Merge pull request #250 from ImperialCollegeLondon/test-imports

Updated module import in pmodel unit tests

docs/source/conf.py

@@ -90,6 +90,7 @@ class MyReferenceStyle(AuthorYearReferenceStyle):
     ("py:class", "numpy._typing._generic_alias.ScalarType"),
     ("py:class", "numpy.float32"),
     ("py:class", "numpy.timedelta64"),
+    ("py:class", "numpy.bool_"),
     ("py:class", "numpy.ndarray"),
     ("py:class", "numpy.dtype"),
     ("py:class", "numpy.dtype[+ScalarType]"),

pyrealm/core/utilities.py

@@ -94,7 +94,7 @@ def check_input_shapes(*args: float | int | np.generic | np.ndarray | None) -> t
         #    # Note that 0-dim ndarrays (which are scalars) pass through
         #    if val.ndim > 0:
         #        shapes.add(val.shape)
-        elif val is None or isinstance(val, float | int | np.generic):
+        elif val is None or isinstance(val, (float | int | np.generic)):
             pass  # No need to track scalars and optional values pass None
         else:
             raise ValueError(f"Unexpected input to check_input_shapes: {type(val)}")

tests/unit/pmodel/test_c3c4competition.py

@@ -11,13 +11,6 @@
 import numpy as np
 import pytest
 
-from pyrealm.pmodel import (
-    C3C4Competition,
-    CalcCarbonIsotopes,
-    PModel,
-    PModelEnvironment,
-)
-
 
 @pytest.mark.parametrize(
     argnames=["pmodel_c3_args", "pmodel_c4_args", "expected"],
@@ -74,6 +67,13 @@
 )
 def test_c3c4competition(pmodel_c3_args, pmodel_c4_args, expected):
     """Test the C3/C4 competition model."""
+    from pyrealm.pmodel import (
+        C3C4Competition,
+        CalcCarbonIsotopes,
+        PModel,
+        PModelEnvironment,
+    )
+
     env = PModelEnvironment(
         tc=np.array([20, 35]),
         patm=np.array([101325]),

tests/unit/pmodel/test_calc_carbon_isotopes.py

@@ -11,8 +11,6 @@
 import numpy as np
 import pytest
 
-from pyrealm.pmodel import CalcCarbonIsotopes, PModel, PModelEnvironment
-
 
 @pytest.mark.parametrize(
     argnames=["pmodelenv_args", "pmodel_args", "expected"],
@@ -69,6 +67,8 @@
 )
 def test_CalcCarbonIsotopes(pmodelenv_args, pmodel_args, expected):
     """Tests the CalcCarbonIsotopes class."""
+    from pyrealm.pmodel import CalcCarbonIsotopes, PModel, PModelEnvironment
+
     env = PModelEnvironment(**pmodelenv_args)
     pmodel = PModel(env, **pmodel_args)
     cci = CalcCarbonIsotopes(pmodel, d13CO2=np.array([-8.4]), D14CO2=np.array([19.2]))

tests/unit/pmodel/test_jmax_limitation.py

@@ -3,15 +3,13 @@
 import numpy as np
 import pytest
 
-# from pyrealm.constants import PModelConst
-from pyrealm.pmodel.jmax_limitation import JmaxLimitation
-from pyrealm.pmodel.optimal_chi import OptimalChiPrentice14
-from pyrealm.pmodel.pmodel_environment import PModelEnvironment
-
 
 @pytest.fixture
 def mock_optimal_chi():
     """Build an OptimalChiABC instance."""
+    from pyrealm.pmodel.optimal_chi import OptimalChiPrentice14
+    from pyrealm.pmodel.pmodel_environment import PModelEnvironment
+
     # Create an instance of OptimalChiABC for testing
     env = PModelEnvironment(
         tc=np.array([20]),
@@ -40,6 +38,8 @@ def mock_optimal_chi():
 )
 def test_jmax_limitation(mock_optimal_chi, method, expected_f_j, expected_f_v):
     """Test that JmaxLimitation class works as expected."""
+    from pyrealm.pmodel.jmax_limitation import JmaxLimitation
+
     # Create an instance of JmaxLimitation with mock OptimalChiABC and test method
     jmax_limitation = JmaxLimitation(mock_optimal_chi, method=method)
     # Assert that calculated f_j and f_v match expected values
@@ -49,6 +49,8 @@ def test_jmax_limitation(mock_optimal_chi, method, expected_f_j, expected_f_v):
 
 def test_invalid_method(mock_optimal_chi):
     """Test that JmaxLimitation raises ValueError for invalid method."""
+    from pyrealm.pmodel.jmax_limitation import JmaxLimitation
+
     # Test invalid method
     with pytest.raises(ValueError):
         JmaxLimitation(mock_optimal_chi, method="invalid_method")

tests/unit/pmodel/test_pmodel_environment.py

@@ -5,15 +5,6 @@
 import numpy as np
 import pytest
 
-from pyrealm.constants import CoreConst, PModelConst
-from pyrealm.pmodel.functions import (
-    calc_co2_to_ca,
-    calc_gammastar,
-    calc_kmm,
-    calc_ns_star,
-)
-from pyrealm.pmodel.pmodel_environment import PModelEnvironment
-
 """"Test that the pmodel environment calculates attributes match the expected values."""
 
 
@@ -36,6 +27,8 @@ def test_pmodel_environment(
     tc, vpd, co2, patm, expected_ca, expected_gammastar, expected_kmm, expected_ns_star
 ):
     """Test the PModelEnvironment class."""
+    from pyrealm.pmodel.pmodel_environment import PModelEnvironment
+
     env = PModelEnvironment(tc=tc, vpd=vpd, co2=co2, patm=patm)
 
     assert env.ca == pytest.approx(expected_ca, abs=1e-5)
@@ -62,6 +55,9 @@ def function_test_data():
 
 def test_out_of_bound_output(function_test_data):
     """Function to calculate kmm."""
+    from pyrealm.constants import PModelConst
+    from pyrealm.pmodel.functions import calc_kmm
+
     tc_ar_values, patm_ar_values, co2_ar_values = function_test_data
 
     pmodel_const = PModelConst()
@@ -84,6 +80,9 @@ def test_out_of_bound_output(function_test_data):
 
 def test_out_of_bound_output_ns_star(function_test_data):
     """Function to calculate ns_star."""
+    from pyrealm.constants import CoreConst
+    from pyrealm.pmodel.functions import calc_ns_star
+
     tc_ar_values, patm_ar_values, _ = function_test_data  # Ignore the third variable
 
     core_const = CoreConst(k_To=298.15, k_Po=101325)
@@ -106,6 +105,9 @@ def test_out_of_bound_output_ns_star(function_test_data):
 
 def test_out_of_bound_output_gammastar(function_test_data):
     """Function to calculate calc_gammastar."""
+    from pyrealm.constants import CoreConst, PModelConst
+    from pyrealm.pmodel.functions import calc_gammastar
+
     tc_ar_values, patm_ar_values, _ = function_test_data
 
     core_const = CoreConst(k_To=298.15, k_Po=101325)
@@ -131,6 +133,8 @@ def test_out_of_bound_output_gammastar(function_test_data):
 
 def test_out_of_bound_output_co2_to_ca(function_test_data):
     """Function to calculate co2_to_ca."""
+    from pyrealm.pmodel.functions import calc_co2_to_ca
+
     _, patm_ar_values, co2_ar_values = function_test_data
 
     co2_to_ca_lower_bound = 0