def test_anosim_pairwise(self):
dm = skbio.DistanceMatrix([[0.00, 0.25, 0.25],
[0.25, 0.00, 0.00],
[0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.CategoricalMetadataColumn(
pd.Series(['a', 'b', 'b'], name='a or b',
index=pd.Index(['sample1', 'sample2', 'sample3'],
name='id')))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, method='anosim',
permutations=42, pairwise=True)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue(os.path.exists(index_fp))
# all expected boxplots are generated
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'a-boxplots.pdf')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'a-boxplots.png')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'b-boxplots.pdf')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'b-boxplots.png')))
# no extra boxplots are generated
self.assertEqual(len(glob.glob('%s/*-boxplots.pdf' % output_dir)),
2)
self.assertEqual(len(glob.glob('%s/*-boxplots.png' % output_dir)),
2)
self.assertTrue('ANOSIM results' in open(index_fp).read())
self.assertTrue('<td>42</td>' in open(index_fp).read())
self.assertFalse('Warning' in open(index_fp).read())
self.assertTrue('Pairwise anosim' in open(index_fp).read())
def test_permanova_pairwise(self):
dm = skbio.DistanceMatrix([[0.00, 0.25, 0.25],
[0.25, 0.00, 0.00],
[0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b'], name='a or b',
index=['sample1', 'sample2', 'sample3']))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, pairwise=True)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue(os.path.exists(index_fp))
# all expected boxplots are generated
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'a-boxplots.pdf')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'a-boxplots.png')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'b-boxplots.pdf')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'b-boxplots.png')))
# no extra boxplots are generated
self.assertEqual(len(glob.glob('%s/*-boxplots.pdf' % output_dir)),
2)
self.assertEqual(len(glob.glob('%s/*-boxplots.png' % output_dir)),
2)
self.assertTrue('PERMANOVA results' in open(index_fp).read())
self.assertTrue('Pairwise permanova' in open(index_fp).read())
self.assertFalse('Warning' in open(index_fp).read())
def test_anosim_pairwise(self):
dm = skbio.DistanceMatrix([[0.00, 0.25, 0.25],
[0.25, 0.00, 0.00],
[0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.CategoricalMetadataColumn(
pd.Series(['a', 'b', 'b'], name='a or b',
index=pd.Index(['sample1', 'sample2', 'sample3'],
name='id')))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, method='anosim',
permutations=42, pairwise=True)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue(os.path.exists(index_fp))
# all expected boxplots are generated
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'a-boxplots.pdf')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'a-boxplots.png')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'b-boxplots.pdf')))
self.assertTrue(os.path.exists(
os.path.join(output_dir, 'b-boxplots.png')))
# no extra boxplots are generated
self.assertEqual(len(glob.glob('%s/*-boxplots.pdf' % output_dir)),
2)
self.assertEqual(len(glob.glob('%s/*-boxplots.png' % output_dir)),
2)
self.assertTrue('ANOSIM results' in open(index_fp).read())
self.assertTrue('<td>42</td>' in open(index_fp).read())
self.assertFalse('Warning' in open(index_fp).read())
self.assertTrue('Pairwise anosim' in open(index_fp).read())
def test_permanova_pairwise(self):
dm = skbio.DistanceMatrix(
[[0.00, 0.25, 0.25], [0.25, 0.00, 0.00], [0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b'],
name='a or b',
index=['sample1', 'sample2', 'sample3']))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, pairwise=True)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue(os.path.exists(index_fp))
# all expected boxplots are generated
self.assertTrue(
os.path.exists(os.path.join(output_dir, 'a-boxplots.pdf')))
self.assertTrue(
os.path.exists(os.path.join(output_dir, 'a-boxplots.png')))
self.assertTrue(
os.path.exists(os.path.join(output_dir, 'b-boxplots.pdf')))
self.assertTrue(
os.path.exists(os.path.join(output_dir, 'b-boxplots.png')))
# no extra boxplots are generated
self.assertEqual(len(glob.glob('%s/*-boxplots.pdf' % output_dir)),
2)
self.assertEqual(len(glob.glob('%s/*-boxplots.png' % output_dir)),
2)
self.assertTrue('PERMANOVA results' in open(index_fp).read())
self.assertTrue('Pairwise permanova' in open(index_fp).read())
self.assertFalse('Warning' in open(index_fp).read())
def test_invalid_method(self):
dm = skbio.DistanceMatrix([[0.00, 0.25, 0.25],
[0.25, 0.00, 0.00],
[0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b'], name='a or b',
index=['sample1', 'sample2', 'sample3']))
with self.assertRaises(ValueError):
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, method='bad!')
def test_invalid_method(self):
dm = skbio.DistanceMatrix(
[[0.00, 0.25, 0.25], [0.25, 0.00, 0.00], [0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b'],
name='a or b',
index=['sample1', 'sample2', 'sample3']))
with self.assertRaises(ValueError):
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, method='bad!')
def test_extra_metadata(self):
dm = skbio.DistanceMatrix([[0.00, 0.25, 0.25],
[0.25, 0.00, 0.00],
[0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b', 'c'], name='a or b',
index=['sample1', 'sample2', 'sample3', 'sample4']))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, permutations=42)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue('<td>2</td>' in open(index_fp).read())
def test_extra_metadata(self):
dm = skbio.DistanceMatrix(
[[0.00, 0.25, 0.25], [0.25, 0.00, 0.00], [0.25, 0.00, 0.00]],
ids=['sample1', 'sample2', 'sample3'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b', 'c'],
name='a or b',
index=['sample1', 'sample2', 'sample3', 'sample4']))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md, permutations=42)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue('<td>2</td>' in open(index_fp).read())
def test_filtered_samples_str_metadata(self):
dm = skbio.DistanceMatrix(
[[0.00, 0.25, 0.25, 0.66], [0.25, 0.00, 0.00, 0.66],
[0.25, 0.00, 0.00, 0.66], [0.66, 0.66, 0.66, 0.00]],
ids=['sample1', 'sample2', 'sample3', 'sample4'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b', ''],
name='a or b',
index=['sample1', 'sample2', 'sample3', 'sample4']))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue('Warning' in open(index_fp).read())
def test_filtered_samples_str_metadata(self):
dm = skbio.DistanceMatrix([[0.00, 0.25, 0.25, 0.66],
[0.25, 0.00, 0.00, 0.66],
[0.25, 0.00, 0.00, 0.66],
[0.66, 0.66, 0.66, 0.00]],
ids=['sample1', 'sample2', 'sample3',
'sample4'])
md = qiime2.MetadataCategory(
pd.Series(['a', 'b', 'b', ''], name='a or b',
index=['sample1', 'sample2', 'sample3', 'sample4']))
with tempfile.TemporaryDirectory() as output_dir:
beta_group_significance(output_dir, dm, md)
index_fp = os.path.join(output_dir, 'index.html')
self.assertTrue('Warning' in open(index_fp).read())
