What's new in this version: 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
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. Usenumpy.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
NumPy 1.16.0 相關參考資料
NumPy Reference - Numpy and Scipy Documentation
NumPy Reference, Release 1.16.0 itemsize [int] Length of one array element in bytes. nbytes [int] Total bytes consumed by the elements of the ...
https://docs.scipy.org
NumPy User Guide - Numpy and Scipy Documentation - SciPy.org
NumPy User Guide, Release 1.16.0. This guide is intended as an introductory overview of NumPy and explains how to install and make use of ...
https://docs.scipy.org
numpy · PyPI
NumPy is the fundamental package for array computing with Python.
https://pypi.org
numpy1.16.0-notes.rst at master · numpynumpy · GitHub
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.
https://github.com
numpynumpy - GitHub
I've got numpy version updated automatically from PyPI to 1.16.0 version today and my tests have failed with the following error on numpy ...
https://github.com
Overview — NumPy v1.16 Manual - Numpy and Scipy Documentation
NumPy v1.16 Manual. Welcome! This is the documentation for NumPy 1.16.0, last updated Jan 31, 2019. Parts of the documentation: ...
https://docs.scipy.org
Release Notes — NumPy v1.16 Manual
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 ...
https://docs.scipy.org
Release Notes — NumPy v1.17 Manual
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 ...
https://docs.scipy.org
Releases · numpynumpy · GitHub
Commonly numpy.broadcast_arrays returns a writeable array with internal ...... The NumPy 1.16.1 release fixes bugs reported against the 1.16.0 release, and
https://github.com
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