def test_check_info_inv():
"""Test checks for common channels across fwd model and cov matrices."""
epochs, data_cov, noise_cov, forward = _get_data()
# make sure same channel lists exist in data to make testing life easier
assert epochs.info['ch_names'] == data_cov.ch_names
assert epochs.info['ch_names'] == noise_cov.ch_names
# check whether bad channels get excluded from the channel selection
# info
info_bads = epochs.info.copy()
info_bads['bads'] = info_bads['ch_names'][1:3] # include two bad channels
picks = _check_info_inv(info_bads, forward, noise_cov=noise_cov)
assert [1, 2] not in picks
# covariance matrix
data_cov_bads = data_cov.copy()
data_cov_bads['bads'] = data_cov_bads.ch_names[0]
picks = _check_info_inv(epochs.info, forward, data_cov=data_cov_bads)
assert 0 not in picks
# noise covariance matrix
noise_cov_bads = noise_cov.copy()
noise_cov_bads['bads'] = noise_cov_bads.ch_names[1]
picks = _check_info_inv(epochs.info, forward, noise_cov=noise_cov_bads)
assert 1 not in picks
# test whether reference channels get deleted
info_ref = epochs.info.copy()
info_ref['chs'][0]['kind'] = 301 # pretend to have a ref channel
picks = _check_info_inv(info_ref, forward, noise_cov=noise_cov)
assert 0 not in picks
# pick channels in all inputs and make sure common set is returned
epochs.pick_channels([epochs.ch_names[ii] for ii in range(10)])
data_cov = pick_channels_cov(
data_cov, include=[data_cov.ch_names[ii] for ii in range(5, 20)])
noise_cov = pick_channels_cov(
noise_cov, include=[noise_cov.ch_names[ii] for ii in range(7, 12)])
picks = _check_info_inv(epochs.info,
forward,
noise_cov=noise_cov,
data_cov=data_cov)
assert list(range(7, 10)) == picks
def test_check_info_inv():
"""Test checks for common channels across fwd model and cov matrices."""
epochs, data_cov, noise_cov, forward = _get_data()
# make sure same channel lists exist in data to make testing life easier
assert epochs.info['ch_names'] == data_cov.ch_names
assert epochs.info['ch_names'] == noise_cov.ch_names
# check whether bad channels get excluded from the channel selection
# info
info_bads = epochs.info.copy()
info_bads['bads'] = info_bads['ch_names'][1:3] # include two bad channels
picks = _check_info_inv(info_bads, forward, noise_cov=noise_cov)
assert [1, 2] not in picks
# covariance matrix
data_cov_bads = data_cov.copy()
data_cov_bads['bads'] = data_cov_bads.ch_names[0]
picks = _check_info_inv(epochs.info, forward, data_cov=data_cov_bads)
assert 0 not in picks
# noise covariance matrix
noise_cov_bads = noise_cov.copy()
noise_cov_bads['bads'] = noise_cov_bads.ch_names[1]
picks = _check_info_inv(epochs.info, forward, noise_cov=noise_cov_bads)
assert 1 not in picks
# test whether reference channels get deleted
info_ref = epochs.info.copy()
info_ref['chs'][0]['kind'] = 301 # pretend to have a ref channel
picks = _check_info_inv(info_ref, forward, noise_cov=noise_cov)
assert 0 not in picks
# pick channels in all inputs and make sure common set is returned
epochs.pick_channels([epochs.ch_names[ii] for ii in range(10)])
data_cov = pick_channels_cov(data_cov, include=[data_cov.ch_names[ii]
for ii in range(5, 20)])
noise_cov = pick_channels_cov(noise_cov, include=[noise_cov.ch_names[ii]
for ii in range(7, 12)])
picks = _check_info_inv(epochs.info, forward, noise_cov=noise_cov,
data_cov=data_cov)
assert list(range(7, 10)) == picks