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    "# Introduction\n",
    "\n",
    "This is a practical guide to using Python to read and analyse data from IRIS. It is meant to complement the existing [IRIS documentation](http://iris.lmsal.com/documents.html) and, in particular, the [Online Guide to IRIS Data Analysis (ITN 26)](http://iris.lmsal.com/itn26/)."
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   "source": [
    "## Why low-level?\n",
    "\n",
    "This guide focuses on using simple and efficient methods to read IRIS data, and does not make use of higher-level abstractions or IRIS-specific packages such as [IRISpy](http://docs.sunpy.org/projects/irispy/en/latest/) or [SunPy](http://sunpy.org/). The motivation is two-fold: to detail a \"barebones\" interface when no other packages are available or performance is the goal, and to provide a simple guide while IRISpy is not mature enough and its API changes quickly."
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    "## Requirements\n",
    "\n",
    "To follow this guide only standard python scientific packages are necessary:\n",
    "\n",
    "* Numpy\n",
    "* Scipy\n",
    "* Matplotlib\n",
    "\n",
    "In addition, [Astropy](http://www.astropy.org/) is necessary for its FITS reader and WCS module.\n",
    "\n",
    "The recommended way to install all these packages is through the [Anaconda Python Distribution](https://www.anaconda.com/download). Once you have Anaconda installed, you can make sure you have all you need by running:\n",
    "\n",
    "```\n",
    "conda install numpy scipy matplotlib astropy \n",
    "```\n",
    "\n",
    "If you want to follow this tutorial using Jupyter (optional), you should also include the packages `jupyterlab` and `ipympl` above, and build the Jupyter lab extensions with:\n",
    "\n",
    "```\n",
    "jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib\n",
    "```\n",
    "\n",
    "<div class=\"alert alert-info\">\n",
    "This guide is written for Python 3. It may not work under Python 2.x.\n",
    "</div>"
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   "source": [
    "## How to use this guide\n",
    "\n",
    "This guide is written in [Jupyter notebook](https://jupyter.org/) format. On the top right corner of each page you find a link \"View page source\". If you save that file (and remove the last `.txt` extension), you can open the page in Jupyter and interact with the data. Alternatively, you can also type the commands here on the normal python console or in `ipython`. Some setup commands such as `%matplotlib inline` only make sense if you are running Jupyter. "
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