code: def power_chisq_at_points_from_precomputed(corr, snr, snr_norm, bins, indices):
      
      num_bins = len(bins) - 1
      chisq = shift_sum(corr, indices, bins) # pylint:disable=assignment-from-no-return
      return (chisq * num_bins - (snr.conj() * snr).real) * (snr_norm ** 2.0)
docs: Calculate the chisq timeseries from precomputed values for only select points.
  
      This function calculates the chisq at each point by explicitly time shifting
      and summing each bin. No FFT is involved.
  
      Parameters
      ----------
      corr: FrequencySeries
          The product of the template and data in the frequency domain.
      snr: numpy.ndarray
          The unnormalized array of snr values at only the selected points in `indices`.
      snr_norm: float
          The normalization of the snr (EXPLAINME : refer to Findchirp paper?)
      bins: List of integers
          The edges of the equal power bins
      indices: Array
          The indices where we will calculate the chisq. These must be relative
          to the given `corr` series.
  
      Returns
      -------
      chisq: Array
          An array containing only the chisq at the selected points.