Awesome
PolynomialBases
<!-- [![GitHub commits since tagged version](https://img.shields.io/github/commits-since/ranocha/PolynomialBases.jl/v0.4.8.svg?style=social&logo=github)](https://github.com/ranocha/PolynomialBases.jl) [![Build status](https://ci.appveyor.com/api/projects/status/i1saoodeqrepiodl?svg=true)](https://ci.appveyor.com/project/ranocha/PolynomialBases-jl) [![PkgEval](https://juliaci.github.io/NanosoldierReports/pkgeval_badges/P/PolynomialBases.svg)](https://juliaci.github.io/NanosoldierReports/pkgeval_badges/report.html) -->A library of functions for polynomial bases used in spectral element methods using the quadrature rules from
FastGaussQuadrature.jl for Float64
and root finding
via the Newton algorithm for other scalar types (such as BigFloat
). The algorithms for interpolation and
differentiation use barycentric weights as described in the book "Implementing Spectral Methods for PDEs"
by David Kopriva. If SymPy.jl/SymEngine.jl
is loaded, symbolic computations using SymPy.Sym
/SymEngine.Basic
are supported.
A brief tutorial is given as notebook.