Skip to content

← neural package

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)