c.p({"A1":True})
c.p({"A2":True})
c.p({"A3":True})
print "stationary distribution: P(A) = %.4f" % c.stationary_distribution()
print "\nTransition Probabilities 1"
TRANSITIONS = [("R","S","S","S","R","S","R")]
t = TransProb(TRANSITIONS)
t.report()
print "\nTransition Probabilities 2"
TRANSITIONS = [("S","S","S","S","S","R","S","S","S","R","R")]
t = TransProb(TRANSITIONS)
t.report()
print "\nTransition Probabilities 3"
TRANSITIONS = [("R","S","S","S","S")]
t = TransProb(TRANSITIONS)
t.report(k=1)
print "\nMarkov Model 1"
MODEL = ("R", 0.5, {True: 0.6, False: 0.2}, "H", {True: 0.4, False: 0.9})
m = MarkovModel(MODEL)
m.p({"R1":True})
m.p({"R1":True}, {"H1":True})
print "\nMarkov Model 2"
MODEL = ("R", 1.0, {True: 0.6, False: 0.2}, "H", {True: 0.4, False: 0.9})
m = MarkovModel(MODEL)
m.p({"R1":True}, {"H1":True})
