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|
import os.path as op
import os
import numpy as np
from numpy.testing import (assert_array_almost_equal, assert_array_equal,
assert_equal, assert_allclose)
import pytest
from mne import (read_events, write_events, make_fixed_length_events,
find_events, pick_events, find_stim_steps, pick_channels,
read_evokeds, Epochs, create_info, compute_raw_covariance)
from mne.io import read_raw_fif, RawArray
from mne.utils import _TempDir, run_tests_if_main
from mne.event import define_target_events, merge_events, AcqParserFIF
from mne.datasets import testing
base_dir = op.join(op.dirname(__file__), '..', 'io', 'tests', 'data')
fname = op.join(base_dir, 'test-eve.fif')
fname_gz = op.join(base_dir, 'test-eve.fif.gz')
fname_1 = op.join(base_dir, 'test-1-eve.fif')
fname_txt = op.join(base_dir, 'test-eve.eve')
fname_txt_1 = op.join(base_dir, 'test-eve-1.eve')
# for testing Elekta averager
elekta_base_dir = op.join(testing.data_path(download=False), 'misc')
fname_raw_elekta = op.join(elekta_base_dir, 'test_elekta_3ch_raw.fif')
fname_ave_elekta = op.join(elekta_base_dir, 'test_elekta-ave.fif')
# using mne_process_raw --raw test_raw.fif --eventsout test-mpr-eve.eve:
fname_txt_mpr = op.join(base_dir, 'test-mpr-eve.eve')
fname_old_txt = op.join(base_dir, 'test-eve-old-style.eve')
raw_fname = op.join(base_dir, 'test_raw.fif')
def test_fix_stim():
"""Test fixing stim STI016 for Neuromag."""
raw = read_raw_fif(raw_fname, preload=True)
# 32768 (016) + 3 (002+001) bits gets incorrectly coded during acquisition
raw._data[raw.ch_names.index('STI 014'), :3] = [0, -32765, 0]
with pytest.warns(RuntimeWarning, match='STI016'):
events = find_events(raw, 'STI 014')
assert_array_equal(events[0], [raw.first_samp + 1, 0, 32765])
events = find_events(raw, 'STI 014', uint_cast=True)
assert_array_equal(events[0], [raw.first_samp + 1, 0, 32771])
def test_add_events():
"""Test adding events to a Raw file."""
# need preload
raw = read_raw_fif(raw_fname)
events = np.array([[raw.first_samp, 0, 1]])
pytest.raises(RuntimeError, raw.add_events, events, 'STI 014')
raw = read_raw_fif(raw_fname, preload=True)
orig_events = find_events(raw, 'STI 014')
# add some events
events = np.array([raw.first_samp, 0, 1])
pytest.raises(ValueError, raw.add_events, events, 'STI 014') # bad shape
events[0] = raw.first_samp + raw.n_times + 1
events = events[np.newaxis, :]
pytest.raises(ValueError, raw.add_events, events, 'STI 014') # bad time
events[0, 0] = raw.first_samp - 1
pytest.raises(ValueError, raw.add_events, events, 'STI 014') # bad time
events[0, 0] = raw.first_samp + 1 # can't actually be first_samp
pytest.raises(ValueError, raw.add_events, events, 'STI FOO')
raw.add_events(events, 'STI 014')
new_events = find_events(raw, 'STI 014')
assert_array_equal(new_events, np.concatenate((events, orig_events)))
raw.add_events(events, 'STI 014', replace=True)
new_events = find_events(raw, 'STI 014')
assert_array_equal(new_events, events)
def test_merge_events():
"""Test event merging."""
events_orig = [[1, 0, 1], [3, 0, 2], [10, 0, 3], [20, 0, 4]]
events_replacement = \
[[1, 0, 12],
[3, 0, 12],
[10, 0, 34],
[20, 0, 34]]
events_no_replacement = \
[[1, 0, 1],
[1, 0, 12],
[1, 0, 1234],
[3, 0, 2],
[3, 0, 12],
[3, 0, 1234],
[10, 0, 3],
[10, 0, 34],
[10, 0, 1234],
[20, 0, 4],
[20, 0, 34],
[20, 0, 1234]]
for replace_events, events_good in [(True, events_replacement),
(False, events_no_replacement)]:
events = merge_events(events_orig, [1, 2], 12, replace_events)
events = merge_events(events, [3, 4], 34, replace_events)
events = merge_events(events, [1, 2, 3, 4], 1234, replace_events)
assert_array_equal(events, events_good)
def test_io_events():
"""Test IO for events."""
tempdir = _TempDir()
# Test binary fif IO
events = read_events(fname) # Use as the gold standard
write_events(op.join(tempdir, 'events-eve.fif'), events)
events2 = read_events(op.join(tempdir, 'events-eve.fif'))
assert_array_almost_equal(events, events2)
# Test binary fif.gz IO
events2 = read_events(fname_gz) # Use as the gold standard
assert_array_almost_equal(events, events2)
write_events(op.join(tempdir, 'events-eve.fif.gz'), events2)
events2 = read_events(op.join(tempdir, 'events-eve.fif.gz'))
assert_array_almost_equal(events, events2)
# Test new format text file IO
write_events(op.join(tempdir, 'events.eve'), events)
events2 = read_events(op.join(tempdir, 'events.eve'))
assert_array_almost_equal(events, events2)
with pytest.warns(RuntimeWarning, match='first row of'):
events2 = read_events(fname_txt_mpr, mask=0, mask_type='not_and')
assert_array_almost_equal(events, events2)
# Test old format text file IO
events2 = read_events(fname_old_txt)
assert_array_almost_equal(events, events2)
write_events(op.join(tempdir, 'events.eve'), events)
events2 = read_events(op.join(tempdir, 'events.eve'))
assert_array_almost_equal(events, events2)
# Test event selection
a = read_events(op.join(tempdir, 'events-eve.fif'), include=1)
b = read_events(op.join(tempdir, 'events-eve.fif'), include=[1])
c = read_events(op.join(tempdir, 'events-eve.fif'),
exclude=[2, 3, 4, 5, 32])
d = read_events(op.join(tempdir, 'events-eve.fif'), include=1,
exclude=[2, 3])
assert_array_equal(a, b)
assert_array_equal(a, c)
assert_array_equal(a, d)
# test reading file with mask=None
events2 = events.copy()
events2[:, -1] = range(events2.shape[0])
write_events(op.join(tempdir, 'events-eve.fif'), events2)
events3 = read_events(op.join(tempdir, 'events-eve.fif'), mask=None)
assert_array_almost_equal(events2, events3)
# Test binary file IO for 1 event
events = read_events(fname_1) # Use as the new gold standard
write_events(op.join(tempdir, 'events-eve.fif'), events)
events2 = read_events(op.join(tempdir, 'events-eve.fif'))
assert_array_almost_equal(events, events2)
# Test text file IO for 1 event
write_events(op.join(tempdir, 'events.eve'), events)
events2 = read_events(op.join(tempdir, 'events.eve'))
assert_array_almost_equal(events, events2)
# test warnings on bad filenames
fname2 = op.join(tempdir, 'test-bad-name.fif')
with pytest.warns(RuntimeWarning, match='-eve.fif'):
write_events(fname2, events)
with pytest.warns(RuntimeWarning, match='-eve.fif'):
read_events(fname2)
def test_find_events():
"""Test find events in raw file."""
events = read_events(fname)
raw = read_raw_fif(raw_fname, preload=True)
# let's test the defaulting behavior while we're at it
extra_ends = ['', '_1']
orig_envs = [os.getenv('MNE_STIM_CHANNEL%s' % s) for s in extra_ends]
os.environ['MNE_STIM_CHANNEL'] = 'STI 014'
if 'MNE_STIM_CHANNEL_1' in os.environ:
del os.environ['MNE_STIM_CHANNEL_1']
events2 = find_events(raw)
assert_array_almost_equal(events, events2)
# now test with mask
events11 = find_events(raw, mask=3, mask_type='not_and')
with pytest.warns(RuntimeWarning, match='events masked'):
events22 = read_events(fname, mask=3, mask_type='not_and')
assert_array_equal(events11, events22)
# Reset some data for ease of comparison
raw._first_samps[0] = 0
raw.info['sfreq'] = 1000
raw._update_times()
stim_channel = 'STI 014'
stim_channel_idx = pick_channels(raw.info['ch_names'],
include=[stim_channel])
# test digital masking
raw._data[stim_channel_idx, :5] = np.arange(5)
raw._data[stim_channel_idx, 5:] = 0
# 1 == '0b1', 2 == '0b10', 3 == '0b11', 4 == '0b100'
pytest.raises(TypeError, find_events, raw, mask="0", mask_type='and')
pytest.raises(ValueError, find_events, raw, mask=0, mask_type='blah')
# testing mask_type. default = 'not_and'
assert_array_equal(find_events(raw, shortest_event=1, mask=1,
mask_type='not_and'),
[[2, 0, 2], [4, 2, 4]])
assert_array_equal(find_events(raw, shortest_event=1, mask=2,
mask_type='not_and'),
[[1, 0, 1], [3, 0, 1], [4, 1, 4]])
assert_array_equal(find_events(raw, shortest_event=1, mask=3,
mask_type='not_and'),
[[4, 0, 4]])
assert_array_equal(find_events(raw, shortest_event=1, mask=4,
mask_type='not_and'),
[[1, 0, 1], [2, 1, 2], [3, 2, 3]])
# testing with mask_type = 'and'
assert_array_equal(find_events(raw, shortest_event=1, mask=1,
mask_type='and'),
[[1, 0, 1], [3, 0, 1]])
assert_array_equal(find_events(raw, shortest_event=1, mask=2,
mask_type='and'),
[[2, 0, 2]])
assert_array_equal(find_events(raw, shortest_event=1, mask=3,
mask_type='and'),
[[1, 0, 1], [2, 1, 2], [3, 2, 3]])
assert_array_equal(find_events(raw, shortest_event=1, mask=4,
mask_type='and'),
[[4, 0, 4]])
# test empty events channel
raw._data[stim_channel_idx, :] = 0
assert_array_equal(find_events(raw), np.empty((0, 3), dtype='int32'))
raw._data[stim_channel_idx, :4] = 1
assert_array_equal(find_events(raw), np.empty((0, 3), dtype='int32'))
raw._data[stim_channel_idx, -1:] = 9
assert_array_equal(find_events(raw), [[14399, 0, 9]])
# Test that we can handle consecutive events with no gap
raw._data[stim_channel_idx, 10:20] = 5
raw._data[stim_channel_idx, 20:30] = 6
raw._data[stim_channel_idx, 30:32] = 5
raw._data[stim_channel_idx, 40] = 6
assert_array_equal(find_events(raw, consecutive=False),
[[10, 0, 5],
[40, 0, 6],
[14399, 0, 9]])
assert_array_equal(find_events(raw, consecutive=True),
[[10, 0, 5],
[20, 5, 6],
[30, 6, 5],
[40, 0, 6],
[14399, 0, 9]])
assert_array_equal(find_events(raw),
[[10, 0, 5],
[20, 5, 6],
[40, 0, 6],
[14399, 0, 9]])
assert_array_equal(find_events(raw, output='offset', consecutive=False),
[[31, 0, 5],
[40, 0, 6],
[14399, 0, 9]])
assert_array_equal(find_events(raw, output='offset', consecutive=True),
[[19, 6, 5],
[29, 5, 6],
[31, 0, 5],
[40, 0, 6],
[14399, 0, 9]])
pytest.raises(ValueError, find_events, raw, output='step',
consecutive=True)
assert_array_equal(find_events(raw, output='step', consecutive=True,
shortest_event=1),
[[10, 0, 5],
[20, 5, 6],
[30, 6, 5],
[32, 5, 0],
[40, 0, 6],
[41, 6, 0],
[14399, 0, 9],
[14400, 9, 0]])
assert_array_equal(find_events(raw, output='offset'),
[[19, 6, 5],
[31, 0, 6],
[40, 0, 6],
[14399, 0, 9]])
assert_array_equal(find_events(raw, consecutive=False, min_duration=0.002),
[[10, 0, 5]])
assert_array_equal(find_events(raw, consecutive=True, min_duration=0.002),
[[10, 0, 5],
[20, 5, 6],
[30, 6, 5]])
assert_array_equal(find_events(raw, output='offset', consecutive=False,
min_duration=0.002),
[[31, 0, 5]])
assert_array_equal(find_events(raw, output='offset', consecutive=True,
min_duration=0.002),
[[19, 6, 5],
[29, 5, 6],
[31, 0, 5]])
assert_array_equal(find_events(raw, consecutive=True, min_duration=0.003),
[[10, 0, 5],
[20, 5, 6]])
# test find_stim_steps merge parameter
raw._data[stim_channel_idx, :] = 0
raw._data[stim_channel_idx, 0] = 1
raw._data[stim_channel_idx, 10] = 4
raw._data[stim_channel_idx, 11:20] = 5
assert_array_equal(find_stim_steps(raw, pad_start=0, merge=0,
stim_channel=stim_channel),
[[0, 0, 1],
[1, 1, 0],
[10, 0, 4],
[11, 4, 5],
[20, 5, 0]])
assert_array_equal(find_stim_steps(raw, merge=-1,
stim_channel=stim_channel),
[[1, 1, 0],
[10, 0, 5],
[20, 5, 0]])
assert_array_equal(find_stim_steps(raw, merge=1,
stim_channel=stim_channel),
[[1, 1, 0],
[11, 0, 5],
[20, 5, 0]])
# put back the env vars we trampled on
for s, o in zip(extra_ends, orig_envs):
if o is not None:
os.environ['MNE_STIM_CHANNEL%s' % s] = o
# Test with list of stim channels
raw._data[stim_channel_idx, 1:101] = np.zeros(100)
raw._data[stim_channel_idx, 10:11] = 1
raw._data[stim_channel_idx, 30:31] = 3
stim_channel2 = 'STI 015'
stim_channel2_idx = pick_channels(raw.info['ch_names'],
include=[stim_channel2])
raw._data[stim_channel2_idx, :] = 0
raw._data[stim_channel2_idx, :100] = raw._data[stim_channel_idx, 5:105]
events1 = find_events(raw, stim_channel='STI 014')
events2 = events1.copy()
events2[:, 0] -= 5
events = find_events(raw, stim_channel=['STI 014', stim_channel2])
assert_array_equal(events[::2], events2)
assert_array_equal(events[1::2], events1)
# test initial_event argument
info = create_info(['MYSTI'], 1000, 'stim')
data = np.zeros((1, 1000))
raw = RawArray(data, info)
data[0, :10] = 100
data[0, 30:40] = 200
assert_array_equal(find_events(raw, 'MYSTI'), [[30, 0, 200]])
assert_array_equal(find_events(raw, 'MYSTI', initial_event=True),
[[0, 0, 100], [30, 0, 200]])
def test_pick_events():
"""Test pick events in a events ndarray."""
events = np.array([[1, 0, 1],
[2, 1, 0],
[3, 0, 4],
[4, 4, 2],
[5, 2, 0]])
assert_array_equal(pick_events(events, include=[1, 4], exclude=4),
[[1, 0, 1],
[3, 0, 4]])
assert_array_equal(pick_events(events, exclude=[0, 2]),
[[1, 0, 1],
[3, 0, 4]])
assert_array_equal(pick_events(events, include=[1, 2], step=True),
[[1, 0, 1],
[2, 1, 0],
[4, 4, 2],
[5, 2, 0]])
def test_make_fixed_length_events():
"""Test making events of a fixed length."""
raw = read_raw_fif(raw_fname)
events = make_fixed_length_events(raw, id=1)
assert events.shape[1] == 3
events_zero = make_fixed_length_events(raw, 1, first_samp=False)
assert_equal(events_zero[0, 0], 0)
assert_array_equal(events_zero[:, 0], events[:, 0] - raw.first_samp)
# With limits
tmin, tmax = raw.times[[0, -1]]
duration = tmax - tmin
events = make_fixed_length_events(raw, 1, tmin, tmax, duration)
assert_equal(events.shape[0], 1)
# With bad limits (no resulting events)
pytest.raises(ValueError, make_fixed_length_events, raw, 1,
tmin, tmax - 1e-3, duration)
# not raw, bad id or duration
pytest.raises(TypeError, make_fixed_length_events, raw, 2.3)
pytest.raises(TypeError, make_fixed_length_events, 'not raw', 2)
pytest.raises(TypeError, make_fixed_length_events, raw, 23, tmin, tmax,
'abc')
# Let's try some ugly sample rate/sample count combos
data = np.random.RandomState(0).randn(1, 27768)
# This breaks unless np.round() is used in make_fixed_length_events
info = create_info(1, 155.4499969482422)
raw = RawArray(data, info)
events = make_fixed_length_events(raw, 1, duration=raw.times[-1])
assert events[0, 0] == 0
assert len(events) == 1
# Without use_rounding=True this breaks
raw = RawArray(data[:, :21216], info)
events = make_fixed_length_events(raw, 1, duration=raw.times[-1])
assert events[0, 0] == 0
assert len(events) == 1
# Make sure it gets used properly by compute_raw_covariance
cov = compute_raw_covariance(raw, tstep=None)
expected = np.cov(data[:, :21216])
np.testing.assert_allclose(cov['data'], expected, atol=1e-12)
def test_define_events():
"""Test defining response events."""
events = read_events(fname)
raw = read_raw_fif(raw_fname)
events_, _ = define_target_events(events, 5, 32, raw.info['sfreq'],
.2, 0.7, 42, 99)
n_target = events[events[:, 2] == 5].shape[0]
n_miss = events_[events_[:, 2] == 99].shape[0]
n_target_ = events_[events_[:, 2] == 42].shape[0]
assert (n_target_ == (n_target - n_miss))
events = np.array([[0, 0, 1],
[375, 0, 2],
[500, 0, 1],
[875, 0, 3],
[1000, 0, 1],
[1375, 0, 3],
[1100, 0, 1],
[1475, 0, 2],
[1500, 0, 1],
[1875, 0, 2]])
true_lag_nofill = [1500., 1500., 1500.]
true_lag_fill = [1500., np.nan, np.nan, 1500., 1500.]
n, lag_nofill = define_target_events(events, 1, 2, 250., 1.4, 1.6, 5)
n, lag_fill = define_target_events(events, 1, 2, 250., 1.4, 1.6, 5, 99)
assert_array_equal(true_lag_fill, lag_fill)
assert_array_equal(true_lag_nofill, lag_nofill)
@testing.requires_testing_data
def test_acqparser():
"""Test AcqParserFIF."""
# no acquisition parameters
pytest.raises(ValueError, AcqParserFIF, {'acq_pars': ''})
# invalid acquisition parameters
pytest.raises(ValueError, AcqParserFIF, {'acq_pars': 'baaa'})
pytest.raises(ValueError, AcqParserFIF, {'acq_pars': 'ERFVersion\n1'})
# test oldish file
raw = read_raw_fif(raw_fname, preload=False)
acqp = AcqParserFIF(raw.info)
# test __repr__()
assert (repr(acqp))
# old file should trigger compat mode
assert (acqp.compat)
# count events and categories
assert_equal(len(acqp.categories), 6)
assert_equal(len(acqp._categories), 17)
assert_equal(len(acqp.events), 6)
assert_equal(len(acqp._events), 17)
# get category
assert (acqp['Surprise visual'])
# test TRIUX file
raw = read_raw_fif(fname_raw_elekta, preload=False)
acqp = raw.acqparser
assert (acqp is raw.acqparser) # same one, not regenerated
# test __repr__()
assert (repr(acqp))
# this file should not be in compatibility mode
assert (not acqp.compat)
# nonexistent category
pytest.raises(KeyError, acqp.__getitem__, 'does not exist')
pytest.raises(KeyError, acqp.get_condition, raw, 'foo')
# category not a string
pytest.raises(TypeError, acqp.__getitem__, 0)
# number of events / categories
assert_equal(len(acqp), 7)
assert_equal(len(acqp.categories), 7)
assert_equal(len(acqp._categories), 32)
assert_equal(len(acqp.events), 6)
assert_equal(len(acqp._events), 32)
# get category
assert (acqp['Test event 5'])
@testing.requires_testing_data
def test_acqparser_averaging():
"""Test averaging with AcqParserFIF vs. Elekta software."""
raw = read_raw_fif(fname_raw_elekta, preload=True)
acqp = AcqParserFIF(raw.info)
for cat in acqp.categories:
# XXX datasets match only when baseline is applied to both,
# not sure where relative dc shift comes from
cond = acqp.get_condition(raw, cat)
eps = Epochs(raw, baseline=(-.05, 0), **cond)
ev = eps.average()
ev_ref = read_evokeds(fname_ave_elekta, cat['comment'],
baseline=(-.05, 0), proj=False)
ev_mag = ev.copy()
ev_mag.pick_channels(['MEG0111'])
ev_grad = ev.copy()
ev_grad.pick_channels(['MEG2643', 'MEG1622'])
ev_ref_mag = ev_ref.copy()
ev_ref_mag.pick_channels(['MEG0111'])
ev_ref_grad = ev_ref.copy()
ev_ref_grad.pick_channels(['MEG2643', 'MEG1622'])
assert_allclose(ev_mag.data, ev_ref_mag.data,
rtol=0, atol=1e-15) # tol = 1 fT
# Elekta put these in a different order
assert ev_grad.ch_names[::-1] == ev_ref_grad.ch_names
assert_allclose(ev_grad.data[::-1], ev_ref_grad.data,
rtol=0, atol=1e-13) # tol = 1 fT/cm
run_tests_if_main()
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