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|
NumPy 1.11.0 Release Notes
**************************
This release supports Python 2.6 - 2.7 and 3.2 - 3.5.
Highlights
==========
Dropped Support
===============
* Bento build support and related files have been removed.
* Single file build support and related files have been removed.
Future Changes
==============
* Relaxed stride checking will become the default in 1.12.0.
* Support for Python 2.6, 3.2, and 3.3 will be dropped in 1.12.0.
Compatibility notes
===================
DeprecationWarning to error
~~~~~~~~~~~~~~~~~~~~~~~~~~~
* Indexing with floats raises IndexError,
e.g., a[0, 0.0].
* Indexing with non-integer array_like raises IndexError,
e.g., a['1', '2']
* Indexing with multiple ellipsis raises IndexError,
e.g., a[..., ...].
* Indexing with boolean where integer expected raises IndexError,
e.g., a[False:True:True].
* Non-integers used as index values raise TypeError,
e.g., in reshape, take, and specifying reduce axis.
FutureWarning to changed behavior
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
* In ``np.lib.split`` an empty array in the result always had dimension
``(0,)`` no matter the dimensions of the array being split. This
has been changed so that the dimensions will be preserved. A
``FutureWarning`` for this change has been in place since Numpy 1.9 but,
due to a bug, sometimes no warning was raised and the dimensions were
already preserved.
C API
~~~~~
Removed the ``check_return`` and ``inner_loop_selector`` members of
the ``PyUFuncObject`` struct (replacing them with ``reserved`` slots
to preserve struct layout). These were never used for anything, so
it's unlikely that any third-party code is using them either, but we
mention it here for completeness.
New Features
============
* `np.histogram` now provides plugin estimators for automatically
estimating the optimal number of bins. Passing one of ['auto', 'fd',
'scott', 'rice', 'sturges'] as the argument to 'bins' results in the
corresponding estimator being used.
* A benchmark suite using `Airspeed Velocity
<http://spacetelescope.github.io/asv/>`__ has been added, converting the
previous vbench-based one. You can run the suite locally via ``python
runtests.py --bench``. For more details, see ``benchmarks/README.rst``.
* A new function ``np.shares_memory`` that can check exactly whether two
arrays have memory overlap is added. ``np.may_share_memory`` also now has
an option to spend more effort to reduce false positives.
* ``SkipTest`` and ``KnownFailureException`` exception classes are exposed
in the ``numpy.testing`` namespace. Raise them in a test function to mark
the test to be skipped or mark it as a known failure, respectively.
* ``f2py.compile`` has a new ``extension`` keyword parameter that allows the
fortran extension to be specified for generated temp files. For instance,
the files can be specifies to be ``*.f90``. The ``verbose`` argument is
also activated, it was previously ignored.
* A ``dtype`` parameter has been added to ``np.random.randint``
Random ndarrays of the following types can now be generated:
- np.bool,
- np.int8, np.uint8,
- np.int16, np.uint16,
- np.int32, np.uint32,
- np.int64, np.uint64,
- np.int_ (long), np.intp
The specification is by precision rather than by C type. Hence, on some
platforms np.int64 may be a `long` instead of `long long` even if the
specified dtype is `long long` because the two may have the same
precision. The resulting type depends on which C type numpy uses for the
given precision. The byteorder specification is also ignored, the
generated arrays are always in native byte order.
Improvements
============
*np.gradient* now supports an ``axis`` argument
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``axis`` parameter was added to *np.gradient* for consistency.
It allows to specify over which axes the gradient is calculated.
*np.lexsort* now supports arrays with object data-type
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The function now internally calls the generic ``npy_amergesort``
when the type does not implement a merge-sort kind of ``argsort``
method.
Memory and speed improvements for masked arrays
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Creating a masked array with ``mask=True`` (resp. ``mask=False``) now uses
``np.ones`` (resp. ``np.zeros``) to create the mask, which is faster and avoid
a big memory peak. Another optimization was done to avoid a memory peak and
useless computations when printing a masked array.
*ndarray.tofile* now uses fallocate on linux
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The function now uses the fallocate system call to reserve sufficient
diskspace on filesystems that support it.
Changes
=======
*np.broadcast* can now be called with a single argument
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The resulting object in that case will simply mimic iteration over
a single array. This change obsoletes distinctions like
if len(x) == 1:
shape = x[0].shape
else:
shape = np.broadcast(*x).shape
Instead, ``np.broadcast`` can be used in all cases.
*np.trace* now respects array subclasses
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This behaviour mimics that of other functions such as ``np.diagonal`` and
ensures, e.g., that for masked arrays ``np.trace(ma)`` and ``ma.trace()`` give
the same result.
Deprecations
============
Views of arrays in Fortran order
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The f_contiguous flag was used to signal that views as a dtypes that
changed the element size would change the first index. This was always a
bit problematical for arrays that were both f_contiguous and c_contiguous
because c_contiguous took precedence. Relaxed stride checking results in
more such dual contiguous arrays and breaks some existing code as a result.
Note that this also affects changing the dtype by assigning to the dtype
attribute of an array. The aim of this deprecation is to restrict views to
c_contiguous arrays at some future time. A work around that is backward
compatible is to use `a.T.view(...).T` instead. A parameter will also be
added to the view method to explicitly ask for Fortran order views, but
that will not be backward compatible.
Invalid arguments for array ordering
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
It is currently possible to pass in arguments for the ```order```
parameter in methods like ```array.flatten``` or ```array.ravel```
that were not one of the following: 'C', 'F', 'A', 'K' (note that
all of these possible values are unicode- and case-insensitive).
Such behaviour will not be allowed in future releases.
Random number generator in the ``testing`` namespace
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Python standard library random number generator was previously exposed in the
``testing`` namespace as ``testing.rand``. Using this generator is not
recommended and it will be removed in a future release. Use generators from
``numpy.random`` namespace instead.
|
