Comparer/ComparerCollection isel

modelskill/comparison/_collection.py

@@ -427,6 +427,25 @@ def sel(
 
         return cc
 
+    def isel(
+        self, model: int | None = None, observation: int | None = None
+    ) -> "ComparerCollection":
+        """Select data based on model and observation index.
+
+        Parameters
+        ----------
+        model : int, optional
+            Model index. If None, all models are selected.
+        observation : int, optional
+            Observation index. If None, all observations are selected.
+
+        Returns
+        -------
+        ComparerCollection
+            New ComparerCollection with selected data.
+        """
+        return self.sel(model=model, observation=observation)
+
     def filter_by_attrs(self, **kwargs) -> "ComparerCollection":
         """Filter by comparer attrs similar to xarray.Dataset.filter_by_attrs
 

modelskill/comparison/_comparison.py

@@ -931,6 +931,21 @@ def sel(
                 d = d.isel(time=mask)
         return Comparer.from_matched_data(data=d, raw_mod_data=raw_mod_data)
 
+    def isel(self, model: int) -> "Comparer":
+        """Select data based on model index.
+
+        Parameters
+        ----------
+        model : int
+            Model index.
+
+        Returns
+        -------
+        Comparer
+            New Comparer with selected data.
+        """
+        return self.sel(model=model)
+
     def where(
         self,
         cond: Union[bool, np.ndarray, xr.DataArray],

tests/test_comparer.py

@@ -444,6 +444,13 @@ def test_pc_sel_model_first(pc):
     assert np.all(pc2.data.m1 == pc.data.m1)
 
 
+def test_pc_isel_model_first(pc):
+    pc2 = pc.isel(model=0)
+    assert pc2.n_points == 5
+    assert pc2.n_models == 1
+    assert np.all(pc2.data.m1 == pc.data.m1)
+
+
 def test_pc_sel_model_last(pc):
     pc2 = pc.sel(model=-1)
     assert pc2.n_points == 5

tests/test_comparercollection.py

@@ -129,6 +129,17 @@ def test_cc_sel_model_last(cc):
     assert cc2.mod_names == ["m3"]
 
 
+def test_cc_isel_model_last(cc):
+    cc2 = cc.isel(model=-1)
+    assert len(cc2) == 1
+    assert cc2.n_models == 1
+    assert cc2.n_points == 5
+    assert cc2.start_time == pd.Timestamp("2019-01-03")
+    assert cc2.end_time == pd.Timestamp("2019-01-07")
+    assert cc2.obs_names == ["fake track obs"]
+    assert cc2.mod_names == ["m3"]
+
+
 # TODO: FAILS
 # def test_cc_sel_time_single(cc):
 #     cc1 = cc.sel(time="2019-01-03")

tests/test_multimodelcompare.py

@@ -125,6 +125,11 @@ def test_mm_skill_obs(cc):
     assert s.loc["SW_2"].bias == s2.loc["SW_2"].bias
 
 
+def test_mm_isel(cc):
+    s2 = cc.isel(observation=-1).skill()
+    assert s2.loc["SW_2"].bias == pytest.approx(0.081431053)
+
+
 def test_mm_mean_skill_obs(cc):
     df = cc.sel(model=0, observation=[0, "c2"]).mean_skill().to_dataframe()
     assert pytest.approx(df.iloc[0].si) == 0.11113215