def METHOD_NAME(self):
    """SetStatus of reversal and threshold potential"""
    excluded = ["a2eif_cond_exp_HW", "mat2_psc_exp", "amat2_psc_exp"]
    models = nest.node_models + nest.synapse_models
    for model in [m for m in models if m not in excluded]:
        if all(key in nest.GetDefaults(model) for key in ("V_th", "E_L")):
            nest.ResetKernel()
            neuron1 = nest.Create(model)
            neuron2 = nest.Create(model)
            # must not depend on the order
            new_EL = -90.0
            new_Vth = -10.0
            if "V_reset" in nest.GetDefaults(model):
                nest.SetStatus(neuron1 + neuron2, {"V_reset": new_EL})
            nest.SetStatus(neuron1, {"E_L": new_EL})
            nest.SetStatus(neuron2, {"V_th": new_Vth})
            nest.SetStatus(neuron1, {"V_th": new_Vth})
            nest.SetStatus(neuron2, {"E_L": new_EL})
            vth1, vth2 = nest.GetStatus(neuron1 + neuron2, "V_th")
            self.assertEqual(vth1, vth2)