def __init__(self):
self.wdm = wdm.MassFunctionWDM(alter_model=wdm.Schneider12_vCDM, wdm_mass=3.0, wdm_model=wdm.Viel05)
self.cdm = hmf.MassFunction()
def __init__(self):
self.wdm = wdm.TransferWDM(wdm_mass=3.0, wdm_model=wdm.Viel05)
self.cdm = hmf.MassFunction()
def __init__(self):
self.wdm = wdm.MassFunctionWDM(alter_model=None, wdm_mass=3.0, wdm_model=wdm.Viel05)
self.cdm = hmf.MassFunction()
def __init__(self):
self.cdm = hmf.MassFunction()
self.cls = wdm.Lovell14(m=self.cdm.m, dndm0=self.cdm.dndm)
def __init__(self):
self.cdm = hmf.MassFunction()
self.cls = wdm.Schneider12(m=self.cdm.m, dndm0=self.cdm.dndm)
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()
def test_incorrect_update_arg():
t = hmf.MassFunction()
t.update(wrong_arg=3)
def test_incorrect_argument():
t = hmf.MassFunction(wrong_arg=3)