Auto-convert Vector{Type} to special container type

General Usage
, ,
1

I’m trying to use this unofficial CasADi interface in Julia since the official interface seems to be a long way from working (couldn’t get it installed in Julia 1.10, as stated in Project.toml). I’m having a hard time handling the fact that CasADi’s main number type, SX, is supposed to behave both as a scalar and as an array, since this leads to vector expressions mixing Array{SX} and SX. As an example, the following code errors:

using CasADi
v = SX("v", 2)
[v[2]; v[1]] + v

because it actually tries to add a Vector{SX} to a SX, thought to be a scalar (since SX <: Real):

ERROR: MethodError: no method matching +(::Vector{SX}, ::SX)
For element-wise addition, use broadcasting with dot syntax: array .+ scalar
The function + exists, but no method is defined for this combination of argument types.

Closest candidates are:
+(::Any, ::Any, ::Any, ::Any…)
@ Base operators.jl:642
+(::PyCall.PyObject, ::Any)
@ PyCall ~/.julia/packages/PyCall/1gn3u/src/pyoperators.jl:13
+(::Complex{Bool}, ::Real)
@ Base complex.jl:323
…

Stacktrace:
[1] top-level scope
@ REPL

So I wonder:

  • can I hijack the Array{SX} constructor to always return an SX?
  • how can I make this work with expressions like scalar_sx * I(3), where the result is a Diagonal <: AbstractMatrix?
  • can I use promote_rule for this?
  • how could I overload the array building operator [...] to make it return an SX instead of an Array?

Currently, I’m handling this through a converter function inserted manually as-needed in my code:

convertSX(x::AbstractArray{SX}) = SX(x)
convertSX(x::AbstractArray) = x

but this is cumbersome, unreliable, and I’m sure there’s a better way of doing this.