Accueil / npm / three@0.186.1 / examples / jsm / tsl / math / voronoiNoise.js
voronoiNoise.js
import { Fn, Loop, dot, float, fract, int, min, sin, vec2, vec3, TWO_PI } from 'three/tsl';
/**
* @module VoronoiNoise
* @three_import import { voronoi2d, voronoi3d } from 'three/addons/tsl/math/voronoiNoise.js';
*/
/**
* Generates a pseudo-random vec2 from the given coordinate.
*
* Reference: {@link https://www.shadertoy.com/view/MslGD8}.
*
* @tsl
* @function
* @param {Node<vec2>} p - The input coordinate.
* @return {Node<vec2>} A pseudo-random value in the range `[0, 1]`.
*/
export const hash2d = /*@__PURE__*/ Fn( ( [ p ] ) => {
return fract( sin( vec2( dot( p, vec2( 127.1, 311.7 ) ), dot( p, vec2( 269.5, 183.3 ) ) ) ).mul( 18.5453 ) );
}, { p: 'vec2', return: 'vec2' } );
/**
* Animated 2D Voronoi noise. The feature points orbit inside their cells so the
* resulting pattern morphs over time.
*
* Reference: {@link https://www.shadertoy.com/view/MslGD8}.
*
* @tsl
* @function
* @param {Node<vec2>} p - The input coordinate.
* @param {Node<float>} time - The animation time.
* @return {Node<float>} The squared distance to the closest feature point, roughly in the range `[0, 1]`.
*/
export const voronoi2d = /*@__PURE__*/ Fn( ( [ p, time ] ) => {
const n = p.floor().toConst();
const f = p.fract().toConst();
const minDist = float( 8 ).toVar();
Loop( { start: int( - 1 ), end: int( 1 ), name: 'x', condition: '<=' }, ( { x } ) => {
Loop( { start: int( - 1 ), end: int( 1 ), name: 'y', condition: '<=' }, ( { y } ) => {
const g = vec2( float( x ), float( y ) ).toConst();
const o = hash2d( n.add( g ) ).toConst();
const r = g.sub( f ).add( sin( time.add( o.mul( TWO_PI ) ) ).mul( 0.5 ).add( 0.5 ) );
minDist.assign( min( minDist, dot( r, r ) ) );
} );
} );
return minDist;
}, { p: 'vec2', time: 'float', return: 'float' } );
/**
* Generates a pseudo-random vec3 from the given coordinate.
*
* @tsl
* @function
* @param {Node<vec3>} p - The input coordinate.
* @return {Node<vec3>} A pseudo-random value in the range `[0, 1]`.
*/
export const hash3d = /*@__PURE__*/ Fn( ( [ p ] ) => {
return fract( sin( vec3( dot( p, vec3( 127.1, 311.7, 74.7 ) ), dot( p, vec3( 269.5, 183.3, 246.1 ) ), dot( p, vec3( 113.5, 271.9, 124.6 ) ) ) ).mul( 18.5453 ) );
}, { p: 'vec3', return: 'vec3' } );
/**
* Animated 3D Voronoi noise. Like {@link voronoi2d} but with a volumetric input
* coordinate so the pattern can be applied to arbitrary surfaces without
* projection artifacts. Evaluates 27 cells instead of 9 and is therefore
* considerably more expensive than the 2D version.
*
* @tsl
* @function
* @param {Node<vec3>} p - The input coordinate.
* @param {Node<float>} time - The animation time.
* @return {Node<float>} The squared distance to the closest feature point, roughly in the range `[0, 1]`.
*/
export const voronoi3d = /*@__PURE__*/ Fn( ( [ p, time ] ) => {
const n = p.floor().toConst();
const f = p.fract().toConst();
const minDist = float( 8 ).toVar();
Loop( { start: int( - 1 ), end: int( 1 ), name: 'x', condition: '<=' }, ( { x } ) => {
Loop( { start: int( - 1 ), end: int( 1 ), name: 'y', condition: '<=' }, ( { y } ) => {
Loop( { start: int( - 1 ), end: int( 1 ), name: 'z', condition: '<=' }, ( { z } ) => {
const g = vec3( float( x ), float( y ), float( z ) ).toConst();
const o = hash3d( n.add( g ) ).toConst();
const r = g.sub( f ).add( sin( time.add( o.mul( TWO_PI ) ) ).mul( 0.5 ).add( 0.5 ) );
minDist.assign( min( minDist, dot( r, r ) ) );
} );
} );
} );
return minDist;
}, { p: 'vec3', time: 'float', return: 'float' } );