Have a dedicated neighborhood property and a get_neighborhood method on Cell

mesa/experimental/cell_space/cell.py

@@ -131,10 +131,34 @@ def is_full(self) -> bool:
     def __repr__(self):  # noqa
         return f"Cell({self.coordinate}, {self.agents})"
 
+    @property
+    @cache
+    def neighborhood(self) -> CellCollection:
+        """Returns the direct neigborhood of the cell
+
+        This is equivalent to cell.get_neighborhood(radius=1)
+
+        """
+        return self.get_neighborhood(radius=1)
+
     # FIXME: Revisit caching strategy on methods
     @cache  # noqa: B019
-    def neighborhood(self, radius: int = 1, include_center: bool = False):
-        """Returns a list of all neighboring cells."""
+    def get_neighborhood(
+        self, radius: int = 1, include_center: bool = False
+    ) -> CellCollection:
+        """Returns a list of all neighboring cells for the given radius
+
+        For getting the direct neighborhood (i.e., radius=1) you can also use
+        the `neighborhood` property.
+
+        Args:
+            radius (int): the radius of the neighborhood
+            include_center (bool): include the center of the neighborhood
+
+        Returns:
+            a list of all neighboring cells
+
+        """
         return CellCollection[Cell](
             self._neighborhood(radius=radius, include_center=include_center),
             random=self.random,

tests/test_cell_space.py

@@ -280,33 +280,45 @@ def test_cell_neighborhood():
     height = 10
     grid = OrthogonalVonNeumannGrid((width, height), torus=False, capacity=None)
     for radius, n in zip(range(1, 4), [2, 5, 9]):
-        neighborhood = grid._cells[(0, 0)].neighborhood(radius=radius)
+        if radius == 1:
+            neighborhood = grid._cells[(0, 0)].neighborhood
+        else:
+            neighborhood = grid._cells[(0, 0)].get_neighborhood(radius=radius)
         assert len(neighborhood) == n
 
     ## Moore
     width = 10
     height = 10
     grid = OrthogonalMooreGrid((width, height), torus=False, capacity=None)
     for radius, n in zip(range(1, 4), [3, 8, 15]):
-        neighborhood = grid._cells[(0, 0)].neighborhood(radius=radius)
+        if radius == 1:
+            neighborhood = grid._cells[(0, 0)].neighborhood
+        else:
+            neighborhood = grid._cells[(0, 0)].get_neighborhood(radius=radius)
         assert len(neighborhood) == n
 
     with pytest.raises(ValueError):
-        grid._cells[(0, 0)].neighborhood(radius=0)
+        grid._cells[(0, 0)].get_neighborhood(radius=0)
 
     # hexgrid
     width = 10
     height = 10
     grid = HexGrid((width, height), torus=False, capacity=None)
     for radius, n in zip(range(1, 4), [2, 6, 11]):
-        neighborhood = grid._cells[(0, 0)].neighborhood(radius=radius)
+        if radius == 1:
+            neighborhood = grid._cells[(0, 0)].neighborhood
+        else:
+            neighborhood = grid._cells[(0, 0)].get_neighborhood(radius=radius)
         assert len(neighborhood) == n
 
     width = 10
     height = 10
     grid = HexGrid((width, height), torus=False, capacity=None)
     for radius, n in zip(range(1, 4), [5, 10, 17]):
-        neighborhood = grid._cells[(1, 0)].neighborhood(radius=radius)
+        if radius == 1:
+            neighborhood = grid._cells[(1, 0)].neighborhood
+        else:
+            neighborhood = grid._cells[(1, 0)].get_neighborhood(radius=radius)
         assert len(neighborhood) == n
 
     # networkgrid