__ 3190 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3191 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3192 { 3193 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3194 PetscErrorCode ierr; 3195 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3196 PetscScalar *x; 3197 MatScalar *aa; 3198 3199 PetscFunctionBegin; 3200 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3201 aa = a->a; 3202 ai = a->i; 3203 aj = a->j; 3204 3205 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3206 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3207 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3208 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3209 for (i=0; i<m; i++) { 3210 ncols = ai[1] - ai[0]; ai++; 3211 if (ncols == A->cmap->n) { /* row is dense */ 3212 x[i] = *aa; if (idx) idx[i] = 0; 3213 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3214 x[i] = 0.0; 3215 if (idx) { /* find first implicit 0.0 in the row */ 3216 idx[i] = 0; /* in case ncols is zero */ 3217 for (j=0; j<ncols; j++) { 3218 if (aj[j] > j) { 3219 idx[i] = j; 3220 break; 3221 } 3222 } 3223 } 3224 } 3225 for (j=0; j<ncols; j++) { 3226 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3227 aa++; aj++; 3228 } 3229 } 3230 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3231 PetscFunctionReturn(0); 3232 } 3233 3234 #include <petscblaslapack.h> 3235 #include <petsc-private/kernels/blockinvert.h> 3236 3237 #undef __FUNCT__ 3238 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3239 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3240 { 3241 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3242 PetscErrorCode ierr; 3243 PetscInt i,bs = A->rmap->bs,mbs = A->rmap->n/A->rmap->bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3244 MatScalar *diag,work[25],*v_work; 3245 PetscReal shift = 0.0; 3246 3247 PetscFunctionBegin; 3248 if (a->ibdiagvalid) { 3249 if (values) *values = a->ibdiag; 3250 PetscFunctionReturn(0); 3251 } 3252 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3253 if (!a->ibdiag) { 3254 ierr = PetscMalloc(bs2*mbs*sizeof(PetscScalar),&a->ibdiag);CHKERRQ(ierr); 3255 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3256 } 3257 diag = a->ibdiag; 3258 if (values) *values = a->ibdiag; 3259 /* factor and invert each block */ 3260 switch (bs) { 3261 case 1: 3262 for (i=0; i<mbs; i++) { 3263 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3264 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3265 } 3266 break; 3267 case 2: 3268 for (i=0; i<mbs; i++) { 3269 ij[0] = 2*i; ij[1] = 2*i + 1; 3270 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3271 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3272 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3273 diag += 4; 3274 } 3275 break; 3276 case 3: 3277 for (i=0; i<mbs; i++) { 3278 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3279 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3280 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3281 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3282 diag += 9; 3283 } 3284 break; 3285 case 4: 3286 for (i=0; i<mbs; i++) { 3287 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3288 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3289 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3290 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3291 diag += 16; 3292 } 3293 break; 3294 case 5: 3295 for (i=0; i<mbs; i++) { 3296 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3297 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3298 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3299 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3300 diag += 25; 3301 } 3302 break; 3303 case 6: 3304 for (i=0; i<mbs; i++) { 3305 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; 3306 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3307 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3308 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3309 diag += 36; 3310 } 3311 break; 3312 case 7: 3313 for (i=0; i<mbs; i++) { 3314 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; 3315 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3316 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3317 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3318 diag += 49; 3319 } 3320 break; 3321 default: 3322 ierr = PetscMalloc3(bs,MatScalar,&v_work,bs,PetscInt,&v_pivots,bs,PetscInt,&IJ);CHKERRQ(ierr); 3323 for (i=0; i<mbs; i++) { 3324 for (j=0; j<bs; j++) { 3325 IJ[j] = bs*i + j; 3326 } 3327 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3328 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3329 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3330 diag += bs2; 3331 } 3332 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3333 } 3334 a->ibdiagvalid = PETSC_TRUE; 3335 PetscFunctionReturn(0); 3336 } 3337 3338 #undef __FUNCT__ 3339 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3340 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3341 { 3342 PetscErrorCode ierr; 3343 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3344 PetscScalar a; 3345 PetscInt m,n,i,j,col; 3346 3347 PetscFunctionBegin; 3348 if (!x->assembled) { 3349 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3350 for (i=0; i<m; i++) { 3351 for (j=0; j<aij->imax[i]; j++) { 3352 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3353 col = (PetscInt)(n*PetscRealPart(a)); 3354 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3355 } 3356 } 3357 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3358 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3359 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3360 PetscFunctionReturn(0); 3361 } 3362 3363 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3364 /* -------------------------------------------------------------------*/ 3365 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3366 MatGetRow_SeqAIJ, 3367 MatRestoreRow_SeqAIJ, 3368 MatMult_SeqAIJ, 3369 /* 4*/ MatMultAdd_SeqAIJ, 3370 MatMultTranspose_SeqAIJ, 3371 MatMultTransposeAdd_SeqAIJ, 3372 0, 3373 0, 3374 0, 3375 /* 10*/ 0, 3376 MatLUFactor_SeqAIJ, 3377 0, 3378 MatSOR_SeqAIJ, 3379 MatTranspose_SeqAIJ, 3380 /*1 5*/ MatGetInfo_SeqAIJ, 3381 MatEqual_SeqAIJ, 3382 MatGetDiagonal_SeqAIJ, 3383 MatDiagonalScale_SeqAIJ, 3384 MatNorm_SeqAIJ, 3385 /* 20*/ 0, 3386 MatAssemblyEnd_SeqAIJ, 3387 MatSetOption_SeqAIJ, 3388 MatZeroEntries_SeqAIJ, 3389 /* 24*/ MatZeroRows_SeqAIJ, 3390 0, 3391 0, 3392 0, 3393 0, 3394 /* 29*/ MatSetUp_SeqAIJ, 3395 0, 3396 0, 3397 0, 3398 0, 3399 /* 34*/ MatDuplicate_SeqAIJ, 3400 0, 3401 0, 3402 MatILUFactor_SeqAIJ, 3403 0, 3404 /* 39*/ MatAXPY_SeqAIJ, 3405 MatGetSubMatrices_SeqAIJ, 3406 MatIncreaseOverlap_SeqAIJ, 3407 MatGetValues_SeqAIJ, 3408 MatCopy_SeqAIJ, 3409 /* 44*/ MatGetRowMax_SeqAIJ, 3410 MatScale_SeqAIJ, 3411 0, 3412 MatDiagonalSet_SeqAIJ, 3413 MatZeroRowsColumns_SeqAIJ, 3414 /* 49*/ MatSetRandom_SeqAIJ, 3415 MatGetRowIJ_SeqAIJ, 3416 MatRestoreRowIJ_SeqAIJ, 3417 MatGetColumnIJ_SeqAIJ, 3418 MatRestoreColumnIJ_SeqAIJ, 3419 /* 54*/ MatFDColoringCreate_SeqAIJ, 3420 0, 3421 0, 3422 MatPermute_SeqAIJ, 3423 0, 3424 /* 59*/ 0, 3425 MatDestroy_SeqAIJ, 3426 MatView_SeqAIJ, 3427 0, 3428 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3429 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3430 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3431 0, 3432 0, 3433 0, 3434 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3435 MatGetRowMinAbs_SeqAIJ, 3436 0, 3437 MatSetColoring_SeqAIJ, 3438 0, 3439 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3440 MatFDColoringApply_AIJ, 3441 0, 3442 0, 3443 0, 3444 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3445 0, 3446 0, 3447 0, 3448 MatLoad_SeqAIJ, 3449 /* 84*/ MatIsSymmetric_SeqAIJ, 3450 MatIsHermitian_SeqAIJ, 3451 0, 3452 0, 3453 0, 3454 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3455 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3456 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3457 MatPtAP_SeqAIJ_SeqAIJ, 3458 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3459 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3460 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3461 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3462 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3463 0, 3464 /* 99*/ 0, 3465 0, 3466 0, 3467 MatConjugate_SeqAIJ, 3468 0, 3469 /*104*/ MatSetValuesRow_SeqAIJ, 3470 MatRealPart_SeqAIJ, 3471 MatImaginaryPart_SeqAIJ, 3472 0, 3473 0, 3474 /*109*/ MatMatSolve_SeqAIJ, 3475 0, 3476 MatGetRowMin_SeqAIJ, 3477 0, 3478 MatMissingDiagonal_SeqAIJ, 3479 /*114*/ 0, 3480 0, 3481 0, 3482 0, 3483 0, 3484 /*119*/ 0, 3485 0, 3486 0, 3487 0, 3488 MatGetMultiProcBlock_SeqAIJ, 3489 /*124*/ MatFindNonzeroRows_SeqAIJ, 3490 MatGetColumnNorms_SeqAIJ, 3491 MatInvertBlockDiagonal_SeqAIJ, 3492 0, 3493 0, 3494 /*129*/ 0, 3495 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3496 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3497 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3498 MatTransposeColoringCreate_SeqAIJ, 3499 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3500 MatTransColoringApplyDenToSp_SeqAIJ, 3501 MatRARt_SeqAIJ_SeqAIJ, 3502 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3503 MatRARtNumeric_SeqAIJ_SeqAIJ, 3504 /*139*/0, 3505 0 3506 }; 3507 3508 #undef __FUNCT__ 3509 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3510 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3511 { 3512 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3513 PetscInt i,nz,n; 3514 3515 PetscFunctionBegin; 3516 nz = aij->maxnz; 3517 n = mat->rmap->n; 3518 for (i=0; i<nz; i++) { 3519 aij->j[i] = indices[i]; 3520 } 3521 aij->nz = nz; 3522 for (i=0; i<n; i++) { 3523 aij->ilen[i] = aij->imax[i]; 3524 } 3525 PetscFunctionReturn(0); 3526 } 3527 3528 #undef __FUNCT__ 3529 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3530 /*@ 3531 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3532 in the matrix. 3533 3534 Input Parameters: 3535 + mat - the SeqAIJ matrix 3536 - indices - the column indices 3537 3538 Level: advanced 3539 3540 Notes: 3541 This can be called if you have precomputed the nonzero structure of the 3542 matrix and want to provide it to the matrix object to improve the performance 3543 of the MatSetValues() operation. 3544 3545 You MUST have set the correct numbers of nonzeros per row in the call to 3546 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3547 3548 MUST be called before any calls to MatSetValues(); 3549 3550 The indices should start with zero, not one. 3551 3552 @*/ 3553 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3554 { 3555 PetscErrorCode ierr; 3556 3557 PetscFunctionBegin; 3558 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3559 PetscValidPointer(indices,2); 3560 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3561 PetscFunctionReturn(0); 3562 } 3563 3564 /* ----------------------------------------------------------------------------------------*/ 3565 3566 #undef __FUNCT__ 3567 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3568 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3569 { 3570 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3571 PetscErrorCode ierr; 3572 size_t nz = aij->i[mat->rmap->n]; 3573 3574 PetscFunctionBegin; 3575 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3576 3577 /* allocate space for values if not already there */ 3578 if (!aij->saved_values) { 3579 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 3580 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3581 } 3582 3583 /* copy values over */ 3584 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3585 PetscFunctionReturn(0); 3586 } 3587 3588 #undef __FUNCT__ 3589 #define __FUNCT__ "MatStoreValues" 3590 /*@ 3591 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3592 example, reuse of the linear part of a Jacobian, while recomputing the 3593 nonlinear portion. 3594 3595 Collect on Mat 3596 3597 Input Parameters: 3598 . mat - the matrix (currently only AIJ matrices support this option) 3599 3600 Level: advanced 3601 3602 Common Usage, with SNESSolve(): 3603 $ Create Jacobian matrix 3604 $ Set linear terms into matrix 3605 $ Apply boundary conditions to matrix, at this time matrix must have 3606 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3607 $ boundary conditions again will not change the nonzero structure 3608 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3609 $ ierr = MatStoreValues(mat); 3610 $ Call SNESSetJacobian() with matrix 3611 $ In your Jacobian routine 3612 $ ierr = MatRetrieveValues(mat); 3613 $ Set nonlinear terms in matrix 3614 3615 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3616 $ // build linear portion of Jacobian 3617 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3618 $ ierr = MatStoreValues(mat); 3619 $ loop over nonlinear iterations 3620 $ ierr = MatRetrieveValues(mat); 3621 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3622 $ // call MatAssemblyBegin/End() on matrix 3623 $ Solve linear system with Jacobian 3624 $ endloop 3625 3626 Notes: 3627 Matrix must already be assemblied before calling this routine 3628 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3629 calling this routine. 3630 3631 When this is called multiple times it overwrites the previous set of stored values 3632 and does not allocated additional space. 3633 3634 .seealso: MatRetrieveValues() 3635 3636 @*/ 3637 PetscErrorCode MatStoreValues(Mat mat) 3638 { 3639 PetscErrorCode ierr; 3640 3641 PetscFunctionBegin; 3642 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3643 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3644 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3645 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3646 PetscFunctionReturn(0); 3647 } 3648 3649 #undef __FUNCT__ 3650 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3651 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3652 { 3653 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3654 PetscErrorCode ierr; 3655 PetscInt nz = aij->i[mat->rmap->n]; 3656 3657 PetscFunctionBegin; 3658 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3659 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3660 /* copy values over */ 3661 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3662 PetscFunctionReturn(0); 3663 } 3664 3665 #undef __FUNCT__ 3666 #define __FUNCT__ "MatRetrieveValues" 3667 /*@ 3668 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3669 example, reuse of the linear part of a Jacobian, while recomputing the 3670 nonlinear portion. 3671 3672 Collect on Mat 3673 3674 Input Parameters: 3675 . mat - the matrix (currently on AIJ matrices support this option) 3676 3677 Level: advanced 3678 3679 .seealso: MatStoreValues() 3680 3681 @*/ 3682 PetscErrorCode MatRetrieveValues(Mat mat) 3683 { 3684 PetscErrorCode ierr; 3685 3686 PetscFunctionBegin; 3687 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3688 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3689 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3690 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3691 PetscFunctionReturn(0); 3692 } 3693 3694 3695 /* --------------------------------------------------------------------------------*/ 3696 #undef __FUNCT__ 3697 #define __FUNCT__ "MatCreateSeqAIJ" 3698 /*@C 3699 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3700 (the default parallel PETSc format). For good matrix assembly performance 3701 the user should preallocate the matrix storage by setting the parameter nz 3702 (or the array nnz). By setting these parameters accurately, performance 3703 during matrix assembly can be increased by more than a factor of 50. 3704 3705 Collective on MPI_Comm 3706 3707 Input Parameters: 3708 + comm - MPI communicator, set to PETSC_COMM_SELF 3709 . m - number of rows 3710 . n - number of columns 3711 . nz - number of nonzeros per row (same for all rows) 3712 - nnz - array containing the number of nonzeros in the various rows 3713 (possibly different for each row) or NULL 3714 3715 Output Parameter: 3716 . A - the matrix 3717 3718 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3719 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3720 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3721 3722 Notes: 3723 If nnz is given then nz is ignored 3724 3725 The AIJ format (also called the Yale sparse matrix format or 3726 compressed row storage), is fully compatible with standard Fortran 77 3727 storage. That is, the stored row and column indices can begin at 3728 either one (as in Fortran) or zero. See the users' manual for details. 3729 3730 Specify the preallocated storage with either nz or nnz (not both). 3731 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3732 allocation. For large problems you MUST preallocate memory or you 3733 will get TERRIBLE performance, see the users' manual chapter on matrices. 3734 3735 By default, this format uses inodes (identical nodes) when possible, to 3736 improve numerical efficiency of matrix-vector products and solves. We 3737 search for consecutive rows with the same nonzero structure, thereby 3738 reusing matrix information to achieve increased efficiency. 3739 3740 Options Database Keys: 3741 + -mat_no_inode - Do not use inodes 3742 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3743 3744 Level: intermediate 3745 3746 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3747 3748 @*/ 3749 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3750 { 3751 PetscErrorCode ierr; 3752 3753 PetscFunctionBegin; 3754 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3755 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3756 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3757 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3758 PetscFunctionReturn(0); 3759 } 3760 3761 #undef __FUNCT__ 3762 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3763 /*@C 3764 MatSeqAIJSetPreallocation - For good matrix assembly performance 3765 the user should preallocate the matrix storage by setting the parameter nz 3766 (or the array nnz). By setting these parameters accurately, performance 3767 during matrix assembly can be increased by more than a factor of 50. 3768 3769 Collective on MPI_Comm 3770 3771 Input Parameters: 3772 + B - The matrix-free 3773 . nz - number of nonzeros per row (same for all rows) 3774 - nnz - array containing the number of nonzeros in the various rows 3775 (possibly different for each row) or NULL 3776 3777 Notes: 3778 If nnz is given then nz is ignored 3779 3780 The AIJ format (also called the Yale sparse matrix format or 3781 compressed row storage), is fully compatible with standard Fortran 77 3782 storage. That is, the stored row and column indices can begin at 3783 either one (as in Fortran) or zero. See the users' manual for details. 3784 3785 Specify the preallocated storage with either nz or nnz (not both). 3786 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3787 allocation. For large problems you MUST preallocate memory or you 3788 will get TERRIBLE performance, see the users' manual chapter on matrices. 3789 3790 You can call MatGetInfo() to get information on how effective the preallocation was; 3791 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3792 You can also run with the option -info and look for messages with the string 3793 malloc in them to see if additional memory allocation was needed. 3794 3795 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3796 entries or columns indices 3797 3798 By default, this format uses inodes (identical nodes) when possible, to 3799 improve numerical efficiency of matrix-vector products and solves. We 3800 search for consecutive rows with the same nonzero structure, thereby 3801 reusing matrix information to achieve increased efficiency. 3802 3803 Options Database Keys: 3804 + -mat_no_inode - Do not use inodes 3805 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3806 - -mat_aij_oneindex - Internally use indexing starting at 1 3807 rather than 0. Note that when calling MatSetValues(), 3808 the user still MUST index entries starting at 0! 3809 3810 Level: intermediate 3811 3812 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3813 3814 @*/ 3815 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3816 { 3817 PetscErrorCode ierr; 3818 3819 PetscFunctionBegin; 3820 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3821 PetscValidType(B,1); 3822 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3823 PetscFunctionReturn(0); 3824 } 3825 3826 #undef __FUNCT__ 3827 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3828 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3829 { 3830 Mat_SeqAIJ *b; 3831 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3832 PetscErrorCode ierr; 3833 PetscInt i; 3834 3835 PetscFunctionBegin; 3836 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3837 if (nz == MAT_SKIP_ALLOCATION) { 3838 skipallocation = PETSC_TRUE; 3839 nz = 0; 3840 } 3841 3842 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3843 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3844 3845 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3846 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3847 if (nnz) { 3848 for (i=0; i<B->rmap->n; i++) { 3849 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]); 3850 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); 3851 } 3852 } 3853 3854 B->preallocated = PETSC_TRUE; 3855 3856 b = (Mat_SeqAIJ*)B->data; 3857 3858 if (!skipallocation) { 3859 if (!b->imax) { 3860 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3861 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3862 } 3863 if (!nnz) { 3864 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3865 else if (nz < 0) nz = 1; 3866 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3867 nz = nz*B->rmap->n; 3868 } else { 3869 nz = 0; 3870 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3871 } 3872 /* b->ilen will count nonzeros in each row so far. */ 3873 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3874 3875 /* allocate the matrix space */ 3876 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3877 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3878 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3879 b->i[0] = 0; 3880 for (i=1; i<B->rmap->n+1; i++) { 3881 b->i[i] = b->i[i-1] + b->imax[i-1]; 3882 } 3883 b->singlemalloc = PETSC_TRUE; 3884 b->free_a = PETSC_TRUE; 3885 b->free_ij = PETSC_TRUE; 3886 #if defined(PETSC_THREADCOMM_ACTIVE) 3887 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3888 #endif 3889 } else { 3890 b->free_a = PETSC_FALSE; 3891 b->free_ij = PETSC_FALSE; 3892 } 3893 3894 b->nz = 0; 3895 b->maxnz = nz; 3896 B->info.nz_unneeded = (double)b->maxnz; 3897 if (realalloc) { 3898 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3899 } 3900 PetscFunctionReturn(0); 3901 } 3902 3903 #undef __FUNCT__ 3904 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3905 /*@ 3906 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3907 3908 Input Parameters: 3909 + B - the matrix 3910 . i - the indices into j for the start of each row (starts with zero) 3911 . j - the column indices for each row (starts with zero) these must be sorted for each row 3912 - v - optional values in the matrix 3913 3914 Level: developer 3915 3916 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3917 3918 .keywords: matrix, aij, compressed row, sparse, sequential 3919 3920 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3921 @*/ 3922 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3923 { 3924 PetscErrorCode ierr; 3925 3926 PetscFunctionBegin; 3927 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3928 PetscValidType(B,1); 3929 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3930 PetscFunctionReturn(0); 3931 } 3932 3933 #undef __FUNCT__ 3934 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3935 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3936 { 3937 PetscInt i; 3938 PetscInt m,n; 3939 PetscInt nz; 3940 PetscInt *nnz, nz_max = 0; 3941 PetscScalar *values; 3942 PetscErrorCode ierr; 3943 3944 PetscFunctionBegin; 3945 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3946 3947 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3948 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3949 3950 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3951 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 3952 for (i = 0; i < m; i++) { 3953 nz = Ii[i+1]- Ii[i]; 3954 nz_max = PetscMax(nz_max, nz); 3955 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3956 nnz[i] = nz; 3957 } 3958 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3959 ierr = PetscFree(nnz);CHKERRQ(ierr); 3960 3961 if (v) { 3962 values = (PetscScalar*) v; 3963 } else { 3964 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 3965 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3966 } 3967 3968 for (i = 0; i < m; i++) { 3969 nz = Ii[i+1] - Ii[i]; 3970 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3971 } 3972 3973 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3974 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3975 3976 if (!v) { 3977 ierr = PetscFree(values);CHKERRQ(ierr); 3978 } 3979 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3980 PetscFunctionReturn(0); 3981 } 3982 3983 #include <../src/mat/impls/dense/seq/dense.h> 3984 #include <petsc-private/kernels/petscaxpy.h> 3985 3986 #undef __FUNCT__ 3987 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3988 /* 3989 Computes (B'*A')' since computing B*A directly is untenable 3990 3991 n p p 3992 ( ) ( ) ( ) 3993 m ( A ) * n ( B ) = m ( C ) 3994 ( ) ( ) ( ) 3995 3996 */ 3997 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3998 { 3999 PetscErrorCode ierr; 4000 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4001 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4002 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4003 PetscInt i,n,m,q,p; 4004 const PetscInt *ii,*idx; 4005 const PetscScalar *b,*a,*a_q; 4006 PetscScalar *c,*c_q; 4007 4008 PetscFunctionBegin; 4009 m = A->rmap->n; 4010 n = A->cmap->n; 4011 p = B->cmap->n; 4012 a = sub_a->v; 4013 b = sub_b->a; 4014 c = sub_c->v; 4015 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 4016 4017 ii = sub_b->i; 4018 idx = sub_b->j; 4019 for (i=0; i<n; i++) { 4020 q = ii[i+1] - ii[i]; 4021 while (q-->0) { 4022 c_q = c + m*(*idx); 4023 a_q = a + m*i; 4024 PetscKernelAXPY(c_q,*b,a_q,m); 4025 idx++; 4026 b++; 4027 } 4028 } 4029 PetscFunctionReturn(0); 4030 } 4031 4032 #undef __FUNCT__ 4033 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 4034 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4035 { 4036 PetscErrorCode ierr; 4037 PetscInt m=A->rmap->n,n=B->cmap->n; 4038 Mat Cmat; 4039 4040 PetscFunctionBegin; 4041 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); 4042 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4043 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4044 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 4045 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4046 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4047 4048 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4049 4050 *C = Cmat; 4051 PetscFunctionReturn(0); 4052 } 4053 4054 /* ----------------------------------------------------------------*/ 4055 #undef __FUNCT__ 4056 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 4057 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4058 { 4059 PetscErrorCode ierr; 4060 4061 PetscFunctionBegin; 4062 if (scall == MAT_INITIAL_MATRIX) { 4063 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4064 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4065 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4066 } 4067 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4068 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4069 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4070 PetscFunctionReturn(0); 4071 } 4072 4073 4074 /*MC 4075 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4076 based on compressed sparse row format. 4077 4078 Options Database Keys: 4079 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4080 4081 Level: beginner 4082 4083 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4084 M*/ 4085 4086 /*MC 4087 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4088 4089 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4090 and MATMPIAIJ otherwise. As a result, for single process communicators, 4091 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 4092 for communicators controlling multiple processes. It is recommended that you call both of 4093 the above preallocation routines for simplicity. 4094 4095 Options Database Keys: 4096 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4097 4098 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 4099 enough exist. 4100 4101 Level: beginner 4102 4103 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4104 M*/ 4105 4106 /*MC 4107 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4108 4109 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4110 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4111 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4112 for communicators controlling multiple processes. It is recommended that you call both of 4113 the above preallocation routines for simplicity. 4114 4115 Options Database Keys: 4116 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4117 4118 Level: beginner 4119 4120 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4121 M*/ 4122 4123 #if defined(PETSC_HAVE_PASTIX) 4124 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 4125 #endif 4126 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4127 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 4128 #endif 4129 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4130 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 4131 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 4132 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 4133 #if defined(PETSC_HAVE_MUMPS) 4134 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 4135 #endif 4136 #if defined(PETSC_HAVE_SUPERLU) 4137 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 4138 #endif 4139 #if defined(PETSC_HAVE_SUPERLU_DIST) 4140 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 4141 #endif 4142 #if defined(PETSC_HAVE_UMFPACK) 4143 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 4144 #endif 4145 #if defined(PETSC_HAVE_CHOLMOD) 4146 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 4147 #endif 4148 #if defined(PETSC_HAVE_LUSOL) 4149 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 4150 #endif 4151 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4152 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 4153 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 4154 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 4155 #endif 4156 #if defined(PETSC_HAVE_CLIQUE) 4157 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 4158 #endif 4159 4160 4161 #undef __FUNCT__ 4162 #define __FUNCT__ "MatSeqAIJGetArray" 4163 /*@C 4164 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 4165 4166 Not Collective 4167 4168 Input Parameter: 4169 . mat - a MATSEQDENSE matrix 4170 4171 Output Parameter: 4172 . array - pointer to the data 4173 4174 Level: intermediate 4175 4176 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4177 @*/ 4178 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4179 { 4180 PetscErrorCode ierr; 4181 4182 PetscFunctionBegin; 4183 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4184 PetscFunctionReturn(0); 4185 } 4186 4187 #undef __FUNCT__ 4188 #define __FUNCT__ "MatSeqAIJRestoreArray" 4189 /*@C 4190 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4191 4192 Not Collective 4193 4194 Input Parameters: 4195 . mat - a MATSEQDENSE matrix 4196 . array - pointer to the data 4197 4198 Level: intermediate 4199 4200 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4201 @*/ 4202 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4203 { 4204 PetscErrorCode ierr; 4205 4206 PetscFunctionBegin; 4207 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4208 PetscFunctionReturn(0); 4209 } 4210 4211 #undef __FUNCT__ 4212 #define __FUNCT__ "MatCreate_SeqAIJ" 4213 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4214 { 4215 Mat_SeqAIJ *b; 4216 PetscErrorCode ierr; 4217 PetscMPIInt size; 4218 4219 PetscFunctionBegin; 4220 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4221 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4222 4223 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 4224 4225 B->data = (void*)b; 4226 4227 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4228 4229 b->row = 0; 4230 b->col = 0; 4231 b->icol = 0; 4232 b->reallocs = 0; 4233 b->ignorezeroentries = PETSC_FALSE; 4234 b->roworiented = PETSC_TRUE; 4235 b->nonew = 0; 4236 b->diag = 0; 4237 b->solve_work = 0; 4238 B->spptr = 0; 4239 b->saved_values = 0; 4240 b->idiag = 0; 4241 b->mdiag = 0; 4242 b->ssor_work = 0; 4243 b->omega = 1.0; 4244 b->fshift = 0.0; 4245 b->idiagvalid = PETSC_FALSE; 4246 b->ibdiagvalid = PETSC_FALSE; 4247 b->keepnonzeropattern = PETSC_FALSE; 4248 b->xtoy = 0; 4249 b->XtoY = 0; 4250 B->same_nonzero = PETSC_FALSE; 4251 4252 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4253 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4254 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4255 4256 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4257 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4258 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4259 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4260 #endif 4261 #if defined(PETSC_HAVE_PASTIX) 4262 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4263 #endif 4264 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4265 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4266 #endif 4267 #if defined(PETSC_HAVE_SUPERLU) 4268 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4269 #endif 4270 #if defined(PETSC_HAVE_SUPERLU_DIST) 4271 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4272 #endif 4273 #if defined(PETSC_HAVE_MUMPS) 4274 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4275 #endif 4276 #if defined(PETSC_HAVE_UMFPACK) 4277 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4278 #endif 4279 #if defined(PETSC_HAVE_CHOLMOD) 4280 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4281 #endif 4282 #if defined(PETSC_HAVE_LUSOL) 4283 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4284 #endif 4285 #if defined(PETSC_HAVE_CLIQUE) 4286 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4287 #endif 4288 4289 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4290 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4291 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4292 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4293 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4294 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4295 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4296 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4297 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4298 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4299 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4300 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4301 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4302 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4303 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4304 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4305 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4306 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4307 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4308 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4309 PetscFunctionReturn(0); 4310 } 4311 4312 #undef __FUNCT__ 4313 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4314 /* 4315 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4316 */ 4317 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4318 { 4319 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4320 PetscErrorCode ierr; 4321 PetscInt i,m = A->rmap->n; 4322 4323 PetscFunctionBegin; 4324 c = (Mat_SeqAIJ*)C->data; 4325 4326 C->factortype = A->factortype; 4327 c->row = 0; 4328 c->col = 0; 4329 c->icol = 0; 4330 c->reallocs = 0; 4331 4332 C->assembled = PETSC_TRUE; 4333 4334 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4335 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4336 4337 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 4338 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4339 for (i=0; i<m; i++) { 4340 c->imax[i] = a->imax[i]; 4341 c->ilen[i] = a->ilen[i]; 4342 } 4343 4344 /* allocate the matrix space */ 4345 if (mallocmatspace) { 4346 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 4347 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4348 4349 c->singlemalloc = PETSC_TRUE; 4350 4351 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4352 if (m > 0) { 4353 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4354 if (cpvalues == MAT_COPY_VALUES) { 4355 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4356 } else { 4357 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4358 } 4359 } 4360 } 4361 4362 c->ignorezeroentries = a->ignorezeroentries; 4363 c->roworiented = a->roworiented; 4364 c->nonew = a->nonew; 4365 if (a->diag) { 4366 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 4367 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4368 for (i=0; i<m; i++) { 4369 c->diag[i] = a->diag[i]; 4370 } 4371 } else c->diag = 0; 4372 4373 c->solve_work = 0; 4374 c->saved_values = 0; 4375 c->idiag = 0; 4376 c->ssor_work = 0; 4377 c->keepnonzeropattern = a->keepnonzeropattern; 4378 c->free_a = PETSC_TRUE; 4379 c->free_ij = PETSC_TRUE; 4380 c->xtoy = 0; 4381 c->XtoY = 0; 4382 4383 c->rmax = a->rmax; 4384 c->nz = a->nz; 4385 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4386 C->preallocated = PETSC_TRUE; 4387 4388 c->compressedrow.use = a->compressedrow.use; 4389 c->compressedrow.nrows = a->compressedrow.nrows; 4390 c->compressedrow.check = a->compressedrow.check; 4391 if (a->compressedrow.use) { 4392 i = a->compressedrow.nrows; 4393 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 4394 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4395 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4396 } else { 4397 c->compressedrow.use = PETSC_FALSE; 4398 c->compressedrow.i = NULL; 4399 c->compressedrow.rindex = NULL; 4400 } 4401 C->same_nonzero = A->same_nonzero; 4402 4403 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4404 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4405 PetscFunctionReturn(0); 4406 } 4407 4408 #undef __FUNCT__ 4409 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4410 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4411 { 4412 PetscErrorCode ierr; 4413 4414 PetscFunctionBegin; 4415 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4416 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4417 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4418 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4419 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4420 PetscFunctionReturn(0); 4421 } 4422 4423 #undef __FUNCT__ 4424 #define __FUNCT__ "MatLoad_SeqAIJ" 4425 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4426 { 4427 Mat_SeqAIJ *a; 4428 PetscErrorCode ierr; 4429 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4430 int fd; 4431 PetscMPIInt size; 4432 MPI_Comm comm; 4433 PetscInt bs = 1; 4434 4435 PetscFunctionBegin; 4436 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4437 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4438 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4439 4440 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4441 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4442 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4443 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4444 4445 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4446 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4447 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4448 M = header[1]; N = header[2]; nz = header[3]; 4449 4450 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4451 4452 /* read in row lengths */ 4453 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 4454 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4455 4456 /* check if sum of rowlengths is same as nz */ 4457 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4458 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); 4459 4460 /* set global size if not set already*/ 4461 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4462 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4463 } else { 4464 /* if sizes and type are already set, check if the vector global sizes are correct */ 4465 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4466 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4467 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4468 } 4469 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); 4470 } 4471 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4472 a = (Mat_SeqAIJ*)newMat->data; 4473 4474 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4475 4476 /* read in nonzero values */ 4477 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4478 4479 /* set matrix "i" values */ 4480 a->i[0] = 0; 4481 for (i=1; i<= M; i++) { 4482 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4483 a->ilen[i-1] = rowlengths[i-1]; 4484 } 4485 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4486 4487 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4488 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4489 PetscFunctionReturn(0); 4490 } 4491 4492 #undef __FUNCT__ 4493 #define __FUNCT__ "MatEqual_SeqAIJ" 4494 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4495 { 4496 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4497 PetscErrorCode ierr; 4498 #if defined(PETSC_USE_COMPLEX) 4499 PetscInt k; 4500 #endif 4501 4502 PetscFunctionBegin; 4503 /* If the matrix dimensions are not equal,or no of nonzeros */ 4504 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4505 *flg = PETSC_FALSE; 4506 PetscFunctionReturn(0); 4507 } 4508 4509 /* if the a->i are the same */ 4510 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4511 if (!*flg) PetscFunctionReturn(0); 4512 4513 /* if a->j are the same */ 4514 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4515 if (!*flg) PetscFunctionReturn(0); 4516 4517 /* if a->a are the same */ 4518 #if defined(PETSC_USE_COMPLEX) 4519 for (k=0; k<a->nz; k++) { 4520 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4521 *flg = PETSC_FALSE; 4522 PetscFunctionReturn(0); 4523 } 4524 } 4525 #else 4526 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4527 #endif 4528 PetscFunctionReturn(0); 4529 } 4530 4531 #undef __FUNCT__ 4532 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4533 /*@ 4534 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4535 provided by the user. 4536 4537 Collective on MPI_Comm 4538 4539 Input Parameters: 4540 + comm - must be an MPI communicator of size 1 4541 . m - number of rows 4542 . n - number of columns 4543 . i - row indices 4544 . j - column indices 4545 - a - matrix values 4546 4547 Output Parameter: 4548 . mat - the matrix 4549 4550 Level: intermediate 4551 4552 Notes: 4553 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4554 once the matrix is destroyed and not before 4555 4556 You cannot set new nonzero locations into this matrix, that will generate an error. 4557 4558 The i and j indices are 0 based 4559 4560 The format which is used for the sparse matrix input, is equivalent to a 4561 row-major ordering.. i.e for the following matrix, the input data expected is 4562 as shown: 4563 4564 1 0 0 4565 2 0 3 4566 4 5 6 4567 4568 i = {0,1,3,6} [size = nrow+1 = 3+1] 4569 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4570 v = {1,2,3,4,5,6} [size = nz = 6] 4571 4572 4573 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4574 4575 @*/ 4576 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4577 { 4578 PetscErrorCode ierr; 4579 PetscInt ii; 4580 Mat_SeqAIJ *aij; 4581 #if defined(PETSC_USE_DEBUG) 4582 PetscInt jj; 4583 #endif 4584 4585 PetscFunctionBegin; 4586 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4587 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4588 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4589 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4590 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4591 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4592 aij = (Mat_SeqAIJ*)(*mat)->data; 4593 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 4594 4595 aij->i = i; 4596 aij->j = j; 4597 aij->a = a; 4598 aij->singlemalloc = PETSC_FALSE; 4599 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4600 aij->free_a = PETSC_FALSE; 4601 aij->free_ij = PETSC_FALSE; 4602 4603 for (ii=0; ii<m; ii++) { 4604 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4605 #if defined(PETSC_USE_DEBUG) 4606 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]); 4607 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4608 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); 4609 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); 4610 } 4611 #endif 4612 } 4613 #if defined(PETSC_USE_DEBUG) 4614 for (ii=0; ii<aij->i[m]; ii++) { 4615 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 4616 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]); 4617 } 4618 #endif 4619 4620 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4621 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4622 PetscFunctionReturn(0); 4623 } 4624 #undef __FUNCT__ 4625 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4626 /*@C 4627 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4628 provided by the user. 4629 4630 Collective on MPI_Comm 4631 4632 Input Parameters: 4633 + comm - must be an MPI communicator of size 1 4634 . m - number of rows 4635 . n - number of columns 4636 . i - row indices 4637 . j - column indices 4638 . a - matrix values 4639 . nz - number of nonzeros 4640 - idx - 0 or 1 based 4641 4642 Output Parameter: 4643 . mat - the matrix 4644 4645 Level: intermediate 4646 4647 Notes: 4648 The i and j indices are 0 based 4649 4650 The format which is used for the sparse matrix input, is equivalent to a 4651 row-major ordering.. i.e for the following matrix, the input data expected is 4652 as shown: 4653 4654 1 0 0 4655 2 0 3 4656 4 5 6 4657 4658 i = {0,1,1,2,2,2} 4659 j = {0,0,2,0,1,2} 4660 v = {1,2,3,4,5,6} 4661 4662 4663 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4664 4665 @*/ 4666 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4667 { 4668 PetscErrorCode ierr; 4669 PetscInt ii, *nnz, one = 1,row,col; 4670 4671 4672 PetscFunctionBegin; 4673 ierr = PetscMalloc(m*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 4674 ierr = PetscMemzero(nnz,m*sizeof(PetscInt));CHKERRQ(ierr); 4675 for (ii = 0; ii < nz; ii++) { 4676 nnz[i[ii]] += 1; 4677 } 4678 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4679 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4680 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4681 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4682 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4683 for (ii = 0; ii < nz; ii++) { 4684 if (idx) { 4685 row = i[ii] - 1; 4686 col = j[ii] - 1; 4687 } else { 4688 row = i[ii]; 4689 col = j[ii]; 4690 } 4691 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4692 } 4693 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4694 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4695 ierr = PetscFree(nnz);CHKERRQ(ierr); 4696 PetscFunctionReturn(0); 4697 } 4698 4699 #undef __FUNCT__ 4700 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4701 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4702 { 4703 PetscErrorCode ierr; 4704 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4705 4706 PetscFunctionBegin; 4707 if (coloring->ctype == IS_COLORING_GLOBAL) { 4708 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4709 a->coloring = coloring; 4710 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4711 PetscInt i,*larray; 4712 ISColoring ocoloring; 4713 ISColoringValue *colors; 4714 4715 /* set coloring for diagonal portion */ 4716 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4717 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4718 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4719 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4720 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4721 ierr = PetscFree(larray);CHKERRQ(ierr); 4722 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4723 a->coloring = ocoloring; 4724 } 4725 PetscFunctionReturn(0); 4726 } 4727 4728 #undef __FUNCT__ 4729 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4730 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4731 { 4732 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4733 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4734 MatScalar *v = a->a; 4735 PetscScalar *values = (PetscScalar*)advalues; 4736 ISColoringValue *color; 4737 4738 PetscFunctionBegin; 4739 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4740 color = a->coloring->colors; 4741 /* loop over rows */ 4742 for (i=0; i<m; i++) { 4743 nz = ii[i+1] - ii[i]; 4744 /* loop over columns putting computed value into matrix */ 4745 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4746 values += nl; /* jump to next row of derivatives */ 4747 } 4748 PetscFunctionReturn(0); 4749 } 4750 4751 #undef __FUNCT__ 4752 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4753 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4754 { 4755 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4756 PetscErrorCode ierr; 4757 4758 PetscFunctionBegin; 4759 a->idiagvalid = PETSC_FALSE; 4760 a->ibdiagvalid = PETSC_FALSE; 4761 4762 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4763 PetscFunctionReturn(0); 4764 } 4765 4766 /* 4767 Special version for direct calls from Fortran 4768 */ 4769 #include <petsc-private/fortranimpl.h> 4770 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4771 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4772 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4773 #define matsetvaluesseqaij_ matsetvaluesseqaij 4774 #endif 4775 4776 /* Change these macros so can be used in void function */ 4777 #undef CHKERRQ 4778 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4779 #undef SETERRQ2 4780 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4781 #undef SETERRQ3 4782 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4783 4784 #undef __FUNCT__ 4785 #define __FUNCT__ "matsetvaluesseqaij_" 4786 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) 4787 { 4788 Mat A = *AA; 4789 PetscInt m = *mm, n = *nn; 4790 InsertMode is = *isis; 4791 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4792 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4793 PetscInt *imax,*ai,*ailen; 4794 PetscErrorCode ierr; 4795 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4796 MatScalar *ap,value,*aa; 4797 PetscBool ignorezeroentries = a->ignorezeroentries; 4798 PetscBool roworiented = a->roworiented; 4799 4800 PetscFunctionBegin; 4801 MatCheckPreallocated(A,1); 4802 imax = a->imax; 4803 ai = a->i; 4804 ailen = a->ilen; 4805 aj = a->j; 4806 aa = a->a; 4807 4808 for (k=0; k<m; k++) { /* loop over added rows */ 4809 row = im[k]; 4810 if (row < 0) continue; 4811 #if defined(PETSC_USE_DEBUG) 4812 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4813 #endif 4814 rp = aj + ai[row]; ap = aa + ai[row]; 4815 rmax = imax[row]; nrow = ailen[row]; 4816 low = 0; 4817 high = nrow; 4818 for (l=0; l<n; l++) { /* loop over added columns */ 4819 if (in[l] < 0) continue; 4820 #if defined(PETSC_USE_DEBUG) 4821 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4822 #endif 4823 col = in[l]; 4824 if (roworiented) value = v[l + k*n]; 4825 else value = v[k + l*m]; 4826 4827 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4828 4829 if (col <= lastcol) low = 0; 4830 else high = nrow; 4831 lastcol = col; 4832 while (high-low > 5) { 4833 t = (low+high)/2; 4834 if (rp[t] > col) high = t; 4835 else low = t; 4836 } 4837 for (i=low; i<high; i++) { 4838 if (rp[i] > col) break; 4839 if (rp[i] == col) { 4840 if (is == ADD_VALUES) ap[i] += value; 4841 else ap[i] = value; 4842 goto noinsert; 4843 } 4844 } 4845 if (value == 0.0 && ignorezeroentries) goto noinsert; 4846 if (nonew == 1) goto noinsert; 4847 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4848 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4849 N = nrow++ - 1; a->nz++; high++; 4850 /* shift up all the later entries in this row */ 4851 for (ii=N; ii>=i; ii--) { 4852 rp[ii+1] = rp[ii]; 4853 ap[ii+1] = ap[ii]; 4854 } 4855 rp[i] = col; 4856 ap[i] = value; 4857 noinsert:; 4858 low = i + 1; 4859 } 4860 ailen[row] = nrow; 4861 } 4862 A->same_nonzero = PETSC_FALSE; 4863 PetscFunctionReturnVoid(); 4864 } 4865 4866 4867