Numpy

==========================

===

The NumPy 1.16.6 release fixes bugs reported against the 1.16.5 release,
and also backports several enhancements from master that seem
appropriate for a release series that is the last to support Python 2.7.
The wheels on PyPI are linked with OpenBLAS v0.3.7, which should fix
errors on Skylake series cpus.

Downstream developers building this release should use Cython \>= 0.29.2
and, if using OpenBLAS, OpenBLAS \>= v0.3.7. The supported Python
versions are 2.7 and 3.5-3.7.

Highlights
==========

- The `np.testing.utils` functions have been updated from 1.19.0-dev0.
This improves the function documentation and error messages as well
extending the `assert_array_compare` function to additional types.

New functions
=============

Allow matmul (``) to work with object arrays.

This is an enhancement that was added in NumPy 1.17 and seems reasonable
to include in the LTS 1.16 release series.

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

Fix regression in matmul (``) for boolean types

Booleans were being treated as integers rather than booleans, which was
a regression from previous behavior.

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

Array comparison assertions include maximum differences

Error messages from array comparison tests such as
`testing.assert_allclose` now include \"max absolute difference\" and
\"max relative difference,\" in addition to the previous \"mismatch\"
percentage. This information makes it easier to update absolute and
relative error tolerances.

Contributors
============

A total of 10 people contributed to this release.

- CakeWithSteak
- Charles Harris
- Chris Burr
- Eric Wieser
- Fernando Saravia
- Lars Grueter
- Matti Picus
- Maxwell Aladago
- Qiming Sun
- Warren Weckesser

Pull requests merged
====================

A total of 14 pull requests were merged for this release.

- [\14211](https://github.com/numpy/numpy/pull/14211): BUG: Fix
uint-overflow if padding with linear\_ramp and negative\...
- [\14275](https://github.com/numpy/numpy/pull/14275): BUG: fixing to
allow unpickling of PY3 pickles from PY2
- [\14340](https://github.com/numpy/numpy/pull/14340): BUG: Fix
misuse of .names and .fields in various places (backport\...
- [\14423](https://github.com/numpy/numpy/pull/14423): BUG: test, fix
regression in converting to ctypes.
- [\14434](https://github.com/numpy/numpy/pull/14434): BUG: Fixed
maximum relative error reporting in assert\_allclose
- [\14509](https://github.com/numpy/numpy/pull/14509): BUG: Fix
regression in boolean matmul.
- [\14686](https://github.com/numpy/numpy/pull/14686): BUG: properly
define PyArray\_DescrCheck
- [\14853](https://github.com/numpy/numpy/pull/14853): BLD: add \'apt
update\' to shippable
- [\14854](https://github.com/numpy/numpy/pull/14854): BUG: Fix
\_ctypes class circular reference. (\13808)
- [\14856](https://github.com/numpy/numpy/pull/14856): BUG: Fix
[np.einsum]{.title-ref} errors on Power9 Linux and z/Linux
- [\14863](https://github.com/numpy/numpy/pull/14863): BLD: Prevent
-flto from optimising long double representation\...
- [\14864](https://github.com/numpy/numpy/pull/14864): BUG: lib: Fix
histogram problem with signed integer arrays.
- [\15172](https://github.com/numpy/numpy/pull/15172): ENH: Backport
improvements to testing functions.
- [\15191](https://github.com/numpy/numpy/pull/15191): REL: Prepare
for 1.16.6 release.

Checksums
=========

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------

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==========================

The NumPy 1.16.5 release fixes bugs reported against the 1.16.4 release, and
also backports several enhancements from master that seem appropriate for a
release series that is the last to support Python 2.7. The wheels on PyPI are
linked with OpenBLAS v0.3.7-dev, which should fix errors on Skylake series
cpus.

Downstream developers building this release should use Cython >= 0.29.2 and, if
using OpenBLAS, OpenBLAS >= v0.3.7. The supported Python versions are 2.7 and
3.5-3.7.


Contributors
============

A total of 18 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

* Alexander Shadchin
* Allan Haldane
* Bruce Merry +
* Charles Harris
* Colin Snyder +
* Dan Allan +
* Emile +
* Eric Wieser
* Grey Baker +
* Maksim Shabunin +
* Marten van Kerkwijk
* Matti Picus
* Peter Andreas Entschev +
* Ralf Gommers
* Richard Harris +
* Sebastian Berg
* Sergei Lebedev +
* Stephan Hoyer

Pull requests merged
====================

A total of 23 pull requests were merged for this release.

* 13742: ENH: Add project URLs to setup.py
* 13823: TEST, ENH: fix tests and ctypes code for PyPy
* 13845: BUG: use npy_intp instead of int for indexing array
* 13867: TST: Ignore DeprecationWarning during nose imports
* 13905: BUG: Fix use-after-free in boolean indexing
* 13933: MAINT/BUG/DOC: Fix errors in _add_newdocs
* 13984: BUG: fix byte order reversal for datetime64[ns]
* 13994: MAINT,BUG: Use nbytes to also catch empty descr during allocation
* 14042: BUG: np.array cleared errors occured in PyMemoryView_FromObject
* 14043: BUG: Fixes for Undefined Behavior Sanitizer (UBSan) errors.
* 14044: BUG: ensure that casting to/from structured is properly checked.
* 14045: MAINT: fix histogram*d dispatchers
* 14046: BUG: further fixup to histogram2d dispatcher.
* 14052: BUG: Replace contextlib.suppress for Python 2.7
* 14056: BUG: fix compilation of 3rd party modules with Py_LIMITED_API...
* 14057: BUG: Fix memory leak in dtype from dict contructor
* 14058: DOC: Document array_function at a higher level.
* 14084: BUG, DOC: add new recfunctions to `__all__`
* 14162: BUG: Remove stray print that causes a SystemError on python 3.7
* 14297: TST: Pin pytest version to 5.0.1.
* 14322: ENH: Enable huge pages in all Linux builds
* 14346: BUG: fix behavior of structured_to_unstructured on non-trivial...
* 14382: REL: Prepare for the NumPy 1.16.5 release.

Checksums
=========

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------

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==========================

The NumPy 1.16.4 release fixes bugs reported against the 1.16.3 release, and
also backports several enhancements from master that seem appropriate for a
release series that is the last to support Python 2.7. The wheels on PyPI are
linked with OpenBLAS v0.3.7-dev, which should fix issues on Skylake series
cpus.

Downstream developers building this release should use Cython >= 0.29.2 and,
if using OpenBLAS, OpenBLAS > v0.3.7. The supported Python versions are 2.7 and
3.5-3.7.


New deprecations
================
Writeable flag of C-API wrapped arrays
--------------------------------------
When an array is created from the C-API to wrap a pointer to data, the only
indication we have of the read-write nature of the data is the ``writeable``
flag set during creation. It is dangerous to force the flag to writeable. In
the future it will not be possible to switch the writeable flag to ``True``
from python. This deprecation should not affect many users since arrays
created in such a manner are very rare in practice and only available through
the NumPy C-API.


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

Potential changes to the random stream
--------------------------------------
Due to bugs in the application of log to random floating point numbers,
the stream may change when sampling from ``np.random.beta``, ``np.random.binomial``,
``np.random.laplace``, ``np.random.logistic``, ``np.random.logseries`` or
``np.random.multinomial`` if a 0 is generated in the underlying MT19937 random stream.
There is a 1 in :math:`10^{53}` chance of this occurring, and so the probability that
the stream changes for any given seed is extremely small. If a 0 is encountered in the
underlying generator, then the incorrect value produced (either ``np.inf``
or ``np.nan``) is now dropped.


Changes
=======

`numpy.lib.recfunctions.structured_to_unstructured` does not squeeze single-field views
---------------------------------------------------------------------------------------
Previously ``structured_to_unstructured(arr[['a']])`` would produce a squeezed
result inconsistent with ``structured_to_unstructured(arr[['a', b']])``. This
was accidental. The old behavior can be retained with
``structured_to_unstructured(arr[['a']]).squeeze(axis=-1)`` or far more simply,
``arr['a']``.


Contributors
============

A total of 10 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

* Charles Harris
* Eric Wieser
* Dennis Zollo +
* Hunter Damron +
* Jingbei Li +
* Kevin Sheppard
* Matti Picus
* Nicola Soranzo +
* Sebastian Berg
* Tyler Reddy


Pull requests merged
====================

A total of 16 pull requests were merged for this release.

* 13392: BUG: Some PyPy versions lack PyStructSequence_InitType2.
* 13394: MAINT, DEP: Fix deprecated ``assertEquals()``
* 13396: BUG: Fix structured_to_unstructured on single-field types (backport)
* 13549: BLD: Make CI pass again with pytest 4.5
* 13552: TST: Register markers in conftest.py.
* 13559: BUG: Removes ValueError for empty kwargs in arraymultiter_new
* 13560: BUG: Add TypeError to accepted exceptions in crackfortran.
* 13561: BUG: Handle subarrays in descr_to_dtype
* 13562: BUG: Protect generators from log(0.0)
* 13563: BUG: Always return views from structured_to_unstructured when...
* 13564: BUG: Catch stderr when checking compiler version
* 13565: BUG: longdouble(int) does not work
* 13587: BUG: distutils/system_info.py fix missing subprocess import (13523)
* 13620: BUG,DEP: Fix writeable flag setting for arrays without base
* 13641: MAINT: Prepare for the 1.16.4 release.
* 13644: BUG: special case object arrays when printing rel-, abs-error

Checksums
=========

MD5
---

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SHA256
------

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7242be12a58fec245ee9734e625964b97cf7e3f2f7d016603f9e56660ce479c7 numpy-1.16.4.zip

==========================

The NumPy 1.16.3 release fixes bugs reported against the 1.16.2 release, and
also backports several enhancements from master that seem appropriate for a
release series that is the last to support Python 2.7. The wheels on PyPI are
linked with OpenBLAS v0.3.4+, which should fix the known threading issues
found in previous OpenBLAS versions.

Downstream developers building this release should use Cython >= 0.29.2 and,
if using OpenBLAS, OpenBLAS > v0.3.4.

The most noticeable change in this release is that unpickling object arrays
when loading ``*.npy`` or ``*.npz`` files now requires an explicit opt-in.
This backwards incompatible change was made in response to
`CVE-2019-6446 <https://nvd.nist.gov/vuln/detail/CVE-2019-6446>`_.


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

Unpickling while loading requires explicit opt-in
-------------------------------------------------
The functions ``np.load``, and ``np.lib.format.read_array`` take an
`allow_pickle` keyword which now defaults to ``False`` in response to
`CVE-2019-6446 <https://nvd.nist.gov/vuln/detail/CVE-2019-6446>`_.


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

Covariance in `random.mvnormal` cast to double
----------------------------------------------
This should make the tolerance used when checking the singular values of the
covariance matrix more meaningful.


Changes
=======

``__array_interface__`` offset now works as documented
------------------------------------------------------
The interface may use an ``offset`` value that was previously mistakenly
ignored.


Checksums
=========

MD5
---

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SHA256
------

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==========================

NumPy 1.16.2 is a quick release fixing several problems encountered on Windows.
The Python versions supported are 2.7 and 3.5-3.7. The Windows problems
addressed are:

- DLL load problems for NumPy wheels on Windows,
- distutils command line parsing on Windows.

There is also a regression fix correcting signed zeros produced by divmod, see
below for details.

Downstream developers building this release should use Cython >= 0.29.2 and, if
using OpenBLAS, OpenBLAS > v0.3.4.

If you are installing using pip, you may encounter a problem with older
installed versions of NumPy that pip did not delete becoming mixed with the
current version, resulting in an ``ImportError``. That problem is particularly
common on Debian derived distributions due to a modified pip. The fix is to
make sure all previous NumPy versions installed by pip have been removed. See
`12736 <https://github.com/numpy/numpy/issues/12736>`__ for discussion of the
issue.


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

Signed zero when using divmod
-----------------------------
Starting in version 1.12.0, numpy incorrectly returned a negatively signed zero
when using the ``divmod`` and ``floor_divide`` functions when the result was
zero. For example:

>>> np.zeros(10)//1
array([-0., -0., -0., -0., -0., -0., -0., -0., -0., -0.])

With this release, the result is correctly returned as a positively signed
zero:

>>> np.zeros(10)//1
array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])


Contributors
============

A total of 5 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

* Charles Harris
* Eric Wieser
* Matti Picus
* Tyler Reddy
* Tony LaTorre +


Pull requests merged
====================

A total of 7 pull requests were merged for this release.

* 12909: TST: fix vmImage dispatch in Azure
* 12923: MAINT: remove complicated test of multiarray import failure mode
* 13020: BUG: fix signed zero behavior in npy_divmod
* 13026: MAINT: Add functions to parse shell-strings in the platform-native...
* 13028: BUG: Fix regression in parsing of F90 and F77 environment variables
* 13038: BUG: parse shell escaping in extra_compile_args and extra_link_args
* 13041: BLD: Windows absolute path DLL loading

Checksums
=========

MD5
---

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SHA256
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