def test__getting_started__example_multinode_constraints():
from bioptim.examples.getting_started import example_multinode_constraints as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/cube.bioMod")
def test__getting_started__example_external_forces():
from bioptim.examples.getting_started import example_external_forces as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/cube_with_forces.bioMod")
def test__symmetrical_torque_driven_ocp__symmetry_by_mapping():
from bioptim.examples.symmetrical_torque_driven_ocp import symmetry_by_mapping as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/cubeSym.bioMod", )
def test__getting_started__custom_objectives():
from bioptim.examples.getting_started import custom_objectives as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/cube.bioMod", )
def test__torque_driven_ocp__spring_load():
from bioptim.examples.torque_driven_ocp import spring_load as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/mass_point.bioMod")
def test__getting_started__example_multiphase():
from bioptim.examples.getting_started import example_multiphase as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/cube.bioMod",
long_optim=True)
def test__acados__cube():
from bioptim.examples.acados import cube as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/cube.bioMod",
n_shooting=10,
tf=2)
def test__acados__pendulum():
from bioptim.examples.acados import pendulum as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/pendulum.bioMod",
n_shooting=41,
final_time=3)
def test__getting_started__custom_initial_guess():
from bioptim.examples.getting_started import custom_initial_guess as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(biorbd_model_path=bioptim_folder +
"/models/cube.bioMod",
n_shooting=30,
final_time=2)
def test__getting_started__pendulum():
from bioptim.examples.getting_started import pendulum as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/pendulum.bioMod",
final_time=3,
n_shooting=100,
)
def test__torque_driven_ocp__phase_transition_uneven_variable_number():
from bioptim.examples.torque_driven_ocp import phase_transition_uneven_variable_number as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/double_pendulum.bioMod",
biorbd_model_path_withTranslations=bioptim_folder +
"/models/double_pendulum_with_translations.bioMod",
)
def test__optimal_time_ocp__pendulum_min_time_Mayer():
from bioptim.examples.optimal_time_ocp import pendulum_min_time_Mayer as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/pendulum.bioMod",
final_time=2,
n_shooting=50,
)
def test__track__track_segment_on_rt():
from bioptim.examples.track import track_segment_on_rt as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube_and_line.bioMod",
n_shooting=30,
final_time=1,
)
def test__getting_started__example_cyclic_movement():
from bioptim.examples.getting_started import example_cyclic_movement as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube.bioMod",
n_shooting=30,
final_time=2,
loop_from_constraint=True,
)
def test__muscle_driven_ocp__static_arm():
from bioptim.examples.muscle_driven_ocp import static_arm as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/arm26.bioMod",
final_time=3,
n_shooting=50,
weight=1000,
)
def test__track__track_marker_on_segment():
from bioptim.examples.track import track_marker_on_segment as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube_and_line.bioMod",
n_shooting=30,
final_time=2,
initialize_near_solution=True,
)
def test__torque_driven_ocp__track_markers_with_torque_actuators():
from bioptim.examples.torque_driven_ocp import track_markers_with_torque_actuators as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube.bioMod",
n_shooting=30,
final_time=2,
actuator_type=1,
)
def test__torque_driven_ocp__trampo_quaternions():
from bioptim.examples.torque_driven_ocp import trampo_quaternions as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder +
"/models/TruncAnd2Arm_Quaternion.bioMod",
n_shooting=5,
final_time=0.25,
)
def test__optimal_time_ocp__time_constraint():
from bioptim.examples.optimal_time_ocp import time_constraint as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/pendulum.bioMod",
final_time=2,
n_shooting=50,
time_min=0.6,
time_max=1,
)
def test__acados__static_arm():
from bioptim.examples.acados import static_arm as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/arm26.bioMod",
final_time=2,
x_warm=None,
n_shooting=51,
use_sx=False,
n_threads=6,
)
def test__torque_driven_ocp__maximize_predicted_height_CoM():
from bioptim.examples.torque_driven_ocp import maximize_predicted_height_CoM as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder +
"/models/2segments_4dof_2contacts.bioMod",
phase_time=0.5,
n_shooting=20,
use_actuators=False,
objective_name="MINIMIZE_COM_VELOCITY",
com_constraints=True,
)
def test__getting_started__example_inequality_constraint():
from bioptim.examples.getting_started import example_inequality_constraint as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder +
"/../torque_driven_ocp/models/2segments_4dof_2contacts.bioMod",
phase_time=0.3,
n_shooting=10,
min_bound=50,
max_bound=np.inf,
mu=0.2,
)
def test_acados_custom_dynamics(problem_type_custom):
if platform == "win32":
print("Test for ACADOS on Windows is skipped")
return
from bioptim.examples.getting_started import custom_dynamics as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp = ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube.bioMod",
problem_type_custom=problem_type_custom,
ode_solver=OdeSolver.RK4(),
use_sx=True,
)
constraints = ConstraintList()
constraints.add(ConstraintFcn.SUPERIMPOSE_MARKERS, node=Node.END, first_marker="m0", second_marker="m2")
ocp.update_constraints(constraints)
sol = ocp.solve(solver=Solver.ACADOS())
# Check some of the results
q, qdot, tau = sol.states["q"], sol.states["qdot"], sol.controls["tau"]
# initial and final position
np.testing.assert_almost_equal(q[:, 0], np.array((2, 0, 0)), decimal=6)
np.testing.assert_almost_equal(q[:, -1], np.array((2, 0, 1.57)))
# initial and final velocities
np.testing.assert_almost_equal(qdot[:, 0], np.array((0, 0, 0)))
np.testing.assert_almost_equal(qdot[:, -1], np.array((0, 0, 0)))
# initial and final controls
np.testing.assert_almost_equal(tau[:, 0], np.array((0, 9.81, 2.27903226)))
np.testing.assert_almost_equal(tau[:, -2], np.array((0, 9.81, -2.27903226)))
def test_acados_several_mayer(cost_type):
if platform == "win32":
print("Test for ACADOS on Windows is skipped")
return
from bioptim.examples.acados import cube as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp = ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube.bioMod",
n_shooting=10,
tf=2,
)
objective_functions = ObjectiveList()
objective_functions.add(ObjectiveFcn.Mayer.MINIMIZE_STATE, key="q", index=[0, 1], target=np.array([[1.0, 2.0]]).T)
objective_functions.add(ObjectiveFcn.Mayer.MINIMIZE_STATE, key="q", index=[2], target=np.array([[3.0]]))
ocp.update_objectives(objective_functions)
solver = Solver.ACADOS()
solver.set_cost_type(cost_type)
sol = ocp.solve(solver=solver)
# Check end state value
q = sol.states["q"]
np.testing.assert_almost_equal(q[0, -1], 1.0)
np.testing.assert_almost_equal(q[1, -1], 2.0)
np.testing.assert_almost_equal(q[2, -1], 3.0)
# Clean test folder
os.remove(f"./acados_ocp.json")
shutil.rmtree(f"./c_generated_code/")
def test__optimal_time_ocp__multiphase_time_constraint():
from bioptim.examples.optimal_time_ocp import multiphase_time_constraint as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
final_time = [2, 5, 4]
time_min = [1, 3, 0.1]
time_max = [2, 4, 0.8]
ns = [20, 30, 20]
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube.bioMod",
final_time=final_time,
time_min=time_min,
time_max=time_max,
n_shooting=ns,
)
def test_acados_options(cost_type):
if platform == "win32" or platform == "darwin":
print("Tests for ACADOS options on Windows and Mac are skipped")
return
from bioptim.examples.acados import pendulum as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp = ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/pendulum.bioMod",
final_time=0.6,
n_shooting=200,
)
tols = [1e-1, 1e1]
iter = []
for tol in tols:
solver = Solver.ACADOS()
solver.set_cost_type(cost_type)
solver.set_nlp_solver_tol_stat(tol)
sol = ocp.solve(solver=solver)
iter += [sol.iterations]
# Check that tol impacted convergence
for i in range(len(tols) - 1):
np.testing.assert_array_less(iter[i + 1], iter[i])
# Clean test folder
os.remove(f"./acados_ocp.json")
shutil.rmtree(f"./c_generated_code/")
def test_acados_control_lagrange_and_state_mayer(cost_type):
if platform == "win32":
print("Test for ACADOS on Windows is skipped")
return
from bioptim.examples.acados import cube as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
n_shooting = 10
target = np.array([[2]])
ocp = ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube.bioMod",
n_shooting=n_shooting,
tf=2,
)
objective_functions = ObjectiveList()
objective_functions.add(ObjectiveFcn.Lagrange.MINIMIZE_CONTROL, key="tau", multi_thread=False)
objective_functions.add(
ObjectiveFcn.Mayer.MINIMIZE_STATE, key="q", index=[0], target=target, weight=1000, multi_thread=False
)
ocp.update_objectives(objective_functions)
solver = Solver.ACADOS()
solver.set_cost_type(cost_type)
sol = ocp.solve(solver=solver)
# Check end state value
q = sol.states["q"]
np.testing.assert_almost_equal(q[0, -1], target.squeeze())
# Clean test folder
os.remove(f"./acados_ocp.json")
shutil.rmtree(f"./c_generated_code/")
def test_acados_one_parameter():
if platform == "win32":
print("Test for ACADOS on Windows is skipped")
return
from bioptim.examples.getting_started import custom_parameters as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp = ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/pendulum.bioMod",
final_time=1,
n_shooting=100,
optim_gravity=True,
optim_mass=False,
min_g=np.array([-1, -1, -10]),
max_g=np.array([1, 1, -5]),
min_m=10,
max_m=30,
target_g=np.array([0, 0, -9.81]),
target_m=20,
use_sx=True,
)
model = ocp.nlp[0].model
objectives = ObjectiveList()
objectives.add(ObjectiveFcn.Mayer.TRACK_STATE, key="q", target=np.array([[0, 3.14]]).T, weight=100000)
objectives.add(ObjectiveFcn.Mayer.TRACK_STATE, key="qdot", target=np.array([[0, 0]]).T, weight=100)
objectives.add(ObjectiveFcn.Lagrange.MINIMIZE_CONTROL, key="tau", index=1, weight=10, multi_thread=False)
objectives.add(ObjectiveFcn.Lagrange.MINIMIZE_STATE, key="qdot", weight=0.000000010, multi_thread=False)
ocp.update_objectives(objectives)
# Path constraint
x_bounds = QAndQDotBounds(model)
x_bounds[[0, 1, 2, 3], 0] = 0
u_bounds = Bounds([-300] * model.nbQ(), [300] * model.nbQ())
ocp.update_bounds(x_bounds, u_bounds)
solver = Solver.ACADOS()
solver.set_nlp_solver_tol_eq(1e-3)
sol = ocp.solve(solver=solver)
# Check some of the results
q, qdot, tau, gravity = sol.states["q"], sol.states["qdot"], sol.controls["tau"], sol.parameters["gravity_xyz"]
# initial and final position
np.testing.assert_almost_equal(q[:, 0], np.array((0, 0)), decimal=6)
np.testing.assert_almost_equal(q[:, -1], np.array((0, 3.14)), decimal=6)
# initial and final velocities
np.testing.assert_almost_equal(qdot[:, 0], np.array((0, 0)), decimal=6)
np.testing.assert_almost_equal(qdot[:, -1], np.array((0, 0)), decimal=6)
# parameters
np.testing.assert_almost_equal(gravity[-1, :], np.array([-9.81]), decimal=6)
# Clean test folder
os.remove(f"./acados_ocp.json")
shutil.rmtree(f"./c_generated_code/")
def test__getting_started__custom_parameters():
from bioptim.examples.getting_started import custom_parameters as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/pendulum.bioMod",
final_time=3,
n_shooting=100,
optim_gravity=True,
optim_mass=True,
min_g=np.array([-1, -1, -10]),
max_g=np.array([1, 1, -5]),
min_m=10,
max_m=30,
target_g=np.array([0, 0, -9.81]),
target_m=20,
)
def test_acados_one_end_constraints():
if platform == "win32":
print("Test for ACADOS on Windows is skipped")
return
from bioptim.examples.acados import cube as ocp_module
bioptim_folder = os.path.dirname(ocp_module.__file__)
ocp = ocp_module.prepare_ocp(
biorbd_model_path=bioptim_folder + "/models/cube.bioMod",
n_shooting=10,
tf=2,
)
model = ocp.nlp[0].model
objective_functions = ObjectiveList()
objective_functions.add(
ObjectiveFcn.Mayer.TRACK_STATE, index=0, key="q", weight=100, target=np.array([[1]]), multi_thread=False
)
objective_functions.add(ObjectiveFcn.Lagrange.MINIMIZE_CONTROL, key="tau", weight=100, multi_thread=False)
ocp.update_objectives(objective_functions)
# Path constraint
x_bounds = QAndQDotBounds(model)
x_bounds[1:6, [0, -1]] = 0
x_bounds[0, 0] = 0
ocp.update_bounds(x_bounds=x_bounds)
constraints = ConstraintList()
constraints.add(ConstraintFcn.SUPERIMPOSE_MARKERS, node=Node.END, first_marker="m0", second_marker="m2")
ocp.update_constraints(constraints)
sol = ocp.solve(solver=Solver.ACADOS())
# Check some of the results
q, qdot, tau = sol.states["q"], sol.states["qdot"], sol.controls["tau"]
# final position
np.testing.assert_almost_equal(q[:, -1], np.array((2, 0, 0)), decimal=6)
# initial and final controls
np.testing.assert_almost_equal(tau[:, 0], np.array((2.72727272, 9.81, 0)), decimal=6)
np.testing.assert_almost_equal(tau[:, -2], np.array((-2.72727272, 9.81, 0)), decimal=6)
