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In recent years, the advancement of computing and its technologies have changed the course of science. With crystallography would be no different: Nowadays, we try not only to theoretically predict the structure of materials, but also reproduct them in software and, with some models, extract data as, for example, the elastic coefficient, the diffusion coefficient, resistance, conformation energy, among others. In Computational crystallography, we usually begin by assembling a file of coordinates, which are nothing more than the positions of each atom in the crystal studied. This is usually generated by a method which involves the replication of a group of atoms in a periodic that spans the R³. However, this method failed to structures that have no classic periodicity, as quasicrystals, liquid crystals, certain ceramics and glasses. We develop a more general method, based on three steps: (i) Choosing an initial geometry that suits the problem, (ii) applying on the geometry to specific selection law and (iii) applying a transformation to these points selected by the law. This method is based on the idea that every given set of points cam be generated by a selection law. This allows us to include not only the regular lattice, but any structures that we know with details. Here, we will make a brief presentation of the method cited and will focus on its applications, presenting some complex structures, such as fractals and quasicrystals, and how to build them by this method. In the same time, we will discuss how to find such laws and the freedom we have to simplify them.