VisLab / ndx-events

NWB extension to store event and TTL pulse data

ndx-events Extension for NWB

This is an NWB extension for storing timestamped event data and TTL pulses.

The latest version is 0.3.0. This is a major change from previous versions.

Events can be:

1. Simple events. These are stored in the Events type. The Events type consists of only a name, a description, and a 1D array of timestamps. This should be used instead of a TimeSeries when the time series has no data.
2. Labeled events. These are stored in the LabeledEvents type. The LabeledEvents type expands on the Events type by adding 1) a 1D array of integer values (data) with the same length as the timestamps and 2) a 1D array of labels (labels) associated with each unique integer value in the data array. The data values are indices into the array of labels. The LabeledEvents type can be used to encode additional information about individual events, such as the reward values for each reward event.
3. TTL pulses. These are stored in the TTLs type. The TTLs type is a subtype of the LabeledEvents type specifically for TTL pulse data. A single instance should be used for all TTL pulse data. The pulse value (or channel) should be stored in the 1D data array, and the labels associated with each pulse value (or channel) should be stored in the 1D array of labels.
4. Annotated events. These are stored in the AnnotatedEventsTable type. The AnnotatedEventsTable type is a subtype of DynamicTable, where each row corresponds to a different event type. The table has a ragged (variable-length) 1D column of event times, such that each event type (row) is associated with an array of event times. Unlike for the other event types, users can add their own custom columns to annotate each event type or event time. This can be useful for storing event metadata related to data preprocessing and analysis, such as marking bad events.

This extension was developed by Ryan Ly, Oliver Rübel, and the NWB Technical Advisory Board. Information about the rationale, background, and alternative approaches to this extension can be found here: https://docs.google.com/document/d/1qcsjyFVX9oI_746RdMoDdmQPu940s0YtDjb1en1Xtdw

Installation

Python:

pip install -U ndx-events

Matlab:

generateExtension('<directory path>/ndx-events/spec/ndx-events.namespace.yaml');

Developer installation

In a Python 3.8-3.12 environment:

pip install -r requirements-dev.txt
pip install -e .

Run tests:

pytest

Install pre-commit hooks:

pre-commit install

Style and other checks:

black .
ruff .
codespell .

Example usage

Python:

This extension was created using ndx-template.