def test_with_metadata(self):
md = qiime2.CategoricalMetadataColumn(
pd.Series(['milo', 'summer', 'russ'], name='pet',
index=pd.Index(['S1', 'S2', 'S3'], name='id')))
heatmap(self.output_dir, self.table, metadata=md)
self.assertBasicVizValidity(self.output_dir)
def test_table_ids_are_subset_of_metadata_ids(self):
md = qiime2.CategoricalMetadataColumn(
pd.Series(['milo', 'russ'], name='pet',
index=pd.Index(['S1', 'S3'], name='id')))
with self.assertRaisesRegex(ValueError, 'not present.*S2'):
heatmap(self.output_dir, self.table, metadata=md)
def test_with_feature_metadata(self):
feature_md = qiime2.CategoricalMetadataColumn(
pd.Series(['peanut', 'dog'], name='species',
index=pd.Index(['O1', 'O2'], name='id')))
heatmap(self.output_dir, self.table, feature_metadata=feature_md)
self.assertBasicVizValidity(self.output_dir)
def test_with_metadata(self):
md = qiime2.CategoricalMetadataColumn(
pd.Series(['milo', 'summer', 'russ'], name='pet',
index=pd.Index(['S1', 'S2', 'S3'], name='id')))
heatmap(self.output_dir, self.table, metadata=md)
self.assertBasicVizValidity(self.output_dir)
def test_table_ids_are_subset_of_metadata_ids(self):
md = qiime2.CategoricalMetadataColumn(
pd.Series(['milo', 'russ'], name='pet',
index=pd.Index(['S1', 'S3'], name='id')))
with self.assertRaisesRegex(ValueError, 'not present.*S2'):
heatmap(self.output_dir, self.table, metadata=md)
def test_extra_metadata_ids(self):
md = qiime2.MetadataCategory(
pd.Series(['milo', 'summer', 'russ', 'peanut'],
name='pet',
index=['S1', 'S2', 'S3', 'S4']))
heatmap(self.output_dir, self.table, metadata=md)
self.assertBasicVizValidity(self.output_dir)
def test_no_sample_cluster(self):
md = qiime2.CategoricalMetadataColumn(
pd.Series(['milo', 'summer', 'russ'], name='pet',
index=pd.Index(['S1', 'S2', 'S3'], name='id')))
heatmap(self.output_dir, self.table, sample_metadata=md,
cluster='features')
self.assertBasicVizValidity(self.output_dir)
def test_with_sample_and_feature_metadata(self):
md = qiime2.CategoricalMetadataColumn(
pd.Series(['milo', 'summer', 'russ'], name='pet',
index=pd.Index(['S1', 'S2', 'S3'], name='id')))
feature_md = qiime2.CategoricalMetadataColumn(
pd.Series(['peanut', 'dog'], name='species',
index=pd.Index(['O1', 'O2'], name='id')))
heatmap(self.output_dir, self.table, sample_metadata=md,
feature_metadata=feature_md)
self.assertBasicVizValidity(self.output_dir)
def test_with_title(self):
heatmap(self.output_dir, self.table, title='foo')
self.assertBasicVizValidity(self.output_dir)
def test_defaults(self):
heatmap(self.output_dir, self.table)
self.assertBasicVizValidity(self.output_dir)
def test_no_normalization(self):
heatmap(self.output_dir, self.table, normalize=False)
self.assertBasicVizValidity(self.output_dir, normalize=False)
def test_empty_table(self):
empty_table = pd.DataFrame([], [], [])
with self.assertRaisesRegex(ValueError, 'empty'):
heatmap(self.output_dir, empty_table)
def test_with_title(self):
heatmap(self.output_dir, self.table, title='foo')
self.assertBasicVizValidity(self.output_dir)
def test_defaults(self):
heatmap(self.output_dir, self.table)
self.assertBasicVizValidity(self.output_dir)
def test_empty_table(self):
empty_table = pd.DataFrame([], [], [])
with self.assertRaisesRegex(ValueError, 'empty'):
heatmap(self.output_dir, empty_table)
def test_no_normalization(self):
heatmap(self.output_dir, self.table, normalize=False)
self.assertBasicVizValidity(self.output_dir, normalize=False)
def test_table_ids_are_subset_of_metadata_ids(self):
md = qiime2.MetadataCategory(
pd.Series(['milo', 'russ'], name='pet', index=['S1', 'S3']))
with self.assertRaisesRegex(ValueError, 'Missing'):
heatmap(self.output_dir, self.table, metadata=md)
