from ca.nengo.model.impl import *
from ca.nengo.model import *
from ca.nengo.model.nef.impl import *
from ca.nengo.model.neuron.impl import *
from ca.nengo.model.neuron import *
from ca.nengo.math.impl import *
from ca.nengo.model.plasticity.impl import *
from ca.nengo.util import *
from ca.nengo.math import *

#Introduce rate-based learning rule
class MyFunction(AbstractFunction):  #Define the rule
   serialVersionUID = 1
   def __init__(self):
      AbstractFunction.__init__(self,7)
   def map(self,x):
      kappa=6e-5; #1e-4 is good with oja
      #return kappa*x[0]*x[6]  #original learning rule
      return kappa*(x[0]*x[6]-(x[0]**2)*x[2]) #oja normalization, smoother results