[−][src]Function appr_dbscan::do_appr_dbscan_points

pub fn do_appr_dbscan_points<const D: usize>(
    points: Vec<Point<D>>, 
    epsilon: f64, 
    rho: f64, 
    min_pts: usize
) -> DBSCANResult<D>

Function that returns the result of the approximate DBSCAN algorithm executed on the set of points contained in points with the given values of epsilon and rho.

Arguments

  • points: the vector of points to execute the algorithm on. All points must be arrays of lenght D
  • epsilon: the radius for the DBSCAN algorithm.
  • rho: the approximation factor. The smaller it is the more precise the result. Usual values are 0.1 and 0.01.
  • min_pts: the minimum number of nearby points required by the DBSCAN algorithm to declare an area as 'dense'.

Constant argument

  • D: The dimensionality of each point in the data.

Return value

This function returns a vector of clusters, where each cluster is a vector of the points contained in it. Each point is stored as an array of f64 ([f64;D]). The element at index 0 is the collection of all noise points, while all the other elements are the actual clusters.

Example

extern crate appr_dbscan;
use appr_dbscan::do_appr_dbscan_points;
use appr_dbscan::utils::DBSCANResult;
 
let points = vec![[0.0,0.0],[1.0,1.0],[0.0,1.0],[1.0,0.0],[2.0,1.0],[0.0,2.0],[2.0,1.0],[1.0,1.0]];
let res : DBSCANResult<2> = do_appr_dbscan_points(points, 0.3, 0.1, 10);
let clusters_count = res.len() - 1;
let noise_points_count = res[0].len();