Builds Radial Basis Functions for input and output values of arbitrary dimensionality using standard or custom distance functions.
$ npm install rbfvar RBF = require('rbf');
var points = [
[0, 0],
[0, 100]
];
// values could be vectors of any dimensionality.
// The computed interpolant function will return values or vectors accordingly.
var values = [
0.0,
1.0
]
// RBF accepts a distance function as a third parameter :
// either one of the following strings or a custom distance function (defaults to 'linear').
//
// - linear: r
// - cubic: r**3
// - quintic: r**5
// - thin-plate: r**2 * log(r)
// - gaussian: exp(-(r/epsilon) ** 2)
// - multiquadric: sqrt((r/epsilon) ** 2 + 1)
// - inverse-multiquadric: 1 / sqrt((r/epsilon) ** 2 + 1)
//
// epsilon can be provided as a 4th parameter. Defaults to the average
// euclidean distance between points.
//
var rbf = RBF(points, values /*, distanceFunction, epsilon */);
console.log(rbf([0, 50])); // => 0.5Partial derivative of a gaussian, original and interpolated with 25 random samples (linear distance function).
Lena, original and interpolated with 4000 random samples (about 6% of the original pixels, linear distance function).
