docs: def lola_image(self, save=False, name='BaseLola.png'):
          ''' Draw the topography of the region of interest
  
          Args:
              save (Optional[bool]): Weither or not to save the image.
                  Defaults to False.
              name (Optional[str]): Absolut path to save the resulting
                  image. Default to 'BaseLola.png' in the working
                  directory.
  
          Returns:
              An image correponding to the region tography. Realized
              from the data taken by the LOLA instrument on board of LRO.
  
          Note:
              Nice to use in a jupyter notebook with ``%matplotib inline``
              activated.
  
              Feel free to modify this method to plot exactly what you need.
  
          '''
  
          fig = plt.figure(figsize=(10, 8))
          ax1 = fig.add_subplot(111)
  
          lon_m, lon_M, lat_m, lat_M = self.lambert_window(
              self.size_window, self.lat0, self.lon0)
          m = Basemap(llcrnrlon=lon_m, llcrnrlat=lat_m, urcrnrlon=lon_M, urcrnrlat=lat_M,
                      resolution='i', projection='laea', rsphere=1734400, lat_0=self.lat0, lon_0=self.lon0)
  
          Xl, Yl, Zl = self.get_arrays('Lola')
          Xl, Yl = m(Xl, Yl)
  
          CS = m.pcolormesh(Xl, Yl, Zl, cmap='gist_earth',
                            alpha=.5, ax=ax1, zorder=1)
          # m.contour(Xl,Yl,Zl,20, colors = 'black', alpha = 1.0 , zorder=2)
  
          xc, yc = m(self.lon0, self.lat0)
          ax1.scatter(xc, yc, s=200, marker='v', zorder=2)
  
          self._add_scale(m, ax1)
          self._add_colorbar(m, CS, ax1, 'Topography')
  
          if save == True:
              fig.savefig(name, rasterized=True, dpi=50,
                          bbox_inches='tight', pad_inches=0.1)