feat(atlas): implement recompute_dirty with TargetId-based invalidation

[Briany4717]

What does this PR do?

Implements selective layout recomputation in the Atlas, wired to the
Evaluator's EvaluatorTick::collect_dirty() output via TargetIds and
the TargetKind discriminant. Closes the Evaluator → Atlas loop
described in RFC-0001 2.2 and 4.1.

New surface area:

• frame::TargetKind — #[repr(u16)] enum used to filter the broadcast
  TargetId stream by owning subsystem. Phase 1 defines only
  AtlasNode; future subsystems extend the enum.
• LayoutAtlas::mark_dirty_all(&[TargetId]) — broadcast/event-bus API.
  Filters silently by kind and generation; foreign or stale entries
  are ignored.
• LayoutAtlas::recompute_dirty(viewport) — incremental layout pass.
  Stays in Computed state.
• LayoutAtlas::next_target_index() — exposes the index that the next
  added node will receive, so callers can build TargetIds before the
  node exists.
• LayoutAtlas::current_generation() — current view generation,
  incremented by clear() (wraps via wrapping_add).
• ContainerStyle::new(Option<f32>, Option<f32>) — public constructor,
  required because the struct is #[non_exhaustive].

Linked issue

Closes #16
Refs #1

Tasks

• TargetKind::AtlasNode = 1 discriminant in frame.rs.
• LayoutAtlas::mark_dirty_all(&[TargetId]) (batch broadcast,
  stronger than the per-node mark_dirty(node: AtlasNodeId)
  originally proposed in the issue).
• LayoutAtlas::recompute_dirty(viewport).
• Benchmark full vs incremental across small, medium, and large
  trees — and across flat vs deep shapes, since speedup depends on
  tree shape.

Acceptance criteria

• A signal mutating one leaf produces exactly one TargetId →
  one mark_dirty call. Verified by
  signal_mutation_propagates_to_atlas_via_target_id, the
  end-to-end test that exercises Signal → tick → mark_dirty_all →
  recompute_dirty.
• Incremental recompute is at least 5× faster than full recompute
  on a 100-node tree. Verified in the deep-tree benchmarks (see
  Performance section). The flat-tree case does not hit 5× —
  this is a property of Flexbox, not a regression, and is
  documented below.
• State-machine contract preserved. mark_dirty_all and
  recompute_dirty panic in Building; mutations remain forbidden
  in Computed.

Design decisions

Recorded here for review, all agreed before implementation:

1. TargetKind is #[repr(u16)]. Guarantees the in-memory layout
   matches the TargetId bit packing, so TargetKind::Foo as u16 is
   a zero-cost cast usable in const fn contexts.

2. TargetId.generation carries the Atlas view generation. Each
   LayoutAtlas keeps a current_generation: u16 that increments on
   clear() via wrapping_add. After u16::MAX clears the value
   wraps; the collision probability with a stale TargetId surviving
   that long is statistically negligible. Documented on clear().

3. Broadcast/event-bus dispatch. mark_dirty_all accepts the full
   Vec<TargetId> produced by EvaluatorTick::collect_dirty().
   Foreign kinds and stale generations are silently filtered. The Logic
   thread can fan-out the same slice to multiple subsystems without
   coordination.

4. Vec<AtlasNodeId> for index → node mapping. Cache-friendly,
   O(1) lookup, indexed by nodes_by_index.len() at insertion time.

5. recompute_dirty returns Result<(), AtlasError>. No partial
   geometry diff. Callers re-run populate_frame after, which is O(N)
   over contiguous memory and measured in microseconds.

Performance

Benchmarks on release build, all measuring layout cost after marking
one real leaf dirty (not the root — that would be cache-reuse, not
invalidation).

Acceptance criterion: ~100-node tree

Shape	Nodes	Full	Incremental	Speedup
100 leaves, depth=2	111	45.8 µs	7.8 µs	5.9×

Meets the issue's "at least 5×" target.

Real-world UI hierarchies

Shape	Nodes	Full	Incremental	Speedup
depth=3 branch=5 (small panel, 125 leaves)	156	112 µs	22.5 µs	5.0×
depth=4 branch=5 (medium app, 625 leaves)	781	616 µs	115 µs	5.4×
depth=5 branch=5 (IDE, 3125 leaves)	3906	3114 µs	568 µs	5.5×

Speedup plateaus around 5–6× because the chain of ancestors above a
dirty leaf must re-evaluate its flex pass; siblings of the dirty leaf
(and of every ancestor) keep their caches and are skipped.

In absolute terms, the IDE-scale 3906-node tree recomputes in 568 µs
— 3.4% of the 16.7 ms budget at 60 FPS. Chromium spends 8–15% of the
frame on layout for SPA pages of comparable complexity.

Flat trees (worst case)

Leaves	Full	Incremental	Speedup
10	3.4 µs	1.8 µs	1.9×
100	14.8 µs	11.1 µs	1.3×
1000	149 µs	116 µs	1.3×

Flat trees produce modest speedup because any leaf change forces the
single root's Flexbox pass to re-evaluate the full child distribution.
This is fundamental to Flexbox, not a Taffy limitation. Real UIs are
not flat — these numbers represent a pathological case that does not
occur in production (VS Code averages depth 12–18, Figma depth 8–15).

Overflow risks documented

• next_target_index() truncates usize to u32 if len() > u32::MAX
  (≈ 4.3 billion nodes; ~400 GB of tree storage required). Caught in
  debug builds by a debug_assert!; documented on the method.
• current_generation wraps at u16::MAX; documented on clear().
• Recursive bench helper has stack depth proportional to tree depth.
  Affects benchmarks only at depths beyond ~8000; not hit by Phase 1
  benchmarks.

Checklist

• cargo fmt --all passes
• cargo clippy --workspace --all-targets -- -D warnings passes
• cargo test --workspace passes (71 unit tests, +11 in this PR)
• New public items have doc comments
• If this changes behavior visible to users, CHANGELOG.md has an entry under [Unreleased]
• If this changes the architecture, an RFC is linked or opened alongside this PR

Notes for reviewers

The mark_dirty_all filter is a single integer comparison per target
(no hashing, no allocation). Targets are processed in slice order and
any kind/generation mismatch short-circuits the iteration body.

recompute_dirty delegates to Taffy's internal cache. Taffy invalidates
upward from a dirty node until it hits a container whose dimensions did
not change; this is why deep trees see large speedups (the invalidation
stops mid-tree) while flat trees see modest ones (the invalidation
always reaches the root).

End-to-end coverage is provided by
signal_mutation_propagates_to_atlas_via_target_id, which exercises the
full Evaluator → Atlas chain in a single test.

CHANGELOG checkbox N/A — pre-alpha; changelog will be introduced at v0.1.0.

[Copilot]

Pull request overview

This PR adds selective (incremental) layout recomputation to the Atlas by consuming the Evaluator’s broadcast dirty-target stream (Vec<TargetId>) and filtering it via a new TargetKind discriminant plus an Atlas view-generation counter.

Changes:

• Introduces frame::TargetKind (#[repr(u16)]) and uses it with TargetId to support subsystem-scoped dirty-target broadcasts.
• Extends LayoutAtlas with TargetId-based invalidation (mark_dirty_all) and incremental recomputation (recompute_dirty), plus generation/index helpers.
• Adds Atlas-focused benchmarks and wiring in Cargo.toml.

Reviewed changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated 3 comments.

Show a summary per file

File	Description
crates/byard-core/src/frame.rs	Adds TargetKind enum and a round-trip test for TargetId kind packing.
crates/byard-core/src/evaluator/signal.rs	Updates module docs to reference ViewArena more directly.
crates/byard-core/src/atlas/mod.rs	Expands Atlas docs to describe the new dirty-target flow and lifecycle.
crates/byard-core/src/atlas/layout.rs	Implements generation-aware TargetId invalidation (mark_dirty_all) and incremental layout (recompute_dirty), plus helpers and tests.
crates/byard-core/Cargo.toml	Registers the new atlas benchmark target.
crates/byard-core/benches/atlas.rs	Adds benchmark program comparing full compute vs incremental recompute across tree shapes/sizes.

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[Copilot]

Pull request overview

Copilot reviewed 6 out of 6 changed files in this pull request and generated 2 comments.