mirror of
https://github.com/hwchase17/langchain
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40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
"""Test math utility functions."""
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from typing import List
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import numpy as np
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from langchain.math_utils import cosine_similarity
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def test_cosine_similarity_zero() -> None:
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X = np.zeros((3, 3))
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Y = np.random.random((3, 3))
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expected = np.zeros((3, 3))
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actual = cosine_similarity(X, Y)
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assert np.allclose(expected, actual)
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def test_cosine_similarity_identity() -> None:
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X = np.random.random((4, 4))
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expected = np.ones(4)
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actual = np.diag(cosine_similarity(X, X))
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assert np.allclose(expected, actual)
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def test_cosine_similarity_empty() -> None:
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empty_list: List[List[float]] = []
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assert len(cosine_similarity(empty_list, empty_list)) == 0
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assert len(cosine_similarity(empty_list, np.random.random((3, 3)))) == 0
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def test_cosine_similarity() -> None:
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X = [[1.0, 2.0, 3.0], [0.0, 1.0, 0.0], [1.0, 2.0, 0.0]]
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Y = [[0.5, 1.0, 1.5], [1.0, 0.0, 0.0], [2.0, 5.0, 2.0]]
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expected = [
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[1.0, 0.26726124, 0.83743579],
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[0.53452248, 0.0, 0.87038828],
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[0.5976143, 0.4472136, 0.93419873],
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]
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actual = cosine_similarity(X, Y)
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assert np.allclose(expected, actual)
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