def get_gamma_G(self, K):
robot_ids = Set([e.id for e in self.robots])
task_ids = Set([e.id for e in self.tasks])
V = Set.descartes_product(robot_ids, task_ids)
V_K = Set([Set(e) for e in itertools.combinations(V, K)])
print("...Calculating gamma_G...")
gamma_G = float('inf')
N = len(self.history) * len(V_K)
progress_bar = ProgressBar(N)
instrument = Instrument()
instrument.start()
k = 0
for t in range(len(self.history)):
S_t = Allocation(self.history[0:t])
for Omega in V_K:
progress_bar.progress(k)
k = k + 1
lhs = 0
for omega in Omega.setminus(Set(S_t)):
lhs = lhs + S_t.get_derivative(Set([omega]))
rhs = S_t.get_derivative(Omega)
frac = rhs / lhs
if frac < gamma_G and rhs != 0 and lhs != 0:
gamma_G = frac
progress_bar.progress(N, 'Finished!\n')
calculation_time = instrument.stop()
print("Calculation time [s]:", calculation_time)
print("Finished calculating gamma_G!\n")
return gamma_G
def get_alpha_G(self, K):
robot_ids = Set([e.id for e in self.robots])
task_ids = Set([e.id for e in self.tasks])
V = Set.descartes_product(robot_ids, task_ids)
V_K = Set([Set(e) for e in itertools.combinations(V, K)])
S_K = self.history
S_K_1 = Set(self.history[:-1])
print("...Calculating alpha_G...")
alpha_G = -float('inf')
N = len(V_K)
progress_bar = ProgressBar(N)
instrument = Instrument()
instrument.start()
k = 0
for Omega in V_K:
progress_bar.progress(k)
k = k + 1
for j_i in S_K_1.setminus(Omega):
i = S_K.index(j_i)
S_i_1 = Allocation(self.history[0:i])
lhs = Allocation(S_i_1.union(Omega)).get_derivative(Set([j_i]))
rhs = S_i_1.get_derivative(Set([j_i]))
frac = (lhs - rhs) / lhs
if frac > alpha_G and rhs != 0 and lhs != 0:
alpha_G = frac
progress_bar.progress(N, 'Finished!\n')
calculation_time = instrument.stop()
print("Calculation time [s]:", calculation_time)
print("Finished calculating alpha_G!\n")
return alpha_G
def __init__(self, path_planner):
self.Q = path_planner.Q
self.X = path_planner.X
QX = Set.descartes_product(self.Q, self.X)
super(QX_set, self).__init__(QX)
