def test_trans_switch_single(self):
"""
Calculate transitions probabilities for switching between blocks
Only calculate a single matrix
"""
k = 5
n = 1e4
rho = 1.5e-8 * 100
mu = 2.5e-8
length = 1000
arg = arglib.sample_arg(k, n, rho, start=0, end=length)
#arglib.write_arg("tmp/a.arg", arg)
#arg = arglib.read_arg("tmp/a.arg")
#arg.set_ancestral()
muts = arglib.sample_arg_mutations(arg, mu)
seqs = arglib.make_alignment(arg, muts)
times = arghmm.get_time_points(5)
arghmm.discretize_arg(arg, times)
new_name = "n%d" % (k - 1)
arg = arghmm.remove_arg_thread(arg, new_name)
model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)
# get recombs
recombs = list(x.pos for x in arghmm.iter_visible_recombs(arg))
print "recomb", recombs
pos = recombs[0] + 1
tree = arg.get_marginal_tree(pos - .5)
last_tree = arg.get_marginal_tree(pos - 1 - .5)
print "states1>>", model.states[pos - 1]
print "states2>>", model.states[pos]
treelib.draw_tree_names(last_tree.get_tree(), minlen=5, maxlen=5)
treelib.draw_tree_names(tree.get_tree(), minlen=5, maxlen=5)
print "pos>>", pos
recomb = [x for x in tree
if x.event == "recomb" and x.pos + 1 == pos][0]
mat = arghmm.calc_transition_probs_switch(tree, last_tree, recomb.name,
model.states[pos - 1],
model.states[pos],
model.nlineages, model.times,
model.time_steps,
model.popsizes, rho)
pc(mat)
def test_trans_switch_single(self):
"""
Calculate transitions probabilities for switching between blocks
Only calculate a single matrix
"""
k = 5
n = 1e4
rho = 1.5e-8 * 100
mu = 2.5e-8
length = 1000
arg = arglib.sample_arg(k, n, rho, start=0, end=length)
#arglib.write_arg("tmp/a.arg", arg)
#arg = arglib.read_arg("tmp/a.arg")
#arg.set_ancestral()
muts = arglib.sample_arg_mutations(arg, mu)
seqs = arglib.make_alignment(arg, muts)
times = arghmm.get_time_points(5)
arghmm.discretize_arg(arg, times)
new_name = "n%d" % (k-1)
arg = arghmm.remove_arg_thread(arg, new_name)
model = arghmm.ArgHmm(arg, seqs, new_name=new_name, times=times)
# get recombs
recombs = list(x.pos for x in arghmm.iter_visible_recombs(arg))
print "recomb", recombs
pos = recombs[0] + 1
tree = arg.get_marginal_tree(pos-.5)
last_tree = arg.get_marginal_tree(pos-1-.5)
print "states1>>", model.states[pos-1]
print "states2>>", model.states[pos]
treelib.draw_tree_names(last_tree.get_tree(), minlen=5, maxlen=5)
treelib.draw_tree_names(tree.get_tree(), minlen=5, maxlen=5)
print "pos>>", pos
recomb = [x for x in tree
if x.event == "recomb" and x.pos+1 == pos][0]
mat = arghmm.calc_transition_probs_switch(
tree, last_tree, recomb.name,
model.states[pos-1], model.states[pos],
model.nlineages, model.times,
model.time_steps, model.popsizes, rho)
pc(mat)
length = 1000
arg = arglib.sample_arg(k, n, rho, start=0, end=length)
arglib.write_arg("tmp/a.arg", arg)
muts = arglib.sample_arg_mutations(arg, mu)
seqs = arglib.make_alignment(arg, muts)
#arg = arglib.read_arg("tmp/a.arg")
#arg.set_ancestral()
#find_recomb_coal(tree, last_tree, recomb_name=None, pos=None)
times = arghmm.get_time_points(30, maxtime=60e3)
arghmm.discretize_arg(arg, times)
# get recombs
recombs = list(x.pos for x in arghmm.iter_visible_recombs(arg))
print "recomb", recombs
pos = recombs[0] + 1
tree = arg.get_marginal_tree(pos-.5)
last_tree = arg.get_marginal_tree(pos-1-.5)
r, c = arghmm.find_recomb_coal(tree, last_tree, pos=pos)
#treelib.draw_tree_names(last_tree.get_tree(), minlen=5, maxlen=5)
#treelib.draw_tree_names(tree.get_tree(), minlen=5, maxlen=5)
model = arghmm.ArgHmm(arg, seqs, new_name="n%d" % (k-1), times=times)
#================================================================
length = 1000
arg = arglib.sample_arg(k, n, rho, start=0, end=length)
arglib.write_arg("tmp/a.arg", arg)
muts = arglib.sample_arg_mutations(arg, mu)
seqs = arglib.make_alignment(arg, muts)
#arg = arglib.read_arg("tmp/a.arg")
#arg.set_ancestral()
#find_recomb_coal(tree, last_tree, recomb_name=None, pos=None)
times = arghmm.get_time_points(30, maxtime=60e3)
arghmm.discretize_arg(arg, times)
# get recombs
recombs = list(x.pos for x in arghmm.iter_visible_recombs(arg))
print "recomb", recombs
pos = recombs[0] + 1
tree = arg.get_marginal_tree(pos - .5)
last_tree = arg.get_marginal_tree(pos - 1 - .5)
r, c = arghmm.find_recomb_coal(tree, last_tree, pos=pos)
#treelib.draw_tree_names(last_tree.get_tree(), minlen=5, maxlen=5)
#treelib.draw_tree_names(tree.get_tree(), minlen=5, maxlen=5)
model = arghmm.ArgHmm(arg, seqs, new_name="n%d" % (k - 1), times=times)
#================================================================
win = summon.Window()