/usr/lib/python2.7/dist-packages/numpy/ma/tests/test_regression.py is in python-numpy 1:1.12.1-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | from __future__ import division, absolute_import, print_function
import warnings
import numpy as np
from numpy.testing import (assert_, TestCase, assert_array_equal,
assert_allclose, run_module_suite,
suppress_warnings)
from numpy.compat import sixu
rlevel = 1
class TestRegression(TestCase):
def test_masked_array_create(self,level=rlevel):
# Ticket #17
x = np.ma.masked_array([0, 1, 2, 3, 0, 4, 5, 6],
mask=[0, 0, 0, 1, 1, 1, 0, 0])
assert_array_equal(np.ma.nonzero(x), [[1, 2, 6, 7]])
def test_masked_array(self,level=rlevel):
# Ticket #61
np.ma.array(1, mask=[1])
def test_mem_masked_where(self,level=rlevel):
# Ticket #62
from numpy.ma import masked_where, MaskType
a = np.zeros((1, 1))
b = np.zeros(a.shape, MaskType)
c = masked_where(b, a)
a-c
def test_masked_array_multiply(self,level=rlevel):
# Ticket #254
a = np.ma.zeros((4, 1))
a[2, 0] = np.ma.masked
b = np.zeros((4, 2))
a*b
b*a
def test_masked_array_repeat(self, level=rlevel):
# Ticket #271
np.ma.array([1], mask=False).repeat(10)
def test_masked_array_repr_unicode(self):
# Ticket #1256
repr(np.ma.array(sixu("Unicode")))
def test_atleast_2d(self):
# Ticket #1559
a = np.ma.masked_array([0.0, 1.2, 3.5], mask=[False, True, False])
b = np.atleast_2d(a)
assert_(a.mask.ndim == 1)
assert_(b.mask.ndim == 2)
def test_set_fill_value_unicode_py3(self):
# Ticket #2733
a = np.ma.masked_array(['a', 'b', 'c'], mask=[1, 0, 0])
a.fill_value = 'X'
assert_(a.fill_value == 'X')
def test_var_sets_maskedarray_scalar(self):
# Issue gh-2757
a = np.ma.array(np.arange(5), mask=True)
mout = np.ma.array(-1, dtype=float)
a.var(out=mout)
assert_(mout._data == 0)
def test_ddof_corrcoef(self):
# See gh-3336
x = np.ma.masked_equal([1, 2, 3, 4, 5], 4)
y = np.array([2, 2.5, 3.1, 3, 5])
# this test can be removed after deprecation.
with suppress_warnings() as sup:
sup.filter(DeprecationWarning, "bias and ddof have no effect")
r0 = np.ma.corrcoef(x, y, ddof=0)
r1 = np.ma.corrcoef(x, y, ddof=1)
# ddof should not have an effect (it gets cancelled out)
assert_allclose(r0.data, r1.data)
if __name__ == "__main__":
run_module_suite()
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