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 charges from the HDF5 file
charges = load_charges(args.charges)
# Load the uniform grid and the coordintes
ugrid, coordinates = load_ugrid_coordinates(args.grid)
ugrid.pbc[:] = 1 # enforce 3D periodic
# 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()
# Determine the grid specification
results['ugrid'] = ugrid
# Ewald parameters
rcut, alpha, gcut = parse_ewald_args(args)
# Some screen info
if log.do_medium:
log('Important parameters:')
log.hline()
log('Number of grid points: %12i' % ugrid.size)
log('Grid shape: [%8i, %8i, %8i]' % tuple(ugrid.shape))
log('Ewald real cutoff: %12.5e' % rcut)
log('Ewald alpha: %12.5e' % alpha)
log('Ewald reciprocal cutoff: %12.5e' % gcut)
log.hline()
# TODO: add summation ranges
log('Computing ESP (may take a while)')
# Allocate and compute ESP grid
esp = np.zeros(ugrid.shape, float)
compute_esp_grid_cube(ugrid, esp, coordinates, charges, rcut, alpha, gcut)
results['esp'] = esp
# Store the results in an HDF5 file
write_script_output(fn_h5, grp_name, results, args)
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 charges from the HDF5 file
charges = load_charges(args.charges)
# Load the uniform grid and the coordintes
ugrid, coordinates = load_ugrid_coordinates(args.grid)
ugrid.pbc[:] = 1 # enforce 3D periodic
# 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()
# Determine the grid specification
results['ugrid'] = ugrid
# Ewald parameters
rcut, alpha, gcut = parse_ewald_args(args)
# Some screen info
if log.do_medium:
log('Important parameters:')
log.hline()
log('Number of grid points: %12i' % ugrid.size)
log('Grid shape: [%8i, %8i, %8i]' % tuple(ugrid.shape))
log('Ewald real cutoff: %12.5e' % rcut)
log('Ewald alpha: %12.5e' % alpha)
log('Ewald reciprocal cutoff: %12.5e' % gcut)
log.hline()
# TODO: add summation ranges
log('Computing ESP (may take a while)')
# Allocate and compute ESP grid
esp = np.zeros(ugrid.shape, float)
compute_esp_grid_cube(ugrid, esp, coordinates, charges, rcut, alpha, gcut)
results['esp'] = esp
# Store the results in an HDF5 file
write_script_output(fn_h5, grp_name, results, args)
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)
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)
