layer-oriented-deep-learning-network-js/lib/math/random.js

A feed-forward neural network with injectable layers, activation functions, and optimizers.

"use strict";

Object.defineProperty(exports, "__esModule", {
    value: true
});
exports.gaussRandom = gaussRandom;
exports.getRandomInt = getRandomInt;
exports.getRandomIntWithZeroMin = getRandomIntWithZeroMin;
/**
 * Returns a random float who's distribution is gaussian.
 *
 * This uses the "Box-Muller transform". More info at:
 * http://stackoverflow.com/questions/25582882/javascript-math-random-normal-distribution-gaussian-bell-curve
 *
 * @returns {number}
 */
function gaussRandom() {
    var u = 1 - Math.random(); // Subtraction to flip [0, 1) to (0, 1].
    var v = 1 - Math.random();
    return Math.sqrt(-2.0 * Math.log(u)) * Math.cos(2.0 * Math.PI * v);
}

function getRandomInt(min, max) {
    return Math.floor(Math.random() * (max - min) + min);
}

function getRandomIntWithZeroMin(max) {
    return Math.floor(Math.random() * max);
}