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,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 PetscInt j,k,nzx = xi[i+1] - xi[i],nzy = yi[i+1] - yi[i]; 2307 const PetscInt *xj = x->j+xi[i],*yj = y->j+yi[i]; 2308 nnz[i] = 0; 2309 for (j=0,k=0; j<nzx; j++) { /* Point in X */ 2310 for (; k<nzy && yj[k]<xj[j]; k++) nnz[i]++; /* Catch up to X */ 2311 if (k<nzy && yj[k]==xj[j]) k++; /* Skip duplicate */ 2312 nnz[i]++; 2313 } 2314 for (; k<nzy; k++) nnz[i]++; 2315 } 2316 /* Preallocate matrix */ 2317 ierr = MatSeqAIJSetPreallocation(B,PETSC_NULL,nnz);CHKERRQ(ierr); 2318 2319 ierr = PetscFree(nnz);CHKERRQ(ierr); 2320 PetscFunctionReturn(0); 2321 } 2322 2323 #undef __FUNCT__ 2324 #define __FUNCT__ "MatAXPY_SeqAIJ" 2325 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2326 { 2327 PetscErrorCode ierr; 2328 PetscInt i; 2329 Mat_SeqAIJ *x = (Mat_SeqAIJ *)X->data,*y = (Mat_SeqAIJ *)Y->data; 2330 PetscBLASInt one=1,bnz = PetscBLASIntCast(x->nz); 2331 Mat B; 2332 2333 PetscFunctionBegin; 2334 if (str == SAME_NONZERO_PATTERN) { 2335 PetscScalar alpha = a; 2336 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 2337 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2338 if (y->xtoy && y->XtoY != X) { 2339 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2340 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 2341 } 2342 if (!y->xtoy) { /* get xtoy */ 2343 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);CHKERRQ(ierr); 2344 y->XtoY = X; 2345 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2346 } 2347 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2348 ierr = PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %d/%d = %G\n",x->nz,y->nz,(PetscReal)(x->nz)/y->nz);CHKERRQ(ierr); 2349 } else { 2350 ierr = MatCreate(((PetscObject)Y)->comm,&B);CHKERRQ(ierr); 2351 ierr = MatSetSizes(B,Y->rmap->n,Y->rmap->N,Y->cmap->n,Y->cmap->N);CHKERRQ(ierr); 2352 ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); 2353 ierr = MatAXPYSetPreallocation_SeqAIJ(B,Y,X);CHKERRQ(ierr); 2354 ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); 2355 ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); 2356 } 2357 PetscFunctionReturn(0); 2358 } 2359 2360 #undef __FUNCT__ 2361 #define __FUNCT__ "MatSetBlockSize_SeqAIJ" 2362 PetscErrorCode MatSetBlockSize_SeqAIJ(Mat A,PetscInt bs) 2363 { 2364 PetscErrorCode ierr; 2365 2366 PetscFunctionBegin; 2367 ierr = PetscLayoutSetBlockSize(A->rmap,bs);CHKERRQ(ierr); 2368 ierr = PetscLayoutSetBlockSize(A->cmap,bs);CHKERRQ(ierr); 2369 PetscFunctionReturn(0); 2370 } 2371 2372 #undef __FUNCT__ 2373 #define __FUNCT__ "MatConjugate_SeqAIJ" 2374 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat mat) 2375 { 2376 #if defined(PETSC_USE_COMPLEX) 2377 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2378 PetscInt i,nz; 2379 PetscScalar *a; 2380 2381 PetscFunctionBegin; 2382 nz = aij->nz; 2383 a = aij->a; 2384 for (i=0; i<nz; i++) { 2385 a[i] = PetscConj(a[i]); 2386 } 2387 #else 2388 PetscFunctionBegin; 2389 #endif 2390 PetscFunctionReturn(0); 2391 } 2392 2393 #undef __FUNCT__ 2394 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 2395 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2396 { 2397 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2398 PetscErrorCode ierr; 2399 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2400 PetscReal atmp; 2401 PetscScalar *x; 2402 MatScalar *aa; 2403 2404 PetscFunctionBegin; 2405 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2406 aa = a->a; 2407 ai = a->i; 2408 aj = a->j; 2409 2410 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2411 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2412 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2413 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2414 for (i=0; i<m; i++) { 2415 ncols = ai[1] - ai[0]; ai++; 2416 x[i] = 0.0; 2417 for (j=0; j<ncols; j++){ 2418 atmp = PetscAbsScalar(*aa); 2419 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2420 aa++; aj++; 2421 } 2422 } 2423 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2424 PetscFunctionReturn(0); 2425 } 2426 2427 #undef __FUNCT__ 2428 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 2429 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2430 { 2431 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2432 PetscErrorCode ierr; 2433 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2434 PetscScalar *x; 2435 MatScalar *aa; 2436 2437 PetscFunctionBegin; 2438 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2439 aa = a->a; 2440 ai = a->i; 2441 aj = a->j; 2442 2443 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2444 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2445 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2446 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2447 for (i=0; i<m; i++) { 2448 ncols = ai[1] - ai[0]; ai++; 2449 if (ncols == A->cmap->n) { /* row is dense */ 2450 x[i] = *aa; if (idx) idx[i] = 0; 2451 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2452 x[i] = 0.0; 2453 if (idx) { 2454 idx[i] = 0; /* in case ncols is zero */ 2455 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2456 if (aj[j] > j) { 2457 idx[i] = j; 2458 break; 2459 } 2460 } 2461 } 2462 } 2463 for (j=0; j<ncols; j++){ 2464 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2465 aa++; aj++; 2466 } 2467 } 2468 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2469 PetscFunctionReturn(0); 2470 } 2471 2472 #undef __FUNCT__ 2473 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 2474 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2475 { 2476 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2477 PetscErrorCode ierr; 2478 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2479 PetscReal atmp; 2480 PetscScalar *x; 2481 MatScalar *aa; 2482 2483 PetscFunctionBegin; 2484 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2485 aa = a->a; 2486 ai = a->i; 2487 aj = a->j; 2488 2489 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2490 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2491 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2492 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2493 for (i=0; i<m; i++) { 2494 ncols = ai[1] - ai[0]; ai++; 2495 if (ncols) { 2496 /* Get first nonzero */ 2497 for(j = 0; j < ncols; j++) { 2498 atmp = PetscAbsScalar(aa[j]); 2499 if (atmp > 1.0e-12) {x[i] = atmp; if (idx) idx[i] = aj[j]; break;} 2500 } 2501 if (j == ncols) {x[i] = *aa; if (idx) idx[i] = *aj;} 2502 } else { 2503 x[i] = 0.0; if (idx) idx[i] = 0; 2504 } 2505 for(j = 0; j < ncols; j++) { 2506 atmp = PetscAbsScalar(*aa); 2507 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2508 aa++; aj++; 2509 } 2510 } 2511 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2512 PetscFunctionReturn(0); 2513 } 2514 2515 #undef __FUNCT__ 2516 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 2517 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2518 { 2519 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2520 PetscErrorCode ierr; 2521 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2522 PetscScalar *x; 2523 MatScalar *aa; 2524 2525 PetscFunctionBegin; 2526 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2527 aa = a->a; 2528 ai = a->i; 2529 aj = a->j; 2530 2531 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2532 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2533 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2534 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2535 for (i=0; i<m; i++) { 2536 ncols = ai[1] - ai[0]; ai++; 2537 if (ncols == A->cmap->n) { /* row is dense */ 2538 x[i] = *aa; if (idx) idx[i] = 0; 2539 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2540 x[i] = 0.0; 2541 if (idx) { /* find first implicit 0.0 in the row */ 2542 idx[i] = 0; /* in case ncols is zero */ 2543 for (j=0;j<ncols;j++) { 2544 if (aj[j] > j) { 2545 idx[i] = j; 2546 break; 2547 } 2548 } 2549 } 2550 } 2551 for (j=0; j<ncols; j++){ 2552 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2553 aa++; aj++; 2554 } 2555 } 2556 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2557 PetscFunctionReturn(0); 2558 } 2559 extern PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 2560 /* -------------------------------------------------------------------*/ 2561 static struct _MatOps MatOps_Values = {MatSetValues_SeqAIJ, 2562 MatGetRow_SeqAIJ, 2563 MatRestoreRow_SeqAIJ, 2564 MatMult_SeqAIJ, 2565 /* 4*/ MatMultAdd_SeqAIJ, 2566 MatMultTranspose_SeqAIJ, 2567 MatMultTransposeAdd_SeqAIJ, 2568 0, 2569 0, 2570 0, 2571 /*10*/ 0, 2572 MatLUFactor_SeqAIJ, 2573 0, 2574 MatSOR_SeqAIJ, 2575 MatTranspose_SeqAIJ, 2576 /*15*/ MatGetInfo_SeqAIJ, 2577 MatEqual_SeqAIJ, 2578 MatGetDiagonal_SeqAIJ, 2579 MatDiagonalScale_SeqAIJ, 2580 MatNorm_SeqAIJ, 2581 /*20*/ 0, 2582 MatAssemblyEnd_SeqAIJ, 2583 MatSetOption_SeqAIJ, 2584 MatZeroEntries_SeqAIJ, 2585 /*24*/ MatZeroRows_SeqAIJ, 2586 0, 2587 0, 2588 0, 2589 0, 2590 /*29*/ MatSetUpPreallocation_SeqAIJ, 2591 0, 2592 0, 2593 MatGetArray_SeqAIJ, 2594 MatRestoreArray_SeqAIJ, 2595 /*34*/ MatDuplicate_SeqAIJ, 2596 0, 2597 0, 2598 MatILUFactor_SeqAIJ, 2599 0, 2600 /*39*/ MatAXPY_SeqAIJ, 2601 MatGetSubMatrices_SeqAIJ, 2602 MatIncreaseOverlap_SeqAIJ, 2603 MatGetValues_SeqAIJ, 2604 MatCopy_SeqAIJ, 2605 /*44*/ MatGetRowMax_SeqAIJ, 2606 MatScale_SeqAIJ, 2607 0, 2608 MatDiagonalSet_SeqAIJ, 2609 0, 2610 /*49*/ MatSetBlockSize_SeqAIJ, 2611 MatGetRowIJ_SeqAIJ, 2612 MatRestoreRowIJ_SeqAIJ, 2613 MatGetColumnIJ_SeqAIJ, 2614 MatRestoreColumnIJ_SeqAIJ, 2615 /*54*/ MatFDColoringCreate_SeqAIJ, 2616 0, 2617 0, 2618 MatPermute_SeqAIJ, 2619 0, 2620 /*59*/ 0, 2621 MatDestroy_SeqAIJ, 2622 MatView_SeqAIJ, 2623 0, 2624 0, 2625 /*64*/ 0, 2626 0, 2627 0, 2628 0, 2629 0, 2630 /*69*/ MatGetRowMaxAbs_SeqAIJ, 2631 MatGetRowMinAbs_SeqAIJ, 2632 0, 2633 MatSetColoring_SeqAIJ, 2634 #if defined(PETSC_HAVE_ADIC) 2635 MatSetValuesAdic_SeqAIJ, 2636 #else 2637 0, 2638 #endif 2639 /*74*/ MatSetValuesAdifor_SeqAIJ, 2640 MatFDColoringApply_AIJ, 2641 0, 2642 0, 2643 0, 2644 /*79*/ 0, 2645 0, 2646 0, 2647 0, 2648 MatLoad_SeqAIJ, 2649 /*84*/ MatIsSymmetric_SeqAIJ, 2650 MatIsHermitian_SeqAIJ, 2651 0, 2652 0, 2653 0, 2654 /*89*/ MatMatMult_SeqAIJ_SeqAIJ, 2655 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 2656 MatMatMultNumeric_SeqAIJ_SeqAIJ, 2657 MatPtAP_Basic, 2658 MatPtAPSymbolic_SeqAIJ, 2659 /*94*/ MatPtAPNumeric_SeqAIJ, 2660 MatMatMultTranspose_SeqAIJ_SeqAIJ, 2661 MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ, 2662 MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ, 2663 MatPtAPSymbolic_SeqAIJ_SeqAIJ, 2664 /*99*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 2665 0, 2666 0, 2667 MatConjugate_SeqAIJ, 2668 0, 2669 /*104*/MatSetValuesRow_SeqAIJ, 2670 MatRealPart_SeqAIJ, 2671 MatImaginaryPart_SeqAIJ, 2672 0, 2673 0, 2674 /*109*/0, 2675 0, 2676 MatGetRowMin_SeqAIJ, 2677 0, 2678 MatMissingDiagonal_SeqAIJ, 2679 /*114*/0, 2680 0, 2681 0, 2682 0, 2683 0, 2684 /*119*/0, 2685 0, 2686 0, 2687 0, 2688 MatGetMultiProcBlock_SeqAIJ 2689 }; 2690 2691 EXTERN_C_BEGIN 2692 #undef __FUNCT__ 2693 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 2694 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 2695 { 2696 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2697 PetscInt i,nz,n; 2698 2699 PetscFunctionBegin; 2700 2701 nz = aij->maxnz; 2702 n = mat->rmap->n; 2703 for (i=0; i<nz; i++) { 2704 aij->j[i] = indices[i]; 2705 } 2706 aij->nz = nz; 2707 for (i=0; i<n; i++) { 2708 aij->ilen[i] = aij->imax[i]; 2709 } 2710 2711 PetscFunctionReturn(0); 2712 } 2713 EXTERN_C_END 2714 2715 #undef __FUNCT__ 2716 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 2717 /*@ 2718 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 2719 in the matrix. 2720 2721 Input Parameters: 2722 + mat - the SeqAIJ matrix 2723 - indices - the column indices 2724 2725 Level: advanced 2726 2727 Notes: 2728 This can be called if you have precomputed the nonzero structure of the 2729 matrix and want to provide it to the matrix object to improve the performance 2730 of the MatSetValues() operation. 2731 2732 You MUST have set the correct numbers of nonzeros per row in the call to 2733 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 2734 2735 MUST be called before any calls to MatSetValues(); 2736 2737 The indices should start with zero, not one. 2738 2739 @*/ 2740 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 2741 { 2742 PetscErrorCode ierr,(*f)(Mat,PetscInt *); 2743 2744 PetscFunctionBegin; 2745 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2746 PetscValidPointer(indices,2); 2747 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqAIJSetColumnIndices_C",(void (**)(void))&f);CHKERRQ(ierr); 2748 if (f) { 2749 ierr = (*f)(mat,indices);CHKERRQ(ierr); 2750 } else { 2751 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to set column indices"); 2752 } 2753 PetscFunctionReturn(0); 2754 } 2755 2756 /* ----------------------------------------------------------------------------------------*/ 2757 2758 EXTERN_C_BEGIN 2759 #undef __FUNCT__ 2760 #define __FUNCT__ "MatStoreValues_SeqAIJ" 2761 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_SeqAIJ(Mat mat) 2762 { 2763 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2764 PetscErrorCode ierr; 2765 size_t nz = aij->i[mat->rmap->n]; 2766 2767 PetscFunctionBegin; 2768 if (aij->nonew != 1) { 2769 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2770 } 2771 2772 /* allocate space for values if not already there */ 2773 if (!aij->saved_values) { 2774 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 2775 ierr = PetscLogObjectMemory(mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2776 } 2777 2778 /* copy values over */ 2779 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2780 PetscFunctionReturn(0); 2781 } 2782 EXTERN_C_END 2783 2784 #undef __FUNCT__ 2785 #define __FUNCT__ "MatStoreValues" 2786 /*@ 2787 MatStoreValues - Stashes a copy of the matrix values; this allows, for 2788 example, reuse of the linear part of a Jacobian, while recomputing the 2789 nonlinear portion. 2790 2791 Collect on Mat 2792 2793 Input Parameters: 2794 . mat - the matrix (currently only AIJ matrices support this option) 2795 2796 Level: advanced 2797 2798 Common Usage, with SNESSolve(): 2799 $ Create Jacobian matrix 2800 $ Set linear terms into matrix 2801 $ Apply boundary conditions to matrix, at this time matrix must have 2802 $ final nonzero structure (i.e. setting the nonlinear terms and applying 2803 $ boundary conditions again will not change the nonzero structure 2804 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 2805 $ ierr = MatStoreValues(mat); 2806 $ Call SNESSetJacobian() with matrix 2807 $ In your Jacobian routine 2808 $ ierr = MatRetrieveValues(mat); 2809 $ Set nonlinear terms in matrix 2810 2811 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 2812 $ // build linear portion of Jacobian 2813 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 2814 $ ierr = MatStoreValues(mat); 2815 $ loop over nonlinear iterations 2816 $ ierr = MatRetrieveValues(mat); 2817 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 2818 $ // call MatAssemblyBegin/End() on matrix 2819 $ Solve linear system with Jacobian 2820 $ endloop 2821 2822 Notes: 2823 Matrix must already be assemblied before calling this routine 2824 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 2825 calling this routine. 2826 2827 When this is called multiple times it overwrites the previous set of stored values 2828 and does not allocated additional space. 2829 2830 .seealso: MatRetrieveValues() 2831 2832 @*/ 2833 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues(Mat mat) 2834 { 2835 PetscErrorCode ierr,(*f)(Mat); 2836 2837 PetscFunctionBegin; 2838 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2839 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 2840 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2841 2842 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatStoreValues_C",(void (**)(void))&f);CHKERRQ(ierr); 2843 if (f) { 2844 ierr = (*f)(mat);CHKERRQ(ierr); 2845 } else { 2846 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to store values"); 2847 } 2848 PetscFunctionReturn(0); 2849 } 2850 2851 EXTERN_C_BEGIN 2852 #undef __FUNCT__ 2853 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 2854 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_SeqAIJ(Mat mat) 2855 { 2856 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2857 PetscErrorCode ierr; 2858 PetscInt nz = aij->i[mat->rmap->n]; 2859 2860 PetscFunctionBegin; 2861 if (aij->nonew != 1) { 2862 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2863 } 2864 if (!aij->saved_values) { 2865 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 2866 } 2867 /* copy values over */ 2868 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2869 PetscFunctionReturn(0); 2870 } 2871 EXTERN_C_END 2872 2873 #undef __FUNCT__ 2874 #define __FUNCT__ "MatRetrieveValues" 2875 /*@ 2876 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 2877 example, reuse of the linear part of a Jacobian, while recomputing the 2878 nonlinear portion. 2879 2880 Collect on Mat 2881 2882 Input Parameters: 2883 . mat - the matrix (currently on AIJ matrices support this option) 2884 2885 Level: advanced 2886 2887 .seealso: MatStoreValues() 2888 2889 @*/ 2890 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues(Mat mat) 2891 { 2892 PetscErrorCode ierr,(*f)(Mat); 2893 2894 PetscFunctionBegin; 2895 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2896 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 2897 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2898 2899 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatRetrieveValues_C",(void (**)(void))&f);CHKERRQ(ierr); 2900 if (f) { 2901 ierr = (*f)(mat);CHKERRQ(ierr); 2902 } else { 2903 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to retrieve values"); 2904 } 2905 PetscFunctionReturn(0); 2906 } 2907 2908 2909 /* --------------------------------------------------------------------------------*/ 2910 #undef __FUNCT__ 2911 #define __FUNCT__ "MatCreateSeqAIJ" 2912 /*@C 2913 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 2914 (the default parallel PETSc format). For good matrix assembly performance 2915 the user should preallocate the matrix storage by setting the parameter nz 2916 (or the array nnz). By setting these parameters accurately, performance 2917 during matrix assembly can be increased by more than a factor of 50. 2918 2919 Collective on MPI_Comm 2920 2921 Input Parameters: 2922 + comm - MPI communicator, set to PETSC_COMM_SELF 2923 . m - number of rows 2924 . n - number of columns 2925 . nz - number of nonzeros per row (same for all rows) 2926 - nnz - array containing the number of nonzeros in the various rows 2927 (possibly different for each row) or PETSC_NULL 2928 2929 Output Parameter: 2930 . A - the matrix 2931 2932 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2933 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2934 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2935 2936 Notes: 2937 If nnz is given then nz is ignored 2938 2939 The AIJ format (also called the Yale sparse matrix format or 2940 compressed row storage), is fully compatible with standard Fortran 77 2941 storage. That is, the stored row and column indices can begin at 2942 either one (as in Fortran) or zero. See the users' manual for details. 2943 2944 Specify the preallocated storage with either nz or nnz (not both). 2945 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2946 allocation. For large problems you MUST preallocate memory or you 2947 will get TERRIBLE performance, see the users' manual chapter on matrices. 2948 2949 By default, this format uses inodes (identical nodes) when possible, to 2950 improve numerical efficiency of matrix-vector products and solves. We 2951 search for consecutive rows with the same nonzero structure, thereby 2952 reusing matrix information to achieve increased efficiency. 2953 2954 Options Database Keys: 2955 + -mat_no_inode - Do not use inodes 2956 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 2957 2958 Level: intermediate 2959 2960 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 2961 2962 @*/ 2963 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 2964 { 2965 PetscErrorCode ierr; 2966 2967 PetscFunctionBegin; 2968 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2969 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2970 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 2971 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 2972 PetscFunctionReturn(0); 2973 } 2974 2975 #undef __FUNCT__ 2976 #define __FUNCT__ "MatSeqAIJSetPreallocation" 2977 /*@C 2978 MatSeqAIJSetPreallocation - For good matrix assembly performance 2979 the user should preallocate the matrix storage by setting the parameter nz 2980 (or the array nnz). By setting these parameters accurately, performance 2981 during matrix assembly can be increased by more than a factor of 50. 2982 2983 Collective on MPI_Comm 2984 2985 Input Parameters: 2986 + B - The matrix-free 2987 . nz - number of nonzeros per row (same for all rows) 2988 - nnz - array containing the number of nonzeros in the various rows 2989 (possibly different for each row) or PETSC_NULL 2990 2991 Notes: 2992 If nnz is given then nz is ignored 2993 2994 The AIJ format (also called the Yale sparse matrix format or 2995 compressed row storage), is fully compatible with standard Fortran 77 2996 storage. That is, the stored row and column indices can begin at 2997 either one (as in Fortran) or zero. See the users' manual for details. 2998 2999 Specify the preallocated storage with either nz or nnz (not both). 3000 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 3001 allocation. For large problems you MUST preallocate memory or you 3002 will get TERRIBLE performance, see the users' manual chapter on matrices. 3003 3004 You can call MatGetInfo() to get information on how effective the preallocation was; 3005 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 3006 You can also run with the option -info and look for messages with the string 3007 malloc in them to see if additional memory allocation was needed. 3008 3009 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 3010 entries or columns indices 3011 3012 By default, this format uses inodes (identical nodes) when possible, to 3013 improve numerical efficiency of matrix-vector products and solves. We 3014 search for consecutive rows with the same nonzero structure, thereby 3015 reusing matrix information to achieve increased efficiency. 3016 3017 Options Database Keys: 3018 + -mat_no_inode - Do not use inodes 3019 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 3020 - -mat_aij_oneindex - Internally use indexing starting at 1 3021 rather than 0. Note that when calling MatSetValues(), 3022 the user still MUST index entries starting at 0! 3023 3024 Level: intermediate 3025 3026 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 3027 3028 @*/ 3029 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 3030 { 3031 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[]); 3032 3033 PetscFunctionBegin; 3034 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 3035 if (f) { 3036 ierr = (*f)(B,nz,nnz);CHKERRQ(ierr); 3037 } 3038 PetscFunctionReturn(0); 3039 } 3040 3041 EXTERN_C_BEGIN 3042 #undef __FUNCT__ 3043 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3044 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3045 { 3046 Mat_SeqAIJ *b; 3047 PetscTruth skipallocation = PETSC_FALSE; 3048 PetscErrorCode ierr; 3049 PetscInt i; 3050 3051 PetscFunctionBegin; 3052 3053 if (nz == MAT_SKIP_ALLOCATION) { 3054 skipallocation = PETSC_TRUE; 3055 nz = 0; 3056 } 3057 3058 ierr = PetscLayoutSetBlockSize(B->rmap,1);CHKERRQ(ierr); 3059 ierr = PetscLayoutSetBlockSize(B->cmap,1);CHKERRQ(ierr); 3060 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3061 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3062 3063 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3064 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3065 if (nnz) { 3066 for (i=0; i<B->rmap->n; i++) { 3067 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]); 3068 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); 3069 } 3070 } 3071 3072 B->preallocated = PETSC_TRUE; 3073 b = (Mat_SeqAIJ*)B->data; 3074 3075 if (!skipallocation) { 3076 if (!b->imax) { 3077 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3078 ierr = PetscLogObjectMemory(B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3079 } 3080 if (!nnz) { 3081 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3082 else if (nz < 0) nz = 1; 3083 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3084 nz = nz*B->rmap->n; 3085 } else { 3086 nz = 0; 3087 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3088 } 3089 /* b->ilen will count nonzeros in each row so far. */ 3090 for (i=0; i<B->rmap->n; i++) { b->ilen[i] = 0; } 3091 3092 /* allocate the matrix space */ 3093 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3094 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3095 ierr = PetscLogObjectMemory(B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3096 b->i[0] = 0; 3097 for (i=1; i<B->rmap->n+1; i++) { 3098 b->i[i] = b->i[i-1] + b->imax[i-1]; 3099 } 3100 b->singlemalloc = PETSC_TRUE; 3101 b->free_a = PETSC_TRUE; 3102 b->free_ij = PETSC_TRUE; 3103 } else { 3104 b->free_a = PETSC_FALSE; 3105 b->free_ij = PETSC_FALSE; 3106 } 3107 3108 b->nz = 0; 3109 b->maxnz = nz; 3110 B->info.nz_unneeded = (double)b->maxnz; 3111 PetscFunctionReturn(0); 3112 } 3113 EXTERN_C_END 3114 3115 #undef __FUNCT__ 3116 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3117 /*@ 3118 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3119 3120 Input Parameters: 3121 + B - the matrix 3122 . i - the indices into j for the start of each row (starts with zero) 3123 . j - the column indices for each row (starts with zero) these must be sorted for each row 3124 - v - optional values in the matrix 3125 3126 Level: developer 3127 3128 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3129 3130 .keywords: matrix, aij, compressed row, sparse, sequential 3131 3132 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3133 @*/ 3134 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3135 { 3136 PetscErrorCode (*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3137 PetscErrorCode ierr; 3138 3139 PetscFunctionBegin; 3140 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3141 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3142 if (f) { 3143 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3144 } 3145 PetscFunctionReturn(0); 3146 } 3147 3148 EXTERN_C_BEGIN 3149 #undef __FUNCT__ 3150 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3151 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3152 { 3153 PetscInt i; 3154 PetscInt m,n; 3155 PetscInt nz; 3156 PetscInt *nnz, nz_max = 0; 3157 PetscScalar *values; 3158 PetscErrorCode ierr; 3159 3160 PetscFunctionBegin; 3161 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3162 3163 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3164 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 3165 for(i = 0; i < m; i++) { 3166 nz = Ii[i+1]- Ii[i]; 3167 nz_max = PetscMax(nz_max, nz); 3168 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3169 nnz[i] = nz; 3170 } 3171 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3172 ierr = PetscFree(nnz);CHKERRQ(ierr); 3173 3174 if (v) { 3175 values = (PetscScalar*) v; 3176 } else { 3177 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 3178 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3179 } 3180 3181 for(i = 0; i < m; i++) { 3182 nz = Ii[i+1] - Ii[i]; 3183 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3184 } 3185 3186 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3187 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3188 3189 if (!v) { 3190 ierr = PetscFree(values);CHKERRQ(ierr); 3191 } 3192 PetscFunctionReturn(0); 3193 } 3194 EXTERN_C_END 3195 3196 #include "../src/mat/impls/dense/seq/dense.h" 3197 #include "private/petscaxpy.h" 3198 3199 #undef __FUNCT__ 3200 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3201 /* 3202 Computes (B'*A')' since computing B*A directly is untenable 3203 3204 n p p 3205 ( ) ( ) ( ) 3206 m ( A ) * n ( B ) = m ( C ) 3207 ( ) ( ) ( ) 3208 3209 */ 3210 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3211 { 3212 PetscErrorCode ierr; 3213 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3214 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3215 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3216 PetscInt i,n,m,q,p; 3217 const PetscInt *ii,*idx; 3218 const PetscScalar *b,*a,*a_q; 3219 PetscScalar *c,*c_q; 3220 3221 PetscFunctionBegin; 3222 m = A->rmap->n; 3223 n = A->cmap->n; 3224 p = B->cmap->n; 3225 a = sub_a->v; 3226 b = sub_b->a; 3227 c = sub_c->v; 3228 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3229 3230 ii = sub_b->i; 3231 idx = sub_b->j; 3232 for (i=0; i<n; i++) { 3233 q = ii[i+1] - ii[i]; 3234 while (q-->0) { 3235 c_q = c + m*(*idx); 3236 a_q = a + m*i; 3237 PetscAXPY(c_q,*b,a_q,m); 3238 idx++; 3239 b++; 3240 } 3241 } 3242 PetscFunctionReturn(0); 3243 } 3244 3245 #undef __FUNCT__ 3246 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 3247 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3248 { 3249 PetscErrorCode ierr; 3250 PetscInt m=A->rmap->n,n=B->cmap->n; 3251 Mat Cmat; 3252 3253 PetscFunctionBegin; 3254 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); 3255 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 3256 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3257 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3258 ierr = MatSeqDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 3259 Cmat->assembled = PETSC_TRUE; 3260 *C = Cmat; 3261 PetscFunctionReturn(0); 3262 } 3263 3264 /* ----------------------------------------------------------------*/ 3265 #undef __FUNCT__ 3266 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 3267 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3268 { 3269 PetscErrorCode ierr; 3270 3271 PetscFunctionBegin; 3272 if (scall == MAT_INITIAL_MATRIX){ 3273 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3274 } 3275 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3276 PetscFunctionReturn(0); 3277 } 3278 3279 3280 /*MC 3281 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3282 based on compressed sparse row format. 3283 3284 Options Database Keys: 3285 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3286 3287 Level: beginner 3288 3289 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3290 M*/ 3291 3292 EXTERN_C_BEGIN 3293 #if defined(PETSC_HAVE_PASTIX) 3294 extern PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 3295 #endif 3296 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SCALAR_SINGLE) && !defined(PETSC_USE_SCALAR_MAT_SINGLE) 3297 extern PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat *); 3298 #endif 3299 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3300 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 3301 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 3302 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscTruth *); 3303 #if defined(PETSC_HAVE_MUMPS) 3304 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 3305 #endif 3306 #if defined(PETSC_HAVE_SUPERLU) 3307 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 3308 #endif 3309 #if defined(PETSC_HAVE_SUPERLU_DIST) 3310 extern PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 3311 #endif 3312 #if defined(PETSC_HAVE_SPOOLES) 3313 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_spooles(Mat,MatFactorType,Mat*); 3314 #endif 3315 #if defined(PETSC_HAVE_UMFPACK) 3316 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 3317 #endif 3318 #if defined(PETSC_HAVE_CHOLMOD) 3319 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 3320 #endif 3321 #if defined(PETSC_HAVE_LUSOL) 3322 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 3323 #endif 3324 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3325 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 3326 extern PetscErrorCode PETSCMAT_DLLEXPORT MatlabEnginePut_SeqAIJ(PetscObject,void*); 3327 extern PetscErrorCode PETSCMAT_DLLEXPORT MatlabEngineGet_SeqAIJ(PetscObject,void*); 3328 #endif 3329 EXTERN_C_END 3330 3331 3332 EXTERN_C_BEGIN 3333 #undef __FUNCT__ 3334 #define __FUNCT__ "MatCreate_SeqAIJ" 3335 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SeqAIJ(Mat B) 3336 { 3337 Mat_SeqAIJ *b; 3338 PetscErrorCode ierr; 3339 PetscMPIInt size; 3340 3341 PetscFunctionBegin; 3342 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 3343 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3344 3345 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 3346 B->data = (void*)b; 3347 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3348 B->mapping = 0; 3349 b->row = 0; 3350 b->col = 0; 3351 b->icol = 0; 3352 b->reallocs = 0; 3353 b->ignorezeroentries = PETSC_FALSE; 3354 b->roworiented = PETSC_TRUE; 3355 b->nonew = 0; 3356 b->diag = 0; 3357 b->solve_work = 0; 3358 B->spptr = 0; 3359 b->saved_values = 0; 3360 b->idiag = 0; 3361 b->mdiag = 0; 3362 b->ssor_work = 0; 3363 b->omega = 1.0; 3364 b->fshift = 0.0; 3365 b->idiagvalid = PETSC_FALSE; 3366 b->keepnonzeropattern = PETSC_FALSE; 3367 b->xtoy = 0; 3368 b->XtoY = 0; 3369 b->compressedrow.use = PETSC_FALSE; 3370 b->compressedrow.nrows = B->rmap->n; 3371 b->compressedrow.i = PETSC_NULL; 3372 b->compressedrow.rindex = PETSC_NULL; 3373 b->compressedrow.checked = PETSC_FALSE; 3374 B->same_nonzero = PETSC_FALSE; 3375 3376 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3377 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3378 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_matlab_C", 3379 "MatGetFactor_seqaij_matlab", 3380 MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 3381 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"PetscMatlabEnginePut_C","MatlabEnginePut_SeqAIJ",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 3382 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"PetscMatlabEngineGet_C","MatlabEngineGet_SeqAIJ",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 3383 #endif 3384 #if defined(PETSC_HAVE_PASTIX) 3385 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C", 3386 "MatGetFactor_seqaij_pastix", 3387 MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 3388 #endif 3389 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SCALAR_SINGLE) && !defined(PETSC_USE_SCALAR_MAT_SINGLE) 3390 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_essl_C", 3391 "MatGetFactor_seqaij_essl", 3392 MatGetFactor_seqaij_essl);CHKERRQ(ierr); 3393 #endif 3394 #if defined(PETSC_HAVE_SUPERLU) 3395 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_C", 3396 "MatGetFactor_seqaij_superlu", 3397 MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 3398 #endif 3399 #if defined(PETSC_HAVE_SUPERLU_DIST) 3400 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_dist_C", 3401 "MatGetFactor_seqaij_superlu_dist", 3402 MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 3403 #endif 3404 #if defined(PETSC_HAVE_SPOOLES) 3405 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_spooles_C", 3406 "MatGetFactor_seqaij_spooles", 3407 MatGetFactor_seqaij_spooles);CHKERRQ(ierr); 3408 #endif 3409 #if defined(PETSC_HAVE_MUMPS) 3410 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", 3411 "MatGetFactor_aij_mumps", 3412 MatGetFactor_aij_mumps);CHKERRQ(ierr); 3413 #endif 3414 #if defined(PETSC_HAVE_UMFPACK) 3415 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_umfpack_C", 3416 "MatGetFactor_seqaij_umfpack", 3417 MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 3418 #endif 3419 #if defined(PETSC_HAVE_CHOLMOD) 3420 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_cholmod_C", 3421 "MatGetFactor_seqaij_cholmod", 3422 MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 3423 #endif 3424 #if defined(PETSC_HAVE_LUSOL) 3425 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_lusol_C", 3426 "MatGetFactor_seqaij_lusol", 3427 MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 3428 #endif 3429 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_petsc_C", 3430 "MatGetFactor_seqaij_petsc", 3431 MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 3432 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactorAvailable_petsc_C", 3433 "MatGetFactorAvailable_seqaij_petsc", 3434 MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 3435 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_bas_C", 3436 "MatGetFactor_seqaij_bas", 3437 MatGetFactor_seqaij_bas); 3438 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetColumnIndices_C", 3439 "MatSeqAIJSetColumnIndices_SeqAIJ", 3440 MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 3441 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 3442 "MatStoreValues_SeqAIJ", 3443 MatStoreValues_SeqAIJ);CHKERRQ(ierr); 3444 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 3445 "MatRetrieveValues_SeqAIJ", 3446 MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 3447 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqsbaij_C", 3448 "MatConvert_SeqAIJ_SeqSBAIJ", 3449 MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 3450 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqbaij_C", 3451 "MatConvert_SeqAIJ_SeqBAIJ", 3452 MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 3453 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqaijperm_C", 3454 "MatConvert_SeqAIJ_SeqAIJPERM", 3455 MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 3456 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C", 3457 "MatConvert_SeqAIJ_SeqAIJCRL", 3458 MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 3459 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 3460 "MatIsTranspose_SeqAIJ", 3461 MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3462 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsHermitianTranspose_C", 3463 "MatIsHermitianTranspose_SeqAIJ", 3464 MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3465 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetPreallocation_C", 3466 "MatSeqAIJSetPreallocation_SeqAIJ", 3467 MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 3468 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C", 3469 "MatSeqAIJSetPreallocationCSR_SeqAIJ", 3470 MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 3471 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatReorderForNonzeroDiagonal_C", 3472 "MatReorderForNonzeroDiagonal_SeqAIJ", 3473 MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 3474 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_seqdense_seqaij_C", 3475 "MatMatMult_SeqDense_SeqAIJ", 3476 MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 3477 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C", 3478 "MatMatMultSymbolic_SeqDense_SeqAIJ", 3479 MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 3480 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C", 3481 "MatMatMultNumeric_SeqDense_SeqAIJ", 3482 MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 3483 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 3484 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3485 PetscFunctionReturn(0); 3486 } 3487 EXTERN_C_END 3488 3489 #undef __FUNCT__ 3490 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 3491 /* 3492 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 3493 */ 3494 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscTruth mallocmatspace) 3495 { 3496 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 3497 PetscErrorCode ierr; 3498 PetscInt i,m = A->rmap->n; 3499 3500 PetscFunctionBegin; 3501 c = (Mat_SeqAIJ*)C->data; 3502 3503 C->factortype = A->factortype; 3504 c->row = 0; 3505 c->col = 0; 3506 c->icol = 0; 3507 c->reallocs = 0; 3508 3509 C->assembled = PETSC_TRUE; 3510 3511 ierr = PetscLayoutSetBlockSize(C->rmap,1);CHKERRQ(ierr); 3512 ierr = PetscLayoutSetBlockSize(C->cmap,1);CHKERRQ(ierr); 3513 ierr = PetscLayoutSetUp(C->rmap);CHKERRQ(ierr); 3514 ierr = PetscLayoutSetUp(C->cmap);CHKERRQ(ierr); 3515 3516 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 3517 ierr = PetscLogObjectMemory(C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 3518 for (i=0; i<m; i++) { 3519 c->imax[i] = a->imax[i]; 3520 c->ilen[i] = a->ilen[i]; 3521 } 3522 3523 /* allocate the matrix space */ 3524 if (mallocmatspace){ 3525 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 3526 ierr = PetscLogObjectMemory(C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3527 c->singlemalloc = PETSC_TRUE; 3528 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3529 if (m > 0) { 3530 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 3531 if (cpvalues == MAT_COPY_VALUES) { 3532 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 3533 } else { 3534 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 3535 } 3536 } 3537 } 3538 3539 c->ignorezeroentries = a->ignorezeroentries; 3540 c->roworiented = a->roworiented; 3541 c->nonew = a->nonew; 3542 if (a->diag) { 3543 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 3544 ierr = PetscLogObjectMemory(C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3545 for (i=0; i<m; i++) { 3546 c->diag[i] = a->diag[i]; 3547 } 3548 } else c->diag = 0; 3549 c->solve_work = 0; 3550 c->saved_values = 0; 3551 c->idiag = 0; 3552 c->ssor_work = 0; 3553 c->keepnonzeropattern = a->keepnonzeropattern; 3554 c->free_a = PETSC_TRUE; 3555 c->free_ij = PETSC_TRUE; 3556 c->xtoy = 0; 3557 c->XtoY = 0; 3558 3559 c->nz = a->nz; 3560 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 3561 C->preallocated = PETSC_TRUE; 3562 3563 c->compressedrow.use = a->compressedrow.use; 3564 c->compressedrow.nrows = a->compressedrow.nrows; 3565 c->compressedrow.checked = a->compressedrow.checked; 3566 if (a->compressedrow.checked && a->compressedrow.use){ 3567 i = a->compressedrow.nrows; 3568 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 3569 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3570 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 3571 } else { 3572 c->compressedrow.use = PETSC_FALSE; 3573 c->compressedrow.i = PETSC_NULL; 3574 c->compressedrow.rindex = PETSC_NULL; 3575 } 3576 C->same_nonzero = A->same_nonzero; 3577 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 3578 3579 ierr = PetscFListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 3580 PetscFunctionReturn(0); 3581 } 3582 3583 #undef __FUNCT__ 3584 #define __FUNCT__ "MatDuplicate_SeqAIJ" 3585 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 3586 { 3587 PetscErrorCode ierr; 3588 3589 PetscFunctionBegin; 3590 ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr); 3591 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 3592 ierr = MatSetType(*B,MATSEQAIJ);CHKERRQ(ierr); 3593 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 3594 PetscFunctionReturn(0); 3595 } 3596 3597 #undef __FUNCT__ 3598 #define __FUNCT__ "MatLoad_SeqAIJ" 3599 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 3600 { 3601 Mat_SeqAIJ *a; 3602 PetscErrorCode ierr; 3603 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 3604 int fd; 3605 PetscMPIInt size; 3606 MPI_Comm comm; 3607 3608 PetscFunctionBegin; 3609 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3610 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3611 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 3612 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3613 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 3614 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 3615 M = header[1]; N = header[2]; nz = header[3]; 3616 3617 if (nz < 0) { 3618 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 3619 } 3620 3621 /* read in row lengths */ 3622 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3623 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 3624 3625 /* check if sum of rowlengths is same as nz */ 3626 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 3627 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); 3628 3629 /* set global size if not set already*/ 3630 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 3631 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 3632 } else { 3633 /* if sizes and type are already set, check if the vector global sizes are correct */ 3634 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 3635 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); 3636 } 3637 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 3638 a = (Mat_SeqAIJ*)newMat->data; 3639 3640 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 3641 3642 /* read in nonzero values */ 3643 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 3644 3645 /* set matrix "i" values */ 3646 a->i[0] = 0; 3647 for (i=1; i<= M; i++) { 3648 a->i[i] = a->i[i-1] + rowlengths[i-1]; 3649 a->ilen[i-1] = rowlengths[i-1]; 3650 } 3651 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3652 3653 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3654 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3655 PetscFunctionReturn(0); 3656 } 3657 3658 #undef __FUNCT__ 3659 #define __FUNCT__ "MatEqual_SeqAIJ" 3660 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscTruth* flg) 3661 { 3662 Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data,*b = (Mat_SeqAIJ *)B->data; 3663 PetscErrorCode ierr; 3664 #if defined(PETSC_USE_COMPLEX) 3665 PetscInt k; 3666 #endif 3667 3668 PetscFunctionBegin; 3669 /* If the matrix dimensions are not equal,or no of nonzeros */ 3670 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 3671 *flg = PETSC_FALSE; 3672 PetscFunctionReturn(0); 3673 } 3674 3675 /* if the a->i are the same */ 3676 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 3677 if (!*flg) PetscFunctionReturn(0); 3678 3679 /* if a->j are the same */ 3680 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 3681 if (!*flg) PetscFunctionReturn(0); 3682 3683 /* if a->a are the same */ 3684 #if defined(PETSC_USE_COMPLEX) 3685 for (k=0; k<a->nz; k++){ 3686 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])){ 3687 *flg = PETSC_FALSE; 3688 PetscFunctionReturn(0); 3689 } 3690 } 3691 #else 3692 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 3693 #endif 3694 PetscFunctionReturn(0); 3695 } 3696 3697 #undef __FUNCT__ 3698 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 3699 /*@ 3700 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 3701 provided by the user. 3702 3703 Collective on MPI_Comm 3704 3705 Input Parameters: 3706 + comm - must be an MPI communicator of size 1 3707 . m - number of rows 3708 . n - number of columns 3709 . i - row indices 3710 . j - column indices 3711 - a - matrix values 3712 3713 Output Parameter: 3714 . mat - the matrix 3715 3716 Level: intermediate 3717 3718 Notes: 3719 The i, j, and a arrays are not copied by this routine, the user must free these arrays 3720 once the matrix is destroyed 3721 3722 You cannot set new nonzero locations into this matrix, that will generate an error. 3723 3724 The i and j indices are 0 based 3725 3726 The format which is used for the sparse matrix input, is equivalent to a 3727 row-major ordering.. i.e for the following matrix, the input data expected is 3728 as shown: 3729 3730 1 0 0 3731 2 0 3 3732 4 5 6 3733 3734 i = {0,1,3,6} [size = nrow+1 = 3+1] 3735 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 3736 v = {1,2,3,4,5,6} [size = nz = 6] 3737 3738 3739 .seealso: MatCreate(), MatCreateMPIAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 3740 3741 @*/ 3742 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt* i,PetscInt*j,PetscScalar *a,Mat *mat) 3743 { 3744 PetscErrorCode ierr; 3745 PetscInt ii; 3746 Mat_SeqAIJ *aij; 3747 #if defined(PETSC_USE_DEBUG) 3748 PetscInt jj; 3749 #endif 3750 3751 PetscFunctionBegin; 3752 if (i[0]) { 3753 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3754 } 3755 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3756 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 3757 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 3758 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 3759 aij = (Mat_SeqAIJ*)(*mat)->data; 3760 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 3761 3762 aij->i = i; 3763 aij->j = j; 3764 aij->a = a; 3765 aij->singlemalloc = PETSC_FALSE; 3766 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 3767 aij->free_a = PETSC_FALSE; 3768 aij->free_ij = PETSC_FALSE; 3769 3770 for (ii=0; ii<m; ii++) { 3771 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 3772 #if defined(PETSC_USE_DEBUG) 3773 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]); 3774 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 3775 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); 3776 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); 3777 } 3778 #endif 3779 } 3780 #if defined(PETSC_USE_DEBUG) 3781 for (ii=0; ii<aij->i[m]; ii++) { 3782 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 3783 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]); 3784 } 3785 #endif 3786 3787 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3788 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3789 PetscFunctionReturn(0); 3790 } 3791 3792 #undef __FUNCT__ 3793 #define __FUNCT__ "MatSetColoring_SeqAIJ" 3794 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 3795 { 3796 PetscErrorCode ierr; 3797 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3798 3799 PetscFunctionBegin; 3800 if (coloring->ctype == IS_COLORING_GLOBAL) { 3801 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 3802 a->coloring = coloring; 3803 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3804 PetscInt i,*larray; 3805 ISColoring ocoloring; 3806 ISColoringValue *colors; 3807 3808 /* set coloring for diagonal portion */ 3809 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3810 for (i=0; i<A->cmap->n; i++) { 3811 larray[i] = i; 3812 } 3813 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3814 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3815 for (i=0; i<A->cmap->n; i++) { 3816 colors[i] = coloring->colors[larray[i]]; 3817 } 3818 ierr = PetscFree(larray);CHKERRQ(ierr); 3819 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3820 a->coloring = ocoloring; 3821 } 3822 PetscFunctionReturn(0); 3823 } 3824 3825 #if defined(PETSC_HAVE_ADIC) 3826 EXTERN_C_BEGIN 3827 #include "adic/ad_utils.h" 3828 EXTERN_C_END 3829 3830 #undef __FUNCT__ 3831 #define __FUNCT__ "MatSetValuesAdic_SeqAIJ" 3832 PetscErrorCode MatSetValuesAdic_SeqAIJ(Mat A,void *advalues) 3833 { 3834 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3835 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j,nlen; 3836 PetscScalar *v = a->a,*values = ((PetscScalar*)advalues)+1; 3837 ISColoringValue *color; 3838 3839 PetscFunctionBegin; 3840 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 3841 nlen = PetscADGetDerivTypeSize()/sizeof(PetscScalar); 3842 color = a->coloring->colors; 3843 /* loop over rows */ 3844 for (i=0; i<m; i++) { 3845 nz = ii[i+1] - ii[i]; 3846 /* loop over columns putting computed value into matrix */ 3847 for (j=0; j<nz; j++) { 3848 *v++ = values[color[*jj++]]; 3849 } 3850 values += nlen; /* jump to next row of derivatives */ 3851 } 3852 PetscFunctionReturn(0); 3853 } 3854 #endif 3855 3856 #undef __FUNCT__ 3857 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 3858 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 3859 { 3860 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3861 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 3862 MatScalar *v = a->a; 3863 PetscScalar *values = (PetscScalar *)advalues; 3864 ISColoringValue *color; 3865 3866 PetscFunctionBegin; 3867 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 3868 color = a->coloring->colors; 3869 /* loop over rows */ 3870 for (i=0; i<m; i++) { 3871 nz = ii[i+1] - ii[i]; 3872 /* loop over columns putting computed value into matrix */ 3873 for (j=0; j<nz; j++) { 3874 *v++ = values[color[*jj++]]; 3875 } 3876 values += nl; /* jump to next row of derivatives */ 3877 } 3878 PetscFunctionReturn(0); 3879 } 3880 3881 /* 3882 Special version for direct calls from Fortran 3883 */ 3884 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3885 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 3886 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3887 #define matsetvaluesseqaij_ matsetvaluesseqaij 3888 #endif 3889 3890 /* Change these macros so can be used in void function */ 3891 #undef CHKERRQ 3892 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)A)->comm,ierr) 3893 #undef SETERRQ2 3894 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 3895 3896 EXTERN_C_BEGIN 3897 #undef __FUNCT__ 3898 #define __FUNCT__ "matsetvaluesseqaij_" 3899 void PETSC_STDCALL matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 3900 { 3901 Mat A = *AA; 3902 PetscInt m = *mm, n = *nn; 3903 InsertMode is = *isis; 3904 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3905 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 3906 PetscInt *imax,*ai,*ailen; 3907 PetscErrorCode ierr; 3908 PetscInt *aj,nonew = a->nonew,lastcol = -1; 3909 MatScalar *ap,value,*aa; 3910 PetscTruth ignorezeroentries = a->ignorezeroentries; 3911 PetscTruth roworiented = a->roworiented; 3912 3913 PetscFunctionBegin; 3914 ierr = MatPreallocated(A);CHKERRQ(ierr); 3915 imax = a->imax; 3916 ai = a->i; 3917 ailen = a->ilen; 3918 aj = a->j; 3919 aa = a->a; 3920 3921 for (k=0; k<m; k++) { /* loop over added rows */ 3922 row = im[k]; 3923 if (row < 0) continue; 3924 #if defined(PETSC_USE_DEBUG) 3925 if (row >= A->rmap->n) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 3926 #endif 3927 rp = aj + ai[row]; ap = aa + ai[row]; 3928 rmax = imax[row]; nrow = ailen[row]; 3929 low = 0; 3930 high = nrow; 3931 for (l=0; l<n; l++) { /* loop over added columns */ 3932 if (in[l] < 0) continue; 3933 #if defined(PETSC_USE_DEBUG) 3934 if (in[l] >= A->cmap->n) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 3935 #endif 3936 col = in[l]; 3937 if (roworiented) { 3938 value = v[l + k*n]; 3939 } else { 3940 value = v[k + l*m]; 3941 } 3942 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 3943 3944 if (col <= lastcol) low = 0; else high = nrow; 3945 lastcol = col; 3946 while (high-low > 5) { 3947 t = (low+high)/2; 3948 if (rp[t] > col) high = t; 3949 else low = t; 3950 } 3951 for (i=low; i<high; i++) { 3952 if (rp[i] > col) break; 3953 if (rp[i] == col) { 3954 if (is == ADD_VALUES) ap[i] += value; 3955 else ap[i] = value; 3956 goto noinsert; 3957 } 3958 } 3959 if (value == 0.0 && ignorezeroentries) goto noinsert; 3960 if (nonew == 1) goto noinsert; 3961 if (nonew == -1) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 3962 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 3963 N = nrow++ - 1; a->nz++; high++; 3964 /* shift up all the later entries in this row */ 3965 for (ii=N; ii>=i; ii--) { 3966 rp[ii+1] = rp[ii]; 3967 ap[ii+1] = ap[ii]; 3968 } 3969 rp[i] = col; 3970 ap[i] = value; 3971 noinsert:; 3972 low = i + 1; 3973 } 3974 ailen[row] = nrow; 3975 } 3976 A->same_nonzero = PETSC_FALSE; 3977 PetscFunctionReturnVoid(); 3978 } 3979 EXTERN_C_END 3980