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Initially span.as_doc() was designed to return a view of the span's contents, as a Doc object. This was a nice idea, but it fails due to the token.idx property, which refers to the character offset within the string. In a span, the idx of the first token might not be 0. Because this data is different, we can't have a view --- it'll be inconsistent. This patch changes span.as_doc() to instead return a copy. The docs are updated accordingly. Closes #1537 * Update test for span.as_doc() * Make span.as_doc() return a copy. Closes #1537 * Document change to Span.as_doc()
198 lines
6.2 KiB
Python
198 lines
6.2 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from spacy.attrs import ORTH, LENGTH
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from spacy.tokens import Doc, Span
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from spacy.vocab import Vocab
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from ..util import get_doc
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@pytest.fixture
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def doc(en_tokenizer):
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# fmt: off
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text = "This is a sentence. This is another sentence. And a third."
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heads = [1, 0, 1, -2, -3, 1, 0, 1, -2, -3, 0, 1, -2, -1]
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deps = ["nsubj", "ROOT", "det", "attr", "punct", "nsubj", "ROOT", "det",
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"attr", "punct", "ROOT", "det", "npadvmod", "punct"]
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# fmt: on
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tokens = en_tokenizer(text)
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return get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps)
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@pytest.fixture
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def doc_not_parsed(en_tokenizer):
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text = "This is a sentence. This is another sentence. And a third."
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tokens = en_tokenizer(text)
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doc = Doc(tokens.vocab, words=[t.text for t in tokens])
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doc.is_parsed = False
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return doc
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def test_spans_sent_spans(doc):
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sents = list(doc.sents)
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assert sents[0].start == 0
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assert sents[0].end == 5
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assert len(sents) == 3
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assert sum(len(sent) for sent in sents) == len(doc)
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def test_spans_root(doc):
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span = doc[2:4]
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assert len(span) == 2
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assert span.text == "a sentence"
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assert span.root.text == "sentence"
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assert span.root.head.text == "is"
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def test_spans_string_fn(doc):
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span = doc[0:4]
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assert len(span) == 4
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assert span.text == "This is a sentence"
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assert span.upper_ == "THIS IS A SENTENCE"
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assert span.lower_ == "this is a sentence"
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def test_spans_root2(en_tokenizer):
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text = "through North and South Carolina"
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heads = [0, 3, -1, -2, -4]
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=heads)
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assert doc[-2:].root.text == "Carolina"
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def test_spans_span_sent(doc, doc_not_parsed):
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"""Test span.sent property"""
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assert len(list(doc.sents))
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assert doc[:2].sent.root.text == "is"
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assert doc[:2].sent.text == "This is a sentence ."
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assert doc[6:7].sent.root.left_edge.text == "This"
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# test on manual sbd
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doc_not_parsed[0].is_sent_start = True
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doc_not_parsed[5].is_sent_start = True
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assert doc_not_parsed[1:3].sent == doc_not_parsed[0:5]
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assert doc_not_parsed[10:14].sent == doc_not_parsed[5:]
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def test_spans_lca_matrix(en_tokenizer):
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"""Test span's lca matrix generation"""
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tokens = en_tokenizer("the lazy dog slept")
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doc = get_doc(tokens.vocab, words=[t.text for t in tokens], heads=[2, 1, 1, 0])
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lca = doc[:2].get_lca_matrix()
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assert lca[0, 0] == 0
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assert lca[0, 1] == -1
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assert lca[1, 0] == -1
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assert lca[1, 1] == 1
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def test_span_similarity_match():
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doc = Doc(Vocab(), words=["a", "b", "a", "b"])
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span1 = doc[:2]
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span2 = doc[2:]
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with pytest.warns(None):
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assert span1.similarity(span2) == 1.0
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assert span1.similarity(doc) == 0.0
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assert span1[:1].similarity(doc.vocab["a"]) == 1.0
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def test_spans_default_sentiment(en_tokenizer):
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"""Test span.sentiment property's default averaging behaviour"""
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text = "good stuff bad stuff"
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tokens = en_tokenizer(text)
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tokens.vocab[tokens[0].text].sentiment = 3.0
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tokens.vocab[tokens[2].text].sentiment = -2.0
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doc = Doc(tokens.vocab, words=[t.text for t in tokens])
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assert doc[:2].sentiment == 3.0 / 2
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assert doc[-2:].sentiment == -2.0 / 2
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assert doc[:-1].sentiment == (3.0 + -2) / 3.0
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def test_spans_override_sentiment(en_tokenizer):
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"""Test span.sentiment property's default averaging behaviour"""
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text = "good stuff bad stuff"
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tokens = en_tokenizer(text)
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tokens.vocab[tokens[0].text].sentiment = 3.0
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tokens.vocab[tokens[2].text].sentiment = -2.0
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doc = Doc(tokens.vocab, words=[t.text for t in tokens])
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doc.user_span_hooks["sentiment"] = lambda span: 10.0
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assert doc[:2].sentiment == 10.0
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assert doc[-2:].sentiment == 10.0
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assert doc[:-1].sentiment == 10.0
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def test_spans_are_hashable(en_tokenizer):
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"""Test spans can be hashed."""
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text = "good stuff bad stuff"
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tokens = en_tokenizer(text)
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span1 = tokens[:2]
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span2 = tokens[2:4]
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assert hash(span1) != hash(span2)
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span3 = tokens[0:2]
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assert hash(span3) == hash(span1)
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def test_spans_by_character(doc):
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span1 = doc[1:-2]
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span2 = doc.char_span(span1.start_char, span1.end_char, label="GPE")
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assert span1.start_char == span2.start_char
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assert span1.end_char == span2.end_char
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assert span2.label_ == "GPE"
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def test_span_to_array(doc):
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span = doc[1:-2]
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arr = span.to_array([ORTH, LENGTH])
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assert arr.shape == (len(span), 2)
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assert arr[0, 0] == span[0].orth
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assert arr[0, 1] == len(span[0])
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def test_span_as_doc(doc):
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span = doc[4:10]
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span_doc = span.as_doc()
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assert span.text == span_doc.text.strip()
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assert isinstance(span_doc, doc.__class__)
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assert span_doc is not doc
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assert span_doc[0].idx == 0
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def test_span_string_label(doc):
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span = Span(doc, 0, 1, label='hello')
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assert span.label_ == 'hello'
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assert span.label == doc.vocab.strings['hello']
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def test_span_string_set_label(doc):
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span = Span(doc, 0, 1)
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span.label_ = 'hello'
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assert span.label_ == 'hello'
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assert span.label == doc.vocab.strings['hello']
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def test_span_ents_property(doc):
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"""Test span.ents for the """
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doc.ents = [
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(doc.vocab.strings["PRODUCT"], 0, 1),
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(doc.vocab.strings["PRODUCT"], 7, 8),
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(doc.vocab.strings["PRODUCT"], 11, 14),
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]
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assert len(list(doc.ents)) == 3
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sentences = list(doc.sents)
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assert len(sentences) == 3
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assert len(sentences[0].ents) == 1
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# First sentence, also tests start of sentence
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assert sentences[0].ents[0].text == "This"
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assert sentences[0].ents[0].label_ == "PRODUCT"
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assert sentences[0].ents[0].start == 0
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assert sentences[0].ents[0].end == 1
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# Second sentence
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assert len(sentences[1].ents) == 1
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assert sentences[1].ents[0].text == "another"
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assert sentences[1].ents[0].label_ == "PRODUCT"
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assert sentences[1].ents[0].start == 7
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assert sentences[1].ents[0].end == 8
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# Third sentence ents, Also tests end of sentence
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assert sentences[2].ents[0].text == "a third ."
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assert sentences[2].ents[0].label_ == "PRODUCT"
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assert sentences[2].ents[0].start == 11
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assert sentences[2].ents[0].end == 14
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