necom Documentation

Calculate pairwise similarity/distance between vectors in input file(s).

Behavior:

• --mode euclid: Euclidean distance.
• --mode euclid --sim: Euclidean distance converted to similarity.
• --mode euclid --binary: binary Euclidean distance (values treated as 0/1).
• --mode euclid --binary --sim --dis: binary Euclidean distance to dissimilarity.
• --mode cosine: cosine similarity (-1 to 1).
• --mode cosine --dis: cosine distance (0 to 2).
• --mode cosine --binary: binary cosine similarity.
• --mode cosine --binary --dis: binary cosine distance.
• --mode jaccard --binary: Jaccard index.
• --mode jaccard: weighted Jaccard similarity.

Input:

• One or two vector files in name<tab>v1<tab>v2<tab>... format (pure TSV).
• One file: self-comparison (all pairs including diagonal).
• Two files: cross-comparison between the two sets.

Output:

• Three-column TSV: name1<tab>name2<tab>score (6 decimal places), one row per pair.

Notes:

• --binary treats positive values as 1, all others as 0, before computing the score.
• --sim converts a distance to a similarity; --dis converts a similarity to a dissimilarity.
• When both --sim and --dis are given, the conversion is applied in the order distance -> similarity -> dissimilarity.
• --parallel <N> sets the number of worker threads (default 1).
• With --parallel > 1, rows may be emitted in non-deterministic order; each row still pairs the first-file entry with all second-file entries in file order.

Examples:

1. Self-compare vectors with binary Jaccard necom mat from-vector vectors.tsv --mode jaccard --binary

2. Cross-compare two vector sets with cosine distance necom mat from-vector set1.tsv set2.tsv --mode cosine --dis -o out.tsv