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File Content: `test_fixes.py`

# Authors: Gael Varoquaux <gael.varoquaux@normalesup.org>
#          Justin Vincent
#          Lars Buitinck
# License: BSD 3 clause

import pickle
import numpy as np

from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_false
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal

from sklearn.utils.fixes import divide, expit
from sklearn.utils.fixes import astype
from sklearn.utils.fixes import MaskedArray


def test_expit():
    # Check numerical stability of expit (logistic function).

    # Simulate our previous Cython implementation, based on
    #http://fa.bianp.net/blog/2013/numerical-optimizers-for-logistic-regression
    assert_almost_equal(expit(1000.), 1. / (1. + np.exp(-1000.)), decimal=16)
    assert_almost_equal(expit(-1000.), np.exp(-1000.) / (1. + np.exp(-1000.)),
                        decimal=16)

    x = np.arange(10)
    out = np.zeros_like(x, dtype=np.float32)
    assert_array_almost_equal(expit(x), expit(x, out=out))


def test_divide():
    assert_equal(divide(.6, 1), .600000000000)


def test_astype_copy_memory():
    a_int32 = np.ones(3, np.int32)

    # Check that dtype conversion works
    b_float32 = astype(a_int32, dtype=np.float32, copy=False)
    assert_equal(b_float32.dtype, np.float32)

    # Changing dtype forces a copy even if copy=False
    assert_false(np.may_share_memory(b_float32, a_int32))

    # Check that copy can be skipped if requested dtype match
    c_int32 = astype(a_int32, dtype=np.int32, copy=False)
    assert_true(c_int32 is a_int32)

    # Check that copy can be forced, and is the case by default:
    d_int32 = astype(a_int32, dtype=np.int32, copy=True)
    assert_false(np.may_share_memory(d_int32, a_int32))

    e_int32 = astype(a_int32, dtype=np.int32)
    assert_false(np.may_share_memory(e_int32, a_int32))


def test_masked_array_obj_dtype_pickleable():
    marr = MaskedArray([1, None, 'a'], dtype=object)

    for mask in (True, False, [0, 1, 0]):
        marr.mask = mask
        marr_pickled = pickle.loads(pickle.dumps(marr))
        assert_array_equal(marr.data, marr_pickled.data)
        assert_array_equal(marr.mask, marr_pickled.mask)

Name	Size	Permission
__pycache__	---	0755
__init__.py	0 bytes	0644
test_bench.py	292 bytes	0644
test_class_weight.py	13151 bytes	0644
test_estimator_checks.py	4395 bytes	0644
test_extmath.py	24372 bytes	0644
test_fast_dict.py	939 bytes	0644
test_fixes.py	2324 bytes	0644
test_graph.py	946 bytes	0644
test_linear_assignment.py	1349 bytes	0644
test_metaestimators.py	2304 bytes	0644
test_multiclass.py	14316 bytes	0644
test_murmurhash.py	2849 bytes	0644
test_optimize.py	768 bytes	0644
test_random.py	7349 bytes	0644
test_seq_dataset.py	2497 bytes	0644
test_shortest_path.py	2841 bytes	0644
test_sparsefuncs.py	17611 bytes	0644
test_stats.py	633 bytes	0644
test_testing.py	7883 bytes	0644
test_utils.py	9089 bytes	0644
test_validation.py	18975 bytes	0644

File Content: test_fixes.py

File Content: `test_fixes.py`