def pytest_funcarg__monty_hall_graph(request):
g = build_bbn(
f_guest_door, f_prize_door, f_monty_door,
domains={
'guest_door': ['A', 'B', 'C'],
'monty_door': ['A', 'B', 'C'],
'prize_door': ['A', 'B', 'C']})
return g
def __export__(self, iterations, screen=True, file=True, pdf=True):
_str = 'Finished inference in ' + str(iterations) + ' iterations.\n'
_str += 'Evaluations: ' + str(iterations * self.population_size) + '\n'
_str += 'Population size: ' + str(self.population_size) + '\n'
_str += 'Nodes: ' + str(self.model_graph.count_nodes) + '\n'
_str += 'Colors: ' + str(len(self.palette)) + '\n'
_str += 'Best individual fitness: ' + str(round(self.__best_individual__().fitness, 2)) + "\n"
_str += 'Marginalization matrix:\n'
some_bbn = build_bbn(
*self._bbn_functions.values(), # unzips list
domains=dict([(x, self.palette) for x in self.node_names])
)
print _str
some_bbn.q()
_dict = copy.deepcopy(self.dependencies)
del _dict[None]
if pdf:
bbn = graphviz.Digraph()
[bbn.node(x) for x in self.node_names]
bbn.edges(_dict.items())
bbn.render('bbn.gv')
self.__best_individual__().export('optimal')
if file:
query = some_bbn.query().items()
query = '\n'.join([str(x) for x in query])
with open('output.txt', 'w') as file:
file.write(_str)
file.write(query)
if screen:
def plot_bbn():
plt.figure(1)
G = nx.DiGraph()
G.add_edges_from(_dict.items())
layout = nx.shell_layout(G)
nx.draw_networkx(G, pos=layout, cmap=plt.get_cmap('jet'), node_color=list(itertools.repeat('cyan', len(self.node_names))))
def plot_optimal():
plt.figure(2)
individual = self.__best_individual__()
G = nx.Graph()
G.add_nodes_from(individual.names)
some_edges = [tuple(list(x)) for x in individual.edges]
G.add_edges_from(some_edges)
layout = nx.shell_layout(G)
nx.draw_networkx(G, pos=layout, cmap=plt.get_cmap('jet'), node_color=individual.colors)
plot_bbn()
plot_optimal()
plt.show()
def pytest_funcarg__monty_hall_graph(request):
g = build_bbn(f_guest_door,
f_prize_door,
f_monty_door,
domains={
'guest_door': ['A', 'B', 'C'],
'monty_door': ['A', 'B', 'C'],
'prize_door': ['A', 'B', 'C']
})
return g
if tabs == ['t', 't', 't']:
return 0.99
elif tabs == ['t', 't', 'f']:
return 0.01
elif tabs == ['t', 'f', 't']:
return 0.9
elif tabs == ['t', 'f', 'f']:
return 0.1
elif tabs == ['f', 't', 't']:
return 0.9
elif tabs == ['f', 't', 'f']:
return 0.1
elif tabs == ['f', 'f', 't']:
return 0
elif tabs == ['f', 'f', 'f']:
return 1
pass
if __name__ == '__main__':
g = build_bbn(f_cloudy,
f_rain,
f_sprinkler,
f_wetgrass,
domains=dict(cloudy=['t', 'f'],
rain=['t', 'f'],
sprinkler=['t', 'f'],
wetgrass=['t', 'f']))
ttt=0.99,
tft=0.9,
ftt=0.97,
fft=0.3) # Note typo in article!
key = make_key(fo, bp, do)
if key in tt:
return tt[key]
key = make_key(fo, bp, not do)
return 1 - tt[key]
def hear_bark(do, hb):
tt = dict(
tt=0.7,
ft=0.01)
key = make_key(do, hb)
if key in tt:
return tt[key]
key = make_key(do, not hb)
return 1 - tt[key]
if __name__ == '__main__':
g = build_bbn(
family_out,
bowel_problem,
light_on,
dog_out,
hear_bark)
g.q()
return 0.5
elif temp_yesterday == 'medium':
return 0.25
elif temp_yesterday == 'cold':
return 0.25
def f_rain_yesterday(rain_yesterday):
return 0.5
def f_temp(season, temp_yesterday, temp):
return season_temp[season][(temp_yesterday, temp)]
def f_rain(season, rain_yesterday, rain):
return season_rain[season][(rain_yesterday, rain)]
if __name__ == '__main__':
g = build_bbn(f_temp_yesterday,
f_rain_yesterday,
f_season,
f_temp,
f_rain,
domains=dict(temp_yesterday=('hot', 'medium', 'cold'),
temp=('hot', 'medium', 'cold'),
season=('spring', 'summer', 'autumn',
'winter')))
g.q()
return 0.41
elif tabs == ['f', 't', 'f']:
return 1 - f_alarm('f', 't', 't')
elif tabs == ['f', 'f', 't']:
return 0.001
elif tabs == ['f', 'f', 'f']:
return 1 - f_alarm('f', 'f', 't')
def f_radio(earthquake, radio):
tabs = [earthquake, radio]
if earthquake == radio:
return 1
else:
return 0
if __name__ == '__main__':
g = build_bbn(f_burglar,
f_earthquake,
f_alarm,
f_radio,
domains=dict(burglar=['t', 'f'],
earthquake=['t', 'f'],
alarm=['t', 'f'],
radio=['t', 'f']))
g.q()
def f_prize_door(prize_door):
return 0.3333333
def f_guest_door(guest_door):
return 0.3333333
def f_monty_door(prize_door, guest_door, monty_door):
if prize_door == guest_door:
if monty_door == prize_door:
return 0
return 0.5
elif prize_door == monty_door:
return 0
elif guest_door == monty_door:
return 0
return 1
if __name__ == "__main__":
g = build_bbn(
f_prize_door,
f_guest_door,
f_monty_door,
domains=dict(
prize_door=['A','B','C'],
guest_door=['A','B','C'],
monty_door=['A','B','C']
))
def pytest_funcarg__cancer_graph(request):
g = build_bbn(
fP, fS, fC, fX, fD,
domains={
'P': ['low', 'high']})
return g
def net(self, inputnodes=None):
function_list = list(self.functions(inputnodes=inputnodes))
net = build_bbn(function_list, domains=self.variables)
return net
table['tt'] = 1.
table['tf'] = 0.
table['ft'] = 0.
table['ff'] = 1.
key = ''
key = key + 't' if earthquake else key + 'f'
key = key + 't' if radioBroadcast else key + 'f'
return table[key]
def f_alarm(burglary, earthquake, alarm):
table = dict()
table['fft'] = 0.001
table['fff'] = 0.999
table['ftt'] = 0.41
table['ftf'] = 0.59
table['tft'] = 0.95
table['tff'] = 0.05
table['ttt'] = 0.98
table['ttf'] = 0.02
key = ''
key = key + 't' if burglary else key + 'f'
key = key + 't' if earthquake else key + 'f'
key = key + 't' if alarm else key + 'f'
return table[key]
if __name__ == '__main__':
g = build_bbn(f_burglary, f_earthquake, f_radioBroadcast, f_alarm)
g.q()
def pytest_funcarg__cancer_graph(request):
g = build_bbn(fP, fS, fC, fX, fD, domains={'P': ['low', 'high']})
return g
def __export__(self, iterations, screen=True, file=True, pdf=True):
_str = 'Finished inference in ' + str(iterations) + ' iterations.\n'
_str += 'Evaluations: ' + str(iterations * self.population_size) + '\n'
_str += 'Population size: ' + str(self.population_size) + '\n'
_str += 'Nodes: ' + str(self.model_graph.count_nodes) + '\n'
_str += 'Colors: ' + str(len(self.palette)) + '\n'
_str += 'Best individual fitness: ' + str(
round(self.__best_individual__().fitness, 2)) + "\n"
_str += 'Marginalization matrix:\n'
some_bbn = build_bbn(
*self._bbn_functions.values(), # unzips list
domains=dict([(x, self.palette) for x in self.node_names]))
print _str
some_bbn.q()
_dict = copy.deepcopy(self.dependencies)
del _dict[None]
if pdf:
bbn = graphviz.Digraph()
[bbn.node(x) for x in self.node_names]
bbn.edges(_dict.items())
bbn.render('bbn.gv')
self.__best_individual__().export('optimal')
if file:
query = some_bbn.query().items()
query = '\n'.join([str(x) for x in query])
with open('output.txt', 'w') as file:
file.write(_str)
file.write(query)
if screen:
def plot_bbn():
plt.figure(1)
G = nx.DiGraph()
G.add_edges_from(_dict.items())
layout = nx.shell_layout(G)
nx.draw_networkx(G,
pos=layout,
cmap=plt.get_cmap('jet'),
node_color=list(
itertools.repeat('cyan',
len(self.node_names))))
def plot_optimal():
plt.figure(2)
individual = self.__best_individual__()
G = nx.Graph()
G.add_nodes_from(individual.names)
some_edges = [tuple(list(x)) for x in individual.edges]
G.add_edges_from(some_edges)
layout = nx.shell_layout(G)
nx.draw_networkx(G,
pos=layout,
cmap=plt.get_cmap('jet'),
node_color=individual.colors)
plot_bbn()
plot_optimal()
plt.show()
return 0.01
return 0.99
def light_on(fo, lo):
tt = dict(tt=0.6, tf=0.4, ft=0.05, ff=0.96)
return tt[make_key(fo, lo)]
def dog_out(fo, bp, do):
tt = dict(ttt=0.99, tft=0.9, ftt=0.97, fft=0.3) # Note typo in article!
key = make_key(fo, bp, do)
if key in tt:
return tt[key]
key = make_key(fo, bp, not do)
return 1 - tt[key]
def hear_bark(do, hb):
tt = dict(tt=0.7, ft=0.01)
key = make_key(do, hb)
if key in tt:
return tt[key]
key = make_key(do, not hb)
return 1 - tt[key]
if __name__ == '__main__':
g = build_bbn(family_out, bowel_problem, light_on, dog_out, hear_bark)
g.q()
def pytest_funcarg__earthquake_bbn(request):
g = build_bbn(
f_burglary, f_earthquake, f_alarm,
f_johncalls, f_marycalls)
return g
if rain:
if grass_wet:
return 0.99
else:
return 0.01
else:
if grass_wet:
return 0.9
else:
return 0.1
else:
if rain:
if grass_wet:
return 0.8
else:
return 0.2
else:
if grass_wet:
return 0.0
else:
return 1
if __name__ == '__main__':
g = build_bbn(f_rain,
f_sprinkler,
f_grass_wet,
domains=dict(rain=[True, False],
sprinkler=[True, False],
grass_wet=[True, False]))
elif tabs == ['f', 'f']:
return 1 - 0.05
def f_mary(mary, alarm):
tabs = [mary, alarm]
if tabs == ['t', 't']:
return 0.70
elif tabs == ['t', 'f']:
return 0.01
elif tabs == ['f', 't']:
return 1 - 0.70
elif tabs == ['f', 'f']:
return 1 - 0.01
if __name__ == '__main__':
g = build_bbn(f_burglar,
f_earthquake,
f_alarm,
f_john,
f_mary,
domains=dict(burglar=['t', 'f'],
earthquake=['t', 'f'],
alarm=['t', 'f'],
john=['t', 'f'],
mary=['t', 'f']))
g.q()
return table[key]
def f_johncalls(alarm, johncalls):
table = dict()
table["tt"] = 0.9
table["tf"] = 0.1
table["ft"] = 0.05
table["ff"] = 0.95
key = ""
key = key + "t" if alarm else key + "f"
key = key + "t" if johncalls else key + "f"
return table[key]
def f_marycalls(alarm, marycalls):
table = dict()
table["tt"] = 0.7
table["tf"] = 0.3
table["ft"] = 0.01
table["ff"] = 0.99
key = ""
key = key + "t" if alarm else key + "f"
key = key + "t" if marycalls else key + "f"
return table[key]
if __name__ == "__main__":
g = build_bbn(f_burglary, f_earthquake, f_alarm, f_johncalls, f_marycalls)
g.q()
return table[key]
def f_johncalls(alarm, johncalls):
table = dict()
table['tt'] = 0.9
table['tf'] = 0.1
table['ft'] = 0.05
table['ff'] = 0.95
key = ''
key = key + 't' if alarm else key + 'f'
key = key + 't' if johncalls else key + 'f'
return table[key]
def f_marycalls(alarm, marycalls):
table = dict()
table['tt'] = 0.7
table['tf'] = 0.3
table['ft'] = 0.01
table['ff'] = 0.99
key = ''
key = key + 't' if alarm else key + 'f'
key = key + 't' if marycalls else key + 'f'
return table[key]
if __name__ == '__main__':
g = build_bbn(f_burglary, f_earthquake, f_alarm, f_johncalls, f_marycalls)
g.q()
"""
from bayesian.bbn import build_bbn
def f_coina(flipa):
if (flipa == 'H'):
return 0.5
elif (flipa == 'T'):
return 0.5
def f_coinb(flipa, flipb):
if (flipa == 'H'):
if (flipb == 'H'):
return 0.6
elif (flipb == 'T'):
return 0.4
elif (flipa == 'T'):
if (flipb == 'H'):
return 0.5
elif (flipb == 'T'):
return 0.5
if __name__ == '__main__':
coins = build_bbn(f_coina,
f_coinb,
domains=dict(flipa=['H', 'T'], flipb=['H', 'T']))
def pytest_funcarg__huang_darwiche_bbn(request):
g = build_bbn(f_a, f_b, f_c, f_d, f_e, f_f, f_g, f_h)
return g
human_action=str(req.human_action),
human_expression=str(req.human_expression)).get(
('robot_expression', 'n'))
c = g.query(object_size=str(req.object_size),
human_action=str(req.human_action),
human_expression=str(req.human_expression)).get(
('robot_expression', 's'))
return predict_robot_expressionResponse(a, b, c)
#section for service
# node is initialised
# service is declared
def main_server():
rospy.init_node('robot_expression_prediction')
s = rospy.Service('predictrobotexpression', predict_robot_expression,
handle_server)
rospy.spin()
if __name__ == '__main__':
g = build_bbn(f_human_expression,
f_human_action,
f_object_size,
f_robot_expression,
domains=dict(human_expression=['1', '2', '3'],
human_action=['1', '2', '3'],
object_size=['1', '2'],
robot_expression=['h', 's', 'n']))
main_server()
def pytest_funcarg__huang_darwiche_bbn(request):
g = build_bbn(f_a, f_b, f_c, f_d, f_e, f_f, f_g, f_h)
return g
def pytest_funcarg__earthquake_bbn(request):
g = build_bbn(f_burglary, f_earthquake, f_alarm, f_johncalls, f_marycalls)
return g
table['ff'] = 1.
key = ''
key = key + 't' if earthquake else key + 'f'
key = key + 't' if radioBroadcast else key + 'f'
return table[key]
def f_alarm(burglary, earthquake, alarm):
table = dict()
table['fft'] = 0.001
table['fff'] = 0.999
table['ftt'] = 0.41
table['ftf'] = 0.59
table['tft'] = 0.95
table['tff'] = 0.05
table['ttt'] = 0.98
table['ttf'] = 0.02
key = ''
key = key + 't' if burglary else key + 'f'
key = key + 't' if earthquake else key + 'f'
key = key + 't' if alarm else key + 'f'
return table[key]
if __name__ == '__main__':
g = build_bbn(
f_burglary,
f_earthquake,
f_radioBroadcast,
f_alarm)
g.q()
elif prize_door == monty_door:
return 0 # Again, Monty wont reveal the prize
elif guest_door == monty_door:
return 0 # Monty will never choose the guest door
else:
# This covers all case where
# the guest has *not* guessed
# correctly and Monty chooses
# the only remaining door that
# wont reveal the prize.
return 1
g = build_bbn(
f_prize_door,
f_guest_door,
f_monty_door,
domains=dict(prize_door=["A", "B", "C"], guest_door=["A", "B", "C"], monty_door=["A", "B", "C"]),
)
def json_convert(query):
"""
function used to convert queries into useful json files
that can be served by bottle and imported into the game
using ajax.
"""
d = {k[0]: {} for k in query.keys()}
[d[k[0]].update({k[1]: r}) for k, r in query.items()]
return json.dumps(d)
if restore:
return p
else:
return 1.0 - p
if __name__ == '__main__':
levels = [True, False]
net = build_bbn(
f_landscape,
f_site,
f_current,
f_future,
f_restore,
# assume simple binary
domains=dict(
landscape=levels,
environment=levels,
eco=levels,
restore=levels
)
)
import itertools
prod = itertools.product(
xrange(0, 101, 25), # landscape metric
xrange(0, 101, 25), # site metric
xrange(0, 101, 25), # current metric
xrange(0, 101, 25), # potential metric
)
def build_bnet(self): functions, domains = self.build_functions_for_nodes() self.g = build_bbn(*functions, domains=domains)
elif temp_yesterday == 'medium':
return 0.25
elif temp_yesterday == 'cold':
return 0.25
def f_rain_yesterday(rain_yesterday):
return 0.5
def f_temp(season, temp_yesterday, temp):
return season_temp[season][(temp_yesterday, temp)]
def f_rain(season, rain_yesterday, rain):
return season_rain[season][(rain_yesterday, rain)]
if __name__ == '__main__':
g = build_bbn(
f_temp_yesterday,
f_rain_yesterday,
f_season,
f_temp,
f_rain,
domains=dict(
temp_yesterday=('hot', 'medium', 'cold'),
temp=('hot', 'medium', 'cold'),
season=('spring', 'summer', 'autumn', 'winter')))
g.q()
def f_relva_molhada(chuva, aspersor, relva_molhada):
if relva_molhada:
if chuva and aspersor:
return 0.99
elif not chuva and aspersor:
return 0.9
elif chuva and not aspersor:
return 0.8
elif not chuva and not aspersor:
return 0
else:
if chuva and aspersor:
return 0.01
elif not chuva and aspersor:
return 0.1
elif chuva and not aspersor:
return 0.2
elif not chuva and not aspersor:
return 1
if __name__ == '__main__':
g = build_bbn(f_chuva,
f_aspersor,
f_relva_molhada,
domains=dict(chuva=[True, False],
aspersor=[True, False],
relva_molhada=[True, False]))
def f_guest_door(guest_door):
return 0.33333333
def f_monty_door(prize_door, guest_door, monty_door):
if prize_door == guest_door: # 参赛者猜对了
if prize_door == monty_door:
return 0 # Monty不会打开有车的那扇门，不可能发生
else:
return 0.5 # Monty会打开其它两扇门，二选一
elif prize_door == monty_door:
return 0 # Monty不会打开有车的那扇门，不可能发生
elif guest_door == monty_door:
return 0 # 门已经由参赛者选定，不可能发生
else:
return 1 # Monty打开另一扇有羊的门
if __name__ == '__main__':
g = build_bbn(f_prize_door,
f_guest_door,
f_monty_door,
domains=dict(prize_door=['A', 'B', 'C'],
guest_door=['A', 'B', 'C'],
monty_door=['A', 'B', 'C']))
g.q()
g.q(guest_door='A')
g.q(guest_door='A', monty_door='B')
if prize_door == monty_door:
return 0 # 没有获得奖项
else:
return 1 / 2 # 选择下一个有山羊的门，现在只有两个选择
elif prize_door == monty_door:
return 0 # 仍然没有选中含有奖项的门
elif guest_door == monty_door:
return 0
else:
# 其他情况
return 1
if __name__ == '__main__':
get_result = build_bbn(
door_with_prize,
door_choosed,
door_monty,
domains=dict(
# 定义每种选项的可选择情况
prize_door=['1', '2', '3'],
guest_door=['1', '2', '3'],
monty_door=['1', '2', '3']))
get_result.q()
get_result.q(guest_door='1')
get_result.q(guest_door='1', monty_door='2')
get_result.q(guest_door='3', monty_door='2')
get_result.q(guest_door='1', monty_door='3')
get_result.q(guest_door='2', monty_door='1')
