cars.applications.rasterization.rasterization_algo
==================================================

.. py:module:: cars.applications.rasterization.rasterization_algo

.. autoapi-nested-parse::

   This module is responsible for the rasterization step:
   - it contains all functions related to 3D representation on a 2D raster grid
   TODO: refactor in several files and remove too-many-lines



Functions
---------

.. autoapisummary::

   cars.applications.rasterization.rasterization_algo.simple_rasterization_dataset_wrapper
   cars.applications.rasterization.rasterization_algo.compute_vector_raster_and_stats
   cars.applications.rasterization.rasterization_algo.rasterize


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

.. py:function:: simple_rasterization_dataset_wrapper(cloud: pandas.DataFrame, resolution: float, epsg: int, xstart: float = None, ystart: float = None, xsize: int = None, ysize: int = None, sigma: float = None, radius: int = 1, dsm_no_data: int = np.nan, texture_no_data: int = np.nan, msk_no_data: int = 255, list_computed_layers: List[str] = None, source_pc_names: List[str] = None, performance_map_classes: List[float] = None, cloud_global_id: int = None) -> xarray.Dataset

   Wrapper of simple_rasterization
   that has xarray.Dataset as inputs and outputs.

   :param cloud: cloud to rasterize
   :param resolution: Resolution of rasterized cells,
       expressed in cloud CRS units or None
   :param epsg: epsg code for the CRS of the final raster
   :param color_list: Additional list of images
       with bands to rasterize (same size as cloud_list), or None
   :param xstart: xstart of the rasterization grid
       (if None, will be estimated by the function)
   :param ystart: ystart of the rasterization grid
       (if None, will be estimated by the function)
   :param xsize: xsize of the rasterization grid
       (if None, will be estimated by the function)
   :param ysize: ysize of the rasterization grid
       (if None, will be estimated by the function)
   :param sigma: sigma for gaussian interpolation.
       (If None, set to resolution)
   :param radius: Radius for hole filling.
   :param dsm_no_data: no data value to use in the final raster
   :param texture_no_data: no data value to use in the final colored raster
   :param msk_no_data: no data value to use in the final mask image
   :param list_computed_layers: list of computed output data
   :param source_pc_names: list of names of point cloud before merging :
       name of sensors pair or name of point cloud file
   :param performance_map_classes: list for step defining border of class
   :type performance_map_classes: list or None
   :param cloud_global_id: global id of pair
   :type cloud_global_id: int
   :return: Rasterized cloud


.. py:function:: compute_vector_raster_and_stats(cloud: pandas.DataFrame, x_start: float, y_start: float, x_size: int, y_size: int, resolution: float, sigma: float, radius: int, list_computed_layers: List[str] = None, cloud_global_id: int = None) -> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray, numpy.ndarray, List[str], Union[None, numpy.ndarray, list, dict]]

   Compute vectorized raster and its statistics.

   :param cloud: Combined cloud
       as returned by the create_combined_cloud function
   :param x_start: x start of the rasterization grid
   :param y_start: y start of the rasterization grid
   :param x_size: x size of the rasterization grid
   :param y_size: y size of the rasterization grid
   :param resolution: Resolution of rasterized cells,
       expressed in cloud CRS units or None.
   :param sigma: Sigma for gaussian interpolation. If None, set to resolution
   :param radius: Radius for hole filling.
   :param list_computed_layers: list of computed output data
   :param cloud_global_id: global id of pair
   :return: a tuple with rasterization results and statistics.


.. py:function:: rasterize(cloud: pandas.DataFrame, resolution: float, epsg: int, x_start: float, y_start: float, x_size: int, y_size: int, sigma: float = None, radius: int = 1, hgt_no_data: int = -32768, texture_no_data: int = 0, msk_no_data: int = 255, list_computed_layers: List[str] = None, source_pc_names: List[str] = None, performance_map_classes: List[float] = None, cloud_global_id: int = None) -> Union[xarray.Dataset, None]

   Rasterize a point cloud with its color bands to a Dataset
   that also contains quality statistics.

   :param cloud: Combined cloud
       as returned by the create_combined_cloud function
   :param resolution: Resolution of rasterized cells,
       expressed in cloud CRS units or None.
   :param epsg: epsg code for the CRS of the final raster
   :param x_start: x start of the rasterization grid
   :param y_start: y start of the rasterization grid
   :param x_size: x size of the rasterization grid
   :param y_size: y size of the rasterization grid
   :param sigma: sigma for gaussian interpolation. If None, set to resolution
   :param radius: Radius for hole filling.
   :param hgt_no_data: no data value to use for height
   :param texture_no_data: no data value to use for color
   :param msk_no_data: no data value to use in the final mask image
   :param list_computed_layers: list of computed output data
   :param source_pc_names: list of source pc names
   :param performance_map_classes: list for step defining border of class
   :type performance_map_classes: list or None
   :param cloud_global_id: global id of pair
   :return: Rasterized cloud color and statistics.