default=100, help='How often to sample the trajectory.') parser.add_argument('--n-balls', type=int, default=5, help='Number of balls in the simulation.') parser.add_argument('--noise', type=float, default=0., help='Noise variance.') parser.add_argument('--seed', type=int, default=42, help='Random seed.') args = parser.parse_args() if args.simulation == 'springs': sim = SpringSim(noise_var=args.noise, n_balls=args.n_balls) suffix = '_springs' elif args.simulation == 'charged': sim = ChargedParticlesSim(noise_var=args.noise, n_balls=args.n_balls) suffix = '_charged' else: raise ValueError('Simulation {} not implemented'.format(args.simulation)) suffix += str(args.n_balls) np.random.seed(args.seed) print(suffix) def generate_dataset(num_sims, length, sample_freq): loc_all = list() vel_all = list() edges_all = list()
sim = HspringsV2TreeRandomClusters( n_children=args.n_children, box_size=args.box_size, interaction_strength=args.interaction_strength, structure_config=args.structure_config) dataset_name = 'HspringsV2' elif args.simulation == 'HspringsV3': sim = HspringsV3TreeRandomAllLevels( n_children=args.n_children, box_size=args.box_size, interaction_strength=args.interaction_strength, structure_config=args.structure_config) dataset_name = 'HspringsV3' elif args.simulation == 'charged': sim = ChargedParticlesSim(noise_var=0.0, n_balls=args.n_balls, box_size=args.box_size, interaction_strength=args.interaction_strength) dataset_name = 'charged' else: raise ValueError('Simulation {} not implemented'.format(args.simulation)) # Hierarchical dataset specifics if 'Hsprings' in args.simulation: if args.different_ball_radius: dataset_name += "DBR" if 'Hsprings' in args.simulation: sep = "_%d" for nc in sim.nc: dataset_name += sep % nc # children sep = "-%d" else:
type=str, default="", help='add a sufix to the name') args = parser.parse_args() initial_vel_norm = 0.5 if not args.initial_vel: initial_vel_norm = 1e-16 if args.simulation == 'springs': sim = SpringSim(noise_var=0.0, n_balls=args.n_balls) suffix = '_springs' elif args.simulation == 'charged': sim = ChargedParticlesSim(noise_var=0.0, n_balls=args.n_balls, vel_norm=initial_vel_norm) suffix = '_charged' else: raise ValueError('Simulation {} not implemented'.format(args.simulation)) suffix += str(args.n_balls) + "_initvel%d" % args.initial_vel + args.sufix np.random.seed(args.seed) print(suffix) def generate_dataset(num_sims, length, sample_freq): loc_all = list() vel_all = list() edges_all = list()
default=5.0, help='Size of a surrounding box. If 0, then no box.') args = parser.parse_args() args_dict = vars(args) git_commit = subprocess.check_output(["git", "describe", "--always"]).strip() if args.simulation == 'springs': sim = SpringSim(noise_var=0.0, n_balls=args.n_balls, box_size=args.boxsize, dim=args.dim) suffix = '_springs_' + str(args.dim) + 'D_' elif args.simulation == 'charged': sim = ChargedParticlesSim(noise_var=0.0, n_balls=args.n_balls, box_size=args.boxsize, dim=args.dim) suffix = '_charged_' + str(args.dim) + 'D_' else: raise ValueError('Simulation {} not implemented'.format(args.simulation)) suffix += str(args.n_balls) suffix += '_' + str(args.name) np.random.seed(args.seed) print(suffix) def generate_dataset(num_sims, length, sample_freq): ds = { "points": list(),