def test_markdown(self):
"""Test whether the _repr_markdown_ method."""
A = (2, 2)
B = (1, 2)
C = (0, 3)
parents = DiscreteKeys()
parents.push_back(B)
parents.push_back(C)
conditional = DiscreteConditional(A, parents,
"0/1 1/3 1/1 3/1 0/1 1/0")
expected = " *P(A|B,C):*\n\n" \
"|*B*|*C*|0|1|\n" \
"|:-:|:-:|:-:|:-:|\n" \
"|0|0|0|1|\n" \
"|0|1|0.25|0.75|\n" \
"|0|2|0.5|0.5|\n" \
"|1|0|0.75|0.25|\n" \
"|1|1|0|1|\n" \
"|1|2|1|0|\n"
def formatter(x: int):
names = ["C", "B", "A"]
return names[x]
actual = conditional._repr_markdown_(formatter)
self.assertEqual(actual, expected)
def test_marginals(self):
conditional = DiscreteConditional(A, [B], "1/2 2/1")
prior = DiscreteConditional(B, "1/2")
pAB = prior * conditional
self.gtsamAssertEquals(prior, pAB.marginal(B[0]))
pA = DiscreteConditional(A, "5/4")
self.gtsamAssertEquals(pA, pAB.marginal(A[0]))
def test_multiply(self):
"""Check calculation of joint P(A,B)"""
conditional = DiscreteConditional(A, [B], "1/2 2/1")
prior = DiscreteConditional(B, "1/2")
# P(A,B) = P(A|B) * P(B) = P(B) * P(A|B)
for actual in [prior * conditional, conditional * prior]:
self.assertEqual(2, actual.nrFrontals())
for v, value in actual.enumerate():
self.assertAlmostEqual(actual(v), conditional(v) * prior(v))
def test_multiply2(self):
"""Check calculation of conditional joint P(A,B|C)"""
A_given_B = DiscreteConditional(A, [B], "1/3 3/1")
B_given_C = DiscreteConditional(B, [C], "1/3 3/1")
# P(A,B|C) = P(A|B)P(B|C) = P(B|C)P(A|B)
for actual in [A_given_B * B_given_C, B_given_C * A_given_B]:
self.assertEqual(2, actual.nrFrontals())
self.assertEqual(1, actual.nrParents())
for v, value in actual.enumerate():
self.assertAlmostEqual(actual(v), A_given_B(v) * B_given_C(v))
def test_multiply4(self):
"""Check calculation of joint P(A,B,C|D,E) = P(A,B|D) P(C|D,E)"""
A_given_B = DiscreteConditional(A, [B], "1/3 3/1")
B_given_D = DiscreteConditional(B, [D], "1/3 3/1")
AB_given_D = A_given_B * B_given_D
C_given_DE = DiscreteConditional(C, [D, E], "4/1 1/1 1/1 1/4")
# P(A,B,C|D,E) = P(A,B|D) P(C|D,E) = P(C|D,E) P(A,B|D)
for actual in [AB_given_D * C_given_DE, C_given_DE * AB_given_D]:
self.assertEqual(3, actual.nrFrontals())
self.assertEqual(2, actual.nrParents())
for v, value in actual.enumerate():
self.assertAlmostEqual(actual(v),
AB_given_D(v) * C_given_DE(v))
def test_single_value_versions(self):
X = (0, 2)
Y = (1, 3)
conditional = DiscreteConditional(X, [Y], "2/8 4/6 5/5")
actual0 = conditional.likelihood(0)
expected0 = DecisionTreeFactor(Y, "0.2 0.4 0.5")
self.gtsamAssertEquals(actual0, expected0, 1e-9)
actual1 = conditional.likelihood(1)
expected1 = DecisionTreeFactor(Y, "0.8 0.6 0.5")
self.gtsamAssertEquals(actual1, expected1, 1e-9)
actual = conditional.sample(2)
self.assertIsInstance(actual, int)
def test_constructor(self):
"""Test constructing a Bayes net."""
bayesNet = DiscreteBayesNet()
Parent, Child = (0, 2), (1, 2)
empty = DiscreteKeys()
prior = DiscreteConditional(Parent, empty, "6/4")
bayesNet.add(prior)
parents = DiscreteKeys()
parents.push_back(Parent)
conditional = DiscreteConditional(Child, parents, "7/3 8/2")
bayesNet.add(conditional)
# Check conversion to factor graph:
fg = DiscreteFactorGraph(bayesNet)
self.assertEqual(fg.size(), 2)
self.assertEqual(fg.at(1).size(), 2)