1 #define PETSCMAT_DLL 2 3 4 /* 5 Defines the basic matrix operations for the AIJ (compressed row) 6 matrix storage format. 7 */ 8 9 10 #include "../src/mat/impls/aij/seq/aij.h" /*I "petscmat.h" I*/ 11 #include "petscblaslapack.h" 12 #include "petscbt.h" 13 14 #undef __FUNCT__ 15 #define __FUNCT__ "MatDiagonalSet_SeqAIJ" 16 PetscErrorCode PETSCMAT_DLLEXPORT MatDiagonalSet_SeqAIJ(Mat Y,Vec D,InsertMode is) 17 { 18 PetscErrorCode ierr; 19 Mat_SeqAIJ *aij = (Mat_SeqAIJ*) Y->data; 20 PetscInt i,*diag, m = Y->rmap->n; 21 MatScalar *aa = aij->a; 22 PetscScalar *v; 23 PetscTruth missing; 24 25 PetscFunctionBegin; 26 if (Y->assembled) { 27 ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,PETSC_NULL);CHKERRQ(ierr); 28 if (!missing) { 29 diag = aij->diag; 30 ierr = VecGetArray(D,&v);CHKERRQ(ierr); 31 if (is == INSERT_VALUES) { 32 for (i=0; i<m; i++) { 33 aa[diag[i]] = v[i]; 34 } 35 } else { 36 for (i=0; i<m; i++) { 37 aa[diag[i]] += v[i]; 38 } 39 } 40 ierr = VecRestoreArray(D,&v);CHKERRQ(ierr); 41 PetscFunctionReturn(0); 42 } 43 } 44 ierr = MatDiagonalSet_Default(Y,D,is);CHKERRQ(ierr); 45 PetscFunctionReturn(0); 46 } 47 48 #undef __FUNCT__ 49 #define __FUNCT__ "MatGetRowIJ_SeqAIJ" 50 PetscErrorCode MatGetRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth inodecompressed,PetscInt *m,PetscInt *ia[],PetscInt *ja[],PetscTruth *done) 51 { 52 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 53 PetscErrorCode ierr; 54 PetscInt i,ishift; 55 56 PetscFunctionBegin; 57 *m = A->rmap->n; 58 if (!ia) PetscFunctionReturn(0); 59 ishift = 0; 60 if (symmetric && !A->structurally_symmetric) { 61 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,ishift,oshift,ia,ja);CHKERRQ(ierr); 62 } else if (oshift == 1) { 63 PetscInt nz = a->i[A->rmap->n]; 64 /* malloc space and add 1 to i and j indices */ 65 ierr = PetscMalloc((A->rmap->n+1)*sizeof(PetscInt),ia);CHKERRQ(ierr); 66 for (i=0; i<A->rmap->n+1; i++) (*ia)[i] = a->i[i] + 1; 67 if (ja) { 68 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),ja);CHKERRQ(ierr); 69 for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1; 70 } 71 } else { 72 *ia = a->i; 73 if (ja) *ja = a->j; 74 } 75 PetscFunctionReturn(0); 76 } 77 78 #undef __FUNCT__ 79 #define __FUNCT__ "MatRestoreRowIJ_SeqAIJ" 80 PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth inodecompressed,PetscInt *n,PetscInt *ia[],PetscInt *ja[],PetscTruth *done) 81 { 82 PetscErrorCode ierr; 83 84 PetscFunctionBegin; 85 if (!ia) PetscFunctionReturn(0); 86 if ((symmetric && !A->structurally_symmetric) || oshift == 1) { 87 ierr = PetscFree(*ia);CHKERRQ(ierr); 88 if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} 89 } 90 PetscFunctionReturn(0); 91 } 92 93 #undef __FUNCT__ 94 #define __FUNCT__ "MatGetColumnIJ_SeqAIJ" 95 PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth inodecompressed,PetscInt *nn,PetscInt *ia[],PetscInt *ja[],PetscTruth *done) 96 { 97 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 98 PetscErrorCode ierr; 99 PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; 100 PetscInt nz = a->i[m],row,*jj,mr,col; 101 102 PetscFunctionBegin; 103 *nn = n; 104 if (!ia) PetscFunctionReturn(0); 105 if (symmetric) { 106 ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,0,oshift,ia,ja);CHKERRQ(ierr); 107 } else { 108 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&collengths);CHKERRQ(ierr); 109 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 110 ierr = PetscMalloc((n+1)*sizeof(PetscInt),&cia);CHKERRQ(ierr); 111 ierr = PetscMalloc((nz+1)*sizeof(PetscInt),&cja);CHKERRQ(ierr); 112 jj = a->j; 113 for (i=0; i<nz; i++) { 114 collengths[jj[i]]++; 115 } 116 cia[0] = oshift; 117 for (i=0; i<n; i++) { 118 cia[i+1] = cia[i] + collengths[i]; 119 } 120 ierr = PetscMemzero(collengths,n*sizeof(PetscInt));CHKERRQ(ierr); 121 jj = a->j; 122 for (row=0; row<m; row++) { 123 mr = a->i[row+1] - a->i[row]; 124 for (i=0; i<mr; i++) { 125 col = *jj++; 126 cja[cia[col] + collengths[col]++ - oshift] = row + oshift; 127 } 128 } 129 ierr = PetscFree(collengths);CHKERRQ(ierr); 130 *ia = cia; *ja = cja; 131 } 132 PetscFunctionReturn(0); 133 } 134 135 #undef __FUNCT__ 136 #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ" 137 PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscTruth symmetric,PetscTruth inodecompressed,PetscInt *n,PetscInt *ia[],PetscInt *ja[],PetscTruth *done) 138 { 139 PetscErrorCode ierr; 140 141 PetscFunctionBegin; 142 if (!ia) PetscFunctionReturn(0); 143 144 ierr = PetscFree(*ia);CHKERRQ(ierr); 145 ierr = PetscFree(*ja);CHKERRQ(ierr); 146 147 PetscFunctionReturn(0); 148 } 149 150 #undef __FUNCT__ 151 #define __FUNCT__ "MatSetValuesRow_SeqAIJ" 152 PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) 153 { 154 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 155 PetscInt *ai = a->i; 156 PetscErrorCode ierr; 157 158 PetscFunctionBegin; 159 ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); 160 PetscFunctionReturn(0); 161 } 162 163 #undef __FUNCT__ 164 #define __FUNCT__ "MatSetValues_SeqAIJ" 165 PetscErrorCode MatSetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) 166 { 167 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 168 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 169 PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; 170 PetscErrorCode ierr; 171 PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; 172 MatScalar *ap,value,*aa = a->a; 173 PetscTruth ignorezeroentries = a->ignorezeroentries; 174 PetscTruth roworiented = a->roworiented; 175 176 PetscFunctionBegin; 177 if (v) PetscValidScalarPointer(v,6); 178 for (k=0; k<m; k++) { /* loop over added rows */ 179 row = im[k]; 180 if (row < 0) continue; 181 #if defined(PETSC_USE_DEBUG) 182 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); 183 #endif 184 rp = aj + ai[row]; ap = aa + ai[row]; 185 rmax = imax[row]; nrow = ailen[row]; 186 low = 0; 187 high = nrow; 188 for (l=0; l<n; l++) { /* loop over added columns */ 189 if (in[l] < 0) continue; 190 #if defined(PETSC_USE_DEBUG) 191 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); 192 #endif 193 col = in[l]; 194 if (v) { 195 if (roworiented) { 196 value = v[l + k*n]; 197 } else { 198 value = v[k + l*m]; 199 } 200 } else { 201 value = 0.; 202 } 203 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 204 205 if (col <= lastcol) low = 0; else high = nrow; 206 lastcol = col; 207 while (high-low > 5) { 208 t = (low+high)/2; 209 if (rp[t] > col) high = t; 210 else low = t; 211 } 212 for (i=low; i<high; i++) { 213 if (rp[i] > col) break; 214 if (rp[i] == col) { 215 if (is == ADD_VALUES) ap[i] += value; 216 else ap[i] = value; 217 low = i + 1; 218 goto noinsert; 219 } 220 } 221 if (value == 0.0 && ignorezeroentries) goto noinsert; 222 if (nonew == 1) goto noinsert; 223 if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); 224 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 225 N = nrow++ - 1; a->nz++; high++; 226 /* shift up all the later entries in this row */ 227 for (ii=N; ii>=i; ii--) { 228 rp[ii+1] = rp[ii]; 229 ap[ii+1] = ap[ii]; 230 } 231 rp[i] = col; 232 ap[i] = value; 233 low = i + 1; 234 noinsert:; 235 } 236 ailen[row] = nrow; 237 } 238 A->same_nonzero = PETSC_FALSE; 239 PetscFunctionReturn(0); 240 } 241 242 243 #undef __FUNCT__ 244 #define __FUNCT__ "MatGetValues_SeqAIJ" 245 PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) 246 { 247 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 248 PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; 249 PetscInt *ai = a->i,*ailen = a->ilen; 250 MatScalar *ap,*aa = a->a; 251 252 PetscFunctionBegin; 253 for (k=0; k<m; k++) { /* loop over rows */ 254 row = im[k]; 255 if (row < 0) {v += n; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",row); */ 256 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); 257 rp = aj + ai[row]; ap = aa + ai[row]; 258 nrow = ailen[row]; 259 for (l=0; l<n; l++) { /* loop over columns */ 260 if (in[l] < 0) {v++; continue;} /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",in[l]); */ 261 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); 262 col = in[l] ; 263 high = nrow; low = 0; /* assume unsorted */ 264 while (high-low > 5) { 265 t = (low+high)/2; 266 if (rp[t] > col) high = t; 267 else low = t; 268 } 269 for (i=low; i<high; i++) { 270 if (rp[i] > col) break; 271 if (rp[i] == col) { 272 *v++ = ap[i]; 273 goto finished; 274 } 275 } 276 *v++ = 0.0; 277 finished:; 278 } 279 } 280 PetscFunctionReturn(0); 281 } 282 283 284 #undef __FUNCT__ 285 #define __FUNCT__ "MatView_SeqAIJ_Binary" 286 PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) 287 { 288 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 289 PetscErrorCode ierr; 290 PetscInt i,*col_lens; 291 int fd; 292 293 PetscFunctionBegin; 294 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 295 ierr = PetscMalloc((4+A->rmap->n)*sizeof(PetscInt),&col_lens);CHKERRQ(ierr); 296 col_lens[0] = MAT_FILE_CLASSID; 297 col_lens[1] = A->rmap->n; 298 col_lens[2] = A->cmap->n; 299 col_lens[3] = a->nz; 300 301 /* store lengths of each row and write (including header) to file */ 302 for (i=0; i<A->rmap->n; i++) { 303 col_lens[4+i] = a->i[i+1] - a->i[i]; 304 } 305 ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); 306 ierr = PetscFree(col_lens);CHKERRQ(ierr); 307 308 /* store column indices (zero start index) */ 309 ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); 310 311 /* store nonzero values */ 312 ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); 313 PetscFunctionReturn(0); 314 } 315 316 EXTERN PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); 317 318 #undef __FUNCT__ 319 #define __FUNCT__ "MatView_SeqAIJ_ASCII" 320 PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) 321 { 322 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 323 PetscErrorCode ierr; 324 PetscInt i,j,m = A->rmap->n,shift=0; 325 const char *name; 326 PetscViewerFormat format; 327 328 PetscFunctionBegin; 329 ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); 330 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 331 if (format == PETSC_VIEWER_ASCII_MATLAB) { 332 PetscInt nofinalvalue = 0; 333 if ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-!shift)) { 334 nofinalvalue = 1; 335 } 336 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 337 ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); 338 ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); 339 ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); 340 ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); 341 342 for (i=0; i<m; i++) { 343 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 344 #if defined(PETSC_USE_COMPLEX) 345 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); 346 #else 347 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+!shift,a->a[j]);CHKERRQ(ierr); 348 #endif 349 } 350 } 351 if (nofinalvalue) { 352 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); 353 } 354 ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); 355 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 356 } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { 357 PetscFunctionReturn(0); 358 } else if (format == PETSC_VIEWER_ASCII_COMMON) { 359 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 360 for (i=0; i<m; i++) { 361 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 362 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 363 #if defined(PETSC_USE_COMPLEX) 364 if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { 365 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 366 } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { 367 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G - %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 368 } else if (PetscRealPart(a->a[j]) != 0.0) { 369 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 370 } 371 #else 372 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,a->a[j]);CHKERRQ(ierr);} 373 #endif 374 } 375 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 376 } 377 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 378 } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { 379 PetscInt nzd=0,fshift=1,*sptr; 380 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 381 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&sptr);CHKERRQ(ierr); 382 for (i=0; i<m; i++) { 383 sptr[i] = nzd+1; 384 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 385 if (a->j[j] >= i) { 386 #if defined(PETSC_USE_COMPLEX) 387 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; 388 #else 389 if (a->a[j] != 0.0) nzd++; 390 #endif 391 } 392 } 393 } 394 sptr[m] = nzd+1; 395 ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); 396 for (i=0; i<m+1; i+=6) { 397 if (i+4<m) {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);} 398 else if (i+3<m) {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);} 399 else if (i+2<m) {ierr = PetscViewerASCIIPrintf(viewer," %D %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2],sptr[i+3]);CHKERRQ(ierr);} 400 else if (i+1<m) {ierr = PetscViewerASCIIPrintf(viewer," %D %D %D\n",sptr[i],sptr[i+1],sptr[i+2]);CHKERRQ(ierr);} 401 else if (i<m) {ierr = PetscViewerASCIIPrintf(viewer," %D %D\n",sptr[i],sptr[i+1]);CHKERRQ(ierr);} 402 else {ierr = PetscViewerASCIIPrintf(viewer," %D\n",sptr[i]);CHKERRQ(ierr);} 403 } 404 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 405 ierr = PetscFree(sptr);CHKERRQ(ierr); 406 for (i=0; i<m; i++) { 407 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 408 if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} 409 } 410 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 411 } 412 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 413 for (i=0; i<m; i++) { 414 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 415 if (a->j[j] >= i) { 416 #if defined(PETSC_USE_COMPLEX) 417 if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { 418 ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 419 } 420 #else 421 if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",a->a[j]);CHKERRQ(ierr);} 422 #endif 423 } 424 } 425 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 426 } 427 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 428 } else if (format == PETSC_VIEWER_ASCII_DENSE) { 429 PetscInt cnt = 0,jcnt; 430 PetscScalar value; 431 432 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 433 for (i=0; i<m; i++) { 434 jcnt = 0; 435 for (j=0; j<A->cmap->n; j++) { 436 if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { 437 value = a->a[cnt++]; 438 jcnt++; 439 } else { 440 value = 0.0; 441 } 442 #if defined(PETSC_USE_COMPLEX) 443 ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",PetscRealPart(value),PetscImaginaryPart(value));CHKERRQ(ierr); 444 #else 445 ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",value);CHKERRQ(ierr); 446 #endif 447 } 448 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 449 } 450 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 451 } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { 452 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 453 #if defined(PETSC_USE_COMPLEX) 454 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix complex general\n");CHKERRQ(ierr); 455 #else 456 ierr = PetscViewerASCIIPrintf(viewer,"%%matrix real general\n");CHKERRQ(ierr); 457 #endif 458 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); 459 for (i=0; i<m; i++) { 460 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 461 #if defined(PETSC_USE_COMPLEX) 462 if (PetscImaginaryPart(a->a[j]) > 0.0) { 463 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %G %G\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 464 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 465 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %G -%G\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 466 } else { 467 ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %G\n", i+shift,a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 468 } 469 #else 470 ierr = PetscViewerASCIIPrintf(viewer,"%D %D %G\n", i+shift, a->j[j]+shift, a->a[j]);CHKERRQ(ierr); 471 #endif 472 } 473 } 474 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 475 } else { 476 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_NO);CHKERRQ(ierr); 477 if (A->factortype){ 478 for (i=0; i<m; i++) { 479 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 480 /* L part */ 481 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 482 #if defined(PETSC_USE_COMPLEX) 483 if (PetscImaginaryPart(a->a[j]) > 0.0) { 484 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 485 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 486 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G - %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 487 } else { 488 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 489 } 490 #else 491 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,a->a[j]);CHKERRQ(ierr); 492 #endif 493 } 494 /* diagonal */ 495 j = a->diag[i]; 496 #if defined(PETSC_USE_COMPLEX) 497 if (PetscImaginaryPart(a->a[j]) > 0.0) { 498 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 499 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 500 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G - %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 501 } else { 502 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 503 } 504 #else 505 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,a->a[j]);CHKERRQ(ierr); 506 #endif 507 508 /* U part */ 509 for (j=a->diag[i+1]+1+shift; j<a->diag[i]+shift; j++) { 510 #if defined(PETSC_USE_COMPLEX) 511 if (PetscImaginaryPart(a->a[j]) > 0.0) { 512 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 513 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 514 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G - %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 515 } else { 516 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 517 } 518 #else 519 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,a->a[j]);CHKERRQ(ierr); 520 #endif 521 } 522 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 523 } 524 } else { 525 for (i=0; i<m; i++) { 526 ierr = PetscViewerASCIIPrintf(viewer,"row %D:",i);CHKERRQ(ierr); 527 for (j=a->i[i]+shift; j<a->i[i+1]+shift; j++) { 528 #if defined(PETSC_USE_COMPLEX) 529 if (PetscImaginaryPart(a->a[j]) > 0.0) { 530 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G + %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 531 } else if (PetscImaginaryPart(a->a[j]) < 0.0) { 532 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G - %G i)",a->j[j]+shift,PetscRealPart(a->a[j]),-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); 533 } else { 534 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,PetscRealPart(a->a[j]));CHKERRQ(ierr); 535 } 536 #else 537 ierr = PetscViewerASCIIPrintf(viewer," (%D, %G) ",a->j[j]+shift,a->a[j]);CHKERRQ(ierr); 538 #endif 539 } 540 ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); 541 } 542 } 543 ierr = PetscViewerASCIIUseTabs(viewer,PETSC_YES);CHKERRQ(ierr); 544 } 545 ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); 546 PetscFunctionReturn(0); 547 } 548 549 #undef __FUNCT__ 550 #define __FUNCT__ "MatView_SeqAIJ_Draw_Zoom" 551 PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) 552 { 553 Mat A = (Mat) Aa; 554 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 555 PetscErrorCode ierr; 556 PetscInt i,j,m = A->rmap->n,color; 557 PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r,maxv = 0.0; 558 PetscViewer viewer; 559 PetscViewerFormat format; 560 561 PetscFunctionBegin; 562 ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); 563 ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); 564 565 ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); 566 /* loop over matrix elements drawing boxes */ 567 568 if (format != PETSC_VIEWER_DRAW_CONTOUR) { 569 /* Blue for negative, Cyan for zero and Red for positive */ 570 color = PETSC_DRAW_BLUE; 571 for (i=0; i<m; i++) { 572 y_l = m - i - 1.0; y_r = y_l + 1.0; 573 for (j=a->i[i]; j<a->i[i+1]; j++) { 574 x_l = a->j[j] ; x_r = x_l + 1.0; 575 #if defined(PETSC_USE_COMPLEX) 576 if (PetscRealPart(a->a[j]) >= 0.) continue; 577 #else 578 if (a->a[j] >= 0.) continue; 579 #endif 580 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 581 } 582 } 583 color = PETSC_DRAW_CYAN; 584 for (i=0; i<m; i++) { 585 y_l = m - i - 1.0; y_r = y_l + 1.0; 586 for (j=a->i[i]; j<a->i[i+1]; j++) { 587 x_l = a->j[j]; x_r = x_l + 1.0; 588 if (a->a[j] != 0.) continue; 589 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 590 } 591 } 592 color = PETSC_DRAW_RED; 593 for (i=0; i<m; i++) { 594 y_l = m - i - 1.0; y_r = y_l + 1.0; 595 for (j=a->i[i]; j<a->i[i+1]; j++) { 596 x_l = a->j[j]; x_r = x_l + 1.0; 597 #if defined(PETSC_USE_COMPLEX) 598 if (PetscRealPart(a->a[j]) <= 0.) continue; 599 #else 600 if (a->a[j] <= 0.) continue; 601 #endif 602 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 603 } 604 } 605 } else { 606 /* use contour shading to indicate magnitude of values */ 607 /* first determine max of all nonzero values */ 608 PetscInt nz = a->nz,count; 609 PetscDraw popup; 610 PetscReal scale; 611 612 for (i=0; i<nz; i++) { 613 if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); 614 } 615 scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; 616 ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); 617 if (popup) {ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr);} 618 count = 0; 619 for (i=0; i<m; i++) { 620 y_l = m - i - 1.0; y_r = y_l + 1.0; 621 for (j=a->i[i]; j<a->i[i+1]; j++) { 622 x_l = a->j[j]; x_r = x_l + 1.0; 623 color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(a->a[count])); 624 ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); 625 count++; 626 } 627 } 628 } 629 PetscFunctionReturn(0); 630 } 631 632 #undef __FUNCT__ 633 #define __FUNCT__ "MatView_SeqAIJ_Draw" 634 PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) 635 { 636 PetscErrorCode ierr; 637 PetscDraw draw; 638 PetscReal xr,yr,xl,yl,h,w; 639 PetscTruth isnull; 640 641 PetscFunctionBegin; 642 ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); 643 ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); 644 if (isnull) PetscFunctionReturn(0); 645 646 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); 647 xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; 648 xr += w; yr += h; xl = -w; yl = -h; 649 ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); 650 ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); 651 ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",PETSC_NULL);CHKERRQ(ierr); 652 PetscFunctionReturn(0); 653 } 654 655 #undef __FUNCT__ 656 #define __FUNCT__ "MatView_SeqAIJ" 657 PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) 658 { 659 PetscErrorCode ierr; 660 PetscTruth iascii,isbinary,isdraw; 661 662 PetscFunctionBegin; 663 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); 664 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); 665 ierr = PetscTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); 666 if (iascii) { 667 ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); 668 } else if (isbinary) { 669 ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); 670 } else if (isdraw) { 671 ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); 672 } else { 673 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"Viewer type %s not supported by SeqAIJ matrices",((PetscObject)viewer)->type_name); 674 } 675 ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); 676 PetscFunctionReturn(0); 677 } 678 679 #undef __FUNCT__ 680 #define __FUNCT__ "MatAssemblyEnd_SeqAIJ" 681 PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) 682 { 683 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 684 PetscErrorCode ierr; 685 PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; 686 PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; 687 MatScalar *aa = a->a,*ap; 688 PetscReal ratio=0.6; 689 690 PetscFunctionBegin; 691 if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); 692 693 if (m) rmax = ailen[0]; /* determine row with most nonzeros */ 694 for (i=1; i<m; i++) { 695 /* move each row back by the amount of empty slots (fshift) before it*/ 696 fshift += imax[i-1] - ailen[i-1]; 697 rmax = PetscMax(rmax,ailen[i]); 698 if (fshift) { 699 ip = aj + ai[i] ; 700 ap = aa + ai[i] ; 701 N = ailen[i]; 702 for (j=0; j<N; j++) { 703 ip[j-fshift] = ip[j]; 704 ap[j-fshift] = ap[j]; 705 } 706 } 707 ai[i] = ai[i-1] + ailen[i-1]; 708 } 709 if (m) { 710 fshift += imax[m-1] - ailen[m-1]; 711 ai[m] = ai[m-1] + ailen[m-1]; 712 } 713 /* reset ilen and imax for each row */ 714 for (i=0; i<m; i++) { 715 ailen[i] = imax[i] = ai[i+1] - ai[i]; 716 } 717 a->nz = ai[m]; 718 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); 719 720 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 721 ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); 722 ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); 723 ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); 724 A->info.mallocs += a->reallocs; 725 a->reallocs = 0; 726 A->info.nz_unneeded = (double)fshift; 727 a->rmax = rmax; 728 729 /* check for zero rows. If found a large number of zero rows, use CompressedRow functions */ 730 ierr = Mat_CheckCompressedRow(A,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); 731 A->same_nonzero = PETSC_TRUE; 732 733 ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); 734 735 a->idiagvalid = PETSC_FALSE; 736 PetscFunctionReturn(0); 737 } 738 739 #undef __FUNCT__ 740 #define __FUNCT__ "MatRealPart_SeqAIJ" 741 PetscErrorCode MatRealPart_SeqAIJ(Mat A) 742 { 743 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 744 PetscInt i,nz = a->nz; 745 MatScalar *aa = a->a; 746 747 PetscFunctionBegin; 748 for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]); 749 PetscFunctionReturn(0); 750 } 751 752 #undef __FUNCT__ 753 #define __FUNCT__ "MatImaginaryPart_SeqAIJ" 754 PetscErrorCode MatImaginaryPart_SeqAIJ(Mat A) 755 { 756 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 757 PetscInt i,nz = a->nz; 758 MatScalar *aa = a->a; 759 760 PetscFunctionBegin; 761 for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]); 762 PetscFunctionReturn(0); 763 } 764 765 #undef __FUNCT__ 766 #define __FUNCT__ "MatZeroEntries_SeqAIJ" 767 PetscErrorCode MatZeroEntries_SeqAIJ(Mat A) 768 { 769 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 770 PetscErrorCode ierr; 771 772 PetscFunctionBegin; 773 ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 774 PetscFunctionReturn(0); 775 } 776 777 #undef __FUNCT__ 778 #define __FUNCT__ "MatDestroy_SeqAIJ" 779 PetscErrorCode MatDestroy_SeqAIJ(Mat A) 780 { 781 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 782 PetscErrorCode ierr; 783 784 PetscFunctionBegin; 785 #if defined(PETSC_USE_LOG) 786 PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); 787 #endif 788 ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); 789 if (a->row) { 790 ierr = ISDestroy(a->row);CHKERRQ(ierr); 791 } 792 if (a->col) { 793 ierr = ISDestroy(a->col);CHKERRQ(ierr); 794 } 795 ierr = PetscFree(a->diag);CHKERRQ(ierr); 796 ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); 797 ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); 798 ierr = PetscFree(a->solve_work);CHKERRQ(ierr); 799 if (a->icol) {ierr = ISDestroy(a->icol);CHKERRQ(ierr);} 800 ierr = PetscFree(a->saved_values);CHKERRQ(ierr); 801 if (a->coloring) {ierr = ISColoringDestroy(a->coloring);CHKERRQ(ierr);} 802 ierr = PetscFree(a->xtoy);CHKERRQ(ierr); 803 if (a->XtoY) {ierr = MatDestroy(a->XtoY);CHKERRQ(ierr);} 804 if (a->compressedrow.checked && a->compressedrow.use){ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);} 805 806 ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); 807 808 ierr = PetscFree(a);CHKERRQ(ierr); 809 810 ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); 811 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatSeqAIJSetColumnIndices_C","",PETSC_NULL);CHKERRQ(ierr); 812 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatStoreValues_C","",PETSC_NULL);CHKERRQ(ierr); 813 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatRetrieveValues_C","",PETSC_NULL);CHKERRQ(ierr); 814 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatConvert_seqaij_seqsbaij_C","",PETSC_NULL);CHKERRQ(ierr); 815 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatConvert_seqaij_seqbaij_C","",PETSC_NULL);CHKERRQ(ierr); 816 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatConvert_seqaij_seqaijperm_C","",PETSC_NULL);CHKERRQ(ierr); 817 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatIsTranspose_C","",PETSC_NULL);CHKERRQ(ierr); 818 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatSeqAIJSetPreallocation_C","",PETSC_NULL);CHKERRQ(ierr); 819 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C","",PETSC_NULL);CHKERRQ(ierr); 820 ierr = PetscObjectComposeFunctionDynamic((PetscObject)A,"MatReorderForNonzeroDiagonal_C","",PETSC_NULL);CHKERRQ(ierr); 821 PetscFunctionReturn(0); 822 } 823 824 #undef __FUNCT__ 825 #define __FUNCT__ "MatSetOption_SeqAIJ" 826 PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscTruth flg) 827 { 828 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 829 PetscErrorCode ierr; 830 831 PetscFunctionBegin; 832 switch (op) { 833 case MAT_ROW_ORIENTED: 834 a->roworiented = flg; 835 break; 836 case MAT_KEEP_NONZERO_PATTERN: 837 a->keepnonzeropattern = flg; 838 break; 839 case MAT_NEW_NONZERO_LOCATIONS: 840 a->nonew = (flg ? 0 : 1); 841 break; 842 case MAT_NEW_NONZERO_LOCATION_ERR: 843 a->nonew = (flg ? -1 : 0); 844 break; 845 case MAT_NEW_NONZERO_ALLOCATION_ERR: 846 a->nonew = (flg ? -2 : 0); 847 break; 848 case MAT_UNUSED_NONZERO_LOCATION_ERR: 849 a->nounused = (flg ? -1 : 0); 850 break; 851 case MAT_IGNORE_ZERO_ENTRIES: 852 a->ignorezeroentries = flg; 853 break; 854 case MAT_USE_COMPRESSEDROW: 855 a->compressedrow.use = flg; 856 break; 857 case MAT_SPD: 858 A->spd_set = PETSC_TRUE; 859 A->spd = flg; 860 if (flg) { 861 A->symmetric = PETSC_TRUE; 862 A->structurally_symmetric = PETSC_TRUE; 863 A->symmetric_set = PETSC_TRUE; 864 A->structurally_symmetric_set = PETSC_TRUE; 865 } 866 break; 867 case MAT_SYMMETRIC: 868 case MAT_STRUCTURALLY_SYMMETRIC: 869 case MAT_HERMITIAN: 870 case MAT_SYMMETRY_ETERNAL: 871 case MAT_NEW_DIAGONALS: 872 case MAT_IGNORE_OFF_PROC_ENTRIES: 873 case MAT_USE_HASH_TABLE: 874 ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); 875 break; 876 case MAT_USE_INODES: 877 /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ 878 break; 879 default: 880 SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); 881 } 882 ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); 883 PetscFunctionReturn(0); 884 } 885 886 #undef __FUNCT__ 887 #define __FUNCT__ "MatGetDiagonal_SeqAIJ" 888 PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) 889 { 890 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 891 PetscErrorCode ierr; 892 PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; 893 PetscScalar *aa=a->a,*x,zero=0.0; 894 895 PetscFunctionBegin; 896 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 897 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 898 899 if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU){ 900 PetscInt *diag=a->diag; 901 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 902 for (i=0; i<n; i++) x[i] = aa[diag[i]]; 903 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 904 PetscFunctionReturn(0); 905 } 906 907 ierr = VecSet(v,zero);CHKERRQ(ierr); 908 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 909 for (i=0; i<n; i++) { 910 nz = ai[i+1] - ai[i]; 911 if (!nz) x[i] = 0.0; 912 for (j=ai[i]; j<ai[i+1]; j++){ 913 if (aj[j] == i) { 914 x[i] = aa[j]; 915 break; 916 } 917 } 918 } 919 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 920 PetscFunctionReturn(0); 921 } 922 923 #include "../src/mat/impls/aij/seq/ftn-kernels/fmult.h" 924 #undef __FUNCT__ 925 #define __FUNCT__ "MatMultTransposeAdd_SeqAIJ" 926 PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) 927 { 928 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 929 PetscScalar *x,*y; 930 PetscErrorCode ierr; 931 PetscInt m = A->rmap->n; 932 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 933 MatScalar *v; 934 PetscScalar alpha; 935 PetscInt n,i,j,*idx,*ii,*ridx=PETSC_NULL; 936 Mat_CompressedRow cprow = a->compressedrow; 937 PetscTruth usecprow = cprow.use; 938 #endif 939 940 PetscFunctionBegin; 941 if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} 942 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 943 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 944 945 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) 946 fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); 947 #else 948 if (usecprow){ 949 m = cprow.nrows; 950 ii = cprow.i; 951 ridx = cprow.rindex; 952 } else { 953 ii = a->i; 954 } 955 for (i=0; i<m; i++) { 956 idx = a->j + ii[i] ; 957 v = a->a + ii[i] ; 958 n = ii[i+1] - ii[i]; 959 if (usecprow){ 960 alpha = x[ridx[i]]; 961 } else { 962 alpha = x[i]; 963 } 964 for (j=0; j<n; j++) y[idx[j]] += alpha*v[j]; 965 } 966 #endif 967 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 968 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 969 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 970 PetscFunctionReturn(0); 971 } 972 973 #undef __FUNCT__ 974 #define __FUNCT__ "MatMultTranspose_SeqAIJ" 975 PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) 976 { 977 PetscErrorCode ierr; 978 979 PetscFunctionBegin; 980 ierr = VecSet(yy,0.0);CHKERRQ(ierr); 981 ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); 982 PetscFunctionReturn(0); 983 } 984 985 #include "../src/mat/impls/aij/seq/ftn-kernels/fmult.h" 986 #undef __FUNCT__ 987 #define __FUNCT__ "MatMult_SeqAIJ" 988 PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) 989 { 990 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 991 PetscScalar *y; 992 const PetscScalar *x; 993 const MatScalar *aa; 994 PetscErrorCode ierr; 995 PetscInt m=A->rmap->n; 996 const PetscInt *aj,*ii,*ridx=PETSC_NULL; 997 PetscInt n,i,nonzerorow=0; 998 PetscScalar sum; 999 PetscTruth usecprow=a->compressedrow.use; 1000 1001 #if defined(PETSC_HAVE_PRAGMA_DISJOINT) 1002 #pragma disjoint(*x,*y,*aa) 1003 #endif 1004 1005 PetscFunctionBegin; 1006 ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); 1007 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1008 aj = a->j; 1009 aa = a->a; 1010 ii = a->i; 1011 if (usecprow){ /* use compressed row format */ 1012 m = a->compressedrow.nrows; 1013 ii = a->compressedrow.i; 1014 ridx = a->compressedrow.rindex; 1015 for (i=0; i<m; i++){ 1016 n = ii[i+1] - ii[i]; 1017 aj = a->j + ii[i]; 1018 aa = a->a + ii[i]; 1019 sum = 0.0; 1020 nonzerorow += (n>0); 1021 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1022 /* for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; */ 1023 y[*ridx++] = sum; 1024 } 1025 } else { /* do not use compressed row format */ 1026 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTAIJ) 1027 fortranmultaij_(&m,x,ii,aj,aa,y); 1028 #else 1029 for (i=0; i<m; i++) { 1030 n = ii[i+1] - ii[i]; 1031 aj = a->j + ii[i]; 1032 aa = a->a + ii[i]; 1033 sum = 0.0; 1034 nonzerorow += (n>0); 1035 PetscSparseDensePlusDot(sum,x,aa,aj,n); 1036 y[i] = sum; 1037 } 1038 #endif 1039 } 1040 ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); 1041 ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); 1042 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1043 PetscFunctionReturn(0); 1044 } 1045 1046 #include "../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h" 1047 #undef __FUNCT__ 1048 #define __FUNCT__ "MatMultAdd_SeqAIJ" 1049 PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) 1050 { 1051 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1052 PetscScalar *x,*y,*z; 1053 const MatScalar *aa; 1054 PetscErrorCode ierr; 1055 PetscInt m = A->rmap->n,*aj,*ii; 1056 #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1057 PetscInt n,i,jrow,j,*ridx=PETSC_NULL; 1058 PetscScalar sum; 1059 PetscTruth usecprow=a->compressedrow.use; 1060 #endif 1061 1062 PetscFunctionBegin; 1063 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1064 ierr = VecGetArray(yy,&y);CHKERRQ(ierr); 1065 if (zz != yy) { 1066 ierr = VecGetArray(zz,&z);CHKERRQ(ierr); 1067 } else { 1068 z = y; 1069 } 1070 1071 aj = a->j; 1072 aa = a->a; 1073 ii = a->i; 1074 #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) 1075 fortranmultaddaij_(&m,x,ii,aj,aa,y,z); 1076 #else 1077 if (usecprow){ /* use compressed row format */ 1078 if (zz != yy){ 1079 ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); 1080 } 1081 m = a->compressedrow.nrows; 1082 ii = a->compressedrow.i; 1083 ridx = a->compressedrow.rindex; 1084 for (i=0; i<m; i++){ 1085 n = ii[i+1] - ii[i]; 1086 aj = a->j + ii[i]; 1087 aa = a->a + ii[i]; 1088 sum = y[*ridx]; 1089 for (j=0; j<n; j++) sum += (*aa++)*x[*aj++]; 1090 z[*ridx++] = sum; 1091 } 1092 } else { /* do not use compressed row format */ 1093 for (i=0; i<m; i++) { 1094 jrow = ii[i]; 1095 n = ii[i+1] - jrow; 1096 sum = y[i]; 1097 for (j=0; j<n; j++) { 1098 sum += aa[jrow]*x[aj[jrow]]; jrow++; 1099 } 1100 z[i] = sum; 1101 } 1102 } 1103 #endif 1104 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1105 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1106 ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); 1107 if (zz != yy) { 1108 ierr = VecRestoreArray(zz,&z);CHKERRQ(ierr); 1109 } 1110 #if defined(PETSC_HAVE_CUDA) 1111 /* 1112 ierr = VecView(xx,0);CHKERRQ(ierr); 1113 ierr = VecView(zz,0);CHKERRQ(ierr); 1114 ierr = MatView(A,0);CHKERRQ(ierr); 1115 */ 1116 #endif 1117 PetscFunctionReturn(0); 1118 } 1119 1120 /* 1121 Adds diagonal pointers to sparse matrix structure. 1122 */ 1123 #undef __FUNCT__ 1124 #define __FUNCT__ "MatMarkDiagonal_SeqAIJ" 1125 PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) 1126 { 1127 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1128 PetscErrorCode ierr; 1129 PetscInt i,j,m = A->rmap->n; 1130 1131 PetscFunctionBegin; 1132 if (!a->diag) { 1133 ierr = PetscMalloc(m*sizeof(PetscInt),&a->diag);CHKERRQ(ierr); 1134 ierr = PetscLogObjectMemory(A, m*sizeof(PetscInt));CHKERRQ(ierr); 1135 } 1136 for (i=0; i<A->rmap->n; i++) { 1137 a->diag[i] = a->i[i+1]; 1138 for (j=a->i[i]; j<a->i[i+1]; j++) { 1139 if (a->j[j] == i) { 1140 a->diag[i] = j; 1141 break; 1142 } 1143 } 1144 } 1145 PetscFunctionReturn(0); 1146 } 1147 1148 /* 1149 Checks for missing diagonals 1150 */ 1151 #undef __FUNCT__ 1152 #define __FUNCT__ "MatMissingDiagonal_SeqAIJ" 1153 PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscTruth *missing,PetscInt *d) 1154 { 1155 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1156 PetscInt *diag,*jj = a->j,i; 1157 1158 PetscFunctionBegin; 1159 *missing = PETSC_FALSE; 1160 if (A->rmap->n > 0 && !jj) { 1161 *missing = PETSC_TRUE; 1162 if (d) *d = 0; 1163 PetscInfo(A,"Matrix has no entries therefor is missing diagonal"); 1164 } else { 1165 diag = a->diag; 1166 for (i=0; i<A->rmap->n; i++) { 1167 if (jj[diag[i]] != i) { 1168 *missing = PETSC_TRUE; 1169 if (d) *d = i; 1170 PetscInfo1(A,"Matrix is missing diagonal number %D",i); 1171 } 1172 } 1173 } 1174 PetscFunctionReturn(0); 1175 } 1176 1177 EXTERN_C_BEGIN 1178 #undef __FUNCT__ 1179 #define __FUNCT__ "MatInvertDiagonal_SeqAIJ" 1180 PetscErrorCode PETSCMAT_DLLEXPORT MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) 1181 { 1182 Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; 1183 PetscErrorCode ierr; 1184 PetscInt i,*diag,m = A->rmap->n; 1185 MatScalar *v = a->a; 1186 PetscScalar *idiag,*mdiag; 1187 1188 PetscFunctionBegin; 1189 if (a->idiagvalid) PetscFunctionReturn(0); 1190 ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); 1191 diag = a->diag; 1192 if (!a->idiag) { 1193 ierr = PetscMalloc3(m,PetscScalar,&a->idiag,m,PetscScalar,&a->mdiag,m,PetscScalar,&a->ssor_work);CHKERRQ(ierr); 1194 ierr = PetscLogObjectMemory(A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); 1195 v = a->a; 1196 } 1197 mdiag = a->mdiag; 1198 idiag = a->idiag; 1199 1200 if (omega == 1.0 && !PetscAbsScalar(fshift)) { 1201 for (i=0; i<m; i++) { 1202 mdiag[i] = v[diag[i]]; 1203 if (!PetscAbsScalar(mdiag[i])) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Zero diagonal on row %D",i); 1204 idiag[i] = 1.0/v[diag[i]]; 1205 } 1206 ierr = PetscLogFlops(m);CHKERRQ(ierr); 1207 } else { 1208 for (i=0; i<m; i++) { 1209 mdiag[i] = v[diag[i]]; 1210 idiag[i] = omega/(fshift + v[diag[i]]); 1211 } 1212 ierr = PetscLogFlops(2.0*m);CHKERRQ(ierr); 1213 } 1214 a->idiagvalid = PETSC_TRUE; 1215 PetscFunctionReturn(0); 1216 } 1217 EXTERN_C_END 1218 1219 #include "../src/mat/impls/aij/seq/ftn-kernels/frelax.h" 1220 #undef __FUNCT__ 1221 #define __FUNCT__ "MatSOR_SeqAIJ" 1222 PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) 1223 { 1224 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1225 PetscScalar *x,d,sum,*t,scale; 1226 const MatScalar *v = a->a,*idiag=0,*mdiag; 1227 const PetscScalar *b, *bs,*xb, *ts; 1228 PetscErrorCode ierr; 1229 PetscInt n = A->cmap->n,m = A->rmap->n,i; 1230 const PetscInt *idx,*diag; 1231 1232 PetscFunctionBegin; 1233 its = its*lits; 1234 1235 if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ 1236 if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} 1237 a->fshift = fshift; 1238 a->omega = omega; 1239 1240 diag = a->diag; 1241 t = a->ssor_work; 1242 idiag = a->idiag; 1243 mdiag = a->mdiag; 1244 1245 ierr = VecGetArray(xx,&x);CHKERRQ(ierr); 1246 ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); 1247 CHKMEMQ; 1248 /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ 1249 if (flag == SOR_APPLY_UPPER) { 1250 /* apply (U + D/omega) to the vector */ 1251 bs = b; 1252 for (i=0; i<m; i++) { 1253 d = fshift + mdiag[i]; 1254 n = a->i[i+1] - diag[i] - 1; 1255 idx = a->j + diag[i] + 1; 1256 v = a->a + diag[i] + 1; 1257 sum = b[i]*d/omega; 1258 PetscSparseDensePlusDot(sum,bs,v,idx,n); 1259 x[i] = sum; 1260 } 1261 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1262 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1263 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1264 PetscFunctionReturn(0); 1265 } 1266 1267 if (flag == SOR_APPLY_LOWER) { 1268 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); 1269 } else if (flag & SOR_EISENSTAT) { 1270 /* Let A = L + U + D; where L is lower trianglar, 1271 U is upper triangular, E = D/omega; This routine applies 1272 1273 (L + E)^{-1} A (U + E)^{-1} 1274 1275 to a vector efficiently using Eisenstat's trick. 1276 */ 1277 scale = (2.0/omega) - 1.0; 1278 1279 /* x = (E + U)^{-1} b */ 1280 for (i=m-1; i>=0; i--) { 1281 n = a->i[i+1] - diag[i] - 1; 1282 idx = a->j + diag[i] + 1; 1283 v = a->a + diag[i] + 1; 1284 sum = b[i]; 1285 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1286 x[i] = sum*idiag[i]; 1287 } 1288 1289 /* t = b - (2*E - D)x */ 1290 v = a->a; 1291 for (i=0; i<m; i++) { t[i] = b[i] - scale*(v[*diag++])*x[i]; } 1292 1293 /* t = (E + L)^{-1}t */ 1294 ts = t; 1295 diag = a->diag; 1296 for (i=0; i<m; i++) { 1297 n = diag[i] - a->i[i]; 1298 idx = a->j + a->i[i]; 1299 v = a->a + a->i[i]; 1300 sum = t[i]; 1301 PetscSparseDenseMinusDot(sum,ts,v,idx,n); 1302 t[i] = sum*idiag[i]; 1303 /* x = x + t */ 1304 x[i] += t[i]; 1305 } 1306 1307 ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); 1308 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1309 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1310 PetscFunctionReturn(0); 1311 } 1312 if (flag & SOR_ZERO_INITIAL_GUESS) { 1313 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 1314 for (i=0; i<m; i++) { 1315 n = diag[i] - a->i[i]; 1316 idx = a->j + a->i[i]; 1317 v = a->a + a->i[i]; 1318 sum = b[i]; 1319 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1320 t[i] = sum; 1321 x[i] = sum*idiag[i]; 1322 } 1323 xb = t; 1324 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1325 } else xb = b; 1326 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 1327 for (i=m-1; i>=0; i--) { 1328 n = a->i[i+1] - diag[i] - 1; 1329 idx = a->j + diag[i] + 1; 1330 v = a->a + diag[i] + 1; 1331 sum = xb[i]; 1332 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1333 if (xb == b) { 1334 x[i] = sum*idiag[i]; 1335 } else { 1336 x[i] = (1-omega)*x[i] + sum*idiag[i]; 1337 } 1338 } 1339 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1340 } 1341 its--; 1342 } 1343 while (its--) { 1344 if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP){ 1345 for (i=0; i<m; i++) { 1346 n = a->i[i+1] - a->i[i]; 1347 idx = a->j + a->i[i]; 1348 v = a->a + a->i[i]; 1349 sum = b[i]; 1350 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1351 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1352 } 1353 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1354 } 1355 if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP){ 1356 for (i=m-1; i>=0; i--) { 1357 n = a->i[i+1] - a->i[i]; 1358 idx = a->j + a->i[i]; 1359 v = a->a + a->i[i]; 1360 sum = b[i]; 1361 PetscSparseDenseMinusDot(sum,x,v,idx,n); 1362 x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; 1363 } 1364 ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); 1365 } 1366 } 1367 ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); 1368 ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); 1369 CHKMEMQ; PetscFunctionReturn(0); 1370 } 1371 1372 1373 #undef __FUNCT__ 1374 #define __FUNCT__ "MatGetInfo_SeqAIJ" 1375 PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) 1376 { 1377 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1378 1379 PetscFunctionBegin; 1380 info->block_size = 1.0; 1381 info->nz_allocated = (double)a->maxnz; 1382 info->nz_used = (double)a->nz; 1383 info->nz_unneeded = (double)(a->maxnz - a->nz); 1384 info->assemblies = (double)A->num_ass; 1385 info->mallocs = (double)A->info.mallocs; 1386 info->memory = ((PetscObject)A)->mem; 1387 if (A->factortype) { 1388 info->fill_ratio_given = A->info.fill_ratio_given; 1389 info->fill_ratio_needed = A->info.fill_ratio_needed; 1390 info->factor_mallocs = A->info.factor_mallocs; 1391 } else { 1392 info->fill_ratio_given = 0; 1393 info->fill_ratio_needed = 0; 1394 info->factor_mallocs = 0; 1395 } 1396 PetscFunctionReturn(0); 1397 } 1398 1399 #undef __FUNCT__ 1400 #define __FUNCT__ "MatZeroRows_SeqAIJ" 1401 PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag) 1402 { 1403 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1404 PetscInt i,m = A->rmap->n - 1,d = 0; 1405 PetscErrorCode ierr; 1406 PetscTruth missing; 1407 1408 PetscFunctionBegin; 1409 if (a->keepnonzeropattern) { 1410 for (i=0; i<N; i++) { 1411 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1412 ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); 1413 } 1414 if (diag != 0.0) { 1415 ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); 1416 if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); 1417 for (i=0; i<N; i++) { 1418 a->a[a->diag[rows[i]]] = diag; 1419 } 1420 } 1421 A->same_nonzero = PETSC_TRUE; 1422 } else { 1423 if (diag != 0.0) { 1424 for (i=0; i<N; i++) { 1425 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1426 if (a->ilen[rows[i]] > 0) { 1427 a->ilen[rows[i]] = 1; 1428 a->a[a->i[rows[i]]] = diag; 1429 a->j[a->i[rows[i]]] = rows[i]; 1430 } else { /* in case row was completely empty */ 1431 ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); 1432 } 1433 } 1434 } else { 1435 for (i=0; i<N; i++) { 1436 if (rows[i] < 0 || rows[i] > m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); 1437 a->ilen[rows[i]] = 0; 1438 } 1439 } 1440 A->same_nonzero = PETSC_FALSE; 1441 } 1442 ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1443 PetscFunctionReturn(0); 1444 } 1445 1446 #undef __FUNCT__ 1447 #define __FUNCT__ "MatGetRow_SeqAIJ" 1448 PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1449 { 1450 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1451 PetscInt *itmp; 1452 1453 PetscFunctionBegin; 1454 if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); 1455 1456 *nz = a->i[row+1] - a->i[row]; 1457 if (v) *v = a->a + a->i[row]; 1458 if (idx) { 1459 itmp = a->j + a->i[row]; 1460 if (*nz) { 1461 *idx = itmp; 1462 } 1463 else *idx = 0; 1464 } 1465 PetscFunctionReturn(0); 1466 } 1467 1468 /* remove this function? */ 1469 #undef __FUNCT__ 1470 #define __FUNCT__ "MatRestoreRow_SeqAIJ" 1471 PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) 1472 { 1473 PetscFunctionBegin; 1474 PetscFunctionReturn(0); 1475 } 1476 1477 #undef __FUNCT__ 1478 #define __FUNCT__ "MatNorm_SeqAIJ" 1479 PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) 1480 { 1481 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1482 MatScalar *v = a->a; 1483 PetscReal sum = 0.0; 1484 PetscErrorCode ierr; 1485 PetscInt i,j; 1486 1487 PetscFunctionBegin; 1488 if (type == NORM_FROBENIUS) { 1489 for (i=0; i<a->nz; i++) { 1490 #if defined(PETSC_USE_COMPLEX) 1491 sum += PetscRealPart(PetscConj(*v)*(*v)); v++; 1492 #else 1493 sum += (*v)*(*v); v++; 1494 #endif 1495 } 1496 *nrm = sqrt(sum); 1497 } else if (type == NORM_1) { 1498 PetscReal *tmp; 1499 PetscInt *jj = a->j; 1500 ierr = PetscMalloc((A->cmap->n+1)*sizeof(PetscReal),&tmp);CHKERRQ(ierr); 1501 ierr = PetscMemzero(tmp,A->cmap->n*sizeof(PetscReal));CHKERRQ(ierr); 1502 *nrm = 0.0; 1503 for (j=0; j<a->nz; j++) { 1504 tmp[*jj++] += PetscAbsScalar(*v); v++; 1505 } 1506 for (j=0; j<A->cmap->n; j++) { 1507 if (tmp[j] > *nrm) *nrm = tmp[j]; 1508 } 1509 ierr = PetscFree(tmp);CHKERRQ(ierr); 1510 } else if (type == NORM_INFINITY) { 1511 *nrm = 0.0; 1512 for (j=0; j<A->rmap->n; j++) { 1513 v = a->a + a->i[j]; 1514 sum = 0.0; 1515 for (i=0; i<a->i[j+1]-a->i[j]; i++) { 1516 sum += PetscAbsScalar(*v); v++; 1517 } 1518 if (sum > *nrm) *nrm = sum; 1519 } 1520 } else { 1521 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); 1522 } 1523 PetscFunctionReturn(0); 1524 } 1525 1526 #undef __FUNCT__ 1527 #define __FUNCT__ "MatTranspose_SeqAIJ" 1528 PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) 1529 { 1530 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1531 Mat C; 1532 PetscErrorCode ierr; 1533 PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; 1534 MatScalar *array = a->a; 1535 1536 PetscFunctionBegin; 1537 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"); 1538 1539 if (reuse == MAT_INITIAL_MATRIX || *B == A) { 1540 ierr = PetscMalloc((1+A->cmap->n)*sizeof(PetscInt),&col);CHKERRQ(ierr); 1541 ierr = PetscMemzero(col,(1+A->cmap->n)*sizeof(PetscInt));CHKERRQ(ierr); 1542 1543 for (i=0; i<ai[m]; i++) col[aj[i]] += 1; 1544 ierr = MatCreate(((PetscObject)A)->comm,&C);CHKERRQ(ierr); 1545 ierr = MatSetSizes(C,A->cmap->n,m,A->cmap->n,m);CHKERRQ(ierr); 1546 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 1547 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); 1548 ierr = PetscFree(col);CHKERRQ(ierr); 1549 } else { 1550 C = *B; 1551 } 1552 1553 for (i=0; i<m; i++) { 1554 len = ai[i+1]-ai[i]; 1555 ierr = MatSetValues_SeqAIJ(C,len,aj,1,&i,array,INSERT_VALUES);CHKERRQ(ierr); 1556 array += len; 1557 aj += len; 1558 } 1559 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1560 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1561 1562 if (reuse == MAT_INITIAL_MATRIX || *B != A) { 1563 *B = C; 1564 } else { 1565 ierr = MatHeaderMerge(A,C);CHKERRQ(ierr); 1566 } 1567 PetscFunctionReturn(0); 1568 } 1569 1570 EXTERN_C_BEGIN 1571 #undef __FUNCT__ 1572 #define __FUNCT__ "MatIsTranspose_SeqAIJ" 1573 PetscErrorCode PETSCMAT_DLLEXPORT MatIsTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscTruth *f) 1574 { 1575 Mat_SeqAIJ *aij = (Mat_SeqAIJ *) A->data,*bij = (Mat_SeqAIJ*) A->data; 1576 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 1577 MatScalar *va,*vb; 1578 PetscErrorCode ierr; 1579 PetscInt ma,na,mb,nb, i; 1580 1581 PetscFunctionBegin; 1582 bij = (Mat_SeqAIJ *) B->data; 1583 1584 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 1585 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 1586 if (ma!=nb || na!=mb){ 1587 *f = PETSC_FALSE; 1588 PetscFunctionReturn(0); 1589 } 1590 aii = aij->i; bii = bij->i; 1591 adx = aij->j; bdx = bij->j; 1592 va = aij->a; vb = bij->a; 1593 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 1594 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 1595 for (i=0; i<ma; i++) aptr[i] = aii[i]; 1596 for (i=0; i<mb; i++) bptr[i] = bii[i]; 1597 1598 *f = PETSC_TRUE; 1599 for (i=0; i<ma; i++) { 1600 while (aptr[i]<aii[i+1]) { 1601 PetscInt idc,idr; 1602 PetscScalar vc,vr; 1603 /* column/row index/value */ 1604 idc = adx[aptr[i]]; 1605 idr = bdx[bptr[idc]]; 1606 vc = va[aptr[i]]; 1607 vr = vb[bptr[idc]]; 1608 if (i!=idr || PetscAbsScalar(vc-vr) > tol) { 1609 *f = PETSC_FALSE; 1610 goto done; 1611 } else { 1612 aptr[i]++; 1613 if (B || i!=idc) bptr[idc]++; 1614 } 1615 } 1616 } 1617 done: 1618 ierr = PetscFree(aptr);CHKERRQ(ierr); 1619 if (B) { 1620 ierr = PetscFree(bptr);CHKERRQ(ierr); 1621 } 1622 PetscFunctionReturn(0); 1623 } 1624 EXTERN_C_END 1625 1626 EXTERN_C_BEGIN 1627 #undef __FUNCT__ 1628 #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" 1629 PetscErrorCode PETSCMAT_DLLEXPORT MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscTruth *f) 1630 { 1631 Mat_SeqAIJ *aij = (Mat_SeqAIJ *) A->data,*bij = (Mat_SeqAIJ*) A->data; 1632 PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; 1633 MatScalar *va,*vb; 1634 PetscErrorCode ierr; 1635 PetscInt ma,na,mb,nb, i; 1636 1637 PetscFunctionBegin; 1638 bij = (Mat_SeqAIJ *) B->data; 1639 1640 ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); 1641 ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); 1642 if (ma!=nb || na!=mb){ 1643 *f = PETSC_FALSE; 1644 PetscFunctionReturn(0); 1645 } 1646 aii = aij->i; bii = bij->i; 1647 adx = aij->j; bdx = bij->j; 1648 va = aij->a; vb = bij->a; 1649 ierr = PetscMalloc(ma*sizeof(PetscInt),&aptr);CHKERRQ(ierr); 1650 ierr = PetscMalloc(mb*sizeof(PetscInt),&bptr);CHKERRQ(ierr); 1651 for (i=0; i<ma; i++) aptr[i] = aii[i]; 1652 for (i=0; i<mb; i++) bptr[i] = bii[i]; 1653 1654 *f = PETSC_TRUE; 1655 for (i=0; i<ma; i++) { 1656 while (aptr[i]<aii[i+1]) { 1657 PetscInt idc,idr; 1658 PetscScalar vc,vr; 1659 /* column/row index/value */ 1660 idc = adx[aptr[i]]; 1661 idr = bdx[bptr[idc]]; 1662 vc = va[aptr[i]]; 1663 vr = vb[bptr[idc]]; 1664 if (i!=idr || PetscAbsScalar(vc-PetscConj(vr)) > tol) { 1665 *f = PETSC_FALSE; 1666 goto done; 1667 } else { 1668 aptr[i]++; 1669 if (B || i!=idc) bptr[idc]++; 1670 } 1671 } 1672 } 1673 done: 1674 ierr = PetscFree(aptr);CHKERRQ(ierr); 1675 if (B) { 1676 ierr = PetscFree(bptr);CHKERRQ(ierr); 1677 } 1678 PetscFunctionReturn(0); 1679 } 1680 EXTERN_C_END 1681 1682 #undef __FUNCT__ 1683 #define __FUNCT__ "MatIsSymmetric_SeqAIJ" 1684 PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscTruth *f) 1685 { 1686 PetscErrorCode ierr; 1687 PetscFunctionBegin; 1688 ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 1689 PetscFunctionReturn(0); 1690 } 1691 1692 #undef __FUNCT__ 1693 #define __FUNCT__ "MatIsHermitian_SeqAIJ" 1694 PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscTruth *f) 1695 { 1696 PetscErrorCode ierr; 1697 PetscFunctionBegin; 1698 ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); 1699 PetscFunctionReturn(0); 1700 } 1701 1702 #undef __FUNCT__ 1703 #define __FUNCT__ "MatDiagonalScale_SeqAIJ" 1704 PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) 1705 { 1706 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1707 PetscScalar *l,*r,x; 1708 MatScalar *v; 1709 PetscErrorCode ierr; 1710 PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; 1711 1712 PetscFunctionBegin; 1713 if (ll) { 1714 /* The local size is used so that VecMPI can be passed to this routine 1715 by MatDiagonalScale_MPIAIJ */ 1716 ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); 1717 if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); 1718 ierr = VecGetArray(ll,&l);CHKERRQ(ierr); 1719 v = a->a; 1720 for (i=0; i<m; i++) { 1721 x = l[i]; 1722 M = a->i[i+1] - a->i[i]; 1723 for (j=0; j<M; j++) { (*v++) *= x;} 1724 } 1725 ierr = VecRestoreArray(ll,&l);CHKERRQ(ierr); 1726 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 1727 } 1728 if (rr) { 1729 ierr = VecGetLocalSize(rr,&n);CHKERRQ(ierr); 1730 if (n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); 1731 ierr = VecGetArray(rr,&r);CHKERRQ(ierr); 1732 v = a->a; jj = a->j; 1733 for (i=0; i<nz; i++) { 1734 (*v++) *= r[*jj++]; 1735 } 1736 ierr = VecRestoreArray(rr,&r);CHKERRQ(ierr); 1737 ierr = PetscLogFlops(nz);CHKERRQ(ierr); 1738 } 1739 PetscFunctionReturn(0); 1740 } 1741 1742 #undef __FUNCT__ 1743 #define __FUNCT__ "MatGetSubMatrix_SeqAIJ" 1744 PetscErrorCode MatGetSubMatrix_SeqAIJ(Mat A,IS isrow,IS iscol,PetscInt csize,MatReuse scall,Mat *B) 1745 { 1746 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*c; 1747 PetscErrorCode ierr; 1748 PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; 1749 PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; 1750 const PetscInt *irow,*icol; 1751 PetscInt nrows,ncols; 1752 PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; 1753 MatScalar *a_new,*mat_a; 1754 Mat C; 1755 PetscTruth stride,sorted; 1756 1757 PetscFunctionBegin; 1758 ierr = ISSorted(isrow,&sorted);CHKERRQ(ierr); 1759 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"ISrow is not sorted"); 1760 ierr = ISSorted(iscol,&sorted);CHKERRQ(ierr); 1761 if (!sorted) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"IScol is not sorted"); 1762 1763 ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); 1764 ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); 1765 ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); 1766 1767 ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); 1768 ierr = ISStride(iscol,&stride);CHKERRQ(ierr); 1769 if (stride && step == 1) { 1770 /* special case of contiguous rows */ 1771 ierr = PetscMalloc2(nrows,PetscInt,&lens,nrows,PetscInt,&starts);CHKERRQ(ierr); 1772 /* loop over new rows determining lens and starting points */ 1773 for (i=0; i<nrows; i++) { 1774 kstart = ai[irow[i]]; 1775 kend = kstart + ailen[irow[i]]; 1776 for (k=kstart; k<kend; k++) { 1777 if (aj[k] >= first) { 1778 starts[i] = k; 1779 break; 1780 } 1781 } 1782 sum = 0; 1783 while (k < kend) { 1784 if (aj[k++] >= first+ncols) break; 1785 sum++; 1786 } 1787 lens[i] = sum; 1788 } 1789 /* create submatrix */ 1790 if (scall == MAT_REUSE_MATRIX) { 1791 PetscInt n_cols,n_rows; 1792 ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); 1793 if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); 1794 ierr = MatZeroEntries(*B);CHKERRQ(ierr); 1795 C = *B; 1796 } else { 1797 ierr = MatCreate(((PetscObject)A)->comm,&C);CHKERRQ(ierr); 1798 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 1799 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 1800 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 1801 } 1802 c = (Mat_SeqAIJ*)C->data; 1803 1804 /* loop over rows inserting into submatrix */ 1805 a_new = c->a; 1806 j_new = c->j; 1807 i_new = c->i; 1808 1809 for (i=0; i<nrows; i++) { 1810 ii = starts[i]; 1811 lensi = lens[i]; 1812 for (k=0; k<lensi; k++) { 1813 *j_new++ = aj[ii+k] - first; 1814 } 1815 ierr = PetscMemcpy(a_new,a->a + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); 1816 a_new += lensi; 1817 i_new[i+1] = i_new[i] + lensi; 1818 c->ilen[i] = lensi; 1819 } 1820 ierr = PetscFree2(lens,starts);CHKERRQ(ierr); 1821 } else { 1822 ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); 1823 ierr = PetscMalloc(oldcols*sizeof(PetscInt),&smap);CHKERRQ(ierr); 1824 ierr = PetscMemzero(smap,oldcols*sizeof(PetscInt));CHKERRQ(ierr); 1825 ierr = PetscMalloc((1+nrows)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 1826 for (i=0; i<ncols; i++) smap[icol[i]] = i+1; 1827 /* determine lens of each row */ 1828 for (i=0; i<nrows; i++) { 1829 kstart = ai[irow[i]]; 1830 kend = kstart + a->ilen[irow[i]]; 1831 lens[i] = 0; 1832 for (k=kstart; k<kend; k++) { 1833 if (smap[aj[k]]) { 1834 lens[i]++; 1835 } 1836 } 1837 } 1838 /* Create and fill new matrix */ 1839 if (scall == MAT_REUSE_MATRIX) { 1840 PetscTruth equal; 1841 1842 c = (Mat_SeqAIJ *)((*B)->data); 1843 if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); 1844 ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); 1845 if (!equal) { 1846 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); 1847 } 1848 ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 1849 C = *B; 1850 } else { 1851 ierr = MatCreate(((PetscObject)A)->comm,&C);CHKERRQ(ierr); 1852 ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); 1853 ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); 1854 ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); 1855 } 1856 c = (Mat_SeqAIJ *)(C->data); 1857 for (i=0; i<nrows; i++) { 1858 row = irow[i]; 1859 kstart = ai[row]; 1860 kend = kstart + a->ilen[row]; 1861 mat_i = c->i[i]; 1862 mat_j = c->j + mat_i; 1863 mat_a = c->a + mat_i; 1864 mat_ilen = c->ilen + i; 1865 for (k=kstart; k<kend; k++) { 1866 if ((tcol=smap[a->j[k]])) { 1867 *mat_j++ = tcol - 1; 1868 *mat_a++ = a->a[k]; 1869 (*mat_ilen)++; 1870 1871 } 1872 } 1873 } 1874 /* Free work space */ 1875 ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); 1876 ierr = PetscFree(smap);CHKERRQ(ierr); 1877 ierr = PetscFree(lens);CHKERRQ(ierr); 1878 } 1879 ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1880 ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 1881 1882 ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); 1883 *B = C; 1884 PetscFunctionReturn(0); 1885 } 1886 1887 #undef __FUNCT__ 1888 #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" 1889 PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,Mat* subMat) 1890 { 1891 PetscErrorCode ierr; 1892 Mat B; 1893 1894 PetscFunctionBegin; 1895 ierr = MatCreate(subComm,&B);CHKERRQ(ierr); 1896 ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); 1897 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 1898 ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); 1899 *subMat = B; 1900 PetscFunctionReturn(0); 1901 } 1902 1903 #undef __FUNCT__ 1904 #define __FUNCT__ "MatILUFactor_SeqAIJ" 1905 PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) 1906 { 1907 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 1908 PetscErrorCode ierr; 1909 Mat outA; 1910 PetscTruth row_identity,col_identity; 1911 1912 PetscFunctionBegin; 1913 if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); 1914 1915 ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); 1916 ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); 1917 1918 outA = inA; 1919 outA->factortype = MAT_FACTOR_LU; 1920 ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); 1921 if (a->row) { ierr = ISDestroy(a->row);CHKERRQ(ierr);} 1922 a->row = row; 1923 ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); 1924 if (a->col) { ierr = ISDestroy(a->col);CHKERRQ(ierr);} 1925 a->col = col; 1926 1927 /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ 1928 if (a->icol) {ierr = ISDestroy(a->icol);CHKERRQ(ierr);} /* need to remove old one */ 1929 ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); 1930 ierr = PetscLogObjectParent(inA,a->icol);CHKERRQ(ierr); 1931 1932 if (!a->solve_work) { /* this matrix may have been factored before */ 1933 ierr = PetscMalloc((inA->rmap->n+1)*sizeof(PetscScalar),&a->solve_work);CHKERRQ(ierr); 1934 ierr = PetscLogObjectMemory(inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); 1935 } 1936 1937 ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); 1938 if (row_identity && col_identity) { 1939 ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); 1940 } else { 1941 ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); 1942 } 1943 PetscFunctionReturn(0); 1944 } 1945 1946 #undef __FUNCT__ 1947 #define __FUNCT__ "MatScale_SeqAIJ" 1948 PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) 1949 { 1950 Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; 1951 PetscScalar oalpha = alpha; 1952 PetscErrorCode ierr; 1953 PetscBLASInt one = 1,bnz = PetscBLASIntCast(a->nz); 1954 1955 PetscFunctionBegin; 1956 BLASscal_(&bnz,&oalpha,a->a,&one); 1957 ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); 1958 PetscFunctionReturn(0); 1959 } 1960 1961 #undef __FUNCT__ 1962 #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" 1963 PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) 1964 { 1965 PetscErrorCode ierr; 1966 PetscInt i; 1967 1968 PetscFunctionBegin; 1969 if (scall == MAT_INITIAL_MATRIX) { 1970 ierr = PetscMalloc((n+1)*sizeof(Mat),B);CHKERRQ(ierr); 1971 } 1972 1973 for (i=0; i<n; i++) { 1974 ierr = MatGetSubMatrix_SeqAIJ(A,irow[i],icol[i],PETSC_DECIDE,scall,&(*B)[i]);CHKERRQ(ierr); 1975 } 1976 PetscFunctionReturn(0); 1977 } 1978 1979 #undef __FUNCT__ 1980 #define __FUNCT__ "MatIncreaseOverlap_SeqAIJ" 1981 PetscErrorCode MatIncreaseOverlap_SeqAIJ(Mat A,PetscInt is_max,IS is[],PetscInt ov) 1982 { 1983 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 1984 PetscErrorCode ierr; 1985 PetscInt row,i,j,k,l,m,n,*nidx,isz,val; 1986 const PetscInt *idx; 1987 PetscInt start,end,*ai,*aj; 1988 PetscBT table; 1989 1990 PetscFunctionBegin; 1991 m = A->rmap->n; 1992 ai = a->i; 1993 aj = a->j; 1994 1995 if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); 1996 1997 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&nidx);CHKERRQ(ierr); 1998 ierr = PetscBTCreate(m,table);CHKERRQ(ierr); 1999 2000 for (i=0; i<is_max; i++) { 2001 /* Initialize the two local arrays */ 2002 isz = 0; 2003 ierr = PetscBTMemzero(m,table);CHKERRQ(ierr); 2004 2005 /* Extract the indices, assume there can be duplicate entries */ 2006 ierr = ISGetIndices(is[i],&idx);CHKERRQ(ierr); 2007 ierr = ISGetLocalSize(is[i],&n);CHKERRQ(ierr); 2008 2009 /* Enter these into the temp arrays. I.e., mark table[row], enter row into new index */ 2010 for (j=0; j<n ; ++j){ 2011 if(!PetscBTLookupSet(table,idx[j])) { nidx[isz++] = idx[j];} 2012 } 2013 ierr = ISRestoreIndices(is[i],&idx);CHKERRQ(ierr); 2014 ierr = ISDestroy(is[i]);CHKERRQ(ierr); 2015 2016 k = 0; 2017 for (j=0; j<ov; j++){ /* for each overlap */ 2018 n = isz; 2019 for (; k<n ; k++){ /* do only those rows in nidx[k], which are not done yet */ 2020 row = nidx[k]; 2021 start = ai[row]; 2022 end = ai[row+1]; 2023 for (l = start; l<end ; l++){ 2024 val = aj[l] ; 2025 if (!PetscBTLookupSet(table,val)) {nidx[isz++] = val;} 2026 } 2027 } 2028 } 2029 ierr = ISCreateGeneral(PETSC_COMM_SELF,isz,nidx,(is+i));CHKERRQ(ierr); 2030 } 2031 ierr = PetscBTDestroy(table);CHKERRQ(ierr); 2032 ierr = PetscFree(nidx);CHKERRQ(ierr); 2033 PetscFunctionReturn(0); 2034 } 2035 2036 /* -------------------------------------------------------------- */ 2037 #undef __FUNCT__ 2038 #define __FUNCT__ "MatPermute_SeqAIJ" 2039 PetscErrorCode MatPermute_SeqAIJ(Mat A,IS rowp,IS colp,Mat *B) 2040 { 2041 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2042 PetscErrorCode ierr; 2043 PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; 2044 const PetscInt *row,*col; 2045 PetscInt *cnew,j,*lens; 2046 IS icolp,irowp; 2047 PetscInt *cwork = PETSC_NULL; 2048 PetscScalar *vwork = PETSC_NULL; 2049 2050 PetscFunctionBegin; 2051 ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); 2052 ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); 2053 ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); 2054 ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); 2055 2056 /* determine lengths of permuted rows */ 2057 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&lens);CHKERRQ(ierr); 2058 for (i=0; i<m; i++) { 2059 lens[row[i]] = a->i[i+1] - a->i[i]; 2060 } 2061 ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr); 2062 ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); 2063 ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); 2064 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); 2065 ierr = PetscFree(lens);CHKERRQ(ierr); 2066 2067 ierr = PetscMalloc(n*sizeof(PetscInt),&cnew);CHKERRQ(ierr); 2068 for (i=0; i<m; i++) { 2069 ierr = MatGetRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2070 for (j=0; j<nz; j++) { cnew[j] = col[cwork[j]];} 2071 ierr = MatSetValues_SeqAIJ(*B,1,&row[i],nz,cnew,vwork,INSERT_VALUES);CHKERRQ(ierr); 2072 ierr = MatRestoreRow_SeqAIJ(A,i,&nz,&cwork,&vwork);CHKERRQ(ierr); 2073 } 2074 ierr = PetscFree(cnew);CHKERRQ(ierr); 2075 (*B)->assembled = PETSC_FALSE; 2076 ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2077 ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2078 ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); 2079 ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); 2080 ierr = ISDestroy(irowp);CHKERRQ(ierr); 2081 ierr = ISDestroy(icolp);CHKERRQ(ierr); 2082 PetscFunctionReturn(0); 2083 } 2084 2085 #undef __FUNCT__ 2086 #define __FUNCT__ "MatCopy_SeqAIJ" 2087 PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) 2088 { 2089 PetscErrorCode ierr; 2090 2091 PetscFunctionBegin; 2092 /* If the two matrices have the same copy implementation, use fast copy. */ 2093 if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { 2094 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2095 Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; 2096 2097 if (a->i[A->rmap->n] != b->i[B->rmap->n]) { 2098 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different"); 2099 } 2100 ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); 2101 } else { 2102 ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); 2103 } 2104 PetscFunctionReturn(0); 2105 } 2106 2107 #undef __FUNCT__ 2108 #define __FUNCT__ "MatSetUpPreallocation_SeqAIJ" 2109 PetscErrorCode MatSetUpPreallocation_SeqAIJ(Mat A) 2110 { 2111 PetscErrorCode ierr; 2112 2113 PetscFunctionBegin; 2114 ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); 2115 PetscFunctionReturn(0); 2116 } 2117 2118 #undef __FUNCT__ 2119 #define __FUNCT__ "MatGetArray_SeqAIJ" 2120 PetscErrorCode MatGetArray_SeqAIJ(Mat A,PetscScalar *array[]) 2121 { 2122 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2123 PetscFunctionBegin; 2124 *array = a->a; 2125 PetscFunctionReturn(0); 2126 } 2127 2128 #undef __FUNCT__ 2129 #define __FUNCT__ "MatRestoreArray_SeqAIJ" 2130 PetscErrorCode MatRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) 2131 { 2132 PetscFunctionBegin; 2133 PetscFunctionReturn(0); 2134 } 2135 2136 #undef __FUNCT__ 2137 #define __FUNCT__ "MatFDColoringApply_SeqAIJ" 2138 PetscErrorCode MatFDColoringApply_SeqAIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx) 2139 { 2140 PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void *))coloring->f; 2141 PetscErrorCode ierr; 2142 PetscInt k,N,start,end,l,row,col,srow,**vscaleforrow,m1,m2; 2143 PetscScalar dx,*y,*xx,*w3_array; 2144 PetscScalar *vscale_array; 2145 PetscReal epsilon = coloring->error_rel,umin = coloring->umin; 2146 Vec w1,w2,w3; 2147 void *fctx = coloring->fctx; 2148 PetscTruth flg = PETSC_FALSE; 2149 2150 PetscFunctionBegin; 2151 if (!coloring->w1) { 2152 ierr = VecDuplicate(x1,&coloring->w1);CHKERRQ(ierr); 2153 ierr = PetscLogObjectParent(coloring,coloring->w1);CHKERRQ(ierr); 2154 ierr = VecDuplicate(x1,&coloring->w2);CHKERRQ(ierr); 2155 ierr = PetscLogObjectParent(coloring,coloring->w2);CHKERRQ(ierr); 2156 ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr); 2157 ierr = PetscLogObjectParent(coloring,coloring->w3);CHKERRQ(ierr); 2158 } 2159 w1 = coloring->w1; w2 = coloring->w2; w3 = coloring->w3; 2160 2161 ierr = MatSetUnfactored(J);CHKERRQ(ierr); 2162 ierr = PetscOptionsGetTruth(((PetscObject)coloring)->prefix,"-mat_fd_coloring_dont_rezero",&flg,PETSC_NULL);CHKERRQ(ierr); 2163 if (flg) { 2164 ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr); 2165 } else { 2166 PetscTruth assembled; 2167 ierr = MatAssembled(J,&assembled);CHKERRQ(ierr); 2168 if (assembled) { 2169 ierr = MatZeroEntries(J);CHKERRQ(ierr); 2170 } 2171 } 2172 2173 ierr = VecGetOwnershipRange(x1,&start,&end);CHKERRQ(ierr); 2174 ierr = VecGetSize(x1,&N);CHKERRQ(ierr); 2175 2176 /* 2177 This is a horrible, horrible, hack. See DMMGComputeJacobian_Multigrid() it inproperly sets 2178 coloring->F for the coarser grids from the finest 2179 */ 2180 if (coloring->F) { 2181 ierr = VecGetLocalSize(coloring->F,&m1);CHKERRQ(ierr); 2182 ierr = VecGetLocalSize(w1,&m2);CHKERRQ(ierr); 2183 if (m1 != m2) { 2184 coloring->F = 0; 2185 } 2186 } 2187 2188 if (coloring->F) { 2189 w1 = coloring->F; 2190 coloring->F = 0; 2191 } else { 2192 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2193 ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr); 2194 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2195 } 2196 2197 /* 2198 Compute all the scale factors and share with other processors 2199 */ 2200 ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);xx = xx - start; 2201 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);vscale_array = vscale_array - start; 2202 for (k=0; k<coloring->ncolors; k++) { 2203 /* 2204 Loop over each column associated with color adding the 2205 perturbation to the vector w3. 2206 */ 2207 for (l=0; l<coloring->ncolumns[k]; l++) { 2208 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2209 dx = xx[col]; 2210 if (dx == 0.0) dx = 1.0; 2211 #if !defined(PETSC_USE_COMPLEX) 2212 if (dx < umin && dx >= 0.0) dx = umin; 2213 else if (dx < 0.0 && dx > -umin) dx = -umin; 2214 #else 2215 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2216 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2217 #endif 2218 dx *= epsilon; 2219 vscale_array[col] = 1.0/dx; 2220 } 2221 } 2222 vscale_array = vscale_array + start;ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2223 ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2224 ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr); 2225 2226 /* ierr = VecView(coloring->vscale,PETSC_VIEWER_STDOUT_WORLD); 2227 ierr = VecView(x1,PETSC_VIEWER_STDOUT_WORLD);*/ 2228 2229 if (coloring->vscaleforrow) vscaleforrow = coloring->vscaleforrow; 2230 else vscaleforrow = coloring->columnsforrow; 2231 2232 ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2233 /* 2234 Loop over each color 2235 */ 2236 for (k=0; k<coloring->ncolors; k++) { 2237 coloring->currentcolor = k; 2238 ierr = VecCopy(x1,w3);CHKERRQ(ierr); 2239 ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);w3_array = w3_array - start; 2240 /* 2241 Loop over each column associated with color adding the 2242 perturbation to the vector w3. 2243 */ 2244 for (l=0; l<coloring->ncolumns[k]; l++) { 2245 col = coloring->columns[k][l]; /* column of the matrix we are probing for */ 2246 dx = xx[col]; 2247 if (dx == 0.0) dx = 1.0; 2248 #if !defined(PETSC_USE_COMPLEX) 2249 if (dx < umin && dx >= 0.0) dx = umin; 2250 else if (dx < 0.0 && dx > -umin) dx = -umin; 2251 #else 2252 if (PetscAbsScalar(dx) < umin && PetscRealPart(dx) >= 0.0) dx = umin; 2253 else if (PetscRealPart(dx) < 0.0 && PetscAbsScalar(dx) < umin) dx = -umin; 2254 #endif 2255 dx *= epsilon; 2256 if (!PetscAbsScalar(dx)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Computed 0 differencing parameter"); 2257 w3_array[col] += dx; 2258 } 2259 w3_array = w3_array + start; ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr); 2260 2261 /* 2262 Evaluate function at x1 + dx (here dx is a vector of perturbations) 2263 */ 2264 2265 ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2266 ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr); 2267 ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr); 2268 ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr); 2269 2270 /* 2271 Loop over rows of vector, putting results into Jacobian matrix 2272 */ 2273 ierr = VecGetArray(w2,&y);CHKERRQ(ierr); 2274 for (l=0; l<coloring->nrows[k]; l++) { 2275 row = coloring->rows[k][l]; 2276 col = coloring->columnsforrow[k][l]; 2277 y[row] *= vscale_array[vscaleforrow[k][l]]; 2278 srow = row + start; 2279 ierr = MatSetValues_SeqAIJ(J,1,&srow,1,&col,y+row,INSERT_VALUES);CHKERRQ(ierr); 2280 } 2281 ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr); 2282 } 2283 coloring->currentcolor = k; 2284 ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr); 2285 xx = xx + start; ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr); 2286 ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2287 ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 2288 PetscFunctionReturn(0); 2289 } 2290 2291 #undef __FUNCT__ 2292 #define __FUNCT__ "MatAXPYSetPreallocation_SeqAIJ" 2293 PetscErrorCode MatAXPYSetPreallocation_SeqAIJ(Mat B,Mat Y,Mat X) 2294 { 2295 PetscInt i,nzx,nzy,m=Y->rmap->N,n=Y->cmap->N; 2296 PetscErrorCode ierr; 2297 Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; 2298 Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; 2299 const PetscInt *xi = x->i,*yi = y->i; 2300 PetscInt *nnz; 2301 2302 PetscFunctionBegin; 2303 ierr = PetscMalloc(n*sizeof(PetscInt),&nnz);CHKERRQ(ierr); 2304 /* Set the number of nonzeros in the new matrix */ 2305 for(i = 0;i < m;i++) { 2306 nzx = xi[i+1] - xi[i]; nzy = yi[i+1] - yi[i]; 2307 if (nzx > nzy) nnz[i] = nzy + (nzx - nzy); 2308 else nnz[i] = nzx + (nzy - nzx); 2309 } 2310 /* Preallocate matrix */ 2311 ierr = MatSeqAIJSetPreallocation(B,PETSC_NULL,nnz);CHKERRQ(ierr); 2312 2313 ierr = PetscFree(nnz);CHKERRQ(ierr); 2314 PetscFunctionReturn(0); 2315 } 2316 2317 #undef __FUNCT__ 2318 #define __FUNCT__ "MatAXPY_SeqAIJ" 2319 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2320 { 2321 PetscErrorCode ierr; 2322 PetscInt i; 2323 Mat_SeqAIJ *x = (Mat_SeqAIJ *)X->data,*y = (Mat_SeqAIJ *)Y->data; 2324 PetscBLASInt one=1,bnz = PetscBLASIntCast(x->nz); 2325 Mat B; 2326 2327 PetscFunctionBegin; 2328 if (str == SAME_NONZERO_PATTERN) { 2329 PetscScalar alpha = a; 2330 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 2331 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2332 if (y->xtoy && y->XtoY != X) { 2333 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2334 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 2335 } 2336 if (!y->xtoy) { /* get xtoy */ 2337 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);CHKERRQ(ierr); 2338 y->XtoY = X; 2339 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2340 } 2341 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2342 ierr = PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %d/%d = %G\n",x->nz,y->nz,(PetscReal)(x->nz)/y->nz);CHKERRQ(ierr); 2343 } else { 2344 ierr = MatCreate(((PetscObject)Y)->comm,&B);CHKERRQ(ierr); 2345 ierr = MatSetSizes(B,Y->rmap->n,Y->rmap->N,Y->cmap->n,Y->cmap->N);CHKERRQ(ierr); 2346 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2347 ierr = MatAXPYSetPreallocation_SeqAIJ(B,Y,X);CHKERRQ(ierr); 2348 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2349 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2350 } 2351 PetscFunctionReturn(0); 2352 } 2353 2354 #undef __FUNCT__ 2355 #define __FUNCT__ "MatSetBlockSize_SeqAIJ" 2356 PetscErrorCode MatSetBlockSize_SeqAIJ(Mat A,PetscInt bs) 2357 { 2358 PetscErrorCode ierr; 2359 2360 PetscFunctionBegin; 2361 ierr = PetscLayoutSetBlockSize(A->rmap,bs);CHKERRQ(ierr); 2362 ierr = PetscLayoutSetBlockSize(A->cmap,bs);CHKERRQ(ierr); 2363 PetscFunctionReturn(0); 2364 } 2365 2366 #undef __FUNCT__ 2367 #define __FUNCT__ "MatConjugate_SeqAIJ" 2368 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat mat) 2369 { 2370 #if defined(PETSC_USE_COMPLEX) 2371 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2372 PetscInt i,nz; 2373 PetscScalar *a; 2374 2375 PetscFunctionBegin; 2376 nz = aij->nz; 2377 a = aij->a; 2378 for (i=0; i<nz; i++) { 2379 a[i] = PetscConj(a[i]); 2380 } 2381 #else 2382 PetscFunctionBegin; 2383 #endif 2384 PetscFunctionReturn(0); 2385 } 2386 2387 #undef __FUNCT__ 2388 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 2389 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2390 { 2391 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2392 PetscErrorCode ierr; 2393 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2394 PetscReal atmp; 2395 PetscScalar *x; 2396 MatScalar *aa; 2397 2398 PetscFunctionBegin; 2399 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2400 aa = a->a; 2401 ai = a->i; 2402 aj = a->j; 2403 2404 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2405 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2406 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2407 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2408 for (i=0; i<m; i++) { 2409 ncols = ai[1] - ai[0]; ai++; 2410 x[i] = 0.0; 2411 for (j=0; j<ncols; j++){ 2412 atmp = PetscAbsScalar(*aa); 2413 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2414 aa++; aj++; 2415 } 2416 } 2417 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2418 PetscFunctionReturn(0); 2419 } 2420 2421 #undef __FUNCT__ 2422 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 2423 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2424 { 2425 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2426 PetscErrorCode ierr; 2427 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2428 PetscScalar *x; 2429 MatScalar *aa; 2430 2431 PetscFunctionBegin; 2432 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2433 aa = a->a; 2434 ai = a->i; 2435 aj = a->j; 2436 2437 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2438 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2439 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2440 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2441 for (i=0; i<m; i++) { 2442 ncols = ai[1] - ai[0]; ai++; 2443 if (ncols == A->cmap->n) { /* row is dense */ 2444 x[i] = *aa; if (idx) idx[i] = 0; 2445 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2446 x[i] = 0.0; 2447 if (idx) { 2448 idx[i] = 0; /* in case ncols is zero */ 2449 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2450 if (aj[j] > j) { 2451 idx[i] = j; 2452 break; 2453 } 2454 } 2455 } 2456 } 2457 for (j=0; j<ncols; j++){ 2458 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2459 aa++; aj++; 2460 } 2461 } 2462 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2463 PetscFunctionReturn(0); 2464 } 2465 2466 #undef __FUNCT__ 2467 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 2468 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2469 { 2470 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2471 PetscErrorCode ierr; 2472 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2473 PetscReal atmp; 2474 PetscScalar *x; 2475 MatScalar *aa; 2476 2477 PetscFunctionBegin; 2478 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2479 aa = a->a; 2480 ai = a->i; 2481 aj = a->j; 2482 2483 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2484 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2485 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2486 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2487 for (i=0; i<m; i++) { 2488 ncols = ai[1] - ai[0]; ai++; 2489 if (ncols) { 2490 /* Get first nonzero */ 2491 for(j = 0; j < ncols; j++) { 2492 atmp = PetscAbsScalar(aa[j]); 2493 if (atmp > 1.0e-12) {x[i] = atmp; if (idx) idx[i] = aj[j]; break;} 2494 } 2495 if (j == ncols) {x[i] = *aa; if (idx) idx[i] = *aj;} 2496 } else { 2497 x[i] = 0.0; if (idx) idx[i] = 0; 2498 } 2499 for(j = 0; j < ncols; j++) { 2500 atmp = PetscAbsScalar(*aa); 2501 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2502 aa++; aj++; 2503 } 2504 } 2505 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2506 PetscFunctionReturn(0); 2507 } 2508 2509 #undef __FUNCT__ 2510 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 2511 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2512 { 2513 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2514 PetscErrorCode ierr; 2515 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2516 PetscScalar *x; 2517 MatScalar *aa; 2518 2519 PetscFunctionBegin; 2520 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2521 aa = a->a; 2522 ai = a->i; 2523 aj = a->j; 2524 2525 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2526 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2527 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2528 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2529 for (i=0; i<m; i++) { 2530 ncols = ai[1] - ai[0]; ai++; 2531 if (ncols == A->cmap->n) { /* row is dense */ 2532 x[i] = *aa; if (idx) idx[i] = 0; 2533 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2534 x[i] = 0.0; 2535 if (idx) { /* find first implicit 0.0 in the row */ 2536 idx[i] = 0; /* in case ncols is zero */ 2537 for (j=0;j<ncols;j++) { 2538 if (aj[j] > j) { 2539 idx[i] = j; 2540 break; 2541 } 2542 } 2543 } 2544 } 2545 for (j=0; j<ncols; j++){ 2546 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2547 aa++; aj++; 2548 } 2549 } 2550 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2551 PetscFunctionReturn(0); 2552 } 2553 extern PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 2554 /* -------------------------------------------------------------------*/ 2555 static struct _MatOps MatOps_Values = {MatSetValues_SeqAIJ, 2556 MatGetRow_SeqAIJ, 2557 MatRestoreRow_SeqAIJ, 2558 MatMult_SeqAIJ, 2559 /* 4*/ MatMultAdd_SeqAIJ, 2560 MatMultTranspose_SeqAIJ, 2561 MatMultTransposeAdd_SeqAIJ, 2562 0, 2563 0, 2564 0, 2565 /*10*/ 0, 2566 MatLUFactor_SeqAIJ, 2567 0, 2568 MatSOR_SeqAIJ, 2569 MatTranspose_SeqAIJ, 2570 /*15*/ MatGetInfo_SeqAIJ, 2571 MatEqual_SeqAIJ, 2572 MatGetDiagonal_SeqAIJ, 2573 MatDiagonalScale_SeqAIJ, 2574 MatNorm_SeqAIJ, 2575 /*20*/ 0, 2576 MatAssemblyEnd_SeqAIJ, 2577 MatSetOption_SeqAIJ, 2578 MatZeroEntries_SeqAIJ, 2579 /*24*/ MatZeroRows_SeqAIJ, 2580 0, 2581 0, 2582 0, 2583 0, 2584 /*29*/ MatSetUpPreallocation_SeqAIJ, 2585 0, 2586 0, 2587 MatGetArray_SeqAIJ, 2588 MatRestoreArray_SeqAIJ, 2589 /*34*/ MatDuplicate_SeqAIJ, 2590 0, 2591 0, 2592 MatILUFactor_SeqAIJ, 2593 0, 2594 /*39*/ MatAXPY_SeqAIJ, 2595 MatGetSubMatrices_SeqAIJ, 2596 MatIncreaseOverlap_SeqAIJ, 2597 MatGetValues_SeqAIJ, 2598 MatCopy_SeqAIJ, 2599 /*44*/ MatGetRowMax_SeqAIJ, 2600 MatScale_SeqAIJ, 2601 0, 2602 MatDiagonalSet_SeqAIJ, 2603 0, 2604 /*49*/ MatSetBlockSize_SeqAIJ, 2605 MatGetRowIJ_SeqAIJ, 2606 MatRestoreRowIJ_SeqAIJ, 2607 MatGetColumnIJ_SeqAIJ, 2608 MatRestoreColumnIJ_SeqAIJ, 2609 /*54*/ MatFDColoringCreate_SeqAIJ, 2610 0, 2611 0, 2612 MatPermute_SeqAIJ, 2613 0, 2614 /*59*/ 0, 2615 MatDestroy_SeqAIJ, 2616 MatView_SeqAIJ, 2617 0, 2618 0, 2619 /*64*/ 0, 2620 0, 2621 0, 2622 0, 2623 0, 2624 /*69*/ MatGetRowMaxAbs_SeqAIJ, 2625 MatGetRowMinAbs_SeqAIJ, 2626 0, 2627 MatSetColoring_SeqAIJ, 2628 #if defined(PETSC_HAVE_ADIC) 2629 MatSetValuesAdic_SeqAIJ, 2630 #else 2631 0, 2632 #endif 2633 /*74*/ MatSetValuesAdifor_SeqAIJ, 2634 MatFDColoringApply_AIJ, 2635 0, 2636 0, 2637 0, 2638 /*79*/ 0, 2639 0, 2640 0, 2641 0, 2642 MatLoad_SeqAIJ, 2643 /*84*/ MatIsSymmetric_SeqAIJ, 2644 MatIsHermitian_SeqAIJ, 2645 0, 2646 0, 2647 0, 2648 /*89*/ MatMatMult_SeqAIJ_SeqAIJ, 2649 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 2650 MatMatMultNumeric_SeqAIJ_SeqAIJ, 2651 MatPtAP_Basic, 2652 MatPtAPSymbolic_SeqAIJ, 2653 /*94*/ MatPtAPNumeric_SeqAIJ, 2654 MatMatMultTranspose_SeqAIJ_SeqAIJ, 2655 MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ, 2656 MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ, 2657 MatPtAPSymbolic_SeqAIJ_SeqAIJ, 2658 /*99*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 2659 0, 2660 0, 2661 MatConjugate_SeqAIJ, 2662 0, 2663 /*104*/MatSetValuesRow_SeqAIJ, 2664 MatRealPart_SeqAIJ, 2665 MatImaginaryPart_SeqAIJ, 2666 0, 2667 0, 2668 /*109*/0, 2669 0, 2670 MatGetRowMin_SeqAIJ, 2671 0, 2672 MatMissingDiagonal_SeqAIJ, 2673 /*114*/0, 2674 0, 2675 0, 2676 0, 2677 0, 2678 /*119*/0, 2679 0, 2680 0, 2681 0, 2682 MatGetMultiProcBlock_SeqAIJ 2683 }; 2684 2685 EXTERN_C_BEGIN 2686 #undef __FUNCT__ 2687 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 2688 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 2689 { 2690 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2691 PetscInt i,nz,n; 2692 2693 PetscFunctionBegin; 2694 2695 nz = aij->maxnz; 2696 n = mat->rmap->n; 2697 for (i=0; i<nz; i++) { 2698 aij->j[i] = indices[i]; 2699 } 2700 aij->nz = nz; 2701 for (i=0; i<n; i++) { 2702 aij->ilen[i] = aij->imax[i]; 2703 } 2704 2705 PetscFunctionReturn(0); 2706 } 2707 EXTERN_C_END 2708 2709 #undef __FUNCT__ 2710 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 2711 /*@ 2712 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 2713 in the matrix. 2714 2715 Input Parameters: 2716 + mat - the SeqAIJ matrix 2717 - indices - the column indices 2718 2719 Level: advanced 2720 2721 Notes: 2722 This can be called if you have precomputed the nonzero structure of the 2723 matrix and want to provide it to the matrix object to improve the performance 2724 of the MatSetValues() operation. 2725 2726 You MUST have set the correct numbers of nonzeros per row in the call to 2727 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 2728 2729 MUST be called before any calls to MatSetValues(); 2730 2731 The indices should start with zero, not one. 2732 2733 @*/ 2734 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 2735 { 2736 PetscErrorCode ierr,(*f)(Mat,PetscInt *); 2737 2738 PetscFunctionBegin; 2739 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2740 PetscValidPointer(indices,2); 2741 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqAIJSetColumnIndices_C",(void (**)(void))&f);CHKERRQ(ierr); 2742 if (f) { 2743 ierr = (*f)(mat,indices);CHKERRQ(ierr); 2744 } else { 2745 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to set column indices"); 2746 } 2747 PetscFunctionReturn(0); 2748 } 2749 2750 /* ----------------------------------------------------------------------------------------*/ 2751 2752 EXTERN_C_BEGIN 2753 #undef __FUNCT__ 2754 #define __FUNCT__ "MatStoreValues_SeqAIJ" 2755 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_SeqAIJ(Mat mat) 2756 { 2757 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2758 PetscErrorCode ierr; 2759 size_t nz = aij->i[mat->rmap->n]; 2760 2761 PetscFunctionBegin; 2762 if (aij->nonew != 1) { 2763 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2764 } 2765 2766 /* allocate space for values if not already there */ 2767 if (!aij->saved_values) { 2768 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 2769 ierr = PetscLogObjectMemory(mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2770 } 2771 2772 /* copy values over */ 2773 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2774 PetscFunctionReturn(0); 2775 } 2776 EXTERN_C_END 2777 2778 #undef __FUNCT__ 2779 #define __FUNCT__ "MatStoreValues" 2780 /*@ 2781 MatStoreValues - Stashes a copy of the matrix values; this allows, for 2782 example, reuse of the linear part of a Jacobian, while recomputing the 2783 nonlinear portion. 2784 2785 Collect on Mat 2786 2787 Input Parameters: 2788 . mat - the matrix (currently only AIJ matrices support this option) 2789 2790 Level: advanced 2791 2792 Common Usage, with SNESSolve(): 2793 $ Create Jacobian matrix 2794 $ Set linear terms into matrix 2795 $ Apply boundary conditions to matrix, at this time matrix must have 2796 $ final nonzero structure (i.e. setting the nonlinear terms and applying 2797 $ boundary conditions again will not change the nonzero structure 2798 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 2799 $ ierr = MatStoreValues(mat); 2800 $ Call SNESSetJacobian() with matrix 2801 $ In your Jacobian routine 2802 $ ierr = MatRetrieveValues(mat); 2803 $ Set nonlinear terms in matrix 2804 2805 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 2806 $ // build linear portion of Jacobian 2807 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 2808 $ ierr = MatStoreValues(mat); 2809 $ loop over nonlinear iterations 2810 $ ierr = MatRetrieveValues(mat); 2811 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 2812 $ // call MatAssemblyBegin/End() on matrix 2813 $ Solve linear system with Jacobian 2814 $ endloop 2815 2816 Notes: 2817 Matrix must already be assemblied before calling this routine 2818 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 2819 calling this routine. 2820 2821 When this is called multiple times it overwrites the previous set of stored values 2822 and does not allocated additional space. 2823 2824 .seealso: MatRetrieveValues() 2825 2826 @*/ 2827 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues(Mat mat) 2828 { 2829 PetscErrorCode ierr,(*f)(Mat); 2830 2831 PetscFunctionBegin; 2832 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2833 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 2834 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2835 2836 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatStoreValues_C",(void (**)(void))&f);CHKERRQ(ierr); 2837 if (f) { 2838 ierr = (*f)(mat);CHKERRQ(ierr); 2839 } else { 2840 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to store values"); 2841 } 2842 PetscFunctionReturn(0); 2843 } 2844 2845 EXTERN_C_BEGIN 2846 #undef __FUNCT__ 2847 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 2848 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_SeqAIJ(Mat mat) 2849 { 2850 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2851 PetscErrorCode ierr; 2852 PetscInt nz = aij->i[mat->rmap->n]; 2853 2854 PetscFunctionBegin; 2855 if (aij->nonew != 1) { 2856 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2857 } 2858 if (!aij->saved_values) { 2859 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 2860 } 2861 /* copy values over */ 2862 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2863 PetscFunctionReturn(0); 2864 } 2865 EXTERN_C_END 2866 2867 #undef __FUNCT__ 2868 #define __FUNCT__ "MatRetrieveValues" 2869 /*@ 2870 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 2871 example, reuse of the linear part of a Jacobian, while recomputing the 2872 nonlinear portion. 2873 2874 Collect on Mat 2875 2876 Input Parameters: 2877 . mat - the matrix (currently on AIJ matrices support this option) 2878 2879 Level: advanced 2880 2881 .seealso: MatStoreValues() 2882 2883 @*/ 2884 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues(Mat mat) 2885 { 2886 PetscErrorCode ierr,(*f)(Mat); 2887 2888 PetscFunctionBegin; 2889 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2890 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 2891 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2892 2893 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatRetrieveValues_C",(void (**)(void))&f);CHKERRQ(ierr); 2894 if (f) { 2895 ierr = (*f)(mat);CHKERRQ(ierr); 2896 } else { 2897 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to retrieve values"); 2898 } 2899 PetscFunctionReturn(0); 2900 } 2901 2902 2903 /* --------------------------------------------------------------------------------*/ 2904 #undef __FUNCT__ 2905 #define __FUNCT__ "MatCreateSeqAIJ" 2906 /*@C 2907 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 2908 (the default parallel PETSc format). For good matrix assembly performance 2909 the user should preallocate the matrix storage by setting the parameter nz 2910 (or the array nnz). By setting these parameters accurately, performance 2911 during matrix assembly can be increased by more than a factor of 50. 2912 2913 Collective on MPI_Comm 2914 2915 Input Parameters: 2916 + comm - MPI communicator, set to PETSC_COMM_SELF 2917 . m - number of rows 2918 . n - number of columns 2919 . nz - number of nonzeros per row (same for all rows) 2920 - nnz - array containing the number of nonzeros in the various rows 2921 (possibly different for each row) or PETSC_NULL 2922 2923 Output Parameter: 2924 . A - the matrix 2925 2926 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2927 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2928 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2929 2930 Notes: 2931 If nnz is given then nz is ignored 2932 2933 The AIJ format (also called the Yale sparse matrix format or 2934 compressed row storage), is fully compatible with standard Fortran 77 2935 storage. That is, the stored row and column indices can begin at 2936 either one (as in Fortran) or zero. See the users' manual for details. 2937 2938 Specify the preallocated storage with either nz or nnz (not both). 2939 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2940 allocation. For large problems you MUST preallocate memory or you 2941 will get TERRIBLE performance, see the users' manual chapter on matrices. 2942 2943 By default, this format uses inodes (identical nodes) when possible, to 2944 improve numerical efficiency of matrix-vector products and solves. We 2945 search for consecutive rows with the same nonzero structure, thereby 2946 reusing matrix information to achieve increased efficiency. 2947 2948 Options Database Keys: 2949 + -mat_no_inode - Do not use inodes 2950 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 2951 2952 Level: intermediate 2953 2954 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 2955 2956 @*/ 2957 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 2958 { 2959 PetscErrorCode ierr; 2960 2961 PetscFunctionBegin; 2962 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2963 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2964 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 2965 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 2966 PetscFunctionReturn(0); 2967 } 2968 2969 #undef __FUNCT__ 2970 #define __FUNCT__ "MatSeqAIJSetPreallocation" 2971 /*@C 2972 MatSeqAIJSetPreallocation - For good matrix assembly performance 2973 the user should preallocate the matrix storage by setting the parameter nz 2974 (or the array nnz). By setting these parameters accurately, performance 2975 during matrix assembly can be increased by more than a factor of 50. 2976 2977 Collective on MPI_Comm 2978 2979 Input Parameters: 2980 + B - The matrix-free 2981 . nz - number of nonzeros per row (same for all rows) 2982 - nnz - array containing the number of nonzeros in the various rows 2983 (possibly different for each row) or PETSC_NULL 2984 2985 Notes: 2986 If nnz is given then nz is ignored 2987 2988 The AIJ format (also called the Yale sparse matrix format or 2989 compressed row storage), is fully compatible with standard Fortran 77 2990 storage. That is, the stored row and column indices can begin at 2991 either one (as in Fortran) or zero. See the users' manual for details. 2992 2993 Specify the preallocated storage with either nz or nnz (not both). 2994 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2995 allocation. For large problems you MUST preallocate memory or you 2996 will get TERRIBLE performance, see the users' manual chapter on matrices. 2997 2998 You can call MatGetInfo() to get information on how effective the preallocation was; 2999 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3000 You can also run with the option -info and look for messages with the string 3001 malloc in them to see if additional memory allocation was needed. 3002 3003 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3004 entries or columns indices 3005 3006 By default, this format uses inodes (identical nodes) when possible, to 3007 improve numerical efficiency of matrix-vector products and solves. We 3008 search for consecutive rows with the same nonzero structure, thereby 3009 reusing matrix information to achieve increased efficiency. 3010 3011 Options Database Keys: 3012 + -mat_no_inode - Do not use inodes 3013 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3014 - -mat_aij_oneindex - Internally use indexing starting at 1 3015 rather than 0. Note that when calling MatSetValues(), 3016 the user still MUST index entries starting at 0! 3017 3018 Level: intermediate 3019 3020 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3021 3022 @*/ 3023 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3024 { 3025 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[]); 3026 3027 PetscFunctionBegin; 3028 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3029 if (f) { 3030 ierr = (*f)(B,nz,nnz);CHKERRQ(ierr); 3031 } 3032 PetscFunctionReturn(0); 3033 } 3034 3035 EXTERN_C_BEGIN 3036 #undef __FUNCT__ 3037 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3038 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3039 { 3040 Mat_SeqAIJ *b; 3041 PetscTruth skipallocation = PETSC_FALSE; 3042 PetscErrorCode ierr; 3043 PetscInt i; 3044 3045 PetscFunctionBegin; 3046 3047 if (nz == MAT_SKIP_ALLOCATION) { 3048 skipallocation = PETSC_TRUE; 3049 nz = 0; 3050 } 3051 3052 ierr = PetscLayoutSetBlockSize(B->rmap,1);CHKERRQ(ierr); 3053 ierr = PetscLayoutSetBlockSize(B->cmap,1);CHKERRQ(ierr); 3054 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3055 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3056 3057 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3058 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3059 if (nnz) { 3060 for (i=0; i<B->rmap->n; i++) { 3061 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]); 3062 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); 3063 } 3064 } 3065 3066 B->preallocated = PETSC_TRUE; 3067 b = (Mat_SeqAIJ*)B->data; 3068 3069 if (!skipallocation) { 3070 if (!b->imax) { 3071 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3072 ierr = PetscLogObjectMemory(B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3073 } 3074 if (!nnz) { 3075 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3076 else if (nz < 0) nz = 1; 3077 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3078 nz = nz*B->rmap->n; 3079 } else { 3080 nz = 0; 3081 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3082 } 3083 /* b->ilen will count nonzeros in each row so far. */ 3084 for (i=0; i<B->rmap->n; i++) { b->ilen[i] = 0; } 3085 3086 /* allocate the matrix space */ 3087 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3088 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3089 ierr = PetscLogObjectMemory(B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3090 b->i[0] = 0; 3091 for (i=1; i<B->rmap->n+1; i++) { 3092 b->i[i] = b->i[i-1] + b->imax[i-1]; 3093 } 3094 b->singlemalloc = PETSC_TRUE; 3095 b->free_a = PETSC_TRUE; 3096 b->free_ij = PETSC_TRUE; 3097 } else { 3098 b->free_a = PETSC_FALSE; 3099 b->free_ij = PETSC_FALSE; 3100 } 3101 3102 b->nz = 0; 3103 b->maxnz = nz; 3104 B->info.nz_unneeded = (double)b->maxnz; 3105 PetscFunctionReturn(0); 3106 } 3107 EXTERN_C_END 3108 3109 #undef __FUNCT__ 3110 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3111 /*@ 3112 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3113 3114 Input Parameters: 3115 + B - the matrix 3116 . i - the indices into j for the start of each row (starts with zero) 3117 . j - the column indices for each row (starts with zero) these must be sorted for each row 3118 - v - optional values in the matrix 3119 3120 Level: developer 3121 3122 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3123 3124 .keywords: matrix, aij, compressed row, sparse, sequential 3125 3126 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3127 @*/ 3128 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3129 { 3130 PetscErrorCode (*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3131 PetscErrorCode ierr; 3132 3133 PetscFunctionBegin; 3134 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3135 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3136 if (f) { 3137 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3138 } 3139 PetscFunctionReturn(0); 3140 } 3141 3142 EXTERN_C_BEGIN 3143 #undef __FUNCT__ 3144 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3145 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3146 { 3147 PetscInt i; 3148 PetscInt m,n; 3149 PetscInt nz; 3150 PetscInt *nnz, nz_max = 0; 3151 PetscScalar *values; 3152 PetscErrorCode ierr; 3153 3154 PetscFunctionBegin; 3155 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3156 3157 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3158 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 3159 for(i = 0; i < m; i++) { 3160 nz = Ii[i+1]- Ii[i]; 3161 nz_max = PetscMax(nz_max, nz); 3162 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3163 nnz[i] = nz; 3164 } 3165 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3166 ierr = PetscFree(nnz);CHKERRQ(ierr); 3167 3168 if (v) { 3169 values = (PetscScalar*) v; 3170 } else { 3171 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 3172 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3173 } 3174 3175 for(i = 0; i < m; i++) { 3176 nz = Ii[i+1] - Ii[i]; 3177 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3178 } 3179 3180 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3181 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3182 3183 if (!v) { 3184 ierr = PetscFree(values);CHKERRQ(ierr); 3185 } 3186 PetscFunctionReturn(0); 3187 } 3188 EXTERN_C_END 3189 3190 #include "../src/mat/impls/dense/seq/dense.h" 3191 #include "private/petscaxpy.h" 3192 3193 #undef __FUNCT__ 3194 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3195 /* 3196 Computes (B'*A')' since computing B*A directly is untenable 3197 3198 n p p 3199 ( ) ( ) ( ) 3200 m ( A ) * n ( B ) = m ( C ) 3201 ( ) ( ) ( ) 3202 3203 */ 3204 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3205 { 3206 PetscErrorCode ierr; 3207 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3208 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3209 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3210 PetscInt i,n,m,q,p; 3211 const PetscInt *ii,*idx; 3212 const PetscScalar *b,*a,*a_q; 3213 PetscScalar *c,*c_q; 3214 3215 PetscFunctionBegin; 3216 m = A->rmap->n; 3217 n = A->cmap->n; 3218 p = B->cmap->n; 3219 a = sub_a->v; 3220 b = sub_b->a; 3221 c = sub_c->v; 3222 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3223 3224 ii = sub_b->i; 3225 idx = sub_b->j; 3226 for (i=0; i<n; i++) { 3227 q = ii[i+1] - ii[i]; 3228 while (q-->0) { 3229 c_q = c + m*(*idx); 3230 a_q = a + m*i; 3231 PetscAXPY(c_q,*b,a_q,m); 3232 idx++; 3233 b++; 3234 } 3235 } 3236 PetscFunctionReturn(0); 3237 } 3238 3239 #undef __FUNCT__ 3240 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 3241 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3242 { 3243 PetscErrorCode ierr; 3244 PetscInt m=A->rmap->n,n=B->cmap->n; 3245 Mat Cmat; 3246 3247 PetscFunctionBegin; 3248 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); 3249 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 3250 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3251 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3252 ierr = MatSeqDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 3253 Cmat->assembled = PETSC_TRUE; 3254 *C = Cmat; 3255 PetscFunctionReturn(0); 3256 } 3257 3258 /* ----------------------------------------------------------------*/ 3259 #undef __FUNCT__ 3260 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 3261 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3262 { 3263 PetscErrorCode ierr; 3264 3265 PetscFunctionBegin; 3266 if (scall == MAT_INITIAL_MATRIX){ 3267 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3268 } 3269 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3270 PetscFunctionReturn(0); 3271 } 3272 3273 3274 /*MC 3275 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3276 based on compressed sparse row format. 3277 3278 Options Database Keys: 3279 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3280 3281 Level: beginner 3282 3283 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3284 M*/ 3285 3286 EXTERN_C_BEGIN 3287 #if defined(PETSC_HAVE_PASTIX) 3288 extern PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 3289 #endif 3290 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SCALAR_SINGLE) && !defined(PETSC_USE_SCALAR_MAT_SINGLE) 3291 extern PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat *); 3292 #endif 3293 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3294 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 3295 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 3296 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscTruth *); 3297 #if defined(PETSC_HAVE_MUMPS) 3298 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 3299 #endif 3300 #if defined(PETSC_HAVE_SUPERLU) 3301 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 3302 #endif 3303 #if defined(PETSC_HAVE_SUPERLU_DIST) 3304 extern PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 3305 #endif 3306 #if defined(PETSC_HAVE_SPOOLES) 3307 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_spooles(Mat,MatFactorType,Mat*); 3308 #endif 3309 #if defined(PETSC_HAVE_UMFPACK) 3310 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 3311 #endif 3312 #if defined(PETSC_HAVE_CHOLMOD) 3313 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 3314 #endif 3315 #if defined(PETSC_HAVE_LUSOL) 3316 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 3317 #endif 3318 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3319 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 3320 extern PetscErrorCode PETSCMAT_DLLEXPORT MatlabEnginePut_SeqAIJ(PetscObject,void*); 3321 extern PetscErrorCode PETSCMAT_DLLEXPORT MatlabEngineGet_SeqAIJ(PetscObject,void*); 3322 #endif 3323 EXTERN_C_END 3324 3325 3326 EXTERN_C_BEGIN 3327 #undef __FUNCT__ 3328 #define __FUNCT__ "MatCreate_SeqAIJ" 3329 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SeqAIJ(Mat B) 3330 { 3331 Mat_SeqAIJ *b; 3332 PetscErrorCode ierr; 3333 PetscMPIInt size; 3334 3335 PetscFunctionBegin; 3336 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 3337 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3338 3339 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 3340 B->data = (void*)b; 3341 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3342 B->mapping = 0; 3343 b->row = 0; 3344 b->col = 0; 3345 b->icol = 0; 3346 b->reallocs = 0; 3347 b->ignorezeroentries = PETSC_FALSE; 3348 b->roworiented = PETSC_TRUE; 3349 b->nonew = 0; 3350 b->diag = 0; 3351 b->solve_work = 0; 3352 B->spptr = 0; 3353 b->saved_values = 0; 3354 b->idiag = 0; 3355 b->mdiag = 0; 3356 b->ssor_work = 0; 3357 b->omega = 1.0; 3358 b->fshift = 0.0; 3359 b->idiagvalid = PETSC_FALSE; 3360 b->keepnonzeropattern = PETSC_FALSE; 3361 b->xtoy = 0; 3362 b->XtoY = 0; 3363 b->compressedrow.use = PETSC_FALSE; 3364 b->compressedrow.nrows = B->rmap->n; 3365 b->compressedrow.i = PETSC_NULL; 3366 b->compressedrow.rindex = PETSC_NULL; 3367 b->compressedrow.checked = PETSC_FALSE; 3368 B->same_nonzero = PETSC_FALSE; 3369 3370 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3371 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3372 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_matlab_C", 3373 "MatGetFactor_seqaij_matlab", 3374 MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 3375 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"PetscMatlabEnginePut_C","MatlabEnginePut_SeqAIJ",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 3376 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"PetscMatlabEngineGet_C","MatlabEngineGet_SeqAIJ",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 3377 #endif 3378 #if defined(PETSC_HAVE_PASTIX) 3379 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C", 3380 "MatGetFactor_seqaij_pastix", 3381 MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 3382 #endif 3383 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SCALAR_SINGLE) && !defined(PETSC_USE_SCALAR_MAT_SINGLE) 3384 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_essl_C", 3385 "MatGetFactor_seqaij_essl", 3386 MatGetFactor_seqaij_essl);CHKERRQ(ierr); 3387 #endif 3388 #if defined(PETSC_HAVE_SUPERLU) 3389 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_C", 3390 "MatGetFactor_seqaij_superlu", 3391 MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 3392 #endif 3393 #if defined(PETSC_HAVE_SUPERLU_DIST) 3394 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_dist_C", 3395 "MatGetFactor_seqaij_superlu_dist", 3396 MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 3397 #endif 3398 #if defined(PETSC_HAVE_SPOOLES) 3399 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_spooles_C", 3400 "MatGetFactor_seqaij_spooles", 3401 MatGetFactor_seqaij_spooles);CHKERRQ(ierr); 3402 #endif 3403 #if defined(PETSC_HAVE_MUMPS) 3404 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", 3405 "MatGetFactor_aij_mumps", 3406 MatGetFactor_aij_mumps);CHKERRQ(ierr); 3407 #endif 3408 #if defined(PETSC_HAVE_UMFPACK) 3409 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_umfpack_C", 3410 "MatGetFactor_seqaij_umfpack", 3411 MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 3412 #endif 3413 #if defined(PETSC_HAVE_CHOLMOD) 3414 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_cholmod_C", 3415 "MatGetFactor_seqaij_cholmod", 3416 MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 3417 #endif 3418 #if defined(PETSC_HAVE_LUSOL) 3419 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_lusol_C", 3420 "MatGetFactor_seqaij_lusol", 3421 MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 3422 #endif 3423 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_petsc_C", 3424 "MatGetFactor_seqaij_petsc", 3425 MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 3426 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactorAvailable_petsc_C", 3427 "MatGetFactorAvailable_seqaij_petsc", 3428 MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 3429 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_bas_C", 3430 "MatGetFactor_seqaij_bas", 3431 MatGetFactor_seqaij_bas); 3432 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetColumnIndices_C", 3433 "MatSeqAIJSetColumnIndices_SeqAIJ", 3434 MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 3435 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 3436 "MatStoreValues_SeqAIJ", 3437 MatStoreValues_SeqAIJ);CHKERRQ(ierr); 3438 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 3439 "MatRetrieveValues_SeqAIJ", 3440 MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 3441 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqsbaij_C", 3442 "MatConvert_SeqAIJ_SeqSBAIJ", 3443 MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 3444 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqbaij_C", 3445 "MatConvert_SeqAIJ_SeqBAIJ", 3446 MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 3447 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqaijperm_C", 3448 "MatConvert_SeqAIJ_SeqAIJPERM", 3449 MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 3450 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C", 3451 "MatConvert_SeqAIJ_SeqAIJCRL", 3452 MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 3453 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 3454 "MatIsTranspose_SeqAIJ", 3455 MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3456 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsHermitianTranspose_C", 3457 "MatIsHermitianTranspose_SeqAIJ", 3458 MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3459 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetPreallocation_C", 3460 "MatSeqAIJSetPreallocation_SeqAIJ", 3461 MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 3462 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C", 3463 "MatSeqAIJSetPreallocationCSR_SeqAIJ", 3464 MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 3465 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatReorderForNonzeroDiagonal_C", 3466 "MatReorderForNonzeroDiagonal_SeqAIJ", 3467 MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 3468 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_seqdense_seqaij_C", 3469 "MatMatMult_SeqDense_SeqAIJ", 3470 MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 3471 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C", 3472 "MatMatMultSymbolic_SeqDense_SeqAIJ", 3473 MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 3474 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C", 3475 "MatMatMultNumeric_SeqDense_SeqAIJ", 3476 MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 3477 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 3478 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3479 PetscFunctionReturn(0); 3480 } 3481 EXTERN_C_END 3482 3483 #undef __FUNCT__ 3484 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 3485 /* 3486 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 3487 */ 3488 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscTruth mallocmatspace) 3489 { 3490 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 3491 PetscErrorCode ierr; 3492 PetscInt i,m = A->rmap->n; 3493 3494 PetscFunctionBegin; 3495 c = (Mat_SeqAIJ*)C->data; 3496 3497 C->factortype = A->factortype; 3498 c->row = 0; 3499 c->col = 0; 3500 c->icol = 0; 3501 c->reallocs = 0; 3502 3503 C->assembled = PETSC_TRUE; 3504 3505 ierr = PetscLayoutSetBlockSize(C->rmap,1);CHKERRQ(ierr); 3506 ierr = PetscLayoutSetBlockSize(C->cmap,1);CHKERRQ(ierr); 3507 ierr = PetscLayoutSetUp(C->rmap);CHKERRQ(ierr); 3508 ierr = PetscLayoutSetUp(C->cmap);CHKERRQ(ierr); 3509 3510 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 3511 ierr = PetscLogObjectMemory(C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 3512 for (i=0; i<m; i++) { 3513 c->imax[i] = a->imax[i]; 3514 c->ilen[i] = a->ilen[i]; 3515 } 3516 3517 /* allocate the matrix space */ 3518 if (mallocmatspace){ 3519 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 3520 ierr = PetscLogObjectMemory(C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3521 c->singlemalloc = PETSC_TRUE; 3522 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3523 if (m > 0) { 3524 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 3525 if (cpvalues == MAT_COPY_VALUES) { 3526 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 3527 } else { 3528 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 3529 } 3530 } 3531 } 3532 3533 c->ignorezeroentries = a->ignorezeroentries; 3534 c->roworiented = a->roworiented; 3535 c->nonew = a->nonew; 3536 if (a->diag) { 3537 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 3538 ierr = PetscLogObjectMemory(C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3539 for (i=0; i<m; i++) { 3540 c->diag[i] = a->diag[i]; 3541 } 3542 } else c->diag = 0; 3543 c->solve_work = 0; 3544 c->saved_values = 0; 3545 c->idiag = 0; 3546 c->ssor_work = 0; 3547 c->keepnonzeropattern = a->keepnonzeropattern; 3548 c->free_a = PETSC_TRUE; 3549 c->free_ij = PETSC_TRUE; 3550 c->xtoy = 0; 3551 c->XtoY = 0; 3552 3553 c->nz = a->nz; 3554 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 3555 C->preallocated = PETSC_TRUE; 3556 3557 c->compressedrow.use = a->compressedrow.use; 3558 c->compressedrow.nrows = a->compressedrow.nrows; 3559 c->compressedrow.checked = a->compressedrow.checked; 3560 if (a->compressedrow.checked && a->compressedrow.use){ 3561 i = a->compressedrow.nrows; 3562 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 3563 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3564 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 3565 } else { 3566 c->compressedrow.use = PETSC_FALSE; 3567 c->compressedrow.i = PETSC_NULL; 3568 c->compressedrow.rindex = PETSC_NULL; 3569 } 3570 C->same_nonzero = A->same_nonzero; 3571 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 3572 3573 ierr = PetscFListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 3574 PetscFunctionReturn(0); 3575 } 3576 3577 #undef __FUNCT__ 3578 #define __FUNCT__ "MatDuplicate_SeqAIJ" 3579 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 3580 { 3581 PetscErrorCode ierr; 3582 3583 PetscFunctionBegin; 3584 ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr); 3585 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 3586 ierr = MatSetType(*B,MATSEQAIJ);CHKERRQ(ierr); 3587 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 3588 PetscFunctionReturn(0); 3589 } 3590 3591 #undef __FUNCT__ 3592 #define __FUNCT__ "MatLoad_SeqAIJ" 3593 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 3594 { 3595 Mat_SeqAIJ *a; 3596 PetscErrorCode ierr; 3597 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 3598 int fd; 3599 PetscMPIInt size; 3600 MPI_Comm comm; 3601 3602 PetscFunctionBegin; 3603 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3604 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3605 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 3606 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3607 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 3608 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 3609 M = header[1]; N = header[2]; nz = header[3]; 3610 3611 if (nz < 0) { 3612 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 3613 } 3614 3615 /* read in row lengths */ 3616 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3617 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 3618 3619 /* check if sum of rowlengths is same as nz */ 3620 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 3621 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); 3622 3623 /* set global size if not set already*/ 3624 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 3625 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 3626 } else { 3627 /* if sizes and type are already set, check if the vector global sizes are correct */ 3628 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 3629 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); 3630 } 3631 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 3632 a = (Mat_SeqAIJ*)newMat->data; 3633 3634 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 3635 3636 /* read in nonzero values */ 3637 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 3638 3639 /* set matrix "i" values */ 3640 a->i[0] = 0; 3641 for (i=1; i<= M; i++) { 3642 a->i[i] = a->i[i-1] + rowlengths[i-1]; 3643 a->ilen[i-1] = rowlengths[i-1]; 3644 } 3645 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3646 3647 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3648 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3649 PetscFunctionReturn(0); 3650 } 3651 3652 #undef __FUNCT__ 3653 #define __FUNCT__ "MatEqual_SeqAIJ" 3654 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscTruth* flg) 3655 { 3656 Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data,*b = (Mat_SeqAIJ *)B->data; 3657 PetscErrorCode ierr; 3658 #if defined(PETSC_USE_COMPLEX) 3659 PetscInt k; 3660 #endif 3661 3662 PetscFunctionBegin; 3663 /* If the matrix dimensions are not equal,or no of nonzeros */ 3664 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 3665 *flg = PETSC_FALSE; 3666 PetscFunctionReturn(0); 3667 } 3668 3669 /* if the a->i are the same */ 3670 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 3671 if (!*flg) PetscFunctionReturn(0); 3672 3673 /* if a->j are the same */ 3674 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 3675 if (!*flg) PetscFunctionReturn(0); 3676 3677 /* if a->a are the same */ 3678 #if defined(PETSC_USE_COMPLEX) 3679 for (k=0; k<a->nz; k++){ 3680 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])){ 3681 *flg = PETSC_FALSE; 3682 PetscFunctionReturn(0); 3683 } 3684 } 3685 #else 3686 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 3687 #endif 3688 PetscFunctionReturn(0); 3689 } 3690 3691 #undef __FUNCT__ 3692 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 3693 /*@ 3694 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 3695 provided by the user. 3696 3697 Collective on MPI_Comm 3698 3699 Input Parameters: 3700 + comm - must be an MPI communicator of size 1 3701 . m - number of rows 3702 . n - number of columns 3703 . i - row indices 3704 . j - column indices 3705 - a - matrix values 3706 3707 Output Parameter: 3708 . mat - the matrix 3709 3710 Level: intermediate 3711 3712 Notes: 3713 The i, j, and a arrays are not copied by this routine, the user must free these arrays 3714 once the matrix is destroyed 3715 3716 You cannot set new nonzero locations into this matrix, that will generate an error. 3717 3718 The i and j indices are 0 based 3719 3720 The format which is used for the sparse matrix input, is equivalent to a 3721 row-major ordering.. i.e for the following matrix, the input data expected is 3722 as shown: 3723 3724 1 0 0 3725 2 0 3 3726 4 5 6 3727 3728 i = {0,1,3,6} [size = nrow+1 = 3+1] 3729 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 3730 v = {1,2,3,4,5,6} [size = nz = 6] 3731 3732 3733 .seealso: MatCreate(), MatCreateMPIAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 3734 3735 @*/ 3736 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt* i,PetscInt*j,PetscScalar *a,Mat *mat) 3737 { 3738 PetscErrorCode ierr; 3739 PetscInt ii; 3740 Mat_SeqAIJ *aij; 3741 #if defined(PETSC_USE_DEBUG) 3742 PetscInt jj; 3743 #endif 3744 3745 PetscFunctionBegin; 3746 if (i[0]) { 3747 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3748 } 3749 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3750 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 3751 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 3752 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 3753 aij = (Mat_SeqAIJ*)(*mat)->data; 3754 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 3755 3756 aij->i = i; 3757 aij->j = j; 3758 aij->a = a; 3759 aij->singlemalloc = PETSC_FALSE; 3760 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 3761 aij->free_a = PETSC_FALSE; 3762 aij->free_ij = PETSC_FALSE; 3763 3764 for (ii=0; ii<m; ii++) { 3765 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 3766 #if defined(PETSC_USE_DEBUG) 3767 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]); 3768 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 3769 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); 3770 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); 3771 } 3772 #endif 3773 } 3774 #if defined(PETSC_USE_DEBUG) 3775 for (ii=0; ii<aij->i[m]; ii++) { 3776 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 3777 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]); 3778 } 3779 #endif 3780 3781 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3782 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3783 PetscFunctionReturn(0); 3784 } 3785 3786 #undef __FUNCT__ 3787 #define __FUNCT__ "MatSetColoring_SeqAIJ" 3788 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 3789 { 3790 PetscErrorCode ierr; 3791 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3792 3793 PetscFunctionBegin; 3794 if (coloring->ctype == IS_COLORING_GLOBAL) { 3795 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 3796 a->coloring = coloring; 3797 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3798 PetscInt i,*larray; 3799 ISColoring ocoloring; 3800 ISColoringValue *colors; 3801 3802 /* set coloring for diagonal portion */ 3803 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3804 for (i=0; i<A->cmap->n; i++) { 3805 larray[i] = i; 3806 } 3807 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3808 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3809 for (i=0; i<A->cmap->n; i++) { 3810 colors[i] = coloring->colors[larray[i]]; 3811 } 3812 ierr = PetscFree(larray);CHKERRQ(ierr); 3813 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3814 a->coloring = ocoloring; 3815 } 3816 PetscFunctionReturn(0); 3817 } 3818 3819 #if defined(PETSC_HAVE_ADIC) 3820 EXTERN_C_BEGIN 3821 #include "adic/ad_utils.h" 3822 EXTERN_C_END 3823 3824 #undef __FUNCT__ 3825 #define __FUNCT__ "MatSetValuesAdic_SeqAIJ" 3826 PetscErrorCode MatSetValuesAdic_SeqAIJ(Mat A,void *advalues) 3827 { 3828 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3829 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j,nlen; 3830 PetscScalar *v = a->a,*values = ((PetscScalar*)advalues)+1; 3831 ISColoringValue *color; 3832 3833 PetscFunctionBegin; 3834 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 3835 nlen = PetscADGetDerivTypeSize()/sizeof(PetscScalar); 3836 color = a->coloring->colors; 3837 /* loop over rows */ 3838 for (i=0; i<m; i++) { 3839 nz = ii[i+1] - ii[i]; 3840 /* loop over columns putting computed value into matrix */ 3841 for (j=0; j<nz; j++) { 3842 *v++ = values[color[*jj++]]; 3843 } 3844 values += nlen; /* jump to next row of derivatives */ 3845 } 3846 PetscFunctionReturn(0); 3847 } 3848 #endif 3849 3850 #undef __FUNCT__ 3851 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 3852 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 3853 { 3854 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3855 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 3856 MatScalar *v = a->a; 3857 PetscScalar *values = (PetscScalar *)advalues; 3858 ISColoringValue *color; 3859 3860 PetscFunctionBegin; 3861 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 3862 color = a->coloring->colors; 3863 /* loop over rows */ 3864 for (i=0; i<m; i++) { 3865 nz = ii[i+1] - ii[i]; 3866 /* loop over columns putting computed value into matrix */ 3867 for (j=0; j<nz; j++) { 3868 *v++ = values[color[*jj++]]; 3869 } 3870 values += nl; /* jump to next row of derivatives */ 3871 } 3872 PetscFunctionReturn(0); 3873 } 3874 3875 /* 3876 Special version for direct calls from Fortran 3877 */ 3878 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3879 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 3880 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3881 #define matsetvaluesseqaij_ matsetvaluesseqaij 3882 #endif 3883 3884 /* Change these macros so can be used in void function */ 3885 #undef CHKERRQ 3886 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)A)->comm,ierr) 3887 #undef SETERRQ2 3888 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 3889 3890 EXTERN_C_BEGIN 3891 #undef __FUNCT__ 3892 #define __FUNCT__ "matsetvaluesseqaij_" 3893 void PETSC_STDCALL matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 3894 { 3895 Mat A = *AA; 3896 PetscInt m = *mm, n = *nn; 3897 InsertMode is = *isis; 3898 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3899 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 3900 PetscInt *imax,*ai,*ailen; 3901 PetscErrorCode ierr; 3902 PetscInt *aj,nonew = a->nonew,lastcol = -1; 3903 MatScalar *ap,value,*aa; 3904 PetscTruth ignorezeroentries = a->ignorezeroentries; 3905 PetscTruth roworiented = a->roworiented; 3906 3907 PetscFunctionBegin; 3908 ierr = MatPreallocated(A);CHKERRQ(ierr); 3909 imax = a->imax; 3910 ai = a->i; 3911 ailen = a->ilen; 3912 aj = a->j; 3913 aa = a->a; 3914 3915 for (k=0; k<m; k++) { /* loop over added rows */ 3916 row = im[k]; 3917 if (row < 0) continue; 3918 #if defined(PETSC_USE_DEBUG) 3919 if (row >= A->rmap->n) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 3920 #endif 3921 rp = aj + ai[row]; ap = aa + ai[row]; 3922 rmax = imax[row]; nrow = ailen[row]; 3923 low = 0; 3924 high = nrow; 3925 for (l=0; l<n; l++) { /* loop over added columns */ 3926 if (in[l] < 0) continue; 3927 #if defined(PETSC_USE_DEBUG) 3928 if (in[l] >= A->cmap->n) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 3929 #endif 3930 col = in[l]; 3931 if (roworiented) { 3932 value = v[l + k*n]; 3933 } else { 3934 value = v[k + l*m]; 3935 } 3936 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 3937 3938 if (col <= lastcol) low = 0; else high = nrow; 3939 lastcol = col; 3940 while (high-low > 5) { 3941 t = (low+high)/2; 3942 if (rp[t] > col) high = t; 3943 else low = t; 3944 } 3945 for (i=low; i<high; i++) { 3946 if (rp[i] > col) break; 3947 if (rp[i] == col) { 3948 if (is == ADD_VALUES) ap[i] += value; 3949 else ap[i] = value; 3950 goto noinsert; 3951 } 3952 } 3953 if (value == 0.0 && ignorezeroentries) goto noinsert; 3954 if (nonew == 1) goto noinsert; 3955 if (nonew == -1) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 3956 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 3957 N = nrow++ - 1; a->nz++; high++; 3958 /* shift up all the later entries in this row */ 3959 for (ii=N; ii>=i; ii--) { 3960 rp[ii+1] = rp[ii]; 3961 ap[ii+1] = ap[ii]; 3962 } 3963 rp[i] = col; 3964 ap[i] = value; 3965 noinsert:; 3966 low = i + 1; 3967 } 3968 ailen[row] = nrow; 3969 } 3970 A->same_nonzero = PETSC_FALSE; 3971 PetscFunctionReturnVoid(); 3972 } 3973 EXTERN_C_END 3974