gwkokab.analysis.core.synthetic_events

Classes

SyntheticEventsBase

Mixin class that provides a random number generator key and seed management for

Functions

injection_generator_parser(→ argparse.ArgumentParser)

Module Contents

class gwkokab.analysis.core.synthetic_events.SyntheticEventsBase(filename: str, model_fn: collections.abc.Callable[Ellipsis, gwkokab.models.utils.ScaledMixture], model_params_filename: str, poisson_mean_filename: str, n_buffer_events: int, derive_parameters: bool = False)

Bases: gwkokab.analysis.core.utils.PRNGKeyMixin, abc.ABC

Mixin class that provides a random number generator key and seed management for classes that require random number generation.

This mixin allows classes to initialize a random key based on a seed and provides a property to access the current random key, which is automatically split to ensure independent random streams across different parts of the code.

from_inverse_transform_sampling() → None

modify_model_params(params: dict) → dict

Hook for subclasses to modify parameters before model instantiation.

save_population(population: numpy.ndarray, indices: numpy.ndarray, buffer_population: numpy.ndarray, buffer_indices: numpy.ndarray, resample_idx: numpy.ndarray, resample_prob: numpy.ndarray) → None

derive_parameters = False

filename

model_fn

property model_parameters: list[str]

Abstractmethod:

Returns the model parameters.

Returns:

list of model parameters.

Return type:

list[str]

model_params

n_buffer_events

property parameters: tuple[str, Ellipsis]

Abstractmethod:

Returns the parameters (intrinsic + extrinsic).

Returns:

list of parameters.

Return type:

tuple[str, …]

poisson_mean_filename

gwkokab.analysis.core.synthetic_events.injection_generator_parser() → argparse.ArgumentParser