def randoms(ns):
zmin = 0
zmax = ns.zmax
dNdZ = read_Nz(ns.nz, ns.ncol, zmin, zmax)
zedges = numpy.linspace(zmin, zmax, 12)
zcenters = 0.5 * (zedges[1:] + zedges[:-1])
dNdZ_ran = lambda z: dNdZ(z) * ns.boost
icdf, Ntotal = geticdf(dNdZ_ran, numpy.linspace(zmin, zmax, 1024))
# drop about 20% of samples to give it enough freedom.
cat = RandomCatalog(csize=int(Ntotal), seed=SEED * 20 + 19)
if cat.comm.rank == 0:
cat.logger.info("Total = %d" % Ntotal)
# generate points uniformly on a sphere.
# FIXME: add uniform sphere to nbodykit's RandomCatalog
z = cat.rng.uniform(-1., 1.)
r = abs(1 - z**2)**0.5
phi = cat.rng.uniform(0, 2 * numpy.pi)
x = da.cos(phi) * r
y = da.sin(phi) * r
z = z
ra, dec = transform.CartesianToEquatorial(da.stack((x, y, z), axis=1),
frame='galactic')
z = icdf(cat.rng.uniform(0, 1))
cat['RA'] = ra.compute()
cat['DEC'] = dec.compute()
cat['Z'] = z
cat['Aemit'] = (1 / (z + 1))
ntarget = numpy.ones_like(z, dtype='i4')
randoms = ArrayCatalog(
{
'RA': cat['RA'].compute().repeat(ntarget, axis=0),
'DEC': cat['DEC'].compute().repeat(ntarget, axis=0),
'Z': cat['Z'].compute().repeat(ntarget, axis=0),
'Aemit': cat['Aemit'].compute().repeat(ntarget, axis=0),
},
comm=cat.comm)
randoms = randoms.sort(('Aemit', ), usecols=['RA', 'DEC', 'Z', 'Aemit'])
randoms.save(ns.output, dataset=ns.odataset)
def make_galcat(aa, mmin, m1, alpha=0.9, censuff=None, satsuff=None, ofolder=None, seed=3333):
'''Assign 0s to
'''
zz = atoz(aa)
#halocat = readincatalog(aa)
halocat = BigFileCatalog(dpath + '/fastpm_%0.4f/'%aa, dataset='LL-0.200')
rank = halocat.comm.rank
halocat.attrs['BoxSize'] = np.broadcast_to(halocat.attrs['BoxSize'], 3)
ghid = halocat.Index.compute()
halocat['GlobalIndex'] = ghid
mp = halocat.attrs['MassTable'][1]*1e10
halocat['Mass'] = halocat['Length'] * mp
halocat['Position'] = halocat['Position']%bs # Wrapping positions assuming periodic boundary conditions
rank = halocat.comm.rank
halocat = halocat.to_subvolumes()
if rank == 0: print('\n ############## Redshift = %0.2f ############## \n'%zz)
hmass = halocat['Mass'].compute()
hpos = halocat['Position'].compute()
hvel = halocat['Velocity'].compute()
rvir = HaloRadius(hmass, cosmo, 1/aa-1).compute()/aa
vdisp = HaloVelocityDispersion(hmass, cosmo, 1/aa-1).compute()
ghid = halocat['GlobalIndex'].compute()
# Select halos that have galaxies
rands = np.random.uniform(size=len(hmass))
ncen = hod.ncen(mh=hmass,mcutc=mmin,sigma=0.2)
ws = (rands < ncen)
hmass = hmass[ws]
hpos = hpos[ws]
hvel = hvel[ws]
rvir = rvir[ws]
vdisp = vdisp[ws]
ghid = ghid[ws]
print('In rank = %d, Catalog size = '%rank, hmass.size)
#Do hod
start = time()
ncen = np.ones_like(hmass)
#nsat = hod.nsat_martin(msat = mmin, mh=hmass, m1f=m1f, alpha=alpha).astype(int)
nsat = hod.nsat_zheng(mh=hmass, m0=mmin, m1=20*mmin, alpha=alpha).astype(int)
#Centrals
cpos, cvel, gchid, chid = hpos, hvel, ghid, np.arange(ncen.size)
spos, svel, shid = hod.mksat(nsat, pos=hpos, vel=hvel,
vdisp=vdisp, conc=7, rvir=rvir, vsat=0.5, seed=seed)
gshid = ghid[shid]
svelh1 = svel*2/3 + cvel[shid]/3.
smmax = hmass[shid]/10.
smmin = np.ones_like(smmax)*mmin
mask = smmin > smmax/3. #Some fudge that should be discussed
smmin[mask] = smmax[mask]/3.
smass = hod.get_msat(hmass[shid], smmax, smmin, alpha)
sathmass = np.zeros_like(hmass)
tot = np.bincount(shid, smass)
sathmass[np.unique(shid)] = tot
cmass = hmass - sathmass # assign remaining mass in centrals
print('In rank = %d, Time taken = '%rank, time()-start)
print('In rank = %d, Number of centrals & satellites = '%rank, ncen.sum(), nsat.sum())
print('In rank = %d, Satellite occupancy: Max and mean = '%rank, nsat.max(), nsat.mean())
#
#Save
cencat = ArrayCatalog({'Position':cpos, 'Velocity':cvel, 'Mass':cmass, 'GlobalID':gchid,
'Nsat':nsat, 'HaloMass':hmass},
BoxSize=halocat.attrs['BoxSize'], Nmesh=halocat.attrs['NC'])
minid, maxid = cencat['GlobalID'].compute().min(), cencat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('before ', rank, minid, maxid)
cencat = cencat.sort('GlobalID')
minid, maxid = cencat['GlobalID'].compute().min(), cencat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('after ', rank, minid, maxid)
if censuff is not None:
colsave = [cols for cols in cencat.columns]
cencat.save(ofolder+'cencat'+censuff, colsave)
satcat = ArrayCatalog({'Position':spos, 'Velocity':svel, 'Velocity_HI':svelh1, 'Mass':smass,
'GlobalID':gshid, 'HaloMass':hmass[shid]},
BoxSize=halocat.attrs['BoxSize'], Nmesh=halocat.attrs['NC'])
minid, maxid = satcat['GlobalID'].compute().min(), satcat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('before ', rank, minid, maxid)
satcat = satcat.sort('GlobalID')
minid, maxid = satcat['GlobalID'].compute().min(), satcat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('after ', rank, minid, maxid)
if satsuff is not None:
colsave = [cols for cols in satcat.columns]
satcat.save(ofolder+'satcat'+satsuff, colsave)
def make_galcat(aa,
mmin,
m1f,
alpha=-1,
censuff=None,
satsuff=None,
ofolder=None,
seed=3333):
'''Assign 0s to
'''
zz = 1 / aa - 1
#halocat = readincatalog(aa)
halocat = BigFileCatalog(args['halofilez'] % aa,
dataset=args['halodataset'])
rank = halocat.comm.rank
mpart, Lbox, rsdfac, acheck = read_conversions(args['headerfilez'] % aa)
halocat.attrs['BoxSize'] = [bs, bs, bs]
halocat.attrs['NC'] = nc
ghid = halocat.Index.compute()
halocat['GlobalIndex'] = ghid
halocat['Mass'] = halocat['Length'] * mpart
halocat['Position'] = halocat[
'Position'] % bs # Wrapping positions assuming periodic boundary conditions
rank = halocat.comm.rank
halocat = halocat.to_subvolumes()
if rank == 0:
print('\n ############## Redshift = %0.2f ############## \n' % zz)
hmass = halocat['Mass'].compute()
hpos = halocat['Position'].compute()
hvel = halocat['Velocity'].compute()
rvir = HaloRadius(hmass, cosmo, 1 / aa - 1).compute() / aa
vdisp = HaloVelocityDispersion(hmass, cosmo, 1 / aa - 1).compute()
ghid = halocat['GlobalIndex'].compute()
print('In rank = %d, Catalog size = ' % rank, hmass.size)
#Do hod
start = time()
ncen = np.ones_like(hmass)
nsat = hod.nsat_martin(msat=mmin, mh=hmass, m1f=m1f,
alpha=alpha).astype(int)
#Centrals
cpos, cvel, gchid, chid = hpos, hvel, ghid, np.arange(ncen.size)
spos, svel, shid = hod.mksat(nsat,
pos=hpos,
vel=hvel,
vdisp=vdisp,
conc=7,
rvir=rvir,
vsat=0.5,
seed=seed)
gshid = ghid[shid]
svelh1 = svel * 2 / 3 + cvel[shid] / 3.
smmax = hmass[shid] / 10.
smmin = np.ones_like(smmax) * mmin
mask = smmin > smmax / 3. #If Mmin and Mmax are too close for satellites, adjust Mmin
smmin[mask] = smmax[mask] / 3.
smass = hod.get_msat(hmass[shid], smmax, smmin, alpha)
sathmass = np.zeros_like(hmass)
tot = np.bincount(shid, smass)
sathmass[np.unique(shid)] = tot
cmass = hmass - sathmass # assign remaining mass in centrals
print('In rank = %d, Time taken = ' % rank, time() - start)
print('In rank = %d, Number of centrals & satellites = ' % rank,
ncen.sum(), nsat.sum())
print('In rank = %d, Satellite occupancy: Max and mean = ' % rank,
nsat.max(), nsat.mean())
#
#Save
cencat = ArrayCatalog(
{
'Position': cpos,
'Velocity': cvel,
'Mass': cmass,
'GlobalID': gchid,
'Nsat': nsat,
'HaloMass': hmass
},
BoxSize=halocat.attrs['BoxSize'],
Nmesh=halocat.attrs['NC'])
minid, maxid = cencat['GlobalID'].compute().min(
), cencat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('before ', rank, minid, maxid)
cencat = cencat.sort('GlobalID')
minid, maxid = cencat['GlobalID'].compute().min(
), cencat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('after ', rank, minid, maxid)
if censuff is not None:
colsave = [cols for cols in cencat.columns]
cencat.save(ofolder + 'cencat' + censuff, colsave)
satcat = ArrayCatalog(
{
'Position': spos,
'Velocity': svel,
'Velocity_HI': svelh1,
'Mass': smass,
'GlobalID': gshid,
'HaloMass': hmass[shid]
},
BoxSize=halocat.attrs['BoxSize'],
Nmesh=halocat.attrs['NC'])
minid, maxid = satcat['GlobalID'].compute().min(
), satcat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('before ', rank, minid, maxid)
satcat = satcat.sort('GlobalID')
minid, maxid = satcat['GlobalID'].compute().min(
), satcat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('after ', rank, minid, maxid)
if satsuff is not None:
colsave = [cols for cols in satcat.columns]
satcat.save(ofolder + 'satcat' + satsuff, colsave)
def make_galcat(aa,
nc,
seed,
bs=1536,
T=40,
B=2,
mmin=10**12.5,
m1=20 * 10**12.5,
alpha=0.9,
censuff=None,
satsuff=None,
simpath=sc_simpath,
outpath=sc_outpath):
'''Assign 0s to
'''
fname = get_filename(nc, seed, T=T, B=B)
spath = simpath + fname
opath = outpath + fname + 'hod/'
try:
os.makedirs(opath)
except:
pass
zz = atoz(aa)
#halocat = readincatalog(aa)
halocat = BigFileCatalog(spath + '/fastpm_%0.4f/' % aa, dataset='LL-0.200')
rank = halocat.comm.rank
halocat.attrs['BoxSize'] = np.broadcast_to(halocat.attrs['BoxSize'], 3)
ghid = halocat.Index.compute()
halocat['GlobalIndex'] = ghid
mp = halocat.attrs['MassTable'][1] * 1e10
halocat['Mass'] = halocat['Length'] * mp
halocat['Position'] = halocat[
'Position'] % bs # Wrapping positions assuming periodic boundary conditions
rank = halocat.comm.rank
halocat = halocat.to_subvolumes()
if rank == 0:
print('\n ############## Redshift = %0.2f ############## \n' % zz)
hmass = halocat['Mass'].compute()
hpos = halocat['Position'].compute()
hvel = halocat['Velocity'].compute()
rvir = HaloRadius(hmass, cosmo, 1 / aa - 1).compute() / aa
vdisp = HaloVelocityDispersion(hmass, cosmo, 1 / aa - 1).compute()
ghid = halocat['GlobalIndex'].compute()
# Select halos that have galaxies
rands = np.random.uniform(size=len(hmass))
ncen = hod.ncen(mh=hmass, mcutc=mmin, sigma=0.2)
ws = (rands < ncen)
hmass = hmass[ws]
hpos = hpos[ws]
hvel = hvel[ws]
rvir = rvir[ws]
vdisp = vdisp[ws]
ghid = ghid[ws]
print('In rank = %d, Catalog size = ' % rank, hmass.size)
#Do hod
start = time()
ncen = np.ones_like(hmass)
#nsat = hod.nsat_martin(msat = mmin, mh=hmass, m1f=m1f, alpha=alpha).astype(int)
nsat = hod.nsat_zheng(mh=hmass, m0=mmin, m1=20 * mmin,
alpha=alpha).astype(int)
#Centrals
cpos, cvel, gchid, chid = hpos, hvel, ghid, np.arange(ncen.size)
spos, svel, shid = hod.mksat(nsat,
pos=hpos,
vel=hvel,
vdisp=vdisp,
conc=7,
rvir=rvir,
vsat=0.5,
seed=seed)
gshid = ghid[shid]
print('In rank = %d, Time taken = ' % rank, time() - start)
print('In rank = %d, Number of centrals & satellites = ' % rank,
ncen.sum(), nsat.sum())
print('In rank = %d, Satellite occupancy: Max and mean = ' % rank,
nsat.max(), nsat.mean())
#
#Save
cencat = ArrayCatalog({
'Position': cpos,
'GlobalID': gchid,
'Nsat': nsat
},
BoxSize=halocat.attrs['BoxSize'],
Nmesh=halocat.attrs['NC'])
minid, maxid = cencat['GlobalID'].compute().min(
), cencat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('before ', rank, minid, maxid)
cencat = cencat.sort('GlobalID')
minid, maxid = cencat['GlobalID'].compute().min(
), cencat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('after ', rank, minid, maxid)
if censuff is not None:
colsave = [cols for cols in cencat.columns]
print("Saving centrals.")
cencat.save(opath + 'cencat' + censuff, colsave)
#satcat = ArrayCatalog({'Position':spos, 'Velocity':svel, 'Velocity_HI':svelh1, 'Mass':smass,
# 'GlobalID':gshid, 'HaloMass':hmass[shid]},
# BoxSize=halocat.attrs['BoxSize'], Nmesh=halocat.attrs['NC'])
satcat = ArrayCatalog({
'Position': spos,
'GlobalID': gshid
},
BoxSize=halocat.attrs['BoxSize'],
Nmesh=halocat.attrs['NC'])
minid, maxid = satcat['GlobalID'].compute().min(
), satcat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('before ', rank, minid, maxid)
satcat = satcat.sort('GlobalID')
minid, maxid = satcat['GlobalID'].compute().min(
), satcat['GlobalID'].compute().max()
if minid < 0 or maxid < 0:
print('after ', rank, minid, maxid)
if satsuff is not None:
colsave = [cols for cols in satcat.columns]
print("Saving sats.")
satcat.save(opath + 'satcat' + satsuff, colsave)