Formalize the two-phase MPHF indexing architecture and update Phase 6 to use `evidence.bin` for direct kmer extraction. Simplify the evidence and unitig storage layouts to flat packed formats enabling O(1) random access. Introduce aggregation traits (`ColumnWeights`, `CountPartials`, `BitPartials`) to support additive distance metric decomposition across partitions. Narrow the documented scope from metagenomic to individual genome datasets, and replace speculative open questions with concrete implementation specifications.
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.
Replace raw SuperkMer routing with a new RoutableSuperKimer type that embeds canonical sequences and precomputed minimizers, enabling direct partition routing via hash. Update the build pipeline to yield RoutableSuperKmers throughout (builder, scatterer), refactor FASTA/unitig export commands to use the new type and compressed outputs (.fasta.gz, .unitigs.fasta.zst), revise SuperKmer header to store n_kmers instead of seql (avoiding 256-byte wrap), and update documentation to reflect minimizer-based theory, two evidence-encoding strategies for unitig-MPHF indexing (global offset vs. ID+rank), and the new obipipeline library architecture with parallel workers, biased scheduling, and error handling.