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Nominatim/nominatim/tokenizer/token_analysis/generic.py
2022-01-18 11:09:21 +01:00

109 lines
3.6 KiB
Python

# SPDX-License-Identifier: GPL-2.0-only
#
# This file is part of Nominatim. (https://nominatim.org)
#
# Copyright (C) 2022 by the Nominatim developer community.
# For a full list of authors see the git log.
"""
Generic processor for names that creates abbreviation variants.
"""
import itertools
import datrie
from nominatim.tokenizer.token_analysis.config_variants import get_variant_config
### Configuration section
def configure(rules, normalization_rules):
""" Extract and preprocess the configuration for this module.
"""
config = {}
config['replacements'], config['chars'] = get_variant_config(rules.get('variants'),
normalization_rules)
config['variant_only'] = rules.get('mode', '') == 'variant-only'
return config
### Analysis section
def create(transliterator, config):
""" Create a new token analysis instance for this module.
"""
return GenericTokenAnalysis(transliterator, config)
class GenericTokenAnalysis:
""" Collects the different transformation rules for normalisation of names
and provides the functions to apply the transformations.
"""
def __init__(self, to_ascii, config):
self.to_ascii = to_ascii
self.variant_only = config['variant_only']
# Set up datrie
if config['replacements']:
self.replacements = datrie.Trie(config['chars'])
for src, repllist in config['replacements']:
self.replacements[src] = repllist
else:
self.replacements = None
def get_variants_ascii(self, norm_name):
""" Compute the spelling variants for the given normalized name
and transliterate the result.
"""
results = set()
for variant in self._generate_word_variants(norm_name):
if not self.variant_only or variant.strip() != norm_name:
trans_name = self.to_ascii.transliterate(variant).strip()
if trans_name:
results.add(trans_name)
return list(results)
def _generate_word_variants(self, norm_name):
baseform = '^ ' + norm_name + ' ^'
baselen = len(baseform)
partials = ['']
startpos = 0
if self.replacements is not None:
pos = 0
force_space = False
while pos < baselen:
full, repl = self.replacements.longest_prefix_item(baseform[pos:],
(None, None))
if full is not None:
done = baseform[startpos:pos]
partials = [v + done + r
for v, r in itertools.product(partials, repl)
if not force_space or r.startswith(' ')]
if len(partials) > 128:
# If too many variants are produced, they are unlikely
# to be helpful. Only use the original term.
startpos = 0
break
startpos = pos + len(full)
if full[-1] == ' ':
startpos -= 1
force_space = True
pos = startpos
else:
pos += 1
force_space = False
# No variants detected? Fast return.
if startpos == 0:
return (norm_name, )
if startpos < baselen:
return (part[1:] + baseform[startpos:-1] for part in partials)
return (part[1:-1] for part in partials)