def test_fasttree_underscore_ids(self):
input_fp = self.get_data_path('aligned-dna-sequences-2.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = fasttree(input_sequences)
# load the resulting tree and test that it has the right number of
# tips and the right tip ids (the branch lengths can vary with
# different versions of FastTree)
obs_tree = skbio.TreeNode.read(str(obs))
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
tip_names.sort()
self.assertEqual(tip_names, ['_s_e_q_1_', '_s_e_q_2_'])
def test_fasttree_underscore_ids(self):
input_fp = self.get_data_path('aligned-dna-sequences-2.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = fasttree(input_sequences)
# load the resulting tree and test that it has the right number of
# tips and the right tip ids (the branch lengths can vary with
# different versions of FastTree)
obs_tree = skbio.TreeNode.read(str(obs))
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
tip_names.sort()
self.assertEqual(tip_names, ['_s_e_q_1_', '_s_e_q_2_'])
def test_fasttree_n_threads(self):
input_fp = self.get_data_path('aligned-dna-sequences-1.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = fasttree(input_sequences, n_threads='auto')
# load the resulting tree and test that it has the right number of
# tips and the right tip ids (the branch lengths can vary with
# different versions of FastTree, and threading can produce
# non-deterministic trees)
obs_tree = skbio.TreeNode.read(str(obs))
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
tip_names.sort()
self.assertEqual(tip_names, ['seq1', 'seq2'])
def test_fasttree_n_threads(self):
input_fp = self.get_data_path('aligned-dna-sequences-1.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = fasttree(input_sequences, n_threads=-1)
# load the resulting tree and test that it has the right number of
# tips and the right tip ids (the branch lengths can vary with
# different versions of FastTree, and threading can produce
# non-deterministic trees)
obs_tree = skbio.TreeNode.read(str(obs))
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
tip_names.sort()
self.assertEqual(tip_names, ['seq1', 'seq2'])
def test_fasttree(self):
input_fp = self.get_data_path('aligned-dna-sequences-1.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = fasttree(input_sequences)
# load the resulting tree and test that it has the right number of
# tips and the right tip ids (the branch lengths can vary with
# different versions of FastTree)
obs_tree = skbio.io.read(obs.open(),
format='newick',
into=skbio.TreeNode)
tips = list(obs_tree.tips())
self.assertEqual(len(tips), 2)
tip_names = [t.name for t in tips]
tip_names.sort()
self.assertEqual(tip_names, ['seq1', 'seq2'])
def test_fasttree_num_threads(capfd):
# Rather than providing an actual filepath, we just run a 'help' command
# Ideally, we supply --help in this param, but not available in FastTree
# So we are using -expert instead, so that FastTree doesn't fail
# ######################
# Output preview/example:
# ######################
# Detailed usage for FastTree 2.1.10 Double precision (No SSE3):
# FastTree [-nt] [-n 100] [-quote] [-pseudo | -pseudo 1.0]
# [-boot 1000 | -nosupport]
# [-intree starting_trees_file | -intree1 starting_tree_file]
# [-quiet | -nopr]
# [-nni 10] [-spr 2] [-noml | -mllen | -mlnni 10]
# [-mlacc 2] [-cat 20 | -nocat] [-gamma]
# [-slow | -fastest] [-2nd | -no2nd] [-slownni] [-seed 1253]
# [-top | -notop] [-topm 1.0 [-close 0.75] [-refresh 0.8]]
# [-matrix Matrix | -nomatrix] [-nj | -bionj]
# [-lg] [-wag] [-nt] [-gtr] [-gtrrates ac ag at cg ct gt]
# [-gtrfreq A C G T]
# [ -constraints constraintAlignment
# [ -constraintWeight 100.0 ] ]
# [-log logfile]
# [ alignment_file ]
# [ -out output_newick_file | > newick_tree]
fasttree('-expert', n_threads=1)
captured = capfd.readouterr()
assert 'OpenMP' not in captured.err
fasttree('-expert', n_threads=20)
captured = capfd.readouterr()
assert 'OpenMP (20 threads)' in captured.err
# This test case ensures that when a user enters 'auto', the n_threads
# var will still be set to the max available on their machine, even if
# the OMP_NUM_THREADS env var has been set on their machine
os.environ['OMP_NUM_THREADS'] = '2560'
fasttree('-expert', n_threads='auto')
captured = capfd.readouterr()
assert 'OpenMP (2560 threads)' not in captured.err
