准备写论文，论文大纲和数据搞定
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sinlatansen
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generate_figures.py
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210
generate_figures.py
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#!/usr/bin/env python
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"""
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Generate paper figures from experimental results.
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"""
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import json
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import matplotlib
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matplotlib.use("Agg") # Non-interactive backend
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import matplotlib.pyplot as plt
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import numpy as np
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def load_statistics():
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"""Load statistics from JSON."""
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with open("results/statistics.json", "r") as f:
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return json.load(f)
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def load_all_results():
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"""Load all raw results."""
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algorithms = ["gradient", "flooding", "random"]
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all_data = {}
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for algo in algorithms:
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with open(f"results/{algo}/all_seeds.json", "r") as f:
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all_data[algo] = json.load(f)
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return all_data
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def plot_pdr_vs_airtime(all_data, stats):
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"""Generate PDR vs Airtime plot."""
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fig, ax = plt.subplots(figsize=(8, 6))
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colors = {"gradient": "#2E86AB", "flooding": "#E94F37", "random": "#7D8491"}
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markers = {"gradient": "o", "flooding": "s", "random": "^"}
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for algo in ["gradient", "flooding", "random"]:
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algo_stats = stats[algo]
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# Get mean and CI
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pdr_mean = algo_stats["pdr"]["mean"]
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pdr_ci = algo_stats["pdr"]["ci_95"]
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air_mean = algo_stats["airtime_usage_percent"]["mean"]
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air_ci = algo_stats["airtime_usage_percent"]["ci_95"]
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# Plot with error bars
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ax.errorbar(
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air_mean,
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pdr_mean,
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xerr=air_ci,
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yerr=pdr_ci,
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fmt=markers[algo],
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color=colors[algo],
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markersize=12,
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capsize=5,
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capthick=2,
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linewidth=2,
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label=f"{algo.capitalize()} ({pdr_mean:.1f}%, {air_mean:.1f}%)",
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)
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# Add individual points (semi-transparent)
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for r in all_data[algo]:
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if "error" not in r:
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ax.scatter(
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r["airtime_usage_percent"],
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r["pdr"],
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alpha=0.15,
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color=colors[algo],
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s=20,
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)
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ax.set_xlabel("Airtime Usage (%)", fontsize=12)
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ax.set_ylabel("Packet Delivery Ratio (%)", fontsize=12)
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ax.set_title(
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"PDR vs Channel Airtime Usage\n(50 seeds per algorithm, error bars = 95% CI)",
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fontsize=14,
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)
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ax.legend(loc="lower right", fontsize=10)
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ax.grid(True, alpha=0.3)
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ax.set_xlim(0, 110)
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ax.set_ylim(0, 35)
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# Add annotation for efficiency frontier
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ax.annotate(
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"Efficiency\nFrontier",
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xy=(40, 12),
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fontsize=10,
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style="italic",
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bbox=dict(boxstyle="round", facecolor="wheat", alpha=0.5),
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)
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plt.tight_layout()
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plt.savefig("figures/pdr_vs_airtime.pdf", dpi=300)
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plt.savefig("figures/pdr_vs_airtime.png", dpi=150)
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print("Saved: figures/pdr_vs_airtime.pdf")
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plt.close()
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def plot_pdr_vs_tx_cost(all_data, stats):
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"""Generate PDR vs TX Cost plot."""
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fig, ax = plt.subplots(figsize=(8, 6))
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colors = {"gradient": "#2E86AB", "flooding": "#E94F37", "random": "#7D8491"}
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markers = {"gradient": "o", "flooding": "s", "random": "^"}
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for algo in ["gradient", "flooding", "random"]:
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algo_stats = stats[algo]
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pdr_mean = algo_stats["pdr"]["mean"]
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pdr_ci = algo_stats["pdr"]["ci_95"]
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tx_mean = algo_stats["tx_per_success"]["mean"]
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tx_ci = algo_stats["tx_per_success"]["ci_95"]
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ax.errorbar(
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tx_mean,
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pdr_mean,
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xerr=tx_ci,
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yerr=pdr_ci,
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fmt=markers[algo],
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color=colors[algo],
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markersize=12,
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capsize=5,
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capthick=2,
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linewidth=2,
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label=f"{algo.capitalize()} (PDR: {pdr_mean:.1f}%)",
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)
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# Add individual points
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for r in all_data[algo]:
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if "error" not in r and r["tx_per_success"] > 0:
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ax.scatter(
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r["tx_per_success"], r["pdr"], alpha=0.15, color=colors[algo], s=20
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)
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ax.set_xlabel("Transmission Cost (TX per Successful Delivery)", fontsize=12)
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ax.set_ylabel("Packet Delivery Ratio (%)", fontsize=12)
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ax.set_title(
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"PDR vs Transmission Cost\n(50 seeds per algorithm, error bars = 95% CI)",
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fontsize=14,
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)
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ax.legend(loc="lower right", fontsize=10)
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ax.grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig("figures/pdr_vs_tx_cost.pdf", dpi=300)
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plt.savefig("figures/pdr_vs_tx_cost.png", dpi=150)
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print("Saved: figures/pdr_vs_tx_cost.pdf")
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plt.close()
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def plot_comparison_bar(stats):
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"""Generate comparison bar chart."""
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fig, axes = plt.subplots(1, 3, figsize=(12, 4))
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algorithms = ["gradient", "flooding", "random"]
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colors = ["#2E86AB", "#E94F37", "#7D8491"]
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metrics = [
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("pdr", "PDR (%)"),
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("airtime_usage_percent", "Airtime (%)"),
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("tx_per_success", "TX/Success"),
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]
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for idx, (metric, label) in enumerate(metrics):
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ax = axes[idx]
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values = [stats[a][metric]["mean"] for a in algorithms]
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errors = [stats[a][metric]["ci_95"] for a in algorithms]
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bars = ax.bar(
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algorithms, values, yerr=errors, color=colors, capsize=5, alpha=0.8
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)
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ax.set_ylabel(label, fontsize=11)
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ax.set_title(label, fontsize=12)
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ax.grid(True, alpha=0.3, axis="y")
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# Add value labels
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for bar, val in zip(bars, values):
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ax.text(
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bar.get_x() + bar.get_width() / 2,
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bar.get_height() + errors[algorithms.index(bar.get_x())],
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f"{val:.1f}",
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ha="center",
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va="bottom",
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fontsize=10,
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)
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plt.tight_layout()
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plt.savefig("figures/comparison_bar.pdf", dpi=300)
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plt.savefig("figures/comparison_bar.png", dpi=150)
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print("Saved: figures/comparison_bar.pdf")
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plt.close()
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def main():
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print("Loading results...")
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stats = load_statistics()
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all_data = load_all_results()
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print("Generating figures...")
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plot_pdr_vs_airtime(all_data, stats)
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plot_pdr_vs_tx_cost(all_data, stats)
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plot_comparison_bar(stats)
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print("\nAll figures saved to figures/")
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if __name__ == "__main__":
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main()
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