old_contents: from astropy.cosmology import Planck13 as cosmo
  
  # default parameters
  h = cosmo.h
  Om_M = cosmo.Om0
  Om_L = 1. - Om_M
  
  
  def bias(mass_halo, z_halo, h=h, Om_M=Om_M, Om_L=Om_L):
      """Calculate halo bias, from Seljak & Warren 2004.
  
      Parameters
      ----------
      mass_halo : ndarray or float
          Halo mass to calculate bias for.
      z_halo : ndarray or float
          Halo z, same type and size as mass_halo.
      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.
      """
      M_nl_0 = (8.73 / h) * (10. ** 12.)         # nonlinear mass today [M_sun]
      M_nl = M_nl_0 * (Om_M + Om_L / ((1. + z_halo) ** 3.))  # scaled to z_lens
      x = mass_halo / M_nl
      b = 0.53 + 0.39 * (x ** 0.45) + 0.13 / (40. * x +
                                              1.) + (5.e-4) * (x ** 1.5)
      return b
  
new_contents: from astropy.cosmology import Planck13 as cosmo
  
  # default parameters
  h = cosmo.h
  Om_M = cosmo.Om0
  Om_L = 1. - Om_M
  
  
  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_halo.
      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.
      """
      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
  
subject: simplify input parameter names