def test_summarize_clusters(kind): """Test cluster summary stcs.""" src_surf = SourceSpaces( [dict(vertno=np.arange(10242), type='surf') for _ in range(2)]) assert src_surf.kind == 'surface' src_vol = SourceSpaces([dict(vertno=np.arange(10), type='vol')]) assert src_vol.kind == 'volume' if kind == 'surface': src = src_surf klass = SourceEstimate elif kind == 'volume': src = src_vol klass = VolSourceEstimate else: assert kind == 'mixed' src = src_surf + src_vol klass = MixedSourceEstimate n_vertices = sum(len(s['vertno']) for s in src) clu = (np.random.random([1, n_vertices]), [ (np.array([0]), np.array([0, 2, 4])) ], np.array([0.02, 0.1]), np.array([12, -14, 30])) kwargs = dict() if kind == 'volume': with pytest.raises(ValueError, match='did not match'): summarize_clusters_stc(clu) assert len(src) == 1 kwargs['vertices'] = [src[0]['vertno']] elif kind == 'mixed': kwargs['vertices'] = src stc_sum = summarize_clusters_stc(clu, **kwargs) assert isinstance(stc_sum, klass) assert stc_sum.data.shape[1] == 2 clu[2][0] = 0.3 with pytest.raises(RuntimeError, match='No significant'): summarize_clusters_stc(clu, **kwargs)
def test_summarize_clusters(): """Test cluster summary stcs.""" clu = (np.random.random([1, 20484]), [(np.array([0]), np.array([0, 2, 4]))], np.array([0.02, 0.1]), np.array([12, -14, 30])) stc_sum = summarize_clusters_stc(clu) assert_true(stc_sum.data.shape[1] == 2) clu[2][0] = 0.3 assert_raises(RuntimeError, summarize_clusters_stc, clu)