mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-27 02:16:32 +03:00
7d50804644
* Migrate regressions 1-1000 * Move serialize test to correct file * Remove tests that won't work in v3 * Migrate regressions 1000-1500 Removed regression test 1250 because v3 doesn't support the old LEX scheme anymore. * Add missing imports in serializer tests * Migrate tests 1500-2000 * Migrate regressions from 2000-2500 * Migrate regressions from 2501-3000 * Migrate regressions from 3000-3501 * Migrate regressions from 3501-4000 * Migrate regressions from 4001-4500 * Migrate regressions from 4501-5000 * Migrate regressions from 5001-5501 * Migrate regressions from 5501 to 7000 * Migrate regressions from 7001 to 8000 * Migrate remaining regression tests * Fixing missing imports * Update docs with new system [ci skip] * Update CONTRIBUTING.md - Fix formatting - Update wording * Remove lemmatizer tests in el lang * Move a few tests into the general tokenizer * Separate Doc and DocBin tests
84 lines
2.8 KiB
Python
84 lines
2.8 KiB
Python
import numpy
|
|
import pytest
|
|
from spacy.attrs import IS_ALPHA, IS_DIGIT
|
|
from spacy.lookups import Lookups
|
|
from spacy.tokens import Doc
|
|
from spacy.util import OOV_RANK
|
|
from spacy.vocab import Vocab
|
|
|
|
|
|
@pytest.mark.issue(361)
|
|
@pytest.mark.parametrize("text1,text2", [("cat", "dog")])
|
|
def test_issue361(en_vocab, text1, text2):
|
|
"""Test Issue #361: Equality of lexemes"""
|
|
assert en_vocab[text1] == en_vocab[text1]
|
|
assert en_vocab[text1] != en_vocab[text2]
|
|
|
|
|
|
@pytest.mark.issue(600)
|
|
def test_issue600():
|
|
vocab = Vocab(tag_map={"NN": {"pos": "NOUN"}})
|
|
doc = Doc(vocab, words=["hello"])
|
|
doc[0].tag_ = "NN"
|
|
|
|
|
|
@pytest.mark.parametrize("text1,prob1,text2,prob2", [("NOUN", -1, "opera", -2)])
|
|
def test_vocab_lexeme_lt(en_vocab, text1, text2, prob1, prob2):
|
|
"""More frequent is l.t. less frequent"""
|
|
lex1 = en_vocab[text1]
|
|
lex1.prob = prob1
|
|
lex2 = en_vocab[text2]
|
|
lex2.prob = prob2
|
|
|
|
assert lex1 < lex2
|
|
assert lex2 > lex1
|
|
|
|
|
|
@pytest.mark.parametrize("text1,text2", [("phantom", "opera")])
|
|
def test_vocab_lexeme_hash(en_vocab, text1, text2):
|
|
"""Test that lexemes are hashable."""
|
|
lex1 = en_vocab[text1]
|
|
lex2 = en_vocab[text2]
|
|
lexes = {lex1: lex1, lex2: lex2}
|
|
assert lexes[lex1].orth_ == text1
|
|
assert lexes[lex2].orth_ == text2
|
|
|
|
|
|
def test_vocab_lexeme_is_alpha(en_vocab):
|
|
assert en_vocab["the"].flags & (1 << IS_ALPHA)
|
|
assert not en_vocab["1999"].flags & (1 << IS_ALPHA)
|
|
assert not en_vocab["hello1"].flags & (1 << IS_ALPHA)
|
|
|
|
|
|
def test_vocab_lexeme_is_digit(en_vocab):
|
|
assert not en_vocab["the"].flags & (1 << IS_DIGIT)
|
|
assert en_vocab["1999"].flags & (1 << IS_DIGIT)
|
|
assert not en_vocab["hello1"].flags & (1 << IS_DIGIT)
|
|
|
|
|
|
def test_vocab_lexeme_add_flag_auto_id(en_vocab):
|
|
is_len4 = en_vocab.add_flag(lambda string: len(string) == 4)
|
|
assert en_vocab["1999"].check_flag(is_len4) is True
|
|
assert en_vocab["1999"].check_flag(IS_DIGIT) is True
|
|
assert en_vocab["199"].check_flag(is_len4) is False
|
|
assert en_vocab["199"].check_flag(IS_DIGIT) is True
|
|
assert en_vocab["the"].check_flag(is_len4) is False
|
|
assert en_vocab["dogs"].check_flag(is_len4) is True
|
|
|
|
|
|
def test_vocab_lexeme_add_flag_provided_id(en_vocab):
|
|
is_len4 = en_vocab.add_flag(lambda string: len(string) == 4, flag_id=IS_DIGIT)
|
|
assert en_vocab["1999"].check_flag(is_len4) is True
|
|
assert en_vocab["199"].check_flag(is_len4) is False
|
|
assert en_vocab["199"].check_flag(IS_DIGIT) is False
|
|
assert en_vocab["the"].check_flag(is_len4) is False
|
|
assert en_vocab["dogs"].check_flag(is_len4) is True
|
|
en_vocab.add_flag(lambda string: string.isdigit(), flag_id=IS_DIGIT)
|
|
|
|
|
|
def test_vocab_lexeme_oov_rank(en_vocab):
|
|
"""Test that default rank is OOV_RANK."""
|
|
lex = en_vocab["word"]
|
|
assert OOV_RANK == numpy.iinfo(numpy.uint64).max
|
|
assert lex.rank == OOV_RANK
|