spaCy/spacy/tests/doc/test_noun_chunks.py
2017-05-28 15:10:22 +02:00

32 lines
1.1 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from ...attrs import HEAD, DEP
from ...symbols import nsubj, dobj, amod, nmod, conj, cc, root
from ...syntax.iterators import english_noun_chunks
from ..util import get_doc
import numpy
def test_doc_noun_chunks_not_nested(en_tokenizer):
text = "Peter has chronic command and control issues"
heads = [1, 0, 4, 3, -1, -2, -5]
deps = ['nsubj', 'ROOT', 'amod', 'nmod', 'cc', 'conj', 'dobj']
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, deps=deps)
tokens.from_array(
[HEAD, DEP],
numpy.asarray([[1, nsubj], [0, root], [4, amod], [3, nmod], [-1, cc],
[-2, conj], [-5, dobj]], dtype='uint64'))
tokens.noun_chunks_iterator = english_noun_chunks
word_occurred = {}
for chunk in tokens.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 tokens.noun_chunks])