def bn_earthquake():
g = core.BayesNet()
g.add_variable('Earthquake', (0, 1))
g.add_variable('Burglar', (0, 1))
g.add_variable('Radio', (0, 1))
g.add_variable('Alarm', (0, 1))
g.add_variable('Phone', (0, 1))
g.add_cpt(None, 'Earthquake',
{0: 0.999,
1: 0.001})
g.add_cpt(None, 'Burglar',
{0: 0.999,
1: 0.001})
g.add_cpt(('Burglar', 'Earthquake'), 'Alarm',
{(0, 0, 0): 0.999,
(0, 0, 1): 0.001,
(1, 0, 0): 0.00999,
(1, 0, 1): 0.99001,
(0, 1, 0): 0.98901,
(0, 1, 1): 0.01099,
(1, 1, 0): 0.0098901,
(1, 1, 1): 0.9901099})
g.add_cpt('Alarm', 'Phone',
{(0, 1): 0,
(0, 0): 1,
(1, 0): 0.3,
(1, 1): 0.7})
g.add_cpt('Earthquake', 'Radio',
{(0, 1): 0,
(0, 0): 1,
(1, 0): 0.5,
(1, 1): 0.5})
return g
def bn_naive_bayes():
g = core.BayesNet()
g.add_variable('Coin', ('a', 'b', 'c'))
g.add_variable('X1', ('H', 'T'))
g.add_variable('X2', ('H', 'T'))
g.add_variable('X3', ('H', 'T'))
g.add_cpt(None, 'Coin', {'a': 1.0 / 3, 'b': 1.0 / 3, 'c': 1.0 / 3})
g.add_cpt('Coin', 'X1',
{('a', 'H'): 0.2,
('a', 'T'): 0.8,
('b', 'H'): 0.6,
('b', 'T'): 0.4,
('c', 'H'): 0.8,
('c', 'T'): 0.2})
g.add_cpt('Coin', 'X2',
{('a', 'H'): 0.2,
('a', 'T'): 0.8,
('b', 'H'): 0.6,
('b', 'T'): 0.4,
('c', 'H'): 0.8,
('c', 'T'): 0.2})
g.add_cpt('Coin', 'X3',
{('a', 'H'): 0.2,
('a', 'T'): 0.8,
('b', 'H'): 0.6,
('b', 'T'): 0.4,
('c', 'H'): 0.8,
('c', 'T'): 0.2})
return g
def bn_exam():
g = core.BayesNet()
g.add_variable('X1', ('0', '1'))
g.add_variable('X2', ('0', '1'))
g.add_variable('X3', ('0', '1'))
g.add_variable('X4', ('0', '1'))
g.add_variable('X5', ('0', '1'))
g.add_variable('X6', ('0', '1'))
g.add_variable('X7', ('0', '1'))
g.add_cpt(None, 'X1', {'0': 1. / 3, '1': 2. / 3})
g.add_cpt(
'X1', 'X2', {
('1', '1'): 3. / 4,
('1', '0'): 1. / 4,
('0', '1'): 1. / 4,
('0', '0'): 3. / 4
})
g.add_cpt(
'X1', 'X3', {
('1', '1'): 3. / 4,
('1', '0'): 1. / 4,
('0', '1'): 1. / 4,
('0', '0'): 3. / 4
})
g.add_cpt(
'X2', 'X4', {
('1', '1'): 3. / 4,
('1', '0'): 1. / 4,
('0', '1'): 1. / 4,
('0', '0'): 3. / 4
})
g.add_cpt(
'X2', 'X5', {
('1', '1'): 3. / 4,
('1', '0'): 1. / 4,
('0', '1'): 1. / 4,
('0', '0'): 3. / 4
})
g.add_cpt(
'X3', 'X6', {
('1', '1'): 3. / 4,
('1', '0'): 1. / 4,
('0', '1'): 1. / 4,
('0', '0'): 3. / 4
})
g.add_cpt(
'X3', 'X7', {
('1', '1'): 3. / 4,
('1', '0'): 1. / 4,
('0', '1'): 1. / 4,
('0', '0'): 3. / 4
})
return g
def bn_vstruct():
g = core.BayesNet()
g.add_variable('X', (0, 1))
g.add_variable('Y', (0, 1))
g.add_variable('Z', (0, 1))
g.add_cpt(None, 'X', {0: 0.001, 1: 0.999})
g.add_cpt(None, 'Y', {0: 0.001, 1: 0.999})
g.add_cpt(
('X', 'Y'), 'Z', {
(0, 0, 0): 0.99,
(0, 0, 1): 0.01,
(0, 1, 0): 0.99,
(0, 1, 1): 0.01,
(1, 0, 0): 0.99,
(1, 0, 1): 0.01,
(1, 1, 0): 0.001,
(1, 1, 1): 0.999
})
return g
def define_graph():
g = core.BayesNet()
g.add_nodes_from(['Earthquake', 'Burglar', 'Radio', 'Alarm', 'Phone'])
g.add_edges_from([('Earthquake', 'Radio'), ('Earthquake', 'Alarm'),
('Burglar', 'Alarm'), ('Alarm', 'Phone')])
return g
def bn_independent():
g = core.BayesNet()
g.add_nodes_from(['X', 'Z'])
return g
def bn_v_structure():
g = core.BayesNet()
g.add_nodes_from(['X', 'Y', 'Z'])
g.add_edges_from([('X', 'Z'), ('Y', 'Z')])
return g
def bn_naive_bayes():
g = core.BayesNet()
g.add_nodes_from(['X', 'Y', 'Z'])
g.add_edges_from([('X', 'Y'), ('X', 'Z')])
return g
def bn_chain():
g = core.BayesNet()
g.add_nodes_from(['X', 'Y', 'Z'])
g.add_edges_from([('X', 'Y'), ('Y', 'Z')])
return g
def bn_dependent():
g = core.BayesNet()
g.add_nodes_from(['X', 'Z'])
g.add_edge('X', 'Z')
return g
import matplotlib.pylab as plt
import core
import bprop
import sampling
# Create earthquake Bayesian network.
bn = core.BayesNet()
bn.add_variable('Earthquake', (0, 1))
bn.add_variable('Burglar', (0, 1))
bn.add_variable('Radio', (0, 1))
bn.add_variable('Alarm', (0, 1))
bn.add_variable('Phone', (0, 1))
bn.add_cpt(None, 'Earthquake',
{0: 0.999,
1: 0.001})
bn.add_cpt(None, 'Burglar',
{0: 0.999,
1: 0.001})
bn.add_cpt(('Burglar', 'Earthquake'), 'Alarm',
{(0, 0, 0): 0.999,
(0, 0, 1): 0.001,
(1, 0, 0): 0.00999,
(1, 0, 1): 0.99001,
(0, 1, 0): 0.98901,
(0, 1, 1): 0.01099,
(1, 1, 0): 0.0098901,
(1, 1, 1): 0.9901099})
bn.add_cpt('Alarm', 'Phone',
{(0, 1): 0,
(0, 0): 1,
