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ClassifyIndependentComponents

Classify independent components using a component classifier.

This categorizes components previously generated by an ICA node such as InfomaxICA into categories such as brain, eye, etc. This node should be used with the following workflow: 1) optional artifact removal (highpass, etc.); if a line-noise removal filter is used, it must be narrow-band (e.g., 1 Hz). 2) Common average reference. 3) ICA. 4) This node. Version 0.2.0

Ports/Properties

data

Data to process.

verbose name
Data
default value
None
port type
DataPort
value type
Packet (can be None)
data direction
INOUT

classifier

Classifier to use. Currently, only ICLabel is supported. This appends an additional field to the space axis of the data named 'labels', which has the component classification labels in it. These labels fall into categories such as 'brain', 'muscle', etc.

verbose name
Classifier
default value
ICLabel
port type
EnumPort
value type
str (can be None)

ensemble_size

Number of classifiers to use in the ensemble. This is only used if the classifier is ICLabel. The default is the maximum of 6, but a smaller number can be chosen to reduce the compute cost.

verbose name
Ensemble Size
default value
6
port type
IntPort
value type
int (can be None)

set_breakpoint

Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.

verbose name
Set Breakpoint (Debug Only)
default value
False
port type
BoolPort
value type
bool (can be None)

metadata

User-definable meta-data associated with the node. Usually reserved for technical purposes.

verbose name
Metadata
default value
{}
port type
DictPort
value type
dict (can be None)