crow.cluster_modules.mass_proxy.gaussian_protocol module

Gaussian class for mass richness distributiosn.

class crow.cluster_modules.mass_proxy.gaussian_protocol.MassRichnessGaussian

Bases: object

Base class for Gaussian mass–richness relations.

This class defines the interface and common utilities for models where the observable mass proxy follows a Gaussian distribution in log-space, conditioned on halo mass and redshift.

gaussian_kernel(log_mass: ndarray[tuple[Any, ...], dtype[float64]], z: ndarray[tuple[Any, ...], dtype[float64]], log_mass_proxy: ndarray[tuple[Any, ...], dtype[float64]]) → ndarray[tuple[Any, ...], dtype[float64]]

Evaluate the Gaussian probability density function.

Parameters:

• log_mass (ndarray of float64) -- Logarithm (base 10) of halo mass.

• z (ndarray of float64) -- Redshift values.

• log_mass_proxy (ndarray of float64) -- Logarithm (base 10) of the observed mass proxy.

Returns:

Value of the Gaussian PDF evaluated at the given inputs.

Return type:

ndarray of float64

abstractmethod get_ln_mass_proxy_mean(log_mass: ndarray[tuple[Any, ...], dtype[float64]], z: ndarray[tuple[Any, ...], dtype[float64]]) → ndarray[tuple[Any, ...], dtype[float64]]

Base class for Gaussian mass–richness relations.

This class defines the interface and common utilities for models where the observable mass proxy follows a Gaussian distribution in log-space, conditioned on halo mass and redshift.

abstractmethod get_ln_mass_proxy_sigma(log_mass: ndarray[tuple[Any, ...], dtype[float64]], z: ndarray[tuple[Any, ...], dtype[float64]]) → ndarray[tuple[Any, ...], dtype[float64]]

Base class for Gaussian mass–richness relations.

This class defines the interface and common utilities for models where the observable mass proxy follows a Gaussian distribution in log-space, conditioned on halo mass and redshift.

integrated_gaussian(log_mass: ndarray[tuple[Any, ...], dtype[float64]], z: ndarray[tuple[Any, ...], dtype[float64]], log_mass_proxy_limits: tuple[float, float]) → ndarray[tuple[Any, ...], dtype[float64]]

Compute the integrated Gaussian probability within given bounds.

This evaluates the integral of the Gaussian distribution between two limits in log10 space of the mass proxy.

Parameters:

• log_mass (ndarray of float64) -- Logarithm (base 10) of halo mass.

• z (ndarray of float64) -- Redshift values.

• log_mass_proxy_limits (tuple of float) -- Lower and upper bounds in log10 space.

Returns:

Integrated probability within the specified bounds.

Return type:

ndarray of float64