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spaCy/spacy/lang/sv/morph_rules.py

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Fix PRON_LEMMA imports
2017-11-06 16:41:53 +00:00
from ...symbols import LEMMA, PRON_LEMMA
Reorganise Swedish language data
2017-05-08 13:54:29 +00:00
Added morph rules
2016-12-20 12:18:41 +00:00
# Used the table of pronouns at https://sv.wiktionary.org/wiki/deras
MORPH_RULES = {
"PRP": {
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"jag": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Sing",
"Case": "Nom",
},
"mig": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Sing",
"Case": "Acc",
},
"mej": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Sing",
"Case": "Acc",
},
"du": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Sing",
"Case": "Nom",
},
"han": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Sing",
"Gender": "Masc",
"Case": "Nom",
},
"honom": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Sing",
"Gender": "Masc",
"Case": "Acc",
},
"hon": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Sing",
"Gender": "Fem",
"Case": "Nom",
},
"henne": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Sing",
"Gender": "Fem",
"Case": "Acc",
},
"det": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Sing",
"Gender": "Neut",
},
"vi": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Case": "Nom",
},
"oss": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Case": "Acc",
},
"ni": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Plur",
"Case": "Nom",
},
"er": {LEMMA: PRON_LEMMA, "PronType": "Prs", "Person": "Two", "Number": "Plur"},
"de": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Plur",
"Case": "Nom",
},
"dom": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Plur",
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
"Case": "Nom,Acc",
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
},
"dem": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Plur",
"Case": "Acc",
},
"min": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Sing",
"Poss": "Yes",
"Reflex": "Yes",
},
"mitt": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Sing",
"Poss": "Yes",
"Reflex": "Yes",
},
"mina": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"din": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Sing",
"Poss": "Yes",
"Reflex": "Yes",
},
"ditt": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Sing",
"Poss": "Yes",
"Reflex": "Yes",
},
"dina": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"hans": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
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
"Number": "Sing,Plur",
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"Gender": "Masc",
"Poss": "Yes",
"Reflex": "Yes",
},
"hennes": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
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
"Number": "Sing,Plur",
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"Gender": "Fem",
"Poss": "Yes",
"Reflex": "Yes",
},
"dess": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
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
"Number": "Sing,Plur",
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"Poss": "Yes",
"Reflex": "Yes",
},
"vår": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"våran": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"vårt": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"vårat": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"våra": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "One",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"eran": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"ert": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"erat": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"era": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Two",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
"deras": {
LEMMA: PRON_LEMMA,
"PronType": "Prs",
"Person": "Three",
"Number": "Plur",
"Poss": "Yes",
"Reflex": "Yes",
},
Added morph rules
2016-12-20 12:18:41 +00:00
},
"VBZ": {
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"är": {
"VerbForm": "Fin",
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
"Person": "One,Two,Three",
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"Tense": "Pres",
"Mood": "Ind",
}
Added morph rules
2016-12-20 12:18:41 +00:00
},
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"VBP": {"är": {"VerbForm": "Fin", "Tense": "Pres", "Mood": "Ind"}},
Added morph rules
2016-12-20 12:18:41 +00:00
"VBD": {
💫 Tidy up and auto-format .py files (#2983) <!--- Provide a general summary of your changes in the title. --> ## Description - [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files. - [x] Update flake8 config to exclude very large files (lemmatization tables etc.) - [x] Update code to be compatible with flake8 rules - [x] Fix various small bugs, inconsistencies and messy stuff in the language data - [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means) Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results. At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information. ### Types of change enhancement, code style ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 16:03:03 +00:00
"var": {"VerbForm": "Fin", "Tense": "Past", "Number": "Sing"},
"vart": {"VerbForm": "Fin", "Tense": "Past", "Number": "Plur"},
},
Added morph rules
2016-12-20 12:18:41 +00:00
}