ParseTriggerChannel¶
Extract event markers from a trigger channel.
The traditional way to mark events in sensor time series is using trigger channels that can take on a number of discrete numeric values (where 0 means "no event"). However, NeuroPype treats event markers as a separate data stream, where each event has a string to identify it and a timestamp of when it happened. This node lets you convert from a trigger channel to the NeuroPype format (markers will be the string versions of the numeric values in the channel). This node does not currently remove the trigger channel itself, so you need to remove it by hand if you are doing machine learning of any kind on the data. Version 1.0.0
Ports/Properties¶
data¶
Data to process.
channel¶
Index of the trigger channel, counting from 0. Negative values count from the end, e.g., -1 is the last channel. If this is None, the data is passed through unmodified.
debounce_ttl¶
Only mark onset times. If a trigger value is held for multiple successive samples, a marker will only be emitted for the first sample. This is typically what you want, since the hold time on the trigger channel usually has to be multiple samples long to ensure that spike is not missed. Disabling this allows you to generate a marker for every non-zero sample.
print_markers¶
Print extracted markers. This is for diagnostic and debugging purposes.
previous_markers¶
Handling mode for previous marker streams. In replace mode, any previous NeuroPype marker stream (e.g., from LSL) will be removed and replaced by the trigger-based marker stream. In ignore mode, a new marker stream will be added and the old one will be kept. Note that if you do this, some subsequent processing nodes that handle marker streams may be confused and will only pick up one of the streams.
set_breakpoint¶
Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.
metadata¶
User-definable meta-data associated with the node. Usually reserved for technical purposes.