<feed xmlns='http://www.w3.org/2005/Atom'>
<title>delta/python-packages/numpy.git/numpy/lib/tests/test_arraypad.py, branch maintenance/1.8.x</title>
<subtitle>github.com: numpy/numpy.git
</subtitle>
<link rel='alternate' type='text/html' href='http://git.baserock.org/cgit/delta/python-packages/numpy.git/'/>
<entry>
<title>TST: New test to ensure np.pad allows pad_width of zero.</title>
<updated>2013-07-05T16:17:26+00:00</updated>
<author>
<name>Jostein Bø Fløystad</name>
<email>jostein.floystad@gmail.com</email>
</author>
<published>2013-07-05T16:17:26+00:00</published>
<link rel='alternate' type='text/html' href='http://git.baserock.org/cgit/delta/python-packages/numpy.git/commit/?id=ea45134062693723c2258b862f87d3750a8dc564'/>
<id>ea45134062693723c2258b862f87d3750a8dc564</id>
<content type='text'>
</content>
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<pre>
</pre>
</div>
</content>
</entry>
<entry>
<title>ENH: improved, faster algorithm for array padding</title>
<updated>2013-05-19T19:35:41+00:00</updated>
<author>
<name>Josh Warner (Mac)</name>
<email>warner.joshua@mayo.edu</email>
</author>
<published>2013-05-08T05:13:41+00:00</published>
<link rel='alternate' type='text/html' href='http://git.baserock.org/cgit/delta/python-packages/numpy.git/commit/?id=246c06d2475718ec36ba193494444464e497c69a'/>
<id>246c06d2475718ec36ba193494444464e497c69a</id>
<content type='text'>
New padding method which scales much better with dimensionality.
This new implementation is fully vectorized, builds each abstracted
n-dimensional padding block in a single step, and takes advantage
of separability. The API is completely preserved, and the old
algorithm is used if a vector function is input for `mode`.

The new algorithm is faster for all tested combinations of inputs,
and scales much better with dimensionality. Execution time reductions
from ~25% for small rank 1 arrays to &gt;99% for rank 4+ arrays observed.
</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
New padding method which scales much better with dimensionality.
This new implementation is fully vectorized, builds each abstracted
n-dimensional padding block in a single step, and takes advantage
of separability. The API is completely preserved, and the old
algorithm is used if a vector function is input for `mode`.

The new algorithm is faster for all tested combinations of inputs,
and scales much better with dimensionality. Execution time reductions
from ~25% for small rank 1 arrays to &gt;99% for rank 4+ arrays observed.
</pre>
</div>
</content>
</entry>
<entry>
<title>2to3: Apply `print` fixer.</title>
<updated>2013-04-06T19:25:26+00:00</updated>
<author>
<name>Charles Harris</name>
<email>charlesr.harris@gmail.com</email>
</author>
<published>2013-04-06T19:25:26+00:00</published>
<link rel='alternate' type='text/html' href='http://git.baserock.org/cgit/delta/python-packages/numpy.git/commit/?id=bb726ca19f434f5055c0efceefe48d89469fcbbe'/>
<id>bb726ca19f434f5055c0efceefe48d89469fcbbe</id>
<content type='text'>
Add `print_function` to all `from __future__ import ...` statements
and use the python3 print function syntax everywhere.

Closes #3078.
</content>
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<pre>
Add `print_function` to all `from __future__ import ...` statements
and use the python3 print function syntax everywhere.

Closes #3078.
</pre>
</div>
</content>
</entry>
<entry>
<title>2to3: Use absolute imports.</title>
<updated>2013-03-28T14:43:26+00:00</updated>
<author>
<name>Charles Harris</name>
<email>charlesr.harris@gmail.com</email>
</author>
<published>2013-03-28T03:49:08+00:00</published>
<link rel='alternate' type='text/html' href='http://git.baserock.org/cgit/delta/python-packages/numpy.git/commit/?id=d4b88c1dbd6898fb6fcebc97f36b421999340f71'/>
<id>d4b88c1dbd6898fb6fcebc97f36b421999340f71</id>
<content type='text'>
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
</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
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
</pre>
</div>
</content>
</entry>
<entry>
<title>2to3: Put `from __future__ import division in every python file.</title>
<updated>2013-03-01T18:22:47+00:00</updated>
<author>
<name>Charles Harris</name>
<email>charlesr.harris@gmail.com</email>
</author>
<published>2013-02-27T20:26:58+00:00</published>
<link rel='alternate' type='text/html' href='http://git.baserock.org/cgit/delta/python-packages/numpy.git/commit/?id=6aa264c4bad9c89ccdd9ecd5a1cb5ef10643ec51'/>
<id>6aa264c4bad9c89ccdd9ecd5a1cb5ef10643ec51</id>
<content type='text'>
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.
</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
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.
</pre>
</div>
</content>
</entry>
<entry>
<title>ENH: Add module containing functions for padding n-dimensional arrays.</title>
<updated>2012-04-04T19:29:16+00:00</updated>
<author>
<name>tim cera</name>
<email>tcera@sjrwmd.com</email>
</author>
<published>2012-02-06T17:51:14+00:00</published>
<link rel='alternate' type='text/html' href='http://git.baserock.org/cgit/delta/python-packages/numpy.git/commit/?id=7270d9e6054e105c6c7ace66b443870a9e299b75'/>
<id>7270d9e6054e105c6c7ace66b443870a9e299b75</id>
<content type='text'>
The various padding functions are exposed as options to a public 'pad'
function.  Example:

    pad(a, 5, mode='mean')

Current modes are 'constant', 'edge', 'linear_ramp', 'maximum', 'mean',
'median', 'minimum', 'reflect', 'symmetric', 'wrap', and &lt;function&gt;

This commit includes unit tests and doctests and is based on feature
request ticket #655.
</content>
<content type='xhtml'>
<div xmlns='http://www.w3.org/1999/xhtml'>
<pre>
The various padding functions are exposed as options to a public 'pad'
function.  Example:

    pad(a, 5, mode='mean')

Current modes are 'constant', 'edge', 'linear_ramp', 'maximum', 'mean',
'median', 'minimum', 'reflect', 'symmetric', 'wrap', and &lt;function&gt;

This commit includes unit tests and doctests and is based on feature
request ticket #655.
</pre>
</div>
</content>
</entry>
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