gwkokab.analysis.core.synthetic_events ====================================== .. py:module:: gwkokab.analysis.core.synthetic_events Classes ------- .. autoapisummary:: gwkokab.analysis.core.synthetic_events.SyntheticEventsBase Functions --------- .. autoapisummary:: gwkokab.analysis.core.synthetic_events.injection_generator_parser Module Contents --------------- .. py:class:: 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: :py:obj:`gwkokab.analysis.core.utils.PRNGKeyMixin`, :py:obj:`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. .. py:method:: from_inverse_transform_sampling() -> None .. py:method:: modify_model_params(params: dict) -> dict Hook for subclasses to modify parameters before model instantiation. .. py:method:: 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 .. py:attribute:: derive_parameters :value: False .. py:attribute:: filename .. py:attribute:: model_fn .. py:property:: model_parameters :type: list[str] :abstractmethod: Returns the model parameters. :returns: list of model parameters. :rtype: list[str] .. py:attribute:: model_params .. py:attribute:: n_buffer_events .. py:property:: parameters :type: tuple[str, Ellipsis] :abstractmethod: Returns the parameters (intrinsic + extrinsic). :returns: list of parameters. :rtype: tuple[str, ...] .. py:attribute:: poisson_mean_filename .. py:function:: injection_generator_parser() -> argparse.ArgumentParser