A collection of jupyter notebooks along with ancillary files.
Several parts of this jupyter demo borrow from the excellent lectures on scientific python by J.R. Johansson. The instructions below can be found in more detail in Lecture 0 of that lecture series.
The best way set-up an scientific Python environment is to use the cross-platform package manager conda from Continuum Analytics. First download and install the Python 3 version of Anaconda. Next, to install the required libraries for these notebooks, simply run:
$ conda install numpy scipy sympy matplotlib jupyter pandas cython ase pymatgen MDAnalysis
This should be sufficient to get a working environment on any platform supported by conda.
In Ubuntu Linux, to install Python 3 and all the requirements for this tutorial run:
$ sudo apt-get install python3-pip
$ sudo -H pip3 install --upgrade scipy numpy sympy matplotlib pandas cython jupyter ase pymatgen MDAnalysis
Although we will be using Python 3 in this tutorial, a similar procedure can be followed for Python 2.
For the section on interfacing python with existing simulation software, please install pycp2k. N.B. You will need to have a cp2k executable installed on your machine.
As a nice continuation with previous tutorials from the MdlS, you can follow this tutorial using Git. To do this simply run:
$ git clone https://github.com/burbanom/PHENIX-lands-upon-Jupyter.git
or download the repository directly.