reggae.theta
============

.. py:module:: reggae.theta

.. autoapi-nested-parse::

   Rather than pass around raw numpy arrays, Reggae uses
   dataclass objects to characterise the various θ parameters
   entering into the model. One is for the background & asymptotic
   p-mode parameters (θ_asy) inherited from pbjam, and one is for
   the dipole modes (θ_reggae) which Reggae as a tool is intended
   to assist in fitting.



Classes
-------

.. autoapisummary::

   reggae.theta.ThetaReg
   reggae.theta.ThetaAsy
   reggae.theta.ThetaBkg
   reggae.theta.ThetaObs


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

.. py:class:: ThetaReg

   Parameters for Reggae (asymptotic description of l = 1 modes)

   If theta is a numpy array, generate an instance as
   theta = ThetaReg(*θ)


   .. py:attribute:: dPi0
      :type:  float


   .. py:attribute:: p_L
      :type:  float


   .. py:attribute:: p_D
      :type:  float


   .. py:attribute:: epsilon_g
      :type:  float


   .. py:attribute:: log_omega_core
      :type:  float


   .. py:attribute:: d01
      :type:  float


   .. py:attribute:: alpha_g
      :type:  float


   .. py:attribute:: inclination
      :type:  float


   .. py:attribute:: log_omega_env
      :type:  float


   .. py:attribute:: dims
      :value: 9



   .. py:method:: asarray()


   .. py:attribute:: bounds


   .. py:attribute:: normalisation
      :value: 1



   .. py:attribute:: beta12


   .. py:attribute:: normal


   .. py:method:: prior_transform(u, bounds=None)
      :staticmethod:


      Prior transform for inverse sampling

      Evaluates the ppf (quantile function) given a set of quantile values u
      drawn from the n-dimensional hypercube. 

      Parameters
      ----------
      u : np.array
          Array of values between 0 and 1 drawn uniformly from the 
          n-dimensional hypercube.
      bounds : np.array
          Array of bounds for the distributions in case they need to be
          truncated.



   .. py:method:: inv_prior_transform(θ, bounds=None)
      :staticmethod:


      Inverse prior transform

      Evaluates the point u in the unit hypercube associated with an array
      of values describing a θ_reg object.

      Parameters
      ----------
      θ : np.array
          Array of values for the fields of θ_reg.
      bounds : np.array
          Array of bounds for the distributions in case they need to be
          truncated.



.. py:class:: ThetaAsy

   Parameters for the asymptotic description of l = 0,2 modes
       


   .. py:attribute:: log_numax
      :type:  float


   .. py:attribute:: log_dnu
      :type:  float


   .. py:attribute:: eps
      :type:  float


   .. py:attribute:: log_d02
      :type:  float


   .. py:attribute:: log_alpha
      :type:  float


   .. py:attribute:: log_hmax
      :type:  float


   .. py:attribute:: log_env_width
      :type:  float


   .. py:attribute:: log_mode_width
      :type:  float


   .. py:attribute:: dims
      :value: 8



   .. py:method:: nmax()

      Compute nmax



   .. py:method:: n_p(n_orders)

      Build array of radial orders



   .. py:method:: nu_0(n_orders)

      Compute frequencies of the radial orders



   .. py:method:: asarray()


.. py:class:: ThetaBkg

   Parameters for the Harvey-like background terms of the model
       


   .. py:attribute:: hsig1
      :type:  float


   .. py:attribute:: dhnu1
      :type:  float


   .. py:attribute:: exp1
      :type:  float


   .. py:attribute:: hsig2
      :type:  float


   .. py:attribute:: dhnu2
      :type:  float


   .. py:attribute:: exp2
      :type:  float


   .. py:attribute:: hsig3
      :type:  float


   .. py:attribute:: hnu3
      :type:  float


   .. py:attribute:: exp3
      :type:  float


   .. py:attribute:: white
      :type:  float


   .. py:attribute:: dims
      :value: 10



   .. py:method:: asarray()


.. py:class:: ThetaObs

   Parameters to compare with additional observational parameters
       


   .. py:attribute:: Teff
      :type:  float


   .. py:attribute:: bprp
      :type:  float


   .. py:attribute:: dims
      :value: 2