On utilise un champ pour stocker l'information de l'option gagnante, et on implémente l'algorithme de schwartz pour dépouiller les votes de condorcet avec schultze

elections/migrations/0019_option_winner.py

@@ -0,0 +1,18 @@
+# Generated by Django 2.2.19 on 2021-04-04 16:31
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ("elections", "0018_auto_20210331_1317"),
+    ]
+
+    operations = [
+        migrations.AddField(
+            model_name="option",
+            name="winner",
+            field=models.BooleanField(default=False, verbose_name="option gagnante"),
+        ),
+    ]

elections/models.py

@@ -123,6 +123,7 @@ class Option(models.Model):
     )
     text = models.TextField(_("texte"), blank=False)
 
+    winner = models.BooleanField(_("option gagnante"), default=False)
     voters = models.ManyToManyField(
         settings.AUTH_USER_MODEL,
         related_name="votes",

elections/templates/elections/election.html

@@ -135,22 +135,21 @@
   {% for o in q.options.all %}
   <div class="panel-block">
     {% if election.tallied and election.results_public %}
+    <span class="tag {% if o.winner %}is-success{% else %}is-primary{% endif %}">
       {% if q.vote_type == "select" %}
-    <span class="tag {% if o.nb_votes == q.max_votes %}is-success{% else %}is-primary{% endif %}">
       <span class="icon">
         <i class="fas fa-vote-yea"></i>
       </span>
       <span>{{ o.nb_votes }}</span>
-    </span>
 
       {% elif q.vote_type == "rank" %}
-    <span class="tag is-primary">
+
       <span class="icon">
         <i class="fas fa-layer-group"></i>
       </span>
       <span>{{ forloop.counter }}</span>
-    </span>
       {% endif %}
+    </span>
     {% endif %}
 
     <span class="ml-2">{{ o.text }}</span>

elections/templates/elections/election_admin.html

@@ -139,32 +139,34 @@
 
   {# Liste des options possibles #}
   {% for o in q.options.all %}
-  <div class="panel-block" id="o_{{ o.pk }}">
+  <div class="panel-block">
-    {% if election.start_date > current_time %}
+    {% if election.tallied %}
-    <span class="tags has-addons mb-0">
+    <span class="tag {% if o.winner %}is-success{% else %}is-primary{% endif %}">
-      <a class="tag is-danger mb-0" title="{% trans "Supprimer" %}" href="{% url 'election.del-option' o.pk %}">
+      {% if q.vote_type == "select" %}
-        <span class="icon">
-          <i class="fas fa-times"></i>
-        </span>
-      </a>
-      <a class="tag is-info mb-0" title="{% trans "Modifier" %}" href="{% url 'election.mod-option' o.pk %}">
-        <span class="icon">
-          <i class="fas fa-edit"></i>
-        </span>
-      </a>
-    </span>
-    {% elif election.tallied %}
-    <span class="tag {% if o.nb_votes == q.max_votes %}is-success{% else %}is-primary{% endif %}">
       <span class="icon">
         <i class="fas fa-vote-yea"></i>
       </span>
       <span>{{ o.nb_votes }}</span>
+
+      {% elif q.vote_type == "rank" %}
+
+      <span class="icon">
+        <i class="fas fa-layer-group"></i>
+      </span>
+      <span>{{ forloop.counter }}</span>
+      {% endif %}
     </span>
     {% endif %}
+
     <span class="ml-2">{{ o.text }}</span>
   </div>
   {% endfor %}
 
+  {# Affiche plus d'informations sur le résultat #}
+  {% if election.tallied %}
+  {{ q.get_results_data }}
+  {% endif %}
+
   {# Rajout d'une option #}
   {% if election.start_date > current_time %}
   <form action="{% url 'election.add-option' q.pk %}" method="post">

elections/utils.py

@@ -2,7 +2,9 @@ import csv
 import io
 import random
 
+import networkx as nx
 import numpy as np
+from networkx.algorithms.dag import ancestors, descendants
 
 from django.contrib.auth.hashers import make_password
 from django.core.exceptions import ValidationError
@@ -85,14 +87,17 @@ class TallyFunctions:
             max_votes = max(max_votes, o.nb_votes)
             options.append(o)
 
+        for o in options:
+            o.winner = o.nb_votes == max_votes
+
         question.max_votes = max_votes
         question.save()
 
-        Option.objects.bulk_update(options, ["nb_votes"])
+        Option.objects.bulk_update(options, ["nb_votes", "winner"])
 
     def tally_rank(question):
         """On dépouille un vote par classement et on crée la matrice des duels"""
-        from .models import Duel, Rank
+        from .models import Duel, Option, Rank
 
         def duel(a, b):
             # Renvoie 1 si a est classé avant b, -1 si c'est l'inverse et
@@ -118,15 +123,23 @@ class TallyFunctions:
             votes = ranks_by_user[user]
             ballots.append(np.array([[duel(x, y) for x in votes] for y in votes]))
 
-        # On additionne les classements de tout le monde
+        if ballots != []:
+            # On additionne les classements de tout le monde pour avoir la matrice
+            # des duels
             duels = np.maximum(sum(ballots), 0)
 
+            # Configuration du graphe
+            graph = nx.DiGraph()
+
+            graph.add_nodes_from(options)
+
             cells = []
 
             # On enregistre la matrice
             for i, line in enumerate(duels):
                 for j, cell in enumerate(line):
                     if cell > 0:
+                        graph.add_edge(options[j], options[i], weight=cell)
                         cells.append(
                             Duel(
                                 question=question,
@@ -137,6 +150,36 @@ class TallyFunctions:
                         )
             Duel.objects.bulk_create(cells)
 
+            # On utilise la méthode de schwartz pour trouver les options gagnantes
+            while graph.edges():
+                losers = set()  # Les options qui se font battre strictement
+                for n in graph.nodes():
+                    losers |= set(descendants(graph, n)) - set(ancestors(graph, n))
+
+                if losers:
+                    # On supprime les options perdantes
+                    for n in losers:
+                        graph.remove_node(n)
+
+                else:
+                    # On n'a pas d'options perdantes, on supprime les arêtes de poids
+                    # le plus faible
+                    min_weight = min(nx.get_edge_attributes(graph, "weight").values())
+                    min_edges = []
+                    for (u, v) in graph.edges():
+                        if graph[u][v]["weight"] == min_weight:
+                            min_edges.append((u, v))
+
+                    for (u, v) in min_edges:
+                        graph.remove_edge(u, v)
+
+            # Les options gagnantes sont celles encore présentes dans le graphe
+            winners = graph.nodes()
+            for o in options:
+                o.winner = o in winners
+
+            Option.objects.bulk_update(options, ["winner"])
+
 
 class ValidateFunctions:
     """Classe pour valider les formsets selon le type de question"""