import subprocess
import re
import numpy as np
import matplotlib.pyplot as plt

def run_pagerank(matrix_path, epsilon, alpha):
    """
    Execute pagerank binary with given parameters
    Returns a dictionary with parsed output or None if execution fails.
    """
    cmd = [
        "./out/pagerank",
        "--matrix", matrix_path,
        "--epsilon", str(epsilon),
        "--alpha", str(alpha)
    ]

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

        data = {}
        match = re.search(r"Read and convert matrix: (\d+\.\d+) seconds", output)
        data["read_time"] = float(match.group(1)) if match else None

        match = re.search(r"Pagerank: (\d+) Iterations", output)
        data["pagerank_iterations"] = int(match.group(1)) if match else None

        match = re.search(r"Pagerank: (\d+\.\d+) seconds", output)
        data["pagerank_time"] = float(match.group(1)) if match else None

        match = re.search(r"Gauss-Seidel: (\d+) Iterations", output)
        data["gauss_seidel_iterations"] = int(match.group(1)) if match else None

        match = re.search(r"Gauss-Seidel:: (\d+\.\d+) seconds", output)
        data["gauss_seidel_time"] = float(match.group(1)) if match else None

        match = re.search(r"Difference norm Pagerank and Gauss-Seidel: (\d+\.\d+)", output)
        data["diff_norm"] = float(match.group(1)) if match else None

        return data

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

def main():
    matrix_path = "./out/input.mtx"
    epsilon = 1e-10
    alpha_values = np.arange(0, 1, 0.1)

    pagerank_iterations = []
    gauss_seidel_iterations = []
    pagerank_times = []
    gauss_seidel_times = []
    diff_norms = []

    for alpha in alpha_values:
        print(f"Running for alpha={alpha:.3f}")
        data = run_pagerank(matrix_path, epsilon, alpha)
        if data:
            pagerank_iterations.append(data["pagerank_iterations"])
            gauss_seidel_iterations.append(data["gauss_seidel_iterations"])
            pagerank_times.append(data["pagerank_time"])
            gauss_seidel_times.append(data["gauss_seidel_time"])
            diff_norms.append(data["diff_norm"])
        else:
            print(f"Skipping alpha={alpha:.3f} due to error")
            pagerank_iterations.append(None)
            gauss_seidel_iterations.append(None)
            pagerank_times.append(None)
            gauss_seidel_times.append(None)
            diff_norms.append(None)

    # plots
    fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(10, 12), sharex=True)

    # 1: Number of iterations
    ax1.plot(alpha_values, pagerank_iterations, label="PageRank Iterations", color="blue")
    ax1.plot(alpha_values, gauss_seidel_iterations, label="Gauss-Seidel Iterations", color="red")
    ax1.set_ylabel("Number of Iterations")
    ax1.set_title("Iterations vs. Alpha")
    ax1.legend()
    ax1.grid(True)

    # 2: Execution time
    ax2.plot(alpha_values, pagerank_times, label="PageRank Time", color="blue")
    ax2.plot(alpha_values, gauss_seidel_times, label="Gauss-Seidel Time", color="red")
    ax2.set_ylabel("Time (seconds)")
    ax2.set_title("Execution Time vs. Alpha")
    ax2.legend()
    ax2.grid(True)

    # 3: Difference norm
    ax3.plot(alpha_values, diff_norms, label="Difference Norm", color="green")
    ax3.set_xlabel("Alpha")
    ax3.set_ylabel("Norm Difference")
    ax3.set_title("Difference Norm between PageRank and Gauss-Seidel vs. Alpha")
    ax3.legend()
    ax3.grid(True)

    plt.show()

if __name__ == "__main__":
    main()