def test_plot_graphs_multi_phases():
# Load graphs_one_phase
PROJECT_FOLDER = Path(__file__).parent / ".."
spec = importlib.util.spec_from_file_location(
"align_markers",
str(PROJECT_FOLDER) +
"/examples/torque_driven_ocp/multiphase_align_markers.py")
graphs_multi_phases = importlib.util.module_from_spec(spec)
spec.loader.exec_module(graphs_multi_phases)
ocp = graphs_multi_phases.prepare_ocp(
biorbd_model_path=str(PROJECT_FOLDER) +
"/examples/torque_driven_ocp/cube.bioMod")
sol = ocp.solve()
plt = ShowResult(ocp, sol)
plt.graphs(automatically_organize=False)
def test_plot_graphs_one_phase():
# Load graphs_one_phase
PROJECT_FOLDER = Path(__file__).parent / ".."
spec = importlib.util.spec_from_file_location(
"align_markers",
str(PROJECT_FOLDER) +
"/examples/torque_driven_ocp/align_markers_with_torque_actuators.py")
graphs_one_phase = importlib.util.module_from_spec(spec)
spec.loader.exec_module(graphs_one_phase)
ocp = graphs_one_phase.prepare_ocp(
biorbd_model_path=str(PROJECT_FOLDER) +
"/examples/torque_driven_ocp/cube.bioMod",
number_shooting_points=30,
final_time=2,
)
sol = ocp.solve()
plt = ShowResult(ocp, sol)
plt.graphs(automatically_organize=False)
def test_plot_merged_graphs():
# Load graphs_one_phase
PROJECT_FOLDER = Path(__file__).parent / ".."
spec = importlib.util.spec_from_file_location(
"align_markers",
str(PROJECT_FOLDER) +
"/examples/muscle_driven_ocp/muscle_excitations_tracker.py")
merged_graphs = importlib.util.module_from_spec(spec)
spec.loader.exec_module(merged_graphs)
# Define the problem
model_path = str(
PROJECT_FOLDER) + "/examples/muscle_driven_ocp/arm26.bioMod"
biorbd_model = biorbd.Model(model_path)
final_time = 0.5
nb_shooting = 9
# Generate random data to fit
np.random.seed(42)
t, markers_ref, x_ref, muscle_excitations_ref = merged_graphs.generate_data(
biorbd_model, final_time, nb_shooting)
biorbd_model = biorbd.Model(
model_path
) # To prevent from non free variable, the model must be reloaded
ocp = merged_graphs.prepare_ocp(
biorbd_model,
final_time,
nb_shooting,
markers_ref,
muscle_excitations_ref,
x_ref[:biorbd_model.nbQ(), :].T,
use_residual_torque=True,
kin_data_to_track="markers",
)
sol = ocp.solve()
plt = ShowResult(ocp, sol)
plt.graphs(automatically_organize=False)
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()
)
def plot_callback(x, q_to_plot):
return x[q_to_plot, :]
if __name__ == "__main__":
# Prepare the Optimal Control Program
ocp = prepare_ocp(biorbd_model_path="pendulum.bioMod", final_time=2, number_shooting_points=50)
# Add my lovely new plot
ocp.add_plot("My New Extra Plot", lambda x, u, p: plot_callback(x, [0, 1, 3]), PlotType.PLOT)
ocp.add_plot(
"My New Extra Plot", lambda x, u, p: plot_callback(x, [1, 3]), plot_type=PlotType.STEP, axes_idx=[1, 2]
)
ocp.add_plot(
"My Second New Extra Plot",
lambda x, u, p: plot_callback(x, [1, 3]),
plot_type=PlotType.INTEGRATED,
axes_idx=[1, 2],
)
# --- Solve the program --- #
sol = ocp.solve(show_online_optim=False)
# --- Show results --- #
result = ShowResult(ocp, sol)
result.graphs()
result.animate()
InterpolationType.CONSTANT,
)
muscle_states_init = InitialConditions(
[muscle_activated_init] * ocp.nlp[0]["model"].nbMuscles() +
[muscle_fatigued_init] * ocp.nlp[0]["model"].nbMuscles() +
[muscle_resting_init] * ocp.nlp[0]["model"].nbMuscles(),
InterpolationType.CONSTANT,
)
X.concatenate(muscle_states_init)
# --- Simulate --- #
sol_simulate = Simulate.from_controls_and_initial_states(ocp,
X,
U,
single_shoot=True)
# --- Save for biorbdviz --- #
OptimalControlProgram.save_get_data(ocp,
sol_simulate,
f"results/simulate.bob",
interpolate_nb_frames=100)
# --- Graph --- #
result_single = ShowResult(ocp, sol_simulate)
result_single.graphs()
# todo multiphase
print("ok")
# result_single.animate()
)
if __name__ == "__main__":
print(f"Show the bounds")
for interpolation_type in InterpolationType:
print(f"Solving problem using {interpolation_type} bounds")
ocp = prepare_ocp("cube.bioMod",
number_shooting_points=30,
final_time=2,
interpolation_type=interpolation_type)
sol = ocp.solve()
print("\n")
# Print the last solution
result_plot = ShowResult(ocp, sol)
result_plot.graphs(adapt_graph_size_to_bounds=True)
for interpolation_type in InterpolationType:
print(f"Solving problem using {interpolation_type} bounds")
ocp = prepare_ocp("cube.bioMod",
number_shooting_points=30,
final_time=2,
interpolation_type=interpolation_type)
sol = ocp.solve()
print("\n")
# Print the last solution
result_plot = ShowResult(ocp, sol)
result_plot.graphs(adapt_graph_size_to_bounds=False)
# ------------- #
return OptimalControlProgram(
biorbd_model,
dynamics,
number_shooting_points,
final_time,
x_init,
u_init,
x_bounds,
u_bounds,
objective_functions,
)
if __name__ == "__main__":
# changer le path quand ce sera pret
ocp = prepare_ocp(
"TruncAnd2Arm_Quaternion.bioMod",
number_shooting_points=5,
final_time=0.25,
)
sol = ocp.solve()
print("\n")
# Print the last solution
result_plot = ShowResult(ocp, sol)
result_plot.graphs()
