def pif_reset():
    defaultclock.reinit()
    sim = Network()
    I = 0.2*nA
    R = 1*Mohm
    lifeq = """
    dV/dt = I*R/ms : volt
    Vth : volt
    """
    thstep = 15*mV
    nrn = NeuronGroup(1, lifeq, threshold="V>=Vth", reset="V=0*mV")
    nrn.V = 0*mV
    nrn.Vth = thstep
    sim.add(nrn)

    #connection = Connection(inputgrp, nrn, state="V", weight=0.5*mV)
    #sim.add(inputgrp, connection)

    vmon = StateMonitor(nrn, "V", record=True)
    thmon = StateMonitor(nrn, "Vth", record=True)
    spikemon = SpikeMonitor(nrn, record=True)

    sim.add(vmon, thmon, spikemon)
    sim.run(duration)
    return vmon, thmon, spikemon
def runsim(fin):
    clear(True)
    gc.collect()
    defaultclock.reinit()
    weight = 0.16*mV
    sim = Network()
    duration = 2.0*second
    Vth = 15*mV
    Vreset = 13.65*mV
    trefr = 2*ms
    lifeq = """
    dV/dt = -V/(10*ms) : volt
    Vth : volt
    """
    nrndef = {"model": lifeq, "threshold": "V>=Vth", "reset": "V=Vreset",
              "refractory": 0.1*ms}
    inputgroups = []
    connections = []
    neurons = []
    Nneurons = len(fin)
    neurons = NeuronGroup(Nneurons, **nrndef)
    neurons.V = 0*mV
    neurons.Vth = 15*mV
    for idx in range(Nneurons):
        fin_i = fin[idx]*Hz
        inputgrp = PoissonGroup(50, fin_i)
        conn = Connection(inputgrp, neurons[idx], state="V", weight=weight)
        inputgroups.append(inputgrp)
        connections.append(conn)
    voltagemon = StateMonitor(neurons, "V", record=True)
    spikemon = SpikeMonitor(neurons, record=True)
    sim.add(neurons, voltagemon, spikemon)
    sim.add(*inputgroups)
    sim.add(*connections)

    @network_operation
    def refractory_threshold(clock):
        for idx in range(Nneurons):
            if (len(spikemon.spiketimes[idx])
                    and clock.t < spikemon.spiketimes[idx][-1]*second+trefr):
                neurons.Vth[idx] = 100*mV
            else:
                neurons.Vth[idx] = Vth

    sim.add(refractory_threshold)
    print("Running simulation of {} neurons for {} s".format(Nneurons, duration))
    sim.run(duration, report="stdout")
    mnpss = []
    allnpss = []
    outisi = []
    for idx in range(Nneurons):
        vmon = voltagemon[idx]
        smon = spikemon[idx]
        if not len(smon):
            continue
        outisi.append(duration*1000/len(smon))
        if len(smon) > 0:
            npss = sl.tools.npss(vmon, smon, 0*mV, 15*mV, 10*ms, 2*ms)
        else:
            npss = 0
        mnpss.append(np.mean(npss))
        allnpss.append(npss)
    return outisi, mnpss