The code belonging to this thesis is split into 5 jupyter notebooks:
DetectCascades: the main file, which computes system-level events, cascades, frequent paths, etc. It uses (almost all the other files)
Events: contains functionality for computing system-level events, cascades, frequent paths
Thresholds: contains all functionality for computing thresholds (including jenks)
Plotting: contains all functionality regarding plotting performance spectra
PlotPerformanceSpectrum: in this notebook, some example plots are shown. Uses the Plotting notebook
In addition to this, there are 2 Python files which are used by the notebooks:
Constants.py: contains all constants (segments, abbreviations, etc) used trhoughout the project
PerformanceSpectrum.py: contains all code needed to plot a performance spectrum (almost completely derived from Tom van Meers work: https://github.com/tomvmeer/PF4PY)