code: def plot_2d(ax, n_labels=1, n_classes=3, length=50):
      X, Y, p_c, p_w_c = make_ml_clf(
          n_samples=150,
          n_features=2,
          n_classes=n_classes,
          n_labels=n_labels,
          length=length,
          allow_unlabeled=False,
          return_distributions=True,
          random_state=RANDOM_SEED,
      )
  
      ax.scatter(
          X[:, 0],
          X[:, 1],
          color=COLORS.take((Y * [1, 2, 4]).sum(axis=1)),
          marker=".",
      )
      ax.scatter(
          p_w_c[0] * length,
          p_w_c[1] * length,
          marker="*",
          linewidth=0.5,
          edgecolor="black",
          s=20 + 1500 * p_c**2,
          color=COLORS.take([1, 2, 4]),
      )
      ax.set_xlabel("Feature 0 count")
      return p_c, p_w_c
  
label_desc: Use image node_id 1 for calling a global function with example usage: plot_2d(ax, n_labels, n_classes, length) and returns: p_c,  p_w_c