def setUp(self):
self.net = network.Network(
[data.DiscreteVariable(i,3) for i in xrange(5)],
"0,1;3,2;2,4;1,4"
)
self.p = prior.UniformPrior(len(self.net.nodes))
self.p2 = prior.UniformPrior(len(self.net.nodes), weight=2.0)
def test_null_prior():
net = network.Network(
[data.DiscreteVariable(i,3) for i in xrange(5)],
"0,1;3,2;2,4;1,4"
)
p1 = prior.NullPrior()
assert p1.loglikelihood(net) == 0.0
net.edges.add((1,4))
assert p1.loglikelihood(net) == 0.0
def setUp(self):
self.net = network.Network(
[data.DiscreteVariable(i,3) for i in xrange(5)],
"0,1;1,3;1,2"
)
energymat = N.array([[ 0.5, 0. , 0.5, 0.5, 0.5],
[ 0.5, 0.5, 0.5, 0.5, 0. ],
[ 0.5, 0.5, 0.5, 0.5, 0.5],
[ 0.5, 0.5, 0.5, 0.5, 5. ],
[ 0.5, 0.5, 0.5, 0.5, 0.5]])
self.p = prior.Prior(len(self.net.nodes), energymat, required_edges=[(1,2)])
def setUp(self):
self.net = network.Network(
[data.DiscreteVariable(i,3) for i in xrange(5)],
"0,1;3,2;2,4;1,4"
)
self.p = prior.Prior(
len(self.net.nodes),
required_edges=[(1,4),(0,1)],
prohibited_edges=[(3,4)],
constraints=[lambda am: not am[0,4]]
)
def setUp(self):
self.nodes = [data.DiscreteVariable(str(i), 3) for i in xrange(6)]
def setUp(self):
self.net = network.Network(
[data.DiscreteVariable(str(i), 3) for i in xrange(6)],
"0,1;4,5;2,3")
def setUp(self):
self.net = network.Network(
[data.DiscreteVariable(str(i), 3) for i in xrange(6)], [(0, 1),
(4, 5),
(2, 3)])
def setUp(self):
self.net = network.Network(
[data.DiscreteVariable(i, 3) for i in xrange(6)])
for edge in [(0, 1), (0, 3), (1, 2)]:
self.net.edges.add(edge)