Massachusetts Institute of Technology

15 Vassar Street, 48-316
Jan 30 - Feb 1, 2014
9:00 am - 4:30 pm

About

Instructors: Aron Ahmadia, Randy Olson

What: Our goal is to help scientists and engineers become more productive by teaching them basic computing skills like program design, version control, testing, and task automation. In this two-day bootcamp, short tutorials will alternate with hands-on practical exercises. Participants will be encouraged both to help one another, and to apply what they have learned to their own research problems during and between sessions. Attendants are offered online office hours: regular events to get one-on-one help from Software Carpentry instructors, online.

Who: The course is aimed at postgraduate students and other scientists who are familiar with basic programming concepts (like loops, conditionals, arrays, and functions) but need help to translate this knowledge into practical tools to help them work more productively.

Requirements: Participants must bring a laptop with a few specific software packages installed. (The list will be sent to participants a week before the bootcamp.)

Content: The syllabus for this bootcamp will include:

using the shell to do more in less time
using version control to manage and share information
basic Python programming
how (and how much) to test programs
documentation and debugging

Contact: Please mail aron@ahmadia.net for more information.

Bootcamp materials

Bootcamp materials can be downloaded here: https://github.com/geocarpentry/2014-01-30-mit/archive/gh-pages.zip

Etherpad

Etherpad can be reached here: https://etherpad.mozilla.org/2014-01-30-mit

Agenda

This agenda may be subject to change.

Day 1
08:00-09:00	Setup Help
09:00-09:30	Introduction and Overview	Aron Ahmadia
09:30-10:30	Automating Your Actions (Shell Part 1)	Aron Ahmadia
10:30-10:45	Break
10:45-12:00	Automating Your Actions (Shell Part 2)	Randy Olson
12:00-13:00	Lunch Break
13:00-13:30	IPython and IPython Notebook Orientation	Aron Ahmadia
13:30-14:45	Numerical Analysis with NumPy	Aron Ahmadia
14:45-15:00	Break
15:00-16:30	Python Programming and Analysis	Randy Olson
17:30-19:30	Boot camp reception	Parsons kitchen on the 3rd floor of building 48
Day 2
08:00-09:00	Office Hour
09:00-09:30	Introduction to Distributed Version Control	Aron Ahmadia
09:30-10:30	Accessing and Creating Software History (Git Part 1)	Aron Ahmadia
10:30-10:45	Break
10:45-12:00	Sharing and Collaborating with GitHub (Git Part 2)	Aron Ahmadia
12:00-13:00	Lunch Break
13:00-14:30	Modularization and Documentation in Python	Randy Olson
14:30-14:45	Break
14:45-16:00	Plotting with matplotlib and Basemap	Randy Olson
16:00-16:30	Boot camp wrap-up	Randy Olson and Aron Ahmadia
Day 3
08:00-09:00	Office Hour
09:00-10:30	Application Vignette 1	Aron Ahmadia
10:30-10:45	Break
10:45-12:00	Application Vignette 2	Randy Olson

Setup

To participate in this Software Carpentry bootcamp, you will need working copies of:

The Bash Shell

Bash is a commonly-used shell. Using a shell gives you more power to do more tasks more quickly with your computer.

Git

Git is a state-of-the-art version control system. It lets you track who made changes to what when and has options for easily updating a shared or public version of your code on github.com.

Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words.

Python

Python is becoming more and more popular in scientific computing, and it's a great language for teaching general programming concepts due to its easy-to-read syntax. We will be using Python version 2.7. Installing all the scientific packages for Python individually can be a bit difficult, so we recommend using an all-in-one installer.

The instructions for installing each of these components is organized below by operating system.

MacOSX

Mac OS X / Bash

The default shell in all versions of Mac OS X is bash, so no need to install anything. You access bash from the Terminal (found in /Applications/Utilities). You may want to keep Terminal in your dock for this workshop.

Mac OS X / Editor

We recommend Text Wrangler or Sublime Text.

Mac OS X / Git

Installing Git may require you to first install XCode. This is a very large download (several gigabytes), so please do it before arriving at the bootcamp.

For Mac OS X 10.7 and higher:

Go to the Xcode website. Get XCode from the App Store making certain to install the command line tools (from the Download preferences pane). Git is included in the command line tools.

For Mac OS X 10.6

If you have Mac OS X 10.6, first get XCode by going to the Apple developer site. You have to sign in with an Apple ID linked to a Developer account. If you don't have one, you can register and create one. Once you log in, go to page 8 and find "XCode 3.2.6 and iOS SDK 4.3 for Snow Leopard". Click to open that section, and then download the .dmg file. Finally, install just git.

Mac OS X / Python

We recommend the all-in-one scientific Python installer Anaconda. (Installation requires using the shell and if you aren't comfortable doing the installation yourself just download the installer and we'll help you at the boot camp.)

Download the installer that matches your operating system and save it in your home folder.
Open a terminal window.
Type
```
bash Anaconda-
```
and then press tab. The name of the file you just downloaded should appear.
Press enter. You will follow the text-only prompts. When there is a colon at the bottom of the screen press the down arrow to move down through the text. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).

Windows

Windows / Git Bash

Install Git for Windows by downloading and running the installer. This will provide you with both Git as well as Bash in the Git Bash program.

Windows / Editor

Notepad++ is a popular free code editor for Windows.

Windows / Anaconda Python

We recommend the all-in-one scientific Python installer Anaconda.
Use all of the defaults for installation.

Windows / Software Carpentry Installer

Finally, there is an optional script for installing the nano editor. Please install this after Anaconda and Git Bash

Download the installer.
If the file opens directly in the browser select File→Save Page As to download it to your computer.
(You may need to restart Windows first if this doesn't work). Double click on the file to run it.

Linux

Linux / Bash

The default shell is usually bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Linux / Git

If Git is not already available on your machine you can try to install it via your distro's package manager (e.g. apt-get).

Linux / Editor

Kate is one option for Linux users.

Linux / Python

Download the installer that matches your operating system and save it in your home folder.
Open a terminal window..
Type
```
bash Anaconda-
```
and then press tab. The name of the file you just downloaded should appear.
Press enter. You will follow the text-only prompts. When there is a colon at the bottom of the screen press the down arrow to move down through the text. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).

Reference Guides

Useful Links

Instructors

Aron Ahmadia is a Hydrological Engineer for the U.S. Army Corps of Engineers. Aron is known for his work at the intersection of applied mathematics, software engineering, and application domains as diverse as adaptive optics, semiconductor lithography, and ice-sheet modeling. He enjoys teaching collaborative development of robust, reproducible, and scalable software tools for computational science.

Randy Olson is a Computer Science graduate research assistant at Michigan State University in Dr. Chris Adami's lab specializing in artificial intelligence, artificial life, and evolutionary computation. He runs a research blog where he writes about scientific computing, data visualization, evolution, and AI. Randy is an ardent advocate of open science and regularly travels the U.S. to teach researchers scientific computing skills at Software Carpentry workshops.