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 vscale_array[col] = (PetscScalar)dx; 2774 } 2775 2776 idx = den2sp; 2777 for (k=0; k<ncolors; k++) { /* loop over colors */ 2778 coloring->currentcolor = k; 2779 2780 /* 2781 Loop over each column associated with color 2782 adding the perturbation to the vector w3 = x1 + dx. 2783 */ 2784 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2785 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 2786 ncolumns_k = ncolumns[k]; 2787 for (l=0; l<ncolumns_k; l++) { /* loop over columns */ 2788 col = columns[k][l]; 2789 //w3_array[col] += 1/vscale_array[col]; 2790 w3_array[col] += vscale_array[col]; 2791 } 2792 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2793 2794 /* 2795 Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 2796 w2 = F(x1 + dx) - F(x1) 2797 */ 2798 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2799 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2800 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2801 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2802 2803 /* 2804 Loop over rows of vector, putting w2/dx into Jacobian matrix 2805 */ 2806 #if defined(JACOBIANCOLOROPT) 2807 ierr = PetscTime(&t0);CHKERRQ(ierr); 2808 #endif 2809 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2810 nrows_k = nrows[k]; 2811 for (l=0; l<nrows_k; l++) { /* loop over rows */ 2812 row = rows[k][l]; /* row index */ 2813 //y[row] *= vscale_array[columnsforrow[k][l]]; 2814 y[row] /= vscale_array[columnsforrow[k][l]]; 2815 ca[idx[l]] = y[row]; 2816 } 2817 idx += nrows_k; 2818 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2819 #if defined(JACOBIANCOLOROPT) 2820 ierr = PetscTime(&t1);CHKERRQ(ierr); 2821 time_setvalues += t1-t0; 2822 #endif 2823 } /* endof for each color */ 2824 #if defined(JACOBIANCOLOROPT) 2825 printf(" MatFDColoringApply_SeqAIJ: time_setvalues %g\n",time_setvalues); 2826 #endif 2827 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2828 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2829 2830 coloring->currentcolor = -1; 2831 PetscFunctionReturn(0); 2832 } 2833 /* --------------------------------------------------------*/ 2834 2835 #undef __FUNCT__ 2836 #define __FUNCT__ "MatFDColoringApply_SeqAIJ_old" 2837 PetscErrorCode MatFDColoringApply_SeqAIJ_old(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2838 { 2839 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2840 PetscErrorCode ierr; 2841 PetscInt k,N,start,end,l,row,col,srow,**vscaleforrow; 2842 PetscScalar dx,*y,*xx,*w3_array; 2843 PetscScalar *vscale_array; 2844 PetscReal epsilon = coloring->error_rel,umin = coloring->umin; 2845 Vec w1,w2,w3; 2846 void *fctx = coloring->fctx; 2847 PetscBool flg = PETSC_FALSE; 2848 2849 PetscFunctionBegin; 2850 printf("MatFDColoringApply_SeqAIJ ...\n"); 2851 if (!coloring->w1) { 2852 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 2853 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w1);CHKERRQ(ierr); 2854 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 2855 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w2);CHKERRQ(ierr); 2856 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2857 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2858 } 2859 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 2860 2861 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2862 ierr = PetscOptionsGetBool(((PetscObject)coloring)->prefix,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2863 if (flg) { 2864 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2865 } else { 2866 PetscBool assembled; 2867 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2868 if (assembled) { 2869 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2870 } 2871 } 2872 2873 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 2874 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2875 2876 if (!coloring->fset) { 2877 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2878 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2879 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2880 } else { 2881 coloring->fset = PETSC_FALSE; 2882 } 2883 2884 /* 2885 Compute all the scale factors and share with other processors 2886 */ 2887 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start; 2888 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start; 2889 for (k=0; k<coloring->ncolors; k++) { 2890 /* 2891 Loop over each column associated with color adding the 2892 perturbation to the vector w3. 2893 */ 2894 for (l=0; l<coloring->ncolumns[k]; l++) { 2895 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2896 dx = xx[col]; 2897 if (dx == 0.0) dx = 1.0; 2898 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2899 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2900 dx *= epsilon; 2901 vscale_array[col] = 1.0/dx; 2902 } 2903 } 2904 vscale_array = vscale_array + start; 2905 2906 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2907 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2908 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2909 2910 /* ierr = VecView(coloring->vscale,PETSC_VIEWER_STDOUT_WORLD); 2911 ierr = VecView(x1,PETSC_VIEWER_STDOUT_WORLD);*/ 2912 2913 if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow; 2914 else vscaleforrow = coloring->columnsforrow; 2915 2916 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2917 /* 2918 Loop over each color 2919 */ 2920 for (k=0; k<coloring->ncolors; k++) { 2921 coloring->currentcolor = k; 2922 2923 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2924 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start; 2925 /* 2926 Loop over each column associated with color adding the 2927 perturbation to the vector w3. 2928 */ 2929 for (l=0; l<coloring->ncolumns[k]; l++) { 2930 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2931 dx = xx[col]; 2932 if (dx == 0.0) dx = 1.0; 2933 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2934 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2935 dx *= epsilon; 2936 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 2937 w3_array[col] += dx; 2938 } 2939 w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2940 2941 /* 2942 Evaluate function at x1 + dx (here dx is a vector of perturbations) 2943 */ 2944 2945 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2946 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2947 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2948 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2949 2950 /* 2951 Loop over rows of vector, putting results into Jacobian matrix 2952 */ 2953 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2954 for (l=0; l<coloring->nrows[k]; l++) { 2955 row = coloring->rows[k][l]; 2956 col = coloring->columnsforrow[k][l]; 2957 y[row] *= vscale_array[vscaleforrow[k][l]]; 2958 srow = row + start; 2959 ierr = MatSetValues_SeqAIJ(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 2960 } 2961 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2962 } 2963 coloring->currentcolor = k; 2964 2965 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2966 xx = xx + start; 2967 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2968 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2969 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2970 PetscFunctionReturn(0); 2971 } 2972 2973 /* 2974 Computes the number of nonzeros per row needed for preallocation when X and Y 2975 have different nonzero structure. 2976 */ 2977 #undef __FUNCT__ 2978 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 2979 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 2980 { 2981 PetscInt i,m=Y->rmap->N; 2982 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2983 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2984 const PetscInt *xi = x->i,*yi = y->i; 2985 2986 PetscFunctionBegin; 2987 /* Set the number of nonzeros in the new matrix */ 2988 for (i=0; i<m; i++) { 2989 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2990 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2991 nnz[i] = 0; 2992 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2993 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 2994 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 2995 nnz[i]++; 2996 } 2997 for (; k<nzy; k++) nnz[i]++; 2998 } 2999 PetscFunctionReturn(0); 3000 } 3001 3002 #undef __FUNCT__ 3003 #define __FUNCT__ "MatAXPY_SeqAIJ" 3004 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 3005 { 3006 PetscErrorCode ierr; 3007 PetscInt i; 3008 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 3009 PetscBLASInt one=1,bnz; 3010 3011 PetscFunctionBegin; 3012 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 3013 if (str == SAME_NONZERO_PATTERN) { 3014 PetscScalar alpha = a; 3015 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 3016 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 3017 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 3018 if (y->xtoy && y->XtoY != X) { 3019 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 3020 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 3021 } 3022 if (!y->xtoy) { /* get xtoy */ 3023 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 3024 y->XtoY = X; 3025 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 3026 } 3027 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 3028 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); 3029 } else { 3030 Mat B; 3031 PetscInt *nnz; 3032 ierr = PetscMalloc(Y->rmap->N*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 3033 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 3034 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 3035 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 3036 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 3037 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 3038 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 3039 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 3040 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 3041 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 3042 ierr = PetscFree(nnz);CHKERRQ(ierr); 3043 } 3044 PetscFunctionReturn(0); 3045 } 3046 3047 #undef __FUNCT__ 3048 #define __FUNCT__ "MatConjugate_SeqAIJ" 3049 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 3050 { 3051 #if defined(PETSC_USE_COMPLEX) 3052 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3053 PetscInt i,nz; 3054 PetscScalar *a; 3055 3056 PetscFunctionBegin; 3057 nz = aij->nz; 3058 a = aij->a; 3059 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3060 #else 3061 PetscFunctionBegin; 3062 #endif 3063 PetscFunctionReturn(0); 3064 } 3065 3066 #undef __FUNCT__ 3067 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 3068 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3069 { 3070 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3071 PetscErrorCode ierr; 3072 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3073 PetscReal atmp; 3074 PetscScalar *x; 3075 MatScalar *aa; 3076 3077 PetscFunctionBegin; 3078 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3079 aa = a->a; 3080 ai = a->i; 3081 aj = a->j; 3082 3083 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3084 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3085 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3086 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3087 for (i=0; i<m; i++) { 3088 ncols = ai[1] - ai[0]; ai++; 3089 x[i] = 0.0; 3090 for (j=0; j<ncols; j++) { 3091 atmp = PetscAbsScalar(*aa); 3092 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3093 aa++; aj++; 3094 } 3095 } 3096 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3097 PetscFunctionReturn(0); 3098 } 3099 3100 #undef __FUNCT__ 3101 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 3102 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3103 { 3104 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3105 PetscErrorCode ierr; 3106 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3107 PetscScalar *x; 3108 MatScalar *aa; 3109 3110 PetscFunctionBegin; 3111 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3112 aa = a->a; 3113 ai = a->i; 3114 aj = a->j; 3115 3116 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3117 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3118 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3119 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3120 for (i=0; i<m; i++) { 3121 ncols = ai[1] - ai[0]; ai++; 3122 if (ncols == A->cmap->n) { /* row is dense */ 3123 x[i] = *aa; if (idx) idx[i] = 0; 3124 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3125 x[i] = 0.0; 3126 if (idx) { 3127 idx[i] = 0; /* in case ncols is zero */ 3128 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3129 if (aj[j] > j) { 3130 idx[i] = j; 3131 break; 3132 } 3133 } 3134 } 3135 } 3136 for (j=0; j<ncols; j++) { 3137 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3138 aa++; aj++; 3139 } 3140 } 3141 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3142 PetscFunctionReturn(0); 3143 } 3144 3145 #undef __FUNCT__ 3146 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 3147 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3148 { 3149 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3150 PetscErrorCode ierr; 3151 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3152 PetscReal atmp; 3153 PetscScalar *x; 3154 MatScalar *aa; 3155 3156 PetscFunctionBegin; 3157 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3158 aa = a->a; 3159 ai = a->i; 3160 aj = a->j; 3161 3162 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3163 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3164 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3165 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); 3166 for (i=0; i<m; i++) { 3167 ncols = ai[1] - ai[0]; ai++; 3168 if (ncols) { 3169 /* Get first nonzero */ 3170 for (j = 0; j < ncols; j++) { 3171 atmp = PetscAbsScalar(aa[j]); 3172 if (atmp > 1.0e-12) { 3173 x[i] = atmp; 3174 if (idx) idx[i] = aj[j]; 3175 break; 3176 } 3177 } 3178 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3179 } else { 3180 x[i] = 0.0; if (idx) idx[i] = 0; 3181 } 3182 for (j = 0; j < ncols; j++) { 3183 atmp = PetscAbsScalar(*aa); 3184 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3185 aa++; aj++; 3186 } 3187 } 3188 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3189 PetscFunctionReturn(0); 3190 } 3191 3192 #undef __FUNCT__ 3193 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3194 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3195 { 3196 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3197 PetscErrorCode ierr; 3198 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3199 PetscScalar *x; 3200 MatScalar *aa; 3201 3202 PetscFunctionBegin; 3203 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3204 aa = a->a; 3205 ai = a->i; 3206 aj = a->j; 3207 3208 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3209 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3210 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3211 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3212 for (i=0; i<m; i++) { 3213 ncols = ai[1] - ai[0]; ai++; 3214 if (ncols == A->cmap->n) { /* row is dense */ 3215 x[i] = *aa; if (idx) idx[i] = 0; 3216 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3217 x[i] = 0.0; 3218 if (idx) { /* find first implicit 0.0 in the row */ 3219 idx[i] = 0; /* in case ncols is zero */ 3220 for (j=0; j<ncols; j++) { 3221 if (aj[j] > j) { 3222 idx[i] = j; 3223 break; 3224 } 3225 } 3226 } 3227 } 3228 for (j=0; j<ncols; j++) { 3229 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3230 aa++; aj++; 3231 } 3232 } 3233 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3234 PetscFunctionReturn(0); 3235 } 3236 3237 #include <petscblaslapack.h> 3238 #include <petsc-private/kernels/blockinvert.h> 3239 3240 #undef __FUNCT__ 3241 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3242 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3243 { 3244 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3245 PetscErrorCode ierr; 3246 PetscInt i,bs = A->rmap->bs,mbs = A->rmap->n/A->rmap->bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3247 MatScalar *diag,work[25],*v_work; 3248 PetscReal shift = 0.0; 3249 3250 PetscFunctionBegin; 3251 if (a->ibdiagvalid) { 3252 if (values) *values = a->ibdiag; 3253 PetscFunctionReturn(0); 3254 } 3255 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3256 if (!a->ibdiag) { 3257 ierr = PetscMalloc(bs2*mbs*sizeof(PetscScalar),&a->ibdiag);CHKERRQ(ierr); 3258 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3259 } 3260 diag = a->ibdiag; 3261 if (values) *values = a->ibdiag; 3262 /* factor and invert each block */ 3263 switch (bs) { 3264 case 1: 3265 for (i=0; i<mbs; i++) { 3266 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3267 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3268 } 3269 break; 3270 case 2: 3271 for (i=0; i<mbs; i++) { 3272 ij[0] = 2*i; ij[1] = 2*i + 1; 3273 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3274 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3275 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3276 diag += 4; 3277 } 3278 break; 3279 case 3: 3280 for (i=0; i<mbs; i++) { 3281 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3282 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3283 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3284 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3285 diag += 9; 3286 } 3287 break; 3288 case 4: 3289 for (i=0; i<mbs; i++) { 3290 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3291 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3292 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3293 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3294 diag += 16; 3295 } 3296 break; 3297 case 5: 3298 for (i=0; i<mbs; i++) { 3299 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3300 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3301 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3302 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3303 diag += 25; 3304 } 3305 break; 3306 case 6: 3307 for (i=0; i<mbs; i++) { 3308 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; 3309 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3310 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3311 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3312 diag += 36; 3313 } 3314 break; 3315 case 7: 3316 for (i=0; i<mbs; i++) { 3317 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; 3318 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3319 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3320 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3321 diag += 49; 3322 } 3323 break; 3324 default: 3325 ierr = PetscMalloc3(bs,MatScalar,&v_work,bs,PetscInt,&v_pivots,bs,PetscInt,&IJ);CHKERRQ(ierr); 3326 for (i=0; i<mbs; i++) { 3327 for (j=0; j<bs; j++) { 3328 IJ[j] = bs*i + j; 3329 } 3330 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3331 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3332 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3333 diag += bs2; 3334 } 3335 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3336 } 3337 a->ibdiagvalid = PETSC_TRUE; 3338 PetscFunctionReturn(0); 3339 } 3340 3341 #undef __FUNCT__ 3342 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3343 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3344 { 3345 PetscErrorCode ierr; 3346 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3347 PetscScalar a; 3348 PetscInt m,n,i,j,col; 3349 3350 PetscFunctionBegin; 3351 if (!x->assembled) { 3352 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3353 for (i=0; i<m; i++) { 3354 for (j=0; j<aij->imax[i]; j++) { 3355 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3356 col = (PetscInt)(n*PetscRealPart(a)); 3357 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3358 } 3359 } 3360 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3361 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3362 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3363 PetscFunctionReturn(0); 3364 } 3365 3366 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3367 /* -------------------------------------------------------------------*/ 3368 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3369 MatGetRow_SeqAIJ, 3370 MatRestoreRow_SeqAIJ, 3371 MatMult_SeqAIJ, 3372 /* 4*/ MatMultAdd_SeqAIJ, 3373 MatMultTranspose_SeqAIJ, 3374 MatMultTransposeAdd_SeqAIJ, 3375 0, 3376 0, 3377 0, 3378 /* 10*/ 0, 3379 MatLUFactor_SeqAIJ, 3380 0, 3381 MatSOR_SeqAIJ, 3382 MatTranspose_SeqAIJ, 3383 /*1 5*/ MatGetInfo_SeqAIJ, 3384 MatEqual_SeqAIJ, 3385 MatGetDiagonal_SeqAIJ, 3386 MatDiagonalScale_SeqAIJ, 3387 MatNorm_SeqAIJ, 3388 /* 20*/ 0, 3389 MatAssemblyEnd_SeqAIJ, 3390 MatSetOption_SeqAIJ, 3391 MatZeroEntries_SeqAIJ, 3392 /* 24*/ MatZeroRows_SeqAIJ, 3393 0, 3394 0, 3395 0, 3396 0, 3397 /* 29*/ MatSetUp_SeqAIJ, 3398 0, 3399 0, 3400 0, 3401 0, 3402 /* 34*/ MatDuplicate_SeqAIJ, 3403 0, 3404 0, 3405 MatILUFactor_SeqAIJ, 3406 0, 3407 /* 39*/ MatAXPY_SeqAIJ, 3408 MatGetSubMatrices_SeqAIJ, 3409 MatIncreaseOverlap_SeqAIJ, 3410 MatGetValues_SeqAIJ, 3411 MatCopy_SeqAIJ, 3412 /* 44*/ MatGetRowMax_SeqAIJ, 3413 MatScale_SeqAIJ, 3414 0, 3415 MatDiagonalSet_SeqAIJ, 3416 MatZeroRowsColumns_SeqAIJ, 3417 /* 49*/ MatSetRandom_SeqAIJ, 3418 MatGetRowIJ_SeqAIJ, 3419 MatRestoreRowIJ_SeqAIJ, 3420 MatGetColumnIJ_SeqAIJ, 3421 MatRestoreColumnIJ_SeqAIJ, 3422 /* 54*/ MatFDColoringCreate_SeqAIJ, 3423 0, 3424 0, 3425 MatPermute_SeqAIJ, 3426 0, 3427 /* 59*/ 0, 3428 MatDestroy_SeqAIJ, 3429 MatView_SeqAIJ, 3430 0, 3431 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3432 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3433 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3434 0, 3435 0, 3436 0, 3437 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3438 MatGetRowMinAbs_SeqAIJ, 3439 0, 3440 MatSetColoring_SeqAIJ, 3441 0, 3442 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3443 MatFDColoringApply_AIJ, 3444 0, 3445 0, 3446 0, 3447 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3448 0, 3449 0, 3450 0, 3451 MatLoad_SeqAIJ, 3452 /* 84*/ MatIsSymmetric_SeqAIJ, 3453 MatIsHermitian_SeqAIJ, 3454 0, 3455 0, 3456 0, 3457 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3458 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3459 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3460 MatPtAP_SeqAIJ_SeqAIJ, 3461 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3462 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3463 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3464 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3465 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3466 0, 3467 /* 99*/ 0, 3468 0, 3469 0, 3470 MatConjugate_SeqAIJ, 3471 0, 3472 /*104*/ MatSetValuesRow_SeqAIJ, 3473 MatRealPart_SeqAIJ, 3474 MatImaginaryPart_SeqAIJ, 3475 0, 3476 0, 3477 /*109*/ MatMatSolve_SeqAIJ, 3478 0, 3479 MatGetRowMin_SeqAIJ, 3480 0, 3481 MatMissingDiagonal_SeqAIJ, 3482 /*114*/ 0, 3483 0, 3484 0, 3485 0, 3486 0, 3487 /*119*/ 0, 3488 0, 3489 0, 3490 0, 3491 MatGetMultiProcBlock_SeqAIJ, 3492 /*124*/ MatFindNonzeroRows_SeqAIJ, 3493 MatGetColumnNorms_SeqAIJ, 3494 MatInvertBlockDiagonal_SeqAIJ, 3495 0, 3496 0, 3497 /*129*/ 0, 3498 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3499 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3500 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3501 MatTransposeColoringCreate_SeqAIJ, 3502 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3503 MatTransColoringApplyDenToSp_SeqAIJ, 3504 MatRARt_SeqAIJ_SeqAIJ, 3505 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3506 MatRARtNumeric_SeqAIJ_SeqAIJ, 3507 /*139*/0, 3508 0 3509 }; 3510 3511 #undef __FUNCT__ 3512 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3513 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3514 { 3515 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3516 PetscInt i,nz,n; 3517 3518 PetscFunctionBegin; 3519 nz = aij->maxnz; 3520 n = mat->rmap->n; 3521 for (i=0; i<nz; i++) { 3522 aij->j[i] = indices[i]; 3523 } 3524 aij->nz = nz; 3525 for (i=0; i<n; i++) { 3526 aij->ilen[i] = aij->imax[i]; 3527 } 3528 PetscFunctionReturn(0); 3529 } 3530 3531 #undef __FUNCT__ 3532 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3533 /*@ 3534 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3535 in the matrix. 3536 3537 Input Parameters: 3538 + mat - the SeqAIJ matrix 3539 - indices - the column indices 3540 3541 Level: advanced 3542 3543 Notes: 3544 This can be called if you have precomputed the nonzero structure of the 3545 matrix and want to provide it to the matrix object to improve the performance 3546 of the MatSetValues() operation. 3547 3548 You MUST have set the correct numbers of nonzeros per row in the call to 3549 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3550 3551 MUST be called before any calls to MatSetValues(); 3552 3553 The indices should start with zero, not one. 3554 3555 @*/ 3556 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3557 { 3558 PetscErrorCode ierr; 3559 3560 PetscFunctionBegin; 3561 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3562 PetscValidPointer(indices,2); 3563 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3564 PetscFunctionReturn(0); 3565 } 3566 3567 /* ----------------------------------------------------------------------------------------*/ 3568 3569 #undef __FUNCT__ 3570 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3571 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3572 { 3573 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3574 PetscErrorCode ierr; 3575 size_t nz = aij->i[mat->rmap->n]; 3576 3577 PetscFunctionBegin; 3578 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3579 3580 /* allocate space for values if not already there */ 3581 if (!aij->saved_values) { 3582 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 3583 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3584 } 3585 3586 /* copy values over */ 3587 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3588 PetscFunctionReturn(0); 3589 } 3590 3591 #undef __FUNCT__ 3592 #define __FUNCT__ "MatStoreValues" 3593 /*@ 3594 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3595 example, reuse of the linear part of a Jacobian, while recomputing the 3596 nonlinear portion. 3597 3598 Collect on Mat 3599 3600 Input Parameters: 3601 . mat - the matrix (currently only AIJ matrices support this option) 3602 3603 Level: advanced 3604 3605 Common Usage, with SNESSolve(): 3606 $ Create Jacobian matrix 3607 $ Set linear terms into matrix 3608 $ Apply boundary conditions to matrix, at this time matrix must have 3609 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3610 $ boundary conditions again will not change the nonzero structure 3611 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3612 $ ierr = MatStoreValues(mat); 3613 $ Call SNESSetJacobian() with matrix 3614 $ In your Jacobian routine 3615 $ ierr = MatRetrieveValues(mat); 3616 $ Set nonlinear terms in matrix 3617 3618 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3619 $ // build linear portion of Jacobian 3620 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3621 $ ierr = MatStoreValues(mat); 3622 $ loop over nonlinear iterations 3623 $ ierr = MatRetrieveValues(mat); 3624 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3625 $ // call MatAssemblyBegin/End() on matrix 3626 $ Solve linear system with Jacobian 3627 $ endloop 3628 3629 Notes: 3630 Matrix must already be assemblied before calling this routine 3631 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3632 calling this routine. 3633 3634 When this is called multiple times it overwrites the previous set of stored values 3635 and does not allocated additional space. 3636 3637 .seealso: MatRetrieveValues() 3638 3639 @*/ 3640 PetscErrorCode MatStoreValues(Mat mat) 3641 { 3642 PetscErrorCode ierr; 3643 3644 PetscFunctionBegin; 3645 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3646 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3647 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3648 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3649 PetscFunctionReturn(0); 3650 } 3651 3652 #undef __FUNCT__ 3653 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3654 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3655 { 3656 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3657 PetscErrorCode ierr; 3658 PetscInt nz = aij->i[mat->rmap->n]; 3659 3660 PetscFunctionBegin; 3661 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3662 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3663 /* copy values over */ 3664 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3665 PetscFunctionReturn(0); 3666 } 3667 3668 #undef __FUNCT__ 3669 #define __FUNCT__ "MatRetrieveValues" 3670 /*@ 3671 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3672 example, reuse of the linear part of a Jacobian, while recomputing the 3673 nonlinear portion. 3674 3675 Collect on Mat 3676 3677 Input Parameters: 3678 . mat - the matrix (currently on AIJ matrices support this option) 3679 3680 Level: advanced 3681 3682 .seealso: MatStoreValues() 3683 3684 @*/ 3685 PetscErrorCode MatRetrieveValues(Mat mat) 3686 { 3687 PetscErrorCode ierr; 3688 3689 PetscFunctionBegin; 3690 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3691 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3692 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3693 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3694 PetscFunctionReturn(0); 3695 } 3696 3697 3698 /* --------------------------------------------------------------------------------*/ 3699 #undef __FUNCT__ 3700 #define __FUNCT__ "MatCreateSeqAIJ" 3701 /*@C 3702 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3703 (the default parallel PETSc format). For good matrix assembly performance 3704 the user should preallocate the matrix storage by setting the parameter nz 3705 (or the array nnz). By setting these parameters accurately, performance 3706 during matrix assembly can be increased by more than a factor of 50. 3707 3708 Collective on MPI_Comm 3709 3710 Input Parameters: 3711 + comm - MPI communicator, set to PETSC_COMM_SELF 3712 . m - number of rows 3713 . n - number of columns 3714 . nz - number of nonzeros per row (same for all rows) 3715 - nnz - array containing the number of nonzeros in the various rows 3716 (possibly different for each row) or NULL 3717 3718 Output Parameter: 3719 . A - the matrix 3720 3721 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3722 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3723 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3724 3725 Notes: 3726 If nnz is given then nz is ignored 3727 3728 The AIJ format (also called the Yale sparse matrix format or 3729 compressed row storage), is fully compatible with standard Fortran 77 3730 storage. That is, the stored row and column indices can begin at 3731 either one (as in Fortran) or zero. See the users' manual for details. 3732 3733 Specify the preallocated storage with either nz or nnz (not both). 3734 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3735 allocation. For large problems you MUST preallocate memory or you 3736 will get TERRIBLE performance, see the users' manual chapter on matrices. 3737 3738 By default, this format uses inodes (identical nodes) when possible, to 3739 improve numerical efficiency of matrix-vector products and solves. We 3740 search for consecutive rows with the same nonzero structure, thereby 3741 reusing matrix information to achieve increased efficiency. 3742 3743 Options Database Keys: 3744 + -mat_no_inode - Do not use inodes 3745 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3746 3747 Level: intermediate 3748 3749 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3750 3751 @*/ 3752 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3753 { 3754 PetscErrorCode ierr; 3755 3756 PetscFunctionBegin; 3757 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3758 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3759 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3760 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3761 PetscFunctionReturn(0); 3762 } 3763 3764 #undef __FUNCT__ 3765 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3766 /*@C 3767 MatSeqAIJSetPreallocation - For good matrix assembly performance 3768 the user should preallocate the matrix storage by setting the parameter nz 3769 (or the array nnz). By setting these parameters accurately, performance 3770 during matrix assembly can be increased by more than a factor of 50. 3771 3772 Collective on MPI_Comm 3773 3774 Input Parameters: 3775 + B - The matrix-free 3776 . nz - number of nonzeros per row (same for all rows) 3777 - nnz - array containing the number of nonzeros in the various rows 3778 (possibly different for each row) or NULL 3779 3780 Notes: 3781 If nnz is given then nz is ignored 3782 3783 The AIJ format (also called the Yale sparse matrix format or 3784 compressed row storage), is fully compatible with standard Fortran 77 3785 storage. That is, the stored row and column indices can begin at 3786 either one (as in Fortran) or zero. See the users' manual for details. 3787 3788 Specify the preallocated storage with either nz or nnz (not both). 3789 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3790 allocation. For large problems you MUST preallocate memory or you 3791 will get TERRIBLE performance, see the users' manual chapter on matrices. 3792 3793 You can call MatGetInfo() to get information on how effective the preallocation was; 3794 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3795 You can also run with the option -info and look for messages with the string 3796 malloc in them to see if additional memory allocation was needed. 3797 3798 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3799 entries or columns indices 3800 3801 By default, this format uses inodes (identical nodes) when possible, to 3802 improve numerical efficiency of matrix-vector products and solves. We 3803 search for consecutive rows with the same nonzero structure, thereby 3804 reusing matrix information to achieve increased efficiency. 3805 3806 Options Database Keys: 3807 + -mat_no_inode - Do not use inodes 3808 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3809 - -mat_aij_oneindex - Internally use indexing starting at 1 3810 rather than 0. Note that when calling MatSetValues(), 3811 the user still MUST index entries starting at 0! 3812 3813 Level: intermediate 3814 3815 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3816 3817 @*/ 3818 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3819 { 3820 PetscErrorCode ierr; 3821 3822 PetscFunctionBegin; 3823 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3824 PetscValidType(B,1); 3825 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3826 PetscFunctionReturn(0); 3827 } 3828 3829 #undef __FUNCT__ 3830 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3831 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3832 { 3833 Mat_SeqAIJ *b; 3834 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3835 PetscErrorCode ierr; 3836 PetscInt i; 3837 3838 PetscFunctionBegin; 3839 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3840 if (nz == MAT_SKIP_ALLOCATION) { 3841 skipallocation = PETSC_TRUE; 3842 nz = 0; 3843 } 3844 3845 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3846 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3847 3848 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3849 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3850 if (nnz) { 3851 for (i=0; i<B->rmap->n; i++) { 3852 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]); 3853 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); 3854 } 3855 } 3856 3857 B->preallocated = PETSC_TRUE; 3858 3859 b = (Mat_SeqAIJ*)B->data; 3860 3861 if (!skipallocation) { 3862 if (!b->imax) { 3863 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3864 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3865 } 3866 if (!nnz) { 3867 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3868 else if (nz < 0) nz = 1; 3869 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3870 nz = nz*B->rmap->n; 3871 } else { 3872 nz = 0; 3873 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3874 } 3875 /* b->ilen will count nonzeros in each row so far. */ 3876 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3877 3878 /* allocate the matrix space */ 3879 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3880 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3881 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3882 b->i[0] = 0; 3883 for (i=1; i<B->rmap->n+1; i++) { 3884 b->i[i] = b->i[i-1] + b->imax[i-1]; 3885 } 3886 b->singlemalloc = PETSC_TRUE; 3887 b->free_a = PETSC_TRUE; 3888 b->free_ij = PETSC_TRUE; 3889 #if defined(PETSC_THREADCOMM_ACTIVE) 3890 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3891 #endif 3892 } else { 3893 b->free_a = PETSC_FALSE; 3894 b->free_ij = PETSC_FALSE; 3895 } 3896 3897 b->nz = 0; 3898 b->maxnz = nz; 3899 B->info.nz_unneeded = (double)b->maxnz; 3900 if (realalloc) { 3901 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3902 } 3903 PetscFunctionReturn(0); 3904 } 3905 3906 #undef __FUNCT__ 3907 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3908 /*@ 3909 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3910 3911 Input Parameters: 3912 + B - the matrix 3913 . i - the indices into j for the start of each row (starts with zero) 3914 . j - the column indices for each row (starts with zero) these must be sorted for each row 3915 - v - optional values in the matrix 3916 3917 Level: developer 3918 3919 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3920 3921 .keywords: matrix, aij, compressed row, sparse, sequential 3922 3923 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3924 @*/ 3925 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3926 { 3927 PetscErrorCode ierr; 3928 3929 PetscFunctionBegin; 3930 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3931 PetscValidType(B,1); 3932 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3933 PetscFunctionReturn(0); 3934 } 3935 3936 #undef __FUNCT__ 3937 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3938 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3939 { 3940 PetscInt i; 3941 PetscInt m,n; 3942 PetscInt nz; 3943 PetscInt *nnz, nz_max = 0; 3944 PetscScalar *values; 3945 PetscErrorCode ierr; 3946 3947 PetscFunctionBegin; 3948 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3949 3950 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3951 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3952 3953 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3954 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 3955 for (i = 0; i < m; i++) { 3956 nz = Ii[i+1]- Ii[i]; 3957 nz_max = PetscMax(nz_max, nz); 3958 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3959 nnz[i] = nz; 3960 } 3961 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3962 ierr = PetscFree(nnz);CHKERRQ(ierr); 3963 3964 if (v) { 3965 values = (PetscScalar*) v; 3966 } else { 3967 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 3968 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3969 } 3970 3971 for (i = 0; i < m; i++) { 3972 nz = Ii[i+1] - Ii[i]; 3973 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3974 } 3975 3976 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3977 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3978 3979 if (!v) { 3980 ierr = PetscFree(values);CHKERRQ(ierr); 3981 } 3982 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3983 PetscFunctionReturn(0); 3984 } 3985 3986 #include <../src/mat/impls/dense/seq/dense.h> 3987 #include <petsc-private/kernels/petscaxpy.h> 3988 3989 #undef __FUNCT__ 3990 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3991 /* 3992 Computes (B'*A')' since computing B*A directly is untenable 3993 3994 n p p 3995 ( ) ( ) ( ) 3996 m ( A ) * n ( B ) = m ( C ) 3997 ( ) ( ) ( ) 3998 3999 */ 4000 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4001 { 4002 PetscErrorCode ierr; 4003 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4004 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4005 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4006 PetscInt i,n,m,q,p; 4007 const PetscInt *ii,*idx; 4008 const PetscScalar *b,*a,*a_q; 4009 PetscScalar *c,*c_q; 4010 4011 PetscFunctionBegin; 4012 m = A->rmap->n; 4013 n = A->cmap->n; 4014 p = B->cmap->n; 4015 a = sub_a->v; 4016 b = sub_b->a; 4017 c = sub_c->v; 4018 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 4019 4020 ii = sub_b->i; 4021 idx = sub_b->j; 4022 for (i=0; i<n; i++) { 4023 q = ii[i+1] - ii[i]; 4024 while (q-->0) { 4025 c_q = c + m*(*idx); 4026 a_q = a + m*i; 4027 PetscKernelAXPY(c_q,*b,a_q,m); 4028 idx++; 4029 b++; 4030 } 4031 } 4032 PetscFunctionReturn(0); 4033 } 4034 4035 #undef __FUNCT__ 4036 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 4037 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4038 { 4039 PetscErrorCode ierr; 4040 PetscInt m=A->rmap->n,n=B->cmap->n; 4041 Mat Cmat; 4042 4043 PetscFunctionBegin; 4044 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); 4045 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4046 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4047 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 4048 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4049 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4050 4051 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4052 4053 *C = Cmat; 4054 PetscFunctionReturn(0); 4055 } 4056 4057 /* ----------------------------------------------------------------*/ 4058 #undef __FUNCT__ 4059 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 4060 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4061 { 4062 PetscErrorCode ierr; 4063 4064 PetscFunctionBegin; 4065 if (scall == MAT_INITIAL_MATRIX) { 4066 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4067 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4068 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4069 } 4070 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4071 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4072 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4073 PetscFunctionReturn(0); 4074 } 4075 4076 4077 /*MC 4078 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4079 based on compressed sparse row format. 4080 4081 Options Database Keys: 4082 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4083 4084 Level: beginner 4085 4086 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4087 M*/ 4088 4089 /*MC 4090 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4091 4092 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4093 and MATMPIAIJ otherwise. As a result, for single process communicators, 4094 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 4095 for communicators controlling multiple processes. It is recommended that you call both of 4096 the above preallocation routines for simplicity. 4097 4098 Options Database Keys: 4099 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4100 4101 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 4102 enough exist. 4103 4104 Level: beginner 4105 4106 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4107 M*/ 4108 4109 /*MC 4110 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4111 4112 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4113 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4114 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4115 for communicators controlling multiple processes. It is recommended that you call both of 4116 the above preallocation routines for simplicity. 4117 4118 Options Database Keys: 4119 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4120 4121 Level: beginner 4122 4123 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4124 M*/ 4125 4126 #if defined(PETSC_HAVE_PASTIX) 4127 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 4128 #endif 4129 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4130 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 4131 #endif 4132 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4133 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 4134 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 4135 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 4136 #if defined(PETSC_HAVE_MUMPS) 4137 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 4138 #endif 4139 #if defined(PETSC_HAVE_SUPERLU) 4140 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 4141 #endif 4142 #if defined(PETSC_HAVE_SUPERLU_DIST) 4143 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 4144 #endif 4145 #if defined(PETSC_HAVE_UMFPACK) 4146 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 4147 #endif 4148 #if defined(PETSC_HAVE_CHOLMOD) 4149 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 4150 #endif 4151 #if defined(PETSC_HAVE_LUSOL) 4152 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 4153 #endif 4154 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4155 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 4156 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 4157 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 4158 #endif 4159 #if defined(PETSC_HAVE_CLIQUE) 4160 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 4161 #endif 4162 4163 4164 #undef __FUNCT__ 4165 #define __FUNCT__ "MatSeqAIJGetArray" 4166 /*@C 4167 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 4168 4169 Not Collective 4170 4171 Input Parameter: 4172 . mat - a MATSEQDENSE matrix 4173 4174 Output Parameter: 4175 . array - pointer to the data 4176 4177 Level: intermediate 4178 4179 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4180 @*/ 4181 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4182 { 4183 PetscErrorCode ierr; 4184 4185 PetscFunctionBegin; 4186 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4187 PetscFunctionReturn(0); 4188 } 4189 4190 #undef __FUNCT__ 4191 #define __FUNCT__ "MatSeqAIJRestoreArray" 4192 /*@C 4193 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4194 4195 Not Collective 4196 4197 Input Parameters: 4198 . mat - a MATSEQDENSE matrix 4199 . array - pointer to the data 4200 4201 Level: intermediate 4202 4203 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4204 @*/ 4205 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4206 { 4207 PetscErrorCode ierr; 4208 4209 PetscFunctionBegin; 4210 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4211 PetscFunctionReturn(0); 4212 } 4213 4214 #undef __FUNCT__ 4215 #define __FUNCT__ "MatCreate_SeqAIJ" 4216 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4217 { 4218 Mat_SeqAIJ *b; 4219 PetscErrorCode ierr; 4220 PetscMPIInt size; 4221 4222 PetscFunctionBegin; 4223 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4224 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4225 4226 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 4227 4228 B->data = (void*)b; 4229 4230 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4231 4232 b->row = 0; 4233 b->col = 0; 4234 b->icol = 0; 4235 b->reallocs = 0; 4236 b->ignorezeroentries = PETSC_FALSE; 4237 b->roworiented = PETSC_TRUE; 4238 b->nonew = 0; 4239 b->diag = 0; 4240 b->solve_work = 0; 4241 B->spptr = 0; 4242 b->saved_values = 0; 4243 b->idiag = 0; 4244 b->mdiag = 0; 4245 b->ssor_work = 0; 4246 b->omega = 1.0; 4247 b->fshift = 0.0; 4248 b->idiagvalid = PETSC_FALSE; 4249 b->ibdiagvalid = PETSC_FALSE; 4250 b->keepnonzeropattern = PETSC_FALSE; 4251 b->xtoy = 0; 4252 b->XtoY = 0; 4253 B->same_nonzero = PETSC_FALSE; 4254 4255 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4256 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4257 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4258 4259 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4260 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4261 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4262 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4263 #endif 4264 #if defined(PETSC_HAVE_PASTIX) 4265 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4266 #endif 4267 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4268 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4269 #endif 4270 #if defined(PETSC_HAVE_SUPERLU) 4271 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4272 #endif 4273 #if defined(PETSC_HAVE_SUPERLU_DIST) 4274 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4275 #endif 4276 #if defined(PETSC_HAVE_MUMPS) 4277 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4278 #endif 4279 #if defined(PETSC_HAVE_UMFPACK) 4280 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4281 #endif 4282 #if defined(PETSC_HAVE_CHOLMOD) 4283 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4284 #endif 4285 #if defined(PETSC_HAVE_LUSOL) 4286 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4287 #endif 4288 #if defined(PETSC_HAVE_CLIQUE) 4289 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4290 #endif 4291 4292 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4293 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4294 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4295 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4296 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4297 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4298 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4299 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4300 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4301 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4302 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4303 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4304 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4305 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4306 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4307 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4308 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4309 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4310 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4311 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4312 PetscFunctionReturn(0); 4313 } 4314 4315 #undef __FUNCT__ 4316 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4317 /* 4318 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4319 */ 4320 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4321 { 4322 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4323 PetscErrorCode ierr; 4324 PetscInt i,m = A->rmap->n; 4325 4326 PetscFunctionBegin; 4327 c = (Mat_SeqAIJ*)C->data; 4328 4329 C->factortype = A->factortype; 4330 c->row = 0; 4331 c->col = 0; 4332 c->icol = 0; 4333 c->reallocs = 0; 4334 4335 C->assembled = PETSC_TRUE; 4336 4337 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4338 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4339 4340 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 4341 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4342 for (i=0; i<m; i++) { 4343 c->imax[i] = a->imax[i]; 4344 c->ilen[i] = a->ilen[i]; 4345 } 4346 4347 /* allocate the matrix space */ 4348 if (mallocmatspace) { 4349 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 4350 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4351 4352 c->singlemalloc = PETSC_TRUE; 4353 4354 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4355 if (m > 0) { 4356 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4357 if (cpvalues == MAT_COPY_VALUES) { 4358 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4359 } else { 4360 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4361 } 4362 } 4363 } 4364 4365 c->ignorezeroentries = a->ignorezeroentries; 4366 c->roworiented = a->roworiented; 4367 c->nonew = a->nonew; 4368 if (a->diag) { 4369 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 4370 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4371 for (i=0; i<m; i++) { 4372 c->diag[i] = a->diag[i]; 4373 } 4374 } else c->diag = 0; 4375 4376 c->solve_work = 0; 4377 c->saved_values = 0; 4378 c->idiag = 0; 4379 c->ssor_work = 0; 4380 c->keepnonzeropattern = a->keepnonzeropattern; 4381 c->free_a = PETSC_TRUE; 4382 c->free_ij = PETSC_TRUE; 4383 c->xtoy = 0; 4384 c->XtoY = 0; 4385 4386 c->rmax = a->rmax; 4387 c->nz = a->nz; 4388 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4389 C->preallocated = PETSC_TRUE; 4390 4391 c->compressedrow.use = a->compressedrow.use; 4392 c->compressedrow.nrows = a->compressedrow.nrows; 4393 c->compressedrow.check = a->compressedrow.check; 4394 if (a->compressedrow.use) { 4395 i = a->compressedrow.nrows; 4396 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 4397 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4398 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4399 } else { 4400 c->compressedrow.use = PETSC_FALSE; 4401 c->compressedrow.i = NULL; 4402 c->compressedrow.rindex = NULL; 4403 } 4404 C->same_nonzero = A->same_nonzero; 4405 4406 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4407 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4408 PetscFunctionReturn(0); 4409 } 4410 4411 #undef __FUNCT__ 4412 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4413 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4414 { 4415 PetscErrorCode ierr; 4416 4417 PetscFunctionBegin; 4418 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4419 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4420 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4421 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4422 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4423 PetscFunctionReturn(0); 4424 } 4425 4426 #undef __FUNCT__ 4427 #define __FUNCT__ "MatLoad_SeqAIJ" 4428 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4429 { 4430 Mat_SeqAIJ *a; 4431 PetscErrorCode ierr; 4432 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4433 int fd; 4434 PetscMPIInt size; 4435 MPI_Comm comm; 4436 PetscInt bs = 1; 4437 4438 PetscFunctionBegin; 4439 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4440 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4441 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4442 4443 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4444 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4445 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4446 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4447 4448 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4449 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4450 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4451 M = header[1]; N = header[2]; nz = header[3]; 4452 4453 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4454 4455 /* read in row lengths */ 4456 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 4457 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4458 4459 /* check if sum of rowlengths is same as nz */ 4460 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4461 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); 4462 4463 /* set global size if not set already*/ 4464 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4465 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4466 } else { 4467 /* if sizes and type are already set, check if the vector global sizes are correct */ 4468 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4469 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4470 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4471 } 4472 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); 4473 } 4474 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4475 a = (Mat_SeqAIJ*)newMat->data; 4476 4477 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4478 4479 /* read in nonzero values */ 4480 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4481 4482 /* set matrix "i" values */ 4483 a->i[0] = 0; 4484 for (i=1; i<= M; i++) { 4485 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4486 a->ilen[i-1] = rowlengths[i-1]; 4487 } 4488 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4489 4490 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4491 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4492 PetscFunctionReturn(0); 4493 } 4494 4495 #undef __FUNCT__ 4496 #define __FUNCT__ "MatEqual_SeqAIJ" 4497 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4498 { 4499 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4500 PetscErrorCode ierr; 4501 #if defined(PETSC_USE_COMPLEX) 4502 PetscInt k; 4503 #endif 4504 4505 PetscFunctionBegin; 4506 /* If the matrix dimensions are not equal,or no of nonzeros */ 4507 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4508 *flg = PETSC_FALSE; 4509 PetscFunctionReturn(0); 4510 } 4511 4512 /* if the a->i are the same */ 4513 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4514 if (!*flg) PetscFunctionReturn(0); 4515 4516 /* if a->j are the same */ 4517 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4518 if (!*flg) PetscFunctionReturn(0); 4519 4520 /* if a->a are the same */ 4521 #if defined(PETSC_USE_COMPLEX) 4522 for (k=0; k<a->nz; k++) { 4523 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4524 *flg = PETSC_FALSE; 4525 PetscFunctionReturn(0); 4526 } 4527 } 4528 #else 4529 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4530 #endif 4531 PetscFunctionReturn(0); 4532 } 4533 4534 #undef __FUNCT__ 4535 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4536 /*@ 4537 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4538 provided by the user. 4539 4540 Collective on MPI_Comm 4541 4542 Input Parameters: 4543 + comm - must be an MPI communicator of size 1 4544 . m - number of rows 4545 . n - number of columns 4546 . i - row indices 4547 . j - column indices 4548 - a - matrix values 4549 4550 Output Parameter: 4551 . mat - the matrix 4552 4553 Level: intermediate 4554 4555 Notes: 4556 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4557 once the matrix is destroyed and not before 4558 4559 You cannot set new nonzero locations into this matrix, that will generate an error. 4560 4561 The i and j indices are 0 based 4562 4563 The format which is used for the sparse matrix input, is equivalent to a 4564 row-major ordering.. i.e for the following matrix, the input data expected is 4565 as shown: 4566 4567 1 0 0 4568 2 0 3 4569 4 5 6 4570 4571 i = {0,1,3,6} [size = nrow+1 = 3+1] 4572 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4573 v = {1,2,3,4,5,6} [size = nz = 6] 4574 4575 4576 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4577 4578 @*/ 4579 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4580 { 4581 PetscErrorCode ierr; 4582 PetscInt ii; 4583 Mat_SeqAIJ *aij; 4584 #if defined(PETSC_USE_DEBUG) 4585 PetscInt jj; 4586 #endif 4587 4588 PetscFunctionBegin; 4589 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4590 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4591 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4592 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4593 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4594 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4595 aij = (Mat_SeqAIJ*)(*mat)->data; 4596 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 4597 4598 aij->i = i; 4599 aij->j = j; 4600 aij->a = a; 4601 aij->singlemalloc = PETSC_FALSE; 4602 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4603 aij->free_a = PETSC_FALSE; 4604 aij->free_ij = PETSC_FALSE; 4605 4606 for (ii=0; ii<m; ii++) { 4607 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4608 #if defined(PETSC_USE_DEBUG) 4609 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]); 4610 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4611 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); 4612 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); 4613 } 4614 #endif 4615 } 4616 #if defined(PETSC_USE_DEBUG) 4617 for (ii=0; ii<aij->i[m]; ii++) { 4618 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 4619 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]); 4620 } 4621 #endif 4622 4623 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4624 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4625 PetscFunctionReturn(0); 4626 } 4627 #undef __FUNCT__ 4628 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4629 /*@C 4630 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4631 provided by the user. 4632 4633 Collective on MPI_Comm 4634 4635 Input Parameters: 4636 + comm - must be an MPI communicator of size 1 4637 . m - number of rows 4638 . n - number of columns 4639 . i - row indices 4640 . j - column indices 4641 . a - matrix values 4642 . nz - number of nonzeros 4643 - idx - 0 or 1 based 4644 4645 Output Parameter: 4646 . mat - the matrix 4647 4648 Level: intermediate 4649 4650 Notes: 4651 The i and j indices are 0 based 4652 4653 The format which is used for the sparse matrix input, is equivalent to a 4654 row-major ordering.. i.e for the following matrix, the input data expected is 4655 as shown: 4656 4657 1 0 0 4658 2 0 3 4659 4 5 6 4660 4661 i = {0,1,1,2,2,2} 4662 j = {0,0,2,0,1,2} 4663 v = {1,2,3,4,5,6} 4664 4665 4666 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4667 4668 @*/ 4669 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4670 { 4671 PetscErrorCode ierr; 4672 PetscInt ii, *nnz, one = 1,row,col; 4673 4674 4675 PetscFunctionBegin; 4676 ierr = PetscMalloc(m*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 4677 ierr = PetscMemzero(nnz,m*sizeof(PetscInt));CHKERRQ(ierr); 4678 for (ii = 0; ii < nz; ii++) { 4679 nnz[i[ii]] += 1; 4680 } 4681 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4682 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4683 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4684 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4685 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4686 for (ii = 0; ii < nz; ii++) { 4687 if (idx) { 4688 row = i[ii] - 1; 4689 col = j[ii] - 1; 4690 } else { 4691 row = i[ii]; 4692 col = j[ii]; 4693 } 4694 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4695 } 4696 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4697 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4698 ierr = PetscFree(nnz);CHKERRQ(ierr); 4699 PetscFunctionReturn(0); 4700 } 4701 4702 #undef __FUNCT__ 4703 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4704 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4705 { 4706 PetscErrorCode ierr; 4707 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4708 4709 PetscFunctionBegin; 4710 if (coloring->ctype == IS_COLORING_GLOBAL) { 4711 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4712 a->coloring = coloring; 4713 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4714 PetscInt i,*larray; 4715 ISColoring ocoloring; 4716 ISColoringValue *colors; 4717 4718 /* set coloring for diagonal portion */ 4719 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4720 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4721 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4722 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4723 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4724 ierr = PetscFree(larray);CHKERRQ(ierr); 4725 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4726 a->coloring = ocoloring; 4727 } 4728 PetscFunctionReturn(0); 4729 } 4730 4731 #undef __FUNCT__ 4732 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4733 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4734 { 4735 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4736 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4737 MatScalar *v = a->a; 4738 PetscScalar *values = (PetscScalar*)advalues; 4739 ISColoringValue *color; 4740 4741 PetscFunctionBegin; 4742 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4743 color = a->coloring->colors; 4744 /* loop over rows */ 4745 for (i=0; i<m; i++) { 4746 nz = ii[i+1] - ii[i]; 4747 /* loop over columns putting computed value into matrix */ 4748 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4749 values += nl; /* jump to next row of derivatives */ 4750 } 4751 PetscFunctionReturn(0); 4752 } 4753 4754 #undef __FUNCT__ 4755 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4756 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4757 { 4758 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4759 PetscErrorCode ierr; 4760 4761 PetscFunctionBegin; 4762 a->idiagvalid = PETSC_FALSE; 4763 a->ibdiagvalid = PETSC_FALSE; 4764 4765 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4766 PetscFunctionReturn(0); 4767 } 4768 4769 /* 4770 Special version for direct calls from Fortran 4771 */ 4772 #include <petsc-private/fortranimpl.h> 4773 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4774 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4775 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4776 #define matsetvaluesseqaij_ matsetvaluesseqaij 4777 #endif 4778 4779 /* Change these macros so can be used in void function */ 4780 #undef CHKERRQ 4781 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4782 #undef SETERRQ2 4783 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4784 #undef SETERRQ3 4785 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4786 4787 #undef __FUNCT__ 4788 #define __FUNCT__ "matsetvaluesseqaij_" 4789 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) 4790 { 4791 Mat A = *AA; 4792 PetscInt m = *mm, n = *nn; 4793 InsertMode is = *isis; 4794 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4795 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4796 PetscInt *imax,*ai,*ailen; 4797 PetscErrorCode ierr; 4798 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4799 MatScalar *ap,value,*aa; 4800 PetscBool ignorezeroentries = a->ignorezeroentries; 4801 PetscBool roworiented = a->roworiented; 4802 4803 PetscFunctionBegin; 4804 MatCheckPreallocated(A,1); 4805 imax = a->imax; 4806 ai = a->i; 4807 ailen = a->ilen; 4808 aj = a->j; 4809 aa = a->a; 4810 4811 for (k=0; k<m; k++) { /* loop over added rows */ 4812 row = im[k]; 4813 if (row < 0) continue; 4814 #if defined(PETSC_USE_DEBUG) 4815 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4816 #endif 4817 rp = aj + ai[row]; ap = aa + ai[row]; 4818 rmax = imax[row]; nrow = ailen[row]; 4819 low = 0; 4820 high = nrow; 4821 for (l=0; l<n; l++) { /* loop over added columns */ 4822 if (in[l] < 0) continue; 4823 #if defined(PETSC_USE_DEBUG) 4824 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4825 #endif 4826 col = in[l]; 4827 if (roworiented) value = v[l + k*n]; 4828 else value = v[k + l*m]; 4829 4830 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4831 4832 if (col <= lastcol) low = 0; 4833 else high = nrow; 4834 lastcol = col; 4835 while (high-low > 5) { 4836 t = (low+high)/2; 4837 if (rp[t] > col) high = t; 4838 else low = t; 4839 } 4840 for (i=low; i<high; i++) { 4841 if (rp[i] > col) break; 4842 if (rp[i] == col) { 4843 if (is == ADD_VALUES) ap[i] += value; 4844 else ap[i] = value; 4845 goto noinsert; 4846 } 4847 } 4848 if (value == 0.0 && ignorezeroentries) goto noinsert; 4849 if (nonew == 1) goto noinsert; 4850 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4851 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4852 N = nrow++ - 1; a->nz++; high++; 4853 /* shift up all the later entries in this row */ 4854 for (ii=N; ii>=i; ii--) { 4855 rp[ii+1] = rp[ii]; 4856 ap[ii+1] = ap[ii]; 4857 } 4858 rp[i] = col; 4859 ap[i] = value; 4860 noinsert:; 4861 low = i + 1; 4862 } 4863 ailen[row] = nrow; 4864 } 4865 A->same_nonzero = PETSC_FALSE; 4866 PetscFunctionReturnVoid(); 4867 } 4868 4869 4870