def test_add_reorder(n_ref):
"""Test that a reference channel can be added and then data reordered."""
# gh-8300
raw = read_raw_fif(raw_fname).crop(0, 0.1).del_proj().pick('eeg')
assert len(raw.ch_names) == 60
chs = ['EEG %03d' % (60 + ii) for ii in range(1, n_ref)] + ['EEG 000']
with pytest.raises(RuntimeError, match='preload'):
with pytest.warns(None): # ignore multiple warning
add_reference_channels(raw, chs, copy=False)
raw.load_data()
if n_ref == 1:
ctx = nullcontext()
else:
assert n_ref == 2
ctx = pytest.warns(RuntimeWarning, match='locations of multiple')
with ctx:
add_reference_channels(raw, chs, copy=False)
data = raw.get_data()
assert_array_equal(data[-1], 0.)
assert raw.ch_names[-n_ref:] == chs
raw.reorder_channels(raw.ch_names[-1:] + raw.ch_names[:-1])
assert raw.ch_names == ['EEG %03d' % ii for ii in range(60 + n_ref)]
data_new = raw.get_data()
data_new = np.concatenate([data_new[1:], data_new[:1]])
assert_allclose(data, data_new)
def test_hp_lp_reversed(fname, lo, hi, warns, monkeypatch):
"""Test HP/LP reversed (gh-8584)."""
fname = str(fname)
raw = read_raw_edf(fname)
assert raw.info['lowpass'] == lo
assert raw.info['highpass'] == hi
monkeypatch.setattr(edf.edf, '_read_edf_header', _hp_lp_rev)
if warns:
ctx = pytest.warns(RuntimeWarning, match='greater than lowpass')
new_lo, new_hi = raw.info['sfreq'] / 2., 0.
else:
ctx = nullcontext()
new_lo, new_hi = lo, hi
with ctx:
raw = read_raw_edf(fname)
assert raw.info['lowpass'] == new_lo
assert raw.info['highpass'] == new_hi
def test_notch_filters(method, filter_length, line_freq, tol):
"""Test notch filters."""
# let's use an ugly, prime sfreq for fun
rng = np.random.RandomState(0)
sfreq = 487
sig_len_secs = 21
t = np.arange(0, int(round(sig_len_secs * sfreq))) / sfreq
# make a "signal"
a = rng.randn(int(sig_len_secs * sfreq))
orig_power = np.sqrt(np.mean(a**2))
# make line noise
a += np.sum([np.sin(2 * np.pi * f * t) for f in line_freqs], axis=0)
# only allow None line_freqs with 'spectrum_fit' mode
pytest.raises(ValueError, notch_filter, a, sfreq, None, 'fft')
pytest.raises(ValueError, notch_filter, a, sfreq, None, 'iir')
if method == 'spectrum_fit' and filter_length == 'auto':
ctx = pytest.deprecated_call(match='will change to 10.')
else:
ctx = nullcontext()
with catch_logging() as log_file:
with ctx:
b = notch_filter(a,
sfreq,
line_freq,
filter_length,
method=method,
verbose=True)
if line_freq is None:
out = [
line.strip().split(':')[0]
for line in log_file.getvalue().split('\n') if line.startswith(' ')
]
assert len(out) == 4, 'Detected frequencies not logged properly'
out = np.array(out, float)
assert_array_almost_equal(out, line_freqs)
new_power = np.sqrt(sum_squared(b) / b.size)
assert_almost_equal(new_power, orig_power, tol)
