def check_background(cosmo):
"""
Check that background and growth functions can be run.
"""
# Types of scale factor input (scalar, list, array)
a_scl = 0.5
a_lst = [0.2, 0.4, 0.6, 0.8, 1.]
a_arr = np.linspace(0.2, 1., 5)
# growth_factor
assert_( all_finite(ccl.growth_factor(cosmo, a_scl)) )
assert_( all_finite(ccl.growth_factor(cosmo, a_lst)) )
assert_( all_finite(ccl.growth_factor(cosmo, a_arr)) )
# growth_factor_unnorm
assert_( all_finite(ccl.growth_factor_unnorm(cosmo, a_scl)) )
assert_( all_finite(ccl.growth_factor_unnorm(cosmo, a_lst)) )
assert_( all_finite(ccl.growth_factor_unnorm(cosmo, a_arr)) )
# growth_rate
assert_( all_finite(ccl.growth_rate(cosmo, a_scl)) )
assert_( all_finite(ccl.growth_rate(cosmo, a_lst)) )
assert_( all_finite(ccl.growth_rate(cosmo, a_arr)) )
# comoving_radial_distance
assert_( all_finite(ccl.comoving_radial_distance(cosmo, a_scl)) )
assert_( all_finite(ccl.comoving_radial_distance(cosmo, a_lst)) )
assert_( all_finite(ccl.comoving_radial_distance(cosmo, a_arr)) )
# h_over_h0
assert_( all_finite(ccl.h_over_h0(cosmo, a_scl)) )
assert_( all_finite(ccl.h_over_h0(cosmo, a_lst)) )
assert_( all_finite(ccl.h_over_h0(cosmo, a_arr)) )
# luminosity_distance
assert_( all_finite(ccl.luminosity_distance(cosmo, a_scl)) )
assert_( all_finite(ccl.luminosity_distance(cosmo, a_lst)) )
assert_( all_finite(ccl.luminosity_distance(cosmo, a_arr)) )
# scale_factor_of_chi
assert_( all_finite(ccl.scale_factor_of_chi(cosmo, a_scl)) )
assert_( all_finite(ccl.scale_factor_of_chi(cosmo, a_lst)) )
assert_( all_finite(ccl.scale_factor_of_chi(cosmo, a_arr)) )
# omega_m_a
assert_( all_finite(ccl.omega_x(cosmo, a_scl, 'matter')) )
assert_( all_finite(ccl.omega_x(cosmo, a_lst, 'matter')) )
assert_( all_finite(ccl.omega_x(cosmo, a_arr, 'matter')) )
def Tspin(z, OmegaH, OmegaM):
## Formula from Tzu-Ching, in mK, arXiv:0709.3672
return 0.3 * (OmegaH / 1e-3) * np.sqrt(
(1 + z) / (2.5) * 0.29 / (OmegaM + (1. - OmegaM) / (1 + z)**3))
# first let's compute background values at our zs
for name, zs in [("zlow", zlow)]: #,("zhigh",zhigh)]:
f = open("background_%s.dat" % (name), 'w')
f.write(
"# z distance(z)[Mpc] growth(z)[normalised at z=0] f(z)=dlng/dlna Tspin(z) [mK] b(z) N(z) [Mpc^3] \n"
)
for z in zs:
print z
afact = 1. / (1 + z)
dist = ccl.luminosity_distance(cosmo, afact) # this is what class has
gf = ccl.growth_factor(cosmo, afact)
gr = ccl.growth_rate(cosmo, afact)
print z, gr
if z < 10:
Ts = Tspin(z, OmegaH, OmegaC)
bias = castorinaBias(z)
Pn = castorinaPn(z) / h**3 # converting from Mpc/h^3 to Mpc^3
else:
Ts = pritchardTSpin(z)
bias = 1.0
Pn = 0.0
f.write("%3.2f %g %g %g %g %g %g \n" %
(z, dist, gf, gr, Ts, bias, Pn))
f.close()
# next write power spectrum
def compare_with_ccl():
"""
Compare some results with CCL to check for accuracy.
"""
# Set-up CCL
import pyccl as ccl
p = default_params
OmegaB = 0.045
cosmo1 = ccl.Cosmology(Omega_c=p['omegaM'] - OmegaB,
Omega_b=OmegaB,
h=p['h'],
Omega_k=0.,
w0=-1.,
wa=0.,
A_s=2.1e-9,
n_s=0.96)
cosmo2 = ccl.Cosmology(Omega_c=p['omegaM'] - OmegaB,
Omega_b=OmegaB,
h=p['h'],
Omega_k=0.02,
w0=-1.,
wa=0.,
A_s=2.1e-9,
n_s=0.96)
cosmo3 = ccl.Cosmology(Omega_c=p['omegaM'] - OmegaB,
Omega_b=OmegaB,
h=p['h'],
Omega_k=0.02,
w0=-0.8,
wa=0.,
A_s=2.1e-9,
n_s=0.96,
m_nu=0.)
# Set z_eq to include massless neutrinos
p['z_eq'] = p['omegaM'] \
/ (cosmo1.params['Omega_g'] + cosmo1.params['Omega_n_rel']) - 1.
print(p['z_eq'])
# Expansion rate
a = np.logspace(-3., 0., 400)
ccl_H1 = (100. * p['h']) * ccl.h_over_h0(cosmo1, a)
ccl_H2 = (100. * p['h']) * ccl.h_over_h0(cosmo2, a)
ccl_H3 = (100. * p['h']) * ccl.h_over_h0(cosmo3, a)
this_H1 = Hz(a, pdict(w0=-1., winf=-1., omegaK=0., zc=2., deltaz=0.5))
this_H2 = Hz(a, pdict(w0=-1., winf=-1., omegaK=0.02, zc=2., deltaz=0.5))
this_H3 = Hz(a, pdict(w0=-0.8, winf=-0.8, omegaK=0.02, zc=2., deltaz=0.5))
# Angular diameter distance
ccl_DA1 = ccl.luminosity_distance(cosmo1, a) * a**2.
ccl_DA2 = ccl.luminosity_distance(cosmo2, a) * a**2.
ccl_DA3 = ccl.luminosity_distance(cosmo3, a) * a**2.
this_DA1 = DAz(a, pdict(w0=-1., winf=-1., omegaK=0., zc=2., deltaz=0.5))
this_DA2 = DAz(a, pdict(w0=-1., winf=-1., omegaK=0.02, zc=2., deltaz=0.5))
this_DA3 = DAz(a, pdict(w0=-0.8, winf=-0.8, omegaK=0.02, zc=2.,
deltaz=0.5))
# Plot comparisons
P.subplot(121)
P.plot(a, this_H1 / ccl_H1 - 1., 'k-', lw=1.8)
P.plot(a, this_H2 / ccl_H2 - 1., 'r-', lw=1.8)
P.plot(a, this_H3 / ccl_H3 - 1., 'b-', lw=1.8)
P.xscale('log')
P.subplot(122)
P.plot(a, this_DA1 / ccl_DA1 - 1., 'k-', lw=1.8)
P.plot(a, this_DA2 / ccl_DA2 - 1., 'r-', lw=1.8)
P.plot(a, this_DA3 / ccl_DA3 - 1., 'b-', lw=1.8)
P.xscale('log')
P.tight_layout()
P.show()
bcm_log10Mc=14.079181246047625, bcm_etab=0.5, bcm_ks=55.0)
# Cosmology where the power spectrum will be computed with an emulator.
cosmo_emu = ccl.Cosmology(Omega_c=0.27, Omega_b=0.05, h=0.67, sigma8=0.83, n_s=0.96,
Neff=3.04, Omega_k=0., transfer_function='emulator',
matter_power_spectrum="emu")
# background quantities
z = np.linspace(0.0001, 5., 100)
a = 1. / (1.+z)
# Compute distances
chi_rad = ccl.comoving_radial_distance(cosmo, a)
chi_ang = ccl.comoving_angular_distance(cosmo,a)
lum_dist = ccl.luminosity_distance(cosmo, a)
dist_mod = ccl.distance_modulus(cosmo, a)
# Plot the comoving radial distance as a function of redshift, as an example.
plt.figure()
plt.plot(z, chi_rad, 'k', linewidth=2)
plt.xlabel('$z$', fontsize=20)
plt.ylabel('Comoving distance, Mpc', fontsize=15)
plt.tick_params(labelsize=13)
# plt.show()
plt.close()
# Compute growth quantities :
D = ccl.growth_factor(cosmo, a)
f = ccl.growth_rate(cosmo, a)