准备写论文，论文大纲和数据搞定

generate_bars.py

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+#!/usr/bin/env python
+"""
+Generate comparison bar chart.
+"""
+
+import json
+import matplotlib
+
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+
+
+def load_statistics():
+    with open("results/statistics.json", "r") as f:
+        return json.load(f)
+
+
+def main():
+    stats = load_statistics()
+
+    fig, axes = plt.subplots(1, 3, figsize=(12, 4))
+
+    algorithms = ["gradient", "flooding", "random"]
+    colors = ["#2E86AB", "#E94F37", "#7D8491"]
+
+    metrics = [
+        ("pdr", "PDR (%)"),
+        ("airtime_usage_percent", "Airtime (%)"),
+        ("tx_per_success", "TX/Success"),
+    ]
+
+    for idx, (metric, label) in enumerate(metrics):
+        ax = axes[idx]
+        values = [stats[a][metric]["mean"] for a in algorithms]
+        errors = [stats[a][metric]["ci_95"] for a in algorithms]
+
+        bars = ax.bar(
+            algorithms, values, yerr=errors, color=colors, capsize=5, alpha=0.8
+        )
+        ax.set_ylabel(label, fontsize=11)
+        ax.set_title(label, fontsize=12)
+        ax.grid(True, alpha=0.3, axis="y")
+
+        # Add value labels
+        for i, (bar, val, err) in enumerate(zip(bars, values, errors)):
+            ax.text(
+                i, val + err + 0.5, f"{val:.1f}", ha="center", va="bottom", fontsize=10
+            )
+
+    plt.tight_layout()
+    plt.savefig("figures/comparison_bar.pdf", dpi=300)
+    plt.savefig("figures/comparison_bar.png", dpi=150)
+    print("Saved: figures/comparison_bar.pdf")
+
+
+if __name__ == "__main__":
+    main()