==========================
NumPy 1.16.1 Release Notes
==========================

The NumPy 1.16.1 release fixes bugs reported against the 1.16.0 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.

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. Note that previously this problem resulted in an ``AttributeError``.


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

A total of 16 people contributed to this release.  People with a "+" by their
names contributed a patch for the first time.

* Antoine Pitrou
* Arcesio Castaneda Medina +
* Charles Harris
* Chris Markiewicz +
* Christoph Gohlke
* Christopher J. Markiewicz +
* Daniel Hrisca +
* EelcoPeacs +
* Eric Wieser
* Kevin Sheppard
* Matti Picus
* OBATA Akio +
* Ralf Gommers
* Sebastian Berg
* Stephan Hoyer
* Tyler Reddy


Enhancements
============

* `#12767 <https://github.com/numpy/numpy/pull/12767>`__: ENH: add mm->q floordiv
* `#12768 <https://github.com/numpy/numpy/pull/12768>`__: ENH: port np.core.overrides to C for speed
* `#12769 <https://github.com/numpy/numpy/pull/12769>`__: ENH: Add np.ctypeslib.as_ctypes_type(dtype), improve `np.ctypeslib.as_ctypes`
* `#12773 <https://github.com/numpy/numpy/pull/12773>`__: ENH: add "max difference" messages to np.testing.assert_array_equal...
* `#12820 <https://github.com/numpy/numpy/pull/12820>`__: ENH: Add mm->qm divmod
* `#12890 <https://github.com/numpy/numpy/pull/12890>`__: ENH: add _dtype_ctype to namespace for freeze analysis


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

* The changed error message emited by array comparison testing functions may
  affect doctests. See below for detail.

* Casting from double and single denormals to float16 has been corrected.  In
  some rare cases, this may result in results being rounded up instead of down,
  changing the last bit (ULP) of the result.


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

divmod operation is now supported for two ``timedelta64`` operands
------------------------------------------------------------------
The divmod operator now handles two ``np.timedelta64`` operands, with
type signature ``mm->qm``.


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

Further improvements to ``ctypes`` support in ``np.ctypeslib``
--------------------------------------------------------------
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, `numpy.ctypeslib.as_ctypes` now supports a much wider range of
array types, including structures, booleans, and integers of non-native
endianness.

Array comparison assertions include maximum differences
-------------------------------------------------------
Error messages from array comparison tests such as
`np.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.


Changes
=======

``timedelta64 % 0`` behavior adjusted to return ``NaT``
-------------------------------------------------------
The modulus operation with two ``np.timedelta64`` operands now returns
``NaT`` in the case of division by zero, rather than returning zero



