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)
