spaCy/spacy/tests/doc/test_array.py

63 lines
2.1 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from ...attrs import ORTH, SHAPE, POS, DEP
from ..util import get_doc
import pytest
def test_doc_array_attr_of_token(en_tokenizer, en_vocab):
text = "An example sentence"
tokens = en_tokenizer(text)
example = tokens.vocab["example"]
assert example.orth != example.shape
feats_array = tokens.to_array((ORTH, SHAPE))
assert feats_array[0][0] != feats_array[0][1]
assert feats_array[0][0] != feats_array[0][1]
def test_doc_stringy_array_attr_of_token(en_tokenizer, en_vocab):
text = "An example sentence"
tokens = en_tokenizer(text)
example = tokens.vocab["example"]
assert example.orth != example.shape
feats_array = tokens.to_array((ORTH, SHAPE))
feats_array_stringy = tokens.to_array(("ORTH", "SHAPE"))
assert feats_array_stringy[0][0] == feats_array[0][0]
assert feats_array_stringy[0][1] == feats_array[0][1]
def test_doc_scalar_attr_of_token(en_tokenizer, en_vocab):
text = "An example sentence"
tokens = en_tokenizer(text)
example = tokens.vocab["example"]
assert example.orth != example.shape
feats_array = tokens.to_array(ORTH)
assert feats_array.shape == (3,)
def test_doc_array_tag(en_tokenizer):
text = "A nice sentence."
pos = ['DET', 'ADJ', 'NOUN', 'PUNCT']
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], pos=pos)
assert doc[0].pos != doc[1].pos != doc[2].pos != doc[3].pos
feats_array = doc.to_array((ORTH, POS))
assert feats_array[0][1] == doc[0].pos
assert feats_array[1][1] == doc[1].pos
assert feats_array[2][1] == doc[2].pos
assert feats_array[3][1] == doc[3].pos
def test_doc_array_dep(en_tokenizer):
text = "A nice sentence."
deps = ['det', 'amod', 'ROOT', 'punct']
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], deps=deps)
feats_array = doc.to_array((ORTH, DEP))
assert feats_array[0][1] == doc[0].dep
assert feats_array[1][1] == doc[1].dep
assert feats_array[2][1] == doc[2].dep
assert feats_array[3][1] == doc[3].dep