一个具备科研可验证性的 LoRa 多跳算法评估基线。

run_experiments.py

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+#!/usr/bin/env python
+"""
+LoRa Mesh Experiment Runner
+
+Usage:
+    python run_experiments.py                    # Quick comparison
+    python run_experiments.py --full             # Full parameter sweep
+    python run_experiments.py --routing gradient # Single algorithm
+"""
+
+import argparse
+import os
+import sys
+
+# Add sim to path
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from sim.experiments.runner import (
+    run_parameter_sweep,
+    run_quick_comparison,
+    save_results_csv,
+    compute_averages,
+)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="LoRa Mesh Experiment Runner")
+
+    parser.add_argument(
+        "--full",
+        action="store_true",
+        help="Run full parameter sweep (slower)",
+    )
+    parser.add_argument(
+        "--routing",
+        choices=["gradient", "flooding", "random"],
+        help="Run only specific routing algorithm",
+    )
+    parser.add_argument(
+        "--nodes",
+        type=int,
+        nargs="+",
+        default=[6, 9, 12, 15],
+        help="Node counts to test",
+    )
+    parser.add_argument(
+        "--area",
+        type=float,
+        nargs="+",
+        default=[500, 800, 1000],
+        help="Area sizes to test",
+    )
+    parser.add_argument(
+        "--time",
+        type=float,
+        default=200,
+        help="Simulation time per experiment",
+    )
+    parser.add_argument(
+        "--output",
+        default="results.csv",
+        help="Output CSV file",
+    )
+
+    args = parser.parse_args()
+
+    print("=" * 60)
+    print("LoRa Mesh Experiment Runner")
+    print("=" * 60)
+
+    if args.full:
+        # Full parameter sweep
+        print("\nRunning full parameter sweep...")
+
+        routings = ["gradient", "flooding", "random"]
+        seeds = [42, 123, 456]
+
+        results = run_parameter_sweep(
+            routings=routings,
+            node_counts=args.nodes,
+            area_sizes=args.area,
+            sim_time=args.time,
+            seeds=seeds,
+        )
+
+        # Compute averages
+        averaged = compute_averages(results)
+
+        # Save both raw and averaged
+        save_results_csv(results, args.output)
+        save_results_csv(averaged, args.output.replace(".csv", "_averaged.csv"))
+
+        print("\n=== Averaged Results ===")
+        for r in averaged:
+            print(
+                f"{r['routing']:10s} nodes={r['nodes']:2d} area={r['area']:4.0f}m "
+                f"PDR={r['avg_pdr']:5.2f}% max_hop={r['avg_max_hop']:.1f}"
+            )
+
+    elif args.routing:
+        # Single routing algorithm
+        print(f"\nRunning {args.routing} algorithm...")
+
+        results = run_parameter_sweep(
+            routings=[args.routing],
+            node_counts=args.nodes,
+            area_sizes=args.area,
+            sim_time=args.time,
+            seeds=[42],
+        )
+
+        save_results_csv(results, args.output)
+
+        print("\n=== Results ===")
+        for r in results:
+            print(
+                f"{r['routing']:10s} nodes={r['nodes']:2d} area={r['area']:4.0f}m "
+                f"PDR={r['pdr']:5.2f}% max_hop={r['max_hop']}"
+            )
+
+    else:
+        # Quick comparison (default)
+        print("\nRunning quick comparison (3 algorithms)...")
+
+        results = run_quick_comparison()
+
+        print("\n=== Results ===")
+        for routing, data in results.items():
+            print(f"\n{routing.upper()}:")
+            print(f"  PDR: {data['pdr']:.2f}%")
+            print(f"  Max Hop: {data['max_hop']}")
+            print(f"  Avg Hop: {data['avg_hop']:.2f}")
+            print(f"  Sent: {data['total_sent']}, Received: {data['total_received']}")
+            print(f"  Collisions: {data['collisions']}")
+
+        # Save quick results
+        save_results_csv([data for data in results.values()], args.output)
+
+        print(f"\n✓ Results saved to {args.output}")
+
+
+if __name__ == "__main__":
+    main()