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filter based on number of sentence added #64

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filter based on number of sentence added #64

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18 changes: 11 additions & 7 deletions summa/summarizer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,21 +95,25 @@ def _get_sentences_with_word_count(sentences, words):
return selected_sentences


def _extract_most_important_sentences(sentences, ratio, words):
def _extract_most_important_sentences(sentences, ratio, words, sen_nb):
sentences.sort(key=lambda s: s.score, reverse=True)

# If no "words" option is selected, the number of sentences is
# reduced by the provided ratio.
if words is None:
# If no "words" option is selected and no "sen_nb" option is selected, the
# number of sentences is reduced by the provided ratio.
if words is None and sen_nb is None:
length = len(sentences) * ratio
return sentences[:int(length)]

# Else, the ratio is ignored.
# Else the number of sentence is used to select the top K sentences
elif sen_nb is not None:
return sentences[:sen_nb]

# Else, the number of words is used to select the best matching sentences.
else:
return _get_sentences_with_word_count(sentences, words)


def summarize(text, ratio=0.2, words=None, language="english", split=False, scores=False, additional_stopwords=None):
def summarize(text, ratio=0.2, words=None, language="english", split=False, scores=False, additional_stopwords=None, sen_nb=None):
if not isinstance(text, str):
raise ValueError("Text parameter must be a Unicode object (str)!")

Expand All @@ -134,7 +138,7 @@ def summarize(text, ratio=0.2, words=None, language="english", split=False, scor
_add_scores_to_sentences(sentences, pagerank_scores)

# Extracts the most important sentences with the selected criterion.
extracted_sentences = _extract_most_important_sentences(sentences, ratio, words)
extracted_sentences = _extract_most_important_sentences(sentences, ratio, words, sen_nb)

# Sorts the extracted sentences by apparition order in the original text.
extracted_sentences.sort(key=lambda s: s.index)
Expand Down