test

ThummeTo · Jun 28, 2023 · f1216dc · f1216dc
1 parent ede8c98
commit f1216dc
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Showing 3 changed files with 50 additions and 44 deletions.
diff --git a/src/batch.jl b/src/batch.jl
@@ -301,8 +301,8 @@ function batchDataSolution(neuralFMU::NeuralFMU, x0_fun, train_t::AbstractArray{
     iStop = timeToIndex(train_t, tStart + batchDuration)
 
     startElement = FMIFlux.FMU2SolutionBatchElement()
-    startElement.tStart = tStart 
-    startElement.tStop = tStart + batchDuration
+    startElement.tStart = train_t[iStart]
+    startElement.tStop = train_t[iStop]
     startElement.xStart = x0_fun(tStart)
 
     startElement.saveat = train_t[iStart:iStop]
@@ -318,12 +318,13 @@ function batchDataSolution(neuralFMU::NeuralFMU, x0_fun, train_t::AbstractArray{
         FMIFlux.run!(neuralFMU, batch[i-1]; lastBatchElement=batch[i], solverKwargs...)
 
         # overwrite start state
-        batch[i].tStart = tStart + (i-1) * batchDuration
-        batch[i].tStop = tStart + i * batchDuration
+        iStart = timeToIndex(train_t, tStart + (i-1) * batchDuration)
+        iStop = timeToIndex(train_t, tStart + i * batchDuration)
+        batch[i].tStart = train_t[iStart]
+        batch[i].tStop = train_t[iStop]
         batch[i].xStart = x0_fun(batch[i].tStart)
 
-        iStart = timeToIndex(train_t, batch[i].tStart)
-        iStop = timeToIndex(train_t, batch[i].tStop)
+
         batch[i].saveat = train_t[iStart:iStop]
         batch[i].targets = targets[iStart:iStop]
 
@@ -339,7 +340,7 @@ function batchDataSolution(neuralFMU::NeuralFMU, x0_fun, train_t::AbstractArray{
 end
 
 function batchDataEvaluation(train_t::AbstractArray{<:Real}, targets::AbstractArray, features::Union{AbstractArray, Nothing}=nothing; 
-    batchDuration::Real=(train_t[end]-train_t[1]), indicesModel=1:length(targets[1]), plot::Bool=false)
+    batchDuration::Real=(train_t[end]-train_t[1]), indicesModel=1:length(targets[1]), plot::Bool=false, round_digits=3)
 
     batch = Array{FMIFlux.FMU2EvaluationBatchElement,1}()
 
@@ -351,8 +352,8 @@ function batchDataEvaluation(train_t::AbstractArray{<:Real}, targets::AbstractAr
     iStop = timeToIndex(train_t, tStart + batchDuration)
 
     startElement = FMIFlux.FMU2EvaluationBatchElement()
-    startElement.tStart = tStart 
-    startElement.tStop = tStart + batchDuration
+    startElement.tStart = train_t[iStart]
+    startElement.tStop = train_t[iStop]
 
     startElement.saveat = train_t[iStart:iStop]
     startElement.targets = targets[iStart:iStop]
@@ -368,12 +369,12 @@ function batchDataEvaluation(train_t::AbstractArray{<:Real}, targets::AbstractAr
     for i in 2:floor(Integer, (train_t[end]-train_t[1])/batchDuration)
         push!(batch, FMIFlux.FMU2EvaluationBatchElement())
 
-        # overwrite start state
-        batch[i].tStart = tStart + (i-1) * batchDuration
-        batch[i].tStop = tStart + i * batchDuration
-
-        iStart = timeToIndex(train_t, batch[i].tStart)
-        iStop = timeToIndex(train_t, batch[i].tStop)
+        iStart = timeToIndex(train_t, tStart + (i-1) * batchDuration)
+        iStop = timeToIndex(train_t, tStart + i * batchDuration)
+
+        batch[i].tStart = train_t[iStart]
+        batch[i].tStop = train_t[iStop]
+
         batch[i].saveat = train_t[iStart:iStop]
         batch[i].targets = targets[iStart:iStop]
         if features != nothing 

diff --git a/test/fmu_params.jl b/test/fmu_params.jl
@@ -60,6 +60,10 @@ function callb(p)
         loss = losssum(p[1])
         @info "[$(iterCB)] Loss: $loss"
         @test loss < lastLoss  
+        #@test p[1][1] == fmu.optim_p[1]
+        #@info "$(fmu.optim_p[1])"
+        #@info "$(p)"
+        #@info "$(problem.parameters)"
         lastLoss = loss
     end
 end
@@ -90,7 +94,8 @@ p_net = Flux.params(problem)
 iterCB = 0
 lastLoss = losssum(p_net[1])
 @info "Start-Loss for net: $lastLoss"
-FMIFlux.train!(losssum, p_net, Iterators.repeated((), parse(Int, ENV["NUMSTEPS"])), optim; cb=()->callb(p_net))
+FMIFlux.train!(losssum, p_net, Iterators.repeated((), parse(Int, ENV["NUMSTEPS"])), optim; cb=()->callb(p_net), gradient=:ForwardDiff, chunk_size=1)
+FMIFlux.train!(losssum, p_net, Iterators.repeated((), parse(Int, ENV["NUMSTEPS"])), optim; cb=()->callb(p_net), gradient=:ReverseDiff)
 
 # check results
 solutionAfter = problem(x0)

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -29,45 +29,45 @@ function runtests(exportingTool)
 
     @testset "Testing FMUs exported from $(ENV["EXPORTINGTOOL"]) ($(ENV["EXPORTINGVERSION"]))" begin
 
-        @info "Layers (layers.jl)"
-        @testset "Layers" begin
-            include("layers.jl")
-        end
+        # @info "Layers (layers.jl)"
+        # @testset "Layers" begin
+        #     include("layers.jl")
+        # end
 
-        @info "ME-NeuralFMU (Continuous) (hybrid_ME.jl)"
-        @testset "ME-NeuralFMU (Continuous)" begin
-            include("hybrid_ME.jl")
-        end
+        # @info "ME-NeuralFMU (Continuous) (hybrid_ME.jl)"
+        # @testset "ME-NeuralFMU (Continuous)" begin
+        #     include("hybrid_ME.jl")
+        # end
 
-        @info "ME-NeuralFMU (Discontinuous) (hybrid_ME_dis.jl)"
-        @testset "ME-NeuralFMU (Discontinuous)" begin
-            include("hybrid_ME_dis.jl")
-        end
+        # @info "ME-NeuralFMU (Discontinuous) (hybrid_ME_dis.jl)"
+        # @testset "ME-NeuralFMU (Discontinuous)" begin
+        #     include("hybrid_ME_dis.jl")
+        # end
 
         @info "NeuralFMU with FMU parameter optimization (fmu_params.jl)"
         @testset "NeuralFMU with FMU parameter optimization" begin
             include("fmu_params.jl")
         end
 
-        @info "Training modes (train_modes.jl)"
-        @testset "Training modes" begin
-            include("train_modes.jl")
-        end
+        # @info "Training modes (train_modes.jl)"
+        # @testset "Training modes" begin
+        #     include("train_modes.jl")
+        # end
 
-        @info "Multi-threading (multi_threading.jl)"
-        @testset "Multi-threading" begin
-            include("multi_threading.jl")
-        end
+        # @info "Multi-threading (multi_threading.jl)"
+        # @testset "Multi-threading" begin
+        #     include("multi_threading.jl")
+        # end
 
-        @info "CS-NeuralFMU (hybrid_CS.jl)"
-        @testset "CS-NeuralFMU" begin
-            include("hybrid_CS.jl")
-        end
+        # @info "CS-NeuralFMU (hybrid_CS.jl)"
+        # @testset "CS-NeuralFMU" begin
+        #     include("hybrid_CS.jl")
+        # end
 
-        @info "Multiple FMUs (multi.jl)"
-        @testset "Multiple FMUs" begin
-            include("multi.jl")
-        end
+        # @info "Multiple FMUs (multi.jl)"
+        # @testset "Multiple FMUs" begin
+        #     include("multi.jl")
+        # end
     end
 end