The FRiM fractal operator belongs to a family of operators, called ASAP, defined by an ordered selection of nearest neighbors. This generalization provides means to improve upon the good properties of FRiM. We propose a fast algorithm to build an ASAP operator mimicking the fractal structure of FRiM for pupils of any size and geometry and to learn the sparse coefficients from empirical data. We empirically show the good approximation by ASAP of correlated statistics and the benefits of ASAP for solving phase restoration problems.