using DelimitedFiles, LinearAlgebra function calculate_all_data(N::Int) ks = -N÷2:N÷2-1 lattice = hcat((collect.(Iterators.product(ks, ks, ks)))...) labels = reshape(collect(1:N^3), (N, N, N)) unique_i = collect(1:N^3) multiplicity = fill(1, length(unique_i)) unique_point = transpose(lattice) return unique_i, unique_point, multiplicity, labels end function calculate_A1_data(N::Int) rotations = readdlm("rotations.mat", ',', Int, '\n') rotations = reshape(rotations, (24, 3, 3)) ks = -N÷2:N÷2-1 lattice = hcat((collect.(Iterators.product(ks, ks, ks)))...) labels = reshape(collect(1:N^3), (N, N, N)) for r in 1:24 rotated_lattice = Matrix(rotations[r, :, :]) * lattice for index in 1:N^3 rotated_lattice_point = rotated_lattice[:, index] (i, j, k) = mod1.(rotated_lattice_point .+ (N÷2 + 1), N) old_label = max(labels[index], labels[i, j, k]) new_label = min(labels[index], labels[i, j, k]) if old_label != new_label for o in findall(isequal(old_label), labels) labels[o] = new_label end end end end unique_i = unique(labels) multiplicity = [count(labels.==i) for i in unique_i] unique_point = transpose(lattice[:, unique_i]) return unique_i, unique_point, multiplicity, labels end function sym_reduce(s, K_partial) I = one(K_partial) K_partial_x1 = kron(kron(K_partial, I), I) K_partial_y1 = kron(kron(I, K_partial), I) K_partial_z1 = kron(kron(I, I), K_partial) K_partial_x2 = kron(kron(K_partial, I), I) K_partial_y2 = kron(kron(I, K_partial), I) K_partial_z2 = kron(kron(I, I), K_partial) for (i, label) in enumerate(s.labels) if i != label K_partial_x2[:, i] .+= K_partial_x2[:, label] K_partial_y2[:, i] .+= K_partial_y2[:, label] K_partial_z2[:, i] .+= K_partial_z2[:, label] end end K_partial_x1 = K_partial_x1[s.unique_i, :] K_partial_y1 = K_partial_y1[s.unique_i, :] K_partial_z1 = K_partial_z1[s.unique_i, :] K_partial_x2 = K_partial_x2[:, s.unique_i] K_partial_y2 = K_partial_y2[:, s.unique_i] K_partial_z2 = K_partial_z2[:, s.unique_i] return (K_partial_x1, K_partial_y1, K_partial_z1), (K_partial_x2, K_partial_y2, K_partial_z2) end