75 lines
2.3 KiB
Julia
75 lines
2.3 KiB
Julia
using DelimitedFiles, LinearAlgebra, StatsBase
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function calculate_all_data(N::Int)
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ks = -N÷2:N÷2-1
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lattice = hcat((collect.(Iterators.product(ks, ks, ks)))...)
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unique_i = collect(1:N^3)
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multiplicity = fill(1, length(unique_i))
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unique_point = transpose(lattice)
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return unique_i, unique_point, multiplicity
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end
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function calculate_A1_data(N::Int)
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rotations = readdlm("rotations.mat", ',', Int, '\n')
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rotations = reshape(rotations, (24, 3, 3))
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ks = -N÷2:N÷2-1
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lattice = hcat((collect.(Iterators.product(ks, ks, ks)))...)
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labels = reshape(collect(1:N^3), (N, N, N))
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for r in 1:24
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rotated_lattice = Matrix(rotations[r, :, :]) * lattice
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for index in 1:N^3
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rotated_lattice_point = rotated_lattice[:, index]
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(i, j, k) = mod1.(rotated_lattice_point .+ (N÷2 + 1), N)
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old_label = max(labels[index], labels[i, j, k])
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new_label = min(labels[index], labels[i, j, k])
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if old_label != new_label
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for o in findall(isequal(old_label), labels)
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labels[o] = new_label
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end
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end
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end
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end
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unique_i = unique(labels)
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multiplicity = countmap(labels)
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unique_point = transpose(lattice[unique_i, :])
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return unique_i, unique_point, multiplicity
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end
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function sym_reduce(s, K_partial)
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I = one(K_partial)
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K_partial_x = kron(kron(K_partial, I), I)
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K_partial_y = kron(kron(I, K_partial), I)
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K_partial_z = kron(kron(I, I), K_partial)
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# for s in 1:N^3
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# if labels[s] != s
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# for mat in (K_partial_x, K_partial_y, K_partial_z)
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# mat[labels[s], :] += mat[s, :]
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# mat[s, :] = 0
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# mat[:, labels[s]] += mat[:, s]
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# mat[:, s] = 0
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# end
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# end
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# end
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for i in s.unique_i
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K_partial_x[i, :] *= s.multiplicity[i]
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K_partial_x[:, i] *= s.multiplicity[i]
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K_partial_y[i, :] *= s.multiplicity[i]
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K_partial_y[:, i] *= s.multiplicity[i]
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K_partial_z[i, :] *= s.multiplicity[i]
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K_partial_z[:, i] *= s.multiplicity[i]
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end
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K_partial_x = K_partial_x[s.unique_i, s.unique_i]
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K_partial_y = K_partial_y[s.unique_i, s.unique_i]
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K_partial_z = K_partial_z[s.unique_i, s.unique_i]
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return K_partial_x, K_partial_y, K_partial_z
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end |