text: import numpy as np
  from ..mapping import Mapper
  from ..utils import choose_pixelization
  import healpy
  
  def test_mapper():
      # 12 pixels
      nside = 1
      scheme = choose_pixelization(pixelization='healpix', nside=nside)
      mapper = Mapper(scheme, [0], [0])
      npix = healpy.nside2npix(nside)
      pix = np.arange(npix)
      ra, dec = healpy.pix2ang(nside, pix, lonlat=True)
  
      N = 5
      for i in range(N):
          data = {
              'ra': ra,
              'dec': dec,
              'source_bin': np.zeros(npix, dtype=float),
              'weight': np.ones(npix, dtype=float),
              'lens_bin': np.zeros(npix, dtype=float),
              'lens_weight': np.ones(npix, dtype=float),
              'g1': pix.astype(float) * 2,
              'g2': np.ones(npix) * i,
  
          }
          # same data multiple times so we can
          # get variances
          mapper.add_data(data)
  
      pixel, ngal, lens_weight, g1, g2, var_g1, var_g2, source_weight = mapper.finalize()
  
      mu_2 = (N - 1) / 2
      # variance
      var_2 = (N - 1) * (2 * N - 1) / 6 - mu_2**2
      # variance on mean
      var_2 /= N
  
      # should see all pixels
      assert np.allclose(pixel, pix)
      # all lens pixels hit once
      assert np.all(ngal[0]==5)
      # averaged down
      assert np.allclose(g1[0], pix*2)
      assert np.allclose(g2[0], mu_2)
      # no variance for g1, since constant
      # for
      assert np.allclose(var_g1[0], 0.0)
      assert np.allclose(var_g2[0], var_2)
      assert np.allclose(source_weight[0], 5)
      assert np.allclose(lens_weight[0], 5)
  
  