def test_evaluate_composition_depth_too_high(self):
with self.assertRaisesRegex(ValueError, "8 is larger than the max"):
_evaluate_composition(
self.exp, self.obs, depth=8, palette='Set1',
plot_tar=True, plot_tdr=True, plot_r_value=True,
plot_r_squared=True, plot_bray_curtis=False,
plot_jaccard=False, plot_observed_features=True,
plot_observed_features_ratio=True, metadata=None)
def test_evaluate_composition_metadata_not_superset(self):
incomplete_md = qiime2.CategoricalMetadataColumn(
pd.Series(['there_can_only_be_one'], name='mock_id',
index=pd.Index(['s3'], name='id')))
with self.assertRaisesRegex(ValueError, "Missing samples in metadata"):
_evaluate_composition(
self.exp_one_sample, self.obs, depth=7, palette='Set1',
plot_tar=True, plot_tdr=True, plot_r_value=True,
plot_r_squared=True, plot_bray_curtis=False,
plot_jaccard=False, plot_observed_features=True,
plot_observed_features_ratio=True, metadata=incomplete_md)
def test_evaluate_composition_metadata_values_not_subset(self):
underrepresented_md = qiime2.CategoricalMetadataColumn(
pd.Series(['there_can_only_be_one', 'what_is_this?',
'i_am_not_really_here'],
name='mock_id', index=pd.Index(['s3', 's1', 's2'],
name='id')))
with self.assertRaisesRegex(ValueError, "Missing samples in table"):
_evaluate_composition(
self.exp_one_sample, self.obs, depth=7, palette='Set1',
plot_tar=True, plot_tdr=True, plot_r_value=True,
plot_r_squared=True, plot_bray_curtis=False,
plot_jaccard=False, plot_observed_features=True,
plot_observed_features_ratio=True,
metadata=underrepresented_md)
def test_evaluate_composition_metadata_not_superset(self):
incomplete_md = qiime2.MetadataCategory(
pd.DataFrame({'mock_id': ['there_can_only_be_one']},
index=['s3'])['mock_id'])
with self.assertRaisesRegex(ValueError, "Missing samples in metadata"):
_evaluate_composition(self.exp_one_sample,
self.obs,
depth=7,
palette='Set1',
plot_tar=True,
plot_tdr=True,
plot_r_value=True,
plot_r_squared=True,
plot_observed_features=True,
plot_observed_features_ratio=True,
metadata=incomplete_md)
def test_evaluate_composition_dont_test_all_levels(self):
empty_expectations = pd.DataFrame(
columns=['s1', 's2', 's3']).astype(float)
empty_expectations.index.name = 'Taxon'
mc = self.misclassified.loc[[
'k__Ag;p__Bg;c__Cg;o__Dg;f__Eg;g__Fg;s__Gg'
]]
mc.index = ['k__Ag;p__Bg;c__Cg;o__Dg;f__Eg']
mc.index.name = 'Taxon'
res = _evaluate_composition(self.exp,
self.obs,
depth=5,
palette='Set1',
plot_tar=True,
plot_tdr=True,
plot_r_value=True,
plot_r_squared=True,
plot_observed_features=True,
plot_observed_features_ratio=True,
metadata=None)
pdt.assert_frame_equal(res[0],
self.exp_results[self.exp_results['level'] < 6])
pdt.assert_frame_equal(res[1], empty_expectations)
pdt.assert_frame_equal(res[2], mc)
pdt.assert_frame_equal(res[3], empty_expectations)
def test_evaluate_composition_mockrobiota(self):
res = _evaluate_composition(
self.exp, self.obs, depth=7, palette='Set1',
plot_tar=True, plot_tdr=True, plot_r_value=True,
plot_r_squared=True, plot_bray_curtis=True,
plot_jaccard=True, plot_observed_features=True,
plot_observed_features_ratio=True, metadata=None)
pdt.assert_frame_equal(res[0], self.exp_results)
pdt.assert_frame_equal(res[1], self.false_neg)
pdt.assert_frame_equal(res[2], self.misclassified)
pdt.assert_frame_equal(res[3], self.underclassified)
def test_evaluate_composition_metadata_values_not_subset(self):
underrepresented_md = qiime2.MetadataCategory(
pd.DataFrame(
{
'mock_id': [
'there_can_only_be_one', 'what_is_this?',
'i_am_not_really_here'
]
},
index=['s3', 's1', 's2'])['mock_id'])
with self.assertRaisesRegex(ValueError, "Missing samples in table"):
_evaluate_composition(self.exp_one_sample,
self.obs,
depth=7,
palette='Set1',
plot_tar=True,
plot_tdr=True,
plot_r_value=True,
plot_r_squared=True,
plot_observed_features=True,
plot_observed_features_ratio=True,
metadata=underrepresented_md)
def test_evaluate_composition_mockrobiota_metadata_map(self):
res = _evaluate_composition(
self.exp, self.obs, depth=7, palette='Set1',
plot_tar=True, plot_tdr=True, plot_r_value=True,
plot_r_squared=True, plot_bray_curtis=False,
plot_jaccard=False, plot_observed_features=True,
plot_observed_features_ratio=True, metadata=self.metadata)
false_neg = self.false_neg[['HMPMockV1.1.Even1',
'HMPMockV1.2.Staggered1']]
pdt.assert_frame_equal(res[0], self.exp_results)
pdt.assert_frame_equal(res[1], false_neg)
pdt.assert_frame_equal(res[2], self.misclassified)
pdt.assert_frame_equal(res[3], self.underclassified)
def test_evaluate_composition_metadata_map_to_mock_sample(self):
res = _evaluate_composition(
self.exp_one_sample, self.obs, depth=7, palette='Set1',
plot_tar=True, plot_tdr=True, plot_r_value=True,
plot_r_squared=True, plot_bray_curtis=False,
plot_jaccard=False, plot_observed_features=True,
plot_observed_features_ratio=True,
metadata=self.metadata_one_sample)
pdt.assert_frame_equal(res[0], self.exp_results)
# false_neg should contain only one column header since the map
# contains one sample (rename to match column name in exp_one_sample)
false_neg = self.false_neg[['s1']]
false_neg.columns = ['there_can_only_be_one']
false_neg.index.name = 'Taxon'
pdt.assert_frame_equal(res[1], false_neg)
pdt.assert_frame_equal(res[2], self.misclassified)
pdt.assert_frame_equal(res[3], self.underclassified)
