def test_metrics():
"""Test simulation metrics."""
src = read_source_spaces(src_fname)
times = np.arange(600) / 1000.
rng = np.random.RandomState(42)
stc1 = simulate_sparse_stc(src, n_dipoles=2, times=times, random_state=rng)
stc2 = simulate_sparse_stc(src, n_dipoles=2, times=times, random_state=rng)
E1_rms = source_estimate_quantification(stc1, stc1, metric='rms')
E2_rms = source_estimate_quantification(stc2, stc2, metric='rms')
E1_cos = source_estimate_quantification(stc1, stc1, metric='cosine')
E2_cos = source_estimate_quantification(stc2, stc2, metric='cosine')
# ### Tests to add
assert (E1_rms == 0.)
assert (E2_rms == 0.)
assert_almost_equal(E1_cos, 0.)
assert_almost_equal(E2_cos, 0.)
stc_bad = stc2.copy().crop(0, 0.5)
pytest.raises(ValueError, source_estimate_quantification, stc1, stc_bad)
stc_bad = stc2.copy()
stc_bad.tmin -= 0.1
pytest.raises(ValueError, source_estimate_quantification, stc1, stc_bad)
pytest.raises(ValueError,
source_estimate_quantification,
stc1,
stc2,
metric='foo')
def test_metrics():
"""Test simulation metrics"""
src = read_source_spaces(src_fname)
times = np.arange(600) / 1000.
rng = np.random.RandomState(42)
stc1 = simulate_sparse_stc(src, n_dipoles=2, times=times, random_state=rng)
stc2 = simulate_sparse_stc(src, n_dipoles=2, times=times, random_state=rng)
E1_rms = source_estimate_quantification(stc1, stc1, metric='rms')
E2_rms = source_estimate_quantification(stc2, stc2, metric='rms')
E1_cos = source_estimate_quantification(stc1, stc1, metric='cosine')
E2_cos = source_estimate_quantification(stc2, stc2, metric='cosine')
# ### Tests to add
assert_true(E1_rms == 0.)
assert_true(E2_rms == 0.)
assert_almost_equal(E1_cos, 0.)
assert_almost_equal(E2_cos, 0.)
stc_bad = stc2.copy().crop(0, 0.5)
assert_raises(ValueError, source_estimate_quantification, stc1, stc_bad)
stc_bad = stc2.copy()
stc_bad.tmin -= 0.1
assert_raises(ValueError, source_estimate_quantification, stc1, stc_bad)
assert_raises(ValueError, source_estimate_quantification, stc1, stc2,
metric='foo')