50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
"""Testing for bicluster metrics module"""
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import numpy as np
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from sklearn.utils.testing import assert_equal, assert_almost_equal
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from sklearn.metrics.cluster.bicluster import _jaccard
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from sklearn.metrics import consensus_score
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def test_jaccard():
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a1 = np.array([True, True, False, False])
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a2 = np.array([True, True, True, True])
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a3 = np.array([False, True, True, False])
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a4 = np.array([False, False, True, True])
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assert_equal(_jaccard(a1, a1, a1, a1), 1)
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assert_equal(_jaccard(a1, a1, a2, a2), 0.25)
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assert_equal(_jaccard(a1, a1, a3, a3), 1.0 / 7)
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assert_equal(_jaccard(a1, a1, a4, a4), 0)
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def test_consensus_score():
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a = [[True, True, False, False],
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[False, False, True, True]]
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b = a[::-1]
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assert_equal(consensus_score((a, a), (a, a)), 1)
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assert_equal(consensus_score((a, a), (b, b)), 1)
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assert_equal(consensus_score((a, b), (a, b)), 1)
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assert_equal(consensus_score((a, b), (b, a)), 1)
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assert_equal(consensus_score((a, a), (b, a)), 0)
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assert_equal(consensus_score((a, a), (a, b)), 0)
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assert_equal(consensus_score((b, b), (a, b)), 0)
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assert_equal(consensus_score((b, b), (b, a)), 0)
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def test_consensus_score_issue2445():
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''' Different number of biclusters in A and B'''
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a_rows = np.array([[True, True, False, False],
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[False, False, True, True],
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[False, False, False, True]])
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a_cols = np.array([[True, True, False, False],
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[False, False, True, True],
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[False, False, False, True]])
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idx = [0, 2]
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s = consensus_score((a_rows, a_cols), (a_rows[idx], a_cols[idx]))
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# B contains 2 of the 3 biclusters in A, so score should be 2/3
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assert_almost_equal(s, 2.0/3.0)
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