PAC初识

import  numpy as np
import matplotlib.pyplot as plt

data = np.array([[2.5,2.4],[0.5,0.7],[2.2,2.9],[1.9,2.2],[3.1,3.0],[2.3,2.7],[2,1.6],[1,1.1],[1.5,1.6],[1.1,0.9]])
e1 = np.mean(data[:,0])
e2 = np.mean(data[:,1])
x = data[:,0]
y = data[:,1]
data1=np.array([[2.5,2.4],[0.5,0.7],[2.2,2.9],[1.9,2.2],[3.1,3.0],[2.3,2.7],[2,1.6],[1,1.1],[1.5,1.6],[1.1,0.9]])
data1[:,0]=x-e1
data1[:,1]=y-e2
DataAdjust=data1
c= np.array([[(1 / (len(x) - 1)) * np.dot((x - e1), (x - e1)),(1 / (len(x) - 1)) * np.dot((x - e1), (y - e2))],[(1 / (len(y) - 1)) * np.dot((y - e2), (x - e1)),(1 / (len(y) - 1)) * np.dot((y - e2), (y - e2))]])
a,b = np.linalg.eig(c)
if a[0] > a[1]:
    b00=b[0,0]
    b01=b[1,0]
    EigenVectors = np.array([[b00],[b01]])
else:
    m=a[1]
    b10=b[0,1]
    b11=b[1,1]
    EigenVectors = np.array([b10,b11])
    EigenVectors=EigenVectors.reshape(2,1)
FinalData=np.dot(DataAdjust,EigenVectors)
FinalData=sorted(FinalData)
print(FinalData)
plt.plot(FinalData,'g-s')
plt.show()