docs: def plot_f_rate(self, ax, X, i, xlim, x, y, binsize=1, yscale='linear',
                      plottype='fill_between', show_label=False, rasterized=False):
          """
          Plot network firing rate plot in subplot object.
          
          
          Parameters
          ----------
          ax : `matplotlib.axes.AxesSubplot` object.
          X : str
              Population name.
          i : int
              Population index in class attribute `X`.
          xlim : list of floats
              Spike time interval, e.g., [0., 1000.].
          x : dict
              Key-value entries are population name and neuron spike times.
          y : dict
              Key-value entries are population name and neuron gid number.
          yscale : 'str'
              Linear, log, or symlog y-axes in rate plot.
          plottype : str
              plot type string in `['fill_between', 'bar']`
          show_label : bool
              whether or not to show labels
          
  
          Returns
          -------
          None
          
          """
          
          bins = np.arange(xlim[0], xlim[1]+binsize, binsize)
          (hist, bins) = np.histogram(x[X], bins=bins)
          
          if plottype == 'fill_between':
              ax.fill_between(bins[:-1], hist * 1000. / self.N_X[i],
                      color=self.colors[i], lw=0.5, label=X, rasterized=rasterized,
                      clip_on=False)
              ax.plot(bins[:-1], hist * 1000. / self.N_X[i],
                      color='k', lw=0.5, label=X, rasterized=rasterized,
                      clip_on=False)
          elif plottype == 'bar':
              ax.bar(bins[:-1], hist * 1000. / self.N_X[i],
                      color=self.colors[i], label=X, rasterized=rasterized ,
                      linewidth=0.25, width=0.9, clip_on=False)
          else:
              mssg = "plottype={} not in ['fill_between', 'bar']".format(plottype)
              raise Exception(mssg)
  
          remove_axis_junk(ax)
  
          ax.axis(ax.axis('tight'))
  
          ax.set_yscale(yscale)
  
          ax.set_xlim(xlim[0], xlim[1])
          if show_label:
              ax.text(xlim[0] + .05*(xlim[1]-xlim[0]), ax.axis()[3]*1.5, X,
                      va='center', ha='left')