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src/simstadt/results/load_profile.py

@@ -33,6 +33,6 @@ class LoadProfileResults(SimStadtResults):
         total = df.sum().sum()
         return [
             KPI("Number of buildings", df.shape[1], precision=0),
-            KPI("Total load", total, "kWh/a", precision=1),
-            KPI("Average load", total / 8760, "kWh/h", precision=1),
+            KPI("Total load", total, "kWh / a", precision=1),
+            KPI("Average load", total / 8760, "kWh / h", precision=1),
         ]

src/simstadt/results/solar_potential.py

@@ -31,9 +31,9 @@ class SolarPotentialResults(SimStadtResults):
     def kpis(self) -> list[KPI]:
         df = self.dataframe
         return [
-            KPI("Annual GHI", df["GHI"].sum() / 1000, "kWh/m²", precision=1),
-            KPI("Average GHI", df["GHI"].mean(), "W/m²", precision=1),
-            KPI("Annual DHI", df["DHI"].sum() / 1000, "kWh/m²", precision=1),
-            KPI("Average DHI", df["DHI"].mean(), "W/m²", precision=1),
+            KPI("Annual GHI", df["GHI"].sum() / 1000, "kWh / m²", precision=1),
+            KPI("Average GHI", df["GHI"].mean(), "W / m²", precision=1),
+            KPI("Annual DHI", df["DHI"].sum() / 1000, "kWh / m²", precision=1),
+            KPI("Average DHI", df["DHI"].mean(), "W / m²", precision=1),
             KPI("Average temperature", float(df["Ta"].mean()), "°C", precision=1),
         ]

tests/test_results.py

@@ -481,9 +481,9 @@ def test_loadprofile_kpis(loadprofile_results):
     assert kpis["Number of buildings"].value == 3
     assert kpis["Number of buildings"].unit is None
     assert kpis["Total load"].value == pytest.approx(17004.0, abs=1.0)
-    assert kpis["Total load"].unit == "kWh/a"
+    assert kpis["Total load"].unit == "kWh / a"
     assert kpis["Average load"].value == pytest.approx(1.9, abs=0.1)
-    assert kpis["Average load"].unit == "kWh/h"
+    assert kpis["Average load"].unit == "kWh / h"
 
 
 def test_loadprofile_no_diagrams(loadprofile_results):
@@ -552,16 +552,16 @@ def test_solar_dataframe(solar_results):
 def test_solar_kpis(solar_results):
     kpis = kpis_by_name(solar_results)
     assert kpis["Annual GHI"].value == pytest.approx(1143.9, abs=0.1)
-    assert kpis["Annual GHI"].unit == "kWh/m²"
+    assert kpis["Annual GHI"].unit == "kWh / m²"
 
     assert kpis["Average GHI"].value == pytest.approx(130, abs=1)
-    assert kpis["Average GHI"].unit == "W/m²"
+    assert kpis["Average GHI"].unit == "W / m²"
 
     assert kpis["Annual DHI"].value == pytest.approx(685.1, abs=0.1)
-    assert kpis["Annual DHI"].unit == "kWh/m²"
+    assert kpis["Annual DHI"].unit == "kWh / m²"
 
     assert kpis["Average DHI"].value == pytest.approx(78, abs=1)
-    assert kpis["Average DHI"].unit == "W/m²"
+    assert kpis["Average DHI"].unit == "W / m²"
 
     assert kpis["Average temperature"].value == pytest.approx(9.73, abs=0.05)
     assert kpis["Average temperature"].unit == "°C"

tests/test_runner.py

@@ -25,11 +25,9 @@ def test_citygml_in_proj_folder(mock_simstadt, tmp_path):
     assert CITYGML.name in results.citygml
     assert results.workflow_path.parent == proj
 
-    rich.print(results.kpis)
     assert len(results.dataframe) > 0
     assert len(results.kpis) == 10
 
-import rich
 
 def test_citygml_with_explicit_project_path(mock_simstadt, tmp_path):
     """CityGML outside .proj with project_path — CityGML is copied to project_path."""