Tutorials

Though the easiest way to get started with the library is to use the script simulation_temp.py (to scan using a single temperature parameter) or simulation_traj.py (to scan using a different parametrization), we include two jupyter notebooks to show the basic usage of the library. In particular, we show the case of the analytical Marchenko-Pastur distribution and the case of the empirical distribution of the eigenvalues of a random matrix.

For more information on the scripts, you can use python <script> --help to get the definition of all command line parameters. Notice that numerical results will be saved in a SQLite database (path provided by the user from command line): you should foresee a utility to explore such database for further processing.