<commit_before>from nltk.probability import FreqDist


class IndexFreqDist(FreqDist):

    def __init__(self, samples=None):
        raise NotImplementedError()

    def inc(self, sample, count=1):
        raise NotImplementedError()

    def __setitem__(self, sample, value):
        raise NotImplementedError()

    def N(self):
        raise NotImplementedError()

    def B(self):
        raise NotImplementedError()

    def samples(self):
        raise NotImplementedError()

    def hapaxes(self):
        raise NotImplementedError()

    def Nr(self, r, bins=None):
        raise NotImplementedError()

    def _cache_Nr_values(self):
        raise NotImplementedError()

    def _cumulative_frequencies(self, samples=None):
        raise NotImplementedError()

    def freq(self, sample):
        raise NotImplementedError()

    def max(self):
        raise NotImplementedError()

    def plot(self, *args, **kwargs):
        raise NotImplementedError()

    def tabulate(self, *args, **kwargs):
        raise NotImplementedError()

    def _sort_keys_by_value(self):
        raise NotImplementedError()

    def keys(self):
        raise NotImplementedError()

    def values(self):
        raise NotImplementedError()

    def items(self):
        raise NotImplementedError()

    def __iter__(self):
        raise NotImplementedError()

    def iterkeys(self):
        raise NotImplementedError()

    def itervalues(self):
        raise NotImplementedError()

    def iteritems(self):<commit_msg>Implement N, B, Nr, hapxes, max, freq for IndexFreqDist<commit_after>from nltk.probability import FreqDist


class IndexFreqDist(FreqDist):

    def __init__(self, samples=None):
        raise NotImplementedError()

    def inc(self, sample, count=1):
        raise NotImplementedError()

    def __setitem__(self, sample, value):
        raise NotImplementedError()

    def N(self):
        return sum(map(lambda term: term.term_frequency, self.index.objects))

    def B(self):
        return self.index.objects.count()

    def samples(self):
        raise NotImplementedError()

    def hapaxes(self):
        return self.Nr(1)

    def Nr(self, r, bins=None):
        if r < 0: raise IndexError, 'FreqDist.Nr(): r must be non-negative'

        # Special case for Nr(0):
        if r == 0:
            if bins is None: return 0
            else: return bins-self.B()

        return self.index.objects.get(term_frequency=r).count()

    def _cache_Nr_values(self):
        raise NotImplementedError()

    def _cumulative_frequencies(self, samples=None):
        raise NotImplementedError()

    def freq(self, sample):
        N = self.N()
        if N < 1:
            return 0
        return float(self[sample]) / N

    def max(self):
        max_token = self.index.objects.order_by("-term_frequency").first()
        return (max_token.token, max_token.term_frequency)

    def plot(self, *args, **kwargs):
        raise NotImplementedError()

    def tabulate(self, *args, **kwargs):
        raise NotImplementedError()

    def _sort_keys_by_value(self):
        raise NotImplementedError()

    def keys(self):
        raise NotImplementedError()

    def values(self):
        raise NotImplementedError()

    def items(self):
        raise NotImplementedError()

    def __iter__(self):
        raise NotImplementedError()

    def iterkeys(self):
        raise NotImplementedError()

    def itervalues(self):
        raise NotImplementedError()

    def iteritems(self):
{'fraction_non_alphanumeric': 0.09894195024306549, 'fraction_numerical': 0.002573634543894767, 'mean_word_length': 2.7371794871794872, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '519193', 'n_tokens_mistral': 1075, 'n_tokens_neox': 1018, 'n_words': 257}