def test_gmm_joint_prob(self):
"""Testing the GMM method
for calculating the joint
log probability of a given point.
Should return -0.9413.
returns:
joint_prob = float
"""
image_file = 'images/self_driving.png'
image_matrix = image_to_matrix(image_file)
num_components = 5
gmm = GaussianMixtureModel(image_matrix, num_components)
gmm.initialize_training()
gmm.means = np.array([0.03921569, 0.1764706, 0.06666667, 0.42745098, 0.2784314])
test_val = 0.03921569
joint_prob = gmm.joint_prob(test_val)
self.assertEqual(round(joint_prob, 4), -0.9413,
msg="Incorrect joint log probability")
def test_gmm_joint_prob(self):
"""Testing the GMM method
for calculating the joint
log probability of a given point.
Should return -0.98196.
returns:
joint_prob = float
"""
image_file = 'images/party_spock.png'
image_matrix = image_to_matrix(image_file)
num_components = 5
gmm = GaussianMixtureModel(image_matrix, num_components)
gmm.initialize_training()
gmm.means = [0.4627451, 0.10196079, 0.027450981,
0.011764706, 0.1254902]
test_val = 0.4627451
joint_prob = gmm.joint_prob(test_val)
self.assertEqual(round(joint_prob, 4), -0.982,
msg="Incorrect joint log probability")