def getArgs(argv):
try:
opts, args = getopt.getopt(sys.argv[1:], 'm:j:p:g:')
except getopt.GetoptError as err:
print str(err)
sys.exit(2)
output = None
operation = None
p_output = None
val = None
for o,a in opts:
if o in ("-j"):
operation = o
output = a
elif o == ("-m"):
operation = o
output = a
elif o == ("-g"):
operation = o
output = a
elif o == ("-p"):
operation = o
p_output = a[0]
val = float(a[1:])
output = a[0]
else:
assert False, "unhandled option"
pollution_val = .9
smoker_val = .3
if(p_output == "S"):
bn = BayesNode.create_bayesNet(pollution_val, val)
elif(p_output == "P"):
bn = BayesNode.create_bayesNet(val, smoker_val)
else:
bn = BayesNode.create_bayesNet(pollution_val, smoker_val)
#call functions for math
if operation == "-m":
if output == "p":
print(bn.nodes["Pollution"].marginal)
elif output == "~p":
print(1.0 - bn.nodes["Pollution"].marginal)
elif output == "P":
print("True:/n")
print(bn.nodes["Pollution"].marginal)
print("/nFalse: ")
print(1.0 - bn.nodes["Pollution"].marginal)
elif output == "s":
print(bn.nodes["Smoker"].marginal)
elif output == "~s":
print(1.0 - bn.nodes["Smoker"].marginal)
elif output == "S":
print("True:")
print(bn.nodes["Smoker"].marginal)
print("False: ")
print(1.0 - bn.nodes["Smoker"].marginal)
elif output == "c":
print(bn.nodes["Cancer"].marginal)
elif output == "~c":
print(1.0 - bn.nodes["Cancer"].marginal)
elif output == "C":
print("True:")
print(bn.nodes["Cancer"].marginal)
print("False: ")
print(1.0 - bn.nodes["Cancer"].marginal)
elif output == "d":
print(bn.nodes["Dyspnoea"].marginal)
elif output == "~d":
print(1.0 - bn.nodes["Dyspnoea"].marginal)
elif output == "D":
print("True:")
print(bn.nodes["Dyspnoea"].marginal)
print("False: ")
print(1.0 - bn.nodes["Dyspnoea"].marginal)
elif output == "x":
print(bn.nodes["XRay"].marginal)
elif output == "~x":
print(1.0 - bn.nodes["XRay"].marginal)
elif output == "X":
print("True:")
print(bn.nodes["XRay"].marginal)
print("False: ")
print(1.0 - bn.nodes["XRay"].marginal)
else:
print("Not a valid option")
sys.exit(2)
elif operation == "-j":
if output == "PSC":
print ProbabilityCalcs.joint_PSC(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"])
else:
wanted = output
print ProbabilityCalcs.joint_psc(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"], wanted)
elif operation == "-g":
#P=H row
if output == "p|d":
x = ProbabilityCalcs.probPollutionGivenDys(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"],bn.nodes["Dyspnoea"])
print(x)
elif output == "p|c":
x = ProbabilityCalcs.probPollutionGivenCancer(bn.nodes["Cancer"], bn.nodes["XRay"], bn.nodes["Pollution"], bn.nodes["Smoker"])
print(x)
elif output == "p|s":
print(1.0 - bn.nodes["Pollution"].marginal)
elif output == "p|cs" :
x = ProbabilityCalcs.probPollutionGivenCancerAndSmoker(bn.nodes["Cancer"], bn.nodes["XRay"], bn.nodes["Pollution"], bn.nodes["Smoker"])
print(x)
elif output == "p|ds" :
x = ProbabilityCalcs.probPollutionGivenDysAndSmoker(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"],bn.nodes["Dyspnoea"])
print(x)
#S=T row
elif output == "s|d":
x = ProbabilityCalcs.probSmokerGivenDyspnoea(bn.nodes["Cancer"],bn.nodes["XRay"],bn.nodes["Pollution"], bn.nodes["Smoker"],bn.nodes["Dyspnoea"])
print(x)
elif output == "s|s" or output == "s|cs" or output == "s|sc":
print("1.0")
elif output == "s|c":
x = ProbabilityCalcs.probSmokerGivenCancer(bn.nodes["Cancer"],bn.nodes["Pollution"],bn.nodes["Smoker"])
print(x)
#C=T row
elif output == "c|d":
x = ProbabilityCalcs.probCancerGivenDyspnoea(bn.nodes["Cancer"], bn.nodes["Dyspnoea"])
print(x)
elif output == "c|s":
x = ProbabilityCalcs.probCancerGivenSmoker(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"])
print(x)
elif output == "c|c":
print("1.0")
elif output == "c|ds":
x = ProbabilityCalcs.probCancerGivenDysAndSmoker(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"],bn.nodes["Dyspnoea"])
print(x)
#not required
elif output == "c|p":
x = ProbabilityCalcs.probCancerGivenPollutionHigh(bn.nodes["Cancer"], bn.nodes["XRay"], bn.nodes["Pollution"], bn.nodes["Smoker"])
print(x)
#X=T row
elif output == "x|d":
x = ProbabilityCalcs.probXrayGivenDys(bn.nodes["Cancer"], bn.nodes["XRay"], bn.nodes["Dyspnoea"])
print(x)
elif output == "x|s":
x = ProbabilityCalcs.probXrayGivenSmoker(bn.nodes["Cancer"], bn.nodes["XRay"], bn.nodes["Pollution"], bn.nodes["Smoker"])
print(x)
elif output == "x|c" or output == "x|sc" or output == "x|cs":
print(bn.nodes["XRay"].probabilities["C"])
elif output == "x|ds":
x = ProbabilityCalcs.probXrayGivenDysandSmoker(bn.nodes["Smoker"], bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Dyspnoea"], bn.nodes["XRay"])
print(x)
#D=T row
elif output == "d|d":
print("1.0")
elif output == "d|s":
x = ProbabilityCalcs.probDyspnoeaGivenSmoker(bn.nodes["Cancer"], bn.nodes["XRay"], bn.nodes["Pollution"], bn.nodes["Smoker"],bn.nodes["Dyspnoea"])
print(x)
elif output == "d|c" or "d|cs":
x = ProbabilityCalcs.probDyspnoeaGivenCancer(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"],bn.nodes["Dyspnoea"])
print(x)
#not required
elif output == "d|p":
x = ProbabilityCalcs.probDyspnoeaGivenPollution(bn.nodes["Cancer"], bn.nodes["Pollution"], bn.nodes["Smoker"],bn.nodes["Dyspnoea"])
print(x)
