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))