Rerun

Clear

Empties all the components of an entity.

The presence of a clear means that a latest-at query of components at a given path(s) will not return any components that were logged at those paths before the clear. Any logged components after the clear are unaffected by the clear.

This implies that a range query that includes time points that are before the clear, still returns all components at the given path(s). Meaning that in practice clears are ineffective when making use of visible time ranges. Scalar plots are an exception: they track clears and use them to represent holes in the data (i.e. discontinuous lines).

Components

Required: ClearIsRecursive

Examples

Flat 

"""Log and then clear data."""

import rerun as rr

rr.init("rerun_example_clear", spawn=True)

vectors = [(1.0, 0.0, 0.0), (0.0, -1.0, 0.0), (-1.0, 0.0, 0.0), (0.0, 1.0, 0.0)]
origins = [(-0.5, 0.5, 0.0), (0.5, 0.5, 0.0), (0.5, -0.5, 0.0), (-0.5, -0.5, 0.0)]
colors = [(200, 0, 0), (0, 200, 0), (0, 0, 200), (200, 0, 200)]

# Log a handful of arrows.
for i, (vector, origin, color) in enumerate(zip(vectors, origins, colors)):
    rr.log(f"arrows/{i}", rr.Arrows3D(vectors=vector, origins=origin, colors=color))

# Now clear them, one by one on each tick.
for i in range(len(vectors)):
    rr.log(f"arrows/{i}", rr.Clear(recursive=False))  # or `rr.Clear.flat()`
Open example recording

Recursive 

"""Log and then clear data recursively."""

import rerun as rr

rr.init("rerun_example_clear_recursive", spawn=True)

vectors = [(1.0, 0.0, 0.0), (0.0, -1.0, 0.0), (-1.0, 0.0, 0.0), (0.0, 1.0, 0.0)]
origins = [(-0.5, 0.5, 0.0), (0.5, 0.5, 0.0), (0.5, -0.5, 0.0), (-0.5, -0.5, 0.0)]
colors = [(200, 0, 0), (0, 200, 0), (0, 0, 200), (200, 0, 200)]

# Log a handful of arrows.
for i, (vector, origin, color) in enumerate(zip(vectors, origins, colors)):
    rr.log(f"arrows/{i}", rr.Arrows3D(vectors=vector, origins=origin, colors=color))

# Now clear all of them at once.
rr.log("arrows", rr.Clear(recursive=True))  # or `rr.Clear.recursive()`
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