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JavaScript vec.euclideanDistance

MarkLogic 12 EA 1 Product Documentation
vec:euclidean-distance

vec:euclidean-distance(
   $vector1 as vec:vector,
   $vector2 as vec:vector
) as xs:double

Summary

Returns the Euclidean distance between two vectors. The vectors must be of the same dimension.

Parameters
vector1 The vector from which to calculate the Euclidean distance to vector2.
vector2 The vector from which to calculate the Euclidean distance to vector1.

Example

  xquery version "1.0-ml";
  let $vec1 := vec:vector((3.14,1.59,2.65))
  let $vec2 := vec:vector((3.58,9.79,3.23))

  return vec:euclidean-distance($vec1,$vec2);

  => 8.23225402832031

Example

  xquery version "1.0-ml";

  let $vec1 := vec:vector(fn:head(fn:doc('pronethalol.json'))/data/array-node{embedding})
  let $vec2 := vec:vector(fn:head(fn:doc('cell_renewal.json'))/data/array-node{embedding})

  return vec:euclidean-distance($vec1,$vec2)

  => The Euclidean distance between vectors in JSON arrays named 'embedding'
      in documents 'pronethalol.json' and 'cell_renewal.json'

Example

xquery version "1.0-ml";
import module namespace op = 'http://marklogic.com/optic'
           at 'MarkLogic/optic.xqy';
import module namespace ovec = 'http://marklogic.com/optic/expression/vec'
           at 'MarkLogic/optic/optic-vec.xqy';

(: construct a query vector from the JSON array node 'emb' in document 'embedding104576.json' :)
let $qv := vec:vector(fn:head(fn:doc('embedding104576.json'))/array-node('emb'))

let $view := op:from-view('vecs','wiki_vectors')
           =>op:bind(op:as('euclDistance',ovec:euclidean-distance(op:col('embedding'),$qv)))
           =>op:select((op:col('title'),op:col('text'),op:col('euclDistance')))
           =>op:order-by(op:asc(op:col('euclDistance')))
           =>op:limit(30)
           =>op:result()
return $view;

(: Performs a linear scan of vectors in the 'embedding' column in the 'wiki_vectors' view to find the top
   30 matches to the query vector $qv
:)

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