BasesAndSamples.jl
BasesAndSamples.jl provides functions for generating some polynomial bases and point sets.
BasesAndSamples.basis_chebyshev — MethodGenerate a basis of chebyshev polynomials up to degree d (inclusive)
BasesAndSamples.basis_gegenbauer — MethodBasis for the Gegenbauer polynomials in dimension n up to degree d. This is the Gegenbauer polynomial with parameter lambda = n/2-1, or the Jacobi polynomial with alpha = beta = (n-3)/2. Normalized to evaluate to 1 at 1. Taken from arxiv/2001.00256, ancillary files, SemidefiniteProgramming.jl
BasesAndSamples.basis_jacobi — FunctionGenerate the Jacobi polynomials with parameters alpha and beta up to degree d (inclusive)
BasesAndSamples.basis_laguerre — MethodGenerate the Laguerre polynomials with parameter alpha up to degree d (inclusive)
BasesAndSamples.basis_monomial — MethodGenerate the monomial basis in variables x... up to degree d (inclusive)
BasesAndSamples.sample_points_chebyshev — FunctionGenerate the d+1 chebyshev points in [a,b]
BasesAndSamples.sample_points_chebyshev_mod — FunctionGenerate the d+1 modified chebyshev points in [a,b]
BasesAndSamples.sample_points_padua — MethodGenerate the Padua points for degree d
BasesAndSamples.sample_points_rescaled_laguerre — MethodGenerate 'rescaled laguerre' points, as in SDPB
BasesAndSamples.sample_points_simplex — MethodGenerate the sample points in the unit simplex with denominator d