def __init__(self, costs, t_s=1):
"""
Class constructor.
Creates the dynamic cost, optionally using the specified sampling
time `t_s`.
Parameters
----------
costs : list
The sequence of static costs.
t_s : float, optional
The sampling time, that is, the time that elapses between two
consecutive costs. The default is 1.
Notes
-----
The costs are implicitly assumed to have the same domain and to be
static.
"""
# create time domain
time = sets.T(t_s, t_min=0, t_max=len(costs) * t_s)
super().__init__(costs[0].dom, time)
self.costs, self.N = costs, len(costs)
self.smooth = min([c.smooth for c in costs])
def __init__(self, nets, t_s=1):
"""
Class constructor.
Parameters
----------
nets : list
A list of the networks over time.
t_s : float, optional
The time after which the network changes to the next configuration.
"""
# create time domain
self.time = sets.T(t_s, t_min=0, t_max=len(nets)*t_s)
# store networks
self.nets, self.N = nets, len(nets)
def __init__(self, t_s, t_max):
super().__init__(sets.R(2, 1), sets.T(t_s, t_max=t_max))
self.smooth = 2
def __init__(self, t_s, t_max, omega=0.02 * math.pi, kappa=7.5, mu=1.75):
super().__init__(sets.R(), sets.T(t_s, t_max=t_max))
self.omega, self.kappa, self.mu = omega, kappa, mu
self.smooth = 2