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94 lines
2.4 KiB
Python
94 lines
2.4 KiB
Python
from __future__ import unicode_literals
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from spacy.attrs import HEAD
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from spacy.en import English
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from spacy.tokens.doc import Doc
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import numpy as np
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import pytest
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@pytest.fixture
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def doc(EN):
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return EN('This is a sentence. This is another sentence. And a third.')
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@pytest.mark.models
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def test_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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@pytest.mark.models
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def test_root(doc):
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np = doc[2:4]
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assert len(np) == 2
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assert np.orth_ == 'a sentence'
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assert np.root.orth_ == 'sentence'
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assert np.root.head.orth_ == 'is'
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def test_root2(EN):
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text = 'through North and South Carolina'
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doc = EN(text)
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heads = np.asarray([[0, 3, -1, -2, -4]], dtype='int32')
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doc.from_array([HEAD], heads.T)
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south_carolina = doc[-2:]
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assert south_carolina.root.text == 'Carolina'
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def test_sent(doc):
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'''Test new span.sent property'''
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#return EN('This is a sentence. This is another sentence. And a third.')
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heads = np.asarray([[1, 0, -1, -1, -1, 1, 0, -1, -1, -1, 2, 1, 0, -1]], dtype='int32')
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doc.from_array([HEAD], heads.T)
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assert len(list(doc.sents))
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span = doc[:2]
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assert span.sent.root.text == 'is'
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assert span.sent.text == 'This is a sentence.'
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span = doc[6:7]
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assert span.sent.root.left_edge.text == 'This'
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def test_default_sentiment(EN):
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'''Test new span.sentiment property's default averaging behaviour'''
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good = EN.vocab[u'good']
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good.sentiment = 3.0
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bad = EN.vocab[u'bad']
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bad.sentiment = -2.0
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doc = Doc(EN.vocab, [u'good', 'stuff', u'bad', u'stuff'])
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good_stuff = doc[:2]
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assert good_stuff.sentiment == 3.0 / 2
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bad_stuff = doc[-2:]
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assert bad_stuff.sentiment == -2. / 2
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good_stuff_bad = doc[:-1]
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assert good_stuff_bad.sentiment == (3.+-2) / 3.
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def test_override_sentiment(EN):
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'''Test new span.sentiment property's default averaging behaviour'''
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good = EN.vocab[u'good']
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good.sentiment = 3.0
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bad = EN.vocab[u'bad']
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bad.sentiment = -2.0
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doc = Doc(EN.vocab, [u'good', 'stuff', u'bad', u'stuff'])
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doc.user_span_hooks['sentiment'] = lambda span: 10.0
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good_stuff = doc[:2]
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assert good_stuff.sentiment == 10.0
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bad_stuff = doc[-2:]
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assert bad_stuff.sentiment == 10.0
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good_stuff_bad = doc[:-1]
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assert good_stuff_bad.sentiment == 10.0
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