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#!/usr/bin/env python
import os
import unittest
from cogent3 import load_aligned_seqs, load_tree
from cogent3.evolve import bootstrap, substitution_model
base_path = os.getcwd()
data_path = os.path.join(base_path, "data")
seqnames = ["Chimpanzee", "Rhesus", "Orangutan", "Human"]
REPLICATES = 2
def float_ge_zero(num, epsilon=1e-6):
"""compare whether a floating point value is >= zero with epsilon
tolerance."""
if num >= 0.0:
return True
elif abs(num - 0.0) < epsilon:
return True
else:
return False
class BootstrapTests(unittest.TestCase):
def gettree(self):
treeobj = load_tree(filename=os.path.join(data_path, "murphy.tree"))
return treeobj.get_sub_tree(seqnames)
def getsubmod(self, choice="F81"):
if choice == "F81":
return substitution_model.TimeReversibleNucleotide(model_gaps=True)
else:
return substitution_model.TimeReversibleNucleotide(
model_gaps=True, predicates={"kappa": "transition"}
)
def getalignmentobj(self):
moltype = self.getsubmod().moltype
alignmentobj = load_aligned_seqs(
os.path.join(data_path, "brca1.fasta"), moltype=moltype
)
return alignmentobj.take_seqs(seqnames)[:1000]
def getcontroller(self, treeobj, submodobj):
return submodobj.make_likelihood_function(treeobj)
def create_null_controller(self, alignobj):
"""A null model controller creator.
We constrain the human chimp branches to be equal."""
treeobj = self.gettree()
submodobj = self.getsubmod()
controller = self.getcontroller(treeobj, submodobj)
# we are setting a local molecular clock for human/chimp
controller.set_local_clock("Human", "Chimpanzee")
return controller
def create_alt_controller(self, alignobj):
"""An alternative model controller. Chimp/Human
branches are free to vary."""
treeobj = self.gettree()
submodobj = self.getsubmod()
controller = self.getcontroller(treeobj, submodobj)
return controller
def calclength(self, likelihood_function):
"""This extracts the length of the human branch and returns it."""
return likelihood_function.get_param_value("length", "Human")
def test_conf_int(self):
"""testing estimation of confidence intervals."""
alignobj = self.getalignmentobj()
bstrap = bootstrap.EstimateConfidenceIntervals(
self.create_null_controller(alignobj), self.calclength, alignobj
)
bstrap.set_num_replicates(REPLICATES)
bstrap.set_seed(1984)
bstrap.run(local=True, show_progress=False)
samplelnL = bstrap.get_sample_lnL()
for lnL in samplelnL:
assert lnL < 0.0, lnL
observed_stat = bstrap.get_observed_stats()
assert float_ge_zero(observed_stat)
samplestats = bstrap.getSampleStats()
for stat in samplestats:
assert float_ge_zero(stat)
self.assertEqual(len(samplelnL), REPLICATES)
self.assertEqual(len(samplestats), REPLICATES)
def test_prob(self):
"""testing estimation of probability."""
alignobj = self.getalignmentobj()
prob_bstrap = bootstrap.EstimateProbability(
self.create_null_controller(alignobj),
self.create_alt_controller(alignobj),
alignobj,
)
prob_bstrap.set_num_replicates(REPLICATES)
prob_bstrap.set_seed(1984)
prob_bstrap.run(local=True, show_progress=False)
self.assertEqual(len(prob_bstrap.get_sample_LR_list()), REPLICATES)
assert float_ge_zero(prob_bstrap.get_observed_LR())
# check the returned sample LR's for being > 0.0
for sample_LR in prob_bstrap.get_sample_LR_list():
# print sample_LR
assert float_ge_zero(sample_LR), sample_LR
# check the returned observed lnL fulfill this assertion too, really
# testing their order
null, alt = prob_bstrap.get_observed_lnL()
assert float_ge_zero(2 * (alt - null))
# now check the structure of the returned sample
for snull, salt in prob_bstrap.get_sample_lnL():
# print salt, snull, 2*(salt-snull)
assert float_ge_zero(2 * (salt - snull))
# be sure we get something back from getprob if proc rank is 0
assert float_ge_zero(prob_bstrap.get_estimated_prob())
if __name__ == "__main__":
unittest.main()
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