Update app.py

app.py

@@ -770,29 +770,42 @@ if uploaded_file is not None:
         sns.heatmap(pivot, ax=axes[word_pos], cmap='YlOrRd')
         axes[word_pos].set_title(f'Word Position {word_pos+1}')
     st.pyplot(fig)
-    
+
     st.subheader("4. Character Connection Patterns")
     char_bigrams = Counter()
     for chars in chars_list:
         for i in range(len(chars)-1):
             char_bigrams[tuple(chars[i:i+2])] += 1
     
+    # Create graph with explicit weight handling
     G = nx.Graph()
-    for (char1, char2), count in char_bigrams.most_common(20):
-        G.add_edge(char1, char2, weight=count)
+    edges_with_weights = []
     
-    fig4 = plt.figure(figsize=(10, 10))
-    pos = nx.spring_layout(G)
+    # Extract top 50 bigrams and their weights
+    for (char1, char2), count in char_bigrams.most_common(50):  # Increased to 50
+        if count > len(chars_list) * 0.01:  # Add frequency threshold
+            edges_with_weights.append((char1, char2, count))
     
-    # Get edge weights properly
-    edge_weights = [G[u][v]['weight'] for u,v in G.edges()]
-    max_weight = max(edge_weights) if edge_weights else 1
+    # Add edges to graph
+    for char1, char2, weight in edges_with_weights:
+        G.add_edge(char1, char2, weight=weight)
     
-    # Draw with correct weight normalization
-    nx.draw(G, pos, with_labels=True, 
+    fig4 = plt.figure(figsize=(15, 15))  # Increased figure size
+    pos = nx.spring_layout(G, k=1)  # Adjusted layout spacing
+    
+    # Calculate edge widths from explicit weight values
+    weights = [w for _, _, w in edges_with_weights]
+    max_weight = max(weights) if weights else 1
+    edge_widths = [w/max_weight * 5 for w in weights]
+    
+    # Draw network with pre-calculated widths
+    nx.draw(G, pos, 
+            with_labels=True,
             node_color='lightblue',
-            node_size=1000,
-            font_size=12,
-            width=[G[u][v]['weight']/max_weight * 5 for u,v in G.edges()])
-    plt.title("Top Character Connections")
+            node_size=2000,  # Increased node size
+            font_size=14,    # Increased font size
+            width=edge_widths)
+    
+    plt.title("Character Connection Network")
     st.pyplot(fig4)
+