Tinkering with code and algorithms for fun
Published
Edited
Nov 17, 2018
1 fork
2 stars
gaussianKernel = {
// Adapted from https://github.com/ghewgill/picomath/blob/master/javascript/erf.js
function erf(x) {
// constants
const a1 = 0.254829592;
const a2 = -0.284496736;
const a3 = 1.421413741;
const a4 = -1.453152027;
const a5 = 1.061405429;
const p = 0.3275911;
// A&S formula 7.1.26
const t = 1.0 / (1.0 + p * Math.abs(x));
const y = 1.0 - (((((a5 * t + a4) * t) + a3) * t + a2) * t + a1) * t * Math.exp(-x * x);
return Math.sign(x) * y;
}
function def_int_gaussian(x, mu, sigma) {
return 0.5 * erf((x - mu) / (Math.SQRT2 * sigma));
}
return function gaussian_kernel(kernel_size = 5, sigma = 1, mu = 0, step = 1) {
const end = 0.5 * kernel_size;
const start = -end;
const coeff = [];
let sum = 0;
let x = start;
let last_int = def_int_gaussian(x, mu, sigma);
let acc = 0;
while (x < end) {
x += step;
const new_int = def_int_gaussian(x, mu, sigma)
let c = new_int - last_int;
coeff.push(c);
sum += c;
last_int = new_int;
}
//normalize
sum = 1/sum;
for (let i = 0; i < coeff.length; i++) {
coeff[i] *= sum;
}
return coeff;
}
}
import {chart} with {data, height} from "@mbostock/d3-bar-chart"
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.