CSPLINE

      Function to evaluate a natural cubic spline at specified data points

      Combines the Numerical Recipes functions SPL_INIT and SPL_INTERP

      result = cspline( x, y, t, [ DERIV = ])

      x - vector of spline node positions, must be monotonic increasing or
          decreasing
      y - vector of node values
      t - x-positions at which to evaluate the spline, scalar or vector
 INPUT-OUTPUT KEYWORD:
      DERIV - values of the second derivatives of the interpolating function
               at the node points.   This is an intermediate step in the
               computation of the natural spline that requires only the X and
               Y vectors.    If repeated interpolation is to be applied to
               the same (X,Y) pair, then some computation time can be saved
               by supplying the DERIV keyword on each call.   On the first call
               DERIV will be computed and returned on output.

       the values for positions t are returned as the function value
       If any of the input variables are double precision, then the output will
       also be double precision; otherwise the output is floating point.

       The following uses the example vectors from the SPL_INTERP documentation
       IDL> x = (findgen(21)/20.0)*2.0*!PI ;X vector
       IDL> y = sin(x)                     ;Y vector
       IDL> t = (findgen(11)/11.0)*!PI     ;Values at which to interpolate
       IDL> plot,x,y,psym=1                ;Plot original grid
       IDL> oplot, t,cspline(x,y,t),psym=2 ;Overplot interpolated values

      The "Numerical Recipes" implementation of the natural cubic spline is
      used, by calling the intrinsic IDL functions SPL_INIT and SPL_INTERP.

      version 1  D. Lindler  May, 1989
      version 2  W. Landsman April, 1997
      Rewrite using the intrinsic SPL_INIT & SPL_INTERP functions
      Converted to IDL V5.0   W. Landsman   September 1997
      Work for monotonic decreasing X vector    W. Landsman   February 1999

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