import json
import numpy as np
import matplotlib.pyplot as plt

with open("output/maxrl_binary_400/Scenario.codegeneration_256_0.6_eval_all.json") as f:
    data = json.load(f)

graded_lists = [item["graded_list"] for item in data]

def bootstrap_pass_at_k(graded_lists, k, n_bootstrap=10000, rng=None):
    if rng is None:
        rng = np.random.default_rng(42)
    problem_scores = []
    for outcomes in graded_lists:
        outcomes_arr = np.array(outcomes, dtype=bool)
        n = len(outcomes_arr)
        samples = rng.integers(0, n, size=(n_bootstrap, k))
        any_pass = outcomes_arr[samples].any(axis=1)
        problem_scores.append(any_pass.mean())
    return np.mean(problem_scores)

k_values = [1, 2, 4, 8, 16, 32, 64, 128, 256]
rng = np.random.default_rng(42)
pass_at_k = [bootstrap_pass_at_k(graded_lists, k, rng=rng) for k in k_values]

print("maxrl_binary_400 pass@k:")
for k, v in zip(k_values, pass_at_k):
    print(f"  pass@{k}: {v:.4f}")

fig, ax = plt.subplots(figsize=(8, 5))
line, = ax.plot(k_values, pass_at_k, marker="o", linewidth=2, markersize=8,
                color="steelblue", label="maxrl_binary_400")
for k, v in zip(k_values, pass_at_k):
    ax.annotate(f"{v:.3f}", (k, v), textcoords="offset points", xytext=(5, 6),
                fontsize=8, color=line.get_color())

ax.set_xscale("log", base=2)
ax.set_xticks(k_values)
ax.set_xticklabels([str(k) for k in k_values])
ax.set_xlabel("k", fontsize=12)
ax.set_ylabel("pass@k", fontsize=12)
ax.set_title("pass@k — maxrl_binary_400 (n=256 samples)", fontsize=13)
ax.set_ylim(0, max(pass_at_k) * 1.3)
ax.legend(fontsize=10)
ax.grid(True, alpha=0.3)
plt.tight_layout()
plt.savefig("maxrl_400_pass_at_k.png", dpi=150)
print("Saved maxrl_400_pass_at_k.png")