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SplitFunction W_prototype fixes #820

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Merged
merged 3 commits into from
Oct 19, 2024
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SplitFunction W_prototype fixes #820

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d4563e0
SplitFunction W_prototype fixes
Oct 18, 2024
3d99bb9
typo
Oct 18, 2024
480c1d8
Update src/scimlfunctions.jl
ChrisRackauckas Oct 19, 2024
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10 changes: 8 additions & 2 deletions src/scimlfunctions.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -455,6 +455,7 @@ SplitFunction{iip,specialize}(f1,f2;
jvp = __has_jvp(f1) ? f1.jvp : nothing,
vjp = __has_vjp(f1) ? f1.vjp : nothing,
jac_prototype = __has_jac_prototype(f1) ? f1.jac_prototype : nothing,
W_prototype = __has_W_prototype(f1) ? f1.W_prototype : nothing,
sparsity = __has_sparsity(f1) ? f1.sparsity : jac_prototype,
paramjac = __has_paramjac(f1) ? f1.paramjac : nothing,
colorvec = __has_colorvec(f1) ? f1.colorvec : nothing,
Expand Down Expand Up @@ -484,6 +485,11 @@ the usage of the `SplitFunction`. These include:
as the prototype and integrators will specialize on this structure where possible. Non-structured
sparsity patterns should use a `SparseMatrixCSC` with a correct sparsity pattern for the Jacobian.
The default is `nothing`, which means a dense Jacobian.
- `W_prototype`: a prototype matrix matching the type that matches the W matrix. For example,
if the Jacobian is tridiagonal, and the mass_matrix is diagonal, then an appropriately sized `Tridiagonal`
matrix can be used as the prototype and integrators will specialize on this structure where possible. Non-structured
sparsity patterns should use a `SparseMatrixCSC` with a correct sparsity pattern for the W matrix.
The default is `nothing`, which means a W of appropriate type for the jacobian and linear solver
- `paramjac(pJ,u,p,t)`: returns the parameter Jacobian ``\frac{df_1}{dp}``.
- `colorvec`: a color vector according to the SparseDiffTools.jl definition for the sparsity
pattern of the `jac_prototype`. This specializes the Jacobian construction when using
Expand Down Expand Up @@ -3080,7 +3086,7 @@ SDEFunction(f::SDEFunction; kwargs...) = f

@add_kwonly function SplitSDEFunction(f1, f2, g, mass_matrix, cache, analytic, tgrad, jac,
jvp, vjp,
jac_prototype, Wfact, Wfact_t, paramjac, observed,
jac_prototype, W_prototype, Wfact, Wfact_t, paramjac, observed,
colorvec, sys)
f1 = f1 isa AbstractSciMLOperator ? f1 : SDEFunction(f1)
f2 = SDEFunction(f2)
Expand All @@ -3091,7 +3097,7 @@ SDEFunction(f::SDEFunction; kwargs...) = f
typeof(Wfact), typeof(Wfact_t), typeof(paramjac), typeof(observed),
typeof(colorvec),
typeof(sys)}(f1, f2, mass_matrix, cache, analytic, tgrad, jac,
jac_prototype, Wfact, Wfact_t, paramjac, observed, colorvec, sys)
jac_prototype, W_prototype, Wfact, Wfact_t, paramjac, observed, colorvec, sys)
end

function SplitSDEFunction{iip, specialize}(f1, f2, g;
Expand Down
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