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Fix EEGLAB events after dropped epochs #14067

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Fix EEGLAB events after dropped epochs #14067

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fb69aa9
Fix EEGLAB events after dropping epochs
viranovskaya Jul 18, 2026
e22d068
Clarify EEGLAB epoch event mapping
viranovskaya Jul 18, 2026
2554ab3
Fix changelog entry number
viranovskaya Jul 18, 2026
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1 change: 1 addition & 0 deletions doc/changes/dev/14067.bugfix.rst
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@@ -0,0 +1 @@
Fix :meth:`mne.Epochs.export` producing invalid EEGLAB event latencies and dummy events after epochs were dropped, by :newcontrib:`Daria Agafonova`.
1 change: 1 addition & 0 deletions doc/changes/names.inc
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Expand Up @@ -72,6 +72,7 @@
.. _Daniel McCloy: https://dan.mccloy.info
.. _Daniel Strohmeier: https://github.com/joewalter
.. _Daniel Tse: https://github.com/Xiezhibin
.. _Daria Agafonova: https://github.com/viranovskaya
.. _Darin Erat Sleiter: https://github.com/dsleiter
.. _David Haslacher: https://github.com/davidhaslacher
.. _David Julien: https://github.com/Swy7ch
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12 changes: 10 additions & 2 deletions mne/export/_eeglab.py
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Expand Up @@ -66,16 +66,24 @@ def _export_epochs(fname, epochs):
else:
annot = None

# eeglabio uses column 0 as latency in the concatenated epochs array and
# column 2 as event type; the original recording sample is not stored here.
events = epochs.events.copy()
events[:, 0] = (
np.arange(len(epochs)) * len(epochs.times) + epochs.time_as_index(0)[0]
)

@larsoner larsoner Jul 18, 2026

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This is odd... if you do this there is no longer any reference to the absolute time in the original recording. It suggests events[:, 2] is the only thing correctly used by eeglabio.epochs.export_set. Is it?

@viranovskaya viranovskaya Jul 18, 2026

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Yes, the absolute sample from the original continuous recording is intentionally not retained in this field. For epoched EEGLAB files, eeglabio uses column 0 as latency in the concatenated epochs array and column 2 as the event type; column 1 is unused. Keeping the original sample numbers is what caused events to point to the wrong epochs after dropping epochs. I clarified this in the code comment.

@larsoner larsoner Jul 18, 2026

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Ohhh.... so I think this fix actually belongs in eeglabio. It should handle the translation from MNE-Python events (which it currently takes) to whatever eeglab wants.

@viranovskaya viranovskaya Jul 18, 2026

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That makes sense. I moved the translation into eeglabio and added tests for dropped epochs and the tmax=0 boundary: jackz314/eeglabio#26. I’ll update this PR once the upstream behavior is settled.


# https://github.com/jackz314/eeglabio/pull/18
kwargs = dict()
if "epoch_indices" in getfullargspec(eeglabio.epochs.export_set).kwonlyargs:
kwargs["epoch_indices"] = epochs.selection
# This also handles zero time falling on the final sample (tmax=0).
kwargs["epoch_indices"] = np.arange(1, len(epochs) + 1)
Comment on lines 78 to +80

@larsoner larsoner Jul 18, 2026

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Is there any reason to pass this at all anymore? I assume if you don't pass it, it defaults to np.arange, no?

@viranovskaya viranovskaya Jul 18, 2026 •
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Good question. In most cases, omitting epoch_indices gives the same result. But when zero time is the final sample (tmax=0), eeglabio assigns the event to the next epoch and resets the latencies. I updated the regression test to cover this case; it fails without the explicit indices and passes with them. So I kept the argument and added a short comment.


eeglabio.epochs.export_set(
fname,
data=epochs.get_data(picks=ch_names),
sfreq=epochs.info["sfreq"],
events=epochs.events,
events=events,
tmin=epochs.tmin,
tmax=epochs.tmax,
ch_names=ch_names,
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43 changes: 42 additions & 1 deletion mne/export/tests/test_export.py
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Expand Up @@ -15,6 +15,7 @@
from mne import (
Annotations,
Epochs,
EpochsArray,
create_info,
read_epochs_eeglab,
read_evokeds,
Expand Down Expand Up @@ -560,7 +561,10 @@ def test_export_epochs_eeglab(tmp_path, preload):
cart_coords = np.array([d["loc"][:3] for d in epochs.info["chs"]]) # just xyz
cart_coords_read = np.array([d["loc"][:3] for d in epochs_read.info["chs"]])
assert_allclose(cart_coords, cart_coords_read)
assert_array_equal(epochs.events[:, 0], epochs_read.events[:, 0]) # latency
event_samples = (
np.arange(len(epochs)) * len(epochs.times) + epochs.time_as_index(0)[0]
)
assert_array_equal(event_samples, epochs_read.events[:, 0])
assert epochs.event_id.keys() == epochs_read.event_id.keys() # just keys
assert_allclose(epochs.times, epochs_read.times)
assert_allclose(epochs.get_data(), epochs_read.get_data())
Expand All @@ -583,6 +587,43 @@ def test_export_epochs_eeglab(tmp_path, preload):
epochs.export(Path(temp_fname), overwrite=True)


def test_export_epochs_eeglab_after_drop(tmp_path):
"""Test EEGLAB event mapping after dropping epochs with tmax=0."""
pytest.importorskip("eeglabio", minversion="0.1.2")
sfreq = 100.0
n_epochs, n_times = 5, 11
info = create_info(["Cz"], sfreq, "eeg")
data = np.zeros((n_epochs, 1, n_times))
events = np.column_stack(
(
np.arange(1, n_epochs + 1) * 100,
np.zeros(n_epochs, int),
[1, 2, 3, 4, 5],
)
)
event_id = {f"event-{code}": code for code in events[:, 2]}
epochs = EpochsArray(
data, info, events=events, event_id=event_id, tmin=-0.1, verbose=False
)
assert epochs.tmax == 0
epochs.drop([1, 3])
assert_array_equal(epochs.selection, [0, 2, 4])

fname = tmp_path / "dropped.set"
epochs.export(fname)
epochs_read = read_epochs_eeglab(fname, verbose="error")

event_samples = (
np.arange(len(epochs)) * len(epochs.times) + epochs.time_as_index(0)[0]
)
assert_array_equal(event_samples, epochs_read.events[:, 0])
kept_codes = set(epochs.events[:, 2])
kept_names = {name for name, code in epochs.event_id.items() if code in kept_codes}
assert set(epochs_read.event_id) == kept_names
assert_allclose(epochs.times, epochs_read.times)
assert_allclose(epochs.get_data(), epochs_read.get_data())


@testing.requires_testing_data
@pytest.mark.parametrize("fmt", ("auto", "mff"))
@pytest.mark.parametrize("do_history", (True, False))
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