Metadata-Version: 1.1
Name: mpi4py-fft
Version: 1.0.3
Summary: mpi4py-fft -- FFT with MPI
Home-page: https://bitbucket.org/mpi4py/mpi4py-fft
Author: Lisandro Dalcin and Mikael Mortensen
Author-email: UNKNOWN
License: UNKNOWN
Description: mpi4py-fft
        ----------
        
        
        .. image:: https://circleci.com/bb/mpi4py/mpi4py-fft.svg?style=svg
            :target: https://circleci.com/bb/mpi4py/mpi4py-fft
        
        .. image:: https://api.codacy.com/project/badge/Grade/edf0f9ed1e114ab090ac4f9863c05fa3
            :target: https://www.codacy.com/app/mikaem/mpi4py-fft?utm_source=mpi4py@bitbucket.org&amp;utm_medium=referral&amp;utm_content=mpi4py/mpi4py-fft&amp;utm_campaign=Badge_Grade
        
        .. image:: https://codecov.io/bb/mpi4py/mpi4py-fft/branch/master/graph/badge.svg
          :target: https://codecov.io/bb/mpi4py/mpi4py-fft
        
        .. image:: https://readthedocs.org/projects/mpi4py-fft/badge/?version=latest
           :target: https://mpi4py-fft.readthedocs.io/en/latest/?badge=latest
           :alt: Documentation Status
        
        
        mpi4py-fft is a Python package for computing Fast Fourier Transforms (FFTs).
        Large arrays are distributed and communications are handled under the hood by
        MPI for Python (mpi4py). To distribute large arrays we are using a
        `new and completely generic algorithm <https://arxiv.org/abs/1804.09536>`_
        that allows for any index set of a multidimensional array to be distributed. We
        can distribute just one index (a slab decomposition), two index sets (pencil
        decomposition) or even more for higher-dimensional arrays.
        
        In mpi4py-fft there is also included a Python interface to the
        `FFTW <http://www.fftw.org>`_ library. This interface can be used without MPI,
        much like `pyfftw <https://hgomersall.github.io/pyFFTW/>`_, and even for
        real-to-real transforms, like discrete cosine or sine transforms.
        
        Further documentation is found at `readthedocs <https://mpi4py-fft.readthedocs.io/en/latest/>`_.
        
        Installation
        ------------
        
        The mpi4py-fft package can be installed using::
        
            pip install mpi4py-fft
        
        or, to get the latest version from bitbucket::
        
            pip install git+https://bitbucket.org/mpi4py/mpi4py-fft@master
        
        It can also be built using conda build from the main source directory::
        
            conda build -c conda-forge conf/
            conda create --name mpi4py_fft mpi4py_fft --use-local
        
        which will pull in the required dependencies from the conda-forge channel.
        
        Mpi4py-fft depends on Python packages
        
            * mpi4py
            * numpy
            * cython
            * six
        
        and the C-library
        
            * `FFTW <http://www.fftw.org>`_
        
        Note that *mpi4py* requires a working MPI installation, with the compiler
        wrapper *mpicc* on your search path. All of the above dependencies are
        available and will be downloaded through the conda-forge channel if
        conda is used for installation.
        
        For IO you need to install either `h5py <https://www.h5py.org>`_ or
        `netCDF4 <http://unidata.github.io/netcdf4-python/>`_ with support for
        MPI. These libraries are, unfortunately, not compiled with MPI on
        conda-forge. The two libraries are available, though, for both OSX and
        linux from the `spectralDNS <https://anaconda.org/spectralDNS>`_ channel
        on anaconda cloud::
        
            conda install -c spectralDNS h5py-parallel netcdf4-parallel
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
