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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, r , 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()
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