def setUp(self):
super().setUp()
empty_table_fp = self.get_data_path('empty_table.biom')
self.empty_table_as_BIOMV210Format = \
BIOMV210Format(empty_table_fp, mode='r')
input_table_fp = self.get_data_path('faith_test_table.biom')
self.input_table_as_BIOMV210Format = \
BIOMV210Format(input_table_fp, mode='r')
rf_table_fp = self.get_data_path('faith_test_table_rf.biom')
self.rf_table_as_BIOMV210Format = BIOMV210Format(rf_table_fp, mode='r')
pa_table_fp = self.get_data_path('faith_test_table_pa.biom')
self.pa_table_as_BIOMV210Format = BIOMV210Format(pa_table_fp, mode='r')
empty_tree_fp = self.get_data_path('empty.tree')
self.empty_tree_as_NewickFormat = NewickFormat(empty_tree_fp, mode='r')
input_tree_fp = self.get_data_path('faith_test.tree')
self.input_tree_as_NewickFormat = NewickFormat(input_tree_fp, mode='r')
root_only_tree_fp = self.get_data_path('root_only.tree')
self.root_only_tree_as_NewickFormat = \
NewickFormat(root_only_tree_fp, mode='r')
missing_tip_tree_fp = self.get_data_path('missing_tip.tree')
self.missing_tip_tree_as_NewickFormat = \
NewickFormat(missing_tip_tree_fp, mode='r')
self.expected = pd.Series(
{
'S1': 0.5,
'S2': 0.7,
'S3': 1.0,
'S4': 100.5,
'S5': 101
},
name='faith_pd')
def setUp(self):
super().setUp()
# expected computed with diversity.beta_phylogenetic (weighted_unifrac)
self.expected = skbio.DistanceMatrix(
np.array([0.44656238, 0.23771096, 0.30489123, 0.23446002,
0.65723575, 0.44911772, 0.381904, 0.69144829,
0.39611776, 0.36568012, 0.53377975, 0.48908025,
0.35155196, 0.28318669, 0.57376916, 0.23395746,
0.24658122, 0.60271637, 0.39802552, 0.36567394,
0.68062701, 0.36862049, 0.48350632, 0.33024631,
0.33266697, 0.53464744, 0.74605075, 0.53951035,
0.49680733, 0.79178838, 0.37109012, 0.52629343,
0.22118218, 0.32400805, 0.43189708, 0.59705893]),
ids=('10084.PC.481', '10084.PC.593', '10084.PC.356',
'10084.PC.355', '10084.PC.354', '10084.PC.636',
'10084.PC.635', '10084.PC.607', '10084.PC.634'))
table_fp = self.get_data_path('crawford.biom')
self.table_as_BIOMV210Format = BIOMV210Format(table_fp, mode='r')
rel_freq_table_fp = self.get_data_path('crawford_rf.biom')
self.rf_table_as_BIOMV210Format = BIOMV210Format(rel_freq_table_fp,
mode='r')
tree_fp = self.get_data_path('crawford.nwk')
self.tree_as_NewickFormat = NewickFormat(tree_fp, mode='r')
def setUp(self):
super().setUp()
valid_table_fp = self.get_data_path('two_feature_table.biom')
self.valid_table_as_BIOMV210Format = \
BIOMV210Format(valid_table_fp, mode='r')
# empty table fp generated from self.empty_table with biom v2.1.7
self.empty_table = biom.Table(np.array([]), [], [])
empty_table_fp = self.get_data_path('empty_table.biom')
self.empty_table_as_BIOMV210Format = \
BIOMV210Format(empty_table_fp, mode='r')
empty_tree_fp = self.get_data_path('empty.tree')
self.empty_tree_as_NewickFormat = NewickFormat(empty_tree_fp, mode='r')
root_only_tree_fp = self.get_data_path('root_only.tree')
self.root_only_tree_as_NewickFormat = NewickFormat(root_only_tree_fp,
mode='r')
missing_tip_tree_fp = self.get_data_path('missing_tip.tree')
self.missing_tip_tree_as_NewickFormat = \
NewickFormat(missing_tip_tree_fp, mode='r')
two_feature_tree_fp = self.get_data_path('two_feature.tree')
self.two_feature_tree_as_NewickFormat = \
NewickFormat(two_feature_tree_fp, mode='r')
extra_tip_tree_fp = self.get_data_path('extra_tip.tree')
self.extra_tip_tree_as_NewickFormat = NewickFormat(extra_tip_tree_fp,
mode='r')
valid_tree_fp = self.get_data_path('three_feature.tree')
self.valid_tree_as_NewickFormat = NewickFormat(valid_tree_fp, mode='r')
def setUp(self):
super().setUp()
# expected computed with skbio.diversity.beta_diversity
self.expected = skbio.DistanceMatrix([[0.00, 0.25, 0.25],
[0.25, 0.00, 0.00],
[0.25, 0.00, 0.00]],
ids=['S1', 'S2', 'S3'])
table_fp = self.get_data_path('two_feature_table.biom')
self.table_as_BIOMV210Format = BIOMV210Format(table_fp, mode='r')
rf_table_fp = self.get_data_path('two_feature_rf_table.biom')
self.rf_table_as_BIOMV210Format = BIOMV210Format(rf_table_fp, mode='r')
p_a_table_fp = self.get_data_path('two_feature_p_a_table.biom')
self.p_a_table_as_BIOMV210Format = BIOMV210Format(p_a_table_fp,
mode='r')
self.table_as_artifact = Artifact.import_data(
'FeatureTable[Frequency]', self.table_as_BIOMV210Format)
tree_fp = self.get_data_path('three_feature.tree')
self.tree_as_NewickFormat = NewickFormat(tree_fp, mode='r')
self.tree_as_artifact = Artifact.import_data(
'Phylogeny[Rooted]', self.tree_as_NewickFormat)
self.unweighted_unifrac_thru_framework = self.plugin.actions[
'unweighted_unifrac']
def _2(obj : np.ndarray) -> BIOMV210Format :
# for X in generate data, or generate constraint
ff = BIOMV210Format()
l1, l2 = [str(i) for i in range(len(obj[0]))],[str(i) for i in range(len(obj))]
data = biom.Table(obj.T,observation_ids=l1,sample_ids=l2)
with ff.open() as fh:
data.to_hdf5(fh, generated_by='qiime2 %s' % version)
return ff
def setUp(self):
super().setUp()
@_validate_requested_cpus
def function_no_params():
pass
self.function_no_params = function_no_params
@_validate_requested_cpus
def function_w_param(n_jobs=3):
return n_jobs
self.function_w_n_jobs_param = function_w_param
@_validate_requested_cpus
def function_w_threads(threads=2):
return threads
self.function_w_threads_param = function_w_threads
@_validate_requested_cpus
def function_w_duplicate_params(n_jobs=3, threads=2):
pass
self.function_w_both = function_w_duplicate_params
self.jaccard_thru_framework = self.plugin.actions['jaccard']
self.unweighted_unifrac_thru_framework = self.plugin.actions[
'unweighted_unifrac']
two_feature_table_fp = self.get_data_path('two_feature_table.biom')
self.two_feature_table = biom.load_table(two_feature_table_fp)
self.two_feature_table_as_BIOMV210Format = BIOMV210Format(
two_feature_table_fp, mode='r')
self.two_feature_table_as_artifact = Artifact.import_data(
'FeatureTable[Frequency]', two_feature_table_fp)
larger_table_fp = self.get_data_path('crawford.biom')
self.larger_table_as_artifact = Artifact.import_data(
'FeatureTable[Frequency]', larger_table_fp)
valid_tree_fp = self.get_data_path('three_feature.tree')
self.valid_tree_as_NewickFormat = NewickFormat(valid_tree_fp, mode='r')
self.valid_tree_as_artifact = Artifact.import_data(
'Phylogeny[Rooted]', valid_tree_fp)
larger_tree_fp = self.get_data_path('crawford.nwk')
self.larger_tree_as_artifact = Artifact.import_data(
'Phylogeny[Rooted]', larger_tree_fp)
def setUp(self):
super().setUp()
self.empty_table = biom.Table(np.array([]), [], [])
# empty table generated from self.empty_table with biom v2.1.7
empty_table_fp = self.get_data_path('empty_table.biom')
self.empty_table_as_BIOMV210Format = BIOMV210Format(empty_table_fp,
mode='r')
valid_table_fp = self.get_data_path('crawford.biom')
self.valid_table_as_BIOMV210Format = BIOMV210Format(valid_table_fp,
mode='r')
not_a_table_fp = self.get_data_path('crawford.nwk')
self.invalid_view_type = NewickFormat(not_a_table_fp, mode='r')
self.valid_table_list = [
self.valid_table_as_BIOMV210Format,
self.valid_table_as_BIOMV210Format
]
self.invalid_table_list = [
self.valid_table_as_BIOMV210Format, self.invalid_view_type
]
self.has_empty_table_list = [
self.empty_table_as_BIOMV210Format,
self.valid_table_as_BIOMV210Format
]
@_disallow_empty_tables
def f1(table: biom.Table):
pass
self.function_with_table_param = f1
@_disallow_empty_tables
def f2():
pass
self.function_without_table_param = f2
def _3(ff: BIOMV210Format) -> np.ndarray:
# for X in regress
with ff.open() as fh:
table = biom.Table.from_hdf5(fh)
array = table.matrix_data.toarray().T # numpy array
return array
def test_biomv210_format_validate_negative(self):
filepath = self.get_data_path('feature-table_v100.biom')
format = BIOMV210Format(filepath, mode='r')
with self.assertRaisesRegex(ValidationError, 'BIOMV210Format'):
format.validate()
def test_biomv210_format_validate_positive(self):
filepath = self.get_data_path('feature-table_v210.biom')
format = BIOMV210Format(filepath, mode='r')
format.validate()