About the course

This course was originally written by Thomas Robitaille, and was adapted by Markus Demleitner, Robert Schmidt, and myself.

The web page for this course is [https://www.lsw.uni-heidelberg.de/users/hludwig/teaching/pycourse/].

The lecturer is Hans-G. Ludwig. You can contact me during the course and at H.Ludwig@lsw.uni-heidelberg.de

Topics

  • Using the IPython Notebook
  • Introduction to Python
  • Modules and Functions
  • Introduction to Numpy and Matplotlib
  • Reading/writing data from files
  • Introduction to Scipy (interpolation, integration, fitting)
  • Object-oriented programming
  • Applying Python to scientific problems ( always on ones mind )

Structure

The block course lasts five days, and each day will follow this schedule:

  • 9:00-10:30 - lecture/exercises
  • 10:30-11:00 - break
  • 11:00-12:30 - lecture/exercises
  • 12:30-13:30 - break for lunch
  • 13:30-14:30 - lecture/exercises
  • 14:30-17:00 - computer pool available to finish homework

The lectures will be mixed with exercise sessions - from time to time I will give you 5 or 10 minutes to complete a given task/exercise. I shall post the solutions of these exercises each day around 16:00 so that you can check your own soliutions.

There will be problem sets during the week, and you will be required to hand these in a deadline indicated on the problem sheet. An average of 60% in the problem sets will be required to obtain 2 credits points at the end of the course. Each participants has to hand in her/his own solution. There is no mandatory presence at the course. The successful participation will be judged based on the handed-in solutions.

The course will be given in English.

I am happy to review or talk about your code/solutions to exercises.

Solutions to problem sheets

All solutions should be submitted as IPython (/Jupyter) notebooks or python programs (one notebook/program per problem set). Please use a filename that contains the name of the problem sheet and your name in the form problemX_familyname.ipynb.

The files should be mailed to Marta Reina-Campos at reina.campos@uni-heidelberg.de.

The following criteria are taken into account for grading problem sets - the notebook/program should:

  • run with no errors under python3
  • produce the correct results
  • be clearly readable, and include text to explain what you are doing and why
  • not include any unused code! (-> readability)
  • be well presented

Please make use of the ability to add comments and text around your code. Make it so that someone not familiar with the problem could read it and understand your solution. If I/O is performed think about the environment in shich the notebook needs to be executed.

There is never a unique solution to a problem, so it does not matter if your programs do not look the same as somebody else's! What matters most is that you get a chance to make mistakes and learn from them.

Policy on handing in solutions

Problem set submissions need to be handed in separately for each participant.

The deadlines for the Problem Sets are:

Problem Set 1 Wednesday, February 15th 7pm CEST

Problem Set 2 Friday, February 17th 7pm CEST

Problem Set 3 Friday, February 24st 7pm CEST

Laptops

If you would like to use Python on your laptop, you have several possibilities:

  • If you have a linux laptop and are familiar with package managers, most major scientific Python packages are available through these
  • Otherwise, try and install the Anaconda Python distribution

Getting set up

Lecture Notes

You can download the notebooks I'm showing, the problem sets and the ancillary data files from here

You can dowload the individual files as we go along.

Just refresh your notebook viewer after you've downloaded a file.

CIP Pool

Before you can run Python in the ways described on this page, you will need to start up a command-line Terminal application. In the CIP pool this is located in the Anwendungen -> Zubehör -> Terminal menu.

To ensure a common environment, in the CIP pool we'll be using an updated version of ipython over what is installed on the machines themselves. To use that, you have to manipulate your path. Here is one way to do that:

 echo "export PATH=/local/py4sci/anaconda3/bin:$PATH" >> ~/.bashrc
 exec bash

You only need to do that once.

Then fetch the notebooks and execute the notebook player (optionally in a subdirectory):

ipython3 notebook

A web browser should open and you should be ready to go.