Source code for abydos.tokenizer._c_or_v_cluster

# Copyright 2019-2020 by Christopher C. Little.
# This file is part of Abydos.
#
# Abydos is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Abydos is distributed in the hope that it will be useful,
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# GNU General Public License for more details.
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"""abydos.tokenizer._c_or_v_cluster.

Consonant or vowel cluster tokenizer.

This tokenizer first performs wordpunct tokenization, so words are split into
separate units and non-letter characters are added as their own units.
Following this, words are further divided into strings of consonants only and
strings of vowels only.
"""

import re
import unicodedata

from typing import Callable, Optional, Set, Union

from ._tokenizer import _Tokenizer

__all__ = ['COrVClusterTokenizer']


[docs] class COrVClusterTokenizer(_Tokenizer): """A C- or V-cluster tokenizer. .. versionadded:: 0.4.0 """ def __init__( self, scaler: Optional[Union[str, Callable[[float], float]]] = None, consonants: Optional[Set[str]] = None, vowels: Optional[Set[str]] = None, ) -> None: """Initialize tokenizer. Parameters ---------- scaler : None, str, or function A scaling function for the Counter: - None : no scaling - 'set' : All non-zero values are set to 1. - 'length' : Each token has weight equal to its length. - 'length-log' : Each token has weight equal to the log of its length + 1. - 'length-exp' : Each token has weight equal to e raised to its length. - a callable function : The function is applied to each value in the Counter. Some useful functions include math.exp, math.log1p, math.sqrt, and indexes into interesting integer sequences such as the Fibonacci sequence. consonants : None or set(str) The set of characters to treat as consonants vowels : None or set(str) The set of characters to treat as vowels .. versionadded:: 0.4.0 """ super(COrVClusterTokenizer, self).__init__(scaler=scaler) if consonants: self._consonants = consonants else: self._consonants = set('bcdfghjklmnpqrstvwxzßBCDFGHJKLMNPQRSTVWXZ') if vowels: self._vowels = vowels else: self._vowels = set('aeiouyAEIOUY') self._regexp = re.compile(r'\w+|[^\w\s]+', flags=0)
[docs] def tokenize(self, string: str) -> 'COrVClusterTokenizer': """Tokenize the term and store it. The tokenized term is stored as an ordered list and as a Counter object. Parameters ---------- string : str The string to tokenize Examples -------- >>> COrVClusterTokenizer().tokenize('seven-twelfths') COrVClusterTokenizer({'s': 1, 'e': 3, 'v': 1, 'n': 1, '-': 1, 'tw': 1, 'lfths': 1}) >>> COrVClusterTokenizer().tokenize('character') COrVClusterTokenizer({'ch': 1, 'a': 2, 'r': 2, 'ct': 1, 'e': 1}) .. versionadded:: 0.4.0 """ self._string = string self._ordered_tokens = [] token_list = self._regexp.findall(self._string) for token in token_list: if ( token[0] not in self._consonants and token[0] not in self._vowels ): self._ordered_tokens.append(token) else: token = unicodedata.normalize('NFD', token) mode = 0 # 0 = starting mode, 1 = cons, 2 = vowels new_token = '' # noqa: S105 for char in token: if char in self._consonants: if mode == 2: self._ordered_tokens.append(new_token) new_token = char else: new_token += char mode = 1 elif char in self._vowels: if mode == 1: self._ordered_tokens.append(new_token) new_token = char else: new_token += char mode = 2 else: # This should cover combining marks, marks, etc. new_token += char self._ordered_tokens.append(new_token) self._ordered_tokens = [ unicodedata.normalize('NFC', token) for token in self._ordered_tokens ] self._scale_and_counterize() return self
if __name__ == '__main__': import doctest doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)