def test_max_calibrate_clique_belief(self):
belief_propagation = BeliefPropagation(self.junction_tree)
belief_propagation.max_calibrate()
clique_belief = belief_propagation.get_clique_beliefs()
phi1 = Factor(['A', 'B'], [2, 3], range(6))
phi2 = Factor(['B', 'C'], [3, 2], range(6))
phi3 = Factor(['C', 'D'], [2, 2], range(4))
b_A_B = phi1 * (phi3.maximize(['D'], inplace=False) * phi2).maximize(['C'], inplace=False)
b_B_C = phi2 * (phi1.maximize(['A'], inplace=False) * phi3.maximize(['D'], inplace=False))
b_C_D = phi3 * (phi1.maximize(['A'], inplace=False) * phi2).maximize(['B'], inplace=False)
np_test.assert_array_almost_equal(clique_belief[('A', 'B')].values, b_A_B.values)
np_test.assert_array_almost_equal(clique_belief[('B', 'C')].values, b_B_C.values)
np_test.assert_array_almost_equal(clique_belief[('C', 'D')].values, b_C_D.values)
def test_max_calibrate_sepset_belief(self):
belief_propagation = BeliefPropagation(self.junction_tree)
belief_propagation.max_calibrate()
sepset_belief = belief_propagation.get_sepset_beliefs()
phi1 = Factor(['A', 'B'], [2, 3], range(6))
phi2 = Factor(['B', 'C'], [3, 2], range(6))
phi3 = Factor(['C', 'D'], [2, 2], range(4))
b_B = (phi1 * (phi3.maximize(['D'], inplace=False) *
phi2).maximize(['C'], inplace=False)).maximize(['A'], inplace=False)
b_C = (phi2 * (phi1.maximize(['A'], inplace=False) *
phi3.maximize(['D'], inplace=False))).maximize(['B'], inplace=False)
np_test.assert_array_almost_equal(sepset_belief[frozenset((('A', 'B'), ('B', 'C')))].values, b_B.values)
np_test.assert_array_almost_equal(sepset_belief[frozenset((('B', 'C'), ('C', 'D')))].values, b_C.values)
def test_max_calibrate_sepset_belief(self):
belief_propagation = BeliefPropagation(self.junction_tree)
belief_propagation.max_calibrate()
sepset_belief = belief_propagation.get_sepset_beliefs()
phi1 = Factor(['A', 'B'], [2, 3], range(6))
phi2 = Factor(['B', 'C'], [3, 2], range(6))
phi3 = Factor(['C', 'D'], [2, 2], range(4))
b_B = (phi1 * (phi3.maximize(['D'], inplace=False) * phi2).maximize(
['C'], inplace=False)).maximize(['A'], inplace=False)
b_C = (phi2 * (phi1.maximize(['A'], inplace=False) *
phi3.maximize(['D'], inplace=False))).maximize(
['B'], inplace=False)
np_test.assert_array_almost_equal(
sepset_belief[frozenset((('A', 'B'), ('B', 'C')))].values,
b_B.values)
np_test.assert_array_almost_equal(
sepset_belief[frozenset((('B', 'C'), ('C', 'D')))].values,
b_C.values)
def test_max_calibrate_clique_belief(self):
belief_propagation = BeliefPropagation(self.junction_tree)
belief_propagation.max_calibrate()
clique_belief = belief_propagation.get_clique_beliefs()
phi1 = Factor(['A', 'B'], [2, 3], range(6))
phi2 = Factor(['B', 'C'], [3, 2], range(6))
phi3 = Factor(['C', 'D'], [2, 2], range(4))
b_A_B = phi1 * (phi3.maximize(['D'], inplace=False) * phi2).maximize(
['C'], inplace=False)
b_B_C = phi2 * (phi1.maximize(['A'], inplace=False) *
phi3.maximize(['D'], inplace=False))
b_C_D = phi3 * (phi1.maximize(['A'], inplace=False) * phi2).maximize(
['B'], inplace=False)
np_test.assert_array_almost_equal(clique_belief[('A', 'B')].values,
b_A_B.values)
np_test.assert_array_almost_equal(clique_belief[('B', 'C')].values,
b_B_C.values)
np_test.assert_array_almost_equal(clique_belief[('C', 'D')].values,
b_C_D.values)
class TestFactorMethods(unittest.TestCase):
def setUp(self):
self.phi = Factor(['x1', 'x2', 'x3'], [2, 2, 2],
np.random.uniform(5, 10, size=8))
self.phi1 = Factor(['x1', 'x2', 'x3'], [2, 3, 2], range(12))
def test_scope(self):
self.assertListEqual(self.phi.scope(), ['x1', 'x2', 'x3'])
self.assertListEqual(self.phi1.scope(), ['x1', 'x2', 'x3'])
def test_assignment(self):
self.assertListEqual(
self.phi.assignment([0]),
[[State('x1', 0), State('x2', 0),
State('x3', 0)]])
self.assertListEqual(
self.phi.assignment([4, 5, 6]),
[[State('x1', 1), State(
'x2', 0), State('x3', 0)],
[State('x1', 1), State('x2', 0),
State('x3', 1)],
[State('x1', 1), State('x2', 1),
State('x3', 0)]])
self.assertListEqual(
self.phi1.assignment(np.array([4, 5, 6])),
[[State('x1', 0), State(
'x2', 2), State('x3', 0)],
[State('x1', 0), State('x2', 2),
State('x3', 1)],
[State('x1', 1), State('x2', 0),
State('x3', 0)]])
def test_assignment_indexerror(self):
self.assertRaises(IndexError, self.phi.assignment, [10])
self.assertRaises(IndexError, self.phi.assignment, [1, 3, 10, 5])
self.assertRaises(IndexError, self.phi.assignment,
np.array([1, 3, 10, 5]))
def test_get_cardinality(self):
self.assertEqual(self.phi.get_cardinality('x1'), 2)
self.assertEqual(self.phi.get_cardinality('x2'), 2)
self.assertEqual(self.phi.get_cardinality('x3'), 2)
def test_get_cardinality_scopeerror(self):
self.assertRaises(exceptions.ScopeError, self.phi.get_cardinality,
'x4')
def test_marginalize(self):
self.phi1.marginalize('x1')
np_test.assert_array_equal(self.phi1.values,
np.array([6, 8, 10, 12, 14, 16]))
self.phi1.marginalize(['x2'])
np_test.assert_array_equal(self.phi1.values, np.array([30, 36]))
self.phi1.marginalize('x3')
np_test.assert_array_equal(self.phi1.values, np.array([66]))
def test_marginalize_scopeerror(self):
self.assertRaises(exceptions.ScopeError, self.phi.marginalize, 'x4')
self.assertRaises(exceptions.ScopeError, self.phi.marginalize, ['x4'])
self.phi.marginalize('x1')
self.assertRaises(exceptions.ScopeError, self.phi.marginalize, 'x1')
def test_normalize(self):
self.phi1.normalize()
np_test.assert_almost_equal(
self.phi1.values,
np.array([
0, 0.01515152, 0.03030303, 0.04545455, 0.06060606, 0.07575758,
0.09090909, 0.10606061, 0.12121212, 0.13636364, 0.15151515,
0.16666667
]))
def test_reduce(self):
self.phi1.reduce([('x1', 0), ('x2', 0)])
np_test.assert_array_equal(self.phi1.values, np.array([0, 1]))
def test_reduce1(self):
self.phi1.reduce([('x2', 0), ('x1', 0)])
np_test.assert_array_equal(self.phi1.values, np.array([0, 1]))
@unittest.skip
def test_complete_reduce(self):
self.phi1.reduce([('x1', 0), ('x2', 0), ('x3', 1)])
np_test.assert_array_equal(self.phi1.values, np.array([0]))
np_test.assert_array_equal(self.phi1.cardinality, np.array([]))
np_test.assert_array_equal(self.phi1.variables, OrderedDict())
def test_reduce_typeerror(self):
self.assertRaises(ValueError, self.phi1.reduce, 'x10')
self.assertRaises(ValueError, self.phi1.reduce, ['x10'])
def test_reduce_scopeerror(self):
self.assertRaises(ValueError, self.phi1.reduce, ('x4', 1))
def test_reduce_sizeerror(self):
self.assertRaises(IndexError, self.phi1.reduce, ('x3', 5))
def test_identity_factor(self):
identity_factor = self.phi.identity_factor()
self.assertEquals(list(identity_factor.variables), ['x1', 'x2', 'x3'])
np_test.assert_array_equal(identity_factor.cardinality, [2, 2, 2])
np_test.assert_array_equal(identity_factor.values, np.ones(8))
def test_factor_product(self):
phi = Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = Factor(['x3', 'x4'], [2, 2], range(4))
prod = factor_product(phi, phi1)
np_test.assert_array_equal(
prod.values,
np.array([0, 0, 0, 0, 0, 1, 2, 3, 0, 2, 4, 6, 0, 3, 6, 9]))
self.assertEqual(
prod.variables,
OrderedDict([('x1', [State('x1', 0),
State('x1', 1)]),
('x2', [State('x2', 0),
State('x2', 1)]),
('x3', [State('x3', 0),
State('x3', 1)]),
('x4', [State('x4', 0),
State('x4', 1)])]))
phi = Factor(['x1', 'x2'], [3, 2], range(6))
phi1 = Factor(['x2', 'x3'], [2, 2], range(4))
prod = factor_product(phi, phi1)
np_test.assert_array_equal(
prod.values, np.array([0, 0, 2, 3, 0, 2, 6, 9, 0, 4, 10, 15]))
self.assertEqual(
prod.variables,
OrderedDict([('x1',
[State('x1', 0),
State('x1', 1),
State('x1', 2)]),
('x2', [State('x2', 0),
State('x2', 1)]),
('x3', [State('x3', 0),
State('x3', 1)])]))
def test_factor_product2(self):
from pgmpy import factors
phi = factors.Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = factors.Factor(['x3', 'x4'], [2, 2], range(4))
prod = phi.product(phi1)
np_test.assert_array_equal(
prod.values,
np.array([0, 0, 0, 0, 0, 1, 2, 3, 0, 2, 4, 6, 0, 3, 6, 9]))
self.assertEqual(
prod.variables,
OrderedDict([('x1', [State('x1', 0),
State('x1', 1)]),
('x2', [State('x2', 0),
State('x2', 1)]),
('x3', [State('x3', 0),
State('x3', 1)]),
('x4', [State('x4', 0),
State('x4', 1)])]))
phi = Factor(['x1', 'x2'], [3, 2], range(6))
phi1 = Factor(['x2', 'x3'], [2, 2], range(4))
prod = phi.product(phi1)
np_test.assert_array_equal(
prod.values, np.array([0, 0, 2, 3, 0, 2, 6, 9, 0, 4, 10, 15]))
self.assertEqual(
prod.variables,
OrderedDict([('x1',
[State('x1', 0),
State('x1', 1),
State('x1', 2)]),
('x2', [State('x2', 0),
State('x2', 1)]),
('x3', [State('x3', 0),
State('x3', 1)])]))
def test_factor_product_non_factor_arg(self):
self.assertRaises(TypeError, factor_product, 1, 2)
def test_factor_mul(self):
phi = Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = Factor(['x3', 'x4'], [2, 2], range(4))
prod = phi * phi1
np_test.assert_array_equal(
prod.values,
np.array([0, 0, 0, 0, 0, 1, 2, 3, 0, 2, 4, 6, 0, 3, 6, 9]))
self.assertEqual(
prod.variables,
OrderedDict([('x1', [State('x1', 0),
State('x1', 1)]),
('x2', [State('x2', 0),
State('x2', 1)]),
('x3', [State('x3', 0),
State('x3', 1)]),
('x4', [State('x4', 0),
State('x4', 1)])]))
def test_factor_divide(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 2, 4])
phi2 = Factor(['x1'], [2], [1, 2])
div = phi1.divide(phi2)
phi3 = Factor(['x1', 'x2'], [2, 2], [1, 2, 1, 2])
self.assertEqual(phi3, div)
def test_factor_divide_truediv(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 2, 4])
phi2 = Factor(['x1'], [2], [1, 2])
div = phi1 / phi2
phi3 = Factor(['x1', 'x2'], [2, 2], [1, 2, 1, 2])
self.assertEqual(phi3, div)
# def test_factor_divide_dividebyzero(self):
# phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 3, 4])
# phi2 = Factor(['x1'], [2], [0, 2])
# self.assertRaises(FloatingPointError, factor_divide, phi1, phi2)
#
def test_factor_divide_invalidvalue(self):
phi1 = Factor(['x1', 'x2'], [3, 2], [0.5, 0.2, 0, 0, 0.3, 0.45])
phi2 = Factor(['x1'], [3], [0.8, 0, 0.6])
div = phi1.divide(phi2)
np_test.assert_array_equal(div.values,
np.array([0.625, 0.25, 0, 0, 0.5, 0.75]))
def test_factor_divide_no_common_scope(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 3, 4])
phi2 = Factor(['x3'], [2], [0, 2])
self.assertRaises(ValueError, factor_divide, phi1, phi2)
def test_factor_divide_non_factor_arg(self):
self.assertRaises(TypeError, factor_divide, 1, 1)
def test_eq(self):
self.assertFalse(self.phi == self.phi1)
self.assertTrue(self.phi == self.phi)
self.assertTrue(self.phi1 == self.phi1)
def test_eq1(self):
phi1 = Factor(['x1', 'x2', 'x3'], [2, 4, 3], range(24))
phi2 = Factor(['x2', 'x1', 'x3'], [4, 2, 3], [
0, 1, 2, 12, 13, 14, 3, 4, 5, 15, 16, 17, 6, 7, 8, 18, 19, 20, 9,
10, 11, 21, 22, 23
])
self.assertTrue(phi1, phi2)
def test_index_for_assignment(self):
for i, j in enumerate(
itertools.product(
*[range(2), range(3), range(2)])):
self.assertEqual(self.phi1._index_for_assignment(j), i)
def test_maximize1(self):
self.phi1.maximize('x1')
self.assertEqual(self.phi1,
Factor(['x2', 'x3'], [3, 2], [6, 7, 8, 9, 10, 11]))
self.phi1.maximize('x2')
self.assertEqual(self.phi1, Factor(['x3'], [2], [10, 11]))
def test_maximize2(self):
self.phi1.maximize(['x1', 'x2'])
self.assertEqual(self.phi1, Factor(['x3'], [2], [10, 11]))
def test_maximize3(self):
self.phi2 = Factor(['x1', 'x2', 'x3'], [3, 2, 2], [
0.25, 0.35, 0.08, 0.16, 0.05, 0.07, 0.00, 0.00, 0.15, 0.21, 0.08,
0.18
])
self.phi2.maximize('x2')
self.assertEqual(
self.phi2,
Factor(['x1', 'x3'], [3, 2], [0.25, 0.35, 0.05, 0.07, 0.15, 0.21]))
def tearDown(self):
del self.phi
del self.phi1
class TestFactorMethods(unittest.TestCase):
def setUp(self):
self.phi = Factor(['x1', 'x2', 'x3'], [2, 2, 2], np.random.uniform(5, 10, size=8))
self.phi1 = Factor(['x1', 'x2', 'x3'], [2, 3, 2], range(12))
self.phi2 = Factor([('x1', 0), ('x2', 0), ('x3', 0)], [2, 3, 2], range(12))
# This larger factor (phi3) caused a bug in reduce
card3 = [3, 3, 3, 2, 2, 2, 2, 2, 2]
self.phi3 = Factor(['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'],
card3, np.arange(np.prod(card3), dtype=np.float))
def test_scope(self):
self.assertListEqual(self.phi.scope(), ['x1', 'x2', 'x3'])
self.assertListEqual(self.phi1.scope(), ['x1', 'x2', 'x3'])
def test_assignment(self):
self.assertListEqual(self.phi.assignment([0]), [[('x1', 0), ('x2', 0), ('x3', 0)]])
self.assertListEqual(self.phi.assignment([4, 5, 6]), [[('x1', 1), ('x2', 0), ('x3', 0)],
[('x1', 1), ('x2', 0), ('x3', 1)],
[('x1', 1), ('x2', 1), ('x3', 0)]])
self.assertListEqual(self.phi1.assignment(np.array([4, 5, 6])),
[[('x1', 0), ('x2', 2), ('x3', 0)],
[('x1', 0), ('x2', 2), ('x3', 1)],
[('x1', 1), ('x2', 0), ('x3', 0)]])
def test_assignment_indexerror(self):
self.assertRaises(IndexError, self.phi.assignment, [10])
self.assertRaises(IndexError, self.phi.assignment, [1, 3, 10, 5])
self.assertRaises(IndexError, self.phi.assignment, np.array([1, 3, 10, 5]))
def test_get_cardinality(self):
self.assertEqual(self.phi.get_cardinality(['x1']), {'x1': 2})
self.assertEqual(self.phi.get_cardinality(['x2']), {'x2': 2})
self.assertEqual(self.phi.get_cardinality(['x3']), {'x3': 2})
self.assertEqual(self.phi.get_cardinality(['x1', 'x2']), {'x1': 2, 'x2': 2})
self.assertEqual(self.phi.get_cardinality(['x1', 'x3']), {'x1': 2, 'x3': 2})
self.assertEqual(self.phi.get_cardinality(['x1', 'x2', 'x3']), {'x1': 2, 'x2': 2, 'x3': 2})
def test_get_cardinality_scopeerror(self):
self.assertRaises(ValueError, self.phi.get_cardinality, ['x4'])
def test_get_cardinality_typeerror(self):
self.assertRaises(TypeError, self.phi.get_cardinality, 'x1')
def test_marginalize(self):
self.phi1.marginalize(['x1'])
np_test.assert_array_equal(self.phi1.values, np.array([[6, 8],
[10, 12],
[14, 16]]))
self.phi1.marginalize(['x2'])
np_test.assert_array_equal(self.phi1.values, np.array([30, 36]))
self.phi1.marginalize(['x3'])
np_test.assert_array_equal(self.phi1.values, np.array(66))
def test_marginalize_scopeerror(self):
self.assertRaises(ValueError, self.phi.marginalize, ['x4'])
self.assertRaises(ValueError, self.phi.marginalize, ['x4'])
self.phi.marginalize(['x1'])
self.assertRaises(ValueError, self.phi.marginalize, ['x1'])
def test_marginalize_typeerror(self):
self.assertRaises(TypeError, self.phi.marginalize, 'x1')
def test_marginalize_shape(self):
values = ['A', 'D', 'F', 'H']
phi3_max = self.phi3.marginalize(values, inplace=False)
# Previously a sorting error caused these to be different
np_test.assert_array_equal(phi3_max.values.shape, phi3_max.cardinality)
def test_normalize(self):
self.phi1.normalize()
np_test.assert_almost_equal(self.phi1.values,
np.array([[[0, 0.01515152],
[0.03030303, 0.04545455],
[0.06060606, 0.07575758]],
[[0.09090909, 0.10606061],
[0.12121212, 0.13636364],
[0.15151515, 0.16666667]]]))
def test_reduce(self):
self.phi1.reduce([('x1', 0), ('x2', 0)])
np_test.assert_array_equal(self.phi1.values, np.array([0, 1]))
def test_reduce1(self):
self.phi1.reduce([('x2', 0), ('x1', 0)])
np_test.assert_array_equal(self.phi1.values, np.array([0, 1]))
def test_reduce_shape(self):
values = [('A', 0), ('D', 0), ('F', 0), ('H', 1)]
phi3_reduced = self.phi3.reduce(values, inplace=False)
# Previously a sorting error caused these to be different
np_test.assert_array_equal(phi3_reduced.values.shape, phi3_reduced.cardinality)
@unittest.skip
def test_complete_reduce(self):
self.phi1.reduce([('x1', 0), ('x2', 0), ('x3', 1)])
np_test.assert_array_equal(self.phi1.values, np.array([1]))
np_test.assert_array_equal(self.phi1.cardinality, np.array([]))
np_test.assert_array_equal(self.phi1.variables, OrderedDict())
def test_reduce_typeerror(self):
self.assertRaises(TypeError, self.phi1.reduce, 'x10')
self.assertRaises(TypeError, self.phi1.reduce, ['x10'])
self.assertRaises(TypeError, self.phi1.reduce, [('x1', 'x2')])
self.assertRaises(TypeError, self.phi1.reduce, [(0, 'x1')])
self.assertRaises(TypeError, self.phi1.reduce, [(0.1, 'x1')])
self.assertRaises(TypeError, self.phi1.reduce, [(0.1, 0.1)])
self.assertRaises(TypeError, self.phi1.reduce, [('x1', 0.1)])
def test_reduce_scopeerror(self):
self.assertRaises(ValueError, self.phi1.reduce, [('x4', 1)])
def test_reduce_sizeerror(self):
self.assertRaises(IndexError, self.phi1.reduce, [('x3', 5)])
def test_identity_factor(self):
identity_factor = self.phi.identity_factor()
self.assertEqual(list(identity_factor.variables), ['x1', 'x2', 'x3'])
np_test.assert_array_equal(identity_factor.cardinality, [2, 2, 2])
np_test.assert_array_equal(identity_factor.values, np.ones(8).reshape(2, 2, 2))
def test_factor_product(self):
phi = Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = Factor(['x3', 'x4'], [2, 2], range(4))
prod = factor_product(phi, phi1)
expected_factor = Factor(['x1', 'x2', 'x3', 'x4'], [2, 2, 2, 2], [0, 0, 0, 0, 0, 1,
2, 3, 0, 2, 4, 6,
0, 3, 6, 9])
self.assertEqual(prod, expected_factor)
self.assertEqual(sorted(prod.variables), ['x1', 'x2', 'x3', 'x4'])
phi = Factor(['x1', 'x2'], [3, 2], range(6))
phi1 = Factor(['x2', 'x3'], [2, 2], range(4))
prod = factor_product(phi, phi1)
expected_factor = Factor(['x1', 'x2', 'x3'], [3, 2, 2], [0, 0, 2, 3, 0, 2,
6, 9, 0, 4, 10, 15])
np_test.assert_almost_equal(prod.values,
np.array([0, 0, 2, 3, 0, 2,
6, 9, 0, 4, 10, 15]).reshape(3, 2, 2))
self.assertEqual(sorted(prod.variables), ['x1', 'x2', 'x3'])
def test_factor_product2(self):
from pgmpy import factors
phi = factors.Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = factors.Factor(['x3', 'x4'], [2, 2], range(4))
prod = phi.product(phi1, inplace=False)
expected_factor = Factor(['x1', 'x2', 'x3', 'x4'], [2, 2, 2, 2],
[0, 0, 0, 0, 0, 1, 2, 3, 0, 2, 4, 6, 0, 3, 6, 9])
self.assertEqual(prod, expected_factor)
self.assertEqual(sorted(prod.variables), ['x1', 'x2', 'x3', 'x4'])
phi = Factor(['x1', 'x2'], [3, 2], range(6))
phi1 = Factor(['x2', 'x3'], [2, 2], range(4))
prod = phi.product(phi1, inplace=False)
expected_factor = Factor(['x1', 'x2', 'x3'], [3, 2, 2],
[0, 0, 2, 3, 0, 2, 6, 9, 0, 4, 10, 15])
self.assertEqual(prod, expected_factor)
self.assertEqual(sorted(prod.variables), ['x1', 'x2', 'x3'])
def test_factor_product_non_factor_arg(self):
self.assertRaises(TypeError, factor_product, 1, 2)
def test_factor_mul(self):
phi = Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = Factor(['x3', 'x4'], [2, 2], range(4))
prod = phi * phi1
sorted_vars = ['x1', 'x2', 'x3', 'x4']
for axis in range(prod.values.ndim):
exchange_index = prod.variables.index(sorted_vars[axis])
prod.variables[axis], prod.variables[exchange_index] = prod.variables[exchange_index], prod.variables[axis]
prod.values = prod.values.swapaxes(axis, exchange_index)
np_test.assert_almost_equal(prod.values.ravel(),
np.array([0, 0, 0, 0, 0, 1,
2, 3, 0, 2, 4, 6,
0, 3, 6, 9]))
self.assertEqual(prod.variables, ['x1', 'x2', 'x3', 'x4'])
def test_factor_divide(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 2, 4])
phi2 = Factor(['x1'], [2], [1, 2])
div = phi1.divide(phi2, inplace=False)
phi3 = Factor(['x1', 'x2'], [2, 2], [1, 2, 1, 2])
self.assertEqual(phi3, div)
def test_factor_divide_truediv(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 2, 4])
phi2 = Factor(['x1'], [2], [1, 2])
div = phi1 / phi2
phi3 = Factor(['x1', 'x2'], [2, 2], [1, 2, 1, 2])
self.assertEqual(phi3, div)
def test_factor_divide_invalid(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 3, 4])
phi2 = Factor(['x1'], [2], [0, 2])
div = phi1.divide(phi2, inplace=False)
np_test.assert_array_equal(div.values.ravel(), np.array([np.inf, np.inf, 1.5, 2]))
def test_factor_divide_no_common_scope(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 3, 4])
phi2 = Factor(['x3'], [2], [0, 2])
self.assertRaises(ValueError, factor_divide, phi1, phi2)
def test_factor_divide_non_factor_arg(self):
self.assertRaises(TypeError, factor_divide, 1, 1)
def test_eq(self):
self.assertFalse(self.phi == self.phi1)
self.assertTrue(self.phi == self.phi)
self.assertTrue(self.phi1 == self.phi1)
def test_eq1(self):
phi1 = Factor(['x1', 'x2', 'x3'], [2, 4, 3], range(24))
phi2 = Factor(['x2', 'x1', 'x3'], [4, 2, 3], [0, 1, 2, 12, 13, 14, 3,
4, 5, 15, 16, 17, 6, 7,
8, 18, 19, 20, 9, 10, 11,
21, 22, 23])
self.assertTrue(phi1, phi2)
def test_maximize1(self):
self.phi1.maximize(['x1'])
self.assertEqual(self.phi1, Factor(['x2', 'x3'], [3, 2], [6, 7, 8, 9, 10, 11]))
self.phi1.maximize(['x2'])
self.assertEqual(self.phi1, Factor(['x3'], [2], [10, 11]))
def test_maximize2(self):
self.phi1.maximize(['x1', 'x2'])
self.assertEqual(self.phi1, Factor(['x3'], [2], [10, 11]))
def test_maximize3(self):
self.phi2 = Factor(['x1', 'x2', 'x3'], [3, 2, 2], [0.25, 0.35, 0.08, 0.16, 0.05, 0.07,
0.00, 0.00, 0.15, 0.21, 0.08, 0.18])
self.phi2.maximize(['x2'])
self.assertEqual(self.phi2, Factor(['x1', 'x3'], [3, 2], [0.25, 0.35, 0.05,
0.07, 0.15, 0.21]))
def test_maximize_shape(self):
values = ['A', 'D', 'F', 'H']
phi3_max = self.phi3.maximize(values, inplace=False)
# Previously a sorting error caused these to be different
np_test.assert_array_equal(phi3_max.values.shape, phi3_max.cardinality)
def test_maximize_scopeerror(self):
self.assertRaises(ValueError, self.phi.maximize, ['x10'])
def test_maximize_typeerror(self):
self.assertRaises(TypeError, self.phi.maximize, 'x1')
def tearDown(self):
del self.phi
del self.phi1
class TestFactorMethods(unittest.TestCase):
def setUp(self):
self.phi = Factor(['x1', 'x2', 'x3'], [2, 2, 2], np.random.uniform(5, 10, size=8))
self.phi1 = Factor(['x1', 'x2', 'x3'], [2, 3, 2], range(12))
def test_scope(self):
self.assertListEqual(self.phi.scope(), ['x1', 'x2', 'x3'])
self.assertListEqual(self.phi1.scope(), ['x1', 'x2', 'x3'])
def test_assignment(self):
self.assertListEqual(self.phi.assignment([0]), [[State('x1', 0), State('x2', 0), State('x3', 0)]])
self.assertListEqual(self.phi.assignment([4, 5, 6]), [[State('x1', 1), State('x2', 0), State('x3', 0)],
[State('x1', 1), State('x2', 0), State('x3', 1)],
[State('x1', 1), State('x2', 1), State('x3', 0)]])
self.assertListEqual(self.phi1.assignment(np.array([4, 5, 6])),
[[State('x1', 0), State('x2', 2), State('x3', 0)],
[State('x1', 0), State('x2', 2), State('x3', 1)],
[State('x1', 1), State('x2', 0), State('x3', 0)]])
def test_assignment_indexerror(self):
self.assertRaises(IndexError, self.phi.assignment, [10])
self.assertRaises(IndexError, self.phi.assignment, [1, 3, 10, 5])
self.assertRaises(IndexError, self.phi.assignment, np.array([1, 3, 10, 5]))
def test_get_cardinality(self):
self.assertEqual(self.phi.get_cardinality('x1'), 2)
self.assertEqual(self.phi.get_cardinality('x2'), 2)
self.assertEqual(self.phi.get_cardinality('x3'), 2)
def test_get_cardinality_scopeerror(self):
self.assertRaises(exceptions.ScopeError, self.phi.get_cardinality, 'x4')
def test_marginalize(self):
self.phi1.marginalize('x1')
np_test.assert_array_equal(self.phi1.values, np.array([6, 8, 10, 12, 14, 16]))
self.phi1.marginalize(['x2'])
np_test.assert_array_equal(self.phi1.values, np.array([30, 36]))
self.phi1.marginalize('x3')
np_test.assert_array_equal(self.phi1.values, np.array([66]))
def test_marginalize_scopeerror(self):
self.assertRaises(exceptions.ScopeError, self.phi.marginalize, 'x4')
self.assertRaises(exceptions.ScopeError, self.phi.marginalize, ['x4'])
self.phi.marginalize('x1')
self.assertRaises(exceptions.ScopeError, self.phi.marginalize, 'x1')
def test_normalize(self):
self.phi1.normalize()
np_test.assert_almost_equal(self.phi1.values, np.array(
[0, 0.01515152, 0.03030303, 0.04545455, 0.06060606,
0.07575758, 0.09090909, 0.10606061, 0.12121212,
0.13636364, 0.15151515, 0.16666667]))
def test_reduce(self):
self.phi1.reduce([('x1', 0), ('x2', 0)])
np_test.assert_array_equal(self.phi1.values, np.array([0, 1]))
def test_reduce1(self):
self.phi1.reduce([('x2', 0), ('x1', 0)])
np_test.assert_array_equal(self.phi1.values, np.array([0, 1]))
@unittest.skip
def test_complete_reduce(self):
self.phi1.reduce([('x1', 0), ('x2', 0), ('x3', 1)])
np_test.assert_array_equal(self.phi1.values, np.array([0]))
np_test.assert_array_equal(self.phi1.cardinality, np.array([]))
np_test.assert_array_equal(self.phi1.variables, OrderedDict())
def test_reduce_typeerror(self):
self.assertRaises(ValueError, self.phi1.reduce, 'x10')
self.assertRaises(ValueError, self.phi1.reduce, ['x10'])
def test_reduce_scopeerror(self):
self.assertRaises(ValueError, self.phi1.reduce, ('x4', 1))
def test_reduce_sizeerror(self):
self.assertRaises(IndexError, self.phi1.reduce, ('x3', 5))
def test_identity_factor(self):
identity_factor = self.phi.identity_factor()
self.assertEquals(list(identity_factor.variables), ['x1', 'x2', 'x3'])
np_test.assert_array_equal(identity_factor.cardinality, [2, 2, 2])
np_test.assert_array_equal(identity_factor.values, np.ones(8))
def test_factor_product(self):
phi = Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = Factor(['x3', 'x4'], [2, 2], range(4))
prod = factor_product(phi, phi1)
np_test.assert_array_equal(prod.values,
np.array([0, 0, 0, 0, 0, 1,
2, 3, 0, 2, 4, 6,
0, 3, 6, 9]))
self.assertEqual(prod.variables, OrderedDict([
('x1', [State('x1', 0), State('x1', 1)]),
('x2', [State('x2', 0), State('x2', 1)]),
('x3', [State('x3', 0), State('x3', 1)]),
('x4', [State('x4', 0), State('x4', 1)])]
))
phi = Factor(['x1', 'x2'], [3, 2], range(6))
phi1 = Factor(['x2', 'x3'], [2, 2], range(4))
prod = factor_product(phi, phi1)
np_test.assert_array_equal(prod.values,
np.array([0, 0, 2, 3, 0, 2, 6, 9, 0, 4, 10, 15]))
self.assertEqual(prod.variables, OrderedDict(
[('x1', [State('x1', 0), State('x1', 1), State('x1', 2)]),
('x2', [State('x2', 0), State('x2', 1)]),
('x3', [State('x3', 0), State('x3', 1)])]))
def test_factor_product2(self):
from pgmpy import factors
phi = factors.Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = factors.Factor(['x3', 'x4'], [2, 2], range(4))
prod = phi.product(phi1)
np_test.assert_array_equal(prod.values,
np.array([0, 0, 0, 0, 0, 1,
2, 3, 0, 2, 4, 6,
0, 3, 6, 9]))
self.assertEqual(prod.variables, OrderedDict([
('x1', [State('x1', 0), State('x1', 1)]),
('x2', [State('x2', 0), State('x2', 1)]),
('x3', [State('x3', 0), State('x3', 1)]),
('x4', [State('x4', 0), State('x4', 1)])]
))
phi = Factor(['x1', 'x2'], [3, 2], range(6))
phi1 = Factor(['x2', 'x3'], [2, 2], range(4))
prod = phi.product(phi1)
np_test.assert_array_equal(prod.values,
np.array([0, 0, 2, 3, 0, 2, 6, 9, 0, 4, 10, 15]))
self.assertEqual(prod.variables, OrderedDict(
[('x1', [State('x1', 0), State('x1', 1), State('x1', 2)]),
('x2', [State('x2', 0), State('x2', 1)]),
('x3', [State('x3', 0), State('x3', 1)])]))
def test_factor_product_non_factor_arg(self):
self.assertRaises(TypeError, factor_product, 1, 2)
def test_factor_mul(self):
phi = Factor(['x1', 'x2'], [2, 2], range(4))
phi1 = Factor(['x3', 'x4'], [2, 2], range(4))
prod = phi * phi1
np_test.assert_array_equal(prod.values,
np.array([0, 0, 0, 0, 0, 1,
2, 3, 0, 2, 4, 6,
0, 3, 6, 9]))
self.assertEqual(prod.variables, OrderedDict([
('x1', [State('x1', 0), State('x1', 1)]),
('x2', [State('x2', 0), State('x2', 1)]),
('x3', [State('x3', 0), State('x3', 1)]),
('x4', [State('x4', 0), State('x4', 1)])]
))
def test_factor_divide(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 2, 4])
phi2 = Factor(['x1'], [2], [1, 2])
div = phi1.divide(phi2)
phi3 = Factor(['x1', 'x2'], [2, 2], [1, 2, 1, 2])
self.assertEqual(phi3, div)
def test_factor_divide_truediv(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 2, 4])
phi2 = Factor(['x1'], [2], [1, 2])
div = phi1 / phi2
phi3 = Factor(['x1', 'x2'], [2, 2], [1, 2, 1, 2])
self.assertEqual(phi3, div)
# def test_factor_divide_dividebyzero(self):
# phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 3, 4])
# phi2 = Factor(['x1'], [2], [0, 2])
# self.assertRaises(FloatingPointError, factor_divide, phi1, phi2)
#
def test_factor_divide_invalidvalue(self):
phi1 = Factor(['x1', 'x2'], [3, 2], [0.5, 0.2, 0, 0, 0.3, 0.45])
phi2 = Factor(['x1'], [3], [0.8, 0, 0.6])
div = phi1.divide(phi2)
np_test.assert_array_equal(div.values, np.array([0.625, 0.25, 0, 0, 0.5, 0.75]))
def test_factor_divide_no_common_scope(self):
phi1 = Factor(['x1', 'x2'], [2, 2], [1, 2, 3, 4])
phi2 = Factor(['x3'], [2], [0, 2])
self.assertRaises(ValueError, factor_divide, phi1, phi2)
def test_factor_divide_non_factor_arg(self):
self.assertRaises(TypeError, factor_divide, 1, 1)
def test_eq(self):
self.assertFalse(self.phi == self.phi1)
self.assertTrue(self.phi == self.phi)
self.assertTrue(self.phi1 == self.phi1)
def test_eq1(self):
phi1 = Factor(['x1', 'x2', 'x3'], [2, 4, 3], range(24))
phi2 = Factor(['x2', 'x1', 'x3'], [4, 2, 3], [0, 1, 2, 12, 13, 14, 3,
4, 5, 15, 16, 17, 6, 7,
8, 18, 19, 20, 9, 10, 11,
21, 22, 23])
self.assertTrue(phi1, phi2)
def test_index_for_assignment(self):
for i, j in enumerate(itertools.product(*[range(2), range(3), range(2)])):
self.assertEqual(self.phi1._index_for_assignment(j), i)
def test_maximize1(self):
self.phi1.maximize('x1')
self.assertEqual(self.phi1, Factor(['x2', 'x3'], [3, 2], [6, 7, 8, 9, 10, 11]))
self.phi1.maximize('x2')
self.assertEqual(self.phi1, Factor(['x3'], [2], [10, 11]))
def test_maximize2(self):
self.phi1.maximize(['x1', 'x2'])
self.assertEqual(self.phi1, Factor(['x3'], [2], [10, 11]))
def test_maximize3(self):
self.phi2 = Factor(['x1', 'x2', 'x3'], [3, 2, 2], [0.25, 0.35, 0.08, 0.16, 0.05, 0.07,
0.00, 0.00, 0.15, 0.21, 0.08, 0.18])
self.phi2.maximize('x2')
self.assertEqual(self.phi2, Factor(['x1', 'x3'], [3, 2], [0.25, 0.35, 0.05,
0.07, 0.15, 0.21]))
def tearDown(self):
del self.phi
del self.phi1
