fix(test)/style(lint): fixed the tests (removing dependence on MockParam) and lint

Author: amyheather

notebooks/analysis.ipynb

@@ -1,5 +1,12 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Analysis"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -11,13 +18,11 @@
     "%autoreload 1\n",
     "%aimport simulation\n",
     "\n",
-    "from collections import Counter\n",
+    "# pylint: disable=wrong-import-position\n",
     "import os\n",
-    "import pandas as pd\n",
     "import plotly.express as px\n",
     "\n",
     "from simulation.parameters import Param\n",
-    "from simulation.model import Model\n",
     "from simulation.runner import Runner"
    ]
   },
@@ -195,6 +200,9 @@
     "        unit_lab = \"acute\"\n",
     "    elif unit == \"rehab\":\n",
     "        unit_lab = \"rehabilitation\"\n",
+    "    else:\n",
+    "        raise ValueError(\"unit must be either 'acute' or 'rehab'\")\n",
+    "\n",
     "    fig.update_layout(\n",
     "        xaxis_title=f\"No. patients in {unit_lab} unit\",\n",
     "        yaxis_title=\"% observations\",\n",
@@ -2116,6 +2124,9 @@
     "        unit_lab = \"acute\"\n",
     "    elif unit == \"rehab\":\n",
     "        unit_lab = \"rehabilitation\"\n",
+    "    else:\n",
+    "        raise ValueError(\"unit must be either 'acute' or 'rehab'\")\n",
+    "\n",
     "    fig.update_layout(\n",
     "        xaxis_title=f\"No. of {unit_lab} beds available\",\n",
     "        yaxis_title=\"Probability of delay\",\n",

simulation/model.py

@@ -129,26 +129,6 @@ def __init__(self, param, run_number):
             rehab_param=self.param.rehab_los,
             distribution_type="lognormal")
 
-        # Add model initialisation details to the log
-        self.param.logger.log(sim_time=self.env.now, msg="Initialise model:\n")
-        self.param.logger.log(vars(self))
-        self.param.logger.log(msg="Parameters:\n ")
-        self.param.logger.log(vars(self.param))
-        self.param.logger.log(msg="Logger:\n ")
-        self.param.logger.log(vars(self.param.logger))
-        self.param.logger.log(msg="ASU arrivals:\n ")
-        self.param.logger.log(vars(self.param.asu_arrivals))
-        self.param.logger.log(msg="ASU LOS:\n ")
-        self.param.logger.log(vars(self.param.asu_los))
-        self.param.logger.log(msg="ASU routing:\n ")
-        self.param.logger.log(vars(self.param.asu_routing))
-        self.param.logger.log(msg="Rehab arrivals:\n ")
-        self.param.logger.log(vars(self.param.rehab_arrivals))
-        self.param.logger.log(msg="Rehab LOS:\n ")
-        self.param.logger.log(vars(self.param.rehab_los))
-        self.param.logger.log(msg="Rehab routing:\n ")
-        self.param.logger.log(vars(self.param.rehab_routing))
-
     def create_distributions(self, asu_param, rehab_param, distribution_type):
         """
         Create a nested dictionary with two items: "asu" and "rehab". Each
@@ -377,6 +357,26 @@ def run(self):
         """
         Run the simulation.
         """
+        # Add model initialisation details to the log
+        self.param.logger.log(sim_time=self.env.now, msg="Initialise model:\n")
+        self.param.logger.log(vars(self))
+        self.param.logger.log(msg="Parameters:\n ")
+        self.param.logger.log(vars(self.param))
+        self.param.logger.log(msg="Logger:\n ")
+        self.param.logger.log(vars(self.param.logger))
+        self.param.logger.log(msg="ASU arrivals:\n ")
+        self.param.logger.log(vars(self.param.asu_arrivals))
+        self.param.logger.log(msg="ASU LOS:\n ")
+        self.param.logger.log(vars(self.param.asu_los))
+        self.param.logger.log(msg="ASU routing:\n ")
+        self.param.logger.log(vars(self.param.asu_routing))
+        self.param.logger.log(msg="Rehab arrivals:\n ")
+        self.param.logger.log(vars(self.param.rehab_arrivals))
+        self.param.logger.log(msg="Rehab LOS:\n ")
+        self.param.logger.log(vars(self.param.rehab_los))
+        self.param.logger.log(msg="Rehab routing:\n ")
+        self.param.logger.log(vars(self.param.rehab_routing))
+
         # Calculate the total run length
         run_length = (self.param.warm_up_period +
                       self.param.data_collection_period)

tests/test_unittest.py

@@ -41,51 +41,36 @@ def test_new_attribute(class_to_test):
 # 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.
+    types specified.
     """
-    param = MockParam()
+    param = Param(
+        asu_arrivals=namedtuple(
+            "ASUArrivals", ["stroke", "tia", "neuro", "other"])(
+            stroke=5, tia=7, neuro=10, other=15),
+        rehab_arrivals=namedtuple(
+            "RehabArrivals", ["stroke", "tia", "other"])(
+            stroke=8, tia=12, other=20))
     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():
+    # Check ASU arrival distributions
+    assert len(model.arrival_dist["asu"]) == 4
+    assert "stroke" in model.arrival_dist["asu"]
+    assert "tia" in model.arrival_dist["asu"]
+    assert "neuro" in model.arrival_dist["asu"]
+    assert "other" in model.arrival_dist["asu"]
+
+    # Check Rehab arrival distributions
+    assert len(model.arrival_dist["rehab"]) == 3
+    assert "stroke" in model.arrival_dist["rehab"]
+    assert "tia" in model.arrival_dist["rehab"]
+    assert "other" in model.arrival_dist["rehab"]
+    assert "neuro" not in model.arrival_dist["rehab"]
+
+    # Check that all arrival distributions are Exponential
+    for _, unit_dict in model.arrival_dist.items():
         for patient_type in unit_dict:
             assert isinstance(unit_dict[patient_type], Exponential)
 
@@ -95,16 +80,16 @@ 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()
+    param = Param()
 
     # 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()
+    samples1 = [model1.arrival_dist["asu"]["stroke"].sample()
                 for _ in range(10)]
-    samples2 = [model2.distributions["asu"]["stroke"].sample()
+    samples2 = [model2.arrival_dist["asu"]["stroke"].sample()
                 for _ in range(10)]
 
     # Check that the samples are the same
@@ -116,7 +101,7 @@ def test_run_time():
     Check that the run length is correct with varying warm-up and data
     collection periods.
     """
-    param = MockParam()
+    param = Param(warm_up_period=10, data_collection_period=20)
 
     # Test with zero warm-up period
     param.warm_up_period = 0