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softcluster.py
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import random
import numpy as np
from numpy import linalg as LA
import matplotlib.pyplot as plt
import math
data1=[]
for i in range(100):
data1=data1+[[0.5+0.5*random.random(),0.5+0.5*random.random()]]
data2=[]
for i in range(100):
data2=data2+[[0.5*random.random(),0.5*random.random()]]
#data3 =[]
#for i in range(30):
# data3=data3+[[0.8,random.random()]]
data=data1+data2#+data3
datax=[]
for i in range(len(data)):
datax=datax+[data[i][0]]
datay=[]
for i in range(len(data)):
datay=datay+[data[i][1]]
plt.scatter(datax,datay)
plt.show()
print np.var(data)
assign = []
for j in range(4):
assign=assign+[[random.random(),random.random()]]
print assign
sum=[]
for i in range(len(data)):
sum=sum+[[]]
r=[]
for i in range(4):
r=r+[[]]
for j in range(len(data)):
r[i]=r[i]+[[]]
update_assign=[]
for k in range(4):
update_assign=update_assign+[[]]
a=0
b=1/(7*np.var(data1))
while a<10:
a=a+1
sum=[]
for i in range(len(data)):
sum=sum+[[]]
for n in range(len(data)):
s=0
for k in range(4):
s=s+np.exp(-b*(LA.norm(np.array(assign[k])-np.array(data[n]))))
sum[n]=s
for j in range(4):
r[j][n]=np.exp(-b*(LA.norm(np.array(assign[j])-np.array(data[n]))))/s
#print a,j,n,r[j][n]
rsum=[]
for i in range(4):
rsum=rsum+[[]]
for k in range(4):
rs=0
for n in range(len(data)):
rs=rs+r[k][n]
rsum[k]=rs
ua=[0,0]
for n in range(len(data)):
ua[0]=ua[0]+r[k][n]*data[n][0]/float(rs)
ua[1]=ua[0]+r[k][n]*data[n][1]/float(rs)
update_assign[k]=ua
assign= update_assign
print assign
c=[[],[],[],[]]
for n in range(len(data)):
a=[]
for k in range(4):
a=a+[r[k][n]]
i=a.index(max(a))
c[i]=c[i]+[data[n]]
circle0= plt.Circle(assign[0],1/math.sqrt(b),color='r',fill=False)
circle1= plt.Circle(assign[1],1/math.sqrt(b),color='g',fill=False)
circle2= plt.Circle(assign[2],1/math.sqrt(b),color='y',fill=False)
circle3= plt.Circle(assign[3],1/math.sqrt(b),color='b',fill=False)
fig, ax=plt.subplots()
plt.xlim([-0.3,1.3])
plt.ylim([-0.3,1.3])
ax.add_artist(circle0)
ax.add_artist(circle1)
ax.add_artist(circle2)
ax.add_artist(circle3)
ax.scatter([x for x,y in c[0]],[y for x,y in c[0]],color='r')
ax.scatter([x for x,y in c[1]],[y for x,y in c[1]],color='g')
ax.scatter([x for x,y in c[2]],[y for x,y in c[2]],color='y')
ax.scatter([x for x,y in c[3]],[y for x,y in c[3]],color='b')
plt.show()