How to exhibit results of SIR or bootstrap properly like in table

[diabloyg]

The SIR could be performed with model and sampling/resampling number, BUT I am quite confused about the data structure of the results and thus don’t know how to read it.

Besides, could there be an default/recommended settings for bootstrap/SIR process? (From a completely new user of Julia)

[vijay]

hi @diabloyg , welcome to the community!

you develop SIR() using this syntax

my_sir = infer(my_fit, Pumas.SIR(samples=200))

you can then get the results of this using the standard coeftable function

coeftable(my_sir)

Besides, could there be an default/recommended settings for bootstrap/SIR process? (From a completely new user of Julia)

There is a major update to the documentation happening that should be released in a day or two and i will point you to the exact location of all the options.

[diabloyg]

@vijay Thanks very much for your reply.

However, when I tried to test my model in another laptop with weaker-performance CPU (AMD Ryzen 7 PRO 3700 U), there are many mistakes during the FOCEI estimation, which didn’t happen in computer with Intel i7 10850.

I wonder is there any difference for Pumas between AMD and Intel. I tried to collect information but have no idea about this.

[andreasnoack]

@diabloyg

there are many mistakes during the FOCEI estimation

Please share the exact errors and warnings that you see as well as the command that you ran. Otherwise, it’s not possible to know what is going on. There shouldn’t be a difference between AMD and Intel so it might be a good idea to check that the two programs are indeed identical.

[diabloyg]

@andreasnoack

Please share the exact errors and warnings that you see as well as the command that you ran. Otherwise, it’s not possible to know what is going on. There shouldn’t be a difference between AMD and Intel so it might be a good idea to check that the two programs are indeed identical.

Generally the mistakes were as follows:

Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ DiffEqBase C:\Users\julia.julia\packages\DiffEqBase\3iigH\src\integrator_interface.jl:343
┌ Warning: dt <= dtmin. Aborting. There is either an error in your model specification or the true solution is unstable.
└ @ DiffEqBase C:\Users\julia.julia\packages\DiffEqBase\3iigH\src\integrator_interface.jl:343

I have copyed the file to the laptop so it should exactly the same. In another Intel platform I successfully get the model and performed SIR. The codes are there:

using CSV, Pumas, Plots, Random, JLD2

dataset = DataFrame!(CSV.File(
“./P1PK_20200907.csv”,
missingstrings = ["", “.”, “NA”, “BQL”],
))

popdata = read_pumas(
dataset,
observations = [:dv],
covariates = [:bw, :age, :sexx, :racex, :alb],
event_data = true,
)

mymodel = @model begin
@param begin
tv_cl ∈ RealDomain(lower = 0.001, upper = 200, init = 40)
tv_vc ∈ RealDomain(lower = 0.001, upper = 10000, init = 5000)
tv_vp ∈ RealDomain(lower = 0.001, upper = 5000, init = 3000)
tv_cld ∈ RealDomain(lower = 0.001, upper = 100, init = 30)
tv_vmax ∈ RealDomain(lower = 0.001, upper = 1000000, init = 200000)
tv_km ∈ RealDomain(lower = 0.001, upper = 1000, init = 400)
tv_bw_cl ∈ RealDomain(lower = 0.001, upper = 3, init = 1.5)
tv_bw_vc ∈ RealDomain(lower = 0.001, upper = 3, init = 1)
omega ∈ PDiagDomain(init = [0.1, 0.1, 0.1, 0.1])
epsprop ∈ RealDomain(lower = 0.0001, init = 0.1)
end
@random begin
eta ~ MvNormal(omega)
end
@covariates bw
@pre begin
bw_cl = tv_bw_cl
bw_vc = tv_bw_vc
cl = tv_cl * (bw / 65)^tv_bw_cl * exp(eta[1])
vc = tv_vc * (bw / 65)^tv_bw_vc * exp(eta[2])
vp = tv_vp * exp(eta[3])
cld = tv_cld * exp(eta[4])
vmax = tv_vmax
km = tv_km
end
@init begin
central = 0
peripheral = 0
end
@vars begin
conc = central / vc
k12 = cld / vc
k21 = cld / vp
ke = cl / vc
end
@dynamics begin
central’ =
-ke * central - k12 * central + k21 * peripheral -
vmax * conc / (km + conc)
peripheral’ = k12 * central - k21 * peripheral
end
@derived begin
dv ~ @. Normal(conc, sqrt(conc * epsprop)^2)
end
end

param = init_param(mymodel)

result = fit(mymodel, popdata, param, Pumas.MAP(Pumas.FOCEI()))

Additionally, when I tried to load the saved results from previouly running, it told me:

┌ Warning: some parameters could not be resolved for type ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}; reconstructing
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238
┌ Warning: some parameters could not be resolved for type Pumas.FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46},Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show_trace, :store_trace, :extended_trace, :g_tol, :allow_f_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc,
:omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}; reading as Pumas.FittedPumasModel{PumasModel,Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show_trace, :store_trace, :extended_trace, :g_tol, :allow_f_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1234
┌ Warning: some parameters could not be resolved for type PumasModel{ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46}; reconstructing
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238

The load process is okey in the computer that I ran the model.

[diabloyg]

@andreasnoack
Since the saved model cannot be load in my AMD laptop, and the exactly same model cannot be fitted, I believe it’s not due to model code itself but something others.

[andreasnoack]

@diabloyg

Additionally, when I tried to load the saved results from previouly running, it told me:

Please include the code that you use for saving and loading as well.

Are you using the same version of Julia and Pumas? What’s the output from versioninfo() and ] st on the two machines?

[diabloyg]

Continuing the discussion from How to exhibit results of SIR or bootstrap properly like in table:

@andreasnoack

versioninfo()

For versioninfo() information:

Julia Version 1.5.2
Commit 539f3ce943 (2020-09-23 23:17 UTC)
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: AMD Ryzen 7 PRO 3700U w/ Radeon Vega Mobile Gfx
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-9.0.1 (ORCJIT, znver1)
Environment:
JULIA_DEPOT_PATH = C:\Users\gyang.julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\local\share\julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\share\julia
JULIA_EDITOR = “D:\JuliaPro-1.5.2-2\app-1.51.0\atom.exe” -a
JULIA_LOAD_PATH = C:\Users\gyang.julia\environments\JuliaPro_v1.5.2-2;C:\Users\gyang.julia\Pumas;@;@v#.#;@stdlib
JULIA_NUM_THREADS = 8
JULIA_PKG_SERVER = pkg.juliahub.com

I think they are the same since they are from one setup packages.

For saving and loading code:

detail = infer(result)

wres = wresiduals(result)

resout = DataFrame(inspect(result))

@save “test2.jld2” result detail wres resout

@load “test2.jld2” result detail wres resout

[andreasnoack]

Please also share the output from ] st and please share the same info from the other machine. There might be small relevant differences so we shouldn’t assume that they are identical.

[diabloyg]

From my view there is no much difference. For the laptop in which estimation cannot run correctly:

] st

Status C:\Users\gyang\.julia\environments\JuliaPro_v1.5.2-2\Project.toml
[c3fe647b] AbstractAlgebra v0.11.1 ⚲
[621f4979] AbstractFFTs v0.5.0 ⚲
[80f14c24] AbstractMCMC v2.1.0 ⚲
[1520ce14] AbstractTrees v0.3.3 ⚲
[79e6a3ab] Adapt v2.3.0 ⚲
[0bf59076] AdvancedHMC v0.2.26 ⚲
[dce04be8] ArgCheck v1.1.0 ⚲
[ec485272] ArnoldiMethod v0.0.4 ⚲
[7d9fca2a] Arpack v0.4.0 ⚲
[68821587] Arpack_jll v3.5.0+3 ⚲
[4fba245c] ArrayInterface v2.13.7 ⚲
[4c555306] ArrayLayouts v0.3.8 ⚲
[69666777] Arrow v0.4.1 ⚲
[56f22d72] Artifacts v1.3.0 ⚲
[bf4720bc] AssetRegistry v0.1.0 ⚲
[c52e3926] Atom v0.12.21 ⚲
[6710c13c] AutoGrad v1.2.3 ⚲
[15f4f7f2] AutoHashEquals v0.2.0 ⚲
[13072b0f] AxisAlgorithms v1.0.0 ⚲
[39de3d68] AxisArrays v0.4.3 ⚲
[ab4f0b2a] BFloat16s v0.1.0 ⚲
[aae01518] BandedMatrices v0.15.15 ⚲
[198e06fe] BangBang v0.3.29 ⚲
[6e4b80f9] BenchmarkTools v0.5.0 ⚲
[b99e7846] BinaryProvider v0.5.10 ⚲
[4ece37e6] Bioequivalence v0.1.9 ⚲
[8e7c35d0] BlockArrays v0.12.11 ⚲
[764a87c0] BoundaryValueDiffEq v2.5.0 ⚲
[e1450e63] BufferedStreams v1.0.0 ⚲
[4f18b42c] BusinessDays v0.9.11 ⚲
[6e34b625] Bzip2_jll v1.0.6+5 ⚲
[fa961155] CEnum v0.4.1 ⚲
[70588ee8] CSSUtil v0.1.1 ⚲
[00ebfdb7] CSTParser v2.5.0 ⚲
[336ed68f] CSV v0.7.7 ⚲
[052768ef] CUDA v2.1.0 ⚲
[83423d85] Cairo_jll v1.16.0+6 ⚲
[49dc2e85] Calculus v0.5.1 ⚲
[a603d957] CanonicalTraits v0.2.3 ⚲
[aafaddc9] CatIndices v0.2.1 ⚲
[324d7699] CategoricalArrays v0.8.3 ⚲
[082447d4] ChainRules v0.7.32 ⚲
[d360d2e6] ChainRulesCore v0.9.17 ⚲
[cdddcdb0] ChainRulesTestUtils v0.5.3 ⚲
[34f1f09b] ClusterManagers v0.3.2 ⚲
[aaaa29a8] Clustering v0.14.2 ⚲
[53a63b46] CodeTools v0.7.1 ⚲
[da1fd8a2] CodeTracking v0.5.12 ⚲
[523fee87] CodecBzip2 v0.7.2 ⚲
[5ba52731] CodecLz4 v0.4.0 ⚲
[944b1d66] CodecZlib v0.7.0 ⚲
[6b39b394] CodecZstd v0.7.0 ⚲
[35d6a980] ColorSchemes v3.10.1 ⚲
[3da002f7] ColorTypes v0.10.9 ⚲
[c3611d14] ColorVectorSpace v0.8.6 ⚲
[5ae59095] Colors v0.12.4 ⚲
[861a8166] Combinatorics v1.0.2 ⚲
[a80b9123] CommonMark v0.6.4 ⚲
[38540f10] CommonSolve v0.2.0 ⚲
[bbf7d656] CommonSubexpressions v0.3.0 ⚲
[34da2185] Compat v3.23.0 ⚲
[e66e0078] CompilerSupportLibraries_jll v0.3.4+0 ⚲
[a33af91c] CompositionsBase v0.1.0 ⚲
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[88cd18e8] ConsoleProgressMonitor v0.1.2 ⚲
[187b0558] ConstructionBase v1.0.0 ⚲
[d38c429a] Contour v0.5.5 ⚲
[150eb455] CoordinateTransformations v0.6.0 ⚲
[adafc99b] CpuId v0.2.2 ⚲
[a8cc5b0e] Crayons v4.0.4 ⚲
[dc8bdbbb] CustomUnitRanges v1.0.0 ⚲
[717857b8] DSP v0.6.8 ⚲
[9a962f9c] DataAPI v1.4.0 ⚲
[a93c6f00] DataFrames v0.21.8 ⚲
[1313f7d8] DataFramesMeta v0.5.1 ⚲
[82cc6244] DataInterpolations v3.2.1 ⚲
[864edb3b] DataStructures v0.18.8 ⚲
[e2d170a0] DataValueInterfaces v1.0.0 ⚲
[e7dc6d0d] DataValues v0.4.13 ⚲
[31a5f54b] Debugger v0.6.6 ⚲
[7806a523] DecisionTree v0.10.10 ⚲
[244e2a9f] DefineSingletons v0.1.0 ⚲
[bcd4f6db] DelayDiffEq v5.25.1 ⚲
[2b5f629d] DiffEqBase v6.48.2 ⚲
[459566f4] DiffEqCallbacks v2.14.1 ⚲
[01453d9d] DiffEqDiffTools v1.7.0 ⚲
[5a0ffddc] DiffEqFinancial v2.4.0 ⚲
[c894b116] DiffEqJump v6.10.1 ⚲
[77a26b50] DiffEqNoiseProcess v5.4.0 ⚲
[055956cb] DiffEqPhysics v3.6.0 ⚲
[41bf760c] DiffEqSensitivity v6.33.0 ⚲
[163ba53b] DiffResults v1.0.2 ⚲
[b552c78f] DiffRules v1.0.1 ⚲
[0c46a032] DifferentialEquations v6.15.0 ⚲
[c619ae07] DimensionalPlotRecipes v1.2.0 ⚲
[b4f34e82] Distances v0.9.2 ⚲
[31c24e10] Distributions v0.23.2 ⚲
[33d173f1] DocSeeker v0.4.2 ⚲
[ffbed154] DocStringExtensions v0.8.3 ⚲
[e30172f5] Documenter v0.25.3 ⚲
[5ae413db] EarCut_jll v2.1.5+1 ⚲
[da5c29d0] EllipsisNotation v0.4.0 ⚲
[7876af07] Example v0.5.3 ⚲
[2e619515] Expat_jll v2.2.7+6 ⚲
[d4d017d3] ExponentialUtilities v1.8.0 ⚲
[e2ba6199] ExprTools v0.1.3 ⚲
[8f5d6c58] EzXML v1.1.0 ⚲
[c87230d0] FFMPEG v0.4.0 ⚲
[b22a6f82] FFMPEG_jll v4.3.1+4 ⚲
[4f61f5a4] FFTViews v0.3.1 ⚲
[7a1cc6ca] FFTW v1.2.4 ⚲
[f5851436] FFTW_jll v3.3.9+6 ⚲
[9aa1b823] FastClosures v0.3.2 ⚲
[5789e2e9] FileIO v1.4.4 ⚲
[1a297f60] FillArrays v0.8.14 ⚲
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[26cc04aa] FiniteDifferences v0.11.2 ⚲
[53c48c17] FixedPointNumbers v0.8.4 ⚲
[08572546] FlameGraphs v0.2.4 ⚲
[587475ba] Flux v0.11.2 ⚲
[a3f928ae] Fontconfig_jll v2.13.1+14 ⚲
[59287772] Formatting v0.4.1 ⚲
[f6369f11] ForwardDiff v0.10.12 ⚲
[d7e528f0] FreeType2_jll v2.10.1+5 ⚲
[559328eb] FriBidi_jll v1.0.5+6 ⚲
[069b7b12] FunctionWrappers v1.1.1 ⚲
[de31a74c] FunctionalCollections v0.5.0 ⚲
[d9f16b24] Functors v0.1.0 ⚲
[fb4132e2] FuzzyCompletions v0.2.4 ⚲
[0656b61e] GLFW_jll v3.3.2+1 ⚲
[38e38edf] GLM v1.3.11 ⚲
[781609d7] GMP_jll v6.1.2+6 ⚲
[0c68f7d7] GPUArrays v6.1.1 ⚲
[61eb1bfa] GPUCompiler v0.8.3 ⚲
[28b8d3ca] GR v0.53.0 ⚲
[d2c73de3] GR_jll v0.52.0+0 ⚲
[6b9d7cbe] GeneralizedGenerated v0.2.8 ⚲
[01680d73] GenericSVD v0.3.0 ⚲
[5c1252a2] GeometryBasics v0.3.3 ⚲
[78b55507] Gettext_jll v0.20.1+7 ⚲
[7746bdde] Glib_jll v2.59.0+4 ⚲
[a2bd30eb] Graphics v1.0.2 ⚲
[42e2da0e] Grisu v1.0.0 ⚲
[19dc6840] HCubature v1.4.0 ⚲
[cd3eb016] HTTP v0.8.19 ⚲
[9fb69e20] Hiccup v0.2.2 ⚲
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[09f84164] HypothesisTests v0.10.2 ⚲
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[22cec73e] InitialValues v0.2.10 ⚲
[505f98c9] InplaceOps v0.3.0 ⚲
[1d5cc7b8] IntelOpenMP_jll v2018.0.3+0 ⚲
[c601a237] Interact v0.10.3 ⚲
[d3863d7c] InteractBase v0.10.5 ⚲
[a98d9a8b] Interpolations v0.12.10 ⚲
[8197267c] IntervalSets v0.5.1 ⚲
[d8418881] Intervals v1.5.0 ⚲
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[c8e1da08] IterTools v1.3.0 ⚲
[42fd0dbc] IterativeSolvers v0.8.4 ⚲
[82899510] IteratorInterfaceExtensions v1.0.0 ⚲
[6042db11] JDBC v0.5.0 ⚲
[033835bb] JLD2 v0.2.4 ⚲
[692b3bcd] JLLWrappers v1.1.3 ⚲
[97c1335a] JSExpr v0.5.2 ⚲
[682c06a0] JSON v0.21.1 ⚲
[7d188eb4] JSONSchema v0.3.2 ⚲
[494afd89] JavaCall v0.7.6 ⚲
[aacddb02] JpegTurbo_jll v2.0.1+3 ⚲
[4076af6c] JuMP v0.21.5 ⚲
[98e50ef6] JuliaFormatter v0.7.6 ⚲
[aa1ae85d] JuliaInterpreter v0.7.26 ⚲
[ea4eb333] JuliaRunClient v0.2.2 ⚲
[b14d175d] JuliaVariables v0.2.3 ⚲
[480116ec] JuliaWebAPI v0.6.2 ⚲
[e5e0dc1b] Juno v0.8.4 ⚲
[5ab0869b] KernelDensity v0.6.2 ⚲
[1902f260] Knet v1.4.3 ⚲
[bcebb21b] Knockout v0.2.4 ⚲
[c1c5ebd0] LAME_jll v3.100.0+3 ⚲
[929cbde3] LLVM v3.3.0 ⚲
[7c4cb9fa] LNR v0.2.1 ⚲
[dd4b983a] LZO_jll v2.10.0+3 ⚲
[b964fa9f] LaTeXStrings v1.2.0 ⚲
[2ee39098] LabelledArrays v1.3.0 ⚲
[23fbe1c1] Latexify v0.14.2 ⚲
[a5e1c1ea] LatinHypercubeSampling v1.7.3 ⚲
[73f95e8e] LatticeRules v0.0.1 ⚲
[50d2b5c4] Lazy v0.15.1 ⚲
[1d6d02ad] LeftChildRightSiblingTrees v0.1.2 ⚲
[dd192d2f] LibVPX_jll v1.9.0+1 ⚲
[e9f186c6] Libffi_jll v3.2.1+4 ⚲
[d4300ac3] Libgcrypt_jll v1.8.5+4 ⚲
[7e76a0d4] Libglvnd_jll v1.3.0+3 ⚲
[7add5ba3] Libgpg_error_jll v1.36.0+3 ⚲
[94ce4f54] Libiconv_jll v1.16.0+7 ⚲
[4b2f31a3] Libmount_jll v2.34.0+3 ⚲
[89763e89] Libtiff_jll v4.1.0+2 ⚲
[38a345b3] Libuuid_jll v2.34.0+7 ⚲
[2ec943e9] Libz v1.0.1 ⚲
[093fc24a] LightGraphs v1.3.0 ⚲
[9c8b4983] LightXML v0.9.0 ⚲
[d3d80556] LineSearches v7.1.0 ⚲
[4345ca2d] Loess v0.5.2 ⚲
[e6f89c97] LoggingExtras v0.4.2 ⚲
[bdcacae8] LoopVectorization v0.8.26 ⚲
[6f1432cf] LoweredCodeUtils v0.4.9 ⚲
[5ced341a] Lz4_jll v1.9.2+2 ⚲
[c7f686f2] MCMCChains v4.2.4 ⚲
[d00139f3] METIS_jll v5.1.0+5 ⚲
[856f044c] MKL_jll v2020.2.254+0 ⚲
[f0e99cf1] MLBase v0.8.0 ⚲
[e80e1ace] MLJModelInterface v0.3.6 ⚲
[d8e11817] MLStyle v0.4.6 ⚲
[1914dd2f] MacroTools v0.5.6 ⚲
[dbb5928d] MappedArrays v0.2.2 ⚲
[b8f27783] MathOptInterface v0.9.18 ⚲
[fdba3010] MathProgBase v0.7.8 ⚲
[739be429] MbedTLS v1.0.3 ⚲
[c8ffd9c3] MbedTLS_jll v2.16.8+1 ⚲
[442fdcdd] Measures v0.3.1 ⚲
[e89f7d12] Media v0.5.0 ⚲
[128add7d] MicroCollections v0.1.0 ⚲
[3ae66bd7] Miletus v1.0.0 ⚲
[e1d29d7a] Missings v0.4.4 ⚲
[ff71e718] MixedModels v3.1.0 ⚲
[78c3b35d] Mocking v0.7.1 ⚲
[961ee093] ModelingToolkit v3.21.0 ⚲
[4886b29c] MonteCarloIntegration v0.0.1 ⚲
[e94cdb99] MosaicViews v0.2.4 ⚲
[46d2c3a1] MuladdMacro v0.2.2 ⚲
[f9640e96] MultiScaleArrays v1.8.1 ⚲
[6f286f6a] MultivariateStats v0.7.0 ⚲
[ffc61752] Mustache v1.0.8 ⚲
[d8a4904e] MutableArithmetics v0.2.11 ⚲
[29142fd5] NCA v1.0.3 ⚲
[d41bc354] NLSolversBase v7.5.0 ⚲
[76087f3c] NLopt v0.6.1 ⚲
[079eb43e] NLopt_jll v2.6.2+0 ⚲
[2774e3e8] NLsolve v4.4.1 ⚲
[872c559c] NNlib v0.7.6 ⚲
[77ba4419] NaNMath v0.3.4 ⚲
[71a1bf82] NameResolution v0.1.5 ⚲
[c020b1a1] NaturalSort v1.0.0 ⚲
[b8a86587] NearestNeighbors v0.4.7 ⚲
[49dea1ee] Nettle v0.5.0 ⚲
[4c82536e] Nettle_jll v3.4.1+2 ⚲
[4d1e1d77] Nullables v1.0.0 ⚲
[510215fc] Observables v0.3.2 ⚲
[6fe1bfb0] OffsetArrays v1.4.0 ⚲
[e7412a2a] Ogg_jll v1.3.4+2 ⚲
[a15396b6] OnlineStats v1.5.7 ⚲
[925886fa] OnlineStatsBase v1.4.4 ⚲
[4536629a] OpenBLAS_jll v0.3.9+5 ⚲
[458c3c95] OpenSSL_jll v1.1.1+6 ⚲
[efe28fd5] OpenSpecFun_jll v0.5.3+4 ⚲
[429524aa] Optim v0.22.0 ⚲
[91d4177d] Opus_jll v1.3.1+3 ⚲
[bac558e1] OrderedCollections v1.3.2 ⚲
[1dea7af3] OrdinaryDiffEq v5.43.0 ⚲
[2f80f16e] PCRE_jll v8.42.0+4 ⚲
[90014a1f] PDMats v0.9.12 ⚲
[9b87118b] PackageCompiler v1.2.3 ⚲
[5432bcbf] PaddedViews v0.5.6 ⚲
[65888b18] ParameterizedFunctions v5.6.0 ⚲
[d96e819e] Parameters v0.12.1 ⚲
[fae87a5f] ParserCombinator v2.0.0 ⚲
[69de0a69] Parsers v1.0.12 ⚲
[fa939f87] Pidfile v1.2.0 ⚲
[b98c9c47] Pipe v1.3.0 ⚲
[30392449] Pixman_jll v0.38.4+5 ⚲
[4722fa14] PkgAuthentication v0.3.0 ⚲
[ccf2f8ad] PlotThemes v2.0.0 ⚲
[995b91a9] PlotUtils v1.0.7 ⚲
[91a5bcdd] Plots v1.8.1 ⚲
[e409e4f3] PoissonRandom v0.4.0 ⚲
[f27b6e38] Polynomials v1.1.11 ⚲
[2dfb63ee] PooledArrays v0.5.3 ⚲
[85a6dd25] PositiveFactorizations v0.2.3 ⚲
[8162dcfd] PrettyPrint v0.2.0 ⚲
[08abe8d2] PrettyTables v0.9.1 ⚲
[27ebfcd6] Primes v0.5.0 ⚲
[33c8b6b6] ProgressLogging v0.1.3 ⚲
[92933f4c] ProgressMeter v1.4.0 ⚲
[3349acd9] ProtoBuf v0.9.0 ⚲
[4f2c3c20] Pumas v1.1.0 ⚲
[0c61e9cd] PumasPlots v0.2.0 ⚲
[b7b41870] PumasTutorials v0.1.1 ⚲
[438e738f] PyCall v1.92.1 ⚲
[d330b81b] PyPlot v2.9.0 ⚲
[784f63db] Qhull_jll v2019.1.0+2 ⚲
[ede63266] Qt_jll v5.15.0+3 ⚲
[1fd47b50] QuadGK v2.4.1 ⚲
[67601950] Quadrature v1.5.0 ⚲
[fcd29c91] QuantEcon v0.16.2 ⚲
[c6596682] QuantileRegressions v0.1.5 ⚲
[8a4e6c94] QuasiMonteCarlo v0.2.1 ⚲
[6f49c342] RCall v0.13.9 ⚲
[fb686558] RandomExtensions v0.4.3 ⚲
[e6cf234a] RandomNumbers v1.4.0 ⚲
[b3c3ace0] RangeArrays v0.3.2 ⚲
[c84ed2f1] Ratios v0.4.0 ⚲
[3cdcf5f2] RecipesBase v1.1.1 ⚲
[01d81517] RecipesPipeline v0.2.1 ⚲
[731186ca] RecursiveArrayTools v2.7.2 ⚲
[f2c3362d] RecursiveFactorization v0.1.4 ⚲
[189a3867] Reexport v0.2.0 ⚲
[42d2dcc6] Referenceables v0.1.0 ⚲
[ae029012] Requires v1.1.0 ⚲
[ae5879a3] ResettableStacks v1.0.0 ⚲
[37e2e3b7] ReverseDiff v1.4.3 ⚲
[295af30f] Revise v2.7.6 ⚲
[708f8203] Richardson v1.2.0 ⚲
[79098fc4] Rmath v0.6.1 ⚲
[f50d1b31] Rmath_jll v0.2.2+1 ⚲
[f2b01f46] Roots v1.0.5 ⚲
[6038ab10] Rotations v1.0.1 ⚲
[21efa798] SIMDPirates v0.8.26 ⚲
[476501e8] SLEEFPirates v0.5.5 ⚲
[1bc83da4] SafeTestsets v0.0.1 ⚲
[321657f4] ScientificTypes v1.1.0 ⚲
[3646fa90] ScikitLearn v0.6.2 ⚲
[6e75b9c4] ScikitLearnBase v0.5.0 ⚲
[6c6a2e73] Scratch v1.0.3 ⚲
[91c51154] SentinelArrays v1.2.16 ⚲
[efcf1570] Setfield v0.7.0 ⚲
[1277b4bf] ShiftedArrays v1.0.0 ⚲
[992d4aef] Showoff v0.3.2 ⚲
[699a6c99] SimpleTraits v0.9.3 ⚲
[ed01d8cd] Sobol v1.4.0 ⚲
[b85f4697] SoftGlobalScope v1.1.0 ⚲
[a2af1166] SortingAlgorithms v0.3.1 ⚲
[47a9eef4] SparseDiffTools v1.10.1 ⚲
[276daf66] SpecialFunctions v0.10.3 ⚲
[171d559e] SplittablesBase v0.1.10 ⚲
[860ef19b] StableRNGs v1.0.0 ⚲
[90137ffa] StaticArrays v0.12.5 ⚲
[2913bbd2] StatsBase v0.33.2 ⚲
[4c63d2b9] StatsFuns v0.9.5 ⚲
[3eaba693] StatsModels v0.6.15 ⚲
[f3b207a7] StatsPlots v0.14.17 ⚲
[9672c7b4] SteadyStateDiffEq v1.5.1 ⚲
[789caeaf] StochasticDiffEq v6.26.0 ⚲
[88034a9c] StringDistances v0.8.0 ⚲
[09ab397b] StructArrays v0.4.4 ⚲
[856f2bd8] StructTypes v1.1.0 ⚲
[bea87d4a] SuiteSparse_jll v5.4.0+9 ⚲
[c3572dad] Sundials v4.3.0 ⚲
[fb77eaff] Sundials_jll v5.2.0+1 ⚲
[7522ee7d] SweepOperator v0.3.0 ⚲
[24249f21] SymPy v1.0.32 ⚲
[d1185830] SymbolicUtils v0.5.2 ⚲
[ab02a1b2] TableOperations v0.3.0 ⚲
[3783bdb8] TableTraits v1.0.0 ⚲
[40c74d1a] TableView v0.6.1 ⚲
[bd369af6] Tables v1.2.1 ⚲
[5d786b92] TerminalLoggers v0.1.2 ⚲
[ac1d9e8a] ThreadsX v0.1.7 ⚲
[06e1c1a7] TiledIteration v0.2.5 ⚲
[f269a46b] TimeZones v1.5.0 ⚲
[a759f4b9] TimerOutputs v0.5.7 ⚲
[0796e94c] Tokenize v0.5.8 ⚲
[9f7883ad] Tracker v0.2.12 ⚲
[3bb67fe8] TranscodingStreams v0.9.5 ⚲
[28d57a85] Transducers v0.4.53 ⚲
[84d833dd] TransformVariables v0.3.4 ⚲
[a2a6695c] TreeViews v0.3.0 ⚲
[30578b45] URIParser v0.4.1 ⚲
[3a884ed6] UnPack v1.0.2 ⚲
[b8865327] UnicodePlots v1.3.0 ⚲
[1986cc42] Unitful v1.5.0 ⚲
[3d5dd08c] VectorizationBase v0.12.33 ⚲
[81def892] VersionParsing v1.2.0 ⚲
[19fa3120] VertexSafeGraphs v0.1.2 ⚲
[a2964d1f] Wayland_jll v1.17.0+4 ⚲
[2381bf8a] Wayland_protocols_jll v1.18.0+4 ⚲
[44d3d7a6] Weave v0.10.6 ⚲
[0f1e0344] WebIO v0.8.93 ⚲
[104b5d7c] WebSockets v1.5.2 ⚲
[cc8bc4a8] Widgets v0.6.2 ⚲
[1b915085] WinReg v0.3.1 ⚲
[efce3f68] WoodburyMatrices v0.5.3 ⚲
[02c8fc9c] XML2_jll v2.9.10+3 ⚲
[aed1982a] XSLT_jll v1.1.33+4 ⚲
[4f6342f7] Xorg_libX11_jll v1.6.9+4 ⚲
[0c0b7dd1] Xorg_libXau_jll v1.0.9+4 ⚲
[935fb764] Xorg_libXcursor_jll v1.2.0+4 ⚲
[a3789734] Xorg_libXdmcp_jll v1.1.3+4 ⚲
[1082639a] Xorg_libXext_jll v1.3.4+4 ⚲
[d091e8ba] Xorg_libXfixes_jll v5.0.3+4 ⚲
[a51aa0fd] Xorg_libXi_jll v1.7.10+4 ⚲
[d1454406] Xorg_libXinerama_jll v1.1.4+4 ⚲
[ec84b674] Xorg_libXrandr_jll v1.5.2+4 ⚲
[ea2f1a96] Xorg_libXrender_jll v0.9.10+4 ⚲
[14d82f49] Xorg_libpthread_stubs_jll v0.1.0+3 ⚲
[c7cfdc94] Xorg_libxcb_jll v1.13.0+3 ⚲
[cc61e674] Xorg_libxkbfile_jll v1.1.0+4 ⚲
[12413925] Xorg_xcb_util_image_jll v0.4.0+0 ⚲
[2def613f] Xorg_xcb_util_jll v0.4.0+0 ⚲
[975044d2] Xorg_xcb_util_keysyms_jll v0.4.0+0 ⚲
[0d47668e] Xorg_xcb_util_renderutil_jll v0.3.9+0 ⚲
[c22f9ab0] Xorg_xcb_util_wm_jll v0.4.1+0 ⚲
[35661453] Xorg_xkbcomp_jll v1.4.2+4 ⚲
[33bec58e] Xorg_xkeyboard_config_jll v2.27.0+4 ⚲
[c5fb5394] Xorg_xtrans_jll v1.4.0+3 ⚲
[ddb6d928] YAML v0.4.2 ⚲
[c2297ded] ZMQ v1.2.1 ⚲
[8f1865be] ZeroMQ_jll v4.3.2+5 ⚲
[a5390f91] ZipFile v0.9.3 ⚲
[83775a58] Zlib_jll v1.2.11+18 ⚲
[3161d3a3] Zstd_jll v1.4.5+2 ⚲
[e88e6eb3] Zygote v0.5.9 ⚲
[700de1a5] ZygoteRules v0.2.0 ⚲
[0ac62f75] libass_jll v0.14.0+4 ⚲
[f638f0a6] libfdk_aac_jll v0.1.6+4 ⚲
[b53b4c65] libpng_jll v1.6.37+6 ⚲
[f27f6e37] libvorbis_jll v1.3.6+6 ⚲
[1270edf5] x264_jll v2020.7.14+2 ⚲
[dfaa095f] x265_jll v3.0.0+3 ⚲
[d8fb68d0] xkbcommon_jll v0.9.1+5 ⚲
[2a0f44e3] Base64 ⚲
[ade2ca70] Dates ⚲
[8bb1440f] DelimitedFiles ⚲
[8ba89e20] Distributed ⚲
[7b1f6079] FileWatching ⚲
[9fa8497b] Future ⚲
[b77e0a4c] InteractiveUtils ⚲
[76f85450] LibGit2 ⚲
[8f399da3] Libdl ⚲
[37e2e46d] LinearAlgebra ⚲
[56ddb016] Logging ⚲
[d6f4376e] Markdown ⚲
[a63ad114] Mmap ⚲
[44cfe95a] Pkg ⚲
[de0858da] Printf ⚲
[9abbd945] Profile ⚲
[3fa0cd96] REPL ⚲
[9a3f8284] Random ⚲
[ea8e919c] SHA ⚲
[9e88b42a] Serialization ⚲
[1a1011a3] SharedArrays ⚲
[6462fe0b] Sockets ⚲
[2f01184e] SparseArrays ⚲
[10745b16] Statistics ⚲
[4607b0f0] SuiteSparse ⚲
[8dfed614] Test ⚲
[cf7118a7] UUIDs ⚲
[4ec0a83e] Unicode ⚲

versioninfo()

Julia Version 1.5.2
Commit 539f3ce943 (2020-09-23 23:17 UTC)
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: AMD Ryzen 7 PRO 3700U w/ Radeon Vega Mobile Gfx
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-9.0.1 (ORCJIT, znver1)
Environment:
JULIA_DEPOT_PATH = C:\Users\gyang.julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\local\share\julia;d:\JuliaPro-1.5.2-2\Julia-1.5.2\share\julia
JULIA_EDITOR = “D:\JuliaPro-1.5.2-2\app-1.51.0\atom.exe” -a
JULIA_LOAD_PATH = C:\Users\gyang.julia\environments\JuliaPro_v1.5.2-2;C:\Users\gyang.julia\Pumas;@;@v#.#;@stdlib
JULIA_NUM_THREADS = 8
JULIA_PKG_SERVER = pkg.juliahub.com

[diabloyg]

For the computer in which the code runs normally:

Status C:\Users\admin\.julia\environments\JuliaPro_v1.5.2-2\Project.toml
[c3fe647b] AbstractAlgebra v0.11.1 ⚲
[621f4979] AbstractFFTs v0.5.0 ⚲
[80f14c24] AbstractMCMC v2.1.0 ⚲
[1520ce14] AbstractTrees v0.3.3 ⚲
[79e6a3ab] Adapt v2.3.0 ⚲
[0bf59076] AdvancedHMC v0.2.26 ⚲
[dce04be8] ArgCheck v1.1.0 ⚲
[ec485272] ArnoldiMethod v0.0.4 ⚲
[7d9fca2a] Arpack v0.4.0 ⚲
[68821587] Arpack_jll v3.5.0+3 ⚲
[4fba245c] ArrayInterface v2.13.7 ⚲
[4c555306] ArrayLayouts v0.3.8 ⚲
[69666777] Arrow v0.4.1 ⚲
[56f22d72] Artifacts v1.3.0 ⚲
[bf4720bc] AssetRegistry v0.1.0 ⚲
[c52e3926] Atom v0.12.21 ⚲
[6710c13c] AutoGrad v1.2.3 ⚲
[15f4f7f2] AutoHashEquals v0.2.0 ⚲
[13072b0f] AxisAlgorithms v1.0.0 ⚲
[39de3d68] AxisArrays v0.4.3 ⚲
[ab4f0b2a] BFloat16s v0.1.0 ⚲
[aae01518] BandedMatrices v0.15.15 ⚲
[198e06fe] BangBang v0.3.29 ⚲
[6e4b80f9] BenchmarkTools v0.5.0 ⚲
[b99e7846] BinaryProvider v0.5.10 ⚲
[4ece37e6] Bioequivalence v0.1.9 ⚲
[8e7c35d0] BlockArrays v0.12.11 ⚲
[764a87c0] BoundaryValueDiffEq v2.5.0 ⚲
[e1450e63] BufferedStreams v1.0.0 ⚲
[4f18b42c] BusinessDays v0.9.11 ⚲
[6e34b625] Bzip2_jll v1.0.6+5 ⚲
[fa961155] CEnum v0.4.1 ⚲
[70588ee8] CSSUtil v0.1.1 ⚲
[00ebfdb7] CSTParser v2.5.0 ⚲
[336ed68f] CSV v0.7.7 ⚲
[052768ef] CUDA v2.1.0 ⚲
[83423d85] Cairo_jll v1.16.0+6 ⚲
[49dc2e85] Calculus v0.5.1 ⚲
[a603d957] CanonicalTraits v0.2.3 ⚲
[aafaddc9] CatIndices v0.2.1 ⚲
[324d7699] CategoricalArrays v0.8.3 ⚲
[082447d4] ChainRules v0.7.32 ⚲
[d360d2e6] ChainRulesCore v0.9.17 ⚲
[cdddcdb0] ChainRulesTestUtils v0.5.3 ⚲
[34f1f09b] ClusterManagers v0.3.2 ⚲
[aaaa29a8] Clustering v0.14.2 ⚲
[53a63b46] CodeTools v0.7.1 ⚲
[da1fd8a2] CodeTracking v0.5.12 ⚲
[523fee87] CodecBzip2 v0.7.2 ⚲
[5ba52731] CodecLz4 v0.4.0 ⚲
[944b1d66] CodecZlib v0.7.0 ⚲
[6b39b394] CodecZstd v0.7.0 ⚲
[35d6a980] ColorSchemes v3.10.1 ⚲
[3da002f7] ColorTypes v0.10.9 ⚲
[c3611d14] ColorVectorSpace v0.8.6 ⚲
[5ae59095] Colors v0.12.4 ⚲
[861a8166] Combinatorics v1.0.2 ⚲
[a80b9123] CommonMark v0.6.4 ⚲
[38540f10] CommonSolve v0.2.0 ⚲
[bbf7d656] CommonSubexpressions v0.3.0 ⚲
[34da2185] Compat v3.23.0 ⚲
[e66e0078] CompilerSupportLibraries_jll v0.3.4+0 ⚲
[a33af91c] CompositionsBase v0.1.0 ⚲
[ed09eef8] ComputationalResources v0.3.2 ⚲
[8f4d0f93] Conda v1.5.0 ⚲
[88cd18e8] ConsoleProgressMonitor v0.1.2 ⚲
[187b0558] ConstructionBase v1.0.0 ⚲
[d38c429a] Contour v0.5.5 ⚲
[150eb455] CoordinateTransformations v0.6.0 ⚲
[adafc99b] CpuId v0.2.2 ⚲
[a8cc5b0e] Crayons v4.0.4 ⚲
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[f638f0a6] libfdk_aac_jll v0.1.6+4 ⚲
[b53b4c65] libpng_jll v1.6.37+6 ⚲
[f27f6e37] libvorbis_jll v1.3.6+6 ⚲
[1270edf5] x264_jll v2020.7.14+2 ⚲
[dfaa095f] x265_jll v3.0.0+3 ⚲
[d8fb68d0] xkbcommon_jll v0.9.1+5 ⚲
[2a0f44e3] Base64 ⚲
[ade2ca70] Dates ⚲
[8bb1440f] DelimitedFiles ⚲
[8ba89e20] Distributed ⚲
[7b1f6079] FileWatching ⚲
[9fa8497b] Future ⚲
[b77e0a4c] InteractiveUtils ⚲
[76f85450] LibGit2 ⚲
[8f399da3] Libdl ⚲
[37e2e46d] LinearAlgebra ⚲
[56ddb016] Logging ⚲
[d6f4376e] Markdown ⚲
[a63ad114] Mmap ⚲
[44cfe95a] Pkg ⚲
[de0858da] Printf ⚲
[9abbd945] Profile ⚲
[3fa0cd96] REPL ⚲
[9a3f8284] Random ⚲
[ea8e919c] SHA ⚲
[9e88b42a] Serialization ⚲
[1a1011a3] SharedArrays ⚲
[6462fe0b] Sockets ⚲
[2f01184e] SparseArrays ⚲
[10745b16] Statistics ⚲
[4607b0f0] SuiteSparse ⚲
[8dfed614] Test ⚲
[cf7118a7] UUIDs ⚲
[4ec0a83e] Unicode ⚲

Julia Version 1.5.2
Commit 539f3ce943 (2020-09-23 23:17 UTC)
Platform Info:
OS: Windows (x86_64-w64-mingw32)
CPU: Intel® Core™ i7-10875H CPU @ 2.30GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-9.0.1 (ORCJIT, skylake)
Environment:
JULIA_DEPOT_PATH = C:\Users\admin.julia;D:\JuliaPro-1.5.2-2\Julia-1.5.2\local\share\julia;D:\JuliaPro-1.5.2-2\Julia-1.5.2\share\julia
JULIA_EDITOR = “D:\JuliaPro-1.5.2-2\app-1.51.0\atom.exe” -a
JULIA_LOAD_PATH = C:\Users\admin.julia\environments\JuliaPro_v1.5.2-2;C:\Users\admin.julia\Pumas;@;@v#.#;@stdlib
JULIA_NUM_THREADS = 8
JULIA_PKG_SERVER = pkg.juliahub.com

[andreasnoack]

Did you run using Pumas before you ran @load “test2.jld2” result detail wres resout?

[diabloyg]

Yes I did. The first line was " using CSV, Pumas, Plots, Random, JLD2".

[diabloyg]

Hi @andreasnoack. I further confirmed that, within once opening of atom, the @load function is ok. However, if I opened the atom for another time, the @load function is invalid even in the same computer. Does this mean that the JLD2 is not compatible with pumas? I also tried other I/O approaches but none of them worked. There are always these message:

Warning: some parameters could not be resolved for type ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}; reconstructing
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238
┌ Warning: some parameters could not be resolved for type Pumas.FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46},Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show_trace, :store_trace, :extended_trace, :g_tol, :allow_f_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc,
:omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}; reading as Pumas.FittedPumasModel{PumasModel,Array{Subject{NamedTuple{(:dv,),Tuple{Array{Union{Missing, Float64},1}}},T2,Array{Pumas.Event{Float64,Float64,Float64,Float64,Float64,Float64,Nothing,Int64},1},Array{Float64,1}} where T2,1},Optim.MultivariateOptimizationResults{Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat},Float64,Array{Float64,1},Float64,Float64,Array{Optim.OptimizationState{Float64,Optim.BFGS{LineSearches.InitialStatic{Float64},LineSearches.BackTracking{Float64,Int64},Pumas.var"#339#340"{NLSolversBase.OnceDifferentiable{Float64,Array{Float64,1},Array{Float64,1}},Array{Float64,1}},Nothing,Optim.Flat}},1},Bool},Pumas.MAP{Pumas.FOCEI},Array{Array{Float64,1},1},NamedTuple{(:optimize_fn, :constantcoef, :omegas, :ensemblealg),Tuple{Pumas.DefaultOptimizeFN{Nothing,NamedTuple{(:show_trace, :store_trace, :extended_trace, :g_tol, :allow_f_increases),Tuple{Bool,Bool,Bool,Float64,Bool}}},NamedTuple{,Tuple{}},Tuple{},EnsembleSerial}},ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}}}
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1234
┌ Warning: some parameters could not be resolved for type PumasModel{ParamSet{NamedTuple{(:tv_cl, :tv_vc, :tv_vp, :tv_cld, :tv_vmax, :tv_km, :tv_bw_cl, :tv_bw_vc, :omega, :epsprop),Tuple{RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Int64},RealDomain{Float64,Int64,Float64},RealDomain{Float64,Int64,Int64},PDiagDomain{PDMats.PDiagMat{Float64,Array{Float64,1}}},RealDomain{Float64,TransformVariables.Infinity{true},Float64}}}},Main.#9#32,Main.#10#33,Main.#12#35,ODEProblem{Nothing,Tuple{Nothing,Nothing},false,Nothing,JLD2.ReconstructedTypes.var"##ODEFunction{false,Main.#13#36,LinearAlgebra.UniformScaling{Bool},Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing,Nothing}#289",Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{,Tuple{}}},DiffEqBase.StandardODEProblem},Main.#14#37,Main.#23#46}; reconstructing
└ @ JLD2 C:\Users\gyang.julia\packages\JLD2\eU405\src\data.jl:1238

[andreasnoack]

We have debugged your issues a little further.

1. It seems that JLD2 isn’t able to handle our models so I’ll recommend using Serialization instead, i.e. something like

julia> open("saved_model.jls", "w") do f
         serialize(f, Dict("fit" => _fit, "infer" => _infer))
       end

and then

julia> d = deserialize("saved_model.jls")
Dict{String,Any} with 2 entries:
  "fit"   => FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:θ, :Ω, :Σ),Tuple{VectorDomain{Array{Flo…
  "infer" => FittedPumasModelInference{FittedPumasModel{PumasModel{ParamSet{NamedTuple{(:θ, :Ω, :Σ),Tu…

2. It looks like there might be some issues with ODE solving on AMD systems but we are still debugging this issues. We’ll let you know once we have a better understanding of the issue.

[diabloyg]

Thanks for your reply.

For the first question, the Serialization worked. However, after I typed " d = deserialize(“saved_model.jls”)" there, the ‘d’ was actually a dictionary object (I suppose, I’m new to programming language), but not a PumasModel, FittedPumasModel object or something produced/to be fitted by Pumas.

Nontheless, those stored/needed objects could be accessed through the dict index such as:

mymodel = d[“index name”].

Which is quite convenient to store all information of a model into one file. Thanks for your recommendation.