Preliminary work shows that hexagonal (2D), as well as BCC and FCC (3D) lattices significantly impact the number of required samples and structure of the optimal solution.
Another parameter should be added:
p_2d = Protein("HPPHPPH", dim=2, lattice="triangular")
p_3d = Protein("HPPHPPH", dim=3, lattice="bcc")
p_3d = Protein("HPPHPPH", dim=3, lattice="square") # default, already implementedThis feature requires significant amounts of non-trivial changes to prospr_core and the visualization code.
Encoding of folds should be changed from signed integers to capitalized characters (e.g. $\pm1\rightarrow \texttt{A},\texttt{a}$).
Preliminary work shows that hexagonal (2D), as well as BCC and FCC (3D) lattices significantly impact the number of required samples and structure of the optimal solution.
Another parameter should be added:
This feature requires significant amounts of non-trivial changes to$\pm1\rightarrow \texttt{A},\texttt{a}$ ).
prospr_coreand the visualization code.Encoding of folds should be changed from signed integers to capitalized characters (e.g.