Fast multidimensional Chebyshev interpolation in Julia
Author stevengj
10 Stars
Updated Last
1 Year Ago
Started In
August 2020


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Fast multidimensional Chebyshev interpolation on a hypercube (Cartesian-product) domain, using a separable (tensor-product) grid of Chebyshev interpolation points.

For domain upper and lower bounds lb and ub, and a given order tuple, you would create an interpolator for a function f via:

using FastChebInterp
x = chebpoints(order, lb, ub) # an array of StaticVector
c = chebfit(f.(x), lb, ub)

and then evaluate the interpolant for a point y (a vector) via c(y).

We also provide a function chebgradient(c,y) that returns a tuple (c(y), ∇c(y)) of the interpolant and its gradient at a point y.

The FastChebInterp package also supports complex and vector-valued functions f. In this case, c(y) returns a vector of interpolants, and one can use chebjacobian(c,y) to compute the tuple (c(y), J(y)) of the interpolant and its Jacobian matrix at y.

This package is an experimental replacement for some of the functionality in ChebyshevApprox.jl in order to get more performance. The ApproxFun.jl package also performs Chebyshev interpolation and many other tasks.