diff --git a/pysindy/utils/base.py b/pysindy/utils/base.py
index cc1733b3..6e80accb 100644
--- a/pysindy/utils/base.py
+++ b/pysindy/utils/base.py
@@ -163,15 +163,11 @@ def wrapper(x, regularization_weight):
             weight_shape = regularization_weight.shape
             if weight_shape != x.shape:
                 raise ValueError(
-                    f"Invalid shape for 'regularization_weight': \
-                        {weight_shape}. Must be the same shape as x: {x.shape}."
+                    f"Invalid shape for 'regularization_weight':"
+                    f"{weight_shape}. Must be the same shape as x: {x.shape}."
                 )
-        else:
-            if not isinstance(regularization_weight, (int, float)) and (
-                isinstance(regularization_weight, np.ndarray)
-                and regularization_weight.shape not in [(1, 1), (1,)]
-            ):
-                raise ValueError("'regularization_weight' must be a scalar")
+        elif not isinstance(regularization_weight, (int, float)):
+            raise ValueError("'regularization_weight' must be a scalar")
         return func(x, regularization_weight)
 
     return wrapper
diff --git a/test/utils/test_utils.py b/test/utils/test_utils.py
index 3ae24ed7..311fe949 100644
--- a/test/utils/test_utils.py
+++ b/test/utils/test_utils.py
@@ -83,35 +83,16 @@ def test_get_regularization(regularization, lam, expected):
     assert result == expected
 
 
-@pytest.mark.parametrize("regularization", ["l0", "l1", "l2"])
-@pytest.mark.parametrize("lam", [1, np.array([1]), np.array([[1]])])
-def test_get_prox_and_regularization_shape(regularization, lam):
-    data = np.array([[-2, 5]]).T
-    reg = get_regularization(regularization)
-    reg_result = reg(data, lam)
-    prox = get_prox(regularization)
-    prox_result = prox(data, lam)
-    assert reg_result is not None
-    assert prox_result is not None
-
-
-@pytest.mark.parametrize(
-    "regularization", ["weighted_l0", "weighted_l1", "weighted_l2"]
-)
-@pytest.mark.parametrize("lam", [np.array([[1, 2]]).T])
-def test_get_weighted_prox_and_regularization_shape(regularization, lam):
-    data = np.array([[-2, 5]]).T
-    reg = get_regularization(regularization)
-    reg_result = reg(data, lam)
-    prox = get_prox(regularization)
-    prox_result = prox(data, lam)
-    assert reg_result is not None
-    assert prox_result is not None
-
-
 @pytest.mark.parametrize("regularization", ["l0", "l1", "l2"])
 @pytest.mark.parametrize(
-    "lam", [np.array([[1, 2]]), np.array([1, 2]), np.array([[1, 2]]).T]
+    "lam",
+    [
+        np.array([[1, 2]]),
+        np.array([1, 2]),
+        np.array([[1, 2]]).T,
+        np.array([1]),
+        np.array([[1]]),
+    ],
 )
 def test_get_prox_and_regularization_bad_shape(regularization, lam):
     data = np.array([[-2, 5]]).T
@@ -127,7 +108,15 @@ def test_get_prox_and_regularization_bad_shape(regularization, lam):
     "regularization", ["weighted_l0", "weighted_l1", "weighted_l2"]
 )
 @pytest.mark.parametrize(
-    "lam", [np.array([[1, 2]]), np.array([1, 2, 3]), np.array([[1, 2, 3]]).T, 1]
+    "lam",
+    [
+        np.array([[1, 2]]),
+        np.array([1, 2, 3]),
+        np.array([[1, 2, 3]]).T,
+        1,
+        np.array([1]),
+        np.array([[1]]),
+    ],
 )
 def test_get_weighted_prox_and_regularization_bad_shape(regularization, lam):
     data = np.array([[-2, 5]]).T