frites.core.gccmi_nd_ccc#
- frites.core.gccmi_nd_ccc(x, y, z, mvaxis=None, traxis=- 1, shape_checking=True, gcrn=True)[source]#
GCCMI between two continuous variables conditioned on a third.
- Parameters
- x, y, znumpy:array_like
Continuous variables. z is the continuous variable that is considered as the condition
- mvaxis
python:int|python:None Spatial location of the axis to consider if multi-variate analysis is needed
- traxis
python:int| -1 Spatial location of the trial axis. By default the last axis is considered
- shape_checkingbool |
python:True Perform a reshape and check that x and y shapes are consistents. For high performances and to avoid extensive memory usage, it’s better to already have x and y with a shape of (…, mvaxis, traxis) and to set this parameter to False
- gcrnbool |
python:True Apply a Gaussian Copula rank normalization. This operation is relatively slow for big arrays.
- Returns
- minumpy:array_like
The mutual information with the same shape as x and y, without the mvaxis and traxis