0.234 is the target acceptance ratio for the random walk Kernel. The value is 0.234 since that’s optimal for Random Walk Metropolis kernel with Gaussian like target [1].
So these 2 lines of code compute the current target scaling in ave_scaling (it’s an approximation), and push the current scaling self.scalings towards this target a little bit [2].
[1] Roberts GO, Gelman A, Gilks WR. Weak convergence and optimal scaling of random walk Metropolis algorithms. The annals of applied probability. 1997;7(1):110-20.
[2] Del Moral, Pierre, Arnaud Doucet, and Ajay Jasra. An adaptive sequential Monte Carlo method for approximate Bayesian computation. Statistics and Computing, 22.5(1009-1020), 2012