1 2 /* 3 Defines the basic matrix operations for sequential dense. 4 */ 5 6 #include <../src/mat/impls/dense/seq/dense.h> 7 #include <petscblaslapack.h> 8 9 #include <../src/mat/impls/aij/seq/aij.h> 10 EXTERN_C_BEGIN 11 #undef __FUNCT__ 12 #define __FUNCT__ "MatConvert_SeqDense_SeqAIJ" 13 PetscErrorCode MatConvert_SeqDense_SeqAIJ(Mat A, MatType newtype,MatReuse reuse,Mat *newmat) 14 { 15 Mat B; 16 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 17 PetscErrorCode ierr; 18 PetscInt i; 19 PetscInt *rows; 20 MatScalar *aa = a->v; 21 22 PetscFunctionBegin; 23 ierr = MatCreate(((PetscObject)A)->comm,&B);CHKERRQ(ierr); 24 ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr); 25 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 26 ierr = MatSeqAIJSetPreallocation(B,A->cmap->n,PETSC_NULL);CHKERRQ(ierr); 27 28 ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&rows);CHKERRQ(ierr); 29 for (i=0; i<A->rmap->n; i++) rows[i] = i; 30 31 for (i=0; i<A->cmap->n; i++) { 32 ierr = MatSetValues(B,A->rmap->n,rows,1,&i,aa,INSERT_VALUES);CHKERRQ(ierr); 33 aa += a->lda; 34 } 35 ierr = PetscFree(rows);CHKERRQ(ierr); 36 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 37 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 38 39 if (reuse == MAT_REUSE_MATRIX) { 40 ierr = MatHeaderReplace(A,B);CHKERRQ(ierr); 41 } else { 42 *newmat = B; 43 } 44 PetscFunctionReturn(0); 45 } 46 EXTERN_C_END 47 48 #undef __FUNCT__ 49 #define __FUNCT__ "MatAXPY_SeqDense" 50 PetscErrorCode MatAXPY_SeqDense(Mat Y,PetscScalar alpha,Mat X,MatStructure str) 51 { 52 Mat_SeqDense *x = (Mat_SeqDense*)X->data,*y = (Mat_SeqDense*)Y->data; 53 PetscScalar oalpha = alpha; 54 PetscInt j; 55 PetscBLASInt N,m,ldax,lday,one = 1; 56 PetscErrorCode ierr; 57 58 PetscFunctionBegin; 59 N = PetscBLASIntCast(X->rmap->n*X->cmap->n); 60 m = PetscBLASIntCast(X->rmap->n); 61 ldax = PetscBLASIntCast(x->lda); 62 lday = PetscBLASIntCast(y->lda); 63 if (ldax>m || lday>m) { 64 for (j=0; j<X->cmap->n; j++) { 65 BLASaxpy_(&m,&oalpha,x->v+j*ldax,&one,y->v+j*lday,&one); 66 } 67 } else { 68 BLASaxpy_(&N,&oalpha,x->v,&one,y->v,&one); 69 } 70 ierr = PetscLogFlops(PetscMax(2*N-1,0));CHKERRQ(ierr); 71 PetscFunctionReturn(0); 72 } 73 74 #undef __FUNCT__ 75 #define __FUNCT__ "MatGetInfo_SeqDense" 76 PetscErrorCode MatGetInfo_SeqDense(Mat A,MatInfoType flag,MatInfo *info) 77 { 78 PetscInt N = A->rmap->n*A->cmap->n; 79 80 PetscFunctionBegin; 81 info->block_size = 1.0; 82 info->nz_allocated = (double)N; 83 info->nz_used = (double)N; 84 info->nz_unneeded = (double)0; 85 info->assemblies = (double)A->num_ass; 86 info->mallocs = 0; 87 info->memory = ((PetscObject)A)->mem; 88 info->fill_ratio_given = 0; 89 info->fill_ratio_needed = 0; 90 info->factor_mallocs = 0; 91 PetscFunctionReturn(0); 92 } 93 94 #undef __FUNCT__ 95 #define __FUNCT__ "MatScale_SeqDense" 96 PetscErrorCode MatScale_SeqDense(Mat A,PetscScalar alpha) 97 { 98 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 99 PetscScalar oalpha = alpha; 100 PetscErrorCode ierr; 101 PetscBLASInt one = 1,j,nz,lda = PetscBLASIntCast(a->lda); 102 103 PetscFunctionBegin; 104 if (lda>A->rmap->n) { 105 nz = PetscBLASIntCast(A->rmap->n); 106 for (j=0; j<A->cmap->n; j++) { 107 BLASscal_(&nz,&oalpha,a->v+j*lda,&one); 108 } 109 } else { 110 nz = PetscBLASIntCast(A->rmap->n*A->cmap->n); 111 BLASscal_(&nz,&oalpha,a->v,&one); 112 } 113 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 114 PetscFunctionReturn(0); 115 } 116 117 #undef __FUNCT__ 118 #define __FUNCT__ "MatIsHermitian_SeqDense" 119 PetscErrorCode MatIsHermitian_SeqDense(Mat A,PetscReal rtol,PetscBool *fl) 120 { 121 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 122 PetscInt i,j,m = A->rmap->n,N; 123 PetscScalar *v = a->v; 124 125 PetscFunctionBegin; 126 *fl = PETSC_FALSE; 127 if (A->rmap->n != A->cmap->n) PetscFunctionReturn(0); 128 N = a->lda; 129 130 for (i=0; i<m; i++) { 131 for (j=i+1; j<m; j++) { 132 if (PetscAbsScalar(v[i+j*N] - PetscConj(v[j+i*N])) > rtol) PetscFunctionReturn(0); 133 } 134 } 135 *fl = PETSC_TRUE; 136 PetscFunctionReturn(0); 137 } 138 139 #undef __FUNCT__ 140 #define __FUNCT__ "MatDuplicateNoCreate_SeqDense" 141 PetscErrorCode MatDuplicateNoCreate_SeqDense(Mat newi,Mat A,MatDuplicateOption cpvalues) 142 { 143 Mat_SeqDense *mat = (Mat_SeqDense*)A->data,*l; 144 PetscErrorCode ierr; 145 PetscInt lda = (PetscInt)mat->lda,j,m; 146 147 PetscFunctionBegin; 148 ierr = PetscLayoutReference(A->rmap,&newi->rmap);CHKERRQ(ierr); 149 ierr = PetscLayoutReference(A->cmap,&newi->cmap);CHKERRQ(ierr); 150 ierr = MatSeqDenseSetPreallocation(newi,PETSC_NULL);CHKERRQ(ierr); 151 if (cpvalues == MAT_COPY_VALUES) { 152 l = (Mat_SeqDense*)newi->data; 153 if (lda>A->rmap->n) { 154 m = A->rmap->n; 155 for (j=0; j<A->cmap->n; j++) { 156 ierr = PetscMemcpy(l->v+j*m,mat->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 157 } 158 } else { 159 ierr = PetscMemcpy(l->v,mat->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 160 } 161 } 162 newi->assembled = PETSC_TRUE; 163 PetscFunctionReturn(0); 164 } 165 166 #undef __FUNCT__ 167 #define __FUNCT__ "MatDuplicate_SeqDense" 168 PetscErrorCode MatDuplicate_SeqDense(Mat A,MatDuplicateOption cpvalues,Mat *newmat) 169 { 170 PetscErrorCode ierr; 171 172 PetscFunctionBegin; 173 ierr = MatCreate(((PetscObject)A)->comm,newmat);CHKERRQ(ierr); 174 ierr = MatSetSizes(*newmat,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 175 ierr = MatSetType(*newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 176 ierr = MatDuplicateNoCreate_SeqDense(*newmat,A,cpvalues);CHKERRQ(ierr); 177 PetscFunctionReturn(0); 178 } 179 180 181 extern PetscErrorCode MatLUFactor_SeqDense(Mat,IS,IS,const MatFactorInfo*); 182 183 #undef __FUNCT__ 184 #define __FUNCT__ "MatLUFactorNumeric_SeqDense" 185 PetscErrorCode MatLUFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy) 186 { 187 MatFactorInfo info; 188 PetscErrorCode ierr; 189 190 PetscFunctionBegin; 191 ierr = MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);CHKERRQ(ierr); 192 ierr = MatLUFactor_SeqDense(fact,0,0,&info);CHKERRQ(ierr); 193 PetscFunctionReturn(0); 194 } 195 196 #undef __FUNCT__ 197 #define __FUNCT__ "MatSolve_SeqDense" 198 PetscErrorCode MatSolve_SeqDense(Mat A,Vec xx,Vec yy) 199 { 200 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 201 PetscErrorCode ierr; 202 PetscScalar *x,*y; 203 PetscBLASInt one = 1,info,m = PetscBLASIntCast(A->rmap->n); 204 205 PetscFunctionBegin; 206 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 207 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 208 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 209 if (A->factortype == MAT_FACTOR_LU) { 210 #if defined(PETSC_MISSING_LAPACK_GETRS) 211 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 212 #else 213 LAPACKgetrs_("N",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info); 214 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve"); 215 #endif 216 } else if (A->factortype == MAT_FACTOR_CHOLESKY){ 217 #if defined(PETSC_MISSING_LAPACK_POTRS) 218 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 219 #else 220 LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info); 221 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 222 #endif 223 } 224 else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 225 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 226 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 227 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 228 PetscFunctionReturn(0); 229 } 230 231 #undef __FUNCT__ 232 #define __FUNCT__ "MatMatSolve_SeqDense" 233 PetscErrorCode MatMatSolve_SeqDense(Mat A,Mat B,Mat X) 234 { 235 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 236 PetscErrorCode ierr; 237 PetscScalar *b,*x; 238 PetscInt n; 239 PetscBLASInt nrhs,info,m=PetscBLASIntCast(A->rmap->n); 240 PetscBool flg; 241 242 PetscFunctionBegin; 243 ierr = PetscObjectTypeCompareAny((PetscObject)B,&flg,MATSEQDENSE,MATMPIDENSE,PETSC_NULL);CHKERRQ(ierr); 244 if (!flg) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_WRONG,"Matrix B must be MATDENSE matrix"); 245 ierr = PetscObjectTypeCompareAny((PetscObject)X,&flg,MATSEQDENSE,MATMPIDENSE,PETSC_NULL);CHKERRQ(ierr); 246 if (!flg) SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_WRONG,"Matrix X must be MATDENSE matrix"); 247 248 ierr = MatGetSize(B,PETSC_NULL,&n);CHKERRQ(ierr); 249 nrhs = PetscBLASIntCast(n); 250 ierr = MatGetArray(B,&b);CHKERRQ(ierr); 251 ierr = MatGetArray(X,&x);CHKERRQ(ierr); 252 253 ierr = PetscMemcpy(x,b,m*nrhs*sizeof(PetscScalar));CHKERRQ(ierr); 254 255 if (A->factortype == MAT_FACTOR_LU) { 256 #if defined(PETSC_MISSING_LAPACK_GETRS) 257 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 258 #else 259 LAPACKgetrs_("N",&m,&nrhs,mat->v,&mat->lda,mat->pivots,x,&m,&info); 260 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"GETRS - Bad solve"); 261 #endif 262 } else if (A->factortype == MAT_FACTOR_CHOLESKY){ 263 #if defined(PETSC_MISSING_LAPACK_POTRS) 264 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 265 #else 266 LAPACKpotrs_("L",&m,&nrhs,mat->v,&mat->lda,x,&m,&info); 267 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS Bad solve"); 268 #endif 269 } 270 else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix must be factored to solve"); 271 272 ierr = MatRestoreArray(B,&b);CHKERRQ(ierr); 273 ierr = MatRestoreArray(X,&x);CHKERRQ(ierr); 274 ierr = PetscLogFlops(nrhs*(2.0*m*m - m));CHKERRQ(ierr); 275 PetscFunctionReturn(0); 276 } 277 278 #undef __FUNCT__ 279 #define __FUNCT__ "MatSolveTranspose_SeqDense" 280 PetscErrorCode MatSolveTranspose_SeqDense(Mat A,Vec xx,Vec yy) 281 { 282 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 283 PetscErrorCode ierr; 284 PetscScalar *x,*y; 285 PetscBLASInt one = 1,info,m = PetscBLASIntCast(A->rmap->n); 286 287 PetscFunctionBegin; 288 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 289 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 290 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 291 /* assume if pivots exist then use LU; else Cholesky */ 292 if (mat->pivots) { 293 #if defined(PETSC_MISSING_LAPACK_GETRS) 294 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 295 #else 296 LAPACKgetrs_("T",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info); 297 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS - Bad solve"); 298 #endif 299 } else { 300 #if defined(PETSC_MISSING_LAPACK_POTRS) 301 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 302 #else 303 LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info); 304 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"POTRS - Bad solve"); 305 #endif 306 } 307 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 308 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 309 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 310 PetscFunctionReturn(0); 311 } 312 313 #undef __FUNCT__ 314 #define __FUNCT__ "MatSolveAdd_SeqDense" 315 PetscErrorCode MatSolveAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 316 { 317 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 318 PetscErrorCode ierr; 319 PetscScalar *x,*y,sone = 1.0; 320 Vec tmp = 0; 321 PetscBLASInt one = 1,info,m = PetscBLASIntCast(A->rmap->n); 322 323 PetscFunctionBegin; 324 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 325 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 326 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 327 if (yy == zz) { 328 ierr = VecDuplicate(yy,&tmp);CHKERRQ(ierr); 329 ierr = PetscLogObjectParent(A,tmp);CHKERRQ(ierr); 330 ierr = VecCopy(yy,tmp);CHKERRQ(ierr); 331 } 332 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 333 /* assume if pivots exist then use LU; else Cholesky */ 334 if (mat->pivots) { 335 #if defined(PETSC_MISSING_LAPACK_GETRS) 336 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 337 #else 338 LAPACKgetrs_("N",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info); 339 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve"); 340 #endif 341 } else { 342 #if defined(PETSC_MISSING_LAPACK_POTRS) 343 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 344 #else 345 LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info); 346 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve"); 347 #endif 348 } 349 if (tmp) { 350 ierr = VecAXPY(yy,sone,tmp);CHKERRQ(ierr); 351 ierr = VecDestroy(&tmp);CHKERRQ(ierr); 352 } else { 353 ierr = VecAXPY(yy,sone,zz);CHKERRQ(ierr); 354 } 355 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 356 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 357 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n);CHKERRQ(ierr); 358 PetscFunctionReturn(0); 359 } 360 361 #undef __FUNCT__ 362 #define __FUNCT__ "MatSolveTransposeAdd_SeqDense" 363 PetscErrorCode MatSolveTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 364 { 365 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 366 PetscErrorCode ierr; 367 PetscScalar *x,*y,sone = 1.0; 368 Vec tmp; 369 PetscBLASInt one = 1,info,m = PetscBLASIntCast(A->rmap->n); 370 371 PetscFunctionBegin; 372 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 373 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 374 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 375 if (yy == zz) { 376 ierr = VecDuplicate(yy,&tmp);CHKERRQ(ierr); 377 ierr = PetscLogObjectParent(A,tmp);CHKERRQ(ierr); 378 ierr = VecCopy(yy,tmp);CHKERRQ(ierr); 379 } 380 ierr = PetscMemcpy(y,x,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 381 /* assume if pivots exist then use LU; else Cholesky */ 382 if (mat->pivots) { 383 #if defined(PETSC_MISSING_LAPACK_GETRS) 384 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRS - Lapack routine is unavailable."); 385 #else 386 LAPACKgetrs_("T",&m,&one,mat->v,&mat->lda,mat->pivots,y,&m,&info); 387 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve"); 388 #endif 389 } else { 390 #if defined(PETSC_MISSING_LAPACK_POTRS) 391 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRS - Lapack routine is unavailable."); 392 #else 393 LAPACKpotrs_("L",&m,&one,mat->v,&mat->lda,y,&m,&info); 394 if (info) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad solve"); 395 #endif 396 } 397 if (tmp) { 398 ierr = VecAXPY(yy,sone,tmp);CHKERRQ(ierr); 399 ierr = VecDestroy(&tmp);CHKERRQ(ierr); 400 } else { 401 ierr = VecAXPY(yy,sone,zz);CHKERRQ(ierr); 402 } 403 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 404 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 405 ierr = PetscLogFlops(2.0*A->cmap->n*A->cmap->n);CHKERRQ(ierr); 406 PetscFunctionReturn(0); 407 } 408 409 /* ---------------------------------------------------------------*/ 410 /* COMMENT: I have chosen to hide row permutation in the pivots, 411 rather than put it in the Mat->row slot.*/ 412 #undef __FUNCT__ 413 #define __FUNCT__ "MatLUFactor_SeqDense" 414 PetscErrorCode MatLUFactor_SeqDense(Mat A,IS row,IS col,const MatFactorInfo *minfo) 415 { 416 #if defined(PETSC_MISSING_LAPACK_GETRF) 417 PetscFunctionBegin; 418 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"GETRF - Lapack routine is unavailable."); 419 #else 420 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 421 PetscErrorCode ierr; 422 PetscBLASInt n,m,info; 423 424 PetscFunctionBegin; 425 n = PetscBLASIntCast(A->cmap->n); 426 m = PetscBLASIntCast(A->rmap->n); 427 if (!mat->pivots) { 428 ierr = PetscMalloc((A->rmap->n+1)*sizeof(PetscBLASInt),&mat->pivots);CHKERRQ(ierr); 429 ierr = PetscLogObjectMemory(A,A->rmap->n*sizeof(PetscBLASInt));CHKERRQ(ierr); 430 } 431 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 432 ierr = PetscFPTrapPush(PETSC_FP_TRAP_OFF);CHKERRQ(ierr); 433 LAPACKgetrf_(&m,&n,mat->v,&mat->lda,mat->pivots,&info); 434 ierr = PetscFPTrapPop();CHKERRQ(ierr); 435 436 if (info<0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_LIB,"Bad argument to LU factorization"); 437 if (info>0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Bad LU factorization"); 438 A->ops->solve = MatSolve_SeqDense; 439 A->ops->solvetranspose = MatSolveTranspose_SeqDense; 440 A->ops->solveadd = MatSolveAdd_SeqDense; 441 A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 442 A->factortype = MAT_FACTOR_LU; 443 444 ierr = PetscLogFlops((2.0*A->cmap->n*A->cmap->n*A->cmap->n)/3);CHKERRQ(ierr); 445 #endif 446 PetscFunctionReturn(0); 447 } 448 449 #undef __FUNCT__ 450 #define __FUNCT__ "MatCholeskyFactor_SeqDense" 451 PetscErrorCode MatCholeskyFactor_SeqDense(Mat A,IS perm,const MatFactorInfo *factinfo) 452 { 453 #if defined(PETSC_MISSING_LAPACK_POTRF) 454 PetscFunctionBegin; 455 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"POTRF - Lapack routine is unavailable."); 456 #else 457 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 458 PetscErrorCode ierr; 459 PetscBLASInt info,n = PetscBLASIntCast(A->cmap->n); 460 461 PetscFunctionBegin; 462 ierr = PetscFree(mat->pivots);CHKERRQ(ierr); 463 464 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 465 LAPACKpotrf_("L",&n,mat->v,&mat->lda,&info); 466 if (info) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_MAT_CH_ZRPVT,"Bad factorization: zero pivot in row %D",(PetscInt)info-1); 467 A->ops->solve = MatSolve_SeqDense; 468 A->ops->solvetranspose = MatSolveTranspose_SeqDense; 469 A->ops->solveadd = MatSolveAdd_SeqDense; 470 A->ops->solvetransposeadd = MatSolveTransposeAdd_SeqDense; 471 A->factortype = MAT_FACTOR_CHOLESKY; 472 ierr = PetscLogFlops((A->cmap->n*A->cmap->n*A->cmap->n)/3.0);CHKERRQ(ierr); 473 #endif 474 PetscFunctionReturn(0); 475 } 476 477 478 #undef __FUNCT__ 479 #define __FUNCT__ "MatCholeskyFactorNumeric_SeqDense" 480 PetscErrorCode MatCholeskyFactorNumeric_SeqDense(Mat fact,Mat A,const MatFactorInfo *info_dummy) 481 { 482 PetscErrorCode ierr; 483 MatFactorInfo info; 484 485 PetscFunctionBegin; 486 info.fill = 1.0; 487 ierr = MatDuplicateNoCreate_SeqDense(fact,A,MAT_COPY_VALUES);CHKERRQ(ierr); 488 ierr = MatCholeskyFactor_SeqDense(fact,0,&info);CHKERRQ(ierr); 489 PetscFunctionReturn(0); 490 } 491 492 #undef __FUNCT__ 493 #define __FUNCT__ "MatCholeskyFactorSymbolic_SeqDense" 494 PetscErrorCode MatCholeskyFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,const MatFactorInfo *info) 495 { 496 PetscFunctionBegin; 497 fact->assembled = PETSC_TRUE; 498 fact->preallocated = PETSC_TRUE; 499 fact->ops->choleskyfactornumeric = MatCholeskyFactorNumeric_SeqDense; 500 PetscFunctionReturn(0); 501 } 502 503 #undef __FUNCT__ 504 #define __FUNCT__ "MatLUFactorSymbolic_SeqDense" 505 PetscErrorCode MatLUFactorSymbolic_SeqDense(Mat fact,Mat A,IS row,IS col,const MatFactorInfo *info) 506 { 507 PetscFunctionBegin; 508 fact->preallocated = PETSC_TRUE; 509 fact->assembled = PETSC_TRUE; 510 fact->ops->lufactornumeric = MatLUFactorNumeric_SeqDense; 511 PetscFunctionReturn(0); 512 } 513 514 EXTERN_C_BEGIN 515 #undef __FUNCT__ 516 #define __FUNCT__ "MatGetFactor_seqdense_petsc" 517 PetscErrorCode MatGetFactor_seqdense_petsc(Mat A,MatFactorType ftype,Mat *fact) 518 { 519 PetscErrorCode ierr; 520 521 PetscFunctionBegin; 522 ierr = MatCreate(((PetscObject)A)->comm,fact);CHKERRQ(ierr); 523 ierr = MatSetSizes(*fact,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 524 ierr = MatSetType(*fact,((PetscObject)A)->type_name);CHKERRQ(ierr); 525 if (ftype == MAT_FACTOR_LU){ 526 (*fact)->ops->lufactorsymbolic = MatLUFactorSymbolic_SeqDense; 527 } else { 528 (*fact)->ops->choleskyfactorsymbolic = MatCholeskyFactorSymbolic_SeqDense; 529 } 530 (*fact)->factortype = ftype; 531 PetscFunctionReturn(0); 532 } 533 EXTERN_C_END 534 535 /* ------------------------------------------------------------------*/ 536 #undef __FUNCT__ 537 #define __FUNCT__ "MatSOR_SeqDense" 538 PetscErrorCode MatSOR_SeqDense(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal shift,PetscInt its,PetscInt lits,Vec xx) 539 { 540 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 541 PetscScalar *x,*b,*v = mat->v,zero = 0.0,xt; 542 PetscErrorCode ierr; 543 PetscInt m = A->rmap->n,i; 544 PetscBLASInt o = 1,bm = PetscBLASIntCast(m); 545 546 PetscFunctionBegin; 547 if (flag & SOR_ZERO_INITIAL_GUESS) { 548 /* this is a hack fix, should have another version without the second BLASdot */ 549 ierr = VecSet(xx,zero);CHKERRQ(ierr); 550 } 551 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 552 ierr = VecGetArray(bb,&b);CHKERRQ(ierr); 553 its = its*lits; 554 if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits); 555 while (its--) { 556 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 557 for (i=0; i<m; i++) { 558 xt = b[i] - BLASdot_(&bm,v+i,&bm,x,&o); 559 x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift); 560 } 561 } 562 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 563 for (i=m-1; i>=0; i--) { 564 xt = b[i] - BLASdot_(&bm,v+i,&bm,x,&o); 565 x[i] = (1. - omega)*x[i] + omega*(xt+v[i + i*m]*x[i])/(v[i + i*m]+shift); 566 } 567 } 568 } 569 ierr = VecRestoreArray(bb,&b);CHKERRQ(ierr); 570 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 571 PetscFunctionReturn(0); 572 } 573 574 /* -----------------------------------------------------------------*/ 575 #undef __FUNCT__ 576 #define __FUNCT__ "MatMultTranspose_SeqDense" 577 PetscErrorCode MatMultTranspose_SeqDense(Mat A,Vec xx,Vec yy) 578 { 579 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 580 PetscScalar *v = mat->v,*x,*y; 581 PetscErrorCode ierr; 582 PetscBLASInt m, n,_One=1; 583 PetscScalar _DOne=1.0,_DZero=0.0; 584 585 PetscFunctionBegin; 586 m = PetscBLASIntCast(A->rmap->n); 587 n = PetscBLASIntCast(A->cmap->n); 588 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 589 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 590 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 591 BLASgemv_("T",&m,&n,&_DOne,v,&mat->lda,x,&_One,&_DZero,y,&_One); 592 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 593 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 594 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->cmap->n);CHKERRQ(ierr); 595 PetscFunctionReturn(0); 596 } 597 598 #undef __FUNCT__ 599 #define __FUNCT__ "MatMult_SeqDense" 600 PetscErrorCode MatMult_SeqDense(Mat A,Vec xx,Vec yy) 601 { 602 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 603 PetscScalar *v = mat->v,*x,*y,_DOne=1.0,_DZero=0.0; 604 PetscErrorCode ierr; 605 PetscBLASInt m, n, _One=1; 606 607 PetscFunctionBegin; 608 m = PetscBLASIntCast(A->rmap->n); 609 n = PetscBLASIntCast(A->cmap->n); 610 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 611 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 612 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 613 BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DZero,y,&_One); 614 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 615 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 616 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n - A->rmap->n);CHKERRQ(ierr); 617 PetscFunctionReturn(0); 618 } 619 620 #undef __FUNCT__ 621 #define __FUNCT__ "MatMultAdd_SeqDense" 622 PetscErrorCode MatMultAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 623 { 624 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 625 PetscScalar *v = mat->v,*x,*y,_DOne=1.0; 626 PetscErrorCode ierr; 627 PetscBLASInt m, n, _One=1; 628 629 PetscFunctionBegin; 630 m = PetscBLASIntCast(A->rmap->n); 631 n = PetscBLASIntCast(A->cmap->n); 632 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 633 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 634 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 635 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 636 BLASgemv_("N",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One); 637 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 638 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 639 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 640 PetscFunctionReturn(0); 641 } 642 643 #undef __FUNCT__ 644 #define __FUNCT__ "MatMultTransposeAdd_SeqDense" 645 PetscErrorCode MatMultTransposeAdd_SeqDense(Mat A,Vec xx,Vec zz,Vec yy) 646 { 647 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 648 PetscScalar *v = mat->v,*x,*y; 649 PetscErrorCode ierr; 650 PetscBLASInt m, n, _One=1; 651 PetscScalar _DOne=1.0; 652 653 PetscFunctionBegin; 654 m = PetscBLASIntCast(A->rmap->n); 655 n = PetscBLASIntCast(A->cmap->n); 656 if (!A->rmap->n || !A->cmap->n) PetscFunctionReturn(0); 657 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 658 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 659 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 660 BLASgemv_("T",&m,&n,&_DOne,v,&(mat->lda),x,&_One,&_DOne,y,&_One); 661 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 662 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 663 ierr = PetscLogFlops(2.0*A->rmap->n*A->cmap->n);CHKERRQ(ierr); 664 PetscFunctionReturn(0); 665 } 666 667 /* -----------------------------------------------------------------*/ 668 #undef __FUNCT__ 669 #define __FUNCT__ "MatGetRow_SeqDense" 670 PetscErrorCode MatGetRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 671 { 672 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 673 PetscScalar *v; 674 PetscErrorCode ierr; 675 PetscInt i; 676 677 PetscFunctionBegin; 678 *ncols = A->cmap->n; 679 if (cols) { 680 ierr = PetscMalloc((A->cmap->n+1)*sizeof(PetscInt),cols);CHKERRQ(ierr); 681 for (i=0; i<A->cmap->n; i++) (*cols)[i] = i; 682 } 683 if (vals) { 684 ierr = PetscMalloc((A->cmap->n+1)*sizeof(PetscScalar),vals);CHKERRQ(ierr); 685 v = mat->v + row; 686 for (i=0; i<A->cmap->n; i++) {(*vals)[i] = *v; v += mat->lda;} 687 } 688 PetscFunctionReturn(0); 689 } 690 691 #undef __FUNCT__ 692 #define __FUNCT__ "MatRestoreRow_SeqDense" 693 PetscErrorCode MatRestoreRow_SeqDense(Mat A,PetscInt row,PetscInt *ncols,PetscInt **cols,PetscScalar **vals) 694 { 695 PetscErrorCode ierr; 696 PetscFunctionBegin; 697 if (cols) {ierr = PetscFree(*cols);CHKERRQ(ierr);} 698 if (vals) {ierr = PetscFree(*vals);CHKERRQ(ierr); } 699 PetscFunctionReturn(0); 700 } 701 /* ----------------------------------------------------------------*/ 702 #undef __FUNCT__ 703 #define __FUNCT__ "MatSetValues_SeqDense" 704 PetscErrorCode MatSetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],const PetscScalar v[],InsertMode addv) 705 { 706 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 707 PetscInt i,j,idx=0; 708 709 PetscFunctionBegin; 710 if (v) PetscValidScalarPointer(v,6); 711 if (!mat->roworiented) { 712 if (addv == INSERT_VALUES) { 713 for (j=0; j<n; j++) { 714 if (indexn[j] < 0) {idx += m; continue;} 715 #if defined(PETSC_USE_DEBUG) 716 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 717 #endif 718 for (i=0; i<m; i++) { 719 if (indexm[i] < 0) {idx++; continue;} 720 #if defined(PETSC_USE_DEBUG) 721 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 722 #endif 723 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 724 } 725 } 726 } else { 727 for (j=0; j<n; j++) { 728 if (indexn[j] < 0) {idx += m; continue;} 729 #if defined(PETSC_USE_DEBUG) 730 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 731 #endif 732 for (i=0; i<m; i++) { 733 if (indexm[i] < 0) {idx++; continue;} 734 #if defined(PETSC_USE_DEBUG) 735 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 736 #endif 737 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 738 } 739 } 740 } 741 } else { 742 if (addv == INSERT_VALUES) { 743 for (i=0; i<m; i++) { 744 if (indexm[i] < 0) { idx += n; continue;} 745 #if defined(PETSC_USE_DEBUG) 746 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 747 #endif 748 for (j=0; j<n; j++) { 749 if (indexn[j] < 0) { idx++; continue;} 750 #if defined(PETSC_USE_DEBUG) 751 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 752 #endif 753 mat->v[indexn[j]*mat->lda + indexm[i]] = v[idx++]; 754 } 755 } 756 } else { 757 for (i=0; i<m; i++) { 758 if (indexm[i] < 0) { idx += n; continue;} 759 #if defined(PETSC_USE_DEBUG) 760 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",indexm[i],A->rmap->n-1); 761 #endif 762 for (j=0; j<n; j++) { 763 if (indexn[j] < 0) { idx++; continue;} 764 #if defined(PETSC_USE_DEBUG) 765 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",indexn[j],A->cmap->n-1); 766 #endif 767 mat->v[indexn[j]*mat->lda + indexm[i]] += v[idx++]; 768 } 769 } 770 } 771 } 772 PetscFunctionReturn(0); 773 } 774 775 #undef __FUNCT__ 776 #define __FUNCT__ "MatGetValues_SeqDense" 777 PetscErrorCode MatGetValues_SeqDense(Mat A,PetscInt m,const PetscInt indexm[],PetscInt n,const PetscInt indexn[],PetscScalar v[]) 778 { 779 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 780 PetscInt i,j; 781 782 PetscFunctionBegin; 783 /* row-oriented output */ 784 for (i=0; i<m; i++) { 785 if (indexm[i] < 0) {v += n;continue;} 786 if (indexm[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested larger than number rows %D",indexm[i],A->rmap->n); 787 for (j=0; j<n; j++) { 788 if (indexn[j] < 0) {v++; continue;} 789 if (indexn[j] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D requested larger than number columns %D",indexn[j],A->cmap->n); 790 *v++ = mat->v[indexn[j]*mat->lda + indexm[i]]; 791 } 792 } 793 PetscFunctionReturn(0); 794 } 795 796 /* -----------------------------------------------------------------*/ 797 798 #undef __FUNCT__ 799 #define __FUNCT__ "MatLoad_SeqDense" 800 PetscErrorCode MatLoad_SeqDense(Mat newmat,PetscViewer viewer) 801 { 802 Mat_SeqDense *a; 803 PetscErrorCode ierr; 804 PetscInt *scols,i,j,nz,header[4]; 805 int fd; 806 PetscMPIInt size; 807 PetscInt *rowlengths = 0,M,N,*cols,grows,gcols; 808 PetscScalar *vals,*svals,*v,*w; 809 MPI_Comm comm = ((PetscObject)viewer)->comm; 810 811 PetscFunctionBegin; 812 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 813 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor"); 814 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 815 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 816 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Not matrix object"); 817 M = header[1]; N = header[2]; nz = header[3]; 818 819 /* set global size if not set already*/ 820 if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) { 821 ierr = MatSetSizes(newmat,M,N,M,N);CHKERRQ(ierr); 822 } else { 823 /* if sizes and type are already set, check if the vector global sizes are correct */ 824 ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr); 825 if (M != grows || N != gcols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,grows,gcols); 826 } 827 ierr = MatSeqDenseSetPreallocation(newmat,PETSC_NULL);CHKERRQ(ierr); 828 829 if (nz == MATRIX_BINARY_FORMAT_DENSE) { /* matrix in file is dense */ 830 a = (Mat_SeqDense*)newmat->data; 831 v = a->v; 832 /* Allocate some temp space to read in the values and then flip them 833 from row major to column major */ 834 ierr = PetscMalloc((M*N > 0 ? M*N : 1)*sizeof(PetscScalar),&w);CHKERRQ(ierr); 835 /* read in nonzero values */ 836 ierr = PetscBinaryRead(fd,w,M*N,PETSC_SCALAR);CHKERRQ(ierr); 837 /* now flip the values and store them in the matrix*/ 838 for (j=0; j<N; j++) { 839 for (i=0; i<M; i++) { 840 *v++ =w[i*N+j]; 841 } 842 } 843 ierr = PetscFree(w);CHKERRQ(ierr); 844 } else { 845 /* read row lengths */ 846 ierr = PetscMalloc((M+1)*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 847 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 848 849 a = (Mat_SeqDense*)newmat->data; 850 v = a->v; 851 852 /* read column indices and nonzeros */ 853 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&scols);CHKERRQ(ierr); 854 cols = scols; 855 ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr); 856 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&svals);CHKERRQ(ierr); 857 vals = svals; 858 ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr); 859 860 /* insert into matrix */ 861 for (i=0; i<M; i++) { 862 for (j=0; j<rowlengths[i]; j++) v[i+M*scols[j]] = svals[j]; 863 svals += rowlengths[i]; scols += rowlengths[i]; 864 } 865 ierr = PetscFree(vals);CHKERRQ(ierr); 866 ierr = PetscFree(cols);CHKERRQ(ierr); 867 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 868 } 869 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 870 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 871 872 PetscFunctionReturn(0); 873 } 874 875 #undef __FUNCT__ 876 #define __FUNCT__ "MatView_SeqDense_ASCII" 877 static PetscErrorCode MatView_SeqDense_ASCII(Mat A,PetscViewer viewer) 878 { 879 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 880 PetscErrorCode ierr; 881 PetscInt i,j; 882 const char *name; 883 PetscScalar *v; 884 PetscViewerFormat format; 885 #if defined(PETSC_USE_COMPLEX) 886 PetscBool allreal = PETSC_TRUE; 887 #endif 888 889 PetscFunctionBegin; 890 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 891 if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) { 892 PetscFunctionReturn(0); /* do nothing for now */ 893 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 894 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 895 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer,"Matrix Object");CHKERRQ(ierr); 896 for (i=0; i<A->rmap->n; i++) { 897 v = a->v + i; 898 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 899 for (j=0; j<A->cmap->n; j++) { 900 #if defined(PETSC_USE_COMPLEX) 901 if (PetscRealPart(*v) != 0.0 && PetscImaginaryPart(*v) != 0.0) { 902 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %G i) ",j,PetscRealPart(*v),PetscImaginaryPart(*v));CHKERRQ(ierr); 903 } else if (PetscRealPart(*v)) { 904 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",j,PetscRealPart(*v));CHKERRQ(ierr); 905 } 906 #else 907 if (*v) { 908 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",j,*v);CHKERRQ(ierr); 909 } 910 #endif 911 v += a->lda; 912 } 913 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 914 } 915 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 916 } else { 917 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); 918 #if defined(PETSC_USE_COMPLEX) 919 /* determine if matrix has all real values */ 920 v = a->v; 921 for (i=0; i<A->rmap->n*A->cmap->n; i++) { 922 if (PetscImaginaryPart(v[i])) { allreal = PETSC_FALSE; break ;} 923 } 924 #endif 925 if (format == PETSC_VIEWER_ASCII_MATLAB) { 926 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 927 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",A->rmap->n,A->cmap->n);CHKERRQ(ierr); 928 ierr = PetscViewerASCIIPrintf(viewer,"%s = zeros(%D,%D);\n",name,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 929 ierr = PetscViewerASCIIPrintf(viewer,"%s = [\n",name);CHKERRQ(ierr); 930 } else { 931 ierr = PetscObjectPrintClassNamePrefixType((PetscObject)A,viewer,"Matrix Object");CHKERRQ(ierr); 932 } 933 934 for (i=0; i<A->rmap->n; i++) { 935 v = a->v + i; 936 for (j=0; j<A->cmap->n; j++) { 937 #if defined(PETSC_USE_COMPLEX) 938 if (allreal) { 939 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)PetscRealPart(*v));CHKERRQ(ierr); 940 } else { 941 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e + %18.16ei ",(double)PetscRealPart(*v),(double)PetscImaginaryPart(*v));CHKERRQ(ierr); 942 } 943 #else 944 ierr = PetscViewerASCIIPrintf(viewer,"%18.16e ",(double)*v);CHKERRQ(ierr); 945 #endif 946 v += a->lda; 947 } 948 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 949 } 950 if (format == PETSC_VIEWER_ASCII_MATLAB) { 951 ierr = PetscViewerASCIIPrintf(viewer,"];\n");CHKERRQ(ierr); 952 } 953 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); 954 } 955 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 956 PetscFunctionReturn(0); 957 } 958 959 #undef __FUNCT__ 960 #define __FUNCT__ "MatView_SeqDense_Binary" 961 static PetscErrorCode MatView_SeqDense_Binary(Mat A,PetscViewer viewer) 962 { 963 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 964 PetscErrorCode ierr; 965 int fd; 966 PetscInt ict,j,n = A->cmap->n,m = A->rmap->n,i,*col_lens,nz = m*n; 967 PetscScalar *v,*anonz,*vals; 968 PetscViewerFormat format; 969 970 PetscFunctionBegin; 971 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 972 973 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 974 if (format == PETSC_VIEWER_NATIVE) { 975 /* store the matrix as a dense matrix */ 976 ierr = PetscMalloc(4*sizeof(PetscInt),&col_lens);CHKERRQ(ierr); 977 col_lens[0] = MAT_FILE_CLASSID; 978 col_lens[1] = m; 979 col_lens[2] = n; 980 col_lens[3] = MATRIX_BINARY_FORMAT_DENSE; 981 ierr = PetscBinaryWrite(fd,col_lens,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 982 ierr = PetscFree(col_lens);CHKERRQ(ierr); 983 984 /* write out matrix, by rows */ 985 ierr = PetscMalloc((m*n+1)*sizeof(PetscScalar),&vals);CHKERRQ(ierr); 986 v = a->v; 987 for (j=0; j<n; j++) { 988 for (i=0; i<m; i++) { 989 vals[j + i*n] = *v++; 990 } 991 } 992 ierr = PetscBinaryWrite(fd,vals,n*m,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 993 ierr = PetscFree(vals);CHKERRQ(ierr); 994 } else { 995 ierr = PetscMalloc((4+nz)*sizeof(PetscInt),&col_lens);CHKERRQ(ierr); 996 col_lens[0] = MAT_FILE_CLASSID; 997 col_lens[1] = m; 998 col_lens[2] = n; 999 col_lens[3] = nz; 1000 1001 /* store lengths of each row and write (including header) to file */ 1002 for (i=0; i<m; i++) col_lens[4+i] = n; 1003 ierr = PetscBinaryWrite(fd,col_lens,4+m,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 1004 1005 /* Possibly should write in smaller increments, not whole matrix at once? */ 1006 /* store column indices (zero start index) */ 1007 ict = 0; 1008 for (i=0; i<m; i++) { 1009 for (j=0; j<n; j++) col_lens[ict++] = j; 1010 } 1011 ierr = PetscBinaryWrite(fd,col_lens,nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 1012 ierr = PetscFree(col_lens);CHKERRQ(ierr); 1013 1014 /* store nonzero values */ 1015 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&anonz);CHKERRQ(ierr); 1016 ict = 0; 1017 for (i=0; i<m; i++) { 1018 v = a->v + i; 1019 for (j=0; j<n; j++) { 1020 anonz[ict++] = *v; v += a->lda; 1021 } 1022 } 1023 ierr = PetscBinaryWrite(fd,anonz,nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 1024 ierr = PetscFree(anonz);CHKERRQ(ierr); 1025 } 1026 PetscFunctionReturn(0); 1027 } 1028 1029 #undef __FUNCT__ 1030 #define __FUNCT__ "MatView_SeqDense_Draw_Zoom" 1031 PetscErrorCode MatView_SeqDense_Draw_Zoom(PetscDraw draw,void *Aa) 1032 { 1033 Mat A = (Mat) Aa; 1034 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1035 PetscErrorCode ierr; 1036 PetscInt m = A->rmap->n,n = A->cmap->n,color,i,j; 1037 PetscScalar *v = a->v; 1038 PetscViewer viewer; 1039 PetscDraw popup; 1040 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r,scale,maxv = 0.0; 1041 PetscViewerFormat format; 1042 1043 PetscFunctionBegin; 1044 1045 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 1046 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 1047 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 1048 1049 /* Loop over matrix elements drawing boxes */ 1050 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 1051 /* Blue for negative and Red for positive */ 1052 color = PETSC_DRAW_BLUE; 1053 for(j = 0; j < n; j++) { 1054 x_l = j; 1055 x_r = x_l + 1.0; 1056 for(i = 0; i < m; i++) { 1057 y_l = m - i - 1.0; 1058 y_r = y_l + 1.0; 1059 #if defined(PETSC_USE_COMPLEX) 1060 if (PetscRealPart(v[j*m+i]) > 0.) { 1061 color = PETSC_DRAW_RED; 1062 } else if (PetscRealPart(v[j*m+i]) < 0.) { 1063 color = PETSC_DRAW_BLUE; 1064 } else { 1065 continue; 1066 } 1067 #else 1068 if (v[j*m+i] > 0.) { 1069 color = PETSC_DRAW_RED; 1070 } else if (v[j*m+i] < 0.) { 1071 color = PETSC_DRAW_BLUE; 1072 } else { 1073 continue; 1074 } 1075 #endif 1076 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1077 } 1078 } 1079 } else { 1080 /* use contour shading to indicate magnitude of values */ 1081 /* first determine max of all nonzero values */ 1082 for(i = 0; i < m*n; i++) { 1083 if (PetscAbsScalar(v[i]) > maxv) maxv = PetscAbsScalar(v[i]); 1084 } 1085 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 1086 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 1087 if (popup) {ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr);} 1088 for(j = 0; j < n; j++) { 1089 x_l = j; 1090 x_r = x_l + 1.0; 1091 for(i = 0; i < m; i++) { 1092 y_l = m - i - 1.0; 1093 y_r = y_l + 1.0; 1094 color = PETSC_DRAW_BASIC_COLORS + (int)(scale*PetscAbsScalar(v[j*m+i])); 1095 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 1096 } 1097 } 1098 } 1099 PetscFunctionReturn(0); 1100 } 1101 1102 #undef __FUNCT__ 1103 #define __FUNCT__ "MatView_SeqDense_Draw" 1104 PetscErrorCode MatView_SeqDense_Draw(Mat A,PetscViewer viewer) 1105 { 1106 PetscDraw draw; 1107 PetscBool isnull; 1108 PetscReal xr,yr,xl,yl,h,w; 1109 PetscErrorCode ierr; 1110 1111 PetscFunctionBegin; 1112 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 1113 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 1114 if (isnull) PetscFunctionReturn(0); 1115 1116 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 1117 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 1118 xr += w; yr += h; xl = -w; yl = -h; 1119 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 1120 ierr = PetscDrawZoom(draw,MatView_SeqDense_Draw_Zoom,A);CHKERRQ(ierr); 1121 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); 1122 PetscFunctionReturn(0); 1123 } 1124 1125 #undef __FUNCT__ 1126 #define __FUNCT__ "MatView_SeqDense" 1127 PetscErrorCode MatView_SeqDense(Mat A,PetscViewer viewer) 1128 { 1129 PetscErrorCode ierr; 1130 PetscBool iascii,isbinary,isdraw; 1131 1132 PetscFunctionBegin; 1133 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 1134 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 1135 ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 1136 1137 if (iascii) { 1138 ierr = MatView_SeqDense_ASCII(A,viewer);CHKERRQ(ierr); 1139 } else if (isbinary) { 1140 ierr = MatView_SeqDense_Binary(A,viewer);CHKERRQ(ierr); 1141 } else if (isdraw) { 1142 ierr = MatView_SeqDense_Draw(A,viewer);CHKERRQ(ierr); 1143 } else { 1144 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Viewer type %s not supported by dense matrix",((PetscObject)viewer)->type_name); 1145 } 1146 PetscFunctionReturn(0); 1147 } 1148 1149 #undef __FUNCT__ 1150 #define __FUNCT__ "MatDestroy_SeqDense" 1151 PetscErrorCode MatDestroy_SeqDense(Mat mat) 1152 { 1153 Mat_SeqDense *l = (Mat_SeqDense*)mat->data; 1154 PetscErrorCode ierr; 1155 1156 PetscFunctionBegin; 1157 #if defined(PETSC_USE_LOG) 1158 PetscLogObjectState((PetscObject)mat,"Rows %D Cols %D",mat->rmap->n,mat->cmap->n); 1159 #endif 1160 ierr = PetscFree(l->pivots);CHKERRQ(ierr); 1161 if (!l->user_alloc) {ierr = PetscFree(l->v);CHKERRQ(ierr);} 1162 ierr = PetscFree(mat->data);CHKERRQ(ierr); 1163 1164 ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr); 1165 ierr = PetscObjectComposeFunctionDynamic((PetscObject)mat,"MatSeqDenseSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 1166 ierr = PetscObjectComposeFunctionDynamic((PetscObject)mat,"MatMatMult_seqaij_seqdense_C","",PETSC_NULL);CHKERRQ(ierr); 1167 ierr = PetscObjectComposeFunctionDynamic((PetscObject)mat,"MatMatMultSymbolic_seqaij_seqdense_C","",PETSC_NULL);CHKERRQ(ierr); 1168 ierr = PetscObjectComposeFunctionDynamic((PetscObject)mat,"MatMatMultNumeric_seqaij_seqdense_C","",PETSC_NULL);CHKERRQ(ierr); 1169 PetscFunctionReturn(0); 1170 } 1171 1172 #undef __FUNCT__ 1173 #define __FUNCT__ "MatTranspose_SeqDense" 1174 PetscErrorCode MatTranspose_SeqDense(Mat A,MatReuse reuse,Mat *matout) 1175 { 1176 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1177 PetscErrorCode ierr; 1178 PetscInt k,j,m,n,M; 1179 PetscScalar *v,tmp; 1180 1181 PetscFunctionBegin; 1182 v = mat->v; m = A->rmap->n; M = mat->lda; n = A->cmap->n; 1183 if (reuse == MAT_REUSE_MATRIX && *matout == A) { /* in place transpose */ 1184 if (m != n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can not transpose non-square matrix in place"); 1185 else { 1186 for (j=0; j<m; j++) { 1187 for (k=0; k<j; k++) { 1188 tmp = v[j + k*M]; 1189 v[j + k*M] = v[k + j*M]; 1190 v[k + j*M] = tmp; 1191 } 1192 } 1193 } 1194 } else { /* out-of-place transpose */ 1195 Mat tmat; 1196 Mat_SeqDense *tmatd; 1197 PetscScalar *v2; 1198 1199 if (reuse == MAT_INITIAL_MATRIX) { 1200 ierr = MatCreate(((PetscObject)A)->comm,&tmat);CHKERRQ(ierr); 1201 ierr = MatSetSizes(tmat,A->cmap->n,A->rmap->n,A->cmap->n,A->rmap->n);CHKERRQ(ierr); 1202 ierr = MatSetType(tmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1203 ierr = MatSeqDenseSetPreallocation(tmat,PETSC_NULL);CHKERRQ(ierr); 1204 } else { 1205 tmat = *matout; 1206 } 1207 tmatd = (Mat_SeqDense*)tmat->data; 1208 v = mat->v; v2 = tmatd->v; 1209 for (j=0; j<n; j++) { 1210 for (k=0; k<m; k++) v2[j + k*n] = v[k + j*M]; 1211 } 1212 ierr = MatAssemblyBegin(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1213 ierr = MatAssemblyEnd(tmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1214 *matout = tmat; 1215 } 1216 PetscFunctionReturn(0); 1217 } 1218 1219 #undef __FUNCT__ 1220 #define __FUNCT__ "MatEqual_SeqDense" 1221 PetscErrorCode MatEqual_SeqDense(Mat A1,Mat A2,PetscBool *flg) 1222 { 1223 Mat_SeqDense *mat1 = (Mat_SeqDense*)A1->data; 1224 Mat_SeqDense *mat2 = (Mat_SeqDense*)A2->data; 1225 PetscInt i,j; 1226 PetscScalar *v1 = mat1->v,*v2 = mat2->v; 1227 1228 PetscFunctionBegin; 1229 if (A1->rmap->n != A2->rmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1230 if (A1->cmap->n != A2->cmap->n) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1231 for (i=0; i<A1->rmap->n; i++) { 1232 v1 = mat1->v+i; v2 = mat2->v+i; 1233 for (j=0; j<A1->cmap->n; j++) { 1234 if (*v1 != *v2) {*flg = PETSC_FALSE; PetscFunctionReturn(0);} 1235 v1 += mat1->lda; v2 += mat2->lda; 1236 } 1237 } 1238 *flg = PETSC_TRUE; 1239 PetscFunctionReturn(0); 1240 } 1241 1242 #undef __FUNCT__ 1243 #define __FUNCT__ "MatGetDiagonal_SeqDense" 1244 PetscErrorCode MatGetDiagonal_SeqDense(Mat A,Vec v) 1245 { 1246 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1247 PetscErrorCode ierr; 1248 PetscInt i,n,len; 1249 PetscScalar *x,zero = 0.0; 1250 1251 PetscFunctionBegin; 1252 ierr = VecSet(v,zero);CHKERRQ(ierr); 1253 ierr = VecGetSize(v,&n);CHKERRQ(ierr); 1254 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1255 len = PetscMin(A->rmap->n,A->cmap->n); 1256 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming mat and vec"); 1257 for (i=0; i<len; i++) { 1258 x[i] = mat->v[i*mat->lda + i]; 1259 } 1260 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1261 PetscFunctionReturn(0); 1262 } 1263 1264 #undef __FUNCT__ 1265 #define __FUNCT__ "MatDiagonalScale_SeqDense" 1266 PetscErrorCode MatDiagonalScale_SeqDense(Mat A,Vec ll,Vec rr) 1267 { 1268 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1269 PetscScalar *l,*r,x,*v; 1270 PetscErrorCode ierr; 1271 PetscInt i,j,m = A->rmap->n,n = A->cmap->n; 1272 1273 PetscFunctionBegin; 1274 if (ll) { 1275 ierr = VecGetSize(ll,&m);CHKERRQ(ierr); 1276 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 1277 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vec wrong size"); 1278 for (i=0; i<m; i++) { 1279 x = l[i]; 1280 v = mat->v + i; 1281 for (j=0; j<n; j++) { (*v) *= x; v+= m;} 1282 } 1283 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 1284 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 1285 } 1286 if (rr) { 1287 ierr = VecGetSize(rr,&n);CHKERRQ(ierr); 1288 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 1289 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vec wrong size"); 1290 for (i=0; i<n; i++) { 1291 x = r[i]; 1292 v = mat->v + i*m; 1293 for (j=0; j<m; j++) { (*v++) *= x;} 1294 } 1295 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 1296 ierr = PetscLogFlops(n*m);CHKERRQ(ierr); 1297 } 1298 PetscFunctionReturn(0); 1299 } 1300 1301 #undef __FUNCT__ 1302 #define __FUNCT__ "MatNorm_SeqDense" 1303 PetscErrorCode MatNorm_SeqDense(Mat A,NormType type,PetscReal *nrm) 1304 { 1305 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1306 PetscScalar *v = mat->v; 1307 PetscReal sum = 0.0; 1308 PetscInt lda=mat->lda,m=A->rmap->n,i,j; 1309 PetscErrorCode ierr; 1310 1311 PetscFunctionBegin; 1312 if (type == NORM_FROBENIUS) { 1313 if (lda>m) { 1314 for (j=0; j<A->cmap->n; j++) { 1315 v = mat->v+j*lda; 1316 for (i=0; i<m; i++) { 1317 #if defined(PETSC_USE_COMPLEX) 1318 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1319 #else 1320 sum += (*v)*(*v); v++; 1321 #endif 1322 } 1323 } 1324 } else { 1325 for (i=0; i<A->cmap->n*A->rmap->n; i++) { 1326 #if defined(PETSC_USE_COMPLEX) 1327 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1328 #else 1329 sum += (*v)*(*v); v++; 1330 #endif 1331 } 1332 } 1333 *nrm = PetscSqrtReal(sum); 1334 ierr = PetscLogFlops(2.0*A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1335 } else if (type == NORM_1) { 1336 *nrm = 0.0; 1337 for (j=0; j<A->cmap->n; j++) { 1338 v = mat->v + j*mat->lda; 1339 sum = 0.0; 1340 for (i=0; i<A->rmap->n; i++) { 1341 sum += PetscAbsScalar(*v); v++; 1342 } 1343 if (sum > *nrm) *nrm = sum; 1344 } 1345 ierr = PetscLogFlops(A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1346 } else if (type == NORM_INFINITY) { 1347 *nrm = 0.0; 1348 for (j=0; j<A->rmap->n; j++) { 1349 v = mat->v + j; 1350 sum = 0.0; 1351 for (i=0; i<A->cmap->n; i++) { 1352 sum += PetscAbsScalar(*v); v += mat->lda; 1353 } 1354 if (sum > *nrm) *nrm = sum; 1355 } 1356 ierr = PetscLogFlops(A->cmap->n*A->rmap->n);CHKERRQ(ierr); 1357 } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No two norm"); 1358 PetscFunctionReturn(0); 1359 } 1360 1361 #undef __FUNCT__ 1362 #define __FUNCT__ "MatSetOption_SeqDense" 1363 PetscErrorCode MatSetOption_SeqDense(Mat A,MatOption op,PetscBool flg) 1364 { 1365 Mat_SeqDense *aij = (Mat_SeqDense*)A->data; 1366 PetscErrorCode ierr; 1367 1368 PetscFunctionBegin; 1369 switch (op) { 1370 case MAT_ROW_ORIENTED: 1371 aij->roworiented = flg; 1372 break; 1373 case MAT_NEW_NONZERO_LOCATIONS: 1374 case MAT_NEW_NONZERO_LOCATION_ERR: 1375 case MAT_NEW_NONZERO_ALLOCATION_ERR: 1376 case MAT_NEW_DIAGONALS: 1377 case MAT_KEEP_NONZERO_PATTERN: 1378 case MAT_IGNORE_OFF_PROC_ENTRIES: 1379 case MAT_USE_HASH_TABLE: 1380 case MAT_SYMMETRIC: 1381 case MAT_STRUCTURALLY_SYMMETRIC: 1382 case MAT_HERMITIAN: 1383 case MAT_SYMMETRY_ETERNAL: 1384 case MAT_IGNORE_LOWER_TRIANGULAR: 1385 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 1386 break; 1387 default: 1388 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %s",MatOptions[op]); 1389 } 1390 PetscFunctionReturn(0); 1391 } 1392 1393 #undef __FUNCT__ 1394 #define __FUNCT__ "MatZeroEntries_SeqDense" 1395 PetscErrorCode MatZeroEntries_SeqDense(Mat A) 1396 { 1397 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1398 PetscErrorCode ierr; 1399 PetscInt lda=l->lda,m=A->rmap->n,j; 1400 1401 PetscFunctionBegin; 1402 if (lda>m) { 1403 for (j=0; j<A->cmap->n; j++) { 1404 ierr = PetscMemzero(l->v+j*lda,m*sizeof(PetscScalar));CHKERRQ(ierr); 1405 } 1406 } else { 1407 ierr = PetscMemzero(l->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1408 } 1409 PetscFunctionReturn(0); 1410 } 1411 1412 #undef __FUNCT__ 1413 #define __FUNCT__ "MatZeroRows_SeqDense" 1414 PetscErrorCode MatZeroRows_SeqDense(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) 1415 { 1416 PetscErrorCode ierr; 1417 Mat_SeqDense *l = (Mat_SeqDense*)A->data; 1418 PetscInt m = l->lda, n = A->cmap->n, i,j; 1419 PetscScalar *slot,*bb; 1420 const PetscScalar *xx; 1421 1422 PetscFunctionBegin; 1423 #if defined(PETSC_USE_DEBUG) 1424 for (i=0; i<N; i++) { 1425 if (rows[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row requested to be zeroed"); 1426 if (rows[i] >= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D requested to be zeroed greater than or equal number of rows %D",rows[i],A->rmap->n); 1427 } 1428 #endif 1429 1430 /* fix right hand side if needed */ 1431 if (x && b) { 1432 ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); 1433 ierr = VecGetArray(b,&bb);CHKERRQ(ierr); 1434 for (i=0; i<N; i++) { 1435 bb[rows[i]] = diag*xx[rows[i]]; 1436 } 1437 ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); 1438 ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); 1439 } 1440 1441 for (i=0; i<N; i++) { 1442 slot = l->v + rows[i]; 1443 for (j=0; j<n; j++) { *slot = 0.0; slot += m;} 1444 } 1445 if (diag != 0.0) { 1446 if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only coded for square matrices"); 1447 for (i=0; i<N; i++) { 1448 slot = l->v + (m+1)*rows[i]; 1449 *slot = diag; 1450 } 1451 } 1452 PetscFunctionReturn(0); 1453 } 1454 1455 #undef __FUNCT__ 1456 #define __FUNCT__ "MatGetArray_SeqDense" 1457 PetscErrorCode MatGetArray_SeqDense(Mat A,PetscScalar *array[]) 1458 { 1459 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1460 1461 PetscFunctionBegin; 1462 if (mat->lda != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Cannot get array for Dense matrices with LDA different from number of rows"); 1463 *array = mat->v; 1464 PetscFunctionReturn(0); 1465 } 1466 1467 #undef __FUNCT__ 1468 #define __FUNCT__ "MatRestoreArray_SeqDense" 1469 PetscErrorCode MatRestoreArray_SeqDense(Mat A,PetscScalar *array[]) 1470 { 1471 PetscFunctionBegin; 1472 *array = 0; /* user cannot accidently use the array later */ 1473 PetscFunctionReturn(0); 1474 } 1475 1476 #undef __FUNCT__ 1477 #define __FUNCT__ "MatGetSubMatrix_SeqDense" 1478 static PetscErrorCode MatGetSubMatrix_SeqDense(Mat A,IS isrow,IS iscol,PetscInt cs,MatReuse scall,Mat *B) 1479 { 1480 Mat_SeqDense *mat = (Mat_SeqDense*)A->data; 1481 PetscErrorCode ierr; 1482 PetscInt i,j,nrows,ncols; 1483 const PetscInt *irow,*icol; 1484 PetscScalar *av,*bv,*v = mat->v; 1485 Mat newmat; 1486 1487 PetscFunctionBegin; 1488 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 1489 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 1490 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 1491 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 1492 1493 /* Check submatrixcall */ 1494 if (scall == MAT_REUSE_MATRIX) { 1495 PetscInt n_cols,n_rows; 1496 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 1497 if (n_rows != nrows || n_cols != ncols) { 1498 /* resize the result matrix to match number of requested rows/columns */ 1499 ierr = MatSetSizes(*B,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1500 } 1501 newmat = *B; 1502 } else { 1503 /* Create and fill new matrix */ 1504 ierr = MatCreate(((PetscObject)A)->comm,&newmat);CHKERRQ(ierr); 1505 ierr = MatSetSizes(newmat,nrows,ncols,nrows,ncols);CHKERRQ(ierr); 1506 ierr = MatSetType(newmat,((PetscObject)A)->type_name);CHKERRQ(ierr); 1507 ierr = MatSeqDenseSetPreallocation(newmat,PETSC_NULL);CHKERRQ(ierr); 1508 } 1509 1510 /* Now extract the data pointers and do the copy,column at a time */ 1511 bv = ((Mat_SeqDense*)newmat->data)->v; 1512 1513 for (i=0; i<ncols; i++) { 1514 av = v + mat->lda*icol[i]; 1515 for (j=0; j<nrows; j++) { 1516 *bv++ = av[irow[j]]; 1517 } 1518 } 1519 1520 /* Assemble the matrices so that the correct flags are set */ 1521 ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1522 ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1523 1524 /* Free work space */ 1525 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 1526 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 1527 *B = newmat; 1528 PetscFunctionReturn(0); 1529 } 1530 1531 #undef __FUNCT__ 1532 #define __FUNCT__ "MatGetSubMatrices_SeqDense" 1533 PetscErrorCode MatGetSubMatrices_SeqDense(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1534 { 1535 PetscErrorCode ierr; 1536 PetscInt i; 1537 1538 PetscFunctionBegin; 1539 if (scall == MAT_INITIAL_MATRIX) { 1540 ierr = PetscMalloc((n+1)*sizeof(Mat),B);CHKERRQ(ierr); 1541 } 1542 1543 for (i=0; i<n; i++) { 1544 ierr = MatGetSubMatrix_SeqDense(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1545 } 1546 PetscFunctionReturn(0); 1547 } 1548 1549 #undef __FUNCT__ 1550 #define __FUNCT__ "MatAssemblyBegin_SeqDense" 1551 PetscErrorCode MatAssemblyBegin_SeqDense(Mat mat,MatAssemblyType mode) 1552 { 1553 PetscFunctionBegin; 1554 PetscFunctionReturn(0); 1555 } 1556 1557 #undef __FUNCT__ 1558 #define __FUNCT__ "MatAssemblyEnd_SeqDense" 1559 PetscErrorCode MatAssemblyEnd_SeqDense(Mat mat,MatAssemblyType mode) 1560 { 1561 PetscFunctionBegin; 1562 PetscFunctionReturn(0); 1563 } 1564 1565 #undef __FUNCT__ 1566 #define __FUNCT__ "MatCopy_SeqDense" 1567 PetscErrorCode MatCopy_SeqDense(Mat A,Mat B,MatStructure str) 1568 { 1569 Mat_SeqDense *a = (Mat_SeqDense*)A->data,*b = (Mat_SeqDense *)B->data; 1570 PetscErrorCode ierr; 1571 PetscInt lda1=a->lda,lda2=b->lda, m=A->rmap->n,n=A->cmap->n, j; 1572 1573 PetscFunctionBegin; 1574 /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */ 1575 if (A->ops->copy != B->ops->copy) { 1576 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 1577 PetscFunctionReturn(0); 1578 } 1579 if (m != B->rmap->n || n != B->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"size(B) != size(A)"); 1580 if (lda1>m || lda2>m) { 1581 for (j=0; j<n; j++) { 1582 ierr = PetscMemcpy(b->v+j*lda2,a->v+j*lda1,m*sizeof(PetscScalar));CHKERRQ(ierr); 1583 } 1584 } else { 1585 ierr = PetscMemcpy(b->v,a->v,A->rmap->n*A->cmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1586 } 1587 PetscFunctionReturn(0); 1588 } 1589 1590 #undef __FUNCT__ 1591 #define __FUNCT__ "MatSetUp_SeqDense" 1592 PetscErrorCode MatSetUp_SeqDense(Mat A) 1593 { 1594 PetscErrorCode ierr; 1595 1596 PetscFunctionBegin; 1597 ierr = MatSeqDenseSetPreallocation(A,0);CHKERRQ(ierr); 1598 PetscFunctionReturn(0); 1599 } 1600 1601 #undef __FUNCT__ 1602 #define __FUNCT__ "MatConjugate_SeqDense" 1603 static PetscErrorCode MatConjugate_SeqDense(Mat A) 1604 { 1605 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1606 PetscInt i,nz = A->rmap->n*A->cmap->n; 1607 PetscScalar *aa = a->v; 1608 1609 PetscFunctionBegin; 1610 for (i=0; i<nz; i++) aa[i] = PetscConj(aa[i]); 1611 PetscFunctionReturn(0); 1612 } 1613 1614 #undef __FUNCT__ 1615 #define __FUNCT__ "MatRealPart_SeqDense" 1616 static PetscErrorCode MatRealPart_SeqDense(Mat A) 1617 { 1618 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1619 PetscInt i,nz = A->rmap->n*A->cmap->n; 1620 PetscScalar *aa = a->v; 1621 1622 PetscFunctionBegin; 1623 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 1624 PetscFunctionReturn(0); 1625 } 1626 1627 #undef __FUNCT__ 1628 #define __FUNCT__ "MatImaginaryPart_SeqDense" 1629 static PetscErrorCode MatImaginaryPart_SeqDense(Mat A) 1630 { 1631 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1632 PetscInt i,nz = A->rmap->n*A->cmap->n; 1633 PetscScalar *aa = a->v; 1634 1635 PetscFunctionBegin; 1636 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 1637 PetscFunctionReturn(0); 1638 } 1639 1640 /* ----------------------------------------------------------------*/ 1641 #undef __FUNCT__ 1642 #define __FUNCT__ "MatMatMult_SeqDense_SeqDense" 1643 PetscErrorCode MatMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1644 { 1645 PetscErrorCode ierr; 1646 1647 PetscFunctionBegin; 1648 if (scall == MAT_INITIAL_MATRIX){ 1649 ierr = MatMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1650 } 1651 ierr = MatMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1652 PetscFunctionReturn(0); 1653 } 1654 1655 #undef __FUNCT__ 1656 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqDense" 1657 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1658 { 1659 PetscErrorCode ierr; 1660 PetscInt m=A->rmap->n,n=B->cmap->n; 1661 Mat Cmat; 1662 1663 PetscFunctionBegin; 1664 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); 1665 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1666 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1667 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1668 ierr = MatSeqDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 1669 Cmat->assembled = PETSC_TRUE; 1670 Cmat->ops->matmult = MatMatMult_SeqDense_SeqDense; 1671 *C = Cmat; 1672 PetscFunctionReturn(0); 1673 } 1674 1675 #undef __FUNCT__ 1676 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqDense" 1677 PetscErrorCode MatMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1678 { 1679 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1680 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 1681 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 1682 PetscBLASInt m,n,k; 1683 PetscScalar _DOne=1.0,_DZero=0.0; 1684 1685 PetscFunctionBegin; 1686 m = PetscBLASIntCast(A->rmap->n); 1687 n = PetscBLASIntCast(B->cmap->n); 1688 k = PetscBLASIntCast(A->cmap->n); 1689 BLASgemm_("N","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda); 1690 PetscFunctionReturn(0); 1691 } 1692 1693 #undef __FUNCT__ 1694 #define __FUNCT__ "MatTransposeMatMult_SeqDense_SeqDense" 1695 PetscErrorCode MatTransposeMatMult_SeqDense_SeqDense(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 1696 { 1697 PetscErrorCode ierr; 1698 1699 PetscFunctionBegin; 1700 if (scall == MAT_INITIAL_MATRIX){ 1701 ierr = MatTransposeMatMultSymbolic_SeqDense_SeqDense(A,B,fill,C);CHKERRQ(ierr); 1702 } 1703 ierr = MatTransposeMatMultNumeric_SeqDense_SeqDense(A,B,*C);CHKERRQ(ierr); 1704 PetscFunctionReturn(0); 1705 } 1706 1707 #undef __FUNCT__ 1708 #define __FUNCT__ "MatTransposeMatMultSymbolic_SeqDense_SeqDense" 1709 PetscErrorCode MatTransposeMatMultSymbolic_SeqDense_SeqDense(Mat A,Mat B,PetscReal fill,Mat *C) 1710 { 1711 PetscErrorCode ierr; 1712 PetscInt m=A->cmap->n,n=B->cmap->n; 1713 Mat Cmat; 1714 1715 PetscFunctionBegin; 1716 if (A->rmap->n != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"A->rmap->n %d != B->rmap->n %d\n",A->rmap->n,B->rmap->n); 1717 ierr = MatCreate(PETSC_COMM_SELF,&Cmat);CHKERRQ(ierr); 1718 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 1719 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 1720 ierr = MatSeqDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 1721 Cmat->assembled = PETSC_TRUE; 1722 *C = Cmat; 1723 PetscFunctionReturn(0); 1724 } 1725 1726 #undef __FUNCT__ 1727 #define __FUNCT__ "MatTransposeMatMultNumeric_SeqDense_SeqDense" 1728 PetscErrorCode MatTransposeMatMultNumeric_SeqDense_SeqDense(Mat A,Mat B,Mat C) 1729 { 1730 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1731 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 1732 Mat_SeqDense *c = (Mat_SeqDense*)C->data; 1733 PetscBLASInt m,n,k; 1734 PetscScalar _DOne=1.0,_DZero=0.0; 1735 1736 PetscFunctionBegin; 1737 m = PetscBLASIntCast(A->cmap->n); 1738 n = PetscBLASIntCast(B->cmap->n); 1739 k = PetscBLASIntCast(A->rmap->n); 1740 /* 1741 Note the m and n arguments below are the number rows and columns of A', not A! 1742 */ 1743 BLASgemm_("T","N",&m,&n,&k,&_DOne,a->v,&a->lda,b->v,&b->lda,&_DZero,c->v,&c->lda); 1744 PetscFunctionReturn(0); 1745 } 1746 1747 #undef __FUNCT__ 1748 #define __FUNCT__ "MatGetRowMax_SeqDense" 1749 PetscErrorCode MatGetRowMax_SeqDense(Mat A,Vec v,PetscInt idx[]) 1750 { 1751 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1752 PetscErrorCode ierr; 1753 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 1754 PetscScalar *x; 1755 MatScalar *aa = a->v; 1756 1757 PetscFunctionBegin; 1758 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 1759 1760 ierr = VecSet(v,0.0);CHKERRQ(ierr); 1761 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1762 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 1763 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1764 for (i=0; i<m; i++) { 1765 x[i] = aa[i]; if (idx) idx[i] = 0; 1766 for (j=1; j<n; j++){ 1767 if (PetscRealPart(x[i]) < PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 1768 } 1769 } 1770 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1771 PetscFunctionReturn(0); 1772 } 1773 1774 #undef __FUNCT__ 1775 #define __FUNCT__ "MatGetRowMaxAbs_SeqDense" 1776 PetscErrorCode MatGetRowMaxAbs_SeqDense(Mat A,Vec v,PetscInt idx[]) 1777 { 1778 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1779 PetscErrorCode ierr; 1780 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 1781 PetscScalar *x; 1782 PetscReal atmp; 1783 MatScalar *aa = a->v; 1784 1785 PetscFunctionBegin; 1786 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 1787 1788 ierr = VecSet(v,0.0);CHKERRQ(ierr); 1789 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1790 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 1791 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1792 for (i=0; i<m; i++) { 1793 x[i] = PetscAbsScalar(aa[i]); 1794 for (j=1; j<n; j++){ 1795 atmp = PetscAbsScalar(aa[i+m*j]); 1796 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = j;} 1797 } 1798 } 1799 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1800 PetscFunctionReturn(0); 1801 } 1802 1803 #undef __FUNCT__ 1804 #define __FUNCT__ "MatGetRowMin_SeqDense" 1805 PetscErrorCode MatGetRowMin_SeqDense(Mat A,Vec v,PetscInt idx[]) 1806 { 1807 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1808 PetscErrorCode ierr; 1809 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,p; 1810 PetscScalar *x; 1811 MatScalar *aa = a->v; 1812 1813 PetscFunctionBegin; 1814 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 1815 1816 ierr = VecSet(v,0.0);CHKERRQ(ierr); 1817 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1818 ierr = VecGetLocalSize(v,&p);CHKERRQ(ierr); 1819 if (p != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 1820 for (i=0; i<m; i++) { 1821 x[i] = aa[i]; if (idx) idx[i] = 0; 1822 for (j=1; j<n; j++){ 1823 if (PetscRealPart(x[i]) > PetscRealPart(aa[i+m*j])) {x[i] = aa[i + m*j]; if (idx) idx[i] = j;} 1824 } 1825 } 1826 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1827 PetscFunctionReturn(0); 1828 } 1829 1830 #undef __FUNCT__ 1831 #define __FUNCT__ "MatGetColumnVector_SeqDense" 1832 PetscErrorCode MatGetColumnVector_SeqDense(Mat A,Vec v,PetscInt col) 1833 { 1834 Mat_SeqDense *a = (Mat_SeqDense*)A->data; 1835 PetscErrorCode ierr; 1836 PetscScalar *x; 1837 1838 PetscFunctionBegin; 1839 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 1840 1841 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 1842 ierr = PetscMemcpy(x,a->v+col*a->lda,A->rmap->n*sizeof(PetscScalar));CHKERRQ(ierr); 1843 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 1844 PetscFunctionReturn(0); 1845 } 1846 1847 1848 #undef __FUNCT__ 1849 #define __FUNCT__ "MatGetColumnNorms_SeqDense" 1850 PetscErrorCode MatGetColumnNorms_SeqDense(Mat A,NormType type,PetscReal *norms) 1851 { 1852 PetscErrorCode ierr; 1853 PetscInt i,j,m,n; 1854 PetscScalar *a; 1855 1856 PetscFunctionBegin; 1857 ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); 1858 ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); 1859 ierr = MatGetArray(A,&a);CHKERRQ(ierr); 1860 if (type == NORM_2) { 1861 for (i=0; i<n; i++ ){ 1862 for (j=0; j<m; j++) { 1863 norms[i] += PetscAbsScalar(a[j]*a[j]); 1864 } 1865 a += m; 1866 } 1867 } else if (type == NORM_1) { 1868 for (i=0; i<n; i++ ){ 1869 for (j=0; j<m; j++) { 1870 norms[i] += PetscAbsScalar(a[j]); 1871 } 1872 a += m; 1873 } 1874 } else if (type == NORM_INFINITY) { 1875 for (i=0; i<n; i++ ){ 1876 for (j=0; j<m; j++) { 1877 norms[i] = PetscMax(PetscAbsScalar(a[j]),norms[i]); 1878 } 1879 a += m; 1880 } 1881 } else SETERRQ(((PetscObject)A)->comm,PETSC_ERR_ARG_WRONG,"Unknown NormType"); 1882 if (type == NORM_2) { 1883 for (i=0; i<n; i++) norms[i] = PetscSqrtReal(norms[i]); 1884 } 1885 PetscFunctionReturn(0); 1886 } 1887 1888 /* -------------------------------------------------------------------*/ 1889 static struct _MatOps MatOps_Values = {MatSetValues_SeqDense, 1890 MatGetRow_SeqDense, 1891 MatRestoreRow_SeqDense, 1892 MatMult_SeqDense, 1893 /* 4*/ MatMultAdd_SeqDense, 1894 MatMultTranspose_SeqDense, 1895 MatMultTransposeAdd_SeqDense, 1896 0, 1897 0, 1898 0, 1899 /*10*/ 0, 1900 MatLUFactor_SeqDense, 1901 MatCholeskyFactor_SeqDense, 1902 MatSOR_SeqDense, 1903 MatTranspose_SeqDense, 1904 /*15*/ MatGetInfo_SeqDense, 1905 MatEqual_SeqDense, 1906 MatGetDiagonal_SeqDense, 1907 MatDiagonalScale_SeqDense, 1908 MatNorm_SeqDense, 1909 /*20*/ MatAssemblyBegin_SeqDense, 1910 MatAssemblyEnd_SeqDense, 1911 MatSetOption_SeqDense, 1912 MatZeroEntries_SeqDense, 1913 /*24*/ MatZeroRows_SeqDense, 1914 0, 1915 0, 1916 0, 1917 0, 1918 /*29*/ MatSetUp_SeqDense, 1919 0, 1920 0, 1921 MatGetArray_SeqDense, 1922 MatRestoreArray_SeqDense, 1923 /*34*/ MatDuplicate_SeqDense, 1924 0, 1925 0, 1926 0, 1927 0, 1928 /*39*/ MatAXPY_SeqDense, 1929 MatGetSubMatrices_SeqDense, 1930 0, 1931 MatGetValues_SeqDense, 1932 MatCopy_SeqDense, 1933 /*44*/ MatGetRowMax_SeqDense, 1934 MatScale_SeqDense, 1935 0, 1936 0, 1937 0, 1938 /*49*/ 0, 1939 0, 1940 0, 1941 0, 1942 0, 1943 /*54*/ 0, 1944 0, 1945 0, 1946 0, 1947 0, 1948 /*59*/ 0, 1949 MatDestroy_SeqDense, 1950 MatView_SeqDense, 1951 0, 1952 0, 1953 /*64*/ 0, 1954 0, 1955 0, 1956 0, 1957 0, 1958 /*69*/ MatGetRowMaxAbs_SeqDense, 1959 0, 1960 0, 1961 0, 1962 0, 1963 /*74*/ 0, 1964 0, 1965 0, 1966 0, 1967 0, 1968 /*79*/ 0, 1969 0, 1970 0, 1971 0, 1972 /*83*/ MatLoad_SeqDense, 1973 0, 1974 MatIsHermitian_SeqDense, 1975 0, 1976 0, 1977 0, 1978 /*89*/ MatMatMult_SeqDense_SeqDense, 1979 MatMatMultSymbolic_SeqDense_SeqDense, 1980 MatMatMultNumeric_SeqDense_SeqDense, 1981 0, 1982 0, 1983 /*94*/ 0, 1984 0, 1985 0, 1986 0, 1987 0, 1988 /*99*/ 0, 1989 0, 1990 0, 1991 MatConjugate_SeqDense, 1992 0, 1993 /*104*/0, 1994 MatRealPart_SeqDense, 1995 MatImaginaryPart_SeqDense, 1996 0, 1997 0, 1998 /*109*/MatMatSolve_SeqDense, 1999 0, 2000 MatGetRowMin_SeqDense, 2001 MatGetColumnVector_SeqDense, 2002 0, 2003 /*114*/0, 2004 0, 2005 0, 2006 0, 2007 0, 2008 /*119*/0, 2009 0, 2010 0, 2011 0, 2012 0, 2013 /*124*/0, 2014 MatGetColumnNorms_SeqDense, 2015 0, 2016 0, 2017 0, 2018 /*129*/0, 2019 MatTransposeMatMult_SeqDense_SeqDense, 2020 MatTransposeMatMultSymbolic_SeqDense_SeqDense, 2021 MatTransposeMatMultNumeric_SeqDense_SeqDense, 2022 }; 2023 2024 #undef __FUNCT__ 2025 #define __FUNCT__ "MatCreateSeqDense" 2026 /*@C 2027 MatCreateSeqDense - Creates a sequential dense matrix that 2028 is stored in column major order (the usual Fortran 77 manner). Many 2029 of the matrix operations use the BLAS and LAPACK routines. 2030 2031 Collective on MPI_Comm 2032 2033 Input Parameters: 2034 + comm - MPI communicator, set to PETSC_COMM_SELF 2035 . m - number of rows 2036 . n - number of columns 2037 - data - optional location of matrix data in column major order. Set data=PETSC_NULL for PETSc 2038 to control all matrix memory allocation. 2039 2040 Output Parameter: 2041 . A - the matrix 2042 2043 Notes: 2044 The data input variable is intended primarily for Fortran programmers 2045 who wish to allocate their own matrix memory space. Most users should 2046 set data=PETSC_NULL. 2047 2048 Level: intermediate 2049 2050 .keywords: dense, matrix, LAPACK, BLAS 2051 2052 .seealso: MatCreate(), MatCreateDense(), MatSetValues() 2053 @*/ 2054 PetscErrorCode MatCreateSeqDense(MPI_Comm comm,PetscInt m,PetscInt n,PetscScalar *data,Mat *A) 2055 { 2056 PetscErrorCode ierr; 2057 2058 PetscFunctionBegin; 2059 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2060 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2061 ierr = MatSetType(*A,MATSEQDENSE);CHKERRQ(ierr); 2062 ierr = MatSeqDenseSetPreallocation(*A,data);CHKERRQ(ierr); 2063 PetscFunctionReturn(0); 2064 } 2065 2066 #undef __FUNCT__ 2067 #define __FUNCT__ "MatSeqDenseSetPreallocation" 2068 /*@C 2069 MatSeqDenseSetPreallocation - Sets the array used for storing the matrix elements 2070 2071 Collective on MPI_Comm 2072 2073 Input Parameters: 2074 + A - the matrix 2075 - data - the array (or PETSC_NULL) 2076 2077 Notes: 2078 The data input variable is intended primarily for Fortran programmers 2079 who wish to allocate their own matrix memory space. Most users should 2080 need not call this routine. 2081 2082 Level: intermediate 2083 2084 .keywords: dense, matrix, LAPACK, BLAS 2085 2086 .seealso: MatCreate(), MatCreateDense(), MatSetValues(), MatSeqDenseSetLDA() 2087 2088 @*/ 2089 PetscErrorCode MatSeqDenseSetPreallocation(Mat B,PetscScalar data[]) 2090 { 2091 PetscErrorCode ierr; 2092 2093 PetscFunctionBegin; 2094 ierr = PetscTryMethod(B,"MatSeqDenseSetPreallocation_C",(Mat,PetscScalar[]),(B,data));CHKERRQ(ierr); 2095 PetscFunctionReturn(0); 2096 } 2097 2098 EXTERN_C_BEGIN 2099 #undef __FUNCT__ 2100 #define __FUNCT__ "MatSeqDenseSetPreallocation_SeqDense" 2101 PetscErrorCode MatSeqDenseSetPreallocation_SeqDense(Mat B,PetscScalar *data) 2102 { 2103 Mat_SeqDense *b; 2104 PetscErrorCode ierr; 2105 2106 PetscFunctionBegin; 2107 B->preallocated = PETSC_TRUE; 2108 2109 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 2110 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 2111 2112 b = (Mat_SeqDense*)B->data; 2113 b->Mmax = B->rmap->n; 2114 b->Nmax = B->cmap->n; 2115 if(b->lda <= 0 || b->changelda) b->lda = B->rmap->n; 2116 2117 if (!data) { /* petsc-allocated storage */ 2118 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2119 ierr = PetscMalloc(b->lda*b->Nmax*sizeof(PetscScalar),&b->v);CHKERRQ(ierr); 2120 ierr = PetscMemzero(b->v,b->lda*b->Nmax*sizeof(PetscScalar));CHKERRQ(ierr); 2121 ierr = PetscLogObjectMemory(B,b->lda*b->Nmax*sizeof(PetscScalar));CHKERRQ(ierr); 2122 b->user_alloc = PETSC_FALSE; 2123 } else { /* user-allocated storage */ 2124 if (!b->user_alloc) { ierr = PetscFree(b->v);CHKERRQ(ierr); } 2125 b->v = data; 2126 b->user_alloc = PETSC_TRUE; 2127 } 2128 B->assembled = PETSC_TRUE; 2129 PetscFunctionReturn(0); 2130 } 2131 EXTERN_C_END 2132 2133 #undef __FUNCT__ 2134 #define __FUNCT__ "MatSeqDenseSetLDA" 2135 /*@C 2136 MatSeqDenseSetLDA - Declare the leading dimension of the user-provided array 2137 2138 Input parameter: 2139 + A - the matrix 2140 - lda - the leading dimension 2141 2142 Notes: 2143 This routine is to be used in conjunction with MatSeqDenseSetPreallocation(); 2144 it asserts that the preallocation has a leading dimension (the LDA parameter 2145 of Blas and Lapack fame) larger than M, the first dimension of the matrix. 2146 2147 Level: intermediate 2148 2149 .keywords: dense, matrix, LAPACK, BLAS 2150 2151 .seealso: MatCreate(), MatCreateSeqDense(), MatSeqDenseSetPreallocation(), MatSetMaximumSize() 2152 2153 @*/ 2154 PetscErrorCode MatSeqDenseSetLDA(Mat B,PetscInt lda) 2155 { 2156 Mat_SeqDense *b = (Mat_SeqDense*)B->data; 2157 2158 PetscFunctionBegin; 2159 if (lda < B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"LDA %D must be at least matrix dimension %D",lda,B->rmap->n); 2160 b->lda = lda; 2161 b->changelda = PETSC_FALSE; 2162 b->Mmax = PetscMax(b->Mmax,lda); 2163 PetscFunctionReturn(0); 2164 } 2165 2166 /*MC 2167 MATSEQDENSE - MATSEQDENSE = "seqdense" - A matrix type to be used for sequential dense matrices. 2168 2169 Options Database Keys: 2170 . -mat_type seqdense - sets the matrix type to "seqdense" during a call to MatSetFromOptions() 2171 2172 Level: beginner 2173 2174 .seealso: MatCreateSeqDense() 2175 2176 M*/ 2177 2178 EXTERN_C_BEGIN 2179 #undef __FUNCT__ 2180 #define __FUNCT__ "MatCreate_SeqDense" 2181 PetscErrorCode MatCreate_SeqDense(Mat B) 2182 { 2183 Mat_SeqDense *b; 2184 PetscErrorCode ierr; 2185 PetscMPIInt size; 2186 2187 PetscFunctionBegin; 2188 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 2189 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1"); 2190 2191 ierr = PetscNewLog(B,Mat_SeqDense,&b);CHKERRQ(ierr); 2192 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 2193 B->data = (void*)b; 2194 2195 b->pivots = 0; 2196 b->roworiented = PETSC_TRUE; 2197 b->v = 0; 2198 b->changelda = PETSC_FALSE; 2199 2200 2201 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqdense_seqaij_C","MatConvert_SeqDense_SeqAIJ",MatConvert_SeqDense_SeqAIJ);CHKERRQ(ierr); 2202 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_petsc_C", 2203 "MatGetFactor_seqdense_petsc", 2204 MatGetFactor_seqdense_petsc);CHKERRQ(ierr); 2205 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqDenseSetPreallocation_C", 2206 "MatSeqDenseSetPreallocation_SeqDense", 2207 MatSeqDenseSetPreallocation_SeqDense);CHKERRQ(ierr); 2208 2209 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_seqaij_seqdense_C", 2210 "MatMatMult_SeqAIJ_SeqDense", 2211 MatMatMult_SeqAIJ_SeqDense);CHKERRQ(ierr); 2212 2213 2214 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_seqaij_seqdense_C", 2215 "MatMatMultSymbolic_SeqAIJ_SeqDense", 2216 MatMatMultSymbolic_SeqAIJ_SeqDense);CHKERRQ(ierr); 2217 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_seqaij_seqdense_C", 2218 "MatMatMultNumeric_SeqAIJ_SeqDense", 2219 MatMatMultNumeric_SeqAIJ_SeqDense);CHKERRQ(ierr); 2220 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQDENSE);CHKERRQ(ierr); 2221 PetscFunctionReturn(0); 2222 } 2223 EXTERN_C_END 2224