This repo contains the scripts and data for the 2021 DSEER "Computing for Research" bootcamp. It will be updated frequently with new materials and solutions to past exercises.

1. Check that your environment is setup correctly

• python
• Github
• package manager
• Jupyter notebook
• libraries

2. Create a git repository on your Desktop
3. Check that you've correctly done steps 1 and 2 by running the welcome.ipynb notebook
4. Read through the syllabus

We expect many of you already have many of the tools we will use in this course installed, but please double check each of them. For your reference, they are:

• python 3.6.x or higher
• a Github account + local installation of git
• pip/pip3 and/or conda
• Jupyter notebook
• libraries: numpy, matplotlib, pandas.
  • other libraries will be installed via pip/conda as necessary during class

We recommend using Anaconda to install python, as the conda installer will also automatically configure many of the common python packages and libraries.

To check your python installation: open your command line of choice (cmd.exe on Windows, "Terminal" on MacOS/Linux) and type python --version. Ensure that you are running Python 3.6 or higher.

• depending on your installation -- especially if you are using a Mac -- this may return Python 2.6 or 2.7. if this is the case, try python3 --version
• if this command returns an error, or your python version is earlier than 3.6, follow the instructions linked here to install Anaconda + python

If you do not already have a github account, you should create one here. We recommend using your UChicago email -- students get a Pro account for free. A Pro account is not necessary for this bootcamp, but you may find it helpful for your research in the future.

You can check if git is locally installed by typing git --version into your command line. If you do not have git installed, follow the instructions linked here.

NOTE: if you are on Windows, follow the link above and also install git bash. This is a command line tool that allows you to use bash/zsh commands.

pip/pip3 and conda are package managers -- installation wizards, even. They will allow you to easily install python libraries (homebrew is another popular one, but more difficult to use). If you installed python with Anaconda, both come pre-installed for you. If you did not use Anaconda to install python (or if you have python but don't remember how you installed it), check your pip3 version by typing pip --version or pip3 --version into the command line.

• if this doesn't work, follow the instructions here to install pip
• if this does work, update pip by typing pip3 install --upgrade pip into the command line
  • depending on your local permissions, this command may fail due to administrator preferences. if this is the case, type sudo pip3 install --upgrade pip into the command line, and type the password you use to log in to your computer when prompted

if you have Anaconda but did not just install it, update conda to the latest version by typing conda update conda into the command line.

We will be using Jupyter notebooks for this bootcamp rather than using a text editor to write our scripts. If you just installed Anaconda, then Jupyter notebook comes pre-installed. To check if you have it installed, type jupyter notebook into the command line. If the Jupyter interface opens in your web browser, then it is installed. Otherwise:

• install Jupyter with pip by typing pip3 install jupyter into the command line (use sudo if you run into trouble with permissions)

Once again, if you have just installed python through Anaconda, these libraries have already been added for you. Otherwise, type pip3 list into the command line to list all python libraries you have installed on your computer. Ensure that numpy, matplotlib, and pandas are all listed.

• to install a package you are missing: pip3 install [package]
• to update a package you already have installed:
  • conda: conda update [package]
  • pip: pip3 install [package] --upgrade
  • please make sure that these packages are up-to-date

This will walk you through creating a git repository on your Desktop through your command line. Note: if you are using Windows, you will want to use the git bash command line.

1. Open your command line, and change directories to your Desktop.

• to see your current directory, type pwd
• to change directories, type cd [directory]
• if you would like to see all folders in the current directory, type ls -d */

2. Type git clone https://github.com/NRT-DSEER/computing_for_research_2021.git
3. Type cd computing_for_research_2021 to move into the new folder

0. If you just completed step 3 above, skip this step. Otherwise, open your command line and cd into the git repository for this class
1. Type jupyter notebook. Your terminal will print a bunch of stuff, and then the Jupyter interface should open in your default browser
2. In this browser tab, click on the file named welcome.ipynb and follow the instructions there -- if everything worked, you're ready to go!

The instructors are both on Slack, and if you have any questions for us, please message us there instead of sending an email. Please check your email for the Slack invite; if you don't see it, check your spam folder. Note that Slack is only available for students taking the live version of the course.

• Ander Feistritzer (he/him) - 2nd year master's student, statistics
• Giorgio Sarro (he/him) - 2nd year PhD student, geophysical sciences

Contact over Slack, or attend office hours.

We will meet M-F from 10am-12:30pm CST, from Aug 30 - Sept 10. There will be no class Monday, Sept 6 for Labor Day.

During class, please post in the Slack channel, or DM the TAs, for real-time responses. For help outside of class time, please attend office hours.

The class will be recorded, and the recordings available to you to rewatch, or catch up on a missed class. They will be on UChicago Box; link pending.

Rough outline of the course. Subject to change.

1. review and advanced python

• course mechanics and expectations
• python you should know
• list comprehensions
• classes and objects

2. matplotlib

• matplotlib and containers
• visual clarity; communicating scientific information
• multidimensional plotting

3. linear algebra + numerical methods I

• numpy
• numerical methods

4. linear algebra + numerical methods II

• linear algebra through numpy and scipy

5. RCC + bash scripting

• bash basics
• RCC access, using the VPN, ssh

6. pandas + seaborn I

• basics of pandas
• manipulating dataframes

7. pandas + seaborn II

• applications

8. working with geosci data I

• netCDF
• xarray
• metpy

9. working with geosci data II

• applications

Office Hours Zoom: https://uchicago.zoom.us/j/97595368275?pwd=RU0vZjlDN25Kb3NTZ0NBdGNaN1l2Zz09

• Meeting ID: 975 9536 8275
• Passcode: 432544

September 1, 2021 (Wednesday)

• 11am-12pm CT (Megan)

September 2, 2021 (Thursday)

• 4-5 pm CT (Jonathan)

September 3, 2021 (Friday)

• 2:30-3:30 pm CT (Ian)

September 7, 2021 (Tuesday)

• 1-2 pm CT (Haynes)

September 8, 2021 (Wednesday)

• 1-2 pm CT (Haynes)

September 9, 2021 (Thursday)

• 2-3 pm CT (Megan)

September 10, 2021 (Friday)

• 9-10 am CT (Jonathan)