8.s05 Setup.ipynb

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    "# Setting Up Python and Jupyter\n",
    "\n",
    "## Install Python (Via Conda)\n",
    "----------\n",
    "\n",
    " \n",
    "It's simplest to install python using `conda` . This will allow you to have a sandboxed environment, with a separate copy of python and any packages needed for the class. The only downside is this approach can be a bit heavy on using hard drive space. If you already have python and need to minimize disk usage, see instructions below for installing jupyter within an existing python install (not recommended). If you already have `conda` , skip ahead to setting up a sandboxed environment. \n",
    "\n",
    "Installing conda is straightforward for Windows, Linux, or OSX by heading to the conda website (https://docs.conda.io/projects/conda/en/latest/user-guide/install/) and following instructions for Miniconda with Python 3.X (3.9 when writing this). Miniconda skips installing a large number of default packages that would come with the Anaconda option. It is okay to install conda even if you have installed python another way (e.g. for another class), since it will just shadow other installations, and we will set it to only do so after you run a terminal command. Check that your install worked by opening a new terminal. On Linux or OSX this is accessible through the Terminal app, whereas on Windows you should use the (newly-installed) Anaconda Prompt. You should see `(base)` in front of the terminal prompt. Running the following commands should show similar results:\n",
    "\n",
    "```\n",
    "    (base) gkanwar@direct-sample:~$ which python        # Linux/OSX only\n",
    "    /Users/gkanwar/miniconda3/bin/python\n",
    "    (base) gkanwar@direct-sample:~$ conda list\n",
    "    # packages in environment at /Users/gkanwar/miniconda3 [... a few packages ...] \n",
    "    (base) gkanwar@direct-sample:~$ python -V Python 3.9.1\n",
    "```\n",
    "\n",
    "This installation is now your default python. I prefer to make this installation *opt-in*, so that you can only access it within a terminal session after explicitly activating it (**NOTE**: this is probably unnecessary on **Windows**, since you are using the Anaconda Prompt). To do so, set the global configuration to not automatically enable this environment by running:\n",
    "\n",
    "\n",
    "     conda config ---set auto_activate_base false\n",
    "\n",
    "If you open a new terminal, you should no longer see `(base)`. Running `which python` should no longer show the miniconda path. Instead, you should either see a path to whatever python you previously had installed, or nothing.\n",
    "\n",
    "Whenever you want to use python, you will need to run `conda activate <some environment name>` . Right now you just have the `base` environment. Let's set up an environment specifically for this class.\n",
    "\n",
    "\n",
    "## Create a sandboxed environment\n",
    "----------\n",
    "At its core, the main purpose of Python virtual environments is to create an isolated environment for Python projects. This means that each project can have its own dependencies, regardless of what dependencies every other project has.\n",
    "\n",
    "Python and python packages are always updating so many coding projects may require the use of previous versions of packages or downgraded versions of python (e.g Python 2.7). To prevent issues from conflicting versions/dependencies it is recommended that every python project be worked on in a *seperate environment*. \n",
    "\n",
    "For each project you can make a new environment with the required version of Python and then install the needed packages in said environment. \n",
    "\n",
    "We will make an environment called 8.s05 with Python 3.9 installed:\n",
    "\n",
    "     conda create --name 8.s05 python=3.9\n",
    "\n",
    "Anything you install in this environment will not be accessible until the environment is activated by running `conda activate 8.s05`. For now let’s check that the environment works. \n",
    "\n",
    "\n",
    "    gkanwar@direct-sample:~$ conda activate 8.s05\n",
    "    (8.s05) gkanwar@direct-sample:~$ which python # Linux/OSX only\n",
    "    /Users/gkanwar/miniconda3/envs/8.s05/bin/python(8.s05) \n",
    "    gkanwar@direct-sample:~$ python -V\n",
    "    Python 3.9.1\n",
    "\n",
    "After activating the environment `(8.s05)` appears in the front of the prompt. That’s how you know your environment is activated and all packages are available. If you need to get out of the environment either run `conda deactivate` or quit the terminal. \n",
    "\n",
    "\n",
    "## Install Packages\n",
    "----------\n",
    "\n",
    " We will use a few numerical packages that support efficient manpulation of data arrays. We also use Jupyter to create notebooks and run our code. \n",
    " Activate the 8.s05 environment, if it’s not already active:\n",
    " `conda activate 8.s05` \n",
    " Install packages: \n",
    " `conda install matplotlib numpy scipy jupyter`\n",
    " \n",
    "**Conda-Forge**\n",
    "Some important python packages are managed by [Conda-Forge](https://conda-forge.org/), a GitHub organization containing repositories of conda recipes. Adding Conda-Forge as a channel will pull from the Conda-Forge repository when searching for packages. \n",
    "\n",
    "\n",
    "    conda config --add channels conda-forge\n",
    "    conda config --set channel_priority strict\n",
    "\n",
    "You will need to use `gwpy` for the LIGO lab and `uproot` for the Jet Substructure lab, both of which can be installed through Conda-Forge. \n",
    "\n",
    "    conda install -c conda-forge uproot\n",
    "    conda install -c conda-forge gwpy\n",
    "## Install Packages Without Conda (not recommended)\n",
    "----------\n",
    "\n",
    "If you followed the section above, skip this. If you have python and don’t want to install `conda`, you can still install the packages via another package manager, such as `pip`. The needed packages are `matplotlib`, `numpy`, `scipy`,  `jupyter`,`gwpy` and `uproot`. \n",
    "\n",
    "## A First Jupyter Notebook\n",
    "----------\n",
    "\n",
    "Let’s check that everything works. As a reminder, the following commands should be run in the terminal (Linux/OSX) or Anaconda Prompt (Windows). \n",
    "\n",
    "\n",
    "- Start up the jupyter notebook service by running `jupyter notebook`. This will open up a tab in your default browser with the Jupyter interface. \n",
    "- In the interface, navigate to a directory where you want to store your notebook files. \n",
    "- In the top right, select `New > Python 3` \n",
    "- Click on `Untitled` and give the notebook a useful name, like `First 8.s05 Notebook`. This determines the name of the file in which the notebook contents are saved. \n",
    "- In the first “cell” (gray box in the main area), enter a python command, e.g. `print(``\"``Hello, world!``\"``)`. \n",
    "- Hit Shift+Enter to execute the cell. You should see `Hello, world!` printed below the cell. \n",
    "\n",
    "We can do something a bit more interesting in our second cell. \n",
    "You should see a plot of a sine function appear, like below!"
   ]
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   "execution_count": 3,
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   "outputs": [
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "xs = np.linspace(-np.pi,np.pi,num=100)\n",
    "ys = np.sin(xs)\n",
    "plt.plot(xs,ys)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "**Retina Screens**\n",
    "\n",
    "On Retina screens (e.g. if you have a semi-recent Macbook), the plot is unbearably blurry by default. I recommend adding a cell at the very top to tell jupyter to make a more crisp plot: \n",
    "\n",
    "- Click in the first cell, then `Insert > Insert Cell Above`, giving a fresh cell at the very top.\n",
    "- Enter and run the following in that cell: \n",
    "     %config InlineBackend.figure format = 'retina'\n",
    "- Now re-make the plot by selecting the cell with the sine plot by hitting Shift+Enter again.\n",
    "\n",
    "**Wrap Up**\n",
    "\n",
    "Feel free to play around and see what you can do in this jupyter notebook! Make sure to save your work by hitting Ctrl-s / Cmd-s or `File > Save and Checkpoint`. \n",
    "\n",
    "Once you are finished, it’s a good idea to terminate your Jupyter session so it doesn’t run in the background. Closing the browser is not good enough, you need to kill the process running in the original terminal where you ran `jupyter notebook`. You can kill this process in one of two ways.\n",
    "\n",
    "\n",
    "1. Find the original tab by Jupyter and click `Quit` in the top right. \n",
    "2. Find the original terminal in which you ran the command, hit Ctrl-c then y+Enter to confirm. \n",
    "\n",
    "You can then close out of all browser tabs. \n",
    "\n",
    "**Additional Resources**\n",
    "\n",
    "Install wget for easier downloading of files for LIGO: https://www.gnu.org/software/wget/"
   ]
  }
 ],
 "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": 4
}