def setUp(self):
from bayesnet import BNet, BVertex, graph
# create a small BayesNet
self.G = G = BNet('Test')
self.a = a = G.add_v(BVertex('a', discrete=False, nvalues=1))
self.b = b = G.add_v(BVertex('b', discrete=False, nvalues=2))
self.c = c = G.add_v(BVertex('c', discrete=False, nvalues=1))
self.d = d = G.add_v(BVertex('d', discrete=True, nvalues=2))
self.e = e = G.add_v(BVertex('e', discrete=True, nvalues=3))
self.f = f = G.add_v(BVertex('f', discrete=False, nvalues=1))
self.g = g = G.add_v(BVertex('g', discrete=False, nvalues=1))
for ep in [(a, c), (b, c), (d, f), (e, f),
(a, g), (b, g), (d, g), (e, g)]:
G.add_e(graph.DirEdge(len(G.e), *ep))
#a,b : continuous(1,2), no parents
#c : continuous(3), 2 continuous parents (a,b)
#d,e : discrete(2,3), no parents
#f : continuous(1), 2 discrete parents (d,e)
#g : continuous(1), 2 discrete parents (d,e) & 2 continuous parents (a,b)
G.InitDistributions()
self.ad = ad = a.distribution
self.bd = bd = b.distribution
self.cd = cd = c.distribution
self.fd = fd = f.distribution
self.gd = gd = g.distribution
def setUp(self):
from bayesnet import BNet, BVertex, graph
# create a small BayesNet
G = BNet('Water Sprinkler Bayesian Network')
c,s,r,w = [G.add_v(BVertex(nm, discrete=True, nvalues=nv)) for nm, nv \
in zip('c s r w'.split(), [2, 3, 4, 2])]
for ep in [(c, r), (c, s), (r, w), (s, w)]:
G.add_e(graph.DirEdge(len(G.e), *ep))
G.InitDistributions()
self.G = G
def setUp(self):
from bayesnet import BNet, BVertex, graph
# create a small BayesNet, Water-Sprinkler
G = BNet('Test')
a, b, c, d = [G.add_v(BVertex(nm, discrete=True, nvalues=nv)) for \
nm, nv in zip('a b c d'.split(), [2, 3, 4, 2])]
ad, bd, cd, dd = a.distribution, b.distribution, \
c.distribution, d.distribution
# sizes = (2,3,4,2)
# a has 3 parents, b,c and d
for ep in [(b, a), (c, a), (d, a)]:
G.add_e(graph.DirEdge(len(G.e), *ep))
G.InitDistributions()
self.G = G
self.a, self.b, self.c, self.d = a, b, c, d
