mirror of https://github.com/explosion/spaCy.git
101 lines
3.3 KiB
Python
101 lines
3.3 KiB
Python
from __future__ import unicode_literals
|
|
|
|
import pytest
|
|
import numpy
|
|
|
|
from spacy.attrs import HEAD, DEP
|
|
from spacy.symbols import root, det, compound, nsubjpass, aux, auxpass, punct, nsubj, cc, amod, conj, advmod, attr, prep, pobj
|
|
|
|
|
|
@pytest.mark.models
|
|
class TestNounChunks:
|
|
@pytest.fixture(scope="class")
|
|
def ex1_en(self, EN):
|
|
example = EN.tokenizer.tokens_from_list('A base phrase should be recognized .'.split(' '))
|
|
EN.tagger.tag_from_strings(example, 'DT NN NN MD VB VBN .'.split(' '))
|
|
example.from_array([HEAD, DEP],
|
|
numpy.asarray(
|
|
[
|
|
[2, det],
|
|
[1, compound],
|
|
[3, nsubjpass],
|
|
[2, aux],
|
|
[1, auxpass],
|
|
[0, root],
|
|
[-1, punct]
|
|
], dtype='int32'))
|
|
return example
|
|
|
|
@pytest.fixture(scope="class")
|
|
def ex2_en(self, EN):
|
|
example = EN.tokenizer.tokens_from_list('A base phrase and a good phrase are often the same .'.split(' '))
|
|
EN.tagger.tag_from_strings(example, 'DT NN NN CC DT JJ NN VBP RB DT JJ .'.split(' '))
|
|
example.from_array([HEAD, DEP],
|
|
numpy.asarray(
|
|
[
|
|
[2, det],
|
|
[1, compound],
|
|
[5, nsubj],
|
|
[-1, cc],
|
|
[1, det],
|
|
[1, amod],
|
|
[-4, conj],
|
|
[0, root],
|
|
[-1, advmod],
|
|
[1, det],
|
|
[-3, attr],
|
|
[-4, punct]
|
|
], dtype='int32'))
|
|
return example
|
|
|
|
@pytest.fixture(scope="class")
|
|
def ex3_en(self, EN):
|
|
example = EN.tokenizer.tokens_from_list('A phrase with another phrase occurs .'.split(' '))
|
|
EN.tagger.tag_from_strings(example, 'DT NN IN DT NN VBZ .'.split(' '))
|
|
example.from_array([HEAD, DEP],
|
|
numpy.asarray(
|
|
[
|
|
[1, det],
|
|
[4, nsubj],
|
|
[-1, prep],
|
|
[1, det],
|
|
[-2, pobj],
|
|
[0, root],
|
|
[-1, punct]
|
|
], dtype='int32'))
|
|
return example
|
|
|
|
# @pytest.fixture(score="class")
|
|
# def ex1_de(self, DE):
|
|
# example = EN.tokenizer.tokens_from_list('Eine Tasse steht auf dem Tisch .'.split(' '))
|
|
# EN.tagger.tag_from_strings(example, 'ART NN VVFIN APPR ART NN $.'.split(' '))
|
|
# example.from_array([HEAD, DEP],
|
|
# numpy.asarray(
|
|
# [
|
|
# [1, det],
|
|
# [4, nsubj],
|
|
# [-1, prep],
|
|
# [1, det],
|
|
# [-2, pobj],
|
|
# [0, root],
|
|
# [-1, punct]
|
|
# ], dtype='int32'))
|
|
# return example
|
|
|
|
def test_en_standard_chunk(self, ex1_en):
|
|
chunks = list(ex1_en.noun_chunks)
|
|
assert len(chunks) == 1
|
|
assert chunks[0].string == 'A base phrase '
|
|
|
|
def test_en_coordinated_chunks(self, ex2_en):
|
|
chunks = list(ex2_en.noun_chunks)
|
|
assert len(chunks) == 2
|
|
assert chunks[0].string == 'A base phrase '
|
|
assert chunks[1].string == 'a good phrase '
|
|
|
|
def test_en_pp_chunks(self, ex3_en):
|
|
chunks = list(ex3_en.noun_chunks)
|
|
assert len(chunks) == 2
|
|
assert chunks[0].string == 'A phrase '
|
|
assert chunks[1].string == 'another phrase '
|