def __init__(self, **kwargs):
Zheng07Cens.__init__(self, **kwargs)
PreservingNgalHeavisideAssembias.__init__(
self,
lower_assembias_bound=self._lower_occupation_bound,
upper_assembias_bound=self._upper_occupation_bound,
method_name_to_decorate='mean_occupation',
**kwargs)
def __init__(self, **kwargs):
Zheng07Cens.__init__(self, threshold = -21)
HeavisideAssembias.__init__(self,
method_name_to_decorate = 'mean_occupation',
lower_assembias_bound = 0.,
upper_assembias_bound = 1,
**kwargs)
def __init__(self, config):
super().__init__(config)
self.cur_wp = np.zeros(11)
if self['sim'] == "bolplanck":
halocat = CachedHaloCatalog(simname='bolplanck')
elif self['sim'] == "old":
halocat = CachedHaloCatalog(
fname='/home/lom31/Halo/hlist_1.00231.list.halotools_v0p1.hdf5',
update_cached_fname=True)
halocat.redshift = 0.
elif self['sim'] == "smdpl":
halocat = CachedHaloCatalog(
fname=
'/home/lom31/.astropy/cache/halotools/halo_catalogs/SMDPL/rockstar/2019-07-03-18-38-02-9731.dat.my_cosmosim_halos.hdf5',
update_cached_fname=True)
#halocat = CachedHaloCatalog(fname='/home/lom31/.astropy/cache/halotools/halo_catalogs/smdpl/rockstar/2019-07-03-18-38-02-9731.dat.my_cosmosim_halos.hdf5',update_cached_fname = True)
halocat.redshift = 0.
elif self['sim'] == "mdr1":
halocat = CachedHaloCatalog(
fname=
'/home/lom31/.astropy/cache/halotools/halo_catalogs/multidark/rockstar/hlist_0.68215.list.halotools_v0p4.hdf5',
update_cached_fname=True)
if self['param'] == 'mvir':
cens_occ_model = Zheng07Cens(threshold=-19)
cens_prof_model = TrivialPhaseSpace()
sats_occ_model = Zheng07Sats(modulate_with_cenocc=True,
threshold=-19)
sats_prof_model = NFWPhaseSpace()
elif self['param'] == 'vmax':
cens_occ_model = Zheng07Cens(prim_haloprop_key='halo_vmax',
threshold=-19)
cens_prof_model = TrivialPhaseSpace()
sats_occ_model = Zheng07Sats(prim_haloprop_key='halo_vmax',
threshold=-19,
modulate_with_cenocc=True)
sats_prof_model = NFWPhaseSpace()
global model_instance
model_instance = HodModelFactory(centrals_occupation=cens_occ_model,
centrals_profile=cens_prof_model,
satellites_occupation=sats_occ_model,
satellites_profile=sats_prof_model)
try:
model_instance.mock.populate()
except:
model_instance.populate_mock(halocat)
def to_halotools(cosmo, redshift, mdef, concentration_key=None, **kwargs):
"""
Return the Zheng 07 HOD model.
See :func:`halotools.empirical_models.zheng07_model_dictionary`.
Parameters
----------
cosmo :
the nbodykit or astropy Cosmology object to use in the model
redshift : float
the desired redshift of the model
mdef : str, optional
string specifying mass definition, used for computing default
halo radii and concentration; should be 'vir' or 'XXXc' or
'XXXm' where 'XXX' is an int specifying the overdensity
concentration_key : str
the name of the column that will specify concentration; if not
provided, the analytic formula from
`Dutton and Maccio 2014 <https://arxiv.org/abs/1402.7073>`_
is used.
**kwargs :
additional keywords passed to the model components; see the
Halotools documentation for further details
Returns
-------
:class:`~halotools.empirical_models.HodModelFactory`
the halotools object implementing the HOD model
"""
from halotools.empirical_models import Zheng07Sats, Zheng07Cens, NFWPhaseSpace, TrivialPhaseSpace
from halotools.empirical_models import HodModelFactory
kwargs.setdefault('modulate_with_cenocc', True)
# need astropy Cosmology
if isinstance(cosmo, Cosmology):
cosmo = cosmo.to_astropy()
# determine concentration key
if concentration_key is None:
conc_mass_model = 'dutton_maccio14'
else:
conc_mass_model = 'direct_from_halo_catalog'
# determine mass column
mass_key = 'halo_m' + mdef
# occupation functions
cenocc = Zheng07Cens(prim_haloprop_key=mass_key, **kwargs)
satocc = Zheng07Sats(prim_haloprop_key=mass_key,
cenocc_model=cenocc,
**kwargs)
satocc._suppress_repeated_param_warning = True
# profile functions
kwargs.update({'cosmology': cosmo, 'redshift': redshift, 'mdef': mdef})
censprof = TrivialPhaseSpace(**kwargs)
satsprof = NFWPhaseSpace(conc_mass_model=conc_mass_model, **kwargs)
# make the model
model = {}
model['centrals_occupation'] = cenocc
model['centrals_profile'] = censprof
model['satellites_occupation'] = satocc
model['satellites_profile'] = satsprof
return HodModelFactory(**model)
],
[
-3.56879870e+00, -2.27808131e+00, -1.34387366e+00, 2.79344609e-01,
-8.16055506e-01, 2.51356140e-01, 5.03253824e-01, 5.08217249e-01,
3.29184438e-01, 1.34667684e-01, 3.97669949e-01, 4.19781524e-01,
1.70968431e-01, 2.40612750e-01, 4.47443368e-01, 6.34967423e-01,
7.59893604e-01, 9.83776744e-01, 1.37576149e+00, 1.55288996e+00,
1.88033657e+00, 2.33929965e+00, 2.93594021e+00, 3.46849456e+00,
4.26576964e+00, 5.18755609e+00, 6.10833984e+00, 7.04389976e+00,
7.09565921e+00
]])
err = np.sqrt(np.array([cov[i, i] for i in range(len(cov))]))
bin_cen = (bin_edges[1:] + bin_edges[:-1]) / 2.
cens_occ_model = Zheng07Cens(prim_haloprop_key='halo_vmax')
cens_prof_model = TrivialPhaseSpace()
sats_occ_model = Zheng07Sats(prim_haloprop_key='halo_vmax')
sats_prof_model = NFWPhaseSpace()
model_instance = HodModelFactory(centrals_occupation=cens_occ_model,
centrals_profile=cens_prof_model,
satellites_occupation=sats_occ_model,
satellites_profile=sats_prof_model)
halocat = CachedHaloCatalog(simname='bolplanck', redshift=0.0)
model_instance.populate_mock(halocat)
#log liklihood
def lnlike(theta): #, wp_val, wperr, model_instance):
