gwkokab.poisson_mean
====================

.. py:module:: gwkokab.poisson_mean


Functions
---------

.. autoapisummary::

   gwkokab.poisson_mean.poisson_mean_from_neural_pdet
   gwkokab.poisson_mean.poisson_mean_from_neural_vt
   gwkokab.poisson_mean.poisson_mean_from_sensitivity_injections


Package Contents
----------------

.. py:function:: poisson_mean_from_neural_pdet(key: jaxtyping.PRNGKeyArray, parameters: collections.abc.Sequence[str], filename: str, batch_size: Optional[int] = None, num_samples: int = 1000, time_scale: Union[int, float, jaxtyping.Array] = 1.0) -> Tuple[Optional[collections.abc.Callable[[jaxtyping.Array], jaxtyping.Array]], collections.abc.Callable[Ellipsis, jaxtyping.Array], dict[str, Any]]

.. py:function:: poisson_mean_from_neural_vt(key: jaxtyping.PRNGKeyArray, parameters: collections.abc.Sequence[str], filename: str, batch_size: Optional[int] = None, num_samples: int = 1000, time_scale: Union[int, float, jaxtyping.Array] = 1.0) -> Tuple[Optional[collections.abc.Callable[[jaxtyping.Array], jaxtyping.Array]], collections.abc.Callable[Ellipsis, jaxtyping.Array], dict[str, Any]]

.. py:function:: poisson_mean_from_sensitivity_injections(key: jaxtyping.PRNGKeyArray, parameters: List[str], filename: str, batch_size: Optional[int] = None, far_cut: float = 1.0, snr_cut: float = 10.0) -> Tuple[Optional[collections.abc.Callable[[jaxtyping.Array], jaxtyping.Array]], collections.abc.Callable[Ellipsis, jaxtyping.Array], dict[str, Any]]