code: def plot_curves(xy_list, xaxis, title):
      """
      plot the curves
  
      :param xy_list: ([(np.ndarray, np.ndarray)]) the x and y coordinates to plot
      :param xaxis: (str) the axis for the x and y output
          (can be X_TIMESTEPS='timesteps', X_EPISODES='episodes' or X_WALLTIME='walltime_hrs')
      :param title: (str) the title of the plot
      """
  
      plt.figure(figsize=(8, 2))
      maxx = max(xy[0][-1] for xy in xy_list)
      minx = 0
      for i, (x, y) in enumerate(xy_list):
          color = COLORS[i]
          plt.scatter(x, y, s=2)
          # Do not plot the smoothed curve at all if the timeseries is shorter than window size.
          if x.shape[0] >= EPISODES_WINDOW:
              # Compute and plot rolling mean with window of size EPISODE_WINDOW
              x, y_mean = window_func(x, y, EPISODES_WINDOW, np.mean)
              plt.plot(x, y_mean, color=color)
      plt.xlim(minx, maxx)
      plt.title(title)
      plt.xlabel(xaxis)
      plt.ylabel("Episode Rewards")
      plt.tight_layout()
  
file_path: stable-baselines/stable_baselines/results_plotter.py
imports: import numpy
  import matplotlib
  import matplotlib.pyplot
  from stable_baselines.bench.monitor import load_results
label_desc: Use image node_id 4 for calling a global function with example usage: plot_curves(xy_list, xaxis, title) without return types