Remove Symbolics sparsity detector (#295)

Author: gdalle

DifferentiationInterface/docs/make.jl

@@ -23,6 +23,7 @@ links = InterLinks(
     "ADTypes" => "https://sciml.github.io/ADTypes.jl/stable/",
     "SparseConnectivityTracer" => "https://adrianhill.de/SparseConnectivityTracer.jl/stable/",
     "SparseMatrixColorings" => "https://gdalle.github.io/SparseMatrixColorings.jl/stable/",
+    "Symbolics" => "https://symbolics.juliasymbolics.org/stable/",
 )
 
 cp(joinpath(@__DIR__, "..", "README.md"), joinpath(@__DIR__, "src", "index.md"); force=true)

DifferentiationInterface/docs/src/operators.md

@@ -160,8 +160,11 @@ When computing sparse Jacobians or Hessians, it is possible to take advantage of
 For this to work, three ingredients are needed (read [this survey](https://epubs.siam.org/doi/10.1137/S0036144504444711) to understand why):
 
 1. An underlying (dense) backend
-2. A sparsity pattern detector like [`TracerSparsityDetector`](@extref SparseConnectivityTracer.TracerSparsityDetector) from [SparseConnectivityTracer.jl](https://github.com/adrhill/SparseConnectivityTracer.jl)
-3. A coloring algorithm like [`GreedyColoringAlgorithm`](@extref SparseMatrixColorings.GreedyColoringAlgorithm) from [SparseMatrixColorings.jl](https://github.com/gdalle/SparseMatrixColorings.jl)
+2. A sparsity pattern detector like:
+   - [`TracerSparsityDetector`](@extref SparseConnectivityTracer.TracerSparsityDetector) from [SparseConnectivityTracer.jl](https://github.com/adrhill/SparseConnectivityTracer.jl)
+   - [`SymbolicsSparsityDetector`](https://symbolics.juliasymbolics.org/dev/manual/sparsity_detection/) from [Symbolics.jl](https://github.com/JuliaSymbolics/Symbolics.jl)
+3. A coloring algorithm like:
+   - [`GreedyColoringAlgorithm`](@extref SparseMatrixColorings.GreedyColoringAlgorithm) from [SparseMatrixColorings.jl](https://github.com/gdalle/SparseMatrixColorings.jl)
 
 These ingredients can be combined within the [`AutoSparse`](@extref ADTypes.AutoSparse) wrapper, which DifferentiationInterface.jl re-exports.
 Note that for sparse Hessians, you need to put the `SecondOrder` backend inside `AutoSparse`, and not the other way around.

DifferentiationInterface/ext/DifferentiationInterfaceSymbolicsExt/DifferentiationInterfaceSymbolicsExt.jl

@@ -38,6 +38,5 @@ myvec(x::AbstractArray) = vec(x)
 
 include("onearg.jl")
 include("twoarg.jl")
-include("detector.jl")
 
 end