- GitHub Repository: http://git.io/bocNDg
- Materials ZipFile: http://git.io/G5i5qA
- Anaconda: https://store.continuum.io/
- In case of no network: grab one of the three USB-Keys
- They read Bruker
- Valentin Haenel from Berlin, Germany
- Freelance software developer and consultant
- Specialise in Git consulting and scientific software tooling
- Acquire data
- Simulation
- Experiment
- Manipulate and process that data
- Visualize results
- Communicate results
- Produce figures for reports or publications
- Write presentations.
- Easy to learn, easy to read, easy to maintain
- Thriving ecosystem of scientific libraries
- Vibrant community
- Numpy and IPython
- Commercial support
- Numpy
- IPython
- Scipy
- Matplotlib
- Pandas
- Sympy
- Scikits-Learn
- PyTables
- Cython
- Ipython (1 hour)
- Using the IPython notebook
- Help system, magic functions, aliases and history
- Numpy (3 hours)
- Basic arrays, dtypes and numerical operations
- Indexing, slicing, reshaping and broadcasting
- Copies, views and fancy indexing
- The tutorial will feature short bursts of small exercises every 5-10 minutes.
- Some of the tutors from the other tutorials are here to help.
- We can have a break in the middle.
- Ipython
- An IPython notebook demonstrating the IPython notebook
- A demo session of the IPython shell
- Numpy (3 hours)
- Two IPython notebooks
- (Semi-)Automatically converted from Python Scientific Lecture Notes
- The generated HTML is included in the GitHub Repository / Zip file and available online
- Grab the IPython notebook, try out the examples, work on the exercises, all from within the notebook.
- Alternatively: view the HTML and copy and paste the examples into an IPython shell or a Python file.
De facto Python interpreter with bells and whistles
Since 2011: available in the browser as IPython notebook:
$ ipython notebook --pylab=inline
- The URL to access the notebook will be printed
- Numpy and Matplotlib tools are available (pylab mode)
- Plots will be displayed inside the notebook (inline mode)