frites.core.cmi_1d_ggg#
- frites.core.cmi_1d_ggg(x, y, z, biascorrect=True, demeaned=False)[source]#
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 |
python:True Specifies whether bias correction should be applied to the estimated MI
- demeanedbool |
python:False Specifies whether the input data already has zero mean (true if it has been copula-normalized)
- Returns
- i
python:float Information shared by x and y conditioned by z (in bits)
- i