From 35b00fdb750be1e95a41c1caa05cb4873c698abe Mon Sep 17 00:00:00 2001 From: Nathanael Bosch Date: Sat, 3 Feb 2024 14:41:42 +0100 Subject: [PATCH] Update the implementation docs a bit --- docs/src/implementation.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/src/implementation.md b/docs/src/implementation.md index 3440f09a4..bb91152fc 100644 --- a/docs/src/implementation.md +++ b/docs/src/implementation.md @@ -41,11 +41,11 @@ ProbNumDiffEq.jl builds around this structure and overloads some of the parts: - `./src/solution.jl` implements the main parts. Note that the main constructor `DiffEqBase.build_solution` is called by `OrdinaryDiffEq.__init`, so OrdinaryDiffEq.jl has control over its inputs. - `MeanProbODESolution <: DiffEqBase.AbstractODESolution` is a wrapper that allows handling the mean of a probabilistic ODE solution the same way one would handle any "standard" ODE solution, by just ignoring the covariances. - - `AbstractODEFilterPosterior <: DiffEqBase.AbstractDiffEqInterpolation` is the current interpolant, but it does not actually fully handle the interpolation right now. This part might be subject to change soon. - - *Plot recipe* in `./src/solution_plotting.jl` + - `AbstractODEFilterPosterior <: DiffEqBase.AbstractDiffEqInterpolation` handles the interpolation. + - *Plot recipe* in `./ext/RecipesBaseExt.jl` - *Sampling* in `./src/solution_sampling.jl` - `DiffEqBase.prepare_alg(::EK1{0})`; closely follows a similar function implemented in OrdinaryDiffEq.jl `./src/alg_utils.jl` - this also required `DiffEqBase.remake(::EK1)` ## Other packages -- `DiffEqDevTools.appxtrue`: We overload this function to work with `ProbODESolution`. This also enables `DiffEqDevTools.WorkPrecision` to work out of the box. +- `DiffEqDevTools.appxtrue`: We extend this function to work with `ProbODESolution`. This also enables `DiffEqDevTools.WorkPrecision` to work out of the box.