run black with new version

simonbesnard1 · Feb 24, 2025 · 119602a · 119602a
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Showing 6 changed files with 8 additions and 8 deletions.
diff --git a/doc/auto_examples/data_processor.py b/doc/auto_examples/data_processor.py
@@ -2,7 +2,7 @@
 GEDIProcessor example with different parallel engines
 =======================================================
 
-This example demonstrates how to use the `gedidb` library to process GEDI granules 
+This example demonstrates how to use the `gedidb` library to process GEDI granules
 with different parallel engines, such as `concurrent.futures.ThreadPoolExecutor` and `dask.distributed.Client`.
 
 A default data configuration file (`data_config.yml`) can be downloaded here:

diff --git a/doc/auto_examples/regional_tileDBdatabase.py b/doc/auto_examples/regional_tileDBdatabase.py
@@ -2,8 +2,8 @@
 Creating a Regional TileDB Array for the Amazon
 ===============================================
 
-This example demonstrates how to create a **regional TileDB array** for the Amazon 
-by modifying the `data_config.yml` file to adjust the **spatial range** based on 
+This example demonstrates how to create a **regional TileDB array** for the Amazon
+by modifying the `data_config.yml` file to adjust the **spatial range** based on
 a bounding box extracted from a GeoJSON file.
 
 A default data configuration file (`data_config.yml`) can be downloaded here:

diff --git a/doc/gallery/data_processor.py b/doc/gallery/data_processor.py
@@ -2,7 +2,7 @@
 GEDIProcessor example with different parallel engines
 =======================================================
 
-This example demonstrates how to use the `gedidb` library to process GEDI granules 
+This example demonstrates how to use the `gedidb` library to process GEDI granules
 with different parallel engines, such as `concurrent.futures.ThreadPoolExecutor` and `dask.distributed.Client`.
 
 A default data configuration file (`data_config.yml`) can be downloaded here:

diff --git a/doc/gallery/regional_tileDBdatabase.py b/doc/gallery/regional_tileDBdatabase.py
@@ -2,8 +2,8 @@
 Creating a Regional TileDB Array for the Amazon
 ===============================================
 
-This example demonstrates how to create a **regional TileDB array** for the Amazon 
-by modifying the `data_config.yml` file to adjust the **spatial range** based on 
+This example demonstrates how to create a **regional TileDB array** for the Amazon
+by modifying the `data_config.yml` file to adjust the **spatial range** based on
 a bounding box extracted from a GeoJSON file.
 
 A default data configuration file (`data_config.yml`) can be downloaded here:

diff --git a/gedidb/utils/geo_processing.py b/gedidb/utils/geo_processing.py
@@ -147,7 +147,7 @@ def _timestamp_to_datetime(days: np.ndarray) -> np.ndarray:
 
 
 def convert_to_days_since_epoch(
-    timestamps: Union[pd.DatetimeIndex, pd.Series, list]
+    timestamps: Union[pd.DatetimeIndex, pd.Series, list],
 ) -> pd.Series:
     """
     Convert nanosecond-precision timestamps to daily timestamps in days since the Unix epoch (1970-01-01).

diff --git a/gedidb/utils/tiledb_consolidation.py b/gedidb/utils/tiledb_consolidation.py
@@ -120,7 +120,7 @@ def _extract_fragments(
 
     @staticmethod
     def _generate_plan(
-        fragments: List[Dict[str, Union[str, Tuple[float, float]]]]
+        fragments: List[Dict[str, Union[str, Tuple[float, float]]]],
     ) -> Dict[int, Dict[str, List[str]]]:
         """
         Generate a plan by grouping overlapping fragments.