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: