algorithms.entropy

Module: algorithms.entropy

Functions

nitime.algorithms.entropy.conditional_entropy(x, y)

The conditional entropy H(X|Y) = H(Y,X) - H(Y). X conditioned on Y

nitime.algorithms.entropy.entropy(*X)

Calculate the entropy of a variable, or joint entropy of several variables.

Parameters:

X : array, or list of arrays

Variable or variables to compute entropy/joint entropy on

Notes

This function can be used to calculate the entropy of a single variable (provided as a single input) or to calculate the joint entropy between two variables (provided as a series of inputs)

nitime.algorithms.entropy.entropy_cc(x, y)

The entropy correlation coefficient:

p(H) = sqrt(MI(X, Y) / 0.5 * (H(X) + H(Y)))

nitime.algorithms.entropy.mutual_information(x, y)

The mutual information between two variables

MI(X, Y) = H(X) + H(Y) - H(X | Y)

Parameters:x, y : array Returns:array : mutual information between x and y

nitime.algorithms.entropy.transfer_entropy(x, y, lag=1)

Transfer entropy for two given signals.

Parameters:

x : array

source

y : array

target

lag : int

Returns:

array : Transfer entropy from x to y