def test_unweighted_sample_external(self):
pda = Pda(sequence_data_path=self.sequences_data_path, tree_path=self.tree_path)
expected_sample = {"A", "D", "E"}
accepted_sample = pda.get_sample(3, self.aux_dir, use_external=True)
if type(accepted_sample) is str:
accepted_sample = list(SeqIO.parse(accepted_sample, "fasta"))
accepted_sample = set([record.id for record in accepted_sample])
self.assertEqual(accepted_sample, expected_sample)
def test_weighted_sample_no_normalization_external(self):
pda = Pda(
sequence_data_path=self.sequences_data_path,
tree_path=self.tree_path,
taxon_to_weight={"A": 0.5, "B": 0.5, "C": 1, "D": 0.01, "E": 0.5},
)
expected_sample = {"A", "D", "E"}
accepted_sample = pda.get_sample(3, self.aux_dir, use_external=True)
if type(accepted_sample) is str:
accepted_sample = list(SeqIO.parse(accepted_sample, "fasta"))
accepted_sample = set([record.id for record in accepted_sample])
self.assertEqual(accepted_sample, expected_sample)
def test_null_weighted_sample(self):
pda = Pda(
sequence_data_path=self.sequences_data_path,
tree_path=self.tree_path,
taxon_to_weight={"A": 1, "B": 1, "C": 1, "D": 1, "E": 1},
)
expected_sample = {"A", "D", "E"}
accepted_sample = pda.get_sample(3, self.aux_dir)
if type(accepted_sample) is str:
accepted_sample = list(SeqIO.parse(accepted_sample, "fasta"))
accepted_sample = set([record.id for record in accepted_sample])
self.assertEqual(accepted_sample, expected_sample)
def test_computed_weights(self):
pda = Pda(sequence_data_path=self.sequences_data_path, tree_path=self.tree_path)
pda.compute_taxon_weights(f"/data/test/aligned_seq_data.fas")
self.assertEqual(
pda.taxon_to_weight,
{
"A": 0.68359375,
"B": 0.68359375,
"C": 0.3645833333333333,
"D": 0.5911458333333334,
"E": 0.7356770833333334,
"F": 0.7356770833333334,
"G": 0.7356770833333334,
"H": 0.7356770833333334,
},
)