def UpdateBestWholeChainEverInMemory(BestWholeChainEverInMemory, GlobalPossibleActionSet, OriginalRNAChain, scaler, clf, scaler_ori, clf_ori):
temp = 0
append_list = []
for item in GlobalPossibleActionSet:
position_of_nucleotide = item.PositionOfNucleotide
reward = item.rewards
#print 'rewards', reward, 'vs', BestWholeChainEverInMemory.rewards
if reward >= BestWholeChainEverInMemory.rewards and item.WholeChainBP != [0 for i in range(0, len(OriginalRNAChain))]:
#print 'FLAG*****BestWC changed', 'new reward:', reward, 'old reward:', BestWholeChainEverInMemory.rewards
BestWholeChainEverInMemory.rewards = reward
BestWholeChainEverInMemory.ChainItself = item.WholeChainBP
BestWholeChainEverInMemory.Parent = item.PartialChain_parent
BestWholeChainEverInMemory.ori_WC = item.ori_WC
temp = temp + 1
elif item.WholeChainBP == [0 for i in range(0, len(OriginalRNAChain))]:
pass
else:
pass
if temp == 0:
print "Sorry, there are no matching partial chain as parent"
#Here we replace the whole chain and scores of the corresponding next step as fortified's.
temp_1 =0
for item in GlobalPossibleActionSet:
position_of_nucleotide = item.PositionOfNucleotide
temp_nuc = BestWholeChainEverInMemory.ChainItself[position_of_nucleotide]
if BestWholeChainEverInMemory.ChainItself[position_of_nucleotide] == 2.5:
temp_nuc = 2
elif BestWholeChainEverInMemory.ChainItself[position_of_nucleotide] == 1.5:
temp_nuc = 1
#print 'item.BasePair', item.BasePair
#print 'BestWholeChainEverInMemory.ChainItself[position_of_nucleotide]', BestWholeChainEverInMemory.ChainItself[position_of_nucleotide]
#print 'temp_nuc', temp_nuc
#print 'item.WholeChainBP[:(position_of_nucleotide-1)]', item.WholeChainBP[:(position_of_nucleotide-1)]
#print 'BestWholeChainEverInMemory.ChainItself[:(position_of_nucleotide-1)]', BestWholeChainEverInMemory.ChainItself[:(position_of_nucleotide-1)]
if item.BasePair == temp_nuc and item.WholeChainBP[:(position_of_nucleotide-1)] == BestWholeChainEverInMemory.ChainItself[:(position_of_nucleotide-1)]:
temp_1 = temp_1 +1
new_item = deepcopy(item)
new_item.WholeChainBP = BestWholeChainEverInMemory.ChainItself
new_item.ori_WC = BestWholeChainEverInMemory.ChainItself
#print 'item.Parent', item.PartialChain_parent.ChainItself, 'VVVSSS', 'new_item.PartialChain_parent', new_item.PartialChain_parent.ChainItself
BestWholeChainEverInMemory.Parent = new_item.PartialChain_parent
new_rewards_1 = entrna_main(''.join(map(str, OriginalRNAChain)), ''.join(map(str, BP_to_DP(BestWholeChainEverInMemory.ChainItself))), scaler, clf)
new_rewards_2 = entrna_main_ori(''.join(map(str, OriginalRNAChain)), ''.join(map(str, BP_to_DP(BestWholeChainEverInMemory.ChainItself))), scaler_ori, clf_ori)
new_rewards_3 = abs(new_rewards_1 - new_rewards_2)
new_item.rewards = new_rewards_1
append_list.append(new_item)
#print 'append_list'
for itera in append_list:
#print 'New_action_deepcopy', itera.Nucleotide, itera.BasePair, itera.rewards, itera.PartialChain_parent, itera.WholeChainBP
GlobalPossibleActionSet.append(itera)
if temp_1 == 0:
raise Exception("Sorry, there's no corresponding action to fortified solution.")
return GlobalPossibleActionSet,BestWholeChainEverInMemory
def GetRewards_ori(WholeChain,OriginalRNAChain,scaler_ori, clf_ori):
"""
In this function we plug in ENTRNA as rewards.
"""
seq = OriginalRNAChain
dp = SeqAttRollOut_RNAfold.TransferIntoDP(WholeChain)
seq_str = ''.join(map(str, seq))
dp_str = ''.join(map(str, dp))
#bp = dp_to_bp(dp)
#print('*Get Rewards Ori:*')
#print('seq_str is:',seq_str)
#print('dp_str is:',dp_str)
foldability = entrna_main_ori(seq_str,dp_str,scaler_ori, clf_ori)
rewards = foldability
#print('Now the rewards is',rewards)
#rewards = random.randrange(0,5)
return rewards
def Calculate_Foldability(seq1,dp_str,scaler_ori, clf_ori):
foldability = entrna_main_ori(seq1,dp_str,scaler_ori, clf_ori)
#foldability = entrna_main(seq1,dp_str,scaler, clf)
#print('foldability',foldability)
return foldability