132 lines
3.9 KiB
Python
132 lines
3.9 KiB
Python
import warnings
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import numpy as np
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import scipy.sparse as sp
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from scipy.linalg import pinv2
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from nose.tools import assert_equal, assert_raises, assert_true
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from numpy.testing import assert_almost_equal, assert_array_equal
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from sklearn.utils import check_random_state
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from sklearn.utils import deprecated
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from sklearn.utils import resample
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from sklearn.utils import safe_mask
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from sklearn.utils import balance_weights
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from sklearn.utils.extmath import pinvh
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def test_make_rng():
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"""Check the check_random_state utility function behavior"""
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assert_true(check_random_state(None) is np.random.mtrand._rand)
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assert_true(check_random_state(np.random) is np.random.mtrand._rand)
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rng_42 = np.random.RandomState(42)
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assert_true(check_random_state(42).randint(100) == rng_42.randint(100))
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rng_42 = np.random.RandomState(42)
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assert_true(check_random_state(rng_42) is rng_42)
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rng_42 = np.random.RandomState(42)
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assert_true(check_random_state(43).randint(100) != rng_42.randint(100))
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assert_raises(ValueError, check_random_state, "some invalid seed")
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def test_resample_noarg():
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"""Border case not worth mentioning in doctests"""
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assert_true(resample() is None)
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def test_deprecated():
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"""Test whether the deprecated decorator issues appropriate warnings"""
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# Copied almost verbatim from http://docs.python.org/library/warnings.html
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# First a function...
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with warnings.catch_warnings(record=True) as w:
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warnings.simplefilter("always")
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@deprecated()
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def ham():
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return "spam"
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spam = ham()
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assert_equal(spam, "spam") # function must remain usable
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assert_equal(len(w), 1)
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assert_true(issubclass(w[0].category, DeprecationWarning))
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assert_true("deprecated" in str(w[0].message).lower())
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# ... then a class.
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with warnings.catch_warnings(record=True) as w:
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warnings.simplefilter("always")
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@deprecated("don't use this")
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class Ham(object):
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SPAM = 1
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ham = Ham()
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assert_true(hasattr(ham, "SPAM"))
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assert_equal(len(w), 1)
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assert_true(issubclass(w[0].category, DeprecationWarning))
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assert_true("deprecated" in str(w[0].message).lower())
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def test_resample_value_errors():
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"""Check that invalid arguments yield ValueError"""
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assert_raises(ValueError, resample, [0], [0, 1])
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assert_raises(ValueError, resample, [0, 1], [0, 1], n_samples=3)
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assert_raises(ValueError, resample, [0, 1], [0, 1], meaning_of_life=42)
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def test_safe_mask():
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random_state = check_random_state(0)
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X = random_state.rand(5, 4)
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X_csr = sp.csr_matrix(X)
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mask = [False, False, True, True, True]
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mask = safe_mask(X, mask)
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assert_equal(X[mask].shape[0], 3)
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mask = safe_mask(X_csr, mask)
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assert_equal(X_csr[mask].shape[0], 3)
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def test_pinvh_simple_real():
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a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 10]], dtype=np.float64)
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a = np.dot(a, a.T)
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a_pinv = pinvh(a)
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assert_almost_equal(np.dot(a, a_pinv), np.eye(3))
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def test_pinvh_nonpositive():
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a = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.float64)
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a = np.dot(a, a.T)
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u, s, vt = np.linalg.svd(a)
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s[0] *= -1
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a = np.dot(u * s, vt) # a is now symmetric non-positive and singular
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a_pinv = pinv2(a)
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a_pinvh = pinvh(a)
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assert_almost_equal(a_pinv, a_pinvh)
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def test_pinvh_simple_complex():
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a = (np.array([[1, 2, 3], [4, 5, 6], [7, 8, 10]])
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+ 1j * np.array([[10, 8, 7], [6, 5, 4], [3, 2, 1]]))
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a = np.dot(a, a.conj().T)
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a_pinv = pinvh(a)
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assert_almost_equal(np.dot(a, a_pinv), np.eye(3))
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def test_balance_weights():
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weights = balance_weights([0, 0, 1, 1])
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assert_array_equal(weights, [1., 1., 1., 1.])
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weights = balance_weights([0, 1, 1, 1, 1])
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assert_array_equal(weights, [1., 0.25, 0.25, 0.25, 0.25])
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weights = balance_weights([0, 0])
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assert_array_equal(weights, [1., 1.])
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