style: pre-commit fixes

README.md

@@ -54,6 +54,7 @@ The easiest way to use PyBaMM is to run a 1C constant-current discharge with a m
 
 ```python3
 import pybamm
+
 model = pybamm.lithium_ion.DFN()  # Doyle-Fuller-Newman model
 sim = pybamm.Simulation(model)
 sim.solve([0, 3600])  # solve for 1 hour
@@ -64,13 +65,16 @@ or simulate an experiment such as a constant-current discharge followed by a con
 
 ```python3
 import pybamm
+
 experiment = pybamm.Experiment(
     [
-        ("Discharge at C/10 for 10 hours or until 3.3 V",
-        "Rest for 1 hour",
-        "Charge at 1 A until 4.1 V",
-        "Hold at 4.1 V until 50 mA",
-        "Rest for 1 hour")
+        (
+            "Discharge at C/10 for 10 hours or until 3.3 V",
+            "Rest for 1 hour",
+            "Charge at 1 A until 4.1 V",
+            "Hold at 4.1 V until 50 mA",
+            "Rest for 1 hour",
+        )
     ]
     * 3,
 )

benchmarks/README.md

@@ -63,8 +63,8 @@ Note that benchmark functions _must_ start with the prefix `time_`, for instance
 
 ```python3
 def time_solve_SPM_ScipySolver(self):
-        solver = pb.ScipySolver()
-        solver.solve(self.model, [0, 3600])
+    solver = pb.ScipySolver()
+    solver.solve(self.model, [0, 3600])
 ```
 
 In the case where some setup is necessary, but should not be timed, a `setup` function
@@ -76,7 +76,7 @@ class TimeSPM:
         model = pb.lithium_ion.SPM()
         geometry = model.default_geometry
 
-	    # ...
+        # ...
 
         self.model = model