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Metadata-Version: 1.1
Name: amp
Version: dev
Summary: UNKNOWN
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Description-Content-Type: UNKNOWN
Description: # Amp: Atomistic Machine-learning Package #
        
        
        *Amp* is an open-source package designed to easily bring machine-learning to atomistic calculations. This project is being developed at Brown University in the School of Engineering, primarily by Andrew Peterson and Alireza Khorshidi, and is released under the GNU General Public License.  *Amp* allows for the modular representation of the potential energy surface, enabling the user to specify or create descriptor and regression methods.
        
        This project lives at:
        https://bitbucket.org/andrewpeterson/amp
        
        Documentation lives at:
        http://amp.readthedocs.org
        
        Users' mailing list lives at:
        https://listserv.brown.edu/?A0=AMP-USERS
        
        If you would like to compile a local version of the documentation, see the README file in the docs directory.
        
        (This project was formerly known as "Neural". The last stable version of Neural can be found at https://bitbucket.org/andrewpeterson/neural)
        
        
        License
        =======
        
         This program is free software: you can redistribute it and/or modify
         it under the terms of the GNU General Public License as published by
         the Free Software Foundation, either version 3 of the License, or
         (at your option) any later version.
        
         This program is distributed in the hope that it will be useful,
         but WITHOUT ANY WARRANTY; without even the implied warranty of
         MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
         GNU General Public License for more details.
        
         You should have received a copy of the GNU General Public License
         along with this program.  If not, see <http://www.gnu.org/licenses/>.
        
        
        Installation
        ============
        
        You can find the installation instructions for this version of Amp in the
        documentation file `docs/installation.rst`.
        
        Documentation
        =============
        
        We currently host multiple versions of the documentation, which includes
        installation instructions, at http://amp.readthedocs.io. 
        
        You can build a local copy of the documentation for this version of Amp.
        You will find instructions to do this in the "Documentation" section of the
        file `docs/develop.rst`.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3