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