slsim.Pipelines package

Submodules

slsim.Pipelines.halos_pipeline module

class slsim.Pipelines.halos_pipeline.HalosSkyPyPipeline(skypy_config=None, sky_area=None, m_min=None, m_max=None, z_max=None, cosmo=None, sigma_8=0.81, n_s=0.96, omega_m=None)[source]

Bases: object

Class for halos configuration.

property halos

SkyPy pipeline for Halos.

Returns:

List of halos.

Return type:

list of dict

property mass_sheet_correction

SkyPy pipeline for mass sheet correction.

Returns:

List of sheet of mass for correction.

Return type:

list of dict

slsim.Pipelines.roman_speclite module

slsim.Pipelines.roman_speclite.configure_roman_filters()[source]
Returns:

Roman filters stored and accessible in speclite

slsim.Pipelines.roman_speclite.filter_names()[source]
Returns:

list of filter names with full path

slsim.Pipelines.skypy_pipeline module

class slsim.Pipelines.skypy_pipeline.SkyPyPipeline(skypy_config=None, sky_area=None, filters=None, cosmo=None, z_min=None, z_max=None)[source]

Bases: object

Class for skypy configuration.

property blue_galaxies

Skypy pipeline for blue galaxies.

Returns:

list of blue galaxies

Return type:

list of dict

property red_galaxies

Skypy pipeline for red galaxies.

Returns:

list of red galaxies

Return type:

list of dict

slsim.Pipelines.sl_hammocks_pipeline module

class slsim.Pipelines.sl_hammocks_pipeline.SLHammocksPipeline(skypy_config=None, slhammocks_config=None, sky_area=None, cosmo=None, z_min=None, z_max=None, loghm_min=11.5, loghm_max=16.0)[source]

Bases: object

SLHammocksPipeline is a class that generate galaxy populations using a halo-model approach. It supports either loading pre-generated galaxy population data from a CSV file or generating the population on-the-fly based on halo occupation and galaxy property models.

The pipeline integrates halo properties (mass, redshift) with stellar masses and computes photometric magnitudes using SkyPy. For this we need to execute skypy pipeline with in this class.

property halo_galaxies

Slhammock pipeline for galaxies.

Returns:

list of galaxies from halo model

Return type:

list of dict

slsim.Pipelines.sl_hammocks_pipeline.halo_galaxy_population(sky_area, cosmo, z_min, z_max, log10host_halo_mass_min, log10host_halo_mass_max, sigma_host_halo_concentration, sigma_central_galaxy_mass, sig_tb, TYPE_GAL_SIZE, frac_SM_IMF, sigma8, ns, TYPE_SMHM, **kwargs)[source]
Parameters:

  • sky_area (~astropy.units.Quantity) – Sky area over which galaxies are sampled. Must be in units of solid angle.

  • cosmo (astropy.cosmology instance or None) – An instance of an astropy cosmology model (e.g., FlatLambdaCDM(H0=70, Om0=0.3)).

  • z_min (float) – Lower limit of the redshift range when generating delector population.

  • z_max (float) – Upper limit of the redshift range when generating delector population.

  • log10host_halo_mass_min (float) – Lower limit of host halo mass (in log10 scale).

  • log10host_halo_mass_max (float) – Upper limit of host halo mass (in log10 scale).

  • sigma_host_halo_concentration (float) – Intrinsic scatter of the concentration parameter of dark matter halos. Represents the variance value in a log-normal distribution. (https://arxiv.org/abs/astro-ph/0608157)

  • sigma_central_galaxy_mass – Intrinsic scatter of the stellar-mass-halo-mass relation. Represents the variance value in a log-normal distribution. (https://iopscience.iop.org/article/10.3847/1538-4357/ac4cb4/pdf) :type sigma_central_galaxy_mass: float

  • sig_tb (float) – Scatter of the galaxy-mass-size relation only used when you set ‘oguri20’ in “TYPE_GAL_SIZE”. Represents the variance value in a log-normal distribution.

  • TYPE_GAL_SIZE (str) – Type of galaxy size model to use. (Now three available options [‘vdw23’, ‘oguri20’, ‘karmakar23’])

  • frac_SM_IMF (float) – Fraction of stellar M/L ratio against the Chabrier initial mass function(IMF). (e.g., 1.0 for Chabrier IMF, 1.715 for Salpeter IMF)

  • TYPE_SMHM (str) – Type of fitting function for the stellar-mass-halo-mass relation for quiescent galaxies, see Behroozi et al. 2019 for detail (Currently three options [‘true’, ‘obs’, ‘true_all’])

  • sigma8 (float) – The normalization of the power spectrum, i.e. the variance when the field is filtered with a top hat filter of radius 8 Mpc/h. This parameter is required to convert from astropy.cosmology to colossus.cosmology

  • ns (float) – The tilt of the primordial power spectrum. This parameter is required to convert from astropy.cosmology to colossus.cosmology

  • kwargs (dict) – keyword arguments

Returns:

table_pop containing as follows: - ‘z” : redshift - ‘halo_mass’ : halo mass in units of M_sol/h - ‘halo_mass_acc’ : halo mass at accretion time in units of M_sol/h for subhalos. - ‘e_h’ : ellipticity of halos defined as 1-q, where q is axis ratio - ‘p_h’ : position angle of halos in units of degree. - ‘concentration’ : concentration parameter of halos - ‘stellar_mass’ : stellar mass in units of M_sol/h - ‘ellipticity’ : ellipticity of galaxies defined as 1-q, where q is axis ratio - ‘p_g’ : position angle of galaxies in units of degree. - ‘tb’ : scale radius of galaxies appeared in Hernquist profile in units of arcsec

slsim.Pipelines.sl_hammocks_pipeline.table_translator_for_slsim(table, cosmo)[source]

Translation astropy.table generated by either ways of loading csv file or implementing halo_galaxy_population function to be readable in slsim.

Parameters:

  • table (astropy.table) – original deflector population

  • cosmo (astropy.cosmology instance or None) – An instance of an astropy cosmology model (e.g., FlatLambdaCDM(H0=70, Om0=0.3)).

Returns:

table. astropy.table.Table. This class initializes an object with data on deflectors.

This data table should have the following columns:

  • ’z’: Redshift of the deflectors

  • ’halo_mass’: M200 of the halo components in units of M_sol

  • ’halo_mass_acc’: M200 of subhalo component at the accretion time in units of M_sol.

    For host halos, this value becomes 0. Currently, this table does not include subhalos.

  • ’e_h’: ellipticily of dark matter halo, which is defined by epsilon=(1-q^2)/(1+q^2), where q=b/a and a, b are major and minor axis of dark matter halo, respectively.

  • ’p_h’: posiiton angle of the halo in units of degree

  • ’concentration’: Concentration parameter of the halo

  • ’stellar_mass’: Mass of stars in the object

  • ’e_g’: ellipticity of the galaxy, which is defined by epsilon=(1-q^2)/(1+q^2), where q=b/a and a, b are major and minor axis of galaxy, respectively

  • ’p_g’: posiiton angle of the galaxy in units of degree

  • ’tb’: the scale radius appreared in Hernquist profile in units of arcsec.

    This parameter relates to the commonly used galaxy effective (half-mass) radius by t_b = 0.551*theta_eff.

  • ’angular_size’: galaxy effective radius in units of arcsec

Module contents

class slsim.Pipelines.HalosSkyPyPipeline(skypy_config=None, sky_area=None, m_min=None, m_max=None, z_max=None, cosmo=None, sigma_8=0.81, n_s=0.96, omega_m=None)[source]

Bases: object

Class for halos configuration.

property halos

SkyPy pipeline for Halos.

Returns:

List of halos.

Return type:

list of dict

property mass_sheet_correction

SkyPy pipeline for mass sheet correction.

Returns:

List of sheet of mass for correction.

Return type:

list of dict

class slsim.Pipelines.SLHammocksPipeline(skypy_config=None, slhammocks_config=None, sky_area=None, cosmo=None, z_min=None, z_max=None, loghm_min=11.5, loghm_max=16.0)[source]

Bases: object

SLHammocksPipeline is a class that generate galaxy populations using a halo-model approach. It supports either loading pre-generated galaxy population data from a CSV file or generating the population on-the-fly based on halo occupation and galaxy property models.

The pipeline integrates halo properties (mass, redshift) with stellar masses and computes photometric magnitudes using SkyPy. For this we need to execute skypy pipeline with in this class.

property halo_galaxies

Slhammock pipeline for galaxies.

Returns:

list of galaxies from halo model

Return type:

list of dict

class slsim.Pipelines.SkyPyPipeline(skypy_config=None, sky_area=None, filters=None, cosmo=None, z_min=None, z_max=None)[source]

Bases: object

Class for skypy configuration.

property blue_galaxies

Skypy pipeline for blue galaxies.

Returns:

list of blue galaxies

Return type:

list of dict

property red_galaxies

Skypy pipeline for red galaxies.

Returns:

list of red galaxies

Return type:

list of dict