def counts_from_config(Config,bigDataDir,version,expName,gridName,mexp_edges,z_edges,lkneeTOverride=None,alphaTOverride=None):
suffix = ""
if lkneeTOverride is not None:
suffix += "_"+str(lkneeTOverride)
if alphaTOverride is not None:
suffix += "_"+str(alphaTOverride)
mgrid,zgrid,siggrid = pickle.load(open(bigDataDir+"szgrid_"+expName+"_"+gridName+ "_v" + version+suffix+".pkl",'rb'))
#mgrid,zgrid,siggrid = pickle.load(open(bigDataDir+"szgrid_"+expName+"_"+gridName+ "_v" + version+suffix+".pkl",'rb'),encoding='latin1')
experimentName = expName
cosmoDict = dict_from_section(Config,"params")
constDict = dict_from_section(Config,'constants')
clusterDict = dict_from_section(Config,'cluster_params')
clttfile = Config.get("general","clttfile")
cc = ClusterCosmology(cosmoDict,constDict,clTTFixFile = clttfile)
beam = list_from_config(Config,experimentName,'beams')
noise = list_from_config(Config,experimentName,'noises')
freq = list_from_config(Config,experimentName,'freqs')
lmax = int(Config.getfloat(experimentName,'lmax'))
lknee = float(Config.get(experimentName,'lknee').split(',')[0])
alpha = float(Config.get(experimentName,'alpha').split(',')[0])
fsky = Config.getfloat(experimentName,'fsky')
SZProf = SZ_Cluster_Model(cc,clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lknee=lknee,alpha=alpha)
hmf = Halo_MF(cc,mexp_edges,z_edges)
hmf.sigN = siggrid.copy()
Ns = np.multiply(hmf.N_of_z_SZ(fsky,SZProf),np.diff(z_edges).reshape(1,z_edges.size-1))
return Ns.ravel().sum()
# HMF
zbin = np.arange(0.,3.0,0.1)
#zbin = np.insert(zbin_temp,0,0.0)
#print zbin
Mexp = np.arange(13.5,15.71,0.01)
start3 = time.time()
SZProf = SZ_Cluster_Model(cc,clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lknee=lknee,alpha=alpha)
HMF = Halo_MF(cc,Mexp,zbin)
dvdz = HMF.dVdz#(zbin)
dndm = HMF.N_of_z_SZ(fsky,SZProf)
sys.exit()
print(("Time for N of z " , time.time() - start3))
# pl = Plotter()
# pl.add(zbin[1:], dndm * dvdz[1:])
# pl.done("output/dndm.png")
print(("Total number of clusters ", np.trapz(dndm ,zbin[:],np.diff(zbin[:]))*fsky))
#np.savetxt('output/dndm_dVdz_1muK_3_0arc.txt',np.transpose([zbin[1:],dndm,dvdz[1:]]))
mfile = "data/S4-7mCMB_all.pkl"
minrange, zinrange, lndM = pickle.load(open(mfile,'rb'))
noise = list_from_config(Config, expName, 'noises')
freq = list_from_config(Config, expName, 'freqs')
lknee = list_from_config(Config, expName, 'lknee')[0]
alpha = list_from_config(Config, expName, 'alpha')[0]
fsky = Config.getfloat(expName, 'fsky')
HMF = Halo_MF(cc, mexp_edges, z_edges)
HMF.sigN = siggrid.copy()
SZProf = SZ_Cluster_Model(cc,
clusterDict,
rms_noises=noise,
fwhms=beam,
freqs=freq,
lknee=lknee,
alpha=alpha)
Nofzs = np.multiply(HMF.N_of_z_SZ(fsky, SZProf),
np.diff(z_edges).reshape(1, z_edges.size - 1)).ravel()
print(Nofzs.sum())
#sys.exit()
saveId = expName + "_" + gridName + "_" + cal + "_v" + ver
Nmzq = np.load(bigDataDir + "N_mzq_" + saveId + "_fid.npy") * fsky
Nmz = Nmzq.sum(axis=-1)
Nz = Nmzq.sum(axis=0).sum(axis=-1)
print(Nz.shape)
m_edges = 10**mexp_edges
masses = (m_edges[1:] + m_edges[:-1]) / 2.
mexp_new = np.log10(np.linspace(masses[0], masses[-1], 10))
z_new = np.linspace(0.25, 2.75, 10)
print(Nmz.sum())
clusterDict,
rms_noises=noise,
fwhms=beam,
freqs=freq,
lknee=lknee,
alpha=alpha)
fsky = 0.4
N1 = hmf.N_of_z() * fsky
#hmf.sigN = np.loadtxt("temp.txt")
try:
hmf.sigN = np.loadtxt("tempSigN.txt")
N2 = hmf.N_of_z_SZ(SZProf) * fsky
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)
# HMF
zbin = np.arange(0.,3.0,0.1)
#zbin = np.insert(zbin_temp,0,0.0)
#print zbin
Mexp = np.arange(13.5,15.71,0.01)
start3 = time.time()
SZProf = SZ_Cluster_Model(cc,clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lknee=lknee,alpha=alpha)
HMF = Halo_MF(cc,Mexp,zbin)
dvdz = HMF.dVdz#(zbin)
dndm = HMF.N_of_z_SZ(SZProf)
sys.exit()
print(("Time for N of z " , time.time() - start3))
# pl = Plotter()
# pl.add(zbin[1:], dndm * dvdz[1:])
# pl.done("output/dndm.png")
print(("Total number of clusters ", np.trapz(dndm ,zbin[:],np.diff(zbin[:]))*fsky))
#np.savetxt('output/dndm_dVdz_1muK_3_0arc.txt',np.transpose([zbin[1:],dndm,dvdz[1:]]))
mfile = "data/S4-7mCMB_all.pkl"
minrange, zinrange, lndM = pickle.load(open(mfile,'rb'))
#mbin = np.arange(12.5,15.5,0.05)+0.05
#zbin_temp = np.arange(0.05,2.05,0.05)
#zbin = np.insert(zbin_temp,0,0.0)
#qbin = np.arange(np.log(5),np.log(500),0.08)
zbin_temp = np.arange(0.05,3.0,0.05)
zbin = np.insert(zbin_temp,0,0.0)
#qbin = np.arange(np.log(6),np.log(500),0.08)
qbin = np.arange(np.log(6),np.log(500),0.08)
mbin = np.arange(13.5, 15.71, .10)
start3 = time.time()
HMF = Halo_MF(clusterCosmology=cc)
dvdz = HMF.dVdz(zbin)
dndm = HMF.N_of_z_SZ(zbin,beam,noise,freq,clusterDict,lknee,alpha,fileFunc)
#dndm2 = HMF.N_of_z(zbin)
#dNdmdz,dm = HMF.N_of_mz_SZ(zbin,beam,noise,freq,clusterDict,lknee,alpha,fileFunc)
#ans = HMF.N_of_mqz_SZ(mass_err,zbin,mbin,np.exp(qbin),beam,noise,freq,clusterDict,lknee,alpha,fileFunc)
print(("Time for N of z " , time.time() - start3))
#np.save('output/dN_dzmq'+experimentName[ii]+cosmologyName,ans)
#print np.max(ans)
#pl = Plotter()
#pl.add(zbin[1:], dndm * dvdz[1:])
#pl.done("output/dndm"+experimentName[ii]+".png")
#print "Total number of clusters ", np.trapz(dndm * dvdz[1:],zbin[1:],np.diff(zbin[1:]))*4.*np.pi*fsky
#print "Total number of clusters possible", np.trapz(dndm2,zbin[1:],np.diff(zbin[1:]))*4.*np.pi*fsky
mexp_edges, z_edges, lndM = pickle.load(open(massGridName,"rb"),encoding='latin1')
zrange = (z_edges[1:]+z_edges[:-1])/2.
beam = list_from_config(Config,expName,'beams')
noise = list_from_config(Config,expName,'noises')
freq = list_from_config(Config,expName,'freqs')
lknee = list_from_config(Config,expName,'lknee')[0]
alpha = list_from_config(Config,expName,'alpha')[0]
fsky = Config.getfloat(expName,'fsky')
HMF = Halo_MF(cc,mexp_edges,z_edges)
HMF.sigN = siggrid.copy()
SZProf = SZ_Cluster_Model(cc,clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lknee=lknee,alpha=alpha)
Nofzs = np.multiply(HMF.N_of_z_SZ(fsky,SZProf),np.diff(z_edges).reshape(1,z_edges.size-1)).ravel()
print(Nofzs.sum())
print(Nofzs,zrange)
#sys.exit()
saveId = expName + "_" + gridName + "_" + cal + "_v" + ver
Nmzq = np.load(bigDataDir+"N_mzq_"+saveId+"_fid.npy")*fsky
Nmz = Nmzq.sum(axis=-1)
Nz = Nmzq.sum(axis=0).sum(axis=-1)
print(Nz.shape)
print(Nz[10:],zrange[10:],np.sum(Nz[10:]))
m_edges = 10**mexp_edges
masses = (m_edges[1:]+m_edges[:-1])/2.
mexp_new = np.log10(np.linspace(masses[0],masses[-1],10))
mgrid,zgrid,siggrid = pickle.load(open(bigDataDir+"szgrid_"+expName+"_"+gridName+ "_v" + version+".pkl",'rb'))
Mexp_edges, z_edges, lndM = pickle.load(open(calFile,"rb"))
HMF = Halo_MF(cc,Mexp_edges,z_edges)
HMF.sigN = siggrid.copy()
#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))