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Modernise tests for merging spans and don't depend on models

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Ines Montani 2017-01-12 12:26:26 +01:00
parent fa8f67596d
commit 99d66d613a
1 changed files with 93 additions and 65 deletions
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spacy/tests/spans/test_merge.py
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@ -1,89 +1,117 @@
# coding: utf-8
from __future__ import unicode_literals
from spacy.attrs import HEAD
from ..util import get_doc
import pytest
import numpy
def test_merge_tokens(EN):
tokens = EN(u'Los Angeles start.')
tokens.from_array([HEAD], numpy.asarray([[1, 1, 0, -1]], dtype='int32').T)
assert len(tokens) == 4
assert tokens[0].head.orth_ == 'Angeles'
assert tokens[1].head.orth_ == 'start'
tokens.merge(0, len('Los Angeles'), 'NNP', 'Los Angeles', 'GPE')
assert len(tokens) == 3
assert tokens[0].orth_ == 'Los Angeles'
assert tokens[0].head.orth_ == 'start'
def test_spans_merge_tokens(en_tokenizer):
text = "Los Angeles start."
heads = [1, 1, 0, -1]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
assert len(doc) == 4
assert doc[0].head.text == 'Angeles'
assert doc[1].head.text == 'start'
doc.merge(0, len('Los Angeles'), 'NNP', 'Los Angeles', 'GPE')
assert len(doc) == 3
assert doc[0].text == 'Los Angeles'
assert doc[0].head.text == 'start'
@pytest.mark.models
def test_merge_heads(EN):
tokens = EN(u'I found a pilates class near work.')
assert len(tokens) == 8
tokens.merge(tokens[3].idx, tokens[4].idx + len(tokens[4]), tokens[4].tag_,
'pilates class', 'O')
assert len(tokens) == 7
assert tokens[0].head.i == 1
assert tokens[1].head.i == 1
assert tokens[2].head.i == 3
assert tokens[3].head.i == 1
assert tokens[4].head.i in [1, 3]
assert tokens[5].head.i == 4
def test_spans_merge_heads(en_tokenizer):
text = "I found a pilates class near work."
heads = [1, 0, 2, 1, -3, -1, -1, -6]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
assert len(doc) == 8
doc.merge(doc[3].idx, doc[4].idx + len(doc[4]), doc[4].tag_, 'pilates class', 'O')
assert len(doc) == 7
assert doc[0].head.i == 1
assert doc[1].head.i == 1
assert doc[2].head.i == 3
assert doc[3].head.i == 1
assert doc[4].head.i in [1, 3]
assert doc[5].head.i == 4
def test_span_np_merges(en_tokenizer):
text = "displaCy is a parse tool built with Javascript"
heads = [1, 0, 2, 1, -3, -1, -1, -1]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
@pytest.mark.models
def test_np_merges(EN):
text = u'displaCy is a parse tool built with Javascript'
tokens = EN(text)
assert tokens[4].head.i == 1
tokens.merge(tokens[2].idx, tokens[4].idx + len(tokens[4]), u'NP', u'tool', u'O')
assert tokens[2].head.i == 1
tokens = EN('displaCy is a lightweight and modern dependency parse tree visualization tool built with CSS3 and JavaScript.')
ents = [(e[0].idx, e[-1].idx + len(e[-1]), e.label_, e.lemma_)
for e in tokens.ents]
assert doc[4].head.i == 1
doc.merge(doc[2].idx, doc[4].idx + len(doc[4]), 'NP', 'tool', 'O')
assert doc[2].head.i == 1
text = "displaCy is a lightweight and modern dependency parse tree visualization tool built with CSS3 and JavaScript."
heads = [1, 0, 8, 3, -1, -2, 4, 3, 1, 1, -9, -1, -1, -1, -1, -2, -15]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
ents = [(e[0].idx, e[-1].idx + len(e[-1]), e.label_, e.lemma_) for e in doc.ents]
for start, end, label, lemma in ents:
merged = tokens.merge(start, end, label, lemma, label)
assert merged != None, (start, end, label, lemma)
merged = doc.merge(start, end, label, lemma, label)
assert merged != None, (start, end, label, lemma)
tokens = EN(u'One test with entities like New York City so the ents list is not void')
text = "One test with entities like New York City so the ents list is not void"
heads = [1, 11, -1, -1, -1, 1, 1, -3, 4, 2, 1, 1, 0, -1, -2]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
for span in tokens.ents:
merged = span.merge()
assert merged != None, (span.start, span.end, span.label_, span.lemma_)
for span in doc.ents:
merged = doc.merge()
assert merged != None, (span.start, span.end, span.label_, span.lemma_)
@pytest.mark.models
def test_entity_merge(EN):
tokens = EN(u'Stewart Lee is a stand up comedian who lives in England and loves Joe Pasquale.\n')
assert(len(tokens) == 17)
for ent in tokens.ents:
def test_spans_entity_merge(en_tokenizer):
text = "Stewart Lee is a stand up comedian who lives in England and loves Joe Pasquale.\n"
heads = [1, 1, 0, 1, 2, -1, -4, 1, -2, -1, -1, -3, -10, 1, -2, -13, -1]
tags = ['NNP', 'NNP', 'VBZ', 'DT', 'VB', 'RP', 'NN', 'WP', 'VBZ', 'IN', 'NNP', 'CC', 'VBZ', 'NNP', 'NNP', '.', 'SP']
ents = [('Stewart Lee', 'PERSON', 0, 2), ('England', 'GPE', 10, 11), ('Joe Pasquale', 'PERSON', 13, 15)]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, tags=tags, ents=ents)
assert len(doc) == 17
for ent in doc.ents:
label, lemma, type_ = (ent.root.tag_, ent.root.lemma_, max(w.ent_type_ for w in ent))
ent.merge(label, lemma, type_)
# check looping is ok
assert(len(tokens) == 15)
assert len(doc) == 15
@pytest.mark.models
def test_sentence_update_after_merge(EN):
tokens = EN(u'Stewart Lee is a stand up comedian. He lives in England and loves Joe Pasquale.')
sent1, sent2 = list(tokens.sents)
def test_spans_sentence_update_after_merge(en_tokenizer):
text = "Stewart Lee is a stand up comedian. He lives in England and loves Joe Pasquale."
heads = [1, 1, 0, 1, 2, -1, -4, -5, 1, 0, -1, -1, -3, -4, 1, -2, -7]
deps = ['compound', 'nsubj', 'ROOT', 'det', 'amod', 'prt', 'attr',
'punct', 'nsubj', 'ROOT', 'prep', 'pobj', 'cc', 'conj',
'compound', 'dobj', 'punct']
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, deps=deps)
sent1, sent2 = list(doc.sents)
init_len = len(sent1)
init_len2 = len(sent2)
merge_me = tokens[0:2]
merge_me.merge(u'none', u'none', u'none')
merge_me2 = tokens[-2:]
merge_me2.merge(u'none', u'none', u'none')
assert(len(sent1) == init_len - 1)
assert(len(sent2) == init_len2 - 1)
doc[0:2].merge('none', 'none', 'none')
doc[-2:].merge('none', 'none', 'none')
assert len(sent1) == init_len - 1
assert len(sent2) == init_len2 - 1
@pytest.mark.models
def test_subtree_size_check(EN):
tokens = EN(u'Stewart Lee is a stand up comedian who lives in England and loves Joe Pasquale')
sent1 = list(tokens.sents)[0]
def test_spans_subtree_size_check(en_tokenizer):
text = "Stewart Lee is a stand up comedian who lives in England and loves Joe Pasquale"
heads = [1, 1, 0, 1, 2, -1, -4, 1, -2, -1, -1, -3, -10, 1, -2]
deps = ['compound', 'nsubj', 'ROOT', 'det', 'amod', 'prt', 'attr',
'nsubj', 'relcl', 'prep', 'pobj', 'cc', 'conj', 'compound',
'dobj']
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, deps=deps)
sent1 = list(doc.sents)[0]
init_len = len(list(sent1.root.subtree))
merge_me = tokens[0:2]
merge_me.merge(u'none', u'none', u'none')
assert(len(list(sent1.root.subtree)) == init_len - 1)
doc[0:2].merge('none', 'none', 'none')
assert len(list(sent1.root.subtree)) == init_len - 1