import pytest
from mne import pick_types, Annotations
from mne.annotations import events_from_annotations, read_annotations
from mne.datasets import testing
from mne.utils import requires_pandas
from mne.io import read_raw_edf, read_raw_bdf, read_raw_fif, edf, read_raw_gdf
from mne.io.tests.test_raw import _test_raw_reader
from mne.io.edf.edf import (_get_edf_default_event_id, _read_annotations_edf,
_read_ch, _parse_prefilter_string, _edf_str,
_read_edf_header, _read_header)
from mne.io.pick import channel_indices_by_type, get_channel_type_constants
from mne.tests.test_annotations import _assert_annotations_equal
td_mark = testing._pytest_mark()
FILE = inspect.getfile(inspect.currentframe())
data_dir = op.join(op.dirname(op.abspath(FILE)), 'data')
montage_path = op.join(data_dir, 'biosemi.hpts') # XXX: missing reader
bdf_path = op.join(data_dir, 'test.bdf')
edf_path = op.join(data_dir, 'test.edf')
duplicate_channel_labels_path = op.join(data_dir,
'duplicate_channel_labels.edf')
edf_uneven_path = op.join(data_dir, 'test_uneven_samp.edf')
bdf_eeglab_path = op.join(data_dir, 'test_bdf_eeglab.mat')
edf_eeglab_path = op.join(data_dir, 'test_edf_eeglab.mat')
edf_uneven_eeglab_path = op.join(data_dir, 'test_uneven_samp.mat')
edf_stim_channel_path = op.join(data_dir, 'test_edf_stim_channel.edf')
edf_txt_stim_channel_path = op.join(data_dir, 'test_edf_stim_channel.txt')
'204 Gradiometers', '102 Magnetometers', '9 Stimulus', '60 EEG',
'1 EOG'
]:
assert ch in html
@testing.requires_testing_data
def test_invalid_subject_birthday():
"""Test handling of an invalid birthday in the raw file."""
with pytest.warns(RuntimeWarning, match='No birthday will be set'):
raw = read_raw_fif(raw_invalid_bday_fname)
assert 'birthday' not in raw.info['subject_info']
@pytest.mark.parametrize('fname', [
pytest.param(ctf_fname, marks=testing._pytest_mark()),
raw_fname,
])
def test_channel_name_limit(tmp_path, monkeypatch, fname):
"""Test that our remapping works properly."""
#
# raw
#
if fname.endswith('fif'):
raw = read_raw_fif(fname)
raw.pick_channels(raw.ch_names[:3])
ref_names = []
data_names = raw.ch_names
else:
assert fname.endswith('.ds')
raw = read_raw_ctf(fname)
if renderer._get_3d_backend() == 'mayavi':
import mayavi # noqa: F401 analysis:ignore
assert isinstance(fig, mayavi.core.scene.Scene)
def _assert_n_actors(fig, renderer, n_actors):
__tracebackhide__ = True
if renderer._get_3d_backend() == 'mayavi':
return
assert len(fig.plotter.renderer.actors) == n_actors
@pytest.mark.slowtest # Slow for Mayavi on Azure
@pytest.mark.parametrize('system', [
'Neuromag',
pytest.param('CTF', marks=testing._pytest_mark()),
'BTi',
'KIT',
])
def test_plot_alignment_meg(renderer, system):
"""Test plotting of MEG sensors + helmet."""
if system == 'Neuromag':
this_info = read_info(evoked_fname)
elif system == 'CTF':
this_info = read_raw_ctf(ctf_fname).info
elif system == 'BTi':
this_info = read_raw_bti(pdf_fname,
config_fname,
hs_fname,
convert=True,
preload=False).info
@pytest.mark.parametrize('fname', ['x.xxx', 'x'])
def test_read_raw_unsupported(fname):
"""Test handling of unsupported file types."""
with pytest.raises(ValueError, match='Unsupported file type'):
read_raw(fname)
@pytest.mark.parametrize('fname', ['x.vmrk', 'x.eeg'])
def test_read_raw_suggested(fname):
"""Test handling of unsupported file types with suggested alternatives."""
with pytest.raises(ValueError, match='Try reading'):
read_raw(fname)
@pytest.mark.parametrize('fname', [
base / 'edf/tests/data/test.edf',
base / 'edf/tests/data/test.bdf',
base / 'brainvision/tests/data/test.vhdr',
base / 'kit/tests/data/test.sqd',
pytest.param(test_base / 'KIT/data_berlin.con',
marks=testing._pytest_mark()),
])
def test_read_raw_supported(fname):
"""Test supported file types."""
read_raw(fname)
read_raw(fname, verbose=False)
raw = read_raw(fname, preload=True)
assert "data loaded" in str(raw)
