{ "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 Array{Int64,1}:\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", "\n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n" ], "image/svg+xml": [ "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\n", "\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": "1.4.1" }, "kernelspec": { "name": "julia-1.4", "display_name": "Julia 1.4.1", "language": "julia" } }, "nbformat": 4 }