def log_posterior_transit(theta, params, model, t, flux, err_flux, priorbounds):
lp = _log_prior_transit(theta, priorbounds)<EOL>if not np.isfinite(lp):<EOL><INDENT>return -np.inf<EOL><DEDENT>else:<EOL><INDENT>return lp + _log_likelihood_transit(theta, params, model, t, flux,<EOL>err_flux, priorbounds)<EOL><DEDENT>
Evaluate posterior probability given proposed model parameters and
the observed flux timeseries.