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obikmer
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Chunk reader
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obipipeline library
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On-disk storage
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MPHF selection
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Unitig evidence encoding
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Evidence elimination (discussion)
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obilayeredmap crate
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PersistentCompactIntVec
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PersistentBitVec
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Merge command
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Kmer filtering (rebuild/dump/unitig)
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Architecture
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Architecture
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Sequences
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Kmer index
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Kmer index
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Table of contents
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Fundamental invariant
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IndexConfig and IndexMeta
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EvidenceKind
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< a href = "#mphflayer-autonomous-kmer-slot-mapping" class = "md-nav__link" >
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MphfLayer — autonomous kmer → slot mapping
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Layer\< D> — MPHF + data payload
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< li class = "md-nav__item" >
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DataStore — slot-indexed data
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Aggregation traits — obicompactvec::traits
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< li class = "md-nav__item" >
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LayeredStore\< S> — recursive aggregation wrapper
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Progressive aggregation principle
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< a href = "#multi-genome-column-invariant" class = "md-nav__link" >
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Multi-genome column invariant
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Query model
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Point query
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Aggregation
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Parallelism model
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< a href = "#reindex-evidence-conversion-in-place" class = "md-nav__link" >
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reindex — evidence conversion in place
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estimate — parameter dry-run
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< span class = "md-nav__icon md-icon" > < / span >
Table of contents
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< ul class = "md-nav__list" data-md-component = "toc" data-md-scrollfix >
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Fundamental invariant
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Three-level hierarchy
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< li class = "md-nav__item" >
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< a href = "#indexconfig-and-indexmeta" class = "md-nav__link" >
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IndexConfig and IndexMeta
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< li class = "md-nav__item" >
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< a href = "#evidencekind" class = "md-nav__link" >
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EvidenceKind
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< li class = "md-nav__item" >
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< a href = "#mphflayer-autonomous-kmer-slot-mapping" class = "md-nav__link" >
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MphfLayer — autonomous kmer → slot mapping
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< / a >
< / li >
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< li class = "md-nav__item" >
< a href = "#layerd-mphf-data-payload" class = "md-nav__link" >
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Layer\< D> — MPHF + data payload
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< li class = "md-nav__item" >
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< a href = "#datastore-slot-indexed-data" class = "md-nav__link" >
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< span class = "md-ellipsis" >
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DataStore — slot-indexed data
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< a href = "#aggregation-traits-obicompactvectraits" class = "md-nav__link" >
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< span class = "md-ellipsis" >
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Aggregation traits — obicompactvec::traits
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< li class = "md-nav__item" >
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< a href = "#layeredstores-recursive-aggregation-wrapper" class = "md-nav__link" >
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LayeredStore\< S> — recursive aggregation wrapper
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< a href = "#progressive-aggregation-principle" class = "md-nav__link" >
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Progressive aggregation principle
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< a href = "#multi-genome-column-invariant" class = "md-nav__link" >
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< span class = "md-ellipsis" >
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Multi-genome column invariant
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< / span >
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< a href = "#query-model" class = "md-nav__link" >
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Query model
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< nav class = "md-nav" aria-label = "Query model" >
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Point query
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Aggregation
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Parallelism model
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< a href = "#reindex-evidence-conversion-in-place" class = "md-nav__link" >
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< span class = "md-ellipsis" >
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reindex — evidence conversion in place
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estimate — parameter dry-run
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< article class = "md-content__inner md-typeset" >
< h1 id = "kmer-index-architecture" > Kmer index architecture< / h1 >
< h2 id = "fundamental-invariant" > Fundamental invariant< / h2 >
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< p > A given canonical kmer belongs to < strong > exactly one partition< / strong > and < strong > exactly one layer< / strong > within that partition. This property makes all aggregation operations decomposable and parallelisable without coordination.< / p >
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< hr / >
< h2 id = "three-level-hierarchy" > Three-level hierarchy< / h2 >
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< div class = "highlight" > < pre > < span > < / span > < code > KmerIndex (index.meta + KmerPartition)
├── partition_0/index/ one directory per minimiser bucket
│ ├── meta.json PartitionMeta { n_layers }
│ ├── layer_0/
│ │ ├── layer_meta.json LayerMeta { evidence: EvidenceKind }
│ │ ├── mphf.bin PtrHash MPHF
│ │ ├── unitigs.bin unitig spine (never overwritten)
│ │ ├── evidence.bin exact evidence (Exact only)
│ │ ├── unitigs.bin.idx block index (Exact only)
│ │ ├── fingerprint.bin fingerprints (Approx only)
│ │ ├── counts/ PersistentCompactIntMatrix (with_counts = true)
│ │ └── presence/ PersistentBitMatrix
│ └── layer_1/
│ └── ...
└── partition_1/index/
└── ...
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< / code > < / pre > < / div >
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< p > < strong > KmerIndex< / strong > : root entry point. Owns < code > IndexMeta< / code > (written to < code > index.meta< / code > ) and a < code > KmerPartition< / code > that routes canonical kmers to partition directories. All partition-level operations are dispatched in parallel via rayon.< / p >
< p > < strong > Partition directory< / strong > : one directory per minimiser bucket. < code > PartitionMeta< / code > (stored as < code > meta.json< / code > ) records < code > n_layers< / code > . Layers within a partition cover disjoint kmer sets.< / p >
< p > < strong > Layer directory< / strong > : one < code > MphfLayer< / code > plus optional data stores. < code > LayerMeta< / code > (stored as < code > layer_meta.json< / code > ) records which < code > EvidenceKind< / code > was used. The MPHF and < code > unitigs.bin< / code > are immutable once built; evidence files are the only part replaced by < code > reindex< / code > .< / p >
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< hr / >
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< h2 id = "indexconfig-and-indexmeta" > IndexConfig and IndexMeta< / h2 >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "k" > struct< / span > < span class = "w" > < / span > < span class = "nc" > IndexConfig< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > kmer_size< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > usize< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > minimizer_size< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > usize< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > n_bits< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > usize< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // log2(n_partitions)< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > with_counts< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > bool< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > evidence< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > EvidenceKind< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > block_bits< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > u8< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // .idx granularity: 2^block_bits unitigs/block; 0 = one entry per unitig< / span >
< span class = "p" > }< / span >
< span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "k" > struct< / span > < span class = "w" > < / span > < span class = "nc" > IndexMeta< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > version< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > u32< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > config< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > IndexConfig< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > genomes< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nb" > Vec< / span > < span class = "o" > < < / span > < span class = "n" > GenomeInfo< / span > < span class = "o" > > < / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // ordered; index = genome column number< / span >
< span class = "p" > }< / span >
< span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "k" > struct< / span > < span class = "w" > < / span > < span class = "nc" > GenomeInfo< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > label< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nb" > String< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "n" > meta< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > HashMap< / span > < span class = "o" > < < / span > < span class = "nb" > String< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "nb" > String< / span > < span class = "o" > > < / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // arbitrary categorical metadata< / span >
< span class = "p" > }< / span >
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< / code > < / pre > < / div >
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< p > < code > IndexMeta< / code > is serialised as < code > index.meta< / code > (JSON). It is the authority for the ordered list of genomes and for the parameters that govern all subsequent operations on the index.< / p >
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< hr / >
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< h2 id = "evidencekind" > EvidenceKind< / h2 >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "k" > enum< / span > < span class = "w" > < / span > < span class = "nc" > EvidenceKind< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "n" > Exact< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "n" > Approx< / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "n" > b< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > u8< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > z< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > u8< / span > < span class = "w" > < / span > < span class = "p" > },< / span >
< span class = "p" > }< / span >
< / code > < / pre > < / div >
< p > Controls which files are written per layer and which query path is taken:< / p >
< table >
< thead >
< tr >
< th > Variant< / th >
< th > Files written< / th >
< th > False-positive rate< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > < code > Exact< / code > < / td >
< td > < code > evidence.bin< / code > , < code > unitigs.bin.idx< / code > < / td >
< td > 0< / td >
< / tr >
< tr >
< td > < code > Approx { b, z }< / code > < / td >
< td > < code > fingerprint.bin< / code > < / td >
< td > ≈ W / 2^(b·z) per read (Findere)< / td >
< / tr >
< / tbody >
< / table >
< p > < code > EvidenceKind< / code > is stored both in < code > IndexConfig< / code > (index-wide default, updated by < code > reindex< / code > ) and in each < code > LayerMeta< / code > (per-layer record of what was actually built).< / p >
< hr / >
< h2 id = "mphflayer-autonomous-kmer-slot-mapping" > MphfLayer — autonomous kmer → slot mapping< / h2 >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "k" > struct< / span > < span class = "w" > < / span > < span class = "nc" > MphfLayer< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "n" > mphf< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > PtrHash< / span > < span class = "o" > < < / span > < span class = "err" > …< / span > < span class = "o" > > < / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "n" > ev< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > LayerEvidence< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // Exact { evidence, unitigs } | Approx { fingerprint }< / span >
< span class = "w" > < / span > < span class = "n" > n< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > usize< / span > < span class = "p" > ,< / span >
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< span class = "p" > }< / span >
< / code > < / pre > < / div >
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< p > < code > MphfLayer::find(kmer)< / code > dispatches transparently to < code > find_exact< / code > or < code > find_approx< / code > based on the evidence loaded at < code > open< / code > time (read from < code > layer_meta.json< / code > ). Returns < code > Some(slot)< / code > only if the kmer is confirmed present; < code > None< / code > for absent or out-of-range.< / p >
< div class = "highlight" > < pre > < span > < / span > < code > find_exact: slot = mphf(kmer); decode evidence → (chunk_id, rank); verify kmer in unitigs
find_approx: slot = mphf(kmer); check fingerprint[slot] == seq_hash(kmer)
< / code > < / pre > < / div >
< p > < code > block_bits< / code > controls the < code > .idx< / code > file written alongside < code > evidence.bin< / code > . At < code > block_bits = 0< / code > , every unitig chunk has an index entry, giving O(1) random access; larger values trade access time for a smaller < code > .idx< / code > .< / p >
< p > The MPHF and < code > unitigs.bin< / code > are never rebuilt by any post-build operation.< / p >
< hr / >
< h2 id = "layerd-mphf-data-payload" > Layer\< D> — MPHF + data payload< / h2 >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "k" > struct< / span > < span class = "w" > < / span > < span class = "nc" > Layer< / span > < span class = "o" > < < / span > < span class = "n" > D< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > LayerData< / span > < span class = "w" > < / span > < span class = "o" > =< / span > < span class = "w" > < / span > < span class = "p" > ()< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "n" > mphf< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > MphfLayer< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "n" > data< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > D< / span > < span class = "p" > ,< / span >
< span class = "p" > }< / span >
< / code > < / pre > < / div >
< p > < code > D< / code > selects the attached data payload:< / p >
< table >
< thead >
< tr >
< th > < code > D< / code > < / th >
< th > Data directory< / th >
< th > < code > Item< / code > returned by < code > query< / code > < / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > < code > ()< / code > < / td >
< td > —< / td >
< td > < code > ()< / code > (set membership only)< / td >
< / tr >
< tr >
< td > < code > PersistentCompactIntMatrix< / code > < / td >
< td > < code > counts/< / code > < / td >
< td > < code > Box< [u32]> < / code > (counts per genome)< / td >
< / tr >
< tr >
< td > < code > PersistentBitMatrix< / code > < / td >
< td > < code > presence/< / code > < / td >
< td > < code > Box< [bool]> < / code > (presence per genome)< / td >
< / tr >
< / tbody >
< / table >
< p > < code > Layer::query(kmer)< / code > delegates to < code > MphfLayer::find< / code > , then calls < code > data.read(slot)< / code > if a slot is returned. Both exact and approximate evidence are handled transparently; the caller sees only < code > Option< Hit< D::Item> > < / code > .< / p >
< p > Build-time entry points:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "n" > Layer< / span > < span class = "o" > < < / span > < span class = "p" > ()< / span > < span class = "o" > > < / span > < span class = "p" > ::< / span > < span class = "n" > build< / span > < span class = "p" > (< / span > < span class = "n" > out_dir< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > block_bits< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "c1" > // set membership< / span >
< span class = "n" > Layer< / span > < span class = "o" > < < / span > < span class = "n" > PersistentCompactIntMatrix< / span > < span class = "o" > > < / span > < span class = "p" > ::< / span > < span class = "n" > build< / span > < span class = "p" > (< / span > < span class = "n" > out_dir< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > block_bits< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > count_of< / span > < span class = "p" > )< / span >
< span class = "n" > Layer< / span > < span class = "o" > < < / span > < span class = "n" > PersistentBitMatrix< / span > < span class = "o" > > < / span > < span class = "p" > ::< / span > < span class = "n" > build_presence< / span > < span class = "p" > (< / span > < span class = "n" > out_dir< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > block_bits< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > n_genomes< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > present_in< / span > < span class = "p" > )< / span >
< span class = "n" > Layer< / span > < span class = "p" > ::< / span > < span class = "o" > < < / span > < span class = "p" > ()< / span > < span class = "o" > > < / span > < span class = "p" > ::< / span > < span class = "n" > build_evidence< / span > < span class = "p" > (< / span > < span class = "n" > layer_dir< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > kind< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > block_bits< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "c1" > // evidence only (reindex path)< / span >
< / code > < / pre > < / div >
< hr / >
< h2 id = "datastore-slot-indexed-data" > DataStore — slot-indexed data< / h2 >
< p > < code > PersistentCompactIntMatrix< / code > and < code > PersistentBitMatrix< / code > are slot-indexed stores. They know nothing about kmers or MPHFs.< / p >
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< table >
< thead >
< tr >
< th > Type< / th >
< th > < code > Item< / code > < / th >
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< th > Aggregation method< / th >
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< th > Use< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > < code > PersistentCompactIntMatrix< / code > < / td >
< td > < code > Box< [u32]> < / code > < / td >
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< td > < code > sum() → Array1< u64> < / code > < / td >
< td > counts per genome per slot< / td >
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< / tr >
< tr >
< td > < code > PersistentBitMatrix< / code > < / td >
< td > < code > Box< [bool]> < / code > < / td >
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< td > < code > count_ones() → Array1< u64> < / code > < / td >
< td > presence per genome per slot< / td >
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< / tr >
< / tbody >
< / table >
< hr / >
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< h2 id = "aggregation-traits-obicompactvectraits" > Aggregation traits — < code > obicompactvec::traits< / code > < / h2 >
< p > Three traits unify the aggregation API across all hierarchy levels.< / p >
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< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > trait< / span > < span class = "w" > < / span > < span class = "n" > ColumnWeights< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nb" > Send< / span > < span class = "w" > < / span > < span class = "o" > +< / span > < span class = "w" > < / span > < span class = "nb" > Sync< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > col_weights< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array1< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > ;< / span >
< span class = "p" > }< / span >
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< span class = "k" > trait< / span > < span class = "w" > < / span > < span class = "n" > CountPartials< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > ColumnWeights< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
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< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_bray< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > ;< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_euclidean< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "p" > ;< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_threshold_jaccard< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > threshold< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kt" > u32< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "p" > (< / span > < span class = "n" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > );< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_relfreq_bray< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > global< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kp" > & < / span > < span class = "nc" > Array1< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "p" > ;< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_relfreq_euclidean< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > global< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kp" > & < / span > < span class = "nc" > Array1< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "p" > ;< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_hellinger< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > global< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kp" > & < / span > < span class = "nc" > Array1< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "p" > ;< / span >
< span class = "w" > < / span > < span class = "c1" > // provided finalisation methods with default impls< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > bray_dist_matrix< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "err" > …< / span > < span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > relfreq_bray_dist_matrix< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "err" > …< / span > < span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "w" > < / span > < span class = "c1" > // …< / span >
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< span class = "p" > }< / span >
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< span class = "k" > trait< / span > < span class = "w" > < / span > < span class = "n" > BitPartials< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > ColumnWeights< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
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< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_jaccard< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "p" > (< / span > < span class = "n" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "n" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > );< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > partial_hamming< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "p" > ;< / span >
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< span class = "w" > < / span > < span class = "c1" > // provided< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > jaccard_dist_matrix< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "err" > …< / span > < span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "w" > < / span > < span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > hamming_dist_matrix< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > u64< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "err" > …< / span > < span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "p" > }< / span >
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< / code > < / pre > < / div >
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< p > Leaf implementors:< / p >
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< table >
< thead >
< tr >
< th > Type< / th >
< th > Traits< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > < code > PersistentCompactIntMatrix< / code > < / td >
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< td > < code > ColumnWeights< / code > , < code > CountPartials< / code > < / td >
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< / tr >
< tr >
< td > < code > PersistentBitMatrix< / code > < / td >
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< td > < code > ColumnWeights< / code > , < code > BitPartials< / code > < / td >
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< / tr >
< / tbody >
< / table >
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< hr / >
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< h2 id = "layeredstores-recursive-aggregation-wrapper" > LayeredStore\< S> — recursive aggregation wrapper< / h2 >
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< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > pub< / span > < span class = "w" > < / span > < span class = "k" > struct< / span > < span class = "w" > < / span > < span class = "nc" > LayeredStore< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "o" > > < / span > < span class = "p" > (< / span > < span class = "nb" > Vec< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "o" > > < / span > < span class = "p" > );< / span >
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< / code > < / pre > < / div >
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< p > Three blanket impls propagate all traits up the hierarchy:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > impl< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > ColumnWeights< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "n" > ColumnWeights< / span > < span class = "w" > < / span > < span class = "k" > for< / span > < span class = "w" > < / span > < span class = "n" > LayeredStore< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "err" > …< / span > < span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "k" > impl< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > CountPartials< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "n" > CountPartials< / span > < span class = "w" > < / span > < span class = "k" > for< / span > < span class = "w" > < / span > < span class = "n" > LayeredStore< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "err" > …< / span > < span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "k" > impl< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "nc" > BitPartials< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "n" > BitPartials< / span > < span class = "w" > < / span > < span class = "k" > for< / span > < span class = "w" > < / span > < span class = "n" > LayeredStore< / span > < span class = "o" > < < / span > < span class = "n" > S< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span > < span class = "w" > < / span > < span class = "err" > …< / span > < span class = "w" > < / span > < span class = "p" > }< / span >
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< / code > < / pre > < / div >
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< p > This makes < code > LayeredStore< LayeredStore< PersistentCompactIntMatrix> > < / code > automatically implement < code > CountPartials< / code > — no separate < code > PartitionedStore< / code > type is needed:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > PersistentCompactIntMatrix leaf (one layer)
LayeredStore< PersistentCompactIntMatrix> one partition (layers are disjoint)
LayeredStore< LayeredStore< …> > whole index (partitions are independent)
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< / code > < / pre > < / div >
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< p > Normalised metrics require global column sums — computed in a two-pass cascade:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "c1" > // on LayeredStore< LayeredStore< PersistentCompactIntMatrix> > < / span >
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< span class = "k" > fn< / span > < span class = "w" > < / span > < span class = "nf" > relfreq_bray_dist_matrix< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "bp" > self< / span > < span class = "p" > )< / span > < span class = "w" > < / span > < span class = "p" > -> < / span > < span class = "w" > < / span > < span class = "nc" > Array2< / span > < span class = "o" > < < / span > < span class = "kt" > f64< / span > < span class = "o" > > < / span > < span class = "w" > < / span > < span class = "p" > {< / span >
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< span class = "w" > < / span > < span class = "kd" > let< / span > < span class = "w" > < / span > < span class = "n" > global< / span > < span class = "w" > < / span > < span class = "o" > =< / span > < span class = "w" > < / span > < span class = "bp" > self< / span > < span class = "p" > .< / span > < span class = "n" > col_weights< / span > < span class = "p" > ();< / span > < span class = "w" > < / span > < span class = "c1" > // pass 1 — sums up hierarchy< / span >
< span class = "w" > < / span > < span class = "kd" > let< / span > < span class = "w" > < / span > < span class = "n" > p< / span > < span class = "w" > < / span > < span class = "o" > =< / span > < span class = "w" > < / span > < span class = "bp" > self< / span > < span class = "p" > .< / span > < span class = "n" > partial_relfreq_bray< / span > < span class = "p" > (< / span > < span class = "o" > & < / span > < span class = "n" > global< / span > < span class = "p" > );< / span > < span class = "w" > < / span > < span class = "c1" > // pass 2 — global broadcast read-only< / span >
< span class = "w" > < / span > < span class = "n" > p< / span > < span class = "p" > .< / span > < span class = "n" > mapv< / span > < span class = "p" > (< / span > < span class = "o" > |< / span > < span class = "n" > v< / span > < span class = "o" > |< / span > < span class = "w" > < / span > < span class = "mf" > 1.0< / span > < span class = "w" > < / span > < span class = "o" > -< / span > < span class = "w" > < / span > < span class = "n" > v< / span > < span class = "p" > )< / span >
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< span class = "p" > }< / span >
< / code > < / pre > < / div >
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< p > Because each kmer belongs to exactly one < code > (partition, layer)< / code > pair, < code > col_weights()< / code > has no double-counting across the hierarchy.< / p >
< hr / >
< h2 id = "progressive-aggregation-principle" > Progressive aggregation principle< / h2 >
< p > No level reaches two levels down. Each level sums contributions from the level immediately below:< / p >
< div class = "highlight" > < pre > < span > < / span > < code > PersistentCompactIntMatrix::col_weights() — one (partition, layer)
↓ Σ across layers
LayeredStore< PersistentCompactIntMatrix> ::col_weights() — one partition
↓ Σ across partitions
LayeredStore< LayeredStore< …> > ::col_weights() — global
< / code > < / pre > < / div >
< p > The same cascade applies to every partial method.< / p >
< hr / >
< h2 id = "multi-genome-column-invariant" > Multi-genome column invariant< / h2 >
< p > After any merge, every layer in every partition has exactly < code > n_genomes< / code > columns, where < code > n_genomes< / code > is the current total in < code > index.meta< / code > . This holds for both < code > PersistentCompactIntMatrix< / code > and < code > PersistentBitMatrix< / code > .< / p >
< p > Maintained by three coordinated operations:< / p >
< p > < strong > Existing layers — column append.< / strong > < code > Layer::append_genome_column< / code > appends one column to each existing layer. Slots matching the incoming genome receive its count or < code > true< / code > ; all other slots receive 0 or < code > false< / code > .< / p >
< p > < strong > New layers — absent columns prepended.< / strong > When a new layer is created for kmers unique to the incoming genome, < code > n_existing_genomes< / code > absent columns are prepended before the incoming genome's column, so the new layer immediately has the same column count as all other layers.< / p >
< p > < strong > First merge, Presence mode — < code > init_presence_matrix< / code > .< / strong > The initial single-genome index has no < code > presence/< / code > directory (presence is implicit). On the first merge, < code > Layer< ()> ::init_presence_matrix< / code > materialises genome 0's presence column (all < code > true< / code > ) retroactively, raising the column count from 0 to 1 before appending column 1.< / p >
< p > This invariant is the precondition for correct progressive aggregation: every level can blindly sum matrices from below because all matrices have the same shape.< / p >
< hr / >
< h2 id = "query-model" > Query model< / h2 >
< h3 id = "point-query" > Point query< / h3 >
< div class = "highlight" > < pre > < span > < / span > < code > minimiser(kmer) → partition p
for each layer l in p:
if let Some(slot) = MphfLayer_l.find(kmer):
return data_l.read(slot)
return None
< / code > < / pre > < / div >
< p > O(n_layers) MPHF probes worst case; O(1) expected. The result comes from exactly one < code > (partition, layer)< / code > .< / p >
< h3 id = "aggregation" > Aggregation< / h3 >
< div class = "highlight" > < pre > < span > < / span > < code > result = reduce(
for p in partitions: // parallel
for l in layers(p): // parallel
partial(data_p_l)
)
< / code > < / pre > < / div >
< p > For normalised metrics, replace with the two-pass cascade.< / p >
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< hr / >
< h2 id = "parallelism-model" > Parallelism model< / h2 >
< table >
< thead >
< tr >
< th > Level< / th >
< th > Unit< / th >
< th > Coordination< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > Across partitions< / td >
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< td > inner stores of < code > LayeredStore< LayeredStore< S> > < / code > < / td >
< td > none< / td >
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< / tr >
< tr >
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< td > Across layers within a partition< / td >
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< td > inner stores of < code > LayeredStore< S> < / code > < / td >
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< td > none — disjoint kmer sets< / td >
< / tr >
< tr >
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< td > Normalised pass 1 (< code > col_weights< / code > )< / td >
< td > per inner store< / td >
< td > none — additive< / td >
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< / tr >
< tr >
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< td > Normalised pass 2 (partial)< / td >
< td > per inner store< / td >
< td > < code > global< / code > broadcast read-only< / td >
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< / tr >
< tr >
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< td > Within a matrix (distance)< / td >
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< td > upper-triangle pair < code > (i,j)< / code > < / td >
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< td > none — rayon < code > par_iter< / code > < / td >
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< / tr >
< / tbody >
< / table >
< hr / >
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< h2 id = "reindex-evidence-conversion-in-place" > reindex — evidence conversion in place< / h2 >
< p > < code > KmerIndex::reindex(target, block_bits)< / code > converts every layer's evidence bundle to < code > target< / code > without touching the MPHF or < code > unitigs.bin< / code > :< / p >
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< ul >
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< li > < code > → Exact< / code > : builds < code > evidence.bin< / code > + < code > unitigs.bin.idx< / code > ; removes < code > fingerprint.bin< / code > < / li >
< li > < code > → Approx { b, z }< / code > : builds < code > fingerprint.bin< / code > ; removes < code > evidence.bin< / code > + < code > unitigs.bin.idx< / code > < / li >
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< / ul >
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< p > On success, < code > IndexConfig::evidence< / code > and < code > IndexConfig::block_bits< / code > are updated in < code > index.meta< / code > . Each layer's < code > layer_meta.json< / code > is also rewritten with the new < code > EvidenceKind< / code > .< / p >
< hr / >
< h2 id = "estimate-parameter-dry-run" > estimate — parameter dry-run< / h2 >
< p > < code > estimate< / code > resolves approximate-evidence parameters (< code > z< / code > , < code > b< / code > , target FP rate) and prints the resulting effective kmer size and per-kmer / per-z-window false-positive rates without touching any index. Used to calibrate < code > Approx { b, z }< / code > before building or reindexing.< / p >
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