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gradboost_pv/preprocessing/region_filtered.py

@@ -2,9 +2,9 @@
 import itertools
 import logging
 import multiprocessing as mp
+import os
 from pathlib import Path
 from typing import Iterable, Tuple, Union
-import os
 
 import geopandas as gpd
 import numpy as np
@@ -16,7 +16,6 @@
 
 from gradboost_pv.models.utils import DEFAULT_DIRECTORY_TO_PROCESSED_NWP
 
-
 logger = logging.getLogger(__name__)
 
 ESO_GEO_JSON_URL = (
@@ -148,9 +147,9 @@ def check_points_in_multipolygon_multiprocessed(
     Returns:
         np.ndarray: _description_
     """
-    filename = './data/uk_region_mask_train.npy'
+    filename = "./data/uk_region_mask_train.npy"
     if os.path.exists(filename):
-        logger.debug('Loading UK region mask from file')
+        logger.debug("Loading UK region mask from file")
         return np.load(filename)
     items = [(point, polygon) for point in points]
     results = list()
@@ -160,8 +159,8 @@ def check_points_in_multipolygon_multiprocessed(
 
     a = np.asarray(results)
 
-    logger.debug(f'Saving UK region mask from file {filename}')
-    np.save('./data/uk_region_mask_train.npy', a)
+    logger.debug(f"Saving UK region mask from file {filename}")
+    np.save("./data/uk_region_mask_train.npy", a)
 
     return a
 
@@ -207,14 +206,14 @@ def load_mask(self) -> xr.DataArray:
             xr.DataArray: UK-region mask, on NWP (x,y) coords
         """
 
-        logger.info('Loading UK region mask from National Grid ESO')
+        logger.info("Loading UK region mask from National Grid ESO")
 
         uk_polygon = query_eso_geojson()
         uk_polygon = process_eso_uk_multipolygon(uk_polygon)
         mask = generate_polygon_mask(self.nwp.coords["x"], self.nwp.coords["y"], uk_polygon)
 
         # convert numpy array to xarray mask for a 1 variable, 1 step times series of (x,y) coords
-        logger.debug('Making mask')
+        logger.debug("Making mask")
         mask = xr.DataArray(
             np.tile(mask.T, (len(self.nwp.coords["init_time"]), 1, 1)),
             dims=["init_time", "x", "y"],

scripts/preprocessing/uk_region_downsample.py

@@ -23,12 +23,14 @@
 
 logger = getLogger("uk-region-filter-nwp-data")
 
-formatString = "[%(asctime)s] {%(pathname)s:%(lineno)d} %(levelname)s - %(message)s"  # specify a format string
+formatString = (
+    "[%(asctime)s] {%(pathname)s:%(lineno)d} %(levelname)s - %(message)s"  # specify a format string
+)
 logLevel = logging.DEBUG  # specify standard log level
 logging.basicConfig(format=formatString, level=logLevel, datefmt="%Y-%m-%d %I:%M:%S")
 
-logging.getLogger('gcsfs').setLevel(logging.INFO)
-logging.getLogger('geopandas').setLevel(logging.INFO)
+logging.getLogger("gcsfs").setLevel(logging.INFO)
+logging.getLogger("geopandas").setLevel(logging.INFO)
 
 FORECAST_HORIZONS = range(NWP_STEP_HORIZON)
 
@@ -74,14 +76,13 @@ def main(base_save_directory: Path):
     date_years.append(dt.datetime(year=years[-1] + 1, month=1, day=1))
 
     for i in range(len(date_years) - 1):
-
         year = date_years[i].year
-        logger.info('Loading NWP data for year %s', year)
+        logger.info("Loading NWP data for year %s", year)
         start_datetime, end_datetime = date_years[i], date_years[i + 1]
         _nwp = nwp.sel(init_time=slice(start_datetime, end_datetime))
 
         # time points to interpolate our nwp data onto.
-        logger.info('Loading GSP datetimes for year %s', year)
+        logger.info("Loading GSP datetimes for year %s", year)
         evaluation_timeseries = (
             gsp.coords["datetime_gmt"]
             .where(
@@ -92,8 +93,8 @@ def main(base_save_directory: Path):
             .values
         )
 
-        logger.debug(f'{evaluation_timeseries=}')
-        logger.debug(f'{evaluation_timeseries.shape=}')
+        logger.debug(f"{evaluation_timeseries=}")
+        logger.debug(f"{evaluation_timeseries.shape=}")
 
         dataset_builder = NWPUKRegionMaskedDatasetBuilder(
             _nwp,