FirstDerivativeFirstOrder.c File Reference

First order approximation to the first derivative. More...

#include <stdio.h>
#include <stdlib.h>
#include <basic.h>
#include <mathfunctions.h>
#include <arrayfunctions.h>
#include <firstderivative.h>
#include <mpivars.h>
#include <hypar.h>

Go to the source code of this file.

Typedefs
typedef MPIVariables	MPIContext
typedef HyPar	SolverContext

Functions
int	FirstDerivativeFirstOrder (double *Df, double *f, int dir, int bias, void *s, void *m)

Detailed Description

First order approximation to the first derivative.

Author

Debojyoti Ghosh

Definition in file FirstDerivativeFirstOrder.c.

Typedef Documentation

MPIContext

typedef MPIVariables MPIContext

Definition at line 15 of file FirstDerivativeFirstOrder.c.

SolverContext

typedef HyPar SolverContext

Definition at line 16 of file FirstDerivativeFirstOrder.c.

Function Documentation

FirstDerivativeFirstOrder()

int FirstDerivativeFirstOrder	(	double *	Df,
		double *	f,
		int	dir,
		int	bias,
		void *	s,
		void *	m
	)

Computes the first-order finite-difference approximation to the first derivative (Note: not divided by the grid spacing):

\begin{equation} \left(\partial f\right)_i = \left\{ \begin{array}{ll} f_{i+1} - f_i & {\rm bias} = 1 \\ f_i - f_{i-1} & {\rm bias} = -1 \end{array}\right. \end{equation}

where \(i\) is the grid index along the spatial dimension of the derivative.

Notes:

• The first derivative is computed at the grid points or the cell centers.
• The first derivative is computed at the ghost points too. Thus, biased schemes are used at and near the boundaries.
• Df and f are 1D arrays containing the function and its computed derivatives on a multi- dimensional grid. The derivative along the specified dimension dir is computed by looping through all grid lines along dir.

Parameters

Df	Array to hold the computed first derivative (with ghost points)
f	Array containing the grid point function values whose first derivative is to be computed (with ghost points)
dir	The spatial dimension along which the derivative is computed
bias	Forward or backward differencing for non-central finite-difference schemes (-1: backward, 1: forward)
s	Solver object of type SolverContext
m	MPI object of type MPIContext

Definition at line 37 of file FirstDerivativeFirstOrder.c.

{
  SolverContext *solver = (SolverContext*) s;
  int           i, j, v;

  int ghosts = solver->ghosts;
  int ndims  = solver->ndims;
  int nvars  = solver->nvars;
  int *dim   = solver->dim_local;


  if ((!Df) || (!f)) {
    fprintf(stderr, "Error in FirstDerivativeSecondOrder(): input arrays not allocated.\n");
    return(1);
  }

  /* create index and bounds for the outer loop, i.e., to loop over all 1D lines along
     dimension "dir"                                                                    */
  int indexC[ndims], index_outer[ndims], bounds_outer[ndims];
  _ArrayCopy1D_(dim,bounds_outer,ndims); bounds_outer[dir] =  1;
  int N_outer; _ArrayProduct1D_(bounds_outer,ndims,N_outer);

#pragma omp parallel for schedule(auto) default(shared) private(i,j,v,index_outer,indexC)
  for (j=0; j<N_outer; j++) {
    _ArrayIndexnD_(ndims,j,bounds_outer,index_outer,0);
    _ArrayCopy1D_(index_outer,indexC,ndims);
    /* left boundary */
    for (i = -ghosts; i < -ghosts+1; i++) {
      int qC, qR;
      indexC[dir] = i  ; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qC );
      indexC[dir] = i+1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qR );
      for (v=0; v<nvars; v++)  Df[qC*nvars+v] = f[qR*nvars+v]-f[qC*nvars+v];
    }
    /* interior */
    for (i = -ghosts+1; i < dim[dir]+ghosts-1; i++) {
      int qC, qL, qR;
      indexC[dir] = i  ; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qC );
      indexC[dir] = i-1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qL);
      indexC[dir] = i+1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qR);
      for (v=0; v<nvars; v++)  Df[qC*nvars+v] = max(bias,0)*f[qR*nvars+v]-bias*f[qC*nvars+v]+min(bias,0)*f[qL*nvars+v];
    }
    /* right boundary */
    for (i = dim[dir]+ghosts-1; i < dim[dir]+ghosts; i++) {
      int qL, qC;
      indexC[dir] = i-1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qL );
      indexC[dir] = i  ; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qC );
      for (v=0; v<nvars; v++)  Df[qC*nvars+v] = f[qC*nvars+v]-f[qL*nvars+v];
    }
  }
  
  return(0);
}