def independent_binomial_log_likelihood( data, parameters ):
a = data.a
b = data.b
d = a + b
mu = parameters['mu']
log_likelihoods = log_binomial_likelihood( a, d, mu )
pi = parameters['pi']
log_pi = np.log( pi )
log_likelihoods = log_likelihoods + log_pi
return log_likelihoods
def joint_binomial_log_likelihood( data, parameters ):
log_likelihoods = {}
for genome in constants.genomes:
a = data.a[genome]
b = data.b[genome]
d = a + b
mu = parameters[genome]['mu']
log_likelihoods[genome] = log_binomial_likelihood( a, d, mu )
pi = parameters['pi']
log_likelihoods = get_joint_log_likelihoods( log_likelihoods, pi )
return log_likelihoods
