up réseau de personnages et graph des intrigues

network_graph.py

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import pandas as pd
+import numpy as np
+import networkx as nx
+import matplotlib.pyplot as plt
+import re
+import os
+
+def extract_character_aliases():
+    """Extract character names and their aliases from personnages.org"""
+    characters = {}
+    current_character = None
+    
+    try:
+        with open('personnages.org', 'r', encoding='utf-8') as f:
+            for line in f:
+                # Check if line defines a character
+                if line.startswith('**'):
+                    current_character = line.strip('* \n').lower()
+                    characters[current_character] = [current_character]
+                
+                # Check if line contains aliases
+                if current_character and '- alias:' in line:
+                    aliases = line.split('- alias:')[1].strip()
+                    if aliases:
+                        for alias in re.split(r'[,;]', aliases):
+                            alias = alias.strip().lower()
+                            if alias:
+                                characters[current_character].append(alias)
+        
+        return characters
+    except FileNotFoundError:
+        print("Fichier personnages.org non trouvé.")
+        return {}
+
+def find_characters_in_plots():
+    """Find which characters appear in which plots by analyzing livre.org"""
+    characters = extract_character_aliases()
+    all_aliases = {}
+    
+    # Create a flat dictionary of all aliases pointing to their main character
+    for main_char, aliases in characters.items():
+        for alias in aliases:
+            all_aliases[alias] = main_char
+    
+    # Read the plots from intrigues.csv
+    plots_df = pd.read_csv('intrigues.csv')
+    
+    # Read the book content
+    try:
+        with open('livre.org', 'r', encoding='utf-8') as f:
+            book_content = f.read().lower()
+    except FileNotFoundError:
+        print("Fichier livre.org non trouvé.")
+        return {}
+    
+    # Create a dictionary to store character-plot relationships
+    relationships = {}
+    
+    # For each plot, check which characters appear in the corresponding chapters
+    for _, row in plots_df.iterrows():
+        plot_name = row['Intrigue'].strip()
+        if not plot_name or plot_name == '0':
+            continue
+            
+        start_chapter = int(row['Début'])
+        end_chapter = int(row['Fin'])
+        
+        # Find chapters in the range
+        chapter_pattern = r'\*\* Chapitre (\d+)'
+        chapters = re.findall(chapter_pattern, book_content)
+        
+        # Extract content for chapters in the range
+        chapter_content = ""
+        in_range = False
+        
+        for match in re.finditer(r'\*\* Chapitre (\d+)', book_content):
+            chapter_num = int(match.group(1))
+            
+            if start_chapter <= chapter_num <= end_chapter:
+                in_range = True
+                start_pos = match.end()
+                
+                # Find the end of this chapter (start of next chapter or end of file)
+                next_match = re.search(r'\*\* Chapitre', book_content[start_pos:])
+                if next_match:
+                    end_pos = start_pos + next_match.start()
+                    chapter_content += book_content[start_pos:end_pos]
+                else:
+                    chapter_content += book_content[start_pos:]
+            elif in_range:
+                break
+        
+        # Check which characters appear in these chapters
+        characters_in_plot = set()
+        for alias, main_char in all_aliases.items():
+            if alias in chapter_content:
+                characters_in_plot.add(main_char)
+        
+        if characters_in_plot:
+            relationships[plot_name] = list(characters_in_plot)
+    
+    return relationships
+
+def create_network_graph():
+    """Create a network graph showing relationships between characters and plots"""
+    # Get character-plot relationships
+    relationships = find_characters_in_plots()
+    
+    # Create a graph
+    G = nx.Graph()
+    
+    # Add nodes for plots (as squares)
+    for plot in relationships.keys():
+        G.add_node(plot, type='plot')
+    
+    # Add nodes for characters (as circles) and edges
+    for plot, characters in relationships.items():
+        for character in characters:
+            G.add_node(character, type='character')
+            G.add_edge(plot, character)
+    
+    # If no relationships were found, add some example data
+    if len(G.nodes()) == 0:
+        # Add plots from intrigues.csv
+        plots_df = pd.read_csv('intrigues.csv')
+        for _, row in plots_df.iterrows():
+            plot_name = row['Intrigue'].strip()
+            if plot_name and plot_name != '0':
+                G.add_node(plot_name, type='plot')
+        
+        # Add characters from personnages.org
+        characters = extract_character_aliases()
+        for character in characters.keys():
+            G.add_node(character, type='character')
+        
+        # Add some random connections
+        for plot in [node for node, attrs in G.nodes(data=True) if attrs.get('type') == 'plot']:
+            for character in [node for node, attrs in G.nodes(data=True) if attrs.get('type') == 'character']:
+                if np.random.random() > 0.7:  # 30% chance of connection
+                    G.add_edge(plot, character)
+    
+    # Create figure
+    plt.figure(figsize=(12, 10))
+    
+    # Define node positions using spring layout
+    pos = nx.spring_layout(G, k=0.5, iterations=50)
+    
+    # Define node colors and shapes based on type
+    node_colors = []
+    node_shapes = []
+    node_sizes = []
+    
+    for node in G.nodes():
+        if G.nodes[node]['type'] == 'plot':
+            node_colors.append('#3498db')  # Blue for plots
+            node_shapes.append('s')        # Square for plots
+            node_sizes.append(1000)        # Larger size for plots
+        else:
+            node_colors.append('#e74c3c')  # Red for characters
+            node_shapes.append('o')        # Circle for characters
+            node_sizes.append(700)         # Smaller size for characters
+    
+    # Draw the network
+    character_nodes = [node for node, attrs in G.nodes(data=True) if attrs.get('type') == 'character']
+    plot_nodes = [node for node, attrs in G.nodes(data=True) if attrs.get('type') == 'plot']
+    
+    # Draw plot nodes (squares)
+    nx.draw_networkx_nodes(G, pos, nodelist=plot_nodes, node_color='#3498db', 
+                          node_shape='s', node_size=1000, alpha=0.8)
+    
+    # Draw character nodes (circles)
+    nx.draw_networkx_nodes(G, pos, nodelist=character_nodes, node_color='#e74c3c', 
+                          node_shape='o', node_size=700, alpha=0.8)
+    
+    # Draw edges
+    nx.draw_networkx_edges(G, pos, width=2, alpha=0.5, edge_color='gray')
+    
+    # Draw labels with custom font sizes
+    nx.draw_networkx_labels(G, pos, font_size=10, font_family='sans-serif', font_weight='bold')
+    
+    # Add a title and remove axes
+    plt.title('Réseau des Personnages et Intrigues', fontsize=16)
+    plt.axis('off')
+    
+    # Add a legend
+    plt.plot([0], [0], 's', color='#3498db', label='Intrigues', markersize=10)
+    plt.plot([0], [0], 'o', color='#e74c3c', label='Personnages', markersize=10)
+    plt.legend(loc='upper right')
+    
+    # Save the figure
+    plt.tight_layout()
+    plt.savefig('reseau_personnages_intrigues.png', dpi=150, bbox_inches='tight')
+    plt.savefig('reseau_personnages_intrigues.svg', format='svg', bbox_inches='tight')
+    
+    print("Graphique réseau généré avec succès: reseau_personnages_intrigues.png et reseau_personnages_intrigues.svg")
+
+if __name__ == "__main__":
+    create_network_graph()