fix: use AbstractVector in jacobian type assertions

[ChrisRackauckas-Claude]

Summary

• Fix TypeError when calling jacobian with non-Vector inputs like SVector
• Change Vector to AbstractVector in type checks and assertions in the jacobian function

Problem

The jacobian function at src/diff.jl:649-656 used Vector in type assertions:

if ops isa Vector{Num}
    ops = unwrap.(ops)::Vector{SymbolicT}

However, vec(scalarize(ops)) can return other AbstractVector subtypes (e.g., SVector), causing a TypeError: in typeassert, expected Vector{Num}, got a value of type SVector{2, Num}.

Solution

Replace Vector with AbstractVector in all type checks and assertions within the function to properly support all AbstractVector subtypes.

Test

using Symbolics
using StaticArrays

@variables x y
ops = SVector(x^2 + y, x*y)
vars = SVector(x, y)

J = Symbolics.jacobian(ops, vars)
# Now works correctly, returning:
# 2×2 Matrix{Num}:
#  2x  1
#   y  x

Fixes #1691

🤖 Generated with Claude Code

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@@             Coverage Diff             @@
##           master    #1697       +/-   ##
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- Coverage   79.80%   21.94%   -57.86%     
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- Misses       1042     3994     +2952     

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[ChrisRackauckas]

@AayushSabharwal why are there so many type assertions in the first place?

[AayushSabharwal]

Type stability, it helps with the benchmarks quite a bit.

[ChrisRackauckas]

Because unwrap can return numbers?

[AayushSabharwal]

Because scalarize doesn't infer, so vec(scalarize(..)) infers to Any, which means everything after that doesn't infer at all.

[ChrisRackauckas]

Why wouldn't scalarize infer?

[AayushSabharwal]

Given just BasicSymbolic there's nothing in the type which can tell the compiler whether scalarize returns a scalar or an array.

[ChrisRackauckas]

Seems like it could be useful if scalarizing gave length 1 vectors?

[AayushSabharwal]

Not really. collect uses scalarize under the hood and we want symbolic matrices to collect to matrices. I also can't imagine the amount of code that breaks from doing this 😅

[AayushSabharwal]

I can (probably) turn scalarize into a different function called stable_scalarize which does what you suggest, and have scalarize just reshape the result. It might also help MTK. The function itself will have lots of dynamic dispatch because we need to call Term.f, but that's nothing new and unavoidable.

[ChrisRackauckas]

Yeah because if this needs to asset Vector for type-stability, then it can't be abstracted. So it might need that utility at least for the differentiation functions.

[schillic]

Any news here? If it takes longer to resolve, a quick fix could be to add a fallback method without the type assertions (and add the Vector type requirement to the signature for the current method).

[schillic]

@ChrisRackauckas @AayushSabharwal if I prepared the fix proposed in my previous comment, would you accept it?

[AayushSabharwal]

Yeah, that works. Thanks!

[schillic]

I tried my proposed fix, but that leads to a method ambiguity and I do not know enough how this library works to resolve it.