1.3: First steps in Trixi.jl: Changing Trixi.jl itself

If you plan on editing Trixi.jl itself, you can download Trixi.jl locally and run it from the cloned directory.

Cloning Trixi.jl

Windows

If you are using Windows, you can clone Trixi.jl by using the GitHub Desktop tool:

If you do not have a GitHub account yet, create it on the GitHub website.
Download and install GitHub Desktop and then log in to your account.
Open GitHub Desktop, press Ctrl+Shift+O.
In the opened window, paste trixi-framework/Trixi.jl and choose the path to the folder where you want to save Trixi.jl. Then click Clone and Trixi.jl will be cloned to your computer.

Now you cloned Trixi.jl and only need to tell Julia to use the local clone as the package sources:

Open a terminal using Win+r and cmd. Navigate to the folder with the cloned Trixi.jl using cd.
Create a new directory run, enter it, and start Julia with the --project=. flag:
```
mkdir run
cd run
julia --project=.
```

Now run the following commands to install all relevant packages:

using Pkg; Pkg.develop(PackageSpec(path="..")) # Tell Julia to use the local Trixi.jl clone
Pkg.add(["OrdinaryDiffEq", "Plots"])  # Install additional packages

Now you already installed Trixi.jl from your local clone. Note that if you installed Trixi.jl this way, you always have to start Julia with the --project flag set to your run directory, e.g.,

julia --project=.

if already inside the run directory.

Linux

You can clone Trixi.jl to your computer by executing the following commands:

git clone git@github.com:trixi-framework/Trixi.jl.git
# If an error occurs, try the following:
# git clone https://github.com/trixi-framework/Trixi.jl
cd Trixi.jl
mkdir run
cd run
julia --project=. -e 'using Pkg; Pkg.develop(PackageSpec(path=".."))' # Tell Julia to use the local Trixi.jl clone
julia --project=. -e 'using Pkg; Pkg.add(["OrdinaryDiffEq", "Plots"])' # Install additional packages

Note that if you installed Trixi.jl this way, you always have to start Julia with the --project flag set to your run directory, e.g.,

julia --project=.

if already inside the run directory.

Additional reading

To further delve into Trixi.jl, you may have a look at the following introductory tutorials.

Introduction to DG methods will teach you how to set up a simple way to approximate the solution of a hyperbolic partial differential equation. It will be especially useful to learn about the Discontinuous Galerkin method and the way it is implemented in Trixi.jl.
Adding a new scalar conservation law and Adding a non-conservative equation describe how to add new physics models that are not yet included in Trixi.jl.
Callbacks gives an overview of how to regularly execute specific actions during a simulation, e.g., to store the solution or adapt the mesh.

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