gwkokab.analysis.n_pls_m_gs.discrete
====================================

.. py:module:: gwkokab.analysis.n_pls_m_gs.discrete


Classes
-------

.. autoapisummary::

   gwkokab.analysis.n_pls_m_gs.discrete.NPowerlawMGaussianDiscreteAnalysis
   gwkokab.analysis.n_pls_m_gs.discrete.NPowerlawMGaussianFDiscreteAnalysis
   gwkokab.analysis.n_pls_m_gs.discrete.NPowerlawMGaussianNDiscreteAnalysis


Functions
---------

.. autoapisummary::

   gwkokab.analysis.n_pls_m_gs.discrete.main


Module Contents
---------------

.. py:class:: NPowerlawMGaussianDiscreteAnalysis(N_pl: int, N_g: int, use_beta_spin_magnitude: bool, use_spin_magnitude_mixture: bool, use_truncated_normal_spin_x: bool, use_truncated_normal_spin_y: bool, use_truncated_normal_spin_z: bool, use_chi_eff_mixture: bool, use_skew_normal_chi_eff: bool, use_truncated_normal_chi_p: bool, use_tilt: bool, use_eccentricity_mixture: bool, use_eccentricity_powerlaw: bool, use_powerlaw_redshift: bool, use_madau_dickinson_redshift: bool, use_cos_iota: bool, use_phi_12: bool, use_polarization_angle: bool, use_right_ascension: bool, use_sin_declination: bool, use_detection_time: bool, use_phi_1: bool, use_phi_2: bool, use_phi_orb: bool, use_mean_anomaly: bool, likelihood_fn: Callable[Ellipsis, Callable], data_loader: gwkokab.analysis.core.inference_io.DiscretePELoader, prior_filename: str, poisson_mean_filename: str, sampler_cfg, variance_cut_threshold: float | None, n_buckets: int, threshold: float, debug_nans: bool = False, profile_memory: bool = False, check_leaks: bool = False)

   Bases: :py:obj:`gwkokab.analysis.n_pls_m_gs.common.NPowerlawMGaussianCore`, :py:obj:`gwkokab.analysis.core.discrete_base.DiscreteBase`


   AnalysisBase is a class which contains all the common functionality among the
   different analyses.

   It is not meant to be used directly, but rather to be subclassed by the specific
   analyses.


.. py:class:: NPowerlawMGaussianFDiscreteAnalysis(N_pl: int, N_g: int, use_beta_spin_magnitude: bool, use_spin_magnitude_mixture: bool, use_truncated_normal_spin_x: bool, use_truncated_normal_spin_y: bool, use_truncated_normal_spin_z: bool, use_chi_eff_mixture: bool, use_skew_normal_chi_eff: bool, use_truncated_normal_chi_p: bool, use_tilt: bool, use_eccentricity_mixture: bool, use_eccentricity_powerlaw: bool, use_powerlaw_redshift: bool, use_madau_dickinson_redshift: bool, use_cos_iota: bool, use_phi_12: bool, use_polarization_angle: bool, use_right_ascension: bool, use_sin_declination: bool, use_detection_time: bool, use_phi_1: bool, use_phi_2: bool, use_phi_orb: bool, use_mean_anomaly: bool, likelihood_fn: Callable[Ellipsis, Callable], data_loader: gwkokab.analysis.core.inference_io.DiscretePELoader, prior_filename: str, poisson_mean_filename: str, sampler_cfg, variance_cut_threshold: float | None, n_buckets: int, threshold: float, debug_nans: bool = False, profile_memory: bool = False, check_leaks: bool = False)

   Bases: :py:obj:`NPowerlawMGaussianDiscreteAnalysis`, :py:obj:`gwkokab.analysis.core.flowMC_base.FlowMCBase`


   AnalysisBase is a class which contains all the common functionality among the
   different analyses.

   It is not meant to be used directly, but rather to be subclassed by the specific
   analyses.


.. py:class:: NPowerlawMGaussianNDiscreteAnalysis(N_pl: int, N_g: int, use_beta_spin_magnitude: bool, use_spin_magnitude_mixture: bool, use_truncated_normal_spin_x: bool, use_truncated_normal_spin_y: bool, use_truncated_normal_spin_z: bool, use_chi_eff_mixture: bool, use_skew_normal_chi_eff: bool, use_truncated_normal_chi_p: bool, use_tilt: bool, use_eccentricity_mixture: bool, use_eccentricity_powerlaw: bool, use_powerlaw_redshift: bool, use_madau_dickinson_redshift: bool, use_cos_iota: bool, use_phi_12: bool, use_polarization_angle: bool, use_right_ascension: bool, use_sin_declination: bool, use_detection_time: bool, use_phi_1: bool, use_phi_2: bool, use_phi_orb: bool, use_mean_anomaly: bool, likelihood_fn: Callable[Ellipsis, Callable], data_loader: gwkokab.analysis.core.inference_io.DiscretePELoader, prior_filename: str, poisson_mean_filename: str, sampler_cfg, variance_cut_threshold: float | None, n_buckets: int, threshold: float, debug_nans: bool = False, profile_memory: bool = False, check_leaks: bool = False)

   Bases: :py:obj:`NPowerlawMGaussianDiscreteAnalysis`, :py:obj:`gwkokab.analysis.core.numpyro_base.NumpyroBase`


   AnalysisBase is a class which contains all the common functionality among the
   different analyses.

   It is not meant to be used directly, but rather to be subclassed by the specific
   analyses.


.. py:function:: main() -> None