diff --git a/docs/src/basics/solution.md b/docs/src/basics/solution.md index 4a7158734..3229fb50e 100644 --- a/docs/src/basics/solution.md +++ b/docs/src/basics/solution.md @@ -191,9 +191,10 @@ Extra fields for solutions of specific problems are specified in the appropriate problem definition page. ## Solution Function Stripping -By default solution objects store functions, making them difficult to serialize. Using the function + +By default solution objects store functions, making them difficult to serialize. Using the function `strip_solution(sol)`, a copy of the solution that does not contain any functions is created. ```@docs SciMLBase.strip_solution -``` \ No newline at end of file +``` diff --git a/docs/src/tutorials/advanced_ode_example.md b/docs/src/tutorials/advanced_ode_example.md index e91d480ff..d9384c63f 100644 --- a/docs/src/tutorials/advanced_ode_example.md +++ b/docs/src/tutorials/advanced_ode_example.md @@ -145,9 +145,9 @@ Note that you should only do this if the sparsity is high, for example, 0.1% of the matrix is non-zeros, otherwise the overhead of sparse matrices can be higher than the gains from sparse differentiation! -[ADTypes.jl](https://github.com/SciML/ADTypes.jl) provides a [common interface for automatic sparsity detection](https://sciml.github.io/ADTypes.jl/stable/#Sparsity-detector) +[ADTypes.jl](https://github.com/SciML/ADTypes.jl) provides a [common interface for automatic sparsity detection](https://sciml.github.io/ADTypes.jl/stable/#Sparsity-detector) via its function `jacobian_sparsity`. -This function can be called using sparsity detectors from [SparseConnectivityTracer.jl](https://github.com/adrhill/SparseConnectivityTracer.jl) +This function can be called using sparsity detectors from [SparseConnectivityTracer.jl](https://github.com/adrhill/SparseConnectivityTracer.jl) or [Symbolics.jl](https://github.com/JuliaSymbolics/Symbolics.jl). We can give an example `du` and `u` and call `jacobian_sparsity` on our function with the example arguments, @@ -166,8 +166,8 @@ jac_sparsity = ADTypes.jacobian_sparsity( Using a different backend for sparsity detection just requires swapping out the detector, e.g. for Symbolics' [`SymbolicsSparsityDetector`](https://docs.sciml.ai/Symbolics/stable/manual/sparsity_detection/#Symbolics.SymbolicsSparsityDetector). -Notice that Julia gives a nice print out of the sparsity pattern. -That's neat, and would be tedious to build by hand! +Notice that Julia gives a nice print out of the sparsity pattern. +That's neat, and would be tedious to build by hand! Now we just pass it to the `ODEFunction` like as before: ```@example stiff1