:py:mod:`wolfhece.acceptability.Parallels`
==========================================

.. py:module:: wolfhece.acceptability.Parallels

.. autoapi-nested-parse::

   Author: University of Liege, HECE, LEMA
   Date: 2024

   Copyright (c) 2024 University of Liege. All rights reserved.

   This script and its content are protected by copyright law. Unauthorized
   copying or distribution of this file, via any medium, is strictly prohibited.



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

.. py:function:: parallel_gpd_clip(layer: list[str], file_path: str, Study_Area: str, output_dir: str, number_procs: int = 1)

   Clip the layers to the study area.

   Process the layers in parallel.

   FIXME: The GPKG driver is it totally parallel compliant?

   :param layer: List of layers to clip
   :param file_path: The path to the file
   :param Study_Area: The study area
   :param output_dir: The output directory where the clipped layers are stored
   :param number_procs: The number of processors to use



.. py:function:: parallel_v2r(manager: wolfhece.acceptability.func.Accept_Manager, attribute: str, pixel: float, number_procs: int = 1, convert_to_sparse: bool = False)

   Convert the vector layers to raster.

   Process the layers in parallel.

   :remark: It is permitted to execute this function in multiprocessing because we write separate files.

   :param manager: The Accept_Manager object
   :param attribute: The attribute to convert to raster
   :param pixel: The pixel size of the raster
   :param number_procs: The number of processors to use



.. py:function:: parallel_datamod(manager: wolfhece.acceptability.func.Accept_Manager, picc: geopandas.GeoDataFrame, capa: geopandas.GeoDataFrame, number_procs: int = 1)

   Apply the data modification to the layers.

   Process the layers in parallel.

   :remark: It is permitted to execute this function in multiprocessing because we write separate files.

   :param manager: The Accept_Manager object
   :param number_procs: The number of processors to use