Variables 1 vgro

tests/core/test_base_model.py

@@ -53,14 +53,9 @@ def data_instance():
         pytest.param(
             {
                 "model_name": "should_pass",
-                "required_init_vars": (
-                    (
-                        "temperature",
-                        ("spatial",),
-                    ),
-                ),
+                "required_init_vars": ("temperature", "wind_speed"),
                 "model_update_bounds": ("1 day", "1 month"),
-                "vars_updated": [],
+                "vars_updated": (),
             },
             does_not_raise(),
             None,
@@ -72,7 +67,7 @@ def data_instance():
                 "model_name": 9,
                 "required_init_vars": (),
                 "model_update_bounds": ("1 day", "1 month"),
-                "vars_updated": [],
+                "vars_updated": (),
             },
             pytest.raises(TypeError),
             "Class attribute model_name in UnnamedModel is not a string",
@@ -87,7 +82,7 @@ def data_instance():
                 "model_name": "should_pass",
                 "required_init_vars": (),
                 "model_update_bounds": ("1 day", "1 time"),
-                "vars_updated": [],
+                "vars_updated": (),
             },
             pytest.raises(ValueError),
             "Class attribute model_update_bounds for UnnamedModel "
@@ -107,7 +102,7 @@ def data_instance():
                 "model_name": "should_pass",
                 "required_init_vars": (),
                 "model_update_bounds": ("1 day", "1 day"),
-                "vars_updated": [],
+                "vars_updated": (),
             },
             pytest.raises(ValueError),
             "Lower time bound for UnnamedModel is not less than the upper bound.",
@@ -126,7 +121,7 @@ def data_instance():
                 "model_name": "should_pass",
                 "required_init_vars": (),
                 "model_update_bounds": ("1 day", "1 second"),
-                "vars_updated": [],
+                "vars_updated": (),
             },
             pytest.raises(ValueError),
             "Lower time bound for UnnamedModel is not less than the upper bound.",
@@ -145,7 +140,7 @@ def data_instance():
                 "model_name": "should_pass",
                 "required_init_vars": (),
                 "model_update_bounds": ("1 meter", "1 day"),
-                "vars_updated": [],
+                "vars_updated": (),
             },
             pytest.raises(ValueError),
             "Class attribute model_update_bounds for UnnamedModel "
@@ -165,7 +160,7 @@ def data_instance():
                 "model_name": "should_pass",
                 "required_init_vars": (),
                 "model_update_bounds": ("1 spongebob", "1 day"),
-                "vars_updated": [],
+                "vars_updated": (),
             },
             pytest.raises(ValueError),
             "Class attribute model_update_bounds for UnnamedModel "
@@ -206,54 +201,40 @@ class UnnamedModel(BaseModel, **init_args):
 
 
 @pytest.mark.parametrize(
-    argnames="riv_value, exp_raise, exp_msg",
+    argnames="value, exp_raise, exp_msg",
     argvalues=[
         pytest.param(
             1,
             pytest.raises(TypeError),
             "Class attribute required_init_vars has the wrong structure in UM",
-            id="RIV is integer",
-        ),
-        pytest.param(
-            ["temperature", (1, 2)],
-            pytest.raises(TypeError),
-            "Class attribute required_init_vars has the wrong structure in UM",
-            id="RIV is list",
-        ),
-        pytest.param(
-            ("temperature", ("spatial",)),
-            pytest.raises(TypeError),
-            "Class attribute required_init_vars has the wrong structure in UM",
-            id="RIV is not nested enough",
+            id="value is integer",
         ),
         pytest.param(
-            (("temperature", (1,)),),
+            ["temperature", "wind_speed"],
             pytest.raises(TypeError),
             "Class attribute required_init_vars has the wrong structure in UM",
-            id="RIV axis is not string",
+            id="value is list",
         ),
         pytest.param(
-            (("temperature", (1,), (2,)),),
+            ("temperature", 1),
             pytest.raises(TypeError),
             "Class attribute required_init_vars has the wrong structure in UM",
-            id="RIV entry is too long",
+            id="value not all strings",
         ),
         pytest.param(
-            (("temperature", ("special",)),),
-            pytest.raises(ValueError),
-            "Class attribute required_init_vars uses unknown core axes in UM: special",
-            id="RIV entry has bad axis name",
-        ),
-        pytest.param(
-            (("temperature", ("spatial",)),),
+            ("temperature", "wind_speed"),
             does_not_raise(),
             None,
-            id="RIV ok",
+            id="value ok",
         ),
     ],
 )
-def test_check_required_init_var_structure(riv_value, exp_raise, exp_msg):
-    """Test that  __init_subclass__ traps bad values for required_init_vars."""
+def test_check_variable_attribute_structure(value, exp_raise, exp_msg):
+    """Test that  __init_subclass__ traps bad values for required_init_vars.
+
+    This could also test the other BaseModel variable attributes, but this checks
+    the mechanism.
+    """
 
     # BaseModel is required here in the code being exec'd from the params.
     from virtual_ecosystem.core.base_model import BaseModel
@@ -263,9 +244,9 @@ def test_check_required_init_var_structure(riv_value, exp_raise, exp_msg):
         class UM(
             BaseModel,
             model_name="should_also_pass",
-            required_init_vars=riv_value,
+            required_init_vars=value,
             model_update_bounds=("1 day", "1 month"),
-            vars_updated=[],
+            vars_updated=(),
         ):
             pass
 
@@ -287,7 +268,7 @@ class InitVarModel(
         model_name="init_var",
         model_update_bounds=("1 second", "1 year"),
         required_init_vars=(),
-        vars_updated=[],
+        vars_updated=(),
     ):
         pass
 
@@ -303,6 +284,10 @@ class InitVarModel(
     assert str(err.value).startswith("Can't instantiate abstract class InitVarModel ")
 
 
+@pytest.mark.skip(
+    "This functionality is going to be handed off to the variables system "
+    "so skipping for now but this will probably be deleted"
+)
 @pytest.mark.parametrize(
     argnames="req_init_vars, raises, exp_err_msg, exp_log",
     argvalues=[
@@ -489,7 +474,7 @@ class TimingTestModel(
         model_name="timing_test",
         model_update_bounds=("1 day", "1 month"),
         required_init_vars=(),
-        vars_updated=[],
+        vars_updated=(),
     ):
         def setup(self) -> None:
             pass

tests/core/test_variables.py

@@ -127,7 +127,9 @@ def test_output_known_variables(known_variables, mocker, tmpdir):
     assert "test_var" in variables.RUN_VARIABLES_REGISTRY
     variables.register_all_variables.assert_called_once()
     variables._discover_models.assert_called_once()
-    variables._collect_initialise_by_vars.assert_called_once_with([])
+    variables._collect_initialise_by_vars.assert_called_once_with(
+        [], check_unique_initialisation=False
+    )
     variables._collect_required_init_vars.assert_called_once_with([])
     variables._collect_updated_by_vars.assert_called_once_with([])
     variables._collect_required_update_vars.assert_called_once_with([])
@@ -239,7 +241,7 @@ def test_collect_required_init_vars(known_variables, run_variables):
 
     class TestModel:
         model_name = "TestModel"
-        required_init_vars = (("test_var", tuple()),)
+        required_init_vars = ("test_var",)
 
     with pytest.raises(ValueError, match="not in the known variables registry."):
         variables._collect_required_init_vars([TestModel])

tests/models/abiotic/test_abiotic_model.py

@@ -11,6 +11,14 @@
 from tests.conftest import log_check
 from virtual_ecosystem.core.exceptions import ConfigurationError
 
+REQUIRED_INIT_VAR_CHECKS = (
+    (DEBUG, "abiotic model: required var 'air_temperature_ref' checked"),
+    (DEBUG, "abiotic model: required var 'relative_humidity_ref' checked"),
+    (DEBUG, "abiotic model: required var 'topofcanopy_radiation' checked"),
+    (DEBUG, "abiotic model: required var 'leaf_area_index' checked"),
+    (DEBUG, "abiotic model: required var 'layer_heights' checked"),
+)
+
 
 def test_abiotic_model_initialization(
     caplog, dummy_climate_data, fixture_core_components
@@ -36,11 +44,7 @@ def test_abiotic_model_initialization(
     # Final check that expected logging entries are produced
     log_check(
         caplog,
-        expected_log=(
-            (DEBUG, "abiotic model: required var 'air_temperature_ref' checked"),
-            (DEBUG, "abiotic model: required var 'relative_humidity_ref' checked"),
-            (DEBUG, "abiotic model: required var 'topofcanopy_radiation' checked"),
-        ),
+        expected_log=REQUIRED_INIT_VAR_CHECKS,
     )
 
 
@@ -80,6 +84,14 @@ def test_abiotic_model_initialization_no_data(caplog, fixture_core_components):
                 ERROR,
                 "abiotic model: init data missing required var 'topofcanopy_radiation'",
             ),
+            (
+                ERROR,
+                "abiotic model: init data missing required var 'leaf_area_index'",
+            ),
+            (
+                ERROR,
+                "abiotic model: init data missing required var 'layer_heights'",
+            ),
             (ERROR, "abiotic model: error checking required_init_vars, see log."),
         ),
     )
@@ -99,9 +111,7 @@ def test_abiotic_model_initialization_no_data(caplog, fixture_core_components):
                     "Information required to initialise the abiotic model successfully "
                     "extracted.",
                 ),
-                (DEBUG, "abiotic model: required var 'air_temperature_ref' checked"),
-                (DEBUG, "abiotic model: required var 'relative_humidity_ref' checked"),
-                (DEBUG, "abiotic model: required var 'topofcanopy_radiation' checked"),
+                *REQUIRED_INIT_VAR_CHECKS,
             ),
             id="default_config",
         ),
@@ -117,9 +127,7 @@ def test_abiotic_model_initialization_no_data(caplog, fixture_core_components):
                     "Information required to initialise the abiotic model successfully "
                     "extracted.",
                 ),
-                (DEBUG, "abiotic model: required var 'air_temperature_ref' checked"),
-                (DEBUG, "abiotic model: required var 'relative_humidity_ref' checked"),
-                (DEBUG, "abiotic model: required var 'topofcanopy_radiation' checked"),
+                *REQUIRED_INIT_VAR_CHECKS,
             ),
             id="modified_config_correct",
         ),
@@ -182,9 +190,7 @@ def test_generate_abiotic_model(
                     "Information required to initialise the abiotic model "
                     "successfully extracted.",
                 ),
-                (DEBUG, "abiotic model: required var 'air_temperature_ref' checked"),
-                (DEBUG, "abiotic model: required var 'relative_humidity_ref' checked"),
-                (DEBUG, "abiotic model: required var 'topofcanopy_radiation' checked"),
+                *REQUIRED_INIT_VAR_CHECKS,
                 (
                     ERROR,
                     "The update interval is slower than the abiotic upper "

tests/models/hydrology/test_above_ground.py

@@ -53,11 +53,7 @@ def test_calculate_soil_evaporation(dens_air, latvap):
     )
 
     exp_evap = np.array([0.745206, 0.092515, 0.135078])
-    exp_ra = np.array([12.5, 50.0, 1250.0])
     np.testing.assert_allclose(result["soil_evaporation"], exp_evap, rtol=0.01)
-    np.testing.assert_allclose(
-        result["aerodynamic_resistance_surface"], exp_ra, rtol=0.01
-    )
 
 
 def test_find_lowest_neighbour(dummy_climate_data):

tests/models/plants/test_canopy.py

@@ -105,7 +105,7 @@ def test_initialise_canopy_layers(plants_data, fixture_core_components):
         "leaf_area_index",
         "layer_fapar",
         "layer_leaf_mass",
-        "layer_absorbed_irradiation",
+        "canopy_absorption",
     )
 
     n_layer = 1 + 10 + 2 + 2

tests/models/plants/test_plants_model.py

@@ -25,7 +25,7 @@ def test_PlantsModel__init__(plants_data, flora, fixture_core_components):
         ("layer_heights", (32 + 30 + 20 + 10 + 1.5 + 0.1 - 0.25 - 1) * 4),
         ("leaf_area_index", 3 * 4),
         ("layer_fapar", (0.4 + 0.2 + 0.1) * 4),
-        ("layer_absorbed_irradiation", 1000 * 4),
+        ("canopy_absorption", 1000 * 4),
     ]
 
     for layer_name, layer_sum in expected_layers:
@@ -51,7 +51,7 @@ def test_PlantsModel_from_config(plants_data, fixture_config, fixture_core_compo
         ("layer_heights", (32 + 30 + 20 + 10 + 1.5 + 0.1 - 0.25 - 1) * 4),
         ("leaf_area_index", 3 * 4),
         ("layer_fapar", (0.4 + 0.2 + 0.1) * 4),
-        ("layer_absorbed_irradiation", 1000 * 4),
+        ("canopy_absorption", 1000 * 4),
     )
 
     for layer_name, layer_sum in expected_layers:
@@ -66,7 +66,7 @@ def test_PlantsModel_update_canopy_layers(fxt_plants_model):
         ("layer_heights", (32 + 30 + 20 + 10) * 4),
         ("leaf_area_index", 3 * 4),
         ("layer_fapar", (0.4 + 0.2 + 0.1) * 4),
-        ("layer_absorbed_irradiation", 0),  # Note that this layer should not be updated
+        ("canopy_absorption", 0),  # Note that this layer should not be updated
     )
 
     # Overwrite the existing data in each layer
@@ -89,7 +89,7 @@ def test_PlantsModel_set_absorbed_irradiance(fxt_plants_model):
         ("layer_heights", (32 + 30 + 20 + 10) * 4),
         ("leaf_area_index", 3 * 4),
         ("layer_fapar", (0.4 + 0.2 + 0.1) * 4),
-        ("layer_absorbed_irradiation", 1000 * 4),  # Is restored by additional call.
+        ("canopy_absorption", 1000 * 4),  # Is restored by additional call.
     )
     # Overwrite the existing data in each layer
     for layer, _ in expected_layers:
@@ -164,7 +164,7 @@ def test_PlantsModel_update(fxt_plants_model):
         ("leaf_area_index", 3 * 4),
         ("layer_fapar", (0.4 + 0.2 + 0.1) * 4),
         ("layer_leaf_mass", 30000 * 4),
-        ("layer_absorbed_irradiation", 1000 * 4),
+        ("canopy_absorption", 1000 * 4),
     )
 
     # Overwrite the existing data in each layer