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 //const PetscInt *colorforrow=coloring->colorforrow,*colorforcolumn=coloring->colorforcolumn; 2717 PetscInt *den2sp=coloring->den2sp,*idx,idx_tmp; 2718 PetscInt **columns=coloring->columns,ncolumns_k,nrows_k; 2719 #if defined(JACOBIANCOLOROPT) 2720 PetscLogDouble t0,t1,t_init=0.0,t_setvals=0.0,t_func=0.0,t_dx=0.0,t_kl=0.0,t00,t11; 2721 #endif 2722 PetscInt nz; 2723 2724 PetscFunctionBegin; 2725 #if defined(JACOBIANCOLOROPT) 2726 ierr = PetscTime(&t0);CHKERRQ(ierr); 2727 #endif 2728 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2729 ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2730 if (flg) { 2731 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2732 } else { 2733 PetscBool assembled; 2734 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2735 if (assembled) { 2736 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2737 } 2738 } 2739 2740 if (!coloring->vscale) { 2741 ierr = VecDuplicate(x1,&coloring->vscale);CHKERRQ(ierr); 2742 } 2743 2744 if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/ 2745 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 2746 } 2747 #if defined(JACOBIANCOLOROPT) 2748 ierr = PetscTime(&t1);CHKERRQ(ierr); 2749 t_init += t1 - t0; 2750 #endif 2751 2752 /* Set w1 = F(x1) */ 2753 #if defined(JACOBIANCOLOROPT) 2754 ierr = PetscTime(&t0);CHKERRQ(ierr); 2755 #endif 2756 if (!coloring->fset) { 2757 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2758 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2759 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2760 } else { 2761 coloring->fset = PETSC_FALSE; 2762 } 2763 #if defined(JACOBIANCOLOROPT) 2764 ierr = PetscTime(&t1);CHKERRQ(ierr); 2765 t_setvals += t1 - t0; 2766 #endif 2767 2768 #if defined(JACOBIANCOLOROPT) 2769 ierr = PetscTime(&t0);CHKERRQ(ierr); 2770 #endif 2771 if (!coloring->w3) { 2772 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2773 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2774 } 2775 w3 = coloring->w3; 2776 2777 /* Compute scale factors: vscale = 1./dx = 1./(epsilon*xx) */ 2778 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 2779 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2780 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2781 for (col=0; col<N; col++) { 2782 if (coloring->htype[0] == 'w') { 2783 dx = 1.0 + unorm; 2784 } else { 2785 dx = xx[col]; 2786 } 2787 if (dx == (PetscScalar)0.0) dx = 1.0; 2788 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2789 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2790 dx *= epsilon; 2791 vscale_array[col] = (PetscScalar)dx; 2792 } 2793 #if defined(JACOBIANCOLOROPT) 2794 ierr = PetscTime(&t1);CHKERRQ(ierr); 2795 t_init += t1 - t0; 2796 #endif 2797 2798 idx = den2sp; 2799 nz = 0; 2800 for (k=0; k<ncolors; k++) { /* loop over colors */ 2801 #if defined(JACOBIANCOLOROPT) 2802 ierr = PetscTime(&t0);CHKERRQ(ierr); 2803 #endif 2804 coloring->currentcolor = k; 2805 2806 /* 2807 Loop over each column associated with color 2808 adding the perturbation to the vector w3 = x1 + dx. 2809 */ 2810 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2811 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 2812 ncolumns_k = ncolumns[k]; 2813 for (l=0; l<ncolumns_k; l++) { /* loop over columns */ 2814 col = columns[k][l]; 2815 w3_array[col] += vscale_array[col]; 2816 } 2817 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2818 #if defined(JACOBIANCOLOROPT) 2819 ierr = PetscTime(&t1);CHKERRQ(ierr); 2820 t_dx += t1 - t0; 2821 #endif 2822 2823 /* 2824 Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 2825 w2 = F(x1 + dx) - F(x1) 2826 */ 2827 #if defined(JACOBIANCOLOROPT) 2828 ierr = PetscTime(&t0);CHKERRQ(ierr); 2829 #endif 2830 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2831 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2832 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2833 #if defined(JACOBIANCOLOROPT) 2834 ierr = PetscTime(&t1);CHKERRQ(ierr); 2835 t_func += t1 - t0; 2836 #endif 2837 2838 #if defined(JACOBIANCOLOROPT) 2839 ierr = PetscTime(&t0);CHKERRQ(ierr); 2840 #endif 2841 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2842 2843 /* 2844 Loop over rows of vector, putting w2/dx into Jacobian matrix 2845 */ 2846 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2847 nrows_k = nrows[k]; 2848 for (l=0; l<nrows_k; l++) { /* loop over rows */ 2849 #if defined(JACOBIANCOLOROPT) 2850 ierr = PetscTime(&t00);CHKERRQ(ierr); 2851 #endif 2852 row = coloring->rowcolden2sp3[3*nz]; 2853 col = coloring->rowcolden2sp3[3*nz+1]; 2854 idx_tmp = coloring->rowcolden2sp3[3*nz+2]; 2855 #if defined(JACOBIANCOLOROPT) 2856 ierr = PetscTime(&t11);CHKERRQ(ierr); 2857 t_kl += t11 - t00; 2858 #endif 2859 //ca[idx[l]] = y[row]/vscale_array[col]; 2860 ca[idx_tmp] = y[row]/vscale_array[col]; 2861 nz++; 2862 } 2863 idx += nrows_k; 2864 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2865 2866 #if defined(JACOBIANCOLOROPT) 2867 ierr = PetscTime(&t1);CHKERRQ(ierr); 2868 t_setvals += t1 - t0; 2869 #endif 2870 } /* endof for each color */ 2871 #if defined(JACOBIANCOLOROPT) 2872 printf(" FDColorApply time: init %g + func %g + setvalues %g + dx %g= %g\n",t_init,t_func,t_setvals,t_dx,t_init+t_func+t_setvals+t_dx); 2873 printf(" FDColorApply time: kl %g\n",t_kl); 2874 #endif 2875 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2876 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2877 2878 coloring->currentcolor = -1; 2879 PetscFunctionReturn(0); 2880 } 2881 /* --------------------------------------------------------*/ 2882 2883 #undef __FUNCT__ 2884 #define __FUNCT__ "MatFDColoringApply_SeqAIJ_old" 2885 PetscErrorCode MatFDColoringApply_SeqAIJ_old(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2886 { 2887 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2888 PetscErrorCode ierr; 2889 PetscInt k,N,start,end,l,row,col,srow,**vscaleforrow; 2890 PetscScalar dx,*y,*xx,*w3_array; 2891 PetscScalar *vscale_array; 2892 PetscReal epsilon = coloring->error_rel,umin = coloring->umin; 2893 Vec w1,w2,w3; 2894 void *fctx = coloring->fctx; 2895 PetscBool flg = PETSC_FALSE; 2896 2897 PetscFunctionBegin; 2898 printf("MatFDColoringApply_SeqAIJ ...\n"); 2899 if (!coloring->w1) { 2900 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 2901 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w1);CHKERRQ(ierr); 2902 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 2903 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w2);CHKERRQ(ierr); 2904 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2905 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2906 } 2907 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 2908 2909 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2910 ierr = PetscOptionsGetBool(((PetscObject)coloring)->prefix,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2911 if (flg) { 2912 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2913 } else { 2914 PetscBool assembled; 2915 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2916 if (assembled) { 2917 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2918 } 2919 } 2920 2921 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 2922 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2923 2924 if (!coloring->fset) { 2925 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2926 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2927 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2928 } else { 2929 coloring->fset = PETSC_FALSE; 2930 } 2931 2932 /* 2933 Compute all the scale factors and share with other processors 2934 */ 2935 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start; 2936 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start; 2937 for (k=0; k<coloring->ncolors; k++) { 2938 /* 2939 Loop over each column associated with color adding the 2940 perturbation to the vector w3. 2941 */ 2942 for (l=0; l<coloring->ncolumns[k]; l++) { 2943 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2944 dx = xx[col]; 2945 if (dx == 0.0) dx = 1.0; 2946 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2947 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2948 dx *= epsilon; 2949 vscale_array[col] = 1.0/dx; 2950 } 2951 } 2952 vscale_array = vscale_array + start; 2953 2954 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2955 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2956 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2957 2958 /* ierr = VecView(coloring->vscale,PETSC_VIEWER_STDOUT_WORLD); 2959 ierr = VecView(x1,PETSC_VIEWER_STDOUT_WORLD);*/ 2960 2961 if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow; 2962 else vscaleforrow = coloring->columnsforrow; 2963 2964 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2965 /* 2966 Loop over each color 2967 */ 2968 for (k=0; k<coloring->ncolors; k++) { 2969 coloring->currentcolor = k; 2970 2971 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2972 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start; 2973 /* 2974 Loop over each column associated with color adding the 2975 perturbation to the vector w3. 2976 */ 2977 for (l=0; l<coloring->ncolumns[k]; l++) { 2978 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2979 dx = xx[col]; 2980 if (dx == 0.0) dx = 1.0; 2981 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2982 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2983 dx *= epsilon; 2984 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 2985 w3_array[col] += dx; 2986 } 2987 w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2988 2989 /* 2990 Evaluate function at x1 + dx (here dx is a vector of perturbations) 2991 */ 2992 2993 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2994 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2995 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2996 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2997 2998 /* 2999 Loop over rows of vector, putting results into Jacobian matrix 3000 */ 3001 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 3002 for (l=0; l<coloring->nrows[k]; l++) { 3003 row = coloring->rows[k][l]; 3004 col = coloring->columnsforrow[k][l]; 3005 y[row] *= vscale_array[vscaleforrow[k][l]]; 3006 srow = row + start; 3007 ierr = MatSetValues_SeqAIJ(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 3008 } 3009 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 3010 } 3011 coloring->currentcolor = k; 3012 3013 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 3014 xx = xx + start; 3015 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 3016 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3017 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3018 PetscFunctionReturn(0); 3019 } 3020 3021 /* 3022 Computes the number of nonzeros per row needed for preallocation when X and Y 3023 have different nonzero structure. 3024 */ 3025 #undef __FUNCT__ 3026 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 3027 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 3028 { 3029 PetscInt i,m=Y->rmap->N; 3030 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 3031 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 3032 const PetscInt *xi = x->i,*yi = y->i; 3033 3034 PetscFunctionBegin; 3035 /* Set the number of nonzeros in the new matrix */ 3036 for (i=0; i<m; i++) { 3037 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 3038 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 3039 nnz[i] = 0; 3040 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 3041 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 3042 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 3043 nnz[i]++; 3044 } 3045 for (; k<nzy; k++) nnz[i]++; 3046 } 3047 PetscFunctionReturn(0); 3048 } 3049 3050 #undef __FUNCT__ 3051 #define __FUNCT__ "MatAXPY_SeqAIJ" 3052 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 3053 { 3054 PetscErrorCode ierr; 3055 PetscInt i; 3056 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 3057 PetscBLASInt one=1,bnz; 3058 3059 PetscFunctionBegin; 3060 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 3061 if (str == SAME_NONZERO_PATTERN) { 3062 PetscScalar alpha = a; 3063 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 3064 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 3065 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 3066 if (y->xtoy && y->XtoY != X) { 3067 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 3068 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 3069 } 3070 if (!y->xtoy) { /* get xtoy */ 3071 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 3072 y->XtoY = X; 3073 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 3074 } 3075 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 3076 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); 3077 } else { 3078 Mat B; 3079 PetscInt *nnz; 3080 ierr = PetscMalloc(Y->rmap->N*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 3081 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 3082 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 3083 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 3084 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 3085 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 3086 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 3087 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 3088 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 3089 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 3090 ierr = PetscFree(nnz);CHKERRQ(ierr); 3091 } 3092 PetscFunctionReturn(0); 3093 } 3094 3095 #undef __FUNCT__ 3096 #define __FUNCT__ "MatConjugate_SeqAIJ" 3097 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 3098 { 3099 #if defined(PETSC_USE_COMPLEX) 3100 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3101 PetscInt i,nz; 3102 PetscScalar *a; 3103 3104 PetscFunctionBegin; 3105 nz = aij->nz; 3106 a = aij->a; 3107 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3108 #else 3109 PetscFunctionBegin; 3110 #endif 3111 PetscFunctionReturn(0); 3112 } 3113 3114 #undef __FUNCT__ 3115 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 3116 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3117 { 3118 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3119 PetscErrorCode ierr; 3120 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3121 PetscReal atmp; 3122 PetscScalar *x; 3123 MatScalar *aa; 3124 3125 PetscFunctionBegin; 3126 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3127 aa = a->a; 3128 ai = a->i; 3129 aj = a->j; 3130 3131 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3132 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3133 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3134 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3135 for (i=0; i<m; i++) { 3136 ncols = ai[1] - ai[0]; ai++; 3137 x[i] = 0.0; 3138 for (j=0; j<ncols; j++) { 3139 atmp = PetscAbsScalar(*aa); 3140 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3141 aa++; aj++; 3142 } 3143 } 3144 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3145 PetscFunctionReturn(0); 3146 } 3147 3148 #undef __FUNCT__ 3149 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 3150 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3151 { 3152 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3153 PetscErrorCode ierr; 3154 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3155 PetscScalar *x; 3156 MatScalar *aa; 3157 3158 PetscFunctionBegin; 3159 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3160 aa = a->a; 3161 ai = a->i; 3162 aj = a->j; 3163 3164 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3165 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3166 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3167 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3168 for (i=0; i<m; i++) { 3169 ncols = ai[1] - ai[0]; ai++; 3170 if (ncols == A->cmap->n) { /* row is dense */ 3171 x[i] = *aa; if (idx) idx[i] = 0; 3172 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3173 x[i] = 0.0; 3174 if (idx) { 3175 idx[i] = 0; /* in case ncols is zero */ 3176 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3177 if (aj[j] > j) { 3178 idx[i] = j; 3179 break; 3180 } 3181 } 3182 } 3183 } 3184 for (j=0; j<ncols; j++) { 3185 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3186 aa++; aj++; 3187 } 3188 } 3189 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3190 PetscFunctionReturn(0); 3191 } 3192 3193 #undef __FUNCT__ 3194 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 3195 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3196 { 3197 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3198 PetscErrorCode ierr; 3199 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3200 PetscReal atmp; 3201 PetscScalar *x; 3202 MatScalar *aa; 3203 3204 PetscFunctionBegin; 3205 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3206 aa = a->a; 3207 ai = a->i; 3208 aj = a->j; 3209 3210 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3211 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3212 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3213 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); 3214 for (i=0; i<m; i++) { 3215 ncols = ai[1] - ai[0]; ai++; 3216 if (ncols) { 3217 /* Get first nonzero */ 3218 for (j = 0; j < ncols; j++) { 3219 atmp = PetscAbsScalar(aa[j]); 3220 if (atmp > 1.0e-12) { 3221 x[i] = atmp; 3222 if (idx) idx[i] = aj[j]; 3223 break; 3224 } 3225 } 3226 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3227 } else { 3228 x[i] = 0.0; if (idx) idx[i] = 0; 3229 } 3230 for (j = 0; j < ncols; j++) { 3231 atmp = PetscAbsScalar(*aa); 3232 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3233 aa++; aj++; 3234 } 3235 } 3236 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3237 PetscFunctionReturn(0); 3238 } 3239 3240 #undef __FUNCT__ 3241 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3242 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3243 { 3244 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3245 PetscErrorCode ierr; 3246 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3247 PetscScalar *x; 3248 MatScalar *aa; 3249 3250 PetscFunctionBegin; 3251 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3252 aa = a->a; 3253 ai = a->i; 3254 aj = a->j; 3255 3256 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3257 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3258 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3259 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3260 for (i=0; i<m; i++) { 3261 ncols = ai[1] - ai[0]; ai++; 3262 if (ncols == A->cmap->n) { /* row is dense */ 3263 x[i] = *aa; if (idx) idx[i] = 0; 3264 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3265 x[i] = 0.0; 3266 if (idx) { /* find first implicit 0.0 in the row */ 3267 idx[i] = 0; /* in case ncols is zero */ 3268 for (j=0; j<ncols; j++) { 3269 if (aj[j] > j) { 3270 idx[i] = j; 3271 break; 3272 } 3273 } 3274 } 3275 } 3276 for (j=0; j<ncols; j++) { 3277 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3278 aa++; aj++; 3279 } 3280 } 3281 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3282 PetscFunctionReturn(0); 3283 } 3284 3285 #include <petscblaslapack.h> 3286 #include <petsc-private/kernels/blockinvert.h> 3287 3288 #undef __FUNCT__ 3289 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3290 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3291 { 3292 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3293 PetscErrorCode ierr; 3294 PetscInt i,bs = A->rmap->bs,mbs = A->rmap->n/A->rmap->bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3295 MatScalar *diag,work[25],*v_work; 3296 PetscReal shift = 0.0; 3297 3298 PetscFunctionBegin; 3299 if (a->ibdiagvalid) { 3300 if (values) *values = a->ibdiag; 3301 PetscFunctionReturn(0); 3302 } 3303 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3304 if (!a->ibdiag) { 3305 ierr = PetscMalloc(bs2*mbs*sizeof(PetscScalar),&a->ibdiag);CHKERRQ(ierr); 3306 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3307 } 3308 diag = a->ibdiag; 3309 if (values) *values = a->ibdiag; 3310 /* factor and invert each block */ 3311 switch (bs) { 3312 case 1: 3313 for (i=0; i<mbs; i++) { 3314 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3315 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3316 } 3317 break; 3318 case 2: 3319 for (i=0; i<mbs; i++) { 3320 ij[0] = 2*i; ij[1] = 2*i + 1; 3321 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3322 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3323 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3324 diag += 4; 3325 } 3326 break; 3327 case 3: 3328 for (i=0; i<mbs; i++) { 3329 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3330 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3331 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3332 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3333 diag += 9; 3334 } 3335 break; 3336 case 4: 3337 for (i=0; i<mbs; i++) { 3338 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3339 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3340 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3341 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3342 diag += 16; 3343 } 3344 break; 3345 case 5: 3346 for (i=0; i<mbs; i++) { 3347 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3348 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3349 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3350 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3351 diag += 25; 3352 } 3353 break; 3354 case 6: 3355 for (i=0; i<mbs; i++) { 3356 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; 3357 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3358 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3359 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3360 diag += 36; 3361 } 3362 break; 3363 case 7: 3364 for (i=0; i<mbs; i++) { 3365 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; 3366 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3367 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3368 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3369 diag += 49; 3370 } 3371 break; 3372 default: 3373 ierr = PetscMalloc3(bs,MatScalar,&v_work,bs,PetscInt,&v_pivots,bs,PetscInt,&IJ);CHKERRQ(ierr); 3374 for (i=0; i<mbs; i++) { 3375 for (j=0; j<bs; j++) { 3376 IJ[j] = bs*i + j; 3377 } 3378 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3379 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3380 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3381 diag += bs2; 3382 } 3383 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3384 } 3385 a->ibdiagvalid = PETSC_TRUE; 3386 PetscFunctionReturn(0); 3387 } 3388 3389 #undef __FUNCT__ 3390 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3391 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3392 { 3393 PetscErrorCode ierr; 3394 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3395 PetscScalar a; 3396 PetscInt m,n,i,j,col; 3397 3398 PetscFunctionBegin; 3399 if (!x->assembled) { 3400 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3401 for (i=0; i<m; i++) { 3402 for (j=0; j<aij->imax[i]; j++) { 3403 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3404 col = (PetscInt)(n*PetscRealPart(a)); 3405 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3406 } 3407 } 3408 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3409 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3410 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3411 PetscFunctionReturn(0); 3412 } 3413 3414 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3415 /* -------------------------------------------------------------------*/ 3416 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3417 MatGetRow_SeqAIJ, 3418 MatRestoreRow_SeqAIJ, 3419 MatMult_SeqAIJ, 3420 /* 4*/ MatMultAdd_SeqAIJ, 3421 MatMultTranspose_SeqAIJ, 3422 MatMultTransposeAdd_SeqAIJ, 3423 0, 3424 0, 3425 0, 3426 /* 10*/ 0, 3427 MatLUFactor_SeqAIJ, 3428 0, 3429 MatSOR_SeqAIJ, 3430 MatTranspose_SeqAIJ, 3431 /*1 5*/ MatGetInfo_SeqAIJ, 3432 MatEqual_SeqAIJ, 3433 MatGetDiagonal_SeqAIJ, 3434 MatDiagonalScale_SeqAIJ, 3435 MatNorm_SeqAIJ, 3436 /* 20*/ 0, 3437 MatAssemblyEnd_SeqAIJ, 3438 MatSetOption_SeqAIJ, 3439 MatZeroEntries_SeqAIJ, 3440 /* 24*/ MatZeroRows_SeqAIJ, 3441 0, 3442 0, 3443 0, 3444 0, 3445 /* 29*/ MatSetUp_SeqAIJ, 3446 0, 3447 0, 3448 0, 3449 0, 3450 /* 34*/ MatDuplicate_SeqAIJ, 3451 0, 3452 0, 3453 MatILUFactor_SeqAIJ, 3454 0, 3455 /* 39*/ MatAXPY_SeqAIJ, 3456 MatGetSubMatrices_SeqAIJ, 3457 MatIncreaseOverlap_SeqAIJ, 3458 MatGetValues_SeqAIJ, 3459 MatCopy_SeqAIJ, 3460 /* 44*/ MatGetRowMax_SeqAIJ, 3461 MatScale_SeqAIJ, 3462 0, 3463 MatDiagonalSet_SeqAIJ, 3464 MatZeroRowsColumns_SeqAIJ, 3465 /* 49*/ MatSetRandom_SeqAIJ, 3466 MatGetRowIJ_SeqAIJ, 3467 MatRestoreRowIJ_SeqAIJ, 3468 MatGetColumnIJ_SeqAIJ, 3469 MatRestoreColumnIJ_SeqAIJ, 3470 /* 54*/ MatFDColoringCreate_SeqAIJ, 3471 0, 3472 0, 3473 MatPermute_SeqAIJ, 3474 0, 3475 /* 59*/ 0, 3476 MatDestroy_SeqAIJ, 3477 MatView_SeqAIJ, 3478 0, 3479 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3480 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3481 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3482 0, 3483 0, 3484 0, 3485 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3486 MatGetRowMinAbs_SeqAIJ, 3487 0, 3488 MatSetColoring_SeqAIJ, 3489 0, 3490 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3491 MatFDColoringApply_AIJ, 3492 0, 3493 0, 3494 0, 3495 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3496 0, 3497 0, 3498 0, 3499 MatLoad_SeqAIJ, 3500 /* 84*/ MatIsSymmetric_SeqAIJ, 3501 MatIsHermitian_SeqAIJ, 3502 0, 3503 0, 3504 0, 3505 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3506 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3507 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3508 MatPtAP_SeqAIJ_SeqAIJ, 3509 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3510 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3511 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3512 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3513 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3514 0, 3515 /* 99*/ 0, 3516 0, 3517 0, 3518 MatConjugate_SeqAIJ, 3519 0, 3520 /*104*/ MatSetValuesRow_SeqAIJ, 3521 MatRealPart_SeqAIJ, 3522 MatImaginaryPart_SeqAIJ, 3523 0, 3524 0, 3525 /*109*/ MatMatSolve_SeqAIJ, 3526 0, 3527 MatGetRowMin_SeqAIJ, 3528 0, 3529 MatMissingDiagonal_SeqAIJ, 3530 /*114*/ 0, 3531 0, 3532 0, 3533 0, 3534 0, 3535 /*119*/ 0, 3536 0, 3537 0, 3538 0, 3539 MatGetMultiProcBlock_SeqAIJ, 3540 /*124*/ MatFindNonzeroRows_SeqAIJ, 3541 MatGetColumnNorms_SeqAIJ, 3542 MatInvertBlockDiagonal_SeqAIJ, 3543 0, 3544 0, 3545 /*129*/ 0, 3546 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3547 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3548 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3549 MatTransposeColoringCreate_SeqAIJ, 3550 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3551 MatTransColoringApplyDenToSp_SeqAIJ, 3552 MatRARt_SeqAIJ_SeqAIJ, 3553 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3554 MatRARtNumeric_SeqAIJ_SeqAIJ, 3555 /*139*/0, 3556 0 3557 }; 3558 3559 #undef __FUNCT__ 3560 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3561 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3562 { 3563 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3564 PetscInt i,nz,n; 3565 3566 PetscFunctionBegin; 3567 nz = aij->maxnz; 3568 n = mat->rmap->n; 3569 for (i=0; i<nz; i++) { 3570 aij->j[i] = indices[i]; 3571 } 3572 aij->nz = nz; 3573 for (i=0; i<n; i++) { 3574 aij->ilen[i] = aij->imax[i]; 3575 } 3576 PetscFunctionReturn(0); 3577 } 3578 3579 #undef __FUNCT__ 3580 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3581 /*@ 3582 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3583 in the matrix. 3584 3585 Input Parameters: 3586 + mat - the SeqAIJ matrix 3587 - indices - the column indices 3588 3589 Level: advanced 3590 3591 Notes: 3592 This can be called if you have precomputed the nonzero structure of the 3593 matrix and want to provide it to the matrix object to improve the performance 3594 of the MatSetValues() operation. 3595 3596 You MUST have set the correct numbers of nonzeros per row in the call to 3597 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3598 3599 MUST be called before any calls to MatSetValues(); 3600 3601 The indices should start with zero, not one. 3602 3603 @*/ 3604 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3605 { 3606 PetscErrorCode ierr; 3607 3608 PetscFunctionBegin; 3609 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3610 PetscValidPointer(indices,2); 3611 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3612 PetscFunctionReturn(0); 3613 } 3614 3615 /* ----------------------------------------------------------------------------------------*/ 3616 3617 #undef __FUNCT__ 3618 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3619 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3620 { 3621 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3622 PetscErrorCode ierr; 3623 size_t nz = aij->i[mat->rmap->n]; 3624 3625 PetscFunctionBegin; 3626 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3627 3628 /* allocate space for values if not already there */ 3629 if (!aij->saved_values) { 3630 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 3631 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3632 } 3633 3634 /* copy values over */ 3635 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3636 PetscFunctionReturn(0); 3637 } 3638 3639 #undef __FUNCT__ 3640 #define __FUNCT__ "MatStoreValues" 3641 /*@ 3642 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3643 example, reuse of the linear part of a Jacobian, while recomputing the 3644 nonlinear portion. 3645 3646 Collect on Mat 3647 3648 Input Parameters: 3649 . mat - the matrix (currently only AIJ matrices support this option) 3650 3651 Level: advanced 3652 3653 Common Usage, with SNESSolve(): 3654 $ Create Jacobian matrix 3655 $ Set linear terms into matrix 3656 $ Apply boundary conditions to matrix, at this time matrix must have 3657 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3658 $ boundary conditions again will not change the nonzero structure 3659 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3660 $ ierr = MatStoreValues(mat); 3661 $ Call SNESSetJacobian() with matrix 3662 $ In your Jacobian routine 3663 $ ierr = MatRetrieveValues(mat); 3664 $ Set nonlinear terms in matrix 3665 3666 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3667 $ // build linear portion of Jacobian 3668 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3669 $ ierr = MatStoreValues(mat); 3670 $ loop over nonlinear iterations 3671 $ ierr = MatRetrieveValues(mat); 3672 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3673 $ // call MatAssemblyBegin/End() on matrix 3674 $ Solve linear system with Jacobian 3675 $ endloop 3676 3677 Notes: 3678 Matrix must already be assemblied before calling this routine 3679 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3680 calling this routine. 3681 3682 When this is called multiple times it overwrites the previous set of stored values 3683 and does not allocated additional space. 3684 3685 .seealso: MatRetrieveValues() 3686 3687 @*/ 3688 PetscErrorCode MatStoreValues(Mat mat) 3689 { 3690 PetscErrorCode ierr; 3691 3692 PetscFunctionBegin; 3693 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3694 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3695 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3696 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3697 PetscFunctionReturn(0); 3698 } 3699 3700 #undef __FUNCT__ 3701 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3702 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3703 { 3704 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3705 PetscErrorCode ierr; 3706 PetscInt nz = aij->i[mat->rmap->n]; 3707 3708 PetscFunctionBegin; 3709 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3710 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3711 /* copy values over */ 3712 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3713 PetscFunctionReturn(0); 3714 } 3715 3716 #undef __FUNCT__ 3717 #define __FUNCT__ "MatRetrieveValues" 3718 /*@ 3719 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3720 example, reuse of the linear part of a Jacobian, while recomputing the 3721 nonlinear portion. 3722 3723 Collect on Mat 3724 3725 Input Parameters: 3726 . mat - the matrix (currently on AIJ matrices support this option) 3727 3728 Level: advanced 3729 3730 .seealso: MatStoreValues() 3731 3732 @*/ 3733 PetscErrorCode MatRetrieveValues(Mat mat) 3734 { 3735 PetscErrorCode ierr; 3736 3737 PetscFunctionBegin; 3738 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3739 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3740 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3741 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3742 PetscFunctionReturn(0); 3743 } 3744 3745 3746 /* --------------------------------------------------------------------------------*/ 3747 #undef __FUNCT__ 3748 #define __FUNCT__ "MatCreateSeqAIJ" 3749 /*@C 3750 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3751 (the default parallel PETSc format). For good matrix assembly performance 3752 the user should preallocate the matrix storage by setting the parameter nz 3753 (or the array nnz). By setting these parameters accurately, performance 3754 during matrix assembly can be increased by more than a factor of 50. 3755 3756 Collective on MPI_Comm 3757 3758 Input Parameters: 3759 + comm - MPI communicator, set to PETSC_COMM_SELF 3760 . m - number of rows 3761 . n - number of columns 3762 . nz - number of nonzeros per row (same for all rows) 3763 - nnz - array containing the number of nonzeros in the various rows 3764 (possibly different for each row) or NULL 3765 3766 Output Parameter: 3767 . A - the matrix 3768 3769 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3770 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3771 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3772 3773 Notes: 3774 If nnz is given then nz is ignored 3775 3776 The AIJ format (also called the Yale sparse matrix format or 3777 compressed row storage), is fully compatible with standard Fortran 77 3778 storage. That is, the stored row and column indices can begin at 3779 either one (as in Fortran) or zero. See the users' manual for details. 3780 3781 Specify the preallocated storage with either nz or nnz (not both). 3782 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3783 allocation. For large problems you MUST preallocate memory or you 3784 will get TERRIBLE performance, see the users' manual chapter on matrices. 3785 3786 By default, this format uses inodes (identical nodes) when possible, to 3787 improve numerical efficiency of matrix-vector products and solves. We 3788 search for consecutive rows with the same nonzero structure, thereby 3789 reusing matrix information to achieve increased efficiency. 3790 3791 Options Database Keys: 3792 + -mat_no_inode - Do not use inodes 3793 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3794 3795 Level: intermediate 3796 3797 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3798 3799 @*/ 3800 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3801 { 3802 PetscErrorCode ierr; 3803 3804 PetscFunctionBegin; 3805 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3806 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3807 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3808 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3809 PetscFunctionReturn(0); 3810 } 3811 3812 #undef __FUNCT__ 3813 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3814 /*@C 3815 MatSeqAIJSetPreallocation - For good matrix assembly performance 3816 the user should preallocate the matrix storage by setting the parameter nz 3817 (or the array nnz). By setting these parameters accurately, performance 3818 during matrix assembly can be increased by more than a factor of 50. 3819 3820 Collective on MPI_Comm 3821 3822 Input Parameters: 3823 + B - The matrix-free 3824 . nz - number of nonzeros per row (same for all rows) 3825 - nnz - array containing the number of nonzeros in the various rows 3826 (possibly different for each row) or NULL 3827 3828 Notes: 3829 If nnz is given then nz is ignored 3830 3831 The AIJ format (also called the Yale sparse matrix format or 3832 compressed row storage), is fully compatible with standard Fortran 77 3833 storage. That is, the stored row and column indices can begin at 3834 either one (as in Fortran) or zero. See the users' manual for details. 3835 3836 Specify the preallocated storage with either nz or nnz (not both). 3837 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3838 allocation. For large problems you MUST preallocate memory or you 3839 will get TERRIBLE performance, see the users' manual chapter on matrices. 3840 3841 You can call MatGetInfo() to get information on how effective the preallocation was; 3842 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3843 You can also run with the option -info and look for messages with the string 3844 malloc in them to see if additional memory allocation was needed. 3845 3846 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3847 entries or columns indices 3848 3849 By default, this format uses inodes (identical nodes) when possible, to 3850 improve numerical efficiency of matrix-vector products and solves. We 3851 search for consecutive rows with the same nonzero structure, thereby 3852 reusing matrix information to achieve increased efficiency. 3853 3854 Options Database Keys: 3855 + -mat_no_inode - Do not use inodes 3856 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3857 - -mat_aij_oneindex - Internally use indexing starting at 1 3858 rather than 0. Note that when calling MatSetValues(), 3859 the user still MUST index entries starting at 0! 3860 3861 Level: intermediate 3862 3863 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3864 3865 @*/ 3866 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3867 { 3868 PetscErrorCode ierr; 3869 3870 PetscFunctionBegin; 3871 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3872 PetscValidType(B,1); 3873 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3874 PetscFunctionReturn(0); 3875 } 3876 3877 #undef __FUNCT__ 3878 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3879 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3880 { 3881 Mat_SeqAIJ *b; 3882 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3883 PetscErrorCode ierr; 3884 PetscInt i; 3885 3886 PetscFunctionBegin; 3887 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3888 if (nz == MAT_SKIP_ALLOCATION) { 3889 skipallocation = PETSC_TRUE; 3890 nz = 0; 3891 } 3892 3893 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3894 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3895 3896 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3897 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3898 if (nnz) { 3899 for (i=0; i<B->rmap->n; i++) { 3900 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]); 3901 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); 3902 } 3903 } 3904 3905 B->preallocated = PETSC_TRUE; 3906 3907 b = (Mat_SeqAIJ*)B->data; 3908 3909 if (!skipallocation) { 3910 if (!b->imax) { 3911 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3912 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3913 } 3914 if (!nnz) { 3915 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3916 else if (nz < 0) nz = 1; 3917 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3918 nz = nz*B->rmap->n; 3919 } else { 3920 nz = 0; 3921 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3922 } 3923 /* b->ilen will count nonzeros in each row so far. */ 3924 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3925 3926 /* allocate the matrix space */ 3927 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3928 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3929 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3930 b->i[0] = 0; 3931 for (i=1; i<B->rmap->n+1; i++) { 3932 b->i[i] = b->i[i-1] + b->imax[i-1]; 3933 } 3934 b->singlemalloc = PETSC_TRUE; 3935 b->free_a = PETSC_TRUE; 3936 b->free_ij = PETSC_TRUE; 3937 #if defined(PETSC_THREADCOMM_ACTIVE) 3938 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3939 #endif 3940 } else { 3941 b->free_a = PETSC_FALSE; 3942 b->free_ij = PETSC_FALSE; 3943 } 3944 3945 b->nz = 0; 3946 b->maxnz = nz; 3947 B->info.nz_unneeded = (double)b->maxnz; 3948 if (realalloc) { 3949 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3950 } 3951 PetscFunctionReturn(0); 3952 } 3953 3954 #undef __FUNCT__ 3955 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3956 /*@ 3957 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3958 3959 Input Parameters: 3960 + B - the matrix 3961 . i - the indices into j for the start of each row (starts with zero) 3962 . j - the column indices for each row (starts with zero) these must be sorted for each row 3963 - v - optional values in the matrix 3964 3965 Level: developer 3966 3967 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3968 3969 .keywords: matrix, aij, compressed row, sparse, sequential 3970 3971 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3972 @*/ 3973 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3974 { 3975 PetscErrorCode ierr; 3976 3977 PetscFunctionBegin; 3978 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3979 PetscValidType(B,1); 3980 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3981 PetscFunctionReturn(0); 3982 } 3983 3984 #undef __FUNCT__ 3985 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3986 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3987 { 3988 PetscInt i; 3989 PetscInt m,n; 3990 PetscInt nz; 3991 PetscInt *nnz, nz_max = 0; 3992 PetscScalar *values; 3993 PetscErrorCode ierr; 3994 3995 PetscFunctionBegin; 3996 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3997 3998 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3999 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4000 4001 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 4002 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 4003 for (i = 0; i < m; i++) { 4004 nz = Ii[i+1]- Ii[i]; 4005 nz_max = PetscMax(nz_max, nz); 4006 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 4007 nnz[i] = nz; 4008 } 4009 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 4010 ierr = PetscFree(nnz);CHKERRQ(ierr); 4011 4012 if (v) { 4013 values = (PetscScalar*) v; 4014 } else { 4015 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 4016 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 4017 } 4018 4019 for (i = 0; i < m; i++) { 4020 nz = Ii[i+1] - Ii[i]; 4021 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 4022 } 4023 4024 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4025 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4026 4027 if (!v) { 4028 ierr = PetscFree(values);CHKERRQ(ierr); 4029 } 4030 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4031 PetscFunctionReturn(0); 4032 } 4033 4034 #include <../src/mat/impls/dense/seq/dense.h> 4035 #include <petsc-private/kernels/petscaxpy.h> 4036 4037 #undef __FUNCT__ 4038 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 4039 /* 4040 Computes (B'*A')' since computing B*A directly is untenable 4041 4042 n p p 4043 ( ) ( ) ( ) 4044 m ( A ) * n ( B ) = m ( C ) 4045 ( ) ( ) ( ) 4046 4047 */ 4048 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4049 { 4050 PetscErrorCode ierr; 4051 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4052 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4053 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4054 PetscInt i,n,m,q,p; 4055 const PetscInt *ii,*idx; 4056 const PetscScalar *b,*a,*a_q; 4057 PetscScalar *c,*c_q; 4058 4059 PetscFunctionBegin; 4060 m = A->rmap->n; 4061 n = A->cmap->n; 4062 p = B->cmap->n; 4063 a = sub_a->v; 4064 b = sub_b->a; 4065 c = sub_c->v; 4066 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 4067 4068 ii = sub_b->i; 4069 idx = sub_b->j; 4070 for (i=0; i<n; i++) { 4071 q = ii[i+1] - ii[i]; 4072 while (q-->0) { 4073 c_q = c + m*(*idx); 4074 a_q = a + m*i; 4075 PetscKernelAXPY(c_q,*b,a_q,m); 4076 idx++; 4077 b++; 4078 } 4079 } 4080 PetscFunctionReturn(0); 4081 } 4082 4083 #undef __FUNCT__ 4084 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 4085 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4086 { 4087 PetscErrorCode ierr; 4088 PetscInt m=A->rmap->n,n=B->cmap->n; 4089 Mat Cmat; 4090 4091 PetscFunctionBegin; 4092 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); 4093 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4094 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4095 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 4096 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4097 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4098 4099 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4100 4101 *C = Cmat; 4102 PetscFunctionReturn(0); 4103 } 4104 4105 /* ----------------------------------------------------------------*/ 4106 #undef __FUNCT__ 4107 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 4108 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4109 { 4110 PetscErrorCode ierr; 4111 4112 PetscFunctionBegin; 4113 if (scall == MAT_INITIAL_MATRIX) { 4114 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4115 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4116 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4117 } 4118 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4119 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4120 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4121 PetscFunctionReturn(0); 4122 } 4123 4124 4125 /*MC 4126 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4127 based on compressed sparse row format. 4128 4129 Options Database Keys: 4130 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4131 4132 Level: beginner 4133 4134 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4135 M*/ 4136 4137 /*MC 4138 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4139 4140 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4141 and MATMPIAIJ otherwise. As a result, for single process communicators, 4142 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 4143 for communicators controlling multiple processes. It is recommended that you call both of 4144 the above preallocation routines for simplicity. 4145 4146 Options Database Keys: 4147 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4148 4149 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 4150 enough exist. 4151 4152 Level: beginner 4153 4154 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4155 M*/ 4156 4157 /*MC 4158 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4159 4160 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4161 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4162 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4163 for communicators controlling multiple processes. It is recommended that you call both of 4164 the above preallocation routines for simplicity. 4165 4166 Options Database Keys: 4167 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4168 4169 Level: beginner 4170 4171 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4172 M*/ 4173 4174 #if defined(PETSC_HAVE_PASTIX) 4175 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 4176 #endif 4177 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4178 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 4179 #endif 4180 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4181 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 4182 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 4183 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 4184 #if defined(PETSC_HAVE_MUMPS) 4185 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 4186 #endif 4187 #if defined(PETSC_HAVE_SUPERLU) 4188 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 4189 #endif 4190 #if defined(PETSC_HAVE_SUPERLU_DIST) 4191 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 4192 #endif 4193 #if defined(PETSC_HAVE_UMFPACK) 4194 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 4195 #endif 4196 #if defined(PETSC_HAVE_CHOLMOD) 4197 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 4198 #endif 4199 #if defined(PETSC_HAVE_LUSOL) 4200 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 4201 #endif 4202 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4203 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 4204 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 4205 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 4206 #endif 4207 #if defined(PETSC_HAVE_CLIQUE) 4208 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 4209 #endif 4210 4211 4212 #undef __FUNCT__ 4213 #define __FUNCT__ "MatSeqAIJGetArray" 4214 /*@C 4215 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 4216 4217 Not Collective 4218 4219 Input Parameter: 4220 . mat - a MATSEQDENSE matrix 4221 4222 Output Parameter: 4223 . array - pointer to the data 4224 4225 Level: intermediate 4226 4227 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4228 @*/ 4229 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4230 { 4231 PetscErrorCode ierr; 4232 4233 PetscFunctionBegin; 4234 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4235 PetscFunctionReturn(0); 4236 } 4237 4238 #undef __FUNCT__ 4239 #define __FUNCT__ "MatSeqAIJRestoreArray" 4240 /*@C 4241 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4242 4243 Not Collective 4244 4245 Input Parameters: 4246 . mat - a MATSEQDENSE matrix 4247 . array - pointer to the data 4248 4249 Level: intermediate 4250 4251 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4252 @*/ 4253 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4254 { 4255 PetscErrorCode ierr; 4256 4257 PetscFunctionBegin; 4258 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4259 PetscFunctionReturn(0); 4260 } 4261 4262 #undef __FUNCT__ 4263 #define __FUNCT__ "MatCreate_SeqAIJ" 4264 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4265 { 4266 Mat_SeqAIJ *b; 4267 PetscErrorCode ierr; 4268 PetscMPIInt size; 4269 4270 PetscFunctionBegin; 4271 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4272 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4273 4274 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 4275 4276 B->data = (void*)b; 4277 4278 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4279 4280 b->row = 0; 4281 b->col = 0; 4282 b->icol = 0; 4283 b->reallocs = 0; 4284 b->ignorezeroentries = PETSC_FALSE; 4285 b->roworiented = PETSC_TRUE; 4286 b->nonew = 0; 4287 b->diag = 0; 4288 b->solve_work = 0; 4289 B->spptr = 0; 4290 b->saved_values = 0; 4291 b->idiag = 0; 4292 b->mdiag = 0; 4293 b->ssor_work = 0; 4294 b->omega = 1.0; 4295 b->fshift = 0.0; 4296 b->idiagvalid = PETSC_FALSE; 4297 b->ibdiagvalid = PETSC_FALSE; 4298 b->keepnonzeropattern = PETSC_FALSE; 4299 b->xtoy = 0; 4300 b->XtoY = 0; 4301 B->same_nonzero = PETSC_FALSE; 4302 4303 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4304 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4305 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4306 4307 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4308 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4309 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4310 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4311 #endif 4312 #if defined(PETSC_HAVE_PASTIX) 4313 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4314 #endif 4315 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4316 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4317 #endif 4318 #if defined(PETSC_HAVE_SUPERLU) 4319 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4320 #endif 4321 #if defined(PETSC_HAVE_SUPERLU_DIST) 4322 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4323 #endif 4324 #if defined(PETSC_HAVE_MUMPS) 4325 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4326 #endif 4327 #if defined(PETSC_HAVE_UMFPACK) 4328 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4329 #endif 4330 #if defined(PETSC_HAVE_CHOLMOD) 4331 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4332 #endif 4333 #if defined(PETSC_HAVE_LUSOL) 4334 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4335 #endif 4336 #if defined(PETSC_HAVE_CLIQUE) 4337 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4338 #endif 4339 4340 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4341 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4342 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4343 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4344 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4345 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4346 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4347 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4348 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4349 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4350 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4351 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4352 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4353 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4354 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4355 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4356 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4357 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4358 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4359 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4360 PetscFunctionReturn(0); 4361 } 4362 4363 #undef __FUNCT__ 4364 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4365 /* 4366 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4367 */ 4368 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4369 { 4370 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4371 PetscErrorCode ierr; 4372 PetscInt i,m = A->rmap->n; 4373 4374 PetscFunctionBegin; 4375 c = (Mat_SeqAIJ*)C->data; 4376 4377 C->factortype = A->factortype; 4378 c->row = 0; 4379 c->col = 0; 4380 c->icol = 0; 4381 c->reallocs = 0; 4382 4383 C->assembled = PETSC_TRUE; 4384 4385 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4386 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4387 4388 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 4389 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4390 for (i=0; i<m; i++) { 4391 c->imax[i] = a->imax[i]; 4392 c->ilen[i] = a->ilen[i]; 4393 } 4394 4395 /* allocate the matrix space */ 4396 if (mallocmatspace) { 4397 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 4398 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4399 4400 c->singlemalloc = PETSC_TRUE; 4401 4402 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4403 if (m > 0) { 4404 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4405 if (cpvalues == MAT_COPY_VALUES) { 4406 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4407 } else { 4408 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4409 } 4410 } 4411 } 4412 4413 c->ignorezeroentries = a->ignorezeroentries; 4414 c->roworiented = a->roworiented; 4415 c->nonew = a->nonew; 4416 if (a->diag) { 4417 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 4418 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4419 for (i=0; i<m; i++) { 4420 c->diag[i] = a->diag[i]; 4421 } 4422 } else c->diag = 0; 4423 4424 c->solve_work = 0; 4425 c->saved_values = 0; 4426 c->idiag = 0; 4427 c->ssor_work = 0; 4428 c->keepnonzeropattern = a->keepnonzeropattern; 4429 c->free_a = PETSC_TRUE; 4430 c->free_ij = PETSC_TRUE; 4431 c->xtoy = 0; 4432 c->XtoY = 0; 4433 4434 c->rmax = a->rmax; 4435 c->nz = a->nz; 4436 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4437 C->preallocated = PETSC_TRUE; 4438 4439 c->compressedrow.use = a->compressedrow.use; 4440 c->compressedrow.nrows = a->compressedrow.nrows; 4441 c->compressedrow.check = a->compressedrow.check; 4442 if (a->compressedrow.use) { 4443 i = a->compressedrow.nrows; 4444 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 4445 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4446 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4447 } else { 4448 c->compressedrow.use = PETSC_FALSE; 4449 c->compressedrow.i = NULL; 4450 c->compressedrow.rindex = NULL; 4451 } 4452 C->same_nonzero = A->same_nonzero; 4453 4454 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4455 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4456 PetscFunctionReturn(0); 4457 } 4458 4459 #undef __FUNCT__ 4460 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4461 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4462 { 4463 PetscErrorCode ierr; 4464 4465 PetscFunctionBegin; 4466 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4467 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4468 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4469 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4470 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4471 PetscFunctionReturn(0); 4472 } 4473 4474 #undef __FUNCT__ 4475 #define __FUNCT__ "MatLoad_SeqAIJ" 4476 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4477 { 4478 Mat_SeqAIJ *a; 4479 PetscErrorCode ierr; 4480 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4481 int fd; 4482 PetscMPIInt size; 4483 MPI_Comm comm; 4484 PetscInt bs = 1; 4485 4486 PetscFunctionBegin; 4487 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4488 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4489 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4490 4491 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4492 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4493 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4494 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4495 4496 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4497 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4498 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4499 M = header[1]; N = header[2]; nz = header[3]; 4500 4501 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4502 4503 /* read in row lengths */ 4504 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 4505 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4506 4507 /* check if sum of rowlengths is same as nz */ 4508 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4509 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); 4510 4511 /* set global size if not set already*/ 4512 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4513 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4514 } else { 4515 /* if sizes and type are already set, check if the vector global sizes are correct */ 4516 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4517 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4518 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4519 } 4520 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); 4521 } 4522 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4523 a = (Mat_SeqAIJ*)newMat->data; 4524 4525 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4526 4527 /* read in nonzero values */ 4528 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4529 4530 /* set matrix "i" values */ 4531 a->i[0] = 0; 4532 for (i=1; i<= M; i++) { 4533 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4534 a->ilen[i-1] = rowlengths[i-1]; 4535 } 4536 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4537 4538 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4539 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4540 PetscFunctionReturn(0); 4541 } 4542 4543 #undef __FUNCT__ 4544 #define __FUNCT__ "MatEqual_SeqAIJ" 4545 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4546 { 4547 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4548 PetscErrorCode ierr; 4549 #if defined(PETSC_USE_COMPLEX) 4550 PetscInt k; 4551 #endif 4552 4553 PetscFunctionBegin; 4554 /* If the matrix dimensions are not equal,or no of nonzeros */ 4555 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4556 *flg = PETSC_FALSE; 4557 PetscFunctionReturn(0); 4558 } 4559 4560 /* if the a->i are the same */ 4561 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4562 if (!*flg) PetscFunctionReturn(0); 4563 4564 /* if a->j are the same */ 4565 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4566 if (!*flg) PetscFunctionReturn(0); 4567 4568 /* if a->a are the same */ 4569 #if defined(PETSC_USE_COMPLEX) 4570 for (k=0; k<a->nz; k++) { 4571 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4572 *flg = PETSC_FALSE; 4573 PetscFunctionReturn(0); 4574 } 4575 } 4576 #else 4577 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4578 #endif 4579 PetscFunctionReturn(0); 4580 } 4581 4582 #undef __FUNCT__ 4583 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4584 /*@ 4585 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4586 provided by the user. 4587 4588 Collective on MPI_Comm 4589 4590 Input Parameters: 4591 + comm - must be an MPI communicator of size 1 4592 . m - number of rows 4593 . n - number of columns 4594 . i - row indices 4595 . j - column indices 4596 - a - matrix values 4597 4598 Output Parameter: 4599 . mat - the matrix 4600 4601 Level: intermediate 4602 4603 Notes: 4604 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4605 once the matrix is destroyed and not before 4606 4607 You cannot set new nonzero locations into this matrix, that will generate an error. 4608 4609 The i and j indices are 0 based 4610 4611 The format which is used for the sparse matrix input, is equivalent to a 4612 row-major ordering.. i.e for the following matrix, the input data expected is 4613 as shown: 4614 4615 1 0 0 4616 2 0 3 4617 4 5 6 4618 4619 i = {0,1,3,6} [size = nrow+1 = 3+1] 4620 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4621 v = {1,2,3,4,5,6} [size = nz = 6] 4622 4623 4624 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4625 4626 @*/ 4627 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4628 { 4629 PetscErrorCode ierr; 4630 PetscInt ii; 4631 Mat_SeqAIJ *aij; 4632 #if defined(PETSC_USE_DEBUG) 4633 PetscInt jj; 4634 #endif 4635 4636 PetscFunctionBegin; 4637 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4638 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4639 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4640 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4641 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4642 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4643 aij = (Mat_SeqAIJ*)(*mat)->data; 4644 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 4645 4646 aij->i = i; 4647 aij->j = j; 4648 aij->a = a; 4649 aij->singlemalloc = PETSC_FALSE; 4650 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4651 aij->free_a = PETSC_FALSE; 4652 aij->free_ij = PETSC_FALSE; 4653 4654 for (ii=0; ii<m; ii++) { 4655 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4656 #if defined(PETSC_USE_DEBUG) 4657 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]); 4658 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4659 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); 4660 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); 4661 } 4662 #endif 4663 } 4664 #if defined(PETSC_USE_DEBUG) 4665 for (ii=0; ii<aij->i[m]; ii++) { 4666 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 4667 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]); 4668 } 4669 #endif 4670 4671 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4672 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4673 PetscFunctionReturn(0); 4674 } 4675 #undef __FUNCT__ 4676 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4677 /*@C 4678 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4679 provided by the user. 4680 4681 Collective on MPI_Comm 4682 4683 Input Parameters: 4684 + comm - must be an MPI communicator of size 1 4685 . m - number of rows 4686 . n - number of columns 4687 . i - row indices 4688 . j - column indices 4689 . a - matrix values 4690 . nz - number of nonzeros 4691 - idx - 0 or 1 based 4692 4693 Output Parameter: 4694 . mat - the matrix 4695 4696 Level: intermediate 4697 4698 Notes: 4699 The i and j indices are 0 based 4700 4701 The format which is used for the sparse matrix input, is equivalent to a 4702 row-major ordering.. i.e for the following matrix, the input data expected is 4703 as shown: 4704 4705 1 0 0 4706 2 0 3 4707 4 5 6 4708 4709 i = {0,1,1,2,2,2} 4710 j = {0,0,2,0,1,2} 4711 v = {1,2,3,4,5,6} 4712 4713 4714 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4715 4716 @*/ 4717 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4718 { 4719 PetscErrorCode ierr; 4720 PetscInt ii, *nnz, one = 1,row,col; 4721 4722 4723 PetscFunctionBegin; 4724 ierr = PetscMalloc(m*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 4725 ierr = PetscMemzero(nnz,m*sizeof(PetscInt));CHKERRQ(ierr); 4726 for (ii = 0; ii < nz; ii++) { 4727 nnz[i[ii]] += 1; 4728 } 4729 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4730 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4731 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4732 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4733 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4734 for (ii = 0; ii < nz; ii++) { 4735 if (idx) { 4736 row = i[ii] - 1; 4737 col = j[ii] - 1; 4738 } else { 4739 row = i[ii]; 4740 col = j[ii]; 4741 } 4742 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4743 } 4744 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4745 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4746 ierr = PetscFree(nnz);CHKERRQ(ierr); 4747 PetscFunctionReturn(0); 4748 } 4749 4750 #undef __FUNCT__ 4751 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4752 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4753 { 4754 PetscErrorCode ierr; 4755 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4756 4757 PetscFunctionBegin; 4758 if (coloring->ctype == IS_COLORING_GLOBAL) { 4759 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4760 a->coloring = coloring; 4761 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4762 PetscInt i,*larray; 4763 ISColoring ocoloring; 4764 ISColoringValue *colors; 4765 4766 /* set coloring for diagonal portion */ 4767 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4768 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4769 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4770 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4771 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4772 ierr = PetscFree(larray);CHKERRQ(ierr); 4773 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4774 a->coloring = ocoloring; 4775 } 4776 PetscFunctionReturn(0); 4777 } 4778 4779 #undef __FUNCT__ 4780 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4781 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4782 { 4783 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4784 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4785 MatScalar *v = a->a; 4786 PetscScalar *values = (PetscScalar*)advalues; 4787 ISColoringValue *color; 4788 4789 PetscFunctionBegin; 4790 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4791 color = a->coloring->colors; 4792 /* loop over rows */ 4793 for (i=0; i<m; i++) { 4794 nz = ii[i+1] - ii[i]; 4795 /* loop over columns putting computed value into matrix */ 4796 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4797 values += nl; /* jump to next row of derivatives */ 4798 } 4799 PetscFunctionReturn(0); 4800 } 4801 4802 #undef __FUNCT__ 4803 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4804 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4805 { 4806 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4807 PetscErrorCode ierr; 4808 4809 PetscFunctionBegin; 4810 a->idiagvalid = PETSC_FALSE; 4811 a->ibdiagvalid = PETSC_FALSE; 4812 4813 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4814 PetscFunctionReturn(0); 4815 } 4816 4817 /* 4818 Special version for direct calls from Fortran 4819 */ 4820 #include <petsc-private/fortranimpl.h> 4821 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4822 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4823 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4824 #define matsetvaluesseqaij_ matsetvaluesseqaij 4825 #endif 4826 4827 /* Change these macros so can be used in void function */ 4828 #undef CHKERRQ 4829 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4830 #undef SETERRQ2 4831 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4832 #undef SETERRQ3 4833 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4834 4835 #undef __FUNCT__ 4836 #define __FUNCT__ "matsetvaluesseqaij_" 4837 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) 4838 { 4839 Mat A = *AA; 4840 PetscInt m = *mm, n = *nn; 4841 InsertMode is = *isis; 4842 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4843 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4844 PetscInt *imax,*ai,*ailen; 4845 PetscErrorCode ierr; 4846 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4847 MatScalar *ap,value,*aa; 4848 PetscBool ignorezeroentries = a->ignorezeroentries; 4849 PetscBool roworiented = a->roworiented; 4850 4851 PetscFunctionBegin; 4852 MatCheckPreallocated(A,1); 4853 imax = a->imax; 4854 ai = a->i; 4855 ailen = a->ilen; 4856 aj = a->j; 4857 aa = a->a; 4858 4859 for (k=0; k<m; k++) { /* loop over added rows */ 4860 row = im[k]; 4861 if (row < 0) continue; 4862 #if defined(PETSC_USE_DEBUG) 4863 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4864 #endif 4865 rp = aj + ai[row]; ap = aa + ai[row]; 4866 rmax = imax[row]; nrow = ailen[row]; 4867 low = 0; 4868 high = nrow; 4869 for (l=0; l<n; l++) { /* loop over added columns */ 4870 if (in[l] < 0) continue; 4871 #if defined(PETSC_USE_DEBUG) 4872 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4873 #endif 4874 col = in[l]; 4875 if (roworiented) value = v[l + k*n]; 4876 else value = v[k + l*m]; 4877 4878 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4879 4880 if (col <= lastcol) low = 0; 4881 else high = nrow; 4882 lastcol = col; 4883 while (high-low > 5) { 4884 t = (low+high)/2; 4885 if (rp[t] > col) high = t; 4886 else low = t; 4887 } 4888 for (i=low; i<high; i++) { 4889 if (rp[i] > col) break; 4890 if (rp[i] == col) { 4891 if (is == ADD_VALUES) ap[i] += value; 4892 else ap[i] = value; 4893 goto noinsert; 4894 } 4895 } 4896 if (value == 0.0 && ignorezeroentries) goto noinsert; 4897 if (nonew == 1) goto noinsert; 4898 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4899 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4900 N = nrow++ - 1; a->nz++; high++; 4901 /* shift up all the later entries in this row */ 4902 for (ii=N; ii>=i; ii--) { 4903 rp[ii+1] = rp[ii]; 4904 ap[ii+1] = ap[ii]; 4905 } 4906 rp[i] = col; 4907 ap[i] = value; 4908 noinsert:; 4909 low = i + 1; 4910 } 4911 ailen[row] = nrow; 4912 } 4913 A->same_nonzero = PETSC_FALSE; 4914 PetscFunctionReturnVoid(); 4915 } 4916 4917 4918