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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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