Distance Calculator

This module allow you to process the db-scan algorithm with n-dimensional data. Optional methods for distance-calculation are Manhattan, Minkowski and Euclidean.

Usage via Commandline

deno run --allow-net https://deno.land/x/db_scan/test.ts

Usage Example

import {DBScan} from "https://deno.land/x/db_scan/mod.ts"

var dataset:Array<number[]>=[[1,1,1],[1,1,2],[1,2,3],[2,4,3],[2,2,2],[3,2,1],[4,3,2],[2,3,3],[3,3,3],[5,5,5],[5,6,5]]
const dbscan=new DBScan()
console.log(dbscan.getclassifiedPointListEuclidean(dataset,2.1,4))      //data, threshold, k-neighbours
console.log(dbscan.getclassifiedPointListManhattan(dataset,2.1,4))      //data, threshold, k-neighbours
console.log(dbscan.getclassifiedPointListMinkowski(dataset,2.1,4,3))    //data, threshold, k-neighbours, p from Minkowski-formula

Output

[
  [ [ 1, 1, 2 ], [ 1, 2, 3 ], [ 2, 2, 2 ], [ 2, 3, 3 ], [ 3, 3, 3 ] ],
  [ [ 1, 1, 1 ], [ 2, 4, 3 ], [ 3, 2, 1 ], [ 4, 3, 2 ] ],
  [ [ 5, 5, 5 ], [ 5, 6, 5 ] ]
]