def get_masses(nu, box=0):
hmf = aemHMF.Aemulus_HMF()
#nu has locations of the ticks in the x axis
#Pick some cosmology, box=16
Ombh2, Omch2, w, ns, ln10As, H0, Neff, sig8 = np.genfromtxt(
AD.path_to_test_box_cosmologies())[int(box)]
h = H0 / 100.
Ob = Ombh2 / h**2
Oc = Omch2 / h**2
Om = Ob + Oc
cosmo = {
"om": Om,
"ob": Ob,
"ol": 1 - Om,
"h": h,
"s8": sig8,
"ns": ns,
"w0": w,
"Neff": Neff,
"wa": 0
}
hmf.set_cosmology(cosmo)
Ms = np.logspace(11, 17, num=100) #Msun/h
a = 1.0
nus = np.array([aemHMF.peak_height(Mi, a) for Mi in Ms])
from scipy.interpolate import interp1d
spl = interp1d(nus, Ms)
return spl(nu) #np.log10(spl(nu))
def calc_hmf(cosmos, zs):
import aemHMF
hmf = aemHMF.Aemulus_HMF()
Nc = len(cosmos)
Nz = len(zs)
dndlMs = np.zeros((Nc, Nz, len(M)))
for i in range(Nc):
Ombh2, Omch2, w, ns, ln10As, H0, Neff, sig8 = cosmos[i]
cosmo = {
'Obh2': Ombh2,
'Och2': Omch2,
'w0': w,
'n_s': ns,
'ln10^{10}A_s': ln10As,
'N_eff': Neff,
'H0': H0
}
hmf.set_cosmology(cosmo)
for j in range(Nz):
z = zs[j]
dndlMs[i, j] = hmf.dndlM(M, z)
continue
print("Finished with dndlM in box%d" % i)
continue
return dndlMs
def get_aemulus_beta(M, z):
import aemHMF
hmf = aemHMF.Aemulus_HMF()
hmf.set_cosmology()
d = 1.0001
dndM1 = hmf.dndlM(M, z) / M
dndM2 = hmf.dndlM(M * d, z) / (M * d)
return np.log(dndM2 / dndM1) / np.log(d)
def mf_obj(i):
Ombh2, Omch2, w, ns, ln10As, H0, Neff, sig8 = AD.building_box_cosmologies(
)[i]
cosmo = {
'Obh2': Ombh2,
'Och2': Omch2,
'w0': w,
'n_s': ns,
'ln10^{10}A_s': ln10As,
'N_eff': Neff,
'H0': H0
}
hmf = aemHMF.Aemulus_HMF()
hmf.set_cosmology(cosmo)
return hmf
def get_cosmo(i):
obh2, och2, w, ns, ln10As, H0, Neff, s8 = AD.building_box_cosmologies()[i]
aemcosmo={'Obh2':obh2, 'Och2':och2, 'w0':w, 'n_s':ns, 'ln10^{10}A_s':ln10As, 'N_eff':Neff, 'H0':H0}
import aemHMF
hmf = aemHMF.Aemulus_HMF()
hmf.set_cosmology(aemcosmo)
h = H0/100.
Omega_b = obh2/h**2
Omega_c = och2/h**2
Omega_m = Omega_b+Omega_c
params = {'output': 'mPk', 'h': h, 'ln10^{10}A_s': ln10As, 'n_s': ns, 'w0_fld': w, 'wa_fld': 0.0, 'Omega_b': Omega_b, 'Omega_cdm': Omega_c, 'Omega_Lambda': 1.- Omega_m, 'N_eff': Neff, 'P_k_max_1/Mpc':10., 'z_max_pk':10. }
cosmo = Class()
cosmo.set(params)
cosmo.compute()
return cosmo, h, Omega_m, hmf
def function_of_z(ax):
cosmo = default_cosmo.copy()
hmf = aemHMF.Aemulus_HMF()
hmf.set_cosmology(cosmo)
sigma = np.linspace(1, 6, num=30)
nu = deltac/sigma
Gz0 = hmf.multiplicity_sigma(sigma, 0.5)
for a in [1.0, 2./3., 0.5, 1./3., 0.25]:
z = 1./a - 1
G = hmf.multiplicity_sigma(sigma, a)
Y = (G-Gz0)/Gz0
ax.plot(nu, Y, label=r"$z=%.1f$"%z)
print "z = %f done"%z
#plt.title(r"$M_{low}$=%.1e $M_{high}$=%.1e"%(min(M), max(M)))
#plt.ylabel(r"$\frac{G(\sigma) - G(\sigma)_{fid}}{G(\sigma)_{fid}}$")
ax.set_xlabel(r"$\nu$")
ax.legend(loc="upper left", frameon=False, fontsize=12)
def function_of_sigma8(ax):
hmf = aemHMF.Aemulus_HMF()
a = 0.5
z = 1./a - 1
cosmo = default_cosmo.copy()
cosmo['s8'] = 0.8
hmf.set_cosmology(cosmo)
nu = np.linspace(1, 6, num=30)
sigma = deltac/nu
Gom0 = hmf.multiplicity_sigma(sigma, a)
for sig8 in [0.7, .75, 0.8, 0.85, .9]:
cosmo["s8"] = sig8
hmf.set_cosmology(cosmo)
G = hmf.multiplicity_sigma(sigma, a)
Y = (G - Gom0)/Gom0
ax.plot(nu, Y, label=r"$\sigma_8=%.2f$"%sig8)
print "z = %f done"%z
#ax.set_ylabel(r"$\frac{G(\sigma)-G(\sigma)_{fid}}{G(\sigma)_{fid}}$")
ax.set_xlabel(r"$\nu$")
ax.legend(loc="upper left", frameon=False, fontsize=12)
def function_of_Omegam(ax):
hmf = aemHMF.Aemulus_HMF()
a = 0.5
z = 1./a - 1
cosmo = default_cosmo.copy()
Om = 0.3
cosmo['om'] = Om
cosmo['ol'] = 1. - Om
hmf.set_cosmology(cosmo)
nu = np.linspace(1, 6, num=30)
sigma = deltac/nu
Gom0 = hmf.multiplicity_sigma(sigma, a)
for Om in [0.26, 0.28, 0.3, 0.32, 0.34]:
cosmo['om'] = Om
cosmo['ol'] = 1. - Om
hmf.set_cosmology(cosmo)
G = hmf.multiplicity_sigma(sigma, a)
Y = (G - Gom0)/Gom0
ax.plot(nu, Y, label=r"$\Omega_m=%.2f$"%Om)
print "z = %f done"%z
ax.set_ylabel(r"$\frac{G(\sigma) - G(\sigma)_{fid}}{G(\sigma)_{fid}}$")
ax.set_xlabel(r"$\nu$")
ax.legend(loc=0, frameon=False, fontsize=12)
def peakheight_test(M, box=0):
hmf = aemHMF.Aemulus_HMF()
#nu has locations of the ticks in the x axis
#Pick some cosmology, box=16
Ombh2, Omch2, w, ns, ln10As, H0, Neff, sig8 = np.genfromtxt(
AD.path_to_test_box_cosmologies())[int(box)]
h = H0 / 100.
Ob = Ombh2 / h**2
Oc = Omch2 / h**2
Om = Ob + Oc
cosmo = {
"om": Om,
"ob": Ob,
"ol": 1 - Om,
"h": h,
"s8": sig8,
"ns": ns,
"w0": w,
"Neff": Neff,
"wa": 0
}
hmf.set_cosmology(cosmo)
a = 0.25
return np.array([aemHMF.peak_height(Mi, a) for Mi in M])
AD.path_to_test_box_cosmologies())[box]
h = H0 / 100.
Ob = Ombh2 / h**2
Oc = Omch2 / h**2
Om = Ob + Oc
cosmo = {
"om": Om,
"ob": Ob,
"ol": 1 - Om,
"h": h,
"s8": sig8,
"ns": ns,
"w0": w,
"Neff": Neff
}
hmf = aemHMF.Aemulus_HMF()
hmf.set_cosmology(cosmo)
N_aem = hmf.n_bins(M_bins, a) * Volume
pdiff = (N - N_aem) / N_aem
f, axarr = plt.subplots(2, sharex=True)
axarr[0].loglog(M, N, ls='', marker='.', c='k')
axarr[0].loglog(M, N_aem, ls='-', c='b')
axarr[0].set_yscale('log')
axarr[1].plot(M, pdiff, c='b', ls='-')
axarr[1].axhline(0, c='k', ls='--')
plt.show()
def get_all_residuals(building_box=True, bf=False):
if building_box:
N_boxes = 40
cospath = AD.path_to_building_box_cosmologies()
outpath = "BB_residuals.txt"
if with_f: outpath = "BB_residuals_f.txt"
else:
N_boxes = 7
cospath = AD.path_to_test_box_cosmologies()
outpath = "test_residuals.txt"
if with_f: outpath = "test_residuals_f.txt"
if bf:
print "Working with best fits"
N_boxes = 40
cospath = AD.path_to_building_box_cosmologies()
outpath = "bestfit_residuals.txt"
N_snaps = 10
hmf = aemHMF.Aemulus_HMF()
z_arr = np.array([])
lM_arr = np.array([])
nu_arr = np.array([])
Residuals = np.array([])
Resid_err = np.array([])
N_arr = np.array([])
err_arr = np.array([])
Nt08_arr = np.array([])
boxnum_arr = np.array([])
snapnum_arr = np.array([])
for i in range(N_boxes):
Ombh2, Omch2, w, ns, ln10As, H0, Neff, sig8 = np.genfromtxt(cospath)[i]
h = H0 / 100.
Ob = Ombh2 / h**2
Oc = Omch2 / h**2
Om = Ob + Oc
cosmo = {
"om": Om,
"ob": Ob,
"ol": 1 - Om,
"h": h,
"s8": sig8,
"ns": ns,
"w0": w,
"Neff": Neff
}
hmf.set_cosmology(cosmo)
for j in range(N_snaps):
z, lM, nu, R, eR, N, err, Nt08, box, snap = get_residuals(
i, j, hmf, building_box, bf)
z_arr = np.concatenate([z_arr, z])
lM_arr = np.concatenate([lM_arr, lM])
nu_arr = np.concatenate([nu_arr, nu])
Residuals = np.concatenate([Residuals, R])
Resid_err = np.concatenate([Resid_err, eR])
N_arr = np.concatenate([N_arr, N])
err_arr = np.concatenate([err_arr, err])
Nt08_arr = np.concatenate([Nt08_arr, Nt08])
boxnum_arr = np.concatenate([boxnum_arr, box])
snapnum_arr = np.concatenate([snapnum_arr, snap])
print "Residuals made for the box at ", i, j
out = np.array([
z_arr, lM_arr, nu_arr, Residuals, Resid_err, N_arr, err_arr, Nt08_arr,
boxnum_arr, snapnum_arr
]).T
np.savetxt(outpath, out)
print "done, with_f = ", with_f, " building_box = ", building_box, " bestfits = ", bf
0.25, 0.333333, 0.5, 0.540541, 0.588235, 0.645161, 0.714286, 0.8, 0.909091,
1.0
])
z = 1. / scale_factors - 1.0
if __name__ == "__main__":
colors = get_colors()
use_nu = True
zs, lMs, nus, R, Re, N, err, Nt08, box, snap = np.genfromtxt(
"BB_residuals.txt", unpack=True)
if use_nu: x = nus
else: x = lMs
fgp = aemHMF.Aemulus_HMF().f
nugp = np.linspace(min(x) - .1, max(x) + .1, 100)
fig, axarr = plt.subplots(1, 2, sharey=True)
#First do the points
ax = 0
for i in range(len(z)):
if i not in [1, 9]: continue
inds = (z[i] == zs)
#print lMs[inds]
#print np.log10(get_masses(nus[inds], z[i]))
axarr[ax].plot(x[inds],
R[inds],
marker='.',
ls='',
markersize=1,
c=colors[i],