msa: Identify Clusters in a Marked Point Pattern Using MSA

In aproudian2/rapt: Atom Probe Tomography Analysis

Identify Clusters in a Marked Point Pattern Using MSA

Description

msa segments a marked pp3 into clusters and background matrix using the maximum separation algorithm (MSA). The marks can have more than two types, but MSA requires that each type is categorized as either a cluster or non-cluster species.

Usage

msa(X, dmax, Nmin, denv, der, clust.mark = c("A"))

Arguments

X	A marked pp3 object on which MSA will be performed.
dmax	The maximum distance two points can be separated by and still be considered part of the same cluster.
Nmin	The minimum number of points needed to classify a grouping of points as a cluster.
denv	Any points within this distance of a point residing in a cluster will be included in the cluster (this controls the addition of background points to a cluster).
der	Any points within this distance of a background matrix point (after enveloping) will be removed from the cluster.
clust.mark	Vector containing the names of the marks in X that should be considered as cluster type points. All points with marks not included in this vector will be considered background points.

Value

A list of:

• radius - A vector containing estimated radius of each cluster found

• den - A vector containing estimated intra-cluster concentration of cluster type points in each cluster found

• bgnd.den - The estimated background concentration of cluster type points within the background (i.e. the entire domain minus the clusters)

• cluster - A list of indices from the original pattern of cluster type points that reside in clusters

• bgnd - A list of indices from the original pattern of background type points that reside in clusters.

References

Marquis, E.A. & Hyde, J.M., "Applications of atom-probe tomography to the characterisation of solute behaviours," Materials Science and Engineering: R: Reports, 69 (4-5), 37-62 (2010): https://doi.org/10.1016/j.mser.2010.05.001

See Also

Other cluster identification functions: gema.gema(), gema.pp3(), gema()

aproudian2/rapt documentation built on Dec. 15, 2022, 4:24 a.m.