spaCy/spacy/tokens/morphanalysis.pyx
2023-09-28 17:09:41 +02:00

93 lines
2.9 KiB
Cython

# cython: profile=False
cimport numpy as np
from libc.string cimport memset
from ..errors import Errors
from ..morphology import Morphology
from ..morphology cimport check_feature, get_by_field, list_features
from ..typedefs cimport attr_t, hash_t
from ..vocab cimport Vocab
cdef class MorphAnalysis:
"""Control access to morphological features for a token."""
def __init__(self, Vocab vocab, features=dict()):
self.vocab = vocab
self.key = self.vocab.morphology.add(features)
analysis = <const MorphAnalysisC*>self.vocab.morphology.tags.get(self.key)
if analysis is not NULL:
self.c = analysis[0]
else:
memset(&self.c, 0, sizeof(self.c))
@classmethod
def from_id(cls, Vocab vocab, hash_t key):
"""Create a morphological analysis from a given ID."""
cdef MorphAnalysis morph = MorphAnalysis.__new__(MorphAnalysis, vocab)
morph.vocab = vocab
morph.key = key
analysis = <const MorphAnalysisC*>vocab.morphology.tags.get(key)
if analysis is not NULL:
morph.c = analysis[0]
else:
memset(&morph.c, 0, sizeof(morph.c))
return morph
def __contains__(self, feature):
"""Test whether the morphological analysis contains some feature."""
cdef attr_t feat_id = self.vocab.strings.as_int(feature)
return check_feature(&self.c, feat_id)
def __iter__(self):
"""Iterate over the features in the analysis."""
cdef attr_t feature
for feature in list_features(&self.c):
yield self.vocab.strings[feature]
def __len__(self):
"""The number of features in the analysis."""
return self.c.length
def __hash__(self):
return self.key
def __eq__(self, other):
if isinstance(other, str):
raise ValueError(Errors.E977)
return self.key == other.key
def __ne__(self, other):
return self.key != other.key
def get(self, field, default=None):
"""Retrieve feature values by field."""
cdef attr_t field_id = self.vocab.strings.as_int(field)
cdef np.ndarray results = get_by_field(&self.c, field_id)
if len(results) == 0:
if default is None:
default = []
return default
features = [self.vocab.strings[result] for result in results]
return [f.split(Morphology.FIELD_SEP)[1] for f in features]
def to_json(self):
"""Produce a json serializable representation as a UD FEATS-style
string.
"""
morph_string = self.vocab.strings[self.c.key]
if morph_string == self.vocab.morphology.EMPTY_MORPH:
return ""
return morph_string
def to_dict(self):
"""Produce a dict representation.
"""
return self.vocab.morphology.feats_to_dict(self.to_json())
def __str__(self):
return self.to_json()
def __repr__(self):
return self.to_json()