connectome/connectome.py
def runconnectome():
    """Each time a set of neuron is stimulated, this method will execute
    The weigted values are accumulated in the postSynaptic array
    Once the accumulation is read, we see what neurons are greater
    then the threshold and fire the neuron or muscle that has exceeded
    the threshold.
    """
    global thisState
    global nextState

    for ps in postSynaptic:
        if ps[:3] not in muscles and abs(postSynaptic[ps][thisState]) > threshold:
            fireNeuron(ps)
    motorcontrol()
    for ps in postSynaptic:
        # if postSynaptic[ps][thisState] != 0:
        #     print ps
        #     print "Before Clone: ", postSynaptic[ps][thisState]

        # fired neurons keep getting reset to previous weight
        # wtf deepcopy -- So, the concern is that the deepcopy doesnt
        # scale up to larger neural networks??
        postSynaptic[ps][thisState] = copy.deepcopy(postSynaptic[ps][nextState])

        # this deep copy is not in the functioning version currently.
        # print "After Clone: ", postSynaptic[ps][thisState]

    thisState,nextState=nextState,thisState
Each time a set of neuron is stimulated, this method will execute
    The weigted values are accumulated in the postSynaptic array
    Once the accumulation is read, we see what neurons are greater
    then the threshold and fire the neuron or muscle that has exceeded
    the threshold.
    
Each time a set of neuron is stimulated, this method will execute
The weigted values are accumulated in the postSynaptic array
Once the accumulation is read, we see what neurons are greater
then the threshold and fire the neuron or muscle that has exceeded
the threshold.
Each time a set of neuron is stimulated this method will execute The weigted values are accumulated in the postSynaptic array Once the accumulation is read we see what neurons are greater then the threshold and fire the neuron or muscle that has exceeded the threshold .
def runconnectome():
    global thisState
    global nextState
    for ps in postSynaptic:
        if ps[:3] not in muscles and abs(postSynaptic[ps][thisState]) > threshold:
            fireNeuron(ps)
    motorcontrol()
    for ps in postSynaptic:
        postSynaptic[ps][thisState] = copy.deepcopy(postSynaptic[ps][nextState])
    thisState,nextState=nextState,thisState
def runconnectome ( ) : global thisState global nextState for ps in postSynaptic : if ps [ : 3 ] not in muscles and abs ( postSynaptic [ ps ] [ thisState ] ) > threshold : fireNeuron ( ps ) motorcontrol ( ) for ps in postSynaptic : postSynaptic [ ps ] [ thisState ] = copy . deepcopy ( postSynaptic [ ps ] [ nextState ] ) thisState , nextState = nextState , thisState
Each time a set of neuron is stimulated, this method will execute
The weigted values are accumulated in the postSynaptic array
Once the accumulation is read, we see what neurons are greater
then the threshold and fire the neuron or muscle that has exceeded
the threshold.
Each time a set of neuron is stimulated this method will execute The weigted values are accumulated in the postSynaptic array Once the accumulation is read we see what neurons are greater then the threshold and fire the neuron or muscle that has exceeded the threshold .
"""Each time a set of neuron is stimulated, this method will execute
    The weigted values are accumulated in the postSynaptic array
    Once the accumulation is read, we see what neurons are greater
    then the threshold and fire the neuron or muscle that has exceeded
    the threshold.
    """ # if postSynaptic[ps][thisState] != 0: #     print ps #     print "Before Clone: ", postSynaptic[ps][thisState] # fired neurons keep getting reset to previous weight # wtf deepcopy -- So, the concern is that the deepcopy doesnt # scale up to larger neural networks?? # this deep copy is not in the functioning version currently. # print "After Clone: ", postSynaptic[ps][thisState]