docs: def bias(mass, z, h=h, Om_M=Om_M, Om_L=Om_L):
      """Calculate halo bias, from Seljak & Warren 2004.
  
      Parameters
      ----------
      mass : ndarray or float
          Halo mass to calculate bias for.
      z : ndarray or float
          Halo z, same type and size as mass.
      h : float, optional
          Hubble parameter, defaults to astropy.cosmology.Planck13.h
      Om_M : float, optional
          Fractional matter density, defaults to
          astropy.cosmology.Planck13.Om0
      Om_L : float, optional
          Fractional dark energy density, defaults to 1-Om_M.
  
      Returns
      ----------
      ndarray or float
          Returns the halo bias, of same type and size as input mass_halo and
          z_halo. Calculated according to Seljak & Warren 2004 for z = 0.
          For halo z > 0, the non-linear mass is adjusted using the input
          cosmological parameters.
  
      References
      ----------
      Based on fitting formula derived from simulations in:
  
      U. Seljak and M.S. Warren, "Large-scale bias and stochasticity of
      haloes and dark matter," Monthly Notices of the Royal Astronomical
      Society, Volume 355, Issue 1, pp. 129-136 (2004).
      """
      M_nl_0 = (8.73 / h) * (10. ** 12.)         # nonlinear mass today [M_sun]
      M_nl = M_nl_0 * (Om_M + Om_L / ((1. + z) ** 3.))  # scaled to z_lens
      x = mass / M_nl
      b = 0.53 + 0.39 * (x ** 0.45) + 0.13 / (40. * x +
                                              1.) + (5.e-4) * (x ** 1.5)
      return b