def setUp(self):
self.train, self.test = corpus.make_train_test_split("mySeed")
self.realTest = corpus.iter_test_corpus()
self.corpus = buildVocabulary(getPhrases(self.train + self.test + self.realTest))
# self.training = buildVocabulary(getPhrases(self.train))
# self.testing = buildVocabulary(getPhrases(self.test))
self.size = 50
def test_iter_test_corpus_simple(self):
test = list(corpus.iter_test_corpus())
self.assertEqual(len(test), 4)
self.assertEqual(set("1 99 100 123".split()), set(x.phraseid for x in test))
self.assertEqual(set("4 7 8 9".split()), set(x.sentenceid for x in test))
self.assertIn("yo mama so fat", [x.phrase for x in test])
self.assertEqual(set([None]), set(x.sentiment for x in test))
def setUp(self):
self.train, self.test = corpus.make_train_test_split("mySeed")
self.realTest = corpus.iter_test_corpus()
self.corpus = buildVocabulary(
getPhrases(self.train + self.test + self.realTest))
# self.training = buildVocabulary(getPhrases(self.train))
# self.testing = buildVocabulary(getPhrases(self.test))
self.size = 50
def test_iter_test_corpus_simple(self):
test = list(corpus.iter_test_corpus())
self.assertEqual(len(test), 4)
self.assertEqual(set("1 99 100 123".split()),
set(x.phraseid for x in test))
self.assertEqual(set("4 7 8 9".split()),
set(x.sentenceid for x in test))
self.assertIn("yo mama so fat", [x.phrase for x in test])
self.assertEqual(set([None]), set(x.sentiment for x in test))
if __name__ == "__main__":
import argparse
import json
import csv
import sys
from samr.corpus import iter_corpus, iter_test_corpus
from samr.predictor import PhraseSentimentPredictor
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("filename")
config = parser.parse_args()
config = json.load(open(config.filename))
t1=int(round(time.time() *1000))
predictor = PhraseSentimentPredictor(**config)
predictor.fit(list(iter_corpus()))
t2=int(round(time.time() *1000))
test = list(iter_test_corpus())
prediction = predictor.predict2(test)
t3=int(round(time.time() *1000))
print t2-t1, t3-t2
writer = csv.writer(sys.stdout)
writer.writerow(("PhraseId", "Sentiment"))
for datapoint, sentiment in zip(test, prediction):
writer.writerow((datapoint.phraseid, sentiment))
value = float(value)
except ValueError:
pass
new[key] = value
return new
if __name__ == "__main__":
import argparse
import json
import csv
import sys
from samr.corpus import iter_corpus, iter_test_corpus
from samr.predictor import PhraseSentimentPredictor
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("filename")
config = parser.parse_args()
config = json.load(open(config.filename))
predictor = PhraseSentimentPredictor(**config)
predictor.fit(list(iter_corpus()))
test = list(iter_test_corpus())
prediction = predictor.predict(test)
writer = csv.writer(sys.stdout)
writer.writerow(("PhraseId", "Sentiment"))
for datapoint, sentiment in zip(test, prediction):
writer.writerow((datapoint.phraseid, sentiment))
