def test_raxml_num_searches(self):
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences, seed=1723, n_searches=5)
obs_tree = skbio.TreeNode.read(str(obs), convert_underscores=False)
obs_tl = list(obs_tree.tip_tip_distances().to_series())
obs_series = set(['%.4f' % e for e in obs_tl])
exp_tree = skbio.TreeNode.read(self.get_data_path('test3.tre'))
exp_tl = list(exp_tree.tip_tip_distances().to_series())
exp_series = set(['%.4f' % e for e in exp_tl])
self.assertEqual(obs_series, exp_series)
def test_raxml_num_searches(self):
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences, seed=1723, n_searches=5)
obs_tree = skbio.TreeNode.read(str(obs), convert_underscores=False)
obs_tl = list(obs_tree.tip_tip_distances().to_series())
obs_series = set(['%.4f' % e for e in obs_tl])
exp_tree = skbio.TreeNode.read(self.get_data_path('test3.tre'))
exp_tl = list(exp_tree.tip_tip_distances().to_series())
exp_series = set(['%.4f' % e for e in exp_tl])
self.assertEqual(obs_series, exp_series)
def test_raxml_model_choice(self):
# Tip to tip dists should NOT be identical under different models.
# Default is GTRGAMMA, we'll compare ouput to GRTGAMMAI & GTRCAT.
# This test is comparing an ordered series of tip-to-tip distances.
# Take note, that for this comparison to work, all must have the same
# seed value set.
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
# default GTRGAMMA
with redirected_stdio(stderr=os.devnull):
gtrg = raxml(input_sequences, seed=1723)
gtrg_tree = skbio.TreeNode.read(str(gtrg),
convert_underscores=False)
gtrg_td = set(gtrg_tree.tip_tip_distances().to_series())
# set GTRGAMMAI
with redirected_stdio(stderr=os.devnull):
gtrgi = raxml(input_sequences,
seed=1723,
substitution_model='GTRGAMMAI')
gtrgi_tree = skbio.TreeNode.read(str(gtrgi),
convert_underscores=False)
gtrgi_td = set(gtrgi_tree.tip_tip_distances().to_series())
# set GTRCAT
with redirected_stdio(stderr=os.devnull):
gtrcat = raxml(input_sequences,
seed=1723,
substitution_model='GTRCAT')
gtrcat_tree = skbio.TreeNode.read(str(gtrcat),
convert_underscores=False)
gtrcat_td = set(gtrcat_tree.tip_tip_distances().to_series())
# test pairs are not equivalent
self.assertNotEqual(gtrg_td, gtrgi_td)
self.assertNotEqual(gtrg_td, gtrcat_td)
self.assertNotEqual(gtrgi_td, gtrcat_td)
def test_raxml_model_choice(self):
# Tip to tip dists should NOT be identical under different models.
# Default is GTRGAMMA, we'll compare ouput to GRTGAMMAI & GTRCAT.
# This test is comparing an ordered series of tip-to-tip distances.
# Take note, that for this comparison to work, all must have the same
# seed value set.
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
# default GTRGAMMA
with redirected_stdio(stderr=os.devnull):
gtrg = raxml(input_sequences, seed=1723)
gtrg_tree = skbio.TreeNode.read(
str(gtrg), convert_underscores=False)
gtrg_td = set(gtrg_tree.tip_tip_distances().to_series())
# set GTRGAMMAI
with redirected_stdio(stderr=os.devnull):
gtrgi = raxml(input_sequences, seed=1723,
substitution_model='GTRGAMMAI')
gtrgi_tree = skbio.TreeNode.read(
str(gtrgi), convert_underscores=False)
gtrgi_td = set(gtrgi_tree.tip_tip_distances().to_series())
# set GTRCAT
with redirected_stdio(stderr=os.devnull):
gtrcat = raxml(input_sequences, seed=1723,
substitution_model='GTRCAT')
gtrcat_tree = skbio.TreeNode.read(
str(gtrcat), convert_underscores=False)
gtrcat_td = set(gtrcat_tree.tip_tip_distances().to_series())
# test pairs are not equivalent
self.assertNotEqual(gtrg_td, gtrgi_td)
self.assertNotEqual(gtrg_td, gtrcat_td)
self.assertNotEqual(gtrgi_td, gtrcat_td)
def test_raxml(self):
# Test that output tree is made.
# Reads tree output and compares tip labels to expected labels.
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences)
obs_tree = skbio.TreeNode.read(str(obs))
# load the resulting tree and test that it has the right number of
# tips and the right tip ids
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
self.assertEqual(set(tip_names),
set(['GCA001510755', 'GCA001045515', 'GCA000454205',
'GCA000473545', 'GCA000196255', 'GCA000686145',
'GCA001950115', 'GCA001971985', 'GCA900007555']))
def test_raxml(self):
# Test that output tree is made.
# Reads tree output and compares tip labels to expected labels.
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences)
obs_tree = skbio.TreeNode.read(str(obs))
# load the resulting tree and test that it has the right number of
# tips and the right tip ids
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
self.assertEqual(set(tip_names),
set(['GCA001510755', 'GCA001045515', 'GCA000454205',
'GCA000473545', 'GCA000196255', 'GCA002142615',
'GCA000686145', 'GCA001950115', 'GCA001971985',
'GCA900007555']))
def test_raxml_underscore_ids(self):
# Test that output tree is made with underscores in tip IDs.
# Some programs and python wrappers may strip underscores.
# Reads tree output and compares tip labels to expected labels.
input_fp = self.get_data_path('aligned-dna-sequences-4.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences)
obs_tree = skbio.TreeNode.read(str(obs), convert_underscores=False)
# load the resulting tree and test that it has the right number of
# tips and the right tip ids
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
self.assertEqual(set(tip_names),
set(['GCA_001510755_1', 'GCA_001045515_1',
'GCA_000454205_1', 'GCA_000473545_1',
'GCA_000196255_1', 'GCA_002142615_1',
'GCA_000686145_1', 'GCA_001950115_1',
'GCA_001971985_1', 'GCA_900007555_1']))
def test_raxml_underscore_ids(self):
# Test that output tree is made with underscores in tip IDs.
# Some programs and python wrappers may strip underscores.
# Reads tree output and compares tip labels to expected labels.
input_fp = self.get_data_path('aligned-dna-sequences-4.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences)
obs_tree = skbio.TreeNode.read(str(obs), convert_underscores=False)
# load the resulting tree and test that it has the right number of
# tips and the right tip ids
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
self.assertEqual(set(tip_names),
set(['GCA_001510755_1', 'GCA_001045515_1',
'GCA_000454205_1', 'GCA_000473545_1',
'GCA_000196255_1', 'GCA_002142615_1',
'GCA_000686145_1', 'GCA_001950115_1',
'GCA_001971985_1', 'GCA_900007555_1']))
def test_raxml_version(self):
# Test that an output tree is made when invoking threads.
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences, raxml_version='SSE3')
obs_tree = skbio.TreeNode.read(str(obs), convert_underscores=False)
# load the resulting tree and test that it has the right number of
# tips and the right tip ids
tips = list(obs_tree.tips())
tip_names = [t.name for t in tips]
self.assertEqual(set(tip_names),
set(['GCA001510755', 'GCA001045515', 'GCA000454205',
'GCA000473545', 'GCA000196255', 'GCA002142615',
'GCA000686145', 'GCA001950115', 'GCA001971985',
'GCA900007555']))
def test_raxml_with_seed(self):
# Test tip-to-tip dists are identical to manually run RAxML output.
# This test is comparing an ordered series of tip-to-tip distances
# to a tree output from a manual run of the default command:
# raxmlHPC -m GTRGAMMA -p 1723 -s aligned-dna-sequences-3.fasta -n q2
# NOTE: I cleanly rounded the tip-to-tip dists (i.e. `%.4f`) as RAxML
# may return slightly different rounding errors on different
# systems.
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences, seed=1723)
obs_tree = skbio.TreeNode.read(str(obs), convert_underscores=False)
obs_tl = list(obs_tree.tip_tip_distances().to_series())
obs_series = set(['%.4f' % e for e in obs_tl])
exp_tree = skbio.TreeNode.read(self.get_data_path('test.tre'))
exp_tl = list(exp_tree.tip_tip_distances().to_series())
exp_series = set(['%.4f' % e for e in exp_tl])
self.assertEqual(obs_series, exp_series)
def test_raxml_with_seed(self):
# Test tip-to-tip dists are identical to manually run RAxML output.
# This test is comparing an ordered series of tip-to-tip distances
# to a tree output from a manual run of the default command:
# raxmlHPC -m GTRGAMMA -p 1723 -s aligned-dna-sequences-3.fasta -n q2
# NOTE: I cleanly rounded the tip-to-tip dists (i.e. `%.4f`) as RAxML
# may return slightly different rounding errors on different
# systems.
input_fp = self.get_data_path('aligned-dna-sequences-3.fasta')
input_sequences = AlignedDNAFASTAFormat(input_fp, mode='r')
with redirected_stdio(stderr=os.devnull):
obs = raxml(input_sequences, seed=1723)
obs_tree = skbio.TreeNode.read(str(obs), convert_underscores=False)
obs_tl = list(obs_tree.tip_tip_distances().to_series())
obs_series = set(['%.4f' % e for e in obs_tl])
exp_tree = skbio.TreeNode.read(self.get_data_path('test.tre'))
exp_tl = list(exp_tree.tip_tip_distances().to_series())
exp_series = set(['%.4f' % e for e in exp_tl])
self.assertEqual(obs_series, exp_series)
