#-*-coding:utf8-*-

'''

Created on 2016-5-15

@author: thinkgamer

'''

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' )

plt.show()

'''

#将NaN替换成平均值函数

def replaceNanWithMean():

datMat = loadDataSet('secom.data', ' ')

numFeat = shape(datMat)[1]

for i in range(numFeat):

meanVal = mean(datMat[nonzero(~isnan(datMat[:,i].A))[0],i]) #values that are not NaN (a number)

datMat[nonzero(isnan(datMat[:,i].A))[0],i] = meanVal #set NaN values to mean

return datMat

#加载数据

dataMat = replaceNanWithMean()

#去除均值

meanVals = mean(dataMat, axis=0)

meanRemoved = dataMat - meanVals

#计算协方差

covMat = cov(meanRemoved, rowvar=0)

#特征值分析

eigVals, eigVects = linalg.eig(mat(covMat))

print eigVals