Remove _to_observation and _to_model from Comparer

src/modelskill/comparison/_collection_plotter.py

@@ -804,10 +804,9 @@ def spatial_overview(
         """
         from ..plotting import spatial_overview
 
-        obs = [cmp._to_observation() for cmp in self.cc]
         # TODO how to add model domain(s)
 
-        return spatial_overview(obs, ax=ax, figsize=figsize, title=title)
+        return spatial_overview(self.cc, ax=ax, figsize=figsize, title=title)
 
     def temporal_coverage(
         self,
@@ -835,11 +834,10 @@ def temporal_coverage(
         """
         from ..plotting import temporal_coverage
 
-        obs = [cmp._to_observation() for cmp in self.cc]
-        mod = self.cc[0]._to_model()
+        mod = list(self.cc[0].raw_mod_data.values())
 
         return temporal_coverage(
-            obs=obs,
+            obs=list(self.cc),
             mod=mod,
             limit_to_model_period=limit_to_model_period,
             marker=marker,

src/modelskill/comparison/_comparison.py

@@ -24,7 +24,6 @@
 from .. import metrics as mtr
 from .. import Quantity
 from ..types import GeometryType
-from ..obs import PointObservation, TrackObservation
 from ..model import PointModelResult, TrackModelResult
 from ..timeseries._timeseries import _validate_data_var_name
 from ._comparer_plotter import ComparerPlotter
@@ -707,37 +706,6 @@ def rename(
 
         return Comparer(matched_data=data, raw_mod_data=raw_mod_data)
 
-    def _to_observation(self) -> PointObservation | TrackObservation:
-        """Convert to Observation"""
-        if self.gtype == "point":
-            df = self.data.drop_vars(["x", "y", "z"])[self._obs_str].to_dataframe()
-            return PointObservation(
-                data=df,
-                name=self.name,
-                x=self.x,
-                y=self.y,
-                z=self.z,
-                quantity=self.quantity,
-                # TODO: add attrs
-            )
-        elif self.gtype == "track":
-            df = self.data.drop_vars(["z"])[[self._obs_str]].to_dataframe()
-            return TrackObservation(
-                data=df,
-                item=0,
-                x_item=1,
-                y_item=2,
-                name=self.name,
-                quantity=self.quantity,
-                # TODO: add attrs
-            )
-        else:
-            raise NotImplementedError(f"Unknown gtype: {self.gtype}")
-
-    def _to_model(self) -> list[PointModelResult | TrackModelResult]:
-        mods = list(self.raw_mod_data.values())
-        return mods
-
     def __add__(self, other):
         warnings.warn(
             "Merging comparers using + is deprecated, use .merge instead.",

src/modelskill/plotting/_spatial_overview.py

@@ -1,5 +1,5 @@
 from __future__ import annotations
-from typing import Optional, Iterable, Tuple, TYPE_CHECKING
+from typing import Optional, Iterable, Protocol, Tuple, TYPE_CHECKING
 
 if TYPE_CHECKING:
     import matplotlib.axes
@@ -8,12 +8,26 @@
 
 from ..model.point import PointModelResult
 from ..model.track import TrackModelResult
-from ..obs import Observation, PointObservation, TrackObservation
 from ._misc import _get_ax
 
 
+class SpatialOverviewItem(Protocol):
+    """Protocol for items that can be plotted in spatial_overview."""
+
+    @property
+    def gtype(self) -> str: ...
+    @property
+    def x(self): ...
+    @property
+    def y(self): ...
+    @property
+    def name(self) -> str: ...
+    @property
+    def n_points(self) -> int: ...
+
+
 def spatial_overview(
-    obs: Observation | Iterable[Observation],
+    obs: SpatialOverviewItem | Iterable[SpatialOverviewItem],
     mod: Optional[
         DfsuModelResult
         | GeometryFM2D
@@ -82,24 +96,24 @@ def spatial_overview(
         g.plot.outline(ax=ax)  # type: ignore
 
     for o in obs:
-        if isinstance(o, PointObservation):
+        if o.gtype == "point":
             ax.scatter(x=o.x, y=o.y, marker="x")
-        elif isinstance(o, TrackObservation):
+        elif o.gtype == "track":
             if o.n_points < 10000:
                 ax.scatter(x=o.x, y=o.y, marker=".")
             else:
                 print(f"{o.name}: Too many points to plot")
                 # TODO: group by lonlat bin or sample randomly
         else:
             raise ValueError(
-                f"Could not show observation {o}. Only PointObservation and TrackObservation supported."
+                f"Could not show {o}. Only point and track geometry types supported."
             )
 
     xlim = ax.get_xlim()
     offset_x = 0.02 * (xlim[1] - xlim[0])
 
     for o in obs:
-        if isinstance(o, PointObservation):
+        if o.gtype == "point":
             # TODO adjust xlim to accomodate text
             ax.annotate(o.name, (o.x + offset_x, o.y))  # type: ignore