Pick coordinates from full dataset in convert.*_to_sgird funcs

docs/user_guide/examples/tutorial_croco_3D.ipynb

@@ -59,7 +59,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we create a FieldSet object using the `FieldSet.from_croco()` method. Note that CROCO is a C-grid (with similar indexing at MITgcm)."
+    "Now we create a FieldSet object using the `convert.croco_to_sgrid()` function to first create an S-Grid compliant datatset, and then use that in  `FieldSet.from_sgrid_conventions()` to create the FieldSet."
    ]
   },
   {
@@ -86,8 +86,7 @@
     "    \"Cs_w\": ds_fields[\"Cs_w\"],\n",
     "}\n",
     "\n",
-    "coords = ds_fields[[\"x_rho\", \"y_rho\", \"s_w\", \"time\"]]\n",
-    "ds_fset = parcels.convert.croco_to_sgrid(fields=fields, coords=coords)\n",
+    "ds_fset = parcels.convert.croco_to_sgrid(fields=fields, coords=ds_fields)\n",
     "\n",
     "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)\n",
     "\n",

docs/user_guide/examples/tutorial_mitgcm.ipynb

@@ -38,11 +38,7 @@
    "id": "3",
    "metadata": {},
    "source": [
-    "We can use a combination of `parcels.convert.mitgcm_to_sgrid` and `FieldSet.from_sgrid_conventions` to read in the data. See below for an example.\n",
-    "\n",
-    "```{note}\n",
-    "It is very important that you provide the corner nodes as coordinates when converting MITgcm data to S-grid conventions. These corner nodes are typically called `XG` and `YG` in MITgcm output. Failing to do so will lead to incorrect interpolation of the velocity fields.\n",
-    "```"
+    "We can use a combination of `parcels.convert.mitgcm_to_sgrid` and `FieldSet.from_sgrid_conventions` to read in the data. See below for an example."
    ]
   },
   {
@@ -52,9 +48,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "coords = ds_fields[[\"XG\", \"YG\", \"Zl\", \"time\"]]\n",
     "ds_fset = parcels.convert.mitgcm_to_sgrid(\n",
-    "    fields={\"U\": ds_fields.UVEL, \"V\": ds_fields.VVEL}, coords=coords\n",
+    "    fields={\"U\": ds_fields.UVEL, \"V\": ds_fields.VVEL}, coords=ds_fields\n",
     ")\n",
     "fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)"
    ]

docs/user_guide/examples/tutorial_nemo.ipynb

@@ -369,7 +369,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "parcels",
+   "display_name": "docs",
    "language": "python",
    "name": "python3"
   },
@@ -383,7 +383,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.14.2"
   }
  },
  "nbformat": 4,

src/parcels/convert.py

@@ -23,6 +23,8 @@
 if typing.TYPE_CHECKING:
     import uxarray as ux
 
+_NEMO_EXPECTED_COORDS = ["glamf", "gphif"]
+
 _NEMO_DIMENSION_COORD_NAMES = ["x", "y", "time", "x", "x_center", "y", "y_center", "depth", "glamf", "gphif"]
 
 _NEMO_AXIS_VARNAMES = {
@@ -42,6 +44,8 @@
     "wo": "W",
 }
 
+_MITGCM_EXPECTED_COORDS = ["XG", "YG", "Zl"]
+
 _MITGCM_AXIS_VARNAMES = {
     "XC": "X",
     "XG": "X",
@@ -70,13 +74,25 @@
     "T": "time",
 }
 
+_CROCO_EXPECTED_COORDS = ["x_rho", "y_rho", "s_w", "time"]
+
 _CROCO_VARNAMES_MAPPING = {
     "x_rho": "lon",
     "y_rho": "lat",
     "s_w": "depth",
 }
 
 
+def _pick_expected_coords(coords: xr.Dataset, expected_coord_names: list[str]) -> xr.Dataset:
+    coords_to_use = {}
+    for name in expected_coord_names:
+        if name in coords:
+            coords_to_use[name] = coords[name]
+        else:
+            raise ValueError(f"Expected coordinate '{name}' not found in provided coords dataset.")
+    return xr.Dataset(coords_to_use)
+
+
 def _maybe_bring_UV_depths_to_depth(ds):
     if "U" in ds.variables and "depthu" in ds.U.coords and "depth" in ds.coords:
         ds["U"] = ds["U"].assign_coords(depthu=ds["depth"].values).rename({"depthu": "depth"})
@@ -245,7 +261,7 @@ def nemo_to_sgrid(*, fields: dict[str, xr.Dataset | xr.DataArray], coords: xr.Da
 
     """
     fields = fields.copy()
-    coords = coords[["gphif", "glamf"]]
+    coords = _pick_expected_coords(coords, _NEMO_EXPECTED_COORDS)
 
     for name, field_da in fields.items():
         if isinstance(field_da, xr.Dataset):
@@ -357,6 +373,8 @@ def mitgcm_to_sgrid(*, fields: dict[str, xr.Dataset | xr.DataArray], coords: xr.
             field_da = field_da.rename(name)
         fields[name] = field_da
 
+    coords = _pick_expected_coords(coords, _MITGCM_EXPECTED_COORDS)
+
     ds = xr.merge(list(fields.values()) + [coords])
     ds.attrs.clear()  # Clear global attributes from the merging
 
@@ -417,6 +435,8 @@ def croco_to_sgrid(*, fields: dict[str, xr.Dataset | xr.DataArray], coords: xr.D
             field_da = field_da.rename(name)
         fields[name] = field_da
 
+    coords = _pick_expected_coords(coords, _CROCO_EXPECTED_COORDS)
+
     ds = xr.merge(list(fields.values()) + [coords])
     ds.attrs.clear()  # Clear global attributes from the merging
 

tests/test_advection.py

@@ -508,8 +508,7 @@ def test_mitgcm():
     data_folder = parcels.download_example_dataset("MITgcm_example_data")
     ds_fields = xr.open_dataset(data_folder / "mitgcm_UV_surface_zonally_reentrant.nc")
 
-    coords = ds_fields[["XG", "YG", "Zl", "time"]]
-    ds_fset = convert.mitgcm_to_sgrid(fields={"U": ds_fields.UVEL, "V": ds_fields.VVEL}, coords=coords)
+    ds_fset = convert.mitgcm_to_sgrid(fields={"U": ds_fields.UVEL, "V": ds_fields.VVEL}, coords=ds_fields)
     fieldset = FieldSet.from_sgrid_conventions(ds_fset)
 
     npart = 10

tests/test_sigmagrids.py

@@ -28,8 +28,7 @@ def test_conversion_3DCROCO():
         "Cs_w": ds_fields["Cs_w"],
     }
 
-    coords = ds_fields[["x_rho", "y_rho", "s_w", "time"]]
-    ds_fset = parcels.convert.croco_to_sgrid(fields=fields, coords=coords)
+    ds_fset = parcels.convert.croco_to_sgrid(fields=fields, coords=ds_fields)
 
     fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
     fieldset.add_constant("hc", ds_fields.hc.item())
@@ -61,8 +60,7 @@ def test_advection_3DCROCO():
         "omega": ds_fields["omega"],
     }
 
-    coords = ds_fields[["x_rho", "y_rho", "s_w", "time"]]
-    ds_fset = parcels.convert.croco_to_sgrid(fields=fields, coords=coords)
+    ds_fset = parcels.convert.croco_to_sgrid(fields=fields, coords=ds_fields)
 
     fieldset = parcels.FieldSet.from_sgrid_conventions(ds_fset)
     fieldset.add_constant("hc", ds_fields.hc.item())