firecrown.models.cluster.mass_proxy.MurataBinned

class firecrown.models.cluster.mass_proxy.MurataBinned(pivot_mass, pivot_redshift)

Bases: MassRichnessGaussian

The mass richness relation defined in Murata 19 for a binned data vector.

Parameters:

• pivot_mass (float) –

• pivot_redshift (float) –

Public Methods:

__init__(pivot_mass, pivot_redshift)	Updatable initialization.
get_proxy_mean(mass, z)	Return observed quantity corrected by redshift and mass.
get_proxy_sigma(mass, z)	Return observed scatter corrected by redshift and mass.
distribution(mass, z, mass_proxy_limits)	Evaluates and returns the mass-richness contribution to the integrand.

Inherited from MassRichnessGaussian

observed_value(p, mass, z, pivot_mass, ...)	Return observed quantity corrected by redshift and mass.
get_proxy_mean(mass, z)	Return observed quantity corrected by redshift and mass.
get_proxy_sigma(mass, z)	Return observed scatter corrected by redshift and mass.

Inherited from Updatable

__init__([parameter_prefix])	Updatable initialization.
__setattr__(key, value)	Set the attribute named key to the supplied value.
set_parameter(key, value)	Sets the parameter to the given value.
set_internal_parameter(key, value)	Assure this InternalParameter has not already been set, and then set it.
set_sampler_parameter(value)	Assure this SamplerParameter has not already been set, and then set it.
update(params)	Update self by calling to prepare for the next MCMC sample.
is_updated()	Determine if the object has been updated.
reset()	Reset the updatable.
required_parameters()	Returns all information about parameters required by this object.
get_params_names()	Return the names of the parameters required by this object.
get_derived_parameters()	Returns a collection of derived parameters.

Private Methods:

Inherited from MassRichnessGaussian

_distribution_binned(mass, z, mass_proxy_limits)	param mass:
_distribution_unbinned(mass, z, mass_proxy)	param mass:

Inherited from Updatable

_update(params)	Method for auxiliary updates to be made to an updatable.
_reset()	Abstract method implemented by all concrete classes to update self.
_required_parameters()	Return a RequiredParameters object containing the information for this class.
_get_derived_parameters()	Returns the derived parameters of an implementation.

---

distribution(mass, z, mass_proxy_limits)

Evaluates and returns the mass-richness contribution to the integrand.

Parameters:

• mass (ndarray[tuple[int, ...], dtype[float64]]) –

• z (ndarray[tuple[int, ...], dtype[float64]]) –

• mass_proxy_limits (tuple[float, float]) –

Return type:

ndarray[tuple[int, ...], dtype[float64]]

get_proxy_mean(mass, z)

Return observed quantity corrected by redshift and mass.

Parameters:

• mass (ndarray[tuple[int, ...], dtype[float64]]) –

• z (ndarray[tuple[int, ...], dtype[float64]]) –

Return type:

ndarray[tuple[int, ...], dtype[float64]]

get_proxy_sigma(mass, z)

Return observed scatter corrected by redshift and mass.

Parameters:

• mass (ndarray[tuple[int, ...], dtype[float64]]) –

• z (ndarray[tuple[int, ...], dtype[float64]]) –

Return type:

ndarray[tuple[int, ...], dtype[float64]]