The notion of the ‘tipping point’, whereby a trend suddenly builds up unstoppable momentum, is widely known after Malcolm Gladwell popularized the concept in his book of the same name.
Knowing when something is about to tip however has proved rather tricky to do. A team of German researchers believe they’ve developed a tool that can do just that however.
Predicting the tipping point
The tool, which is documented in a recently published paper, aims to unify complex network theory and nonlinear time series analysis. This approach is important as most complex systems, whether weather patterns or financial markets, are inherently nonlinear in nature.
“Pyunicorn works like a macroscope, [which], if used the right way, allows to distill the essence of information from a network or time series data,” the researchers say.
The tool has numerous applications, such as being able to identify critical elements in the network, such as bottlenecks, as well as helping to spot tipping points in systems.
The system was developed in partnership with collaborators at PIK, Humboldt University Berlin, the Stockholm Resilience Centre, Institute for Marine and Atmospheric Research Utrecht, University of Aberdeen and Nishny Novgorod State University, located respectively in Germany, Sweden, The Netherlands, the United Kingdom and Russia.
“Many of these methods were newly developed by our team and, moreover, there was a lack of coherent software implementations for existing methods,” the team say. “Pyunicorn was developed to close this gap and to provide an integrative software framework for applying and further developing methods for complex networks and nonlinear time series analysis and their combinations.”
About the tool
Pyunicorn is developed using the open source language Python, and is designed in a modular way to enable it to be as flexible as possible. This adaptability makes it effective in a range of scenarios, including interactive analysis sessions all the way up to huge data analysis efforts conducted on supercomputers.
The aim was always to make the software publicly available, and also as easy to use as possible to encourage a wide range of users to utilize the tool, whether from computer science or medicine, climatology to economics.
“Many of the provided methods were not freely available before to the scientific community, and weren’t available in the flexible and popular Python programming language,” the team say.
The next steps are to try and speed up the code and ensure it works with the Python 3.x platform. It will be interesting to see just how widely adopted the software becomes.
If you’d like to give it a go yourself, you can download the code via GitHub: https://github.com/pik-copan/pyunicorn.
