class InputNeuron(object):
def __init__(self, neuron_id = None):
Neuron.__init__(self)
self.__id = neuron_id
self.__local.append(0)
self.__output.append(0)
def __accumulate(self, *argin):
self.__local[0] = argin[0]
def __activate(self):
self.__output[0] = self.__local[0]
def probagate(self, *argin):
self.__accumulate(*argin)
self.__activate()
return self.__output[0]
def neuronId():
return self.__id
def local(self):
return self.__local
def output(self):
return self.__output
Neuron.register(InputNeuron)
self.__local[i] = self.__local[i+1]
self.__local[-1] = sum(argin)
def __activate(self):
if not len(self.__local):
return
output = 0.0
if self.activate_mode == 'Logistic':
output = 1.0 / (1.0 + exp(-self.__local[-1]))
for i in range(self.__num - 1):
self.__output[i] = self.__output[i+1]
self.__output[-1] = output
def probagate(self, *argin):
self.__accumulate(*argin)
self.__activate()
return self.__output[-1]
def neuronId():
return self.__id
def local(self):
return self.__local
def output(self):
return self.__output
Neuron.register(Perceptron)
class InputNeuron(object):
def __init__(self, neuron_id=None):
Neuron.__init__(self)
self.__id = neuron_id
self.__local.append(0)
self.__output.append(0)
def __accumulate(self, *argin):
self.__local[0] = argin[0]
def __activate(self):
self.__output[0] = self.__local[0]
def probagate(self, *argin):
self.__accumulate(*argin)
self.__activate()
return self.__output[0]
def neuronId():
return self.__id
def local(self):
return self.__local
def output(self):
return self.__output
Neuron.register(InputNeuron)