Metadata-Version: 1.0
Name: nept
Version: 0.1.0
Summary: Neuroelectrophysiology tools
Home-page: https://github.com/vandermeerlab/nept
Author: Emily Irvine
Author-email: emilymirvine@gmail.com
License: UNKNOWN
Description-Content-Type: UNKNOWN
Description: .. image:: https://img.shields.io/travis/vandermeerlab/nept/master.svg
          :target: https://travis-ci.org/vandermeerlab/nept
          :alt: Travis-CI build status
        
        .. image:: https://img.shields.io/codecov/c/github/vandermeerlab/nept/master.svg
          :target: https://codecov.io/gh/vandermeerlab/nept/branch/master
          :alt: Test coverage
        
        .. image:: https://img.shields.io/badge/docs-latest-blue.svg
          :target: https://vandermeerlab.github.io/nept/
          :alt: Documentation Status
        
        **********************************
        nept: Neuroelectrophysiology tools
        **********************************
        
        Formerly ``vdmlab``, renamed to emphasize general abilities of this library.
        
        Getting started
        ===============
        
        If you don't already have python 3, we recommend you download it using Miniconda 
        from `Continuum Analytics <http://conda.pydata.org/miniconda.html>`_.
        
        We recommend using a separate python environment.
        
        Open a **new** terminal, create and activate a new conda environment::
        
          conda create -n yourenv python=3.5
          activate yourenv [Windows] or source activate yourenv [Linux]
        
        Install package dependencies::
        
          conda install matplotlib jupyter scipy numpy pandas seaborn pytest coverage
        
        For Shapely, try::
        
          pip install shapely
        
        If that fails, in Windows, download the most recent wheel file 
        `here <http://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely>`_.
        Once downloaded, install with wheel.
        
        .. code:: bash
        
          pip install yourshapelyinstall.whl
        
        Installation
        ============
        
        Clone nept from Github and use a developer installation::
        
          git clone https://github.com/vandermeerlab/nept.git
          cd nept
          python setup.py develop
        
        Documentation
        =============
        
        Users
        -----
        
        Check `GitHub Pages <https://vandermeerlab.github.io/nept/>`_
        for the latest version of the nept documentation.
        
        Developers
        ----------
        
        Ensure you have sphinx, numpydic, and mock::
        
          conda install ghp-import sphinx numpydoc sphinx_rtd_theme
        
        Install nbsphinx so notebooks in the documentations can be executed::
          
          pip install nbsphinx --user
        
        Build the latest version of the documentation using 
        in the nept directory prior to pushing it to Github::
        
          sphinx-build docs docs/_build
        
        And push it to Github::
        
          docs/update.sh
        
        Testing
        =======
        
        Run tests with `pytest <http://docs.pytest.org/en/latest/usage.html>`_.
        
        Check coverage with `codecov <https://codecov.io/gh/vandermeerlab/nept>`_.
        
        License
        =======
        
        The nept codebase is made available under made available 
        under the `MIT license <LICENSE.rst>`_
        that allows using, copying and sharing.
        
        The file ``nept/neuralynx_loaders.py`` contains code from 
        `nlxio <https://github.com/bwillers/nlxio>`_ by Bernard Willers, 
        used with permission. 
        
        Projects using nept
        ===================
        
        `emi_shortcut <https://github.com/vandermeerlab/emi_shortcut>`_
        
        `emi_biconditional <https://github.com/vandermeerlab/emi_biconditional>`_
        
Platform: UNKNOWN
