def map(self, sol: Solution, lam=empty_array, nu=empty_array) -> Solution:
# sol.lam = lam
if len(sol.nu) == 0:
sol.nu = np.ones(self.nu_len)
return sol
def inv_map(self, sol: Solution, retain_dual=True) -> Solution:
if not retain_dual:
sol.lam = empty_array
sol.nu = empty_array
sol.cost = self.compute_cost(sol.t, sol.y, sol.q, sol.u, sol.p, sol.k)
return sol
def scale_sol(sol: Trajectory, scale_factors, inv=False):
sol = copy.deepcopy(sol)
if inv:
op = np.multiply
else:
op = np.divide
sol.t = op(sol.t, scale_factors[0])
sol.y = op(sol.y, scale_factors[1])
sol.q = op(sol.q, scale_factors[2])
if sol.u.size > 0:
sol.u = op(sol.u, scale_factors[3])
sol.p = op(sol.p, scale_factors[4])
sol.nu = op(sol.nu, scale_factors[5])
sol.k = op(sol.k, scale_factors[6])
return sol
def inv_map(self, sol: Solution) -> Solution:
sol.lam = sol.y[:, self.costate_idxs]
sol.y = np.delete(sol.y, self.costate_idxs, axis=1)
sol.nu = np.delete(sol.nu, self.constraint_adjoints_idxs)
return sol
