Events and Timelines

Timelines

Each piece of logged data is associated with one or more timelines. By default, each log is added to the log_time timeline, with a timestamp assigned by the SDK.

In Python, use the set time functions (set_time_sequence, set_time_seconds, set_time_nanos) to associate logs with other timestamps on other timelines. For example:

for frame in read_sensor_frames():
    rr.set_time_sequence("frame_idx", frame.idx)
    rr.set_time_seconds("sensor_time", frame.timestamp)

    rr.log_points("sensor/points", frame.points)

This will add the logged points to the timelines log_time, frame_idx, and sensor_time. You can then choose which timeline you want to organize your data along in the expanded timeline view in the bottom of the Rerun Viewer.

Timeless data

The logging functions all have timeless = False parameters. Timeless entities belong to all timelines (existing ones, and ones not yet created) and are shown leftmost in the time panel in the viewer. This is useful for entities that aren't part of normal data capture, but set the scene for how they are shown. For instance, if you are logging cars on a street, perhaps you want to always show a street mesh as part of the scenery, and for that it makes sense for that data to be timeless.

Similarly, coordinate systems (logged with rr.log_view_coordinates) are normally timeless.