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')