fixed cross checks

Project.toml

@@ -1,7 +1,7 @@
 name = "FMI"
 uuid = "14a09403-18e3-468f-ad8a-74f8dda2d9ac"
 authors = ["TT <[email protected]>", "LM <[email protected]>", "JK <[email protected]>"]
-version = "0.13.0"
+version = "0.13.1"
 
 [deps]
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
@@ -14,12 +14,12 @@ Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 ThreadPools = "b189fb0b-2eb5-4ed4-bc0c-d34c51242431"
 
 [compat]
-DifferentialEquations = "7.10.0 - 7.11.0"
+DifferentialEquations = "7.7.0 - 7.11"
 Downloads = "1"
 FMIExport = "0.3.0"
 FMIImport = "0.16.0"
 LinearAlgebra = "1"
-ProgressMeter = "1.7.0 - 1.9.0"
+ProgressMeter = "1.7.0 - 1.9"
 Requires = "1.3.0"
 ThreadPools = "2.1.1"
 julia = "1.6"

README.md

@@ -13,7 +13,7 @@
 [![Run PkgEval](https://github.com/ThummeTo/FMI.jl/actions/workflows/Eval.yml/badge.svg)](https://github.com/ThummeTo/FMI.jl/actions/workflows/Eval.yml)
 [![Coverage](https://codecov.io/gh/ThummeTo/FMI.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/ThummeTo/FMI.jl)
 [![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
-[![FMI Downloads](https://shields.io/endpoint?url=https://pkgs.genieframework.com/api/v1/badge/FMI)](https://pkgs.genieframework.com?packages=FMI).
+[![FMI Downloads](https://shields.io/endpoint?url=https://pkgs.genieframework.com/api/v1/badge/FMI)](https://pkgs.genieframework.com?packages=FMI)
 
 
 ## How can I use FMI.jl?
@@ -89,7 +89,7 @@ To keep dependencies nice and clean, the original package [*FMI.jl*](https://git
 - [*FMICore.jl*](https://github.com/ThummeTo/FMICore.jl): C-code wrapper for the FMI-standard
 - [*FMISensitivity.jl*](https://github.com/ThummeTo/FMISensitivity.jl): Static and dynamic sensitivities over FMUs
 - [*FMIBuild.jl*](https://github.com/ThummeTo/FMIBuild.jl): Compiler/Compilation dependencies for FMIExport.jl
-- [*FMIFlux.jl*](https://github.com/ThummeTo/FMIFlux.jl): Machine Learning with FMUs (differentiation over FMUs)
+- [*FMIFlux.jl*](https://github.com/ThummeTo/FMIFlux.jl): Machine Learning with FMUs
 - [*FMIZoo.jl*](https://github.com/ThummeTo/FMIZoo.jl): A collection of testing and example FMUs
 
 ## What Platforms are supported?

cross_checks/Project.toml

@@ -1,5 +1,6 @@
 [deps]
 ArgParse = "c7e460c6-2fb9-53a9-8c5b-16f535851c63"
+Base64 = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
 FMI = "14a09403-18e3-468f-ad8a-74f8dda2d9ac"

cross_checks/cross_check.jl

@@ -14,13 +14,17 @@ using DelimitedFiles
 using Tables
 using Statistics
 
+import Base64
+
 include("cross_check_config.jl")
 include("cross_check_lib.jl")
 
 # Main Array that holds all information about the excecuted cross checks and results
 crossChecks = []
 
-getInputValues = t -> t
+getInputValues = function(t, u)
+    return nothing
+end
 
 function parse_commandline()
     s = ArgParseSettings()
@@ -89,11 +93,12 @@ function runCrossCheckFmu(checkPath::String, resultPath::String, check::FmuCross
             if isfile(joinpath(checkPath, "$(check.fmuCheck)_in.csv"))
                 inputValues = CSV.File(joinpath(checkPath, "$(check.fmuCheck)_in.csv")) |> Tables.rowtable
                 hasInputValues = true
-                getInputValues = function(t)
+                getInputValues = function(t, u)
                     for (valIndex, val) in enumerate(inputValues)
                         if val.time >= t
-                            a = collect(inputValues[valIndex])[2:end] 
-                            return a
+                            u[:] = inputValues[valIndex][2:end] 
+                            # a = collect(inputValues[valIndex])[2:end] 
+                            # return a
                             break;
                         end
                     end

test/FMI2/sim_ME.jl

@@ -86,6 +86,12 @@ dataLength = length(solution.states.u)
 @test solution.values.t[1] == t_start 
 @test solution.values.t[end] == t_stop 
 
+# value/state getters 
+@test solution.states.t == fmi2GetSolutionTime(solution)
+@test collect(s[1] for s in solution.values.saveval) == fmi2GetSolutionValue(solution, 1; isIndex=true)
+@test collect(u[1] for u in solution.states.u      ) == fmi2GetSolutionState(solution, 1; isIndex=true)
+@test isapprox(fmi2GetSolutionState(solution, 2; isIndex=true), fmi2GetSolutionDerivative(solution, 1; isIndex=true); atol=1e-4)
+
 # reference values from Simulation in Dymola2020x (Dassl)
 @test sum(abs.(solution.states.u[1] - [0.5, 0.0])) < 1e-4
 @test sum(abs.(solution.states.u[end] - [1.05444, 1e-10])) < 0.01

test/runtests.jl

@@ -80,9 +80,13 @@ function runtestsFMI2(exportingTool)
             end
         end
 
-        @info "Performance (performance.jl)"
-        @testset "Performance" begin
-            include("FMI2/performance.jl")
+        if VERSION >= v"1.9.0"
+            @info "Performance (performance.jl)"
+            @testset "Performance" begin
+                include("FMI2/performance.jl")
+            end
+        else
+            @info "Julia Version $(VERSION), skipping performance tests ..."
         end
 
         @info "Plotting (plots.jl)"