Splats a sparse set of points into an ndarray using a Dirichlet kernel. If you want some alternative kernel to filter them after the fact, you can apply a convolution to the resulting array as a post process.
var ndarray = require('ndarray')
var splat = require('splat-points')
var zeros = require('zeros')
var show = require('ndarray-show')
var points = ndarray([
0, 0,
80, 50,
0.3, 76,
100, 22.3
], [4,2], [2,1])
var grid = splat(zeros([128, 128]), points)
show(grid)
require('splat-points')(out, points[, weights, radius])Splats a sparse set of points onto an array using a Dirichlet kernel.
out is the array which is splatted ontopoints is an n-by-d dimensional ndarray of pointsweights is an array of weights (either an ndarray or a flat)radius is the radius of the points to splatReturns out
(c) 2015 Mikola Lysenko. MIT License