mirror of
https://github.com/explosion/spaCy.git
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131 lines
4.4 KiB
Python
131 lines
4.4 KiB
Python
from __future__ import unicode_literals
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import pytest
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from spacy.tokens import Doc
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from spacy.syntax.nonproj import PseudoProjectivity
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@pytest.mark.models
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def test_single_period(EN):
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string = 'A test sentence.'
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words = EN(string)
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assert len(words) == 4
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assert len(list(words.sents)) == 1
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assert sum(len(sent) for sent in words.sents) == len(words)
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@pytest.mark.models
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def test_single_no_period(EN):
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string = 'A test sentence'
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words = EN(string)
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assert len(words) == 3
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assert len(list(words.sents)) == 1
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assert sum(len(sent) for sent in words.sents) == len(words)
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@pytest.mark.models
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def test_single_exclamation(EN):
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string = 'A test sentence!'
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words = EN(string)
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assert len(words) == 4
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assert len(list(words.sents)) == 1
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assert sum(len(sent) for sent in words.sents) == len(words)
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@pytest.mark.models
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def test_single_question(EN):
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string = 'A test sentence?'
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words = EN(string, tag=False, parse=True)
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assert len(words) == 4
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assert len(list(words.sents)) == 1
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assert sum(len(sent) for sent in words.sents) == len(words)
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@pytest.mark.models
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def test_sentence_breaks(EN):
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doc = EN.tokenizer.tokens_from_list(u'This is a sentence . This is another one .'.split(' '))
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EN.tagger(doc)
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with EN.parser.step_through(doc) as stepwise:
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('L-nsubj')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('S')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('L-det')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('R-attr')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('D')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('R-punct')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('B-ROOT')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('L-nsubj')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('S')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('L-attr')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('R-attr')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('D')
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assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
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stepwise.transition('R-punct')
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assert len(list(doc.sents)) == 2
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for tok in doc:
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assert tok.dep != 0 or tok.is_space
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assert [ tok.head.i for tok in doc ] == [1,1,3,1,1,6,6,8,6,6]
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def apply_transition_sequence(model, doc, sequence):
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with model.parser.step_through(doc) as stepwise:
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for transition in sequence:
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stepwise.transition(transition)
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@pytest.mark.models
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def test_sbd_serialization_projective(EN):
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"""
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test that before and after serialization, the sentence boundaries are the same.
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"""
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example = EN.tokenizer.tokens_from_list(u"I bought a couch from IKEA. It was n't very comfortable .".split(' '))
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EN.tagger(example)
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apply_transition_sequence(EN, example, ['L-nsubj','S','L-det','R-dobj','D','R-prep','R-pobj','B-ROOT','L-nsubj','R-neg','D','S','L-advmod','R-acomp','D','R-punct'])
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example_serialized = Doc(EN.vocab).from_bytes(example.to_bytes())
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assert example.to_bytes() == example_serialized.to_bytes()
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assert [s.text for s in example.sents] == [s.text for s in example_serialized.sents]
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# TODO:
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# @pytest.mark.models
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# def test_sbd_serialization_nonprojective(DE):
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# """
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# test that before and after serialization, the sentence boundaries are the same in a non-projective sentence.
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# """
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# example = EN.tokenizer.tokens_from_list(u"Den Mann hat Peter nicht gesehen . Er war zu langsam .".split(' '))
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# EN.tagger(example)
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# apply_transition_sequence(EN, example, ['L-nk','L-oa||oc','R-sb','D','S','L-ng','B-ROOT','L-nsubj','R-neg','D','S','L-advmod','R-acomp','D','R-punct'])
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# print [(t.dep_,t.head.i) for t in example]
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# example_serialized = Doc(EN.vocab).from_bytes(example.to_bytes())
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# assert example.to_bytes() == example_serialized.to_bytes()
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# assert [s.text for s in example.sents] == [s.text for s in example_serialized.sents]
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