Metadata-Version: 2.1
Name: chemlg
Version: 0.6.0
Summary: ChemLG is a smart and massive parallel molecular library generator for  chemical and materials sciences.
Home-page: UNKNOWN
Author: Mohammad Atif Faiz Afzal, Johannes Hachmann
Author-email: m27@buffalo.edu, hachmann@buffalo.edu
License: BSD-3C
Project-URL: url, https://hachmannlab.github.io/chemlg/
Project-URL: Source, https://github.com/hachmannlab/chemlg
Description: [![Build Status](https://travis-ci.org/hachmannlab/chemlg.svg?branch=master)](https://travis-ci.org/hachmannlab/chemlg)
        [![codecov](https://codecov.io/gh/hachmannlab/chemlg/branch/master/graph/badge.svg)](https://codecov.io/gh/hachmannlab/chemlg)
        # ChemLG – A Library Generator for the Exploration and Enumeration of Chemical and Materials Spaces.
        ChemLG is a smart and massive parallel molecular library generator for chemical and materials sciences.
        
        Program Version: 0.3
        
        Release Date: July 4, 2019
        
        With contributions by:
        Janhavi Abhay Dudwadkar (UB): Jupyter GUI
        
        ## Code Design:
        ChemLG is developed in the Python 3 programming language and uses OpenBabel and its Python extension, Pybel for handling molecules. The development follows a strictly modular and object-oriented design to make the overall code as flexible and versatile as possible. ChemLG can be run on a single core or in parallel on multiple cores. For the parallel execution, MPI4Py is also required along with OpenBabel as dependencies of ChemLG.
        
        ## Documentation:
        ChemLG documentation can be found here https://hachmannlab.github.io/chemlg
        
        ## Installation and Dependencies:
        It is highly recommended that a virtual environment is used to run ChemLG. The virtual environment and ChemLG and its dependencies can be installed as:
        
        
            conda create --name my_chemlg_env python=3.6
            source activate my_chemlg_env
            conda install -c openbabel openbabel
            conda install -c anaconda mpi4py
            pip install chemlg
        
        You can test the installation with:
        
            pytest -v
        
        
        
        ## Citation:
        Please cite the use of ChemLG as:
        
        
            (1) Afzal, M. A. F.; Vishwakarma, G.; Dudwadkar, J. A.;Haghighatlari, M.; Hachmann, J. ChemLG– A Library Generator for the Exploration and Enumeration of Chemical and Materials Spaces. 2019; https://github.com/hachmannlab/chemlg
            (2) M.A.F. Afzal, G. Vishwakarma, J. Hachmann, ChemLG – A Molecular and Materials Library Generator for the Enumeration and Exploration of Chemical Space. Available from: https://hachmannlab.github.io/chemlg. 
            (3) J. Hachmann, M.A.F. Afzal, M. Haghighatlari, Y. Pal, Building and Deploying a Cyberinfrastructure for the Data-Driven Design of Chemical Systems and the Exploration of Chemical Space, Mol. Simul. 44 (2018), 921-929. DOI: 10.1080/08927022.2018.1471692
        
        ## Acknowledgement
        ChemLG is based upon work supported by the U.S. National Science Foundation under grant #OAC-1751161. It was also supported by start-up funds provided by UB's School of Engineering and Applied Science and UB's Department of Chemical and Biological Engineering, the New York State Center of Excellence in Materials Informatics through seed grant #1140384-8-75163, and the U.S. Department of Energy under grant #DE-SC0017193.
        
        ## License and Copyright:
        ChemLG is copyright (C) 2015-2018 Johannes Hachmann and Mohammad Atif Faiz Afzal, all rights reserved. 
        ChemLG is distributed under 3-Clause BSD License (https://opensource.org/licenses/BSD-3-Clause).
        
        (C) 2015-2018 Johannes Hachmann, Mohammad Atif Faiz Afzal
        University at Buffalo - The State University of New York (UB)
        Contact: hachmann@buffalo.edu, m27@buffalo.edu
        http://hachmannlab.cbe.buffalo.edu
        
Keywords: Library Generator,Molecular Library,Materials Science,Drug Discovery
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Natural Language :: English
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Provides-Extra: docs
Provides-Extra: tests
