def ruleEncodingAlgorithm(knowledgeBase):
network = []
for l in len(knowledgeBase):
current = RBM(len(knowledgeBase[l][0][0].x), len(knowledgeBase[l][0]))
for i in range(len(knowledgeBase[l])):
for j in range(len(knowledgeBase[l][i].x)):
if knowledgeBase[l][i].x[j] == True:
current.w[i][j] = knowledgeBase[l][i].c
elif knowledgeBase[l][i].x[j] == False:
current.w[i][j] = -knowledgeBase[l][i].c
network.append(current)
dbn = DBN([network[0]._input_size] + [x._output_size for x in network], [],
[])
return dbn.load_from_rbms(len(network) - 1, network)
