`mne.events_from_annotations` returns events that barely overlap with annotation

I noticed that mne.events_from_annotations sometimes returns events that barely even overlap with an actual annotation when chunk_duration is used. I think this might have been the actual reason behind the issue https://github.com/mne-tools/mne-python/issues/5684#issuecomment-438211200.

The issue seems to arise when an annotation has a duration that is only slightly over chunk_duration. A first event will cover almost the entire annotation, but a second annotation will be created that might start within the annotation, but will barely overlap with it. Because of that, in some rare cases, the second event is identical to the next annotation - causing mne.Epochs to throw an error due to duplicate events.

Steps and/or code to reproduce

import mne
import numpy as np


# Create fake data with annotations
data = np.random.randn(2, 16000)
info = mne.create_info(
    ch_names=['EEG1', 'EEG2'], ch_types=['eeg', 'eeg'], sfreq=256)
raw = mne.io.RawArray(data, info)

onset = [0, 30]
duration = [30.1, 30]
description = ['0', '0']
annots = mne.Annotations(onset, duration, description)
raw = raw.set_annotations(annots)

# Extract epochs
events, event_ids = mne.events_from_annotations(raw, chunk_duration=30)
epochs = mne.Epochs(
    raw, events, tmin=0, tmax=30, baseline=None, on_missing='warning')

Expected results

I would have expected events to contain two events only: one for the first annotation [0, 30.1] and one for the second [30, 60]. An option would be to have an argument that lets the user decide whether events need to completely overlap with the annotation to be returned.

Actual results

events is:

array([[   0,    0,    1],
       [7680,    0,    1],
       [7680,    0,    1]])

Because of the duplicate row, mne.Epochs returns RuntimeError: Event time samples were not unique.

Additional information

Platform:      Linux-4.17.13-041713-generic-x86_64-with-debian-buster-sid
Python:        3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 17:14:51)  [GCC 7.2.0]
Executable:    /home/hubert/miniconda3/envs/dl-eeg/bin/python
CPU:           x86_64: 4 cores
Memory:        15.6 GB

mne:           0.18.dev0
numpy:         1.16.0 {blas=openblas, lapack=openblas}
scipy:         1.1.0
matplotlib:    2.2.3 {backend=TkAgg}

sklearn:       0.20.2
nibabel:       Not found
mayavi:        4.6.2 {qt_api=pyqt5, PyQt5=5.11.3}
cupy:          Not found
pandas:        0.23.4
dipy:          Not found

[hubertjb]

@mmagnuski @agramfort Thanks again!

[hubertjb]

Thanks for looking at this @mmagnuski!