Changelog for python38-Bottleneck-1.3.5-1.2.x86_64.rpm :

* Sun Aug 14 2022 Arun Persaud - update to version 1.3.5:
* Bug Fixes + Fix numpy deprecation of non-tuple indices
* Enhancements + Switch build to manylinux_2_24_x86_64 using cibuildwheel
* Sat Mar 12 2022 Arun Persaud - specfile:
* update copyright year- update to version 1.3.4:
* Bug Fixes + Fix Memory leak with big-endian data- changes from version 1.3.3:
* Bug Fixes + Fix Python 3.10 build
* Enhancements + Provide pre-compiled wheels for most x86_64 architectures
* Wed Feb 17 2021 Benjamin Greiner - Skip python36 build: NumPy 1.20 in Tumbleweed does not provide python36-numpy anymore (NEP 29).
* Mon Mar 30 2020 John Vandenberg - Require numpy 1.16.0, removing Python 2 support which provides a lower version- Activate test suite
* Sat Mar 14 2020 Arun Persaud - specfile:
* update copyright year- update to version 1.3.2:
* Bug Fixes + Explicitly declare numpy version dependency in pyproject.toml for Python 3.8, fixing certain cases where pip install would fail. Thanks to AATTgoggle, AATTastrofrog, and AATT0xb0b for reporting. (:issue:`277`)
* Fri Nov 22 2019 Arun Persaud - specfile:
* update copyright year- update to version 1.3.1:
* Bug Fixes + Fix memory leak in :func:`bottleneck.nanmedian` with the default argument of axis=None. Thanks to AATTjsmodic for reporting! (:issue:`276`, :issue:`278`) + Add regression test for memory leak case (:issue:`279`)- changes from version 1.3.0:
* Project Updates + Bottleneck has a new maintainer, Christopher Whelan (AATTqwhelan on GitHub). + Documentation now hosted at https://bottleneck.readthedocs.io + 1.3.x will be the last release to support Python 2.7 + Bottleneck now supports and is tested against Python 3.7 and 3.8. (:issue:`211`, :issue:`268`) + The LICENSE file has been restructured to only include the license for the Bottleneck project to aid license audit tools. There has been no change to the licensing of Bottleneck. + Licenses for other projects incorporated by Bottleneck are now reproduced in full in separate files in the LICENSES/ directory (eg, LICENSES/NUMPY_LICENSE) + All licenses have been updated. Notably, setuptools is now MIT licensed and no longer under the ambiguous dual PSF/Zope license. + Bottleneck now uses PEP 518 for specifying build dependencies, with per Python version specifications (:issue:`247`)
* Enhancements + Remove numpydoc package from Bottleneck source distribution + :func:`bottleneck.slow.reduce.nansum` and :func:`bottleneck.slow.reduce.ss` now longer coerce output to have the same dtype as input + Test (tox, travis, appveyor) against latest numpy (in conda) + Performance benchmarking also available via asv + versioneer now used for versioning (:issue:`213`) + Test suite now uses pytest as nose is deprecated (:issue:`222`) + python setup.py build_ext --inplace is now incremental (:issue:`224`) + python setup.py clean now cleans all artifacts (:issue:`226`) + Compiler feature support now identified by testing rather than hardcoding (:issue:`227`) + The BN_OPT_3 macro allows selective use of -O3 at the function level (:issue:`223`) + Contributors are now automatically cited in the release notes (:issue:`244`)
* Performance + Speed up :func:`bottleneck.reduce.anynan` and :func:`bottleneck.reduce.allnan` by 2x via BN_OPT_3 (:issue:`223`) + All functions covered by asv benchmarks + :func:`bottleneck.nonreduce.replace` speedup of 4x via more explicit typing (:issue:`239`) + :func:`bottleneck.reduce.median` up to 2x faster for Fortran-ordered arrays (:issue:`248`)
* Bug Fixes + Documentation fails to build on Python 3 (:issue:`170`) + :func:`bottleneck.benchmark.bench` crashes on python 3.6.3, numpy 1.13.3 (:issue:`175`) + :func:`bottleneck.nonreduce_axis.push` raises when n=None is explicitly passed (:issue:`178`) + :func:`bottleneck.reduce.nansum` wrong output when a = np.ones((2, 2))[..., np.newaxis] same issue of other reduce functions (:issue:`183`) + Silenced FutureWarning from NumPy in the slow version of move functions (:issue:`194`) + Installing bottleneck onto a system that does not already have Numpy (:issue:`195`) + Memory leaked when input was not a NumPy array (:issue:`201`) + Tautological comparison in :func:`bottleneck.move.move_rank` removed (:issue:`207`, :issue:`212`)
* Cleanup + The ez_setup.py module is no longer packaged (:issue:`211`) + Building documentation is now self-contained in make doc (:issue:`214`) + Codebase now flake8 compliant and run on every commit + Codebase now uses black for autoformatting (:issue:`253`)
* Wed Sep 27 2017 arunAATTgmx.de- update to version 1.2.1:
* #156 Installing bottleneck when two versions of NumPy are present
* #157 Compiling on Ubuntu 14.04 inside a Windows 7 WMware
* #159 Occasional segmentation fault in nanargmin, nanargmax, median, and nanmedian when all of the following conditions are met: axis is None, input array is 2d or greater, and input array is not C contiguous.
* #163 Reducing np.array([2
*
*31], dtype=np.int64) overflows on Windows
* Wed Apr 19 2017 toddrme2178AATTgmail.com- Implement single-spec version.
* Mon Nov 14 2016 dmuellerAATTsuse.com- update to 1.2.0: This release is a complete rewrite of Bottleneck. - Bottleneck is now written in C - Cython is no longer a dependency - Source tarball size reduced by 80% - Build time reduced by 66% - Install size reduced by 45%
* Mon Apr 27 2015 benoit.moninAATTgmx.fr- update to version 1.0.0:
* \"python setup.py build\" is 18.7 times faster
* Function-call overhead cut in half---a big speed up for small input arrays
* Arbitrary ndim input arrays accelerated; previously only 1d, 2d, and 3d
* bn.nanrankdata is twice as fast for float input arrays
* bn.move_max, bn.move_min are faster for int input arrays
* No speed penalty for reducing along all axes when input is Fortran ordered
* Compiled binaries 14.1 times smaller
* Source tarball 4.7 times smaller
* 9.8 times less C code
* 4.3 times less Cython code
* 3.7 times less Python code
* Requires numpy 1.9.1
* Single API, e.g.: bn.nansum instead of bn.nansum and nansum_2d_float64_axis0
* On 64-bit systems bn.nansum(int32) returns int32 instead of int64
* bn.nansum now returns 0 for all NaN slices (as does numpy 1.9.1)
* Reducing over all axes returns, e.g., 6.0; previously np.float64(6.0)
* bn.ss() now has default axis=None instead of axis=0
* bn.nn() is no longer in bottleneck
* Previous releases had moving window function pairs: move_sum, move_nansum
* This release only has half of the pairs: move_sum
* Instead a new input parameter, min_count, has been added
* min_count=None same as old move_sum; min_count=1 same as old move_nansum
* If # non-NaN values in window < min_count, then NaN assigned to the window
* Exception: move_median does not take min_count as input
* Can now install bottleneck with pip even if numpy is not already installed
* bn.move_max, bn.move_min now return float32 for float32 input- increase required numpy version to 1.9.1