code: def inFootprint(self, pixels, nside=None):
          
          if np.isscalar(pixels): pixels = np.array([pixels])
          if nside is None: nside = self.nside_likelihood
  
          inside = np.zeros( len(pixels), dtype='bool')
          if not self.nside_catalog:
              catalog_pix = [0]
          else:
              catalog_pix = superpixel(pixels,nside,self.nside_catalog)
              catalog_pix = np.intersect1d(catalog_pix,self.catalog_pixels)
  
          for filenames in self.filenames[catalog_pix]:
              # ADW: Need to replace with healpix functions...
              #logger.debug("Loading %s"%filenames['mask_1'])
              #subpix_1,val_1 = ugali.utils.skymap.readSparseHealpixMap(filenames['mask_1'],'MAGLIM',construct_map=False)
              _n,subpix_1,val_1 = read_partial_map(filenames['mask_1'],'MAGLIM',fullsky=False)
              #logger.debug("Loading %s"%filenames['mask_2'])
              #subpix_2,val_2 = ugali.utils.skymap.readSparseHealpixMap(filenames['mask_2'],'MAGLIM',construct_map=False)
              _n,subpix_2,val_2 = read_partial_map(filenames['mask_2'],'MAGLIM',fullsky=False)
              subpix = np.intersect1d(subpix_1,subpix_2)
              superpix = np.unique(superpixel(subpix,self.nside_pixel,nside))
              inside |= np.in1d(pixels, superpix)
              
          return inside
docs: Open each valid filename for the set of pixels and determine the set 
          of subpixels with valid data.