# Adding saveat to DifferentialEquations.jl solve causes conversion error when using custom variable type
**URL:** https://discourse.julialang.org/t/adding-saveat-to-differentialequations-jl-solve-causes-conversion-error-when-using-custom-variable-type/66275
**Category:** General Usage
**Tags:** diffeq, error-message
**Created:** [August 12, 2021, 2:42pm UTC](https://discourse.julialang.org/t/adding-saveat-to-differentialequations-jl-solve-causes-conversion-error-when-using-custom-variable-type/66275 "2021-08-12T14:42:01Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@SMijin](https://discourse.julialang.org/u/SMijin)
#### Post date: [August 12, 2021, 2:42pm UTC](https://discourse.julialang.org/t/adding-saveat-to-differentialequations-jl-solve-causes-conversion-error-when-using-custom-variable-type/66275/1 "2021-08-12T14:42:01Z")
I’ve got a simple struct that looks something like this:
```julia
mutable struct variable{T,N} <: AbstractArray{T,N}
values :: Array{T,N}
spaceIDs :: Vector{Int}
end
```
I’ve defined `Base.:+`, as well as `Base.:*` and `Base:./`(with scalar), as well as the basic `AbstractArray` interface functions. I define an ODEProblem with an in-place function (that does nothing) and pass it to solve. It works great (even when the passed problem actually does something to the variables) if I don’t include the saveat option. However `soln = solve(prob,saveat=0.1);` throws a conversion error with the start of the stacktrace:
```julia
Stacktrace:
[1] push!(a::Vector{AMPS.vars.variable{Float64, 2}}, item::Matrix{Float64})
@ Base ./array.jl:928
[2] copyat_or_push!(a::Vector{AMPS.vars.variable{Float64, 2}}, i::Int64, x::Matrix{Float64}, nc::Type{Val{false}})
@ RecursiveArrayTools ~/.julia/packages/RecursiveArrayTools/e9IdM/src/utils.jl:79
[3] _savevalues!(integrator::OrdinaryDiffEq.ODEIntegrator{OrdinaryDiffEq.Tsit5, true, AMPS.vars.variable{Float64, 2}, Nothing, Float64, SciMLBase.NullParameters, Float64, Float64, Float64, Float64, Vector{AMPS.vars.variable{Float64, 2}}, SciMLBase.ODESolution{Float64, 3, Vector{AMPS.vars.variable{Float64, 2}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{AMPS.vars.variable{Float64, 2}}}, SciMLBase.ODEProblem{AMPS.vars.variable{Float64, 2}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, SciMLBase.ODEFunction{true, Main.finitediff.var"#test2D#2", LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, OrdinaryDiffEq.Tsit5, OrdinaryDiffEq.InterpolationData{SciMLBase.ODEFunction{true, Main.finitediff.var"#test2D#2", LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{AMPS.vars.variable{Float64, 2}}, Vector{Float64}, Vector{Vector{AMPS.vars.variable{Float64, 2}}}, OrdinaryDiffEq.Tsit5Cache{AMPS.vars.variable{Float64, 2}, AMPS.vars.variable{Float64, 2}, AMPS.vars.variable{Float64, 2}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}}}, DiffEqBase.DEStats}, SciMLBase.ODEFunction{true, Main.finitediff.var"#test2D#2", LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, OrdinaryDiffEq.Tsit5Cache{AMPS.vars.variable{Float64, 2}, AMPS.vars.variable{Float64, 2}, AMPS.vars.variable{Float64, 2}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}}, OrdinaryDiffEq.DEOptions{Float64, Float64, Float64, Float64, OrdinaryDiffEq.PIController{Rational{Int64}}, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, DiffEqBase.CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryMinHeap{Float64}, DataStructures.BinaryMinHeap{Float64}, Nothing, Nothing, Int64, Tuple{}, Float64, Tuple{}}, AMPS.vars.variable{Float64, 2}, Float64, Nothing, OrdinaryDiffEq.DefaultInit}, force_save::Bool, reduce_size::Bool)
@ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/AgIKX/src/integrators/integrator_utils.jl:64
```
Looks like it tries to push! a matrix instead of my defined struct. Anyone have an idea why this might be happening? I guess that the solver at some point interprets my array type as a standard matrix, but why would this happen only when I specify saveat?
---
### Author:  [@SMijin](https://discourse.julialang.org/u/SMijin)
#### Post date: [August 12, 2021, 3:07pm UTC](https://discourse.julialang.org/t/adding-saveat-to-differentialequations-jl-solve-causes-conversion-error-when-using-custom-variable-type/66275/2 "2021-08-12T15:07:45Z")
Adding MWE:
```julia
using Lazy, DifferentialEquations
mutable struct variable{T,N} <: AbstractArray{T,N}
values :: Array{T,N}
spaceIDs :: Vector{Int}
end
@forward variable.values (Base.size, Base.getindex, Base.setindex!, Base.length)
Base.similar(v::variable) = variable(similar(v.values),v.spaceIDs)
Base.similar(v::variable,::Type{T}) where{T} = variable(similar(v.values,T),v.spaceIDs)
function Base.:+(x::variable{T,N},y::variable{T,N}) where {T,N}
all(x.spaceIDs == y.spaceIDs) ? variable(x.values+y.values,x.spaceIDs) : error("Attempted to add variables defined on different spaces")
end
Base.:*(x::Number,y::variable) = variable(x*y.values,y.spaceIDs)
Base.:*(x::variable,y::Number) = variable(y*x.values,x.spaceIDs)
Base.:/(x::variable,y::Number) = variable(x.values/y,x.spaceIDs)
u0mat = zeros(100,100)
u0 = variable(u0mat,[1,2])
du = variable(u0mat,[1,2])
function test(du,u,p,t) end
prob = ODEProblem(test, u0, (0.,5.));
soln = solve(prob,saveat=0.1);
```
---
### Author:  [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)
#### Post date: [August 12, 2021, 3:22pm UTC](https://discourse.julialang.org/t/adding-saveat-to-differentialequations-jl-solve-causes-conversion-error-when-using-custom-variable-type/66275/3 "2021-08-12T15:22:29Z")
Broadcast definitions are probably missing. [https://github.com/SciML/DEDataArrays.jl](https://github.com/SciML/DEDataArrays.jl) probably would help.
---
### Author:  [@SMijin](https://discourse.julialang.org/u/SMijin)
#### Post date: [August 12, 2021, 3:43pm UTC](https://discourse.julialang.org/t/adding-saveat-to-differentialequations-jl-solve-causes-conversion-error-when-using-custom-variable-type/66275/4 "2021-08-12T15:43:27Z")
It was the broadcast definitions, thanks! Added the first two from here [https://docs.julialang.org/en/v1/manual/interfaces/#man-interfaces-broadcasting](https://docs.julialang.org/en/v1/manual/interfaces/#man-interfaces-broadcasting) and it no longer breaks when using saveat.