Expands MatrixGroupOps with partial_group_min/max helpers for bitwise reductions and introduces add_col_from methods to persist external vectors as matrix columns. Refactors column aggregation in the partitioner to leverage these group operations directly, replacing iterative row processing with simplified builder lifecycle management and explicit metadata serialization.
Refactors column and matrix access to use unified `BitSliceView` and `IntSliceView` abstractions, replacing legacy `PackedCol`/`IntColView` types. Introduces `BitSlice`/`IntSlice` traits for zero-copy, trait-based bitwise and arithmetic operations across persistent and temporary vector types. Removes deprecated in-memory `MemoryBitVec` and `MemoryIntVec` implementations and their tests, while updating dependent crates to use the new view-based API and `BitSliceMut` trait.
Introduces `TempCompactIntVec` and `TempBitVec` as temporary, file-backed intermediates to replace eager in-memory vectors, enabling OS-level paging under memory pressure. Updates the `MatrixGroupOps` trait to return `io::Result` types, allowing proper error propagation and supporting chunked accumulation for large column groups. Includes builder patterns with `.freeze()` finalization, automatic `TempDir` cleanup on drop, and necessary test updates to handle the new fallible signatures. Also fixes `Cargo.toml` section ordering.
Introduce the `ColGroup` struct and `MatrixGroupOps` trait to manage named subsets of column indices and perform additive aggregations (count, sum, any). Implement these operations for `PersistentBitMatrix` and `PersistentCompactIntMatrix`, applying size-optimized branches for presence counts and direct accumulation for small groups. Additionally, add a `mask_with` trait method that efficiently zero-sets elements based on a mask, optimized for sparse masks with O(n_zeros) complexity. Include comprehensive tests covering overflow handling, slot masking, and result additivity across partitioned data.
This commit introduces `BitColView` and `IntColView` to abstract over Columnar and Packed storage formats, implementing `BitSlice` and `IntSlice` for uniform column access. It adds `col_view()` accessors to `PersistentBitMatrix` and `PackedCompactIntMatrix`, explicitly panicking on implicit variants. The new types are publicly re-exported, and unit tests are added to validate per-element retrieval, aggregation methods, and parity with the original columnar representation.
Centralizes overflow handling and improves modularity by replacing manual mmap indexing and row loops with composable iterator patterns. This change leverages Rust's iterator traits for efficient, idiomatic column traversal while encapsulating data access in a dedicated view struct.
Introduce `byte_sum` and `byte_count_nonzero` to efficiently aggregate compact-int byte slices, bypassing per-element decoding and overflow map lookups. Refactor `sum()` and `count_nonzero()` across the matrix, reader, and traits modules to use direct memory-mapped slice iteration and idiomatic Rust iterators. Additionally, expose `MemoryIntIter` publicly and implement `IntoIterator` and `IntSlice` for `MemoryIntVec` to enable standard iteration and delegate aggregation to the new helpers.
Refactor parallel matrix construction by extracting reusable `pairwise_matrix` and `pairwise2_matrix` helpers, and consolidate binary record deserialization into dedicated parsing functions. Add `set` and `iter` methods to `BitSliceMut` and `MemoryBitVec` for ergonomic bit manipulation and iteration. Standardize JSON field extraction via `meta::field`, expose `MemoryBitIter`, and improve test reliability by automatically cleaning up temporary directories.
Introduce `MemoryBitVec` and `MemoryIntVec` for efficient in-memory storage with hybrid compression and overflow handling. Implement `BitSlice`, `BitSliceMut`, `IntSlice`, and `IntSliceMut` traits across persistent and memory-backed types to enable generic slice operations and bitwise/arithmetic overloads. Add `col_persist` and `col_as_memory` methods to `BitMatrix` and `IntMatrix` for efficient column extraction. Align with the new single-pass rebuild architecture by supporting fast kmer filtering and matrix rebuilding. Includes comprehensive tests and profiling instrumentation for the packing phase.
Replaces `rayon` parallel iteration across index, rebuild, reindex, and select modules with a custom `PartitionRunner`. This introduces NUMA-aware task distribution with CPU pinning and round-robin scheduling, eliminating `Arc`, `Mutex`, and atomic synchronization primitives in favor of a flat, pre-spawned worker architecture. Error handling is simplified via `.map_err()` and the `?` operator, while progress bar updates are decoupled into dedicated callbacks.
Introduces allocation-free `sum()` and `count_nonzero()` methods for compact integer vectors, extending the `ColumnWeights` trait with `partial_kmer_counts`. Adds parallel partition scanning to the k-mer index for computing per-genome distinct k-mer counts, and exposes a new `--stats` CLI flag to output these statistics as CSV.
Introduces parallelized pairwise distance matrix computation for Jaccard, Hamming, Bray-Curtis, Euclidean, and Hellinger metrics across `Columnar`, `Packed`, and `Implicit` matrix variants. Adds trait methods and convenience wrappers, safely handles normalization and zero-denominator edge cases, and updates test suites to import required traits for validation.
Add the `tracing` crate to `obidebruinj`, `obisys`, and resolve it in `Cargo.lock`. Replace `eprintln!` statements with structured `debug!` and `info!` macros. Introduce a `TracedBar` wrapper for progress bars and enhance the `Stage` lifecycle to emit structured events for timing, memory metrics, and swap warnings. Add a progress spinner for unitig degree computation. Extend `PersistentBitMatrix` with columnar bit-vector operations and parallel distance methods, enabling uniform distance computations across all storage layouts while replacing previous panics with dimension-based fallbacks.
Explicitly close file handles and remove temporary artifacts after serialization to prevent disk space leaks. Additionally, compact internal matrix structures immediately upon loading the KmerIndex to improve memory efficiency and prepare for downstream operations.
Unifies bit and integer matrix storage into `PersistentBitMatrix` and `PersistentCompactIntMatrix` enums, supporting both columnar and memory-mapped single-file layouts. Introduces `LayerMeta` to persist layer dimensions as `layer_meta.json`, enabling correct initialization of implicit presence matrices. Adds CLI commands (`pack` and `--upgrade-index`) to convert existing columnar indices to the compact format and backfill missing metadata. Updates partitionner and layered map logic to use the new persistent builders, optimized memory allocation, and auto-detected storage backends.
Introduce zero-allocation row extraction and query result buffers across `obicompactvec` and `obikpartitionner` to eliminate per-kmer heap allocations. Replace in-memory MPHF deserialization with memory-mapped, zero-copy views to reduce runtime memory footprint. Add configurable I/O chunking, a RAM-aware `--chunk-size` parameter, and system memory monitoring via the new `sysinfo` dependency. Re-export `PreloadedIndex` for external consumers.
Introduces a new `merge` CLI subcommand and underlying implementation to consolidate multiple pre-indexed k-mer indexes into a single output. Adds `append_column` methods to persistent bit and int matrices to enable incremental genome column expansion without rebuilding the MPHF. Includes new error variants for index readiness and configuration mismatches, adds a `--force` flag to the index command, and updates documentation and navigation structure accordingly.
Introduces ColumnWeights, CountPartials, and BitPartials traits to compute and finalize partial distance matrices. Implements these traits for PersistentBitMatrix, PersistentCompactIntMatrix, and a new LayeredStore<S> wrapper that aggregates metrics across layers via parallel reduction. Adds ndarray for numerical aggregation and updates architecture documentation to reflect the trait-driven design and pending refactoring roadmap.
Add comprehensive documentation for the `obilayeredmap` crate, `PersistentCompactIntVec`, `PersistentBitVec`, and the hierarchical k-mer index architecture, including sidebar navigation updates across all documentation pages. Refactor the Bray-Curtis distance computation in `obicompactvec` to decouple numerator and denominator calculations, replacing direct pairwise calls with explicit loops over precomputed sums. Update tests to verify column sum accuracy and align with the simplified API.
Introduces parallel `count_ones` for `BitMatrix` and parallel column-sum aggregation alongside three pairwise distance constructors (Bray-Curtis, Euclidean, Hellinger) for `IntMatrix`. These methods support partial, layer-wise data by accepting precomputed global column sums for normalization, enabling additive decomposition across partitions. Includes unit tests verifying mathematical equivalence and partition additivity.
Introduce parallel distance matrix generation using `ndarray` and `rayon` for both `BitMatrix` and `IntMatrix`. Adds full and additive-partial variants for Jaccard, Hamming, Bray-Curtis, Euclidean, and Hellinger metrics. Includes comprehensive unit tests verifying matrix symmetry, zero diagonals, and numerical correctness against pairwise calculations.
Introduces `PersistentBitMatrix` and `PersistentCompactIntMatrix` to replace single-file vector storage with a column-major, directory-based layout. Each column is persisted as an individual file alongside a lightweight `meta.json` for dimension tracking. Migrates `obilayeredmap` to use these multi-column structures, updating Rust APIs, query return types, and build signatures. Includes comprehensive documentation, unit and integration tests for persistence and accessors, and refactors distance calculation helpers.
Eric Coissac