532 litter model should average abiotic quantities over relevant soil layers

tests/models/litter/conftest.py

@@ -67,12 +67,14 @@ def dummy_litter_data(fixture_core_components):
 
     # Vertically structured variables
     data["soil_temperature"] = lyr_strct.from_template()
-    data["soil_temperature"][lyr_strct.index_all_soil] = 20
+    data["soil_temperature"][lyr_strct.index_topsoil] = 20
+    data["soil_temperature"][lyr_strct.index_subsoil] = [19.5, 18.7, 18.7, 17.6]
 
     # At present the soil model only uses the top soil layer, so this is the
     # only one with real test values in
     data["matric_potential"] = lyr_strct.from_template()
     data["matric_potential"][lyr_strct.index_topsoil] = [-10.0, -25.0, -100.0, -100.0]
+    data["matric_potential"][lyr_strct.index_subsoil] = [-11.0, -29.5, -123.0, -154.1]
 
     data["air_temperature"] = lyr_strct.from_template()
     data["air_temperature"][lyr_strct.index_filled_atmosphere] = np.array(

tests/models/litter/test_env_factors.py

@@ -1,6 +1,7 @@
 """Test module for litter.env_factors.py."""
 
 import numpy as np
+import pytest
 
 from virtual_ecosystem.models.litter.constants import LitterConsts
 
@@ -27,21 +28,151 @@ def test_calculate_temperature_effect_on_litter_decomp(
     assert np.allclose(actual_factor, expected_factor)
 
 
-def test_calculate_soil_water_effect_on_litter_decomp():
+def test_calculate_soil_water_effect_on_litter_decomp(
+    dummy_litter_data, fixture_core_components
+):
     """Test that soil moisture effects on decomposition are calculated correctly."""
     from virtual_ecosystem.models.litter.env_factors import (
         calculate_soil_water_effect_on_litter_decomp,
     )
 
-    water_potentials = np.array([-10.0, -25.0, -100.0, -400.0])
-
-    expected_factor = [1.0, 0.88496823, 0.71093190, 0.53689556]
+    expected_factor = [1.0, 0.88496823, 0.71093190, 0.71093190]
 
     actual_factor = calculate_soil_water_effect_on_litter_decomp(
-        water_potentials,
+        water_potential=dummy_litter_data["matric_potential"][
+            fixture_core_components.layer_structure.index_topsoil_scalar
+        ],
         water_potential_halt=LitterConsts.litter_decay_water_potential_halt,
         water_potential_opt=LitterConsts.litter_decay_water_potential_optimum,
         moisture_response_curvature=LitterConsts.moisture_response_curvature,
     )
 
     assert np.allclose(actual_factor, expected_factor)
+
+
+@pytest.mark.parametrize(
+    "increased_depth,expected_av_temps",
+    [
+        pytest.param(
+            True,
+            [18.6319817, 18.498648, 18.498648, 18.315315],
+            id="increased depth",
+        ),
+        pytest.param(
+            False,
+            [18.0729725, 18.0729725, 18.0729725, 18.0729725],
+            id="normal depth",
+        ),
+    ],
+)
+def test_average_temperature_over_microbially_active_layers(
+    dummy_litter_data, fixture_core_components, increased_depth, expected_av_temps
+):
+    """Check averaging of temperatures over soil layers works correctly."""
+    from virtual_ecosystem.models.litter.env_factors import (
+        average_temperature_over_microbially_active_layers,
+    )
+
+    if increased_depth:
+        fixture_core_components.layer_structure.soil_layer_active_thickness = np.array(
+            [0.5, 0.25]
+        )
+        fixture_core_components.layer_structure.max_depth_of_microbial_activity = 0.75
+
+    actual_av_temps = average_temperature_over_microbially_active_layers(
+        soil_temperatures=dummy_litter_data["soil_temperature"],
+        surface_temperature=dummy_litter_data["air_temperature"][
+            fixture_core_components.layer_structure.index_surface
+        ].to_numpy(),
+        layer_structure=fixture_core_components.layer_structure,
+    )
+
+    assert np.allclose(actual_av_temps, expected_av_temps)
+
+
+@pytest.mark.parametrize(
+    "increased_depth,expected_water_pots",
+    [
+        pytest.param(
+            True,
+            [-10.1667, -25.750, -103.8333, -109.0167],
+            id="increased depth",
+        ),
+        pytest.param(
+            False,
+            [-10.0, -25.0, -100.0, -100.0],
+            id="normal depth",
+        ),
+    ],
+)
+def test_average_water_potential_over_microbially_active_layers(
+    dummy_litter_data, fixture_core_components, increased_depth, expected_water_pots
+):
+    """Check averaging of water potentials over soil layers works correctly."""
+    from virtual_ecosystem.models.litter.env_factors import (
+        average_water_potential_over_microbially_active_layers,
+    )
+
+    if increased_depth:
+        fixture_core_components.layer_structure.soil_layer_active_thickness = np.array(
+            [0.5, 0.25]
+        )
+        fixture_core_components.layer_structure.max_depth_of_microbial_activity = 0.75
+
+    actual_water_pots = average_water_potential_over_microbially_active_layers(
+        water_potentials=dummy_litter_data["matric_potential"],
+        layer_structure=fixture_core_components.layer_structure,
+    )
+
+    assert np.allclose(actual_water_pots, expected_water_pots)
+
+
+@pytest.mark.parametrize(
+    "increased_depth,expected_factors",
+    [
+        pytest.param(
+            True,
+            {
+                "temp_above": [0.1878681, 0.1878681, 0.1878681, 0.1878681],
+                "temp_below": [0.2407699, 0.2377353, 0.2377353, 0.2335993],
+                "water": [0.9979245, 0.8812574, 0.7062095, 0.7000939],
+            },
+            id="increased depth",
+        ),
+        pytest.param(
+            False,
+            {
+                "temp_above": [0.1878681, 0.1878681, 0.1878681, 0.1878681],
+                "temp_below": [0.2281971, 0.2281971, 0.2281971, 0.2281971],
+                "water": [1.0, 0.88496823, 0.71093190, 0.71093190],
+            },
+            id="normal depth",
+        ),
+    ],
+)
+def test_calculate_environmental_factors(
+    dummy_litter_data, fixture_core_components, increased_depth, expected_factors
+):
+    """Check that the calculation of the relevant environmental factors is correct."""
+    from virtual_ecosystem.models.litter.env_factors import (
+        calculate_environmental_factors,
+    )
+
+    if increased_depth:
+        fixture_core_components.layer_structure.soil_layer_active_thickness = np.array(
+            [0.5, 0.25]
+        )
+        fixture_core_components.layer_structure.max_depth_of_microbial_activity = 0.75
+
+    actual_factors = calculate_environmental_factors(
+        air_temperatures=dummy_litter_data["air_temperature"],
+        soil_temperatures=dummy_litter_data["soil_temperature"],
+        water_potentials=dummy_litter_data["matric_potential"],
+        layer_structure=fixture_core_components.layer_structure,
+        constants=LitterConsts,
+    )
+
+    assert set(expected_factors.keys()) == set(actual_factors.keys())
+
+    for key in actual_factors.keys():
+        assert np.allclose(actual_factors[key], expected_factors[key])

tests/models/litter/test_litter_model.py

@@ -311,12 +311,12 @@ def test_update(fixture_litter_model, dummy_litter_data):
     end_above_meta = [0.32072786, 0.15473132, 0.08523907, 0.08074153]
     end_above_struct = [0.50470382, 0.25068224, 0.09843778, 0.11163532]
     end_woody = [4.7745168, 11.89872931, 7.3614112, 7.3314112]
-    end_below_meta = [0.4090768, 0.37287148, 0.06883228, 0.08315412]
-    end_below_struct = [0.6066315, 0.31860251, 0.02010566, 0.03038382]
+    end_below_meta = [0.41087696, 0.37434507, 0.06905624, 0.08337808]
+    end_below_struct = [0.6066914, 0.31869812, 0.02010607, 0.03038423]
     end_lignin_above_struct = [0.49790843, 0.10067782, 0.70495536, 0.71045831]
     end_lignin_woody = [0.49580586, 0.79787834, 0.35224223, 0.35012603]
-    end_lignin_below_struct = [0.50313604, 0.2658639, 0.7499951, 0.82142894]
-    c_mineral = [0.02987233, 0.02316114, 0.00786517, 0.00786517]
+    end_lignin_below_struct = [0.50313573, 0.26585915, 0.7499951, 0.82142798]
+    c_mineral = [0.02652423, 0.02033658, 0.00746131, 0.00746131]
 
     fixture_litter_model.update(time_index=0)
 

tests/models/litter/test_litter_pools.py

@@ -96,8 +96,8 @@ def test_calculate_decay_rates(dummy_litter_data, fixture_core_components):
         "metabolic_above": [0.00450883, 0.00225442, 0.00105206, 0.00105206],
         "structural_above": [1.6742967e-4, 6.1857359e-4, 1.1086908e-5, 1.1086908e-5],
         "woody": [0.0004832, 0.00027069, 0.0015888, 0.0015888],
-        "metabolic_below": [0.01092804, 0.00894564, 0.00135959, 0.00135959],
-        "structural_below": [3.6365995e-04, 5.803657e-04, 2.469074e-06, 2.469074e-06],
+        "metabolic_below": [0.00912788, 0.00747205, 0.00113563, 0.00113563],
+        "structural_below": [3.0375501e-4, 4.8476324e-4, 2.0623487e-6, 2.0623487e-6],
     }
 
     actual_decay = calculate_decay_rates(
@@ -109,15 +109,10 @@ def test_calculate_decay_rates(dummy_litter_data, fixture_core_components):
         lignin_above_structural=dummy_litter_data["lignin_above_structural"].to_numpy(),
         lignin_woody=dummy_litter_data["lignin_woody"].to_numpy(),
         lignin_below_structural=dummy_litter_data["lignin_below_structural"].to_numpy(),
-        surface_temp=dummy_litter_data["air_temperature"][
-            fixture_core_components.layer_structure.index_surface_scalar
-        ].to_numpy(),
-        topsoil_temp=dummy_litter_data["soil_temperature"][
-            fixture_core_components.layer_structure.index_topsoil_scalar
-        ].to_numpy(),
-        water_potential=dummy_litter_data["matric_potential"][
-            fixture_core_components.layer_structure.index_topsoil_scalar
-        ].to_numpy(),
+        air_temperatures=dummy_litter_data["air_temperature"],
+        soil_temperatures=dummy_litter_data["soil_temperature"],
+        water_potentials=dummy_litter_data["matric_potential"],
+        layer_structure=fixture_core_components.layer_structure,
         constants=LitterConsts,
     )