swarmpal.experimental._local_magnetic_model
===========================================

.. py:module:: swarmpal.experimental._local_magnetic_model


Attributes
----------

.. autoapisummary::

   swarmpal.experimental._local_magnetic_model.LATEST_CHAOS
   swarmpal.experimental._local_magnetic_model.CHAOS_REGISTRY
   swarmpal.experimental._local_magnetic_model.CHAOS_BASE_URL


Classes
-------

.. autoapisummary::

   swarmpal.experimental._local_magnetic_model.LocalForwardMagneticModel


Functions
---------

.. autoapisummary::

   swarmpal.experimental._local_magnetic_model.fetch_chaos_file
   swarmpal.experimental._local_magnetic_model.fetch_latest_chaos_files
   swarmpal.experimental._local_magnetic_model.evaluate_chaos


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

.. py:data:: LATEST_CHAOS

.. py:data:: CHAOS_REGISTRY

.. py:data:: CHAOS_BASE_URL
   :value: 'https://zenodo.org/records/14893049/files/'


.. py:function:: fetch_chaos_file(filename)

.. py:function:: fetch_latest_chaos_files()

.. py:function:: evaluate_chaos(longitude: numpy.typing.ArrayLike, latitude: numpy.typing.ArrayLike, radius: numpy.typing.ArrayLike, time: numpy.typing.ArrayLike)

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

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


   Compute a magnetic model locally and append it to a datatree


   .. py:property:: process_name


   .. py:method:: set_config(dataset='SW_OPER_MAGA_LR_1B', model_descriptor='CHAOS-Core')


   .. py:method:: _call(datatree)