From 7cadf4584f0e271cd8bac4e772ce9327e168d366 Mon Sep 17 00:00:00 2001 From: Mateusz Baran Date: Tue, 3 Sep 2024 17:41:00 +0200 Subject: [PATCH] improve docs --- src/ManifoldDiffEq.jl | 8 ++++++-- src/interpolation.jl | 4 ++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/src/ManifoldDiffEq.jl b/src/ManifoldDiffEq.jl index 0418ce5..ebad339 100644 --- a/src/ManifoldDiffEq.jl +++ b/src/ManifoldDiffEq.jl @@ -93,12 +93,13 @@ Type parameter `T` denotes scalar floating point type of the solution Fields: * `u`: the representation of the ODE solution. Uses a nested power manifold representation. -* `t`: time point at which values in `u` were calculated. +* `t`: time points at which values in `u` were calculated. * `k`: the representation of the `f` function evaluations at time points `k`. Uses a nested power manifold representation. * `prob`: original problem that was solved. * `alg`: [`AbstractManifoldDiffEqAlgorithm`](@ref) used to obtain the solution. -* `interp` [`ManifoldInterpolationData`](@ref) +* `interp` [`ManifoldInterpolationData`](@ref). It is used for calculating solution values + at times `t` other then the ones at which it was saved. * `dense`: `true` if ODE solution is saved at every step and `false` otherwise. * `stats`: [`DEStats`](https://docs.sciml.ai/DiffEqDocs/stable/basics/solution/#SciMLBase.DEStats) of the solver * `retcode`: [`ReturnCode`](https://docs.sciml.ai/SciMLBase/stable/interfaces/Solutions/#retcodes) of the solution. @@ -191,6 +192,9 @@ alg_extrapolates(::AbstractManifoldDiffEqAlgorithm) = false struct DefaultInit end + +# Adapted from OrdinaryDiffEq.jl: +# https://github.com/SciML/OrdinaryDiffEq.jl/blob/1eef9db17600766bb71e7dce0cb105ae5f99b2a5/lib/OrdinaryDiffEqCore/src/solve.jl#L11 function SciMLBase.__init( prob::ManifoldODEProblem, alg::AbstractManifoldDiffEqAlgorithm, diff --git a/src/interpolation.jl b/src/interpolation.jl index b29d8d9..ec7ddad 100644 --- a/src/interpolation.jl +++ b/src/interpolation.jl @@ -3,8 +3,8 @@ """ struct ManifoldInterpolationData end - -Inspired by `OrdinaryDiffEq.OrdinaryDiffEqInterpolation`. +Inspired by [`OrdinaryDiffEq.InterpolationData`](https://github.com/SciML/OrdinaryDiffEq.jl/blob/41333beef24655d43d370af19b37efd9888179f6/lib/OrdinaryDiffEqCore/src/interp_func.jl#L4). +The main difference is using on-manifold interpolation instead of the Euclidean one. """ struct ManifoldInterpolationData{F,uType,tType,kType,cacheType,TM} f::F