Easily creating and manipulating numerical data

NumPy

Join our mailing list

Stay up to date with latest software releases, news, software discounts, deals and more.

Subscribe

NumPy 1.16.0

  -  4.82 MB  -  Open Source

Sometimes latest versions of the software can cause issues when installed on older devices or devices running an older version of the operating system. Software makers usually fix these issues but it can take them some time. What you can do in the meantime is to download and install an older version of NumPy 1.16.0.


For those interested in downloading the most recent release of NumPy or reading our review, simply click here.


All old versions distributed on our website are completely virus-free and available for download at no cost.


We would love to hear from you

If you have any questions or ideas that you want to share with us - head over to our Contact page and let us know. We value your feedback!

  • NumPy 1.16.0 Screenshots

    The images below have been resized. Click on them to view the screenshots in full size.

    NumPy 1.16.0 Screenshot 1
  • NumPy 1.16.0 Screenshot 2
  • NumPy 1.16.0 Screenshot 3
  • NumPy 1.16.0 Screenshot 4
  • NumPy 1.16.0 Screenshot 5

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

Join our mailing list

Stay up to date with latest software releases, news, software discounts, deals and more.

Subscribe