Feature/multiple model support for residual hist on comparer

modelskill/comparison/_comparer_plotter.py

@@ -763,7 +763,7 @@ def taylor(
 
     def residual_hist(
         self, bins=100, title=None, color=None, figsize=None, ax=None, **kwargs
-    ) -> matplotlib.axes.Axes:
+    ) -> matplotlib.axes.Axes | list[matplotlib.axes.Axes]:
         """plot histogram of residual values
 
         Parameters
@@ -776,20 +776,67 @@ def residual_hist(
             residual color, by default "#8B8D8E"
         figsize : tuple, optional
             figure size, by default None
-        ax : matplotlib.axes.Axes, optional
+        ax : matplotlib.axes.Axes | list[matplotlib.axes.Axes], optional
             axes to plot on, by default None
         **kwargs
             other keyword arguments to plt.hist()
 
         Returns
         -------
-        matplotlib.axes.Axes
+        matplotlib.axes.Axes | list[matplotlib.axes.Axes]
         """
+        cmp = self.comparer
+
+        if cmp.n_models == 1:
+            return self._residual_hist_one_model(
+                bins=bins,
+                title=title,
+                color=color,
+                figsize=figsize,
+                ax=ax,
+                mod_name=cmp.mod_names[0],
+                **kwargs,
+            )
+
+        if ax is not None and len(ax) != len(cmp.mod_names):
+            raise ValueError("Number of axes must match number of models")
+
+        axs = ax if ax is not None else [None] * len(cmp.mod_names)
+
+        for i, mod_name in enumerate(cmp.mod_names):
+            cmp_model = cmp.sel(model=mod_name)
+            ax_mod = cmp_model.plot.residual_hist(
+                bins=bins,
+                title=title,
+                color=color,
+                figsize=figsize,
+                ax=axs[i],
+                **kwargs,
+            )
+            axs[i] = ax_mod
+
+        return axs
+
+    def _residual_hist_one_model(
+        self,
+        bins=100,
+        title=None,
+        color=None,
+        figsize=None,
+        ax=None,
+        mod_name=None,
+        **kwargs,
+    ) -> matplotlib.axes.Axes:
+        """Residual histogram for one model only"""
         _, ax = _get_fig_ax(ax, figsize)
 
         default_color = "#8B8D8E"
         color = default_color if color is None else color
-        title = f"Residuals, {self.comparer.name}" if title is None else title
+        title = (
+            f"Residuals, Observation: {self.comparer.name}, Model: {mod_name}"
+            if title is None
+            else title
+        )
         ax.hist(self.comparer._residual, bins=bins, color=color, **kwargs)
         ax.set_title(title)
         ax.set_xlabel(f"Residuals of {self.comparer._unit_text}")

tests/test_comparer.py

@@ -711,6 +711,8 @@ def test_to_dataframe_tc(tc):
 
 # ======================== plotting ========================
 
+PLOT_FUNCS_RETURNING_MANY_AX = ["scatter", "hist", "residual_hist"]
+
 
 @pytest.fixture(
     params=[
@@ -727,11 +729,20 @@ def test_to_dataframe_tc(tc):
 def pc_plot_function(pc, request):
     func = getattr(pc.plot, request.param)
     # special cases requiring a model to be selected
-    if request.param in ["scatter", "hist", "residual_hist"]:
+    if request.param in PLOT_FUNCS_RETURNING_MANY_AX:
         func = getattr(pc.sel(model=0).plot, request.param)
     return func
 
 
+@pytest.mark.parametrize("kind", PLOT_FUNCS_RETURNING_MANY_AX)
+def test_plots_returning_multiple_axes(pc, kind):
+    n_models = 2
+    func = getattr(pc.plot, kind)
+    ax = func()
+    assert len(ax) == n_models
+    assert all(isinstance(a, plt.Axes) for a in ax)
+
+
 def test_plot_returns_an_object(pc_plot_function):
     obj = pc_plot_function()
     assert obj is not None
@@ -824,7 +835,6 @@ def test_plots_directional(pt_df):
 
 
 def test_from_matched_track_data():
-
     df = pd.DataFrame(
         {
             "lat": [55.0, 55.1],