halomod.halo_model.TracerHaloModel¶
- class halomod.halo_model.TracerHaloModel(*args, **kwargs)[source]¶
Describe spatial statistics of a tracer population (eg. galaxies) using a HOD.
All of the quantities in
DMHaloModel
are available here, with the addition of several more explicitly for the tracer population, including cross-correlations.Note that the flexibility of prescribing different models for the tracer population than the underlying DM halo population is afforded for such components as the profile and concentration-mass relation. By default,these are set to be the same as the DM models. This may be useful if eg. galaxies are not expected to trace the underlying dark matter density within a halo.
Note that all *_model parameters can be a string or a class of the type described below. If a string, it should be the name of a class that must exist in the relevant module within
halomod
.- Parameters
hod_model (str or
HOD
subclass, optional) – A model for the halo occupation distribution.hod_params (dict, optional) – Parameters for the HOD model.
tracer_profile_model (str or
Profile
subclass, optional) – A density profile model for the abundance of the tracer within haloes of a given mass.tracer_profile_params (dict, optional) – Parameters for the tracer density profile model.
tracer_concentration_model (str or
CMRelation
subclass, optional) – A concentration-mass relation supporting the tracer profile.tracer_concentration_params (dict, optional) – Parameters for the tracer CM relation.
tracer_density (float, optional) – Total density of the tracer, in the units specified by the HOD model. This can be used to set the minimum halo mass of the HOD.
force_1halo_turnover (bool, optional) – Whether to force the 1-halo term to turnover on large scales. THis induces a heuristic modification which ensures that the 1-halo term does not grow larger than the two-halo term on very large scales.
:param All other parameters are passed to
DMHaloModel
.:Methods
__init__
([hod_model, hod_params, …])Initializer for the class.
clone
(**kwargs)Create and return an updated clone of the current object.
get_all_parameter_defaults
([recursive])Dictionary of all parameters and defaults.
Yield all parameter names in the class.
get_dependencies
(*q)Determine all parameter dependencies of the quantities in q.
parameter_info
([names])Prints information about each parameter in the class.
power_hh
(k[, mmin, mmax, mmin2, mmax2])The halo-centre power spectrum of haloes in a given mass range.
Obtain a list of all available output quantities.
update
(**kwargs)Updates any parameter passed.
validate
()Perform validation of the input parameters as they relate to each other.
Attributes
Switch to turn off exceptions for mdef’s not matching hmf_model
Maximum mass at which to perform analysis [units \(\log_{10}M_\odot h^{-1}\)].
Minimum mass at which to perform analysis [units \(\log_{10}M_\odot h^{-1}\)].
The halo bias as a function of halo mass.
The effective bias of matter in DM halos.
The tracer occupation-weighted halo bias factor (Tinker 2005).
Bias Model.
Dictionary of parameters for the Bias model.
The total fraction of tracers that are centrals.
The mean central occupation of the tracer as a function of halo mass.
Concentration-mass-redshift relation.
An instance of a COLOSSUS cosmology, which can be used to perform various COLOSSUS operations.
Options for colossus cosmology not set/derived in the astropy cosmology.
The halo model 1-halo dark matter auto-correlation function.
A callable returning the halo model 1-halo DM auto-correlation function.
The 1-halo term of the tracer auto correlations.
A callable returning the 1-halo term of the tracer auto correlations.
The 1-halo term of the cross correlation between tracer and matter.
A callable returning the 1-halo cross-corr between tracer and matter.
The cen-sat part of the 1-halo term of the tracer auto-correlation function.
A callable returning the cen-sat part of the 1-halo term of the tracer auto-correlation function.
The satellite-satellite part of the 1-halo term of the tracer auto-correlation function.
A callable returning the satellite-satellite part of the 1-halo term of the tracer auto-correlation function.
The 2-halo term of the matter auto-correlation.
A callable returning the 2-halo term of the matter auto-correlation at arbitrary k.
The 2-halo term of the tracer auto-correlation.
A callable returning the 2-halo term of the tracer auto-correlation.
The 2-halo term of the cross-correlation between tracer and matter.
A callable returning the 2-halo cross-corr between tracer and matter.
The halo-model-derived nonlinear dark matter auto-correlation function.
A callable returning the halo-model DM auto-correlation function.
The tracer auto correlation function.
A callable returning the tracer auto correlation function.
Cross-correlation of tracer with matter.
A callable returning the cross-correlation of tracer with matter.
See
corr_auto_tracer()
.The nonlinear (from halofit) auto-correlation function of dark matter.
A callable returning the nonlinear auto-correlation function of dark matter.
The linear auto-correlation function of dark matter.
A callable returning the linear auto-correlation function of dark matter.
See
corr_auto_matter()
.Cosmographic object (
astropy.cosmology.FLRW
object), with custom cosmology fromcosmo_params
applied.The basis for the cosmology – see astropy documentation.
Parameters for the cosmology that deviate from the base cosmology passed.
The critical overdensity for collapse, \(\delta_c\).
Dimensionless power spectrum, \(\Delta_k = \frac{k^3 P(k)}{2\pi^2}\).
Disable converting mass function from builtin definition to that provided.
Step-size of log wave-numbers
log10 interval between mass bins
The differential mass function in terms of natural log of m,
len=len(m)
[units \(h^3 Mpc^{-3}\)]The differential mass function in terms of log of m,
len=len(m)
[units \(h^3 Mpc^{-3}\)]The number density of haloes,
len=len(m)
[units \(h^4 M_\odot^{-1} Mpc^{-3}\)]The width of r bin.
A string identifier for the type of halo exclusion used (or None).
Dictionary of parameters for the Exclusion model.
Instantiated model for filter/window functions.
A model for the window/filter function.
Model parameters for filter_model.
Suppress 1-halo power on scales larger than a few virial radii.
The multiplicity function, \(f(\sigma)\), for hmf_model.
The instantiated growth model.
The growth factor.
The model to use to calculate the growth function/growth rate.
Relevant parameters of the
growth_model
.Halo bias.
The concentration-mass relation.
A halo_concentration-mass relation
Dictionary of parameters for the concentration model.
The halo overdensity with respect to the critical density.
The halo overdensity with respect to the mean background.
A class containing the elements necessary to calculate halo halo_profile quantities.
Mass-normalised halo profile self-convolution, with shape (len(r), len(m)).
The halo density halo_profile model.
Dictionary of parameters for the Profile model.
Mass-normalised halo density profile, with shape (len(r), len(m)).
Mass-normalised fourier halo profile, with shape (len(k), len(m)).
The spectrum with which the halo-centre power spectrum is identified.
The width of k bin in log10.
The maximum k bin in log10.
The minimum k bin in log10.
Instantiated model for the hmf fitting function.
A model to use as the fitting function \(f(\sigma)\)
Model parameters for hmf_model.
A class representing the HOD
HOD
class.Dictionary of parameters for the HOD model.
Size of simulation volume in which to expect one halo of mass m (with 95% probability), ` len=len(m)` [units \(Mpch^{-1}\)]
Wavenumbers, [h/Mpc]
The wave-numbers at which halo-model power spectra are calculated.
A callable returning the linear power as a function of k (in h/Mpc).
Maximum (natural) log wave-number,
k
[h/Mpc].Minimum (natural) log wave-number,
k
[h/Mpc].Natural log of inverse mass variance,
len=len(m)
.Halo masses (defined via
mdef
).Average host-halo mass (in log10 units).
The nonlinear mass, nu(Mstar) = 1.
The halo mass-definition model instance.
A model to use as the mass definition.
Model parameters for mdef_model.
Mean density of universe at redshift z.
Mean density of universe at z=0, [Msun h^2 / Mpc**3]
The mean density of the tracer.
The mean density of the tracer, in the units defined in the HOD.
Spectral index of fluctuations
Effective spectral index at scale of halo radius,
len=len(m)
The cumulative mass function above m,
len=len(m)
[units \(h^3 Mpc^{-3}\)]Dimensionless nonlinear power spectrum.
Non-linear log power [units \(Mpc^3/h^3\)].
A callable returning the nonlinear (halofit) power as a function of k (in h/Mpc).
A normalised filter, such that filter.sigma(8) == sigma8
The parameter \(\nu = \left(\frac{\delta_c}{\sigma}\right)^2\),
len=len(m)
Dictionary of all parameters and their current values
Normalised log power spectrum [units \(Mpc^3/h^3\)].
The halo model-derived nonlinear 1-halo dark matter auto-power spectrum.
A callable returning the halo model 1-halo DM auto-power spectrum.
The total 1-halo term of the tracer auto power spectrum.
A callable returning the total 1-halo term of the tracer auto power spectrum.
The total 1-halo cross-power spectrum between tracer and matter.
A callable returning the total 1-halo cross-power spectrum between tracer and matter.
The cen-sat part of the 1-halo term of the tracer auto-power spectrum.
A callable returning the cen-sat part of the 1-halo term of the tracer auto-power spectrum.
The satellite-satellite part of the 1-halo term of the tracer auto-power spectrum.
A callable returning the satellite-satellite part of the 1-halo term of the tracer auto-power spectrum.
The halo model 2-halo matter auto-power spectrum at
k_hm
.Return the halo model 2-halo matter auto-power spectrum at k.
The 2-halo term of the tracer auto-power spectrum.
Return the 2-halo term of the tracer auto-power spectrum at k.
The 2-halo term of the cross-power spectrum between tracer and matter.
A callable returning the 2-halo cross-power between tracer and matter.
The halo-model-derived nonlinear dark power auto-power spectrum.
A callable returning the halo-model DM auto-power spectrum.
Auto-power spectrum of the tracer.
Cross-power spectrum between tracer and matter.
A callable returning cross-power spectrum of tracer and matter.
See
power_auto_tracer()
.See
corr_auto_tracer()
.See
power_auto_matter()
.Scales at which correlation functions are computed [Mpc/h].
The radii corresponding to the masses m.
Mass density in haloes >m,
len=len(m)
[units \(M_\odot h^2 Mpc^{-3}\)]Mass density in haloes <m,
len=len(m)
[units \(M_\odot h^2 Mpc^{-3}\)]If True, r bins are logarithmically distributed.
Maximum length scale.
Minimum length scale.
Number of r bins.
The total fraction of tracers that are satellites.
The mean satellite occupation of the tracer as a function of halo mass.
A class containing relevant methods to calculate scale-dependent bias corrections.
Return the correction for scale dependancy of bias.
Model of Scale Dependant Bias.
Dictionary of parameters for Scale Dependant Bias.
The sqrt of the mass variance at z,
len=len(m)
.RMS linear density fluctuations in spheres of radius 8 Mpc/h
Whether to use updated HALOFIT coefficients from Takahashi+12.
The mean total occupation of the tracer as a function of halo mass.
The concentrations corresponding to
m()
.Concentration-mass relation model instance.
The tracer concentration-mass relation.
Dictionary of parameters for tracer concentration-mass relation.
Mean density of the tracer, ONLY if passed directly.
The total tracer density in halos of mass m.
The minimum halo mass of integrals over the tracer population.
Object to calculate quantities of the tracer profile.
The mass-normalised profile self-convolution of the tracer, shape (len(r), len(m)).
The tracer density halo_profile model.
Dictionary of parameters for the tracer Profile model.
The mass-normalised density profile of the tracer, with shape (len(r), len(m)).
The mass-normalised fourier density profile of the tracer, shape (len(k), len(m)).
The instantiated transfer model
Normalised CDM log transfer function.
Defines which transfer function model to use.
Relevant parameters of the transfer_model.
Redshift.