# Copyright 2018-2020 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,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Abydos. If not, see <http://www.gnu.org/licenses/>.
"""abydos.tokenizer._nltk.
NLTK tokenizer wrapper class
"""
from inspect import isclass
from ._tokenizer import _Tokenizer
[docs]class NLTKTokenizer(_Tokenizer):
"""NLTK tokenizer wrapper class.
.. versionadded:: 0.4.0
"""
def __init__(self, nltk_tokenizer=None, scaler=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.
nltk_tokenizer : Object
An instantiated tokenizer from NLTK.
.. versionadded:: 0.4.0
"""
super(NLTKTokenizer, self).__init__(scaler)
if (
hasattr(nltk_tokenizer, 'tokenize')
and 'nltk.tokenize' in nltk_tokenizer.__module__
):
if isclass(nltk_tokenizer):
self.nltk_tokenizer = nltk_tokenizer()
else:
self.nltk_tokenizer = nltk_tokenizer
else:
raise TypeError(
'nltk_tokenizer must be an initialized tokenizer from the'
+ ' NLTK package (e.g. TweetTokenizer()).'
)
[docs] def tokenize(self, string):
"""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
--------
>>> from nltk.tokenize.casual import TweetTokenizer
>>> nltk_tok = TweetTokenizer()
>>> NLTKTokenizer(nltk_tokenizer=nltk_tok).tokenize(
... '.@Twitter Today is #lit!')
NLTKTokenizer({'.': 1, '@Twitter': 1, 'Today': 1, 'is': 1, '#lit': 1,
'!': 1})
.. versionadded:: 0.4.0
"""
self._string = string
self._ordered_tokens = self.nltk_tokenizer.tokenize(string)
super(NLTKTokenizer, self).tokenize()
return self
if __name__ == '__main__':
import doctest
doctest.testmod(optionflags=doctest.NORMALIZE_WHITESPACE)