@testset "Find Closest" begin

   using JuMP
   using Thesis: treat_inputs

  # Initial Setup
  sc = Sc("test")
  a = rand(15000:1.:40000)
  e = rand(0.01:0.01:0.5)
  i = rand(0.01:0.01:π/6)
  T = 2π*√(a^3/μs["Earth"])
  prop_time = 2T
  n = 30

  # A simple orbit raising
  start = oe_to_xyz([ a, e, i, 0., 0., 0. ], μs["Earth"])
  ΔVs = repeat([0.6, 0., 0.]', outer=(n,1))
  final = prop(ΔVs, start, sc, μs["Earth"], prop_time)[3]
  new_T = 2π*√(xyz_to_oe(final, μs["Earth"])[1]^3/μs["Earth"])

  # This should be close enough to 0.6
  Tr, TΘ, Th = conv_T(repeat([0.6], n), repeat([0.], n), repeat([0.], n),
                      start,
                      sc.mass,
                      sc,
                      prop_time,
                      μs["Earth"])
  result, solution = nlp_solve(start,
                               final,
                               sc,
                               μs["Earth"],
                               0.0,
                               prop_time,
                               Tr,
                               TΘ,
                               Th)

  # Test and plot
  @test JuMP.termination_status(result) == MOI.OPTIMAL
  path1 = prop(zeros((100,3)), start, sc, μs["Earth"], T)[1]
  path2, mass, calc_final = prop(treat_inputs(JuMP.value.(solution)), start, sc, μs["Earth"], prop_time)
  path3 = prop(zeros((100,3)), calc_final, sc, μs["Earth"], new_T)[1]
  path4 = prop(zeros((100,3)), final, sc, μs["Earth"], new_T)[1]
  savefig(plot_orbits([path1, path2, path3, path4],
                      labels=["initial", "transit", "after transit", "final"],
                      colors=["#FFFFFF","#FF4444","#44FF44","#4444FF"]),
          "../plots/find_closest_test.html")
  # if termination_status(result) == :OPTIMAL
  #   @test norm(calc_final - final) < 1e-4
  # end

end