#va = potvariables(pot)
jointpot = multpots(pot)
#print("jointpot.variables:", jointpot.variables)
#print("jointpot.card:", jointpot.card)
#print("jointpot.table:", jointpot.table)
#print(jointpot.variables)
DAG = dag(pot) # Generate the DAG adjacency matrix
print("DAG adjacency matrix: \n", DAG)
evidencedpot = setpot(jointpot, alarm, yes)
#FIXME: arbitrary setting
#evidencedpot.variables = evidencedpot.variables[1:]
#print("................................................")
#print("evidencedpot.variables:", evidencedpot.variables)
#print("evidencedpot.table: \n", evidencedpot.table)
#print("evidencepot.variables:", evidencedpot.table)
conditionedpot = condpot(evidencedpot, burglar)
print("p(burglar|alarm=yes)")
print("conditionedpot.variables:", conditionedpot.variables)
print("conditionedpot.table: \n", conditionedpot.table)
# jointpot = multpots(pot); % joint distribution
evidencedpot = setpot(jointpot, [alarm, radio], [yes, yes])
conditionedpot = condpot(evidencedpot, burglar)
print("p(burglar|alarm=yes, radio=yes):")
print("conditionedpot.variables:", conditionedpot.variables)
print("conditionedpot.table: \n", conditionedpot.table)
#print("type:", (conditionedpot.table).dtype)
#va = potvariables(pot) jointpot = multpots(pot) #print "jointpot.variables:", jointpot.variables #print "jointpot.card:", jointpot.card #print "jointpot.table:", jointpot.table #print jointpot.variables DAG = dag(pot) # Generate the DAG adjacency matrix print "DAG adjacency matrix: \n", DAG evidencedpot = setpot(jointpot, alarm, yes) #FIXME: arbitrary setting #evidencedpot.variables = evidencedpot.variables[1:] #print "................................................" #print "evidencedpot.variables:", evidencedpot.variables #print "evidencedpot.table: \n", evidencedpot.table #print "evidencepot.variables:", evidencedpot.table conditionedpot = condpot(evidencedpot, burglar) print "p(burglar|alarm=yes)" print "conditionedpot.variables:", conditionedpot.variables print "conditionedpot.table: \n", conditionedpot.table # jointpot = multpots(pot); % joint distribution evidencedpot = setpot(jointpot, [alarm, radio], [yes, yes]) conditionedpot = condpot(evidencedpot, burglar) print "p(burglar|alarm=yes, radio=yes):" print "conditionedpot.variables:", conditionedpot.variables print "conditionedpot.table: \n", conditionedpot.table #print "type:", (conditionedpot.table).dtype
jointpot = multpots(pot) # joint distribution
#FIXME: arbitrary set order and swaped
#jointpot.variables = [0,1,2]
#jointpot.table = np.swapaxes(jointpot.table,0,2)
print "jointpot.variables:", jointpot.variables
print "joint distribution generated as: jointpot \n", jointpot.table
sum = jointpot.table.sum()
print "knife = ", variable[knife].domain[used], "maid = ", variable[
maid].domain[murderer], "butler = ", variable[butler].domain[murderer]
DAG = dag(pot) # Generate the DAG adjacency matrix
print "DAG adjacency matrix: \n", DAG
evidencedpot = setpot(jointpot, knife, used)
#FIXME: arbitrary setting
#evidencedpot.variables = evidencedpot.variables[1:]
print "................................................"
print "evidencedpot.variables:", evidencedpot.variables
print "evidencedpot.table: \n", evidencedpot.table
conditionedpot = condpot(evidencedpot, butler)
print "conditionedpot.variables:", conditionedpot.variables
print "conditionedpot.table: \n", conditionedpot.table
# jointpot = multpots(pot); % joint distribution
#drawNet(dag(pot),variable);
#disp('p(butler|knife=used):')
#disptable(condpot(setpot(jointpot,knife,used),butler),variable);
pot[knife].variables=np.array([knife,butler,maid]) # define array below using this variable order
pot[knife].card = np.array([2, 2, 2])
table = np.zeros((2,2,2))
table[used, notmurderer, notmurderer]=0.3
table[used, notmurderer, murderer] =0.2
table[used, murderer, notmurderer]=0.6
table[used, murderer, murderer] =0.1
pot[knife].table = table
pot[knife].table[notused][:][:]=1-pot[knife].table[used][:][:] # due to normalisation
jointpot = multpots(pot) # joint distribution
DAG = dag(pot) # Generate the DAG adjacency matrix
print "DAG adjacency matrix: \n", DAG
evidencedpot = setpot(jointpot,knife,used)
#FIXME: arbitrary setting
#evidencedpot.variables = evidencedpot.variables[1:]
conditionedpot = condpot(evidencedpot,[butler])
print "conditionedpot.variables:", conditionedpot.variables
print "conditionedpot.card:", conditionedpot.card
print "conditionedpot.table: \n", conditionedpot.table
# jointpot = multpots(pot); % joint distribution
#drawNet(dag(pot),variable);
#disp('p(butler|knife=used):')
#disptable(condpot(setpot(jointpot,knife,used),butler),variable);
print "knife created at:", pot[knife]
jointpot = multpots(pot) # joint distribution
#FIXME: arbitrary set order and swaped
#jointpot.variables = [0,1,2]
#jointpot.table = np.swapaxes(jointpot.table,0,2)
print "jointpot.variables:", jointpot.variables
print "joint distribution generated as: jointpot \n", jointpot.table
sum = jointpot.table.sum()
print "knife = ", variable[knife].domain[used], "maid = ", variable[maid].domain[murderer], "butler = ", variable[butler].domain[murderer]
DAG = dag(pot) # Generate the DAG adjacency matrix
print "DAG adjacency matrix: \n", DAG
evidencedpot = setpot(jointpot,knife,used)
#FIXME: arbitrary setting
#evidencedpot.variables = evidencedpot.variables[1:]
print "................................................"
print "evidencedpot.variables:", evidencedpot.variables
print "evidencedpot.table: \n", evidencedpot.table
conditionedpot = condpot(evidencedpot,butler)
print "conditionedpot.variables:", conditionedpot.variables
print "conditionedpot.table: \n", conditionedpot.table
# jointpot = multpots(pot); % joint distribution
#drawNet(dag(pot),variable);
#disp('p(butler|knife=used):')
#disptable(condpot(setpot(jointpot,knife,used),butler),variable);