firecrown.models.cluster.mass_proxy
The mass richness kernel module.
This module holds the classes that define the mass richness relations that can be included in the cluster abundance integrand. These are implementations of Kernels.
Attributes
Classes
The representation of mass richness relations that are of a gaussian form. |
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The mass richness relation defined in Murata 19 for a binned data vector. |
|
The mass richness relation defined in Murata 19 for a unbinned data vector. |
Module Contents
- class firecrown.models.cluster.mass_proxy.MassRichnessGaussian(parameter_prefix=None)[source]
Bases:
firecrown.updatable.Updatable
The representation of mass richness relations that are of a gaussian form.
- Parameters:
parameter_prefix (None | str)
- static observed_value(p, mass, z, pivot_mass, log1p_pivot_redshift)[source]
Return observed quantity corrected by redshift and mass.
- Parameters:
p (tuple[float, float, float])
mass (numpy.typing.NDArray[numpy.float64])
z (numpy.typing.NDArray[numpy.float64])
pivot_mass (float)
log1p_pivot_redshift (float)
- Return type:
numpy.typing.NDArray[numpy.float64]
- firecrown.models.cluster.mass_proxy.MURATA_DEFAULT_MU_P0 = 3.0
- firecrown.models.cluster.mass_proxy.MURATA_DEFAULT_MU_P1 = 0.8
- firecrown.models.cluster.mass_proxy.MURATA_DEFAULT_MU_P2 = -0.3
- firecrown.models.cluster.mass_proxy.MURATA_DEFAULT_SIGMA_P0 = 0.3
- firecrown.models.cluster.mass_proxy.MURATA_DEFAULT_SIGMA_P1 = 0.0
- firecrown.models.cluster.mass_proxy.MURATA_DEFAULT_SIGMA_P2 = 0.0
- class firecrown.models.cluster.mass_proxy.MurataBinned(pivot_mass, pivot_redshift)[source]
Bases:
MassRichnessGaussian
The mass richness relation defined in Murata 19 for a binned data vector.
- Parameters:
pivot_mass (float)
pivot_redshift (float)
- pivot_redshift
- pivot_mass
- log1p_pivot_redshift
- mu_p0
- mu_p1
- mu_p2
- sigma_p0
- sigma_p1
- sigma_p2
- get_proxy_mean(mass, z)[source]
Return observed quantity corrected by redshift and mass.
- Parameters:
mass (numpy.typing.NDArray[numpy.float64])
z (numpy.typing.NDArray[numpy.float64])
- Return type:
numpy.typing.NDArray[numpy.float64]
- get_proxy_sigma(mass, z)[source]
Return observed scatter corrected by redshift and mass.
- Parameters:
mass (numpy.typing.NDArray[numpy.float64])
z (numpy.typing.NDArray[numpy.float64])
- Return type:
numpy.typing.NDArray[numpy.float64]
- distribution(mass, z, mass_proxy_limits)[source]
Evaluates and returns the mass-richness contribution to the integrand.
- Parameters:
mass (numpy.typing.NDArray[numpy.float64])
z (numpy.typing.NDArray[numpy.float64])
mass_proxy_limits (tuple[float, float])
- Return type:
numpy.typing.NDArray[numpy.float64]
- class firecrown.models.cluster.mass_proxy.MurataUnbinned(pivot_mass, pivot_redshift)[source]
Bases:
MassRichnessGaussian
The mass richness relation defined in Murata 19 for a unbinned data vector.
- Parameters:
pivot_mass (float)
pivot_redshift (float)
- pivot_redshift
- pivot_mass
- log1p_pivot_redshift
- mu_p0
- mu_p1
- mu_p2
- sigma_p0
- sigma_p1
- sigma_p2
- get_proxy_mean(mass, z)[source]
Return observed quantity corrected by redshift and mass.
- Parameters:
mass (numpy.typing.NDArray[numpy.float64])
z (numpy.typing.NDArray[numpy.float64])
- Return type:
numpy.typing.NDArray[numpy.float64]
- get_proxy_sigma(mass, z)[source]
Return observed scatter corrected by redshift and mass.
- Parameters:
mass (numpy.typing.NDArray[numpy.float64])
z (numpy.typing.NDArray[numpy.float64])
- Return type:
numpy.typing.NDArray[numpy.float64]
- distribution(mass, z, mass_proxy)[source]
Evaluates and returns the mass-richness contribution to the integrand.
- Parameters:
mass (numpy.typing.NDArray[numpy.float64])
z (numpy.typing.NDArray[numpy.float64])
mass_proxy (numpy.typing.NDArray[numpy.float64])
- Return type:
numpy.typing.NDArray[numpy.float64]