perf: improve Hilbert curve correctness and add bulk API (#207)#216
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acgetchell merged 7 commits intomainfrom Feb 26, 2026
Merged
perf: improve Hilbert curve correctness and add bulk API (#207)#216acgetchell merged 7 commits intomainfrom
acgetchell merged 7 commits intomainfrom
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Implements correctness fixes, API improvements, and comprehensive testing for the Hilbert space-filling curve ordering utilities. ## Correctness Fixes - Add debug_assert guards in hilbert_index_from_quantized for parameter validation (bits range and overflow checks) - Fix quantization truncation bias by changing from NumCast::from(scaled) to scaled.round().to_u32() for fairer spatial distribution across grid cells, improving point ordering quality ## API Design - Add HilbertError enum with InvalidBitsParameter, IndexOverflow, and DimensionTooLarge variants for proper error handling - Implement hilbert_indices_prequantized() returning Result<Vec<u128>, HilbertError> for bulk processing of pre-quantized coordinates - Bulk API avoids redundant quantization computation, significantly improving performance for large insertion batches ## Testing - Add 4D continuity test verifying Hilbert curve property on 256-point grid (bits=2) - Add quantization rounding distribution test validating fair cell assignment - Add 5 comprehensive tests for prequantized API covering success cases, empty input, and all error conditions - All 17 Hilbert-specific tests pass (11 existing + 6 new) ## Known Issue Temporarily ignore repair_fallback_produces_valid_triangulation test as the rounding change affects insertion order, exposing a latent geometric degeneracy issue in triangulation construction. This is properly documented and tracked under issue #204 for investigation.
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WalkthroughCentralized Hilbert parameter validation and errors; added bulk pre-quantized Hilbert-index API; quantization now rounds-to-nearest; introduced unchecked quantize helper; hilbert APIs and sorting now return Results with overflow and parameter checks; Delaunay ordering falls back to deterministic lexicographic key on Hilbert errors; expanded tests and ignored one flaky test with FIXME. Changes
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes Possibly related issues
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Actionable comments posted: 1
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@src/core/util/hilbert.rs`:
- Around line 388-414: Handle the D == 0 case early in
hilbert_indices_prequantized: after validating bits/dimension/overflow, if the
compile-time dimension D is zero return a Vec<u128> with one 0u128 per input
point (i.e., length quantized.len()) instead of calling
hilbert_index_from_quantized (which panics via transposed[0]); this preserves
the Result-based API and avoids the panic from hilbert_index_from_quantized when
D == 0.
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…culation Ensures correct behavior for `hilbert_indices_prequantized` when the dimensionality `D` is zero. In such a space, all points map to the single origin, and their Hilbert curve index is always 0. This change adds an early return for this specific edge case. Refs: #207
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⚠️ Outside diff range comments (1)
src/core/util/hilbert.rs (1)
249-261:⚠️ Potential issue | 🟡 MinorAdd D == 0 handling for consistency with other functions.
hilbert_sort_keyis the only code path that doesn't guard againstD == 0before callinghilbert_index_from_quantized. This creates an inconsistency withhilbert_indexandhilbert_indices_prequantized, which both handle this case. In release builds (wheredebug_assertis inactive), calling any of the three public functionshilbert_sort_by_stable,hilbert_sort_by_unstable, orhilbert_sorted_indiceswithD == 0would panic when accessingtransposed[0]on an empty array.Proposed fix
fn hilbert_sort_key<T: CoordinateScalar, const D: usize>( coords: &[T; D], bounds: (T, T), bits: u32, ) -> (u128, [u32; D]) { // Keep assertions consistent with `hilbert_index`. validate_hilbert_params::<D>(bits); + if D == 0 { + return (0, [0_u32; D]); + } + let q = hilbert_quantize(coords, bounds, bits); let idx = hilbert_index_from_quantized(&q, bits); (idx, q) }🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/core/util/hilbert.rs` around lines 249 - 261, The function hilbert_sort_key fails when D == 0 because it always calls hilbert_index_from_quantized, which accesses transposed[0] and panics for empty arrays; to fix, keep the existing validate_hilbert_params and call hilbert_quantize as now, then add a D == 0 branch that returns (0, q) immediately (u128 zero index and the quantized empty array) instead of calling hilbert_index_from_quantized; this mirrors the handling in hilbert_index and hilbert_indices_prequantized and prevents panics from public callers like hilbert_sort_by_stable, hilbert_sort_by_unstable, and hilbert_sorted_indices.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Outside diff comments:
In `@src/core/util/hilbert.rs`:
- Around line 249-261: The function hilbert_sort_key fails when D == 0 because
it always calls hilbert_index_from_quantized, which accesses transposed[0] and
panics for empty arrays; to fix, keep the existing validate_hilbert_params and
call hilbert_quantize as now, then add a D == 0 branch that returns (0, q)
immediately (u128 zero index and the quantized empty array) instead of calling
hilbert_index_from_quantized; this mirrors the handling in hilbert_index and
hilbert_indices_prequantized and prevents panics from public callers like
hilbert_sort_by_stable, hilbert_sort_by_unstable, and hilbert_sorted_indices.
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Additional details and impacted files@@ Coverage Diff @@
## main #216 +/- ##
==========================================
- Coverage 61.77% 61.74% -0.04%
==========================================
Files 48 48
Lines 12359 12431 +72
==========================================
+ Hits 7635 7675 +40
- Misses 4724 4756 +32
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Refactors Hilbert curve quantization and indexing functions to return `Result` instead of panicking on invalid input parameters or index overflow. This enhances robustness and allows callers to handle errors gracefully. Introduces an internal `hilbert_quantize_unchecked` for performance-critical paths, ensuring validated inputs bypass `Result` overhead. The Delaunay triangulation vertex sorting now includes a fallback to lexicographic ordering if Hilbert index calculation encounters an error. Refs: #207
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🧹 Nitpick comments (1)
src/core/util/hilbert.rs (1)
177-193: Consolidate repeated Hilbert parameter validation into a helper.The same bits/dimension/overflow validation logic is duplicated in multiple public APIs. Extracting a shared validator will reduce drift risk and keep future behavior changes consistent.
♻️ Refactor sketch
+#[inline] +fn validate_hilbert_params<const D: usize>(bits: u32) -> Result<u128, HilbertError> { + if bits == 0 || bits > 31 { + return Err(HilbertError::InvalidBitsParameter { bits }); + } + let d_u32 = u32::try_from(D).map_err(|_| HilbertError::DimensionTooLarge { dimension: D })?; + let total_bits = u128::from(d_u32) * u128::from(bits); + if total_bits > 128 { + return Err(HilbertError::IndexOverflow { + dimension: D, + bits, + total_bits, + }); + } + Ok(total_bits) +}- if bits == 0 || bits > 31 { ... } - let d_u32 = u32::try_from(D).map_err(|_| HilbertError::DimensionTooLarge { dimension: D })?; - let total_bits = u128::from(d_u32) * u128::from(bits); - if total_bits > 128 { ... } + let _ = validate_hilbert_params::<D>(bits)?;Also applies to: 321-334, 389-402, 487-503, 545-558
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/core/util/hilbert.rs` around lines 177 - 193, Extract the repeated validation logic (checking bits range, converting D to u32, and computing total_bits/overflow) into a single private helper (for example validate_hilbert_params) that accepts the original D and bits parameters and returns the validated d_u32 and computed total_bits or an Err(HilbertError::...) on failure; replace the duplicated blocks (the current code using bits, D, d_u32, and total_bits and returning HilbertError::InvalidBitsParameter, HilbertError::DimensionTooLarge, HilbertError::IndexOverflow) with calls to this helper from each public API (including where hilbert_quantize is using the same checks) so all callers reuse the same validation path.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@AGENTS.md`:
- Around line 78-95: Run the repository spell-checker by executing the "just
spell-check" command after editing AGENTS.md, review the reported flags, and for
any legitimate technical terms (e.g., labels like "enhancement", "rust", command
snippets such as `gh issue comment`, or other domain-specific tokens) add them
to the typos.toml dictionary so they are not flagged in future runs; ensure you
commit the updated typos.toml alongside the documentation change.
In `@src/core/delaunay_triangulation.rs`:
- Around line 1229-1233: The fallback currently uses input_index (via <u128 as
From<u32>>::from(u32::try_from(input_index)...)) which yields input-order, not
lexicographic order; change the closure passed to
hilbert_index(...).unwrap_or_else(...) to compute a lexicographic key from the
vertex coordinates instead. Specifically, use vertex.point().coords() with the
same quantization/bit width (bits_per_coord) and bounds used by hilbert_index to
convert each coordinate into an integer, clamp to the valid range, and then pack
those integer coord components into a single u128 lexicographic key (e.g., by
left-shifting and OR-ing components in coordinate order) so that failed Hilbert
entries sort by coordinate lexicographic order rather than input_index.
In `@src/core/util/hilbert.rs`:
- Around line 510-513: The function hilbert_indices_prequantized currently
forwards arbitrary u32 values to hilbert_index_from_quantized, allowing values >
2^bits-1 to be silently truncated; add a validation step in
hilbert_indices_prequantized that computes max = (1u32 << bits) - 1 and checks
each quantized value q <= max, returning a clear Err (or panicking consistently
with the crate's error style) if any q is out-of-range, and apply the same guard
to the related pre-quantized helper referenced around lines 213-220 (e.g., the
singular hilbert_index_prequantized/hilbert_index_from_quantized call) so inputs
are validated before index computation.
---
Nitpick comments:
In `@src/core/util/hilbert.rs`:
- Around line 177-193: Extract the repeated validation logic (checking bits
range, converting D to u32, and computing total_bits/overflow) into a single
private helper (for example validate_hilbert_params) that accepts the original D
and bits parameters and returns the validated d_u32 and computed total_bits or
an Err(HilbertError::...) on failure; replace the duplicated blocks (the current
code using bits, D, d_u32, and total_bits and returning
HilbertError::InvalidBitsParameter, HilbertError::DimensionTooLarge,
HilbertError::IndexOverflow) with calls to this helper from each public API
(including where hilbert_quantize is using the same checks) so all callers reuse
the same validation path.
Comment on lines
+78
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Run just spell-check after editing this documentation.
Please run the spell-check command for this added section and add any legitimate technical terms to typos.toml if flagged, as per the documentation guidelines.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@AGENTS.md` around lines 78 - 95, Run the repository spell-checker by
executing the "just spell-check" command after editing AGENTS.md, review the
reported flags, and for any legitimate technical terms (e.g., labels like
"enhancement", "rust", command snippets such as `gh issue comment`, or other
domain-specific tokens) add them to the typos.toml dictionary so they are not
flagged in future runs; ensure you commit the updated typos.toml alongside the
documentation change.
Comment on lines
+1229
to
+1233
| let idx = hilbert_index(vertex.point().coords(), bounds, bits_per_coord) | ||
| .unwrap_or_else(|_| { | ||
| // On error, fall back to lexicographic ordering based on input index | ||
| <u128 as From<u32>>::from(u32::try_from(input_index).unwrap_or(u32::MAX)) | ||
| }); |
There was a problem hiding this comment.
Fallback path is input-order, not lexicographic.
At Line 1232, the fallback key is derived from input_index, so failed Hilbert entries are sorted by original input order. That contradicts the lexicographic fallback intent and can make results permutation-dependent when Hilbert indexing fails.
💡 Proposed fix
- let idx = hilbert_index(vertex.point().coords(), bounds, bits_per_coord)
- .unwrap_or_else(|_| {
- // On error, fall back to lexicographic ordering based on input index
- <u128 as From<u32>>::from(u32::try_from(input_index).unwrap_or(u32::MAX))
- });
+ let idx = hilbert_index(vertex.point().coords(), bounds, bits_per_coord)
+ .unwrap_or_else(|_| {
+ // On error, force fallback ordering to rely on the existing
+ // lexicographic + input-index tie-breakers in `sort_by`.
+ u128::MAX
+ });🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/core/delaunay_triangulation.rs` around lines 1229 - 1233, The fallback
currently uses input_index (via <u128 as
From<u32>>::from(u32::try_from(input_index)...)) which yields input-order, not
lexicographic order; change the closure passed to
hilbert_index(...).unwrap_or_else(...) to compute a lexicographic key from the
vertex coordinates instead. Specifically, use vertex.point().coords() with the
same quantization/bit width (bits_per_coord) and bounds used by hilbert_index to
convert each coordinate into an integer, clamp to the valid range, and then pack
those integer coord components into a single u128 lexicographic key (e.g., by
left-shifting and OR-ing components in coordinate order) so that failed Hilbert
entries sort by coordinate lexicographic order rather than input_index.
Comment on lines
+510
to
+513
| Ok(quantized | ||
| .iter() | ||
| .map(|q| hilbert_index_from_quantized(q, bits)) | ||
| .collect()) |
There was a problem hiding this comment.
Pre-quantized inputs are not validated against bits width.
hilbert_indices_prequantized accepts arbitrary u32 values and forwards directly to index computation. Values above 2^bits - 1 can silently alias because only the lower bits are consumed, which can produce incorrect ordering without an error.
💡 Suggested invariant guard
fn hilbert_index_from_quantized<const D: usize>(coords: &[u32; D], bits: u32) -> u128 {
@@
debug_assert!(
(D as u128) * u128::from(bits) <= 128,
"Hilbert index would overflow u128 for D={D} and bits={bits}"
);
+ let max_quantized = (1_u32 << bits) - 1;
+ debug_assert!(
+ coords.iter().all(|&c| c <= max_quantized),
+ "quantized coords must be in [0, 2^bits): bits={bits}, max={max_quantized}, coords={coords:?}"
+ );Also applies to: 213-220
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@src/core/util/hilbert.rs` around lines 510 - 513, The function
hilbert_indices_prequantized currently forwards arbitrary u32 values to
hilbert_index_from_quantized, allowing values > 2^bits-1 to be silently
truncated; add a validation step in hilbert_indices_prequantized that computes
max = (1u32 << bits) - 1 and checks each quantized value q <= max, returning a
clear Err (or panicking consistently with the crate's error style) if any q is
out-of-range, and apply the same guard to the related pre-quantized helper
referenced around lines 213-220 (e.g., the singular
hilbert_index_prequantized/hilbert_index_from_quantized call) so inputs are
validated before index computation.
The CI workflow now integrates nextest to generate comprehensive JUnit XML test reports. These reports are uploaded to Codecov for enhanced test analytics and archived as a workflow artifact. This complements existing Tarpaulin-based coverage generation, providing better separation of concerns for test execution and coverage instrumentation. A new nextest.toml configures default and CI-specific profiles, including retries for flaky tests and output settings. Refs: #207
There was a problem hiding this comment.
🧹 Nitpick comments (1)
.github/workflows/codecov.yml (1)
141-150: Pincodecov/test-results-actionto a SHA hash for supply-chain security.All other actions in this workflow are pinned to specific commit SHAs (e.g.,
codecov/codecov-action@671740ac38dd9b0130fbe1cec585b89eea48d3de), but this action uses only a version tag (@v1). This inconsistency creates a supply-chain risk if the tag is moved to a compromised commit.🔒 Proposed fix
- name: Upload test results to Codecov if: ${{ success() && hashFiles('test-results/junit.xml') != '' }} - uses: codecov/test-results-action@v1 + uses: codecov/test-results-action@0fa95f0e1eeaafde2c782583b36b28ad0d8c77d3 # v1 with: files: test-results/junit.xml🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In @.github/workflows/codecov.yml around lines 141 - 150, The GitHub Actions workflow uses codecov/test-results-action@v1 without pinning to a specific SHA commit, which risks supply-chain security. Replace the version tag in the Upload test results to Codecov step's uses field by specifying a fixed commit SHA hash for codecov/test-results-action, similar to how codecov/codecov-action is pinned. This ensures consistent and secure action usage.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Nitpick comments:
In @.github/workflows/codecov.yml:
- Around line 141-150: The GitHub Actions workflow uses
codecov/test-results-action@v1 without pinning to a specific SHA commit, which
risks supply-chain security. Replace the version tag in the Upload test results
to Codecov step's uses field by specifying a fixed commit SHA hash for
codecov/test-results-action, similar to how codecov/codecov-action is pinned.
This ensures consistent and secure action usage.
Temporarily ignores a performance test in boundary analysis due to its occasional flakiness. The test's fixed point configuration can lead to geometric degeneracies during triangulation, causing failures. This allows other related work to progress while the root cause is investigated. Updates the Codecov test results GitHub Action to v1.2.1 for internal CI/CD maintenance. Refs: #204
The previous CI setup relied on `nextest.toml` for JUnit XML output, which was not consistently generating the file. This update ensures reliable creation of the JUnit XML file by explicitly specifying the output path for `cargo nextest run`, crucial for Codecov Test Analytics. Refs: #207
Adjusts the Codecov GitHub Actions workflow to no longer explicitly specify the JUnit output path for `cargo nextest run`. The path is now managed via the `.config/nextest.toml` configuration file, centralizing nextest settings. This updates all subsequent steps to check for the JUnit XML file in the new default location (`target/nextest/ci/test-results/junit.xml`), improving consistency and simplifying the test execution command. Refs: 207
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Implements correctness fixes, API improvements, and comprehensive testing for the Hilbert space-filling curve ordering utilities.
Correctness Fixes
API Design
Testing
Closes #207
Known Issue
Temporarily ignore repair_fallback_produces_valid_triangulation test as the rounding change affects insertion order, exposing a latent geometric degeneracy issue in triangulation construction. This is properly documented and tracked under issue #204 for investigation.