Fast, continuous interpolation of discrete datasets in Julia
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Updated
Sep 25, 2024 - Julia
Fast, continuous interpolation of discrete datasets in Julia
Sparse Grid Discretization with the Discontinuous Galerkin Method for solving PDEs
FEMBasis contains interpolation routines for finite element function spaces. Given ansatz and coordinates of domain, shape functions are calculated symbolically in a very general way to get efficient code. Shape functions can also be given directly and in that case partial derivatives are calculated automatically.
DIVAnd performs an n-dimensional variational analysis of arbitrarily located observations
Julia library for the string interpolation of HTML and SVG
A collection of B-spline tools in Julia
Tools for working with Fourier space.
Scalar-valued local function approximation across a real-valued vector space
Kriging estimators for the GeoStats.jl framework
Monotonic cubic interpolation in Julia
Geostatistical estimation solvers for the GeoStats.jl framework
Basic (+chebyshev) interpolation recipes in Julia
Multivariate Normal Hermite-Birkhoff Interpolating Splines in Julia
A framework for multivariate functions together with constructors for schumaker splines, OLS, Chebyshev, MARS splines for approximation.
Pure Julia implementation of 1D & 2D cubic Hermite spline interpolation.
Natural neighbour interpolation methods for scattered data interpolation and derivative generation of planar point sets.
Multivariate (generalized) scattered data interpolation with symmetric (conditionally) positive definite kernel functions in arbitrary dimension
Centripetal Catmull-Rom curves for interpoint traversal
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