LoadError: MethodError: no method matching _sparse(::SymbolicUtils.BasicSymbolic{Any}, ::Int64)

[tmigot]

I tried the following code:

using Symbolics, IfElse

f(x) = Base.ifelse( # IfElse.ifelse doesn't work either
    x[1] <= 0,
    -x[1],
    x[1],
)
x0 = ones(1)
nvar = 1

@variables xs[1:nvar]
xsi = Symbolics.scalarize(xs)
fun = f(xsi)
S = Symbolics.hessian_sparsity(fun, xsi)

and got the following error

ERROR: LoadError: MethodError: no method matching _sparse(::SymbolicUtils.BasicSymbolic{Any}, ::Int64)
Closest candidates are:
  _sparse(::Number, ::Any) at .julia\packages\Symbolics\gy00O\src\linearity.jl:170
  _sparse(::Symbolics.TermCombination, ::Any) at .julia\packages\Symbolics\gy00O\src\linearity.jl:147
Stacktrace:
 [1] hessian_sparsity(expr::Num, vars::Vector{Num}; full::Bool)
   @ Symbolics .julia\packages\Symbolics\gy00O\src\diff.jl:679
 [2] hessian_sparsity(expr::Num, vars::Vector{Num})
   @ Symbolics .julia\packages\Symbolics\gy00O\src\diff.jl:671

It might be related to #888 .

[aravindh-krishnamoorthy]

Sorry, but it's unclear to me what are you trying to achieve here? Isn't ifelse(x <= 0, -x, x) just abs(x), which is non-differentiable?

[tmigot]

@aravindh-krishnamoorthy you are right, let me reformulate the example. The error is the same if the function is differentiable as follows:

using Symbolics

f(x) = Base.ifelse(
    x[1] <= 0,
    -x[1]^2,
    x[1]^2,
)
x0 = ones(1)
nvar = 1

@variables xs[1:nvar]
xsi = Symbolics.scalarize(xs)
fun = f(xsi)
S = Symbolics.hessian_sparsity(fun, xsi)

[ChrisRackauckas]

@shashi do you know what's going on in this one?