def test_random_fn(self):
def myrand(num_rows, num_cols):
# One dm to rule them all...
data = np.empty((num_rows, num_cols))
data.fill(42)
return data
exp = DistanceMatrix(np.asarray([[0, 42, 42], [42, 0, 42],
[42, 42, 0]]), ['1', '2', '3'])
obs = randdm(3, random_fn=myrand)
self.assertEqual(obs, exp)
def test_default_usage(self):
exp = DistanceMatrix(np.asarray([[0.0]]), ['1'])
obs = randdm(1)
self.assertEqual(obs, exp)
obs = randdm(2)
self.assertEqual(obs.shape, (2, 2))
self.assertEqual(obs.ids, ('1', '2'))
obs1 = randdm(5)
num_trials = 10
found_diff = False
for _ in range(num_trials):
obs2 = randdm(5)
if obs1 != obs2:
found_diff = True
break
self.assertTrue(found_diff)
def test_default_usage(self):
exp = DistanceMatrix(np.asarray([[0.0]]), ['1'])
obs = randdm(1)
self.assertEqual(obs, exp)
obs = randdm(2)
self.assertEqual(obs.shape, (2, 2))
self.assertEqual(obs.ids, ('1', '2'))
obs1 = randdm(5)
num_trials = 10
found_diff = False
for _ in range(num_trials):
obs2 = randdm(5)
if obs1 != obs2:
found_diff = True
break
self.assertTrue(found_diff)
def test_random_fn(self):
def myrand(num_rows, num_cols):
# One dm to rule them all...
data = np.empty((num_rows, num_cols))
data.fill(42)
return data
exp = DistanceMatrix(np.asarray([[0, 42, 42], [42, 0, 42],
[42, 42, 0]]), ['1', '2', '3'])
obs = randdm(3, random_fn=myrand)
self.assertEqual(obs, exp)
def test_invalid_input(self):
# Invalid dimensions.
with self.assertRaises(DissimilarityMatrixError):
randdm(0)
# Invalid dimensions.
with self.assertRaises(ValueError):
randdm(-1)
# Invalid number of IDs.
with self.assertRaises(DissimilarityMatrixError):
randdm(2, ids=['foo'])
def test_invalid_input(self):
# Invalid dimensions.
with self.assertRaises(DissimilarityMatrixError):
randdm(0)
# Invalid dimensions.
with self.assertRaises(ValueError):
randdm(-1)
# Invalid number of IDs.
with self.assertRaises(DissimilarityMatrixError):
randdm(2, ids=['foo'])
def test_constructor(self):
exp = DissimilarityMatrix(np.asarray([[0.0]]), ['1'])
obs = randdm(1, constructor=DissimilarityMatrix)
self.assertEqual(obs, exp)
self.assertEqual(type(obs), DissimilarityMatrix)
def test_ids(self):
ids = ['foo', 'bar', 'baz']
obs = randdm(3, ids=ids)
self.assertEqual(obs.shape, (3, 3))
self.assertEqual(obs.ids, tuple(ids))
def test_large_matrix_for_symmetry(self):
obs3 = randdm(100)
self.assertEqual(obs3, obs3.T)
def _create_distance_matrix(self, sample_ids):
dm = randdm(len(sample_ids), sample_ids)
fd, fp = mkstemp(suffix='.txt', dir=self.out_dir)
close(fd)
dm.write(fp)
return fp
def test_constructor(self):
exp = DissimilarityMatrix(np.asarray([[0.0]]), ['1'])
obs = randdm(1, constructor=DissimilarityMatrix)
self.assertEqual(obs, exp)
self.assertEqual(type(obs), DissimilarityMatrix)
def test_ids(self):
ids = ['foo', 'bar', 'baz']
obs = randdm(3, ids=ids)
self.assertEqual(obs.shape, (3, 3))
self.assertEqual(obs.ids, tuple(ids))
def test_large_matrix_for_symmetry(self):
obs3 = randdm(100)
self.assertEqual(obs3, obs3.T)
def test_constructor(self):
"""Test generating random dist mats with a specific constructor."""
exp = DissimilarityMatrix(np.asarray([[0.0]]), ['1'])
obs = randdm(1, constructor=DissimilarityMatrix)
self.assertEqual(obs, exp)
self.assertEqual(type(obs), DissimilarityMatrix)
def test_ids(self):
"""Test generating random distance matrices with specific IDs."""
ids = ['foo', 'bar', 'baz']
obs = randdm(3, ids=ids)
self.assertEqual(obs.shape, (3, 3))
self.assertEqual(obs.ids, tuple(ids))
