more ruff happiness

src/iblphotometry/io.py

@@ -231,12 +231,15 @@ def from_raw_neurophotometrics_file_to_ibl_df(
 
     return df
 
+
 def from_raw_neurophotometrics_file(
     path: str | Path,
     drop_first=True,
     validate=True,
 ) -> dict:
-    df = from_raw_neurophotometrics_file_to_ibl_df(path, drop_first=drop_first, validate=validate)
+    df = from_raw_neurophotometrics_file_to_ibl_df(
+        path, drop_first=drop_first, validate=validate
+    )
     data_columns = [col for col in df.columns if col.startswith('G')]
     read_config = dict(
         data_columns=data_columns,

src/iblphotometry_tests/test_loaders.py

@@ -19,17 +19,20 @@ def test_from_array(self):
     # for neurophotometrics hardware
     def test_from_raw_neurophotometrics_file(self):
         # the single direct version
-        raw_dfs_a = fpio.from_raw_neurophotometrics_file(self.paths['raw_neurophotometrics_csv'])
-
+        raw_dfs_a = fpio.from_raw_neurophotometrics_file(
+            self.paths['raw_neurophotometrics_csv']
+        )
+
         # the chained version
-        df = fpio.from_raw_neurophotometrics_file_to_ibl_df(self.paths['raw_neurophotometrics_csv'])
+        df = fpio.from_raw_neurophotometrics_file_to_ibl_df(
+            self.paths['raw_neurophotometrics_csv']
+        )
         raw_dfs_b = fpio.from_ibl_dataframe(df)
 
         # check if they are the same
         assert raw_dfs_a.keys() == raw_dfs_b.keys()
         for key in raw_dfs_a.keys():
             pd.testing.assert_frame_equal(raw_dfs_a[key], raw_dfs_b[key])
-
 
     # from pqt files as they are returned from ONE by .load_dataset()
     def test_from_ibl_pqt(self):