def test_query_rule(self):
# Evidence Rules
fire_er = EvidenceRule("Fire", "Fire_Sensor", ["true", "false"],
["true", "false"], fire_cprob, fire_sensor_cprob)
human_er = EvidenceRule("Human", "Human_Sensor", ["true", "false"],
["true", "false"], human_cprob, human_sensor_cprob)
# Query Rules
qr = QueryRule('Human', 'Human in Danger', ["true", "false"], human_cprob, "Fire", ["true", "false"], 10, joint_functions.mean)
# Create engine
engine = InferenceEngine([fire_er, human_er], [qr])
##### EVIDENCE
e1 = Observation(10, 30, "Fire_Sensor", ["true", "false"], "true")
e2 = Observation(10, 30, "Human_Sensor", ["true", "false"], "true")
# bn, bn_evidences = engine.infer_bn([e1, e2])
#
# # Validate result
# self.assertEqual(len(bn.V), 6, "number of vertices in query rule")
# self.assertEqual(len(bn.E), 4, "number of edges for query rule")
e3 = Observation(12, 30, "Fire_Sensor", ["true", "false"], "true")
bn, bn_evidences = engine.infer_bn([e1, e2, e3])
# Validate result
self.assertEqual(len(bn.V), 8, "number of vertices in query rule")
self.assertEqual(len(bn.E), 5, "number of edges for query rule")
print "V: ", bn.V
print "E: ", bn.E
print "Evidences: ", bn_evidences
print "Vertex loc", engine.vertex_locations
def rrrtest_evidence_rule(self):
# Evidence Rules
erules = []
er = EvidenceRule("Fire", "Fire_Sensor", ["true", "false"],
["true", "false"], fire_cprob, fire_sensor_cprob)
erules.append(er)
# Query Rules
# Create engine
engine = InferenceEngine(erules, [])
# Evidence
e1 = Observation(10, 30, "Fire_Sensor", ["true", "false"], "true")
# run inference engine
bn, bn_evidences = engine.infer_bn([e1])
# Validate result
self.assertEqual(len(bn.V), 2)
# Another evidence
e2 = Observation(50, 30, "Fire_Sensor", ["true", "false"], "true")
# run inference engine
bn, bn_evidences = engine.infer_bn([e1, e2])
# Validate result
self.assertEqual(len(bn.V), 4)
# Another evidence in the same location of e1
e3 = Observation(10, 30, "Fire_Sensor", ["true", "false"], "true")
# run inference engine
bn, bn_evidences = engine.infer_bn([e1, e2, e3])
# Validate result
self.assertEqual(len(bn.V), 5, "Error for evidence in the same location")
self.assertEqual(len(bn.E), 3, "Error for evidence in the same location")
import pickle
from gi.repository import Gtk
from infengine.InferenceEngine import InferenceEngine
from infengine.gis import geojson
from lib_sallybn.disc_bayes_net.BoxDiscreteBN import BoxDiscreteBN, Mode
import rules2 as rules
with open('evidences.pkl', 'rb') as evidence_input:
evidences = pickle.load(evidence_input)
## Engine
engine = InferenceEngine(rules.get_rules())
# create bayesian network
bn, bn_evidences = engine.infer_bn(evidences)
# Output Layer
geojson.write(bn, engine.vertex_locations, bn_evidences)
##### Show the resultant Bayesian Network
# for i in range(1, 16, 5):
# bn, bn_evidences = engine.infer_bn(evidences[:i])
# window = Gtk.Window()
# window.set_size_request(800, 600)
#
# box = BoxDiscreteBN(window, disc_bn=bn)
# box.evidences = bn_evidences
# box.organize_graph(random=False)
# box.set_mode(Mode.run)
joint_functions.mean)
cr = CommunityRule('Human', 'Community', ["true", "false"], COMMUNITY_RADIO,
joint_functions.mean)
cdr = QueryRule('Community', 'Community in Danger', ["true", "false"], human_danger_cprob, "Fire", ["true", "false"],
10,
joint_functions.mean)
# Grid rule
human_gridr = GridRule("Human", "Human_Sensor", ["true", "false"],
["true", "false"], human_cprob, human_sensor_cprob, Grid(0, 0, 30, 60, 3, 7))
# Create engine
#engine = InferenceEngine([fire_er, human_er, qr, cr, cdr])
engine = InferenceEngine([human_gridr])
##### EVIDENCE
ef1 = Observation(10, 30, "Fire_Sensor", ["true", "false"], "true")
ef2 = Observation(19, 30, "Fire_Sensor", ["true", "false"], "false")
eh1 = Observation(10.0, 20.0, "Human_Sensor", ["true", "false"], "true")
eh2 = Observation(5, 19, "Human_Sensor", ["true", "false"], "false")
eh3 = Observation(15, 18, "Human_Sensor", ["true", "false"], "true")
eh4 = Observation(16, 17, "Human_Sensor", ["true", "false"], "true")
eh5 = Observation(-124.4577, 108.0135, "Human_Sensor", ["true", "false"], "true")
# bn, bn_evidences = engine.infer_bn([eh2, eh3, eh4, eh1, eh5, ])
bn, bn_evidences = engine.infer_bn([eh1, eh2, eh3, eh4])
