55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
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import numpy as np
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from numpy.testing import assert_array_equal
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from sklearn.utils._unique import attach_unique, cached_unique
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from sklearn.utils.validation import check_array
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def test_attach_unique_attaches_unique_to_array():
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arr = np.array([1, 2, 2, 3, 4, 4, 5])
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arr_ = attach_unique(arr)
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assert_array_equal(arr_.dtype.metadata["unique"], np.array([1, 2, 3, 4, 5]))
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assert_array_equal(arr_, arr)
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def test_cached_unique_returns_cached_unique():
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my_dtype = np.dtype(np.float64, metadata={"unique": np.array([1, 2])})
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arr = np.array([1, 2, 2, 3, 4, 4, 5], dtype=my_dtype)
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assert_array_equal(cached_unique(arr), np.array([1, 2]))
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def test_attach_unique_not_ndarray():
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"""Test that when not np.ndarray, we don't touch the array."""
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arr = [1, 2, 2, 3, 4, 4, 5]
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arr_ = attach_unique(arr)
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assert arr_ is arr
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def test_attach_unique_returns_view():
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"""Test that attach_unique returns a view of the array."""
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arr = np.array([1, 2, 2, 3, 4, 4, 5])
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arr_ = attach_unique(arr)
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assert arr_.base is arr
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def test_attach_unique_return_tuple():
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"""Test return_tuple argument of the function."""
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arr = np.array([1, 2, 2, 3, 4, 4, 5])
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arr_tuple = attach_unique(arr, return_tuple=True)
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assert isinstance(arr_tuple, tuple)
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assert len(arr_tuple) == 1
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assert_array_equal(arr_tuple[0], arr)
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arr_single = attach_unique(arr, return_tuple=False)
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assert isinstance(arr_single, np.ndarray)
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assert_array_equal(arr_single, arr)
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def test_check_array_keeps_unique():
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"""Test that check_array keeps the unique metadata."""
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arr = np.array([[1, 2, 2, 3, 4, 4, 5]])
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arr_ = attach_unique(arr)
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arr_ = check_array(arr_)
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assert_array_equal(arr_.dtype.metadata["unique"], np.array([1, 2, 3, 4, 5]))
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assert_array_equal(arr_, arr)
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