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# Author: Teon Brooks <teon.brooks@gmail.com>
#
# License: BSD (3-clause)
import inspect
import os.path as op
import numpy as np
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal)
import pytest
from scipy import linalg
import scipy.io
import mne
from mne import pick_types, Epochs, find_events, read_events
from mne.datasets.testing import requires_testing_data
from mne.transforms import apply_trans
from mne.tests.common import assert_dig_allclose
from mne.utils import run_tests_if_main, _TempDir
from mne.io import read_raw_fif, read_raw_kit, read_epochs_kit
from mne.io.constants import FIFF
from mne.io.kit.coreg import read_sns
from mne.io.kit.constants import KIT
from mne.io.tests.test_raw import _test_raw_reader
from mne.surface import _get_ico_surface
FILE = inspect.getfile(inspect.currentframe())
parent_dir = op.dirname(op.abspath(FILE))
data_dir = op.join(parent_dir, 'data')
sqd_path = op.join(data_dir, 'test.sqd')
sqd_umd_path = op.join(data_dir, 'test_umd-raw.sqd')
epochs_path = op.join(data_dir, 'test-epoch.raw')
events_path = op.join(data_dir, 'test-eve.txt')
mrk_path = op.join(data_dir, 'test_mrk.sqd')
mrk2_path = op.join(data_dir, 'test_mrk_pre.sqd')
mrk3_path = op.join(data_dir, 'test_mrk_post.sqd')
elp_txt_path = op.join(data_dir, 'test_elp.txt')
hsp_txt_path = op.join(data_dir, 'test_hsp.txt')
elp_path = op.join(data_dir, 'test.elp')
hsp_path = op.join(data_dir, 'test.hsp')
data_path = mne.datasets.testing.data_path(download=False)
sqd_as_path = op.join(data_path, 'KIT', 'test_as-raw.con')
@requires_testing_data
def test_data():
"""Test reading raw kit files."""
pytest.raises(TypeError, read_raw_kit, epochs_path)
pytest.raises(TypeError, read_epochs_kit, sqd_path)
pytest.raises(ValueError, read_raw_kit, sqd_path, mrk_path, elp_txt_path)
pytest.raises(ValueError, read_raw_kit, sqd_path, None, None, None,
list(range(200, 190, -1)))
pytest.raises(ValueError, read_raw_kit, sqd_path, None, None, None,
list(range(167, 159, -1)), '*', 1, True)
# check functionality
raw_mrk = read_raw_kit(sqd_path, [mrk2_path, mrk3_path], elp_txt_path,
hsp_txt_path)
raw_py = _test_raw_reader(read_raw_kit, input_fname=sqd_path, mrk=mrk_path,
elp=elp_txt_path, hsp=hsp_txt_path,
stim=list(range(167, 159, -1)), slope='+',
stimthresh=1)
assert 'RawKIT' in repr(raw_py)
assert_equal(raw_mrk.info['kit_system_id'], KIT.SYSTEM_NYU_2010)
# check number/kind of channels
assert_equal(len(raw_py.info['chs']), 193)
kit_channels = (('kind', {FIFF.FIFFV_MEG_CH: 157, FIFF.FIFFV_REF_MEG_CH: 3,
FIFF.FIFFV_MISC_CH: 32, FIFF.FIFFV_STIM_CH: 1}),
('coil_type', {FIFF.FIFFV_COIL_KIT_GRAD: 157,
FIFF.FIFFV_COIL_KIT_REF_MAG: 3,
FIFF.FIFFV_COIL_NONE: 33}))
for label, target in kit_channels:
actual = {id_: sum(ch[label] == id_ for ch in raw_py.info['chs']) for
id_ in target.keys()}
assert_equal(actual, target)
# Test stim channel
raw_stim = read_raw_kit(sqd_path, mrk_path, elp_txt_path, hsp_txt_path,
stim='<', preload=False)
for raw in [raw_py, raw_stim, raw_mrk]:
stim_pick = pick_types(raw.info, meg=False, ref_meg=False,
stim=True, exclude='bads')
stim1, _ = raw[stim_pick]
stim2 = np.array(raw.read_stim_ch(), ndmin=2)
assert_array_equal(stim1, stim2)
# Binary file only stores the sensor channels
py_picks = pick_types(raw_py.info, exclude='bads')
raw_bin = op.join(data_dir, 'test_bin_raw.fif')
raw_bin = read_raw_fif(raw_bin, preload=True)
bin_picks = pick_types(raw_bin.info, stim=True, exclude='bads')
data_bin, _ = raw_bin[bin_picks]
data_py, _ = raw_py[py_picks]
# this .mat was generated using the Yokogawa MEG Reader
data_Ykgw = op.join(data_dir, 'test_Ykgw.mat')
data_Ykgw = scipy.io.loadmat(data_Ykgw)['data']
data_Ykgw = data_Ykgw[py_picks]
assert_array_almost_equal(data_py, data_Ykgw)
py_picks = pick_types(raw_py.info, stim=True, ref_meg=False,
exclude='bads')
data_py, _ = raw_py[py_picks]
assert_array_almost_equal(data_py, data_bin)
# KIT-UMD data
_test_raw_reader(read_raw_kit, input_fname=sqd_umd_path)
raw = read_raw_kit(sqd_umd_path)
assert_equal(raw.info['kit_system_id'], KIT.SYSTEM_UMD_2014_12)
# check number/kind of channels
assert_equal(len(raw.info['chs']), 193)
for label, target in kit_channels:
actual = {id_: sum(ch[label] == id_ for ch in raw.info['chs']) for
id_ in target.keys()}
assert_equal(actual, target)
# KIT Academia Sinica
raw = read_raw_kit(sqd_as_path, slope='+')
assert_equal(raw.info['kit_system_id'], KIT.SYSTEM_AS_2008)
assert_equal(raw.info['chs'][100]['ch_name'], 'MEG 101')
assert_equal(raw.info['chs'][100]['kind'], FIFF.FIFFV_MEG_CH)
assert_equal(raw.info['chs'][100]['coil_type'], FIFF.FIFFV_COIL_KIT_GRAD)
assert_equal(raw.info['chs'][157]['ch_name'], 'MEG 158')
assert_equal(raw.info['chs'][157]['kind'], FIFF.FIFFV_REF_MEG_CH)
assert_equal(raw.info['chs'][157]['coil_type'],
FIFF.FIFFV_COIL_KIT_REF_MAG)
assert_equal(raw.info['chs'][160]['ch_name'], 'EEG 001')
assert_equal(raw.info['chs'][160]['kind'], FIFF.FIFFV_EEG_CH)
assert_equal(raw.info['chs'][160]['coil_type'], FIFF.FIFFV_COIL_EEG)
assert_array_equal(find_events(raw), [[91, 0, 2]])
def test_epochs():
"""Test reading epoched SQD file."""
raw = read_raw_kit(sqd_path, stim=None)
events = read_events(events_path)
raw_epochs = Epochs(raw, events, None, tmin=0, tmax=.099, baseline=None)
data1 = raw_epochs.get_data()
epochs = read_epochs_kit(epochs_path, events_path)
data11 = epochs.get_data()
assert_array_equal(data1, data11)
def test_raw_events():
"""Test creating stim channel from raw SQD file."""
def evts(a, b, c, d, e, f=None):
out = [[269, a, b], [281, b, c], [1552, c, d], [1564, d, e]]
if f is not None:
out.append([2000, e, f])
return out
raw = read_raw_kit(sqd_path)
assert_array_equal(find_events(raw, output='step', consecutive=True),
evts(255, 254, 255, 254, 255, 0))
raw = read_raw_kit(sqd_path, slope='+')
assert_array_equal(find_events(raw, output='step', consecutive=True),
evts(0, 1, 0, 1, 0))
raw = read_raw_kit(sqd_path, stim='<', slope='+')
assert_array_equal(find_events(raw, output='step', consecutive=True),
evts(0, 128, 0, 128, 0))
raw = read_raw_kit(sqd_path, stim='<', slope='+', stim_code='channel')
assert_array_equal(find_events(raw, output='step', consecutive=True),
evts(0, 160, 0, 160, 0))
raw = read_raw_kit(sqd_path, stim=range(160, 162), slope='+',
stim_code='channel')
assert_array_equal(find_events(raw, output='step', consecutive=True),
evts(0, 160, 0, 160, 0))
def test_ch_loc():
"""Test raw kit loc."""
raw_py = read_raw_kit(sqd_path, mrk_path, elp_txt_path, hsp_txt_path,
stim='<')
raw_bin = read_raw_fif(op.join(data_dir, 'test_bin_raw.fif'))
ch_py = np.array([ch['loc'] for ch in
raw_py._raw_extras[0]['channels'][:160]])
# ch locs stored as m, not mm
ch_py[:, :3] *= 1e3
ch_sns = read_sns(op.join(data_dir, 'sns.txt'))
assert_array_almost_equal(ch_py, ch_sns, 2)
assert_array_almost_equal(raw_py.info['dev_head_t']['trans'],
raw_bin.info['dev_head_t']['trans'], 4)
for py_ch, bin_ch in zip(raw_py.info['chs'], raw_bin.info['chs']):
if bin_ch['ch_name'].startswith('MEG'):
# the stored ch locs have more precision than the sns.txt
assert_array_almost_equal(py_ch['loc'], bin_ch['loc'], decimal=2)
# test when more than one marker file provided
mrks = [mrk_path, mrk2_path, mrk3_path]
read_raw_kit(sqd_path, mrks, elp_txt_path, hsp_txt_path, preload=False)
# this dataset does not have the equivalent set of points :(
raw_bin.info['dig'] = raw_bin.info['dig'][:8]
raw_py.info['dig'] = raw_py.info['dig'][:8]
assert_dig_allclose(raw_py.info, raw_bin.info)
def test_hsp_elp():
"""Test KIT usage of *.elp and *.hsp files against *.txt files."""
raw_txt = read_raw_kit(sqd_path, mrk_path, elp_txt_path, hsp_txt_path)
raw_elp = read_raw_kit(sqd_path, mrk_path, elp_path, hsp_path)
# head points
pts_txt = np.array([dig_point['r'] for dig_point in raw_txt.info['dig']])
pts_elp = np.array([dig_point['r'] for dig_point in raw_elp.info['dig']])
assert_array_almost_equal(pts_elp, pts_txt, decimal=5)
# transforms
trans_txt = raw_txt.info['dev_head_t']['trans']
trans_elp = raw_elp.info['dev_head_t']['trans']
assert_array_almost_equal(trans_elp, trans_txt, decimal=5)
# head points in device space
pts_txt_in_dev = apply_trans(linalg.inv(trans_txt), pts_txt)
pts_elp_in_dev = apply_trans(linalg.inv(trans_elp), pts_elp)
assert_array_almost_equal(pts_elp_in_dev, pts_txt_in_dev, decimal=5)
def test_decimate():
"""Test decimation of digitizer headshapes with too many points."""
# load headshape and convert to meters
hsp_mm = _get_ico_surface(5)['rr'] * 100
hsp_m = hsp_mm / 1000.
# save headshape to a file in mm in temporary directory
tempdir = _TempDir()
sphere_hsp_path = op.join(tempdir, 'test_sphere.txt')
np.savetxt(sphere_hsp_path, hsp_mm)
# read in raw data using spherical hsp, and extract new hsp
with pytest.warns(RuntimeWarning,
match='was automatically downsampled .* FastScan'):
raw = read_raw_kit(sqd_path, mrk_path, elp_txt_path, sphere_hsp_path)
# collect headshape from raw (should now be in m)
hsp_dec = np.array([dig['r'] for dig in raw.info['dig']])[8:]
# with 10242 points and _decimate_points set to resolution of 5 mm, hsp_dec
# should be a bit over 5000 points. If not, something is wrong or
# decimation resolution has been purposefully changed
assert len(hsp_dec) > 5000
# should have similar size, distance from center
dist = np.sqrt(np.sum((hsp_m - np.mean(hsp_m, axis=0))**2, axis=1))
dist_dec = np.sqrt(np.sum((hsp_dec - np.mean(hsp_dec, axis=0))**2, axis=1))
hsp_rad = np.mean(dist)
hsp_dec_rad = np.mean(dist_dec)
assert_array_almost_equal(hsp_rad, hsp_dec_rad, decimal=3)
run_tests_if_main()
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