naturalneighbor 0.1.1

Fast, discrete natural neighbor interpolation in 3D.

Natural neighbor interpolation is a method for interpolating scattered data (i.e. you know the values of a function at scattered locations). It is often superior to linear barycentric interpolation, which is a commonly used method of interpolation provided by Scipy’s griddata function.

There are several implementations of 2D natural neighbor interpolation in Python. We needed a fast 3D implementation that could run without a GPU, so we wrote an implementation of Discrete Sibson Interpolation (a version of natural neighbor interpolation that is fast but introduces slight errors as compared to “geometric” natural neighbor interpolation).

See https://doi.org/10.1109/TVCG.2006.27 for details.

Future Work

• Change arguments so that you don’t need to pass in a full grid (i.e. change from the griddata API); this is good because it reduces memory footprint and, unlike other griddata methods, I think we really need our interpolated points to lie on a grid.

• Add a bunch of tests

• Check that the input dimensions are correct

• Add option to avoid extrapolation

• Support floats and doubles

• Support 2D

• Support higher dimensions (?)

• Add documentation with discussion on limitations of discrete sibson’s method