swarmpal.toolboxes.fac.processes
================================

.. py:module:: swarmpal.toolboxes.fac.processes


Classes
-------

.. autoapisummary::

   swarmpal.toolboxes.fac.processes.FAC_single_sat
   swarmpal.toolboxes.fac.processes.PalFacDataTreeAccessor


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

.. py:class:: FAC_single_sat(config: dict | None = None, active_tree: str = '/', inplace: bool = True)

   Bases: :py:obj:`swarmpal.io.PalProcess`


   Provides the process for the classic single-satellite FAC algorithm


   .. py:property:: process_name


   .. py:method:: set_config(dataset: str = 'SW_OPER_MAGA_LR_1B', model_varname: str = 'B_NEC_CHAOS', measurement_varname: str = 'B_NEC', inclination_limit: float = 30, time_jump_limit: int = 1, include_auxiliaries: bool = True, output_dataset: str = 'PAL_FAC_single_sat') -> None

      Configures the process

      :param dataset: Dataset to use, by default "SW_OPER_MAGA_LR_1B"
      :type dataset: str, optional
      :param model_varname: Name of the magnetic model predictions, by default "B_NEC_Model"
      :type model_varname: str, optional
      :param measurement_varname: Name of the measurements, by default "B_NEC"
      :type measurement_varname: str, optional
      :param inclination_limit: Limit of inclination for FAC validity (in degrees), by default 30
      :type inclination_limit: float, optional
      :param time_jump_limit: Maximum allowable time step in data for FAC validity (in seconds), by default 1
      :type time_jump_limit: int, optional
      :param include_auxiliaries: Whether to include e.g. Latitude, Longitude, Flags, etc, by default True
      :type include_auxiliaries: bool, optional
      :param output_dataset: Sets the name of the dataset in the data tree that TFA processes will write results to, by default "PAL_FAC_singlesat"
      :type output_dataset: str



   .. py:method:: _call(datatree)


   .. py:method:: _validate()


   .. py:method:: _get_time(dataset)


   .. py:method:: _get_positions(dataset)


   .. py:method:: _get_B_res(dataset)


   .. py:method:: _get_B_model(dataset)


   .. py:method:: _append_aux(ds_in, ds_out)

      Extract auxiliary information from inputs and add to output dataset



.. py:class:: PalFacDataTreeAccessor(datatree)

   .. py:attribute:: _datatree


   .. py:method:: quicklook()