ESC202:Spring 2021: Monday Zoom Lecture: 13:00-14:00 Exercises: 14:00-17:00 in MS-Teams

TAs: Stefan Schafroth and Sebastian Schulz

Dear Students, Communication will take place via this web-site, including assignments. Video lectures are provided below and the pdf of the lecture notes can be found here. The lectures will use Zoom and the assignments session will use MS-Teams as in the last semester. Many thanks!

Joachim Stadel

Videos for the lectures can be found here (they are too large for my Wiki):

ESC202 Video downloads

22. Feb. 2021: Tree Structures and Dimensional Searching

In order to qualify for the final semester project and a passing grade you will need to hand in 80% satisfactory assignments (to the satisfaction of the TAs). Assignments should be individual and should be in python and provide a correct virtual environment!

For help getting started with virtual environments, please read carefully Python Virtual Environments for Pip and Python Virtual Environments for Conda.

You should email 3 things to Sebastian (sebastian.schulz@uzh.ch):

1. The working python source code
2. The requirements.txt file for your virtual environment
3. A .pdf or .png image or animation of the output of your program

Template: template.zip

Instructions:

Please add the names of the people you work together (if you do) to the comment section of your python scripts.

Create a virtual environment using

Pip

- run virtualenv yourenv_name to create a virtual environment

- run source yourenv_name/bin/activate to activate yourenv_name

- install necessary libraries that you want using pip install package_name

- work in that directory, get your outputs (*.pdf, *.png, *jpeg, *.mp4, etc…)

- run pip freeze > requirements.txt to get your list of libraries

Conda

- run conda create -n yourenvname python=x.x anaconda to create a virtual environment

- run source activate yourenvname to activate yourenv_name

- install necessary libraries that you want using conda install -n yourenv_name package_name

- work in that directory, get your outputs (*.pdf, *.png, *jpeg, *.mp4, etc…)

- run conda list –export > requirements.txt to get your list of libraries

1.k-Nearest Neighbors algorithm (you can set k=8 or other values to test). You should check the code via direct computation (O(N^2)). Solution is expected to include a priority queue over the 8 NN particles, but could also explore the use of a further prioq over the nearest cells during the treewalk as discussed in the lecture.