def instantiate_grids(self):
mubins = list_from_config(self.config, 'general', 'mubins')
self.mus = np.linspace(mubins[0], mubins[1], int(mubins[2]) + 1)
cc = ClusterCosmology(paramDict=self.params,
constDict=self.constdict,
clTTFixFile=self.clttfile)
clst = Clustering(self.inifile, self.expname, self.gridname,
self.version, cc)
self.ks = clst.HMF.kh
self.ps_fid = clst.fine_ps_bar(self.mus)
self.veff_fid = clst.V_eff(self.mus)
self.deltaks = np.gradient(self.ks)
self.deltamus = np.gradient(self.mus)
fparams[key] = float(val)
expName = 'S4-1.0-CDT'
gridName = 'grid-owl2'
version = '0.6'
cc = ClusterCosmology(fparams, constDict, clTTFixFile=clttfile)
clst = Clustering(INIFILE, expName, gridName, version, cc)
fsky = 1.
ks = clst.HMF.kh
delta_ks = np.gradient(ks)
zs = clst.HMF.zarr[1:-1]
mus = np.linspace(-1, 1, 9)
deltamu = np.gradient(mus)
ps_bars = clst.fine_ps_bar(mus)
v_effs = clst.V_eff(mus)
noise = np.sqrt(8) * np.pi * np.sqrt(
1 / (deltamu * v_effs * (ks**2)[..., np.newaxis, np.newaxis] *
delta_ks[..., np.newaxis, np.newaxis])) * ps_bars
snr = ps_bars / noise
print(noise.shape)
print(np.einsum('ijk,ijk', noise, noise))
print(np.sum(snr**2))
elif rank % 2 == 1:
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])
####FIX THIS
cc = ClusterCosmology(passParams, constDict, clTTFixFile=clttfile)
clst = Clustering(expName, gridName, version, cc)
pbar = clst.fine_ps_bar(mubin_edges)
veff = clst.V_eff(mubin_edges)
fish_fac_err = veff * clst.HMF.kh**2 / pbar**2 # Tegmark 1997
#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), fish_fac_err)
INIFILE = "input/pipeline.ini"
expName = 'S4-1.0-CDT'
gridName = 'grid-owl2'
version = '0.6'
clst = Clustering(INIFILE, expName, gridName, version)
fsky = 1.
ks = clst.HMF.kh
zs = clst.HMF.zarr[1:-1]
mus = np.array([0])
v0s = clst.v0(fsky, 1000)
v_effs = clst.V_eff(mus, fsky, 1000)
plt.plot(zs, v0s, label=r"$V_0$")
plt.plot(zs, v_effs[43, :, :], label=r"$V_{eff}(k\approx 0.001)$")
plt.plot(zs, v_effs[114, :, :], label=r"$V_{eff}(k\approx 0.05)$")
plt.plot(zs, v_effs[127, :, :], label=r"$V_{eff}(k\approx 0.1)$")
plt.plot(zs, v_effs[139, :, :], label=r"$V_{eff}(k\approx 0.2)$")
#plt.plot(ks, v_effs[0])
#plt.xscale('log')
plt.xlim((0, 1.8))
plt.yscale('log')
plt.xlabel(r'$z$')
plt.ylabel(r'$V_{eff}(k)$')
plt.legend(loc='best')
plt.savefig('volumes_test.svg')