Source code assignments for MAE345 (COS346, ECE345, MAE549).
This repository contains Jupyter notebook assignments for Princeton's MAE345 class. It is organized in the following manner:
- All Jupyter notebooks are placed in the top level directory so they have access to all other Python modules and paths referenced in them are consistent.
- All data provided / collected for use in assignments resides in
data
.
Included in this repository is a conda environment named env-mae345.yml
. For the unfamiliar, conda (short for Anaconda) is a tool for managing Python environments --- collections of software and libraries for developing Python programs. Conda environments make it very easy to reproduce and share code with other developers (in this case between the students and AIs).
To install the environment, do the following:
-
Download and install Anaconda.
-
On Mac and Linux, open the terminal. Navigate to where this repository has been downloaded (entering
ls
will list the files and directories accessible from your current directory andcd <name>
will change you to the<name>
directory) and runconda env create -f env-mae345.yml
. Accept any of the prompted changes. On Windows, do the same, use the Anaconda Prompt application that should be present in your start menu (on Windows you need to usedir
to list the contents of a directory instead ofls
).
To work on an assignment, open the terminal (on Windows you need to use the same Anaconda Prompt application you used to install the environment) and navigate to the directory containing this repository. Enter the command conda activate mae345
to load the environment. Then run either jupyter lab
or jupyter notebook
. Both launch an interface for editing and running Python scripts in your browser. The former is a newer, more featureful interface while the latter is older and straightforward. Follow the instructions within the notebook to complete the assignment.
Submission instructions are included at the end of each notebook file.
As new assignments are released, either download the new files and place them in the folder containing the existing labs, or redownload this repository and replace the existing folder. You do not need to recreate the conda environment.