我的kmeans聚类 python代码

仿制matlab的kmeans聚类 http://blog.csdn.net/nbu2004/article/details/43084999注意 data 是list类型，但二维array类型也没问题。比起MATLAB，Python只能更简单，即使没有MATLAB矩阵表达式。

# -*- coding: utf-8 -*-# import copyimport numpy as  npimport numpy.linalg as LAdef kmeans(data, K, dist=lambda x,y: LA.norm(x-y), tol=1e-8):    '''    arguments:    data: list of data    K: int, numbers of classes    dist: distance    return: kls, ctr        example:'''    ctr = data[:K]    N = len(data)    while True:        # Assignment step        kls = [[] for _ in range(K)]                # K clusters        for dt in data:            d = dist(dt, ctr[0])            ind = 0            for k, ck in enumerate(ctr[1:], 1):                d0 = dist(dt, ck)                if d0 < d:                    ind = k                    d = d0            kls[ind].append(dt)   # data l is in ind-th cluster                # Update step        S = 0        newctr = []        for k in range(K):                     # calculate new centroids            ck = np.mean(np.array(kls[k]), 0)            S += dist(ck, ctr[k])            newctr.append(ck)                   if S <= tol:            break        else:            ctr = newctr                   # update the centroids    return kls, ctr# testdata = np.random.rand(100,2)K = 4kls, ctr = kmeans(data, K)clr=['r','k','g','b']import matplotlib.pyplot as pltfor k in range(K):    for kk in kls[k]:        plt.plot(kk[0], kk[1], clr[k]+'o')    plt.plot(ctr[k][0], ctr[k][1], clr[k]+'+')plt.show()