def test_meta_validation(self):
with self.assertRaisesRegex(ValueError, "position 1.*not.*BIOM"):
meta((self.table1, self.not_a_table), (self.tree1, self.tree2),
method='unweighted')
with self.assertRaisesRegex(ValueError, "position 1.*not.*newick"):
meta((self.table1, self.table2), (self.tree1, self.not_a_tree),
method='unweighted')
def test_meta_unifrac_unbalanced(self):
with self.assertRaisesRegex(ValueError, ("Number of trees and tables "
"must be the same.")):
meta(('a', ), ('a', 'b'))
with self.assertRaisesRegex(ValueError, ("Number of trees and tables "
"must be the same.")):
meta(('a', 'b'), ('a', ))
def test_meta_unifrac_unbalanced(self):
with self.assertRaisesRegex(ValueError, ("Number of trees and tables "
"must be the same.")):
meta((self.table1, ), (self.tree1, self.tree2),
method='unweighted')
with self.assertRaisesRegex(ValueError, ("Number of trees and tables "
"must be the same.")):
meta((self.table1, self.table2), (self.tree1, ),
method='unweighted')
def test_meta_unifrac_unbalanced_weights(self):
with self.assertRaisesRegex(
ValueError, "Number of weights does not "
"match number of trees and "
"tables."):
meta(
(self.table1, self.table2),
(self.tree1, self.tree2),
weights=(1, 2, 3),
)
def test_meta_validation(self):
with self.assertRaisesRegex(ValueError,
"Table does not appear to be a "
"BIOM-Format v2.1"):
meta((self.table1, self.not_a_table), (self.tree1, self.tree2),
method='unweighted')
with self.assertRaisesRegex(ValueError,
"The phylogeny does not "
"appear to be newick"):
meta((self.table1, self.table2), (self.tree1, self.not_a_tree),
method='unweighted')
def beta_phylogenetic_meta_passthrough(
tables: BIOMV210Format,
phylogenies: NewickFormat,
metric: str,
threads: int = 1,
variance_adjusted: bool = False,
alpha: float = None,
bypass_tips: bool = False,
weights: list = None,
consolidation: str = 'skipping_missing_values' # noqa
) -> skbio.DistanceMatrix:
# Ideally we remove this when we can support optional type-mapped params.
if alpha is not None and metric != 'generalized_unifrac':
raise ValueError("The alpha parameter is only allowed when the "
"selected metric is 'generalized_unifrac'")
metric_map = {
'unweighted_unifrac': 'unweighted',
'weighted_normalized_unifrac': 'weighted_normalized',
'weighted_unifrac': 'weighted_unnormalized',
'generalized_unifrac': 'generalized'
}
metric = metric_map[metric]
return unifrac.meta(tuple([str(t) for t in tables]),
tuple([str(p) for p in phylogenies]),
weights=weights,
threads=threads,
consolidation=consolidation,
method=metric,
variance_adjusted=variance_adjusted,
alpha=alpha,
bypass_tips=bypass_tips)
def test_meta_unifrac(self):
"""meta_unifrac should give correct result on sample trees"""
result = meta([self.table1, self.table2], [self.tree1, self.tree2],
weights=[1, 1],
consolidation='skipping-missing-values',
method='unweighted')
u1_distances = np.array([[0, 10/16., 8/13.],
[10/16., 0, 8/17.],
[8/13., 8/17., 0]])
u2_distances = np.array([[0, 11/14., 6/13.],
[11/14., 0, 7/13.],
[6/13., 7/13., 0]])
exp = (u1_distances + u2_distances) / 2
npt.assert_almost_equal(exp, result.data)
self.assertEqual(tuple('ABC'), result.ids)
def test_meta_unifrac(self):
"""meta_unifrac should give correct result on sample trees"""
t1 = self.get_data_path('t1.newick')
t2 = self.get_data_path('t2.newick')
e1 = self.get_data_path('e1.biom')
e2 = self.get_data_path('e2.biom')
result = meta([e1, e2], [t1, t2],
weights=[1, 1],
consolidation='skipping-missing-values',
method='unweighted')
u1_distances = np.array([[0, 10 / 16.,
8 / 13.], [10 / 16., 0, 8 / 17.],
[8 / 13., 8 / 17., 0]])
u2_distances = np.array([[0, 11 / 14.,
6 / 13.], [11 / 14., 0, 7 / 13.],
[6 / 13., 7 / 13., 0]])
exp = (u1_distances + u2_distances) / 2
npt.assert_almost_equal(exp, result.data)
self.assertEqual(tuple('ABC'), result.ids)
def test_meta_unifrac_alpha_not_generalized(self):
with self.assertRaisesRegex(ValueError, "The alpha parameter can"):
meta(('a', ), ('b', ),
method='generalized',
alpha=1,
consolidation='skipping_missing_matrices')
def test_meta_unifrac_bad_consolidation(self):
with self.assertRaisesRegex(ValueError,
"Consolidation \(foo\) unrecognized."):
meta(('a', ), ('b', ), method='unweighted', consolidation='foo')
def test_meta_unifrac_bad_method(self):
with self.assertRaisesRegex(ValueError, "Method \(bar\) "
"unrecognized."):
meta(('a', ), ('b', ), method='bar')
def test_meta_unifrac_no_method(self):
with self.assertRaisesRegex(ValueError, "No method specified."):
meta(('a', ), ('b', ))
def test_meta_unifrac_missing(self):
with self.assertRaisesRegex(ValueError, "No trees specified."):
meta(('a', ), tuple())
with self.assertRaisesRegex(ValueError, "No tables specified."):
meta(tuple(), ('a', ))
def test_meta_unifrac_bad_method(self):
with self.assertRaisesRegex(ValueError, r"Method \(bar\) "
"unrecognized."):
meta((self.table1, ), (self.tree1, ), method='bar')
def test_meta_unifrac_missing(self):
with self.assertRaisesRegex(ValueError, "No trees specified."):
meta((self.table1, ), tuple(), method='unweighted')
with self.assertRaisesRegex(ValueError, "No tables specified."):
meta(tuple(), (self.tree1, ), method='unweighted')
