REA graph dataset generator

REA_generator.py

import networkx as nx
import random

# Set the number of resources, events, and agents
num_resources = 80
num_events = 30
num_agents = 10

# Initialize the graph
G = nx.Graph()

# Add the nodes to the graph, representing resources, events, and agents
G.add_nodes_from(["resource_{}".format(i) for i in range(num_resources)])
G.add_nodes_from(["event_{}".format(i) for i in range(num_events)])
G.add_nodes_from(["agent_{}".format(i) for i in range(num_agents)])

# Generate random edges between resources and events, indicating that the resource is used in the event
for i in range(num_resources):
    for j in range(num_events):
        if random.random() < 0.5:  # Set the probability of an edge being added
            G.add_edge("resource_{}".format(i), "event_{}".format(j))

# Generate random edges between events and agents, indicating that the agent is involved in the event
for i in range(num_events):
    for j in range(num_agents):
        if random.random() < 0.5:  # Set the probability of an edge being added
            G.add_edge("event_{}".format(i), "agent_{}".format(j))

# Print out the number of nodes and edges in the graph
print("Number of nodes: {}".format(G.number_of_nodes()))
print("Number of edges: {}".format(G.number_of_edges()))

# nx.draw(G)
#nx.drawing.write_dot(G, "example.dot")
nx.drawing.nx_pydot.write_dot(G, "example.dot")