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(),