docs: def toy_background(self,mc_source_id=2,seed=None):
          """
          Quick uniform background generation.
          """
  
          logger.info("Running toy background simulation...")
          size = 20000
          nstar = np.random.poisson(size)
          #np.random.seed(0)
          logger.info("Simulating %i background stars..."%nstar)
  
          ### # Random points from roi pixels
          ### idx = np.random.randint(len(self.roi.pixels)-1,size=nstar)
          ### pix = self.roi.pixels[idx]
  
          # Random points drawn from subpixels
          logger.info("Generating uniform positions...")
          idx = np.random.randint(0,len(self.subpix)-1,size=nstar)
          lon,lat = pix2ang(self.nside_subpixel,self.subpix[idx])
  
          pix = ang2pix(self.nside_pixel, lon, lat)
          lon,lat = pix2ang(self.nside_pixel,pix)
  
          # Single color
          #mag_1 = 19.05*np.ones(len(pix))
          #mag_2 = 19.10*np.ones(len(pix))
  
          # Uniform in color
          logger.info("Generating uniform CMD...")
          mag_1 = np.random.uniform(self.config['mag']['min'],self.config['mag']['max'],size=nstar)
          color = np.random.uniform(self.config['color']['min'],self.config['color']['max'],size=nstar)
  
          mag_2 = mag_1 - color
  
          # There is probably a better way to do this step without creating the full HEALPix map
          mask = -1. * np.ones(hp.nside2npix(self.nside_pixel))
          mask[self.roi.pixels] = self.mask.mask_1.mask_roi_sparse
          mag_lim_1 = mask[pix]
          mask = -1. * np.ones(hp.nside2npix(self.nside_pixel))
          mask[self.roi.pixels] = self.mask.mask_2.mask_roi_sparse
          mag_lim_2 = mask[pix]
          
          #mag_err_1 = 1.0*np.ones(len(pix))
          #mag_err_2 = 1.0*np.ones(len(pix))
          mag_err_1 = self.photo_err_1(mag_lim_1 - mag_1)
          mag_err_2 = self.photo_err_2(mag_lim_2 - mag_2)
          mc_source_id = mc_source_id * np.ones(len(mag_1))
  
          select = (mag_lim_1>mag_1)&(mag_lim_2>mag_2)
  
          hdu = ugali.observation.catalog.makeHDU(self.config,mag_1[select],mag_err_1[select],
                                                  mag_2[select],mag_err_2[select],
                                                  lon[select],lat[select],mc_source_id[select])
          catalog = ugali.observation.catalog.Catalog(self.config, data=hdu.data)
          return catalog