code: def plot_model_weights(means, covs, ax):
      fmts = ["bo", "ro", "yx", "k+", "gx"]
      labels = ["arm{}".format(i) for i in range(5)]
  
      ax.set_title("Weights distributions of arms")
  
      for i in range(0, 5):
          x, y = np.random.multivariate_normal(
              means[i] / 30, covs[i], 5000
          ).T
          ax.plot(x, y, fmts[i], label=labels[i])
  
      ax.set_aspect("equal")
      ax.grid(True, which="both")
      ax.axhline(y=0, color="k")
      ax.axvline(x=0, color="k")
      ax.legend(loc="best")
  
file_path: ray/rllib_contrib/bandit/examples/tune_lin_ts_train_wheel_env.py
imports: import argparse
  import time
  import numpy
  from matplotlib import pyplot
  from rllib_bandit.bandit import BanditLinTSConfig
  import ray
  from ray import air, tune
  from ray.rllib.examples.env.bandit_envs_discrete import WheelBanditEnv
label_desc: Use image node_id 1 for calling a global function with example usage: plot_model_weights(means, covs, ax) without return types