Contents Menu Expand Light mode Dark mode Auto light/dark, in light mode Auto light/dark, in dark mode Skip to content
PyTwinNet Documentation
Logo
Light Logo Dark Logo
  • Getting Started
  • User Guide Overview
  • Propagation & Link Budget
  • Received Power
  • SINR
  • Throughput
  • RIS Beams & MIMO (Primer)
  • Reinforcement Learning for Power Control
  • Acceleration (Numba)
  • Example
  • Real-Time Dashboard
  • Config-Driven Experiments
  • Keys
  • Examples
    • Heterogeneous Network Placement
    • SINR & Throughput Example
    • RIS + MIMO Demo
    • RL Power Control
  • SINR & Throughput Example
  • API Reference
Back to top
View this page

pytwinnet.optimization.simple_greedy¶

Classes

SimpleGreedyOptimizer([step_db, ...])

class pytwinnet.optimization.simple_greedy.SimpleGreedyOptimizer(step_db=1.0, max_power_dbm=30.0, iterations=10)[source]¶

Bases: Optimizer

Parameters:
  • step_db (float)

  • max_power_dbm (float)

  • iterations (int)

iterations: int = 10¶
max_power_dbm: float = 30.0¶
optimize(twin, objective)[source]¶
Return type:

Dict[str, Any]

Parameters:
  • twin (DigitalTwin)

  • objective (Objective)

step_db: float = 1.0¶
Copyright © 2025, Oluwaseyi Giwa
Made with Sphinx and @pradyunsg's Furo
On this page
  • pytwinnet.optimization.simple_greedy
    • SimpleGreedyOptimizer
      • SimpleGreedyOptimizer.iterations
      • SimpleGreedyOptimizer.max_power_dbm
      • SimpleGreedyOptimizer.optimize()
      • SimpleGreedyOptimizer.step_db