def get_box_resids(i):
cosmo, h, Omega_m = get_cosmo(i)
M = np.logspace(12, 16, num=200) #Msun/h
k = np.logspace(-5, 1, num=1000) #Mpc^-1
bfpath = "bf_%s_box%d.txt" % (name, i)
print i, name
params = np.loadtxt(bfpath)
zb = np.array([])
Mb = np.array([])
nub = np.array([])
R = np.array([])
Re = np.array([])
for j in range(0, 10): #snap
Mlo, Mhi, N, Mtot = AD.building_box_binned_mass_function(i, j).T
Mj = Mtot / N
Mb = np.concatenate((Mb, Mj))
zb = np.concatenate((zb, np.ones_like(N) * zs[j]))
edge = 10**np.concatenate((Mlo, Mhi[-1:]))
cov = AD.building_box_binned_mass_function_covariance(i, j)
icov = np.linalg.inv(cov)
err = np.sqrt(np.diag(cov))
p = np.array([cosmo.pk_lin(ki, zs[j]) for ki in k]) * h**3
nub = np.concatenate((nub, bias.nu_at_M(Mj, k / h, p, Omega_m)))
d, e, f, g = model_swap(params, name, x[j])
dndM = massfunction.dndM_at_M(M, k / h, p, Omega_m, d, e, f, g)
Nmodel = massfunction.n_in_bins(edge, M, dndM) * volume
R = np.concatenate((R, (Nmodel - N) / Nmodel))
Re = np.concatenate((Re, err / Nmodel))
return Mb, nub, zb, R, Re
def test_massfn():
from szar import counts
import hmf
from cluster_toolkit import massfunction
zs = np.linspace(0.,3.,20)
ms = np.geomspace(1e14,1e17,200)
ks = np.geomspace(1e-3,10,101)
from enlib import bench
with bench.show("init"):
hcos = hm.HaloModel(zs,ks,ms=ms,mass_function="tinker")
dndM_ct2 = np.zeros((zs.size,ms.size))
for i,z in enumerate(zs):
h = hmf.MassFunction(z=z,Mmin=np.log10(ms.min()*hcos.h),Mmax=np.log10(ms.max()*hcos.h))
if i==0: dndM_ct = np.zeros((zs.size,h.dndm.size))
dndM_ct[i,:] = h.dndm.copy()
dndM_ct2[i,:] = massfunction.dndM_at_M(ms*hcos.h, hcos.ks_sigma2/hcos.h, hcos.sPzk[i]*hcos.h**3, hcos.om0)
fsky = 0.4
hmf = counts.Halo_MF(counts.ClusterCosmology(hcos.params,skipCls=True),np.log10(ms),zs)
nz_szar = hmf.N_of_z()*fsky
print(nz_szar,nz_szar.shape)
# sys.exit()
print(hcos.nzm.shape,hcos.bh.shape)
bh = hcos.bh
nzm = hcos.nzm
# ims,ins = np.loadtxt("data/tinker2008Fig5.txt",unpack=True,delimiter=',')
# pl = io.Plotter(xyscale='linlin')
# pl.add(ims,ins,ls="--")
# pl.add(np.log10(ms*hcos.h),np.log10(nzm[0,:]*ms**2./hcos.rho_matter_z(0.)))
# pl.done()
chis = hcos.results.angular_diameter_distance(hcos.zs) * (1+hcos.zs)
nz = np.trapz(nzm,ms,axis=-1)*4.*np.pi*chis**2./hcos.results.h_of_z(hcos.zs)*fsky
nz_ct = np.trapz(dndM_ct,h.m,axis=-1)*4.*np.pi*chis**2./hcos.results.h_of_z(hcos.zs)*fsky * hcos.h**3.
nz_ct2 = np.trapz(dndM_ct2,ms,axis=-1)*4.*np.pi*chis**2./hcos.results.h_of_z(hcos.zs)*fsky * hcos.h**3.
pl = io.Plotter()
pl.add(zs,nz,label='hmvec')
pl.add(hmf.zarr,nz_szar,ls='--',label='szar')
pl.add(zs,nz_ct,ls='-.',label='hmf')
pl.add(zs,nz_ct2,ls='-.',label='ct')
pl.done()
n = np.trapz(nz,zs)
print(n)
n = np.trapz(nz_szar,hmf.zarr)
print(n)
n = np.trapz(nz_ct,zs)
print(n)
n = np.trapz(nz_ct2,zs)
print(n)
def test_mf_binned():
M2 = np.logspace(12, 16, num=100)
dn = mf.dndM_at_M(M2, k / h, p, Omega_m)
edges = np.logspace(12, 16, 11)
n = mf.n_in_bins(edges, M2, dn)
npt.assert_array_less(n[1:], n[:-1])
n2 = np.array([
mf.n_in_bin(edges[i], edges[i + 1], M2, dn)
for i in range(len(edges) - 1)
])
npt.assert_array_less(n2[1:], n2[:-1])
npt.assert_array_equal(n, n2)
def mass_func(pars, args):
x = args['x']
Omega_m = args['Omega_m']
M = args['M']
k = args['k']
ps = args['ps']
edges = args['edges'] #Msun/h
Nout = []
for i in range(len(x)):
d, e, f, g = model_swap(pars, args['name'], x[i])
dndM = massfunction.dndM_at_M(M, k, ps[i], Omega_m, d, e, f, g)
Nout.append(massfunction.n_in_bins(edges[i], M, dndM) * volume)
return Nout
def test_dndM_M():
n = mf.dndM_at_M(M, k / h, p, Omega_m) * M
npt.assert_array_less(n[1:], n[:-1])
"""
def test_dndM():
n = mf.dndM_at_M(M, k / h, p, Omega_m) * M
k2 = k / h
n2 = np.array([mf.dndM_at_M(Mi, k2, p, Omega_m) for Mi in M]) * M
npt.assert_array_equal(n, n2)