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()
def __init__(self,iniFile,expName,gridName,version,ClusterCosmology):
Config = SafeConfigParser()
Config.optionxform=str
Config.read(iniFile)
self.cc = ClusterCosmology
bigDataDir = Config.get('general','bigDataDirectory')
self.clttfile = Config.get('general','clttfile')
self.constDict = dict_from_section(Config,'constants')
self.clusterDict = dict_from_section(Config,'cluster_params')
#version = Config.get('general','version')
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]
self.fsky = Config.getfloat(expName,'fsky')
self.mgrid,self.zgrid,siggrid = pickle.load(open(bigDataDir+"szgrid_"+expName+"_"+gridName+ "_v" + version+".pkl",'rb'))
#self.cc = ClusterCosmology(self.fparams,self.constDict,clTTFixFile=self.clttfile)
self.SZProp = SZ_Cluster_Model(self.cc,self.clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lknee=lknee,alpha=alpha)
self.HMF = Halo_MF(self.cc,self.mgrid,self.zgrid)
self.HMF.sigN = siggrid.copy()
def sel_counts_from_config(Config,bigDataDir,version,expName,gridName,calName,mexp_edges,z_edges,lkneeTOverride=None,alphaTOverride=None,zmin=-np.inf,zmax=np.inf,mmin=-np.inf,mmax=np.inf,recalculate=False,override_params=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'),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")
if override_params is not None:
for key in override_params.keys():
cosmoDict[key] = override_params[key]
# print(cosmoDict)
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()
saveId = save_id(expName,gridName,calName,version)
# Fiducial number counts
if recalculate:
from . import counts
# get s/n q-bins
qs = list_from_config(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
calFile = mass_grid_name_owl(bigDataDir,calName)
mexp_edges, z_edges, lndM = pickle.load(open(calFile,"rb"))
dN_dmqz = hmf.N_of_mqz_SZ(lndM,qbin_edges,SZProf)
nmzq = counts.getNmzq(dN_dmqz,mexp_edges,z_edges,qbin_edges)
else:
nmzq = np.load(fid_file(bigDataDir,saveId))
nmzq = nmzq*fsky
zs = (z_edges[1:]+z_edges[:-1])/2.
zsel = np.logical_and(zs>zmin,zs<=zmax)
M_edges = 10**mexp_edges
M = (M_edges[1:]+M_edges[:-1])/2.
Mexp = np.log10(M)
msel = np.logical_and(Mexp>mmin,Mexp<=mmax)
Ns = nmzq.sum(axis=-1)[msel,:][:,zsel]
return Ns #.ravel().sum()
qspacing = Config.get('general', 'qbins_spacing')
if qspacing == "log":
qbins = np.logspace(np.log10(qs[0]), np.log10(qs[1]), int(qs[2]) + 1)
elif qspacing == "linear":
qbins = np.linspace(qs[0], qs[1], int(qs[2]) + 1)
else:
raise ValueError
cc = ClusterCosmology(fparams, constDict, clTTFixFile=clttfile)
HMF = Halo_MF(cc, mexprange, zrange)
HMF.sigN = siggrid.copy()
SZProf = SZ_Cluster_Model(cc,
clusterDict,
rms_noises=noise,
fwhms=beam,
freqs=freq,
lknee=lknee,
alpha=alpha)
h = 0.05
# s80, As = getA(fparams,constDict,zrange,kmax=11.)
# s8zs = As*s80
dNFid_dmzq = HMF.N_of_mqz_SZ(lndM * massMultiplier, qbins, SZProf)
np.save(bigDataDir + "N_mzq_" + saveId + "_fid_sigma8",
getNmzq(dNFid_dmzq, mgrid, zrange, qbins))
origPk = HMF.pk.copy()
print("Calculating derivatives for overall power ...")
# numts=10000
cosmoDict = dict_from_section(Config,cosmologyName)
#cosmoDict = dict_from_section(Config,'WMAP9')
constDict = dict_from_section(Config,'constants')
clusterDict = dict_from_section(Config,clusterParams)
cc = ClusterCosmology(cosmoDict,constDict,pickling=True,clTTFixFile = "data/cltt_lensed_Feb18.txt")
# make an SZ profile example
SZProfExample = SZ_Cluster_Model(clusterCosmology=cc,clusterDict=clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lmax=lmax,lknee=lknee,alpha=alpha,dell=dell,pmaxN=pmaxN,numps=numps,v3mode=2,fsky=0.4)
#MM = 10**np.linspace(13.,14.,5)
#print SZProfExample.quickVar(MM,zz,tmaxN=tmaxN,numts=numts)
#sys.exit()
print(("quickvar " , np.sqrt(SZProfExample.quickVar(MM,zz,tmaxN=tmaxN,numts=numts))))
#print "filtvar " , np.sqrt(SZProfExample.filter_variance(MM,zz))
#experimentName = "CMB-Probe-50cm"
experimentName = "CCATP-MSIP"
#experimentName = "CCATP-SO-MSIP"
beams = listFromConfig(Config, experimentName, 'beams')
noises = listFromConfig(Config, experimentName, 'noises')
freqs = listFromConfig(Config, experimentName, 'freqs')
lmax = int(Config.getfloat(experimentName, 'lmax'))
lknee = listFromConfig(Config, experimentName, 'lknee')[0]
alpha = listFromConfig(Config, experimentName, 'alpha')[0]
fsky = Config.getfloat(experimentName, 'fsky')
SZProfExample = SZ_Cluster_Model(clusterCosmology=cc,
clusterDict=clusterDict,
rms_noises=noises,
fwhms=beams,
freqs=freqs,
lmax=lmax,
lknee=lknee,
alpha=alpha)
ILC = ILC_simple(clusterCosmology=cc,
rms_noises=noises,
fwhms=beams,
freqs=freqs,
lmax=lmax,
lknee=lknee,
alpha=alpha)
experimentName = "CCATP-SO-MSIP"
beams = listFromConfig(Config, experimentName, 'beams')
noises = listFromConfig(Config, experimentName, 'noises')
fsky = Config.getfloat(expName, 'fsky')
try:
v3mode = Config.getint(expName, 'V3mode')
except:
v3mode = -1
fparams = {}
for (key, val) in Config.items('params'):
if ',' in val:
param, step = val.split(',')
fparams[key] = float(param)
else:
fparams[key] = float(val)
cc = ClusterCosmology(fparams, constDict, clTTFixFile=clttfile)
HMF = Halo_MF(cc, mexp_edges, z_edges)
SZCluster = SZ_Cluster_Model(cc,
clusterDict,
rms_noises=noise,
fwhms=beam,
freqs=freq,
lknee=lknee,
alpha=alpha,
v3mode=v3mode,
fsky=fsky)
HMF.updateSigN(SZCluster)
HMF.updatePfunc(SZCluster)
np.save(bigDataDir + "Sel_func" + saveId, HMF.Pfunc)
# numts=10000
cosmoDict = dictFromSection(Config,cosmologyName)
#cosmoDict = dictFromSection(Config,'WMAP9')
constDict = dictFromSection(Config,'constants')
clusterDict = dictFromSection(Config,clusterParams)
cc = ClusterCosmology(cosmoDict,constDict,pickling=True,clTTFixFile = "data/cltt_lensed_Feb18.txt")
# make an SZ profile example
SZProfExample = SZ_Cluster_Model(clusterCosmology=cc,clusterDict=clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lmax=lmax,lknee=lknee,alpha=alpha,dell=dell,pmaxN=pmaxN,numps=numps,qmin=6)
version = Config.get('general','version')
bigDataDir = Config.get('general','bigDataDirectory')
calFile = bigDataDir+"lensgrid_"+gridName+"_"+calName+".pkl"
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)
alphaT = comm.bcast(alphaT, root=0)
kh = comm.bcast(kh, root=0)
pk = comm.bcast(pk, root=0)
Mexp_edges = comm.bcast(Mexp_edges, root=0)
z_edges = comm.bcast(z_edges, root=0)
if rank == 0: print("Broadcasted.")
cc = ClusterCosmology(fparams, constDict, clTTFixFile=clttfile)
if doSZ:
HMF = Halo_MF(cc, mgrid, zgrid, kh=kh, powerZK=pk)
SZCluster = SZ_Cluster_Model(cc,
clusterDict,
rms_noises=noise,
fwhms=beam,
freqs=freq,
lknee=lkneeT,
alpha=alphaT,
fg=doFg,
tsz_cib=dotsz_cib,
v3mode=v3mode,
fsky=fsky)
numms = mgrid.size
numzs = zgrid.size
if doLens:
MerrGrid = np.zeros((numms, numzs))
if True: #doRayDeriv:
MerrGridUp = np.zeros((numms, numzs))
MerrGridDn = np.zeros((numms, numzs))
if doSZ: siggrid = np.zeros((numms, numzs))
assert np.all(mgrid==mexp_edges)
assert np.all(z_edges==zgrid)
cc = ClusterCosmology(fparams,constDict,clTTFixFile=clttfile)
HMF = Halo_MF(cc,mgrid,zgrid)
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
SZProp = SZ_Cluster_Model(cc,clusterDict,rms_noises = noise,fwhms=beam,freqs=freq,lknee=lknee,alpha=alpha)
Mwl = 10**HMF.Mexp
z_arr = HMF.zarr
M_arr = np.outer(HMF.M,np.ones([len(z_arr)]))
if HMF.sigN is None: HMF.updateSigN(SZProp)
sigN = HMF.sigN
q_arr = old_div((qbin_edges[1:]+qbin_edges[:-1]),2.)
blah = SZProp.P_of_qn_corr(SZProp.lnY,M_arr,z_arr,sigN,q_arr,Mwl)#,lndM)
#dN_dmqz_corr = HMF.N_of_mqz_SZ_corr(lndM,qbin_edges,SZProp)
#dN_dmqz = HMF.N_of_mqz_SZ(lndM,qbin_edges,SZProp)