コード例 #1
0
def main():
    args = parse_args()

    fn_h5, grp_name = parse_h5(args.output, 'output')
    # check if the group is already present (and not empty) in the output file
    if check_output(fn_h5, grp_name, args.overwrite):
        return

    # Load the cost function from the HDF5 file
    cost, used_volume = load_cost(args.cost)

    # Find the optimal charges
    results = {}
    results['x'] = cost.solve(args.qtot, args.ridge)
    results['charges'] = results['x'][:cost.natom]

    # Related properties
    results['cost'] = cost.value(results['x'])
    if results['cost'] < 0:
        results['rmsd'] = 0.0
    else:
        results['rmsd'] = (results['cost'] / used_volume)**0.5

    # Worst case stuff
    results['cost_worst'] = cost.worst(0.0)
    if results['cost_worst'] < 0:
        results['rmsd_worst'] = 0.0
    else:
        results['rmsd_worst'] = (results['cost_worst'] / used_volume)**0.5

    # Write some things on screen
    if log.do_medium:
        log('Important parameters:')
        log.hline()
        log('RMSD charges:                  %10.5e' % np.sqrt(
            (results['charges']**2).mean()))
        log('RMSD ESP:                      %10.5e' % results['rmsd'])
        log('Worst RMSD ESP:                %10.5e' % results['rmsd_worst'])
        log.hline()

    # Perform a symmetry analysis if requested
    if args.symmetry is not None:
        mol_pot = IOData.from_file(args.symmetry[0])
        mol_sym = IOData.from_file(args.symmetry[1])
        if not hasattr(mol_sym, 'symmetry'):
            raise ValueError('No symmetry information found in %s.' %
                             args.symmetry[1])
        aim_results = {'charges': results['charges']}
        sym_results = symmetry_analysis(mol_pot.coordinates, mol_pot.cell,
                                        mol_sym.symmetry, aim_results)
        results['symmetry'] = sym_results

    # Store the results in an HDF5 file
    write_script_output(fn_h5, grp_name, results, args)
コード例 #2
0
ファイル: horton-esp-fit.py プロジェクト: rmcgibbo/horton
def main():
    args = parse_args()

    fn_h5, grp_name = parse_h5(args.output, 'output')
    # check if the group is already present (and not empty) in the output file
    if check_output(fn_h5, grp_name, args.overwrite):
        return

    # Load the cost function from the HDF5 file
    cost, used_volume = load_cost(args.cost)

    # Find the optimal charges
    results = {}
    results['x'] = cost.solve(args.qtot, args.ridge)
    results['charges'] = results['x'][:cost.natom]

    # Related properties
    results['cost'] = cost.value(results['x'])
    if results['cost'] < 0:
        results['rmsd'] = 0.0
    else:
        results['rmsd'] = (results['cost']/used_volume)**0.5

    # Worst case stuff
    results['cost_worst'] = cost.worst(0.0)
    if results['cost_worst'] < 0:
        results['rmsd_worst'] = 0.0
    else:
        results['rmsd_worst'] = (results['cost_worst']/used_volume)**0.5

    # Write some things on screen
    if log.do_medium:
        log('Important parameters:')
        log.hline()
        log('RMSD charges:                  %10.5e' % np.sqrt((results['charges']**2).mean()))
        log('RMSD ESP:                      %10.5e' % results['rmsd'])
        log('Worst RMSD ESP:                %10.5e' % results['rmsd_worst'])
        log.hline()

    # Perform a symmetry analysis if requested
    if args.symmetry is not None:
        sys = System.from_file(args.symmetry[0])
        sys_sym = System.from_file(args.symmetry[1])
        sym = sys_sym.extra.get('symmetry')
        if sym is None:
            raise ValueError('No symmetry information found in %s.' % args.symmetry[1])
        sys_results = {'charges': results['charges']}
        sym_results = symmetry_analysis(sys, sym, sys_results)
        results['symmetry'] = sym_results
        sys.extra['symmetry'] = sym

    # Store the results in an HDF5 file
    write_script_output(fn_h5, grp_name, results, args)
コード例 #3
0
ファイル: horton-esp-test.py プロジェクト: susilehtola/horton
def main():
    args = parse_args()

    fn_h5, grp_name = parse_h5(args.output, 'output')
    # check if the group is already present (and not empty) in the output file
    if check_output(fn_h5, grp_name, args.overwrite):
        return

    # Load the cost function from the HDF5 file
    cost, used_volume = load_cost(args.cost)

    # Load the charges from the HDF5 file
    charges = load_charges(args.charges)

    # Fix total charge if requested
    if args.qtot is not None:
        charges -= (charges.sum() - args.qtot) / len(charges)

    # Store parameters in output
    results = {}
    results['qtot'] = charges.sum()

    # Fitness of the charges
    results['cost'] = cost.value_charges(charges)
    if results['cost'] < 0:
        results['rmsd'] = 0.0
    else:
        results['rmsd'] = (results['cost'] / used_volume)**0.5

    # Worst case stuff
    results['cost_worst'] = cost.worst(0.0)
    if results['cost_worst'] < 0:
        results['rmsd_worst'] = 0.0
    else:
        results['rmsd_worst'] = (results['cost_worst'] / used_volume)**0.5

    # Write some things on screen
    if log.do_medium:
        log('RMSD charges:                  %10.5e' % np.sqrt(
            (charges**2).mean()))
        log('RMSD ESP:                      %10.5e' % results['rmsd'])
        log('Worst RMSD ESP:                %10.5e' % results['rmsd_worst'])
        log.hline()

    # Store the results in an HDF5 file
    write_script_output(fn_h5, grp_name, results, args)
コード例 #4
0
def main():
    args = parse_args()

    fn_h5, grp_name = parse_h5(args.output, 'output')
    # check if the group is already present (and not empty) in the output file
    if check_output(fn_h5, grp_name, args.overwrite):
        return

    # Load the cost function from the HDF5 file
    cost, used_volume = load_cost(args.cost)

    # Find the optimal charges
    results = {}

    # MODIFICATION HERE

    results['x'] = cost.solve(args.qtot, args.ridge)
    results['charges'] = results['x'][:cost.natom]

    # Related properties
    results['cost'] = cost.value(results['x'])
    if results['cost'] < 0:
        results['rmsd'] = 0.0
    else:
        results['rmsd'] = (results['cost'] / used_volume)**0.5

    # Worst case stuff
    results['cost_worst'] = cost.worst(0.0)
    if results['cost_worst'] < 0:
        results['rmsd_worst'] = 0.0
    else:
        results['rmsd_worst'] = (results['cost_worst'] / used_volume)**0.5

    # Write some things on screen
    if log.do_medium:
        log('Important parameters:')
        log.hline()
        log('RMSD charges:                  %10.5e' % np.sqrt(
            (results['charges']**2).mean()))
        log('RMSD ESP:                      %10.5e' % results['rmsd'])
        log('Worst RMSD ESP:                %10.5e' % results['rmsd_worst'])
        log.hline()

    # Store the results in an HDF5 file
    write_script_output(fn_h5, grp_name, results, args)
コード例 #5
0
ファイル: horton-esp-test.py プロジェクト: FarnazH/hortonqa
def main():
    args = parse_args()

    fn_h5, grp_name = parse_h5(args.output, 'output')
    # check if the group is already present (and not empty) in the output file
    if check_output(fn_h5, grp_name, args.overwrite):
        return

    # Load the cost function from the HDF5 file
    cost, used_volume = load_cost(args.cost)

    # Load the charges from the HDF5 file
    charges = load_charges(args.charges)

    # Fix total charge if requested
    if args.qtot is not None:
        charges -= (charges.sum() - args.qtot)/len(charges)

    # Store parameters in output
    results = {}
    results['qtot'] = charges.sum()

    # Fitness of the charges
    results['cost'] = cost.value_charges(charges)
    if results['cost'] < 0:
        results['rmsd'] = 0.0
    else:
        results['rmsd'] = (results['cost']/used_volume)**0.5

    # Worst case stuff
    results['cost_worst'] = cost.worst(0.0)
    if results['cost_worst'] < 0:
        results['rmsd_worst'] = 0.0
    else:
        results['rmsd_worst'] = (results['cost_worst']/used_volume)**0.5

    # Write some things on screen
    if log.do_medium:
        log('RMSD charges:                  %10.5e' % np.sqrt((charges**2).mean()))
        log('RMSD ESP:                      %10.5e' % results['rmsd'])
        log('Worst RMSD ESP:                %10.5e' % results['rmsd_worst'])
        log.hline()

    # Store the results in an HDF5 file
    write_script_output(fn_h5, grp_name, results, args)
コード例 #6
0
def main():
    args = parse_args()

    fn_h5, grp_name = parse_h5(args.output, 'output')
    # check if the group is already present (and not empty) in the output file
    if check_output(fn_h5, grp_name, args.overwrite):
        return

    # Load the cost function from the HDF5 file
    cost, used_volume = load_cost(args.cost)

    # Find the optimal charges
    results = {}
    results['x'] = cost.solve(args.qtot, args.ridge)
    results['charges'] = results['x'][:cost.natom]

    # Related properties
    results['cost'] = cost.value(results['x'])
    if results['cost'] < 0:
        results['rmsd'] = 0.0
    else:
        results['rmsd'] = (results['cost']/used_volume)**0.5

    # Worst case stuff
    results['cost_worst'] = cost.worst(0.0)
    if results['cost_worst'] < 0:
        results['rmsd_worst'] = 0.0
    else:
        results['rmsd_worst'] = (results['cost_worst']/used_volume)**0.5

    # Write some things on screen
    if log.do_medium:
        log('Important parameters:')
        log.hline()
        log('RMSD charges:                  %10.5e' % np.sqrt((results['charges']**2).mean()))
        log('RMSD ESP:                      %10.5e' % results['rmsd'])
        log('Worst RMSD ESP:                %10.5e' % results['rmsd_worst'])
        log.hline()

    # Store the results in an HDF5 file
    write_script_output(fn_h5, grp_name, results, args)