docs: def make_qq_plot(kev, obs, mdl, unit, key_text):
      """Make a quantile-quantile plot comparing events and a model.
  
      *kev*
        A 1D, sorted array of event energy bins measured in keV.
      *obs*
        A 1D array giving the number or rate of events in each bin.
      *mdl*
        A 1D array giving the modeled number or rate of events in each bin.
      *unit*
        Text describing the unit in which *obs* and *mdl* are measured; will
        be shown on the plot axes.
      *key_text*
        Text describing the quantile-quantile comparison quantity; will be
        shown on the plot legend.
      Returns:
        An :class:`omega.RectPlot` instance.
  
      *TODO*: nothing about this is Sherpa-specific. Same goes for some of the
      plotting routines in :mod:`pkwit.environments.casa.data`; might be
      reasonable to add a submodule for generic X-ray-y plotting routines.
  
      """
      import omega as om
  
      kev = np.asarray(kev)
      obs = np.asarray(obs)
      mdl = np.asarray(mdl)
  
      c_obs = np.cumsum(obs)
      c_mdl = np.cumsum(mdl)
      mx = max(c_obs[-1], c_mdl[-1])
  
      p = om.RectPlot()
      p.addXY([0, mx], [0, mx], '1:1')
      p.addXY(c_mdl, c_obs, key_text)
  
      # HACK: this range of numbers is chosen to give reasonable sampling for my
      # sources, which are typically quite soft.
      locs = np.array([0, 0.05, 0.08, 0.11, 0.17, 0.3, 0.4, 0.7, 1]) * (kev.size - 2)
      c0 = mx * 1.05
      c1 = mx * 1.1
  
      for loc in locs:
          i0 = int(np.floor(loc))
          frac = loc - i0
          kevval = (1 - frac) * kev[i0] + frac * kev[i0+1]
          mdlval = (1 - frac) * c_mdl[i0] + frac * c_mdl[i0+1]
          obsval = (1 - frac) * c_obs[i0] + frac * c_obs[i0+1]
          p.addXY([mdlval, mdlval], [c0, c1], '%.2f keV' % kevval, dsn=2)
          p.addXY([c0, c1], [obsval, obsval], None, dsn=2)
  
      p.setLabels('Cumulative model ' + unit, 'Cumulative data ' + unit)
      p.defaultKeyOverlay.vAlign = 0.3
      return p