= Example of using Pellet to verify a Catapult model
from owlready2 import *

= Load the ontology and model
onto = get_ontology("catapult.owl").load()

= Create a reasoner instance
reasoner = Pellet()

= Run the reasoner to check for inconsistencies
reasoner.run(onto)

= Check for inconsistencies
if onto.inconsistent:
    print("Inconsistency found!")
    for error in onto.inconsistent:
        print(f"Error: {error}")
else:
    print("Model is consistent!")

= Example of using SHACL to validate a Catapult model
from rdflib import Graph
from rdflib.plugins.sparql import prepareQuery
from shaclex import validate

= Load the ontology and model
g = Graph()
g.parse("catapult_model.ttl", format="turtle")

= Load the SHACL shapes
shapes = Graph()
shapes.parse("catapult_shapes.ttl", format="turtle")

= Validate the model against the shapes
results = validate(g, shacl_graph=shapes, inference="rdfs", abort_on_first=False)

= Check validation results
if results.conforms:
    print("Model validation passed!")
else:
    print("Model validation failed!")
    for result in results:
        print(f"Violation: {result}")

= Example of using NetworkX to check for cycles in a SoA
import networkx as nx

= Create a directed graph from the SoA model
G = nx.DiGraph()

= Add nodes and edges from the SoA model
G.add_node("Gravity")
G.add_node("AirTemp")
G.add_edge("Gravity", "FireSimulation")
G.add_edge("AirTemp", "FireSimulation")
G.add_edge("FireSimulation", "ImpactVelocity")
G.add_edge("ImpactVelocity", "PinHeight")
G.add_edge("PinHeight", "ImpactVelocity")  # Intentional cycle for demonstration

= Check for cycles
if nx.is_directed_acyclic_graph(G):
    print("SoA is a valid DAG (no cycles)")
else:
    print("SoA contains a cycle!")
    cycle = nx.find_cycle(G)
    print(f"Cycle detected: {cycle}")