docstr: Plot the main graph displaying distances between methods
  
  Parameters
  ----------
  mean_distances : DataFrame
      DataFrame storing all pairwise distances between methods
docstr_tok: ["Plot","the","main","graph","displaying","distances","between","methods","Parameters","--","--","--","--","--","mean_distances",":","DataFrame","DataFrame","storing","all","pairwise","distances","between","methods"]
code: def plot_comparison(self, mean_distances):
      """
      Plot the main graph displaying distances between methods
  
      Parameters
      ----------
      mean_distances : DataFrame
          DataFrame storing all pairwise distances between methods
      """
      font = {"color": "#{:02x}{:02x}{:02x}".format(50, 50, 50)}
  
      fig, ax = plt.subplots(ncols=1, figsize=(10, 6))
  
      ax.text(
          x=0.5,
          y=1.04,
          s="Consistency of explanations:",
          fontsize=24,
          ha="center",
          transform=fig.transFigure,
          **font,
      )
      ax.text(
          x=0.5,
          y=0.98,
          s="How similar are explanations from different methods?",
          fontsize=18,
          ha="center",
          transform=fig.transFigure,
          **font,
      )
  
      ax.set_title(
          "Average distances between the explanations",
          fontsize=14,
          pad=-60,
      )
  
      coords = self.calculate_coords(mean_distances)
  
      ax.scatter(coords[:, 0], coords[:, 1], marker="o")
  
      for i in range(len(mean_distances.columns)):
          ax.annotate(
              mean_distances.columns[i],
              xy=coords[i, :],
              xytext=(-5, 5),
              textcoords="offset points",
              ha="right",
              va="bottom",
          )
          self.draw_arrow(
              ax,
              coords[i, :],
              coords[(i + 1) % mean_distances.shape[0], :],
              mean_distances.iloc[i, (i + 1) % mean_distances.shape[0]],
          )
  
      # set gray background
      ax.set_facecolor("#F5F5F2")
      # draw solid white grid lines
      ax.grid(color="w", linestyle="solid")
  
      lim = (coords.min().min(), coords.max().max())
      margin = 0.1 * (lim[1] - lim[0])
      lim = (lim[0] - margin, lim[1] + margin)
      ax.set(xlim=lim, ylim=lim)
      ax.set_aspect("equal", anchor="C")
      ax.set_xticklabels([])
      ax.set_yticklabels([])
      ax.set_xticks(ax.get_yticks())
  
      return fig
  
imports: from category_encoders import OrdinalEncoder
  import copy
  import itertools
  import matplotlib.pyplot
  import numpy
  import pandas
  from plotly import graph_objs
  from plotly.offline import plot
  from plotly.subplots import make_subplots
  from sklearn.manifold import MDS
  from shapash import SmartExplainer
  from shapash.style.style_utils import colors_loading, select_palette, define_style
label_desc: Use image node_id 11 for calling the Consistency obj's underlying member method code with example usage: obj.plot_comparison(mean_distances) and returns: fig