Consistent KPI case

src/simstadt/results/heat_demand.py

@@ -12,7 +12,7 @@ from .providers import Providers
 
 @dataclass(repr=False)
 class HeatDemandResults(SimStadtResults):
-    """Results for Heat Demand (and Heat+Cool Demand) workflows."""
+    """Results for Heat demand (and Heat+Cool demand) workflows."""
 
     MAX_FLAT_ROOF_DIFFERENCE = 0.1  # [m]
     TOTAL_DEMAND = "Total Yearly Heating + DHW demand"
@@ -47,7 +47,7 @@ class HeatDemandResults(SimStadtResults):
             custom_kpis.extend(
                 [
                     KPI("Number of heated buildings", heated_buildings, precision=0),
-                    KPI("Specific Heating Demand", specific_heat_demand, "kWh / (m² · a)", precision=0),
+                    KPI("Specific Heating demand", specific_heat_demand, "kWh / (m² · a)", precision=0),
                 ]
             )
             sums.extend(
@@ -59,7 +59,7 @@ class HeatDemandResults(SimStadtResults):
 
         if df.attrs["Cooling"]:
             specific_cooling_demand = df["Yearly Cooling demand"].sum() / df["Heated area"].sum()
-            custom_kpis.append(KPI("Specific Cooling Demand", specific_cooling_demand, "kWh / (m² · a)", precision=0))
+            custom_kpis.append(KPI("Specific Cooling demand", specific_cooling_demand, "kWh / (m² · a)", precision=0))
             sums.append(("Yearly Cooling demand", "kWh / a"))
 
         # TODO: rename to average year of construction?
@@ -73,7 +73,7 @@ class HeatDemandResults(SimStadtResults):
             rot=0,
             ylabel="[MWh]",
             width=0.8,
-            color={"Monthly Heating Demand": "darkred", "Monthly Cooling Demand": "darkblue"},
+            color={"Monthly Heating demand": "darkred", "Monthly Cooling demand": "darkblue"},
         )
         plt.savefig(heat_png, bbox_inches="tight", dpi=300)
         plt.close(ax.figure)
@@ -89,5 +89,5 @@ class HeatDemandResults(SimStadtResults):
                 col for col in df.columns if search_str in col and "Yearly" not in col and "Specific" not in col
             ]
             if found_cols:
-                monthly_df[f"Monthly {mode} Demand"] = (df[found_cols].sum() / 1000).values
+                monthly_df[f"Monthly {mode} demand"] = (df[found_cols].sum() / 1000).values
         return monthly_df

tests/test_cli.py

@@ -86,7 +86,7 @@ def test_run_files_flag(mock_simstadt, run_cli, capsys, tmp_path):
     out, _ = run_cli(capsys, HEAT_TEMPLATE, CITYGML, "-p", proj, "--files")
     assert "Output files:" in out
     assert "MiniBuchwald_hourly_demand.csv" in out
-    assert "Specific Heating Demand" in out
+    assert "Specific Heating demand" in out
     assert "Mean Uvalue" in out
 
 

tests/test_results.py

@@ -103,7 +103,7 @@ def test_heating_kpis(heating_results):
     assert kpis["Year of construction"].value == pytest.approx(1963, abs=0.5)
     assert heating_results.kpi("Number of buildings").value == 24
     assert heating_results.kpi("Number of buildings").unit is None
-    assert heating_results.kpi("Specific Heating Demand").value == pytest.approx(
+    assert heating_results.kpi("Specific Heating demand").value == pytest.approx(
         100, abs=5
     )
     with pytest.raises(ValueError, match="No 'Not here' KPI found"):
@@ -170,11 +170,11 @@ def test_heating_and_cooling_result_type(heating_and_cooling_results):
 def test_heating_and_cooling_kpis(heating_and_cooling_results):
     kpis = kpis_by_name(heating_and_cooling_results)
     assert "Yearly Heating demand" in kpis
-    assert "Specific Heating Demand" in kpis
+    assert "Specific Heating demand" in kpis
     assert "Yearly Cooling demand" in kpis
-    assert "Specific Cooling Demand" in kpis
+    assert "Specific Cooling demand" in kpis
     assert heating_and_cooling_results.kpi(
-        "Specific Cooling Demand"
+        "Specific Cooling demand"
     ).value == pytest.approx(20, abs=1)
     assert len(kpis) == 12
 
@@ -207,11 +207,11 @@ def test_cooling_result_type(cooling_results):
 def test_cooling_kpis(cooling_results):
     kpis = kpis_by_name(cooling_results)
     assert "Yearly Heating demand" not in kpis
-    assert "Specific Heating Demand" not in kpis
+    assert "Specific Heating demand" not in kpis
     assert "Yearly Cooling demand" in kpis
-    assert "Specific Cooling Demand" in kpis
-    assert kpis["Specific Cooling Demand"].value == pytest.approx(20, abs=0.5)
-    assert kpis["Specific Cooling Demand"].unit == "kWh / (m² · a)"
+    assert "Specific Cooling demand" in kpis
+    assert kpis["Specific Cooling demand"].value == pytest.approx(20, abs=0.5)
+    assert kpis["Specific Cooling demand"].unit == "kWh / (m² · a)"
     assert len(kpis) == 8
 
 

tests/test_simulations.py

@@ -32,8 +32,8 @@ def test_heat_demand():
     assert "Yearly Heating demand" in kpis
     assert kpis["Yearly Heating demand"].value > 0
     assert kpis["Yearly Heating demand"].unit == "kWh / a"
-    assert kpis["Specific Heating Demand"].value == pytest.approx(100, abs=30)
-    assert kpis["Specific Heating Demand"].unit == "kWh / (m² · a)"
+    assert kpis["Specific Heating demand"].value == pytest.approx(100, abs=30)
+    assert kpis["Specific Heating demand"].unit == "kWh / (m² · a)"
     assert kpis["Mean Uvalue"].value == pytest.approx(1, abs=0.2)
     assert kpis["Mean Uvalue"].unit == "W / (m² · K)"
     assert kpis["Year of construction"].value == pytest.approx(1950, abs=50)