{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "nbsphinx": "hidden"
   },
   "source": [
    "This notebook is part of the `nbsphinx` documentation: http://nbsphinx.readthedocs.io/."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Code Cells\n",
    "\n",
    "## Code, Output, Streams\n",
    "\n",
    "An empty code cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Two empty lines:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Leading/trailing empty lines:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "# 2 empty lines before, 1 after\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A simple output:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "6 * 7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The standard output stream:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print('Hello, world!')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Normal output + standard output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print('Hello, world!')\n",
    "6 * 7"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The standard error stream is highlighted and displayed just below the code cell.\n",
    "The standard output stream comes afterwards (with no special highlighting).\n",
    "Finally, the \"normal\" output is displayed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "\n",
    "print(\"I'll appear on the standard error stream\", file=sys.stderr, flush=True)\n",
    "print(\"I'll appear on the standard output stream\")\n",
    "\"I'm the 'normal' output\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Special Display Formats\n",
    "\n",
    "See [IPython example notebook](https://nbviewer.jupyter.org/github/ipython/ipython/blob/master/examples/IPython Kernel/Rich Output.ipynb).\n",
    "\n",
    "TODO: tables? e.g. Pandas DataFrame?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Local Image Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "i = Image(filename='images/notebook_icon.png')\n",
    "i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "display(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For some reason this doesn't work with `Image(...)`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import SVG\n",
    "SVG(filename='images/python_logo.svg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Image URLs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Image(url='https://www.python.org/static/img/python-logo-large.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Image(url='https://www.python.org/static/img/python-logo-large.png', embed=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Image(url='http://jupyter.org/assets/nav_logo.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Image(url='https://www.python.org/static/favicon.ico')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Image(url='http://python.org/images/python-logo.gif')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import Math\n",
    "eq = Math(r\"\\int_{-\\infty}^\\infty f(x) \\delta(x - x_0) dx = f(x_0)\")\n",
    "eq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "display(eq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%%latex\n",
    "\\begin{equation}\n",
    "\\int_{-\\infty}^\\infty f(x) \\delta(x - x_0) dx = f(x_0)\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### YouTube Videos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from IPython.display import YouTubeVideo\n",
    "YouTubeVideo('WAikxUGbomY')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unsupported Output Types\n",
    "\n",
    "If a code cell produces data with an unsupported MIME type, the Jupyter Notebook doesn't generate any output.\n",
    "`nbsphinx`, however, shows a warning message."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "display({\n",
    "    'text/x-python': 'print(\"Hello, world!\")',\n",
    "    'text/x-haskell': 'main = putStrLn \"Hello, world!\"',\n",
    "}, raw=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ANSI Colors\n",
    "\n",
    "The standard output and standard error streams may contain [ANSI escape sequences](https://en.wikipedia.org/wiki/ANSI_escape_code) to change the text and background colors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print('BEWARE: \\x1b[1;33;41mugly colors\\x1b[m!', file=sys.stderr, flush=True)\n",
    "print('ABC\\x1b[43mDEF\\x1b[35mGHI\\x1b[1mJKL\\x1b[49mMNO\\x1b[39mPQR\\x1b[22mSTU')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following code showing the 8 basic ANSI colors is based on http://tldp.org/HOWTO/Bash-Prompt-HOWTO/x329.html.\n",
    "Each of the 8 colors has an \"intense\" variation, which is used for bold text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "text = ' XYZ '\n",
    "formatstring = '\\x1b[{}m' + text + '\\x1b[m'\n",
    "\n",
    "print(' ' * 6 + ' ' * len(text) +\n",
    "      ''.join('{:^{}}'.format(bg, len(text)) for bg in range(40, 48)))\n",
    "for fg in range(30, 38):\n",
    "    for bold in False, True:\n",
    "        fg_code = ('1;' if bold else '') + str(fg)\n",
    "        print(' {:>4} '.format(fg_code) + formatstring.format(fg_code) +\n",
    "              ''.join(formatstring.format(fg_code + ';' + str(bg))\n",
    "                      for bg in range(40, 48)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ANSI also supports a set of 256 indexed colors.\n",
    "The following code showing all of them is based on http://bitmote.com/index.php?post/2012/11/19/Using-ANSI-Color-Codes-to-Colorize-Your-Bash-Prompt-on-Linux."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "formatstring = '\\x1b[38;5;{0};48;5;{0}mX\\x1b[1mX\\x1b[m'\n",
    "\n",
    "print('  + ' + ''.join('{:2}'.format(i) for i in range(36)))\n",
    "print('  0 ' + ''.join(formatstring.format(i) for i in range(16)))\n",
    "for i in range(7):\n",
    "    i = i * 36 + 16\n",
    "    print('{:3} '.format(i) + ''.join(formatstring.format(i + j)\n",
    "                                      for j in range(36) if i + j < 256))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can even use 24-bit RGB colors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "start = 255, 0, 0\n",
    "end = 0, 0, 255\n",
    "length = 79\n",
    "out = []\n",
    "\n",
    "for i in range(length):\n",
    "    rgb = [start[c] + int(i * (end[c] - start[c]) / length) for c in range(3)]\n",
    "    out.append('\\x1b['\n",
    "               '38;2;{rgb[2]};{rgb[1]};{rgb[0]};'\n",
    "               '48;2;{rgb[0]};{rgb[1]};{rgb[2]}mX\\x1b[m'.format(rgb=rgb))\n",
    "print(''.join(out))"
   ]
  }
 ],
 "metadata": {
  "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": "3.5.1+"
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 },
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