def hmf(self, z, Mmin, Mmax, q_out = 'dndlnM', hmf_code='colossus', print_cosmo=False):
if(hmf_code=='colossus'):
params = {'flat': True, 'H0': self.H0, 'Om0': self.om, 'Ob0': self.ob, 'sigma8': self.sigma8, 'ns': self.ns}
col_cosmology.addCosmology('myCosmo', params)
colcosmo=col_cosmology.setCosmology('myCosmo')
if print_cosmo:
print(colcosmo)
#Mass_bin = np.logspace(np.log10(Mmin),np.log10(Mmax), num=500)
Mh = 10**(np.linspace(np.log10(Mmin),np.log10(Mmax), num=200))
Mh=Mh/self.h
#mfunc = mass_function.massFunction(Mh, z, mdef = self.halo_model_mdef, model = self.halo_model, q_out = q_out)
mfunc = mass_function.massFunction(Mh, z, mdef = '200m', model = 'tinker08', q_out = q_out)
mpc_to_m= 3.086e+22
mfunc*=(mpc_to_m)**-3
dndm=mfunc
return Mh, dndm
if(hmf_code=='hmf'):
from hmf import cosmo as cosmo_hmf
my_cosmo = cosmo_hmf.Cosmology()
my_cosmo.update(cosmo_params={"H0":self.H0,"Om0":self.om,"Ode0":self.ol,"Ob0":self.ob})
mf=MassFunction(Mmin=np.log10(Mmin), Mmax=np.log10(Mmax), hmf_model= 'ST')
mf.update(z=z)
mpc_to_m= 3.086e+22
#hm, dndm= mf.m, mf.dndlnm
hm, dndm= mf.m/self.h, mf.dndlnm *(mpc_to_m)**-3 #* self.h**4*(mpc_to_m)**-3
# dndm*=(mpc_to_m)**-3
return hm, dndm
Om_a, H0_a, ns_a, sigma8_a, delta_a = AllCombinations[idx]
#for Om, dc in [(xi,yj) for xi in AllOm for yj in delta_h]:
#print x, y
print(Om_a, H0_a, ns_a, sigma8_a, delta_a)
print '-----------------'
# Standard Cosmology
#HaloMF = MassFunction(cosmo_model = cosmo.WMAP5)
#my_cosmo = cosmo.Cosmology(cosmo_model=cosmo.WMAP5)
# Custom cosmology
#new_model = LambdaCDM(H0 = 75.0, Om0= 0.4, Tcmb0 = 2.7, Ob0 = 0.3, Ode0=0.4)
new_model = LambdaCDM(H0 = H0_a, Om0= Om_a, Tcmb0 = 2.7, Ob0 = 0.1, Ode0=1-Om_a)
HaloMF = MassFunction(cosmo_model = new_model, delta_h = delta_a, sigma_8 = sigma8_a)
HaloMF.update(n = ns_a)
my_cosmo = cosmo.Cosmology(cosmo_model = new_model)
k = np.logspace(np.log(1e-3), np.log(5), 100)
delta_k =
sigma_8 = 0.8
z = 0.0
hmf.halofit.halofit(k, delta_k, sigma_8, z, cosmo=None, takahashi=True)
print HaloMF.parameter_values # Check for parameters properly
cumulative_mass_func = HaloMF.ngtm
xxy = np.hstack( [Om_a, H0_a, ns_a, sigma8_a, delta_a , cumulative_mass_func[::10]] )
y = np.vstack( (y, xxy) )
def main():
# set cosmology and linear power spectrum
'''
H0=70.0
Omega_M=0.279000
Omega_b=0.046100
w0=-1.000000
Omega_k=0.000000
n_s=0.972000
inputPk="../input_pk/wmap9_fid_matterpower_z0.dat"
nH = 2.4e21
opt = 1
'''
H0 = 67.32117
Omega_M = 0.3158
Omega_b = 0.0490
w0 = -1.000000
Omega_k = 0.000000
n_s = 0.96605
inputPk = "../input_pk/planck_2018_test_matterpower.dat"
nH = 2.4e21
opt = 1
xx_power.init_cosmology(H0, Omega_M, Omega_b, w0, Omega_k, n_s, nH,
inputPk, opt)
shot_noise = 0.00
ell = 10.**np.linspace(np.log10(10.), np.log10(3.e4), 31)
theta_fid = [
4.0, 3.e-5, 0.0800, 0.120000, 1.000000, 0.180000, 0.800000, 0.500000,
0.10000, 1.720000, 0.195000, 0.010000, 0.800000, 0.9, 1.0, 6.0, 3.0
]
param_ind_dict = {
'eps_f': 0,
'eps_DM': 1,
'f_star': 2,
'S_star': 3,
'A_C': 4,
'alpha_nt': 5,
'n_nt': 6,
'beta_nt': 7,
'gamma_mod0': 8,
'gamma_mod_zslope': 9,
'x_break': 10,
'x_smooth': 11,
'n_nt_mod': 12,
'clump0': 13,
'clump_zslope': 14,
'x_clump': 15,
'alpha_clump1': 16,
}
param_label_dict = {
'eps_f': r'$\epsilon_f/10^{-6}$',
'eps_DM': r'$\epsilon_{DM}$',
'f_star': r'$f_\star$',
'S_star': r'$S_\star$',
'A_C': r'$A_C$',
'alpha_nt': r'$\alpha_{nt}$',
'n_nt': r'$n_{nt}$',
'beta_nt': r'$\beta_{nt}$',
'gamma_mod0': r'$\Gamma_0$',
'gamma_mod_zslope': r'$\beta_\Gamma$',
'n_nt_mod': '$n_{nt,mod}$',
'clump0': r'$C_0$',
'clump_zslope': r'$\beta_C$',
'x_clump': r'$x_{C}$',
'alpha_clump1': r'$\alpha_{C1}$',
'alpha_clump2': r'$\alpha_{C2}$'
}
#rosat_ell, rosat_cl, rosat_var = read_data("../ROSAT/rosat_R4_R7_mask_hfi_R2_small_ell.txt")
#rosat_cl *= rosat_ell*(rosat_ell+1.)/(2.0*math.pi)
#rosat_cl_err = np.sqrt(rosat_var)*rosat_ell*(rosat_ell+1.)/(2.0*math.pi)
#params = ['eps_f', 'f_star', 'S_star', 'alpha_nt', 'n_nt', 'beta_nt', 'gamma_mod0', 'gamma_mod_zslope', 'clump0', 'clump_zslope', 'x_clump', 'alpha_clump1', 'alpha_clump2' ]
params = ['eps_f', 'f_star', 'clump0']
redshift, dlz = np.linspace(-4, np.log10(3.0), 10, retstep=True)
redshift = 10**redshift
print(dlz)
my_cosmo = cosmo.Cosmology()
hubble = my_cosmo.cosmo.h
print(hubble)
mvir, dlm = np.linspace(13, 16, 20, retstep=True)
flux, dlf = np.linspace(-20, -10, 20, retstep=True)
mvir = 10**mvir
flux = 10**flux
Nsperster = np.zeros(flux.shape)
redo = False
if redo:
for iv, f in enumerate(flux):
for iz, z in enumerate(redshift):
dVdz = my_cosmo.cosmo.differential_comoving_volume(
z).value * hubble**3
s = []
for mass in mvir:
ff, m500 = xray_flux(mass, z, theta_fid)
s.append(ff)
s = np.array(s)
mlim = np.interp(f, s, mvir)
#h = hmf.MassFunction(z=z, Mmin=13, Mmax=16, dlog10m=0.1)
h = hmf.MassFunction(z=z)
Nm = 0.0
for im, mass in enumerate(h.m):
if mass >= mlim:
Nm += h.dlog10m * h.dndlog10m[im] * dVdz * z * dlz
Nsperster[iv] += Nm
np.save("logNlogS.npy", Nsperster)
surveys = ["CDFS", "COSMOS", "XXL", "S82", "RASS"]
areas = [0.25, 2.0, 50.0, 31.0, 4.0 * 3.141592 * ster2sqdeg * 0.25]
sens = [0.66e-15, 1.7e-15, 5e-15, 0.87e-15, 5.6e-13]
fig = plt.figure(figsize=(4, 4))
ax = fig.add_axes([0.21, 0.16, 0.75, 0.75])
print(areas, sens)
ax.scatter(areas, sens, s=1.0, marker='o')
for i, txt in enumerate(surveys):
ax.annotate(txt, (areas[i], sens[i]))
ax.set_xlabel(r'Area [deg$^2$]')
ax.set_ylabel(r'flux [erg/s/cm$^2$]')
ax.set_xscale('log')
ax.set_yscale('log')
#ax.set_xlim(1e-2, 1e5 )
#ax.set_ylim(1e-16, 1e-12)
#ax.legend(loc='best')
plt.show()
fig.savefig("wedding_test.png")
fig.clf()
plt.axis([6, 11.5, 1e-6, 5e0])
leg = plt.legend(loc='upper right', numpoints=1, labelspacing=0.1)
leg.draw_frame(False) # Don't want a box frame
for t in leg.get_texts(): # Reduce the size of the text
t.set_fontsize(PlotScripts.global_legendsize)
outputFile = "hmf_z{0:.2f}.png".format(z)
#plt.savefig(outputFile, bbox_inches='tight') # Save the figure
#print('Saved file to {0}'.format(outputFile))
#plt.close()
if __name__ == '__main__':
PlotScripts.Set_Params_Plot()
filepath = '/lustre/projects/p004_swin/bsmith/1.6Gpc/means/halo_1721673/dm_gadget/data/'
cosmol = AllVars.Set_Params_Britton(
) # Set the parameters for Britton's model.
my_cosmo = cosmo.Cosmology(cosmo_model=cosmol) # Update the hmf cosmology.
britton_cosmo = FlatLambdaCDM(H0=69.5, Om0=0.285, Ob0=0.04845)
hmf = MassFunction()
hmf.update(cosmo_params={"H0": 69.5, "Om0": 0.285}, Mmax=11, Mmin=6)
for snapshot_idx in range(snaplow, snaphigh + 1):
#plot_snapshot(filepath, snapshot_idx, 0, 0)
#plot_density_grid(filepath, snapshot_idx, 128)
#plot_halos(filepath, snapshot_idx)
#check_bounds(filepath, snapshot_idx)
plot_hmf(filepath, snapshot_idx, hmf)