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