self vars_prev [ previous for in vars_nowself transition_factors transition_factors self init_factors init_factors self var_index {var_index[vis the index of variable for , in enumerate(vars_now)self var_index[ ]= here is variable dbnprobdbn py -(continued , variable_pair(" "domain=[false,true] , variable_pair(" "domain=[false,true] , variable_pair(" "domain=[false,true] dynamics pc prob( ,[ , ],[[[ , ],[ , ]],[[ , ],[ , ]]]pb prob( ,[ , ],[[[ , ],[ , ]],[[ , ],[ , ]]]pa prob( ,[ , ],[[[ , ],[ , ]],[[ , ],[ , ]]] initial distribution pa prob( ,[],[ , ]pb prob( ,[ ],[[ , ],[ , ]]pc prob( ,[],[ , ] dbn dbn("simple dbn",[ , , ],[pa,pb,pc],[pa ,pb ,pc ]here is the animal example probdbn py -(continued from probhmm import closemicfarmicmidmicsmmmcscmcmmcc pos_ ,pos_ variable_pair("position",domain=[ , , , ]mic ,mic variable_pair("mic "mic ,mic variable_pair("mic "mic ,mic variable_pair("mic " conditional probabilities see hmm for the values of sm,mmcetc ppos prob(pos_ [pos_ ][[smmmcmmcmmc]#was in middle [mcmscmccmcc]#was in corner [mcmmccscmcc]#was in corner [mcmmccmccsc]]#was in corner pm prob(mic [pos_ ][[ -midmicmidmic][ -closemicclosemic][ -farmicfarmic][ -farmicfarmic]]pm prob(mic [pos_ ][[ -midmicmidmic][ -farmicfarmic][ -closemicclosemic][ -farmicfarmic]]pm prob(mic [pos_ ][[ -midmicmidmic][ -farmicfarmic][ -farmicfarmic][ -closemicclosemic]]ipos prob(pos_ ,[][ ]dbn_an =dbn("animal dbn",[pos_ ,mic ,mic ,mic ][ppospm pm pm ][ipospm pm pm ]version june