58 lines
2.1 KiB
Julia
58 lines
2.1 KiB
Julia
@testset "Find Closest" begin
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using JuMP
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# Initial Setup
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sc = Sc("test")
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a = rand(15000:1.:40000)
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e = rand(0.01:0.01:0.5)
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i = rand(0.01:0.01:π/6)
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T = 2π*√(a^3/μs["Earth"])
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prop_time = 2T
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n = 30
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# A simple orbit raising
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start = oe_to_xyz([ a, e, i, 0., 0., 0. ], μs["Earth"])
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Tx, Ty, Tz = conv_T(repeat([0.6], n), repeat([0.], n), repeat([0.], n),
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start,
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sc.mass,
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sc,
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prop_time,
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μs["Earth"])
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final = prop(hcat(Tx, Ty, Tz), start, sc, μs["Earth"], prop_time)[3]
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new_T = 2π*√(xyz_to_oe(final, μs["Earth"])[1]^3/μs["Earth"])
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# This should be close enough to 0.6
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Tx, Ty, Tz = conv_T(repeat([0.6], n), repeat([0.], n), repeat([0.], n),
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start,
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sc.mass,
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sc,
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prop_time,
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μs["Earth"])
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result, solution = nlp_solve(start,
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final,
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sc,
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μs["Earth"],
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0.0,
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prop_time,
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Tx,
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Ty,
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Tz)
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# solver_options=("max_cpu_time" => 30.))
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# Test and plot
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@test JuMP.termination_status(result) == MOI.OPTIMAL
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path1 = prop(zeros((100,3)), start, sc, μs["Earth"], T)[1]
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path2, mass, calc_final = prop(treat_inputs(JuMP.value.(solution)), start, sc, μs["Earth"], prop_time)
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path3 = prop(zeros((100,3)), calc_final, sc, μs["Earth"], new_T)[1]
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path4 = prop(zeros((100,3)), final, sc, μs["Earth"], new_T)[1]
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savefig(plot_orbits([path1, path2, path3, path4],
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labels=["initial", "transit", "after transit", "final"],
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colors=["#FFFFFF","#FF4444","#44FF44","#4444FF"]),
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"../plots/find_closest_test.html")
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# if termination_status(result) == :OPTIMAL
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# @test norm(calc_final - final) < 1e-4
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# end
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end
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