reggae
======

.. py:module:: reggae


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/reggae/__main__/index
   /autoapi/reggae/asymptotic/index
   /autoapi/reggae/dipolestar/index
   /autoapi/reggae/psdmodel/index
   /autoapi/reggae/qtconsole/index
   /autoapi/reggae/reggae/index
   /autoapi/reggae/theta/index
   /autoapi/reggae/utils/index
   /autoapi/reggae/version/index


Classes
-------

.. autoapisummary::

   reggae.DipoleStar


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

.. py:class:: DipoleStar(s=None, f=None)

   Generalisation of pbjam.star to assist in determination of dipole mixed-mode
   parameters.


   .. py:attribute:: labels
      :value: ['$\\Delta\\Pi_0$ (relative)', '$L_0$', '$D_0$', '$\\epsilon_g$', '$\\log...



   .. py:attribute:: _extra_ndims
      :value: 1



   .. py:attribute:: _psd_model


   .. py:attribute:: s
      :value: None



   .. py:attribute:: f
      :value: None



   .. py:method:: from_pbjam(star)
      :classmethod:


      Import and prepare results from PBjam

      Takes instances of the either the pbjam.star or pbjam.modeID.modeIDsampler 
      classes and constructs a residual spectrum, by dividing out the l=2,0 (including
      the background) or just the background respectively.

      Parameters
      ----------
      klass: self
          reggae.DipoleStar class self.
      star: object
          Instance of pbjam.star or pbjam.modeID.modeIDsampler classes. 



   .. py:method:: __call__(dynamic=False, **kwargs)


   .. py:method:: summarise(sampler=None)


   .. py:method:: ptform(u)

      Turns coordinates on the unit cube into θ_reg object

      Parameters
      ----------
      u: list
          Point location in the unit hypercube.

      Returns
      -------
      x: jnp.array
          Point location in model parameter space.



   .. py:method:: inv_ptform(θ_reg, norm)

      Turns θ_reg object into coordinates on the unit cube

      Parameters
      ----------
      θ_reg: ThetaReg object or array-like
          Point location in model parameters space.
      norm: jnp.array
          Normalisation

      Returns: jnp.array
          Point location in the unit hypercube.



   .. py:method:: model(theta)

      Construct the model for the likelihood evaluation

      Parameters
      ----------
      theta: jnp.array
          Array of model parameters.

      Returns
      -------
      mod: jnp.array
          Spectrum model.



   .. py:method:: ln_like(theta)

      Evaluate the model log-likelihood at theta

      The log-likelihood is the joint probability of observing
      the spectrum given the model.

      Parameters
      ----------
      theta: jnp.array
          Array of model parameters

      Returns
      -------
      lnlike: float
          log-likelihood at theta.



   .. py:method:: get_bounds()

      Set bounds for model parameter priors.

      Returns
      -------
      bounds: list
          List of bounds.



   .. py:method:: select_n_g()

      Select the relevant radial g-mode orders

      Based on prior estimates of the relevant range period spacing and 
      eps_g, computes g-modes that significantly overlap with the envelope.

      These will be used to compute the model.

      Returns
      -------
      n_g: jnp.array
          List of radial orders for the g-modes.



   .. py:method:: _prepare_theta_asy(star)
      :staticmethod:


      Get parameters for asymptotic l=2,0+background model.

      Parameters
      ----------
      star: object
          Either a pbjam.star or pbjam.modeID.modeIDsampler class instance.

      Returns
      -------
      nu_0: jnp.array
          l=0 mode frequencies.
      nu_2: jnp.array
          l=2 mode frequencies.
      ThetaAsy: object
          ThetaAsy class instance, containing l=2,0 and background model parameters.



   .. py:method:: make_pbjam_model(star, n_samples=50)
      :staticmethod:


      Construct a spectrum model from PBjam output

      Takes either a pbjam.star or pbjam.modeID.modeIDsampler object from a previous
      PBjam run. This is used to construct a residual spectrum.

      In the case of a pbjam.star object being passed, a set of models are drawn
      and averaged.

      Parameters
      ----------
      star: object
          Either a pbjam.star or pbjam.modeID.modeIDsampler object.
      n_samples: int, optional
          Number of samples to use to construct the mean model. Default is 50.

      Returns
      -------
      mod: jnp.array
          Spectrum model.



   .. py:method:: simplex(theta_reg, norm, **kwargs)

      Find maximum log-likelihood using Nelder-Mead downhill simplex minimization.

      Parameters
      ----------
      theta_reg: dataclass
          A ThetaReg dataclass instance
      norm: jnp.array
          An initial point in model parameter space.



   .. py:method:: genetic_algorithm(solve_kwargs=None, **kwargs)

      Find the maximum likelihood using a genetic algorithm.

      Any keyword arguments are passed to the yabox.DE initializatoin.

      solve_kwarg: dict, optional
          Dictionary of argumentts to pass to the yabox.DE.solve method.