def demo(scorer=None, compare_scorer=None):
    """Finds bigram collocations in the files of the WebText corpus."""
    from nltk.metrics import BigramAssocMeasures, spearman_correlation, ranks_from_scores

    if scorer is None:
        scorer = BigramAssocMeasures.likelihood_ratio
    if compare_scorer is None:
        compare_scorer = BigramAssocMeasures.raw_freq

    from nltk.corpus import stopwords, webtext

    ignored_words = stopwords.words('english')
    word_filter = lambda w: 3 < len(w) or w.lower() in ignored_words

    for file in webtext.fileids():
        words = [word.lower()
                 for word in webtext.words(file)]

        cf = BigramCollocationFinder.from_words(words)
        cf.apply_freq_filter(3)
        cf.apply_word_filter(word_filter)

        corr = spearman_correlation(ranks_from_scores(cf.score_ngrams(scorer)),
                                    ranks_from_scores(cf.score_ngrams(compare_scorer)))
        print(file)
        print('\t', [' '.join(tup) for tup in cf.nbest(scorer, 15)])
        print('\t Correlation to %s: %0.4f' % (compare_scorer.__name__, corr))

# Slows down loading too much
# bigram_measures = BigramAssocMeasures()
# trigram_measures = TrigramAssocMeasures()
dataset/ETHPy150Open nltk/nltk/nltk/collocations.py/demo/swapped operands of `<`