mirror of https://github.com/explosion/spaCy.git
110 lines
3.9 KiB
Python
110 lines
3.9 KiB
Python
import pytest
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from spacy.tokens import Doc
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pytestmark = pytest.mark.filterwarnings("ignore::DeprecationWarning")
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def test_ru_doc_lemmatization(ru_lemmatizer):
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words = ["мама", "мыла", "раму"]
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pos = ["NOUN", "VERB", "NOUN"]
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morphs = [
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"Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing",
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"Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act",
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"Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing",
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]
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doc = Doc(ru_lemmatizer.vocab, words=words, pos=pos, morphs=morphs)
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doc = ru_lemmatizer(doc)
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lemmas = [token.lemma_ for token in doc]
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assert lemmas == ["мама", "мыть", "рама"]
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@pytest.mark.parametrize(
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"text,lemmas",
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[
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("гвоздики", ["гвоздик", "гвоздика"]),
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("люди", ["человек"]),
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("реки", ["река"]),
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("кольцо", ["кольцо"]),
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("пепперони", ["пепперони"]),
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],
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)
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def test_ru_lemmatizer_noun_lemmas(ru_lemmatizer, text, lemmas):
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doc = Doc(ru_lemmatizer.vocab, words=[text], pos=["NOUN"])
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result_lemmas = ru_lemmatizer.pymorphy2_lemmatize(doc[0])
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assert sorted(result_lemmas) == lemmas
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@pytest.mark.parametrize(
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"text,pos,morph,lemma",
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[
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("рой", "NOUN", "", "рой"),
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("рой", "VERB", "", "рыть"),
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("клей", "NOUN", "", "клей"),
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("клей", "VERB", "", "клеить"),
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("три", "NUM", "", "три"),
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("кос", "NOUN", "Number=Sing", "кос"),
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("кос", "NOUN", "Number=Plur", "коса"),
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("кос", "ADJ", "", "косой"),
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("потом", "NOUN", "", "пот"),
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("потом", "ADV", "", "потом"),
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],
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)
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def test_ru_lemmatizer_works_with_different_pos_homonyms(
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ru_lemmatizer, text, pos, morph, lemma
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):
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doc = Doc(ru_lemmatizer.vocab, words=[text], pos=[pos], morphs=[morph])
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result_lemmas = ru_lemmatizer.pymorphy2_lemmatize(doc[0])
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assert result_lemmas == [lemma]
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@pytest.mark.parametrize(
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"text,morph,lemma",
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[
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("гвоздики", "Gender=Fem", "гвоздика"),
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("гвоздики", "Gender=Masc", "гвоздик"),
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("вина", "Gender=Fem", "вина"),
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("вина", "Gender=Neut", "вино"),
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],
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)
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def test_ru_lemmatizer_works_with_noun_homonyms(ru_lemmatizer, text, morph, lemma):
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doc = Doc(ru_lemmatizer.vocab, words=[text], pos=["NOUN"], morphs=[morph])
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result_lemmas = ru_lemmatizer.pymorphy2_lemmatize(doc[0])
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assert result_lemmas == [lemma]
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def test_ru_lemmatizer_punct(ru_lemmatizer):
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doc = Doc(ru_lemmatizer.vocab, words=["«"], pos=["PUNCT"])
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assert ru_lemmatizer.pymorphy2_lemmatize(doc[0]) == ['"']
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doc = Doc(ru_lemmatizer.vocab, words=["»"], pos=["PUNCT"])
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assert ru_lemmatizer.pymorphy2_lemmatize(doc[0]) == ['"']
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def test_ru_doc_lookup_lemmatization(ru_lookup_lemmatizer):
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assert ru_lookup_lemmatizer.mode == "pymorphy3_lookup"
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words = ["мама", "мыла", "раму"]
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pos = ["NOUN", "VERB", "NOUN"]
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morphs = [
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"Animacy=Anim|Case=Nom|Gender=Fem|Number=Sing",
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"Aspect=Imp|Gender=Fem|Mood=Ind|Number=Sing|Tense=Past|VerbForm=Fin|Voice=Act",
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"Animacy=Anim|Case=Acc|Gender=Fem|Number=Sing",
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]
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doc = Doc(ru_lookup_lemmatizer.vocab, words=words, pos=pos, morphs=morphs)
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doc = ru_lookup_lemmatizer(doc)
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lemmas = [token.lemma_ for token in doc]
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assert lemmas == ["мама", "мыла", "раму"]
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@pytest.mark.parametrize(
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"word,lemma",
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(
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("бременем", "бремя"),
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("будешь", "быть"),
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("какая-то", "какой-то"),
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),
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)
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def test_ru_lookup_lemmatizer(ru_lookup_lemmatizer, word, lemma):
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assert ru_lookup_lemmatizer.mode == "pymorphy3_lookup"
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doc = Doc(ru_lookup_lemmatizer.vocab, words=[word])
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assert ru_lookup_lemmatizer(doc)[0].lemma_ == lemma
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