Appendix_00_Notebook_Tour.ipynb

{
 "metadata": {
  "name": "Appendix_00_Notebook_Tour"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This material is included with permission from IPython documentation available online from: https://github.com/ipython/ipython-in-depth"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# A brief tour of the IPython notebook\n",
      "\n",
      "This document will give you a brief tour of the capabilities of the IPython notebook.  \n",
      "You can view its contents by scrolling around, or execute each cell by typing `Shift-Enter`.\n",
      "After you conclude this brief high-level tour, you should read the accompanying notebook \n",
      "titled `01_notebook_introduction`, which takes a more step-by-step approach to the features of the\n",
      "system.  \n",
      "\n",
      "The rest of the notebooks in this directory illustrate various other aspects and \n",
      "capabilities of the IPython notebook; some of them may require additional libraries to be executed.\n",
      "\n",
      "**NOTE:** This notebook *must* be run from its own directory, so you must ``cd``\n",
      "to this directory and then start the notebook, but do *not* use the ``--notebook-dir``\n",
      "option to run it from another location.\n",
      "\n",
      "The first thing you need to know is that you are still controlling the same old IPython you're used to,\n",
      "so things like shell aliases and magic commands still work:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pwd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 1,
       "text": [
        "u'/Users/minrk/dev/ip/mine/docs/examples/notebooks'"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ls"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "00_notebook_tour.ipynb          callbacks.ipynb                 python-logo.svg\r\n",
        "01_notebook_introduction.ipynb  cython_extension.ipynb          rmagic_extension.ipynb\r\n",
        "Animations_and_Progress.ipynb   display_protocol.ipynb          sympy.ipynb\r\n",
        "Capturing Output.ipynb          formatting.ipynb                sympy_quantum_computing.ipynb\r\n",
        "Script Magics.ipynb             octavemagic_extension.ipynb     trapezoid_rule.ipynb\r\n",
        "animation.m4v                   progbar.ipynb\r\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "message = 'The IPython notebook is great!'\n",
      "# note: the echo command does not run on Windows, it's a unix command.\n",
      "!echo $message"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "The IPython notebook is great!\r\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Plots with matplotlib"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "IPython adds an 'inline' matplotlib backend,\n",
      "which embeds any matplotlib figures into the notebook."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
        "For more information, type 'help(pylab)'.\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = linspace(0, 3*pi, 500)\n",
      "plot(x, sin(x**2))\n",
      "title('A simple chirp');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
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AvfZOHEif98nAzd7RrfRlITV8VlYWNmzYgCuvvBLJZBJ33XUX5s+fj40bNwIA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\nkL6BgYHBGML/B3suibfww4xPAAAAAElFTkSuQmCC\n"
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You can paste blocks of input with prompt markers, such as those from\n",
      "[the official Python tutorial](http://docs.python.org/tutorial/interpreter.html#interactive-mode)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      ">>> the_world_is_flat = 1\n",
      ">>> if the_world_is_flat:\n",
      "...     print \"Be careful not to fall off!\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Be careful not to fall off!\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Errors are shown in informative ways:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%run non_existent_file"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "ERROR: File `u'non_existent_file.py'` not found."
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = 1\n",
      "y = 4\n",
      "z = y/(1-x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "ZeroDivisionError",
       "evalue": "integer division or modulo by zero",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mZeroDivisionError\u001b[0m                         Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-8-dc39888fd1d2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      2\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m4\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 3\u001b[1;33m \u001b[0mz\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m-\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;31mZeroDivisionError\u001b[0m: integer division or modulo by zero"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "When IPython needs to display additional information (such as providing details on an object via `x?`\n",
      "it will automatically invoke a pager at the bottom of the screen:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "magic"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Non-blocking output of kernel\n",
      "\n",
      "If you execute the next cell, you will see the output arriving as it is generated, not all at the end."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time, sys\n",
      "for i in range(8):\n",
      "    print i,\n",
      "    time.sleep(0.5)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "0 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "2 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "3 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "4 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "5 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "6 "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "7\n"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Clean crash and restart\n",
      "\n",
      "We call the low-level system libc.time routine with the wrong argument via\n",
      "ctypes to segfault the Python interpreter:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sys\n",
      "from ctypes import CDLL\n",
      "# This will crash a Linux or Mac system; equivalent calls can be made on Windows\n",
      "dll = 'dylib' if sys.platform == 'darwin' else '.so.6'\n",
      "libc = CDLL(\"libc.%s\" % dll) \n",
      "libc.time(-1)  # BOOM!!"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": "*"
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Markdown cells can contain formatted text and code\n",
      "\n",
      "You can *italicize*, **boldface**\n",
      "\n",
      "* build\n",
      "* lists\n",
      "\n",
      "and embed code meant for illustration instead of execution in Python:\n",
      "\n",
      "    def f(x):\n",
      "        \"\"\"a docstring\"\"\"\n",
      "        return x**2\n",
      "\n",
      "or other languages:\n",
      "\n",
      "    if (i=0; i<n; i++) {\n",
      "      printf(\"hello %d\\n\", i);\n",
      "      x += 4;\n",
      "    }"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Courtesy of MathJax, you can include mathematical expressions both inline: \n",
      "$e^{i\\pi} + 1 = 0$  and displayed:\n",
      "\n",
      "$$e^x=\\sum_{i=0}^\\infty \\frac{1}{i!}x^i$$"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Rich displays: include anyting a browser can show\n",
      "\n",
      "Note that we have an actual protocol for this, see the `display_protocol` notebook for further details.\n",
      "\n",
      "### Images"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Image\n",
      "Image(filename='../../source/_static/logo.png')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "png": 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       "prompt_number": 1,
       "text": [
        "<IPython.core.display.Image at 0x10faeafd0>"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "An image can also be displayed from raw data or a url"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Image(url='http://python.org/images/python-logo.gif')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<img src=\"http://python.org/images/python-logo.gif\" />"
       ],
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "<IPython.core.display.Image at 0x1060e7410>"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "SVG images are also supported out of the box (since modern browsers do a good job of rendering them):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import SVG\n",
      "SVG(filename='python-logo.svg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 3,
       "svg": [
        "<svg height=\"115.02pt\" id=\"svg2\" inkscape:version=\"0.43\" sodipodi:docbase=\"/home/sdeibel\" sodipodi:docname=\"logo-python-generic.svg\" sodipodi:version=\"0.32\" version=\"1.0\" width=\"388.84pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:cc=\"http://web.resource.org/cc/\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:inkscape=\"http://www.inkscape.org/namespaces/inkscape\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\" xmlns:sodipodi=\"http://inkscape.sourceforge.net/DTD/sodipodi-0.dtd\" xmlns:svg=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n",
        "  <metadata id=\"metadata2193\">\n",
        "    <rdf:RDF>\n",
        "      <cc:Work rdf:about=\"\">\n",
        "        <dc:format>image/svg+xml</dc:format>\n",
        "        <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n",
        "      </cc:Work>\n",
        "    </rdf:RDF>\n",
        "  </metadata>\n",
        "  <sodipodi:namedview bordercolor=\"#666666\" borderopacity=\"1.0\" id=\"base\" inkscape:current-layer=\"svg2\" inkscape:cx=\"243.02499\" inkscape:cy=\"71.887497\" inkscape:pageopacity=\"0.0\" inkscape:pageshadow=\"2\" inkscape:window-height=\"543\" inkscape:window-width=\"791\" inkscape:window-x=\"0\" inkscape:window-y=\"0\" inkscape:zoom=\"1.4340089\" pagecolor=\"#ffffff\"/>\n",
        "  <defs id=\"defs4\">\n",
        "    <linearGradient id=\"linearGradient2795\">\n",
        "      <stop id=\"stop2797\" offset=\"0\" style=\"stop-color:#b8b8b8;stop-opacity:0.49803922\"/>\n",
        "      <stop id=\"stop2799\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient2787\">\n",
        "      <stop id=\"stop2789\" offset=\"0\" style=\"stop-color:#7f7f7f;stop-opacity:0.5\"/>\n",
        "      <stop id=\"stop2791\" offset=\"1\" style=\"stop-color:#7f7f7f;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient3676\">\n",
        "      <stop id=\"stop3678\" offset=\"0\" style=\"stop-color:#b2b2b2;stop-opacity:0.5\"/>\n",
        "      <stop id=\"stop3680\" offset=\"1\" style=\"stop-color:#b3b3b3;stop-opacity:0\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient3236\">\n",
        "      <stop id=\"stop3244\" offset=\"0\" style=\"stop-color:#f4f4f4;stop-opacity:1\"/>\n",
        "      <stop id=\"stop3240\" offset=\"1\" style=\"stop-color:#ffffff;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient4671\">\n",
        "      <stop id=\"stop4673\" offset=\"0\" style=\"stop-color:#ffd43b;stop-opacity:1\"/>\n",
        "      <stop id=\"stop4675\" offset=\"1\" style=\"stop-color:#ffe873;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient id=\"linearGradient4689\">\n",
        "      <stop id=\"stop4691\" offset=\"0\" style=\"stop-color:#5a9fd4;stop-opacity:1\"/>\n",
        "      <stop id=\"stop4693\" offset=\"1\" style=\"stop-color:#306998;stop-opacity:1\"/>\n",
        "    </linearGradient>\n",
        "    <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2987\" x1=\"224.23996\" x2=\"-65.308502\" xlink:href=\"#linearGradient4671\" y1=\"144.75717\" y2=\"144.75717\"/>\n",
        "    <linearGradient gradientTransform=\"translate(100.2702,99.61116)\" gradientUnits=\"userSpaceOnUse\" id=\"linearGradient2990\" x1=\"172.94208\" x2=\"26.670298\" xlink:href=\"#linearGradient4689\" y1=\"77.475983\" y2=\"76.313133\"/>\n",
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       ],
       "text": [
        "<IPython.core.display.SVG at 0x10fb998d0>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#### Embedded vs Non-embedded Images"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "As of IPython 0.13, images are embedded by default for compatibility with QtConsole, and the ability to still be displayed offline.\n",
      "\n",
      "Let's look at the differences:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# by default Image data are embedded\n",
      "Embed      = Image(    'http://scienceview.berkeley.edu/view/images/newview.jpg')\n",
      "\n",
      "# if kwarg `url` is given, the embedding is assumed to be false\n",
      "SoftLinked = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg')\n",
      "\n",
      "# In each case, embed can be specified explicitly with the `embed` kwarg\n",
      "# ForceEmbed = Image(url='http://scienceview.berkeley.edu/view/images/newview.jpg', embed=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Today's image from a webcam at Berkeley, (at the time I created this notebook). This should also work in the Qtconsole.\n",
      "Drawback is that the saved notebook will be larger, but the image will still be present offline."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "Embed"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
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+lASoKhSUc4oCA1M0AM+tDNAHPGaG6oAbsVCc1RQpNAmhAZoE0KLm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JsEjY4wSD5ZrN0s+s9D9PaXqHQ/Ul3rd9ds/i313vAgg+nw8Rs7qAQSuMHO0epxzknJKK/3Nc1D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\n3prgmYlQfpOQMHkmuDVMI//Z\n",
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "<IPython.core.display.Image at 0x10fb99b50>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Today's image from same webcam at Berkeley, (refreshed every minutes, if you reload the notebook), visible only with an active internet connexion, that should be different from the previous one. This will not work on Qtconsole.\n",
      "Notebook saved with this kind of image will be lighter and always reflect the current version of the source, but the image won't display offline."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "SoftLinked"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<img src=\"http://scienceview.berkeley.edu/view/images/newview.jpg\" />"
       ],
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<IPython.core.display.Image at 0x10fb99b10>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Of course, if you re-run the all notebook, the two images will be the same again."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Video"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And more exotic objects can also be displayed, as long as their representation supports \n",
      "the IPython display protocol.\n",
      "\n",
      "For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other\n",
      "hosted content is trivial):"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import YouTubeVideo\n",
      "# a talk about IPython at Sage Days at U. Washington, Seattle.\n",
      "# Video credit: William Stein.\n",
      "YouTubeVideo('1j_HxD4iLn8')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "\n",
        "            <iframe\n",
        "                width=\"400\"\n",
        "                height=\"300\"\n",
        "                src=\"http://www.youtube.com/embed/1j_HxD4iLn8\"\n",
        "                frameborder=\"0\"\n",
        "                allowfullscreen\n",
        "            ></iframe>\n",
        "        "
       ],
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "<IPython.lib.display.YouTubeVideo at 0x10fba2190>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Using the nascent video capabilities of modern browsers, you may also be able to display local\n",
      "videos.  At the moment this doesn't work very well in all browsers, so it may or may not work for you;\n",
      "we will continue testing this and looking for ways to make it more robust.  \n",
      "\n",
      "The following cell loads a local file called  `animation.m4v`, encodes the raw video as base64 for http\n",
      "transport, and uses the HTML5 video tag to load it. On Chrome 15 it works correctly, displaying a control\n",
      "bar at the bottom with a play/pause button and a location slider."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "video = open(\"animation.m4v\", \"rb\").read()\n",
      "video_encoded = video.encode(\"base64\")\n",
      "video_tag = '<video controls alt=\"test\" src=\"data:video/x-m4v;base64,{0}\">'.format(video_encoded)\n",
      "HTML(data=video_tag)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<video controls alt=\"test\" src=\"data:video/x-m4v;base64,AAAAHGZ0eXBNNFYgAAACAGlzb21pc28yYXZjMQAAAAhmcmVlAAAqiW1kYXQAAAKMBgX//4jcRem9\n",
        "5tlIt5Ys2CDZI+7veDI2NCAtIGNvcmUgMTE4IC0gSC4yNjQvTVBFRy00IEFWQyBjb2RlYyAtIENv\n",
        "cHlsZWZ0IDIwMDMtMjAxMSAtIGh0dHA6Ly93d3cudmlkZW9sYW4ub3JnL3gyNjQuaHRtbCAtIG9w\n",
        "dGlvbnM6IGNhYmFjPTEgcmVmPTMgZGVibG9jaz0xOjA6MCBhbmFseXNlPTB4MzoweDExMyBtZT1o\n",
        "ZXggc3VibWU9NyBwc3k9MSBwc3lfcmQ9MS4wMDowLjAwIG1peGVkX3JlZj0xIG1lX3JhbmdlPTE2\n",
        "IGNocm9tYV9tZT0xIHRyZWxsaXM9MSA4eDhkY3Q9MSBjcW09MCBkZWFkem9uZT0yMSwxMSBmYXN0\n",
        "X3Bza2lwPTEgY2hyb21hX3FwX29mZnNldD0tMiB0aHJlYWRzPTEgc2xpY2VkX3RocmVhZHM9MCBu\n",
        "cj0wIGRlY2ltYXRlPTEgaW50ZXJsYWNlZD0wIGJsdXJheV9jb21wYXQ9MCBjb25zdHJhaW5lZF9p\n",
        "bnRyYT0wIGJmcmFtZXM9MyBiX3B5cmFtaWQ9MiBiX2FkYXB0PTEgYl9iaWFzPTAgZGlyZWN0PTEg\n",
        "d2VpZ2h0Yj0xIG9wZW5fZ29wPTAgd2VpZ2h0cD0yIGtleWludD0yNTAga2V5aW50X21pbj0yNSBz\n",
        "Y2VuZWN1dD00MCBpbnRyYV9yZWZyZXNoPTAgcmNfbG9va2FoZWFkPTQwIHJjPWNyZiBtYnRyZWU9\n",
        "MSBjcmY9MjMuMCBxY29tcD0wLjYwIHFwbWluPTAgcXBtYXg9NjkgcXBzdGVwPTQgaXBfcmF0aW89\n",
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        "\">"
       ],
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "<IPython.core.display.HTML at 0x10fba28d0>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Local Files\n",
      "\n",
      "The above examples embed images and video from the notebook filesystem in the output\n",
      "areas of code cells.  It is also possible to request these files directly in markdown cells\n",
      "if they reside in the notebook directory via relative urls prefixed with `files/`:\n",
      "\n",
      "    files/[subdirectory/]<filename>\n",
      "\n",
      "\n",
      "For example, in the example notebook folder, we have the Python logo, addressed as:\n",
      "\n",
      "    <img src=\"files/python-logo.svg\" />\n",
      "\n",
      "<img src=\"/files/python-logo.svg\" />\n",
      "\n",
      "and a video with the HTML5 video tag:\n",
      "\n",
      "    <video controls src=\"files/animation.m4v\" />\n",
      "\n",
      "<video controls src=\"/files/animation.m4v\" />\n",
      "\n",
      "These do not embed the data into the notebook file,\n",
      "and require that the files exist when you are viewing the notebook.\n",
      "\n",
      "### Security of local files\n",
      "\n",
      "Note that this means that the IPython notebook server also acts as a generic file server\n",
      "for files inside the same tree as your notebooks.  Access is not granted outside the\n",
      "notebook folder so you have strict control over what files are visible, but for this\n",
      "reason it is highly recommended that you do not run the notebook server with a notebook\n",
      "directory at a high level in your filesystem (e.g. your home directory).\n",
      "\n",
      "When you run the notebook in a password-protected manner, local file access is restricted\n",
      "to authenticated users unless read-only views are active."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### External sites\n",
      "\n",
      "You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia\n",
      "page for mobile users:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>"
       ],
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "<IPython.core.display.HTML at 0x1094900d0>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Mathematics\n",
      "\n",
      "And we also support the display of mathematical expressions typeset in LaTeX, which is rendered\n",
      "in the browser thanks to the [MathJax library](http://mathjax.org).  \n",
      "\n",
      "Note that this is *different* from the above examples.  Above we were typing mathematical expressions\n",
      "in Markdown cells (along with normal text) and letting the browser render them; now we are displaying\n",
      "the output of a Python computation as a LaTeX expression wrapped by the `Math()` object so the browser\n",
      "renders it.  The `Math` object will add the needed LaTeX delimiters (`$$`) if they are not provided:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Math\n",
      "Math(r'F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "$$F(k) = \\int_{-\\infty}^{\\infty} f(x) e^{2\\pi i k} dx$$"
       ],
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "<IPython.core.display.Math at 0x10fba26d0>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "With the `Latex` class, you have to include the delimiters yourself.  This allows you to use other LaTeX modes such as `eqnarray`:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import Latex\n",
      "Latex(r\"\"\"\\begin{eqnarray}\n",
      "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
      "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
      "\\end{eqnarray}\"\"\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{eqnarray}\n",
        "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
        "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0 \n",
        "\\end{eqnarray}"
       ],
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<IPython.core.display.Latex at 0x10fba2c10>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Or you can enter latex directly with the `%%latex` cell magic:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%latex\n",
      "\\begin{aligned}\n",
      "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
      "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
      "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
      "\\end{aligned}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "latex": [
        "\\begin{aligned}\n",
        "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{E}} & = 4 \\pi \\rho \\\\\n",
        "\\nabla \\times \\vec{\\mathbf{E}}\\, +\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{B}}}{\\partial t} & = \\vec{\\mathbf{0}} \\\\\n",
        "\\nabla \\cdot \\vec{\\mathbf{B}} & = 0\n",
        "\\end{aligned}"
       ],
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.Latex at 0x10a617c90>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There is also a `%%javascript` cell magic for running javascript directly,\n",
      "and `%%svg` for manually entering SVG content."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Loading external codes\n",
      "* Drag and drop a ``.py`` in the dashboard\n",
      "* Use ``%load`` with any local or remote url: [the Matplotlib Gallery!](http://matplotlib.sourceforge.net/gallery.html)\n",
      "\n",
      "In this notebook we've kept the output saved so you can see the result, but you should run the next\n",
      "cell yourself (with an active internet connection)."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's make sure we have pylab again, in case we have restarted the kernel due to the crash demo above"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
        "For more information, type 'help(pylab)'.\n"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%load http://matplotlib.sourceforge.net/mpl_examples/pylab_examples/integral_demo.py"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#!/usr/bin/env python\n",
      "\n",
      "# implement the example graphs/integral from pyx\n",
      "from pylab import *\n",
      "from matplotlib.patches import Polygon\n",
      "\n",
      "def func(x):\n",
      "    return (x-3)*(x-5)*(x-7)+85\n",
      "\n",
      "ax = subplot(111)\n",
      "\n",
      "a, b = 2, 9 # integral area\n",
      "x = arange(0, 10, 0.01)\n",
      "y = func(x)\n",
      "plot(x, y, linewidth=1)\n",
      "\n",
      "# make the shaded region\n",
      "ix = arange(a, b, 0.01)\n",
      "iy = func(ix)\n",
      "verts = [(a,0)] + zip(ix,iy) + [(b,0)]\n",
      "poly = Polygon(verts, facecolor='0.8', edgecolor='k')\n",
      "ax.add_patch(poly)\n",
      "\n",
      "text(0.5 * (a + b), 30,\n",
      "     r\"$\\int_a^b f(x)\\mathrm{d}x$\", horizontalalignment='center',\n",
      "     fontsize=20)\n",
      "\n",
      "axis([0,10, 0, 180])\n",
      "figtext(0.9, 0.05, 'x')\n",
      "figtext(0.1, 0.9, 'y')\n",
      "ax.set_xticks((a,b))\n",
      "ax.set_xticklabels(('a','b'))\n",
      "ax.set_yticks([])\n",
      "show()\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 16
    }
   ],
   "metadata": {}
  }
 ]
}