def multi_mklik(q = Qparams, switch=switch, name="multi_mklik"):
locs = discrete.locs_from_switchpoint(tree,tree[int(switch)],locsarray)
# l = discrete.create_likelihood_function_multimk(tree=tree, chars=chars,
# Qtype=Qtype, locs = locs,
# pi="Equal", min=False)
np.copyto(qarray, q)
return l(qarray, locs=locs)
# 0.38377105527703087
# In between the two rates, but closer to the slow rate
# (which takes up most of the tree) as expected
# Comparing the likelihoods of the MAP estimates,
# for lack of a better comparison
Q1avg = np.percentile(Q1, 50)
Q2avg = np.percentile(Q2, 50)
multiregime_Q = np.array([[[-Q1avg,Q1avg],
[Q1avg,-Q1avg]],
[[-Q2avg,Q2avg],
[Q2avg,-Q2avg]]])
multiregime_locs = discrete.locs_from_switchpoint(mr_tree, mr_tree[int(scipy.stats.mode(out["switch"])[0])])
multiregime_likelihood = discrete.mk_mr(mr_tree, mr_chars,
multiregime_Q, multiregime_locs,
pi="Equal")
singleregime_Q = np.array([[-Qavg,Qavg],
[Qavg,-Qavg]])
singleregime_likelihood = discrete.mk(mr_tree, mr_chars, singleregime_Q,
pi="Equal")
multiregime_likelihood
singleregime_likelihood
# 0.38377105527703087
# In between the two rates, but closer to the slow rate
# (which takes up most of the tree) as expected
# Comparing the likelihoods of the MAP estimates,
# for lack of a better comparison
Q1avg = np.percentile(Q1, 50)
Q2avg = np.percentile(Q2, 50)
multiregime_Q = np.array([[[-Q1avg,Q1avg],
[Q1avg,-Q1avg]],
[[-Q2avg,Q2avg],
[Q2avg,-Q2avg]]])
multiregime_locs = discrete.locs_from_switchpoint(mr_tree, mr_tree[int(scipy.stats.mode(out["switch"])[0])])
multiregime_likelihood = discrete.mk_multi_regime(mr_tree, mr_chars,
multiregime_Q, multiregime_locs,
pi="Equal")
singleregime_Q = np.array([[-Qavg,Qavg],
[Qavg,-Qavg]])
singleregime_likelihood = discrete.mk(mr_tree, mr_chars, singleregime_Q,
pi="Equal")
multiregime_likelihood
singleregime_likelihood
