def test_evoked_arithmetic():
"""Test evoked arithmetic
"""
ev = read_evokeds(fname, condition=0)
ev1 = EvokedArray(np.ones_like(ev.data), ev.info, ev.times[0], nave=20)
ev2 = EvokedArray(-np.ones_like(ev.data), ev.info, ev.times[0], nave=10)
# combine_evoked([ev1, ev2]) should be the same as ev1 + ev2:
# data should be added according to their `nave` weights
# nave = ev1.nave + ev2.nave
ev = ev1 + ev2
assert_equal(ev.nave, ev1.nave + ev2.nave)
assert_allclose(ev.data, 1. / 3. * np.ones_like(ev.data))
ev = ev1 - ev2
assert_equal(ev.nave, ev1.nave + ev2.nave)
assert_equal(ev.comment, ev1.comment + ' - ' + ev2.comment)
assert_allclose(ev.data, np.ones_like(ev1.data))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ev = merge_evoked([ev1, ev2])
assert_true(len(w) >= 1)
assert_allclose(ev.data, 1. / 3. * np.ones_like(ev.data))
# default comment behavior if evoked.comment is None
old_comment1 = ev1.comment
old_comment2 = ev2.comment
ev1.comment = None
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ev = ev1 - ev2
assert_equal(ev.comment, 'unknown')
ev1.comment = old_comment1
ev2.comment = old_comment2
# equal weighting
ev = combine_evoked([ev1, ev2], weights='equal')
assert_allclose(ev.data, np.zeros_like(ev1.data))
# combine_evoked([ev1, ev2], weights=[1, 0]) should yield the same as ev1
ev = combine_evoked([ev1, ev2], weights=[1, 0])
assert_equal(ev.nave, ev1.nave)
assert_allclose(ev.data, ev1.data)
# simple subtraction (like in oddball)
ev = combine_evoked([ev1, ev2], weights=[1, -1])
assert_allclose(ev.data, 2 * np.ones_like(ev1.data))
assert_raises(ValueError, combine_evoked, [ev1, ev2], weights='foo')
assert_raises(ValueError, combine_evoked, [ev1, ev2], weights=[1])
# grand average
evoked1, evoked2 = read_evokeds(fname, condition=[0, 1], proj=True)
ch_names = evoked1.ch_names[2:]
evoked1.info['bads'] = ['EEG 008'] # test interpolation
evoked1.drop_channels(evoked1.ch_names[:1])
evoked2.drop_channels(evoked2.ch_names[1:2])
gave = grand_average([evoked1, evoked2])
assert_equal(gave.data.shape, [len(ch_names), evoked1.data.shape[1]])
assert_equal(ch_names, gave.ch_names)
assert_equal(gave.nave, 2)
def test_arithmetic():
"""Test evoked arithmetic."""
ev = read_evokeds(fname, condition=0)
ev20 = EvokedArray(np.ones_like(ev.data), ev.info, ev.times[0], nave=20)
ev30 = EvokedArray(np.ones_like(ev.data), ev.info, ev.times[0], nave=30)
tol = dict(rtol=1e-9, atol=0)
# test subtraction
sub1 = combine_evoked([ev, ev], weights=[1, -1])
sub2 = combine_evoked([ev, -ev], weights=[1, 1])
assert np.allclose(sub1.data, np.zeros_like(sub1.data), atol=1e-20)
assert np.allclose(sub2.data, np.zeros_like(sub2.data), atol=1e-20)
# test nave weighting. Expect signal ampl.: 1*(20/50) + 1*(30/50) == 1
# and expect nave == ev1.nave + ev2.nave
ev = combine_evoked([ev20, ev30], weights='nave')
assert np.allclose(ev.nave, ev20.nave + ev30.nave)
assert np.allclose(ev.data, np.ones_like(ev.data), **tol)
# test equal-weighted sum. Expect signal ampl. == 2
# and expect nave == 1/sum(1/naves) == 1/(1/20 + 1/30) == 12
ev = combine_evoked([ev20, ev30], weights=[1, 1])
assert np.allclose(ev.nave, 12.)
assert np.allclose(ev.data, ev20.data + ev30.data, **tol)
# test equal-weighted average. Expect signal ampl. == 1
# and expect nave == 1/sum(weights²/naves) == 1/(0.5²/20 + 0.5²/30) == 48
ev = combine_evoked([ev20, ev30], weights='equal')
assert np.allclose(ev.nave, 48.)
assert np.allclose(ev.data, np.mean([ev20.data, ev30.data], axis=0), **tol)
# test zero weights
ev = combine_evoked([ev20, ev30], weights=[1, 0])
assert ev.nave == ev20.nave
assert np.allclose(ev.data, ev20.data, **tol)
# default comment behavior if evoked.comment is None
old_comment1 = ev20.comment
ev20.comment = None
ev = combine_evoked([ev20, -ev30], weights=[1, -1])
assert_equal(ev.comment.count('unknown'), 2)
assert ('-unknown' in ev.comment)
assert (' + ' in ev.comment)
ev20.comment = old_comment1
with pytest.raises(ValueError, match="Invalid value for the 'weights'"):
combine_evoked([ev20, ev30], weights='foo')
with pytest.raises(ValueError, match='weights must be the same size as'):
combine_evoked([ev20, ev30], weights=[1])
# grand average
evoked1, evoked2 = read_evokeds(fname, condition=[0, 1], proj=True)
ch_names = evoked1.ch_names[2:]
evoked1.info['bads'] = ['EEG 008'] # test interpolation
evoked1.drop_channels(evoked1.ch_names[:1])
evoked2.drop_channels(evoked2.ch_names[1:2])
gave = grand_average([evoked1, evoked2])
assert_equal(gave.data.shape, [len(ch_names), evoked1.data.shape[1]])
assert_equal(ch_names, gave.ch_names)
assert_equal(gave.nave, 2)
with pytest.raises(TypeError, match='All elements must be an instance of'):
grand_average([1, evoked1])
gave = grand_average([ev20, ev20, -ev30]) # (1 + 1 + -1) / 3 = 1/3
assert_allclose(gave.data, np.full_like(gave.data, 1. / 3.))
# test channel (re)ordering
evoked1, evoked2 = read_evokeds(fname, condition=[0, 1], proj=True)
data2 = evoked2.data # assumes everything is ordered to the first evoked
data = (evoked1.data + evoked2.data) / 2.
evoked2.reorder_channels(evoked2.ch_names[::-1])
assert not np.allclose(data2, evoked2.data)
with pytest.warns(RuntimeWarning, match='reordering'):
evoked3 = combine_evoked([evoked1, evoked2], weights=[0.5, 0.5])
assert np.allclose(evoked3.data, data)
assert evoked1.ch_names != evoked2.ch_names
assert evoked1.ch_names == evoked3.ch_names
def test_arithmetic():
"""Test evoked arithmetic."""
ev = read_evokeds(fname, condition=0)
ev1 = EvokedArray(np.ones_like(ev.data), ev.info, ev.times[0], nave=20)
ev2 = EvokedArray(-np.ones_like(ev.data), ev.info, ev.times[0], nave=10)
# combine_evoked([ev1, ev2]) should be the same as ev1 + ev2:
# data should be added according to their `nave` weights
# nave = ev1.nave + ev2.nave
ev = combine_evoked([ev1, ev2], weights='nave')
assert_allclose(ev.nave, ev1.nave + ev2.nave)
assert_allclose(ev.data, 1. / 3. * np.ones_like(ev.data))
# with same trial counts, a bunch of things should be equivalent
for weights in ('nave', [0.5, 0.5]):
ev = combine_evoked([ev1, ev1], weights=weights)
assert_allclose(ev.data, ev1.data)
assert_allclose(ev.nave, 2 * ev1.nave)
ev = combine_evoked([ev1, -ev1], weights=weights)
assert_allclose(ev.data, 0., atol=1e-20)
assert_allclose(ev.nave, 2 * ev1.nave)
# adding evoked to itself
ev = combine_evoked([ev1, ev1], weights='equal')
assert_allclose(ev.data, 2 * ev1.data)
assert_allclose(ev.nave, ev1.nave / 2)
# subtracting evoked from itself
ev = combine_evoked([ev1, -ev1], weights='equal')
assert_allclose(ev.data, 0., atol=1e-20)
assert_allclose(ev.nave, ev1.nave / 2)
# subtracting different evokeds
ev = combine_evoked([ev1, -ev2], weights='equal')
assert_allclose(ev.data, 2., atol=1e-20)
expected_nave = 1. / (1. / ev1.nave + 1. / ev2.nave)
assert_allclose(ev.nave, expected_nave)
# default comment behavior if evoked.comment is None
old_comment1 = ev1.comment
old_comment2 = ev2.comment
ev1.comment = None
ev = combine_evoked([ev1, -ev2], weights=[1, -1])
assert_equal(ev.comment.count('unknown'), 2)
assert ('-unknown' in ev.comment)
assert (' + ' in ev.comment)
ev1.comment = old_comment1
ev2.comment = old_comment2
# equal weighting
ev = combine_evoked([ev1, ev2], weights='equal')
assert_allclose(ev.data, np.zeros_like(ev1.data))
# combine_evoked([ev1, ev2], weights=[1, 0]) should yield the same as ev1
ev = combine_evoked([ev1, ev2], weights=[1, 0])
assert_allclose(ev.nave, ev1.nave)
assert_allclose(ev.data, ev1.data)
# simple subtraction (like in oddball)
ev = combine_evoked([ev1, ev2], weights=[1, -1])
assert_allclose(ev.data, 2 * np.ones_like(ev1.data))
pytest.raises(ValueError, combine_evoked, [ev1, ev2], weights='foo')
pytest.raises(ValueError, combine_evoked, [ev1, ev2], weights=[1])
# grand average
evoked1, evoked2 = read_evokeds(fname, condition=[0, 1], proj=True)
ch_names = evoked1.ch_names[2:]
evoked1.info['bads'] = ['EEG 008'] # test interpolation
evoked1.drop_channels(evoked1.ch_names[:1])
evoked2.drop_channels(evoked2.ch_names[1:2])
gave = grand_average([evoked1, evoked2])
assert_equal(gave.data.shape, [len(ch_names), evoked1.data.shape[1]])
assert_equal(ch_names, gave.ch_names)
assert_equal(gave.nave, 2)
pytest.raises(TypeError, grand_average, [1, evoked1])
gave = grand_average([ev1, ev1, ev2]) # (1 + 1 + -1) / 3 = 1/3
assert_allclose(gave.data, np.full_like(gave.data, 1. / 3.))
# test channel (re)ordering
evoked1, evoked2 = read_evokeds(fname, condition=[0, 1], proj=True)
data2 = evoked2.data # assumes everything is ordered to the first evoked
data = (evoked1.data + evoked2.data) / 2.
evoked2.reorder_channels(evoked2.ch_names[::-1])
assert not np.allclose(data2, evoked2.data)
with pytest.warns(RuntimeWarning, match='reordering'):
ev3 = combine_evoked([evoked1, evoked2], weights=[0.5, 0.5])
assert np.allclose(ev3.data, data)
assert evoked1.ch_names != evoked2.ch_names
assert evoked1.ch_names == ev3.ch_names
def test_arithmetic():
"""Test evoked arithmetic"""
ev = read_evokeds(fname, condition=0)
ev1 = EvokedArray(np.ones_like(ev.data), ev.info, ev.times[0], nave=20)
ev2 = EvokedArray(-np.ones_like(ev.data), ev.info, ev.times[0], nave=10)
# combine_evoked([ev1, ev2]) should be the same as ev1 + ev2:
# data should be added according to their `nave` weights
# nave = ev1.nave + ev2.nave
with warnings.catch_warnings(record=True): # deprecation no weights
ev = combine_evoked([ev1, ev2])
assert_equal(ev.nave, ev1.nave + ev2.nave)
assert_allclose(ev.data, 1. / 3. * np.ones_like(ev.data))
# with same trial counts, a bunch of things should be equivalent
for weights in ('nave', 'equal', [0.5, 0.5]):
ev = combine_evoked([ev1, ev1], weights=weights)
assert_allclose(ev.data, ev1.data)
assert_equal(ev.nave, 2 * ev1.nave)
ev = combine_evoked([ev1, -ev1], weights=weights)
assert_allclose(ev.data, 0., atol=1e-20)
assert_equal(ev.nave, 2 * ev1.nave)
ev = combine_evoked([ev1, -ev1], weights='equal')
assert_allclose(ev.data, 0., atol=1e-20)
assert_equal(ev.nave, 2 * ev1.nave)
ev = combine_evoked([ev1, -ev2], weights='equal')
expected = int(round(1. / (0.25 / ev1.nave + 0.25 / ev2.nave)))
assert_equal(expected, 27) # this is reasonable
assert_equal(ev.nave, expected)
# default comment behavior if evoked.comment is None
old_comment1 = ev1.comment
old_comment2 = ev2.comment
ev1.comment = None
ev = combine_evoked([ev1, -ev2], weights=[1, -1])
assert_equal(ev.comment.count('unknown'), 2)
assert_true('-unknown' in ev.comment)
assert_true(' + ' in ev.comment)
ev1.comment = old_comment1
ev2.comment = old_comment2
# equal weighting
ev = combine_evoked([ev1, ev2], weights='equal')
assert_allclose(ev.data, np.zeros_like(ev1.data))
# combine_evoked([ev1, ev2], weights=[1, 0]) should yield the same as ev1
ev = combine_evoked([ev1, ev2], weights=[1, 0])
assert_equal(ev.nave, ev1.nave)
assert_allclose(ev.data, ev1.data)
# simple subtraction (like in oddball)
ev = combine_evoked([ev1, ev2], weights=[1, -1])
assert_allclose(ev.data, 2 * np.ones_like(ev1.data))
assert_raises(ValueError, combine_evoked, [ev1, ev2], weights='foo')
assert_raises(ValueError, combine_evoked, [ev1, ev2], weights=[1])
# grand average
evoked1, evoked2 = read_evokeds(fname, condition=[0, 1], proj=True)
ch_names = evoked1.ch_names[2:]
evoked1.info['bads'] = ['EEG 008'] # test interpolation
evoked1.drop_channels(evoked1.ch_names[:1])
evoked2.drop_channels(evoked2.ch_names[1:2])
gave = grand_average([evoked1, evoked2])
assert_equal(gave.data.shape, [len(ch_names), evoked1.data.shape[1]])
assert_equal(ch_names, gave.ch_names)
assert_equal(gave.nave, 2)
assert_raises(ValueError, grand_average, [1, evoked1])
def test_arithmetic():
"""Test evoked arithmetic."""
ev = read_evokeds(fname, condition=0)
ev1 = EvokedArray(np.ones_like(ev.data), ev.info, ev.times[0], nave=20)
ev2 = EvokedArray(-np.ones_like(ev.data), ev.info, ev.times[0], nave=10)
# combine_evoked([ev1, ev2]) should be the same as ev1 + ev2:
# data should be added according to their `nave` weights
# nave = ev1.nave + ev2.nave
ev = combine_evoked([ev1, ev2], weights='nave')
assert_equal(ev.nave, ev1.nave + ev2.nave)
assert_allclose(ev.data, 1. / 3. * np.ones_like(ev.data))
# with same trial counts, a bunch of things should be equivalent
for weights in ('nave', 'equal', [0.5, 0.5]):
ev = combine_evoked([ev1, ev1], weights=weights)
assert_allclose(ev.data, ev1.data)
assert_equal(ev.nave, 2 * ev1.nave)
ev = combine_evoked([ev1, -ev1], weights=weights)
assert_allclose(ev.data, 0., atol=1e-20)
assert_equal(ev.nave, 2 * ev1.nave)
ev = combine_evoked([ev1, -ev1], weights='equal')
assert_allclose(ev.data, 0., atol=1e-20)
assert_equal(ev.nave, 2 * ev1.nave)
ev = combine_evoked([ev1, -ev2], weights='equal')
expected = int(round(1. / (0.25 / ev1.nave + 0.25 / ev2.nave)))
assert_equal(expected, 27) # this is reasonable
assert_equal(ev.nave, expected)
# default comment behavior if evoked.comment is None
old_comment1 = ev1.comment
old_comment2 = ev2.comment
ev1.comment = None
ev = combine_evoked([ev1, -ev2], weights=[1, -1])
assert_equal(ev.comment.count('unknown'), 2)
assert_true('-unknown' in ev.comment)
assert_true(' + ' in ev.comment)
ev1.comment = old_comment1
ev2.comment = old_comment2
# equal weighting
ev = combine_evoked([ev1, ev2], weights='equal')
assert_allclose(ev.data, np.zeros_like(ev1.data))
# combine_evoked([ev1, ev2], weights=[1, 0]) should yield the same as ev1
ev = combine_evoked([ev1, ev2], weights=[1, 0])
assert_equal(ev.nave, ev1.nave)
assert_allclose(ev.data, ev1.data)
# simple subtraction (like in oddball)
ev = combine_evoked([ev1, ev2], weights=[1, -1])
assert_allclose(ev.data, 2 * np.ones_like(ev1.data))
assert_raises(ValueError, combine_evoked, [ev1, ev2], weights='foo')
assert_raises(ValueError, combine_evoked, [ev1, ev2], weights=[1])
# grand average
evoked1, evoked2 = read_evokeds(fname, condition=[0, 1], proj=True)
ch_names = evoked1.ch_names[2:]
evoked1.info['bads'] = ['EEG 008'] # test interpolation
evoked1.drop_channels(evoked1.ch_names[:1])
evoked2.drop_channels(evoked2.ch_names[1:2])
gave = grand_average([evoked1, evoked2])
assert_equal(gave.data.shape, [len(ch_names), evoked1.data.shape[1]])
assert_equal(ch_names, gave.ch_names)
assert_equal(gave.nave, 2)
assert_raises(ValueError, grand_average, [1, evoked1])
