def test_corpus(self):
with open("../data/pt_BR/nnp") as f:
nnp = [line.rstrip() for line in f.readlines()]
with open("../data/pt_BR/terms") as f:
terms = [line.rstrip() for line in f.readlines()]
with open("../data/pt_BR/patterns") as f:
patterns = [line.rstrip() for line in f.readlines()]
data = LoadData(['../corpus/sel1.csv', '../corpus/sel2.csv']).load()
p = PreProcessing(nnp, terms, patterns)
tokens = []
for d in data.values():
tokens += p.clean_and_stem(d)
bow, bow_features_names = p.build_bow(tokens)
dist = np.sum(bow.toarray(), axis=0)
tbow = {}
for term, count in zip(bow_features_names, dist):
tbow[term] = count
import operator
with open("bow", "w") as f:
f.write(str(len(tbow)))
f.write(
str(
sorted(tbow.items(),
key=operator.itemgetter(1),
reverse=True)))
terms = p.compute_tfidf(data.values(), eliminate_zeros=True)
with open("terms", "w") as f:
f.write(str(terms))
def test(self):
p = PreProcessing([], [], [])
cts = machado.fileids()[:5]
tokens = []
for c in cts:
text = machado.raw(c)
tokens += p.clean_and_stem(text)
bow, bow_features_names = p.build_bow(tokens)
dist = np.sum(bow.toarray(), axis=0)
tbow = {}
for term, count in zip(bow_features_names, dist):
tbow[term] = count
import operator
print sorted(tbow.items(), key=operator.itemgetter(1), reverse=True)
texts = {}
for c in cts:
text = machado.raw(c)
texts[c] = text
terms = p.compute_tfidf(texts.values(), top_n=10, eliminate_zeros=True)
print terms