Ifa 0.2.0

Description:

ifa 0.2.0

Information Flow Analysis=========================IFA is a simple and fast library for information theory research and information flow analysis. It's a Python module written C++, Cython.Installation============Dependencies:* numpyIf you have Cython some cpp files will get regenerated during installation```bash pip install ifa```Or if you want the developmen version:```bash git clone https://github.com/janekolszak/ifa.git; cd ifa; sudo make install;```Usage=====Computing Jensen–Shannon divergence:```python from ifa.distribution import Distribution from ifa.divergence import jsd from numpy.testing import assert_allclose p = Distribution(["A", "B"], [0.5, 0.5]) q = Distribution(["A", "C"], [0.5, 0.5]) assert_allclose(jsd(p, 0.5, q, 0.5), [0.5])```What's inside:==============* Distribution class with some basic operations* Divergences: * Jensen–Shannon divergence * Kullback–Leibler divergence* Functions to compute information flow between distributions