We are pleased to announce that Inform, a cross-platform C library for information-theoretic analysis of dynamical systems, is now in print (doi: 10.3389/frobt.2018.00060). Inform uses high-level wrappers, including Python and R, to expedite the application of information theory to dynamical systems without sacrificing performance.
Inform easily converts time series observations into distributions and has a huge repertoire of information measures that can be applied to these distributions, including Shannon Entropy, Mutual Information, Transfer Entropy, and Active Information - to name just a few. Application of Inform is extremely simple. For example, using PyInform, we can compute the Active Information of a dynamical series in a single line of code:
To download inform and see the full list of Inform functions visit the documentation at https://elife-asu.github.io/Inform/.
Sara Imari Walker