import json

from libpgm.nodedata import NodeData

from libpgm.graphskeleton import GraphSkeleton

from libpgm.discretebayesiannetwork import DiscreteBayesianNetwork

from libpgm.tablecpdfactorization import TableCPDFactorization

# load nodedata and graphskeleton

nd = NodeData()

skel = GraphSkeleton()

nd.load("tests/net1.json") # any input file

skel.load("tests/net1.json")

# topologically order graphskeleton

skel.toporder()

# load bayesian network

bn = DiscreteBayesianNetwork(skel, nd)

fn = TableCPDFactorization(bn)

# sample

result = fn.specificquery(dict(C='T'), dict(B='F'))

# output

print json.dumps(result, indent=2)