[ French version ]
Course (CDFT1-03) proposed by the doctoral school.
This module is intended for people who want to learn the python language, in order to use it for their research work
This course is composed of five 3-hours sessions :
~1.5 sessions of introduction to Python (base objects and instructions, using the command line, reading/writing files,...⁾
~1.5 sessions of introduction to scientific computing with Python (numpy and scipy), graphical display in 1D, 2D (matplotlib) and 3D (mayavi and mlab)
2 sessions for a "personal project", during which each person can write or expand a Python program as a function of his/her interests: bring you own data and analyse them, use a Python library developed in your lab, etc...
The room in which this training takes place is equipped with windows computers: in order to login onto these computers, UJF students must come with their AGALAN login & passwords, which is given with their student card (login can still be done for non-UJF students). However, it is highly recommended to bring your own laptop during this training, so that you can continue working when you get back to your lab.
If you bring your own laptop, please first install a complete Python distribution, including scientific librairies. Do not install python from the pyton.org website, because it does not include all the scientific libraries, and it is best to install everything in a single package.
- for Windows:
Python(x,y) (free, open-source, very complete)
or Enthought Python Distribution (free for academics only, open-source).
Anaconda (untested but popular, with python 2.7 and 3.4 versions)
- for MacOSX:
Most Python libraries (scipy,numpy, mayavi) are available through macports - I strongly recommend this even if installation takes time.
Enthought Python Distribution (free for academics only, open-source)
Anaconda (untested but popular, with python 2.7 and 3.4 versions)
- for Linux:
install at least the following packages (exact names may vary according to the exact brand): python, ipython, scipy, numpy, kwrite, kate, matplotlib, mayavi (or mayavi2)
Documents for the training :
The training will take place at the IRMA tower:
access map: http://www-lmc.imag.fr/Contact/goToCampus.html
Access to the training room is by going to the back of the tower, as shown below:
