shareloc.geofunctions.localization
==================================

.. py:module:: shareloc.geofunctions.localization

.. autoapi-nested-parse::

   Localization class for localization functions.



Classes
-------

.. autoapisummary::

   shareloc.geofunctions.localization.Localization


Functions
---------

.. autoapisummary::

   shareloc.geofunctions.localization.coloc


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

.. py:class:: Localization(model, elevation=None, image=None, epsg=None)

   Base class for localization function.
   Underlying model can be both multi layer localization grids or RPCs models


   .. py:attribute:: use_rpc


   .. py:attribute:: model


   .. py:attribute:: default_elevation
      :value: 0.0



   .. py:attribute:: dtm
      :value: None



   .. py:attribute:: image
      :value: None



   .. py:attribute:: epsg
      :value: None



   .. py:method:: direct(row, col, h=None, using_geotransform=False)

      direct localization

      :param row: sensor row
      :type row: float or 1D np.ndarray
      :param col: sensor col
      :type col: float or 1D np.ndarray
      :param h: altitude, if none DTM is used
      :type h: float or 1D np.ndarray
      :param using_geotransform: using_geotransform
      :type using_geotransform: boolean
      :return coordinates: [lon,lat,h] (2D np.array)
      :rtype: np.ndarray of 2D dimension



   .. py:method:: extent(margin=0.0)

      returns model extent:
          * whole validity domains if image is not given
          * image footprint if image is set
          * epipolar footprint if right_model is set

      :param margin: footprint margin (in degrees)
      :type margin: float
      :return: extent [lon_min,lat_min,lon max,lat max] (2D np.array)
      :rtype: numpy.array



   .. py:method:: inverse(lon, lat, h=None, using_geotransform=False)

      inverse localization

      :param lat:  latitude (or y)
      :param lon: longitude (or x)
      :param h: altitude
      :param using_geotransform: using_geotransform
      :type using_geotransform: boolean
      :return: coordinates [row,col,h] (1D np.ndarray)
      :rtype: Tuple(1D np.ndarray row position, 1D np.ndarray col position, 1D np.ndarray alt)



.. py:function:: coloc(model1, model2, row, col, elevation=None, image1=None, image2=None, using_geotransform=False)

   Colocalization : direct localization with model1, then inverse localization with model2

   :param model1: geometric model 1
   :type model1: GeomodelTemplate
   :param model2: geometric model 2
   :type model2: GeomodelTemplate
   :param row: sensor row
   :type row: int or 1D numpy array
   :param col: sensor col
   :type col: int or 1D numpy array
   :param elevation: elevation
   :type elevation: shareloc.dtm or float or 1D numpy array
   :param image1: image class to handle geotransform
   :type image1: shareloc.image.Image
   :param image2: image class to handle geotransform
   :type image2: shareloc.image.Image
   :param using_geotransform: using_geotransform
   :type using_geotransform: boolean
   :return: Corresponding sensor position [row, col, altitude] in the geometric model 2
   :rtype: Tuple(1D np.array row position, 1D np.array col position, 1D np.array alt)
      using row and col input dimensions