51 lines
1.7 KiB
Julia
51 lines
1.7 KiB
Julia
@testset "Find Closest" begin
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println("Testing NLP solver")
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using NLsolve, PlotlyJS
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# Initial Setup
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sc = Sc("test")
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fresh_sc = copy(sc)
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a = rand(25000:1.:40000)
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e = rand(0.01:0.01:0.05)
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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 = 5T
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n = 200
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# A simple orbit raising
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start_mass = 10_000.
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start = [ oe_to_xyz([ a, e, i, 0., 0., 0. ], μs["Earth"]); start_mass ]
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Tx, Ty, Tz = conv_T(repeat([0.9], n), repeat([0.], n), repeat([0.], n),
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start,
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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, copy(sc), μs["Earth"], prop_time)[2]
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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 converge
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Tx, Ty, Tz = conv_T(repeat([0.89], n), repeat([0.], n), repeat([0.], n),
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start,
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sc,
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prop_time,
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μs["Earth"])
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result = nlp_solve(start, final, sc, μs["Earth"], 0.0, prop_time, hcat(Tx, Ty, Tz))
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# Test and plot
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@test result.converged
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path1 = prop(zeros((100,3)), start, sc, μs["Earth"], T)[1]
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path2, calc_final = prop(result.zero, 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, fresh_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 result.converged
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@test norm(calc_final[1:6] - final[1:6]) < 1e-4
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end
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end
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