This repository contains the data and the code for the paper.
Martin Gerlach, Eduardo G. Altmann, Testing Statistical Laws in Complex Systems, Physical Review Letters, to appear (2019).
- get the repository:
git clone https://github.com/martingerlach/testing-statistical-laws-in-complex-systems
- install the following python packages (e.g. via pip):
numpy, scipy, pandas, matplotlib, mpmath, statsmodels
- The folder
code/contains notebooks with the analysis of each Dataset (.ipynb or .html)- Earthquake data:
Analysis_real-data_earthquakes.ipynb - Text Interevent data:
Analysis_real-data_texts-interevent-times.ipynb - Text Frequency-rank data:
Analysis_real-data_texts-rank-frequency.ipynb - Network data:
Analysis_real-data_networks-degree.ipynb - Synthetic data:
Analysis_synthetic-data.ipynb
- Earthquake data:
- The code for all functions can be found in
src/
We analyze several datasets which we included in the repo. They are contained in the folder data/
- Earthquakes: from the Southern California Earthquake Data Center
- Books from Project Gutenberg: from the Standardized Project Gutenberg Corpus
- Networks: KONECT Project: Internet Topology in the folder
data/networks/. The timeseries data for the sequence of degrees is in the folderdata/networks/samplingand was obtained using the code insrc/sampling-nets.py - Synthetic data: The timeseries can be generated using the code in
src/modules_mcmc_zipf.py. There is an example of a correlated timeseries indata/synthetic/ts_synthetic_Ntypes1000_Ntokens100000_alpha1.5_mu0.01_k5