docs: def prophist2d(self,propx,propy, mask=None,
                     logx=False,logy=False,
                     fig=None,selected=False,**kwargs):
          """Makes a 2d density histogram of two given properties
  
          :param propx,propy:
              Names of properties to histogram.  Must be names of columns
              in ``self.stars`` table.
  
          :param mask: (optional)
              Boolean mask (``True`` is good) to say which indices to plot.
              Must be same length as ``self.stars``.
  
          :param logx,logy: (optional)
              Whether to plot the log10 of x and/or y properties.
  
          :param fig: (optional)
              Argument passed to :func:`plotutils.setfig`.
  
          :param selected: (optional)
              If ``True``, then only the "selected" stars (that is, stars
              obeying all distribution constraints attached to this object)
              will be plotted.  In this case, ``mask`` will be ignored.
  
          :param kwargs:
              Additional keyword arguments passed to :func:`plotutils.plot2dhist`.
  
          """
  
          if mask is not None:
              inds = np.where(mask)[0]
          else:
              if selected:
                  inds = self.selected.index
              else:
                  inds = self.stars.index
  
          if selected:
              xvals = self.selected[propx].iloc[inds].values
              yvals = self.selected[propy].iloc[inds].values
          else:
              if mask is None:
                  mask = np.ones_like(self.stars.index)
              xvals = self.stars[mask][propx].values
              yvals = self.stars[mask][propy].values
  
          #forward-hack for EclipsePopulations...
          #TODO: reorganize.
          if propx=='depth' and hasattr(self,'depth'):
              xvals = self.depth.iloc[inds].values
          if propy=='depth' and hasattr(self,'depth'):
              yvals = self.depth.iloc[inds].values
  
          if logx:
              xvals = np.log10(xvals)
          if logy:
              yvals = np.log10(yvals)
  
          plot2dhist(xvals,yvals,fig=fig,**kwargs)
          plt.xlabel(propx)
          plt.ylabel(propy)