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__ "MatAXPY_SeqAIJ" 2293 PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) 2294 { 2295 PetscErrorCode ierr; 2296 PetscInt i; 2297 Mat_SeqAIJ *x = (Mat_SeqAIJ *)X->data,*y = (Mat_SeqAIJ *)Y->data; 2298 PetscBLASInt one=1,bnz = PetscBLASIntCast(x->nz); 2299 2300 PetscFunctionBegin; 2301 if (str == SAME_NONZERO_PATTERN) { 2302 PetscScalar alpha = a; 2303 BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one); 2304 } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ 2305 if (y->xtoy && y->XtoY != X) { 2306 ierr = PetscFree(y->xtoy);CHKERRQ(ierr); 2307 ierr = MatDestroy(y->XtoY);CHKERRQ(ierr); 2308 } 2309 if (!y->xtoy) { /* get xtoy */ 2310 ierr = MatAXPYGetxtoy_Private(X->rmap->n,x->i,x->j,PETSC_NULL, y->i,y->j,PETSC_NULL, &y->xtoy);CHKERRQ(ierr); 2311 y->XtoY = X; 2312 ierr = PetscObjectReference((PetscObject)X);CHKERRQ(ierr); 2313 } 2314 for (i=0; i<x->nz; i++) y->a[y->xtoy[i]] += a*(x->a[i]); 2315 ierr = PetscInfo3(Y,"ratio of nnz(X)/nnz(Y): %d/%d = %G\n",x->nz,y->nz,(PetscReal)(x->nz)/y->nz);CHKERRQ(ierr); 2316 } else { 2317 ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); 2318 } 2319 PetscFunctionReturn(0); 2320 } 2321 2322 #undef __FUNCT__ 2323 #define __FUNCT__ "MatSetBlockSize_SeqAIJ" 2324 PetscErrorCode MatSetBlockSize_SeqAIJ(Mat A,PetscInt bs) 2325 { 2326 PetscErrorCode ierr; 2327 2328 PetscFunctionBegin; 2329 ierr = PetscLayoutSetBlockSize(A->rmap,bs);CHKERRQ(ierr); 2330 ierr = PetscLayoutSetBlockSize(A->cmap,bs);CHKERRQ(ierr); 2331 PetscFunctionReturn(0); 2332 } 2333 2334 #undef __FUNCT__ 2335 #define __FUNCT__ "MatConjugate_SeqAIJ" 2336 PetscErrorCode PETSCMAT_DLLEXPORT MatConjugate_SeqAIJ(Mat mat) 2337 { 2338 #if defined(PETSC_USE_COMPLEX) 2339 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2340 PetscInt i,nz; 2341 PetscScalar *a; 2342 2343 PetscFunctionBegin; 2344 nz = aij->nz; 2345 a = aij->a; 2346 for (i=0; i<nz; i++) { 2347 a[i] = PetscConj(a[i]); 2348 } 2349 #else 2350 PetscFunctionBegin; 2351 #endif 2352 PetscFunctionReturn(0); 2353 } 2354 2355 #undef __FUNCT__ 2356 #define __FUNCT__ "MatGetRowMaxAbs_SeqAIJ" 2357 PetscErrorCode MatGetRowMaxAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2358 { 2359 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2360 PetscErrorCode ierr; 2361 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2362 PetscReal atmp; 2363 PetscScalar *x; 2364 MatScalar *aa; 2365 2366 PetscFunctionBegin; 2367 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2368 aa = a->a; 2369 ai = a->i; 2370 aj = a->j; 2371 2372 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2373 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2374 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2375 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2376 for (i=0; i<m; i++) { 2377 ncols = ai[1] - ai[0]; ai++; 2378 x[i] = 0.0; 2379 for (j=0; j<ncols; j++){ 2380 atmp = PetscAbsScalar(*aa); 2381 if (PetscAbsScalar(x[i]) < atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2382 aa++; aj++; 2383 } 2384 } 2385 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2386 PetscFunctionReturn(0); 2387 } 2388 2389 #undef __FUNCT__ 2390 #define __FUNCT__ "MatGetRowMax_SeqAIJ" 2391 PetscErrorCode MatGetRowMax_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2392 { 2393 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2394 PetscErrorCode ierr; 2395 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2396 PetscScalar *x; 2397 MatScalar *aa; 2398 2399 PetscFunctionBegin; 2400 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2401 aa = a->a; 2402 ai = a->i; 2403 aj = a->j; 2404 2405 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2406 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2407 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2408 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2409 for (i=0; i<m; i++) { 2410 ncols = ai[1] - ai[0]; ai++; 2411 if (ncols == A->cmap->n) { /* row is dense */ 2412 x[i] = *aa; if (idx) idx[i] = 0; 2413 } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ 2414 x[i] = 0.0; 2415 if (idx) { 2416 idx[i] = 0; /* in case ncols is zero */ 2417 for (j=0;j<ncols;j++) { /* find first implicit 0.0 in the row */ 2418 if (aj[j] > j) { 2419 idx[i] = j; 2420 break; 2421 } 2422 } 2423 } 2424 } 2425 for (j=0; j<ncols; j++){ 2426 if (PetscRealPart(x[i]) < PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2427 aa++; aj++; 2428 } 2429 } 2430 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2431 PetscFunctionReturn(0); 2432 } 2433 2434 #undef __FUNCT__ 2435 #define __FUNCT__ "MatGetRowMinAbs_SeqAIJ" 2436 PetscErrorCode MatGetRowMinAbs_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2437 { 2438 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2439 PetscErrorCode ierr; 2440 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2441 PetscReal atmp; 2442 PetscScalar *x; 2443 MatScalar *aa; 2444 2445 PetscFunctionBegin; 2446 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2447 aa = a->a; 2448 ai = a->i; 2449 aj = a->j; 2450 2451 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2452 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2453 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2454 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2455 for (i=0; i<m; i++) { 2456 ncols = ai[1] - ai[0]; ai++; 2457 if (ncols) { 2458 /* Get first nonzero */ 2459 for(j = 0; j < ncols; j++) { 2460 atmp = PetscAbsScalar(aa[j]); 2461 if (atmp > 1.0e-12) {x[i] = atmp; if (idx) idx[i] = aj[j]; break;} 2462 } 2463 if (j == ncols) {x[i] = *aa; if (idx) idx[i] = *aj;} 2464 } else { 2465 x[i] = 0.0; if (idx) idx[i] = 0; 2466 } 2467 for(j = 0; j < ncols; j++) { 2468 atmp = PetscAbsScalar(*aa); 2469 if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} 2470 aa++; aj++; 2471 } 2472 } 2473 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2474 PetscFunctionReturn(0); 2475 } 2476 2477 #undef __FUNCT__ 2478 #define __FUNCT__ "MatGetRowMin_SeqAIJ" 2479 PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) 2480 { 2481 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 2482 PetscErrorCode ierr; 2483 PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; 2484 PetscScalar *x; 2485 MatScalar *aa; 2486 2487 PetscFunctionBegin; 2488 if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2489 aa = a->a; 2490 ai = a->i; 2491 aj = a->j; 2492 2493 ierr = VecSet(v,0.0);CHKERRQ(ierr); 2494 ierr = VecGetArray(v,&x);CHKERRQ(ierr); 2495 ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); 2496 if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); 2497 for (i=0; i<m; i++) { 2498 ncols = ai[1] - ai[0]; ai++; 2499 if (ncols == A->cmap->n) { /* row is dense */ 2500 x[i] = *aa; if (idx) idx[i] = 0; 2501 } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ 2502 x[i] = 0.0; 2503 if (idx) { /* find first implicit 0.0 in the row */ 2504 idx[i] = 0; /* in case ncols is zero */ 2505 for (j=0;j<ncols;j++) { 2506 if (aj[j] > j) { 2507 idx[i] = j; 2508 break; 2509 } 2510 } 2511 } 2512 } 2513 for (j=0; j<ncols; j++){ 2514 if (PetscRealPart(x[i]) > PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} 2515 aa++; aj++; 2516 } 2517 } 2518 ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); 2519 PetscFunctionReturn(0); 2520 } 2521 extern PetscErrorCode PETSCMAT_DLLEXPORT MatFDColoringApply_AIJ(Mat,MatFDColoring,Vec,MatStructure*,void*); 2522 /* -------------------------------------------------------------------*/ 2523 static struct _MatOps MatOps_Values = {MatSetValues_SeqAIJ, 2524 MatGetRow_SeqAIJ, 2525 MatRestoreRow_SeqAIJ, 2526 MatMult_SeqAIJ, 2527 /* 4*/ MatMultAdd_SeqAIJ, 2528 MatMultTranspose_SeqAIJ, 2529 MatMultTransposeAdd_SeqAIJ, 2530 0, 2531 0, 2532 0, 2533 /*10*/ 0, 2534 MatLUFactor_SeqAIJ, 2535 0, 2536 MatSOR_SeqAIJ, 2537 MatTranspose_SeqAIJ, 2538 /*15*/ MatGetInfo_SeqAIJ, 2539 MatEqual_SeqAIJ, 2540 MatGetDiagonal_SeqAIJ, 2541 MatDiagonalScale_SeqAIJ, 2542 MatNorm_SeqAIJ, 2543 /*20*/ 0, 2544 MatAssemblyEnd_SeqAIJ, 2545 MatSetOption_SeqAIJ, 2546 MatZeroEntries_SeqAIJ, 2547 /*24*/ MatZeroRows_SeqAIJ, 2548 0, 2549 0, 2550 0, 2551 0, 2552 /*29*/ MatSetUpPreallocation_SeqAIJ, 2553 0, 2554 0, 2555 MatGetArray_SeqAIJ, 2556 MatRestoreArray_SeqAIJ, 2557 /*34*/ MatDuplicate_SeqAIJ, 2558 0, 2559 0, 2560 MatILUFactor_SeqAIJ, 2561 0, 2562 /*39*/ MatAXPY_SeqAIJ, 2563 MatGetSubMatrices_SeqAIJ, 2564 MatIncreaseOverlap_SeqAIJ, 2565 MatGetValues_SeqAIJ, 2566 MatCopy_SeqAIJ, 2567 /*44*/ MatGetRowMax_SeqAIJ, 2568 MatScale_SeqAIJ, 2569 0, 2570 MatDiagonalSet_SeqAIJ, 2571 0, 2572 /*49*/ MatSetBlockSize_SeqAIJ, 2573 MatGetRowIJ_SeqAIJ, 2574 MatRestoreRowIJ_SeqAIJ, 2575 MatGetColumnIJ_SeqAIJ, 2576 MatRestoreColumnIJ_SeqAIJ, 2577 /*54*/ MatFDColoringCreate_SeqAIJ, 2578 0, 2579 0, 2580 MatPermute_SeqAIJ, 2581 0, 2582 /*59*/ 0, 2583 MatDestroy_SeqAIJ, 2584 MatView_SeqAIJ, 2585 0, 2586 0, 2587 /*64*/ 0, 2588 0, 2589 0, 2590 0, 2591 0, 2592 /*69*/ MatGetRowMaxAbs_SeqAIJ, 2593 MatGetRowMinAbs_SeqAIJ, 2594 0, 2595 MatSetColoring_SeqAIJ, 2596 #if defined(PETSC_HAVE_ADIC) 2597 MatSetValuesAdic_SeqAIJ, 2598 #else 2599 0, 2600 #endif 2601 /*74*/ MatSetValuesAdifor_SeqAIJ, 2602 MatFDColoringApply_AIJ, 2603 0, 2604 0, 2605 0, 2606 /*79*/ 0, 2607 0, 2608 0, 2609 0, 2610 MatLoad_SeqAIJ, 2611 /*84*/ MatIsSymmetric_SeqAIJ, 2612 MatIsHermitian_SeqAIJ, 2613 0, 2614 0, 2615 0, 2616 /*89*/ MatMatMult_SeqAIJ_SeqAIJ, 2617 MatMatMultSymbolic_SeqAIJ_SeqAIJ, 2618 MatMatMultNumeric_SeqAIJ_SeqAIJ, 2619 MatPtAP_Basic, 2620 MatPtAPSymbolic_SeqAIJ, 2621 /*94*/ MatPtAPNumeric_SeqAIJ, 2622 MatMatMultTranspose_SeqAIJ_SeqAIJ, 2623 MatMatMultTransposeSymbolic_SeqAIJ_SeqAIJ, 2624 MatMatMultTransposeNumeric_SeqAIJ_SeqAIJ, 2625 MatPtAPSymbolic_SeqAIJ_SeqAIJ, 2626 /*99*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, 2627 0, 2628 0, 2629 MatConjugate_SeqAIJ, 2630 0, 2631 /*104*/MatSetValuesRow_SeqAIJ, 2632 MatRealPart_SeqAIJ, 2633 MatImaginaryPart_SeqAIJ, 2634 0, 2635 0, 2636 /*109*/0, 2637 0, 2638 MatGetRowMin_SeqAIJ, 2639 0, 2640 MatMissingDiagonal_SeqAIJ, 2641 /*114*/0, 2642 0, 2643 0, 2644 0, 2645 0, 2646 /*119*/0, 2647 0, 2648 0, 2649 0, 2650 MatGetMultiProcBlock_SeqAIJ 2651 }; 2652 2653 EXTERN_C_BEGIN 2654 #undef __FUNCT__ 2655 #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" 2656 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) 2657 { 2658 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2659 PetscInt i,nz,n; 2660 2661 PetscFunctionBegin; 2662 2663 nz = aij->maxnz; 2664 n = mat->rmap->n; 2665 for (i=0; i<nz; i++) { 2666 aij->j[i] = indices[i]; 2667 } 2668 aij->nz = nz; 2669 for (i=0; i<n; i++) { 2670 aij->ilen[i] = aij->imax[i]; 2671 } 2672 2673 PetscFunctionReturn(0); 2674 } 2675 EXTERN_C_END 2676 2677 #undef __FUNCT__ 2678 #define __FUNCT__ "MatSeqAIJSetColumnIndices" 2679 /*@ 2680 MatSeqAIJSetColumnIndices - Set the column indices for all the rows 2681 in the matrix. 2682 2683 Input Parameters: 2684 + mat - the SeqAIJ matrix 2685 - indices - the column indices 2686 2687 Level: advanced 2688 2689 Notes: 2690 This can be called if you have precomputed the nonzero structure of the 2691 matrix and want to provide it to the matrix object to improve the performance 2692 of the MatSetValues() operation. 2693 2694 You MUST have set the correct numbers of nonzeros per row in the call to 2695 MatCreateSeqAIJ(), and the columns indices MUST be sorted. 2696 2697 MUST be called before any calls to MatSetValues(); 2698 2699 The indices should start with zero, not one. 2700 2701 @*/ 2702 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) 2703 { 2704 PetscErrorCode ierr,(*f)(Mat,PetscInt *); 2705 2706 PetscFunctionBegin; 2707 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2708 PetscValidPointer(indices,2); 2709 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatSeqAIJSetColumnIndices_C",(void (**)(void))&f);CHKERRQ(ierr); 2710 if (f) { 2711 ierr = (*f)(mat,indices);CHKERRQ(ierr); 2712 } else { 2713 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to set column indices"); 2714 } 2715 PetscFunctionReturn(0); 2716 } 2717 2718 /* ----------------------------------------------------------------------------------------*/ 2719 2720 EXTERN_C_BEGIN 2721 #undef __FUNCT__ 2722 #define __FUNCT__ "MatStoreValues_SeqAIJ" 2723 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues_SeqAIJ(Mat mat) 2724 { 2725 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2726 PetscErrorCode ierr; 2727 size_t nz = aij->i[mat->rmap->n]; 2728 2729 PetscFunctionBegin; 2730 if (aij->nonew != 1) { 2731 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2732 } 2733 2734 /* allocate space for values if not already there */ 2735 if (!aij->saved_values) { 2736 ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&aij->saved_values);CHKERRQ(ierr); 2737 ierr = PetscLogObjectMemory(mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); 2738 } 2739 2740 /* copy values over */ 2741 ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2742 PetscFunctionReturn(0); 2743 } 2744 EXTERN_C_END 2745 2746 #undef __FUNCT__ 2747 #define __FUNCT__ "MatStoreValues" 2748 /*@ 2749 MatStoreValues - Stashes a copy of the matrix values; this allows, for 2750 example, reuse of the linear part of a Jacobian, while recomputing the 2751 nonlinear portion. 2752 2753 Collect on Mat 2754 2755 Input Parameters: 2756 . mat - the matrix (currently only AIJ matrices support this option) 2757 2758 Level: advanced 2759 2760 Common Usage, with SNESSolve(): 2761 $ Create Jacobian matrix 2762 $ Set linear terms into matrix 2763 $ Apply boundary conditions to matrix, at this time matrix must have 2764 $ final nonzero structure (i.e. setting the nonlinear terms and applying 2765 $ boundary conditions again will not change the nonzero structure 2766 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 2767 $ ierr = MatStoreValues(mat); 2768 $ Call SNESSetJacobian() with matrix 2769 $ In your Jacobian routine 2770 $ ierr = MatRetrieveValues(mat); 2771 $ Set nonlinear terms in matrix 2772 2773 Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: 2774 $ // build linear portion of Jacobian 2775 $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); 2776 $ ierr = MatStoreValues(mat); 2777 $ loop over nonlinear iterations 2778 $ ierr = MatRetrieveValues(mat); 2779 $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian 2780 $ // call MatAssemblyBegin/End() on matrix 2781 $ Solve linear system with Jacobian 2782 $ endloop 2783 2784 Notes: 2785 Matrix must already be assemblied before calling this routine 2786 Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before 2787 calling this routine. 2788 2789 When this is called multiple times it overwrites the previous set of stored values 2790 and does not allocated additional space. 2791 2792 .seealso: MatRetrieveValues() 2793 2794 @*/ 2795 PetscErrorCode PETSCMAT_DLLEXPORT MatStoreValues(Mat mat) 2796 { 2797 PetscErrorCode ierr,(*f)(Mat); 2798 2799 PetscFunctionBegin; 2800 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2801 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 2802 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2803 2804 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatStoreValues_C",(void (**)(void))&f);CHKERRQ(ierr); 2805 if (f) { 2806 ierr = (*f)(mat);CHKERRQ(ierr); 2807 } else { 2808 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to store values"); 2809 } 2810 PetscFunctionReturn(0); 2811 } 2812 2813 EXTERN_C_BEGIN 2814 #undef __FUNCT__ 2815 #define __FUNCT__ "MatRetrieveValues_SeqAIJ" 2816 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues_SeqAIJ(Mat mat) 2817 { 2818 Mat_SeqAIJ *aij = (Mat_SeqAIJ *)mat->data; 2819 PetscErrorCode ierr; 2820 PetscInt nz = aij->i[mat->rmap->n]; 2821 2822 PetscFunctionBegin; 2823 if (aij->nonew != 1) { 2824 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); 2825 } 2826 if (!aij->saved_values) { 2827 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); 2828 } 2829 /* copy values over */ 2830 ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); 2831 PetscFunctionReturn(0); 2832 } 2833 EXTERN_C_END 2834 2835 #undef __FUNCT__ 2836 #define __FUNCT__ "MatRetrieveValues" 2837 /*@ 2838 MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for 2839 example, reuse of the linear part of a Jacobian, while recomputing the 2840 nonlinear portion. 2841 2842 Collect on Mat 2843 2844 Input Parameters: 2845 . mat - the matrix (currently on AIJ matrices support this option) 2846 2847 Level: advanced 2848 2849 .seealso: MatStoreValues() 2850 2851 @*/ 2852 PetscErrorCode PETSCMAT_DLLEXPORT MatRetrieveValues(Mat mat) 2853 { 2854 PetscErrorCode ierr,(*f)(Mat); 2855 2856 PetscFunctionBegin; 2857 PetscValidHeaderSpecific(mat,MAT_CLASSID,1); 2858 if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); 2859 if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); 2860 2861 ierr = PetscObjectQueryFunction((PetscObject)mat,"MatRetrieveValues_C",(void (**)(void))&f);CHKERRQ(ierr); 2862 if (f) { 2863 ierr = (*f)(mat);CHKERRQ(ierr); 2864 } else { 2865 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Wrong type of matrix to retrieve values"); 2866 } 2867 PetscFunctionReturn(0); 2868 } 2869 2870 2871 /* --------------------------------------------------------------------------------*/ 2872 #undef __FUNCT__ 2873 #define __FUNCT__ "MatCreateSeqAIJ" 2874 /*@C 2875 MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format 2876 (the default parallel PETSc format). For good matrix assembly performance 2877 the user should preallocate the matrix storage by setting the parameter nz 2878 (or the array nnz). By setting these parameters accurately, performance 2879 during matrix assembly can be increased by more than a factor of 50. 2880 2881 Collective on MPI_Comm 2882 2883 Input Parameters: 2884 + comm - MPI communicator, set to PETSC_COMM_SELF 2885 . m - number of rows 2886 . n - number of columns 2887 . nz - number of nonzeros per row (same for all rows) 2888 - nnz - array containing the number of nonzeros in the various rows 2889 (possibly different for each row) or PETSC_NULL 2890 2891 Output Parameter: 2892 . A - the matrix 2893 2894 It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), 2895 MatXXXXSetPreallocation() paradgm instead of this routine directly. 2896 [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] 2897 2898 Notes: 2899 If nnz is given then nz is ignored 2900 2901 The AIJ format (also called the Yale sparse matrix format or 2902 compressed row storage), is fully compatible with standard Fortran 77 2903 storage. That is, the stored row and column indices can begin at 2904 either one (as in Fortran) or zero. See the users' manual for details. 2905 2906 Specify the preallocated storage with either nz or nnz (not both). 2907 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2908 allocation. For large problems you MUST preallocate memory or you 2909 will get TERRIBLE performance, see the users' manual chapter on matrices. 2910 2911 By default, this format uses inodes (identical nodes) when possible, to 2912 improve numerical efficiency of matrix-vector products and solves. We 2913 search for consecutive rows with the same nonzero structure, thereby 2914 reusing matrix information to achieve increased efficiency. 2915 2916 Options Database Keys: 2917 + -mat_no_inode - Do not use inodes 2918 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 2919 2920 Level: intermediate 2921 2922 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() 2923 2924 @*/ 2925 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) 2926 { 2927 PetscErrorCode ierr; 2928 2929 PetscFunctionBegin; 2930 ierr = MatCreate(comm,A);CHKERRQ(ierr); 2931 ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); 2932 ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); 2933 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); 2934 PetscFunctionReturn(0); 2935 } 2936 2937 #undef __FUNCT__ 2938 #define __FUNCT__ "MatSeqAIJSetPreallocation" 2939 /*@C 2940 MatSeqAIJSetPreallocation - For good matrix assembly performance 2941 the user should preallocate the matrix storage by setting the parameter nz 2942 (or the array nnz). By setting these parameters accurately, performance 2943 during matrix assembly can be increased by more than a factor of 50. 2944 2945 Collective on MPI_Comm 2946 2947 Input Parameters: 2948 + B - The matrix-free 2949 . nz - number of nonzeros per row (same for all rows) 2950 - nnz - array containing the number of nonzeros in the various rows 2951 (possibly different for each row) or PETSC_NULL 2952 2953 Notes: 2954 If nnz is given then nz is ignored 2955 2956 The AIJ format (also called the Yale sparse matrix format or 2957 compressed row storage), is fully compatible with standard Fortran 77 2958 storage. That is, the stored row and column indices can begin at 2959 either one (as in Fortran) or zero. See the users' manual for details. 2960 2961 Specify the preallocated storage with either nz or nnz (not both). 2962 Set nz=PETSC_DEFAULT and nnz=PETSC_NULL for PETSc to control dynamic memory 2963 allocation. For large problems you MUST preallocate memory or you 2964 will get TERRIBLE performance, see the users' manual chapter on matrices. 2965 2966 You can call MatGetInfo() to get information on how effective the preallocation was; 2967 for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; 2968 You can also run with the option -info and look for messages with the string 2969 malloc in them to see if additional memory allocation was needed. 2970 2971 Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix 2972 entries or columns indices 2973 2974 By default, this format uses inodes (identical nodes) when possible, to 2975 improve numerical efficiency of matrix-vector products and solves. We 2976 search for consecutive rows with the same nonzero structure, thereby 2977 reusing matrix information to achieve increased efficiency. 2978 2979 Options Database Keys: 2980 + -mat_no_inode - Do not use inodes 2981 . -mat_inode_limit <limit> - Sets inode limit (max limit=5) 2982 - -mat_aij_oneindex - Internally use indexing starting at 1 2983 rather than 0. Note that when calling MatSetValues(), 2984 the user still MUST index entries starting at 0! 2985 2986 Level: intermediate 2987 2988 .seealso: MatCreate(), MatCreateMPIAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() 2989 2990 @*/ 2991 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) 2992 { 2993 PetscErrorCode ierr,(*f)(Mat,PetscInt,const PetscInt[]); 2994 2995 PetscFunctionBegin; 2996 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",(void (**)(void))&f);CHKERRQ(ierr); 2997 if (f) { 2998 ierr = (*f)(B,nz,nnz);CHKERRQ(ierr); 2999 } 3000 PetscFunctionReturn(0); 3001 } 3002 3003 EXTERN_C_BEGIN 3004 #undef __FUNCT__ 3005 #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" 3006 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) 3007 { 3008 Mat_SeqAIJ *b; 3009 PetscTruth skipallocation = PETSC_FALSE; 3010 PetscErrorCode ierr; 3011 PetscInt i; 3012 3013 PetscFunctionBegin; 3014 3015 if (nz == MAT_SKIP_ALLOCATION) { 3016 skipallocation = PETSC_TRUE; 3017 nz = 0; 3018 } 3019 3020 ierr = PetscLayoutSetBlockSize(B->rmap,1);CHKERRQ(ierr); 3021 ierr = PetscLayoutSetBlockSize(B->cmap,1);CHKERRQ(ierr); 3022 ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); 3023 ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); 3024 3025 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; 3026 if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %d",nz); 3027 if (nnz) { 3028 for (i=0; i<B->rmap->n; i++) { 3029 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]); 3030 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); 3031 } 3032 } 3033 3034 B->preallocated = PETSC_TRUE; 3035 b = (Mat_SeqAIJ*)B->data; 3036 3037 if (!skipallocation) { 3038 if (!b->imax) { 3039 ierr = PetscMalloc2(B->rmap->n,PetscInt,&b->imax,B->rmap->n,PetscInt,&b->ilen);CHKERRQ(ierr); 3040 ierr = PetscLogObjectMemory(B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); 3041 } 3042 if (!nnz) { 3043 if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; 3044 else if (nz < 0) nz = 1; 3045 for (i=0; i<B->rmap->n; i++) b->imax[i] = nz; 3046 nz = nz*B->rmap->n; 3047 } else { 3048 nz = 0; 3049 for (i=0; i<B->rmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} 3050 } 3051 /* b->ilen will count nonzeros in each row so far. */ 3052 for (i=0; i<B->rmap->n; i++) { b->ilen[i] = 0; } 3053 3054 /* allocate the matrix space */ 3055 ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); 3056 ierr = PetscMalloc3(nz,PetscScalar,&b->a,nz,PetscInt,&b->j,B->rmap->n+1,PetscInt,&b->i);CHKERRQ(ierr); 3057 ierr = PetscLogObjectMemory(B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); 3058 b->i[0] = 0; 3059 for (i=1; i<B->rmap->n+1; i++) { 3060 b->i[i] = b->i[i-1] + b->imax[i-1]; 3061 } 3062 b->singlemalloc = PETSC_TRUE; 3063 b->free_a = PETSC_TRUE; 3064 b->free_ij = PETSC_TRUE; 3065 } else { 3066 b->free_a = PETSC_FALSE; 3067 b->free_ij = PETSC_FALSE; 3068 } 3069 3070 b->nz = 0; 3071 b->maxnz = nz; 3072 B->info.nz_unneeded = (double)b->maxnz; 3073 PetscFunctionReturn(0); 3074 } 3075 EXTERN_C_END 3076 3077 #undef __FUNCT__ 3078 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" 3079 /*@ 3080 MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. 3081 3082 Input Parameters: 3083 + B - the matrix 3084 . i - the indices into j for the start of each row (starts with zero) 3085 . j - the column indices for each row (starts with zero) these must be sorted for each row 3086 - v - optional values in the matrix 3087 3088 Level: developer 3089 3090 The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() 3091 3092 .keywords: matrix, aij, compressed row, sparse, sequential 3093 3094 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ 3095 @*/ 3096 PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) 3097 { 3098 PetscErrorCode (*f)(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]); 3099 PetscErrorCode ierr; 3100 3101 PetscFunctionBegin; 3102 PetscValidHeaderSpecific(B,MAT_CLASSID,1); 3103 ierr = PetscObjectQueryFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",(void (**)(void))&f);CHKERRQ(ierr); 3104 if (f) { 3105 ierr = (*f)(B,i,j,v);CHKERRQ(ierr); 3106 } 3107 PetscFunctionReturn(0); 3108 } 3109 3110 EXTERN_C_BEGIN 3111 #undef __FUNCT__ 3112 #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" 3113 PetscErrorCode PETSCMAT_DLLEXPORT MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) 3114 { 3115 PetscInt i; 3116 PetscInt m,n; 3117 PetscInt nz; 3118 PetscInt *nnz, nz_max = 0; 3119 PetscScalar *values; 3120 PetscErrorCode ierr; 3121 3122 PetscFunctionBegin; 3123 ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); 3124 3125 if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); 3126 ierr = PetscMalloc((m+1) * sizeof(PetscInt), &nnz);CHKERRQ(ierr); 3127 for(i = 0; i < m; i++) { 3128 nz = Ii[i+1]- Ii[i]; 3129 nz_max = PetscMax(nz_max, nz); 3130 if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); 3131 nnz[i] = nz; 3132 } 3133 ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); 3134 ierr = PetscFree(nnz);CHKERRQ(ierr); 3135 3136 if (v) { 3137 values = (PetscScalar*) v; 3138 } else { 3139 ierr = PetscMalloc(nz_max*sizeof(PetscScalar), &values);CHKERRQ(ierr); 3140 ierr = PetscMemzero(values, nz_max*sizeof(PetscScalar));CHKERRQ(ierr); 3141 } 3142 3143 for(i = 0; i < m; i++) { 3144 nz = Ii[i+1] - Ii[i]; 3145 ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); 3146 } 3147 3148 ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3149 ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3150 3151 if (!v) { 3152 ierr = PetscFree(values);CHKERRQ(ierr); 3153 } 3154 PetscFunctionReturn(0); 3155 } 3156 EXTERN_C_END 3157 3158 #include "../src/mat/impls/dense/seq/dense.h" 3159 #include "private/petscaxpy.h" 3160 3161 #undef __FUNCT__ 3162 #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" 3163 /* 3164 Computes (B'*A')' since computing B*A directly is untenable 3165 3166 n p p 3167 ( ) ( ) ( ) 3168 m ( A ) * n ( B ) = m ( C ) 3169 ( ) ( ) ( ) 3170 3171 */ 3172 PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) 3173 { 3174 PetscErrorCode ierr; 3175 Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; 3176 Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; 3177 Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; 3178 PetscInt i,n,m,q,p; 3179 const PetscInt *ii,*idx; 3180 const PetscScalar *b,*a,*a_q; 3181 PetscScalar *c,*c_q; 3182 3183 PetscFunctionBegin; 3184 m = A->rmap->n; 3185 n = A->cmap->n; 3186 p = B->cmap->n; 3187 a = sub_a->v; 3188 b = sub_b->a; 3189 c = sub_c->v; 3190 ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); 3191 3192 ii = sub_b->i; 3193 idx = sub_b->j; 3194 for (i=0; i<n; i++) { 3195 q = ii[i+1] - ii[i]; 3196 while (q-->0) { 3197 c_q = c + m*(*idx); 3198 a_q = a + m*i; 3199 PetscAXPY(c_q,*b,a_q,m); 3200 idx++; 3201 b++; 3202 } 3203 } 3204 PetscFunctionReturn(0); 3205 } 3206 3207 #undef __FUNCT__ 3208 #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" 3209 PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) 3210 { 3211 PetscErrorCode ierr; 3212 PetscInt m=A->rmap->n,n=B->cmap->n; 3213 Mat Cmat; 3214 3215 PetscFunctionBegin; 3216 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); 3217 ierr = MatCreate(((PetscObject)A)->comm,&Cmat);CHKERRQ(ierr); 3218 ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); 3219 ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); 3220 ierr = MatSeqDenseSetPreallocation(Cmat,PETSC_NULL);CHKERRQ(ierr); 3221 Cmat->assembled = PETSC_TRUE; 3222 *C = Cmat; 3223 PetscFunctionReturn(0); 3224 } 3225 3226 /* ----------------------------------------------------------------*/ 3227 #undef __FUNCT__ 3228 #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" 3229 PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) 3230 { 3231 PetscErrorCode ierr; 3232 3233 PetscFunctionBegin; 3234 if (scall == MAT_INITIAL_MATRIX){ 3235 ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); 3236 } 3237 ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); 3238 PetscFunctionReturn(0); 3239 } 3240 3241 3242 /*MC 3243 MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, 3244 based on compressed sparse row format. 3245 3246 Options Database Keys: 3247 . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() 3248 3249 Level: beginner 3250 3251 .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType 3252 M*/ 3253 3254 EXTERN_C_BEGIN 3255 #if defined(PETSC_HAVE_PASTIX) 3256 extern PetscErrorCode MatGetFactor_seqaij_pastix(Mat,MatFactorType,Mat*); 3257 #endif 3258 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SCALAR_SINGLE) && !defined(PETSC_USE_SCALAR_MAT_SINGLE) 3259 extern PetscErrorCode MatGetFactor_seqaij_essl(Mat,MatFactorType,Mat *); 3260 #endif 3261 extern PetscErrorCode PETSCMAT_DLLEXPORT MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); 3262 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_petsc(Mat,MatFactorType,Mat*); 3263 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_bas(Mat,MatFactorType,Mat*); 3264 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactorAvailable_seqaij_petsc(Mat,MatFactorType,PetscTruth *); 3265 #if defined(PETSC_HAVE_MUMPS) 3266 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_aij_mumps(Mat,MatFactorType,Mat*); 3267 #endif 3268 #if defined(PETSC_HAVE_SUPERLU) 3269 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_superlu(Mat,MatFactorType,Mat*); 3270 #endif 3271 #if defined(PETSC_HAVE_SUPERLU_DIST) 3272 extern PetscErrorCode MatGetFactor_seqaij_superlu_dist(Mat,MatFactorType,Mat*); 3273 #endif 3274 #if defined(PETSC_HAVE_SPOOLES) 3275 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_spooles(Mat,MatFactorType,Mat*); 3276 #endif 3277 #if defined(PETSC_HAVE_UMFPACK) 3278 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_umfpack(Mat,MatFactorType,Mat*); 3279 #endif 3280 #if defined(PETSC_HAVE_CHOLMOD) 3281 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_cholmod(Mat,MatFactorType,Mat*); 3282 #endif 3283 #if defined(PETSC_HAVE_LUSOL) 3284 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_lusol(Mat,MatFactorType,Mat*); 3285 #endif 3286 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3287 extern PetscErrorCode PETSCMAT_DLLEXPORT MatGetFactor_seqaij_matlab(Mat,MatFactorType,Mat*); 3288 extern PetscErrorCode PETSCMAT_DLLEXPORT MatlabEnginePut_SeqAIJ(PetscObject,void*); 3289 extern PetscErrorCode PETSCMAT_DLLEXPORT MatlabEngineGet_SeqAIJ(PetscObject,void*); 3290 #endif 3291 EXTERN_C_END 3292 3293 3294 EXTERN_C_BEGIN 3295 #undef __FUNCT__ 3296 #define __FUNCT__ "MatCreate_SeqAIJ" 3297 PetscErrorCode PETSCMAT_DLLEXPORT MatCreate_SeqAIJ(Mat B) 3298 { 3299 Mat_SeqAIJ *b; 3300 PetscErrorCode ierr; 3301 PetscMPIInt size; 3302 3303 PetscFunctionBegin; 3304 ierr = MPI_Comm_size(((PetscObject)B)->comm,&size);CHKERRQ(ierr); 3305 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); 3306 3307 ierr = PetscNewLog(B,Mat_SeqAIJ,&b);CHKERRQ(ierr); 3308 B->data = (void*)b; 3309 ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); 3310 B->mapping = 0; 3311 b->row = 0; 3312 b->col = 0; 3313 b->icol = 0; 3314 b->reallocs = 0; 3315 b->ignorezeroentries = PETSC_FALSE; 3316 b->roworiented = PETSC_TRUE; 3317 b->nonew = 0; 3318 b->diag = 0; 3319 b->solve_work = 0; 3320 B->spptr = 0; 3321 b->saved_values = 0; 3322 b->idiag = 0; 3323 b->mdiag = 0; 3324 b->ssor_work = 0; 3325 b->omega = 1.0; 3326 b->fshift = 0.0; 3327 b->idiagvalid = PETSC_FALSE; 3328 b->keepnonzeropattern = PETSC_FALSE; 3329 b->xtoy = 0; 3330 b->XtoY = 0; 3331 b->compressedrow.use = PETSC_FALSE; 3332 b->compressedrow.nrows = B->rmap->n; 3333 b->compressedrow.i = PETSC_NULL; 3334 b->compressedrow.rindex = PETSC_NULL; 3335 b->compressedrow.checked = PETSC_FALSE; 3336 B->same_nonzero = PETSC_FALSE; 3337 3338 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3339 #if defined(PETSC_HAVE_MATLAB_ENGINE) 3340 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_matlab_C", 3341 "MatGetFactor_seqaij_matlab", 3342 MatGetFactor_seqaij_matlab);CHKERRQ(ierr); 3343 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"PetscMatlabEnginePut_C","MatlabEnginePut_SeqAIJ",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); 3344 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"PetscMatlabEngineGet_C","MatlabEngineGet_SeqAIJ",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); 3345 #endif 3346 #if defined(PETSC_HAVE_PASTIX) 3347 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_pastix_C", 3348 "MatGetFactor_seqaij_pastix", 3349 MatGetFactor_seqaij_pastix);CHKERRQ(ierr); 3350 #endif 3351 #if defined(PETSC_HAVE_ESSL) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_SCALAR_SINGLE) && !defined(PETSC_USE_SCALAR_MAT_SINGLE) 3352 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_essl_C", 3353 "MatGetFactor_seqaij_essl", 3354 MatGetFactor_seqaij_essl);CHKERRQ(ierr); 3355 #endif 3356 #if defined(PETSC_HAVE_SUPERLU) 3357 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_C", 3358 "MatGetFactor_seqaij_superlu", 3359 MatGetFactor_seqaij_superlu);CHKERRQ(ierr); 3360 #endif 3361 #if defined(PETSC_HAVE_SUPERLU_DIST) 3362 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_superlu_dist_C", 3363 "MatGetFactor_seqaij_superlu_dist", 3364 MatGetFactor_seqaij_superlu_dist);CHKERRQ(ierr); 3365 #endif 3366 #if defined(PETSC_HAVE_SPOOLES) 3367 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_spooles_C", 3368 "MatGetFactor_seqaij_spooles", 3369 MatGetFactor_seqaij_spooles);CHKERRQ(ierr); 3370 #endif 3371 #if defined(PETSC_HAVE_MUMPS) 3372 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_mumps_C", 3373 "MatGetFactor_aij_mumps", 3374 MatGetFactor_aij_mumps);CHKERRQ(ierr); 3375 #endif 3376 #if defined(PETSC_HAVE_UMFPACK) 3377 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_umfpack_C", 3378 "MatGetFactor_seqaij_umfpack", 3379 MatGetFactor_seqaij_umfpack);CHKERRQ(ierr); 3380 #endif 3381 #if defined(PETSC_HAVE_CHOLMOD) 3382 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_cholmod_C", 3383 "MatGetFactor_seqaij_cholmod", 3384 MatGetFactor_seqaij_cholmod);CHKERRQ(ierr); 3385 #endif 3386 #if defined(PETSC_HAVE_LUSOL) 3387 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_lusol_C", 3388 "MatGetFactor_seqaij_lusol", 3389 MatGetFactor_seqaij_lusol);CHKERRQ(ierr); 3390 #endif 3391 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_petsc_C", 3392 "MatGetFactor_seqaij_petsc", 3393 MatGetFactor_seqaij_petsc);CHKERRQ(ierr); 3394 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactorAvailable_petsc_C", 3395 "MatGetFactorAvailable_seqaij_petsc", 3396 MatGetFactorAvailable_seqaij_petsc);CHKERRQ(ierr); 3397 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatGetFactor_bas_C", 3398 "MatGetFactor_seqaij_bas", 3399 MatGetFactor_seqaij_bas); 3400 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetColumnIndices_C", 3401 "MatSeqAIJSetColumnIndices_SeqAIJ", 3402 MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); 3403 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatStoreValues_C", 3404 "MatStoreValues_SeqAIJ", 3405 MatStoreValues_SeqAIJ);CHKERRQ(ierr); 3406 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatRetrieveValues_C", 3407 "MatRetrieveValues_SeqAIJ", 3408 MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); 3409 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqsbaij_C", 3410 "MatConvert_SeqAIJ_SeqSBAIJ", 3411 MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); 3412 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqbaij_C", 3413 "MatConvert_SeqAIJ_SeqBAIJ", 3414 MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); 3415 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqaijperm_C", 3416 "MatConvert_SeqAIJ_SeqAIJPERM", 3417 MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); 3418 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C", 3419 "MatConvert_SeqAIJ_SeqAIJCRL", 3420 MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); 3421 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsTranspose_C", 3422 "MatIsTranspose_SeqAIJ", 3423 MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3424 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatIsHermitianTranspose_C", 3425 "MatIsHermitianTranspose_SeqAIJ", 3426 MatIsTranspose_SeqAIJ);CHKERRQ(ierr); 3427 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetPreallocation_C", 3428 "MatSeqAIJSetPreallocation_SeqAIJ", 3429 MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); 3430 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C", 3431 "MatSeqAIJSetPreallocationCSR_SeqAIJ", 3432 MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); 3433 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatReorderForNonzeroDiagonal_C", 3434 "MatReorderForNonzeroDiagonal_SeqAIJ", 3435 MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); 3436 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMult_seqdense_seqaij_C", 3437 "MatMatMult_SeqDense_SeqAIJ", 3438 MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); 3439 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C", 3440 "MatMatMultSymbolic_SeqDense_SeqAIJ", 3441 MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); 3442 ierr = PetscObjectComposeFunctionDynamic((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C", 3443 "MatMatMultNumeric_SeqDense_SeqAIJ", 3444 MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); 3445 ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); 3446 ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); 3447 PetscFunctionReturn(0); 3448 } 3449 EXTERN_C_END 3450 3451 #undef __FUNCT__ 3452 #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" 3453 /* 3454 Given a matrix generated with MatGetFactor() duplicates all the information in A into B 3455 */ 3456 PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscTruth mallocmatspace) 3457 { 3458 Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; 3459 PetscErrorCode ierr; 3460 PetscInt i,m = A->rmap->n; 3461 3462 PetscFunctionBegin; 3463 c = (Mat_SeqAIJ*)C->data; 3464 3465 C->factortype = A->factortype; 3466 c->row = 0; 3467 c->col = 0; 3468 c->icol = 0; 3469 c->reallocs = 0; 3470 3471 C->assembled = PETSC_TRUE; 3472 3473 ierr = PetscLayoutSetBlockSize(C->rmap,1);CHKERRQ(ierr); 3474 ierr = PetscLayoutSetBlockSize(C->cmap,1);CHKERRQ(ierr); 3475 ierr = PetscLayoutSetUp(C->rmap);CHKERRQ(ierr); 3476 ierr = PetscLayoutSetUp(C->cmap);CHKERRQ(ierr); 3477 3478 ierr = PetscMalloc2(m,PetscInt,&c->imax,m,PetscInt,&c->ilen);CHKERRQ(ierr); 3479 ierr = PetscLogObjectMemory(C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); 3480 for (i=0; i<m; i++) { 3481 c->imax[i] = a->imax[i]; 3482 c->ilen[i] = a->ilen[i]; 3483 } 3484 3485 /* allocate the matrix space */ 3486 if (mallocmatspace){ 3487 ierr = PetscMalloc3(a->i[m],PetscScalar,&c->a,a->i[m],PetscInt,&c->j,m+1,PetscInt,&c->i);CHKERRQ(ierr); 3488 ierr = PetscLogObjectMemory(C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3489 c->singlemalloc = PETSC_TRUE; 3490 ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3491 if (m > 0) { 3492 ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); 3493 if (cpvalues == MAT_COPY_VALUES) { 3494 ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 3495 } else { 3496 ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); 3497 } 3498 } 3499 } 3500 3501 c->ignorezeroentries = a->ignorezeroentries; 3502 c->roworiented = a->roworiented; 3503 c->nonew = a->nonew; 3504 if (a->diag) { 3505 ierr = PetscMalloc((m+1)*sizeof(PetscInt),&c->diag);CHKERRQ(ierr); 3506 ierr = PetscLogObjectMemory(C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); 3507 for (i=0; i<m; i++) { 3508 c->diag[i] = a->diag[i]; 3509 } 3510 } else c->diag = 0; 3511 c->solve_work = 0; 3512 c->saved_values = 0; 3513 c->idiag = 0; 3514 c->ssor_work = 0; 3515 c->keepnonzeropattern = a->keepnonzeropattern; 3516 c->free_a = PETSC_TRUE; 3517 c->free_ij = PETSC_TRUE; 3518 c->xtoy = 0; 3519 c->XtoY = 0; 3520 3521 c->nz = a->nz; 3522 c->maxnz = a->nz; /* Since we allocate exactly the right amount */ 3523 C->preallocated = PETSC_TRUE; 3524 3525 c->compressedrow.use = a->compressedrow.use; 3526 c->compressedrow.nrows = a->compressedrow.nrows; 3527 c->compressedrow.checked = a->compressedrow.checked; 3528 if (a->compressedrow.checked && a->compressedrow.use){ 3529 i = a->compressedrow.nrows; 3530 ierr = PetscMalloc2(i+1,PetscInt,&c->compressedrow.i,i,PetscInt,&c->compressedrow.rindex);CHKERRQ(ierr); 3531 ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); 3532 ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); 3533 } else { 3534 c->compressedrow.use = PETSC_FALSE; 3535 c->compressedrow.i = PETSC_NULL; 3536 c->compressedrow.rindex = PETSC_NULL; 3537 } 3538 C->same_nonzero = A->same_nonzero; 3539 ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); 3540 3541 ierr = PetscFListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); 3542 PetscFunctionReturn(0); 3543 } 3544 3545 #undef __FUNCT__ 3546 #define __FUNCT__ "MatDuplicate_SeqAIJ" 3547 PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) 3548 { 3549 PetscErrorCode ierr; 3550 3551 PetscFunctionBegin; 3552 ierr = MatCreate(((PetscObject)A)->comm,B);CHKERRQ(ierr); 3553 ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); 3554 ierr = MatSetType(*B,MATSEQAIJ);CHKERRQ(ierr); 3555 ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); 3556 PetscFunctionReturn(0); 3557 } 3558 3559 #undef __FUNCT__ 3560 #define __FUNCT__ "MatLoad_SeqAIJ" 3561 PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) 3562 { 3563 Mat_SeqAIJ *a; 3564 PetscErrorCode ierr; 3565 PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; 3566 int fd; 3567 PetscMPIInt size; 3568 MPI_Comm comm; 3569 3570 PetscFunctionBegin; 3571 ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); 3572 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 3573 if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); 3574 ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); 3575 ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); 3576 if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); 3577 M = header[1]; N = header[2]; nz = header[3]; 3578 3579 if (nz < 0) { 3580 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); 3581 } 3582 3583 /* read in row lengths */ 3584 ierr = PetscMalloc(M*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr); 3585 ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); 3586 3587 /* check if sum of rowlengths is same as nz */ 3588 for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; 3589 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); 3590 3591 /* set global size if not set already*/ 3592 if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { 3593 ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); 3594 } else { 3595 /* if sizes and type are already set, check if the vector global sizes are correct */ 3596 ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); 3597 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); 3598 } 3599 ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); 3600 a = (Mat_SeqAIJ*)newMat->data; 3601 3602 ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); 3603 3604 /* read in nonzero values */ 3605 ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); 3606 3607 /* set matrix "i" values */ 3608 a->i[0] = 0; 3609 for (i=1; i<= M; i++) { 3610 a->i[i] = a->i[i-1] + rowlengths[i-1]; 3611 a->ilen[i-1] = rowlengths[i-1]; 3612 } 3613 ierr = PetscFree(rowlengths);CHKERRQ(ierr); 3614 3615 ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3616 ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3617 PetscFunctionReturn(0); 3618 } 3619 3620 #undef __FUNCT__ 3621 #define __FUNCT__ "MatEqual_SeqAIJ" 3622 PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscTruth* flg) 3623 { 3624 Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data,*b = (Mat_SeqAIJ *)B->data; 3625 PetscErrorCode ierr; 3626 #if defined(PETSC_USE_COMPLEX) 3627 PetscInt k; 3628 #endif 3629 3630 PetscFunctionBegin; 3631 /* If the matrix dimensions are not equal,or no of nonzeros */ 3632 if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { 3633 *flg = PETSC_FALSE; 3634 PetscFunctionReturn(0); 3635 } 3636 3637 /* if the a->i are the same */ 3638 ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); 3639 if (!*flg) PetscFunctionReturn(0); 3640 3641 /* if a->j are the same */ 3642 ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); 3643 if (!*flg) PetscFunctionReturn(0); 3644 3645 /* if a->a are the same */ 3646 #if defined(PETSC_USE_COMPLEX) 3647 for (k=0; k<a->nz; k++){ 3648 if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])){ 3649 *flg = PETSC_FALSE; 3650 PetscFunctionReturn(0); 3651 } 3652 } 3653 #else 3654 ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); 3655 #endif 3656 PetscFunctionReturn(0); 3657 } 3658 3659 #undef __FUNCT__ 3660 #define __FUNCT__ "MatCreateSeqAIJWithArrays" 3661 /*@ 3662 MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) 3663 provided by the user. 3664 3665 Collective on MPI_Comm 3666 3667 Input Parameters: 3668 + comm - must be an MPI communicator of size 1 3669 . m - number of rows 3670 . n - number of columns 3671 . i - row indices 3672 . j - column indices 3673 - a - matrix values 3674 3675 Output Parameter: 3676 . mat - the matrix 3677 3678 Level: intermediate 3679 3680 Notes: 3681 The i, j, and a arrays are not copied by this routine, the user must free these arrays 3682 once the matrix is destroyed 3683 3684 You cannot set new nonzero locations into this matrix, that will generate an error. 3685 3686 The i and j indices are 0 based 3687 3688 The format which is used for the sparse matrix input, is equivalent to a 3689 row-major ordering.. i.e for the following matrix, the input data expected is 3690 as shown: 3691 3692 1 0 0 3693 2 0 3 3694 4 5 6 3695 3696 i = {0,1,3,6} [size = nrow+1 = 3+1] 3697 j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row 3698 v = {1,2,3,4,5,6} [size = nz = 6] 3699 3700 3701 .seealso: MatCreate(), MatCreateMPIAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() 3702 3703 @*/ 3704 PetscErrorCode PETSCMAT_DLLEXPORT MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt* i,PetscInt*j,PetscScalar *a,Mat *mat) 3705 { 3706 PetscErrorCode ierr; 3707 PetscInt ii; 3708 Mat_SeqAIJ *aij; 3709 #if defined(PETSC_USE_DEBUG) 3710 PetscInt jj; 3711 #endif 3712 3713 PetscFunctionBegin; 3714 if (i[0]) { 3715 SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); 3716 } 3717 ierr = MatCreate(comm,mat);CHKERRQ(ierr); 3718 ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); 3719 ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); 3720 ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); 3721 aij = (Mat_SeqAIJ*)(*mat)->data; 3722 ierr = PetscMalloc2(m,PetscInt,&aij->imax,m,PetscInt,&aij->ilen);CHKERRQ(ierr); 3723 3724 aij->i = i; 3725 aij->j = j; 3726 aij->a = a; 3727 aij->singlemalloc = PETSC_FALSE; 3728 aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ 3729 aij->free_a = PETSC_FALSE; 3730 aij->free_ij = PETSC_FALSE; 3731 3732 for (ii=0; ii<m; ii++) { 3733 aij->ilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; 3734 #if defined(PETSC_USE_DEBUG) 3735 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]); 3736 for (jj=i[ii]+1; jj<i[ii+1]; jj++) { 3737 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); 3738 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); 3739 } 3740 #endif 3741 } 3742 #if defined(PETSC_USE_DEBUG) 3743 for (ii=0; ii<aij->i[m]; ii++) { 3744 if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]); 3745 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]); 3746 } 3747 #endif 3748 3749 ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3750 ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); 3751 PetscFunctionReturn(0); 3752 } 3753 3754 #undef __FUNCT__ 3755 #define __FUNCT__ "MatSetColoring_SeqAIJ" 3756 PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) 3757 { 3758 PetscErrorCode ierr; 3759 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3760 3761 PetscFunctionBegin; 3762 if (coloring->ctype == IS_COLORING_GLOBAL) { 3763 ierr = ISColoringReference(coloring);CHKERRQ(ierr); 3764 a->coloring = coloring; 3765 } else if (coloring->ctype == IS_COLORING_GHOSTED) { 3766 PetscInt i,*larray; 3767 ISColoring ocoloring; 3768 ISColoringValue *colors; 3769 3770 /* set coloring for diagonal portion */ 3771 ierr = PetscMalloc(A->cmap->n*sizeof(PetscInt),&larray);CHKERRQ(ierr); 3772 for (i=0; i<A->cmap->n; i++) { 3773 larray[i] = i; 3774 } 3775 ierr = ISGlobalToLocalMappingApply(A->mapping,IS_GTOLM_MASK,A->cmap->n,larray,PETSC_NULL,larray);CHKERRQ(ierr); 3776 ierr = PetscMalloc(A->cmap->n*sizeof(ISColoringValue),&colors);CHKERRQ(ierr); 3777 for (i=0; i<A->cmap->n; i++) { 3778 colors[i] = coloring->colors[larray[i]]; 3779 } 3780 ierr = PetscFree(larray);CHKERRQ(ierr); 3781 ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,&ocoloring);CHKERRQ(ierr); 3782 a->coloring = ocoloring; 3783 } 3784 PetscFunctionReturn(0); 3785 } 3786 3787 #if defined(PETSC_HAVE_ADIC) 3788 EXTERN_C_BEGIN 3789 #include "adic/ad_utils.h" 3790 EXTERN_C_END 3791 3792 #undef __FUNCT__ 3793 #define __FUNCT__ "MatSetValuesAdic_SeqAIJ" 3794 PetscErrorCode MatSetValuesAdic_SeqAIJ(Mat A,void *advalues) 3795 { 3796 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3797 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j,nlen; 3798 PetscScalar *v = a->a,*values = ((PetscScalar*)advalues)+1; 3799 ISColoringValue *color; 3800 3801 PetscFunctionBegin; 3802 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 3803 nlen = PetscADGetDerivTypeSize()/sizeof(PetscScalar); 3804 color = a->coloring->colors; 3805 /* loop over rows */ 3806 for (i=0; i<m; i++) { 3807 nz = ii[i+1] - ii[i]; 3808 /* loop over columns putting computed value into matrix */ 3809 for (j=0; j<nz; j++) { 3810 *v++ = values[color[*jj++]]; 3811 } 3812 values += nlen; /* jump to next row of derivatives */ 3813 } 3814 PetscFunctionReturn(0); 3815 } 3816 #endif 3817 3818 #undef __FUNCT__ 3819 #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" 3820 PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) 3821 { 3822 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3823 PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; 3824 MatScalar *v = a->a; 3825 PetscScalar *values = (PetscScalar *)advalues; 3826 ISColoringValue *color; 3827 3828 PetscFunctionBegin; 3829 if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); 3830 color = a->coloring->colors; 3831 /* loop over rows */ 3832 for (i=0; i<m; i++) { 3833 nz = ii[i+1] - ii[i]; 3834 /* loop over columns putting computed value into matrix */ 3835 for (j=0; j<nz; j++) { 3836 *v++ = values[color[*jj++]]; 3837 } 3838 values += nl; /* jump to next row of derivatives */ 3839 } 3840 PetscFunctionReturn(0); 3841 } 3842 3843 /* 3844 Special version for direct calls from Fortran 3845 */ 3846 #if defined(PETSC_HAVE_FORTRAN_CAPS) 3847 #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ 3848 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) 3849 #define matsetvaluesseqaij_ matsetvaluesseqaij 3850 #endif 3851 3852 /* Change these macros so can be used in void function */ 3853 #undef CHKERRQ 3854 #define CHKERRQ(ierr) CHKERRABORT(((PetscObject)A)->comm,ierr) 3855 #undef SETERRQ2 3856 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) 3857 3858 EXTERN_C_BEGIN 3859 #undef __FUNCT__ 3860 #define __FUNCT__ "matsetvaluesseqaij_" 3861 void PETSC_STDCALL matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) 3862 { 3863 Mat A = *AA; 3864 PetscInt m = *mm, n = *nn; 3865 InsertMode is = *isis; 3866 Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; 3867 PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; 3868 PetscInt *imax,*ai,*ailen; 3869 PetscErrorCode ierr; 3870 PetscInt *aj,nonew = a->nonew,lastcol = -1; 3871 MatScalar *ap,value,*aa; 3872 PetscTruth ignorezeroentries = a->ignorezeroentries; 3873 PetscTruth roworiented = a->roworiented; 3874 3875 PetscFunctionBegin; 3876 ierr = MatPreallocated(A);CHKERRQ(ierr); 3877 imax = a->imax; 3878 ai = a->i; 3879 ailen = a->ilen; 3880 aj = a->j; 3881 aa = a->a; 3882 3883 for (k=0; k<m; k++) { /* loop over added rows */ 3884 row = im[k]; 3885 if (row < 0) continue; 3886 #if defined(PETSC_USE_DEBUG) 3887 if (row >= A->rmap->n) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); 3888 #endif 3889 rp = aj + ai[row]; ap = aa + ai[row]; 3890 rmax = imax[row]; nrow = ailen[row]; 3891 low = 0; 3892 high = nrow; 3893 for (l=0; l<n; l++) { /* loop over added columns */ 3894 if (in[l] < 0) continue; 3895 #if defined(PETSC_USE_DEBUG) 3896 if (in[l] >= A->cmap->n) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); 3897 #endif 3898 col = in[l]; 3899 if (roworiented) { 3900 value = v[l + k*n]; 3901 } else { 3902 value = v[k + l*m]; 3903 } 3904 if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; 3905 3906 if (col <= lastcol) low = 0; else high = nrow; 3907 lastcol = col; 3908 while (high-low > 5) { 3909 t = (low+high)/2; 3910 if (rp[t] > col) high = t; 3911 else low = t; 3912 } 3913 for (i=low; i<high; i++) { 3914 if (rp[i] > col) break; 3915 if (rp[i] == col) { 3916 if (is == ADD_VALUES) ap[i] += value; 3917 else ap[i] = value; 3918 goto noinsert; 3919 } 3920 } 3921 if (value == 0.0 && ignorezeroentries) goto noinsert; 3922 if (nonew == 1) goto noinsert; 3923 if (nonew == -1) SETERRABORT(((PetscObject)A)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); 3924 MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); 3925 N = nrow++ - 1; a->nz++; high++; 3926 /* shift up all the later entries in this row */ 3927 for (ii=N; ii>=i; ii--) { 3928 rp[ii+1] = rp[ii]; 3929 ap[ii+1] = ap[ii]; 3930 } 3931 rp[i] = col; 3932 ap[i] = value; 3933 noinsert:; 3934 low = i + 1; 3935 } 3936 ailen[row] = nrow; 3937 } 3938 A->same_nonzero = PETSC_FALSE; 3939 PetscFunctionReturnVoid(); 3940 } 3941 EXTERN_C_END 3942