Using showtext with Jupyter

try-showtext.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using showtext with Jupyter\n",
    "\n",
    "showtext is a great library by Yixuan Qiu for drawing\n",
    "the font glyphs as shapes so the viewer does not need\n",
    "to have the fonts installed:\n",
    "\n",
    "- https://github.com/yixuan/showtext\n",
    "- https://CRAN.R-project.org/package=showtext\n",
    "\n",
    "## Summary\n",
    "\n",
    "The package works on Linux with Jupyter, but only if you\n",
    "write the plot to a PNG file `\"filename.png\"` and then load it with\n",
    "`IRdisplay::display_png(\"filename.png\")`.\n",
    "\n",
    "Is there a way to get the automatically printed plots to work with showtext?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: sysfonts\n",
      "Loading required package: showtextdb\n"
     ]
    }
   ],
   "source": [
    "library(showtext)\n",
    "library(IRdisplay)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "###  Download font file from web  ###\n",
    "\n",
    "download.file(\"http://fontpro.com/download-family.php?file=36289\",\n",
    "              \"newrocker.ttf\", mode=\"wb\")\n",
    "download.file(\"http://fontpro.com/download-family.php?file=35128\",\n",
    "              \"cutetumblr.ttf\", mode =\"wb\")\n",
    "\n",
    "font_add(\"newrocker\", \"newrocker.ttf\")\n",
    "font_add(\"cutetumblr\", \"cutetumblr.ttf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example 1\n",
    "\n",
    "This does not work. The fonts are not loaded when the plot is automatically printed to the screen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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L/ekps0aZLKcQoKChQ3ZgsODt63b1+dHXfu3Kl4CEFQUFBhYWFt7RX3pgkODq7z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\nAACgCIIdAACAIgh2AAAAiiDYAQAAKOLf/3H2iQRMeh4AAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "source": "R display func"
    }
   ],
   "source": [
    "plot(1, type = \"n\")\n",
    "showtext_begin()\n",
    "text(1, 1.2, \"Let me tell you a story\", cex = 3, family = \"newrocker\")\n",
    "text(1, 0.8, \"Long long ago...\", cex = 3, family = \"cutetumblr\")\n",
    "showtext_end()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example 2\n",
    "\n",
    "This one works. We write the plot to a PNG file and then load it with `IRdisplay::display_png()`.\n",
    "\n",
    "Is there a way to get this behavior by default for the automatically printed plots?\n",
    "\n",
    "I wonder if it is possible to use showtext with jupyter seamlessly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<strong>png:</strong> 2"
      ],
      "text/latex": [
       "\\textbf{png:} 2"
      ],
      "text/markdown": [
       "**png:** 2"
      ],
      "text/plain": [
       "png \n",
       "  2 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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BKggCABCggSoIAgAQoIEqCAIAEKCBKggCABCggSoIAgAQoIEqCAIAEKCBKggCAB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\noIAgAQoIEqDg/wFI4n7QPavlvwAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data",
     "source": "R display func"
    }
   ],
   "source": [
    "png(\"showtext-ex2.png\", width = 7, height = 7, units = \"in\", res = 120)\n",
    "plot(1, type = \"n\")\n",
    "showtext_begin()\n",
    "text(1, 1.2, \"Let me tell you a story\", cex = 4, family = \"newrocker\")\n",
    "text(1, 0.8, \"Long long ago...\", cex = 4, family = \"cutetumblr\")\n",
    "showtext_end()\n",
    "dev.off()\n",
    "IRdisplay::display_png(file=\"showtext-ex2.png\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}