Hi there!! to be clear about fractionaldiffeq.jl

[beloved321]

How do i do so
julia> using Pkg
julia> Pkg.update("FractionalDiffEq")???

[beloved321]

to be clear, it is a pkg, cos i have tried exactly that an i get an error

[ErikQQY]

Sorry, I can't get what you mean.

Can you describe your usage, and post your code and the error message here, that would be nice to explore the bugs😃

[beloved321]

julia> using FractionalDiffEq, Plots (process:9076): GLib-GIO-WARNING **: 14:30:09 <https://www.youtube.com/watch?v=ti16lYst-Bc&t=43200s>.828: Unexpectedly, UWP app `6760NGPDFLab.PDFX_1.3.15.0_x64__sbe4t8mqwq93a' (AUMId `6760NGPDFLab.PDFX_sbe4t8mqwq93a!App') supports 32 extensions but has no verbs julia> function chua!(du, x, p, t) a = 10.725; b = 10.593; c = 0.268; m0 = -1.1726; m1 = -0.7872; du[1] = a*(x[2]-x[1]-(m1*x[1]+0.5*(m0-m1)*(abs(x[1]+1)-abs(x[1]-1)))) du[2] = u[1]-u[2]+u[3] du[3] = -b*u[2]-c*u[3] end chua! (generic function with 1 method) julia> α = [0.93, 0.99, 0.92]; julia> x0 = [0.2; -0.1; 0.1]; julia> h = 0.001 0.001 julia> prob = FODESystem(chua!, α, x0) FODESystem(chua!, [0.93, 0.99, 0.92], [0.2, -0.1, 0.1]) julia> tn = 200; julia> result = solve(prob, h, tn, NonLinearAlg()) ERROR: MethodError: no method matching chua!(::Float64, ::Vector{Float64}, ::Int64) Closest candidates are: chua!(::Any, ::Any, ::Any, ::Any) at REPL[2]:1 Stacktrace: [1] macro expansion @ C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\NonLinear\NonLinear.jl:38 [inlined] [2] macro expansion @ .\simdloop.jl:77 [inlined] [3] macro expansion @ C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\NonLinear\NonLinear.jl:37 [inlined] [4] macro expansion @ .\simdloop.jl:77 [inlined] [5] solve(prob::FODESystem, h::Float64, tn::Int64, ::NonLinearAlg, L0::Float64) @ FractionalDiffEq C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\NonLinear\NonLinear.jl:34 [6] solve(prob::FODESystem, h::Float64, tn::Int64, ::NonLinearAlg) @ FractionalDiffEq C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\NonLinear\NonLinear.jl:15 [7] top-level scope @ REPL[8]:1 I want to understand where I missed it

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On Tue, Jun 7, 2022 at 3:45 PM Qingyu Qu ***@***.***> wrote: Sorry, I can't get what you mean. Can you describe your usage, and post your code and the error message here, that would be nice to explore the bugs😃 — Reply to this email directly, view it on GitHub <#36 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AZQI4XUNOWYSB6KQDEFHNZ3VN5N65ANCNFSM5YC36QLQ> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[ErikQQY]

May I ask for the version of FractionalDiffEq.jl?

You can get this by:

julia>]
pkg>st FractionalDiffEq

[beloved321]

pkg> st FractionalDiffEq
Status C:\Users\BELOVED\.julia\environments\v1.7\Project.toml
[c7492dd8] FractionalDiffEq v0.2.0

[ErikQQY]

Oops, I think that is a very old version, please update FractionalDiffEq.jl to the latest version:

julia> using Pkg
julia> Pkg.update("FractionalDiffEq")

Then the Chua system example in README would be working: https://github.com/SciFracX/FractionalDiffEq.jl#system-of-fractional-differential-equations

[beloved321]

julia> using FractionalDiffEq, Plots (process:8496): GLib-GIO-WARNING **: 16:38:52.722: Unexpectedly, UWP app `6760NGPDFLab.PDFX_1.3.15.0_x64__sbe4t8mqwq93a' (AUMId `6760NGPDFLab.PDFX_sbe4t8mqwq93a!App') supports 32 extensions but has no verbs julia> function chua!(du, x, p, t) a = 10.723; b = 10.593; c = 0.268 m0 = -1.1726 m1 = -0.7872 du[1] = a*(x[2]-x[1]-(m1*x[1]+0.5*(m0-m1)*(abs(x[1]+1)-abs(x[1]-1)))) du[2] = x[1]-x[2]+x[3] du[3] = -b*x[2]-c*x[3] end chua! (generic function with 1 method) julia> α = [0.93, 0.99, 0.92]; julia> x0 = [0.2; -0.1; 0.1]; julia> h = 0.01; tspan = (0, 100); julia> prob = FODESystem(chua!, α, x0, tspan) ERROR: MethodError: no method matching FODESystem(::typeof(chua!), ::Vector{Float64}, ::Vector{Float64}, ::Tuple{Int64, Int64}) Closest candidates are: FODESystem(::Function, ::AbstractArray, ::AbstractArray) at C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\PECE.jl:112 FODESystem(::Any, ::Any, ::Any) at C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\PECE.jl:112 Stacktrace: [1] top-level scope @ REPL[9]:1 julia> prob = FODESystem(chua!, α, x0) FODESystem(chua!, [0.93, 0.99, 0.92], [0.2, -0.1, 0.1]) julia> result = solve(prob, h, tspan, NonLinearAlg()) ERROR: MethodError: no method matching /(::Tuple{Int64, Int64}, ::Float64) Closest candidates are: /(::Any, ::ChainRulesCore.AbstractThunk) at C:\Users\BELOVED\.julia\packages\ChainRulesCore\GUvJT\src\tangent_types\thunks.jl:33 /(::StridedArray{P}, ::Real) where P<:Dates.Period at C:\Users\BELOVED\AppData\Local\Programs\Julia-1.7.3\share\julia\stdlib\v1.7\Dates\src\deprecated.jl:44 /(::Union{SparseArrays.SparseVector{Tv, Ti}, SubArray{Tv, 1, <:SparseArrays.AbstractSparseVector{Tv, Ti}, Tuple{Base.Slice{Base.OneTo{Int64}}}, false}, SubArray{Tv, 1, <:SparseArrays.AbstractSparseMatrixCSC{Tv, Ti}, Tuple{Base.Slice{Base.OneTo{Int64}}, Int64}, false}} where {Tv, Ti}, ::Number) at C:\Users\BELOVED\AppData\Local\Programs\Julia-1.7.3\share\julia\stdlib\v1.7\SparseArrays\src\sparsevector.jl:1476 ... Stacktrace: [1] solve(prob::FODESystem, h::Float64, tn::Tuple{Int64, Int64}, ::NonLinearAlg, L0::Float64) @ FractionalDiffEq C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\NonLinear\NonLinear.jl:17 [2] solve(prob::FODESystem, h::Float64, tn::Tuple{Int64, Int64}, ::NonLinearAlg) @ FractionalDiffEq C:\Users\BELOVED\.julia\packages\FractionalDiffEq\uk4Ug\src\NonLinear\NonLinear.jl:15 [3] top-level scope @ REPL[11]:1 I guess I am still missing something even after the update. I am very grateful for your responses. I will be grateful if you still take a look at it

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On Tue, Jun 7, 2022 at 4:03 PM Qingyu Qu ***@***.***> wrote: Oops, I think that is a very old version, please update FractionalDiffEq.jl to the latest version: julia> using Pkg julia> Pkg.update("FractionalDiffEq") Then the Chua system example in README would be working: https://github.com/SciFracX/FractionalDiffEq.jl#system-of-fractional-differential-equations — Reply to this email directly, view it on GitHub <#36 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AZQI4XT65NGYMSYIRZR6C6DVN5QCZANCNFSM5YC36QLQ> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[ErikQQY]

Very sorry for the inconvenience, I think the latest version 0.2.6 should work, there are a lot of changes compared to the old versions.

[beloved321]

Julia or FractionalDiffEq

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On Tue, Jun 7, 2022, 5:16 PM Qingyu Qu ***@***.***> wrote: Very sorry for the inconvenience, I think the latest version 0.2.6 should work, there are a lot of changes compared to the old versions. — Reply to this email directly, view it on GitHub <#36 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AZQI4XWQMB2MVZDL45SB3GTVN5YV5ANCNFSM5YC36QLQ> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[ErikQQY]

I think you are using FractionalDiffEq.jl 0.2.5, that is a very old version( I have not released for a long time, my apologies🥲), I think updating to 0.2.6 would solve all of the problems.😃

[ErikQQY]

Yes, update FractionalDiffEq.jl to version 0.2.6, there should be no problems.😄

[beloved321]

Yea, Thanks a lot. so this is what I did, I download the v1.8.0 of julia and it worked perfectly. Now I will try to build a fractional order lorenz system. I want to do so in the caputo sense, I believe there is provision for it.
I am so grateful for your responses all the while.

[ErikQQY]

It is great to see that FractionalDiffEq.jl is helping! So I will close this issue for now. If you have any other questions about this package, don't hesitate to ping me.😄