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python-Bottleneck
python-Bottleneck.changes
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File python-Bottleneck.changes of Package python-Bottleneck
------------------------------------------------------------------- Fri Apr 19 11:14:59 UTC 2024 - Ben Greiner <code@bnavigator.de> - Update to 1.3.8 * Maintenance updates - Pin to numpy < 2: Fails to build otherwise. Upstream is working on it. ------------------------------------------------------------------- Tue Mar 14 22:42:33 UTC 2023 - Dirk Müller <dmueller@suse.com> - update to 1.3.7: * Python 3.11 wheel available ------------------------------------------------------------------- Fri Jan 20 15:18:50 UTC 2023 - Dirk Müller <dmueller@suse.com> - update to 1.3.6: * Fix ValueError: cannot convert float NaN to integer with new numpy version * Python 3.6 wheel won't be built anymore because of the deprecation in the associated Python Github action ------------------------------------------------------------------- Fri Dec 23 17:21:43 UTC 2022 - Ben Greiner <code@bnavigator.de> - Skip a failing test -- gh#pydata/bottleneck#423 - Add rpmlintrc ------------------------------------------------------------------- Sun Aug 14 15:00:35 UTC 2022 - Arun Persaud <arun@gmx.de> - 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 05:34:03 UTC 2022 - Arun Persaud <arun@gmx.de> - 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 22:59:05 UTC 2021 - Benjamin Greiner <code@bnavigator.de> - Skip python36 build: NumPy 1.20 in Tumbleweed does not provide python36-numpy anymore (NEP 29). ------------------------------------------------------------------- Mon Mar 30 07:02:07 UTC 2020 - John Vandenberg <jayvdb@gmail.com> - Require numpy 1.16.0, removing Python 2 support which provides a lower version - Activate test suite ------------------------------------------------------------------- Sat Mar 14 15:57:22 UTC 2020 - Arun Persaud <arun@gmx.de> - 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 @goggle, @astrofrog, and @0xb0b for reporting. (:issue:`277`) ------------------------------------------------------------------- Fri Nov 22 06:15:40 UTC 2019 - Arun Persaud <arun@gmx.de> - 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 @jsmodic 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 (@qwhelan 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 22:20:10 UTC 2017 - arun@gmx.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 18:37:17 UTC 2017 - toddrme2178@gmail.com - Implement single-spec version. ------------------------------------------------------------------- Mon Nov 14 14:24:23 UTC 2016 - dmueller@suse.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 19:23:55 UTC 2015 - benoit.monin@gmx.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 ------------------------------------------------------------------- Thu May 8 10:58:17 UTC 2014 - toddrme2178@gmail.com - Update to version 0.8.0 - This version of Bottleneck requires NumPy 1.8 - nanargmin and nanargmax behave like the corresponding functions in NumPy 1.8 - nanargmax/nanargmin wrong for redundant max/min values in 1d int arrays ------------------------------------------------------------------- Tue Oct 22 12:07:46 UTC 2013 - toddrme2178@gmail.com - Update to version 0.7.0 + bn.rankdata() is twice as fast (with input a = np.random.rand(1000000)) + C files now included in github repo; cython not needed to try latest + C files are now generated with Cython 0.19.1 instead of 0.16 + Test bottleneck across multiple python/numpy versions using tox + Source tarball size cut in half ------------------------------------------------------------------- Fri Jun 22 13:11:43 UTC 2012 - saschpe@suse.de - %py_requires is only needed for SLE_11_SP2 (and older), newer Python package releases generate the RPM requires for the Python ABI automatically ------------------------------------------------------------------- Fri Jun 22 12:25:12 UTC 2012 - saschpe@suse.de - Update to version 0.6.0: + replace(arr, old, new), e.g, replace(arr, np.nan, 0) + nn(arr, arr0, axis) nearest neighbor and its index of 1d arr0 in 2d arr + anynan(arr, axis) faster alternative to np.isnan(arr).any(axis) + allnan(arr, axis) faster alternative to np.isnan(arr).all(axis) + Python 3.2 support (may work on earlier verions of Python 3) + C files are now generated with Cython 0.16 instead of 0.14.1 + Upgrade numpydoc from 0.3.1 to 0.4 to support Sphinx 1.0.1 + Support for Python 2.5 dropped + Default axis for benchmark suite is now axis=1 (was 0) + #31 Confusing error message in partsort and argpartsort + #32 Update path in MANIFEST.in + #35 Wrong output for very large (2**31) input arrays ------------------------------------------------------------------- Fri Jun 1 09:05:36 UTC 2012 - toddrme2178@gmail.com - spec file cleanups - fix license tag ------------------------------------------------------------------- Mon Feb 27 21:55:40 UTC 2012 - scorot@free.fr - version 0.5.0 ------------------------------------------------------------------- Fri Jan 22 00:00:00 UTC 2011 - scorot@gtt.fr - Initial release
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