refactor(tests): move test_negative_inputs to unit test

Although it uses Param and Model, it is focussed on testing functionality of Model in detecting invalid parameters, so feels appropriately classified as a unit test

tests/test_functionaltest.py

@@ -20,42 +20,6 @@
 from simulation.model import Param, Model, Runner, MonitoredResource
 
 
-@pytest.mark.parametrize('param_name, value, rule', [
-    ('patient_inter', 0, 'positive'),
-    ('mean_n_consult_time', 0, 'positive'),
-    ('number_of_runs', 0, 'positive'),
-    ('audit_interval', 0, 'positive'),
-    ('warm_up_period', -1, 'non_negative'),
-    ('data_collection_period', -1, 'non_negative')
-])
-def test_negative_inputs(param_name, value, rule):
-    """
-    Check that the model fails when inputs that are zero or negative are used.
-
-    Arguments:
-        param_name (string):
-            Name of parameter to change in the Param() class.
-        value (float|int):
-            Invalid value for parameter.
-        rule (string):
-            Either 'positive' (if value must be > 0) or 'non-negative' (if
-            value must be >= 0).
-    """
-    # Create parameter class with an invalid value
-    param = Param(**{param_name: value})
-
-    # Construct the expected error message
-    if rule == 'positive':
-        expected_message = f'Parameter "{param_name}" must be greater than 0.'
-    else:
-        expected_message = (f'Parameter "{param_name}" must be greater than ' +
-                            'or equal to 0.')
-
-    # Verify that initialising the model raises the correct error
-    with pytest.raises(ValueError, match=expected_message):
-        Model(param=param, run_number=0)
-
-
 def test_negative_results():
     """
     Check that values are non-negative.

tests/test_unittest.py

@@ -22,7 +22,7 @@
 import pytest
 
 from simulation.logging import SimLogger
-from simulation.model import Param, Exponential
+from simulation.model import Param, Model, Exponential
 
 
 def test_new_attribute():
@@ -38,6 +38,42 @@ def test_new_attribute():
         param.new_entry = 3
 
 
+@pytest.mark.parametrize('param_name, value, rule', [
+    ('patient_inter', 0, 'positive'),
+    ('mean_n_consult_time', 0, 'positive'),
+    ('number_of_runs', 0, 'positive'),
+    ('audit_interval', 0, 'positive'),
+    ('warm_up_period', -1, 'non_negative'),
+    ('data_collection_period', -1, 'non_negative')
+])
+def test_negative_inputs(param_name, value, rule):
+    """
+    Check that the model fails when inputs that are zero or negative are used.
+
+    Arguments:
+        param_name (string):
+            Name of parameter to change in the Param() class.
+        value (float|int):
+            Invalid value for parameter.
+        rule (string):
+            Either 'positive' (if value must be > 0) or 'non-negative' (if
+            value must be >= 0).
+    """
+    # Create parameter class with an invalid value
+    param = Param(**{param_name: value})
+
+    # Construct the expected error message
+    if rule == 'positive':
+        expected_message = f'Parameter "{param_name}" must be greater than 0.'
+    else:
+        expected_message = (f'Parameter "{param_name}" must be greater than ' +
+                            'or equal to 0.')
+
+    # Verify that initialising the model raises the correct error
+    with pytest.raises(ValueError, match=expected_message):
+        Model(param=param, run_number=0)
+
+
 def test_exponentional():
     """
     Test that the Exponentional class behaves as expected.