# Ngl.ftcurvp

Calculates an interpolatory spline under tension through a sequence of functional values for a periodic function.

## Prototype

iarray = Ngl.ftcurvp(xi, yi, p, xo)

## Arguments

*xi*

An array containing the abscissae for the input function, with
rightmost dimension *npts*. If *xi* is multi-dimensional,
it must have the same dimension sizes as *yi*.

*yi*

An array of any dimensionality, whose rightmost dimension is
*npts*, containing the functional values of the input function.
That is, *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
must not be less than *xi*(*npts*-1) - *xi*(0).

*xo*

A 1D array of length *nxo* containing the abscissae for the
interpolated values.

## Return value

*iarray*

An array of the same dimensionality as *yi*, but with the
rightmost dimension replaced by *nxo*, containing the
interpolated functional values at the points specified by *xo*.

## Description

This function calculates an interpolatory spline under tension through a sequence of functional values for a periodic function. This function is a Python version of the function of the same name in the Fitgrid package of the ngmath library.

The first two arguments are multi-dimensional arrays specifying X/Y coordinates of the input data to be used for interpolation. These arrays can be Python lists or tuples, or NumPy arrays. The third argument specifies the period of function; the period has to be at least as large as the span of the input X coordinates. The final argument is a 1-dimensional array specifying the desired X coordinates at which to interpolate. The interpolated values at the specified coordinates are returned as a multi-dimensional NumPy float array.

## See Also

## Examples

See ngl07p.py.