{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.5 グラフを画像ファイルに出力"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Colaboratoryを使う場合には次のセルのコメントを外して(Ctrl+/)実行します"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install plotly==4.10.0\n",
    "# !wget https://github.com/plotly/orca/releases/download/v1.2.1/orca-1.2.1-x86_64.AppImage -O /usr/local/bin/orca\n",
    "# !chmod +x /usr/local/bin/orca\n",
    "# !apt-get install xvfb libgtk2.0-0 libgconf-2-4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "fig = go.Figure([go.Scatter(x=[1, 2, 3], y=[5, 3, 2])])\n",
    "fig.write_image(\"fig1.png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "\n",
    "img_bytes = fig.to_image(format=\"png\")\n",
    "Image(img_bytes)"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Raw Cell Format",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}