# 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.phonetic._statistics_canada.
Statistics Canada phonetic encoding
"""
from unicodedata import normalize as unicode_normalize
from ._phonetic import _Phonetic
__all__ = ['StatisticsCanada']
[docs]class StatisticsCanada(_Phonetic):
"""Statistics Canada code.
The original description of this algorithm could not be located, and
may only have been specified in an unpublished TR. The coding does not
appear to be in use by Statistics Canada any longer. In its place, this is
an implementation of the "Census modified Statistics Canada name coding
procedure".
The modified version of this algorithm is described in Appendix B of
:cite:`Moore:1977`.
.. versionadded:: 0.3.6
"""
def __init__(self, max_length: int = 4) -> None:
"""Initialize StatisticsCanada instance.
Parameters
----------
max_length : int
The length of the code returned (defaults to 4)
.. versionadded:: 0.4.0
"""
self._max_length = max_length
[docs] def encode(self, word: str) -> str:
"""Return the Statistics Canada code for a word.
Parameters
----------
word : str
The word to transform
Returns
-------
str
The Statistics Canada name code value
Examples
--------
>>> pe = StatisticsCanada()
>>> pe.encode('Christopher')
'CHRS'
>>> pe.encode('Niall')
'NL'
>>> pe.encode('Smith')
'SMTH'
>>> pe.encode('Schmidt')
'SCHM'
.. versionadded:: 0.3.0
.. versionchanged:: 0.3.6
Encapsulated in class
"""
# uppercase, normalize, decompose, and filter non-A-Z out
word = unicode_normalize('NFKD', word.upper())
word = ''.join(c for c in word if c in self._uc_set)
if not word:
return ''
code = word[1:]
for vowel in self._uc_vy_set:
code = code.replace(vowel, '')
code = word[0] + code
code = self._delete_consecutive_repeats(code)
code = code.replace(' ', '')
return code[: self._max_length]
if __name__ == '__main__':
import doctest
doctest.testmod()