Merge pull request #73 from DEEPDIP-project/update_ins

Made functions compatible with most up-to-date version of INS

Project.toml

@@ -24,6 +24,7 @@ Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
 LuxCUDA = "d0bbae9a-e099-4d5b-a835-1c6931763bda"
 LuxCore = "bb33d45b-7691-41d6-9220-0943567d0623"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
+#NeuralClosure = "099dac27-d7f2-4047-93d5-0baee36b9c25"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationOptimisers = "42dfb2eb-d2b4-4451-abcd-913932933ac1"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
@@ -48,14 +49,15 @@ Documenter = "1"
 FFTW = "1"
 GLMakie = "0.10"
 Glob = "1"
-IncompressibleNavierStokes = "1"
+IncompressibleNavierStokes = "^2.0.1"
 JLD2 = "0.5"
 JuliaFormatter = "1"
 Juno = "0.8"
 Literate = "2"
 Lux = "1"
 LuxCUDA = "0.3"
 LuxCore = "1"
+#NeuralClosure = "^1.0.0"
 NNlib = "0.9"
 Optimization = "4"
 OptimizationOptimisers = "0.3"

simulations/NavierStokes_2D/scripts/evaluate_posteriori.jl

@@ -1,5 +1,5 @@
 using CoupledNODE: cnn
-using CoupledNODE.NavierStokes: create_right_hand_side_with_closure, INS_to_NN
+using CoupledNODE.NavierStokes: create_right_hand_side_with_closure
 using DifferentialEquations: ODEProblem, solve, Tsit5
 using IncompressibleNavierStokes: IncompressibleNavierStokes as INS
 using JLD2: load, @load
@@ -21,8 +21,8 @@ params = load("simulations/NavierStokes_2D/data/params_data.jld2", "params")
 D = params.D # dimension
 # Build LES setups and assemble operators
 setups = map(params.nles) do nles
-    x = ntuple(α -> LinRange(T(0.0), T(1.0), nles[α] + 1), params.D)
-    INS.Setup(x...; params.Re)
+    x = ntuple(α -> LinRange(T(0.0), T(1.0), nles + 1), params.D)
+    INS.Setup(; x = x, Re = params.Re)
 end
 
 # Create model
@@ -45,16 +45,15 @@ dt = params.Δt
 tspan = [T(0), T(1)]
 
 u0 = INS.random_field(setups[ig], T(0))
-u0_NN = INS_to_NN(u0)
-prob = ODEProblem(dudt_nn, u0_NN, tspan, θ_posteriori)
-sol = solve(prob, Tsit5(); u0 = u0_NN, p = θ_posteriori, dt = dt, adaptive = false)
+prob = ODEProblem(dudt_nn, u0, tspan, θ_posteriori)
+sol = solve(prob, Tsit5(); u0 = u0, p = θ_posteriori, dt = dt, adaptive = false)
 
 # Plot the field results
 function animation_plots(sol_ode, setup; variable = "vorticity")
     anim = Plots.Animation()
     for (idx, (t, u)) in enumerate(zip(sol_ode.t, sol_ode.u))
         if variable == "vorticity"
-            ω = INS.vorticity((u[:, :, 1], u[:, :, 2]), setup)
+            ω = INS.vorticity(u, setup)
             title = @sprintf("Vorticity, t = %.3f s", t)
             vor_lims = extrema(ω) # can specify manually other limits
             fig = Plots.heatmap(ω'; xlabel = "x", ylabel = "y", title, clims = vor_lims,

simulations/NavierStokes_2D/scripts/generate_data.jl

@@ -21,23 +21,23 @@ Nsim_test = 2
 params = (;
     D = 2,
     Re = T(1e3),
+    lims = (T(0.0), T(1.0)),
+    nles = [16, 32],
+    ndns = 64,
+    filters = (NC.FaceAverage(),),
     tburn = T(5e-2),
     tsim = T(0.5),
-    Δt = T(5e-3),
-    nles = [(16, 16), (32, 32)],
-    ndns = (64, 64),
-    filters = (NC.FaceAverage(),),
-    create_psolver = INS.psolver_spectral,
+    savefreq = 1,
+    Δt = T(5e-3), create_psolver = INS.psolver_spectral,
     icfunc = (setup, psolver, rng) -> INS.random_field(
         setup, zero(eltype(setup.grid.x[1])); kp = 20, psolver, rng),
-    rng,
-    savefreq = 1
+    rng
 )
 
 data_train = [NC.create_les_data(; params...) for _ in 1:Nsim_train];
 data_test = [NC.create_les_data(; params...) for _ in 1:Nsim_test];
 
-# save data
+#save data
 jldsave("simulations/NavierStokes_2D/data/data_train.jld2"; data_train)
 jldsave("simulations/NavierStokes_2D/data/data_test.jld2"; data_test)
 jldsave("simulations/NavierStokes_2D/data/params_data.jld2"; params)

simulations/NavierStokes_2D/scripts/preprocess_posteriori.jl

@@ -11,14 +11,14 @@ params = load("simulations/NavierStokes_2D/data/params_data.jld2", "params")
 
 # Build LES setups and assemble operators
 setups = map(params.nles) do nles
-    x = ntuple(α -> LinRange(T(0.0), T(1.0), nles[α] + 1), params.D)
-    INS.Setup(x...; params.Re)
+    x = ntuple(α -> LinRange(T(0.0), T(1.0), nles + 1), params.D)
+    INS.Setup(; x = x, Re = params.Re)
 end
 
 # * A posteriori io_arrays 
 using CoupledNODE.NavierStokes: create_io_arrays_posteriori
 io_post = create_io_arrays_posteriori(data, setups)
-
+ig = 1
 # Example of dimensions and how to operate with io_arrays_posteriori
 (n, _, dim, samples, nsteps) = size(io_post[ig].u) # (nles, nles, D, samples, tsteps+1)
 (samples, nsteps) = size(io_post[ig].t)

simulations/NavierStokes_2D/scripts/preprocess_priori.jl

@@ -11,8 +11,8 @@ params = load("simulations/NavierStokes_2D/data/params_data.jld2", "params")
 
 # Build LES setups and assemble operators
 setups = map(params.nles) do nles
-    x = ntuple(α -> LinRange(T(0.0), T(1.0), nles[α] + 1), params.D)
-    INS.Setup(x...; params.Re)
+    x = ntuple(α -> LinRange(T(0.0), T(1.0), nles + 1), params.D)
+    INS.Setup(; x = x, Re = params.Re)
 end
 
 # create io_arrays

simulations/NavierStokes_2D/scripts/train_posteriori.jl

@@ -15,7 +15,7 @@ include("preprocess_posteriori.jl")
 using ComponentArrays: ComponentArray
 using Lux: Lux
 u = io_post[ig].u[:, :, :, 1, 1:50]
-T = setups[1].T
+#T = setups[1].T
 d = D = setups[1].grid.dimension()
 N = size(u, 1)
 emb_size = 8