from Evaluation import *
from DictRelevant import *
import time
startPoint=[".A",".T",".W",".B"]
fileDoc="cisi/CISI.ALL"
fileStopList="cacm/common_words"
fileQuerry="cisi/CISI.QRY"
fileRel='cisi/CISI.REL'
sim_func_dict={1:'product',2:'product_log',3:'cosinus',4:'cosinus_log',5:'langue',6:'langue_corr',7:'BM25'}
ind_sim_func=4
if __name__=="__main__":
db= DictBase(startPoint)
db.execute(fileDoc, fileStopList)
# print db.word_dict['recognition'] #2634 OK
#print db.tf_mat[2634] #OK
'''
{396: 1, 653: 1, 1426: 1, 1044: 1, 89: 1, 474: 2, 927: 1, 1458: 2, 797: 2, 48: 1, 1202: 2, 94: 1, 568: 2, 1337: 1, 799: 1, 1341: 2, 908: 1, 1421: 1, 601: 1, 858: 1, 861: 1, 990: 1, 863: 1, 102: 2, 108: 1, 1134: 1, 495: 1, 241: 1, 890: 3, 1403: 1, 895: 1}
'''
qr=Querry(startPoint,db.word_dict)
qr.readQuerry(fileQuerry)
sim =similarity(db, qr.querry_dict,ind_sim_func)
dr=DictRelevant()
dr.readRelevantQuerry(fileRel)
print "finish readRel Dictionary"
sim_func=sim_func_dict[ind_sim_func]
eva= Evaluation(db, dr, -1, getattr(sim,sim_func))
#eva= Evaluation(db, dr, 100, sim.cosinus )
print eva.mean_avg_prec()
