cars.applications.rasterization.abstract_pc_rasterization_app
=============================================================

.. py:module:: cars.applications.rasterization.abstract_pc_rasterization_app

.. autoapi-nested-parse::

   this module contains the abstract PointCloudRasterization application class.



Classes
-------

.. autoapisummary::

   cars.applications.rasterization.abstract_pc_rasterization_app.PointCloudRasterization


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

.. py:class:: PointCloudRasterization(conf=None)

   Bases: :py:obj:`cars.applications.application_template.ApplicationTemplate`


   PointCloudRasterization


   .. py:attribute:: available_applications
      :type:  Dict


   .. py:attribute:: default_application
      :value: 'simple_gaussian'



   .. py:method:: __init_subclass__(short_name, **kwargs)
      :classmethod:



   .. py:method:: get_margins(resolution)
      :abstractmethod:


      Get the margin to use for terrain tiles

      :param resolution: resolution of raster data (in target CRS unit)
      :type epsg: float

      :return: margin in meters or degrees



   .. py:method:: get_optimal_tile_size(max_ram_per_worker, superposing_point_clouds=1, point_cloud_resolution=0.5)
      :abstractmethod:


      Get the optimal tile size to use, depending on memory available

      :param max_ram_per_worker: maximum ram available
      :type max_ram_per_worker: int
      :param superposing_point_clouds: number of point clouds superposing
      :type superposing_point_clouds: int
      :param point_cloud_resolution: resolution of point cloud
      :type point_cloud_resolution: float

      :return: optimal tile size in meter
      :rtype: float




   .. py:method:: run(point_clouds, epsg, output_crs, resolution, orchestrator=None, dsm_file_name=None, weights_file_name=None, color_file_name=None, classif_file_name=None, performance_map_file_name=None, ambiguity_file_name=None, contributing_pair_file_name=None, filling_file_name=None, color_dtype=None, dump_dir=None)
      :abstractmethod:


      Run PointCloudRasterisation application.

      Creates a CarsDataset filled with dsm tiles.

      :param point_clouds: merged point cloud
      :type point_clouds: CarsDataset filled with pandas.DataFrame
      :param epsg: epsg of raster data
      :type epsg: str
      :param resolution: resolution of raster data (in target CRS unit)
      :type epsg: float
      :param orchestrator: orchestrator used
      :param dsm_file_name: path of dsm
      :type dsm_file_name: str
      :param weights_file_name: path of dsm weights
      :type weights_file_name: str
      :param color_file_name: path of color
      :type color_file_name: str
      :param classif_file_name: path of color
      :type classif_file_name: str
      :param performance_map_file_name: path of confidence file
      :type performance_map_file_name: str
      :param ambiguity_file_name: path to the ambiguity
      :type ambiguity_file_name: str
      :param contributing_pair_file_name: path of contributing pair file
      :type contributing_pair_file_name: str
      :param filling_file_name: path of filling file
      :type filling_file_name: str
      :param color_dtype: output color image type
      :type color_dtype: str (numpy type)
      :param dump_dir: directory used for outputs with no associated filename
      :type dump_dir: str

      :return: raster DSM
      :rtype: CarsDataset filled with xr.Dataset