[Numpy-discussion] NumPy 1.12.0rc1

Charles R Harris charlesr.harris at gmail.com
Mon Dec 19 20:43:48 EST 2016


Hi All,

I am pleased to announce the release of NumPy 1.12.0rc1.  This release
supports  Python 2.7 and 3.4 - 3.6 and is the result of 406 pull requests
submitted by 139 contributors and comprises a large number of fixes and
improvements. Among the many improvements it is difficult to  pick out just
a few as standing above the others, but the following may be of particular
interest or indicate areas likely to have future consequences.

* Order of operations in ``np.einsum`` can now be optimized for large speed
improvements.
* New ``signature`` argument to ``np.vectorize`` for vectorizing with core
dimensions.
* The ``keepdims`` argument was added to many functions.
* New context manager for testing warnings
* Support for BLIS in numpy.distutils
* Much improved support for PyPy (not yet finished)

The release notes are quite sizable and rather than put them inline I've
attached them as a file. They may also be viewed at Github
<https://github.com/numpy/numpy/releases/tag/v1.12.0rc1>. Zip files and
tarballs may also be found the Github link. Wheels and a zip archive are
available from PyPI, which is the recommended method of installation.

Cheers,

Charles Harris
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20161219/a61085af/attachment.html>
-------------- next part --------------
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1

==========================
NumPy 1.12.0 Release Notes
==========================

This release supports Python 2.7 and 3.4 - 3.6.

Highlights
==========
The NumPy 1.12.0 release contains a large number of fixes and improvements, but
few that stand out above all others. That makes picking out the highlights
somewhat arbitrary but the following may be of particular interest or indicate
areas likely to have future consequences.

* Order of operations in ``np.einsum`` can now be optimized for large speed improvements.
* New ``signature`` argument to ``np.vectorize`` for vectorizing with core dimensions.
* The ``keepdims`` argument was added to many functions.
* New context manager for testing warnings
* Support for BLIS in numpy.distutils
* Much improved support for PyPy (not yet finished)

Dropped Support
===============

* Support for Python 2.6, 3.2, and 3.3 has been dropped.


Added Support
=============

* Support for PyPy 2.7 v5.6.0 has been added. While not complete (nditer
  ``updateifcopy`` is not supported yet), this is a milestone for PyPy's
  C-API compatibility layer.


Build System Changes
====================

* Library order is preserved, instead of being reordered to match that of
  the directories.


Deprecations
============

Assignment of ndarray object's ``data`` attribute
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Assigning the 'data' attribute is an inherently unsafe operation as pointed
out in gh-7083. Such a capability will be removed in the future.

Unsafe int casting of the num attribute in ``linspace``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
``np.linspace`` now raises DeprecationWarning when num cannot be safely
interpreted as an integer.

Insufficient bit width parameter to ``binary_repr``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If a 'width' parameter is passed into ``binary_repr`` that is insufficient to
represent the number in base 2 (positive) or 2's complement (negative) form,
the function used to silently ignore the parameter and return a representation
using the minimal number of bits needed for the form in question. Such behavior
is now considered unsafe from a user perspective and will raise an error in the
future.


Future Changes
==============

* In 1.13 NAT will always compare False except for ``NAT != NAT``,
  which will be True.  In short, NAT will behave like NaN
* In 1.13 np.average will preserve subclasses, to match the behavior of most
  other numpy functions such as np.mean. In particular, this means calls which
  returned a scalar may return a 0-d subclass object instead.

Multiple-field manipulation of structured arrays
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In 1.13 the behavior of structured arrays involving multiple fields will change
in two ways:

First, indexing a structured array with multiple fields (eg,
``arr[['f1', 'f3']]``) will return a view into the original array in 1.13,
instead of a copy. Note the returned view will have extra padding bytes
corresponding to intervening fields in the original array, unlike the copy in
1.12, which will affect code such as ``arr[['f1', 'f3']].view(newdtype)``.

Second, for numpy versions 1.6 to 1.12 assignment between structured arrays
occurs "by field name": Fields in the destination array are set to the
identically-named field in the source array or to 0 if the source does not have
a field::

    >>> a = np.array([(1,2),(3,4)], dtype=[('x', 'i4'), ('y', 'i4')])
    >>> b = np.ones(2, dtype=[('z', 'i4'), ('y', 'i4'), ('x', 'i4')])
    >>> b[:] = a
    >>> b
    array([(0, 2, 1), (0, 4, 3)],
          dtype=[('z', '<i4'), ('y', '<i4'), ('x', '<i4')])

In 1.13 assignment will instead occur "by position": The Nth field of the
destination will be set to the Nth field of the source regardless of field
name. The old behavior can be obtained by using indexing to reorder the fields
before
assignment, e.g., ``b[['x', 'y']] = a[['y', 'x']]``.


Compatibility notes
===================

DeprecationWarning to error
~~~~~~~~~~~~~~~~~~~~~~~~~~~

* Indexing with floats raises ``IndexError``,
  e.g., a[0, 0.0].
* Indexing with non-integer array_like raises ``IndexError``,
  e.g., ``a['1', '2']``
* Indexing with multiple ellipsis raises ``IndexError``,
  e.g., ``a[..., ...]``.
* Non-integers used as index values raise ``TypeError``,
  e.g., in ``reshape``, ``take``, and specifying reduce axis.

FutureWarning to changed behavior
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

* ``np.full`` now returns an array of the fill-value's dtype if no dtype is
  given, instead of defaulting to float.
* np.average will emit a warning if the argument is a subclass of ndarray,
  as the subclass will be preserved starting in 1.13. (see Future Changes)

``power`` and ``**`` raise errors for integer to negative integer powers
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The previous behavior depended on whether numpy scalar integers or numpy
integer arrays were involved.

For arrays

* Zero to negative integer powers returned least integral value.
* Both 1, -1 to negative integer powers returned correct values.
* The remaining integers returned zero when raised to negative integer powers.

For scalars

* Zero to negative integer powers returned least integral value.
* Both 1, -1 to negative integer powers returned correct values.
* The remaining integers sometimes returned zero, sometimes the
  correct float depending on the integer type combination.

All of these cases now raise a ``ValueError`` except for those integer
combinations whose common type is float, for instance uint64 and int8. It was
felt that a simple rule was the best way to go rather than have special
exceptions for the integer units. If you need negative powers, use an inexact
type.

Relaxed stride checking is the default
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This will have some impact on code that assumed that ``F_CONTIGUOUS`` and
``C_CONTIGUOUS`` were mutually exclusive and could be set to determine the
default order for arrays that are now both.

The ``np.percentile`` 'midpoint' interpolation method fixed for exact indices
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The 'midpoint' interpolator now gives the same result as 'lower' and 'higher' when
the two coincide. Previous behavior of 'lower' + 0.5 is fixed.

``keepdims`` kwarg is passed through to user-class methods
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
numpy functions that take a ``keepdims`` kwarg now pass the value
through to the corresponding methods on ndarray sub-classes.  Previously the
``keepdims`` keyword would be silently dropped.  These functions now have
the following behavior:

1. If user does not provide ``keepdims``, no keyword is passed to the underlying
   method.
2. Any user-provided value of ``keepdims`` is passed through as a keyword
   argument to the method.

This will raise in the case where the method does not support a
``keepdims`` kwarg and the user explicitly passes in ``keepdims``.

The following functions are changed: ``sum``, ``product``,
``sometrue``, ``alltrue``, ``any``, ``all``, ``amax``, ``amin``,
``prod``, ``mean``, ``std``, ``var``, ``nanmin``, ``nanmax``,
``nansum``, ``nanprod``, ``nanmean``, ``nanmedian``, ``nanvar``,
``nanstd``

``bitwise_and`` identity changed
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The previous identity was 1, it is now -1. See entry in `Improvements`_ for
more explanation.

ma.median warns and returns nan when unmasked invalid values are encountered
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Similar to unmasked median the masked median `ma.median` now emits a Runtime
warning and returns `NaN` in slices where an unmasked `NaN` is present.

Greater consistancy in ``assert_almost_equal``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The precision check for scalars has been changed to match that for arrays. It
is now::

    abs(actual - desired) < 1.5 * 10**(-decimal)

Note that this is looser than previously documented, but agrees with the
previous implementation used in ``assert_array_almost_equal``. Due to the
change in implementation some very delicate tests may fail that did not
fail before.

``NoseTester`` behaviour of warnings during testing
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When ``raise_warnings="develop"`` is given, all uncaught warnings will now
be considered a test failure. Previously only selected ones were raised.
Warnings which are not caught or raised (mostly when in release mode)
will be shown once during the test cycle similar to the default python
settings.

``assert_warns`` and ``deprecated`` decorator more specific
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``assert_warns`` function and context manager are now more specific
to the given warning category. This increased specificity leads to them
being handled according to the outer warning settings. This means that
no warning may be raised in cases where a wrong category warning is given
and ignored outside the context. Alternatively the increased specificity
may mean that warnings that were incorrectly ignored will now be shown
or raised. See also the new ``suppress_warnings`` context manager.
The same is true for the ``deprecated`` decorator.

C API
~~~~~
No changes.


New Features
============

Writeable keyword argument for ``as_strided``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
``np.lib.stride_tricks.as_strided`` now has a ``writeable``
keyword argument. It can be set to False when no write operation
to the returned array is expected to avoid accidental
unpredictable writes.

``axes`` keyword argument for ``rot90``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``axes`` keyword argument in ``rot90`` determines the plane in which the
array is rotated. It defaults to ``axes=(0,1)`` as in the originial function.

Generalized ``flip``
~~~~~~~~~~~~~~~~~~~~
``flipud`` and ``fliplr`` reverse the elements of an array along axis=0 and
axis=1 respectively. The newly added ``flip`` function reverses the elements of
an array along any given axis.

* ``np.count_nonzero`` now has an ``axis`` parameter, allowing
  non-zero counts to be generated on more than just a flattened
  array object.

BLIS support in ``numpy.distutils``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Building against the BLAS implementation provided by the BLIS library is now
supported.  See the ``[blis]`` section in ``site.cfg.example`` (in the root of
the numpy repo or source distribution).

Hook in ``numpy/__init__.py`` to run distribution-specific checks
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Binary distributions of numpy may need to run specific hardware checks or load
specific libraries during numpy initialization.  For example, if we are
distributing numpy with a BLAS library that requires SSE2 instructions, we
would like to check the machine on which numpy is running does have SSE2 in
order to give an informative error.

Add a hook in ``numpy/__init__.py`` to import a ``numpy/_distributor_init.py``
file that will remain empty (bar a docstring) in the standard numpy source,
but that can be overwritten by people making binary distributions of numpy.

New nanfunctions ``nancumsum`` and ``nancumprod`` added
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Nan-functions ``nancumsum`` and ``nancumprod`` have been added to
compute ``cumsum`` and ``cumprod`` by ignoring nans.

``np.interp`` can now interpolate complex values
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
``np.lib.interp(x, xp, fp)`` now allows the interpolated array ``fp``
to be complex and will interpolate at ``complex128`` precision.

New polynomial evaluation function ``polyvalfromroots`` added
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The new function ``polyvalfromroots`` evaluates a polynomial at given points
from the roots of the polynomial. This is useful for higher order polynomials,
where expansion into polynomial coefficients is inaccurate at machine
precision.

New array creation function ``geomspace`` added
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The new function ``geomspace`` generates a geometric sequence.  It is similar
to ``logspace``, but with start and stop specified directly:
``geomspace(start, stop)`` behaves the same as
``logspace(log10(start), log10(stop))``.

New context manager for testing warnings
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A new context manager ``suppress_warnings`` has been added to the testing
utils. This context manager is designed to help reliably test warnings.
Specifically to reliably filter/ignore warnings. Ignoring warnings
by using an "ignore" filter in Python versions before 3.4.x can quickly
result in these (or similar) warnings not being tested reliably.

The context manager allows to filter (as well as record) warnings similar
to the ``catch_warnings`` context, but allows for easier specificity.
Also printing warnings that have not been filtered or nesting the
context manager will work as expected. Additionally, it is possible
to use the context manager as a decorator which can be useful when
multiple tests give need to hide the same warning.

New masked array functions ``ma.convolve`` and ``ma.correlate`` added
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
These functions wrapped the non-masked versions, but propagate through masked
values. There are two different propagation modes. The default causes masked
values to contaminate the result with masks, but the other mode only outputs
masks if there is no alternative.

New ``float_power`` ufunc
~~~~~~~~~~~~~~~~~~~~~~~~~
The new ``float_power`` ufunc is like the ``power`` function except all
computation is done in a minimum precision of float64. There was a long
discussion on the numpy mailing list of how to treat integers to negative
integer powers and a popular proposal was that the ``__pow__`` operator should
always return results of at least float64 precision. The ``float_power``
function implements that option. Note that it does not support object arrays.

``np.loadtxt`` now supports a single integer as ``usecol`` argument
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Instead of using ``usecol=(n,)`` to read the nth column of a file
it is now allowed to use ``usecol=n``. Also the error message is
more user friendly when a non-integer is passed as a column index.

Improved automated bin estimators for ``histogram``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Added 'doane' and 'sqrt' estimators to ``histogram`` via the ``bins``
argument. Added support for range-restricted histograms with automated
bin estimation.

``np.roll`` can now roll multiple axes at the same time
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``shift`` and ``axis`` arguments to ``roll`` are now broadcast against each
other, and each specified axis is shifted accordingly.

The ``__complex__`` method has been implemented for the ndarrays
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Calling ``complex()`` on a size 1 array will now cast to a python
complex.

``pathlib.Path`` objects now supported
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The standard ``np.load``, ``np.save``, ``np.loadtxt``, ``np.savez``, and similar
functions can now take ``pathlib.Path`` objects as an argument instead of a
filename or open file object.

New ``bits`` attribute for ``np.finfo``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This makes ``np.finfo`` consistent with ``np.iinfo`` which already has that
attribute.

New ``signature`` argument to ``np.vectorize``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This argument allows for vectorizing user defined functions with core
dimensions, in the style of NumPy's
:ref:`generalized universal functions<c-api.generalized-ufuncs>`. This allows
for vectorizing a much broader class of functions. For example, an arbitrary
distance metric that combines two vectors to produce a scalar could be
vectorized with ``signature='(n),(n)->()'``. See ``np.vectorize`` for full
details.

Emit py3kwarnings for division of integer arrays
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
To help people migrate their code bases from Python 2 to Python 3, the
python interpreter has a handy option -3, which issues warnings at runtime.
One of its warnings is for integer division::

    $ python -3 -c "2/3"

    -c:1: DeprecationWarning: classic int division

In Python 3, the new integer division semantics also apply to numpy arrays.
With this version, numpy will emit a similar warning::

    $ python -3 -c "import numpy as np; np.array(2)/np.array(3)"

    -c:1: DeprecationWarning: numpy: classic int division

numpy.sctypes now includes bytes on Python3 too
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Previously, it included str (bytes) and unicode on Python2, but only str
(unicode) on Python3.


Improvements
============

``bitwise_and`` identity changed
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The previous identity was 1 with the result that all bits except the LSB were
masked out when the reduce method was used.  The new identity is -1, which
should work properly on twos complement machines as all bits will be set to
one.

Generalized Ufuncs will now unlock the GIL
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Generalized Ufuncs, including most of the linalg module, will now unlock
the Python global interpreter lock.

Caches in `np.fft` are now bounded in total size and item count
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The caches in `np.fft` that speed up successive FFTs of the same length can no
longer grow without bounds. They have been replaced with LRU (least recently
used) caches that automatically evict no longer needed items if either the
memory size or item count limit has been reached.

Improved handling of zero-width string/unicode dtypes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Fixed several interfaces that explicitly disallowed arrays with zero-width
string dtypes (i.e. ``dtype('S0')`` or ``dtype('U0')``, and fixed several
bugs where such dtypes were not handled properly.  In particular, changed
``ndarray.__new__`` to not implicitly convert ``dtype('S0')`` to
``dtype('S1')`` (and likewise for unicode) when creating new arrays.

Integer ufuncs vectorized with AVX2
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If the cpu supports it at runtime the basic integer ufuncs now use AVX2
instructions. This feature is currently only available when compiled with GCC.

Order of operations optimization in ``np.einsum``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
``np.einsum`` now supports the ``optimize`` argument which will optimize the
order of contraction. For example, ``np.einsum`` would complete the chain dot
example ``np.einsum(‘ij,jk,kl->il’, a, b, c)`` in a single pass which would
scale like ``N^4``; however, when ``optimize=True`` ``np.einsum`` will create
an intermediate array to reduce this scaling to ``N^3`` or effectively
``np.dot(a, b).dot(c)``. Usage of intermediate tensors to reduce scaling has
been applied to the general einsum summation notation. See ``np.einsum_path``
for more details.

quicksort has been changed to an introsort
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The quicksort kind of ``np.sort`` and ``np.argsort`` is now an introsort which
is regular quicksort but changing to a heapsort when not enough progress is
made. This retains the good quicksort performance while changing the worst case
runtime from ``O(N^2)`` to ``O(N*log(N))``.

``ediff1d`` improved performance and subclass handling
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ediff1d function uses an array instead on a flat iterator for the
subtraction.  When to_begin or to_end is not None, the subtraction is performed
in place to eliminate a copy operation.  A side effect is that certain
subclasses are handled better, namely astropy.Quantity, since the complete
array is created, wrapped, and then begin and end values are set, instead of
using concatenate.

Improved precision of ``ndarray.mean`` for float16 arrays
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The computation of the mean of float16 arrays is now carried out in float32 for
improved precision. This should be useful in packages such as scikit-learn
where the precision of float16 is adequate and its smaller footprint is
desireable.


Changes
=======

All array-like methods are now called with keyword arguments in fromnumeric.py
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Internally, many array-like methods in fromnumeric.py were being called with
positional arguments instead of keyword arguments as their external signatures
were doing. This caused a complication in the downstream 'pandas' library
that encountered an issue with 'numpy' compatibility. Now, all array-like
methods in this module are called with keyword arguments instead.

Operations on np.memmap objects return numpy arrays in most cases
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Previously operations on a memmap object would misleadingly return a memmap
instance even if the result was actually not memmapped.  For example,
``arr + 1`` or ``arr + arr`` would return memmap instances, although no memory
from the output array is memmaped. Version 1.12 returns ordinary numpy arrays
from these operations.

Also, reduction of a memmap (e.g.  ``.sum(axis=None``) now returns a numpy
scalar instead of a 0d memmap.

stacklevel of warnings increased
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The stacklevel for python based warnings was increased so that most warnings
will report the offending line of the user code instead of the line the
warning itself is given. Passing of stacklevel is now tested to ensure that
new warnings will receive the ``stacklevel`` argument.

This causes warnings with the "default" or "module" filter to be shown once
for every offending user code line or user module instead of only once. On
python versions before 3.4, this can cause warnings to appear that were falsely
ignored before, which may be surprising especially in test suits.



Contributors to maintenance/1.12.x
==================================

A total of 139 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

- - Aditya Panchal
- - Ales Erjavec +
- - Alex Griffing
- - Alexandr Shadchin +
- - Alistair Muldal
- - Allan Haldane
- - Amit Aronovitch +
- - Andrei Kucharavy +
- - Antony Lee
- - Antti Kaihola +
- - Arne de Laat +
- - Auke Wiggers +
- - AustereCuriosity +
- - Badhri Narayanan Krishnakumar +
- - Ben North +
- - Ben Rowland +
- - Bertrand Lefebvre
- - Boxiang Sun
- - CJ Carey
- - Charles Harris
- - Christoph Gohlke
- - Daniel Ching +
- - Daniel Rasmussen +
- - Daniel Smith +
- - David Schaich +
- - Denis Alevi +
- - Devin Jeanpierre +
- - Dmitry Odzerikho
- - Dongjoon Hyun +
- - Edward Richards +
- - Ekaterina Tuzova +
- - Emilien Kofman +
- - Endolith
- - Eren Sezener +
- - Eric Moore
- - Eric Quintero +
- - Eric Wieser +
- - Erik M. Bray
- - Frederic Bastien +
- - Friedrich Dunne +
- - Gerrit Holl
- - Golnaz Irannejad +
- - Graham Markall +
- - Greg Knoll +
- - Greg Young
- - Gustavo Serra Scalet +
- - Ines Wichert +
- - Irvin Probst +
- - Jaime Fernandez
- - James Sanders +
- - Jan David Mol +
- - Jan Schlüter
- - Jeremy Tuloup +
- - John Kirkham
- - John Zwinck +
- - Jonathan Helmus
- - Joseph Fox-Rabinovitz
- - Josh Wilson +
- - Joshua Warner +
- - Julian Taylor
- - Ka Wo Chen +
- - Kamil Rytarowski +
- - Kelsey Jordahl +
- - Kevin Deldycke +
- - Khaled Ben Abdallah Okuda +
- - Lion Krischer +
- - Loïc Estève +
- - Luca Mussi +
- - Mads Ohm Larsen +
- - Manoj Kumar +
- - Mario Emmenlauer +
- - Marshall Bockrath-Vandegrift +
- - Marshall Ward +
- - Marten van Kerkwijk
- - Mathieu Lamarre +
- - Matthew Brett
- - Matthew Harrigan +
- - Matthias Geier
- - Matti Picus +
- - Meet Udeshi +
- - Michael Felt +
- - Michael Goerz +
- - Michael Martin +
- - Michael Seifert +
- - Mike Nolta +
- - Nathaniel Beaver +
- - Nathaniel J. Smith
- - Naveen Arunachalam +
- - Nick Papior
- - Nikola Forró +
- - Oleksandr Pavlyk +
- - Olivier Grisel
- - Oren Amsalem +
- - Pauli Virtanen
- - Pavel Potocek +
- - Pedro Lacerda +
- - Peter Creasey +
- - Phil Elson +
- - Philip Gura +
- - Phillip J. Wolfram +
- - Pierre de Buyl +
- - Raghav RV +
- - Ralf Gommers
- - Ray Donnelly +
- - Rehas Sachdeva
- - Rob Malouf +
- - Robert Kern
- - Samuel St-Jean
- - Sanchez Gonzalez Alvaro +
- - Saurabh Mehta +
- - Scott Sanderson +
- - Sebastian Berg
- - Shayan Pooya +
- - Shota Kawabuchi +
- - Simon Conseil
- - Simon Gibbons
- - Sorin Sbarnea +
- - Stefan van der Walt
- - Stephan Hoyer
- - Steven J Kern +
- - Stuart Archibald
- - Tadeu Manoel +
- - Takuya Akiba +
- - Thomas A Caswell
- - Tom Bird +
- - Tony Kelman +
- - Toshihiro Kamishima +
- - Valentin Valls +
- - Varun Nayyar
- - Victor Stinner +
- - Warren Weckesser
- - Wendell Smith
- - Wojtek Ruszczewski +
- - Xavier Abellan Ecija +
- - Yaroslav Halchenko
- - Yash Shah +
- - Yinon Ehrlich +
- - Yu Feng +
- - nevimov +

Pull requests merged for maintenance/1.12.x
===========================================

A total of 406 pull requests were merged for this release.

- - `#4073 <https://github.com/numpy/numpy/pull/4073>`__: BUG: change real output checking to test if all imaginary parts...
- - `#4619 <https://github.com/numpy/numpy/pull/4619>`__: BUG : np.sum silently drops keepdims for sub-classes of ndarray
- - `#5488 <https://github.com/numpy/numpy/pull/5488>`__: ENH: add `contract`: optimizing numpy's einsum expression
- - `#5706 <https://github.com/numpy/numpy/pull/5706>`__: ENH: make some masked array methods behave more like ndarray...
- - `#5822 <https://github.com/numpy/numpy/pull/5822>`__: Allow many distributions to have a scale of 0.
- - `#6054 <https://github.com/numpy/numpy/pull/6054>`__: WIP: MAINT: Add deprecation warning to views of multi-field indexes
- - `#6298 <https://github.com/numpy/numpy/pull/6298>`__: Check lower base limit in base_repr.
- - `#6430 <https://github.com/numpy/numpy/pull/6430>`__: Fix issues with zero-width string fields
- - `#6656 <https://github.com/numpy/numpy/pull/6656>`__: ENH: usecols now accepts an int when only one column has to be...
- - `#6660 <https://github.com/numpy/numpy/pull/6660>`__: Added pathlib support for several functions
- - `#6872 <https://github.com/numpy/numpy/pull/6872>`__: ENH: linear interpolation of complex values in lib.interp
- - `#6997 <https://github.com/numpy/numpy/pull/6997>`__: MAINT: Simplify mtrand.pyx helpers
- - `#7003 <https://github.com/numpy/numpy/pull/7003>`__: BUG: Fix string copying for np.place
- - `#7026 <https://github.com/numpy/numpy/pull/7026>`__: DOC: Clarify behavior in np.random.uniform
- - `#7055 <https://github.com/numpy/numpy/pull/7055>`__: BUG: One Element Array Inputs Return Scalars in np.random
- - `#7063 <https://github.com/numpy/numpy/pull/7063>`__: REL: Update master branch after 1.11.x branch has been made.
- - `#7073 <https://github.com/numpy/numpy/pull/7073>`__: DOC: Update the 1.11.0 release notes.
- - `#7076 <https://github.com/numpy/numpy/pull/7076>`__: MAINT: Update the git .mailmap file.
- - `#7082 <https://github.com/numpy/numpy/pull/7082>`__: TST, DOC: Added Broadcasting Tests in test_random.py
- - `#7087 <https://github.com/numpy/numpy/pull/7087>`__: BLD: fix compilation on non glibc-Linuxes
- - `#7088 <https://github.com/numpy/numpy/pull/7088>`__: BUG: Have `norm` cast non-floating point arrays to 64-bit float...
- - `#7090 <https://github.com/numpy/numpy/pull/7090>`__: ENH: Added 'doane' and 'sqrt' estimators to np.histogram in numpy.function_base
- - `#7091 <https://github.com/numpy/numpy/pull/7091>`__: Revert "BLD: fix compilation on non glibc-Linuxes"
- - `#7092 <https://github.com/numpy/numpy/pull/7092>`__: BLD: fix compilation on non glibc-Linuxes
- - `#7099 <https://github.com/numpy/numpy/pull/7099>`__: TST: Suppressed warnings
- - `#7102 <https://github.com/numpy/numpy/pull/7102>`__: MAINT: Removed conditionals that are always false in datetime_strings.c
- - `#7105 <https://github.com/numpy/numpy/pull/7105>`__: DEP: Deprecate as_strided returning a writable array as default
- - `#7109 <https://github.com/numpy/numpy/pull/7109>`__: DOC: update Python versions requirements in the install docs
- - `#7114 <https://github.com/numpy/numpy/pull/7114>`__: MAINT: Fix typos in docs
- - `#7116 <https://github.com/numpy/numpy/pull/7116>`__: TST: Fixed f2py test for win32 virtualenv
- - `#7118 <https://github.com/numpy/numpy/pull/7118>`__: TST: Fixed f2py test for non-versioned python executables
- - `#7119 <https://github.com/numpy/numpy/pull/7119>`__: BUG: Fixed mingw.lib error
- - `#7125 <https://github.com/numpy/numpy/pull/7125>`__: DOC: Updated documentation wording and examples for np.percentile.
- - `#7129 <https://github.com/numpy/numpy/pull/7129>`__: BUG: Fixed 'midpoint' interpolation of np.percentile in odd cases.
- - `#7131 <https://github.com/numpy/numpy/pull/7131>`__: Fix setuptools sdist
- - `#7133 <https://github.com/numpy/numpy/pull/7133>`__: ENH: savez: temporary file alongside with target file and improve...
- - `#7134 <https://github.com/numpy/numpy/pull/7134>`__: MAINT: Fix some typos in a code string and comments
- - `#7141 <https://github.com/numpy/numpy/pull/7141>`__: BUG: Unpickled void scalars should be contiguous
- - `#7144 <https://github.com/numpy/numpy/pull/7144>`__: MAINT: Change `call_fortran` into `callfortran` in comments.
- - `#7145 <https://github.com/numpy/numpy/pull/7145>`__: BUG: Fixed regressions in np.piecewise in ref to #5737 and #5729.
- - `#7147 <https://github.com/numpy/numpy/pull/7147>`__: Temporarily disable __numpy_ufunc__
- - `#7148 <https://github.com/numpy/numpy/pull/7148>`__: ENH,TST: Bump stacklevel and add tests for warnings
- - `#7149 <https://github.com/numpy/numpy/pull/7149>`__: TST: Add missing suffix to temppath manager
- - `#7152 <https://github.com/numpy/numpy/pull/7152>`__: BUG: mode kwargs passed as unicode to np.pad raises an exception
- - `#7156 <https://github.com/numpy/numpy/pull/7156>`__: BUG: Reascertain that linspace respects ndarray subclasses in...
- - `#7167 <https://github.com/numpy/numpy/pull/7167>`__: DOC: Update Wikipedia references for mtrand.pyx
- - `#7171 <https://github.com/numpy/numpy/pull/7171>`__: TST: Fixed f2py test for Anaconda non-win32
- - `#7174 <https://github.com/numpy/numpy/pull/7174>`__: DOC: Fix broken pandas link in release notes
- - `#7177 <https://github.com/numpy/numpy/pull/7177>`__: ENH: added axis param for np.count_nonzero
- - `#7178 <https://github.com/numpy/numpy/pull/7178>`__: BUG: Fix binary_repr for negative numbers
- - `#7180 <https://github.com/numpy/numpy/pull/7180>`__: BUG: Fixed previous attempt to fix dimension mismatch in nanpercentile
- - `#7181 <https://github.com/numpy/numpy/pull/7181>`__: DOC: Updated minor typos in function_base.py and test_function_base.py
- - `#7191 <https://github.com/numpy/numpy/pull/7191>`__: DOC: add vstack, hstack, dstack reference to stack documentation.
- - `#7193 <https://github.com/numpy/numpy/pull/7193>`__: MAINT: Removed supurious assert in histogram estimators
- - `#7194 <https://github.com/numpy/numpy/pull/7194>`__: BUG: Raise a quieter `MaskedArrayFutureWarning` for mask changes.
- - `#7195 <https://github.com/numpy/numpy/pull/7195>`__: STY: Drop some trailing spaces in `numpy.ma.core`.
- - `#7196 <https://github.com/numpy/numpy/pull/7196>`__: Revert "DOC: add vstack, hstack, dstack reference to stack documentation."
- - `#7197 <https://github.com/numpy/numpy/pull/7197>`__: TST: Pin virtualenv used on Travis CI.
- - `#7198 <https://github.com/numpy/numpy/pull/7198>`__: ENH: Unlock the GIL for gufuncs
- - `#7199 <https://github.com/numpy/numpy/pull/7199>`__: MAINT: Cleanup for histogram bin estimator selection
- - `#7201 <https://github.com/numpy/numpy/pull/7201>`__: Raise IOError on not a file in python2
- - `#7202 <https://github.com/numpy/numpy/pull/7202>`__: MAINT: Made `iterable` return a boolean
- - `#7209 <https://github.com/numpy/numpy/pull/7209>`__: TST: Bump `virtualenv` to 14.0.6
- - `#7211 <https://github.com/numpy/numpy/pull/7211>`__: DOC: Fix fmin examples
- - `#7215 <https://github.com/numpy/numpy/pull/7215>`__: MAINT: Use PySlice_GetIndicesEx instead of custom reimplementation
- - `#7229 <https://github.com/numpy/numpy/pull/7229>`__: ENH: implement __complex__
- - `#7231 <https://github.com/numpy/numpy/pull/7231>`__: MRG: allow distributors to run custom init
- - `#7232 <https://github.com/numpy/numpy/pull/7232>`__: BLD: Switch order of test for lapack_mkl and openblas_lapack
- - `#7239 <https://github.com/numpy/numpy/pull/7239>`__: DOC: Removed residual merge markup from previous commit
- - `#7240 <https://github.com/numpy/numpy/pull/7240>`__: Change 'pubic' to 'public'.
- - `#7241 <https://github.com/numpy/numpy/pull/7241>`__: MAINT: update doc/sphinxext to numpydoc 0.6.0, and fix up some...
- - `#7243 <https://github.com/numpy/numpy/pull/7243>`__: ENH: Adding support to the range keyword for estimation of the...
- - `#7246 <https://github.com/numpy/numpy/pull/7246>`__: DOC: metion writeable keyword in as_strided in release notes
- - `#7247 <https://github.com/numpy/numpy/pull/7247>`__: TST: Fail quickly on AppVeyor for superseded PR builds
- - `#7248 <https://github.com/numpy/numpy/pull/7248>`__: DOC: remove link to documentation wiki editor from HOWTO_DOCUMENT.
- - `#7250 <https://github.com/numpy/numpy/pull/7250>`__: DOC,REL: Update 1.11.0 notes.
- - `#7251 <https://github.com/numpy/numpy/pull/7251>`__: BUG: only benchmark complex256 if it exists
- - `#7252 <https://github.com/numpy/numpy/pull/7252>`__: Forward port a fix and enhancement from 1.11.x
- - `#7253 <https://github.com/numpy/numpy/pull/7253>`__: DOC: note in h/v/dstack points users to stack/concatenate
- - `#7254 <https://github.com/numpy/numpy/pull/7254>`__: BUG: Enforce dtype for randint singletons
- - `#7256 <https://github.com/numpy/numpy/pull/7256>`__: MAINT: Use `is None` or `is not None` instead of `== None` or...
- - `#7257 <https://github.com/numpy/numpy/pull/7257>`__: DOC: Fix mismatched variable names in docstrings.
- - `#7258 <https://github.com/numpy/numpy/pull/7258>`__: ENH: Make numpy floor_divide and remainder agree with Python...
- - `#7260 <https://github.com/numpy/numpy/pull/7260>`__: BUG/TST: Fix #7259, do not "force scalar" for already scalar...
- - `#7261 <https://github.com/numpy/numpy/pull/7261>`__: Added self to mailmap
- - `#7266 <https://github.com/numpy/numpy/pull/7266>`__: BUG: Segfault for classes with deceptive __len__
- - `#7268 <https://github.com/numpy/numpy/pull/7268>`__: ENH: add geomspace function
- - `#7274 <https://github.com/numpy/numpy/pull/7274>`__: BUG: Preserve array order in np.delete
- - `#7275 <https://github.com/numpy/numpy/pull/7275>`__: DEP: Warn about assigning 'data' attribute of ndarray
- - `#7276 <https://github.com/numpy/numpy/pull/7276>`__: DOC: apply_along_axis missing whitespace inserted (before colon)
- - `#7278 <https://github.com/numpy/numpy/pull/7278>`__: BUG: Make returned unravel_index arrays writeable
- - `#7279 <https://github.com/numpy/numpy/pull/7279>`__: TST: Fixed elements being shuffled
- - `#7280 <https://github.com/numpy/numpy/pull/7280>`__: MAINT: Remove redundant trailing semicolons.
- - `#7285 <https://github.com/numpy/numpy/pull/7285>`__: BUG: Make Randint Backwards Compatible with Pandas
- - `#7286 <https://github.com/numpy/numpy/pull/7286>`__: MAINT: Fix typos in docs/comments of `ma` and `polynomial` modules.
- - `#7292 <https://github.com/numpy/numpy/pull/7292>`__: Clarify error on repr failure in assert_equal.
- - `#7294 <https://github.com/numpy/numpy/pull/7294>`__: ENH: add support for BLIS to numpy.distutils
- - `#7295 <https://github.com/numpy/numpy/pull/7295>`__: DOC: understanding code and getting started section to dev doc
- - `#7296 <https://github.com/numpy/numpy/pull/7296>`__: Revert part of #3907 which incorrectly propogated MaskedArray...
- - `#7299 <https://github.com/numpy/numpy/pull/7299>`__: DOC: Fix mismatched variable names in docstrings.
- - `#7300 <https://github.com/numpy/numpy/pull/7300>`__: DOC: dev: stop recommending keeping local master updated with...
- - `#7301 <https://github.com/numpy/numpy/pull/7301>`__: DOC: Update release notes
- - `#7305 <https://github.com/numpy/numpy/pull/7305>`__: BUG: Remove data race in mtrand: two threads could mutate the...
- - `#7307 <https://github.com/numpy/numpy/pull/7307>`__: DOC: Missing some characters in link.
- - `#7308 <https://github.com/numpy/numpy/pull/7308>`__: BUG: Incrementing the wrong reference on return
- - `#7310 <https://github.com/numpy/numpy/pull/7310>`__: STY: Fix GitHub rendering of ordered lists >9
- - `#7311 <https://github.com/numpy/numpy/pull/7311>`__: ENH: Make _pointer_type_cache functional
- - `#7313 <https://github.com/numpy/numpy/pull/7313>`__: DOC: corrected grammatical error in quickstart doc
- - `#7325 <https://github.com/numpy/numpy/pull/7325>`__: BUG, MAINT: Improve fromnumeric.py interface for downstream compatibility
- - `#7328 <https://github.com/numpy/numpy/pull/7328>`__: DEP: Deprecated using a float index in linspace
- - `#7331 <https://github.com/numpy/numpy/pull/7331>`__: Add comment, TST: fix MemoryError on win32
- - `#7332 <https://github.com/numpy/numpy/pull/7332>`__: Check for no solution in np.irr Fixes #6744
- - `#7338 <https://github.com/numpy/numpy/pull/7338>`__: TST: Install `pytz` in the CI.
- - `#7340 <https://github.com/numpy/numpy/pull/7340>`__: DOC: Fixed math rendering in tensordot docs.
- - `#7341 <https://github.com/numpy/numpy/pull/7341>`__: TST: Add test for #6469
- - `#7344 <https://github.com/numpy/numpy/pull/7344>`__: DOC: Fix more typos in docs and comments.
- - `#7346 <https://github.com/numpy/numpy/pull/7346>`__: Generalized flip
- - `#7347 <https://github.com/numpy/numpy/pull/7347>`__: ENH Generalized rot90
- - `#7348 <https://github.com/numpy/numpy/pull/7348>`__: Maint: Removed extra space from `ureduce`
- - `#7349 <https://github.com/numpy/numpy/pull/7349>`__: MAINT: Hide nan warnings for masked internal MA computations
- - `#7350 <https://github.com/numpy/numpy/pull/7350>`__: BUG: MA ufuncs should set mask to False, not array([False])
- - `#7351 <https://github.com/numpy/numpy/pull/7351>`__: TST: Fix some MA tests to avoid looking at the .data attribute
- - `#7358 <https://github.com/numpy/numpy/pull/7358>`__: BUG: pull request related to the issue #7353
- - `#7359 <https://github.com/numpy/numpy/pull/7359>`__: Update 7314, DOC: Clarify valid integer range for random.seed...
- - `#7361 <https://github.com/numpy/numpy/pull/7361>`__: MAINT: Fix copy and paste oversight.
- - `#7363 <https://github.com/numpy/numpy/pull/7363>`__: ENH: Make no unshare mask future warnings less noisy
- - `#7366 <https://github.com/numpy/numpy/pull/7366>`__: TST: fix #6542, add tests to check non-iterable argument raises...
- - `#7373 <https://github.com/numpy/numpy/pull/7373>`__: ENH: Add bitwise_and identity
- - `#7378 <https://github.com/numpy/numpy/pull/7378>`__: added NumPy logo and separator
- - `#7382 <https://github.com/numpy/numpy/pull/7382>`__: MAINT: cleanup np.average
- - `#7385 <https://github.com/numpy/numpy/pull/7385>`__: DOC: note about wheels / windows wheels for pypi
- - `#7386 <https://github.com/numpy/numpy/pull/7386>`__: Added label icon to Travis status
- - `#7397 <https://github.com/numpy/numpy/pull/7397>`__: BUG: incorrect type for objects whose __len__ fails
- - `#7398 <https://github.com/numpy/numpy/pull/7398>`__: DOC: fix typo
- - `#7404 <https://github.com/numpy/numpy/pull/7404>`__: Use PyMem_RawMalloc on Python 3.4 and newer
- - `#7406 <https://github.com/numpy/numpy/pull/7406>`__: ENH ufunc called on memmap return a ndarray
- - `#7407 <https://github.com/numpy/numpy/pull/7407>`__: BUG: Fix decref before incref for in-place accumulate
- - `#7410 <https://github.com/numpy/numpy/pull/7410>`__: DOC: add nanprod to the list of math routines
- - `#7414 <https://github.com/numpy/numpy/pull/7414>`__: Tweak corrcoef
- - `#7415 <https://github.com/numpy/numpy/pull/7415>`__: DOC: Documention fixes
- - `#7416 <https://github.com/numpy/numpy/pull/7416>`__: BUG: Incorrect handling of range in `histogram` with automatic...
- - `#7418 <https://github.com/numpy/numpy/pull/7418>`__: DOC: Minor typo fix, hermefik -> hermefit.
- - `#7421 <https://github.com/numpy/numpy/pull/7421>`__: ENH: adds np.nancumsum and np.nancumprod
- - `#7423 <https://github.com/numpy/numpy/pull/7423>`__: BUG: Ongoing fixes to PR#7416
- - `#7430 <https://github.com/numpy/numpy/pull/7430>`__: DOC: Update 1.11.0-notes.
- - `#7433 <https://github.com/numpy/numpy/pull/7433>`__: MAINT: FutureWarning for changes to np.average subclass handling
- - `#7437 <https://github.com/numpy/numpy/pull/7437>`__: np.full now defaults to the filling value's dtype.
- - `#7438 <https://github.com/numpy/numpy/pull/7438>`__: Allow rolling multiple axes at the same time.
- - `#7439 <https://github.com/numpy/numpy/pull/7439>`__: BUG: Do not try sequence repeat unless necessary
- - `#7442 <https://github.com/numpy/numpy/pull/7442>`__: MANT: Simplify diagonal length calculation logic
- - `#7445 <https://github.com/numpy/numpy/pull/7445>`__: BUG: reference count leak in bincount, fixes #6805
- - `#7446 <https://github.com/numpy/numpy/pull/7446>`__: DOC: ndarray typo fix
- - `#7447 <https://github.com/numpy/numpy/pull/7447>`__: BUG: scalar integer negative powers gave wrong results.
- - `#7448 <https://github.com/numpy/numpy/pull/7448>`__: DOC: array "See also" link to full and full_like instead of fill
- - `#7456 <https://github.com/numpy/numpy/pull/7456>`__: BUG: int overflow in reshape, fixes #7455, fixes #7293
- - `#7463 <https://github.com/numpy/numpy/pull/7463>`__: BUG: fix array too big error for wide dtypes.
- - `#7466 <https://github.com/numpy/numpy/pull/7466>`__: BUG: segfault inplace object reduceat, fixes #7465
- - `#7468 <https://github.com/numpy/numpy/pull/7468>`__: BUG: more on inplace reductions, fixes #615
- - `#7469 <https://github.com/numpy/numpy/pull/7469>`__: MAINT: Update git .mailmap
- - `#7472 <https://github.com/numpy/numpy/pull/7472>`__: MAINT: Update .mailmap.
- - `#7477 <https://github.com/numpy/numpy/pull/7477>`__: MAINT: Yet more .mailmap updates for recent contributors.
- - `#7481 <https://github.com/numpy/numpy/pull/7481>`__: BUG: Fix segfault in PyArray_OrderConverter
- - `#7482 <https://github.com/numpy/numpy/pull/7482>`__: BUG: Memory Leak in _GenericBinaryOutFunction
- - `#7489 <https://github.com/numpy/numpy/pull/7489>`__: Faster real_if_close.
- - `#7491 <https://github.com/numpy/numpy/pull/7491>`__: DOC: Update subclassing doc regarding downstream compatibility
- - `#7496 <https://github.com/numpy/numpy/pull/7496>`__: BUG: don't use pow for integer power ufunc loops.
- - `#7504 <https://github.com/numpy/numpy/pull/7504>`__: DOC: remove "arr" from keepdims docstrings
- - `#7505 <https://github.com/numpy/numpy/pull/7505>`__: MAIN: fix to #7382, make scl in np.average writeable
- - `#7507 <https://github.com/numpy/numpy/pull/7507>`__: MAINT: Remove nose.SkipTest import.
- - `#7508 <https://github.com/numpy/numpy/pull/7508>`__: DOC: link frompyfunc and vectorize
- - `#7511 <https://github.com/numpy/numpy/pull/7511>`__: numpy.power(0, 0) should return 1
- - `#7515 <https://github.com/numpy/numpy/pull/7515>`__: BUG: MaskedArray.count treats negative axes incorrectly
- - `#7518 <https://github.com/numpy/numpy/pull/7518>`__: BUG: Extend glibc complex trig functions blacklist to glibc <...
- - `#7521 <https://github.com/numpy/numpy/pull/7521>`__: DOC: rephrase writeup of memmap changes
- - `#7522 <https://github.com/numpy/numpy/pull/7522>`__: BUG: Fixed iteration over additional bad commands
- - `#7526 <https://github.com/numpy/numpy/pull/7526>`__: DOC: Removed an extra `:const:`
- - `#7529 <https://github.com/numpy/numpy/pull/7529>`__: BUG: Floating exception with invalid axis in np.lexsort
- - `#7534 <https://github.com/numpy/numpy/pull/7534>`__: MAINT: Update setup.py to reflect supported python versions.
- - `#7536 <https://github.com/numpy/numpy/pull/7536>`__: MAINT: Always use PyCapsule instead of PyCObject in mtrand.pyx
- - `#7539 <https://github.com/numpy/numpy/pull/7539>`__: MAINT: Cleanup of random stuff
- - `#7549 <https://github.com/numpy/numpy/pull/7549>`__: BUG: allow graceful recovery for no Liux compiler
- - `#7562 <https://github.com/numpy/numpy/pull/7562>`__: BUG: Fix test_from_object_array_unicode (test_defchararray.TestBasic)…
- - `#7565 <https://github.com/numpy/numpy/pull/7565>`__: BUG: Fix test_ctypeslib and test_indexing for debug interpreter
- - `#7566 <https://github.com/numpy/numpy/pull/7566>`__: MAINT: use manylinux1 wheel for cython
- - `#7568 <https://github.com/numpy/numpy/pull/7568>`__: Fix a false positive OverflowError in Python 3.x when value above...
- - `#7579 <https://github.com/numpy/numpy/pull/7579>`__: DOC: clarify purpose of Attributes section
- - `#7584 <https://github.com/numpy/numpy/pull/7584>`__: BUG: fixes #7572, percent in path
- - `#7586 <https://github.com/numpy/numpy/pull/7586>`__: Make np.ma.take works on scalars
- - `#7587 <https://github.com/numpy/numpy/pull/7587>`__: BUG: linalg.norm(): Don't convert object arrays to float
- - `#7598 <https://github.com/numpy/numpy/pull/7598>`__: Cast array size to int64 when loading from archive
- - `#7602 <https://github.com/numpy/numpy/pull/7602>`__: DOC: Remove isreal and iscomplex from ufunc list
- - `#7605 <https://github.com/numpy/numpy/pull/7605>`__: DOC: fix incorrect Gamma distribution parameterization comments
- - `#7609 <https://github.com/numpy/numpy/pull/7609>`__: BUG: Fix TypeError when raising TypeError
- - `#7611 <https://github.com/numpy/numpy/pull/7611>`__: ENH: expose test runner raise_warnings option
- - `#7614 <https://github.com/numpy/numpy/pull/7614>`__: BLD: Avoid using os.spawnve in favor of os.spawnv in exec_command
- - `#7618 <https://github.com/numpy/numpy/pull/7618>`__: BUG: distance arg of np.gradient must be scalar, fix docstring
- - `#7626 <https://github.com/numpy/numpy/pull/7626>`__: DOC: RST definition list fixes
- - `#7627 <https://github.com/numpy/numpy/pull/7627>`__: MAINT: unify tup processing, move tup use to after all PyTuple_SetItem...
- - `#7630 <https://github.com/numpy/numpy/pull/7630>`__: MAINT: add ifdef around PyDictProxy_Check macro
- - `#7631 <https://github.com/numpy/numpy/pull/7631>`__: MAINT: linalg: fix comment, simplify math
- - `#7634 <https://github.com/numpy/numpy/pull/7634>`__: BLD: correct C compiler customization in system_info.py Closes...
- - `#7635 <https://github.com/numpy/numpy/pull/7635>`__: BUG: ma.median alternate fix for #7592
- - `#7636 <https://github.com/numpy/numpy/pull/7636>`__: MAINT: clean up testing.assert_raises_regexp, 2.6-specific code...
- - `#7637 <https://github.com/numpy/numpy/pull/7637>`__: MAINT: clearer exception message when importing multiarray fails.
- - `#7639 <https://github.com/numpy/numpy/pull/7639>`__: TST: fix a set of test errors in master.
- - `#7643 <https://github.com/numpy/numpy/pull/7643>`__: DOC : minor changes to linspace docstring
- - `#7651 <https://github.com/numpy/numpy/pull/7651>`__: BUG: one to any power is still 1. Broken edgecase for int arrays
- - `#7655 <https://github.com/numpy/numpy/pull/7655>`__: BLD: Remove Intel compiler flag -xSSE4.2
- - `#7658 <https://github.com/numpy/numpy/pull/7658>`__: BUG: fix incorrect printing of 1D masked arrays
- - `#7659 <https://github.com/numpy/numpy/pull/7659>`__: BUG: Temporary fix for str(mvoid) for object field types
- - `#7664 <https://github.com/numpy/numpy/pull/7664>`__: BUG: Fix unicode with byte swap transfer and copyswap
- - `#7667 <https://github.com/numpy/numpy/pull/7667>`__: Restore histogram consistency
- - `#7668 <https://github.com/numpy/numpy/pull/7668>`__: ENH: Do not check the type of module.__dict__ explicit in test.
- - `#7669 <https://github.com/numpy/numpy/pull/7669>`__: BUG: boolean assignment no GIL release when transfer needs API
- - `#7673 <https://github.com/numpy/numpy/pull/7673>`__: DOC: Create Numpy 1.11.1 release notes.
- - `#7675 <https://github.com/numpy/numpy/pull/7675>`__: BUG: fix handling of right edge of final bin.
- - `#7678 <https://github.com/numpy/numpy/pull/7678>`__: BUG: Fix np.clip bug NaN handling for Visual Studio 2015
- - `#7679 <https://github.com/numpy/numpy/pull/7679>`__: MAINT: Fix up C++ comment in arraytypes.c.src.
- - `#7681 <https://github.com/numpy/numpy/pull/7681>`__: DOC: Update 1.11.1 release notes.
- - `#7686 <https://github.com/numpy/numpy/pull/7686>`__: ENH: Changing FFT cache to a bounded LRU cache
- - `#7688 <https://github.com/numpy/numpy/pull/7688>`__: DOC: fix broken genfromtxt examples in user guide. Closes gh-7662.
- - `#7689 <https://github.com/numpy/numpy/pull/7689>`__: BENCH: add correlate/convolve benchmarks.
- - `#7696 <https://github.com/numpy/numpy/pull/7696>`__: DOC: update wheel build / upload instructions
- - `#7699 <https://github.com/numpy/numpy/pull/7699>`__: BLD: preserve library order
- - `#7704 <https://github.com/numpy/numpy/pull/7704>`__: ENH: Add bits attribute to np.finfo
- - `#7712 <https://github.com/numpy/numpy/pull/7712>`__: BUG: Fix race condition with new FFT cache
- - `#7715 <https://github.com/numpy/numpy/pull/7715>`__: BUG: Remove memory leak in np.place
- - `#7719 <https://github.com/numpy/numpy/pull/7719>`__: BUG: Fix segfault in np.random.shuffle for arrays of different...
- - `#7723 <https://github.com/numpy/numpy/pull/7723>`__: Change mkl_info.dir_env_var from MKL to MKLROOT
- - `#7727 <https://github.com/numpy/numpy/pull/7727>`__: DOC: Corrections in Datetime Units-arrays.datetime.rst
- - `#7729 <https://github.com/numpy/numpy/pull/7729>`__: DOC: fix typo in savetxt docstring (closes #7620)
- - `#7733 <https://github.com/numpy/numpy/pull/7733>`__: Update 7525, DOC: Fix order='A' docs of np.array.
- - `#7734 <https://github.com/numpy/numpy/pull/7734>`__: Update 7542, ENH: Add `polyrootval` to numpy.polynomial
- - `#7735 <https://github.com/numpy/numpy/pull/7735>`__: BUG: fix issue on OS X with Python 3.x where npymath.ini was...
- - `#7739 <https://github.com/numpy/numpy/pull/7739>`__: DOC: Mention the changes of #6430 in the release notes.
- - `#7740 <https://github.com/numpy/numpy/pull/7740>`__: DOC: add reference to poisson rng
- - `#7743 <https://github.com/numpy/numpy/pull/7743>`__: Update 7476, DEP: deprecate Numeric-style typecodes, closes #2148
- - `#7744 <https://github.com/numpy/numpy/pull/7744>`__: DOC: Remove "ones_like" from ufuncs list (it is not)
- - `#7746 <https://github.com/numpy/numpy/pull/7746>`__: DOC: Clarify the effect of rcond in numpy.linalg.lstsq.
- - `#7747 <https://github.com/numpy/numpy/pull/7747>`__: Update 7672, BUG: Make sure we don't divide by zero
- - `#7748 <https://github.com/numpy/numpy/pull/7748>`__: DOC: Update float32 mean example in docstring
- - `#7754 <https://github.com/numpy/numpy/pull/7754>`__: Update 7612, ENH: Add broadcast.ndim to match code elsewhere.
- - `#7757 <https://github.com/numpy/numpy/pull/7757>`__: Update 7175, BUG: Invalid read of size 4 in PyArray_FromFile
- - `#7759 <https://github.com/numpy/numpy/pull/7759>`__: BUG: Fix numpy.i support for numpy API < 1.7.
- - `#7760 <https://github.com/numpy/numpy/pull/7760>`__: ENH: Make assert_almost_equal & assert_array_almost_equal consistent.
- - `#7766 <https://github.com/numpy/numpy/pull/7766>`__: fix an English typo
- - `#7771 <https://github.com/numpy/numpy/pull/7771>`__: DOC: link geomspace from logspace
- - `#7773 <https://github.com/numpy/numpy/pull/7773>`__: DOC: Remove a redundant the
- - `#7777 <https://github.com/numpy/numpy/pull/7777>`__: DOC: Update Numpy 1.11.1 release notes.
- - `#7785 <https://github.com/numpy/numpy/pull/7785>`__: DOC: update wheel building procedure for release
- - `#7789 <https://github.com/numpy/numpy/pull/7789>`__: MRG: add note of 64-bit wheels on Windows
- - `#7791 <https://github.com/numpy/numpy/pull/7791>`__: f2py.compile issues (#7683)
- - `#7799 <https://github.com/numpy/numpy/pull/7799>`__: "lambda" is not allowed to use as keyword arguments in a sample...
- - `#7803 <https://github.com/numpy/numpy/pull/7803>`__: BUG: interpret 'c' PEP3118/struct type as 'S1'.
- - `#7807 <https://github.com/numpy/numpy/pull/7807>`__: DOC: Misplaced parens in formula
- - `#7817 <https://github.com/numpy/numpy/pull/7817>`__: BUG: Make sure npy_mul_with_overflow_<type> detects overflow.
- - `#7818 <https://github.com/numpy/numpy/pull/7818>`__: numpy/distutils/misc_util.py fix for #7809: check that _tmpdirs...
- - `#7820 <https://github.com/numpy/numpy/pull/7820>`__: MAINT: Allocate fewer bytes for empty arrays.
- - `#7823 <https://github.com/numpy/numpy/pull/7823>`__: BUG: Fixed masked array behavior for scalar inputs to np.ma.atleast_*d
- - `#7834 <https://github.com/numpy/numpy/pull/7834>`__: DOC: Added an example
- - `#7839 <https://github.com/numpy/numpy/pull/7839>`__: Pypy fixes
- - `#7840 <https://github.com/numpy/numpy/pull/7840>`__: Fix ATLAS version detection
- - `#7842 <https://github.com/numpy/numpy/pull/7842>`__: Fix versionadded tags
- - `#7848 <https://github.com/numpy/numpy/pull/7848>`__: MAINT: Fix remaining uses of deprecated Python imp module.
- - `#7853 <https://github.com/numpy/numpy/pull/7853>`__: BUG: Make sure numpy globals keep identity after reload.
- - `#7863 <https://github.com/numpy/numpy/pull/7863>`__: ENH: turn quicksort into introsort
- - `#7866 <https://github.com/numpy/numpy/pull/7866>`__: Document runtests extra argv
- - `#7871 <https://github.com/numpy/numpy/pull/7871>`__: BUG: handle introsort depth limit properly
- - `#7879 <https://github.com/numpy/numpy/pull/7879>`__: DOC: fix typo in documentation of loadtxt (closes #7878)
- - `#7885 <https://github.com/numpy/numpy/pull/7885>`__: Handle NetBSD specific <sys/endian.h>
- - `#7889 <https://github.com/numpy/numpy/pull/7889>`__: DOC: #7881. Fix link to record arrays
- - `#7894 <https://github.com/numpy/numpy/pull/7894>`__: fixup-7790, BUG: construct ma.array from np.array which contains...
- - `#7898 <https://github.com/numpy/numpy/pull/7898>`__: Spelling and grammar fix.
- - `#7903 <https://github.com/numpy/numpy/pull/7903>`__: BUG: fix float16 type not being called due to wrong ordering
- - `#7908 <https://github.com/numpy/numpy/pull/7908>`__: BLD: Fixed detection for recent MKL versions
- - `#7911 <https://github.com/numpy/numpy/pull/7911>`__: BUG: fix for issue#7835 (ma.median of 1d)
- - `#7912 <https://github.com/numpy/numpy/pull/7912>`__: ENH: skip or avoid gc/objectmodel differences btwn pypy and cpython
- - `#7918 <https://github.com/numpy/numpy/pull/7918>`__: ENH: allow numpy.apply_along_axis() to work with ndarray subclasses
- - `#7922 <https://github.com/numpy/numpy/pull/7922>`__: ENH: Add ma.convolve and ma.correlate for #6458
- - `#7925 <https://github.com/numpy/numpy/pull/7925>`__: Monkey-patch _msvccompile.gen_lib_option like any other compilators
- - `#7931 <https://github.com/numpy/numpy/pull/7931>`__: BUG: Check for HAVE_LDOUBLE_DOUBLE_DOUBLE_LE in npy_math_complex.
- - `#7936 <https://github.com/numpy/numpy/pull/7936>`__: ENH: improve duck typing inside iscomplexobj
- - `#7937 <https://github.com/numpy/numpy/pull/7937>`__: BUG: Guard against buggy comparisons in generic quicksort.
- - `#7938 <https://github.com/numpy/numpy/pull/7938>`__: DOC: add cbrt to math summary page
- - `#7941 <https://github.com/numpy/numpy/pull/7941>`__: BUG: Make sure numpy globals keep identity after reload.
- - `#7943 <https://github.com/numpy/numpy/pull/7943>`__: DOC: #7927. Remove deprecated note for memmap relevant for Python...
- - `#7952 <https://github.com/numpy/numpy/pull/7952>`__: BUG: Use keyword arguments to initialize Extension base class.
- - `#7956 <https://github.com/numpy/numpy/pull/7956>`__: BLD: remove __NUMPY_SETUP__ from builtins at end of setup.py
- - `#7963 <https://github.com/numpy/numpy/pull/7963>`__: BUG: MSVCCompiler grows 'lib' & 'include' env strings exponentially.
- - `#7965 <https://github.com/numpy/numpy/pull/7965>`__: BUG: cannot modify tuple after use
- - `#7976 <https://github.com/numpy/numpy/pull/7976>`__: DOC: Fixed documented dimension of return value
- - `#7977 <https://github.com/numpy/numpy/pull/7977>`__: DOC: Create 1.11.2 release notes.
- - `#7979 <https://github.com/numpy/numpy/pull/7979>`__: DOC: Corrected allowed keywords in add_(installed_)library
- - `#7980 <https://github.com/numpy/numpy/pull/7980>`__: ENH: Add ability to runtime select ufunc loops, add AVX2 integer...
- - `#7985 <https://github.com/numpy/numpy/pull/7985>`__: Rebase 7763, ENH: Add new warning suppression/filtering context
- - `#7987 <https://github.com/numpy/numpy/pull/7987>`__: DOC: See also np.load and np.memmap in np.lib.format.open_memmap
- - `#7988 <https://github.com/numpy/numpy/pull/7988>`__: DOC: Include docstring for cbrt, spacing and fabs in documentation
- - `#7999 <https://github.com/numpy/numpy/pull/7999>`__: ENH: add inplace cases to fast ufunc loop macros
- - `#8006 <https://github.com/numpy/numpy/pull/8006>`__: DOC: Update 1.11.2 release notes.
- - `#8008 <https://github.com/numpy/numpy/pull/8008>`__: MAINT: Remove leftover imp module imports.
- - `#8009 <https://github.com/numpy/numpy/pull/8009>`__: DOC: Fixed three typos in the c-info.ufunc-tutorial
- - `#8011 <https://github.com/numpy/numpy/pull/8011>`__: DOC: Update 1.11.2 release notes.
- - `#8014 <https://github.com/numpy/numpy/pull/8014>`__: BUG: Fix fid.close() to use os.close(fid)
- - `#8016 <https://github.com/numpy/numpy/pull/8016>`__: BUG: Fix numpy.ma.median.
- - `#8018 <https://github.com/numpy/numpy/pull/8018>`__: BUG: Fixes return for np.ma.count if keepdims is True and axis...
- - `#8021 <https://github.com/numpy/numpy/pull/8021>`__: DOC: change all non-code instances of Numpy to NumPy
- - `#8027 <https://github.com/numpy/numpy/pull/8027>`__: ENH: Add platform indepedent lib dir to PYTHONPATH
- - `#8028 <https://github.com/numpy/numpy/pull/8028>`__: DOC: Update 1.11.2 release notes.
- - `#8030 <https://github.com/numpy/numpy/pull/8030>`__: BUG: fix np.ma.median with only one non-masked value and an axis...
- - `#8038 <https://github.com/numpy/numpy/pull/8038>`__: MAINT: Update error message in rollaxis.
- - `#8040 <https://github.com/numpy/numpy/pull/8040>`__: Update add_newdocs.py
- - `#8042 <https://github.com/numpy/numpy/pull/8042>`__: BUG: core: fix bug in NpyIter buffering with discontinuous arrays
- - `#8045 <https://github.com/numpy/numpy/pull/8045>`__: DOC: Update 1.11.2 release notes.
- - `#8050 <https://github.com/numpy/numpy/pull/8050>`__: remove refcount semantics, now a.resize() almost always requires...
- - `#8051 <https://github.com/numpy/numpy/pull/8051>`__: Clear signaling NaN exceptions
- - `#8054 <https://github.com/numpy/numpy/pull/8054>`__: ENH: add signature argument to vectorize for vectorizing like...
- - `#8057 <https://github.com/numpy/numpy/pull/8057>`__: BUG: lib: Simplify (and fix) pad's handling of the pad_width
- - `#8061 <https://github.com/numpy/numpy/pull/8061>`__: BUG : financial.pmt modifies input (issue #8055)
- - `#8064 <https://github.com/numpy/numpy/pull/8064>`__: MAINT: Add PMIP files to .gitignore
- - `#8065 <https://github.com/numpy/numpy/pull/8065>`__: BUG: Assert fromfile ending earlier in pyx_processing
- - `#8066 <https://github.com/numpy/numpy/pull/8066>`__: BUG, TST: Fix python3-dbg bug in Travis script
- - `#8071 <https://github.com/numpy/numpy/pull/8071>`__: MAINT: Add Tempita to randint helpers
- - `#8075 <https://github.com/numpy/numpy/pull/8075>`__: DOC: Fix description of isinf in nan_to_num
- - `#8080 <https://github.com/numpy/numpy/pull/8080>`__: BUG: non-integers can end up in dtype offsets
- - `#8081 <https://github.com/numpy/numpy/pull/8081>`__: Update outdated Nose URL to nose.readthedocs.io
- - `#8083 <https://github.com/numpy/numpy/pull/8083>`__: ENH: Deprecation warnings for `/` integer division when running...
- - `#8084 <https://github.com/numpy/numpy/pull/8084>`__: DOC: Fix erroneous return type description for np.roots.
- - `#8087 <https://github.com/numpy/numpy/pull/8087>`__: BUG: financial.pmt modifies input #8055
- - `#8088 <https://github.com/numpy/numpy/pull/8088>`__: MAINT: Remove duplicate randint helpers code.
- - `#8093 <https://github.com/numpy/numpy/pull/8093>`__: MAINT: fix assert_raises_regex when used as a context manager
- - `#8096 <https://github.com/numpy/numpy/pull/8096>`__: ENH: Vendorize tempita.
- - `#8098 <https://github.com/numpy/numpy/pull/8098>`__: DOC: Enhance description/usage for np.linalg.eig*h
- - `#8103 <https://github.com/numpy/numpy/pull/8103>`__: Pypy fixes
- - `#8104 <https://github.com/numpy/numpy/pull/8104>`__: Fix test code on cpuinfo's main function
- - `#8107 <https://github.com/numpy/numpy/pull/8107>`__: BUG: Fix array printing with precision=0.
- - `#8109 <https://github.com/numpy/numpy/pull/8109>`__: Fix bug in ravel_multi_index for big indices (Issue #7546)
- - `#8110 <https://github.com/numpy/numpy/pull/8110>`__: BUG: distutils: fix issue with rpath in fcompiler/gnu.py
- - `#8111 <https://github.com/numpy/numpy/pull/8111>`__: ENH: Add a tool for release authors and PRs.
- - `#8112 <https://github.com/numpy/numpy/pull/8112>`__: DOC: Fix "See also" links in linalg.
- - `#8114 <https://github.com/numpy/numpy/pull/8114>`__: BUG: core: add missing error check after PyLong_AsSsize_t
- - `#8121 <https://github.com/numpy/numpy/pull/8121>`__: DOC: Improve histogram2d() example.
- - `#8122 <https://github.com/numpy/numpy/pull/8122>`__: BUG: Fix broken pickle in MaskedArray when dtype is object (Return...
- - `#8124 <https://github.com/numpy/numpy/pull/8124>`__: BUG: Fixed build break
- - `#8125 <https://github.com/numpy/numpy/pull/8125>`__: Rebase, BUG: Fixed deepcopy of F-order object arrays.
- - `#8127 <https://github.com/numpy/numpy/pull/8127>`__: BUG: integers to a negative integer powers should error.
- - `#8141 <https://github.com/numpy/numpy/pull/8141>`__: improve configure checks for broken systems
- - `#8142 <https://github.com/numpy/numpy/pull/8142>`__: BUG: np.ma.mean and var should return scalar if no mask
- - `#8148 <https://github.com/numpy/numpy/pull/8148>`__: BUG: import full module path in npy_load_module
- - `#8153 <https://github.com/numpy/numpy/pull/8153>`__: MAINT: Expose void-scalar "base" attribute in python
- - `#8156 <https://github.com/numpy/numpy/pull/8156>`__: DOC: added example with empty indices for a scalar, #8138
- - `#8160 <https://github.com/numpy/numpy/pull/8160>`__: BUG: fix _array2string for structured array (issue #5692)
- - `#8164 <https://github.com/numpy/numpy/pull/8164>`__: MAINT: Update mailmap for NumPy 1.12.0
- - `#8165 <https://github.com/numpy/numpy/pull/8165>`__: Fixup 8152, BUG: assert_allclose(..., equal_nan=False) doesn't...
- - `#8167 <https://github.com/numpy/numpy/pull/8167>`__: Fixup 8146, DOC: Clarify when PyArray_{Max, Min, Ptp} return...
- - `#8168 <https://github.com/numpy/numpy/pull/8168>`__: DOC: Minor spelling fix in genfromtxt() docstring.
- - `#8173 <https://github.com/numpy/numpy/pull/8173>`__: BLD: Enable build on AIX
- - `#8174 <https://github.com/numpy/numpy/pull/8174>`__: DOC: warn that dtype.descr is only for use in PEP3118
- - `#8177 <https://github.com/numpy/numpy/pull/8177>`__: MAINT: Add python 3.6 support to suppress_warnings
- - `#8178 <https://github.com/numpy/numpy/pull/8178>`__: MAINT: Fix ResourceWarning new in Python 3.6.
- - `#8180 <https://github.com/numpy/numpy/pull/8180>`__: FIX: protect stolen ref by PyArray_NewFromDescr in array_empty
- - `#8181 <https://github.com/numpy/numpy/pull/8181>`__: ENH: Improve announce to find github squash-merge commits.
- - `#8182 <https://github.com/numpy/numpy/pull/8182>`__: MAINT: Update .mailmap
- - `#8183 <https://github.com/numpy/numpy/pull/8183>`__: MAINT: Ediff1d performance
- - `#8184 <https://github.com/numpy/numpy/pull/8184>`__: MAINT: make `assert_allclose` behavior on `nan`s match pre 1.12
- - `#8188 <https://github.com/numpy/numpy/pull/8188>`__: DOC: 'highest' is exclusive for randint()
- - `#8189 <https://github.com/numpy/numpy/pull/8189>`__: BUG: setfield should raise if arr is not writeable
- - `#8190 <https://github.com/numpy/numpy/pull/8190>`__: ENH: Add a float_power function with at least float64 precision.
- - `#8197 <https://github.com/numpy/numpy/pull/8197>`__: DOC: Add missing arguments to np.ufunc.outer
- - `#8198 <https://github.com/numpy/numpy/pull/8198>`__: DEP: Deprecate the keepdims argument to accumulate
- - `#8199 <https://github.com/numpy/numpy/pull/8199>`__: MAINT: change path to env in distutils.system_info. Closes gh-8195.
- - `#8200 <https://github.com/numpy/numpy/pull/8200>`__: BUG: Fix structured array format functions
- - `#8202 <https://github.com/numpy/numpy/pull/8202>`__: ENH: specialize name of dev package by interpreter
- - `#8205 <https://github.com/numpy/numpy/pull/8205>`__: DOC: change development instructions from SSH to HTTPS access.
- - `#8216 <https://github.com/numpy/numpy/pull/8216>`__: DOC: Patch doc errors for atleast_nd and frombuffer
- - `#8218 <https://github.com/numpy/numpy/pull/8218>`__: BUG: ediff1d should return subclasses
- - `#8219 <https://github.com/numpy/numpy/pull/8219>`__: DOC: Turn SciPy references into links.
- - `#8222 <https://github.com/numpy/numpy/pull/8222>`__: ENH: Make numpy.mean() do more precise computation
- - `#8227 <https://github.com/numpy/numpy/pull/8227>`__: BUG: Better check for invalid bounds in np.random.uniform.
- - `#8231 <https://github.com/numpy/numpy/pull/8231>`__: ENH: Refactor numpy ** operators for numpy scalar integer powers
- - `#8234 <https://github.com/numpy/numpy/pull/8234>`__: DOC: Clarified when a copy is made in numpy.asarray
- - `#8236 <https://github.com/numpy/numpy/pull/8236>`__: DOC: Fix documentation pull requests.
- - `#8238 <https://github.com/numpy/numpy/pull/8238>`__: MAINT: Update pavement.py
- - `#8239 <https://github.com/numpy/numpy/pull/8239>`__: ENH: Improve announce tool.
- - `#8240 <https://github.com/numpy/numpy/pull/8240>`__: REL: Prepare for 1.12.x branch
- - `#8243 <https://github.com/numpy/numpy/pull/8243>`__: BUG: Update operator `**` tests for new behavior.
- - `#8246 <https://github.com/numpy/numpy/pull/8246>`__: REL: Reset strides for RELAXED_STRIDE_CHECKING for 1.12 releases.
- - `#8265 <https://github.com/numpy/numpy/pull/8265>`__: BUG: np.piecewise not working for scalars
- - `#8272 <https://github.com/numpy/numpy/pull/8272>`__: TST: Path test should resolve symlinks when comparing
- - `#8282 <https://github.com/numpy/numpy/pull/8282>`__: DOC: Update 1.12.0 release notes.
- - `#8286 <https://github.com/numpy/numpy/pull/8286>`__: BUG: Fix pavement.py write_release_task.
- - `#8296 <https://github.com/numpy/numpy/pull/8296>`__: BUG: Fix iteration over reversed subspaces in mapiter_ at name@.
- - `#8304 <https://github.com/numpy/numpy/pull/8304>`__: BUG: Fix PyPy crash in PyUFunc_GenericReduction.
- - `#8319 <https://github.com/numpy/numpy/pull/8319>`__: BLD: blacklist powl (longdouble power function) on OS X.
- - `#8320 <https://github.com/numpy/numpy/pull/8320>`__: BUG: do not link to Accelerate if OpenBLAS, MKL or BLIS are found.
- - `#8322 <https://github.com/numpy/numpy/pull/8322>`__: BUG: fixed kind specifications for parameters
- - `#8336 <https://github.com/numpy/numpy/pull/8336>`__: BUG: fix packbits and unpackbits to correctly handle empty arrays
- - `#8338 <https://github.com/numpy/numpy/pull/8338>`__: BUG: fix test_api test that fails intermittently in python 3
- - `#8339 <https://github.com/numpy/numpy/pull/8339>`__: BUG: Fix ndarray.tofile large file corruption in append mode.
- - `#8359 <https://github.com/numpy/numpy/pull/8359>`__: BUG: Fix suppress_warnings (again) for Python 3.6.
- - `#8372 <https://github.com/numpy/numpy/pull/8372>`__: BUG: Fixes for ma.median and nanpercentile.
- - `#8373 <https://github.com/numpy/numpy/pull/8373>`__: BUG: correct letter case
- - `#8379 <https://github.com/numpy/numpy/pull/8379>`__: DOC: Update 1.12.0-notes.rst.
- - `#8390 <https://github.com/numpy/numpy/pull/8390>`__: ENH: retune apply_along_axis nanmedian cutoff in 1.12
- - `#8391 <https://github.com/numpy/numpy/pull/8391>`__: DEP: Fix escaped string characters deprecated in Python 3.6.
- - `#8394 <https://github.com/numpy/numpy/pull/8394>`__: DOC: create 1.11.3 release notes.
- - `#8399 <https://github.com/numpy/numpy/pull/8399>`__: BUG: Fix author search in announce.py
- - `#8402 <https://github.com/numpy/numpy/pull/8402>`__: DOC, MAINT: Update 1.12.0 notes and mailmap.

Checksums
=========

MD5
~~~

a8dcb183dbe9b336f7bdfb3c9dcab1c4  numpy-1.12.0rc1-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
a0fffded3c5b4562782a60c062205d24  numpy-1.12.0rc1-cp27-cp27m-manylinux1_i686.whl
74a6d2ca493f4ed2aa9a26076eda592d  numpy-1.12.0rc1-cp27-cp27m-manylinux1_x86_64.whl
51a3e553c16d830f9600d071d0a70c34  numpy-1.12.0rc1-cp27-cp27mu-manylinux1_i686.whl
6382c2e48197c009a23b8f122c50c782  numpy-1.12.0rc1-cp27-cp27mu-manylinux1_x86_64.whl
108384da4efc1271cd9a7b9f58763fdc  numpy-1.12.0rc1-cp27-none-win32.whl
c5d45db386d4170d1f19900c55680385  numpy-1.12.0rc1-cp27-none-win_amd64.whl
e06a3e32380f0157ac8829b6da60989b  numpy-1.12.0rc1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
4678191e76df688e8b9fea08267484f9  numpy-1.12.0rc1-cp34-cp34m-manylinux1_i686.whl
a3cfbc1d045476e7ab1fc4cb297f1410  numpy-1.12.0rc1-cp34-cp34m-manylinux1_x86_64.whl
23aa6b0e7997bee8ba161054b8eca263  numpy-1.12.0rc1-cp34-none-win32.whl
f85e2376c835c6a4aed56908df0b2627  numpy-1.12.0rc1-cp34-none-win_amd64.whl
30b88d280aca4d979ce274a6f8802786  numpy-1.12.0rc1-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
a24092d34595bd8f47183e15c512fd25  numpy-1.12.0rc1-cp35-cp35m-manylinux1_i686.whl
99f1613b09845583e4cdd3c27fe0b581  numpy-1.12.0rc1-cp35-cp35m-manylinux1_x86_64.whl
41ed4df28cc2aa4b8ead5474d92e68ec  numpy-1.12.0rc1-cp35-none-win32.whl
dbed48e11c520aed00701cd77f4eff3b  numpy-1.12.0rc1-cp35-none-win_amd64.whl
fec43bde3d3dac92873c11f574aa3c28  numpy-1.12.0rc1.tar.gz
92e300ed24811cd119d3f04168bfcdae  numpy-1.12.0rc1.zip

SHA256
~~~~~~

cdad735c13b344321c9b9174761bdc2e22a199a4cd6c18612f1b02ebe58b4ff7  numpy-1.12.0rc1-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
0172a1987bb3c0ad0b6eec88abc49207d9746cc6f519c599b797a992a53a404c  numpy-1.12.0rc1-cp27-cp27m-manylinux1_i686.whl
1bbd7f2a07514afd5c9298a19953b15ff2b4a2759135aee19231570aab220525  numpy-1.12.0rc1-cp27-cp27m-manylinux1_x86_64.whl
cf2539d4af2409feb005d227d4a88d5371f663974aed57d1fa489a6d17d67bbc  numpy-1.12.0rc1-cp27-cp27mu-manylinux1_i686.whl
6bb0cff8e6fbca38b5048509e991a4697ffdd21ddd7453830cfc80474517d46a  numpy-1.12.0rc1-cp27-cp27mu-manylinux1_x86_64.whl
d23ca5d4d83ac872b7f9d9cd8d6c0c2d243e491199b9bb581f3892b17108acce  numpy-1.12.0rc1-cp27-none-win32.whl
8ede1d028243199666e9ec3980afd773e91af12172e7c9274e1d9dfe86e22169  numpy-1.12.0rc1-cp27-none-win_amd64.whl
210afcb0d2893c19171d78e77d23ab05885379c0fb14cfacefdfc73d69192800  numpy-1.12.0rc1-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
2ffacc9645ed40a10c14aca477999e8ea5f7422e4806a3843fd2ccbaf7ed5ad4  numpy-1.12.0rc1-cp34-cp34m-manylinux1_i686.whl
fc59b0aa44d37c5183ef288d172d81eed8772017c349acb137f8f3cb871d3ff7  numpy-1.12.0rc1-cp34-cp34m-manylinux1_x86_64.whl
46c018582f7003bd424a2776e8bef1370c1a78bd6d76af921ad6ce28539b71de  numpy-1.12.0rc1-cp34-none-win32.whl
930815b162785e77e0ff41651931155a21482f286bc432f9bc552c4308782150  numpy-1.12.0rc1-cp34-none-win_amd64.whl
78835904da4e0e143ba671a7eff8d63282d4d2db868d09c7c9e0cd4f216e43c2  numpy-1.12.0rc1-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
0e71e0b43fcc925fbe227f58dc2f875c4d92299c644ae2243a8cd21e050e3acd  numpy-1.12.0rc1-cp35-cp35m-manylinux1_i686.whl
9c357f1cbaf3aae7f656e0ecd3d2f186622b9424fccb1b587ab13247b68bbc9a  numpy-1.12.0rc1-cp35-cp35m-manylinux1_x86_64.whl
0c3fe4c1ee1955a58cb98b0cc4727dff9c9acf2521d3d34609fc8f772f56ab79  numpy-1.12.0rc1-cp35-none-win32.whl
998b229248b6219938827175a5852463dd1640785df3dd8e15b2ba9018217652  numpy-1.12.0rc1-cp35-none-win_amd64.whl
2a8defaf03473fdaa15e34e849b71221f8ab3da1a7eed510799d55c913b99b06  numpy-1.12.0rc1.tar.gz
7c860cf028b13a88487fde1dcd1ce8f0859a6882c477c42083f50e48c297427e  numpy-1.12.0rc1.zip
-----BEGIN PGP SIGNATURE-----

iQEcBAEBAgAGBQJYWH3jAAoJEGefIoN3xSR7e/wIANIfp4+7gdsFKUMtyrWnlCfz
GtAOX+N+mecTelbDEylnl2D2SDwHrnv1XrJ6hT888jPqnjlnw9NDLkLa9ilVLTAd
8Y5Bo1AZ2PHxyOHPirfGflU0qdlk+T25Ekz43TuyRDNCXoe4ZuQ0GsEzvO2nWFLu
X/oaU16z/xNU5p4uV69emPsku5G3d11X6uP5JHYg5kSAE8pvx/jIv8PMFHC5GfTv
MR6Q7+Oi2gJVa22866o2pq8bqViwLehGQLe95Cs91F8NMTNxxyG3bb7gVO4oLPZ3
5wEVAzFLbwPqgYH9K++sG52FoTJxe7tLCuj+EaLrffK5PywoGEP6Ub5/qKiQaBU=
=hArc
-----END PGP SIGNATURE-----


More information about the NumPy-Discussion mailing list