using DelimitedFiles;

lcat(x...) = cat(x...; dims=1)

function tofloat(x)
  if x isa AbstractString
    x = replace(x, ","=>".");
    return parse(Float64, x)
  end
  return x
end
# noms_nuls = [ "BLANCS", "NULS", "ABSTENTION" ]
noms_nuls = [];
noms_x = lcat([ "MACRON", "LE PEN", "FILLON", "MÉLENCHON", "HAMON",
 "DUPONT-AIGNAN", "LASSALLE", "POUTOU", "ASSELINEAU", "ARTHAUD", "CHEMINADE" ],
 noms_nuls)
tmp_y = readdlm("euro1.csv", ';', quotes=true)
noms_y = lcat([ tmp_eur[2,13+7j] for j=1:34 ], noms_nuls)
function read_results(f,c,noms=false)
  E0 = readdlm(f,c,quotes=true);
  m = div(size(E0,2)-18,7)
  E1 = fill(0.,size(E0,1)-1,m+2+length(noms_nuls));
  for i=1:size(E1,1)
    l = i+1
    k = E0[l,1]
    if k isa AbstractString
      if k[1] == '2'; k = 20; end # Corse
      if k[1] == 'Z'; k = 97; end # DOM-COM
    end
    E1[i,1] = 1000*k+E0[l,3];
    E1[i,2] = E0[l,16];
    if length(noms_nuls) >= 1 E1[i,m+3] = E0[l,10]; end
    if length(noms_nuls) >= 2 E1[i,m+4] = E0[l,13]; end
    if length(noms_nuls) >= 3 E1[i,m+5] = E0[l,6]; end
    for j=1:m
      y = tofloat(E0[l,16+7j]) #  18+7j = %, 16+7j = exprimés
      if noms != false
        for k = 1:size(noms, 1)
          if E0[l,14+7*j] == noms[k]
#             print("$i, $j => $k $(noms[k])\n")
            E1[i,k+2] = y
          end
        end
      else
        E1[i,j+2] = y
      end
    end
  end
  return E1
end
function read_x() read_results("prez.csv",',', noms_x) end
function read_y() read_results("euro.csv",';') end


function merge_mat(A,B)
  M = Pair{Int,Int}[]
  sA = size(A,1)
  sB = size(B,1)
  j = 1
  for i = 1:sA
    a = A[i,1]
#     print("testing A[$i] = $a\n")
    while B[j,1] < a && j < sB; j+=1; end
#     print("  B[$j,1]=$(B[j,1])\n")
    if(B[j,1] == a); M = lcat(M,[i=>j]); end
  end
  A1 = fill(0., size(M,1), size(A,2)-2)
  B1 = fill(0., size(M,1), size(B,2)-2)
  W = fill(0, size(M,1))
  for i = 1:size(M,1)
#     print("M[$i] = $(M[i])\n")
    w = A[M[i].first,2]; w = (w == 0) ? 1 : w; # prevents div-by-0
    W[i] = w; # A[M[i].first, 2]
    for j = 1:size(A1,2)
      A1[i,j] = A[M[i].first,j+2]
    end
    for j = 1:size(B1,2)
      B1[i,j] = B[M[i].second,j+2]
    end
  end
  A1,B1,W
end

A0 = read_x()
B0 = read_y()
X,Y,weight = merge_mat(A0,B0)
N = size(X,1)
sX = size(X,2)
sY = size(Y,2)
result_y = [Int(sum([ B0[i,j+2] for i=1:size(B0,1) ])) for j=1:sY]
result_x = [Int(sum([X[i,j] for i=1:N])) for j=1:sX]

perm_y = lcat(sortperm(result_y[1:sY-length(noms_nuls)],rev=true),
  sY-length(noms_nuls)+1:sY)
Y = [Y[i,perm_y[j]] for i=1:N,j=1:sY]
noms_y = [noms_y[perm_y[j]] for j=1:sY]

using JuMP
using Ipopt
model = Model(with_optimizer(Ipopt.Optimizer))

@variable(model, a[1:sY,1:sX] >= 0)
# @constraint(model, stoch[i=1:sX], sum(a[j,i] for j=1:sY) == 1)
L = [-2*sum([ X[i,k]*Y[i,j]/weight[i] for i=1:N ]) for j=1:sY, k=1:sX ];
Q = [  sum([ X[i,k]*X[i,l]/weight[i] for i=1:N]) for k=1:sX, l=1:sX ];
# @constraint(model, consist[j=1:sY],
#   sum(a[j,i]*result_x[i] for i=1:sX) == result_y[j]);

@objective(model, Min, sum(L[j,k]*a[j,k] for j=1:sY, k=1:sX)
  + sum(Q[k,l]*a[j,k]*a[j,l] for j=1:sY, k=1:sX, l=1:sX));

optimize!(model)
Sol = value.(a)
writedlm("solved.csv",
  hcat(lcat("",noms_x), permutedims(hcat(noms_y, Sol), (2,1))))

open("transfer.txt", "w") do f
for j=1:sX, i=1:sY
  c=Int(round(Sol[i,j]*result_x[j]/2.3e5))
  x=noms_x[j]
  y=noms_y[i]
  if c > 0
  write(f, "$x\t[$c]\t$y\n")
  end
end end

# using LinearAlgebra
# tX = transpose(X)  # * Diagonal(W)
# K = tX*X
# sK = Symmetric(K)
# L = tX*Y
# Z = sK\L