def _set_optimization_variables_initials(self, pinit, xinit):
xinit = inputchecks.check_states_data(xinit, \
self._discretization.system.nx, \
self._discretization.number_of_intervals)
repretitions_xinit = \
self._discretization.optimization_variables["X"][:,:-1].shape[1] / \
self._discretization.number_of_intervals
Xinit = ci.repmat(xinit[:, :-1], repretitions_xinit, 1)
Xinit = ci.horzcat([ \
Xinit.reshape((self._discretization.system.nx, \
Xinit.size() / self._discretization.system.nx)),
xinit[:, -1],
])
pinit = inputchecks.check_parameter_data(pinit, \
self._discretization.system.np)
Pinit = pinit
Vinit = np.zeros(self._discretization.optimization_variables["V"].shape)
EPS_Uinit = np.zeros( \
self._discretization.optimization_variables["EPS_U"].shape)
self._optimization_variables_initials = ci.veccat([ \
Pinit,
Xinit,
EPS_Uinit,
Vinit,
])
def __generate_simulation_ode(self, pdata, qdata):
p = inputchecks.check_parameter_data(pdata, self.__system.np)
q = inputchecks.check_constant_controls_data(qdata, self.__system.nq)
ode_fcn = ci.mx_function("ode_fcn", \
[self.__system.u, self.__system.q, self.__system.x, \
self.__system.eps_u, self.__system.p], \
[self.__system.f])
# Needs to be changes for allowance of explicit time dependecy!
self.__ode_parameters_applied = ode_fcn.call([ \
self.__system.u, q, self.__system.x, \
np.zeros(self.__system.neps_u), p])[0]
def __generate_simulation_ode(self, pdata, qdata):
p = inputchecks.check_parameter_data(pdata, self.__system.np)
q = inputchecks.check_constant_controls_data(qdata, self.__system.nq)
ode_fcn = ci.mx_function(
"ode_fcn",
[self.__system.u, self.__system.q, self.__system.x, self.__system.eps_u, self.__system.p],
[self.__system.f],
)
# Needs to be changes for allowance of explicit time dependency!
self.__ode_parameters_applied = ode_fcn(
[self.__system.u, q, self.__system.x, np.zeros(self.__system.neps_u), p]
)[0]
def _set_optimization_variables_initials(self, pinit, xinit):
xinit = inputchecks.check_states_data(xinit, \
self._discretization.system.nx, \
self._discretization.number_of_intervals)
repretitions_xinit = \
self._discretization.optimization_variables["X"][:,:-1].shape[1] / \
self._discretization.number_of_intervals
Xinit = ci.repmat(xinit[:, :-1], repretitions_xinit, 1)
Xinit = ci.horzcat([ \
Xinit.reshape((self._discretization.system.nx, \
Xinit.numel() / self._discretization.system.nx)),
xinit[:, -1],
])
pinit = inputchecks.check_parameter_data(pinit, \
self._discretization.system.np)
Pinit = pinit
Vinit = np.zeros(
self._discretization.optimization_variables["V"].shape)
EPS_Uinit = np.zeros( \
self._discretization.optimization_variables["EPS_U"].shape)
self._optimization_variables_initials = ci.veccat([ \
Pinit,
Xinit,
Vinit,
EPS_Uinit,
])
def _set_parameter_guess(self, pdata):
self._pdata = inputchecks.check_parameter_data(pdata, \
self._discretization.system.np)
def _set_parameter_guess(self, pdata):
self._pdata = inputchecks.check_parameter_data(pdata, \
self._discretization.system.np)