#ifdef PETSC_RCS_HEADER
static char vcid[] = "$Id: matrix.c,v 1.283 1998/03/20 22:48:33 bsmith Exp bsmith $";
#endif

/*
   This is where the abstract matrix operations are defined
*/

#include "src/mat/matimpl.h"        /*I "mat.h" I*/
#include "src/vec/vecimpl.h"  
#include "pinclude/pviewer.h"

#undef __FUNC__  
#define __FUNC__ "MatGetRow"
/*@C
   MatGetRow - Gets a row of a matrix.  You MUST call MatRestoreRow()
   for each row that you get to ensure that your application does
   not bleed memory.

   Input Parameters:
.  mat - the matrix
.  row - the row to get

   Output Parameters:
.  ncols -  the number of nonzeros in the row
.  cols - if nonzero, the column numbers
.  vals - if nonzero, the values

   Notes:
   This routine is provided for people who need to have direct access
   to the structure of a matrix.  We hope that we provide enough
   high-level matrix routines that few users will need it. 

   MatGetRow() always returns 0-based column indices, regardless of
   whether the internal representation is 0-based (default) or 1-based.

   For better efficiency, set cols and/or vals to PETSC_NULL if you do
   not wish to extract these quantities.

   The user can only examine the values extracted with MatGetRow();
   the values cannot be altered.  To change the matrix entries, one
   must use MatSetValues().

   You can only have one call to MatGetRow() outstanding for a particular
   matrix at a time.

   Fortran Notes:
$     The calling sequence from Fortran is 
$
$       MatGetRow(matrix,row,ncols,cols,values,ierr)
$         Mat     matrix (input)
$         integer row    (input)
$         integer ncols  (output)
$         integer cols(maxcols) (output)
$         double precision (or double complex) values(maxcols) output
$     Where maxcols is larger then or equal to the maximum nonzeros in 
$     any row of the matrix.

   Caution:
   Do not try to change the contents of the output arrays (cols and vals).
   In some cases, this may corrupt the matrix.

.keywords: matrix, row, get, extract

.seealso: MatRestoreRow(), MatSetValues()
@*/
int MatGetRow(Mat mat,int row,int *ncols,int **cols,Scalar **vals)
{
  int   ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(ncols);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->getrow) SETERRQ(PETSC_ERR_SUP,0,"");
  PLogEventBegin(MAT_GetRow,mat,0,0,0);
  ierr = (*mat->ops->getrow)(mat,row,ncols,cols,vals); CHKERRQ(ierr);
  PLogEventEnd(MAT_GetRow,mat,0,0,0);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatRestoreRow"
/*@C  
   MatRestoreRow - Frees any temporary space allocated by MatGetRow().

   Input Parameters:
.  mat - the matrix
.  row - the row to get
.  ncols, cols - the number of nonzeros and their columns
.  vals - if nonzero the column values

   Notes: 
$    This should be called after you have finished examining the entries.

   Fortran Notes:
$     The calling sequence from Fortran is 
$
$       MatRestoreRow(matrix,row,ncols,cols,values,ierr)
$         Mat     matrix (input)
$         integer row    (input)
$         integer ncols  (output)
$         integer cols(maxcols) (output)
$         double precision (or double complex) values(maxcols) output
$     Where maxcols is larger then or equal to the maximum nonzeros in 
$     any row of the matrix. In Fortran you must call MatRestoreRow()
$     after a call to MatGetRow() before you make another call to 
$     MatGetRow()

.keywords: matrix, row, restore

.seealso:  MatGetRow()
@*/
int MatRestoreRow(Mat mat,int row,int *ncols,int **cols,Scalar **vals)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(ncols);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (!mat->ops->restorerow) PetscFunctionReturn(0);
  ierr = (*mat->ops->restorerow)(mat,row,ncols,cols,vals);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatView"
/*@C
   MatView - Visualizes a matrix object.

   Input Parameters:
.  mat - the matrix
.  ptr - visualization context

   Notes:
   The available visualization contexts include
$     VIEWER_STDOUT_SELF - standard output (default)
$     VIEWER_STDOUT_WORLD - synchronized standard
$       output where only the first processor opens
$       the file.  All other processors send their 
$       data to the first processor to print. 
$     VIEWER_DRAWX_WORLD - graphical display of nonzero structure

   The user can open alternative vistualization contexts with
$    ViewerFileOpenASCII() - output to a specified file
$    ViewerFileOpenBinary() - output in binary to a
$         specified file; corresponding input uses MatLoad()
$    ViewerDrawOpenX() - output nonzero matrix structure to 
$         an X window display
$    ViewerMatlabOpen() - output matrix to Matlab viewer.
$         Currently only the sequential dense and AIJ
$         matrix types support the Matlab viewer.

   The user can call ViewerSetFormat() to specify the output
   format of ASCII printed objects (when using VIEWER_STDOUT_SELF,
   VIEWER_STDOUT_WORLD and ViewerFileOpenASCII).  Available formats include
$    VIEWER_FORMAT_ASCII_DEFAULT - default, prints matrix contents
$    VIEWER_FORMAT_ASCII_MATLAB - Matlab format
$    VIEWER_FORMAT_ASCII_IMPL - implementation-specific format
$      (which is in many cases the same as the default)
$    VIEWER_FORMAT_ASCII_INFO - basic information about the matrix
$      size and structure (not the matrix entries)
$    VIEWER_FORMAT_ASCII_INFO_LONG - more detailed information about the 
$      matrix structure

.keywords: matrix, view, visualize, output, print, write, draw

.seealso: ViewerSetFormat(), ViewerFileOpenASCII(), ViewerDrawOpenX(), 
          ViewerMatlabOpen(), ViewerFileOpenBinary(), MatLoad()
@*/
int MatView(Mat mat,Viewer viewer)
{
  int          format, ierr, rows, cols;
  FILE         *fd;
  char         *cstr;
  ViewerType   vtype;
  MPI_Comm     comm = mat->comm;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (viewer) PetscValidHeaderSpecific(viewer,VIEWER_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");

  if (!viewer) {
    viewer = VIEWER_STDOUT_SELF;
  }

  ierr = ViewerGetType(viewer,&vtype);
  if (vtype == ASCII_FILE_VIEWER || vtype == ASCII_FILES_VIEWER) {
    ierr = ViewerGetFormat(viewer,&format); CHKERRQ(ierr);  
    ierr = ViewerASCIIGetPointer(viewer,&fd); CHKERRQ(ierr);
    if (format == VIEWER_FORMAT_ASCII_INFO || format == VIEWER_FORMAT_ASCII_INFO_LONG) {
      PetscFPrintf(comm,fd,"Matrix Object:\n");
      ierr = MatGetType(mat,PETSC_NULL,&cstr); CHKERRQ(ierr);
      ierr = MatGetSize(mat,&rows,&cols); CHKERRQ(ierr);
      PetscFPrintf(comm,fd,"  type=%s, rows=%d, cols=%d\n",cstr,rows,cols);
      if (mat->ops->getinfo) {
        MatInfo info;
        ierr = MatGetInfo(mat,MAT_GLOBAL_SUM,&info); CHKERRQ(ierr);
        PetscFPrintf(comm,fd,"  total: nonzeros=%d, allocated nonzeros=%d\n",
                     (int)info.nz_used,(int)info.nz_allocated);
      }
    }
  }
  if (mat->ops->view) {ierr = (*mat->ops->view)(mat,viewer); CHKERRQ(ierr);}
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatDestroy"
/*@C
   MatDestroy - Frees space taken by a matrix.
  
   Input Parameter:
.  mat - the matrix

.keywords: matrix, destroy
@*/
int MatDestroy(Mat mat)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (--mat->refct > 0) PetscFunctionReturn(0);

  if (mat->mapping) {
    ierr = ISLocalToGlobalMappingDestroy(mat->mapping); CHKERRQ(ierr);
  }
  if (mat->bmapping) {
    ierr = ISLocalToGlobalMappingDestroy(mat->bmapping); CHKERRQ(ierr);
  }
  ierr = (*mat->ops->destroy)(mat); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatValid"
/*@
   MatValid - Checks whether a matrix object is valid.

   Input Parameter:
.  m - the matrix to check 

   Output Parameter:
   flg - flag indicating matrix status, either
$     PETSC_TRUE if matrix is valid;
$     PETSC_FALSE otherwise.

.keywords: matrix, valid
@*/
int MatValid(Mat m,PetscTruth *flg)
{
  PetscFunctionBegin;
  PetscValidIntPointer(flg);
  if (!m)                           *flg = PETSC_FALSE;
  else if (m->cookie != MAT_COOKIE) *flg = PETSC_FALSE;
  else                              *flg = PETSC_TRUE;
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSetValues"
/*@ 
   MatSetValues - Inserts or adds a block of values into a matrix.
   These values may be cached, so MatAssemblyBegin() and MatAssemblyEnd() 
   MUST be called after all calls to MatSetValues() have been completed.

   Input Parameters:
.  mat - the matrix
.  v - a logically two-dimensional array of values
.  m, idxm - the number of rows and their global indices 
.  n, idxn - the number of columns and their global indices
.  addv - either ADD_VALUES or INSERT_VALUES, where
$     ADD_VALUES - adds values to any existing entries
$     INSERT_VALUES - replaces existing entries with new values

   Notes:
   By default the values, v, are row-oriented and unsorted.
   See MatSetOption() for other options.

   Calls to MatSetValues() with the INSERT_VALUES and ADD_VALUES 
   options cannot be mixed without intervening calls to the assembly
   routines.

   MatSetValues() uses 0-based row and column numbers in Fortran 
   as well as in C.

   Efficiency Alert:
   The routine MatSetValuesBlocked() may offer much better efficiency
   for users of block sparse formats (MATSEQBAIJ and MATMPIBAIJ).

.keywords: matrix, insert, add, set, values

.seealso: MatSetOption(), MatAssemblyBegin(), MatAssemblyEnd(), MatSetValuesBlocked()
@*/
int MatSetValues(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v,InsertMode addv)
{
  int ierr;

  PetscFunctionBegin;
  if (!m || !n) PetscFunctionReturn(0); /* no values to insert */
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(idxm);
  PetscValidIntPointer(idxn);
  PetscValidScalarPointer(v);
  if (mat->insertmode == NOT_SET_VALUES) {
    mat->insertmode = addv;
  }
#if defined(USE_PETSC_BOPT_g)
  else if (mat->insertmode != addv) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,1,"Cannot mix add values and insert values");
  }
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
#endif

  if (mat->assembled) {
    mat->was_assembled = PETSC_TRUE; 
    mat->assembled     = PETSC_FALSE;
  }
  PLogEventBegin(MAT_SetValues,mat,0,0,0);
  ierr = (*mat->ops->setvalues)(mat,m,idxm,n,idxn,v,addv);CHKERRQ(ierr);
  PLogEventEnd(MAT_SetValues,mat,0,0,0);  
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSetValuesBlocked"
/*@ 
   MatSetValuesBlocked - Inserts or adds a block of values into a matrix.

   Input Parameters:
.  mat - the matrix
.  v - a logically two-dimensional array of values
.  m, idxm - the number of block rows and their global block indices 
.  n, idxn - the number of block columns and their global block indices
.  addv - either ADD_VALUES or INSERT_VALUES, where
$     ADD_VALUES - adds values to any existing entries
$     INSERT_VALUES - replaces existing entries with new values

   Notes:
   By default the values, v, are row-oriented and unsorted. So the layout of 
   v is the same as for MatSetValues(). See MatSetOption() for other options.

   Calls to MatSetValuesBlocked() with the INSERT_VALUES and ADD_VALUES 
   options cannot be mixed without intervening calls to the assembly
   routines.

   MatSetValuesBlocked() uses 0-based row and column numbers in Fortran 
   as well as in C.

   Each time an entry is set within a sparse matrix via MatSetValues(),
   internal searching must be done to determine where to place the the
   data in the matrix storage space.  By instead inserting blocks of 
   entries via MatSetValuesBlocked(), the overhead of matrix assembly is
   reduced.

   Restrictions:
   MatSetValuesBlocked() is currently supported only for the block AIJ
   matrix format (MATSEQBAIJ and MATMPIBAIJ, which are created via
   MatCreateSeqBAIJ() and MatCreateMPIBAIJ()).

.keywords: matrix, insert, add, set, values

.seealso: MatSetOption(), MatAssemblyBegin(), MatAssemblyEnd(), MatSetValues()
@*/
int MatSetValuesBlocked(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v,InsertMode addv)
{
  int ierr;

  PetscFunctionBegin;
  if (!m || !n) PetscFunctionReturn(0); /* no values to insert */
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(idxm);
  PetscValidIntPointer(idxn);
  PetscValidScalarPointer(v);
  if (mat->insertmode == NOT_SET_VALUES) {
    mat->insertmode = addv;
  }
#if defined(USE_PETSC_BOPT_g) 
  else if (mat->insertmode != addv) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,1,"Cannot mix add values and insert values");
  }
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
#endif

  if (mat->assembled) {
    mat->was_assembled = PETSC_TRUE; 
    mat->assembled     = PETSC_FALSE;
  }
  PLogEventBegin(MAT_SetValues,mat,0,0,0);
  ierr = (*mat->ops->setvaluesblocked)(mat,m,idxm,n,idxn,v,addv);CHKERRQ(ierr);
  PLogEventEnd(MAT_SetValues,mat,0,0,0);  
  PetscFunctionReturn(0);
}

/*MC
   MatSetValue - Set a single entry into a matrix.

   Input Parameters:
.  m - the matrix
.  row - the row location of the entry
.  col - the column location of the entry
.  value - the value to insert
.  mode - either INSERT_VALUES or ADD_VALUES

   Synopsis:
   void MatSetValue(Mat m,int row,int col,Scalar value,InsertMode mode);

   Notes: For efficiency one should use MatSetValues() and set 
several or many values simultaneously.

.seealso: MatSetValues()
M*/

#undef __FUNC__  
#define __FUNC__ "MatGetValues"
/*@ 
   MatGetValues - Gets a block of values from a matrix.

   Input Parameters:
.  mat - the matrix
.  v - a logically two-dimensional array for storing the values
.  m, idxm - the number of rows and their global indices 
.  n, idxn - the number of columns and their global indices

   Notes:
   The user must allocate space (m*n Scalars) for the values, v.
   The values, v, are then returned in a row-oriented format, 
   analogous to that used by default in MatSetValues().

   MatGetValues() uses 0-based row and column numbers in
   Fortran as well as in C.

   MatGetValues() requires that the matrix has been assembled
   with MatAssemblyBegin()/MatAssemblyEnd().  Thus, calls to
   MatSetValues() and MatGetValues() CANNOT be made in succession
   without intermediate matrix assembly.

.keywords: matrix, get, values

.seealso: MatGetRow(), MatGetSubmatrices(), MatSetValues()
@*/
int MatGetValues(Mat mat,int m,int *idxm,int n,int *idxn,Scalar *v)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(idxm);
  PetscValidIntPointer(idxn);
  PetscValidScalarPointer(v);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->getvalues) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_GetValues,mat,0,0,0);
  ierr = (*mat->ops->getvalues)(mat,m,idxm,n,idxn,v); CHKERRQ(ierr);
  PLogEventEnd(MAT_GetValues,mat,0,0,0);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSetLocalToGlobalMapping"
/*@
   MatSetLocalToGlobalMapping - Sets a local-to-global numbering for use by
   the routine MatSetValuesLocal() to allow users to insert matrix entries
   using a local (per-processor) numbering.

   Input Parameters:
.  x - the matrix
.  mapping - mapping created with ISLocalToGlobalMappingCreate() 
             or ISLocalToGlobalMappingCreateIS()

.keywords: matrix, set, values, local, global, mapping

.seealso:  MatAssemblyBegin(), MatAssemblyEnd(), MatSetValues(), MatSetValuesLocal()
@*/
int MatSetLocalToGlobalMapping(Mat x,ISLocalToGlobalMapping mapping)
{
  PetscFunctionBegin;
  PetscValidHeaderSpecific(x,MAT_COOKIE);
  PetscValidHeaderSpecific(mapping,IS_LTOGM_COOKIE);

  if (x->mapping) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Mapping already set for matrix");
  }

  x->mapping = mapping;
  PetscObjectReference((PetscObject)mapping);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSetLocalToGlobalMappingBlocked"
/*@
   MatSetLocalToGlobalMappingBlocked - Sets a local-to-global numbering for use
   by the routine MatSetValuesBlockedLocal() to allow users to insert matrix
   entries using a local (per-processor) numbering.

   Input Parameters:
.  x - the matrix
.  mapping - mapping created with ISLocalToGlobalMappingCreate() or
             ISLocalToGlobalMappingCreateIS()

.keywords: matrix, set, values, local ordering

.seealso:  MatAssemblyBegin(), MatAssemblyEnd(), MatSetValues(), MatSetValuesBlockedLocal(),
           MatSetValuesBlocked(), MatSetValuesLocal()
@*/
int MatSetLocalToGlobalMappingBlocked(Mat x,ISLocalToGlobalMapping mapping)
{
  PetscFunctionBegin;
  PetscValidHeaderSpecific(x,MAT_COOKIE);
  PetscValidHeaderSpecific(mapping,IS_LTOGM_COOKIE);

  if (x->bmapping) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Mapping already set for matrix");
  }
 
  x->bmapping = mapping;
  PetscObjectReference((PetscObject)mapping);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSetValuesLocal"
/*@
   MatSetValuesLocal - Inserts or adds values into certain locations of a matrix,
   using a local ordering of the nodes. 

   Input Parameters:
.  x - the matrix
.  nrow, irow - number of rows and their local indices
.  ncol, icol - number of columns and their local indices
.  y -  a logically two-dimensional array of values
.  addv - either INSERT_VALUES or ADD_VALUES, where
$     ADD_VALUES - adds values to any existing entries
$     INSERT_VALUES - replaces existing entries with new values

   Notes:
   Before calling MatSetValuesLocal(), the user must first set the
   local-to-global mapping by calling MatSetLocalToGlobalMapping().

   Calls to MatSetValuesLocal() with the INSERT_VALUES and ADD_VALUES 
   options cannot be mixed without intervening calls to the assembly
   routines.

   These values may be cached, so MatAssemblyBegin() and MatAssemblyEnd() 
   MUST be called after all calls to MatSetValuesLocal() have been completed.

.keywords: matrix, set, values, local ordering

.seealso:  MatAssemblyBegin(), MatAssemblyEnd(), MatSetValues(), MatSetLocalToGlobalMapping()
@*/
int MatSetValuesLocal(Mat mat,int nrow,int *irow,int ncol, int *icol,Scalar *y,InsertMode addv) 
{
  int ierr,irowm[2048],icolm[2048];

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(irow);
  PetscValidIntPointer(icol);
  PetscValidScalarPointer(y);

  if (mat->insertmode == NOT_SET_VALUES) {
    mat->insertmode = addv;
  }
#if defined(USE_PETSC_BOPT_g) 
  else if (mat->insertmode != addv) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,1,"Cannot mix add values and insert values");
  }
  if (!mat->mapping) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Local to global never set with MatSetLocalToGlobalMapping");
  }
  if (nrow > 2048 || ncol > 2048) {
    SETERRQ(PETSC_ERR_SUP,0,"Number column/row indices must be <= 2048");
  }
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
#endif

  if (mat->assembled) {
    mat->was_assembled = PETSC_TRUE; 
    mat->assembled     = PETSC_FALSE;
  }
  PLogEventBegin(MAT_SetValues,mat,0,0,0);
  ierr = ISLocalToGlobalMappingApply(mat->mapping,nrow,irow,irowm); CHKERRQ(ierr);
  ierr = ISLocalToGlobalMappingApply(mat->mapping,ncol,icol,icolm);CHKERRQ(ierr); 
  ierr = (*mat->ops->setvalues)(mat,nrow,irowm,ncol,icolm,y,addv);CHKERRQ(ierr);
  PLogEventEnd(MAT_SetValues,mat,0,0,0);  
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSetValuesBlockedLocal"
/*@
   MatSetValuesBlockedLocal - Inserts or adds values into certain locations of a matrix,
   using a local ordering of the nodes a block at a time. 

   Input Parameters:
.  x - the matrix
.  nrow, irow - number of rows and their local indices
.  ncol, icol - number of columns and their local indices
.  y -  a logically two-dimensional array of values
.  addv - either INSERT_VALUES or ADD_VALUES, where
$     ADD_VALUES - adds values to any existing entries
$     INSERT_VALUES - replaces existing entries with new values

   Notes:
   Before calling MatSetValuesBlockedLocal(), the user must first set the
   local-to-global mapping by calling MatSetLocalToGlobalMappingBlocked(),
   where the mapping MUST be set for matrix blocks, not for matrix elements.

   Calls to MatSetValuesBlockedLocal() with the INSERT_VALUES and ADD_VALUES 
   options cannot be mixed without intervening calls to the assembly
   routines.

   These values may be cached, so MatAssemblyBegin() and MatAssemblyEnd() 
   MUST be called after all calls to MatSetValuesBlockedLocal() have been completed.

.keywords: matrix, set, values, blocked, local

.seealso:  MatAssemblyBegin(), MatAssemblyEnd(), MatSetValuesLocal(), MatSetLocalToGlobalMappingBlocked()
@*/
int MatSetValuesBlockedLocal(Mat mat,int nrow,int *irow,int ncol,int *icol,Scalar *y,InsertMode addv) 
{
  int ierr,irowm[2048],icolm[2048];

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(irow);
  PetscValidIntPointer(icol);
  PetscValidScalarPointer(y);
  if (mat->insertmode == NOT_SET_VALUES) {
    mat->insertmode = addv;
  }
#if defined(USE_PETSC_BOPT_g) 
  else if (mat->insertmode != addv) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,1,"Cannot mix add values and insert values");
  }
  if (!mat->bmapping) {
    SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Local to global never set with MatSetLocalToGlobalMappingBlocked");
  }
  if (nrow > 2048 || ncol > 2048) {
    SETERRQ(PETSC_ERR_SUP,0,"Number column/row indices must be <= 2048");
  }
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
#endif

  if (mat->assembled) {
    mat->was_assembled = PETSC_TRUE; 
    mat->assembled     = PETSC_FALSE;
  }
  PLogEventBegin(MAT_SetValues,mat,0,0,0);
  ierr = ISLocalToGlobalMappingApply(mat->bmapping,nrow,irow,irowm); CHKERRQ(ierr);
  ierr = ISLocalToGlobalMappingApply(mat->bmapping,ncol,icol,icolm); CHKERRQ(ierr);
  ierr = (*mat->ops->setvaluesblocked)(mat,nrow,irowm,ncol,icolm,y,addv);CHKERRQ(ierr);
  PLogEventEnd(MAT_SetValues,mat,0,0,0);  
  PetscFunctionReturn(0);
}

/* --------------------------------------------------------*/
#undef __FUNC__  
#define __FUNC__ "MatMult"
/*@
   MatMult - Computes the matrix-vector product, y = Ax.

   Input Parameters:
.  mat - the matrix
.  x   - the vector to be multilplied

   Output Parameters:
.  y - the result

   Notes:
   The vectors x and y cannot be the same.  I.e., one cannot
   call MatMult(A,y,y).

.keywords: matrix, multiply, matrix-vector product

.seealso: MatMultTrans(), MatMultAdd(), MatMultTransAdd()
@*/
int MatMult(Mat mat,Vec x,Vec y)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(x,VEC_COOKIE);PetscValidHeaderSpecific(y,VEC_COOKIE); 
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (x == y) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"x and y must be different vectors");
  if (mat->N != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim"); 
  if (mat->M != y->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec y: global dim"); 
  if (mat->m != y->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec y: local dim"); 

  PLogEventBegin(MAT_Mult,mat,x,y,0);
  ierr = (*mat->ops->mult)(mat,x,y); CHKERRQ(ierr);
  PLogEventEnd(MAT_Mult,mat,x,y,0);

  PetscFunctionReturn(0);
}   

#undef __FUNC__  
#define __FUNC__ "MatMultTrans"
/*@
   MatMultTrans - Computes matrix transpose times a vector.

   Input Parameters:
.  mat - the matrix
.  x   - the vector to be multilplied

   Output Parameters:
.  y - the result

   Notes:
   The vectors x and y cannot be the same.  I.e., one cannot
   call MatMultTrans(A,y,y).

.keywords: matrix, multiply, matrix-vector product, transpose

.seealso: MatMult(), MatMultAdd(), MatMultTransAdd()
@*/
int MatMultTrans(Mat mat,Vec x,Vec y)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(x,VEC_COOKIE); PetscValidHeaderSpecific(y,VEC_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (x == y) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"x and y must be different vectors");
  if (mat->M != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim"); 
  if (mat->N != y->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec y: global dim"); 
  PLogEventBegin(MAT_MultTrans,mat,x,y,0);
  ierr = (*mat->ops->multtrans)(mat,x,y); CHKERRQ(ierr);
  PLogEventEnd(MAT_MultTrans,mat,x,y,0);
  PetscFunctionReturn(0);
}   

#undef __FUNC__  
#define __FUNC__ "MatMultAdd"
/*@
    MatMultAdd -  Computes v3 = v2 + A * v1.

    Input Parameters:
.   mat - the matrix
.   v1, v2 - the vectors

    Output Parameters:
.   v3 - the result

   Notes:
   The vectors v1 and v3 cannot be the same.  I.e., one cannot
   call MatMultAdd(A,v1,v2,v1).

.keywords: matrix, multiply, matrix-vector product, add

.seealso: MatMultTrans(), MatMult(), MatMultTransAdd()
@*/
int MatMultAdd(Mat mat,Vec v1,Vec v2,Vec v3)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(v1,VEC_COOKIE);
  PetscValidHeaderSpecific(v2,VEC_COOKIE); PetscValidHeaderSpecific(v3,VEC_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix");
  if (mat->N != v1->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v1: global dim");
  if (mat->M != v2->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v2: global dim");
  if (mat->M != v3->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v3: global dim");
  if (mat->m != v3->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v3: local dim"); 
  if (mat->m != v2->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v2: local dim"); 
  if (v1 == v3) SETERRQ(PETSC_ERR_ARG_IDN,0,"v1 and v3 must be different vectors");

  PLogEventBegin(MAT_MultAdd,mat,v1,v2,v3);
  ierr = (*mat->ops->multadd)(mat,v1,v2,v3); CHKERRQ(ierr);
  PLogEventEnd(MAT_MultAdd,mat,v1,v2,v3);
  PetscFunctionReturn(0);
}   

#undef __FUNC__  
#define __FUNC__ "MatMultTransAdd"
/*@
   MatMultTransAdd - Computes v3 = v2 + A' * v1.

   Input Parameters:
.  mat - the matrix
.  v1, v2 - the vectors

   Output Parameters:
.  v3 - the result

   Notes:
   The vectors v1 and v3 cannot be the same.  I.e., one cannot
   call MatMultTransAdd(A,v1,v2,v1).

.keywords: matrix, multiply, matrix-vector product, transpose, add

.seealso: MatMultTrans(), MatMultAdd(), MatMult()
@*/
int MatMultTransAdd(Mat mat,Vec v1,Vec v2,Vec v3)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(v1,VEC_COOKIE);
  PetscValidHeaderSpecific(v2,VEC_COOKIE);PetscValidHeaderSpecific(v3,VEC_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->multtransadd) SETERRQ(PETSC_ERR_SUP,0,"");
  if (v1 == v3) SETERRQ(PETSC_ERR_ARG_IDN,0,"v1 and v3 must be different vectors");
  if (mat->M != v1->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v1: global dim");
  if (mat->N != v2->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v2: global dim");
  if (mat->N != v3->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec v3: global dim");

  PLogEventBegin(MAT_MultTransAdd,mat,v1,v2,v3);
  ierr = (*mat->ops->multtransadd)(mat,v1,v2,v3); CHKERRQ(ierr);
  PLogEventEnd(MAT_MultTransAdd,mat,v1,v2,v3); 
  PetscFunctionReturn(0);
}
/* ------------------------------------------------------------*/
#undef __FUNC__  
#define __FUNC__ "MatGetInfo"
/*@C
   MatGetInfo - Returns information about matrix storage (number of
   nonzeros, memory, etc.).

   Input Parameters:
.  mat - the matrix

   Output Parameters:
.  flag - flag indicating the type of parameters to be returned
$    flag = MAT_LOCAL: local matrix
$    flag = MAT_GLOBAL_MAX: maximum over all processors
$    flag = MAT_GLOBAL_SUM: sum over all processors
.  info - matrix information context

   Notes:
   The MatInfo context contains a variety of matrix data, including
   number of nonzeros allocated and used, number of mallocs during
   matrix assembly, etc.  Additional information for factored matrices
   is provided (such as the fill ratio, number of mallocs during
   factorization, etc.).  Much of this info is printed to STDOUT
   when using the runtime options 
$       -log_info -mat_view_info

   Example for C/C++ Users:
   See the file ${PETSC_DIR}/include/mat.h for a complete list of
   data within the MatInfo context.  For example, 
$
$      MatInfo info;
$      Mat     A;
$      double  mal, nz_a, nz_u;
$
$      MatGetInfo(A,MAT_LOCAL,&info);
$      mal  = info.mallocs;
$      nz_a = info.nz_allocated;
$

   Example for Fortran Users:
   Fortran users should declare info as a double precision
   array of dimension MAT_INFO_SIZE, and then extract the parameters
   of interest.  See the file ${PETSC_DIR}/include/FINCLUDE/mat.h
   a complete list of parameter names.
$
$      double  precision info(MAT_INFO_SIZE)
$      double  precision mal, nz_a
$      Mat     A
$      integer ierr
$
$      call MatGetInfo(A,MAT_LOCAL,info,ierr)
$      mal = info(MAT_INFO_MALLOCS)
$      nz_a = info(MAT_INFO_NZ_ALLOCATED)
$

.keywords: matrix, get, info, storage, nonzeros, memory, fill
@*/
int MatGetInfo(Mat mat,MatInfoType flag,MatInfo *info)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(info);
  if (!mat->ops->getinfo) SETERRQ(PETSC_ERR_SUP,0,"");
  ierr = (*mat->ops->getinfo)(mat,flag,info);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}   

/* ----------------------------------------------------------*/
#undef __FUNC__  
#define __FUNC__ "MatILUDTFactor"
/*@  
   MatILUDTFactor - Performs a drop tolerance ILU factorization.

   Input Parameters:
.  mat - the matrix
.  dt  - the drop tolerance
.  maxnz - the maximum number of nonzeros per row allowed?
.  row - row permutation
.  col - column permutation

   Output Parameters:
.  fact - the factored matrix

.keywords: matrix, factor, LU, in-place

.seealso: MatLUFactorSymbolic(), MatLUFactorNumeric(), MatCholeskyFactor()
@*/
int MatILUDTFactor(Mat mat,double dt,int maxnz,IS row,IS col,Mat *fact)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(fact);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->iludtfactor) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_ILUFactor,mat,row,col,0); 
  ierr = (*mat->ops->iludtfactor)(mat,dt,maxnz,row,col,fact); CHKERRQ(ierr);
  PLogEventEnd(MAT_ILUFactor,mat,row,col,0);

  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatLUFactor"
/*@  
   MatLUFactor - Performs in-place LU factorization of matrix.

   Input Parameters:
.  mat - the matrix
.  row - row permutation
.  col - column permutation
.  f - expected fill as ratio of original fill.

.keywords: matrix, factor, LU, in-place

.seealso: MatLUFactorSymbolic(), MatLUFactorNumeric(), MatCholeskyFactor()
@*/
int MatLUFactor(Mat mat,IS row,IS col,double f)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->M != mat->N) SETERRQ(PETSC_ERR_ARG_WRONG,0,"matrix must be square");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->lufactor) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_LUFactor,mat,row,col,0); 
  ierr = (*mat->ops->lufactor)(mat,row,col,f); CHKERRQ(ierr);
  PLogEventEnd(MAT_LUFactor,mat,row,col,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatILUFactor"
/*@  
   MatILUFactor - Performs in-place ILU factorization of matrix.

   Input Parameters:
.  mat - the matrix
.  row - row permutation
.  col - column permutation
.  f - expected fill as ratio of original fill.
.  level - number of levels of fill.

   Notes: 
   Probably really in-place only when level of fill is zero.

.keywords: matrix, factor, ILU, in-place

.seealso: MatILUFactorSymbolic(), MatLUFactorNumeric(), MatCholeskyFactor()
@*/
int MatILUFactor(Mat mat,IS row,IS col,double f,int level)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->M != mat->N) SETERRQ(PETSC_ERR_ARG_WRONG,0,"matrix must be square");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->ilufactor) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_ILUFactor,mat,row,col,0); 
  ierr = (*mat->ops->ilufactor)(mat,row,col,f,level); CHKERRQ(ierr);
  PLogEventEnd(MAT_ILUFactor,mat,row,col,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatLUFactorSymbolic"
/*@  
   MatLUFactorSymbolic - Performs symbolic LU factorization of matrix.
   Call this routine before calling MatLUFactorNumeric().

   Input Parameters:
.  mat - the matrix
.  row, col - row and column permutations
.  f - expected fill as ratio of the original number of nonzeros, 
       for example 3.0; choosing this parameter well can result in 
       more efficient use of time and space. Run with the option -log_info
       to determine an optimal value to use

   Output Parameter:
.  fact - new matrix that has been symbolically factored

   Notes:
   See the file ${PETSC_DIR}/Performace for additional information about
   choosing the fill factor for better efficiency.

.keywords: matrix, factor, LU, symbolic, fill

.seealso: MatLUFactor(), MatLUFactorNumeric(), MatCholeskyFactor()
@*/
int MatLUFactorSymbolic(Mat mat,IS row,IS col,double f,Mat *fact)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->M != mat->N) SETERRQ(PETSC_ERR_ARG_WRONG,0,"matrix must be square");
  PetscValidPointer(fact);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->lufactorsymbolic) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_LUFactorSymbolic,mat,row,col,0); 
  ierr = (*mat->ops->lufactorsymbolic)(mat,row,col,f,fact); CHKERRQ(ierr);
  PLogEventEnd(MAT_LUFactorSymbolic,mat,row,col,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatLUFactorNumeric"
/*@  
   MatLUFactorNumeric - Performs numeric LU factorization of a matrix.
   Call this routine after first calling MatLUFactorSymbolic().

   Input Parameters:
.  mat - the matrix
.  row, col - row and  column permutations

   Output Parameters:
.  fact - symbolically factored matrix that must have been generated
          by MatLUFactorSymbolic()

   Notes:
   See MatLUFactor() for in-place factorization.  See 
   MatCholeskyFactorNumeric() for the symmetric, positive definite case.  

.keywords: matrix, factor, LU, numeric

.seealso: MatLUFactorSymbolic(), MatLUFactor(), MatCholeskyFactor()
@*/
int MatLUFactorNumeric(Mat mat,Mat *fact)
{
  int ierr,flg;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(fact);
  PetscValidHeaderSpecific(*fact,MAT_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->M != (*fact)->M || mat->N != (*fact)->N)
    SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Mat *fact: global dim");
  if (!(*fact)->ops->lufactornumeric) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_LUFactorNumeric,mat,*fact,0,0); 
  ierr = (*(*fact)->ops->lufactornumeric)(mat,fact); CHKERRQ(ierr);
  PLogEventEnd(MAT_LUFactorNumeric,mat,*fact,0,0); 
  ierr = OptionsHasName(PETSC_NULL,"-mat_view_draw",&flg); CHKERRQ(ierr);
  if (flg) {
    ierr = OptionsHasName(0,"-mat_view_contour",&flg); CHKERRQ(ierr);
    if (flg) {
      ViewerPushFormat(VIEWER_DRAWX_(mat->comm),VIEWER_FORMAT_DRAW_CONTOUR,0);CHKERRQ(ierr);
    }
    ierr = MatView(*fact,VIEWER_DRAWX_(mat->comm)); CHKERRQ(ierr);
    ierr = ViewerFlush(VIEWER_DRAWX_(mat->comm)); CHKERRQ(ierr);
    if (flg) {
      ViewerPopFormat(VIEWER_DRAWX_(mat->comm));CHKERRQ(ierr);
    }
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatCholeskyFactor"
/*@  
   MatCholeskyFactor - Performs in-place Cholesky factorization of a
   symmetric matrix. 

   Input Parameters:
.  mat - the matrix
.  perm - row and column permutations
.  f - expected fill as ratio of original fill

   Notes:
   See MatLUFactor() for the nonsymmetric case.  See also
   MatCholeskyFactorSymbolic(), and MatCholeskyFactorNumeric().

.keywords: matrix, factor, in-place, Cholesky

.seealso: MatLUFactor(), MatCholeskyFactorSymbolic(), MatCholeskyFactorNumeric()
@*/
int MatCholeskyFactor(Mat mat,IS perm,double f)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->M != mat->N) SETERRQ(PETSC_ERR_ARG_WRONG,0,"matrix must be square");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->choleskyfactor) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_CholeskyFactor,mat,perm,0,0); 
  ierr = (*mat->ops->choleskyfactor)(mat,perm,f); CHKERRQ(ierr);
  PLogEventEnd(MAT_CholeskyFactor,mat,perm,0,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatCholeskyFactorSymbolic"
/*@  
   MatCholeskyFactorSymbolic - Performs symbolic Cholesky factorization
   of a symmetric matrix. 

   Input Parameters:
.  mat - the matrix
.  perm - row and column permutations
.  f - expected fill as ratio of original

   Output Parameter:
.  fact - the factored matrix

   Notes:
   See MatLUFactorSymbolic() for the nonsymmetric case.  See also
   MatCholeskyFactor() and MatCholeskyFactorNumeric().

.keywords: matrix, factor, factorization, symbolic, Cholesky

.seealso: MatLUFactorSymbolic(), MatCholeskyFactor(), MatCholeskyFactorNumeric()
@*/
int MatCholeskyFactorSymbolic(Mat mat,IS perm,double f,Mat *fact)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(fact);
  if (mat->M != mat->N) SETERRQ(PETSC_ERR_ARG_WRONG,0,"matrix must be square");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->choleskyfactorsymbolic) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_CholeskyFactorSymbolic,mat,perm,0,0);
  ierr = (*mat->ops->choleskyfactorsymbolic)(mat,perm,f,fact); CHKERRQ(ierr);
  PLogEventEnd(MAT_CholeskyFactorSymbolic,mat,perm,0,0);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatCholeskyFactorNumeric"
/*@  
   MatCholeskyFactorNumeric - Performs numeric Cholesky factorization
   of a symmetric matrix. Call this routine after first calling
   MatCholeskyFactorSymbolic().

   Input Parameter:
.  mat - the initial matrix

   Output Parameter:
.  fact - the factored matrix

.keywords: matrix, factor, numeric, Cholesky

.seealso: MatCholeskyFactorSymbolic(), MatCholeskyFactor(), MatLUFactorNumeric()
@*/
int MatCholeskyFactorNumeric(Mat mat,Mat *fact)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(fact);
  if (!mat->ops->choleskyfactornumeric) SETERRQ(PETSC_ERR_SUP,0,"");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->M != (*fact)->M || mat->N != (*fact)->N)
    SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Mat *fact: global dim");

  PLogEventBegin(MAT_CholeskyFactorNumeric,mat,*fact,0,0);
  ierr = (*mat->ops->choleskyfactornumeric)(mat,fact); CHKERRQ(ierr);
  PLogEventEnd(MAT_CholeskyFactorNumeric,mat,*fact,0,0);
  PetscFunctionReturn(0);
}

/* ----------------------------------------------------------------*/
#undef __FUNC__  
#define __FUNC__ "MatSolve"
/*@
   MatSolve - Solves A x = b, given a factored matrix.

   Input Parameters:
.  mat - the factored matrix
.  b - the right-hand-side vector

   Output Parameter:
.  x - the result vector

   Notes:
   The vectors b and x cannot be the same.  I.e., one cannot
   call MatSolve(A,x,x).

.keywords: matrix, linear system, solve, LU, Cholesky, triangular solve

.seealso: MatSolveAdd(), MatSolveTrans(), MatSolveTransAdd()
@*/
int MatSolve(Mat mat,Vec b,Vec x)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(b,VEC_COOKIE); PetscValidHeaderSpecific(x,VEC_COOKIE);
  if (x == b) SETERRQ(PETSC_ERR_ARG_IDN,0,"x and b must be different vectors");
  if (!mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Unfactored matrix");
  if (mat->N != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim");
  if (mat->M != b->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: global dim");
  if (mat->m != b->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: local dim"); 
  if (mat->M == 0 && mat->N == 0) PetscFunctionReturn(0);

  if (!mat->ops->solve) SETERRQ(PETSC_ERR_SUP,0,"");
  PLogEventBegin(MAT_Solve,mat,b,x,0); 
  ierr = (*mat->ops->solve)(mat,b,x); CHKERRQ(ierr);
  PLogEventEnd(MAT_Solve,mat,b,x,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatForwardSolve"
/* @
   MatForwardSolve - Solves L x = b, given a factored matrix, A = LU.

   Input Parameters:
.  mat - the factored matrix
.  b - the right-hand-side vector

   Output Parameter:
.  x - the result vector

   Notes:
   MatSolve() should be used for most applications, as it performs
   a forward solve followed by a backward solve.

   The vectors b and x cannot be the same.  I.e., one cannot
   call MatForwardSolve(A,x,x).

.keywords: matrix, forward, LU, Cholesky, triangular solve

.seealso: MatSolve(), MatBackwardSolve()
@ */
int MatForwardSolve(Mat mat,Vec b,Vec x)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
  if (x == b) SETERRQ(PETSC_ERR_ARG_IDN,0,"x and b must be different vectors");
  if (!mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Unfactored matrix");
  if (!mat->ops->forwardsolve) SETERRQ(PETSC_ERR_SUP,0,"");
  if (mat->N != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim");
  if (mat->M != b->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: global dim");
  if (mat->m != b->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: local dim"); 

  PLogEventBegin(MAT_ForwardSolve,mat,b,x,0); 
  ierr = (*mat->ops->forwardsolve)(mat,b,x); CHKERRQ(ierr);
  PLogEventEnd(MAT_ForwardSolve,mat,b,x,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatBackwardSolve"
/* @
   MatBackwardSolve - Solves U x = b, given a factored matrix, A = LU.

   Input Parameters:
.  mat - the factored matrix
.  b - the right-hand-side vector

   Output Parameter:
.  x - the result vector

   Notes:
   MatSolve() should be used for most applications, as it performs
   a forward solve followed by a backward solve.

   The vectors b and x cannot be the same.  I.e., one cannot
   call MatBackwardSolve(A,x,x).

.keywords: matrix, backward, LU, Cholesky, triangular solve

.seealso: MatSolve(), MatForwardSolve()
@ */
int MatBackwardSolve(Mat mat,Vec b,Vec x)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
  if (x == b) SETERRQ(PETSC_ERR_ARG_IDN,0,"x and b must be different vectors");
  if (!mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Unfactored matrix");
  if (!mat->ops->backwardsolve) SETERRQ(PETSC_ERR_SUP,0,"");
  if (mat->N != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim");
  if (mat->M != b->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: global dim");
  if (mat->m != b->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: local dim"); 

  PLogEventBegin(MAT_BackwardSolve,mat,b,x,0); 
  ierr = (*mat->ops->backwardsolve)(mat,b,x); CHKERRQ(ierr);
  PLogEventEnd(MAT_BackwardSolve,mat,b,x,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSolveAdd"
/*@
   MatSolveAdd - Computes x = y + inv(A)*b, given a factored matrix.

   Input Parameters:
.  mat - the factored matrix
.  b - the right-hand-side vector
.  y - the vector to be added to 

   Output Parameter:
.  x - the result vector

   Notes:
   The vectors b and x cannot be the same.  I.e., one cannot
   call MatSolveAdd(A,x,y,x).

.keywords: matrix, linear system, solve, LU, Cholesky, add

.seealso: MatSolve(), MatSolveTrans(), MatSolveTransAdd()
@*/
int MatSolveAdd(Mat mat,Vec b,Vec y,Vec x)
{
  Scalar one = 1.0;
  Vec    tmp;
  int    ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(y,VEC_COOKIE);
  PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
  if (x == b) SETERRQ(PETSC_ERR_ARG_IDN,0,"x and b must be different vectors");
  if (!mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Unfactored matrix");
  if (mat->N != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim");
  if (mat->M != b->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: global dim");
  if (mat->M != y->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec y: global dim");
  if (mat->m != b->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: local dim"); 
  if (x->n != y->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Vec x,Vec y: local dim"); 

  PLogEventBegin(MAT_SolveAdd,mat,b,x,y); 
  if (mat->ops->solveadd)  {
    ierr = (*mat->ops->solveadd)(mat,b,y,x); CHKERRQ(ierr);
  } 
  else {
    /* do the solve then the add manually */
    if (x != y) {
      ierr = MatSolve(mat,b,x); CHKERRQ(ierr);
      ierr = VecAXPY(&one,y,x); CHKERRQ(ierr);
    } else {
      ierr = VecDuplicate(x,&tmp); CHKERRQ(ierr);
      PLogObjectParent(mat,tmp);
      ierr = VecCopy(x,tmp); CHKERRQ(ierr);
      ierr = MatSolve(mat,b,x); CHKERRQ(ierr);
      ierr = VecAXPY(&one,tmp,x); CHKERRQ(ierr);
      ierr = VecDestroy(tmp); CHKERRQ(ierr);
    }
  }
  PLogEventEnd(MAT_SolveAdd,mat,b,x,y); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSolveTrans"
/*@
   MatSolveTrans - Solves A' x = b, given a factored matrix.

   Input Parameters:
.  mat - the factored matrix
.  b - the right-hand-side vector

   Output Parameter:
.  x - the result vector

   Notes:
   The vectors b and x cannot be the same.  I.e., one cannot
   call MatSolveTrans(A,x,x).

.keywords: matrix, linear system, solve, LU, Cholesky, transpose

.seealso: MatSolve(), MatSolveAdd(), MatSolveTransAdd()
@*/
int MatSolveTrans(Mat mat,Vec b,Vec x)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
  if (!mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Unfactored matrix");
  if (x == b) SETERRQ(PETSC_ERR_ARG_IDN,0,"x and b must be different vectors");
  if (!mat->ops->solvetrans) SETERRQ(PETSC_ERR_SUP,0,"");
  if (mat->M != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim");
  if (mat->N != b->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: global dim");

  PLogEventBegin(MAT_SolveTrans,mat,b,x,0); 
  ierr = (*mat->ops->solvetrans)(mat,b,x); CHKERRQ(ierr);
  PLogEventEnd(MAT_SolveTrans,mat,b,x,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSolveTransAdd"
/*@
   MatSolveTransAdd - Computes x = y + inv(trans(A)) b, given a 
                      factored matrix. 

   Input Parameters:
.  mat - the factored matrix
.  b - the right-hand-side vector
.  y - the vector to be added to 

   Output Parameter:
.  x - the result vector

   Notes:
   The vectors b and x cannot be the same.  I.e., one cannot
   call MatSolveTransAdd(A,x,y,x).

.keywords: matrix, linear system, solve, LU, Cholesky, transpose, add  

.seealso: MatSolve(), MatSolveAdd(), MatSolveTrans()
@*/
int MatSolveTransAdd(Mat mat,Vec b,Vec y,Vec x)
{
  Scalar one = 1.0;
  int    ierr;
  Vec    tmp;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(y,VEC_COOKIE);
  PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
  if (x == b) SETERRQ(PETSC_ERR_ARG_IDN,0,"x and b must be different vectors");
  if (!mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Unfactored matrix");
  if (mat->M != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim");
  if (mat->N != b->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: global dim");
  if (mat->N != y->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec y: global dim");
  if (x->n != y->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Vec x,Vec y: local dim");

  PLogEventBegin(MAT_SolveTransAdd,mat,b,x,y); 
  if (mat->ops->solvetransadd) {
    ierr = (*mat->ops->solvetransadd)(mat,b,y,x); CHKERRQ(ierr);
  }
  else {
    /* do the solve then the add manually */
    if (x != y) {
      ierr = MatSolveTrans(mat,b,x); CHKERRQ(ierr);
      ierr = VecAXPY(&one,y,x); CHKERRQ(ierr);
    }
    else {
      ierr = VecDuplicate(x,&tmp); CHKERRQ(ierr);
      PLogObjectParent(mat,tmp);
      ierr = VecCopy(x,tmp); CHKERRQ(ierr);
      ierr = MatSolveTrans(mat,b,x); CHKERRQ(ierr);
      ierr = VecAXPY(&one,tmp,x); CHKERRQ(ierr);
      ierr = VecDestroy(tmp); CHKERRQ(ierr);
    }
  }
  PLogEventEnd(MAT_SolveTransAdd,mat,b,x,y); 
  PetscFunctionReturn(0);
}
/* ----------------------------------------------------------------*/

#undef __FUNC__  
#define __FUNC__ "MatRelax"
/*@
   MatRelax - Computes one relaxation sweep.

   Input Parameters:
.  mat - the matrix
.  b - the right hand side
.  omega - the relaxation factor
.  flag - flag indicating the type of SOR, one of
$     SOR_FORWARD_SWEEP
$     SOR_BACKWARD_SWEEP
$     SOR_SYMMETRIC_SWEEP (SSOR method)
$     SOR_LOCAL_FORWARD_SWEEP
$     SOR_LOCAL_BACKWARD_SWEEP
$     SOR_LOCAL_SYMMETRIC_SWEEP (local SSOR)
$     SOR_APPLY_UPPER, SOR_APPLY_LOWER - applies 
$       upper/lower triangular part of matrix to
$       vector (with omega)
$     SOR_ZERO_INITIAL_GUESS - zero initial guess
.  shift -  diagonal shift
.  its - the number of iterations

   Output Parameters:
.  x - the solution (can contain an initial guess)

   Notes:
   SOR_LOCAL_FORWARD_SWEEP, SOR_LOCAL_BACKWARD_SWEEP, and
   SOR_LOCAL_SYMMETRIC_SWEEP perform seperate independent smoothings
   on each processor. 

   Application programmers will not generally use MatRelax() directly,
   but instead will employ the SLES/PC interface.

   Notes for Advanced Users:
   The flags are implemented as bitwise inclusive or operations.
   For example, use (SOR_ZERO_INITIAL_GUESS | SOR_SYMMETRIC_SWEEP)
   to specify a zero initial guess for SSOR.

.keywords: matrix, relax, relaxation, sweep
@*/
int MatRelax(Mat mat,Vec b,double omega,MatSORType flag,double shift,
             int its,Vec x)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(b,VEC_COOKIE);  PetscValidHeaderSpecific(x,VEC_COOKIE);
  if (!mat->ops->relax) SETERRQ(PETSC_ERR_SUP,0,"");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (mat->N != x->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec x: global dim");
  if (mat->M != b->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: global dim");
  if (mat->m != b->n) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat mat,Vec b: local dim");

  PLogEventBegin(MAT_Relax,mat,b,x,0); 
  ierr =(*mat->ops->relax)(mat,b,omega,flag,shift,its,x); CHKERRQ(ierr);
  PLogEventEnd(MAT_Relax,mat,b,x,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatCopy_Basic"
/*
      Default matrix copy routine.
*/
int MatCopy_Basic(Mat A,Mat B)
{
  int    ierr,i,rstart,rend,nz,*cwork;
  Scalar *vwork;

  PetscFunctionBegin;
  ierr = MatZeroEntries(B); CHKERRQ(ierr);
  ierr = MatGetOwnershipRange(A,&rstart,&rend); CHKERRQ(ierr);
  for (i=rstart; i<rend; i++) {
    ierr = MatGetRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr);
    ierr = MatSetValues(B,1,&i,nz,cwork,vwork,INSERT_VALUES); CHKERRQ(ierr);
    ierr = MatRestoreRow(A,i,&nz,&cwork,&vwork); CHKERRQ(ierr);
  }
  ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
  ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatCopy"
/*@C  
   MatCopy - Copys a matrix to another matrix.

   Input Parameters:
.  A - the matrix

   Output Parameter:
.  B - where the copy is put

   Notes:
   MatCopy() copies the matrix entries of a matrix to another existing
   matrix (after first zeroing the second matrix).  A related routine is
   MatConvert(), which first creates a new matrix and then copies the data.
   
.keywords: matrix, copy, convert

.seealso: MatConvert()
@*/
int MatCopy(Mat A,Mat B)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(A,MAT_COOKIE); PetscValidHeaderSpecific(B,MAT_COOKIE);
  if (!A->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (A->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (A->M != B->M || A->N != B->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat A,Mat B: global dim");

  PLogEventBegin(MAT_Copy,A,B,0,0); 
  if (A->ops->copy) { 
    ierr = (*A->ops->copy)(A,B); CHKERRQ(ierr);
  }
  else { /* generic conversion */
    ierr = MatCopy_Basic(A,B); CHKERRQ(ierr);
  }
  PLogEventEnd(MAT_Copy,A,B,0,0); 
  PetscFunctionReturn(0);
}

static int MatConvertersSet = 0;
static int (*MatConverters[MAX_MATRIX_TYPES][MAX_MATRIX_TYPES])(Mat,MatType,Mat*) = 
           {{0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0},
            {0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0},
            {0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0},
            {0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0},
            {0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0},
            {0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0}};

#undef __FUNC__  
#define __FUNC__ "MatConvertRegister"
/*@C
    MatConvertRegister - Allows one to register a routine that converts between
        two matrix types.

  Input Parameters:
.   intype - the type of matrix (defined in include/mat.h), for example, MATSEQAIJ.
.   outtype - new matrix type, or MATSAME

.seealso: MatConvertRegisterAll()
@*/
int MatConvertRegister(MatType intype,MatType outtype,int (*converter)(Mat,MatType,Mat*))
{
  PetscFunctionBegin;
  MatConverters[intype][outtype] = converter;
  MatConvertersSet               = 1;
  PetscFunctionReturn(0);
}  

#undef __FUNC__  
#define __FUNC__ "MatConvert"
/*@C  
   MatConvert - Converts a matrix to another matrix, either of the same
   or different type.

   Input Parameters:
.  mat - the matrix
.  newtype - new matrix type.  Use MATSAME to create a new matrix of the
   same type as the original matrix.

   Output Parameter:
.  M - pointer to place new matrix

   Notes:
   MatConvert() first creates a new matrix and then copies the data from
   the first matrix.  A related routine is MatCopy(), which copies the matrix
   entries of one matrix to another already existing matrix context.

.keywords: matrix, copy, convert

.seealso: MatCopy(), MatDuplicate()
@*/
int MatConvert(Mat mat,MatType newtype,Mat *M)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(M);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 

  if (newtype > MAX_MATRIX_TYPES || newtype < -1) {
    SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,1,"Not a valid matrix type");
  }
  *M  = 0;

  if (!MatConvertersSet) {
    ierr = MatLoadRegisterAll(); CHKERRQ(ierr);
  }

  PLogEventBegin(MAT_Convert,mat,0,0,0); 
  if ((newtype == mat->type || newtype == MATSAME) && mat->ops->convertsametype) {
    ierr = (*mat->ops->convertsametype)(mat,M,COPY_VALUES); CHKERRQ(ierr);
  } else {
    if (!MatConvertersSet) {
      ierr = MatConvertRegisterAll(); CHKERRQ(ierr);
    }
    if (!MatConverters[mat->type][newtype]) {
      SETERRQ(PETSC_ERR_ARG_WRONG,1,"Invalid matrix type, or matrix converter not registered");
    }
    ierr = (*MatConverters[mat->type][newtype])(mat,newtype,M); CHKERRQ(ierr);
  }
  PLogEventEnd(MAT_Convert,mat,0,0,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatDuplicate"
/*@C  
   MatDuplicate - Duplicates a matrix including the non-zero structure, but 
     does not copy over the values.

   Input Parameters:
.  mat - the matrix

   Output Parameter:
.  M - pointer to place new matrix

.keywords: matrix, copy, convert, duplicate

.seealso: MatCopy(), MatDuplicate(), MatConvert()
@*/
int MatDuplicate(Mat mat,Mat *M)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(M);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 

  *M  = 0;
  PLogEventBegin(MAT_Convert,mat,0,0,0); 
  if (!mat->ops->convertsametype) {
    SETERRQ(PETSC_ERR_SUP,1,"Not written for this matrix type");
  }
  ierr = (*mat->ops->convertsametype)(mat,M,DO_NOT_COPY_VALUES); CHKERRQ(ierr);
  PLogEventEnd(MAT_Convert,mat,0,0,0); 
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetDiagonal"
/*@ 
   MatGetDiagonal - Gets the diagonal of a matrix.

   Input Parameters:
.  mat - the matrix
.  v - the vector for storing the diagonal

   Output Parameter:
.  v - the diagonal of the matrix

   Notes: For the SeqAIJ matrix format, this routine may also be called
    on a LU factored matrix; in that case it routines the reciprocal of 
    the diagonal entries in U. It returns the entries permuted by the 
    row and column permutation used during the symbolic factorization.

.keywords: matrix, get, diagonal
@*/
int MatGetDiagonal(Mat mat,Vec v)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);PetscValidHeaderSpecific(v,VEC_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  /*
     The error checking for a factored matrix is handled inside 
    each matrix type, since MatGetDiagonal() is supported by 
    factored AIJ matrices
  */
  /* if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix");  */
  if (!mat->ops->getdiagonal) SETERRQ(PETSC_ERR_SUP,0,"");
  ierr = (*mat->ops->getdiagonal)(mat,v);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatTranspose"
/*@C
   MatTranspose - Computes an in-place or out-of-place transpose of a matrix.

   Input Parameter:
.  mat - the matrix to transpose

   Output Parameters:
.  B - the transpose (or pass in PETSC_NULL for an in-place transpose)

.keywords: matrix, transpose

.seealso: MatMultTrans(), MatMultTransAdd()
@*/
int MatTranspose(Mat mat,Mat *B)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->transpose) SETERRQ(PETSC_ERR_SUP,0,""); 
  ierr = (*mat->ops->transpose)(mat,B);CHKERRQ(ierr);
  PetscFunctionReturn(0);  
}

#undef __FUNC__  
#define __FUNC__ "MatPermute"
/*@C
   MatPermute - Creates a new matrix with rows and columns permuted from the 
       original.

   Input Parameter:
.  mat - the matrix to permute
.  row - row permutation
.  col - column permutation

   Output Parameters:
.  B - the permuted matrix

.keywords: matrix, transpose

.seealso: MatGetReordering()
@*/
int MatPermute(Mat mat,IS row,IS col,Mat *B)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(row,IS_COOKIE);
  PetscValidHeaderSpecific(col,IS_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->permute) SETERRQ(PETSC_ERR_SUP,0,""); 
  ierr = (*mat->ops->permute)(mat,row,col,B);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatEqual"
/*@
   MatEqual - Compares two matrices.

   Input Parameters:
.  A - the first matrix
.  B - the second matrix

   Output Parameter:
.  flg : PETSC_TRUE if the matrices are equal;
         PETSC_FALSE otherwise.

.keywords: matrix, equal, equivalent
@*/
int MatEqual(Mat A,Mat B,PetscTruth *flg)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(A,MAT_COOKIE); PetscValidHeaderSpecific(B,MAT_COOKIE);
  PetscValidIntPointer(flg);
  if (!A->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (!B->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (A->M != B->M || A->N != B->N) SETERRQ(PETSC_ERR_ARG_SIZ,0,"Mat A,Mat B: global dim");
  if (!A->ops->equal) SETERRQ(PETSC_ERR_SUP,0,"");
  ierr = (*A->ops->equal)(A,B,flg);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatDiagonalScale"
/*@
   MatDiagonalScale - Scales a matrix on the left and right by diagonal
   matrices that are stored as vectors.  Either of the two scaling
   matrices can be PETSC_NULL.

   Input Parameters:
.  mat - the matrix to be scaled
.  l - the left scaling vector (or PETSC_NULL)
.  r - the right scaling vector (or PETSC_NULL)

   Notes:
   MatDiagonalScale() computes A <- LAR, where
$      L = a diagonal matrix
$      R = a diagonal matrix

.keywords: matrix, diagonal, scale

.seealso: MatDiagonalScale()
@*/
int MatDiagonalScale(Mat mat,Vec l,Vec r)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (!mat->ops->diagonalscale) SETERRQ(PETSC_ERR_SUP,0,"");
  if (l) PetscValidHeaderSpecific(l,VEC_COOKIE); 
  if (r) PetscValidHeaderSpecific(r,VEC_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 

  PLogEventBegin(MAT_Scale,mat,0,0,0);
  ierr = (*mat->ops->diagonalscale)(mat,l,r); CHKERRQ(ierr);
  PLogEventEnd(MAT_Scale,mat,0,0,0);
  PetscFunctionReturn(0);
} 

#undef __FUNC__  
#define __FUNC__ "MatScale"
/*@
    MatScale - Scales all elements of a matrix by a given number.

    Input Parameters:
.   mat - the matrix to be scaled
.   a  - the scaling value

    Output Parameter:
.   mat - the scaled matrix

.keywords: matrix, scale

.seealso: MatDiagonalScale()
@*/
int MatScale(Scalar *a,Mat mat)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidScalarPointer(a);
  if (!mat->ops->scale) SETERRQ(PETSC_ERR_SUP,0,"");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 

  PLogEventBegin(MAT_Scale,mat,0,0,0);
  ierr = (*mat->ops->scale)(a,mat); CHKERRQ(ierr);
  PLogEventEnd(MAT_Scale,mat,0,0,0);
  PetscFunctionReturn(0);
} 

#undef __FUNC__  
#define __FUNC__ "MatNorm"
/*@ 
   MatNorm - Calculates various norms of a matrix.

   Input Parameters:
.  mat - the matrix
.  type - the type of norm, NORM_1, NORM_2, NORM_FROBENIUS, NORM_INFINITY

   Output Parameters:
.  norm - the resulting norm 

.keywords: matrix, norm, Frobenius
@*/
int MatNorm(Mat mat,NormType type,double *norm)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidScalarPointer(norm);

  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->norm) SETERRQ(PETSC_ERR_SUP,0,"Not for this matrix type");
  ierr = (*mat->ops->norm)(mat,type,norm);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

/* 
     This variable is used to prevent counting of MatAssemblyBegin() that
   are called from within a MatAssemblyEnd().
*/
static int MatAssemblyEnd_InUse = 0;
#undef __FUNC__  
#define __FUNC__ "MatAssemblyBegin"
/*@
   MatAssemblyBegin - Begins assembling the matrix.  This routine should
   be called after completing all calls to MatSetValues().

   Input Parameters:
.  mat - the matrix 
.  type - type of assembly, either MAT_FLUSH_ASSEMBLY or MAT_FINAL_ASSEMBLY
 
   Notes: 
   MatSetValues() generally caches the values.  The matrix is ready to
   use only after MatAssemblyBegin() and MatAssemblyEnd() have been called.
   Use MAT_FLUSH_ASSEMBLY when switching between ADD_VALUES and INSERT_VALUES
   in MatSetValues(); use MAT_FINAL_ASSEMBLY for the final assembly before
   using the matrix.

.keywords: matrix, assembly, assemble, begin

.seealso: MatAssemblyEnd(), MatSetValues()
@*/
int MatAssemblyBegin(Mat mat,MatAssemblyType type)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix.\n did you forget to call MatSetUnfactored()?"); 
  if (mat->assembled) {
    mat->was_assembled = PETSC_TRUE; 
    mat->assembled     = PETSC_FALSE;
  }
  if (!MatAssemblyEnd_InUse) {
    PLogEventBegin(MAT_AssemblyBegin,mat,0,0,0);
    if (mat->ops->assemblybegin){ierr = (*mat->ops->assemblybegin)(mat,type);CHKERRQ(ierr);}
    PLogEventEnd(MAT_AssemblyBegin,mat,0,0,0);
  } else {
    if (mat->ops->assemblybegin){ierr = (*mat->ops->assemblybegin)(mat,type);CHKERRQ(ierr);}
  }
  PetscFunctionReturn(0);
}


#undef __FUNC__  
#define __FUNC__ "MatView_Private"
/*
    Processes command line options to determine if/how a matrix
  is to be viewed. Called by MatAssemblyEnd() and MatLoad().
*/
int MatView_Private(Mat mat)
{
  int ierr,flg;

  PetscFunctionBegin;
  ierr = OptionsHasName(PETSC_NULL,"-mat_view_info",&flg); CHKERRQ(ierr);
  if (flg) {
    ierr = ViewerPushFormat(VIEWER_STDOUT_(mat->comm),VIEWER_FORMAT_ASCII_INFO,0);CHKERRQ(ierr);
    ierr = MatView(mat,VIEWER_STDOUT_(mat->comm)); CHKERRQ(ierr);
    ierr = ViewerPopFormat(VIEWER_STDOUT_(mat->comm));CHKERRQ(ierr);
  }
  ierr = OptionsHasName(PETSC_NULL,"-mat_view_info_detailed",&flg);CHKERRQ(ierr);
  if (flg) {
    ierr = ViewerPushFormat(VIEWER_STDOUT_(mat->comm),VIEWER_FORMAT_ASCII_INFO_LONG,0);CHKERRQ(ierr);
    ierr = MatView(mat,VIEWER_STDOUT_(mat->comm)); CHKERRQ(ierr);
    ierr = ViewerPopFormat(VIEWER_STDOUT_(mat->comm));CHKERRQ(ierr);
  }
  ierr = OptionsHasName(PETSC_NULL,"-mat_view",&flg); CHKERRQ(ierr);
  if (flg) {
    ierr = MatView(mat,VIEWER_STDOUT_(mat->comm)); CHKERRQ(ierr);
  }
  ierr = OptionsHasName(PETSC_NULL,"-mat_view_matlab",&flg); CHKERRQ(ierr);
  if (flg) {
    ierr = ViewerPushFormat(VIEWER_STDOUT_(mat->comm),VIEWER_FORMAT_ASCII_MATLAB,"M");CHKERRQ(ierr);
    ierr = MatView(mat,VIEWER_STDOUT_(mat->comm)); CHKERRQ(ierr);
    ierr = ViewerPopFormat(VIEWER_STDOUT_(mat->comm));CHKERRQ(ierr);
  }
  ierr = OptionsHasName(PETSC_NULL,"-mat_view_draw",&flg); CHKERRQ(ierr);
  if (flg) {
    ierr = OptionsHasName(0,"-mat_view_contour",&flg); CHKERRQ(ierr);
    if (flg) {
      ViewerPushFormat(VIEWER_DRAWX_(mat->comm),VIEWER_FORMAT_DRAW_CONTOUR,0);CHKERRQ(ierr);
    }
    ierr = MatView(mat,VIEWER_DRAWX_(mat->comm)); CHKERRQ(ierr);
    ierr = ViewerFlush(VIEWER_DRAWX_(mat->comm)); CHKERRQ(ierr);
    if (flg) {
      ViewerPopFormat(VIEWER_DRAWX_(mat->comm));CHKERRQ(ierr);
    }
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatAssemblyEnd"
/*@
   MatAssemblyEnd - Completes assembling the matrix.  This routine should
   be called after MatAssemblyBegin().

   Input Parameters:
.  mat - the matrix 
.  type - type of assembly, either MAT_FLUSH_ASSEMBLY or MAT_FINAL_ASSEMBLY

   Options Database Keys:
$  -mat_view_info : Prints info on matrix at
$      conclusion of MatEndAssembly()
$  -mat_view_info_detailed: Prints more detailed info.
$  -mat_view : Prints matrix in ASCII format.
$  -mat_view_matlab : Prints matrix in Matlab format.
$  -mat_view_draw : Draws nonzero structure of matrix,
$      using MatView() and DrawOpenX().
$  -display <name> : Set display name (default is host)
$  -draw_pause <sec> : Set number of seconds to pause after display

   Notes: 
   MatSetValues() generally caches the values.  The matrix is ready to
   use only after MatAssemblyBegin() and MatAssemblyEnd() have been called.
   Use MAT_FLUSH_ASSEMBLY when switching between ADD_VALUES and INSERT_VALUES
   in MatSetValues(); use MAT_FINAL_ASSEMBLY for the final assembly before
   using the matrix.

.keywords: matrix, assembly, assemble, end

.seealso: MatAssemblyBegin(), MatSetValues(), DrawOpenX(), MatView()
@*/
int MatAssemblyEnd(Mat mat,MatAssemblyType type)
{
  int        ierr;
  static int inassm = 0;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);

  inassm++;
  MatAssemblyEnd_InUse++;
  PLogEventBegin(MAT_AssemblyEnd,mat,0,0,0);
  if (mat->ops->assemblyend) {
    ierr = (*mat->ops->assemblyend)(mat,type); CHKERRQ(ierr);
  }

  /* Flush assembly is not a true assembly */
  if (type != MAT_FLUSH_ASSEMBLY) {
    mat->assembled  = PETSC_TRUE; mat->num_ass++;
  }
  mat->insertmode = NOT_SET_VALUES;
  PLogEventEnd(MAT_AssemblyEnd,mat,0,0,0);
  MatAssemblyEnd_InUse--;

  if (inassm == 1 && type != MAT_FLUSH_ASSEMBLY) {
    ierr = MatView_Private(mat); CHKERRQ(ierr);
  }
  inassm--;
  PetscFunctionReturn(0);
}


#undef __FUNC__  
#define __FUNC__ "MatCompress"
/*@
   MatCompress - Tries to store the matrix in as little space as 
   possible.  May fail if memory is already fully used, since it
   tries to allocate new space.

   Input Parameters:
.  mat - the matrix 

.keywords: matrix, compress
@*/
int MatCompress(Mat mat)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->ops->compress) {ierr = (*mat->ops->compress)(mat);CHKERRQ(ierr);}
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatSetOption"
/*@
   MatSetOption - Sets a parameter option for a matrix. Some options
   may be specific to certain storage formats.  Some options
   determine how values will be inserted (or added). Sorted, 
   row-oriented input will generally assemble the fastest. The default
   is row-oriented, nonsorted input. 

   Input Parameters:
.  mat - the matrix 
.  option - the option, one of those listed below (and possibly others),
             e.g., MAT_ROWS_SORTED, MAT_NEW_NONZERO_LOCATION_ERROR

   Options Describing Matrix Structure:
$    MAT_SYMMETRIC - symmetric in terms of both structure and value
$    MAT_STRUCTURALLY_SYMMETRIC - symmetric nonzero structure

   Options For Use with MatSetValues():
   Insert a logically dense subblock, which can be

$    MAT_ROW_ORIENTED - row-oriented
$    MAT_COLUMN_ORIENTED - column-oriented
$    MAT_ROWS_SORTED - sorted by row
$    MAT_ROWS_UNSORTED - not sorted by row
$    MAT_COLUMNS_SORTED - sorted by column
$    MAT_COLUMNS_UNSORTED - not sorted by column

   Not these options reflect the data you pass in with MatSetValues(); it has 
   nothing to do with how the data is stored internally in the matrix 
   data structure.

   When (re)assembling a matrix, we can restrict the input for
   efficiency/debugging purposes.

$    MAT_NO_NEW_NONZERO_LOCATIONS - additional insertions will not be
        allowed if they generate a new nonzero
$    MAT_YES_NEW_NONZERO_LOCATIONS - additional insertions will be allowed
$    MAT_NO_NEW_DIAGONALS - additional insertions will not be allowed if
         they generate a nonzero in a new diagonal (for block diagonal format only)
$    MAT_YES_NEW_DIAGONALS - new diagonals will be allowed (for block diagonal format only)
$    MAT_IGNORE_OFF_PROC_ENTRIES - drop off-processor entries
$    MAT_NEW_NONZERO_LOCATION_ERROR - generate error for new matrix entry
$    MAT_USE_HASH_TABLE - use hash table which speeds up the Matrix assembly

   Notes:
   Some options are relevant only for particular matrix types and
   are thus ignored by others.  Other options are not supported by
   certain matrix types and will generate an error message if set.

   If using a Fortran 77 module to compute a matrix, one may need to 
   use the column-oriented option (or convert to the row-oriented 
   format).  

   MAT_NO_NEW_NONZERO_LOCATIONS indicates that any add or insertion 
   that would generate a new entry in the nonzero structure is instead
   ignored.  Thus, if memory has not alredy been allocated for this particular 
   data, then the insertion is ignored. For dense matrices, in which
   the entire array is allocated, no entries are ever ignored. 

   MAT_NEW_NONZERO_LOCATION_ERROR indicates that any add or insertion 
   that would generate a new entry in the nonzero structure instead produces 
   an error. (Currently supported for AIJ and BAIJ formats only.)
   This is a useful flag when using SAME_NONZERO_PATTERN in calling
   SLESSetOperators() to ensure that the nonzero pattern truely does 
   remain unchanged.

   MAT_NEW_NONZERO_ALLOCATION_ERROR indicates that any add or insertion 
   that would generate a new entry that has not been preallocated will 
   instead produce an error. (Currently supported for AIJ and BAIJ formats
   only.) This is a useful flag when debugging matrix memory preallocation.

   MAT_IGNORE_OFF_PROC_ENTRIES indicates entries destined for 
   other processors should be dropped, rather than stashed.
   This is useful if you know that the "owning" processor is also 
   always generating the correct matrix entries, so that PETSc need
   not transfer duplicate entries generated on another processor.
   
   MAT_USE_HASH_TABLE indicates that a hash table be used to improve the
   searches during matrix assembly. When this flag is set, the hash table
   is created during the first Matrix Assembly. This hash table is
   used the next time through, during MatSetVaules()/MatSetVaulesBlocked()
   to improve the searching of indices. MAT_NO_NEW_NONZERO_LOCATIONS flag 
   should be used with MAT_USE_HASH_TABLE flag. This option is currently
   supported by MATMPIBAIJ format only.

.keywords: matrix, option, row-oriented, column-oriented, sorted, nonzero
@*/
int MatSetOption(Mat mat,MatOption op)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->ops->setoption) {ierr = (*mat->ops->setoption)(mat,op);CHKERRQ(ierr);}
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatZeroEntries"
/*@
   MatZeroEntries - Zeros all entries of a matrix.  For sparse matrices
   this routine retains the old nonzero structure.

   Input Parameters:
.  mat - the matrix 

.keywords: matrix, zero, entries

.seealso: MatZeroRows()
@*/
int MatZeroEntries(Mat mat)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->zeroentries) SETERRQ(PETSC_ERR_SUP,0,"");

  PLogEventBegin(MAT_ZeroEntries,mat,0,0,0);
  ierr = (*mat->ops->zeroentries)(mat); CHKERRQ(ierr);
  PLogEventEnd(MAT_ZeroEntries,mat,0,0,0);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatZeroRows"
/*@ 
   MatZeroRows - Zeros all entries (except possibly the main diagonal)
   of a set of rows of a matrix.

   Input Parameters:
.  mat - the matrix
.  is - index set of rows to remove
.  diag - pointer to value put in all diagonals of eliminated rows.
          Note that diag is not a pointer to an array, but merely a
          pointer to a single value.

   Notes:
   For the AIJ matrix formats this removes the old nonzero structure,
   but does not release memory.  For the dense and block diagonal
   formats this does not alter the nonzero structure.

   The user can set a value in the diagonal entry (or for the AIJ and
   row formats can optionally remove the main diagonal entry from the
   nonzero structure as well, by passing a null pointer as the final
   argument).

   For the parallel case, all processes that share the matrix (i.e.,
   those in the communicator used for matrix creation) MUST call this
   routine, regardless of whether any rows being zeroed are owned by
   them.

.keywords: matrix, zero, rows, boundary conditions 

.seealso: MatZeroEntries(), 
@*/
int MatZeroRows(Mat mat,IS is, Scalar *diag)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(is,IS_COOKIE);
  if (diag) PetscValidScalarPointer(diag);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->zerorows) SETERRQ(PETSC_ERR_SUP,0,"");

  ierr = (*mat->ops->zerorows)(mat,is,diag); CHKERRQ(ierr);
  ierr = MatView_Private(mat); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatZeroRowsLocal"
/*@ 
   MatZeroRowsLocal - Zeros all entries (except possibly the main diagonal)
   of a set of rows of a matrix; using local numbering of rows.

   Input Parameters:
.  mat - the matrix
.  is - index set of rows to remove
.  diag - pointer to value put in all diagonals of eliminated rows.
          Note that diag is not a pointer to an array, but merely a
          pointer to a single value.

   Notes:
   For the AIJ matrix formats this removes the old nonzero structure,
   but does not release memory.  For the dense and block diagonal
   formats this does not alter the nonzero structure.

   The user can set a value in the diagonal entry (or for the AIJ and
   row formats can optionally remove the main diagonal entry from the
   nonzero structure as well, by passing a null pointer as the final
   argument).

.keywords: matrix, zero, rows, boundary conditions 

.seealso: MatZeroEntries(), 
@*/
int MatZeroRowsLocal(Mat mat,IS is, Scalar *diag)
{
  int ierr;
  IS  newis;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidHeaderSpecific(is,IS_COOKIE);
  if (diag) PetscValidScalarPointer(diag);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (!mat->ops->zerorows) SETERRQ(PETSC_ERR_SUP,0,"");

  ierr = ISLocalToGlobalMappingApplyIS(mat->mapping,is,&newis); CHKERRQ(ierr);
  ierr =  (*mat->ops->zerorows)(mat,newis,diag); CHKERRQ(ierr);
  ierr = ISDestroy(newis);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetSize"
/*@
   MatGetSize - Returns the numbers of rows and columns in a matrix.

   Input Parameter:
.  mat - the matrix

   Output Parameters:
.  m - the number of global rows
.  n - the number of global columns

.keywords: matrix, dimension, size, rows, columns, global, get

.seealso: MatGetLocalSize()
@*/
int MatGetSize(Mat mat,int *m,int* n)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  ierr = (*mat->ops->getsize)(mat,m,n);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetLocalSize"
/*@
   MatGetLocalSize - Returns the number of rows and columns in a matrix
   stored locally.  This information may be implementation dependent, so
   use with care.

   Input Parameters:
.  mat - the matrix

   Output Parameters:
.  m - the number of local rows
.  n - the number of local columns

.keywords: matrix, dimension, size, local, rows, columns, get

.seealso: MatGetSize()
@*/
int MatGetLocalSize(Mat mat,int *m,int* n)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  ierr = (*mat->ops->getlocalsize)(mat,m,n);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetOwnershipRange"
/*@
   MatGetOwnershipRange - Returns the range of matrix rows owned by
   this processor, assuming that the matrix is laid out with the first
   n1 rows on the first processor, the next n2 rows on the second, etc.
   For certain parallel layouts this range may not be well defined.

   Input Parameters:
.  mat - the matrix

   Output Parameters:
.  m - the global index of the first local row
.  n - one more than the global index of the last local row

.keywords: matrix, get, range, ownership
@*/
int MatGetOwnershipRange(Mat mat,int *m,int* n)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(m);
  PetscValidIntPointer(n);
  if (!mat->ops->getownershiprange) SETERRQ(PETSC_ERR_SUP,0,"");
  ierr = (*mat->ops->getownershiprange)(mat,m,n);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatILUFactorSymbolic"
/*@  
   MatILUFactorSymbolic - Performs symbolic ILU factorization of a matrix.
   Uses levels of fill only, not drop tolerance. Use MatLUFactorNumeric() 
   to complete the factorization.

   Input Parameters:
.  mat - the matrix
.  row - row permutation
.  column - column permutation
.  fill - number of levels of fill
.  f - expected fill as ratio of the original number of nonzeros, 
       for example 3.0; choosing this parameter well can result in 
       more efficient use of time and space. Run your code with -log_info 
       to determine an optimal value to use.

   Output Parameters:
.  fact - new matrix that has been symbolically factored

   Notes:
   See the file ${PETSC_DIR}/Performace for additional information about
   choosing the fill factor for better efficiency.

.keywords: matrix, factor, incomplete, ILU, symbolic, fill

.seealso: MatLUFactorSymbolic(), MatLUFactorNumeric()
@*/
int MatILUFactorSymbolic(Mat mat,IS row,IS col,double f,int fill,Mat *fact)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(fact);
  if (fill < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Levels of fill negative");
  if (!mat->ops->ilufactorsymbolic) SETERRQ(PETSC_ERR_SUP,0,"Only MatCreateMPIRowbs() matrices support parallel ILU");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 

  PLogEventBegin(MAT_ILUFactorSymbolic,mat,row,col,0);
  ierr = (*mat->ops->ilufactorsymbolic)(mat,row,col,f,fill,fact); CHKERRQ(ierr);
  PLogEventEnd(MAT_ILUFactorSymbolic,mat,row,col,0);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatIncompleteCholeskyFactorSymbolic"
/*@  
   MatIncompleteCholeskyFactorSymbolic - Performs symbolic incomplete
   Cholesky factorization for a symmetric matrix.  Use 
   MatCholeskyFactorNumeric() to complete the factorization.

   Input Parameters:
.  mat - the matrix
.  perm - row and column permutation
.  fill - levels of fill
.  f - expected fill as ratio of original fill

   Output Parameter:
.  fact - the factored matrix

   Note:  Currently only no-fill factorization is supported.

.keywords: matrix, factor, incomplete, ICC, Cholesky, symbolic, fill

.seealso: MatCholeskyFactorNumeric(), MatCholeskyFactor()
@*/
int MatIncompleteCholeskyFactorSymbolic(Mat mat,IS perm,double f,int fill,Mat *fact)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(fact);
  if (mat->factor) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 
  if (fill < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,0,"Fill negative");
  if (!mat->ops->incompletecholeskyfactorsymbolic) SETERRQ(PETSC_ERR_SUP,0,"Currently only MatCreateMPIRowbs() matrices support ICC in parallel");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");

  PLogEventBegin(MAT_IncompleteCholeskyFactorSymbolic,mat,perm,0,0);
  ierr = (*mat->ops->incompletecholeskyfactorsymbolic)(mat,perm,f,fill,fact);CHKERRQ(ierr);
  PLogEventEnd(MAT_IncompleteCholeskyFactorSymbolic,mat,perm,0,0);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetArray"
/*@C
   MatGetArray - Returns a pointer to the element values in the matrix.
   This routine  is implementation dependent, and may not even work for 
   certain matrix types. You MUST call MatRestoreArray() when you no 
   longer need to access the array.

   Input Parameter:
.  mat - the matrix

   Output Parameter:
.  v - the location of the values

   Fortran Note:
   The Fortran interface is slightly different from that given below.
   See the Fortran chapter of the users manual and 
   petsc/src/mat/examples for details.

.keywords: matrix, array, elements, values

.seealso: MatRestoreArray()
@*/
int MatGetArray(Mat mat,Scalar **v)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(v);
  if (!mat->ops->getarray) SETERRQ(PETSC_ERR_SUP,0,"");
  ierr = (*mat->ops->getarray)(mat,v);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatRestoreArray"
/*@C
   MatRestoreArray - Restores the matrix after MatGetArray has been called.

   Input Parameter:
.  mat - the matrix
.  v - the location of the values

   Fortran Note:
   The Fortran interface is slightly different from that given below.
   See the users manual and petsc/src/mat/examples for details.

.keywords: matrix, array, elements, values, restore

.seealso: MatGetArray()
@*/
int MatRestoreArray(Mat mat,Scalar **v)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidPointer(v);
  if (!mat->ops->restorearray) SETERRQ(PETSC_ERR_SUP,0,"");
  ierr = (*mat->ops->restorearray)(mat,v);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetSubMatrices"
/*@C
   MatGetSubMatrices - Extracts several submatrices from a matrix. If submat
     points to an array of valid matrices, they may be reused to store the new
     submatrices.

   Input Parameters:
.  mat - the matrix
.  n   - the number of submatrixes to be extracted
.  irow, icol - index sets of rows and columns to extract
.  scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

   Output Parameter:
.  submat - the array of submatrices

   Notes:
   MatGetSubMatrices() can extract only sequential submatrices
   (from both sequential and parallel matrices). Use MatGetSubMatrix()
   to extract a parallel submatrix.

   When extracting submatrices from a parallel matrix, each processor can
   form a different submatrix by setting the rows and columns of its
   individual index sets according to the local submatrix desired.

   When finished using the submatrices, the user should destroy
   them with MatDestroySubMatrices().

.keywords: matrix, get, submatrix, submatrices

.seealso: MatDestroyMatrices(), MatGetSubMatrix()
@*/
int MatGetSubMatrices(Mat mat,int n,IS *irow,IS *icol,MatGetSubMatrixCall scall,Mat **submat)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (!mat->ops->getsubmatrices) SETERRQ(PETSC_ERR_SUP,0,"");
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");

  PLogEventBegin(MAT_GetSubMatrices,mat,0,0,0);
  ierr = (*mat->ops->getsubmatrices)(mat,n,irow,icol,scall,submat); CHKERRQ(ierr);
  PLogEventEnd(MAT_GetSubMatrices,mat,0,0,0);

  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatDestroyMatrices"
/*@C
   MatDestroyMatrices - Destroys a set of matrices obtained with MatGetSubMatrices().

   Input Parameters:
.  n - the number of local matrices
.  mat - the matrices

.keywords: matrix, destroy, submatrix, submatrices

.seealso: MatGetSubMatrices()
@*/
int MatDestroyMatrices(int n,Mat **mat)
{
  int ierr,i;

  PetscFunctionBegin;
  if (n < 0) SETERRQ(PETSC_ERR_ARG_OUTOFRANGE,1,"Trying to destroy negative number of matrices");
  PetscValidPointer(mat);
  for ( i=0; i<n; i++ ) {
    ierr = MatDestroy((*mat)[i]); CHKERRQ(ierr);
  }
  if (n) PetscFree(*mat);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatIncreaseOverlap"
/*@
   MatIncreaseOverlap - Given a set of submatrices indicated by index sets,
   replaces the index sets by larger ones that represent submatrices with
   additional overlap.

   Input Parameters:
.  mat - the matrix
.  n   - the number of index sets
.  is  - the array of pointers to index sets
.  ov  - the additional overlap requested

.keywords: matrix, overlap, Schwarz

.seealso: MatGetSubMatrices()
@*/
int MatIncreaseOverlap(Mat mat,int n, IS *is,int ov)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (!mat->assembled) SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for unassembled matrix");
  if (mat->factor)     SETERRQ(PETSC_ERR_ARG_WRONGSTATE,0,"Not for factored matrix"); 

  if (ov == 0) PetscFunctionReturn(0);
  if (!mat->ops->increaseoverlap) SETERRQ(PETSC_ERR_SUP,0,"");
  PLogEventBegin(MAT_IncreaseOverlap,mat,0,0,0);
  ierr = (*mat->ops->increaseoverlap)(mat,n,is,ov); CHKERRQ(ierr);
  PLogEventEnd(MAT_IncreaseOverlap,mat,0,0,0);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatPrintHelp"
/*@
   MatPrintHelp - Prints all the options for the matrix.

   Input Parameter:
.  mat - the matrix 

   Options Database Keys:
$  -help, -h

.keywords: mat, help

.seealso: MatCreate(), MatCreateXXX()
@*/
int MatPrintHelp(Mat mat)
{
  static int called = 0;
  int        ierr;
  MPI_Comm   comm;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);

  comm = mat->comm;
  if (!called) {
    (*PetscHelpPrintf)(comm,"General matrix options:\n");
    (*PetscHelpPrintf)(comm,"  -mat_view_info: view basic matrix info during MatAssemblyEnd()\n");
    (*PetscHelpPrintf)(comm,"  -mat_view_info_detailed: view detailed matrix info during MatAssemblyEnd()\n");
    (*PetscHelpPrintf)(comm,"  -mat_view_draw: draw nonzero matrix structure during MatAssemblyEnd()\n");
    (*PetscHelpPrintf)(comm,"      -draw_pause <sec>: set seconds of display pause\n");
    (*PetscHelpPrintf)(comm,"      -display <name>: set alternate display\n");
    called = 1;
  }
  if (mat->ops->printhelp) {
    ierr = (*mat->ops->printhelp)(mat); CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetBlockSize"
/*@
   MatGetBlockSize - Returns the matrix block size; useful especially for the
   block row and block diagonal formats.
   
   Input Parameter:
.  mat - the matrix

   Output Parameter:
.  bs - block size

   Notes:
$  block diagonal formats: MATSEQBDIAG, MATMPIBDIAG
$  block row formats: MATSEQBAIJ, MATMPIBAIJ

.keywords: matrix, get, block, size 

.seealso: MatCreateSeqBAIJ(), MatCreateMPIBAIJ(), MatCreateSeqBDiag(), MatCreateMPIBDiag()
@*/
int MatGetBlockSize(Mat mat,int *bs)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(bs);
  if (!mat->ops->getblocksize) SETERRQ(PETSC_ERR_SUP,0,"");
  ierr = (*mat->ops->getblocksize)(mat,bs);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetRowIJ"
/*@C
      MatGetRowIJ - Returns the compress row storage i and j indices for sequential matrices.
                 EXPERTS ONLY.

  Input Parameters:
.   mat - the matrix
.   shift -  0 or 1 indicating we want the indices starting at 0 or 1
.   symmetric - PETSC_TRUE or PETSC_FALSE indicating the matrix data structure should be
                symmetrized

  Output Parameters:
.   n - number of rows and columns in the (possibly compressed) matrix
.   ia - the row indices
.   ja - the column indices
.   done - PETSC_TRUE or PETSC_FALSE indicated that the values have been returned
@*/
int MatGetRowIJ(Mat mat,int shift,PetscTruth symmetric,int *n,int **ia,int** ja,PetscTruth *done)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (ia) PetscValidIntPointer(ia);
  if (ja) PetscValidIntPointer(ja);
  PetscValidIntPointer(done);
  if (!mat->ops->getrowij) *done = PETSC_FALSE;
  else {
    *done = PETSC_TRUE;
    ierr  = (*mat->ops->getrowij)(mat,shift,symmetric,n,ia,ja,done); CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetColumnIJ"
/*@C
      MatGetColumnIJ - Returns the compress Column storage i and j indices for sequential matrices.
                 EXPERTS ONLY.

  Input Parameters:
.   mat - the matrix
.   shift - 1 or zero indicating we want the indices starting at 0 or 1
.   symmetric - PETSC_TRUE or PETSC_FALSE indicating the matrix data structure should be
                symmetrized

  Output Parameters:
.   n - number of Columns and columns in the (possibly compressed) matrix
.   ia - the Column indices
.   ja - the column indices
.   done - PETSC_TRUE or PETSC_FALSE indicated that the values have been returned
@*/
int MatGetColumnIJ(Mat mat,int shift,PetscTruth symmetric,int *n,int **ia,int** ja,PetscTruth *done)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (ia) PetscValidIntPointer(ia);
  if (ja) PetscValidIntPointer(ja);
  PetscValidIntPointer(done);

  if (!mat->ops->getcolumnij) *done = PETSC_FALSE;
  else {
    *done = PETSC_TRUE;
    ierr  = (*mat->ops->getcolumnij)(mat,shift,symmetric,n,ia,ja,done); CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatRestoreRowIJ"
/*@C
      MatRestoreRowIJ - Call after you are completed with the ia,ja indices obtained with
                     MatGetRowIJ(). EXPERTS ONLY.

  Input Parameters:
.   mat - the matrix
.   shift - 1 or zero indicating we want the indices starting at 0 or 1
.   symmetric - PETSC_TRUE or PETSC_FALSE indicating the matrix data structure should be
                symmetrized

  Output Parameters:
.   n - size of (possibly compressed) matrix
.   ia - the row indices
.   ja - the column indices
.   done - PETSC_TRUE or PETSC_FALSE indicated that the values have been returned
@*/
int MatRestoreRowIJ(Mat mat,int shift,PetscTruth symmetric,int *n,int **ia,int** ja,PetscTruth *done)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (ia) PetscValidIntPointer(ia);
  if (ja) PetscValidIntPointer(ja);
  PetscValidIntPointer(done);

  if (!mat->ops->restorerowij) *done = PETSC_FALSE;
  else {
    *done = PETSC_TRUE;
    ierr  = (*mat->ops->restorerowij)(mat,shift,symmetric,n,ia,ja,done); CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatRestoreColumnIJ"
/*@C
      MatRestoreColumnIJ - Call after you are completed with the ia,ja indices obtained with
                     MatGetColumnIJ(). EXPERTS ONLY.

  Input Parameters:
.   mat - the matrix
.   shift - 1 or zero indicating we want the indices starting at 0 or 1
.   symmetric - PETSC_TRUE or PETSC_FALSE indicating the matrix data structure should be
                symmetrized

  Output Parameters:
.   n - size of (possibly compressed) matrix
.   ia - the Column indices
.   ja - the column indices
.   done - PETSC_TRUE or PETSC_FALSE indicated that the values have been returned
@*/
int MatRestoreColumnIJ(Mat mat,int shift,PetscTruth symmetric,int *n,int **ia,int** ja,PetscTruth *done)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  if (ia) PetscValidIntPointer(ia);
  if (ja) PetscValidIntPointer(ja);
  PetscValidIntPointer(done);

  if (!mat->ops->restorecolumnij) *done = PETSC_FALSE;
  else {
    *done = PETSC_TRUE;
    ierr  = (*mat->ops->restorecolumnij)(mat,shift,symmetric,n,ia,ja,done); CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatColoringPatch"
/*@C
      MatColoringPatch - EXPERTS ONLY, used inside matrix coloring routines that 
          use matGetRowIJ() and/or MatGetColumnIJ().

  Input Parameters:
.   mat - the matrix
.   n   - number of colors
.   colorarray - array indicating color for each column

  Output Parameters:
.   iscoloring - coloring generated using colorarray information

@*/
int MatColoringPatch(Mat mat,int n,int *colorarray,ISColoring *iscoloring)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);
  PetscValidIntPointer(colorarray);

  if (!mat->ops->coloringpatch) {SETERRQ(PETSC_ERR_SUP,0,"");}
  else {
    ierr  = (*mat->ops->coloringpatch)(mat,n,colorarray,iscoloring); CHKERRQ(ierr);
  }
  PetscFunctionReturn(0);
}


#undef __FUNC__  
#define __FUNC__ "MatSetUnfactored"
/*@
   MatSetUnfactored - Resets a factored matrix to be treated as unfactored.

   Input Paramter:
.  mat - the factored matrix to be reset

   Notes: 
   This routine should be used only with factored matrices formed by in-place
   factorization via ILU(0) (or by in-place LU factorization for the MATSEQDENSE
   format).  This option can save memory, for example, when solving nonlinear
   systems with a matrix-free Newton-Krylov method and a matrix-based, in-place
   ILU(0) preconditioner.  

  Note that one can specify in-place ILU(0) factorization by calling 
$     PCType(pc,PCILU);
$     PCILUSeUseInPlace(pc);
  or by using the options -pc_type ilu -pc_ilu_in_place

  In-place factorization ILU(0) can also be used as a local
  solver for the blocks within the block Jacobi or additive Schwarz
  methods (runtime option: -sub_pc_ilu_in_place).  See the discussion 
  of these preconditioners in the users manual for details on setting
  local solver options.

.seealso: PCILUSetUseInPlace(), PCLUSetUseInPlace()

.keywords: matrix-free, in-place ILU, in-place LU
@*/
int MatSetUnfactored(Mat mat)
{
  int ierr;

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);  
  mat->factor = 0;
  if (!mat->ops->setunfactored) PetscFunctionReturn(0);
  ierr = (*mat->ops->setunfactored)(mat); CHKERRQ(ierr);
  PetscFunctionReturn(0);
}

#undef __FUNC__  
#define __FUNC__ "MatGetType"
/*@C
   MatGetType - Gets the matrix type and name (as a string) from the matrix.

   Input Parameter:
.  mat - the matrix

   Output Parameter:
.  type - the matrix type (or use PETSC_NULL)
.  name - name of matrix type (or use PETSC_NULL)

.keywords: matrix, get, type, name
@*/
int MatGetType(Mat mat,MatType *type,char **name)
{
  int  itype = (int)mat->type;
  char *matname[10];

  PetscFunctionBegin;
  PetscValidHeaderSpecific(mat,MAT_COOKIE);

  if (type) *type = (MatType) mat->type;
  if (name) {
    /* Note:  Be sure that this list corresponds to the enum in mat.h */
    matname[0] = "MATSEQDENSE";
    matname[1] = "MATSEQAIJ";
    matname[2] = "MATMPIAIJ";
    matname[3] = "MATSHELL";
    matname[4] = "MATMPIROWBS";
    matname[5] = "MATSEQBDIAG";
    matname[6] = "MATMPIBDIAG";
    matname[7] = "MATMPIDENSE";
    matname[8] = "MATSEQBAIJ";
    matname[9] = "MATMPIBAIJ";
    
    if (itype < 0 || itype > 9) *name = "Unknown matrix type";
    else                        *name = matname[itype];
  }
  PetscFunctionReturn(0);
}

/*MC
    MatGetArrayF90 - Accesses a matrix array from Fortran90.

    Input Parameter:
.   x - matrix

    Output Parameter:
.   xx_v - the Fortran90 pointer to the array
.   ierr - error code

    Synopsis:
    MatGetArrayF90(Mat x,{Scalar, pointer :: xx_v(:)},integer ierr)

    Usage: 
$     Scalar, pointer xx_v(:)
$     ....
$     call MatGetArrayF90(x,xx_v,ierr)
$     a = xx_v(3)
$     call MatRestoreArrayF90(x,xx_v,ierr)

    Notes:
    Currently only supported using the NAG F90 compiler.

.seealso:  MatRestoreArrayF90(), MatGetArray(), MatRestoreArray()

.keywords:  matrix, array, f90
M*/

/*MC
    MatRestoreArrayF90 - Restores a matrix array that has been
    accessed with MatGetArrayF90().

    Input Parameters:
.   x - matrix
.   xx_v - the Fortran90 pointer to the array

    Output Parameter:
.   ierr - error code

    Synopsis:
    MatRestoreArrayF90(Mat x,{Scalar, pointer :: xx_v(:)},integer ierr)

    Example of Usage: 
$      Scalar, pointer xx_v(:)
$      ....
$      call MatGetArrayF90(x,xx_v,ierr)
$      a = xx_v(3)
$      call MatRestoreArrayF90(x,xx_v,ierr)
   
    Notes:
    Currently only supported using the NAG F90 compiler.

.seealso:  MatGetArrayF90(), MatGetArray(), MatRestoreArray()

.keywords:  matrix, array, f90
M*/


#undef __FUNC__  
#define __FUNC__ "MatGetSubMatrix"
/*@
     MatGetSubMatrix - Gets a single submatrix on the same number of processors
                       as the original matrix.

   Input Parameters:
.   mat - the original matrix
.   isrow - rows this processor should obtain
.   iscol - columns for all processors you wish kept
.   csize - number of columns "local" to this processor (does nothing for sequential 
            matrices). This should match the result from VecGetLocalSize() if you 
            plan to use the matrix in a A*x
.  cll - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX

   Output Parameters:
.   newmat - the new submatrix, of the same type as the old

.seealso: MatGetSubMatrices()

@*/
int MatGetSubMatrix(Mat mat,IS isrow,IS iscol,int csize,MatGetSubMatrixCall cll,Mat *newmat)
{
  int     ierr, size;
  Mat     *local;

  PetscFunctionBegin;
  MPI_Comm_size(mat->comm,&size);

  /* if original matrix is on just one processor then use submatrix generated */
  if (size == 1 && cll == MAT_REUSE_MATRIX) {
    ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_REUSE_MATRIX,&newmat);CHKERRQ(ierr);
    PetscFunctionReturn(0);
  } else if (size == 1) {
    ierr = MatGetSubMatrices(mat,1,&isrow,&iscol,MAT_INITIAL_MATRIX,&local);CHKERRQ(ierr);
    *newmat = *local;
    PetscFree(local);
    PetscFunctionReturn(0);
  }

  if (!mat->ops->getsubmatrix) SETERRQ(PETSC_ERR_SUP,0,"Not currently implemented");
  ierr = (*mat->ops->getsubmatrix)(mat,isrow,iscol,csize,cll,newmat);CHKERRQ(ierr);
  PetscFunctionReturn(0);
}