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test.py
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test.py
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'''
ny.checkin
mid,uid,time,lat,lng,locid
1152544297120748018,7359659,2015-12-31 21:06:48-05:00,40.755269694,-73.980860525,39955188
ny.vname
locid,4sqid,locname
14621096,4f1c1b9fe4b0f67a9769ffce,Christian Pentecostal Church
ny.vcat
locid,catid,rating,likes,cicnt,tipcnt,usercnt
14621096,7032,100.0,4,189,1,55
ny.demo
uid,gender,conf_gender,race,conf_race,age,range_age
35113472,2,97.3803,1,67.4674,31,5
'''
import pickle
import numpy as np
import random
class DataCollector:
def __init__(self,config):
self.file_path = '/home/hsucheng/DRS/dataset/RS/'
self.arg = config
self.L,self.H,self.topk = self.arg.L,self.arg.H,self.arg.topk
self.N = 20
def _load_raw_data_(self):
'''
raw data: 1.ny.checkin, 2.ny.vcat, 3.ny.vname
'''
self.ny_checkin = open(self.file_path+'ny.checkin','r').readlines()[:500000]
self.ny_vcat = open(self.file_path+'ny.vcat','r').readlines()
self.ny_vname = open(self.file_path+'ny.vname','r').readlines()
self.ny_demo = open(self.file_path+'ny.demo','r').readlines()
def _ny_demo2dict_(self):
gender_tocken,race_tocken,age_tocken = 2,3,3
onehot_len = gender_tocken * race_tocken * age_tocken
tocken2onehot,index = dict(),0
for i in range(gender_tocken):
for j in range(race_tocken):
for k in range(age_tocken):
tocken_ = str(i+1)+'-'+str(j+1)+'-'+str(k+1)
onehot_ = list()
for h in range(onehot_len):
if h == index:
onehot_.append(1)
else:
onehot_.append(0)
index += 1
tocken2onehot[tocken_] = onehot_
onehot_list = list(tocken2onehot.values())
#gender_list,race_list,age_list = list(),list(),list()
uid2attr = dict()
for ny_demo_i in self.ny_demo[1:]:
ny_demo_i = ny_demo_i.split(',')
uid_,gender_,race_,age_ = ny_demo_i[0],int(ny_demo_i[1]),int(ny_demo_i[3]),int(ny_demo_i[5])
if age_ <= 20:
age_ = 1
elif age_ > 20 and age_ <= 40:
age_ = 2
else:
age_ = 3
tocken_ = str(gender_) + '-' + str(race_) + '-' + str(age_)
onehot_ = tocken2onehot[tocken_]
if uid_ not in uid2attr:
onehot_ = random.choice(onehot_list)
uid2attr[uid_] = onehot_
uid2attr['nothing'] = onehot_
return uid2attr
def _ny_checkin2dict_(self):
'''
uid2locid_time :
key-> uid_
value-> [(locid_,time_),(locid_,time_),(locid_,time_),....]
locid2detail :
key-> locid_
value-> [lat_,lng_]
'''
uid2locid_time,locid2detail = dict(),dict()
for ny_checkin_i in self.ny_checkin[1:]:
ny_checkin_i = ny_checkin_i.split(',')
uid_,time_,locid_ = ny_checkin_i[1],ny_checkin_i[2],ny_checkin_i[5].strip('\n')
lat_,lng_ = ny_checkin_i[3],ny_checkin_i[4]
if uid_ not in uid2locid_time:
uid2locid_time[uid_] = list()
uid2locid_time[uid_] = [(locid_,time_)] + uid2locid_time[uid_]
if locid_ not in locid2detail:
locid2detail[locid_] = [lat_,lng_]
return uid2locid_time,locid2detail
def _ny_vname2dict_(self):
'''
locid2locname :
key-> locid_
value-> locname_
'''
locid2locname = dict()
for ny_vname_i in self.ny_vname[1:]:
ny_vname_i = ny_vname_i.split(',')
locid_,locname_ = ny_vname_i[0],ny_vname_i[2]
if locid_ not in locid2locname:
locid2locname[locid_] = locname_
return locid2locname
def _ny_vcat2dict_(self):
'''
locid2catid :
key-> locid_
value-> catid_
'''
locid2catid = dict()
for ny_vcat_i in self.ny_vcat[1:]:
ny_vcat_i = ny_vcat_i.split(',')
locid_,catid_ = ny_vcat_i[0],str(int(int(ny_vcat_i[1])*0.001))
if locid_ not in locid2catid:
locid2catid[locid_] = catid_
return locid2catid
def _locid2detail_Merge_(self,locid2detail,locid2locname,locid2catid,uid2locid_time):
locid_name_ = list(set(locid2detail.keys()))
for i in range(len(locid_name_)):
if locid_name_[i] in locid2locname:
locname_ = locid2locname[locid_name_[i]]
locid2detail[locid_name_[i]].append(locname_)
else:
locid2detail[locid_name_[i]].append('none_name')
if locid_name_[i] in locid2catid:
catid_ = locid2catid[locid_name_[i]]
locid2detail[locid_name_[i]].append(catid_)
else:
locid2detail[locid_name_[i]].append('11')
return locid2detail
def main_data2dict(self,save=True):
'''
uid2locid_time
key: uid
value: [(locid,time),(locid,time),...]
locid2detail
key: locid
value: [lat_,lng_,locname_,catid_]
or value: [lat_,lng_,none_name,11]
'''
if save:
self._load_raw_data_()
uid2locid_time,locid2detail = self._ny_checkin2dict_()
locid2locname = self._ny_vname2dict_()
locid2catid = self._ny_vcat2dict_()
uid2attr = self._ny_demo2dict_()
locid2detail = self._locid2detail_Merge_(locid2detail,locid2locname,locid2catid,uid2locid_time)
ig_main1_data = {
'uid2locid_time':uid2locid_time,
'locid2detail':locid2detail,
'uid2attr':uid2attr,
}
file = open('ig_main1_data.pickle', 'wb')
pickle.dump(ig_main1_data, file)
file.close()
else:
with open('ig_main1_data.pickle', 'rb') as file:
ig_main1_data = pickle.load(file)
uid2locid_time = ig_main1_data['uid2locid_time']
locid2detail = ig_main1_data['locid2detail']
uid2attr = ig_main1_data['uid2attr']
return uid2locid_time,locid2detail,uid2attr
def _limit_in_seqlen_(self,uid2locid_time):
old_uid_list_ = list(uid2locid_time.keys())
for i in range(len(old_uid_list_)):
locid_time_ = uid2locid_time[old_uid_list_[i]]
if len(locid_time_) < (self.N + self.L + self.topk):
del uid2locid_time[old_uid_list_[i]]
else:
uid2locid_time[old_uid_list_[i]] = uid2locid_time[old_uid_list_[i]][:self.N + self.L + self.topk]
return uid2locid_time
def _element2ids_(self,uid2locid_time,locid2detail):
old_uid_list_ = list(uid2locid_time.keys())
locid_list_,vc_list_ = list(),list()
for i in range(len(old_uid_list_)):
locid_time_ = uid2locid_time[old_uid_list_[i]]
for j in range(len(locid_time_)):
locid_list_.append(locid_time_[j][0])
detail_ = locid2detail[locid_time_[j][0]]
vc_list_.append(detail_[-1])
locid_list_ = list(set(locid_list_))
vc_list_ = list(set(vc_list_))
ids_ = 0
self.uid2ids,self.locid2ids,self.vc2ids = dict(),dict(),dict()
for i in range(len(locid_list_)):
self.locid2ids[locid_list_[i]] = ids_
ids_ +=1
for i in range(len(old_uid_list_)):
self.uid2ids[old_uid_list_[i]] = ids_
ids_ +=1
for i in range(len(vc_list_)):
self.vc2ids[vc_list_[i]] = ids_
ids_ +=1
node_num = ids_
return old_uid_list_,locid_list_,node_num
def _replace_element_with_ids_(self,old_uid_list_,locid_list_,uid2locid_time,locid2detail,uid2attr):
new_uid2locid_time = dict()
for i in range(len(old_uid_list_)):
uid_ids_ = self.uid2ids[old_uid_list_[i]]
locid_time_ = uid2locid_time[old_uid_list_[i]]
new_uid2locid_time[uid_ids_] = [(self.locid2ids[locid_time_[j][0]],locid_time_[j][1]) for j in range(len(locid_time_))]
new_locid2detail = dict()
for i in range(len(locid_list_)):
detail_ = locid2detail[locid_list_[i]]
detail_[-1] = self.vc2ids[detail_[-1]]
new_locid2detail[self.locid2ids[locid_list_[i]]] = detail_
new_uid2attr = dict()
for i in range(len(old_uid_list_)):
uid_ids_ = self.uid2ids[old_uid_list_[i]]
if old_uid_list_[i] in uid2attr:
attr_ = uid2attr[old_uid_list_[i]]
else:
attr_ = uid2attr['nothing']
new_uid2attr[uid_ids_] = attr_
return new_uid2locid_time,new_locid2detail,new_uid2attr
def _seq_data_building_(self,old_uid_list_,uid2locid_time):
new_uid_list_ = [self.uid2ids[old_uid_list_[i]] for i in range(len(old_uid_list_))]
user_np,seq_train,seq_test,test_set = list(),list(),list(),list()
for i in range(len(new_uid_list_)):
locid_time_ = uid2locid_time[new_uid_list_[i]]
train_part = locid_time_[:self.N]
testX_part = locid_time_[self.N:self.N+self.L]
testY_part = locid_time_[self.N+self.L:]
for j in range(len(train_part)-self.L-self.H+1):
train_part_j_ = train_part[j:j+self.L+self.H]
user_np.append(new_uid_list_[i])
seq_train.append([train_part_j_[k][0] for k in range(len(train_part_j_))])
seq_test.append([testX_part[j][0] for j in range(len(testX_part))])
test_set.append([testY_part[j][0] for j in range(len(testY_part))])
user_np = np.array(user_np)
seq_train = np.array(seq_train)
seq_test = np.array(seq_test)
return new_uid_list_,user_np,seq_train,seq_test,test_set
def _edge_building_(self,uid_list_,uid2locid_time,locid2detail):
u2v,u2vc,v2u,v2vc = dict(),dict(),dict(),dict()
for i in range(len(uid_list_)):
locid_time_ = uid2locid_time[uid_list_[i]]
v_list_,u_vc_list_ = list(),list()
for j in range(len(locid_time_)):
locid_ = locid_time_[j][0]
v_list_.append(locid_)
if locid_ not in v2u:
v2u[locid_] = list()
v2u[locid_].append(uid_list_[i])
vc_ = locid2detail[locid_][-1]
u_vc_list_.append(vc_)
if locid_ not in v2vc:
v2vc[locid_] = vc_
v_list_ = list(set(v_list_))
u2v[uid_list_[i]] = v_list_
u_vc_list_ = list(set(u_vc_list_))
u2vc[uid_list_[i]] = u_vc_list_
v2u_keys = list(v2u.keys())
for i in range(len(v2u_keys)):
v2u[v2u_keys[i]] = list(set(v2u[v2u_keys[i]]))
return u2v,u2vc,v2u,v2vc
def main_datadict2traindata(self,uid2locid_time,locid2detail,uid2attr,save=True):
if save:
uid2locid_time = self._limit_in_seqlen_(uid2locid_time)
old_uid_list_,locid_list_,node_num = self._element2ids_(uid2locid_time,locid2detail)
uid2locid_time,locid2detail,uid2attr = self._replace_element_with_ids_(old_uid_list_,locid_list_,uid2locid_time,locid2detail,uid2attr)
uid_list_,user_np,seq_train,seq_test,test_set = self._seq_data_building_(old_uid_list_,uid2locid_time)
u2v,u2vc,v2u,v2vc = self._edge_building_(uid_list_,uid2locid_time,locid2detail)
relation_num = 6 #u_vc,u,v,v_vc
ig_main2_data = {
'uid2locid_time':uid2locid_time,
'locid2detail':locid2detail,
'node_num':node_num,
'uid_list_':uid_list_,
'user_np':user_np,
'seq_train':seq_train,
'seq_test':seq_test,
'test_set':test_set,
'u2v':u2v,
'u2vc':u2vc,
'v2u':v2u,
'v2vc':v2vc,
'relation_num':relation_num,
'uid2attr':uid2attr,
}
file = open('ig_main2_data.pickle', 'wb')
pickle.dump(ig_main2_data, file)
file.close()
else:
with open('ig_main2_data.pickle', 'rb') as file:
ig_main2_data = pickle.load(file)
uid2locid_time = ig_main2_data['uid2locid_time']
locid2detail = ig_main2_data['locid2detail']
node_num = ig_main2_data['node_num']
uid_list_ = ig_main2_data['uid_list_']
user_np = ig_main2_data['user_np']
seq_train = ig_main2_data['seq_train']
seq_test = ig_main2_data['seq_test']
test_set = ig_main2_data['test_set']
u2v = ig_main2_data['u2v']
u2vc = ig_main2_data['u2vc']
v2u = ig_main2_data['v2u']
v2vc = ig_main2_data['v2vc']
return uid2locid_time,locid2detail,node_num,relation_num,uid_list_,user_np,seq_train,seq_test,test_set,u2v,u2vc,v2u,v2vc
def main(self,save1=True,save2=True):
#if save1:
uid2locid_time,locid2detail,uid2attr = self.main_data2dict(save1)
uid2locid_time,locid2detail,node_num,relation_num,uid_list_,user_np,seq_train,seq_test,test_set,u2v,u2vc,v2u,v2vc = self.main_datadict2traindata(uid2locid_time,locid2detail,uid2attr,save2)
return uid2locid_time,locid2detail,node_num,relation_num,uid_list_,user_np,seq_train,seq_test,test_set,u2v,u2vc,v2u,v2vc