diff --git a/src/simweights/_weighter.py b/src/simweights/_weighter.py
index 5112039..afd7996 100644
--- a/src/simweights/_weighter.py
+++ b/src/simweights/_weighter.py
@@ -139,7 +139,7 @@ def effective_area(
         self: Weighter,
         energy_bins: ArrayLike,
         cos_zenith_bins: ArrayLike,
-        flux: Any = 1e-4, # default is 1 GeV^-1 m^-2 sr^-1 flux
+        flux: Any = 1e-4,  # default is 1 GeV^-1 m^-2 sr^-1 flux
         mask: ArrayLike | None = None,
     ) -> NDArray[np.float64]:
         r"""Calculate The effective area for the given energy and zenith bins.
@@ -204,9 +204,20 @@ def effective_area(
             return np.asarray(hist_val / (e_width * 2 * np.pi * z_width * nspecies), dtype=np.float64)
         elif callable(flux):
             flux_pdgids = [pdgid.value for pdgid in flux.pdgids]
-            flux_func = lambda E: sum([flux._funcs[flux_pdgids.index(np.unique(self.get_weight_column("pdgid")[maska])[i_species])](E) for i_species in range(nspecies)])
+            flux_func = lambda E: sum(
+                [
+                    flux._funcs[flux_pdgids.index(np.unique(self.get_weight_column("pdgid")[maska])[i_species])](E)
+                    for i_species in range(nspecies)
+                ]
+            )
             from scipy.integrate import quad
-            flux_integrals = np.asarray([quad(flux_func, energy_bins[bin_index], energy_bins[bin_index+1])[0] for bin_index in range(len(energy_bins)-1)])
+
+            flux_integrals = np.asarray(
+                [
+                    quad(flux_func, energy_bins[bin_index], energy_bins[bin_index + 1])[0]
+                    for bin_index in range(len(energy_bins) - 1)
+                ]
+            )
             e_width, z_width = np.meshgrid(flux_integrals, np.ediff1d(czbin))
             return np.asarray(1e-4 * hist_val / (e_width * 2 * np.pi * z_width), dtype=np.float64)
         else: