def test_diversity_gini2(create_testfolder, metric): f = create_testfolder / "test.h5" vdj = ddl.read_h5(f) vdj.data['sample_id'] = 'sample_test' vdj.data['contig_QC_pass'] = '******' ddl.update_metadata(vdj, retrieve=['sample_id', 'contig_QC_pass'], split=False) ddl.tl.clone_diversity(vdj, groupby='sample_id', resample=True, downsample=6, key='sequence', n_resample=5, metric=metric) if metric == 'clone_network' or metric is None: assert not vdj.metadata.clone_network_cluster_size_gini.empty assert not vdj.metadata.clone_network_vertex_size_gini.empty if metric == 'clone_degree': assert not vdj.metadata.clone_degree.empty assert not vdj.metadata.clone_size_gini.empty assert not vdj.metadata.clone_degree_gini.empty if metric == 'clone_centrality': assert not vdj.metadata.clone_centrality.empty assert not vdj.metadata.clone_centrality_gini.empty
def test_diversity_rarefaction3(create_testfolder): f = create_testfolder / "test.h5" vdj = ddl.read_h5(f) vdj.data['sample_id'] = 'sample_test' vdj.data['contig_QC_pass'] = '******' ddl.update_metadata(vdj, retrieve=['sample_id', 'contig_QC_pass'], split=False) df = ddl.tl.clone_rarefaction(vdj, groupby='sample_id') assert isinstance(df, dict) p = ddl.pl.clone_rarefaction(vdj, color='sample_id') assert p is not None
def test_diversity2c(create_testfolder): f = create_testfolder / "test.h5" vdj = ddl.read_h5(f) vdj.data['sample_id'] = 'sample_test' vdj.data['contig_QC_pass'] = '******' ddl.update_metadata(vdj, retrieve=['sample_id', 'contig_QC_pass'], split=False) x = ddl.tl.clone_diversity(vdj, groupby='sample_id', key='sequence', update_obs_meta=False) assert isinstance(x, pd.DataFrame)
def test_diversity2b(create_testfolder): f = create_testfolder / "test.h5" vdj = ddl.read_h5(f) vdj.data['sample_id'] = 'sample_test' vdj.data['contig_QC_pass'] = '******' ddl.update_metadata(vdj, retrieve=['sample_id', 'contig_QC_pass'], split=False) ddl.tl.clone_diversity(vdj, groupby='sample_id', use_contracted=True, key='sequence') assert not vdj.metadata.clone_network_cluster_size_gini.empty assert not vdj.metadata.clone_network_vertex_size_gini.empty
def test_diversity2a(create_testfolder): f = create_testfolder / "test.h5" vdj = ddl.read_h5(f) vdj.data['sample_id'] = 'sample_test' vdj.data['contig_QC_pass'] = '******' ddl.update_metadata( vdj, retrieve=['sample_id', 'contig_QC_pass'], retrieve_mode=['merge and unique only', 'merge and unique only']) ddl.tl.clone_diversity(vdj, groupby='sample_id', reconstruct_network=False, key='sequence') assert not vdj.metadata.clone_network_cluster_size_gini.empty assert not vdj.metadata.clone_network_vertex_size_gini.empty
def test_update_metadata(): test = ddl.read_h5("tests/test2.h5") ddl.update_metadata(test, "sequence_id") test.write_h5("tests/test2.h5", compression="bzip2") print(test)
def test_update_metadata(): test = ddl.read_h5("tests/test.h5") ddl.update_metadata(test, "sequence_id") print(test)