def entropy_gain(self, action, data=None): return entropy_gains.theory_entropy_gain(action, data)
import newmodel import learners import entropy_gains import world import Datapoint import test_data dcol=test_data.dat_col rl=learners.RandomLearner() print entropy_gains.theory_entropy_gain(rl.choose_action(dcol)) tl=learners.TheoryLearner() #print tl.choose_action(dcol) print entropy_gains.theory_entropy_gain(((0,0),(2,0))) #print entropy_gains.theory_entropy_gain(tl.choose_action(dcol)) # import test_data # d0=test_data.dat_col[0] # #print 'oh! ', newmodel.p_data_hypothesis([d0], 0, (0,0)) # print 'oh! ', newmodel.p_singledata_hypothesis(d0, 2, (0,0)) # d0.display() # suma=0 # count=0 # for m in world.machines: # for t in world.available_toys: