Numerical Methods for Partial Differential Equations

This page is prepared to support students attending the tutorial sessions for the course Numerical Methods for Partial Differential Equations. It serves as a place to find weekly hints, short explanations, and useful notes related to the exercise sheets. In the first week, you will find information on installing the required packages and forming homework groups, while in later weeks, the page will include brief guidance that can help with both the theoretical and coding parts of the exercises. The aim is to make it easier to follow the course materials, understand the exercises, and prepare efficiently for each tutorial.

Week 1

Python Environment Setup: Before starting the coding tasks, it is essential to have a properly configured Python environment. Using Conda makes it easy to manage different Python versions, install the required packages, and keep your setup organized without interfering with other projects.

I have prepared a detailed step-by-step guide for setting up Python with Conda. The guide covers everything from installing Conda (Anaconda or Miniconda), creating and activating environments, installing all necessary packages, to verifying that your environment is ready to run Python code. Following these instructions ensures that you can work smoothly on the coding tasks and avoid common setup issues. You can access the full instructions here.

References