Metadata-Version: 1.1
Name: MPInterfaces-Latest
Version: 1.8.2
Summary: High throughput analysis of interfaces using VASP and Materials Project tools
Home-page: https://github.com/henniggroup/MPInterfaces
Author: Joshua J. Gabriel, Michael Ashton
Author-email: joshgabriel92@ufl.edu, ashtonmv@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: .. image:: https://travis-ci.org/henniggroup/MPInterfaces.svg?branch=master
        .. image:: https://codecov.io/gh/henniggroup/MPInterfaces/coverage.svg?branch=master
        
        MPinterfaces is a python package that enables high throughput Density
        Functional Theory(DFT) analysis of arbitrary material interfaces(two dimensional
        materials, hetero-structure, ligand capped
        nanoparticles and surfaces in the presence of solvents) using
        VASP_, VASPsol_, LAMMPS_, materialsproject_ database
        as well as their open source tools_ and a little bit of ase_.
        
        .. _materialsproject: https://github.com/materialsproject
        
        .. _VASPsol: https://github.com/henniggroup/VASPsol
        
        .. _VASP: http://www.vasp.at/
        
        .. _tools: https://github.com/materialsproject
        
        .. _LAMMPS: http://lammps.sandia.gov/
        
        .. _ase: https://wiki.fysik.dtu.dk/ase/
        
        .. image:: https://github.com/henniggroup/MPInterfaces/blob/master/docs/mpinterfaces-logo.png
           :width: 75 %
           :align: center
        
        Installation
        ==============
        
        Prepping - Setting up Virtual Environments with Miniconda
        -------------------------------
        
        We recommend setting up virtual environment
        using Miniconda which can be installed according to their instructions from https://conda.io/miniconda.html
        
        Follow the following steps to set up virtual environment using Miniconda
        
        $ conda create -n name_of_your_environment python=3.6
        
        On Mac OS and Linux
        
        $ source activate name_of_your_environment
        
        $ conda install numpy scipy matplotlib ipython
        
        On Windows:
        
        $ activate name_of_your_environment
        
        Note: You will need to have C++ libraries properly
        installed for the package to install correctly on Windows.
        
        For teaching and demo purposes, we recommend using Microsoft Azure notebooks, 
        an example of which is at https://notebooks.azure.com/JoshGabriel92/libraries/PourbaixCourse
        which contains two notebooks that illustrate installing pymatgen and pyhull for on the fly
        data science tutorials. We have one notebook FeOH_Example.ipynb for Pourbaix diagrams and an MPInterfacesDemo that illustrate other features of the MPInterfaces code with more to come.
        
        Note for SuperComputer Clusters with Linux OS:
        
        HiperGator2 and other linux based supercomputing clusters
        have shared modules one of which are the C++ modules under gcc.
        This needs to be loaded before any of the aforementioned 
        gcc/5.2.0 has all the shared libraries
        required for a successful installation.
        
        Do the following on HiperGator2 before you create
        the Miniconda environment:
        
        $ module purge 
        $ module load gcc/5.2.0
        
        Get the stable release version from PyPI
        ----------------------------------------
        
        Once you have a nicely prepped virtual environment with miniconda
        and you do not seek to do extensive code development/contributions, 
        we recommend installing from PyPI with:
        
        $ pip install MPInterfaces_Latest
        
        Get the latest bleeding edge version 
        ------------------------------------
        
        If you would like to develop and contribute we recommend getting the bleeding edge 
        copy from the github repository.
         
        If you already have a local copy, steps 1 and 2 of the following instructions
        can be skipped. Just do a "git pull" from the MPInterfaces folder and go to
        step 3(if the local copy was installed in the develop mode this step can be skipped too).
        
        Note: on using virtual environments on your own machine, we recommend to use Miniconda.
        
        1. Clone the latest version from github
        
          - git clone https://github.com/henniggroup/MPInterfaces.git
        
        2. cd MPInterfaces
        
        3. python setup.py install(or develop)
        
        4. Copy the mpint_config.yaml file from config_files/mpint_config.yaml
           to mpinterfaces/mpint_config.yaml
           and update the file so that you have the following
           environment variables :
        
           - MAPI_KEY=the_key_obtained_from_materialsproject
        
           - PMG_VASP_PSP_DIR=path_to_vasp_potcar_files
        
        
        How to Install Latest Pymatgen
        ------------------------------
        
        See http://pymatgen.org/#getting-pymatgen
        
        
        Documentation
        ==============
        
        A very minimal documentation is avaiable at
        
        http://henniggroup.github.io/MPInterfaces/
        
        and work is underway to improve it.
        
        
        Usage
        ==========
        
        We use pymatgen tools for all structure manipulation tasks, so it would
        be a good idea to start from here:
        
        http://pymatgen.org/#using-pymatgen
        
        The examples folder contain some sample scripts that demonstrate the
        usage of mpinterfaces as well as materialsproject packages. For basic
        usage please see **docs/usage.rst**.
        
        
        Cite
        ======
        
        If you use MPInterfaces for your work, please cite the paper: mpinterfaces-paper_
        
        .. _mpinterfaces-paper: http://www.sciencedirect.com/science/article/pii/S0927025616302440
        
        
        License
        =======
        
        MPInterfaces is released under the MIT License.::
        
            Copyright (c) 2014-2017 Henniggroup Cornell/University of Florida & NIST
        
            Permission is hereby granted, free of charge, to any person obtaining a copy of
            this software and associated documentation files (the "Software"), to deal in
            the Software without restriction, including without limitation the rights to
            use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
            the Software, and to permit persons to whom the Software is furnished to do so,
            subject to the following conditions:
        
            The above copyright notice and this permission notice shall be included in all
            copies or substantial portions of the Software.
        
            THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
            IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
            FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
            COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
            IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
            CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
        
        
        Contributing
        =============
        
        We try to follow the coding style used by pymatgen(PEP8):
        
        http://pymatgen.org/contributing.html#coding-guidelines
        
        
        Authors
        =========
        
        Kiran Mathew
        
        Joshua Gabriel
        
        Michael Ashton
        
        Arunima Singh
        
        Joshua T. Paul
        
        Seve G. Monahan
        
        Richard G. Hennig
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
