spaCy/spacy/tests/lang/en/test_parser.py
Ines Montani b6e991440c 💫 Tidy up and auto-format tests (#2967)
* Auto-format tests with black

* Add flake8 config

* Tidy up and remove unused imports

* Fix redefinitions of test functions

* Replace orths_and_spaces with words and spaces

* Fix compatibility with pytest 4.0

* xfail test for now

Test was previously overwritten by following test due to naming conflict, so failure wasn't reported

* Unfail passing test

* Only use fixture via arguments

Fixes pytest 4.0 compatibility
2018-11-27 01:09:36 +01:00

85 lines
3.1 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from ...util import get_doc
def test_en_parser_noun_chunks_standard(en_tokenizer):
text = "A base phrase should be recognized."
heads = [2, 1, 3, 2, 1, 0, -1]
tags = ["DT", "JJ", "NN", "MD", "VB", "VBN", "."]
deps = ["det", "amod", "nsubjpass", "aux", "auxpass", "ROOT", "punct"]
tokens = en_tokenizer(text)
doc = get_doc(
tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
)
chunks = list(doc.noun_chunks)
assert len(chunks) == 1
assert chunks[0].text_with_ws == "A base phrase "
def test_en_parser_noun_chunks_coordinated(en_tokenizer):
# fmt: off
text = "A base phrase and a good phrase are often the same."
heads = [2, 1, 5, -1, 2, 1, -4, 0, -1, 1, -3, -4]
tags = ["DT", "NN", "NN", "CC", "DT", "JJ", "NN", "VBP", "RB", "DT", "JJ", "."]
deps = ["det", "compound", "nsubj", "cc", "det", "amod", "conj", "ROOT", "advmod", "det", "attr", "punct"]
# fmt: on
tokens = en_tokenizer(text)
doc = get_doc(
tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
)
chunks = list(doc.noun_chunks)
assert len(chunks) == 2
assert chunks[0].text_with_ws == "A base phrase "
assert chunks[1].text_with_ws == "a good phrase "
def test_en_parser_noun_chunks_pp_chunks(en_tokenizer):
text = "A phrase with another phrase occurs."
heads = [1, 4, -1, 1, -2, 0, -1]
tags = ["DT", "NN", "IN", "DT", "NN", "VBZ", "."]
deps = ["det", "nsubj", "prep", "det", "pobj", "ROOT", "punct"]
tokens = en_tokenizer(text)
doc = get_doc(
tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
)
chunks = list(doc.noun_chunks)
assert len(chunks) == 2
assert chunks[0].text_with_ws == "A phrase "
assert chunks[1].text_with_ws == "another phrase "
def test_en_parser_noun_chunks_appositional_modifiers(en_tokenizer):
# fmt: off
text = "Sam, my brother, arrived to the house."
heads = [5, -1, 1, -3, -4, 0, -1, 1, -2, -4]
tags = ["NNP", ",", "PRP$", "NN", ",", "VBD", "IN", "DT", "NN", "."]
deps = ["nsubj", "punct", "poss", "appos", "punct", "ROOT", "prep", "det", "pobj", "punct"]
# fmt: on
tokens = en_tokenizer(text)
doc = get_doc(
tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
)
chunks = list(doc.noun_chunks)
assert len(chunks) == 3
assert chunks[0].text_with_ws == "Sam "
assert chunks[1].text_with_ws == "my brother "
assert chunks[2].text_with_ws == "the house "
def test_en_parser_noun_chunks_dative(en_tokenizer):
text = "She gave Bob a raise."
heads = [1, 0, -1, 1, -3, -4]
tags = ["PRP", "VBD", "NNP", "DT", "NN", "."]
deps = ["nsubj", "ROOT", "dative", "det", "dobj", "punct"]
tokens = en_tokenizer(text)
doc = get_doc(
tokens.vocab, words=[t.text for t in tokens], tags=tags, deps=deps, heads=heads
)
chunks = list(doc.noun_chunks)
assert len(chunks) == 3
assert chunks[0].text_with_ws == "She "
assert chunks[1].text_with_ws == "Bob "
assert chunks[2].text_with_ws == "a raise "