spaCy/spacy/tests/lang/en/test_noun_chunks.py
2020-09-21 20:43:54 +02:00

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])