Awesome
BasicInterpolators.jl
Interpolation methods with a simple interface
contributions welcome
Documentation | Status |
---|---|
Use Julia's package manager to install
julia> ]add BasicInterpolators
Interpolation Methods
One Dimension
- linear
- piecewise cubic
- cubic spline (natural or clamped)
- Chebyshev
- arbitrary order polynomials (Neville's method)
- polynomial coefficients (efficient Vandermonde solver)
- end-point cubic Hermite
Two Dimensions, Regular Grid
- linear
- piecewise cubic
- Chebyshev
N-Dimensions, Scattered Points
- radial basis functions (any choice of function)
- Shepard
Basic Usage
See the tutorial for more complete examples.
using BasicInterpolators, ForwardDiff
#some data to interpolate
x = [-1, 0.5, 2, 3]
y = [1, 3, -0.5, 0]
#a linear interpolation struct
p = LinearInterpolator(x, y)
#interpolate at one point
p(2.5)
#interpolate at lots of points
p.(LinRange(-1, 3, 100))
#compute the derivative dy/dx
ForwardDiff.derivative(p, 1.0)
#make an interpolator that doesn't check boundaries (allows extrapolation)
p = LinearInterpolator(x, y, NoBoundaries())
Other packages
Some notable packages with other/advanced methods:
For a longer list, look here.