rot-js/lib/noise/simplex.js

A roguelike toolkit in JavaScript

import Noise from "./noise.js";
import RNG from "../rng.js";
import { mod } from "../util.js";
const F2 = 0.5 * (Math.sqrt(3) - 1);
const G2 = (3 - Math.sqrt(3)) / 6;
/**
 * A simple 2d implementation of simplex noise by Ondrej Zara
 *
 * Based on a speed-improved simplex noise algorithm for 2D, 3D and 4D in Java.
 * Which is based on example code by Stefan Gustavson (stegu@itn.liu.se).
 * With Optimisations by Peter Eastman (peastman@drizzle.stanford.edu).
 * Better rank ordering method by Stefan Gustavson in 2012.
 */
export default class Simplex extends Noise {
    /**
     * @param gradients Random gradients
     */
    constructor(gradients = 256) {
        super();
        this._gradients = [
            [0, -1],
            [1, -1],
            [1, 0],
            [1, 1],
            [0, 1],
            [-1, 1],
            [-1, 0],
            [-1, -1]
        ];
        let permutations = [];
        for (let i = 0; i < gradients; i++) {
            permutations.push(i);
        }
        permutations = RNG.shuffle(permutations);
        this._perms = [];
        this._indexes = [];
        for (let i = 0; i < 2 * gradients; i++) {
            this._perms.push(permutations[i % gradients]);
            this._indexes.push(this._perms[i] % this._gradients.length);
        }
    }
    get(xin, yin) {
        let perms = this._perms;
        let indexes = this._indexes;
        let count = perms.length / 2;
        let n0 = 0, n1 = 0, n2 = 0, gi; // Noise contributions from the three corners
        // Skew the input space to determine which simplex cell we're in
        let s = (xin + yin) * F2; // Hairy factor for 2D
        let i = Math.floor(xin + s);
        let j = Math.floor(yin + s);
        let t = (i + j) * G2;
        let X0 = i - t; // Unskew the cell origin back to (x,y) space
        let Y0 = j - t;
        let x0 = xin - X0; // The x,y distances from the cell origin
        let y0 = yin - Y0;
        // For the 2D case, the simplex shape is an equilateral triangle.
        // Determine which simplex we are in.
        let i1, j1; // Offsets for second (middle) corner of simplex in (i,j) coords
        if (x0 > y0) {
            i1 = 1;
            j1 = 0;
        }
        else { // lower triangle, XY order: (0,0)->(1,0)->(1,1)
            i1 = 0;
            j1 = 1;
        } // upper triangle, YX order: (0,0)->(0,1)->(1,1)
        // A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and
        // a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), where
        // c = (3-sqrt(3))/6
        let x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) unskewed coords
        let y1 = y0 - j1 + G2;
        let x2 = x0 - 1 + 2 * G2; // Offsets for last corner in (x,y) unskewed coords
        let y2 = y0 - 1 + 2 * G2;
        // Work out the hashed gradient indices of the three simplex corners
        let ii = mod(i, count);
        let jj = mod(j, count);
        // Calculate the contribution from the three corners
        let t0 = 0.5 - x0 * x0 - y0 * y0;
        if (t0 >= 0) {
            t0 *= t0;
            gi = indexes[ii + perms[jj]];
            let grad = this._gradients[gi];
            n0 = t0 * t0 * (grad[0] * x0 + grad[1] * y0);
        }
        let t1 = 0.5 - x1 * x1 - y1 * y1;
        if (t1 >= 0) {
            t1 *= t1;
            gi = indexes[ii + i1 + perms[jj + j1]];
            let grad = this._gradients[gi];
            n1 = t1 * t1 * (grad[0] * x1 + grad[1] * y1);
        }
        let t2 = 0.5 - x2 * x2 - y2 * y2;
        if (t2 >= 0) {
            t2 *= t2;
            gi = indexes[ii + 1 + perms[jj + 1]];
            let grad = this._gradients[gi];
            n2 = t2 * t2 * (grad[0] * x2 + grad[1] * y2);
        }
        // Add contributions from each corner to get the final noise value.
        // The result is scaled to return values in the interval [-1,1].
        return 70 * (n0 + n1 + n2);
    }
}