Introduction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Introduction\n",
    "\n",
    "## Author 1, Author 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Outline\n",
    "\n",
    "1. Theory\n",
    "2. Results\n",
    "3. Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 1. Theory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### 1. 1 Text and formula"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "We can place as many Markdown chunks into the script as needed. They can be used to style and structure the text. \n",
    "The finished script can be rendered to HTML and PDF and the renderer will use a LaTeX-like syntax to render \n",
    "formulas into the document.\n",
    "\n",
    "From the very same script document, we can compile a set of slides. We simply need to adjust for each chunk if it should be a slide on its own, a subslide or fragment of a slide. Alternatively, we can also ignore chunks in case they are just meant to be used in a full featured script document. This chunk is set to be skipped and will not render into slides. Then in the next chunk, we can just place the important stuff."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We can place **styled** *text* here, or even render a formula:\n",
    "$$ E = mc^2$$\n",
    "Formulas can also go $in = li + ne$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### 1.2 Code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "We can also place some Code chunks into the document. They are run at compile time. Let's set up some variables in Octave."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "m =  7800\n",
      "c =  300000000\n"
     ]
    }
   ],
   "source": [
    "m = 78000       % [g]\n",
    "c = 300000000   % [m/s]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 2. Results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "### 2.1 Apply the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We apply the given model:\n",
    "\n",
    "$$ E = mc^2 $$\n",
    "\n",
    "and print the result to the screen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "E =    7.0200e+20\r\n"
     ]
    }
   ],
   "source": [
    "E = m * c^2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### 2.2 Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "What about applying the model to different input values and plotting them?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = [1000 1500 2000 78000 100000 500000];\n",
    "E = m * c^2;\n",
    "\n",
    "figure;\n",
    "plot(m, E, 'x-r');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 3. Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Well, that plot was neither surprising nor impressive. But I hope you got the point how a script like this could be brought to life."
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Octave",
   "language": "octave",
   "name": "octave"
  },
  "language_info": {
   "file_extension": ".m",
   "help_links": [
    {
     "text": "GNU Octave",
     "url": "https://www.gnu.org/software/octave/support.html"
    },
    {
     "text": "Octave Kernel",
     "url": "https://github.com/Calysto/octave_kernel"
    },
    {
     "text": "MetaKernel Magics",
     "url": "https://metakernel.readthedocs.io/en/latest/source/README.html"
    }
   ],
   "mimetype": "text/x-octave",
   "name": "octave",
   "version": "4.2.2"
  }
 },
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}