Add support for network model results (Res1d)

pyproject.toml

@@ -49,7 +49,7 @@ dev = [
     "quarto-cli==1.5.57",
     "quartodoc==0.11.1",
     "netCDF4",
-    "dask",
+    "mikeio1d>=1.1.1",
 ]
 
 test = [

src/modelskill/__init__.py

@@ -39,8 +39,14 @@
     GridModelResult,
     DfsuModelResult,
     DummyModelResult,
+    NetworkModelResult,
+)
+from .obs import (
+    observation,
+    PointObservation,
+    TrackObservation,
+    NetworkLocationObservation,
 )
-from .obs import observation, PointObservation, TrackObservation
 from .matching import from_matched, match
 from .configuration import from_config
 from .settings import options, get_option, set_option, reset_option, load_style
@@ -90,8 +96,10 @@ def load(filename: Union[str, Path]) -> Comparer | ComparerCollection:
     "GridModelResult",
     "DfsuModelResult",
     "DummyModelResult",
+    "NetworkModelResult",
     "observation",
     "PointObservation",
+    "NetworkLocationObservation",
     "TrackObservation",
     "TimeSeries",
     "match",

src/modelskill/matching.py

@@ -28,7 +28,14 @@
 from .model.dummy import DummyModelResult
 from .model.grid import GridModelResult
 from .model.track import TrackModelResult
-from .obs import Observation, PointObservation, TrackObservation, observation
+from .model.network import NetworkModelResult
+from .obs import (
+    Observation,
+    PointObservation,
+    TrackObservation,
+    NetworkLocationObservation,
+    observation,
+)
 from .timeseries import TimeSeries
 from .types import Period
 
@@ -50,6 +57,7 @@
     GridModelResult,
     DfsuModelResult,
     TrackModelResult,
+    NetworkModelResult,
     DummyModelResult,
 ]
 ObsInputType = Union[
@@ -274,7 +282,15 @@ def match(
 
     if len(obs) > 1 and isinstance(mod, Collection) and len(mod) > 1:
         if not all(
-            isinstance(m, (DfsuModelResult, GridModelResult, DummyModelResult))
+            isinstance(
+                m,
+                (
+                    DfsuModelResult,
+                    GridModelResult,
+                    NetworkModelResult,
+                    DummyModelResult,
+                ),
+            )
             for m in mod
         ):
             raise ValueError(
@@ -337,7 +353,15 @@ def _match_single_obs(
     raw_mod_data = {
         m.name: (
             m.extract(observation, spatial_method=spatial_method)
-            if isinstance(m, (DfsuModelResult, GridModelResult, DummyModelResult))
+            if isinstance(
+                m,
+                (
+                    DfsuModelResult,
+                    GridModelResult,
+                    DummyModelResult,
+                    NetworkModelResult,
+                ),
+            )
             else m
         )
         for m in model_results
@@ -379,6 +403,7 @@ def _match_space_time(
     idxs = [m.time for m in raw_mod_data.values()]
     period = _get_global_start_end(idxs)
 
+    # TODO is the trim step necessary?
     observation = observation.trim(period.start, period.end, no_overlap=obs_no_overlap)
     if len(observation.data.time) == 0:
         return None
@@ -425,8 +450,10 @@ def _parse_single_obs(
     obs: ObsInputType,
     obs_item: Optional[int | str],
     gtype: Optional[GeometryTypes],
-) -> PointObservation | TrackObservation:
-    if isinstance(obs, (PointObservation, TrackObservation)):
+) -> PointObservation | TrackObservation | NetworkLocationObservation:
+    if isinstance(
+        obs, (PointObservation, TrackObservation, NetworkLocationObservation)
+    ):
         if obs_item is not None:
             raise ValueError(
                 "obs_item argument not allowed if obs is an modelskill.Observation type"
@@ -446,6 +473,7 @@ def _parse_single_model(
     | TrackModelResult
     | GridModelResult
     | DfsuModelResult
+    | NetworkModelResult
     | DummyModelResult
 ):
     if isinstance(
@@ -478,6 +506,7 @@ def _parse_single_model(
                 TrackModelResult,
                 GridModelResult,
                 DfsuModelResult,
+                NetworkModelResult,
                 DummyModelResult,
             ),
         )

src/modelskill/model/__init__.py

@@ -21,6 +21,7 @@
 from .dfsu import DfsuModelResult
 from .grid import GridModelResult
 from .dummy import DummyModelResult
+from .network import NetworkModelResult
 
 __all__ = [
     "PointModelResult",
@@ -29,4 +30,5 @@
     "GridModelResult",
     "model_result",
     "DummyModelResult",
+    "NetworkModelResult",
 ]

src/modelskill/model/network.py

@@ -0,0 +1,58 @@
+from typing import Any
+from pathlib import Path
+from typing import Optional
+
+import pandas as pd
+
+# from ..quantity import Quantity
+
+from ._base import SelectedItems
+from ..obs import NetworkLocationObservation, PointObservation, TrackObservation
+from .point import PointModelResult
+
+
+class NetworkModelResult:
+    def __init__(
+        self,
+        data: str | Path,
+        *,
+        name: str,
+        item: str | int | None = None,
+        # quantity: Optional[Quantity] = None,
+        aux_items: Optional[list[int | str]] = None,
+    ) -> None:
+        import mikeio1d
+
+        df = mikeio1d.Res1D(data).to_dataframe()
+
+        self.data = df
+        self.time = df.index
+        self.name = name
+        self.item = item
+
+        # TODO load from file
+        data_vars = ["Discharge", "Water Level"]
+
+        sel_items = SelectedItems.parse(data_vars, item=item, aux_items=aux_items)
+
+        self.sel_items = sel_items
+
+    def extract(
+        self,
+        observation: PointObservation | TrackObservation | NetworkLocationObservation,
+        **kwargs: Any,
+    ) -> PointModelResult:
+        if not isinstance(observation, NetworkLocationObservation):
+            raise TypeError(
+                "NetworkModelResult can only extract NetworkLocationObservation"
+            )
+        col = f"{self.item}:{observation.reach}:{observation.chainage}"
+
+        df = pd.DataFrame()
+        df[observation.name] = self.data[col]
+        df.index = self.time
+        return PointModelResult(
+            data=df,
+            name=self.name,
+            item=observation.name,
+        )

src/modelskill/obs.py

@@ -226,6 +226,37 @@ def z(self, value):
         self.data["z"] = value
 
 
+class NetworkLocationObservation(PointObservation):
+    def __init__(
+        self,
+        data: PointType,
+        *,
+        reach: str,
+        chainage: str,
+        item: Optional[int | str] = None,
+        x: Optional[float] = None,
+        y: Optional[float] = None,
+        name: Optional[str] = None,
+        weight: float = 1.0,
+        quantity: Optional[Quantity] = None,
+        aux_items: Optional[list[int | str]] = None,
+        attrs: Optional[dict] = None,
+    ) -> None:
+        self.reach = reach
+        self.chainage = chainage
+        super().__init__(
+            data=data,
+            item=item,
+            x=x,
+            y=y,
+            name=name,
+            weight=weight,
+            quantity=quantity,
+            aux_items=aux_items,
+            attrs=attrs,
+        )
+
+
 class TrackObservation(Observation):
     """Class for observation with locations moving in space, e.g. satellite altimetry
 

src/modelskill/timeseries/_timeseries.py

@@ -339,5 +339,6 @@ def trim(
                     warnings.warn(msg)
                 case _:
                     pass
-
-        return self.__class__(data)
+        copy = deepcopy(self)
+        copy.data = data
+        return copy

tests/model/test_network.py

@@ -0,0 +1,11 @@
+import modelskill as ms
+
+
+def test_network_model_result_has_name():
+    mod = ms.NetworkModelResult(
+        "tests/testdata/network/Vida_1BaseDefault_Network_HD.res1d",
+        name="Vida",
+        item="Discharge",
+    )
+
+    assert mod.name == "Vida"

tests/observation/test_network_obs.py

@@ -0,0 +1,16 @@
+import modelskill as ms
+
+
+def test_network_observation():
+    obs = ms.NetworkLocationObservation(
+        "tests/testdata/network/vidaa_mag_4905.dfs0",
+        item=0,
+        reach="VIDAA-MAG",
+        chainage="4905",
+        name="By the bridge",
+    )
+    assert obs.name == "By the bridge"
+    assert obs.quantity.name == "Discharge"
+    assert obs.quantity.unit == "m^3/s"
+    assert obs.reach == "VIDAA-MAG"
+    assert obs.chainage == "4905"

tests/test_match.py

@@ -616,3 +616,21 @@ def test_multiple_models_same_name(tmp_path: Path) -> None:
 
     with pytest.raises(ValueError, match="HKZN_local_2017_DutchCoast"):
         ms.match(obs, [mr1, mr2])
+
+
+def test_network():
+    obs = ms.NetworkLocationObservation(
+        "tests/testdata/network/vidaa_mag_4905.dfs0",
+        item=0,
+        reach="VIDAA-MAG",
+        chainage="4905",
+    )
+    mod = ms.NetworkModelResult(
+        "tests/testdata/network/Vida_1BaseDefault_Network_HD.res1d",
+        name="Vida",
+        item="Discharge",
+    )
+
+    cmp = ms.match(obs, mod)
+    assert cmp.n_points == 37
+    assert cmp.score()["Vida"] == pytest.approx(0.11985827)