def linear_param_bvp(linear_param_dae, param_vars):
def initial_value(p):
return jnp.array([p, 2., 1.])
t = Time(0., 1., time_grid=np.linspace(0., 1., 10))
return ParameterInitialValueProblem(*param_vars, initial_value, t,
linear_param_dae, 1)
def linear_param_bvp(linear_param_dae, param_vars):
initial_value = lambda p: jnp.array([[1., 0.], [0., 0.]]) # noqa: E731
final_value = lambda p: jnp.array([[0., 0.], [1., 0.]]) # noqa: E731
inhomogeneity = lambda p: jnp.array([0., p]) # noqa: E731
t = Time(0., np.pi / 2., time_grid=np.linspace(0., np.pi / 2., 10))
bvs = ParameterBoundaryValues(*param_vars, initial_value, final_value,
inhomogeneity, 2)
return ParameterBoundaryValueProblem(*param_vars, t, linear_param_dae, bvs)
def test_solve_localized(self, localized_bvp, localized_ivp,
localized_flow_prob):
nodes = np.linspace(0, 1, 3)
stepsize = 1e-4
time_interval = Time(0., 1., time_grid=np.linspace(0., 1., 10))
localized_bvp.init_solver(localized_flow_prob, localized_ivp, nodes,
stepsize)
localized_bvp.solve(time_interval)
def initial_value_problem(linear_dae):
initial_value = np.array([1., 2.])
time_interval = Time(0., 1.)
return InitialValueProblem(initial_value, time_interval, linear_dae)
def flow_problem(linear_dae):
time_interval = Time(0., 1.)
flowprob = LinearFlow(time_interval, linear_dae)
return flowprob
def variables3():
loc_vars = InputStateVariables(2, 1, time=Time(0., 2.))
hl_vars = ParameterContainer(2, domain=RNDomain(1))
return hl_vars, loc_vars
def localized_ivp(localized_bvp):
time_interval = Time(0., 1.)
ivp = InitialValueProblem(np.zeros(2), time_interval,
localized_bvp.dynamical_system)
return ivp
def localized_flow_prob(localized_bvp):
time_interval = Time(0., 1.)
flowprob = LinearFlow(time_interval, localized_bvp.dynamical_system)
return flowprob
def pdoc_objective(q, s, r, m, variables2):
time = Time(0., 2.)
return ParameterLQRObjective(*variables2, time, q, s, r, m)
def pdoc_objective_2(q_2, s_2, r, m_2, variables3):
time = Time(0., 2.)
return ParameterLQRObjective(*variables3, time, q_2, s_2, r, m_2)
def pdoc_objective_3(q_3, s_3, r, m_3, variables3):
time = Time(0., 2.)
return ParameterLQRObjective(*variables3, time, q_3, s_3, r, m_3)
def bvp(linear_dae, boundary_values):
time_interval = Time(0., 1.)
return BoundaryValueProblem(time_interval, linear_dae, boundary_values)