mirror of https://github.com/explosion/spaCy.git
61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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from ..util import get_doc, get_cosine, add_vecs_to_vocab
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import numpy
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import pytest
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@pytest.fixture
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def vectors():
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return [("apple", [1, 2, 3]), ("orange", [-1, -2, -3])]
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@pytest.fixture()
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def vocab(en_vocab, vectors):
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add_vecs_to_vocab(en_vocab, vectors)
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return en_vocab
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def test_vectors_similarity_LL(vocab, vectors):
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[(word1, vec1), (word2, vec2)] = vectors
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lex1 = vocab[word1]
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lex2 = vocab[word2]
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assert lex1.has_vector
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assert lex2.has_vector
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assert lex1.vector_norm != 0
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assert lex2.vector_norm != 0
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assert lex1.vector[0] != lex2.vector[0] and lex1.vector[1] != lex2.vector[1]
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assert numpy.isclose(lex1.similarity(lex2), get_cosine(vec1, vec2))
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assert numpy.isclose(lex2.similarity(lex2), lex1.similarity(lex1))
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def test_vectors_similarity_TT(vocab, vectors):
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[(word1, vec1), (word2, vec2)] = vectors
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doc = get_doc(vocab, words=[word1, word2])
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assert doc[0].has_vector
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assert doc[1].has_vector
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assert doc[0].vector_norm != 0
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assert doc[1].vector_norm != 0
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assert doc[0].vector[0] != doc[1].vector[0] and doc[0].vector[1] != doc[1].vector[1]
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assert numpy.isclose(doc[0].similarity(doc[1]), get_cosine(vec1, vec2))
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assert numpy.isclose(doc[1].similarity(doc[0]), doc[0].similarity(doc[1]))
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def test_vectors_similarity_TD(vocab, vectors):
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[(word1, vec1), (word2, vec2)] = vectors
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doc = get_doc(vocab, words=[word1, word2])
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assert doc.similarity(doc[0]) == doc[0].similarity(doc)
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def test_vectors_similarity_DS(vocab, vectors):
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[(word1, vec1), (word2, vec2)] = vectors
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doc = get_doc(vocab, words=[word1, word2])
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assert doc.similarity(doc[:2]) == doc[:2].similarity(doc)
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def test_vectors_similarity_TS(vocab, vectors):
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[(word1, vec1), (word2, vec2)] = vectors
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doc = get_doc(vocab, words=[word1, word2])
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assert doc[:2].similarity(doc[0]) == doc[0].similarity(doc[:2])
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