from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np

with open("out.log") as fh:
    values = [map(float, line.strip().split()) for line in fh]
    #values = [(b, a, l) for (b, a, l) in values if b >= 0.04]
    am = max(values, key=lambda x: x[4])
    # am[0] = 1./am[0]
    print am
    alpha, delta, beta, _ , l = zip(*values)
    alpha = 1./np.array(alpha)

    fig = plt.figure(figsize=(12, 8))
    ax = fig.gca(projection='3d')

    ax.plot_trisurf(alpha, delta, l, cmap=cm.jet, linewidth=0.001)
    plt.xlabel("alpha")
    plt.ylabel("delta")
    ax.set_zlabel('Likelihood')
    #plt.savefig("ll.pdf")
    plt.show()