def test_cpd_init(self):
cpd = TabularCPD('grade', 3, [[0.1, 0.1, 0.1]])
self.assertEqual(cpd.variable, 'grade')
self.assertEqual(cpd.variable_card, 3)
self.assertEqual(list(cpd.variables), ['grade'])
np_test.assert_array_equal(cpd.cardinality, np.array([3]))
np_test.assert_array_almost_equal(cpd.values, np.array([0.1, 0.1, 0.1]))
cpd = TabularCPD('grade', 3, [[0.1, 0.1, 0.1, 0.1, 0.1, 0.1],
[0.1, 0.1, 0.1, 0.1, 0.1, 0.1],
[0.8, 0.8, 0.8, 0.8, 0.8, 0.8]],
evidence=['intel', 'diff'], evidence_card=[3, 2])
self.assertEqual(cpd.variable, 'grade')
self.assertEqual(cpd.variable_card, 3)
np_test.assert_array_equal(cpd.cardinality, np.array([3, 2, 3]))
self.assertListEqual(list(cpd.variables), ['grade', 'diff', 'intel'])
np_test.assert_array_equal(cpd.values, np.array([0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.1, 0.1, 0.1,
0.8, 0.8, 0.8, 0.8, 0.8, 0.8]).reshape(3, 2, 3))
cpd = TabularCPD('grade', 3, [[0.1, 0.1],
[0.1, 0.1],
[0.8, 0.8]],
evidence='evi1', evidence_card=2)
self.assertEqual(cpd.variable, 'grade')
self.assertEqual(cpd.variable_card, 3)
np_test.assert_array_equal(cpd.cardinality, np.array([3, 2]))
self.assertListEqual(list(cpd.variables), ['grade', 'evi1'])
np_test.assert_array_equal(cpd.values, np.array([0.1, 0.1,
0.1, 0.1,
0.8, 0.8]).reshape(3, 2))
def test__repr__(self):
grade_cpd = TabularCPD('grade', 3, [[0.1, 0.1, 0.1, 0.1, 0.1, 0.1],
[0.1, 0.1, 0.1, 0.1, 0.1, 0.1],
[0.8, 0.8, 0.8, 0.8, 0.8, 0.8]],
evidence=['intel', 'diff'], evidence_card=[3, 2])
intel_cpd = TabularCPD('intel', 3, [[0.5], [0.3], [0.2]])
diff_cpd = TabularCPD('grade', 3, [[0.1, 0.1], [0.1, 0.1], [0.8, 0.8]], evidence=['diff'], evidence_card=[2])
self.assertEqual(repr(grade_cpd), '<TabularCPD representing P(grade:3 | intel:3, diff:2) at {address}>'
.format(address=hex(id(grade_cpd))))
self.assertEqual(repr(intel_cpd), '<TabularCPD representing P(intel:3) at {address}>'
.format(address=hex(id(intel_cpd))))
self.assertEqual(repr(diff_cpd), '<TabularCPD representing P(grade:3 | diff:2) at {address}>'
.format(address=hex(id(diff_cpd))))
def setUp(self):
self.cpd = TabularCPD(
'grade',
3, [[0.1, 0.1, 0.1, 0.1, 0.1, 0.1], [0.1, 0.1, 0.1, 0.1, 0.1, 0.1],
[0.8, 0.8, 0.8, 0.8, 0.8, 0.8]],
evidence=['intel', 'diff'],
evidence_card=[3, 2])
def test_normalize(self):
cpd_un_normalized = TabularCPD(
'grade', 2, [[0.7, 0.2, 0.6, 0.2], [0.4, 0.4, 0.4, 0.8]],
['intel', 'diff'], [2, 2])
cpd_un_normalized.normalize()
np_test.assert_array_almost_equal(
cpd_un_normalized.values,
np.array([
0.63636364, 0.33333333, 0.6, 0.2, 0.36363636, 0.66666667, 0.4,
0.8
]))
