scipy.special.entr#

scipy.special.entr(x, out=None) = <ufunc 'entr'>#

Elementwise function for computing entropy.

\[\begin{split}\text{entr}(x) = \begin{cases} - x \log(x) & x > 0 \\ 0 & x = 0 \\ -\infty & \text{otherwise} \end{cases}\end{split}\]
Parameters:
xndarray

Input array.

outndarray, optional

Optional output array for the function values

Returns:
resscalar or ndarray

The value of the elementwise entropy function at the given points x.

Notes

New in version 0.15.0.

This function is concave.

The origin of this function is in convex programming; see [1]. Given a probability distribution \(p_1, \ldots, p_n\), the definition of entropy in the context of information theory is

\[\sum_{i = 1}^n \mathrm{entr}(p_i).\]

To compute the latter quantity, use scipy.stats.entropy.

References

[1]

Boyd, Stephen and Lieven Vandenberghe. Convex optimization. Cambridge University Press, 2004. DOI:https://doi.org/10.1017/CBO9780511804441