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 //const PetscInt *colorforrow=coloring->colorforrow,*colorforcolumn=coloring->colorforcolumn; 2738 PetscInt *den2sp=coloring->den2sp,*idx,idx_tmp; 2739 PetscInt **columns=coloring->columns,ncolumns_k,nrows_k; 2740 #if defined(JACOBIANCOLOROPT) 2741 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; 2742 #endif 2743 PetscInt nz; 2744 2745 PetscFunctionBegin; 2746 #if defined(JACOBIANCOLOROPT) 2747 ierr = PetscTime(&t0);CHKERRQ(ierr); 2748 #endif 2749 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2750 ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2751 if (flg) { 2752 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2753 } else { 2754 PetscBool assembled; 2755 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2756 if (assembled) { 2757 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2758 } 2759 } 2760 2761 if (!coloring->vscale) { 2762 ierr = VecDuplicate(x1,&coloring->vscale);CHKERRQ(ierr); 2763 } 2764 2765 if (coloring->htype[0] == 'w') { /* tacky test; need to make systematic if we add other approaches to computing h*/ 2766 ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr); 2767 } 2768 #if defined(JACOBIANCOLOROPT) 2769 ierr = PetscTime(&t1);CHKERRQ(ierr); 2770 t_init += t1 - t0; 2771 #endif 2772 2773 /* Set w1 = F(x1) */ 2774 #if defined(JACOBIANCOLOROPT) 2775 ierr = PetscTime(&t0);CHKERRQ(ierr); 2776 #endif 2777 if (!coloring->fset) { 2778 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2779 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2780 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2781 } else { 2782 coloring->fset = PETSC_FALSE; 2783 } 2784 #if defined(JACOBIANCOLOROPT) 2785 ierr = PetscTime(&t1);CHKERRQ(ierr); 2786 t_setvals += t1 - t0; 2787 #endif 2788 2789 #if defined(JACOBIANCOLOROPT) 2790 ierr = PetscTime(&t0);CHKERRQ(ierr); 2791 #endif 2792 if (!coloring->w3) { 2793 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2794 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2795 } 2796 w3 = coloring->w3; 2797 2798 /* Compute scale factors: vscale = 1./dx = 1./(epsilon*xx) */ 2799 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr); 2800 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2801 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2802 for (col=0; col<N; col++) { 2803 if (coloring->htype[0] == 'w') { 2804 dx = 1.0 + unorm; 2805 } else { 2806 dx = xx[col]; 2807 } 2808 if (dx == (PetscScalar)0.0) dx = 1.0; 2809 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2810 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2811 dx *= epsilon; 2812 vscale_array[col] = (PetscScalar)dx; 2813 } 2814 #if defined(JACOBIANCOLOROPT) 2815 ierr = PetscTime(&t1);CHKERRQ(ierr); 2816 t_init += t1 - t0; 2817 #endif 2818 2819 idx = den2sp; 2820 nz = 0; 2821 for (k=0; k<ncolors; k++) { /* loop over colors */ 2822 #if defined(JACOBIANCOLOROPT) 2823 ierr = PetscTime(&t0);CHKERRQ(ierr); 2824 #endif 2825 coloring->currentcolor = k; 2826 2827 /* 2828 Loop over each column associated with color 2829 adding the perturbation to the vector w3 = x1 + dx. 2830 */ 2831 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2832 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr); 2833 ncolumns_k = ncolumns[k]; 2834 for (l=0; l<ncolumns_k; l++) { /* loop over columns */ 2835 col = columns[k][l]; 2836 w3_array[col] += vscale_array[col]; 2837 } 2838 ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2839 #if defined(JACOBIANCOLOROPT) 2840 ierr = PetscTime(&t1);CHKERRQ(ierr); 2841 t_dx += t1 - t0; 2842 #endif 2843 2844 /* 2845 Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations) 2846 w2 = F(x1 + dx) - F(x1) 2847 */ 2848 #if defined(JACOBIANCOLOROPT) 2849 ierr = PetscTime(&t0);CHKERRQ(ierr); 2850 #endif 2851 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2852 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2853 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2854 #if defined(JACOBIANCOLOROPT) 2855 ierr = PetscTime(&t1);CHKERRQ(ierr); 2856 t_func += t1 - t0; 2857 #endif 2858 2859 #if defined(JACOBIANCOLOROPT) 2860 ierr = PetscTime(&t0);CHKERRQ(ierr); 2861 #endif 2862 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2863 2864 /* 2865 Loop over rows of vector, putting w2/dx into Jacobian matrix 2866 */ 2867 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2868 nrows_k = nrows[k]; 2869 for (l=0; l<nrows_k; l++) { /* loop over rows */ 2870 #if defined(JACOBIANCOLOROPT) 2871 ierr = PetscTime(&t00);CHKERRQ(ierr); 2872 #endif 2873 row = coloring->rowcolden2sp3[3*nz]; 2874 col = coloring->rowcolden2sp3[3*nz+1]; 2875 idx_tmp = coloring->rowcolden2sp3[3*nz+2]; 2876 #if defined(JACOBIANCOLOROPT) 2877 ierr = PetscTime(&t11);CHKERRQ(ierr); 2878 t_kl += t11 - t00; 2879 #endif 2880 //ca[idx[l]] = y[row]/vscale_array[col]; 2881 ca[idx_tmp] = y[row]/vscale_array[col]; 2882 nz++; 2883 } 2884 idx += nrows_k; 2885 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2886 2887 #if defined(JACOBIANCOLOROPT) 2888 ierr = PetscTime(&t1);CHKERRQ(ierr); 2889 t_setvals += t1 - t0; 2890 #endif 2891 } /* endof for each color */ 2892 #if defined(JACOBIANCOLOROPT) 2893 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); 2894 printf(" FDColorApply time: kl %g\n",t_kl); 2895 #endif 2896 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2897 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2898 2899 coloring->currentcolor = -1; 2900 PetscFunctionReturn(0); 2901 } 2902 /* --------------------------------------------------------*/ 2903 2904 #undef __FUNCT__ 2905 #define __FUNCT__ "MatFDColoringApply_SeqAIJ_old" 2906 PetscErrorCode MatFDColoringApply_SeqAIJ_old(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2907 { 2908 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f; 2909 PetscErrorCode ierr; 2910 PetscInt k,N,start,end,l,row,col,srow,**vscaleforrow; 2911 PetscScalar dx,*y,*xx,*w3_array; 2912 PetscScalar *vscale_array; 2913 PetscReal epsilon = coloring->error_rel,umin = coloring->umin; 2914 Vec w1,w2,w3; 2915 void *fctx = coloring->fctx; 2916 PetscBool flg = PETSC_FALSE; 2917 2918 PetscFunctionBegin; 2919 printf("MatFDColoringApply_SeqAIJ ...\n"); 2920 if (!coloring->w1) { 2921 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 2922 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w1);CHKERRQ(ierr); 2923 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 2924 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w2);CHKERRQ(ierr); 2925 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2926 ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr); 2927 } 2928 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 2929 2930 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2931 ierr = PetscOptionsGetBool(((PetscObject)coloring)->prefix,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr); 2932 if (flg) { 2933 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2934 } else { 2935 PetscBool assembled; 2936 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2937 if (assembled) { 2938 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2939 } 2940 } 2941 2942 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 2943 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2944 2945 if (!coloring->fset) { 2946 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2947 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2948 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2949 } else { 2950 coloring->fset = PETSC_FALSE; 2951 } 2952 2953 /* 2954 Compute all the scale factors and share with other processors 2955 */ 2956 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start; 2957 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start; 2958 for (k=0; k<coloring->ncolors; k++) { 2959 /* 2960 Loop over each column associated with color adding the 2961 perturbation to the vector w3. 2962 */ 2963 for (l=0; l<coloring->ncolumns[k]; l++) { 2964 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2965 dx = xx[col]; 2966 if (dx == 0.0) dx = 1.0; 2967 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2968 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2969 dx *= epsilon; 2970 vscale_array[col] = 1.0/dx; 2971 } 2972 } 2973 vscale_array = vscale_array + start; 2974 2975 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2976 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2977 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2978 2979 /* ierr = VecView(coloring->vscale,PETSC_VIEWER_STDOUT_WORLD); 2980 ierr = VecView(x1,PETSC_VIEWER_STDOUT_WORLD);*/ 2981 2982 if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow; 2983 else vscaleforrow = coloring->columnsforrow; 2984 2985 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2986 /* 2987 Loop over each color 2988 */ 2989 for (k=0; k<coloring->ncolors; k++) { 2990 coloring->currentcolor = k; 2991 2992 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2993 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start; 2994 /* 2995 Loop over each column associated with color adding the 2996 perturbation to the vector w3. 2997 */ 2998 for (l=0; l<coloring->ncolumns[k]; l++) { 2999 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 3000 dx = xx[col]; 3001 if (dx == 0.0) dx = 1.0; 3002 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 3003 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 3004 dx *= epsilon; 3005 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 3006 w3_array[col] += dx; 3007 } 3008 w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 3009 3010 /* 3011 Evaluate function at x1 + dx (here dx is a vector of perturbations) 3012 */ 3013 3014 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 3015 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 3016 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 3017 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 3018 3019 /* 3020 Loop over rows of vector, putting results into Jacobian matrix 3021 */ 3022 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 3023 for (l=0; l<coloring->nrows[k]; l++) { 3024 row = coloring->rows[k][l]; 3025 col = coloring->columnsforrow[k][l]; 3026 y[row] *= vscale_array[vscaleforrow[k][l]]; 3027 srow = row + start; 3028 ierr = MatSetValues_SeqAIJ(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 3029 } 3030 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 3031 } 3032 coloring->currentcolor = k; 3033 3034 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 3035 xx = xx + start; 3036 ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 3037 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3038 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3039 PetscFunctionReturn(0); 3040 } 3041 3042 /* 3043 Computes the number of nonzeros per row needed for preallocation when X and Y 3044 have different nonzero structure. 3045 */ 3046 #undef __FUNCT__ 3047 #define __FUNCT__ "MatAXPYGetPreallocation_SeqAIJ" 3048 PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat Y,Mat X,PetscInt *nnz) 3049 { 3050 PetscInt i,m=Y->rmap->N; 3051 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 3052 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 3053 const PetscInt *xi = x->i,*yi = y->i; 3054 3055 PetscFunctionBegin; 3056 /* Set the number of nonzeros in the new matrix */ 3057 for (i=0; i<m; i++) { 3058 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 3059 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 3060 nnz[i] = 0; 3061 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 3062 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 3063 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 3064 nnz[i]++; 3065 } 3066 for (; k<nzy; k++) nnz[i]++; 3067 } 3068 PetscFunctionReturn(0); 3069 } 3070 3071 #undef __FUNCT__ 3072 #define __FUNCT__ "MatAXPY_SeqAIJ" 3073 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 3074 { 3075 PetscErrorCode ierr; 3076 PetscInt i; 3077 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; 3078 PetscBLASInt one=1,bnz; 3079 3080 PetscFunctionBegin; 3081 ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); 3082 if (str == SAME_NONZERO_PATTERN) { 3083 PetscScalar alpha = a; 3084 PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); 3085 ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); 3086 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 3087 if (y->xtoy && y->XtoY != X) { 3088 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 3089 ierr = MatDestroy(&y->XtoY);CHKERRQ(ierr); 3090 } 3091 if (!y->xtoy) { /* get xtoy */ 3092 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,NULL, y->i,y->j,NULL, &y->xtoy);CHKERRQ(ierr); 3093 y->XtoY = X; 3094 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 3095 } 3096 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 3097 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); 3098 } else { 3099 Mat B; 3100 PetscInt *nnz; 3101 ierr = PetscMalloc(Y->rmap->N*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 3102 ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); 3103 ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); 3104 ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); 3105 ierr = MatSetBlockSizes(B,Y->rmap->bs,Y->cmap->bs);CHKERRQ(ierr); 3106 ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); 3107 ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); 3108 ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); 3109 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 3110 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 3111 ierr = PetscFree(nnz);CHKERRQ(ierr); 3112 } 3113 PetscFunctionReturn(0); 3114 } 3115 3116 #undef __FUNCT__ 3117 #define __FUNCT__ "MatConjugate_SeqAIJ" 3118 PetscErrorCode MatConjugate_SeqAIJ(Mat mat) 3119 { 3120 #if defined(PETSC_USE_COMPLEX) 3121 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3122 PetscInt i,nz; 3123 PetscScalar *a; 3124 3125 PetscFunctionBegin; 3126 nz = aij->nz; 3127 a = aij->a; 3128 for (i=0; i<nz; i++) a[i] = PetscConj(a[i]); 3129 #else 3130 PetscFunctionBegin; 3131 #endif 3132 PetscFunctionReturn(0); 3133 } 3134 3135 #undef __FUNCT__ 3136 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 3137 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3138 { 3139 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3140 PetscErrorCode ierr; 3141 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3142 PetscReal atmp; 3143 PetscScalar *x; 3144 MatScalar *aa; 3145 3146 PetscFunctionBegin; 3147 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3148 aa = a->a; 3149 ai = a->i; 3150 aj = a->j; 3151 3152 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3153 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3154 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3155 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3156 for (i=0; i<m; i++) { 3157 ncols = ai[1] - ai[0]; ai++; 3158 x[i] = 0.0; 3159 for (j=0; j<ncols; j++) { 3160 atmp = PetscAbsScalar(*aa); 3161 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3162 aa++; aj++; 3163 } 3164 } 3165 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3166 PetscFunctionReturn(0); 3167 } 3168 3169 #undef __FUNCT__ 3170 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 3171 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3172 { 3173 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3174 PetscErrorCode ierr; 3175 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3176 PetscScalar *x; 3177 MatScalar *aa; 3178 3179 PetscFunctionBegin; 3180 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3181 aa = a->a; 3182 ai = a->i; 3183 aj = a->j; 3184 3185 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3186 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3187 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3188 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3189 for (i=0; i<m; i++) { 3190 ncols = ai[1] - ai[0]; ai++; 3191 if (ncols == A->cmap->n) { /* row is dense */ 3192 x[i] = *aa; if (idx) idx[i] = 0; 3193 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 3194 x[i] = 0.0; 3195 if (idx) { 3196 idx[i] = 0; /* in case ncols is zero */ 3197 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 3198 if (aj[j] > j) { 3199 idx[i] = j; 3200 break; 3201 } 3202 } 3203 } 3204 } 3205 for (j=0; j<ncols; j++) { 3206 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3207 aa++; aj++; 3208 } 3209 } 3210 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3211 PetscFunctionReturn(0); 3212 } 3213 3214 #undef __FUNCT__ 3215 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 3216 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3217 { 3218 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3219 PetscErrorCode ierr; 3220 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3221 PetscReal atmp; 3222 PetscScalar *x; 3223 MatScalar *aa; 3224 3225 PetscFunctionBegin; 3226 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3227 aa = a->a; 3228 ai = a->i; 3229 aj = a->j; 3230 3231 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3232 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3233 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3234 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); 3235 for (i=0; i<m; i++) { 3236 ncols = ai[1] - ai[0]; ai++; 3237 if (ncols) { 3238 /* Get first nonzero */ 3239 for (j = 0; j < ncols; j++) { 3240 atmp = PetscAbsScalar(aa[j]); 3241 if (atmp > 1.0e-12) { 3242 x[i] = atmp; 3243 if (idx) idx[i] = aj[j]; 3244 break; 3245 } 3246 } 3247 if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} 3248 } else { 3249 x[i] = 0.0; if (idx) idx[i] = 0; 3250 } 3251 for (j = 0; j < ncols; j++) { 3252 atmp = PetscAbsScalar(*aa); 3253 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 3254 aa++; aj++; 3255 } 3256 } 3257 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3258 PetscFunctionReturn(0); 3259 } 3260 3261 #undef __FUNCT__ 3262 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 3263 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 3264 { 3265 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3266 PetscErrorCode ierr; 3267 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 3268 PetscScalar *x; 3269 MatScalar *aa; 3270 3271 PetscFunctionBegin; 3272 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3273 aa = a->a; 3274 ai = a->i; 3275 aj = a->j; 3276 3277 ierr = VecSet(v,0.0);CHKERRQ(ierr); 3278 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 3279 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 3280 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 3281 for (i=0; i<m; i++) { 3282 ncols = ai[1] - ai[0]; ai++; 3283 if (ncols == A->cmap->n) { /* row is dense */ 3284 x[i] = *aa; if (idx) idx[i] = 0; 3285 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 3286 x[i] = 0.0; 3287 if (idx) { /* find first implicit 0.0 in the row */ 3288 idx[i] = 0; /* in case ncols is zero */ 3289 for (j=0; j<ncols; j++) { 3290 if (aj[j] > j) { 3291 idx[i] = j; 3292 break; 3293 } 3294 } 3295 } 3296 } 3297 for (j=0; j<ncols; j++) { 3298 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 3299 aa++; aj++; 3300 } 3301 } 3302 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 3303 PetscFunctionReturn(0); 3304 } 3305 3306 #include <petscblaslapack.h> 3307 #include <petsc-private/kernels/blockinvert.h> 3308 3309 #undef __FUNCT__ 3310 #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" 3311 PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) 3312 { 3313 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 3314 PetscErrorCode ierr; 3315 PetscInt i,bs = A->rmap->bs,mbs = A->rmap->n/A->rmap->bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; 3316 MatScalar *diag,work[25],*v_work; 3317 PetscReal shift = 0.0; 3318 3319 PetscFunctionBegin; 3320 if (a->ibdiagvalid) { 3321 if (values) *values = a->ibdiag; 3322 PetscFunctionReturn(0); 3323 } 3324 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 3325 if (!a->ibdiag) { 3326 ierr = PetscMalloc(bs2*mbs*sizeof(PetscScalar),&a->ibdiag);CHKERRQ(ierr); 3327 ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); 3328 } 3329 diag = a->ibdiag; 3330 if (values) *values = a->ibdiag; 3331 /* factor and invert each block */ 3332 switch (bs) { 3333 case 1: 3334 for (i=0; i<mbs; i++) { 3335 ierr = MatGetValues(A,1,&i,1,&i,diag+i);CHKERRQ(ierr); 3336 diag[i] = (PetscScalar)1.0 / (diag[i] + shift); 3337 } 3338 break; 3339 case 2: 3340 for (i=0; i<mbs; i++) { 3341 ij[0] = 2*i; ij[1] = 2*i + 1; 3342 ierr = MatGetValues(A,2,ij,2,ij,diag);CHKERRQ(ierr); 3343 ierr = PetscKernel_A_gets_inverse_A_2(diag,shift);CHKERRQ(ierr); 3344 ierr = PetscKernel_A_gets_transpose_A_2(diag);CHKERRQ(ierr); 3345 diag += 4; 3346 } 3347 break; 3348 case 3: 3349 for (i=0; i<mbs; i++) { 3350 ij[0] = 3*i; ij[1] = 3*i + 1; ij[2] = 3*i + 2; 3351 ierr = MatGetValues(A,3,ij,3,ij,diag);CHKERRQ(ierr); 3352 ierr = PetscKernel_A_gets_inverse_A_3(diag,shift);CHKERRQ(ierr); 3353 ierr = PetscKernel_A_gets_transpose_A_3(diag);CHKERRQ(ierr); 3354 diag += 9; 3355 } 3356 break; 3357 case 4: 3358 for (i=0; i<mbs; i++) { 3359 ij[0] = 4*i; ij[1] = 4*i + 1; ij[2] = 4*i + 2; ij[3] = 4*i + 3; 3360 ierr = MatGetValues(A,4,ij,4,ij,diag);CHKERRQ(ierr); 3361 ierr = PetscKernel_A_gets_inverse_A_4(diag,shift);CHKERRQ(ierr); 3362 ierr = PetscKernel_A_gets_transpose_A_4(diag);CHKERRQ(ierr); 3363 diag += 16; 3364 } 3365 break; 3366 case 5: 3367 for (i=0; i<mbs; i++) { 3368 ij[0] = 5*i; ij[1] = 5*i + 1; ij[2] = 5*i + 2; ij[3] = 5*i + 3; ij[4] = 5*i + 4; 3369 ierr = MatGetValues(A,5,ij,5,ij,diag);CHKERRQ(ierr); 3370 ierr = PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift);CHKERRQ(ierr); 3371 ierr = PetscKernel_A_gets_transpose_A_5(diag);CHKERRQ(ierr); 3372 diag += 25; 3373 } 3374 break; 3375 case 6: 3376 for (i=0; i<mbs; i++) { 3377 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; 3378 ierr = MatGetValues(A,6,ij,6,ij,diag);CHKERRQ(ierr); 3379 ierr = PetscKernel_A_gets_inverse_A_6(diag,shift);CHKERRQ(ierr); 3380 ierr = PetscKernel_A_gets_transpose_A_6(diag);CHKERRQ(ierr); 3381 diag += 36; 3382 } 3383 break; 3384 case 7: 3385 for (i=0; i<mbs; i++) { 3386 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; 3387 ierr = MatGetValues(A,7,ij,7,ij,diag);CHKERRQ(ierr); 3388 ierr = PetscKernel_A_gets_inverse_A_7(diag,shift);CHKERRQ(ierr); 3389 ierr = PetscKernel_A_gets_transpose_A_7(diag);CHKERRQ(ierr); 3390 diag += 49; 3391 } 3392 break; 3393 default: 3394 ierr = PetscMalloc3(bs,MatScalar,&v_work,bs,PetscInt,&v_pivots,bs,PetscInt,&IJ);CHKERRQ(ierr); 3395 for (i=0; i<mbs; i++) { 3396 for (j=0; j<bs; j++) { 3397 IJ[j] = bs*i + j; 3398 } 3399 ierr = MatGetValues(A,bs,IJ,bs,IJ,diag);CHKERRQ(ierr); 3400 ierr = PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work);CHKERRQ(ierr); 3401 ierr = PetscKernel_A_gets_transpose_A_N(diag,bs);CHKERRQ(ierr); 3402 diag += bs2; 3403 } 3404 ierr = PetscFree3(v_work,v_pivots,IJ);CHKERRQ(ierr); 3405 } 3406 a->ibdiagvalid = PETSC_TRUE; 3407 PetscFunctionReturn(0); 3408 } 3409 3410 #undef __FUNCT__ 3411 #define __FUNCT__ "MatSetRandom_SeqAIJ" 3412 static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) 3413 { 3414 PetscErrorCode ierr; 3415 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; 3416 PetscScalar a; 3417 PetscInt m,n,i,j,col; 3418 3419 PetscFunctionBegin; 3420 if (!x->assembled) { 3421 ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); 3422 for (i=0; i<m; i++) { 3423 for (j=0; j<aij->imax[i]; j++) { 3424 ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); 3425 col = (PetscInt)(n*PetscRealPart(a)); 3426 ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); 3427 } 3428 } 3429 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); 3430 ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3431 ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3432 PetscFunctionReturn(0); 3433 } 3434 3435 extern PetscErrorCode MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 3436 /* -------------------------------------------------------------------*/ 3437 static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, 3438 MatGetRow_SeqAIJ, 3439 MatRestoreRow_SeqAIJ, 3440 MatMult_SeqAIJ, 3441 /* 4*/ MatMultAdd_SeqAIJ, 3442 MatMultTranspose_SeqAIJ, 3443 MatMultTransposeAdd_SeqAIJ, 3444 0, 3445 0, 3446 0, 3447 /* 10*/ 0, 3448 MatLUFactor_SeqAIJ, 3449 0, 3450 MatSOR_SeqAIJ, 3451 MatTranspose_SeqAIJ, 3452 /*1 5*/ MatGetInfo_SeqAIJ, 3453 MatEqual_SeqAIJ, 3454 MatGetDiagonal_SeqAIJ, 3455 MatDiagonalScale_SeqAIJ, 3456 MatNorm_SeqAIJ, 3457 /* 20*/ 0, 3458 MatAssemblyEnd_SeqAIJ, 3459 MatSetOption_SeqAIJ, 3460 MatZeroEntries_SeqAIJ, 3461 /* 24*/ MatZeroRows_SeqAIJ, 3462 0, 3463 0, 3464 0, 3465 0, 3466 /* 29*/ MatSetUp_SeqAIJ, 3467 0, 3468 0, 3469 0, 3470 0, 3471 /* 34*/ MatDuplicate_SeqAIJ, 3472 0, 3473 0, 3474 MatILUFactor_SeqAIJ, 3475 0, 3476 /* 39*/ MatAXPY_SeqAIJ, 3477 MatGetSubMatrices_SeqAIJ, 3478 MatIncreaseOverlap_SeqAIJ, 3479 MatGetValues_SeqAIJ, 3480 MatCopy_SeqAIJ, 3481 /* 44*/ MatGetRowMax_SeqAIJ, 3482 MatScale_SeqAIJ, 3483 0, 3484 MatDiagonalSet_SeqAIJ, 3485 MatZeroRowsColumns_SeqAIJ, 3486 /* 49*/ MatSetRandom_SeqAIJ, 3487 MatGetRowIJ_SeqAIJ, 3488 MatRestoreRowIJ_SeqAIJ, 3489 MatGetColumnIJ_SeqAIJ, 3490 MatRestoreColumnIJ_SeqAIJ, 3491 /* 54*/ MatFDColoringCreate_SeqAIJ, 3492 0, 3493 0, 3494 MatPermute_SeqAIJ, 3495 0, 3496 /* 59*/ 0, 3497 MatDestroy_SeqAIJ, 3498 MatView_SeqAIJ, 3499 0, 3500 MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, 3501 /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, 3502 MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 3503 0, 3504 0, 3505 0, 3506 /* 69*/ MatGetRowMaxAbs_SeqAIJ, 3507 MatGetRowMinAbs_SeqAIJ, 3508 0, 3509 MatSetColoring_SeqAIJ, 3510 0, 3511 /* 74*/ MatSetValuesAdifor_SeqAIJ, 3512 MatFDColoringApply_AIJ, 3513 0, 3514 0, 3515 0, 3516 /* 79*/ MatFindZeroDiagonals_SeqAIJ, 3517 0, 3518 0, 3519 0, 3520 MatLoad_SeqAIJ, 3521 /* 84*/ MatIsSymmetric_SeqAIJ, 3522 MatIsHermitian_SeqAIJ, 3523 0, 3524 0, 3525 0, 3526 /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, 3527 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 3528 MatMatMultNumeric_SeqAIJ_SeqAIJ, 3529 MatPtAP_SeqAIJ_SeqAIJ, 3530 MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, 3531 /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 3532 MatMatTransposeMult_SeqAIJ_SeqAIJ, 3533 MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, 3534 MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 3535 0, 3536 /* 99*/ 0, 3537 0, 3538 0, 3539 MatConjugate_SeqAIJ, 3540 0, 3541 /*104*/ MatSetValuesRow_SeqAIJ, 3542 MatRealPart_SeqAIJ, 3543 MatImaginaryPart_SeqAIJ, 3544 0, 3545 0, 3546 /*109*/ MatMatSolve_SeqAIJ, 3547 0, 3548 MatGetRowMin_SeqAIJ, 3549 0, 3550 MatMissingDiagonal_SeqAIJ, 3551 /*114*/ 0, 3552 0, 3553 0, 3554 0, 3555 0, 3556 /*119*/ 0, 3557 0, 3558 0, 3559 0, 3560 MatGetMultiProcBlock_SeqAIJ, 3561 /*124*/ MatFindNonzeroRows_SeqAIJ, 3562 MatGetColumnNorms_SeqAIJ, 3563 MatInvertBlockDiagonal_SeqAIJ, 3564 0, 3565 0, 3566 /*129*/ 0, 3567 MatTransposeMatMult_SeqAIJ_SeqAIJ, 3568 MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, 3569 MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, 3570 MatTransposeColoringCreate_SeqAIJ, 3571 /*134*/ MatTransColoringApplySpToDen_SeqAIJ, 3572 MatTransColoringApplyDenToSp_SeqAIJ, 3573 MatRARt_SeqAIJ_SeqAIJ, 3574 MatRARtSymbolic_SeqAIJ_SeqAIJ, 3575 MatRARtNumeric_SeqAIJ_SeqAIJ, 3576 /*139*/0, 3577 0 3578 }; 3579 3580 #undef __FUNCT__ 3581 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 3582 PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 3583 { 3584 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3585 PetscInt i,nz,n; 3586 3587 PetscFunctionBegin; 3588 nz = aij->maxnz; 3589 n = mat->rmap->n; 3590 for (i=0; i<nz; i++) { 3591 aij->j[i] = indices[i]; 3592 } 3593 aij->nz = nz; 3594 for (i=0; i<n; i++) { 3595 aij->ilen[i] = aij->imax[i]; 3596 } 3597 PetscFunctionReturn(0); 3598 } 3599 3600 #undef __FUNCT__ 3601 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 3602 /*@ 3603 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 3604 in the matrix. 3605 3606 Input Parameters: 3607 + mat - the SeqAIJ matrix 3608 - indices - the column indices 3609 3610 Level: advanced 3611 3612 Notes: 3613 This can be called if you have precomputed the nonzero structure of the 3614 matrix and want to provide it to the matrix object to improve the performance 3615 of the MatSetValues() operation. 3616 3617 You MUST have set the correct numbers of nonzeros per row in the call to 3618 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 3619 3620 MUST be called before any calls to MatSetValues(); 3621 3622 The indices should start with zero, not one. 3623 3624 @*/ 3625 PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 3626 { 3627 PetscErrorCode ierr; 3628 3629 PetscFunctionBegin; 3630 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3631 PetscValidPointer(indices,2); 3632 ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); 3633 PetscFunctionReturn(0); 3634 } 3635 3636 /* ----------------------------------------------------------------------------------------*/ 3637 3638 #undef __FUNCT__ 3639 #define __FUNCT__ "MatStoreValues_SeqAIJ" 3640 PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) 3641 { 3642 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3643 PetscErrorCode ierr; 3644 size_t nz = aij->i[mat->rmap->n]; 3645 3646 PetscFunctionBegin; 3647 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3648 3649 /* allocate space for values if not already there */ 3650 if (!aij->saved_values) { 3651 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 3652 ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 3653 } 3654 3655 /* copy values over */ 3656 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3657 PetscFunctionReturn(0); 3658 } 3659 3660 #undef __FUNCT__ 3661 #define __FUNCT__ "MatStoreValues" 3662 /*@ 3663 MatStoreValues - Stashes a copy of the matrix values; this allows, for 3664 example, reuse of the linear part of a Jacobian, while recomputing the 3665 nonlinear portion. 3666 3667 Collect on Mat 3668 3669 Input Parameters: 3670 . mat - the matrix (currently only AIJ matrices support this option) 3671 3672 Level: advanced 3673 3674 Common Usage, with SNESSolve(): 3675 $ Create Jacobian matrix 3676 $ Set linear terms into matrix 3677 $ Apply boundary conditions to matrix, at this time matrix must have 3678 $ final nonzero structure (i.e. setting the nonlinear terms and applying 3679 $ boundary conditions again will not change the nonzero structure 3680 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3681 $ ierr = MatStoreValues(mat); 3682 $ Call SNESSetJacobian() with matrix 3683 $ In your Jacobian routine 3684 $ ierr = MatRetrieveValues(mat); 3685 $ Set nonlinear terms in matrix 3686 3687 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 3688 $ // build linear portion of Jacobian 3689 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 3690 $ ierr = MatStoreValues(mat); 3691 $ loop over nonlinear iterations 3692 $ ierr = MatRetrieveValues(mat); 3693 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 3694 $ // call MatAssemblyBegin/End() on matrix 3695 $ Solve linear system with Jacobian 3696 $ endloop 3697 3698 Notes: 3699 Matrix must already be assemblied before calling this routine 3700 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 3701 calling this routine. 3702 3703 When this is called multiple times it overwrites the previous set of stored values 3704 and does not allocated additional space. 3705 3706 .seealso: MatRetrieveValues() 3707 3708 @*/ 3709 PetscErrorCode MatStoreValues(Mat mat) 3710 { 3711 PetscErrorCode ierr; 3712 3713 PetscFunctionBegin; 3714 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3715 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3716 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3717 ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); 3718 PetscFunctionReturn(0); 3719 } 3720 3721 #undef __FUNCT__ 3722 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 3723 PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) 3724 { 3725 Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; 3726 PetscErrorCode ierr; 3727 PetscInt nz = aij->i[mat->rmap->n]; 3728 3729 PetscFunctionBegin; 3730 if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 3731 if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 3732 /* copy values over */ 3733 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 3734 PetscFunctionReturn(0); 3735 } 3736 3737 #undef __FUNCT__ 3738 #define __FUNCT__ "MatRetrieveValues" 3739 /*@ 3740 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 3741 example, reuse of the linear part of a Jacobian, while recomputing the 3742 nonlinear portion. 3743 3744 Collect on Mat 3745 3746 Input Parameters: 3747 . mat - the matrix (currently on AIJ matrices support this option) 3748 3749 Level: advanced 3750 3751 .seealso: MatStoreValues() 3752 3753 @*/ 3754 PetscErrorCode MatRetrieveValues(Mat mat) 3755 { 3756 PetscErrorCode ierr; 3757 3758 PetscFunctionBegin; 3759 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 3760 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 3761 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 3762 ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); 3763 PetscFunctionReturn(0); 3764 } 3765 3766 3767 /* --------------------------------------------------------------------------------*/ 3768 #undef __FUNCT__ 3769 #define __FUNCT__ "MatCreateSeqAIJ" 3770 /*@C 3771 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 3772 (the default parallel PETSc format). For good matrix assembly performance 3773 the user should preallocate the matrix storage by setting the parameter nz 3774 (or the array nnz). By setting these parameters accurately, performance 3775 during matrix assembly can be increased by more than a factor of 50. 3776 3777 Collective on MPI_Comm 3778 3779 Input Parameters: 3780 + comm - MPI communicator, set to PETSC_COMM_SELF 3781 . m - number of rows 3782 . n - number of columns 3783 . nz - number of nonzeros per row (same for all rows) 3784 - nnz - array containing the number of nonzeros in the various rows 3785 (possibly different for each row) or NULL 3786 3787 Output Parameter: 3788 . A - the matrix 3789 3790 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 3791 MatXXXXSetPreallocation() paradgm instead of this routine directly. 3792 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 3793 3794 Notes: 3795 If nnz is given then nz is ignored 3796 3797 The AIJ format (also called the Yale sparse matrix format or 3798 compressed row storage), is fully compatible with standard Fortran 77 3799 storage. That is, the stored row and column indices can begin at 3800 either one (as in Fortran) or zero. See the users' manual for details. 3801 3802 Specify the preallocated storage with either nz or nnz (not both). 3803 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3804 allocation. For large problems you MUST preallocate memory or you 3805 will get TERRIBLE performance, see the users' manual chapter on matrices. 3806 3807 By default, this format uses inodes (identical nodes) when possible, to 3808 improve numerical efficiency of matrix-vector products and solves. We 3809 search for consecutive rows with the same nonzero structure, thereby 3810 reusing matrix information to achieve increased efficiency. 3811 3812 Options Database Keys: 3813 + -mat_no_inode - Do not use inodes 3814 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3815 3816 Level: intermediate 3817 3818 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 3819 3820 @*/ 3821 PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 3822 { 3823 PetscErrorCode ierr; 3824 3825 PetscFunctionBegin; 3826 ierr = MatCreate(comm,A);CHKERRQ(ierr); 3827 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 3828 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 3829 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 3830 PetscFunctionReturn(0); 3831 } 3832 3833 #undef __FUNCT__ 3834 #define __FUNCT__ "MatSeqAIJSetPreallocation" 3835 /*@C 3836 MatSeqAIJSetPreallocation - For good matrix assembly performance 3837 the user should preallocate the matrix storage by setting the parameter nz 3838 (or the array nnz). By setting these parameters accurately, performance 3839 during matrix assembly can be increased by more than a factor of 50. 3840 3841 Collective on MPI_Comm 3842 3843 Input Parameters: 3844 + B - The matrix-free 3845 . nz - number of nonzeros per row (same for all rows) 3846 - nnz - array containing the number of nonzeros in the various rows 3847 (possibly different for each row) or NULL 3848 3849 Notes: 3850 If nnz is given then nz is ignored 3851 3852 The AIJ format (also called the Yale sparse matrix format or 3853 compressed row storage), is fully compatible with standard Fortran 77 3854 storage. That is, the stored row and column indices can begin at 3855 either one (as in Fortran) or zero. See the users' manual for details. 3856 3857 Specify the preallocated storage with either nz or nnz (not both). 3858 Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory 3859 allocation. For large problems you MUST preallocate memory or you 3860 will get TERRIBLE performance, see the users' manual chapter on matrices. 3861 3862 You can call MatGetInfo() to get information on how effective the preallocation was; 3863 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3864 You can also run with the option -info and look for messages with the string 3865 malloc in them to see if additional memory allocation was needed. 3866 3867 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3868 entries or columns indices 3869 3870 By default, this format uses inodes (identical nodes) when possible, to 3871 improve numerical efficiency of matrix-vector products and solves. We 3872 search for consecutive rows with the same nonzero structure, thereby 3873 reusing matrix information to achieve increased efficiency. 3874 3875 Options Database Keys: 3876 + -mat_no_inode - Do not use inodes 3877 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3878 - -mat_aij_oneindex - Internally use indexing starting at 1 3879 rather than 0. Note that when calling MatSetValues(), 3880 the user still MUST index entries starting at 0! 3881 3882 Level: intermediate 3883 3884 .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3885 3886 @*/ 3887 PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3888 { 3889 PetscErrorCode ierr; 3890 3891 PetscFunctionBegin; 3892 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3893 PetscValidType(B,1); 3894 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); 3895 PetscFunctionReturn(0); 3896 } 3897 3898 #undef __FUNCT__ 3899 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3900 PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3901 { 3902 Mat_SeqAIJ *b; 3903 PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; 3904 PetscErrorCode ierr; 3905 PetscInt i; 3906 3907 PetscFunctionBegin; 3908 if (nz >= 0 || nnz) realalloc = PETSC_TRUE; 3909 if (nz == MAT_SKIP_ALLOCATION) { 3910 skipallocation = PETSC_TRUE; 3911 nz = 0; 3912 } 3913 3914 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3915 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3916 3917 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3918 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3919 if (nnz) { 3920 for (i=0; i<B->rmap->n; i++) { 3921 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]); 3922 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); 3923 } 3924 } 3925 3926 B->preallocated = PETSC_TRUE; 3927 3928 b = (Mat_SeqAIJ*)B->data; 3929 3930 if (!skipallocation) { 3931 if (!b->imax) { 3932 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3933 ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3934 } 3935 if (!nnz) { 3936 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3937 else if (nz < 0) nz = 1; 3938 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3939 nz = nz*B->rmap->n; 3940 } else { 3941 nz = 0; 3942 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3943 } 3944 /* b->ilen will count nonzeros in each row so far. */ 3945 for (i=0; i<B->rmap->n; i++) b->ilen[i] = 0; 3946 3947 /* allocate the matrix space */ 3948 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3949 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3950 ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3951 b->i[0] = 0; 3952 for (i=1; i<B->rmap->n+1; i++) { 3953 b->i[i] = b->i[i-1] + b->imax[i-1]; 3954 } 3955 b->singlemalloc = PETSC_TRUE; 3956 b->free_a = PETSC_TRUE; 3957 b->free_ij = PETSC_TRUE; 3958 #if defined(PETSC_THREADCOMM_ACTIVE) 3959 ierr = MatZeroEntries_SeqAIJ(B);CHKERRQ(ierr); 3960 #endif 3961 } else { 3962 b->free_a = PETSC_FALSE; 3963 b->free_ij = PETSC_FALSE; 3964 } 3965 3966 b->nz = 0; 3967 b->maxnz = nz; 3968 B->info.nz_unneeded = (double)b->maxnz; 3969 if (realalloc) { 3970 ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 3971 } 3972 PetscFunctionReturn(0); 3973 } 3974 3975 #undef __FUNCT__ 3976 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3977 /*@ 3978 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3979 3980 Input Parameters: 3981 + B - the matrix 3982 . i - the indices into j for the start of each row (starts with zero) 3983 . j - the column indices for each row (starts with zero) these must be sorted for each row 3984 - v - optional values in the matrix 3985 3986 Level: developer 3987 3988 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3989 3990 .keywords: matrix, aij, compressed row, sparse, sequential 3991 3992 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3993 @*/ 3994 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3995 { 3996 PetscErrorCode ierr; 3997 3998 PetscFunctionBegin; 3999 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 4000 PetscValidType(B,1); 4001 ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); 4002 PetscFunctionReturn(0); 4003 } 4004 4005 #undef __FUNCT__ 4006 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 4007 PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 4008 { 4009 PetscInt i; 4010 PetscInt m,n; 4011 PetscInt nz; 4012 PetscInt *nnz, nz_max = 0; 4013 PetscScalar *values; 4014 PetscErrorCode ierr; 4015 4016 PetscFunctionBegin; 4017 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 4018 4019 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 4020 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 4021 4022 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 4023 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 4024 for (i = 0; i < m; i++) { 4025 nz = Ii[i+1]- Ii[i]; 4026 nz_max = PetscMax(nz_max, nz); 4027 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 4028 nnz[i] = nz; 4029 } 4030 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 4031 ierr = PetscFree(nnz);CHKERRQ(ierr); 4032 4033 if (v) { 4034 values = (PetscScalar*) v; 4035 } else { 4036 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 4037 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 4038 } 4039 4040 for (i = 0; i < m; i++) { 4041 nz = Ii[i+1] - Ii[i]; 4042 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 4043 } 4044 4045 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4046 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4047 4048 if (!v) { 4049 ierr = PetscFree(values);CHKERRQ(ierr); 4050 } 4051 ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); 4052 PetscFunctionReturn(0); 4053 } 4054 4055 #include <../src/mat/impls/dense/seq/dense.h> 4056 #include <petsc-private/kernels/petscaxpy.h> 4057 4058 #undef __FUNCT__ 4059 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 4060 /* 4061 Computes (B'*A')' since computing B*A directly is untenable 4062 4063 n p p 4064 ( ) ( ) ( ) 4065 m ( A ) * n ( B ) = m ( C ) 4066 ( ) ( ) ( ) 4067 4068 */ 4069 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 4070 { 4071 PetscErrorCode ierr; 4072 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 4073 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 4074 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 4075 PetscInt i,n,m,q,p; 4076 const PetscInt *ii,*idx; 4077 const PetscScalar *b,*a,*a_q; 4078 PetscScalar *c,*c_q; 4079 4080 PetscFunctionBegin; 4081 m = A->rmap->n; 4082 n = A->cmap->n; 4083 p = B->cmap->n; 4084 a = sub_a->v; 4085 b = sub_b->a; 4086 c = sub_c->v; 4087 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 4088 4089 ii = sub_b->i; 4090 idx = sub_b->j; 4091 for (i=0; i<n; i++) { 4092 q = ii[i+1] - ii[i]; 4093 while (q-->0) { 4094 c_q = c + m*(*idx); 4095 a_q = a + m*i; 4096 PetscKernelAXPY(c_q,*b,a_q,m); 4097 idx++; 4098 b++; 4099 } 4100 } 4101 PetscFunctionReturn(0); 4102 } 4103 4104 #undef __FUNCT__ 4105 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 4106 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 4107 { 4108 PetscErrorCode ierr; 4109 PetscInt m=A->rmap->n,n=B->cmap->n; 4110 Mat Cmat; 4111 4112 PetscFunctionBegin; 4113 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); 4114 ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); 4115 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 4116 ierr = MatSetBlockSizes(Cmat,A->rmap->bs,B->cmap->bs);CHKERRQ(ierr); 4117 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 4118 ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); 4119 4120 Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; 4121 4122 *C = Cmat; 4123 PetscFunctionReturn(0); 4124 } 4125 4126 /* ----------------------------------------------------------------*/ 4127 #undef __FUNCT__ 4128 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 4129 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 4130 { 4131 PetscErrorCode ierr; 4132 4133 PetscFunctionBegin; 4134 if (scall == MAT_INITIAL_MATRIX) { 4135 ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4136 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 4137 ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); 4138 } 4139 ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4140 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 4141 ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); 4142 PetscFunctionReturn(0); 4143 } 4144 4145 4146 /*MC 4147 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 4148 based on compressed sparse row format. 4149 4150 Options Database Keys: 4151 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 4152 4153 Level: beginner 4154 4155 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 4156 M*/ 4157 4158 /*MC 4159 MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. 4160 4161 This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, 4162 and MATMPIAIJ otherwise. As a result, for single process communicators, 4163 MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported 4164 for communicators controlling multiple processes. It is recommended that you call both of 4165 the above preallocation routines for simplicity. 4166 4167 Options Database Keys: 4168 . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() 4169 4170 Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when 4171 enough exist. 4172 4173 Level: beginner 4174 4175 .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ 4176 M*/ 4177 4178 /*MC 4179 MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. 4180 4181 This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, 4182 and MATMPIAIJCRL otherwise. As a result, for single process communicators, 4183 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 4184 for communicators controlling multiple processes. It is recommended that you call both of 4185 the above preallocation routines for simplicity. 4186 4187 Options Database Keys: 4188 . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() 4189 4190 Level: beginner 4191 4192 .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL 4193 M*/ 4194 4195 #if defined(PETSC_HAVE_PASTIX) 4196 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 4197 #endif 4198 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4199 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat*); 4200 #endif 4201 PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 4202 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 4203 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 4204 extern PetscErrorCode MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscBool*); 4205 #if defined(PETSC_HAVE_MUMPS) 4206 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 4207 #endif 4208 #if defined(PETSC_HAVE_SUPERLU) 4209 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 4210 #endif 4211 #if defined(PETSC_HAVE_SUPERLU_DIST) 4212 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 4213 #endif 4214 #if defined(PETSC_HAVE_UMFPACK) 4215 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 4216 #endif 4217 #if defined(PETSC_HAVE_CHOLMOD) 4218 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 4219 #endif 4220 #if defined(PETSC_HAVE_LUSOL) 4221 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 4222 #endif 4223 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4224 PETSC_EXTERN PetscErrorCode MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 4225 extern PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); 4226 extern PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); 4227 #endif 4228 #if defined(PETSC_HAVE_CLIQUE) 4229 PETSC_EXTERN PetscErrorCode MatGetFactor_aij_clique(Mat,MatFactorType,Mat*); 4230 #endif 4231 4232 4233 #undef __FUNCT__ 4234 #define __FUNCT__ "MatSeqAIJGetArray" 4235 /*@C 4236 MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored 4237 4238 Not Collective 4239 4240 Input Parameter: 4241 . mat - a MATSEQDENSE matrix 4242 4243 Output Parameter: 4244 . array - pointer to the data 4245 4246 Level: intermediate 4247 4248 .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() 4249 @*/ 4250 PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) 4251 { 4252 PetscErrorCode ierr; 4253 4254 PetscFunctionBegin; 4255 ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4256 PetscFunctionReturn(0); 4257 } 4258 4259 #undef __FUNCT__ 4260 #define __FUNCT__ "MatSeqAIJRestoreArray" 4261 /*@C 4262 MatSeqAIJRestoreArray - returns access to the array where the data for a SeqSeqAIJ matrix is stored obtained by MatSeqAIJGetArray() 4263 4264 Not Collective 4265 4266 Input Parameters: 4267 . mat - a MATSEQDENSE matrix 4268 . array - pointer to the data 4269 4270 Level: intermediate 4271 4272 .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() 4273 @*/ 4274 PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) 4275 { 4276 PetscErrorCode ierr; 4277 4278 PetscFunctionBegin; 4279 ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); 4280 PetscFunctionReturn(0); 4281 } 4282 4283 #undef __FUNCT__ 4284 #define __FUNCT__ "MatCreate_SeqAIJ" 4285 PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) 4286 { 4287 Mat_SeqAIJ *b; 4288 PetscErrorCode ierr; 4289 PetscMPIInt size; 4290 4291 PetscFunctionBegin; 4292 ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); 4293 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 4294 4295 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 4296 4297 B->data = (void*)b; 4298 4299 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 4300 4301 b->row = 0; 4302 b->col = 0; 4303 b->icol = 0; 4304 b->reallocs = 0; 4305 b->ignorezeroentries = PETSC_FALSE; 4306 b->roworiented = PETSC_TRUE; 4307 b->nonew = 0; 4308 b->diag = 0; 4309 b->solve_work = 0; 4310 B->spptr = 0; 4311 b->saved_values = 0; 4312 b->idiag = 0; 4313 b->mdiag = 0; 4314 b->ssor_work = 0; 4315 b->omega = 1.0; 4316 b->fshift = 0.0; 4317 b->idiagvalid = PETSC_FALSE; 4318 b->ibdiagvalid = PETSC_FALSE; 4319 b->keepnonzeropattern = PETSC_FALSE; 4320 b->xtoy = 0; 4321 b->XtoY = 0; 4322 B->same_nonzero = PETSC_FALSE; 4323 4324 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4325 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); 4326 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); 4327 4328 #if defined(PETSC_HAVE_MATLAB_ENGINE) 4329 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_matlab_C",MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 4330 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 4331 ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 4332 #endif 4333 #if defined(PETSC_HAVE_PASTIX) 4334 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 4335 #endif 4336 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) 4337 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_essl_C",MatGetFactor_seqaij_essl);CHKERRQ(ierr); 4338 #endif 4339 #if defined(PETSC_HAVE_SUPERLU) 4340 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_C",MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 4341 #endif 4342 #if defined(PETSC_HAVE_SUPERLU_DIST) 4343 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_superlu_dist_C",MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 4344 #endif 4345 #if defined(PETSC_HAVE_MUMPS) 4346 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_aij_mumps);CHKERRQ(ierr); 4347 #endif 4348 #if defined(PETSC_HAVE_UMFPACK) 4349 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_umfpack_C",MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 4350 #endif 4351 #if defined(PETSC_HAVE_CHOLMOD) 4352 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_cholmod_C",MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 4353 #endif 4354 #if defined(PETSC_HAVE_LUSOL) 4355 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_lusol_C",MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 4356 #endif 4357 #if defined(PETSC_HAVE_CLIQUE) 4358 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_clique_C",MatGetFactor_aij_clique);CHKERRQ(ierr); 4359 #endif 4360 4361 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_petsc_C",MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 4362 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactorAvailable_petsc_C",MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 4363 ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_bas_C",MatGetFactor_seqaij_bas);CHKERRQ(ierr); 4364 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 4365 ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); 4366 ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 4367 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 4368 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 4369 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 4370 ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 4371 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4372 ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 4373 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 4374 ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 4375 ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 4376 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 4377 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 4378 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 4379 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 4380 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 4381 PetscFunctionReturn(0); 4382 } 4383 4384 #undef __FUNCT__ 4385 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 4386 /* 4387 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 4388 */ 4389 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) 4390 { 4391 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 4392 PetscErrorCode ierr; 4393 PetscInt i,m = A->rmap->n; 4394 4395 PetscFunctionBegin; 4396 c = (Mat_SeqAIJ*)C->data; 4397 4398 C->factortype = A->factortype; 4399 c->row = 0; 4400 c->col = 0; 4401 c->icol = 0; 4402 c->reallocs = 0; 4403 4404 C->assembled = PETSC_TRUE; 4405 4406 ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); 4407 ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); 4408 4409 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 4410 ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 4411 for (i=0; i<m; i++) { 4412 c->imax[i] = a->imax[i]; 4413 c->ilen[i] = a->ilen[i]; 4414 } 4415 4416 /* allocate the matrix space */ 4417 if (mallocmatspace) { 4418 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 4419 ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4420 4421 c->singlemalloc = PETSC_TRUE; 4422 4423 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4424 if (m > 0) { 4425 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 4426 if (cpvalues == MAT_COPY_VALUES) { 4427 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4428 } else { 4429 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 4430 } 4431 } 4432 } 4433 4434 c->ignorezeroentries = a->ignorezeroentries; 4435 c->roworiented = a->roworiented; 4436 c->nonew = a->nonew; 4437 if (a->diag) { 4438 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 4439 ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 4440 for (i=0; i<m; i++) { 4441 c->diag[i] = a->diag[i]; 4442 } 4443 } else c->diag = 0; 4444 4445 c->solve_work = 0; 4446 c->saved_values = 0; 4447 c->idiag = 0; 4448 c->ssor_work = 0; 4449 c->keepnonzeropattern = a->keepnonzeropattern; 4450 c->free_a = PETSC_TRUE; 4451 c->free_ij = PETSC_TRUE; 4452 c->xtoy = 0; 4453 c->XtoY = 0; 4454 4455 c->rmax = a->rmax; 4456 c->nz = a->nz; 4457 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 4458 C->preallocated = PETSC_TRUE; 4459 4460 c->compressedrow.use = a->compressedrow.use; 4461 c->compressedrow.nrows = a->compressedrow.nrows; 4462 c->compressedrow.check = a->compressedrow.check; 4463 if (a->compressedrow.use) { 4464 i = a->compressedrow.nrows; 4465 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 4466 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 4467 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 4468 } else { 4469 c->compressedrow.use = PETSC_FALSE; 4470 c->compressedrow.i = NULL; 4471 c->compressedrow.rindex = NULL; 4472 } 4473 C->same_nonzero = A->same_nonzero; 4474 4475 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 4476 ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 4477 PetscFunctionReturn(0); 4478 } 4479 4480 #undef __FUNCT__ 4481 #define __FUNCT__ "MatDuplicate_SeqAIJ" 4482 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 4483 { 4484 PetscErrorCode ierr; 4485 4486 PetscFunctionBegin; 4487 ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); 4488 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 4489 ierr = MatSetBlockSizes(*B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr); 4490 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 4491 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 4492 PetscFunctionReturn(0); 4493 } 4494 4495 #undef __FUNCT__ 4496 #define __FUNCT__ "MatLoad_SeqAIJ" 4497 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 4498 { 4499 Mat_SeqAIJ *a; 4500 PetscErrorCode ierr; 4501 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 4502 int fd; 4503 PetscMPIInt size; 4504 MPI_Comm comm; 4505 PetscInt bs = 1; 4506 4507 PetscFunctionBegin; 4508 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 4509 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 4510 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 4511 4512 ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); 4513 ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); 4514 ierr = PetscOptionsEnd();CHKERRQ(ierr); 4515 if (bs > 1) {ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr);} 4516 4517 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 4518 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 4519 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 4520 M = header[1]; N = header[2]; nz = header[3]; 4521 4522 if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 4523 4524 /* read in row lengths */ 4525 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 4526 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 4527 4528 /* check if sum of rowlengths is same as nz */ 4529 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 4530 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); 4531 4532 /* set global size if not set already*/ 4533 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 4534 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 4535 } else { 4536 /* if sizes and type are already set, check if the vector global sizes are correct */ 4537 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 4538 if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ 4539 ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); 4540 } 4541 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); 4542 } 4543 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 4544 a = (Mat_SeqAIJ*)newMat->data; 4545 4546 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 4547 4548 /* read in nonzero values */ 4549 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 4550 4551 /* set matrix "i" values */ 4552 a->i[0] = 0; 4553 for (i=1; i<= M; i++) { 4554 a->i[i] = a->i[i-1] + rowlengths[i-1]; 4555 a->ilen[i-1] = rowlengths[i-1]; 4556 } 4557 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 4558 4559 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4560 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4561 PetscFunctionReturn(0); 4562 } 4563 4564 #undef __FUNCT__ 4565 #define __FUNCT__ "MatEqual_SeqAIJ" 4566 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) 4567 { 4568 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; 4569 PetscErrorCode ierr; 4570 #if defined(PETSC_USE_COMPLEX) 4571 PetscInt k; 4572 #endif 4573 4574 PetscFunctionBegin; 4575 /* If the matrix dimensions are not equal,or no of nonzeros */ 4576 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 4577 *flg = PETSC_FALSE; 4578 PetscFunctionReturn(0); 4579 } 4580 4581 /* if the a->i are the same */ 4582 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4583 if (!*flg) PetscFunctionReturn(0); 4584 4585 /* if a->j are the same */ 4586 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 4587 if (!*flg) PetscFunctionReturn(0); 4588 4589 /* if a->a are the same */ 4590 #if defined(PETSC_USE_COMPLEX) 4591 for (k=0; k<a->nz; k++) { 4592 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { 4593 *flg = PETSC_FALSE; 4594 PetscFunctionReturn(0); 4595 } 4596 } 4597 #else 4598 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 4599 #endif 4600 PetscFunctionReturn(0); 4601 } 4602 4603 #undef __FUNCT__ 4604 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 4605 /*@ 4606 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 4607 provided by the user. 4608 4609 Collective on MPI_Comm 4610 4611 Input Parameters: 4612 + comm - must be an MPI communicator of size 1 4613 . m - number of rows 4614 . n - number of columns 4615 . i - row indices 4616 . j - column indices 4617 - a - matrix values 4618 4619 Output Parameter: 4620 . mat - the matrix 4621 4622 Level: intermediate 4623 4624 Notes: 4625 The i, j, and a arrays are not copied by this routine, the user must free these arrays 4626 once the matrix is destroyed and not before 4627 4628 You cannot set new nonzero locations into this matrix, that will generate an error. 4629 4630 The i and j indices are 0 based 4631 4632 The format which is used for the sparse matrix input, is equivalent to a 4633 row-major ordering.. i.e for the following matrix, the input data expected is 4634 as shown: 4635 4636 1 0 0 4637 2 0 3 4638 4 5 6 4639 4640 i = {0,1,3,6} [size = nrow+1 = 3+1] 4641 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 4642 v = {1,2,3,4,5,6} [size = nz = 6] 4643 4644 4645 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4646 4647 @*/ 4648 PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) 4649 { 4650 PetscErrorCode ierr; 4651 PetscInt ii; 4652 Mat_SeqAIJ *aij; 4653 #if defined(PETSC_USE_DEBUG) 4654 PetscInt jj; 4655 #endif 4656 4657 PetscFunctionBegin; 4658 if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 4659 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4660 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4661 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4662 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4663 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 4664 aij = (Mat_SeqAIJ*)(*mat)->data; 4665 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 4666 4667 aij->i = i; 4668 aij->j = j; 4669 aij->a = a; 4670 aij->singlemalloc = PETSC_FALSE; 4671 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 4672 aij->free_a = PETSC_FALSE; 4673 aij->free_ij = PETSC_FALSE; 4674 4675 for (ii=0; ii<m; ii++) { 4676 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 4677 #if defined(PETSC_USE_DEBUG) 4678 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]); 4679 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 4680 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); 4681 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); 4682 } 4683 #endif 4684 } 4685 #if defined(PETSC_USE_DEBUG) 4686 for (ii=0; ii<aij->i[m]; ii++) { 4687 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 4688 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]); 4689 } 4690 #endif 4691 4692 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4693 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4694 PetscFunctionReturn(0); 4695 } 4696 #undef __FUNCT__ 4697 #define __FUNCT__ "MatCreateSeqAIJFromTriple" 4698 /*@C 4699 MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) 4700 provided by the user. 4701 4702 Collective on MPI_Comm 4703 4704 Input Parameters: 4705 + comm - must be an MPI communicator of size 1 4706 . m - number of rows 4707 . n - number of columns 4708 . i - row indices 4709 . j - column indices 4710 . a - matrix values 4711 . nz - number of nonzeros 4712 - idx - 0 or 1 based 4713 4714 Output Parameter: 4715 . mat - the matrix 4716 4717 Level: intermediate 4718 4719 Notes: 4720 The i and j indices are 0 based 4721 4722 The format which is used for the sparse matrix input, is equivalent to a 4723 row-major ordering.. i.e for the following matrix, the input data expected is 4724 as shown: 4725 4726 1 0 0 4727 2 0 3 4728 4 5 6 4729 4730 i = {0,1,1,2,2,2} 4731 j = {0,0,2,0,1,2} 4732 v = {1,2,3,4,5,6} 4733 4734 4735 .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 4736 4737 @*/ 4738 PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) 4739 { 4740 PetscErrorCode ierr; 4741 PetscInt ii, *nnz, one = 1,row,col; 4742 4743 4744 PetscFunctionBegin; 4745 ierr = PetscMalloc(m*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 4746 ierr = PetscMemzero(nnz,m*sizeof(PetscInt));CHKERRQ(ierr); 4747 for (ii = 0; ii < nz; ii++) { 4748 nnz[i[ii]] += 1; 4749 } 4750 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 4751 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 4752 /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ 4753 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 4754 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); 4755 for (ii = 0; ii < nz; ii++) { 4756 if (idx) { 4757 row = i[ii] - 1; 4758 col = j[ii] - 1; 4759 } else { 4760 row = i[ii]; 4761 col = j[ii]; 4762 } 4763 ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); 4764 } 4765 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4766 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 4767 ierr = PetscFree(nnz);CHKERRQ(ierr); 4768 PetscFunctionReturn(0); 4769 } 4770 4771 #undef __FUNCT__ 4772 #define __FUNCT__ "MatSetColoring_SeqAIJ" 4773 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 4774 { 4775 PetscErrorCode ierr; 4776 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4777 4778 PetscFunctionBegin; 4779 if (coloring->ctype == IS_COLORING_GLOBAL) { 4780 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 4781 a->coloring = coloring; 4782 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 4783 PetscInt i,*larray; 4784 ISColoring ocoloring; 4785 ISColoringValue *colors; 4786 4787 /* set coloring for diagonal portion */ 4788 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 4789 for (i=0; i<A->cmap->n; i++) larray[i] = i; 4790 ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); 4791 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 4792 for (i=0; i<A->cmap->n; i++) colors[i] = coloring->colors[larray[i]]; 4793 ierr = PetscFree(larray);CHKERRQ(ierr); 4794 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 4795 a->coloring = ocoloring; 4796 } 4797 PetscFunctionReturn(0); 4798 } 4799 4800 #undef __FUNCT__ 4801 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 4802 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 4803 { 4804 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4805 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 4806 MatScalar *v = a->a; 4807 PetscScalar *values = (PetscScalar*)advalues; 4808 ISColoringValue *color; 4809 4810 PetscFunctionBegin; 4811 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 4812 color = a->coloring->colors; 4813 /* loop over rows */ 4814 for (i=0; i<m; i++) { 4815 nz = ii[i+1] - ii[i]; 4816 /* loop over columns putting computed value into matrix */ 4817 for (j=0; j<nz; j++) *v++ = values[color[*jj++]]; 4818 values += nl; /* jump to next row of derivatives */ 4819 } 4820 PetscFunctionReturn(0); 4821 } 4822 4823 #undef __FUNCT__ 4824 #define __FUNCT__ "MatSeqAIJInvalidateDiagonal" 4825 PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat A) 4826 { 4827 Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data; 4828 PetscErrorCode ierr; 4829 4830 PetscFunctionBegin; 4831 a->idiagvalid = PETSC_FALSE; 4832 a->ibdiagvalid = PETSC_FALSE; 4833 4834 ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); 4835 PetscFunctionReturn(0); 4836 } 4837 4838 /* 4839 Special version for direct calls from Fortran 4840 */ 4841 #include <petsc-private/fortranimpl.h> 4842 #if defined(PETSC_HAVE_FORTRAN_CAPS) 4843 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 4844 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 4845 #define matsetvaluesseqaij_ matsetvaluesseqaij 4846 #endif 4847 4848 /* Change these macros so can be used in void function */ 4849 #undef CHKERRQ 4850 #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) 4851 #undef SETERRQ2 4852 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 4853 #undef SETERRQ3 4854 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) 4855 4856 #undef __FUNCT__ 4857 #define __FUNCT__ "matsetvaluesseqaij_" 4858 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) 4859 { 4860 Mat A = *AA; 4861 PetscInt m = *mm, n = *nn; 4862 InsertMode is = *isis; 4863 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 4864 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 4865 PetscInt *imax,*ai,*ailen; 4866 PetscErrorCode ierr; 4867 PetscInt *aj,nonew = a->nonew,lastcol = -1; 4868 MatScalar *ap,value,*aa; 4869 PetscBool ignorezeroentries = a->ignorezeroentries; 4870 PetscBool roworiented = a->roworiented; 4871 4872 PetscFunctionBegin; 4873 MatCheckPreallocated(A,1); 4874 imax = a->imax; 4875 ai = a->i; 4876 ailen = a->ilen; 4877 aj = a->j; 4878 aa = a->a; 4879 4880 for (k=0; k<m; k++) { /* loop over added rows */ 4881 row = im[k]; 4882 if (row < 0) continue; 4883 #if defined(PETSC_USE_DEBUG) 4884 if (row >= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 4885 #endif 4886 rp = aj + ai[row]; ap = aa + ai[row]; 4887 rmax = imax[row]; nrow = ailen[row]; 4888 low = 0; 4889 high = nrow; 4890 for (l=0; l<n; l++) { /* loop over added columns */ 4891 if (in[l] < 0) continue; 4892 #if defined(PETSC_USE_DEBUG) 4893 if (in[l] >= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 4894 #endif 4895 col = in[l]; 4896 if (roworiented) value = v[l + k*n]; 4897 else value = v[k + l*m]; 4898 4899 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 4900 4901 if (col <= lastcol) low = 0; 4902 else high = nrow; 4903 lastcol = col; 4904 while (high-low > 5) { 4905 t = (low+high)/2; 4906 if (rp[t] > col) high = t; 4907 else low = t; 4908 } 4909 for (i=low; i<high; i++) { 4910 if (rp[i] > col) break; 4911 if (rp[i] == col) { 4912 if (is == ADD_VALUES) ap[i] += value; 4913 else ap[i] = value; 4914 goto noinsert; 4915 } 4916 } 4917 if (value == 0.0 && ignorezeroentries) goto noinsert; 4918 if (nonew == 1) goto noinsert; 4919 if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 4920 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 4921 N = nrow++ - 1; a->nz++; high++; 4922 /* shift up all the later entries in this row */ 4923 for (ii=N; ii>=i; ii--) { 4924 rp[ii+1] = rp[ii]; 4925 ap[ii+1] = ap[ii]; 4926 } 4927 rp[i] = col; 4928 ap[i] = value; 4929 noinsert:; 4930 low = i + 1; 4931 } 4932 ailen[row] = nrow; 4933 } 4934 A->same_nonzero = PETSC_FALSE; 4935 PetscFunctionReturnVoid(); 4936 } 4937 4938 4939