Préparation WEI 2023

apps/wei/tests/test_wei_algorithm_2023.py

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+# Copyright (C) 2018-2023 by BDE ENS Paris-Saclay
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import random
+
+from django.contrib.auth.models import User
+from django.test import TestCase
+
+from ..forms.surveys.wei2023 import WEIBusInformation2023, WEISurvey2023, WORDS, WEISurveyInformation2023
+from ..models import Bus, WEIClub, WEIRegistration
+
+
+class TestWEIAlgorithm(TestCase):
+    """
+    Run some tests to ensure that the WEI algorithm is working well.
+    """
+    fixtures = ('initial',)
+
+    def setUp(self):
+        """
+        Create some test data, with one WEI and 10 buses with random score attributions.
+        """
+        self.wei = WEIClub.objects.create(
+            name="WEI 2023",
+            email="wei2023@example.com",
+            date_start='2023-09-16',
+            date_end='2023-09-18',
+            year=2023,
+        )
+
+        self.buses = []
+        for i in range(10):
+            bus = Bus.objects.create(wei=self.wei, name=f"Bus {i}", size=10)
+            self.buses.append(bus)
+            information = WEIBusInformation2023(bus)
+            for word in WORDS:
+                information.scores[word] = random.randint(0, 101)
+            information.save()
+            bus.save()
+
+    def test_survey_algorithm_small(self):
+        """
+        There are only a few people in each bus, ensure that each person has its best bus
+        """
+        # Add a few users
+        for i in range(10):
+            user = User.objects.create(username=f"user{i}")
+            registration = WEIRegistration.objects.create(
+                user=user,
+                wei=self.wei,
+                first_year=True,
+                birth_date='2000-01-01',
+            )
+            information = WEISurveyInformation2023(registration)
+            for j in range(1, 21):
+                setattr(information, f'word{j}', random.choice(WORDS))
+            information.step = 20
+            information.save(registration)
+            registration.save()
+
+        # Run algorithm
+        WEISurvey2023.get_algorithm_class()().run_algorithm()
+
+        # Ensure that everyone has its first choice
+        for r in WEIRegistration.objects.filter(wei=self.wei).all():
+            survey = WEISurvey2023(r)
+            preferred_bus = survey.ordered_buses()[0][0]
+            chosen_bus = survey.information.get_selected_bus()
+            self.assertEqual(preferred_bus, chosen_bus)
+
+    def test_survey_algorithm_full(self):
+        """
+        Buses are full of first year people, ensure that they are happy
+        """
+        # Add a lot of users
+        for i in range(95):
+            user = User.objects.create(username=f"user{i}")
+            registration = WEIRegistration.objects.create(
+                user=user,
+                wei=self.wei,
+                first_year=True,
+                birth_date='2000-01-01',
+            )
+            information = WEISurveyInformation2023(registration)
+            for j in range(1, 21):
+                setattr(information, f'word{j}', random.choice(WORDS))
+            information.step = 20
+            information.save(registration)
+            registration.save()
+
+        # Run algorithm
+        WEISurvey2023.get_algorithm_class()().run_algorithm()
+
+        penalty = 0
+        # Ensure that everyone seems to be happy
+        # We attribute a penalty for each user that didn't have its first choice
+        # The penalty is the square of the distance between the score of the preferred bus
+        # and the score of the attributed bus
+        # We consider it acceptable if the mean of this distance is lower than 5 %
+        for r in WEIRegistration.objects.filter(wei=self.wei).all():
+            survey = WEISurvey2023(r)
+            chosen_bus = survey.information.get_selected_bus()
+            buses = survey.ordered_buses()
+            score = min(v for bus, v in buses if bus == chosen_bus)
+            max_score = buses[0][1]
+            penalty += (max_score - score) ** 2
+
+            self.assertLessEqual(max_score - score, 25)  # Always less than 25 % of tolerance
+
+        self.assertLessEqual(penalty / 100, 25)  # Tolerance of 5 %