def test_flat_acq_skip():
"""Test that acquisition skips are handled properly."""
raw = read_raw_fif(skip_fname).load_data()
n_annot = len(raw.annotations)
mark_flat(raw)
assert len(raw.annotations) == n_annot
assert raw.info['bads'] == [ # MaxFilter finds the same 21 channels
'MEG%04d' % (int(num), )
for num in '141 331 421 431 611 641 1011 1021 1031 1241 1421 '
'1741 1841 2011 2131 2141 2241 2531 2541 2611 2621'.split()
]
def test_annotate_flat(first_samp):
"""Test marking flat segments."""
# Test if ECG analysis will work on data that is not preloaded
n_ch, n_times = 11, 1000
data = np.random.RandomState(0).randn(n_ch, n_times)
assert not (np.diff(data, axis=-1) == 0).any() # nothing flat at first
info = create_info(n_ch, 1000., 'eeg')
info['meas_date'] = (1, 2)
# test first_samp != for gh-6295
raw = RawArray(data, info, first_samp=first_samp)
raw.info['bads'] = [raw.ch_names[-1]]
#
# First make a channel flat the whole time
#
raw_0 = raw.copy()
raw_0._data[0] = 0.
for kwargs, bads, want_times in [
# Anything < 1 will mark spatially
(dict(bad_percent=100.), [], 0),
(dict(bad_percent=99.9), [raw.ch_names[0]], n_times),
(dict(), [raw.ch_names[0]], n_times)
]: # default (1)
raw_time = raw_0.copy()
annot, got_bads = annotate_flat(raw_0, verbose='debug', **kwargs)
assert got_bads == bads
raw_time.set_annotations(raw_time.annotations + annot)
raw_time.info['bads'] += got_bads
n_good_times = raw_time.get_data(reject_by_annotation='omit').shape[1]
assert n_good_times == want_times
with pytest.deprecated_call(match='annotate_flat'):
raw_time_2 = mark_flat(raw_0.copy(), verbose='debug', **kwargs)
_assert_annotations_equal(raw_time_2.annotations, raw_time.annotations)
assert raw_time_2.info['bads'] == raw_time.info['bads']
#
# Now make a channel flat for 20% of the time points
#
raw_0 = raw.copy()
n_good_times = int(round(0.8 * n_times))
raw_0._data[0, n_good_times:] = 0.
threshold = 100 * (n_times - n_good_times) / n_times
for kwargs, bads, want_times in [
# Should change behavior at bad_percent=20
(dict(bad_percent=100), [], n_good_times),
(dict(bad_percent=threshold), [], n_good_times),
(dict(bad_percent=threshold - 1e-5), [raw.ch_names[0]], n_times),
(dict(), [raw.ch_names[0]], n_times)
]:
annot, got_bads = annotate_flat(raw_0, verbose='debug', **kwargs)
assert got_bads == bads
raw_time = raw_0.copy()
raw_time.set_annotations(raw_time.annotations + annot)
raw_time.info['bads'] += got_bads
n_good_times = raw_time.get_data(reject_by_annotation='omit').shape[1]
assert n_good_times == want_times
with pytest.raises(TypeError, match='must be an instance of BaseRaw'):
annotate_flat(0.)
with pytest.raises(ValueError, match='not convert string to float'):
annotate_flat(raw, 'x')
def test_mark_flat(first_samp):
"""Test marking flat segments."""
# Test if ECG analysis will work on data that is not preloaded
n_ch, n_times = 11, 1000
data = np.random.RandomState(0).randn(n_ch, n_times)
assert not (np.diff(data, axis=-1) == 0).any() # nothing flat at first
info = create_info(n_ch, 1000., 'eeg')
info['meas_date'] = (1, 2)
# test first_samp != for gh-6295
raw = RawArray(data, info, first_samp=first_samp)
raw.info['bads'] = [raw.ch_names[-1]]
#
# First make a channel flat the whole time
#
raw_0 = raw.copy()
raw_0._data[0] = 0.
for kwargs, bads, want_times in [
# Anything < 1 will mark spatially
(dict(bad_percent=100.), [], 0),
(dict(bad_percent=99.9), [raw.ch_names[0]], n_times),
(dict(), [raw.ch_names[0]], n_times)]: # default (1)
raw_time = mark_flat(raw_0.copy(), verbose='debug', **kwargs)
want_bads = raw.info['bads'] + bads
assert raw_time.info['bads'] == want_bads
n_good_times = raw_time.get_data(reject_by_annotation='omit').shape[1]
assert n_good_times == want_times
#
# Now make a channel flat for 20% of the time points
#
raw_0 = raw.copy()
n_good_times = int(round(0.8 * n_times))
raw_0._data[0, n_good_times:] = 0.
threshold = 100 * (n_times - n_good_times) / n_times
for kwargs, bads, want_times in [
# Should change behavior at bad_percent=20
(dict(bad_percent=100), [], n_good_times),
(dict(bad_percent=threshold), [], n_good_times),
(dict(bad_percent=threshold - 1e-5), [raw.ch_names[0]], n_times),
(dict(), [raw.ch_names[0]], n_times)]:
raw_time = mark_flat(raw_0.copy(), verbose='debug', **kwargs)
want_bads = raw.info['bads'] + bads
assert raw_time.info['bads'] == want_bads
n_good_times = raw_time.get_data(reject_by_annotation='omit').shape[1]
assert n_good_times == want_times
with pytest.raises(TypeError, match='must be an instance of BaseRaw'):
mark_flat(0.)
with pytest.raises(ValueError, match='not convert string to float'):
mark_flat(raw, 'x')