refmod
======

.. py:module:: refmod


Submodules
----------

.. toctree::
   :maxdepth: 1

   /autoapi/refmod/dtm_helper/index
   /autoapi/refmod/hapke/index
   /autoapi/refmod/inverse/index




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

.. py:class:: Hapke(/, **data)



   !!! abstract "Usage Documentation"
       [Models](../concepts/models.md)

   A base class for creating Pydantic models.

   .. attribute:: __class_vars__

      The names of the class variables defined on the model.

   .. attribute:: __private_attributes__

      Metadata about the private attributes of the model.

   .. attribute:: __signature__

      The synthesized `__init__` [`Signature`][inspect.Signature] of the model.

   .. attribute:: __pydantic_complete__

      Whether model building is completed, or if there are still undefined fields.

   .. attribute:: __pydantic_core_schema__

      The core schema of the model.

   .. attribute:: __pydantic_custom_init__

      Whether the model has a custom `__init__` function.

   .. attribute:: __pydantic_decorators__

      Metadata containing the decorators defined on the model.
      This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.

   .. attribute:: __pydantic_generic_metadata__

      Metadata for generic models; contains data used for a similar purpose to
      __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

   .. attribute:: __pydantic_parent_namespace__

      Parent namespace of the model, used for automatic rebuilding of models.

   .. attribute:: __pydantic_post_init__

      The name of the post-init method for the model, if defined.

   .. attribute:: __pydantic_root_model__

      Whether the model is a [`RootModel`][pydantic.root_model.RootModel].

   .. attribute:: __pydantic_serializer__

      The `pydantic-core` `SchemaSerializer` used to dump instances of the model.

   .. attribute:: __pydantic_validator__

      The `pydantic-core` `SchemaValidator` used to validate instances of the model.

   .. attribute:: __pydantic_fields__

      A dictionary of field names and their corresponding [`FieldInfo`][pydantic.fields.FieldInfo] objects.

   .. attribute:: __pydantic_computed_fields__

      A dictionary of computed field names and their corresponding [`ComputedFieldInfo`][pydantic.fields.ComputedFieldInfo] objects.

   .. attribute:: __pydantic_extra__

      A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]
      is set to `'allow'`.

   .. attribute:: __pydantic_fields_set__

      The names of fields explicitly set during instantiation.

   .. attribute:: __pydantic_private__

      Values of private attributes set on the model instance.

   Create a new model by parsing and validating input data from keyword arguments.

   Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
   validated to form a valid model.

   `self` is explicitly positional-only to allow `self` as a field name.


   .. py:attribute:: single_scattering_albedo
      :type:  numpy.typing.NDArray


   .. py:attribute:: incidence_direction
      :type:  numpy.typing.NDArray


   .. py:attribute:: emission_direction
      :type:  numpy.typing.NDArray


   .. py:attribute:: surface_orientation
      :type:  numpy.typing.NDArray


   .. py:attribute:: phase_function_type
      :type:  functions.phase.PhaseFunctionType
      :value: None



   .. py:attribute:: roughness
      :type:  float
      :value: None



   .. py:attribute:: shadow_hiding_h
      :type:  float
      :value: None



   .. py:attribute:: shadow_hiding_b0
      :type:  float
      :value: None



   .. py:attribute:: coherant_backscattering_h
      :type:  float
      :value: None



   .. py:attribute:: coherant_backscattering_b0
      :type:  float
      :value: None



   .. py:attribute:: phase_function_args
      :type:  tuple
      :value: None



   .. py:attribute:: model
      :type:  Literal['amsa', 'imsa']
      :value: None



   .. py:attribute:: h_level
      :type:  Literal[1, 2]
      :value: None



   .. py:attribute:: backend
      :type:  Literal['numpy', 'numba']
      :value: None



   .. py:attribute:: model_config

      Configuration for the model, should be a dictionary conforming to [`ConfigDict`][pydantic.config.ConfigDict].


   .. py:method:: refl()

      Calculate the reflectance using the specified Hapke model.

      :returns: The calculated reflectance.
      :rtype: npt.NDArray