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import json
import networkx as nx
import matplotlib.pyplot as plt
# Define the path to your index.json file
index_file_path = "graphs/index.json"
# Load the data from index.json
def load_index_data(file_path):
"""Load the index.json file and parse its contents."""
with open(file_path, "r") as file:
data = json.load(file)
return data
def build_graph(data):
"""Builds a directed graph based on entities and relationships."""
G = nx.DiGraph()
# Add nodes for each entity
for entity_id, entity_info in data["entities"].items():
label = entity_info.get("label", entity_id)
# Use label separately to avoid duplicate keyword arguments
G.add_node(entity_id, label=label, **{k: v for k, v in entity_info.items() if k != "label"})
# Add edges for each relationship
for relationship in data["relationships"]:
source = relationship["source"]
target = relationship["target"]
relationship_label = relationship["attributes"].get("relationship", "related_to")
G.add_edge(source, target, label=relationship_label)
return G
# Visualize the graph using Matplotlib
def visualize_graph(G, title="340B Program - Inferred Contextual Relationships"):
"""Visualizes the graph with nodes and relationships."""
pos = nx.spring_layout(G) # Position nodes with a spring layout
# Draw nodes with labels
plt.figure(figsize=(15, 10))
nx.draw_networkx_nodes(G, pos, node_size=3000, node_color="lightblue", alpha=0.7)
nx.draw_networkx_labels(G, pos, font_size=10, font_color="black", font_weight="bold")
# Draw edges with labels
nx.draw_networkx_edges(G, pos, arrowstyle="->", arrowsize=20, edge_color="gray", connectionstyle="arc3,rad=0.1")
edge_labels = {(u, v): d["label"] for u, v, d in G.edges(data=True)}
nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels, font_color="red", font_size=9)
# Set plot title and display
plt.title(title)
plt.axis("off")
plt.show()
# Main execution
if __name__ == "__main__":
# Load data from the index.json
data = load_index_data(index_file_path)
# Build the graph with entities and relationships
G = build_graph(data)
# Visualize the graph
visualize_graph(G) |