PyInform is a python library of information-theoretic measures for time series data. PyInform is backed by the Inform C library.

The library is built out of three primary components.

1. The pyinform.dist.Dist class provides discrete, emperical probability distributions. These form the basis for all of the information-theoretic measures.

2. A collection of information measures built upon the distribution class provide the core algorithms for the library and are implemented in the pyinform.shannon submodule.

3. A host of measures of information dynamics on time series are built upon the core information measures. Each measure is housed in its own submodule, but are exposed for convenience by the root packge, pyinform.

In addition to the core components, a small collection of utilities are provided by the pyinform module.

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