Training course: "Scientific Python"
(Course no. 53/2011 in the training programme of Forschungszentrum Jülich)
Instructors: | Dr. Olav Zimmermann, Dr. Jan Meinke, JSC |
Contents: | Python is being increasingly used in scientific computing as it is easy to make changes and explore new ideas. The course will begin with an overview of NumPy and SciPy and then work along examples targeted at people interested in Python's capabilities and potential applications in their fields. Many Python packages support scientific computing. NumPy provides functionality for working with arrays. SciPy contains functionality for performing common tasks on these arrays, for example linear algebra, optimisation, numerical integration, and much more. Matplotlib is used to produce publication-quality plots. The course will begin with an overview of NumPy and SciPy and then work along examples targeted at people interested in Python's capabilities and potential applications in their fields. |
Duration: | 3 days |
Date: | 10-12 October 2011, 09:00 - 16:30 |
Venue: | Ausbildungsraum 1, Jülich Supercomputing Centre, building 16.3, room 021 |
Registration: | A minimum of 5 participants is required. Please register with Dr. Olav Zimmermann |
The course will be structured as follows:
Day 1:
- When to use Python?
- SciPy/NumPy overview
- Working with NumPy arrays and matrices
- The SciPy modules
Day2:
- Matplotlib
- Integration with other languages (C/C++, Fortran).
Day 3:
- Depending on the audience the third day will be either dedicated to Life Science applications (e.g. BioPython, MMTK) or interfacing GPUs (pyOpenCL)
This course is aimed at scientists who wish to explore the productivity gains made possible by Python. The course is taught in English.
Basic experience in Python such as provided by the “Einführung in Python” course given by Rebecca Breu is assumed.