def test_ep_tight(self):
theta = DirichletParameterNode(
'theta',
Factor(['X', 'ZDummy'], {
'X': ['same', 'diff'],
'ZDummy': ['dummy']
}, {
('same', 'dummy'): 1,
('diff', 'dummy'): 1,
},
logarithmetic=False))
X = DiscreteVariableNode('X', ['same', 'diff'], logarithmetic=False)
D = DiscreteVariableNode('ZDummy', ['dummy'], logarithmetic=False)
f = DirichletFactorNode('f')
X.observed({('same', ): 0.50001, ('diff', ): 0.49999})
f.connect(theta)
f.connect(X, parent=False)
f.connect(D)
# Add nodes to lbp.
lbp = LBP(strategy='tree')
lbp.add_nodes([f, X, D, theta])
for i in range(50):
lbp.run()
#print theta.alpha.pretty_print(precision=5)
lbp.init_messages()
print theta.alpha.pretty_print(precision=5)
def test_ep_tight(self):
theta = DirichletParameterNode('theta', Factor(
['X', 'ZDummy'],
{
'X': ['same', 'diff'],
'ZDummy': ['dummy']
},
{
('same', 'dummy'): 1,
('diff', 'dummy'): 1,
}, logarithmetic=False))
X = DiscreteVariableNode('X', ['same', 'diff'], logarithmetic=False)
D = DiscreteVariableNode('ZDummy', ['dummy'], logarithmetic=False)
f = DirichletFactorNode('f')
X.observed({('same',): 0.50001, ('diff',): 0.49999})
f.connect(theta)
f.connect(X, parent=False)
f.connect(D)
# Add nodes to lbp.
lbp = LBP(strategy='tree')
lbp.add_nodes([
f, X, D, theta
])
for i in range(50):
lbp.run()
#print theta.alpha.pretty_print(precision=5)
lbp.init_messages()
def test_single_linked(self):
f_h_o = {
("save", "osave"): 0.8,
("del", "osave"): 0.2,
("save", "odel"): 0.2,
("del", "odel"): 0.8,
}
f_h_h = {
("save", "save"): 0.9,
("del", "save"): 0.1,
("save", "del"): 0.1,
("del", "del"): 0.9
}
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DiscreteFactorNode("fact_h1_o1", Factor(
['hid1', 'obs1'],
{
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
},
f_h_o))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DiscreteFactorNode("fact_h2_o2", Factor(
['hid2', 'obs2'],
{
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
},
f_h_o))
fact_h1_h2 = DiscreteFactorNode("fact_h1_h2", Factor(
['hid1', 'hid2'],
{
"hid1": ["save", "del"],
"hid2": ["save", "del"],
},
f_h_h))
hid3 = DiscreteVariableNode("hid3", ["save", "del"])
obs3 = DiscreteVariableNode("obs3", ["osave", "odel"])
fact_h3_o3 = DiscreteFactorNode("fact_h3_o3", Factor(
['hid3', 'obs3'],
{
"hid3": ["save", "del"],
"obs3": ["osave", "odel"]
},
f_h_o))
fact_h2_h3 = DiscreteFactorNode("fact_h2_h3", Factor(
['hid2', 'hid3'],
{
"hid2": ["save", "del"],
"hid3": ["save", "del"],
},
f_h_h))
# Connect nodes.
obs1.connect(fact_h1_o1)
obs2.connect(fact_h2_o2)
obs3.connect(fact_h3_o3)
fact_h1_o1.connect(hid1)
fact_h2_o2.connect(hid2)
fact_h3_o3.connect(hid3)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
hid2.connect(fact_h2_h3)
hid3.connect(fact_h2_h3)
# Add nodes to lbp.
lbp = LBP(strategy='tree')
lbp.add_nodes([
obs1, obs2, obs3,
fact_h1_o1, fact_h2_o2, fact_h3_o3,
hid1, hid2, hid3,
fact_h1_h2, fact_h2_h3
])
obs1.observed({('osave',): 1})
lbp.run()
self.assertAlmostEqual(hid1.belief[('save',)], 0.8)
self.assertAlmostEqual(hid2.belief[('save',)], 0.8 * 0.9 + 0.2 * 0.1, places=6)
self.assertAlmostEqual(hid3.belief[('save',)],
hid2.belief[('save',)] * 0.9 + hid2.belief[('del',)] * 0.1,
places=6)
def test_ep(self):
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DirichletFactorNode("fact_h1_o1")
theta_h1_o1 = DirichletParameterNode('theta_h1_o1', Factor(
['hid1', 'obs1'],
{
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
},
{
("save", "osave"): 1,
("save", "odel"): 1,
("del", "osave"): 1,
("del", "odel"): 1,
}))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DirichletFactorNode("fact_h2_o2")
theta_h2_o2 = DirichletParameterNode('theta_h2_o2', Factor(
['hid2', 'obs2'],
{
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
},
{
("save", "osave"): 1,
("save", "odel"): 1,
("del", "osave"): 1,
("del", "odel"): 1,
}))
fact_h1_h2 = DiscreteFactorNode("fact_h1_h2", Factor(
['hid1', 'hid2'],
{
"hid1": ["save", "del"],
"hid2": ["save", "del"],
},
{
("save", "save"): 0.9,
("save", "del"): 0.1,
("del", "save"): 0,
("del", "del"): 1
}))
# Connect nodes.
obs1.connect(fact_h1_o1, parent=False)
fact_h1_o1.connect(hid1)
fact_h1_o1.connect(theta_h1_o1)
obs2.connect(fact_h2_o2, parent=False)
fact_h2_o2.connect(hid2)
fact_h2_o2.connect(theta_h2_o2)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
# Add nodes to lbp.
lbp = LBP(strategy='tree')
lbp.add_nodes([
obs1, obs2,
fact_h1_o1, fact_h2_o2,
theta_h1_o1, theta_h2_o2,
hid1, hid2,
fact_h1_h2
])
obs1.observed({('osave',): 1})
obs2.observed({('osave',): 1})
hid1.observed({('save',): 1})
hid2.observed({('save',): 1})
for i in range(100):
lbp.run()
#print theta_h1_o1.alpha.pretty_print(precision=5)
lbp.init_messages()
def test_layers(self):
f_h_o = {
("save", "osave"): 0.8,
("del", "osave"): 0.2,
("save", "odel"): 0.2,
("del", "odel"): 0.8,
}
f_h_h = {
("save", "save"): 0.9,
("del", "save"): 0.1,
("save", "del"): 0.1,
("del", "del"): 0.9
}
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DiscreteFactorNode("fact_h1_o1", Factor(
['hid1', 'obs1'],
{
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
},
f_h_o))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DiscreteFactorNode("fact_h2_o2", Factor(
['hid2', 'obs2'],
{
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
},
f_h_o))
fact_h1_h2 = DiscreteFactorNode("fact_h1_h2", Factor(
['hid1', 'hid2'],
{
"hid1": ["save", "del"],
"hid2": ["save", "del"],
},
f_h_h))
hid3 = DiscreteVariableNode("hid3", ["save", "del"])
obs3 = DiscreteVariableNode("obs3", ["osave", "odel"])
fact_h3_o3 = DiscreteFactorNode("fact_h3_o3", Factor(
['hid3', 'obs3'],
{
"hid3": ["save", "del"],
"obs3": ["osave", "odel"]
},
f_h_o))
fact_h2_h3 = DiscreteFactorNode("fact_h2_h3", Factor(
['hid2', 'hid3'],
{
"hid2": ["save", "del"],
"hid3": ["save", "del"],
},
f_h_h))
# Connect nodes.
obs1.connect(fact_h1_o1)
obs2.connect(fact_h2_o2)
obs3.connect(fact_h3_o3)
fact_h1_o1.connect(hid1)
fact_h2_o2.connect(hid2)
fact_h3_o3.connect(hid3)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
hid2.connect(fact_h2_h3)
hid3.connect(fact_h2_h3)
# Set observations.
obs1.observed({('osave',): 1})
# Add nodes to lbp.
lbp = LBP(strategy='layers')
lbp.add_layers([
[obs1, hid1, fact_h1_o1],
[obs2, hid2, fact_h2_o2, fact_h1_h2],
[obs3, hid3, fact_h3_o3, fact_h2_h3],
])
lbp.run()
self.assertAlmostEqual(hid1.belief[('save',)], 0.8)
self.assertAlmostEqual(hid2.belief[('save',)], 0.8 * 0.9 + 0.2 * 0.1, places=6)
# @DM: The original test that fails at my computer.
# self.assertAlmostEqual(hid3.belief[('save',)], hid2.belief[('save',)] * 0.9 + hid2.belief[('del',)] * 0.1)
# MK: This one passes.
self.assertAlmostEqual(
hid3.belief[('save',)],
hid2.belief[('save',)] * 0.9 + hid2.belief[('del',)] * 0.1,
places=6)
lbp = LBP(strategy='layers')
lbp.add_layers([
[obs1, hid1, fact_h1_o1]
])
lbp.run()
self.assertAlmostEqual(hid1.belief[('save',)], 0.8)
lbp.add_layer([obs2, hid2, fact_h2_o2, fact_h1_h2])
lbp.run(from_layer=0)
self.assertAlmostEqual(hid2.belief[('save',)], 0.8 * 0.9 + 0.2 * 0.1, places=6)
lbp.add_layers([
[obs3, hid3, fact_h3_o3, fact_h2_h3]
])
lbp.run(from_layer='last')
self.assertAlmostEqual(hid3.belief[('save',)], hid2.belief[('save',)] * 0.9 + hid2.belief[('del',)] * 0.1)
def test_network(self):
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DiscreteFactorNode("fact_h1_o1", Factor(
['hid1', 'obs1'],
{
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
},
{
("save", "osave"): 0.8,
("save", "odel"): 0.3,
("del", "osave"): 0.2,
("del", "odel"): 0.7,
}))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DiscreteFactorNode("fact_h2_o2", Factor(
['hid2', 'obs2'],
{
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
},
{
("save", "osave"): 0.8,
("save", "odel"): 0.2,
("del", "osave"): 0.2,
("del", "odel"): 0.8,
}))
fact_h1_h2 = DiscreteFactorNode("fact_h1_h2", Factor(
['hid1', 'hid2'],
{
"hid1": ["save", "del"],
"hid2": ["save", "del"],
},
{
("save", "save"): 0.9,
("save", "del"): 0.1,
("del", "save"): 0,
("del", "del"): 1
}))
# Connect nodes.
obs1.connect(fact_h1_o1)
fact_h1_o1.connect(hid1)
obs2.connect(fact_h2_o2)
fact_h2_o2.connect(hid2)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
# Add nodes to lbp.
lbp = LBP()
lbp.add_nodes([
obs1, fact_h1_o1, hid1,
obs2, fact_h2_o2, hid2,
fact_h1_h2
])
obs1.observed({('osave',): 1})
lbp.run(n_iterations=1)
self.assertAlmostEqual(hid1.belief[('save',)], 0.8)
obs2.observed({('odel',): 1})
lbp.run(n_iterations=1)
self.assertAlmostEqual(hid1.belief[('save',)], 0.56521738)
def test_single_linked(self):
f_h_o = {
("save", "osave"): 0.8,
("del", "osave"): 0.2,
("save", "odel"): 0.2,
("del", "odel"): 0.8,
}
f_h_h = {
("save", "save"): 0.9,
("del", "save"): 0.1,
("save", "del"): 0.1,
("del", "del"): 0.9
}
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DiscreteFactorNode(
"fact_h1_o1",
Factor(['hid1', 'obs1'], {
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
}, f_h_o))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DiscreteFactorNode(
"fact_h2_o2",
Factor(['hid2', 'obs2'], {
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
}, f_h_o))
fact_h1_h2 = DiscreteFactorNode(
"fact_h1_h2",
Factor(['hid1', 'hid2'], {
"hid1": ["save", "del"],
"hid2": ["save", "del"],
}, f_h_h))
hid3 = DiscreteVariableNode("hid3", ["save", "del"])
obs3 = DiscreteVariableNode("obs3", ["osave", "odel"])
fact_h3_o3 = DiscreteFactorNode(
"fact_h3_o3",
Factor(['hid3', 'obs3'], {
"hid3": ["save", "del"],
"obs3": ["osave", "odel"]
}, f_h_o))
fact_h2_h3 = DiscreteFactorNode(
"fact_h2_h3",
Factor(['hid2', 'hid3'], {
"hid2": ["save", "del"],
"hid3": ["save", "del"],
}, f_h_h))
# Connect nodes.
obs1.connect(fact_h1_o1)
obs2.connect(fact_h2_o2)
obs3.connect(fact_h3_o3)
fact_h1_o1.connect(hid1)
fact_h2_o2.connect(hid2)
fact_h3_o3.connect(hid3)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
hid2.connect(fact_h2_h3)
hid3.connect(fact_h2_h3)
# Add nodes to lbp.
lbp = LBP(strategy='tree')
lbp.add_nodes([
obs1, obs2, obs3, fact_h1_o1, fact_h2_o2, fact_h3_o3, hid1, hid2,
hid3, fact_h1_h2, fact_h2_h3
])
obs1.observed({('osave', ): 1})
lbp.run()
self.assertAlmostEqual(hid1.belief[('save', )], 0.8)
self.assertAlmostEqual(hid2.belief[('save', )],
0.8 * 0.9 + 0.2 * 0.1,
places=6)
self.assertAlmostEqual(hid3.belief[('save', )],
hid2.belief[('save', )] * 0.9 +
hid2.belief[('del', )] * 0.1,
places=6)
def test_ep(self):
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DirichletFactorNode("fact_h1_o1")
theta_h1_o1 = DirichletParameterNode(
'theta_h1_o1',
Factor(['hid1', 'obs1'], {
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
}, {
("save", "osave"): 1,
("save", "odel"): 1,
("del", "osave"): 1,
("del", "odel"): 1,
}))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DirichletFactorNode("fact_h2_o2")
theta_h2_o2 = DirichletParameterNode(
'theta_h2_o2',
Factor(['hid2', 'obs2'], {
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
}, {
("save", "osave"): 1,
("save", "odel"): 1,
("del", "osave"): 1,
("del", "odel"): 1,
}))
fact_h1_h2 = DiscreteFactorNode(
"fact_h1_h2",
Factor(['hid1', 'hid2'], {
"hid1": ["save", "del"],
"hid2": ["save", "del"],
}, {
("save", "save"): 0.9,
("save", "del"): 0.1,
("del", "save"): 0,
("del", "del"): 1
}))
# Connect nodes.
obs1.connect(fact_h1_o1, parent=False)
fact_h1_o1.connect(hid1)
fact_h1_o1.connect(theta_h1_o1)
obs2.connect(fact_h2_o2, parent=False)
fact_h2_o2.connect(hid2)
fact_h2_o2.connect(theta_h2_o2)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
# Add nodes to lbp.
lbp = LBP(strategy='tree')
lbp.add_nodes([
obs1, obs2, fact_h1_o1, fact_h2_o2, theta_h1_o1, theta_h2_o2, hid1,
hid2, fact_h1_h2
])
obs1.observed({('osave', ): 1})
obs2.observed({('osave', ): 1})
hid1.observed({('save', ): 1})
hid2.observed({('save', ): 1})
for i in range(100):
lbp.run()
print theta_h1_o1.alpha.pretty_print(precision=5)
lbp.init_messages()
def test_layers(self):
f_h_o = {
("save", "osave"): 0.8,
("del", "osave"): 0.2,
("save", "odel"): 0.2,
("del", "odel"): 0.8,
}
f_h_h = {
("save", "save"): 0.9,
("del", "save"): 0.1,
("save", "del"): 0.1,
("del", "del"): 0.9
}
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DiscreteFactorNode(
"fact_h1_o1",
Factor(['hid1', 'obs1'], {
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
}, f_h_o))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DiscreteFactorNode(
"fact_h2_o2",
Factor(['hid2', 'obs2'], {
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
}, f_h_o))
fact_h1_h2 = DiscreteFactorNode(
"fact_h1_h2",
Factor(['hid1', 'hid2'], {
"hid1": ["save", "del"],
"hid2": ["save", "del"],
}, f_h_h))
hid3 = DiscreteVariableNode("hid3", ["save", "del"])
obs3 = DiscreteVariableNode("obs3", ["osave", "odel"])
fact_h3_o3 = DiscreteFactorNode(
"fact_h3_o3",
Factor(['hid3', 'obs3'], {
"hid3": ["save", "del"],
"obs3": ["osave", "odel"]
}, f_h_o))
fact_h2_h3 = DiscreteFactorNode(
"fact_h2_h3",
Factor(['hid2', 'hid3'], {
"hid2": ["save", "del"],
"hid3": ["save", "del"],
}, f_h_h))
# Connect nodes.
obs1.connect(fact_h1_o1)
obs2.connect(fact_h2_o2)
obs3.connect(fact_h3_o3)
fact_h1_o1.connect(hid1)
fact_h2_o2.connect(hid2)
fact_h3_o3.connect(hid3)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
hid2.connect(fact_h2_h3)
hid3.connect(fact_h2_h3)
# Set observations.
obs1.observed({('osave', ): 1})
# Add nodes to lbp.
lbp = LBP(strategy='layers')
lbp.add_layers([
[obs1, hid1, fact_h1_o1],
[obs2, hid2, fact_h2_o2, fact_h1_h2],
[obs3, hid3, fact_h3_o3, fact_h2_h3],
])
lbp.run()
self.assertAlmostEqual(hid1.belief[('save', )], 0.8)
self.assertAlmostEqual(hid2.belief[('save', )],
0.8 * 0.9 + 0.2 * 0.1,
places=6)
# @DM: The original test that fails at my computer.
# self.assertAlmostEqual(hid3.belief[('save',)], hid2.belief[('save',)] * 0.9 + hid2.belief[('del',)] * 0.1)
# MK: This one passes.
self.assertAlmostEqual(hid3.belief[('save', )],
hid2.belief[('save', )] * 0.9 +
hid2.belief[('del', )] * 0.1,
places=6)
lbp = LBP(strategy='layers')
lbp.add_layers([[obs1, hid1, fact_h1_o1]])
lbp.run()
self.assertAlmostEqual(hid1.belief[('save', )], 0.8)
lbp.add_layer([obs2, hid2, fact_h2_o2, fact_h1_h2])
lbp.run(from_layer=0)
self.assertAlmostEqual(hid2.belief[('save', )],
0.8 * 0.9 + 0.2 * 0.1,
places=6)
lbp.add_layers([[obs3, hid3, fact_h3_o3, fact_h2_h3]])
lbp.run(from_layer='last')
self.assertAlmostEqual(
hid3.belief[('save', )],
hid2.belief[('save', )] * 0.9 + hid2.belief[('del', )] * 0.1)
def test_network(self):
# Create nodes.
hid1 = DiscreteVariableNode("hid1", ["save", "del"])
obs1 = DiscreteVariableNode("obs1", ["osave", "odel"])
fact_h1_o1 = DiscreteFactorNode(
"fact_h1_o1",
Factor(['hid1', 'obs1'], {
"hid1": ["save", "del"],
"obs1": ["osave", "odel"]
}, {
("save", "osave"): 0.8,
("save", "odel"): 0.3,
("del", "osave"): 0.2,
("del", "odel"): 0.7,
}))
hid2 = DiscreteVariableNode("hid2", ["save", "del"])
obs2 = DiscreteVariableNode("obs2", ["osave", "odel"])
fact_h2_o2 = DiscreteFactorNode(
"fact_h2_o2",
Factor(['hid2', 'obs2'], {
"hid2": ["save", "del"],
"obs2": ["osave", "odel"]
}, {
("save", "osave"): 0.8,
("save", "odel"): 0.2,
("del", "osave"): 0.2,
("del", "odel"): 0.8,
}))
fact_h1_h2 = DiscreteFactorNode(
"fact_h1_h2",
Factor(['hid1', 'hid2'], {
"hid1": ["save", "del"],
"hid2": ["save", "del"],
}, {
("save", "save"): 0.9,
("save", "del"): 0.1,
("del", "save"): 0,
("del", "del"): 1
}))
# Connect nodes.
obs1.connect(fact_h1_o1)
fact_h1_o1.connect(hid1)
obs2.connect(fact_h2_o2)
fact_h2_o2.connect(hid2)
hid1.connect(fact_h1_h2)
hid2.connect(fact_h1_h2)
# Add nodes to lbp.
lbp = LBP()
lbp.add_nodes(
[obs1, fact_h1_o1, hid1, obs2, fact_h2_o2, hid2, fact_h1_h2])
obs1.observed({('osave', ): 1})
lbp.run(n_iterations=1)
self.assertAlmostEqual(hid1.belief[('save', )], 0.8)
obs2.observed({('odel', ): 1})
lbp.run(n_iterations=1)
self.assertAlmostEqual(hid1.belief[('save', )], 0.56521738)
