| Commit message (Collapse) | Author | Age | Files | Lines |
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WarningManager was a workaround for the lack of the with statement
in Python versions < 2.6. As those versions are no longer supported
it can be removed.
Deprecation notes are added to WarningManager and WarningMessage, but
to avoid a cascade of messages in third party apps, no warnings are
raised at this time, that can be done later.
Closes #3519.
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Range test for n was incorrect.
Closes #3480
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Also edited the 'Parameters' section of the docstring to comply
with the numpy docstring standard.
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Deprecate non integer arguments
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Also minor changes in the documentation.
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Following deprecations would cause problems otherwise.
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See doc/TESTS.rst.txt for the reason.
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Ensure that the multivariate_normal size argument can be a numpy integer. Add regression test. Apply PEP8 to test_regression.py. Regenerate mtrand.c.
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See doc/TESTS.rst.txt for the reason.
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There are two test functions named `test_hypergeometric_range`
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The numliterals fixer replaces the old style octal number like '01' by
'0o1' removes the 'L' suffix.
Octal values were previously mistakenly specified in some dates, those
uses have been corrected by removing the leading zeros.
Simply Removing the 'L' suffix should not be a problem, but in some
testing code it looks neccesary, so in those places the Python long
constructor is used instead.
The 'long' type is no longer defined in Python 3. Because we need to
have it defined for Python 2 it is added to numpy/compat/np3k.py where
it is defined as 'int' for Python 3 and 'long' for Python 2. The `long`
fixer then needs to be skipped so that it doesn't undo the good work.
Closes #3074, #3067.
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Add `print_function` to all `from __future__ import ...` statements
and use the python3 print function syntax everywhere.
Closes #3078.
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DOC: Formatting fixes using regex
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also other spacing or formatting mistakes
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The new import `absolute_import` is added the `from __future__ import`
statement and The 2to3 `import` fixer is run to make the imports
compatible. There are several things that need to be dealt with to make
this work.
1) Files meant to be run as scripts run in a different environment than
files imported as part of a package, and so changes to those files need
to be skipped. The affected script files are:
* all setup.py files
* numpy/core/code_generators/generate_umath.py
* numpy/core/code_generators/generate_numpy_api.py
* numpy/core/code_generators/generate_ufunc_api.py
2) Some imported modules are not available as they are created during
the build process and consequently 2to3 is unable to handle them
correctly. Files that import those modules need a bit of extra work.
The affected files are:
* core/__init__.py,
* core/numeric.py,
* core/_internal.py,
* core/arrayprint.py,
* core/fromnumeric.py,
* numpy/__init__.py,
* lib/npyio.py,
* lib/function_base.py,
* fft/fftpack.py,
* random/__init__.py
Closes #3172
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BUG: fix random.choice scalar object result and disallow 0-d arrays
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Object arrays failed due to bad check for finding out if the result should
be a scalar type and not an array when size=None. Also in this case the
creation of the new array was wrong. This should be fixed with this.
The second fix is to forbid 0-d arrays. Allowing 0-d arrays does not
make much sense. But it is dangerous because for example floats will
be interpreted as 1-d arrays, while one may expect that they are interpreted
as integers. This also saves the trouble of reliably detecting all integers...
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This should be harmless, as we already are division clean. However,
placement of this import takes some care. In the future a script
can be used to append new features without worry, at least until
such time as it exceeds a single line. Having that ability will
make it easier to deal with absolute imports and printing updates.
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This removes files and code supporting scons builds. After this change
numpy will only support builds using distutils or bento. The removal of
scons has been discussed on the list several times and a decision has been
made that scons support is no longer needed. This was originally discussed
for numpy 1.7 and because the distutils and bento methods are still
available we are skipping the usual deprecation period.
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Commit acf7421128b9d974d5153759650b7aaee3c2efec introduced a change in the handling of the `size` argument but the docstring wasn't updated accordingly. This commit fixes the issue.
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fix a spelling error
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An random.random call from within mtrand was done by a call to
np.random.random instead of inside the class. This can possibly lead
to non-deterministic results after seeding.
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Thanks to @alan-isaac for pointing out the 0-d vs. scalar issue.
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Random choice used np.unique to find new indices when replace
was False and p given. This is wrong since unique will sort the
indices. This solves the bug, but likely not ideal.
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The size argument to random.choice should work like it does for all
other functions in random as well.
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The problem was that in 32bit Ubuntu 12.04, one gets the following:
>
/home/njs/numpy/.tox/py27/local/lib/python2.7/site-packages/numpy/random/tests/test_random.py(363)test_pareto()
-> np.testing.assert_array_almost_equal(actual, desired, decimal=15)
(Pdb) actual[1, 0]
52828779.702948704
(Pdb) desired[1, 0]
52828779.702948518
and the test was comparing the numbers to 1e-14, which obviously
failed.
Fixes #424.
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Fixes #416
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The logic in np.random.shuffle was... not very sensible. Fixes trac
ticket #2074.
This patch also exposes a completely unrelated issue in
numpy.testing. Filed as Github issue #347 and marked as knownfail for
now.
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We use the new register_outputs_simple + remove some redundant code.
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_dotblas needs more work to remove direct access to ndarray internals.
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The non-deprecated macros and functions were defined for Cython in
numpy.pxd and mtrand was fixed to use them. In particular, direct
access to structure internals in mtrand.pyx needed to be replaced
by the new access functions.
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This fixes a problem on 64 bit Windows where a 64 bit index is
needed but long is only 32 bits.
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is exactly 1.0.
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