def independent_beta_binomial_log_likelihood( data, parameters ):
a = data.a
b = data.b
d = a + b
alpha = parameters['alpha']
beta = parameters['beta']
log_likelihoods = log_beta_binomial_likelihood( a, d, alpha, beta )
pi = parameters['pi']
log_likelihoods = log_likelihoods + np.log( pi )
return log_likelihoods
def joint_beta_binomial_log_likelihood( data, parameters ):
log_likelihoods = {}
for genome in constants.genomes:
a = data.a[genome]
b = data.b[genome]
d = a + b
alpha = parameters[genome]['alpha']
beta = parameters[genome]['beta']
log_likelihoods[genome] = log_beta_binomial_likelihood( a, d, alpha, beta )
pi = parameters['pi']
log_likelihoods = get_joint_log_likelihoods( log_likelihoods, pi )
return log_likelihoods
