UniquePoints: Unique Points

In DatabionicSwarm: Swarm Intelligence for Self-Organized Clustering

Unique Points

Description

return only the unique points in Datapoints

Usage

UniquePoints(Datapoints, Eps=1e-10)

Arguments

Datapoints	[1:n,1:d] matrix of Datapoints points of dimension d, the points are in the rows
Eps	Optional,scalar above zero that defines minimum non-identical euclidean distance between two points

Details

Euclidean distance is computed and used within. Setting Eps to a very small number results in the identification of unique data points. Setting epsilon to a higher number results in the definition of mesh points within an d-dimensional R-ball graph.

Value

List with

Unique	[1:k,1:d] Datapoints points without duplicate points
IsDuplicate	[1:n,1:n] matrix,for i!=j IsDuplicate[i,j]== 1 if Datapoints[i,] == Datapoints[j,] IsDuplicate[i,i]==0
UniqueInd	[1:k] index vector such that Unique == Datapoints[UniqueInd,], it has k non-consecutive numbers or labels, each label defines a row number within Datapoints[1:n,1:d] of a unique data point
Uniq2DatapointsInd	[1:n] index vector. It has k unique index numbers representing the arbitrary labels. Each labels is mapped uniquely to a point in Unique. Logically in a way such that Datapoints == Unique[Uniq2DatapointsInd,] (will not work directly in R this way)

Author(s)

Michael Thrun

Examples

Datapoints2D=rbind(c(1,2),c(1,2),c(1,3),c(3,1))
V=UniquePoints(Datapoints2D)

DatabionicSwarm documentation built on June 22, 2024, 9:41 a.m.