def main():
N = 100
rep = 10
rs = np.logspace(-3, 0, 30)
x_p2 = mix(0.2, (rep, N))
x_p3 = mix(0.3, (rep, N))
x_p5 = mix(0.5, (rep, N))
es = np.zeros((2, len(rs)))
for ir, r in enumerate(rs):
runs = np.zeros((2, rep))
for i in range(rep):
runs[0, i] = entropy.cross_fuzzyen(x_p2[i, :], x_p3[i, :], 2, r, 2)
runs[1, i] = entropy.cross_fuzzyen(x_p3[i, :], x_p5[i, :], 2, r, 2)
es[:, ir] = np.mean(runs, axis=1)
fig, ax = plt.subplots()
ax.semilogx(rs, es[0], 'ro-', label='MIX(0.2) vs. MIX(0.3)')
ax.semilogx(rs, es[1], 'ko-', label='MIX(0.3) vs. MIX(0.5)')
ax.legend()
ax.set_ylim(0, 6)
plt.show()
def test_copies(self):
x = np.random.uniform(low=0, high=1, size=(2, 100))
x0 = np.copy(x[0])
x1 = np.copy(x[1])
entropy.sampen(x0, 2, 0.1)
assert_equal(x0, x[0])
entropy.fuzzyen(x0, 2, 0.1, 2)
assert_equal(x0, x[0])
entropy.cross_sampen(x0, x1, 2, 0.1)
assert_equal(x0, x[0])
assert_equal(x1, x[1])
entropy.cross_fuzzyen(x0, x1, 2, 0.1, 2)
assert_equal(x0, x[0])
assert_equal(x1, x[1])
