90 lines
2.6 KiB
Python
90 lines
2.6 KiB
Python
from nose.tools import assert_equal, assert_raises, assert_true
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import warnings
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import numpy as np
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import scipy.sparse as sp
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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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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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