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from numpy import *
def loadDataSet(filename,delim = "\t"):
fr = open(filename)
stringArr = [line.strip().split(delim) for line in fr.readlines()]
datArr = [map(float, line) for line in stringArr]
return mat(datArr)
#dataMat对应数据集,N个特征
def pca(dataMat, topNfeat=9999999):
meanVals = mean(dataMat, axis = 0) #求平均值
meanRemoved = dataMat - meanVals #去平均值
covMat = cov(meanRemoved,rowvar=0) #计算协防差矩阵
eigVals, eigVects = linalg.eig(mat(covMat))
eigValInd = argsort(eigVals)
#从小到大对N个值排序
eigValInd = eigValInd[: -(topNfeat + 1) : -1]
redEigVects = eigVects[:, eigValInd]
#将数据转换到新空间
lowDDataMat = meanRemoved * redEigVects
reconMat = (lowDDataMat * redEigVects.T) + meanVals
return lowDDataMat, reconMat
#测试
dataMat = loadDataSet("testSet.txt")
lowDMat, reconMat = pca(dataMat,1)
print shape(lowDMat)
#show
import matplotlib
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(dataMat[:,0].flatten().A[0], dataMat[:,1].flatten().A[0], marker='^', s = 90 )
ax.scatter(reconMat[:,0].flatten().A[0], reconMat[:,1].flatten().A[0],marker='o', s = 50 , c ='red' )