def test_recomb(self):
"""
Investigate the fact that some recombinations are not visible
"""
k = 3
n = 1e4
rho = 1.5e-8 * 20
mu = 2.5e-8
length = 1000
arg = arglib.sample_arg(k, n, rho, start=0, end=length)
times = arghmm.get_time_points(10)
arghmm.discretize_arg(arg, times)
arg.set_ancestral()
arg.prune()
recombs = arglib.get_recomb_pos(arg)
# find recombs by walking
recombs2 = []
i = 0
while True:
tree = arg.get_marginal_tree(i - .5)
recomb = arghmm.find_tree_next_recomb(tree, i + 1, tree=True)
if recomb:
recombs2.append(recomb.pos)
i = recomb.pos
else:
break
# these are suppose to differ because some recombination occur
# in the hole of ancestral sequence intervals
print recombs
print recombs2
arglib.write_arg("tmp/b.arg", arg)
def test_recomb(self):
"""
Investigate the fact that some recombinations are not visible
"""
k = 3
n = 1e4
rho = 1.5e-8 * 20
mu = 2.5e-8
length = 1000
arg = arglib.sample_arg(k, n, rho, start=0, end=length)
times = arghmm.get_time_points(10)
arghmm.discretize_arg(arg, times)
arg.set_ancestral()
arg.prune()
recombs = arglib.get_recomb_pos(arg)
# find recombs by walking
recombs2 = []
i = 0
while True:
tree = arg.get_marginal_tree(i-.5)
recomb = arghmm.find_tree_next_recomb(tree, i+1, tree=True)
if recomb:
recombs2.append(recomb.pos)
i = recomb.pos
else:
break
# these are suppose to differ because some recombination occur
# in the hole of ancestral sequence intervals
print recombs
print recombs2
arglib.write_arg("tmp/b.arg", arg)
#arg2.set_ancestral()
#arg2.prune()
# load model
mu = 2.5e-8
rho = 1.5e-8
new_name = "n4"
model = arghmm.ArgHmm(arg2, seqs, new_name=new_name, times=times,
rho=rho, mu=mu)
pos = 9910
tree = arg2.get_marginal_tree(pos-.5)
last_tree = arg2.get_marginal_tree(pos-1-.5)
recomb = arghmm.find_tree_next_recomb(arg2, pos - 1)
states1 = model.states[pos-1]
states2 = model.states[pos]
model.check_local_tree(pos)
mat = arghmm.calc_transition_probs_switch(
tree, last_tree, recomb.name,
states1, states2,
model.nlineages, model.times,
model.time_steps, model.popsizes, model.rho)
#pos2 = 7000
#n = model.get_num_states(pos2)
#mat2 = [[model.prob_transition(pos2-1, i, pos2, j)
# for j in range(n)] for i in range(n)]
# load model
mu = 2.5e-8
rho = 1.5e-8
new_name = "n4"
model = arghmm.ArgHmm(arg2,
seqs,
new_name=new_name,
times=times,
rho=rho,
mu=mu)
pos = 9910
tree = arg2.get_marginal_tree(pos - .5)
last_tree = arg2.get_marginal_tree(pos - 1 - .5)
recomb = arghmm.find_tree_next_recomb(arg2, pos - 1)
states1 = model.states[pos - 1]
states2 = model.states[pos]
model.check_local_tree(pos)
mat = arghmm.calc_transition_probs_switch(tree, last_tree, recomb.name,
states1, states2,
model.nlineages, model.times,
model.time_steps, model.popsizes,
model.rho)
#pos2 = 7000
#n = model.get_num_states(pos2)
#mat2 = [[model.prob_transition(pos2-1, i, pos2, j)
# for j in range(n)] for i in range(n)]