From 993363533aae3101f204d48866a9d28f2305848e Mon Sep 17 00:00:00 2001 From: "Jeffrey M. Hokanson" Date: Mon, 23 Nov 2020 00:15:16 -0500 Subject: [PATCH] Longer description of library purpose --- README.md | 38 ++++++++++++++++++++++++++++++++++++++ 1 file changed, 38 insertions(+) diff --git a/README.md b/README.md index c9f6deb..2ddb744 100644 --- a/README.md +++ b/README.md @@ -5,6 +5,44 @@ [![Coverage Status](https://coveralls.io/repos/github/jeffrey-hokanson/polyrat/badge.svg?branch=master)](https://coveralls.io/github/jeffrey-hokanson/polyrat?branch=master) [![Documentation Status](https://readthedocs.org/projects/polyrat/badge/?version=latest)](https://polyrat.readthedocs.io/en/latest/?badge=latest) +PolyRat is a library for polynomial and rational approximation. +Formally we can think of [polynomials](https://en.wikipedia.org/wiki/Polynomial#Polynomial_functions) as a sum of powers of : + + + +A [rational function](https://en.wikipedia.org/wiki/Rational_function) is a ratio of two polynomial functions + + + +The goal of this library is to construct polynomial and rational approximations +given a collection of point data consisting of pairs of +inputs +and outputs . +The goal of this library is to provide algorithms for constructing these approximations +in a variety of norms, namely [two-norm and sup-norm](https://en.wikipedia.org/wiki/Norm_(mathematics)#p-norm). + +The polynomial approximation problem is relatively straightfoward +as it is a convex problem for any p-norm with p≥1. +However, there is still a need to be careful +in the construction of the polynomial basis for high-degree polynomials +to avoid ill-conditioning. +Here we provide access to a number of polynomial bases: + +* tensor-product polynomials based on Numpy (e.g., Monomial, Legendre, etc.); +* [Vandermonde with Arnoldi](https://arxiv.org/abs/1911.09988) polynomial basis; +* [barycentric Lagrange](https://doi.org/10.1137/S0036144502417715) polynomial bases. + +The rational approximation problem is still an open research problem. +This library provides a variety of algorithms for constructing rational approximations +including: + +* [Adaptive Anderson Antoulas](https://doi.org/10.1137/16M1106122) +* [Sanathanan Koerner iteration](https://doi.org/10.1109/TAC.1963.1105517) +* [Stabilized Sanathanan Koerner iteration](https://arxiv.org/abs/2009.10803) +* [Vector Fitting](https://doi.org/10.1109/61.772353) + + + ## Installation