# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import datetime as dt
import os
import shutil
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from mne import pick_types
from mne._fiff.constants import FIFF
from mne.datasets.testing import data_path, requires_testing_data
from mne.io import read_raw_nirx
from mne.io.tests.test_raw import _test_raw_reader
from mne.preprocessing import annotate_nan
from mne.preprocessing.nirs import (
_reorder_nirx,
short_channels,
source_detector_distances,
)
from mne.transforms import _get_trans, apply_trans
testing_path = data_path(download=False)
fname_nirx_15_0 = testing_path / "NIRx" / "nirscout" / "nirx_15_0_recording"
fname_nirx_15_2 = testing_path / "NIRx" / "nirscout" / "nirx_15_2_recording"
fname_nirx_15_2_short = (
testing_path / "NIRx" / "nirscout" / "nirx_15_2_recording_w_short"
)
fname_nirx_15_3_short = testing_path / "NIRx" / "nirscout" / "nirx_15_3_recording"
# This file has no saturated sections
nirsport1_wo_sat = (
testing_path / "NIRx" / "nirsport_v1" / "nirx_15_3_recording_wo_saturation"
)
# This file has saturation / but not on the optode pairing in montage
nirsport1_w_sat = (
testing_path
/ "NIRx"
/ "nirsport_v1"
/ "nirx_15_3_recording_w_saturation_not_on_montage_channels"
)
# This file has saturation in channels of interest
nirsport1_w_fullsat = (
testing_path
/ "NIRx"
/ "nirsport_v1"
/ "nirx_15_3_recording_w_saturation_on_montage_channels"
)
# NIRSport2 device using Aurora software
nirsport2 = testing_path / "NIRx" / "nirsport_v2" / "aurora_recording _w_short_and_acc"
nirsport2_2021_9 = testing_path / "NIRx" / "nirsport_v2" / "aurora_2021_9"
nirsport2_2021_9_6 = testing_path / "NIRx" / "nirsport_v2" / "aurora_2021_9_6"
def test_nirsport_v2_matches_snirf(nirx_snirf):
"""Test NIRSport2 raw files return same data as snirf."""
raw, raw_snirf = nirx_snirf
_reorder_nirx(raw_snirf)
assert raw.ch_names == raw_snirf.ch_names
assert_allclose(raw._data, raw_snirf._data)
# Check the timing of annotations match (naming is different)
assert_allclose(raw.annotations.onset, raw_snirf.annotations.onset)
assert_array_equal(raw.ch_names, raw_snirf.ch_names)
# This test fails as snirf encodes name incorrectly.
# assert raw.info["subject_info"]["first_name"] ==
# raw_snirf.info["subject_info"]["first_name"]
@requires_testing_data
@pytest.mark.filterwarnings("ignore:.*Extraction of measurement.*:")
def test_nirsport_v2():
"""Test NIRSport2 file."""
raw = read_raw_nirx(nirsport2, preload=True)
assert raw._data.shape == (40, 128)
# Test distance between optodes matches values from
# nirsite https://github.com/mne-tools/mne-testing-data/pull/86
# figure 3
allowed_distance_error = 0.005
assert_allclose(
source_detector_distances(raw.copy().pick("S1_D1 760").info),
[0.0304],
atol=allowed_distance_error,
)
assert_allclose(
source_detector_distances(raw.copy().pick("S2_D2 760").info),
[0.0400],
atol=allowed_distance_error,
)
# Test location of detectors
# The locations of detectors can be seen in the first
# figure on this page...
# https://github.com/mne-tools/mne-testing-data/pull/86
allowed_dist_error = 0.0002
locs = [ch["loc"][6:9] for ch in raw.info["chs"]]
head_mri_t, _ = _get_trans("fsaverage", "head", "mri")
mni_locs = apply_trans(head_mri_t, locs)
assert raw.info["ch_names"][0][3:5] == "D1"
assert_allclose(mni_locs[0], [-0.0841, -0.0464, -0.0129], atol=allowed_dist_error)
assert raw.info["ch_names"][2][3:5] == "D6"
assert_allclose(mni_locs[2], [-0.0841, -0.0138, 0.0248], atol=allowed_dist_error)
assert raw.info["ch_names"][34][3:5] == "D5"
assert_allclose(mni_locs[34], [0.0845, -0.0451, -0.0123], atol=allowed_dist_error)
# Test location of sensors
# The locations of sensors can be seen in the second
# figure on this page...
# https://github.com/mne-tools/mne-testing-data/pull/86
locs = [ch["loc"][3:6] for ch in raw.info["chs"]]
head_mri_t, _ = _get_trans("fsaverage", "head", "mri")
mni_locs = apply_trans(head_mri_t, locs)
assert raw.info["ch_names"][0][:2] == "S1"
assert_allclose(mni_locs[0], [-0.0848, -0.0162, -0.0163], atol=allowed_dist_error)
assert raw.info["ch_names"][9][:2] == "S2"
assert_allclose(mni_locs[9], [-0.0, -0.1195, 0.0142], atol=allowed_dist_error)
assert raw.info["ch_names"][39][:2] == "S8"
assert_allclose(mni_locs[34], [0.0828, -0.046, 0.0285], atol=allowed_dist_error)
assert len(raw.annotations) == 3
assert raw.annotations.description[0] == "1.0"
assert raw.annotations.description[2] == "6.0"
# Lose tolerance as I am eyeballing the time differences on screen
assert_allclose(np.diff(raw.annotations.onset), [2.3, 3.1], atol=0.1)
mon = raw.get_montage()
assert len(mon.dig) == 27
@requires_testing_data
@pytest.mark.filterwarnings("ignore:.*Extraction of measurement.*:")
def test_nirsport_v1_wo_sat():
"""Test NIRSport1 file with no saturation."""
raw = read_raw_nirx(nirsport1_wo_sat, preload=True)
# Test data import
assert raw._data.shape == (26, 164)
assert raw.info["sfreq"] == 10.416667
# By default real data is returned
assert np.sum(np.isnan(raw.get_data())) == 0
raw = read_raw_nirx(nirsport1_wo_sat, preload=True, saturated="nan")
data = raw.get_data()
assert data.shape == (26, 164)
assert np.sum(np.isnan(data)) == 0
raw = read_raw_nirx(nirsport1_wo_sat, saturated="annotate")
data = raw.get_data()
assert data.shape == (26, 164)
assert np.sum(np.isnan(data)) == 0
@pytest.mark.filterwarnings("ignore:.*Extraction of measurement.*:")
@requires_testing_data
def test_nirsport_v1_w_sat():
"""Test NIRSport1 file with NaNs but not in channel of interest."""
raw = read_raw_nirx(nirsport1_w_sat)
# Test data import
data = raw.get_data()
assert data.shape == (26, 176)
assert raw.info["sfreq"] == 10.416667
assert np.sum(np.isnan(data)) == 0
raw = read_raw_nirx(nirsport1_w_sat, saturated="nan")
data = raw.get_data()
assert data.shape == (26, 176)
assert np.sum(np.isnan(data)) == 0
raw = read_raw_nirx(nirsport1_w_sat, saturated="annotate")
data = raw.get_data()
assert data.shape == (26, 176)
assert np.sum(np.isnan(data)) == 0
@pytest.mark.filterwarnings("ignore:.*Extraction of measurement.*:")
@requires_testing_data
@pytest.mark.parametrize("preload", (True, False))
@pytest.mark.parametrize("meas_date", (None, "orig"))
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)
@requires_testing_data
def test_nirx_hdr_load():
"""Test reading NIRX files using path to header file."""
fname = fname_nirx_15_2_short / "NIRS-2019-08-23_001.hdr"
raw = read_raw_nirx(fname, preload=True)
# Test data import
assert raw._data.shape == (26, 145)
assert raw.info["sfreq"] == 12.5
@requires_testing_data
def test_nirx_missing_warn():
"""Test reading NIRX files when missing data."""
with pytest.raises(FileNotFoundError, match="does not exist"):
read_raw_nirx(fname_nirx_15_2_short / "1", preload=True)
@requires_testing_data
def test_nirx_missing_evt(tmp_path):
"""Test reading NIRX files when missing data."""
shutil.copytree(fname_nirx_15_2_short, str(tmp_path) + "/data/")
os.rename(
tmp_path / "data" / "NIRS-2019-08-23_001.evt",
tmp_path / "data" / "NIRS-2019-08-23_001.xxx",
)
fname = tmp_path / "data" / "NIRS-2019-08-23_001.hdr"
raw = read_raw_nirx(fname, preload=True)
assert raw.annotations.onset.shape == (0,)
@requires_testing_data
def test_nirx_dat_warn(tmp_path):
"""Test reading NIRX files when missing data."""
shutil.copytree(fname_nirx_15_2_short, str(tmp_path) + "/data/")
os.rename(
tmp_path / "data" / "NIRS-2019-08-23_001.dat",
tmp_path / "data" / "NIRS-2019-08-23_001.tmp",
)
fname = tmp_path / "data" / "NIRS-2019-08-23_001.hdr"
with pytest.warns(RuntimeWarning, match="A single dat"):
read_raw_nirx(fname, preload=True)
@requires_testing_data
def test_nirx_15_2_short():
"""Test reading NIRX files."""
raw = read_raw_nirx(fname_nirx_15_2_short, preload=True)
# Test data import
assert raw._data.shape == (26, 145)
assert raw.info["sfreq"] == 12.5
assert raw.info["meas_date"] == dt.datetime(
2019, 8, 23, 7, 37, 4, 540000, tzinfo=dt.timezone.utc
)
# Test channel naming
assert raw.info["ch_names"][:4] == [
"S1_D1 760",
"S1_D1 850",
"S1_D9 760",
"S1_D9 850",
]
assert raw.info["ch_names"][24:26] == ["S5_D13 760", "S5_D13 850"]
# Test frequency encoding
assert raw.info["chs"][0]["loc"][9] == 760
assert raw.info["chs"][1]["loc"][9] == 850
# Test info import
assert raw.info["subject_info"] == dict(
sex=1,
first_name="MNE",
middle_name="Test",
last_name="Recording",
birthday=dt.date(2014, 8, 23),
his_id="MNE_Test_Recording",
)
# Test distance between optodes matches values from
# nirsite https://github.com/mne-tools/mne-testing-data/pull/51
# step 4 figure 2
allowed_distance_error = 0.0002
assert_allclose(
source_detector_distances(raw.copy().pick("S1_D1 760").info),
[0.0304],
atol=allowed_distance_error,
)
assert_allclose(
source_detector_distances(raw.copy().pick("S2_D10 760").info),
[0.0086],
atol=allowed_distance_error,
)
# Test which channels are short
# These are the ones marked as red at
# https://github.com/mne-tools/mne-testing-data/pull/51 step 4 figure 2
is_short = short_channels(raw.info)
assert_array_equal(is_short[:9:2], [False, True, False, True, False])
is_short = short_channels(raw.info, threshold=0.003)
assert_array_equal(is_short[:3:2], [False, False])
is_short = short_channels(raw.info, threshold=50)
assert_array_equal(is_short[:3:2], [True, True])
# Test trigger events
assert_array_equal(raw.annotations.description, ["3.0", "2.0", "1.0"])
# Test location of detectors
# The locations of detectors can be seen in the first
# figure on this page...
# https://github.com/mne-tools/mne-testing-data/pull/51
# And have been manually copied below
# These values were reported in mm, but according to this page...
# https://mne.tools/stable/auto_tutorials/intro/plot_40_sensor_locations.html
# 3d locations should be specified in meters, so that's what's tested below
# Detector locations are stored in the third three loc values
allowed_dist_error = 0.0002
locs = [ch["loc"][6:9] for ch in raw.info["chs"]]
head_mri_t, _ = _get_trans("fsaverage", "head", "mri")
mni_locs = apply_trans(head_mri_t, locs)
assert raw.info["ch_names"][0][3:5] == "D1"
assert_allclose(mni_locs[0], [-0.0841, -0.0464, -0.0129], atol=allowed_dist_error)
assert raw.info["ch_names"][4][3:5] == "D3"
assert_allclose(mni_locs[4], [0.0846, -0.0142, -0.0156], atol=allowed_dist_error)
assert raw.info["ch_names"][8][3:5] == "D2"
assert_allclose(mni_locs[8], [0.0207, -0.1062, 0.0484], atol=allowed_dist_error)
assert raw.info["ch_names"][12][3:5] == "D4"
assert_allclose(mni_locs[12], [-0.0196, 0.0821, 0.0275], atol=allowed_dist_error)
assert raw.info["ch_names"][16][3:5] == "D5"
assert_allclose(mni_locs[16], [-0.0360, 0.0276, 0.0778], atol=allowed_dist_error)
assert raw.info["ch_names"][19][3:5] == "D6"
assert_allclose(mni_locs[19], [0.0352, 0.0283, 0.0780], atol=allowed_dist_error)
assert raw.info["ch_names"][21][3:5] == "D7"
assert_allclose(mni_locs[21], [0.0388, -0.0477, 0.0932], atol=allowed_dist_error)
@requires_testing_data
def test_nirx_15_3_short():
"""Test reading NIRX files."""
raw = read_raw_nirx(fname_nirx_15_3_short, preload=True)
# Test data import
assert raw._data.shape == (26, 220)
assert raw.info["sfreq"] == 12.5
# Test channel naming
assert raw.info["ch_names"][:4] == [
"S1_D2 760",
"S1_D2 850",
"S1_D9 760",
"S1_D9 850",
]
assert raw.info["ch_names"][24:26] == ["S5_D13 760", "S5_D13 850"]
# Test frequency encoding
assert raw.info["chs"][0]["loc"][9] == 760
assert raw.info["chs"][1]["loc"][9] == 850
# Test info import
assert raw.info["subject_info"] == dict(
birthday=dt.date(2020, 8, 18),
sex=0,
first_name="testMontage\\0ATestMontage",
his_id="testMontage\\0ATestMontage",
)
# Test distance between optodes matches values from
# https://github.com/mne-tools/mne-testing-data/pull/72
allowed_distance_error = 0.001
assert_allclose(
source_detector_distances(raw.copy().pick("S1_D2 760").info),
[0.0304],
atol=allowed_distance_error,
)
assert_allclose(
source_detector_distances(raw.copy().pick("S5_D13 760").info),
[0.0076],
atol=allowed_distance_error,
)
# Test which channels are short
# These are the ones marked as red at
# https://github.com/mne-tools/mne-testing-data/pull/72
is_short = short_channels(raw.info)
assert_array_equal(is_short[:9:2], [False, True, False, True, False])
is_short = short_channels(raw.info, threshold=0.003)
assert_array_equal(is_short[:3:2], [False, False])
is_short = short_channels(raw.info, threshold=50)
assert_array_equal(is_short[:3:2], [True, True])
# Test trigger events
assert_array_equal(raw.annotations.description, ["4.0", "2.0", "1.0"])
# Test location of detectors
# The locations of detectors can be seen in the first
# figure on this page...
# https://github.com/mne-tools/mne-testing-data/pull/72
# And have been manually copied below
allowed_dist_error = 0.0002
locs = [ch["loc"][6:9] for ch in raw.info["chs"]]
head_mri_t, _ = _get_trans("fsaverage", "head", "mri")
mni_locs = apply_trans(head_mri_t, locs)
assert raw.info["ch_names"][0][3:5] == "D2"
assert_allclose(mni_locs[0], [-0.0841, -0.0464, -0.0129], atol=allowed_dist_error)
assert raw.info["ch_names"][4][3:5] == "D1"
assert_allclose(mni_locs[4], [0.0846, -0.0142, -0.0156], atol=allowed_dist_error)
assert raw.info["ch_names"][8][3:5] == "D3"
assert_allclose(mni_locs[8], [0.0207, -0.1062, 0.0484], atol=allowed_dist_error)
assert raw.info["ch_names"][12][3:5] == "D4"
assert_allclose(mni_locs[12], [-0.0196, 0.0821, 0.0275], atol=allowed_dist_error)
assert raw.info["ch_names"][16][3:5] == "D5"
assert_allclose(mni_locs[16], [-0.0360, 0.0276, 0.0778], atol=allowed_dist_error)
assert raw.info["ch_names"][19][3:5] == "D6"
assert_allclose(mni_locs[19], [0.0388, -0.0477, 0.0932], atol=allowed_dist_error)
assert raw.info["ch_names"][21][3:5] == "D7"
assert_allclose(mni_locs[21], [-0.0394, -0.0483, 0.0928], atol=allowed_dist_error)
@requires_testing_data
def test_locale_encoding(tmp_path):
"""Test NIRx encoding."""
fname = tmp_path / "latin"
shutil.copytree(fname_nirx_15_2, fname)
hdr_fname = fname / "NIRS-2019-10-02_003.hdr"
hdr = list()
with open(hdr_fname, "rb") as fid:
hdr.extend(line for line in fid)
# French
hdr[2] = b'Date="jeu. 13 f\xe9vr. 2020"\r\n'
with open(hdr_fname, "wb") as fid:
for line in hdr:
fid.write(line)
read_raw_nirx(fname, verbose="debug")
# German
hdr[2] = b'Date="mi 13 dez 2020"\r\n'
with open(hdr_fname, "wb") as fid:
for line in hdr:
fid.write(line)
read_raw_nirx(fname, verbose="debug")
# Italian
hdr[2] = b'Date="ven 24 gen 2020"\r\n'
hdr[3] = b'Time="10:57:41.454"\r\n'
with open(hdr_fname, "wb") as fid:
for line in hdr:
fid.write(line)
raw = read_raw_nirx(fname, verbose="debug")
want_dt = dt.datetime(2020, 1, 24, 10, 57, 41, 454000, tzinfo=dt.timezone.utc)
assert raw.info["meas_date"] == want_dt
@requires_testing_data
def test_nirx_15_2():
"""Test reading NIRX files."""
raw = read_raw_nirx(fname_nirx_15_2, preload=True)
# Test data import
assert raw._data.shape == (64, 67)
assert raw.info["sfreq"] == 3.90625
assert raw.info["meas_date"] == dt.datetime(
2019, 10, 2, 9, 8, 47, 511000, tzinfo=dt.timezone.utc
)
# Test channel naming
assert raw.info["ch_names"][:4] == [
"S1_D1 760",
"S1_D1 850",
"S1_D10 760",
"S1_D10 850",
]
# Test info import
assert raw.info["subject_info"] == dict(
sex=1,
first_name="TestRecording",
birthday=dt.date(1989, 10, 2),
his_id="TestRecording",
)
# Test trigger events
assert_array_equal(raw.annotations.description, ["4.0", "6.0", "2.0"])
print(raw.annotations.onset)
# Test location of detectors
allowed_dist_error = 0.0002
locs = [ch["loc"][6:9] for ch in raw.info["chs"]]
head_mri_t, _ = _get_trans("fsaverage", "head", "mri")
mni_locs = apply_trans(head_mri_t, locs)
assert raw.info["ch_names"][0][3:5] == "D1"
assert_allclose(mni_locs[0], [-0.0292, 0.0852, -0.0142], atol=allowed_dist_error)
assert raw.info["ch_names"][15][3:5] == "D4"
assert_allclose(mni_locs[15], [-0.0739, -0.0756, -0.0075], atol=allowed_dist_error)
# Old name aliases for backward compat
assert "fnirs_cw_amplitude" in raw
with pytest.raises(ValueError, match="Invalid value"):
"fnirs_raw" in raw
assert "fnirs_od" not in raw
picks = pick_types(raw.info, fnirs="fnirs_cw_amplitude")
assert len(picks) > 0
@requires_testing_data
def test_nirx_aurora_2021_9_6():
"""Test reading NIRX files."""
raw = read_raw_nirx(nirsport2_2021_9_6, preload=True)
assert len(raw.annotations) == 3
assert raw.annotations.description[0] == "1.0"
assert raw.annotations.description[2] == "3.0"
@requires_testing_data
def test_nirx_15_0():
"""Test reading NIRX files."""
raw = read_raw_nirx(fname_nirx_15_0, preload=True)
# Test data import
assert raw._data.shape == (20, 92)
assert raw.info["sfreq"] == 6.25
assert raw.info["meas_date"] == dt.datetime(
2019, 10, 27, 13, 53, 34, 209000, tzinfo=dt.timezone.utc
)
# Test channel naming
assert raw.info["ch_names"][:12] == [
"S1_D1 760",
"S1_D1 850",
"S2_D2 760",
"S2_D2 850",
"S3_D3 760",
"S3_D3 850",
"S4_D4 760",
"S4_D4 850",
"S5_D5 760",
"S5_D5 850",
"S6_D6 760",
"S6_D6 850",
]
# Test info import
assert raw.info["subject_info"] == {
"birthday": dt.date(2004, 10, 27),
"first_name": "NIRX",
"last_name": "Test",
"sex": FIFF.FIFFV_SUBJ_SEX_UNKNOWN,
"his_id": "NIRX_Test",
}
# Test trigger events
assert_array_equal(raw.annotations.description, ["1.0", "2.0", "2.0"])
# Test location of detectors
allowed_dist_error = 0.0002
locs = [ch["loc"][6:9] for ch in raw.info["chs"]]
head_mri_t, _ = _get_trans("fsaverage", "head", "mri")
mni_locs = apply_trans(head_mri_t, locs)
assert raw.info["ch_names"][0][3:5] == "D1"
assert_allclose(mni_locs[0], [0.0287, -0.1143, -0.0332], atol=allowed_dist_error)
assert raw.info["ch_names"][15][3:5] == "D8"
assert_allclose(mni_locs[15], [-0.0693, -0.0480, 0.0657], atol=allowed_dist_error)
# Test distance between optodes matches values from
allowed_distance_error = 0.0002
assert_allclose(
source_detector_distances(raw.copy().pick("S1_D1 760").info),
[0.0300],
atol=allowed_distance_error,
)
assert_allclose(
source_detector_distances(raw.copy().pick("S7_D7 760").info),
[0.0392],
atol=allowed_distance_error,
)
@requires_testing_data
@pytest.mark.parametrize(
"fname, boundary_decimal",
(
[fname_nirx_15_2_short, 1],
[fname_nirx_15_2, 0],
[fname_nirx_15_2, 0],
[nirsport2_2021_9, 0],
),
)
def test_nirx_standard(fname, boundary_decimal):
"""Test standard operations."""
_test_raw_reader(
read_raw_nirx, fname=fname, boundary_decimal=boundary_decimal
) # low fs
# Below are the native (on-disk) orders, which should be preserved
@requires_testing_data
@pytest.mark.parametrize(
"fname, want_order",
[
(
fname_nirx_15_0,
[
"S1_D1",
"S2_D2",
"S3_D3",
"S4_D4",
"S5_D5",
"S6_D6",
"S7_D7",
"S8_D8",
"S9_D9",
"S10_D10",
],
), # noqa: E501
(
fname_nirx_15_2,
[
"S1_D1",
"S1_D10",
"S2_D1",
"S2_D2",
"S3_D2",
"S3_D3",
"S4_D3",
"S4_D4",
"S5_D4",
"S5_D5",
"S6_D5",
"S6_D6",
"S7_D6",
"S7_D7",
"S8_D7",
"S8_D8",
"S9_D8",
"S9_D9",
"S10_D9",
"S10_D10",
"S11_D11",
"S11_D12",
"S12_D12",
"S12_D13",
"S13_D13",
"S13_D14",
"S14_D14",
"S14_D15",
"S15_D15",
"S15_D16",
"S16_D11",
"S16_D16",
],
), # noqa: E501
(
fname_nirx_15_2_short,
[
"S1_D1",
"S1_D9",
"S2_D3",
"S2_D10",
"S3_D2",
"S3_D11",
"S4_D4",
"S4_D12",
"S5_D5",
"S5_D6",
"S5_D7",
"S5_D8",
"S5_D13",
],
), # noqa: E501
(
fname_nirx_15_3_short,
[
"S1_D2",
"S1_D9",
"S2_D1",
"S2_D10",
"S3_D3",
"S3_D11",
"S4_D4",
"S4_D12",
"S5_D5",
"S5_D6",
"S5_D7",
"S5_D8",
"S5_D13",
],
), # noqa: E501
(
nirsport1_wo_sat,
[
"S1_D4",
"S1_D5",
"S1_D6",
"S2_D5",
"S2_D6",
"S3_D5",
"S4_D1",
"S4_D3",
"S4_D4",
"S5_D1",
"S5_D2",
"S6_D1",
"S6_D3",
],
), # noqa: E501
(
nirsport2,
[
"S1_D1",
"S1_D6",
"S1_D9",
"S2_D2",
"S2_D10",
"S3_D5",
"S3_D7",
"S3_D11",
"S4_D8",
"S4_D12",
"S5_D3",
"S5_D13",
"S6_D4",
"S6_D14",
"S7_D1",
"S7_D6",
"S7_D15",
"S8_D5",
"S8_D7",
"S8_D16",
],
), # noqa: E501
(
nirsport2_2021_9,
[
"S1_D1",
"S1_D3",
"S2_D1",
"S2_D2",
"S2_D4",
"S3_D2",
"S3_D5",
"S4_D1",
"S4_D3",
"S4_D4",
"S4_D6",
"S5_D2",
"S5_D4",
"S5_D5",
"S5_D7",
"S6_D3",
"S6_D6",
"S7_D4",
"S7_D6",
"S7_D7",
"S8_D5",
"S8_D7",
],
), # noqa: E501
],
)
def test_channel_order(fname, want_order):
"""Test that logical channel order is preserved."""
raw = read_raw_nirx(fname)
ch_names = raw.ch_names
prefixes = [ch_name.split()[0] for ch_name in ch_names]
assert prefixes[::2] == prefixes[1::2]
prefixes = prefixes[::2]
assert prefixes == want_order
Datasets
Models
