def RateUpdt(ss, nt, inputOn):
"""
RateUpdt updates the neuron in rate-code mode
this just calls the relevant activation code directly, bypassing most other stuff.
"""
ly = leabra.Layer(ss.Net.LayerByName("Neuron"))
nrn = leabra.Neuron(ly.Neurons[0])
ly.Act.VmFmG(nrn)
ly.Act.ActFmG(nrn)
nrn.Ge = nrn.Ge * ly.Act.Gbar.E
def Harmony(ss, nt):
"""
Harmony computes the harmony (excitatory net input Ge * Act)
"""
harm = float(0)
nu = 0
for lyi in nt.Layers:
ly = leabra.Layer(handle=lyi)
if ly.IsOff():
continue
for nrni in ly.Neurons:
nrn = leabra.Neuron(handle=nrni)
harm += nrn.Ge * nrn.Act
nu += 1
if nu > 0:
harm /= float(nu)
return harm
def LogTstCyc(ss, dt, cyc):
"""
LogTstCyc adds data from current cycle to the TstCycLog table.
"""
if dt.Rows <= cyc:
dt.SetNumRows(cyc + 1)
row = cyc
ly = leabra.Layer(ss.Net.LayerByName("Neuron"))
nrn = leabra.Neuron(ly.Neurons[0])
dt.SetCellFloat("Cycle", row, float(cyc))
dt.SetCellFloat("Ge", row, float(nrn.Ge))
dt.SetCellFloat("Inet", row, float(nrn.Inet))
dt.SetCellFloat("Vm", row, float(nrn.Vm))
dt.SetCellFloat("Act", row, float(nrn.Act))
dt.SetCellFloat("Spike", row, float(nrn.Spike))
dt.SetCellFloat("Gk", row, float(nrn.Gk))
dt.SetCellFloat("ISI", row, float(nrn.ISI))
dt.SetCellFloat("AvgISI", row, float(nrn.ISIAvg))
# note: essential to use Go version of update when called from another goroutine
if cyc % ss.UpdtInterval == 0:
ss.TstCycPlot.GoUpdate()