Update numpy to 1.14.5

[pyup-bot]

This PR updates numpy from 1.14.3 to 1.14.5.

Changelog

1.14.5

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

This is a bugfix release for bugs reported following the 1.14.4 release. The
most significant fixes are:

* fixes for compilation errors on alpine and NetBSD

The Python versions supported in this release are 2.7 and 3.4 - 3.6. The Python
3.6 wheels available from PIP are built with Python 3.6.2 and should be
compatible with all previous versions of Python 3.6. The source releases were
cythonized with Cython 0.28.2 and should work for the upcoming Python 3.7.

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

A total of 1 person contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

* Charles Harris

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

A total of 2 pull requests were merged for this release.

* `11274 <https://github.com/numpy/numpy/pull/11274>`__: BUG: Correct use of NPY_UNUSED.
* `11294 <https://github.com/numpy/numpy/pull/11294>`__: BUG: Remove extra trailing parentheses.



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

1.14.4

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

This is a bugfix release for bugs reported following the 1.14.3 release. The
most significant fixes are:

* fixes for compiler instruction reordering that resulted in NaN's not being
properly propagated in `np.max` and `np.min`,

* fixes for bus faults on SPARC and older ARM due to incorrect alignment
checks.

There are also improvements to printing of long doubles on PPC platforms. All
is not yet perfect on that platform, the whitespace padding is still incorrect
and is to be fixed in numpy 1.15, consequently NumPy still fails some
printing-related (and other) unit tests on ppc systems. However, the printed
values are now correct.

Note that NumPy will error on import if it detects incorrect float32 `dot`
results. This problem has been seen on the Mac when working in the Anaconda
enviroment and is due to a subtle interaction between MKL and PyQt5.  It is not
strictly a NumPy problem, but it is best that users be aware of it.  See the
gh-8577 NumPy issue for more information.

The Python versions supported in this release are 2.7 and 3.4 - 3.6. The Python
3.6 wheels available from PIP are built with Python 3.6.2 and should be
compatible with all previous versions of Python 3.6. The source releases were
cythonized with Cython 0.28.2 and should work for the upcoming Python 3.7.

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

A total of 7 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

* Allan Haldane
* Charles Harris
* Marten van Kerkwijk
* Matti Picus
* Pauli Virtanen
* Ryan Soklaski +
* Sebastian Berg

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

A total of 11 pull requests were merged for this release.

* `11104 <https://github.com/numpy/numpy/pull/11104>`__: BUG: str of DOUBLE_DOUBLE format wrong on ppc64
* `11170 <https://github.com/numpy/numpy/pull/11170>`__: TST: linalg: add regression test for gh-8577
* `11174 <https://github.com/numpy/numpy/pull/11174>`__: MAINT: add sanity-checks to be run at import time
* `11181 <https://github.com/numpy/numpy/pull/11181>`__: BUG: void dtype setup checked offset not actual pointer for alignment
* `11194 <https://github.com/numpy/numpy/pull/11194>`__: BUG: Python2 doubles don't print correctly in interactive shell.
* `11198 <https://github.com/numpy/numpy/pull/11198>`__: BUG: optimizing compilers can reorder call to npy_get_floatstatus
* `11199 <https://github.com/numpy/numpy/pull/11199>`__: BUG: reduce using SSE only warns if inside SSE loop
* `11203 <https://github.com/numpy/numpy/pull/11203>`__: BUG: Bytes delimiter/comments in genfromtxt should be decoded
* `11211 <https://github.com/numpy/numpy/pull/11211>`__: BUG: Fix reference count/memory leak exposed by better testing
* `11219 <https://github.com/numpy/numpy/pull/11219>`__: BUG: Fixes einsum broadcasting bug when optimize=True
* `11251 <https://github.com/numpy/numpy/pull/11251>`__: DOC: Document 1.14.4 release.


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

Links

• PyPI: https://pypi.org/project/numpy
• Changelog: https://pyup.io/changelogs/numpy/
• Homepage: http://www.numpy.org

[coveralls]

Pull Request Test Coverage Report for Build 131

• 0 of 0 changed or added relevant lines in 0 files are covered.
• No unchanged relevant lines lost coverage.
• Overall coverage remained the same at 59.446%

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Totals
Change from base Build 110:	0.0%
Covered Lines:	4204
Relevant Lines:	7072

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