]
    return G


def vis(s1, s2, markovLik1, markovLik2, cyklik1, cyklik2):
    figsize = (30, 8)
    fig = plt.figure(figsize=figsize)
    ax = fig.add_subplot(2, 1, 1)
    ax.plot(s1, "--o")
    ax.set_title("Markov = %.4f \n CYK = %.4f" % (markovLik1, cyklik1))
    plt.grid()
    bx = fig.add_subplot(2, 1, 2)
    bx.plot(s2, "--o")
    bx.set_title("Markov = %.4f \n CYK = %.4f" % (markovLik2, cyklik2))
    plt.grid()
    plt.show()


if __name__ == "__main__":
    _, s1 = sample()
    _, s2 = sample2()
    g = grammar()
    m = markov()
    markovLik1, _ = m.decode(s1)
    markovLik2, _ = m.decode(s2)
    cyklik1 = cyk(s1, g)
    cyklik2 = cyk(s2, g)
    vis(s1, s2, markovLik1, markovLik2, cyklik1, cyklik2)
    # markovLearning(s1)
    # markovLearning(s2)
Exemple #2
0
def build(bp, root):
	a, b, c = root
	if c:
		(i,j, g, nta) = a
		(i, s1, bb, ntb) = b 
		(s2, j, cc, ntc) = c
		print "%s[%s:%s] -> %s[%s:%s] %s[%s:%s]"%(nta, i, j, ntb, i, s1, ntc, s2, j)
		build(bp, bp[i, s1, bb])
		build(bp, bp[s2, j, cc])
	else:
		(i,j, g, nta) = a
		(i, s1, bb, ntb) = b
		print "%s[%s] -> %s[%s]"%(nta, i, ntb, i)

if __name__ == '__main__':
	_, S = sample()
	
	A = Dist(np.array([0.0]), np.array([0.1]))
	B = Dist(np.array([5.0]), np.array([0.1]))
	C = Dist(np.array([-5.0]), np.array([0.1]))

	G = [ ('NT_1', A, None, 1.0), ('NT_2', B, None, 1.0), ("NT_3", C, None, 1.0), 
			("NT_4", "NT_1", "NT_1", 0.2), ("NT_4", "NT_4", "NT_1", 0.8),
			("NT_5", "NT_2", "NT_2", 0.2), ("NT_5", "NT_5", "NT_2", 0.8),
			("NT_6", "NT_3", "NT_3", 0.2), ("NT_6", "NT_6", "NT_3", 0.8),
			("NT_7", "NT_5", "NT_4", 1.0), ("NT_S", "NT_7", "NT_6", 1.0) ]

	print cyk(S, G)