demcompare
==========

.. py:module:: demcompare

.. autoapi-nested-parse::

   Demcompare init module file.
   Demcompare aims at coregistering and comparing two Digital Elevation Models(DEM)



Submodules
----------

.. toctree::
   :maxdepth: 1

   /api_reference/demcompare/classification_layer/index
   /api_reference/demcompare/coregistration/index
   /api_reference/demcompare/dataset_tools/index
   /api_reference/demcompare/dem_processing/index
   /api_reference/demcompare/dem_tools/index
   /api_reference/demcompare/demcompare/index
   /api_reference/demcompare/demcompare_tiles/index
   /api_reference/demcompare/helpers_init/index
   /api_reference/demcompare/img_tools/index
   /api_reference/demcompare/internal_typing/index
   /api_reference/demcompare/log_conf/index
   /api_reference/demcompare/metric/index
   /api_reference/demcompare/report/index
   /api_reference/demcompare/sphinx_project_generator/index
   /api_reference/demcompare/stats_dataset/index
   /api_reference/demcompare/stats_processing/index
   /api_reference/demcompare/transformation/index


Attributes
----------

.. autoapisummary::

   demcompare.__version__
   demcompare.__author__
   demcompare.__email__


Functions
---------

.. autoapisummary::

   demcompare.run
   demcompare.load_input_dems
   demcompare.run_coregistration


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

.. py:data:: __version__

.. py:data:: __author__
   :value: 'CNES'


.. py:data:: __email__
   :value: 'cars@cnes.fr'


.. py:function:: run(json_file_path: str, loglevel: int = logging.WARNING)

   Demcompare RUN execution.

   :param json_file_path: Input Json configuration file
   :type json_file_path: str
   :param loglevel: Choose Loglevel (default: WARNING)
   :type loglevel: int


.. py:function:: load_input_dems(cfg: internal_typing.ConfigType) -> Tuple[xarray.Dataset, Union[None, xarray.Dataset]]

   Loads the input dems according to the input cfg

   :param cfg: input configuration
   :type cfg: ConfigType
   :return: input_ref and input_dem datasets or None
   :rtype:   Tuple(xr.Dataset, xr.Dataset)
         The xr.Datasets containing :

         - im : 2D (row, col) xarray.DataArray float32
         - trans: 1D (trans_len) xarray.DataArray


.. py:function:: run_coregistration(cfg: internal_typing.ConfigType, input_ref: xarray.Dataset, input_sec: xarray.Dataset) -> Tuple[xarray.Dataset, xarray.Dataset]

   Runs the dems coregistration

   :param cfg: coregistration configuration
   :type cfg: ConfigType
   :param input_ref: input ref
   :type input_ref: xr.DataSet containing :

               - im : 2D (row, col) xarray.DataArray float32
               - trans: 1D (trans_len) xarray.DataArray
   :param input_sec: input dem
   :type input_sec: xr.DataSet containing :

               - im : 2D (row, col) xarray.DataArray float32
               - trans: 1D (trans_len) xarray.DataArray
   :return: reproj_coreg_sec, reproj_coreg_ref
   :rtype:   Tuple(xr.Dataset, xr.Dataset)
            The xr.Datasets containing :

            - im : 2D (row, col) xarray.DataArray float32
            - trans: 1D (trans_len) xarray.DataArray