if args.seed != -1:
np.random.seed(args.seed)
pi = np.random.permutation(size) if args.seed is not None else np.array(
[i for i in range(size)])
rng = default_rng()
metricList = [Metric.Energy, Metric.Consensus]
state = '$r_{stable}$'
c_len = 'length'
data = {c_len: [], state: [], 'fct': []}
for metric in metricList:
data[metric.name] = []
conf = create_config(c_type, n=args.n)
states = states_per_magnet(size, 0.0)
conf.set_states(states)
for i, p in enumerate(r_factor):
rules = rules_per_ratio(size, p)
conf.set_rules(rules)
evol, metrics = evolve(config=conf,
perm=pi,
steps=args.steps,
metricList=metricList,
cycleBreak=True)
data[c_len].append(cycle_length(evol)[0])
rstab = p / (size - p) if size != p else np.inf
data[state].append(rstab)
data['fct'].append(p)
np.random.seed(args.seed)
pi = np.random.permutation(args.n)
metricList = [Metric.Energy, Metric.Consensus]
magnetList = [0, 0.2, 0.4, 0.6, 0.8]
agree = {
'init_magnet': [],
'length': [],
'Magnetization_mean': [],
'Magnetization_min': [],
'Magnetization_max': [],
'Magnetization_std': [],
'SpinGlass': [],
'unstables': []
}
conf = create_config(ConfigType.Ring, n=args.n)
for i, mag in enumerate(magnetList):
init_states = [State.ON] * round((size * (0.5 + mag / 2)) - 10**
(-9)) + [State.OFF] * round(
(size * (0.5 - mag / 2) + 10**(-9)))
np.random.seed()
np.random.shuffle(init_states)
init_rule = np.array([Rule.STABLE] * size)
curr_rule = init_rule
conf.set_rules(init_rule)
conf.set_states(init_states)
curr_magnet = mag
stables = [0]
while curr_magnet < 1 and stables != []:
array, out = evolve(conf,
np.random.seed(args.seed)
pi = np.random.permutation(size)
metricList = [Metric.Energy, Metric.Consensus]
magnetList = [0, 0.2, 0.4, 0.6, 0.8]
agree = {
'init_magnet': [],
'length': [],
'Magnetization_mean': [],
'Magnetization_min': [],
'Magnetization_max': [],
'Magnetization_std': [],
'SpinGlass': [],
'unstables': []
}
conf = create_config(ConfigType.Torus, n=args.n)
rng = default_rng()
for i, mag in enumerate(magnetList):
init_states = [State.ON] * round((size * (0.5 + mag / 2)) - 10**
(-9)) + [State.OFF] * round(
(size * (0.5 - mag / 2) + 10**(-9)))
rng.shuffle(init_states)
init_rule = np.array([Rule.STABLE] * size)
curr_rule = init_rule
conf.set_rules(init_rule)
conf.set_states(init_states)
curr_magnet = mag
stables = [0]
while curr_magnet < 1 and stables != []:
type=int,
default=0,
help='first majority preference')
parser.add_argument("-s",
'--second',
type=int,
default=1,
help='second majority preference')
args = parser.parse_args()
assert (args.first != args.second)
size = args.n**2
c_type = ConfigType.Torus
config = create_config(configType=c_type, n=args.n)
magnetList = [-0.4, -0.3, -0.2, -0.1]
stabList = [0.0, 0.2, 0.4, 0.5, 0.6, 0.8]
pi = np.random.permutation(size)
rules, metrics = setup()
le = 'length'
out = {
'init_magnet': [],
'Energy': [],
'Density': [],
'order': [],
'init_stab': [],
le: []
}