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"
    }
   },
   "cell_type": "markdown",
   "id": "unlikely-monkey",
   "metadata": {
    "toc-hr-collapsed": false
   },
   "source": [
    "![jsc-logo.jpg](attachment:67258d94-84e6-4a0c-ae8f-c74332ec082e.jpg)\n",
    "Author: [Jens Henrik Göbbert](mailto:j.goebbert@fz-juelich.de)\n",
    "------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "recorded-shame",
   "metadata": {
    "toc-hr-collapsed": false
   },
   "source": [
    "# JupyterLab Tour\n",
    "\n",
    "This is the first time you are using JupyterLab? Let us have a look at the user interface and some general concepts.\n",
    "\n",
    "-------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "functioning-yesterday",
   "metadata": {},
   "source": [
    "## What’s Markdown?\n",
    "\n",
    "Markdown is a light markup language with a simple text syntax. Markdown should be easy to write and above all easy to read.\n",
    "John Gruber developed the Markdown language in 2004 in collaboration with Aaron Swartz with the goal of enabling people to \"write in an easy to read and easy to write plain text format and possibly convert it to structurally correct XHTML (or HTML)\".\n",
    "However, one should not assume that \"Markdown\" is a substitute for HTML. HTML is a format for publishing, while Markdown is a format for reading. \n",
    "The syntax of markup is minimal and only applies to a tiny portion of HTML tags. The idea of Markdown is to make it easier to read, write and edit prose, without the intention of creating a syntax that only serves to quickly add HTML tags. Therefore, the formatting syntax of Markdown deals only with questions that can be expressed in plain text.\n",
    "For everything else, use HTML. You don't have to make any preamble or delimitation to indicate that you are switching from Markdown to HTML - you simply use the tags.\n",
    "\n",
    "The following examples start with some simple examples and then show some not so common tricks.\n",
    "Have fun with them!\n",
    "\n",
    "-------------------------------------------------------"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "plastic-religion",
   "metadata": {},
   "source": [
    "#### Exercise 1:\n",
    "Write some markdown with \n",
    "1. italic\n",
    "2. bold\n",
    "3. python code block \n",
    "4. Math (inline formula)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sustained-stock",
   "metadata": {},
   "source": [
    "1. *italic* or _italic_\n",
    "2. **bold** or __bold__\n",
    "3. code block with triple backtick fence\n",
    "```python\n",
    "def function():\n",
    "  pass\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "touched-dollar",
   "metadata": {},
   "source": [
    "#### Exercise 2:\n",
    "The Markdown parser included in the Jupyter Notebook is MathJax-aware. This means that you can freely mix in mathematical expressions using the [MathJax subset of Tex and LaTeX](https://docs.mathjax.org/en/latest/input/tex/). \n",
    "Write mathematical equations in markdown\n",
    "1. inline mode: f(x) = a^2 + b^2 + c^2\n",
    "   - for math that is included within a line or paragraph of text\n",
    "2. display mode: x_\\pm = \\frac{-b \\pm \\sqrt(b^2-4ac)}{2a}\n",
    "   - display mode is for math that is set apart from the main text"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "superb-phone",
   "metadata": {},
   "source": [
    "$f(x) = a^2 + b^2 + c^2$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "random-dryer",
   "metadata": {},
   "source": [
    "$$x_\\pm = \\frac{-b \\pm \\sqrt(b^2-4ac)}{2a}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "olympic-stevens",
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Exercise 2:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "accredited-pulse",
   "metadata": {},
   "outputs": [],
   "source": [
    "from random"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}