mirror of https://github.com/explosion/spaCy.git
45 lines
1.4 KiB
Python
45 lines
1.4 KiB
Python
import numpy
|
|
from spacy.attrs import HEAD, DEP
|
|
from spacy.symbols import nsubj, dobj, amod, nmod, conj, cc, root
|
|
from spacy.lang.en.syntax_iterators import noun_chunks
|
|
from spacy.tokens import Doc
|
|
import pytest
|
|
|
|
|
|
def test_noun_chunks_is_parsed(en_tokenizer):
|
|
"""Test that noun_chunks raises Value Error for 'en' language if Doc is not parsed.
|
|
"""
|
|
doc = en_tokenizer("This is a sentence")
|
|
with pytest.raises(ValueError):
|
|
list(doc.noun_chunks)
|
|
|
|
|
|
def test_en_noun_chunks_not_nested(en_vocab):
|
|
words = ["Peter", "has", "chronic", "command", "and", "control", "issues"]
|
|
heads = [1, 1, 6, 6, 3, 3, 1]
|
|
deps = ["nsubj", "ROOT", "amod", "nmod", "cc", "conj", "dobj"]
|
|
doc = Doc(en_vocab, words=words, heads=heads, deps=deps)
|
|
doc.from_array(
|
|
[HEAD, DEP],
|
|
numpy.asarray(
|
|
[
|
|
[1, nsubj],
|
|
[0, root],
|
|
[4, amod],
|
|
[3, nmod],
|
|
[-1, cc],
|
|
[-2, conj],
|
|
[-5, dobj],
|
|
],
|
|
dtype="uint64",
|
|
),
|
|
)
|
|
doc.noun_chunks_iterator = noun_chunks
|
|
word_occurred = {}
|
|
for chunk in doc.noun_chunks:
|
|
for word in chunk:
|
|
word_occurred.setdefault(word.text, 0)
|
|
word_occurred[word.text] += 1
|
|
for word, freq in word_occurred.items():
|
|
assert freq == 1, (word, [chunk.text for chunk in doc.noun_chunks])
|