Make Impact.concat support ImpactForecast

Author: peanutfun

climada/engine/impact.py

@@ -2208,9 +2208,12 @@ def stack_attribute(attr_name: str) -> np.ndarray:
         imp_mat = sparse.vstack(imp_mats)
 
         # Concatenate other attributes
-        kwargs = {
-            attr: stack_attribute(attr) for attr in ("date", "frequency", "at_event")
-        }
+        concat_attrs = {
+            name.lstrip("_")  # Private attributes with getter/setter
+            for name, value in first_imp.__dict__.items()
+            if isinstance(value, np.ndarray)
+        }.difference(("event_id", "coord_exp", "eai_exp", "aai_agg"))
+        kwargs = {attr: stack_attribute(attr) for attr in concat_attrs}
 
         # Get remaining attributes from first impact object in list
         return cls(

climada/engine/test/test_impact_forecast.py

@@ -202,13 +202,23 @@ def test_no_select(self, impact_forecast, impact_kwargs):
         assert imp_fc_select.imp_mat.shape == (0, num_centroids)
 
 
-@pytest.mark.skip("Concat from base class does not work")
-def test_impact_forecast_concat(impact_forecast, member):
+def test_impact_forecast_concat(impact_forecast, member, lead_time):
     """Check if Impact.concat works on the derived class"""
     impact_fc = ImpactForecast.concat(
         [impact_forecast, impact_forecast], reset_event_ids=True
     )
     npt.assert_array_equal(impact_fc.member, np.concatenate([member, member]))
+    npt.assert_array_equal(impact_fc.lead_time, np.concatenate([lead_time, lead_time]))
+    npt.assert_array_equal(
+        impact_fc.event_id, np.arange(impact_fc.imp_mat.shape[0]) + 1
+    )
+    npt.assert_array_equal(impact_fc.event_name, impact_forecast.event_name * 2)
+    npt.assert_array_equal(
+        impact_fc.imp_mat.toarray(),
+        np.vstack(
+            (impact_forecast.imp_mat.toarray(), impact_forecast.imp_mat.toarray())
+        ),
+    )
 
 
 def test_impact_forecast_blocked_methods(impact_forecast):