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updated eeglab.py to account for SET files that contain trials but no… #12704

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53 changes: 44 additions & 9 deletions mne/io/eeglab/eeglab.py
Original file line number Diff line number Diff line change
Expand Up @@ -619,6 +619,35 @@ def __init__(
"You should try using read_raw_eeglab function."
)

def generate_boundary_events(n_trials):
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"""
Generate boundary events for epoched data without events.

Parameters
----------
n_trials (int): Number of trials (epochs)
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Returns
-------
numpy.ndarray: Array of boundary events
dict: Event id dictionary
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"""
events = np.zeros((n_trials, 3), dtype=np.int64) # Explicitly use int64
events[:, 0] = np.arange(
n_trials, dtype=np.int64
) # Start from 0 for sample numbers
events[:, 1] = 0 # Previous event value
events[:, 2] = 1 # Boundary marker

event_id = {"boundary": 1}

# Double-check the array type
assert (
events.dtype == np.int64
), f"Events dtype is {events.dtype}, expected np.int64"

return events, event_id

if events is None and eeg.trials > 1:
# first extract the events and construct an event_id dict
event_name, event_latencies, unique_ev = list(), list(), list()
Expand Down Expand Up @@ -656,15 +685,21 @@ def __init__(
)

# now fill up the event array
events = np.zeros((eeg.trials, 3), dtype=int)
for idx in range(0, eeg.trials):
if idx == 0:
prev_stim = 0
elif idx > 0 and event_latencies[idx] - event_latencies[idx - 1] == 1:
prev_stim = event_id[event_name[idx - 1]]
events[idx, 0] = event_latencies[idx]
events[idx, 1] = prev_stim
events[idx, 2] = event_id[event_name[idx]]
if event_id is None and not event_name and not event_latencies:
# account for EEGLAB with trials but no events
events, event_id = generate_boundary_events(eeg.trials)
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else:
events = np.zeros((eeg.trials, 3), dtype=int)
for idx in range(0, eeg.trials):
if idx == 0:
prev_stim = 0
elif (
idx > 0 and event_latencies[idx] - event_latencies[idx - 1] == 1
):
prev_stim = event_id[event_name[idx - 1]]
events[idx, 0] = event_latencies[idx]
events[idx, 1] = prev_stim
events[idx, 2] = event_id[event_name[idx]]
elif isinstance(events, (str, Path, PathLike)):
events = read_events(events)

Expand Down
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