Introduction to Statistical Mechanics in python 3.x, using jupyter notebooks. This repository is part of the University of Milano course Introduzione alla Fisica Statistica.
We will go through the notebooks of each seassion together. Each notebook explores a different topic and proposes some exercises for you to do. There will be some time for you to try the exercises, and we will solve some of them together. You are expected then to solve the rest of exercises on your own.
Please send your solutions no later than the indicated date using the labonline platform.
To follow these lectures, you need a modern installation of python
, together with jupyter
, numpy
, matplotlib
and some other standard python libraries. The simplest way to install all these packages without interfeering with your current python installation is the Anaconda distribution. Choose python 3.x and your OS, download, install, and you should be good to go.
Alternatively, if you cannot install jupyter
on your computer, you can use the mybinder
online environment, which is basically an online version of the repository. Notice that the code will not run on your computer, and that you will loose your work if you close the browser window. To launch the mybinder page for the course, click here!
After completing a notebook, remember to download it to your local computer!
These instructions should work for linux & mac users. Windows users might not be able to execute the
which
command, and might need to install thegit
command beforehand. In case of technical difficulties, please use the binder online environment.
Open a terminal and cd
to a directory of your choice
$ cd Documents
Check that you have correctly installed Anaconda's python.
$ which python
/home/username/anaconda3/bin/python
Clone this repository
$ git clone https://github.com/SZapperi/stat-mech-python-course.git
A new folder called stat-mech-python-course
will be created. Enter it and start jupyter by typing jupyter lab
$ cd stat-mech-python-course
$ jupyter lab
A browser window/tab pointing to localhost:8888
will open automatically. Open the notebooks
folder, then open the first notebook by double-clicking 1-Generating-Random-Numbers.ipynb
. You are ready to go!
Being able to re-use someone else's code is as important as being able to write your own. You are not supposed to figure out everything by yourself, so googling how to X in python is just fine. In addition, some useful resources are:
-
Ask questions
-
Official documentation sites
-
Tutorials
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Windows users
If you need help please write a note in the labonline forum