def halocat_init(halo_catalog, z_median):
"""
Initial population of halo catalog using populate_mock function
Parameters
----------
halo_catalog: string
Path to halo catalog
z_median: float
Median redshift of survey
Returns
---------
model: halotools model instance
Model based on behroozi 2010 SMHM
"""
halocat = CachedHaloCatalog(fname=halo_catalog, update_cached_fname=True)
"""
prim_haloprop_key : String giving the column name of the primary halo
property governing stellar mass.
"""
model = PrebuiltSubhaloModelFactory('behroozi10', redshift=z_median, \
prim_haloprop_key='halo_macc')
model.populate_mock(halocat, seed=5)
return model
def populate_mock(key,halocat):
"""
Populates mock halo catalog with galaxies using Behroozi 2010 relation
Parameters
----------
key: string
Halo mass property used to populate mock (halo_mvir or halo_macc)
halocat: hdf5 file
Mock halo catalog
Returns
---------
model:
subhalo-based composite model
"""
model = PrebuiltSubhaloModelFactory('behroozi10',redshift=0.0186,\
prim_haloprop_key=key)
model.populate_mock(halocat)
return model
def halocat_init(halo_cat, z):
"""
Initial population of halo catalog using populate_mock function
Parameters
----------
halo_cat: string
Path to halo catalog
z: float
Median redshift of survey
Returns
---------
model: halotools model instance
Model based on behroozi 2010 SMHM
"""
halocat = CachedHaloCatalog(fname=halo_cat, update_cached_fname=True)
model = PrebuiltSubhaloModelFactory('behroozi10', redshift=z, \
prim_haloprop_key='halo_macc')
model.populate_mock(halocat, seed=5)
return model
(eco_buff.logmstar.values >= 8.9)]
cvar = 0.125
volume = 151829.26 # Survey volume without buffer [Mpc/h]^3
# BMF
eco_nobuff_mstellar = eco_nobuff.logmstar.values
eco_nobuff_mgas = eco_nobuff.logmgas.values
eco_nobuff_mbary = calc_bary(eco_nobuff_mstellar, eco_nobuff_mgas)
maxis, phi, err, bins = diff_bmf(eco_nobuff_mbary, volume, cvar, False)
halocat = CachedHaloCatalog(fname=halo_catalog, update_cached_fname=True)
z_model = np.median(eco_nobuff.grpcz.values) / (3 * 10**5)
model = PrebuiltSubhaloModelFactory('behroozi10', redshift=z_model,
prim_haloprop_key='halo_macc')
model.populate_mock(halocat)
# ensure reproducibility
rseed = 12
np.random.seed(rseed)
behroozi10_param_vals = [12.35,10.72,0.44,0.57,0.15]
nwalkers = 250
ndim = 5
p0 = behroozi10_param_vals + 0.1*np.random.rand(ndim*nwalkers).\
reshape((nwalkers,ndim))
with Pool(processes=20) as pool:
sampler = emcee.EnsembleSampler(nwalkers, ndim, lnprob, args=(phi, err)\
,pool=pool)
start = time.time()
prim_haloprop_key='halo_macc')
model5 = PrebuiltSubhaloModelFactory('behroozi10',
redshift=z_median,
prim_haloprop_key='halo_macc')
print('Setting up halocats')
###Halocats
halocat1 = CachedHaloCatalog(fname=halo_catalog)
halocat2 = CachedHaloCatalog(fname=halo_catalog)
halocat3 = CachedHaloCatalog(fname=halo_catalog)
halocat4 = CachedHaloCatalog(fname=halo_catalog)
halocat5 = CachedHaloCatalog(fname=halo_catalog)
print('Initial mock population')
###Populate mocks
model1.populate_mock(halocat1)
model2.populate_mock(halocat2)
model3.populate_mock(halocat3)
model4.populate_mock(halocat4)
model5.populate_mock(halocat5)
def gals(Mhalo_value, Mstellar_value, Mlow_slope, Mhigh_slope,
Mstellar_scatter):
###Parameter values
model1.param_dict['smhm_m1_0'] = Mhalo_value
model2.param_dict['smhm_m0_0'] = Mstellar_value
model3.param_dict['smhm_beta_0'] = Mlow_slope
model4.param_dict['smhm_delta_0'] = Mhigh_slope
model5.param_dict['scatter_model_param1'] = Mstellar_scatter