def test_sample_confidence_region():
"""Test sampling from confidence region."""
random_state = check_random_state(0)
means = np.array([[0.0, 1.0], [2.0, -1.0]])
covariances = np.array([[[0.5, 0.0], [0.0, 5.0]], [[5.0, 0.0], [0.0,
0.5]]])
gmm = GMM(n_components=2,
priors=np.array([0.5, 0.5]),
means=means,
covariances=covariances,
random_state=random_state)
samples = gmm.sample_confidence_region(100, 0.7)
for sample in samples:
assert_true(gmm.is_in_confidence_region(sample, 0.7))
n_samples = 1000
plt.figure(figsize=(20, 5))
ax = plt.subplot(141)
ax.set_title("Unconstrained Sampling")
samples = gmm.sample(n_samples)
ax.scatter(samples[:, 0], samples[:, 1], alpha=0.9, s=1, label="Samples")
plot_error_ellipses(ax, gmm, factors=(1.0, 2.0), colors=["orange", "orange"])
ax.set_xlim((-10, 10))
ax.set_ylim((-10, 10))
ax = plt.subplot(142)
ax.set_title(r"95.45 % Confidence Region ($2\sigma$)")
samples = gmm.sample_confidence_region(n_samples, 0.9545)
ax.scatter(samples[:, 0], samples[:, 1], alpha=0.9, s=1, label="Samples")
plot_error_ellipses(ax, gmm, factors=(1.0, 2.0), colors=["orange", "orange"])
ax.set_xlim((-10, 10))
ax.set_ylim((-10, 10))
ax = plt.subplot(143)
ax.set_title(r"68.27 % Confidence Region ($\sigma$)")
samples = gmm.sample_confidence_region(n_samples, 0.6827)
ax.scatter(samples[:, 0], samples[:, 1], alpha=0.9, s=1, label="Samples")
plot_error_ellipses(ax, gmm, factors=(1.0, 2.0), colors=["orange", "orange"])
ax.set_xlim((-10, 10))
ax.set_ylim((-10, 10))
ax.legend()
ax = plt.subplot(144)
