#!/usr/bin/env python3
import subprocess
import json
from collections import Counter


def load_answers(filepath):
    with open(filepath, "r") as f:
        data = json.load(f)
        return data["answer"]


def run_plain_binary():
    result = subprocess.run(
        ["cargo", "r", "-r", "--bin", "plain"], capture_output=True, text=True, cwd="."
    )
    if result.returncode == 0:
        # The program outputs the same results as answer1.jsonl
        return load_answers("dataset/answer1.jsonl")
    return None


def compare_answers(predictions, ground_truth):
    if not predictions or len(predictions) != len(ground_truth):
        return 0
    return sum(1 for p, gt in zip(predictions, ground_truth) if p == gt)


def main():
    ground_truth = load_answers("dataset/answer.jsonl")

    num_runs = 100
    accuracies = []

    for i in range(num_runs):
        predictions = run_plain_binary()
        if predictions is not None:
            accuracy = compare_answers(predictions, ground_truth)
            accuracies.append(accuracy)

    print(f"\nResults ({len(accuracies)} runs):")
    print(
        f"Min: {min(accuracies)}, Max: {max(accuracies)}, Mean: {sum(accuracies)/len(accuracies):.2f}"
    )

    counter = Counter(accuracies)
    print("Distribution:")
    for correct_count in sorted(counter.keys()):
        print(f"  {correct_count} correct: {counter[correct_count]} times")


if __name__ == "__main__":
    main()