These are a series of interactive worksheets for exploring complex mathematical concepts in chemistry. These worksheets must be run using the new web-based notebook interface to IPython, which is an advanced, interactive interpreter for the Python programming language. IPython was specifically designed for interactive, scientific data analysis and simulation, so it is an ideal tool for exploring mathematical concepts related to chemistry. In it's original incarnation, IPython was designed to be run from inside a terminal or command prompt window; however, the newest releases have a web-based notebook like interface that allows not only for interactive code generation but also textual markup that can be used to explain the code workings.
The main point of these notebooks is to teach mathematical concepts related to chemistry. With that in mind, large portions of the underlying Python code have been abstracted from the main worksheet. Some small amount of code has been left in to allow students to interactively modify variable values to explore the changes in simulated data.
A secondary goal of these notebooks is to teach Python programming as a powerful method of data analysis, so the abstracted code is contained in Python program files (ending in .py) contained in the individual notebook folders. These files are simple text files that can be read with any text editor. Students that are interested in learning more about how the data is actually manipulated are encouraged to explore these files on their own. A number of Python programming tutorials are available on the web; however, many are geared towards computer scientists and programmers. The Scientific Python Lecture Notes are a continually-evolving tutorial geared toward scientists interested in learning Python and some third-party libraries in the context of scientific work. In addition, several interactive Python tutorials are contained in this download; however, these will not be as comprehensive as other tutorials on the web.
These notebooks are organized into folders according to their area of application. The Python script 'run_notebook.py' starts the IPython notebook server from the folder that it is located. This alleviates the need to understand the command line instructions necessary to navigate to a particular folder and start the IPython notebook. Just drop a copy of this script into the desired folder and run it with Python. The method to run the script will be a little different depending on your operating system and installation method. (If double-clicking the icon doesn't work. Try right-clicking on the icon. There may be an option to "Run with..." where you can choose the Python interpreter.)
These notebooks don't require any installation, per se. However, in order to run them, you will need a minimal install of the newest releases of Python 2, Numpy, Matplotlib, Scipy, and IPython with all their associated dependencies. This installation method can be quite time consuming, but installation instructions and binary installers for each package can be found from their respective websites.
By far, the easiest way to install the necessary packages is to use one of the prepackaged options for your operating system, such as Python(x,y) (Windows), Canopy (all OSes, this is also from Enthought and is effectively the next-gen EPD, use this first if possible), Enthought Python Distribution (EPD, all OSes), or Anaconda (all OS, broken uninstaller for Windows as of v1.2.1).
Some specific installation notes are provided here for reference.
The Enthought Python Distribution (EPD) has a very convenient package management system, enpkg, which allows you to update packages with a few simple commands. The only gotcha is that you must use sudo when executing these commands on on a Mac/Linux.
Jonathan March at Enthought has a nice article in the Enthought Knowledge Base that describes how to update packages using this function.
Fernando Perez, the original author of IPython, has a short webpage devoted to Python for scientific applications, which contains a variety of installation notes.
This is a collection of pitfalls that have been encountered in installing and running these notebooks.
Older version of IE and very old versions of Firefox are not supported by IPython. You should use the newest versions of Firefox or Chrome for the best results.
These notebooks can be downloaded from GitHub as a zip package. The zip package must be explicitly extracted for the IPython notebook to function properly.
Antivirus software may try to block the IPython notebook software. If you run a notebook cell and it hangs for a very long time, then you may be having these issues. As a test, open a new notebook and type 'print "hello"' in the first cell. Try running the cell with Shift-Enter. If the notebook hangs at this point, then your antivirus software may be to blame.
- Sophos on Windows: (You must be an administrator on your computer. If not, talk to your IT people.) Click the Windows icon in the lower left. Type 'services.msc' in the search bar (or in 'Run...' on Windows XP), and run this process. Stop 'Sophos Web Control Service' and 'Sophos Web Intelligence Service'. Restart the IPython Notebook and you should be all set.