class TestOrderedSkeleton(unittest.TestCase):
def setUp(self):
self.os = OrderedSkeleton()
self.os.load("unittestdict.txt")
self.gs = GraphSkeleton()
self.gs.load("unittestdict.txt")
def test_constructor(self):
self.assertNotEqual(self.os.V, self.gs.V)
self.gs.toporder()
self.assertEqual(self.os.V, self.gs.V)
class TestOrderedSkeleton(unittest.TestCase):
def setUp(self):
self.os = OrderedSkeleton()
self.os.load("unittestdict.txt")
self.gs = GraphSkeleton()
self.gs.load("unittestdict.txt")
def test_constructor(self):
self.assertNotEqual(self.os.V, self.gs.V)
self.gs.toporder()
self.assertEqual(self.os.V, self.gs.V)
def __init__(self, nodes):
self.nodes = {}
self.children = defaultdict(list)
self.parents = defaultdict(list)
self.outputs = {}
for name, node_spec in nodes.iteritems():
node_type = node_spec["type"]
if node_type == "inferred":
parents = node_spec["parents"]
# store the relationship between these elements
for parent in parents:
normalised = normalise_name(parent)
self.parents[name].append(normalised)
self.children[normalised].append(name)
truth_table = parse_truth_table(node_spec["p"], parents)
node = make_node(truth_table, parents, node_type)
self.nodes[name] = node
if node_type == "fsm_input":
node = make_node([1.0, 0.0], None, node_type)
self.nodes[name] = node
if node_type == "sensor_input":
proxy_node = make_node([1.0, 0.0], None, "proxy")
proxy_name = "_proxy_%s" % name
self.nodes[proxy_name] = proxy_node
self.children[proxy_name].append(name)
node = make_node({
"['T']": [1.0, 0.0],
"['F']": [0.0, 1.0]
}, [proxy_name], node_type)
self.nodes[name] = node
if node_type == "output":
self.outputs[name] = node_spec
for node in self.nodes:
if len(self.children[node]) > 0:
self.nodes[node]["children"] = self.children[node]
else:
self.nodes[node]["children"] = None
# certainty scaling
self.event_caution = 0.0
og = OrderedSkeleton()
og.V = self.nodes.keys()
edges = []
for k, children in self.children.iteritems():
for child in children:
edges.append((k, child))
og.E = edges
og.toporder()
nd = NodeData()
nd.Vdata = self.nodes
#logging.debug(pprint.pformat(nd.Vdata))
self.net = DiscreteBayesianNetwork(og, nd)
self.factor_net = TableCPDFactorization(self.net)
def setUp(self):
self.os = OrderedSkeleton()
self.os.load("unittestdict.txt")
self.gs = GraphSkeleton()
self.gs.load("unittestdict.txt")
def setUp(self):
self.os = OrderedSkeleton()
self.os.load("unittestdict.txt")
self.gs = GraphSkeleton()
self.gs.load("unittestdict.txt")
