chebyshev

🚀 Julia package for orthogonal polynomial transforms 🏂

High performance computational platform in Python for the spectral Galerkin method

Elegant Butterworth and Chebyshev filter implemented in C, with float/double precision support. Works well on many platforms. You can also use this package in C++ and bridge to many other languages for good performance.

A web app that generates code for efficiently approximating mathematical functions of one variable.

🚅 Fast orthogonal polynomial transforms 🏄

Spectral Methods in Python

An IIR filter class implementation in Python

Basic (+chebyshev) interpolation recipes in Julia

Building blocks of spectral methods for Julia.

Distance/Similarity functions for Bag of Words, Strings, Vectors and more.

Propagators for Quantum Dynamics and Optimal Control

The tools for proper interactions between ApproxFun.jl and DifferentialEquations.jl for pseudospectiral partial differential equation discretizations in scientific machine learning (SciML)

MFM community development code

Python functions for orthogonal polynomials and (real, 2D, orthonormal) spherical harmonics

A C++ polynomials and related algorithms.

Battery Optimal Layer Design (BOLD) Toolbox for optimising layer configuration of pouch cells

Einstein.jl is a high-performance suite designed to compute arbitrary-precision solutions of PDEs in general relativity.

Experimental Krylov subspace solvers in Fortran/OpenMP focused on numerical stability, matrix-free methods and performance analysis.

The last few solves you'll ever pay for: certified accelerator + identification layer over any black-box parametric solver, built on resona's effective-rank dial.

Machine learning functions written in goLang: