pytikz.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Demo of pytikz, a Python interface to Ti*k*Z"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The import package is called `tikz`. For interactive use, importing the contents into the current namespace is more convenient."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tikz import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using `Picture` objects to create graphics\n",
    "\n",
    "Example graphic from the manual, [Part I](https://pgf-tikz.github.io/pgf/pgfmanual.pdf#part.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creating a graphic always involves creating a `Picture` object and performing operations on it. Here, the `draw()` method accepts a path specification (determines what to draw) as well as options (determine how to draw)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# define coordinates as a list of tuples\n",
    "coords = [(0, 0), (0, 2), (1, 3.25), (2, 2), (2, 0), (0, 2), (2, 2), (0, 0), (2, 0)]\n",
    "\n",
    "# create `Picture` object\n",
    "pic = Picture()\n",
    "# draw a line following the coordinates\n",
    "pic.draw(line(coords), thick=True, rounded_corners='4pt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Evaluating the `Picture` object in the notebook renders the graphic as a PNG and embeds it in the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "image/png": "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\n",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\" \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" version=\"1.1\" width=\"57.49pt\" height=\"92.92pt\" viewBox=\"0 0 57.49 92.92\">\n<g enable-background=\"new\">\n<path transform=\"matrix(1,0,0,-1,.39900209,92.520999)\" stroke-width=\".79701\" stroke-linecap=\"butt\" stroke-miterlimit=\"10\" stroke-linejoin=\"miter\" fill=\"none\" stroke=\"#000000\" d=\"M 0 0 L 0 52.70851 C 0 54.90945 1.12 58.09363 2.50163 59.82066 L 25.84517 89.00006 C 27.22679 90.7271 29.46681 90.7271 30.84843 89.00006 L 54.19197 59.82066 C 55.57361 58.09363 56.69362 54.90945 56.69362 52.70851 L 56.69362 3.9851 C 56.69362 1.78416 55.43199 1.2616 53.87566 2.81789 L 2.81795 53.87572 C 1.26163 55.43202 1.78416 56.69362 3.9851 56.69362 L 52.70851 56.69362 C 54.90945 56.69362 55.43199 55.43202 53.87566 53.87572 L 2.81795 2.81789 C 1.26163 1.2616 1.78416 0 3.9851 0 L 56.69362 0 \"/>\n</g>\n</svg>\n",
      "text/plain": "<tikz.Picture at 0x7fee73bf0160>"
     },
     "metadata": {},
     "execution_count": 3
    }
   ],
   "source": [
    "pic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The method `code()` returns the LaTeX/TikZ code of the `Picture` object, which is a `tikzpicture` environment. The same method is present on all objects that represent parts of the graphics. Notice how the structure of the Python code mimics that of the TikZ code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "\\begin{tikzpicture}\n\\draw[thick,rounded corners=4pt] (0,0) -- (0,2) -- (1,3.25) -- (2,2) -- (2,0) -- (0,2) -- (2,2) -- (0,0) -- (2,0);\n\\end{tikzpicture}\n"
    }
   ],
   "source": [
    "print(pic.code())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The method `demo()` of a `Picture` object shows both the rendered graphic and the underlying code in the notebook. It takes an optional argument `dpi` to specify the rendering resolution. It is intended to be used during development and debugging of a picture."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}\n\\draw[thick,rounded corners=4pt] (0,0) -- (0,2) -- (1,3.25) -- (2,2) -- (2,0) -- (0,2) -- (2,2) -- (0,0) -- (2,0);\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "pic.demo(dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The method `document_code()` of a `Picture` object returns the complete LaTeX/TikZ code used to render the graphic. When a graphic is rendered, internally this code is written to a temporary file and compiled with (pdf/Xe/Lua) LaTeX. The resulting PDF is read and can be either saved (using the method `write_image()`) or rastered for display in the notebook. A rastered version can also be saved."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A picture for Karl's students\n",
    "\n",
    "Based on the code developed in the first tutorial of the manual, [§2](https://pgf-tikz.github.io/pgf/pgfmanual.pdf#section.2)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
      "text/html": "<div style=\"background-color:#e0e0e0;margin:0\">\n  <div>\n    <div style=\"padding:10px;float:left\">      <img 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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}[scale=3,line cap=round]\n\\tikzset{important line/.style={very thick}}\n\\colorlet{anglecolor}{green!50!black}\n\\colorlet{sincolor}{red}\n\\colorlet{coscolor}{blue}\n\\colorlet{tancolor}{orange!80!black}\n\\draw[help lines,very thin] (-1.4,-1.4) grid[step=0.5cm] (1.4,1.4);\n\\draw (0,0) circle[radius=1];\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "pic = Picture(scale=3, line_cap='round')\n",
    "\n",
    "## define styles\n",
    "pic.style('important line', very_thick=True)\n",
    "\n",
    "# define colors\n",
    "pic.colorlet('anglecolor', 'green!50!black')\n",
    "pic.colorlet('sincolor', 'red')\n",
    "pic.colorlet('coscolor', 'blue')\n",
    "pic.colorlet('tancolor', 'orange!80!black')\n",
    "\n",
    "# background grid\n",
    "pic.draw((-1.4, -1.4), grid((1.4, 1.4), step='0.5cm'),\n",
    "    help_lines=True, very_thin=True)\n",
    "\n",
    "# circle\n",
    "pic.draw((0, 0), circle(radius=1))\n",
    "\n",
    "pic.demo(dpi=110)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
      "text/html": "<div style=\"background-color:#e0e0e0;margin:0\">\n  <div>\n    <div style=\"padding:10px;float:left\">      <img 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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}[scale=3,line cap=round]\n\\tikzset{important line/.style={very thick}}\n\\colorlet{anglecolor}{green!50!black}\n\\colorlet{sincolor}{red}\n\\colorlet{coscolor}{blue}\n\\colorlet{tancolor}{orange!80!black}\n\\draw[help lines,very thin] (-1.4,-1.4) grid[step=0.5cm] (1.4,1.4);\n\\draw (0,0) circle[radius=1];\n\\begin{scope}\n\\draw[-&gt;] (-1.5,0) -- (1.5,0) node[right] {$x$} coordinate (x axis);\n\\draw[-&gt;] (0,-1.5) -- (0,1.5) node[above] {$y$} coordinate (y axis);\n\\draw[xshift=-1 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$-1$};\n\\draw[xshift=-0.5 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$-0.5$};\n\\draw[xshift=0 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$0$};\n\\draw[xshift=0.5 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$0.5$};\n\\draw[xshift=1 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$1$};\n\\draw[yshift=-1 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$-1$};\n\\draw[yshift=-0.5 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$-0.5$};\n\\draw[yshift=0 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$0$};\n\\draw[yshift=0.5 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$0.5$};\n\\draw[yshift=1 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$1$};\n\\end{scope}\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "# `scope` environment to contain the axes code\n",
    "scope = pic.scope()\n",
    "\n",
    "# horizontal axis and label\n",
    "scope.draw((-1.5, 0), lineto((1.5, 0)), node('$x$', right=True), coordinate(name='x axis'),\n",
    "    opt='->')\n",
    "\n",
    "# vertical axis and label\n",
    "scope.draw((0, -1.5), lineto((0, 1.5)), node('$y$', above=True), coordinate(name='y axis'),\n",
    "    opt='->')\n",
    "\n",
    "# ticks and tick labels on horizontal axis\n",
    "for x in [-1, -0.5, 0, 0.5, 1]:\n",
    "    scope.draw('(0pt,1pt)', lineto('(0pt,-1pt)'), node(f'${x}$', below=True, fill='white'),\n",
    "        xshift=f'{x} cm')\n",
    "\n",
    "# ticks and tick labels on vertical axis\n",
    "for y in [-1, -0.5, 0, 0.5, 1]:\n",
    "    scope.draw('(1pt,0pt)', lineto('(-1pt,0pt)'), node(f'${y}$', left=True, fill='white'),\n",
    "        yshift=f'{y} cm')\n",
    "\n",
    "pic.demo(dpi=110)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}[scale=3,line cap=round]\n\\tikzset{important line/.style={very thick}}\n\\colorlet{anglecolor}{green!50!black}\n\\colorlet{sincolor}{red}\n\\colorlet{coscolor}{blue}\n\\colorlet{tancolor}{orange!80!black}\n\\draw[help lines,very thin] (-1.4,-1.4) grid[step=0.5cm] (1.4,1.4);\n\\draw (0,0) circle[radius=1];\n\\begin{scope}\n\\draw[-&gt;] (-1.5,0) -- (1.5,0) node[right] {$x$} coordinate (x axis);\n\\draw[-&gt;] (0,-1.5) -- (0,1.5) node[above] {$y$} coordinate (y axis);\n\\draw[xshift=-1 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$-1$};\n\\draw[xshift=-0.5 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$-0.5$};\n\\draw[xshift=0 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$0$};\n\\draw[xshift=0.5 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$0.5$};\n\\draw[xshift=1 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$1$};\n\\draw[yshift=-1 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$-1$};\n\\draw[yshift=-0.5 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$-0.5$};\n\\draw[yshift=0 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$0$};\n\\draw[yshift=0.5 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$0.5$};\n\\draw[yshift=1 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$1$};\n\\end{scope}\n\\path[fill=green!20,draw=anglecolor] (0,0) -- (3mm,0mm) arc[start angle=0,end angle=30,radius=3mm] --cycle;\n\\draw (15:2mm) node[anglecolor] {$\\alpha$};\n\\draw[important line,sincolor] (30:1cm) -- (30:1cm |- x axis) node[left=1pt,fill=white,pos=0.5] {$\\sin \\alpha$};\n\\draw[important line,coscolor] (30:1cm |- x axis) -- (0,0) node[below=2pt,fill=white,pos=0.5] {$\\cos \\alpha$};\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "# angle of 30 degrees\n",
    "pic.path((0, 0), lineto('(3mm,0mm)'), arc(start_angle=0, end_angle=30, radius='3mm'), '--cycle',\n",
    "    fill='green!20', draw='anglecolor')\n",
    "# label for angle\n",
    "pic.draw('(15:2mm)', node(r'$\\alpha$', anglecolor=True))\n",
    "\n",
    "# sine line and label\n",
    "pic.draw('(30:1cm)', lineto('(30:1cm |- x axis)'),\n",
    "    node(r'$\\sin \\alpha$', left='1pt', fill='white', pos=0.5),\n",
    "    important_line=True, sincolor=True)\n",
    "\n",
    "# cosine line and label\n",
    "pic.draw('(30:1cm |- x axis)', lineto((0,0)),\n",
    "    node(r'$\\cos \\alpha$', below='2pt', fill='white', pos=0.5),\n",
    "    important_line=True, coscolor=True)\n",
    "\n",
    "pic.demo(dpi=110)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}[scale=3,line cap=round]\n\\tikzset{important line/.style={very thick}}\n\\colorlet{anglecolor}{green!50!black}\n\\colorlet{sincolor}{red}\n\\colorlet{coscolor}{blue}\n\\colorlet{tancolor}{orange!80!black}\n\\draw[help lines,very thin] (-1.4,-1.4) grid[step=0.5cm] (1.4,1.4);\n\\draw (0,0) circle[radius=1];\n\\begin{scope}\n\\draw[-&gt;] (-1.5,0) -- (1.5,0) node[right] {$x$} coordinate (x axis);\n\\draw[-&gt;] (0,-1.5) -- (0,1.5) node[above] {$y$} coordinate (y axis);\n\\draw[xshift=-1 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$-1$};\n\\draw[xshift=-0.5 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$-0.5$};\n\\draw[xshift=0 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$0$};\n\\draw[xshift=0.5 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$0.5$};\n\\draw[xshift=1 cm] (0pt,1pt) -- (0pt,-1pt) node[below,fill=white] {$1$};\n\\draw[yshift=-1 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$-1$};\n\\draw[yshift=-0.5 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$-0.5$};\n\\draw[yshift=0 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$0$};\n\\draw[yshift=0.5 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$0.5$};\n\\draw[yshift=1 cm] (1pt,0pt) -- (-1pt,0pt) node[left,fill=white] {$1$};\n\\end{scope}\n\\path[fill=green!20,draw=anglecolor] (0,0) -- (3mm,0mm) arc[start angle=0,end angle=30,radius=3mm] --cycle;\n\\draw (15:2mm) node[anglecolor] {$\\alpha$};\n\\draw[important line,sincolor] (30:1cm) -- (30:1cm |- x axis) node[left=1pt,fill=white,pos=0.5] {$\\sin \\alpha$};\n\\draw[important line,coscolor] (30:1cm |- x axis) -- (0,0) node[below=2pt,fill=white,pos=0.5] {$\\cos \\alpha$};\n\\path[name path=upward line] (1,0) -- (1,1);\n\\path[name path=sloped line] (0,0) -- (30:1.5);\n\\draw[name intersections={of=upward line and sloped line, by=t}] ;\n\\draw[tancolor,very thick] (1,0) -- (t) node[right=1pt,fill=white,pos=0.5] {$\n            \\displaystyle\n            \\tan \\alpha\n            \\color{black} = \\frac{\n                \\color{red} \\sin \\alpha}{\n                \\color{blue} \\cos \\alpha}\n            $};\n\\draw (0,0) -- (t);\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "# To determine the top of the tangent line, the intersection of a line at 30 degrees from the origin with a line upwards from (1, 0) is determined\n",
    "pic.usetikzlibrary('intersections')\n",
    "pic.path((1, 0), lineto((1, 1)), name_path='upward line')\n",
    "pic.path((0, 0), lineto('(30:1.5)'), name_path='sloped line')\n",
    "pic.draw(name_intersections='{of=upward line and sloped line, by=t}')\n",
    "\n",
    "# tangent line and label\n",
    "pic.draw((1, 0), lineto('(t)'), node(\n",
    "            r\"\"\"$\n",
    "            \\displaystyle\n",
    "            \\tan \\alpha\n",
    "            \\color{black} = \\frac{\n",
    "                \\color{red} \\sin \\alpha}{\n",
    "                \\color{blue} \\cos \\alpha}\n",
    "            $\"\"\",\n",
    "            right='1pt', fill='white', pos=0.5),\n",
    "        tancolor=True, very_thick=True)\n",
    "\n",
    "# line from the origin to the top of the tangent line\n",
    "pic.draw((0, 0), lineto('(t)'))\n",
    "\n",
    "pic.demo(dpi=110)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "image/png": 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      "text/plain": "<tikz.Picture at 0x7fee860b2040>"
     },
     "metadata": {},
     "execution_count": 10
    }
   ],
   "source": [
    "pic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A logo for pytikz\n",
    "\n",
    "The logo consists of curved lines shaped like the letters 'p' and 'y', and the text 'TikZ'. Additionally, circles are used to mark the end points of the curved lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}\n\\tikzset{x=1ex,y=1ex}\n\\clip (-0.215,-1.2) rectangle (6.6,1.74);\n\\tikzset{every node/.style={inner sep=0,outer sep=0}}\n\\draw[darkgray,line cap=round,semithick] (0,-1) -- (0,1) .. controls (0.9,1.1) and (0.9,-0.1) .. (0,0) [xshift=1ex] (0,1) .. controls (0,0) .. (0.7,0) (0.7,1) -- (0.7,0) .. controls (0.7,-1) .. (0,-1) [xshift=0.8ex] (0,0) node[anchor=base west] {\\color{darkgray}Ti\\emph{\\color{orange}k}Z};\n\\draw[ultra thin,fill=white] (0,-1) circle[radius=0.25pt] (0,1) circle[radius=0.25pt] (0,0) circle[radius=0.25pt] [xshift=1ex] (0,1) circle[radius=0.25pt] (0.7,0) circle[radius=0.25pt] (0.7,1) circle[radius=0.25pt] (0,-1) circle[radius=0.25pt];\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "pic = Picture()\n",
    "\n",
    "# align coordinate system with font metrics\n",
    "pic.tikzset(x='1ex', y='1ex')\n",
    "\n",
    "# adjust the space around the contents\n",
    "pic.clip((-0.215, -1.2), rectangle((6.6, 1.74)))\n",
    "\n",
    "# style: remove space around node text\n",
    "pic.style('every node', inner_sep=0, outer_sep=0)\n",
    "\n",
    "# draw curved lines and text\n",
    "pic.draw(\n",
    "    # 'p'\n",
    "    (0, -1), lineto((0, 1)), curveto((0, 0), control1=(0.9, 1.1), control2=(0.9, -0.1)),\n",
    "    options(xshift='1ex'),\n",
    "    # 'y'\n",
    "    (0, 1), curveto((0.7, 0), control1=(0, 0)),\n",
    "    (0.7, 1), lineto((0.7, 0)), curveto((0, -1), control1=(0.7, -1)),\n",
    "    options(xshift='0.8ex'),\n",
    "    # 'TikZ'\n",
    "    (0, 0), node(r'\\color{darkgray}Ti\\emph{\\color{orange}k}Z', anchor='base west'),\n",
    "    darkgray=True, line_cap='round', semithick=True)\n",
    "\n",
    "# mark end points of curved lines\n",
    "pic.draw(\n",
    "    # points on 'p'\n",
    "    (0, -1), circle(radius='0.25pt'),\n",
    "    (0, 1), circle(radius='0.25pt'),\n",
    "    (0, 0), circle(radius='0.25pt'),\n",
    "    options(xshift='1ex'),\n",
    "    # point on 'y'\n",
    "    (0, 1), circle(radius='0.25pt'),\n",
    "    (0.7, 0), circle(radius='0.25pt'),\n",
    "    (0.7, 1), circle(radius='0.25pt'),\n",
    "    (0, -1), circle(radius='0.25pt'),\n",
    "    ultra_thin=True, fill='white')\n",
    "\n",
    "# version for the documentation\n",
    "pic.write_image('docs/logo.png', dpi=1200)\n",
    "\n",
    "pic.demo(dpi=1200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## An illustration for the documentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
      "text/html": "<div style=\"background-color:#e0e0e0;margin:0\">\n  <div>\n    <div style=\"padding:10px;float:left\">      <img 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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}\n\\colorlet{action}{red!80!black}\n\\colorlet{coordinate}{blue!60!black}\n\\colorlet{option}{violet}\n\\colorlet{operation}{lime!60!black}\n\\tikzset{every node/.style={inner sep=0,outer sep=0}}\n\\tikzset{font=\\tt}\n\\node (a) {pic};\n\\node[anchor=base west] (a2) at (a.base east) {.};\n\\node[anchor=base west,color=action] (b) at (a2.base east) {draw};\n\\node[anchor=base west] (c) at (b.base east) {(};\n\\node[anchor=base west,color=coordinate] (d) at (c.base east) {(-1.4, -1.4)};\n\\node[anchor=base west] (e) at (d.base east) {,$~$};\n\\node[anchor=base west,color=operation] (f) at (e.base east) {grid};\n\\node[anchor=base west] (g) at (f.base east) {(};\n\\node[anchor=base west,color=coordinate] (h) at (g.base east) {(-1.4, -1.4)};\n\\node[anchor=base west] (i) at (h.base east) {,$~$};\n\\node[anchor=base west,color=option] (j) at (i.base east) {step=0.5};\n\\node[anchor=base west] (k) at (j.base east) {)};\n\\node[anchor=base west] (k2) at (k.base east) {,$~$};\n\\node[anchor=base west,color=option] (l) at (k2.base east) {help\\_lines=True};\n\\node[anchor=base west] (m) at (l.base east) {)};\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "pic = Picture()\n",
    "\n",
    "# define colors\n",
    "pic.colorlet('action', 'red!80!black')\n",
    "pic.colorlet('coordinate', 'blue!60!black')\n",
    "pic.colorlet('option', 'violet')\n",
    "pic.colorlet('operation', 'lime!60!black')\n",
    "\n",
    "# nodes without padding\n",
    "pic.style('every node', inner_sep=0, outer_sep=0)\n",
    "\n",
    "# 'teletype' font for code\n",
    "pic.tikzset(font=r'\\tt')\n",
    "\n",
    "# create one node for each section of the code\n",
    "# Each is positioned relative to the previous one, to get continuous text.\n",
    "pic.node(r'pic', 'a')\n",
    "pic.node(r'.', 'a2',\n",
    "    at='(a.base east)', anchor='base west')\n",
    "pic.node('draw', 'b',\n",
    "    at='(a2.base east)', anchor='base west', color='action')\n",
    "pic.node('(', 'c',\n",
    "    at='(b.base east)', anchor='base west')\n",
    "pic.node('(-1.4, -1.4)', 'd',\n",
    "    at='(c.base east)', anchor='base west', color='coordinate')\n",
    "pic.node(',$~$', 'e',\n",
    "    at='(d.base east)', anchor='base west')\n",
    "pic.node('grid', 'f',\n",
    "    at='(e.base east)', anchor='base west', color='operation')\n",
    "pic.node('(', 'g',\n",
    "    at='(f.base east)', anchor='base west')\n",
    "pic.node('(-1.4, -1.4)', 'h',\n",
    "    at='(g.base east)', anchor='base west', color='coordinate')\n",
    "pic.node(',$~$', 'i',\n",
    "    at='(h.base east)', anchor='base west')\n",
    "pic.node('step=0.5', 'j',\n",
    "    at='(i.base east)', anchor='base west', color='option')\n",
    "pic.node(')', 'k',\n",
    "    at='(j.base east)', anchor='base west')\n",
    "pic.node(',$~$', 'k2',\n",
    "    at='(k.base east)', anchor='base west')\n",
    "pic.node('help\\_lines=True', 'l',\n",
    "    at='(k2.base east)', anchor='base west', color='option')\n",
    "pic.node(')', 'm',\n",
    "    at='(l.base east)', anchor='base west')\n",
    "\n",
    "pic.demo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}\n\\colorlet{action}{red!80!black}\n\\colorlet{coordinate}{blue!60!black}\n\\colorlet{option}{violet}\n\\colorlet{operation}{lime!60!black}\n\\tikzset{every node/.style={inner sep=0,outer sep=0}}\n\\tikzset{font=\\tt}\n\\node (a) {pic};\n\\node[anchor=base west] (a2) at (a.base east) {.};\n\\node[anchor=base west,color=action] (b) at (a2.base east) {draw};\n\\node[anchor=base west] (c) at (b.base east) {(};\n\\node[anchor=base west,color=coordinate] (d) at (c.base east) {(-1.4, -1.4)};\n\\node[anchor=base west] (e) at (d.base east) {,$~$};\n\\node[anchor=base west,color=operation] (f) at (e.base east) {grid};\n\\node[anchor=base west] (g) at (f.base east) {(};\n\\node[anchor=base west,color=coordinate] (h) at (g.base east) {(-1.4, -1.4)};\n\\node[anchor=base west] (i) at (h.base east) {,$~$};\n\\node[anchor=base west,color=option] (j) at (i.base east) {step=0.5};\n\\node[anchor=base west] (k) at (j.base east) {)};\n\\node[anchor=base west] (k2) at (k.base east) {,$~$};\n\\node[anchor=base west,color=option] (l) at (k2.base east) {help\\_lines=True};\n\\node[anchor=base west] (m) at (l.base east) {)};\n\\tikzset{downarrow/.style={shorten &lt;=0.8em,shorten &gt;=0.4em,&lt;-}}\n\\tikzset{uparrow/.style={shorten &lt;=0.4em,shorten &gt;=0.8em,&lt;-}}\n\\tikzset{font=\\sf\\small}\n\\draw[downarrow] (a.base) -- +(0,2.5em) node[anchor=base] {picture object};\n\\draw[uparrow] (b.base) -- +(0,-2.5em) node[anchor=base,color=action,align=center,yshift=-\\baselineskip] {path\\\\action};\n\\draw[downarrow] (h.base) -- +(0,2.5em) node[anchor=base,color=coordinate] {coordinate};\n\\draw[uparrow] (f.base) -- +(0,-2.5em) node[anchor=base,color=operation] {path operation};\n\\draw[downarrow] (d.base) -- +(0,2.5em) node[anchor=base,color=coordinate] {coordinate};\n\\draw[uparrow] (j.base) -- +(0,-2.5em) node[anchor=base,color=option,align=center,yshift=-\\baselineskip] {path oper.\\\\option};\n\\draw[downarrow] (l.base) -- +(0,2.5em) node[anchor=base,color=option] {path action option};\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "# define arrow styles\n",
    "# All arrows and annotation are positioned relative to the baseline,\n",
    "# with symmetric shortening of the arrows for upper and lower annotations.\n",
    "pic.style('downarrow', opt='shorten <=0.8em,shorten >=0.4em,<-')\n",
    "pic.style('uparrow', opt='shorten <=0.4em,shorten >=0.8em,<-')\n",
    "\n",
    "# small 'sans serif' font for annotations\n",
    "pic.tikzset(font=r'\\sf\\small')\n",
    "\n",
    "# arrows and annotation nodes\n",
    "pic.draw('(a.base)', lineto('+(0,2.5em)'),\n",
    "    node('picture object', anchor='base'),\n",
    "    downarrow=True)\n",
    "pic.draw('(b.base)', lineto('+(0,-2.5em)'),\n",
    "    node(r'path\\\\action', anchor='base', color='action',\n",
    "        align='center', yshift=r'-\\baselineskip'),\n",
    "    uparrow=True)\n",
    "pic.draw('(h.base)', lineto('+(0,2.5em)'),\n",
    "    node('coordinate', anchor='base', color='coordinate'),\n",
    "    downarrow=True)\n",
    "pic.draw('(f.base)', lineto('+(0,-2.5em)'),\n",
    "    node('path operation', anchor='base', color='operation'),\n",
    "    uparrow=True)\n",
    "pic.draw('(d.base)', lineto('+(0,2.5em)'),\n",
    "    node('coordinate', anchor='base', color='coordinate'),\n",
    "    downarrow=True)\n",
    "pic.draw('(j.base)', lineto('+(0,-2.5em)'),\n",
    "    node(r'path oper.\\\\option', anchor='base', color='option',\n",
    "        align='center', yshift=r'-\\baselineskip'),\n",
    "    uparrow=True)\n",
    "pic.draw('(l.base)', lineto('+(0,2.5em)'),\n",
    "    node('path action option', anchor='base', color='option'),\n",
    "    downarrow=True)\n",
    "\n",
    "pic.demo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<IPython.core.display.HTML object>",
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\">\n    </div>\n    <pre\n        style=\"width:47%;margin:0;padding:10px;float:right;white-space:pre-wrap;font-size:smaller\"\n        >\\begin{tikzpicture}\n\\colorlet{action}{red!80!black}\n\\colorlet{coordinate}{blue!60!black}\n\\colorlet{option}{violet}\n\\colorlet{operation}{lime!60!black}\n\\tikzset{every node/.style={inner sep=0,outer sep=0}}\n\\tikzset{font=\\tt}\n\\node (a) {pic};\n\\node[anchor=base west] (a2) at (a.base east) {.};\n\\node[anchor=base west,color=action] (b) at (a2.base east) {draw};\n\\node[anchor=base west] (c) at (b.base east) {(};\n\\node[anchor=base west,color=coordinate] (d) at (c.base east) {(-1.4, -1.4)};\n\\node[anchor=base west] (e) at (d.base east) {,$~$};\n\\node[anchor=base west,color=operation] (f) at (e.base east) {grid};\n\\node[anchor=base west] (g) at (f.base east) {(};\n\\node[anchor=base west,color=coordinate] (h) at (g.base east) {(-1.4, -1.4)};\n\\node[anchor=base west] (i) at (h.base east) {,$~$};\n\\node[anchor=base west,color=option] (j) at (i.base east) {step=0.5};\n\\node[anchor=base west] (k) at (j.base east) {)};\n\\node[anchor=base west] (k2) at (k.base east) {,$~$};\n\\node[anchor=base west,color=option] (l) at (k2.base east) {help\\_lines=True};\n\\node[anchor=base west] (m) at (l.base east) {)};\n\\tikzset{downarrow/.style={shorten &lt;=0.8em,shorten &gt;=0.4em,&lt;-}}\n\\tikzset{uparrow/.style={shorten &lt;=0.4em,shorten &gt;=0.8em,&lt;-}}\n\\tikzset{font=\\sf\\small}\n\\draw[downarrow] (a.base) -- +(0,2.5em) node[anchor=base] {picture object};\n\\draw[uparrow] (b.base) -- +(0,-2.5em) node[anchor=base,color=action,align=center,yshift=-\\baselineskip] {path\\\\action};\n\\draw[downarrow] (h.base) -- +(0,2.5em) node[anchor=base,color=coordinate] {coordinate};\n\\draw[uparrow] (f.base) -- +(0,-2.5em) node[anchor=base,color=operation] {path operation};\n\\draw[downarrow] (d.base) -- +(0,2.5em) node[anchor=base,color=coordinate] {coordinate};\n\\draw[uparrow] (j.base) -- +(0,-2.5em) node[anchor=base,color=option,align=center,yshift=-\\baselineskip] {path oper.\\\\option};\n\\draw[downarrow] (l.base) -- +(0,2.5em) node[anchor=base,color=option] {path action option};\n\\draw[color=lightgray] (d.base west) ++(0,-0.4em) -- +(0,-4.1em) coordinate (n);\n\\draw[color=lightgray] (k.base east) ++(0,-0.4em) -- +(0,-4.1em) coordinate (o);\n\\draw[decorate,decoration={brace,mirror},color=lightgray] (n) -- (o) node[pos=0.5,below=0.6em,color=black] {path specification};\n\\path (current bounding box.north east) +(2em, 2em);\n\\path (current bounding box.south west) +(-2em, -2em);\n\\end{tikzpicture}</pre>\n  </div>\n  <div style=\"clear:both\"></div>\n</div>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "# brace for path specification\n",
    "pic.usetikzlibrary('decorations.pathreplacing')\n",
    "pic.draw('(d.base west)', '++(0,-0.4em)', lineto('+(0,-4.1em)'), coordinate('n'),\n",
    "    color='lightgray')\n",
    "pic.draw('(k.base east)', '++(0,-0.4em)', lineto('+(0,-4.1em)'), coordinate('o'),\n",
    "    color='lightgray')\n",
    "pic.draw('(n)', lineto('(o)'),\n",
    "    node('path specification', pos=0.5, below='0.6em', color='black'),\n",
    "    decorate=True, decoration='{brace,mirror}', color='lightgray')\n",
    "\n",
    "# add padding around contents\n",
    "pic.path('(current bounding box.north east)', '+(2em, 2em)')\n",
    "pic.path('(current bounding box.south west)', '+(-2em, -2em)')\n",
    "\n",
    "# write SVG into documentation folder\n",
    "pic.write_image('docs/tikz/design.svg')\n",
    "\n",
    "pic.demo()"
   ]
  }
 ],
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