ftcurvp

ftcurvp calculates an interpolatory spline under tension through a sequence of functional values for a periodic function. ftcurvp is in the Fitgrid package -- a package containing 1D and 2D interpolators using cubic splines under tension.

Synopsis

    function ftcurvp(
        xi[*] : float,
        yi[*] : float,
        p[1]  : float,
        xo[*] : float
    )

Arguments

xi
A 1D array of any size (npts) containing the abscissae for the input function.
yi
A 1D array containing the npts functional values of the input function -- yi(k) is the functional value at xi(k) for k=0,npts-1.
p
A scalar value specifying the period of the input function. The value of p must not be less than xi(n-1) - xi(0).
xo
A 1D array containing the abscissae for the interpolated values.

Return value

ftcurvp returns a 1D array that contains the interpolated functional values at the points specified in xo.

Description

There are some parameters that can alter the behavior of ftcurvp. These parameters all have reasonable default values. However, users may change any of these parameters by invoking ftsetp prior to calling ftcurvp. ftcurvp is called after all of the desired values for control parameters have been set.

The only control parameter that applies to ftcurvp is: sig.

The value for the parameter sig specifies the tension factor. Values near zero result in a cubic spline; large values (e.g. 50) result in nearly a polygonal line. A typical value is 1. (the default).

You can extrapolate values with ftcurvp (that is calculate interpolated values for abscissae outside of the domain of the input), but these values are, in general, unreliable.

Example

begin
  xi = (/  0.00,   2.00,   5.00,   8.00,  10.00,  13.00,     \
          15.00,  18.00,  21.00,  23.00,  30.00         /)
  yi = (/  1.00,   0.81,   0.00,  -0.81,  -1.00,  -0.84,     \
          -0.56,   0.04,   0.73,   1.18,   2.0          /)

  npts = 201
  xo   = fspan(0.,35.,npts)

  yo = ftcurvp(xi, yi, 31., xo)
end

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$Revision: 1.7 $ $Date: 1998/11/11 23:32:18 $