diff --git a/hh.jl b/hh.jl
deleted file mode 100644
index 8043135cd1e53a67aedea6f54b2c7476424d33ce..0000000000000000000000000000000000000000
--- a/hh.jl
+++ /dev/null
@@ -1,78 +0,0 @@
-using PyCall
-neuronunit = pyimport("neuronunit")
-#om = neuronunit#.optimisation.optimization.management
-#neuronunit = pyimport("neuronunit")
-
-#] add https://github.com/AStupidBear/SpikingNeuralNetworks.jl
-
-# Pkg.add("https://github.com/AStupidBear/SpikingNeuralNetworks.jl")
-
-
-using GR
-
-
-import SpikingNeuralNetworks
-
-
-
-using Unitful
-
-using Plots, SpikingNeuralNetworks
-SNN = SpikingNeuralNetworks
-E = SNN.HH(;N = 1)
-E.I = [0.003]
-
-SNN.monitor(E, [:v])
-SNN.sim!([E], []; dt = 0.01, duration = 102)
-
-
-SNN.vecplot(E, :v) |> display
-
-#=
-using Pkg
-try
-   using UnicodePlotsi
-   #using NSGAII
-catch
-   Pkg.add("UnicodePlots")
-   #Pkg.add("NSGAII")
-   using UnicodePlots
-   #using NSGAII
-end
-
-using NSGAII, vOptSpecific, vOptGeneric, GLPK, GLPKMathProgInterface, PyPlot
-m = vModel(solver = GLPKSolverMIP())
-id = load2UKP("2KP500-1A.DAT")
-
-p1, p2, w, c = id.P1, id.P2, id.W, id.C
-
-@variable(m, x[1:length(p1)], Bin)
-@addobjective(m, Max, dot(x, p1))
-@addobjective(m, Max, dot(x, p2))
-@constraint(m, dot(x, w) <= c)
-
-function plot_pop(P, titre)
-  clf()
-  ax = gca()
-  ax[:set_xlim]([15800, 20570])
-  ax[:set_ylim]([15630, 20877])
-  p = plot(map(x -> x.y[1], P), map(x -> x.y[2], P), "bo", markersize=1, label="nsga")
-  title(titre)
-  !isinteractive() && show()
-  sleep(0.1)
-end
-
-nsga(100, 5000, m, fplot = p->plot_pop(p, "without seed"), plotevery=500)
-
-solve(m, method=:dichotomy)
-
-Y_N = getY_N(m)
-seed = [getvalue(x, 1), getvalue(x, length(Y_N)), getvalue(x, length(Y_N)÷2)]
-nsga(100, 5000, m, fplot = p->plot_pop(p, "with seed"), seed=seed, plotevery=500)
-
-f1 = map(y -> y[1], Y_N)
-f2 = map(y -> y[2], Y_N)
-xlabel("z1") ; ylabel("z2")
-p = plot(f1,f2,"kx", markersize = "2", label="exact")
-legend() ; display(p)
-=#