Events and Timelines

Timelines

Each piece of logged data is associated with one or more timelines.

The logging SDK always creates two timelines for you:

• log_tick - a sequence timeline with the sequence number of the log call
• log_time - a temporal timeline with the time of the log call

You can use the set time functions (Python reference: 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("sensor/points", rr.Points3D(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.

Events

An event refer to an instance of logging one or more component batches to one or more timelines. In the viewer, the Time panel provide a graphical representation of these events across time and entities.

Timeless data

The rr.log() function has a timeless=False default argument. If timeless=True is used instead, the entity become timeless. 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 or annotation context are typically timeless.