BaseFittingFunction

class hmf.mass_function.fitting_functions.BaseFittingFunction(nu2: ndarray, m: None | ndarray = None, z: float = 0.0, n_eff: None | ndarray = None, mass_definition: None | BaseMassDefinition = None, cosmo: FLRW = FlatLambdaCDM(name='Planck15', H0=<Quantity 67.74 km / (Mpc s)>, Om0=0.3075, Tcmb0=<Quantity 2.7255 K>, Neff=3.046, m_nu=<Quantity [0., 0., 0.06] eV>, Ob0=0.0486), delta_c: float = 1.68647, **model_parameters)

Base-class for a halo mass function fit.

This class should not be called directly, rather use a subclass which is specific to a certain fitting formula. The only method necessary to define for any subclass is fsigma, as well as a dictionary of default parameters as a class variable _defaults. Model parameters defined here are accessed through the params instance attribute (and may be overridden at instantiation by the user). A subclass may optionally define a cutmask property, to override the default behaviour of returning True for the whole range.

In addition, several class attributes, req_*, identify the required arguments for a given subclass. These must be set accordingly.

Examples

The following would be an example of defining the Sheth-Tormen mass function (which is already included), showing the basic idea of subclassing this class:

>>> class SMT(FittingFunction):
>>>     # Subclass requirements
>>>     req_sigma = False
>>>     req_z     = False
>>>
>>>     # Default parameters
>>>     _defaults = {"a":0.707, "p":0.3, "A":0.3222}
>>>
>>>     @property
>>>     def fsigma(self):
>>>        A = self.params['A']
>>>        a = self.params["a"]
>>>        p = self.params['p']
>>>
>>>        return (A * np.sqrt(2.0 * a / np.pi) * self.nu *
>>>               np.exp(-(a * self.nu2) / 2.0)
>>>               * (1 + (1.0 / (a * self.nu2)) ** p))

In that example, we did not specify cutmask.

Parameters:

nu2array_like

A vector of peak-heights, \(\delta_c^2/\sigma^2\) corresponding to m

marray_like, optional

A vector of halo masses [units M_sun/h]. Only necessary if req_mass is True. Typically provides limits of applicability. Must correspond to nu2.

zfloat, optional

The redshift. Only required if req_z is True, in which case the default is 0.

n_effarray_like, optional

The effective spectral index at m. Only required if req_neff is True.

mass_definitionhmf.halos.mass_definitions.MassDefinition instance

A halo mass definition. Only required for fits which explicitly include a parameterization for halo definition.

cosmoastropy.cosmology.FLRW instance, optional

A cosmology. Default is Planck15. Either omegam_z or cosmo is required if req_omz is True. If both are passed, omegam_z takes precedence.

**model_parametersunpacked-dictionary

These parameters are model-specific. For any model, list the available parameters (and their defaults) using <model>._defaults

Attributes

Methods

__init__(nu2: ndarray, m: None | ndarray = None, z: float = 0.0, n_eff: None | ndarray = None, mass_definition: None | BaseMassDefinition = None, cosmo: FLRW = FlatLambdaCDM(name='Planck15', H0=<Quantity 67.74 km / (Mpc s)>, Om0=0.3075, Tcmb0=<Quantity 2.7255 K>, Neff=3.046, m_nu=<Quantity [0., 0., 0.06] eV>, Ob0=0.0486), delta_c: float = 1.68647, **model_parameters)

classmethod get_measured_mdef()

Get the mass definition used in the defining simulation.

classmethod get_models() → dict[str, type]

Get a dictionary of all implemented models for this component.