code: def plot_potato_2D(
      ax, cax, X, Y, p_zscores, p_center, covs, p_colors, clabel
  ):
      qcs = ax.contourf(
          X,
          Y,
          p_zscores,
          levels=20,
          vmin=p_zscores.min(),
          vmax=p_zscores.max(),
          cmap="RdYlBu_r",
          alpha=0.5,
      )
      ax.contour(X, Y, p_zscores, levels=[z_th], colors="k")
      sc = ax.scatter(covs[:, 0, 0], covs[:, 1, 1], c=p_colors)
      ax.scatter(p_center[0, 0], p_center[1, 1], c="k", s=100)
      if cax:
          cbar = fig.colorbar(qcs, cax=cax)
      else:
          cbar = fig.colorbar(qcs, ax=ax)
      cbar.ax.set_ylabel(clabel)
      return sc
  
file_path: pyRiemann/examples/artifacts/plot_detect_riemannian_potato_EEG.py
imports: from functools import partial
  import os
  import numpy
  from matplotlib import pyplot
  from matplotlib.animation import FuncAnimation
  from mne.datasets import sample
  from mne.io import read_raw_fif
  from mne import make_fixed_length_epochs
  from pyriemann.estimation import Covariances
  from pyriemann.clustering import Potato
  from pyriemann.utils.viz import _add_alpha
label_desc: Use image node_id 2 for calling a global function with example usage: plot_potato_2D(ax, cax, X, Y, p_zscores, p_center, covs, p_colors, clabel) and returns: sc