spaCy/spacy/tests/parser/test_sbd.py

141 lines
4.6 KiB
Python
Raw Normal View History

from __future__ import unicode_literals
import pytest
from spacy.tokens import Doc
from spacy.syntax.nonproj import PseudoProjectivity
2015-04-19 22:39:18 +03:00
2015-09-21 12:23:38 +03:00
@pytest.mark.models
def test_single_period(EN):
string = 'A test sentence.'
words = EN(string)
assert len(words) == 4
2015-03-14 18:10:42 +03:00
assert len(list(words.sents)) == 1
assert sum(len(sent) for sent in words.sents) == len(words)
2015-09-21 12:23:38 +03:00
@pytest.mark.models
def test_single_no_period(EN):
string = 'A test sentence'
words = EN(string)
assert len(words) == 3
2015-03-14 18:10:42 +03:00
assert len(list(words.sents)) == 1
assert sum(len(sent) for sent in words.sents) == len(words)
2015-09-21 12:23:38 +03:00
@pytest.mark.models
def test_single_exclamation(EN):
string = 'A test sentence!'
words = EN(string)
assert len(words) == 4
2015-03-14 18:10:42 +03:00
assert len(list(words.sents)) == 1
assert sum(len(sent) for sent in words.sents) == len(words)
2015-09-21 12:23:38 +03:00
@pytest.mark.models
def test_single_question(EN):
string = 'A test sentence?'
2016-05-02 16:26:07 +03:00
words = EN(string, tag=False, parse=True)
assert len(words) == 4
2015-03-14 18:10:42 +03:00
assert len(list(words.sents)) == 1
assert sum(len(sent) for sent in words.sents) == len(words)
@pytest.mark.models
def test_sentence_breaks(EN):
doc = EN.tokenizer.tokens_from_list(u'This is a sentence . This is another one .'.split(' '))
EN.tagger(doc)
with EN.parser.step_through(doc) as stepwise:
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('L-nsubj')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('S')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('L-det')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('R-attr')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('D')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('R-punct')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('B-ROOT')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('L-nsubj')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('S')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('L-attr')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('R-attr')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('D')
assert EN.parser.moves.is_valid(stepwise.stcls,'B-ROOT')
stepwise.transition('R-punct')
assert len(list(doc.sents)) == 2
for tok in doc:
assert tok.dep != 0 or tok.is_space
assert [ tok.head.i for tok in doc ] == [1,1,3,1,1,6,6,8,6,6]
2016-04-21 18:15:10 +03:00
def apply_transition_sequence(model, doc, sequence):
with model.parser.step_through(doc) as stepwise:
for transition in sequence:
stepwise.transition(transition)
2016-04-21 18:15:10 +03:00
@pytest.mark.models
def test_sbd_serialization_projective(EN):
"""
test that before and after serialization, the sentence boundaries are the same.
"""
example = EN.tokenizer.tokens_from_list(u"I bought a couch from IKEA. It was n't very comfortable .".split(' '))
2016-04-21 18:15:10 +03:00
EN.tagger(example)
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'])
example_serialized = Doc(EN.vocab).from_bytes(example.to_bytes())
assert example.to_bytes() == example_serialized.to_bytes()
assert [s.text for s in example.sents] == [s.text for s in example_serialized.sents]
2016-05-04 17:00:28 +03:00
def test_sbd_empty_string(EN):
'''Test Issue #309: SBD fails on empty string
'''
doc = EN(u' ')
doc.is_parsed = True
assert len(doc) == 1
sents = list(doc.sents)
assert len(sents) == 1
# TODO:
# @pytest.mark.models
# def test_sbd_serialization_nonprojective(DE):
# """
# test that before and after serialization, the sentence boundaries are the same in a non-projective sentence.
# """
# example = EN.tokenizer.tokens_from_list(u"Den Mann hat Peter nicht gesehen . Er war zu langsam .".split(' '))
# EN.tagger(example)
# 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'])
# print [(t.dep_,t.head.i) for t in example]
# example_serialized = Doc(EN.vocab).from_bytes(example.to_bytes())
# assert example.to_bytes() == example_serialized.to_bytes()
# assert [s.text for s in example.sents] == [s.text for s in example_serialized.sents]
2016-04-21 18:15:10 +03:00