/** * The Koch snowflake is a fractal curve and one of the earliest fractals to have been described. * * The Koch snowflake can be built up iteratively, in a sequence of stages. The first stage is an equilateral triangle, * and each successive stage is formed by adding outward bends to each side of the previous stage, making smaller * equilateral triangles. This can be achieved through the following steps for each line: * 1. divide the line segment into three segments of equal length. * 2. draw an equilateral triangle that has the middle segment from step 1 as its base and points outward. * 3. remove the line segment that is the base of the triangle from step 2. * * (description adapted from https://en.wikipedia.org/wiki/Koch_snowflake) * (for a more detailed explanation and an implementation in the Processing language, see * https://natureofcode.com/book/chapter-8-fractals/ #84-the-koch-curve-and-the-arraylist-technique). */ /** Class to handle the vector calculations. */ export class Vector2 { constructor(x, y) { this.x = x this.y = y } /** * Vector addition * * @param vector The vector to be added. * @returns The sum-vector. */ add(vector) { const x = this.x + vector.x const y = this.y + vector.y return new Vector2(x, y) } /** * Vector subtraction * * @param vector The vector to be subtracted. * @returns The difference-vector. */ subtract(vector) { const x = this.x - vector.x const y = this.y - vector.y return new Vector2(x, y) } /** * Vector scalar multiplication * * @param scalar The factor by which to multiply the vector. * @returns The scaled vector. */ multiply(scalar) { const x = this.x * scalar const y = this.y * scalar return new Vector2(x, y) } /** * Vector rotation (see https://en.wikipedia.org/wiki/Rotation_matrix) * * @param angleInDegrees The angle by which to rotate the vector. * @returns The rotated vector. */ rotate(angleInDegrees) { const radians = (angleInDegrees * Math.PI) / 180 const ca = Math.cos(radians) const sa = Math.sin(radians) const x = ca * this.x - sa * this.y const y = sa * this.x + ca * this.y return new Vector2(x, y) } } /** * Go through the number of iterations determined by the argument "steps". * * Be careful with high values (above 5) since the time to calculate increases exponentially. * * @param initialVectors The vectors composing the shape to which the algorithm is applied. * @param steps The number of iterations. * @returns The transformed vectors after the iteration-steps. */ export function iterate(initialVectors, steps) { let vectors = initialVectors for (let i = 0; i < steps; i++) { vectors = iterationStep(vectors) } return vectors } /** * Loops through each pair of adjacent vectors. * * Each line between two adjacent vectors is divided into 4 segments by adding 3 additional vectors in-between the * original two vectors. The vector in the middle is constructed through a 60 degree rotation so it is bent outwards. * * @param vectors The vectors composing the shape to which the algorithm is applied. * @returns The transformed vectors after the iteration-step. */ function iterationStep(vectors) { const newVectors = [] for (let i = 0; i < vectors.length - 1; i++) { const startVector = vectors[i] const endVector = vectors[i + 1] newVectors.push(startVector) const differenceVector = endVector.subtract(startVector).multiply(1 / 3) newVectors.push(startVector.add(differenceVector)) newVectors.push( startVector.add(differenceVector).add(differenceVector.rotate(60)) ) newVectors.push(startVector.add(differenceVector.multiply(2))) } newVectors.push(vectors[vectors.length - 1]) return newVectors }