1 2 /* 3 Defines the basic matrix operations for the AIJ (compressed row) 4 matrix storage format. 5 */ 6 7 8 #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ 9 #include <petscblaslapack.h> 10 #include <petscbt.h> 11 #include <petsc-private/kernels/blocktranspose.h> 12 #if defined(PETSC_THREADCOMM_ACTIVE) 13 #include <petscthreadcomm.h> 14 #endif 15 16 #undef __FUNCT__ 17 #define __FUNCT__ "MatGetColumnNorms_SeqAIJ" 18 PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) 19 { 20 PetscErrorCode ierr; 21 PetscInt i,m,n; 22 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; 23 24 PetscFunctionBegin; 25 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 26 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 27 if (type == NORM_2) { 28 for (i=0; i<aij->i[m]; i++) { 29 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); 30 } 31 } else if (type == NORM_1) { 32 for (i=0; i<aij->i[m]; i++) { 33 norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); 34 } 35 } else if (type == NORM_INFINITY) { 36 for (i=0; i<aij->i[m]; i++) { 37 norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); 38 } 39 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 40 41 if (type == NORM_2) { 42 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 43 } 44 PetscFunctionReturn(0); 45 } 46 47 #undef __FUNCT__ 48 #define __FUNCT__ "MatFindZeroDiagonals_SeqAIJ_Private" 49 PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) 50 { 51 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 52 const MatScalar *aa = a->a; 53 PetscInt i,m=A->rmap->n,cnt = 0; 54 const PetscInt *jj = a->j,*diag; 55 PetscInt *rows; 56 PetscErrorCode ierr; 57 58 PetscFunctionBegin; 59 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 60 diag = a->diag; 61 for (i=0; i<m; i++) { 62 if ((jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 63 cnt++; 64 } 65 } 66 ierr = PetscMalloc(cnt*sizeof(PetscInt),&rows);CHKERRQ(ierr); 67 cnt = 0; 68 for (i=0; i<m; i++) { 69 if ((jj[diag[i]] != i) || (aa[diag[i]] == 0.0)) { 70 rows[cnt++] = i; 71 } 72 } 73 *nrows = cnt; 74 *zrows = rows; 75 PetscFunctionReturn(0); 76 } 77 78 #undef __FUNCT__ 79 #define __FUNCT__ "MatFindZeroDiagonals_SeqAIJ" 80 PetscErrorCode MatFindZeroDiagonals_SeqAIJ(Mat A,IS *zrows) 81 { 82 PetscInt nrows,*rows; 83 PetscErrorCode ierr; 84 85 PetscFunctionBegin; 86 *zrows = NULL; 87 ierr = MatFindZeroDiagonals_SeqAIJ_Private(A,&nrows,&rows);CHKERRQ(ierr); 88 ierr = ISCreateGeneral(PetscObjectComm((PetscObject)A),nrows,rows,PETSC_OWN_POINTER,zrows);CHKERRQ(ierr); 89 PetscFunctionReturn(0); 90 } 91 92 #undef __FUNCT__ 93 #define __FUNCT__ "MatFindNonzeroRows_SeqAIJ" 94 PetscErrorCode MatFindNonzeroRows_SeqAIJ(Mat A,IS *keptrows) 95 { 96 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 97 const MatScalar *aa; 98 PetscInt m=A->rmap->n,cnt = 0; 99 const PetscInt *ii; 100 PetscInt n,i,j,*rows; 101 PetscErrorCode ierr; 102 103 PetscFunctionBegin; 104 *keptrows = 0; 105 ii = a->i; 106 for (i=0; i<m; i++) { 107 n = ii[i+1] - ii[i]; 108 if (!n) { 109 cnt++; 110 goto ok1; 111 } 112 aa = a->a + ii[i]; 113 for (j=0; j<n; j++) { 114 if (aa[j] != 0.0) goto ok1; 115 } 116 cnt++; 117 ok1:; 118 } 119 if (!cnt) PetscFunctionReturn(0); 120 ierr = PetscMalloc((A->rmap->n-cnt)*sizeof(PetscInt),&rows);CHKERRQ(ierr); 121 cnt = 0; 122 for (i=0; i<m; i++) { 123 n = ii[i+1] - ii[i]; 124 if (!n) continue; 125 aa = a->a + ii[i]; 126 for (j=0; j<n; j++) { 127 if (aa[j] != 0.0) { 128 rows[cnt++] = i; 129 break; 130 } 131 } 132 } 133 ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,keptrows);CHKERRQ(ierr); 134 PetscFunctionReturn(0); 135 } 136 137 #undef __FUNCT__ 138 #define __FUNCT__ "MatDiagonalSet_SeqAIJ" 139 PetscErrorCode MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 140 { 141 PetscErrorCode ierr; 142 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 143 PetscInt i,*diag, m = Y->rmap->n; 144 MatScalar *aa = aij->a; 145 PetscScalar *v; 146 PetscBool missing; 147 148 PetscFunctionBegin; 149 if (Y->assembled) { 150 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); 151 if (!missing) { 152 diag = aij->diag; 153 ierr = VecGetArray(D,&v);CHKERRQ(ierr); 154 if (is == INSERT_VALUES) { 155 for (i=0; i<m; i++) { 156 aa[diag[i]] = v[i]; 157 } 158 } else { 159 for (i=0; i<m; i++) { 160 aa[diag[i]] += v[i]; 161 } 162 } 163 ierr = VecRestoreArray(D,&v);CHKERRQ(ierr); 164 PetscFunctionReturn(0); 165 } 166 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 167 } 168 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 169 PetscFunctionReturn(0); 170 } 171 172 #undef __FUNCT__ 173 #define __FUNCT__ "MatGetRowIJ_SeqAIJ" 174 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *m,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 175 { 176 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 177 PetscErrorCode ierr; 178 PetscInt i,ishift; 179 180 PetscFunctionBegin; 181 *m = A->rmap->n; 182 if (!ia) PetscFunctionReturn(0); 183 ishift = 0; 184 if (symmetric && !A->structurally_symmetric) { 185 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 186 } else if (oshift == 1) { 187 PetscInt *tia; 188 PetscInt nz = a->i[A->rmap->n]; 189 /* malloc space and add 1 to i and j indices */ 190 ierr = PetscMalloc((A->rmap->n+1)*sizeof(PetscInt),&tia);CHKERRQ(ierr); 191 for (i=0; i<A->rmap->n+1; i++) tia[i] = a->i[i] + 1; 192 *ia = tia; 193 if (ja) { 194 PetscInt *tja; 195 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&tja);CHKERRQ(ierr); 196 for (i=0; i<nz; i++) tja[i] = a->j[i] + 1; 197 *ja = tja; 198 } 199 } else { 200 *ia = a->i; 201 if (ja) *ja = a->j; 202 } 203 PetscFunctionReturn(0); 204 } 205 206 #undef __FUNCT__ 207 #define __FUNCT__ "MatRestoreRowIJ_SeqAIJ" 208 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 209 { 210 PetscErrorCode ierr; 211 212 PetscFunctionBegin; 213 if (!ia) PetscFunctionReturn(0); 214 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 215 ierr = PetscFree(*ia);CHKERRQ(ierr); 216 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 217 } 218 PetscFunctionReturn(0); 219 } 220 221 #undef __FUNCT__ 222 #define __FUNCT__ "MatGetColumnIJ_SeqAIJ" 223 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 224 { 225 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 226 PetscErrorCode ierr; 227 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 228 PetscInt nz = a->i[m],row,*jj,mr,col; 229 230 PetscFunctionBegin; 231 *nn = n; 232 if (!ia) PetscFunctionReturn(0); 233 if (symmetric) { 234 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 235 } else { 236 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&collengths);CHKERRQ(ierr); 237 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 238 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&cia);CHKERRQ(ierr); 239 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cja);CHKERRQ(ierr); 240 jj = a->j; 241 for (i=0; i<nz; i++) { 242 collengths[jj[i]]++; 243 } 244 cia[0] = oshift; 245 for (i=0; i<n; i++) { 246 cia[i+1] = cia[i] + collengths[i]; 247 } 248 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 249 jj = a->j; 250 for (row=0; row<m; row++) { 251 mr = a->i[row+1] - a->i[row]; 252 for (i=0; i<mr; i++) { 253 col = *jj++; 254 255 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 256 } 257 } 258 ierr = PetscFree(collengths);CHKERRQ(ierr); 259 *ia = cia; *ja = cja; 260 } 261 PetscFunctionReturn(0); 262 } 263 264 #undef __FUNCT__ 265 #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ" 266 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) 267 { 268 PetscErrorCode ierr; 269 270 PetscFunctionBegin; 271 if (!ia) PetscFunctionReturn(0); 272 273 ierr = PetscFree(*ia);CHKERRQ(ierr); 274 ierr = PetscFree(*ja);CHKERRQ(ierr); 275 PetscFunctionReturn(0); 276 } 277 278 /* 279 MatGetColumnIJ_SeqAIJ_Color() and MatRestoreColumnIJ_SeqAIJ_Color() are customized from 280 MatGetColumnIJ_SeqAIJ() and MatRestoreColumnIJ_SeqAIJ() by adding an output 281 spidx[], index of a->a, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqAIJ() 282 */ 283 #undef __FUNCT__ 284 #define __FUNCT__ "MatGetColumnIJ_SeqAIJ_Color" 285 PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 286 { 287 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 288 PetscErrorCode ierr; 289 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 290 PetscInt nz = a->i[m],row,*jj,mr,col; 291 PetscInt *cspidx; 292 293 PetscFunctionBegin; 294 *nn = n; 295 if (!ia) PetscFunctionReturn(0); 296 if (symmetric) { 297 SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"MatGetColumnIJ_SeqAIJ_Color() not supported for the case symmetric"); 298 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); 299 } else { 300 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&collengths);CHKERRQ(ierr); 301 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 302 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&cia);CHKERRQ(ierr); 303 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cja);CHKERRQ(ierr); 304 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cspidx);CHKERRQ(ierr); 305 jj = a->j; 306 for (i=0; i<nz; i++) { 307 collengths[jj[i]]++; 308 } 309 cia[0] = oshift; 310 for (i=0; i<n; i++) { 311 cia[i+1] = cia[i] + collengths[i]; 312 } 313 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 314 jj = a->j; 315 for (row=0; row<m; row++) { 316 mr = a->i[row+1] - a->i[row]; 317 for (i=0; i<mr; i++) { 318 col = *jj++; 319 320 cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */ 321 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 322 } 323 } 324 ierr = PetscFree(collengths);CHKERRQ(ierr); 325 *ia = cia; *ja = cja; 326 *spidx = cspidx; 327 } 328 PetscFunctionReturn(0); 329 } 330 331 #undef __FUNCT__ 332 #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ_Color" 333 PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) 334 { 335 PetscErrorCode ierr; 336 337 PetscFunctionBegin; 338 if (!ia) PetscFunctionReturn(0); 339 340 ierr = PetscFree(*ia);CHKERRQ(ierr); 341 ierr = PetscFree(*ja);CHKERRQ(ierr); 342 ierr = PetscFree(*spidx);CHKERRQ(ierr); 343 PetscFunctionReturn(0); 344 } 345 346 #undef __FUNCT__ 347 #define __FUNCT__ "MatSetValuesRow_SeqAIJ" 348 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 349 { 350 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 351 PetscInt *ai = a->i; 352 PetscErrorCode ierr; 353 354 PetscFunctionBegin; 355 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 356 PetscFunctionReturn(0); 357 } 358 359 #undef __FUNCT__ 360 #define __FUNCT__ "MatSetValues_SeqAIJ" 361 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 362 { 363 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 364 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 365 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 366 PetscErrorCode ierr; 367 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 368 MatScalar *ap,value,*aa = a->a; 369 PetscBool ignorezeroentries = a->ignorezeroentries; 370 PetscBool roworiented = a->roworiented; 371 372 PetscFunctionBegin; 373 if (v) PetscValidScalarPointer(v,6); 374 for (k=0; k<m; k++) { /* loop over added rows */ 375 row = im[k]; 376 if (row < 0) continue; 377 #if defined(PETSC_USE_DEBUG) 378 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 379 #endif 380 rp = aj + ai[row]; ap = aa + ai[row]; 381 rmax = imax[row]; nrow = ailen[row]; 382 low = 0; 383 high = nrow; 384 for (l=0; l<n; l++) { /* loop over added columns */ 385 if (in[l] < 0) continue; 386 #if defined(PETSC_USE_DEBUG) 387 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 388 #endif 389 col = in[l]; 390 if (v) { 391 if (roworiented) { 392 value = v[l + k*n]; 393 } else { 394 value = v[k + l*m]; 395 } 396 } else { 397 value = 0.; 398 } 399 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 400 401 if (col <= lastcol) low = 0; 402 else high = nrow; 403 lastcol = col; 404 while (high-low > 5) { 405 t = (low+high)/2; 406 if (rp[t] > col) high = t; 407 else low = t; 408 } 409 for (i=low; i<high; i++) { 410 if (rp[i] > col) break; 411 if (rp[i] == col) { 412 if (is == ADD_VALUES) ap[i] += value; 413 else ap[i] = value; 414 low = i + 1; 415 goto noinsert; 416 } 417 } 418 if (value == 0.0 && ignorezeroentries) goto noinsert; 419 if (nonew == 1) goto noinsert; 420 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 421 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 422 N = nrow++ - 1; a->nz++; high++; 423 /* shift up all the later entries in this row */ 424 for (ii=N; ii>=i; ii--) { 425 rp[ii+1] = rp[ii]; 426 ap[ii+1] = ap[ii]; 427 } 428 rp[i] = col; 429 ap[i] = value; 430 low = i + 1; 431 noinsert:; 432 } 433 ailen[row] = nrow; 434 } 435 A->same_nonzero = PETSC_FALSE; 436 PetscFunctionReturn(0); 437 } 438 439 440 #undef __FUNCT__ 441 #define __FUNCT__ "MatGetValues_SeqAIJ" 442 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 443 { 444 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 445 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 446 PetscInt *ai = a->i,*ailen = a->ilen; 447 MatScalar *ap,*aa = a->a; 448 449 PetscFunctionBegin; 450 for (k=0; k<m; k++) { /* loop over rows */ 451 row = im[k]; 452 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 453 if (row >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); 454 rp = aj + ai[row]; ap = aa + ai[row]; 455 nrow = ailen[row]; 456 for (l=0; l<n; l++) { /* loop over columns */ 457 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 458 if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1); 459 col = in[l]; 460 high = nrow; low = 0; /* assume unsorted */ 461 while (high-low > 5) { 462 t = (low+high)/2; 463 if (rp[t] > col) high = t; 464 else low = t; 465 } 466 for (i=low; i<high; i++) { 467 if (rp[i] > col) break; 468 if (rp[i] == col) { 469 *v++ = ap[i]; 470 goto finished; 471 } 472 } 473 *v++ = 0.0; 474 finished:; 475 } 476 } 477 PetscFunctionReturn(0); 478 } 479 480 481 #undef __FUNCT__ 482 #define __FUNCT__ "MatView_SeqAIJ_Binary" 483 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 484 { 485 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 486 PetscErrorCode ierr; 487 PetscInt i,*col_lens; 488 int fd; 489 FILE *file; 490 491 PetscFunctionBegin; 492 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 493 ierr = PetscMalloc((4+A->rmap->n)*sizeof(PetscInt),&col_lens);CHKERRQ(ierr); 494 495 col_lens[0] = MAT_FILE_CLASSID; 496 col_lens[1] = A->rmap->n; 497 col_lens[2] = A->cmap->n; 498 col_lens[3] = a->nz; 499 500 /* store lengths of each row and write (including header) to file */ 501 for (i=0; i<A->rmap->n; i++) { 502 col_lens[4+i] = a->i[i+1] - a->i[i]; 503 } 504 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 505 ierr = PetscFree(col_lens);CHKERRQ(ierr); 506 507 /* store column indices (zero start index) */ 508 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 509 510 /* store nonzero values */ 511 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 512 513 ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); 514 if (file) { 515 fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs); 516 } 517 PetscFunctionReturn(0); 518 } 519 520 extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 521 522 #undef __FUNCT__ 523 #define __FUNCT__ "MatView_SeqAIJ_ASCII" 524 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 525 { 526 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 527 PetscErrorCode ierr; 528 PetscInt i,j,m = A->rmap->n,shift=0; 529 const char *name; 530 PetscViewerFormat format; 531 532 PetscFunctionBegin; 533 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 534 if (format == PETSC_VIEWER_ASCII_MATLAB) { 535 PetscInt nofinalvalue = 0; 536 if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-!shift))) { 537 nofinalvalue = 1; 538 } 539 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 540 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 541 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 542 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 543 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 544 545 for (i=0; i<m; i++) { 546 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 547 #if defined(PETSC_USE_COMPLEX) 548 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e + %18.16ei \n",i+1,a->j[j]+!shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 549 #else 550 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+!shift,a->a[j]);CHKERRQ(ierr); 551 #endif 552 } 553 } 554 if (nofinalvalue) { 555 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 556 } 557 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 558 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 559 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 560 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 561 PetscFunctionReturn(0); 562 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 563 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 564 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 565 for (i=0; i<m; i++) { 566 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 567 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 568 #if defined(PETSC_USE_COMPLEX) 569 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 570 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 571 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 572 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 573 } else if (PetscRealPart(a->a[j]) != 0.0) { 574 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 575 } 576 #else 577 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr);} 578 #endif 579 } 580 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 581 } 582 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 583 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 584 PetscInt nzd=0,fshift=1,*sptr; 585 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 586 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 587 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&sptr);CHKERRQ(ierr); 588 for (i=0; i<m; i++) { 589 sptr[i] = nzd+1; 590 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 591 if (a->j[j] >= i) { 592 #if defined(PETSC_USE_COMPLEX) 593 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 594 #else 595 if (a->a[j] != 0.0) nzd++; 596 #endif 597 } 598 } 599 } 600 sptr[m] = nzd+1; 601 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 602 for (i=0; i<m+1; i+=6) { 603 if (i+4<m) { 604 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4],sptr[i+5]);CHKERRQ(ierr); 605 } else if (i+3<m) { 606 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3],sptr[i+4]);CHKERRQ(ierr); 607 } else if (i+2<m) { 608 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr); 609 } else if (i+1<m) { 610 ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr); 611 } else if (i<m) { 612 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr); 613 } else { 614 ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr); 615 } 616 } 617 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 618 ierr = PetscFree(sptr);CHKERRQ(ierr); 619 for (i=0; i<m; i++) { 620 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 621 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 622 } 623 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 624 } 625 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 626 for (i=0; i<m; i++) { 627 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 628 if (a->j[j] >= i) { 629 #if defined(PETSC_USE_COMPLEX) 630 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 631 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 632 } 633 #else 634 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",a->a[j]);CHKERRQ(ierr);} 635 #endif 636 } 637 } 638 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 639 } 640 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 641 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 642 PetscInt cnt = 0,jcnt; 643 PetscScalar value; 644 645 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 646 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 647 for (i=0; i<m; i++) { 648 jcnt = 0; 649 for (j=0; j<A->cmap->n; j++) { 650 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 651 value = a->a[cnt++]; 652 jcnt++; 653 } else { 654 value = 0.0; 655 } 656 #if defined(PETSC_USE_COMPLEX) 657 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",PetscRealPart(value),PetscImaginaryPart(value));CHKERRQ(ierr); 658 #else 659 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",value);CHKERRQ(ierr); 660 #endif 661 } 662 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 663 } 664 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 665 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 666 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 667 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 668 #if defined(PETSC_USE_COMPLEX) 669 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix complex general\n");CHKERRQ(ierr); 670 #else 671 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix real general\n");CHKERRQ(ierr); 672 #endif 673 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 674 for (i=0; i<m; i++) { 675 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 676 #if defined(PETSC_USE_COMPLEX) 677 if (PetscImaginaryPart(a->a[j]) > 0.0) { 678 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g %g\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 679 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 680 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g -%g\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 681 } else { 682 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 683 } 684 #else 685 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+shift, a->j[j]+shift, (double)a->a[j]);CHKERRQ(ierr); 686 #endif 687 } 688 } 689 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 690 } else { 691 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 692 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer);CHKERRQ(ierr); 693 if (A->factortype) { 694 for (i=0; i<m; i++) { 695 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 696 /* L part */ 697 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 698 #if defined(PETSC_USE_COMPLEX) 699 if (PetscImaginaryPart(a->a[j]) > 0.0) { 700 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 701 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 702 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 703 } else { 704 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 705 } 706 #else 707 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr); 708 #endif 709 } 710 /* diagonal */ 711 j = a->diag[i]; 712 #if defined(PETSC_USE_COMPLEX) 713 if (PetscImaginaryPart(a->a[j]) > 0.0) { 714 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(1.0/a->a[j]),PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 715 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 716 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(1.0/a->a[j]),-PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); 717 } else { 718 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); 719 } 720 #else 721 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)1.0/a->a[j]);CHKERRQ(ierr); 722 #endif 723 724 /* U part */ 725 for (j=a->diag[i+1]+1+shift; j<a->diag[i]+shift; j++) { 726 #if defined(PETSC_USE_COMPLEX) 727 if (PetscImaginaryPart(a->a[j]) > 0.0) { 728 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 729 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 730 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 731 } else { 732 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 733 } 734 #else 735 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr); 736 #endif 737 } 738 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 739 } 740 } else { 741 for (i=0; i<m; i++) { 742 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 743 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 744 #if defined(PETSC_USE_COMPLEX) 745 if (PetscImaginaryPart(a->a[j]) > 0.0) { 746 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 747 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 748 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 749 } else { 750 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 751 } 752 #else 753 ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j]+shift,(double)a->a[j]);CHKERRQ(ierr); 754 #endif 755 } 756 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 757 } 758 } 759 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 760 } 761 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 762 PetscFunctionReturn(0); 763 } 764 765 #include <petscdraw.h> 766 #undef __FUNCT__ 767 #define __FUNCT__ "MatView_SeqAIJ_Draw_Zoom" 768 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 769 { 770 Mat A = (Mat) Aa; 771 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 772 PetscErrorCode ierr; 773 PetscInt i,j,m = A->rmap->n,color; 774 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r,maxv = 0.0; 775 PetscViewer viewer; 776 PetscViewerFormat format; 777 778 PetscFunctionBegin; 779 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 780 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 781 782 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 783 /* loop over matrix elements drawing boxes */ 784 785 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 786 /* Blue for negative, Cyan for zero and Red for positive */ 787 color = PETSC_DRAW_BLUE; 788 for (i=0; i<m; i++) { 789 y_l = m - i - 1.0; y_r = y_l + 1.0; 790 for (j=a->i[i]; j<a->i[i+1]; j++) { 791 x_l = a->j[j]; x_r = x_l + 1.0; 792 if (PetscRealPart(a->a[j]) >= 0.) continue; 793 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 794 } 795 } 796 color = PETSC_DRAW_CYAN; 797 for (i=0; i<m; i++) { 798 y_l = m - i - 1.0; y_r = y_l + 1.0; 799 for (j=a->i[i]; j<a->i[i+1]; j++) { 800 x_l = a->j[j]; x_r = x_l + 1.0; 801 if (a->a[j] != 0.) continue; 802 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 803 } 804 } 805 color = PETSC_DRAW_RED; 806 for (i=0; i<m; i++) { 807 y_l = m - i - 1.0; y_r = y_l + 1.0; 808 for (j=a->i[i]; j<a->i[i+1]; j++) { 809 x_l = a->j[j]; x_r = x_l + 1.0; 810 if (PetscRealPart(a->a[j]) <= 0.) continue; 811 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 812 } 813 } 814 } else { 815 /* use contour shading to indicate magnitude of values */ 816 /* first determine max of all nonzero values */ 817 PetscInt nz = a->nz,count; 818 PetscDraw popup; 819 PetscReal scale; 820 821 for (i=0; i<nz; i++) { 822 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 823 } 824 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 825 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 826 if (popup) { 827 ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); 828 } 829 count = 0; 830 for (i=0; i<m; i++) { 831 y_l = m - i - 1.0; y_r = y_l + 1.0; 832 for (j=a->i[i]; j<a->i[i+1]; j++) { 833 x_l = a->j[j]; x_r = x_l + 1.0; 834 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(a->a[count])); 835 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 836 count++; 837 } 838 } 839 } 840 PetscFunctionReturn(0); 841 } 842 843 #include <petscdraw.h> 844 #undef __FUNCT__ 845 #define __FUNCT__ "MatView_SeqAIJ_Draw" 846 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 847 { 848 PetscErrorCode ierr; 849 PetscDraw draw; 850 PetscReal xr,yr,xl,yl,h,w; 851 PetscBool isnull; 852 853 PetscFunctionBegin; 854 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 855 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 856 if (isnull) PetscFunctionReturn(0); 857 858 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 859 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 860 xr += w; yr += h; xl = -w; yl = -h; 861 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 862 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 863 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); 864 PetscFunctionReturn(0); 865 } 866 867 #undef __FUNCT__ 868 #define __FUNCT__ "MatView_SeqAIJ" 869 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 870 { 871 PetscErrorCode ierr; 872 PetscBool iascii,isbinary,isdraw; 873 874 PetscFunctionBegin; 875 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 876 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 877 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 878 if (iascii) { 879 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 880 } else if (isbinary) { 881 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 882 } else if (isdraw) { 883 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 884 } 885 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 886 PetscFunctionReturn(0); 887 } 888 889 #undef __FUNCT__ 890 #define __FUNCT__ "MatAssemblyEnd_SeqAIJ" 891 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 892 { 893 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 894 PetscErrorCode ierr; 895 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 896 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 897 MatScalar *aa = a->a,*ap; 898 PetscReal ratio = 0.6; 899 900 PetscFunctionBegin; 901 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 902 903 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 904 for (i=1; i<m; i++) { 905 /* move each row back by the amount of empty slots (fshift) before it*/ 906 fshift += imax[i-1] - ailen[i-1]; 907 rmax = PetscMax(rmax,ailen[i]); 908 if (fshift) { 909 ip = aj + ai[i]; 910 ap = aa + ai[i]; 911 N = ailen[i]; 912 for (j=0; j<N; j++) { 913 ip[j-fshift] = ip[j]; 914 ap[j-fshift] = ap[j]; 915 } 916 } 917 ai[i] = ai[i-1] + ailen[i-1]; 918 } 919 if (m) { 920 fshift += imax[m-1] - ailen[m-1]; 921 ai[m] = ai[m-1] + ailen[m-1]; 922 } 923 /* reset ilen and imax for each row */ 924 for (i=0; i<m; i++) { 925 ailen[i] = imax[i] = ai[i+1] - ai[i]; 926 } 927 a->nz = ai[m]; 928 if (fshift && a->nounused == -1) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D, %D unneeded", m, A->cmap->n, fshift); 929 930 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 931 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 932 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 933 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 934 935 A->info.mallocs += a->reallocs; 936 a->reallocs = 0; 937 A->info.nz_unneeded = (double)fshift; 938 a->rmax = rmax; 939 940 ierr = MatCheckCompressedRow(A,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 941 942 A->same_nonzero = PETSC_TRUE; 943 944 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 945 946 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 947 PetscFunctionReturn(0); 948 } 949 950 #undef __FUNCT__ 951 #define __FUNCT__ "MatRealPart_SeqAIJ" 952 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 953 { 954 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 955 PetscInt i,nz = a->nz; 956 MatScalar *aa = a->a; 957 PetscErrorCode ierr; 958 959 PetscFunctionBegin; 960 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 961 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 962 PetscFunctionReturn(0); 963 } 964 965 #undef __FUNCT__ 966 #define __FUNCT__ "MatImaginaryPart_SeqAIJ" 967 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 968 { 969 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 970 PetscInt i,nz = a->nz; 971 MatScalar *aa = a->a; 972 PetscErrorCode ierr; 973 974 PetscFunctionBegin; 975 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 976 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 977 PetscFunctionReturn(0); 978 } 979 980 #if defined(PETSC_THREADCOMM_ACTIVE) 981 PetscErrorCode MatZeroEntries_SeqAIJ_Kernel(PetscInt thread_id,Mat A) 982 { 983 PetscErrorCode ierr; 984 PetscInt *trstarts=A->rmap->trstarts; 985 PetscInt n,start,end; 986 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 987 988 start = trstarts[thread_id]; 989 end = trstarts[thread_id+1]; 990 n = a->i[end] - a->i[start]; 991 ierr = PetscMemzero(a->a+a->i[start],n*sizeof(PetscScalar));CHKERRQ(ierr); 992 return 0; 993 } 994 995 #undef __FUNCT__ 996 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 997 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 998 { 999 PetscErrorCode ierr; 1000 1001 PetscFunctionBegin; 1002 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatZeroEntries_SeqAIJ_Kernel,1,A);CHKERRQ(ierr); 1003 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1004 PetscFunctionReturn(0); 1005 } 1006 #else 1007 #undef __FUNCT__ 1008 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 1009 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 1010 { 1011 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1012 PetscErrorCode ierr; 1013 1014 PetscFunctionBegin; 1015 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 1016 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 1017 PetscFunctionReturn(0); 1018 } 1019 #endif 1020 1021 #undef __FUNCT__ 1022 #define __FUNCT__ "MatDestroy_SeqAIJ" 1023 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 1024 { 1025 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1026 PetscErrorCode ierr; 1027 1028 PetscFunctionBegin; 1029 #if defined(PETSC_USE_LOG) 1030 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 1031 #endif 1032 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 1033 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 1034 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 1035 ierr = PetscFree(a->diag);CHKERRQ(ierr); 1036 ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); 1037 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 1038 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 1039 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 1040 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 1041 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 1042 ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); 1043 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 1044 ierr = MatDestroy(&a->XtoY);CHKERRQ(ierr); 1045 ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); 1046 ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); 1047 1048 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 1049 ierr = PetscFree(A->data);CHKERRQ(ierr); 1050 1051 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 1052 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); 1053 ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); 1054 ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); 1055 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); 1056 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); 1057 ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); 1058 ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); 1059 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); 1060 ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); 1061 ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); 1062 PetscFunctionReturn(0); 1063 } 1064 1065 #undef __FUNCT__ 1066 #define __FUNCT__ "MatSetOption_SeqAIJ" 1067 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) 1068 { 1069 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1070 PetscErrorCode ierr; 1071 1072 PetscFunctionBegin; 1073 switch (op) { 1074 case MAT_ROW_ORIENTED: 1075 a->roworiented = flg; 1076 break; 1077 case MAT_KEEP_NONZERO_PATTERN: 1078 a->keepnonzeropattern = flg; 1079 break; 1080 case MAT_NEW_NONZERO_LOCATIONS: 1081 a->nonew = (flg ? 0 : 1); 1082 break; 1083 case MAT_NEW_NONZERO_LOCATION_ERR: 1084 a->nonew = (flg ? -1 : 0); 1085 break; 1086 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1087 a->nonew = (flg ? -2 : 0); 1088 break; 1089 case MAT_UNUSED_NONZERO_LOCATION_ERR: 1090 a->nounused = (flg ? -1 : 0); 1091 break; 1092 case MAT_IGNORE_ZERO_ENTRIES: 1093 a->ignorezeroentries = flg; 1094 break; 1095 case MAT_CHECK_COMPRESSED_ROW: 1096 a->compressedrow.check = flg; 1097 break; 1098 case MAT_SPD: 1099 case MAT_SYMMETRIC: 1100 case MAT_STRUCTURALLY_SYMMETRIC: 1101 case MAT_HERMITIAN: 1102 case MAT_SYMMETRY_ETERNAL: 1103 /* These options are handled directly by MatSetOption() */ 1104 break; 1105 case MAT_NEW_DIAGONALS: 1106 case MAT_IGNORE_OFF_PROC_ENTRIES: 1107 case MAT_USE_HASH_TABLE: 1108 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1109 break; 1110 case MAT_USE_INODES: 1111 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 1112 break; 1113 default: 1114 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 1115 } 1116 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 1117 PetscFunctionReturn(0); 1118 } 1119 1120 #undef __FUNCT__ 1121 #define __FUNCT__ "MatGetDiagonal_SeqAIJ" 1122 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 1123 { 1124 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1125 PetscErrorCode ierr; 1126 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 1127 PetscScalar *aa=a->a,*x,zero=0.0; 1128 1129 PetscFunctionBegin; 1130 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 1131 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1132 1133 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { 1134 PetscInt *diag=a->diag; 1135 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1136 for (i=0; i<n; i++) x[i] = 1.0/aa[diag[i]]; 1137 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1138 PetscFunctionReturn(0); 1139 } 1140 1141 ierr = VecSet(v,zero);CHKERRQ(ierr); 1142 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1143 for (i=0; i<n; i++) { 1144 nz = ai[i+1] - ai[i]; 1145 if (!nz) x[i] = 0.0; 1146 for (j=ai[i]; j<ai[i+1]; j++) { 1147 if (aj[j] == i) { 1148 x[i] = aa[j]; 1149 break; 1150 } 1151 } 1152 } 1153 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1154 PetscFunctionReturn(0); 1155 } 1156 1157 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1158 #undef __FUNCT__ 1159 #define __FUNCT__ "MatMultTransposeAdd_SeqAIJ" 1160 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 1161 { 1162 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1163 PetscScalar *x,*y; 1164 PetscErrorCode ierr; 1165 PetscInt m = A->rmap->n; 1166 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1167 MatScalar *v; 1168 PetscScalar alpha; 1169 PetscInt n,i,j,*idx,*ii,*ridx=NULL; 1170 Mat_CompressedRow cprow = a->compressedrow; 1171 PetscBool usecprow = cprow.use; 1172 #endif 1173 1174 PetscFunctionBegin; 1175 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 1176 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1177 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1178 1179 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 1180 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 1181 #else 1182 if (usecprow) { 1183 m = cprow.nrows; 1184 ii = cprow.i; 1185 ridx = cprow.rindex; 1186 } else { 1187 ii = a->i; 1188 } 1189 for (i=0; i<m; i++) { 1190 idx = a->j + ii[i]; 1191 v = a->a + ii[i]; 1192 n = ii[i+1] - ii[i]; 1193 if (usecprow) { 1194 alpha = x[ridx[i]]; 1195 } else { 1196 alpha = x[i]; 1197 } 1198 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 1199 } 1200 #endif 1201 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1202 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1203 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1204 PetscFunctionReturn(0); 1205 } 1206 1207 #undef __FUNCT__ 1208 #define __FUNCT__ "MatMultTranspose_SeqAIJ" 1209 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 1210 { 1211 PetscErrorCode ierr; 1212 1213 PetscFunctionBegin; 1214 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 1215 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 1216 PetscFunctionReturn(0); 1217 } 1218 1219 #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> 1220 #if defined(PETSC_THREADCOMM_ACTIVE) 1221 PetscErrorCode MatMult_SeqAIJ_Kernel(PetscInt thread_id,Mat A,Vec xx,Vec yy) 1222 { 1223 PetscErrorCode ierr; 1224 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1225 PetscScalar *y; 1226 const PetscScalar *x; 1227 const MatScalar *aa; 1228 PetscInt *trstarts=A->rmap->trstarts; 1229 PetscInt n,start,end,i; 1230 const PetscInt *aj,*ai; 1231 PetscScalar sum; 1232 1233 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1234 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1235 start = trstarts[thread_id]; 1236 end = trstarts[thread_id+1]; 1237 aj = a->j; 1238 aa = a->a; 1239 ai = a->i; 1240 for (i=start; i<end; i++) { 1241 n = ai[i+1] - ai[i]; 1242 aj = a->j + ai[i]; 1243 aa = a->a + ai[i]; 1244 sum = 0.0; 1245 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1246 y[i] = sum; 1247 } 1248 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1249 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1250 return 0; 1251 } 1252 1253 #undef __FUNCT__ 1254 #define __FUNCT__ "MatMult_SeqAIJ" 1255 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1256 { 1257 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1258 PetscScalar *y; 1259 const PetscScalar *x; 1260 const MatScalar *aa; 1261 PetscErrorCode ierr; 1262 PetscInt m=A->rmap->n; 1263 const PetscInt *aj,*ii,*ridx=NULL; 1264 PetscInt n,i,nonzerorow=0; 1265 PetscScalar sum; 1266 PetscBool usecprow=a->compressedrow.use; 1267 1268 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1269 #pragma disjoint(*x,*y,*aa) 1270 #endif 1271 1272 PetscFunctionBegin; 1273 aj = a->j; 1274 aa = a->a; 1275 ii = a->i; 1276 if (usecprow) { /* use compressed row format */ 1277 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1278 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1279 m = a->compressedrow.nrows; 1280 ii = a->compressedrow.i; 1281 ridx = a->compressedrow.rindex; 1282 for (i=0; i<m; i++) { 1283 n = ii[i+1] - ii[i]; 1284 aj = a->j + ii[i]; 1285 aa = a->a + ii[i]; 1286 sum = 0.0; 1287 nonzerorow += (n>0); 1288 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1289 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1290 y[*ridx++] = sum; 1291 } 1292 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1293 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1294 } else { /* do not use compressed row format */ 1295 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1296 fortranmultaij_(&m,x,ii,aj,aa,y); 1297 #else 1298 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatMult_SeqAIJ_Kernel,3,A,xx,yy);CHKERRQ(ierr); 1299 #endif 1300 } 1301 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1302 PetscFunctionReturn(0); 1303 } 1304 #else 1305 #undef __FUNCT__ 1306 #define __FUNCT__ "MatMult_SeqAIJ" 1307 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 1308 { 1309 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1310 PetscScalar *y; 1311 const PetscScalar *x; 1312 const MatScalar *aa; 1313 PetscErrorCode ierr; 1314 PetscInt m=A->rmap->n; 1315 const PetscInt *aj,*ii,*ridx=NULL; 1316 PetscInt n,i,nonzerorow=0; 1317 PetscScalar sum; 1318 PetscBool usecprow=a->compressedrow.use; 1319 1320 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1321 #pragma disjoint(*x,*y,*aa) 1322 #endif 1323 1324 PetscFunctionBegin; 1325 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1326 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1327 aj = a->j; 1328 aa = a->a; 1329 ii = a->i; 1330 if (usecprow) { /* use compressed row format */ 1331 m = a->compressedrow.nrows; 1332 ii = a->compressedrow.i; 1333 ridx = a->compressedrow.rindex; 1334 for (i=0; i<m; i++) { 1335 n = ii[i+1] - ii[i]; 1336 aj = a->j + ii[i]; 1337 aa = a->a + ii[i]; 1338 sum = 0.0; 1339 nonzerorow += (n>0); 1340 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1341 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1342 y[*ridx++] = sum; 1343 } 1344 } else { /* do not use compressed row format */ 1345 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1346 fortranmultaij_(&m,x,ii,aj,aa,y); 1347 #else 1348 #if defined(PETSC_THREADCOMM_ACTIVE) 1349 ierr = PetscThreadCommRunKernel(PetscObjectComm((PetscObject)A),(PetscThreadKernel)MatMult_SeqAIJ_Kernel,3,A,xx,yy);CHKERRQ(ierr); 1350 #else 1351 for (i=0; i<m; i++) { 1352 n = ii[i+1] - ii[i]; 1353 aj = a->j + ii[i]; 1354 aa = a->a + ii[i]; 1355 sum = 0.0; 1356 nonzerorow += (n>0); 1357 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1358 y[i] = sum; 1359 } 1360 #endif 1361 #endif 1362 } 1363 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1364 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1365 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1366 PetscFunctionReturn(0); 1367 } 1368 #endif 1369 1370 #undef __FUNCT__ 1371 #define __FUNCT__ "MatMultMax_SeqAIJ" 1372 PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) 1373 { 1374 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1375 PetscScalar *y; 1376 const PetscScalar *x; 1377 const MatScalar *aa; 1378 PetscErrorCode ierr; 1379 PetscInt m=A->rmap->n; 1380 const PetscInt *aj,*ii,*ridx=NULL; 1381 PetscInt n,i,nonzerorow=0; 1382 PetscScalar sum; 1383 PetscBool usecprow=a->compressedrow.use; 1384 1385 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1386 #pragma disjoint(*x,*y,*aa) 1387 #endif 1388 1389 PetscFunctionBegin; 1390 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1391 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1392 aj = a->j; 1393 aa = a->a; 1394 ii = a->i; 1395 if (usecprow) { /* use compressed row format */ 1396 m = a->compressedrow.nrows; 1397 ii = a->compressedrow.i; 1398 ridx = a->compressedrow.rindex; 1399 for (i=0; i<m; i++) { 1400 n = ii[i+1] - ii[i]; 1401 aj = a->j + ii[i]; 1402 aa = a->a + ii[i]; 1403 sum = 0.0; 1404 nonzerorow += (n>0); 1405 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1406 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1407 y[*ridx++] = sum; 1408 } 1409 } else { /* do not use compressed row format */ 1410 for (i=0; i<m; i++) { 1411 n = ii[i+1] - ii[i]; 1412 aj = a->j + ii[i]; 1413 aa = a->a + ii[i]; 1414 sum = 0.0; 1415 nonzerorow += (n>0); 1416 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1417 y[i] = sum; 1418 } 1419 } 1420 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1421 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1422 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1423 PetscFunctionReturn(0); 1424 } 1425 1426 #undef __FUNCT__ 1427 #define __FUNCT__ "MatMultAddMax_SeqAIJ" 1428 PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1429 { 1430 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1431 PetscScalar *y,*z; 1432 const PetscScalar *x; 1433 const MatScalar *aa; 1434 PetscErrorCode ierr; 1435 PetscInt m = A->rmap->n,*aj,*ii; 1436 PetscInt n,i,*ridx=NULL; 1437 PetscScalar sum; 1438 PetscBool usecprow=a->compressedrow.use; 1439 1440 PetscFunctionBegin; 1441 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1442 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1443 if (zz != yy) { 1444 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 1445 } else { 1446 z = y; 1447 } 1448 1449 aj = a->j; 1450 aa = a->a; 1451 ii = a->i; 1452 if (usecprow) { /* use compressed row format */ 1453 if (zz != yy) { 1454 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1455 } 1456 m = a->compressedrow.nrows; 1457 ii = a->compressedrow.i; 1458 ridx = a->compressedrow.rindex; 1459 for (i=0; i<m; i++) { 1460 n = ii[i+1] - ii[i]; 1461 aj = a->j + ii[i]; 1462 aa = a->a + ii[i]; 1463 sum = y[*ridx]; 1464 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1465 z[*ridx++] = sum; 1466 } 1467 } else { /* do not use compressed row format */ 1468 for (i=0; i<m; i++) { 1469 n = ii[i+1] - ii[i]; 1470 aj = a->j + ii[i]; 1471 aa = a->a + ii[i]; 1472 sum = y[i]; 1473 PetscSparseDenseMaxDot(sum,x,aa,aj,n); 1474 z[i] = sum; 1475 } 1476 } 1477 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1478 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1479 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1480 if (zz != yy) { 1481 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 1482 } 1483 PetscFunctionReturn(0); 1484 } 1485 1486 #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> 1487 #undef __FUNCT__ 1488 #define __FUNCT__ "MatMultAdd_SeqAIJ" 1489 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1490 { 1491 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1492 PetscScalar *y,*z; 1493 const PetscScalar *x; 1494 const MatScalar *aa; 1495 PetscErrorCode ierr; 1496 PetscInt m = A->rmap->n,*aj,*ii; 1497 PetscInt n,i,*ridx=NULL; 1498 PetscScalar sum; 1499 PetscBool usecprow=a->compressedrow.use; 1500 1501 PetscFunctionBegin; 1502 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1503 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1504 if (zz != yy) { 1505 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 1506 } else { 1507 z = y; 1508 } 1509 1510 aj = a->j; 1511 aa = a->a; 1512 ii = a->i; 1513 if (usecprow) { /* use compressed row format */ 1514 if (zz != yy) { 1515 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1516 } 1517 m = a->compressedrow.nrows; 1518 ii = a->compressedrow.i; 1519 ridx = a->compressedrow.rindex; 1520 for (i=0; i<m; i++) { 1521 n = ii[i+1] - ii[i]; 1522 aj = a->j + ii[i]; 1523 aa = a->a + ii[i]; 1524 sum = y[*ridx]; 1525 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1526 z[*ridx++] = sum; 1527 } 1528 } else { /* do not use compressed row format */ 1529 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1530 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1531 #else 1532 for (i=0; i<m; i++) { 1533 n = ii[i+1] - ii[i]; 1534 aj = a->j + ii[i]; 1535 aa = a->a + ii[i]; 1536 sum = y[i]; 1537 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1538 z[i] = sum; 1539 } 1540 #endif 1541 } 1542 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1543 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1544 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1545 if (zz != yy) { 1546 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 1547 } 1548 #if defined(PETSC_HAVE_CUSP) 1549 /* 1550 ierr = VecView(xx,0);CHKERRQ(ierr); 1551 ierr = VecView(zz,0);CHKERRQ(ierr); 1552 ierr = MatView(A,0);CHKERRQ(ierr); 1553 */ 1554 #endif 1555 PetscFunctionReturn(0); 1556 } 1557 1558 /* 1559 Adds diagonal pointers to sparse matrix structure. 1560 */ 1561 #undef __FUNCT__ 1562 #define __FUNCT__ "MatMarkDiagonal_SeqAIJ" 1563 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1564 { 1565 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1566 PetscErrorCode ierr; 1567 PetscInt i,j,m = A->rmap->n; 1568 1569 PetscFunctionBegin; 1570 if (!a->diag) { 1571 ierr = PetscMalloc(m*sizeof(PetscInt),&a->diag);CHKERRQ(ierr); 1572 ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); 1573 } 1574 for (i=0; i<A->rmap->n; i++) { 1575 a->diag[i] = a->i[i+1]; 1576 for (j=a->i[i]; j<a->i[i+1]; j++) { 1577 if (a->j[j] == i) { 1578 a->diag[i] = j; 1579 break; 1580 } 1581 } 1582 } 1583 PetscFunctionReturn(0); 1584 } 1585 1586 /* 1587 Checks for missing diagonals 1588 */ 1589 #undef __FUNCT__ 1590 #define __FUNCT__ "MatMissingDiagonal_SeqAIJ" 1591 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) 1592 { 1593 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1594 PetscInt *diag,*jj = a->j,i; 1595 1596 PetscFunctionBegin; 1597 *missing = PETSC_FALSE; 1598 if (A->rmap->n > 0 && !jj) { 1599 *missing = PETSC_TRUE; 1600 if (d) *d = 0; 1601 PetscInfo(A,"Matrix has no entries therefore is missing diagonal"); 1602 } else { 1603 diag = a->diag; 1604 for (i=0; i<A->rmap->n; i++) { 1605 if (jj[diag[i]] != i) { 1606 *missing = PETSC_TRUE; 1607 if (d) *d = i; 1608 PetscInfo1(A,"Matrix is missing diagonal number %D",i); 1609 break; 1610 } 1611 } 1612 } 1613 PetscFunctionReturn(0); 1614 } 1615 1616 #undef __FUNCT__ 1617 #define __FUNCT__ "MatInvertDiagonal_SeqAIJ" 1618 PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1619 { 1620 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1621 PetscErrorCode ierr; 1622 PetscInt i,*diag,m = A->rmap->n; 1623 MatScalar *v = a->a; 1624 PetscScalar *idiag,*mdiag; 1625 1626 PetscFunctionBegin; 1627 if (a->idiagvalid) PetscFunctionReturn(0); 1628 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1629 diag = a->diag; 1630 if (!a->idiag) { 1631 ierr = PetscMalloc3(m,PetscScalar,&a->idiag,m,PetscScalar,&a->mdiag,m,PetscScalar,&a->ssor_work);CHKERRQ(ierr); 1632 ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1633 v = a->a; 1634 } 1635 mdiag = a->mdiag; 1636 idiag = a->idiag; 1637 1638 if (omega == 1.0 && !PetscAbsScalar(fshift)) { 1639 for (i=0; i<m; i++) { 1640 mdiag[i] = v[diag[i]]; 1641 if (!PetscAbsScalar(mdiag[i])) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1642 idiag[i] = 1.0/v[diag[i]]; 1643 } 1644 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1645 } else { 1646 for (i=0; i<m; i++) { 1647 mdiag[i] = v[diag[i]]; 1648 idiag[i] = omega/(fshift + v[diag[i]]); 1649 } 1650 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1651 } 1652 a->idiagvalid = PETSC_TRUE; 1653 PetscFunctionReturn(0); 1654 } 1655 1656 #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> 1657 #undef __FUNCT__ 1658 #define __FUNCT__ "MatSOR_SeqAIJ" 1659 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1660 { 1661 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1662 PetscScalar *x,d,sum,*t,scale; 1663 const MatScalar *v = a->a,*idiag=0,*mdiag; 1664 const PetscScalar *b, *bs,*xb, *ts; 1665 PetscErrorCode ierr; 1666 PetscInt n = A->cmap->n,m = A->rmap->n,i; 1667 const PetscInt *idx,*diag; 1668 1669 PetscFunctionBegin; 1670 its = its*lits; 1671 1672 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1673 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1674 a->fshift = fshift; 1675 a->omega = omega; 1676 1677 diag = a->diag; 1678 t = a->ssor_work; 1679 idiag = a->idiag; 1680 mdiag = a->mdiag; 1681 1682 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1683 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1684 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1685 if (flag == SOR_APPLY_UPPER) { 1686 /* apply (U + D/omega) to the vector */ 1687 bs = b; 1688 for (i=0; i<m; i++) { 1689 d = fshift + mdiag[i]; 1690 n = a->i[i+1] - diag[i] - 1; 1691 idx = a->j + diag[i] + 1; 1692 v = a->a + diag[i] + 1; 1693 sum = b[i]*d/omega; 1694 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1695 x[i] = sum; 1696 } 1697 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1698 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1699 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1700 PetscFunctionReturn(0); 1701 } 1702 1703 if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1704 else if (flag & SOR_EISENSTAT) { 1705 /* Let A = L + U + D; where L is lower trianglar, 1706 U is upper triangular, E = D/omega; This routine applies 1707 1708 (L + E)^{-1} A (U + E)^{-1} 1709 1710 to a vector efficiently using Eisenstat's trick. 1711 */ 1712 scale = (2.0/omega) - 1.0; 1713 1714 /* x = (E + U)^{-1} b */ 1715 for (i=m-1; i>=0; i--) { 1716 n = a->i[i+1] - diag[i] - 1; 1717 idx = a->j + diag[i] + 1; 1718 v = a->a + diag[i] + 1; 1719 sum = b[i]; 1720 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1721 x[i] = sum*idiag[i]; 1722 } 1723 1724 /* t = b - (2*E - D)x */ 1725 v = a->a; 1726 for (i=0; i<m; i++) t[i] = b[i] - scale*(v[*diag++])*x[i]; 1727 1728 /* t = (E + L)^{-1}t */ 1729 ts = t; 1730 diag = a->diag; 1731 for (i=0; i<m; i++) { 1732 n = diag[i] - a->i[i]; 1733 idx = a->j + a->i[i]; 1734 v = a->a + a->i[i]; 1735 sum = t[i]; 1736 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1737 t[i] = sum*idiag[i]; 1738 /* x = x + t */ 1739 x[i] += t[i]; 1740 } 1741 1742 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1743 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1744 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1745 PetscFunctionReturn(0); 1746 } 1747 if (flag & SOR_ZERO_INITIAL_GUESS) { 1748 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1749 for (i=0; i<m; i++) { 1750 n = diag[i] - a->i[i]; 1751 idx = a->j + a->i[i]; 1752 v = a->a + a->i[i]; 1753 sum = b[i]; 1754 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1755 t[i] = sum; 1756 x[i] = sum*idiag[i]; 1757 } 1758 xb = t; 1759 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1760 } else xb = b; 1761 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1762 for (i=m-1; i>=0; i--) { 1763 n = a->i[i+1] - diag[i] - 1; 1764 idx = a->j + diag[i] + 1; 1765 v = a->a + diag[i] + 1; 1766 sum = xb[i]; 1767 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1768 if (xb == b) { 1769 x[i] = sum*idiag[i]; 1770 } else { 1771 x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1772 } 1773 } 1774 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1775 } 1776 its--; 1777 } 1778 while (its--) { 1779 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { 1780 for (i=0; i<m; i++) { 1781 /* lower */ 1782 n = diag[i] - a->i[i]; 1783 idx = a->j + a->i[i]; 1784 v = a->a + a->i[i]; 1785 sum = b[i]; 1786 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1787 t[i] = sum; /* save application of the lower-triangular part */ 1788 /* upper */ 1789 n = a->i[i+1] - diag[i] - 1; 1790 idx = a->j + diag[i] + 1; 1791 v = a->a + diag[i] + 1; 1792 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1793 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1794 } 1795 xb = t; 1796 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1797 } else xb = b; 1798 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { 1799 for (i=m-1; i>=0; i--) { 1800 sum = xb[i]; 1801 if (xb == b) { 1802 /* whole matrix (no checkpointing available) */ 1803 n = a->i[i+1] - a->i[i]; 1804 idx = a->j + a->i[i]; 1805 v = a->a + a->i[i]; 1806 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1807 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1808 } else { /* lower-triangular part has been saved, so only apply upper-triangular */ 1809 n = a->i[i+1] - diag[i] - 1; 1810 idx = a->j + diag[i] + 1; 1811 v = a->a + diag[i] + 1; 1812 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1813 x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ 1814 } 1815 } 1816 if (xb == b) { 1817 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1818 } else { 1819 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ 1820 } 1821 } 1822 } 1823 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1824 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1825 PetscFunctionReturn(0); 1826 } 1827 1828 1829 #undef __FUNCT__ 1830 #define __FUNCT__ "MatGetInfo_SeqAIJ" 1831 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1832 { 1833 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1834 1835 PetscFunctionBegin; 1836 info->block_size = 1.0; 1837 info->nz_allocated = (double)a->maxnz; 1838 info->nz_used = (double)a->nz; 1839 info->nz_unneeded = (double)(a->maxnz - a->nz); 1840 info->assemblies = (double)A->num_ass; 1841 info->mallocs = (double)A->info.mallocs; 1842 info->memory = ((PetscObject)A)->mem; 1843 if (A->factortype) { 1844 info->fill_ratio_given = A->info.fill_ratio_given; 1845 info->fill_ratio_needed = A->info.fill_ratio_needed; 1846 info->factor_mallocs = A->info.factor_mallocs; 1847 } else { 1848 info->fill_ratio_given = 0; 1849 info->fill_ratio_needed = 0; 1850 info->factor_mallocs = 0; 1851 } 1852 PetscFunctionReturn(0); 1853 } 1854 1855 #undef __FUNCT__ 1856 #define __FUNCT__ "MatZeroRows_SeqAIJ" 1857 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1858 { 1859 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1860 PetscInt i,m = A->rmap->n - 1,d = 0; 1861 PetscErrorCode ierr; 1862 const PetscScalar *xx; 1863 PetscScalar *bb; 1864 PetscBool missing; 1865 1866 PetscFunctionBegin; 1867 if (x && b) { 1868 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1869 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1870 for (i=0; i<N; i++) { 1871 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1872 bb[rows[i]] = diag*xx[rows[i]]; 1873 } 1874 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1875 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1876 } 1877 1878 if (a->keepnonzeropattern) { 1879 for (i=0; i<N; i++) { 1880 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1881 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1882 } 1883 if (diag != 0.0) { 1884 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1885 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1886 for (i=0; i<N; i++) { 1887 a->a[a->diag[rows[i]]] = diag; 1888 } 1889 } 1890 A->same_nonzero = PETSC_TRUE; 1891 } else { 1892 if (diag != 0.0) { 1893 for (i=0; i<N; i++) { 1894 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1895 if (a->ilen[rows[i]] > 0) { 1896 a->ilen[rows[i]] = 1; 1897 a->a[a->i[rows[i]]] = diag; 1898 a->j[a->i[rows[i]]] = rows[i]; 1899 } else { /* in case row was completely empty */ 1900 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1901 } 1902 } 1903 } else { 1904 for (i=0; i<N; i++) { 1905 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1906 a->ilen[rows[i]] = 0; 1907 } 1908 } 1909 A->same_nonzero = PETSC_FALSE; 1910 } 1911 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1912 PetscFunctionReturn(0); 1913 } 1914 1915 #undef __FUNCT__ 1916 #define __FUNCT__ "MatZeroRowsColumns_SeqAIJ" 1917 PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1918 { 1919 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1920 PetscInt i,j,m = A->rmap->n - 1,d = 0; 1921 PetscErrorCode ierr; 1922 PetscBool missing,*zeroed,vecs = PETSC_FALSE; 1923 const PetscScalar *xx; 1924 PetscScalar *bb; 1925 1926 PetscFunctionBegin; 1927 if (x && b) { 1928 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1929 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1930 vecs = PETSC_TRUE; 1931 } 1932 ierr = PetscMalloc(A->rmap->n*sizeof(PetscBool),&zeroed);CHKERRQ(ierr); 1933 ierr = PetscMemzero(zeroed,A->rmap->n*sizeof(PetscBool));CHKERRQ(ierr); 1934 for (i=0; i<N; i++) { 1935 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1936 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1937 1938 zeroed[rows[i]] = PETSC_TRUE; 1939 } 1940 for (i=0; i<A->rmap->n; i++) { 1941 if (!zeroed[i]) { 1942 for (j=a->i[i]; j<a->i[i+1]; j++) { 1943 if (zeroed[a->j[j]]) { 1944 if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; 1945 a->a[j] = 0.0; 1946 } 1947 } 1948 } else if (vecs) bb[i] = diag*xx[i]; 1949 } 1950 if (x && b) { 1951 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1952 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1953 } 1954 ierr = PetscFree(zeroed);CHKERRQ(ierr); 1955 if (diag != 0.0) { 1956 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1957 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1958 for (i=0; i<N; i++) { 1959 a->a[a->diag[rows[i]]] = diag; 1960 } 1961 } 1962 A->same_nonzero = PETSC_TRUE; 1963 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1964 PetscFunctionReturn(0); 1965 } 1966 1967 #undef __FUNCT__ 1968 #define __FUNCT__ "MatGetRow_SeqAIJ" 1969 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1970 { 1971 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1972 PetscInt *itmp; 1973 1974 PetscFunctionBegin; 1975 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1976 1977 *nz = a->i[row+1] - a->i[row]; 1978 if (v) *v = a->a + a->i[row]; 1979 if (idx) { 1980 itmp = a->j + a->i[row]; 1981 if (*nz) *idx = itmp; 1982 else *idx = 0; 1983 } 1984 PetscFunctionReturn(0); 1985 } 1986 1987 /* remove this function? */ 1988 #undef __FUNCT__ 1989 #define __FUNCT__ "MatRestoreRow_SeqAIJ" 1990 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1991 { 1992 PetscFunctionBegin; 1993 PetscFunctionReturn(0); 1994 } 1995 1996 #undef __FUNCT__ 1997 #define __FUNCT__ "MatNorm_SeqAIJ" 1998 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1999 { 2000 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2001 MatScalar *v = a->a; 2002 PetscReal sum = 0.0; 2003 PetscErrorCode ierr; 2004 PetscInt i,j; 2005 2006 PetscFunctionBegin; 2007 if (type == NORM_FROBENIUS) { 2008 for (i=0; i<a->nz; i++) { 2009 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 2010 } 2011 *nrm = PetscSqrtReal(sum); 2012 } else if (type == NORM_1) { 2013 PetscReal *tmp; 2014 PetscInt *jj = a->j; 2015 ierr = PetscMalloc((A->cmap->n+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 2016 ierr = PetscMemzero(tmp,A->cmap->n*sizeof(PetscReal));CHKERRQ(ierr); 2017 *nrm = 0.0; 2018 for (j=0; j<a->nz; j++) { 2019 tmp[*jj++] += PetscAbsScalar(*v); v++; 2020 } 2021 for (j=0; j<A->cmap->n; j++) { 2022 if (tmp[j] > *nrm) *nrm = tmp[j]; 2023 } 2024 ierr = PetscFree(tmp);CHKERRQ(ierr); 2025 } else if (type == NORM_INFINITY) { 2026 *nrm = 0.0; 2027 for (j=0; j<A->rmap->n; j++) { 2028 v = a->a + a->i[j]; 2029 sum = 0.0; 2030 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 2031 sum += PetscAbsScalar(*v); v++; 2032 } 2033 if (sum > *nrm) *nrm = sum; 2034 } 2035 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 2036 PetscFunctionReturn(0); 2037 } 2038 2039 /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ 2040 #undef __FUNCT__ 2041 #define __FUNCT__ "MatTransposeSymbolic_SeqAIJ" 2042 PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) 2043 { 2044 PetscErrorCode ierr; 2045 PetscInt i,j,anzj; 2046 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; 2047 PetscInt an=A->cmap->N,am=A->rmap->N; 2048 PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; 2049 2050 PetscFunctionBegin; 2051 /* Allocate space for symbolic transpose info and work array */ 2052 ierr = PetscMalloc((an+1)*sizeof(PetscInt),&ati);CHKERRQ(ierr); 2053 ierr = PetscMalloc(ai[am]*sizeof(PetscInt),&atj);CHKERRQ(ierr); 2054 ierr = PetscMalloc(an*sizeof(PetscInt),&atfill);CHKERRQ(ierr); 2055 ierr = PetscMemzero(ati,(an+1)*sizeof(PetscInt));CHKERRQ(ierr); 2056 2057 /* Walk through aj and count ## of non-zeros in each row of A^T. */ 2058 /* Note: offset by 1 for fast conversion into csr format. */ 2059 for (i=0;i<ai[am];i++) ati[aj[i]+1] += 1; 2060 /* Form ati for csr format of A^T. */ 2061 for (i=0;i<an;i++) ati[i+1] += ati[i]; 2062 2063 /* Copy ati into atfill so we have locations of the next free space in atj */ 2064 ierr = PetscMemcpy(atfill,ati,an*sizeof(PetscInt));CHKERRQ(ierr); 2065 2066 /* Walk through A row-wise and mark nonzero entries of A^T. */ 2067 for (i=0;i<am;i++) { 2068 anzj = ai[i+1] - ai[i]; 2069 for (j=0;j<anzj;j++) { 2070 atj[atfill[*aj]] = i; 2071 atfill[*aj++] += 1; 2072 } 2073 } 2074 2075 /* Clean up temporary space and complete requests. */ 2076 ierr = PetscFree(atfill);CHKERRQ(ierr); 2077 ierr = MatCreateSeqAIJWithArrays(PetscObjectComm((PetscObject)A),an,am,ati,atj,NULL,B);CHKERRQ(ierr); 2078 2079 (*B)->rmap->bs = A->cmap->bs; 2080 (*B)->cmap->bs = A->rmap->bs; 2081 2082 b = (Mat_SeqAIJ*)((*B)->data); 2083 b->free_a = PETSC_FALSE; 2084 b->free_ij = PETSC_TRUE; 2085 b->nonew = 0; 2086 PetscFunctionReturn(0); 2087 } 2088 2089 #undef __FUNCT__ 2090 #define __FUNCT__ "MatTranspose_SeqAIJ" 2091 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 2092 { 2093 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2094 Mat C; 2095 PetscErrorCode ierr; 2096 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 2097 MatScalar *array = a->a; 2098 2099 PetscFunctionBegin; 2100 if (reuse == MAT_REUSE_MATRIX && A == *B && m != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Square matrix only for in-place"); 2101 2102 if (reuse == MAT_INITIAL_MATRIX || *B == A) { 2103 ierr = PetscMalloc((1+A->cmap->n)*sizeof(PetscInt),&col);CHKERRQ(ierr); 2104 ierr = PetscMemzero(col,(1+A->cmap->n)*sizeof(PetscInt));CHKERRQ(ierr); 2105 2106 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 2107 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2108 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 2109 ierr = MatSetBlockSizes(C,A->cmap->bs,A->rmap->bs);CHKERRQ(ierr); 2110 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2111 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 2112 ierr = PetscFree(col);CHKERRQ(ierr); 2113 } else { 2114 C = *B; 2115 } 2116 2117 for (i=0; i<m; i++) { 2118 len = ai[i+1]-ai[i]; 2119 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 2120 array += len; 2121 aj += len; 2122 } 2123 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2124 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2125 2126 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 2127 *B = C; 2128 } else { 2129 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 2130 } 2131 PetscFunctionReturn(0); 2132 } 2133 2134 #undef __FUNCT__ 2135 #define __FUNCT__ "MatIsTranspose_SeqAIJ" 2136 PetscErrorCode MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2137 { 2138 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2139 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2140 MatScalar *va,*vb; 2141 PetscErrorCode ierr; 2142 PetscInt ma,na,mb,nb, i; 2143 2144 PetscFunctionBegin; 2145 bij = (Mat_SeqAIJ*) B->data; 2146 2147 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2148 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2149 if (ma!=nb || na!=mb) { 2150 *f = PETSC_FALSE; 2151 PetscFunctionReturn(0); 2152 } 2153 aii = aij->i; bii = bij->i; 2154 adx = aij->j; bdx = bij->j; 2155 va = aij->a; vb = bij->a; 2156 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 2157 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 2158 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2159 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2160 2161 *f = PETSC_TRUE; 2162 for (i=0; i<ma; i++) { 2163 while (aptr[i]<aii[i+1]) { 2164 PetscInt idc,idr; 2165 PetscScalar vc,vr; 2166 /* column/row index/value */ 2167 idc = adx[aptr[i]]; 2168 idr = bdx[bptr[idc]]; 2169 vc = va[aptr[i]]; 2170 vr = vb[bptr[idc]]; 2171 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 2172 *f = PETSC_FALSE; 2173 goto done; 2174 } else { 2175 aptr[i]++; 2176 if (B || i!=idc) bptr[idc]++; 2177 } 2178 } 2179 } 2180 done: 2181 ierr = PetscFree(aptr);CHKERRQ(ierr); 2182 ierr = PetscFree(bptr);CHKERRQ(ierr); 2183 PetscFunctionReturn(0); 2184 } 2185 2186 #undef __FUNCT__ 2187 #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" 2188 PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) 2189 { 2190 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; 2191 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 2192 MatScalar *va,*vb; 2193 PetscErrorCode ierr; 2194 PetscInt ma,na,mb,nb, i; 2195 2196 PetscFunctionBegin; 2197 bij = (Mat_SeqAIJ*) B->data; 2198 2199 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 2200 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 2201 if (ma!=nb || na!=mb) { 2202 *f = PETSC_FALSE; 2203 PetscFunctionReturn(0); 2204 } 2205 aii = aij->i; bii = bij->i; 2206 adx = aij->j; bdx = bij->j; 2207 va = aij->a; vb = bij->a; 2208 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 2209 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 2210 for (i=0; i<ma; i++) aptr[i] = aii[i]; 2211 for (i=0; i<mb; i++) bptr[i] = bii[i]; 2212 2213 *f = PETSC_TRUE; 2214 for (i=0; i<ma; i++) { 2215 while (aptr[i]<aii[i+1]) { 2216 PetscInt idc,idr; 2217 PetscScalar vc,vr; 2218 /* column/row index/value */ 2219 idc = adx[aptr[i]]; 2220 idr = bdx[bptr[idc]]; 2221 vc = va[aptr[i]]; 2222 vr = vb[bptr[idc]]; 2223 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 2224 *f = PETSC_FALSE; 2225 goto done; 2226 } else { 2227 aptr[i]++; 2228 if (B || i!=idc) bptr[idc]++; 2229 } 2230 } 2231 } 2232 done: 2233 ierr = PetscFree(aptr);CHKERRQ(ierr); 2234 ierr = PetscFree(bptr);CHKERRQ(ierr); 2235 PetscFunctionReturn(0); 2236 } 2237 2238 #undef __FUNCT__ 2239 #define __FUNCT__ "MatIsSymmetric_SeqAIJ" 2240 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2241 { 2242 PetscErrorCode ierr; 2243 2244 PetscFunctionBegin; 2245 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2246 PetscFunctionReturn(0); 2247 } 2248 2249 #undef __FUNCT__ 2250 #define __FUNCT__ "MatIsHermitian_SeqAIJ" 2251 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) 2252 { 2253 PetscErrorCode ierr; 2254 2255 PetscFunctionBegin; 2256 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 2257 PetscFunctionReturn(0); 2258 } 2259 2260 #undef __FUNCT__ 2261 #define __FUNCT__ "MatDiagonalScale_SeqAIJ" 2262 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 2263 { 2264 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2265 PetscScalar *l,*r,x; 2266 MatScalar *v; 2267 PetscErrorCode ierr; 2268 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; 2269 2270 PetscFunctionBegin; 2271 if (ll) { 2272 /* The local size is used so that VecMPI can be passed to this routine 2273 by MatDiagonalScale_MPIAIJ */ 2274 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 2275 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 2276 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 2277 v = a->a; 2278 for (i=0; i<m; i++) { 2279 x = l[i]; 2280 M = a->i[i+1] - a->i[i]; 2281 for (j=0; j<M; j++) (*v++) *= x; 2282 } 2283 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 2284 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2285 } 2286 if (rr) { 2287 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 2288 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 2289 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 2290 v = a->a; jj = a->j; 2291 for (i=0; i<nz; i++) (*v++) *= r[*jj++]; 2292 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 2293 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 2294 } 2295 ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); 2296 PetscFunctionReturn(0); 2297 } 2298 2299 #undef __FUNCT__ 2300 #define __FUNCT__ "MatGetSubMatrix_SeqAIJ" 2301 PetscErrorCode MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 2302 { 2303 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 2304 PetscErrorCode ierr; 2305 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 2306 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 2307 const PetscInt *irow,*icol; 2308 PetscInt nrows,ncols; 2309 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 2310 MatScalar *a_new,*mat_a; 2311 Mat C; 2312 PetscBool stride,sorted; 2313 2314 PetscFunctionBegin; 2315 ierr = ISSorted(isrow,&sorted);CHKERRQ(ierr); 2316 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted"); 2317 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); 2318 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted"); 2319 2320 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 2321 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 2322 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 2323 2324 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 2325 ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); 2326 if (stride && step == 1) { 2327 /* special case of contiguous rows */ 2328 ierr = PetscMalloc2(nrows,PetscInt,&lens,nrows,PetscInt,&starts);CHKERRQ(ierr); 2329 /* loop over new rows determining lens and starting points */ 2330 for (i=0; i<nrows; i++) { 2331 kstart = ai[irow[i]]; 2332 kend = kstart + ailen[irow[i]]; 2333 for (k=kstart; k<kend; k++) { 2334 if (aj[k] >= first) { 2335 starts[i] = k; 2336 break; 2337 } 2338 } 2339 sum = 0; 2340 while (k < kend) { 2341 if (aj[k++] >= first+ncols) break; 2342 sum++; 2343 } 2344 lens[i] = sum; 2345 } 2346 /* create submatrix */ 2347 if (scall == MAT_REUSE_MATRIX) { 2348 PetscInt n_cols,n_rows; 2349 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 2350 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 2351 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 2352 C = *B; 2353 } else { 2354 PetscInt rbs,cbs; 2355 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2356 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2357 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2358 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2359 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2360 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2361 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2362 } 2363 c = (Mat_SeqAIJ*)C->data; 2364 2365 /* loop over rows inserting into submatrix */ 2366 a_new = c->a; 2367 j_new = c->j; 2368 i_new = c->i; 2369 2370 for (i=0; i<nrows; i++) { 2371 ii = starts[i]; 2372 lensi = lens[i]; 2373 for (k=0; k<lensi; k++) { 2374 *j_new++ = aj[ii+k] - first; 2375 } 2376 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 2377 a_new += lensi; 2378 i_new[i+1] = i_new[i] + lensi; 2379 c->ilen[i] = lensi; 2380 } 2381 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 2382 } else { 2383 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 2384 ierr = PetscMalloc(oldcols*sizeof(PetscInt),&smap);CHKERRQ(ierr); 2385 ierr = PetscMemzero(smap,oldcols*sizeof(PetscInt));CHKERRQ(ierr); 2386 ierr = PetscMalloc((1+nrows)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2387 for (i=0; i<ncols; i++) { 2388 #if defined(PETSC_USE_DEBUG) 2389 if (icol[i] >= oldcols) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Requesting column beyond largest column icol[%D] %D <= A->cmap->n %D",i,icol[i],oldcols); 2390 #endif 2391 smap[icol[i]] = i+1; 2392 } 2393 2394 /* determine lens of each row */ 2395 for (i=0; i<nrows; i++) { 2396 kstart = ai[irow[i]]; 2397 kend = kstart + a->ilen[irow[i]]; 2398 lens[i] = 0; 2399 for (k=kstart; k<kend; k++) { 2400 if (smap[aj[k]]) { 2401 lens[i]++; 2402 } 2403 } 2404 } 2405 /* Create and fill new matrix */ 2406 if (scall == MAT_REUSE_MATRIX) { 2407 PetscBool equal; 2408 2409 c = (Mat_SeqAIJ*)((*B)->data); 2410 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 2411 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 2412 if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 2413 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 2414 C = *B; 2415 } else { 2416 PetscInt rbs,cbs; 2417 ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); 2418 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 2419 ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); 2420 ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); 2421 ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); 2422 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 2423 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 2424 } 2425 c = (Mat_SeqAIJ*)(C->data); 2426 for (i=0; i<nrows; i++) { 2427 row = irow[i]; 2428 kstart = ai[row]; 2429 kend = kstart + a->ilen[row]; 2430 mat_i = c->i[i]; 2431 mat_j = c->j + mat_i; 2432 mat_a = c->a + mat_i; 2433 mat_ilen = c->ilen + i; 2434 for (k=kstart; k<kend; k++) { 2435 if ((tcol=smap[a->j[k]])) { 2436 *mat_j++ = tcol - 1; 2437 *mat_a++ = a->a[k]; 2438 (*mat_ilen)++; 2439 2440 } 2441 } 2442 } 2443 /* Free work space */ 2444 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 2445 ierr = PetscFree(smap);CHKERRQ(ierr); 2446 ierr = PetscFree(lens);CHKERRQ(ierr); 2447 } 2448 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2449 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2450 2451 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 2452 *B = C; 2453 PetscFunctionReturn(0); 2454 } 2455 2456 #undef __FUNCT__ 2457 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 2458 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) 2459 { 2460 PetscErrorCode ierr; 2461 Mat B; 2462 2463 PetscFunctionBegin; 2464 if (scall == MAT_INITIAL_MATRIX) { 2465 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 2466 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 2467 ierr = MatSetBlockSizes(B,mat->rmap->bs,mat->cmap->bs);CHKERRQ(ierr); 2468 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2469 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 2470 *subMat = B; 2471 } else { 2472 ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); 2473 } 2474 PetscFunctionReturn(0); 2475 } 2476 2477 #undef __FUNCT__ 2478 #define __FUNCT__ "MatILUFactor_SeqAIJ" 2479 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 2480 { 2481 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2482 PetscErrorCode ierr; 2483 Mat outA; 2484 PetscBool row_identity,col_identity; 2485 2486 PetscFunctionBegin; 2487 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 2488 2489 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 2490 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 2491 2492 outA = inA; 2493 outA->factortype = MAT_FACTOR_LU; 2494 2495 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 2496 ierr = ISDestroy(&a->row);CHKERRQ(ierr); 2497 2498 a->row = row; 2499 2500 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 2501 ierr = ISDestroy(&a->col);CHKERRQ(ierr); 2502 2503 a->col = col; 2504 2505 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 2506 ierr = ISDestroy(&a->icol);CHKERRQ(ierr); 2507 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 2508 ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); 2509 2510 if (!a->solve_work) { /* this matrix may have been factored before */ 2511 ierr = PetscMalloc((inA->rmap->n+1)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); 2512 ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2513 } 2514 2515 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 2516 if (row_identity && col_identity) { 2517 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 2518 } else { 2519 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 2520 } 2521 PetscFunctionReturn(0); 2522 } 2523 2524 #undef __FUNCT__ 2525 #define __FUNCT__ "MatScale_SeqAIJ" 2526 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 2527 { 2528 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 2529 PetscScalar oalpha = alpha; 2530 PetscErrorCode ierr; 2531 PetscBLASInt one = 1,bnz; 2532 2533 PetscFunctionBegin; 2534 ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); 2535 PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); 2536 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 2537 ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); 2538 PetscFunctionReturn(0); 2539 } 2540 2541 #undef __FUNCT__ 2542 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 2543 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 2544 { 2545 PetscErrorCode ierr; 2546 PetscInt i; 2547 2548 PetscFunctionBegin; 2549 if (scall == MAT_INITIAL_MATRIX) { 2550 ierr = PetscMalloc((n+1)*sizeof(Mat),B);CHKERRQ(ierr); 2551 } 2552 2553 for (i=0; i<n; i++) { 2554 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 2555 } 2556 PetscFunctionReturn(0); 2557 } 2558 2559 #undef __FUNCT__ 2560 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 2561 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 2562 { 2563 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2564 PetscErrorCode ierr; 2565 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 2566 const PetscInt *idx; 2567 PetscInt start,end,*ai,*aj; 2568 PetscBT table; 2569 2570 PetscFunctionBegin; 2571 m = A->rmap->n; 2572 ai = a->i; 2573 aj = a->j; 2574 2575 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 2576 2577 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&nidx);CHKERRQ(ierr); 2578 ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); 2579 2580 for (i=0; i<is_max; i++) { 2581 /* Initialize the two local arrays */ 2582 isz = 0; 2583 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2584 2585 /* Extract the indices, assume there can be duplicate entries */ 2586 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2587 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2588 2589 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2590 for (j=0; j<n; ++j) { 2591 if (!PetscBTLookupSet(table,idx[j])) nidx[isz++] = idx[j]; 2592 } 2593 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2594 ierr = ISDestroy(&is[i]);CHKERRQ(ierr); 2595 2596 k = 0; 2597 for (j=0; j<ov; j++) { /* for each overlap */ 2598 n = isz; 2599 for (; k<n; k++) { /* do only those rows in nidx[k], which are not done yet */ 2600 row = nidx[k]; 2601 start = ai[row]; 2602 end = ai[row+1]; 2603 for (l = start; l<end; l++) { 2604 val = aj[l]; 2605 if (!PetscBTLookupSet(table,val)) nidx[isz++] = val; 2606 } 2607 } 2608 } 2609 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,PETSC_COPY_VALUES,(is+i));CHKERRQ(ierr); 2610 } 2611 ierr = PetscBTDestroy(&table);CHKERRQ(ierr); 2612 ierr = PetscFree(nidx);CHKERRQ(ierr); 2613 PetscFunctionReturn(0); 2614 } 2615 2616 /* -------------------------------------------------------------- */ 2617 #undef __FUNCT__ 2618 #define __FUNCT__ "MatPermute_SeqAIJ" 2619 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2620 { 2621 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2622 PetscErrorCode ierr; 2623 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2624 const PetscInt *row,*col; 2625 PetscInt *cnew,j,*lens; 2626 IS icolp,irowp; 2627 PetscInt *cwork = NULL; 2628 PetscScalar *vwork = NULL; 2629 2630 PetscFunctionBegin; 2631 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2632 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2633 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2634 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2635 2636 /* determine lengths of permuted rows */ 2637 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2638 for (i=0; i<m; i++) lens[row[i]] = a->i[i+1] - a->i[i]; 2639 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 2640 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2641 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 2642 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2643 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2644 ierr = PetscFree(lens);CHKERRQ(ierr); 2645 2646 ierr = PetscMalloc(n*sizeof(PetscInt),&cnew);CHKERRQ(ierr); 2647 for (i=0; i<m; i++) { 2648 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2649 for (j=0; j<nz; j++) cnew[j] = col[cwork[j]]; 2650 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2651 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2652 } 2653 ierr = PetscFree(cnew);CHKERRQ(ierr); 2654 2655 (*B)->assembled = PETSC_FALSE; 2656 2657 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2658 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2659 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2660 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2661 ierr = ISDestroy(&irowp);CHKERRQ(ierr); 2662 ierr = ISDestroy(&icolp);CHKERRQ(ierr); 2663 PetscFunctionReturn(0); 2664 } 2665 2666 #undef __FUNCT__ 2667 #define __FUNCT__ "MatCopy_SeqAIJ" 2668 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2669 { 2670 PetscErrorCode ierr; 2671 2672 PetscFunctionBegin; 2673 /* If the two matrices have the same copy implementation, use fast copy. */ 2674 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2675 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2676 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2677 2678 if (a->i[A->rmap->n] != b->i[B->rmap->n]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different"); 2679 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2680 } else { 2681 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2682 } 2683 PetscFunctionReturn(0); 2684 } 2685 2686 #undef __FUNCT__ 2687 #define __FUNCT__ "MatSetUp_SeqAIJ" 2688 PetscErrorCode MatSetUp_SeqAIJ(Mat A) 2689 { 2690 PetscErrorCode ierr; 2691 2692 PetscFunctionBegin; 2693 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2694 PetscFunctionReturn(0); 2695 } 2696 2697 #undef __FUNCT__ 2698 #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" 2699 PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2700 { 2701 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2702 2703 PetscFunctionBegin; 2704 *array = a->a; 2705 PetscFunctionReturn(0); 2706 } 2707 2708 #undef __FUNCT__ 2709 #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" 2710 PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2711 { 2712 PetscFunctionBegin; 2713 PetscFunctionReturn(0); 2714 } 2715 2716 /* Optimize MatFDColoringApply_AIJ() by using array den2sp to skip calling MatSetValues() */ 2717 //#define JACOBIANCOLOROPT 2718 #if defined(JACOBIANCOLOROPT) 2719 #include <petsctime.h> 2720 #endif 2721 #undef __FUNCT__ 2722 #define __FUNCT__ "MatFDColoringApply_SeqAIJ" 2723 PetscErrorCode MatFDColoringApply_SeqAIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2724 { 2725 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2726 PetscErrorCode ierr; 2727 PetscInt k,l,row,col,N; 2728 PetscScalar dx,*y,*xx,*w3_array; 2729 PetscScalar *vscale_array; 2730 PetscReal epsilon=coloring->error_rel,umin = coloring->umin,unorm; 2731 Vec w1=coloring->w1,w2=coloring->w2,w3; 2732 void *fctx=coloring->fctx; 2733 PetscBool flg=PETSC_FALSE; 2734 Mat_SeqAIJ *csp=(Mat_SeqAIJ*)J->data; 2735 PetscScalar *ca=csp->a; 2736 const PetscInt ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows; 2737 PetscInt *den2sp=coloring->den2sp,*idx; 2738 PetscInt **rows=coloring->rows,**columns=coloring->columns,ncolumns_k,nrows_k,**columnsforrow=coloring->columnsforrow; 2739 #if defined(JACOBIANCOLOROPT) 2740 PetscLogDouble t0,t1,t_init=0.0,t_setvals=0.0,t_func=0.0,t_dx=0.0,t_kl=0.0,t00,t11; 2741 #endif 2742 PetscInt kl; 2743 2744 PetscFunctionBegin; 2745 #if defined(JACOBIANCOLOROPT) 2746 ierr = PetscTime(&t0);CHKERRQ(ierr); 2747 #endif 2748 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2749 ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2750 if (flg) { 2751 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2752 } else { 2753 PetscBool assembled; 2754 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2755 if (assembled) { 2756 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2757 } 2758 } 2759 2760 if (!coloring->vscale) { 2761 ierr = VecDuplicate(x1,&coloring->vscale);CHKERRQ(ierr); 2762 } 2763 2764 if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/ 2765 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 2766 } 2767 #if defined(JACOBIANCOLOROPT) 2768 ierr = PetscTime(&t1);CHKERRQ(ierr); 2769 t_init += t1 - t0; 2770 #endif 2771 2772 /* Set w1 = F(x1) */ 2773 #if defined(JACOBIANCOLOROPT) 2774 ierr = PetscTime(&t0);CHKERRQ(ierr); 2775 #endif 2776 if (!coloring->fset) { 2777 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2778 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2779 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2780 } else { 2781 coloring->fset = PETSC_FALSE; 2782 } 2783 #if defined(JACOBIANCOLOROPT) 2784 ierr = PetscTime(&t1);CHKERRQ(ierr); 2785 t_setvals += t1 - t0; 2786 #endif 2787 2788 #if defined(JACOBIANCOLOROPT) 2789 ierr = PetscTime(&t0);CHKERRQ(ierr); 2790 #endif 2791 if (!coloring->w3) { 2792 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2793 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2794 } 2795 w3 = coloring->w3; 2796 2797 /* Compute scale factors: vscale = 1./dx = 1./(epsilon*xx) */ 2798 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 2799 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2800 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2801 for (col=0; col<N; col++) { 2802 if (coloring->htype[0] == 'w') { 2803 dx = 1.0 + unorm; 2804 } else { 2805 dx = xx[col]; 2806 } 2807 if (dx == (PetscScalar)0.0) dx = 1.0; 2808 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2809 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2810 dx *= epsilon; 2811 vscale_array[col] = (PetscScalar)dx; 2812 } 2813 #if defined(JACOBIANCOLOROPT) 2814 ierr = PetscTime(&t1);CHKERRQ(ierr); 2815 t_init += t1 - t0; 2816 #endif 2817 2818 idx = den2sp; 2819 for (k=0; k<ncolors; k++) { /* loop over colors */ 2820 #if defined(JACOBIANCOLOROPT) 2821 ierr = PetscTime(&t0);CHKERRQ(ierr); 2822 #endif 2823 coloring->currentcolor = k; 2824 2825 /* 2826 Loop over each column associated with color 2827 adding the perturbation to the vector w3 = x1 + dx. 2828 */ 2829 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2830 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 2831 ncolumns_k = ncolumns[k]; 2832 for (l=0; l<ncolumns_k; l++) { /* loop over columns */ 2833 col = columns[k][l]; 2834 w3_array[col] += vscale_array[col]; 2835 } 2836 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2837 #if defined(JACOBIANCOLOROPT) 2838 ierr = PetscTime(&t1);CHKERRQ(ierr); 2839 t_dx += t1 - t0; 2840 #endif 2841 2842 /* 2843 Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 2844 w2 = F(x1 + dx) - F(x1) 2845 */ 2846 #if defined(JACOBIANCOLOROPT) 2847 ierr = PetscTime(&t0);CHKERRQ(ierr); 2848 #endif 2849 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2850 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2851 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2852 #if defined(JACOBIANCOLOROPT) 2853 ierr = PetscTime(&t1);CHKERRQ(ierr); 2854 t_func += t1 - t0; 2855 #endif 2856 2857 #if defined(JACOBIANCOLOROPT) 2858 ierr = PetscTime(&t0);CHKERRQ(ierr); 2859 #endif 2860 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2861 2862 /* 2863 Loop over rows of vector, putting w2/dx into Jacobian matrix 2864 */ 2865 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2866 nrows_k = nrows[k]; 2867 for (l=0; l<nrows_k; l++) { /* loop over rows */ 2868 #if defined(JACOBIANCOLOROPT) 2869 ierr = PetscTime(&t00);CHKERRQ(ierr); 2870 #endif 2871 row = rows[k][l]; /* row index */ 2872 kl = columnsforrow[k][l]; 2873 #if defined(JACOBIANCOLOROPT) 2874 ierr = PetscTime(&t11);CHKERRQ(ierr); 2875 t_kl += t11 - t00; 2876 #endif 2877 2878 ca[idx[l]] = y[row]/vscale_array[kl];//y[row]/vscale_array[columnsforrow[k][l]]; 2879 } 2880 idx += nrows_k; 2881 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2882 2883 #if defined(JACOBIANCOLOROPT) 2884 ierr = PetscTime(&t1);CHKERRQ(ierr); 2885 t_setvals += t1 - t0; 2886 #endif 2887 } /* endof for each color */ 2888 #if defined(JACOBIANCOLOROPT) 2889 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); 2890 printf(" FDColorApply time: kl %g\n",t_kl); 2891 #endif 2892 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2893 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2894 2895 coloring->currentcolor = -1; 2896 PetscFunctionReturn(0); 2897 } 2898 /* --------------------------------------------------------*/ 2899 2900 #undef __FUNCT__ 2901 #define __FUNCT__ "MatFDColoringApply_SeqAIJ_old" 2902 PetscErrorCode MatFDColoringApply_SeqAIJ_old(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2903 { 2904 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2905 PetscErrorCode ierr; 2906 PetscInt k,N,start,end,l,row,col,srow,**vscaleforrow; 2907 PetscScalar dx,*y,*xx,*w3_array; 2908 PetscScalar *vscale_array; 2909 PetscReal epsilon = coloring->error_rel,umin = coloring->umin; 2910 Vec w1,w2,w3; 2911 void *fctx = coloring->fctx; 2912 PetscBool flg = PETSC_FALSE; 2913 2914 PetscFunctionBegin; 2915 printf("MatFDColoringApply_SeqAIJ ...\n"); 2916 if (!coloring->w1) { 2917 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 2918 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w1);CHKERRQ(ierr); 2919 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 2920 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w2);CHKERRQ(ierr); 2921 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2922 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2923 } 2924 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 2925 2926 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2927 ierr = PetscOptionsGetBool(((PetscObject)coloring)->prefix,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2928 if (flg) { 2929 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2930 } else { 2931 PetscBool assembled; 2932 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2933 if (assembled) { 2934 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2935 } 2936 } 2937 2938 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 2939 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2940 2941 if (!coloring->fset) { 2942 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2943 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2944 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2945 } else { 2946 coloring->fset = PETSC_FALSE; 2947 } 2948 2949 /* 2950 Compute all the scale factors and share with other processors 2951 */ 2952 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start; 2953 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start; 2954 for (k=0; k<coloring->ncolors; k++) { 2955 /* 2956 Loop over each column associated with color adding the 2957 perturbation to the vector w3. 2958 */ 2959 for (l=0; l<coloring->ncolumns[k]; l++) { 2960 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2961 dx = xx[col]; 2962 if (dx == 0.0) dx = 1.0; 2963 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2964 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2965 dx *= epsilon; 2966 vscale_array[col] = 1.0/dx; 2967 } 2968 } 2969 vscale_array = vscale_array + start; 2970 2971 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2972 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2973 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2974 2975 /* ierr = VecView(coloring->vscale,PETSC_VIEWER_STDOUT_WORLD); 2976 ierr = VecView(x1,PETSC_VIEWER_STDOUT_WORLD);*/ 2977 2978 if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow; 2979 else vscaleforrow = coloring->columnsforrow; 2980 2981 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2982 /* 2983 Loop over each color 2984 */ 2985 for (k=0; k<coloring->ncolors; k++) { 2986 coloring->currentcolor = k; 2987 2988 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2989 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start; 2990 /* 2991 Loop over each column associated with color adding the 2992 perturbation to the vector w3. 2993 */ 2994 for (l=0; l<coloring->ncolumns[k]; l++) { 2995 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2996 dx = xx[col]; 2997 if (dx == 0.0) dx = 1.0; 2998 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2999 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 3000 dx *= epsilon; 3001 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 3002 w3_array[col] += dx; 3003 } 3004 w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 3005 3006 /* 3007 Evaluate function at x1 + dx (here dx is a vector of perturbations) 3008 */ 3009 3010 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 3011 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 3012 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 3013 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 3014 3015 /* 3016 Loop over rows of vector, putting results into Jacobian matrix 3017 */ 3018 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 3019 for (l=0; l<coloring->nrows[k]; l++) { 3020 row = coloring->rows[k][l]; 3021 col = coloring->columnsforrow[k][l]; 3022 y[row] *= vscale_array[vscaleforrow[k][l]]; 3023 srow = row + start; 3024 ierr = MatSetValues_SeqAIJ(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 3025 } 3026 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 3027 } 3028 coloring->currentcolor = k; 3029 3030 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 3031 xx = xx + start; 3032 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 3033 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3034 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3035 PetscFunctionReturn(0); 3036 } 3037 3038 /* 3039 Computes the number of nonzeros per row needed for preallocation when X and Y 3040 have different nonzero structure. 3041 */ 3042 #undef __FUNCT__ 3043 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 3044 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 3045 { 3046 PetscInt i,m=Y->rmap->N; 3047 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 3048 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 3049 const PetscInt *xi = x->i,*yi = y->i; 3050 3051 PetscFunctionBegin; 3052 /* Set the number of nonzeros in the new matrix */ 3053 for (i=0; i<m; i++) { 3054 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 3055 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 3056 nnz[i] = 0; 3057 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 3058 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 3059 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 3060 nnz[i]++; 3061 } 3062 for (; k<nzy; k++) nnz[i]++; 3063 } 3064 PetscFunctionReturn(0); 3065 } 3066 3067 #undef __FUNCT__ 3068 #define __FUNCT__ "MatAXPY_SeqAIJ" 3069 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 3070 { 3071 PetscErrorCode ierr; 3072 PetscInt i; 3073 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 3074 PetscBLASInt one=1,bnz; 3075 3076 PetscFunctionBegin; 3077 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 3078 if (str == SAME_NONZERO_PATTERN) { 3079 PetscScalar alpha = a; 3080 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 3081 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 3082 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 3083 if (y->xtoy && y->XtoY != X) { 3084 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 3085 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 3086 } 3087 if (!y->xtoy) { /* get xtoy */ 3088 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 3089 y->XtoY = X; 3090 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 3091 } 3092 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 3093 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); 3094 } else { 3095 Mat B; 3096 PetscInt *nnz; 3097 ierr = PetscMalloc(Y->rmap->N*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 3098 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 3099 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 3100 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 3101 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 3102 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 3103 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 3104 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 3105 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 3106 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 3107 ierr = PetscFree(nnz);CHKERRQ(ierr); 3108 } 3109 PetscFunctionReturn(0); 3110 } 3111 3112 #undef __FUNCT__ 3113 #define __FUNCT__ "MatConjugate_SeqAIJ" 3114 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 3115 { 3116 #if defined(PETSC_USE_COMPLEX) 3117 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3118 PetscInt i,nz; 3119 PetscScalar *a; 3120 3121 PetscFunctionBegin; 3122 nz = aij->nz; 3123 a = aij->a; 3124 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3125 #else 3126 PetscFunctionBegin; 3127 #endif 3128 PetscFunctionReturn(0); 3129 } 3130 3131 #undef __FUNCT__ 3132 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 3133 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3134 { 3135 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3136 PetscErrorCode ierr; 3137 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3138 PetscReal atmp; 3139 PetscScalar *x; 3140 MatScalar *aa; 3141 3142 PetscFunctionBegin; 3143 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3144 aa = a->a; 3145 ai = a->i; 3146 aj = a->j; 3147 3148 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3149 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3150 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3151 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3152 for (i=0; i<m; i++) { 3153 ncols = ai[1] - ai[0]; ai++; 3154 x[i] = 0.0; 3155 for (j=0; j<ncols; j++) { 3156 atmp = PetscAbsScalar(*aa); 3157 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3158 aa++; aj++; 3159 } 3160 } 3161 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3162 PetscFunctionReturn(0); 3163 } 3164 3165 #undef __FUNCT__ 3166 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 3167 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3168 { 3169 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3170 PetscErrorCode ierr; 3171 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3172 PetscScalar *x; 3173 MatScalar *aa; 3174 3175 PetscFunctionBegin; 3176 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3177 aa = a->a; 3178 ai = a->i; 3179 aj = a->j; 3180 3181 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3182 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3183 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3184 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3185 for (i=0; i<m; i++) { 3186 ncols = ai[1] - ai[0]; ai++; 3187 if (ncols == A->cmap->n) { /* row is dense */ 3188 x[i] = *aa; if (idx) idx[i] = 0; 3189 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3190 x[i] = 0.0; 3191 if (idx) { 3192 idx[i] = 0; /* in case ncols is zero */ 3193 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3194 if (aj[j] > j) { 3195 idx[i] = j; 3196 break; 3197 } 3198 } 3199 } 3200 } 3201 for (j=0; j<ncols; j++) { 3202 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3203 aa++; aj++; 3204 } 3205 } 3206 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3207 PetscFunctionReturn(0); 3208 } 3209 3210 #undef __FUNCT__ 3211 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 3212 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3213 { 3214 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3215 PetscErrorCode ierr; 3216 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3217 PetscReal atmp; 3218 PetscScalar *x; 3219 MatScalar *aa; 3220 3221 PetscFunctionBegin; 3222 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3223 aa = a->a; 3224 ai = a->i; 3225 aj = a->j; 3226 3227 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3228 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3229 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3230 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); 3231 for (i=0; i<m; i++) { 3232 ncols = ai[1] - ai[0]; ai++; 3233 if (ncols) { 3234 /* Get first nonzero */ 3235 for (j = 0; j < ncols; j++) { 3236 atmp = PetscAbsScalar(aa[j]); 3237 if (atmp > 1.0e-12) { 3238 x[i] = atmp; 3239 if (idx) idx[i] = aj[j]; 3240 break; 3241 } 3242 } 3243 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3244 } else { 3245 x[i] = 0.0; if (idx) idx[i] = 0; 3246 } 3247 for (j = 0; j < ncols; j++) { 3248 atmp = PetscAbsScalar(*aa); 3249 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3250 aa++; aj++; 3251 } 3252 } 3253 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3254 PetscFunctionReturn(0); 3255 } 3256 3257 #undef __FUNCT__ 3258 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3259 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3260 { 3261 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3262 PetscErrorCode ierr; 3263 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3264 PetscScalar *x; 3265 MatScalar *aa; 3266 3267 PetscFunctionBegin; 3268 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3269 aa = a->a; 3270 ai = a->i; 3271 aj = a->j; 3272 3273 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3274 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3275 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3276 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3277 for (i=0; i<m; i++) { 3278 ncols = ai[1] - ai[0]; ai++; 3279 if (ncols == A->cmap->n) { /* row is dense */ 3280 x[i] = *aa; if (idx) idx[i] = 0; 3281 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3282 x[i] = 0.0; 3283 if (idx) { /* find first implicit 0.0 in the row */ 3284 idx[i] = 0; /* in case ncols is zero */ 3285 for (j=0; j<ncols; j++) { 3286 if (aj[j] > j) { 3287 idx[i] = j; 3288 break; 3289 } 3290 } 3291 } 3292 } 3293 for (j=0; j<ncols; j++) { 3294 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3295 aa++; aj++; 3296 } 3297 } 3298 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3299 PetscFunctionReturn(0); 3300 } 3301 3302 #include <petscblaslapack.h> 3303 #include <petsc-private/kernels/blockinvert.h> 3304 3305 #undef __FUNCT__ 3306 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3307 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3308 { 3309 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3310 PetscErrorCode ierr; 3311 PetscInt i,bs = A->rmap->bs,mbs = A->rmap->n/A->rmap->bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3312 MatScalar *diag,work[25],*v_work; 3313 PetscReal shift = 0.0; 3314 3315 PetscFunctionBegin; 3316 if (a->ibdiagvalid) { 3317 if (values) *values = a->ibdiag; 3318 PetscFunctionReturn(0); 3319 } 3320 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3321 if (!a->ibdiag) { 3322 ierr = PetscMalloc(bs2*mbs*sizeof(PetscScalar),&a->ibdiag);CHKERRQ(ierr); 3323 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3324 } 3325 diag = a->ibdiag; 3326 if (values) *values = a->ibdiag; 3327 /* factor and invert each block */ 3328 switch (bs) { 3329 case 1: 3330 for (i=0; i<mbs; i++) { 3331 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3332 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3333 } 3334 break; 3335 case 2: 3336 for (i=0; i<mbs; i++) { 3337 ij[0] = 2*i; ij[1] = 2*i + 1; 3338 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3339 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3340 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3341 diag += 4; 3342 } 3343 break; 3344 case 3: 3345 for (i=0; i<mbs; i++) { 3346 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3347 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3348 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3349 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3350 diag += 9; 3351 } 3352 break; 3353 case 4: 3354 for (i=0; i<mbs; i++) { 3355 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3356 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3357 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3358 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3359 diag += 16; 3360 } 3361 break; 3362 case 5: 3363 for (i=0; i<mbs; i++) { 3364 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3365 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3366 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3367 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3368 diag += 25; 3369 } 3370 break; 3371 case 6: 3372 for (i=0; i<mbs; i++) { 3373 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; 3374 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3375 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3376 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3377 diag += 36; 3378 } 3379 break; 3380 case 7: 3381 for (i=0; i<mbs; i++) { 3382 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; 3383 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3384 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3385 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3386 diag += 49; 3387 } 3388 break; 3389 default: 3390 ierr = PetscMalloc3(bs,MatScalar,&v_work,bs,PetscInt,&v_pivots,bs,PetscInt,&IJ);CHKERRQ(ierr); 3391 for (i=0; i<mbs; i++) { 3392 for (j=0; j<bs; j++) { 3393 IJ[j] = bs*i + j; 3394 } 3395 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3396 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3397 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3398 diag += bs2; 3399 } 3400 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3401 } 3402 a->ibdiagvalid = PETSC_TRUE; 3403 PetscFunctionReturn(0); 3404 } 3405 3406 #undef __FUNCT__ 3407 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3408 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3409 { 3410 PetscErrorCode ierr; 3411 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3412 PetscScalar a; 3413 PetscInt m,n,i,j,col; 3414 3415 PetscFunctionBegin; 3416 if (!x->assembled) { 3417 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3418 for (i=0; i<m; i++) { 3419 for (j=0; j<aij->imax[i]; j++) { 3420 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3421 col = (PetscInt)(n*PetscRealPart(a)); 3422 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3423 } 3424 } 3425 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3426 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3427 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3428 PetscFunctionReturn(0); 3429 } 3430 3431 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3432 /* -------------------------------------------------------------------*/ 3433 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3434 MatGetRow_SeqAIJ, 3435 MatRestoreRow_SeqAIJ, 3436 MatMult_SeqAIJ, 3437 /* 4*/ MatMultAdd_SeqAIJ, 3438 MatMultTranspose_SeqAIJ, 3439 MatMultTransposeAdd_SeqAIJ, 3440 0, 3441 0, 3442 0, 3443 /* 10*/ 0, 3444 MatLUFactor_SeqAIJ, 3445 0, 3446 MatSOR_SeqAIJ, 3447 MatTranspose_SeqAIJ, 3448 /*1 5*/ MatGetInfo_SeqAIJ, 3449 MatEqual_SeqAIJ, 3450 MatGetDiagonal_SeqAIJ, 3451 MatDiagonalScale_SeqAIJ, 3452 MatNorm_SeqAIJ, 3453 /* 20*/ 0, 3454 MatAssemblyEnd_SeqAIJ, 3455 MatSetOption_SeqAIJ, 3456 MatZeroEntries_SeqAIJ, 3457 /* 24*/ MatZeroRows_SeqAIJ, 3458 0, 3459 0, 3460 0, 3461 0, 3462 /* 29*/ MatSetUp_SeqAIJ, 3463 0, 3464 0, 3465 0, 3466 0, 3467 /* 34*/ MatDuplicate_SeqAIJ, 3468 0, 3469 0, 3470 MatILUFactor_SeqAIJ, 3471 0, 3472 /* 39*/ MatAXPY_SeqAIJ, 3473 MatGetSubMatrices_SeqAIJ, 3474 MatIncreaseOverlap_SeqAIJ, 3475 MatGetValues_SeqAIJ, 3476 MatCopy_SeqAIJ, 3477 /* 44*/ MatGetRowMax_SeqAIJ, 3478 MatScale_SeqAIJ, 3479 0, 3480 MatDiagonalSet_SeqAIJ, 3481 MatZeroRowsColumns_SeqAIJ, 3482 /* 49*/ MatSetRandom_SeqAIJ, 3483 MatGetRowIJ_SeqAIJ, 3484 MatRestoreRowIJ_SeqAIJ, 3485 MatGetColumnIJ_SeqAIJ, 3486 MatRestoreColumnIJ_SeqAIJ, 3487 /* 54*/ MatFDColoringCreate_SeqAIJ, 3488 0, 3489 0, 3490 MatPermute_SeqAIJ, 3491 0, 3492 /* 59*/ 0, 3493 MatDestroy_SeqAIJ, 3494 MatView_SeqAIJ, 3495 0, 3496 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3497 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3498 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3499 0, 3500 0, 3501 0, 3502 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3503 MatGetRowMinAbs_SeqAIJ, 3504 0, 3505 MatSetColoring_SeqAIJ, 3506 0, 3507 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3508 MatFDColoringApply_AIJ, 3509 0, 3510 0, 3511 0, 3512 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3513 0, 3514 0, 3515 0, 3516 MatLoad_SeqAIJ, 3517 /* 84*/ MatIsSymmetric_SeqAIJ, 3518 MatIsHermitian_SeqAIJ, 3519 0, 3520 0, 3521 0, 3522 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3523 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3524 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3525 MatPtAP_SeqAIJ_SeqAIJ, 3526 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3527 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3528 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3529 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3530 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3531 0, 3532 /* 99*/ 0, 3533 0, 3534 0, 3535 MatConjugate_SeqAIJ, 3536 0, 3537 /*104*/ MatSetValuesRow_SeqAIJ, 3538 MatRealPart_SeqAIJ, 3539 MatImaginaryPart_SeqAIJ, 3540 0, 3541 0, 3542 /*109*/ MatMatSolve_SeqAIJ, 3543 0, 3544 MatGetRowMin_SeqAIJ, 3545 0, 3546 MatMissingDiagonal_SeqAIJ, 3547 /*114*/ 0, 3548 0, 3549 0, 3550 0, 3551 0, 3552 /*119*/ 0, 3553 0, 3554 0, 3555 0, 3556 MatGetMultiProcBlock_SeqAIJ, 3557 /*124*/ MatFindNonzeroRows_SeqAIJ, 3558 MatGetColumnNorms_SeqAIJ, 3559 MatInvertBlockDiagonal_SeqAIJ, 3560 0, 3561 0, 3562 /*129*/ 0, 3563 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3564 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3565 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3566 MatTransposeColoringCreate_SeqAIJ, 3567 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3568 MatTransColoringApplyDenToSp_SeqAIJ, 3569 MatRARt_SeqAIJ_SeqAIJ, 3570 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3571 MatRARtNumeric_SeqAIJ_SeqAIJ, 3572 /*139*/0, 3573 0 3574 }; 3575 3576 #undef __FUNCT__ 3577 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3578 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3579 { 3580 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3581 PetscInt i,nz,n; 3582 3583 PetscFunctionBegin; 3584 nz = aij->maxnz; 3585 n = mat->rmap->n; 3586 for (i=0; i<nz; i++) { 3587 aij->j[i] = indices[i]; 3588 } 3589 aij->nz = nz; 3590 for (i=0; i<n; i++) { 3591 aij->ilen[i] = aij->imax[i]; 3592 } 3593 PetscFunctionReturn(0); 3594 } 3595 3596 #undef __FUNCT__ 3597 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3598 /*@ 3599 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3600 in the matrix. 3601 3602 Input Parameters: 3603 + mat - the SeqAIJ matrix 3604 - indices - the column indices 3605 3606 Level: advanced 3607 3608 Notes: 3609 This can be called if you have precomputed the nonzero structure of the 3610 matrix and want to provide it to the matrix object to improve the performance 3611 of the MatSetValues() operation. 3612 3613 You MUST have set the correct numbers of nonzeros per row in the call to 3614 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3615 3616 MUST be called before any calls to MatSetValues(); 3617 3618 The indices should start with zero, not one. 3619 3620 @*/ 3621 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3622 { 3623 PetscErrorCode ierr; 3624 3625 PetscFunctionBegin; 3626 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3627 PetscValidPointer(indices,2); 3628 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3629 PetscFunctionReturn(0); 3630 } 3631 3632 /* ----------------------------------------------------------------------------------------*/ 3633 3634 #undef __FUNCT__ 3635 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3636 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3637 { 3638 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3639 PetscErrorCode ierr; 3640 size_t nz = aij->i[mat->rmap->n]; 3641 3642 PetscFunctionBegin; 3643 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3644 3645 /* allocate space for values if not already there */ 3646 if (!aij->saved_values) { 3647 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 3648 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3649 } 3650 3651 /* copy values over */ 3652 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3653 PetscFunctionReturn(0); 3654 } 3655 3656 #undef __FUNCT__ 3657 #define __FUNCT__ "MatStoreValues" 3658 /*@ 3659 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3660 example, reuse of the linear part of a Jacobian, while recomputing the 3661 nonlinear portion. 3662 3663 Collect on Mat 3664 3665 Input Parameters: 3666 . mat - the matrix (currently only AIJ matrices support this option) 3667 3668 Level: advanced 3669 3670 Common Usage, with SNESSolve(): 3671 $ Create Jacobian matrix 3672 $ Set linear terms into matrix 3673 $ Apply boundary conditions to matrix, at this time matrix must have 3674 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3675 $ boundary conditions again will not change the nonzero structure 3676 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3677 $ ierr = MatStoreValues(mat); 3678 $ Call SNESSetJacobian() with matrix 3679 $ In your Jacobian routine 3680 $ ierr = MatRetrieveValues(mat); 3681 $ Set nonlinear terms in matrix 3682 3683 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3684 $ // build linear portion of Jacobian 3685 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3686 $ ierr = MatStoreValues(mat); 3687 $ loop over nonlinear iterations 3688 $ ierr = MatRetrieveValues(mat); 3689 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3690 $ // call MatAssemblyBegin/End() on matrix 3691 $ Solve linear system with Jacobian 3692 $ endloop 3693 3694 Notes: 3695 Matrix must already be assemblied before calling this routine 3696 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3697 calling this routine. 3698 3699 When this is called multiple times it overwrites the previous set of stored values 3700 and does not allocated additional space. 3701 3702 .seealso: MatRetrieveValues() 3703 3704 @*/ 3705 PetscErrorCode MatStoreValues(Mat mat) 3706 { 3707 PetscErrorCode ierr; 3708 3709 PetscFunctionBegin; 3710 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3711 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3712 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3713 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3714 PetscFunctionReturn(0); 3715 } 3716 3717 #undef __FUNCT__ 3718 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3719 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3720 { 3721 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3722 PetscErrorCode ierr; 3723 PetscInt nz = aij->i[mat->rmap->n]; 3724 3725 PetscFunctionBegin; 3726 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3727 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3728 /* copy values over */ 3729 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3730 PetscFunctionReturn(0); 3731 } 3732 3733 #undef __FUNCT__ 3734 #define __FUNCT__ "MatRetrieveValues" 3735 /*@ 3736 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3737 example, reuse of the linear part of a Jacobian, while recomputing the 3738 nonlinear portion. 3739 3740 Collect on Mat 3741 3742 Input Parameters: 3743 . mat - the matrix (currently on AIJ matrices support this option) 3744 3745 Level: advanced 3746 3747 .seealso: MatStoreValues() 3748 3749 @*/ 3750 PetscErrorCode MatRetrieveValues(Mat mat) 3751 { 3752 PetscErrorCode ierr; 3753 3754 PetscFunctionBegin; 3755 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3756 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3757 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3758 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3759 PetscFunctionReturn(0); 3760 } 3761 3762 3763 /* --------------------------------------------------------------------------------*/ 3764 #undef __FUNCT__ 3765 #define __FUNCT__ "MatCreateSeqAIJ" 3766 /*@C 3767 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3768 (the default parallel PETSc format). For good matrix assembly performance 3769 the user should preallocate the matrix storage by setting the parameter nz 3770 (or the array nnz). By setting these parameters accurately, performance 3771 during matrix assembly can be increased by more than a factor of 50. 3772 3773 Collective on MPI_Comm 3774 3775 Input Parameters: 3776 + comm - MPI communicator, set to PETSC_COMM_SELF 3777 . m - number of rows 3778 . n - number of columns 3779 . nz - number of nonzeros per row (same for all rows) 3780 - nnz - array containing the number of nonzeros in the various rows 3781 (possibly different for each row) or NULL 3782 3783 Output Parameter: 3784 . A - the matrix 3785 3786 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3787 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3788 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3789 3790 Notes: 3791 If nnz is given then nz is ignored 3792 3793 The AIJ format (also called the Yale sparse matrix format or 3794 compressed row storage), is fully compatible with standard Fortran 77 3795 storage. That is, the stored row and column indices can begin at 3796 either one (as in Fortran) or zero. See the users' manual for details. 3797 3798 Specify the preallocated storage with either nz or nnz (not both). 3799 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3800 allocation. For large problems you MUST preallocate memory or you 3801 will get TERRIBLE performance, see the users' manual chapter on matrices. 3802 3803 By default, this format uses inodes (identical nodes) when possible, to 3804 improve numerical efficiency of matrix-vector products and solves. We 3805 search for consecutive rows with the same nonzero structure, thereby 3806 reusing matrix information to achieve increased efficiency. 3807 3808 Options Database Keys: 3809 + -mat_no_inode - Do not use inodes 3810 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3811 3812 Level: intermediate 3813 3814 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3815 3816 @*/ 3817 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3818 { 3819 PetscErrorCode ierr; 3820 3821 PetscFunctionBegin; 3822 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3823 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3824 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3825 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3826 PetscFunctionReturn(0); 3827 } 3828 3829 #undef __FUNCT__ 3830 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3831 /*@C 3832 MatSeqAIJSetPreallocation - For good matrix assembly performance 3833 the user should preallocate the matrix storage by setting the parameter nz 3834 (or the array nnz). By setting these parameters accurately, performance 3835 during matrix assembly can be increased by more than a factor of 50. 3836 3837 Collective on MPI_Comm 3838 3839 Input Parameters: 3840 + B - The matrix-free 3841 . nz - number of nonzeros per row (same for all rows) 3842 - nnz - array containing the number of nonzeros in the various rows 3843 (possibly different for each row) or NULL 3844 3845 Notes: 3846 If nnz is given then nz is ignored 3847 3848 The AIJ format (also called the Yale sparse matrix format or 3849 compressed row storage), is fully compatible with standard Fortran 77 3850 storage. That is, the stored row and column indices can begin at 3851 either one (as in Fortran) or zero. See the users' manual for details. 3852 3853 Specify the preallocated storage with either nz or nnz (not both). 3854 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3855 allocation. For large problems you MUST preallocate memory or you 3856 will get TERRIBLE performance, see the users' manual chapter on matrices. 3857 3858 You can call MatGetInfo() to get information on how effective the preallocation was; 3859 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3860 You can also run with the option -info and look for messages with the string 3861 malloc in them to see if additional memory allocation was needed. 3862 3863 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3864 entries or columns indices 3865 3866 By default, this format uses inodes (identical nodes) when possible, to 3867 improve numerical efficiency of matrix-vector products and solves. We 3868 search for consecutive rows with the same nonzero structure, thereby 3869 reusing matrix information to achieve increased efficiency. 3870 3871 Options Database Keys: 3872 + -mat_no_inode - Do not use inodes 3873 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3874 - -mat_aij_oneindex - Internally use indexing starting at 1 3875 rather than 0. Note that when calling MatSetValues(), 3876 the user still MUST index entries starting at 0! 3877 3878 Level: intermediate 3879 3880 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3881 3882 @*/ 3883 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3884 { 3885 PetscErrorCode ierr; 3886 3887 PetscFunctionBegin; 3888 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3889 PetscValidType(B,1); 3890 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3891 PetscFunctionReturn(0); 3892 } 3893 3894 #undef __FUNCT__ 3895 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3896 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3897 { 3898 Mat_SeqAIJ *b; 3899 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3900 PetscErrorCode ierr; 3901 PetscInt i; 3902 3903 PetscFunctionBegin; 3904 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3905 if (nz == MAT_SKIP_ALLOCATION) { 3906 skipallocation = PETSC_TRUE; 3907 nz = 0; 3908 } 3909 3910 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3911 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3912 3913 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3914 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3915 if (nnz) { 3916 for (i=0; i<B->rmap->n; i++) { 3917 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]); 3918 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); 3919 } 3920 } 3921 3922 B->preallocated = PETSC_TRUE; 3923 3924 b = (Mat_SeqAIJ*)B->data; 3925 3926 if (!skipallocation) { 3927 if (!b->imax) { 3928 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3929 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3930 } 3931 if (!nnz) { 3932 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3933 else if (nz < 0) nz = 1; 3934 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3935 nz = nz*B->rmap->n; 3936 } else { 3937 nz = 0; 3938 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3939 } 3940 /* b->ilen will count nonzeros in each row so far. */ 3941 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3942 3943 /* allocate the matrix space */ 3944 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3945 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3946 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3947 b->i[0] = 0; 3948 for (i=1; i<B->rmap->n+1; i++) { 3949 b->i[i] = b->i[i-1] + b->imax[i-1]; 3950 } 3951 b->singlemalloc = PETSC_TRUE; 3952 b->free_a = PETSC_TRUE; 3953 b->free_ij = PETSC_TRUE; 3954 #if defined(PETSC_THREADCOMM_ACTIVE) 3955 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3956 #endif 3957 } else { 3958 b->free_a = PETSC_FALSE; 3959 b->free_ij = PETSC_FALSE; 3960 } 3961 3962 b->nz = 0; 3963 b->maxnz = nz; 3964 B->info.nz_unneeded = (double)b->maxnz; 3965 if (realalloc) { 3966 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3967 } 3968 PetscFunctionReturn(0); 3969 } 3970 3971 #undef __FUNCT__ 3972 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3973 /*@ 3974 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3975 3976 Input Parameters: 3977 + B - the matrix 3978 . i - the indices into j for the start of each row (starts with zero) 3979 . j - the column indices for each row (starts with zero) these must be sorted for each row 3980 - v - optional values in the matrix 3981 3982 Level: developer 3983 3984 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3985 3986 .keywords: matrix, aij, compressed row, sparse, sequential 3987 3988 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3989 @*/ 3990 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3991 { 3992 PetscErrorCode ierr; 3993 3994 PetscFunctionBegin; 3995 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3996 PetscValidType(B,1); 3997 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 3998 PetscFunctionReturn(0); 3999 } 4000 4001 #undef __FUNCT__ 4002 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 4003 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 4004 { 4005 PetscInt i; 4006 PetscInt m,n; 4007 PetscInt nz; 4008 PetscInt *nnz, nz_max = 0; 4009 PetscScalar *values; 4010 PetscErrorCode ierr; 4011 4012 PetscFunctionBegin; 4013 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 4014 4015 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4016 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4017 4018 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 4019 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 4020 for (i = 0; i < m; i++) { 4021 nz = Ii[i+1]- Ii[i]; 4022 nz_max = PetscMax(nz_max, nz); 4023 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 4024 nnz[i] = nz; 4025 } 4026 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 4027 ierr = PetscFree(nnz);CHKERRQ(ierr); 4028 4029 if (v) { 4030 values = (PetscScalar*) v; 4031 } else { 4032 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 4033 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 4034 } 4035 4036 for (i = 0; i < m; i++) { 4037 nz = Ii[i+1] - Ii[i]; 4038 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 4039 } 4040 4041 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4042 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4043 4044 if (!v) { 4045 ierr = PetscFree(values);CHKERRQ(ierr); 4046 } 4047 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4048 PetscFunctionReturn(0); 4049 } 4050 4051 #include <../src/mat/impls/dense/seq/dense.h> 4052 #include <petsc-private/kernels/petscaxpy.h> 4053 4054 #undef __FUNCT__ 4055 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 4056 /* 4057 Computes (B'*A')' since computing B*A directly is untenable 4058 4059 n p p 4060 ( ) ( ) ( ) 4061 m ( A ) * n ( B ) = m ( C ) 4062 ( ) ( ) ( ) 4063 4064 */ 4065 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4066 { 4067 PetscErrorCode ierr; 4068 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4069 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4070 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4071 PetscInt i,n,m,q,p; 4072 const PetscInt *ii,*idx; 4073 const PetscScalar *b,*a,*a_q; 4074 PetscScalar *c,*c_q; 4075 4076 PetscFunctionBegin; 4077 m = A->rmap->n; 4078 n = A->cmap->n; 4079 p = B->cmap->n; 4080 a = sub_a->v; 4081 b = sub_b->a; 4082 c = sub_c->v; 4083 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 4084 4085 ii = sub_b->i; 4086 idx = sub_b->j; 4087 for (i=0; i<n; i++) { 4088 q = ii[i+1] - ii[i]; 4089 while (q-->0) { 4090 c_q = c + m*(*idx); 4091 a_q = a + m*i; 4092 PetscKernelAXPY(c_q,*b,a_q,m); 4093 idx++; 4094 b++; 4095 } 4096 } 4097 PetscFunctionReturn(0); 4098 } 4099 4100 #undef __FUNCT__ 4101 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 4102 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4103 { 4104 PetscErrorCode ierr; 4105 PetscInt m=A->rmap->n,n=B->cmap->n; 4106 Mat Cmat; 4107 4108 PetscFunctionBegin; 4109 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); 4110 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4111 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4112 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 4113 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4114 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4115 4116 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4117 4118 *C = Cmat; 4119 PetscFunctionReturn(0); 4120 } 4121 4122 /* ----------------------------------------------------------------*/ 4123 #undef __FUNCT__ 4124 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 4125 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4126 { 4127 PetscErrorCode ierr; 4128 4129 PetscFunctionBegin; 4130 if (scall == MAT_INITIAL_MATRIX) { 4131 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4132 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4133 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4134 } 4135 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4136 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4137 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4138 PetscFunctionReturn(0); 4139 } 4140 4141 4142 /*MC 4143 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4144 based on compressed sparse row format. 4145 4146 Options Database Keys: 4147 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4148 4149 Level: beginner 4150 4151 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4152 M*/ 4153 4154 /*MC 4155 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4156 4157 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4158 and MATMPIAIJ otherwise. As a result, for single process communicators, 4159 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 4160 for communicators controlling multiple processes. It is recommended that you call both of 4161 the above preallocation routines for simplicity. 4162 4163 Options Database Keys: 4164 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4165 4166 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 4167 enough exist. 4168 4169 Level: beginner 4170 4171 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4172 M*/ 4173 4174 /*MC 4175 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4176 4177 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4178 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4179 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4180 for communicators controlling multiple processes. It is recommended that you call both of 4181 the above preallocation routines for simplicity. 4182 4183 Options Database Keys: 4184 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4185 4186 Level: beginner 4187 4188 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4189 M*/ 4190 4191 #if defined(PETSC_HAVE_PASTIX) 4192 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 4193 #endif 4194 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4195 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 4196 #endif 4197 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4198 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 4199 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 4200 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 4201 #if defined(PETSC_HAVE_MUMPS) 4202 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 4203 #endif 4204 #if defined(PETSC_HAVE_SUPERLU) 4205 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 4206 #endif 4207 #if defined(PETSC_HAVE_SUPERLU_DIST) 4208 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 4209 #endif 4210 #if defined(PETSC_HAVE_UMFPACK) 4211 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 4212 #endif 4213 #if defined(PETSC_HAVE_CHOLMOD) 4214 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 4215 #endif 4216 #if defined(PETSC_HAVE_LUSOL) 4217 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 4218 #endif 4219 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4220 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 4221 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 4222 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 4223 #endif 4224 #if defined(PETSC_HAVE_CLIQUE) 4225 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 4226 #endif 4227 4228 4229 #undef __FUNCT__ 4230 #define __FUNCT__ "MatSeqAIJGetArray" 4231 /*@C 4232 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 4233 4234 Not Collective 4235 4236 Input Parameter: 4237 . mat - a MATSEQDENSE matrix 4238 4239 Output Parameter: 4240 . array - pointer to the data 4241 4242 Level: intermediate 4243 4244 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4245 @*/ 4246 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4247 { 4248 PetscErrorCode ierr; 4249 4250 PetscFunctionBegin; 4251 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4252 PetscFunctionReturn(0); 4253 } 4254 4255 #undef __FUNCT__ 4256 #define __FUNCT__ "MatSeqAIJRestoreArray" 4257 /*@C 4258 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4259 4260 Not Collective 4261 4262 Input Parameters: 4263 . mat - a MATSEQDENSE matrix 4264 . array - pointer to the data 4265 4266 Level: intermediate 4267 4268 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4269 @*/ 4270 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4271 { 4272 PetscErrorCode ierr; 4273 4274 PetscFunctionBegin; 4275 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4276 PetscFunctionReturn(0); 4277 } 4278 4279 #undef __FUNCT__ 4280 #define __FUNCT__ "MatCreate_SeqAIJ" 4281 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4282 { 4283 Mat_SeqAIJ *b; 4284 PetscErrorCode ierr; 4285 PetscMPIInt size; 4286 4287 PetscFunctionBegin; 4288 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4289 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4290 4291 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 4292 4293 B->data = (void*)b; 4294 4295 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4296 4297 b->row = 0; 4298 b->col = 0; 4299 b->icol = 0; 4300 b->reallocs = 0; 4301 b->ignorezeroentries = PETSC_FALSE; 4302 b->roworiented = PETSC_TRUE; 4303 b->nonew = 0; 4304 b->diag = 0; 4305 b->solve_work = 0; 4306 B->spptr = 0; 4307 b->saved_values = 0; 4308 b->idiag = 0; 4309 b->mdiag = 0; 4310 b->ssor_work = 0; 4311 b->omega = 1.0; 4312 b->fshift = 0.0; 4313 b->idiagvalid = PETSC_FALSE; 4314 b->ibdiagvalid = PETSC_FALSE; 4315 b->keepnonzeropattern = PETSC_FALSE; 4316 b->xtoy = 0; 4317 b->XtoY = 0; 4318 B->same_nonzero = PETSC_FALSE; 4319 4320 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4321 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4322 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4323 4324 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4325 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4326 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4327 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4328 #endif 4329 #if defined(PETSC_HAVE_PASTIX) 4330 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4331 #endif 4332 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4333 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4334 #endif 4335 #if defined(PETSC_HAVE_SUPERLU) 4336 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4337 #endif 4338 #if defined(PETSC_HAVE_SUPERLU_DIST) 4339 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4340 #endif 4341 #if defined(PETSC_HAVE_MUMPS) 4342 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4343 #endif 4344 #if defined(PETSC_HAVE_UMFPACK) 4345 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4346 #endif 4347 #if defined(PETSC_HAVE_CHOLMOD) 4348 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4349 #endif 4350 #if defined(PETSC_HAVE_LUSOL) 4351 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4352 #endif 4353 #if defined(PETSC_HAVE_CLIQUE) 4354 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4355 #endif 4356 4357 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4358 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4359 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4360 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4361 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4362 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4363 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4364 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4365 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4366 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4367 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4368 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4369 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4370 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4371 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4372 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4373 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4374 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4375 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4376 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4377 PetscFunctionReturn(0); 4378 } 4379 4380 #undef __FUNCT__ 4381 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4382 /* 4383 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4384 */ 4385 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4386 { 4387 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4388 PetscErrorCode ierr; 4389 PetscInt i,m = A->rmap->n; 4390 4391 PetscFunctionBegin; 4392 c = (Mat_SeqAIJ*)C->data; 4393 4394 C->factortype = A->factortype; 4395 c->row = 0; 4396 c->col = 0; 4397 c->icol = 0; 4398 c->reallocs = 0; 4399 4400 C->assembled = PETSC_TRUE; 4401 4402 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4403 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4404 4405 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 4406 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4407 for (i=0; i<m; i++) { 4408 c->imax[i] = a->imax[i]; 4409 c->ilen[i] = a->ilen[i]; 4410 } 4411 4412 /* allocate the matrix space */ 4413 if (mallocmatspace) { 4414 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 4415 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4416 4417 c->singlemalloc = PETSC_TRUE; 4418 4419 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4420 if (m > 0) { 4421 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4422 if (cpvalues == MAT_COPY_VALUES) { 4423 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4424 } else { 4425 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4426 } 4427 } 4428 } 4429 4430 c->ignorezeroentries = a->ignorezeroentries; 4431 c->roworiented = a->roworiented; 4432 c->nonew = a->nonew; 4433 if (a->diag) { 4434 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 4435 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4436 for (i=0; i<m; i++) { 4437 c->diag[i] = a->diag[i]; 4438 } 4439 } else c->diag = 0; 4440 4441 c->solve_work = 0; 4442 c->saved_values = 0; 4443 c->idiag = 0; 4444 c->ssor_work = 0; 4445 c->keepnonzeropattern = a->keepnonzeropattern; 4446 c->free_a = PETSC_TRUE; 4447 c->free_ij = PETSC_TRUE; 4448 c->xtoy = 0; 4449 c->XtoY = 0; 4450 4451 c->rmax = a->rmax; 4452 c->nz = a->nz; 4453 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4454 C->preallocated = PETSC_TRUE; 4455 4456 c->compressedrow.use = a->compressedrow.use; 4457 c->compressedrow.nrows = a->compressedrow.nrows; 4458 c->compressedrow.check = a->compressedrow.check; 4459 if (a->compressedrow.use) { 4460 i = a->compressedrow.nrows; 4461 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 4462 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4463 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4464 } else { 4465 c->compressedrow.use = PETSC_FALSE; 4466 c->compressedrow.i = NULL; 4467 c->compressedrow.rindex = NULL; 4468 } 4469 C->same_nonzero = A->same_nonzero; 4470 4471 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4472 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4473 PetscFunctionReturn(0); 4474 } 4475 4476 #undef __FUNCT__ 4477 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4478 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4479 { 4480 PetscErrorCode ierr; 4481 4482 PetscFunctionBegin; 4483 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4484 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4485 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4486 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4487 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4488 PetscFunctionReturn(0); 4489 } 4490 4491 #undef __FUNCT__ 4492 #define __FUNCT__ "MatLoad_SeqAIJ" 4493 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4494 { 4495 Mat_SeqAIJ *a; 4496 PetscErrorCode ierr; 4497 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4498 int fd; 4499 PetscMPIInt size; 4500 MPI_Comm comm; 4501 PetscInt bs = 1; 4502 4503 PetscFunctionBegin; 4504 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4505 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4506 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4507 4508 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4509 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4510 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4511 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4512 4513 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4514 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4515 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4516 M = header[1]; N = header[2]; nz = header[3]; 4517 4518 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4519 4520 /* read in row lengths */ 4521 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 4522 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4523 4524 /* check if sum of rowlengths is same as nz */ 4525 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4526 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); 4527 4528 /* set global size if not set already*/ 4529 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4530 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4531 } else { 4532 /* if sizes and type are already set, check if the vector global sizes are correct */ 4533 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4534 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4535 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4536 } 4537 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); 4538 } 4539 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4540 a = (Mat_SeqAIJ*)newMat->data; 4541 4542 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4543 4544 /* read in nonzero values */ 4545 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4546 4547 /* set matrix "i" values */ 4548 a->i[0] = 0; 4549 for (i=1; i<= M; i++) { 4550 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4551 a->ilen[i-1] = rowlengths[i-1]; 4552 } 4553 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4554 4555 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4556 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4557 PetscFunctionReturn(0); 4558 } 4559 4560 #undef __FUNCT__ 4561 #define __FUNCT__ "MatEqual_SeqAIJ" 4562 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4563 { 4564 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4565 PetscErrorCode ierr; 4566 #if defined(PETSC_USE_COMPLEX) 4567 PetscInt k; 4568 #endif 4569 4570 PetscFunctionBegin; 4571 /* If the matrix dimensions are not equal,or no of nonzeros */ 4572 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4573 *flg = PETSC_FALSE; 4574 PetscFunctionReturn(0); 4575 } 4576 4577 /* if the a->i are the same */ 4578 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4579 if (!*flg) PetscFunctionReturn(0); 4580 4581 /* if a->j are the same */ 4582 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4583 if (!*flg) PetscFunctionReturn(0); 4584 4585 /* if a->a are the same */ 4586 #if defined(PETSC_USE_COMPLEX) 4587 for (k=0; k<a->nz; k++) { 4588 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4589 *flg = PETSC_FALSE; 4590 PetscFunctionReturn(0); 4591 } 4592 } 4593 #else 4594 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4595 #endif 4596 PetscFunctionReturn(0); 4597 } 4598 4599 #undef __FUNCT__ 4600 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4601 /*@ 4602 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4603 provided by the user. 4604 4605 Collective on MPI_Comm 4606 4607 Input Parameters: 4608 + comm - must be an MPI communicator of size 1 4609 . m - number of rows 4610 . n - number of columns 4611 . i - row indices 4612 . j - column indices 4613 - a - matrix values 4614 4615 Output Parameter: 4616 . mat - the matrix 4617 4618 Level: intermediate 4619 4620 Notes: 4621 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4622 once the matrix is destroyed and not before 4623 4624 You cannot set new nonzero locations into this matrix, that will generate an error. 4625 4626 The i and j indices are 0 based 4627 4628 The format which is used for the sparse matrix input, is equivalent to a 4629 row-major ordering.. i.e for the following matrix, the input data expected is 4630 as shown: 4631 4632 1 0 0 4633 2 0 3 4634 4 5 6 4635 4636 i = {0,1,3,6} [size = nrow+1 = 3+1] 4637 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4638 v = {1,2,3,4,5,6} [size = nz = 6] 4639 4640 4641 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4642 4643 @*/ 4644 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4645 { 4646 PetscErrorCode ierr; 4647 PetscInt ii; 4648 Mat_SeqAIJ *aij; 4649 #if defined(PETSC_USE_DEBUG) 4650 PetscInt jj; 4651 #endif 4652 4653 PetscFunctionBegin; 4654 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4655 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4656 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4657 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4658 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4659 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4660 aij = (Mat_SeqAIJ*)(*mat)->data; 4661 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 4662 4663 aij->i = i; 4664 aij->j = j; 4665 aij->a = a; 4666 aij->singlemalloc = PETSC_FALSE; 4667 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4668 aij->free_a = PETSC_FALSE; 4669 aij->free_ij = PETSC_FALSE; 4670 4671 for (ii=0; ii<m; ii++) { 4672 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4673 #if defined(PETSC_USE_DEBUG) 4674 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]); 4675 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4676 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); 4677 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); 4678 } 4679 #endif 4680 } 4681 #if defined(PETSC_USE_DEBUG) 4682 for (ii=0; ii<aij->i[m]; ii++) { 4683 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 4684 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]); 4685 } 4686 #endif 4687 4688 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4689 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4690 PetscFunctionReturn(0); 4691 } 4692 #undef __FUNCT__ 4693 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4694 /*@C 4695 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4696 provided by the user. 4697 4698 Collective on MPI_Comm 4699 4700 Input Parameters: 4701 + comm - must be an MPI communicator of size 1 4702 . m - number of rows 4703 . n - number of columns 4704 . i - row indices 4705 . j - column indices 4706 . a - matrix values 4707 . nz - number of nonzeros 4708 - idx - 0 or 1 based 4709 4710 Output Parameter: 4711 . mat - the matrix 4712 4713 Level: intermediate 4714 4715 Notes: 4716 The i and j indices are 0 based 4717 4718 The format which is used for the sparse matrix input, is equivalent to a 4719 row-major ordering.. i.e for the following matrix, the input data expected is 4720 as shown: 4721 4722 1 0 0 4723 2 0 3 4724 4 5 6 4725 4726 i = {0,1,1,2,2,2} 4727 j = {0,0,2,0,1,2} 4728 v = {1,2,3,4,5,6} 4729 4730 4731 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4732 4733 @*/ 4734 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4735 { 4736 PetscErrorCode ierr; 4737 PetscInt ii, *nnz, one = 1,row,col; 4738 4739 4740 PetscFunctionBegin; 4741 ierr = PetscMalloc(m*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 4742 ierr = PetscMemzero(nnz,m*sizeof(PetscInt));CHKERRQ(ierr); 4743 for (ii = 0; ii < nz; ii++) { 4744 nnz[i[ii]] += 1; 4745 } 4746 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4747 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4748 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4749 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4750 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4751 for (ii = 0; ii < nz; ii++) { 4752 if (idx) { 4753 row = i[ii] - 1; 4754 col = j[ii] - 1; 4755 } else { 4756 row = i[ii]; 4757 col = j[ii]; 4758 } 4759 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4760 } 4761 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4762 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4763 ierr = PetscFree(nnz);CHKERRQ(ierr); 4764 PetscFunctionReturn(0); 4765 } 4766 4767 #undef __FUNCT__ 4768 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4769 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4770 { 4771 PetscErrorCode ierr; 4772 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4773 4774 PetscFunctionBegin; 4775 if (coloring->ctype == IS_COLORING_GLOBAL) { 4776 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4777 a->coloring = coloring; 4778 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4779 PetscInt i,*larray; 4780 ISColoring ocoloring; 4781 ISColoringValue *colors; 4782 4783 /* set coloring for diagonal portion */ 4784 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4785 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4786 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4787 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4788 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4789 ierr = PetscFree(larray);CHKERRQ(ierr); 4790 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4791 a->coloring = ocoloring; 4792 } 4793 PetscFunctionReturn(0); 4794 } 4795 4796 #undef __FUNCT__ 4797 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4798 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4799 { 4800 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4801 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4802 MatScalar *v = a->a; 4803 PetscScalar *values = (PetscScalar*)advalues; 4804 ISColoringValue *color; 4805 4806 PetscFunctionBegin; 4807 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4808 color = a->coloring->colors; 4809 /* loop over rows */ 4810 for (i=0; i<m; i++) { 4811 nz = ii[i+1] - ii[i]; 4812 /* loop over columns putting computed value into matrix */ 4813 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4814 values += nl; /* jump to next row of derivatives */ 4815 } 4816 PetscFunctionReturn(0); 4817 } 4818 4819 #undef __FUNCT__ 4820 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4821 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4822 { 4823 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4824 PetscErrorCode ierr; 4825 4826 PetscFunctionBegin; 4827 a->idiagvalid = PETSC_FALSE; 4828 a->ibdiagvalid = PETSC_FALSE; 4829 4830 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4831 PetscFunctionReturn(0); 4832 } 4833 4834 /* 4835 Special version for direct calls from Fortran 4836 */ 4837 #include <petsc-private/fortranimpl.h> 4838 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4839 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4840 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4841 #define matsetvaluesseqaij_ matsetvaluesseqaij 4842 #endif 4843 4844 /* Change these macros so can be used in void function */ 4845 #undef CHKERRQ 4846 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4847 #undef SETERRQ2 4848 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4849 #undef SETERRQ3 4850 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4851 4852 #undef __FUNCT__ 4853 #define __FUNCT__ "matsetvaluesseqaij_" 4854 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) 4855 { 4856 Mat A = *AA; 4857 PetscInt m = *mm, n = *nn; 4858 InsertMode is = *isis; 4859 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4860 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4861 PetscInt *imax,*ai,*ailen; 4862 PetscErrorCode ierr; 4863 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4864 MatScalar *ap,value,*aa; 4865 PetscBool ignorezeroentries = a->ignorezeroentries; 4866 PetscBool roworiented = a->roworiented; 4867 4868 PetscFunctionBegin; 4869 MatCheckPreallocated(A,1); 4870 imax = a->imax; 4871 ai = a->i; 4872 ailen = a->ilen; 4873 aj = a->j; 4874 aa = a->a; 4875 4876 for (k=0; k<m; k++) { /* loop over added rows */ 4877 row = im[k]; 4878 if (row < 0) continue; 4879 #if defined(PETSC_USE_DEBUG) 4880 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4881 #endif 4882 rp = aj + ai[row]; ap = aa + ai[row]; 4883 rmax = imax[row]; nrow = ailen[row]; 4884 low = 0; 4885 high = nrow; 4886 for (l=0; l<n; l++) { /* loop over added columns */ 4887 if (in[l] < 0) continue; 4888 #if defined(PETSC_USE_DEBUG) 4889 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4890 #endif 4891 col = in[l]; 4892 if (roworiented) value = v[l + k*n]; 4893 else value = v[k + l*m]; 4894 4895 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4896 4897 if (col <= lastcol) low = 0; 4898 else high = nrow; 4899 lastcol = col; 4900 while (high-low > 5) { 4901 t = (low+high)/2; 4902 if (rp[t] > col) high = t; 4903 else low = t; 4904 } 4905 for (i=low; i<high; i++) { 4906 if (rp[i] > col) break; 4907 if (rp[i] == col) { 4908 if (is == ADD_VALUES) ap[i] += value; 4909 else ap[i] = value; 4910 goto noinsert; 4911 } 4912 } 4913 if (value == 0.0 && ignorezeroentries) goto noinsert; 4914 if (nonew == 1) goto noinsert; 4915 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4916 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4917 N = nrow++ - 1; a->nz++; high++; 4918 /* shift up all the later entries in this row */ 4919 for (ii=N; ii>=i; ii--) { 4920 rp[ii+1] = rp[ii]; 4921 ap[ii+1] = ap[ii]; 4922 } 4923 rp[i] = col; 4924 ap[i] = value; 4925 noinsert:; 4926 low = i + 1; 4927 } 4928 ailen[row] = nrow; 4929 } 4930 A->same_nonzero = PETSC_FALSE; 4931 PetscFunctionReturnVoid(); 4932 } 4933 4934 4935