def fiddlebias(aa, saveb=False, bname='h1bias.txt', ofolder=None):
#Fiddling bias for halos. Deprecated.
print('Read in catalogs')
halocat = readincatalog(aa, matter=False)
hpos = halocat['Position']
hmass = halocat['Mass']
h1mass = dohod.HI_mass(hmass, aa)
dm = BigFileMesh(project + sim + '/fastpm_%0.4f/'%aa + '/dmesh_N%04d'%nc, '1').paint()
if ofolder is None: ofolder = project + '/%s/fastpm_%0.4f/'%(sim, aa)
#measure power
pm = ParticleMesh(BoxSize = bs, Nmesh = [nc, nc, nc])
pkm = FFTPower(dm/dm.cmean(), mode='1d').power
k, pkm = pkm['k'], pkm['power']
##H1
print("H1")
h1mesh = pm.paint(hpos, mass=h1mass)
pkh1 = FFTPower(h1mesh/h1mesh.cmean(), mode='1d').power['power']
pkh1m = FFTPower(h1mesh/h1mesh.cmean(), second=dm/dm.cmean(), mode='1d').power['power']
#Bias
b1h1 = pkh1m/pkm
b1h1sq = pkh1/pkm
if saveb:
np.savetxt(ofolder+bname, np.stack((k, b1h1, b1h1sq**0.5), axis=1),
header='k, pkh1xm/pkm, pkh1/pkm^0.5')
return k, b1h1, b1h1sq
def calc_bias(aa, h1mesh, suff):
'''Compute the bias(es) for the HI'''
if rank == 0: print('Calculating bias')
if rank == 0:
print("Processing a={:.4f}...".format(aa))
print('Reading DM mesh...')
dm = BigFileMesh(args['matterfile'] % (aa), 'N1024').paint()
dm /= dm.cmean()
if rank == 0: print('Computing DM P(k)...')
pkmm = FFTPower(dm, mode='1d').power
k, pkmm = pkmm['k'], pkmm['power'] # Ignore shotnoise.
if rank == 0: print('Done.')
#
pkh1h1 = FFTPower(h1mesh, mode='1d').power
kk = pkh1h1.coords['k']
pkh1h1 = pkh1h1['power'] - pkh1h1.attrs['shotnoise']
pkh1mm = FFTPower(h1mesh, second=dm, mode='1d').power['power']
if rank == 0: print('Done.')
# Compute the biases.
b1x = np.abs(pkh1mm / (pkmm + 1e-10))
b1a = np.abs(pkh1h1 / (pkmm + 1e-10))**0.5
if rank == 0: print("Finishing processing a={:.4f}.".format(aa))
#
if rank == 0:
fout = open(outfolder + "HI_bias_{:6.4f}.txt".format(aa), "w")
fout.write("# {:>8s} {:>10s} {:>10s} {:>15s}\n".\
format("k","b1_x","b1_a","Pkmm"))
for i in range(1, kk.size):
fout.write("{:10.5f} {:10.5f} {:10.5f} {:15.5e}\n".\
format(kk[i],b1x[i],b1a[i],pkmm[i].real))
fout.close()
def make_lagfields(nc,
seed,
bs=1536,
T=40,
B=2,
simpath=sc_simpath,
outpath=sc_outpath,
Rsm=0):
fname = get_filename(nc, seed, T=T, B=B)
spath = simpath + fname
opath = outpath + fname
try:
os.makedirs(opath)
except:
pass
pm = ParticleMesh(BoxSize=bs, Nmesh=[nc, nc, nc], dtype='f4')
rank = pm.comm.rank
lin = BigFileMesh(spath + '/linear', 'LinearDensityK').paint()
lin -= lin.cmean()
print(rank, 'lin field read')
header = '1,b1,b2,bg,bk'
names = header.split(',')
lag_fields = tools.getlagfields(
pm, lin, R=Rsm) # use the linear field at the desired redshift
print(rank, 'lag field created')
for i, ff in enumerate(lag_fields):
x = FieldMesh(ff)
x.save(opath + 'lag', dataset=names[i], mode='real')
def calc_bias(aa,mcut,suff):
'''Compute the bias(es) for the HI'''
print('Read in DM mesh')
dm = BigFileMesh(project+sim+'/fastpm_%0.4f/'%aa+\
'/dmesh_N%04d'%nc,'1').paint()
dm /= dm.cmean()
pkmm = FFTPower(dm,mode='1d').power
k,pkmm= pkmm['k'],pkmm['power'] # Ignore shotnoise.
#
print('Read in central/satellite catalogs')
cencat = BigFileCatalog(project+sim+'/fastpm_%0.4f/cencat'%aa)
satcat = BigFileCatalog(project+sim+'/fastpm_%0.4f/satcat'%aa+suff)
#
cencat['HImass'] = HI_hod(cencat['Mass'],aa,mcut)
satcat['HImass'] = HI_hod(satcat['Mass'],aa,mcut)
totHImass = cencat['HImass'].sum().compute() +\
satcat['HImass'].sum().compute()
cencat['HImass']/= totHImass/float(nc)**3
satcat['HImass']/= totHImass/float(nc)**3
#
allcat = MultipleSpeciesCatalog(['cen','sat'],cencat,satcat)
#
h1mesh = allcat.to_mesh(BoxSize=bs,Nmesh=[nc,nc,nc],weight='HImass')
pkh1h1 = FFTPower(h1mesh,mode='1d').power
pkh1h1 = pkh1h1['power']-pkh1h1.attrs['shotnoise']
pkh1mm = FFTPower(h1mesh,second=dm,mode='1d').power['power']
# Compute the biases.
b1x = np.abs(pkh1mm/(pkmm+1e-10))
b1a = np.abs(pkh1h1/(pkmm+1e-10))**0.5
return(k,b1x,b1a,np.abs(pkmm))
def calc_bias(aa, h1mesh, suff):
'''Compute the bias(es) for the HI'''
if rank == 0:
print("Processing a={:.4f}...".format(aa))
print('Reading DM mesh...')
if ncsim == 10240:
dm = BigFileMesh(scratchyf+sim+'/fastpm_%0.4f/'%aa+\
'/1-mesh/N%04d'%nc,'').paint()
else:
dm = BigFileMesh(project+sim+'/fastpm_%0.4f/'%aa+\
'/dmesh_N%04d/1/'%nc,'').paint()
dm /= dm.cmean()
if rank == 0: print('Computing DM P(k)...')
pkmm = FFTPower(dm, mode='1d').power
k, pkmm = pkmm['k'], pkmm['power'] # Ignore shotnoise.
if rank == 0: print('Done.')
#
pkh1h1 = FFTPower(h1mesh, mode='1d').power
pkh1h1 = pkh1h1['power'] - pkh1h1.attrs['shotnoise']
pkh1mm = FFTPower(h1mesh, second=dm, mode='1d').power['power']
if rank == 0: print('Done.')
# Compute the biases.
b1x = np.abs(pkh1mm / (pkmm + 1e-10))
b1a = np.abs(pkh1h1 / (pkmm + 1e-10))**0.5
if rank == 0: print("Finishing processing a={:.4f}.".format(aa))
return (k, b1x, b1a, np.abs(pkmm))
def fiddlebiasgal(aa, suff, nc=nc, mcfv=[1.], saveb=False, bname='h1bias', ofolder=None):
'''Fiddle bias for galaxies'''
if ofolder is None: ofolder = project + '/%s/fastpm_%0.4f/'%(sim, aa)
pm = ParticleMesh(BoxSize = bs, Nmesh = [nc, nc, nc])
print('Read in catalogs')
cencat = BigFileCatalog(project + sim + '/fastpm_%0.4f/cencat'%aa)
satcat = BigFileCatalog(project + sim + '/fastpm_%0.4f/satcat'%aa+suff)
cpos, spos = cencat['Position'], satcat['Position']
cmass, smass = cencat['Mass'], satcat['Mass']
pos = np.concatenate((cpos, spos), axis=0)
dm = BigFileMesh(project + sim + '/fastpm_%0.4f/'%aa + '/dmesh_N%04d'%nc, '1').paint()
pkm = FFTPower(dm/dm.cmean(), mode='1d').power
k, pkm = pkm['k'], pkm['power']
b1, b1sq = np.zeros((k.size, len(mcfv))), np.zeros((k.size, len(mcfv)))
for imc, mcf in enumerate(mcfv):
print(mcf)
ch1mass = HI_masscutfiddle(cmass, aa, mcutf=mcf)
sh1mass = HI_masscutfiddle(smass, aa, mcutf=mcf)
h1mass = np.concatenate((ch1mass, sh1mass), axis=0)
#
h1mesh = pm.paint(pos, mass=h1mass)
pkh1 = FFTPower(h1mesh/h1mesh.cmean(), mode='1d').power['power']
pkh1m = FFTPower(h1mesh/h1mesh.cmean(), second=dm/dm.cmean(), mode='1d').power['power']
#Bias
b1[:, imc] = pkh1m/pkm
b1sq[:, imc] = pkh1/pkm
np.savetxt(ofolder+bname+'auto'+suff+'.txt', np.concatenate((k.reshape(-1, 1), b1sq**0.5), axis=1),
header='mcut factors = %s\nk, pkh1xm/pkm, pkh1/pkm^0.5'%mcfv)
np.savetxt(ofolder+bname+'cross'+suff+'.txt', np.concatenate((k.reshape(-1, 1), b1), axis=1),
header='mcut factors = %s\nk, pkh1xm/pkm, pkh1mx/pkm'%mcfv)
return k, b1, b1sq
def calc_bias(aa, mcut, suff):
'''Compute the bias(es) for the HI'''
if rank == 0:
print("Processing a={:.4f}...".format(aa))
print('Reading DM mesh...')
dm = BigFileMesh(scratch1+sim+'/fastpm_%0.4f/'%aa+\
'/1-mesh/N%04d'%nc,'').paint()
dm /= dm.cmean()
if rank == 0: print('Computing DM P(k)...')
pkmm = FFTPower(dm, mode='1d').power
k, pkmm = pkmm['k'], pkmm['power'] # Ignore shotnoise.
if rank == 0: print('Done.')
#
if rank == 0: print('Reading central/satellite catalogs...')
cencat = BigFileCatalog(scratch2 + sim +
'/fastpm_%0.4f/cencat-16node' % aa)
satcat = BigFileCatalog(scratch2 + sim + '/fastpm_%0.4f/satcat' % aa +
suff)
if rank == 0: print('Catalogs read.')
#
if rank == 0: print('Computing HI masses...')
cencat['HImass'] = HI_hod(cencat['Mass'], aa, mcut)
satcat['HImass'] = HI_hod(satcat['Mass'], aa, mcut)
rankHImass = cencat['HImass'].sum().compute() +\
satcat['HImass'].sum().compute()
rankHImass = np.array([rankHImass])
totHImass = np.zeros(1, dtype='float')
comm.Allreduce(rankHImass, totHImass, MPI.SUM)
totHImass = totHImass[0]
cencat['HImass'] /= totHImass / float(nc)**3
satcat['HImass'] /= totHImass / float(nc)**3
if rank == 0: print('HI masses done.')
#
if rank == 0: print('Combining catalogs and computing P(k)...')
allcat = MultipleSpeciesCatalog(['cen', 'sat'], cencat, satcat)
h1mesh = allcat.to_mesh(BoxSize=bs, Nmesh=[nc, nc, nc], weight='HImass')
pkh1h1 = FFTPower(h1mesh, mode='1d').power
pkh1h1 = pkh1h1['power'] - pkh1h1.attrs['shotnoise']
pkh1mm = FFTPower(h1mesh, second=dm, mode='1d').power['power']
if rank == 0: print('Done.')
# Compute the biases.
b1x = np.abs(pkh1mm / (pkmm + 1e-10))
b1a = np.abs(pkh1h1 / (pkmm + 1e-10))**0.5
if rank == 0: print("Finishing processing a={:.4f}.".format(aa))
return (k, b1x, b1a, np.abs(pkmm))
def calc_bias(aa,h1mesh, outfolder, fname):
'''Compute the bias(es) for the HI'''
if rank==0: print('Calculating bias')
if rank==0:
print("Processing a={:.4f}...".format(aa))
print('Reading DM mesh...')
if ncsim == 10240:
dm = BigFileMesh(scratchyf+sim+'/fastpm_%0.4f/'%aa+\
'/1-mesh/N%04d'%nc,'').paint()
else:
dm = BigFileMesh(project+sim+'/fastpm_%0.4f/'%aa+\
'/dmesh_N%04d/1/'%nc,'').paint()
dm /= dm.cmean()
if rank==0: print('Computing DM P(k)...')
pkmm = FFTPower(dm,mode='1d').power
k,pkmm= pkmm['k'],pkmm['power'] # Ignore shotnoise.
if rank==0: print('Done.')
#
pkh1h1 = FFTPower(h1mesh,mode='1d').power
kk = pkh1h1.coords['k']
pkh1h1 = pkh1h1['power']-pkh1h1.attrs['shotnoise']
pkh1mm = FFTPower(h1mesh,second=dm,mode='1d').power['power']
if rank==0: print('Done.')
# Compute the biases.
b1x = np.abs(pkh1mm/(pkmm+1e-10))
b1a = np.abs(pkh1h1/(pkmm+1e-10))**0.5
if rank==0: print("Finishing processing a={:.4f}.".format(aa))
#
if rank==0:
fout = open(outfolder + "{}_bias_{:6.4f}.txt".format(fname, aa),"w")
fout.write("# {:>8s} {:>10s} {:>10s} {:>15s}\n".\
format("k","b1_x","b1_a","Pkmm"))
for i in range(1,kk.size):
fout.write("{:10.5f} {:10.5f} {:10.5f} {:15.5e}\n".\
format(kk[i],b1x[i],b1a[i],pkmm[i].real))
fout.close()
except:
pass
####################################
#initiate
#
if ray:
hmeshreal = BigFileMesh(
'/global/cscratch1/sd/chmodi/m3127/H1mass/highres/%d-9100/fastpm_%0.4f/HImesh-N%04d/'
% (bs * 10, aa, ncd), 'ModelA').paint()
else:
hmeshreal = BigFileMesh(
'/global/cscratch1/sd/chmodi/m3127/H1mass/highres/%d-9100-fixed/fastpm_%0.4f/HImesh-N%04d/'
% (bs * 10, aa, ncd), 'ModelA').paint()
hmeshreal /= hmeshreal.cmean()
hmeshreal -= 1
if rsdpos:
if ray:
hmesh = BigFileMesh(
'/global/cscratch1/sd/chmodi/m3127/H1mass/highres/%d-9100/fastpm_%0.4f/HImeshz-N%04d/'
% (bs * 10, aa, ncd), 'ModelA').paint()
else:
hmesh = BigFileMesh(
'/global/cscratch1/sd/chmodi/m3127/H1mass/highres/%d-9100-fixed/fastpm_%0.4f/HImeshz-N%04d/'
% (bs * 10, aa, ncd), 'ModelA').paint()
hmesh /= hmesh.cmean()
hmesh -= 1.
if rsdpos:
if ray:
with open(pp) as ff:
for line in ff.readlines():
if 'RSDFactor' in line: rsdfac = float(line.split()[-2])
else:
if ray:
hmesh = BigFileMesh(
'/global/cscratch1/sd/chmodi/m3127/H1mass/highres/%d-9100/fastpm_%0.4f/HImesh-N%04d/'
% (bs * 10, aa, nc), 'ModelA').paint()
else:
hmesh = BigFileMesh(
'/global/cscratch1/sd/chmodi/m3127/H1mass/highres/%d-9100-fixed/fastpm_%0.4f/HImesh-N%04d/'
% (bs * 10, aa, nc), 'ModelA').paint()
rsdfac = 0
rsdfac *= 100. / aa ##Add hoc factor due to incorrect velocity dimensions in nbody.py
hmesh /= hmesh.cmean()
hmesh -= 1.
if rank == 0: print('RSD factor is : ', rsdfac)
##
##rankweight = sum(masswt.compute())
##totweight = comm.allreduce(rankweight)
##rankweight = sum((masswt**2).compute())
##totweight2 = comm.allreduce(rankweight)
#noise = bs**3 / (hmesh.csum()**2 / (hmesh**2).csum())
noise = None
if rank == 0: print('Noise : ', noise)
#########################################
#dynamics
stages = numpy.linspace(0.01, aa, nsteps, endpoint=True)
if pmdisp: dynamic_model = NBodyModel(cosmo, truth_pm, B=B, steps=stages)
aa = 1.0000
zz = 1/aa-1
dgrow = cosmo.scale_independent_growth_factor(zz)
Rsm = 0
dpath = '/global/cscratch1/sd/yfeng1/m3127/desi/6144-%d-40eae2464/'%(seed)
lpath = '/global/cscratch1/sd/chmodi/m3127/crowcanyon/N%d-T0/S%d/'%(nc, seed)
ofolder = lpath + '/spectra/'
try: os.makedirs(ofolder)
except : pass
pm = ParticleMesh(BoxSize=bs, Nmesh=[nc, nc, nc], dtype='f4')
rank = pm.comm.rank
#grid = pm.mesh_coordinates()*bs/nc
lin = BigFileMesh(lpath+ '/linear', 'LinearDensityK').paint()
lin -= lin.cmean()
print(rank, 'lin field read')
header = '1,b1,b2,bg,bk'
names = header.split(',')
lag_fields = tools.getlagfields(pm, lin, R=Rsm) # use the linear field at the desired redshift
print(rank, 'lag field created')
for i, ff in enumerate(lag_fields):
x = FieldMesh(ff)
x.save(lpath + 'lag', dataset=names[i], mode='real')
###
def measurepk(nc=nc, dpath=scratchyf):
'''plot the power spectrum of halos on 'nc' grid'''
pm = ParticleMesh(BoxSize=bs, Nmesh=[nc, nc, nc])
for i, aa in enumerate(aafiles):
zz = zzfiles[i]
if rank == 0: print('redshift = ', zz)
if ncsim == 10240:
dm = BigFileMesh(scratchyf+sim+'/fastpm_%0.4f/'%aa+\
'/1-mesh/N%04d'%nc,'').paint()
else: dm = BigFileMesh(project+sim+'/fastpm_%0.4f/'%aa+\
'/dmesh_N%04d/1/'%nc,'').paint()
#dm = BigFileMesh(project + sim + '/fastpm_%0.4f/'%aa + '/dmesh_N%04d'%nc, '1').paint()
halos = BigFileCatalog(scratchyf + sim + '/fastpm_%0.4f/' % aa,
dataset='LL-0.200')
mp = halos.attrs['MassTable'][1] * 1e10
if rank == 0: print('Mass of particle is = %0.2e' % mp)
hmass = halos["Length"].compute() * mp
hpos = halos['Position'].compute()
layout = pm.decompose(hpos)
if rank == 0: print("paint")
hpmesh = pm.paint(hpos, layout=layout)
hmesh = pm.paint(hpos, mass=hmass, layout=layout)
print(rank, dm.cmean(), hmesh.cmean(), hpmesh.cmean())
pkm = FFTPower(dm / dm.cmean(), mode='1d').power
pkh = FFTPower(hmesh / hmesh.cmean(), mode='1d').power
pkhp = FFTPower(hpmesh / hpmesh.cmean(), mode='1d').power
pkhm = FFTPower(hmesh / hmesh.cmean(),
second=dm / dm.cmean(),
mode='1d').power
pkhpm = FFTPower(hpmesh / hpmesh.cmean(),
second=dm / dm.cmean(),
mode='1d').power
def savebinned(path, binstat, header):
if halos.comm.rank == 0:
k, p, modes = binstat['k'].real, binstat[
'power'].real, binstat['modes'].real
np.savetxt(path,
np.stack((k, p, modes), axis=1),
header=header)
ofolder = "../data/outputs/halos/{}/".format(sim)
if rank == 0:
print(ofolder)
try:
os.makedirs(ofolder)
except:
pass
savebinned(ofolder + 'pkhp_%0.4f.txt' % aa,
pkhp,
header='k, P(k), Nmodes')
savebinned(ofolder + 'pkhm_%0.4f.txt' % aa,
pkh,
header='k, P(k), Nmodes')
savebinned(ofolder + 'pkd_%0.4f.txt' % aa,
pkm,
header='k, P(k), Nmodes')
savebinned(ofolder + 'pkhpxd_%0.4f.txt' % aa,
pkhpm,
header='k, P(k), Nmodes')
savebinned(ofolder + 'pkhmxd_%0.4f.txt' % aa,
pkhm,
header='k, P(k), Nmodes')
def make_bias_plot():
"""Does the work of making the real-space xi(r) and b(r) figure."""
hmesh = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap', 'mapp').paint()
noises = np.loadtxt('/global/u1/c/chmodi/Programs/21cm/21cm_cleaning/data/summaryHI.txt').T
for i in range(noises[0].size):
if noises[0][i] == np.round(1/aa-1, 2): noise = noises[3][i]
print(noise)
zamod = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/fitp/', 'mapp').paint()
pmmod = BigFileMesh(dpath+'T05-B1/opt_s999_h1massA_fourier/fitp/', 'mapp').paint()
fin = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap/', 'd').paint()
fin /= fin.cmean()
fin -= 1
finsm = ft.smooth(fin, 3, 'gauss')
grid = pm.mesh_coordinates()*bs/nc
params, finmod = getbias(pm, basemesh=finsm, hmesh=hmesh, pos=grid, grid=grid) #
models = [zamod, pmmod, finmod, fin.copy()]
lbls = ['ZA shift', 'PM shift', 'Eulerian (R=3)', 'Final Matter']
lss = ['-', '-', '-', '--']
fig, ax = plt.subplots(1, 3, figsize=(15, 4))
for ii, mod in enumerate(models):
pmod = FFTPower(mod, mode='1d').power
k, pmod = pmod['k'], pmod['power']
ph = FFTPower(hmesh, mode='1d').power['power']
pxmodh = FFTPower(hmesh, second=mod, mode='1d').power['power']
perr = FFTPower(hmesh -mod, mode='1d').power['power']
ax[0].plot(k, pxmodh/(pmod*ph)**0.5, label=lbls[ii], lw=2, ls=lss[ii])
ax[0].set_ylabel('$r_{cc}$', fontdict=font)
ax[1].plot(k,(pmod/ph)**0.5, lw=2, ls=lss[ii])
#ax[1].set_ylabel(r'$\sqrt{P_{\rm mod}/P_{hh}}$', fontdict=font)
ax[1].set_ylabel(r'$T_f$', fontdict=font)
ax[2].plot(k, perr, lw=2, ls=lss[ii])
ax[2].set_ylabel(r'$P_{\delta_{\rm mod}-\delta_h}$', fontdict=font)
ax[2].set_yscale('log')
ax[2].axhline(noise)
for axis in ax:
axis.set_xscale('log')
axis.grid(which='both')
axis.legend(prop=fontmanage)
axis.set_xlabel(r'$k\quad [h\,{\rm Mpc}^{-1}]$', fontdict=font)
axis.set_xscale('log')
# Put on some more labels.
for axis in ax:
axis.set_xscale('log')
for tick in axis.xaxis.get_major_ticks():
tick.label.set_fontproperties(fontmanage)
for tick in axis.yaxis.get_major_ticks():
tick.label.set_fontproperties(fontmanage)
##and finish
plt.tight_layout(rect=[0, 0, 1, 0.95])
plt.savefig(figpath + '/bfit_L%04d_%04d.pdf'%(bs, aa*10000))
def make_biask_plot():
"""Does the work of making the real-space xi(r) and b(r) figure."""
hmesh = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap', 'mapp').paint()
noises = np.loadtxt('/global/u1/c/chmodi/Programs/21cm/21cm_cleaning/data/summaryHI.txt').T
for i in range(noises[0].size):
if noises[0][i] == np.round(1/aa-1, 2): noise = noises[3][i]
print(noise)
zamod = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/fitp/', 'mapp').paint()
pmmod = BigFileMesh(dpath+'T05-B1/opt_s999_h1massA_fourier/fitp/', 'mapp').paint()
fin = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap/', 'd').paint()
fin /= fin.cmean()
fin -= 1
finsm = ft.smooth(fin, 3, 'gauss')
grid = pm.mesh_coordinates()*bs/nc
params, finmod = getbias(pm, basemesh=finsm, hmesh=hmesh, pos=grid, grid=grid)
models = [zamod, pmmod, finmod, finsm.copy()]
lbls = ['ZA shift', 'PM shift', 'Eulerian (R=3)', 'Eulerian (R=3), $b_1$']
lss = ['-', '-', '-', '--']
lin = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap/', 's').paint()
dyn = BigFileCatalog('/global/cscratch1/sd/chmodi/m3127/cm_lowres/5stepT-B1/%d-%d-9100-fixed/fastpm_%0.4f/1'%(bs, nc, aa))
dgrow = cosmo.scale_independent_growth_factor(zz)
zapos = za.doza(lin.r2c(), grid, z=zz, dgrow=dgrow)
fpos = dyn['Position']
params, _ = getbias(pm, basemesh=lin, hmesh=hmesh, pos=zapos, grid=grid)
kk, paramsk, _ = getbiask(pm, basemesh=lin, hmesh=hmesh, pos=zapos, grid=grid)
fig, ax = plt.subplots(1, 2, figsize=(9, 4))
for ii, mod in enumerate(models):
pmod = FFTPower(mod, mode='1d').power
k, pmod = pmod['k'], pmod['power']
ph = FFTPower(hmesh, mode='1d').power['power']
if ii == 3:
mod *= (ph[1]/pmod[1]).real **0.5
pmod *= (ph[1]/pmod[1]).real
pxmodh = FFTPower(hmesh, second=mod, mode='1d').power['power']
perr = FFTPower(hmesh -mod, mode='1d').power['power']
ax[0].plot(k, perr, lw=2, ls=lss[ii], label=lbls[ii])
ax[0].set_ylabel(r'$P_{\rm err}$', fontdict=font)
ax[0].set_yscale('log')
ax[0].axhline(noise, color='k', ls="--")
ax[0].set_ylim(2, 5e2)
lbls = ['$b_1$', '$b_2$', '$b_s$']
for ii in range(3):
ax[1].plot(kk, paramsk[ii], lw=2, color='C%d'%ii, label=lbls[ii])
ax[1].axhline(params[ii], lw=1, color='C%d'%ii, ls="--")
ax[1].set_ylabel(r'$b(k)$', fontdict=font)
for axis in ax:
axis.set_xscale('log')
axis.grid(which='both')
axis.legend(prop=fontmanage, ncol=2)
axis.set_xlabel(r'$k\quad [h\,{\rm Mpc}^{-1}]$', fontdict=font)
axis.set_xscale('log')
# Put on some more labels.
for axis in ax:
axis.set_xscale('log')
for tick in axis.xaxis.get_major_ticks():
tick.label.set_fontproperties(fontmanage)
for tick in axis.yaxis.get_major_ticks():
tick.label.set_fontproperties(fontmanage)
##and finish
plt.tight_layout(rect=[0, 0, 1, 0.95])
plt.savefig(figpath + '/bfitk_L%04d_%04d.pdf'%(bs, aa*10000))
def make_bias2p_plot():
"""Does the work of making the real-space xi(r) and b(r) figure."""
hmesh = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap', 'mapp').paint()
grid = pm.mesh_coordinates()*bs/nc
noises = np.loadtxt('/global/u1/c/chmodi/Programs/21cm/21cm_cleaning/data/summaryHI.txt').T
for i in range(noises[0].size):
if noises[0][i] == np.round(1/aa-1, 2): noise = noises[3][i]
print(noise)
zamod = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/fitp/', 'mapp').paint()
try: pmmod = BigFileMesh(dpath+'T05-B1/opt_s999_h1massA_fourier/fitp/', 'mapp').paint()
except:
lin = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap/', 's').paint()
dyn = BigFileCatalog('/global/cscratch1/sd/chmodi/m3127/cm_lowres/5stepT-B1/%d-%d-9100-fixed/fastpm_%0.4f/1'%(bs, nc, aa))
fpos = dyn['Position']
_, pmod = getbias(pm, basemesh=lin, hmesh=hmesh, pos=fpos, grid=grid, fpos=fpos)
fin = BigFileMesh(dpath+'ZA/opt_s999_h1massA_fourier/datap/', 'd').paint()
fin /= fin.cmean()
fin -= 1
finsm = ft.smooth(fin, 3, 'gauss')
params, finmod = getbias(pm, basemesh=finsm, hmesh=hmesh, pos=grid, grid=grid)
models = [zamod, pmmod, finmod, finsm.copy()]
lbls = ['ZA shift', 'PM shift', 'Eulerian (R=3)', 'Eulerian (R=3), $b_1$']
lss = ['-', '-', '-', '--']
fig, ax = plt.subplots(1, 2, figsize=(9, 4))
for ii, mod in enumerate(models):
pmod = FFTPower(mod, mode='1d').power
k, pmod = pmod['k'], pmod['power']
ph = FFTPower(hmesh, mode='1d').power['power']
if ii == 3:
mod *= (ph[1]/pmod[1]).real**0.5
pmod *= (ph[1]/pmod[1]).real
pxmodh = FFTPower(hmesh, second=mod, mode='1d').power['power']
perr = FFTPower(hmesh -mod, mode='1d').power['power']
ax[0].plot(k, pxmodh/(pmod*ph)**0.5, label=lbls[ii], lw=2, ls=lss[ii])
ax[0].set_ylabel('$r_{cc}$', fontdict=font)
#if ii == 3: pmod *= ph[1]/pmod[1]
ax[1].plot(k,(pmod/ph)**0.5, lw=2, ls=lss[ii])
ax[1].set_ylabel(r'$T_f$', fontdict=font)
#ax[1].set_ylabel(r'$\sqrt{P_{\rm mod}/P_{hh}}$', fontdict=font)
for axis in ax:
axis.set_xscale('log')
axis.grid(which='both')
axis.legend(prop=fontmanage)
axis.set_xlabel(r'$k\quad [h\,{\rm Mpc}^{-1}]$', fontdict=font)
axis.set_xscale('log')
# Put on some more labels.
for axis in ax:
axis.set_xscale('log')
for tick in axis.xaxis.get_major_ticks():
tick.label.set_fontproperties(fontmanage)
for tick in axis.yaxis.get_major_ticks():
tick.label.set_fontproperties(fontmanage)
##and finish
plt.tight_layout(rect=[0, 0, 1, 0.95])
plt.savefig(figpath + '/bfit2p_L%04d_%04d.pdf'%(bs, aa*10000))
if __name__ == "__main__":
bs, nc = 400, 256
dpath = '/global/cscratch1/sd/chmodi/cosmo4d/data/z00/L%04d_N%04d_S0100_40step/' % (
bs, nc)
aa = 1.0000
zz = 1 / aa - 1
Rsm = 0
zadisp = True
pm = ParticleMesh(BoxSize=bs, Nmesh=[nc, nc, nc])
rank = pm.comm.rank
#grid = pm.mesh_coordinates()*bs/nc
lin = BigFileMesh(dpath + '/mesh', 's').paint()
print(lin.cmean())
dyn = BigFileCatalog(dpath + '/dynamic/1')
hcat = BigFileCatalog(dpath + '/FOF/')
for Rsm in [0, 2]:
for zadisp in [True, False]:
#
grid = dyn['InitPosition'].compute()
fpos = dyn['Position'].compute()
print(rank, (grid - fpos).std(axis=0))
dgrow = cosmo.scale_independent_growth_factor(zz)
if zadisp: fpos = za.doza(lin.r2c(), grid, z=zz, dgrow=dgrow)
dlay = pm.decompose(fpos)
hpos = hcat['CMPosition']