[WIP] Codex/upgrade numpy 2 4

.github/workflows/run_tests_linux.yml

@@ -40,7 +40,7 @@ jobs:
 
       - name: Install extra dependencies
         run: | 
-          conda install pytest-cov black pytest pytest-cov codecov packaging pytest-mpl -cconda-forge
+          conda install "numpy>=2.4,<3" pytest-cov black pytest pytest-cov codecov packaging pytest-mpl -cconda-forge
           sudo apt install -y librhash-dev
 
       - name: Install ACADOS on Linux

.github/workflows/run_tests_osx_win.yml

@@ -47,7 +47,7 @@ jobs:
           conda list
 
       - name: Install extra dependencies
-        run: conda install pytest-cov black pytest pytest-cov codecov packaging -cconda-forge
+        run: conda install "numpy>=2.4,<3" pytest-cov black pytest pytest-cov codecov packaging -cconda-forge
 
       - name: Install ACADOS on Mac
         run: |

bioptim/gui/plot.py

@@ -635,10 +635,15 @@ def _add_vertical_lines(self, ax):
 
     def _add_bounds_to_plot(self, i, nlp, variable, ctr, ax, mapping_to_first_index):
         """Add bounds to a specific plot"""
-        if nlp.plot[variable].bounds.type == InterpolationType.EACH_FRAME:
+        if nlp.plot[variable].bounds.type in [InterpolationType.EACH_FRAME, InterpolationType.ALL_POINTS]:
             ns = nlp.plot[variable].bounds.min.shape[1] - 1
         else:
             ns = nlp.ns
+        t = (
+            [np.linspace(0, ns, ns + 1) for i in range(len(self.t))]
+            if nlp.plot[variable].bounds.type == InterpolationType.ALL_POINTS
+            else self.t
+        )
 
         # TODO: introduce repeat for the COLLOCATIONS min/max_bounds only for states graphs.
         # For now the plots in COLLOCATIONS with LINEAR are not giving the right values
@@ -652,8 +657,8 @@ def _add_bounds_to_plot(self, i, nlp, variable, ctr, ax, mapping_to_first_index)
             bounds_min = np.concatenate((bounds_min, [bounds_min[-1]]))
             bounds_max = np.concatenate((bounds_max, [bounds_max[-1]]))
 
-        self.plots_bounds.append([ax.step(self.t[i], bounds_min, where="post", **self.plot_options["bounds"]), i])
-        self.plots_bounds.append([ax.step(self.t[i], bounds_max, where="post", **self.plot_options["bounds"]), i])
+        self.plots_bounds.append([ax.step(t[i], bounds_min, where="post", **self.plot_options["bounds"]), i])
+        self.plots_bounds.append([ax.step(t[i], bounds_max, where="post", **self.plot_options["bounds"]), i])
 
     def _add_new_axis(self, variable: Str, nb: Int, n_rows: Int, n_cols: Int):
         """

bioptim/misc/mapping.py

@@ -408,11 +408,12 @@ def __init__(
         dependency_matrix: list = [None for _ in range(len(first))]
         oppose = []
         for i in range(len(first)):
-            if first[i] != 0 and first[i] > 0:
-                dependency_matrix[i] = int(first[i] - 1)
-            if first[i] < 0:
+            value = first[i, 0]
+            if value != 0 and value > 0:
+                dependency_matrix[i] = int(value - 1)
+            if value < 0:
                 oppose.append(i)
-                dependency_matrix[i] = int(abs(first[i]) - 1)
+                dependency_matrix[i] = int(abs(value) - 1)
 
         def _build_to_second(dependency_matrix: AnyList, independent_indices: AnyTuple):
             """

bioptim/optimization/receding_horizon_optimization.py

@@ -763,8 +763,8 @@ def solve(
         )
 
         if self.parameters.shape != 0 and get_all_iterations:
-            final_solution_parameters_dict = [{key: None} for key in solution[0].parameters.keys()][0]
-            for key in solution[0].parameters.keys():
+            final_solution_parameters_dict = [{key: None} for key in solution[1][0].parameters.keys()][0]
+            for key in solution[1][0].parameters.keys():
                 key_val = []
                 for sol in solution[1]:
                     key_val.append(sol.parameters[key])

bioptim/optimization/solution/solution.py

@@ -256,12 +256,11 @@ def from_initial_guess(cls, ocp, sol: list):
 
         dt, sol_states, sol_controls, sol_params, sol_algebraic_states = sol
 
-        vector = np.ndarray((0, 1))
-
         # For time
         if len(dt.shape) == 1:
             dt = dt[:, np.newaxis]
-        vector = np.concatenate((vector, dt))
+
+        state_vector = [dt]
 
         # For states
         for p, ss in enumerate(sol_states):
@@ -278,9 +277,8 @@ def from_initial_guess(cls, ocp, sol: list):
 
             for i in range(all_ns[p] * nb_intermediate_frames + 1):
                 for key in ss.keys():
-                    vector = np.concatenate(
-                        (vector, ss[key].init.evaluate_at(i, nb_intermediate_frames)[:, np.newaxis])
-                    )
+                    state_vector.append(ss[key].init.evaluate_at(i, nb_intermediate_frames)[:, None])
+        vector = np.vstack(state_vector)
 
         # For controls
         for p, ss in enumerate(sol_controls):

environment.yml

@@ -4,7 +4,8 @@ channels:
 - conda-forge
 dependencies:
 - biorbd >=1.11.1
+- numpy >=2.4,<3
 - matplotlib
 - pyqt
 - pyqtgraph
-- python-graphviz
+- python-graphviz