/* Defines the basic matrix operations for the AIJ (compressed row) matrix storage format. */ #include <../src/mat/impls/aij/seq/aij.h> /*I "petscmat.h" I*/ #include #include #include #undef __FUNCT__ #define __FUNCT__ "MatGetColumnNorms_SeqAIJ" PetscErrorCode MatGetColumnNorms_SeqAIJ(Mat A,NormType type,PetscReal *norms) { PetscErrorCode ierr; PetscInt i,m,n; Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; PetscFunctionBegin; ierr = MatGetSize(A,&m,&n);CHKERRQ(ierr); ierr = PetscMemzero(norms,n*sizeof(PetscReal));CHKERRQ(ierr); if (type == NORM_2) { for (i=0; ii[m]; i++) { norms[aij->j[i]] += PetscAbsScalar(aij->a[i]*aij->a[i]); } } else if (type == NORM_1) { for (i=0; ii[m]; i++) { norms[aij->j[i]] += PetscAbsScalar(aij->a[i]); } } else if (type == NORM_INFINITY) { for (i=0; ii[m]; i++) { norms[aij->j[i]] = PetscMax(PetscAbsScalar(aij->a[i]),norms[aij->j[i]]); } } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown NormType"); if (type == NORM_2) { for (i=0; idata; PetscInt i,m=A->rmap->n,cnt = 0, bs = A->rmap->bs; const PetscInt *jj = a->j,*ii = a->i; PetscInt *rows; PetscErrorCode ierr; PetscFunctionBegin; for (i=0; i bs*((i+bs)/bs)-1))) { cnt++; } } ierr = PetscMalloc1(cnt,&rows);CHKERRQ(ierr); cnt = 0; for (i=0; i bs*((i+bs)/bs)-1))) { rows[cnt] = i; cnt++; } } ierr = ISCreateGeneral(PETSC_COMM_SELF,cnt,rows,PETSC_OWN_POINTER,is);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatFindZeroDiagonals_SeqAIJ_Private" PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat A,PetscInt *nrows,PetscInt **zrows) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; const MatScalar *aa = a->a; PetscInt i,m=A->rmap->n,cnt = 0; const PetscInt *jj = a->j,*diag; PetscInt *rows; PetscErrorCode ierr; PetscFunctionBegin; ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); diag = a->diag; for (i=0; idata; const MatScalar *aa; PetscInt m=A->rmap->n,cnt = 0; const PetscInt *ii; PetscInt n,i,j,*rows; PetscErrorCode ierr; PetscFunctionBegin; *keptrows = 0; ii = a->i; for (i=0; ia + ii[i]; for (j=0; jrmap->n-cnt,&rows);CHKERRQ(ierr); cnt = 0; for (i=0; ia + ii[i]; for (j=0; jdata; PetscInt i,m = Y->rmap->n; const PetscInt *diag; MatScalar *aa = aij->a; const PetscScalar *v; PetscBool missing; PetscFunctionBegin; if (Y->assembled) { ierr = MatMissingDiagonal_SeqAIJ(Y,&missing,NULL);CHKERRQ(ierr); if (!missing) { diag = aij->diag; ierr = VecGetArrayRead(D,&v);CHKERRQ(ierr); if (is == INSERT_VALUES) { for (i=0; idata; PetscErrorCode ierr; PetscInt i,ishift; PetscFunctionBegin; *m = A->rmap->n; if (!ia) PetscFunctionReturn(0); ishift = 0; if (symmetric && !A->structurally_symmetric) { ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,ishift,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); } else if (oshift == 1) { PetscInt *tia; PetscInt nz = a->i[A->rmap->n]; /* malloc space and add 1 to i and j indices */ ierr = PetscMalloc1(A->rmap->n+1,&tia);CHKERRQ(ierr); for (i=0; irmap->n+1; i++) tia[i] = a->i[i] + 1; *ia = tia; if (ja) { PetscInt *tja; ierr = PetscMalloc1(nz+1,&tja);CHKERRQ(ierr); for (i=0; ij[i] + 1; *ja = tja; } } else { *ia = a->i; if (ja) *ja = a->j; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRestoreRowIJ_SeqAIJ" PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) { PetscErrorCode ierr; PetscFunctionBegin; if (!ia) PetscFunctionReturn(0); if ((symmetric && !A->structurally_symmetric) || oshift == 1) { ierr = PetscFree(*ia);CHKERRQ(ierr); if (ja) {ierr = PetscFree(*ja);CHKERRQ(ierr);} } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetColumnIJ_SeqAIJ" PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool *done) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; PetscInt nz = a->i[m],row,*jj,mr,col; PetscFunctionBegin; *nn = n; if (!ia) PetscFunctionReturn(0); if (symmetric) { ierr = MatToSymmetricIJ_SeqAIJ(A->rmap->n,a->i,a->j,0,oshift,(PetscInt**)ia,(PetscInt**)ja);CHKERRQ(ierr); } else { ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); jj = a->j; for (i=0; ij; for (row=0; rowi[row+1] - a->i[row]; for (i=0; ia, to be used in MatTransposeColoringCreate_SeqAIJ() and MatFDColoringCreate_SeqXAIJ() */ #undef __FUNCT__ #define __FUNCT__ "MatGetColumnIJ_SeqAIJ_Color" PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,*collengths,*cia,*cja,n = A->cmap->n,m = A->rmap->n; PetscInt nz = a->i[m],row,*jj,mr,col; PetscInt *cspidx; PetscFunctionBegin; *nn = n; if (!ia) PetscFunctionReturn(0); ierr = PetscCalloc1(n+1,&collengths);CHKERRQ(ierr); ierr = PetscMalloc1(n+1,&cia);CHKERRQ(ierr); ierr = PetscMalloc1(nz+1,&cja);CHKERRQ(ierr); ierr = PetscMalloc1(nz+1,&cspidx);CHKERRQ(ierr); jj = a->j; for (i=0; ij; for (row=0; rowi[row+1] - a->i[row]; for (i=0; ii[row] + i; /* index of a->j */ cja[cia[col] + collengths[col]++ - oshift] = row + oshift; } } ierr = PetscFree(collengths);CHKERRQ(ierr); *ia = cia; *ja = cja; *spidx = cspidx; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRestoreColumnIJ_SeqAIJ_Color" PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool *done) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatRestoreColumnIJ_SeqAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);CHKERRQ(ierr); ierr = PetscFree(*spidx);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetValuesRow_SeqAIJ" PetscErrorCode MatSetValuesRow_SeqAIJ(Mat A,PetscInt row,const PetscScalar v[]) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt *ai = a->i; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscMemcpy(a->a+ai[row],v,(ai[row+1]-ai[row])*sizeof(PetscScalar));CHKERRQ(ierr); PetscFunctionReturn(0); } /* MatSeqAIJSetValuesLocalFast - An optimized version of MatSetValuesLocal() for SeqAIJ matrices with several assumptions - a single row of values is set with each call - no row or column indices are negative or (in error) larger than the number of rows or columns - the values are always added to the matrix, not set - no new locations are introduced in the nonzero structure of the matrix This does NOT assume the global column indices are sorted */ #include #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJSetValuesLocalFast" PetscErrorCode MatSeqAIJSetValuesLocalFast(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt low,high,t,row,nrow,i,col,l; const PetscInt *rp,*ai = a->i,*ailen = a->ilen,*aj = a->j; PetscInt lastcol = -1; MatScalar *ap,value,*aa = a->a; const PetscInt *ridx = A->rmap->mapping->indices,*cidx = A->cmap->mapping->indices; row = ridx[im[0]]; rp = aj + ai[row]; ap = aa + ai[row]; nrow = ailen[row]; low = 0; high = nrow; for (l=0; l 5) { t = (low+high)/2; if (rp[t] > col) high = t; else low = t; } for (i=low; idata; PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; PetscInt *imax = a->imax,*ai = a->i,*ailen = a->ilen; PetscErrorCode ierr; PetscInt *aj = a->j,nonew = a->nonew,lastcol = -1; MatScalar *ap,value,*aa = a->a; PetscBool ignorezeroentries = a->ignorezeroentries; PetscBool roworiented = a->roworiented; PetscFunctionBegin; for (k=0; k= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); #endif rp = aj + ai[row]; ap = aa + ai[row]; rmax = imax[row]; nrow = ailen[row]; low = 0; high = nrow; for (l=0; 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); #endif col = in[l]; if (roworiented) { value = v[l + k*n]; } else { value = v[k + l*m]; } if ((value == 0.0 && ignorezeroentries) && (is == ADD_VALUES)) continue; if (col <= lastcol) low = 0; else high = nrow; lastcol = col; while (high-low > 5) { t = (low+high)/2; if (rp[t] > col) high = t; else low = t; } for (i=low; i col) break; if (rp[i] == col) { if (is == ADD_VALUES) ap[i] += value; else ap[i] = value; low = i + 1; goto noinsert; } } if (value == 0.0 && ignorezeroentries) goto noinsert; if (nonew == 1) goto noinsert; if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at (%D,%D) in the matrix",row,col); MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); N = nrow++ - 1; a->nz++; high++; /* shift up all the later entries in this row */ for (ii=N; ii>=i; ii--) { rp[ii+1] = rp[ii]; ap[ii+1] = ap[ii]; } rp[i] = col; ap[i] = value; low = i + 1; A->nonzerostate++; noinsert:; } ailen[row] = nrow; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetValues_SeqAIJ" PetscErrorCode MatGetValues_SeqAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[]) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j; PetscInt *ai = a->i,*ailen = a->ilen; MatScalar *ap,*aa = a->a; PetscFunctionBegin; for (k=0; k= A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->n-1); rp = aj + ai[row]; ap = aa + ai[row]; nrow = ailen[row]; for (l=0; 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); col = in[l]; high = nrow; low = 0; /* assume unsorted */ while (high-low > 5) { t = (low+high)/2; if (rp[t] > col) high = t; else low = t; } for (i=low; i col) break; if (rp[i] == col) { *v++ = ap[i]; goto finished; } } *v++ = 0.0; finished:; } } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatView_SeqAIJ_Binary" PetscErrorCode MatView_SeqAIJ_Binary(Mat A,PetscViewer viewer) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,*col_lens; int fd; FILE *file; PetscFunctionBegin; ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); ierr = PetscMalloc1(4+A->rmap->n,&col_lens);CHKERRQ(ierr); col_lens[0] = MAT_FILE_CLASSID; col_lens[1] = A->rmap->n; col_lens[2] = A->cmap->n; col_lens[3] = a->nz; /* store lengths of each row and write (including header) to file */ for (i=0; irmap->n; i++) { col_lens[4+i] = a->i[i+1] - a->i[i]; } ierr = PetscBinaryWrite(fd,col_lens,4+A->rmap->n,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr); ierr = PetscFree(col_lens);CHKERRQ(ierr); /* store column indices (zero start index) */ ierr = PetscBinaryWrite(fd,a->j,a->nz,PETSC_INT,PETSC_FALSE);CHKERRQ(ierr); /* store nonzero values */ ierr = PetscBinaryWrite(fd,a->a,a->nz,PETSC_SCALAR,PETSC_FALSE);CHKERRQ(ierr); ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr); if (file) { fprintf(file,"-matload_block_size %d\n",(int)PetscAbs(A->rmap->bs)); } PetscFunctionReturn(0); } extern PetscErrorCode MatSeqAIJFactorInfo_Matlab(Mat,PetscViewer); #undef __FUNCT__ #define __FUNCT__ "MatView_SeqAIJ_ASCII" PetscErrorCode MatView_SeqAIJ_ASCII(Mat A,PetscViewer viewer) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n; const char *name; PetscViewerFormat format; PetscFunctionBegin; ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); if (format == PETSC_VIEWER_ASCII_MATLAB) { PetscInt nofinalvalue = 0; if (m && ((a->i[m] == a->i[m-1]) || (a->j[a->nz-1] != A->cmap->n-1))) { /* Need a dummy value to ensure the dimension of the matrix. */ nofinalvalue = 1; } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer,"%% Size = %D %D \n",m,A->cmap->n);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer,"%% Nonzeros = %D \n",a->nz);CHKERRQ(ierr); #if defined(PETSC_USE_COMPLEX) ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,4);\n",a->nz+nofinalvalue);CHKERRQ(ierr); #else ierr = PetscViewerASCIIPrintf(viewer,"zzz = zeros(%D,3);\n",a->nz+nofinalvalue);CHKERRQ(ierr); #endif ierr = PetscViewerASCIIPrintf(viewer,"zzz = [\n");CHKERRQ(ierr); for (i=0; ii[i]; ji[i+1]; j++) { #if defined(PETSC_USE_COMPLEX) ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",i+1,a->j[j]+1,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); #else ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",i+1,a->j[j]+1,(double)a->a[j]);CHKERRQ(ierr); #endif } } if (nofinalvalue) { #if defined(PETSC_USE_COMPLEX) ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e %18.16e\n",m,A->cmap->n,0.,0.);CHKERRQ(ierr); #else ierr = PetscViewerASCIIPrintf(viewer,"%D %D %18.16e\n",m,A->cmap->n,0.0);CHKERRQ(ierr); #endif } ierr = PetscObjectGetName((PetscObject)A,&name);CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer,"];\n %s = spconvert(zzz);\n",name);CHKERRQ(ierr); ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO || format == PETSC_VIEWER_ASCII_INFO) { PetscFunctionReturn(0); } else if (format == PETSC_VIEWER_ASCII_COMMON) { ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); for (i=0; ii[i]; ji[i+1]; j++) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) > 0.0 && PetscRealPart(a->a[j]) != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[j]) < 0.0 && PetscRealPart(a->a[j]) != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else if (PetscRealPart(a->a[j]) != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); } #else if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr);} #endif } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); } else if (format == PETSC_VIEWER_ASCII_SYMMODU) { PetscInt nzd=0,fshift=1,*sptr; ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); ierr = PetscMalloc1(m+1,&sptr);CHKERRQ(ierr); for (i=0; ii[i]; ji[i+1]; j++) { if (a->j[j] >= i) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) nzd++; #else if (a->a[j] != 0.0) nzd++; #endif } } } sptr[m] = nzd+1; ierr = PetscViewerASCIIPrintf(viewer," %D %D\n\n",m,nzd);CHKERRQ(ierr); for (i=0; ii[i]; ji[i+1]; j++) { if (a->j[j] >= i) {ierr = PetscViewerASCIIPrintf(viewer," %D ",a->j[j]+fshift);CHKERRQ(ierr);} } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); for (i=0; ii[i]; ji[i+1]; j++) { if (a->j[j] >= i) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) != 0.0 || PetscRealPart(a->a[j]) != 0.0) { ierr = PetscViewerASCIIPrintf(viewer," %18.16e %18.16e ",(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } #else if (a->a[j] != 0.0) {ierr = PetscViewerASCIIPrintf(viewer," %18.16e ",(double)a->a[j]);CHKERRQ(ierr);} #endif } } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); } else if (format == PETSC_VIEWER_ASCII_DENSE) { PetscInt cnt = 0,jcnt; PetscScalar value; #if defined(PETSC_USE_COMPLEX) PetscBool realonly = PETSC_TRUE; for (i=0; ii[m]; i++) { if (PetscImaginaryPart(a->a[i]) != 0.0) { realonly = PETSC_FALSE; break; } } #endif ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); for (i=0; icmap->n; j++) { if (jcnt < a->i[i+1]-a->i[i] && j == a->j[cnt]) { value = a->a[cnt++]; jcnt++; } else { value = 0.0; } #if defined(PETSC_USE_COMPLEX) if (realonly) { ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)PetscRealPart(value));CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer," %7.5e+%7.5e i ",(double)PetscRealPart(value),(double)PetscImaginaryPart(value));CHKERRQ(ierr); } #else ierr = PetscViewerASCIIPrintf(viewer," %7.5e ",(double)value);CHKERRQ(ierr); #endif } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); } else if (format == PETSC_VIEWER_ASCII_MATRIXMARKET) { PetscInt fshift=1; ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); #if defined(PETSC_USE_COMPLEX) ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate complex general\n");CHKERRQ(ierr); #else ierr = PetscViewerASCIIPrintf(viewer,"%%%%MatrixMarket matrix coordinate real general\n");CHKERRQ(ierr); #endif ierr = PetscViewerASCIIPrintf(viewer,"%D %D %D\n", m, A->cmap->n, a->nz);CHKERRQ(ierr); for (i=0; ii[i]; ji[i+1]; j++) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) > 0.0) { ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[j]) < 0.0) { ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g -%g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer,"%D %D, %g\n", i+fshift,a->j[j]+fshift,(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); } #else ierr = PetscViewerASCIIPrintf(viewer,"%D %D %g\n", i+fshift, a->j[j]+fshift, (double)a->a[j]);CHKERRQ(ierr); #endif } } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); } else { ierr = PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);CHKERRQ(ierr); if (A->factortype) { for (i=0; ii[i]; ji[i+1]; j++) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) > 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[j]) < 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); } #else ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); #endif } /* diagonal */ j = a->diag[i]; #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) > 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)PetscImaginaryPart(1.0/a->a[j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[j]) < 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(1.0/a->a[j]),(double)(-PetscImaginaryPart(1.0/a->a[j])));CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(1.0/a->a[j]));CHKERRQ(ierr); } #else ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)(1.0/a->a[j]));CHKERRQ(ierr); #endif /* U part */ for (j=a->diag[i+1]+1; jdiag[i]; j++) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) > 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[j]) < 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)(-PetscImaginaryPart(a->a[j])));CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); } #else ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); #endif } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } } else { for (i=0; ii[i]; ji[i+1]; j++) { #if defined(PETSC_USE_COMPLEX) if (PetscImaginaryPart(a->a[j]) > 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g + %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else if (PetscImaginaryPart(a->a[j]) < 0.0) { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g - %g i)",a->j[j],(double)PetscRealPart(a->a[j]),(double)-PetscImaginaryPart(a->a[j]));CHKERRQ(ierr); } else { ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)PetscRealPart(a->a[j]));CHKERRQ(ierr); } #else ierr = PetscViewerASCIIPrintf(viewer," (%D, %g) ",a->j[j],(double)a->a[j]);CHKERRQ(ierr); #endif } ierr = PetscViewerASCIIPrintf(viewer,"\n");CHKERRQ(ierr); } } ierr = PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);CHKERRQ(ierr); } ierr = PetscViewerFlush(viewer);CHKERRQ(ierr); PetscFunctionReturn(0); } #include #undef __FUNCT__ #define __FUNCT__ "MatView_SeqAIJ_Draw_Zoom" PetscErrorCode MatView_SeqAIJ_Draw_Zoom(PetscDraw draw,void *Aa) { Mat A = (Mat) Aa; Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n,color; PetscReal xl,yl,xr,yr,x_l,x_r,y_l,y_r,maxv = 0.0; PetscViewer viewer; PetscViewerFormat format; PetscFunctionBegin; ierr = PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);CHKERRQ(ierr); ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr); ierr = PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);CHKERRQ(ierr); /* loop over matrix elements drawing boxes */ if (format != PETSC_VIEWER_DRAW_CONTOUR) { /* Blue for negative, Cyan for zero and Red for positive */ color = PETSC_DRAW_BLUE; for (i=0; ii[i]; ji[i+1]; j++) { x_l = a->j[j]; x_r = x_l + 1.0; if (PetscRealPart(a->a[j]) >= 0.) continue; ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); } } color = PETSC_DRAW_CYAN; for (i=0; ii[i]; ji[i+1]; j++) { x_l = a->j[j]; x_r = x_l + 1.0; if (a->a[j] != 0.) continue; ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); } } color = PETSC_DRAW_RED; for (i=0; ii[i]; ji[i+1]; j++) { x_l = a->j[j]; x_r = x_l + 1.0; if (PetscRealPart(a->a[j]) <= 0.) continue; ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); } } } else { /* use contour shading to indicate magnitude of values */ /* first determine max of all nonzero values */ PetscInt nz = a->nz,count; PetscDraw popup; PetscReal scale; for (i=0; ia[i]) > maxv) maxv = PetscAbsScalar(a->a[i]); } scale = (245.0 - PETSC_DRAW_BASIC_COLORS)/maxv; ierr = PetscDrawGetPopup(draw,&popup);CHKERRQ(ierr); if (popup) { ierr = PetscDrawScalePopup(popup,0.0,maxv);CHKERRQ(ierr); } count = 0; for (i=0; ii[i]; ji[i+1]; j++) { x_l = a->j[j]; x_r = x_l + 1.0; color = PETSC_DRAW_BASIC_COLORS + (PetscInt)(scale*PetscAbsScalar(a->a[count])); ierr = PetscDrawRectangle(draw,x_l,y_l,x_r,y_r,color,color,color,color);CHKERRQ(ierr); count++; } } } PetscFunctionReturn(0); } #include #undef __FUNCT__ #define __FUNCT__ "MatView_SeqAIJ_Draw" PetscErrorCode MatView_SeqAIJ_Draw(Mat A,PetscViewer viewer) { PetscErrorCode ierr; PetscDraw draw; PetscReal xr,yr,xl,yl,h,w; PetscBool isnull; PetscFunctionBegin; ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr); ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0); ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);CHKERRQ(ierr); xr = A->cmap->n; yr = A->rmap->n; h = yr/10.0; w = xr/10.0; xr += w; yr += h; xl = -w; yl = -h; ierr = PetscDrawSetCoordinates(draw,xl,yl,xr,yr);CHKERRQ(ierr); ierr = PetscDrawZoom(draw,MatView_SeqAIJ_Draw_Zoom,A);CHKERRQ(ierr); ierr = PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatView_SeqAIJ" PetscErrorCode MatView_SeqAIJ(Mat A,PetscViewer viewer) { PetscErrorCode ierr; PetscBool iascii,isbinary,isdraw; PetscFunctionBegin; ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr); ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr); ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr); if (iascii) { ierr = MatView_SeqAIJ_ASCII(A,viewer);CHKERRQ(ierr); } else if (isbinary) { ierr = MatView_SeqAIJ_Binary(A,viewer);CHKERRQ(ierr); } else if (isdraw) { ierr = MatView_SeqAIJ_Draw(A,viewer);CHKERRQ(ierr); } ierr = MatView_SeqAIJ_Inode(A,viewer);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatAssemblyEnd_SeqAIJ" PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat A,MatAssemblyType mode) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax; PetscInt m = A->rmap->n,*ip,N,*ailen = a->ilen,rmax = 0; MatScalar *aa = a->a,*ap; PetscReal ratio = 0.6; PetscFunctionBegin; if (mode == MAT_FLUSH_ASSEMBLY) PetscFunctionReturn(0); if (m) rmax = ailen[0]; /* determine row with most nonzeros */ for (i=1; inonzerorowcnt = 0; for (i=0; inonzerorowcnt += ((ai[i+1] - ai[i]) > 0); } a->nz = ai[m]; 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); ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); ierr = PetscInfo4(A,"Matrix size: %D X %D; storage space: %D unneeded,%D used\n",m,A->cmap->n,fshift,a->nz);CHKERRQ(ierr); ierr = PetscInfo1(A,"Number of mallocs during MatSetValues() is %D\n",a->reallocs);CHKERRQ(ierr); ierr = PetscInfo1(A,"Maximum nonzeros in any row is %D\n",rmax);CHKERRQ(ierr); A->info.mallocs += a->reallocs; a->reallocs = 0; A->info.nz_unneeded = (PetscReal)fshift; a->rmax = rmax; ierr = MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,m,ratio);CHKERRQ(ierr); ierr = MatAssemblyEnd_SeqAIJ_Inode(A,mode);CHKERRQ(ierr); ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRealPart_SeqAIJ" PetscErrorCode MatRealPart_SeqAIJ(Mat A) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt i,nz = a->nz; MatScalar *aa = a->a; PetscErrorCode ierr; PetscFunctionBegin; for (i=0; idata; PetscInt i,nz = a->nz; MatScalar *aa = a->a; PetscErrorCode ierr; PetscFunctionBegin; for (i=0; idata; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscMemzero(a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); ierr = MatSeqAIJInvalidateDiagonal(A);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDestroy_SeqAIJ" PetscErrorCode MatDestroy_SeqAIJ(Mat A) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscFunctionBegin; #if defined(PETSC_USE_LOG) PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->n,A->cmap->n,a->nz); #endif ierr = MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);CHKERRQ(ierr); ierr = ISDestroy(&a->row);CHKERRQ(ierr); ierr = ISDestroy(&a->col);CHKERRQ(ierr); ierr = PetscFree(a->diag);CHKERRQ(ierr); ierr = PetscFree(a->ibdiag);CHKERRQ(ierr); ierr = PetscFree2(a->imax,a->ilen);CHKERRQ(ierr); ierr = PetscFree3(a->idiag,a->mdiag,a->ssor_work);CHKERRQ(ierr); ierr = PetscFree(a->solve_work);CHKERRQ(ierr); ierr = ISDestroy(&a->icol);CHKERRQ(ierr); ierr = PetscFree(a->saved_values);CHKERRQ(ierr); ierr = ISColoringDestroy(&a->coloring);CHKERRQ(ierr); ierr = PetscFree2(a->compressedrow.i,a->compressedrow.rindex);CHKERRQ(ierr); ierr = PetscFree(a->matmult_abdense);CHKERRQ(ierr); ierr = MatDestroy_SeqAIJ_Inode(A);CHKERRQ(ierr); ierr = PetscFree(A->data);CHKERRQ(ierr); ierr = PetscObjectChangeTypeName((PetscObject)A,0);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetColumnIndices_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqsbaij_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqbaij_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqaijperm_C",NULL);CHKERRQ(ierr); #if defined(PETSC_HAVE_ELEMENTAL) ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_elemental_C",NULL);CHKERRQ(ierr); #endif ierr = PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqaij_seqdense_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocation_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatSeqAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)A,"MatReorderForNonzeroDiagonal_C",NULL);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetOption_SeqAIJ" PetscErrorCode MatSetOption_SeqAIJ(Mat A,MatOption op,PetscBool flg) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscFunctionBegin; switch (op) { case MAT_ROW_ORIENTED: a->roworiented = flg; break; case MAT_KEEP_NONZERO_PATTERN: a->keepnonzeropattern = flg; break; case MAT_NEW_NONZERO_LOCATIONS: a->nonew = (flg ? 0 : 1); break; case MAT_NEW_NONZERO_LOCATION_ERR: a->nonew = (flg ? -1 : 0); break; case MAT_NEW_NONZERO_ALLOCATION_ERR: a->nonew = (flg ? -2 : 0); break; case MAT_UNUSED_NONZERO_LOCATION_ERR: a->nounused = (flg ? -1 : 0); break; case MAT_IGNORE_ZERO_ENTRIES: a->ignorezeroentries = flg; break; case MAT_SPD: case MAT_SYMMETRIC: case MAT_STRUCTURALLY_SYMMETRIC: case MAT_HERMITIAN: case MAT_SYMMETRY_ETERNAL: /* These options are handled directly by MatSetOption() */ break; case MAT_NEW_DIAGONALS: case MAT_IGNORE_OFF_PROC_ENTRIES: case MAT_USE_HASH_TABLE: ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr); break; case MAT_USE_INODES: /* Not an error because MatSetOption_SeqAIJ_Inode handles this one */ break; default: SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op); } ierr = MatSetOption_SeqAIJ_Inode(A,op,flg);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetDiagonal_SeqAIJ" PetscErrorCode MatGetDiagonal_SeqAIJ(Mat A,Vec v) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,j,n,*ai=a->i,*aj=a->j,nz; PetscScalar *aa=a->a,*x,zero=0.0; PetscFunctionBegin; ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); if (A->factortype == MAT_FACTOR_ILU || A->factortype == MAT_FACTOR_LU) { PetscInt *diag=a->diag; ierr = VecGetArray(v,&x);CHKERRQ(ierr); for (i=0; i #undef __FUNCT__ #define __FUNCT__ "MatMultTransposeAdd_SeqAIJ" PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec xx,Vec zz,Vec yy) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscScalar *y; const PetscScalar *x; PetscErrorCode ierr; PetscInt m = A->rmap->n; #if !defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) const MatScalar *v; PetscScalar alpha; PetscInt n,i,j; const PetscInt *idx,*ii,*ridx=NULL; Mat_CompressedRow cprow = a->compressedrow; PetscBool usecprow = cprow.use; #endif PetscFunctionBegin; if (zz != yy) {ierr = VecCopy(zz,yy);CHKERRQ(ierr);} ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecGetArray(yy,&y);CHKERRQ(ierr); #if defined(PETSC_USE_FORTRAN_KERNEL_MULTTRANSPOSEAIJ) fortranmulttransposeaddaij_(&m,x,a->i,a->j,a->a,y); #else if (usecprow) { m = cprow.nrows; ii = cprow.i; ridx = cprow.rindex; } else { ii = a->i; } for (i=0; ij + ii[i]; v = a->a + ii[i]; n = ii[i+1] - ii[i]; if (usecprow) { alpha = x[ridx[i]]; } else { alpha = x[i]; } for (j=0; jnz);CHKERRQ(ierr); ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMultTranspose_SeqAIJ" PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec xx,Vec yy) { PetscErrorCode ierr; PetscFunctionBegin; ierr = VecSet(yy,0.0);CHKERRQ(ierr); ierr = MatMultTransposeAdd_SeqAIJ(A,xx,yy,yy);CHKERRQ(ierr); PetscFunctionReturn(0); } #include <../src/mat/impls/aij/seq/ftn-kernels/fmult.h> #undef __FUNCT__ #define __FUNCT__ "MatMult_SeqAIJ" PetscErrorCode MatMult_SeqAIJ(Mat A,Vec xx,Vec yy) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscScalar *y; const PetscScalar *x; const MatScalar *aa; PetscErrorCode ierr; PetscInt m=A->rmap->n; const PetscInt *aj,*ii,*ridx=NULL; PetscInt n,i; PetscScalar sum; PetscBool usecprow=a->compressedrow.use; #if defined(PETSC_HAVE_PRAGMA_DISJOINT) #pragma disjoint(*x,*y,*aa) #endif PetscFunctionBegin; ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecGetArray(yy,&y);CHKERRQ(ierr); aj = a->j; aa = a->a; ii = a->i; if (usecprow) { /* use compressed row format */ ierr = PetscMemzero(y,m*sizeof(PetscScalar));CHKERRQ(ierr); m = a->compressedrow.nrows; ii = a->compressedrow.i; ridx = a->compressedrow.rindex; for (i=0; ij + ii[i]; aa = a->a + ii[i]; sum = 0.0; PetscSparseDensePlusDot(sum,x,aa,aj,n); /* for (j=0; jj + ii[i]; aa = a->a + ii[i]; sum = 0.0; PetscSparseDensePlusDot(sum,x,aa,aj,n); y[i] = sum; } #endif } ierr = PetscLogFlops(2.0*a->nz - a->nonzerorowcnt);CHKERRQ(ierr); ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMultMax_SeqAIJ" PetscErrorCode MatMultMax_SeqAIJ(Mat A,Vec xx,Vec yy) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscScalar *y; const PetscScalar *x; const MatScalar *aa; PetscErrorCode ierr; PetscInt m=A->rmap->n; const PetscInt *aj,*ii,*ridx=NULL; PetscInt n,i,nonzerorow=0; PetscScalar sum; PetscBool usecprow=a->compressedrow.use; #if defined(PETSC_HAVE_PRAGMA_DISJOINT) #pragma disjoint(*x,*y,*aa) #endif PetscFunctionBegin; ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecGetArray(yy,&y);CHKERRQ(ierr); aj = a->j; aa = a->a; ii = a->i; if (usecprow) { /* use compressed row format */ m = a->compressedrow.nrows; ii = a->compressedrow.i; ridx = a->compressedrow.rindex; for (i=0; ij + ii[i]; aa = a->a + ii[i]; sum = 0.0; nonzerorow += (n>0); PetscSparseDenseMaxDot(sum,x,aa,aj,n); /* for (j=0; jj + ii[i]; aa = a->a + ii[i]; sum = 0.0; nonzerorow += (n>0); PetscSparseDenseMaxDot(sum,x,aa,aj,n); y[i] = sum; } } ierr = PetscLogFlops(2.0*a->nz - nonzerorow);CHKERRQ(ierr); ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArray(yy,&y);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMultAddMax_SeqAIJ" PetscErrorCode MatMultAddMax_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscScalar *y,*z; const PetscScalar *x; const MatScalar *aa; PetscErrorCode ierr; PetscInt m = A->rmap->n,*aj,*ii; PetscInt n,i,*ridx=NULL; PetscScalar sum; PetscBool usecprow=a->compressedrow.use; PetscFunctionBegin; ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); aj = a->j; aa = a->a; ii = a->i; if (usecprow) { /* use compressed row format */ if (zz != yy) { ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); } m = a->compressedrow.nrows; ii = a->compressedrow.i; ridx = a->compressedrow.rindex; for (i=0; ij + ii[i]; aa = a->a + ii[i]; sum = y[*ridx]; PetscSparseDenseMaxDot(sum,x,aa,aj,n); z[*ridx++] = sum; } } else { /* do not use compressed row format */ for (i=0; ij + ii[i]; aa = a->a + ii[i]; sum = y[i]; PetscSparseDenseMaxDot(sum,x,aa,aj,n); z[i] = sum; } } ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); PetscFunctionReturn(0); } #include <../src/mat/impls/aij/seq/ftn-kernels/fmultadd.h> #undef __FUNCT__ #define __FUNCT__ "MatMultAdd_SeqAIJ" PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec xx,Vec yy,Vec zz) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscScalar *y,*z; const PetscScalar *x; const MatScalar *aa; PetscErrorCode ierr; const PetscInt *aj,*ii,*ridx=NULL; PetscInt m = A->rmap->n,n,i; PetscScalar sum; PetscBool usecprow=a->compressedrow.use; PetscFunctionBegin; ierr = VecGetArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecGetArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); aj = a->j; aa = a->a; ii = a->i; if (usecprow) { /* use compressed row format */ if (zz != yy) { ierr = PetscMemcpy(z,y,m*sizeof(PetscScalar));CHKERRQ(ierr); } m = a->compressedrow.nrows; ii = a->compressedrow.i; ridx = a->compressedrow.rindex; for (i=0; ij + ii[i]; aa = a->a + ii[i]; sum = y[*ridx]; PetscSparseDensePlusDot(sum,x,aa,aj,n); z[*ridx++] = sum; } } else { /* do not use compressed row format */ #if defined(PETSC_USE_FORTRAN_KERNEL_MULTADDAIJ) fortranmultaddaij_(&m,x,ii,aj,aa,y,z); #else for (i=0; ij + ii[i]; aa = a->a + ii[i]; sum = y[i]; PetscSparseDensePlusDot(sum,x,aa,aj,n); z[i] = sum; } #endif } ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); ierr = VecRestoreArrayRead(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArrayPair(yy,zz,&y,&z);CHKERRQ(ierr); #if defined(PETSC_HAVE_CUSP) /* ierr = VecView(xx,0);CHKERRQ(ierr); ierr = VecView(zz,0);CHKERRQ(ierr); ierr = MatView(A,0);CHKERRQ(ierr); */ #endif PetscFunctionReturn(0); } /* Adds diagonal pointers to sparse matrix structure. */ #undef __FUNCT__ #define __FUNCT__ "MatMarkDiagonal_SeqAIJ" PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat A) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n; PetscFunctionBegin; if (!a->diag) { ierr = PetscMalloc1(m,&a->diag);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)A, m*sizeof(PetscInt));CHKERRQ(ierr); } for (i=0; irmap->n; i++) { a->diag[i] = a->i[i+1]; for (j=a->i[i]; ji[i+1]; j++) { if (a->j[j] == i) { a->diag[i] = j; break; } } } PetscFunctionReturn(0); } /* Checks for missing diagonals */ #undef __FUNCT__ #define __FUNCT__ "MatMissingDiagonal_SeqAIJ" PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat A,PetscBool *missing,PetscInt *d) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt *diag,*ii = a->i,i; PetscFunctionBegin; *missing = PETSC_FALSE; if (A->rmap->n > 0 && !ii) { *missing = PETSC_TRUE; if (d) *d = 0; PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n"); } else { diag = a->diag; for (i=0; irmap->n; i++) { if (diag[i] >= ii[i+1]) { *missing = PETSC_TRUE; if (d) *d = i; PetscInfo1(A,"Matrix is missing diagonal number %D\n",i); break; } } } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatInvertDiagonal_SeqAIJ" /* Negative shift indicates do not generate an error if there is a zero diagonal, just invert it anyways */ PetscErrorCode MatInvertDiagonal_SeqAIJ(Mat A,PetscScalar omega,PetscScalar fshift) { Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; PetscErrorCode ierr; PetscInt i,*diag,m = A->rmap->n; MatScalar *v = a->a; PetscScalar *idiag,*mdiag; PetscFunctionBegin; if (a->idiagvalid) PetscFunctionReturn(0); ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); diag = a->diag; if (!a->idiag) { ierr = PetscMalloc3(m,&a->idiag,m,&a->mdiag,m,&a->ssor_work);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)A, 3*m*sizeof(PetscScalar));CHKERRQ(ierr); v = a->a; } mdiag = a->mdiag; idiag = a->idiag; if (omega == 1.0 && PetscRealPart(fshift) <= 0.0) { for (i=0; iidiagvalid = PETSC_TRUE; PetscFunctionReturn(0); } #include <../src/mat/impls/aij/seq/ftn-kernels/frelax.h> #undef __FUNCT__ #define __FUNCT__ "MatSOR_SeqAIJ" PetscErrorCode MatSOR_SeqAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscScalar *x,d,sum,*t,scale; const MatScalar *v = a->a,*idiag=0,*mdiag; const PetscScalar *b, *bs,*xb, *ts; PetscErrorCode ierr; PetscInt n = A->cmap->n,m = A->rmap->n,i; const PetscInt *idx,*diag; PetscFunctionBegin; its = its*lits; if (fshift != a->fshift || omega != a->omega) a->idiagvalid = PETSC_FALSE; /* must recompute idiag[] */ if (!a->idiagvalid) {ierr = MatInvertDiagonal_SeqAIJ(A,omega,fshift);CHKERRQ(ierr);} a->fshift = fshift; a->omega = omega; diag = a->diag; t = a->ssor_work; idiag = a->idiag; mdiag = a->mdiag; ierr = VecGetArray(xx,&x);CHKERRQ(ierr); ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr); /* We count flops by assuming the upper triangular and lower triangular parts have the same number of nonzeros */ if (flag == SOR_APPLY_UPPER) { /* apply (U + D/omega) to the vector */ bs = b; for (i=0; ii[i+1] - diag[i] - 1; idx = a->j + diag[i] + 1; v = a->a + diag[i] + 1; sum = b[i]*d/omega; PetscSparseDensePlusDot(sum,bs,v,idx,n); x[i] = sum; } ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); PetscFunctionReturn(0); } if (flag == SOR_APPLY_LOWER) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SOR_APPLY_LOWER is not implemented"); else if (flag & SOR_EISENSTAT) { /* Let A = L + U + D; where L is lower trianglar, U is upper triangular, E = D/omega; This routine applies (L + E)^{-1} A (U + E)^{-1} to a vector efficiently using Eisenstat's trick. */ scale = (2.0/omega) - 1.0; /* x = (E + U)^{-1} b */ for (i=m-1; i>=0; i--) { n = a->i[i+1] - diag[i] - 1; idx = a->j + diag[i] + 1; v = a->a + diag[i] + 1; sum = b[i]; PetscSparseDenseMinusDot(sum,x,v,idx,n); x[i] = sum*idiag[i]; } /* t = b - (2*E - D)x */ v = a->a; for (i=0; idiag; for (i=0; ii[i]; idx = a->j + a->i[i]; v = a->a + a->i[i]; sum = t[i]; PetscSparseDenseMinusDot(sum,ts,v,idx,n); t[i] = sum*idiag[i]; /* x = x + t */ x[i] += t[i]; } ierr = PetscLogFlops(6.0*m-1 + 2.0*a->nz);CHKERRQ(ierr); ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); PetscFunctionReturn(0); } if (flag & SOR_ZERO_INITIAL_GUESS) { if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { for (i=0; ii[i]; idx = a->j + a->i[i]; v = a->a + a->i[i]; sum = b[i]; PetscSparseDenseMinusDot(sum,x,v,idx,n); t[i] = sum; x[i] = sum*idiag[i]; } xb = t; ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); } else xb = b; if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { for (i=m-1; i>=0; i--) { n = a->i[i+1] - diag[i] - 1; idx = a->j + diag[i] + 1; v = a->a + diag[i] + 1; sum = xb[i]; PetscSparseDenseMinusDot(sum,x,v,idx,n); if (xb == b) { x[i] = sum*idiag[i]; } else { x[i] = (1-omega)*x[i] + sum*idiag[i]; /* omega in idiag */ } } ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ } its--; } while (its--) { if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) { for (i=0; ii[i]; idx = a->j + a->i[i]; v = a->a + a->i[i]; sum = b[i]; PetscSparseDenseMinusDot(sum,x,v,idx,n); t[i] = sum; /* save application of the lower-triangular part */ /* upper */ n = a->i[i+1] - diag[i] - 1; idx = a->j + diag[i] + 1; v = a->a + diag[i] + 1; PetscSparseDenseMinusDot(sum,x,v,idx,n); x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ } xb = t; ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); } else xb = b; if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) { for (i=m-1; i>=0; i--) { sum = xb[i]; if (xb == b) { /* whole matrix (no checkpointing available) */ n = a->i[i+1] - a->i[i]; idx = a->j + a->i[i]; v = a->a + a->i[i]; PetscSparseDenseMinusDot(sum,x,v,idx,n); x[i] = (1. - omega)*x[i] + (sum + mdiag[i]*x[i])*idiag[i]; } else { /* lower-triangular part has been saved, so only apply upper-triangular */ n = a->i[i+1] - diag[i] - 1; idx = a->j + diag[i] + 1; v = a->a + diag[i] + 1; PetscSparseDenseMinusDot(sum,x,v,idx,n); x[i] = (1. - omega)*x[i] + sum*idiag[i]; /* omega in idiag */ } } if (xb == b) { ierr = PetscLogFlops(2.0*a->nz);CHKERRQ(ierr); } else { ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); /* assumes 1/2 in upper */ } } } ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr); ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetInfo_SeqAIJ" PetscErrorCode MatGetInfo_SeqAIJ(Mat A,MatInfoType flag,MatInfo *info) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscFunctionBegin; info->block_size = 1.0; info->nz_allocated = (double)a->maxnz; info->nz_used = (double)a->nz; info->nz_unneeded = (double)(a->maxnz - a->nz); info->assemblies = (double)A->num_ass; info->mallocs = (double)A->info.mallocs; info->memory = ((PetscObject)A)->mem; if (A->factortype) { info->fill_ratio_given = A->info.fill_ratio_given; info->fill_ratio_needed = A->info.fill_ratio_needed; info->factor_mallocs = A->info.factor_mallocs; } else { info->fill_ratio_given = 0; info->fill_ratio_needed = 0; info->factor_mallocs = 0; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatZeroRows_SeqAIJ" PetscErrorCode MatZeroRows_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt i,m = A->rmap->n - 1,d = 0; PetscErrorCode ierr; const PetscScalar *xx; PetscScalar *bb; PetscBool missing; PetscFunctionBegin; if (x && b) { ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); ierr = VecGetArray(b,&bb);CHKERRQ(ierr); for (i=0; i m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); bb[rows[i]] = diag*xx[rows[i]]; } ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); } if (a->keepnonzeropattern) { for (i=0; i m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); } if (diag != 0.0) { ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); for (i=0; ia[a->diag[rows[i]]] = diag; } } } else { if (diag != 0.0) { for (i=0; i m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); if (a->ilen[rows[i]] > 0) { a->ilen[rows[i]] = 1; a->a[a->i[rows[i]]] = diag; a->j[a->i[rows[i]]] = rows[i]; } else { /* in case row was completely empty */ ierr = MatSetValues_SeqAIJ(A,1,&rows[i],1,&rows[i],&diag,INSERT_VALUES);CHKERRQ(ierr); } } } else { for (i=0; i m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); a->ilen[rows[i]] = 0; } } A->nonzerostate++; } ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatZeroRowsColumns_SeqAIJ" PetscErrorCode MatZeroRowsColumns_SeqAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt i,j,m = A->rmap->n - 1,d = 0; PetscErrorCode ierr; PetscBool missing,*zeroed,vecs = PETSC_FALSE; const PetscScalar *xx; PetscScalar *bb; PetscFunctionBegin; if (x && b) { ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr); ierr = VecGetArray(b,&bb);CHKERRQ(ierr); vecs = PETSC_TRUE; } ierr = PetscCalloc1(A->rmap->n,&zeroed);CHKERRQ(ierr); for (i=0; i m) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range", rows[i]); ierr = PetscMemzero(&a->a[a->i[rows[i]]],a->ilen[rows[i]]*sizeof(PetscScalar));CHKERRQ(ierr); zeroed[rows[i]] = PETSC_TRUE; } for (i=0; irmap->n; i++) { if (!zeroed[i]) { for (j=a->i[i]; ji[i+1]; j++) { if (zeroed[a->j[j]]) { if (vecs) bb[i] -= a->a[j]*xx[a->j[j]]; a->a[j] = 0.0; } } } else if (vecs) bb[i] = diag*xx[i]; } if (x && b) { ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr); ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr); } ierr = PetscFree(zeroed);CHKERRQ(ierr); if (diag != 0.0) { ierr = MatMissingDiagonal_SeqAIJ(A,&missing,&d);CHKERRQ(ierr); if (missing) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Matrix is missing diagonal entry in row %D",d); for (i=0; ia[a->diag[rows[i]]] = diag; } } ierr = MatAssemblyEnd_SeqAIJ(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetRow_SeqAIJ" PetscErrorCode MatGetRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt *itmp; PetscFunctionBegin; if (row < 0 || row >= A->rmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range",row); *nz = a->i[row+1] - a->i[row]; if (v) *v = a->a + a->i[row]; if (idx) { itmp = a->j + a->i[row]; if (*nz) *idx = itmp; else *idx = 0; } PetscFunctionReturn(0); } /* remove this function? */ #undef __FUNCT__ #define __FUNCT__ "MatRestoreRow_SeqAIJ" PetscErrorCode MatRestoreRow_SeqAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v) { PetscFunctionBegin; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatNorm_SeqAIJ" PetscErrorCode MatNorm_SeqAIJ(Mat A,NormType type,PetscReal *nrm) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; MatScalar *v = a->a; PetscReal sum = 0.0; PetscErrorCode ierr; PetscInt i,j; PetscFunctionBegin; if (type == NORM_FROBENIUS) { for (i=0; inz; i++) { sum += PetscRealPart(PetscConj(*v)*(*v)); v++; } *nrm = PetscSqrtReal(sum); } else if (type == NORM_1) { PetscReal *tmp; PetscInt *jj = a->j; ierr = PetscCalloc1(A->cmap->n+1,&tmp);CHKERRQ(ierr); *nrm = 0.0; for (j=0; jnz; j++) { tmp[*jj++] += PetscAbsScalar(*v); v++; } for (j=0; jcmap->n; j++) { if (tmp[j] > *nrm) *nrm = tmp[j]; } ierr = PetscFree(tmp);CHKERRQ(ierr); } else if (type == NORM_INFINITY) { *nrm = 0.0; for (j=0; jrmap->n; j++) { v = a->a + a->i[j]; sum = 0.0; for (i=0; ii[j+1]-a->i[j]; i++) { sum += PetscAbsScalar(*v); v++; } if (sum > *nrm) *nrm = sum; } } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for two norm"); PetscFunctionReturn(0); } /* Merged from MatGetSymbolicTranspose_SeqAIJ() - replace MatGetSymbolicTranspose_SeqAIJ()? */ #undef __FUNCT__ #define __FUNCT__ "MatTransposeSymbolic_SeqAIJ" PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat A,Mat *B) { PetscErrorCode ierr; PetscInt i,j,anzj; Mat_SeqAIJ *a=(Mat_SeqAIJ*)A->data,*b; PetscInt an=A->cmap->N,am=A->rmap->N; PetscInt *ati,*atj,*atfill,*ai=a->i,*aj=a->j; PetscFunctionBegin; /* Allocate space for symbolic transpose info and work array */ ierr = PetscCalloc1(an+1,&ati);CHKERRQ(ierr); ierr = PetscMalloc1(ai[am],&atj);CHKERRQ(ierr); ierr = PetscMalloc1(an,&atfill);CHKERRQ(ierr); /* Walk through aj and count ## of non-zeros in each row of A^T. */ /* Note: offset by 1 for fast conversion into csr format. */ for (i=0;icmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); b = (Mat_SeqAIJ*)((*B)->data); b->free_a = PETSC_FALSE; b->free_ij = PETSC_TRUE; b->nonew = 0; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatTranspose_SeqAIJ" PetscErrorCode MatTranspose_SeqAIJ(Mat A,MatReuse reuse,Mat *B) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; Mat C; PetscErrorCode ierr; PetscInt i,*aj = a->j,*ai = a->i,m = A->rmap->n,len,*col; MatScalar *array = a->a; PetscFunctionBegin; 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"); if (reuse == MAT_INITIAL_MATRIX || *B == A) { ierr = PetscCalloc1(1+A->cmap->n,&col);CHKERRQ(ierr); for (i=0; icmap->n,m,A->cmap->n,m);CHKERRQ(ierr); ierr = MatSetBlockSizes(C,PetscAbs(A->cmap->bs),PetscAbs(A->rmap->bs));CHKERRQ(ierr); ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,col);CHKERRQ(ierr); ierr = PetscFree(col);CHKERRQ(ierr); } else { C = *B; } for (i=0; idata,*bij = (Mat_SeqAIJ*) A->data; PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; MatScalar *va,*vb; PetscErrorCode ierr; PetscInt ma,na,mb,nb, i; PetscFunctionBegin; bij = (Mat_SeqAIJ*) B->data; ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); if (ma!=nb || na!=mb) { *f = PETSC_FALSE; PetscFunctionReturn(0); } aii = aij->i; bii = bij->i; adx = aij->j; bdx = bij->j; va = aij->a; vb = bij->a; ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); for (i=0; i tol) { *f = PETSC_FALSE; goto done; } else { aptr[i]++; if (B || i!=idc) bptr[idc]++; } } } done: ierr = PetscFree(aptr);CHKERRQ(ierr); ierr = PetscFree(bptr);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatIsHermitianTranspose_SeqAIJ" PetscErrorCode MatIsHermitianTranspose_SeqAIJ(Mat A,Mat B,PetscReal tol,PetscBool *f) { Mat_SeqAIJ *aij = (Mat_SeqAIJ*) A->data,*bij = (Mat_SeqAIJ*) A->data; PetscInt *adx,*bdx,*aii,*bii,*aptr,*bptr; MatScalar *va,*vb; PetscErrorCode ierr; PetscInt ma,na,mb,nb, i; PetscFunctionBegin; bij = (Mat_SeqAIJ*) B->data; ierr = MatGetSize(A,&ma,&na);CHKERRQ(ierr); ierr = MatGetSize(B,&mb,&nb);CHKERRQ(ierr); if (ma!=nb || na!=mb) { *f = PETSC_FALSE; PetscFunctionReturn(0); } aii = aij->i; bii = bij->i; adx = aij->j; bdx = bij->j; va = aij->a; vb = bij->a; ierr = PetscMalloc1(ma,&aptr);CHKERRQ(ierr); ierr = PetscMalloc1(mb,&bptr);CHKERRQ(ierr); for (i=0; i tol) { *f = PETSC_FALSE; goto done; } else { aptr[i]++; if (B || i!=idc) bptr[idc]++; } } } done: ierr = PetscFree(aptr);CHKERRQ(ierr); ierr = PetscFree(bptr);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatIsSymmetric_SeqAIJ" PetscErrorCode MatIsSymmetric_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatIsTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatIsHermitian_SeqAIJ" PetscErrorCode MatIsHermitian_SeqAIJ(Mat A,PetscReal tol,PetscBool *f) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatIsHermitianTranspose_SeqAIJ(A,A,tol,f);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDiagonalScale_SeqAIJ" PetscErrorCode MatDiagonalScale_SeqAIJ(Mat A,Vec ll,Vec rr) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscScalar *l,*r,x; MatScalar *v; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n,n = A->cmap->n,M,nz = a->nz,*jj; PetscFunctionBegin; if (ll) { /* The local size is used so that VecMPI can be passed to this routine by MatDiagonalScale_MPIAIJ */ ierr = VecGetLocalSize(ll,&m);CHKERRQ(ierr); if (m != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left scaling vector wrong length"); ierr = VecGetArray(ll,&l);CHKERRQ(ierr); v = a->a; for (i=0; ii[i+1] - a->i[i]; for (j=0; jcmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Right scaling vector wrong length"); ierr = VecGetArray(rr,&r);CHKERRQ(ierr); v = a->a; jj = a->j; for (i=0; idata,*c; PetscErrorCode ierr; PetscInt *smap,i,k,kstart,kend,oldcols = A->cmap->n,*lens; PetscInt row,mat_i,*mat_j,tcol,first,step,*mat_ilen,sum,lensi; const PetscInt *irow,*icol; PetscInt nrows,ncols; PetscInt *starts,*j_new,*i_new,*aj = a->j,*ai = a->i,ii,*ailen = a->ilen; MatScalar *a_new,*mat_a; Mat C; PetscBool stride; PetscFunctionBegin; ierr = ISGetIndices(isrow,&irow);CHKERRQ(ierr); ierr = ISGetLocalSize(isrow,&nrows);CHKERRQ(ierr); ierr = ISGetLocalSize(iscol,&ncols);CHKERRQ(ierr); ierr = PetscObjectTypeCompare((PetscObject)iscol,ISSTRIDE,&stride);CHKERRQ(ierr); if (stride) { ierr = ISStrideGetInfo(iscol,&first,&step);CHKERRQ(ierr); } else { first = 0; step = 0; } if (stride && step == 1) { /* special case of contiguous rows */ ierr = PetscMalloc2(nrows,&lens,nrows,&starts);CHKERRQ(ierr); /* loop over new rows determining lens and starting points */ for (i=0; i= first) { starts[i] = k; break; } } sum = 0; while (k < kend) { if (aj[k++] >= first+ncols) break; sum++; } lens[i] = sum; } /* create submatrix */ if (scall == MAT_REUSE_MATRIX) { PetscInt n_cols,n_rows; ierr = MatGetSize(*B,&n_rows,&n_cols);CHKERRQ(ierr); if (n_rows != nrows || n_cols != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Reused submatrix wrong size"); ierr = MatZeroEntries(*B);CHKERRQ(ierr); C = *B; } else { PetscInt rbs,cbs; ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); } c = (Mat_SeqAIJ*)C->data; /* loop over rows inserting into submatrix */ a_new = c->a; j_new = c->j; i_new = c->i; for (i=0; ia + starts[i],lensi*sizeof(PetscScalar));CHKERRQ(ierr); a_new += lensi; i_new[i+1] = i_new[i] + lensi; c->ilen[i] = lensi; } ierr = PetscFree2(lens,starts);CHKERRQ(ierr); } else { ierr = ISGetIndices(iscol,&icol);CHKERRQ(ierr); ierr = PetscCalloc1(oldcols,&smap);CHKERRQ(ierr); ierr = PetscMalloc1(1+nrows,&lens);CHKERRQ(ierr); for (i=0; i= oldcols) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Requesting column beyond largest column icol[%D] %D <= A->cmap->n %D",i,icol[i],oldcols); #endif smap[icol[i]] = i+1; } /* determine lens of each row */ for (i=0; iilen[irow[i]]; lens[i] = 0; for (k=kstart; kdata); if ((*B)->rmap->n != nrows || (*B)->cmap->n != ncols) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong size"); ierr = PetscMemcmp(c->ilen,lens,(*B)->rmap->n*sizeof(PetscInt),&equal);CHKERRQ(ierr); if (!equal) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Cannot reuse matrix. wrong no of nonzeros"); ierr = PetscMemzero(c->ilen,(*B)->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); C = *B; } else { PetscInt rbs,cbs; ierr = MatCreate(PetscObjectComm((PetscObject)A),&C);CHKERRQ(ierr); ierr = MatSetSizes(C,nrows,ncols,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr); ierr = ISGetBlockSize(isrow,&rbs);CHKERRQ(ierr); ierr = ISGetBlockSize(iscol,&cbs);CHKERRQ(ierr); ierr = MatSetBlockSizes(C,rbs,cbs);CHKERRQ(ierr); ierr = MatSetType(C,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation_SeqAIJ(C,0,lens);CHKERRQ(ierr); } c = (Mat_SeqAIJ*)(C->data); for (i=0; iilen[row]; mat_i = c->i[i]; mat_j = c->j + mat_i; mat_a = c->a + mat_i; mat_ilen = c->ilen + i; for (k=kstart; kj[k]])) { *mat_j++ = tcol - 1; *mat_a++ = a->a[k]; (*mat_ilen)++; } } } /* Free work space */ ierr = ISRestoreIndices(iscol,&icol);CHKERRQ(ierr); ierr = PetscFree(smap);CHKERRQ(ierr); ierr = PetscFree(lens);CHKERRQ(ierr); /* sort */ for (i = 0; i < nrows; i++) { PetscInt ilen; mat_i = c->i[i]; mat_j = c->j + mat_i; mat_a = c->a + mat_i; ilen = c->ilen[i]; ierr = PetscSortIntWithMatScalarArray(ilen,mat_j,mat_a);CHKERRQ(ierr); } } ierr = MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = ISRestoreIndices(isrow,&irow);CHKERRQ(ierr); *B = C; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetMultiProcBlock_SeqAIJ" PetscErrorCode MatGetMultiProcBlock_SeqAIJ(Mat mat,MPI_Comm subComm,MatReuse scall,Mat *subMat) { PetscErrorCode ierr; Mat B; PetscFunctionBegin; if (scall == MAT_INITIAL_MATRIX) { ierr = MatCreate(subComm,&B);CHKERRQ(ierr); ierr = MatSetSizes(B,mat->rmap->n,mat->cmap->n,mat->rmap->n,mat->cmap->n);CHKERRQ(ierr); ierr = MatSetBlockSizesFromMats(B,mat,mat);CHKERRQ(ierr); ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr); ierr = MatDuplicateNoCreate_SeqAIJ(B,mat,MAT_COPY_VALUES,PETSC_TRUE);CHKERRQ(ierr); *subMat = B; } else { ierr = MatCopy_SeqAIJ(mat,*subMat,SAME_NONZERO_PATTERN);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatILUFactor_SeqAIJ" PetscErrorCode MatILUFactor_SeqAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; PetscErrorCode ierr; Mat outA; PetscBool row_identity,col_identity; PetscFunctionBegin; if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels=0 supported for in-place ilu"); ierr = ISIdentity(row,&row_identity);CHKERRQ(ierr); ierr = ISIdentity(col,&col_identity);CHKERRQ(ierr); outA = inA; outA->factortype = MAT_FACTOR_LU; ierr = PetscObjectReference((PetscObject)row);CHKERRQ(ierr); ierr = ISDestroy(&a->row);CHKERRQ(ierr); a->row = row; ierr = PetscObjectReference((PetscObject)col);CHKERRQ(ierr); ierr = ISDestroy(&a->col);CHKERRQ(ierr); a->col = col; /* Create the inverse permutation so that it can be used in MatLUFactorNumeric() */ ierr = ISDestroy(&a->icol);CHKERRQ(ierr); ierr = ISInvertPermutation(col,PETSC_DECIDE,&a->icol);CHKERRQ(ierr); ierr = PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);CHKERRQ(ierr); if (!a->solve_work) { /* this matrix may have been factored before */ ierr = PetscMalloc1(inA->rmap->n+1,&a->solve_work);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)inA, (inA->rmap->n+1)*sizeof(PetscScalar));CHKERRQ(ierr); } ierr = MatMarkDiagonal_SeqAIJ(inA);CHKERRQ(ierr); if (row_identity && col_identity) { ierr = MatLUFactorNumeric_SeqAIJ_inplace(outA,inA,info);CHKERRQ(ierr); } else { ierr = MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(outA,inA,info);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatScale_SeqAIJ" PetscErrorCode MatScale_SeqAIJ(Mat inA,PetscScalar alpha) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)inA->data; PetscScalar oalpha = alpha; PetscErrorCode ierr; PetscBLASInt one = 1,bnz; PetscFunctionBegin; ierr = PetscBLASIntCast(a->nz,&bnz);CHKERRQ(ierr); PetscStackCallBLAS("BLASscal",BLASscal_(&bnz,&oalpha,a->a,&one)); ierr = PetscLogFlops(a->nz);CHKERRQ(ierr); ierr = MatSeqAIJInvalidateDiagonal(inA);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetSubMatrices_SeqAIJ" PetscErrorCode MatGetSubMatrices_SeqAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[]) { PetscErrorCode ierr; PetscInt i; PetscFunctionBegin; if (scall == MAT_INITIAL_MATRIX) { ierr = PetscMalloc1(n+1,B);CHKERRQ(ierr); } for (i=0; idata; PetscErrorCode ierr; PetscInt row,i,j,k,l,m,n,*nidx,isz,val; const PetscInt *idx; PetscInt start,end,*ai,*aj; PetscBT table; PetscFunctionBegin; m = A->rmap->n; ai = a->i; aj = a->j; if (ov < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"illegal negative overlap value used"); ierr = PetscMalloc1(m+1,&nidx);CHKERRQ(ierr); ierr = PetscBTCreate(m,&table);CHKERRQ(ierr); for (i=0; idata; PetscErrorCode ierr; PetscInt i,nz = 0,m = A->rmap->n,n = A->cmap->n; const PetscInt *row,*col; PetscInt *cnew,j,*lens; IS icolp,irowp; PetscInt *cwork = NULL; PetscScalar *vwork = NULL; PetscFunctionBegin; ierr = ISInvertPermutation(rowp,PETSC_DECIDE,&irowp);CHKERRQ(ierr); ierr = ISGetIndices(irowp,&row);CHKERRQ(ierr); ierr = ISInvertPermutation(colp,PETSC_DECIDE,&icolp);CHKERRQ(ierr); ierr = ISGetIndices(icolp,&col);CHKERRQ(ierr); /* determine lengths of permuted rows */ ierr = PetscMalloc1(m+1,&lens);CHKERRQ(ierr); for (i=0; ii[i+1] - a->i[i]; ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); ierr = MatSetSizes(*B,m,n,m,n);CHKERRQ(ierr); ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation_SeqAIJ(*B,0,lens);CHKERRQ(ierr); ierr = PetscFree(lens);CHKERRQ(ierr); ierr = PetscMalloc1(n,&cnew);CHKERRQ(ierr); for (i=0; iassembled = PETSC_FALSE; ierr = MatAssemblyBegin(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(*B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = ISRestoreIndices(irowp,&row);CHKERRQ(ierr); ierr = ISRestoreIndices(icolp,&col);CHKERRQ(ierr); ierr = ISDestroy(&irowp);CHKERRQ(ierr); ierr = ISDestroy(&icolp);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatCopy_SeqAIJ" PetscErrorCode MatCopy_SeqAIJ(Mat A,Mat B,MatStructure str) { PetscErrorCode ierr; PetscFunctionBegin; /* If the two matrices have the same copy implementation, use fast copy. */ if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; Mat_SeqAIJ *b = (Mat_SeqAIJ*)B->data; if (a->i[A->rmap->n] != b->i[B->rmap->n]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzeros in two matrices are different"); ierr = PetscMemcpy(b->a,a->a,(a->i[A->rmap->n])*sizeof(PetscScalar));CHKERRQ(ierr); } else { ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetUp_SeqAIJ" PetscErrorCode MatSetUp_SeqAIJ(Mat A) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatSeqAIJSetPreallocation_SeqAIJ(A,PETSC_DEFAULT,0);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJGetArray_SeqAIJ" PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat A,PetscScalar *array[]) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscFunctionBegin; *array = a->a; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJRestoreArray_SeqAIJ" PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat A,PetscScalar *array[]) { PetscFunctionBegin; PetscFunctionReturn(0); } /* Computes the number of nonzeros per row needed for preallocation when X and Y have different nonzero structure. */ #undef __FUNCT__ #define __FUNCT__ "MatAXPYGetPreallocation_SeqX_private" PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt m,const PetscInt *xi,const PetscInt *xj,const PetscInt *yi,const PetscInt *yj,PetscInt *nnz) { PetscInt i,j,k,nzx,nzy; PetscFunctionBegin; /* Set the number of nonzeros in the new matrix */ for (i=0; irmap->N; Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data; Mat_SeqAIJ *y = (Mat_SeqAIJ*)Y->data; PetscErrorCode ierr; PetscFunctionBegin; /* Set the number of nonzeros in the new matrix */ ierr = MatAXPYGetPreallocation_SeqX_private(m,x->i,x->j,y->i,y->j,nnz);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatAXPY_SeqAIJ" PetscErrorCode MatAXPY_SeqAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str) { PetscErrorCode ierr; Mat_SeqAIJ *x = (Mat_SeqAIJ*)X->data,*y = (Mat_SeqAIJ*)Y->data; PetscBLASInt one=1,bnz; PetscFunctionBegin; ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr); if (str == SAME_NONZERO_PATTERN) { PetscScalar alpha = a; PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one)); ierr = MatSeqAIJInvalidateDiagonal(Y);CHKERRQ(ierr); ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr); } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */ ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr); } else { Mat B; PetscInt *nnz; ierr = PetscMalloc1(Y->rmap->N,&nnz);CHKERRQ(ierr); ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr); ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr); ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr); ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr); ierr = MatSetType(B,(MatType) ((PetscObject)Y)->type_name);CHKERRQ(ierr); ierr = MatAXPYGetPreallocation_SeqAIJ(Y,X,nnz);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation(B,0,nnz);CHKERRQ(ierr); ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr); ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr); ierr = PetscFree(nnz);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatConjugate_SeqAIJ" PetscErrorCode MatConjugate_SeqAIJ(Mat mat) { #if defined(PETSC_USE_COMPLEX) Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; PetscInt i,nz; PetscScalar *a; PetscFunctionBegin; nz = aij->nz; a = aij->a; for (i=0; idata; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; PetscReal atmp; PetscScalar *x; MatScalar *aa; PetscFunctionBegin; if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); aa = a->a; ai = a->i; aj = a->j; ierr = VecSet(v,0.0);CHKERRQ(ierr); ierr = VecGetArray(v,&x);CHKERRQ(ierr); ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); for (i=0; idata; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; PetscScalar *x; MatScalar *aa; PetscFunctionBegin; if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); aa = a->a; ai = a->i; aj = a->j; ierr = VecSet(v,0.0);CHKERRQ(ierr); ierr = VecGetArray(v,&x);CHKERRQ(ierr); ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); for (i=0; icmap->n) { /* row is dense */ x[i] = *aa; if (idx) idx[i] = 0; } else { /* row is sparse so already KNOW maximum is 0.0 or higher */ x[i] = 0.0; if (idx) { idx[i] = 0; /* in case ncols is zero */ for (j=0;j j) { idx[i] = j; break; } } } } for (j=0; jdata; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n,*ai,*aj,ncols,n; PetscReal atmp; PetscScalar *x; MatScalar *aa; PetscFunctionBegin; if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); aa = a->a; ai = a->i; aj = a->j; ierr = VecSet(v,0.0);CHKERRQ(ierr); ierr = VecGetArray(v,&x);CHKERRQ(ierr); ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); if (n != A->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector, %D vs. %D rows", A->rmap->n, n); for (i=0; i 1.0e-12) { x[i] = atmp; if (idx) idx[i] = aj[j]; break; } } if (j == ncols) {x[i] = PetscAbsScalar(*aa); if (idx) idx[i] = *aj;} } else { x[i] = 0.0; if (idx) idx[i] = 0; } for (j = 0; j < ncols; j++) { atmp = PetscAbsScalar(*aa); if (atmp > 1.0e-12 && PetscAbsScalar(x[i]) > atmp) {x[i] = atmp; if (idx) idx[i] = *aj;} aa++; aj++; } } ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatGetRowMin_SeqAIJ" PetscErrorCode MatGetRowMin_SeqAIJ(Mat A,Vec v,PetscInt idx[]) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,j,m = A->rmap->n,ncols,n; const PetscInt *ai,*aj; PetscScalar *x; const MatScalar *aa; PetscFunctionBegin; if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); aa = a->a; ai = a->i; aj = a->j; ierr = VecSet(v,0.0);CHKERRQ(ierr); ierr = VecGetArray(v,&x);CHKERRQ(ierr); ierr = VecGetLocalSize(v,&n);CHKERRQ(ierr); if (n != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector"); for (i=0; icmap->n) { /* row is dense */ x[i] = *aa; if (idx) idx[i] = 0; } else { /* row is sparse so already KNOW minimum is 0.0 or lower */ x[i] = 0.0; if (idx) { /* find first implicit 0.0 in the row */ idx[i] = 0; /* in case ncols is zero */ for (j=0; j j) { idx[i] = j; break; } } } } for (j=0; j PetscRealPart(*aa)) {x[i] = *aa; if (idx) idx[i] = *aj;} aa++; aj++; } } ierr = VecRestoreArray(v,&x);CHKERRQ(ierr); PetscFunctionReturn(0); } #include #include #undef __FUNCT__ #define __FUNCT__ "MatInvertBlockDiagonal_SeqAIJ" PetscErrorCode MatInvertBlockDiagonal_SeqAIJ(Mat A,const PetscScalar **values) { Mat_SeqAIJ *a = (Mat_SeqAIJ*) A->data; PetscErrorCode ierr; PetscInt i,bs = PetscAbs(A->rmap->bs),mbs = A->rmap->n/bs,ipvt[5],bs2 = bs*bs,*v_pivots,ij[7],*IJ,j; MatScalar *diag,work[25],*v_work; PetscReal shift = 0.0; PetscFunctionBegin; if (a->ibdiagvalid) { if (values) *values = a->ibdiag; PetscFunctionReturn(0); } ierr = MatMarkDiagonal_SeqAIJ(A);CHKERRQ(ierr); if (!a->ibdiag) { ierr = PetscMalloc1(bs2*mbs,&a->ibdiag);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));CHKERRQ(ierr); } diag = a->ibdiag; if (values) *values = a->ibdiag; /* factor and invert each block */ switch (bs) { case 1: for (i=0; iibdiagvalid = PETSC_TRUE; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetRandom_SeqAIJ" static PetscErrorCode MatSetRandom_SeqAIJ(Mat x,PetscRandom rctx) { PetscErrorCode ierr; Mat_SeqAIJ *aij = (Mat_SeqAIJ*)x->data; PetscScalar a; PetscInt m,n,i,j,col; PetscFunctionBegin; if (!x->assembled) { ierr = MatGetSize(x,&m,&n);CHKERRQ(ierr); for (i=0; iimax[i]; j++) { ierr = PetscRandomGetValue(rctx,&a);CHKERRQ(ierr); col = (PetscInt)(n*PetscRealPart(a)); ierr = MatSetValues(x,1,&i,1,&col,&a,ADD_VALUES);CHKERRQ(ierr); } } } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not yet coded"); ierr = MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatShift_SeqAIJ" PetscErrorCode MatShift_SeqAIJ(Mat Y,PetscScalar a) { PetscErrorCode ierr; Mat_SeqAIJ *aij = (Mat_SeqAIJ*)Y->data; PetscFunctionBegin; if (!aij->nz) { ierr = MatSeqAIJSetPreallocation(Y,1,NULL);CHKERRQ(ierr); } ierr = MatShift_Basic(Y,a);CHKERRQ(ierr); PetscFunctionReturn(0); } /* -------------------------------------------------------------------*/ static struct _MatOps MatOps_Values = { MatSetValues_SeqAIJ, MatGetRow_SeqAIJ, MatRestoreRow_SeqAIJ, MatMult_SeqAIJ, /* 4*/ MatMultAdd_SeqAIJ, MatMultTranspose_SeqAIJ, MatMultTransposeAdd_SeqAIJ, 0, 0, 0, /* 10*/ 0, MatLUFactor_SeqAIJ, 0, MatSOR_SeqAIJ, MatTranspose_SeqAIJ, /*1 5*/ MatGetInfo_SeqAIJ, MatEqual_SeqAIJ, MatGetDiagonal_SeqAIJ, MatDiagonalScale_SeqAIJ, MatNorm_SeqAIJ, /* 20*/ 0, MatAssemblyEnd_SeqAIJ, MatSetOption_SeqAIJ, MatZeroEntries_SeqAIJ, /* 24*/ MatZeroRows_SeqAIJ, 0, 0, 0, 0, /* 29*/ MatSetUp_SeqAIJ, 0, 0, 0, 0, /* 34*/ MatDuplicate_SeqAIJ, 0, 0, MatILUFactor_SeqAIJ, 0, /* 39*/ MatAXPY_SeqAIJ, MatGetSubMatrices_SeqAIJ, MatIncreaseOverlap_SeqAIJ, MatGetValues_SeqAIJ, MatCopy_SeqAIJ, /* 44*/ MatGetRowMax_SeqAIJ, MatScale_SeqAIJ, MatShift_SeqAIJ, MatDiagonalSet_SeqAIJ, MatZeroRowsColumns_SeqAIJ, /* 49*/ MatSetRandom_SeqAIJ, MatGetRowIJ_SeqAIJ, MatRestoreRowIJ_SeqAIJ, MatGetColumnIJ_SeqAIJ, MatRestoreColumnIJ_SeqAIJ, /* 54*/ MatFDColoringCreate_SeqXAIJ, 0, 0, MatPermute_SeqAIJ, 0, /* 59*/ 0, MatDestroy_SeqAIJ, MatView_SeqAIJ, 0, MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ, /* 64*/ MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ, MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ, 0, 0, 0, /* 69*/ MatGetRowMaxAbs_SeqAIJ, MatGetRowMinAbs_SeqAIJ, 0, MatSetColoring_SeqAIJ, 0, /* 74*/ MatSetValuesAdifor_SeqAIJ, MatFDColoringApply_AIJ, 0, 0, 0, /* 79*/ MatFindZeroDiagonals_SeqAIJ, 0, 0, 0, MatLoad_SeqAIJ, /* 84*/ MatIsSymmetric_SeqAIJ, MatIsHermitian_SeqAIJ, 0, 0, 0, /* 89*/ MatMatMult_SeqAIJ_SeqAIJ, MatMatMultSymbolic_SeqAIJ_SeqAIJ, MatMatMultNumeric_SeqAIJ_SeqAIJ, MatPtAP_SeqAIJ_SeqAIJ, MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy, /* 94*/ MatPtAPNumeric_SeqAIJ_SeqAIJ, MatMatTransposeMult_SeqAIJ_SeqAIJ, MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ, MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ, 0, /* 99*/ 0, 0, 0, MatConjugate_SeqAIJ, 0, /*104*/ MatSetValuesRow_SeqAIJ, MatRealPart_SeqAIJ, MatImaginaryPart_SeqAIJ, 0, 0, /*109*/ MatMatSolve_SeqAIJ, 0, MatGetRowMin_SeqAIJ, 0, MatMissingDiagonal_SeqAIJ, /*114*/ 0, 0, 0, 0, 0, /*119*/ 0, 0, 0, 0, MatGetMultiProcBlock_SeqAIJ, /*124*/ MatFindNonzeroRows_SeqAIJ, MatGetColumnNorms_SeqAIJ, MatInvertBlockDiagonal_SeqAIJ, 0, 0, /*129*/ 0, MatTransposeMatMult_SeqAIJ_SeqAIJ, MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ, MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ, MatTransposeColoringCreate_SeqAIJ, /*134*/ MatTransColoringApplySpToDen_SeqAIJ, MatTransColoringApplyDenToSp_SeqAIJ, MatRARt_SeqAIJ_SeqAIJ, MatRARtSymbolic_SeqAIJ_SeqAIJ, MatRARtNumeric_SeqAIJ_SeqAIJ, /*139*/0, 0, 0, MatFDColoringSetUp_SeqXAIJ, MatFindOffBlockDiagonalEntries_SeqAIJ, /*144*/MatCreateMPIMatConcatenateSeqMat_SeqAIJ }; #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJSetColumnIndices_SeqAIJ" PetscErrorCode MatSeqAIJSetColumnIndices_SeqAIJ(Mat mat,PetscInt *indices) { Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; PetscInt i,nz,n; PetscFunctionBegin; nz = aij->maxnz; n = mat->rmap->n; for (i=0; ij[i] = indices[i]; } aij->nz = nz; for (i=0; iilen[i] = aij->imax[i]; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJSetColumnIndices" /*@ MatSeqAIJSetColumnIndices - Set the column indices for all the rows in the matrix. Input Parameters: + mat - the SeqAIJ matrix - indices - the column indices Level: advanced Notes: This can be called if you have precomputed the nonzero structure of the matrix and want to provide it to the matrix object to improve the performance of the MatSetValues() operation. You MUST have set the correct numbers of nonzeros per row in the call to MatCreateSeqAIJ(), and the columns indices MUST be sorted. MUST be called before any calls to MatSetValues(); The indices should start with zero, not one. @*/ PetscErrorCode MatSeqAIJSetColumnIndices(Mat mat,PetscInt *indices) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(mat,MAT_CLASSID,1); PetscValidPointer(indices,2); ierr = PetscUseMethod(mat,"MatSeqAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));CHKERRQ(ierr); PetscFunctionReturn(0); } /* ----------------------------------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "MatStoreValues_SeqAIJ" PetscErrorCode MatStoreValues_SeqAIJ(Mat mat) { Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; PetscErrorCode ierr; size_t nz = aij->i[mat->rmap->n]; PetscFunctionBegin; if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); /* allocate space for values if not already there */ if (!aij->saved_values) { ierr = PetscMalloc1(nz+1,&aij->saved_values);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));CHKERRQ(ierr); } /* copy values over */ ierr = PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatStoreValues" /*@ MatStoreValues - Stashes a copy of the matrix values; this allows, for example, reuse of the linear part of a Jacobian, while recomputing the nonlinear portion. Collect on Mat Input Parameters: . mat - the matrix (currently only AIJ matrices support this option) Level: advanced Common Usage, with SNESSolve(): $ Create Jacobian matrix $ Set linear terms into matrix $ Apply boundary conditions to matrix, at this time matrix must have $ final nonzero structure (i.e. setting the nonlinear terms and applying $ boundary conditions again will not change the nonzero structure $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); $ ierr = MatStoreValues(mat); $ Call SNESSetJacobian() with matrix $ In your Jacobian routine $ ierr = MatRetrieveValues(mat); $ Set nonlinear terms in matrix Common Usage without SNESSolve(), i.e. when you handle nonlinear solve yourself: $ // build linear portion of Jacobian $ ierr = MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); $ ierr = MatStoreValues(mat); $ loop over nonlinear iterations $ ierr = MatRetrieveValues(mat); $ // call MatSetValues(mat,...) to set nonliner portion of Jacobian $ // call MatAssemblyBegin/End() on matrix $ Solve linear system with Jacobian $ endloop Notes: Matrix must already be assemblied before calling this routine Must set the matrix option MatSetOption(mat,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE); before calling this routine. When this is called multiple times it overwrites the previous set of stored values and does not allocated additional space. .seealso: MatRetrieveValues() @*/ PetscErrorCode MatStoreValues(Mat mat) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(mat,MAT_CLASSID,1); if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); ierr = PetscUseMethod(mat,"MatStoreValues_C",(Mat),(mat));CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRetrieveValues_SeqAIJ" PetscErrorCode MatRetrieveValues_SeqAIJ(Mat mat) { Mat_SeqAIJ *aij = (Mat_SeqAIJ*)mat->data; PetscErrorCode ierr; PetscInt nz = aij->i[mat->rmap->n]; PetscFunctionBegin; if (!aij->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first"); if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first"); /* copy values over */ ierr = PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatRetrieveValues" /*@ MatRetrieveValues - Retrieves the copy of the matrix values; this allows, for example, reuse of the linear part of a Jacobian, while recomputing the nonlinear portion. Collect on Mat Input Parameters: . mat - the matrix (currently on AIJ matrices support this option) Level: advanced .seealso: MatStoreValues() @*/ PetscErrorCode MatRetrieveValues(Mat mat) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(mat,MAT_CLASSID,1); if (!mat->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix"); if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix"); ierr = PetscUseMethod(mat,"MatRetrieveValues_C",(Mat),(mat));CHKERRQ(ierr); PetscFunctionReturn(0); } /* --------------------------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "MatCreateSeqAIJ" /*@C MatCreateSeqAIJ - Creates a sparse matrix in AIJ (compressed row) format (the default parallel PETSc format). For good matrix assembly performance the user should preallocate the matrix storage by setting the parameter nz (or the array nnz). By setting these parameters accurately, performance during matrix assembly can be increased by more than a factor of 50. Collective on MPI_Comm Input Parameters: + comm - MPI communicator, set to PETSC_COMM_SELF . m - number of rows . n - number of columns . nz - number of nonzeros per row (same for all rows) - nnz - array containing the number of nonzeros in the various rows (possibly different for each row) or NULL Output Parameter: . A - the matrix It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(), MatXXXXSetPreallocation() paradgm instead of this routine directly. [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation] Notes: If nnz is given then nz is ignored The AIJ format (also called the Yale sparse matrix format or compressed row storage), is fully compatible with standard Fortran 77 storage. That is, the stored row and column indices can begin at either one (as in Fortran) or zero. See the users' manual for details. Specify the preallocated storage with either nz or nnz (not both). Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory allocation. For large problems you MUST preallocate memory or you will get TERRIBLE performance, see the users' manual chapter on matrices. By default, this format uses inodes (identical nodes) when possible, to improve numerical efficiency of matrix-vector products and solves. We search for consecutive rows with the same nonzero structure, thereby reusing matrix information to achieve increased efficiency. Options Database Keys: + -mat_no_inode - Do not use inodes - -mat_inode_limit - Sets inode limit (max limit=5) Level: intermediate .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays() @*/ PetscErrorCode MatCreateSeqAIJ(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatCreate(comm,A);CHKERRQ(ierr); ierr = MatSetSizes(*A,m,n,m,n);CHKERRQ(ierr); ierr = MatSetType(*A,MATSEQAIJ);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation_SeqAIJ(*A,nz,nnz);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJSetPreallocation" /*@C MatSeqAIJSetPreallocation - For good matrix assembly performance the user should preallocate the matrix storage by setting the parameter nz (or the array nnz). By setting these parameters accurately, performance during matrix assembly can be increased by more than a factor of 50. Collective on MPI_Comm Input Parameters: + B - The matrix . nz - number of nonzeros per row (same for all rows) - nnz - array containing the number of nonzeros in the various rows (possibly different for each row) or NULL Notes: If nnz is given then nz is ignored The AIJ format (also called the Yale sparse matrix format or compressed row storage), is fully compatible with standard Fortran 77 storage. That is, the stored row and column indices can begin at either one (as in Fortran) or zero. See the users' manual for details. Specify the preallocated storage with either nz or nnz (not both). Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory allocation. For large problems you MUST preallocate memory or you will get TERRIBLE performance, see the users' manual chapter on matrices. You can call MatGetInfo() to get information on how effective the preallocation was; for example the fields mallocs,nz_allocated,nz_used,nz_unneeded; You can also run with the option -info and look for messages with the string malloc in them to see if additional memory allocation was needed. Developers: Use nz of MAT_SKIP_ALLOCATION to not allocate any space for the matrix entries or columns indices By default, this format uses inodes (identical nodes) when possible, to improve numerical efficiency of matrix-vector products and solves. We search for consecutive rows with the same nonzero structure, thereby reusing matrix information to achieve increased efficiency. Options Database Keys: + -mat_no_inode - Do not use inodes . -mat_inode_limit - Sets inode limit (max limit=5) - -mat_aij_oneindex - Internally use indexing starting at 1 rather than 0. Note that when calling MatSetValues(), the user still MUST index entries starting at 0! Level: intermediate .seealso: MatCreate(), MatCreateAIJ(), MatSetValues(), MatSeqAIJSetColumnIndices(), MatCreateSeqAIJWithArrays(), MatGetInfo() @*/ PetscErrorCode MatSeqAIJSetPreallocation(Mat B,PetscInt nz,const PetscInt nnz[]) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(B,MAT_CLASSID,1); PetscValidType(B,1); ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocation_C",(Mat,PetscInt,const PetscInt[]),(B,nz,nnz));CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJSetPreallocation_SeqAIJ" PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat B,PetscInt nz,const PetscInt *nnz) { Mat_SeqAIJ *b; PetscBool skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE; PetscErrorCode ierr; PetscInt i; PetscFunctionBegin; if (nz >= 0 || nnz) realalloc = PETSC_TRUE; if (nz == MAT_SKIP_ALLOCATION) { skipallocation = PETSC_TRUE; nz = 0; } ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5; if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz); if (nnz) { for (i=0; irmap->n; i++) { 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]); 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); } } B->preallocated = PETSC_TRUE; b = (Mat_SeqAIJ*)B->data; if (!skipallocation) { if (!b->imax) { ierr = PetscMalloc2(B->rmap->n,&b->imax,B->rmap->n,&b->ilen);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)B,2*B->rmap->n*sizeof(PetscInt));CHKERRQ(ierr); } if (!nnz) { if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 10; else if (nz < 0) nz = 1; for (i=0; irmap->n; i++) b->imax[i] = nz; nz = nz*B->rmap->n; } else { nz = 0; for (i=0; irmap->n; i++) {b->imax[i] = nnz[i]; nz += nnz[i];} } /* b->ilen will count nonzeros in each row so far. */ for (i=0; irmap->n; i++) b->ilen[i] = 0; /* allocate the matrix space */ ierr = MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);CHKERRQ(ierr); ierr = PetscMalloc3(nz,&b->a,nz,&b->j,B->rmap->n+1,&b->i);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)B,(B->rmap->n+1)*sizeof(PetscInt)+nz*(sizeof(PetscScalar)+sizeof(PetscInt)));CHKERRQ(ierr); b->i[0] = 0; for (i=1; irmap->n+1; i++) { b->i[i] = b->i[i-1] + b->imax[i-1]; } b->singlemalloc = PETSC_TRUE; b->free_a = PETSC_TRUE; b->free_ij = PETSC_TRUE; } else { b->free_a = PETSC_FALSE; b->free_ij = PETSC_FALSE; } b->nz = 0; b->maxnz = nz; B->info.nz_unneeded = (double)b->maxnz; if (realalloc) { ierr = MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJSetPreallocationCSR" /*@ MatSeqAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format. Input Parameters: + B - the matrix . i - the indices into j for the start of each row (starts with zero) . j - the column indices for each row (starts with zero) these must be sorted for each row - v - optional values in the matrix Level: developer The i,j,v values are COPIED with this routine; to avoid the copy use MatCreateSeqAIJWithArrays() .keywords: matrix, aij, compressed row, sparse, sequential .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatSeqAIJSetPreallocation(), MatCreateSeqAIJ(), SeqAIJ @*/ PetscErrorCode MatSeqAIJSetPreallocationCSR(Mat B,const PetscInt i[],const PetscInt j[],const PetscScalar v[]) { PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(B,MAT_CLASSID,1); PetscValidType(B,1); ierr = PetscTryMethod(B,"MatSeqAIJSetPreallocationCSR_C",(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,i,j,v));CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJSetPreallocationCSR_SeqAIJ" PetscErrorCode MatSeqAIJSetPreallocationCSR_SeqAIJ(Mat B,const PetscInt Ii[],const PetscInt J[],const PetscScalar v[]) { PetscInt i; PetscInt m,n; PetscInt nz; PetscInt *nnz, nz_max = 0; PetscScalar *values; PetscErrorCode ierr; PetscFunctionBegin; if (Ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Ii[0] must be 0 it is %D", Ii[0]); ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr); ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr); ierr = MatGetSize(B, &m, &n);CHKERRQ(ierr); ierr = PetscMalloc1(m+1, &nnz);CHKERRQ(ierr); for (i = 0; i < m; i++) { nz = Ii[i+1]- Ii[i]; nz_max = PetscMax(nz_max, nz); if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D", i, nnz); nnz[i] = nz; } ierr = MatSeqAIJSetPreallocation(B, 0, nnz);CHKERRQ(ierr); ierr = PetscFree(nnz);CHKERRQ(ierr); if (v) { values = (PetscScalar*) v; } else { ierr = PetscCalloc1(nz_max, &values);CHKERRQ(ierr); } for (i = 0; i < m; i++) { nz = Ii[i+1] - Ii[i]; ierr = MatSetValues_SeqAIJ(B, 1, &i, nz, J+Ii[i], values + (v ? Ii[i] : 0), INSERT_VALUES);CHKERRQ(ierr); } ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); if (!v) { ierr = PetscFree(values);CHKERRQ(ierr); } ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr); PetscFunctionReturn(0); } #include <../src/mat/impls/dense/seq/dense.h> #include #undef __FUNCT__ #define __FUNCT__ "MatMatMultNumeric_SeqDense_SeqAIJ" /* Computes (B'*A')' since computing B*A directly is untenable n p p ( ) ( ) ( ) m ( A ) * n ( B ) = m ( C ) ( ) ( ) ( ) */ PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat A,Mat B,Mat C) { PetscErrorCode ierr; Mat_SeqDense *sub_a = (Mat_SeqDense*)A->data; Mat_SeqAIJ *sub_b = (Mat_SeqAIJ*)B->data; Mat_SeqDense *sub_c = (Mat_SeqDense*)C->data; PetscInt i,n,m,q,p; const PetscInt *ii,*idx; const PetscScalar *b,*a,*a_q; PetscScalar *c,*c_q; PetscFunctionBegin; m = A->rmap->n; n = A->cmap->n; p = B->cmap->n; a = sub_a->v; b = sub_b->a; c = sub_c->v; ierr = PetscMemzero(c,m*p*sizeof(PetscScalar));CHKERRQ(ierr); ii = sub_b->i; idx = sub_b->j; for (i=0; i0) { c_q = c + m*(*idx); a_q = a + m*i; PetscKernelAXPY(c_q,*b,a_q,m); idx++; b++; } } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatMatMultSymbolic_SeqDense_SeqAIJ" PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat A,Mat B,PetscReal fill,Mat *C) { PetscErrorCode ierr; PetscInt m=A->rmap->n,n=B->cmap->n; Mat Cmat; PetscFunctionBegin; 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); ierr = MatCreate(PetscObjectComm((PetscObject)A),&Cmat);CHKERRQ(ierr); ierr = MatSetSizes(Cmat,m,n,m,n);CHKERRQ(ierr); ierr = MatSetBlockSizesFromMats(Cmat,A,B);CHKERRQ(ierr); ierr = MatSetType(Cmat,MATSEQDENSE);CHKERRQ(ierr); ierr = MatSeqDenseSetPreallocation(Cmat,NULL);CHKERRQ(ierr); Cmat->ops->matmultnumeric = MatMatMultNumeric_SeqDense_SeqAIJ; *C = Cmat; PetscFunctionReturn(0); } /* ----------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "MatMatMult_SeqDense_SeqAIJ" PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat A,Mat B,MatReuse scall,PetscReal fill,Mat *C) { PetscErrorCode ierr; PetscFunctionBegin; if (scall == MAT_INITIAL_MATRIX) { ierr = PetscLogEventBegin(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); ierr = MatMatMultSymbolic_SeqDense_SeqAIJ(A,B,fill,C);CHKERRQ(ierr); ierr = PetscLogEventEnd(MAT_MatMultSymbolic,A,B,0,0);CHKERRQ(ierr); } ierr = PetscLogEventBegin(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); ierr = MatMatMultNumeric_SeqDense_SeqAIJ(A,B,*C);CHKERRQ(ierr); ierr = PetscLogEventEnd(MAT_MatMultNumeric,A,B,0,0);CHKERRQ(ierr); PetscFunctionReturn(0); } /*MC MATSEQAIJ - MATSEQAIJ = "seqaij" - A matrix type to be used for sequential sparse matrices, based on compressed sparse row format. Options Database Keys: . -mat_type seqaij - sets the matrix type to "seqaij" during a call to MatSetFromOptions() Level: beginner .seealso: MatCreateSeqAIJ(), MatSetFromOptions(), MatSetType(), MatCreate(), MatType M*/ /*MC MATAIJ - MATAIJ = "aij" - A matrix type to be used for sparse matrices. This matrix type is identical to MATSEQAIJ when constructed with a single process communicator, and MATMPIAIJ otherwise. As a result, for single process communicators, MatSeqAIJSetPreallocation is supported, and similarly MatMPIAIJSetPreallocation is supported for communicators controlling multiple processes. It is recommended that you call both of the above preallocation routines for simplicity. Options Database Keys: . -mat_type aij - sets the matrix type to "aij" during a call to MatSetFromOptions() Developer Notes: Subclasses include MATAIJCUSP, MATAIJPERM, MATAIJCRL, and also automatically switches over to use inodes when enough exist. Level: beginner .seealso: MatCreateAIJ(), MatCreateSeqAIJ(), MATSEQAIJ,MATMPIAIJ M*/ /*MC MATAIJCRL - MATAIJCRL = "aijcrl" - A matrix type to be used for sparse matrices. This matrix type is identical to MATSEQAIJCRL when constructed with a single process communicator, and MATMPIAIJCRL otherwise. As a result, for single process communicators, MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported for communicators controlling multiple processes. It is recommended that you call both of the above preallocation routines for simplicity. Options Database Keys: . -mat_type aijcrl - sets the matrix type to "aijcrl" during a call to MatSetFromOptions() Level: beginner .seealso: MatCreateMPIAIJCRL,MATSEQAIJCRL,MATMPIAIJCRL, MATSEQAIJCRL, MATMPIAIJCRL M*/ PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*); #if defined(PETSC_HAVE_ELEMENTAL) PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*); #endif PETSC_EXTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*); #if defined(PETSC_HAVE_MATLAB_ENGINE) PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*); PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*); #endif #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJGetArray" /*@C MatSeqAIJGetArray - gives access to the array where the data for a SeqSeqAIJ matrix is stored Not Collective Input Parameter: . mat - a MATSEQAIJ matrix Output Parameter: . array - pointer to the data Level: intermediate .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() @*/ PetscErrorCode MatSeqAIJGetArray(Mat A,PetscScalar **array) { PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscUseMethod(A,"MatSeqAIJGetArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJGetMaxRowNonzeros" /*@C MatSeqAIJGetMaxRowNonzeros - returns the maximum number of nonzeros in any row Not Collective Input Parameter: . mat - a MATSEQAIJ matrix Output Parameter: . nz - the maximum number of nonzeros in any row Level: intermediate .seealso: MatSeqAIJRestoreArray(), MatSeqAIJGetArrayF90() @*/ PetscErrorCode MatSeqAIJGetMaxRowNonzeros(Mat A,PetscInt *nz) { Mat_SeqAIJ *aij = (Mat_SeqAIJ*)A->data; PetscFunctionBegin; *nz = aij->rmax; PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSeqAIJRestoreArray" /*@C MatSeqAIJRestoreArray - returns access to the array where the data for a MATSEQAIJ matrix is stored obtained by MatSeqAIJGetArray() Not Collective Input Parameters: . mat - a MATSEQAIJ matrix . array - pointer to the data Level: intermediate .seealso: MatSeqAIJGetArray(), MatSeqAIJRestoreArrayF90() @*/ PetscErrorCode MatSeqAIJRestoreArray(Mat A,PetscScalar **array) { PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscUseMethod(A,"MatSeqAIJRestoreArray_C",(Mat,PetscScalar**),(A,array));CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatCreate_SeqAIJ" PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat B) { Mat_SeqAIJ *b; PetscErrorCode ierr; PetscMPIInt size; PetscFunctionBegin; ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);CHKERRQ(ierr); if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Comm must be of size 1"); ierr = PetscNewLog(B,&b);CHKERRQ(ierr); B->data = (void*)b; ierr = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr); b->row = 0; b->col = 0; b->icol = 0; b->reallocs = 0; b->ignorezeroentries = PETSC_FALSE; b->roworiented = PETSC_TRUE; b->nonew = 0; b->diag = 0; b->solve_work = 0; B->spptr = 0; b->saved_values = 0; b->idiag = 0; b->mdiag = 0; b->ssor_work = 0; b->omega = 1.0; b->fshift = 0.0; b->idiagvalid = PETSC_FALSE; b->ibdiagvalid = PETSC_FALSE; b->keepnonzeropattern = PETSC_FALSE; ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJGetArray_C",MatSeqAIJGetArray_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJRestoreArray_C",MatSeqAIJRestoreArray_SeqAIJ);CHKERRQ(ierr); #if defined(PETSC_HAVE_MATLAB_ENGINE) ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEnginePut_C",MatlabEnginePut_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"PetscMatlabEngineGet_C",MatlabEngineGet_SeqAIJ);CHKERRQ(ierr); #endif ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetColumnIndices_C",MatSeqAIJSetColumnIndices_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqsbaij_C",MatConvert_SeqAIJ_SeqSBAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqbaij_C",MatConvert_SeqAIJ_SeqBAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijperm_C",MatConvert_SeqAIJ_SeqAIJPERM);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqaijcrl_C",MatConvert_SeqAIJ_SeqAIJCRL);CHKERRQ(ierr); #if defined(PETSC_HAVE_ELEMENTAL) ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_elemental_C",MatConvert_SeqAIJ_Elemental);CHKERRQ(ierr); #endif ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqaij_seqdense_C",MatConvert_SeqAIJ_SeqDense);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatIsHermitianTranspose_C",MatIsTranspose_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocation_C",MatSeqAIJSetPreallocation_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatSeqAIJSetPreallocationCSR_C",MatSeqAIJSetPreallocationCSR_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatReorderForNonzeroDiagonal_C",MatReorderForNonzeroDiagonal_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMult_seqdense_seqaij_C",MatMatMult_SeqDense_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultSymbolic_seqdense_seqaij_C",MatMatMultSymbolic_SeqDense_SeqAIJ);CHKERRQ(ierr); ierr = PetscObjectComposeFunction((PetscObject)B,"MatMatMultNumeric_seqdense_seqaij_C",MatMatMultNumeric_SeqDense_SeqAIJ);CHKERRQ(ierr); ierr = MatCreate_SeqAIJ_Inode(B);CHKERRQ(ierr); ierr = PetscObjectChangeTypeName((PetscObject)B,MATSEQAIJ);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDuplicateNoCreate_SeqAIJ" /* Given a matrix generated with MatGetFactor() duplicates all the information in A into B */ PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace) { Mat_SeqAIJ *c,*a = (Mat_SeqAIJ*)A->data; PetscErrorCode ierr; PetscInt i,m = A->rmap->n; PetscFunctionBegin; c = (Mat_SeqAIJ*)C->data; C->factortype = A->factortype; c->row = 0; c->col = 0; c->icol = 0; c->reallocs = 0; C->assembled = PETSC_TRUE; ierr = PetscLayoutReference(A->rmap,&C->rmap);CHKERRQ(ierr); ierr = PetscLayoutReference(A->cmap,&C->cmap);CHKERRQ(ierr); ierr = PetscMalloc2(m,&c->imax,m,&c->ilen);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)C, 2*m*sizeof(PetscInt));CHKERRQ(ierr); for (i=0; iimax[i] = a->imax[i]; c->ilen[i] = a->ilen[i]; } /* allocate the matrix space */ if (mallocmatspace) { ierr = PetscMalloc3(a->i[m],&c->a,a->i[m],&c->j,m+1,&c->i);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)C, a->i[m]*(sizeof(PetscScalar)+sizeof(PetscInt))+(m+1)*sizeof(PetscInt));CHKERRQ(ierr); c->singlemalloc = PETSC_TRUE; ierr = PetscMemcpy(c->i,a->i,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); if (m > 0) { ierr = PetscMemcpy(c->j,a->j,(a->i[m])*sizeof(PetscInt));CHKERRQ(ierr); if (cpvalues == MAT_COPY_VALUES) { ierr = PetscMemcpy(c->a,a->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); } else { ierr = PetscMemzero(c->a,(a->i[m])*sizeof(PetscScalar));CHKERRQ(ierr); } } } c->ignorezeroentries = a->ignorezeroentries; c->roworiented = a->roworiented; c->nonew = a->nonew; if (a->diag) { ierr = PetscMalloc1(m+1,&c->diag);CHKERRQ(ierr); ierr = PetscLogObjectMemory((PetscObject)C,(m+1)*sizeof(PetscInt));CHKERRQ(ierr); for (i=0; idiag[i] = a->diag[i]; } } else c->diag = 0; c->solve_work = 0; c->saved_values = 0; c->idiag = 0; c->ssor_work = 0; c->keepnonzeropattern = a->keepnonzeropattern; c->free_a = PETSC_TRUE; c->free_ij = PETSC_TRUE; c->rmax = a->rmax; c->nz = a->nz; c->maxnz = a->nz; /* Since we allocate exactly the right amount */ C->preallocated = PETSC_TRUE; c->compressedrow.use = a->compressedrow.use; c->compressedrow.nrows = a->compressedrow.nrows; if (a->compressedrow.use) { i = a->compressedrow.nrows; ierr = PetscMalloc2(i+1,&c->compressedrow.i,i,&c->compressedrow.rindex);CHKERRQ(ierr); ierr = PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));CHKERRQ(ierr); ierr = PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));CHKERRQ(ierr); } else { c->compressedrow.use = PETSC_FALSE; c->compressedrow.i = NULL; c->compressedrow.rindex = NULL; } c->nonzerorowcnt = a->nonzerorowcnt; C->nonzerostate = A->nonzerostate; ierr = MatDuplicate_SeqAIJ_Inode(A,cpvalues,&C);CHKERRQ(ierr); ierr = PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatDuplicate_SeqAIJ" PetscErrorCode MatDuplicate_SeqAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatCreate(PetscObjectComm((PetscObject)A),B);CHKERRQ(ierr); ierr = MatSetSizes(*B,A->rmap->n,A->cmap->n,A->rmap->n,A->cmap->n);CHKERRQ(ierr); if (!(A->rmap->n % A->rmap->bs) && !(A->cmap->n % A->cmap->bs)) { ierr = MatSetBlockSizesFromMats(*B,A,A);CHKERRQ(ierr); } ierr = MatSetType(*B,((PetscObject)A)->type_name);CHKERRQ(ierr); ierr = MatDuplicateNoCreate_SeqAIJ(*B,A,cpvalues,PETSC_TRUE);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatLoad_SeqAIJ" PetscErrorCode MatLoad_SeqAIJ(Mat newMat, PetscViewer viewer) { Mat_SeqAIJ *a; PetscErrorCode ierr; PetscInt i,sum,nz,header[4],*rowlengths = 0,M,N,rows,cols; int fd; PetscMPIInt size; MPI_Comm comm; PetscInt bs = newMat->rmap->bs; PetscFunctionBegin; /* force binary viewer to load .info file if it has not yet done so */ ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr); ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr); ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"view must have one processor"); ierr = PetscOptionsBegin(comm,NULL,"Options for loading SEQAIJ matrix","Mat");CHKERRQ(ierr); ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr); ierr = PetscOptionsEnd();CHKERRQ(ierr); if (bs < 0) bs = 1; ierr = MatSetBlockSize(newMat,bs);CHKERRQ(ierr); ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr); ierr = PetscBinaryRead(fd,header,4,PETSC_INT);CHKERRQ(ierr); if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object in file"); M = header[1]; N = header[2]; nz = header[3]; if (nz < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format on disk,cannot load as SeqAIJ"); /* read in row lengths */ ierr = PetscMalloc1(M,&rowlengths);CHKERRQ(ierr); ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr); /* check if sum of rowlengths is same as nz */ for (i=0,sum=0; i< M; i++) sum +=rowlengths[i]; if (sum != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_READ,"Inconsistant matrix data in file. no-nonzeros = %dD, sum-row-lengths = %D\n",nz,sum); /* set global size if not set already*/ if (newMat->rmap->n < 0 && newMat->rmap->N < 0 && newMat->cmap->n < 0 && newMat->cmap->N < 0) { ierr = MatSetSizes(newMat,PETSC_DECIDE,PETSC_DECIDE,M,N);CHKERRQ(ierr); } else { /* if sizes and type are already set, check if the matrix global sizes are correct */ ierr = MatGetSize(newMat,&rows,&cols);CHKERRQ(ierr); if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */ ierr = MatGetLocalSize(newMat,&rows,&cols);CHKERRQ(ierr); } 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); } ierr = MatSeqAIJSetPreallocation_SeqAIJ(newMat,0,rowlengths);CHKERRQ(ierr); a = (Mat_SeqAIJ*)newMat->data; ierr = PetscBinaryRead(fd,a->j,nz,PETSC_INT);CHKERRQ(ierr); /* read in nonzero values */ ierr = PetscBinaryRead(fd,a->a,nz,PETSC_SCALAR);CHKERRQ(ierr); /* set matrix "i" values */ a->i[0] = 0; for (i=1; i<= M; i++) { a->i[i] = a->i[i-1] + rowlengths[i-1]; a->ilen[i-1] = rowlengths[i-1]; } ierr = PetscFree(rowlengths);CHKERRQ(ierr); ierr = MatAssemblyBegin(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(newMat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatEqual_SeqAIJ" PetscErrorCode MatEqual_SeqAIJ(Mat A,Mat B,PetscBool * flg) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data,*b = (Mat_SeqAIJ*)B->data; PetscErrorCode ierr; #if defined(PETSC_USE_COMPLEX) PetscInt k; #endif PetscFunctionBegin; /* If the matrix dimensions are not equal,or no of nonzeros */ if ((A->rmap->n != B->rmap->n) || (A->cmap->n != B->cmap->n) ||(a->nz != b->nz)) { *flg = PETSC_FALSE; PetscFunctionReturn(0); } /* if the a->i are the same */ ierr = PetscMemcmp(a->i,b->i,(A->rmap->n+1)*sizeof(PetscInt),flg);CHKERRQ(ierr); if (!*flg) PetscFunctionReturn(0); /* if a->j are the same */ ierr = PetscMemcmp(a->j,b->j,(a->nz)*sizeof(PetscInt),flg);CHKERRQ(ierr); if (!*flg) PetscFunctionReturn(0); /* if a->a are the same */ #if defined(PETSC_USE_COMPLEX) for (k=0; knz; k++) { if (PetscRealPart(a->a[k]) != PetscRealPart(b->a[k]) || PetscImaginaryPart(a->a[k]) != PetscImaginaryPart(b->a[k])) { *flg = PETSC_FALSE; PetscFunctionReturn(0); } } #else ierr = PetscMemcmp(a->a,b->a,(a->nz)*sizeof(PetscScalar),flg);CHKERRQ(ierr); #endif PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatCreateSeqAIJWithArrays" /*@ MatCreateSeqAIJWithArrays - Creates an sequential AIJ matrix using matrix elements (in CSR format) provided by the user. Collective on MPI_Comm Input Parameters: + comm - must be an MPI communicator of size 1 . m - number of rows . n - number of columns . i - row indices . j - column indices - a - matrix values Output Parameter: . mat - the matrix Level: intermediate Notes: The i, j, and a arrays are not copied by this routine, the user must free these arrays once the matrix is destroyed and not before You cannot set new nonzero locations into this matrix, that will generate an error. The i and j indices are 0 based The format which is used for the sparse matrix input, is equivalent to a row-major ordering.. i.e for the following matrix, the input data expected is as shown: 1 0 0 2 0 3 4 5 6 i = {0,1,3,6} [size = nrow+1 = 3+1] j = {0,0,2,0,1,2} [size = nz = 6]; values must be sorted for each row v = {1,2,3,4,5,6} [size = nz = 6] .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateMPIAIJWithArrays(), MatMPIAIJSetPreallocationCSR() @*/ PetscErrorCode MatCreateSeqAIJWithArrays(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat) { PetscErrorCode ierr; PetscInt ii; Mat_SeqAIJ *aij; #if defined(PETSC_USE_DEBUG) PetscInt jj; #endif PetscFunctionBegin; if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0"); ierr = MatCreate(comm,mat);CHKERRQ(ierr); ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); /* ierr = MatSetBlockSizes(*mat,,);CHKERRQ(ierr); */ ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,MAT_SKIP_ALLOCATION,0);CHKERRQ(ierr); aij = (Mat_SeqAIJ*)(*mat)->data; ierr = PetscMalloc2(m,&aij->imax,m,&aij->ilen);CHKERRQ(ierr); aij->i = i; aij->j = j; aij->a = a; aij->singlemalloc = PETSC_FALSE; aij->nonew = -1; /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/ aij->free_a = PETSC_FALSE; aij->free_ij = PETSC_FALSE; for (ii=0; iiilen[ii] = aij->imax[ii] = i[ii+1] - i[ii]; #if defined(PETSC_USE_DEBUG) 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]); for (jj=i[ii]+1; jji[m]; ii++) { if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %D index = %D",ii,j[ii]); 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]); } #endif ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatCreateSeqAIJFromTriple" /*@C MatCreateSeqAIJFromTriple - Creates an sequential AIJ matrix using matrix elements (in COO format) provided by the user. Collective on MPI_Comm Input Parameters: + comm - must be an MPI communicator of size 1 . m - number of rows . n - number of columns . i - row indices . j - column indices . a - matrix values . nz - number of nonzeros - idx - 0 or 1 based Output Parameter: . mat - the matrix Level: intermediate Notes: The i and j indices are 0 based The format which is used for the sparse matrix input, is equivalent to a row-major ordering.. i.e for the following matrix, the input data expected is as shown: 1 0 0 2 0 3 4 5 6 i = {0,1,1,2,2,2} j = {0,0,2,0,1,2} v = {1,2,3,4,5,6} .seealso: MatCreate(), MatCreateAIJ(), MatCreateSeqAIJ(), MatCreateSeqAIJWithArrays(), MatMPIAIJSetPreallocationCSR() @*/ PetscErrorCode MatCreateSeqAIJFromTriple(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt *i,PetscInt *j,PetscScalar *a,Mat *mat,PetscInt nz,PetscBool idx) { PetscErrorCode ierr; PetscInt ii, *nnz, one = 1,row,col; PetscFunctionBegin; ierr = PetscCalloc1(m,&nnz);CHKERRQ(ierr); for (ii = 0; ii < nz; ii++) { nnz[i[ii] - !!idx] += 1; } ierr = MatCreate(comm,mat);CHKERRQ(ierr); ierr = MatSetSizes(*mat,m,n,m,n);CHKERRQ(ierr); ierr = MatSetType(*mat,MATSEQAIJ);CHKERRQ(ierr); ierr = MatSeqAIJSetPreallocation_SeqAIJ(*mat,0,nnz);CHKERRQ(ierr); for (ii = 0; ii < nz; ii++) { if (idx) { row = i[ii] - 1; col = j[ii] - 1; } else { row = i[ii]; col = j[ii]; } ierr = MatSetValues(*mat,one,&row,one,&col,&a[ii],ADD_VALUES);CHKERRQ(ierr); } ierr = MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr); ierr = PetscFree(nnz);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetColoring_SeqAIJ" PetscErrorCode MatSetColoring_SeqAIJ(Mat A,ISColoring coloring) { PetscErrorCode ierr; Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscFunctionBegin; if (coloring->ctype == IS_COLORING_GLOBAL) { ierr = ISColoringReference(coloring);CHKERRQ(ierr); a->coloring = coloring; } else if (coloring->ctype == IS_COLORING_GHOSTED) { PetscInt i,*larray; ISColoring ocoloring; ISColoringValue *colors; /* set coloring for diagonal portion */ ierr = PetscMalloc1(A->cmap->n,&larray);CHKERRQ(ierr); for (i=0; icmap->n; i++) larray[i] = i; ierr = ISGlobalToLocalMappingApply(A->cmap->mapping,IS_GTOLM_MASK,A->cmap->n,larray,NULL,larray);CHKERRQ(ierr); ierr = PetscMalloc1(A->cmap->n,&colors);CHKERRQ(ierr); for (i=0; icmap->n; i++) colors[i] = coloring->colors[larray[i]]; ierr = PetscFree(larray);CHKERRQ(ierr); ierr = ISColoringCreate(PETSC_COMM_SELF,coloring->n,A->cmap->n,colors,PETSC_OWN_POINTER,&ocoloring);CHKERRQ(ierr); a->coloring = ocoloring; } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatSetValuesAdifor_SeqAIJ" PetscErrorCode MatSetValuesAdifor_SeqAIJ(Mat A,PetscInt nl,void *advalues) { Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt m = A->rmap->n,*ii = a->i,*jj = a->j,nz,i,j; MatScalar *v = a->a; PetscScalar *values = (PetscScalar*)advalues; ISColoringValue *color; PetscFunctionBegin; if (!a->coloring) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Coloring not set for matrix"); color = a->coloring->colors; /* loop over rows */ for (i=0; idata; PetscErrorCode ierr; PetscFunctionBegin; a->idiagvalid = PETSC_FALSE; a->ibdiagvalid = PETSC_FALSE; ierr = MatSeqAIJInvalidateDiagonal_Inode(A);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_SeqAIJ" PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat) { PetscErrorCode ierr; PetscFunctionBegin; ierr = MatCreateMPIMatConcatenateSeqMat_MPIAIJ(comm,inmat,n,scall,outmat);CHKERRQ(ierr); PetscFunctionReturn(0); } /* Special version for direct calls from Fortran */ #include #if defined(PETSC_HAVE_FORTRAN_CAPS) #define matsetvaluesseqaij_ MATSETVALUESSEQAIJ #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE) #define matsetvaluesseqaij_ matsetvaluesseqaij #endif /* Change these macros so can be used in void function */ #undef CHKERRQ #define CHKERRQ(ierr) CHKERRABORT(PetscObjectComm((PetscObject)A),ierr) #undef SETERRQ2 #define SETERRQ2(comm,ierr,b,c,d) CHKERRABORT(comm,ierr) #undef SETERRQ3 #define SETERRQ3(comm,ierr,b,c,d,e) CHKERRABORT(comm,ierr) #undef __FUNCT__ #define __FUNCT__ "matsetvaluesseqaij_" PETSC_EXTERN void PETSC_STDCALL matsetvaluesseqaij_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[],InsertMode *isis, PetscErrorCode *_ierr) { Mat A = *AA; PetscInt m = *mm, n = *nn; InsertMode is = *isis; Mat_SeqAIJ *a = (Mat_SeqAIJ*)A->data; PetscInt *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N; PetscInt *imax,*ai,*ailen; PetscErrorCode ierr; PetscInt *aj,nonew = a->nonew,lastcol = -1; MatScalar *ap,value,*aa; PetscBool ignorezeroentries = a->ignorezeroentries; PetscBool roworiented = a->roworiented; PetscFunctionBegin; MatCheckPreallocated(A,1); imax = a->imax; ai = a->i; ailen = a->ilen; aj = a->j; aa = a->a; for (k=0; k= A->rmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Row too large"); #endif rp = aj + ai[row]; ap = aa + ai[row]; rmax = imax[row]; nrow = ailen[row]; low = 0; high = nrow; for (l=0; l= A->cmap->n) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Column too large"); #endif col = in[l]; if (roworiented) value = v[l + k*n]; else value = v[k + l*m]; if (value == 0.0 && ignorezeroentries && (is == ADD_VALUES)) continue; if (col <= lastcol) low = 0; else high = nrow; lastcol = col; while (high-low > 5) { t = (low+high)/2; if (rp[t] > col) high = t; else low = t; } for (i=low; i col) break; if (rp[i] == col) { if (is == ADD_VALUES) ap[i] += value; else ap[i] = value; goto noinsert; } } if (value == 0.0 && ignorezeroentries) goto noinsert; if (nonew == 1) goto noinsert; if (nonew == -1) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero in the matrix"); MatSeqXAIJReallocateAIJ(A,A->rmap->n,1,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar); N = nrow++ - 1; a->nz++; high++; /* shift up all the later entries in this row */ for (ii=N; ii>=i; ii--) { rp[ii+1] = rp[ii]; ap[ii+1] = ap[ii]; } rp[i] = col; ap[i] = value; A->nonzerostate++; noinsert:; low = i + 1; } ailen[row] = nrow; } PetscFunctionReturnVoid(); }