def test_process_graph_1_factor(self):
"""
Test that the get_posterior_joint returns the correct joint distribution (after the graph has been processed)
for a graph constructed with a single factor.
"""
factors = [self.p_a_b_c]
cga = ClusterGraph(factors)
cga.process_graph()
actual_posterior_joint = cga.get_posterior_joint()
expected_posterior_joint = self.p_a_b_c.copy()
self.assertTrue(
actual_posterior_joint.equals(expected_posterior_joint))
def test_process_graph_1_factor_se(self):
"""
Test that the get_posterior_joint returns the correct joint distribution (after the graph has been processed)
for a graph constructed with a single factor and special evidence.
"""
factors = [self.p_a_b_c]
cga = ClusterGraph(factors, special_evidence={"a": 0.3})
cga.process_graph()
actual_posterior_joint = cga.get_posterior_joint()
expected_posterior_joint = self.p_a_b_c.observe(["a"], [0.3])
self.assertTrue(
actual_posterior_joint.equals(expected_posterior_joint))
def test_get_posterior_joint(self):
"""
Test that the get_posterior_joint returns the correct joint distribution after the graph has been processed.
"""
factors = [self.p_a, self.p_b_g_a, self.p_c_g_a]
cga = ClusterGraph(factors)
cga.process_graph()
actual_posterior_joint = cga.get_posterior_joint()
actual_posterior_joint._update_covform()
expected_posterior_joint = self.p_a_b_c.copy()
self.assertTrue(
actual_posterior_joint.equals(expected_posterior_joint))