from UserAnalyser import *
from TimeAnalyser import *
import math
import sys
import pickle
#Frequency over the common
if __name__ == "__main__":
keywords = open(sys.argv[2], 'r').readline().strip("\n").split(",")
userstream = Tweetstream(jsonfilee=sys.argv[3],
jsonformat=False,
keywords=keywords)
topicstream = Tweetstream(jsonfilee=sys.argv[1],
jsonformat=False,
keywords=keywords)
ua = UserAnalyser(sys.argv[4], keywords=keywords)
ua.load_usersVectors()
ua.load_idf()
ua.load_usersScore()
rank = dict()
# normalizar pelo numero de kw no topic vector
for t in userstream:
score = 0.0
if t['user_id'] in ua.usersScore:
rank[t['id']] = ua.usersScore[t['user_id']]
else:
rank[t['id']] = 0
#prinit score, nwindow
pickle.dump(rank, open(sys.argv[4] + "_rank_USER_noNorm.pick", 'w'),
pickle.HIGHEST_PROTOCOL)
from UserAnalyser import *
from Tweetstream import *
import sys
l = [
119372344, 44175574, 126477271, 252422812, 26299276, 560049049, 388473707,
1217370608, 842373594, 139960190, 45584847, 63573676, 274629513, 94176291,
68545824, 98997286, 139177492, 14201313, 118852899, 269567535
]
if __name__ == "__main__":
keywords = open(sys.argv[3], 'r').readline().strip("\n").split(",")
ts = Tweetstream(jsonfilee=sys.argv[2],
jsonformat=False,
keywords=keywords)
ua = UserAnalyser(sys.argv[1], tweetstream=ts)
ua.compute_usersVectors()
ua.compute_idf()
ua.compute_usersScore()
# for u in l:
# print ua.usersVectors[u]
# print ua.usersScore[u]