Dear Community,
I am relatively new to julia and want to model ordinary differential equations. Installing the OrdinaryDiffEq package failed, and the output of julia> import Pkg; Pkg.precompile() is:
julia> import Pkg; Pkg.precompile()
Precompiling project...
✗ LinearSolve
✗ NonlinearSolve
✗ OrdinaryDiffEq
0 dependencies successfully precompiled in 37 seconds. 123 already precompiled.
ERROR: The following 1 direct dependency failed to precompile:
OrdinaryDiffEq [1dea7af3-3e70-54e6-95c3-0bf5283fa5ed]
Failed to precompile OrdinaryDiffEq [1dea7af3-3e70-54e6-95c3-0bf5283fa5ed] to /home/severin/.julia/compiled/v1.8/OrdinaryDiffEq/jl_1F51NA.
ERROR: LoadError: MethodError: convert(::Type{Union{}}, ::SparseArrays.SparseMatrixCSC{Float64, Int64}) is ambiguous. Candidates:
convert(T::Type{<:LinearAlgebra.LowerTriangular}, m::SparseArrays.AbstractSparseMatrixCSC) in SparseArrays at /usr/share/julia/stdlib/v1.8/SparseArrays/src/sparsematrix.jl:753
convert(T::Type{<:SparseArrays.SparseVector}, m::SparseArrays.AbstractSparseMatrixCSC) in SparseArrays at /usr/share/julia/stdlib/v1.8/SparseArrays/src/sparsevector.jl:466
convert(T::Type{<:LinearAlgebra.SymTridiagonal}, m::SparseArrays.AbstractSparseMatrixCSC) in SparseArrays at /usr/share/julia/stdlib/v1.8/SparseArrays/src/sparsematrix.jl:749
convert(T::Type{<:LinearAlgebra.Bidiagonal}, m::AbstractMatrix) in LinearAlgebra at /usr/share/julia/stdlib/v1.8/LinearAlgebra/src/bidiag.jl:203
convert(T::Type{<:LinearAlgebra.Tridiagonal}, m::SparseArrays.AbstractSparseMatrixCSC) in SparseArrays at /usr/share/julia/stdlib/v1.8/SparseArrays/src/sparsematrix.jl:751
convert(T::Type{<:SparseArrays.AbstractSparseMatrixCSC}, m::AbstractMatrix) in SparseArrays at /usr/share/julia/stdlib/v1.8/SparseArrays/src/sparsematrix.jl:745
convert(T::Type{<:LinearAlgebra.UpperTriangular}, m::SparseArrays.AbstractSparseMatrixCSC) in SparseArrays at /usr/share/julia/stdlib/v1.8/SparseArrays/src/sparsematrix.jl:755
convert(T::Type{<:LinearAlgebra.Diagonal}, m::SparseArrays.AbstractSparseMatrixCSC) in SparseArrays at /usr/share/julia/stdlib/v1.8/SparseArrays/src/sparsematrix.jl:747
convert(::Type{Union{}}, a::AbstractArray) in Base at array.jl:618
convert(T::Type{<:BitArray}, a::AbstractArray) in Base at bitarray.jl:580
convert(::Type{T}, M::AbstractArray) where T<:OffsetArrays.OffsetArray in OffsetArrays at /home/severin/.julia/packages/OffsetArrays/TcCEq/src/OffsetArrays.jl:256
convert(::Type{T}, a::AbstractArray) where T<:Array in Base at array.jl:617
convert(::Type{SA}, a::AbstractArray) where SA<:StaticArraysCore.StaticArray in StaticArrays at /home/severin/.julia/packages/StaticArrays/jA1zK/src/convert.jl:194
convert(::Type{Union{}}, x) in Base at essentials.jl:213
convert(::Type{T}, obj) where T<:FunctionWrappers.FunctionWrapper in FunctionWrappers at /home/severin/.julia/packages/FunctionWrappers/Q5cBx/src/FunctionWrappers.jl:113
convert(::Type{T}, arg) where T<:VecElement in Base at baseext.jl:19
Possible fix, define
convert(::Type{Union{}}, ::SparseArrays.AbstractSparseMatrixCSC)
Stacktrace:
[1] Sparspak.SpkSparseSolver.SparseSolver{Int64, Float64}(p::SparseArrays.SparseMatrixCSC{Float64, Int64}, slvr::Sparspak.SpkSparseBase._SparseBase{Int64, Float64}, n::Int64, ma::Int64, na::Int64, mc::Int64, nc::Int64, _inmatrixdone::Bool, _orderdone::Bool, _symbolicdone::Bool, _factordone::Bool, _trisolvedone::Bool, _refinedone::Bool, _condestdone::Bool) (repeats 2 times)
@ Sparspak.SpkSparseSolver ~/.julia/packages/Sparspak/ZSfSg/src/SparseMethod/SpkSparseSolver.jl:18
[2] Sparspak.SpkSparseSolver.SparseSolver(m::SparseArrays.SparseMatrixCSC{Float64, Int64})
@ Sparspak.SparseCSCInterface ~/.julia/packages/Sparspak/ZSfSg/src/SparseCSCInterface/SparseCSCInterface.jl:189
[3] sparspaklu(m::SparseArrays.SparseMatrixCSC{Float64, Int64}; factorize::Bool)
@ Sparspak.SparseCSCInterface ~/.julia/packages/Sparspak/ZSfSg/src/SparseCSCInterface/SparseCSCInterface.jl:219
[4] init_cacheval(#unused#::LinearSolve.SparspakFactorization, A::SparseArrays.SparseMatrixCSC{Float64, Int64}, b::Vector{Float64}, u::Vector{Float64}, Pl::IterativeSolvers.Identity, Pr::IterativeSolvers.Identity, maxiters::Int64, abstol::Float64, reltol::Float64, verbose::Bool, assumptions::LinearSolve.OperatorAssumptions{Nothing})
@ LinearSolve ~/.julia/packages/LinearSolve/dxfUd/src/factorization.jl:514
[5] init(::SciMLBase.LinearProblem{Nothing, true, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, SciMLBase.NullParameters, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::LinearSolve.SparspakFactorization; alias_A::Bool, alias_b::Bool, abstol::Float64, reltol::Float64, maxiters::Int64, verbose::Bool, Pl::IterativeSolvers.Identity, Pr::IterativeSolvers.Identity, assumptions::LinearSolve.OperatorAssumptions{Nothing}, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ LinearSolve ~/.julia/packages/LinearSolve/dxfUd/src/common.jl:117
[6] init(::SciMLBase.LinearProblem{Nothing, true, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, SciMLBase.NullParameters, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::LinearSolve.SparspakFactorization)
@ LinearSolve ~/.julia/packages/LinearSolve/dxfUd/src/common.jl:88
[7] solve(::SciMLBase.LinearProblem{Nothing, true, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, SciMLBase.NullParameters, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::LinearSolve.SparspakFactorization; kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
@ LinearSolve ~/.julia/packages/LinearSolve/dxfUd/src/common.jl:157
[8] solve(::SciMLBase.LinearProblem{Nothing, true, SparseArrays.SparseMatrixCSC{Float64, Int64}, Vector{Float64}, SciMLBase.NullParameters, Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::LinearSolve.SparspakFactorization)
@ LinearSolve ~/.julia/packages/LinearSolve/dxfUd/src/common.jl:154
[9] macro expansion
@ ~/.julia/packages/LinearSolve/dxfUd/src/LinearSolve.jl:92 [inlined]
[10] top-level scope
@ ~/.julia/packages/SnoopPrecompile/1XXT1/src/SnoopPrecompile.jl:62
[11] top-level scope
@ stdin:1
in expression starting at /home/severin/.julia/packages/LinearSolve/dxfUd/src/LinearSolve.jl:1
in expression starting at stdin:1
ERROR: LoadError: Failed to precompile LinearSolve [7ed4a6bd-45f5-4d41-b270-4a48e9bafcae] to /home/severin/.julia/compiled/v1.8/LinearSolve/jl_bHyaCx.
Stacktrace:
[1] top-level scope
@ stdin:1
in expression starting at /home/severin/.julia/packages/OrdinaryDiffEq/pIBDs/src/OrdinaryDiffEq.jl:1
in expression starting at stdin:1
Stacktrace:
[1] top-level scope
@ REPL[7]:1
julia>
I somehow suspect the (communication with the) suite sparse manjaro package, because this package was just updated today, and installation of OrdinaryDiffEq was impossible at all before the update. On the other hand, the error message suggests an error in some julia code to me…
I would appreciate if someone could help me. I don’t know it this is helpful, but the output of versioninfo() is
julia> versioninfo()
Julia Version 1.8.5
Commit 17cfb8e65e* (2023-01-08 06:45 UTC)
Platform Info:
OS: Linux (x86_64-pc-linux-gnu)
CPU: 12 × Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-14.0.6 (ORCJIT, skylake)
Threads: 1 on 12 virtual cores
Environment:
LD_LIBRARY_PATH = /usr/lib/julia
julia>
Thank you!
Cheers
Severin