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# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
# Andrew Dykstra <andrew.r.dykstra@gmail.com>
#
# License: BSD (3-clause)
import os.path as op
from copy import deepcopy
import warnings
import numpy as np
from numpy.testing import (assert_array_almost_equal, assert_equal,
assert_array_equal, assert_allclose)
from nose.tools import assert_true, assert_raises, assert_not_equal
from mne import (equalize_channels, pick_types, read_evoked, write_evoked,
read_evokeds, write_evokeds)
from mne.evoked import _get_peak, EvokedArray
from mne.epochs import EpochsArray
from mne.utils import _TempDir, requires_pandas, requires_nitime
from mne.io.meas_info import create_info
from mne.externals.six.moves import cPickle as pickle
warnings.simplefilter('always')
fname = op.join(op.dirname(__file__), '..', 'io', 'tests', 'data',
'test-ave.fif')
fname_gz = op.join(op.dirname(__file__), '..', 'io', 'tests', 'data',
'test-ave.fif.gz')
tempdir = _TempDir()
def test_hash_evoked():
"""Test evoked hashing
"""
ave = read_evokeds(fname, 0)
ave_2 = read_evokeds(fname, 0)
assert_equal(hash(ave), hash(ave_2))
# do NOT use assert_equal here, failing output is terrible
assert_true(pickle.dumps(ave) == pickle.dumps(ave_2))
ave_2.data[0, 0] -= 1
assert_not_equal(hash(ave), hash(ave_2))
def test_io_evoked():
"""Test IO for evoked data (fif + gz) with integer and str args
"""
ave = read_evokeds(fname, 0)
write_evokeds(op.join(tempdir, 'evoked-ave.fif'), ave)
ave2 = read_evokeds(op.join(tempdir, 'evoked-ave.fif'))[0]
# This not being assert_array_equal due to windows rounding
assert_true(np.allclose(ave.data, ave2.data, atol=1e-16, rtol=1e-3))
assert_array_almost_equal(ave.times, ave2.times)
assert_equal(ave.nave, ave2.nave)
assert_equal(ave._aspect_kind, ave2._aspect_kind)
assert_equal(ave.kind, ave2.kind)
assert_equal(ave.last, ave2.last)
assert_equal(ave.first, ave2.first)
# test compressed i/o
ave2 = read_evokeds(fname_gz, 0)
assert_true(np.allclose(ave.data, ave2.data, atol=1e-16, rtol=1e-8))
# test str access
condition = 'Left Auditory'
assert_raises(ValueError, read_evokeds, fname, condition, kind='stderr')
assert_raises(ValueError, read_evokeds, fname, condition,
kind='standard_error')
ave3 = read_evokeds(fname, condition)
assert_array_almost_equal(ave.data, ave3.data, 19)
# test deprecation warning for read_evoked and write_evoked
# XXX should be deleted for 0.9 release
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ave = read_evoked(fname, setno=0)
assert_true(w[0].category == DeprecationWarning)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
write_evoked(op.join(tempdir, 'evoked-ave.fif'), ave)
assert_true(w[0].category == DeprecationWarning)
# test read_evokeds and write_evokeds
types = ['Left Auditory', 'Right Auditory', 'Left visual', 'Right visual']
aves1 = read_evokeds(fname)
aves2 = read_evokeds(fname, [0, 1, 2, 3])
aves3 = read_evokeds(fname, types)
write_evokeds(op.join(tempdir, 'evoked-ave.fif'), aves1)
aves4 = read_evokeds(op.join(tempdir, 'evoked-ave.fif'))
for aves in [aves2, aves3, aves4]:
for [av1, av2] in zip(aves1, aves):
assert_array_almost_equal(av1.data, av2.data)
assert_array_almost_equal(av1.times, av2.times)
assert_equal(av1.nave, av2.nave)
assert_equal(av1.kind, av2.kind)
assert_equal(av1._aspect_kind, av2._aspect_kind)
assert_equal(av1.last, av2.last)
assert_equal(av1.first, av2.first)
assert_equal(av1.comment, av2.comment)
# test warnings on bad filenames
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
fname2 = op.join(tempdir, 'test-bad-name.fif')
write_evokeds(fname2, ave)
read_evokeds(fname2)
assert_true(len(w) == 2)
def test_shift_time_evoked():
""" Test for shifting of time scale
"""
# Shift backward
ave = read_evokeds(fname, 0)
ave.shift_time(-0.1, relative=True)
write_evokeds(op.join(tempdir, 'evoked-ave.fif'), ave)
# Shift forward twice the amount
ave_bshift = read_evokeds(op.join(tempdir, 'evoked-ave.fif'), 0)
ave_bshift.shift_time(0.2, relative=True)
write_evokeds(op.join(tempdir, 'evoked-ave.fif'), ave_bshift)
# Shift backward again
ave_fshift = read_evokeds(op.join(tempdir, 'evoked-ave.fif'), 0)
ave_fshift.shift_time(-0.1, relative=True)
write_evokeds(op.join(tempdir, 'evoked-ave.fif'), ave_fshift)
ave_normal = read_evokeds(fname, 0)
ave_relative = read_evokeds(op.join(tempdir, 'evoked-ave.fif'), 0)
assert_true(np.allclose(ave_normal.data, ave_relative.data,
atol=1e-16, rtol=1e-3))
assert_array_almost_equal(ave_normal.times, ave_relative.times, 10)
assert_equal(ave_normal.last, ave_relative.last)
assert_equal(ave_normal.first, ave_relative.first)
# Absolute time shift
ave = read_evokeds(fname, 0)
ave.shift_time(-0.3, relative=False)
write_evokeds(op.join(tempdir, 'evoked-ave.fif'), ave)
ave_absolute = read_evokeds(op.join(tempdir, 'evoked-ave.fif'), 0)
assert_true(np.allclose(ave_normal.data, ave_absolute.data,
atol=1e-16, rtol=1e-3))
assert_equal(ave_absolute.first, int(-0.3 * ave.info['sfreq']))
def test_evoked_resample():
"""Test for resampling of evoked data
"""
# upsample, write it out, read it in
ave = read_evokeds(fname, 0)
sfreq_normal = ave.info['sfreq']
ave.resample(2 * sfreq_normal)
write_evokeds(op.join(tempdir, 'evoked-ave.fif'), ave)
ave_up = read_evokeds(op.join(tempdir, 'evoked-ave.fif'), 0)
# compare it to the original
ave_normal = read_evokeds(fname, 0)
# and compare the original to the downsampled upsampled version
ave_new = read_evokeds(op.join(tempdir, 'evoked-ave.fif'), 0)
ave_new.resample(sfreq_normal)
assert_array_almost_equal(ave_normal.data, ave_new.data, 2)
assert_array_almost_equal(ave_normal.times, ave_new.times)
assert_equal(ave_normal.nave, ave_new.nave)
assert_equal(ave_normal._aspect_kind, ave_new._aspect_kind)
assert_equal(ave_normal.kind, ave_new.kind)
assert_equal(ave_normal.last, ave_new.last)
assert_equal(ave_normal.first, ave_new.first)
# for the above to work, the upsampling just about had to, but
# we'll add a couple extra checks anyway
assert_true(len(ave_up.times) == 2 * len(ave_normal.times))
assert_true(ave_up.data.shape[1] == 2 * ave_normal.data.shape[1])
def test_evoked_detrend():
"""Test for detrending evoked data
"""
ave = read_evokeds(fname, 0)
ave_normal = read_evokeds(fname, 0)
ave.detrend(0)
ave_normal.data -= np.mean(ave_normal.data, axis=1)[:, np.newaxis]
picks = pick_types(ave.info, meg=True, eeg=True, exclude='bads')
assert_true(np.allclose(ave.data[picks], ave_normal.data[picks],
rtol=1e-8, atol=1e-16))
@requires_nitime
def test_evoked_to_nitime():
""" Test to_nitime """
ave = read_evokeds(fname, 0)
evoked_ts = ave.to_nitime()
assert_equal(evoked_ts.data, ave.data)
picks2 = [1, 2]
ave = read_evokeds(fname, 0)
evoked_ts = ave.to_nitime(picks=picks2)
assert_equal(evoked_ts.data, ave.data[picks2])
@requires_pandas
def test_as_data_frame():
"""Test evoked Pandas exporter"""
ave = read_evokeds(fname, 0)
assert_raises(ValueError, ave.as_data_frame, picks=np.arange(400))
df = ave.as_data_frame()
assert_true((df.columns == ave.ch_names).all())
df = ave.as_data_frame(use_time_index=False)
assert_true('time' in df.columns)
assert_array_equal(df.values[:, 1], ave.data[0] * 1e13)
assert_array_equal(df.values[:, 3], ave.data[2] * 1e15)
def test_evoked_proj():
"""Test SSP proj operations
"""
for proj in [True, False]:
ave = read_evokeds(fname, condition=0, proj=proj)
assert_true(all(p['active'] == proj for p in ave.info['projs']))
# test adding / deleting proj
if proj:
assert_raises(ValueError, ave.add_proj, [],
{'remove_existing': True})
assert_raises(ValueError, ave.del_proj, 0)
else:
projs = deepcopy(ave.info['projs'])
n_proj = len(ave.info['projs'])
ave.del_proj(0)
assert_true(len(ave.info['projs']) == n_proj - 1)
ave.add_proj(projs, remove_existing=False)
assert_true(len(ave.info['projs']) == 2 * n_proj - 1)
ave.add_proj(projs, remove_existing=True)
assert_true(len(ave.info['projs']) == n_proj)
ave = read_evokeds(fname, condition=0, proj=False)
data = ave.data.copy()
ave.apply_proj()
assert_allclose(np.dot(ave._projector, data), ave.data)
def test_get_peak():
"""Test peak getter
"""
evoked = read_evokeds(fname, condition=0, proj=True)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmin=1)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmax=0.9)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', tmin=0.02,
tmax=0.01)
assert_raises(ValueError, evoked.get_peak, ch_type='mag', mode='foo')
assert_raises(RuntimeError, evoked.get_peak, ch_type=None, mode='foo')
assert_raises(ValueError, evoked.get_peak, ch_type='misc', mode='foo')
ch_idx, time_idx = evoked.get_peak(ch_type='mag')
assert_true(ch_idx in evoked.ch_names)
assert_true(time_idx in evoked.times)
ch_idx, time_idx = evoked.get_peak(ch_type='mag',
time_as_index=True)
assert_true(time_idx < len(evoked.times))
data = np.array([[0., 1., 2.],
[0., -3., 0]])
times = np.array([.1, .2, .3])
ch_idx, time_idx = _get_peak(data, times, mode='abs')
assert_equal(ch_idx, 1)
assert_equal(time_idx, 1)
ch_idx, time_idx = _get_peak(data * -1, times, mode='neg')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
ch_idx, time_idx = _get_peak(data, times, mode='pos')
assert_equal(ch_idx, 0)
assert_equal(time_idx, 2)
assert_raises(ValueError, _get_peak, data + 1e3, times, mode='neg')
assert_raises(ValueError, _get_peak, data - 1e3, times, mode='pos')
def test_drop_channels_mixin():
"""Test channels-dropping functionality
"""
evoked = read_evokeds(fname, condition=0, proj=True)
drop_ch = evoked.ch_names[:3]
ch_names = evoked.ch_names[3:]
ch_names_orig = evoked.ch_names
dummy = evoked.drop_channels(drop_ch, copy=True)
assert_equal(ch_names, dummy.ch_names)
assert_equal(ch_names_orig, evoked.ch_names)
assert_equal(len(ch_names_orig), len(evoked.data))
evoked.drop_channels(drop_ch)
assert_equal(ch_names, evoked.ch_names)
assert_equal(len(ch_names), len(evoked.data))
def test_pick_channels_mixin():
"""Test channel-picking functionality
"""
evoked = read_evokeds(fname, condition=0, proj=True)
ch_names = evoked.ch_names[:3]
ch_names_orig = evoked.ch_names
dummy = evoked.pick_channels(ch_names, copy=True)
assert_equal(ch_names, dummy.ch_names)
assert_equal(ch_names_orig, evoked.ch_names)
assert_equal(len(ch_names_orig), len(evoked.data))
evoked.pick_channels(ch_names)
assert_equal(ch_names, evoked.ch_names)
assert_equal(len(ch_names), len(evoked.data))
def test_equalize_channels():
"""Test equalization of channels
"""
evoked1 = read_evokeds(fname, condition=0, proj=True)
evoked2 = evoked1.copy()
ch_names = evoked1.ch_names[2:]
evoked1.drop_channels(evoked1.ch_names[:1])
evoked2.drop_channels(evoked2.ch_names[1:2])
my_comparison = [evoked1, evoked2]
equalize_channels(my_comparison)
for e in my_comparison:
assert_equal(ch_names, e.ch_names)
def test_array_epochs():
"""Test creating evoked from array
"""
# creating
rng = np.random.RandomState(42)
data1 = rng.randn(20, 60)
sfreq = 1e3
ch_names = ['EEG %03d' % (i + 1) for i in range(20)]
types = ['eeg'] * 20
info = create_info(ch_names, sfreq, types)
evoked1 = EvokedArray(data1, info, tmin=-0.01)
# save, read, and compare evokeds
tmp_fname = op.join(tempdir, 'evkdary-ave.fif')
evoked1.save(tmp_fname)
evoked2 = read_evokeds(tmp_fname)[0]
data2 = evoked2.data
assert_allclose(data1, data2)
assert_allclose(evoked1.times, evoked2.times)
assert_equal(evoked1.first, evoked2.first)
assert_equal(evoked1.last, evoked2.last)
assert_equal(evoked1.kind, evoked2.kind)
assert_equal(evoked1.nave, evoked2.nave)
# now compare with EpochsArray (with single epoch)
data3 = data1[np.newaxis, :, :]
events = np.c_[10, 0, 1]
evoked3 = EpochsArray(data3, info, events=events, tmin=-0.01).average()
assert_allclose(evoked1.data, evoked3.data)
assert_allclose(evoked1.times, evoked3.times)
assert_equal(evoked1.first, evoked3.first)
assert_equal(evoked1.last, evoked3.last)
assert_equal(evoked1.kind, evoked3.kind)
assert_equal(evoked1.nave, evoked3.nave)
# test match between channels info and data
ch_names = ['EEG %03d' % (i + 1) for i in range(19)]
types = ['eeg'] * 19
info = create_info(ch_names, sfreq, types)
assert_raises(ValueError, EvokedArray, data1, info, tmin=-0.01)
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