spaCy/spacy/tokens/morphanalysis.pxd

from ..structs cimport MorphAnalysisC
from ..typedefs cimport hash_t
from ..vocab cimport Vocab


cdef class MorphAnalysis:
    cdef readonly Vocab vocab
    cdef readonly hash_t key
    cdef MorphAnalysisC c
Add header for morphanalysis 2019-03-07 16:24:57 +00:00			`from ..structs cimport MorphAnalysisC`
Configure isort to use the Black profile, recursively isort the `spacy` module (#12721) * Use isort with Black profile * isort all the things * Fix import cycles as a result of import sorting * Add DOCBIN_ALL_ATTRS type definition * Add isort to requirements * Remove isort from build dependencies check * Typo 2023-06-14 15:48:41 +00:00			`from ..typedefs cimport hash_t`
			`from ..vocab cimport Vocab`
Add header for morphanalysis 2019-03-07 16:24:57 +00:00

			`cdef class MorphAnalysis:`
			`cdef readonly Vocab vocab`
Modify morphology to support arbitrary features (#4932) * Restructure tag maps for MorphAnalysis changes Prepare tag maps for upcoming MorphAnalysis changes that allow arbritrary features. * Use default tag map rather than duplicating for ca / uk / vi * Import tag map into defaults for ga * Modify tag maps so all morphological fields and features are strings * Move features from `"Other"` to the top level * Rewrite tuples as strings separated by `","` * Rewrite morph symbols for fr lemmatizer as strings * Export MorphAnalysis under spacy.tokens * Modify morphology to support arbitrary features Modify `Morphology` and `MorphAnalysis` so that arbitrary features are supported. * Modify `MorphAnalysisC` so that it can support arbitrary features and multiple values per field. `MorphAnalysisC` is redesigned to contain: * key: hash of UD FEATS string of morphological features * array of `MorphFeatureC` structs that each contain a hash of `Field` and `Field=Value` for a given morphological feature, which makes it possible to: * find features by field * represent multiple values for a given field * `get_field()` is renamed to `get_by_field()` and is no longer `nogil`. Instead a new helper function `get_n_by_field()` is `nogil` and returns `n` features by field. * `MorphAnalysis.get()` returns all possible values for a field as a list of individual features such as `["Tense=Pres", "Tense=Past"]`. * `MorphAnalysis`'s `str()` and `repr()` are the UD FEATS string. * `Morphology.feats_to_dict()` converts a UD FEATS string to a dict where: * Each field has one entry in the dict * Multiple values remain separated by a separator in the value string * `Token.morph_` returns the UD FEATS string and you can set `Token.morph_` with a UD FEATS string or with a tag map dict. * Modify get_by_field to use np.ndarray Modify `get_by_field()` to use np.ndarray. Remove `max_results` from `get_n_by_field()` and always iterate over all the fields. * Rewrite without MorphFeatureC * Add shortcut for existing feats strings as keys Add shortcut for existing feats strings as keys in `Morphology.add()`. * Check for '_' as empty analysis when adding morphs * Extend helper converters in Morphology Add and extend helper converters that convert and normalize between: * UD FEATS strings (`"Case=dat,gen\|Number=sing"`) * per-field dict of feats (`{"Case": "dat,gen", "Number": "sing"}`) * list of individual features (`["Case=dat", "Case=gen", "Number=sing"]`) All converters sort fields and values where applicable. 2020-01-23 21:01:54 +00:00			`cdef readonly hash_t key`
Add header for morphanalysis 2019-03-07 16:24:57 +00:00			`cdef MorphAnalysisC c`