mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-25 17:36:30 +03:00
241 lines
8.3 KiB
Python
241 lines
8.3 KiB
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
from ..util import get_doc
|
|
from ...tokens import Doc
|
|
from ...vocab import Vocab
|
|
|
|
import pytest
|
|
import numpy
|
|
|
|
|
|
@pytest.mark.parametrize('text', [["one", "two", "three"]])
|
|
def test_doc_api_compare_by_string_position(en_vocab, text):
|
|
doc = get_doc(en_vocab, text)
|
|
# Get the tokens in this order, so their ID ordering doesn't match the idx
|
|
token3 = doc[-1]
|
|
token2 = doc[-2]
|
|
token1 = doc[-1]
|
|
token1, token2, token3 = doc
|
|
assert token1 < token2 < token3
|
|
assert not token1 > token2
|
|
assert token2 > token1
|
|
assert token2 <= token3
|
|
assert token3 >= token1
|
|
|
|
|
|
def test_doc_api_getitem(en_tokenizer):
|
|
text = "Give it back! He pleaded."
|
|
tokens = en_tokenizer(text)
|
|
assert tokens[0].text == 'Give'
|
|
assert tokens[-1].text == '.'
|
|
with pytest.raises(IndexError):
|
|
tokens[len(tokens)]
|
|
|
|
def to_str(span):
|
|
return '/'.join(token.text for token in span)
|
|
|
|
span = tokens[1:1]
|
|
assert not to_str(span)
|
|
span = tokens[1:4]
|
|
assert to_str(span) == 'it/back/!'
|
|
span = tokens[1:4:1]
|
|
assert to_str(span) == 'it/back/!'
|
|
with pytest.raises(ValueError):
|
|
tokens[1:4:2]
|
|
with pytest.raises(ValueError):
|
|
tokens[1:4:-1]
|
|
|
|
span = tokens[-3:6]
|
|
assert to_str(span) == 'He/pleaded'
|
|
span = tokens[4:-1]
|
|
assert to_str(span) == 'He/pleaded'
|
|
span = tokens[-5:-3]
|
|
assert to_str(span) == 'back/!'
|
|
span = tokens[5:4]
|
|
assert span.start == span.end == 5 and not to_str(span)
|
|
span = tokens[4:-3]
|
|
assert span.start == span.end == 4 and not to_str(span)
|
|
|
|
span = tokens[:]
|
|
assert to_str(span) == 'Give/it/back/!/He/pleaded/.'
|
|
span = tokens[4:]
|
|
assert to_str(span) == 'He/pleaded/.'
|
|
span = tokens[:4]
|
|
assert to_str(span) == 'Give/it/back/!'
|
|
span = tokens[:-3]
|
|
assert to_str(span) == 'Give/it/back/!'
|
|
span = tokens[-3:]
|
|
assert to_str(span) == 'He/pleaded/.'
|
|
|
|
span = tokens[4:50]
|
|
assert to_str(span) == 'He/pleaded/.'
|
|
span = tokens[-50:4]
|
|
assert to_str(span) == 'Give/it/back/!'
|
|
span = tokens[-50:-40]
|
|
assert span.start == span.end == 0 and not to_str(span)
|
|
span = tokens[40:50]
|
|
assert span.start == span.end == 7 and not to_str(span)
|
|
|
|
span = tokens[1:4]
|
|
assert span[0].orth_ == 'it'
|
|
subspan = span[:]
|
|
assert to_str(subspan) == 'it/back/!'
|
|
subspan = span[:2]
|
|
assert to_str(subspan) == 'it/back'
|
|
subspan = span[1:]
|
|
assert to_str(subspan) == 'back/!'
|
|
subspan = span[:-1]
|
|
assert to_str(subspan) == 'it/back'
|
|
subspan = span[-2:]
|
|
assert to_str(subspan) == 'back/!'
|
|
subspan = span[1:2]
|
|
assert to_str(subspan) == 'back'
|
|
subspan = span[-2:-1]
|
|
assert to_str(subspan) == 'back'
|
|
subspan = span[-50:50]
|
|
assert to_str(subspan) == 'it/back/!'
|
|
subspan = span[50:-50]
|
|
assert subspan.start == subspan.end == 4 and not to_str(subspan)
|
|
|
|
|
|
@pytest.mark.parametrize('text', ["Give it back! He pleaded.",
|
|
" Give it back! He pleaded. "])
|
|
def test_doc_api_serialize(en_tokenizer, text):
|
|
tokens = en_tokenizer(text)
|
|
new_tokens = get_doc(tokens.vocab).from_bytes(tokens.to_bytes())
|
|
assert tokens.text == new_tokens.text
|
|
assert [t.text for t in tokens] == [t.text for t in new_tokens]
|
|
assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
|
|
|
|
|
|
def test_doc_api_set_ents(en_tokenizer):
|
|
text = "I use goggle chrone to surf the web"
|
|
tokens = en_tokenizer(text)
|
|
assert len(tokens.ents) == 0
|
|
tokens.ents = [(tokens.vocab.strings['PRODUCT'], 2, 4)]
|
|
assert len(list(tokens.ents)) == 1
|
|
assert [t.ent_iob for t in tokens] == [0, 0, 3, 1, 0, 0, 0, 0]
|
|
assert tokens.ents[0].label_ == 'PRODUCT'
|
|
assert tokens.ents[0].start == 2
|
|
assert tokens.ents[0].end == 4
|
|
|
|
|
|
def test_doc_api_merge(en_tokenizer):
|
|
text = "WKRO played songs by the beach boys all night"
|
|
|
|
# merge 'The Beach Boys'
|
|
doc = en_tokenizer(text)
|
|
assert len(doc) == 9
|
|
doc.merge(doc[4].idx, doc[6].idx + len(doc[6]), tag='NAMED', lemma='LEMMA',
|
|
ent_type='TYPE')
|
|
assert len(doc) == 7
|
|
assert doc[4].text == 'the beach boys'
|
|
assert doc[4].text_with_ws == 'the beach boys '
|
|
assert doc[4].tag_ == 'NAMED'
|
|
|
|
# merge 'all night'
|
|
doc = en_tokenizer(text)
|
|
assert len(doc) == 9
|
|
doc.merge(doc[7].idx, doc[8].idx + len(doc[8]), tag='NAMED', lemma='LEMMA',
|
|
ent_type='TYPE')
|
|
assert len(doc) == 8
|
|
assert doc[7].text == 'all night'
|
|
assert doc[7].text_with_ws == 'all night'
|
|
|
|
|
|
def test_doc_api_merge_children(en_tokenizer):
|
|
"""Test that attachments work correctly after merging."""
|
|
text = "WKRO played songs by the beach boys all night"
|
|
doc = en_tokenizer(text)
|
|
assert len(doc) == 9
|
|
doc.merge(doc[4].idx, doc[6].idx + len(doc[6]), tag='NAMED', lemma='LEMMA',
|
|
ent_type='TYPE')
|
|
|
|
for word in doc:
|
|
if word.i < word.head.i:
|
|
assert word in list(word.head.lefts)
|
|
elif word.i > word.head.i:
|
|
assert word in list(word.head.rights)
|
|
|
|
|
|
def test_doc_api_merge_hang(en_tokenizer):
|
|
text = "through North and South Carolina"
|
|
doc = en_tokenizer(text)
|
|
doc.merge(18, 32, tag='', lemma='', ent_type='ORG')
|
|
doc.merge(8, 32, tag='', lemma='', ent_type='ORG')
|
|
|
|
|
|
def test_doc_api_sents_empty_string(en_tokenizer):
|
|
doc = en_tokenizer("")
|
|
doc.is_parsed = True
|
|
sents = list(doc.sents)
|
|
assert len(sents) == 0
|
|
|
|
|
|
def test_doc_api_runtime_error(en_tokenizer):
|
|
# Example that caused run-time error while parsing Reddit
|
|
text = "67% of black households are single parent \n\n72% of all black babies born out of wedlock \n\n50% of all black kids don\u2019t finish high school"
|
|
deps = ['nsubj', 'prep', 'amod', 'pobj', 'ROOT', 'amod', 'attr', '',
|
|
'nummod', 'prep', 'det', 'amod', 'pobj', 'acl', 'prep', 'prep',
|
|
'pobj', '', 'nummod', 'prep', 'det', 'amod', 'pobj', 'aux', 'neg',
|
|
'ROOT', 'amod', 'dobj']
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], deps=deps)
|
|
|
|
nps = []
|
|
for np in doc.noun_chunks:
|
|
while len(np) > 1 and np[0].dep_ not in ('advmod', 'amod', 'compound'):
|
|
np = np[1:]
|
|
if len(np) > 1:
|
|
nps.append((np.start_char, np.end_char, np.root.tag_, np.text, np.root.ent_type_))
|
|
for np in nps:
|
|
start, end, tag, lemma, ent_type = np
|
|
doc.merge(start, end, tag=tag, lemma=lemma, ent_type=ent_type)
|
|
|
|
|
|
def test_doc_api_right_edge(en_tokenizer):
|
|
"""Test for bug occurring from Unshift action, causing incorrect right edge"""
|
|
text = "I have proposed to myself, for the sake of such as live under the government of the Romans, to translate those books into the Greek tongue."
|
|
heads = [2, 1, 0, -1, -1, -3, 15, 1, -2, -1, 1, -3, -1, -1, 1, -2, -1, 1,
|
|
-2, -7, 1, -19, 1, -2, -3, 2, 1, -3, -26]
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
|
|
assert doc[6].text == 'for'
|
|
subtree = [w.text for w in doc[6].subtree]
|
|
assert subtree == ['for', 'the', 'sake', 'of', 'such', 'as',
|
|
'live', 'under', 'the', 'government', 'of', 'the', 'Romans', ',']
|
|
assert doc[6].right_edge.text == ','
|
|
|
|
|
|
def test_doc_api_has_vector():
|
|
vocab = Vocab()
|
|
vocab.reset_vectors(width=2)
|
|
vocab.set_vector('kitten', vector=numpy.asarray([0., 2.], dtype='f'))
|
|
doc = Doc(vocab, words=['kitten'])
|
|
assert doc.has_vector
|
|
|
|
def test_lowest_common_ancestor(en_tokenizer):
|
|
tokens = en_tokenizer('the lazy dog slept')
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=[2, 1, 1, 0])
|
|
lca = doc.get_lca_matrix()
|
|
assert(lca[1, 1] == 1)
|
|
assert(lca[0, 1] == 2)
|
|
assert(lca[1, 2] == 2)
|
|
|
|
def test_parse_tree(en_tokenizer):
|
|
"""Tests doc.print_tree() method."""
|
|
text = 'I like New York in Autumn.'
|
|
heads = [1, 0, 1, -2, -3, -1, -5]
|
|
tags = ['PRP', 'IN', 'NNP', 'NNP', 'IN', 'NNP', '.']
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, tags=tags)
|
|
# full method parse_tree(text) is a trivial composition
|
|
trees = doc.print_tree()
|
|
assert len(trees) > 0
|
|
tree = trees[0]
|
|
assert all(k in list(tree.keys()) for k in ['word', 'lemma', 'NE', 'POS_fine', 'POS_coarse', 'arc', 'modifiers'])
|
|
assert tree['word'] == 'like' # check root is correct
|