Basic Usage

To populate a DM catalogue with mock galaxies assigned a UV magnitude you would do something like:

# read the GADGET SUBFIND tables
from scampy.io.subfind_table import subfind_table
tab = subfind_table( "/path/to/subhalo_tab_snap" )
tab.read_all_files()

# build halo and sub-halo catalogue objects
import numpy as np
from scampy.catalogue import haloCat, subhaloCat, catalogue

haloes = haloCat(
    len( tab.content['GroupMass'] ),
    Mhalo    = tab.content['GroupMass'],
    Rhalo    = tab.content['GroupRadiusM200'],
    X        = tab.content['GroupPos'][:, 0],
    Y        = tab.content['GroupPos'][:, 1],
    Z        = tab.content['GroupPos'][:, 2],
    firstSub = tab.content['GroupFirstSub'],
    numSubs  = tab.content['GroupNsubs'],
)
subhaloes = subhaloCat(
    len( tab.content['SubhaloMass'] ),
    Msubh  = tab.content['SubhaloMass'],
    Parent = tab.content['SubhaloGrNr'],
    X      = tab.content['SubhaloPos'][:, 0],
    Y      = tab.content['SubhaloPos'][:, 1],
    Z      = tab.content['SubhaloPos'][:, 2],
)
cat = catalogue( haloes, subhaloes, Lbox = 512. )  # Lbox in Mpc/h

# select host sub-haloes with an HOD
from scampy.hod import HOD, get_hosts
hod   = HOD( Mmin=1.e12, siglogM=0.5, M0=1.e12, M1=1.e13, alpha=1. )
hosts = get_hosts( cat, Pcen=hod.Pcen, Psat=hod.Psat )

# define a Schechter-like UV luminosity function
def schechter ( mag ) :
    alpha = -1.07
    norm  = 1.6e-2
    mstar = -19.7 + 5. * np.log10( 5. )
    lum   = -0.4 * ( mag - mstar )
    return 0.4 * np.log( 10 ) * norm * 10**( -0.07 * lum ) * np.exp( -10**lum )

# assign magnitudes via sub-halo abundance matching
from scampy.sham import match_distribution
magnitudes = match_distribution(
    cat.subhaloes['Msubh'][hosts], schechter,
    minF = -25, maxF = -10, factF = 1. / cat.volume,
)

The magnitudes array contains the UV magnitude assigned to each mock galaxy.

Installation

The recommended installation uses pip:

pip install scampy

To install from source after cloning the repository:

git clone https://github.com/TommasoRonconi/scampy.git
cd scampy
pip install .

Alternatively, a conda environment file is provided:

conda env create -f scampy_environment.yml
conda activate scampy
pip install .

Requirements

Runtime:

• numpy

• scipy

• matplotlib>=3.6

• h5py

Python: 3.10 or later recommended (3.8+ supported).

Documentation (optional):

• sphinx>=5.0

• sphinx-rtd-theme

• myst-parser