LAST OCCURENCE :Friday, February 1, 2019
This workshop is intended for people wishing to use Python for numerical simulations and data analysis. It will present in detail the computational core of the “scientific Python ecosystem”, the NumPy and SciPy packages.
The workshop is given in English (questions in French possible) by Dr. Robert Cimrman and Prof. Ales Janka.
NumPy package enhances the Python language with powerful n-dimensional array data-structure allowing fast vectorized numerical computations. SciPy is a collection of domain-specific numerical algorithms built on NumPy (e.g. for data-analysis, numerical optimization, advanced linear algebra, differential equations..)
- Knowledge of the Python syntax.
- Ability to write simple scripts in your favorite editor/IDE.
After the course, the participant will:
- have good knowledge of the NumPy package (manipulation with basic data structures) and a good orientation in SciPy’s functionality,
- know how to plot data using Matplotlib,
- know the best practices for combining NumPy and SciPy into a fast Python code for solving a typical scientific computing task (reading data, numerical processing, visualization, writing results, reporting).
- gain hands-on experience with IPython shell,
- be able to use Jupyter notebook.
- Introduction to the NumPy and SciPy packages.
- Manipulating arrays (vectors, matrices) in NumPy.
- Basic operations and functions:
- File I/O (scipy.io)
- Fourier Transforms and Signal Processing
- Linear Algebra (linear systems, eigenvalue problems)
- Sparse matrices, graphs and meshes
- Matplotlib visualization
The participants are requested to bring their own laptops. (Please, contact us if it is not possible.)
A compilation of course materials (lecture notes, Jupyter notebook exercises, cheat sheats, etc.) is here
The maximum number of participants is 18.
The participation fee is 500 CHF / 400 CHF for Swiss Engineering-section Fribourg members.