Package Release Info

python-pyFFTW-0.12.0-bp154.1.35

Update Info: Base Release
Available in Package Hub : 15 SP4

platforms

AArch64
ppc64le
s390x
x86-64

subpackages

python3-pyFFTW

Change Logs

Version: 0.12.0-bp152.1.8
* Sun Feb 02 2020 Atri Bhattacharya <badshah400@gmail.com>
- Update to version 0.12.0:
  + scipy.fft interface This interface operates like the existing
    scipy.fftpack interface, but matches the API of the newer
    scipy.fft module introduced in SciPy 1.4.
  + test suite was updated to be compatible with more recent dask
    (gh#pyFFTW/pyFFTW#278).
  + Cython variable _N was renamed to avoid a name conflict with a
    preprocessor token on some platforms (gh#pyFFTW/pyFFTW#259).
  + Cython code has been updated to explicitly use
    `language_level=3str` for compatibility with a future Cython
    3.0 release.
- Drop 265.patch: Incorporated upstream.
- Update URL and Source URL to point to new github repository.
* Mon Jan 27 2020 Martin Hauke <mardnh@gmx.de>
- Add patch:
  * 265.patch (Fix Factory builds)
    https://github.com/pyFFTW/pyFFTW/pull/265
* Sat Dec 22 2018 Todd R <toddrme2178@gmail.com>
- Update to version 0.11.1
  + New features
  * Dask interface
  * Fast transform planning utility
  * Expanded support for norm keyword argument in the numpy interfaces
  * Support for norm keyword argument in FFTW builders
  * Dynamic library detection at build and run time
  * OpenMP threading support
  * Custom Configuration of Planners and Interfaces
  + Bugs Fixed
  * A platform-dependent bug that results in potentially overwriting a previously
    computed output upon repeated calls to the numpy interfaces was fixed (#199).
  * Fix to potential platform-dependent integer overflow in empty_aligned (#192).
  * rfftfreq is now present in the numpy fft interfaces for numpy >= 1.8 (#207)
  + Other changes
  * float16 inputs are now transformed using single rather than double precision.
  * The default planning for the numpy and scipy interfaces has changed from
    FFTW_MEASURE to FFTW_ESTIMATE.  This results in faster planning.  In cases
    where the same transform is to be repeated many times, it is likely
    advantageous to manually specify FFTW_MEASURE instead (or use the FFTW builders
    to pre-plan the FFT).
  * FutureWarnings related to NumPy multiindexing in NumPy 1.15 are avoided by
    using more modern indexing conventions.
  * version number handling is now automatically handled by versioneer
  * All documentation is now built and hosted at Read the Docs (
    http://pyfftw.readthedocs.io).
Version: 0.10.4-bp150.2.4
* Sun Oct 08 2017 jengelh@inai.de
- Replace future aims in description.
* Wed Aug 23 2017 toddrme2178@gmail.com
- Implement single-spec version
- Update to version 0.10.4
  + Fixed bugs:
  * Numpy interface can fail with non-writeable arrays.
  * undefined symbol: simd\_alignment with gcc 5.3.0
  * FTBFS: TypeError: can't pickle Cython.Compiler.FlowControl.NameAssignment objects
  + Closed issues:
  * pyfftw fails with ImportError/undefined symbol fftwl\_plan\_with\_nthreads
  * pyfftw does not appear to be using available wisdom files
  * Accuracy of non-power 2 data
  * Cannot find fftw3l when installing from pip
  * Incorrect links to docs
  * PyFFTW returning all zero array after transform...
  * Move to separate pyFFTW project page
  * Release GIL during planning?
  * Merging/sharing wisdom
  * scipy interface patching.
  * very slow test suite
  * setup: some targets should not require numpy to be installed
  * 2x margin on the planning timelimit test is inadequate in windows on Complex64
* Mon Feb 01 2016 toddrme2178@gmail.com
- update to version 0.10.1:
  * it seems that pypi has an annoying feature that minor tweaks can't
    be pushed without a new release.
- changes from version 0.10.0:
  * Closed issues:
    + Conda downloads are failing
    + Python 3.4 and WinPython
    + Installing pyfftw on Anaconda3 on Windows 7
    + is python 3.5 supported?
    + deadlock of cache handler at interpreter shutdown
    + pyFFTW breaks when forked
    + build with mingw
    + Striding in n\_byte\_align not on a uniform standard
    + No exception on wrong arguments of function call of
    pyfftw.FFTW\(...\)
    + pyfftw vs numpy.fft: faster and slower
    + simple transposes?
    + `Datatype not supported` with scipy
    + Update tutorial with new byte align functions
    + OS X Installation errors:
    + Wrong results for pyfftw's ifft?
    + Installing on OS X Mavericks
    + Install error. Ld cannot find -lfftw3f
    + new source release with updated licensing
    + Crash during initialization of FFTW plan for r2c and c2r with
    Intel compiler
    + Move FFTW class definition to pyfftw.pxd
    + Provide transform metadata such as axes and direction
    + Provide shape and dtype properties
    + problem with very large arrays: OverflowError: value too large
    to convert to int
    + add support for in-place multidimensional r2c transform
    + Add numpy interface for hfft
    + add cython as a build dependency
    + Potential memory leak in caching
    + Allow GIL to be released with threads=1
    + Building for 64bit windows
    + Test failure using numpy 1.6.2
    + Remove the requirement for users to specify alignment
    + pyfftw.interfaces can only handle numpy arrays
  * Merged pull requests:
    + Release GIL during both single- and multi-thread execution
    + Support FFTW\_WISDOM\_ONLY
    + Release GIL around FFTW planning
    + Updated the tutorial to reflect changes with new aligned array
    + Add description for installing on OS X
    + close issue \#8 (More numpy like aligned array creation)
    + Discrete sine transform imports
* Sat Apr 19 2014 mardnh@gmx.de
- cleanup package
* Tue Apr 15 2014 mardnh@gmx.de
- initial package