'''
Created on Jul 8, 2014
This a Izhikevh neuron model class
@author: sun

Aug 21 add the method in "Hybrid spiking models"
'''
class Izhike():
    '''
    classdocs
    '''


    def __init__(self, a, b, c, d,deltT):
        '''
        Constructor
        '''
        
        #print ri
        #self.a = a+0.08*ri
        #self.b = b-0.05*ri
        self.a = a
        self.b = b
        self.c = c
        self.d = d    
        self.v=0
        self.u=0
        self.I=0
        #self.deltT=0.25
        self.Th=30
        self.dt=deltT

    def model(self,dt,I):
        #VSignal=[]#membrane potential of the neuron
        #USignal=[]#membrane recovery variable
        #tmpv=self.v
        #tmpu=self.u
        spikeflag=False
        #self.deltT=dt
        self.I=I
        ov=self.v
        self.v+=(dt/2.)*(0.04*(self.v**2) + 5*self.v + 140 - self.u+self.I)
        self.v+=(dt/2.)*(0.04*(self.v**2) + 5*self.v + 140 - self.u+self.I)
        #self.Th=30
        if self.v>=self.Th:
            tp=(self.Th-ov)/(self.v-ov)*self.dt
            #print tp
            self.u+=tp*(self.a*(self.b*self.Th-self.u))
            self.v=self.c
            self.u=self.u+self.d
            #spikeflag=True
        else:
            self.u+=self.dt*(self.a*(self.b*self.v-self.u))
        return self.v,self.u