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Documenter.jl committed Feb 7, 2024
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{"documenter":{"julia_version":"1.9.4","generation_timestamp":"2024-02-05T18:49:51","documenter_version":"1.2.1"}}
{"documenter":{"julia_version":"1.9.4","generation_timestamp":"2024-02-07T10:57:59","documenter_version":"1.2.1"}}
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{
"cell_type": "markdown",
"source": [
"# 5: DG schemes via `DGMulti` solver"
"# 6: DG schemes via `DGMulti` solver"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 6: Other SBP schemes (FD, CGSEM) via `DGMulti` solver"
"# 7: Other SBP schemes (FD, CGSEM) via `DGMulti` solver"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 2: DGSEM with flux differencing"
"# 3: DGSEM with flux differencing"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 12: Adaptive mesh refinement"
"# 13: Adaptive mesh refinement"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 11: Adding new parabolic terms"
"# 12: Adding new parabolic terms"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 8: Adding a new scalar conservation law"
"# 9: Adding a new scalar conservation law"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 9: Adding a non-conservative equation"
"# 10: Adding a non-conservative equation"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 18: Custom semidiscretizations"
"# 19: Custom semidiscretizations"
],
"metadata": {}
},
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{
"cell_type": "markdown",
"source": [
"# 17: Differentiable programming"
"# 18: Differentiable programming"
],
"metadata": {}
},
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{
"cells": [
{
"cell_type": "markdown",
"source": [
"# 1.3: First steps in Trixi.jl: Changing Trixi.jl itself"
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"**Note:** To improve responsiveness via caching, the notebooks are updated only once a week. They are only\n",
"available for the latest stable release of Trixi.jl at the time of caching."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"If you plan on editing Trixi.jl itself, you can download Trixi.jl locally and run it from\n",
"the cloned directory."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"## Cloning Trixi.jl"
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"### Windows"
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"If you are using Windows, you can clone Trixi.jl by using the GitHub Desktop tool:\n",
"- If you do not have a GitHub account yet, create it on\n",
" the [GitHub website](https://github.com/join).\n",
"- Download and install [GitHub Desktop](https://desktop.github.com/) and then log in to\n",
" your account.\n",
"- Open GitHub Desktop, press `Ctrl+Shift+O`.\n",
"- In the opened window, paste `trixi-framework/Trixi.jl` and choose the path to the folder where\n",
" you want to save Trixi.jl. Then click `Clone` and Trixi.jl will be cloned to your computer."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"Now you cloned Trixi.jl and only need to tell Julia to use the local clone as the package sources:\n",
"- Open a terminal using `Win+r` and `cmd`. Navigate to the folder with the cloned Trixi.jl using `cd`.\n",
"- Create a new directory `run`, enter it, and start Julia with the `--project=.` flag:\n",
" ```shell\n",
" mkdir run\n",
" cd run\n",
" julia --project=.\n",
" ```\n",
"- Now run the following commands to install all relevant packages:\n",
" ```julia\n",
" using Pkg; Pkg.develop(PackageSpec(path=\"..\")) # Tell Julia to use the local Trixi.jl clone\n",
" Pkg.add([\"OrdinaryDiffEq\", \"Plots\"]) # Install additional packages\n",
" ```"
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"Now you already installed Trixi.jl from your local clone. Note that if you installed Trixi.jl\n",
"this way, you always have to start Julia with the `--project` flag set to your `run` directory,\n",
"e.g.,\n",
"```shell\n",
"julia --project=.\n",
"```\n",
"if already inside the `run` directory."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"### Linux"
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"You can clone Trixi.jl to your computer by executing the following commands:\n",
"```shell\n",
"git clone [email protected]:trixi-framework/Trixi.jl.git\n",
"# If an error occurs, try the following:\n",
"# git clone https://github.com/trixi-framework/Trixi.jl\n",
"cd Trixi.jl\n",
"mkdir run\n",
"cd run\n",
"julia --project=. -e 'using Pkg; Pkg.develop(PackageSpec(path=\"..\"))' # Tell Julia to use the local Trixi.jl clone\n",
"julia --project=. -e 'using Pkg; Pkg.add([\"OrdinaryDiffEq\", \"Plots\"])' # Install additional packages\n",
"```\n",
"Note that if you installed Trixi.jl this way,\n",
"you always have to start Julia with the `--project` flag set to your `run` directory, e.g.,\n",
"```shell\n",
"julia --project=.\n",
"```\n",
"if already inside the `run` directory."
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"## Additional reading"
],
"metadata": {}
},
{
"cell_type": "markdown",
"source": [
"To further delve into Trixi.jl, you may have a look at the following introductory tutorials.\n",
"- Introduction to DG methods will teach you how to set up a\n",
" simple way to approximate the solution of a hyperbolic partial differential equation. It will\n",
" be especially useful to learn about the\n",
" [Discontinuous Galerkin method](https://en.wikipedia.org/wiki/Discontinuous_Galerkin_method)\n",
" and the way it is implemented in Trixi.jl.\n",
"- Adding a new scalar conservation law and\n",
" Adding a non-conservative equation\n",
" describe how to add new physics models that are not yet included in Trixi.jl.\n",
"- Callbacks gives an overview of how to regularly execute specific actions\n",
" during a simulation, e.g., to store the solution or adapt the mesh."
],
"metadata": {}
}
],
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