def test_annotate_nan(meas_date):
"""Tests automatic NaN annotation generation."""
# Load data
raw = mne.io.read_raw_fif(raw_fname)
sfreq = 100
raw.resample(sfreq)
if meas_date is None:
raw.set_meas_date(None)
# No Nans, annotate returns empty annots
assert not np.isnan(raw._data).any()
annot_nan = annotate_nan(raw)
assert len(annot_nan) == 0
# but orig_time should be meas_date
assert annot_nan.orig_time == raw.info["meas_date"]
# insert block of NaN from 1s to 3s for one channel
nan_ch_idx = 0
raw._data[nan_ch_idx, 1 * sfreq:3 * sfreq] = np.nan
# annotate_nan accurately finds this
annot_nan = annotate_nan(raw)
onset = np.array([1.])
if raw.info["meas_date"]:
onset += raw.first_time
assert_array_equal(annot_nan.onset, onset)
assert_array_equal(annot_nan.duration, np.array([2]))
assert_array_equal(annot_nan.description, np.array(['BAD_NAN']))
assert len(annot_nan.ch_names) == 1
assert annot_nan.ch_names[0] == (raw.ch_names[nan_ch_idx], )
# Set the NaN annotations to the raw object
raw.set_annotations(annot_nan)
def test_nirsport_v1_w_bad_sat(preload, meas_date):
"""Test NIRSport1 file with NaNs."""
fname = nirsport1_w_fullsat
raw = read_raw_nirx(fname, preload=preload)
data = raw.get_data()
assert not np.isnan(data).any()
assert len(raw.annotations) == 5
# annotated version and ignore should have same data but different annot
raw_ignore = read_raw_nirx(fname, saturated='ignore', preload=preload)
assert_allclose(raw_ignore.get_data(), data)
assert len(raw_ignore.annotations) == 2
assert not any('NAN' in d for d in raw_ignore.annotations.description)
# nan version should not have same data, but we can give it the same annot
raw_nan = read_raw_nirx(fname, saturated='nan', preload=preload)
data_nan = raw_nan.get_data()
assert np.isnan(data_nan).any()
assert not np.allclose(raw_nan.get_data(), data)
raw_nan_annot = raw_ignore.copy()
if meas_date is None:
raw.set_meas_date(None)
raw_nan.set_meas_date(None)
raw_nan_annot.set_meas_date(None)
nan_annots = annotate_nan(raw_nan)
assert nan_annots.orig_time == raw_nan.info["meas_date"]
raw_nan_annot.set_annotations(nan_annots)
use_mask = np.where(raw.annotations.description == 'BAD_SATURATED')
for key in ('onset', 'duration'):
a = getattr(raw_nan_annot.annotations, key)[::2] # one ch in each
b = getattr(raw.annotations, key)[use_mask] # two chs in each
assert_allclose(a, b)