#!/bin/python3
import argparse, subprocess, re, tempfile, os
import numpy as np
import matplotlib.pyplot as plt
from gen_values import generate_test_file

def run_agcd(input_file):
    cmd = ["./target/release/approximate-gcd", "agcd", input_file]

    try:
        result = subprocess.run(cmd, capture_output=True, text=True, check=True)
        output = result.stdout

        match = re.search(r"Recovered p: (\d+)", output)
        return int(match.group(1)) if match else None

    except subprocess.CalledProcessError as e:
        print(f"Error running command for input_file={input_file}: {e}")
        return None
    except (AttributeError, ValueError) as e:
        print(f"Error parsing output for input_file={input_file}: {e}")
        return None


def plot_curves(noise_bits, p_bits, test_numbers, successes):
    plt.figure(figsize=(10, 6))
    plt.plot(test_numbers, successes, marker='o')
    plt.xlabel('Number of Test Values')
    plt.ylabel('Success (1 = Correct, 0 = Incorrect)')
    plt.title(f'Success vs. Number of Test Values\n(noise_bits={noise_bits}, p_bits={p_bits})')
    plt.grid(True)
    plt.ylim(-0.1, 1.1)
    plt.yticks([0, 1])
    plt.xticks(test_numbers)
    plt.savefig('success_plot.png')
    plt.show()

def main():
    parser = argparse.ArgumentParser(description='Test AGCD with varying number of test values.')
    parser.add_argument('--noise_bits', type=int, default=8, help='Number of noise bits')
    parser.add_argument('--p_bits', type=int, default=128, help='Number of bits for p')
    parser.add_argument('--min_values', type=int, default=2, help='Minimum number of test values')
    parser.add_argument('--max_values', type=int, default=100, help='Maximum number of test values')
    args = parser.parse_args()

    noise_bits = args.noise_bits
    p_bits = args.p_bits
    test_numbers = range(args.min_values, args.max_values + 1)
    successes = []

    for num_values in test_numbers:
        # Create temporary test file
        with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.txt') as tmp_file:
            true_p = generate_test_file(noise_bits, num_values, p_bits, tmp_file.name)

            # Run AGCD
            recovered_p = run_agcd(tmp_file.name)

            # Check if recovery was successful
            success = 1 if recovered_p != None and abs(recovered_p - true_p) <= 4 else 0
            successes.append(success)

            # Clean up
            os.unlink(tmp_file.name)

        print(f"Number of values: {num_values}, Success: {'Yes' if success else 'No'}")

    # Plot the results
    plot_curves(noise_bits, p_bits, test_numbers, successes)

if __name__ == "__main__":
    main()