Imported Upstream version 1.16.0upstream/1.16.0

10 files changed, 597 insertions, 27 deletions

diff --git a/doc/release/1.13.0-notes.rst b/doc/release/1.13.0-notes.rst
index 4554e53ea..3b719db09 100644
--- a/doc/release/1.13.0-notes.rst
+++ b/doc/release/1.13.0-notes.rst
@@ -183,11 +183,11 @@ override the behavior of NumPy's ufuncs. This works quite similarly to Python's
 ``__mul__`` and other binary operation routines. See the documentation for a
 more detailed description of the implementation and behavior of this new
 option. The API is provisional, we do not yet guarantee backward compatibility
-as modifications may be made pending feedback. See the NEP_ and
+as modifications may be made pending feedback. See `NEP 13`_  and
 documentation_ for more details.
 
-.. _NEP: https://github.com/numpy/numpy/blob/master/doc/neps/ufunc-overrides.rst
-.. _documentation: https://github.com/charris/numpy/blob/master/doc/source/reference/arrays.classes.rst
+.. _`NEP 13`: http://www.numpy.org/neps/nep-0013-ufunc-overrides.html
+.. _documentation: https://github.com/numpy/numpy/blob/master/doc/source/reference/arrays.classes.rst
 
 New ``positive`` ufunc
 ----------------------
diff --git a/doc/release/1.13.1-notes.rst b/doc/release/1.13.1-notes.rst
index 807296a85..88a4bc3dd 100644
--- a/doc/release/1.13.1-notes.rst
+++ b/doc/release/1.13.1-notes.rst
@@ -13,7 +13,7 @@ used with 3.6.0 due to Python bug 29943_. NumPy 1.13.2 will be released shortly
 after Python 3.6.2 is out to fix that problem. If you are using 3.6.0 the
 workaround is to upgrade to 3.6.1 or use an earlier Python version.
 
-.. _#29943: https://bugs.python.org/issue29943
+.. _29943: https://bugs.python.org/issue29943
 
 
 Pull requests merged
@@ -21,7 +21,7 @@ Pull requests merged
 A total of 19 pull requests were merged for this release.
 
 * #9240 DOC: BLD: fix lots of Sphinx warnings/errors.
-* #9255 Revert "DEP: Raise TypeError for subtract(bool_, bool_)."
+* #9255 Revert "DEP: Raise TypeError for subtract(bool, bool)."
 * #9261 BUG: don't elide into readonly and updateifcopy temporaries for...
 * #9262 BUG: fix missing keyword rename for common block in numpy.f2py
 * #9263 BUG: handle resize of 0d array
diff --git a/doc/release/1.14.0-notes.rst b/doc/release/1.14.0-notes.rst
index 0f14f7703..462631de6 100644
--- a/doc/release/1.14.0-notes.rst
+++ b/doc/release/1.14.0-notes.rst
@@ -14,11 +14,11 @@ dropping Python 2.7 support in the runup to 2020. The decision has been made to
 support 2.7 for all releases made in 2018, with the last release being
 designated a long term release with support for bug fixes extending through
 2019. In 2019 support for 2.7 will be dropped in all new releases. More details
-can be found in the relevant NEP_.
+can be found in `NEP 12`_.
 
 This release supports Python 2.7 and 3.4 - 3.6.
 
-.. _NEP: https://github.com/numpy/numpy/blob/master/doc/neps/dropping-python2.7-proposal.rst
+.. _`NEP 12`: http://www.numpy.org/neps/nep-0014-dropping-python2.7-proposal.html
 
 
 Highlights
@@ -134,8 +134,8 @@ are marked readonly. In the past, it was possible to get away with::
     var_arr = np.asarray(val)
     val_arr += 1  # now errors, previously changed np.ma.masked.data
 
-``np.ma`` functions producing ``fill_value``s have changed
-----------------------------------------------------------
+``np.ma`` functions producing ``fill_value`` s have changed
+-----------------------------------------------------------
 Previously, ``np.ma.default_fill_value`` would return a 0d array, but
 ``np.ma.minimum_fill_value`` and ``np.ma.maximum_fill_value`` would return a
 tuple of the fields. Instead, all three methods return a structured ``np.void``
diff --git a/doc/release/1.14.1-notes.rst b/doc/release/1.14.1-notes.rst
index 2ed4c3e14..7b95c2e28 100644
--- a/doc/release/1.14.1-notes.rst
+++ b/doc/release/1.14.1-notes.rst
@@ -67,7 +67,7 @@ A total of 36 pull requests were merged for this release.
 * `#10431 <https://github.com/numpy/numpy/pull/10431>`__: REL: Add 1.14.1 release notes template
 * `#10435 <https://github.com/numpy/numpy/pull/10435>`__: MAINT: Use ValueError for duplicate field names in lookup (backport)
 * `#10534 <https://github.com/numpy/numpy/pull/10534>`__: BUG: Provide a better error message for out-of-order fields
-* `#10536 <https://github.com/numpy/numpy/pull/10536>`__: BUG: Resize bytes_ columns in genfromtxt (backport of #10401)
+* `#10536 <https://github.com/numpy/numpy/pull/10536>`__: BUG: Resize bytes columns in genfromtxt (backport of #10401)
 * `#10537 <https://github.com/numpy/numpy/pull/10537>`__: BUG: multifield-indexing adds padding bytes: revert for 1.14.1
 * `#10539 <https://github.com/numpy/numpy/pull/10539>`__: BUG: fix np.save issue with python 2.7.5
 * `#10540 <https://github.com/numpy/numpy/pull/10540>`__: BUG: Add missing DECREF in Py2 int() cast
diff --git a/doc/release/1.15.0-notes.rst b/doc/release/1.15.0-notes.rst
index 0e3d2a525..7235ca915 100644
--- a/doc/release/1.15.0-notes.rst
+++ b/doc/release/1.15.0-notes.rst
@@ -99,7 +99,7 @@ Deprecations
 * Users of ``nditer`` should use the nditer object as a context manager
   anytime one of the iterator operands is writeable, so that numpy can
   manage writeback semantics, or should call ``it.close()``. A
- `RuntimeWarning` may be emitted otherwise in these cases.
+  `RuntimeWarning` may be emitted otherwise in these cases.
 
 * The ``normed`` argument of ``np.histogram``, deprecated long ago in 1.6.0,
   now emits a ``DeprecationWarning``.
@@ -227,13 +227,6 @@ Changes to ``PyArray_GetDTypeTransferFunction``
 significant performance hit, consider implementing ``copyswapn`` to reflect the
 implementation of ``PyArray_GetStridedCopyFn``.  See `#10898
 <https://github.com/numpy/numpy/pull/10898>`__.
-* Functions ``npy_get_floatstatus_barrier`` and ``npy_clear_floatstatus_barrier``
-  have been added and should be used in place of the ``npy_get_floatstatus``and
-  ``npy_clear_status`` functions. Optimizing compilers like GCC 8.1 and Clang
-  were rearranging the order of operations when the previous functions were
-  used in the ufunc SIMD functions, resulting in the floatstatus flags being '
-  checked before the operation whose status we wanted to check was run.
-  See `#10339 <https://github.com/numpy/numpy/issues/10370>`__.
 
 
 New Features
diff --git a/doc/release/1.16.0-notes.rst b/doc/release/1.16.0-notes.rst
new file mode 100644
index 000000000..de636933f
--- /dev/null
+++ b/doc/release/1.16.0-notes.rst
@@ -0,0 +1,534 @@
+==========================
+NumPy 1.16.0 Release Notes
+==========================
+
+This NumPy release is the last one to support Python 2.7 and will be maintained
+as a long term release with bug fixes until 2020.  Support for Python 3.4 been
+dropped, the supported Python versions are 2.7 and 3.5-3.7. 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 and, if
+using OpenBLAS, OpenBLAS > v0.3.4.
+
+This release has seen a lot of refactoring and features many bug fixes, improved
+code organization, and better cross platform compatibility. Not all of these
+improvements will be visible to users, but they should help make maintenance
+easier going forward.
+
+
+Highlights
+==========
+
+* Experimental support for overriding numpy functions,
+  see ``__array_function__`` below.
+
+* The ``matmul`` function is now a ufunc. This provides better
+  performance and allows overriding with ``__array_ufunc__``.
+
+* Improved support for the ARM and POWER architectures.
+
+* Improved support for AIX and PyPy.
+
+* Improved interop with ctypes.
+
+* Improved support for PEP 3118.
+
+
+
+New functions
+=============
+
+* New functions added to the `numpy.lib.recfuntions` module to ease the
+  structured assignment changes:
+
+    * ``assign_fields_by_name``
+    * ``structured_to_unstructured``
+    * ``unstructured_to_structured``
+    * ``apply_along_fields``
+    * ``require_fields``
+
+  See the user guide at <https://docs.scipy.org/doc/numpy/user/basics.rec.html>
+  for more info.
+
+
+New deprecations
+================
+
+* The type dictionaries `numpy.core.typeNA` and `numpy.core.sctypeNA` are
+  deprecated. They were buggy and not documented and will be removed in the
+  1.18 release. Use`numpy.sctypeDict` instead.
+
+* The `numpy.asscalar` function is deprecated. It is an alias to the more
+  powerful `numpy.ndarray.item`, not tested, and fails for scalars.
+
+* The `numpy.set_array_ops` and `numpy.get_array_ops` functions are deprecated.
+  As part of `NEP 15`, they have been deprecated along with the C-API functions
+  :c:func:`PyArray_SetNumericOps` and :c:func:`PyArray_GetNumericOps`. Users
+  who wish to override the inner loop functions in built-in ufuncs should use
+  :c:func:`PyUFunc_ReplaceLoopBySignature`.
+
+* The `numpy.unravel_index` keyword argument ``dims`` is deprecated, use
+  ``shape`` instead.
+
+* The `numpy.histogram` ``normed`` argument is deprecated.  It was deprecated
+  previously, but no warning was issued.
+
+* The ``positive`` operator (``+``) applied to non-numerical arrays is
+  deprecated. See below for details.
+
+* Passing an iterator to the stack functions is deprecated
+
+
+Expired deprecations
+====================
+
+* NaT comparisons now return ``False`` without a warning, finishing a
+  deprecation cycle begun in NumPy 1.11.
+
+* ``np.lib.function_base.unique`` was removed, finishing a deprecation cycle
+  begun in NumPy 1.4. Use `numpy.unique` instead.
+
+* multi-field indexing now returns views instead of copies, finishing a
+  deprecation cycle begun in NumPy 1.7. The change was previously attempted in
+  NumPy 1.14 but reverted until now.
+
+* ``np.PackageLoader`` and ``np.pkgload`` have been removed. These were
+  deprecated in 1.10, had no tests, and seem to no longer work in 1.15.
+
+
+Future changes
+==============
+
+* NumPy 1.17 will drop support for Python 2.7.
+
+
+Compatibility notes
+===================
+
+f2py script on Windows
+----------------------
+On Windows, the installed script for running f2py is now an ``.exe`` file
+rather than a ``*.py`` file and should be run from the command line as ``f2py``
+whenever the ``Scripts`` directory is in the path. Running ``f2py`` as a module
+``python -m numpy.f2py [...]`` will work without path modification in any
+version of NumPy.
+
+NaT comparisons
+---------------
+Consistent with the behavior of NaN, all comparisons other than inequality
+checks with datetime64 or timedelta64 NaT ("not-a-time") values now always
+return ``False``, and inequality checks with NaT now always return ``True``.
+This includes comparisons beteween NaT values. For compatibility with the
+old behavior, use ``np.isnat`` to explicitly check for NaT or convert
+datetime64/timedelta64 arrays with ``.astype(np.int64)`` before making
+comparisons.
+
+complex64/128 alignment has changed
+-----------------------------------
+The memory alignment of complex types is now the same as a C-struct composed of
+two floating point values, while before it was equal to the size of the type.
+For many users (for instance on x64/unix/gcc) this means that complex64 is now
+4-byte aligned instead of 8-byte aligned. An important consequence is that
+aligned structured dtypes may now have a different size. For instance,
+``np.dtype('c8,u1', align=True)`` used to have an itemsize of 16 (on x64/gcc)
+but now it is 12.
+
+More in detail, the complex64 type now has the same alignment as a C-struct
+``struct {float r, i;}``, according to the compiler used to compile numpy, and
+similarly for the complex128 and complex256 types.
+
+nd_grid __len__ removal
+-----------------------
+``len(np.mgrid)`` and ``len(np.ogrid)`` are now considered nonsensical
+and raise a ``TypeError``.
+
+``np.unravel_index`` now accepts ``shape`` keyword argument
+-----------------------------------------------------------
+Previously, only the ``dims`` keyword argument was accepted
+for specification of the shape of the array to be used
+for unraveling. ``dims`` remains supported, but is now deprecated.
+
+multi-field views return a view instead of a copy
+-------------------------------------------------
+Indexing a structured array with multiple fields, e.g., ``arr[['f1', 'f3']]``,
+returns a view into the original array instead of a copy. The returned view
+will often have extra padding bytes corresponding to intervening fields in the
+original array, unlike before, which will affect code such as
+``arr[['f1', 'f3']].view('float64')``. This change has been planned since numpy
+1.7. Operations hitting this path have emitted ``FutureWarnings`` since then.
+Additional ``FutureWarnings`` about this change were added in 1.12.
+
+To help users update their code to account for these changes, a number of
+functions have been added to the ``numpy.lib.recfunctions`` module which
+safely allow such operations. For instance, the code above can be replaced
+with ``structured_to_unstructured(arr[['f1', 'f3']], dtype='float64')``.
+See the "accessing multiple fields" section of the
+`user guide <https://docs.scipy.org/doc/numpy/user/basics.rec.html#accessing-multiple-fields>`__.
+
+
+C API changes
+=============
+
+The :c:data:`NPY_API_VERSION` was incremented to 0x0000D, due to the addition
+of:
+
+* :c:member:`PyUFuncObject.core_dim_flags`
+* :c:member:`PyUFuncObject.core_dim_sizes`
+* :c:member:`PyUFuncObject.identity_value`
+* :c:function:`PyUFunc_FromFuncAndDataAndSignatureAndIdentity`
+
+
+New Features
+============
+
+Integrated squared error (ISE) estimator added to ``histogram``
+---------------------------------------------------------------
+This method (``bins='stone'``) for optimizing the bin number is a
+generalization of the Scott's rule. The Scott's rule assumes the distribution
+is approximately Normal, while the ISE_ is a non-parametric method based on
+cross-validation.
+
+.. _ISE: https://en.wikipedia.org/wiki/Histogram#Minimizing_cross-validation_estimated_squared_error
+
+``max_rows`` keyword added for ``np.loadtxt``
+---------------------------------------------
+New keyword ``max_rows`` in `numpy.loadtxt` sets the maximum rows of the
+content to be read after ``skiprows``, as in `numpy.genfromtxt`.
+
+modulus operator support added for ``np.timedelta64`` operands
+--------------------------------------------------------------
+The modulus (remainder) operator is now supported for two operands
+of type ``np.timedelta64``. The operands may have different units
+and the return value will match the type of the operands.
+
+
+Improvements
+============
+
+no-copy pickling of numpy arrays
+--------------------------------
+Up to protocol 4, numpy array pickling created 2 spurious copies of the data
+being serialized.  With pickle protocol 5, and the ``PickleBuffer`` API, a
+large variety of numpy arrays can now be serialized without any copy using
+out-of-band buffers, and with one less copy using in-band buffers. This
+results, for large arrays, in an up to 66% drop in peak memory usage.
+
+build shell independence
+------------------------
+NumPy builds should no longer interact with the host machine
+shell directly. ``exec_command`` has been replaced with
+``subprocess.check_output`` where appropriate.
+
+`np.polynomial.Polynomial` classes render in LaTeX in Jupyter notebooks
+-----------------------------------------------------------------------
+When used in a front-end that supports it, `Polynomial` instances are now
+rendered through LaTeX. The current format is experimental, and is subject to
+change.
+
+``randint`` and ``choice`` now work on empty distributions
+----------------------------------------------------------
+Even when no elements needed to be drawn, ``np.random.randint`` and
+``np.random.choice`` raised an error when the arguments described an empty
+distribution. This has been fixed so that e.g.
+``np.random.choice([], 0) == np.array([], dtype=float64)``.
+
+``linalg.lstsq``, ``linalg.qr``, and ``linalg.svd`` now work with empty arrays
+------------------------------------------------------------------------------
+Previously, a ``LinAlgError`` would be raised when an empty matrix/empty
+matrices (with zero rows and/or columns) is/are passed in. Now outputs of
+appropriate shapes are returned.
+
+Chain exceptions to give better error messages for invalid PEP3118 format strings
+---------------------------------------------------------------------------------
+This should help track down problems.
+
+Einsum optimization path updates and efficiency improvements
+------------------------------------------------------------
+Einsum was synchronized with the current upstream work.
+
+`numpy.angle` and `numpy.expand_dims` now work on ``ndarray`` subclasses
+------------------------------------------------------------------------
+In particular, they now work for masked arrays.
+
+``NPY_NO_DEPRECATED_API`` compiler warning suppression
+------------------------------------------------------
+Setting ``NPY_NO_DEPRECATED_API`` to a value of 0 will suppress the current compiler
+warnings when the deprecated numpy API is used.
+
+``np.diff`` Added kwargs prepend and append
+-------------------------------------------
+New kwargs ``prepend`` and ``append``, allow for values to be inserted on
+either end of the differences.  Similar to options for `ediff1d`. Now the
+inverse of `cumsum` can be obtained easily via ``prepend=0``.
+
+ARM support updated
+-------------------
+Support for ARM CPUs has been updated to accommodate 32 and 64 bit targets,
+and also big and little endian byte ordering. AARCH32 memory alignment issues
+have been addressed. CI testing has been expanded to include AARCH64 targets
+via the services of shippable.com.
+
+Appending to build flags
+------------------------
+`numpy.distutils` has always overridden rather than appended to `LDFLAGS` and
+other similar such environment variables for compiling Fortran extensions.
+Now, if the `NPY_DISTUTILS_APPEND_FLAGS` environment variable is set to 1, the
+behavior will be appending.  This applied to: `LDFLAGS`, `F77FLAGS`,
+`F90FLAGS`, `FREEFLAGS`, `FOPT`, `FDEBUG`, and `FFLAGS`.  See gh-11525 for more
+details.
+
+Generalized ufunc signatures now allow fixed-size dimensions
+------------------------------------------------------------
+By using a numerical value in the signature of a generalized ufunc, one can
+indicate that the given function requires input or output to have dimensions
+with the given size. E.g., the signature of a function that converts a polar
+angle to a two-dimensional cartesian unit vector would be ``()->(2)``; that
+for one that converts two spherical angles to a three-dimensional unit vector
+would be ``(),()->(3)``; and that for the cross product of two
+three-dimensional vectors would be ``(3),(3)->(3)``.
+
+Note that to the elementary function these dimensions are not treated any
+differently from variable ones indicated with a name starting with a letter;
+the loop still is passed the corresponding size, but it can now count on that
+size being equal to the fixed one given in the signature.
+
+Generalized ufunc signatures now allow flexible dimensions
+----------------------------------------------------------
+Some functions, in particular numpy's implementation of ``@`` as ``matmul``,
+are very similar to generalized ufuncs in that they operate over core
+dimensions, but one could not present them as such because they were able to
+deal with inputs in which a dimension is missing. To support this, it is now
+allowed to postfix a dimension name with a question mark to indicate that the
+dimension does not necessarily have to be present.
+
+With this addition, the signature for ``matmul`` can be expressed as
+``(m?,n),(n,p?)->(m?,p?)``.  This indicates that if, e.g., the second operand
+has only one dimension, for the purposes of the elementary function it will be
+treated as if that input has core shape ``(n, 1)``, and the output has the
+corresponding core shape of ``(m, 1)``. The actual output array, however, has
+the flexible dimension removed, i.e., it will have shape ``(..., m)``.
+Similarly, if both arguments have only a single dimension, the inputs will be
+presented as having shapes ``(1, n)`` and ``(n, 1)`` to the elementary
+function, and the output as ``(1, 1)``, while the actual output array returned
+will have shape ``()``. In this way, the signature allows one to use a
+single elementary function for four related but different signatures,
+``(m,n),(n,p)->(m,p)``, ``(n),(n,p)->(p)``, ``(m,n),(n)->(m)`` and
+``(n),(n)->()``.
+
+``np.clip`` and the ``clip`` method check for memory overlap
+------------------------------------------------------------
+The ``out`` argument to these functions is now always tested for memory overlap
+to avoid corrupted results when memory overlap occurs.
+
+New value ``unscaled`` for option ``cov`` in ``np.polyfit``
+-----------------------------------------------------------
+A further possible value has been added to the ``cov`` parameter of the
+``np.polyfit`` function. With ``cov='unscaled'`` the scaling of the covariance
+matrix is disabled completely (similar to setting ``absolute_sigma=True`` in
+``scipy.optimize.curve_fit``). This would be useful in occasions, where the
+weights are given by 1/sigma with sigma being the (known) standard errors of
+(Gaussian distributed) data points, in which case the unscaled matrix is
+already a correct estimate for the covariance matrix.
+
+Detailed docstrings for scalar numeric types
+--------------------------------------------
+The ``help`` function, when applied to numeric types such as `numpy.intc`,
+`numpy.int_`, and `numpy.longlong`, now lists all of the aliased names for that
+type, distinguishing between platform -dependent and -independent aliases.
+
+``__module__`` attribute now points to public modules
+-----------------------------------------------------
+The ``__module__`` attribute on most NumPy functions has been updated to refer
+to the preferred public module from which to access a function, rather than
+the module in which the function happens to be defined. This produces more
+informative displays for functions in tools such as IPython, e.g., instead of
+``<function 'numpy.core.fromnumeric.sum'>`` you now see
+``<function 'numpy.sum'>``.
+
+Large allocations marked as suitable for transparent hugepages
+--------------------------------------------------------------
+On systems that support transparent hugepages over the madvise system call
+numpy now marks that large memory allocations can be backed by hugepages which
+reduces page fault overhead and can in some fault heavy cases improve
+performance significantly. On Linux the setting for huge pages to be used,
+`/sys/kernel/mm/transparent_hugepage/enabled`, must be at least `madvise`.
+Systems which already have it set to `always` will not see much difference as
+the kernel will automatically use huge pages where appropriate.
+
+Users of very old Linux kernels (~3.x and older) should make sure that
+`/sys/kernel/mm/transparent_hugepage/defrag` is not set to `always` to avoid
+performance problems due concurrency issues in the memory defragmentation.
+
+Alpine Linux (and other musl c library distros) support
+-------------------------------------------------------
+We now default to use `fenv.h` for floating point status error reporting.
+Previously we had a broken default that sometimes would not report underflow,
+overflow, and invalid floating point operations. Now we can support non-glibc
+distrubutions like Alpine Linux as long as they ship `fenv.h`.
+
+Speedup ``np.block`` for large arrays
+-------------------------------------
+Large arrays (greater than ``512 * 512``) now use a blocking algorithm based on
+copying the data directly into the appropriate slice of the resulting array.
+This results in significant speedups for these large arrays, particularly for
+arrays being blocked along more than 2 dimensions.
+
+``arr.ctypes.data_as(...)`` holds a reference to arr
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Previously the caller was responsible for keeping the array alive for the
+lifetime of the pointer.
+
+Speedup ``np.take`` for read-only arrays
+----------------------------------------
+The implementation of ``np.take`` no longer makes an unnecessary copy of the
+source array when its ``writeable`` flag is set to ``False``.
+
+Support path-like objects for more functions
+--------------------------------------------
+The ``np.core.records.fromfile`` function now supports ``pathlib.Path``
+and other path-like objects in addition to a file object. Furthermore, the
+``np.load`` function now also supports path-like objects when using memory
+mapping (``mmap_mode`` keyword argument).
+
+Better behaviour of ufunc identities during reductions
+------------------------------------------------------
+Universal functions have an ``.identity`` which is used when ``.reduce`` is
+called on an empty axis.
+
+As of this release, the logical binary ufuncs, `logical_and`, `logical_or`,
+and `logical_xor`, now have ``identity`` s of type `bool`, where previously they
+were of type `int`. This restores the 1.14 behavior of getting ``bool`` s when
+reducing empty object arrays with these ufuncs, while also keeping the 1.15
+behavior of getting ``int`` s when reducing empty object arrays with arithmetic
+ufuncs like ``add`` and ``multiply``.
+
+Additionally, `logaddexp` now has an identity of ``-inf``, allowing it to be
+called on empty sequences, where previously it could not be.
+
+This is possible thanks to the new
+:c:function:`PyUFunc_FromFuncAndDataAndSignatureAndIdentity`, which allows
+arbitrary values to be used as identities now.
+
+Improved conversion from ctypes objects
+---------------------------------------
+Numpy has always supported taking a value or type from ``ctypes`` and
+converting it into an array or dtype, but only behaved correctly for simpler
+types. As of this release, this caveat is lifted - now:
+
+* The ``_pack_`` attribute of ``ctypes.Structure``, used to emulate C's
+  ``__attribute__((packed))``, is respected.
+* Endianness of all ctypes objects is preserved
+* ``ctypes.Union`` is supported
+* Non-representable constructs raise exceptions, rather than producing
+  dangerously incorrect results:
+
+  * Bitfields are no longer interpreted as sub-arrays
+  * Pointers are no longer replaced with the type that they point to
+
+A new ``ndpointer.contents`` member
+-----------------------------------
+This matches the ``.contents`` member of normal ctypes arrays, and can be used
+to construct an ``np.array`` around the pointers contents.  This replaces
+``np.array(some_nd_pointer)``, which stopped working in 1.15.  As a side effect
+of this change, ``ndpointer`` now supports dtypes with overlapping fields and
+padding.
+
+``matmul`` is now a ``ufunc``
+-----------------------------
+`numpy.matmul` is now a ufunc which means that both the function and the
+``__matmul__`` operator can now be overridden by ``__array_ufunc__``. Its
+implementation has also changed. It uses the same BLAS routines as
+`numpy.dot`, ensuring its performance is similar for large matrices.
+
+Start and stop arrays for ``linspace``, ``logspace`` and ``geomspace``
+----------------------------------------------------------------------
+These functions used to be limited to scalar stop and start values, but can
+now take arrays, which will be properly broadcast and result in an output
+which has one axis prepended.  This can be used, e.g., to obtain linearly
+interpolated points between sets of points.
+
+CI extended with additional services
+------------------------------------
+We now use additional free CI services, thanks to the companies that provide:
+
+* Codecoverage testing via codecov.io
+* Arm testing via shippable.com
+* Additional test runs on azure pipelines
+
+These are in addition to our continued use of travis, appveyor (for wheels) and
+LGTM
+
+
+Changes
+=======
+
+Comparison ufuncs will now error rather than return NotImplemented
+------------------------------------------------------------------
+Previously, comparison ufuncs such as ``np.equal`` would return
+`NotImplemented` if their arguments had structured dtypes, to help comparison
+operators such as ``__eq__`` deal with those.  This is no longer needed, as the
+relevant logic has moved to the comparison operators proper (which thus do
+continue to return `NotImplemented` as needed). Hence, like all other ufuncs,
+the comparison ufuncs will now error on structured dtypes.
+
+Positive will now raise a deprecation warning for non-numerical arrays
+----------------------------------------------------------------------
+Previously, ``+array`` unconditionally returned a copy. Now, it will
+raise a ``DeprecationWarning`` if the array is not numerical (i.e.,
+if ``np.positive(array)`` raises a ``TypeError``. For ``ndarray``
+subclasses that override the default ``__array_ufunc__`` implementation,
+the ``TypeError`` is passed on.
+
+``NDArrayOperatorsMixin`` now implements matrix multiplication
+--------------------------------------------------------------
+Previously, ``np.lib.mixins.NDArrayOperatorsMixin`` did not implement the
+special methods for Python's matrix multiplication operator (``@``). This has
+changed now that ``matmul`` is a ufunc and can be overridden using
+``__array_ufunc__``.
+
+The scaling of the covariance matrix in ``np.polyfit`` is different
+-------------------------------------------------------------------
+So far, ``np.polyfit`` used a non-standard factor in the scaling of the the
+covariance matrix. Namely, rather than using the standard ``chisq/(M-N)``, it
+scaled it with ``chisq/(M-N-2)`` where M is the number of data points and N is the
+number of parameters.  This scaling is inconsistent with other fitting programs
+such as e.g. ``scipy.optimize.curve_fit`` and was changed to ``chisq/(M-N)``.
+
+``maximum`` and ``minimum`` no longer emit warnings
+---------------------------------------------------
+As part of code introduced in 1.10,  ``float32`` and ``float64`` set invalid
+float status when a Nan is encountered in `numpy.maximum` and `numpy.minimum`,
+when using SSE2 semantics. This caused a `RuntimeWarning` to sometimes be
+emitted. In 1.15 we fixed the inconsistencies which caused the warnings to
+become more conspicuous. Now no warnings will be emitted.
+
+Umath and multiarray c-extension modules merged into a single module
+--------------------------------------------------------------------
+The two modules were merged, according to `NEP 15`_. Previously `np.core.umath`
+and `np.core.multiarray` were seperate c-extension modules. They are now python
+wrappers to the single `np.core/_multiarray_math` c-extension module.
+
+.. _`NEP 15` : http://www.numpy.org/neps/nep-0015-merge-multiarray-umath.html
+
+``getfield`` validity checks extended
+-------------------------------------
+`numpy.ndarray.getfield` now checks the dtype and offset arguments to prevent
+accessing invalid memory locations.
+
+NumPy functions now support overrides with ``__array_function__``
+-----------------------------------------------------------------
+It is now possible to override the implementation of almost all NumPy functions
+on non-NumPy arrays by defining a ``__array_function__`` method, as described
+in `NEP 18`_. The sole exception are functions for explicitly casting to NumPy
+arrays such as ``np.array``. As noted in the NEP, this feature remains
+experimental and the details of how to implement such overrides may change in
+the future.
+
+.. _`NEP 15` : http://www.numpy.org/neps/nep-0015-merge-multiarray-umath.html
+.. _`NEP 18` : http://www.numpy.org/neps/nep-0018-array-function-protocol.html
+
+Arrays based off readonly buffers cannot be set ``writeable``
+-------------------------------------------------------------
+We now disallow setting the ``writeable`` flag True on arrays created
+from ``fromstring(readonly-buffer)``.
diff --git a/doc/release/1.3.0-notes.rst b/doc/release/1.3.0-notes.rst
index 3ec93e0b0..239714246 100644
--- a/doc/release/1.3.0-notes.rst
+++ b/doc/release/1.3.0-notes.rst
@@ -14,7 +14,7 @@ Python 2.6 support
 Python 2.6 is now supported on all previously supported platforms, including
 windows.
 
-http://www.python.org/dev/peps/pep-0361/
+https://www.python.org/dev/peps/pep-0361/
 
 Generalized ufuncs
 ------------------
@@ -235,7 +235,7 @@ This should make the porting to new platforms easier, and more robust. In
 particular, the configuration stage does not need to execute any code on the
 target platform, which is a first step toward cross-compilation.
 
-http://numpy.github.io/neps/math_config_clean.html
+https://www.numpy.org/neps/nep-0003-math_config_clean.html
 
 umath refactor
 --------------
@@ -247,7 +247,7 @@ Improvements to build warnings
 
 Numpy can now build with -W -Wall without warnings
 
-http://numpy.github.io/neps/warnfix.html
+https://www.numpy.org/neps/nep-0002-warnfix.html
 
 Separate core math library
 --------------------------
diff --git a/doc/release/1.7.0-notes.rst b/doc/release/1.7.0-notes.rst
index 72aab4d4f..f111f80dc 100644
--- a/doc/release/1.7.0-notes.rst
+++ b/doc/release/1.7.0-notes.rst
@@ -101,7 +101,7 @@ to NumPy 1.6:
 
 The notes in `doc/source/reference/arrays.datetime.rst <https://github.com/numpy/numpy/blob/maintenance/1.7.x/doc/source/reference/arrays.datetime.rst>`_
 (also available in the online docs at `arrays.datetime.html
-<http://docs.scipy.org/doc/numpy/reference/arrays.datetime.html>`_) should be
+<https://docs.scipy.org/doc/numpy/reference/arrays.datetime.html>`_) should be
 consulted for more details.
 
 Custom formatter for printing arrays
@@ -280,9 +280,9 @@ The macros in old_defines.h are deprecated and will be removed in the next
 major release (>= 2.0). The sed script tools/replace_old_macros.sed can be
 used to replace these macros with the newer versions.
 
-You can test your code against the deprecated C API by #defining
-NPY_NO_DEPRECATED_API to the target version number, for example
-NPY_1_7_API_VERSION, before including any NumPy headers.
+You can test your code against the deprecated C API by adding a line
+composed of ``#define NPY_NO_DEPRECATED_API`` and the target version number,
+such as ``NPY_1_7_API_VERSION``, before including any NumPy headers.
 
 The ``NPY_CHAR`` member of the ``NPY_TYPES`` enum is deprecated and will be
 removed in NumPy 1.8. See the discussion at
diff --git a/doc/release/template.rst b/doc/release/template.rst
new file mode 100644
index 000000000..db9458ac1
--- /dev/null
+++ b/doc/release/template.rst
@@ -0,0 +1,43 @@
+==========================
+NumPy 1.xx.x Release Notes
+==========================
+
+
+Highlights
+==========
+
+
+New functions
+=============
+
+
+New deprecations
+================
+
+
+Expired deprecations
+====================
+
+
+Future changes
+==============
+
+
+Compatibility notes
+===================
+
+
+C API changes
+=============
+
+
+New Features
+============
+
+
+Improvements
+============
+
+
+Changes
+=======
diff --git a/doc/release/time_based_proposal.rst b/doc/release/time_based_proposal.rst
index 555be6863..2eb13562d 100644
--- a/doc/release/time_based_proposal.rst
+++ b/doc/release/time_based_proposal.rst
@@ -123,7 +123,7 @@ References
 
         * Proposed schedule for Gnome from Havoc Pennington (one of the core
           GTK and Gnome manager):
-          http://mail.gnome.org/archives/gnome-hackers/2002-June/msg00041.html
+          https://mail.gnome.org/archives/gnome-hackers/2002-June/msg00041.html
           The proposed schedule is heavily based on this email
 
-        * http://live.gnome.org/ReleasePlanning/Freezes
+        * https://wiki.gnome.org/ReleasePlanning/Freezes