test/docs(model): add some unit tests for Model + update log with thoughts

Author: amyheather

docs/log.md

@@ -612,4 +612,119 @@ class Model:
 
         # Run the simulation
         self.env.run(until=run_length)
+```
+
+## Tests
+
+We could add some basic tests now, e.g.
+
+* Check that distributions are created for all patients (eg. "stroke" in distributions asu, "tia" in ...)
+* Run with no warm-up and check env.now == param.data_collection_period
+* Run with no data collection and check env.now == param.warm_up 
+
+Although as not actually doing warm-up logic yet, going down that path a bit premature.
+
+> 💡 Start with basic run time, then change to warm up + data collection
+
+> 💡 Maybe don't need to be mentioning tests at this stage yet.
+
+```
+class MockParam:
+    """
+    Mock parameter class.
+    """
+    def __init__(self):
+        """
+        Initialise with specific run periods and arrival parameters.
+        """
+        self.warm_up_period = 10
+        self.data_collection_period = 20
+
+        self.asu_arrivals = namedtuple(
+            "ASUArrivals", ["stroke", "tia", "neuro", "other"])(
+            stroke=5, tia=7, neuro=10, other=15
+        )
+        self.rehab_arrivals = namedtuple(
+            "RehabArrivals", ["stroke", "tia", "other"])(
+            stroke=8, tia=12, other=20
+        )
+
+
+def test_create_distributions():
+    """
+    Test that distributions are created correctly for all units and patient
+    types specified in MockParam.
+    """
+    param = MockParam()
+    model = Model(param, run_number=42)
+
+    # Check ASU distributions
+    assert len(model.distributions["asu"]) == 4
+    assert "stroke" in model.distributions["asu"]
+    assert "tia" in model.distributions["asu"]
+    assert "neuro" in model.distributions["asu"]
+    assert "other" in model.distributions["asu"]
+
+    # Check Rehab distributions
+    assert len(model.distributions["rehab"]) == 3
+    assert "stroke" in model.distributions["rehab"]
+    assert "tia" in model.distributions["rehab"]
+    assert "other" in model.distributions["rehab"]
+    assert "neuro" not in model.distributions["rehab"]
+
+    # Check that all distributions are Exponential
+    for _, unit_dict in model.distributions.items():
+        for patient_type in unit_dict:
+            assert isinstance(unit_dict[patient_type], Exponential)
+
+
+def test_sampling_seed_reproducibility():
+    """
+    Test that using the same seed produces the same results when sampling
+    from one of the arrival distributions.
+    """
+    param = MockParam()
+
+    # Create two models with the same seed
+    model1 = Model(param, run_number=123)
+    model2 = Model(param, run_number=123)
+
+    # Sample from a distribution in both models
+    samples1 = [model1.distributions["asu"]["stroke"].sample()
+                for _ in range(10)]
+    samples2 = [model2.distributions["asu"]["stroke"].sample()
+                for _ in range(10)]
+
+    # Check that the samples are the same
+    np.testing.assert_array_almost_equal(samples1, samples2)
+
+
+def test_run_time():
+    """
+    Check that the run length is correct with varying warm-up and data
+    collection periods.
+    """
+    param = MockParam()
+
+    # Test with zero warm-up period
+    param.warm_up_period = 0
+    model = Model(param, run_number=42)
+    model.run()
+    assert model.env.now == param.data_collection_period
+
+    # Test with zero data collection period
+    param.warm_up_period = 10
+    param.data_collection_period = 0
+    model = Model(param, run_number=42)
+    model.run()
+    assert model.env.now == 10
+    # assert len(model.patients) == 0
+
+    # Test with warm-up and data collection period
+    param.warm_up_period = 12
+    param.data_collection_period = 9
+    model = Model(param, run_number=42)
+    model.run()
+    assert model.env.now == 21
+    assert len(model.patients) > 0
 ```

tests/test_unittest.py

@@ -2,13 +2,21 @@
 Unit tests
 """
 
+from collections import namedtuple
+import numpy as np
 import pytest
+from sim_tools.distributions import Exponential
 
 from simulation.parameters import (
     ASUArrivals, RehabArrivals, ASULOS, RehabLOS,
     ASURouting, RehabRouting, Param)
+from simulation.model import Model
 
 
+# -----------------------------------------------------------------------------
+# Parameters
+# -----------------------------------------------------------------------------
+
 @pytest.mark.parametrize("class_to_test", [
     ASUArrivals, RehabArrivals, ASULOS, RehabLOS,
     ASURouting, RehabRouting, Param])
@@ -27,3 +35,107 @@ def test_new_attribute(class_to_test):
     with pytest.raises(AttributeError,
                        match="only possible to modify existing attributes"):
         setattr(instance, "new_entry", 3)
+
+
+# -----------------------------------------------------------------------------
+# Model
+# -----------------------------------------------------------------------------
+
+class MockParam:
+    """
+    Mock parameter class.
+    """
+    def __init__(self):
+        """
+        Initialise with specific run periods and arrival parameters.
+        """
+        self.warm_up_period = 10
+        self.data_collection_period = 20
+
+        self.asu_arrivals = namedtuple(
+            "ASUArrivals", ["stroke", "tia", "neuro", "other"])(
+            stroke=5, tia=7, neuro=10, other=15
+        )
+        self.rehab_arrivals = namedtuple(
+            "RehabArrivals", ["stroke", "tia", "other"])(
+            stroke=8, tia=12, other=20
+        )
+
+
+def test_create_distributions():
+    """
+    Test that distributions are created correctly for all units and patient
+    types specified in MockParam.
+    """
+    param = MockParam()
+    model = Model(param, run_number=42)
+
+    # Check ASU distributions
+    assert len(model.distributions["asu"]) == 4
+    assert "stroke" in model.distributions["asu"]
+    assert "tia" in model.distributions["asu"]
+    assert "neuro" in model.distributions["asu"]
+    assert "other" in model.distributions["asu"]
+
+    # Check Rehab distributions
+    assert len(model.distributions["rehab"]) == 3
+    assert "stroke" in model.distributions["rehab"]
+    assert "tia" in model.distributions["rehab"]
+    assert "other" in model.distributions["rehab"]
+    assert "neuro" not in model.distributions["rehab"]
+
+    # Check that all distributions are Exponential
+    for _, unit_dict in model.distributions.items():
+        for patient_type in unit_dict:
+            assert isinstance(unit_dict[patient_type], Exponential)
+
+
+def test_sampling_seed_reproducibility():
+    """
+    Test that using the same seed produces the same results when sampling
+    from one of the arrival distributions.
+    """
+    param = MockParam()
+
+    # Create two models with the same seed
+    model1 = Model(param, run_number=123)
+    model2 = Model(param, run_number=123)
+
+    # Sample from a distribution in both models
+    samples1 = [model1.distributions["asu"]["stroke"].sample()
+                for _ in range(10)]
+    samples2 = [model2.distributions["asu"]["stroke"].sample()
+                for _ in range(10)]
+
+    # Check that the samples are the same
+    np.testing.assert_array_almost_equal(samples1, samples2)
+
+
+def test_run_time():
+    """
+    Check that the run length is correct with varying warm-up and data
+    collection periods.
+    """
+    param = MockParam()
+
+    # Test with zero warm-up period
+    param.warm_up_period = 0
+    model = Model(param, run_number=42)
+    model.run()
+    assert model.env.now == param.data_collection_period
+
+    # Test with zero data collection period
+    param.warm_up_period = 10
+    param.data_collection_period = 0
+    model = Model(param, run_number=42)
+    model.run()
+    assert model.env.now == 10
+    # assert len(model.patients) == 0
+
+    # Test with warm-up and data collection period
+    param.warm_up_period = 12
+    param.data_collection_period = 9
+    model = Model(param, run_number=42)
+    model.run()
+    assert model.env.now == 21
+    assert len(model.patients) > 0