Remap coords fix

test/test_remap.py

@@ -265,3 +265,45 @@ def test_b_quadrilateral(gridpath, datasetpath):
     out = uxds['var2'].remap.bilinear(destination_grid=dest)
 
     assert out.size > 0
+
+def test_b_coords_remap_to_faces(gridpath):
+    """Bilinear remap should change the array when remap_to != source."""
+    mesh_path = gridpath("mpas", "QU", "mesh.QU.1920km.151026.nc")
+    uxds = ux.open_dataset(mesh_path, mesh_path)
+    dest = ux.open_grid(gridpath("ugrid", "geoflow-small", "grid.nc"))
+
+    uxda_with_coords = ux.core.UxDataArray(
+        data=uxds["latCell"],
+        uxgrid=uxds.uxgrid,
+        coords={"Mesh2_face_lat": uxds.uxgrid.face_lat,
+                "Mesh_Face_lon": uxds.uxgrid.face_lon,
+                }
+    )
+
+    da_remap_b = uxda_with_coords.remap.bilinear(
+        destination_grid=dest, remap_to="faces"
+    )
+
+    assert (da_remap_b.Mesh_Face_lon.size == dest.face_lon.size)
+    assert np.array_equal(da_remap_b.Mesh_Face_lon.values, dest.face_lon.values)
+
+def test_b_coords_remap_to_nodes(gridpath):
+    """Bilinear remap should change the array when remap_to != source."""
+    mesh_path = gridpath("mpas", "QU", "mesh.QU.1920km.151026.nc")
+    uxds = ux.open_dataset(mesh_path, mesh_path)
+    dest = ux.open_grid(gridpath("ugrid", "geoflow-small", "grid.nc"))
+
+    uxda_with_coords = ux.core.UxDataArray(
+        data=uxds["latCell"],
+        uxgrid=uxds.uxgrid,
+        coords={"Mesh2_face_lat": uxds.uxgrid.face_lat,
+                "Mesh_Face_lon": uxds.uxgrid.face_lon,
+                }
+    )
+
+    da_remap_b = uxda_with_coords.remap.bilinear(
+        destination_grid=dest, remap_to="nodes"
+    )
+
+    assert (da_remap_b.Mesh_Node_lon.size == dest.node_lon.size)
+    assert np.array_equal(da_remap_b.Mesh_Node_lon.values, dest.node_lon.values)

uxarray/conventions/ugrid.py

@@ -84,12 +84,14 @@
     "standard_name": "x",
     "long name": "Cartesian x location of the corner nodes of each face",
     "units": "meters",
+    "axis": "X",
 }
 
 NODE_Y_ATTRS = {
     "standard_name": "y",
     "long name": "Cartesian y location of the corner nodes of each face",
     "units": "meters",
+    "axis": "Y",
 }
 
 NODE_Z_ATTRS = {
@@ -104,12 +106,14 @@
     "standard_name": "x",
     "long name": "Cartesian x location of the center of each edge",
     "units": "meters",
+    "axis": "X",
 }
 
 EDGE_Y_ATTRS = {
     "standard_name": "y",
     "long name": "Cartesian y location of the center of each edge",
     "units": "meters",
+    "axis": "Y",
 }
 
 EDGE_Z_ATTRS = {
@@ -124,12 +128,14 @@
     "standard_name": "x",
     "long name": "Cartesian x location of the center of each face",
     "units": "meters",
+    "axis": "X",
 }
 
 FACE_Y_ATTRS = {
     "standard_name": "y",
     "long name": "Cartesian y location of the center of each face",
     "units": "meters",
+    "axis": "Y",
 }
 
 FACE_Z_ATTRS = {

uxarray/remap/bilinear.py

@@ -29,7 +29,7 @@
 def _bilinear(
     source: UxDataArray | UxDataset,
     destination_grid: Grid,
-    destination_dim: str = "n_face",
+    remap_to: str = "faces",
 ) -> np.ndarray:
     """Bilinear Remapping between two grids, mapping data that resides on the
     corner nodes, edge centers, or face centers on the source grid to the
@@ -39,8 +39,8 @@ def _bilinear(
     ---------
     source_uxda : UxDataArray
         Source UxDataArray
-    remap_to : str, default="nodes"
-        Location of where to map data, either "nodes", "edge centers", or "face centers"
+    remap_to : str, default="faces"
+        Which grid element receives the remapped values, either "nodes", "edges", or "faces"
 
     Returns
     -------
@@ -49,7 +49,7 @@ def _bilinear(
     """
 
     # ensure array is a np.ndarray
-    _assert_dimension(destination_dim)
+    _assert_dimension(remap_to)
 
     # Ensure the destination grid is normalized
     destination_grid.normalize_cartesian_coordinates()
@@ -70,12 +70,12 @@ def _bilinear(
         dual = source.uxgrid.get_dual()
 
         # get destination coordinate pairs
-        point_xyz = _prepare_points(destination_grid, destination_dim)
+        point_xyz = _prepare_points(destination_grid, remap_to)
 
         weights, indices = _barycentric_weights(
             point_xyz=point_xyz,
             dual=dual,
-            data_size=getattr(destination_grid, f"n_{KDTREE_DIM_MAP[destination_dim]}"),
+            data_size=getattr(destination_grid, f"n_{KDTREE_DIM_MAP[remap_to]}"),
             source_grid=ds.uxgrid,
         )
 
@@ -87,8 +87,8 @@ def _bilinear(
             inds, w = indices, weights
 
             # pack indices & weights into tiny DataArrays:
-            indexer = xr.DataArray(inds, dims=[LABEL_TO_COORD[destination_dim], "k"])
-            weight_da = xr.DataArray(w, dims=[LABEL_TO_COORD[destination_dim], "k"])
+            indexer = xr.DataArray(inds, dims=[LABEL_TO_COORD[remap_to], "k"])
+            weight_da = xr.DataArray(w, dims=[LABEL_TO_COORD[remap_to], "k"])
 
             # gather the k neighbor values:
             da_k = da.isel({source_dim: indexer}, ignore_grid=True)
@@ -103,7 +103,7 @@ def _bilinear(
             remapped_vars[name] = da
 
     ds_remapped = _construct_remapped_ds(
-        source, remapped_vars, destination_grid, destination_dim
+        source, remapped_vars, destination_grid, remap_to
     )
 
     return ds_remapped[name] if is_da else ds_remapped

uxarray/remap/inverse_distance_weighted.py

@@ -52,7 +52,7 @@ def _idw_weights(distances, power):
 def _inverse_distance_weighted_remap(
     source: UxDataArray | UxDataset,
     destination_grid: Grid,
-    destination_dim: str = "n_face",
+    remap_to: str = "faces",
     power: int = 2,
     k: int = 8,
 ):
@@ -68,8 +68,8 @@ def _inverse_distance_weighted_remap(
         The data to be remapped.
     destination_grid : Grid
         The UXarray grid instance on which to interpolate data.
-    destination_dim : {'n_node', 'n_edge', 'n_face'}, default='n_face'
-        The spatial dimension on `destination_grid` to receive interpolated values.
+    remap_to : {'nodes', 'edges', 'faces'}, default='faces'
+        Which grid element receives the remapped values, either "nodes", "edges", or "faces"
     power : int, default=2
         Exponent in the inverse-distance weighting function. Larger values
         emphasize closer neighbors.
@@ -88,9 +88,9 @@ def _inverse_distance_weighted_remap(
     """
     # Fall back onto nearest neighbor
     if k == 1:
-        return _nearest_neighbor_remap(source, destination_grid, destination_dim)
+        return _nearest_neighbor_remap(source, destination_grid, remap_to)
 
-    _assert_dimension(destination_dim)
+    _assert_dimension(remap_to)
 
     # Perform remapping on a UxDataset
     ds, is_da, name = _to_dataset(source)
@@ -106,7 +106,7 @@ def _inverse_distance_weighted_remap(
             ds.uxgrid,
             destination_grid,
             src_dim,
-            destination_dim,
+            remap_to,
             k=k,
             return_distances=True,
         )
@@ -123,8 +123,8 @@ def _inverse_distance_weighted_remap(
             inds, w = indices_weights_map[source_dim]
 
             # pack indices & weights into tiny DataArrays:
-            indexer = xr.DataArray(inds, dims=[LABEL_TO_COORD[destination_dim], "k"])
-            weight_da = xr.DataArray(w, dims=[LABEL_TO_COORD[destination_dim], "k"])
+            indexer = xr.DataArray(inds, dims=[LABEL_TO_COORD[remap_to], "k"])
+            weight_da = xr.DataArray(w, dims=[LABEL_TO_COORD[remap_to], "k"])
 
             # gather the k neighbor values:
             da_k = da.isel({source_dim: indexer}, ignore_grid=True)
@@ -139,7 +139,7 @@ def _inverse_distance_weighted_remap(
             remapped_vars[name] = da
 
     ds_remapped = _construct_remapped_ds(
-        source, remapped_vars, destination_grid, destination_dim
+        source, remapped_vars, destination_grid, remap_to
     )
 
     return ds_remapped[name] if is_da else ds_remapped

uxarray/remap/nearest_neighbor.py

@@ -75,7 +75,7 @@ def _nearest_neighbor_query(
 def _nearest_neighbor_remap(
     source: UxDataArray | UxDataset,
     destination_grid: Grid,
-    destination_dim: str = "n_face",
+    remap_to: str = "faces",
 ):
     """
     Apply nearest-neighbor remapping from a UXarray object onto another grid.
@@ -88,15 +88,15 @@ def _nearest_neighbor_remap(
         The data array or dataset to be remapped.
     destination_grid : Grid
         The UXarray Grid instance to which data will be remapped.
-    destination_dim : str, default='n_face'
-        The spatial dimension on the destination grid ('n_node', 'n_edge', 'n_face').
+    remap_to : str, default='faces'
+        Which grid element receives the remapped values, either 'nodes', 'edges', 'faces').
 
     Returns
     -------
     UxDataArray or UxDataset
         A new UXarray object with data values assigned to `destination_grid`.
     """
-    _assert_dimension(destination_dim)
+    _assert_dimension(remap_to)
 
     # Perform remapping on a UxDataset
     ds, is_da, name = _to_dataset(source)
@@ -106,9 +106,7 @@ def _nearest_neighbor_remap(
 
     # Build Nearest Neighbor Index Arrays
     indices_map: dict[str, np.ndarray] = {
-        src_dim: _nearest_neighbor_query(
-            ds.uxgrid, destination_grid, src_dim, destination_dim
-        )
+        src_dim: _nearest_neighbor_query(ds.uxgrid, destination_grid, src_dim, remap_to)
         for src_dim in dims_to_remap
     }
     remapped_vars = {}
@@ -122,7 +120,7 @@ def _nearest_neighbor_remap(
             indexer = xr.DataArray(
                 indices,
                 dims=[
-                    LABEL_TO_COORD[destination_dim],
+                    LABEL_TO_COORD[remap_to],
                 ],
             )
 
@@ -134,7 +132,7 @@ def _nearest_neighbor_remap(
             remapped_vars[name] = da
 
     ds_remapped = _construct_remapped_ds(
-        source, remapped_vars, destination_grid, destination_dim
+        source, remapped_vars, destination_grid, remap_to
     )
 
     return ds_remapped[name] if is_da else ds_remapped