def get_mixture(cls,
log_counts, codon_distn,
ts, tv, syn, nonsyn, compo, asym_compo,
natural_theta,
):
"""
@return: finite_distn, pre_Q_matrices
"""
cls.check_theta(natural_theta)
p0 = natural_theta[0]
p1 = 1 - p0
first_omega = natural_theta[1]
second_omega = natural_theta[2]
kappa = natural_theta[3]
nt_distn = markovutil.ratios_to_distn(natural_theta[4:4+3])
first_pre_Q = fmutsel.get_pre_Q(
log_counts,
fmutsel.genic_fixation,
ts, tv, syn, nonsyn, compo, asym_compo,
nt_distn, kappa, first_omega,
)
second_pre_Q = fmutsel.get_pre_Q(
log_counts,
fmutsel.genic_fixation,
ts, tv, syn, nonsyn, compo, asym_compo,
nt_distn, kappa, second_omega,
)
return (p0, p1), (first_pre_Q, second_pre_Q)
def get_pre_Q(cls,
log_counts, codon_distn,
ts, tv, syn, nonsyn, compo, asym_compo,
natural_theta,
):
cls.check_theta(natural_theta)
kappa = natural_theta[0]
omega = natural_theta[1]
nt_distn = markovutil.ratios_to_distn(natural_theta[2:5])
pre_Q = fmutsel.get_pre_Q(
log_counts,
fmutsel.preferred_recessive_fixation,
ts, tv, syn, nonsyn, compo, asym_compo,
nt_distn, kappa, omega,
)
return pre_Q
def get_pre_Q(cls,
log_counts, codon_distn,
ts, tv, syn, nonsyn, compo, asym_compo,
theta,
):
cls.check_theta(theta)
kappa = algopy.exp(theta[0])
omega = algopy.exp(theta[1])
nt_distn = markovutil.log_ratios_to_distn(theta[2:5])
pre_Q = fmutsel.get_pre_Q(
log_counts,
fmutsel.preferred_dominant_fixation,
ts, tv, syn, nonsyn, compo, asym_compo,
nt_distn, kappa, omega,
)
return pre_Q
def get_pre_Q(cls,
log_counts, codon_distn,
ts, tv, syn, nonsyn, compo, asym_compo,
natural_theta,
):
cls.check_theta(natural_theta)
first_proportion = natural_theta[0]
first_omega = natural_theta[1]
second_omega = natural_theta[2]
kappa = natural_theta[3]
nt_distn = markovutil.ratios_to_distn(natural_theta[4:4+3])
pre_Q = fmutsel.get_pre_Q(
log_counts,
fmutsel.genic_fixation,
ts, tv, syn, nonsyn, compo, asym_compo,
nt_distn, kappa, omega,
)
return pre_Q
