FastPolynomialRoots.jl
Fast and backward stable computation of roots of polynomials in Julia
Install / Use
/learn @andreasnoack/FastPolynomialRoots.jlREADME
FastPolynomialRoots.jl - Fast and backward stable computation of roots of polynomials
This package is a Julia wrapper of the Fortran programs accompanying Fast and Backward Stable Computation of Roots of Polynomials by Jared L. Aurentz, Thomas Mach, Raf Vandebril and David S. Watkins.
Usage
The package provides the unexported function FastPolynomialRoots.rootsFastPolynomialRoots(p::Vector{<:Union{Float64,Complex{Float64}}})
which computes the roots of the polynomial p[1] + p[2]*x + p[3]*x^2 + ... + p[k]*x^(k-1). The package also overwrites the roots(::Polynomial) methods in the Polynomials package for Float64 and Complex{Float64} elements with the fast versions provided by this package. See the examples below.
Example 1: Speed up roots
julia> using Polynomials, BenchmarkTools, FastPolynomialRoots
julia> @btime roots(p) setup=(p = Polynomial(randn(500)));
223.135 ms (23 allocations: 3.97 MiB)
julia> @btime FastPolynomialRoots.roots(p) setup=(p = Polynomial(randn(500)));
30.786 ms (7 allocations: 26.41 KiB)
Example 2: Roots of a polynomial of degree 10,000
A computation of this size would not be feasible on a desktop with the traditional method but can be handled by FastPolynomialRoots.
julia> using Polynomials, BenchmarkTools, FastPolynomialRoots
julia> n = 10000;
julia> r = @btime FastPolynomialRoots.roots(p) setup=(p = Polynomial(randn(n + 1)));
10.290 s (13 allocations: 508.38 KiB)
julia> sum(isreal, r)
7
julia> 2/π*log(n) + 0.6257358072 + 2/(n*π) # Edelman and Kostlan
6.489284260212659
