code: def view(self, channel_names='auto',
               gates=None,
               diag_kw={}, offdiag_kw={},
               gate_colors=None, **kwargs):
          
          if channel_names == 'auto':
              channel_names = list(self.channel_names)
  
          def plot_region(channels, **kwargs):
              if channels[0] == channels[1]:
                  channels = channels[0]
              kind = 'histogram'
  
              self.plot(channels, kind=kind, gates=gates,
                        gate_colors=gate_colors, autolabel=False)
  
          channel_list = np.array(list(channel_names), dtype=object)
          channel_mat = [[(x, y) for x in channel_list] for y in channel_list]
          channel_mat = DataFrame(channel_mat, columns=channel_list, index=channel_list)
          kwargs.setdefault('wspace', 0.1)
          kwargs.setdefault('hspace', 0.1)
          return plot_ndpanel(channel_mat, plot_region, **kwargs)
docs: Generates a matrix of subplots allowing for a quick way
          to examine how the sample looks in different channels.
  
          Parameters
          ----------
          channel_names : [list | 'auto']
              List of channel names to plot.
          offdiag_plot : ['histogram' | 'scatter']
              Specifies the type of plot for the off-diagonal elements.
          diag_kw : dict
              Not implemented
  
          Returns
          ------------
  
          axes references