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* IA profile --------- Co-authored-by: Nick Koukoufilippas <nikfilippas@gmail.com> Co-authored-by: Christos Georgiou <chr.p.georgiou@gmail.com>
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| # Taken from github.com/c-d-leonard/IA_GGL/blob/CCL_IAhalo_bm/ | ||
| # Written by Danielle Leonard. | ||
| # This is script is intended to provide code to benchmark the | ||
| # integration over the halo mass function and HOD quantities for | ||
| # the IA halo model in CCL | ||
|
|
||
| import numpy as np | ||
| import scipy.integrate | ||
| import pyccl as ccl | ||
|
|
||
|
|
||
| def normalisation(Mhalo, cosmo, conc, z): | ||
| """ Returns the 'normalisation factor' that goes into the IA halo model | ||
| power spectrum: satelite fraction * Nsat / tot_ns as a function of Mhalo. | ||
| Mhalo is the vector of halo masses over which to integrate in units of Msol | ||
| cosmo is a pyccl cosmology object | ||
| conc is a concentration relation object | ||
| z is the redshift at which to calculate this | ||
| """ | ||
|
|
||
| # Get the halo mass function | ||
| HMF_setup = ccl.halos.MassFuncTinker10(cosmo) | ||
| HMF = HMF_setup.get_mass_function(cosmo, Mhalo, 1. / (1. + z)) | ||
|
|
||
| # Get HOD quantities we need | ||
| HODHProf = ccl.halos.HaloProfileHOD(conc) | ||
| Ncen_lens = HODHProf._Nc(Mhalo, 1. / (1. + z)) | ||
| Nsat_lens = HODHProf._Ns(Mhalo, 1. / (1. + z)) | ||
|
|
||
| # Get total number of satellite galaxies | ||
| tot_ns = scipy.integrate.simps(Ncen_lens * Nsat_lens * HMF, np.log10(Mhalo)) | ||
| tot_nc = scipy.integrate.simps((Ncen_lens) * HMF, np.log10(Mhalo)) | ||
|
|
||
| tot_all = tot_ns + tot_nc | ||
|
|
||
| # Fraction of satellites: | ||
| f_s = tot_ns / tot_all | ||
|
|
||
| return f_s / tot_ns * Nsat_lens | ||
|
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||
|
|
||
| if (__name__ == "__main__"): | ||
| Mhalo = np.logspace(10., 16, 30) # Units Msol | ||
|
|
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| z = 0.0 | ||
|
|
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| cosmo = ccl.Cosmology(Omega_c=0.25, Omega_b=0.05, Omega_k=0, sigma8=0.81, n_s=0.96, h=1.) | ||
|
|
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| concentration = ccl.halos.ConcentrationDuffy08() | ||
|
|
||
| norm_term = normalisation(Mhalo, cosmo, concentration, z) | ||
|
|
||
| save = np.column_stack((Mhalo, norm_term)) | ||
| np.savetxt('../IA_halomodel_norm_term.dat', save) | ||
|
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||
|
|
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