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()
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 ...")
HMF.pk = origPk.copy()
HMF.pk[:, :] *= (1. + old_div(h, 2.))**2.
dNUp_dmqz = HMF.N_of_mqz_SZ(lndM * massMultiplier, qbins, SZProf)
Nup = getNmzq(dNUp_dmqz, mgrid, zrange, qbins)
HMF.pk = origPk.copy()
HMF.pk[:, :] *= (1. - old_div(h, 2.))**2.
dNDn_dmqz = HMF.N_of_mqz_SZ(lndM * massMultiplier, qbins, SZProf)
Ndn = getNmzq(dNDn_dmqz, mgrid, zrange, qbins)
myParam = inParamList[myParamIndex]
passParams[myParam] = fparams[myParam] + old_div(stepSizes[myParam],2.)
elif rank%2==0:
myParam = inParamList[myParamIndex]
passParams[myParam] = fparams[myParam] - old_div(stepSizes[myParam],2.)
if rank!=0: print(rank,myParam,fparams[myParam],passParams[myParam])
cc = ClusterCosmology(passParams,constDict,clTTFixFile=clttfile)
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,v3mode=v3mode,fsky=fsky)
if (YWLcorrflag == 1):
dN_dmqz = HMF.N_of_mqz_SZ_corr(lndM*massMultiplier,qbin_edges,SZProf)
else:
dN_dmqz = HMF.N_of_mqz_SZ(lndM*massMultiplier,qbin_edges,SZProf)
if rank==0:
#np.save(bigDataDir+"N_dzmq_"+saveId+"_fid",dN_dmqz)
np.save(sfisher.fid_file(bigDataDir,saveId),getNmzq(dN_dmqz,mexp_edges,z_edges,qbin_edges))
dUps = {}
dDns = {}
print("Waiting for ups and downs...")
for i in range(1,numcores):
data = np.empty(dN_dmqz.shape, dtype=np.float64)
comm.Recv(data, source=i, tag=77)
myParamIndex = old_div((i+1),2)-1
if i%2==1:
dUps[inParamList[myParamIndex]] = data.copy()
elif i%2==0:
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'))
outmerr = interpolate_grid(lndM,minrange,zinrange,Mexp,zbin,regular=False,kind="cubic",bounds_error=False,fill_value=np.inf)
q_arr = np.logspace(np.log10(6.),np.log10(500.),64)
dnqmz = HMF.N_of_mqz_SZ(outmerr,q_arr,SZProf)
N,Nofz = getTotN(dnqmz,Mexp,zbin,q_arr,returnNz=True)
print((N*fsky))
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)) pl.add(zs, Nofz * fsky, label="mqz") pl.legendOn() pl.done(outDir + "nsRefactor.png") nnoq = np.trapz(dnqmz, q_arr, axis=2) * fsky pl = Plotter() pl.plot2d(nnoq) pl.done(outDir + "ngridRefactor.png")
vals.sort()
for val in vals:
print((key, val))
uppassparams = fparams.copy()
dnpassparams = fparams.copy()
uppassparams[key] = fparams[key]+old_div(val,2.)
dnpassparams[key] = fparams[key]-old_div(val,2.)
cc = ClusterCosmology(uppassparams,constDict,clTTFixFile=clttfile)
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)
Nup = HMF.N_of_mqz_SZ(lndM*massMultiplier,qbin_edges,SZProf)
cc = ClusterCosmology(dnpassparams,constDict,clTTFixFile=clttfile)
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)
Ndn = HMF.N_of_mqz_SZ(lndM*massMultiplier,qbin_edges,SZProf)
dNdp = old_div((getNmzq(Nup,mexp_edges,z_edges,qbin_edges)-getNmzq(Ndn,mexp_edges,z_edges,qbin_edges)),val)
Nz = dNdp.copy().sum(axis=-1).sum(axis=0)
Nm = dNdp.copy().sum(axis=-1).sum(axis=-1)
Nq = dNdp.copy().sum(axis=0).sum(axis=0)
