Python for MATLAB users – 2015
Welcome to this workshop on Python programming intended for researchers familiar with MATLAB. The course includes basic as well as advanced topics in Python programming. No previous knowledge in Python is necessary. The course will take place at KTH, Stockholm and is free of charge.
The course includes the following basic topics:
- Numerical computation with NumPy, SciPy and matplotlib
- Using the Jupyter notebook
- Object oriented programming in Python
- Testing numerical code with unit tests
We will also attempt to cover the following more advanced topics:
This is a SeSE-workshop (not a regular SeSE-course) and will not give you any ECTS credits.
The workshop will take place 7–8 December at KTH. We will meet on Monday morning at 09:15, at the Mathematics department, Floor 7, seminar room 3721
Monday 7 December
09:15-11:45, Lecture – Mathematics department, Floor 7, seminar room 3721
13:15-16:30, Exercises – Mathematics department, Floor 4, room 3434
Tuesday 8 December
09:15-11:45, Lecture – Mathematics department, Floor 7, seminar room 3721 We meet at the street floor of the math department (Lindstedtsvägen 25) at 09:10.
13:15-16:30, Faxen seminar room, Mechanics department
- Bisection method (Solution)
- Random polynomials (Solution)
- Frequency Response (Solution)
- Derivator (Solution)
Please contact the lecturer Olivier Verdier for further information.
Before attending the course, you should install Python for scientific computing, in order to be able to do the exercises. Please install Python from the anaconda distribution. You should download the Python 3.4 version.
You can then check that the installation works properly by following these steps:
- Fire up a terminal, and issue the following command:
- You should now be in an IPython session in your favorite web browser. Press the “New” button, and choose “Python 3” in the menu.
- You should now be inside a new notebook. Choose the first cell, and paste the following code:
%pylab %matplotlib inline for i in range(5): plot(cumsum(randint(2, size=1000) - .5), alpha=.7)
Now press Shift+return.
You should see a graph appearing in the cell, just below the Python code you just entered.
Please contact me if any of those steps do not work as expected.