firecrown.models.cluster.kernel

The cluster kernel module.

This module holds the classes that define the kernels that can be included in the cluster abundance integrand.

Classes

KernelType

The kernels that can be included in the cluster abundance integrand.

Completeness

The completeness kernel for the numcosmo simulated survey.

Purity

The purity kernel for the numcosmo simulated survey.

TrueMass

The true mass kernel.

SpectroscopicRedshift

The spec-z kernel.

Module Contents

class firecrown.models.cluster.kernel.KernelType(*args, **kwds)[source]

Bases: enum.Enum

Inheritance diagram of firecrown.models.cluster.kernel.KernelType

The kernels that can be included in the cluster abundance integrand.

MASS = 1
Z = 2
MASS_PROXY = 3
Z_PROXY = 4
COMPLETENESS = 5
PURITY = 6
class firecrown.models.cluster.kernel.Completeness[source]

The completeness kernel for the numcosmo simulated survey.

This kernel will affect the integrand by accounting for the incompleteness of a cluster selection.

distribution(mass, z)[source]

Evaluates and returns the completeness contribution to the integrand.

Parameters:
  • mass (numpy.typing.NDArray[numpy.float64])

  • z (numpy.typing.NDArray[numpy.float64])

Return type:

numpy.typing.NDArray[numpy.float64]

class firecrown.models.cluster.kernel.Purity[source]

The purity kernel for the numcosmo simulated survey.

This kernel will affect the integrand by accounting for the purity of a cluster selection.

distribution(z, mass_proxy, mass_proxy_limits)[source]

Evaluates and returns the purity contribution to the integrand.

Parameters:
  • z (numpy.typing.NDArray[numpy.float64])

  • mass_proxy (numpy.typing.NDArray[numpy.float64])

  • mass_proxy_limits (tuple[float, float])

Return type:

numpy.typing.NDArray[numpy.float64]

class firecrown.models.cluster.kernel.TrueMass[source]

The true mass kernel.

Assuming we measure the true mass, this will always be 1.

distribution()[source]

Evaluates and returns the mass distribution contribution to the integrand.

We have set this to 1.0 (i.e. it does not affect the mass distribution)

Return type:

numpy.typing.NDArray[numpy.float64]

class firecrown.models.cluster.kernel.SpectroscopicRedshift[source]

The spec-z kernel.

Assuming the spectroscopic redshift has no uncertainties, this is akin to multiplying by 1.

distribution()[source]

Evaluates and returns the z distribution contribution to the integrand.

We have set this to 1.0 (i.e. it does not affect the redshift distribution)

Return type:

numpy.typing.NDArray[numpy.float64]