chore: import upstream snapshot with attribution
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@@ -0,0 +1,112 @@
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//! Demonstrates how to implement custom archetypes and components, and extend existing ones.
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use rerun::{
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ComponentBatch as _, ComponentDescriptor, SerializedComponentBatch,
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demo_util::grid,
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external::{arrow, glam, re_sdk_types},
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};
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// ---
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/// A custom [component bundle] that extends Rerun's builtin [`rerun::Points3D`] archetype with extra
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/// [`rerun::Component`]s.
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///
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/// [component bundle]: [`AsComponents`]
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struct CustomPoints3D {
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points3d: rerun::Points3D,
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confidences: Option<Vec<Confidence>>,
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}
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impl rerun::AsComponents for CustomPoints3D {
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fn as_serialized_batches(&self) -> Vec<SerializedComponentBatch> {
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std::iter::chain(
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self.points3d.as_serialized_batches(),
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std::iter::once(self.confidences.as_ref().and_then(|batch| {
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batch.serialized(ComponentDescriptor {
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archetype: Some("user.CustomPoints3D".into()),
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component: "user.CustomPoints3D:confidences".into(),
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component_type: Some(
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<Confidence as rerun::Component>::name(),
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),
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})
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}))
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.flatten(),
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)
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.collect()
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}
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}
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// ---
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/// A custom [`rerun::Component`] that is backed by a builtin [`rerun::Float32`] scalar.
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#[derive(Debug, Clone, Copy, rerun::SizeBytes)]
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struct Confidence(rerun::Float32);
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impl From<f32> for Confidence {
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fn from(v: f32) -> Self {
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Self(rerun::Float32(v))
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}
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}
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impl rerun::Loggable for Confidence {
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#[inline]
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fn arrow_datatype() -> arrow::datatypes::DataType {
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rerun::Float32::arrow_datatype()
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}
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#[inline]
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fn to_arrow_opt<'a>(
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data: impl IntoIterator<
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Item = Option<impl Into<std::borrow::Cow<'a, Self>>>,
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>,
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) -> re_sdk_types::SerializationResult<arrow::array::ArrayRef>
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where
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Self: 'a,
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{
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rerun::Float32::to_arrow_opt(
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data.into_iter().map(|opt| opt.map(Into::into).map(|c| c.0)),
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)
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}
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}
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impl rerun::Component for Confidence {
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#[inline]
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fn name() -> rerun::ComponentType {
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"user.Confidence".into()
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}
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}
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// ---
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fn main() -> Result<(), Box<dyn std::error::Error>> {
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let rec = rerun::RecordingStreamBuilder::new("rerun_example_custom_data")
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.spawn()?;
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rec.log(
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"left/my_confident_point_cloud",
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&CustomPoints3D {
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points3d: rerun::Points3D::new(grid(
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glam::Vec3::splat(-5.0),
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glam::Vec3::splat(5.0),
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3,
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)),
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confidences: Some(vec![42f32.into()]),
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},
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)?;
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rec.log(
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"right/my_polarized_point_cloud",
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&CustomPoints3D {
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points3d: rerun::Points3D::new(grid(
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glam::Vec3::splat(-5.0),
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glam::Vec3::splat(5.0),
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3,
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)),
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confidences: Some(
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(0..27).map(|i| i as f32).map(Into::into).collect(),
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),
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},
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)?;
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Ok(())
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}
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