Ica Components

Module name: IcaComponents

Package: CEAMSModules 7.4.0

Version: 2.0.0

Overview

Finds components of a signal with independent component analysis.

Taken from _fastica.py. Read more in the FastICA documentation.

Inputs

Input	Format	Default	Description
signals	List	—	List of signal with dictionary of channels with SignalModel with properties : name: The name of the channel samples: The samples of the signal alias: The alias of the channel sample_rate: The sample rate of the signal start_time: The start time of the recording montage_index: The index of the montage used for this signal is_modified: Value caracterizing if the signal as been modify from the original parameters : dict parameters to decompose the signal. ICA_algo : string (‘infomax’ or ‘fastICA’) n_components : int, default=None
parameters	dict	Came in the description column	Parameters to decompose the signal. {‘ICA_algo’: ‘infomax’ or ‘fastICA’, ‘n_components’: None, ‘algorithm’: ‘parallel’, ‘whiten’: ‘arbitrary-variance’, ‘fun’: ‘logcosh’, ‘max_iter’: 1000, ‘tol’: 0.0001, ‘random_state’: None}

Parameters

Parameter	Format	Default	Description
ICA_algo	string	‘infomax’ or ‘fastICA’	The algorithm to use for the ICA.
n_components	int	None	The number of components to extract. If None, all components are extracted.
algorithm	string	‘parallel’	The algorithm to use for the ICA.
whiten	string or bool	‘arbitrary-variance’	The whitening strategy to use.
fun	string	‘logcosh’	The functional form of the G function used in the approximation to neg-entropy.
fun_args	dict	None	Arguments to send to the functional form. If None, the default arguments are used.
max_iter	int	200	The maximum number of iterations during fit.
tol	float	0.0001	The tolerance on update at each iteration.
w_init	ndarray of shape (n_components, n_components)	None	The mixing matrix to be used to initialize the algorithm. If None, a random matrix is used.
random_state	int	None	Used to initialize w_init when not specified, with a normal distribution.

Outputs

Output	Format	Description
components	List	List of signal_models obtain after the decomposition

Usage in a process

1. Open Dev Tools -> New process in Snooz.

2. In the Module Library, find Ica Components under the Signal Processing category.

3. Drag the module onto the process canvas.

4. Connect the required inputs from upstream modules (or set values in the Settings tab).

5. Connect outputs to downstream modules as needed.

6. Double-click the module to configure parameters in the Settings tab.

7. Run the process and inspect results in the Results tab.

Note

For general guidance on building processes with modules, see Explore examples.