use geovista.common.VTK_CELL_IDS (#1299)

src/geovista/common.py

@@ -443,7 +443,7 @@ def from_cartesian(
             pole_submesh = mesh.extract_points(pole_pids)
             pole_pids = set(pole_pids)
             # get the cids (cell-indices) of mesh cells with polar vertices
-            pole_cids = np.unique(pole_submesh["vtkOriginalCellIds"])
+            pole_cids = np.unique(pole_submesh[VTK_CELL_IDS])
             for cid in pole_cids:
                 # get the pids (point-indices) of the polar cell points
                 # NOTE: pyvista 0.38.0: cell_point_ids(cid) -> get_cell(cid).point_ids
@@ -496,8 +496,7 @@ def from_cartesian(
                     mesh.extract_points(poi_pids)
                 )
                 cell_pids = [
-                    mesh.get_cell(cid).point_ids
-                    for cid in poi_cells["vtkOriginalCellIds"]
+                    mesh.get_cell(cid).point_ids for cid in poi_cells[VTK_CELL_IDS]
                 ]
                 mask_positive = lons[cell_pids] > 0
                 if np.any(mask_positive):

src/geovista/search.py

@@ -19,7 +19,7 @@
 
 import lazy_loader as lazy
 
-from .common import MixinStrEnum, to_cartesian
+from .common import VTK_CELL_IDS, MixinStrEnum, to_cartesian
 from .crs import WGS84, from_wkt
 from .transform import transform_points
 
@@ -350,7 +350,7 @@ def find_cell_neighbours(mesh: pv.PolyData, cid: CellIDLike) -> CellIDs:
     # determine the unique points
     pids = np.unique(list(pids))
     # get the cell-ids of cells containing at least one common point
-    result = set(mesh.extract_points(pids)["vtkOriginalCellIds"])
+    result = set(mesh.extract_points(pids)[VTK_CELL_IDS])
     # remove the original cell/s
     result -= set(cid)
 
@@ -412,7 +412,7 @@ def find_nearest_cell(
 
     if poi_is_vertex:
         pid = pids[mask][0]
-        result = sorted(mesh.extract_points(pid)["vtkOriginalCellIds"])
+        result = sorted(mesh.extract_points(pid)[VTK_CELL_IDS])
     else:
         result = [cid]