diff --git a/pybamm/spatial_methods/spectral_volume.py b/pybamm/spatial_methods/spectral_volume.py
index f6d4dcd817..53e6a6fce7 100644
--- a/pybamm/spatial_methods/spectral_volume.py
+++ b/pybamm/spatial_methods/spectral_volume.py
@@ -288,7 +288,7 @@ def gradient(self, symbol, discretised_symbol, boundary_conditions):
 
         # Multiply by gradient matrix
         out = (gradient_matrix @ reconstructed_symbol
-            + penalty_matrix @ discretised_symbol)
+               + penalty_matrix @ discretised_symbol)
 
         # Add Neumann boundary conditions, if defined
         if symbol.id in boundary_conditions:
@@ -362,7 +362,7 @@ def gradient_matrix(self, domain, auxiliary_domains):
             for i in range(1, n - 1):
                 sub_matrix[i * d, i * (d + 1):(i + 1) * (d + 1)] = (
                     f * sub_matrix_raw[i * (d + 1),
-                                         i * (d + 1):(i + 1) * (d + 1)]
+                                       i * (d + 1):(i + 1) * (d + 1)]
                 )
                 sub_matrix[i * d + 1:(i + 1) * d,
                            i * (d + 1):(i + 1) * (d + 1)] = (
@@ -371,7 +371,7 @@ def gradient_matrix(self, domain, auxiliary_domains):
                 )
                 sub_matrix[(i + 1) * d, i * (d + 1):(i + 1) * (d + 1)] = (
                     f * sub_matrix_raw[i * (d + 1) + d,
-                                         i * (d + 1):(i + 1) * (d + 1)]
+                                       i * (d + 1):(i + 1) * (d + 1)]
                 )
             sub_matrix[-d - 1, -d - 1:] = f * sub_matrix_raw[-d - 1, -d - 1:]
             sub_matrix[-d:, -d - 1:] = sub_matrix_raw[-d:, -d - 1:]
@@ -416,7 +416,7 @@ def penalty_matrix(self, domain, auxiliary_domains):
         n = submesh.npts
         d = self.order
         e = np.zeros(n - 1)
-        e[d-1::d] = 1 / submesh.d_nodes[d-1::d]
+        e[d - 1::d] = 1 / submesh.d_nodes[d - 1::d]
         sub_matrix = vstack([
             np.zeros(n),
             diags([-e, e], [0, 1], shape=(n - 1, n)),