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

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

scripts/backtest_sites.py

@@ -118,11 +118,13 @@ class PadForwardPVIterDataPipe(IterDataPipe):
     to run out of data to slice for the forecast part.
     """
 
-    def __init__(self, pv_dp: IterDataPipe,
-                 forecast_duration: np.timedelta64,
-                 history_duration: np.timedelta64,
-                 time_resolution_minutes: np.timedelta64
-                ):
+    def __init__(
+        self,
+        pv_dp: IterDataPipe,
+        forecast_duration: np.timedelta64,
+        history_duration: np.timedelta64,
+        time_resolution_minutes: np.timedelta64,
+    ):
         """Init"""
 
         super().__init__()
@@ -137,7 +139,12 @@ def __iter__(self):
         """Iter"""
 
         for xr_data in self.pv_dp:
-            t_end = xr_data.time_utc.data[0] + self.history_duration + self.forecast_duration + self.time_resolution_minutes
+            t_end = (
+                xr_data.time_utc.data[0]
+                + self.history_duration
+                + self.forecast_duration
+                + self.time_resolution_minutes
+            )
             time_idx = np.arange(xr_data.time_utc.data[0], t_end, self.time_resolution_minutes)
 
             if len(xr_data.time_utc.data) < self.min_seq_length:
@@ -439,10 +446,10 @@ def get_datapipe(config_path: str) -> NumpyBatch:
     )
 
     config = load_yaml_configuration(config_path)
-    data_pipeline['pv'] = data_pipeline['pv'].pad_forward_pv(
-        forecast_duration=np.timedelta64(config.input_data.pv.forecast_minutes, 'm'),
-        history_duration=np.timedelta64(config.input_data.pv.history_minutes, 'm'),
-        time_resolution_minutes=np.timedelta64(config.input_data.pv.time_resolution_minutes, 'm')
+    data_pipeline["pv"] = data_pipeline["pv"].pad_forward_pv(
+        forecast_duration=np.timedelta64(config.input_data.pv.forecast_minutes, "m"),
+        history_duration=np.timedelta64(config.input_data.pv.history_minutes, "m"),
+        time_resolution_minutes=np.timedelta64(config.input_data.pv.time_resolution_minutes, "m"),
     )
 
     data_pipeline = DictDatasetIterDataPipe(