def drawfenkai(filename):
from getDir import GetDirName
import os
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + "\\" + "starlog")
for path_file in other:
TimePic = []
for i in range(len(path_file)):
temp = []
path_file_name = parent_path + path_file[i] + os.sep + filename
# print(path_file_name)
data = np.loadtxt(path_file_name, dtype=str, delimiter=",", usecols=(0, 1, 2), unpack=False)
start = data[1][1].split(" ")[0]
for i in range(len(data)):
tmp = []
tmp.append(canculateDate(data[i][1], start))
tmp.append(canculateDate(data[i][2], start))
tmp.append(data[i][0])
temp.append(tmp)
TimePic.append(temp)
print(path_file_name)
drewPic(TimePic, path_file_name)
def drawfenkai(filename):
from getDir import GetDirName
import os
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + '\\' +
'starlog')
for path_file in other:
TimePic = []
for i in range(len(path_file)):
temp = []
path_file_name = parent_path + path_file[i] + os.sep + filename
#print(path_file_name)
data = np.loadtxt(path_file_name,
dtype=str,
delimiter=',',
usecols=(0, 1, 2),
unpack=False)
start = data[1][1].split(' ')[0]
for i in range(len(data)):
tmp = []
tmp.append(canculateDate(data[i][1], start))
tmp.append(canculateDate(data[i][2], start))
tmp.append(data[i][0])
temp.append(tmp)
TimePic.append(temp)
print(path_file_name)
drewPic(TimePic, path_file_name)
def create_model(labelFileName='RClabelTime.txt'):
FileName=[]
from getDir import GetDirName
import os
getdir=GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles,AllFiles,other=getdir.getUserFiles(parent_path+'\\'+'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name=parent_path+path_file[i]+os.sep+labelFileName
FileName.append(path_file_name)
train_set=[]
for file in FileName: #一个file 就是一天的数据路径，也就是一天的数据,外层一个for循环就是 写找完一天的记录
ondaydata=np.loadtxt(file,dtype=str,delimiter=',',usecols=(0,1,3)) #label,starttime,continuetime
tempsentence=[]
for i in range(len(ondaydata)):
datasstrip=ondaydata[i][1].split(' ')
word=ondaydata[i][0]+'_'+datasstrip[0]+'_'+time2hour(datasstrip[1])+'_'+str(int(ondaydata[i][2])//(10*60))
tempsentence.append(word)
train_set.append(tempsentence)
dic = corpora.Dictionary(train_set)
corpus = [dic.doc2bow(text) for text in train_set]
tfidf = models.TfidfModel(corpus)
corpus_tfidf = tfidf[corpus]
lda = models.LdaModel(corpus_tfidf, id2word = dic, num_topics = 24)
corpus_lda = lda[corpus_tfidf]
lda.save(".\\LDA_all_27\\SemanticLda"+str(24)+".txt")
dic.save(".\\LDA_all_27\\SemanticDic"+str(24)+".txt")
tfidf.save(".\\LDA_all_27\\SemanticTFIDF"+str(24)+".txt")
return lda,dic,tfidf,train_set,AllUserFiles
def calculate_user_sim_onBluetooth():
userlist = []
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + os.sep +
'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name = parent_path + path_file[
i] + os.sep + 'bluetooth.txt'
if os.path.exists(path_file_name):
userlist.append(path_file_name.split(os.sep)[-3])
userlist = list(set(userlist))
print userlist
for i in range(len(userlist) - 1):
for j in range(i, len(userlist)):
print userlist[i], userlist[j]
result = calculate_bluetooth_sim(userlist[i], userlist[j])
ans.write(userlist[i])
ans.write(',')
ans.write(userlist[j])
ans.write(',')
ans.write(str(result))
ans.write('\n')
def get_fenlei_user():
wifi_path=[]
getdir=GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles,AllFiles,other=getdir.getUserFiles(parent_path+os.sep+'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name=parent_path+path_file[i]+os.sep+'wifi.txt'
wifi_path.append(path_file_name)
return wifi_path
def get_fenlei_user():
wifi_path = []
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + os.sep + "starlog")
for path_file in other:
for i in range(len(path_file)):
path_file_name = parent_path + path_file[i] + os.sep + "bluetooth.txt"
if os.path.exists(path_file_name):
wifi_path.append(path_file_name)
#####Trans_btoothjson_txt(path_file_name) first time to excue this func will create blueeth csv file with add model to do
return wifi_path
def mian():
from Semantics_of_Trajectories import Calculate_semantic_of_point
from stop_points import getfullfilepath
full = getfullfilepath()
for n in range(len(full)):
path_file = full[n].replace("locationGPS.txt", "location.txt")
gps_data, timestamp, accur = get_data(path_file)
# print len(accur)
# print len(timestamp)
labels, SP = getStayPoint(gps_data, timestamp, disthreshold=90, timethreshold=180)
# print len(labels)
# print(len(labels)-1)
print (full[n])
labels.append(labels[len(labels) - 1]) #!!!!!!!!注意，labels的长度可能为0 好奇怪
# print len(labels)
# print len(SP)
# print SP
stoppointlabel = []
labDIC = {}
for i in range(len(SP)):
value = Calculate_semantic_of_point.Match_semantics(SP[i], 90)
stoppointlabel.append(value)
labDIC[i] = value
init_rs_staypoint_time(labels, gps_data, timestamp, accur, SP, labDIC, path_file)
# 分类的用户的文件夹
from getDir import GetDirName
import os
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + "\\" + "starlog")
for path_file in other:
for i in range(len(path_file)):
path_file_name = parent_path + path_file[i] + os.sep + "location.txt"
gps_data, timestamp, accur = get_data(path_file_name)
labels, SP = getStayPoint(gps_data, timestamp, disthreshold=90, timethreshold=180)
print (path_file[i])
labels.append(labels[len(labels) - 1]) #!!!!!!!!注意，labels的长度可能为0 好奇怪
stoppointlabel = []
labDIC = {}
for i in range(len(SP)):
value = Calculate_semantic_of_point.Match_semantics(SP[i], 90)
stoppointlabel.append(value)
labDIC[i] = value
init_rs_staypoint_time(labels, gps_data, timestamp, accur, SP, labDIC, path_file_name)
def mian():
from Semantics_of_Trajectories import Calculate_semantic_of_point
from stop_points import getfullfilepath
full=getfullfilepath()
for n in range(len(full)):
path_file=full[n].replace('locationGPS.txt','location.txt')
gps_data,timestamp,accur = get_data(path_file)
# print len(accur)
# print len(timestamp)
labels,SP = getStayPoint(gps_data,timestamp,disthreshold=90,timethreshold=180)
#print len(labels)
#print(len(labels)-1)
print(full[n])
labels.append(labels[len(labels)-1]) #!!!!!!!!注意，labels的长度可能为0 好奇怪
# print len(labels)
# print len(SP)
# print SP
stoppointlabel=[]
labDIC={}
for i in range(len(SP)):
value=Calculate_semantic_of_point.Match_semantics(SP[i],90)
stoppointlabel.append(value)
labDIC[i]=value
init_rs_staypoint_time(labels,gps_data,timestamp,accur,SP,labDIC,path_file)
#分类的用户的文件夹
from getDir import GetDirName
import os
getdir=GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles,AllFiles,other=getdir.getUserFiles(parent_path+'\\'+'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name=parent_path+path_file[i]+os.sep+'location.txt'
gps_data,timestamp,accur = get_data(path_file_name)
labels,SP = getStayPoint(gps_data,timestamp,disthreshold=90,timethreshold=180)
print(path_file[i])
labels.append(labels[len(labels)-1]) #!!!!!!!!注意，labels的长度可能为0 好奇怪
stoppointlabel=[]
labDIC={}
for i in range(len(SP)):
value=Calculate_semantic_of_point.Match_semantics(SP[i],90)
stoppointlabel.append(value)
labDIC[i]=value
init_rs_staypoint_time(labels,gps_data,timestamp,accur,SP,labDIC,path_file_name)
def main():
from label_add_time import GetSemanticGPSpath
full=GetSemanticGPSpath()
for n in range(len(full)):
path_file=full[n].replace('semanticGPS.txt','RC_stoppoint.txt')
print(path_file)
Read_RC_stoppoint(path_file)
print 'ok.....have process over'
#分类的用户的文件夹
from getDir import GetDirName
import os
getdir=GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles,AllFiles,other=getdir.getUserFiles(parent_path+'\\'+'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name=parent_path+path_file[i]+os.sep+'RC_stoppoint.txt'
Read_RC_stoppoint(path_file_name)
print 'ok.....have process over'
def RC_Label_Time_process():
filelist = GetSemanticGPSpath()
lda = ldaHelper()
for file in filelist:
f = file.replace('semanticGPS.txt', 'RC_stoppoint.txt')
write_labelTime2file(lda.Add_RCtimestamp(f), f)
print('have done %s' % f)
#分类的用户的文件夹
from getDir import GetDirName
import os
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + '\\' +
'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name = parent_path + path_file[
i] + os.sep + 'RC_stoppoint.txt'
write_labelTime2file(lda.Add_RCtimestamp(path_file_name),
path_file_name)
def main():
from label_add_time import GetSemanticGPSpath
full = GetSemanticGPSpath()
for n in range(len(full)):
path_file = full[n].replace('semanticGPS.txt', 'RC_stoppoint.txt')
print(path_file)
Read_RC_stoppoint(path_file)
print 'ok.....have process over'
#分类的用户的文件夹
from getDir import GetDirName
import os
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + '\\' +
'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name = parent_path + path_file[
i] + os.sep + 'RC_stoppoint.txt'
Read_RC_stoppoint(path_file_name)
print 'ok.....have process over'
def create_model(labelFileName='RClabelTime.txt'):
FileName = []
from getDir import GetDirName
import os
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles, AllFiles, other = getdir.getUserFiles(parent_path + '\\' +
'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name = parent_path + path_file[i] + os.sep + labelFileName
FileName.append(path_file_name)
train_set = []
for file in FileName: #一个file 就是一天的数据路径，也就是一天的数据,外层一个for循环就是 写找完一天的记录
ondaydata = np.loadtxt(file,
dtype=str,
delimiter=',',
usecols=(0, 1,
3)) #label,starttime,continuetime
tempsentence = []
for i in range(len(ondaydata)):
datasstrip = ondaydata[i][1].split(' ')
word = ondaydata[i][0] + '_' + datasstrip[0] + '_' + time2hour(
datasstrip[1]) + '_' + str(int(ondaydata[i][2]) // (10 * 60))
tempsentence.append(word)
train_set.append(tempsentence)
dic = corpora.Dictionary(train_set)
corpus = [dic.doc2bow(text) for text in train_set]
tfidf = models.TfidfModel(corpus)
corpus_tfidf = tfidf[corpus]
lda = models.LdaModel(corpus_tfidf, id2word=dic, num_topics=24)
corpus_lda = lda[corpus_tfidf]
lda.save(".\\LDA_all_27\\SemanticLda" + str(24) + ".txt")
dic.save(".\\LDA_all_27\\SemanticDic" + str(24) + ".txt")
tfidf.save(".\\LDA_all_27\\SemanticTFIDF" + str(24) + ".txt")
return lda, dic, tfidf, train_set, AllUserFiles
def calculate_user_sim_onBluetooth():
userlist = []
getdir = GetDirName()
parent_path = os.path.dirname(os.getcwd())
AllUserFiles,AllFiles,other = getdir.getUserFiles(parent_path+os.sep+'starlog')
for path_file in other:
for i in range(len(path_file)):
path_file_name = parent_path+path_file[i]+os.sep+'bluetooth.txt'
if os.path.exists(path_file_name):
userlist.append(path_file_name.split(os.sep)[-3])
userlist = list(set(userlist))
print userlist
for i in range(len(userlist)-1):
for j in range(i,len(userlist)):
print userlist[i],userlist[j]
result= calculate_bluetooth_sim(userlist[i],userlist[j])
ans.write(userlist[i])
ans.write(',')
ans.write(userlist[j])
ans.write(',')
ans.write(str(result))
ans.write('\n')
file_processGPS.writelines(',')
file_processGPS.writelines('0.0')
file_processGPS.write('\n')
file_processGPS.close()
def drewgps(weidu, jindu, date):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(jindu, weidu, c='r', marker='.')
plt.title('location of : %s' % date)
plt.savefig('.\\GPS_pic\\' + date + '.png', dpi=800)
plt.close()
#plt.show()
if __name__ == '__main__':
getdir = GetDirName()
dirlist = []
dirlist = getdir.printPath(".\\GPS_Get_PreProcesser")
print(dirlist)
for wenjianjia in dirlist:
print ".\\GPS_Get_PreProcesser" + '\\' + wenjianjia + '\\' + 'location.txt', wenjianjia
readfile(
".\\GPS_Get_PreProcesser" + '\\' + wenjianjia + '\\' +
'location.txt', wenjianjia)
#下面是写分开每个用户的结果哦
AllUserFiles, AllFiles, other = getdir.getUserFiles()
for wenjianjia in AllFiles:
readfile(wenjianjia + os.sep + 'location.txt', wenjianjia)
file_processGPS.writelines(',')
file_processGPS.writelines(i[1])
file_processGPS.writelines(',')
file_processGPS.writelines(i[2])
file_processGPS.writelines(',')
file_processGPS.writelines(i[3])
file_processGPS.writelines(',')
file_processGPS.writelines('0.0')
file_processGPS.write('\n')
file_processGPS.close()
def drewgps(weidu,jindu,date):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.scatter(jindu,weidu,c='r',marker='.')
plt.title('location of : %s' % date)
plt.savefig('.\\GPS_pic\\'+date+'.png',dpi=800)
plt.close()
#plt.show()
if __name__=='__main__':
getdir=GetDirName()
dirlist=[]
dirlist=getdir.printPath(".\\GPS_Get_PreProcesser")
print(dirlist)
for wenjianjia in dirlist:
print ".\\GPS_Get_PreProcesser"+ '\\' + wenjianjia + '\\' + 'location.txt',wenjianjia
readfile(".\\GPS_Get_PreProcesser"+ '\\' + wenjianjia + '\\' + 'location.txt',wenjianjia)
#下面是写分开每个用户的结果哦
AllUserFiles,AllFiles,other=getdir.getUserFiles()
for wenjianjia in AllFiles:
readfile(wenjianjia + os.sep+ 'location.txt',wenjianjia)
