The Python programming language is increasingly popular. It is a versatile language for general purpose programming and accessible for novice programmers. However, it is also increasingly used for applications in the domain of scientific computing. This training introduces modules that are useful in that context.
Learning outcomes
When you complete this training you will
- be able to use numpy to represent and compute with multidimensional arrays;
- have an overview of the scope of scipy;
- be able to create data visualizations with matplotlib and bokeh;
- be able to use sympy to do symbolic computations;
- be able to represent and manipulate data in HDF5 format;
- know how to start on an image or video manipulation project.
Schedule
Total duration: 4 hours.
| Subject | Duration |
|---|---|
| introduction and motivation | 5 min. |
| numpy | 80 min. |
| scipy | 25 min. |
| coffee break | 10 min. |
| matplotlib & bokeh | 30 min. |
| sympy | 25 min. |
| HDF5 | 40 min. |
| scikit-image & OpenCV | 20 min. |
| wrap up | 10 min. |
Training materials
Slides are available in the GitHub repository, as well as example code and hands-on material.
Target audience
This training is for you if you need to use Python for scientific computing.
Prerequisites
You will need experience programming in Python. This is not a training that starts from scratch.
If you plan to do Python programming in a Linux or HPC environment you should be familiar with these as well.
Trainer(s)
- Geert Jan Bex (geertjan.bex@uhasselt.be)