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pyomeca · Jul 17, 2023 · 7ef44d4 · 7ef44d4
1 parent e45bc11
commit 7ef44d4
Showing 1 changed file with 30 additions and 4 deletions.
diff --git a/bioptim/interfaces/acados_interface.py b/bioptim/interfaces/acados_interface.py
@@ -593,14 +593,33 @@ def add_nonlinear_ls_mayer(acados, objectives, x, u, p, s, node=None):
 
                     if J.type.get_type() == ObjectiveFunction.LagrangeFunction:
                         add_nonlinear_ls_lagrange(
-                            self, J, nlp.states.cx_start, nlp.controls.cx_start, nlp.parameters.cx, nlp.stochastic_variables.cx_start
+                            self,
+                            J,
+                            nlp.states.cx_start,
+                            nlp.controls.cx_start,
+                            nlp.parameters.cx,
+                            nlp.stochastic_variables.cx_start,
                         )
 
                         # Deal with first and last node
-                        add_nonlinear_ls_mayer(self, J, nlp.states.cx_start, nlp.controls.cx_start, nlp.parameters.cx, nlp.stochastic_variables.cx_start)
+                        add_nonlinear_ls_mayer(
+                            self,
+                            J,
+                            nlp.states.cx_start,
+                            nlp.controls.cx_start,
+                            nlp.parameters.cx,
+                            nlp.stochastic_variables.cx_start,
+                        )
 
                     elif J.type.get_type() == ObjectiveFunction.MayerFunction:
-                        add_nonlinear_ls_mayer(self, J, nlp.states.cx_start, nlp.controls.cx_start, nlp.parameters.cx, nlp.stochastic_variables.cx_start)
+                        add_nonlinear_ls_mayer(
+                            self,
+                            J,
+                            nlp.states.cx_start,
+                            nlp.controls.cx_start,
+                            nlp.parameters.cx,
+                            nlp.stochastic_variables.cx_start,
+                        )
                     else:
                         raise RuntimeError("The objective function is not Lagrange nor Mayer.")
 
@@ -610,7 +629,14 @@ def add_nonlinear_ls_mayer(acados, objectives, x, u, p, s, node=None):
                 nlp = ocp.nlp[0]  # Assume 1 phase
                 for j, J in enumerate(ocp.J):
                     J.node = [Node.END]
-                    add_nonlinear_ls_mayer(self, J, nlp.states.cx_start, nlp.controls.cx_start, nlp.parameters.cx, nlp.stochastic_variables.cx_start)
+                    add_nonlinear_ls_mayer(
+                        self,
+                        J,
+                        nlp.states.cx_start,
+                        nlp.controls.cx_start,
+                        nlp.parameters.cx,
+                        nlp.stochastic_variables.cx_start,
+                    )
 
             # Set costs
             self.acados_ocp.model.cost_y_expr = (