HIPER: Hypergraph-based Investigation of Perturbation Effects and Resilience
Welcome to HIPER’s documentation! HIPER provides optimized data structures and algorithms for hypernetwork analysis and attack simulation.
The library implements hypernetworks using efficient dict-of-sets representation to achieve O(1) amortized performance for most operations.
Quick Start
from hiper import Hypernetwork
# Create new hypernetwork instance
hn = Hypernetwork()
# Add hyperedges connecting multiple nodes
hn.add_hyperedge(0, [1, 2, 3])
hn.add_hyperedge(1, [2, 3, 4, 5])
hn.add_hyperedge(2, [1, 4, 6])
# Analyze network properties
print(f"Network order: {hn.order()}")
print(f"Network size: {hn.size()}")
print(f"Average degree: {hn.avg_deg():.2f}")
Key Features
Optimized Data Structures: Efficient dict-of-sets representation for O(1) amortized operations
Attack Simulation: Comprehensive security analysis through individual and coordinated attacks
Resilience Analysis: TOPSIS-based node ranking and removal strategies
Modular Architecture: Selective importing based on application requirements
Comprehensive Metrics: Detailed network characterization and structural features
Table of Contents
User Guide
API Reference
License