Archetype counts too

src/simstadt/results/energy_grid.py

 import json
+from collections import Counter
 from dataclasses import dataclass
 from typing import ClassVar
 
@@ -34,6 +35,7 @@ class EnergyGridResults(SimStadtResults):
         df.attrs["number_of_households"] = sum(b["number_of_households"] for b in buildings)
         df.attrs["number_of_people"] = sum(sum(b["people_in_units"]) for b in buildings)
         df.attrs["total_heated_area"] = sum(b["heated_area"] for b in buildings)
+        df.attrs["archetype_counts"] = Counter(b["quarter_archetype"] for b in buildings)
         return df
 
     @property
@@ -42,10 +44,13 @@ class EnergyGridResults(SimStadtResults):
         total_heated_area = df.attrs["total_heated_area"]
         total_heat_kwh = df["heat_demand"].sum()
         total_elec_kwh = df["electricity_demand"].sum()
+        most_common_archetype, most_common_count = df.attrs["archetype_counts"].most_common(1)[0]
+        archetype_share = 100 * most_common_count / df.attrs["number_of_buildings"]
         return [
             KPI("Number of buildings", df.attrs["number_of_buildings"], precision=0),
             KPI("Number of households", df.attrs["number_of_households"], precision=0),
-            KPI("Number of people", df.attrs["number_of_people"], precision=0),
+            KPI("Number of inhabitants", df.attrs["number_of_people"], precision=0),
+            KPI("Most common archetype", archetype_share, f"% ({most_common_archetype})", precision=0),
             KPI("Total heated area", total_heated_area, "m²", precision=0),
             KPI("Total electricity demand", total_elec_kwh / 1000, "MWh / a", precision=1),
             KPI("Specific electricity demand", total_elec_kwh / total_heated_area, "kWh / (m² · a)", precision=1),
@@ -54,3 +59,7 @@ class EnergyGridResults(SimStadtResults):
             KPI("Total PV production", df["pv_production"].sum() / 1000, "MWh / a", precision=1),
             KPI("Average temperature", float(df["ambient_temperature"].mean()), "°C", precision=1),
         ]
+
+    @property
+    def more_info(self) -> dict:
+        return self.dataframe.attrs["archetype_counts"]

tests/test_results.py

@@ -655,8 +655,8 @@ def test_energy_grid_kpis(energy_grid_results):
     assert kpis["Number of buildings"].unit is None
     assert kpis["Number of households"].value == 8
     assert kpis["Number of households"].unit is None
-    assert kpis["Number of people"].value == 13
-    assert kpis["Number of people"].unit is None
+    assert kpis["Number of inhabitants"].value == 13
+    assert kpis["Number of inhabitants"].unit is None
     assert kpis["Total heated area"].value == pytest.approx(1198.1, abs=0.1)
     assert kpis["Total heated area"].unit == "m²"
     assert kpis["Total electricity demand"].value == pytest.approx(17.0, abs=0.1)
@@ -671,7 +671,14 @@ def test_energy_grid_kpis(energy_grid_results):
     assert kpis["Total PV production"].unit == "MWh / a"
     assert kpis["Average temperature"].value == pytest.approx(9.95, abs=0.05)
     assert kpis["Average temperature"].unit == "°C"
-    assert len(kpis) == 10
+    assert kpis["Most common archetype"].value == pytest.approx(66.7, abs=0.1)
+    assert kpis["Most common archetype"].unit == "% (QA_2)"
+    assert len(kpis) == 11
+
+
+def test_energy_grid_more_info(energy_grid_results):
+    info = energy_grid_results.more_info
+    assert info == {"QA_2": 2, "QA_4": 1}
 
 
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