IA profile v3

benchmarks/data/IA_halomodel_Cell_test.txt

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benchmarks/data/codes/IAhalo_normalisation_benchmark.py

@@ -0,0 +1,56 @@
+# 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
+
+
+if (__name__ == "__main__"):
+    Mhalo = np.logspace(10., 16, 30)  # Units Msol
+
+    z = 0.0
+
+    cosmo = ccl.Cosmology(Omega_c=0.25, Omega_b=0.05, Omega_k=0, sigma8=0.81, n_s=0.96, h=1.)
+
+    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)
+
+