eegprep.eeg_amica

eegprep.eeg_amica(EEG, posact='off', sortcomps='off', num_models=1, max_iter=2000, num_mix_comps=3, pcakeep=None, outdir=None, amica_binary=None, max_threads=4, **kwargs)

Perform ICA decomposition using AMICA (Adaptive Mixture ICA).

AMICA fits one or more ICA models with generalized Gaussian mixture source distributions via an external Fortran binary. Standard ICA fields are populated from model 0. The full multi-model output is stored in EEG[‘etc’][‘amica’].

EEGPrep wheels do not ship AMICA binaries. Provide the executable with the amica_binary argument, the AMICA_BINARY environment variable, or PATH.

Parameters

EEGdict

EEGLAB-like data structure.

posactstr | bool, optional

If ‘on’ or True, normalize component signs so max(abs(activations)) is positive. Default is ‘off’.

sortcompsstr | bool, optional

If ‘on’ or True, sort components by descending activation variance. Default is ‘off’.

num_modelsint

Number of ICA models to fit.

max_iterint

Maximum number of training iterations.

num_mix_compsint

Number of mixture components per source.

pcakeepint or None

Number of principal components to retain. Default: nbchan.

outdirstr or None

Output directory for AMICA. If None, a temporary directory is used.

amica_binarystr or None

Path to AMICA binary. If None, auto-detected from AMICA_BINARY, a source-tree development binary, EEGLAB’s AMICA plugin, or PATH.

max_threadsint

Maximum number of threads for the binary.

kwargsdict

Additional AMICA parameters passed through to the binary.

Returns

dict

The updated EEG structure with ICA fields.