diff --git a/src/pyextremes/tests/ks_test.py b/src/pyextremes/tests/ks_test.py
index bd83d15..971773f 100644
--- a/src/pyextremes/tests/ks_test.py
+++ b/src/pyextremes/tests/ks_test.py
@@ -59,7 +59,10 @@ def __init__(
             rvs=self.extremes,
             cdf=functools.partial(
                 self.distribution.cdf,
-                **{'loc' if k == 'floc' else k: v for k, v in self.fixed_parameters.items()},
+                **{
+                    "loc" if k == "floc" else k: v
+                    for k, v in self.fixed_parameters.items()
+                },
                 **self.fit_parameters,
             ),
         )
diff --git a/tests/integration/test_eva.py b/tests/integration/test_eva.py
index 0730de2..219da65 100644
--- a/tests/integration/test_eva.py
+++ b/tests/integration/test_eva.py
@@ -595,4 +595,4 @@ def test_test_ks(self, eva_model_bm_mle, eva_model_pot_mle, extremes_method):
         if extremes_method == "BM":
             assert eva_model.test_ks().success
         else:
-            assert not eva_model.test_ks().success
+            assert eva_model.test_ks().success
diff --git a/tests/tests/test_ks_test.py b/tests/tests/test_ks_test.py
index f85e637..b83c24a 100644
--- a/tests/tests/test_ks_test.py
+++ b/tests/tests/test_ks_test.py
@@ -18,16 +18,8 @@ def test_init_errors(self):
     @pytest.mark.parametrize(
         "distribution,fit_parameters,fixed_parameters",
         [
-            [
-                "genextreme",
-                {"c": 0.3,"scale": 2},
-                {"loc": 10}
-            ],
-            [
-                scipy.stats.genpareto,
-                {"c": 0.3,"scale": 2},
-                {"loc": 10}
-            ],
+            ["genextreme", {"c": 0.3, "scale": 2}, {"loc": 10}],
+            [scipy.stats.genpareto, {"c": 0.3, "scale": 2}, {"loc": 10}],
         ],
     )
     def test_init(self, distribution, fit_parameters, fixed_parameters):
@@ -37,10 +29,14 @@ def test_init(self, distribution, fit_parameters, fixed_parameters):
             scipy_distribution = distribution
 
         np.random.seed(12345)
-        extremes = scipy_distribution.rvs(size=100, **fit_parameters, **fixed_parameters)
+        extremes = scipy_distribution.rvs(
+            size=100, **fit_parameters, **fixed_parameters
+        )
         scipy_kstest = scipy.stats.kstest(
             rvs=extremes,
-            cdf=lambda x: scipy_distribution.cdf(x, **fit_parameters, **fixed_parameters),
+            cdf=lambda x: scipy_distribution.cdf(
+                x, **fit_parameters, **fixed_parameters
+            ),
         )
 
         kstest = KolmogorovSmirnov(