Calculates an interpolatory spline under tension through a sequence of functional values for a periodic function.
iarray = Ngl.ftcurvp(xi, yi, p, xo)
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.
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.
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.