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#coding=utf-8
# 我是中文 ————Lost
'''
Read File on 2016.4.4
file2mat -> savemat (-> readmat)
file2mat
Input: file and a num<=1
Output: if num=1,return mat and label
if num<1,return a random [trainMat,trainLabel,testMat,testLabel]
savemat
save matrix as txt
readmat
load matrix
——————————————————————————————————————————————————————————————————————
you can use it like this:
import ReadFile.py as *
trainMat,trainLabel,testMat,testLabel=file2mat('filename',0.8)
savetxt('savename',trainMat)
Tmat=readmat('savename')
——————————————————————————————————————————————————————————————————————
PengKun
'''
from numpy import *
import operator
from os import listdir
import random
import linecache
print "加载成功"
# savetxt和loadtxt适合读写1维和二维数组
# 保存数组,按%g的格式保存，现在还没有解决对齐的问题
def savemat(filename,mat):
"{:<10}".format(mat)
savetxt(filename,mat,fmt="%g")
# 读取数组
def readmat(filename):
return loadtxt(filename)
# 随机选数
# 适用于末位标签
def rand2mat(alldata,randpart):
m,n=alldata.shape
n=n-1 #去除标签
randNumber=[i for i in range(m)]
random.shuffle(randNumber)
partition=int(randpart*m)
# print alldata,randNumber,partition
trainLabel=[]
testLabel=[]
trainPart=randNumber[:partition]
testPart=randNumber[partition:]
testMat= zeros((len(testPart),n))
trainMat=zeros((len(trainPart),n))
for i,x in enumerate(trainPart):
trainMat[i,:]=alldata[x, :-1]
trainLabel.append(int(alldata[x, -1]))
for j,y in enumerate(testPart):
testMat[j,:]=alldata[y, :-1]
testLabel.append(int(alldata[y, -1]))
return trainMat,trainLabel,testMat,testLabel
# 读取数据
def file2mat(filename,randpart):
fr = open(filename)
numberOfLines = len(fr.readlines()) #get the number of lines in the file
fr = open(filename)
FeatureOfLines = len(fr.readline().strip().split('\t')) # get the feature and label,feature=FeatureOfLines-1
# FeatureOfLines = linecache.getlines(filename,1).count('\t') # same as FeatureOfLines
returnMat = zeros((numberOfLines,FeatureOfLines)) #prepare matrix to return
# print returnMat
classLabelVector = [] #prepare labels return
fr = open(filename)
index = 0
for line in fr.readlines():
line = line.strip()
listFromLine = line.split('\t')
returnMat[index,:] = listFromLine[:]
# print returnMat.dtype
# print listFromLine,returnMat
classLabelVector.append(int(listFromLine[-1]))
index += 1
# print returnMat
if randpart!=1:
trainMat,trainLabel,testMat,testLabel=rand2mat(returnMat,randpart)
return trainMat,trainLabel,testMat,testLabel
else:
return returnMat[:,:-1],classLabelVector