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codes/experiments/synthetic_data/analysis/speed_ratio.py

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+import pandas as pd
+import matplotlib.pyplot as plt
+import os
+
+csv_file = "results/synthetic_data/raw/20260302_183202.csv"
+save_folder = f"results/synthetic_data/derived/{os.path.splitext(os.path.basename(csv_file))[0]}"
+os.makedirs(save_folder, exist_ok=True)
+
+df = pd.read_csv(csv_file)
+# df = df[df["reached"] == True].copy()
+
+key_cols = ["nodes", "density", "std", "sigma", "trial", "seed"]
+
+pivot_time = (
+    df.pivot_table(index=key_cols, columns="algorithm", values="time", aggfunc="mean")
+    .reset_index()
+)
+pivot_time["speed_ratio"] = pivot_time["binary"] / pivot_time["fibonacci"]
+
+# print((pivot_time["speed_ratio"] > 1).sum())
+# print((pivot_time["speed_ratio"] < 1).sum())
+
+relax = (
+    df[df["algorithm"] == "binary"][key_cols + ["relax_success"]]
+)
+
+merged = pivot_time.merge(relax, on=key_cols, how="left")
+
+plt.figure(figsize=(6, 4))
+plt.scatter(merged["relax_success"], merged["speed_ratio"], marker=".")
+plt.axhline(y=1.0, color='red', linestyle='--')
+plt.xlabel("decrease_key (binary)")
+plt.ylabel("speed_ratio (binary / fibonacci)")
+plt.title("decrease_key vs speed_ratio")
+plt.grid(True)
+plt.tight_layout()
+plt.savefig(f"{save_folder}/decrease_key_vs_speed_ratio.png", dpi=300)
+plt.close()