Merge pull request #325 from ImperialCollegeLondon/feature/clean_up

Remove old temperature and moisture dependance

tests/conftest.py

@@ -139,7 +139,10 @@ def dummy_carbon_data(layer_roles_fixture):
             DataArray(np.full((13, 4), np.nan), dims=["layers", "cell_id"]),
             # At present the soil model only uses the top soil layer, so this is the
             # only one with real test values in
-            DataArray([[0.5, 0.7, 0.6, 0.2]], dims=["layers", "cell_id"]),
+            DataArray(
+                [[0.472467929, 0.399900047, 0.256053640, 0.153616897]],
+                dims=["layers", "cell_id"],
+            ),
             DataArray(np.full((1, 4), np.nan), dims=["layers", "cell_id"]),
         ],
         dim="layers",
@@ -151,6 +154,23 @@ def dummy_carbon_data(layer_roles_fixture):
             "cell_id": data.grid.cell_id,
         }
     )
+    # TODO - Eventually this should replace the dummy soil moisture entirely
+    data["matric_potential"] = xr.concat(
+        [
+            DataArray(np.full((13, 4), np.nan), dims=["layers", "cell_id"]),
+            # At present the soil model only uses the top soil layer, so this is the
+            # only one with real test values in
+            DataArray([[-3.0, -10.0, -250.0, -10000.0]], dims=["layers", "cell_id"]),
+            DataArray(np.full((1, 4), np.nan), dims=["layers", "cell_id"]),
+        ],
+        dim="layers",
+    ).assign_coords(
+        {
+            "layers": np.arange(0, 15),
+            "layer_roles": ("layers", layer_roles_fixture),
+            "cell_id": data.grid.cell_id,
+        }
+    )
     data["soil_temperature"] = xr.concat(
         [
             DataArray(np.full((13, 4), np.nan), dims=["dim_0", "cell_id"]),

tests/models/litter/conftest.py

@@ -68,12 +68,15 @@ def dummy_litter_data(layer_roles_fixture):
     )
 
     # The layer dependant data has to be handled separately
-    data["soil_moisture"] = concat(
+    data["matric_potential"] = concat(
         [
             DataArray(np.full((13, 3), np.nan), dims=["layers", "cell_id"]),
             # At present the soil model only uses the top soil layer, so this is the
             # only one with real test values in
-            DataArray([[0.25, 0.45, 0.3]], dims=["layers", "cell_id"]),
+            DataArray(
+                [[-10.0, -25.0, -100.0]],
+                dims=["layers", "cell_id"],
+            ),
             DataArray(np.full((1, 3), np.nan), dims=["layers", "cell_id"]),
         ],
         dim="layers",

tests/models/litter/test_litter_model.py

@@ -441,12 +441,12 @@ def test_update(litter_model_fixture, dummy_litter_data):
     end_above_meta = [0.29587973, 0.14851276, 0.07041856]
     end_above_struct = [0.50055126, 0.25010012, 0.0907076]
     end_woody = [4.702103, 11.802315, 7.300997]
-    end_below_meta = [0.394145, 0.35923, 0.069006]
-    end_below_struct = [0.60027118, 0.30975403, 0.02047743]
+    end_below_meta = [0.38949196, 0.36147436, 0.06906041]
+    end_below_struct = [0.60011634, 0.30989963, 0.02047753]
     end_lignin_above_struct = [0.4996410, 0.1004310, 0.6964345]
     end_lignin_woody = [0.49989001, 0.79989045, 0.34998229]
     end_lignin_below_struct = [0.499760108, 0.249922519, 0.737107757]
-    c_mineral = [0.0212182, 0.02746286, 0.00796359]
+    c_mineral = [0.02987233, 0.02316114, 0.00786517]
 
     litter_model_fixture.update(time_index=0)
 
@@ -468,23 +468,3 @@ def test_update(litter_model_fixture, dummy_litter_data):
         dummy_litter_data["lignin_below_structural"], end_lignin_below_struct
     )
     assert np.allclose(dummy_litter_data["litter_C_mineralisation_rate"], c_mineral)
-
-
-def test_convert_soil_moisture_to_water_potential(
-    dummy_litter_data, top_soil_layer_index
-):
-    """Test that function to convert soil moisture to a water potential works."""
-    from virtual_rainforest.models.litter.litter_model import (
-        convert_soil_moisture_to_water_potential,
-    )
-
-    expected_potentials = [-297.14104, -4.2647655, -79.666189]
-
-    actual_potentials = convert_soil_moisture_to_water_potential(
-        dummy_litter_data["soil_moisture"][top_soil_layer_index].to_numpy(),
-        air_entry_water_potential=LitterConsts.air_entry_water_potential,
-        water_retention_curvature=LitterConsts.water_retention_curvature,
-        saturated_water_content=LitterConsts.saturated_water_content,
-    )
-
-    assert np.allclose(actual_potentials, expected_potentials)

tests/models/litter/test_litter_pools.py

@@ -14,30 +14,25 @@ def temp_and_water_factors(
     dummy_litter_data, surface_layer_index, top_soil_layer_index
 ):
     """Temperature and water factors for the various litter layers."""
-    from virtual_rainforest.models.litter.litter_model import (
-        convert_soil_moisture_to_water_potential,
-    )
     from virtual_rainforest.models.litter.litter_pools import (
         calculate_environmental_factors,
     )
 
-    water_potentials = convert_soil_moisture_to_water_potential(
-        dummy_litter_data["soil_moisture"][top_soil_layer_index],
-        air_entry_water_potential=LitterConsts.air_entry_water_potential,
-        water_retention_curvature=LitterConsts.water_retention_curvature,
-        saturated_water_content=LitterConsts.saturated_water_content,
-    )
-
     environmental_factors = calculate_environmental_factors(
         surface_temp=dummy_litter_data["air_temperature"][surface_layer_index],
         topsoil_temp=dummy_litter_data["soil_temperature"][top_soil_layer_index],
-        water_potential=water_potentials,
+        water_potential=dummy_litter_data["matric_potential"][top_soil_layer_index],
         constants=LitterConsts,
     )
 
     return environmental_factors
 
 
+# TODO - Compare the below
+# [-297.1410435034187, -4.264765510307134, -79.66618999943468]
+# [-10.0, -25.0, -100.0]
+
+
 @pytest.fixture
 def decay_rates(dummy_litter_data, temp_and_water_factors):
     """Decay rates for the various litter pools."""
@@ -59,17 +54,14 @@ def test_calculate_environmental_factors(
         calculate_environmental_factors,
     )
 
-    # TODO - hardcoding this in, but eventually this should be added to the data object.
-    water_potentials = [-10.0, -25.0, -100.0]
-
     expected_water_factors = [1.0, 0.88496823, 0.71093190]
     expected_temp_above_factors = [0.1878681, 0.1878681, 0.1878681]
     expected_temp_below_factors = [0.2732009, 0.2732009, 0.2732009]
 
     environmental_factors = calculate_environmental_factors(
         surface_temp=dummy_litter_data["air_temperature"][surface_layer_index],
         topsoil_temp=dummy_litter_data["soil_temperature"][top_soil_layer_index],
-        water_potential=water_potentials,
+        water_potential=dummy_litter_data["matric_potential"][top_soil_layer_index],
         constants=LitterConsts,
     )
 
@@ -104,7 +96,7 @@ def test_calculate_moisture_effect_on_litter_decomp(top_soil_layer_index):
         calculate_moisture_effect_on_litter_decomp,
     )
 
-    water_potentials = [-10.0, -25.0, -100.0, -400.0]
+    water_potentials = np.array([-10.0, -25.0, -100.0, -400.0])
 
     expected_factor = [1.0, 0.88496823, 0.71093190, 0.53689556]
 
@@ -139,9 +131,6 @@ def test_calculate_change_in_litter_variables(
     dummy_litter_data, surface_layer_index, top_soil_layer_index
 ):
     """Test that litter pool update calculation is correct."""
-    from virtual_rainforest.models.litter.litter_model import (
-        convert_soil_moisture_to_water_potential,
-    )
     from virtual_rainforest.models.litter.litter_pools import (
         calculate_change_in_litter_variables,
     )
@@ -150,30 +139,24 @@ def test_calculate_change_in_litter_variables(
         "litter_pool_above_metabolic": [0.29587973, 0.14851276, 0.07041856],
         "litter_pool_above_structural": [0.50055126, 0.25010012, 0.0907076],
         "litter_pool_woody": [4.702103, 11.802315, 7.300997],
-        "litter_pool_below_metabolic": [0.394145, 0.35923, 0.069006],
-        "litter_pool_below_structural": [0.60027118, 0.30975403, 0.02047743],
+        "litter_pool_below_metabolic": [0.38949196, 0.36147436, 0.06906041],
+        "litter_pool_below_structural": [0.60011634, 0.30989963, 0.02047753],
         "lignin_above_structural": [0.4996410, 0.1004310, 0.6964345],
         "lignin_woody": [0.49989001, 0.79989045, 0.34998229],
         "lignin_below_structural": [0.499760108, 0.249922519, 0.737107757],
-        "litter_C_mineralisation_rate": [0.0212182, 0.02746286, 0.00796359],
+        "litter_C_mineralisation_rate": [0.02987233, 0.02316114, 0.00786517],
     }
 
-    # Calculate water potential
-    water_potential = convert_soil_moisture_to_water_potential(
-        dummy_litter_data["soil_moisture"][top_soil_layer_index].to_numpy(),
-        air_entry_water_potential=LitterConsts.air_entry_water_potential,
-        water_retention_curvature=LitterConsts.water_retention_curvature,
-        saturated_water_content=LitterConsts.saturated_water_content,
-    )
-
     result = calculate_change_in_litter_variables(
         surface_temp=dummy_litter_data["air_temperature"][
             surface_layer_index
         ].to_numpy(),
         topsoil_temp=dummy_litter_data["soil_temperature"][
             top_soil_layer_index
         ].to_numpy(),
-        water_potential=water_potential,
+        water_potential=dummy_litter_data["matric_potential"][
+            top_soil_layer_index
+        ].to_numpy(),
         above_metabolic=dummy_litter_data["litter_pool_above_metabolic"].to_numpy(),
         above_structural=dummy_litter_data["litter_pool_above_structural"].to_numpy(),
         woody=dummy_litter_data["litter_pool_woody"].to_numpy(),
@@ -200,8 +183,8 @@ def test_calculate_decay_rates(dummy_litter_data, temp_and_water_factors):
         "metabolic_above": [0.00450883, 0.00225442, 0.00105206],
         "structural_above": [1.67429665e-4, 6.18573593e-4, 1.10869077e-5],
         "woody": [0.0004832, 0.00027069, 0.0015888],
-        "metabolic_below": [0.00627503, 0.01118989, 0.00141417],
-        "structural_below": [2.08818451e-4, 7.25965456e-4, 2.56818870e-6],
+        "metabolic_below": [0.01092804, 0.00894564, 0.00135959],
+        "structural_below": [3.63659952e-04, 5.80365659e-04, 2.46907410e-06],
     }
 
     actual_decay = calculate_decay_rates(
@@ -362,7 +345,7 @@ def test_calculate_litter_decay_metabolic_below(
         calculate_litter_decay_metabolic_below,
     )
 
-    expected_decay = [0.00627503, 0.01118989, 0.00141417]
+    expected_decay = [0.01092804, 0.00894564, 0.00135959]
 
     actual_decay = calculate_litter_decay_metabolic_below(
         temperature_factor=temp_and_water_factors["temp_below"],
@@ -382,7 +365,7 @@ def test_calculate_litter_decay_structural_below(
         calculate_litter_decay_structural_below,
     )
 
-    expected_decay = [2.08818451e-04, 7.25965456e-04, 2.56818870e-06]
+    expected_decay = [3.63659952e-04, 5.80365659e-04, 2.46907410e-06]
 
     actual_decay = calculate_litter_decay_structural_below(
         temperature_factor=temp_and_water_factors["temp_below"],