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add KochSnowflake.js
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186
Recursive/KochSnowflake.js
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186
Recursive/KochSnowflake.js
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/**
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* The Koch snowflake is a fractal curve and one of the earliest fractals to have been described.
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* The Koch snowflake can be built up iteratively, in a sequence of stages. The first stage is an
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* equilateral triangle, and each successive stage is formed by adding outward bends to each side of
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* the previous stage, making smaller equilateral triangles. This can be achieved through the
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* following steps for each line: 1. divide the line segment into three segments of equal length. 2.
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* draw an equilateral triangle that has the middle segment from step 1 as its base and points
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* outward. 3. remove the line segment that is the base of the triangle from step 2. (description
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* adapted from https://en.wikipedia.org/wiki/Koch_snowflake ) (for a more detailed explanation and
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* an implementation in the Processing language, see
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* https://natureofcode.com/book/chapter-8-fractals/ #84-the-koch-curve-and-the-arraylist-technique
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* ).
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*/
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/*
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Doctests
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Test iterate-method
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> iterate([new Vector2(0, 0), new Vector2(1, 0)], 1)[0];
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{"x": 0, "y": 0}
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> iterate([new Vector2(0, 0), new Vector2(1, 0)], 1)[1];
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{"x": 1/3, "y": 0}
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> iterate([new Vector2(0, 0), new Vector2(1, 0)], 1)[2];
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{"x": 1/2, "y": Math.sin(Math.PI / 3) / 3}
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> iterate([new Vector2(0, 0), new Vector2(1, 0)], 1)[3];
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{"x": 2/3, "y": 0}
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> iterate([new Vector2(0, 0), new Vector2(1, 0)], 1)[4];
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{"x": 1, "y": 0}
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*/
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/** Class to handle the vector calculations. */
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class Vector2 {
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constructor (x, y) {
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this.x = x
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this.y = y
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}
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/**
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* Vector addition
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*
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* @param vector The vector to be added.
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* @returns The sum-vector.
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*/
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add (vector) {
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const x = this.x + vector.x
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const y = this.y + vector.y
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return new Vector2(x, y)
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}
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/**
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* Vector subtraction
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*
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* @param vector The vector to be subtracted.
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* @returns The difference-vector.
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*/
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subtract (vector) {
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const x = this.x - vector.x
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const y = this.y - vector.y
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return new Vector2(x, y)
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}
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/**
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* Vector scalar multiplication
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*
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* @param scalar The factor by which to multiply the vector.
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* @returns The scaled vector.
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*/
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multiply (scalar) {
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const x = this.x * scalar
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const y = this.y * scalar
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return new Vector2(x, y)
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}
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/**
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* Vector rotation (see https://en.wikipedia.org/wiki/Rotation_matrix)
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*
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* @param angleInDegrees The angle by which to rotate the vector.
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* @returns The rotated vector.
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*/
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rotate (angleInDegrees) {
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const radians = angleInDegrees * Math.PI / 180
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const ca = Math.cos(radians)
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const sa = Math.sin(radians)
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const x = ca * this.x - sa * this.y
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const y = sa * this.x + ca * this.y
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return new Vector2(x, y)
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}
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}
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/**
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* Method to render the Koch snowflake to a canvas.
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*
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* @param canvasWidth The width of the canvas.
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* @param steps The number of iterations.
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* @returns The canvas of the rendered Koch snowflake.
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*/
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function getKochSnowflake (canvasWidth = 600, steps = 5) {
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if (canvasWidth <= 0) {
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throw new Error('canvasWidth should be greater than zero')
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}
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const offsetX = canvasWidth / 10.0
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const offsetY = canvasWidth / 3.7
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const vector1 = new Vector2(offsetX, offsetY)
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const vector2 =
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new Vector2(canvasWidth / 2, Math.sin(Math.PI / 3) * canvasWidth * 0.8 + offsetY)
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const vector3 = new Vector2(canvasWidth - offsetX, offsetY)
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const initialVectors = []
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initialVectors.push(vector1)
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initialVectors.push(vector2)
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initialVectors.push(vector3)
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initialVectors.push(vector1)
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const vectors = iterate(initialVectors, steps)
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return drawToCanvas(vectors, canvasWidth, canvasWidth)
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}
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/**
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* Utility-method to render the Koch snowflake to a canvas.
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*
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* @param vectors The vectors defining the edges to be rendered.
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* @param canvasWidth The width of the canvas.
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* @param canvasHeight The height of the canvas.
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* @returns The canvas of the rendered edges.
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*/
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function drawToCanvas (vectors, canvasWidth, canvasHeight) {
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const canvas = document.createElement('canvas')
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canvas.width = canvasWidth
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canvas.height = canvasHeight
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// Draw the edges
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const ctx = canvas.getContext('2d')
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ctx.beginPath()
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ctx.moveTo(vectors[0].x, vectors[0].y)
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for (let i = 1; i < vectors.length; i++) {
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ctx.lineTo(vectors[i].x, vectors[i].y)
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}
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ctx.stroke()
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return canvas
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}
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/**
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* Go through the number of iterations determined by the argument "steps". Be careful with high
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* values (above 5) since the time to calculate increases exponentially.
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*
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* @param initialVectors The vectors composing the shape to which the algorithm is applied.
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* @param steps The number of iterations.
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* @returns The transformed vectors after the iteration-steps.
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*/
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function iterate (initialVectors, steps) {
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let vectors = initialVectors
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for (let i = 0; i < steps; i++) {
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vectors = iterationStep(vectors)
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}
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return vectors
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}
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/**
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* Loops through each pair of adjacent vectors. Each line between two adjacent vectors is divided
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* into 4 segments by adding 3 additional vectors in-between the original two vectors. The vector
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* in the middle is constructed through a 60 degree rotation so it is bent outwards.
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*
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* @param vectors The vectors composing the shape to which the algorithm is applied.
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* @returns The transformed vectors after the iteration-step.
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*/
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function iterationStep (vectors) {
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const newVectors = []
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for (let i = 0; i < vectors.length - 1; i++) {
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const startVector = vectors[i]
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const endVector = vectors[i + 1]
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newVectors.push(startVector)
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const differenceVector = endVector.subtract(startVector).multiply(1 / 3)
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newVectors.push(startVector.add(differenceVector))
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newVectors.push(startVector.add(differenceVector).add(differenceVector.rotate(60)))
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newVectors.push(startVector.add(differenceVector.multiply(2)))
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}
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newVectors.push(vectors[vectors.length - 1])
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return newVectors
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}
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// plot the results if the script is executed in a browser with a window-object
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if (typeof window !== 'undefined') {
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const canvas = getKochSnowflake()
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document.body.append(canvas)
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}
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