56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
# Authors: Gael Varoquaux <gael.varoquaux@normalesup.org>
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# Justin Vincent
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# Lars Buitinck
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# License: BSD 3 clause
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import numpy as np
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from nose.tools import assert_equal
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from nose.tools import assert_false
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from nose.tools import assert_true
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from numpy.testing import (assert_almost_equal,
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assert_array_almost_equal)
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from sklearn.utils.fixes import divide, expit
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from sklearn.utils.fixes import astype
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def test_expit():
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# Check numerical stability of expit (logistic function).
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# Simulate our previous Cython implementation, based on
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#http://fa.bianp.net/blog/2013/numerical-optimizers-for-logistic-regression
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assert_almost_equal(expit(1000.), 1. / (1. + np.exp(-1000.)), decimal=16)
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assert_almost_equal(expit(-1000.), np.exp(-1000.) / (1. + np.exp(-1000.)),
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decimal=16)
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x = np.arange(10)
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out = np.zeros_like(x, dtype=np.float32)
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assert_array_almost_equal(expit(x), expit(x, out=out))
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def test_divide():
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assert_equal(divide(.6, 1), .600000000000)
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def test_astype_copy_memory():
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a_int32 = np.ones(3, np.int32)
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# Check that dtype conversion works
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b_float32 = astype(a_int32, dtype=np.float32, copy=False)
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assert_equal(b_float32.dtype, np.float32)
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# Changing dtype forces a copy even if copy=False
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assert_false(np.may_share_memory(b_float32, a_int32))
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# Check that copy can be skipped if requested dtype match
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c_int32 = astype(a_int32, dtype=np.int32, copy=False)
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assert_true(c_int32 is a_int32)
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# Check that copy can be forced, and is the case by default:
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d_int32 = astype(a_int32, dtype=np.int32, copy=True)
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assert_false(np.may_share_memory(d_int32, a_int32))
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e_int32 = astype(a_int32, dtype=np.int32)
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assert_false(np.may_share_memory(e_int32, a_int32))
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