Text for kerning fonts

RandomKerningText.ipynb

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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We are working on the kerning of the xkcd font being developed in this GitHub repo:\n",
      "\n",
      "https://github.com/ipython/xkcd-font"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The purpose of this IPython notebook is to create text that we can use to help us kern the font. To do this we generate random text that covers as many of the letter digraphs as possible. The approach used here is rather pedestrian, but it works fairly well if you are OK with random text.\n",
      "\n",
      "First let's enable the xkcd font we are working on kerning. This loads the current version of the font into the Notebook:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import xkcdify"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "xkcdify(borders=False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "    <style>\n",
        "    @font-face {\n",
        "        font-family: \"xkcd\";\n",
        "        src: url('http://xkcd.com/fonts/xkcd-Regular.otf');\n",
        "    }\n",
        "    \n",
        "        .CodeMirror {font-family: xkcd; font-size: 120%}\n",
        "        \n",
        "        .rendered_html {font-family: xkcd; font-size: 120%}\n",
        "        pre, code {font-family: xkcd; font-size: 120%}\n",
        "        .rendered_html table {border: 2px solid black;}\n",
        "        .rendered_html tr {border: 2px solid black;}\n",
        "        .rendered_html th {border: 2px solid black; padding: 0.45em 1em;}\n",
        "        .rendered_html td {border: 2px solid black; padding: 0.45em 1em;}\n",
        "        \n",
        "        div.prompt {font-family: xkcd; font-size: 120%}\n",
        "        \n",
        "        div.output_area pre {font-family: xkcd; font-size: 120%}\n",
        "        </style>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x100f79210>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's also adjust the font size and line height of the text we are going to view:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "HTML(\"\"\"\n",
      "<style>\n",
      "div.output_area pre {font-size: 150%; line-height: 1.5;}\n",
      "</style>\n",
      "\"\"\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "<style>\n",
        "div.output_area pre {font-size: 150%; line-height: 1.5;}\n",
        "</style>\n"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "<IPython.core.display.HTML at 0x100f791d0>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now, define some functions for generating our kerning text:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import random\n",
      "from IPython.utils.text import wrap_paragraphs"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 64
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "alpha = 'abcdefghijklmnopqrstuvwxyz'.upper()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 98
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def random_word(size):\n",
      "    \"\"\"Generate a random word of size.\"\"\"\n",
      "    return ''.join(random.sample(alpha, size))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 99
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def random_text(nwords, min_size=2, max_size=15, ncols=80):\n",
      "    \"\"\"Generate random text with n words of length (min_size, max_size).\"\"\"\n",
      "    words = []\n",
      "    for i in range(nwords):\n",
      "        size = random.randint(min_size,max_size)\n",
      "        word = random_word(size)\n",
      "        words.append(word)\n",
      "    return wrap_paragraphs(' '.join(words), ncols=ncols)[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 100
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def count_digraphs(text):\n",
      "    \"\"\"Count the total number of unique digraphs in a text.\"\"\"\n",
      "    digraphs = set()\n",
      "    words = text.split(' ')\n",
      "    for word in words:\n",
      "        for i in range(len(word)-1):\n",
      "            digraphs.add(word[i:i+2])\n",
      "    return len(digraphs)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 101
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Generate some text:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "text = random_text(200)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 102
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Here is the sample text we can use for kerning:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print text"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
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      }
     ],
     "prompt_number": 103
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This sample has a good fraction of the total number of digraphs:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "count = count_digraphs(text); count"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 116,
       "text": [
        "611"
       ]
      }
     ],
     "prompt_number": 116
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "total = 26.0**2; total"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 117,
       "text": [
        "676.0"
       ]
      }
     ],
     "prompt_number": 117
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fraction = count/total; fraction"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 119,
       "text": [
        "0.9038461538461539"
       ]
      }
     ],
     "prompt_number": 119
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(text)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 97,
       "text": [
        "1833"
       ]
      }
     ],
     "prompt_number": 97
    }
   ],
   "metadata": {}
  }
 ]
}