Calculate an approximate pixel coverage fraction from the two masks.

        We have no way to know a priori how much the coverage of the
        two masks overlap in a give pixel. For example, masks that each
        have frac = 0.5 could have a combined frac = [0.0 to 0.5]. 
        The limits will be: 
          max:  min(frac1,frac2)
          min:  max((frac1+frac2)-1, 0.0)

        Sometimes we are lucky and our fracdet is actually already
        calculated for the two masks combined, so that the max
        condition is satisfied. That is what we will assume...

def _fracRoiSparse(self):
        """
        Calculate an approximate pixel coverage fraction from the two masks.

        We have no way to know a priori how much the coverage of the
        two masks overlap in a give pixel. For example, masks that each
        have frac = 0.5 could have a combined frac = [0.0 to 0.5]. 
        The limits will be: 
          max:  min(frac1,frac2)
          min:  max((frac1+frac2)-1, 0.0)

        Sometimes we are lucky and our fracdet is actually already
        calculated for the two masks combined, so that the max
        condition is satisfied. That is what we will assume...
        """
        self.frac_roi_sparse = np.min([self.mask_1.frac_roi_sparse,self.mask_2.frac_roi_sparse],axis=0)
        return self.frac_roi_sparse