File size: 2,728 Bytes
f5b1acc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
import json
import networkx as nx
import matplotlib.pyplot as plt
import os
# Define the path to your index.json file
index_file_path = "graphs/index.json"
# Define colors for domains
domain_colors = {
"Legislation": "red",
"Healthcare Systems": "blue",
"Healthcare Policies": "green",
"Default": "grey"
}
# Load index data
def load_index_data(file_path):
with open(file_path, "r") as file:
return json.load(file)
# Load and parse entities
def build_graph(data):
G = nx.DiGraph()
for entity_id, entity_info in data["entities"].items():
label = entity_info.get("label", entity_id)
domain = entity_info.get("inherits_from", "Default")
color = domain_colors.get(domain, "grey") # Set color, defaulting to "grey" if domain is missing
G.add_node(entity_id, label=label, color=color)
# Load additional relationships if specified in the entity data
file_path = entity_info.get("file_path")
if file_path and os.path.exists(file_path):
with open(file_path, "r") as f:
entity_data = json.load(f)
for rel in entity_data.get("relationships", []):
G.add_edge(rel["source"], rel["target"], label=rel["attributes"]["relationship"])
# Add relationships from index.json
for relationship in data["relationships"]:
G.add_edge(relationship["source"], relationship["target"], label=relationship["attributes"].get("relationship", "related_to"))
return G
# Enhanced visualization
def visualize_graph(G, title="Inferred Contextual Relationships"):
pos = nx.spring_layout(G)
plt.figure(figsize=(15, 10))
# Draw nodes with colors
node_colors = [G.nodes[node].get("color", "grey") for node in G.nodes] # Default to "grey" if color is missing
nx.draw_networkx_nodes(G, pos, node_size=3000, node_color=node_colors, alpha=0.8)
# Draw labels
nx.draw_networkx_labels(G, pos, font_size=10, 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=8)
# Save as PDF and display
plt.title(title)
plt.axis("off")
plt.savefig("graph_visualization.pdf") # Export as PDF
plt.show()
# Main execution
if __name__ == "__main__":
# Load data from 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) |