att=stage2,
spread=spread,
hex=hex,
Ns=Ndish)
wedge_noise_model = mapnoise.WedgeNoiseModel(pm=truth_pm,
power=1,
seed=100,
kmin=kmin,
angle=angle)
#Create and save data if not found
s_truth = BigFileMesh(dfolder + 'linear', 'LinearDensityK').paint()
dyn = BigFileCatalog(dfolder + 'fastpm_%0.4f/1' % aa)
dlayout = truth_pm.decompose(dyn['Position'])
d_truth = truth_pm.paint(dyn['Position'], layout=dlayout)
hmesh = truth_pm.create(mode='real', value=hmesh[...])
s_truth = truth_pm.create(mode='real', value=s_truth[...])
try:
data_p = map.Observable.load(optfolder + '/datap')
except:
data_p = map.Observable(hmesh, d_truth, s_truth)
data_p.save(optfolder + 'datap/')
try:
data_n = map.Observable.load(optfolder + '/datan')
except:
data_n = truth_noise_model.add_noise(data_p)
data_n.save(optfolder + 'datan/')
try:
rsdfac = 0
rsdfac *= 100. / aa ##Add hoc factor due to incorrect velocity dimensions in nbody.py
###########################################
###dynamics
if upsample:
data_pf4 = map.Observable.load(optfolder + '/datap_up')
#data_n = map.Observable.load(optfolder+'/datan_up')
#data_w = map.Observable.load(optfolder+'/dataw_up')
else:
data_pf4 = map.Observable.load(optfolder + '/datap')
#data_n = map.Observable.load(optfolder+'/datan')
#data_w = map.Observable.load(optfolder+'/dataw')
meshm = truth_pm.create(mode='real', value=data_pf4.mapp)
meshd = truth_pm.create(mode='real', value=data_pf4.s)
meshs = truth_pm.create(mode='real', value=data_pf4.s)
data_p = map.Observable(meshm, meshd, meshs)
##Get bias
pkd = FFTPower(data_p.d, mode='1d').power
pkh = FFTPower(hmeshreal, mode='1d').power
#pkx = FFTPower(hmeshreal, second=data_p.d, mode='1d').power
bias = ((pkh['power'].real / pkd['power'].real)[1:6]**0.5).mean()
if rank == 0: print('Bias = %0.2f' % bias)
Rsm = 8
Rbao = Rsm / 2**0.5
ff = cosmo.scale_independent_growth_rate(zz)
beta = bias / ff
else:
hmesh = BigFileMesh(
proj + '/HV%d-F/fastpm_%0.4f/HImesh-N%04d/' %
(bs * 10, aa, nc2), 'ModelD').paint()
hmesh /= hmesh.cmean()
hmesh -= 1.
if ray:
dnewfolder = '/global/cscratch1/sd/chmodi/m3127/cm_lowres/%dstepT-B%d/%d-%d-9100/' % (
nsteps, B, bs, nc * 2)
else:
dnewfolder = '/global/cscratch1/sd/chmodi/m3127/cm_lowres/%dstepT-B%d/%d-%d-9100-fixed/' % (
nsteps, B, bs, nc * 2)
s_truth = BigFileMesh(dnewfolder + 'linear', 'LinearDensityK').paint()
s_truth = new_pm.create(mode='real', value=s_truth[...])
dyn = BigFileCatalog(dnewfolder + 'fastpm_%0.4f/1' % aa)
dlayout = new_pm.decompose(dyn['Position'])
d_truth = new_pm.paint(dyn['Position'], layout=dlayout)
hmesh = new_pm.create(mode='real', value=hmesh[...])
data_p = map.Observable(hmesh, d_truth, s_truth, lmesh)
data_p.save(optfolder + 'datap_up/')
try:
data_n = map.Observable.load(optfolder + '/datan_up')
except:
data_n = truth_noise_model.add_noise(data_p)
data_n.save(optfolder + 'datan_up/')
try:
