def compute(filename, topics=2):
doc = Document(LDATester.PATH + filename + ".txt")
gold_doc = Document(LDATester.PATH + filename + "_gold.txt")
topics = len(gold_doc.sentences)
ldaSummary = LDATester.getSummary(doc, topics)
# print ldaSummary
return BLEU.computeNormalize(gold_doc.document, ldaSummary, ignore=True)
def compute(filename):
gold_doc = Document(LDATester.PATH + filename + "_gold.txt")
doc = Document(LDATester.PATH + filename + ".txt")
## Get random summary
indices = [x for x in range(len(doc.sentences))]
random.shuffle(indices)
indices = indices[0 : len(gold_doc.sentences)]
sentences = [doc.sentences[i] for i in indices]
calibration = [doc.getSentenceOrginal(sentence) for sentence in sentences]
calibration = " ".join(calibration)
return BLEU.computeNormalize(gold_doc.document, calibration)
def compute(filename):
doc = Document(FrequencyTester.PATH + filename + ".txt")
gold_doc = Document(FrequencyTester.PATH + filename + "_gold.txt")
freqSummary = FrequencyTester.getSummary(doc, len(gold_doc.sentences))
return BLEU.computeNormalize(gold_doc.document, freqSummary, ignore=True)
