def run(self,
zlim,
nmesh,
Poles=[0, 2, 4],
dK=None,
kMin=0.0,
use_fkp=True,
P0fkp=6e3):
zmin, zmax = zlim
self.randoms['Selection'] = (self.randoms['Z'] >=
zmin) & (self.randoms['Z'] < zmax)
self.data['Selection'] = (self.data['Z'] >= zmin) & (self.data['Z'] <
zmax)
#
# combine the data and randoms into a single catalog
# add the n(z) columns to the FKPCatalog
#
fkp = nb.FKPCatalog(self.data, self.randoms)
fkp['randoms/NZ'] = self.nofz(self.randoms['Z'])
fkp['data/NZ'] = self.nofz(self.data['Z'])
mesh = fkp.to_mesh(Nmesh=nmesh, nbar='NZ')
#
#
r = nb.ConvolvedFFTPower(mesh,
poles=Poles,
dk=dK,
kmin=kMin,
use_fkp_weights=use_fkp,
P0_FKP=P0fkp)
output = {}
output['attrs'] = r.attrs
output['attrs']['zbin'] = zlim
output['poles_data'] = r.poles
output['nz'] = self.nofz
return output
# apply the Completeness weights to both data and randoms
if sys_tot:
if rank ==0:print('including sys_tot')
data['WEIGHT'] = data['WEIGHT_SYSTOT'] * data['WEIGHT_NOZ'] * data['WEIGHT_CP']
else:
if rank ==0:print('excluding sys_tot')
data['WEIGHT'] = data['WEIGHT_NOZ'] * data['WEIGHT_CP'] # data['WEIGHT_SYSTOT']
randoms['WEIGHT'] = randoms['WEIGHT_SYSTOT'] * randoms['WEIGHT_NOZ'] * randoms['WEIGHT_CP']
# combine the data and randoms into a single catalog
fkp = nb.FKPCatalog(data, randoms, nbar='NZ')
mesh = fkp.to_mesh(Nmesh=nmesh, fkp_weight='WEIGHT_FKP', comp_weight='WEIGHT', window='tsc')
# compute
r = nb.ConvolvedFFTPower(mesh, poles=[0, 2, 4], dk=0.001, kmin=0.0)
# save
r.save(output_path)
# --- save in txt format
comm.Barrier()
if rank == 0:
#
# write P0-shotnoise P2 P4 to file
with open(output_path.replace('.json', '.txt'), 'w') as output:
# write the attributes
for k in r.attrs:
output.write(f'#{k:20s} : {r.attrs[k]}\n')
def run_ConvolvedFFTPower(galaxy_path,
random_path,
output_path,
use_systot=True,
zmin=None,
zmax=None,
compmin=0.5,
cosmology=None,
boxsize=None,
nmesh=512,
dk=0.002,
poles=[0, 2, 4],
kmax=None,
comm=None,
return_pk=False):
if isinstance(nmesh, list):
if len(nmesh)==1:
nmesh=nmesh[0]
if isinstance(boxsize, list):
if len(boxsize)==1:
boxsize=boxsize[0]
if (cosmology is None) or (cosmology=='boss'):
# the fiducial BOSS DR12 cosmology
# see Alam et al. https://arxiv.org/abs/1607.03155
cosmo = Cosmology(h=0.676).match(Omega0_m=0.31)
elif cosmology=='ezmock':
_h = 0.6777
_Ob0 = 0.048206
_Ocdm0 = 0.307115 - _Ob0
cosmo = Cosmology(h=_h, Omega_b=_Ob0, Omega_cdm=_Ocdm0,
m_ncdm=None, n_s=0.9611, T_cmb=2.7255).match(sigma8=0.8225)
elif cosmology=='boss2':
h = 0.676
redshift = 1.48
cos = Cosmology(h=0.676,Omega0_b=0.022/h**2,n_s=0.97).match(Omega0_m=0.31)
cosmo = cos.match(sigma8=0.8)
elif isinstance(cosmology, Cosmology):
cosmo = cosmology
else:
raise NotImplementedError(f'{cosmology} is not implemented')
data = FITSCat(galaxy_path)
random = FITSCat(random_path)
# select based on redshift and comp_BOSS
kwargs = dict(compmin=compmin, zmin=zmin, zmax=zmax)
data = data.trim_redshift_range(**kwargs)
random = random.trim_redshift_range(**kwargs)
# sky to xyz
data.sky_to_xyz(cosmo)
random.sky_to_xyz(cosmo)
# prepare weights
data.apply_weight(use_systot=use_systot)
random.apply_weight(use_systot=True) # always weight randoms by systot
# combine the data and randoms into a single catalog
mesh_kwargs = {'interlaced': True,'window': 'tsc'}
fkp = nb.FKPCatalog(data, random, nbar='NZ', BoxSize=boxsize)
mesh = fkp.to_mesh(Nmesh=nmesh, fkp_weight='WEIGHT_FKP', **mesh_kwargs)
r = nb.ConvolvedFFTPower(mesh, poles=poles, dk=dk, kmin=0.0, kmax=kmax)
comm.Barrier()
if comm.rank == 0:
for parameter in ['sigma8', 'Omega0_m', 'h', 'n_s',
'Omega0_b', 'Omega0_lambda']:
r.attrs[parameter] = getattr(cosmo, parameter)
if comm.rank == 0:
output_dir = os.path.dirname(os.path.abspath(output_path))
if not os.path.exists(output_dir):
os.makedirs(output_dir)
r.save(output_path)
if return_pk:
if comm.rank == 0:
return r
# initialize the FKP source
# add the n(z) columns to the FKPCatalog
randoms['NZ'] = nofz(randoms[zcol_name])
data['NZ'] = nofz(data[zcol_name])
fkp = nb.FKPCatalog(data, randoms, nbar='NZ')
Pzero = 6000
fkp['data/FKPWeight'] = 1.0 / (1 + fkp['data/NZ'] * Pzero)
fkp['randoms/FKPWeight'] = 1.0 / (1 + fkp['randoms/NZ'] * Pzero)
mesh = fkp.to_mesh(Nmesh=ns.nmesh,
fkp_weight='FKPWeight',
comp_weight='Weight',
window='tsc')
r = nb.ConvolvedFFTPower(mesh, poles=ns.poles, dk=0.005, kmin=0.0)
comm.Barrier()
if rank == 0:
#
# write P0-shotnoise P2 P4 to file
output = open(ns.output, 'w')
for k in args:
output.write(f'#{k:20s} : {args[k]}\n')
# write the attributes
for k in r.attrs:
output.write(f'#{k:20s} : {r.attrs[k]}\n')
output.write('# k_avg P0 P2 P4 Nmodes\n')