Updated tests

src/simstadt/results.py

@@ -481,10 +481,11 @@ class SolarPotentialResults(SimStadtResults):
     def kpis(self) -> list[KPI]:
         df = self.dataframe
         return [
-            #TODO: Add averages too?
             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("Mean temperature", float(df["Ta"].mean()), "°C", 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

@@ -6,9 +6,9 @@ import pandas as pd
 import pytest
 
 from simstadt import (
+    KPI,
     GreenWaterResults,
     HeatDemandResults,
-    KPI,
     LoadProfileResults,
     PhotovoltaicResults,
     SimStadtResults,
@@ -38,12 +38,16 @@ def find_output_files(workflow_name: str) -> list[Path]:
 # Heat demand (heating only)
 # ---------------------------------------------------------------------------
 
+
 @pytest.fixture(scope="module")
 def heating_results() -> SimStadtResults:
     output_files = [
-        TEST_REPOSITORY / "CGSC.proj/101_HeatDemand.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
-        TEST_REPOSITORY / "CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.csv",
-        TEST_REPOSITORY / "CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.log",
+        TEST_REPOSITORY
+        / "CGSC.proj/101_HeatDemand.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
+        TEST_REPOSITORY
+        / "CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.csv",
+        TEST_REPOSITORY
+        / "CGSC.proj/101_HeatDemand.flow/04_MonthlyEnergyBalance.step/Grombuehl_mini_Steinheilstrasse_DIN18599_HEATING.log",
     ]
     return create_simstadt_results("Heat demand simulation for Grombühl", output_files)
 
@@ -93,7 +97,10 @@ def test_heating_kpis(heating_results):
     assert kpis["Storey number"].value == pytest.approx(4, abs=0.5)
     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("Specific Heating Demand").value == pytest.approx(100, abs=5)
+    assert heating_results.kpi("Number of buildings").unit is None
+    assert heating_results.kpi("Specific Heating Demand").value == pytest.approx(
+        100, abs=5
+    )
     with pytest.raises(ValueError, match="No 'Not here' KPI found"):
         heating_results.kpi("Not here")
     assert len(kpis) == 10  # heating only
@@ -139,33 +146,36 @@ def test_heating_repr(heating_results):
 
 
 # ---------------------------------------------------------------------------
-# Heat + cool demand
+# Heating + cooling demand
 # ---------------------------------------------------------------------------
 
+
 @pytest.fixture(scope="module")
-def heat_cool_results() -> SimStadtResults:
+def heating_and_cooling_results() -> SimStadtResults:
     return create_simstadt_results(
         "Heating and cooling demand simulation for Grombühl",
         find_output_files("104_HeatAndCoolDemand.flow"),
     )
 
 
-def test_heating_cool_result_type(heat_cool_results):
-    assert isinstance(heat_cool_results, HeatDemandResults)
+def test_heating_and_cooling_result_type(heating_and_cooling_results):
+    assert isinstance(heating_and_cooling_results, HeatDemandResults)
 
 
-def test_heating_cool_kpis(heat_cool_results):
-    kpis = kpis_by_name(heat_cool_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 "Yearly Cooling demand" in kpis
     assert "Specific Cooling Demand" in kpis
-    assert heat_cool_results.kpi("Specific Cooling Demand").value == pytest.approx(20, abs=1)
+    assert heating_and_cooling_results.kpi("Specific Cooling Demand").value == pytest.approx(
+        20, abs=1
+    )
     assert len(kpis) == 12
 
 
-def test_heating_cool_diagrams(heat_cool_results):
-    diagrams = heat_cool_results.diagrams
+def test_heating_and_cooling_diagrams(heating_and_cooling_results):
+    diagrams = heating_and_cooling_results.diagrams
     assert len(diagrams) > 0
     assert "Monthly demands" in diagrams
     for diagram in diagrams.values():
@@ -176,6 +186,7 @@ def test_heating_cool_diagrams(heat_cool_results):
 # Cooling only
 # ---------------------------------------------------------------------------
 
+
 @pytest.fixture(scope="module")
 def cooling_results() -> SimStadtResults:
     return create_simstadt_results(
@@ -203,11 +214,14 @@ def test_cooling_kpis(cooling_results):
 # Green water
 # ---------------------------------------------------------------------------
 
+
 @pytest.fixture(scope="module")
 def greenwater_results() -> SimStadtResults:
     output_files = [
-        TEST_REPOSITORY / "CGSC.proj/102_GreenWater.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
-        TEST_REPOSITORY / "CGSC.proj/102_GreenWater.flow/03_GreenWater.step/Grombühl_mini_with_trees_greenwater.csv",
+        TEST_REPOSITORY
+        / "CGSC.proj/102_GreenWater.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
+        TEST_REPOSITORY
+        / "CGSC.proj/102_GreenWater.flow/03_GreenWater.step/Grombühl_mini_with_trees_greenwater.csv",
     ]
     return create_simstadt_results("Green Water simulation for Grombühl", output_files)
 
@@ -321,11 +335,14 @@ def test_greenwater_repr(greenwater_results):
 # Photovoltaic
 # ---------------------------------------------------------------------------
 
+
 @pytest.fixture(scope="module")
 def pv_results() -> SimStadtResults:
     output_files = [
-        TEST_REPOSITORY / "CGSC.proj/103_PV.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
-        TEST_REPOSITORY / "CGSC.proj/103_PV.flow/04_PhotovoltaicPotential.step/Grombühl_mini_with_trees_meteonorm_Hay_pv_potential.csv",
+        TEST_REPOSITORY
+        / "CGSC.proj/103_PV.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
+        TEST_REPOSITORY
+        / "CGSC.proj/103_PV.flow/04_PhotovoltaicPotential.step/Grombühl_mini_with_trees_meteonorm_Hay_pv_potential.csv",
     ]
     return create_simstadt_results("PV for Grombühl", output_files)
 
@@ -409,10 +426,13 @@ def test_pv_no_log(pv_results):
 # Edge cases
 # ---------------------------------------------------------------------------
 
+
 def test_greenwater_without_trees():
     output_files = [
-        TEST_REPOSITORY / "CGSC.proj/102_GreenWater.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
-        TEST_REPOSITORY / "CGSC.proj/102_GreenWater.flow/03_GreenWater.step/Grombühl_mini_greenwater.csv",
+        TEST_REPOSITORY
+        / "CGSC.proj/102_GreenWater.flow/02_WeatherProcessor.step/hourly_GHI_DHI_Ta_meteonorm_Wuerzburg.prn",
+        TEST_REPOSITORY
+        / "CGSC.proj/102_GreenWater.flow/03_GreenWater.step/Grombühl_mini_greenwater.csv",
     ]
     results = create_simstadt_results("Green Water without trees", output_files)
     with pytest.raises(ValueError, match="any tree"):
@@ -425,10 +445,12 @@ def test_greenwater_without_trees():
 # Load profile
 # ---------------------------------------------------------------------------
 
+
 @pytest.fixture(scope="module")
 def loadprofile_results() -> SimStadtResults:
     output_files = [
-        LOAD_PROFILE_FLOW / "02_LoadProfileGenerator.step/MiniBuchwald_load_profile_Hourly.csv",
+        LOAD_PROFILE_FLOW
+        / "02_LoadProfileGenerator.step/MiniBuchwald_load_profile_Hourly.csv",
     ]
     return create_simstadt_results("Load profile for MiniBuchwald", output_files)
 
@@ -475,7 +497,10 @@ def test_loadprofile_project(loadprofile_results):
 def test_loadprofile_params(loadprofile_results):
     assert loadprofile_results.short_name == "LoadProfile"
     assert loadprofile_results.name == "LoadProfile_Template"
-    assert loadprofile_results.workflow_provider == "de.hftstuttgart.simstadtworkflows.energy.LoadProfileProvider"
+    assert (
+        loadprofile_results.workflow_provider
+        == "de.hftstuttgart.simstadtworkflows.energy.LoadProfileProvider"
+    )
 
 
 def test_loadprofile_serialization(loadprofile_results):
@@ -485,7 +510,9 @@ def test_loadprofile_serialization(loadprofile_results):
     assert reconstructed.description == loadprofile_results.description
     assert len(reconstructed.output_files) == len(loadprofile_results.output_files)
     assert len(reconstructed.kpis) == 3
-    pd.testing.assert_frame_equal(reconstructed.dataframe, loadprofile_results.dataframe)
+    pd.testing.assert_frame_equal(
+        reconstructed.dataframe, loadprofile_results.dataframe
+    )
 
 
 def test_loadprofile_repr(loadprofile_results):
@@ -498,6 +525,7 @@ def test_loadprofile_repr(loadprofile_results):
 # Solar potential
 # ---------------------------------------------------------------------------
 
+
 @pytest.fixture(scope="module")
 def solar_results() -> SimStadtResults:
     output_files = [
@@ -525,9 +553,18 @@ 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["Average GHI"].value == pytest.approx(130, abs=1)
+    assert kpis["Average GHI"].unit == "W/m²"
+
     assert kpis["Annual DHI"].value == pytest.approx(685.1, abs=0.1)
-    assert kpis["Mean temperature"].value == pytest.approx(9.73, abs=0.05)
-    assert kpis["Mean temperature"].unit == "°C"
+    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 temperature"].value == pytest.approx(9.73, abs=0.05)
+    assert kpis["Average temperature"].unit == "°C"
 
 
 def test_solar_no_diagrams(solar_results):
@@ -551,7 +588,7 @@ def test_solar_serialization(solar_results):
     reconstructed = SimStadtResults.from_json(json_str)
     assert isinstance(reconstructed, SolarPotentialResults)
     assert reconstructed.description == solar_results.description
-    assert len(reconstructed.kpis) == 3
+    assert len(reconstructed.kpis) == 5
     pd.testing.assert_frame_equal(reconstructed.dataframe, solar_results.dataframe)
 
 
@@ -563,8 +600,10 @@ def test_solar_repr(solar_results):
 
 def test_broken_simulation():
     output_files = [
-        TEST_REPOSITORY / "CGSC.proj/103_PV.flow/02_WeatherProcessor.step/notATable.log",
-        TEST_REPOSITORY / "CGSC.proj/103_PV.flow/04_PhotovoltaicPotential.step/StillNotATable.png",
+        TEST_REPOSITORY
+        / "CGSC.proj/103_PV.flow/02_WeatherProcessor.step/notATable.log",
+        TEST_REPOSITORY
+        / "CGSC.proj/103_PV.flow/04_PhotovoltaicPotential.step/StillNotATable.png",
     ]
     results = create_simstadt_results("FakeTests", output_files)
     with pytest.raises(ValueError, match="any CSV file"):
@@ -572,4 +611,4 @@ def test_broken_simulation():
     with pytest.raises(ValueError, match="any CSV file"):
         results.to_json()
     with pytest.raises(ValueError, match="any CSV file"):
-        _ = results.kpis
+        results.kpis