spaCy/spacy/tests/util.py

107 lines
3.4 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
import numpy
import tempfile
import shutil
import contextlib
import msgpack
from pathlib import Path
from spacy.tokens import Doc, Span
from spacy.attrs import POS, HEAD, DEP
from spacy.compat import path2str
@contextlib.contextmanager
def make_tempfile(mode='r'):
f = tempfile.TemporaryFile(mode=mode)
yield f
f.close()
@contextlib.contextmanager
def make_tempdir():
d = Path(tempfile.mkdtemp())
yield d
shutil.rmtree(path2str(d))
def get_doc(vocab, words=[], pos=None, heads=None, deps=None, tags=None, ents=None):
"""Create Doc object from given vocab, words and annotations."""
pos = pos or [''] * len(words)
tags = tags or [''] * len(words)
heads = heads or [0] * len(words)
deps = deps or [''] * len(words)
for value in (deps+tags+pos):
vocab.strings.add(value)
doc = Doc(vocab, words=words)
attrs = doc.to_array([POS, HEAD, DEP])
for i, (p, head, dep) in enumerate(zip(pos, heads, deps)):
attrs[i, 0] = doc.vocab.strings[p]
attrs[i, 1] = head
attrs[i, 2] = doc.vocab.strings[dep]
doc.from_array([POS, HEAD, DEP], attrs)
if ents:
doc.ents = [Span(doc, start, end, label=doc.vocab.strings[label])
for start, end, label in ents]
if tags:
for token in doc:
token.tag_ = tags[token.i]
return doc
def apply_transition_sequence(parser, doc, sequence):
"""Perform a series of pre-specified transitions, to put the parser in a
desired state."""
for action_name in sequence:
if '-' in action_name:
move, label = action_name.split('-')
parser.add_label(label)
with parser.step_through(doc) as stepwise:
for transition in sequence:
stepwise.transition(transition)
def add_vecs_to_vocab(vocab, vectors):
"""Add list of vector tuples to given vocab. All vectors need to have the
same length. Format: [("text", [1, 2, 3])]"""
length = len(vectors[0][1])
vocab.reset_vectors(width=length)
for word, vec in vectors:
vocab.set_vector(word, vector=vec)
return vocab
def get_cosine(vec1, vec2):
"""Get cosine for two given vectors"""
return numpy.dot(vec1, vec2) / (numpy.linalg.norm(vec1) * numpy.linalg.norm(vec2))
def assert_docs_equal(doc1, doc2):
"""Compare two Doc objects and assert that they're equal. Tests for tokens,
tags, dependencies and entities."""
assert [ t.orth for t in doc1 ] == [ t.orth for t in doc2 ]
assert [ t.pos for t in doc1 ] == [ t.pos for t in doc2 ]
assert [ t.tag for t in doc1 ] == [ t.tag for t in doc2 ]
assert [ t.head.i for t in doc1 ] == [ t.head.i for t in doc2 ]
assert [ t.dep for t in doc1 ] == [ t.dep for t in doc2 ]
if doc1.is_parsed and doc2.is_parsed:
assert [ s for s in doc1.sents ] == [ s for s in doc2.sents ]
assert [ t.ent_type for t in doc1 ] == [ t.ent_type for t in doc2 ]
assert [ t.ent_iob for t in doc1 ] == [ t.ent_iob for t in doc2 ]
assert [ ent for ent in doc1.ents ] == [ ent for ent in doc2.ents ]
def assert_packed_msg_equal(b1, b2):
"""Assert that two packed msgpack messages are equal."""
msg1 = msgpack.loads(b1, encoding='utf8')
msg2 = msgpack.loads(b2, encoding='utf8')
assert sorted(msg1.keys()) == sorted(msg2.keys())
for (k1, v1), (k2, v2) in zip(sorted(msg1.items()), sorted(msg2.items())):
assert k1 == k2
assert v1 == v2