/
eog.py
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/
eog.py
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# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
import numpy as np
from ._peak_finder import peak_finder
from .. import pick_types, pick_channels
from ..utils import logger, verbose, _pl, _validate_type
from ..filter import filter_data
from ..epochs import Epochs
@verbose
def find_eog_events(raw, event_id=998, l_freq=1, h_freq=10,
filter_length='10s', ch_name=None, tstart=0,
reject_by_annotation=False, thresh=None, verbose=None):
"""Locate EOG artifacts.
.. note:: To control true-positive and true-negative detection rates, you
may adjust the ``thresh`` parameter.
Parameters
----------
raw : instance of Raw
The raw data.
event_id : int
The index to assign to found events.
l_freq : float
Low cut-off frequency to apply to the EOG channel in Hz.
h_freq : float
High cut-off frequency to apply to the EOG channel in Hz.
filter_length : str | int | None
Number of taps to use for filtering.
%(ch_name_eog)s
tstart : float
Start detection after tstart seconds.
reject_by_annotation : bool
Whether to omit data that is annotated as bad.
thresh : float | None
Threshold to trigger the detection of an EOG event. This controls the
thresholding of the underlying peak-finding algorithm. Larger values
mean that fewer peaks (i.e., fewer EOG events) will be detected.
If ``None``, use the default of ``(max(eog) - min(eog)) / 4``,
with ``eog`` being the filtered EOG signal.
%(verbose)s
Returns
-------
eog_events : array
Events.
See Also
--------
create_eog_epochs
compute_proj_eog
"""
# Getting EOG Channel
eog_inds = _get_eog_channel_index(ch_name, raw)
logger.info('EOG channel index for this subject is: %s' % eog_inds)
# Reject bad segments.
reject_by_annotation = 'omit' if reject_by_annotation else None
eog, times = raw.get_data(picks=eog_inds,
reject_by_annotation=reject_by_annotation,
return_times=True)
times = times * raw.info['sfreq'] + raw.first_samp
eog_events = _find_eog_events(eog, event_id=event_id, l_freq=l_freq,
h_freq=h_freq,
sampling_rate=raw.info['sfreq'],
first_samp=raw.first_samp,
filter_length=filter_length,
tstart=tstart, thresh=thresh,
verbose=verbose)
# Map times to corresponding samples.
eog_events[:, 0] = np.round(times[eog_events[:, 0] -
raw.first_samp]).astype(int)
return eog_events
@verbose
def _find_eog_events(eog, event_id, l_freq, h_freq, sampling_rate, first_samp,
filter_length='10s', tstart=0., thresh=None,
verbose=None):
"""Find EOG events."""
logger.info('Filtering the data to remove DC offset to help '
'distinguish blinks from saccades')
# filtering to remove dc offset so that we know which is blink and saccades
# hardcode verbose=False to suppress filter param messages (since this
# filter is not under user control)
fmax = np.minimum(45, sampling_rate / 2.0 - 0.75) # protect Nyquist
filteog = np.array([filter_data(
x, sampling_rate, 2, fmax, None, filter_length, 0.5, 0.5,
phase='zero-double', fir_window='hann', fir_design='firwin2',
verbose=False) for x in eog])
temp = np.sqrt(np.sum(filteog ** 2, axis=1))
indexmax = np.argmax(temp)
# easier to detect peaks with filtering.
filteog = filter_data(
eog[indexmax], sampling_rate, l_freq, h_freq, None,
filter_length, 0.5, 0.5, phase='zero-double', fir_window='hann',
fir_design='firwin2')
# detecting eog blinks and generating event file
logger.info('Now detecting blinks and generating corresponding events')
temp = filteog - np.mean(filteog)
n_samples_start = int(sampling_rate * tstart)
if np.abs(np.max(temp)) > np.abs(np.min(temp)):
eog_events, _ = peak_finder(filteog[n_samples_start:],
thresh, extrema=1)
else:
eog_events, _ = peak_finder(filteog[n_samples_start:],
thresh, extrema=-1)
eog_events += n_samples_start
n_events = len(eog_events)
logger.info(f'Number of EOG events detected: {n_events}')
eog_events = np.array([eog_events + first_samp,
np.zeros(n_events, int),
event_id * np.ones(n_events, int)]).T
return eog_events
def _get_eog_channel_index(ch_name, inst):
"""Get EOG channel indices."""
_validate_type(ch_name, types=(None, str, list), item_name='ch_name')
if ch_name is None:
eog_inds = pick_types(inst.info, meg=False, eeg=False, stim=False,
eog=True, ecg=False, emg=False, ref_meg=False,
exclude='bads')
if eog_inds.size == 0:
raise RuntimeError('No EOG channel(s) found')
ch_names = [inst.ch_names[i] for i in eog_inds]
elif isinstance(ch_name, str):
ch_names = [ch_name]
else: # it's a list
ch_names = ch_name.copy()
# ensure the specified channels are present in the data
if ch_name is not None:
not_found = [ch_name for ch_name in ch_names
if ch_name not in inst.ch_names]
if not_found:
raise ValueError(f'The specified EOG channel{_pl(not_found)} '
f'cannot be found: {", ".join(not_found)}')
eog_inds = pick_channels(inst.ch_names, include=ch_names)
logger.info(f'Using EOG channel{_pl(ch_names)}: {", ".join(ch_names)}')
return eog_inds
@verbose
def create_eog_epochs(raw, ch_name=None, event_id=998, picks=None, tmin=-0.5,
tmax=0.5, l_freq=1, h_freq=10, reject=None, flat=None,
baseline=None, preload=True, reject_by_annotation=True,
thresh=None, decim=1, verbose=None):
"""Conveniently generate epochs around EOG artifact events.
%(create_eog_epochs)s
Parameters
----------
raw : instance of Raw
The raw data.
%(ch_name_eog)s
event_id : int
The index to assign to found events.
%(picks_all)s
tmin : float
Start time before event.
tmax : float
End time after event.
l_freq : float
Low pass frequency to apply to the EOG channel while finding events.
h_freq : float
High pass frequency to apply to the EOG channel while finding events.
reject : dict | None
Rejection parameters based on peak-to-peak amplitude.
Valid keys are 'grad' | 'mag' | 'eeg' | 'eog' | 'ecg'.
If reject is None then no rejection is done. Example::
reject = dict(grad=4000e-13, # T / m (gradiometers)
mag=4e-12, # T (magnetometers)
eeg=40e-6, # V (EEG channels)
eog=250e-6 # V (EOG channels)
)
flat : dict | None
Rejection parameters based on flatness of signal.
Valid keys are 'grad' | 'mag' | 'eeg' | 'eog' | 'ecg', and values
are floats that set the minimum acceptable peak-to-peak amplitude.
If flat is None then no rejection is done.
baseline : tuple or list of length 2, or None
The time interval to apply rescaling / baseline correction.
If None do not apply it. If baseline is (a, b)
the interval is between "a (s)" and "b (s)".
If a is None the beginning of the data is used
and if b is None then b is set to the end of the interval.
If baseline is equal to (None, None) all the time
interval is used. If None, no correction is applied.
preload : bool
Preload epochs or not.
%(reject_by_annotation_epochs)s
.. versionadded:: 0.14.0
thresh : float
Threshold to trigger EOG event.
%(decim)s
.. versionadded:: 0.21.0
%(verbose)s
Returns
-------
eog_epochs : instance of Epochs
Data epoched around EOG events.
See Also
--------
find_eog_events
compute_proj_eog
Notes
-----
Filtering is only applied to the EOG channel while finding events.
The resulting ``eog_epochs`` will have no filtering applied (i.e., have
the same filter properties as the input ``raw`` instance).
"""
events = find_eog_events(raw, ch_name=ch_name, event_id=event_id,
l_freq=l_freq, h_freq=h_freq,
reject_by_annotation=reject_by_annotation,
thresh=thresh)
# create epochs around EOG events
eog_epochs = Epochs(raw, events=events, event_id=event_id, tmin=tmin,
tmax=tmax, proj=False, reject=reject, flat=flat,
picks=picks, baseline=baseline, preload=preload,
reject_by_annotation=reject_by_annotation,
decim=decim)
return eog_epochs