{
"cells": [
{
"cell_type": "markdown",
"source": [
"# **8.** Example"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "slide"
}
}
},
{
"cell_type": "markdown",
"source": [
"This is an example generated with Literate based on this\n",
"source file: [`example.jl`](https://github.com/fredrikekre/Literate.jl/blob/master/examples/example.jl).\n",
"You are seeing the\n",
"generated notebook output. The corresponding markdown (HTML) output\n",
"can be found here: [`example.html`](https://fredrikekre.github.io/Literate.jl/dev/generated/example.html),\n",
"and the plain script output can be found here: [`example.jl`](./example.jl)."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "slide"
}
}
},
{
"cell_type": "markdown",
"source": [
"To view this notebook as a slideshow, install the [RISE plugin](https://rise.readthedocs.io/en/stable/installation.html)\n",
"and press `alt-r` to start. Use spacebar to advance."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
}
},
{
"cell_type": "markdown",
"source": [
"It is recommended to have the [source file](https://github.com/fredrikekre/Literate.jl/blob/master/examples/example.jl)\n",
"available when reading this, to better understand how the syntax in the source file\n",
"corresponds to the output you are seeing."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
}
},
{
"cell_type": "markdown",
"source": [
"### Basic syntax\n",
"The basic syntax for Literate is simple, lines starting with `# ` is interpreted\n",
"as markdown, and all the other lines are interpreted as code. Here is some code:"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "slide"
}
}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "2//5"
},
"metadata": {},
"execution_count": 1
}
],
"cell_type": "code",
"source": [
"x = 1//3\n",
"y = 2//5"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
},
"execution_count": 1
},
{
"cell_type": "markdown",
"source": [
"In markdown sections we can use markdown syntax. For example, we can\n",
"write *text in italic font*, **text in bold font** and use\n",
"[links](https://www.youtube.com/watch?v=dQw4w9WgXcQ)."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "subslide"
}
}
},
{
"cell_type": "markdown",
"source": [
"It is possible to filter out lines depending on the output using the\n",
"`#md`, `#nb`, `#jl` and `#src` tags (see Filtering lines):\n",
"- This line starts with `#nb` and is thus only visible in the notebook output."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
}
},
{
"cell_type": "markdown",
"source": [
"The source file is parsed in chunks of markdown and code. Starting a line\n",
"with `#-` manually inserts a chunk break. For example, if we want to\n",
"display the output of the following operations we may insert `#-` in\n",
"between. These two code blocks will now end up in different\n",
"`@example`-blocks in the markdown output, and two different notebook cells\n",
"in the notebook output."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "subslide"
}
}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "11//15"
},
"metadata": {},
"execution_count": 2
}
],
"cell_type": "code",
"source": [
"x + y"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "subslide"
}
},
"execution_count": 2
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "2//15"
},
"metadata": {},
"execution_count": 3
}
],
"cell_type": "code",
"source": [
"x * y"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
},
"execution_count": 3
},
{
"cell_type": "markdown",
"source": [
"### Output capturing\n",
"Code chunks are by default placed in Documenter `@example` blocks in the generated\n",
"markdown. This means that the output will be captured in a block when Documenter is\n",
"building the docs. In notebooks the output is captured in output cells, if the\n",
"`execute` keyword argument is set to true. Output to `stdout`/`stderr` is also\n",
"captured."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "slide"
}
}
},
{
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"This string is printed to stdout.\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": "4-element Vector{Int64}:\n 1\n 2\n 3\n 4"
},
"metadata": {},
"execution_count": 4
}
],
"cell_type": "code",
"source": [
"function foo()\n",
" println(\"This string is printed to stdout.\")\n",
" return [1, 2, 3, 4]\n",
"end\n",
"\n",
"foo()"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "subslide"
}
},
"execution_count": 4
},
{
"cell_type": "markdown",
"source": [
"Just like in the REPL, outputs ending with a semicolon hides the output:"
],
"metadata": {}
},
{
"outputs": [],
"cell_type": "code",
"source": [
"1 + 1;"
],
"metadata": {},
"execution_count": 5
},
{
"cell_type": "markdown",
"source": [
"Both Documenter's `@example` block and notebooks can display images. Here is an example\n",
"where we generate a simple plot using the\n",
"[Plots.jl](https://github.com/JuliaPlots/Plots.jl) package"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "subslide"
}
}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "Plot{Plots.GRBackend() n=2}",
"image/png": 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",
"text/html": [
"\n",
"\n"
],
"image/svg+xml": [
"\n",
"\n"
]
},
"metadata": {},
"execution_count": 6
}
],
"cell_type": "code",
"source": [
"using Plots\n",
"x = range(0, stop=6π, length=1000)\n",
"y1 = sin.(x)\n",
"y2 = cos.(x)\n",
"plot(x, [y1, y2])"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "subslide"
}
},
"execution_count": 6
},
{
"cell_type": "markdown",
"source": [
"### Custom processing\n",
"\n",
"It is possible to give Literate custom pre- and post-processing functions.\n",
"For example, here we insert a placeholder value `y = 321` in the source, and use a\n",
"preprocessing function that replaces it with `y = 321` in the rendered output."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "slide"
}
}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "123"
},
"metadata": {},
"execution_count": 7
}
],
"cell_type": "code",
"source": [
"x = 123"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "subslide"
}
},
"execution_count": 7
},
{
"cell_type": "markdown",
"source": [
"In this case the preprocessing function is defined by"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
}
},
{
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "pre (generic function with 1 method)"
},
"metadata": {},
"execution_count": 8
}
],
"cell_type": "code",
"source": [
"function pre(s::String)\n",
" s = replace(s, \"x = 123\" => \"y = 321\")\n",
" return s\n",
"end"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
},
"execution_count": 8
},
{
"cell_type": "markdown",
"source": [
"### Documenter.jl interaction\n",
"\n",
"In the source file it is possible to use Documenter.jl style references,\n",
"such as `@ref` and `@id`. These will be filtered out in the notebook output.\n",
"For example, here is a link, but it is only\n",
"visible as a link if you are reading the markdown output. We can also\n",
"use equations:"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "slide"
}
}
},
{
"cell_type": "markdown",
"source": [
"$$\n",
"\\int_\\Omega \\nabla v \\cdot \\nabla u\\ \\mathrm{d}\\Omega = \\int_\\Omega v f\\ \\mathrm{d}\\Omega\n",
"$$"
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
}
},
{
"cell_type": "markdown",
"source": [
"using Documenters math syntax. Documenters syntax is automatically changed to\n",
"`\\begin{equation} ... \\end{equation}` in the notebook output to display correctly."
],
"metadata": {
"name": "A slide ",
"slideshow": {
"slide_type": "fragment"
}
}
},
{
"cell_type": "markdown",
"source": [
"---\n",
"\n",
"*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*"
],
"metadata": {}
}
],
"nbformat_minor": 3,
"metadata": {
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.9.3"
},
"kernelspec": {
"name": "julia-1.9",
"display_name": "Julia 1.9.3",
"language": "julia"
}
},
"nbformat": 4
}