firecrown.likelihood.number_counts

Number counts source and systematics.

Classes

NumberCounts	Source class for number counts.
NumberCountsFactory	Factory class for NumberCounts objects.
ConstantMagnificationBiasSystematic	Simple constant magnification bias systematic.
MagnificationBiasSystematic	Magnification bias systematic.
PhotoZShift	Photo-z shift systematic.
PTNonLinearBiasSystematic	Non-linear bias systematic.

Package Contents

class firecrown.likelihood.number_counts.NumberCounts(*, sacc_tracer, has_rsd=False, derived_scale=False, scale=1.0, systematics=None)

Bases: firecrown.likelihood._base.SourceGalaxy[firecrown.likelihood.number_counts._args.NumberCountsArgs]

Source class for number counts.

Parameters:

• sacc_tracer (str)

• has_rsd (bool)

• derived_scale (bool)

• scale (float)

• systematics (None | collections.abc.Sequence[firecrown.likelihood._base.SourceGalaxySystematic[firecrown.likelihood.number_counts._args.NumberCountsArgs]])

sacc_tracer

has_rsd = False

derived_scale = False

bias

systematics: firecrown.updatable.UpdatableCollection[firecrown.likelihood._base.SourceGalaxySystematic[firecrown.likelihood.number_counts._args.NumberCountsArgs]]

scale = 1.0

current_tracer_args: None | firecrown.likelihood.number_counts._args.NumberCountsArgs = None

tracer_args: firecrown.likelihood.number_counts._args.NumberCountsArgs

classmethod create_ready(inferred_zdist, has_rsd=False, derived_scale=False, scale=1.0, systematics=None)

Create a NumberCounts object with the given tracer name and scale.

This is the recommended way to create a NumberCounts object. It creates a fully initialized object.

Parameters:

• inferred_zdist (firecrown.metadata_types.InferredGalaxyZDist) – the inferred redshift distribution

• has_rsd (bool) – whether to include RSD in the tracer

• derived_scale (bool) – whether to include a derived parameter for the scale of the tracer

• scale (float) – the initial scale of the tracer

• systematics (None | list[firecrown.likelihood._base.SourceGalaxySystematic[firecrown.likelihood.number_counts._args.NumberCountsArgs]]) – a list of systematics to apply to the tracer

Returns:

a fully initialized NumberCounts object

Return type:

NumberCounts

create_tracers(tools)

Create the tracers for this source.

Parameters:

tools (firecrown.modeling_tools.ModelingTools) – the ModelingTools used to create the tracers

Returns:

a tuple of tracers and the updated tracer_args

Return type:

tuple[list[firecrown.likelihood._base.Tracer], firecrown.likelihood.number_counts._args.NumberCountsArgs]

get_scale()

Return the scale for this source.

Returns:

the scale for this source.

Return type:

float

class firecrown.likelihood.number_counts.NumberCountsFactory(/, **data)

Bases: pydantic.BaseModel

Factory class for NumberCounts objects.

Parameters:

data (Any)

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

type_source: firecrown.metadata_types.TypeSource

per_bin_systematics: collections.abc.Sequence[NumberCountsSystematicFactory] = None

global_systematics: collections.abc.Sequence[NumberCountsSystematicFactory] = None

include_rsd: bool = False

model_post_init(_, /)

Initialize the NumberCountsFactory.

Return type:

None

create(inferred_zdist)

Create a NumberCounts object with the given tracer name and scale.

Parameters:

inferred_zdist (firecrown.metadata_types.InferredGalaxyZDist) – the inferred redshift distribution

Returns:

a fully initialized NumberCounts object

Return type:

firecrown.likelihood.number_counts._source.NumberCounts

create_from_metadata_only(sacc_tracer)

Create an WeakLensing object with the given tracer name and scale.

Parameters:

sacc_tracer (str) – the name of the tracer

Returns:

a fully initialized NumberCounts object

Return type:

firecrown.likelihood.number_counts._source.NumberCounts

class firecrown.likelihood.number_counts.ConstantMagnificationBiasSystematic(sacc_tracer)

Bases: NumberCountsSystematic

Simple constant magnification bias systematic.

This systematic adds a constant magnification bias model for galaxy number contrast.

The following parameters are special Updatable parameters, which means that they can be updated by the sampler, sacc_tracer is going to be used as a prefix for the parameters:

Variables:

mag_bias – the magnification bias.

Parameters:

sacc_tracer (str)

mag_bias

apply(tools, tracer_arg)

Apply a constant magnification bias systematic.

Parameters:

• tools (firecrown.modeling_tools.ModelingTools) – currently unused, but required by interface

• tracer_arg (firecrown.likelihood.number_counts._args.NumberCountsArgs) – a NumberCountsArgs object with values to be updated

Returns:

an updated NumberCountsArgs object

Return type:

firecrown.likelihood.number_counts._args.NumberCountsArgs

class firecrown.likelihood.number_counts.MagnificationBiasSystematic(sacc_tracer)

Bases: NumberCountsSystematic

Magnification bias systematic.

This systematic adds a magnification bias model for galaxy number contrast following Joachimi & Bridle (2010), arXiv:0911.2454.

The following parameters are special Updatable parameters, which means that they can be updated by the sampler, sacc_tracer is going to be used as a prefix for the parameters:

Variables:

• r_lim – the limiting magnitude.

• sig_c – the intrinsic dispersion of the source redshift distribution.

• eta – the slope of the luminosity function.

• z_c – the characteristic redshift of the source distribution.

• z_m – the slope of the source redshift distribution.

Parameters:

sacc_tracer (str)

r_lim

sig_c

eta

z_c

z_m

apply(tools, tracer_arg)

Apply a magnification bias systematic.

Parameters:

• tools (firecrown.modeling_tools.ModelingTools) – currently unused, but required by the interface

• tracer_arg (firecrown.likelihood.number_counts._args.NumberCountsArgs) – a NumberCountsArgs object with values to be updated

Returns:

an updated NumberCountsArgs object

Return type:

firecrown.likelihood.number_counts._args.NumberCountsArgs

class firecrown.likelihood.number_counts.PhotoZShift(sacc_tracer, active=True)

Bases: firecrown.likelihood._base.SourceGalaxyPhotoZShift[firecrown.likelihood.number_counts._args.NumberCountsArgs]

Photo-z shift systematic.

Parameters:

• sacc_tracer (str)

• active (bool)

class firecrown.likelihood.number_counts.PTNonLinearBiasSystematic(sacc_tracer=None)

Bases: NumberCountsSystematic

Non-linear bias systematic.

This systematic adds a linear bias model which varies with redshift and the growth function.

The following parameters are special Updatable parameters, which means that they can be updated by the sampler, sacc_tracer is going to be used as a prefix for the parameters:

Variables:

• b_2 – the quadratic bias.

• b_s – the stochastic bias.

Parameters:

sacc_tracer (None | str)

b_2

b_s

apply(tools, tracer_arg)

Apply a non-linear bias systematic.

Parameters:

• tools (firecrown.modeling_tools.ModelingTools) – currently unused, but required by interface

• tracer_arg (firecrown.likelihood.number_counts._args.NumberCountsArgs) – a NumberCountsArgs object with values to be updated

Returns:

the updated NumberCountsArgs object

Return type:

firecrown.likelihood.number_counts._args.NumberCountsArgs