diff --git a/examples/gss_divergent_optima/gss_divergent_optima.py b/examples/gss_divergent_optima/gss_divergent_optima.py
index 5a6cf20d7..969f3f9aa 100644
--- a/examples/gss_divergent_optima/gss_divergent_optima.py
+++ b/examples/gss_divergent_optima/gss_divergent_optima.py
@@ -23,7 +23,8 @@
 """
 
 demography = fwdpy11.ForwardDemesGraph.from_demes(
-    yaml, burnin=10*N, burnin_is_exact=True)
+    yaml, burnin=10 * N + 200, burnin_is_exact=True
+)
 
 moving_optimum_deme_0 = fwdpy11.GSSmo(
     [
@@ -70,8 +71,7 @@
             # Mapping of trait (genetic) value to fitness
             gvalue_to_fitness=moving_optimum_deme_0,
         ),
-        fwdpy11.Additive(ndemes=2, scaling=2,
-                         gvalue_to_fitness=moving_optimum_deme_1),
+        fwdpy11.Additive(ndemes=2, scaling=2, gvalue_to_fitness=moving_optimum_deme_1),
     ],
 }
 
@@ -79,7 +79,7 @@
 pop = fwdpy11.DiploidPopulation([N, N], 1.0)
 rng = fwdpy11.GSLrng(1010)
 fwdpy11.evolvets(rng, pop, params, 100)
-assert pop.generation == 10*N + 200
+assert pop.generation == 10 * N + 200
 md = np.array(pop.diploid_metadata, copy=False)
 df = pd.DataFrame.from_records(md[["deme", "g", "w"]])
 g = df.groupby(["deme"])