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

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

mne/tests/test_epochs.py

@@ -582,7 +582,7 @@ def my_reject_2(epoch_data):
     for kwarg in ("reject", "flat"):
         with pytest.raises(
             TypeError,
-            match=r".* must be an instance of numeric, got <class 'function'> instead."
+            match=r".* must be an instance of numeric, got <class 'function'> instead.",
         ):
             Epochs(
                 raw,
@@ -2227,7 +2227,9 @@ def test_callable_reject():
         baseline=None,
         preload=True,
     )
-    epochs.drop_bad(reject=dict(eeg=lambda x: ((np.median(x, axis=1) > 1e-3).any(), "eeg median")))
+    epochs.drop_bad(
+        reject=dict(eeg=lambda x: ((np.median(x, axis=1) > 1e-3).any(), "eeg median"))
+    )
 
     assert epochs.drop_log[2] == ("eeg median",)
 
@@ -2239,7 +2241,9 @@ def test_callable_reject():
         baseline=None,
         preload=True,
     )
-    epochs.drop_bad(reject=dict(eeg=lambda x: ((np.max(x, axis=1) > 1).any(), ("eeg max",))))
+    epochs.drop_bad(
+        reject=dict(eeg=lambda x: ((np.max(x, axis=1) > 1).any(), ("eeg max",)))
+    )
 
     assert epochs.drop_log[0] == ("eeg max",)
 
@@ -3354,6 +3358,7 @@ def test_drop_epochs():
         ("a", "b"),
     ]
 
+
 @pytest.mark.parametrize("preload", (True, False))
 def test_drop_epochs_mult(preload):
     """Test that subselecting epochs or making fewer epochs is similar."""

tutorials/preprocessing/20_rejecting_bad_data.py

@@ -379,7 +379,9 @@
     preload=True,
 )
 
-epochs.drop_bad(reject=dict(eeg=lambda x: ((np.max(x, axis=1) > 1e-2).any(), "max amp")))
+epochs.drop_bad(
+    reject=dict(eeg=lambda x: ((np.max(x, axis=1) > 1e-2).any(), "max amp"))
+)
 epochs.plot(scalings=dict(eeg=50e-5))
 
 # %%
@@ -401,7 +403,9 @@
     preload=True,
 )
 
-epochs.drop_bad(reject=dict(eeg=lambda x: ((np.median(x, axis=1) > 1e-4).any(), "median amp")))
+epochs.drop_bad(
+    reject=dict(eeg=lambda x: ((np.median(x, axis=1) > 1e-4).any(), "median amp"))
+)
 epochs.plot(scalings=dict(eeg=50e-5))
 
 # %%