K-均值的质心

Question

import math, random, os, operator, matplotlib, matplotlib.pyplot

from string import split


def EuDist(vecA, vecB):
    return math.sqrt(sum(map(lambda x: x * x, [i - j for i, j in zip(vecA, vecB)])))

filename = "points.txt"
FILE = open(filename, "w")
for i in range(33):
    line = str(random.uniform(1, 2) + random.uniform(-1, 1)) + "\t" + str(random.uniform(4, 5) + random.uniform(-1, 1)) + "\n"
    FILE.write(line)
for i in range(33):
line = str(random.uniform(4, 6) + random.uniform(-1, 1)) + "\t" + str(random.uniform(4, 6) + random.uniform(-1, 1)) + "\n"
    FILE.write(line)
for i in range(34):
    line = str(random.uniform(2, 3) + random.uniform(-1, 1)) + "\t" + str(random.uniform(2, 3) + random.uniform(-1, 1)) + "\n"
    FILE.write(line)
FILE.close()

dataFile = open("points.txt")
dataset = []
for line in dataFile:
    lineSplit = split(line[: -2], "\t")
    dataset.append([float(value) for value in lineSplit])

maxIters = input("Enter the maximum number of iterations: ")
center = input("Enter a number of clusters: ")

centoids = random.sample(dataset, center)
m = len(dataset)
cluster = [[] for i in range(len(centoids))]
for i in range(maxIters):
    cluster = [[] for v in range(len(centoids))]
    for j in range(m):
    minK = 0
    minDis = 100
    for k in range(len(centoids)):
        if operator.le(EuDist(dataset[j], centoids[k]), minDis):
            minDis = EuDist(dataset[j], centoids[k])
            minK = k
    cluster[minK].append(j)
for t in range(len(centoids)):
    x0 = sum([dataset[x][0] for x in cluster[t]])
    y0 = sum([dataset[x][1] for x in cluster[t]])
    centoids[k] = [x0 / len(cluster[t]), y0 / len(cluster[t])]

matplotlib.pyplot.plot(hold = False)
colorarr=["b", "r", "y", "g", "p"]
for k in range(len(cluster)):
    clusterPoint = [dataset[x] for x in cluster[k]]
    x0 = [x[0] for x in clusterPoint]
    y0 = [x[1] for x in clusterPoint]
    center = [(x0, y0) for x in clusterPoint]
    matplotlib.pyplot.show(centoids)
    matplotlib.pyplot.hold(True)
    matplotlib.pyplot.scatter(x0, y0, center, c = colorarr[k])
picname = "picture_number_" + str(i + 1) + ".png"
matplotlib.pyplot.savefig(picname)

代码工作正常，但我有个问题。我不知道如何在这张图上显示星系团的质心。我知道我需要使用变量centoids，但我不知道具体如何使用。请给我一个提示。

Answer 1

我不能百分之百确定你想要什么，但我认为你只是想在这些星系团的散点图上夸大你的星系团的中心线，都是一个数字(每个星系团都有自己的颜色)。

这样的东西可以起作用：

from matplotlib import pyplot as plt
import numpy as np

data = {
    'x': np.random.rand(4, 100),
    'y': np.random.rand(4, 100),
}
centoids = {
    'x': np.random.rand(4),
    'y': np.random.rand(4),
}
colorarr = ["b", "r", "y", "g"]

for i, cluster in enumerate(zip(data['x'], data['y'])):
    plt.scatter(cluster[0], cluster[1], s=50, c=colorarr[i])
plt.grid(True)
plt.scatter(centoids['x'], centoids['y'], marker='+', color=colorarr, s=330)
plt.savefig("random.png")

只需使用这里显示的几行plt.；您不需要更多，当然也不需要hold变量或show。基本上，您只是简单地在前一个集群的顶部绘制了每个集群，而在这个之上的是集群的中心线。

在上一个scatter中，我向color关键字提供了完整的colorarr：这样，每个质心都得到集群的相应颜色。

在您的代码中，它应该如下所示：

colorarr=["b", "r", "y", "g", "p"]
for k in range(len(cluster)):
    clusterPoint = [dataset[x] for x in cluster[k]]
    x0 = [x[0] for x in clusterPoint]
    y0 = [x[1] for x in clusterPoint]
    center = [(x0, y0) for x in clusterPoint]
    matplotlib.pyplot.scatter(x0, y0, center, c = colorarr[k])
xcentoids, ycentoids = zip(*centoids)
matplotlib.pyplot.scatter(xcentoids, ycentoids, marker='+', color=colorarr, s=330)
picname = "picture_number_" + str(i + 1) + ".png"
matplotlib.pyplot.savefig(picname)