pendulum = importlib.util.module_from_spec(spec)
spec.loader.exec_module(pendulum)
ocp = pendulum.prepare_ocp(
biorbd_model_path="pendulum.bioMod",
final_time=2,
number_shooting_points=10,
nb_threads=2,
)
X = InitialGuess([0, 0, 0, 0])
U = InitialGuess([-1, 1])
# --- Single shooting --- #
sol_simulate_single_shooting = Simulate.from_controls_and_initial_states(
ocp, X, U, single_shoot=True)
result_single = ShowResult(ocp, sol_simulate_single_shooting)
result_single.graphs()
# --- Multiple shooting --- #
sol_simulate_multiple_shooting = Simulate.from_controls_and_initial_states(
ocp, X, U, single_shoot=False)
result_multiple = ShowResult(ocp, sol_simulate_multiple_shooting)
result_multiple.graphs()
# --- Single shooting --- #
result_single.animate()
# --- Multiple shooting --- #
result_multiple.animate()
print("Results using ACADOS")
print(f"Final objective: {np.nansum(sol_obj_acados)}")
analyse_acados = ObjectivePrinter(ocp_acados, sol_obj_acados)
analyse_acados.by_function()
print(f"Time to solve: {sol_acados['time_tot']}sec")
print(f"")
print(
f"Results using Ipopt{'' if warm_start_ipopt_from_acados_solution else ' not'} "
f"warm started from ACADOS solution"
)
print(f"Final objective : {np.nansum(sol_obj_ipopt)}")
analyse_ipopt = ObjectivePrinter(ocp_ipopt, sol_obj_ipopt)
analyse_ipopt.by_function()
print(f"Time to solve: {sol_ipopt['time_tot']}sec")
print(f"")
result_acados = ShowResult(ocp_acados, sol_acados)
result_ipopt = ShowResult(ocp_ipopt, sol_ipopt)
visualizer = result_acados.animate(show_now=False)
visualizer.extend(result_ipopt.animate(show_now=False))
# Update biorbd-viz by hand so they can be visualized simultaneously
should_continue = True
while should_continue:
for i, b in enumerate(visualizer):
if b.vtk_window.is_active:
b.update()
else:
should_continue = False
# ------------- #
return OptimalControlProgram(
biorbd_model,
dynamics,
number_shooting_points,
final_time,
x_init,
u_init,
x_bounds,
u_bounds,
objective_functions,
constraints,
ode_solver=ode_solver,
)
if __name__ == "__main__":
ocp = prepare_ocp("cube.bioMod",
number_shooting_points=30,
final_time=2,
use_actuators=False)
# --- Solve the program --- #
sol = ocp.solve(show_online_optim=True)
# --- Show results --- #
result = ShowResult(ocp, sol)
result.animate()
return OptimalControlProgram(
biorbd_model,
dynamics,
number_shooting_points,
phase_time,
x_init,
u_init,
x_bounds,
u_bounds,
objective_functions,
tau_mapping=tau_mapping,
)
if __name__ == "__main__":
model_path = "2segments_4dof_2contacts.bioMod"
t = 0.5
ns = 20
ocp = prepare_ocp(model_path=model_path,
phase_time=t,
number_shooting_points=ns,
use_actuators=False)
# --- Solve the program --- #
sol = ocp.solve(show_online_optim=True)
# --- Show results --- #
result = ShowResult(ocp, sol)
result.animate(nb_frames=40)
u_init = InitialGuessList()
u_init.add([tau_init] * biorbd_model.nbGeneralizedTorque() +
[muscle_init] * biorbd_model.nbMuscleTotal())
# ------------- #
return OptimalControlProgram(
biorbd_model,
dynamics,
number_shooting_points,
final_time,
x_init,
u_init,
x_bounds,
u_bounds,
objective_functions,
)
if __name__ == "__main__":
ocp = prepare_ocp(biorbd_model_path="arm26_with_contact.bioMod",
final_time=2,
number_shooting_points=20)
# --- Solve the program --- #
sol = ocp.solve(show_online_optim=True)
# --- Show results --- #
result = ShowResult(ocp, sol)
result.animate(show_meshes=False)
result.graphs()
def main(args=None):
init = None
if args:
init = args[:-1]
pwd = args[-1]
save_path = "2p_init_"+str(init[0])+"_"+str(init[1])+"_"+str(init[2])+"_"+str(init[3])+"_sol.bo"
if os.path.exists(save_path):
return
model_path = (
"../models/jumper2contacts.bioMod",
"../models/jumper1contacts.bioMod",
)
time_min = [0.2, 0.05]
time_max = [0.5, 1]
phase_time = [0.6, 0.2]
number_shooting_points = [30, 15]
tic = time()
ocp = prepare_ocp(
model_path=model_path,
phase_time=phase_time,
ns=number_shooting_points,
time_min=time_min,
time_max=time_max,
init=init,
)
sol = ocp.solve(
show_online_optim=False,
solver_options={"hessian_approximation": "limited-memory", "max_iter": 200}
)
utils.warm_start_nmpc(sol, ocp)
ocp.solver.set_lagrange_multiplier(sol)
sol = ocp.solve(
show_online_optim=True,
solver_options={"hessian_approximation": "exact",
"max_iter": 1000,
"warm_start_init_point": "yes",
}
)
toc = time() - tic
print(f"Time to solve : {toc}sec")
if init:
ocp.save(sol, save_path)
ocp.save_get_data(sol, save_path + 'b')
ssh = SSHClient()
ssh.load_system_host_keys()
ssh.connect('pariterre.net', username='******', password=pwd)
with SCPClient(ssh.get_transport()) as scp:
scp.put(save_path, save_path)
scp.get(save_path)
scp.put(save_path + 'b', save_path + 'b')
scp.get(save_path + 'b')
result = ShowResult(ocp, sol)
result.animate(nb_frames=241)
ocp = prepare_ocp(
model_path=model_path,
phase_time=phase_time,
ns=number_shooting_points,
time_min=time_min,
time_max=time_max,
)
sol = ocp.solve(show_online_optim=False,
solver_options={
"hessian_approximation": "limited-memory",
"max_iter": 200
})
utils.warm_start_nmpc(sol, ocp)
ocp.solver.set_lagrange_multiplier(sol)
sol = ocp.solve(show_online_optim=True,
solver_options={
"hessian_approximation": "exact",
"max_iter": 1000,
"warm_start_init_point": "yes",
})
toc = time() - tic
print(f"Time to solve : {toc}sec")
result = ShowResult(ocp, sol)
result.animate(nb_frames=241)
dynamics,
number_shooting_points,
final_time,
x_init,
u_init,
x_bounds,
u_bounds,
objective_functions,
nb_integration_steps=5,
control_type=control_type,
ode_solver=ode_solver,
)
if __name__ == "__main__":
ocp = prepare_ocp(
biorbd_model_path="cube_and_line.bioMod",
number_shooting_points=30,
final_time=2,
marker_velocity_or_displacement="disp", # "velo"
marker_in_first_coordinates_system=True,
control_type=ControlType.LINEAR_CONTINUOUS,
)
# --- Solve the program --- #
sol = ocp.solve(show_online_optim=True)
# --- Show results --- #
result = ShowResult(ocp, sol)
result.animate(nb_frames=200)
