wolfhece.acceptability.Parallels

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

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Module Contents

wolfhece.acceptability.Parallels.parallel_gpd_clip(layer: list[str], file_path: str, Study_Area: str, output_dir: str, number_procs: int = 1)[source]

Clip the layers to the study area.

Process the layers in parallel.

FIXME: The GPKG driver is it totally parallel compliant?

Parameters:

  • layer – List of layers to clip

  • file_path – The path to the file

  • Study_Area – The study area

  • output_dir – The output directory where the clipped layers are stored

  • number_procs – The number of processors to use

wolfhece.acceptability.Parallels.parallel_v2r(manager: wolfhece.acceptability.func.Accept_Manager, attribute: str, pixel: float, number_procs: int = 1, convert_to_sparse: bool = False)[source]

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.

Parameters:

  • manager – The Accept_Manager object

  • attribute – The attribute to convert to raster

  • pixel – The pixel size of the raster

  • number_procs – The number of processors to use

wolfhece.acceptability.Parallels.parallel_datamod(manager: wolfhece.acceptability.func.Accept_Manager, picc: geopandas.GeoDataFrame, capa: geopandas.GeoDataFrame, number_procs: int = 1)[source]

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.

Parameters:

  • manager – The Accept_Manager object

  • number_procs – The number of processors to use