/
kMean-02.py
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/
kMean-02.py
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import numpy as np
import matplotlib.pyplot as plt
import scipy as sp
import scipy.linalg as linalg
#-----------------------------------------------------------------
#計算兩個向量的歐基米得距離
def dist_raw(v1, v2):
delta=v1-v2
return linalg.norm(delta.tolist())
#-----------------------------------------------------------------
#-----------------------------------------------------------------
#計算ndarray中的某元素值個數
def count_array(nd, v):
cnt=0
for i in range(len(nd)):
if nd[i]==v:
cnt=cnt+1
return cnt
#-----------------------------------------------------------------
#-----------------------------------------------------------------
#計算ndarray中的加總
def sum_array(nd, label, v):
d1=0
d2=0
for i in range(len(label)):
if label[i]==v:
d1=d1+nd[i][0]
d2=d2+nd[i][1]
return np.array([d1, d2])
#-----------------------------------------------------------------
#
total_size=500 #偶數
group_size=5
repeat_time=100
# 產生常態分配亂數成績
chi01=np.random.randn(int(total_size/2))*10+60
eng01=np.random.randn(int(total_size/2))*10+60
chi02=np.random.randn(int(total_size/2))*10+40
eng02=np.random.randn(int(total_size/2))*10+40
# 修正資料
chi01=chi01.clip(0, 100)
eng01=eng01.clip(0, 100)
chi02=chi02.clip(0, 100)
eng02=eng02.clip(0, 100)
data01=np.concatenate([chi01, chi02])
data02=np.concatenate([eng01, eng02])
label=np.zeros(total_size)
data=np.array([data01, data02])
data=data.reshape(total_size, 2)
np.random.shuffle(data)
#分簇
data_center=data[0:group_size]
for i in range(group_size):
label[i]=i
dist=np.zeros(group_size)
for i in range(group_size, total_size):
min=999
idx=-1
for k in range(group_size):
dist[k]=dist_raw(data_center[k], data[i])
if dist[k]<min:
lab=k
min=dist[k]
label[i]=lab
m=sum_array(data, label, lab)
data_center[lab]=m/count_array(label, lab)
for t in range(1, repeat_time):
for i in range(0, total_size):
for k in range(group_size):
dist[k]=dist_raw(data_center[k], data[i])
min=999
idx=-1
for k in range(group_size):
if dist[k]<min:
lab=k
min=dist[k]
label[i]=lab
m=sum_array(data, label, lab)
data_center[lab]=m/count_array(label, lab)
for k in range(group_size):
print('群集', k, '中心:', data_center[k])
# 設定字型及大小
plt.rcParams['font.sans-serif']=['SimHei']
plt.rcParams['font.size'] = 14
# 設定圖標題
plt.title('國文-英文成績分佈(依入學方式分別)')
# 設定x軸及y軸標題
plt.xlabel('國文成績')
plt.ylabel('英文成績')
# 資料表內的grid
plt.grid(True)
# 設定x軸及y軸的尺規範圍
plt.axis([-5, 105, -5, 105])
# 繪製資料
for i in range(group_size):
print_data=data[label==i]
plt.scatter(print_data[:,0], print_data[:,1], c=np.random.rand(3,1))
plt.plot(data_center[i][0], data_center[i][1], 'ro')
# 顯示圖表
plt.show()