def METHOD_NAME():
    """ephys.simulators: test if NrnSimulator constructor works"""
    # Check with minstep specified
    neuron_sim = ephys.simulators.NrnSimulator()
    assert neuron_sim.cvode.minstep() == 0.0
    assert neuron_sim.cvode_minstep == 0.0
    # Check default minstep before and after run
    neuron_sim = ephys.simulators.NrnSimulator(cvode_minstep=0.01)
    assert neuron_sim.cvode.minstep() == 0.
    neuron_sim.run(tstop=10)
    assert neuron_sim.cvode.minstep() == 0.
    # Check with that minstep is set back to the original value after run
    neuron_sim = ephys.simulators.NrnSimulator(cvode_minstep=0.0)
    neuron_sim.cvode_minstep = 0.05
    assert neuron_sim.cvode.minstep() == 0.05
    neuron_sim.run(tstop=10)
    assert neuron_sim.cvode.minstep() == 0.05
    # Check that the minstep is effective
    cvode_minstep = 0.012
    params = {'gnabar_hh': 0.10299326453483033,
              'gkbar_hh': 0.027124836082684685}
    simplecell = examples.simplecell.SimpleCell()
    evaluator = simplecell.cell_evaluator
    evaluator.cell_model.unfreeze(params.keys())
    evaluator.sim = ephys.simulators.NrnSimulator(cvode_minstep=cvode_minstep)
    responses = evaluator.run_protocols(
        protocols=evaluator.fitness_protocols.values(),
        param_values=params)
    ton = list(evaluator.fitness_protocols.values())[0].stimuli[0].step_delay
    toff = ton + list(evaluator.fitness_protocols.values())[0].stimuli[
        0].step_duration
    t_series = numpy.array(responses['Step1.soma.v']['time'])
    t_series = t_series[((ton + 1.) < t_series) & (t_series < (toff - 1.))]
    min_dt = numpy.min(numpy.ediff1d(t_series))
    assert (min_dt >= cvode_minstep) == 1
    evaluator.cell_model.freeze(params)