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from sklearn.utils.testing import (assert_array_equal, assert_equal,
assert_raises)
from scipy.sparse import bsr_matrix, csc_matrix, csr_matrix
from sklearn.feature_selection import VarianceThreshold
data = [[0, 1, 2, 3, 4],
[0, 2, 2, 3, 5],
[1, 1, 2, 4, 0]]
def test_zero_variance():
# Test VarianceThreshold with default setting, zero variance.
for X in [data, csr_matrix(data), csc_matrix(data), bsr_matrix(data)]:
sel = VarianceThreshold().fit(X)
assert_array_equal([0, 1, 3, 4], sel.get_support(indices=True))
assert_raises(ValueError, VarianceThreshold().fit, [[0, 1, 2, 3]])
assert_raises(ValueError, VarianceThreshold().fit, [[0, 1], [0, 1]])
def test_variance_threshold():
# Test VarianceThreshold with custom variance.
for X in [data, csr_matrix(data)]:
X = VarianceThreshold(threshold=.4).fit_transform(X)
assert_equal((len(data), 1), X.shape)
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