color-k-means.js

function getRGBCluster(k = 3, rRange = 255, gRange = 255, bRange = 255) {
	function equal(means, newMeans) {
		return means.every((mean, index) => 
			mean[0] === newMeans[index][0]
			&& mean[1] === newMeans[index][1]
			&& mean[2] === newMeans[index][2]
		)
	}

	function assignment(data, means) {
		const clusters = Array(means.length).fill().map(() => [])

		// 对每个点进行分类
		data.forEach(point => {
	        let minIndex = 0;

	        means.reduce((prev, mean, index) => {
	        	const distance = euclideanDistance(point, mean);

	        	if (distance < prev) {
	        		minIndex = index;
	        		return distance
	        	}

	        	return prev;
	        }, Number.MAX_VALUE)

	        clusters[minIndex].push(point);
		});

		const newMeans = clusters.map(cluster => average(cluster))

		return newMeans;
	}

	// 获取所有的颜色，调整步长可以减少样本集合的数量
	function getColors(rRange, gRange, bRange) {
		const colors = [];

		let [r, g, b] = [];

		for (r = 0; r <= rRange; r += 1) {
			for (g = 0; g <= gRange; g += 1) {
				for (b = 0; b <= bRange; b += 1) {
					colors.push([r, g, b]);
				}
			}
		}

		return colors;
	}

	function getMeans(k, originData) {
		const means = [];
		const data = [].concat(originData);

		while(k--) {
			const index = Math.floor(Math.random() * data.length);
			means.push(data[index]);
			data.splice(index, 1);
		}

		return means;
	}

	// 计算欧几里得距离
	function euclideanDistance(point1, point2) {
		return Math.sqrt(
			Math.pow(point1[0] - point2[0], 2)
			+ Math.pow(point1[1] - point2[1], 2)
			+ Math.pow(point1[2] - point2[2], 2)
		)
	}

	// 计算平均点
	function average(colors) {
		return colors
			.reduce(
				(sum, color) => [sum[0] + color[0], sum[1] + color[1], sum[2] + color[2]],
				[0, 0, 0]
			)
			.map(sum => sum / colors.length)
	}

	const colors = getColors(rRange, gRange, bRange);

	let means = getMeans(k, colors);
	console.log(`means:`, means)

	let newMeans = assignment(colors, means);
	console.log(`newMeans:`, newMeans)

	let count = 0;
	while(!equal(means, newMeans)) {
		means = newMeans;
		newMeans = assignment(colors, means);
		count += 1;
	}

	return newMeans;
}

console.log(getRGBCluster(3, 100, 100, 100));