return utilr
node_fr.assign_func(failure_risk)
# create new network
dbnet = Network("Soliman2014InfDiag")
# add nodes to network
dbnet.add_nodes([node_m, node_k] + aarray + marray + insparray + uiarray +
rarray + urarray + [node_fr])
# add link: must be prior to defining nodes
dbnet.add_link()
# define nodes
dbnet.define_nodes()
# compile the net
dbnet.compile_net()
# enable autoupdate
dbnet.set_autoupdate()
# save the network
dbnet.save_net("Soliman2014InfDiag.dne")
#type 2
dbnet.retract_netfindings()
dummy = dbnet.get_node_expectedutils(node_insp)
dummy = dbnet.get_node_expectedutils(node_repair)
decision = dbnet.get_node_funcstate(node_repair, [2, 4])
print 'If the inspection decision is {} and meausre is {}, the best repair decision is {}.\n'.format(
node_insp.statenames[2], marray[0].statenames[4],
node_repair.statenames[decision])
return utilr
node_fr.assign_func(failure_risk)
# create new network
dbnet = Network("Soliman2014InfDiag")
# add nodes to network
dbnet.add_nodes([node_m, node_k]+aarray+marray+insparray+uiarray+rarray+urarray+[node_fr])
# add link: must be prior to defining nodes
dbnet.add_link()
# define nodes
dbnet.define_nodes()
# compile the net
dbnet.compile_net()
# enable autoupdate
dbnet.set_autoupdate()
# save the network
dbnet.save_net("Soliman2014InfDiag.dne")
#type 2
dbnet.retract_netfindings()
dummy = dbnet.get_node_expectedutils(node_insp)
dummy = dbnet.get_node_expectedutils(node_repair)
decision = dbnet.get_node_funcstate(node_repair, [2,4])
print 'If the inspection decision is {} and meausre is {}, the best repair decision is {}.\n'.format(
node_insp.statenames[2], marray[0].statenames[4], node_repair.statenames[decision])
# decision making
# type 1
dbnet.enter_finding(forecast, 0)
utils = dbnet.get_node_expectedutils(umbrella)
print 'If the forecast is sunny, expected utility of {} is {}, of {} is {}\n'.format(
umbrella.statenames[0], utils[0],
umbrella.statenames[1], utils[1])
dbnet.retract_netfindings()
dbnet.enter_finding(forecast, 1)
utils = dbnet.get_node_expectedutils(umbrella)
print 'If the forecast is cloudy, expected utility of {} is {}, of {} is {}\n'.format(
umbrella.statenames[0], utils[0],
umbrella.statenames[1], utils[1])
dbnet.retract_netfindings()
dbnet.enter_finding(forecast, 2)
utils = dbnet.get_node_expectedutils(umbrella)
print 'If the forecast is rainy, expected utility of {} is {}, of {} is {}\n'.format(
umbrella.statenames[0], utils[0],
umbrella.statenames[1], utils[1])
#type 2
dbnet.retract_netfindings()
dummy = dbnet.get_node_expectedutils(umbrella)
for fs in range(forecast.nstates()):
decision = dbnet.get_node_funcstate(umbrella, [fs])
print 'If the forecast is {}, the best decision is {}.\n'.format(
forecast.statenames[fs], umbrella.statenames[decision])
dbnet.set_autoupdate()
# save the network
dbnet.save_net("BNdecision.dne")
# decision making
# type 1
dbnet.enter_finding(forecast, 0)
utils = dbnet.get_node_expectedutils(umbrella)
print 'If the forecast is sunny, expected utility of {} is {}, of {} is {}\n'.format(
umbrella.statenames[0], utils[0], umbrella.statenames[1], utils[1])
dbnet.retract_netfindings()
dbnet.enter_finding(forecast, 1)
utils = dbnet.get_node_expectedutils(umbrella)
print 'If the forecast is cloudy, expected utility of {} is {}, of {} is {}\n'.format(
umbrella.statenames[0], utils[0], umbrella.statenames[1], utils[1])
dbnet.retract_netfindings()
dbnet.enter_finding(forecast, 2)
utils = dbnet.get_node_expectedutils(umbrella)
print 'If the forecast is rainy, expected utility of {} is {}, of {} is {}\n'.format(
umbrella.statenames[0], utils[0], umbrella.statenames[1], utils[1])
#type 2
dbnet.retract_netfindings()
dummy = dbnet.get_node_expectedutils(umbrella)
for fs in range(forecast.nstates()):
decision = dbnet.get_node_funcstate(umbrella, [fs])
print 'If the forecast is {}, the best decision is {}.\n'.format(
forecast.statenames[fs], umbrella.statenames[decision])