diff --git a/heat/core/tests/test_signal.py b/heat/core/tests/test_signal.py
index bf5e5d50d1..0c8af0a59e 100644
--- a/heat/core/tests/test_signal.py
+++ b/heat/core/tests/test_signal.py
@@ -101,10 +101,10 @@ def test_convolve2d(self):
         dis_kernel_even = ht.arange(16, split=0).reshape((4, 4)).astype(ht.int)
 
         with self.assertRaises(TypeError):
-            signal_wrong_type = [[0, 1, 2, "tre", 4]]*5
+            signal_wrong_type = [[0, 1, 2, "tre", 4]] * 5
             ht.convolve2d(signal_wrong_type, kernel_odd)
         with self.assertRaises(TypeError):
-            filter_wrong_type = [[ 1, "pizza", "pineapple"]]*3
+            filter_wrong_type = [[1, "pizza", "pineapple"]] * 3
             ht.convolve2d(dis_signal, filter_wrong_type, mode="full")
         with self.assertRaises(ValueError):
             ht.convolve2d(dis_signal, kernel_odd, mode="invalid")
@@ -127,15 +127,21 @@ def test_convolve2d(self):
                 # odd kernel size
                 conv = ht.convolve2d(dis_signal, kernel_odd, mode=mode)
                 gathered = manipulations.resplit(conv, axis=None)
-                self.assertTrue(ht.equal(full_odd[i : len(full_odd) - i, i : len(full_odd) - i], gathered))
+                self.assertTrue(
+                    ht.equal(full_odd[i : len(full_odd) - i, i : len(full_odd) - i], gathered)
+                )
 
                 conv = ht.convolve2d(dis_signal, dis_kernel_odd, mode=mode)
                 gathered = manipulations.resplit(conv, axis=None)
-                self.assertTrue(ht.equal(full_odd[i : len(full_odd) - i, i : len(full_odd) - i], gathered))
+                self.assertTrue(
+                    ht.equal(full_odd[i : len(full_odd) - i, i : len(full_odd) - i], gathered)
+                )
 
                 conv = ht.convolve2d(signal, dis_kernel_odd, mode=mode)
                 gathered = manipulations.resplit(conv, axis=None)
-                self.assertTrue(ht.equal(full_odd[i : len(full_odd) - i, i : len(full_odd) - i], gathered))
+                self.assertTrue(
+                    ht.equal(full_odd[i : len(full_odd) - i, i : len(full_odd) - i], gathered)
+                )
 
                 # different data types
                 conv = ht.convolve2d(dis_signal.astype(ht.float), kernel_odd)
@@ -167,8 +173,8 @@ def test_convolve2d(self):
 
                 # distributed large signal and kernel
                 np.random.seed(12)
-                np_a = np.random.randint(1000, size = (140, 250))
-                np_b = np.random.randint(1000, size = (39, 17))
+                np_a = np.random.randint(1000, size=(140, 250))
+                np_b = np.random.randint(1000, size=(39, 17))
                 sc_conv = sig.convolve2d(np_a, np_b, mode=mode)
 
                 a = ht.array(np_a, split=0, dtype=ht.int32)