pymatgen.cli.gaussian_analyzer — pymatgen 2020.7.3 documentation

# Source code for pymatgen.cli.gaussian_analyzer

    #!/usr/bin/env python
    #  coding: utf-8
    # Copyright (c) Pymatgen Development Team.
    # Distributed under the terms of the MIT License.

    """
    A convenience script engine to read Gaussian output in a directory tree.
    """

    __author__ = "Shyue Ping Ong"
    __copyright__ = "Copyright 2012, The Materials Project"
    __version__ = "1.0"
    __maintainer__ = "Shyue Ping Ong"
    __email__ = "shyue@mit.edu"
    __date__ = "Jul 9, 2012"

    import argparse
    import os
    import logging
    import re

    from pymatgen.apps.borg.hive import GaussianToComputedEntryDrone
    from pymatgen.apps.borg.queen import BorgQueen
    import multiprocessing
    from tabulate import tabulate

    save_file = "gau_data.gz"

    def get_energies(rootdir, reanalyze, verbose):
        """
        :param rootdir:
        :param reanalyze:
        :param verbose:
        :return:
        """
        if verbose:
            FORMAT = "%(relativeCreated)d msecs : %(message)s"
            logging.basicConfig(level=logging.INFO, format=FORMAT)
        drone = GaussianToComputedEntryDrone(inc_structure=True,
                                             parameters=['filename'])
        ncpus = multiprocessing.cpu_count()
        logging.info('Detected {} cpus'.format(ncpus))
        queen = BorgQueen(drone, number_of_drones=ncpus)
        if os.path.exists(save_file) and not reanalyze:
            msg = 'Using previously assimilated data from {}.'.format(save_file) + \
                  ' Use -f to force re-analysis.'
            queen.load_data(save_file)
        else:
            queen.parallel_assimilate(rootdir)
            msg = 'Results saved to {} for faster reloading.'.format(save_file)
            queen.save_data(save_file)

        entries = queen.get_data()
        entries = sorted(entries, key=lambda x: x.parameters['filename'])
        all_data = [(e.parameters['filename'].replace("./", ""),
                     re.sub(r"\s+", "", e.composition.formula),
                     "{}".format(e.parameters['charge']),
                     "{}".format(e.parameters['spin_mult']),
                     "{:.5f}".format(e.energy), "{:.5f}".format(e.energy_per_atom),
                     ) for e in entries]
        headers = ("Directory", "Formula", "Charge", "Spin Mult.", "Energy",
                   "E/Atom")
        print(tabulate(all_data, headers=headers))
        print("")
        print(msg)

    def main():
        """
        Main function
        """
        desc = '''
        Convenient Gaussian run analyzer which can recursively go into a directory
        to search results.
        Author: Shyue Ping Ong
        Version: 1.0
        Last updated: Jul 6 2012'''

        parser = argparse.ArgumentParser(description=desc)
        parser.add_argument('directories', metavar='dir', default='.', type=str,
                            nargs='*', help='directory to process')
        parser.add_argument('-v', '--verbose', dest="verbose",
                            action='store_const', const=True,
                            help='verbose mode. Provides detailed output ' +
                                 'on progress.')
        parser.add_argument('-f', '--force', dest="reanalyze",
                            action='store_const',
                            const=True,
                            help='force reanalysis. Typically, gaussian_analyzer' +
                                 ' will just reuse a gaussian_analyzer_data.gz if ' +
                                 'present. This forces the analyzer to reanalyze.')

        args = parser.parse_args()
        for d in args.directories:
            get_energies(d, args.reanalyze, args.verbose)

    if __name__ == "__main__":
        main()