Metadata-Version: 1.1
Name: shenfun
Version: 1.3.1
Summary: Shenfun -- Automated Spectral-Galerkin framework
Home-page: https://github.com/spectralDNS/shenfun
Author: Mikael Mortensen
Author-email: mikaem@math.uio.no
License: UNKNOWN
Description: Shenfun
        =======
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        Description
        -----------
        Shenfun is a high performance computing platform for solving partial differential equations (PDEs) by the spectral Galerkin method. The user interface to shenfun is very similar to `FEniCS <https://fenicsproject.org>`_, but applications are limited to multidimensional tensor product grids. The code is parallelized with MPI through the `mpi4py-fft <https://bitbucket.org/mpi4py/mpi4py-fft>`_ package.
        
        Shenfun enables fast development of efficient and accurate PDE solvers (spectral order and accuracy), in the comfortable high-level Python language. The spectral accuracy is ensured by using high-order *global* orthogonal basis functions (Fourier, Legendre and Chebyshev), as opposed to finite element codes that are using low-order *local* basis functions. Efficiency is ensured through vectorization (`Numpy <https://www.numpy.org/>`_), parallelization (`mpi4py <https://bitbucket.org/mpi4py/mpi4py>`_) and by moving critical routines to `Cython <https://cython.org/>`_ or `Numba <https://numba.pydata.org>`_. Shenfun has been used to run turbulence simulations (Direct Numerical Simulations) on thousands of processors on high-performance supercomputers, see the `spectralDNS <https://github.com/spectralDNS/spectralDNS>`_ repository.
        
        The demo folder contains several examples for the Poisson, Helmholtz and Biharmonic equations. For extended documentation and installation instructions see `ReadTheDocs <http://shenfun.readthedocs.org>`_. See also this `paper <https://raw.githack.com/spectralDNS/shenfun/master/docs/demos/mekit17/pub/shenfun_bootstrap.html>`_.
        
        Installation
        ------------
        
        Shenfun can be installed using either `pip <https://pypi.org/project/pip/>`_ or `conda <https://conda.io/docs/>`_, see `installation chapter on readthedocs <https://shenfun.readthedocs.io/en/latest/installation.html>`_.
        
        Dependencies
        ------------
        
            * `Python <https://www.python.org/>`_ 2.7, 3.3 or above. Test suits are run with Python 2.7 and 3.6.
            * A functional MPI 2.x/3.x implementation like `MPICH <https://www.mpich.org>`_ or `Open MPI <https://www.open-mpi.org>`_ built with shared/dynamic libraries.
            * `FFTW <http://www.fftw.org/>`_ version 3, also built with shared/dynamic libraries.
            * Python modules:
                * `Numpy <https://www.numpy.org/>`_
                * `Scipy <https://www.scipy.org/>`_
                * `Sympy <https://www.sympy.org>`_
                * `Cython <https://cython.org/>`_
                * `mpi4py <https://bitbucket.org/mpi4py/mpi4py>`_
                * `mpi4py-fft <https://bitbucket.org/mpi4py/mpi4py-fft>`_
        
        Contact
        -------
        For comments, issues, bug-reports and requests, please use the issue tracker of the current repository, or see `How to contribute? <https://shenfun.readthedocs.io/en/latest/howtocontribute.html>`_ at readthedocs. Otherwise the principal author can be reached at::
        
            Mikael Mortensen
            mikaem at math.uio.no
            http://folk.uio.no/mikaem/
            Department of Mathematics
            University of Oslo
            Norway
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
