[RTM when tests pass] fixing example model paths

README.md

@@ -44,6 +44,7 @@ As a tour guide that uses this binder, you can watch the `bioptim` workshop that
 
 A GUI is available to run all the current examples. To run it you can use the following command, from the root folder of the project:
 ```bash
+conda install -c conda-forge pyqt pyqtgraph
 python -m bioptim.examples
 ```
 Please refer to section [Examples](#examples) for more information on how to run the examples.

bioptim/examples/__main__.py

@@ -23,9 +23,12 @@
 # Avoid clash with module name
 examples_ = OrderedDict(
     [
-        ("acados", OrderedDict([("Static arm", "static_arm.py"), ("Cube", "cube.py"), ("Pendulum", "pendulum.py")])),
         (
-            "fatigue",
+            "toy_examples/acados",
+            OrderedDict([("Static arm", "static_arm.py"), ("Cube", "cube.py"), ("Pendulum", "pendulum.py")]),
+        ),
+        (
+            "toy_examples/fatigue",
             OrderedDict(
                 [
                     ("Pendulum with fatigue", "pendulum_with_fatigue.py"),
@@ -37,32 +40,39 @@
             "getting_started",
             OrderedDict(
                 [
-                    ("Custom Bounds", "custom_bounds.py"),
-                    ("Custom constraint", "custom_constraint.py"),
-                    ("Custom initial guess", "custom_initial_guess.py"),
                     ("Custom objectives", "custom_objectives.py"),
                     ("Custom parameters", "custom_parameters.py"),
                     ("Custom phase transitions", "custom_phase_transitions.py"),
                     ("Custom plotting", "custom_plotting.py"),
-                    ("Example cyclic movement", "example_cyclic_movement.py"),
                     ("Example external forces", "example_external_forces.py"),
                     ("Example inequality constraint", "example_inequality_constraint.py"),
-                    ("Example mapping", "example_mapping.py"),
                     ("Example multiphase", "example_multiphase.py"),
-                    ("Example optimal time", "example_optimal_time.py"),
                     ("Example simulation", "example_simulation.py"),
-                    ("Pendulum", "pendulum.py"),
+                    ("Example cyclic movement", "example_cyclic_movement.py"),
+                    ("Basic OCP", "basic_ocp.py"),
+                    ("Example constraint weight", "custom_constraint_weights.py"),
+                    ("How to plot", "how_to_plot.py"),
+                ]
+            ),
+        ),
+        (
+            "toy_examples/feature_examples",
+            OrderedDict(
+                [
+                    ("Custom Bounds", "custom_bounds.py"),
+                    ("Custom constraint", "custom_constraint.py"),
+                    ("Custom initial guess", "custom_initial_guess.py"),
                 ]
             ),
         ),
         (
-            "moving_horizon_estimation",
+            "toy_examples/moving_horizon_estimation",
             OrderedDict(
                 [("Cyclic nmpc", "cyclic_nmpc.py"), ("Mhe", "mhe.py"), ("Multi cyclic nmpc", "multi_cyclic_nmpc.py")]
             ),
         ),
         (
-            "muscle_driven_ocp",
+            "toy_examples/muscle_driven_ocp",
             OrderedDict(
                 [
                     ("Muscle activations tracker", "muscle_activations_tracker.py"),
@@ -73,7 +83,7 @@
             ),
         ),
         (
-            "muscle_driven_with_contact",
+            "toy_examples/muscle_driven_with_contact",
             OrderedDict(
                 [
                     ("Contact forces inequality constraint muscle", "contact_forces_inequality_constraint_muscle.py"),
@@ -86,7 +96,7 @@
             ),
         ),
         (
-            "optimal_time_ocp",
+            "toy_examples/optimal_time_ocp",
             OrderedDict(
                 [
                     ("Multiphase time constraint", "multiphase_time_constraint.py"),
@@ -96,7 +106,7 @@
             ),
         ),
         (
-            "symmetrical_torque_driven_ocp",
+            "toy_examples/symmetrical_torque_driven_ocp",
             OrderedDict(
                 [
                     ("Symmetry by constraint", "symmetry_by_constraint.py"),
@@ -105,7 +115,7 @@
             ),
         ),
         (
-            "torque_driven_ocp",
+            "toy_examples/torque_driven_ocp",
             OrderedDict(
                 [
                     ("Maximize predicted height center_of_mass", "maximize_predicted_height_CoM.py"),
@@ -126,7 +136,7 @@
             ),
         ),
         (
-            "track",
+            "toy_examples/tracking",
             OrderedDict(
                 [
                     ("Track marker on segment", "track_marker_on_segment.py"),

bioptim/examples/getting_started/example_multistart.py

@@ -23,6 +23,7 @@
     PhaseDynamics,
     SolutionMerge,
 )
+from bioptim.examples.utils import ExampleUtils
 
 
 def prepare_ocp(
@@ -196,7 +197,8 @@ def prepare_multi_start(
 def main():
     # --- Prepare the multi-start and run it --- #
 
-    bio_model_path = ["models/pendulum.bioMod"]
+    example_path = ExampleUtils.folder
+    bio_model_path = [example_path + "/models/pendulum.bioMod"]
     final_time = [1]
     n_shooting = [30, 40, 50]
     seed = [0, 1, 2, 3]
@@ -208,7 +210,7 @@ def main():
         "seed": seed,
     }
 
-    save_folder = "./temporary_results"
+    save_folder = example_path + "/./temporary_results"
     multi_start = prepare_multi_start(
         combinatorial_parameters=combinatorial_parameters,
         save_folder=save_folder,

bioptim/examples/toy_examples/discrete_mechanics_and_optimal_control/example_variational_integrator_pendulum.py

@@ -14,6 +14,7 @@
     VariationalTorqueBiorbdModel,
     VariationalOptimalControlProgram,
 )
+from bioptim.examples.utils import ExampleUtils
 import numpy as np
 
 
@@ -92,7 +93,8 @@ def main():
     n_shooting = 100
 
     # --- Prepare the ocp --- #
-    ocp = prepare_ocp(bio_model_path="models/pendulum.bioMod", final_time=1, n_shooting=n_shooting)
+    biorbd_model_path = ExampleUtils.folder + "/models/pendulum.bioMod"
+    ocp = prepare_ocp(bio_model_path=biorbd_model_path, final_time=1, n_shooting=n_shooting)
 
     # --- Print ocp structure --- #
     ocp.print(to_console=False, to_graph=False)

bioptim/examples/toy_examples/discrete_mechanics_and_optimal_control/example_variational_integrator_with_holonomic_constraints_pendulum.py

@@ -17,6 +17,7 @@
     VariationalTorqueBiorbdModel,
     VariationalOptimalControlProgram,
 )
+from bioptim.examples.utils import ExampleUtils
 import numpy as np
 
 
@@ -111,7 +112,8 @@ def main():
     n_shooting = 100
 
     # --- Prepare the ocp --- #
-    ocp = prepare_ocp(bio_model_path="models/pendulum_holonomic.bioMod", final_time=1, n_shooting=n_shooting)
+    biorbd_model_path = ExampleUtils.folder + "/models/pendulum_holonomic.bioMod"
+    ocp = prepare_ocp(bio_model_path=biorbd_model_path, final_time=1, n_shooting=n_shooting)
 
     # --- Print ocp structure --- #
     ocp.print(to_console=False, to_graph=False)

bioptim/examples/toy_examples/feature_examples/custom_constraint_weights.py

@@ -32,6 +32,7 @@
     PhaseDynamics,
     ConstraintWeight,
 )
+from bioptim.examples.utils import ExampleUtils
 
 
 def custom_weight(node: int, n_nodes: int) -> float:
@@ -172,6 +173,7 @@ def main():
     """
 
     nodes_to_test = [Node.START, Node.INTERMEDIATES, Node.ALL_SHOOTING]
+    biorbd_model_path = ExampleUtils.folder + "/models/cube.bioMod"
 
     for interpolation_type in InterpolationType:
         for node in nodes_to_test:
@@ -183,7 +185,11 @@ def main():
 
             print(f"Solving problem using {interpolation_type} weight applied at {node} nodes.")
             ocp = prepare_ocp(
-                "models/cube.bioMod", n_shooting=30, final_time=2, interpolation_type=interpolation_type, node=node
+                biorbd_model_path=biorbd_model_path,
+                n_shooting=30,
+                final_time=2,
+                interpolation_type=interpolation_type,
+                node=node,
             )
             sol = ocp.solve()
             print("\n")

bioptim/examples/toy_examples/feature_examples/example_multinode_objective.py

@@ -19,6 +19,7 @@
     MultinodeObjectiveList,
     CostType,
 )
+from bioptim.examples.utils import ExampleUtils
 
 
 def multinode_min_controls(controllers: list[PenaltyController]):
@@ -125,7 +126,8 @@ def main():
 
     # --- Prepare the ocp --- #
     n_shooting = 30
-    ocp = prepare_ocp(biorbd_model_path="models/pendulum.bioMod", final_time=1, n_shooting=n_shooting)
+    biorbd_model_path = ExampleUtils.folder + "/models/pendulum.bioMod"
+    ocp = prepare_ocp(biorbd_model_path=biorbd_model_path, final_time=1, n_shooting=n_shooting)
     ocp.add_plot_penalty(CostType.ALL)
 
     # --- Solve the ocp --- #

bioptim/examples/toy_examples/holonomic_constraints/two_pendulums.py

@@ -25,6 +25,7 @@
     SolutionMerge,
     OdeSolver,
 )
+from bioptim.examples.utils import ExampleUtils
 
 
 def compute_all_states(sol, bio_model: HolonomicTorqueBiorbdModel):
@@ -197,8 +198,8 @@ def main():
     Runs the optimization and animates it
     """
 
-    model_path = "models/two_pendulums.bioMod"
-    ocp, bio_model = prepare_ocp(biorbd_model_path=model_path)
+    biorbd_model_path = ExampleUtils.folder + "/models/two_pendulums.bioMod"
+    ocp, bio_model = prepare_ocp(biorbd_model_path=biorbd_model_path)
 
     # --- Solve the program --- #
     sol = ocp.solve(Solver.IPOPT())
@@ -211,15 +212,15 @@ def main():
     if viewer == "bioviz":
         import bioviz
 
-        viz = bioviz.Viz(model_path)
+        viz = bioviz.Viz(biorbd_model_path)
         viz.load_movement(q)
         viz.exec()
 
     if viewer == "pyorerun":
         import pyorerun
 
         viz = pyorerun.PhaseRerun(t_span=np.concatenate(sol.decision_time()).squeeze())
-        viz.add_animated_model(pyorerun.BiorbdModel(model_path), q=q)
+        viz.add_animated_model(pyorerun.BiorbdModel(biorbd_model_path), q=q)
 
         viz.rerun("double_pendulum")
 

bioptim/examples/toy_examples/holonomic_constraints/two_pendulums_algebraic.py

@@ -28,6 +28,7 @@
     CostType,
     OdeSolver,
 )
+from bioptim.examples.utils import ExampleUtils
 from .custom_dynamics import (
     ModifiedHolonomicTorqueBiorbdModel,
     constraint_holonomic,
@@ -232,8 +233,8 @@ def main():
     Runs the optimization and animates it
     """
 
-    model_path = "models/two_pendulums.bioMod"
-    ocp, bio_model = prepare_ocp(biorbd_model_path=model_path)
+    biorbd_model_path = ExampleUtils.folder + "/models/two_pendulums.bioMod"
+    ocp, bio_model = prepare_ocp(biorbd_model_path=biorbd_model_path)
     ocp.add_plot_penalty(CostType.ALL)
 
     # --- Solve the program --- #
@@ -248,14 +249,14 @@ def main():
     if viewer == "bioviz":
         import bioviz
 
-        viz = bioviz.Viz(model_path)
+        viz = bioviz.Viz(biorbd_model_path)
         viz.load_movement(q)
         viz.exec()
 
     if viewer == "pyorerun":
         from pyorerun import BiorbdModel as PyorerunBiorbdModel, PhaseRerun
 
-        pyomodel = PyorerunBiorbdModel(model_path)
+        pyomodel = PyorerunBiorbdModel(biorbd_model_path)
         viz = PhaseRerun(t_span=np.concatenate(sol.decision_time()).squeeze())
         viz.add_animated_model(pyomodel, q=q)
 

bioptim/examples/toy_examples/inverse_optimal_control/double_pendulum_torque_driven_IOCP.py

@@ -23,12 +23,13 @@
     PhaseDynamics,
     SolutionMerge,
 )
+from bioptim.examples.utils import ExampleUtils
 
 
 def prepare_ocp(
     weights,
     coefficients,
-    biorbd_model_path="models/double_pendulum.bioMod",
+    biorbd_model_path,
     phase_dynamics: PhaseDynamics = PhaseDynamics.SHARED_DURING_THE_PHASE,
     n_threads: int = 4,
     expand_dynamics: bool = True,
@@ -119,7 +120,8 @@ def fitness(self, weights):
         """
         global i_inverse
         i_inverse += 1
-        ocp = prepare_ocp(weights, self.coefficients)
+        biorbd_model_path = ExampleUtils.folder + "/models/double_pendulums.bioMod"
+        ocp = prepare_ocp(weights, self.coefficients, biorbd_model_path=biorbd_model_path)
         sol = ocp.solve(self.solver)
         print(
             f"+++++++++++++++++++++++++++ Optimized the {i_inverse}th ocp in the inverse algo +++++++++++++++++++++++++++"
@@ -148,7 +150,8 @@ def main():
 
     # Generate data using OCP
     weights_to_track = [0.4, 0.3, 0.3]
-    ocp_to_track = prepare_ocp(weights=weights_to_track, coefficients=[1, 1, 1])
+    biorbd_model_path = ExampleUtils.folder + "/models/double_pendulums.bioMod"
+    ocp_to_track = prepare_ocp(weights=weights_to_track, coefficients=[1, 1, 1], biorbd_model_path=biorbd_model_path)
     ocp_to_track.add_plot_penalty(CostType.ALL)
     solver = Solver.IPOPT()
     # solver.set_linear_solver("ma57")  # Much faster, but necessite libhsl installed
@@ -163,7 +166,7 @@ def main():
     for i in range(len(weights_to_track)):
         weights_pareto = [0, 0, 0]
         weights_pareto[i] = 1
-        ocp_pareto = prepare_ocp(weights=weights_pareto, coefficients=[1, 1, 1])
+        ocp_pareto = prepare_ocp(weights=weights_pareto, coefficients=[1, 1, 1], biorbd_model_path=biorbd_model_path)
         sol_pareto = ocp_pareto.solve(solver)
         # sol_pareto.animate()
         coefficients.append(sol_pareto.cost)
@@ -215,7 +218,7 @@ def main():
     # Compare the kinematics
     import biorbd
 
-    ocp_final = prepare_ocp(weights=pop_weights, coefficients=coefficients)
+    ocp_final = prepare_ocp(weights=pop_weights, coefficients=coefficients, biorbd_model_path=biorbd_model_path)
     sol_final = ocp_final.solve(solver)
     states = sol_final.decision_states(to_merge=SolutionMerge.NODES)
     controls = sol_final.decision_controls(to_merge=SolutionMerge.NODES)

bioptim/examples/toy_examples/moving_horizon_estimation/cyclic_nmpc.py

@@ -22,6 +22,7 @@
     Solution,
     PhaseDynamics,
 )
+from bioptim.examples.utils import ExampleUtils
 
 
 class MyCyclicNMPC(CyclicNonlinearModelPredictiveControl):
@@ -76,14 +77,14 @@ def prepare_nmpc(
 
 
 def main():
-    model_path = "models/arm2.bioMod"
+    biorbd_model_path = ExampleUtils.folder + "/models/arm2.bioMod"
     torque_max = 50
 
     cycle_duration = 1
     cycle_len = 20
     n_cycles = 3
 
-    nmpc = prepare_nmpc(model_path, cycle_len=cycle_len, cycle_duration=cycle_duration, max_torque=torque_max)
+    nmpc = prepare_nmpc(biorbd_model_path, cycle_len=cycle_len, cycle_duration=cycle_duration, max_torque=torque_max)
 
     def update_functions(_nmpc: CyclicNonlinearModelPredictiveControl, cycle_idx: int, _sol: Solution):
         return cycle_idx < n_cycles  # True if there are still some cycle to perform

bioptim/examples/toy_examples/moving_horizon_estimation/mhe.py

@@ -34,6 +34,7 @@
     PhaseDynamics,
     SolutionMerge,
 )
+from bioptim.examples.utils import ExampleUtils
 
 
 def states_to_markers(bio_model, states):
@@ -182,7 +183,7 @@ def get_solver_options(solver):
 
 
 def main():
-    biorbd_model_path = "models/cart_pendulum.bioMod"
+    biorbd_model_path = ExampleUtils.folder + "/models/cart_pendulum.bioMod"
     bio_model = TorqueBiorbdModel(biorbd_model_path)
 
     solver = Solver.IPOPT()  # or Solver.ACADOS()  # If ACADOS is used, it must be manually installed