diff --git a/pystencils/fd/derivation.py b/pystencils/fd/derivation.py
index 5e77fcdfb2fd0e9bc09a4d35b55083898c328e01..5a9d79e8fe4038a090c8da84507747ed97633b86 100644
--- a/pystencils/fd/derivation.py
+++ b/pystencils/fd/derivation.py
@@ -340,4 +340,10 @@ class FiniteDifferenceStaggeredStencilDerivation:
         plot(pts, data=ws)
 
     def apply(self, field):
-        return sum([field.__getitem__(point) * weight for point, weight in zip(self.points, self.weights)])
+        if field.index_dimensions == 0:
+            return sum([field.__getitem__(point) * weight for point, weight in zip(self.points, self.weights)])
+        else:
+            total = field.neighbor_vector(self.points[0]) * self.weights[0]
+            for point, weight in zip(self.points[1:], self.weights[1:]):
+                total += field.neighbor_vector(point) * weight
+            return total
diff --git a/pystencils/field.py b/pystencils/field.py
index 6b3fa9f8c4c5fa21cd799fc9ff37d090224794af..dfe71c692ecf307753459fb219431c977546f3c6 100644
--- a/pystencils/field.py
+++ b/pystencils/field.py
@@ -441,6 +441,22 @@ class Field(AbstractField):
         center = tuple([0] * self.spatial_dimensions)
         return Field.Access(self, center)
 
+    def neighbor_vector(self, offset):
+        """Like neighbor, but returns the entire vector/tensor stored at offset."""
+        if self.spatial_dimensions == 2 and len(offset) == 3:
+            assert offset[2] == 0
+            offset = offset[:2]
+
+        if self.index_dimensions == 0:
+            return sp.Matrix([self.__getitem__(offset)])
+        elif self.index_dimensions == 1:
+            return sp.Matrix([self.__getitem__(offset)(i) for i in range(self.index_shape[0])])
+        elif self.index_dimensions == 2:
+            return sp.Matrix([[self.__getitem__(offset)(i, k) for k in range(self.index_shape[1])]
+                             for i in range(self.index_shape[0])])
+        else:
+            raise NotImplementedError("neighbor_vector is not implemented for more than 2 index dimensions")
+
     def __getitem__(self, offset):
         if type(offset) is np.ndarray:
             offset = tuple(offset)
diff --git a/pystencils_tests/test_fd_derivation.ipynb b/pystencils_tests/test_fd_derivation.ipynb
index 95568cf2c0c07e36d667ef196e7b0dd3bb04f790..f992c8ac5051dd83553cb7da3e6842c9be1aa8c3 100644
--- a/pystencils_tests/test_fd_derivation.ipynb
+++ b/pystencils_tests/test_fd_derivation.ipynb
@@ -153,7 +153,7 @@
      "data": {
       "image/png": "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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f05740f2470>"
+       "<matplotlib.figure.Figure at 0x7f06c885ccf8>"
       ]
      },
      "metadata": {},
@@ -332,8 +332,10 @@
     "assert FiniteDifferenceStaggeredStencilDerivation(\"T\", 3, (2,)).apply(c3) == c3[0, 0, 1] - c3[0, 0, 0]\n",
     "assert FiniteDifferenceStaggeredStencilDerivation(\"B\", 3, (2,)).apply(c3) == c3[0, 0, 0] - c3[0, 0, -1]\n",
     "\n",
-    "assert FiniteDifferenceStaggeredStencilDerivation(\"NE\", 2, (0,)).apply(c) + FiniteDifferenceStaggeredStencilDerivation(\"NE\", 2, (1,)).apply(c) == c[1, 1] - c[0, 0]\n",
-    "assert FiniteDifferenceStaggeredStencilDerivation(\"NE\", 3, (0,)).apply(c3) + FiniteDifferenceStaggeredStencilDerivation(\"NE\", 3, (1,)).apply(c3) == c3[1, 1, 0] - c3[0, 0, 0]"
+    "assert FiniteDifferenceStaggeredStencilDerivation(\"NE\", 2, (0,)).apply(c) + \\\n",
+    "       FiniteDifferenceStaggeredStencilDerivation(\"NE\", 2, (1,)).apply(c) == c[1, 1] - c[0, 0]\n",
+    "assert FiniteDifferenceStaggeredStencilDerivation(\"NE\", 3, (0,)).apply(c3) + \\\n",
+    "       FiniteDifferenceStaggeredStencilDerivation(\"NE\", 3, (1,)).apply(c3) == c3[1, 1, 0] - c3[0, 0, 0]"
    ]
   },
   {
@@ -345,7 +347,7 @@
      "data": {
       "image/png": 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\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f0571eccd68>"
+       "<matplotlib.figure.Figure at 0x7f06c669c898>"
       ]
      },
      "metadata": {},
@@ -353,7 +355,20 @@
     }
    ],
    "source": [
-    "FiniteDifferenceStaggeredStencilDerivation(\"NE\", 2, (0, 1)).visualize()"
+    "d = FiniteDifferenceStaggeredStencilDerivation(\"NE\", 2, (0, 1))\n",
+    "assert d.apply(c) == c[0,0] + c[1,1] - c[1,0] - c[0,1]\n",
+    "d.visualize()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "v3 = ps.fields(\"v(3): [3D]\")\n",
+    "assert FiniteDifferenceStaggeredStencilDerivation(\"E\", 3, (0,)).apply(v3) == \\\n",
+    "       sp.Matrix([v3[1,0,0](i) - v3[0,0,0](i) for i in range(*v3.index_shape)])"
    ]
   },
   {