#!/bin/python3
import argparse
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 \(power\): (\d+) Iterations", output)
        data["pagerank_iterations"] = int(match.group(1)) if match else None

        match = re.search(r"Pagerank \(power\): (\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 power 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 generate_data(matrix_path, epsilon, alpha_values):
    pagerank_iterations = []
    gauss_seidel_iterations = []
    pagerank_times = []
    gauss_seidel_times = []
    diff_norms = []

    for alpha in alpha_values:
        print(f"Running for alpha={alpha:.6f}")
        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:.6f} 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)

    return (pagerank_iterations, gauss_seidel_iterations, pagerank_times, gauss_seidel_times, diff_norms)


def plot_curves(alpha_values, pagerank_iterations, gauss_seidel_iterations, pagerank_times, gauss_seidel_times, diff_norms):
    # plots
    fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(10, 12), sharex=False)

    # 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. α")
    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. α")
    ax2.legend()
    ax2.grid(True)

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

    plt.show()


def main():
    parser = argparse.ArgumentParser(description='Pagerank vs Gauß Seidel execution time depending on α')
    parser.add_argument('--alpha', type=int, default=10, help='number of alpha to test in the range (0,1)')
    parser.add_argument('--max_alpha', type=float, default=1, help='stay strictly below this alpha')
    parser.add_argument('--epsilon', type=float, default=1e-7, help='epsilon value for the convergence')
    parser.add_argument('--matrix', type=str, default="out/input.mtx", help='path to the matrix file')
    args = parser.parse_args()

    alpha_values = np.arange(0, args.max_alpha, (1/args.alpha))

    (pagerank_iterations, gauss_seidel_iterations, pagerank_times, gauss_seidel_times, diff_norms) = generate_data(args.matrix, args.epsilon, alpha_values)
    plot_curves(alpha_values, pagerank_iterations, gauss_seidel_iterations, pagerank_times, gauss_seidel_times, diff_norms)


if __name__ == "__main__":
    main()