RISE-Demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## <center>RISE</center>\n",
    "## <center>Turn your notebooks into slideshows</center>\n",
    "<center><em>Use jupyter to create a slideshow</em></center>\n",
    "\n",
    "\n",
    "Use the space bar to advance to the next slide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Goals\n",
    "- Turn an existing Jupyter notebook into a slide show\n",
    "- Use Jupyter to create a slide show - *It does not have to start out as a notebook*\n",
    "- Embed executable code into slides\n",
    "- Add images to slides\n",
    "- Even embed youtube videos!\n",
    "\n",
    "Shift-Space to go backward, Space to go forward"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Slide types - Slide Show Domain"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Slide - A normal slide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Sub-Slide - A slide that is \"below\" the previous slide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Fragment - A piece of a slide that appears on the existing slide"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Skip - A cell that will not appear in the slide show"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Notes - A slide that shows up in the presenter view only\n",
    "  - press \"t\" to see the presenter notes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "If you pressed \"t\", you will now see the presenter view."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This slide combined a slide cell and 6 fragments"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "This cell will NOT appear in the slide show because it is designed to be skipped."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Cell Types - Jupyter Notebook Domain"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Code - Contains code in some language that will be executed by a kernel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Jup ter and RISE - reveal.js work really well together\n",
      "Note - don't forget to fix this bug.\n"
     ]
    }
   ],
   "source": [
    "# Shift-Enter to execute this code\n",
    "print('Jup ter and RISE - reveal.js work really well together')\n",
    "print(\"Note - don't forget to fix this bug.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Markdown - A cell that is formatted \n",
    "  - Generally consistently with GitHub markdown syntax\n",
    "  - Can contain some embedded HTML syntax\n",
    "  "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Markdown - A cell that is formatted \n",
    "  - Generally consistently with GitHub markdown syntax\n",
    "  - Can contain some embedded HTML syntax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- Raw NBConvert\n",
    "  - Displayed as is. \n",
    "  - Not executable, though it might look like code.\n",
    "  - Not formatted.\n",
    "  - Used above to show how markdown looks before executing it."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Documentation for RISE\n",
    "[ReadTheDocs for RISE](https://rise.readthedocs.io/en/latest/index.html)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The docs tell you two ways to install it locally and how to use it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Hello world'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# press Shift-Enter to execute this code\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.ion()\n",
    "\n",
    "\"Hello world\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# of course you can show figures\n",
    "\n",
    "def polynom(x):\n",
    "    return 2 * x**2 - 20 * x + 2\n",
    "\n",
    "X = np.linspace(-10, 10)\n",
    "Y = polynom(X)\n",
    "plt.plot(X, Y);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e9b55aad5ed04407a63094e2cc6c8fcd",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=0.0, description='offset', max=10.0, min=-10.0, step=0.25), Output()),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# and everything works as usual\n",
    "\n",
    "# an animation to illustrate \n",
    "# translation by variable change\n",
    "from ipywidgets import interact, FloatSlider\n",
    "\n",
    "def parabolic(offset):\n",
    "    X = np.linspace(-10, 10)\n",
    "    Y = polynom(X-offset)\n",
    "    # use same y scale for all offsets\n",
    "    plt.gca().set_ylim([-100, 500])\n",
    "    plt.plot(X, Y);\n",
    "    \n",
    "interact(parabolic, \n",
    "         offset=FloatSlider(min=-10., max=10.,\n",
    "                           step=0.25));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### How do we use the notebook to set up slides?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### Step 1\n",
    "- View, Cell Toolbar, Slideshow\n",
    "- This should create a selection for each cell\n",
    "- Two ways to view an image\n",
    "\n",
    "\n",
    "![menu](images/ViewMenu.png \"title\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<img src=\"files/images/ViewMenu.png\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Step 2\n",
    "  - Select the slide types to meet the needs of your slide show\n",
    " \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### Step 3\n",
    "- Run the slide show to see what we have so far.\n",
    "- Click on the first cell then\n",
    "- Click on the Enter/Exit RISE Slideshow icon in the menu bar far right or Alt-R\n",
    "- Click on space bar to advance through the slides"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### This is a sub-slide\n",
    "- Navigate to it with the space bar, or \n",
    "- click the down arrow on the bottom left when running the show."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "A key feature is that the slide show does not need to be static.\n",
    "We can even add some code that is too big for a slide, and execute it.\n",
    "If the code or output is too \"tall\" we will have a scroll bar."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Let's display some mathematical equations\n",
    "\n",
    "\n",
    "### Maxwell's Equations\n",
    "\n",
    "\\begin{align}\n",
    "\\nabla \\times \\vec{\\mathbf{B}} -\\, \\frac1c\\, \\frac{\\partial\\vec{\\mathbf{E}}}{\\partial t} & = \\frac{4\\pi}{c}\\vec{\\mathbf{j}} \\\\   \\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{align}\n",
    "\n",
    "\n",
    "### The probability of getting (k) heads when flipping (n) coins is\n",
    "\n",
    "\\begin{equation*}\n",
    "P(E)   = {n \\choose k} p^k (1-p)^{ n-k}\n",
    "\\end{equation*}\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "heads occured 52 times.\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "\n",
    "n     = 100\n",
    "heads = 0\n",
    "for _ in range(n):\n",
    "    if random.randint(0, 1) == 1:\n",
    "        heads += 1\n",
    "print(f'heads occured {heads} times.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "heads occured 56 times.\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "\n",
    "n     = 100\n",
    "heads = 0\n",
    "for _ in range(n):\n",
    "    if random.randint(0, 1) == 1:\n",
    "        heads += 1\n",
    "print(f'heads occured {heads} times.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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\n",
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"400\"\n",
       "            height=\"300\"\n",
       "            src=\"https://www.youtube.com/embed/CUpwLhZh66A\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.YouTubeVideo at 0x7fbe9d8e85c0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.lib.display import YouTubeVideo\n",
    "YouTubeVideo('CUpwLhZh66A')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "Notes - the need for speed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Mig-28 observed in a 4G negative dive - classified."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# That's all folks!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "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": "3.7.3"
  },
  "rise": {
   "autolaunch": true,
   "enable_chalkboard": true,
   "scroll": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}