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https://github.com/kalmarek/PropertyT.jl.git
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92 lines
2.6 KiB
Julia
92 lines
2.6 KiB
Julia
using JuMP
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function products{T<:Real}(S1::Array{Array{T,2},1}, S2::Array{Array{T,2},1})
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result = [0*similar(S1[1])]
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for x in S1
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for y in S2
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push!(result, x*y)
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end
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end
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return unique(result[2:end])
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end
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function read_GAP_raw_list(filename::String)
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return eval(parse(String(read(filename))))
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end
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function create_product_matrix(matrix_constraints)
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l = length(matrix_constraints)
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product_matrix = zeros(Int, (l, l))
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for (index, pairs) in enumerate(matrix_constraints)
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for (i,j) in pairs
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product_matrix[i,j] = index
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end
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end
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return product_matrix
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end
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function create_product_matrix(basis::Array{Array{Float64,2},1}, limit::Int)
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product_matrix = Array{Int}(limit,limit)
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constraints = constraints = [Array{Int,1}[] for x in 1:121]
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for i in 1:limit
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x_inv = inv(basis[i])
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for j in 1:limit
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w::Array{Float64,2} = x_inv*basis[j]
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function f(x::Array{Float64,2})
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if x == w
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return true
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else
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return false
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end
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end
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index = findfirst(f, basis)
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product_matrix[i,j] = index
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if index ≤ limit
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push!(constraints[index],[i,j])
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end
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end
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end
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return product_matrix, constraints
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end
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function create_SDP_problem(matrix_constraints,
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Δ²::GroupAlgebraElement, Δ::GroupAlgebraElement)
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N = length(Δ)
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@assert length(Δ) == length(Δ²)
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@assert length(Δ) == length(matrix_constraints)
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m = Model();
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@variable(m, A[1:N, 1:N], SDP)
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@SDconstraint(m, A >= zeros(size(A)))
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@variable(m, κ >= 0.0)
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@objective(m, Max, κ)
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for (pairs, δ², δ) in zip(matrix_constraints, Δ².coordinates, Δ.coordinates)
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@constraint(m, sum(A[i,j] for (i,j) in pairs) == δ² - κ*δ)
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end
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return m
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end
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function resulting_SOS{T<:Number, S<:Number}(sqrt_matrix::Array{T,2}, elt::GroupAlgebraElement{S})
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zzz = zeros(T, size(sqrt_matrix)[1])
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result::GroupAlgebraElement{T} = GroupAlgebraElement(zzz, elt.product_matrix)
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for i in 1:length(result)
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new_base = GroupAlgebraElement(sqrt_matrix[:,i], elt.product_matrix)
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result += new_base*new_base
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end
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return result
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end
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function correct_to_augmentation_ideal{T<:Rational}(sqrt_matrix::Array{T,2})
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sqrt_corrected = similar(sqrt_matrix)
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l = size(sqrt_matrix,2)
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for i in 1:l
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col = view(sqrt_matrix,:,i)
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sqrt_corrected[:,i] = col - sum(col)//l
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# @assert sum(sqrt_corrected[:,i]) == 0
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end
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return sqrt_corrected
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end
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