Thriving Thriving Julia JL
↑ 67 ?
KernelInterpolation.jl JoshuaLampert/KernelInterpolation.jl

Multivariate (generalized) scattered data interpolation with symmetric (conditionally) positive definite kernel functions in arbitrary dimension

https://joshualampert.github.io/KernelInterpolation.jl/ ↗
HEALTH ? 96 / Healthy
// solo builder// hidden gem interpolationkernel-methodsradial-basis-functionjuliacollocation-methodnumerical-simulation-frameworkmeshfreesimulation ?
10-2023 · today · JoshuaLampert
★20 Share View on GitHub ↗

// readme

KernelInterpolation.jl

KernelInterpolation.jl is a Julia package that implements methods for multivariate interpolation in arbitrary dimension based on symmetric (conditionally) positive-definite kernels with a focus on radial basis functions. It can be used for classical interpolation of scattered data, as well as for generalized (Hermite-Birkhoff) interpolation by using a meshfree collocation approach. This can be used to solve partial differential equations both stationary ones and time-dependent ones by using some time integration method from OrdinaryDiffEq.jl. Additionally, local radial basis function finite differences (RBF-FD) are supported for sparse PDE discretization.

Installation

If you have not yet installed Julia, then you first need to download Julia. Please follow the instructions for your operating system. KernelInterpolation.jl works with Julia v1.10 and newer. KernelInterpolation.jl is a registered Julia package. Therefore, you can install it by executing the following commands from the Julia REPL…