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#coding:utf8
from tools import balance
from pymongo import Connection
from small_utils.progress_bar import progress_bar
from collections import Counter
from tools import get_features
from settings import RAW_DATA_DIR
from tools import get_balance_params
from tools import combine_dict
import random
from collections import Counter
from settings import base_dir
from settings import labeled_feature_file_dir
from label_arbiter import LabelArbiter
from test import get_test_uids
def construct_train_set(attribute,training_count):
product_features=get_features(feature_file=base_dir+'/features/product.feature')
mention_features=get_features(feature_file=base_dir+'/features/mention.feature',existent_features=product_features)
review_featuers=get_features(feature_file=base_dir+'/features/review.feature',existent_features=mention_features)
mention_features_1=get_features(feature_file=base_dir+'/features/mention_1.feature',existent_features=review_featuers)
test_uids=get_test_uids()
labeled_feature_file='%s/review_constraint_%s.constraints'%(labeled_feature_file_dir,attribute)
label_arbiter=LabelArbiter(labeled_feature_file=labeled_feature_file)
collection=Connection().jd.train_users
bar=progress_bar(collection.count())
guess=[]
for index,user in enumerate(collection.find()):
if user['_id'] in test_uids:
continue
features=combine_dict(user['mentions_0'],Counter('products'))
label,confidence=label_arbiter.arbitrate_label(features)
x=[]
#user['products']=[]
for f,v in Counter(user['products']).items():
if f not in product_features:
continue
x.append((product_features[f],v))
#user['mentions']={}
for f,v in user['mentions_0'].items():
if f not in mention_features:
continue
x.append((mention_features[f],v))
#user['review']=[]
for f,v in Counter(user['review']).items():
if f not in review_featuers:
continue
x.append((review_featuers[f],v))
#user['mentions_1_1']={}
for f,v in user['mentions_1_1'].items():
f=f+'_1'
if f not in mention_features_1:
continue
x.append((mention_features_1[f],v))
x=sorted(x,key=lambda d:d[0])
str_x=' '.join(map(lambda f:'%s:%f'%f,x))
guess.append(
(user['_id'],
label,
abs(confidence),
str_x,
sum(user['mentions'].values()),
))
bar.draw(index+1)
data0=filter(lambda d:d[1]==0,guess)
data0=sorted(data0,key=lambda d:d[2],reverse=True)
data1=filter(lambda d:d[1]==1,guess)
data1=sorted(data1,key=lambda d:d[2],reverse=True)
data2=filter(lambda d:d[1]==-1,guess)
data2=sorted(data2,key=lambda d:d[4],reverse=True)
dimention=min(len(data0),len(data1),training_count/2)
data0=data0[:dimention]
data1=data1[:dimention]
data2=data2[:dimention]
fout=open(RAW_DATA_DIR+'iterate_label2trainset/%s_train.data'%attribute,'w')
uid_output=open(RAW_DATA_DIR+'iterate_label2trainset/%s_train_uids.data'%attribute,'w')
for d in data0+data1:
fout.write('%d %s\n'%(d[1],d[3]))
uid_output.write('%s\n'%d[0])
fout=open(RAW_DATA_DIR+'iterate_label2trainset/%s_train_unlabel.data'%attribute,'w')
uid_output=open(RAW_DATA_DIR+'iterate_label2trainset/%s_train_unlabel_uids.data'%attribute,'w')
for d in data2:
fout.write('%d %s\n'%(d[1],d[3]))
uid_output.write('%s\n'%d[0])
def construct_test_set(attribute):
product_features=get_features(feature_file=base_dir+'/features/product.feature')
mention_features=get_features(feature_file=base_dir+'/features/mention.feature',existent_features=product_features)
review_featuers=get_features(feature_file=base_dir+'/features/review.feature',existent_features=mention_features)
mention_features_1=get_features(feature_file=base_dir+'/features/mention_1.feature',existent_features=review_featuers)
collection=Connection().jd.test_users
balance_params=get_balance_params(attribute,collection)
print 'Balance params: ',balance_params
bar=progress_bar(collection.count())
fout=open(RAW_DATA_DIR+'iterate_label2trainset/%s_test.data'%attribute,'w')
uid_output=open(RAW_DATA_DIR+'iterate_label2trainset/%s_test_uids.data'%attribute,'w')
for index,user in enumerate(collection.find()):
try:
label=user['profile'][attribute].index(1)
except Exception as e:
continue
if random.random()>balance_params[label]:
continue
'============'
x=[]
#user['products']=[]
for f,v in Counter(user['products']).items():
if f not in product_features:
continue
x.append((product_features[f],v))
#user['mentions']={}
for f,v in user['mentions'].items():
if f not in mention_features:
continue
x.append((mention_features[f],v))
#user['review']=[]
for f,v in Counter(user['review']).items():
if f not in review_featuers:
continue
x.append((review_featuers[f],v))
#user['mentions_1_1']={}
for f,v in user['mentions_1_1'].items():
f=f+'_1'
if f not in mention_features_1:
continue
x.append((mention_features_1[f],v))
x=sorted(x,key=lambda d:d[0])
str_x=' '.join(map(lambda f:'%s:%f'%f,x))
fout.write('%d %s\n'%(label,str_x))
uid_output.write('%s\n'%(user['_id']))
bar.draw(index+1)
def construct(attribute,training_count):
construct_train_set(attribute,training_count)
construct_test_set(attribute)
if __name__=='__main__':
construct_test_set('gender')