def METHOD_NAME():
    emg = nk.emg_simulate(duration=20, sampling_rate=1000, burst_number=3)
    emg_signals, info = nk.emg_process(emg, sampling_rate=1000)
    epochs = nk.epochs_create(
        emg_signals,
        events=[3000, 6000, 9000],
        sampling_rate=1000,
        epochs_start=-0.1,
        epochs_end=1.9,
    )
    emg_eventrelated = nk.emg_eventrelated(epochs)
    # Test amplitude features
    no_activation = np.where(emg_eventrelated["EMG_Activation"] == 0)[0][0]
    assert int(pd.DataFrame(emg_eventrelated.values[no_activation]).isna().sum()) == 5
    assert np.alltrue(
        np.nansum(np.array(emg_eventrelated["EMG_Amplitude_Mean"]))
        < np.nansum(np.array(emg_eventrelated["EMG_Amplitude_Max"]))
    )
    assert len(emg_eventrelated["Label"]) == 3
    # Test warning on missing columns
    with pytest.warns(
        nk.misc.NeuroKitWarning, match=r".*does not have an `EMG_Onsets`.*"
    ):
        first_epoch_key = list(epochs.keys())[0]
        first_epoch_copy = epochs[first_epoch_key].copy()
        del first_epoch_copy["EMG_Onsets"]
        nk.emg_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
    with pytest.warns(
        nk.misc.NeuroKitWarning, match=r".*does not have an `EMG_Activity`.*"
    ):
        first_epoch_key = list(epochs.keys())[0]
        first_epoch_copy = epochs[first_epoch_key].copy()
        del first_epoch_copy["EMG_Activity"]
        nk.emg_eventrelated({**epochs, first_epoch_key: first_epoch_copy})
    with pytest.warns(
        nk.misc.NeuroKitWarning, match=r".*does not have an.*`EMG_Amplitude`.*"
    ):
        first_epoch_key = list(epochs.keys())[0]
        first_epoch_copy = epochs[first_epoch_key].copy()
        del first_epoch_copy["EMG_Amplitude"]
        nk.emg_eventrelated({**epochs, first_epoch_key: first_epoch_copy})