JOSS review: installation error

[ranocha]

This is part of the review openjournals/joss-reviews#7048. I get the following error when installing the package on Julia 1.10:

Precompiling project...
  ✗ ProbNumDiffEq
  ✗ ProbNumDiffEq → RecipesBaseExt
  71 dependencies successfully precompiled in 80 seconds. 173 already precompiled.
  1 dependency had output during precompilation:
┌ Espresso
│  WARNING: could not import Base.Slot into Espresso
└  
  2 dependencies errored.
  For a report of the errors see `julia> err`. To retry use `pkg> precompile`

julia> using ProbNumDiffEq
Precompiling ProbNumDiffEq
        Info Given ProbNumDiffEq was explicitly requested, output will be shown live 
ERROR: LoadError: MethodError: no method matching get_fsalfirstlast(::ProbNumDiffEq.EKCache{Nothing, ProbNumDiffEq.IsometricKroneckerCovariance{Float64}, ProbNumDiffEq.var"#Proj#121"{Float64, ProbNumDiffEq.IsometricKroneckerCovariance{Float64}}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, LinearAlgebra.Diagonal{Float64, Vector{Float64}}}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, LinearAlgebra.Diagonal{Float64, Vector{Float64}}}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, LinearAlgebra.Adjoint{Float64, Matrix{Float64}}}, Vector{Float64}, Vector{Float64}, ProbNumDiffEq.Gaussian{Vector{Float64}, PSDMatrices.PSDMatrix{Float64, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}}}, ProbNumDiffEq.IWP{Float64}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}, PSDMatrices.PSDMatrix{Float64, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}, Nothing, Nothing, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}, Vector{Float64}, Matrix{Float64}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}, ProbNumDiffEq.AffineNormalKernel{ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}, Vector{Float64}, PSDMatrices.PSDMatrix{Float64, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}}}, LinearAlgebra.Diagonal{Float64, FillArrays.Fill{Float64, 1, Tuple{Base.OneTo{Int64}}}}, ProbNumDiffEq.DynamicDiffusion, ProbNumDiffEq.StandardODEMeasurementModel{true, SciMLBase.ODEFunction{true, true, ProbNumDiffEq.var"#lorenz#148", LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}}, ProbNumDiffEq.Gaussian{Vector{Float64}, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}}, ProbNumDiffEq.Gaussian{Vector{Float64}, PSDMatrices.PSDMatrix{Float64, ProbNumDiffEq.RightIsometricKroneckerProduct{Float64, Matrix{Float64}}}}, Float64, Float64, Vector{Float64}, SciMLBase.UJacobianWrapper{true, SciMLBase.ODEFunction{true, true, ProbNumDiffEq.var"#lorenz#148", LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, Float64, SciMLBase.NullParameters}, Nothing, Vector{Float64}}, ::Vector{Float64})

Closest candidates are:
  get_fsalfirstlast(::OrdinaryDiffEqCore.CompositeCache, ::Any)
   @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/4A2vD/src/caches/basic_caches.jl:16
  get_fsalfirstlast(::OrdinaryDiffEqTsit5.Tsit5Cache, ::Any)
   @ OrdinaryDiffEqTsit5 ~/.julia/packages/OrdinaryDiffEqTsit5/DHYtz/src/tsit_caches.jl:39
  get_fsalfirstlast(::OrdinaryDiffEqQPRK.QPRK98Cache, ::Any)
   @ OrdinaryDiffEqQPRK ~/.julia/packages/OrdinaryDiffEqQPRK/7AUMg/src/qprk_caches.jl:33
  ...

Stacktrace:
  [1] __init(prob::SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, SciMLBase.ODEFunction{true, true, ProbNumDiffEq.var"#lorenz#148", LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, alg::ProbNumDiffEq.EK0{ProbNumDiffEq.IWP{Float64}, ProbNumDiffEq.DynamicDiffusion, ProbNumDiffEq.TaylorModeInit, Nothing, UnionAll}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{Val{true}}; saveat::Tuple{}, tstops::Tuple{}, d_discontinuities::Tuple{}, save_idxs::Nothing, save_everystep::Bool, save_on::Bool, save_start::Bool, save_end::Nothing, callback::Nothing, dense::Bool, calck::Bool, dt::Float64, dtmin::Float64, dtmax::Float64, force_dtmin::Bool, adaptive::Bool, gamma::Rational{Int64}, abstol::Nothing, reltol::Nothing, qmin::Rational{Int64}, qmax::Int64, qsteady_min::Int64, qsteady_max::Int64, beta1::Nothing, beta2::Nothing, qoldinit::Rational{Int64}, controller::Nothing, fullnormalize::Bool, failfactor::Int64, maxiters::Int64, internalnorm::typeof(DiffEqBase.ODE_DEFAULT_NORM), internalopnorm::typeof(LinearAlgebra.opnorm), isoutofdomain::typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), unstable_check::typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), verbose::Bool, timeseries_errors::Bool, dense_errors::Bool, advance_to_tstop::Bool, stop_at_next_tstop::Bool, initialize_save::Bool, progress::Bool, progress_steps::Int64, progress_name::String, progress_message::typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), progress_id::Symbol, userdata::Nothing, allow_extrapolation::Bool, initialize_integrator::Bool, alias_u0::Bool, alias_du0::Bool, initializealg::OrdinaryDiffEqCore.DefaultInit, kwargs::@Kwargs{})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/4A2vD/src/solve.jl:472
  [2] __init(prob::SciMLBase.ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, SciMLBase.ODEFunction{true, true, ProbNumDiffEq.var"#lorenz#148", LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing, Nothing, Nothing, Nothing}, @Kwargs{}, SciMLBase.StandardODEProblem}, alg::ProbNumDiffEq.EK0{ProbNumDiffEq.IWP{Float64}, ProbNumDiffEq.DynamicDiffusion, ProbNumDiffEq.TaylorModeInit, Nothing, UnionAll}, timeseries_init::Tuple{}, ts_init::Tuple{}, ks_init::Tuple{}, recompile::Type{Val{true}})
    @ OrdinaryDiffEqCore ~/.julia/packages/OrdinaryDiffEqCore/4A2vD/src/solve.jl:11
[...]

[nathanaelbosch]

Thanks for bringing this up. This is likely related to #322 and unfortunately I didn't have the time to keep up with the OrdinaryDiffEq.jl changes these last weeks. But I will do my best to resolve this as quickly as I can now.

[nathanaelbosch]

#325 will resolve this. To use the package right away you could install this branch from github with

] add ProbNumDiffEq#hotfix/get_fsalfirstlast

But I will also make sure to get the PR merged with passing tests asap and then do a quick patch release.

[ranocha]

Thanks! I will wait for the patch release

[nathanaelbosch]

I just released 0.16.1 and checked that I can indeed install it in a fresh environment. I will close this for now, but if you still encounter some installation problem please feel free to reopen. And of course thank you a lot for taking the time to review this package!

[nathanaelbosch]

Hi @ranocha, were you able to confirm that the package can now be installed correctly? If there is any other related open issue, please let me know and I'll do my best to take care of it.

[ranocha]

Thanks, it works for me indeed