pyphi.measures.distribution.intrinsic_difference#
- pyphi.measures.distribution.intrinsic_difference(p, q)[source]#
Compute the intrinsic difference (ID) between two distributions.
This is defined as
\[\max_i \left\{ p_i \log_2 \left( \frac{p_i}{q_i} \right) \right\}\]where \(p_i \log_2 \left( \frac{p_i}{q_i} \right)\) is \(0\) when \(p_i = 0\), and \(+\infty\) when \(p_i > 0\) and \(q_i = 0\).
See the following paper:
Barbosa LS, Marshall W, Streipert S, Albantakis L, Tononi G (2020). A measure for intrinsic information. Sci Rep, 10, 18803. https://doi.org/10.1038/s41598-020-75943-4
- Parameters:
p (np.ndarray) – The first probability distribution.
q (np.ndarray) – The second probability distribution.
- Returns:
float – The intrinsic difference.
- Return type: