11

import numpy as np
x=np.random.randint(0,34,20)
y=np.zeros(20)
k=3
def initcenter(x,k):
    return x[0:k].reshape(k)
def nearest(kc,i):
    d=(abs(kc-i))
    w=np.where(d==np.min(d))
    return w[0][0]
def xclassify(x,y,kc):
    for i in range(x.shape[0]):
         y[i]=nearest(kc,x[i])
    return y
def kcmean(x,y,kc,k):
    l=list(kc)
    flag=False
    for c in range(k):
        m=np.where(y==c)
        n=np.mean(x[m])
        if l[c]!=n:
            l[c]=nflag=True
    return(np.array(l),flag)
kc=initcenter(x,k)
flag=True
print(x,y,kc,flag)
while flag:
    y=xclassify(x,y,kc)
    kc,flag=kcmean(x,y,kc,k)
print(y,kc)