def test_beta_errors(self):
skl = Sculptor(self.bt, self.mf, self.tree, 'Day', 'Host',
'unittest-beta-errors')
self.to_delete.append('roc-curves/%s' % skl.name)
skl.randomly_select(5)
with self.assertRaisesRegex(ValueError, 'find one or more metrics'):
skl.beta_table(metrics=['does_not_exist'])
def test_random_select_errors(self):
obs = Sculptor(self.bt, self.mf, self.tree, 'Day', 'Host',
'random-select-errors')
with self.assertRaisesRegex(ValueError, 'uniformly subsampled'):
obs.alpha_table()
with self.assertRaisesRegex(ValueError, 'uniformly subsampled'):
obs.beta_table()
with self.assertRaisesRegex(ValueError, 'uniformly subsampled'):
obs.microbes_over_time()
def test_beta(self):
skl = Sculptor(self.bt, self.mf, self.tree, 'Day', 'Host',
'unittest-test-beta')
path = 'roc-curves/%s/cached-matrices/' % skl.name
# avoid any unwanted accidents
self.to_delete.append('roc-curves/%s/' % skl.name)
np.random.seed(0)
skl.randomly_select(5)
obs = skl.beta_table(['unweighted_unifrac', 'jaccard'])
data = [[
0.3927777777777778, 0.4126532637086283, 0.9375, 0.12499999999999999
], [0.6557886557886559, 0.1365522219610505, 1.0, 0.0]]
columns = [
'unweighted_unifrac_mean', 'unweighted_unifrac_std',
'jaccard_mean', 'jaccard_std'
]
exp = pd.DataFrame(data=data,
columns=columns,
index=pd.Index(['A', 'B'], name='Host'))
pd.util.testing.assert_frame_equal(obs, exp)
self.assertTrue(os.path.exists(path))
self.assertTrue(
os.path.exists(os.path.join(path, 'unweighted_unifrac.full.'
'txt')))
self.assertTrue(os.path.exists(os.path.join(path, 'jaccard.full.txt')))