gwkokab.analysis.ecc_matters.common

Shared definitions for the eccentricity-matters analysis family.

The simplest of the four families: a single-component population whose masses follow the Wysocki2019MassModel and whose eccentricity is a truncated normal. There are no component counts and no use_* flags – the parameter list is fixed – which makes it the natural family to read first when following how the analysis matrix fits together.

See : file:docs/source/examples/ecc_plus_spin/ for a complete worked run.

Classes

EccentricityMattersCore

Family half of the eccentricity-matters analysis.

Functions

EccentricityMattersModel(...)

Build the eccentricity-matters population model.

Module Contents

class gwkokab.analysis.ecc_matters.common.EccentricityMattersCore

Family half of the eccentricity-matters analysis.

Mixed with a data-representation base – DiscreteBase or AnalyticalGWalkBase – and a sampler mixin, to form a complete analysis.

model_fn

The population model factory, EccentricityMattersModel().

property model_parameters: List[str]

The flat list of population hyper-parameters to be inferred.

Fixed, since this family has no optional physical parameters. These names are what the regex keys of prior_cfg.json are matched against.

Returns:

Hyper-parameter names.

Return type:

List[str]

property parameters: Tuple[str, ...]

The event coordinates this analysis reads from the data.

Returns:

The two source-frame component masses and the eccentricity, in that order.

Return type:

Tuple[str, …]

gwkokab.analysis.ecc_matters.common.EccentricityMattersModel(log_rate: jaxtyping.Array, alpha_m: jaxtyping.Array, mmin: jaxtyping.Array, mmax: jaxtyping.Array, loc: jaxtyping.Array, scale: jaxtyping.Array, low: jaxtyping.Array, high: jaxtyping.Array, *, validate_args: bool | None = None) → gwkokab.models.utils.ScaledMixture

Build the eccentricity-matters population model.

A single-component ScaledMixture whose one component is the product of a Wysocki2019MassModel over the two masses – a truncated power law on \(m_1\), with \(m_2\) uniform between \(m_{\text{min}}\) and \(m_1\) – and a truncated normal over eccentricity.

Parameters:

• log_rate (Array) – Log merger rate of the population, in natural logarithm.

• alpha_m (Array) – Power law index of the primary mass.

• mmin (Array) – Minimum mass.

• mmax (Array) – Maximum mass.

• loc (Array) – Location of the eccentricity distribution.

• scale (Array) – Scale of the eccentricity distribution.

• low (Array) – Lower truncation of the eccentricity distribution.

• high (Array) – Upper truncation of the eccentricity distribution.

• validate_args (Optional[bool], optional) – Whether to validate distribution parameters and inputs. Defaults to None.

Returns:

The population model, over \((m_1, m_2, \varepsilon)\).

Return type:

ScaledMixture