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RemoveOutlierTrials

Removes trials (instances) that have abnormally large signal values.

This node supports offline data. The node requires that the given data has an instance axis, which indexes multiple "trials", or "observations". The node calculates a measure of outlyingness for each such trial using a measure of choice, and removes trials whose measure is above a certain settable threshold (in robust standard deviations) from the data distribution. Version 1.1.0

Ports/Properties

data

Data to process.

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

transformation

Optional data transformation to apply before calculating the measure. The temporal-difference operation calculates successive differences along time.

verbose name
Transformation
default value
raw
port type
EnumPort
value type
str (can be None)

measure

Measure to use. The trial norm is the root mean square (RMS) value of the whole trial, while the max-channel norm is the maximum RMS value across all channels (requires a space axis to be present).

verbose name
Measure
default value
trial-norm
port type
EnumPort
value type
str (can be None)

threshold

Removal threshold in standard deviations.

verbose name
Threshold
default value
10
port type
FloatPort
value type
float (can be None)

verbose

Verbose output.

verbose name
Verbose
default value
True
port type
BoolPort
value type
bool (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)