get_cmap is a function of matplotlib.pyplot since version 3.8.0

bioptim/gui/check_conditioning.py

@@ -2,7 +2,6 @@
 from casadi import Function, jacobian, hessian, sum1
 from matplotlib import pyplot as plt
 import matplotlib.colors as mcolors
-import matplotlib.cm as mcm
 from ..interfaces.ipopt_interface import IpoptInterface
 
 
@@ -116,7 +115,7 @@ def evaluate_hessian_objective(v, ocp):
 
 def create_conditioning_plots(ocp):
 
-    cmap = mcm.get_cmap("seismic")
+    cmap = plt.get_cmap("seismic")
     cmap.set_bad(color="k")
     interface = IpoptInterface(ocp)
     variables_vector = ocp.variables_vector
@@ -231,7 +230,7 @@ def update_objective_plot(v, ocp):
     hessian_matrix, condition_number, convexity = evaluate_hessian_objective(v, ocp)
     axis_obj = ocp.conditioning_plots["axis_obj"]
     im_objectives_hessian = ocp.conditioning_plots["im_objectives_hessian"]
-    cmap = mcm.get_cmap("seismic")
+    cmap = plt.get_cmap("seismic")
 
     # Hessian objective plot
     hess_min = np.min(hessian_matrix) if hessian_matrix.shape[0] != 0 else 0

bioptim/gui/ipopt_output_plot.py

@@ -3,7 +3,6 @@
 import numpy as np
 from casadi import jacobian, gradient, sum1, Function
 from matplotlib import pyplot as plt
-from matplotlib.cm import get_cmap
 
 from ..misc.parameters_types import Str, Int
 
@@ -18,7 +17,7 @@ def create_ipopt_output_plot(ocp, interface):
     axs[2].set_ylabel("inf_du", fontweight="bold")
 
     plots = []
-    colors = get_cmap("viridis")
+    colors = plt.get_cmap("viridis")
     for i in range(3):
         plot = axs[i].plot([0], [1], linestyle="-", marker=".", color="k")
         plots.append(plot[0])

environment.yml

@@ -5,7 +5,7 @@ channels:
 dependencies:
 - python >=3.10
 - biorbd >=1.12,<1.13
-- matplotlib
+- matplotlib >= 3.8.0
 - pyqt
 - pyqtgraph
 - python-graphviz