frites.core.cmi_1d_ggg

frites.core.cmi_1d_ggg(x, y, z, biascorrect=True, demeaned=False)

Conditional MI between two Gaussian variables conditioned on a third.

I = cmi_ggg(x,y,z) returns the CMI between two (possibly multidimensional) Gaussian variables, x and y, conditioned on a third, z, with bias correction.

Parameters:

x, y, znumpy:array_like

Gaussians arrays of shape (n_epochs,) or (n_dimensions, n_epochs).

biascorrectbool | True

Specifies whether bias correction should be applied to the estimated MI

demeanedbool | False

Specifies whether the input data already has zero mean (true if it has been copula-normalized)

Returns:

ifloat

Information shared by x and y conditioned by z (in bits)