A Julia package to construct orthogonal polynomials, their quadrature rules, and use it with polynomial chaos expansions.

Nodes and modes for high order finite element methods

AlgDiff is a Python class implementing all necessary tools for the design, analysis, and discretization of algebraic differentiators. An interface to Matlab is also provided.

Associated Legendre Polynomials and Spherical Harmonics in Julia

A Python module to compute multidimensional arrays of evaluated (orthogonal) functions.

Generate orthogonal polynomials for arbitrary probability density functions

Raku package for functionalities based on Chebyshev polynomials.

quad-precision orthogonal polynomial least squares

Orthogonal polynomials in 3D, based on a tensor product construction of 1D orthogonal polynomials. The 1D polynomials are defined in terms of a three-term recurrence relation derived with Gram-Schmidt on standard monomials.

Jacobi, Gegenbauer, Chebyshev of first, second, third, fourth kind, Legendre, Laguerre, Hermite, shifted Chebyshev and Legendre polynomials

Orthogonal regression polynomial approximation: no SLE, fast, high precision, no dependencies

All my assignments to the course MM5016 at Stockholm University