Confirm outdated review comment on _parse_network_input is no longer applicable

src/modelskill/comparison/_comparison.py

@@ -27,7 +27,7 @@
 from .. import Quantity
 from ..types import GeometryType
 from ..obs import PointObservation, TrackObservation, NodeObservation
-from ..model import PointModelResult, TrackModelResult, NetworkModelResult
+from ..model import PointModelResult, TrackModelResult
 from ..timeseries._timeseries import _validate_data_var_name
 from ._comparer_plotter import ComparerPlotter
 from ..metrics import _parse_metric
@@ -461,7 +461,7 @@ def __init__(
         matched_data: xr.Dataset,
         raw_mod_data: dict[
             str,
-            PointModelResult | TrackModelResult | NetworkModelResult | NodeModelResult,
+            PointModelResult | TrackModelResult | NodeModelResult,
         ]
         | None = None,
     ) -> None:
@@ -488,7 +488,6 @@ def from_matched_data(
                 str,
                 PointModelResult
                 | TrackModelResult
-                | NetworkModelResult
                 | NodeModelResult,
             ]
         ] = None,
@@ -784,7 +783,7 @@ def _to_observation(self) -> PointObservation | TrackObservation | NodeObservati
         else:
             raise NotImplementedError(f"Unknown gtype: {self.gtype}")
 
-    def _to_model(self) -> list[PointModelResult | TrackModelResult]:
+    def _to_model(self) -> list[PointModelResult | TrackModelResult | NodeModelResult]:
         mods = list(self.raw_mod_data.values())
         return mods
 
@@ -1314,7 +1313,7 @@ def load(filename: Union[str, Path]) -> "Comparer":
 
         if data.gtype == "point":
             raw_mod_data: Dict[
-                str, PointModelResult | TrackModelResult | NetworkModelResult
+                str, PointModelResult | TrackModelResult | NodeModelResult
             ] = {}
 
             for var in data.data_vars:

src/modelskill/matching.py

@@ -11,6 +11,7 @@
     Sequence,
     TypeVar,
     Union,
+    cast,
     get_args,
     overload,
 )
@@ -350,17 +351,20 @@ def _match_single_obs(
     if len(names) != len(set(names)):
         raise ValueError(f"Duplicate model names found: {names}")
 
-    raw_mod_data = {}
+    raw_mod_data: dict[str, PointModelResult | TrackModelResult | NodeModelResult] = {}
     for m in models:
         if isinstance(m, (DfsuModelResult, GridModelResult, DummyModelResult)):
             # These model types support spatial interpolation
-            extracted = m.extract(obs, spatial_method=spatial_method)
+            extracted: PointModelResult | TrackModelResult | NodeModelResult = m.extract(
+                cast(PointObservation | TrackObservation, obs),
+                spatial_method=spatial_method,
+            )
         elif isinstance(m, NetworkModelResult):
             # Network models use exact node selection (no spatial interpolation)
-            extracted = m.extract(obs)
+            extracted = m.extract(cast(NodeObservation, obs))
         else:
-            # Other model types (e.g., already extracted TimeSeries)
-            extracted = m
+            # Other model types (already point/track timeseries - no extraction needed)
+            extracted = cast(PointModelResult | TrackModelResult, m)
 
         raw_mod_data[m.name] = extracted
 

src/modelskill/model/network.py

@@ -8,7 +8,7 @@
 from modelskill.obs import Observation
 from modelskill.timeseries import TimeSeries, _parse_network_node_input
 
-from ._base import SpatialField, _validate_overlap_in_time, SelectedItems
+from ._base import _validate_overlap_in_time, SelectedItems
 from ..obs import NodeObservation
 from ..quantity import Quantity
 from ..types import PointType
@@ -74,6 +74,8 @@ def __init__(
     def node(self) -> int:
         """Node ID of model result"""
         node_val = self.data.coords.get("node")
+        if node_val is None:
+            raise ValueError("No node coordinate found in data")
         return int(node_val.item())
 
     def interp_time(self, observation: Observation, **kwargs: Any) -> NodeModelResult:
@@ -155,7 +157,7 @@ def _get_valid_times(
         return df[valid_idx].index
 
 
-class NetworkModelResult(SpatialField):
+class NetworkModelResult:
     """Model result for network data with time and node dimensions.
 
     Construct a NetworkModelResult from an xarray.Dataset with time and node coordinates

src/modelskill/obs.py

@@ -408,7 +408,7 @@ def __init__(
         super().__init__(data=data, weight=weight, attrs=attrs)
 
     @property
-    def node(self) -> int:
+    def node(self) -> Optional[int]:
         """Node ID of observation"""
         node_val = self.data.coords.get("node")
         if node_val is not None:
@@ -509,7 +509,7 @@ def __iter__(self):
     @property
     def nodes(self) -> list[int]:
         """List of node IDs for all observations"""
-        return [obs.node for obs in self.observations]
+        return [obs.node for obs in self.observations if obs.node is not None]
 
     @property
     def names(self) -> list[str]: