from TestDocument import TestDocument
from UnlabelledDoc import UnlabelledDoc
import pickle
if __name__ == '__main__':
reload(sys)
sys.setdefaultencoding('utf8')
# Parse the configuration
config = cp.RawConfigParser()
config.read('config.py')
trainfile = config.get('init', 'trainfile')
content = open(trainfile).read()
doc = TrainDocument(content)
sent = doc.get_sentences()[0]
print sent.pos_tags
pickle.dump(doc,open('TrainDoc.pickle','w'))
pickle.dump(doc.sentences,open('Sentences.pickle','w'))
# # Open test documents as wel
testfile = config.get('init', 'testfile')
testcontent = open(testfile).read()
testdoc = TestDocument(testcontent)
pickle.dump(testdoc.sentences, open('SentencesTest.pickle','w'))
# IF lu learning is enabled, then read the unlabelled corpus also
lu = int(config.get('LU','lu'))
print 'LU learning configuration : ' + str(lu)
__author__ = 'vignesh'
from TrainDocument import TrainDocument
f2 = '/Users/vignesh/Documents/Phd/Courses/fall15/CS521SNLP/ClassProject/corpus/kappa/sahisnukappafull.txt'
c2 = open(f2).read()
doc2 = TrainDocument(c2)
sent2 = doc2.get_sentences()
labels2 = []
for i in range(len(sent2)):
l2 = sent2[i].labels
labels2 += l2
print len(labels2)
# write them
outfile = open('labels2forkappa.txt','w')
for i in range(len(labels2)):
outfile.write(labels2[i])
outfile.write('\n')
outfile.close()
