From c03d4f661bb1195aafa8ac1cf6059a9f77c128f9 Mon Sep 17 00:00:00 2001 From: Nathan Boyer <65452054+nathanrboyer@users.noreply.github.com> Date: Tue, 14 Nov 2023 10:32:25 -0500 Subject: [PATCH] Fix broken Note --- docs/src/getting_started/fit_simulation.md | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/docs/src/getting_started/fit_simulation.md b/docs/src/getting_started/fit_simulation.md index a7fd141d6dc..10ee7b58a08 100644 --- a/docs/src/getting_started/fit_simulation.md +++ b/docs/src/getting_started/fit_simulation.md @@ -183,11 +183,10 @@ datasol = solve(prob, saveat = 1) data = Array(datasol) ``` -!!! note - +!!! note -For more details on using DifferentialEquations.jl, check out the -[getting started with DifferentialEquations.jl tutorial](https://docs.sciml.ai/DiffEqDocs/stable/getting_started/). + For more details on using DifferentialEquations.jl, check out the + [getting started with DifferentialEquations.jl tutorial](https://docs.sciml.ai/DiffEqDocs/stable/getting_started/). ### Step 3: Set Up the Cost Function for Optimization @@ -202,7 +201,7 @@ For our case, we want to change around just the parameters, so we can do `remake !!! note - `remake` can change multiple items at once by passing more keyword arguments! I.e., `remake(prob, u0 = newu0, p = newp)` + `remake` can change multiple items at once by passing more keyword arguments, i.e., `remake(prob, u0 = newu0, p = newp)`. This can be used to extend the example to simultaneously learn the initial conditions and parameters! Now use `remake` to build the cost function. After we solve the new problem, we will calculate the sum of squared errors