VERSION = "1.1 6-Jan-2025" print(f"Pink Panther Graphs v{VERSION}") """ 1. Download Miniconda at https://docs.conda.io/en/latest/miniconda.html and install it. 2. Create Python environment #conda deactivate #conda env list #conda env remove --name allkinds conda create --name allkinds python=3.10 conda activate allkinds pip install networkx matplotlib rdflib 3. How To Launch On Laptop cd '/Users/cshallah/OraPub/0-Blog-Wider-View/HTML-new/20250101 A Graphs/projects/graphs-all-kinds' conda activate allkinds python pink_panther_graphs.py """ import networkx as nx import matplotlib.pyplot as plt from rdflib import Graph, Literal, RDF, URIRef, Namespace import json import matplotlib.patches as mpatches class PinkPantherGraphs: def __init__(self): self.fig_size = (12, 8) def create_network_graph(self): """ Creates a simple network graph of the Pink Panther heist """ print("\n=== Network Graph Example ===") print("Demonstrating simple connections between entities in the heist") G = nx.DiGraph() # Add nodes by category suspects = ['The Phantom', 'Inside Man'] locations = ['Casino Royale', 'Safe Room', 'Hotel Lobby'] investigators = ['Inspector Clouseau', 'Security Chief'] # Add nodes with different colors for each category for suspect in suspects: G.add_node(suspect, node_type='suspect') for location in locations: G.add_node(location, node_type='location') for investigator in investigators: G.add_node(investigator, node_type='investigator') # Add edges (connections) edges = [ ('The Phantom', 'Casino Royale'), ('The Phantom', 'Inside Man'), ('Inside Man', 'Safe Room'), ('Inspector Clouseau', 'Casino Royale'), ('Security Chief', 'Safe Room'), ('Casino Royale', 'Safe Room'), ('Hotel Lobby', 'Casino Royale') ] G.add_edges_from(edges) # Print network graph information print("\nNetwork Graph Data:") print("\nNodes by Category:") print(" Suspects:", suspects) print(" Locations:", locations) print(" Investigators:", investigators) print("\nConnections (Edges):") for edge in edges: print(f" {edge[0]} --> {edge[1]}") # Visualize the graph plt.figure(figsize=self.fig_size) pos = nx.spring_layout(G, seed=1) # Draw nodes with different colors node_colors = ['red' if G.nodes[node]['node_type'] == 'suspect' else 'lightblue' if G.nodes[node]['node_type'] == 'location' else 'green' for node in G.nodes()] # Draw nodes and edges separately for more control nx.draw_networkx_nodes(G, pos, node_color=node_colors, node_size=2000) nx.draw_networkx_edges(G, pos, arrows=True, arrowsize=30, edge_color='black', width=2, connectionstyle='arc3,rad=0.2', # Add curved connections node_size=2000) # Tell edge drawing about node size # Draw labels below nodes by adjusting the vertical position label_pos = {node: (coords[0], coords[1] - 0.16) for node, coords in pos.items()} nx.draw_networkx_labels(G, label_pos, font_size=10, font_weight='bold') plt.title("Pink Panther Heist - Network Graph") # Add legend legend_elements = [ mpatches.Patch(color='red', label='Suspect'), mpatches.Patch(color='lightblue', label='Location'), mpatches.Patch(color='green', label='Investigator') ] plt.legend(handles=legend_elements) plt.axis('off') plt.show() def create_property_graph(self): """ Creates and visualizes a property graph representation of the Pink Panther heist """ print("\n=== Property Graph Example ===") print("Demonstrating relationships with properties") # Define nodes with properties nodes = { 'phantom': { 'id': 'phantom', 'type': 'person', 'name': 'The Phantom', 'properties': { 'expertise': ['safe_cracking', 'disguise'], 'last_known_location': 'Monaco' } }, 'casino': { 'id': 'casino', 'type': 'location', 'name': 'Casino Royale', 'properties': { 'security_level': 'Maximum', 'surveillance_coverage': '90%' } }, 'diamond': { 'id': 'diamond', 'type': 'item', 'name': 'Pink Panther Diamond', 'properties': { 'value': '50 million', 'security': 'Level 10' } } } # Define relationships with properties relationships = [ { 'from': 'phantom', 'to': 'casino', 'type': 'VISITED', 'properties': { 'timestamp': '2024-03-15 23:00', 'duration': '45min', 'detected': False } }, { 'from': 'phantom', 'to': 'diamond', 'type': 'STOLE', 'properties': { 'timestamp': '2024-03-15 23:30', 'method': 'Safe cracking' } } ] # Print property graph information print("\nNodes with Properties:") print(json.dumps(nodes, indent=2)) print("\nRelationships with Properties:") print(json.dumps(relationships, indent=2)) # Create visualization graph G = nx.DiGraph() # Add nodes to visualization graph for node_id, node_data in nodes.items(): label = f"{node_data['name']}\n({', '.join(f'{k}: {v}' for k, v in node_data['properties'].items())})" G.add_node(node_id, node_type=node_data['type'], label=label) # Add edges to visualization graph for rel in relationships: label = f"{rel['type']}\n({', '.join(f'{k}: {v}' for k, v in rel['properties'].items())})" G.add_edge(rel['from'], rel['to'], relationship=rel['type'], label=label) # Visualize the property graph plt.figure(figsize=self.fig_size) # Create layout with more horizontal spread pos = nx.spring_layout(G, k=0.5, # Reduced from 2 to bring nodes closer iterations=200, seed=18) # Draw nodes node_colors = ['lightcoral' if G.nodes[node]['node_type'] == 'person' else 'lightblue' if G.nodes[node]['node_type'] == 'location' else 'lightgreen' for node in G.nodes()] nx.draw_networkx_nodes(G, pos, node_color=node_colors, node_size=1000) # Draw node labels node_labels = {node: G.nodes[node]['label'] for node in G.nodes()} label_pos = {node: (coords[0], coords[1] - 0.17) for node, coords in pos.items()} nx.draw_networkx_labels(G, label_pos, node_labels, font_size=8) # Draw edges with curves and labels for (u, v, data) in G.edges(data=True): # Draw curved edge nx.draw_networkx_edges(G, pos, edgelist=[(u, v)], edge_color='gray', arrows=True, arrowsize=20, connectionstyle='arc3,rad=0.5', node_size=3000) # Calculate edge label position (above the curved edge) edge_center = ((pos[u][0] + pos[v][0])/2, (pos[u][1] + pos[v][1])/2 + 0.2) # Offset above the edge # Add edge label plt.text(edge_center[0], edge_center[1], data['label'], horizontalalignment='center', verticalalignment='center', fontsize=8, bbox=dict(facecolor='white', edgecolor='none', alpha=0.7)) # Add legend legend_elements = [ mpatches.Patch(color='lightcoral', label='Person'), mpatches.Patch(color='lightblue', label='Location'), mpatches.Patch(color='lightgreen', label='Item') ] plt.legend(handles=legend_elements) plt.title("Pink Panther Heist - Property Graph") plt.axis('off') plt.show() def create_knowledge_graph(self): """ Creates and visualizes a knowledge graph representation of the Pink Panther heist """ print("\n=== Knowledge Graph Example ===") print("Demonstrating semantic relationships and inferences") # Create a new RDF graph g = Graph() # Create namespace PP = Namespace("http://pp.org/") # Define all triples triples = [ (PP.PinkPantherDiamond, RDF.type, PP.Jewel), (PP.PinkPantherDiamond, PP.hasValue, Literal("50000000")), (PP.PinkPantherDiamond, PP.storedIn, PP.CasinoRoyaleVault), (PP.ThePhantom, RDF.type, PP.Criminal), (PP.HeistEvent_001, PP.hasTarget, PP.PinkPantherDiamond), (PP.HeistEvent_001, PP.hasPerpetrator, PP.ThePhantom), (PP.HeistEvent_001, PP.occuredAt, PP.CasinoRoyale), (PP.HeistEvent_001, PP.occuredOn, Literal("2024-03-15")), (PP.HeistEvent_001, RDF.type, PP.Event), (PP.CasinoRoyaleVault, RDF.type, PP.Location), (PP.CasinoRoyale, RDF.type, PP.Location) ] # Add all triples to the graph for triple in triples: g.add(triple) # Print the triples print("\nKnowledge Graph Triples:") for subj, pred, obj in g: print(f"{subj.n3()} {pred.n3()} {obj.n3()}") # Example of a simple query print("\nQuery Example - Find all events involving the Pink Panther Diamond:") qres = g.query( """ SELECT ?event ?perpetrator ?date WHERE { ?event ?p ?o . ?event pp:hasTarget pp:PinkPantherDiamond . ?event pp:hasPerpetrator ?perpetrator . ?event pp:occuredOn ?date . } """, initNs={"pp": PP} ) for row in qres: print(f"Event: {row.event}, Perpetrator: {row.perpetrator}, Date: {row.date}") # Create visualization graph G = nx.DiGraph() # Extract nodes and their types from triples nodes = set() node_types = {} for subj, pred, obj in triples: # Add subject node nodes.add(str(subj).split('/')[-1]) # Get the last part of the URI # Add object node if it's not a literal if not isinstance(obj, Literal): nodes.add(str(obj).split('/')[-1]) # Determine node types based on RDF type relationships if pred == RDF.type: node_types[str(subj).split('/')[-1]] = str(obj).split('/')[-1].lower() # Add nodes to graph for node in nodes: G.add_node(node, node_type=node_types.get(node, 'default')) # Add edges from triples for subj, pred, obj in triples: if not isinstance(obj, Literal): # Skip edges to literal values source = str(subj).split('/')[-1] target = str(obj).split('/')[-1] # Clean up the edge label if pred == RDF.type: label = 'type' else: label = str(pred).split('/')[-1] G.add_edge(source, target, label=label) # Visualize the knowledge graph plt.figure(figsize=self.fig_size) pos = nx.spring_layout(G, k=1, iterations=50, seed=3) # Draw nodes with different colors for different types node_colors = ['lightgreen' if G.nodes[node]['node_type'] == 'jewel' else 'lightgray' if G.nodes[node]['node_type'] == 'criminal' else 'lightblue' if G.nodes[node]['node_type'] == 'location' else 'lightcoral' if G.nodes[node]['node_type'] == 'event' else 'peachpuff' for node in G.nodes()] nx.draw_networkx_nodes(G, pos, node_color=node_colors, node_size=1000) # Draw labels below nodes label_pos = {node: (coords[0], coords[1] - 0.15) for node, coords in pos.items()} nx.draw_networkx_labels(G, label_pos) # Draw edges and labels nx.draw_networkx_edges(G, pos, edge_color='black', arrows=True, arrowsize=30, width=2, connectionstyle='arc3,rad=0.15', node_size=1000) edge_labels = nx.get_edge_attributes(G, 'label') nx.draw_networkx_edge_labels(G, pos, edge_labels, font_size=8, bbox=dict(facecolor='white', edgecolor='none', alpha=0.7)) # Add legend legend_elements = [ mpatches.Patch(color='lightgreen', label='Jewel'), mpatches.Patch(color='lightgray', label='Criminal'), mpatches.Patch(color='lightblue', label='Location'), mpatches.Patch(color='lightcoral', label='Event'), mpatches.Patch(color='peachpuff', label='Default') ] plt.legend(handles=legend_elements) plt.title("Pink Panther Heist - Knowledge Graph") plt.axis('off') plt.show() def main(): graphs = PinkPantherGraphs() # Create and display each type of graph graphs.create_network_graph() graphs.create_property_graph() graphs.create_knowledge_graph() if __name__ == "__main__": main()