New upstream version 1.16.5

4a740ccf · Sandro Tosi · f5956cfa · 4a740ccf · 4a740ccf · 4a740ccf
Commit 4a740ccf authored 5 years ago by Sandro Tosi
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -11,15 +11,18 @@ include site.cfg.example
 include numpy/random/mtrand/generate_mtrand_c.py
 recursive-include numpy/random/mtrand *.pyx *.pxd
 # Add build support that should go in sdist, but not go in bdist/be installed
+# Note that sub-directories that don't have __init__ are apparently not
+# included by 'recursive-include', so list those separately
+recursive-include numpy *
 recursive-include numpy/_build_utils *
-recursive-include numpy/linalg/lapack_lite *.c *.h
+recursive-include numpy/linalg/lapack_lite *
 include runtests.py
 include tox.ini pytest.ini .coveragerc
 recursive-include tools *
 # Add sdist files whose use depends on local configuration.
 include numpy/core/src/common/cblasfuncs.c
 include numpy/core/src/common/python_xerbla.c
-# Adding scons build related files not found by distutils
+# Adding build related files not found by distutils
 recursive-include numpy/core/code_generators *.py *.txt
 recursive-include numpy/core *.in *.h
 # Add documentation and benchmarks: we don't use add_data_dir since we do not

--- a/PKG-INFO
+++ b/PKG-INFO
 Metadata-Version: 1.2
 Name: numpy
-Version: 1.16.2
+Version: 1.16.5
 Summary:  NumPy is the fundamental package for array computing with Python.
 Home-page: https://www.numpy.org
 Author: NumPy Developers
 Author-email: numpy-discussion@python.org
 License: BSD
 Download-URL: https://pypi.python.org/pypi/numpy
+Project-URL: Bug Tracker, https://github.com/numpy/numpy/issues
+Project-URL: Source Code, https://github.com/numpy/numpy
 Description-Content-Type: UNKNOWN
 Description: It provides:
        

--- a/doc/changelog/1.16.3-changelog.rst
+++ b/doc/changelog/1.16.3-changelog.rst
+
+Contributors
+============
+
+A total of 16 people contributed to this release.  People with a "+" by their
+names contributed a patch for the first time.
+
+* Andreas Schwab
+* Bharat Raghunathan +
+* Bran +
+* Charles Harris
+* Eric Wieser
+* Jakub Wilk
+* Kevin Sheppard
+* Marten van Kerkwijk
+* Matti Picus
+* Paul Ivanov
+* Ralf Gommers
+* Sebastian Berg
+* Tyler Reddy
+* Warren Weckesser
+* Yu Feng
+* adeak +
+
+Pull requests merged
+====================
+
+A total of 26 pull requests were merged for this release.
+
+* `#13072 <https://github.com/numpy/numpy/pull/13072>`__: BUG: Fixes to numpy.distutils.Configuration.get_version (#13056)
+* `#13082 <https://github.com/numpy/numpy/pull/13082>`__: BUG: Fix errors in string formatting while producing an error
+* `#13083 <https://github.com/numpy/numpy/pull/13083>`__: BUG: Convert fortran flags in environment variable
+* `#13084 <https://github.com/numpy/numpy/pull/13084>`__: BUG: Remove error-prone borrowed reference handling
+* `#13085 <https://github.com/numpy/numpy/pull/13085>`__: BUG: Add error checks when converting integers to datetime types
+* `#13091 <https://github.com/numpy/numpy/pull/13091>`__: BUG: Remove our patched version of `distutils.split_quoted`
+* `#13141 <https://github.com/numpy/numpy/pull/13141>`__: BUG: Fix testsuite failures on ppc and riscv
+* `#13142 <https://github.com/numpy/numpy/pull/13142>`__: BUG: Fix parameter validity checks in ``random.choice``
+* `#13143 <https://github.com/numpy/numpy/pull/13143>`__: BUG: Ensure linspace works on object input.
+* `#13144 <https://github.com/numpy/numpy/pull/13144>`__: BLD: fix include list for sdist building.
+* `#13145 <https://github.com/numpy/numpy/pull/13145>`__: BUG: __array_interface__ offset was always ignored
+* `#13274 <https://github.com/numpy/numpy/pull/13274>`__: MAINT: f2py: Add a cast to avoid a compiler warning.
+* `#13275 <https://github.com/numpy/numpy/pull/13275>`__: BUG, MAINT: fix reference count error on invalid input to ndarray.flat
+* `#13276 <https://github.com/numpy/numpy/pull/13276>`__: ENH: Cast covariance to double in random mvnormal
+* `#13278 <https://github.com/numpy/numpy/pull/13278>`__: BUG: Fix null pointer dereference in PyArray_DTypeFromObjectHelper
+* `#13339 <https://github.com/numpy/numpy/pull/13339>`__: BUG: Use C call to sysctlbyname for AVX detection on MacOS.
+* `#13340 <https://github.com/numpy/numpy/pull/13340>`__: BUG: Fix crash when calling savetxt on a padded array
+* `#13341 <https://github.com/numpy/numpy/pull/13341>`__: BUG: ufunc.at iteration variable size fix
+* `#13342 <https://github.com/numpy/numpy/pull/13342>`__: DOC: Add as_ctypes_type to the documentation
+* `#13350 <https://github.com/numpy/numpy/pull/13350>`__: BUG: Return the coefficients array directly
+* `#13351 <https://github.com/numpy/numpy/pull/13351>`__: BUG/MAINT: Tidy typeinfo.h and .c
+* `#13359 <https://github.com/numpy/numpy/pull/13359>`__: BUG: Make allow_pickle=False the default for loading
+* `#13360 <https://github.com/numpy/numpy/pull/13360>`__: DOC: fix some doctest failures
+* `#13363 <https://github.com/numpy/numpy/pull/13363>`__: BUG/MAINT: Tidy typeinfo.h and .c
+* `#13381 <https://github.com/numpy/numpy/pull/13381>`__: BLD: address mingw-w64 issue. Follow-up to gh-9977
+* `#13382 <https://github.com/numpy/numpy/pull/13382>`__: REL: Prepare for the NumPy release.
--- a/doc/changelog/1.16.4-changelog.rst
+++ b/doc/changelog/1.16.4-changelog.rst
+
+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 <https://github.com/numpy/numpy/pull/13392>`__: BUG: Some PyPy versions lack PyStructSequence_InitType2.
+* `#13394 <https://github.com/numpy/numpy/pull/13394>`__: MAINT, DEP: Fix deprecated ``assertEquals()``
+* `#13396 <https://github.com/numpy/numpy/pull/13396>`__: BUG: Fix structured_to_unstructured on single-field types (backport)
+* `#13549 <https://github.com/numpy/numpy/pull/13549>`__: BLD: Make CI pass again with pytest 4.5
+* `#13552 <https://github.com/numpy/numpy/pull/13552>`__: TST: Register markers in conftest.py.
+* `#13559 <https://github.com/numpy/numpy/pull/13559>`__: BUG: Removes ValueError for empty kwargs in arraymultiter_new
+* `#13560 <https://github.com/numpy/numpy/pull/13560>`__: BUG: Add TypeError to accepted exceptions in crackfortran.
+* `#13561 <https://github.com/numpy/numpy/pull/13561>`__: BUG: Handle subarrays in descr_to_dtype
+* `#13562 <https://github.com/numpy/numpy/pull/13562>`__: BUG: Protect generators from log(0.0)
+* `#13563 <https://github.com/numpy/numpy/pull/13563>`__: BUG: Always return views from structured_to_unstructured when...
+* `#13564 <https://github.com/numpy/numpy/pull/13564>`__: BUG: Catch stderr when checking compiler version
+* `#13565 <https://github.com/numpy/numpy/pull/13565>`__: BUG: longdouble(int) does not work
+* `#13587 <https://github.com/numpy/numpy/pull/13587>`__: BUG: distutils/system_info.py fix missing subprocess import (#13523)
+* `#13620 <https://github.com/numpy/numpy/pull/13620>`__: BUG,DEP: Fix writeable flag setting for arrays without base
+* `#13641 <https://github.com/numpy/numpy/pull/13641>`__: MAINT: Prepare for the 1.16.4 release.
+* `#13644 <https://github.com/numpy/numpy/pull/13644>`__: BUG: special case object arrays when printing rel-, abs-error
--- a/doc/changelog/1.16.5-changelog.rst
+++ b/doc/changelog/1.16.5-changelog.rst
+
+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 <https://github.com/numpy/numpy/pull/13742>`__: ENH: Add project URLs to setup.py
+* `#13823 <https://github.com/numpy/numpy/pull/13823>`__: TEST, ENH: fix tests and ctypes code for PyPy
+* `#13845 <https://github.com/numpy/numpy/pull/13845>`__: BUG: use npy_intp instead of int for indexing array
+* `#13867 <https://github.com/numpy/numpy/pull/13867>`__: TST: Ignore DeprecationWarning during nose imports
+* `#13905 <https://github.com/numpy/numpy/pull/13905>`__: BUG: Fix use-after-free in boolean indexing
+* `#13933 <https://github.com/numpy/numpy/pull/13933>`__: MAINT/BUG/DOC: Fix errors in _add_newdocs
+* `#13984 <https://github.com/numpy/numpy/pull/13984>`__: BUG: fix byte order reversal for datetime64[ns]
+* `#13994 <https://github.com/numpy/numpy/pull/13994>`__: MAINT,BUG: Use nbytes to also catch empty descr during allocation
+* `#14042 <https://github.com/numpy/numpy/pull/14042>`__: BUG: np.array cleared errors occured in PyMemoryView_FromObject
+* `#14043 <https://github.com/numpy/numpy/pull/14043>`__: BUG: Fixes for Undefined Behavior Sanitizer (UBSan) errors.
+* `#14044 <https://github.com/numpy/numpy/pull/14044>`__: BUG: ensure that casting to/from structured is properly checked.
+* `#14045 <https://github.com/numpy/numpy/pull/14045>`__: MAINT: fix histogram*d dispatchers
+* `#14046 <https://github.com/numpy/numpy/pull/14046>`__: BUG: further fixup to histogram2d dispatcher.
+* `#14052 <https://github.com/numpy/numpy/pull/14052>`__: BUG: Replace contextlib.suppress for Python 2.7
+* `#14056 <https://github.com/numpy/numpy/pull/14056>`__: BUG: fix compilation of 3rd party modules with Py_LIMITED_API...
+* `#14057 <https://github.com/numpy/numpy/pull/14057>`__: BUG: Fix memory leak in dtype from dict contructor
+* `#14058 <https://github.com/numpy/numpy/pull/14058>`__: DOC: Document array_function at a higher level.
+* `#14084 <https://github.com/numpy/numpy/pull/14084>`__: BUG, DOC: add new recfunctions to `__all__`
+* `#14162 <https://github.com/numpy/numpy/pull/14162>`__: BUG: Remove stray print that causes a SystemError on python 3.7
+* `#14297 <https://github.com/numpy/numpy/pull/14297>`__: TST: Pin pytest version to 5.0.1.
+* `#14322 <https://github.com/numpy/numpy/pull/14322>`__: ENH: Enable huge pages in all Linux builds
+* `#14346 <https://github.com/numpy/numpy/pull/14346>`__: BUG: fix behavior of structured_to_unstructured on non-trivial...
+* `#14382 <https://github.com/numpy/numpy/pull/14382>`__: REL: Prepare for the NumPy 1.16.5 release.
--- a/doc/release/1.16.1-notes.rst
+++ b/doc/release/1.16.1-notes.rst
@@ -80,9 +80,9 @@ Improvements

 Further improvements to ``ctypes`` support in ``np.ctypeslib``
 --------------------------------------------------------------
-A new ``np.ctypeslib.as_ctypes_type`` function has been added, which can be
+A new `numpy.ctypeslib.as_ctypes_type` function has been added, which can be
 used to converts a `dtype` into a best-guess `ctypes` type. Thanks to this
-new function, ``np.ctypeslib.as_ctypes`` now supports a much wider range of
+new function, `numpy.ctypeslib.as_ctypes` now supports a much wider range of
 array types, including structures, booleans, and integers of non-native
 endianness.


--- a/doc/release/1.16.3-notes.rst
+++ b/doc/release/1.16.3-notes.rst
+==========================
+NumPy 1.16.3 Release Notes
+==========================
+
+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.
+
--- a/doc/release/1.16.4-notes.rst
+++ b/doc/release/1.16.4-notes.rst
+==========================
+NumPy 1.16.4 Release Notes
+==========================
+
+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 <https://github.com/numpy/numpy/pull/13392>`__: BUG: Some PyPy versions lack PyStructSequence_InitType2.
+* `#13394 <https://github.com/numpy/numpy/pull/13394>`__: MAINT, DEP: Fix deprecated ``assertEquals()``
+* `#13396 <https://github.com/numpy/numpy/pull/13396>`__: BUG: Fix structured_to_unstructured on single-field types (backport)
+* `#13549 <https://github.com/numpy/numpy/pull/13549>`__: BLD: Make CI pass again with pytest 4.5
+* `#13552 <https://github.com/numpy/numpy/pull/13552>`__: TST: Register markers in conftest.py.
+* `#13559 <https://github.com/numpy/numpy/pull/13559>`__: BUG: Removes ValueError for empty kwargs in arraymultiter_new
+* `#13560 <https://github.com/numpy/numpy/pull/13560>`__: BUG: Add TypeError to accepted exceptions in crackfortran.
+* `#13561 <https://github.com/numpy/numpy/pull/13561>`__: BUG: Handle subarrays in descr_to_dtype
+* `#13562 <https://github.com/numpy/numpy/pull/13562>`__: BUG: Protect generators from log(0.0)
+* `#13563 <https://github.com/numpy/numpy/pull/13563>`__: BUG: Always return views from structured_to_unstructured when...
+* `#13564 <https://github.com/numpy/numpy/pull/13564>`__: BUG: Catch stderr when checking compiler version
+* `#13565 <https://github.com/numpy/numpy/pull/13565>`__: BUG: longdouble(int) does not work
+* `#13587 <https://github.com/numpy/numpy/pull/13587>`__: BUG: distutils/system_info.py fix missing subprocess import (#13523)
+* `#13620 <https://github.com/numpy/numpy/pull/13620>`__: BUG,DEP: Fix writeable flag setting for arrays without base
+* `#13641 <https://github.com/numpy/numpy/pull/13641>`__: MAINT: Prepare for the 1.16.4 release.
+* `#13644 <https://github.com/numpy/numpy/pull/13644>`__: BUG: special case object arrays when printing rel-, abs-error
--- a/doc/release/1.16.5-notes.rst
+++ b/doc/release/1.16.5-notes.rst
+==========================
+NumPy 1.16.5 Release Notes
+==========================
+
+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 <https://github.com/numpy/numpy/pull/13742>`__: ENH: Add project URLs to setup.py
+* `#13823 <https://github.com/numpy/numpy/pull/13823>`__: TEST, ENH: fix tests and ctypes code for PyPy
+* `#13845 <https://github.com/numpy/numpy/pull/13845>`__: BUG: use npy_intp instead of int for indexing array
+* `#13867 <https://github.com/numpy/numpy/pull/13867>`__: TST: Ignore DeprecationWarning during nose imports
+* `#13905 <https://github.com/numpy/numpy/pull/13905>`__: BUG: Fix use-after-free in boolean indexing
+* `#13933 <https://github.com/numpy/numpy/pull/13933>`__: MAINT/BUG/DOC: Fix errors in _add_newdocs
+* `#13984 <https://github.com/numpy/numpy/pull/13984>`__: BUG: fix byte order reversal for datetime64[ns]
+* `#13994 <https://github.com/numpy/numpy/pull/13994>`__: MAINT,BUG: Use nbytes to also catch empty descr during allocation
+* `#14042 <https://github.com/numpy/numpy/pull/14042>`__: BUG: np.array cleared errors occured in PyMemoryView_FromObject
+* `#14043 <https://github.com/numpy/numpy/pull/14043>`__: BUG: Fixes for Undefined Behavior Sanitizer (UBSan) errors.
+* `#14044 <https://github.com/numpy/numpy/pull/14044>`__: BUG: ensure that casting to/from structured is properly checked.
+* `#14045 <https://github.com/numpy/numpy/pull/14045>`__: MAINT: fix histogram*d dispatchers
+* `#14046 <https://github.com/numpy/numpy/pull/14046>`__: BUG: further fixup to histogram2d dispatcher.
+* `#14052 <https://github.com/numpy/numpy/pull/14052>`__: BUG: Replace contextlib.suppress for Python 2.7
+* `#14056 <https://github.com/numpy/numpy/pull/14056>`__: BUG: fix compilation of 3rd party modules with Py_LIMITED_API...
+* `#14057 <https://github.com/numpy/numpy/pull/14057>`__: BUG: Fix memory leak in dtype from dict contructor
+* `#14058 <https://github.com/numpy/numpy/pull/14058>`__: DOC: Document array_function at a higher level.
+* `#14084 <https://github.com/numpy/numpy/pull/14084>`__: BUG, DOC: add new recfunctions to `__all__`
+* `#14162 <https://github.com/numpy/numpy/pull/14162>`__: BUG: Remove stray print that causes a SystemError on python 3.7
+* `#14297 <https://github.com/numpy/numpy/pull/14297>`__: TST: Pin pytest version to 5.0.1.
+* `#14322 <https://github.com/numpy/numpy/pull/14322>`__: ENH: Enable huge pages in all Linux builds
+* `#14346 <https://github.com/numpy/numpy/pull/14346>`__: BUG: fix behavior of structured_to_unstructured on non-trivial...
+* `#14382 <https://github.com/numpy/numpy/pull/14382>`__: REL: Prepare for the NumPy 1.16.5 release.
--- a/doc/scipy-sphinx-theme/_theme/scipy/layout.html
+++ b/doc/scipy-sphinx-theme/_theme/scipy/layout.html
@@ -121,7 +121,9 @@
    {%- endblock %}
    {{ css() }}
    {%- if not embedded %}
+    {%- block scripts %}
    {{ script() }}
+    {%- endblock %}
    {%- if use_opensearch %}
    <link rel="search" type="application/opensearchdescription+xml"
          title="{% trans docstitle=docstitle|e %}Search within {{ docstitle }}{% endtrans %}"

--- a/doc/source/reference/arrays.classes.rst
+++ b/doc/source/reference/arrays.classes.rst
@@ -6,8 +6,15 @@ Standard array subclasses

 .. currentmodule:: numpy

-The :class:`ndarray` in NumPy is a "new-style" Python
-built-in-type. Therefore, it can be inherited from (in Python or in C)
+.. note::
+
+    Subclassing a ``numpy.ndarray`` is possible but if your goal is to create
+    an array with *modified* behavior, as do dask arrays for distributed
+    computation and cupy arrays for GPU-based computation, subclassing is
+    discouraged. Instead, using numpy's
+    :ref:`dispatch mechanism <basics.dispatch>` is recommended.
+
+The :class:`ndarray` can be inherited from (in Python or in C)
 if desired. Therefore, it can form a foundation for many useful
 classes. Often whether to sub-class the array object or to simply use
 the core array component as an internal part of a new class is a
@@ -151,6 +158,121 @@ NumPy provides several hooks that classes can customize:
      :func:`__array_prepare__`, :data:`__array_priority__` mechanism
      described below for ufuncs (which may eventually be deprecated).

+.. py:method:: class.__array_function__(func, types, args, kwargs)
+
+   .. versionadded:: 1.16
+
+   .. note::
+
+       - In NumPy 1.17, the protocol is enabled by default, but can be disabled
+         with ``NUMPY_EXPERIMENTAL_ARRAY_FUNCTION=0``.
+       - In NumPy 1.16, you need to set the environment variable
+         ``NUMPY_EXPERIMENTAL_ARRAY_FUNCTION=1`` before importing NumPy to use
+         NumPy function overrides.
+       - Eventually, expect to ``__array_function__`` to always be enabled.
+
+   -  ``func`` is an arbitrary callable exposed by NumPy's public API,
+      which was called in the form ``func(*args, **kwargs)``.
+   -  ``types`` is a `collection <collections.abc.Collection>`_
+      of unique argument types from the original NumPy function call that
+      implement ``__array_function__``.
+   -  The tuple ``args`` and dict ``kwargs`` are directly passed on from the
+      original call.
+
+   As a convenience for ``__array_function__`` implementors, ``types``
+   provides all argument types with an ``'__array_function__'`` attribute.
+   This allows implementors to quickly identify cases where they should defer
+   to ``__array_function__`` implementations on other arguments.
+   Implementations should not rely on the iteration order of ``types``.
+
+   Most implementations of ``__array_function__`` will start with two
+   checks:
+
+   1.  Is the given function something that we know how to overload?
+   2.  Are all arguments of a type that we know how to handle?
+
+   If these conditions hold, ``__array_function__`` should return the result
+   from calling its implementation for ``func(*args, **kwargs)``.  Otherwise,
+   it should return the sentinel value ``NotImplemented``, indicating that the
+   function is not implemented by these types.
+
+   There are no general requirements on the return value from
+   ``__array_function__``, although most sensible implementations should
+   probably return array(s) with the same type as one of the function's
+   arguments.
+
+   It may also be convenient to define a custom decorators (``implements``
+   below) for registering ``__array_function__`` implementations.
+
+   .. code:: python
+
+       HANDLED_FUNCTIONS = {}
+
+       class MyArray:
+           def __array_function__(self, func, types, args, kwargs):
+               if func not in HANDLED_FUNCTIONS:
+                   return NotImplemented
+               # Note: this allows subclasses that don't override
+               # __array_function__ to handle MyArray objects
+               if not all(issubclass(t, MyArray) for t in types):
+                   return NotImplemented
+               return HANDLED_FUNCTIONS[func](*args, **kwargs)
+
+       def implements(numpy_function):
+           """Register an __array_function__ implementation for MyArray objects."""
+           def decorator(func):
+               HANDLED_FUNCTIONS[numpy_function] = func
+               return func
+           return decorator
+
+       @implements(np.concatenate)
+       def concatenate(arrays, axis=0, out=None):
+           ...  # implementation of concatenate for MyArray objects
+
+       @implements(np.broadcast_to)
+       def broadcast_to(array, shape):
+           ...  # implementation of broadcast_to for MyArray objects
+
+   Note that it is not required for ``__array_function__`` implementations to
+   include *all* of the corresponding NumPy function's optional arguments
+   (e.g., ``broadcast_to`` above omits the irrelevant ``subok`` argument).
+   Optional arguments are only passed in to ``__array_function__`` if they
+   were explicitly used in the NumPy function call.
+
+   Just like the case for builtin special methods like ``__add__``, properly
+   written ``__array_function__`` methods should always return
+   ``NotImplemented`` when an unknown type is encountered. Otherwise, it will
+   be impossible to correctly override NumPy functions from another object
+   if the operation also includes one of your objects.
+
+   For the most part, the rules for dispatch with ``__array_function__``
+   match those for ``__array_ufunc__``. In particular:
+
+   -  NumPy will gather implementations of ``__array_function__`` from all
+      specified inputs and call them in order: subclasses before
+      superclasses, and otherwise left to right. Note that in some edge cases
+      involving subclasses, this differs slightly from the
+      `current behavior <https://bugs.python.org/issue30140>`_ of Python.
+   -  Implementations of ``__array_function__`` indicate that they can
+      handle the operation by returning any value other than
+      ``NotImplemented``.
+   -  If all ``__array_function__`` methods return ``NotImplemented``,
+      NumPy will raise ``TypeError``.
+
+   If no ``__array_function__`` methods exists, NumPy will default to calling
+   its own implementation, intended for use on NumPy arrays. This case arises,
+   for example, when all array-like arguments are Python numbers or lists.
+   (NumPy arrays do have a ``__array_function__`` method, given below, but it
+   always returns ``NotImplemented`` if any argument other than a NumPy array
+   subclass implements ``__array_function__``.)
+
+   One deviation from the current behavior of ``__array_ufunc__`` is that
+   NumPy will only call ``__array_function__`` on the *first* argument of each
+   unique type. This matches Python's `rule for calling reflected methods
+   <https://docs.python.org/3/reference/datamodel.html#object.__ror__>`_, and
+   this ensures that checking overloads has acceptable performance even when
+   there are a large number of overloaded arguments.
+
 .. py:method:: class.__array_finalize__(obj)

   This method is called whenever the system internally allocates a

--- a/doc/source/reference/routines.ctypeslib.rst
+++ b/doc/source/reference/routines.ctypeslib.rst
@@ -8,6 +8,7 @@ C-Types Foreign Function Interface (:mod:`numpy.ctypeslib`)

 .. autofunction:: as_array
 .. autofunction:: as_ctypes
+.. autofunction:: as_ctypes_type
 .. autofunction:: ctypes_load_library
 .. autofunction:: load_library
 .. autofunction:: ndpointer
--- a/doc/source/release.rst
+++ b/doc/source/release.rst
@@ -2,6 +2,10 @@
 Release Notes
 *************

+.. include:: ../release/1.16.5-notes.rst
+.. include:: ../release/1.16.4-notes.rst
+.. include:: ../release/1.16.3-notes.rst
+.. include:: ../release/1.16.2-notes.rst
 .. include:: ../release/1.16.1-notes.rst
 .. include:: ../release/1.16.0-notes.rst
 .. include:: ../release/1.15.4-notes.rst

--- a/doc/source/user/basics.dispatch.rst
+++ b/doc/source/user/basics.dispatch.rst
+.. _basics.dispatch:
+
+*******************************
+Writing custom array containers
+*******************************
+
+.. automodule:: numpy.doc.dispatch
+
--- a/doc/source/user/basics.rst
+++ b/doc/source/user/basics.rst
@@ -12,4 +12,5 @@ NumPy basics
   basics.broadcasting
   basics.byteswapping
   basics.rec
+   basics.dispatch
   basics.subclassing
--- a/doc/sphinxext/.travis.yml
+++ b/doc/sphinxext/.travis.yml
@@ -17,13 +17,13 @@ cache:
 before_install:
  - sudo apt-get install texlive texlive-latex-extra latexmk
  - pip install --upgrade pip setuptools  # Upgrade pip and setuptools to get ones with `wheel` support
-  - pip install --find-links http://wheels.astropy.org/ --find-links http://wheels2.astropy.org/ --trusted-host wheels.astropy.org --trusted-host wheels2.astropy.org --use-wheel nose numpy matplotlib ${SPHINX_SPEC}
+  - pip install pytest numpy matplotlib ${SPHINX_SPEC}
 script:
  - |
    python setup.py sdist
    cd dist
    pip install numpydoc* -v
-  - nosetests numpydoc
+  - pytest --pyargs numpydoc
  - |
    cd ../doc
    make SPHINXOPTS=$SPHINXOPTS html

--- a/doc/sphinxext/doc/example.py
+++ b/doc/sphinxext/doc/example.py
@@ -93,7 +93,7 @@ def foo(var1, var2, long_var_name='hi'):

    .. math:: X(e^{j\omega } ) = x(n)e^{ - j\omega n}

-    And even use a greek symbol like :math:`omega` inline.
+    And even use a Greek symbol like :math:`\omega` inline.

    References
    ----------

--- a/doc/sphinxext/doc/format.rst
+++ b/doc/sphinxext/doc/format.rst
@@ -119,6 +119,8 @@ The sections of a function's docstring are:

     """

+.. highlight:: rst
+
 2. **Deprecation warning**

   A section (use if applicable) to warn users that the object is deprecated.
@@ -250,13 +252,21 @@ The sections of a function's docstring are:
   Support for the **Yields** section was added in `numpydoc
   <https://github.com/numpy/numpydoc>`_ version 0.6.

-7. **Other Parameters**
+7. **Receives**
+
+   Explanation of parameters passed to a generator's ``.send()`` method,
+   formatted as for Parameters, above.  Since, like for Yields and Returns, a
+   single object is always passed to the method, this may describe either the
+   single parameter, or positional arguments passed as a tuple.  If a docstring
+   includes Receives it must also include Yields.
+
+8. **Other Parameters**

   An optional section used to describe infrequently used parameters.
   It should only be used if a function has a large number of keyword
   parameters, to prevent cluttering the **Parameters** section.

-8. **Raises**
+9. **Raises**

   An optional section detailing which errors get raised and under
   what conditions::
@@ -269,55 +279,55 @@ The sections of a function's docstring are:
   This section should be used judiciously, i.e., only for errors
   that are non-obvious or have a large chance of getting raised.

-9. **Warns**
+10. **Warns**

   An optional section detailing which warnings get raised and
   under what conditions, formatted similarly to Raises.

-10. **Warnings**
+11. **Warnings**

-   An optional section with cautions to the user in free text/reST.
+    An optional section with cautions to the user in free text/reST.

-11. **See Also**
+12. **See Also**

-   An optional section used to refer to related code.  This section
-   can be very useful, but should be used judiciously.  The goal is to
-   direct users to other functions they may not be aware of, or have
-   easy means of discovering (by looking at the module docstring, for
-   example).  Routines whose docstrings further explain parameters
-   used by this function are good candidates.
+    An optional section used to refer to related code.  This section
+    can be very useful, but should be used judiciously.  The goal is to
+    direct users to other functions they may not be aware of, or have
+    easy means of discovering (by looking at the module docstring, for
+    example).  Routines whose docstrings further explain parameters
+    used by this function are good candidates.

-   As an example, for ``numpy.mean`` we would have::
+    As an example, for ``numpy.mean`` we would have::

-     See Also
-     --------
-     average : Weighted average
+      See Also
+      --------
+      average : Weighted average

-   When referring to functions in the same sub-module, no prefix is
-   needed, and the tree is searched upwards for a match.
+    When referring to functions in the same sub-module, no prefix is
+    needed, and the tree is searched upwards for a match.

-   Prefix functions from other sub-modules appropriately.  E.g.,
-   whilst documenting the ``random`` module, refer to a function in
-   ``fft`` by
+    Prefix functions from other sub-modules appropriately.  E.g.,
+    whilst documenting the ``random`` module, refer to a function in
+    ``fft`` by

-   ::
+    ::

-     fft.fft2 : 2-D fast discrete Fourier transform
+      fft.fft2 : 2-D fast discrete Fourier transform

-   When referring to an entirely different module::
+    When referring to an entirely different module::

-     scipy.random.norm : Random variates, PDFs, etc.
+      scipy.random.norm : Random variates, PDFs, etc.

-   Functions may be listed without descriptions, and this is
-   preferable if the functionality is clear from the function name::
+    Functions may be listed without descriptions, and this is
+    preferable if the functionality is clear from the function name::

-     See Also
-     --------
-     func_a : Function a with its description.
-     func_b, func_c_, func_d
-     func_e
+      See Also
+      --------
+      func_a : Function a with its description.
+      func_b, func_c_, func_d
+      func_e

-12. **Notes**
+13. **Notes**

    An optional section that provides additional information about the
    code, possibly including a discussion of the algorithm. This
@@ -362,7 +372,7 @@ The sections of a function's docstring are:
    where filename is a path relative to the reference guide source
    directory.

-13. **References**
+14. **References**

    References cited in the **notes** section may be listed here,
    e.g. if you cited the article below using the text ``[1]_``,
@@ -393,7 +403,9 @@ The sections of a function's docstring are:
        docstring, the table markup will be broken by numpydoc processing.  See
        `numpydoc issue #130 <https://github.com/numpy/numpydoc/issues/130>`_

-14. **Examples**
+.. highlight:: pycon
+
+15. **Examples**

    An optional section for examples, using the `doctest
    <http://docs.python.org/library/doctest.html>`_ format.
@@ -413,6 +425,14 @@ The sections of a function's docstring are:
      >>> np.add([1, 2], [3, 4])
      array([4, 6])

+    The example code may be split across multiple lines, with each line after
+    the first starting with '... '::
+
+      >>> np.add([[1, 2], [3, 4]],
+      ...        [[5, 6], [7, 8]])
+      array([[ 6,  8],
+             [10, 12]])
+
    For tests with a result that is random or platform-dependent, mark the
    output as such::

@@ -456,6 +476,7 @@ The sections of a function's docstring are:
    `matplotlib.sphinxext.plot_directive` is loaded as a Sphinx extension in
    ``conf.py``.

+.. highlight:: rst

 Documenting classes
 -------------------
@@ -493,7 +514,9 @@ In general, it is not necessary to list class methods.  Those that are
 not part of the public API have names that start with an underscore.
 In some cases, however, a class may have a great many methods, of
 which only a few are relevant (e.g., subclasses of ndarray).  Then, it
-becomes useful to have an additional **Methods** section::
+becomes useful to have an additional **Methods** section:
+
+.. code-block:: python

  class Photo(ndarray):
      """

--- a/doc/sphinxext/doc/index.rst
+++ b/doc/sphinxext/doc/index.rst
@@ -22,3 +22,4 @@ Documentation
    install
    format
    example
+    validation
--- a/doc/sphinxext/doc/validation.rst
+++ b/doc/sphinxext/doc/validation.rst
+==============================
+Validating NumpyDoc docstrings
+==============================
+
+One tool for validating docstrings is to see how an object's dosctring
+translates to Restructured Text.  Using numpydoc as a command-line tool
+facilitates this. For example to see the Restructured Text generated
+for ``numpy.ndarray``, use:
+
+.. code-block:: bash
+
+    $ python -m numpydoc numpy.ndarray