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Eric Coissac 8c7017a99d ⬆️ version bump to v4.5

- Update obioptions.Version from "Release 4.4.29" to "/v/ Release v5"
- Update version.txt from 4.29 → .30
(automated by Makefile)

2026-04-13 13:34:53 +02:00

`obidist` Package: Efficient Symmetric Distance/Similarity Matrix Management

The *DistMatrix type provides a memory-efficient, symmetric matrix implementation for distance or similarity data.

Storage Strategy: Only the upper triangle (i < j) is stored, reducing memory usage from O(n²) to n(n−1)/2.
Diagonal Handling: Diagonal entries are fixed (0.0 for distances, 1.0 for similarities); assignments to diagonal indices are silently ignored.
Symmetry Guarantee: Get(i, j) and Set(i, j, v) automatically handle both (i,j) and (j,i), ensuring consistency.

Constructors

Function	Description
`NewDistMatrix(n)` / `WithLabels(labels)`	Creates n×n distance matrix (diag = 0).
`NewSimilarityMatrix(n)` / `WithLabels(labels)`	Creates n×n similarity matrix (diag = 1).

Get(i, j) / Set(i, j, v): Access/update symmetric entries.
Size() int, GetLabel(i) / SetLabel(i, label): Query/mutate element labels.
Labels() []string, GetRow(i) / GetColumn(j): Retrieve full rows/columns (as copies).

MinDistance(), MaxDistance() → (value, i, j) of the extremal off-diagonal entry.
Copy() *DistMatrix: Deep copy for immutability-safe operations.
ToFullMatrix() → [][]float64: Converts to dense representation (use sparingly).

Designed for clustering, phylogenetics, or any domain requiring fast symmetric matrix access with minimal footprint.