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How to use running_count method in lisa

Best Python code snippet using lisa_python

encode_string.py

Source:encode_string.py

1import re2import string3import unicodedata4from pathlib import Path5from collections import Counter6from articlenizer import sentenize7def handle_unicode_characters(s):8    """Handle unicode characters appearing in string. Some do actually contain valuable information for NLP applications. But there is also a lot of "unnecessary" unicode in scientific texts (at least from an Software-NER perspective). It can either be dropped, or different codes can be summarized by one characters. 9    Args:10        s (string): string to transform11    Returns:12        string: unicode 'normalized' string13    """14    dropped_char_indices = []15    running_count = 016    out_s = ''17    for char in s:18        if re.match(r"[A-Za-z0-9\s]", char) is not None or char in string.punctuation:19            # keep "normal" chars20            out_s += char21            running_count += 122        else:23            # here we will deal with unicode24            if char in ['Â©', 'â¢', 'Â®']:25                # 'TradeMarks' are tricky but often used to indicate external equipment in studies26                out_s += 'â¢'27                running_count += 128                continue29            if char == 'Â°':30                # Temperatures are almost always indicated by Â°31                out_s += char32                running_count += 133                continue34            # some unicodes are combined and based on 'normal' characters -> we want to keep the base characters, e.g. Ã¡ -> a35            unicode_matched = False36            #char_37            u_map = unicodedata.decomposition(char)38            if u_map and len(u_map) > 1:39                split_codes = [code for code in u_map.split() if not re.match(r'<.*>', code)]40                for code in split_codes:41                    code_char = chr(int(code, 16))42                    if re.match(r'[a-zA-Z]', code_char):43                        out_s += code_char # TODO44                        unicode_matched = True45                        running_count += 146                        break47            if unicode_matched: 48                continue49            # normalized unicode for everything else just to be save.. 50            char = unicodedata.normalize('NFC', char)51            if len(char) > 1:52                print(RuntimeWarning("Unkown unicode character with length > 1: {} -- ignored".format(char)))53                continue54            # we want to keep basic greek letters no matter what55            if char == 'Âµ': # yes, they are actually different: this is the 'micro sign'56                char = 'Î¼' # this the greek letter..57            if ( ord(char) >= 945 and ord(char) <= 970 ) or ( ord(char) >= 913 and ord(char) <= 938 ):58                out_s += char59                running_count += 160                continue61            # the rest is based on unicode categories some of which are considered important and others are not62            category = unicodedata.category(char)63            if category == 'Pi':64                if  ord(char) == 8216 or ord(char) == 8219:65                    out_s += char66                else:67                    out_s += 'â'68                running_count += 169            elif category == 'Pf':70                if ord(char) == 8217:71                    out_s += 'â'72                else:73                    out_s += 'â'74                running_count += 175            elif category == 'Pd':76                char = '-'77                out_s += char78                running_count += 179            elif category == 'Sc':80                out_s += char81                running_count += 182            elif category in ['Pe', 'Cf', 'Ps', 'So', 'Sk', 'No']:83                dropped_char_indices.append([running_count, char])84                running_count += 185            elif category == 'Lm':86                if ord(char) >= 697 and ord(char) <= 719:87                    char ="'"88                    running_count += 189                    out_s += char90            elif category in ['Lu', 'Ll', 'Po']:91                # keep92                out_s += char93                running_count += 194            elif category == 'Sm':95                # Mathsymbols, TODO: handle them better?96                out_s += char97                running_count += 198                unicode_in_sent = True99            else:100                #print("Encountered an unhandled unicode character: {} - DROPPED".format(char))101                dropped_char_indices.append([running_count, char])102                running_count += 1103    ...

counting.py

Source:counting.py

1from kairotic.elements import DECK_SIZE, SUITS, CARD_VALUES2class Count:3    def __init__(self):4        self.cards_seen = 05        self._n_decks = None6    @property7    def n_decks(self):8        if self._n_decks is None:9            raise UnboundLocalError("Count not attached to a Shoe")10        else:11            return self._n_decks12    def reset(self):13        self.cards_seen = 014    def update(self, card):15        self.cards_seen += 116    @property17    def half_decks_seen(self):18        return round(self.cards_seen / (DECK_SIZE / 2))19    @property20    def decks_rem(self):21        return max(self.n_decks - self.half_decks_seen / 2, .5)22class ScalarCount(Count):23    def __init__(self):24        super().__init__()25        self.running_count = 026    def reset(self):27        super().reset()28        self.running_count = 029    @property30    def true_count(self):31        return round(self.running_count / self.decks_rem)32class HiLo(ScalarCount):33    name = 'HiLo'34    def update(self, card):35        super().update(card)36        if card.value in ['2', '3', '4', '5', '6']:37            self.running_count += 138        elif card.value in ['10', 'J', 'Q', 'K', 'A']:39            self.running_count -= 140class VectorCount(Count):41    def __init__(self):42        super().__init__()43        self.running_count = dict()44    def reset(self):45        self.running_count = {key: 0 for key in self.running_count}46    @property47    def true_count(self):48        return {key: round(count / self.decks_rem) for key, count in self.running_count.items()}49class PerfectValueCount(VectorCount):50    name = 'Perfect Value Count'51    def __init__(self):52        super().__init__()53        self.running_count = {v: 0 for v in CARD_VALUES}54    def update(self, card):55        super().update(card)...

reducer_stat.py

Source:reducer_stat.py

1#!/usr/bin/python32import sys3def update_mean(running_mean, running_count, batch_mean, batch_count):4    batch_mean = (running_mean * running_count + batch_mean * batch_count) / (running_count + batch_count)5    batch_count = running_count + batch_count6    return batch_mean, batch_count7def update_var(running_mean, running_var, running_count, batch_mean, batch_var, batch_count):8    var = (running_var * running_count + batch_var * batch_count) / (running_count + batch_count)9    var += running_count * ((running_mean - batch_mean) / (running_count + batch_count)) ** 210    return var11if __name__ == '__main__':12    global_mean = 013    global_count = 014    global_var = 015    for i, raw_line in enumerate(sys.stdin):16        line = raw_line.strip()17        loc_mean, loc_var, loc_count = list(map(float, line.split('\t')))18        new_mean, new_count = update_mean(global_mean, global_count, loc_mean, loc_count)19        global_var = update_var(global_mean, global_var, global_count, loc_mean, loc_var, loc_count)20        global_mean, global_count = new_mean, new_count21    print('map_reduce mean: {}'.format(global_mean))...

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