demcompare.classification_layer.slope_classification
====================================================

.. py:module:: demcompare.classification_layer.slope_classification

.. autoapi-nested-parse::

   Mainly contains the SlopeClassification class.



Classes
-------

.. autoapisummary::

   demcompare.classification_layer.slope_classification.SlopeClassificationLayer


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

.. py:class:: SlopeClassificationLayer(name: str, classification_layer_kind: str, cfg: Dict, dem: xarray.Dataset = None)

   Bases: :py:obj:`demcompare.classification_layer.classification_layer_template.ClassificationLayerTemplate`


   SlopeClassificationLayer


   .. py:attribute:: _RANGES
      :value: [0, 5, 10, 25, 45]



   .. py:attribute:: ranges
      :type:  List


   .. py:method:: fill_conf_and_schema(cfg: demcompare.internal_typing.ConfigType = None) -> demcompare.internal_typing.ConfigType

      Add default values to the dictionary if there are missing
      elements and define the configuration schema

      :param cfg: coregistration configuration
      :type cfg: ConfigType
      :return cfg: coregistration configuration updated
      :rtype: ConfigType



   .. py:method:: check_ranges(cfg: dict) -> None
      :staticmethod:


      Verify users configuration for ranges in slope classification
      :param cfg: slope configuration
      :type cfg: dict
      :return: None



   .. py:method:: _create_labelled_map()

      Create the labelled map and save it if necessary
      :return: None



   .. py:method:: _create_slope_map_datasets(dem: xarray.Dataset)

      Create slope map datasets

      :param dem: input dem
      :type dem:    xr.DataSet containing :

              - image : 2D (row, col) xr.DataArray float32
              - georef_transform: 1D (trans_len) xr.DataArray
              - classification_layer_masks : 3D (row, col, indicator)
                xr.DataArray
      :return: None



   .. py:method:: _generate_classes(ranges) -> collections.OrderedDict
      :staticmethod:


      Create classes from ranges

      :param ranges: ranges
      :type ranges: List
      :return: classes
      :rtype: collections.OrderedDict



   .. py:method:: _classify_slope_by_ranges(slope_dataset: xarray.Dataset, support: str = 'ref')

      Create the map for each slope using the input ranges
      (value interval is transformed into 1 value (interval minimum value))

      :param slope_dataset: slope dataset
      :type slope_dataset:    xr.DataSet containing :

              - image : 2D (row, col) xr.DataArray float32
              - georef_transform: 1D (trans_len) xr.DataArray
              - classification_layer_masks : 3D (row, col, indicator)
                xr.DataArray
      :param support: support dem, ref or sec
      :type support: str
      :return: None