[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

AUTHORS

@@ -5,4 +5,4 @@ code or documentation. For a full contributor list, see:
 <https://github.com/calliope-project/module_area_potentials/graphs/contributors>
 
 Linh Ho-Tran, <L.Ho@tudelft.nl>
-Stefan Pfenninger-Lee, <s.pfenninger@tudelft.nl>
+Stefan Pfenninger-Lee, <s.pfenninger@tudelft.nl>

tests/integration/Snakefile

@@ -1,17 +1,21 @@
 # Emulate a user configuring the module.
 configfile: workflow.source_path("./test_config.yaml")
 
+
 rule download_netherlands_shapes:
-    message: "Download and unzip the Netherlands shapes."
+    message:
+        "Download and unzip the Netherlands shapes."
     output:
         "results/module_area_potentials/resources/user/shapes/NLD.parquet",
     shell:
         """
         curl -sSLo {output} https://surfdrive.surf.nl/files/index.php/s/ey3RmiCbajp69oQ/download
         """
 
+
 rule download_netherlands_protected_areas:
-    message: "Download and unzip a dummy drop-in dataset for Netherlands protected areas (not based on WDPA)."
+    message:
+        "Download and unzip a dummy drop-in dataset for Netherlands protected areas (not based on WDPA)."
     output:
         zipfile="results/module_area_potentials/resources/user/wdpa.gdb.zip",
         wdpa=directory("results/module_area_potentials/resources/user/wdpa.gdb"),
@@ -21,20 +25,27 @@ rule download_netherlands_protected_areas:
         unzip {output.zipfile} -d results/module_area_potentials/resources/user/
         """
 
+
 # Import the module and configure it.
 # `snakefile:` specifies the module. It can use file paths and special github(...) / gitlab(...) markers
 # `prefix:` re-routes all input/output paths of the module, helping to avoid file conflicts.
 module module_area_potentials:
-    snakefile: "../../workflow/Snakefile"
-    config: config["module_area_potentials"]
-    prefix: "results/module_area_potentials/"
+    snakefile:
+        "../../workflow/Snakefile"
+    config:
+        config["module_area_potentials"]
+    prefix:
+        "results/module_area_potentials/"
+
 
 # rename all module rules with a prefix, to avoid naming conflicts.
 use rule * from module_area_potentials as module_area_potentials_*
 
+
 # Request something from the module
 rule all:
-    message: "Run the module for the Netherlands shapes."
+    message:
+        "Run the module for the Netherlands shapes."
     default_target: True
     input:
         "results/module_area_potentials/resources/user/shapes/NLD.parquet",

workflow/Snakefile

@@ -20,10 +20,12 @@ with open(workflow.source_path("internal/settings.yaml"), "r") as f:
 workflow.source_path("scripts/script_utils.py")
 workflow.source_path("scripts/geo.py")
 
+
 wildcard_constraints:
     shape="[a-zA-Z0-9_-]+",
     tech="|".join(config["techs"].keys()),
 
+
 # Add all your includes here.
 include: "rules/automatic.smk"
 include: "rules/prepare.smk"

workflow/internal/config.schema.yaml

@@ -41,4 +41,4 @@ properties:
         shapes_buffer:
           type: object
       required: ["initial_area", "continuous_layers", "binary_layers"]
-      additionalProperties: false
+      additionalProperties: false

workflow/rules/automatic.smk

@@ -1,5 +1,6 @@
 """Rules to used to download automatic resource files."""
 
+
 rule download_cutout_slope:
     message:
         "Download slope data covering the bounds of the input shapefile."
@@ -12,6 +13,7 @@ rule download_cutout_slope:
     wrapper:
         "v7.2.0/geo/rasterio/clip-geotiff"
 
+
 rule download_cutout_bathymetry:
     message:
         "Download bathymetry data covering the bounds of the input shapefile."
@@ -24,6 +26,7 @@ rule download_cutout_bathymetry:
     wrapper:
         "v7.2.0/geo/rasterio/clip-geotiff"
 
+
 rule download_globcover:
     message:
         "Download the GlobCover land cover data (~380 MB)."
@@ -36,6 +39,7 @@ rule download_globcover:
     shell:
         'curl -sSLo {output} "{params.url}"'
 
+
 rule unzip_globcover:
     message:
         "Unzip the relevant TIF files from the GlobCover zip file."
@@ -57,6 +61,7 @@ rule unzip_globcover:
         rm -R $temp_dir
         """
 
+
 rule download_ghsl:
     message:
         "Download the GHSL (Global Human Settlement Layer) built-up surface data."
@@ -69,6 +74,7 @@ rule download_ghsl:
     shell:
         'curl -sSLo {output} "{params.url}"'
 
+
 rule unzip_ghsl:
     message:
         "Unzip the relevant TIF file from the GHSL data."

workflow/rules/prepare.smk

@@ -1,5 +1,6 @@
 """Cut out the datasets to bounds determined by the input shapefile."""
 
+
 rule cutout_landcover:
     message:
         "Cut land cover data to the bounds of the input shapefile."
@@ -15,6 +16,7 @@ rule cutout_landcover:
         rio clip --overwrite "{input.landcover}" "{output}" --bounds "$(fio info '{input.shapes}' --bounds)"
         """
 
+
 rule cutout_settlement:
     message:
         "Cut settlement data to the bounds of the input shapefile."

workflow/rules/process.smk

@@ -1,6 +1,6 @@
 rule prepare_resampled_inputs:
     message:
-        "Resample inputs for {wildcards.shape} to the projection and resolution of the land cover data, while aggregating land cover types.",
+        "Resample inputs for {wildcards.shape} to the projection and resolution of the land cover data, while aggregating land cover types."
     input:
         script=workflow.source_path("../scripts/resample.py"),
         shapes="resources/user/shapes/{shape}.parquet",
@@ -24,6 +24,7 @@ rule prepare_resampled_inputs:
         "{output.resampled_input}" "{output.plot}"
         """
 
+
 rule area_potential:
     message:
         "Compute area potential for the tech {wildcards.tech} and shapes {wildcards.shape}."
@@ -48,16 +49,17 @@ rule area_potential:
         python "{input.script}" "{input.shapes}" "{input.resampled_path}" "{params.config}" "{params.buffer_crs}" "{output.area_potential}" "{output.plot}"
         """
 
+
 rule area_potential_report:
     message:
-        "Generate an overview report of the area potential for all techs in shapes {wildcards.shape}.",
+        "Generate an overview report of the area potential for all techs in shapes {wildcards.shape}."
     input:
         shapes="resources/user/shapes/{shape}.parquet",
         resampled_path=rules.prepare_resampled_inputs.output.resampled_input,
         area_potentials=expand(
             "results/{{shape}}/area_potential_{tech}.tif",
             tech=config["techs"].keys(),
-        )
+        ),
     output:
         csv="results/{shape}/area_potential_report.csv",
         html=report(

workflow/scripts/area_potential.py

@@ -14,12 +14,7 @@
 @click.argument("output_path", type=str)
 @click.argument("plot_path", type=str)
 def get_area_potential(
-    shapes_path,
-    resampled_path,
-    config,
-    buffer_crs,
-    output_path,
-    plot_path,
+    shapes_path, resampled_path, config, buffer_crs, output_path, plot_path
 ):
     shapes = gpd.read_parquet(shapes_path)
     ds = xr.open_dataset(resampled_path, decode_coords="all")

workflow/scripts/report.py

@@ -39,7 +39,7 @@ def report(shapes, resampled_path, area_potentials, csv_path, html_path):
     sums.name = "Total"
     df = pd.concat([df, sums.to_frame().T])
 
-    df.to_html(html_path, float_format=lambda x: f"{x/1e6:.2f}")
+    df.to_html(html_path, float_format=lambda x: f"{x / 1e6:.2f}")
 
 
 if __name__ == "__main__":

workflow/scripts/resample.py

@@ -127,9 +127,9 @@ def determine_pixel_areas(raster_input):
     """
     # the following is based on https://gis.stackexchange.com/a/288034/77760
     # and assumes the data to be in EPSG:4326
-    assert (
-        raster_input.rio.crs.to_epsg() == 4326
-    ), "raster_input does not have the projection EPSG:4326"
+    assert raster_input.rio.crs.to_epsg() == 4326, (
+        "raster_input does not have the projection EPSG:4326"
+    )
     resolution = raster_input.rio.resolution()[0]  # resolution in degrees
     varea_of_pixel = np.vectorize(lambda lat: _area_of_pixel(resolution, lat))
     pixel_area = varea_of_pixel(raster_input.y) * 1000**2  # convert to m^2
@@ -206,10 +206,7 @@ def get_same_shape_and_resolution(
     print(f"Number of land regions: {len(shapes_land)}")
     print(f"Number of maritime regions: {len(shapes_maritime)}")
 
-    resampled["regions"] = (
-        ("y", "x"),
-        _rasterize_regions(shapes, reference_raster),
-    )
+    resampled["regions"] = (("y", "x"), _rasterize_regions(shapes, reference_raster))
 
     mask_land = xr.DataArray(
         np.isin(resampled["regions"], shapes_land),