This does about the same as chebappxg for unform grids, though
no grid map function is constructed, as a fixed such function is used.
A Chebyshev-interpolation ch is made for val with
chebappx. Upon evaluation the uniform grid in each dimension
is mapped differentiably to the Chebyshev-knots so that ch is
evaluated in \(sin(\frac{\pi }{sin(0.5*pi*x*(1-n)/n)}\eqn{
x(1-n)}{2n})\) where n is the number of knots
in the dimension, possibly after x has been remapped from the
hypercube interval to [-1,1].
Thus, the interpolation is not a polynomial.
For ucappx the function values are provided, the number of grid
points in each dimension is to be found in dim(val). For
ucappxf the function to be interpolated is fun, and the number
of grid points is passed in dims.
As the example shows, this approximation is better than the Chebyshev
approximation for some functions.