except:
N2 = hmf.N_of_z_SZ(SZProf) * fsky
np.savetxt("tempSigN.txt", hmf.sigN)
pl = Plotter()
pl.plot2d(hmf.sigN)
pl.done(outDir + "signRefactor.png")
pl = Plotter(scaleY='log')
pl.add(zs, N1)
pl.add(zs, N2)
Ntot1 = np.trapz(N2, zs)
print(Ntot1)
sn, ntot = hmf.Mass_err(fsky, outmerr, SZProf)
print(ntot)
#q_arr = np.logspace(np.log10(6.),np.log10(500.),64)
qs = [6., 500., 64]
qbin_edges = np.logspace(np.log10(qs[0]), np.log10(qs[1]), int(qs[2]) + 1)
q_arr = old_div((qbin_edges[1:] + qbin_edges[:-1]), 2.)
dnqmz = hmf.N_of_mqz_SZ(outmerr, qbin_edges, SZProf)
print((qbin_edges.shape))
print((dnqmz.shape))
N, Nofz = getTotN(dnqmz, Mexp_edges, z_edges, qbin_edges, returnNz=True)
print((N * fsky))
#MM = 10**np.linspace(13.,14.,5)
#print SZProfExample.quickVar(MM,zz,tmaxN=tmaxN,numts=numts)
#sys.exit()
#print z_edges
#print HMF.N_of_z()
Nzs = HMF.N_of_z_SZ(fsky,SZProfExample)*np.diff(z_edges)
zcents = old_div((z_edges[1:]+z_edges[:-1]),2.)
pl = Plotter()
pl.add(zcents,Nzs)
pl.done("nz.png")
print((HMF.Mass_err(fsky,lndM*24.0,SZProfExample)))
#print "quickvar " , np.sqrt(SZProfExample.quickVar(MM,zz,tmaxN=tmaxN,numts=numts))
#print "filtvar " , np.sqrt(SZProfExample.filter_variance(MM,zz))
#print "y_m",SZProfExample.Y_M(MM,zz)
#R500 = cc.rdel_c(MM,zz,500.).flatten()[0]
#print R500
#print cc.rhoc(0)
noise = listFromConfig(Config, experimentName, 'noises')
freq = listFromConfig(Config, experimentName, 'freqs')
lmax = int(Config.getfloat(experimentName, 'lmax'))
lknee = Config.getfloat(experimentName, 'lknee')
alpha = Config.getfloat(experimentName, 'alpha')
fsky = Config.getfloat(experimentName, 'fsky')
cosmoDict = dictFromSection(Config, cosmologyName)
constDict = dictFromSection(Config, 'constants')
clusterDict = dictFromSection(Config, clusterParams)
cc = ClusterCosmology(cosmoDict, constDict, lmax)
mass_err_file = Config.get(experimentName, 'mass_err')
mass_err = np.loadtxt(mass_err_file)
zbin_temp = np.arange(0.1, 2.01, 0.05)
zbin = np.insert(zbin_temp, 0, 0.0)
HMF = Halo_MF(clusterCosmology=cc)
errs, Ntot = HMF.Mass_err(mass_err, zbin, beam, noise, freq, clusterDict,
lknee, alpha, fileFunc)
print((np.sqrt(errs)))
print(Ntot)
#HSC_mass = np.loadtxt('input/HSC_DeltalnM_z0_z1.txt',unpack=True)
#HSC_mass = np.transpose(HSC_mass)
#print np.shape(HSC_mass), np.shape(dndzdm)
N1 = hmf.N_of_z()*fsky
hmf.sigN = siggrid
N2 = hmf.N_of_z_SZ(SZProf)*fsky
pl = Plotter(scaleY='log')
pl.add(zs,N1)
pl.add(zs,N2)
Ntot0 = np.dot(N1,np.diff(z_edges))
Ntot1 = np.dot(N2,np.diff(z_edges))
print(("All clusters in the Universe ",Ntot0))
print(("All clusters detectable at qmin ",SZProf.qmin," is ",Ntot1))
sn,ntot = hmf.Mass_err(fsky,lndM,SZProf)
outmerr = lndM
print(("All clusters according to Mass_err ", ntot))
# get s/n q-bins
qs = listFromConfig(Config,'general','qbins')
qspacing = Config.get('general','qbins_spacing')
if qspacing=="log":
qbin_edges = np.logspace(np.log10(qs[0]),np.log10(qs[1]),int(qs[2])+1)
elif qspacing=="linear":
qbin_edges = np.linspace(qs[0],qs[1],int(qs[2])+1)
else:
raise ValueError
q_arr = old_div((qbin_edges[1:]+qbin_edges[:-1]),2.)
