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| #!/usr/bin/env python | |
| # Output looks like this: | |
| # | |
| # $ python ./kmeans.py | |
| # Centroids: [[14, 17], [17, 7], [3, 15]] | |
| # Done: [[17.5, 16.5], [16.5, 4.166666666666667], [1.8, 1.6]] | |
| # 0: [[15, 14], [18, 14], [20, 20], [17, 18]] | |
| # 1: [[12, 10], [20, 0], [19, 2], [18, 1], [11, 9], [19, 3]] | |
| # 2: [[0, 1], [1, 1], [2, 2], [3, 3], [3, 1]] | |
| import math | |
| from random import randint | |
| K = 3 | |
| data = [[0,1], [1,1], [2,2], [3,3], [15,14], [12,10], [18,14], [20,0], [19,2], | |
| [18,1], [11,9], [3,1], [19,3], [20,20], [17,18]] | |
| def distance(p1, p2): | |
| """euclidean distance""" | |
| dims = len(p1) | |
| d = math.sqrt(sum([(p1[d]-p2[d])**2 for d in range(dims)])) | |
| return abs(d) | |
| # initialize centroids | |
| min_x = min([x for x,y in data]) | |
| min_y = min([y for x,y in data]) | |
| max_x = max([x for x,y in data]) | |
| max_y = max([y for x,y in data]) | |
| centroids = [[randint(min_x, max_x), randint(min_y, max_y)] for i in range(K)] | |
| print(f"Centroids: {centroids}") | |
| def cluster_loop(centroids): | |
| # distance from each point to each centroid | |
| distances = [[] for i in range(K)] | |
| for idx, c in enumerate(centroids): | |
| for point in data: | |
| d = distance(point, c) | |
| distances[idx].append(d) | |
| # closest centroid to each point | |
| nearest = [ds.index(min(ds)) for ds in zip(*distances)] | |
| clusters = [[] for i in range(K)] | |
| for n,p in zip(nearest,data): | |
| clusters[n].append(p) | |
| # create new centroids | |
| new_centroids = [] | |
| for idx,c in enumerate(clusters): | |
| if not c: | |
| new_centroids.append(centroids[idx]) | |
| else: | |
| avg_x = sum([x for x,y in c]) / len(c) | |
| avg_y = sum([y for x,y in c]) / len(c) | |
| new_centroids.append([avg_x, avg_y]) | |
| return new_centroids, clusters | |
| done = False | |
| while not done: | |
| new_centroids, clusters = cluster_loop(centroids) | |
| done = centroids == new_centroids | |
| centroids = new_centroids | |
| print(f"Done: {centroids}") | |
| for idx,cluster in enumerate(clusters): | |
| print(f"{idx}: {cluster}") |
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