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.

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

Associated Legendre Polynomials and Spherical Harmonics in Julia

Generate orthogonal polynomials for arbitrary probability density functions

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.

quad-precision orthogonal polynomial least squares

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

Raku package for functionalities based on Chebyshev polynomials.

All my assignments to the course MM5016 at Stockholm University