def test_subsample_features(self):
t = Table(np.array([[0, 1, 3], [1, 1, 2]]).T,
['O1', 'O2', 'O3'],
['S1', 'S2'])
a = subsample(t, 2, 'feature')
self.assertEqual(a.shape, (2, 2))
sample_ids = frozenset(a.ids(axis='observation'))
self.assertIn(sample_ids, set([frozenset(['O1', 'O2']),
frozenset(['O1', 'O3']),
frozenset(['O2', 'O3'])]))
self.assertEqual(set(a.ids(axis='sample')), set(['S1', 'S2']))
for i in a.ids(axis='observation'):
npt.assert_equal(t.data(i, axis='observation'),
a.data(i, axis='observation'))
def test_subsample_features_empty(self):
t = Table(
np.array([[0, 0, 0], [0, 0, 0]]).T, ['O1', 'O2', 'O3'],
['S1', 'S2'])
with self.assertRaisesRegex(ValueError, "contains no"):
subsample(t, 2, 'feature')
def test_subsample_features_oversample(self):
t = Table(
np.array([[0, 1, 3], [1, 1, 2]]).T, ['O1', 'O2', 'O3'],
['S1', 'S2'])
with self.assertRaisesRegex(ValueError, "depth exceeds"):
subsample(t, 10, 'feature')
