code: def subsample_snps_map(seqchunk, nmask, maparr):
      
      ## mask columns that contain Ns
      rmask = np.zeros(seqchunk.shape[1], dtype=np.bool_)
  
      ## apply mask to the mapfile
      last_loc = -1
      for idx in xrange(maparr.shape[0]):
          if maparr[idx] != last_loc:
              if not nmask[idx]:
                  rmask[idx] = True
              last_loc = maparr[idx]
      
      ## apply mask
      #newarr = seqchunk[:, rmask]
      
      ## return smaller Nmasked array
      return rmask
docs: removes ncolumns from snparray prior to matrix calculation, and 
      subsamples 'linked' snps (those from the same RAD locus) such that
      for these four samples only 1 SNP per locus is kept. This information
      comes from the 'map' array (map file).