text: import matplotlib.pyplot as plt
  import numpy as np
  
  import matplotlib as mpl
  
  import deltametrics as dm
  
  
  vs = dm.plot.VariableSet()
  
  N = 256
  gradient = np.linspace(0, 1, N)
  gradient = np.vstack((gradient, gradient))
  
  
  def over_coordinates(ax_lims):
      tri_low = np.array([[0, 0],
                          [0 - 10, 0.5],
                          [0, 1]])
      tri_high = np.array([[N, 0],
                           [N + 10, 0.5],
                           [N, 1]])
      name_xy = np.array([-240, 0.8])
      label_xy = np.array([-240, 0.4])
  
      return tri_low, tri_high, name_xy, label_xy
  
  
  def show_an_info(Info, ax):
      """Show a specific info.
      """
      ax_lims = ax.get_position().get_points()
      tri_low, tri_high, name_xy, label_xy = over_coordinates(ax_lims)
  
      ax.imshow(gradient, aspect='auto', cmap=Info.cmap)
      if not Info.norm:
          ax.set_xticks([])
      else:
          ax.set_xticks([Info.vmin])
          ax.add_patch(mpl.patches.Polygon(tri_low, closed=True,
                       color=Info.cmap._rgba_over, clip_on=False))
          ax.add_patch(mpl.patches.Polygon(tri_high, closed=True,
                       color=Info.cmap._rgba_over, clip_on=False))
  
      ax.text(name_xy[0], name_xy[1], 'name: ' + Info.name, fontsize=8,
              horizontalalignment='left', verticalalignment='bottom')
      ax.text(label_xy[0], label_xy[1], 'label: ' + Info.label, fontsize=8,
              horizontalalignment='left', verticalalignment='bottom')
  
      ax.set_yticks([])
      ax.set_ylim([0, 1])
      ax.tick_params(labelsize=8)
  
  nvi = len(vs.known_list)
  fig, ax = plt.subplots(nvi, 1, figsize=(8, 8))
  plt.tight_layout()
  plt.subplots_adjust(left=0.487, right=0.95)
  ax = ax.flatten()
  for i, v in enumerate(vs.known_list):
      show_an_info(vs[v], ax[i])
  
  plt.show()
  