isofit.configs.sections.inversion_config
========================================

.. py:module:: isofit.configs.sections.inversion_config


Classes
-------

.. autoapisummary::

   isofit.configs.sections.inversion_config.InversionConfig
   isofit.configs.sections.inversion_config.McmcConfig
   isofit.configs.sections.inversion_config.LeastSquaresConfig


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

.. py:class:: InversionConfig(sub_configdic: dict = None)

   Bases: :py:obj:`isofit.configs.base_config.BaseConfigSection`


   Inversion configuration.


   .. py:attribute:: _windows_type
      :value: []



   .. py:attribute:: windows
      :value: None


      inversion retrieval windows to operate over.

      :type: List[List[float]]


   .. py:attribute:: _cressie_map_confidence_type


   .. py:attribute:: cressie_map_confidence
      :value: False


      



      N. Cressie [ASA 2018] suggests an alternate definition of S_hat for
      more statistically-consistent posterior confidence estimation, this flag runs in this mode

      :type: bool


   .. py:attribute:: _mcmc_type


   .. py:attribute:: mcmc

      MCMC parameters, only used if mode = mcmc.


   .. py:attribute:: _integration_grid_type


   .. py:attribute:: integration_grid

      Grid of inversion points to execute if mode='grid'.  Either fixed, or starting points, depending
      on self.fixed_inversion_grid


   .. py:attribute:: _priors_in_initial_guess_type


   .. py:attribute:: priors_in_initial_guess
      :value: True


      Boolean to inidicate the use of surface priors outside of the inversion windows during the
      intial guess.


   .. py:attribute:: _inversion_grid_as_preseed_type


   .. py:attribute:: inversion_grid_as_preseed
      :value: False


      Parameter indicating whether to treat the inversion grid as:
      (True) - a series of seeds for the optimization (variable by the optimization algorithm).
      (False) - a set of fixed points (not variable by the optimization algorithm)


   .. py:attribute:: _least_squares_params_type


   .. py:attribute:: least_squares_params

      Least squares parameters for core inversion solve.
      See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.least_squares.html
      for details.


   .. py:method:: _check_config_validity() -> List[str]


.. py:class:: McmcConfig(sub_configdic: dict = None)

   Bases: :py:obj:`isofit.configs.base_config.BaseConfigSection`


   MCMC inversion configuration.


   .. py:attribute:: _iterations_type


   .. py:attribute:: iterations
      :value: 10000


      Number of MCMC iterations to run.

      :type: int


   .. py:attribute:: _burnin_type


   .. py:attribute:: burnin
      :value: 200



   .. py:attribute:: _regularizer_type


   .. py:attribute:: regularizer
      :value: 0.001



   .. py:attribute:: _proposal_scaling_type


   .. py:attribute:: proposal_scaling
      :value: 0.01



   .. py:attribute:: _verbose_type


   .. py:attribute:: verbose
      :value: True



   .. py:attribute:: _restart_every_type


   .. py:attribute:: restart_every
      :value: 2000



   .. py:method:: _check_config_validity() -> List[str]


.. py:class:: LeastSquaresConfig(sub_configdic: dict = None)

   Bases: :py:obj:`isofit.configs.base_config.BaseConfigSection`


   Least squares config parameters.


   .. py:attribute:: _method_type


   .. py:attribute:: method
      :value: 'trf'


      Optimzation method to use. Default 'trf'.

      :type: str


   .. py:attribute:: _max_nfev_type


   .. py:attribute:: max_nfev
      :value: 20


      Maximum number of function evaluations before the termination.
      If None (default), the value is chosen automatically. Default 20.

      :type: int


   .. py:attribute:: _xtol_type


   .. py:attribute:: xtol
      :value: None


      Tolerance for termination by the change of the independent variables.
      Default is None, which disables termination from this criteria.

      :type: float


   .. py:attribute:: _ftol_type


   .. py:attribute:: ftol
      :value: 0.01


      Tolerance for termination by the change of the cost function.
      Default is 0.01

      :type: float


   .. py:attribute:: _gtol_type


   .. py:attribute:: gtol
      :value: None


      Tolerance for termination by the norm of the gradient.
      Default is None, which disables termination from this criteria.

      :type: float


   .. py:attribute:: _tr_solver_type


   .. py:attribute:: tr_solver
      :value: 'lsmr'


      Method for solving trust-region subproblems, relevant only for ‘trf’ and ‘dogbox’ methods.
      Options are None, 'exact', or 'lsmr'

      :type: str


   .. py:method:: _check_config_validity() -> List[str]