Bon

script/src/truc_test/truc_test_pyvis.py

 import csv
 import networkx as nx
-from networkx.algorithms.community.louvain import louvain_communities
+from networkx.algorithms.community import louvain_communities
 from pyvis.network import Network
-import networkx as nx
-G = nx.Graph()
-
-path_node = "/home/agryos/Documents/Hackiie/graphe_association/res_script/nodes_avec_fantome.csv"
+import random
 
 
-total_noeud = []
-with (open(path_node, newline='') as csvfile):
+def centrality_to_color(value):
+    """Convertit une valeur de centralité (0 à 1) en couleur hex (bleu → rouge)."""
+    r = int(value * 255)
+    g = 0
+    b = int(255 - value * 255)
+    return f'#{r:02x}{g:02x}{b:02x}'
 
-    spamreader = csv.reader(csvfile, delimiter=',', quotechar='|')
 
-    for row in spamreader:
+# 1. Lecture du graphe biparti
+B = nx.Graph()
+path_node = "/home/agryos/Documents/Hackiie/graphe_association/res_script/nodes_sans_fantome.csv"
+with open(path_node, newline='') as csvfile:
+    reader = csv.reader(csvfile, delimiter=',', quotechar='|')
+    for row in reader:
         if row[0] == "Id":
             continue
-        id_node = int(row[0])
-        label_node = row[1]
-        categorie = row[2]
-        color = "red" if categorie == "Asso" else "blue"
-        node_to_add = (id_node,{"label":label_node, "categorie":categorie,"color":color})
-        total_noeud.append(node_to_add)
+        node_id = int(row[0])
+        label = row[1]
+        categorie = row[2]  # "Asso" ou "Eleve"
+        B.add_node(node_id, label=label, bipartite=categorie)
 
-G.add_nodes_from(total_noeud)
-
-maxi = 0
-total_edge = []
-path_edge = "/home/agryos/Documents/Hackiie/graphe_association/res_script/edges_avec_fantome.csv"
+# 2. Lecture des arêtes
+path_edge = "/home/agryos/Documents/Hackiie/graphe_association/res_script/edges_sans_fantome.csv"
 with open(path_edge, newline='') as csvfile:
-
-    spamreader = csv.reader(csvfile, delimiter=',', quotechar='|')
-
-    for row in spamreader:
+    reader = csv.reader(csvfile, delimiter=',', quotechar='|')
+    for row in reader:
         if row[0] == "Source":
             continue
-        edge_source = int(row[0])
-        edge_target = int(row[1])
-        edge_weight = float(row[4])
-        maxi = max(maxi,edge_weight)
-
-        edge_to_add = (edge_source,edge_target,edge_weight)
-        total_edge.append(edge_to_add)
-
-total_edge_normalized = []
-min_w = 1
-max_w = 10
-for (x1,x2,w) in total_edge:
-    total_edge_normalized.append((x1,x2,(max_w - min_w)*w/maxi + min_w))
-
-G.add_weighted_edges_from(total_edge_normalized)
-
-options = str({
-  "physics": {
-    "forceAtlas2Based": {
-      "theta": 0.55,
-      "gravitationalConstant": -23,
-      "centralGravity": 0.02,
-      "springLength": 160,
-      "springConstant": 0.005,
-      "damping": 0.31,
-      "avoidOverlap": 1
-    },
-    "maxVelocity": 33,
-    "minVelocity": 0.66,
-    "solver": "forceAtlas2Based",
-    "timestep": 0.25
-  }
-}).replace('\'','"')
-print(options)
+        src = int(row[0])
+        tgt = int(row[1])
+        weight = float(row[4])
+        B.add_edge(src, tgt, weight=weight)
 
-communaute = louvain_communities(G,"weight",0.5)
-print(communaute)
-import random
+# 3. Projection sur les élèves uniquement
+eleves = [n for n, d in B.nodes(data=True) if d["bipartite"] != "Asso"]
+G_proj = nx.bipartite.weighted_projected_graph(B, eleves)
 
-for edge in G.edges:
-    G.ed = "brown"
+positions = nx.fruchterman_reingold_layout(G_proj, seed=42, k=1,scale=6)  # k ajuste l'espacement
 
-for s in communaute:
-    col = ["#"+''.join([random.choice('ABCDEF0123456789') for i in range(6)])][0]
-    print(col)
-    for idx in s:
-        if len(s) == 1:
-            G.nodes[idx][color] = "grey"
+# 4. Calcul de la centralité
+centrality = nx.betweenness_centrality(G_proj,weight="weight")  # ou nx.betweenness_centrality(G_proj, weight="weight")
 
 
-nt = Network('500px', '500px')
-nt.from_nx(G)
-nt.force_atlas_2based(-23,0.02,160,0.015,0.31,1)
-nt.save_graph("python_truc.html")
+# 6. Affichage avec PyVis
+net = Network("900px", "900px")
+net.set_options('''
+{"physics": {
+    "enabled": false
+  },
+  "nodes": {
     
-nt.show_buttons(filter_=True)
-nt.show('nx.html',notebook=False)
+    "highlight": {
+      "border": {
+        "width": 3,
+        "color": {
+          "highlight": "red"
+        }
+      },
+      "color": {
+        "highlight": {
+          "background": "yellow",
+          "border": "red"
+        }
+      }
+    }
+  },
+  "edges": {
+    "highlight": {
+      "color": {
+        "highlight": "#e1ccc8"
+      },
+      "width": 3
+    }
+  }
+}
+''')
+maxi = 0
+for node, pos in positions.items():
+    cent_value = centrality.get(node, 0)
+    maxi = max(cent_value,maxi)
+# 6. Ajout des nœuds avec couleur selon centralité
+for node, pos in positions.items():
+    label = B.nodes[node].get("label", str(node))
+    cent_value = centrality.get(node, 0)
+    color = centrality_to_color(cent_value/maxi)
+    x = pos[0] * 1000
+    y = pos[1] * 1000
+    net.add_node(
+        node,
+        label=label,
+        color=color,
+        borderWidth=2,
+        x=x,
+        y=y,
+        fixed=True,
+        title=f"{label}<br>Centralité : {cent_value:.3f}"
+    )
+
+
+
+# 7. Ajout des arêtes
+for src, tgt, data in G_proj.edges(data=True):
+    net.add_edge(src, tgt, value=data["weight"])
+
+
+net.save_graph("chaatgpt_truc.html")
+
+net.show("projection_communautes.html",notebook=False)