def test_potential_initializer():
"""
Tests potential initialization.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
def test_potential_initializer():
"""
Tests potential initialization.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
e_potentials = {
'0=on': 0.50000,
'0=off': 0.50000,
'0=on,1=on': 0.50000,
'0=on,1=off': 0.50000,
'0=off,1=on': 0.40000,
'0=off,1=off': 0.60000,
'0=on,2=on': 0.70000,
'0=on,2=off': 0.30000,
'0=off,2=on': 0.20000,
'0=off,2=off': 0.80000,
'1=on,3=on': 0.90000,
'1=on,3=off': 0.10000,
'1=off,3=on': 0.50000,
'1=off,3=off': 0.50000,
'2=on,4=on': 0.30000,
'2=on,4=off': 0.70000,
'2=off,4=on': 0.60000,
'2=off,4=off': 0.40000,
'3=on,4=on,5=on': 0.01000,
'3=on,4=on,5=off': 0.99000,
'3=on,4=off,5=on': 0.01000,
'3=on,4=off,5=off': 0.99000,
'3=off,4=on,5=on': 0.01000,
'3=off,4=on,5=off': 0.99000,
'3=off,4=off,5=on': 0.99000,
'3=off,4=off,5=off': 0.01000,
'2=on,6=on': 0.80000,
'2=on,6=off': 0.20000,
'2=off,6=on': 0.10000,
'2=off,6=off': 0.90000,
'4=on,6=on,7=on': 0.05000,
'4=on,6=on,7=off': 0.95000,
'4=on,6=off,7=on': 0.95000,
'4=on,6=off,7=off': 0.05000,
'4=off,6=on,7=on': 0.95000,
'4=off,6=on,7=off': 0.05000,
'4=off,6=off,7=on': 0.95000,
'4=off,6=off,7=off': 0.05000
}
o_potentials = '\n'.join([str(node.potential) for node in bbn.get_nodes()]).split('\n')
o_potentials = [p.split('|') for p in o_potentials]
o_potentials = {tokens[0]: float(tokens[1]) for tokens in o_potentials}
assert len(e_potentials) == len(o_potentials)
for k, lhs in o_potentials.items():
assert k in e_potentials
rhs = e_potentials[k]
assert lhs == rhs
def test_transformer():
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
join_tree = Transformer.transform(cliques)
def test_moralizer():
"""
Tests moralization.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
def test_triangulator():
"""
Tests triangulation.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
def test_potential_initializer():
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
# assert later
# for node in bbn.get_nodes():
# potential = node.potential
# print('{} {}'.format(node.id, node.variable.name))
# print(potential)
#
# assert 1 == 2
def test_moralizer():
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
# assert later
# for node in ug.get_nodes():
# print(node)
# for edge in ug.get_edges():
# print(edge)
#
# assert 1 == 2
def test_initializer():
"""
Tests initialization.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
join_tree = Transformer.transform(cliques)
Initializer.initialize(join_tree)
def apply_from_serde(join_tree):
"""
Applies propagation to join tree from a deserialzed join tree.
:param join_tree: Join tree.
:return: Join tree (the same one passed in).
"""
join_tree.listener = None
join_tree.evidences = dict()
PotentialInitializer.reinit(join_tree)
Initializer.initialize(join_tree)
Propagator.propagate(join_tree)
join_tree.set_listener(InferenceController())
return join_tree
def apply(bbn):
"""
Sets up the specified BBN for probability propagation in tree clusters (PPTC).
:param bbn: BBN graph.
:return: Join tree.
"""
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
join_tree = Transformer.transform(cliques)
Initializer.initialize(join_tree)
Propagator.propagate(join_tree)
join_tree.set_listener(InferenceController())
return join_tree
def test_triangulator():
"""
Tests triangulation.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
e_cliques = set(
['(d,e,f)', '(e,g,h)', '(c,e,g)', '(a,b,c)', '(b,c,d)', '(c,d,e)'])
o_cliques = [str(c) for c in cliques]
assert len(e_cliques) == len(o_cliques)
for c in e_cliques:
assert c in o_cliques
def test_moralizer():
"""
Tests moralization.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
e_edges = set([
'0--1', '0--2', '1--3', '2--4', '3--5', '4--5', '2--6', '4--7', '6--7',
'3--4', '4--6'
])
o_edges = set([str(edge) for edge in ug.get_edges()])
assert len(e_edges) == len(o_edges)
for e in e_edges:
assert e in o_edges
def reapply(join_tree, cpts):
"""
Reapply propagation to join tree with new CPTs. The join tree structure is kept but the BBN node CPTs
are updated. A new instance/copy of the join tree will be returned.
:param join_tree: Join tree.
:param cpts: Dictionary of new CPTs. Keys are id's of nodes and values are new CPTs.
:return: Join tree.
"""
jt = copy.deepcopy(join_tree)
jt.update_bbn_cpts(cpts)
jt.listener = None
jt.evidences = dict()
PotentialInitializer.reinit(jt)
Initializer.initialize(jt)
Propagator.propagate(jt)
jt.set_listener(InferenceController())
return jt
def test_transformer():
"""
Tests transformer.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
join_tree = Transformer.transform(cliques)
e_nodes = set([
'(d,e,f)', '(e,g,h)', '(c,e,g)', '(a,b,c)', '(b,c,d)', '(c,d,e)',
'|(a,b,c) -- b,c -- (b,c,d)|', '|(b,c,d) -- c,d -- (c,d,e)|',
'|(c,e,g) -- c,e -- (c,d,e)|', '|(d,e,f) -- d,e -- (c,d,e)|',
'|(e,g,h) -- e,g -- (c,e,g)|'
])
e_edges = set([
'(a,b,c)--|(a,b,c) -- b,c -- (b,c,d)|--(b,c,d)',
'(b,c,d)--|(b,c,d) -- c,d -- (c,d,e)|--(c,d,e)',
'(c,e,g)--|(c,e,g) -- c,e -- (c,d,e)|--(c,d,e)',
'(d,e,f)--|(d,e,f) -- d,e -- (c,d,e)|--(c,d,e)',
'(e,g,h)--|(e,g,h) -- e,g -- (c,e,g)|--(c,e,g)'
])
o_nodes = [str(n) for n in join_tree.get_nodes()]
o_edges = [str(e) for e in join_tree.get_edges()]
assert len(e_nodes) == len(o_nodes)
for n in e_nodes:
assert n in o_nodes
assert len(e_edges) == len(o_edges)
for e in e_edges:
assert e in o_edges
def test_initializer():
"""
Tests initialization.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
join_tree = Transformer.transform(cliques)
Initializer.initialize(join_tree)
e_potentials = {
'3=on,4=on,5=on': 0.01000,
'3=on,4=on,5=off': 0.99000,
'3=on,4=off,5=on': 0.01000,
'3=on,4=off,5=off': 0.99000,
'3=off,4=on,5=on': 0.01000,
'3=off,4=on,5=off': 0.99000,
'3=off,4=off,5=on': 0.99000,
'3=off,4=off,5=off': 0.01000,
'4=on,6=on,7=on': 0.05000,
'4=on,6=on,7=off': 0.95000,
'4=on,6=off,7=on': 0.95000,
'4=on,6=off,7=off': 0.05000,
'4=off,6=on,7=on': 0.95000,
'4=off,6=on,7=off': 0.05000,
'4=off,6=off,7=on': 0.95000,
'4=off,6=off,7=off': 0.05000,
'2=on,4=on,6=on': 0.80000,
'2=on,4=on,6=off': 0.20000,
'2=on,4=off,6=on': 0.80000,
'2=on,4=off,6=off': 0.20000,
'2=off,4=on,6=on': 0.10000,
'2=off,4=on,6=off': 0.90000,
'2=off,4=off,6=on': 0.10000,
'2=off,4=off,6=off': 0.90000,
'0=on,1=on,2=on': 0.17500,
'0=off,1=on,2=on': 0.04000,
'0=on,1=on,2=off': 0.07500,
'0=off,1=on,2=off': 0.16000,
'0=on,1=off,2=on': 0.17500,
'0=off,1=off,2=on': 0.06000,
'0=on,1=off,2=off': 0.07500,
'0=off,1=off,2=off': 0.24000,
'1=on,2=on,3=on': 0.90000,
'1=off,2=on,3=on': 0.50000,
'1=on,2=on,3=off': 0.10000,
'1=off,2=on,3=off': 0.50000,
'1=on,2=off,3=on': 0.90000,
'1=off,2=off,3=on': 0.50000,
'1=on,2=off,3=off': 0.10000,
'1=off,2=off,3=off': 0.50000,
'2=on,3=on,4=on': 0.30000,
'2=off,3=on,4=on': 0.60000,
'2=on,3=on,4=off': 0.70000,
'2=off,3=on,4=off': 0.40000,
'2=on,3=off,4=on': 0.30000,
'2=off,3=off,4=on': 0.60000,
'2=on,3=off,4=off': 0.70000,
'2=off,3=off,4=off': 0.40000,
'1=on,2=on': 1.00000,
'1=on,2=off': 1.00000,
'1=off,2=on': 1.00000,
'1=off,2=off': 1.00000,
'2=on,3=on': 1.00000,
'2=on,3=off': 1.00000,
'2=off,3=on': 1.00000,
'2=off,3=off': 1.00000,
'2=on,4=on': 1.00000,
'2=on,4=off': 1.00000,
'2=off,4=on': 1.00000,
'2=off,4=off': 1.00000,
'3=on,4=on': 1.00000,
'3=on,4=off': 1.00000,
'3=off,4=on': 1.00000,
'3=off,4=off': 1.00000,
'4=on,6=on': 1.00000,
'4=on,6=off': 1.00000,
'4=off,6=on': 1.00000,
'4=off,6=off': 1.00000
}
o_potentials = '\n'.join([str(v) for _, v in join_tree.potentials.items()]).split('\n')
o_potentials = [p.split('|') for p in o_potentials]
o_potentials = {tokens[0]: float(tokens[1]) for tokens in o_potentials}
assert len(e_potentials) == len(o_potentials)
for k, lhs in o_potentials.items():
assert k in e_potentials
rhs = e_potentials[k]
assert lhs == rhs
def test_propagator():
"""
Tests propagation.
:return: None.
"""
bbn = BbnUtil.get_huang_graph()
PotentialInitializer.init(bbn)
ug = Moralizer.moralize(bbn)
cliques = Triangulator.triangulate(ug)
join_tree = Transformer.transform(cliques)
Initializer.initialize(join_tree)
Propagator.propagate(join_tree)
e_potentials = {
'3=on,4=on,5=on': 0.00315,
'3=on,4=on,5=off': 0.31155,
'3=on,4=off,5=on': 0.00365,
'3=on,4=off,5=off': 0.36165,
'3=off,4=on,5=on': 0.00150,
'3=off,4=on,5=off': 0.14880,
'3=off,4=off,5=on': 0.16800,
'3=off,4=off,5=off': 0.00170,
'4=on,6=on,7=on': 0.00705,
'4=on,6=on,7=off': 0.13395,
'4=on,6=off,7=on': 0.30780,
'4=on,6=off,7=off': 0.01620,
'4=off,6=on,7=on': 0.26030,
'4=off,6=on,7=off': 0.01370,
'4=off,6=off,7=on': 0.24795,
'4=off,6=off,7=off': 0.01305,
'2=on,4=on,6=on': 0.10800,
'2=on,4=on,6=off': 0.02700,
'2=on,4=off,6=on': 0.25200,
'2=on,4=off,6=off': 0.06300,
'2=off,4=on,6=on': 0.03300,
'2=off,4=on,6=off': 0.29700,
'2=off,4=off,6=on': 0.02200,
'2=off,4=off,6=off': 0.19800,
'0=on,1=on,2=on': 0.17500,
'0=off,1=on,2=on': 0.04000,
'0=on,1=on,2=off': 0.07500,
'0=off,1=on,2=off': 0.16000,
'0=on,1=off,2=on': 0.17500,
'0=off,1=off,2=on': 0.06000,
'0=on,1=off,2=off': 0.07500,
'0=off,1=off,2=off': 0.24000,
'1=on,2=on,3=on': 0.19350,
'1=off,2=on,3=on': 0.11750,
'1=on,2=on,3=off': 0.02150,
'1=off,2=on,3=off': 0.11750,
'1=on,2=off,3=on': 0.21150,
'1=off,2=off,3=on': 0.15750,
'1=on,2=off,3=off': 0.02350,
'1=off,2=off,3=off': 0.15750,
'2=on,3=on,4=on': 0.09330,
'2=off,3=on,4=on': 0.22140,
'2=on,3=on,4=off': 0.21770,
'2=off,3=on,4=off': 0.14760,
'2=on,3=off,4=on': 0.04170,
'2=off,3=off,4=on': 0.10860,
'2=on,3=off,4=off': 0.09730,
'2=off,3=off,4=off': 0.07240,
'1=on,2=on': 0.21500,
'1=on,2=off': 0.23500,
'1=off,2=on': 0.23500,
'1=off,2=off': 0.31500,
'2=on,3=on': 0.31100,
'2=on,3=off': 0.13900,
'2=off,3=on': 0.36900,
'2=off,3=off': 0.18100,
'2=on,4=on': 0.13500,
'2=on,4=off': 0.31500,
'2=off,4=on': 0.33000,
'2=off,4=off': 0.22000,
'3=on,4=on': 0.31470,
'3=on,4=off': 0.36530,
'3=off,4=on': 0.15030,
'3=off,4=off': 0.16970,
'4=on,6=on': 0.14100,
'4=on,6=off': 0.32400,
'4=off,6=on': 0.27400,
'4=off,6=off': 0.26100
}
o_potentials = '\n'.join([str(v) for _, v in join_tree.potentials.items()
]).split('\n')
o_potentials = [p.split('|') for p in o_potentials]
o_potentials = {tokens[0]: float(tokens[1]) for tokens in o_potentials}
assert len(e_potentials) == len(o_potentials)
for k, lhs in o_potentials.items():
assert k in e_potentials
rhs = e_potentials[k]
assert lhs == rhs