parser.add_argument(
'-t',
'--type_offset',
type=int,
default=0,
help=
'the type offset for the rod models of the simulation (for cluster data)')
parser.add_argument('-n',
'--every',
type=int,
default=1,
help='every which snapshot to analyse (for cluster data')
args = parser.parse_args()
model = rods.Rod_model(rods.Rod_params().from_file(args.config_file))
for in_file in args.in_files:
raw_data = rods_tools.parse_dump_file(in_file)
_, _, data_structure, _ = next(raw_data)
del raw_data
if args.cluster_data:
if 'c_micelle_ID' in data_structure:
timesteps, box_sizes, cluster_data = rods_tools.clusters.get_cluster_data(
rods_tools.parse_dump_file(in_file), 'micelle_ID', args.every,
model, args.type_offset)
micelle_output_path = os.path.splitext(
if mpi_rank == 0:
py_lmp = PyLammps(cmdargs=['-echo', 'both'],
comm=mpi_comm,
verbose=args.verbose)
else:
py_lmp = PyLammps(cmdargs=['-echo', 'both'], comm=mpi_comm)
py_lmp.log('"' + log_path + '"')
rod_params = rods.Rod_params()
if mpi_rank == 0:
rod_params.from_file(args.cfg_file)
rod_params = mpi_comm.bcast(rod_params, root=0)
# CREATE BASE OBJECTS
model = rods.Rod_model(rod_params)
simulation = rods.Simulation(py_lmp, model, run_args.temp, seed, output_folder)
py_lmp.units("lj")
py_lmp.dimension(3)
py_lmp.boundary("p p p")
py_lmp.lattice("sc", 1 / (run_args.cell_size**3))
py_lmp.region("box", "block", -run_args.num_cells / 2, run_args.num_cells / 2,
-run_args.num_cells / 2, run_args.num_cells / 2,
-run_args.num_cells / 2, run_args.num_cells / 2)
simulation.setup("box")
simulation.create_rods(box=None)
# ROD DYNAMICS
py_lmp.fix("thermostat", "all", "langevin", run_args.temp, run_args.temp,
run_args.damp, seed) #, "zero yes")
parser.add_argument('-c', '--cluster_data', action='store_true',
help='produce a "_micelle_data" and/or a "_fibril_data" file for each input file')
parser.add_argument('-l', '--last_dump', action='store_true',
help='produce a "_last_dump" file, containing the last snapshot, for each input file')
parser.add_argument('-m', '--membrane', action='store_true',
help='produce an "_adsorbed" file for each input file')
parser.add_argument('-t', '--type_offset', type=int, default=0,
help='the type offset for the rod models of the simulation (for cluster data)')
parser.add_argument('-n', '--every', type=int, default=1,
help='every which snapshot to analyse (for cluster data')
args = parser.parse_args()
model = rods.Rod_model(args.config_file)
for in_file in args.in_files:
raw_data = rods_tools.parse_dump_file(in_file)
_, _, data_structure, _ = next(raw_data)
del raw_data
if args.cluster_data:
if 'c_micelle_ID' in data_structure:
timesteps, box_sizes, cluster_data = rods_tools.clusters.get_cluster_data(
rods_tools.parse_dump_file(in_file), 'micelle_ID',
args.every, model, args.type_offset)
micelle_output_path = os.path.splitext(in_file)[0]+"_micelle_data"
log_filename = '{:d}.lammps'.format(seed)
log_path = os.path.join(output_folder, log_filename)
run_args = rods.rod_model.Params()
execfile(args.run_file, {
'__builtins__': None,
'True': True,
'False': False,
'None': None
}, vars(run_args))
out_freq = args.output_freq if args.output_freq != None else run_args.run_length
py_lmp = PyLammps(cmdargs=['-screen', 'none'])
py_lmp.log('"' + log_path + '"')
model = rods.Rod_model(args.cfg_file)
simulation = rods.Simulation(py_lmp, model, seed, output_folder)
py_lmp.units("lj")
py_lmp.dimension(3)
py_lmp.boundary("p p p")
py_lmp.lattice("sc", 1 / (run_args.cell_size**3))
py_lmp.region("box", "block", -run_args.num_cells / 2, run_args.num_cells / 2,
-run_args.num_cells / 2, run_args.num_cells / 2,
-run_args.num_cells / 2, run_args.num_cells / 2)
simulation.setup("box")
simulation.create_rods(box=None)
# DYNAMICS
py_lmp.fix("thermostat", "all", "langevin", run_args.temp, run_args.temp,
run_args.damp, seed) #, "zero yes")