Simplify ensemble indexing #839
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Should fix the segfaults on SciMLSensitivity, and there are tests to ensure it does not regress
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| prob = ODEProblem((u, p, t) -> 1.01u, 0.5, (0.0, 1.0)) | ||
| A = [1 2 | ||
| 3 4] | ||
| prob = ODEProblem((u, p, t) -> A*u, ones(2,2), (0.0, 1.0)) |
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| prob = ODEProblem((u, p, t) -> A*u, ones(2,2), (0.0, 1.0)) | |
| prob = ODEProblem((u, p, t) -> A * u, ones(2, 2), (0.0, 1.0)) |
| ensemble_prob = EnsembleProblem(prob, prob_func = prob_func) | ||
| sim = solve(ensemble_prob, Tsit5(), EnsembleThreads(), trajectories = 10) | ||
| sim = solve(ensemble_prob, Tsit5(), EnsembleThreads(), trajectories = 10, saveat=0.01) | ||
| @test sim isa EnsembleSolution |
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| sim = solve(ensemble_prob, Tsit5(), EnsembleThreads(), trajectories = 10, saveat=0.01) | |
| sim = solve(ensemble_prob, Tsit5(), EnsembleThreads(), trajectories = 10, saveat = 0.01) |
test/downstream/ensemble_diffeq.jl
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| @test size(sim[1,:,:,:]) == (2,101,10) | |
| @test size(sim[:,1,:,:]) == (2,101,10) | |
| @test size(sim[:,:,1,:]) == (2,2,10) | |
| @test size(sim[:,:,:,1]) == (2,2,101) | |
| @test Array(sim)[1,:,:,:] == sim[1,:,:,:] | |
| @test Array(sim)[:,1,:,:] == sim[:,1,:,:] | |
| @test Array(sim)[:,:,1,:] == sim[:,:,1,:] | |
| @test Array(sim)[:,:,:,1] == sim[:,:,:,1] | |
| @test size(sim[1, :, :, :]) == (2, 101, 10) | |
| @test size(sim[:, 1, :, :]) == (2, 101, 10) | |
| @test size(sim[:, :, 1, :]) == (2, 2, 10) | |
| @test size(sim[:, :, :, 1]) == (2, 2, 101) | |
| @test Array(sim)[1, :, :, :] == sim[1, :, :, :] | |
| @test Array(sim)[:, 1, :, :] == sim[:, 1, :, :] | |
| @test Array(sim)[:, :, 1, :] == sim[:, :, 1, :] | |
| @test Array(sim)[:, :, :, 1] == sim[:, :, :, 1] |
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| @test sol[1,:,i] == sol.u[i][x] | ||
| @test sol[2,:,i] == sol.u[i][y] |
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| @test sol[1,:,i] == sol.u[i][x] | |
| @test sol[2,:,i] == sol.u[i][y] | |
| @test sol[1, :, i] == sol.u[i][x] | |
| @test sol[2, :, i] == sol.u[i][y] |
| # TODO: fix the interpolation | ||
| @test only.(sol(1.0, idxs = [x])) ≈ last.(sol[x, :]) | ||
| @test only.(sol(0.0, idxs = [x])) == sol[1, 1, :] | ||
| @test only.(sol(1.0, idxs = [x])) ≈ [sol[i][1, end] for i in 1:3] |
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| @test only.(sol(1.0, idxs = [x])) ≈ [sol[i][1, end] for i in 1:3] | |
| @test only.(sol(1.0, idxs = [x])) ≈ [sol[i][1, end] for i in 1:3] |
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Should fix the segfaults on SciMLSensitivity, and there are tests to ensure it does not regress