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"""Test reading of NEDF format."""
# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from mne import find_events
from mne._fiff.constants import FIFF
from mne.datasets import testing
from mne.io.nedf import _parse_nedf_header, read_raw_nedf
from mne.io.tests.test_raw import _test_raw_reader
eeg_path = testing.data_path(download=False, verbose=True)
eegfile = eeg_path / "nedf" / "testdata.nedf"
stimhdr = b"""
<nedf>
<NEDFversion>1.3</NEDFversion>
<NumberOfChannelsOfAccelerometer>%d</NumberOfChannelsOfAccelerometer>
<EEGSettings>
<TotalNumberOfChannels>4</TotalNumberOfChannels>
<EEGSamplingRate>500</EEGSamplingRate>
<EEGMontage><C>A</C><C>B</C><C>C</C><C>D</C></EEGMontage>
<NumberOfRecordsOfEEG>11</NumberOfRecordsOfEEG>
</EEGSettings>
<STIMSettings/>
</nedf>\x00"""
pytest.importorskip("defusedxml")
@pytest.mark.parametrize("nacc", (0, 3))
def test_nedf_header_parser(nacc):
"""Test NEDF header parsing and dtype extraction."""
with pytest.warns(RuntimeWarning, match="stim channels.*ignored"):
info, dt, dt_last, n_samples, n_full = _parse_nedf_header(stimhdr % nacc)
assert n_samples == 11
assert n_full == 2
nchan = 4
assert info["nchan"] == nchan
assert dt.itemsize == 200 + nacc * 2
if nacc:
assert dt.names[0] == "acc"
assert dt["acc"].shape == (nacc,)
assert dt["data"].shape == (5,) # blocks of 5 EEG samples each
assert dt_last["data"].shape == (1,) # plus one last extra one
eegsampledt = dt["data"].subdtype[0]
assert eegsampledt.names == ("eeg", "stim", "trig")
assert eegsampledt["eeg"].shape == (nchan, 3)
assert eegsampledt["stim"].shape == (2, nchan, 3)
def test_invalid_headers():
"""Test that invalid headers raise exceptions."""
tpl = b"""<nedf>
<NEDFversion>1.3</NEDFversion>
<EEGSettings>
%s
<EEGMontage><C>A</C><C>B</C><C>C</C><C>D</C></EEGMontage>
</EEGSettings>
</nedf>\x00"""
nchan = b"<TotalNumberOfChannels>4</TotalNumberOfChannels>"
sr = b"<EEGSamplingRate>500</EEGSamplingRate>"
hdr = {
"null": b"No null terminator",
"Unknown additional": (
b"<a><NEDFversion>1.3</NEDFversion>"
+ b"<AdditionalChannelStatus>???</AdditionalChannelStatus></a>\x00"
), # noqa: E501
"No EEG channels found": b"<a><NEDFversion>1.3</NEDFversion></a>\x00",
"TotalNumberOfChannels not found": tpl % b"No nchan.",
"!= channel count": tpl
% (sr + b"<TotalNumberOfChannels>52</TotalNumberOfChannels>"),
"EEGSamplingRate not found": tpl % nchan,
"NumberOfRecordsOfEEG not found": tpl % (sr + nchan),
}
for match, invalid_hdr in hdr.items():
with pytest.raises(RuntimeError, match=match):
_parse_nedf_header(invalid_hdr)
sus_hdrs = {
"unsupported": b"<a><NEDFversion>25</NEDFversion></a>\x00",
"tested": (
b"<a><NEDFversion>1.3</NEDFversion><stepDetails>"
+ b"<DeviceClass>STARSTIM</DeviceClass></stepDetails></a>\x00"
),
}
for match, sus_hdr in sus_hdrs.items():
with pytest.warns(RuntimeWarning, match=match):
with pytest.raises(RuntimeError, match="No EEG channels found"):
_parse_nedf_header(sus_hdr)
@testing.requires_testing_data
def test_nedf_data():
"""Test reading raw NEDF files."""
raw = read_raw_nedf(eegfile)
nsamples = len(raw)
assert nsamples == 32538
events = find_events(raw, shortest_event=1)
assert len(events) == 4
assert_array_equal(events[:, 2], [1, 1, 1, 1])
onsets = events[:, 0] / raw.info["sfreq"]
assert raw.info["sfreq"] == 500
data_end = raw.get_data("Fp1", nsamples - 100, nsamples).mean()
assert_allclose(data_end, 0.0176, atol=0.01)
assert_allclose(raw.get_data("Fpz", 0, 100).mean(), 0.0185, atol=0.01)
assert_allclose(onsets, [22.384, 38.238, 49.496, 63.15])
assert raw.info["meas_date"].year == 2019
assert raw.ch_names[2] == "AF7"
for ch in raw.info["chs"][:-1]:
assert ch["kind"] == FIFF.FIFFV_EEG_CH
assert ch["unit"] == FIFF.FIFF_UNIT_V
assert raw.info["chs"][-1]["kind"] == FIFF.FIFFV_STIM_CH
assert raw.info["chs"][-1]["unit"] == FIFF.FIFF_UNIT_V
# full tests
_test_raw_reader(read_raw_nedf, filename=eegfile)
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