SparsityDetection.jl
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SciML
Automatic detection of sparsity in pure Julia functions for sparsity-enabled scientific machine learning (SciML)
I am getting a `MethodError: no method matching setindex!(::Cassette.NoMetaMeta, ::Cassette.Meta{Cassette.NoMetaData,Cassette.NoMetaMeta}, ::Int64)` when I run the code snippet below. As pointed out at [17] in the [stacktrace](https://gist.github.com/ferrolho/46e7164fc4bad1c6e033c6ce1f0ea827), [this is the line](https://github.com/JuliaRobotics/RigidBodyDynamics.jl/blob/fdb9e5ab12f0435318e87ee81d5f0a9edc08c762/src/mechanism_algorithms.jl#L762)...
```julia using OrdinaryDiffEq, LinearAlgebra, SparseArrays, SparsityDetection # Define the constants for the PDE const α₂ = 1.0 const α₃ = 1.0 const β₁ = 1.0 const β₂ = 1.0 const...
The following code (MWE) results in `LoadError: MethodError: objects of type TypeVar are not callable` Both Win10 and Mac, Julia 1.4.2, freshly updated all packages (SparsityDetection 0.3.2, DiffEqOperators 4.10.0) ```...
I am trying to call `jacobian_sparsity` with a function that solves an `ODEProblem`, but it crashes with the error `ERROR: MethodError: no method matching metadatatype(::Type{Cassette.Context{nametype(JacobianSparsityContext),Tuple{Sparsity,SparsityDetection.Path},Cassette.Tag{nametype(JacobianSparsityContext),0x5a4345c7a7af0026,Nothing},SparsityDetection.var"##PassType#253",IdDict{Module,Dict{Symbol,Cassette.BindingMeta}},Cassette.DisableHooks}}, ::Type{Type})`. Minimal working example: ```julia...
Cassette prints these errors when adding too many variables. But the end result is still correct. When adding fewer numbers, say 4, I get no errors. ```jl using SparsityDetection function...
I am trying to use this package with Turing.jl and I ran into the following error: ```julia ERROR: MethodError: no method matching metadatatype(::Type{Cassette.Context{nametype(JacobianSparsityContext),Tuple{Sparsity,SparsityDetection.Path},Cassette.Tag{nametype(JacobianSparsityContext),0xcf4d328d8191b6e5,Nothing},SparsityDetection.var"##PassType#253",IdDict{Module,Dict{Symbol,Cassette.BindingMeta}},Cassette.DisableHooks}}, ::Type{Type}) Closest candidates are: metadatatype(::Type{#s16} where #s16
In various sparsity packages y and dx are used interchangeably in documentation and API. Also sometimes capitalized Y, X.
```julia using SparsityDetection function f(du, u, p, t) Q = reinterpret(Complex{Float64}, u) dQ = reinterpret(Complex{Float64}, du) dQ .= Q end input = rand(Float64, 4) output = similar(input) sparsity_pattern = sparsity!((dx,...
The following code yields the identity, as it should ``` function f1(dx, x) for i in 1:length(x) dx[i] = x[i]^2 end end input = rand(10) output = similar(input) sparsity_pattern1 =...
JuliaInterpreter could speed up this package in theory. We usually need to run it once, and the compilation is garbage anyway. A simple problem such as ```julia julia> @interpret sparsity!((y,x)->y[1:2]...
