import os
import pandas as pd
import matplotlib.pyplot as plt

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["algorithm"] == "binary"].copy()
df["relax_success_ratio"] = df["relax_success"] / df["relax_attempts"]

# N vs extract_min_calls
grouped = df.groupby("nodes")["extract_min_calls"].mean()

plt.figure(figsize=(6,4))
plt.plot(grouped.index, grouped.values, marker='o')
plt.xlabel("N (nodes)")
plt.ylabel("Average extract_min_calls")
plt.title("Nodes vs Extract-Min Calls")
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{save_folder}/N_vs_extract_min.png", dpi=300)
plt.close()

# Density vs relax_attempts
grouped = df.groupby("density")["relax_attempts"].mean()

plt.figure(figsize=(6,4))
plt.plot(grouped.index, grouped.values, marker='o')
plt.xlabel("Density")
plt.ylabel("Average relax_attempts")
plt.title("Density vs Relax Attempts")
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{save_folder}/density_vs_relax_attempts.png", dpi=300)
plt.close()

# Sigma vs relax_success_ratio
grouped = df.groupby("sigma")["relax_success_ratio"].mean()

plt.figure(figsize=(6,4))
plt.plot(grouped.index, grouped.values, marker='o')
plt.xlabel("Sigma (lognormal)")
plt.ylabel("Relax Success Ratio")
plt.title("Sigma vs Relax Success Ratio")
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{save_folder}/sigma_vs_relax_ratio.png", dpi=300)
plt.close()