ZuMandelbaum15Sats¶
- class halotools.empirical_models.ZuMandelbaum15Sats(threshold=10.5, prim_haloprop_key='halo_m200m', **kwargs)[source]¶
Bases:
OccupationComponent
HOD-style model for a satellite galaxy occupation based on Zu & Mandelbaum 2015.
Note
The
ZuMandelbaum15Sats
model is part of thezu_mandelbaum15
prebuilt composite HOD-style model. For a tutorial on thezu_mandelbaum15
composite model, see Zu & Mandelbaum et al. (2015) Composite Model.- Parameters:
- thresholdfloat, optional
Stellar mass threshold of the mock galaxy sample in h=1 solar mass units. Default value is specified in the
model_defaults
module.- prim_haloprop_keystring, optional
String giving the column name of the primary halo property governing the occupation statistics of gal_type galaxies. Default value is specified in the
model_defaults
module.
Notes
Note also that the best-fit parameters of this model are based on the
halo_m200m
halo mass definition. Using alternative choices of mass definition will require altering the model parameters in order to mock up the same model published in Zu & Mandelbaum 2015. The Colossus python package written by Benedikt Diemer can be used to convert between different halo mass definitions. This may be useful if you wish to use an existing halo catalog for which the halo mass definition you need is unavailable.Examples
>>> sat_model = ZuMandelbaum15Sats() >>> sat_model = ZuMandelbaum15Sats(threshold=11) >>> sat_model = ZuMandelbaum15Sats(prim_haloprop_key='halo_mvir')
Methods Summary
mean_occupation
(**kwargs)Expected number of satellite galaxies in a halo of mass halo_mass.
Methods Documentation
- mean_occupation(**kwargs)[source]¶
Expected number of satellite galaxies in a halo of mass halo_mass.
- Parameters:
- prim_haloproparray, optional
array of masses of table in the catalog
- tableobject, optional
Data table storing halo catalog.
- Returns:
- mean_nsatarray
Mean number of satellite galaxies in the halo of the input mass.
Examples
>>> sat_model = ZuMandelbaum15Sats() >>> halo_masses = np.logspace(11, 15, 25) >>> mean_nsat = sat_model.mean_occupation(prim_haloprop=halo_masses)