[Mne_analysis] Could you help me find events from ".set" file?

[Soan KIM]

        External Email - Use Caution        

Hello, I am a student learning MNE-python.
I have trouble finding events in my ".set" file. It appears empty.
I've also tried mne.io.read_epochs_eeglab with my another epoched ".set"
file, but the list of events is also empty.
To be specific, my raw eeg file was '.vhdr', '.vmrk', and
'.eeg.(BrainProduct)', with no stim_channel. And the data had no problem
when I pre-processed and ran statistics with EEGLAB and ERPlab. Could you
please help me?

Thank you.

This is how my file looks like.

<Info | 17 non-empty fields
    bads : list | 0 items
    ch_names : list | Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1, ...
    chs : list | 30 items (EEG: 30)
    comps : list | 0 items
    custom_ref_applied : bool | False
    dev_head_t : Transform | 3 items
    dig : list | 29 items (29 EEG)
    events : list | 0 items
    highpass : float | 0.0 Hz
    hpi_meas : list | 0 items
    hpi_results : list | 0 items
    lowpass : float | 125.0 Hz
    meas_date : NoneType | unspecified
    nchan : int | 30
    proc_history : list | 0 items
    projs : list | 0 items
    sfreq : float | 250.0 Hz
    acq_pars : NoneType
    acq_stim : NoneType
    ctf_head_t : NoneType
    description : NoneType
    dev_ctf_t : NoneType
    experimenter : NoneType
    file_id : NoneType
    gantry_angle : NoneType
    hpi_subsystem : NoneType
    kit_system_id : NoneType
    line_freq : NoneType
    meas_id : NoneType
    proj_id : NoneType
    proj_name : NoneType
    subject_info : NoneType
    xplotter_layout : NoneType



This is my code :

raw = mne.io.read_raw_eeglab('/001.set', preload=True)
event_id = {'B1(1)': 1, 'B2(2)':2, 'B3(3)':3, 'B4(4)':4, 'B5(5)':5,
'B6(6)':6, 'B7(7)':7}
events= mne.find_events(raw)
data, times = raw[:, :]
data.shape
start, stop = raw.time_as_index([0, 503955])
data, times = raw[:, start:stop]
times.max()
picks = mne.pick_types(raw.info
,meg=False,eeg=True,stim=False,eog=False,ecg=False,misc=False)

events = mne.find_events(raw, stim_channel=None, verbose=True)
events[:]

array([], shape=(0, 3), dtype=int32)
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